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Rick Perry’s Data Center REIT Fermi Targets $13 Billion Valuation in U.S. IPO

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Fermi, a real estate investment trust co-founded by former U.S. Energy Secretary Rick Perry, is seeking a valuation of up to $13.16 billion in its planned U.S. initial public offering, the company announced on Wednesday. The move comes as the surge in artificial intelligence drives demand for massive data center infrastructure.

The Amarillo, Texas-based firm aims to raise as much as $550 million by offering 25 million shares priced between $18 and $22 each.

Data centers have become prime assets as technology companies rush to build the computing power needed for advanced AI models. Fermi joins a growing list of AI-focused firms, such as CoreWeave and WhiteFiber, that have tapped public markets this year.

Founded in January 2025, Fermi has set its sights on developing the world’s largest energy and data complex, fueled by a combination of nuclear, natural gas, and solar power. Despite its ambitions, the company remains in an early development stage and has yet to generate revenue, reporting a $6.4 million loss since inception through June 30.

Fermi’s flagship initiative, known as Project Matador, plans to deliver up to 11 gigawatts of power for data centers by 2038, including one gigawatt ready by the end of 2026. The complex will span more than 5,200 acres in Texas and is expected to attract hyperscaler tenants.

“AI is arguably the investment story of a lifetime, but at this stage Fermi is still a story, and it’ll be interesting to see how much investors will pay for it,” said Matt Kennedy, senior strategist at Renaissance Capital. He described the valuation target as “very ambitious” for a development-stage company, highlighting the importance of securing contracts.

UBS, Evercore, Cantor and Mizuho are leading the IPO, with Fermi planning to list on both Nasdaq and the London Stock Exchange under the ticker “FRMI.” Proceeds from the offering will be used to purchase equipment and powered shells for the Texas complex.

OpenAI, Oracle and SoftBank to Build Five New AI Data Centers for $500 Billion Stargate Project

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OpenAI, Oracle and SoftBank announced plans to construct five new artificial intelligence data centers in the United States as part of their massive Stargate project, an initiative expected to reshape AI infrastructure.

President Donald Trump hosted leading tech CEOs in January to launch Stargate, a private-sector effort aiming to spend up to $500 billion on the compute power needed to support the next generation of AI.

OpenAI and Oracle will build three new facilities in Shackelford County, Texas, Doña Ana County, New Mexico, and an undisclosed Midwestern site. Together with SoftBank and its affiliate, OpenAI will also develop two additional centers in Lordstown, Ohio, and Milam County, Texas.

These new facilities, combined with Oracle-OpenAI’s Abilene, Texas expansion and ongoing projects with CoreWeave, will boost Stargate’s total data center capacity to nearly 7 gigawatts. According to OpenAI, this represents over $400 billion in investments over the next three years. The ultimate goal remains 10 gigawatts of total capacity.

“AI can only fulfill its promise if we build the compute to power it,” OpenAI CEO Sam Altman said in a statement.

The new projects are expected to create 25,000 on-site jobs. The announcement follows Nvidia’s pledge on Monday to invest up to $100 billion in OpenAI and supply data center chips.

To finance Stargate, OpenAI and its partners plan to use debt financing and lease chips, according to sources familiar with the matter.

With backing from Microsoft, OpenAI joins other tech giants pouring billions into AI infrastructure to support services such as ChatGPT and Copilot.

Given AI’s growing importance in sensitive fields like defense—and with China racing to catch up—both the private sector and the Trump administration have made AI infrastructure a strategic priority.

Micron tops forecasts with AI-fueled HBM demand, sees strong Q1 revenue

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Micron Technology projected first-quarter revenue of $12.5 billion ± $300 million, well above Wall Street’s estimate of $11.94 billion, as booming demand for its high-bandwidth memory (HBM) chips drives growth amid the AI race.

AI demand supercharges Micron

  • Q4 HBM revenue hit nearly $2 billion, putting Micron on pace for ~$8B annually, CEO Sanjay Mehrotra said.

  • HBM chips, built by stacking DRAM vertically, reduce power use while enabling massive data processing — making them indispensable for training and running advanced AI models.

  • Micron is a key HBM supplier to Nvidia, whose dominance in AI accelerators makes HBM supply one of the most competitive battlegrounds in semiconductors.

2026 outlook already sold out

  • Micron expects to lock in deals for all 2026 HBM capacity in the coming months.

  • HBM3E pricing agreements are nearly complete; HBM4 pricing talks are ongoing.

  • “The pricing on HBM4 is actually significantly higher than the pricing on HBM3E,” said Chief Business Officer Sumit Sadana, citing tight supply and strong ROI expectations.

  • TSMC will partner with Micron to manufacture the base logic die for its HBM4E chips.

Financial performance

  • Adjusted Q4 EPS: $3.03, topping forecasts.

  • Adjusted gross margin forecast (Q1): 51.5%, far above expectations of 45.9%.

  • Analysts said stronger-than-expected pricing drove the margin boost.

U.S. policy and subsidies

  • Micron has received $6.2B under the CHIPS and Science Act, passed under former President Joe Biden.

  • Current Commerce Secretary Howard Lutnick is exploring converting subsidies into equity stakes in chipmakers, but Sadana said Micron does not expect its grant terms to change.

  • Micron recently received a disbursement after completing a milestone at its Idaho fab, Mehrotra confirmed.

Big picture

Micron is riding the wave of AI-driven chip demand, securing long-term contracts at higher prices while boosting profitability. With HBM4 set to command premium pricing, Micron is positioning itself as a critical player alongside Nvidia, Samsung, and SK Hynix in the global AI supply chain.