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Jensen embraced AI as a way to recover TAM after ASICs took over crypto mining. You can see that between-period in NVidia revenue and profit graphs. By that t

Jensen embraced AI as a way to recover TAM after ASICs took over crypto mining. You can see that between-period in NVidia revenue and profit graphs. By that time, GP-GPU had been around for a long, long time. CUDA still doesn't have much to do with AI - sure, it supports AI usage, even includes some AI-specific features (low-mixed precision blocked operations).

cameldrv 2y ago
Jensen embraced AI way before that. CuDNN was released back in 2014. I remember being at ICLR in 2015, and there were three companies with booths: Google and Facebook who were recruiting, and NVIDIA was selling a 4 GPU desktop computer.
- dartos 2y ago
  Well as soon as matmul has a marketable use (ML predictive algorithms) nvidia was on top of it. I don’t think they were thinking of LLMs in 2014, tbf.
  - throwaway314155 2y ago
    Effectively no one was but LLM's are precisely "ML predictive algorithms". That neural networks more broadly would scale at all on gaming chips is plenty foresight to be impressed with.
  - ghc 2y ago
    I invested in an LLM company in 2014 and nvidia was very aggressive in giving GPUs for use in training models. Their program wasn't targeted specifically at LLMs, but they were definitely aware of the uses. In case anyone is confused, here's an explanatory tweet about one of the founders of that company: https://x.com/jxmnop/status/1725949517940294055 https://x.com/jxmnop/status/1725949517940294055 . LLMs have been in the works for awhile. But you need lots of money to make them good! Even back in 2014 they were mining reddit for training data.
- esjeon 2y ago
  No. At the time, it was about GPGPU, not AI.
aleph_minus_one 2y ago
> Jensen embraced AI as a way to recover TAM after ASICs took over crypto mining. TAM: Total Addressable Market
- samarthr1 2y ago
  Thanks, that was a TIL moment
latchkey 2y ago
ASIC's never took over mining ethereum because the algo was memory hard and producing ASIC's wasn't as profitable as just throwing GPUs at the problem... https://www.vijaypradeep.com/blog/2017-04-28-ethereums-memory-hardness-explained https://www.vijaypradeep.com/blog/2017-04-28-ethereums-memor... At the peak, there were around 18-25m GPUs deployed worldwide. Source: I mined with 150k AMD GPUs.

cameldrv 2y ago

Jensen embraced AI way before that. CuDNN was released back in 2014. I remember being at ICLR in 2015, and there were three companies with booths: Google and Facebook who were recruiting, and NVIDIA was selling a 4 GPU desktop computer.

dartos 2y ago
Well as soon as matmul has a marketable use (ML predictive algorithms) nvidia was on top of it. I don’t think they were thinking of LLMs in 2014, tbf.
- throwaway314155 2y ago
  Effectively no one was but LLM's are precisely "ML predictive algorithms". That neural networks more broadly would scale at all on gaming chips is plenty foresight to be impressed with.
- ghc 2y ago
  I invested in an LLM company in 2014 and nvidia was very aggressive in giving GPUs for use in training models. Their program wasn't targeted specifically at LLMs, but they were definitely aware of the uses. In case anyone is confused, here's an explanatory tweet about one of the founders of that company: https://x.com/jxmnop/status/1725949517940294055 https://x.com/jxmnop/status/1725949517940294055 . LLMs have been in the works for awhile. But you need lots of money to make them good! Even back in 2014 they were mining reddit for training data.
esjeon 2y ago
No. At the time, it was about GPGPU, not AI.

aleph_minus_one 2y ago

> Jensen embraced AI as a way to recover TAM after ASICs took over crypto mining. TAM: Total Addressable Market

samarthr1 2y ago
Thanks, that was a TIL moment

latchkey 2y ago

ASIC's never took over mining ethereum because the algo was memory hard and producing ASIC's wasn't as profitable as just throwing GPUs at the problem... https://www.vijaypradeep.com/blog/2017-04-28-ethereums-memory-hardness-explained https://www.vijaypradeep.com/blog/2017-04-28-ethereums-memor... At the peak, there were around 18-25m GPUs deployed worldwide. Source: I mined with 150k AMD GPUs.