On Sun, Aug 25, 2013 at 12:16 AM, Chris de Morsella
<cdemorse...@yahoo.com> wrote:
> Telmo -- Another crucial difference between the brain and current computer
> architectures is the huge difference between the two in terms of signal to
> noise ratios. The brain is a crackling and very noisy place and is in this
> way is very unlike silicon chips where the signal is very clear (at a large
> energy cost incidentally)
> We may experience our minds as a splendid inner silence

I wish! :)

> -- well maybe not
> all of us -- but the actual brain environment is highly chatty and is
> cascading with signals talking over each other more like a lively cocktail
> party really.
> Computer architecture is the exact opposite in this regard, and this
> suggests that the two architectures must be very different and work on
> different principles or at least in very different manners.

Completely agree.

> The brain seems to excel at somehow -- through what sleight of hand? --
> pulling beautifully ordered reifications of sensorial perception streams
> (like the illusion we create of the three dimensional world arrayed in a
> stable manner around our point of perception that does not experience sudden
> gaps but instead persists in majestic stability even as the sensorial stream
> shuts down -- for example whenever we move our eyeballs from one spot to
> another)
> And it does so in the midst of a veritable cacophony of countless signals
> that would totally overwhelm any software we have and bring any attempt we
> could possibly cobble together to try to manage it or make sense of it to a
> grinding overloaded crashing halt.
> This is a fundamental architectural difference between how logic is built
> up, layer by layer, on a computer and how the brain does things. They are
> profoundly different approaches to how things are done.

Undoubtably. And it might not be a coincidence that these
architectural differences are correlated with very distinct sets of
strengths and weaknesses in terms of problem solving.

Telmo.

> -Chris
>
> -----Original Message-----
> From: everything-list@googlegroups.com
> [mailto:everything-list@googlegroups.com] On Behalf Of Telmo Menezes
> Sent: Saturday, August 24, 2013 2:00 PM
> To: everything-list@googlegroups.com
> Subject: Re: Deep Blue vs The Tianhe-2 Supercomputer
>
> On Sat, Aug 24, 2013 at 9:05 PM, Platonist Guitar Cowboy
> <multiplecit...@gmail.com> wrote:
>> As I tried to comment in the other thread concerning chess: it's not
>> just about power, it's also about quality of coding. Just one fresh
>> opening, a novel variation or line in the mid game, a bug in the code,
>> one position falsely assessed, and all computing power in the universe
>> will still lose that game. To generalize this to all problems seems a
>> bit quick. PGC
>
> I agree with the sentiment. Chess is a very narrow case though: the min-max
> algorithm plus a brutal amount of computing power is surely going to beat a
> human. The min-max algorithm is so simple that it is not that hard to
> implement with zero defects. The issue, though, is the following: we
> currently only know how to beat top human players with brutal computational
> power. The part of the human brain devoted to playing chess (even in a Grand
> Master) cannot possibly match what we already do artificially in terms of
> computing power. It must use smarter algorithms. Our brain cannot possibly
> hold the gigantic search trees involved in min-max, it must be doing
> something much more clever. We don't know what that is.
>
> We are now approaching a point where we can have supercomputers with the
> same estimated computational power of a human brain, but we are very far
> from replicating its capabilities. There's even a lot of stuff insects do
> that we are not close to matching. I dare even say bacteria. There are many
> fundamental algorithms yet to be discovered, that's for sure.
>
> Also, Moore's law is bound to hit a physical limit. It cannot be that far
> now. It's already fishy, since it's being driven mostly by multicore
> architectures. Moving from the sequential to the parallel world is far from
> trivial in terms of software engineering. The brain is massively parallel
> and asynchronous, and we are still very bad with that sort of stuff. Maybe
> that's precisely where the missing good stuff lies.
>
> Incidentally, Richard Feynman was involved with a startup that tried to
> create a new type of highly parallel computer. Here's an interesting read
> about it:
>
> http://longnow.org/essays/richard-feynman-connection-machine/
>
> I love this part:
>
> "We were arguing about what the name of the company should be when Richard
> walked in, saluted, and said, "Richard Feynman reporting for duty. OK, boss,
> what's my assignment?" The assembled group of not-quite-graduated MIT
> students was astounded.
>
> After a hurried private discussion ("I don't know, you hired him..."), we
> informed Richard that his assignment would be to advise on the application
> of parallel processing to scientific problems.
>
> "That sounds like a bunch of baloney," he said. "Give me something real to
> do."
>
> So we sent him out to buy some office supplies."
>
>
> Telmo.
>
>>
>> On Sat, Aug 24, 2013 at 6:07 PM, John Clark <johnkcl...@gmail.com> wrote:
>>>
>>> Suppose that in 1997 you had a very difficult problem to solve, so
>>> difficult that it would take Deep Blue, the supercomputer that beat
>>> the best human chess player in the world, 18 years to solve, what should
> you do?
>>> You'd do better to let Moore's law do all the heavy lifting and leave
>>> Deep Blue alone and sit on your hands from 1997 until just 2 minutes
>>> ago, because that's how long it would take the 2013 supercomputer
>>> Tianhe-2 to solve the problem. And in 20 years your wristwatch will
>>> be more powerful than Tianhe-2.
>>>
>>>   John K Clark
>>>
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