Using AMD for AI solutions is not seen as the primary choice with NVIDIAs market dominance but the availability and price of GPUs and equipment is a key reason. Ultimately, with some lead times for certain extremely popular NVIDIA equipment being longer than some users need, AMD is an option. 

• High performance: AMD GPUs offer excellent performance for AI workloads, thanks to their high core count and high clock speeds.

• Low power consumption: AMD GPUs are relatively power-efficient, which can save on costs.

• Open source support: AMD GPUs are well-supported by the open source community, which makes it easy to find drivers and software for them.

• Good value: AMD GPUs offer good value for the money, especially compared to NVIDIA GPUs.

Cons of AMD for AI

• Lack of tensor cores: AMD GPUs do not have tensor cores, which can be a disadvantage for some AI workloads.

• Limited software support: AMD GPUs are not supported by as many software packages as NVIDIA GPUs.

• Less mature platform: AMD's AI platform is less mature than NVIDIA's platform, which can lead to some challenges.

Overall, AMD GPUs are a good choice for AI workloads, especially for those who are looking for high performance and low power consumption. However, AMD GPUs do not have tensor cores and are not supported by as many software packages as NVIDIA GPUs.

As a premier AMD partner, we can assess your needs and which option is best for you.

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