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Eric Schmidt · Anthropic · Demis Hassabis · Claude · Google ·

Every few decades, someone publishes that science has reached its end

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In 1903, the revered physicist Albert Michelson wrote that the “facts of physical science have all been discovered.” In the 1980s, Stephen Hawking predicted that theoretical physics might be finished by the end of the century.

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Every few decades, someone announces that science has reached its end. In 2024, Demis Hassabis and John Jumper of Google DeepMind were awarded part of the Nobel in chemistry for their neural network AlphaFold, which predicts the three-dimensional structures of proteins by learning from thousands of experimentally measured shapes. To be sure, AI will bring extraordinary changes to science, but it has become increasingly clear that AlphaFold, and things like it, may not be the best template for that metamorphosis. The primary condition for AlphaFold’s success was the existence of the Protein Data Bank, a data set of roughly 170,000 experimentally validated protein structures on which DeepMind’s team could train its model. But even in fields with the requisite cohesion and resources, and where the relevant data are not rendered inaccessible by commercial ownership, another barrier is too little discussed: the scientific impossibility of generating comparable data.

Read full article at MIT Technology Review →

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