A link to a login wall is just spam.

I’m okay with the downvotes. There’s a stronger anti-AI sentiment now than even just a month ago, and on the whole I think that’s going to be a good thing.

Yes, it was released in March. One important point is that these results are based on the semi-private test set. Perhaps it’s best to wait until it is measured against the fully private test set, but that might not happen for months.

I agree with most of this. I’ve also said in the past that LLMs cannot think, and I think that’s still true for most models. The reason ARC-AGI-3 is interesting is that it was specifically designed to test reasoning, adaptability, novel problem solving, planning, memory, etc. So it was a surprise to me that Astra was able to defeat it so effectively, and that Astra invents algebras for each novel task.

But I agree we can’t trust OpenAI if these results are self-reported, and we may not be able to trust the ARC Prize Foundation fully either. Extraordinary claims require extraordinary evidence, so we need replication, transparency, and proper open science to confirm things.

I also agree with ARC Prize’s conclusion, that there are still capabilities any AI system would need to demonstrate before we can claim a full general intelligence.

I guess this is being down-voted just because it feels pro-AI. Believe me I get it, you can look at my anti-AI post history. But I think it’s important to also keep an eye out for real signals towards general intelligence, which is why I wanted to share this. I’m not celebrating it, just bringing awareness.

They basically pass the buck to the individual developer without taking any responsibility themselves.

Debian acknowledges that the legal status of material produced by generative AI systems remains the subject of ongoing discussion in many jurisdictions, including questions relating to copyright, authorship, licensing, and potential reproduction of training material.

The responsibility for every contribution rests with the contributor who submits it, who remains accountable for its technical quality, legal acceptability, and suitability for inclusion in Debian.

“It may be illegal or against FOSS, but that’s up to you to decide, good luck I guess”

ARC Prize maintains multiple tracks around their benchmarks. They have “verified” leaderboards, “community” leaderboards, and they also run the ARC Prize competition.

They update the “verified” leaderboards when they test raw LLMs without sophisticated harnesses. They seem to update this sporadically and only occasionally do press releases or blog posts about new scores. For example, the latest score from Claude Opus 5 (High) is 30% at $20,000, and they didn’t post about that as far as I know. Again, this just the raw LLM without an agentic or world-model harness.

The ARC Prize competition has a harder set of criteria. Participants have to use smaller, open models with a limited compute budget, with open source code, and of course the solutions are verified by ARC Prize at the end of the competition.

The “community” leaderboards, which is what this post is about, are self-reported and not verified by ARC Prize. There are no restrictions on what model is used or limitations on compute. So naturally they aren’t going to make official news releases about those, unless they decide to verify them at some point.

The only reason I chose to post this is that the top solutions seem legitimate, with source code released, and two of them have associated papers.

It think it’s still unwise to talk about these topics in broad terms like AGI and even “intelligence”. We still have to pick the capabilities apart to have useful discussions about them. I agree these games are better tests than many benchmarks, but it’s also important to note that these solutions use a combination of well-designed deterministic harnesses, as well as LLMs. So it’s inaccurate to say that “LLMs have achieved AGI” (not sure if that’s what you were getting at). This feels like an important milestone, but we’ll have to continue to probe for failure cases in other categories of problems.

Aside from emotional intelligence, experience, embodiment, etc., these ARC-AGI-3 solutions all rely on the sandbox being a safe environment to fail. They iterate through the problem thousands of times before coming to a final solution. Many real-world human problems cannot be re-tried safely or efficiently.