Explainability, Reasoning, Priors and GPT-3

Episode 18 of the Machine Learning Street Talk (MLST) podcast, hosted by Machine Learning Street Talk (MLST), titled "Explainability, Reasoning, Priors and GPT-3" was published on September 16, 2020 and runs 85 minutes.

September 16, 2020 ·85m · Machine Learning Street Talk (MLST)

Summary

This week Dr. Tim Scarfe and Dr. Keith Duggar discuss Explainability, Reasoning, Priors and GPT-3. We check out Christoph Molnar's book on intepretability, talk about priors vs experience in NNs, whether NNs are reasoning and also cover articles by Gary Marcus and Walid Saba critiquing deep learning. We finish with a brief discussion of Chollet's ARC challenge and intelligence paper.  00:00:00 Intro 00:01:17 Explainability and Christoph Molnars book on Intepretability 00:26:45 Explainability - Feature visualisation 00:33:28 Architecture / CPPNs 00:36:10 Invariance and data parsimony, priors and experience, manifolds 00:42:04 What NNs learn / logical view of modern AI (Walid Saba article) 00:47:10 Core knowledge 00:55:33 Priors vs experience  00:59:44 Mathematical reasoning  01:01:56 Gary Marcus on GPT-3  01:09:14 Can NNs reason at all?  01:18:05 Chollet intelligence paper/ARC challenge

Episode Description