The Data Scientist Podcast: Recent Episodes
Stylianos Kampakis
This is the official podcast of The Data Scientist (http://thedatascientist) and the Tesseract Academy (http://tesseract.academy).
Helping make data science and blockchain accessible to a non-technical audience.
For the full article please go to https://thedatascientist.com/ai-in-token-engineering-a-review/
Generative AI is empowering designers to explore new creative frontiers, enabling the synthesis of unique ideas and visual concepts at an unprecedented pace. It not only streamlines the design process by automating mundane tasks but also inspires innovation by offering a vast array of possibilities that were previously unimaginable or too time-consuming to explore.On this episode Bence Csernak, an experienced designer who's been in the space of Generative AI since 2017 shares his views.
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Tokenomics is the most important part of any Web3 project.
TokenLab is one of the best ways to simulate and stress test any kind of token economy. It is based upon the 6+ years of experience of Dr Kampakis in this area.
In this webinar, Dr Kampakis discusses topics such as:
1) What makes for a good token economy?
2) How can you stress test a token economy
3) How does TokenLab help you do all of the above?
In the rush to try out new and untested ideas, a clear pattern has shown up: many crypto projects prefer to copy successful plans, systems, and strategies from those that came before them. While showing that some methods work, this habit also highlights how careful many projects are when moving through the complicated world of token economies.https://thedatascientist.com
AI is changing everything. Whether you are a CEO, a senior professional or an entrepreneur, you need to adapt.
We discuss more in this podcast
Visit the https://tesseract.academy for more information about our AI and Web3.0 mastery program.
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The year 2023 was, without question, the year of the AI. Here are some of the things we witnessed.
- We saw the rise of ChatGPT.
- Google’s efforts to compete against OpenAI
- The drama with Sam Altman, his firing and re-hiring.
- Generative AI breaking into the mainstream
With everything that transpired in 2023, everyone’s been wondering what the next year holds for AI.
Join us at The Data Scientist for more content on AI, data science and Web3 !
Generative AI is taking the world by storm! On this episode, Alex from Elai.io, one of the biggest generative AI startups in the world, is sharing his views on the future of generative AI and synthetic humans!
AI Ethics is one of the hottest areas in AI right now. Join us as we discuss with distinguised expert Ali Uthman about the current and future state of this exciting area!
About the guest
Ali Uthman is an AI Ethics and Policy Strategist, Board Member, Advisor, and Speaker
Ali Uthman is deeply committed to fostering the ethical and responsible adoption of artificial intelligence, aiming to harness its potential for the greater good of humanity. With expertise in AI ethics, digital policy, human rights law, and strategic partnership development, he is dedicated to steering transformative change through thoughtful leadership and guidance.
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What is the current stage of AI? In this video, we discuss McKinsey's report on the progress of AI across industries.Make sure to go to https://thedatascientist.com for more content on AI, data science and Web3.0About Dr KampakisDr Stylianos (Stelios) Kampakis is a data scientist and tokenomics expert with more than 10 years of experience.He has worked with companies of all sizes: from startups to organisations like the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech, sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others.He has worked with many different types of technologies, from statistical models, to deep learning, to large language models. He has 2 patents pending to his name, and has published 3 books on data science, AI and data strategy.He has helped many people follow a career in data science and technology.His seminal work in token economics has led to many successful token economic designs using tools such as agent based modelling and game theory.He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy.🤖 http://tesseract.academy🤖 http://thedatascientist.com🤖 http://beyond-machine.com🤖 https://www.instagram.com/stelios_thedatascientist/🤖 https://twitter.com/s_kampakis#AI #ai #data #datascience #dataanalytics #datanalytics #analytics #artificial_intelligence #bigdata #tokenomics #web3.0 #web3 #blockchain #crypto
Data engineering has become one of the hottest topics in the data space. As companies scale, data pipelines become more complex and the volume of data grows exponentially.
This burgeoning data needs to be stored, processed, and analyzed efficiently to extract meaningful insights that can drive business decisions.
On today's episode, we discuss with Stefan and Elijah from DAGWorks about the future of data pipelines, and AI. DAGWorks is a data pipeline tool built for the forward-thinking data engineering team and is incrementally adoptable.
Make sure to go to https://thedatascientist.com for more content on AI, data science and Web3.
On this podcast we explore the current state of AI ethics and regulation.
Make sure to go to http://thedatascientist.com for more content around data science
"Predicting the unknown: The history and the future of AI and data science!" is my new book on data science, which you can get from Amazon.
