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THROUGH THE VALLEY

1/ AI is getting better at building the next AI - OpenAI has apparently automated training experimental models, according to The Information, while Anthropic says AI now leads ~26% of its R&D work and collaborates on 90%.

This is getting into “recursive self-improvement” territory. Basically, AI helps build a better AI, which then gets better at building the next one, and you repeat. It’s an old idea (goes back to the 1950s) and one of the ways people think AI progress could suddenly get very fast.

We’re not there yet, though. Current models still can’t really run this loop without humans, and some of what we’re seeing might just be very good coding automation.

But the pace is getting insane. In 2022, models struggled with basic arithmetic. By 2023, they could pass the bar exam. In 2024, they were writing decent software and doing graduate-level science. By late 2025, some top engineers were saying AI was doing most of their coding. And the models arriving in 2026 are another pretty big jump.

METR has a nice way of tracking this. They measure how long a task would take a human expert, then see whether an AI can do the whole thing on its own. That went from ~10-minute tasks to an hour, then several hours. Claude Opus 4.5 was at nearly 5 hours, with the number roughly doubling every 7 months (and recent data suggests maybe closer to 4).

And that doesn’t include the newest models yet.

2/ OpenAI’s new model is apparently solving unsolved maths problems - OpenAI says an internal model it started training just 24 days ago has already resolved 100+ long-standing open problems across maths, including the Navier-Stokes Millennium Prize problem. Apparently, the pace surprised even its own mathematicians.

So they’ve put together an independent advisory group with some pretty serious mathematicians, including Edward Witten, Timothy Gowers and Martin Hairer. They’ll help review the results, figure out how/when to release them and basically tell OpenAI when they think it’s doing something wrong. They’re unpaid and can publicly disagree with the company too.

There’s already some pushback from mathematicians about AI labs treating unsolved problems as benchmarks. Fair enough when your 24-day-old model is apparently knocking out problems people have been stuck on for years.

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THAT’S ALL FOR TODAY

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