A new economic reality is starting to take hold in AI. It already underpins the industry’s giant data centres and it will one day become an iron rule for all companies that use machine-generated intelligence.
That, at least, is according to Jensen Huang, chief executive of Nvidia, who promoted the idea heavily at his company’s main annual tech event this week. His theory helps to make a case for Nvidia’s continued dominance in chips. But it also reveals how far the industry has to go to make a wider case for the technology.
Huang’s take on AI economics is based around the production, consumption and monetisation of tokens. These are the most basic units of output from large language models: it takes about 1,300 tokens to generate 1,000 words of text. The key metric, he argues, is the cost per token of output. And as the main input into AI-powered services, he adds, tokens translate directly into revenue.