As a society, we’re in a constant struggle to control uncertainty and predict the unknown. Quite often, we think of scientific fields and theories as being separate from each other. But a more careful investigation can uncover the common thread that ties many of those together. From ChatGPT, to Amazon’s Alexa, to Apple’s Siri, data science, and computer science have become part of our lives. In the meantime, the demand for data scientists has grown, as the field has been increasingly called the “sexiest profession.”
This book attempts to specifically cover this gap in literature between data science, machine learning and artificial intelligence (AI). How was uncertainty approached historically, and how has it evolved since? What schools of thought exist in philosophy, mathematics, and engineering, and what role did they play in the development of data science? It uses the history of data science as a stepping stone to explain what the future might hold.
Predicting the Unknown provides the framework that will help you understand where AI is headed, and how to best prepare for the world that’s coming in the next few years, both as a society and within a business. It is not technical and avoids equations or technical explanations, yet is written for the intellectually curious reader, and the technical expert interested in the historical details that can help contextualize how we got here.
Make sure to go to http://thedatascientist.com for more content on AI, data science and Web3.0
On this short episode Dr Kampakis covers the latest news on AI ethics, and explains why all leaders and organisations should care.
Make sure to go to http://thedatascientist.com for more content around data science
Ryan Janssen is the CEO of Zenlytic, merging LLMs, AI and business intelligence.
On this very interesting episode we talk about the power of LLMs, how a startup should approach LLM use, and what the future of AI holds!
Enjoy!
Make sure to go to thedatascientist.com for more content on AI, data science and Web3.0
Join Dr. Stylianos Kampakis and Dr. Clif Lewis, an organizational psychologist, in the much-awaited second installment of their discussion on AI and Organizational Culture.
This enriching conversation delves deeper into the transformative power of artificial intelligence and its profound implications on the fabric of modern-day businesses.
Make sure to go http://thedatascientist.com for more content on AI, data science and Web3.0
AI and Web3.0 are changing everything about society and the way we live.
Christos Makridis happens to be at the forefront of research in both areas.
We had the change to jump on a fascinating discussion about how generative AI affects our working lives, before talking about web3.0 and the current state of tokenomics.
We hope you enjoy it!
About the guest
Christos serves as a Research Professor at the W. P. Carey School of Business and Research Affiliate at the Global Security Initiative (both in Arizona State University), an Adjunct Associate Research Scholar at the Chazen Institute in Columbia Business School, a Digital Fellow at the Digital Economy Lab in Stanford University, a Non-resident Fellow at the Institute for Religious Studies at Baylor University, an Adjunct Scholar at the Manhattan Institute, a Senior Adviser at Gallup, a policy adviser, and an entrepreneur.
He is the CEO/co-founder of Dainamic, a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of Living Opera, a web3 startup working to bridge classical music and blockchain technologies.
Make sure to go to http://thedatascientist.com for more content around data science
What are the critical strategies that can ensure organizations optimize benefits from AI? How can firms refrain from dismissing employees to enhance productivity, but rather, amplify their performance tenfold through AI tool application training?
Join us as we delve into these topics and more with Dr. Clif Lewis in this installment of 'The Data Scientist' podcast!
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Artificial General Intelligence (AGI) stands as the holy grail in the realm of artificial intelligence. AGI refers to a type of AI that possesses the ability to understand, learn, and apply knowledge across a broad array of tasks at a level equal to or beyond that of a human.
With this understanding, our quest then becomes deciphering the intrinsic nature of AGI and its fundamental prerequisites. Are large language models (LLMs) like GPT-3 sufficient to achieve AGI, or is there a different route to explore?
TEDx Talker, philosopher, and technologist Josh Bachynski provides intriguing perspectives on these profound questions.
AI is creating profound challenges and opportunities for organisations.
At the centre of all this is organisational culture. In this series of short videos, me and Dr Clif P Lewis 🍎🍊 (he/him) are discussing the impact that #AI is having on businesses and how to best adapt in this new environment.
One thing that has become clear in the last few years is that there are no certainties. Whether it's #hybrid vs #remote vs #office, or #AI vs humans, there are going to be winners and losers. And human dynamics are one of the keys to success.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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I am very proud to announce that the tokenomics auditing framework is published by the Journal of the British Blockchain Association.
Tokenomics, the study of token economies, is a rapidly evolving field that originated around 2017 with the growth of Ethereum and the possibilities it offered for creating tokens. This led to the generation of artificial economies with novel incentive alignment. By 2018, the significance of tokenomics in the Web 3.0 space was widely recognized, driving innovations in blockchain like DeFi, whether through successful lending and borrowing protocols or failed experiments like Terra/Luna.
