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> I think the main problem is computers are still too slow I don't think this is right. Depending on your neuron model, you'd probably be able to simulate as m

by lars 15y ago

> I think the main problem is computers are still too slow I don't think this is right. Depending on your neuron model, you'd probably be able to simulate as many neurons as is in the human brain if you threw it against, say, Google's server farm. The brain is modular, so you should be able to parallelize it relatively easily. The reason no one has done that yet is that we don't yet know enough about how to connect those neurons the way they are connected in the brain. (The Blue Brain project aim to have this figured out by 2019 though.)

Detrus 15y ago
Oh yea Google's server farm has just about the guesstimated computational power of a human brain, 20 petaflops. Supercomputers can simulate a rat or bee brain with a few teraflops. I was talking about regular personal computers that individual researches can use to experiment. Supercomputer time is expensive and there are lots of annoying technical problems. They also use a lot of poorly optimized software. I figure another 5 years, a few doublings in GPU speed, new OpenCL/CUDA based neural net software and we'll fit a bee brain in one PC. Memristors are expected by 2015 http://spectrum.ieee.org/robotics/artificial-intelligence/moneta-a-mind-made-from-memristors/0 http://spectrum.ieee.org/robotics/artificial-intelligence/mo... they'll help run such brains in real time. Also these old charts http://www.transhumanist.com/volume1/moravec.htm http://www.transhumanist.com/volume1/moravec.htm comparing brains to computers need to be adjusted because glial cells also participate in signal processing. So we need a few teraflops of padding.