Sergey Levine(@svlevine):Learning from suboptimal data is important, because robots make suboptimal data on their own, and the more robots there are, the more data they make. If you want to contribute to building a public, open dataset of suboptimal data, check this out!

Sergey Levine

@svlevine

Associate Professor at UC Berkeley Co-founder, Physical Intelligence

参加 April 2018

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Sergey Levine@svlevine

2026.07.31 03:50

Learning from suboptimal data is important, because robots make suboptimal data on their own, and the more robots there are, the more data they make. If you want to contribute to building a public, open dataset of suboptimal data, check this out!

Paul Zhou@zhiyuan_zhou_

2026.07.30 18:40

This is a robot failing to grasp a ball. Almost every robot lab produces clips like this daily… and almost all of them get thrown away. This is the most abundant but underused resource in robot learning. We’re collecting all of it now as ✨OopsieData✨, please join us!