The crushing demand for AI has also revealed the limits of the global supply chain for powerful chips used to develop and field AI models.
The continuing chip crunch has affected businesses large and small, including some of the AI industry’s leading platforms and may not meaningfully improve for at least a year or more, according to industry analysts.
The latest sign of a potentially extended shortage in AI chips came in Microsoft’s annual report recently. The report identifies, for the first time, the availability of graphics processing units (GPUs) as a possible risk factor for investors.
GPUs are a critical type of hardware that helps run the countless calculations involved in training and deploying artificial intelligence algorithms.
“We continue to identify and evaluate opportunities to expand our datacenter locations and increase our server capacity to meet the evolving needs of our customers, particularly given the growing demand for AI services,” Microsoft wrote. “Our datacenters depend on the availability of permitted and buildable land, predictable energy, networking supplies, and servers, including graphics processing units (‘GPUs’) and other components.”
Microsoft’s nod to GPUs highlights how access to computing power serves as a critical bottleneck for AI. The issue directly affects companies that are building AI tools and products, and indirectly affects businesses and end-users who hope to apply the technology for their own purposes.
OpenAI CEO Sam Altman, testifying before the US Senate in May, suggested that the company’s chatbot tool was struggling to keep up with the number of requests users were throwing at it.