Google reportedly capped Meta's use of Gemini AI for coding and chatbots

Google capped Meta's use of its Gemini AI model after Meta exceeded its computing capacity, according to sources. The incident highlights that even major tech companies face computing power shortages despite massive data center investments. Meta uses Gemini for customer service, chatbots, and coding, and was forced to request more efficient token usage from employees.

Google reportedly capped Meta's use of Gemini AI for coding and chatbots Even tech giants with their own LLMs are having trouble finding enough computing power. Google was forced to cap Meta's use of its Gemini AI https://www.engadget.com/2176568/google-redesigned-gemini-comes-with-a-new-interface-and-ai-models/ model after Mark Zuckerberg's company exceeded its computing capacity, sources familiar with the matter told The Financial Times . The incident reveals that even tech giants with their own LLMs are having trouble finding enough computing power for themselves, let alone their customers. Meta does not operate its own cloud business and is trying to rapidly expand its own data center build out, having pledged $600 billion https://www.engadget.com/ai/meta-says-it-will-invest-600-billion-in-the-us-with-ai-data-centers-front-and-center-195000377.html in cloud computing investments over the next two years. Google reportedly warned the social media company about its capacity limits in March, in turn forcing Meta to request that employees use tokens more efficiently, the sources said. Gemini AI is being used by Meta for customer service, advertiser chatbots and coding, alongside processes like harmful content takedowns and scam detection. Meta initially chose Gemini for those things because it outperformed its own Llama open-source models, the sources said. The company also employs other models like Anthropic's Claude for similar purposes. Despite the billions spent so far on data centers, big companies are struggling to get enough capacity for their usage needs. Google itself recently agreed to pay SpaceX $920 million a month https://www.engadget.com/2188862/google-spacex-xai-data-center-deal-gemini/ to use xAI's data centers, due to the extra computing power required for Gemini Enterprise. AI power users are benefiting from the boom, but providers like OpenAI aren't profiting https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb828?syn-25a6b1a6=1 yet, since revenue earned from AI so far is a small percentage of the costs, according to analysts https://www.americanbanker.com/news/the-cost-of-ais-compute-is-coming-into-focus-and-its-a-lot . Recently, token prices have surged, forcing some companies to back off https://www.itpro.com/technology/artificial-intelligence/what-were-seeing-right-now-is-just-rapid-escalation-in-ai-token-spend-accenture-tells-staff-to-stop-using-ai-for-unnecessary-tasks-amid-surging-costs on AI usage — including, it appears, the AI companies themselves.