I would be extremely surprised if the motivation for putting bfloat16 in tensorflow was not the TPU. That first public commit was ~1.5 years before TPUv2 was announced at I/O, so it was almost certainly already in development.

bfloat16 was first in DistBelief, so it actually predates TensorFlow and TPUs (I worked on both systems). IIRC the motivation was more about minimizing parameter exchange bandwidth for large-scale CPU clusters rather than minimizing memory bandwidth within accelerators, but the idea generalized.

Thank you! I didn't know this. I thought they introduced them shortly after announcing TPU v1 in the 2016 (or 2017, can't remember) Google I/O.