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

Episode 14

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.

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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


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

About the Podcast

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Machine Learning Engineered
Helping you bring ML out of the lab and into products that people love.

About your host

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Charlie You

Charlie currently works as a Machine Learning Engineer at Workday. He graduated from RPI with a B.S. in Computer Science and taught himself ML through online courses and projects. In his free time, Charlie enjoys investing and trading, playing poker, and training Brazilian Jiu-Jitsu.