Google caps Meta's Gemini AI access as computing capacity crunch disrupts rival's projects

Google caps Meta's Gemini use as AI demand strains capacity

Google has put limits on Meta's use of its Gemini AI models after the social media giant sought more computing capacity than the rival tech group could provide, in the latest evidence of the infrastructure constraints facing even the world's largest AI providers. Google told Meta around March that it could not provide all of the Gemini capacity the company wanted to purchase, according to three people familiar with the matter, in a move that has disrupted and delayed some of Meta's internal AI projects. Owing to the restrictions, which remain in place, as well as a broader push to streamline AI costs, Meta has encouraged staff to be more efficient with AI tokens -- the units that measure AI usage, several people said. Several other Google clients have been affected by the restrictions, although to a lesser extent, according to one person familiar with the matter. Meta has been particularly impacted because of its exceptionally high demand for Google's models, the person said. The decision by Google to cap a large customer's access to its models offers a rare glimpse into the infrastructure pressures and bottlenecks building across the AI industry. Despite spending tens of billions of dollars on chips, data centres and power, even the largest tech companies are struggling to secure enough computing power to support surging demand for advanced models and AI services. As a direct result of the demands, particularly from big corporate customers such as Meta, Google has raced to secure additional capacity, according to one person familiar with the matter. Google earlier this month signed a $920mn-a-month deal to lease computing capacity from Elon Musk's SpaceX. Google and Meta declined to comment. At its first-quarter earnings in April, Google chief executive Sundar Pichai said that the company's cloud revenue exceeded $20bn for the first time, while its backlog of signed -- but not yet delivered -- cloud contracts nearly doubled quarter on quarter to more than $460bn. "Obviously, we are compute-constrained in the near term," Pichai said. "And as an example, our Cloud revenue would have been higher if we were able to meet the demand." Demand for AI computing has risen sharply as companies deploy chatbots, coding assistants and AI agents across their businesses. The resulting increase in inference workloads -- tasks required to run models after they have been trained -- has emerged as one of the industry's biggest challenges. AI lab Anthropic, the maker of the popular Claude chatbot, last month struck a deal with SpaceX that is similar to the deal it has with Google. The constraints illustrate the extent to which Meta has relied on rival models such as Gemini, as the social platform spends aggressively to become a leader in AI and improve its own models. Chief executive Mark Zuckerberg has been pouring billions of dollars into tapping talent and securing infrastructure in order to develop what he dubs "personal superintelligence". Unlike Google, Meta does not have a cloud business and is racing to build out its fleet of data centres for its own training and inference needs. As part of the push, Meta has committed to investing $600bn in the US by 2028. Gemini has been used internally at Meta as part of a push to automate some of its safety processes, such as rooting out scams and taking down harmful content, as well as for its customer services and advertising help chatbots. It is also used internally for some workflows and coding, alongside other models such as Anthropic's Claude. Meta initially chose to use Gemini because it performed better than the social media company's own Llama open-source models, according to people familiar with the matter. More recently, Meta has begun to shift to prioritise its new Muse Spark model, several people said, which is viewed as more competitive with Gemini and reduces the company's dependence on external models for some applications.

Google limits Meta's use of its Gemini AI models, FT reports

June 28 (Reuters) - Google has put limits on Meta's (META.O), opens new tab use of its Gemini AI models after the social media company sought more computing capacity than the rival tech group could provide, the Financial Times reported on Sunday. Google, owned by Alphabet (GOOGL.O), opens new tab, told Meta around March it could not meet the full Gemini capacity the company had sought to purchase, the newspaper said, ⁠adding that the shortfall disrupted and delayed some of Meta's internal AI projects. Several other Google clients have also been affected, though to a lesser extent, according to the report. Meta has been particularly impacted due to its exceptionally high demand for Google's models, the FT said. Reuters could not immediately verify the report, which cited people familiar with the matter. Google and Meta did not ⁠immediately respond to requests for comment outside business hours. Due to the restrictions, Meta has encouraged staff to be more efficient with AI tokens, the units that measure AI usage, the FT report said. Even as ⁠companies continue to spend billions on chips and data centres, they are still struggling to secure enough computing power to support the growing demand ⁠for AI services. Revenue at Google Cloud grew to $20 billion in the first quarter ended March, but CEO Sundar Pichai said computing ⁠power constraints prevented even higher growth and contributed to the cloud unit's backlog nearly doubling quarter on quarter. Reporting by Abu Sultan in Bengaluru; Editing by William Mallard and Sonali Paul Our Standards: The Thomson Reuters Trust Principles., opens new tab

Google Limits Meta's Gemini AI Access Amid Rising Compute Demand

Google has reportedly limited Meta's access to Gemini AI models due to compute constraints, highlighting growing pressure on AI infrastructure as tech giants compete for processing power to expand generative AI capabilities. Google has reportedly restricted Meta's access to its Gemini AI models after the social media giant requested more computing capacity than Google could provide. The move highlights the mounting infrastructure challenges even the world's biggest AI companies are facing as demand for generative AI continues to rise. According to a Financial Times report, Google informed Meta around March that it could not fulfill the company's full request for Gemini capacity, disrupting some of Meta's internal AI projects. Reuters has not independently verified the report.