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Comment by arnaudsm | Hacker News Reader

Limiting the RAM so AI researchers buy Quadro/Titan cards.

Just like Canon that downgraded their DSLRs to protect their cinema cameras, NVIDIA will loose shares with enthusiasts while AMD (which got solid TF/PyTorch support recently) can finally catch up.

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You will be happy to know that the RTX 3060 has 12GB of VRAM. I try BERT-Large training on it here:

https://www.naut.ca/blog/2021/03/16/rtx-3060-vs-jetson-agx-f...

> Just like Canon that downgraded their DSLRs to protect their cinema cameras, NVIDIA will loose shares with enthusiasts while AMD (which got solid TF/PyTorch support recently) can finally catch up.

Is this for real? As in: I'm thinking about starting to do model training with TensorFlow. I can buy an AMD GPU to use for this and not regret it later?

I always thought that the marketing jargon "cannibalize your market" just meant "create a kick ass product"

I hate marketing.

Here's a tutorial : https://medium.com/analytics-vidhya/install-tensorflow-2-for...

I haven't tested myself, but since I have PTSD from Linux CUDA installations I'm glad competition is finally here.

whether or not the drivers work for quick demos/benchmarks is not really what I care about with AMD, tbh, their ML pipeline sw QA is bad, historically the major problem was long-term stability. Segfaulting 12 hours into a run is not good for an ML practitioner's sanity.

True but without comparable offerings like CUDA, it's not really looking bright tbh. Open CL and open vino are years behind virtually speaking with respect to support.

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