The reliance on public data — mostly web data — to train AI is holding back the AI field. That’s according to Daniel Beutel, a tech entrepreneur and researcher at the University of Cambridge, who co-founded a startup, Flower, to solve what he sees as a growing problem in AI research.
“Public, centralized data is only a tiny fraction of all the data in the world,” Beutel told TechCrunch in an email interview. “In contrast, distributed data — the data that’s trapped on devices like phones, wearables and internet of things devices or in organizational silos, such as business units within an enterprises — is much larger and more comprehensive, but out of reach for AI today.”
Flower, which Beutel co-started in 2020 with Cambridge colleagues Taner Topal and Nicholas Lane, the ex-head of Samsung’s AI Center in Cambridge, is an attempt to “decentralize” the AI training process through a platform that allows developers to train models on dat...
