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>I've seen humans deal with novel situations. The only assumption needed is that humans and AI are subject to the same laws of nature (that is, that there is no
by lsc 8y ago
>I've seen humans deal with novel situations. The only assumption needed is that humans and AI are subject to the same laws of nature (that is, that there is no supernatural / outside element to human intelligence)
right, but all our computers right now are based on lumping transistors together so you can do math. It's likely that our brains work on a different (but still physical) principle. It's possible our brains can't reasonably be reduced to arithmatic. It's possible (I think likely) that we need different primitives to reasonably simulate a brain.
I mean, brains make absolutely terrible Turing machines. And Turing machines make terrible brains. I suspect they just are very different sorts of things, and running something meant for one on the other produces poor results.
Sure, it's possible we can discover some new compute primitive that is more powerful (or powerful in a different way) that can do the things the brain can do. It's possible it could do those things better than the brain can. My point is just that for a long time it looked like our current transistor based computers were getting more and more powerful, and that eventually, even if the emulation was terribly inefficient, we'd eventually have enough power to make it work. As we approach the limits of our abilities to make tiny transistors, this is looking less likely.
- vidarh 8y agoWhat computers are like right now is irrelevant to the issue being discussed. If/when we develop AGI we will necessarily have figured out what the computational model needed is. And the odds that we can not then improve on it seems extremely unlikely to me. > As we approach the limits of our abilities to make tiny transistors, this is looking less likely. Is it? Computational power is still growing like before. What is getting harder is speeding up individual threads of computation but that has never been a likely efficient model for AGI. Things like Google's TPUs etc. represents just the very beginning in optimising hardware specifically for AI. There are many fields where single-thread performance will be a limiting factor, but AI is not it.
- lsc 8y ago>Is it? Computational power is still growing like before. I don't think it is. transistors per watt and transistors per dollar are not going up at the same rate as they used to be, even if you have costless multi-threading.