Google is having the best and worst month of its AI life at once. Its cloud arm just grew 82% in a quarter, and the researchers who made the company an AI pioneer keep leaving. The two facts are connected, and the link is compute.
Some Google researchers cannot get the chips they need for ambitious projects, and they have grown frustrated, CNBC reported. Google Cloud, meanwhile, sells those same chips to outside customers, including Anthropic, whose models compete directly with Gemini. The chips, Google’s home-grown TPUs, are the scarce resource everyone is fighting over.
Selling the picks and shovels
You can watch the strategy in the open. This week Google Cloud announced that Mirendil, a frontier AI lab, will train its models on Google’s TPUs and Nvidia chips. Nearly every big AI lab now rents Google’s infrastructure. It is a lucrative business, and a far surer one than building the best model yourself.
That is the choice facing a $4 trillion company. Frontier models cost a fortune to train, with no guaranteed payoff. Selling the compute is highly profitable, and growing faster than Amazon’s or Microsoft’s clouds. So the question, four years into the AI boom, is blunt. Does Google need to build the best model, or is it better off letting rivals foot that bill?
