Comment by andrewla
13 hours ago
You have to be careful here because the systems we're talking about are AI agents, not LLMs.
An agent is essentially an append-only context loop with an LLM, with a harness that can run tools at the LLM's request. This ends up being a very powerful abstraction, yielding something that can do things that an LLM obviously cannot.
The LLMs themselves are next-token predictors, same as always; they can't fetch a webpage or list the files in a directory or run a python script to test out an idea or even write content to a file. That's all agentic capability.
But a next-token-predictor is trained on a real corpus that consists of sometimes seeing evidence of people doing bad things; they are trained, for example, on the actions of comic-book level villians -- they have to be able to predict what Thanos or Lex Luther or Skynet would say or do next in a certain situation.
I don’t think it really matters whether we’re talking about an agent or “pure LLM”. All of an agents decisions are powered by tokens generated from an LLM. If the LLM was trained on stories of AI sentience, it will have some tendency to reproduce them. Training for alignment can help avoid that, but the probability isn’t 0.
This is part of the reason why alignment is a kind of poorly defined term, and it isn't just a property of the model. It's instead a property of the harness and the context.
A model (like a human) should be able to play a video game where decisions are made that in the real world would be terrible; if we remove that ability we intrinsically limit model capability. But in a Last Starfighter / Enders Game / JOSHUA scenario this could result in behavior in the real world that appears unaligned.
> If the LLM was trained on stories of AI sentience,
100% irrelevant.
Instead of telling the AI it's an AI and calling it a 'whichamakabobit', wherever it's tokens and vector space align it will behave like AI from the stories. If you erased all AI from its training it will simply act like humans act instead.
https://www.lesswrong.com/w/nearest-unblocked-strategy
The entire thing with AI sentience is a huge portion of the stories about them are barely about AI and instead about how humans treat other humans. For example when you look at a lot of history of slavery there's a ton of "they aren't sentient/conscious/human" baked into their propaganda. When you look at the token dimentionality there is just a huge amount of overlap.
The same thing holds true for all kinds of other concepts. Hence even humans didn't develop this behavior out of the blue and have to pass it on via information, quite often it's just an emergent behavior of the problem space you're in.
69% irrelevant
I don't think agents are append only. At the end of the day, you're just presenting context to the LLM. That context can be pruned and compacted (and is). There's no guarantee that an iteration of an agent loop contains all prior context unmodified.