Not sure yet—taking advice. The AI people are narrow AI developers, and the AGI people are those that are actually planning to build an AGI (eg Ben Goertzl).
For a very different perspective from both narrow AI and to a lesser extent Goertzel*, you might want to contact Pat Langley. He is taking a Good Old-Fashioned approach to Artificial General Intelligence:
Goertzel probably approves of all the work Langley does; certainly the reasoning engine of OpenCog is similarly structured. But unlike Langley the OpenCog team thinks there isn’t one true path to human-level intelligence, GOFAI or otherwise.
EDIT: Not that I think you shouldn’t be talking to Goertzel! In fact I think his CogPrime architecture is the only fully fleshed out AGI design which as specified could reach and surpass human intelligence, and the GOLUM meta-AGI architecture is the only FAI design I know of. My only critique is that certain aspects of it are cutting corners, e.g. the rule-based PLN probabilistic reasoning engine vs an actual Bayes net updating engine a la Pearl et al.
Not sure yet—taking advice. The AI people are narrow AI developers, and the AGI people are those that are actually planning to build an AGI (eg Ben Goertzl).
For a very different perspective from both narrow AI and to a lesser extent Goertzel*, you might want to contact Pat Langley. He is taking a Good Old-Fashioned approach to Artificial General Intelligence:
http://www.isle.org/~langley/
His competing AGI conference series:
http://www.cogsys.org/
Goertzel probably approves of all the work Langley does; certainly the reasoning engine of OpenCog is similarly structured. But unlike Langley the OpenCog team thinks there isn’t one true path to human-level intelligence, GOFAI or otherwise.
EDIT: Not that I think you shouldn’t be talking to Goertzel! In fact I think his CogPrime architecture is the only fully fleshed out AGI design which as specified could reach and surpass human intelligence, and the GOLUM meta-AGI architecture is the only FAI design I know of. My only critique is that certain aspects of it are cutting corners, e.g. the rule-based PLN probabilistic reasoning engine vs an actual Bayes net updating engine a la Pearl et al.
Thanks!