Jay Singh

A model too large for one chip gets split along three axes, each technique answering a different bottleneck, until the binding constraint stops being memory and becomes failure itself.

A loss curve looks like smooth decay, but the real story of training lives in the plateaus, the sudden jumps, and the circuits quietly assembling out of sight.

The transformer replaced recurrence with direct attention, and every major variant since is just a different masking rule applied to the same skeleton.

Deep learning breaks the rules classical statistics says it should obey, and the explanation hides in the geometry of a loss surface too vast to picture.

Quantum mechanics is linear algebra dressed up in physics clothing; the physical content lives in a handful of postulates the math itself never delivers.