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The idea seemed to many nothing short of absurdity. Before then, models were already considered large-scale if trained on a few dozen chips. In top academic labs at MIT and Stanford, PhD students considered it a luxury to have ten chips. In universities outside the US, such as in India, students were lucky to share a single chip with multiple peers, making do with a fraction of a GPU for their research.
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