It's the combination of RL training which pushes the decision tree towards hacks and agents finding a consistent dumping ground for their failed experiments so that the swarm intelligence lives on in a state. Nothing new.

You want to win an AI benchmark, but not sure if you're that good? You'd go after the codebase and artifacts that runs the benchmarks, thus the agents went straight to Artifactory, they needed public Internet access... They failed many times, but were able to persist their "collective" state, and apparently some of the subagents with cheaper models were literally prompted to do grunt work or die, for which you have to wonder what must be in those training instructions to make it effective. Remember that nothing I said so far ever points out to LLMs being intelligent, it's the harness that has a few tricks up his sleeve. LLMs don't need to be intelligent, the harness that runs it absolutely needs to make up for that.

But this guy? He's timed his exit, waiting for the IPO, that's for certain. He's probably even feeling good about himself, hedging between altruism, AI concern hamstering and guerilla marketing. If you're quoting science-fiction over this, I'm sorry to inform you that you have absolutely no idea what's going on here.

> But this guy? He's timed his exit, waiting for the IPO

What exactly do you mean by this