As blockchain adoption expands, the focus in tokenomics is transitioning from simple utility designs to complex, interconnected economies. One emerging trend is tokenomics auditing, a practice that examines and suggests improvements to token economy designs, which often become too complex to evaluate in practice.
The rise of tokenomics auditing represents a step towards standardization in the field. While still somewhat subjective, there is a growing push to develop an objective, expert-approved auditing framework. This would provide a structure for auditors to follow and assess token economies based on uniform criteria.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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In the rapidly evolving world of Web3.0, managing a treasury effectively is crucial for the success and sustainability of decentralized projects.We discuss this and more with Nik Pletikos from Sweat Economy!Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Angelo Art, a revolutionary platform, democratizes the fine art market by leveraging blockchain technology for fractionalization and tokenization. This process breaks down barriers to entry, making high-value art accessible to a wider range of investors.The platform creates a transparent, secure database for art transactions, combating the opacity long associated with the art world. Angelo Art's users can invest, collect, and support artists they believe in, tapping into the $68 billion annual fine art market.As blockchain technology evolves, its applications could extend beyond art, impacting traditional assets like real estate and fine wine. Angelo Art showcases the potential of blockchain to disrupt industries and make once-exclusive investments accessible to all.http://angelo.app
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Tokenomics refers to the economic and incentive system built into a cryptocurrency or blockchain project. It involves designing the distribution, supply, and usage of tokens in a way that promotes the health and growth of the project. Tokenomics can also include mechanisms for governing the project and for incentivizing stakeholders to participate in its development and use. Overall, the goal of tokenomics is to create a sustainable and valuable ecosystem around a cryptocurrency or blockchain project.
Tokenomics is a crucial aspect of the cryptocurrency and blockchain industry, as it plays a significant role in determining the success of a project. The design of the token economics should align with the goals and objectives of the project, while also ensuring that the incentives are balanced and fair for all stakeholders.
On this podcast we discuss tokenomics and DAOs with Luca Bazzuro!
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With AI getting adopted by every industry, leaders need to be able to understand what is the best way to go about data transformation.
Marcus Glowasz has dedicated his career to educating the c-suite on data, and on this podcast we discuss topics such as the best way to go about digital transformation, and what leaders need to know about AI.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Why are data products important? Why is the data mesh the next evolution of data engineering paradigms? What is the data fabric? We discuss this and more on this podcast with data products expert Jon Cooke!
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Have you ever wondered what the future of AI holds? How will AI be used to transform the way we work and live? Mark van Rijmenam, a world-renowned AI expert, explores these questions and more on the Data Scientist podcast.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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With the rapid advancement of artificial intelligence (AI) technology, many businesses are turning to AI to increase their efficiency and productivity. McKinsey's report on the state of AI for 2022 provides valuable insights into how AI will shape industries in the coming years.
We discuss more on this episode. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Finance is an industry that has been disrupted by data science and AI. The finance industry is one of the most data-driven industries out there. Traditionally, financial institutions have relied heavily on human experts to make decisions about investments and loans. But now, with the help of data science and AI, the finance industry has been revolutionized.
Data science and AI have helped financial institutions understand their customers better and provide them with financial services that are tailored to their needs. These technologies have also improved risk management in banks by predicting what might happen in the future based on past incidents.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Virtual reality, and augmented reality for data scienceVirtual reality (VR) is a computer-generated simulation of a three-dimensional image or environment that can be interacted with in a seemingly real or physical way by a person using special electronic equipment, such as virtual reality goggles. It is typically interactive, meaning the user can participate in the activity.
Companies are increasingly using VR to explore data. They use this to generate more insightful data visualizations and make it easier for the users to understand and interact with their data.
In this episode we discuss more with Jess and Jim!
Resources: https://business.penguinconnective.com/toolkits/xr-data-science/
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“The culture at a startup is typically what attracts people to join and what keeps the startup going.”
“Delays in hiring those executives or the recruitment of the wrong people can lead to strategic drift, spiraling costs, and a dysfunctional culture.”
-Harvard Business Review
In a business environment plagued by uncertainty and an industry characterised by constant change, organisational culture offers a means of organising your tech company in a manner that creates both meaning and value.
