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I am very impressed with what Google has done for the state of machine learning infrastructure. I'm looking forward to future models based on OpenXLA which can
by reaperman 4y ago
I am very impressed with what Google has done for the state of machine learning infrastructure. I'm looking forward to future models based on OpenXLA which can run between Nvidia, Apple Silicon, and google's TPU's. My main limiter to using TPU more often is model compatibility. The TPU hardware is clearly the very best, just not always cost-effective for those of us who are starved of available engineering hours. OpenXLA may fix this if it lives up to its promise.
That said, it's also incredible how fast things move in this space:
> Midjourney, one of the leading text-to-image AI startups, have been using Cloud TPU v4 to train their state-of-the-art model, coincidentally also called “version four”.
Midjourney is already on v5 as of the date of publication of this press release.
- nestorD 4y ago> model compatibility JAX will compile your model with XLA today, letting you run it on Nvidia, Apple Silicon (CPU for now), google's TPU, etc. Overall, XLA really shines on TPUs, is doing very well on GPUs and sadly lags behind on CPUs (reaching about single core performance). As a bonus, JAX is basically Numpy++: you can use it to build scientific/numerical software and run it easily on GPU and TPU!
- gallabytes 4y agoyeah we trained v5 on TPUs and continue to train on them.