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All of this work suggests that under the hood, today’s AIs are overly complicated, patched-together Rube Goldberg machines full of ad-hoc solutions for answering our prompts.NEIN!!!Understanding that these systems are long lists of cobbled-together rules of thumb could go a long way to explaining why they struggle when they’re asked to do things even a little bit outside their training, says Vafa.DOCH!!!This research also suggests why many models are so massive: They have to memorize an endless list of rules of thumb, and can’t compress that knowledge into a mental model like a person can. It might also help explain why they have to learn on such enormous amounts of data, where a person can pick something up after just a few trials: To derive all those individual rules of thumb, they have to see every possible combination of words, images, game-board positions and the like. And to really train them well, they need to see those combinations over and over.OOOOOOH!!!Scheiße, Bernd! Hätte uns nur jemand rechtzeitig gesagt, dass das Bullshit ist!