--- Benjamin Goertzel <[EMAIL PROTECTED]> wrote:

> On 5/3/07, Mike Tintner <[EMAIL PROTECTED]> wrote:
> >
> >  James,
> >
> > It's interesting - there is a general huge block here - and culture-wide -
> > to thinking about intelligence in terms of problems as opposed to the
> means
> > and media of solution (or if you like the tasks vs the tools).
> >
> 
> 
> What you seem to be missing, Mike, is that the approach you are advocating
> is EXACTLY THE APPROACH TAKEN BY THE MAINSTREAM OF ACADEMIC AI RESEARCH
> TODAY.
> 
> If you go to the AAAI conference, you can see 1000 papers presented
> discussing AI in the context of particular problems, problem classes, etc.
> 
> There is really nothing unusual about what you are suggesting.  It's just
> that this particular email list is dominated by people who have decided a
> different approach is more promising.

Maybe that is why this group is like a race where everyone has drawn their own
finish line.

> Your list is all about means - AGI that uses this language or that, and that
> > uses a body or not. Similarly, Pei's and Ben's expositions of their
> systems
> > are all about how-it-works rather than what-it-does.
> >
> 
> 
> Because how-it-works is the hard part!   What-it-does is not the hard part.

Sorry, I disagree.  If you focus on how it works, you end up with a system
whose inner workings are well understood, but nevertheless useless, like Cyc.

You need MEASURABLE goals on REAL data.  I don't mean to be critical, but if
your system is trained in a sim world with artificial language, you end up
with a big Blocks World.  You simply can't simulate the high algorithmic
complexity of real data.  And real data is hard to collect.

I admit my own approach (text compression) hasn't worked either.  If you look
at the progression of winning programs, you'll see an endless series of tweaks
of thousands of parameters, with no real insights into how natural language is
understood.

Yeah, we need another approach, maybe genetically engineering monkeys for
bigger brains.


-- Matt Mahoney, [EMAIL PROTECTED]

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