Slashdot Mirror
Leech Neuron Computers
Ralph Bearpark writes "The biological computer is born.
A computer made of neurons taken from leeches has been created by US scientists. "I'
I'd actually read about some of this research being done back in the early 80s at Bell Labs. Apparently they could actually get some read/write to the leech neurons, for use as storage devices, but they...uh...kept dying after for a few minutes. Anyone confirm/deny that?
Don't you guys remember all these movies where the AI takes over the world? Like Terminator, for instance, or Matrix? Well, now it can finally become a reality. According, to the article, the leech computer can actually think for itself, without having to be told what to do. Just think of the implications... I say if AI does take over the world, it would have to be biological.
Am I the only one who's paranoid?
___
If you think big enough, you'll never have to do it.
I can just amagine....
"..this top of the line Intel Slugium 500 with NNX..."
I can't see anyone wanting to get their hands dirty everytime their slugs explode because they over clock them, and where are the animal rights guys? If they were doing this with pigs [what a sight] they [the animal rights dudes] would be all over them.. Interesting article anyways.. Its a neat idea, and would make replacing CPU's a bit cheaper...
Stan "Myconid" Brinkerhoff
SB.
In a previous lifetime I did some preliminary research on 'living computers'. Turns out the ethical issues are pretty small but the two issues that really have to be solved are: 1) connectivity (if it can't talk to current computers it's not going to be developed) 2) architecture (take it massively parallel and it dwarfs current computing capacity, otherwise forget it.)
Neurons don't actually link up well to current computers. They are perfect for massive parallelism however. Can we figure out how to utilize that and then can we figure out how to wire it up ?
So long and thanks for all the fish . . . !!!
I've seen some basic laboratory work in a physics conference and read some theoretical works prior to this report. If you think of neurons as basic units (as they should be), what is the optimal behaviour they all should have in the beginning (birth)? This is one of the central issues of neural computing. It's now believed by many that the spike trains that neurons emit to their neighbours contains the "information content". The first thing one could do with the spike trains is to retransmit them, or return them to the senders. It turns out that it is exactly what neurons do when they first find each other out. Only things get really messy and intractable when they seem to know what they are doing. (one obvious behaviour is specialization, which could be a result of instability, or phase separation, of the syncronization process). The efforts these guys are trying are probably to exploit some known behaviour after neurons somehow begin to stabilize into some functional units.
One reason why the problem is so difficult is that information is not encoded in a static physical format. In a digital computer, you may stop the quartz oscillator and hold some gates to on or off to read out the specs, painstakingly. On a neuron, you can't do that! Spike trains are dynamical processes that have many more possible ways to encode information. A useful analogy is from languages. Let's say every single individual in this world speaks a different language in the beginning, but with the same alphabets. When I write "one" on the floor, how would the guy next to me know what it means when the word of the same meaning for him/her is "aye caramba"!
This field is a very broad subject encompassing biology, physics and statistical mechanics. One may found an interesting but quite speculative starting point to work its way backward from Frank C. Hoppensteadt et al. in the April 5 issue of Physical Review Letters, 1999. Science and Nature also may often have articles on the latest development in this field.