AI's 'language model' bet looks fragile

EVERY INVESTOR KNOWS not to put all your eggs in one basket. So why is Silicon Valley betting on just one way to build artificial intelligence?

- Bloomberg

This year the world's four largest tech firms will spend $344 billion on AI, mostly on data centers used to train and run so-called large language models (LLMs) like ChatGPT that can process text, audio, and visual content. The technology is largely underpinned by the same technique of predicting tokens that appear next in a sequence.

Their spending isn't all in vain of course. Personal-use chatbots are already growing quickly, with some AI start-ups starting to break even and businesses still in the early stages of boosting themselves with generative AI. Large language models represent the first AI technique to achieve mainstream adoption at enormous scale: More than 700 million people use ChatGPT each week, for instance.

But history is full of people who got fixated on a single "winning" approach to tech, only to fall behind when the landscape suddenly shifted. Think of BlackBerry's devotion to the physical keyboard before Apple Inc. crushed it with touchscreens, or Yahoo's big bet on portals while Google quietly dominated search.