Cognixia Podcast: Recent Episodes
Cognixia
The Cognixia podcast is brought to you by Cognixia. We aim to enlighten people with the digital transformations occurring around the globe by sharing our experiences and tales of learning adventures. This podcast is your one stop for everything Tech and Digital. We believe in shaping the world by giving people a memorable learning experience thus enabling digital ready minds.
Welcome to the Cognixia Podcast, where we bring you expertperspectives on digital transformation, reskilling, upskilling, and emerging technologies.
In this episode, we explore one of the most important shiftsshaping the future of Global Capability Centers (GCCs): the move toward a cloud-native future.
Cloud computing has already transformed the way businessesoperate. But cloud-native goes a step further. It’s about designing applications for scalability, agility, and resilience, enabling organizations to innovate faster than ever before. For GCCs, cloud-native adoption is not just an opportunity — it’s a necessity.
In this episode, you will learn:
- Why GCCs must transition from traditional cloud adoption to cloud-native architectures.
- The essential skills for cloud-native success - from containerization and Kubernetes to infrastructure as code and DevOps.
- How a DevOps and agile mindset is just as important as mastering tools.
- The role of leadership in driving cloud-native transformation through continuous upskilling.
- How Cognixia helps GCCs with customized cloud-native training programs.
Cloud-native adoption is about more than technology. It’sabout people. Teams need the right skills and culture to succeed in this new environment. Without upskilling, GCCs risk falling behind in delivering innovation and value.
At Cognixia, we specialize in helping GCCs and enterprisesprepare for tomorrow’s infrastructure. Our training programs cover Kubernetes, DevOps, cloud security, automation, and more, ensuring that employees gain hands-on, job-ready skills.
By listening to this episode, you’ll gain a deeper understanding of why cloud-native matters, how GCCs can get it right, and what it takes to build a future-ready workforce.
Stay tuned until the end as we share how Cognixia partnerswith organizations worldwide to drive cloud-native talent transformation.
The Cognixia Podcast is your trusted resource for insightson GCCs, digital transformation, and the skills that power the future of work. Subscribe today to stay ahead of the curve.
Learn more at www.cognixia.com. Stay curious. Stay skilled. Keep transforming the future - with Cognixia.
In this episode of the Cognixia Podcast, we dive intoa topic that doesn’t always get the spotlight it deserves - leadership in Global Capability Centers (GCCs).
While conversations around GCCs often focus on technology -artificial intelligence, automation, cloud, and cybersecurity - the truth is, none of these innovations can succeed without the right leaders guiding the way. That’s why upskilling leaders has become mission-critical for every GCC that wants to thrive in today’s digital-first world.
What you’ll learn in this episode:
- How the role of GCC leaders has evolved from managing cost and delivery to driving global innovation.
- Why digital fluency is essential for leaders, even if they aren’t coders or technical experts.
- The importance of mastering hybrid leadership skills to inspire and engage globally distributed teams.
- How leaders can develop strategic vision to align GCC operations with enterprise-wide transformation goals.
- Real-world insights into how GCCs can transform from delivery hubs into innovation engines through leadership development.
Why Leadership Matters in GCC Transformation
A decade ago, a GCC leader’s success was measured by costsavings and efficiency. Today, the metrics have changed. Leaders are now expected to deliver enterprise-wide impact by harnessing digital technologies, driving innovation, and enabling agility.
Without strong, future-ready leaders, GCCs risk stayingstuck in legacy models. With the right leadership skills, however, they can become strategic hubs of innovation, growth, and transformation.
Cognixia’s Approach to Leadership Upskilling
At Cognixia, we understand that leadership is aboutmuch more than technical know-how. That’s why we partner with GCCs to design custom leadership development programs that focus on:
- Building digital awareness – helping leaders understand how AI, cloud, and automation reshape business.
- Cultivating agile leadership – enabling managers to lead with adaptability, design thinking, and innovation.
- Strengthening cross-cultural and global collaboration – critical for managing distributed and hybrid teams.
Our goal is to help GCCs develop leaders who can inspireteams, execute strategies, and shape the digital-first enterprise of the future.
Why You Should Listen
If you’re a GCC professional, enterprise leader, or someonepassionate about digital transformation, this episode offers valuable insights into the skills leaders need to succeed in today’s rapidly evolving business environment.
By the end of this conversation, you’ll understand why upskilling leaders isn’t optional - it’s essential. And you’ll see how investing in leadership can unlock innovation, resilience, and sustainable growth for your GCC.
Stay Connected with Cognixia
The Cognixia Podcast brings you expert insights intoreskilling, upskilling, digital transformation, and the future of work. Each episode explores the trends and technologies shaping tomorrow’s enterprises, with a special focus on the role of Global Capability Centers.
Subscribe now to never miss an episode, and join us inshaping the future of work. Learn more at www.cognixia.com. Stay curious. Stay skilled. Keep transforming the future - with Cognixia.
In this episode of the Cognixia Podcast, we tackle one of the most urgent challenges facing Global Capability Centers (GCCs): reskilling for the AI era.
Artificial Intelligence is no longer just a buzzword - it’s transforming industries at scale. From automating back-office processes to delivering real-time insights and enabling new business models, AI is at the core of digital transformation. For GCCs, this shift creates an urgent need to reskill their workforce and prepare employees for new, AI-driven roles.
What you’ll learn in this episode:
- Why AI is disrupting every industry and what that means for GCCs.
- How reskilling helps employees transition from routine tasks to high-value digital roles.
- The core AI-related skills GCCs must prioritize - from machine learning to data science to prompt engineering.
- The three pillars of successful reskilling programs: skill mapping, structured pathways, and continuous learning.
- How Cognixia helps GCCs build AI-ready talent pipelines through enterprise-scale programs.
Reskilling: The Urgency for GCCs
Industry studies suggest that more than 60% of jobs will be impacted by AI. That doesn’t mean jobs will disappear - it means jobs will evolve. For GCCs, this means reskilling is no longer optional. The ability to rapidly build AI-first skills will determine whether a GCC can remain relevant and competitive in the global landscape.
Reskilling isn’t about teaching theory. It’s about preparing employees for real-world AI applications. It’s about helping developers evolve into AI solution builders, analysts into insight generators, and leaders into AI strategists.
Cognixia’s Approach to AI Reskilling
At Cognixia, we help GCCs and enterprises build future-ready talent through:
- AI, ML, and Data Science training tailored for real-world challenges.
- Cloud and cybersecurity programs that support end-to-end digital transformation.
- Leadership workshops that prepare managers to integrate AI into strategy and decision-making.
Our focus is on hands-on, immersive learning that equips employees with practical, job-ready skills.
Why You Should Listen
If you work in a GCC, lead enterprise transformation, or want to understand how AI is reshaping the workforce, this episode is for you. You’ll discover why reskilling is urgent, how GCCs can get it right, and how the right programs can transform disruption into opportunity.
This conversation will give you a clear picture of what it takes for GCCs to not only keep up with AI but to lead the AI revolution.
Stay Connected with Cognixia
The Cognixia Podcast is your gateway to expert insights on digital transformation, reskilling, upskilling, GCCs, and emerging technologies. Subscribe today to stay ahead ofthe curve.
Learn more at www.cognixia.com. Stay curious. Stayskilled. Keep transforming the future - with Cognixia.
Welcome to the Cognixia Podcast, your destination for insights on digital transformation, emerging technologies, and the future of work. In this episode, we explore the rise of GlobalCapability Centers (GCCs) and their growing role as the innovation engines of global enterprises.
When GCCs first began in the 1990s, their primary focus was cost savings. By centralizing operations and improving efficiency, enterprises gained financial and operational advantages.But today, GCCs are no longer just cost centers - they have transformed into strategic hubs driving global business transformation.
What you’ll discover in this episode:
- The evolution of GCCs from back-office functions to strategic innovation hubs.
- Why India has become the global hub for GCCs, with a thriving ecosystem and a projected workforce of 4.5 million by 2030.
- Key drivers behind GCC growth, including AI,automation, cloud, and cybersecurity.
- The major challenges GCCs face — from talentshortages to leadership gaps to cultural transformation.
- Why upskilling and reskilling are non-negotiable for building future-ready GCCs.
GCCs as Innovation Engines
GCCs are no longer just about support and delivery. They are now creating digital solutions that transform customer experiences, power predictive insights, and accelerateenterprise innovation. More than half of Fortune 500 companies already have a GCC in India, highlighting the strategic value of this model.
But the journey is not without challenges. The demand for AI, data science, and cloud expertise is exploding, creating intense competition for talent. At the same time, GCC leaders musttransition from operational managers to strategic visionaries who can balance global strategies with local execution.
Cognixia’s Role in Talent Transformation
At Cognixia, we believe that the success of GCCs depends on people - not just technology. That’s why we partner with enterprises and GCCs to design custom learning journeysthat:
- Bridge digital skill gaps.
- Deliver hire-train-deploy programs to onboard job-ready talent.
- Focus on AI, cloud, cybersecurity, and leadership development.
By empowering workforces, we help GCCs evolve into innovation powerhouses that drive global growth.
Why You Should Listen
If you’re a GCC leader, digital transformation professional, or just curious about the future of work, this episode is packed with insights. You’ll learn why GCCs are critical to enterprise success and how upskilling, reskilling, and leadershipdevelopment are reshaping the landscape.
This episode will inspire you to think about GCCs not as cost centers, but as innovation engines that will define the future of global business.
Stay Connected with Cognixia
The Cognixia Podcast brings you expert perspectives on digital transformation, GCCs, reskilling, upskilling, and the future of work. Subscribe today and join the conversation shaping tomorrow’s enterprises. Learn more at www.cognixia.com
Stay curious. Stay skilled. Keep transforming the future - with Cognixia.
Welcome back to the Cognixia Podcast! This week, we explore one of the most exciting intersections in technology today - artificial intelligence in Microsoft Power BI. Power BI has already become a cornerstone of business intelligence, empowering over 5 million users worldwide to visualize data and make smarter decisions. But with AI integration, it’s entering an entirely new era - one where data analysis becomes faster, smarter, and more intuitive than ever before.
Traditional Power BI workflows have long relied on time-intensive manual processes - preparing datasets, writing DAX formulas, and maintaining complex models. While powerful, these approaches often create bottlenecks and limit how quickly organizations can act on insights. Enter AI-powered enhancements that are reshaping every stage of the BI lifecycle.
In this episode, we break down how AI is:
- Democratizing analytics through natural language queries - ask Power BI a plain-English question like “Show me quarterly sales trends by product category” and get instant, accurate visualizations.
- Accelerating insights with the Key Influencers visual, which automatically identifies the factors driving critical business outcomes.
- Optimizing data modeling by suggesting schemas, detecting anomalies, and predicting refresh failures before they happen.
- Enhancing predictive power via seamless integration with Azure Machine Learning, enabling real-time forecasting, anomaly detection, and embedded ML models in reports.
We also explore the emerging role of Model Context Protocol (MCP) servers in Power BI environments. Imagine an AI assistant that fully understands your organization’s data models, business rules, and reporting needs. With MCP servers, AI could generate complex DAX calculations, recommend optimizations, and maintain consistency across teams - fundamentally transforming development workflows.
The evolution doesn’t stop at automation. AI is pushing Power BI toward conversational analytics, where users interact with data through natural dialogues. No coding, no formulas - just intuitive, business-friendly conversations that lead directly to actionable insights.
And it goes deeper: AI can proactively surface trends, correlations, and anomalies you didn’t even think to ask about. It can turn raw insights into executive-ready narratives with automated storytelling features, bridging the gap between technical detail and business strategy.
Of course, adopting AI in Power BI isn’t just about technology. Organizations must address data quality, governance, security, and change management to fully realize its potential. Hybrid approaches - where AI automation complements human expertise - will remain critical to success.
Looking ahead, the future promises even more: autonomous data prep, multimodal analytics that integrate text, images, and audio, and real-time AI-driven decision-making. In this vision, Power BI becomes more than a reporting tool - it evolves into a proactive, predictive, and conversational intelligence platform.
Tune in as we unpack how AI is revolutionizing business intelligence, what it means for organizations worldwide, and how you can prepare to harness this transformation.
Because in the new world of BI, those who adapt first won’t just keep up - they’ll lead.
In this game-changing episode of the Cognixia Podcast, we unpack one of the most misunderstood concepts in today’s tech-driven business world - the difference between “Doing AI” and “Using AI.” It’s a distinction that’s shaping boardroom debates, technology budgets, and competitive landscapes across every industry. Get it wrong, and you risk pouring millions into projects that drain resources without delivering results. Get it right, and you position your organization for lasting success in the AI-powered economy.
“Doing AI” means building artificial intelligence from the ground up - designing neural networks, training models, and pushing the boundaries of what AI can do. It’s the domain of research labs, tech giants, and companies whose competitive advantage depends on proprietary capabilities. “Using AI,” on the other hand, means leveraging existing AI platforms, tools, and APIs to solve business problems quickly and cost-effectively - without reinventing the wheel.
Through real-world examples from healthcare, finance, manufacturing, retail, and tech, we show how this choice plays out in practice. A pharmaceutical company developing unique drug discovery algorithms may need to do AI. A hospital optimizing patient scheduling can thrive by using AI tools already available. An investment bank may require custom trading algorithms, while a community bank gains more value from proven fraud detection solutions.
We explore the radically different investment profiles, timelines, and talent needs of each approach, as well as the risks of getting them wrong. You’ll learn how AI-as-a-Service is leveling the playing field for companies to access world-class capabilities, and why the next 2-3 years will be critical for aligning your strategy.
Whether you’re a startup founder, CIO, business leader, or just curious about how AI is shaping the future, this episode will equip you with the clarity to decide whether your organization should be building AI - or buying it. The answer could determine your competitive future.
Welcome to another electrifying episode of the Cognixia Podcast – your weekly deep dive into the most transformative technologies shaping our future.
This week, we explore a seismic leap in artificial intelligence that's about to redefine everything we thought we knew: GPT-5. Slated for release in August 2025, OpenAI’s latest flagship model isn’t just another upgrade—it’s a quantum leap in how AI understands, reasons, and interacts with the world.
Imagine an AI that doesn’t just respond—it remembers, reasons, and adapts. GPT-5 promises context-aware intelligence, long-term memory, multi-modal capabilities, and unprecedented performance across text, audio, image, and even video generation. From deep philosophical discussions to complex business planning, from writing code to creating visual content—GPT-5 is designed to operate like a brilliant human collaborator.
In this episode, we cover:
- The evolution of GPT models—from GPT-1’s humble beginnings to the multimodal revolution of GPT-4 and 4o
- How GPT-5 marks a turning point with "magic unified intelligence"—one AI that does it all, without switching between models
- A breakdown of its Mini and Nano variants, designed for lower-power devices and mobile platforms—bringing AI everywhere, for everyone
- Massive improvements in factual accuracy, reduced hallucinations, and structured problem solving
- Real-world applications across industries: education, healthcare, software development, creativity, and enterprise productivity
- The game-changing potential of enhanced memory, allowing long-term contextual relationships with users
- Why experts (including Sam Altman) are calling this release “weirdly powerful”—and what that really means
- The ethical and infrastructure challenges behind building AI this advanced: compute, alignment, safety, and environmental cost
We also dive into the broader implications:
- How GPT-5 could impact global AI competition, digital sovereignty, and economic leadership
- What this means for job roles, upskilling, and human-machine collaboration
- The philosophical and societal questions we must now ask about creativity, identity, and intelligence in an AI-enhanced future
Whether you're a developer, business leader, educator, or simply an AI-curious explorer, this episode is your guide to understanding what’s coming—and why GPT-5 isn’t just smarter, but potentially civilization-shifting.
Buckle up—because we’re not just talking about better AI.
We’re talking about the dawn of an entirely new era of human-computer symbiosis.
In this week's eye-opening episode of the Cognixia Podcast, we pull back the curtain on an invisible yet urgent environmental cost of the AI revolution – water consumption. Titled “Meta’s AI Megacentres and the Hidden Water Crisis,” this episode explores how the global race for artificial intelligence dominance is draining not just data, but also one of our most precious and limited natural resources: water.
We begin in small-town Georgia, where residents are facing a disturbing reality – dry wells, rising water costs, and growing anxiety – all in the shadow of massive AI data centers. These aren't ordinary server farms; they are Meta’s next-gen AI megacentres, Prometheus and Hyperion, designed to power cutting-edge models but demanding millions of gallons of water daily to cool their high-performance computing infrastructure.
How much water are we talking about? Try up to 6 million gallons per day, per facility – more than some entire countries use. This episode walks you through the technical physics of AI data center cooling, why traditional air systems no longer suffice, and how liquid cooling systems – necessary to prevent catastrophic heat failures – create a permanent, unrelenting thirst for ultra-pure water.
But this story is about far more than pipes and processors. We shine a light on the human impact – families forced to drill deeper wells at enormous personal cost, communities burdened by skyrocketing utility bills, and the rising feeling of helplessness as decisions made in Silicon Valley reshape lives across rural America.
Listeners will learn about:
- Why advanced AI systems generate power-plant levels of heat
- How water-dependent cooling systems are essential for modern AI training
- The regulatory loopholes that allow such massive resource use with limited oversight
- The emerging concept of "resource colonialism" by Big Tech
- How Meta’s promises of efficiency and sustainability often come too late
We also unpack the sociological and ethical tensions at play. What happens when billion-dollar data centers rise in towns with fragile ecosystems and limited public infrastructure? Is the pursuit of slightly better AI models worth draining aquifers that took millennia to form?
This episode challenges the long-held myth of a “clean” digital economy. AI may seem intangible, but its foundations are rooted in very real, very physical resources – and the environmental costs are becoming too big to ignore.
With climate change already escalating droughts and water scarcity, we pose the difficult questions: Are these AI megacentres sustainable? Who bears the cost of technological progress? And can we strike a balance between innovation and community stewardship?
As we reflect on the stories of Prometheus and Hyperion, we invite you to consider a broader truth: every tech breakthrough has a footprint, and how we manage that impact will shape the world for generations.
Tune in now to this powerful episode that connects emerging technology, infrastructure, and human resilience. Stay informed, stay curious, and as always – happy learning!
Messaging apps have long been essential to how we connect—but what happens when artificial intelligence turns these familiar platforms into intelligent, proactive, and deeply personalized assistants?
In this episode of the Cognixia Podcast, we explore how AI is transforming WhatsApp and other messaging platforms into smart, intuitive digital hubs, setting the stage for a massive shift in how billions of people communicate every day.
With over 2.7 billion users, WhatsApp isn’t just a messaging app—it’s the default communication channel for half the planet. And now, with recent AI breakthroughs, it's poised to become something far more powerful: a personalized assistant that understands context, communicates across languages, automates tasks, and bridges the gap between consumers and businesses—seamlessly, intelligently, and at scale.
We break down:
- How WhatsApp and messaging apps are evolving from static chats to AI-first communication platforms
- The emergence of RCS (Rich Communication Services) and how it positions Android for the AI era of messaging
- Why AI-powered features like real-time translation, smart summaries, and emotionally aware assistants are set to become standard
- How businesses are adopting messaging platforms with built-in conversational AI to deliver better customer experiences and boost engagement
- The hidden potential of AI + messaging in emerging markets, education, healthcare, and internal enterprise communication
This isn’t science fiction. It's already happening—with Google, Meta, OpenAI, and several startups racing to redefine what messaging apps can do.
We also explore:
- The role of AI in transforming customer service—from bots to intelligent agents that remember past conversations
- Federated learning and on-device AI as a response to growing data privacy concerns
- Why AI-native messaging will disrupt traditional apps like email, calendars, and even browsers
- The future of multilingual, multimodal communication in real time
By 2026, experts predict that smart messaging assistants will be responsible for over 50% of digital customer interactions. The convergence of AI, NLP, and massive messaging adoption is leading us into a new era—where your chat app becomes a full-service digital concierge.
Whether you’re a tech leader, digital marketer, L&D head, or business strategist, this episode is your guide to understanding what’s next in intelligent communication—and how to stay ahead of the curve.
In this episode of the Cognixia Podcast, we dive deep into the cutting edge of AI-powered creativity as we explore Baidu’s groundbreaking MuseSteamer platform—a revolutionary image-to-video technology that’s transforming the future of digital marketing.
Imagine turning a single image into a dynamic 10-second video in seconds. Now imagine doing that at scale, in different styles, with AI understanding your target audience, product, and campaign goals. Welcome to Baidu’s Steamer-I2V model—delivering Turbo, Pro, and Lite video generation modes tailored for every marketing scenario.
But MuseSteamer is more than a cool AI feature—it's a strategic weapon in Baidu’s race against ByteDance, Tencent, and global players like OpenAI’s Sora. This episode unpacks how Baidu is reshaping not only how video content is created but how marketers think about creativity, scale, and speed in the AI era.
We explore:
- How MuseSteamer transforms single images into scroll-stopping videos
- Why Baidu is focusing exclusively on business users and marketers
- The rise of multimodal search, where prompts include images, voice, and long-form queries
- China’s rapidly evolving AI advertising arms race
- The emerging challenge of the “AI video upsell”—where scale and quality drive new pressures for content teams
- Why AI isn’t replacing creativity—but amplifying it
With ByteDance launching Doubao and Tencent pushing Yuanbao, Baidu’s move into AI-powered video production isn’t just timely—it’s essential for survival in one of the most aggressive tech ecosystems in the world. And with regulatory landscapes in flux, Baidu’s focus on first-mover advantage among Chinese marketers could have global ripple effects.
We also break down the technical brilliance of MuseSteamer: how it animates images with intelligent motion, contextual storytelling, and mode flexibility, and how it fits within Baidu’s broader marketing tech stack. The future of content is multimodal, real-time, and AI-enhanced—and MuseSteamer offers a glimpse into what the next decade of digital marketing might look like.
If you're a marketer, content creator, or tech enthusiast, this episode offers a rare look behind the scenes of a platform that could change how the world tells stories. From campaign ideation to execution, AI tools like MuseSteamer will challenge us to rethink everything we know about creativity, cost, and content velocity.
Tune in to discover how Baidu’s bold vision is redefining the global AI marketing game—and what it means for you.
In this episode of the Cognixia Podcast, we journey into the heart of the Industrial Internet of Things (IIoT) revolution—where machines talk, factories think, and visionary CIOs are reimagining what manufacturing looks like in 2025.
Step onto the modern shop floor: sensors hum, AI agents make real-time decisions, and collaborative robots (cobots) perform in sync with human teammates. It’s not science fiction—it’s the reality being engineered by industrial leaders right now.
This episode explores:
- The evolution from Industry 4.0 to Industry 5.0
- The transformative power of IIoT ecosystems—where machines, systems, and humans collaborate
- How CIOs are overcoming legacy infrastructure, cultural resistance, and skills shortages
- The rise of agentic AI and conversational systems that make factory data actionable for everyone
- The critical role of cobots, cloud platforms, and scalable frameworks like Reliance Jio’s Lego-as-a-Service
We spotlight the staggering impact of IIoT implementation: 20–30% reduction in unplanned downtime, 15–25% increases in equipment effectiveness, and smarter decision-making fueled by real-time data. More importantly, we reveal how smart factories are no longer just automated—they’re adaptive, intelligent, and human-centered.
CIOs are no longer just IT leaders—they’re transformation architects. From reshaping job roles to embedding digital literacy on the floor, their work is driving sustainable innovation and workforce resilience.
Whether you’re a tech strategist, manufacturing professional, or innovation enthusiast, this episode will change how you think about the future of production. This is not just a tech trend—it’s the next industrial revolution. Tune in to understand how IIoT is not only redefining factory floors, but also the role of leadership, talent, and imagination in building truly intelligent enterprises.
Join us for a dynamic, insightful conversation on how the CIOs of today are engineering the factories of tomorrow.
In this powerful episode of the Cognixia Podcast, we dive into one of the most meaningful and innovative applications of artificial intelligence in recent times – Britannia’s A-eye platform, a groundbreaking initiative transforming the grocery shopping experience for visually impaired individuals.
We’re not just talking about a new feature or a tech upgrade. This is a story of how genuine empathy and cutting-edge technology came together to solve a challenge most of us never even think about: how to make grocery shopping independent, dignified, and empowering for the millions who cannot rely on sight to make everyday decisions.
Developed through a unique collaboration between Britannia, Google, WPP, Mindshare, and Mission Accessibility, A-eye is a multimodal AI solution that uses a smartphone’s camera and voice input to provide real-time product information, comparisons, guidance, and navigation. But what truly sets this initiative apart is its commitment to inclusive design—from day one, visually impaired users were involved in co-creating the system, ensuring that the solution truly meets their needs.
You’ll learn how A-eye uses computer vision, natural language processing, and contextual awareness to go far beyond identifying products. It understands user preferences, dietary restrictions, and even shopping history to recommend items, suggest alternatives, and deliver personalized insights. Whether it’s comparing protein content, identifying allergens, or navigating aisles, A-eye becomes a shopping assistant tailored to each user’s unique lifestyle.
More than a technical marvel, A-eye is a case study in ethical innovation—showing how AI, when built with intention and community engagement, can create powerful social impact. The episode explores:
- The real-world challenges visually impaired shoppers face in traditional retail
- How multimodal AI bridges accessibility gaps through audio, vision, and touch
- The importance of "nothing about us, without us" in inclusive tech development
- The wider implications of this technology across global retail and other sectors
From increased independence to more confident purchasing decisions, the early impact stories of A-eye are inspiring—and serve as a blueprint for brands everywhere. This isn’t just accessibility as a checkbox. It’s accessibility as innovation, unlocking new possibilities and markets while making the world a little fairer.
If you care about inclusive design, the social good potential of AI, or how technology can transform everyday experiences in meaningful ways—this episode is for you.
Join us for a heartfelt and eye-opening conversation that proves AI’s greatest impact comes not from mimicking humans, but from amplifying human potential.
Welcome to this week’s episode of the Cognixia Podcast, where we dive deep into the groundbreaking world of specialized robotics—a revolution that's quietly transforming industries while redefining what machines can achieve.
Forget humanoid robots from science fiction. Today’s real innovation lies in robots built for specific purposes, engineered with precision and designed to perform individual tasks better, faster, and more consistently than any human could. From warehouses to farms, factories to operating rooms, these robots are not trying to replicate human form—they’re surpassing human performance in focused areas of work.
In this episode, we explore how specialized robots are being developed and deployed at scale. Learn how industrial robots from companies like Boston Dynamics, ABB, and KUKA are streamlining manufacturing lines with pinpoint precision. Discover how Amazon’s 500,000+ robotic systems handle logistics at superhuman speeds and accuracy. Dive into surgical robotics like the da Vinci system, which enhances a surgeon’s capabilities with tremor-free control and 3D visualization.
We’ll also journey through the evolution of robotics—from the first industrial arm, Unimate, in the 1960s to today’s AI-powered machines that learn, adapt, and improve continuously. You’ll find out why the future of robotics doesn’t lie in general-purpose humanoids but in domain-specific excellence: robots that lay 1,000 bricks per hour, autonomously harvest crops, and even operate miles beneath the ocean’s surface.
This episode sheds light on:
- Why specialization leads to better performance and higher ROI
- How AI, sensors, and computer vision are enabling real-time adaptability
- The growing role of collaborative robots (cobots) working side-by-side with humans
- The economic impact, with productivity gains of 85% in robotics-driven sectors
- The massive investments flowing into robotics startups focused on niche applications
With global spending on robotics expected to exceed $200 billion annually by 2025, this isn't just a trend—it’s a technological movement reshaping the future of work and industry.
Whether you're a tech enthusiast, a professional exploring automation, or just curious about the future, this episode will give you a fresh, eye-opening perspective on where robotics is heading—and why it's not about building robots that look human, but ones that work better than we ever could.
Join us for this exciting episode of the Cognixia Podcast as we go beyond the code to uncover the rise of specialized robotics and the invisible revolution happening all around us.
The Cognixia podcast episode explores DigiYatra, India's pioneering facial recognition-based digital identity system revolutionizing airport travel. Implemented across 24 airports and processing over 48 million passengers, DigiYatra enables paperless boarding via facial biometrics, eliminating queues and document checks. The system boasts a resilient, distributed architecture and custom AI trained on India’s vast demographic diversity. Its success stems from strong privacy safeguards, transparency, and optional adoption, earning user trust. DigiYatra's tech stack and adaptive algorithms ensure high accuracy even in complex conditions. More than a travel innovation, it sets a global example for inclusive, privacy-conscious digital identity systems at scale.
This Cognixia Podcast is about Bank of India announcing a significant ₹2,000 crore investment in IT upgrades for FY26, marking a major step in modernizing its banking infrastructure. This move highlights a shift in India's public banking sector toward prioritizing digital transformation and cybersecurity amid rising cyber threats and evolving customer expectations. The investment aims to enhance operational efficiency, boost security, and close the technology gap with global banks. It also reflects the broader shift in Indian banking where technology is now seen as a core capability. This transformation could redefine customer experiences and strengthen the country’s entire financial ecosystem for the digital future.
