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You can only throw so much money at a problem.
This, more or less, is the line being taken by AI researchers in a recent survey. Asked whether "scaling up" current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was "unlikely" or "very unlikely" to succeed.
Published in a new report, the findings of the survey, which queried 475 AI researchers and was conducted by scientists at the Association for the Advancement of Artificial Intelligence, offer a resounding rebuff to the tech industry's long-preferred method of achieving AI gains — by furnishing generative models, and the data centers that are used to train and run them, with more hardware. Given that AGI is what AI developers all claim to be their end game, it's safe to say that scaling is widely seen as a dead end.
"The vast investments in scaling, unaccompanied by any comparable efforts to understand what was going on, always seemed to me...