Predictive Training with Future Embeddings
cephaloform · x · 2026-07-13
The author suggests that instead of merely reconstructing current embeddings, training objectives might yield better results by simultaneously predicting future or past embeddings.
They also expressed surprise that no one has yet applied NLA (Nonlinear Analysis/Modeling) to encoded sensor readings to build digital twins of real-world dynamic systems, such as a tree.
Related event: Exploring NLA for Digital Twins of Real-World Dynamic Systems(2 posts)→
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