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Francois Chollet is leaving Google

(developers.googleblog.com)
377 points xnx | 3 comments | 13 Nov 24 22:28 UTC | HN request time: 0.002s | source
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fchollet ◴[14 Nov 24 07:27 UTC] No.42133844[source]▶
Hi HN, Francois here. Happy to answer any questions!

Here's a start --

"Did you get poached by Anthropic/etc": No, I am starting a new company with a friend. We will announce more about it in due time!

"Who uses Keras in production": Off the top of my head the current list includes Midjourney, YouTube, Waymo, Google across many products (even Ads started moving to Keras recently!), Netflix, Spotify, Snap, GrubHub, Square/Block, X/Twitter, and many non-tech companies like United, JPM, Orange, Walmart, etc. In total Keras has ~2M developers and powers ML at many companies big and small. This isn't all TF -- many of our users have started running Keras on JAX or PyTorch.

"Why did you decide to merge Keras into TensorFlow in 2019": I didn't! The decision was made in 2018 by the TF leads -- I was a L5 IC at the time and that was an L8 decision. The TF team was huge at the time, 50+ people, while Keras was just me and the open-source community. In retrospect I think Keras would have been better off as an independent multi-backend framework -- but that would have required me quitting Google back then. Making Keras multi-backend again in 2023 has been one of my favorite projects to work on, both from the engineering & architecture side of things but also because the product is truly great (also, I love JAX)!

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trott ◴[14 Nov 24 08:13 UTC] No.42134092[source]▶
Congrats, François, and good luck!

Q: The ARC Prize blog mentions that you plan to make ARC harder for machines and easier for humans. I'm curious if it will be adapted to resist scaling the training dataset (Like what BARC did -- see my other comment here)? As it stands today, I feel like the easiest approach to solving it would be BARC x10 or so, rather than algorithmic inventions.

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fchollet ◴[14 Nov 24 08:18 UTC] No.42134128[source]▶
Right, one rather uninteresting line of approaches to ARC consists of trying to anticipate what might be in the test set, by generating millions of synthetic tasks. This can only work on relatively simple tasks, since the chance of task collision (between the test set and what you generate) is very low for any sophisticated task.

ARC 2 will improve on ARC 1 by making tasks less brute-forceable (both in the sense of making in harder to find the solution program by generating random programs built on a DSL, and in the sense of making it harder to guess the test tasks via brute force task generation). We'll keep the human facing difficulty roughly constant, which will be controlled via human testing.

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1. versteegen ◴[14 Nov 24 10:07 UTC] No.42134679[source]▶
Hi! As someone who spent the last month pouring myself into the ARC challenge (which has been lots of fun, thanks so much for creating it), I'm happy to see it made harder, but please make it harder by requiring more reasoning, not by requiring more human-like visual perception! ARC is almost perfect as a benchmark for analogical reasoning, except for the need for lots of image processing as well. [Edit: however, I've realised that perception is representation, so requiring it is a good thing.]

Any plan for more validation data to match the new harder testset?

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2. Skylyz ◴[14 Nov 24 14:05 UTC] No.42136224[source]▶
I had never thought about how close perception and reasoning are from a computational point of view, the parts of ARC that we call "reasoning" seem to just be operations that the human brain is not predisposed to solve easily.

A very interesting corollary is that the first AGIs might be way better thinkers than humans by default because of how they can seamlessly integrate new programs into their cognition in a perfect symbiosis with computers.

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3. versteegen ◴[14 Nov 24 23:57 UTC] No.42142627[source]▶
Perception is the representation of raw inputs into a form useful for further processing, but it is not a feed-forward computation. You repeatedly re-represent what you see as you keep looking. Particularly something like an ARC puzzle where you have to find a representation that reveals the pattern. That's what my ARC solver is about (I did not finish it for the deadline).

> A very interesting corollary is that the first AGIs might be way better thinkers than humans by default

I agree at least this far. Human System 2 cognition has some very severe limitations (especially working memory, speed, and error rate) which an AGI probably would not have. Beyond fixing those limitations, I agree with François that we shouldn't assume there aren't diminishing intelligence returns to better mental architectures.