CoreWeave acquires Core Scientific for $9B to power AI infrastructure push

Nvidia-backed AI cloud provider CoreWeave is acquiring crypto miner Core Scientific for about $9 billion, giving it access to 1.3 gigawatts of contracted power to support growing demand for AI and high-performance computing (HPC) workloads.

The acquisition reflects a shift in data center strategy as AI infrastructure providers look to secure energy-intensive facilities originally built for purposes like cryptocurrency mining.

In a statement, CoreWeave said the deal will enhance its vertical integration by expanding its owned and operated data center footprint, allowing it to scale GPU-powered services for enterprise and research customers.

“Verticalizing the ownership of Core Scientific’s high-performance data center infrastructure enables CoreWeave to significantly enhance operating efficiency and de-risk our future expansion, solidifying our growth trajectory,” CoreWeave CEO Michael Intrator said in the statement.

AI infra race

Demand for AI infrastructure is expected to rise as more organizations advance their AI initiatives, with global spending projected to exceed $200 billion over the next five years, according to market research firm IDC.

“It is not easy to ramp up build and infrastructure quickly, and hence AI infrastructure companies will look for all possible avenues to ramp up,” said Sharath Srinivasamurthy, research vice president at IDC. “Since crypto mining infrastructure is primarily GPU-driven, it makes it easy to repurpose them to drive enterprise workloads. What is important is taking care of necessary security and governance guardrails and compliance with data and AI regulations.”

Such a shift, analysts say, could offer short-term benefits for enterprises, particularly in cost and access, but also introduces new operational risks.

“This acquisition may potentially lower enterprise pricing through lease cost elimination and annual savings, while improving GPU access via expanded power capacity, enabling faster deployment of Nvidia chipsets and systems,” said Charlie Dai, VP and principal analyst at Forrester. “However, service reliability risks persist during this crypto-to-AI retrofitting.”

This also indicates that struggling vendors such as Core Scientific and similar have a way to cash out, according to Yugal Joshi, partner at Everest Group.

“However, it does not materially impact the availability of Nvidia GPUs and similar for enterprises,” Joshi added. “Consolidation does impact the pricing power of vendors.”

Concerns for enterprises

Rising demand for AI-ready infrastructure can raise concerns among enterprises, particularly over access to power-rich data centers and future capacity constraints.

“The biggest concern that CIOs should have with this acquisition is that mature data center infrastructure with dedicated power is an acquisition target,” said Hyoun Park, CEO and chief analyst at Amalgam Insights. “This may turn out to create challenges for CIOs currently collocating data workloads or seeking to keep more of their data loads on private data centers rather than in the cloud.”

Others point out that the pivot from mining crypto coins to serving compute highlights a necessary but risky repurposing trend.

“Crypto facilities bring power and space, but not always enterprise assurance,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “While high-density cooling and electrical capacity make them attractive for AI workloads, their design DNA – batch processing, ASIC thermal loads, limited telemetry – doesn’t translate seamlessly into AI inference or real-time model operations.”

This means that CIOs will need to perform rigorous due diligence on airflow schematics, environmental zoning, and remote monitoring capabilities before committing production AI pipelines to these sites.

Source:: Network World