From: Dani Eder (email@example.com)
Date: Mon May 01 2006 - 18:42:23 MDT
> When it becomes possible, for the first time, to
> build something that
> generates new knowledge in such a way that it is not
> limited by the
> speed of the human brain, then you're just not in
> Kansas any more.
If that's the point, I'm well aware of it, and if you
read my archived posts on "hardware progress" I've
even tracked when I expect it to occur.
To sum up an argument I've made in the past, a
machine with one human-equivalent in potential
should take on the order of 20 years to train,
because that's how long we do. Given a 2 year or
so doubling time in computer power, two years later
a 2x human potential machine would take 10 years
to train, etc. so the earliest expected date of
more than trained human ability is 8.5 years after
the first human-equivalent is reached (6 years
for technology improvements + 2.5 years to train).
After that a rapid run-up to the singularity can
occur at any time. One superintelligent machine
may not do that much by iteslf, but if one can
be built, so can many.
Businesses, being economically rational, will employ
machines when they are cheaper than people. If
a machine can do the job of a design engineer, it
is worth on the order of $3 million. That's because
a machine can work 5x the average hours of a human,
and an engineer with fringe benefits and overhead
runs ~$120K/yr x 5 yr econonmic life of the machine.
I use 3x10^6 Gflops as human-equivalent, so it works
out that when computers cost <$1/Gflop, you would
expect them to be deployed in large numbers because
they would be cheaper than people, and after that
the pace of technology development should accelerate.
The last time I projected a date for $1/Gflop, it
was about 2016.
Dani (not Danni by the way) Eder
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