“Speed Limit for Information Acquisition in Stochastic Learning Dynamics” SGD doesn’t just optimize parameters, it gradually encodes information about latent structure in the data. This paper models SGD as a stochastic process and derives a Fisher-information speed limit that upper-bounds how fast model parameters can acquire information, separating contributions from deterministic gradient drift and minibatch noise. In linear regression, the bound predicts which latent variables are learned…