As the summer of 2022 came to a close, Meta CEO Mark Zuckerberg gathered his top lieutenants for a five-hour dissection of the company's computing capacity, focused on its ability to do cutting-edge artificial intelligence work, according to a company memo dated Sept 20 reviewed by Reuters. They had a thorny problem: despite high-profile investments in AI research, the social...
A security guard stands watch by the Meta sign outside the headquarters of Facebook parent company Meta Platforms Inc in Mountain View, California, US, on Nov 9, 2022.As the summer of 2022 came to a close, Meta CEO Mark Zuckerberg gathered his top lieutenants for a five-hour dissection of the company's computing capacity, focused on its ability to do cutting-edge artificial intelligence work, according to a company memo dated Sept 20 reviewed by Reuters.
For more than a year, Meta has been engaged in a massive project to whip its AI infrastructure into shape. While the company has publicly acknowledged "playing a little bit of catch-up" on AI hardware trends, details of the overhaul - including capacity crunches, leadership changes and a scrapped AI chip project - have not been reported previously.
Meanwhile, Microsoft-backed OpenAI's ChatGPT surged to become the fastest-growing consumer application in history after its Nov. 30 debut, triggering an arms race among tech giants to release products using so-called generative AI, which, beyond recognizing patterns in data like other AI, creates human-like written and visual content in response to prompts.
According to two of those sources, the company also started using its own custom chip it had designed in-house for inference, an AI process in which algorithms trained on huge amounts of data make judgments and generate responses to prompts. More than a dozen executives left Meta during the months-long upheaval, according to their LinkedIn profiles and a source familiar with the departures, a near-wholesale change of AI infrastructure leadership.Meta next started retooling its data centers to accommodate the incoming GPUs, which draw more power and produce more heat than CPUs, and which must be clustered closely together with specialized networking between them.
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