Add 1 billion dollars! OpenAI partners with SoftBank to bet on AI data centers!

In the core collaboration, OpenAI has selected SB Energy to build and operate a 1.2 gigawatt large-scale AI data center in Milam County, Texas, USA. This cooperation not only injects momentum into SB Energy's transformation and expansion, but also reflects the comprehensive upgrading of the "energy arms race" among global technology giants around AI computing infrastructure.

From the perspective of cooperation details, the core goal is to promote SB Energy's transformation into a professional AI data center developer and operator. Both parties have stated that $1 billion will support business expansion, but the valuation has not been disclosed. This cooperation is not simply a capital injection, but a deep strategic synergy - OpenAI outputs AI data center engineering technology, combined with SB Energy's infrastructure and energy development experience, to create a new data center model for efficient computing power expansion. Among them, the 1.2 gigawatt data center in Texas is crucial, as its power supply can meet the needs of about 750000 American households and will become the core computing power base for OpenAI's big model training and inference.

Behind the cooperation lies the rigid demand for computing infrastructure in the AI industry, with power supply being the core bottleneck. With the expansion of large model parameters and the increase in training and inference tasks, the power consumption of AI data centers is growing exponentially. According to data from the International Energy Agency, the typical power consumption of AI data centers is equivalent to 100000 households. By 2030, the global power consumption of data centers will reach 945 terawatt hours, slightly exceeding Japan's national electricity consumption. For giants like OpenAI, stable and sufficient power directly determines the speed and competitiveness of AI technology iteration. Therefore, OpenAI has chosen to collaborate with SB Energy, which has been deeply involved in energy infrastructure. SB Energy, which previously focused on renewable energy and energy storage, has expanded into the data center field in recent years. Multiple gigawatt level parks are under development, and the first batch of facilities have been constructed. Its energy integration capabilities are expected to overcome the power constraints of OpenAI's computing power expansion.

This layout is not an isolated case, but a microcosm of technology giants seizing the high ground of AI computing infrastructure. On the same day, Meta announced that it had reached multiple deals and is expected to receive over 6 gigawatts of nuclear power supply to meet data center demand. In fact, Microsoft, Google, Amazon, and others have also locked in power sources through long-term power purchase agreements and investments in small modular reactors. The vertical integration strategy of "computing power expansion+energy binding" has become a consensus in the industry. Technology companies no longer passively rely on traditional power systems, but actively control the energy lifeline. The "energy arms race" of AI core infrastructure has fully begun.

This investment will accelerate the scale and intensive development of AI data centers. On the one hand, SB Energy, with $1 billion in funding and OpenAI technology empowerment, is expected to quickly rise as a key player in global AI data centers, and its innovative model may become an industry model; On the other hand, the giant's investment in the energy sector will promote the deep integration of AI and the energy industry, forcing the upgrading of power infrastructure and giving rise to green computing solutions. But the potential risks cannot be ignored: if the demand for AI falls short of expectations, excessive investment in computing infrastructure may lead to overcapacity; The deep integration of the energy and computing power industry chain may also exacerbate industry concentration and squeeze the space for small and medium-sized AI enterprises.