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Learning Edge Cases with Self-Supervised Machine Learning
The podcast discusses the use of self-supervised machine learning for learning edge cases with a learned discovery mechanism that goes beyond just looking at similar or dissimilar images, but rather identifying images that are somewhere in between. The resulting edge cases are then sent back for annotation to improve the learning process.