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A Skeptical Reaction To IBM's Cat Brain Simulation Claims
kreyszig writes "The recent story of a cat brain simulation from IBM had me wondering if this was really possible as described. Now a senior researcher in the same field has publicly denounced IBM's claims."
More optimisticaly, dontmakemethink points out an "astounding article about new 'Neurogrid' computer chips which offer brain-like computing with extremely low power consumption. In a simulation of 55 million neurons on a traditional supercomputer, 320,000 watts of power was required, while a 1-million neuron Neurogrid chip array is expected to consume less than one watt."
More than this, their simulated neurons aren't anywhere close to the real thing. A real neuron, an individual cell, has tremendous computing power due to the distribution of a bunch of different ion channel types (active conductances) in a highly complex dendritic tree. Simulating a few seconds of just ONE neuron accurately can take several minutes to several hours of supercomputer time. I know this because I do it for a living.
He's not arguing that it didn't work, he's arguing that they essentially ran a simulation of a large Artificial Neural Network, a relatively trivial task as long as you have a big enough computer behind it. ANNs are essentially points that connect to each other and learn by assigning weights to these various connections- this is essentially the simplest possible way to simulate the behavior of a neuron. The argument is being made that to claim an ANN, regardless of its size, approaches the capabilities of any mammalian brain is simply wrong, and that a true attempt to create such a simulation would need to factor in the stochasticity of ion channels, branchings in neurons and various other biological phenomena that have a tremendous impact on how our brains work.
Without reading more details on the original work, I'm inclined to say that he has a very valid point if they were indeed only running a large ANN model.
My research recently took me to some of Markram's work - the guy is brilliant and REALISTIC. His research goals are simple and attainable and any claims of success he has are *well* within the real world. He's incrementally worked his way up from a few neurons - the way a *real* scientist works; and to him, the simplest "brain simulation" of any sort is definitely possible, but far off in the future.