Google has limited Meta’s use of its Gemini AI models, citing high demand for computing capacity. According to a report by the Financial Times, Google informed Meta in March that it could not meet the full Gemini capacity the company had sought to purchase.

The restriction has impacted Meta’s internal AI projects, with the company encouraging staff to be more efficient with AI tokens. The move highlights the challenges companies face in securing enough computing power to support growing demand for AI services.

Computing Power Constraints

Google Cloud’s revenue grew to $20 billion in the first quarter, but CEO Sundar Pichai noted that computing power constraints prevented even higher growth. The company’s cloud unit’s backlog nearly doubled quarter on quarter.

The issue is not unique to Google and Meta, as companies continue to struggle to secure sufficient computing power to support AI services. The demand for AI has led to increased investment in chips and data centers, but the industry still faces challenges in meeting the growing need for computing capacity.

Original reporting: Appleton, WI News Feed (HLL/CB) — read the source article.