From Ideation to Implementation: How Microsoft Achieved its ChatGPT Goals

  • Microsoft Corp (NASDAQ: MSFT) pledged to build a massive, cutting-edge supercomputer for OpenAI in 2019 when it invested $1 billion.

  • Microsoft had to find ways to string together tens of thousands of Nvidia Corp's (NASDAQ: NVDA) A100 graphics chips, the workhorse for training AI models, and change how it positions servers on racks, Bloomberg reports.

  • OpenAI needed access to robust cloud computing services for long periods as it tried to train an increasingly large set of AI programs called models.

  • Microsoft executive vice president Scott Guthrie said it cost Microsoft over several hundred million dollars.

  • "We built a system architecture that could operate and be reliable at a very large scale. That's what resulted in ChatGPT being possible," said Nidhi Chappell, Microsoft general manager.

  • "That's one model that came out of it. There's going to be many, many others."

  • Microsoft uses the same resources it built for OpenAI to train and run its own large AI models, including the new Bing search bot.

  • Microsoft is already at work on the next generation of the AI supercomputer, part of an expanded deal with OpenAI in which Microsoft added $10 billion.

  • Training a massive AI model requires a large pool of connected graphics processing units in one place, like the AI supercomputer Microsoft assembled.

  • For the AI supercomputer, Microsoft had to develop software to get the best results from the GPUs and the networking equipment.

  • Microsoft also deploys graphics chips for inference which are geographically dispersed throughout the company's more than 60 regions of data centers.

  • The company is adding the latest Nvidia graphics chip for AI workloads, the H100, and the newest version of Nvidia's Infiniband networking technology to share data even faster.

  • Price Action: MSFT shares traded higher by 2.61% at $255.09 on the last check Monday.

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