Meta has reportedly signed a deal worth billions of dollars to rent AI chips from Google so that it can make AI models that are more advanced.
The move shows that AI development has become costly and time-consuming, making firms resort to spending a lot of money on computing power to make new AI systems.
Instead of taking years to develop all the hardware required for AI development, Meta is leveraging Google’s existing infrastructure to develop AI faster and stay ahead in the AI race.
The acquisition comes in parallel to the current trend in the tech industry with firms investing in chips and data infrastructure to cater to the increasing demand for AI products.
In essence, innovation and computing power are now equally important in the development of next-generation AI.
META ramps up AI push with multiple chip partnerships
Meta is ramping up its AI ambitions by teaming up with multiple chipmakers to secure the computing power needed for new artificial intelligence projects.
The company recently explored a potential $60 billion AI chip deal with AMD, alongside an earlier agreement with Nvidia for both current and next-generation processors.
Rather than depending on one supplier, Meta appears to be spreading its bets as demand for AI hardware continues to surge.
Meanwhile, Google is positioning its Tensor Processing Units (TPUs) as a strong alternative to Nvidia’s widely used GPUs, with TPU sales becoming a key growth area for its cloud business.
Reports suggest Meta is also in talks to use Google’s TPUs in its data centers next year, highlighting how tech giants are increasingly collaborating, even while competing, to build the infrastructure powering the AI boom.
AI chip industry surges as artificial intelligence moves from niche tech to everyday use
In the past five years, the AI chip market has grown at an unprecedented rate due to the increased adoption of artificial intelligence from a niche area to a mainstream technology used in day-to-day tools and businesses.
The rapid growth of generative AI, cloud computing, and sophisticated software has led to a massive demand for high-performance chips that are capable of handling large amounts of data at high speeds.
Tech companies have begun to spend a lot of money on making special chips that could handle AI-related tasks. At the same time, data centers began to grow in size to support these new infrastructure needs.
In parallel, governments have started backing local chip production, seeing AI hardware as strategically important. Today, AI chips are at the heart of the global tech race and one of the fastest-growing areas in the semiconductor industry.