On Tue, Apr 9, 2013 at 12:46 PM, Ben Goertzel <[email protected]> wrote:
> Matt, as you well know, OpenCog is not trying to emulate the human
> brain in detail, so that detailed calculations of computational
> requirements based on the human brain are not directly relevant

Ben, as you well know, my estimate is not for a detailed brain
emulation. It is for a neural network with approximately the same
number of synapses and response time. Each synapse requires one
multiply and one add operation per cycle, or 2 of each if updated.
That is a vast simplification of the behavior of real neurons, but
sufficient to get equivalent high level behavior according to
generally accepted theory.

It seems very convenient that your estimate of computing power for AGI
exactly matches the computing power you have available. And yet people
with thousands of times more computing power have only been able to
solve much easier problems like recognizing cat faces or winning at
Jeopardy.

So I would really like to know how many nodes and links (OpenCog,
DeSTIN, or otherwise) you need for AGI. How many concepts and how many
relations? How do you get these numbers? I explained my estimate of
10^7 features and 10^13 relations for vision. You need to explain why
those numbers are wrong. Intuition is not an explanation.

> In a similar way, you could prove airplanes can't fly by tabulating
> the number of computations implicit in the activity of a bird's cells

No. I can estimate how much energy is required to transport a given
amount of weight by an airplane by measuring it in birds. That works
because evolution and the airline industry have both put a lot of work
into optimizing it. By a similar argument, we don't have human level
intelligence in insect sized brains, or in machines of equivalent
computing power. Why not?


-- Matt Mahoney, [email protected]


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AGI
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