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We can call it a data optimization problem, but that does not tell us anything about how we go about solving it, or even what we are optimizing for. Alternativ

• joe_the_user 8y ago
  "We can call it a data optimization problem, but that does not tell us anything about how we go about solving it, or even what we are optimizing for." If you have a time-ordered stream of data, the problem of predicting the output given previous input naturally suggests itself. There are other approaches, of course. "Alternatively, perhaps what's being optimized is so general that generalized AI is not, and cannot be, 'just' an optimization problem in any useful sense." - Perhaps you mean this as "the problem is so complex that it can't be naively approached only with conventional, local optimization tools". Because a huge optimization problem is still an optimization problem in some meaningful senses, I mean I could consider my life as a "fun" or "flow" or "enlightenment" optimization problem. In general, it seems like a lot of reactions to particular AI methods go from "this approach isn't enough to get us all the way there" to "real AI is fundamentally, absolutely different from this, this approach is useless", a jump I don't think is justified.