Windows manufacturer Microsoft and AI research firm OpenAI are reportedly teaming up for a groundbreaking project that could see the development of a cutting-edge data center known as Stargate. This ambitious undertaking is estimated to cost a whopping $100 billion, making it one of the largest data centers in existence.
According to sources familiar with the matter, Microsoft is expected to spearhead the financing of this project, which is slated for a grand debut in 2028. The data center is anticipated to house an AI supercomputer, which will mark a significant milestone in the evolution of AI technologies.
The substantial investment required for this endeavor stems from the rising demand for data centers capable of handling advanced processing tasks. The companies behind the project are currently in the third phase of planning, with the fourth phase supercomputer set to materialize in 2026.
With the speculated cost of the project potentially exceeding $100 billion, OpenAI CEO Sam Altman and Microsoft’s estimates suggest that Stargate will be a key component of the final phase. This hefty price tag is largely attributed to the acquisition of powerful AI chips, which have become increasingly expensive in recent times.
For instance, the latest ‘Blackwell’ B200 AI chip from Nvidia falls within the $30,000 to $40,000 price range as noted by Nvidia CEO Jensen Huang. Microsoft’s move to introduce custom computing chips further underscores the company’s commitment to advancing AI capabilities.
A Microsoft spokesperson highlighted the company’s ongoing efforts to drive innovation in infrastructure needed for AI advancements. Despite refraining from specific details on Stargate, the spokesperson emphasized Microsoft’s dedication to pushing the boundaries of AI technology.
The total expenses for this ambitious project could soar above $115 billion, surpassing Microsoft’s capital spending on servers, buildings, and equipment in 2023. As the collaboration between Microsoft and OpenAI progresses, the development of Stargate could pave the way for groundbreaking advancements in AI computing capabilities.
