“No one deploys AI at Meta’s scale,” Nvidia CEO Jensen Huang said in a news release. Meta plans capital expenditure, mostly on data centers and the computing infrastructure they contain, of $115 billion-$135 billion this year — more than some hyperscalers, which rent their computing capacity to others. Meta is keeping it all for itself.
This could be bad news for other enterprises, as the demands of the hyperscalers and big customers like Meta is leading to a decrease in the availability of chips to train and run AI models.
IDC is predicting that the broader AI-driven chip shortage will have a significant effect on the IT market over the next two years as companies struggle to replace everything from laptops to servers. In particular, businesses looking for Nvidia processors may be forced to look elsewhere.
