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.
Let's ask GPT4!
I dunno. The “fallacy of composition” is just made up of 3 words, and there’s not a lot that you can explain with only three words.
How... did it map oversimplification to... holistic thinking??? Saying that it's "just statistics" is wrong because "just statistics" covers some very complicated models in principle. They weren't saying that simple subsystems are incapable of generating complex behavior.
God, why do people think these things are intelligent? I guess people fall for cons all the time...