Letitia Parcalabescu is a PhD candidate at the University of Heidelberg focused on multi-modal machine learning, specifically with vision and language. Learn more about Letitia: https://www.cl.uni-heidelberg.de/~parcalabescu/ (https://www.cl.uni-heidelberg.de/~parcalabescu/) https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA (https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA) Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://bitly.com/mle-newsletter (http://bitly.com/mle-newsletter) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/ (https://www.givingwhatwecan.org/) Subscribe to ML Engineered: https://mlengineered.com/listen (https://mlengineered.com/listen) Comments? Questions? Submit them here: http://bitly.com/mle-survey (http://bitly.com/mle-survey) Timestamps: 01:30 Follow Charlie on Twitter (https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI)) 02:40 Letitia Parcalabescu 03:55 How she got started in CS and ML 07:20 What is multi-modal machine learning? (https://www.youtube.com/playlist?list=PLpZBeKTZRGPNKxoNaeMD9GViU_aH_HJab (https://www.youtube.com/playlist?list=PLpZBeKTZRGPNKxoNaeMD9GViU_aH_HJab)) 16:55 Most exciting use-cases for ML 20:45 The 5 stages of machine understanding (https://www.youtube.com/watch?v=-niprVHNrgI (https://www.youtube.com/watch?v=-niprVHNrgI)) 23:15 The future of multi-modal ML (GPT-50?) 27:00 The importance of communicating AI breakthroughs to the general public 37:40 Positive applications of the future “GPT-50” 43:35 Letitia’s CVPR paper on phrase grounding (https://openaccess.thecvf.com/content_CVPRW_2020/papers/w56/Parcalabescu_Exploring_Phrase_Grounding_Without_Training_Contextualisation_and_Extension_to_Text-Based_CVPRW_2020_paper.pdf (https://openaccess.thecvf.com/content_CVPRW_2020/papers/w56/Parcalabescu_Exploring_Phrase_Grounding_Without_Training_Contextualisation_and_Extension_to_Text-Based_CVPRW_2020_paper.pdf)) 53:15 ViLBERT: is attention all you need in multi-modal ML? (https://arxiv.org/abs/1908.02265 (https://arxiv.org/abs/1908.02265)) 57:00 Preventing “modality dominance” 01:03:25 How she keeps up in such a fast-moving field 01:10:50 Why she started her AI Coffee Break YouTube Channel (https://www.youtube.com/c/AICoffeeBreakwithLetitiaParcalabescu/ (https://www.youtube.com/c/AICoffeeBreakwithLetitiaParcalabescu/)) 01:18:10 Rapid fire questions Links: https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA (AI Coffee Break Youtube Channel) https://openaccess.thecvf.com/content_CVPRW_2020/papers/w56/Parcalabescu_Exploring_Phrase_Grounding_Without_Training_Contextualisation_and_Extension_to_Text-Based_CVPRW_2020_paper.pdf (Exploring Phrase Grounding without Training) https://www.youtube.com/playlist?list=PLpZBeKTZRGPNKxoNaeMD9GViU_aH_HJab (AI Coffee Break series on Multi-Modal learning) https://www.youtube.com/watch?v=-niprVHNrgI (What does it take for an AI to understand language?) https://arxiv.org/abs/1908.02265 (ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations)