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I'm super curious why you were optimistic about AGI in the first place? it seem to me that a majority of the performance gains in ML are a result of using bett
by zippy5 6y ago
I'm super curious why you were optimistic about AGI in the first place?
it seem to me that a majority of the performance gains in ML are a result of using better hardware to run brute-force statistics with larger more complex models but the algorithms themselves have been improving at a nominal rate.
- mellosouls 6y agoI'm optimistic about AGI because I see no reason for it not to be implemented (though the time-frame is a different matter). Going by the hype articles (which may be unrepresentative), we just seem to be moving faster and faster on an impressively powerful, but AGI-irrelevant train along a machine "learning" railway track and although I suspect plenty of people on the train would like to get off, the drivers and momentum are making that very difficult, as indicated in the OP article. I'm completely optimistic about AGI, just think we are allowing the excitement of the advances in Artificial Unintelligence over the last few years erroneously dominate our thinking about it - at least in the sort of papers that turn up in tech-related feeds. Again, this may be unrepresentative of the top thinkers in computer science (machine-learning/whatever). My own (layman!) opinion is that the good ideas have and will continue to come from external (or intersecting) fields, philosophy, neuroscience, etc; not computer scientists raving about the power of DeepWhatever using cloud-enabled networks.
- zippy5 6y agoThanks for sharing! I totally agree with you that we seemed to focus a little too narrowly. If you haven't read it already, you might enjoy the book Range awesome look at the impact of interdisciplinary innovation
- mellosouls 6y agoI assume you mean: Range: How Generalists Triumph in a Specialized World by David Epstein. I'll check it out - thank you.