On Tue, Jul 16, 2013 at 4:52 AM, Jim Bromer <[email protected]> wrote:

> a simple initial feasibility test may be designed around this format as a
> means of designing a way for a computer program to learn direction from a
> human user so that it can further discover interesting ways to acquire
> structured knowledge



Jim,

We have nothing against intentions to experiment, even though we slightly
prefer the results of experiments over the intentions - not that I am not
guilty of the same crime, mind you. Now, scalability is the number one risk
of wannabe intelligent systems, and you are not going to escape the problem
by avoiding the discussion or the formalization. I will kindly remind you
that learning systems abound in the 50 year old history of the field, even
though I believe the right mix of ambition and resources was not there 99%
of the time. Now, what kind of learning you want to do? In my humble
opinion it does not get any more simple than template learning or Bayesian
learning. In the first you are more in "canned response" territory, in that
you can save/remember your entire "lifestream" of inputs and the choose
"rewarding" outputs based on similarity metrics (nearest neighbor,
whatever) between your actual input and previously rewarding output. In
Bayesian learning, which is not at all uncommon biologically despite taking
mathematicians thousands of years to formulate it, you probably can account
for a slightly more dynamic world (like one in which "I am hungry" only
gets you food half of the time or once a day). I guess the Bayesian world
would be driven by random number generators that will regularly break away
from canned responses. Both "solutions" are mathematically
multidimensional, or rather dimensionally cursed, if the problem domain is
not a toy then the implied mathematical objects are pretty enormous.
​
Do I think any such model can scale to human-level intelligence? Not
really. Do I think it can provide a lifetime of hobbyist entertainment? I
sure do. Is there learning of a third kind? I doubt it.

I will briefly restate my hunch; human-level intelligence will need a lot
of real world statistics that more generally enable loads of heuristics,
all at the service of real world simulations, possibly agent-based ones,
that are scrutinized quickly and result in appropriate action.

AT



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AGI
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