jbn@GLACIER.STANFORD.EDU (John B. Nagle) (07/01/88)
Date: Wed, 29 Jun 88 11:23 EDT
From: John B. Nagle <jbn@glacier.stanford.edu>
Subject: Reproducing the brain in low-power analog CMOS
To: AILIST@ai.ai.mit.edu
Forget Turing machines. The smart money is on reproducing the brain
with low-pwer analog CMOS VLSI. Carver Mead is down at Caltech, reverse
engineering the visual system of monkeys and building equivalent electronic
circuits. Progress seems to be rapid. Very possibly, traditional AI will
be bypassed by the VLSI people.
John Naglelishka@uwslh.UUCP (Fish-Guts) (07/18/88)
To: comp-ai-digest@rutgers.edu Path: uwvax!uwslh!lishka From: Fish-Guts <uwvax!uwslh!lishka@rutgers.edu> Newsgroups: comp.ai.digest Subject: Re: Reproducing the brain in low-power analog CMOS (LONG!) Date: Sat, 2 Jul 88 11:03 EDT References: <19880701045841.7.NICK@INTERLAKEN.LCS.MIT.EDU> Reply-To: Fish-Guts <uwvax!uwslh!lishka@rutgers.edu> Organization: U of Wisconsin-Madison, State Hygiene Lab Lines: 108 In a previous article,jbn@GLACIER.STANFORD.EDU (John B. Nagle) writes: >Date: Wed, 29 Jun 88 11:23 EDT >From: John B. Nagle <jbn@glacier.stanford.edu> >Subject: Reproducing the brain in low-power analog CMOS >To: AILIST@ai.ai.mit.edu > > > Forget Turing machines. The smart money is on reproducing the brain >with low-pwer analog CMOS VLSI. Carver Mead is down at Caltech, reverse >engineering the visual system of monkeys and building equivalent electronic >circuits. Progress seems to be rapid. Very possibly, traditional AI will >be bypassed by the VLSI people. > > John Nagle There is one catch: you do need to know what the Brain (be it human, monkey, or insect) is doing at a neuronal level. After two courses in Neurobiology, I am convinced that humans are quite far away from understanding even a fraction of what is going on. Although I do not know much about the research happening at Caltech, I would suspect that they are reverse engineering the visual system from the retina and working their way back to the visual cortex. From what I was taught, the first several stages in the visual system consist of "preprocessing circuits" (in a Professor's words), and serve to transform the signals from the rods and cones into higher-order constructs (i.e. lines, motion, etc.). If this is indeed what they are researching at Caltech, then it is a good choice, although a rather low level one. I would bet that these stages lend themselves well to being implemented in hardware, although I don't know how many "deep" issues about the Brain and Mind that implementation of these circuits will solve. One of my Professors pointed out that studying higher order visual functions is hard because of all of the preprocessing stages that occur before the visual cortex (where higher order functions are thought to occur). Since we do not yet know exactly what kinds of "data abstractions" are reaching the visual cortex, it is hard to come up with any hardcore theories of the visual cortex because noone really knows what the input to that area looks like. Sure, we know what enters the retina, and a fair bit about the workings of the rods and cones, but how the signals are transformed as they pass through the bipolar, horizontal, amacrine, and ganglion cells is not known to any great certainty. [NOTE: a fair bit seems to be known about how individual classes of neurons tranform the signals, but the overall *picture* is what is still missing]. Maybe this is what the folks at Caltech are trying to do; I am not sure. It would help a great deal in later studies of the visual system to know what kinds of inputs are reaching the visual cortex. However, there are other areas of research that do address higher order functions in cortex. The particular area that I am thinking of is the Olfactory System, specifically the Pyriform Cortex. This cortex is only one synapse away from the olfactory sensory apparatus, so the input into the Pyriform Cortex is *not* preprocessed to any great degree; much less so than the > 4 levels of preprocessing that occur in the visual system. Futhermore, the Pyriform Cortex seems to be similar in structure to several Neural Net models, including some proposed by Hopfield (who does much of his work in hardware). Therefore, it is much easier to figure out what sort of inputs are reaching the Pyriform Cortex, though even this has been elusive to a large degree. The current research indicates that certain Neural Net models effectively duplicate characteristics of the cortex to a good degree. I have read several interesting articles on the storage and retrieval of previous odors in the Pyriform Cortex; these papers use Content-Addressable Memory (also called Associative Memory) as the predominant model. There is even some direct modelling being done by a couple of Grad. students on a Sun workstatoin down in California. [If anyone wants these references, send me email; if there is enough interest, I will post them]. My point is: do not write off AI (especially Neural Net) theories so fast; there is much interesting work being done right now that has a much potential as being important in the long run as the work being done at Caltech. Just because they are implementing Brain *circuits* and *architecture* in hardware does not mean they will get any closer than AI researchers. I still believe that AI researchers are doing much more higher order research than anything that has been implemented in hardware. Furthermore, the future of AI does not lie only in Artificial Intelligence and Computer Science. You bring up a good point: look at other disciplines as well; your example was hardware. But look even further: Neurobiology is a fairly important area of reasearch in this area. So are the Computational sciences: Hopfield does quite a bit of research here. Furthermore, Hopfield is (or was, at least) a Physicist; in fact I saw him give a lecture here at the UW about his networks where he related his work to AI, Neurobiology, Physics, Computational Sciences, and more...and the talk took place (and was sponsored by) the Physics department. Research into AI and Brain related fields is being performed in many discplines, and each will influence all others in the end. Whew! Sorry to get up on my soapbox, but I had to let it out. Remember, these are just my humble opinions, so don't take them too seriously if you do not like them. I would be happy to discuss this further over email, and I can give you references to some interesting articles to read on ties between AI and Neurobiology (almost all dealing with the Olfactory System, as that looks the most promising from my point of view). -Chris-- Christopher Lishka | lishka@uwslh.uucp Wisconsin State Lab of Hygiene | lishka%uwslh.uucp@cs.wisc.edu Immunology Section (608)262-1617 | ...!{rutgers|ucbvax|...}!uwvax!uwslh!lishka "...Just because someone is shy and gets straight A's does not mean they won't put wads of gum in your arm pits." - Lynda Barry, "Ernie Pook's Commeek: Gum of Mystery"