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What is contrastive / metric learning, and how does it learn good embeddings?

Contrastive learning is how modern embeddings (CLIP, sentence encoders, SimCLR) are actually trained. The signal is the pull-positives-push-negatives objective, the InfoNCE loss, and why the number and hardness of negatives makes or breaks quality.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Contrastive learning is how modern embeddings (CLIP, sentence encoders, SimCLR) are actually trained. The signal is the pull-positives-push-negatives objective, the InfoNCE loss, and why the number and hardness of negatives makes or breaks quality.

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