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JEPA

technique
Last discussed Aug 8, 2026

Joint Embedding Predictive Architecture - a training technique developed by Yann LeCun for world models.

What creators say

GW
Guanming Wang
mentioned
Used for: Learning to predict future observations using MSE loss between current and future latent encodings vs: Contrasted with distribution-based approaches that treat the future as a dist...

"Some people, like LeCun, they were doing JEPA. They think about maybe we can have two different encoders — one encoding the current observation and the other encoding a future observation. By doing loss on the current observation latent and the fu..."

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Cal Newport
mentioned
Used for: Training world models with high-level representations

"If you've heard of JEPA, Joint Embedding Predictive Architecture, this is a new training technique that LeCun came up with for training a world model"

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