Internally, TPU is much cheaper for the same amount of compute compared to GPU, so I don't see much reasons why they need to use GPU. Probably >99% of compute budgets are spent on TPU. It might be true if you say these <1% still counts, but I guess it is pretty safe to say all of its meaningful production workload are running on TPU. It is simply too expensive to run a meaningful amount of compute on non-TPU.
Just to clarify, TPU has been in development for a decade and it is quite mature these days. Years ago internal consumers had to accept the CPU/GPU and TPU duality but I think this case is getting rarer. I guess this is even more true for DeepMind since itself owns a ML infra team. They likely be able to fix most of the issues with a high priority.
Just to clarify, TPU has been in development for a decade and it is quite mature these days. Years ago internal consumers had to accept the CPU/GPU and TPU duality but I think this case is getting rarer. I guess this is even more true for DeepMind since itself owns a ML infra team. They likely be able to fix most of the issues with a high priority.