On Wed, Dec 26, 2012 at 1:10 AM, Ben Goertzel <b...@goertzel.org> wrote:
> At this moment, Watson is certainly a  more impressively demonstrable
> system than OpenCog.  It also is the result of massively more
> man-years (and even massively more dollars) of effort, of course...

Watson is 20 people for 3 years and $3 million for hardware. What is
it for OpenCog?

> If OpenCog is successful it will lead (at some time well before it
> hypothetically leads to a human-level AGI) to an English dialogue
> system that is able to flexibly, common-sensically converse about what
> a virtual or robotic agent is experiencing...
>
> As I am not the one obsessed with quantitative metrics, boiling that
> down into a formal test is not really my problem...

Is any work being done on language at all? I've seen no mention of it
since the 2010 puppy demo.

> I would imagine that if one formulated a highly precise test for
> "flexible, common-sensical conversation about the experiences of a
> virtual or robotic agent", then some Watson-like approach might well
> work for passing that test ------ even though this approach would not
> be effectively generalizable to human-level AGI.....  But if we got to
> this level with an OpenCog system, I believe we would be well on the
> path to human-level AGI

Do you think that rule based systems like RelEx and NatGen are a
viable approach to the problem?

Not that I am ruling it out. I think Watson uses rule based parsing in
many of its 100 or so techniques. The input to Watson generally lacks
spelling and grammar errors. OTOH, Google uses statistical methods to
deal with noise, but lacks the ability to analyze complex sentence
structures.

I'm interested in what approach you plan to take and how you plan to
evaluate the results (or not).

--
-- Matt Mahoney, mattmahone...@gmail.com


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