#51 Francois Chollet - Intelligence and Generalisation

episode

Machine Learning Street Talk (MLST) not yet transcribed

▲ 0

Transcript

This episode hasn't been transcribed yet Upvotes decide what gets transcribed next — 0 so far. Sign in to upvote

More from Machine Learning Street Talk (MLST)

VAEs Are Energy-Based Models? [Dr. Jeff Beck] 46 min · 25 Jan 2026

Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta] 53 min · 23 Jan 2026

Why Every Brain Metaphor in History Has Been Wrong [SPECIAL EDITION] 42 min · 23 Jan 2026

Adversarial Examples and Data Modelling - Andrew Ilyas (MIT) 1h 28m · 22 Aug 2024

All episodes from Machine Learning Street Talk (MLST) →

Report any issue

Source

Recorded16 Apr 2021

Publisheranchor.fm ↗

Handlerec:2107494

Show notes

In today's show we are joined by Francois Chollet, I have been inspired by Francois ever since I read his Deep Learning with Python book and started using the Keras library which he invented many, many years ago. Francois has a clarity of thought that I've never seen in any other human being! He has extremely interesting views on intelligence as generalisation, abstraction and an information conversation ratio. He wrote on the measure of intelligence at the end of 2019 and it had a huge impact on my thinking. He thinks that NNs can only model continuous problems, which have a smooth learnable manifold and that many "type 2" problems which involve reasoning and/or planning are not suitable for NNs. He thinks that many problems have type 1 and type 2 enmeshed together. He thinks that the future of AI must include program synthesis to allow us to generalise broadly from a few examples, but the search could be guided by neural networks because the search space is interpolative to some extent. https://youtu.be/J0p_thJJnoo Tim's Whimsical notes; https://whimsical.com/chollet-show-QQ2atZUoRR3yFDsxKVzCbj

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.