Matt,
First of all, we are, I take it, discussing how the brain or a computer can
recognize an individual face from a video - obviously the brain cannot
match a face to a selection of a billion other faces.
Hawkins' answer to your point that the brain runs masses of neurons in
parallel in order to accomplish facial recognition is:
"if I have many millions of neurons working together, isn't that like a
parallel computer? Not really. Brains operate in parallel & parallel
computers operate in parallel, but that's the only thing they have in
common"..
His basic point, as I understand, is that no matter how many levels of brain
are working on this problem of facial recognition, they are each still only
going to be able to perform about ONE HUNDRED steps each in that half
second. Let's assume there are levels for recognising the invariant
identity of this face, different features, colours, shape, motion etc -
each of those levels is still going to have to reach its conclusions
EXTREMELY rapidly in a very few steps.
And all this, as I said, I would have thought all you guys should be able to
calculate within a very rough ballpark figure. Neurons only transmit signals
at relatively slow speeds, right? Roughly five million times slower than
computers. There must be a definite limit to how many neurons can be
activated and how many operations they can perform to deal with a facial
recognition problem, from the time the light hits the retina to a half
second later? This is the sort of thing you all love to calculate and is
really important - but where are you when one really needs you?
Hawkins' point as to how the brain can decide in a hundred steps what takes
a computer a million or billion steps (usually without much success) is:
"The answer is the brain doesn't 'compute' the answers ; it retrieves the
answers from memory. In essence, the answers were stored inmemory a long
time ago. It only takes a few steps to retrieve something from memory. Slow
neurons are not only fast enough to do this, but they constitute the memory
themselves. The entire cortex is a memory system. It isn't a computer at
all." [ON INtelligence - Chapter on Memory]
I was v. crudely arguing something like this in a discussion with Richard
about massive parallel computation. If Hawkins is right, and I think he's
at least warm, you guys have surely got it all wrong. (although you might
still argue like Ben that you can it do your way not the brain's - but
hell, the difference in efficiency is so vast it surely ought to break your
engineering heart).
Matt/ MT:
Thanks. And I repeat my question elsewhere : you don't think that the
human
brain which does this in say half a second, (right?), is using massive
computation to recognize that face?
So if I give you a video clip then you can match the person in the video to
the correct photo out of 10^9 choices on the Internet in 0.5 seconds, and
this
will all run on your PC? Let me know when your program is finished so I can
try it out.
You guys with all your mathematical calculations re the brain's total
neurons and speed of processing surely should be able to put ball-park
figures on the maximum amount of processing that the brain can do here.
Hawkins argues:
"neurons are slow, so in that half a second, the information entering your
brain can only traverse a chain ONE HUNDRED neurons long. ..the brain
'computes' solutions to problems like this in one hundred steps or fewer,
regardless of how many total neurons might be involved. From the moment
light enters your eye to the time you [recognize the image], a chain no
longer than one hundred neurons could be involved. A digital computer
attempting to solve the same problem would take BILLIONS of steps. One
hundred computer instructions are barely enough to move a single character
on the computer's display, let alone do something interesting."
Which is why the human brain is so bad at arithmetic and other tasks that
require long chains of sequential steps. But somehow it can match a face to
a
name in 0.5 seconds. Neurons run in PARALLEL. Your PC does not. Your
brain
performs 10^11 weighted sums of 10^15 values in 0.1 seconds. Your PC will
not.
IOW, if that's true, the massive computational approach is surely
RIDICULOUS - a grotesque travesty of engineering principles of economy,
no?
Like using an entire superindustry of people to make a single nut? And, of
course, it still doesn't work. Because you just don't understand how
perception works in the first place.
Oh right... so let's make our computational capabilities even more
massive,
right? Really, really massive. No, no, even bigger than that....?
> > Matt,:AGI research needs
> >>> special hardware with massive computational capabilities.
> >
>
> Could you give an example or two of the kind of problems that your AGI
> system(s) will need such massive capabilities to solve? It's so good -
> in
> fact, I would argue, essential - to ground these discussions.
For example, I ask the computer "who is this?" and attach a video clip
from
my
security camera.
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