The main thing I notice AIs do that humans don't is write lots of scripts running searches and verifications. They don't work in a small search space, and they aren't using a gigabrain directly on a large search space. They're just writing lots of scripts to search large spaces that would be annoying to do. When I watch them work, I mostly think, "Oh I probably should've been doing that. But I'm just so lazy, I would never crank out 1000 lines of Python doing a bunch of Grobner basis or group theory calculations just to test a hypothesis." Even if it would've been more reliable and less work overall. Your computer runs billions of clock cycles per second, and AIs will actually use it for thinking. I also think: If math had "industrial value", then this would've been systematized and you could train people to search for math solutions like an AI. Maybe Bel is superhuman, but lots of people could be an Astra if the computational approaches were written down and taught. It's the difference between "stare at a paper, think, hope a pattern comes to mind" vs. "What is a good search space? Let me feed that into an SMT solver or CAS or custom C++ searcher." Of course, many people do that, but not as fluently and consistently as AI.

GPT-6 Astra has just beaten a standard game of Factorio with enemies enabled after nearly 44 hours in-game time, and 4 days 11 hours on his Codex /goal clock. At API pricing, logs indicate it would've cost about $4500. It could probably be 50x cheaper by offloading more to Luna and providing some standard scripts for common tasks. My next test might be Astra coaching Muse Spark or Qwen 3.8 27B into solving a random seed, now that we have successful logs to review.