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I don’t think it will be a crash per se, I just think that at some point every major cloud provider will build their own silicon and this will drive demand for

I don’t think it will be a crash per se, I just think that at some point every major cloud provider will build their own silicon and this will drive demand for NVidia’s cards down by a lot. It will take some years for it to happen, but it will happen eventually.

ryandvm 2y ago
Not implausible, but I'd say we're 10 years out from the FAANGs replacing their silicon AND CUDA.
- Jensson 2y ago
  Google is already there, others are starting to look at it. And one of them might sell to the others if it becomes profitable enough.
  - Daishiman 2y ago
    Yeah but google has shown complete ineptitude at selling anything that’s not their cash cow and the change in culture doesn’t seem close by.
- mrbungie 2y ago
  Gemini might not be as cool as GPT, but it already runs on TPUs. So the "G" in FAANG is not as dependent on Nvidia as the others.
- matwood 2y ago
  It doesn't have to be a full replacement. Meta for example is already running both. Interesting how they state [1]: "This announcement is one step in our ambitious infrastructure roadmap. By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s." 350k NVDA GPUs, but the compute power of 600k. See here for how quickly their silicon is advancing [2]. No one is saying NVDA will go away. But the stock is priced for near perfect growth projections. NVDA's second biggest customer like Meta cutting back even just a bit will hit NVDA's bottom line. That's the stock risk. [1] https://engineering.fb.com/2024/03/12/data-center-engineering/building-metas-genai-infrastructure/ https://engineering.fb.com/2024/03/12/data-center-engineerin... [2] https://ai.meta.com/blog/next-generation-meta-training-inference-accelerator-AI-MTIA/ https://ai.meta.com/blog/next-generation-meta-training-infer...

ryandvm 2y ago

Not implausible, but I'd say we're 10 years out from the FAANGs replacing their silicon AND CUDA.

Jensson 2y ago
Google is already there, others are starting to look at it. And one of them might sell to the others if it becomes profitable enough.
- Daishiman 2y ago
  Yeah but google has shown complete ineptitude at selling anything that’s not their cash cow and the change in culture doesn’t seem close by.
mrbungie 2y ago
Gemini might not be as cool as GPT, but it already runs on TPUs. So the "G" in FAANG is not as dependent on Nvidia as the others.
matwood 2y ago
It doesn't have to be a full replacement. Meta for example is already running both. Interesting how they state [1]: "This announcement is one step in our ambitious infrastructure roadmap. By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s." 350k NVDA GPUs, but the compute power of 600k. See here for how quickly their silicon is advancing [2]. No one is saying NVDA will go away. But the stock is priced for near perfect growth projections. NVDA's second biggest customer like Meta cutting back even just a bit will hit NVDA's bottom line. That's the stock risk. [1] https://engineering.fb.com/2024/03/12/data-center-engineering/building-metas-genai-infrastructure/ https://engineering.fb.com/2024/03/12/data-center-engineerin... [2] https://ai.meta.com/blog/next-generation-meta-training-inference-accelerator-AI-MTIA/ https://ai.meta.com/blog/next-generation-meta-training-infer...