JEPA

April 18, 2025

JEPAis an example of a predictive coding architecture. Predictive coding is the idea that the brain works by predicting the next sensory input and learns from the error between the prediction and the actual input. Hierarchies of this kind of prediction allow higher level elements to predict the outputs of lower-level elements, building up deeper and more complex semantics.

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Dynamic Shapes in PyTorch

April 4, 2025

Dynamic shapes are one of the more distinctive parts of torch.compile. Rather than specializing a graph to static shapes (which works in many cases!), PyTorch’s approach allows a single graph to work for a variety of sizes, so things like sequence length or batch size can vary. It does this by reasoning about shapes symbolically: instead of using fixed shape values, it uses placeholders and infers rules that constrain those shapes.

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