Foundation Model Risks
Percy and Daniel discuss the risks associated with foundation models, including biases, data poisoning, and the challenges of making these models reliable. They delve into the implications of using public data for training and the need for interventions in data collection practices to mitigate harmful outcomes.In this clip
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The Gradient
Percy Liang on Machine Learning Robustness, Foundation Models, and Reproducibility
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