The Cognixia podcast highlights a groundbreaking partnership between Bengaluru International Airport Limited and KPMG India to implement Generative AI (GenAI) at Kempegowda International Airport. This AI-driven system aims to transform airport operations from reactive to predictive, improving efficiency, passenger experience, and adaptability. GenAI will generate insights and real-time solutions using data from passenger flows, flight schedules, baggage tracking, and more. Unlike one-size-fits-all systems, this AI platform is custom-built for Bengaluru, with scalability for future use elsewhere. Importantly, the initiative enhances—not replaces—human roles, empowering airport staff and setting new global benchmarks for intelligent, responsive, and human-centric airport management.
This episode of the Cognixia Podcast is about a viral video showing a humanoid robot acting aggressively in a Chinese factory has reignited fears about robot safety. Though the cause was likely a coding glitch in the Unitree H1 robot, social media exploded with memes and conspiracy theories. The incident reflects deeper public anxiety about fast-evolving robotics and AI technologies. While engineers understand that complexity can lead to malfunctions, the public often reacts emotionally, fueled by sci-fi tropes. This raises critical issues around safety standards, liability, privacy, and the need for stronger regulation. True innovation must prioritize safety, reliability, and ethical responsibility as robots become more common in society.
This Cognixia Podcast episode traces the rise and fall of Skype, a pioneer in internet communication. Launched in 2003 by the creators of Kazaa, Skype introduced free voice calls using peer-to-peer technology, revolutionizing global connectivity. It soared to fame, was acquired by eBay and later Microsoft, and evolved into a powerful business tool. However, with the rise of mobile-first platforms like WhatsApp, Zoom, and Microsoft Teams, Skype lost its edge. Teams became Microsoft’s new communication focus, especially during the COVID-19 pandemic. Despite its decline, Skype’s legacy endures as a trailblazer that redefined digital communication worldwide.
The Cognixia podcast explores the advanced technology behind cricket measurements, especially during IPL 2025. It traces the evolution from radar guns in the 1970s to today’s ultra-HD cameras, AI algorithms, and smart balls that track speed, distance, trajectory, and even impact force. Innovations like Hawk-Eye, Hot Spot, and real-time data processing enhance gameplay analysis and broadcast experiences. These systems provide precise stats like Bumrah’s 153.4 km/h yorkers and Pant’s 100+ meter sixes. Modern broadcasts use AR graphics and global data sharing to enrich fan engagement. This technology not only entertains but also supports coaching, safety, and player performance improvement.
In this episode of the Cognixia Podcast, the spotlight is on Shark Tank's Kevin O'Leary, who is building North America’s largest AI data center in Canada. Designed to meet the surging demand for AI computing power, the facility spans hundreds of acres and leverages hydroelectric, solar, and wind energy for sustainable operations. It features cutting-edge cooling and heat recycling systems and includes community benefits like local education and training programs. Despite facing regulatory, logistical, and supply chain challenges, the project aims for carbon neutrality and positions Canada as a major global AI hub, potentially reshaping the industry’s infrastructure standards.
The Cognixia Podcast explores fostering a culture of continuous improvement in Scrum teams. Continuous improvement, rooted in Agile and Lean principles, extends beyond Sprint Retrospectives to creating a mindset of constant learning and optimization. Key strategies include making retrospectives effective, using data-driven insights, encouraging learning, empowering teams, breaking down silos, and fostering psychological safety. Visibility, connection to purpose, and embedding improvement in team rituals are crucial. Sustaining momentum requires varied focus, linking improvement to career growth, and seeking external inspiration. The best teams continuously evolve, making incremental progress each Sprint. The episode concludes with a call for lifelong learning.
The Cognixia Podcast explores how politeness—like saying “please” and “thank you”—impacts AI models such as ChatGPT. While these courtesies seem trivial, they add up to significant computational costs, potentially tens of thousands of dollars, due to the extra tokens processed. Yet, OpenAI sees this as a worthwhile investment because polite interactions enhance user experience, improve response quality, and foster respectful human-AI relationships. Politeness also reinforces positive behavioral habits and builds trust, which contributes to user satisfaction and brand loyalty. Ultimately, these small tokens help shape a more thoughtful, respectful future in human-AI interaction, aligning technology use with human values.
The Cognixia Podcast explores the viral “Ghibli AI” trend, where users generate Studio Ghibli-style portraits using OpenAI’s enhanced image-generation tools. Fueled by social media and hashtags like #GhibliMe, the trend exploded due to its accessibility and the whimsical charm of the Ghibli aesthetic. While fun, it contrasts sharply with Ghibli co-founder Hayao Miyazaki’s philosophy, which values human artistry over AI. The episode dives into the tech behind the trend, the cultural impact, and ethical concerns about copyright and authenticity. It raises questions about the role of AI in art and the potential commercialization of beloved artistic styles without proper context or consent.
This Cognixia Podcast discusses how Zomato faced performance issues with its old PHP-based PDF generation system, struggling with latency and scalability. Instead of opting for commercial solutions, they built Espresso, a high-performance PDF generation system using Go for speed and concurrency, Rod for headless Chromium rendering, and Go PDF for signing. Optimization strategies included pre-paint PDF generation, fine-tuned Chromium flags, and DataURI image prefetching. Espresso generates and signs PDFs in under 200ms, handling 120,000 requests per minute, reducing server costs by 90%. Open-sourced on GitHub, it showcases Zomato’s engineering excellence in solving real-world technical challenges.
The Cognixia Podcast explores Medusa Ransomware, a major cyber threat impacting over 300 organizations. Medusa operates using a Ransomware-as-a-Service (RaaS) model, where developers license ransomware to affiliates who execute attacks. This model has industrialized ransomware, making it more accessible to cybercriminals. Medusa employs double-extortion tactics, encrypting files and exfiltrating data to pressure victims into paying ransoms ranging from $50,000 to $5 million. Organizations can defend against such threats with robust backups, phishing awareness, software updates, access controls, and incident response planning. The podcast emphasizes cybersecurity as an ongoing process essential for business trust, compliance, and financial security.
The Cognixia Podcast discusses emerging digital technologies, with this episode focusing on Binance delisting Tether’s USDT stablecoin for European Economic Area (EEA) users. Binance, the world’s largest crypto exchange, made this decision in response to new EEA regulations under the Markets in Crypto-Assets (MiCA) framework. USDT, a major stablecoin pegged to the US dollar, has faced scrutiny over its reserves and alleged illicit activities. The move highlights increasing regulatory pressures in crypto, potential market shifts, and the need for traders to adapt. The episode explores alternative stablecoins, regulatory impacts, and the future of stablecoins amid growing compliance demands.
The Cognixia Podcast explores emerging digital technologies and this episode discusses a breakthrough in data center energy efficiency. Data centers consume vast amounts of electricity, contributing to 2% of global emissions. Researchers at the University of Waterloo have discovered that modifying 30 lines of code in the Linux kernel's network stack can cut energy consumption by 30%. This technique, called "interrupt request suspension," reduces CPU interruptions during high-traffic periods, improving efficiency and performance. Implementing this change could significantly reduce costs and environmental impact without requiring major infrastructure changes, paving the way for energy-conscious software development in the future.
The Cognixia Podcast explores GPT-4.5, a groundbreaking advancement in AI. Unlike its predecessors, this model excels in deep research, pattern recognition, creativity, and emotional intelligence. It synthesizes information, understands sarcasm, and generates highly nuanced, human-like responses. GPT-4.5 surpasses competitors like Copilot, Gemini, and Alexa+ by offering advanced coding assistance, contextual understanding, and dynamic interaction. While it reduces AI hallucinations and enhances fact-checking, challenges remain, including ethical concerns, sustainability, and cybersecurity risks. The episode emphasizes the need for skilled professionals and responsible AI development, highlighting GPT-4.5’s potential to transform human-technology interactions.
The Cognixia podcast explores Microsoft Fabric, a revolutionary data analytics platform that unifies Azure Data Factory, Synapse Analytics, and Power BI into a seamless experience. Fabric eliminates the need to switch between multiple tools, offering a consistent interface for data ingestion, processing, and visualization. Key features include OneLake for centralized data storage, collaborative workspaces, real-time analytics, and AI-powered insights. Businesses benefit from cost efficiency, enhanced security, and improved collaboration. Fabric's integration with Microsoft tools makes adoption easier, promising a future of unified data workflows. While still evolving, it represents the next big shift in data analytics. Happy learning!
The Cognixia podcast discusses burnout among IT professionals, sparked by industry leaders advocating extended work hours. It highlights research showing that productivity declines beyond 50-55 hours per week and excessive work can cause serious health issues. The episode shares ten strategies to combat burnout, including setting work-life boundaries, using the Pomodoro Technique, taking strategic breaks, exercising, practicing mindfulness, optimizing the work environment, prioritizing sleep, building professional networks, learning to say no, and continuous skill development. It emphasizes that sustainable work habits lead to long-term productivity and innovation. The episode concludes by reinforcing the importance of mental and physical well-being.
This Cognixia Podcast describes India's latest budget has significantly boosted AI in education, with a new AI center of excellence increasing total investment in such centers to ₹500 crore. This initiative aligns with the National Education Policy 2020, aiming to personalize learning and modernize education. The IndiaAI Mission's budget has surged to ₹2,000 crore, highlighting India’s commitment to AI leadership. Additionally, five national skill development centers and 50,000 Atal Tinkering Labs will foster innovation. Expanding BharatNet will improve rural digital access, while AI-powered tools will enhance teaching and learning. These efforts position India as a global tech hub, though implementation challenges remain.
The Cognixia Podcast discusses the latest advancements in digital technologies, focusing on DeepSeek, a Chinese AI company that has launched two powerful models—DeepSeek v3 and R1—at a fraction of the cost compared to competitors. DeepSeek rivals OpenAI’s GPT-4, excelling in reasoning, problem-solving, and coding assistance. Notably, it is open-source, allowing developers to access, modify, and contribute to its development. The launch disrupted the AI landscape, impacting stock markets and raising skepticism. However, its affordability and transparency democratize AI access, fostering global innovation. The podcast emphasizes staying open to emerging players in AI and the exciting future of technological advancements.
The Cognixia Podcast explores the concept of AI "temperature," a key parameter controlling the randomness and creativity of Generative AI tools. At low temperatures, AI produces precise, reliable responses, while higher settings make it more unpredictable and creative. The podcast discusses various AI tools—ChatGPT (chameleon-like adaptability), Google's Gemini (strategic thinker), Microsoft Copilot (code wizard), and Perplexity (research guru). It also highlights AI hallucinations, where tools generate misleading or incorrect information. To avoid errors, users should verify facts, compare responses, and trust human judgment. AI is a powerful tool, but human oversight remains essential for accuracy and creativity.
The Cognixia Podcast dives into ChatGPT's revolutionary new "Tasks" feature, a game-changing addition that transforms the AI chatbot into a personal assistant capable of scheduling and executing tasks. Tasks allow users to set reminders, schedule actions, and handle complex tasks like analyzing reports or summarizing data autonomously. Positioned as the next step toward Agenetic AI, this feature showcases the potential for AI systems to understand, adapt, and make intelligent decisions. OpenAI’s vision includes AI managing workflows dynamically and independently. The podcast highlights Cognixia’s commitment to keeping users ahead in tech through live, instructor-led courses in AI and emerging technologies.
The Cognixia Podcast explores India’s digital privacy revolution through the new Digital Personal Data Protection Bill. This transformative bill introduces measures like ‘Data Fiduciaries’ to ensure transparency in data collection and gives users rights to access, correct, and delete personal data. Companies face hefty fines for violations and must justify data collection. The bill balances privacy with digital innovation, catering to India’s unique challenges, like first-time internet users and startups adapting to compliance. While promising, issues like ‘deemed consent’ and data localization pose challenges. Overall, it empowers users with control over their digital lives, fostering a privacy-conscious India.
This Cognixia Podcast describes how OpenAI plans to develop superintelligence by 2025, aiming for AI that surpasses human intelligence across all domains. Superintelligence could revolutionize fields like science, medicine, and climate research. However, challenges like achieving human-like context understanding, efficient energy use, and ethical safeguards remain. Quantum computing may provide the computational power needed but is still in early stages. OpenAI emphasizes aligning AI with human values, focusing on safety and benefits rather than risks. While the timeline may be ambitious, the potential transformative impact of superintelligence is immense, making this a pivotal moment in AI's evolution. Stay tuned for more updates from Cognixia!
This Cognixia Podcast episode explores the popular "dark mode" feature in apps and devices. Originating from the energy-efficient CRT displays of the 70s, dark mode has evolved into a sought-after feature for reducing eye strain and saving battery life, particularly on OLED screens. It reduces visual fatigue in dim environments and minimizes blue light exposure, aiding better sleep. Developers face challenges in designing effective dark modes, balancing contrast, accessibility, and brand identity. Despite some drawbacks, like halation effects, dark mode enhances inclusivity for users with light sensitivity or impairments. It's a thoughtful, multi-layered feature, combining science, design, and user experience.
The Cognixia Podcast kicks off 2025 by introducing NVIDIA's Jetson Orin Nano Super Developer Kit, a groundbreaking at-home supercomputer that enhances generative AI performance by 70%. Featuring an NVIDIA Ampere architecture GPU, a 6-core Arm CPU, and 67 INT8 TOPS, it offers 50% more memory bandwidth and runs on just 25 watts. Priced at half its predecessor, it supports up to four cameras and is CUDA and CUDNN compatible, making it ideal for generative AI and robotics development. NVIDIA’s innovation empowers developers to explore AI at the edge, advancing fields like manufacturing, healthcare, and creative arts. Stay tuned for more insights!
The Cognixia Podcast explores how cryptocurrency theft occurs and offers tips for prevention. Despite blockchain’s touted security, vulnerabilities arise through exchange hacks, exit scams, phishing attacks, and device hacks. Exchange hacks exploit decentralized systems, while exit scams involve fraudulent ICOs or developers abandoning projects, like the Squid Game token. Phishing attacks often stem from suspicious emails containing malware, compromising credentials and wallets. Device hacking, such as SIM swaps, targets smaller investors. To stay safe, users should store assets in hardware wallets, enable multi-factor authentication, avoid suspicious links, and secure private keys. Vigilance and proactive security measures are crucial in mitigating risks.
This episode of the Cognixia Podcast explores the widespread issue of piracy in the Japanese manga and anime industry, emphasizing the billions of dollars in revenue lost annually. Japan plans to invest $2 million to develop an AI-powered system to detect and curb piracy by analyzing copyrighted content and piracy site layouts. The initiative reflects global efforts to combat piracy, as seen in South Korea's recent measures. The episode highlights the creative effort behind anime and manga, urging fans to support original work and report piracy. It concludes with a call to action to say no to piracy and protect creative industries.
The Cognixia Podcast explores emerging digital technologies, focusing this episode on AI advancements, particularly ChatGPT. Since its launch in 2022, ChatGPT has revolutionized tech interactions, offering features like personalized memory, coding assistance with Canvas, and advanced models like GPT-4 and OpenAI o1. These tools empower developers, enabling even beginners to tackle complex tasks. While AI enhances productivity and creativity, it’s not flawless and requires critical oversight. Challenges like legal concerns over AI-generated code and potential automation of entry-level jobs highlight its limitations. Despite this, AI continues to evolve, promising transformative potential while urging users to balance innovation with responsibility.
This Cognixia podcast episode explores platform engineering as a rapidly evolving discipline in modern digital transformation. Highlighting insights from the 3rd State of Platform Engineering Report, it notes that most platform teams are under two years old, driven by needs like automation, infrastructure standardization, and developer self-service. Platform engineering complements DevOps, addressing gaps such as repetitive tasks and enhancing time-to-market. While the industry is in its early stages, with limited measurement and adoption maturity, some organizations have advanced capabilities. Key focus areas include CI/CD, Kubernetes, and Infrastructure-as-Code. For sustainable growth, organizations should invest in training and robust frameworks.
The Cognixia podcast explores emerging digital technologies, offering insights to inspire skill development and career growth. This episode focuses on convincing senior management to adopt IT Service Management (ITSM) solutions. It emphasizes understanding key decision-makers' interests, addressing their concerns, and framing ITSM as an investment that boosts efficiency, customer satisfaction, and profitability. The podcast outlines six steps: presenting the case, explaining current challenges, highlighting benefits, addressing process improvements, showcasing financial gains, and providing a detailed implementation plan. Tailor your approach to suit organizational needs and overcome resistance to change. Finally, Cognixia offers ITIL 4 certification training for interested professionals.
The Cognixia Podcast explores emerging technologies, discussing advancements like AI’s surprising applications. This episode delves into “digital olfaction” and “scent teleportation,” innovative technologies enabling AI to detect, analyze, and recreate scents. By capturing chemical signatures of aromas, AI can digitally transmit and replicate scents, revolutionizing industries such as online shopping, healthcare, and virtual reality. While applications like detecting gas leaks or customizing fragrances offer immense potential, concerns arise about over-dependence on AI diminishing human instincts. The episode emphasizes mindful tech use and collaboration between human and artificial intelligence for optimal results. Stay curious and keep learning for career growth!
This episode of the Cognixia Podcast dives into the concept of passkeys, an emerging method of passwordless authentication that’s becoming more secure and popular than traditional passwords. Passkeys use cryptographic keys (public and private) to authenticate users, making them resistant to phishing and other attacks that commonly compromise passwords. Unlike passwords, passkeys are often tied to specific devices and typically require biometric authentication, adding another layer of security. Passkeys can simplify login by eliminating the need for users to remember complex passwords while also reducing the risks associated with stolen credentials. They work seamlessly across compatible ecosystems, though current limitations include cross-platform challenges (e.g., iPhone passkeys don’t transfer easily to Windows laptops). Supported by standards from W3C and the FIDO Alliance, passkeys have gained support from Apple, Google, Microsoft, and major browsers. While they aren’t entirely hack-proof, they are significantly more secure than passwords, and over time, they might fully replace them. The episode ends by encouraging listeners to stay tuned for more updates on emerging digital technologies.
In this episode of the Cognixia podcast, the discussion centers on a recent lawsuit filed by Dow Jones and the New York Post against Perplexity AI. The publishers accuse Perplexity of using their copyrighted content without authorization for its AI-generated summaries, a practice they argue undercuts content discoverability and revenue. Unlike Google, which supports content discovery through its AI summaries, Perplexity allegedly bypasses this, impacting publishers’ revenue models. The lawsuit also highlights concerns over "hallucinated" content, where Perplexity generates false information. This ongoing legal battle underscores tensions between media companies and AI firms over content usage rights and compensation.
The cognixia podcast discusses the significance of networks, particularly 5G and the upcoming 6G, which is expected to roll out by 2030. While 6G will offer faster speeds and minimal latency, India faces challenges, particularly a lack of skilled professionals and underdeveloped infrastructure. Although India has ambitious goals for 6G patents and standards, significant gaps remain, especially in workforce readiness and infrastructure investment. The country also needs to enhance its global presence in technology committees and increase research funding. As India strives to be a leader in 6G, the podcast highlights the importance of upskilling and sustainability efforts.
The Cognixia Podcast discusses the 2024 Nobel Prize in Physics, awarded to AI pioneers John Hopfield and Geoffrey Hinton. Their work in artificial neural networks, foundational to modern AI, stems from principles in physics. Hopfield created a network mimicking atomic spin to save and reconstruct data patterns, while Hinton advanced this with the Boltzmann Machine, which autonomously recognizes patterns in data using statistical physics. The podcast highlights how physics has played a crucial role in AI’s development, emphasizing the interconnectedness of scientific fields and urging listeners to keep learning and evolving their skills.
This episode of the Cognixia Podcast covers the new Windows 11 24H2 update, highlighting its AI-powered features, enhanced security, and improved user experience. Key upgrades include support for Wi-Fi 7, a redesigned File Explorer, and features like customizable energy-saving modes, advanced assistive hearing aids, and better privacy settings. Developers and IT professionals benefit from the new sudo commands, Rust support, and enhanced cybersecurity features. The episode explains how users can access the update through Windows Update services and emphasizes the importance of staying updated for improved security and performance. The episode concludes with a reminder to check out their festive offers.
This episode from the Cognixia Podcast explores how to monetize an API using AWS services, particularly the Amazon API Gateway. It covers key challenges like managing subscriptions, handling payments globally, and controlling API access. The episode suggests using the AWS Marketplace to sell APIs but notes that it limits potential customers to AWS users. Alternatives include broader API marketplaces like Rapid API, or subscription platforms like Stripe and FastSpring. It explains how combining API Gateway, Lambda functions, and a payment platform can create a functional API monetization system, emphasizing careful marketplace selection and usage plan considerations.
This episode from the Cognixia Podcast discusses the increasing incidents of email-based security breaches in Critical National Infrastructure (CNI) companies, which include utilities, transport, telecom, data centers, and more. It highlights how cyberattackers are using emails as a primary method to infiltrate CNI organizations, with ransomware attacks on the rise. A report by OPSWAT shows that 80% of CNI companies experienced email-related breaches in 2023, and many organizations still underestimate email risks. The episode also explains that legacy systems and outdated infrastructure make CNI companies especially vulnerable to these cyberattacks.
It discusses the UK’s recent move to classify data centers as CNI, emphasizing the need for stronger security and government support for these facilities. The episode also touches on the global vulnerability of CNI organizations due to the reliance on legacy systems, which can be 20-30 years old. A key takeaway is the need for innovation and updating systems in CNI companies to prevent future cyberattacks. Finally, the episode reflects on how email-based threats could severely impact these organizations and stresses the importance of improving cybersecurity.
This episode of the Cognixia podcast discusses the global semiconductor chip shortage, which started in 2020 due to the Covid-19 pandemic. The shortage is driven by supply chain disruptions, high demand across industries, and challenges in chip production, which can take up to six months. Factors like trade wars, natural disasters, and export restrictions from China have worsened the issue. Despite production improvements, shortages persist, impacting industries like automotive and IoT. However, the future looks bright, with the semiconductor market expected to grow, potentially reaching $1 trillion by 2030, driven by demand in automotive, data storage, and wireless technology.
The Cognixia podcast discusses the latest update from Microsoft in Power BI, enabling users to write DAX queries via the web interface. Previously only available in Power BI Desktop, this feature allows users to create calculations, build models, and perform advanced data analysis. DAX (Data Analysis Expressions) is highlighted as a powerful tool for extracting insights from data through custom measures and statistical analysis. However, limitations remain on the web version, such as disappearing queries and the inability to save them like in the desktop version. Future updates are anticipated to enhance web features further.
The cognixia podcast discusses the rise of the Mojo programming language, which raised $100 million in funding in 2024. Mojo combines Python's ease of use with the performance of C, making it a potential game-changer, especially in AI development. While some wonder if Mojo will replace Python, the podcast suggests that Mojo complements Python by improving performance without sacrificing user-friendliness. Mojo is considered more of a competitor to C++ than Python. For AI programmers, learning both Python and Mojo is recommended, as each offers unique strengths that will help meet the evolving needs of AI development.
In this Cognixia podcast episode, the focus is on ErLang, a programming language with high median salaries, surpassing even popular languages like Python and Rust, as per the 2024 Stack Overflow Developer Survey. Despite ErLang's low adoption rate, it is highly valuable, particularly in industries like telecom and banking, due to its strength in handling concurrent processes and mission-critical applications. ErLang developers are rare, making their skills highly sought-after and well-compensated. The podcast encourages developers to consider learning ErLang alongside more popular languages to enhance their career prospects.
The Cognixia podcast discusses the environmental challenge of e-waste and introduces a new flexible material developed by researchers at MIT, the University of Utah, and Meta. This material could revolutionize electronics by allowing for complex, multi-layered circuits while being recyclable. Unlike the commonly used polyimide, which is energy-intensive to produce and difficult to recycle, the new material is a form of polyimide that hardens quickly at room temperature and can be dissolved for recycling. This innovation could help mitigate e-waste and advance electronics, making technology more sustainable and accessible.
The Cognixia podcast episode highlights the significant role of AI at the Paris 2024 Olympics. Intel, Google, and Alibaba have partnered to enhance the event's technological capabilities, from AI-powered chatbots and digital twins to advanced sports analytics and sustainability efforts. AI tools have been crucial in ensuring fairness, transparency, and improved athlete performance through data insights. The episode also notes the Olympic Committee's commitment to sustainability and AI's broader impact on sports, hinting at future innovations. The podcast concludes with a teaser for the next episode, encouraging listeners to keep learning.
In this week's episode of the Cognixia podcast, the focus is on SearchGPT, OpenAI's upcoming search engine that combines AI-generated content with human-written articles, offering a conversational interface that allows users to ask follow-up questions. Unlike traditional search engines, SearchGPT provides real-time, up-to-date information and prominently credits original content creators, addressing previous concerns about AI content generation. While still in its prototype phase, SearchGPT shows potential to disrupt the search engine market. The episode also touches on Google's dominance and the evolving nature of search engines. Stay tuned for more updates next week!
In this week's Cognixia podcast, we discuss the importanceof lifelong learning, drawing inspiration from Theodore Roosevelt's dedication to knowledge. In today’s fast-changing world, continuous skill acquisition is crucial for staying relevant professionally. Set realistic learning goals, leverage tools like Generative AI, and track your progress with apps. Engage with your curiosity to find personal fulfillment and professional growth. Visit Cognixia for courses on emerging technologies. Happy learning!
Hello everyone and welcome back to the Cognixia podcast! Endpoint protection has been a buzzword in the world of cybersecurity for quite a bit now. Endpoint protection involves software running on local machines so they wouldn’t run malicious software or any unintended code. It is like a more modern name for the good old anti-virus and firewalls, sounds like it, no? It has two key components – a backend control center and an agent software which would be installed on the end point devices. And, if you haven’t guessed so far, endpoint devices are the user devices – mobile phones, laptops, desktops, etc. The endpoint protection agent software is constantly running on the endpoint devices. So, if you run a program or application that the agent feels needs to be prevented, a sensor would be notified by the operating system of the device and it will prevent the execution. The main endpoint application would also be notified about the blocked execution, which would further notify the control center, using the internet.
Simply put, this is a surveillance system of sorts. To be seriously effective they need to be deeply embedded into the operating system. It would also need to have the capability and requisite permissions to bypass lots of internal security systems.
So what happened exactly that more than 8.5 million systems were affected? Banking services came to a halt, countless flights were canceled, travelers were stranded, retail services came grinding to a stop, and an unimaginable number of workplaces were left staring at what is popularly called “The Blue Screen of Death”. While this number is less than 1% of Microsoft devices sold and operational globally, the broad economic and societal impact of even that 1% is unfathomable.
This is the first time such an incident has had figures, that too of this magnitude revealed. It is believed that this could be the worst cyber event in history. And, while the event is largely being labeled as a “Microsoft outage”, it is actually caused by an update that was rolled out by CrowdStrike, not Microsoft. The closest next big incident would be the WannaCry cyberattack of 2017 where over 300,000 devices were affected in over 150 countries. But do you see the difference between 8.5 million devices and 300,000 devices?
On 19 July at 04:09 UTC, CrowdStrike carried out a regular release of one such ‘sensor’ as a Windows device driver which would hook and attach deeper into Windows, one of the updates as part of the ongoing protection mechanisms of the Falcon platform. To do this, it would need special permissions, of course. These drivers would be written in C and C++, the same as the Windows kernels and core libraries. The configuration system triggered a logic error leading to a system crash and the blue screen of death or BSOD on impacted systems.
Hello everyone and welcome back to the Cognixia podcast! we talk about a major infrastructure innovation called the Hollow Core Fiber. As technology evolves, it requires the infrastructure supporting it to evolve as well, to keep up with the demands of the change. In this AI era, large scale computing is becoming an everyday thing and it is impossible to carry this out without strong, resilient, and foolproof infrastructure to support it. This is what could be called ‘Purpose-Built Infrastructure’. This can’t happen by just picking up a bunch of hardware and dumping it at a data center somewhere in the world, can it? That’s not how scientific breakthroughs and innovations really happen, do they?
At the Microsoft Ignite event in November 2023, a vey revolutionary technology came to everyone’s attention. This tech was called the hollow core fiber. It is an innovative optical fiber that can revolutionize global cloud infrastructure by not just offering superior quality but also improved latency and a more secure data transmission.
The hollow core fiber technology or HCF uses a proprietary design where light propagates in the air core of a hollow fiber. The cores of traditional fibers are made of optical glass, hence the name optical glass fiber or optical fiber. The HCF offers advantages over this traditional optical fiber.
But how do you prevent light leakage in a hollow core fiber and how do you ensure that the light keeps moving ahead in a straight path?
Well, the structure of the hollow core fiber has nested tubes that help reduce any unwanted light leakage and that also ensures that the light keeps moving ahead in a straight path through the hollow core.
If you go back to your high school physics class, you will remember that light travels faster through air than through glass. This helps the hollow core fiber to be about 47% faster than the standard silica glass. This, in turn, leads to much faster speeds and much lower latency when using the HCF. The HCF would also offer much higher bandwidth per fiber.
