| > Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing. I disagree. Thought experiment: design a circuit which has as many inputs and outputs as a biological neurone, such that it always maps inputs to outputs in the same way (including the observation that this isn't a static map but one which changes over time), then connect them as neurons are in one of us. While clearly nothing like an natural brain on a cellular level, I believe this is a sufficient similarity to be "the same parlour tricks". The question then is: how close does the design actually need to be, while not losing anything of importance? Perceptrons were only ever a toy model, so they may well be insufficient; but on the other hand, for a sense of scale, GPT-3 is about the complexity of a rodent brain rather than a human brain — and that suggests that humans could learn to be simultaneous experts in many dozens of fields and languages with a mere tenth of a percentage point of our brains if only we lived long enough to read the entire internet. Which matters most — neurons, connective structure, learning environment, or something else — is, I think, still an open question. But even between all the differences, AI collectively are general purpose enough to at least suspect these things have got a lot of similarities where it matters. |