this post was submitted on 25 Nov 2023
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Machine Learning
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I mean, everyone is just sorta ignoring the fact that no ML technique has been shown to do anything more than just mimic statistical aspects of the training set. Is statistical mimicry AGI? On some performance benchmarks, it appears better statistical mimicry does approach capabilities we associate with AGI.
I personally am quite suspicious that the best lever to pull is just giving it more parameters. Our own brains have such complicated neural/psychological circuitry for executive function, long and short term memory, types I and II thinking, "internal" dialog and visual models, and more importantly, the ability to few-shot learn the logical underpinnings of an example set. Without a fundamental change in how we train NNs or even our conception of effective NNs to begin with, we're not going to see the paradigm shift everyone's been waiting for.
We need a name for the fallacy where people call highly nonlinear algorithms with billions of parameters "just statistics", as if all they're doing is linear regression.
ChatGPT isn't AGI yet, but it is a huge leap in modeling natural language. The fact that there's some statistics involved explains neither of those two points.
We need a name for the illness that is people throwing some shoddy homebrew "L"LM at their misshapen prompts - if you can call them that - and then concluding that it's just bad imitation of speech because they keep asking their models to produce page after page of sonic fanfic. Or thinking everything is equally hallucination-prone.
Really, the moronic takes about all this are out of this world, never even mind how people all of a sudden have a very clear idea of what intelligence, among the most ambiguous and ill-defined notions we debate, entails. Except they're struggling putting this knowledge into words, it's more about the feel of it all, y'know.