Hello everyone and welcome back to the Cognixia podcast. These are the communication, people management, and personality traits that make you a project manager people want to work with. Imagine a project manager as an orchestra conductor. They gotta guide each musician (team member) to play their part in harmony. That takes serious people skills to keep everyone motivated and moving in the same direction.
Project managers also need to be communication chameleons. They chat with higher-ups, the HR and admin folks, and even customers, vendors, and other teams. Each interaction requires them to adjust their communication style to get the best results. Mastering these soft skills is key to becoming a project management rockstar.
Soft skills, now what are they? These aren't skills you can learn from a coding tutorial – they are the people skills that make you a great teammate and a great leader. Think communication, collaboration, emotional intelligence – basically, anything that helps you work effectively with others. And let's be honest, projects rarely succeed in a vacuum – you need a strong team to get things done, it always succeeds on the backs of the people working on it. This is why soft skills are becoming increasingly important, no matter which industry you operate in or what your job title may be. They are like the glue that holds everything together, even for project managers with the best certifications the market can offer.
Technical skills might lay the groundwork for your project, but soft skills are the secret sauce to smooth execution. Think about it – even the most recognized project management certification, the PMP®, highlights the importance of soft skills like critical thinking, managing conflict, and making tough decisions. These might seem intangible, but they're the magic ingredients that turn a good project manager into a great one. So, before we dive into how to develop these essential skills, let's explore why they're becoming such a big deal in the project management world.
Hello everyone and welcome back to the Cognixia podcast. Maybe you were trying to buy something from the latest sale on your favorite online shop, or you wanted to buy a gift for someone, or you were trying to track a parcel. Happens to all of us, doesn’t it?
Most times we would drop trying and tell ourselves that we will do this later, right? But how many times do we really go back? Sometimes we do, sometimes we don’t, right? That is the cost the company paid for the downtime it faced, and usually, it is more than just a lost business.
A recent Splunk Report has shared that downtime costs the world’s largest companies about $400 billion every year – approximately 9% of their profits! This is the equivalent of about $9,000 lost for every minute of system failure or service degradation. Direct revenue loss is the biggest drain from downtime, but other hidden costs include diminished shareholder value, stagnant productivity, and reputational damage. The Report also goes on to share that a Forbes Global 2000 company would take about 75 days for its revenues to recover to where it stood financially before the downtime incident.
Hello everyone and welcome back to the Cognixia podcast. The theory of disruptive innovation was first introduced in 1995. Since then, it has proved to be a powerful way of thinking about innovation-driven growth. From Intel to Salesforce, disruptive innovations have been highly regarded and the theory is a guiding star for all individuals and organizations who want to do something cutting-edge.
Fast-forward to 2024, the disruption theory is threatened to become a victim of its own success. The theory, as experts opine, has been widely misunderstood and its fundamentals are frequently misapplied, often quite grossly.
Hello everyone and welcome back to the CognixiapodcastThe US Federal Bureau of Investigation, Cybersecurity and Infrastructure Security Agency, Department of Health & Human Services, and the Multi-State Information Sharing & Analysis Center issued a joint cybersecurity advisory. This advisory aimed to share more information about the “Black Basta”. Black Basta affiliates have been attacking entities across the United States, Canada, Japan, the UK, Australia, and New Zealand. Over 500 organizations have been impacted globally to date. At least 12 of the 16 critical infrastructure sectors have had data stolen from them so far.According to Kaspersky in its latest findings about the state of ransomware in 2024, Black Basta is ranked the 12th most active ransomware family in 2023, with a 71% rise in the number of victims in 2023 as compared to 2022.But, what is Black Basta?Black Basta is a Ransomware-as-a-Service whose first variants were discovered in April 2022. It is believed that Black Basta might have links to FIN7, a threat actor also called “Carbanak” active since 2012. It is affiliated with multiple ransomware operations. Black Basta’s modus operandi is quite similar to the older Conti ransomware structure, however, no proven links have been found between the two.What is Black Basta’s Modus Operandi?Black Basta affiliates employ a multi-pronged approach to infiltrate target networks. Their tactics focus on gaining initial access through various methods.One common technique involves phishing attacks. These deceptive emails aim to trick recipients into surrendering sensitive information or clicking malicious links. These links can download malware or redirect users to fake login pages designed to steal credentials.Another tactic Black Basta utilizes is exploiting known vulnerabilities in software or systems. If these vulnerabilities haven't been addressed through security patches, attackers can take advantage of them to gain unauthorized access.In some cases, Black Basta affiliates may opt to acquire valid credentials from underground marketplaces. These credentials, often obtained through previous cyberattacks, are sold by illicit actors known as Initial Access Brokers. By purchasing login information for targeted systems, Black Basta can bypass the initial intrusion stage altogether.
Hello everyone and welcome back to the Cognixia podcast. Imagine a bustling office filled with paper trails a mile long, overflowing filing cabinets, and employees scrambling to find critical documents. This organizational nightmare used to be the reality for many businesses. Enter Enterprise Content Management (ECM), a lifesaver that emerged in the late 1940s alongside the rise of lean manufacturing principles. Back then, it was known as the Toyota Production System, focusing on streamlining physical document storage and retrieval.
Fast forward to today, ECM has evolved into a sophisticated digital ecosystem. It's essentially a central nervous system for all your organization's information, encompassing documents, emails, images, videos, and more. Think of it as a giant, digital filing cabinet with superpowers! ECM goes beyond just storing information; it allows for secure access, version control, automated workflows, and even intelligent search functionalities.
Why is ECM so important for organizations? In today's data-driven world, information is a vital asset. ECM helps businesses tame the content chaos by offering several key benefits. Firstly, it boosts efficiency and productivity. Employees can locate documents quickly, eliminating wasted time searching through physical archives.
Secondly, ECM enhances collaboration by providing a central repository for shared information, ensuring everyone is on the same page. Thirdly, it strengthens compliance by enabling organizations to effectively manage and retain critical documents according to regulations. Finally, robust ECM systems can even leverage AI to automate tasks like document classification and data extraction, further streamlining operations and unlocking valuable insights from your content. In essence, ECM is the key to a well-organized, efficient, and information-driven organization.
Hello everyone and welcome back to the Cognixia podcast. The acquisition of HashiCorp is part of an effort to broaden IBM’s hybrid cloud, multi-cloud, and AI portfolio. Eventually, IBM plans to build a complete end-to-end platform using HashiCorp’s resources. The press release from IBM had Arvind Krishna sharing that IBM’s and HashiCorp’s combined portfolios would help clients manage growing applications and infrastructure complexity as well as create a comprehensively hybrid cloud platform designed for the AI era. In the same press release, the CEO of HashiCorp, Dave McJannet opined that IBM’s leadership in the hybrid cloud along with its rich history of innovation make it an ideal home for HashiCorp as they enter the next phase of their growth journey. So, what does HashiCorp do and what value does it bring to the IBM table?HashiCorp makes the HashiCorp Cloud Platform for critical lifecycle management and security applications with options for integration with major cloud providers like Google Cloud Platform and Amazon AWS. In the fiscal year 2024, HashiCorp reported a revenue of $583.1 million. With the acquisition deal, HashiCorp would get access to a much wider customer base and the opportunity to work closely with IBM on multi-cloud automation deployments. Here, we would also like to mention that Terraform by HashiCorp has often been regarded as the industry standard for infrastructure provisioning in hybrid and multi-cloud environments. In today’s competitive environment, AI has taken just about everything by storm, including cloud companies and platforms. A cloud platform would be left significantly behind in the market if it did not offer AI integrations and enablement. This is something HashiCorp could add huge value to the IBM products. HashiCorp brings the infrastructure that is suited for Generative AI products. HashiCorp’s tools in this regard are best fit for heterogeneous, dynamic, and complex environments. The sheer number of AI offerings and applications can sometimes be extremely overwhelming for users, and HashiCorp’s tools can help strengthen IBM products to keep the users sharp yet comfortable. Moreover, the public cloud environment has been so transformative that it is very clear now that multi-cloud and hybrid cloud environments are the way forward. This is a reality, after all, we all need to face and accept now.This strategic move positions IBM as a one-stop shop for businesses seeking robust, hybrid cloud infrastructure with a focus on security and automation. HashiCorp's expertise in multi-cloud management tools like Terraform, coupled with IBM's Red Hat acquisition, creates a powerful platform for businesses to seamlessly navigate across various cloud environments. This empowers users and consumers with greater flexibility and control over their cloud deployments, fostering innovation and agility.Additionally, the combined strengths of IBM and HashiCorp hold immense potential for the burgeoning field of Generative AI. HashiCorp's infrastructure management solutions combined with IBM's leading AI tools like Watson can pave the way for the development and deployment of large-scale, secure Generative AI applications. Imagine AI models that can design new materials, generate realistic simulations, or create personalized content – all facilitated by a robust and scalable cloud infrastructure. This convergence will ultimately benefit users and consumers by accelerating the development and accessibility of powerful Generative AI solutions across various industries.
Hello everyone and welcome back to the Cognixia podcast. Synthetic biology (SynBio) is a rapidly developing field that combines biology, engineering, and computer science to design and create new biological systems or modify existing ones. It blends the disciplines of biology (how with engineering principles as well as computational tools to manipulate and reprogram living organisms. Synthetic biology aims to create novel biological entities with specific functions or to improve existing ones. These functions can range from producing new medicines and materials to engineering microbes for environmental cleanup.
So, imagine you have a toolkit of building blocks like genes, proteins, etc. and you also have the skills and knowledge to assemble them into new and useful systems, quite akin to a programmer writing code to build a new software application, then what you would be doing would be under the domain of synthetic biology.
Synthetic biology or SynBio for short, holds immense potential to transform many fields. It can help the healthcare and pharmaceutical sectors in developing new drugs, vaccines, and personalized therapies. It can help the biomaterials space by creating sustainable materials with desired properties. It can help the agriculture sector by helping create unique engineered crops with improved yields or disease resistance. It can also help fuel innovations in the biofuel space by developing cleaner and more efficient energy sources.
SynBio enables rapid transformation by offering a revolutionary approach to manipulating living organisms. This powerful combination of biology, engineering, and computer science is fueling innovation across a vast spectrum. Imagine engineering yeast to produce sustainable fabrics or crafting microbes to clean up polluted environments., now how cool is that! These are just a few examples of how SynBio is blurring the lines between science fiction and reality.
One major area of disruption is medicine. Synthetic biology plays a pivotal role in the development of new drugs and therapies. By editing genes with incredible precision, researchers can create organisms that produce life-saving medications like insulin or fight off diseases by engineering CAR-T cells to target cancer. Beyond treatment, SynBio is also paving the way for personalized medicine, allowing scientists to tailor therapies to individual patients' genetic profiles.
Hello everyone and welcome back to the Cognixia podcast. In September 1983, Richard Stallman launched a project that would fundamentally alter the software landscape: GNU. This operating system emerged as a free alternative to the dominant Unix systems of the era. Stallman's vision was driven by a core belief: software should be open and accessible to all. He saw a growing trend towards proprietary software and copyright restrictions, and GNU was his response. This philosophy – that unrestricted access to code, free from commercial limitations, would benefit the world – became the foundation of the free software movement.
Fast forward four decades. Today's tech landscape is dominated by proprietary software, generating billions for tech corporations. Many everyday technologies, from complex language models like ChatGPT to seemingly simple smart thermostats, function as black boxes for consumers. Against this backdrop, Richard Stallman's vision of a free software movement might appear like a utopian ideal, overpowered by commercial forces.
However, the story doesn't end there. In 2024, the free and open-source software (FOSS) movement is not only enduring but thriving. FOSS has become a cornerstone of the tech industry, playing a crucial role in innovation and development.
Open-source software (OSS) has become a ubiquitous element in modern technology. A staggering 96% of codebases now incorporate some form of OSS, demonstrating its widespread adoption. This collaborative spirit extends to platforms like GitHub, the world's largest hub for open-source development, boasting over 100 million users worldwide.
Even within the commercial sector, the value of open source is recognized. Amazon Web Services (AWS), a major cloud computing platform, actively supports the development and maintenance of open-source projects. This commitment was further solidified in December last year when AWS pledged its patent portfolio to an open-use community.
This trend towards open-source collaboration comes at a time when public trust in private tech companies is declining. In response, organizations like Google, Spotify, the Ford Foundation, Bloomberg, and even NASA have established new funding initiatives. These efforts not only support open-source projects but also extend the principles of open collaboration to scientific research endeavors – a movement known as open science.
The widespread adoption of open-source software (OSS) has brought benefits and challenges. While OSS has become a cornerstone of modern technology, its long-standing leadership and diversity issues require critical attention.
Hello everyone and welcome back to the Cognixia podcast. Around 423 years ago, the titular character of Shakespeare’s legendary play – Hamley said “To be or not to be”. Today, four centuries later, we ponder on another such dilemma, and we say, “To Devin or Not to Devin”. Now if that confuses you, allow us to explain, because that is what today’s episode is all about – Devin.ai. So, fasten your seatbelts amigos and amigas, we are in for a ride.
Devin is a revolutionary AI that functions as a software engineer. This groundbreaking technology, created by Cognition under Scott Wu's leadership, can code, debug, and even develop apps and websites. Devin signifies a major advancement in AI's role within software development. Unlike AI advancements that threaten job security, Devin is designed to work alongside humans, boosting productivity rather than replacing them. This AI's ability to learn and adapt is transforming how software engineering tasks are tackled, paving the way for a future of closer collaboration between humans and AI.
Devin.ai isn't your average program. This cool AI tool is like having a whole new kind of engineer on your team – one that can code! Devin understands your instructions like your text commands, to be specific, and can tackle tasks like checking how well an app performs.
The way it works is super nifty. Devin has its own toolbox – a command line, code editor, and even a web browser. Using these tools, Devin can not only access information but also understand it, thanks to its built-in reasoning engine. Plus, it seems to have some serious long-term planning skills, likely powered by fancy reinforcement learning.
So, what can Devin actually do? Well, buckle up! This AI can build websites, find, and fix bugs in code like a champ, deploy applications, and even train other AI models. Sounds pretty impressive, right?
Hello everyone and welcome back to the Cognixia podcast.
The increasing popularity of electric vehicles (EVs) is accompanied by growing concerns about malfunctioning charging stations. This presents challenges for both EV owners and the companies that manage charging infrastructure.
The global shift towards electric vehicles (EVs) has experienced significant momentum in recent years. Governments around the world are actively promoting EV adoption through purchase incentives and investments in charging infrastructure. However, this rapid growth has exposed a critical gap – the lack of a sufficiently developed charging infrastructure. Owing to this, there is significant ‘charging anxiety’ in the market, if we can call it that. People are not as much worried about the range, as they are about reliable, safe charging.
The burgeoning popularity of electric vehicles (EVs) is encountering a significant roadblock: unreliable charging infrastructure. A substantial portion of EV owners experience the frustration of encountering malfunctioning or inoperable charging stations. Industry reports indicate that over 20% of charging attempts fail, with a staggering 72% of these failures attributable to charger issues.
This pervasive problem extends beyond mere inconvenience for users. It translates into a substantial financial burden. Estimates suggest that as much as $20 billion of the global $100 billion investment in EV charging infrastructure is currently rendered ineffective due to non-functional chargers.
Hello everyone and welcome back to the Cognixia podcast. What is CI?Continuous integration (CI) is a fundamental practice within the DevOps methodology. It emerged in the late 1990s as a response to the challenges of traditional software development, where infrequent and large code merges often led to integration issues and bugs. CI automates integrating code changes from developers into a central repository. Every time a developer commits their code, automated builds and tests are triggered, providing immediate feedback on the code's functionality and compatibility with the existing codebase.This continuous integration cycle offers significant benefits to both developers and users. Developers can identify and fix errors early in the development process, leading to faster bug resolution and a more stable codebase. Additionally, CI empowers developers with frequent feedback, allowing them to iterate and improve code quality more efficiently. Ultimately, CI translates to a smoother development process and a more reliable, bug-free final product for users. By enabling faster development cycles and early detection of issues, CI paves the way for quicker delivery of new features and functionalities to users.So, CI has been around for a while now. But then, so has DevOps.DevOps has been around for a while, yeah, but that's a good thing! Many of you haven't experienced the struggles of waterfall development or even know what tools like Visual Test were – that's awesome! While understanding different approaches can be helpful, focusing on the current tools that matter most is key.Today, we have entire DevOps stacks that streamline development, building, testing, and even deployment within an agile environment. These constantly evolve, with new features and capabilities emerging all the time.Remember how everyone used to talk about Application Release Orchestration (ARO)? That term faded away, right? You might even hear it again occasionally, sparking a "wait, is that coming back?" moment. Vendors come and go, products merge, and some disappear entirely. This is a sign of a healthy market – needs evolve, users mature, and better solutions emerge. Sure, having a product vanish can be frustrating, but the prevalence of open source in CI/CD helps soften the blow. As outdated tools fall by the wayside, newer, better options take their place, making the whole ecosystem stronger.Speaking of tools, let's talk about Jenkins. It's widely used, maybe a little too widely used. Usage seems to be dipping, and the developers are making improvements to address things that push organizations toward other solutions. The good thing about Jenkins is that it can do everything. But that is also part of the problem with Jenkins. While Jenkins was once a simpler tool, years of competition and evolving needs have turned it into a bit of a heavyweight. If you're working on a small project or a team using it solo with basic requirements, all you really need is something that gets a quality product out the door fast.
Hello everyone, and welcome back to the Cognixia podcast. how does ITIL 4 help you be a better leader?first, ITIL 4 enables you to have more holistic thinking. ITIL 4 moves away from siloed thinking and encourages leaders to consider the "Four Dimensions of Service Management." These dimensions - Organizations and People, Information and Technology, Partners and Suppliers, and Value Streams and Processes - help you see the big picture and make decisions that benefit the entire ecosystem.Second, ITIL 4 will help you lead with agility and adaptability. The IT landscape is constantly evolving. ITIL 4 emphasizes the importance of being flexible and responsive to change. As a leader, you can foster an agile environment where teams can quickly adapt to new technologies and market demands.Third, ITIL 4 facilitates and encourages collaboration. Gone are the days of the lone wolf leader. ITIL 4 highlights the importance of collaboration across teams and departments. By fostering a collaborative culture, you can leverage the diverse expertise within your organization and achieve better outcomes.Fouth, ITIL 4 emphasizes adopting a customer-centric approach and it inspires you to do the same. ITIL 4 focuses on the importance of aligning IT services with customer needs. As a leader, you can ensure your team focuses on delivering value to customers and meeting their expectations.What is a leader without the ability to innovate and invest in continuous improvement? Fifth, this is what ITIL 4 helps you achieve. ITIL 4 encourages a culture of continuous improvement. As a leader, you can create an environment where innovation is encouraged, and lessons learned are used to constantly improve processes and services.These are just some of the ways that the concepts and frameworks of ITIL 4 can help you be a better leader. When you get down to implementing it, the possibilities will be endless.
Hello everyone and welcome back to the Cognixia podcast!who is a data steward?The data steward role emerged in the early 2000s as organizations grappled with the explosion of digital information. As data became a strategic asset, concerns arose about its quality, security, and compliance with regulations. Enter the data steward: a champion tasked with overseeing the well-being of an organization's data assets.Popularity for this role soared with the rise of data governance initiatives and the implementation of stricter data privacy regulations like GDPR and CCPA. Data stewards became crucial in navigating the complexities of data management, ensuring data accuracy, accessibility, and responsible usage.Their responsibilities are multifaceted, encompassing everything from defining data ownership and access controls to managing data quality and ensuring adherence to data governance policies. They act as a bridge between technical and business teams, translating data needs into actionable plans and ensuring data is used effectively to drive informed decision-making.Data stewards play a critical role in ensuring the quality, security, and responsible use of data within an organization. Their work could revolve around multiple areas, such as:One, data governance and policy.Here, a data steward would be involved in defining and enforcing data governance policies, collaborating with stakeholders, monitoring compliance, etc.Two, data quality and management.The data steward could be actively working on defining data standards & formats, monitoring data quality, and ensuring proper documentation takes place for data origin, transformation, as well as usage to maintain traceability and accountability.Three, data security and access control.A data steward’s role would require defining and enforcing data access controls, implementing security measures, and staying updated on data privacy regulations like GDPR and CCPA, etc. They would work in tandem with other teams to ensure the right data security measures are implemented across the organization. Last and most importantly, communication and collaboration. Data stewards act as an important liaison between the technical and the business teams, acting as a bridge between the technical aspects of data management and the business needs of different departments. They are responsible for promoting data literacy in the organization. Their contributions play a critical role in enabling data-driven decision-making in the organization since they are responsible for translating data insights into actionable plans for various data functions.
Hello everybody and welcome back to the Cognixia podcast! An Azure Administrator would have subject matter expertise in implementing, managing, and monitoring an organization’s Microsoft Azure environment, including virtual networks, storage, compute, identity, security, and governance.
According to Microsoft, as an Azure Administrator, you often serve as a part of a larger team dedicated to implementing an organization’s cloud infrastructure. You also coordinate with other roles to deliver Azure networking, security, database, application development, and DevOps solutions.
An Azure administrator would also be well-versed in operating systems, networking, servers, and virtualization. Besides, they would also have vast experience with PowerShell, Azure CLI, the Azure portal, Azure Resource Manager templates, and Microsoft Entra ID.
With Microsoft Azure's continued growth in cloud computing, the role of a Microsoft Azure Administrator becomes ever more crucial. These individuals require a deep understanding of Azure's infrastructure, services, and management tools. This expertise allows them to effectively design, implement, monitor, and maintain cloud solutions that empower organizations around the world.
The heart of the Microsoft Azure Administrator role lies in navigating the intricacies of Azure's infrastructure. This includes gaining a thorough grasp of virtual machines, networking, storage, and security within the Azure environment. This translates to configuring virtual networks, implementing robust storage solutions, and fortifying defenses with firewalls, encryption, and access controls.
Azure isn't just about infrastructure - it's a dynamic ecosystem of services that address various business requirements. A skilled Azure Administrator effortlessly navigates services like Azure App Service for seamless web hosting, Azure SQL Database for efficient data management, and Azure Active Directory for streamlined identity and access management. This strategic use of services allows administrators to boost operational efficiency, improve scalability, and optimize resources for maximum performance.
Hello everybody and welcome to the Cognixia podcast!
what is a password manager?
Imagine your passwords as tiny secrets, each needing its own locked box. But juggling hundreds of boxes could be such a nightmare! That's where password managers come in - like a master safe for all your secrets, guarded by one super-strong password (your master password). Think of it as Fort Knox for your logins!
But it's not just storage. Password managers are like personal password chefs, whipping up unique, complex passwords that would make even the strongest hacker cry. Plus, they remember them all, so you don't have to. No more scrambling to recall that password you used once in 2012!
And the best part? They're like automatic door openers for your online accounts. Just tap your master password and boom, you're in! This not only saves you time but also protects you from sneaky malware trying to steal your keys.
Worried about losing your secrets if you switch devices? Don't sweat it! Good password managers keep your info synced across everything, from your phone to your laptop, so you're always covered.
So, ditch the mental juggling act and treat your online life to a password manager. It's like giving your digital self a security upgrade and a much-needed vacation from memorizing gibberish!
Now, there are different types of password managers in the market. There are cloud password managers and local password managers. There are different password managers designed for individuals, families, small businesses, and large enterprises. Ideally, organizations should steer clear from the consumer versions of password managers and instead, invest in enterprise-class tools that would offer greater security from an enterprise perspective for all privileged accounts, services, systems, applications, etc.
To understand cloud-based password management, imagine your passwords living rent-free in a super secure online apartment building. That's the cloud! Now, this comes with some pros and some cons. The pros are, one, it is a syncing heaven. You can access your passwords on any device, anywhere, seamlessly. No more scrambling to remember what password you used on your work laptop versus your phone. There is an option for easy disaster recovery. Lost your computer? No sweat! Your passwords are safely backed up in the cloud, ready to be accessed when you need them.
Hello everyone and welcome back to the Cognixia podcast. Emerging technologies hold immense potential and promise, but without a way to focus the right tech on the most pressing challenges, companies and the world at large cannot gain their full value. This is where deep tech comes in. Deep tech involves leveraging mature and emerging technologies to solve the largest problems facing the world today while enabling bold business objectives & invigorating value chains.
Deep tech stands for cutting-edge technologies that build on advanced science and engineering innovations to bring disruptive new products to the market. According to an MIT paper, “If innovation is the match between problems like customer needs or opportunities and solutions like technology, business models, etc. then deep tech is the part of the solutions space based on breakthrough science and engineering.
The term ‘deep tech’ was first coined by Swati Chaturvedi, the founder of Propel(X), the world’s first platform dedicated to angel investing in deep tech startups. When the term was coined, it was intended to categorize startups in the life sciences, energy, clean technology, computer sciences, materials, and chemical sectors. However, since then, the definition has evolved and will continue to evolve, it is a more dynamic concept, as is just about everything in tech.
Today, the deep tech space involves cutting-edge technologies like artificial intelligence, biotechnology, quantum computing, blockchain, and much more, more industries have come under its umbrella, including agriculture, aerospace, green energy, mobility, etc.
Hello everyone and welcome back to the Cognixia podcast. The renowned UK security think tank, the Royal United Services Institute has published new research detailing the possible effects of ransomware attacks on businesses and staff, society, the economy as well as national security. Interestingly, it also highlights an impact that not a lot of us usually consider when we talk about the cost and effects of ransomware – the impact on physical and mental health. In today’s episode, we talk about these hidden costs of ransomware attacks, so stay tuned.
Who is the Royal United Services Institute?
The Royal United Services Institute or RUSI is the world’s oldest and the UK’s leading defence and security think tank. Its mission is to inform, influence, and enhance the public debate on a safer and more stable world. It is a research-led institute, that produces independent, practical, and innovative analysis to address today’s complex challenges.
Ransomware incidents are a scourge in our society globally. A ransomware attack takes a visible toll on organizations, individuals, the economy, and even national security. But there are some intangible and not so easily visible impacts of ransomware attacks too. These include physical, financial, reputational, psychological, and social harms. Ransomware is a risk to everyone, whether you are an organization or an individual, whether you are a small startup or a gigantic corporation. The financial costs and losses resulting from a ransomware attack can threaten the entire existence of the organization. Besides, it damages the reputation of the individual or organization too, making them look unprofessional or incapable and exposing sensitive data to vulnerabilities and exploitation.
Hello everyone and welcome back to the Cognixia podcast. DevOps is giving way to DevSecOps, but the pace at which this is happening isn’t quite heartening to see. Another development in the space is Security-as-Code, which works in tandem with DevSecOps, and that is what we will be talking about in today’s episode.
While there is no doubt in any of our minds that security is an integral part of the software, we usually tend to leave it for the end of the SDLC, by which time it is already too late to handle such a critical aspect of the software. This will cause delays in your software development timelines. Since we are all conditioned to believe that security is a one-time thing, most times nobody bothered to automate the security testing, so you’re stuck with doing everything manually, which only takes so much more time than automated testing.
To change this scenario, experts suggest two critical steps. First, shift security to the left. Meaning, why should security be added as an afterthought? Why should security be incorporated after everything else is already completed? Instead, move security steps to the left, making it an integral part of the SDLC, and not a step to be taken after the SDLC is complete.
Second, invest in automation. Manual work is often very tedious, time-consuming, prone to errors, and risky. Instead, put in the effort to automate the security aspects and testing. Automate the process of defining policies, security test cases, etc., and save both time and resources, plus, no errors!
Hello everyone and welcome back to the Cognixia podcast. we visit two very popular terms of our times – Platform engineering and DevOps, and we will explore not just what they are but also, more importantly, how they are different from each other because we understand it can get a little confusing at times. In the fast-moving, modern software development and operations world, terms like DevOps, platform engineering, and Site Reliability Engineering are so commonly thrown around, sometimes even used interchangeably, that it can be hard to keep up and navigate these different domains smoothly. The distinction between these terms is quite nuanced and quite critical to understand, we believe. So that is what we will focus on in today’s episode.
In essence, platform engineering, DevOps, and site reliability engineering or SRE are related but they are distinct disciplines by themselves and do not mean the same thing. They all play varying roles in the development and operation of reliable and scalable software systems but they are quite different from each other. Let us first take a quick look at what each of these terms means.
To begin with, DevOps. DevOps is a cultural and collaborative approach to software development and IT operations with a focus on breaking the silos between the two functions while improving communication, collaboration, and efficiency. It is not a specific job role as such but more like a cultural philosophy for teams and organizations to follow. It revolves around the idea of encouraging developers to take on greater operational responsibilities and for operations teams to be more involved in the development process. It involves a lot of different tools and practices like CI/CD pipelines, automated testing, Infrastructure-as-Code, etc.