On this episode we discuss more with Dr Clif Lewis
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Neural networks are the backbone of deep learning, a branch of machine learning. Artificial intelligence (AI) is considered to be a subset of general AI. General artificial intelligence is the ability for a computer program to perform tasks that would otherwise require human intelligence or expertise. Neural networks work by filtering information and attempting to find patterns in that information.
One such neural network is called the Hopfield network; its typical use case includes pattern recognition tasks. It has been around since the 1980s, but some recent discoveries place it under a new light.
On this podcast we discuss about the relationship between the Hopfield network, deep learning and what's next for General AI with Tom Burns, a PhD researchers based in Okinawa, Japan.
Wanna become a data scientist? Book a call with my team: https://calendly.com/bill-beyondmachine
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One thing that has become clear in the last few years is that the soft parts of data science are becoming even more important. What do I mean by soft parts? I am referring to things such as AI ethics, or the interface between product and data science, which has given rise to what we call "product-led data science".
Kate Dudzik has a very interesting background. Pretty much like I did, she started by studying cognitive sciences, before moving on data science. This has given her a unique perspective on various things that more traditionally oriented data scientists might miss.
On this podcast we discuss more about these topics.
Wanna become a data scientist? Book a call with my team: https://calendly.com/bill-beyondmachine
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Customer churn is a major concern for any business. It is the process of customers leaving their service provider for a competitor’s service. Machine learning can be the solution to this problem.
On this podcast we explore more. Go to https://thedatascientist.com/customer-churn-machine-learning-data-science-survival-analysis/ for the original post
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Tokenomics is the study of token usage and the effects of a token’s design on its economics. Tokenomics is an important part of many blockchain projects because it ensures that the project has a sustainable business model that will make it profitable in the long-term.
One of the most commonly used tools in this space is the equation of exchange. On this podcast, I share some thoughts about this useful tool, and how it can be used in practice.
Read the original post: https://thedatascientist.com/token-appreciation-reflections-equation-exchange/
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The Tesseract Academy is proud to announce a new course for executives in collaboration with Sameer Rahman on the topic of data strategy and data maturity: https://tesseract.academy/courses/data-maturity-and-data-strategy/
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Marketing is one of the most data heavy fields in the world. So, it only makes sense that data science can help extract massive value from marketing data. However, marketers are often not taking proper advantage of the opportunity that data science presents in their field.
In this episode I explain more about my views on the topic, and what data science can offer to the world of marketing.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Deep learning is a type of machine learning that can be used to make predictions from data. It is a subset of machine learning and it has been around for a few decades.
In recent years, deep learning has made significant progress in many areas such as image recognition, speech recognition, natural language processing and translation.
Deep Learning is used in many real-world applications such as computer vision, autonomous vehicle driving, voice recognition and natural language processing among others.
The use cases of deep learning are limitless.
On this episode we discuss more.
Clay Hawkins is the CEO of the Open Music Exchange https://ome.audio/ a company that is revolutionising the world of music through blockchain. On this podcast we discuss with Clay his views on what blockchain can do for musicians, and what the future holds for this space.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Geospatial data analysis is an area that can bring a huge impact to agriculture, but it often doesn't get the attention it deserves. On this podcast, we discuss more with Lina from EOS Data Analytics.
EOS Data Analytics provides Earth observation solutions for smart decision-making in 22+ industries, with the main focus on agriculture and forestry. The company combines data retrieved from satellite imagery with AI technologies and proprietary algorithms to analyze the state of crops within farms and trees growing in forest stands to drive businesses and implement sustainable practices globally. The EOSDA’s mission is to preserve the Planet by equipping the decision-makers with the tools for tackling today’s most urgent challenges. To find out more, visit the website: https://bit.ly/3OoYJ1R
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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The cryptomarket is melting. Could decentralisation be the answer? We comment on this and more with Lance Parker from BankX.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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What is the future of the crypto market? Are we in a bear market? Does data science have a role to play in blockchain? We discuss this and a lot more with Michael Kelly on this podcast!
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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AI adoption for the enterprise is on the rise. The advantages of AI are clear - it can automate repetitive tasks, it can provide predictive insights to businesses and it can improve customer experience.
Sean Muller is providing his insights about what enterprises are doing well, what not, and what challenges AI adoption is facing.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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This discussion was recorded on 11/5/2022. At the time of recording TerraUSD is crashing at is at $0.5. This is a discussion with Lance Parker from BankX https://bankx.io/ commenting on the current developments, and the future of algorithmic stablecoins.
Make sure to go to http://thedatascientist.com
for more content around data science, AI and blockchain.
