Deep Learning Alchemy
Simon discusses the lack of overarching theories in deep learning, highlighting the gap between experimental findings and theoretical explanations. He delves into the challenges of relying on unrealistic assumptions and the disconnect between empirical results and theoretical predictions.In this clip
From this podcast

Machine Learning Street Talk (MLST)
Understanding Deep Learning - Prof. SIMON PRINCE [STAFF FAVOURITE]
Related Questions
Why are neural networks hard to explain in the context of the episode Stephen Wolfram: ChatGPT and the Nature of Truth, Reality & Computation | Lex Fridman Podcast #376 and the clip Neural Nets and Symbolism?
Why are neural networks hard to explain in the context of the episode Stephen Wolfram: ChatGPT and the Nature of Truth, Reality & Computation | Lex Fridman Podcast #376 and the clip Neural Nets and Symbolism?
Why are neural networks hard to explain in the context of the episode Stephen Wolfram: ChatGPT and the Nature of Truth, Reality & Computation | Lex Fridman Podcast #376 and the clip Neural Nets and Symbolism?