Hello everyone and welcome back to the Cognixia podcast. we talk about something we all use but don’t pay much attention to these days. At least not as much as we once used to. Today, we talk about anti-virus software. At one point in time, not so long ago, anti-virus software was very highly sought-after and the market was also flooded with pirated copies of popular software brands like McAfee, Norton, Kaspersky, AVG, Avira, etc. The entire process was also quite tedious, buy a CD, run it on your desktop or laptop, and it was all very time-consuming. Sometimes, the installation would fail and you would need to seek help. You knew that if you didn’t do this, the virus lurking everywhere – from the free song download websites to random forwarded emails or even the pen drives you used to share files with friends would strike, and you would need to format your entire system to clean it out, losing all your files and data on the system in the process. Then came mobile phones and with that came antivirus apps, install them on your phone to keep things safe. We have all at some point been annoyed with those apps because they wouldn’t let us uninstall the apps, or change the SIM cards, and it would be very frustrating at times. But in the interest of safety and security, we let it be. We looked for bundles and packages when we bought new phones so we could get a free subscription to the antivirus app with it. Back then, the thought of a rogue virus wreaking havoc on your pixelated screen sent shivers down your spine. Antivirus software was our knight in shining armor, diligently guarding our digital gates against those pesky malware invaders.Fast forward to 2024. Cloud computing, AI-powered devices, and hyper-connected ecosystems have revolutionized our digital realm. So, the question begs: are traditional antivirus software and apps still relevant in this ever-evolving landscape?The answer is a nuanced one. While the nature of threats has shifted, antivirus solutions haven't become obsolete. They've simply adapted and evolved alongside the changing security landscape.
Hello everyone and welcome back to the Cognixiapodcast.
According to the official Microsoft documentation, PowerShell is a cross-platform task automation solution made up of a command-line shell, a scripting language, and a configuration management framework. PowerShell runs on Windows, Linux, and MacOS. PowerShell is an object-oriented automation engine and scripting language with an interactive command-line shell developed by Microsoft. It aims to help users configure systems and automate administrative tasks. It is quite a mature tool and has a proven as well as established record as an automation tool for users both within and outside the IT function. Originally, PowerShell was offered as a proprietary software however, now PowerShell is available on all Windows systems by default. In 2016, Microsoft open-sourced PowerShell and made it available both on MacOS as well as Linux systems. So, what does PowerShell do?PowerShell was designed to help users with automating their tasks. For instance, if you are looking to automate your batch processing, PowerShell is the tool to help you with this. If you want to create system management tools for your commonly implemented processes, then PowerShell is the tool for you. Apart from this, PowerShell also serves as a replacement for Microsoft’s Command Prompt which goes back to the times of MS-DOS. PowerShell became the default command-line interface for Windows 10 with the build 14791, which is also how most of us today become acquainted with the PowerShell technology. With that, we can say that PowerShell is a modern command shell that includes the best features of many popular shells, however, unlike a lot of other shells which would only accept and return texts, PowerShell will accept and return .Net objects, making it so much more powerful and versatile compared to other shells.
Hello everyone and welcome back to the Cognixia podcast. we will talk about MongoDB and Amazon CodeWhisperer. Earlier in November 2023, MongoDB and Amazon Web Services made a groundbreaking announcement. MongoDB, Inc. and Amazon Web Servinces, Inc. announced that “The two companies are collaborating to optimize Amazon CodeWhisperer to provide enhanced suggestions for application development & modernization on MongoDB’s industry-leading developer data platform that millions of developers and tens of thousands of customers rely on every day for business-critical applications. Trained on billions of lines of Amazon and publicly available code, Amazon CodeWhisperer is an AI-powered coding companion from AWS that generates code suggestions based on natural-language comments or existing code in developers’ Integrated Development Environments or IDE.”“Working together with AWS, MongoDB provided curated training data for MongoDB use cases and took part in the evaluation of Amazon CodeWhisperer outputs throughout the training process to promote high-quality code suggestions. While Amazon CodeWhisperer already provided support for building applications on MongoDB, developers can now get enhanced suggestions that reflect best practices, allowing developers to ideate more quickly, rapidly prototype new features, as well as accelerate application development,” the Press Release continued.The developer landscape is buzzing with excitement around Generative AI coding companions like Amazon CodeWhisperer. These coding companions are unlocking new ways to work, freeing developers from routine tasks and letting them tackle truly challenging problems. CodeWhisperer already shines when working on common coding and AWS API tasks, and now, thanks to the collaboration with MongoDB, the combined capabilities would be extended to millions more developers who build with MongoDB.With Amazon CodeWhisperer coming into the hands of even more developers courtesy of this collaboration, they would be more empowered than ever before to tap into the transformative power of Generative AI. This isn't just about changing how users interact with apps; it is about changing how developers build them. The partnership between AWS and MongoDB to train Amazon CodeWhisperer on MongoDB is a major step in that direction, giving developers the boost they need to build faster and focus on higher-value tasks.
Welcome to the Cognixia podcast. Earlier in December 2023, the 2023 UN Climate Change Conference convened in Dubai, as part of which some very important meetings of the Conference of the Parties or COP 28 took place. These meetings strived to deliver a successful COP 28 that drives global transformation towards a low-emission and climate-resilient world, fostering ambitious climate change action, and facilitating implementation including related support. The Incoming Presidency announced that the focus of the COP 28 would be four major paradigm shifts:
One, fast-tracking the energy transition and slashing emissions before 2030
Two, transforming climate finance, by delivering on old promises and setting the framework for a new deal on finance
Three, putting nature, people, lives, and livelihoods at the heart of climate action, and
Four, mobilizing for the most inclusive COP ever
In the face of the dire situation we are in climate-wise, all measures are important, and everybody has a role to play. The world is potentially set to breach the 1.5C temperature increase threshold by 2027. 2023 saw some major climate change-driven disasters, such as the wildfires in Hawaii, the cloak of orange haze from the record Canadian fires, July becoming the hottest month on the planet since 1880, heat waves in February and the cyclonic activity at the beginning and end of monsoon in India, the worsening hold of El Niño. The world as a whole is under a lot of pressure to slash its carbon emissions to meet the net zero goals set for 2050.
The time to wake up and ensure sustainability measures are weaved into everything we do was yesterday and the world is waking up to this reality now. While all industries are gradually taking responsibility and driving change in their respective spaces, one sector that is undergoing rapid transformation to meet their sustainability goals and ensure that there is progress without compromising the future of the planet is the Technology space.
The tech industry is responsible for a very large carbon footprint, there is no denying that. The data centers, the coding that goes into keeping them working as well as all the code they handle daily, artificial intelligence, machine learning algorithms, wireless throughputs, etc. come with a very energy-intensive nature, and while they do wonders for changing the world around us for the better, they are not exactly sustainable or planet-friendly from an environmental impact perspective. Just the data centers, a large majority of which are in the United States, and the transmission networks account for about 3% of the global electricity consumption as well as about 3.5% of global greenhouse gas emissions. While these numbers might appear quite small, consider this – these numbers are roughly the same as those for the entire aviation industry. In fact, they are just slightly lesser than those for all the industries of the world that manufacture fertilizers, pharmaceuticals, refrigerants, and oil & gas extraction together, which hold about 3.6% of global carbon emissions. On this front, a Reimagining Futures Study by Ernst & Young finds that more than half the enterprises who participated in the study felt that emerging technologies could play a vital role in accelerating global sustainability.
Hello everyone and welcome back to the Cognixia podcast. Salesforce is an easy-to-use, simple-to-set-up, all-in-one CRM platform that helps you take your business to the next level. It offers a multitude of products under its umbrella for different sizes of businesses and different business needs. It is the world’s most trusted customer relationship management platform that can help an organization’s marketing, sales, commerce, service, as well as IT teams work as one irrespective of where in the world they are all located. Every tea, even every team member could be in different parts of the world and Salesforce would bring them together virtually to ensure operations take place seamlessly, without a hitch. It is used by over 150,000 companies, both big and small to manage and grow their businesses. If you browse their website, you will see how Salesforce helps businesses save up to 20 hours of work each week which can be used more productively in doing important tasks, it helps improve sales productivity by up to 29% while reducing support costs by up to 27%, and even reduces the customer acquisition costs for organizations by up to 27%. Salesforce, after all, is a cloud-based software designed to help businesses connect to their customers in a whole new way, so they can find more prospects, close more deals, and wow more customers with their amazing service. In the recently concluded Salesforce World Tour New York 2023 event, Salesforce announced expanded capabilities of its Generative AI assistant called Einstein Copilot as well as enhanced integration with Apple offerings. The Data Cloud Vector Database is being added to the Salesforce Data Cloud which would allow both the Salesforce Data Cloud as well as Einstein Copilot to handle large amounts of unstructured data. The Data Vector Cloud Database is expected to be a very major enhancement for the Salesforce Data Cloud and the pilot for the same is expected to be launched in February 2024. But what is this Data Vector Cloud Database? It is an integrated vector database support that enables a user to use a wide variety of data types. Using this, unstructured data like PDFs, emails, audio files, social media content, etc. can be combined with structured data such as purchase history, customer support cases, and product inventory. Salesforce also has a Generative AI assistant called Einstein Copilot. Einstein Copilot, once the pilot we just mentioned is launched, will be able to use unstructured data to respond to questions and perform analysis by accessing the data for the same through the Salesforce Data Cloud. Einstein Copilot is also expected to become available to users around February 2024.
Hello everybody and welcome back to the Cognixia podcast. If you remember the headlines from November last year, you will recall that ChatGPT became so popular that it broke all records held by any platforms and apps in the past and reached a mind-blowing one million users in just five days of its launch. This huge surge in user sign-ups was hailed as an undeniable testimony to the growing interest in large language models and as an indicator of the beginning of a new era powered by artificial intelligence. Countless reports of potential job losses and rampant unemployment triggered by AI circulated, while there were also plenty of reports highlighting how the world was going to change for the better thanks to artificial intelligence. From writing marketing copy to creating interesting blogs, generating social media captions writing scripts for videos, writing poetry and prose, ChatGPT has become very commonplace in generating content. It does come with limitations and obstacles, sure, but it does work as a great aid for anyone seeking some help to generate content, hashtags, etc. ChatGPT has also found a great place in the education space. In the past year, educators have used ChatGPT to craft personalized learning experiences for the learners, build interactive exercises, and send personalized feedback for the learners. Students are also leveraging the power of ChatGPT to help with their learning journeys and for self-directed learning and language acquisition. The advent of automation had already begun transforming customer service and user experience. ChatGPT only championed the potential of AI to transform this space further. In the past year, several businesses have adopted ChatGPT to improve how users interact with the brand and their customer service interactions. ChatGPT can answer common customer queries, resolve basic issues, provide 24/7 personalized support, and more without breaking the bank. The interactions can be so human-like that it can often be challenging to identify whether you spoke to an AI or a human! ChatGPT has also helped countless IT professionals – developers, QA testers, coders and programmers, engineers, project managers, and more to accomplish their tasks more efficiently – writing code, checking code, testing code, mapping resources, doing complex calculations, running test scenarios, etc. Some of these individuals were also the initial adopters of ChatGPT and have reaped amazing benefits from using the tool.
Hello everyone and welcome back to the Cognixia podcast. We talk about the recently released “The State of Developer Ecosystem 2023” Report by JetBrains. This report is a culmination of insights gathered from 26,348 developers from all around the globe. The world of developers is vast and diverse, making it an endlessly fascinating realm for exploration & learning. Through yearly research initiatives like this one, our goal is to explore this captivating world, uncover valuable insights about developers and their craft, and then share these facts with the community. The State of the Developer Ecosystem Report analyzes and presents valuable insights on a wide range of topics from programming languages, tools, and technologies to demographics and fun facts.
It also digs deeper into the lifestyle of developers, showcasing the current passions and hobbies among developers. The 2023 State of Developers Report also includes insights on artificial intelligence, a category that has been newly introduced to the Report. The Report showcases the features of AI that developers are commonly using, the challenges they face, and some insights into how the situation is around the adoption of AI-enhanced tools.
Now, this begs the question of who is doing the research for this and how is the research done. Well, the State of the Developer Ecosystem Report is a report brought out by JetBrains. JetBrains is a company that aims to make professional software development a more productive and enjoyable experience. JetBrains helps developers work faster by automating common, repetitive tasks to enable them to stay focused on code design & the big picture. For this, they provide tools to explore and familiarize with code bases faster. JetBrains’ products are designed to help developers take care of quality during all stages of development and spend less time on maintenance tasks.
Hello everyone and welcome back to the Cognixia podcast. When developing applications, one often needs to integrate third-party or open-source dependencies into the applications to meet the intended business requirement or utility. For instance, a food delivery app could be dependent on Google Maps or MapMyIndia for the Map functionality on which a user can track their food. An e-commerce app or website could have a dependency on WhatsApp for enabling a live chat with a customer service bot or a customer service rep to help answer any queries that the customer of the platform may have. These dependencies could be paid for by the using entity to the service/API provider or it could be open-source and play an important role in supporting the efficient functioning as well as any other features that the application might be providing.
The simple logic here was instead of building a whole functionality from scratch, which by no means is an easy feat since it takes looking for and hiring the right people with the right skills and domain knowledge, and a boatload of resources to put together a team, lots of time, and so much more. Instead, one could use the API or functionality built by someone else, something that is already tested and ready to use with established success, just integrate it into whatever you are building, and voila! The functionality creator could get a licensing fee or a royalty payment of sorts, and the user entity has a perfectly functioning feature that would be highly valuable for its users.
Sounds like a great thing, right? It totally is. Then where exactly is the problem?
Well, whenever great innovations have taken place, haven’t the unscrupulous elements always caught up with them sooner or later for their gains while penalizing or harming others in some way?
Dependencies are no exception. Enters Dependency Confusion Attack.
Dependency confusion attacks are relatively new to the world, but in the short time they have been around, they have sent ripples around the world showing the unimaginable levels of harm they can cause. So, who is at risk? How do these attacks function? Can we do something to stop it or fight it once it happens? We are sure you have many questions, and we will try our best to answer as many of these as possible in this podcast episode.
New research by OX Security, a DevOps software supply chain company has revealed that just about every application that has more than 1 billion users and more than 50% of applications with roughly 30 million users are highly vulnerable to dependency confusion attacks. The research also makes a shocking revelation – organizations that are at the most risk would likely have about a whopping 73% of their assets exposed to dependency confusion attacks!
Hello everyone and welcome back to the Cognixia podcast. we talk about something that has been in the news a lot this year and actually makes it to the news for all the undesirable reasons every year for quite some years now. Today, we talk about the AQI or the Air Quality Index. This year, Delhi became the World’s most polluted city in the world, with Mumbai and Kolkatta not far behind in the air quality index. Diwali time makes the air in these cities become absolutely unbreathable, with the rampant air pollution from bursting firecrackers, construction work, industrial pollution, burning the stubbles in farms, etc. and it is affecting the lives and health of everyone in and around these cities.
Air pollution levels in most of the urban areas are a cause of serious concern. It is the right of the people to know the quality of the air they are breathing. However, the data generated by the National Ambient Air Monitoring Network are reported in a form that may not be easily understood by common people. This system of air quality information was found inadequate to facilitate people’s participation in the air quality improvement efforts. With this in mind, the Central Pollution Control Board developed the Air Quality Index for Indian cities as a tool to disseminate information on air quality in qualitative terms, as well as its associated and likely impact on health. The Air Quality Index has six key objectives:
1.Resource allocation
2.Ranking of locations
3.Enforcement of standards
4.Trend analysis
5.Public information, and
6.Scientific research
Let us begin by first understanding what is the Air Quality Index. The Air Quality Index or AQI was introduced in 2015 and aimed at quantifying the severity of air pollution at a particular location. It is measured by recording the levels of multiple pollutants in the air. It is a single composite index that monitors eight important individual pollutants. These eight pollutants are PM10, PM2.5, nitrogen dioxide, sulfur dioxide, carbon monoxide, ground-level ozone, ammonia, and lead. These metrics are measured at different monitoring stations and the metric values are calculated using their average concentration values over a 24-hour span for all metrics except the carbon monoxide and the ground-level ozone metrics, which are measured over 8 hours. The health breakpoint concentration is also taken into consideration when calculating the AQI. Based on this, the worst sub-index value would be taken as the Air Quality Index for the location.
Hello everyone, and welcome back to the Cognixia podcast. we continue our conversation about Generative AI, this time with a focus on different job roles and how managers can use Generative AI to design better job roles for the organization as well as employees. Organizations do their best to improve employee engagement and keep employee turnover as minimal as possible. But, there is one key metric, or rather a very important attribute that often gets ignored or hasn’t been checked much so far employee burnout. Surveys conducted by Gallup in the United States in 2022 showed that 40% of the employees surveyed reported that the job hurt their mental health and around 30% have shared that they regularly face burnout. About 32% have said that they feel engaged at work while 17% have said that they were actively disengaged. On a global level, the employees’ lack of engagement has been estimated to cost employers roughly $7.8 trillion, which is equivalent to a whopping 11% of the global gross domestic product, according to a report in the MIT Sloan Management Review.
Experts opine that a lot of disengagement and work stress employees go through is rooted in how organizations design job roles for the employees. Decades of extensive research by experts have discovered that poor work design leads to negative employee outcomes – mental strain, high turnover, job dissatisfaction, decreased productivity, impaired learning, etc.
The MIT Sloan research goes on to highlight that quite often, the managers in organizations lack the understanding and insight to design high-quality jobs. With the recent advances in technology, this is a very critical area in which artificial intelligence can help organizations. It can help bridge the knowledge gap among managers and enable organizations to design high-quality work which would be a win-win situation for both the organization as well as the employees, current and potential. But before the managers are empowered to do this, they need to be well-versed in the pros and cons of using Generative AI for work design.
Hello everyone, and welcome back to the Cognixia podcast. The ICC Men’s Cricket World Cup is in full swing in India, packed with nail-biting action and some stellar performances by different cricketers and teams. For all of us at home, watching the matches on our televisions, laptops, tablets, and mobile phones, our match-viewing experience has been significantly enhanced in recent times. We can see the analytics and charts clearly on our screen, while chilling on our couches, munching on our favorite chips and dips. Like all sports, cricket has benefitted greatly by embracing technological advances. It has enhanced the experience not just for the players and viewers, but also for the umpires, commentators, coaches, selection committees, and a lot of other people. “Cricket fans across the world will be able to experience and engage with the game like never before through new digital activities, placing fans at the center of the ICC Men’s Cricket World Cup 2023,” says ICC on their website. ICC has shared that it is leveraging the ICC’s first-of-its-kind vertical feed coverage to create highlights tailored for hundreds of millions of fans that access the content on their mobile phones and will be available to access on the ICC app, website, and the ICC Meta channels. ICC is actively leveraging its WhatsApp and Instagram channels to share exclusive news and videos, enabling millions of fans worldwide to stay connected and up-to-date with what’s happening at the World Cup 2023. Exclusive content on both these channels includes match highlights, breaking team news, viral videos, etc.
Hello everyone and welcome back to the Cognixia podcast. To understand what large language models are, we first need to understand what transformer models are. As a human, we see the text as one word at a time and comprehend it accordingly, whereas machines see the text as just a bunch of characters. Machines were usually unable to interpret text like human beings can. However, this began changing when Vaswani et al published a paper establishing something called the transformer model. A transformer model is based on the attention mechanism, which enables the machine to read an entire sentence or even an entire paragraph instead of one character or one word at a time, and once the machine has consumed the entire input text, it will be capable of producing an output based on the input received. This enables the transformer model to understand the context of the input and deliver better outputs. These transformer models are the basis of many other models commonly used in machine learning and generative AI today. They process data by tokenizing the input and simultaneously conducting mathematical equations to.
Large Language Models are more advanced and complex versions of the transformer model in a way. A large language model is a deep learning algorithm that can perform a variety of natural language processing tasks. The large language models use transformer models and are trained using very, very large data sets. This is also why the models are called LARGE language models. Due to the wide training and powerful transformer models at the backbone, the large language models are equipped to recognize, translate, predict, or generate text or other content. From understanding protein structures to writing code, these large language models can be trained to do a very wide range of things. But how are transformer models and other machine learning models able to predict text? According to a very influential and interesting paper by Claude Shannon titled “Prediction and Entropy of Printed English”, the English language has an entropy of 2.1 bits per letter, despite having 27 letters, that is, 26 alphabets and 1 space, hence, 27. If these letters were used randomly, the entropy would be about 4.8 bits per letter, which would make it easier for machine learning models, especially the transformer models to predict what would come next in a human language text. The models keep repeating this process again and again, creating entire paragraphs, word by word, that we then receive as an output.
Also, how does the transformer model or the machine learning model comprehend and deal with grammar? The model sees grammar as a pattern of how different words are used in a sentence or a context. It would be challenging for anyone to list out all the rules of grammar and then teach them to a machine-learning model. Instead, the models are programmed to acquire these grammar rules implicitly using examples. When the transformer model is large enough, as is the case for large language models, the model can be trained to learn a lot more than just the grammar rules, learning to extend these ideas beyond just the examples it has been trained on.
Hello everyone, and welcome back to the Cognixia podcast. With the Search Generative Experience, Google is bringing the power of Generative AI to its search platform to offer its users new ways of finding, visualizing, and creating content. In a recent blog post, Google said, “Search has long been a place where you can find information to help with life’s questions – whether they are big or small. With advances in AI, we have continued to develop simpler and smarter ways to help you uncover useful insights & make sense of information. As we continue to experiment with bringing Generative AI capabilities into Search, we are testing new ways to get more done as you are searching – like creating an image that can bring an idea to life, or getting help on a written draft when you need a starting point.”So, what is the Search Generative Experience? On this, Google elaborates, “There are times when you might be looking for a specific image, but you can’t find exactly what you have in mind. Or maybe you have an idea that you need help visualizing. So beginning today, we are introducing the ability to create images with our Generative AI-powered Search Experience or SGE.”Simply put, Search Generative Experience or SGE enables Google users to generate AI images and text by entering a prompt into the Google Search bar. This is like how the popular Generative AI-powered text-to-image tools like Midjourney and DALL-E 2 function. This capability also rivals Microsoft’s Bing Chat powered by GPT-4. Users can opt-in for the SGE after which they will see an option to create the AI-generated images directly when using Google Images. The model, however, is currently in its trial phase. The function is currently only rolled out in the United States for users aged 18 and above.
Hello everyone and welcome back to the Cognixia podcast. Twenty years ago, Dan Brown published his world-renowned book – the Da Vinci Code. Three years later, a film adapted from it with the same title starring Tom Hanks was released worldwide. The book and the movie both, were super interesting, and make for a great read and a great watch even today. The story takes the viewers and readers through the Louvre in Paris, stars the Mona Lisa and The Last Supper, and so many other renowned paintings, all on a quest for the Holy Grail. If you paid attention to the book or the movie or both, you would have encountered a sequence of numbers mentioned in the plot that was essential to decoding a clue that Professor Langdon is working on with Sophie. This sequence of numbers is usually written in a triangle form and is called the Fibonacci Sequence.
If you are thoroughly lost, let us explain a little more. First, what is the Fibonacci sequence?
The Fibonacci Sequence was first discussed in Europe by Leonardo of Pisa, whose nickname was Fibonacci in the early 13th century. However, the origin or the first mentions of the sequence can be traced back to about 2000 BCE in Indian literature. There is an enormous amount of literature about and using the sequence today, and it has connections to multiple branches of mathematics.
In the Fibonacci sequence, every number is the sum of the preceding two numbers, so the sequence goes 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, and so on. It is a fantastic example of a second-order linear recurrence relation.
Now, why is this Fibonacci sequence important? The Fibonacci sequence is a sort of nature’s secret code. The number of petals in a flower, the seed heads of a flower, countless paintings, plant spirals, pinecones, hurricanes, spiral galaxies in space, and so much more are examples of the Fibonacci sequence. The ratio, shapes, and arrangements formed by the Fibonacci numbers are everywhere – growth patterns of plants, arrangements of leaves, sections of your fingers, spiral shapes of sea shells, how your eye sees things, everywhere!
So, why is this Fibonacci sequence important in Scrum? What can it be used for there?
Scrum teams use the Fibonacci numbers to understand the scope and size of their product backlog items. Here, size is not just a measure of how many people are involved or how long it will take to complete the task. The size of a product backlog item involves two major components:1.Scope2.ComplexityAgile teams will usually not use size as an indicator of the time, the size of a product backlog item cannot be say, one day. Time is never a good indicator for estimating the size and complexity of a work item. A senior team member could finish a task in say 2 days, while a junior team member or a new team member may take 4 days. This wouldn’t be an accurate representation of size then. The size of a product backlog item should give a shared idea of the scope as well as the complexity of the work, not individual time estimates.
Developers on the scrum would regularly discuss which items to bring into the sprint. When these discussions happen, size is an essential aspect to consider so that different stakeholders get a precise idea of what to expect. So, how does one describe the relative sizes between the different product backlog items? This is where the Fibonacci sequence does the magic.
Hello everyone and welcome back to the Cognixia podcast. The important aspects of project management, that is, conflict management. A project runs on the back of the efforts of its people. These people come from different backgrounds, different teams, different disciplines, and different ideologies, and are required to work together for the success of the project. Often, these people may have never worked together before. To top it off, the project works within the defined constraints of resources, time, and scope. This makes the environment quite conducive for conflicts to arise. Since the project manager leads all the teams and is responsible for ensuring everything runs smoothly, it becomes an important part of their job to address any conflicts that might arise and to resolve them at the earliest in the best possible manner. To equip the project manager with the right tools, the Project Management Body of Knowledge Guide, or the PMBOK Guide for short, recommends some effective strategies and techniques. Conflict management is one of the disciplines covered by the PMBOK Guide and is an important part of the certification exam outline for the Project Management Professional certification by the Project Management Institute. As you must already know, the latest edition of the PMBOK Guide is the 7th edition of this guide. The PMBOK Guide is a flagship publication of the Project Management Institute. The PMBOK Guide – 7th edition, according to the Project Management Institute, “adapts to the changes in the industry and helps you achieve your goals effectively, no matter what they are.”Integrating different disciplines and a diverse range of skills is imperative for the success of a project. Conflicts will always arise; we have slowly understood that. However, the existence of conflict doesn’t have to always be detrimental to the project or the organization. If managed and resolved effectively, conflicts can be beneficial for the project and the organization too. The project manager would undoubtedly play a key role in diffusing such situations while ensuring everyone and everything is on track and there is no adverse impact on the performance of the team or the outcomes of the project.What is a conflict? Anytime there is a difference of perception, opinion, or belief among two or more people, it is a conflict. Simply put, when people disagree, it usually is or leads to a conflict. In a project management situation, the project manager is responsible for creating a culture of harmony and collaboration. Conflict is natural and inevitable when there are multiple people with such diverse backgrounds, opinions, ideas, and realities, come together to collaborate. However, research has increasingly shown that when conflict is effectively managed, it can lead to better performance and more positive outcomes. Gone are the days when conflicts were a bane and a nightmare for any organization. In today’s world, little or no conflict means, little or no innovation, little or no change, and little to no room for improvement for the organization. Now, no organization would want that, would they?
Hello everyone, and welcome back to the Cognixia podcast. First, let us understand what bioengineering is. Bioengineering is the application of the principles and design concepts of engineering to the study & manipulation of biological systems and the development of biological products. It is a broad field of study that includes a very wide range of disciplines from biomedical engineering to agricultural engineering and bioprocess engineering to environmental engineering. Bioengineering is a rapidly advancing field with varied applications. Bioengineering professionals are playing a crucial role in improving human health and well-being for mankind globally.
Innovations in bioengineering, like most fields of science and technology, are driven by academia, often through the startup route. We are seeing more and more companies and startups come up in the bioengineering space, pushing the biomedical world to be more innovative and creative than ever before. The market is huge. According to McKinsey Research, apart from the transformational benefits to human health & well-being as well as a more sustainably managed environment, just about 400 bioengineering use cases, almost all of which are scientifically feasible, could have an economic impact of approximately $2 trillion to $4 trillion per annum from 2030 to 2040.
As technologies evolve, the pace of innovation in bioengineering is also accelerating. According to SynBioBeta – a professional network for biological engineers, investment in synthetic biology companies raised about $4.6 billion in the first quarter of 2021 alone! This is more than four times the investment in the same quarter a year earlier.
Hello everyone and welcome back to the Cognixia podcast. This week, we talk about something that the entire nation came together to celebrate – the Chandrayaan-3. Chandrayaan-3 is the Indian lunar exploration mission under the Indian Space Research Organization’s Chandrayaan program. The Chandrayaan-3 had a lander named Vikram and a rover named Pragyan, very similar to the previous edition of the Chandrayaan, Chandrayaan-2. The Chandrayaan-3 was launched on 14 July 2023 and it entered the lunar orbit on 5 August. On 23 August, the lander touched down on the South Pole of the moon, making India the fourth country to successfully land on the moon after Russia, USA, and China, and the first-ever country to land on the South Pole of the moon.
One technology that has played an important role in the success of this mission is artificial intelligence. Chandrayaan-3 has been able to greatly improve its planning, navigation, data analysis, and overall operational efficiency, thanks to artificial intelligence. Let us look at the information we could find on how artificial intelligence has contributed to the success of Chandrayaan-3.