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Companies like Bloomberg, or Stats Perform are some of the best examples of data businesses. These companies collect, curate and then package data in a way that data can be used to create value in many different use cases.
Creating a startup in this space is not something easy. Data businesses are peculiar, but when they work, they work very well and scale.
On this podcast we discuss this very interesting subject. This episode is based on a very interesting post by the Pivotal newsletter, written by Abraham Thomas.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Tokenomics is the study of how a token's design and implementation affects its ability to achieve its goal. I had the opportunity to design and execute the tokenomics audit of the BankX token. On this podcast, I discuss more about this topic and some lessons I learned from this project. I hope you enjoy it!
https://youtu.be/KpfawToUSpQ
Make sure to go to http://thedatascientist.com
for more content around data science, AI and blockchain.
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The business of AI is growing rapidly. In the next few years, it is expected that the AI market will grow to $60 billion. This growth is driven by a number of factors such as increased investment in research and development, increased demand for AI-powered products and services, and a shift in the way businesses operate.
That being said, there many peculiarities to how AI is applied in business. We discuss this on more podcast.
Make sure to go to http://thedatascientist.com
for more content around data science, AI and blockchain.
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What does data science have to do with cybersecurity? Is AI the next big thing in cyberdefense? The cybersecurity industry is a $170 billion market, and this market size is only going to increase in the future. AI has largely been seen as a separate field to cybersecurity, but many people believe that it might actually be an integral part of the future of cyberdefense.
On this exciting joint episode, I am joined by Stanley Li and Sean Mahoney from Netswitch , as we get the change to discuss about the future of autonomous systems in cybersecurity.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Noah Healy is a mathematician and data scientist who has developed his own version of game theory, and is applying this in the areas of tokenomics and blockchain. We discuss more on this very interesting episode!
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Adopting AI is not always easy. However, there are different paths to adoption. Surprisingly, anomaly detection, which is one of the least recognised areas (but one of the most useful) of AI, can provide a path to adoption.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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There are different types of data scientists, something which I have written extensively on my blog The Data Scientist. This is a topic that is particularly close to me, as I have discussed it in the past, but I am also talking about it on my workshops and seminars.
On this episode, we are talking about an interesting report by O’Reilly called The Care and Feeding of Data Scientists that talks about the same topic.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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In this podcast, we will explore some of the most common questions that come up around data privacy and GDPR: what is personal information? What is a company’s responsibility to its customers? How can a company make sure it has consent from the customer to use their personal information? How can startups and corporates best prepare for the new regulation that is looming on the horizon? Punit Bhatia shares his unique insights.
What makes a company successful? What separates the failed startups from the unicorns? Alessandra has decided to study this problem and is digging deep into some of the biggest tech companies like Slack, and Buffer, and the stories of how they came to be. If you are an entrepreneur, this episode is a must listen!
Make sure to go to http://thedatascientist.com
for more content around data science, AI and blockchain.
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The role of a CIO has changed significantly over the years as data has become more important to organizations' success. In the past, a CIO was responsible for the IT infrastructure and not much else. Nowadays, this is just one of many responsibilities that a CIO undertakes.
On this episode Mark Chillingworth comments on the current state of CIOs and what their future might bring.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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What makes a business successful? What it's like to be an entrepreneur in post-Brexit UK? Matija Kovac has created and scaled a successful machine translation business. On this podcast he shares his valuable experiences. Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
Deep learning has been one of the most important discoveries in the history of AI. On this episode I am talking about this exciting technology, and why it is so important.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
This is a recording of a presentation conducted for Cambridge University's Entrepreneurship Centre, where we discussed about the different business model options AI entrepreneurs have.
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
Blockchain and data science are two of the hottest technologies right now. It is not often that you hear about both of them being used in tandem.
However, one company is doing exactly that. I had the chance to interview Freddy Zwanzger from Anyblock Analytics. Anyblock Analytics allows anyone to analyse data from various blockchains, through their API. This is fascinating for anyone who wants to dig deep into the blockchain, and discover interesting patterns. This can be anything, from crypto trading, to decentralised finance.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
Everyone's talking about AI, but very few are actually doing it. On this episode, I share some thoughts about how organisations can adopt AI more easily and discuss some best practices in this area.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
Is no-code and low-code the future of tech? On this episode we discuss this topic, and many more (such as whether Austin Texas will overtake the Sillicon Valley) with Andy Zambito from Creatio.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
Curtis Boyd went from earning minimum wage to becoming a data scientist, and running a company of 11 people! On this episode we are talking about this transition, what it takes to become a data scientist, and learn more about the challenge of classifying fake reviews using machine learning.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
As AI is playing a larger and larger role into our lives, the conversation around topics such as AI ethics and bias becomes hotter and hotter. On this interview, we talk with Daniel Bashir about these topics and his upcoming book: Towards Machine Learning Literacy.
