Shulou(Shulou.com)11/24 Report--

According to foreign media citing sources familiar with the matter, Microsoft plans to launch its first chip designed to support artificial intelligence (AI) at next month's annual developer conference. The move is the result of years of efforts and could help Microsoft reduce its dependence on Nvidia AI chips. With the surge in demand, Nvidia's AI chips have been in short supply.

Microsoft's chip, similar to the Nvidia graphics processor (GPU), is designed for data center servers that train and run large language models, the software behind conversational artificial intelligence functions such as OpenAI's ChatGPT. Microsoft's data center servers currently use Nvidia's GPU to support cloud customers, including OpenAI and Intuit, as well as artificial intelligence features in Microsoft's productivity applications.

The chip, code-named Athena, is likely to be unveiled at Microsoft's Ignite conference in Seattle on November 14. Athena is expected to compete with Nvidia's flagship microprocessor H100 GPU to accelerate artificial intelligence in the data center. The custom chip has been secretly tested by a team of Microsoft and its partner OpenAI.

Microsoft began developing Athena chips around 2019, seeking to cut costs while also hoping to increase its bargaining chips with Nvidia. Azure currently relies on Nvidia's GPU to implement the AI functions used by Microsoft, OpenAI and cloud customers. But with Athena, Microsoft can follow in the footsteps of competitors AWS and Google to provide cloud users with self-developed artificial intelligence chips.

Details of Athena's performance are unclear, but Microsoft hopes the chip will rival Nvidia's H100. Although many companies are peddling excellent hardware and cost-effectiveness, Nvidia GPU is still the first choice for artificial intelligence developers, thanks to the company's CUDA platform. Attracting users to new hardware and software will be the key to Microsoft.

Microsoft's own development of AI chips may also reduce its dependence on Nvidia in the face of tight GPU supplies. It is reported that after starting to work closely with OpenAI, Microsoft ordered at least hundreds of thousands of Nvidia chips to support OpenAI products and research needs. By using your own chip, you can save a lot of money.

OpenAI may also be considering reducing its reliance on Microsoft and Nvidia chips. It has been reported recently that the artificial intelligence research laboratory is considering making its own artificial intelligence chip. Recent job postings on OpenAI's website also indicate that the company intends to recruit people to evaluate and co-design artificial intelligence hardware.

While Microsoft and other cloud service providers do not immediately stop buying GPU from Nvidia, persuading their cloud customers to use internal chips rather than Nvidia's GPU servers may be economically beneficial in the long run. Microsoft is also working closely with AMD on the upcoming artificial intelligence chip MI300X. With the surge in the workload of artificial intelligence, this diversified approach offers a variety of options. Competitors in cloud computing are using similar strategies to avoid vendor lock-ins.

Amazon and Google have strategically integrated their artificial intelligence chips into promotions in their cloud businesses. Amazon will provide financial support to OpenAI's rival Anthropic on the condition that Anthropic will use Amazon's artificial intelligence chips, named Trainium and interentia, respectively. Meanwhile, Google announced that customers such as artificial intelligence image developers Midjourney and Character AI are using the company's tensor processing units.

As artificial intelligence chips become an important part of the data center, betting on the rewards in this area is likely to be high. With this development, Microsoft will also join the ranks of competitors to compete for market share in the accelerated development of artificial intelligence chips. With Athena, Microsoft can provide more choices for cloud customers and develop a more independent path for the next generation of artificial intelligence infrastructure.

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