A lot of algorithms are run to design and develop a space exploration mission vehicle. The Chandrayaan-3 is no exception. Artificial intelligence played a crucial role in developing the algorithms and then designing as well as developing the Vikram lander, the Pragyan rover, and the entire Chandrayaan-3. The design for the Chandrayaan-3 was optimized for weight, performance, and safety with the help of algorithms powered by artificial intelligence too.
Hello everyone and welcome back to the Cognixia podcast. what is data hoarding. Data hoarding is the excessive collection and retention of data. It is also sometimes referred to as digital hoarding. It is a growing challenge in the tech space. Countless organizations have a field time keeping on purchasing more and more storage space to accommodate the growing amount of data. Not just structured data but unstructured data is also growing enormously, necessitating increasing amounts of precious storage space. This is also leading to a major problem of disconnected data silos. Just as hoarding things in real life can be a problem, and mind you, Marie Kondo wrote a whole book about dealing with this, hoarding in the digital world is also a problem. This commonly happens when organizations tend to save data, maybe out of habit, out of the fear of losing it, out of hope that it will be useful someday, or even simply because they didn’t know any better.
A new study has found that 47% of consumers would stop buying from a company that fails to control how much unnecessary or unwanted data it is storing. Compare this to the fact that in this environment, 60% of Gen Z consumers have online accounts that they no longer use, and about 69% have never tried to close these unused accounts. This was found in a study conducted by Veritas Technologies. Useless data about these accounts lies unused in data centers, which keep using up electricity and resources. Experts opine that such useless data could account for roughly 2% of all global carbon emissions. 2% may not sound like a lot but to put this in perspective, take this – this size of the carbon footprint is the same size of the entire airline industry put together, the entire global aviation industry together! Now does that feel huge? Data centers around the world run 24 by 7 and by 2030, they are expected to be using up about 8% of all electricity that gets produced on the planet.
In the middle of that is the fact that most consumers are absolutely unaware of the impact of their own carbon footprint. 44% of the consumers surveyed said that it was wrong for businesses to waste energy and cause pollution by storing unnecessary information online. However, 51% also believe that electronic versions of their account-related statements and other documents stored online do not have any negative environmental impact. The Veritas study also found that 49% of the consumers surveyed thought that it was the responsibility of the organizations that store this data to delete it when it is no longer required or useful.
There is a slightly older study, conducted again, by Veritas Research, which found that about 35% of the enterprise data is dark. Dark data means that the data has an unknown value. It also found that about 50% of the data stored by organizations is redundant, obsolete, or trivial. A good move in this direction is that a lot of companies are now including the environmental impact of their data storage in their corporate environmental, social, and governance reports.
According to a report by the IDC, about 60% of the storage budget is not really spent on storage. Instead, it is spent on secondary copies of data for data protection, such as backups, backup software licenses, replication, and disaster recovery. It also found that about one-third of IT organizations are spending most of their IT storage on this secondary data. This makes it important for organizations to define cold data storage strategies and work on establishing unstructured data management policies. The risk of not identifying and eliminating unnecessary data, basically the risk of not stopping data hoarding is too huge to ignore any longer.
welcome back to the Cognixia podcast. What is digital trust. According to the World Economic Forum, digital trust is an individual’s expectation that digital technologies and services, as well as the organizations that provide them, would protect the interests of the stakeholders, and do their bit to uphold societal expectations & values. Now, we agree, that that is a very heavy definition. Let us try to break it down and simplify it a little bit. According to TechTarget, digital trust is the confidence the users have in the ability of the people, technologies, and processes to create a secure digital world. Now that’s much simpler and easier to comprehend, isn’t it? So, by extension, when an individual or a business decides to use another individual or business’ digital products or services, they confirm that they have digital trust in the business. Why is it important for businesses? Well, the more digital trust a business receives, the more users it is likely to gain, and the more robust would be its top-line numbers. We all understand the importance of online data security at the current time. Protecting digital privacy and safeguarding the users as well as the businesses against cybercrime is indispensable. This necessitates state-of-the-art trust technology that can keep everyone safe and ensure that the valuable digital trust does not break. According to a recent report by the IDC, with digital trust emerging as a paramount concern for organizations and consumers, business leaders and technology suppliers must expand their understanding of trust and its importance to success in the new digital economy. Customers increasingly want to know the companies that they are doing business with or whose products and services they are using, are authentic and worth the trust they are putting in them. Businesses also need to constantly be on their toes to demonstrate their digital trustworthiness and authenticity in business, and one of the most important means to do that is by relying on the best-in-class digital trust technologies.
Hello everyone, and welcome back to the Cognixia podcast.
Google has reported that it will leverage artificial intelligence for several online safety features and share insights with users about whether the information they are seeing could have been posted on the dark web. Google made this announcement at the Google I/O Conference. What are these new features and how are they going to use artificial intelligence? Let’s take a deeper look into this.
- The first measure revolves around image searches. Google Image Search will begin flagging AI-generated content.
- Secondly, Google also plans to enhance its safe browsing features by leveraging artificial intelligence to scan dangerous websites and files.
- Thirdly, if you are a Google One subscriber, you can now also run dark web reports to check if your personal information is listed in any attacker’s target lists
- Google is enhancing its spam filtering as well as Google Maps security capabilities. These features are not exactly getting an artificial intelligence boost,
- One of the major developments in this regard from Google is also the integration of the PaLM 2 Large Language Model, which will help make its key products and services much simpler and smarter. PaLM 2 is short for Pathways Language Model
Hello everyone and welcome back to the Cognixia podcast. we are going to talk about a new programming language that is becoming incredibly popular among AI developers, the language is a perfect fit for working with artificial intelligence, it is very simple and user-friendly like Python, and it is as quick as Rust, and has the performance and control like C++. Now, let’s take a second to just appreciate how awesome that is! This is the Mojo language. Mojo achieves high performance through innovative compiler technologies like integrated caching, multi-threading, cloud distribution, etc. It also includes auto-tuning and meta-programming which enables code optimization for various hardware. Let us look at some of the key features of the Mojo language:First, Mojo has a Python-like syntax and dynamic typing ability which makes the Mojo language very easy to learn if you are already familiar with Python. When you are working with modern developments in artificial intelligence and machine learning, then knowing Python is inevitable and with those skills, you can easily work with Mojo too.Second, you can import and use any of the Python libraries in Mojo, easily. Mojo has complete interoperability with Python, so you won’t have to keep wondering how easy your task would be if only you had access to the matplotlib library, just import it into Mojo and get working!Third, Mojo follows a very easy unified programming model that is super beginner-friendly and highly scalable for a wide range of use cases based on accelerators. It accomplishes this by combining dynamic and systems language capabilities. Fourth, the Mojo compiler applies advanced optimizations and GPU/TPU code generation, thereby supporting both Just-in-Time compilation as well as Ahead-of-Time compilation. Fifth, there are zero cost abstractions, so you can take control of the storage by inline-allocating values into the structures. Sixth, Mojo offers language-integrated auto-tuning, which enables you to automatically find the best values for your parameters to make the most of your target hardware. Seventh, you can very easily extend your models with pre- as well as post-processing operations, and you can even replace the operations with custom operations, taking full advantage of kernel fusion, graph rewrites, shape functions, etc.Finally, the Mojo language gives the user full control over the memory layout, concurrency, and other low-level details.
If you have been keeping up with the news recently, then you would surely have heard about how OpenAI, the company that created the world-famous generative AI tool – ChatGPT is on the verge of bankruptcy and how it is burning cash every day to keep the tool going. And, if you didn’t know that already, now you do. According to a report by Analytics India Magazine, OpenAI might go bankrupt by the end of 2024. The report adds that ChatGPT, one of OpenAI’s most important and most popular products is losing popularity and it is costing the company about $700,000 every single day to maintain ChatGPT. We would also like to refresh our listeners’ memories that Microsoft is OpenAI’s single biggest investor, having invested $10 billion in OpenAI. The competition in the Generative AI tools market is seriously heating up and the newest kid on the block, Llama 2, which is a partnership between Meta and Microsoft is the latest competitor for ChatGPT. But Microsoft has already integrated GPT into its products like Bing Chat and Windows Copilot. It also very recently released the Azure ChatGPT as part of its Azure cloud universe.
This brings us to the question that we seek to address in today’s episode – Is ChatGPT losing traffic and users, and is its popularity waning? Well, factually speaking, for the first time it was launched in November last year, ChatGPT has seen a decline in website visits, which in a way does point towards a supposed decline in the popularity of AI chatbots and AI-powered image generators. According to SimilarWeb, the global desktop and mobile traffic to the ChatGPT website has witnessed a decline of 9.7% in June, as compared to the numbers for May. The number of unique visitors to the ChatGPT website has also declined by about 5.7%. Along the same line, the amount of time the users are spending on the ChatGPT website has also gone down by about 8.5%.
One thing we can say for sure is that the Generative AI tools market is heating up and getting very interesting. We are all watching it closely to see how things will pan out.
With that, we come to the end of this episode of the Cognixia podcast. We hope you enjoyed listening to us today and learned something new during this episode. If you would like to recommend any topics to us or have any questions, feel free to reach out to us, we would love to hear from you.
we talk about something that has now become more than a menace and is threatening both individuals as well as enterprises. At some point, we are sure you have heard about this technology, maybe in the newspapers, online portals, or your Google Discover feed. We are talking about ‘Deepfakes’. These deepfakes are becoming a huge threat to everyone. In this episode, we will cover what are deepfakes, and how they are posing a threat to enterprises.
So, first, let us understand what are deepfakes. If you have come across the video that went viral in which Barack Obama called Donald Trump some expletives or Mark Zuckerberg announced that he had complete, total control of billions of people’s stolen data or even the one where popular Game of Thrones character, Jon Snow, delivers a moving apology for the dismal ending of the otherwise very famous show? If you have, then you have encountered a deepfake. In a way, deepfakes are the 21st-century version of Photoshop. Remember those times when pictures could be doctored easily using Photoshop and anybody could be inserted into any backdrop, doing anything in pictures? Deepfakes are an unscrupulous menace along the same lines. Deepfakes are fake pictures or videos or even audio generated using a form of artificial intelligence called deep learning, hence the name – deep fake. If you want to dance like a pro or just star in your favorite movie with all your favorite stars, you could make a deep fake and be a part of the next Christopher Nolan masterpiece!
Deepfakes are not going away anytime soon, they would continue to threaten individuals and enterprises. Organizations need to pull up their socks and stay proactive to safeguard themselves against such deepfake attacks. Get your workforce upskilled to top-notch cybersecurity skills, and invest in building a strong, responsible, and resilient brand. The rest of the story is for time and fate to tell.
Do check out our website, www.cognixia.com to learn more about our live online instructor-led cybersecurity courses.
The ITIL 4 certifications required to be updated only when a new update to the ITIL library was released. For instance, anybody with the ITIL v3 certification was required to take an ITIL 4 Managing Professionals exam after a short re-training to upgrade their credentials to ITIL 4. This way, once the library was updated, one could transition to the latest update to keep their credentials current. However, from January 2023, all ITIL 4 certifications would be issued with a renew-by date that would be three years from the award date. Any certification holders who do not renew their certifications within three years of the award date will still be a part of the Successful Candidates Register but a note will be added to their record to indicate that their certification is not aligned with the current certification requirements.
So, if you are someone who has pursued their ITIL certification in 2023, or are planning to pursue it in the future, your certification comes with a renew-by date which would be exactly three years from the award date of the certification. But what if you already had an ITIL 4 certification, something you earned already before 2023? In that case, this is what you can do:
If you were certified before 30 June 2020, you have until 1 June 2023 to choose to renew your ITIL 4 certification, irrespective of when the certification was issued. If you were certified after June 2020, you will have the option of renewing your certificate within three years of the original award date.
If you are wondering how you can find out what your renew-by date is, allow us to help. You need to log into your PeopleCert account to get all the information about your ITIL 4 certification.
The Scrum Product Owner is a stakeholder with a deep understanding of the product as well as the market. A Scrum Product Owner is responsible for the product backlog. A product backlog is a list of features and requirements for the product. The Scrum Product Owner ensures the product backlog is complete, accurate, and appropriately prioritized. Their role also involves working with the development teams to ensure that the items in the product backlog are delivered appropriately to meet user and customer needs.
Scrum Product Owners need to have a solid understanding of the users, the marketplace, the competitors, and even the trends. According to the Scrum Guide, the Scrum Product Owner is responsible for the value of the product resulting from the work of the development team. The Scrum Product Owner also actively works on prioritizing the work during sprint planning meetings while also motivating the team with well-defined goals, responding to any questions anybody in or outside the team might have, etc.
a Scrum Product Owner is someone who makes the final decisions about the features that will be offered by a product. They need to be very good business analysts. They need to have a very strong understanding of the business strategy and objectives. They are the ones who keep the development teams in line with the company’s vision and business. Additionally, and very importantly, they must be excellent communicators. They must be constantly communicating with internal and external stakeholders, as well as with the team members, so they can’t afford to have a communication gap or any drop in communications. Apart from this, a good Scrum Product Owner would need to have some other important skills. Now, we know we’ve said the word important enough times, and you might be wondering how come everything is important, but well, it is true. A Scrum Product Owner must be good at multiple things, and all of that we mentioned are important.
if you are beginning to wonder how the role of a Scrum Product Owner is different from the role of a Scrum Master, fret not, we are going to answer that too.
While both Scrum Master and Scrum Product Owners play very important roles in an Agile environment. However, they work together closely. The Scrum Master is the leader of the Agile team and they support the Scrum Product Owner by sharing updates with team members and employees. In contrast, the Scrum Product Owner manages the product backlog while ensuring the company derives maximum value from the product.
Hello everyone, and welcome back to the Cognixia podcast. We are back with another interesting episode today. Every week, we get together to discuss a new topic from the world of emerging digital technologies – from new developments to hands-on guides, from things you should know to what you can do to embrace new tools and best practices, and so much more.
Did you know that in 2022, the world spent over $150 billion worldwide to stop or fight hackers, without seeing all that much success? The Russian government continues its cyberattacks against Ukraine, ransomware attacks are at an all-time high, especially against hospitals and schools, or even entire governments, crypto hacks continue, and they are getting increasingly expensive, the hackers are getting younger and the hacked are becoming increasingly high-profile.
So, what can we expect in the world of cybersecurity in the coming time?
Remember the cyberattack on ViaSat in Ukraine last year? ViaSat is a US satellite communications company, whose services were being used by civilians as well as troops in Ukraine. The cyberattack on ViaSat caused a major communications breakdown at the start of the Russia-Ukraine war. Since then, there have been countless cyberattacks involving a variety of wiper malware, malicious computer code, and much more. This does account for and in a way contributes to cyber warfare. Cases of cyberespionage are also on the rise and will continue to be so.
While we are on this topic, did you know the difference between cyber warfare and cyber espionage? Let us tell you that.
The biggest difference between cyber warfare and cyber espionage lies in their primary goal. The primary goal of cyber warfare is to disrupt the activities of a country or state or territory. In contrast, the primary goal of cyber espionage is for the attacker to remain hidden for as long as possible and gather maximum possible intelligence. While the former is all about disruption and an outright attack, the latter is more about stealing information and valuable secrets.
This week, we talk about a very interesting topic in a space that is becoming increasingly popular all around the world – no code. ‘No code’ is a software development approach that requires the user to have little to no programming skills or experience to build an application. Using no-code tools, line of business employees who have the essential domain knowledge and institutional knowledge, while having a thorough understanding of the requirements for an app, but do not possess any coding or programming knowledge and skills, can easily create an application or a website or even add functionalities to existing applications and websites.
Interestingly, no code development is a misnomer of sorts. No code development does require coding, a lot of it. However, all this coding takes place behind the scenes and is invisible to the end-users who use these platforms to carry out their development tasks. Like its cousin – low code development, no code uses a visual integrated development environment. A visual integrated development environment is a software suite that consolidates the basic tools that are required to write and test the software. Commonly, these tools use a model-driven development approach which uses a software model to map out how the software system should work before the actual coding process begins. Once the requisite software has been created, the testing can be carried out using Model-based Testing or MBT, after which, it can be deployed.
The NoCodeFounders community. NoCodeFounders is the world’s largest no-code community with 17,837 founders and businesses using no-code tools to build and grow their businesses faster and cheaper. The community comprises founders, freelancers, agencies, marketers, product people, intrapreneurs, developers, makers, and no-code enthusiasts who choose to use no-code tools for building their businesses and projects. Emmanuel Straschnov, the CEO of .bubble says about NoCodeFounders, “NCF is one of the best founders communities out there. NCF has brought together high-caliber, collaborative, and engaged founders building great businesses with no code.
Buildcamp is a community of no-coders who are working together to build amazing new products. Through the Buildcamp community, you could meet people anywhere in the world who are facing similar challenges as you and learn in an interactive manner on the platform. Joining the community is free for everyone. The community offers useful tutorials and mini-courses, helping members learn how to build apps using top tools like Bubble and more. You can avail a premium membership for a small monthly fee and access the premium mini-courses as well as exclusive deals.
With that, we come to the end of this week’s episode of the Cognixia podcast. Hope you found it useful and insightful.
DDoS stands for Distributed Denial-of-Service. A DDoS attack is a malicious attempt to disrupt the normal traffic of a targeted server, service, or network by overwhelming the target and/or its surrounding infrastructure with a flood of internet traffic. DDoS attacks rely on multiple compromised computer systems for their effectiveness and the sources of their attack traffic. DDoS attacks compromise not just computer systems but also connected devices as well as IoT setups. To understand this better, imagine a traffic jam on a national highway that is clogging up the whole traffic to and from two points that the highway connects, thereby preventing anybody from going from city A to city B and from city B to city A. This is what a DDoS attack does to the system, preventing normal functioning by clogging up the system.
So, how does a DDoS attack function?
To operate and function, DDoS functions require machines connected to the internet, basically, a network of internet-connected devices, including computer systems as well as connected devices. Once the network is infected with malware, the devices in the network can now be remotely controlled by the attack. The individual devices are then called bots or sometimes even called zombies, while the group of devices is called the botnet.
So, once the network is infected, it becomes a botnet. Once the botnet is established, the attacker can carry out the attack further. This is usually done by sending instructions remotely to every bot in the botnet.
The botnet can then target a potential victim’s server or network. To attack the victim’s server or network, every bot is made to send requests to the victim’s IP addresses. This would cause the victim’s server or network to be overwhelmed. This would clog the system completely, resulting in denial-of-service to the regular, normal traffic.
We hope you enjoyed listening to it and learned something new from it. We promise to come back next week with another new, exciting episode of the Cognixia podcast.
about how Netflix uses AWS to provide a seamless global service to its users around the world. Like most global businesses today, cloud computing is integral for Netflix to function. Netflix uses a wide range of AWS services to provide a seamless service to its users around the world. This includes Amazon Elastic Cloud Compute, Amazon Simple Storage Service, Amazon CloudFront, Amazon Rekognition, Amazon Kinesis, AWS Lambda, AWS Auto Scaling, and many more.
Did you know that Netflix began as a mail-based DVD rental business on 29 August 1997? Since then, Netflix has evolved greatly and has become a streaming giant.
Amazon Elastic Compute Cloud, popularly referred to as Amazon EC2. EC2 offers the broadest and deepest compute platform, with over 600 instances and a choice of the latest processor, storage, networking, operating system, and purchase model to help meet the requirements of the user’s workloads. Amazon EC2 provides virtual machines that Netflix uses to run its streaming applications. Since, EC2 is highly scalable, thus enabling Netflix can easily add or remove servers as required to meet changing demands.
Next, let us look at Amazon Simple Storage Service, popularly referred to as Amazon S3. Amazon S3 is an objective storage service offering industry-leading scalability, data availability, security, and performance. Using S3, users can store and protect any amount of data for just about any use case – from data lakes to cloud-native applications, and even mobile applications. S3 offers cost-effective storage classes, easy-to-use management features, cost optimization, data organization, access-control configurations, etc. based on user requirements. Amazon S3 provides object storage for Netflix to store its content on the cloud. S3 is highly durable and available, enabling Netflix to offer content to its users reliably anytime, anywhere.
These are some of the top ways in which Netflix uses the amazing features offered by AWS to offer a seamless, personalized, desirable experience to its users. I am sure, you now have a slightly better idea of how Netflix is so popular and how AWS supports Netflix in its great functioning.
we come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us today as much as we enjoyed creating & recording this episode
we talk about something that becomes quite a topic of conversation at this time of the year, each year - weather forecasts. Come monsoon, most of us keep a keen eye on the weather forecasts to get some idea of when it will rain and plan our trips, commutes, etc. If we are stuck at work and it starts raining badly, we check the weather forecast to see if the rains are going to stop anytime soon then we can leave a bit later and go home safely. The cyclone season in the country starts before and ends after the monsoon, so we also keep an eye on those forecasts. From the days when we would all be glued to the television to watch the weather bulletin that came on about twice a day, with the presenter announcing the maximum and minimum temperatures recorded in the different capital cities of the states of India to today when we have weather forecast widgets on our phones, tablets, laptops, desktops, smartwatches, etc. weather forecasts have truly come a very long way.
Two main things where technology can be very useful. The first would be to improve the accuracy of the weather forecasts, and the second would be to make the forecast data comprehensible and accessible to stakeholders in different domains. Suppose you are a non-profit organization that works in the disaster relief space, like say you are a part of a disaster-relief team at the Red Cross. You usually need about a month’s lead time to arrange supplies and relief measures for say a flood. Now, if you get the right information in the month of April that there is going to be a major flood and cyclone on the eastern coast in the Odisha – Andhra Pradesh belt in May, you could get your team together, make the necessary arrangements, work with the government to evacuate the people and get them to safer places, the assets can be safeguarded wherever possible, and accomplish a lot more before the cyclone and flood actually hit in a month. Currently, you don’t get information that much in advance, and we also don’t have an accurate idea of where the cyclone will hit, will it fizzle out or get stronger, etc. There are reasonable probabilities involved in every forecast too.
We go back to something that has been a very happening topic for quite some time now - Generative AI bots. To be more specific, as the title would have already told you by now, in today’s episode we compare two of the most popular generative AI bots in the world right now – OpenAI’s ChatGPT and Google Bard. Both are interactive conversational smart chatbots powered by principles of artificial intelligence, from two of the major tech houses on the planet. Both come with their unique pros and cons.
what is ChatGPT?
ChatGPT is an artificial intelligence-powered chatbot by OpenAI that is empowered to have a conversation by generating human-like responses to textual inputs provided by users. ChatGPT has been trained on humongous amounts of data using a large language model.
what is Google Bard?
Like ChatGPT, Google Bard is another AI-powered chatbot. Like ChatGPT, Google Bard can also answer questions and generate text in response to user prompts.
This is as simple as we could explain this, but if you go just by this, then you might feel they are the same thing, just different companies. Well, in a way, it wouldn’t be quite wrong either. But there are quite a few differences too.
The very first point we would like to highlight is the pricing. The basic version of ChatGPT is free for users. However, it has a daily limit of 100 questions, meaning you can ask up to 100 questions to ChatGPT a day for free if you are using the free basic version. However, you can upgrade to the premium version for $20 a month, which would give you faster response times, and open access to many premium features. This is because premium users use GPT-4 which is the latest, more updated, and premium version, whereas free users use GPT-3.5, which is the previous version of the model. If you do not have an existing contract with OpenAI, then you would need to join the waitlist for the ChatGPT API to get access to the same.
Both ChatGPT and Google Bard are chatbots powered by artificial intelligence that has been trained on large natural language models, so their responses could also be similar. Ask the same question to ChatGPT and Google Bard, and you will get quite a similar response from both, except if you ask something that is more time-specific or requires more current information. In that case, the answers would be separate, since, as we mentioned before, ChatGPT has information till 2021 only, whereas Google Bard is constantly updated since it has full access to the updated search library of Google Search.
Bard is Google’s public tool in the very highly competitive artificial intelligence chatbot space. Another popular player in this field, as we have mentioned before, is OpenAI’s ChatGPT. So, simply put, Google Bard is yet another artificial intelligence-powered chatbot in the market. It was launched in early 2023. Back then, it was an experiment that was fundamentally based on a conversational large language model. You enter a text as a prompt for Bard, and then Bard generates a response to the prompts you have entered. The biggest strength of Google Bard lies in its ability to access the internet and leverage the power of Google search for generating its responses.
What can you use Google Bard for?
You can do a lot of different things using Google Bard. It is a smart, intelligent tool that can be used to explore ideas, compose text, write code, and much more. We’d say, look at Bard like an intelligent friend or colleague, and ask them something accordingly. So, say you want to brainstorm some ideas, or you want to research some topic and want to find some books or related concepts or information related to that topic, or you want to draft an email to someone, or you want to create an outline for say a project or a proposal, or you want to paraphrase or summarize some text, or you want to write some code, or you want to debug some code, Google Bard can do it for you.
Now, because Bard has access to Google Search, one thing Bard can do very well is to streamline the search for you. Imagine, you are planning to buy a new mobile phone. Ideally, you will look for a particular brand and model, then dig up all the specifications and reviews for it across different websites, and then, maybe compile a Google Doc that would contain all the information that can help you do a comparative. You keep doing this for every brand and model you are interested in, till you have all the information and can make the choice that is right for you. But with Google Bard, you don’t need to follow this cumbersome process
Google Search essentially functions on the back of keywords. The links the search delivers in response to the search query are pulled up against how relevant the particular link would be for the user’s search query based on the keywords. There are also featured snippets of information that Google Search feels would answer the user query best.
In contrast, Google Bard responds to natural language prompts. The response to the prompt is a string of interactions, it is like a chat conversation, and you can also expand, clarify, or rephrase that response. You can’t do this in Search. Also, in Search, you would need to click on individual links to get the information you need, it is not directly presented to you like Bard would.
We talk about a technology that we all are using to some extent in some form at work, at home, or even both. This has necessitated having an increasingly entrepreneurial workforce that is dynamic, more creative, more innovative, and more collaborative. According to a report by Automation Anywhere, about 95% of the people surveyed consider intelligent automation as a key component of their transformation strategy. Organizations are also contributing to this by incorporating automation into their digital transformation initiatives with a focus on centralizing automation planning.
A recent forecast by Gartner says that by 2024 businesses would be lowering their operating costs by about 30% by bringing together modern technologies and process automation. How successful businesses would be in doing this is also subject to speculation now, but the outcomes would be significantly dependent on the business’s ability to accelerate and master the change in different aspects and parts of the business. However, one thing can be said with certainty - businesses that recognize the need for changing processes as soon as possible and consider it important to embrace intelligent automation, not just in talks but also in action, in processes, and wherever possible, would stand n good stead for achieving successful outcomes in the future. An expert has opined in this regard that the future will belong to organizations that are strategically focused on embracing and implementing intelligent operations while encouraging and supporting their workforce to reskill as well as be innovative in adopting new ways to work in synergy with automation.
We don’t think anybody needs to be told any more about why they need to embrace intelligent automation, but if someone still asked us, we would say there are four major benefits a business can derive from embracing intelligent automation:
- staying relevant for the stakeholders, especially the customers and the market
- being able to do things more efficiently
- supports and encourages continuous learning among all team members
- Provides an enhanced and frictionless experience for all the stakeholders
Technology is evolving very, very rapidly and organizations everywhere will need to pull up their socks and keep up with this rapid pace of transformation to prevent becoming obsolete. Remaining agile is almost mandatory. A good starting point in this direction would be to start small and take up small, measurable intelligent automation opportunities, something that can be implemented without overwhelming anybody.
We come to the end of this week’s episode of the Cognixia podcast. We will be back next week with another interesting and inspiring episode of the podcast. Do check out our previous episodes if you haven’t already. You can leave us a review and share our episodes with your friends and colleagues, it would help us a lot.
Hello everyone and welcome to a fresh new episode of the Cognixia podcast. Every week, we come together to discuss something new from the world of emerging digital technologies and strive to inspire our listeners to learn something new and take the next big leap in their careers by ramping up their skills and knowledge.
About two years back, an artist named Beeple sold an NFT-based artwork for a whopping $69 million. In 2021, $69 million was equivalent to an unimaginable INR 5.2 billion. That was two years ago, and the world has gone around twice since. Since then, NFTs have shaken up the world of art, tech, and so many other subcultures. Interestingly, the journey has been quite a rollercoaster. Artists and collectors have built fortunes on the back of NFTs, a horde of brands have plunged into the space, marketing gimmicks galore, the metaverse has risen and gotten somewhat lost in the corridors of tech fads but keeps showing up here and there once in a while, and the space has become so happening.
However, in recent times, NFTs have lost their shine a bit. Their momentum has dropped, the sales of NFTs have cratered considerably and the crypto market has seen an unignorable loss of value. Will the communities that got created during the early days of the NFTs still be maintained? Will those crazy growth days come back or was it just a fad that has now fizzled out? One thing we can say for sure is that the situation is somewhat complicated and things are not as easy as they might seem. But we don’t intend to scare you off, so let us begin simply by first trying to understand what are NFTs.
