For more than a year, Meta has been engaged in a massive project to whip its AI infrastructure into shape.
They had a thorny problem: despite high-profile investments in AI research, the social media giant had been slow to adopt expensive AI-friendly hardware and software systems for its main business, hobbling its ability to keep pace with innovation at scale even as it increasingly relied on AI to support its growth, according to the memo, company statements and interviews with 12 people familiar with the changes, who spoke on condition of anonymity to discuss internal company matters.
Asked about the memo and the restructuring, Meta spokesperson Jon Carvill said the company"has a proven track record in creating and deploying state-of-the-art infrastructure at scale combined with deep expertise in AI research and engineering." 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. Executives also that spring set about reorganizing Meta's AI units, naming two new heads of engineering in the process, including Janardhan, the author of the September memo.
The facilities needed 24 to 32 times the networking capacity and new liquid cooling systems to manage the clusters' heat, requiring them to be"entirely redesigned," according to Janardhan's memo and four sources familiar with the project, details of which have not previously been disclosed.
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