The Financial Times reports that Google has placed limits on the use of Meta’s Gemini artificial intelligence model because Facebook’s parent company demanded more computing power than Meta can provide, underscoring the growing strain on AI infrastructure despite record investments by big tech companies.
The Financial Times reported, citing people familiar with the matter, that Google informed Meta around March that it would not be able to provide all of Gemini’s computing power that the social media company was looking to buy. The shortage halted and delayed some of Meta’s internal AI projects, according to the report.
As restrictions continue, Meta also asked employees to use AI tokens (the unit of measurement for AI usage) more efficiently as part of a broader effort to optimize computing resources and AI spending.
According to news reports, Meta has been affected more than other Google Cloud customers due to very high demand for its Gemini model. Other customers are also experiencing capacity constraints to a lesser extent.
Alphabet has long been aware of these constraints. Chief Executive Officer Sundar Pichai said in the company’s first-quarter results that despite strong customer demand, demand for AI services exceeds available computing power, limiting Google Cloud’s growth. Google Cloud generated $20 billion in revenue in the quarter, but its backlog skyrocketed due to a lack of capacity.
Despite investing heavily in its own AI capabilities, Meta is increasingly reliant on Google’s Gemini model for workloads such as software development, safety automation and customer service, according to the Financial Times. The company is also working to reduce its reliance on external providers by expanding its use of in-house AI models, the report said.
According to a McKinsey report, their research predicts that data centers will need $6.7 trillion worldwide by 2030 to keep up with the demand for computing power. Data centers equipped to handle AI processing loads are projected to require $5.2 trillion in capital investment, while data centers powering traditional IT applications are projected to require $1.5 trillion in capital investment.
