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This is an interesting comment - where would you draw the line between AI and applied statistics? A lot of AI which happens to be ML (not saying there is non-ML
by abhgh 8y ago
This is an interesting comment - where would you draw the line between AI and applied statistics? A lot of AI which happens to be ML (not saying there is non-ML AI, just that a significant chunk of AI being practiced today is ML) also happens to be applied statistics. Or have statistical interpretations.
Also, because something has been around for decades does not make it not AI. For ex the cheque OCR mentioned probably runs off (or can feasibly run off) of a neural network. I think the parent's comment holds well - not sure about the last line though ...
- ModernMech 8y agoThe line is clear: everything today branded "AI" is just applied statistics. AI is a buzzword. I don't know what the definition of intelligence is, but I have a feeling it doesn't rest anywhere near concepts like function approximation, and that's all even the most sophisticated "AIs" at Google or Facebook or Apple boil down to.
- abhgh 8y agoWhat was not clear from your earlier comment, and is now, is that when you say AI you don't mean AI as is practiced by most of academia and the industry but the vision of Artificial General Intelligence (AGI). If so, yes, that's a good point to make. However, it is debatable whether the path of statistical learning wont lead to AGI, or is not how our brains function, or the truth partly does comprise of statistical learning and part of something else. The Norvig-Chomsky debate is an example of the arguments on both sides.
- ModernMech 8y agoI didn't make an earlier comment. You're replying to my one and only comment. > when you say AI you don't mean AI as is practiced by most of academia and the industry but the vision of Artificial General Intelligence (AGI). What I actually mean is people practicing what they call "AI" in academia and the industry have co-opted the name to make what they do sound more interesting. First it was called "statistics". Then it was called "pattern matching". Then it was called "machine learning". Now it's called "AI". But it hasn't changed meaningfully through any iteration of these labels.
- abhgh 8y agoOops, sorry! To your point, I agree. They hype around the area has evolved much faster than the area itself.
- blt 8y agoI don't really think that characterization is fair, for example GANs, there is no data set of correct input output pairs for the function that is learned.
- sullyj3 8y agoIf you can definitely a problem rigorously, you've essentially defined a function. So "function approximation" is basically "general problem solving approximation".