Introduction

In episode 51 of The Gradient Podcast, Daniel Bashir speaks to François Chollet.

François is a Senior Staff Software Engineer at Google and creator of the Keras deep learning library, which has enabled many people (including me) to get their hands dirty with the world of deep learning. Francois is also the author of the book “Deep Learning with Python.” Francois is interested in understanding the nature of abstraction and developing algorithms capable of autonomous abstraction and democratizing the development and deployment of AI technology, among other topics. 

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Outline:

* (00:00) Intro + Daniel has far too much fun pronouncing “François Chollet”

* (02:00) How François got into AI

* (08:00) Keras and user experience, library as product, progressive disclosure of complexity

* (18:20) François’ comments on the state of ML frameworks and what different frameworks are useful for

* (23:00) On the Measure of Intelligence: historical perspectives

* (28:00) Intelligence vs cognition, overlaps

* (32:30) How core is Core Knowledge?

* (39:15) Cognition priors, metalearning priors

* (43:10) Defining intelligence

* (49:30) François’ comments on modern deep learning systems

* (55:50) Program synthesis as a path to intelligence

* (1:02:30) Difficulties on program synthesis

* (1:09:25) François’ concerns about current AI

* (1:14:30) The need for regulation

* (1:16:40) Thoughts on longtermism

* (1:23:30) Where we can expect exponential progress in AI

* (1:26:35) François’ advice on becoming a good engineer

* (1:29:03) Outro

Links:

* François’ personal page

* On the Measure of Intelligence

* Keras