All biological organisms, considered as signalling or information processing networks, are massively parallel: huge amounts of similar cells with slightly different state signalling one another. It's not surprising that the biological evolved brain works the same way. A turing machine-like sequential computer powerful/fast enough for general intelligence would be far less likely to evolve.
So the fact that human intelligence is slow and parallel isn't evidence for thinking you can't implement intelligence as a fast serial algorithm. It's only evidence that the design is likely to be different from that of human brains.
It's likely true that we don't have the algorithmic (or other mathematical) techniques yet to make general intelligence. But that doesn't seem to me to be evidence that such algorithms would be qualitatively different from what we do have. We could just as easily be a few specific algorithmic inventions away from a general intelligence implementation.
Finally, as far as sheer scale goes, we're on track to achieve rough computational parity with a human brain in a single multi-processor cluster within IIRC something like a decade.
I'm not trying to play burden of proof tennis here but surely the fact that the only "intelligence" that we know of is implemented in a massively parallel way should give you pause as to assuming that it can be done serially. Unless of course the kind of AI that humans create is nothing like the human mind, in which my question is irrelevant.
But that doesn't seem to me to be evidence that such algorithms would be qualitatively different from what we do have.
But we already know that the existing algorithms (in the brain) are qualitatively diff...
Haven't had one of these for awhile. This thread is for questions or comments that you've felt silly about not knowing/understanding. Let's try to exchange info that seems obvious, knowing that due to the illusion of transparency it really isn't so obvious!