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François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast



Lex Fridman

François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with deep neural networks. It serves as an interface to several deep learning libraries, most popular of which is TensorFlow, and it was integrated into TensorFlow main codebase a while back. Aside from creating an exceptionally useful and popular library, François is also a world-class AI researcher and software engineer at Google, and is definitely an outspoken, if not controversial, personality in the AI world, especially in the realm of ideas around the future of artificial intelligence. This conversation is part of the Artificial Intelligence podcast.

INFO:
Podcast website: https://lexfridman.com/ai
Full episodes playlist: http://bit.ly/2EcbaKf
Clips playlist: http://bit.ly/2JYkbfZ

EPISODE LINKS:
François twitter: https://twitter.com/fchollet
François web: https://fchollet.com/

OUTLINE:
0:00 – Introduction
1:14 – Self-improving AGI
7:51 – What is intelligence?
15:23 – Science progress
26:57 – Fear of existential threats of AI
28:11 – Surprised by deep learning
30:38 – Keras and TensorFlow 2.0
42:28 – Software engineering on a large team
46:23 – Future of TensorFlow and Keras
47:53 – Current limits of deep learning
58:05 – Program synthesis
1:00:36 – Data and hand-crafting of architectures
1:08:37 – Concerns about short-term threats in AI
1:24:21 – Concerns about long-term existential threats from AI
1:29:11 – Feeling about creating AGI
1:33:49 – Does human-level intelligence need a body?
1:34:19 – Good test for intelligence
1:50:30 – AI winter

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39 thoughts on “François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast
  1. I really enjoyed this conversation with François. Here's the outline:
    0:00 – Introduction
    1:14 – Self-improving AGI
    7:51 – What is intelligence?
    15:23 – Science progress
    26:57 – Fear of existential threats of AI
    28:11 – Surprised by deep learning
    30:38 – Keras and TensorFlow 2.0
    42:28 – Software engineering on a large team
    46:23 – Future of TensorFlow and Keras
    47:53 – Current limits of deep learning
    58:05 – Program synthesis
    1:00:36 – Data and hand-crafting of architectures
    1:08:37 – Concerns about short-term threats in AI
    1:24:21 – Concerns about long-term existential threats from AI
    1:29:11 – Feeling about creating AGI
    1:33:49 – Does human-level intelligence need a body?
    1:34:19 – Good test for intelligence
    1:50:30 – AI winter

  2. This guy is obsessed with limitations. How can he not understand the human mind has no limitations. Every time we get to a point in technology where naysayers believe we are limited, we break through in a different substrate.

  3. Hey lex! Ur podcast is really very cool! I think it would be really great if you could invite few of these people in ur podcast: Sergey Levine,Szegedy, Mnih,David Silver,Noam Brown, Chelsea Finn,Andrej karpathy and few other people

  4. Love what Francois brought up at 1:16:31 . We've been working on an interface for controlling our RL model on news recommendations. It currently looks like this: https://ibb.co/Ht3cjXV
    We're working on a slider next to control the degree to which we add "random" news instead of the RL model's. Random being a list of top 40 publishers, where we filter to have one article per source and try to avoid duplicates.
    The news is currently down, having issues with the API provider. Hopefully coming back soon.

  5. From what I understand, his notion of "skill" is more of a measure of "adaptivity to a new environment"? Isn't that just redefining words? What about the skill to be able to improve yourself indefinitely? It's not trivial, or else everyone would be a champion of any field since you just need to practise again and again to become better…but isn't that the hardest part of anything? Being efficient to something withing a set of constraint is one part of the equation, but certainly not the best predictor of "skill" imho.

  6. Isn't intelligence all priors. Intelligence is a form of knowledge not an attribute that can be separated out from the other properties of the system/agent

  7. I submit that generally speaking news feeds and passive content consumption panders to impulsivity.. Should we be more deliberate in our procurement of information?

  8. This is wonderful, as always. Thank you very much (Lex for this series of podcasts, which I believe will be historical and of paramount cultural importance, and François for Keras ** and ** the sanity in a field where so many people go crazy about extrapolations) . Can anybody tell me how it is possible to get the "dead silence" when no one is speaking? Audacity achieves this?

  9. (1:47:00) I dont think Chollet is right about gendered facial discrimination being definitively socialized. 'That DNA doesnt change fast enough to cover our divergence from chimpanzees.' A pre existing facial discrimination hardware could have been part of the cause of that change, and a small change to that hardware might explain the difference. Conversely, and additionally, not identifying mates comes at a tremendous cost.

  10. They say dont read the comment section, but thats definitely not good advice for this chap. Youre doing an awesome job, Lex. I miss the technical in-the-know things as i have no education in the field, but i love thinking about the principles discussed in your podcasts. The thousand brains theory one was my favourite. Keep going at it! Thanks for your hard work. Peace

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