AI Has Already Run Out of Training Data, Goldman's Data Chief Says

AI has run out of training data, according to Neema Raphael, Goldman Sachs' chief data officer and head of data engineering. "We've already run out of data," Raphael said on the bank's podcast. He said this shortage is already shaping how developers build new AI systems. China's DeepSeek may have kept costs down by training on outputs from existing models instead of fresh data. The web has been tapped out. Developers have been using synthetic data -- machine-generated material that offers unlimited supply but carries quality risks. Raphael said he doesn't think the lack of fresh data will be a massive constraint. "From an enterprise perspective, I think there's still a lot of juice I'd say to be squeezed in that," he said. Proprietary datasets held by corporations could make AI tools far more valuable. The challenge is "understanding the data, understanding the business context of the data, and then being able to normalize it."

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