Some people called “N. F. T.”, some call it “nefts”. NFT stands for non-fungible token. Non-fungible is an attribute of the token implying that the token is unique and cannot be replaced by something else. To give you an example, a bitcoin is a fungible token, you can trade one bitcoin for another, and it will still be the same thing, right? However, NFTs are one-of-a-kind. If you traded an NFT for another NFT, you will have a different NFT in your possession and not the same one you originally had because each NFT is different, which means, it is non-fungible. So, to put it in one line, an NFT is an irreplaceable, unique token. Now, how do the NFTs function?
According to IBM, multi-cloud is the use of cloud services from two or more vendors, giving organizations more flexibility for optimizing performance, controlling costs, and leveraging the best cloud technologies available. It can be something as simple as using SaaS from different cloud vendors. However, in an enterprise setting, the multi-cloud would usually refer to running the enterprise applications on PaaS or IaaS from multi-cloud service providers, like Amazon Web Services, Google Cloud Platform, IBM Cloud, Microsoft Azure, etc.
While we are at it, let us also understand what is a multi-cloud solution. A multi-cloud solution is a portable cloud computing solution across multiple cloud providers' cloud infrastructures. These solutions would usually be built on open-source, cloud-native platforms like Kubernetes and would be supported by all the public cloud providers. These solutions would also include workload management capabilities across multiple cloud platforms with a central console.
Understanding some popular myths around multi-cloud
Myth # 1: Multicloud involves no vendor lock-in
Myth # 2: Multicloud is always a cost-effective solution
Myth # 3: Multicloud deployments require traditional systems to be eliminated
It is also a fact that doing this makes multi-cloud systems a lot more complex and expensive. But if an enterprise is trying to solve problems holistically while being scalable, flexible, and agile, then it makes sense to extend this benefit to as many systems as possible.
However, in sum-total whether to go multi-cloud or not and how to use the multi-cloud, and how many systems to include the multi-cloud would depend on every enterprise’s case, there is no one-size-fits-all universal solution.
That are the top three myths about multi-cloud that we wanted to bust today. We hope you found this information useful.
With that, we come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us today as much as we enjoyed creating & recording this episode.
If you have been keeping up with the news, you would be aware of the ongoing crisis in Sudan. A deadly power struggle erupted in Sudan in mid-April, between the military factions after the transition to a civilian-led government faltered. Intense clashes are occurring between Sudan’s military and its main paramilitary forces, which have so far killed hundreds of people while thousands are trying to flee the country, running away from a burgeoning civil war that threatens to destabilize the wider region including and around Sudan. That is more or less the gist of what is happening, but to understand more about why all the fighting is taking place and why it is of so much significance, we recommend you catch up on the news.
Now, to rescue the Indians stranded in Sudan, India launched Operation Kaveri, where India sends out flights to the country to rescue as many Indians as possible and bring them back to India. So far quite a lot of people have been brought back home and the Indian Air Force is undoubtedly doing a brilliant job in commanding and executing these rescue missions.
In one such very daring operation, a C-130J heavy-lift aircraft, flown by the Indian Air Force rescued 121 people from a tiny airstrip in Wadi Sayyidna, located about 40km north of the badly violence-hit capital city of Sudan – Khartoum. The operation took place on the intervening night between 27 and 28 April 2023. This operation was carried out especially to rescue people who are unable to reach Port Sudan, which is currently the key exit point from where India is rescuing its people from Sudan.
So, you now have some idea of what are electro-optical sensors, how they operate, what they are used for, the technologies that power them, and why they are so important for everyone. And with that, we come to the end of this week’s episode of the Cognixia podcast.
One such area where artificial intelligence is making quite a mark is DevSecOps. We are going to take a quick minute here to tell everybody what is DevSecOps. DevSecOps is the practice of integrating security testing at every stage of the software development process. This would include the tools & processes which facilitate collaboration among developers, security specialists, operations team members, etc. to ensure that the final product, the software, or the application is both efficient and secure. To put it in a very simplified form, DevSecOps adds the element of security to the DevOps culture, weaving it into the process itself, instead of adding measures as an afterthought after the software or the application has been produced.
Going back to our topic for the day, how is artificial intelligence reshaping the roles of a developer in the DevSecOps environment?
The recent Seventh Annual Global DevSecOps Report by GitLab has found that artificial intelligence and machine learning in the software development workflow have found promise but challenges like the complexity of the toolchain and concerns about security continue to remain. According to this research, about 65% of the developers are not using artificial intelligence and machine learning in their code-testing efforts or have plans to do this in the next three years. This is quite a huge step in the automation of the software development process.
This survey by GitLab covers over 5,000 IT leaders, CISOs, and developers across various sectors including financial services, automotive, healthcare, telecommunications, and information technology. The survey focused on understanding the successes, challenges, and priorities for the DevSecOps implementation.
One of the very interesting things this report found, as we mentioned just now, was how artificial intelligence and machine learning is being adopted in the software development process. In 2022, only 55% of the developers were using AI/ML to check their code, while this number is now up to 62%. Also, last year, only 39% of the developers were using bots in the testing process; this number is up to 53% this year.
Some of the top skills, Git Lab reports are considered essential for security professionals are:
1.Artificial intelligence and machine learning
2.Soft skills
3.Subject matter expertise
4.Metrics & quantitative insights
This definitely indicates that all-round expertise and skill set are essential for a successful career in security and overcoming security challenges they would encounter in their work.
To make the most of emerging technologies like artificial intelligence and machine learning in the security and DevSecOps space, enterprises must invest in the right training and tools for their teams to leverage the potential of these technologies in the software development and security workflow processes.
Hello everyone and welcome back to the Cognixia podcast. As of 2022, women earn, on average, about 82% of what men earn which is only a 2% increase from 2002, according to Pew Research. Women are highly underrepresented in STEM fields, even more so in managerial roles, making up only 27% of the workforce in those industries, combined, according to the US Bureau of Labor Statistics.
This trend is not limited to women in tech. It is a fact that women are increasingly and deeply underrepresented in higher-paying positions. Pull up the median pay data for any industry, not just tech, and the problem becomes quite clear. Studies have also found that companies which disclose the pay gaps are more likely to fix them compared to those that do not.
According to a 2021 survey by Hired, men in tech were offered higher salaries than women for the same job title 59% of the time. On average, women in tech were offered salaries 2.5% less than the ones that men were given for the same roles. Women also suffered a greater job loss compared to men during the pandemic. Reports say that about five million women have lost their jobs since February 2020. A slight ray of hope comes from a 2021 survey by MetLife which found that of the women who were considering coming back to the workforce post-pandemic, 8 in 10 said that they would like to change their careers and pursue something in STEM now.
There are also representational issues, which researchers say, has an enormous impact on the paychecks women receive. Women in tech have extremely low representation, which only gets lower as we move up the ladder. This, in turn, pushes average and median salaries for women in tech way below that of men, who are well-represented at all tiers. On the other side, women also negotiate less, and when they do, they are hardly ever as aggressive as men are when negotiating the salaries. Put it all together, and it creates a multiplier effect which collectively pushes salaries down for all women.
We will talk about the most recent development in the AI space – GPT-4. A lot of you would have already heard about it, some might even be on the waitlist to get the API, and some might have tried it and tinkered around a bit with it, though we are sure, some are still to discover it. No matter where you stand, we can promise today’s episode should help you get a lot of information about GPT-4.
GPT-4 is the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model which is of course not as capable as human beings in a lot of real-world scenarios, it can still be said to exhibit human-level performance on various professional and academic benchmarks. If the claims on the OpenAI website are anything to go by, GPT-4 has passed the simulated bar exam with a score around the top 10% of the test takers. OpenAI has taken 6 months iteratively aligning GPT-4 using lessons from the adversarial testing program as well as ChatGPT, delivering the best-ever results on factuality, steerability, and keeping within the guardrails.
GPT-4 is more reliable, creative, and capable of handling a lot more than its predecessors. GPT-4 can accept inputs in the form of text as well as images. This allows users to specify any vision or language task to GPT-4. The outputs would be textual – could be a natural language, could be code, etc. Despite being multi-modal, its results are at par with text-only inputs. GPT-4 can also be augmented with test-time techniques which were intended for text-only language models, such as a few-shot or a chain-of-thought prompting.
We are eager to see how GPT-4 pans out for everyone as more and more artificial intelligence-powered technologies and developments come to the fore to empower everyone. The future is surely going to reveal some very interesting developments, disruptions, and revolutions.
ChatGPT is known for being a human-like conversationalist. This dialogue format and the training it is backed by empower ChatGPT to answer follow-up questions, challenge premises that might be incorrect, and reject requests that it feels are inappropriate. The key factor here is that ChatGPT is trained and not programmed to do what it does which makes it so much more human. So, what do you think, will ChatGPT take away your job?
Well, a decade ago, in 2013, a study by the University of Oxford found that about 47% of US jobs would be taken away by artificial intelligence in the coming two decades. Halfway through to that point, it doesn’t seem quite likely, and the prediction appears to be quite off the mark. But there are still ten years to go and we know how unpredictable are the times we live in. While millions of jobs may still not get replaced by artificial intelligence in this timeline, as we get more and more exposure to new emerging technologies like ChatGPT, some territory encroachment is bound to happen.
Anu Madgavkar, a partner at the McKinsey Global Institute opines in this regard that human judgment will still need to be applied to these emerging technologies to avoid errors and bias. Tools like ChatGPT can be considered to be productivity-enhancing tools, and may not become complete replacements for all human efforts. In our opinion, ChatGPT does have the potential to disrupt not just blue-collar work but white-collar work as well.
Earlier in March, Infosys Founder – Narayana Murthy was speaking to the press on the sidelines of the NASSCOM Technology and Leadership Forum, where he said that in 1977-78, there was a thing called program generators. At that time, everybody said that the youngsters will now lose all their jobs. But we can see that this did not happen. The human mind is the most flexible instrument, he said, it can adapt very well. And all that happened was people start solving bigger and bigger problems, which these program generators could not handle. Murthy went on to say that we should use ChatGPT as a base and then show our creativity, show our smartness, and show our innovation.
If you keep your skills updated and you keep adding new skills to your repertoire, it makes you super invaluable an asset, and machines will have a run for their money trying to replace you, and despite that, would likely fail! And, for updating your skills, you need to go to www.cognixia.com and check our course offerings, talk to us in the chat window there, we promise it is manned by actual human beings and there is no ChatGPT there, enroll for a live instructor-led online course, and get going on your upskilling journey.
ChatGPT can be integrated with automation development and leveraged to provide personalized customer interactions – from responding to common queries to delivering support for more complex problems. This automation would improve accuracy, reduce response times, and be available & accessible 24x7, all of which are very important factors in the current times. This, in turn, leads to enhanced customer satisfaction and better consistency of responses. So, in this episode, we will explore the different ways that ChatGPT’s capabilities can be leveraged to enable automation development as well as design.
One of the first ways to leverage ChatGPT for fueling automation development & design is to understand other developers’ codes. If you just copy the code, you would like to understand in the ChatGPT window and ask what the particular code will do ChatGPT will give you insights into what can be accomplished by that code. However, as we mention in ChatGPT episode 3 of this series, the last week’s episode, ChatGPT has some data privacy and copyright concerns, so be careful about what code you are sharing with ChatGPT, and that you are not violating anybody’s privacy or intellectual property rights in the process.
we come to the end of this week’s episode and the fourth part in our five-part series on ChatGPT. Next week’s episode will be the last and final part of this special series, and we hope you are enjoying listening to it. ChatGPT can be a valuable tool to have in your arsenal, but take it with a pinch of salt, we’d say, it comes with its unique set of challenges and loopholes too. With time, maybe these challenges will get resolved, and the loopholes will be plugged in, but until then, just be careful!
It is said that if you have ever written a blog, a product review on any platform, commented on anything online, or just about written anything on the online space, chances are your words were used for training ChatGPT. ChatGPT knows what you wrote, irrespective of whether you wanted it to know about it or not. By now, we have told you a few times about the humongous amount of data that went into training ChatGPT. As a thumb rule, the more data used for training a large language model like ChatGPT, the better the model would be at identifying patterns, predicting what’s next, and delivering plausible text. Just for a quick refresher, we would like to remind you that more than 300 billion words existing all over the internet have been used to train the ChatGPT model. This includes books, articles, blogs, websites, posts, comments, and so much more. Now, it is a good thing that the model has been trained on so much data.First, nobody was asked for permission to use their data for training ChatGPT. This is basically a violation of people’s privacy. If I have a blog I write on, anybody using the content of the blog for any person is ideally required to seek permission from me before using the content. OpenAI did not do this for any of the data it used to train ChatGPT. Some of the data used could be sensitive in nature for a multitude of reasons, and it is clearly a data privacy violation here. Plus, a lot of the content in this mix that ChatGPT has been trained on would be copyright-protected or proprietary information. For instance, you ask ChatGPT to pull up some paragraphs from some novel, and when ChatGPT delivers those paragraphs, you know that that content is copyright-protected and cannot be reproduced without the permission of the publishers. I think we as users might be handing over sensitive information to ChatGPT without realizing it. This data then ends up being in the public domain and poses a definite data privacy risk. Say, you are a lawyer who asked ChatGPT to draft some legal agreements for you or you are a business executive who asked ChatGPT to draft some emails to your clients for you or you are a developer who asked ChatGPT to check some code for you. In all these cases, all your data – being drafted or being checked, now goes into the public domain as ChatGPT accesses it. Now, these are undoubtedly confidential pieces of information and one can’t afford to have any leakage in them. But you inadvertently gave ChatGPT access to it, by extension putting it into a freely accessible public domain. according to OpenAI’s privacy policy, the company collects users’ IP addresses, browser type & settings, as well as user data around their interactions with the site, such as the type of content they engage with, the features that the users use, as well as the different actions they take online. To make it clearer, if you are a ChatGPT user, OpenAI is collecting all the data about your online browsing activity over time as well as across multiple websites. What’s more alarming, in my opinion, is the fact that OpenAI has stated that it may share the user’s personal information with unspecified third parties, without actually informing them, to meet their, that is OpenAI’s business objectives. Now, that is definitely scary. A lot of websites and platforms do that already, considering how many places we are asked to share personal information without being given a choice, data privacy is taken quite lightly as it is. The privacy risks that come with using ChatGPT sure seem a little concerning. I think we could all do with being mindful of what we share with ChatGPT. I would also recommend making sure we log out once we are done using the tool. Yeah, so I think this is what we had to tell you about the data privacy concerns associated with ChatGPT. We hope we were able to help you get a different perspective on things in this episode.
ChatGPT is a transformer-based language model that uses deep neural networks to process & understands the text. Now, due to this architecture, ChatGPT can generate more fluent and natural-sounding text than any other models have been able to accomplish previously. Additionally, the ChatGPT model has been trained on a very wide range of content on the internet we could even say that ChatGPT has been trained using just about all the content available on the internet. Due to this, ChatGPT is better equipped to understand and respond to various topics, be it everyday conversations or technical discussions.
ChatGPT also does not understand anything it says, and it also kinda doesn’t care. A lot of scholars and academics like Gebru have been warning us about the dangers and limitations of generative AI models, but the sheer excitement that the release and subsequent functioning of ChatGPT have generated has drowned out all the noise and warnings. In fact, Gebru had been fired from Google, it is said after she wrote her seminal paper.
Two of the most prominent AI-powered intelligent chatbot tools would be ChatGPT by OpenAI and Sparrow by Google. Both these tools have the potential to change the way we interact with the digital world and digital systems. Both ChatGPT and Sparrow provide users with an effortless and natural communication experience which is, undoubtedly, one of their biggest USPs.
ChatGPT is a state-of-the-art language model developed by OpenAI, a leading artificial intelligence organization. ChatGPT has been designed to understand and generate human-like text making it a powerful tool for many applications. The tool is based on the original framework for pre-trained models, called the Generative Pre-trained Transformers or GPTs. The tool is trained so widely and effectively that it can generate content that is almost indistinguishable from human-generated content in both the matter and the style!
To get a bit more technical, ChatGPT is a transformer-based language model that uses deep neural networks to process & understand the text. Now, due to this architecture, ChatGPT can generate more fluent and natural-sounding text than any other models have been able to accomplish previously.
Sparrow by Google is a chatbot built by DeepMind - the artificial intelligence research group at Google. Like ChatGPT, Sparrow can also understand natural language inputs and respond to them. This makes Sparrow a very valuable tool for customer service and customer support applications. Its ability to process and understand the inputs come from advanced deep-learning algorithms. Sparrow is capable of handling queries in multiple languages as well as dialects, making it useful for a global user base, even in territories where English may not be as commonly spoken. There are multiple areas where Sparrow would score much higher than ChatGPT, and one of the most important areas in that would be data privacy and safety. Did you know? that Sparrow has been designed with data security and privacy in mind, so sensitive information is strongly guarded and the user data is handled very responsibly?
Sparrow uses something called the “transformer-based pre-training”. With this method, Sparrow is able to comprehend the meaning of a sentence, even if Sparrow has never encountered some of the words or terms in the sentence ever before. How cool is that?
With that, we come to the end of this week’s episode as well as the first episode in our five-part series about ChatGPT. We hope you enjoyed listening to it, and we are really excited about the next episode, which will the second one in this series. Stay tuned for the next episode of the Cognixia podcast, we have a very, very interesting topic lined up for it, and we totally can’t wait to share it with you.
DevOps is a set of practices and guidelines that help improve software development productivity. It has immensely helped shorten the software development lifecycle while delivering high-quality applications with a steady and consistent delivery of code.
One thing that played a major role in enabling the success of DevOps was containerization. If we had to explain in very simple terms what containerization was, we would say it is the process of placing the code, the environment, as well as its dependencies in an isolated space during the application development process. This, in turn, enhances the speed of deployment, patching, and scaling. Containerization has helped resolve some of the biggest problems that deployment faced and its benefits extend beyond just deployment – from boosting the ability to standardize and automate to enabling people to work across languages and technologies.
Kubernetes is an open-source system for container orchestration. It is a tool that enables one to manage, scale, and automate the process of software deployment. If we had to describe in very simple terms, how Kubernetes is helpful in DevOps, we would say it helps combine the development and maintenance phases of the software systems which improves agility.
To simplify it further, we would say, containerization using Kubernetes is an efficient and effective way to implement DevOps compared to the traditional monolithic approach. Using Kubernetes, one can create and manage containers on cloud-based server systems. Using Kubernetes, DevOps teams can bring down the burden on the infrastructure by letting the containers operate on a different machine or environment without breaking down either machines or environments, keeping everything functioning smoothly.
maybe we will just suffice to say that every DevOps engineer must absolutely invest time and effort towards learning and mastering Kubernetes, it is important and it is almost essential. If you are someone who would like to learn DevOps or Kubernetes, we totally recommend checking out our live online instructor-led courses for DevOps as well as Docker & Kubernetes.
we come to the end of this week’s episode. If you would like to learn more about RESTful APIs, while sharpening and validating your skills, we would recommend signing up for our live online instructor-led DevOps Plus training and certification course
We hope this helps you understand what we are trying to say about what you must and must not do when designing RESTful APIs.
A cloud engineer is an IT professional who takes care of any technological responsibilities associated with cloud computing – from design to planning, management to maintenance, and support. Under the bigger bracket of cloud engineers, there are more specific roles, such as:
- Cloud architect
- Cloud software engineer
- Cloud security engineer
- Cloud systems engineer
- Cloud network engineer
Some must-have skills for a cloud engineer include Linux, database, programming, networking, DevOps, Containerization, Virtualization, API, and cloud security.
Their specific responsibilities and scale could vary from organization to organization, but the mistakes they must avoid would remain quite constant.
So, let us look at the common mistakes that cloud engineers must avoid.
- Mistake # 1: Assuming the cloud is Titanic
- Mistake # 2: Overpaying
- Mistake # 3: Mis-use of administrator privileges
- Mistake # 4: Assuming you can do everything on your own
Meanwhile, if you would like to check out our cloud courses – AZ-104: Microsoft Azure Administrator, Cloud computing with AWS, among others, visit our website – www.cognixia.com.
We talk about Kubernetes deployment strategies. We talk about what is Kubernetes in a lot of our episodes. Kubernetes is a very popular open-source container orchestration system for automating software deployment, scaling, and management. It was originally designed by Google and is now maintained by the Cloud Native Computing Foundation.
Now, there are quite a few different ways in which an application can be released in Kubernetes. One must pick whatever approach works for them, meets their requirements, and ensures the dependability of their infrastructure when the updates to the application are rolled out.
Let’s take a quick minute to understand what is deployment in Kubernetes. In Kubernetes, a deployment is a resource object that specifies the final state of a program. Deployments are declaratory so the state to be achieved is not usually specified. Instead, the desired configuration must be specified. The deployment controller can manage things with that information and complete the tasks automatically in the best possible way. A deployment can be used to specify the entire process of an application, even cover the images to be used, the number of pods required, and how they would need to be modified.
As we mentioned before, in this episode we will be talking about the Kubernetes deployment strategies, so what are the different deployment strategies in Kubernetes?
A deployment strategy would specify how to update and develop the different Kubernetes application versions. Kubernetes deployment strategies offer users ways to minimize downtime and interruptions that would be caused by rolling out upgrades and deploying the applications. So, let us take a quick look at the different Kubernetes deployment strategies.
Canary deployments can be chosen if you are not fully sure about the platform’s stability or are skeptical about the potential effects of launching a new software version. In this way, we enable user testing of the application and platform integration. By integrating deployments with all the other Kubernetes functionalities, users can build more reliable containerized apps to meet any need at hand.
With that, we come to the end of this week’s Cognixia podcast episode. We hope you enjoyed listening to us. If you have any questions or suggestions, drop us a line on any of our social media handles.
We will talk about what is .Net, what it does, what is the new version all about, what value it brings to the table, and what it means for enterprise applications. So, without further ado, let’s begin.
We hear people talking about .Net time and again, chances are some of you may even have used it at some point or continue to use it in your everyday life today. But to level the ground for everybody and bring everyone on the same page, let us take a minute to answer the very simple question – what is .Net?
According to Microsoft, .Net is a free, cross-platform, open-source developer platform for building many different types of applications. With .Net, one can use multiple language editors & libraries to build for web, mobile, desktop, games, IoT, and a lot more. To put it in a nutshell .Net is an open-source developer platform created by Microsoft for building many different types of applications.
Over the years, .Net has evolved considerably. The platform has expanded beyond the original .Net Core which has brought to the fore many important changes made to the .Net platform. .Net is now open-source and cross-platform. It is also no longer tied to the Windows’ release cycles. Earlier, there would be many, many years of gap between even consecutive releases for .Net, however, this has improved significantly in recent times. Nowadays, there is a new .Net release every year.
In line with these developments, the latest version of .Net – the .Net 7 arrived at the end of 2022 and has been gradually making waves among users – both individuals and enterprises. The new version quite expectedly carried a host of new features and brought along some valuable ways to bring the older .Net framework code to the new platform. The .Net 7 has prioritized the improvement of performance. It has also focused on enabling users to go straight from the development tools to the cloud-native containers that can be used in Kubernetes.
Until this version came along, .Net was only able to support Intel and AMD processors. But a whole new generation of ARM processors has been staring right back at us for a while now, so building in support for these processors was becoming critical, which has now been addressed in .Net 7. Power and space budgets are getting tighter.
Additionally, the .Net 7 is built with better code. This is one of the major improvements we are seeing in this new release – a continuous improvement in the base class libraries that are used to build the code. With this, the developers’ skills become significantly transferable – so you can learn .Net once and then use those skills to build everything – from desktop applications to the web, from mobile applications to server code, and everything in between. APIs are available for providing user interfaces web servers distributed applications, etc.
.Net 7 also keeps up with the latest development in the industry and now offers support for DevOps practices. It offers support for many tools which support the now increasingly popular OpenTelemetry standards.
We can say that .Net 7 is a truly modern release. The new release sheds the baggage of two decades of the legacy framework that .Net has built and instead gives users a whole new platform is an amazing thing here. This is effectively the third release for the new .Net and we see major improvements happening with each version. The new .Net is a new, improved, and effectively future-proof version of the platform packing some very amazing features.
We come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us. The year has just begun, and the appraisal season will be here soon.
At Cognixia podcast, every week we bring you a bite-size dosage of the latest happenings, discussions, guides, and a lot more from the world of emerging digital technologies.
This week we talk about something major that happened earlier in January 2023. A computer outage at the Federal Aviation Administration brought flights across the United States to a complete standstill, with hundreds of delays quickly cascading through the systems at airports worldwide. The US government confirmed that there was no evidence of a cyberattack. In this episode, we will delve deeper into what happened that day.
The Federal Aviation Administration or the FAA has a system that sends vital communication to the pilots. This system experienced a massive outage causing thousands of flights to be grounded. This system is called the NOTAM or Notice to Air Missions. Before a flight takes off, the pilots and airline dispatchers in the US are required to review the notices in the NOTAM. This would include important information about the weather runway closures, ongoing construction work, etc. which would be required for the flight’s smooth journey. Earlier, NOTAM used to be telephone-based, however, over time, NOTAM was moved online.
The NOTAM system broke down earlier in January 2023 and it was a few hours before the system came back up, but not before 1200 flight cancelations and more than 7800 delays on the East coast itself. Some of the busiest airports in the world – Chicago, New York, Los Angeles Atlanta, etc. are in the United States and they saw between 30 to 40% of flights being delayed due to this outage.
A few days after the incident, it was revealed that unspecified personnel were responsible for corrupting a file in the system, which caused the outage of the FAA NOTAM’s computer system. According to a Fortune News Report, FAA does have stringent procedures in place to ensure that data doesn’t get damaged by technicians when they are working on the systems.
Reportedly, when the system began having issues, the technicians working with the NOTAM system switched to the backup systems. Unfortunately, the backup systems were trying to access the same damaged files as the original systems leading to system breakdown. To restore the system, a complete shutdown became essential. This, in turn, called for about 90 minutes of a complete halt on all flight departures to be announced by the FAA.
The Ponemon Institute predicts that on average the cost of an unplanned outage like the one NOTAM experienced runs to about $9000 per minute, leading to $540,000 per hour. There would be many other indirect costs over and above this as well. Building system resilience is extremely important. Every enterprise today is at enough risk from the outside world, the least it can do is to minimize risk from internal factors like outages and breakdowns because the system was not resilient enough. These things can go a long way in safeguarding an organization’s interests and reputation while eliminating the possibility of incurring tremendous losses due to these issues.
We talk about the relationship between two very important areas of the IT space – IT service management, commonly referred to as ITSM, and Software-as-a-Service, commonly referred to as SaaS. We will explore the relationship between ITSM and SaaS, and how they work together.
SaaS management is the process and practice of tracking and managing the full lifecycle of all the cloud applications deployed in an organization. SaaS management helps improve business value through processes that create complete centralized visibility of the wide range of tools that employees use, optimizing spending, improving routine processes, and automating complex or repetitive tasks.
ITSM and SaaS management must work together is financial management. Every organization hopes to keep its costs down and keep its ROIs high. However, it has often been found that companies end up overspending by a giant margin on cloud applications, and in a lot of cases, they don’t even realize they have overspent. It has also been found that about one-third of the spending on SaaS applications usually goes to waste in the form of unused applications underutilized licenses, duplicate licenses, redundant licenses, hidden costs, incorrect access profiles, etc.
Common functions served by effective SaaS management include:
- Contain SaaS application costs
- Manage SaaS licenses
- Plan SaaS renewals
- Manage SaaS vendors and contracts
- Ensure visibility into the SaaS purchases
- Eliminate and reduce shadow IT
- Strengthen the security of SaaS applications
- Maintain active SaaS inventory, and
- Enhance and facilitate IT collaboration
So, this helps you understand how important SaaS management is for every organization and how it works in synchronization with the IT service management functions. It is all about effective collaboration for smoother, more efficient & secure operations.
The ITIL 4 Foundation certification is the perfect starting point for a stellar career in the field of IT service management and can do wonders for your professional journey, so get in touch with us today to know more about this globally recognized certification.
Agile project management is a non-linear approach to organizing and carrying out the delivery of a project through its lifecycle. This approach involves breaking larger goals into smaller tasks that are more manageable, easier to accomplish, and simpler to tweak & adjust as required during the course of the project. This enables teams to accomplish the smaller tasks quickly and easily, compared to taking the pressure of accomplishing bigger, more ambitious goals which would not just take more time and effort but can also get tedious and tiring. Breaking the bigger goals into smaller tasks also helps corrective action and mitigation measures can be implemented sooner, ensuring adjustments get made to keep up with any errors made, changes in consumer demands, scope change, or change creep, etc., and continue moving towards the desired project outcomes.
Apart from this, agile project management encourages collaboration. When a bigger goal is broken down into smaller tasks, there are a lot of different people and different teams who would be working on these smaller tasks, which would together influence the overall outcome of the project. Most times, the tasks accomplished by one team would help another team accomplish their task or influence their outcomes in some way since the smaller tasks would be correlated, being a part of the same bigger goal.
