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open science and AI impact scaling
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Releasing AlphaFold’s predictions for all 200 million proteins maximized global scientific impact
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Releasing AlphaFold’s predictions for all 200 million proteins maximized global scientific impact
Demis Hassabis decided to publicly release AlphaFold’s predictions for all ~200 million known proteins—hosted via the European Bioinformatics Institute—because the system’s speed (seconds per protein) and accuracy enabled unprecedented scale, far exceeding what any single organization could leverage internally.
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we should fold all the proteins because not only was AlphaFold accurate, it was extremely fast. It could fold a protein in a matter of seconds. And then collaborate with, in the end European Bioinformatics Institute in Cambridge which hosts many of the biggest biology databases scientists use, and just host the entire 200 million protein structures on their database and just allow it to be as simple as a Google search to just find your protein structure.
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So most people thought it was at least 10, 20 years away before we would have enough data and the right types of algorithms to tackle that. But we felt that using every technique we knew in the end that we could make progress with that and it turned out to be the case. And then when we decided to, well, how would we make the maximum impact with this? It was obvious to me that
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