Re: What is the state of Robotics Currently.

fox@xxxxxxxxxxxxxxxxxxx wrote:

All of the problems except economic and engineering ones have been
solved. AI has been more advanced than most hobbiests realize for a
long time.

My main interest is in AI, not robotics. I am a hobbyist but yet a still
have I have a good understanding of the field of AI. No one has invented a
machine than can learn, on its own, to do all those things. The current
learning algorithms are very limited. They tend to only be applied, and
work with, very specific toy problems.

I tend to be optimistic about how long that's going to take (I've
recently made another 10 year bet on the subject), but it's possible it
will still take another 50 or 100 years to duplicate human level
learning skills.

You are not taking into account the fact that human learning skills
are not a fixed quantity. Average human skills are dropping about as
fast as computer capabilities are rising.

I've never heard that reported. What data is there to support that idea?

Even so a million dollar humaniod robot is closer to a goldfish than
to a minimum wage human worker in practical functionality today.

True.

This is the technology that's holding robotics back and no one
really knows how long it's going to take to solve.

Decent vision, voice, reflexes, navigation, planning, and general
purpose learning and reasoning are out of the range of computing
toys today but we are pretty close. They are way out of the range
of most toy robot.

Right. There are reasons I made the bet that human level machine
intelligence would be here in the next 10 years. (9 now). I think we are
closer than most people believe.

Consider that if a neuron can be simulated with 100 instructions
per second a thousand dollar laptop can simulate 10^7
interconnected neurons and 10^4 of them interconnected could
do much of what a person does with a couple pounds of grey
matter. Now once you figure out how to get that ten million
dollars worth of computers and megawatt power supply
inside the head of that humanoid android that you want to
replace your minimum wage servant you have solved an
important remaining problem. Then you just have a few
other engineering problems to get those other manufacturing
costs and maintanence costs down below those of a jumbo
jet.

Well, those calculates are very questionable (as are all attempts to
estimate the amount of computing power to duplicate human intelligence
since no one knows what computer power is needed - it's still an apples to
oranges comparison at best).

How many instructions per second does it take to simulate a transistor
which can switch a billion times per second in a digital circuit? Neurons
fire around 1000 times per second max and you said it takes 100
instructions per second to simulate one so I assume this means you would
estimate 10^8 instructions per second to simulate a transistor. Using this
logic, it would take a building full of interconnected lap tops just to
duplicate the power of a single CPU chip. And that of course is absurd
because we know it only takes one CPU chip to duplicate a CPU chip and not
a building full of lap tops.

We don't need to simulate transistors to create a computer, and we won't
create intelligent machines by simulating neurons in software. Cortex
simulation projects are great research tools, but they are not going to be
the basis of real intelligent machines any more than SPICE circuit
emulators are used to build radios.

The problem with estimating the amount of hardware that's needed to
duplicate human level intelligence is that we don't yet know how to build
it, and if we can't build it, all estimations of how much hardware it's
going to take are likely to be way off base - in either direction.

For example, with neurons switching at 1000 times per second and 100
billion of them in a brain, you get hardware with a max speed of around
10^14 operations per second. But transistors can switch 10^9 times per
second so you only need 10^5 transistors to get the same max switching
performance. A lap top with 1 GB of memory has over 8x10^9 transistors in
it (one per every bit of memory). That means a single lap top has 80,000
times more computing power than a human brain.

Now, I'm not trying to argue that this is a valid way to estimate the
amount of hardware required, but I am tying to argue that it's probably no
less valid than your numbers. A lap top sized board full of custom chips
has more information processing power than than a human brain. But once we
understand how to build human level intelligence into a machine, will we be
able to do build it in that form? We just don't know yet since no one
knows how to build it in any form.

I suspect however that as we finish mastering the technology, that is
exactly what we will end up with - custom hardware that if built with
today's electronics technology, would only be the size of desk top
computer.

Neurons range from 4 to 100 microns in size. Transistors are below .25
microns now. Large parts of the brain is filled with interconnects (white
matter), computers reduce interconnects by using high speed switching and
sharing interconnects. Evolution didn't have access to high speed
switching devices so to keep response time low, it had to use massive
interconnects. When we redesign with a different technology (transistors
instead of neurons) we will end up with a very different architecture.
It's likely a design with more switching devices (transistors) and fewer
interconnects will be the optimal solution when building with the higher
speed transistors. In the end, I expect our machines will be substantially
smaller than a human brain in order to duplicate it's same power.

All we can do is make
some wild guesses. (and work hard to solve it).

I heard that a lot fourty years ago before better and better
solutions to most problems were demonstrated.

Of course, remember that people argued that controled
heavier than air flying machines were simply impossible
for years after the Wright Brothers demonstrated it,

Yeah, I was just reading about the amount resistance the idea got.
Interesting stuff.

The real problems are neither AI nor econcomics. They
sort themselves out. The real problems are social just
as was predicted fifty years ago.

Well, the social issues are sorting themselves out as well. There's a lot
of momentum to be overcome. A surprisingly huge percentage of the
population still doesn't believe in evolution after 150 years. But like
the Wright brothers, once you build something that works, it doesn't take
long to make society believe. I believe it was only a few years to get rid
of the doubters in the case of the Wright Brothers work. With the speed of
communication we have today, word would spread very fast - if only we had
something to show them.

--
Curt Welch http://CurtWelch.Com/
curt@xxxxxxxx http://NewsReader.Com/
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