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This breaks my brain, because I know Google trains it models on TPUs and they're seen as faster, and if they're better at inference, and can train, then why is
by refulgentis 2y ago
This breaks my brain, because I know Google trains it models on TPUs and they're seen as faster, and if they're better at inference, and can train, then why is Nvidia in a unique position? My understanding was always it's as simple as it required esoteric tooling
- smueller1234 2y agoMultiple types of TPUs. (I work for Google, but the above is public information.)
- vineyardmike 2y agoBecause people generally don’t use TPUs outside of Google. The tooling is different, the access is metered through GCP, etc. Nvidia is in a vaguely unique position in that their products have great tooling support and few companies sell silicon at their scale.
- refulgentis 2y agoCorrect, I'm pointing out politely that's in conflict with the person I'm replying to.
- koe123 2y agoPossibly naive but I very much view CUDA and its integration into ML frameworks being nvidias moat