The writer is a professor emeritus at New York University and author of ‘Taming Silicon Valley: How We Can Ensure That AI Works for Us’
Between now and 2030, US hyperscalers like Meta, Microsoft, Alphabet and Amazon are expected to spend over $5tn on compute. It is a huge bet on technology — one that has already led some tech companies to reduce buybacks and issue new debt and stock. What is it that they hope to get for their money?
“Scaling compute” is AI industry terminology for spending more on data centres and the chips that go inside them — GPUs made by Nvidia, for example, TPUs in the case of Alphabet. These power the large language models used in generative systems such as chatbots like ChatGPT, Gemini and Claude. Compute is shorthand for how much computation a given system can do. More compute means adding more chips better able to compute at high speeds in parallel, allowing for the training and use (known as inference) of ever larger neural networks.