AI frontier slowdown could give second tier leg up

That should insulate so-called hyperscalers like Amazon, Alphabet and Meta, which make up the bulk of capital spending to some degree. Yet current AI winners like $5.3 trillion Nvidia, whose graphics processing units are vital for training models, and South Korea's SK Hynix, which supplies high-bandwidth memory for such chips, look worse off.

Intel, for example, which specialises in another type of semiconductor called central processing units, may be a major beneficiary. Data centres catered to training advanced models generally require 1 CPU for every 8 GPUs; boss Lip Bu Tan has flagged that for iterative tasks carried out by agents, the ratio is one to one. Nvidia challengers that focus on inference, like Cerebras Systems, also stand to gain, as well as Samsung Electronics, whose conventional memory products are more suited for CPUs.

With less emphasis on frontier AI capabilities, model developers can also better compete on efficiency and costs. That will reshape competition and business models. So investors need not panic about a sudden market downturn. Whether that's enough to save the world from an impending machine-driven apocalypse is another matter.