Can they just start investing in software so folks from ml/deep learning field can just get out from nvidia monopoly -.-
MI100 finally brings hardware accelerated matrix-multiplication to the table (bfloat16, FP16, and even FP32 matrix multiplication).
Now that MI100 has matrix-multiplication units, now comes the part where that is distributed to the software. (Hooking up TensorFlow to use them).
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Without Matrix Multiplication units, there was really no point even writing software (aside from maybe preparation of the eventual rise of AMD's matrix-multiplication routines).
But 6800 XT won't have matrix-multiplication units. Only the CDNA architecture has those. So I'm not entirely sure if 6800 XT would even be an adequate competitor to deep learning applications, even if ROCm supported it entirely.
They don't. GOOG rents them.
https://cloud.google.com/terms/service-terms Service Specific Terms -> AI and Machine Learning.
You can't use Google's fully-trained models as a reference in order to train your own models. Lower-level uses of TPUs to train your own models from your own training data are unrelated to those restrictions.
Certainly nothing in the Acceptable Use Policy looks anti-competitive to me.
Obvious disclaimer is obvious: IANAL.