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Less study material in its dataset I should think -- you would do well on the GRE too if you memorized every study guide on the internet.
Then that suggests that it's GRE score is not an effective measure of its "IQ"
I have a vested interest in the GRE being an effective measure because it would make me rather high IQ lol.
So as a defense of the GRE I will let it be known that ETS (GRE test makers) hires a suspiciously large number of psychometric PhDs, the last time I checked more than half the job openings were for psychometricians, and they know exactly what they are doing (making a socially acceptable IQ test). If its bad at that, it's probably not for a lack of trying.
And that an "IQ test" a language model has an advantage on, probably because of plenty of training data doesn't imply humans are prone to that failure (success) mode of the test. Not for a difference in kind but magnitude, no human reads literal billions of tokens.
I don't know what the implications/inferences are. It's certainly interesting that a LLM can do non first order quantitative reasoning questions at all to me. Suggests to me that is there an overlap of language and quantitative reasoning in whatsoever space GPT is pulling its inferences from, might even be universal.
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Sure -- same goes for the tests that it did score well on though.
Ed: sorry misread -- yes, that's exactly what I'm suggesting. All of the tests they are giving it are testing its ability to memorize study material from its training set -- which may be useful for some things, but in no sense is "intelligence", particularly not "intelligence" as in "Artificial General Intelligence"
Ideally one could test this by writing a test of pretty low difficulty level (say tenth grade non-advanced math) but with questions framed in a completely different way from the AP/SAT type stuff in the dataset. Then compare results with an actual tenth grader.
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