RE: [agi] Intelligence by definition

[Ben Goertzel]

hi,   ***  It seems to me that conceptual difference between vision & language is in the level of generalization, aside from different sensor/actuator orientation. Social Interaction? Once you start coding things that are learnable, where do you stop before ending up with just another expert system?Isn't this all about scalable learning, which should develop environmentally specific functional specialization on it's own?  ***   Well, in Novamente we are not coding *specific knowledge* that is learnable... but we are coding implicit knowledge as to what sorts of learning processes are most useful in which specialized subdomains...     ***  What single algorithm? How do you evaluate 'dealing'? How do you derive/select you algorithms for unknown inputs without first quantitatively defining your objectives? You definition of intelligence doesn't seem to be functional to me, goals can't be defined solely by their complexity.    Without deductive derivation we are stuck with trial & error, which can take millenia.  ***   The Novamente design is mathematically formulated, but not mathematically derived.  That is, individual formulas used in the system are mathematically derived, but the system as a whole has been designed by intuition (based on integrating a lot of different ideas from a lot of different domains) rather than by formal derivation.   In my view, we are nowhere near possessing the right kind of math to derive a realistic AI design from definitions in a rigorous way.  Juergen Schmidhuber's OOPS system is an attempt in this direction, but though I like Juergen's work, I think this design is too simplistic to be a functional AGI.    http://www.idsia.ch/~juergen/oops.html    Maybe further work in the OOPS direction will yield something like what you're suggesting...    ***  Also, the reason human learning is so slow is 'hardware' - specific: it takes a lot longer to build new connections than to access them. That's not the case for computer hardware.  ***   I don't think you're right about the reason human learning is so slow.  It is not just hardware inefficiency, it is the fact that a lot of trial-and-error-based algorithms are used in the brain.    *** That's true, but human brain is an accident of incremental & obviously unfinished evolution, not some grand design.  Besides, I think to some extent these different areas are specialized not so much by genetic design but by the impact of the input types they recieve. In any case, you must admit, this stone age 'design' doesn't perform very well now & it will get worse as the changes accelerate.  ***   The human brain has many flaws and is not a perfect guide for AGI, but it has far more general intelligence than any existing computer program, and so it is certainly worth carefully studying when designing a would-be AGI system.   Novamente is intended to ultimately go beyond what the human brain can accomplish, but for version 1 we'll be contented to achieve human-level general intelligence ;-)   -- Ben Goertzel