Jakarta, INTI - Google has reportedly restricted Meta Platforms Inc.'s access to its Gemini artificial intelligence (AI) model due to Google’s limited computing capacity. According to a Financial Times report, the limited capacity caused Google to implement restrictions on some of its clients, with Meta as one of the most impacted.
This restriction affects several of Meta's internal projects, prompting the company to urge its employees to use its AI tokens more sparingly and efficiently. Meta previously utilized Gemini to support various security processes, such as removing malicious content and preventing fraud, as the model was deemed to perform better than its own open-source model, Llama.
However, as it seeks to reduce its reliance on third-party technology, Meta has now begun increasing its use of its newest internal AI model, Muse Spark. This reflects the growing pressure on global AI infrastructure amid soaring computing and energy requirements to support data center growth.
Big Companies' Efforts in Meeting Capacity Demand
In early June, Google agreed to pay Elon Musk's SpaceX USD 920 million per month for computing power as part of a USD 30 billion cloud services deal that runs through mid-2029, as it seeks to meet the huge demand for capacity.
Meanwhile, Meta continues to expand its investment in AI, a key focus for CEO Mark Zuckerberg. To support this strategy, the company announced plans to reduce approximately 10% of its workforce, or approximately 8,000 positions, earlier this year. Additionally, Meta is moving approximately 7,000 employees into new roles related to AI development as part of a comprehensive corporate restructuring.
Conclusion
Google has reportedly restricted Meta Platforms Inc.'s use of its Gemini AI model due to limited computing capacity. This restriction impacts several of Meta's internal projects, prompting the company to urge employees to use its AI token more efficiently. Meta previously used Gemini because it was considered to perform better than its open-source model, Llama, but the company is now shifting to a new internal model, Muse Spark, to reduce its reliance on external technology. This reflects the growing pressure on global AI infrastructure.
Read more: Samsung Plans an Investment of Rp11.600 Trillion in South Korea to Boost AI Development