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I don't really like the term "AGI", and I prefer to use "strong AI" to denote artificial intelligence at human level or above. First of all, because intelligence is never general in any real sense. Human intelligence itself is highly specialized. Specialization is a requirement.
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Second, because "AGI" makes it sounds like intelligence is a binary: either it's general or it's not. In fact, intelligence is more like a spectrum, from intelligence with weaker generalization capabilities, to intelligence with stronger generalization capabilities.
It would be illusory to believe that all we have to do to "solve intelligence" is to reach a specific threshold of "general intelligence", and that our work would then be done. You can't "invent AGI". But you always create intelligence with stronger generalization power.
How much different is this http://theconversation.com/does-playing-chess-make-you-smarter-a-look-at-the-evidence-76062 … than the critiques of Alpha Go and DeepBlue as not being AGI or even AI?
How can we quantify the difference of strong AI from ordinary AI? Should there be a standardized test to measure the IQ of AI? Should we call it AIQ
?
While that sounds convincing, it's contrary to psychological scientific consensus. Evidence strongly suggests a g factor: people who are good at one cognitive task are very likely to be good at another.
I came here to say this. g theory is one of the most dependable findings in psychology
Who used the term general artificial intelligence first? Was it John McCarthy?
General is meant to signify the adaptive nature of the intelligence (as opposed to narrow). A calculator for example is a narrow intelligence. A calculator would be strong intelligence wrt to long division.
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