3 ms·

We know very little about intelligence, really. We don't know of any attributes that can reliably predict genial achievement. We can't even say for certain tha

We know very little about intelligence, really. We don't know of any attributes that can reliably predict genial achievement. We can't even say for certain that what your geniuses of choice has more of, is the same thing we have more of than animals. It's easy to imagine supergeniuses, but as soon as you try to describe rigorously what they should be capable of, you're immediately on shakier ground. It's a bit like imagining future computer programs. We're doing a lot of things with our computers today that people couldn't have imagined 40 years ago, or outright rejected (my father's thesis advisor asserted that computers would get a lot more powerful, but would never become powerful enough to compute with images). But there are also a lot of things they thought would be easy, which turned out hard, or even impossible. In computer science, we have some ideas of the "hard limits", since the field started with Turing and computational complexity theory has progressed steadily. For human-like intelligence, or "general learning", we know very little (except that every hard limit we know from computer science applies to brains too!).

joe_the_user 10y ago
"We know very little about intelligence, really. We don't know of any attributes that can reliably predict genial achievement. "We can't even say for certain that what your geniuses of choice has more of, is the same thing we have more of than animals." Agreed. It could even be that thing that makes these "geniuses" is simply circumstances. Regardless, the various human beings who accomplish an incredible amount in certain ways show that accomplish such advances is possible for material object. This is in contrast to looking at a apparently semi-random stream of data and expecting to predict N times better than ordinary statistics. It's merely "some reason to think things are possible" versus "no a-priori reason to think it is possible". Also, with computing, even a lot of complexity theory is hard interpret. For example, a fair portion of NP-complete problems (such as SAT) are actually reasonably easy most of the time, with the theoretical worst exponential case performance being fairly rare.

joe_the_user 10y ago

"We know very little about intelligence, really. We don't know of any attributes that can reliably predict genial achievement. "We can't even say for certain that what your geniuses of choice has more of, is the same thing we have more of than animals." Agreed. It could even be that thing that makes these "geniuses" is simply circumstances. Regardless, the various human beings who accomplish an incredible amount in certain ways show that accomplish such advances is possible for material object. This is in contrast to looking at a apparently semi-random stream of data and expecting to predict N times better than ordinary statistics. It's merely "some reason to think things are possible" versus "no a-priori reason to think it is possible". Also, with computing, even a lot of complexity theory is hard interpret. For example, a fair portion of NP-complete problems (such as SAT) are actually reasonably easy most of the time, with the theoretical worst exponential case performance being fairly rare.