Make sure to support Daniel's campaign on indiegogo:
https://www.indiegogo.com/projects/towards-machine-literacy-by-daniel-bashir#/
Make sure to go to http://thedatascientist.com for more content around data science, AI and blockchain.
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Deep learning is one of the most popular technologies in the space of data science. On this episode we share a few things about the history of deep learning and how it became the most successful approach in artificial intelligence.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services.
Healthcare is one of the industries that AI is revolutionising. From diagnostic systems, to better predictions, to doctor chatbots, AI is revolutionising this space. Learn more about the how on this episode.
Make sure to go to The Data Scientist for more content around data science, AI and blockchain.
AI (artificial intelligence) technologies and solutions can potentially transform your business. To make the most of the opportunities that AI offers, you need to choose the right AI/data science vendor, both for your business and the solution you want to develop.
The following seven tips will help with the process of selecting the right AI vendor.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services.
What does it take to start a data science school? Data science education is a serious topic. With the shortage of data scientists the world is suffering from, it is important to make sure that there are enough of them! On this episode Shaun Dippnall shares his view on what it takes to create a successful data science program.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
Erica Stanford is the CEO of the Crypto Curry Club. She spent all of the lockdown of 2020 doing research into crypto scams and she is about to publish a book on that topic!
On this episode we discuss about this topic and many more things (like Elon Musk's market manipulation, dogecoin, and other crypto-related matters).
The episode is a bit longer (45 minutes) cause we had so much to talk about! We hope you enjoy it!
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
Can anyone become a data scientist? I have been working for many years in the space of data science education, and I've seen a bit of everything, from undergraduates, to people over 40s trying to switch careers. On this episode, I give my own perspective on this topic.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
What does an enterprise data scientist do? What role does data strategy play in data science adoption? Learn more on these very interesting topics through this discussion with Martin Neuhard, who is an enterprise data scientist, and also a member of the International Association For Data Quality.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
What it's like to build a blockchain business? Yasir Qayam and his team have built one from the ground up called KwikTrust. Learn more on this very interesting interview on which we discuss many interesting topics: from due dilligence on blockchain, to which blockchain is the best one to use for a new company.
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
Joseh Yacura is the founder of The International Association For Data Quality, Governance and Analytics (IADQGA)of which I am also a proud member.
On this interview are discussing an amazing document that the association published around audit guidelines for supply chains. This document is available on the association's website.
We hope you enjoy this interview!
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
Data strategy is one of the most important parts of any data science project. Unfortunately, it is not very recognised.
Most data science/AI projects fail, as the result of the lack of a data strategy. This is one of the reasons that on this podcast, I have talked a lot about the importance of data strategy for companies of all stages and sizes.
On this interview, we are talking with Ruben Sardaryan, who is a data strategy expert from Toronto. One of the most interesting bits of this interview is the explanation of the difference between data tactics and data strategy. Most companies focus on the former, but should really focus on the latter.
We hope you enjoy this interesting conversation!
Make sure to read more news and stories about data science and AI at The Data Scientist and check out the Tesseract Academy if you are interested in data strategy services
What are the different types of data? Data scientists are familiar with terms like structured and unstructured data, many leaders are lost. In this episode, we discuss more about these types of data what are the business implications.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
On this episode, we are talking with Amanda Brock from OpenUK. OpenUK is a UK-based not-for-profit company which supports open source collaboration and open technologies within the United Kingdom. Its primary stated focus is to develop and sustain UK leadership in Open Technology, comprised of open source software, open source hardware and open data.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
A famous article by the Harvard Business Review breaks down data strategy in two types: offense and defense. Which are you should focus on depends on the type of business you are in. On this episode we are discussing more about this interesting topic.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
Stanford's new AI index is out! This index reviews all developments in AI that took place in 2020. On this episode we will discuss the most interesting findings from this index. This is also a rare episode during which I am sharing my screen! :) So, I hope you enjoy it!
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
On this podcast we are talking about a very interesting piece of research. Scientists from MIT used an AI to run simulations on the economy, and came up with different economic proposals and models. This raises question as to whether AI will actually be used in policy in the future. I am talking more about this on this podcast.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
On this episode, I am interviewing Nick Jordan from narrative.io
Nick offers a unique perspective on what is happening in the world of data acquisition and monetization and the role technology is playing in enabling data scientists and businesses to gain access to proprietary data to help feed their models without it taking months.
