Discover this podcast and so much more

Podcasts are free to enjoy without a subscription. We also offer ebooks, audiobooks, and so much more for just $11.99/month.

Explainability, Reasoning, Priors and GPT-3

Explainability, Reasoning, Priors and GPT-3

FromMachine Learning Street Talk (MLST)


Explainability, Reasoning, Priors and GPT-3

FromMachine Learning Street Talk (MLST)

ratings:
Length:
86 minutes
Released:
Sep 16, 2020
Format:
Podcast episode

Description

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
Released:
Sep 16, 2020
Format:
Podcast episode

Titles in the series (100)

This is the audio podcast for the ML Street Talk YouTube channel at https://www.youtube.com/c/MachineLearningStreetTalk Thanks for checking us out! We think that scientists and engineers are the heroes of our generation. Each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is unabashedly technical and non-commercial, so you will hear no annoying pitches. Corporate- and MBA-speak is banned on street talk, "data product", "digital transformation" are banned, we promise :) Dr. Tim Scarfe, Dr. Yannic Kilcher and Dr. Keith Duggar.