Less than a year to destroy Arc-AGI-2 - wow.
I unironically believe that arc-agi-3 will have a introduction to solved time of 1 month
ARC-AGI-3 has a nasty combo of spatial reasoning + explore/exploit. It's basically adversarial vs current AIs.
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The average ARC AGI 2 score for a single human is around 60%. "100% of tasks have been solved by at least 2 humans (many by more) in under 2 attempts. The average test-taker score was 60%." https://arcprize.org/arc-agi/2/
Worth keeping in mind that in this case the test takers were random members of the general public. The score of e.g. people with bachelor's degrees in science and engineering would be significantly higher.
Google is absolutely running away with it. The greatest trick they ever pulled was letting people think they were behind.
Their models might be impressive, but their products absolutely suck donkey balls. I’ve given Gemini web/cli two months and ran away back to ChatGPT. Seriously, it would just COMPLETELY forget context mid dialog. When asked about improving air quality it just gave me a list of (mediocre) air purifiers without asking for any context whatsoever, and I can list thousands of conversations like that. Shopping or comparing…
It is also one of the worst models to have a sort of ongoing conversation with.
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The idea that an AI lab would pay a small army of human artists to create training data for $animal on $transport just to cheat on my stupid benchmark delights me.
When you're spending trillions on capex, paying a couple of people to make some doodles in SVGs would not be a big expense.
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I must be holding these things wrong because I'm not seeing any of these God like superpowers everyone seem to enjoy.
Who said they’re godlike today? And yes, you are probably using them wrong if you don’t find them useful or don’t see the rapid improvement.
Every new model release neckbeards come out of the basements to tell us the singularity will be there in two more weeks
Not trained for agentic workflows yet unfortunately - this looks like it will be fantastic when they have an agent friendly one. Super exciting.
Its really weird how you all are begging to be replaced by llms, you think if agentic workflows get good enough you're going to keep your job? Or not have your salary reduced by 50%? If Agents get good enough it's not going to build some profitable startup for you (or whatever people think they're doing with the llm slot machines) because that implies that anyone else with access to that agent can just copy you, its…
it is interesting that the video demo is generating .stl model. I run a lot of tests of LLMs generating OpenSCAD code (as I have recently launched https://modelrift.com text-to-CAD AI editor) and Gemini 3 family LLMs are actually giving the best price-to-performance ratio now. But they are very, VERY far from being able to spit out a complex OpenSCAD model in one shot. So, I had to implement a full fledged "screensho…
We download the stl and import to bambu. Works pretty well. A direct push would be nice, but not necessary.
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François Chollet, creator of ARC-AGI, has consistently said that solving the benchmark does not mean we have AGI. It has always been meant as a stepping stone to encourage progress in the correct direction rather than as an indicator of reaching the destination. That's why he is working on ARC-AGI-3 (to be released in a few weeks) and ARC-AGI-4. His definition of reaching AGI, as I understand it, is when it becomes i…
> His definition of reaching AGI, as I understand it, is when it becomes impossible to construct the next version of ARC-AGI because we can no longer find tasks that are feasible for normal humans but unsolved by AI. That is the best definition I've yet to read. If something claims to be conscious and we can't prove it's not, we have no choice but to believe it. Thats said, I'm reminded of the impossible voting tests…
I think being better at this particular benchmark does not imply they're 'smarter'.
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Who said they’re godlike today? And yes, you are probably using them wrong if you don’t find them useful or don’t see the rapid improvement.
Let's come back in 12 months and discuss your singularity then. Meanwhile I spent like $30 on a few models as a test yesterday, none of them could tell me why my goroutine system was failing, even though it was painfully obvious (I purposefully added one too many wg.Done), gemini, codex, minimax 2.5, they all shat the bed on a very obvious problem but I am to believe they're 98% conscious and better at logic and math…
Projects:
https://github.com/alexispurslane/oxen
https://github.com/alexispurslane/org-lsp
(Note that org-lsp has a much improved version of the same indexer as oxen; the first was purely my design, the second I decided to listen to K2.5 more and it found a bunch of potential race conditions and fixed them)
shrug