Ben Bajarin, chief executive and principal analyst at tech consultancy Creative Strategies, estimated the deal, announced on Tuesday, would be worth billions of dollars.<\/p>\n
Meta<\/a> chief Mark Zuckerberg last month announced the Facebook and WhatsApp owner would nearly double its AI infrastructure spending to as much as $135bn this year.<\/p>\n Nvidia, which for the past three years has been the chief beneficiary of the massive global spending spree on AI infrastructure, is facing increasingly forceful moves by its customers to reduce their dependency on its hardware.<\/p>\n Google, Amazon and Microsoft have all announced new in-house chips in recent months, while OpenAI has co-developed a chip with Broadcom and struck a significant deal with AMD.<\/p>\n Meta has also invested in developing several AI chips in-house. Zuckerberg has outlined plans to achieve a lower cost of computing by deploying its own processors, which are optimised to the company\u2019s \u201cunique workloads\u201d. <\/p>\n However, the chip strategy had suffered some technical challenges and rollout delays, according to one person familiar with the matter. <\/p>\n Meta, already a big Nvidia customer, has now committed to buy Nvidia\u2019s next generation \u201cVera Rubin\u201d chips. <\/p>\n It is also the first Big Tech group to say it will buy standalone \u201ccentral processing units\u201d from Nvidia to run its AI models.<\/p>\n The decision by Nvidia chief Jensen Huang to offer its CPUs separately \u2014 rather than as part of a single integrated product including its graphics processing units \u2014 marks a major shift in its sales strategy.<\/p>\n GPUs are capable of the massive parallel processing required for training the biggest AI models. But tech groups are increasingly shifting towards \u201cinference\u201d workloads \u2014 the process of running AI models. <\/p>\n \u201cThe question of why Meta are deploying Nvidia\u2019s CPUs at scale is the most interesting thing in this announcement,\u201d said Bajarin. \u201cWe were in the \u2018training\u2019 era, and now we are moving more to the \u2018inference era\u2019, which demands a completely different approach.\u201d<\/p>\n A number of start-ups are, meanwhile, offering chips specialised for inference, marking a potential threat to Nvidia\u2019s position as the dominant AI chip provider. In December, Nvidia scooped up talent from inference chip company Groq, in a move to shore up its position in the market.<\/p>\n Nvidia\u2019s stock fell sharply late last year after The Information reported that Meta was in talks with Google to buy the search group\u2019s Tensor Processing Units, although no such deal has been announced.<\/p>\n Recommended<\/p>\n
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