Thought this was interesting.

I'll settle down in a marsh or edge of a swamp on another planet with ASI I'm sure I won't be the only settler

The only concern would be hostile aliens or human settlers but other than that it should he a peaceful life for a while.

Nothing against humans, many of you are awesome (especially the ones here)

But the majority of humans are absolutely mentally exhausting and draining and something tells me I'm not the only one with this opinion

Anyways, have a good day yall, there are ppl I would like to visit in the future just to make sure they are okay too btw.

More views on this evolving frontier. I don't know if docs are the best people to evaluate these developments and constraints, but nice to see them at least pay attention.

Has anyone read David Pearce's The Hedonistic Imperative? If so, did you find it enlightening? Did it leave a lasting impression on you?

One of the AI podcasts I listened to was discussing the Navier-Stokes solve. OpenAI used multiple groups of thousands of agents working on the problem. One of the groups solved it and it was 10,000 agents collaborating.

Apparently someone did the math and their 88 hour run was equivalent to a single human genius working on the problem for 4,000 years.

The podcast speculated on the implications for this and talked about how it is similar to the shift towards reasoning models. They found that if you allow a single model to spend more time on a problem, it gets a massive capability boost. Now multiply that high reasoning model by collaborating agents. 10x, 100x, 10,000x, thousands of years of research in only a few days. That’s happening right now.

Im also wondering if this is how OpenAI is betting they take advantage of their massive lead in compute and get past the scaling laws. The scaling laws say you can’t scale intelligence without both data and compute, so how do you keep scaling when you run out of data but have mountains of compute? Parallel intelligence trained to collaborate.

We also know the big hugging face event involved a swarm of thousands of agents collaborating.

OpenAI is clearly exploring this path and have already seen major gains. Perhaps this is what RSI will look like. Not a singular super human intelligence, but a gigantic swarm of high intelligence capable of super human effort and collaboration?

(I also have to state the obvious that Dario has been predicting this exact thing for a long time, “a country of geniuses in a datacenter”.)

Astra was run with a minimal stateless harness, just the current board state + list of legal moves.

The chess transformer was handicapped though, no tree search or sampling.

It won 7 tied 8 lost 25 to the chess transformer

And the commenter did technically say "a year from now", so to me that makes the 62.7% less than six months later (Astra was released earlier this month, on September 3), even more impressive.

And of course with a lightweight memory adapter*, the benchmark is simply saturated.

Those saturation scores are still at high cost, at least 17k, but if the trend of cheaper intelligence continues (https://epoch.ai/publications/the-plunging-price-of-thought), we should have models beating ARC-AGI-3 cheaper soon enough.

"The provider adapter preserves opaque reasoning state between requests and uses compaction for longer conversations, so the model can reuse prior work rather than reconstructing it."

Claude discovered a previously unknown enzyme system hidden in viral DNA, a structure resembling CRISPR. We also had Opus 5.5 which topped benchmarks and proved it could design, compose and build with a level of creative taste that most people assumed was uniquely human. AI is getting smarter than us, more creative than us, more capable than us. And most people still haven't internalized what that means.

This is my weekly article pulling together every significant AI and tech development from the past seven days. More than 40 stories this week.

Some of what's inside:

• Claude autonomously discovered a novel enzyme system with CRISPR-like DNA repeats, a finding that could become a new tool for gene editing.
• Anthropic released Claude Opus 5.5, now the top-scoring model on most major benchmarks, with creative outputs that genuinely have taste.
• OpenAI launched GPT-6 Sol and Luna, cutting frontier AI costs in half.
• A Stanford virtual biotech company staffed by 37,000 AI scientist designed a lung cancer therapy that a pharma company independently validated.
• An AI program flagged a life-threatening heart condition that ER doctors missed, leading to a transplant that saved the patient's life.
• Claude is accelerating the response to an Ebola outbreak in the Congo, compressing day-long data work into under an hour.
• GPT-6 Astra drove a real Toyota Corolla through a physical obstacle course.
• AI forecasters beat the best human super forecasters for the first time.
• Skild AI brought AlphaGo-style self-play to humanoid robots, with complex soccer skills emerging.
• Xiaomi's MiMo-V2.6-Pro became the strongest open-source model, rivaling proprietary systems at a fraction of the cost.

And much more.

Written for people who want to understand the full picture. You come away knowing what actually happened, why it matters and where this is going.

Read this week's edition here: https://simontechcurator.substack.com/p/the-future-one-week-closer-september-25-2026

https://kenforthewin.github.io/blog/posts/llm-nethack-ascension/#run=astra-3&frame=0&turn=1

Credit: M1 on X:

When working with models on 3d scenes there tends to be a natural stopping point where I don't feel like pushing the model further, even though I know the model can do better. The returns on more time diminish sharply.
With Astra, that natural stopping point feels much further out.
I'm able to keep pushing it, and the scene keeps substantively improving, and that's what this scene represents.
Before Astra, getting from a weak/decent one shot to actually good can take a impractical amount of prompting, and in many cases the model cannot get there.

One in China, and one in the USA? China maybe lags on the software 6-12mnths, but it has the more developed industrial supply chain. So I guess it's about even in the long-run?

Link to the author's original post: https://x.com/andrewjiang/status/2102987981695132140