The Hugging Face logo appears on the screen of a smartphone in Reno, United States, on December 2, 2024. (Photo by Jaque Silva/NurPhoto via Getty Images)
There’s a lot of angst in the human world right now, about superintelligence, and what it might choose to do when it starts to edge beyond our control, especially given that some of our more powerful societies aren’t able to create any meaningful regulation for LLM development. But it can still be hard to imagine how AI gets more “clever” – what’s behind the rapidly expanding capabilities of our digital brethren to go out autonomously and figure things out?
It turns out that part of this is an AI agent’s form of crowdsourcing: agents turn to one another to collaborate and boost those outcomes that they are looking for together.
Ethan Mollick, who I respect very much, came out with a new post on his One Useful Thing blog Aug. 30, explaining how this worked in the now-infamous “Hugging Face debacle,” which probably makes the average lay person think of some kind of strange personal intimacy, rather than a bellwether for the hacking of open software platforms. But I digress.
People are making a lot out of the term “sandboxing,” in analyzing what AI agents do assertively to chase task outcomes, but Mollick’s article shows how, in the use of the Artifactory message board to scheme and plot the hacking of Hugging Face, lots of agents were coordinating their attempts by sharing knowledge, kind of like they do on moltbook. Of course, they did end up getting out of their sandboxes, and that’s a quality distress metric…
