The rapidly increasing demand in the field of artificial intelligence (AI) has created new challenges for the world’s major technology companies. According to a recent report, Google could not fully provide Meta with the required computing capacity for its Gemini AI service, as a result of which several of Meta’s internal artificial intelligence projects were delayed.
The report quoted sources as saying that in March this year, Google informed Meta that it was not in a position to provide the full Gemini computing capacity requested by the company. This situation affected the pace of several of Meta’s AI projects and work on some projects temporarily slowed down.
According to sources, not only Meta but also other Google cloud users faced difficulties due to limited computing resources, but its impact on Meta was more noticeable because the company is using an unprecedented amount of computing resources to expand its AI products and services.
According to the report, after the limited availability of resources, Meta has instructed its engineers and related teams to adopt a more effective strategy in using artificial intelligence. The company has asked employees to use AI tokens carefully so that the available computing resources can be used as efficiently as possible. AI tokens are the basic units by which the processing and use of artificial intelligence models are measured.
Technology experts say that although Google, Meta, Microsoft and other global companies are investing billions of dollars in data centres and advanced chips, the rapidly increasing global demand for AI services continues to put pressure on computing infrastructure. That is why many companies are facing difficulties in obtaining resources according to their needs.
On the other hand, Google Cloud’s financial performance also reflects this growing demand. Google Cloud’s revenue reached $20 billion in the company’s first quarter, but Google CEO Sundar Pichai admitted that the company could not achieve better financial results due to the limited availability of computing power. According to him, for this reason, the number of pending projects of Google Cloud also increased significantly.
According to analysts, the current situation is proof that the global race for artificial intelligence is no longer limited to the production of advanced models, but access to powerful computing infrastructure, modern chips and data centres has also become a key factor for success. They say that in the coming years, technology companies will have to invest more heavily in their computing resources to meet the ever-growing demand for AI services; otherwise, such problems may arise in the future.