I was not arguing about the limits of computing, rather, IBM's specific
design.
it doesn't really realistically emulate real neurons, rather it is a
from what I can gather a simplistic "accumulate and fire" model, with
the neurons hard-wired into a grid.
I suspect something more "generic" would be needed.
another question is what can be done in the near term and on present
hardware (future hardware may or may not exist, but any new hardware may
take years to make it into typical end-user systems).
the second part of the question is:
assuming one can transition to a purely biology-like model, is this a
good tradeoff?...
if one gets rid of a few of the limitations of computers but gains some
of the limitations of biology, this may not be an ideal solution.
better would be to try for a strategy where the merits of both can be
gained, and as many limitations as possible can be avoided.
most likely, this would be via a hybrid model.
or such...
On 10/25/2011 9:07 AM, Paul Homer wrote:
I've always suspected that it comes from the ability to see around
corners, which appears to be a rare ability. If someone keeps seeing
things that other people say aren't there, eventually it will drive
them a little crazy :-)
An amazing example of this (I think) is contained in this video:
http://www.randsinrepose.com/archives/2011/10/06/you_are_underestimating_the_future.html
Paul.
------------------------------------------------------------------------
*From:* John Zabroski <[email protected]>
*To:* Fundamentals of New Computing <[email protected]>
*Sent:* Tuesday, October 25, 2011 11:55:29 AM
*Subject:* Re: [fonc] IBM eyes brain-like computing
Brian,
I recommend you pick up a copy of Ray Kurzweil's The Singularity
Is Near. Ray is smarter than basically everyone, and although a
tad bit crazy (teaching at MIT will do that to you :)), he is a
legitimate genius.
Basically, before arguing about the limits of computing, read Ray
Kurzweil. Others have written similar stuff here and there, but
nobody is as passionate and willing to argue about the subject as Ray.
Cheers,
Z-Bo
On Fri, Oct 14, 2011 at 2:44 PM, BGB <[email protected]
<mailto:[email protected]>> wrote:
On 10/14/2011 9:29 AM, karl ramberg wrote:
Interesting article :
http://www.itnews.com.au/News/276700,ibm-eyes-brain-like-computing.aspx
Not much details, but the what they envisions seems to be
more of the
character a autonomic system that can be quarried for
answers, not
programmed like today's computers.
I have seen stuff about this several times, with some articles
actively demeaning and belittling / trivializing the existing
pre-programmed Von Veumann / stored-program style machines.
but, one can ask, but why then are there these machines in the
first place:
largely it is because the human mind also falls on its face
for tasks which computers can perform easily, such as
performing large amounts of calculations (and being readily
updated).
also, IBM is exploring some lines of chips (neural-net
processors, ...) which may well be able to do a few
interesting things, but I predict, will fall far short of
their present claims.
it is likely that the "road forwards" will not be a "one or
the other" scenario, but will likely result in hybrid systems
combining the strengths of both.
for example, powerful neural-nets would be a nice addition,
but I would not want to see them at the cost of
programmability, ability to copy or install software, make
backups, ...
better IMO is if the neural nets could essentially exist
in-computer as giant data-cubes under program control, which
can be paused/resumed, or loaded from or stored to the HDD, ...
also, programs using neural-nets would still remain as
software in the traditional sense, and maybe neural-nets would
be stored/copied/... as ordinary files.
(for example, if a human-like mind could be represented as
several TB worth of data-files...).
granted, also debatable is how to best represent/process the
neural-nets.
IBM is exploring the use of hard-wired logic and "crossbar
arrays" / memristors / ...
also implied was that all of the neural state was stored in
the chip itself in a non-volatile manner, and also (by
implication from things read) not readily subject to being
read/written externally.
my own thoughts had been more along the lines of fine-grained
GPUs, where the architecture would be vaguely similar to a GPU
but probably with lots more cores and each likely only being a
simple integer unit (or fixed-point), probably with some local
cache memory.
likely, these units would be specialized some for the task,
with common calculations/... likely being handled in hardware.
the more cheaper/immediate route would be, of course, to just
do it on the GPU (lots of GPU power and OpenCL or similar). or
maybe creating an OpenGL-like library dedicated mostly to
running neural nets on the GPU (with both built-in neuron
types, and maybe also "neuronal shaders", sort of like
"fragment shaders" or similar). maybe called "OpenNNL" or
something...
although potentially not as powerful (in terms of
neurons/watt), I think my idea would have an advantage that it
would allow more variety in neuron behavior, which could
likely be necessary for making this sort of thing "actually
work" in a practical sense.
however, I think the idea of memristors is also cool, but I
would presume that their use would more likely be as a type of
RAM / NVRAM / SSD-like technology, and not in conflict with
the existing technology and architecture.
or such...
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