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Review - Machine Learning and Bayesian inference (Jens Jasche)
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Yann LeCun: World Models: Enabling the next AI revolution
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Neel Nanda – Mechanistic Interpretability: A Whirlwind Tour
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This Physicist May Have Just Solved Quantum Gravity
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Terence Tao: Nobody Understands Why AI Actually Works
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Predicting the rules behind - Deep Symbolic Regression for Recurrent Sequences (w/ author interview)
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Is the Future of Linear Algebra.. Random?
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ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein
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Interpretable Machine Learning with SymbolicRegression.jl | Miles Cranmer | JuliaCon 2023
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ETH Zürich AISE: Symbolic Regression and Model Discovery
![Yann LeCun's $1B Bet Against LLMs [Part 1]](https://i.ytimg.com/vi/kYkIdXwW2AE/hqdefault.jpg?sqp=-oaymwEjCNACELwBSFryq4qpAxUIARUAAAAAGAElAADIQj0AgKJDeAE=&rs=AOn4CLDbV4izF3i-wxevCVIn7FJjoy1vlA)
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Yann LeCun's $1B Bet Against LLMs [Part 1]
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Geoffrey Hinton reveals the surprising truth about AI’s limits and potential
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The Hardest Questions in Physics | World Science Festival
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Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
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This is not the AI we were promised | The Royal Society
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A Philosophical Look at System Dynamics
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How AI Cracked the Protein Folding Code and Won a Nobel Prize
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The Potential for AI in Science and Mathematics - Terence Tao
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Is AI Hiding Its Full Power? With Geoffrey Hinton
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