SB Energy, the SoftBank Group–controlled developer of a massive planned Ohio data center project for OpenAI, is considering going public in December or possibly waiting until next year, according to people familiar with the discussions.

That is a later timeline than previously expected. The data center developer was aiming to go public as soon as September, The Information reported in August. But since then, the public market has soured on initial public offerings from data center and AI cloud companies. Australian cloud firm Firmus yanked its IPO plans earlier this month, and others are considering delaying their offerings.

Nvidia on Wednesday announced new deals with chip substrate suppliers Ibiden, Samsung Electro-Mechanics and Unimicron, to ensure it has enough component materials to produce more of its AI server chips in the coming years. It said the deals, which include a multibillion-dollar reservation ...

Nvidia on Wednesday announced new deals with chip substrate suppliers Ibiden, Samsung Electro-Mechanics and Unimicron, to ensure it has enough component materials to produce more of its AI server chips in the coming years. It said the deals, which include a multibillion-dollar reservation ...

Nvidia is in talks to invest hundreds of millions of dollars in Australian AI cloud provider Firmus, which abruptly pulled its initial public offering early this month, according to people familiar with the talks.

The discussion indicates that Nvidia is likely to continue backing a group of unproven firms known as neoclouds that is facing financial pressure after they stacked up on debt to purchase Nvidia graphics processing units for data centers. Nvidia has already put more than $170 billion on the line for such firms and other large customers, including credit guarantees to help them raise the debt, according to The Information’s analysis.

Nvidia has become something of a central bank for companies expanding the market for its chips beyond tech giants, backstopping customers and demand. But as Nvidia-backed cloud firms come under pressure, the question is how much further it will go.

The chipmaker has already disclosed as much as $164.5 billion in guarantees and other commitments to support new data centers, including agreements to pay landlords if tenants default on leases and promises to buy capacity, filings show, as of the company’s July quarter. That’s on top of more than $7 billion it has invested or agreed to invest directly in AI cloud providers.

How many young AI cloud providers can the market, and Nvidia, support?

That’s one of the big questions after a week in which investors worried about the data center buildout and the risks that its unproven participants, known as neoclouds, are taking. Those risks include loading up on debt (CoreWeave) or trying to go public without much of a track record (Firmus and Nscale). Firmus abruptly pulled its public offering last week while shares of CoreWeave and its smaller rivals fell around 20%. The concerns even hit bigger AI cloud providers like Oracle.

Data center and neocloud executives told me there’s a limit to the number of AI cloud providers that can exist, even if Nvidia provides many of them with investment or backstops.

Portland-based startup Mueon raised $65 million to develop a new way to arrange AI server rack components. The company says its design could fit up to ten times more computing capacity into the same amount of power as existing data center setups. This approach could ease constraints on global ...

Nvidia is tracking “every single gigawatt of land, power and shell around the world, literally everything on the planet,” CEO Jensen Huang said at Goldman Sachs’ annual tech conference earlier this month. “We know where everything is.”

Why track power so intently?

Nvidia sees power availability as a key barrier to getting its AI server chips online as soon as they ship, as we’ve chronicled in this column over and over. While securing power is the first step to any AI data center project, even before getting the land or chips, developers that work with Google, Microsoft, Oracle and others fear a glut of unused chips due to an eventual power shortage.

Apple has been working on plans for an enterprise server using its own chips that could incorporate networking equipment from Nvidia, people familiar with the project said, as the Mac maker looks to capitalize on surging interest in its computers for AI.

Apple has been developing the server with plans to sell it to AI developers, other businesses and governments, the people said. The product under consideration would come in two versions—a smaller one with two of Apple’s planned M8 Ultra chips clustered together and a bigger one with four M8 Ultra chips. The M-series Ultra chips are Apple’s highest-performance chips and power products including the Mac Studio.

The Department of Justice is looking into whether Nvidia tried to avoid antitrust scrutiny in its $20 billion deal to license the technology of chip startup Groq and hire most of its employees in December, the New York Times reported Wednesday.

The two companies described the deal as a “ ...

Gimlet Labs said late last week it had raised $300 million at a valuation of about $3 billion, in a round led by new investor Andreessen Horowitz. Today we have unreported details on how that round, which boosted its valuation by a whopping 16 times from its last PitchBook valuation, came together.

The three-year-old startup, which helps AI developers run models using different AI chips simultaneously, raised the round after the company’s executives told some potential investors that based on signed contracts, OpenAI was likely to spend more than $100 million a year on its services, according to a person familiar with the company. Such outlays, if they transpire, would be significant given it just emerged from stealth in October. 

This windfall would be in the future, however. “We have explored possibilities with Gimlet but we are not a paying customer,” said an OpenAI spokesperson.

Nvidia is doubling down on its open-source efforts, pouring investment into an ambitious new in-house AI model that it hopes will drive demand for its hardware—but that could also compete with customers and partners.

Nvidia is aiming for the new model, the biggest of a family that it is calling Nemotron 4, to be on par in its performance with the best open-source AI models in the world, according to several people who work on Nemotron. The research paper detailing Nvidia’s last big model had 570 authors, and employees said Nemotron 4 would involve even more people. “Everyone just wants to be involved at this point,” one former employee said.

A group of private equity giants has signed a preliminary agreement with Nvidia to raise $500 billion to help finance AI infrastructure, Nvidia said on Monday. The firms are Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. The partnerships haven’t yet been finalized, per an ...

Nvidia has agreed to invest $2 billion into Lancium, the power infrastructure developer behind the OpenAI and Oracle AI campus in Texas, and has agreed to commit another $1 billion as the developer secures additional planned power, The Information reported late Friday. The deal values Lancium ...

Nvidia has agreed to invest $2 billion into Lancium, the power infrastructure developer behind the OpenAI and Oracle AI campus in Texas, and has agreed to commit another $1 billion as the developer secures additional planned power, three people familiar with the transaction said. The deal values Lancium and its portfolio of land and power connections at around $10 billion in enterprise value, which includes the investment and its debt.

The $2 billion would give Nvidia a roughly 20% stake in the Blackstone-backed power developer. Nvidia’s stake could grow to around 30% with the additional $1 billion once more of Lancium’s campuses hit certain thresholds, including grid hookups, the people said. The deal is intended to help Nvidia secure multiple gigawatts of pending power rights for its chip customers’ data projects at a time when energy for AI data centers is becoming harder to come by.