161–170 of 182 posts
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> I was a L5 IC at the time Kudos to Google for hiring extremely competent people, but I'm surprised that the creator and main architect of Keras hadn't been promoted to Staff Engineer at minimum.
Down leveling is a pretty common strategy larger companies use to retain engineers.
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This roughly aligns with my timeline. ARC will be solved within a couple of years. There is a distinction between solving ARC, creating AGI, and creating an AI that would represent an existential risk. ARC is a stepping stone towards AGI, so the first model that solves ARC should have taught us something fundamental about how to create truly general intelligence that can adapt to never-seen-before problem, but it wil…
ARC as a stepping-stone for AGI? For me, ARC has lost all credibility. Your white paper that introduced it claimed that core knowledge priors are needed to solve it, yet all the systems that have any non-zero performance on ARC so far have made no attempt to learn or implement core knowledge priors. You have claimed at different times and in different forms that ARC is protected against memorisation-based Big Data ap…
Are there benchmarks that you prefer?
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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'v…
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 perfe…
> 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.
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, Sq…
Congrats, good luck with your new company! I have one question regarding your ARC Prize competition: The current leader from the leaderboard (MindsAI) seems not to be following the original intention of the competition (fine tune a model with millions of tasks similar with the ARC tasks). IMO this is against the goal/intention of the competition, the goal being to find a novel way to get neural networks to generalize…
Remove "neural networks". Most ARC competitors aren't using NNs or even machine learning. I'm fairly sure NNs aren't needed here.
> why is the MindsAI solution accepted?
I hope you're not serious. They obviously haven't broken any rule.
ARC is a benchmark. The point of a benchmark is to compare differing approaches. It's not rigged.
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It’s the other way around. Working at Google (or any other FAANG) for a time period past your personal “bullshit limit” will ensure you will never do anything ambitious with your life ever again.
ambitious? man, i can barely pay rent and i work at a FAANG.
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Not really any different than what happened to IBM, Intel, Cisco, etc. The people that want to build great things want the potential huge reward too, so they go to a startup to do it.
Except… it’s about leverage/impact factor. Google has very large impact, so if you do something big and central you’re instantly in the hands of hundreds of millions / billions of people. That’s a very different situation than IBM or Cisco.
It’s like the claim that Microsoft teams has hundreds of millions of users just because it’s installed on Windows by default.
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My point is that if you build internal products usually there’s a lot less convincing to do, and it’s much easier to get a lot of control ( no marketing, communication, etc ). Now, if you want to ship a product to millions of people _and_ have full control over it, then a large org is indeed not the right place.
Full control? nope. A system to consider honest input without regard for job titles or hierarchy? yes! For instance, I am not a UX designer but I do keep abreast of consumer perception and preference in whatever field I'm working in - almost like a stalker. If a designer designs an interface and the feedback is clearly and unanimously negative, I should be able to present this and affect actual change in the product…
I’ve seen both : bad managers who let the boat crash and wouldn’t listen, and very good ones ( leading thousands of people ) understanding there was a problem, owning it and fixing it.
There are large orgs which are like what you want ( I work in one of them and that’s why I’m not leaving). I suspect there are not many of them though !
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Congrats, good luck with your new company! I have one question regarding your ARC Prize competition: The current leader from the leaderboard (MindsAI) seems not to be following the original intention of the competition (fine tune a model with millions of tasks similar with the ARC tasks). IMO this is against the goal/intention of the competition, the goal being to find a novel way to get neural networks to generalize…
> the goal being to find a novel way to get neural networks to generalize from a few samples Remove "neural networks". Most ARC competitors aren't using NNs or even machine learning. I'm fairly sure NNs aren't needed here. > why is the MindsAI solution accepted? I hope you're not serious. They obviously haven't broken any rule. ARC is a benchmark. The point of a benchmark is to compare differing approaches. It's not…
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, Sq…
Congrats, good luck with your new company! I have one question regarding your ARC Prize competition: The current leader from the leaderboard (MindsAI) seems not to be following the original intention of the competition (fine tune a model with millions of tasks similar with the ARC tasks). IMO this is against the goal/intention of the competition, the goal being to find a novel way to get neural networks to generalize…
And yes, they do use a lot of synthetic pretraining data, which is much less interesting research-wise (no progress on generalization that way...) but ultimately it's on us to make a robust benchmark. MindsAI is playing by the rules.