Hi Dennis,
Sorry for the long delay in reply, I've been on vacation and am now plowing through a big pile of backed-up emails
To answer your three questions...
1) We have an NLP framework that uses a variation of the carnegie-mellon "link parser" together with a bunch of special "semantic algorithms" for mapping syntactic links into semantic ones, and some probabilistic inference based algorithms for semantic disambiguation & reference resolution. Given a sentence this framework makes a number of prioritized guesses regarding the correct interpretation of the sentence. The user gets to view these guesses and correct them via a UI; for instance, they can select from several possible parses, they can change the selected meaning of a word to a different one (choosing from a menu of known meanings or defining a new one), etc. The overall process is much slower than just freely typing in natural language, but much faster than entering knowledge using an expert system, formal logic based approach.
This will go into commercial use for one of our customers as of early september.
2) Of course, I agree that ambiguity can never be fully eliminated from natural language. NOvamente internally can deal with ambiguity.
3) As for an example of a program generated by Sasha.... In language processing, an example would be an algorithm for reference resolution --- normally one would code such a thing in C++ and stick it in a Novamente MindAgent, but if one codes it in Sasha then Novamente can not only execute it but also study and modify it, because it will be represented in the form of Novamente nodes and links. In a vision context, an example would be an algorithm for edge detection.
This is less far along than INLINK. Right now we are using Sasha to generate programs doing simple math stuff and list manipulations etc. Over the next couple months we will hook it into the rest of Novamente and start using it for applications like the ones described above. The point is, it's a way of getting procedural knowledge into the system in a precise yet learnable/adaptable way. Whereas INLINK is a way of getting declarative knowledge into the system.
Not very much like the process of teaching a human infant, of course. I think that kind of experiential interactive learning is going to be critical to teaching Novamente, BUT, I think it makes sense to augment it with these kinds of tricks like INLINK and Sasha, as a way of overcoming the deficit Novamente has, compared to humans, in terms of its lack of an evolved cognitive endowment.
I plan to write a document on this stuff during the next few days (or perhaps the next week if things go slowly), and I'll post it to the list when I do...
--Ben G
Dennis Gorelik <[EMAIL PROTECTED]> wrote:
Ben,
1) Could you describe what is the architecture of you INLINK
interactive framework?
How is it going to handle natural language?
2) I doubt that it's possible to communicate in natural language
completely unambiguously. There always will be some uncertainty.
Intelligent system itself will have to decide how to interpret
incoming message.
3) Could you give an example of a program which will be generated by
Sasha programming framework?
Sunday, July 4, 2004, 8:58:01 AM, you wrote:
BG> We're developing two powerful methods for communicating with Novamente:
BG> 1) the INLINK interactive NL framework, which allows natural
BG> language to be communicated to Novamente correctly and
BG> unambiguously
BG> 2) the Sasha programming framework, which allows the easy
BG> construction of software programs that manipulate Novamente nodes
BG> and links [and, rapid executable versions of these programs will
BG> be produced via supercompilation, www.supercompilers.com]. Right
BG> now, Novamente MindAgents, the processes that guide Novamente
BG> cognition, are coded as C++ objects which are opaque to Novamente
BG> cognition; but with the advent of Sasha, we'll be able to code
BG> MindAgents as Novamente nodes and links which can in principle be
BG> modified/improved/replaced by Novamente cognition.
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