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Culture War Roundup for the week of February 17, 2025

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What crucial characteristic is AI missing? Agency? It's not missing it so much as they just choose not to implement it.

Knowing that there is a real world, out there, beyond language.

Are the moon landings a hoax? Large Language Models can say what people say, perhaps rather more fluently and persuasively. If one is open to the possibility that there is more than one kind of intelligence, then LLM's have one of those kinds of intelligence, and in greater degree than an average human. But LLM's are rather stuck on giving their own opinion of whether the moon landings are a hoax, because they don't know whether the moon is real or fictional. Nor do the know whether the Earth is real or fictional. The whole "ground truth" thing is missing.

We don't know the "ground truth" either, though. All the information that we parse, such as touching the Earth or seeing the moon in the sky or through a telescope are basically hallucinations created by our brains based on the sensory input that we take in through detection mechanisms in our cells. We have to trust that the qualia that we experience are somewhat accurate representations of the "ground truth." Our experience is such that we perceive reality accurately enough such that we can keep surviving both as individuals and as a species, but who knows just how accurate that really is?

LLMs are certainly far more limited compared to us in the variety of sensory input they can take in, or how often it can update itself permanently based on that sensory input, and the difference in quantity is probably large enough to have a quality of its own.

My guess as to the biggest missing factor between here and AGI is efficient online and self-directed learning (aka continuous or lifetime learning).

More specifically, a means of avoiding the inward spiral that comes when the model's output becomes part of its input (via the chat context). I've noticed that LLMs very quickly become less flexible as a conversation progresses, and I think this kind of self-imitation is part of it. I'm working on something and I'd like to force the AI to push itself out of distribution, but I'm not sure how.

Yes, agency. How do you know they know how to implement it?

Because it exists? The agentic AIs are already a thing

Those don't really work. There have been a bunch of iterations but prompts of the form 'decide what you should do to achieve task X and then do it' don't produce good results in situ and it's not really clear why. I think partly because AI is not good at conceptualising the space of unknowns and acting under uncertainty, and it's not good at collaborating with others. Agentic AI tends to get lost, or muddled, or hare off in the wrong direction. This may be suboptimal training, of course.

I read Zvi he follows AI much closer than I will ever bother to.

There are potential tricks around the problem you talk about. One of the easier ones is asking the AI to prompt engineer itself. "How would you request a task to do X" ... "How would you improve this prompt that is a request to do task X" ... keep doing that and asking separately "which is a better prompt to do task X".

The sense I get is that there is thinking that an AI is doing, but it is mostly like a dice roll. Rolling consecutively for a cumulatively high number isn't a great strategy, but you don't need to do that. You can instead do something where you re-roll for the best possible roll, then move on to the next roll and do the same thing.