From: Matt Mahoney (matmahoney@yahoo.com)
Date: Fri Sep 21 2007 - 19:01:34 MDT
--- CyTG <cytg.net@gmail.com> wrote:
> Off topic from a ghost :) .. but you guys are frequently talking about
> beeing somewhat far away from the takeoff scenario both in terms of software
> and hardware.. are there any lists/sites that deals with a more precise
> micro detailed evaluation of these specifics? Just how much hardware do we
> think we need in regards to wich framework and what does curret frameworks
> lack? What bottlenecks, hurdles, are we looking at and what sort of R&D are
> going into solving them ?
> If anyone knows!
> Thanks.
We have historically underestimated the difficulty of AI. Take your pick:
- Turing predicted in 1950 that in 50 years a machine with 10^9 bits of
memory, but no faster than current hardware at the time could pass the Turing
test [1].
- Landauer estimated that human long term memory capacity is 10^9 bits [2].
- The Blue Brain project simulated a mouse cortex (1/1000 the size of a human
cortex) at 1 ms resolution in 1/10 real time on the 4096 processor Blue Gene/L
with 1 TB memory [3].
- Google is about as close as we have to AI right now, and they use a few
hundred thousand processors.
- The human brain has about 10^15 synapses. Neurons have an information rate
of about 10 bits per second. Therefore the equivalent computation is 10^16
OPS and 10^15 bits of memory.
Of course simulating one brain is not enough. For computers to surpass the
human race as a whole, you need to simulate about 10^10 brains.
References
1. Turing, A. M., (1950) Computing Machinery and Intelligence, Mind,
59:433-460.
2. Landauer, Tom (1986), How much do people remember? Some estimates of the
quantity of learned information in long term memory, Cognitive Science (10)
pp. 477-493.
3. Frye, James, R. Ananthanarayanan, D. S. Modha (2007), Toward Real-Time,
Mouse-Scale Cortical Simulations, IBM Research Report RJ10404 (A0702-001) Feb.
5, 2007. http://www.modha.org/papers/rj10404.pdf
-- Matt Mahoney, matmahoney@yahoo.com
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