Chips & Supply · United States

SpaceX in talks to borrow $40 billion to buy Nvidia chips

Credited to The Hindu BusinessLine · thehindubusinessline.com · 16h ago

Photograph · The Hindu BusinessLine

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Tech companies and AI model developers are investing and borrowing hundreds of billions of dollars to build and lease giant data centers full of chips to power AI systems

By Bloomberg

Elon Musk’s SpaceX is in talks with banks and investors to raise $40 billion of debt to buy chips from Nvidia Corp., people familiar with the matter said, underscoring the insatiable demand among AI developers for more computing power.

Pacific Investment Management Co. is one of the investment managers looking at the deal, said the people, who spoke on condition of anonymity as the talks are private. SpaceX’s fundraising discussions are in an early stage and could end without a deal being completed, they said.

Musk’s AI, satellite and rocket conglomerate is seeking to raise about $10 billion in bank loans and $30 billion in investment-grade debt to pay for the chips, the Financial Times reported earlier, citing unnamed sources familiar with the matter.

Apollo Global Management Inc. is leading the financing, in a deal that is expected to close in 2027, the newspaper said.

Tech companies and AI model developers are investing and borrowing hundreds of billions of dollars to build and lease giant data centers full of chips to power AI systems.

The worldwide expansion of computing capacity has sent the cost of everything from land to chips and power-generation equipment soaring, touching off a series of massive financing deals.

Nvidia, SpaceX and Apollo didn’t immediately respond to requests for comment. SpaceX shares erased gains in postmarket trading following the FT’s report, falling 1.2 per cent in US postmarket trading to $169.79. Nvidia’s stock rose fractionally.

Just last month, Musk said Colossus 2, an AI computing cluster built by his xAI business, may more than double its current Nvidia chip count by the end of the year. It was the most detailed timetable that the trillionaire has given yet for expansion plans for the Memphis-area cluster.

Colossus 2 now has 110,000 Nvidia GB200 chips and 440,000 GB300s, Musk said in a post on X. A further 220,000 GB300s are due to be operational next week, with another 220,000 expected in November, he said. An additional 220,000 may come online late December “if we get lucky,” he said.

Musk’s xAI has recruited multiple Wall Street firms to test its Grok chatbot, including Apollo and Morgan Stanley.

Apollo was among the US investment giants that Nvidia tapped for a high-profile partnership in August to source $500 billion in financing for AI infrastructure.

The coalition — which also includes Blackstone Inc., BlackRock Inc., Brookfield Asset Management, Goldman Sachs Group Inc. and KKR & Co. — said at the time that they’d “create dedicated pools of capital at significant scale at attractive rates for Nvidia customers.”

Executives indicated that it will focus on debt financing to provide access to compute for Nvidia’s largest customers and signaled that there were already many deals in the works that would qualify toward this commitment.

More stories like this are available on bloomberg.com

Chips & SupplyUnited States

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Chips & Supply · United States

Vinci targets faster chip design and simulation with physics-driven AI

Credited to SiliconANGLE · siliconangle.com · 15h ago

Photograph · SiliconANGLE

Simulation is a hardware engineer’s best friend, adept at finding issues in product designs and avoiding a disastrous deployment. Yet the process of orchestrating simulations has required specialized skills and lots of time. A Silicon Valley-based startup is working to change this picture.

Vinci4D Inc., which emerged from stealth in December, has built a software platform that enables engineers to run simulations a day after a design change rather than two weeks later. Issues can be detected much faster with the tool, shortening product development cycles. Vinci believes that its physics-driven AI software operates up to 1,000 times faster than conventional simulation tools, with higher accuracy.

“Can I ship my product faster while making it slightly better performing? We started from there,” said Hardik Kabaria (pictured), co-founder and chief executive officer of Vinci. “We took … the [physics] equations and trained an AI model ourselves. We packaged it in software with the harness that gets deployed. When you or our customers start using the product, it works out of the box accurately.”

Kabaria spoke with Christophe Bertrand at SEMICON West, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Vinci’s technology addresses the intersection of advanced manufacturing requirements, infrastructure reliability and long-term operational performance. (* Disclosure below.)

AI combines with physics-based simulation

Prior to founding Vinci, Kabaria pursued doctoral work at Stanford University that helped solve one of simulation’s thorniest problems: automating high-fidelity meshing for complex, real-world geometries. Vinci unites deep, physics-based simulation with production-grade artificial intelligence.

“AI moves at light speed, and our goal is to make the physics move at the same speed that the AI is moving so we can enable our customers, our partners to design the best hardware possible,” Kabaria told theCUBE. “The job for us is to ship physics software at the speed of light so that anybody who has a physics question, they get their answer at the inference speed.”

As semiconductor facilities become more technically demanding, chipmakers are becoming increasingly focused on the engineering expertise and infrastructure needed to support complex manufacturing environments. An example of this can be found in Vinci’s work with Advanced Micro Devices Inc.

“As you can imagine, they design some of the best hardware on which the AI is being inferred and trained, and our software also works on the best hardware AMD creates as the inference platform,” Kabaria said. “That means now somebody can use AMD’s MI355x to perform an inference of Vinci software to better understand their printed circuit boards, chip packages, all the way to the back end of the line in a 3D stacked integrated circuit. The loop for AI is not future; it’s happening.”

AMD is also an investor in Vinci through its venture arm. Earlier this month, Vinci closed a $250 million funding round at a $1.5 billion valuation. Advent, Temasek and Xora jointly led the Series B deal, which included several venture capital firms, along with AMD Ventures.

Asked what he expected for his company and the industry over the next year, Kabaria noted that advances in AI and simulation tools will depend on more than just one firm.

“It’s not just one team or one company’s job,” Kabaria said. “I still go back to hardware is an ecosystem. The whole set of us will come together to create a next level of pace at which the innovation will push out.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of SEMICON West:

(* Disclosure: TheCUBE is a paid media partner for the SEMICON West event. Neither Vinci, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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