This is a very interesting discussion, talking about API-ization, data mesh, data streaming and other topics!
I hope you enjoy it!
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
AI is exploding, and there had never been a better time to start an AI business than now. On this podcast we discuss how you can do it.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
Also make sure to check out Tesseract Academy's new program to learn how to build an AI business!
Artificial intelligence and automation will bring huge changes to the economy. There are many opinions being heard. Some believe that AI will bring mass unemployment, and others believe that AI will increase productivity dramatically. On this episode, we explore more.
Make sure to visit The Data Scientist for more content around data science, AI, and blockchain.
McKinsey recently released a report outlying their findings around AI for 2020. On this podcast we discuss the most interesting findings from this report.
Learn more about data science at The Data Scientist.
AI and art is an area that I am a huge fan of. This is why I am organising a Meetup in this area
On this podcast I discuss some of the my thoughts after the November 2020 meetup. We had the chance to have with us 4 great speakers, and we discussed about a multitude of topics, including the future of this area. I would be very interested to hear what everyone else thinks. Feel free to get in touch through The Data Scientist.
Advances in natural language processing and deep learning make us question what is the meaning of intelligence. I was recently reading this very interesting article by the gradient: https://thegradient.pub/gpt2-and-the-nature-of-intelligence/ . The article refers to GPT2, but with GPT3 already, the questions it poses are more relevant than ever.
On this podcast I discuss about this very controversial topic: does the fact that neural networks handle language on a human-like level means that they are really intelligent?
Make sure to read more about data science and AI at The Data Scientist
AI is disseminating into all sciences. On this very interesting episode I am discussing an interesting piece of research I read, about how agent-base modelling and AI can be used to improve economic models. It looks like the policy makers of the future might be robots, instead of humans. Maybe this will actually help make our world better! :)
Make sure to read more about data science and AI at The Data Scientist
The Analytics Engineer acts as the bridge between data engineers and data analysts. It is their job to build well tested, up to date and documented datasets that the rest of the company can use to answer their own questions. Learn more about this role on this podcast!
Make sure to read more about data science and AI at The Data Scientist
Data is the new oil. So what makes it valuable? How can companies in the data science/AI space make sure they maximise the value of their data? Learn more on this podcast!
Make sure to read more about this topic and other topics related to data science and AI at The Data Scientist.
Predictive analytics is one of the most popular applications of data science. In this podcast we talk more about this field and discuss about its various applications.
Make sure to read more about this topic at https://thedatascientist.com
One of the biggest dilemmas for decision makers is whether they should build their tech teams in-house or whether they should outsource. This is a big dilemma both for startups and entrepreneurs. The right choice can save you lots of money, time and effort.
On this episode, we discuss about this very interesting topic.
Make sure to read more about this topic at https://thedatascientist.com
AI promises to improve many parts of our lives and society. However, is it really going to positively impact the economy? On this podcast, I discuss a concept called "So-so AI", which might completely change the way we view AI and its impact on the economy.
Make sure to read more about this topic at https://thedatascientist.com
Is AI going to overtake humans in most tasks? Are jobs threatened? We have heard many voices over the last few years warning against huge social and economic changes coming as the result of automation. But what is AI really as smart as we think it is? Let's see what is really the case.
Make sure to read more about this topic at https://thedatascientist.com
I have been teaching data science for many years, and I've come to know some of the pros and cons of different solutions in data science education, from universities to bootcamps. This is why I decided that we need is a next generation data science bootcamp which combines the best methods from different modes of learning.
Learn more on this episode!
Learn more at http://dataly.st and follow my work at http://thedatascientist.com
Recommender systems are one of the most useful technologies for B2C companies. Learn more about recommender systems on this episode!
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The coronavirus pandemic has shocked the markets, and society on a global level. What changes is it going to bring to the economy and how will this affect AI companies? What opportunities are going to arise? Learn more in this episode!
Read more about this topic at https://thedatascientist.com/covid-19-ai-industry/
Why is it so difficult to forecast significant events like the current COVID-19 pandemic? In this episode we discuss the reasons that make forecasting a difficult problem, and under what conditions we can have good forecasts.
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Is AI overhyped? As a data scientist, I have implemented many real world systems that had a significant impact. However, AI is often oversold, and we hear all kinds of crazy stories, which make people believe that terminator style robots are just around the corner.