Benefits of Agile project management
- Quicker Project Delivery
- Improved Teamwork
- Increased Flexibility
- Focus on Risk Management
- Improved Efficiency
We hope you now have a much better understanding of agile project management and it will help you with your work or inspire you to learn more about it. You can enroll for Cognixia’s live online instructor-led project management training and certification course or you can also sign up for our Certified Scrum Master training, which is also live online and instructor-led.
we are going to be talking about something that has been a very happening technology for quite some time now – Low-code. As the name suggests, the technology involves minimal possible coding, helping someone with absolutely no background or practice in coding to be able to create applications easily. The technology is seeing a huge demand as it does not just reduce the dependence on skilled coding professionals but allows anyone to easily build anything they want with minimal coding. Low-code tech enables business technologists to work outside the folds and umbrellas of conventional IT and create a tech or analytical capabilities for business use. Some latest projections about this technology have been published recently, which is exactly what we will be talking about in today’s episode.
According to the latest research by Gartner, low-code technology is set to grow to nearly $27 billion in 2023 fueled by hyper-automation and composability. This would be a roughly 20% increase over 2022. Of the different components of low-code tech, low-code application platforms are forecast to see the largest growth, growing by approximately 25% to reach nearly USD 10 million in 2023.
Gartner has also predicted that by 2026, developers outside the formal IT departments will account for over 80% of the user base for low-code development tools. To get an idea of how huge this is, we would like to tell you that this number was 60% in 2021.
Gartner has also opined that by 2026 a large number of organizations will have hyper-automation and composable business initiatives in place, which would be a major driver for the demand for low-code technology. In these fast-paced times, there is a dire need for speedy application delivery and highly customizable automation workflows.
If you are a current or aspiring IT professional or a business technologist, or someone looking to learn a new skill, do check out low-code technology. To take it a notch up, you can add a certification in DevOps or cloud computing to your repertoire, which would be a huge boost not just for your skills, but also for your resume.
ChatGPT by OpenAI is making headlines all over the world and it has gone totally viral. So, we at Cognixia podcast thought, why not talk about what ChatGPT is and what the hype is all about, that is exactly what today’s episode is going to do.
ChatGPT is not exactly the catchiest, smoothest name we have ever seen for a bot, instead, it sounds more like some complicated computer component, or maybe some chemical or pharmaceutical drug, pretty boring, eh? Boring name aside, ChatGPT, in reality, is the internet’s best-known language-processing AI model. But before we tell you more about ChatGPT, we are going to take a minute to tell you who is OpenAI.
To understand what is ChatGPT, let us rewind a bit and take a look at GPT-3, the technology powering ChatGPT. GPT-3 stands for Generative Pretrained Transformer – 3, which is a state-of-the-art language processing AI model built by OpenAI. GPT-3 can generate human-like text and has a very wide range of applications. Applications of GPT-3 include language translations, language modeling, application text generation, etc.
What should you do if you want to try using the bot? This is the easy part. You go to OpenAI’s website and create an account on the website. Then once you have logged in, you can try the ChatGPT. You can go crazy asking it all sorts of questions and enjoy talking to the bot.
Sounds very exciting, doesn’t it? Our podcast writers almost got tempted to get the ChatGPT to write the podcast episodes too. Maybe they did get ChatGPT to actually do it, we don’t know, they won’t tell us! We have been talking to the bot for a bit now and we are definitely finding the conversations very interesting and helpful. It is indeed a big step for artificial intelligence and machine learning and automation.
If you live in the Northern Hemisphere, you know that the days are getting colder and the mercury is dropping a bit every day. This makes for the perfect weather for that mug of hot chocolate and some warm ginger or cinnamon cookies, doesn’t it? But it is also a prime season for something else – flu. The cold, dry, winter air makes us susceptible to influenza. Not a lot of us take influenza very seriously, we call it just a viral fever and get on with life, but globally, it is a huge thing and there are response and surveillance systems that keep an eye on what’s happening with influenza everywhere. And this is not a new development, health authorities have been trying to combat and control the spread of influenza since the 40s.
In 1947, the WHO Interim Committee of the United Nations agreed to begin a Global Influenza Program – the GIP, for the study and control of influenza. It was a time when a major outbreak of influenza in Europe was an immediate concern, so identifying the virus responsible for it, and developing vaccines that would help fight the virus was a top priority. Sounds like a familiar circumstance now, doesn’t it? Regional Influenza Centers were set up in response in 1948. Then, five years later, the Global Influenza Surveillance Network or GISN was established as there was a need for an influenza surveillance system to keep track of the methods and measures being deployed for disease prevention and control. This GISN then got renamed to what we today know as the Global Influenza Surveillance and Response System or GISRS.
Every year, sentinel physicians and hospital networks contribute about 3-4 million clinical specimens with related information to the National Influenza Centers for virus detection and preliminary analysis, reports WHO. From these, about 40,000 are sent to the WHO Collaborating Centers, where 10,00 of these 40,000 are characterized for their antigenic and genetic properties.
At that time, the countries also agreed to work with the WHO to develop an Influenza Virus Traceability Mechanism (IVTM) which would help track all influenza viruses that existed across the globe and had pandemic potential. The IVTM, it was agreed, would let the users trace the geographic transfer of influenza viruses sing Geotrace and also be able to view the derivation tree for these.
We would also recommend that if you are considering building a career in cloud computing then do consider obtaining an official Microsoft certification to validate your skills and knowledge. Goes without saying, the best place to begin would be the AZ-104: Microsoft Azure Administrator Course, the official Microsoft certification examination, clearing which you earn the credentials of a Microsoft Certified Azure Administrator.
We talk about a challenge a lot of Scrum Masters face these days – managing distributed teams. In the post-covid world. Having distributed teams are commonplace. Geographical boundaries and physical presence are no longer important to get work done. A rigid manifesto would lead to utter failure in such a scenario. But the agile methodology has always been flexible and adaptable to changing times and changing needs, thankfully.
Undoubtedly, the Certified Scrum Master is one of the most critical roles in an agile organization. So, the pressure and challenge of managing distributed teams also fall on the shoulders of the Scrum Master.
We talk about some best practices that would help Scrum Masters better manage distributed teams. Here are some of the best practices we recommend.
- Listen
- Value All Stakeholders
- Convert Ideas to Achievable Goals
- Keep the Hierarchy Flat
- Are the team members happy?
- Bring in the Agile Toolbox
- Review and Improve
- Embrace Flexibility
- Usher in the Creativity
- Automate and Digitalize
Now, that are ten super best practices that Scrum Masters everywhere can follow and implement to effectively manage distributed teams. When Agile methodology first came out, it was something intended for use by software companies and IT teams. However, it is important to understand that the foundation of Agile is based on widely-accepted, established values and principles. It is based on the wisdom and knowledge that has been collected by professionals and practitioners over the decades. Agile does not stand for rigid rules that make it suffocating for everyone to function in these changing times. Rather, Agile is intended to help everyone perform better, its principles and ideas can be adapted to suit every organization and there is really no one right way.
This week are going to do something we love doing – busting myths. Like with just about everything that exists in this world, the technology space is also rife with a lot of myths and misconceptions which prove to be rather silly sometimes or could even lead someone to make very expensive errors in their work or life. This makes busting myths super important, of course.
We will debunk not one, not two, but FIVE myths about the cloud. Now, we know that cloud computing has been around for a significant amount of time now. The Covid-19 pandemic sure accelerated cloud adoption around the world as enterprises got pushed into a corner, necessitating a jump to remote operations made embracing the cloud almost indispensable.
Before we begin busting these myths, we would like to highlight the fact that innovators and pioneers are all set to reap more than $1 trillion in run-rate EBIDTA across Fortune 500 companies alone in 2030.
According to a 2021 O’Reilly survey, today, almost 50% of organizations have a cloud-first approach and about 30% of the organizations surveyed choose to describe themselves as cloud-native. Yet another 37% of the surveyed organizations have plans in place to become cloud-native in three or more years.
let us move on to the main agenda of today’s episode – debunking five major cloud computing myths.
Myth # 1: When you embrace the cloud, you must give up control
Myth # 2: Cloud is only for organizations with simple, straightforward environments
Myth # 3: Companies in regulated industries should stay away from the cloud
Myth # 4: If the data is out of sight, it no longer remains reliable or resilient
But in the competitive, fast-paced, rapidly evolving times we live in, where digital transformation is not just a fancy goal but a need of the hour, the cloud is the foundation an organization’s digital aspirations would be built on and achieved. IT decision-makers would have to pay heed to their honest advisors while using their sensibilities and reliable information to make the right decisions for their organizations.
Like with every innovation – new and old, there would be myths and misinformation rampant about the cloud too. IT decision-makers would have to pay heed to their honest advisors while using their sensibilities and reliable information to make the right decisions for their organizations.
AWS Certified Solutions Architect certification and Microsoft Certified Cloud Administrator or an Azure DevOps professional. 2022 is about to end so this is a good time to prepare to leap in your career for next year after all, right?
Microsoft is introducing granular personal access tokens for its Azure DevOps REST APIs to limit the risks and damages when access credentials are leaked or stolen. Now, some weeks back, the renowned cybersecurity firm – Praetorian came out with details on how their researchers accessed the internal corporate networks of companies using GitHub, an entity owned by Microsoft, for their CI/CD tools. The researchers were able to compromise the access to GitHub using an accidentally leaked PAT.
According to Praetoria’s report, there are multiple ways in which developers could compromise a personal access token – they could fall victim to a phishing scam, or their devices could get compromised, or they might mistakenly include the PAT in the command-line logs!
Personal Access Tokens or PATs are alternatives to passwords and are used for authenticating the identity of someone accessing a system or website. They are also used to authenticate the identities of the developers using the various APIs and scripts on a platform. In this particular case, the personal access tokens are used to authenticate users and developers into Azure DevOps. A personal access token would have a lot of information embedded into it.
Azure DevOps, the personal access tokens would contain information about an individual’s security credentials which would help the system identify the individual as well as provide other information such as the organizations that they have access to & the scope of every access. But with evolving systems and safeguards, cybercriminals tend to switch tactics too, focusing increasingly on stealing access credentials to corporate networks instead of just compromising systems.
Personal access tokens have evolved too. Earlier, the PATs were relatively more coarse-grained, giving access to all repositories and organizations which were accessible to token’s users, without any associated control or visibility of what was happening to the user’s organizations. Over time, there was a need to change this and the personal access tokens have gotten significantly finer-grained now.
To earn this Microsoft certification, you need to clear the official Microsoft certification exam – AZ-400: Designing and Implementing Microsoft DevOps Solutions. This Microsoft certification is ideal for developers and infrastructure administrators who also have subject matter expertise in working with people, processes, and products to enable the continuous delivery of value in their organizations. If this is a path you would like to embark on or you would like to know more about this or any of our other live online instructor-led training and certification courses, talk to us today!
SAFe and Behavior-driven Development. In today’s competitive environment, these two are very, very important, so we decided let us have an episode discussing these. So, without any further ado, let’s begin!
What is SAFe?
SAFe is a knowledge base of proven, integrated principles, practices, and competencies for achieving business agility using Lean, Agile, and DevOps. The latest version of SAFe is SAFe 5, which is built around the seven core competencies of the lean enterprise that are critical to achieving and sustaining a competitive advantage in these increasingly digital times.
Now, what are these seven core competencies? These seven core competencies are:
- Lean-agile leadership
- Team and technical agility
- Agile product delivery
- Enterprise solution delivery
- Lean portfolio management
- Organizational agility, and
- Continuous learning culture
SAFe 5, the latest version of SAFe aims to enable the business agility that is required for enterprises to compete and thrive in the digital age.
Now, as we said before, SAFe is very important in today’s competitive and fast-paced times. So, if you would like to learn more about SAFe 5.1, a good step to take would be to be a Certified SAFe Agilist. And, you already know what you need to do to get started, right?
Having a project management team in place is one of the most important and useful things an organization could do. As an organization grows, the project in the organization grows in size and scale too, becoming more and more complex, making it indispensable to have a skilled professional project management team in place.
If you are an aspiring project manager, an existing project manager, an individual working in the project management team in any capacity, or in an organization that has embraced project management but still finding its feet, or just anybody who wishes to learn more about project management, this episode is going to be super useful for you, so keep listening.
The top five project management best practices for you:
- Always begin with a plan
- No such thing as Overcommunication
- Always keep documentation for everything
- Never underestimate the power of risk management
- Safeguard against Scope Creep
These five project management best practices will ensure that you as a project manager or your organization have effective and efficient project management operations in place. Always remember that is the little things that often get overlooked that make the world of a difference. This is what would set apart an outstanding project manager from an ordinary one, so what are you aspiring for?
Another thing that sets you apart from the crowd and helps you along on your journey to be an outstanding project manager is a Project Management Professional certification from the Project Management Institute. It is the world’s most recognized and most sought-after project management certification, it has immense international recognition and there is a burgeoning community of PMI-PMP certified project managers. Cognixia – your one-stop talent transformation solution provider helps you prepare for the PMP certification exam and earn your PMP credentials while juggling a full-time job, right from wherever you are.
Videos are often a stove-piped domain for developers. Streaming videos comes with a couple of challenges and technical issues. On the back end, there’s transcoding, trade-offs between file sizes, and computing when encoding as well as compression. For developers, making it possible to just playback videos on devices can bring unique challenges across platforms like Android, iOS, and web browsers. This also explains why there are so many video infrastructure providers and video player providers in the market.
Here come open-source video players like Video.js, jPlayer, MediaElement.js, Plyr, and Clapper. There are also some JavaScript-specific video players as well like the ReactPlayer, Videogular, Vue-core-video-player, and Stencil-video-player. And there are also some proprietary video players like JWPLayer, Bitmovin, Theo, Nexplayer, and castLabs. Every one of these players and categories comes with its pros and cons, and developers choose whatever they feel would best meet their requirements or whatever the organization feels is the best fit for their needs. But the biggest challenge that the developers face when working with videos is that these are all closed ecosystems.
Video as a web medium has been shackling up developers and applications letting highly specialized video engineers who have kept all the understanding of the back-end considerations for handling the media content close to their hearts. But open-source is helping developers break these shackles and making things easier as well as efficient for everybody.
Check out Cognixia’s DevOps training and certification course to learn more. You can visit our website and connect with us there or on any of our social media handles, our team will reach out to you and guide you around this. This DevOps training is 100% live online and instructor-led, plus you get a dedicated PoC throughout your course duration, access to all the learning material via our LMS, and so much more.
We talk about a designation or job title, if you may, that is gaining huge popularity, and why your organization might be needing this individual. We are talking about a Data Quality Manager. This designation did not exist much earlier but as more and more organizations but as more and more organizations engage with cloud computing and realize the true potential by unlocking valuable insights, having a data quality manager is the need of the hour for countless enterprises.
Who is a Data Quality Manager?
A data quality manager is an individual “responsible for assessing, managing, and maintaining the data quality across an organization.” The data quality manager works with various teams to ensure that all the data that is being collected and processed in the organization is consistently accurate and meets the regulatory requirements & compliances. Data quality management is an increasingly critical aspect in every business and if it is not seen as critical just yet in your organization.
According to the US Bureau of Labor Statistics Occupational Outlook Handbook, it is one of the fastest-growing job titles in the US. The same trend seems to reflect across the globe as more and more enterprises join the data analysis bandwagon. And if the experts are to be believed, which they must since they are the experts, the job title of data quality managers is expected to see a whopping 36% growth in the coming decade.
Cognixia’s Cloud Computing with AWS online training will help you prepare thoroughly for the AWS certification exam. Our pool of experienced, certified trainers have years of experience in the field and are best placed to guide you with everything you need to ace the AWS online certification exam. So, check out the live online hands-on instructor-led AWS training and certification opportunities with Cognixia.
An Agile Release Train (ART) is a network of Agile teams working to achieve the same objective. ARTs demand all teams implement, test, and deliver software or products.
But what exactly is PI in Agile? A program increment (PI) is a timeframe in which an ART provides additional value in the form of functional software or systems. Sprints are to Scrum teams what iterations are to Agile teams.
So, what does Agile PI planning mean? A program increment planning meeting is a face-to-face gathering of all teams involved in an Agile release train. The PI planning activity discusses the product strategy, chooses features, and determines team constraints. It enables everyone to collaborate to develop answers to possible bottlenecks before they occur. PI planning is critical in the Scaled Agile Framework (SAFe) to maintain the basic concepts of alignment, transparency, built-in quality, and program execution.
Why is PI planning important?
- Maintains team trust
- Improve UX advice
- Increase cross-collaboration
- Completes work quickly
- Fast decision-making
Effective PI planning steps
- Organizational preparation
- Content readiness
- Logistics planning & accessibility
What takes place at a PI planning event?
PI planning normally takes two days. It follows a standard plan with a presentation of the business setting and purpose, followed by team planning breakouts in which teams set their goals for the next program increment.
Each team submits a draught of their plans at the end of the first day of planning. The draughts are examined for risks and dependencies, and the teams collaborate to identify solutions.
The Leading SAFe certification training provides you with all of the skills and information you need to help the business align around shared goals and objectives. It will also help you enhance value generation and workflow from planning to delivery. Furthermore, the SAFe Agilist training & certification program will shed light on what makes organizations more customer-centric, as well as assist participants in learning how to execute SAFe alignment & planning events, such as PI planning.
We talk about two terms that get used interchangeably but don’t mean the same thing in reality – Data migration and Data integration. Both processes play very different roles in the data management and preparation lifecycle. While there are a few similarities between the two terms, there are also some significant differences that set the two apart.
What is Data Migration?
Data migration involves moving data from one location to another and would involve a change in the database, the application, or the storage. Data migration is usually undertaken when one needs to modernize the databases or the data warehouses need to be modernized or there is new data from new or old sources. There could be other reasons and causes too, but these are the most common ones.
The most common tools used for carrying out data migration are:
- CloverDX
- Microsoft SQL Server Migration Assistant
- IBM Informix
- AWS Cloud Data Migration
- Amazon DocumentDB
- IBM Cloud Migration Services
- Talend Open Studio
A good data migration tool should be able to let users schedule jobs, organize workflows, and map and profile data, while also letting one carry out post-migration audits.
What is Data Integration?
Data integration, as the name suggests involves integration or merging. Data integration involves merging data from different sources into one single database or a single data warehouse. Data integration plays an important role in helping organizations make better, more informed decisions while having access to better data quality and better data analysis.
Data integration is a commonly used process for building data warehouses, and improving reporting, querying, and analytics.
The most common tools used for data integration include:
- Integrate.io
- Azure Data Factory
- Oracle Data Integrator
- Dataddo
- Informatica
- Talend
A good data integration tool would enable users to write data to target systems, services, and/or applications that one aims to use.
Data integration and data migration are two very large topics to cover in the short time that one podcast episode permits, but if you are an aspiring cloud professional, data professional, or even an aspiring DevOps professional, you will delve deeper into it as you train and prepare to be a skilled professional in your field of interest.
What is the Metaverse?
Metaverse is a term used to describe a combination of virtual reality and mixed reality worlds that can be accessed through a browser or a headset which would let people have real-time interactions and experiences across distances. What’s even more interesting is that according to Bloomberg Business Analysis, the metaverse could potentially unlock nearly 800 billion dollar market opportunity! That is how huge the Metaverse is and is going to be.
the demand for IT service management is soaring as high as ever, with experts opining that the demand is only set to go higher, showing no signs of slowing down. In today’s fast-paced world, enterprises need to have the right talent in the right place to manage the challenges the enterprise might encounter as it goes on to embrace the new technologies, besides also being prepared for whatever the future might throw its way.
For the metaverse, just having skilled IT professionals is not enough. To ace the metaverse wave, there would be a need for individuals who can excel at IT functions while also being capable of working in cross-business units and cross-solution functions. This necessitates a wide range of experience and knowledge in the individual.
Let us take a minute here to just speculate about the various possible avenues that an enterprise could explore, based on what we know about the metaverse today:
- Create virtual versions of one’s existing products and services to sell in the metaverse
- Create virtual shops to sell real-world products and services in the metaverse
- Create a complementary range of products and services to offer with the real-world products and services to generate new revenue streams
- Create virtual spaces, events in the metaverse, or metaverse-exclusive communities to generate engagement, etc.
The emergence of the Metaverse-as-a-Service is evitable. To manage the services, one needs top-notch IT service management talent. The best ITSM talent would be ITIL certified, so if this is an area of interest for you, getting started on the ITIL certification career path is exactly what you need to do. The first step on the career path is the ITIL 4 Foundation certification, so you know what you need to do.
The AWS Elastic Beanstalk is an easy-to-use service from Amazon Web Services for deploying and scaling the web applications & services that are developed using Java, .Net, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers like Apache, Nginx, Passenger, and IIS.
With AWS Elastic Beanstalk, all one needs to do is upload their code and then the Elastic Beanstalk would automatically step in to handle the complete deployment process – from capacity provisioning and load balancing to auto-scaling and application health monitoring.
AWS Elastic Beanstalk is undoubtedly the fastest way to get web applications up and running on AWS. If you are working with a PHP, Java, Python, Ruby, Node.js, .NET, Go, or Docker web application, then AWS Elastic Beanstalk should be a preferred option for you.
At its core, the AWS Elastic Beanstalk uses the core AWS services such as the Amazon Elastic Compute Cloud or the Amazon EC2, Amazon Elastic Container Service (ECS), AWS Auto Scaling, and Elastic Load Balancing (ELB) for supporting applications to scale them up for handling traffic from millions of users spread across geographies.
we can understand why AWS cloud computing and AWS Elastic Beanstalk, in particular, have been extremely useful for some of the most known brands in the world like Zillow, Prezi, JellyButton Games, BMW, Crowd Chat, Samsung Business, etc., right?
So, that’s the primer on AWS Elastic Beanstalk. Now you know what is AWS Elastic Beanstalk, what it does, what are its most important features, and what are its key benefits. You can bookmark or save this episode, as it would be very useful when you are preparing for an interview or an exam, and you can always revisit it to refresh the information.
With that, we come to the end of this week’s episode of the Cognixia podcast. Thank you for tuning in, we hope you enjoyed listening to us today. Until next week then!
Hello everybody and welcome back to the Cognixia podcast!
The simplest answer to this question would be open source is anything that has a design that is publicly accessible, so people can modify and share it freely. The term ‘open source’ in the specific context of software came around to represent the unique approach that was being used to create software programs.
how does software become open-source?
Well, simply put, open-source software is software whose source code can be inspected, modified, and enhanced by anybody. Source code is the technical side of software that is not meant for the users to see, it dictates how software functions and what it does. It is usually the programmers who have access and visibility to the source code of any software, it is they who are responsible to ensure that the software performs the functions it is intended for, in the way it is designed, and eliminates any bugs that might be encountered.
Some open-source software also offers a copy-left license for users. A copy-left license is the opposite of a copyright. A copyleft license requires that any user who modifies the open-source software in any way would also be required to release the source code for the same along with the program. Furthermore, some open-source licenses require that any user who alters and shares an open-source program with anybody would also be required to share the source code of the modified program without charging a licensing fee for it.
One of the most popular open-source software in the world right now is Kubernetes. It has this huge popularity all over the world, and Kubernetes skills are highly valuable and sought-after in the market right now. So, if you are looking for the next big thing for your career and this is a route that appeals to you, reach out to us today to know more about our Docker and Kubernetes certification course. The training covers everything you need to know to become a Certified Kubernetes Application Developer. Now that should be a gigantic leap for your career, shouldn’t it?
The Formula 1 championship is going on in full swing with some nail-biting edge-of-the-seat action race after race. While Max Verstappen, the defending champion from last year is still leading the pack, the fight for the title and the constructors’ championship is super tight and entertaining.
For the uninitiated, Formula 1® racing began in 1950 and is the world’s most prestigious motor racing competition as well as the world’s most popular annual sporting series. Currently, the FIA Formula One World Championship TM runs from March to December spanning 23 races in 20 countries across four continents. In recent years, the F1 experience has transformed significantly – for the teams, drivers, crew, analysts and stewards, and even audiences – both remote and on-site.
One of the key technologies that have helped bring about major changes and advances to Formula 1 racing is cloud computing. If you follow the sport, you already know that F1 racing uses Amazon Web Services or AWS cloud computing platform from Amazon for its functioning. Cloud transformation has been one of the goals on the tech side for Formula 1 and to accelerate cloud transformation, Formula 1 is moving the large majority of its infrastructure from its on-premise data centers to AWS. Another focus area for Formula 1 has been the standardization of AWS’ machine learning and data analytics services. Together, Formula 1 and AWS are working hand-in-hand to enhance race strategies, data tracking systems, as well as digital broadcasts using a range of services from the AWS bundle, such as Amazon SageMaker, AWS Lambda, AWS serverless computing, AWS analytics, etc.
According to AWS, by sourcing historical data and using it to teach Amazon SageMaker complex machine learning algorithms, Formula 1 can predict race strategy outcomes with increasing accuracy for teams, cars, as well as drivers.
We come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us. AWS is a powerful partner to have for any enterprise, no matter what industry they operate in. To power revolutions such as these, you need to have the right skills and expertise.
Every week, we pick up a topic around one of the emerging digital technologies and discuss it in a little more depth, aiming to help our countless listeners from around the world set on a path to learn something new. From DevOps to Kubernetes, Cloud Computing to ITIL, we cover a wide range of topics on our podcast. We also take up topics suggested & requested by our audience in the podcast too, after you, our listeners are very, very important to us.
And today, we are taking up a topic you requested – What are the career growth options for Certified Scrum Masters? We have the list of questions you had and we are going to do our best to answer your questions.
Cognixia is offering some very attractive offers on our live online instructor-led Certified Scrum Master training and certification course, and if you would like to get started hit us up in our DMs, drop us a line via email, call us, send us a WhatsApp, get in touch with us on the chat on our website, anywhere you prefer, and our career development team will reach out to you and guide you ahead.
With that, we come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us, and we are super thankful that you took time out to listen to us.
A lot of organizations these days are moving to creating and working with cloud-native applications. If your organization is one of them, then you are most likely working with Kubernetes. Kubernetes, after all, is the de facto standard for building containerized applications around the world. In fact, according to a recent CNCF report, 96% of organizations are either already using Kubernetes or evaluating the prospect of using Kubernetes to build and manage their applications. Kubernetes has over 5.6 million users spread all over the globe, which when you look objectively, you realize represents 31% of back-end developers. 31% may not sound too huge, but remember it is 31% of developers using one single platform – that is huge. The remaining 69% is divided between so many different platforms. Now, that is a significant market share. Moreover, this figure grows year-over-year, pushing up the amount of data that Kubernetes generates as well, in turn helping improve the platform.
Kubernetes security mistakes
- Default Configurations
- Multiple Admins
- Unrestricted Access
- Assuming Isolation
- Vulnerable Imported YAMLs
- Keeping Sensitive Information in ConfigMaps
- Skipping Regular Scans
All these things are such simple, easy things to do, which is also probably why it gets skipped maybe? But not everything should have complex solutions and elaborate mechanisms. Sometimes, simple does the trick just fine, isn’t it? So is Kubernetes security. Ensure you don’t make these mistakes and you are already on your way to enhancing the security of your clusters.
With that, we come to the end of this week’s episode of the Cognixia podcast. We hope you enjoyed listening to us today.
Organization uses Microsoft Azure as its primary cloud computing platform. You have been working with implementing, managing, and monitoring your organization’s Azure environment, including tasks that involve virtual networks, storage, compute, identity, security, governance, etc. Now, you want to learn some more in the same area of expertise and want to validate your skills & expertise in the field. You look for training and certification that could help you in this regard. You find that Microsoft Azure has an official Microsoft Certification exam for this – the AZ-104: Microsoft Azure Administrator, after clearing which you will get the credentials of a Microsoft Certified Azure Administrator.
What should you do to convince your manager to get you Microsoft Certified?
-
Build your business case
-
Show your manager the bigger, better picture
-
Weigh everything on driving positive business outcomes
-
Be ready with your rebuttals
-
Highlight your loyalty and commitment to the team & the company
-
Present a post-training plan
This is where we would like to tell you about Cognixia’s AZ-104: Microsoft Azure Administrator training and certification course. Cognixia is a Microsoft Silver Partner and offers the complete portfolio of Microsoft Certification programs per the official exam outline.
With that, we come to the end of this week’s episode of the Cognixia podcast, hope you found it useful.
One such topic that got recommended to us by one of our listeners was to discuss the differences between a DevOps Architect and a DevOps Engineer. So often, we find these two titles being used interchangeably and it can get very confusing to know what each role entails.
What do DevOps Architects and DevOps Engineers do?
DevOps Architect
The DevOps Architect’s role is more conceptual and is more high-level. Their work revolves around overall software goals and business goals. They need to have a solid understanding of capabilities and constraints to do their roles.
DevOps Engineer
The DevOps Engineer’s role is more execution and implementation-oriented. Their background might be similar to that of a DevOps Architect, but their work is more on the realizing the plans side.
