zlacker

>>snewma+(OP)
Cyc ("Syke") is one of those projects I've long found vaguely fascinating though I've never had the time / spoons to look into it significantly. It's an AI project based on a comprehensive ontology and knowledgebase.

Wikipedia's overview: <https://en.wikipedia.org/wiki/Cyc>

Project / company homepage: <https://cyc.com/>

>>dredmo+83
I worked with Cyc. It was an impressive attempt to do the thing that it does, but it didn't work out. It was the last great attempt to do AI in the "neat" fashion, and its failure helped bring about the current, wildly successful "scruffy" approaches to AI.

It's failure is no shade against Doug. Somebody had to try it, and I'm glad it was one of the brightest guys around. I think he clung on to it long after it was clear that it wasn't going to work out, but breakthroughs do happen. (The current round of machine learning itself is a revival of a technique that had been abandoned, but people who stuck with it anyway discovered the tricks that made it go.)

>>jfenge+B7
Why did it didn't work out ?

>>Kuinox+Jc
Take a look at https://en.m.wikipedia.org/wiki/SHRDLU

Cyc is sort of like that, but for everything. Not just a small limited world. I believe it didn’t work out because it’s really hard.

>>jfoutz+0f
If we are to develop understandable AGI, I think that some kind of (mathematically correct) probabilistic reasoning based on a symbolic knowledge base is the way to go. You would probably need to have some version of a Neural Net on the front end to make it useful though.

So you'd use the NN to recognize that the thing in front of the camera is a cat, and that would be fed into the symbolic knowledge base for further reasoning.

The knowledge base will contain facts like the cat is likely to "meow" at some point, especially if it wants attention. Based on the relevant context, the knowledge base would also know that the cat is unlikely to be able to talk, unless it is a cat in a work of fiction, for example.