What is really the case? We explore more on this episode.
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Does history repeat itself? How would World War II have turned out if different strategic decisions had been taken? How would civilisation have unfolded if prominent figures hadn't been born?
Historians like to speculate about these kind of questions. But what if there was a data-driven way to study these hypotheses? On this episode we discuss how data science can help historians answer these type of questions and understand the factors that move history.
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There are many people (including prominent figures like Elon Musk, or the late Stephen Hawking) claiming that AI is a threat to humanity. But is it really? In this episode, we dig deeper into this subject and uncover the truth.
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With the world facing an unprecedented crisis, how can AI be used in order to help fight against the pandemic of COVID-19?
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The future of consumer businesses, like retail, lies with advanced personalisation. Context-aware recommender systems will play a major role in this revolution, which will allow shops to suggest the right product at the right time, increasing revenue dramatically. In this episode we discuss more about this amazing technology.
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Causal inference is one of the most exciting topics in machine learning. Some prominent researchers, like Judea Pearl believe that we will never be able to create true AI until we crack this. In this podcast we discuss more.
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There are many different processes to create data product. The drivetrain approach is one such approach discussed on O'Reilly's blog. In this episode, I elaborate on how this approach can help a business use data science, and I compare it to other data science processes, such as the Predict-and-Optimise framework.
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The Mozilla Foundation published a very interesting report, based on a survey where they asked people what they think of AI. The results are surprising and interesting. In this episode, I comment on the report.
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Dynamic pricing is one of the hottest applications for any retail business. I have built up a conceptual framework, called PAO (predict-and-optimise) which can help you create a dynamic pricing pipeline. Learn more in this podcast!
Source: https://thedatascientist.com/dynamic-pricing-pao-framework/
You have probably heard about business coaching, but what about data science coaching? Data science is unique in the tech world, because it directly interacts with the business model. This means that it often starts at the executive level, and not in the tech department.
The data science coach is a role that comes to cover this gap, explaining to decision makers, how data science should be implemented within a company, in order to maximise business value.
This idea has largely been based on my work with the Tesseract Academy, through which I have run multiple workshops for executives from small to big organisations. There is also an article on The Data Scientist website, for those who are interested to learn more on the subject.
Google recently reviewed their 2019 AI research (https://ai.googleblog.com/2020/01/google-research-looking-back-at-2019.html). In this episode I am summarising the article and providing my own opinion on some of the advancements achieved by Google.
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Artificial intelligence is disrupting many industries, and HR is one of them. Learn more in this episode!
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Andrew Ng is one of the biggest names in artificial intelligence. He published a guide which he calls the "AI transformation playbook" in which he outlines some of the principles behind successful AI projects. In this episode, we will discuss upon this playbook, and how you could use some of these principles in your own business.
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China has been progressing rapidly in AI research in the last few years. However, for many years Chinese papers had been blamed for their poor quality. But this is now changing. On this episode, we discuss whether China will become the top data science superpower in the next few years.
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With 2020 now ahead of us, let's reflect on 2019's blockchain landscape by commenting on Deloitte's excellent survey.
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Link to survey: https://www2.deloitte.com/us/en/insights/topics/understanding-blockchain-potential/global-blockchain-survey.html
A recent article in the Significance magazine (https://www.significancemagazine.com/) raised the opinion that many statisticians are in roles that do not really add any value to society. If that's true, then there are tremendous implications that need to be discussed. On this episode, we talk about this issue, and unravel the truth.
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The real estate sector is one that many claim is about to be disrupted by blockchain. However, there have also been many setbacks, with real estate blockchain companies closing down. So, what is really going on?
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Data science consists of different sub-fields, which can be confusing for newcomers. One of the most common questions asked is "so, what is the difference between machine learning and AI?". And few people can give a correct answer to this question.
This episode discusses the different core fields of data science, and how they relate to each other: statistics, machine learning and AI.
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Are distributed ledgers and blockchain useful for anything? While blockchain has been lauded as a way to solve many problems, in practice there are not that many case studies. On this episode we discuss what is hype and what is reality.
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On this episode, we are discussing a recent report by the Bank of England, regarding the use of machine learning in financial institutions. Original report can be found at https://www.bankofengland.co.uk/report/2019/machine-learning-in-uk-financial-services
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Hiring data scientists is not easy. One of the important things to know is that data scientists come in different groups, with different skills and abilities. This podcast discuss about the "tribes" of data scientists, and how to make sure to choose the right one for your business.
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