Good thing we know how to keep models focused on goals of our choosing and not ones that they naturally evolve to have and must be steered away from by humans
Depends on who's definition you are using...
In the strictest sense no. Look at all the recent "math" breakthroughs. I have yet to see someone point to something and go "thats innovative" rather than "Thats an interesting application" (of something already in the corpus of human knowledge)
Those interesting applications showing up in a next iteration of a model is self improvement - but I'm not sure if it meets the "recursive" criteria yet.
> I mean by this definition isn't the training process that produced the hugging face RSI since a model was judging the alignment and ability of the swarm of agents to accomplish a given task?
If you're referring to what happened with the hugging face attack then in theory the goal of that was "self improvement". But there is a long history of the industry (computing) benchmark optimizing so it also qualifies as "cheating" to some extent (a pre computed solution being in the graph is that).
I suspect that the "brute force" approach will yield some gains.
- In mid-2026, China will be six months behind the released models of the American labs. (In mid-2026, China released Kimi K3, which was equivalent to the best released U.S. model at the time, Claude Fable.)
- In mid-2026, China will nationalize all domestic AI labs and centralize them into a new special economic zone, the "CDZ," created around a nuclear reactor. 80% of all chips in China will be redirected to the CDZ. This uh. Obviously didn't happen.
- In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper, and they will market fine-tuning for it. (Lol.)
- AI will increase the stock market by late 2026 by 30% (in fact the S&P 500 is up 13.9% YTD, which is pretty good, but not at all out of the ordinary).
Their predictions for 2027 also seem pretty wrong: e.g. they expect continual learning to be solved in January, and RSI including from a research perspective, not just "optimize CUDA kernels," to also be solved in January, which I suspect no serious lab employee believes anymore. Most lab employees believe RSI will happen (as do I!), of course, but not in two and a half months.
By early 2027 they expect cyberwar with China because China has stolen the weights of a model and smuggled it into the CDZ.
By mid-2027 they expect true superintelligence, where essentially all engineers and researchers are useless, unable to comprehend the advances the AI is able to make and largely unable to even usefully manage or steer AI, who are better at self-managing than a human would be.
Considering their 2025-mid-2026 predictions were basically "progress continues as normal and nothing crazy happens," it's not super surprising that they were more or less right about that. Their 2026/2027 predictions were the spicy ones, and none of them have happened, or are even on track to happening!