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CoreWeave is rewriting how it pays for the AI boom, according to thecompany’s third-quarter earnings, reported on Tuesday. CoreWeave, a neocloud that rents out the computing power behind AI, said it’s increasingly asking customers to pay up front, borrowing against specific contracts, and even pursuing short-term deals that could lead to higher prices. The new strategies could help CoreWeave finance its growth more efficiently while squeezing more cash from existing infrastructure. But these bets only hold if today’s demand and pricing power continue. CoreWeave reported $3.66 billion in revenue, up 168% from the year prior, but it also posted a $709 million net loss and $846 million in quarterly interest expense. “We will not use the unsecured debt market to fund our business at current yields, nor do we need to,” CoreWeave CEO Michael Intrator said during Tuesday’s earnings call. Instead, CoreWeave’s plan is to rely on loans backed by specific customer contracts, drawing on funds as needed to finance most of infrastructure it still has to build to deliver on its significant backlog of $132.5 billion. CoreWeave also said it expects about $9 billion in customer prepayments and deposits over the next three months, including more than $3 billion tied to signing new customer contracts for capacity it has already built, which requires no additional spending on hardware. Rivals Nebius and IREN have also relied on hefty Microsoft prepayments to pay for computing capacity, signaling that the industry is moving toward asking Big Tech to pay up for their buildouts. Upfront payments could alleviate CoreWeave’s immediate borrowing needs, but they also commit the company to providing services at a price that might be less attractive down the road if compute demand continues to surge. CoreWeave is also looking to capitalize on that growing demand by signing more shorter-term contracts that can command much higher prices. The company raised prices across its offerings by about 25% in July and by another 10% later in the quarter. Prices are still climbing this quarter, in a way that “more than offset[s] cost increases,” said Intrator. “We are also allocating more capacity to short-term opportunities, where the pricing justifies it, selling capacity at more than $40 million per megawatt annually, while pricing for new infrastructure on four and five-year contracts is moving to $20 million to $25 million per megawatt,” the chief executive said. CoreWeave’s financing strategy now revolves around those opportunities. In August, the company closed a $2.6 billion loan, its first designed specifically for shorter-term customer contracts. Known as DDTL 5.5, it lets CoreWeave borrow in installments as it needs the money. While short-term deals let CoreWeave charge higher prices and change them more frequently, it’s a tradeoff. Lenders give more weight to longer-term contracts, even if they’re priced lower, because they value predictable cash flow and consistency to repay the loan above all. Even though Wall Street reacted positively to CoreWeave’s earnings, bond investors are much less sanguine. Last month, yields on some of thecompany’s bonds hit above 15%,highlighting that investors are concerned about the debt needed to fund data center buildouts before those investments see a return. In short, CoreWeave is finding new ways to expand without relying on unsecured debt. The strategy it has chosen could boost profits, but it also carries greater risk around contract renewals and pricing — and it just goes to show how dependent the AI infrastructure boom is on sustained, and as yet unproven, demand. TechCrunch has reached out to CoreWeave for more information about its loan facility.
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The data center boom is running into serious real-world obstacles, from widespreadlocal oppositionand permitting delays to ascramble for electricity. Before those challenges even come into play, though, there’s a more basic problem: A lot of the projects being announced may never get built in the first place. Withbillions of dollarsin AI infrastructure investment at stake, separating realistic projects from speculative ones is becoming increasingly important. On this episode of TechCrunch’sEquitypodcast, hosts Rebecca Bellan and Tim De Chant are joined byBrent Nelson, senior managing director of markets and strategy atAscend Analytics, to separate the data center projects that are likely to get built from the ones that may never get off the ground. Listen to the full episode to hear about: Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.
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A key figure in Meta’s growth into a social media and tech industry powerhouse is leaving the company. Santosh Janardhan, the company’s longtime head of infrastructure and co-head of engineering, will be stepping down, Meta told TechCrunch. He will be replaced by Dave Brown, who joined the company as vice president of infrastructure earlier this year, the company added. Previous to coming aboard at Meta, Brown spent 19 years at Amazon, where he focused on compute, cloud, and AI,his LinkedIn shows. It sounds like Janardhan will remain at Meta for a little bit, although he is expected to leave next year. “Santosh will stay on for transition and he is moving into an advisory role on Meta Compute,” said a Meta representative. Janardhan, who originally joined the company in 2009, helped the firm grow into the massive internet presence that it is today. Bloombergoriginally reportedJanardhan’s departure, citing an internal memo that had recently been circulated. It’s unclear why Janardhan is stepping down from the role. The memo did not specify the reasons for his departure and Meta didn’t immediately respond to a request for clarity on the issue. However, Janardhan’s memoapparently citedthe need to “pass the baton.” In recent years, the company’s investment in infrastructurehas exploded, as it seeks to keep up with its competitors in the AI race. Earlier this year, Janardhan was taskedwith leading Meta Compute, the company initiative to scale its data center investments and strategy.
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Loading the player… The data center boom is running into serious real-world obstacles, from widespreadlocal oppositionand permitting delays to ascramble for electricity. Before those challenges even come into play, though, there’s a more basic problem: A lot of the projects being announced may never get built in the first place. Withbillions of dollarsin AI infrastructure investment at stake, separating realistic projects from speculative ones is becoming increasingly important. On this episode of TechCrunch’sEquitypodcast, hosts Rebecca Bellan and Tim De Chant are joined byBrent Nelson, senior managing director of markets and strategy atAscend Analytics, to separate the data center projects that are likely to get built from the ones that may never get off the ground. Subscribe to Equity onYouTube,Apple Podcasts,Overcast,Spotifyand all the casts. You also can follow Equity onXandThreads, at @EquityPod.
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The Series A funding will support engineering and enterprise expansion as the startup launches PuppyGraph 1.0 graph query engine.
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IBM had historically used high-skilled visa programmes to address talent shortages, but its participation had been declining for several years.
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Anthropic is offering 825 million shares of Class A common stock at an indicative price range of $70–78 per share.
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AI agents today—the ones that can use your web browser and autonomously perform tasks—are getting more intuitive. But are they safe enough?
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The Japanese investment giant has written off billions of dollars after changing its plans for US data centre infrastructure, while also reporting losses linked to its OpenAI deal.
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The health AI company’s Parrotlet-A 2.5 Pro speech model and Lipi agentic harness convert doctor-patient consultations into structured digital health records.
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IBM and Microsoft have launched Imagine Enterprise, an agentic AI platform combining agents with enterprise cloud, data, and security technologies.
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The offering runs on PTC's Windchill platform and covers IP management, supplier collaboration, product introduction, quality, and regulatory compliance.
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