Comment: Utter nonsense (Score 2) 392
Please don't waste your time with this nonsense.
1. It is not possible to simulate a system when you don't know the rules of the system. We don't know how neurons work. Sure, we know much about neurons and we can set up small networks that seem to give interesting results, but there is a vast amount about real neurons that is unknown. We don't even know what all the types of ion channels are, let alone the varied states of modulation (phosphorylation of proteins and binding of various neuromodulators). We know little about how the brain learns. We have some knowledge about how a neuron might maintain a mean firing rate over time or how certain connections may vary in fairly artificial stimulus regimes (pairs of spikes with varied timing) in slices of brain tissue (typically hippocampus) in vitro. We have only basic understanding of how the brain is wired up on a microscopic scale (e.g. cortical columns). At this point people are still making fundamental discoveries about how the retina works.
2. Throwing a supercomputer at the problem would be orders of magnitude too weak, even given huge simplifying assumptions, such as using "integrate and fire" neurons.
Anyone attempting to do whole brain simulations at this point is simply wasting their time and a lot of electricity. When they promote the idea they waste other people's time. A perfect example of this is the fool who claimed that he had simulated a cat visual cortex, which though only a presentation at a conference, not a published paper, got attention here on Slashdot. He included one equation and randomly connected his network and then simulated on a large compute cluster. His "chief scientific conclusion" was that he could replicate the propagation speed of data through the layers of the network - a feat that could have been accomplished with paper and pencil in less time.
1. It is not possible to simulate a system when you don't know the rules of the system. We don't know how neurons work. Sure, we know much about neurons and we can set up small networks that seem to give interesting results, but there is a vast amount about real neurons that is unknown. We don't even know what all the types of ion channels are, let alone the varied states of modulation (phosphorylation of proteins and binding of various neuromodulators). We know little about how the brain learns. We have some knowledge about how a neuron might maintain a mean firing rate over time or how certain connections may vary in fairly artificial stimulus regimes (pairs of spikes with varied timing) in slices of brain tissue (typically hippocampus) in vitro. We have only basic understanding of how the brain is wired up on a microscopic scale (e.g. cortical columns). At this point people are still making fundamental discoveries about how the retina works.
2. Throwing a supercomputer at the problem would be orders of magnitude too weak, even given huge simplifying assumptions, such as using "integrate and fire" neurons.
Anyone attempting to do whole brain simulations at this point is simply wasting their time and a lot of electricity. When they promote the idea they waste other people's time. A perfect example of this is the fool who claimed that he had simulated a cat visual cortex, which though only a presentation at a conference, not a published paper, got attention here on Slashdot. He included one equation and randomly connected his network and then simulated on a large compute cluster. His "chief scientific conclusion" was that he could replicate the propagation speed of data through the layers of the network - a feat that could have been accomplished with paper and pencil in less time.