Exactly. To me and I’d bet most others in the field machine learning is just a powerful tool to enable new things that weren’t previously doable. Acting like it’s a wasted effort because you don’t think it’ll lead to AGI is just silly. It’s not just about AGI.https://twitter.com/tdietterich/status/1203189592712568832 …
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Replying to @citnaj
Ok, but I can't really see any reason why deep learning won't (some day in the "distant" future) lead to something that can be called human-like intelligence. CNN already approximate human visual cortex, reinforcement learning already produces human-like strategies to win games.
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And deep learning is just 7 years old, imagine the breadth it'll have when it will become a "mature" discipline with solid software engineering principles embedded into it and universally recognized.
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I don’t think that it is a proper characterization to say DL is around 7 years old. Some of the core ideas are at least 25-30 years old. However lack of data, computing power and organized, large-scale sharing (GitHub) among practitioners restricted its scope earlier.
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It’s really even older than that depending on how you look at it. It goes back to the perceptrons of 60 years ago! But indeed the term “deep learning” was basically a rebranding of neural networks, which were way out of style previously.
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Absolutely! What I meant was some of the most celebrated aspects of DL (or less ambiguously end-to-end representation learning) today (CNN, LSTM, two agents learning adversarially against each other - to name a few) were already fleshed out by mid nineties.
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This is really important to remember and acknowledge! Good things take time.
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