Microsoft is Set to Make a Whole Lot More of Its Own AI Chips

Dow Jones08-11 03:50

Microsoft plans to greatly increase production of its artificial-intelligence chips, according to a report on Monday.

According to tech-focused news outlet the Information, which cited people familiar with the matter, Microsoft is expected to unveil its Maia 300 chip as early as next month. The company has reportedly held discussions with chip maker Taiwan Semiconductor Manufacturing to fill an order of more than 300,000 units of the chip for delivery in 2027.

Andrew Wall, general manager of Microsoft's Azure Maia division, said in a statement to Barron's that "Microsoft continues to invest in custom silicon as part of our long-term AI infrastructure strategy. While we don't share production volumes, the figures reported don't reflect the scale of our program." Wall added that Microsoft expects the "Azure Maia deployments to support AI workload demand measured in gigawatts."

Taiwan Semi didn't immediately respond to a request for comment.

Microsoft stock was up 1.1% on Monday while Taiwan Semi stock gained 0.5%.

Microsoft initially introduced its Maia chip in November 2023, and then launched the Maia 200 iteration in January of this year. It makes sense that the company would want to ramp up production, as chip supplies remain pressured and costs rise as demand for AI computing power soars.

Tech giants are spending hundreds of billions of dollars to build the infrastructure needed to power AI. Making their own chips and cutting costs is important in this hefty spending environment, especially as these companies rely heavily on one semiconductor maker, Nvidia, for their AI chip needs. Alphabet's Google Cloud unit has developed its Tensor Processing Units while Amazon.com's Amazon Web Services offers its Trainium accelerator.

"Microsoft's development of in-house chip design capabilities reflects a broader trend among hyperscalers toward vertical integration of the AI infrastructure stack in response to rising costs, power constraints, and supply limitations," Jim Hines, research director of computing systems platforms and technologies at IDC, said.

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