Unsupervised Learning Insights
Craig discusses the effectiveness of using unsupervised learning with deep nets, emphasizing how representations from image patches can lead to accurate classifications without labeled data. He highlights the importance of data augmentation techniques, like altering color balance, to prevent models from relying on simple visual cues. The conversation also touches on the relationship between unsupervised methods and contrastive learning, drawing parallels to video frame prediction.In this clip
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Eye on AI
Geoffrey Everest Hinton reviews his work in 2020 and talks about what he sees on the AI horizon
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