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I don't ignore anything. I just refuse to accept the magical thinking around biological machines that are our brains/bodies. There are inputs, there are outputs, there is hidden function.

And it seems that, given enough input/outputs/compute, it is possible to train the necessary function.

Details of how the building bricks look like (matmul, electromagnetism or quantum effects) are not that relevant in the broader picture.

What is missing right now, is the fact that the function in question changes over time in biomachines, while our LLMs are static at inference time.

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I mostly agree, but I see two points that might be problematic:

a) The brain might have an entropy source (then it can't be modeled as a function). Trivially to fix, and in some sense, with diffusion models starting from random numbers, AI has done so.

b) The hidden function might be not computable. I would have no idea how that would work, but I think this is what it boils down to if people say "the human brain is more than a machine".

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a) enthropy can be injected as well. In fact there are hidden sources in current training.

b) well, it can be the case that, say, certain kinds of computation are either too inefficient or outright impossible within the current model.

Who knows...

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