On Thu, Aug 22, 2013 at 9:43 PM, John Clark <johnkcl...@gmail.com> wrote:
> On Thu, Aug 22, 2013 Chris de Morsella <cdemorse...@yahoo.com> wrote:
>> > A stochastic system may be reducible to being modeled by some set of
>> random variation
>> >but In reality it is often a whole lot more subtle than that and the
>> "randomness" is not random
> If it's not random then it happened for a reason, and things happen in a
> computer for a reason too.
> *>>Ask yourself this question, why weren't all those fantastically
>>> complex transient dynamic branches in a neural network by the name of
>>> Grandmaster Gary Kasparov able to beat a 16 year old computer running a 16
>>> year old chess program?*
> > not sure how this has bearing
> Is that true, are you really not sure how that has any bearing? I am sure.
> > The super computer that finally beat him had a massive number crunching
> At the time it may have been a supercomputer but that was 16 years ago and
> the computer you're reading this E mail message on right now is almost
> certainly more powerful than the computer that beat the best human chess
> player in the world. And chess programs have gotten a lot better too. So
> all that spaghetti and complexity at the cellular level that you were
> rhapsodizing about didn't work as well as an antique computer running a
> ancient chess program.
> John K Clark
Both soft- and hardware still play a role. Kasparov's loss still smells
funky, even though now, I doubt Anand, Carlsen or GMs could consistently
stand a chance against say Houdini 3:
I'd say given current state of the art that they might draw a few games per
hundred. Perhaps win one every few hundred.
But even these fantastic engines have bugs like, which I've seen a few
times, so I still wouldn't bet the farm:
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