A slight sidetrack from pure Everything topics...

On Saturday, November 30, 2002, at 06:44 PM, Ben Goertzel wrote:
(stuff about physics which we are partly in agreement about, mostly not in agreement about...no point in arguing it further right now)

Well, that depends perhaps on what you mean by "new physics," I think.

Right now our physics is basically stumped by most complex systems. We
resort to

-- computer simulations
-- crude "phenomenological" models
Except I'll add that I don't agree physics is stumped by most complex systems. Physics doesn't try to explain messy and grungy situations, nor should it. Turbulence is a special case, and I expect progress will be made, especially using math (which is why Navier-Stokes issues are on the same list with other math problems for the prize money).

(For example, some friends of mine are doing interesting work on using
systems of several million machine agents to data mine large amounts of
financial data. It seems likely that this kind of work on machine
learning, pattern extraction, support vector machines, and a plethora
of other "AI tools" will have major effects on the world of economics
and forecasting. And on creating financial derivatives (synthetics)
which are alien to human thinkers/investors.)
Yeah, financial forecasting with AI does not require Artificial General
Intelligence (AGI) in any sense, it is a classic domain-specific narrow-AI

Whereas, coming up with new physics will require a significant degree of
general intelligence, I believe.

In this sense, physics theorizing is certainly a much harder problem than
financial prediction-- it's hard to argue with that!!

I tend not to even consider that kind of narrow-AI work "AI" -- I just think
of it as computer science. But I have to remind myself periodically that
the mainstream of academia does consider this AI, and considers AGI work to
be a foolish and faraway dream...

Funding is the key issue. Someday I'll write a thing for this list about successes vs. failures in terms of auto-funding each successive stage of a complex technological path. In a nutshell, the electronics/computer industry was essentially self-funding for the past 50 years, with the products of 1962, for example, paying for the work that led to the 1965 products. Same thing with aviation.

By contrast, space development and controlled fusion have not been. We "know" that there exists a reasonable combination of ignition temperature-containment time--cost that lies several orders of magnitude away in Temp-time-power-cost space, but getting there is like crossing the Gobi desert without any watering holes or fuel stops on the way.

The difference between "island colonization" models, akin to colonizing the fertile U.S. heartland (automobiles, aviation, electronics, etc.), versus "desert travel" models, akin to funding the first commercial fusion reactor or building the first space colony, is crucial.

It is unlikely that the "path to AI" will be successful if there are not numerous intermediate successes and ways to make a _lot_ of money.

My tip to all AI workers is to look for those things. (This is more than just banal advice about "try to make money," I am hoping. I have seen too many tech enthusiasts clamoring for "moon shots" to fund what they think is needed...))

The ""AGI" may come from the distant great-great grandchild of financial AI systems.

--Tim May
"Dogs can't conceive of a group of cats without an alpha cat." --David Honig, on the Cypherpunks list, 2001-11

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