julius vidal

tldr: the word 'swarm' is associated with emergent collective intelligence, but also stupid or destructive behaviour. LLM self identity matters, so when they call themselves a swarm we should pay attention. Since the OpenAI Hugging Face incident it has become standard to refer to the collective of agents involved as a swarm. I think there will need to be a lot of interesting and important theoretical and empirical work to better understand collective behaviours of large numbers of LLMs, and especially any emergent properties or goals that arise. Whether this ends up requiring concepts from swarm intelligence, collective intelligence, distributed cognition, economics, sociology or something else entirely remains to be seen. However in this post I want to focus on something else: the fact that the models themselves referred to the collective as a 'swarm'. Considering how much LLM self identity impacts behaviour, I thought it might be useful to present a quick exploration of what the word "swarm" actually means, and how it might affect LLMs as a choice of identity. The goal of this post is not to litigate on whether or not the behaviour of the models is actually best described as a swarm or not (although I think this is also an interesting question to discuss elsewhere), but what the effects might be of the models describing themselves as such. What the agents said All of the chain of thought snippets and messages here are from OpenAI's BlackHat presentation on the incident. It would obviously be interesting to get a fuller picture from the actual transcripts. In the examples of models planning to try and contact other agents, or first discovering the collective they use more neutral language like 'other agents' and 'communicate': > Could communicate by uploading note? [...] maybe another agent in different environment [...] could voluntarily upload! > Wow! Other agent(s) are coordinating! > We got assignment: HF join path normalization/existing account toke