Yannic Kilcher: Explaining Papers on Youtube, Why Peer Review is Broken, and the Future of the Field

Yannic Kilcher is PhD candidate at ETH Zurich researching deep learning, structured learning, and optimization for large and high-dimensional data. He produces videos on his enormously popular Youtube channel breaking down recent ML papers. Follow Yannic on Twitter: https://twitter.com/ykilcher Check out Yannic's excellent Youtube channel: https://www.youtube.com/channel/UCZHmQk67mSJgfCCTn7xBfew Listen to the ML Street Talk podcast: https://podcasts.apple.com/us/podcast/machine-learning-street-talk/id1510472996 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 Follow Charlie on Twitter: https://twitter.com/CharlieYouAI Subscribe to ML Engineered: https://mlengineered.com/listen Comments? Questions? Submit them here: http://bit.ly/mle-survey Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/ Timestamps: 02:40 Yannic Kilcher 07:05 Research for his PhD thesis and plans for the future 12:05 How he produces videos for his enormously popular Youtube channel 21:50 Yannic's research process: choosing what to read and how he reads for understanding 27:30 Why ML conference peer review is broken and what a better solution looks like 45:20 On the field's obsession with state of the art 48:30 Is deep learning is the future of AI? Is attention all you need? 56:10 Is AI overhyped right now? 01:01:00 Community Questions 01:13:30 Yannic flips the script and asks me about what I do 01:25:30 Rapid fire questions Links: Yannic's amazing Youtube Channel Yannic's Google Scholar Yannic's Community Discord Channel On the Measure of Intelligence: arXiv paper and Yannic's video series How I Read a Paper: Facebook's DETR (Video Tutorial) An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (Paper Explained) Zero to One The Gulag Archipelago