If we were to simplify things further, we would say, if an organization has a DevOps team then it most definitely needs DevOps engineers. If the organization does not deal with very complex deployments and has pretty fairly established operations and infrastructure tools & practices, then the organization could build a whole team and carry out their operations smoothly with just DevOps Engineers alone and may not feel the need for DevOps Architects.
However, if the organization has software architects or enterprise architects on board, then we would recommend the company also get some DevOps architects on board sooner rather than later.
Also, Cognixia’s DevOps online training courses are up with some amazing discounts right now, so do check them out and sign up as soon as possible before the seats run out.
We talk about automation and one of the most common areas in an organization that does not often get its de – the helpdesk.
Helpdesk as a function sees a lot of tasks that are repeatable and hence, automate-able. The best part, it is not even that expensive – in monetary terms and otherwise. For example, resetting passwords, unlocking accounts that got locked, assigning access to folders and applications, prioritizing and assigning incidents and service requests, managing tickets, etc.
Imagine these tasks were automated so you didn’t need to have specific individuals whose responsibility was performing these tasks. Can you see how many bottlenecks would get eliminated, how quickly and efficiently so many tasks could be performed, and how easier life would get for the helpdesk team as well as the stakeholders?
what happens when you use manual workflows in your helpdesks despite having tasks that can be automated?
First, your user satisfaction and trust take a hit. You know those people who have to keep sending emails and keep calling or reaching out to your helpdesk team on the company’s internal messenger, yeah, we have all been through that at some point, haven’t we?
Second, you lose time – yours as well as your customers’. This time lost could have been spent on doing more productive activities instead of on administrative drudgery.
Third, you lose energy. Let us accept it, those repetitive tasks we are talking about are frustrating. Waiting for them to get done is also frustrating. While a customer waits for the helpdesk executive to find the time to address their request
Fourth, you lose out on issues and projects that will escape through the cracks in your manual workflows. Tickets that got missed, queries that remained unaddressed, you know what we are talking about.
Fifth, you lose out on opportunities for knowledge sharing among the team. With manual workflows, the helpdesk team got so busy resetting passwords and unlocking systems for the customers
Sixth, and most importantly, the team loses its reputation and reliability. Now, this is an expensive affair, won’t you agree? If the customers are convinced that the helpdesk team is unreliable and cannot be trusted.
we are sure you understand the immense benefits of helpdesk automation packs, but let us highlight them for you to make a good business case for it. Here are some of the top benefits of helpdesk automation:
- Faster response times
- More accurate, automatic reporting
- Improved user-communication
- Skyrocketing productivity
- Increased staff satisfaction
- Focus on the user
ITIL 4 Foundation is your gateway to pursuing a flourishing career in IT service management and is the first step in the ITIL 4 certification pathway. So, don’t lose this opportunity, and reach out to us now!
welcome back to the Cognixia podcast! Thank you for tuning in, we really appreciate it. Each week, we pick up a new topic from the world of emerging technologies and talk about it in a little detail to help our listeners learn something new.
Serverless Architecture is quite the buzzword these days. Serverless architecture, if we remember correctly, is a term that was added to the technological stack just a few years ago and has since then, it has gained immense popularity, especially after the debut of AWS Lambda in 2014.
The eCommerce sector has seen remarkable expansion. Because they frequently handle high volumes of traffic at various times of the day and during different periods of the year. This, in addition to establishing, administering, and sustaining IT infrastructure in on-premises data centers, can pose hurdles to the scalability and expansion of their enterprises.
When you start developing an app, there are many unknown factors, beginning with how valuable it can be to users. It may be difficult to scale a poorly designed yet successful system. However, that is still a better choice than the alternative.
As a result, it is usually advised to begin with a small version or MVP and assess how well it works. And then add additional features in the form of microservices.
AWS offers all of the benefits of the cloud, including flexibility, shorter time-to-market, and elasticity, among other things. In terms of data availability and high transfer stability, AWS exceeds other cloud service providers on the market. It has been the leading cloud computing platform in the world, holding the largest market share in the market for so many years now.
Cognixia offers a hands-on live online instructor-led cloud computing with AWS training for individuals that covers all the important concepts to earn your AWS certification – from the fundamentals of cloud computing and AWS to more advanced concepts like the different cloud service models – PaaS, SaaS, IaaS; the Amazon Virtual Private Cloud, etc. So, if you would like to, and we do strongly recommend, do get AWS certified with Cognixia. Talk to us today to get started with the online training, our career development team would be happy to guide you.
Hello everybody and welcome back to the Cognixia podcast. As a software developer, one of the biggest challenges that one faces is how to make informed choices about which external software and products to use in their builds. It can be quite challenging to determine if a system that is being built is appropriately secured, and it becomes even more challenging when there is an external entity or third-party involved.
SLSA stands for Supply chain Levels for Software Artifacts. It is a security framework, we would say a checklist of standards and controls of sorts, to prevent tampering, improve the integrity, and secure packages & infrastructure in your projects, businesses, or enterprises. SLSA, in a way, represents how you can go from being safe enough to be as resilient as possible, no matter where you stand in the software supply chain. No matter what software you are building, a vulnerability can arise at any stage of the software supply chain. The more complex a system becomes, the more important it is to have the necessary checks and best practices in place to ensure that the artifact integrity is maintained and to ensure that the source code that the development team is counting on is the code that is being used.
Who is the SLSA for?
Now, you could be a developer, you could be a business or an enterprise, and the SLSA would still be suitable for you. SLSA compliance levels provide an industry standard, a recognizable level of protection and compliance. SLSA is adaptable and it is designed keeping in mind the wider security ecosystem. It is easy for just about anybody to adopt and use.
And with that, we come to the end of this week’s episode. If you are looking for DevOps certifications to validate your skills, do talk to us to learn more about our live, instructor-led, online learning solutions. Until next week then. Happy learning!
Hello everyone and welcome back to the Cognixia podcast.
We already know about the situation between Russia and Ukraine going on for quite some time now. It has been challenging times for Ukraine and corporations as well as governments from across the world have stepped in to help in whatever way they can. Ukraine too has stepped up and appreciated the help it has received. And if you have been keeping up with the news, we are sure you would have read about Microsoft and AWS having recently received the Ukraine Peace Prize for their cloud services. Google received the same prize back in May as well. So, what is this peace prize being awarded for, and how is cloud computing helping keep the peace?
Did you know that Ukraine has a ‘Minister of Digital Transformation’? Yes, they do. Mykhailo Fedorov is the current Vice Prime Minister of Ukraine as well as the Minister of Digital Transformation. We often see job titles in corporate organizations for individuals facilitating digital transformation in the company but not that often that we see an official government minister for the same, do we?
While there have been no specific details about why the Ukraine Peace Prize has been awarded to these cloud services companies, the Minister of Digital Transformation has said that Microsoft stands for truth and peace and they are glad to have Microsoft’s support. The Minister goes on to explain AWS’ contribution by saying that Amazon AWS literally saved their digital infrastructure – their state registries and critical databases which were migrated to the AWS cloud environment. He went on to elaborate that Ukraine is ready to cooperate on government technology solutions and reform the judicial sphere radically.
One thing all these news reports tell us quite simply is the importance of cloud computing and the need for urgent cloud migration. We live in uncertain times, and not just the Ukraine-Russia conflict, but the ongoing Coronavirus pandemic has proved it to us better than anything else could. Resilience is the need of the hour, and cloud computing is almost indispensable to enterprise resilience. Besides resilience, there are countless benefits of cloud migration – reduction in the total cost of ownership, faster time to delivery, enhanced opportunities for innovation, agility, flexibility, and ability to keep up with changing market demands & consumer needs, etc
But as individuals, what can you do? Well, you can sharpen your skills in working with cloud computing and help your organization realize the potential of the cloud. To accomplish any of these, your skills need to be top-notch. Would there even be a better way to do this than to have an official Microsoft Training or Amazon cloud certification validating your skills & expertise in the field? So, this is your opportunity to get trained and acquire the skills you need to be an outstanding cloud professional.
Voice-over by : Ankit Gupta
Hello everyone and welcome back to the Cognixia podcast. Every week we discuss a new topic in our episodes to help our audience learn something new and we are loving all the feedback and suggestions we are getting from you.
What is Containerization?
The simplest way we can put it is that Containerization is the building of applications using containers.
This begs the question – What are containers?
Containers are the solution to the constant challenge developers face of getting the software to run reliably when it is moved from one computing environment to another, say from the developer’s desktop to a testing environment, or from a staging environment to a production environment, or even from a physical machine in a data center to a virtual machine on the cloud.
Containerization and virtualization are two different processes but they have some similarities. Containerization and Virtualization both enable total isolation of applications to help them be operational in multiple environments. The key differences between containerization and virtualization lie in the size and the probabilities they deal with. Virtual machines are much larger than containers, running into gigabytes, while containers are much smaller running into megabytes.
What is Kubernetes?
Kubernetes is an open-source container orchestration platform that helps manage distributed containerized applications at large scales. It is, hands-down, the most popular tool for container orchestration in the world, usually the number one choice for most developers.
Cognixia's Docker and Kubernetes training that covers all the important aspects of working with containers, and focuses on the two most popular tools for working with containers – Docker and Kubernetes. It is 100% online, live, and instructor-led, the sessions take place over the weekends and are delivered by highly experienced instructors.
The metaverse is such a happening buzzword right now, everybody seems to be talking about it. Some of us know what it is, and some of us have been an active part of it, but there are a lot of us who would like to know more. Metaverse is indeed a very concept and it is evolving pretty quickly that the more you learn, there more there is to learn.
Mark Zuckerberg is talking about it, Satya Nadella is talking about it, and the tech houses are calling the Metaverse the future of the internet. But what is the Metaverse, really?
Kristi Woolsey, the associate director at BCG Plantinion, as reported by the Forbes magazine, says that the metaverse is a term that is used to describe a combination of the virtual reality and mixed reality worlds that can be accessed through a browser or a headset which would let people have real-time interactions and experiences across distances. She goes on to say that the current increase in attention to the metaverse is partly driven by the very recent ability to fully ‘own’ virtual objects experiences, or even land. Thanks to Blockchain, you could now define a virtual object and buy it and sell it. This has created new economies where everything is taking place virtually. Now, we understand, that a lot of you feel that paying real money for a virtual piece of land or a virtual object is a super crazy idea, but to put it into perspective, until many years back, purchasing domain names was also considered to be a very crazy idea – it was also a virtual piece of real estate of sorts. And today, purchasing domain names is no longer a crazy idea, it is a necessity.
According to the Bloomberg business analysis 2021, the metaverse could potentially unlock a nearly $800 billion market opportunity! Now, that’s a humongous amount, isn’t it?
We are a Microsoft Silver Partner offering the complete portfolio of the Microsoft Certification courses. So, talk to us today, drop us an email, give us a call, talk to us in the chat window on our website
We talk about Scrum Masters and Product Owners. Both individuals play critical roles in agile teams but what we often forget is that both the roles need each other to perform their roles effectively. Today, we will discuss how Product Owners need qualified, efficient, and skilled Scrum Masters to do due justice to their role.
who is a Scrum Master? A Scrum Master is a professional who serves as the leader of the team using Agile Project Management through the duration and course of a project. Scrum Masters facilitate all communication and collaboration between the various team players and the leadership team, working to ensure successful outcomes. A Scrum Master ensures that everybody understands their roles, responsibilities, and goals, that the right people are available and placed in the right roles to accomplish project goals, practice and inspire others to practice agile values, principles, & practices, work towards building a conducive environment to facilitate creative teamwork, encourage team members to proceed with the project at a sustainable pace to meet the goals in sync with the defined timelines, keep everyone motivated and charged to accomplish their tasks and perform their roles, work with the senior management, HR, etc. to manage and implement change in the organization to ensure the product teams have the powers they need and everybody is equipped with whatever they need to leverage the Agile practices. Besides this, Scrum Masters also prepare and facilitate meetings such as sprint planning, daily scrum, sprint review, sprint retrospective, product strategy, product roadmap workshops, etc.
Cognixia – the world’s leading digital talent transformation company offers thorough, hands-on, live, online, instructor-led Certified Scrum Master training for individuals and the corporate workforce. To know more about the training programs, get in touch with us today. And keep sending us your feedback and suggestions about the podcast, we truly enjoy reading your emails and DMs.
Risk management is quite the topic of the moment these days, and just a little Google search will tell you how very important it is. The nature of risk for businesses keeps evolving so keeping up with the latest threats and opportunities, could be from the perspective of security, climate, health, finance, technology, personnel, culture, etc. is very important. This is what is described as the VUCA environment, where VUCA stands for Volatile, Uncertain, Complex, and Ambiguous. Managing risks in the VUCA environment is becoming quite a high-stakes game now, with environmental factors, social factors, and governance factors, among others making it quite a critical task that is becoming a commonplace discussion in the boardroom.
With risks becoming so common and high stakes, don’t you think it is extremely important for everybody in the organization to understand these risks and how to manage & mitigate them? We do think so. We believe that while there are specialized skills and job roles that are dedicated to risk management and mitigation, effective risk management can be achieved better if everybody is involved in it and aware of it. This would require the enterprise to be better prepared and bring wider capabilities on board to combat the risks it encounters, which would be hugely beneficial for them too.
ITIL or the Information Technology Infrastructure Library is an IT service management framework of best practices that aims to help businesses manage risk, strengthen customer relations, and build an IT environment that is conducive to growth, scale, and change. Over time, it has undergone several revisions, with the latest version being ITIL 4. ITIL 4 focuses on automating processes, improving service management, and integrating IT into business such that IT functions no longer remain mere support functions for the business but emerge as critical value-generating functions instead.
To learn more about ITIL and to build a career in this field, we strongly recommend setting out on the ITIL 4 career path. This career path contains a host of internationally recognized certifications from Axelos, and you can train from Axelos authorized training organizations like Cognixia to prepare for the ITIL certification exams. The first step in the ITIL 4 career path is the ITIL 4 Foundation certification.
Voice-over by : Ankit Gupta
Platform engineering is the discipline of designing and building toolchains and workflows that enable self-service capabilities for the software engineering organizations in the cloud-native era.
Now that we know what is platform engineering, let us try to answer who is a platform engineer. A platform engineer is a person in an organization who provides an integrated product that covers the operational necessities of the entire lifecycle of an application. This integrated product that the platform engineers provide is often referred to as an Internal Developer Platform. Since we have set out to answer questions, let us also try to answer what is an Internal Developer Platform. An Internal Developer Platform or IDP is a layer of best-in-class tech and tooling that an engineering team would have at hand. The IDP would help the operations team to structure their setup and it also enables the development team to meet their needs.
We would like to quote Evan Bottcher from the renowned company, Thoughtworks, on this:
“Platforms are a foundation of self-service APIs, tools, services, knowledge, and support, which are arranged as a compelling internal product. Autonomous delivery teams can make use of the platform to deliver product features at a higher pace with reduced coordination.”
A platform engineer needs to have a Bachelor’s degree n computer science or engineering. They need to be adept with Python and other computer programming languages. They should be proficient in working with APIs. They need to be skilled in working with scripting and frameworks. And lastly, they should be well-versed in working with a range of operating systems.
we come to an end to this week’s episode of the Cognixia podcast. Keep sending us your feedback and suggestions. Until next week! Happy learning!
The most asked-about role we got this suggestion for, is the role of a cloud architect. Cloud architects are seeing quite a humongous demand in the market right now, and trust on this one, this demand is only going to keep soaring up as more and more organizations realize that they just cannot do without embracing cloud computing and migrating their resources to the cloud or perish!
With that in mind, in today’s episode, we will talk about the top five skills a cloud architect needs to succeed in his or her role. So, without further ado, let’s begin!
The top five skills every cloud architect must have are:
- Technical competency
- Sales skills
- Leadership skills
- Strong communication skills
- Solid business acumen
Cloud Computing with AWS training is, in fact, designed to help you ace the AWS Certified Cloud Solutions Architect – Associate certification exam, along with offering you multiple hands-on projects, to help you learn thoroughly and practically. Now, we’ll say it is not too fair to make that career growth wait, so talk to us, get certified, and move ahead in your career. What more can we say, until next week then! Stay tuned for our next episode and keep sending us your feedback and suggestions.
We had discussed some common cloud computing interview questions and we received a lot of positive feedback for the same. We are very glad it helped you in preparing for your interviews. So, this week, we are back with one more interview questions and answers episode. We will discuss some common questions you may encounter in a Kubernetes technical interview.
Kubernetes is an open-source distributed technology that is used for scheduling and executing containers in and across clusters. It is the go-to tool for container orchestration and is considered to be the de-facto standard for the same. The way the market stands, if you are building containerized applications, you would be using Kubernetes for sure.
Cognixia – the world’s leading digital talent transformation company offers a top-notch Docker and Kubernetes training and certification program which would help you learn all the important concepts and skills to ace a career in Kubernetes. The program is 100% live virtual instructor-led, making sure you can attend the program from anywhere. From the fundamentals of Docker and Kubernetes to running Kubernetes instances on Minikube, working with Kubernetes clusters, modifying workloads, working with the Kubernetes API specialized workloads, scaling deployments and application security, and understanding the complete container ecosystem, Cognixia’s Docker and Kubernetes online training covers everything. So, get started today!
we are talking about something that has become very critical for achieving those ambitious digital transformation goals that you or your organization has set – practices and frameworks like DevOps, Agile, Lean Management, etc., and how they fit with another very important framework – ITIL 4.
Agile, DevOps, Learn Management, and ITIL 4 are concepts that work very well together. They fit in well with each other and can together contribute to your digital transformation efforts.
The ITIL or the Information Technology Information Library was a set of books that were first published n the 1980s containing best practices, frameworks, methods, etc. published by the British Government. Since then, the books have evolved and been revised a few times, with ITIL 4 being the latest version. All the six publications that are part of the ITIL 4 library give due importance to other technology concepts, frameworks, methodologies, etc. that would be practiced in an organization apart from ITIL, such as Agile, Learn management, DevOps, etc. ITIL 4 pulls some of the best concepts from the leading best practices and methods followed by organizations everywhere and codifies them all into these six volumes. Together, ITIL 4 serves as a thorough reference for IT professionals at all levels and business leaders.
We offer the complete portfolio of ITIL 4 certifications and modules for individuals and the corporate workforce, of course, including and beginning with the ITIL 4 Foundation training and certification. We follow the official Axelos outline and guidelines for our ITIL training and at the end of the training, you get to appear for the official ITIL 4 Foundation certification exam.
Organizations are increasingly setting ambitious digital transformation goals to stay ahead in the market and make the most of the advances in technology. This is leading to enterprise developers facing severe burnout and exhaustion. Hiring new engineering expertise comes with unique challenges as the skills gap is growing wider and wider with time. So, how should one achieve their digital transformation goals?
According to the same survey, the top-most factor that is causing this developer burnout would be the increasing workload and the demands made of the developers from the other teams that they work with. A huge 39% of the individuals who participated in the survey stated that this was the top reason for the burnout. 37% of the individuals also felt that the pressures of the digital transformation goals of the organization were causing the developers to feel burnt out. 35% of the respondents also opined that they had been struggling to learn the skills that they were required to have to work with new technologies & approaches that the organization implements.
let us tell you about the findings of another study. This study conducted by Forrester found that about 10-15% of the surveyed enterprises are already using low code platforms like Unqork. Yet another study by Gartner has predicted that 65% of all the app development functions taking place in an organization will be performed by low code platforms by the year 2024.
With all the findings of these studies and surveys, you can understand that low code platforms could change the way the IT teams, especially the development function take place in an enterprise. It doesn’t exactly take intensive exhausting training for a non-IT background individual to take the plunge as a business technologist.
However, a little training can always be helpful for the individuals and the organization. And this is where Cognixia aims to help everyone. Our live online instructor-led DevOps training and certification program is just what you need to brush up on the fundamentals and learn all about the important tools, frameworks, best practices, etc. which can get you started in the field of software and application development. The course is designed by industry experts focusing on hands-on learning to ensure you are fully equipped with all the skills and knowledge you need for your role in the organization. So, do go to our website and check the course out.
Voice-over by: Ankit Gupta
There are a lot of organizations out there for whom the production operating systems revolve entirely around Red Hat Enterprise Linux. With each new version, Red Hat Enterprise Linux has pushed the bar higher on so many fronts.
The RHEL 9 will be available for the four architectures:
• Intel/AMD64
• ARM 64-bit
• IBM Power LE, and
• IBM Z
But what makes the Enterprise Linux 9 unique among all the versions so far is that it is the first release that is based on CentOS Stream, which has enabled developers everywhere to contribute to and test code thoroughly before release.
The system now offers improved container development by allowing you to base your containers on the RHEL 9 Beta UBI base images. These would be available in micro, minimal, and init images. If you have a fully subscribed RHEL 9 beta container host, it will even let you pull additional RPMS from the RHEL 9 beta repositories. Add to this, RHEL 9 now ships with cgroups2 by default, as well as with the latest version of Podman.
Cognixia is the official authorized training partner for Red Hat and we offer the complete portfolio of Red Hat training and certification for corporate workforce. Red Hat training has been found to enhance the productivity and efficiency of teams manifold and the Red Hat certifications offer one of the highest ROIs for teams among all IT certifications. So, talk to us today and we can discuss how we can help you meet your digital transformation goals and improve the performance of your teams with Red Hat training and certifications. We would love to know what you think of the RHEL 9 too.
we compare two top-notch DevOps tools – Terraform vs. Ansible. This should be an interesting comparison, considering how immensely popular both these tools are in the market today. We will cover some key points about both the tools and try to understand which tool among the two works best in which situation.
HashiCorp Terraform is an open-source Infrastructure-as-Code management tool created chiefly for orchestration and provisioning in data center environments. By itself, Terraform does not directly configure or install applications or software. Terraform is mainly used for creating, changing, and destroying servers to reach a particular desired end state. As a tool, Terraform has a declarative approach to network management.
Red Hat Ansible is also an Infrastructure-as-Code management tool. However, compared to Terraform, Ansible uses a procedural approach. This is the main way Ansible is different from Terraform – their approaches. With Ansible, user-defined steps are used in a configuration for achieving a desired state or change. So, if intend to add installations or software over existing networks, Ansible would be your go-to tool. Besides, Ansible is agentless, uses SSH or other authentication methods for communication, and is lightweight & efficient.
Our DevOps training course is live, online, and instructor-led and will help you gain an edge in the market while helping you accelerate your career. The course covers a whole bunch of tools as well as the important concepts and skills to help you grow your career in the field of DevOps.
According to Red Hat, a CI/CD pipeline is a series of steps that must be performed to deliver a new version of the software. CI/CD stands for Continuous Integration/ Continuous Delivery.
A CI/CD pipeline brings in the scope to monitor and automate the improvement of the application development processes, especially during the integration and testing phases as well as during the delivery and deployment phases. The CI/CD pipeline can be established using specific CI/CD tools. Two of the best CI/CD tools in the market currently are Bamboo and Jenkins. Of these, Jenkins has long been the gold standard in DevOps. Compared to this, Bamboo is a relatively newer tool but has become quite popular in a short time. Let us dig deeper into these two tools now.
Our DevOps training and certification course introduces learners to DevOps and its significance in software development. It talks about different software development methodologies, virtualization, different types of server virtualization, etc. It also covers working with the most important DevOps tools – from Vagrant to Jenkins, Docker to Kubernetes, Chef, and SaltStack to Pupper and Ansible, Nagios, and many more. It also covers a thorough discussion on CI/CD pipeline automation.
A hybrid multi-cloud architecture was deemed ideal for the great majority of respondents' organizations. Over half of those polled stated they plan to be utilizing a multi-cloud environment within the next one to three years.
The issue of the industry falling behind was virtually universal among those polled, with 90% agreeing that tackling this challenge needed a hybrid multi-cloud approach to ensure security, data integration, compatibility, security, and cost.
IT professionals in healthcare say that they have transferred apps to or from the cloud in the previous year, claiming data privacy and security as the main reasons.
Cognixia's Microsoft AZ-104 training prepares participants to acquire the Microsoft Azure Administrator certification, which validates their abilities and knowledge as an Azure administrator and distinguishes them from the competition.
Learn and upskill yourself from the comfort of your home with Cognixia's intuitive & comprehensive deep learning training.
Cloud computing is one of the leading digital technologies of today that offers a very wide range of opportunities for individuals to grow their careers. With the right skill set and knowledge in place, one can build a flourishing, successful career in cloud computing. You could be seeking an opportunity as a cloud administrator or a cloud developer or a specialist or any other role, there are some fundamental questions that you would likely be asked in your interview with potential employers. Let us seek to answer some of them
- How would you say cloud solutions compare against on-premise computing?
- what is your understanding of cloud computing? How would you define it in your words?
- what are the three most popular cloud service models?
- what about Function-as-a-Service?
- Suppose you have a fully functional cloud ecosystem in an organization, what would you say are the main constituents of this ecosystem?
- How would you explain the cloud computing architecture in simple terms, say to somebody who has a very basic understanding of technology?
- What would you say are the advantages of this serverless computing for an organization?
- If I was looking for an open-source cloud computing solution, what would you recommend?
- Why do you think microservices are important in cloud computing?
- Should an organization consider the hybrid cloud model? What does the model offer an organization?
We offer certification programs for Microsoft Azure, AWS Cloud Computing, as well as Google Cloud Platform. Besides, our programs are 100% live virtual instructor-led, giving you an opportunity to learn from the comfort of your home, over the weekends.
This podcast will help you grasp the major differences between the two main Machine Learning methodologies that serve as the foundation of those systems: Supervised & Unsupervised Learning.
The simplest answer would be - one utilizes labeled data to predict outputs, whereas the other does not.
However, you should be aware of several variables since they decide which strategy is best suited to the use case.
Cognixia is one of the world's leading digital talent transformation companies committed to providing you and your team with insightful digital technology training and certifications programs.
Cognixia's machine learning online trainingcourse discusses the most recent machine learning algorithms as well as the common threads that can be utilized in the future to learn a variety of methods.
According to PMI, a project is "a temporary endeavor undertaken to create a unique product, service, or result." By temporary, we mean a project with a clear beginning and end. And project management is described as "applying knowledge, expertise, tools, and procedures to project operations to achieve project goals."
These principles serve as a general guideline on how to run things. They may not offer all the answers or show you exactly what to do, but they point you in the right direction.
Cognixia's online PMP training explains the distinctions between project management & operations management.
Our PMP Certification Training intends to help professionals manage projects more efficiently and effectively by utilizing the Project Management Life Cycle.
Voice-over by : Ankit Gupta
Cloud expertise is in great demand, and because Amazon Web Services (AWS) is the most popular public cloud, AWS cloud computing certifications are a growing market. According to a report:
· Cloud certifications make an applicant more impactful to 82% of hiring managers.
· While evaluating applications or candidates, 87% of hiring managers prioritize hands-on industry experience and valid certifications instead of a university degree.
There is certainly a shortage of AWS-certified experts today. That is why professionals with cloud expertise are in high demand and they get to earn higher salaries.
If you know the companies you want to work for that uses AWS regularly, you should take the course and move ahead with the certification.
A cloud administrator is a technical expert who manages a company's cloud computing services. They are the experts in cloud & system administration, assisting in the secure and uninterrupted operation of a company's IT networks and systems.
A cloud administrator is responsible for transitioning locally hosted systems to the cloud, configuring cloud environments to match the company's objectives, and architecting data management systems. Their responsibilities also include maintenance tasks like responding to trouble reports and alarms, creating patches for any problems that might occur, and using cloud-native & serverless development methodologies for new apps.
Cognixia's Microsoft Azure training will prepare you for the Microsoft AZ-104: Microsoft Azure Administrator certification exam.
IT service management (ITSM) is a business strategy that combines information technology and other business processes into services that improve how their bundled services are delivered to the customers.
ITSM manages technology from the beginning to the end. Everything from service design to development, deployment, and support is recorded, regulated, and structured. The framework is a set of best practices telling how your organization should approach and engage with its technology.
ITIL is the accelerator for sustainable career advancement for every IT worker, regardless of stages. ITIL 4 certification, as the pinnacle of IT best practices, is the ideal approach for professionals to demonstrate to existing and future employers that they are ready to make an impact.
ITIL 4 will assist you in developing the knowledge and practical tools required to become more productive at work and generate optimal value within your company. Furthermore, you will be in a great position to improve your current service management methods, such as assessing and overseeing the efficacy of IT services. Finally, you will share a global language that will allow you to communicate with premier IT experts all around the world.
The world has been seeing a constant shift driven by innovations. With resources being scarce in nature, human resources are the most being relied upon. With right approach, human individuals can be trained and prepared in order to hone their talent to yield the desirable result. We, at Cognixia aim to build a skilled workforce to drive meaningful innovations. Cognixia is a Collabera Learning Solutions Company and the world’s leading digital talent transformation partner.
In the first episode of our podcast, we discuss about our approach towards creating and providing skilled workforce, our three main offerings – JUMP for enterprises, Rewire for enterprises, and Rewire Direct for individuals and our curricula.