There are arguments that the brain is quantum, as in parts of it locally using quantum effects. Which if true, might make a counter-argument, as there will be bigger data centers needed if the goal is to simulate the brain classically.
On the other side, advancement in quantum computers would make current LLM inference much faster. Because of the extreme cooling needed, i dont think the energy demand would become less.
With AI companies talking about AGI, i sometimes wonder if they really need the machines for serving inference to customers, or they have a formula for computational capacity that could run an AGI, and they just want to reach that level.
Can you give me some pointers?
Last I heard researches simulated an entire brain of a fruitfly with just a classic neuron approach [0] and if I recall it worked great.
I know a human brain is many orders of magnitude more complex, and that there are some birds that use quantum navigation - so it's certainly not impossible by any stretch, though I am quite interested in this statement since it's the first I hear about it.
> the brain is quantum
Doesn't that apply to everything that exists in the material world?
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If the brain does rely on quantum effects, it's still possible the quantum effects in use are able to be simulated efficiently on a classical computer. For example if it's a matter of signal transfer rather than quantum computation, that could be simulated rather easily.