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Training these models is not a "hardware" problem.

deleted 4mo ago
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nomel 4mo ago
I think that simplifies it a bit. You can't train without hardware, which is why the Chinese companies are illegally importing Nvidia cards [1]. [1] https://www.theinformation.com/articles/deepseek-using-banned-nvidia-chips-race-build-next-model https://www.theinformation.com/articles/deepseek-using-banne...
- adrian_b 4mo ago
  The usefulness of the smuggled NVIDIA GPUs has greatly diminished for AI purposes, because the elimination of NVIDIA as a competitor has allowed the growth of the production of domestic GPUs. Moreover, China has just demonstrated a supercomputer faster than any US supercomputer, which unlike the US supercomputers, which need GPUs, achieves its high computational throughput with custom CPUs designed in China (implementing an Armv9-A ISA with SME, i.e. the scalable matrix extension, and with BF16/INT8 operations for AI). The CPUs used in that supercomputer can reach both a computational throughput and a memory bandwidth sufficiently high for training any LLMs (they have fast HBM memory). Their only disadvantage in comparison with the best NVIDIA GPUs is a slightly lower energy efficiency, but China has abundant cheap energy so this is not a serious disadvantage for them.
  - menaerus 4mo ago
    SIMD programmers have to be paid very well then in the China ... Jokes aside, some 2 or 3 years ago I thought that it is becoming inevitable for CPU designs to become an extended versions of their already quite capable vectorized execution engine units.
  - deleted 3mo ago
    [deleted]
- trollbridge 4mo ago
  There is significant evidence they are transitioning to Huawei and other home-grown CPUs and NPUs.
  - 0xbadcafebee 4mo ago
    It was announced in April that Deepseek v4 ran at launch on Huawei Ascend chips. They then shared details of their implementation with other Chinese providers to strengthen the Chinese market against import restrictions (more people buying Huawei leads to more production, cheaper capacity)
  - nomel 3mo ago
    Yes, hardware is very important, which is why they're being forced to ramp up their local chips! ;)

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nomel 4mo ago

I think that simplifies it a bit. You can't train without hardware, which is why the Chinese companies are illegally importing Nvidia cards [1]. [1] https://www.theinformation.com/articles/deepseek-using-banned-nvidia-chips-race-build-next-model https://www.theinformation.com/articles/deepseek-using-banne...

adrian_b 4mo ago
The usefulness of the smuggled NVIDIA GPUs has greatly diminished for AI purposes, because the elimination of NVIDIA as a competitor has allowed the growth of the production of domestic GPUs. Moreover, China has just demonstrated a supercomputer faster than any US supercomputer, which unlike the US supercomputers, which need GPUs, achieves its high computational throughput with custom CPUs designed in China (implementing an Armv9-A ISA with SME, i.e. the scalable matrix extension, and with BF16/INT8 operations for AI). The CPUs used in that supercomputer can reach both a computational throughput and a memory bandwidth sufficiently high for training any LLMs (they have fast HBM memory). Their only disadvantage in comparison with the best NVIDIA GPUs is a slightly lower energy efficiency, but China has abundant cheap energy so this is not a serious disadvantage for them.
- menaerus 4mo ago
  SIMD programmers have to be paid very well then in the China ... Jokes aside, some 2 or 3 years ago I thought that it is becoming inevitable for CPU designs to become an extended versions of their already quite capable vectorized execution engine units.
- deleted 3mo ago
  [deleted]
trollbridge 4mo ago
There is significant evidence they are transitioning to Huawei and other home-grown CPUs and NPUs.
- 0xbadcafebee 4mo ago
  It was announced in April that Deepseek v4 ran at launch on Huawei Ascend chips. They then shared details of their implementation with other Chinese providers to strengthen the Chinese market against import restrictions (more people buying Huawei leads to more production, cheaper capacity)
- nomel 3mo ago
  Yes, hardware is very important, which is why they're being forced to ramp up their local chips! ;)