Re: tlug: Karl-Max has cool dreams [was: dual-pentium processors]

[Karl-Max Wagner <karlmax@example.com>]

> But I don't think this is universally applicable.

I never said it is that. But as you pointed out this kind of
problem is extremely frequent.

> Raaaaight.  Not!  I mean, I think that's inappropriate.  What we know
> neural networks (and similar) to be good at are excellent approximate
> solutions to pattern recognition problems, "trainability," and the

I didn't think so much of neural networks. Most paralell
processing schemes are a lot more primitive than that. Take
image processors as an example. It is easy to cut an image into
small pieces to be processed sepately ( for the most part ).
There are other problems of that kind, like weather forecasting,
code cracking ( remember the RC5 cracking initiative ! ). In
fact, that kind of things are what most computers are
processing.

> like.  To apply parallel hardware discription languages to arbitrary
> problems will require the willingness to accept approximate answers
> from our machines.

There ain't anything like and "exact" answer. Your answers are
only as good as your input values. So in fact approximate
answers are the order of the day. Anybody using circuit analyzer
software knows that......

> Uh-uh.  People are cheaper and more flexible.  What we want from our

Hmmm......actually people are pretty expensive.....

> machines is better reliability than people can give you.  We know very

It's another question whether they give that to youm Machines
are great in messing things up. No human being can make such a
mess than a computer running Amok.

> little about getting exact solutions to arbitrary problems based on
> parallel computation.

Actually - do we need them ? In practice approximate solutions
are good enough.

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"It was hell. They knew it.          Karl-Max Wagner
  But they called it                 karlmax@example.com
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