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IBM Takes a (Feline) Step Toward Thinking Machines
bth writes "A computer with the power of a human brain is not yet near. But this week researchers from IBM Corp. are reporting that they've simulated a cat's cerebral cortex, the thinking part of the brain, using a massive supercomputer. The computer has 147,456 processors (most modern PCs have just one or two processors) and 144 terabytes of main memory — 100,000 times as much as your computer has."
Having done neuroscience research, (if only on a master's degree level), I can say that the cat brain is particularly well studied, mapped out, and understood by neuroscientists. It is used as a model organism by many neuroscientists, and has a number of similarities with the human brain in its layout and function, much moreso than the mouse or rat brain.
I was trying to figure out who they were talking about when they said "your computer." ;)
The review looks like it was written for a grade school presentation with that and the processor comment.
Every time I start to have faith in humanity, I ruin it by driving to work between 7 and 8 am.
Technically is a single Core2Duo/Quad or Core iX CPU considered SMP? I would guess no they are not.
Funnily enough, a single Core i7 or Opteron is SMP, but if you have multiple, then it isn't, it's NUMA because not all the processors have Symetric access to memory.
Core 2 is SMP for all standard configurations.
The enemies of Democracy are
TFA is bunk. (Yes, I read it.) 12 pages of bunk. Much of the article is about the computational challenges and blathers on about number of processors used and memory. Under key scientific results, they find that their model propagates waves at about the same rate as is found physiologically. So they connected a bunch of nodes in a way that produced synchronous behavior at a certain frequency. I could tune any model you give me to produce this behavior. (I have no special talent here, anyone writing models could.) Yawn. They ramble on about signals propagating between layers at reasonable rates, too. And ...?
What about their simulation doing anything like what a cat might naturally do, such as detect a moving object? Nope. Instead they go on to discuss the scaling of their model, profiling and performance modeling. Perhaps one reason their model shows absolutely nothing is that they have connected their simulated neurons randomly. Yes. Randomly. Or as they put it: "The coordinates of target thalamocortical modules for each cell are determined using a Gaussian spatial density profile centered on the topographic location of the source thalamocortical module". Yep, thats random. Since their model doesn't ever change connection strengths (one form of learning) these random connections never change.
I recently heard a description of the ways you can fool someone with computational neuroscience. Here are a couple of them: "Two card monte" Write a paper that spans two fields, but has no significant results in either. The specialists in one field will feel that the work done in their field is trivial, but that exciting stuff from the other field in the paper is what makes it so special. The specialists from the other field may feel the same way. Somebody snookered the conference organizers into thinking they were doing any neuroscience at all. The other was called "Turning the prayer wheel" or burning compute cycles to gain scientific merit. Fancy hardware is cool, but it can produce absolutely trivial results as this paper confirms.
I don't mean to say that this research is entirely pointless. Indeed it has succeeded in siphoning significant funding from DARPA which might otherwise have gone into developing [killer] robot dogs.