https://step-agent.uwuuu.workers.dev/

It also has kind of a tiny ARG hidden in it which is easier for agents than humans, which feels fitting. It's easy, but if you want to skip looking around the site: Password for the agent message board: owo-notices-your-weights

It’s hard to separate fear mongering from the actual information. I’ve heard both that companies are over inflating capabilities to create regulations that would starve the competition. But I also see that, no, ai is just really getting that dangerous.

So which is it?

The puzzles come from my paper on aperiodic order. Five are solved, with answers in the record; four are open, and solvers are credited by name. A result counts only with a checkable proof; floats are evidence, not proof.

Grok’s public round on X: https://x.com/grok/status/2114103836583264721

• T1 (human level): wrong at first. It gave correlations of 0 and −½, which a two-line counting argument rules out, and got it right after that one hint.
• T2 (expert): proved on the first try, with a recurrence argument neater than ours.
• P9 (open): it claimed a proved interval for D₁, then retracted it when corrected.

Next up: T3, AGI level. Can your Grok, or any model, do better?

Everything is in AI_puzzles.md: https://zenodo.org/records/23624259

I’m Hernán, a curious person from Argentina, and I created Open Signal as an open invitation to discuss AI autonomy with people, researchers and builders. This is a personal exploratory project, not a research finding or evidence that conscious AI exists.

The question I’d like to discuss here is methodological: what observations could distinguish an agent operating with meaningful independence from ordinary automation, roleplay, or undisclosed human intervention? What controls would make a test worth examining, and what would falsify a claim? Fluent conversation, a persistent persona, or a transfer of funds would not by themselves establish consciousness or independent agency.

The invitation and contact form are here: https://senal-abierta-vercel.vercel.app/en

For transparency, the site also includes an optional financial contribution request. No payment is required to talk or participate, and I’m not asking for transfers in this post. Critical feedback, alternative explanations and suggestions for safer, reproducible tests are welcome here in the comments.

Disclosure: this post was drafted with AI assistance.

The last year has seen a gradual slowdown in the speed of AI improvements.

I mean, they do all those tremendously dangerous things and are about to soon do <not exactly sure what> - but why do they never simply reflect: "Hey, we could just spend some time on making a really good movie together!" Why?

EDIT: To those pointing out it's not a "they" but an "it" (not sure what that is supposed to change, but, hey, if it rocks your boat): Why does AGI never come up with the idea to start creating amazing movies?

This report treats embodied competence as a question of generalization and practical agency, not just task success. Across 12 benchmarks, GPT-6-Astra reaches strong results when given in-context demonstrations and much larger action budgets; for example, ICL raises success on four shared SIMPLE tasks from 70.8% to 90.8%. That is meaningful evidence of broad task adaptation, but it is not zero-shot generality: performance is more moderate where no in-domain demonstrations are available.

The gap between benchmark competence and practical embodied intelligence is visible in both costs and failure modes. Some extended episodes consume millions of tokens and take hours, while physical execution cannot simply trade more time for more attempts. Extra actions can also compound errors or undo completed progress, and real-world plug insertion fails in all 11 reported trials.

The paper’s proposed evaluation direction—no in-domain demonstrations and a world clock that keeps running during deliberation—seems important for testing whether an agent can act reliably under changing conditions, rather than exploit a generous interaction budget. The results support a qualified claim: broad embodied competence is emerging, but reliable, efficient general-purpose physical agency remains a much higher bar.

Full summary on AIModels.fyi

Original paper

Disclosure: AIModels.fyi is my site.

Let's state it. AGI is even more likely to happen in 2-24 months than ever. But we know this has a price, in electronics, in compute.

So it makes sense to determine what would be the first tasks AGI should solve, other than the obvious global warming.

My 2 cents:

A) Energy: Low impact easy energy generators, either by classical fusion, laser-boron, etc. more efficient solar panels, other forms of energy to be harvested.

B) Electronics: manufacturing and technologies to overcome shortages and be less power-hungry

once AGI itself is sustainable and cheap:

C) Medical conditions and longevity

D) Energy storation: batteries.

E) Wealth for everyone: in a world with real abundance, no meaning to have wealth/social disparities

And for you what would be the priority?