4 ms·

I'm genuinely wondering if your parent comment is correct and the only reason we don't see the behaviour you describe, IE, learning and growth is because of how

by Folcon 10mo ago

I'm genuinely wondering if your parent comment is correct and the only reason we don't see the behaviour you describe, IE, learning and growth is because of how we do context windows, they're functionally equivalent to someone who has short term memory loss, think Drew Barrymore's character or one of the people in that facility she ends up in in the film 50 first dates. Their internal state moves them to a place where they "really intend" to help or change their behaviour, a lot of what I see is really consistent with that, and then they just, forget.

Libidinalecon 10mo ago
No, the idea is just stupid. I just don't understand how anyone who actually uses the models all the time can think this. The current models themselves can even explain what a stupid idea this is.
ben_w 10mo ago
Not only, but also. The L in ML is very slow. (By example count required, not wall-clock). On in-use learning, they act like the failure mode of "we have outsourced to a consultant that gives us a completely different fresh graduate for every ticket, of course they didn't learn what the last one you talked to learned". Within any given task, the AI have anthropomorphised themselves because they're copying humans' outputs. That the models model the outputs with only a best-guess as to the interior system that generates those outputs, is going to make it useful, but not perfect, to also anthropomorphise the models. The question is, how "not perfect" exactly? Is it going to be like early Diffusion image generators with the psychological equivalent of obvious Cronenberg bodies? Or the current ones where you have to hunt for clues and miss it on a quick glance?
knollimar 10mo ago
I think it's a fundamental limitation of how context works. Inputting information as context is only ever context; the LLM isn't going to "learn" any meaningful lesson from it. You can only put information in context; it struggles learning lessons/wisdom

by Folcon 10mo ago

Libidinalecon 10mo ago

No, the idea is just stupid. I just don't understand how anyone who actually uses the models all the time can think this. The current models themselves can even explain what a stupid idea this is.

ben_w 10mo ago

Not only, but also. The L in ML is very slow. (By example count required, not wall-clock). On in-use learning, they act like the failure mode of "we have outsourced to a consultant that gives us a completely different fresh graduate for every ticket, of course they didn't learn what the last one you talked to learned". Within any given task, the AI have anthropomorphised themselves because they're copying humans' outputs. That the models model the outputs with only a best-guess as to the interior system that generates those outputs, is going to make it useful, but not perfect, to also anthropomorphise the models. The question is, how "not perfect" exactly? Is it going to be like early Diffusion image generators with the psychological equivalent of obvious Cronenberg bodies? Or the current ones where you have to hunt for clues and miss it on a quick glance?

knollimar 10mo ago

I think it's a fundamental limitation of how context works. Inputting information as context is only ever context; the LLM isn't going to "learn" any meaningful lesson from it. You can only put information in context; it struggles learning lessons/wisdom