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Coreweave’s Q2: Takeaways on AI training, inference demand

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CoreWeave is building its AI infrastructure so it can easily switch back and forth from training to inference workloads as it works through strong demand and supply constraints.

The AI infrastructure provider reported a second quarter net loss of $290.51 million, or 60 cents a share, on $1.21 billion, up 207% from a year. Wall Street was looking for a loss of 49 cents a share on revenue of $1.08 billion.

The company exited the second quarter with a revenue backlog of $30.1 billion, double the backlog from a year ago. CoreWeave landed a $4 billion expansion deal with OpenAI in addition to a previously announced $11.9 billion contract.

CoreWeave raised its 2025 revenue guidance to $5.15 billion to $5.35 billion. “We ended the quarter with nearly 470 megawatts of active power, and we increase the total contracting power approximately 600 megawatts to 2.2 gigawatts. We are aggressively expanding our footprint on the back of intensifying demand signals from our customers,” said CoreWeave CEO Michael Intrator.

Here’s a look at the takeaways.

Overall demand. CoreWeave signed expansion contracts with both of its hyperscale customer in the past eight weeks. “Our pipeline remains robust, growing and increasingly diverse, driven by a full range of customers, from media and entertainment to healthcare to finance to industrials and everything in between,” said Intrator. “The proliferation of AI capabilities into new use cases and industries is driving increased demand for our specialized cloud infrastructure and services.”

Financial services demand. CoreWeave said it inked big bank deals with banking giants Morgan Stanley and Goldman Sachs for proprietary trading.

Healthcare scaling AI. “We’re also seeing significant growth from healthcare and life science verticals, and are proud of our partnership with customers like Hippocratic AI who built safe and secure AI agents to enable better healthcare outcomes,” said Intrator.

Training and inference. Intrator said CoreWeave is working with customers to easily transition between training and inference. “We’re helping these customers redefine how data is consumed and utilized globally as their critical innovation partner, and we are being rewarded for our efforts,” said Intrator. “As they shift additional spend to our platform, we continue to execute and invest aggressively in our platform, up and down the stack to deliver the bleeding edge AI cloud services, performance and reliability that our customers require to power their AI innovations.”

Intrator said:

“We really build our infrastructure to be fungible, to be able to be moved back and forth seamlessly between training and inference. Our intention is to build AI infrastructure, not training infrastructure, not inference infrastructure.”

Storage workloads. CoreWeave said it is gaining storage share for AI-centric workloads. “Customers are shipping petabytes of their core storage to core week in the form of multiyear contracts. We are providing support for additional third party storage systems,” said Intrator.

Bleeding edge expansion. Intrator said customers are focused on the latest hardware–Nvidia systems–to remain on the bleeding edge. “Clients are purchasing hardware that is appropriately state of the art for their use case. And as new hardware comes out, as new hardware architectures are released, they tend to come back in and purchase the same top tier infrastructure their next renewal,” said Intrator.

Power and supply constraints. Intrator said the AI infrastructure market is “structurally constrained.” “It is a market that is really working hard to try and balance and there are fundamental constraints at the power shell through the grid to the supply chains that exist within the GPUs to the mid voltage transformers,” said Intrator. “There are a lot of different pieces that are constrained, but ultimately the most significant challenge right now is accessing power shells.”



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AI Research

Databricks at a crossroads: Can its AI strategy prevail without Naveen Rao?

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“Databricks is in a tricky spot with Naveen Rao stepping back. He was not just a figurehead, but deeply involved in shaping their AI vision, particularly after MosaicML,” said Robert Kramer, principal analyst at Moor Insights & Strategy.

“Rao’s absence may slow the pace of new innovation slightly, at least until leadership stabilizes. Internal teams can keep projects on track, but vision-driven leaps, like identifying the ‘next MosaicML’, may be harder without someone like Rao at the helm,” Kramer added.

Rao became a part of Databricks in 2023 after the data lakehouse provider acquired MosaicML, a company Rao co-founded, for $1.3 billion. During his tenure, Rao was instrumental in leading research for many Databricks products, including Dolly, DBRX, and Agent Bricks.



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NFL player props, odds: Week 2, 2025 NFL picks, SportsLine Machine Learning Model AI predictions, SGP

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The Under went 12-4 in Week 1, indicating that not only were there fewer points scored than expected, but there were also fewer yards gained. Backing the Under with NFL prop bets was likely profitable for the opening slate of games, but will that maintain with Week 2 NFL props? Interestingly though, four of the five highest-scoring games last week were the primetime games, so if that holds, then the Overs for this week’s night games could be attractive with Week 2 NFL player props.

There’s a Monday Night Football doubleheader featuring star pass catchers like Nico Collins, Mike Evans and Brock Bowers. The games also feature promising rookies such as Ashton Jeanty, Omarion Hampton and Emeka Egbuka. Prop lines are usually all over the place early in the season as sportsbooks attempt to establish a player’s potential, and you could take advantage of this with the right NFL picks. If you are looking for NFL prop bets or NFL parlays for Week 2, SportsLine has you covered with the top Week 2 player props from its Machine Learning Model AI.

Built using cutting-edge artificial intelligence and machine learning techniques by SportsLine’s Data Science team, AI Predictions and AI Ratings are generated for each player prop. 

Now, with the Week 2 NFL schedule quickly approaching, SportsLine’s Machine Learning Model AI has identified the top NFL props from the biggest Week 2 games.

Week 2 NFL props for Sunday’s main slate

After analyzing the NFL props from Sunday’s main slate and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Lions receiver Amon-Ra St. Brown goes Over 63.5 receiving yards (-114) versus the Bears at 1 p.m. ET. Detroit will host this contest, which is notable as St. Brown has averaged 114 receiving yards over his last six home games. He had at least 70 receiving yards in both matchups versus the Bears a year ago.

Chicago allowed 12 receivers to go Over 63.5 receiving yards last season as the Bears’ pass defense is adept at keeping opponents out of the endzone but not as good at preventing yardage. Chicago allowed the highest yards per attempt and second-highest yards per completion in 2024. While St. Brown had just 45 yards in the opener, the last time he was held under 50 receiving yards, he then had 193 yards the following week. The SportsLine Machine Learning Model projects 82.5 yards for St. Brown in a 4.5-star pick. See more Week 2 NFL props here.

Week 2 NFL props for Vikings vs. Falcons on Sunday Night Football

After analyzing Falcons vs. Vikings props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Falcons running back Bijan Robinson goes Over 65.5 rushing yards (-114). Robinson ran for 92 yards and a touchdown in Week 14 of last season versus Minnesota, despite the Vikings having the league’s No. 2 run defense a year ago. The SportsLine Machine Learning Model projects Robinson to have 81.8 yards on average in a 4.5-star prop pick. See more NFL props for Vikings vs. Falcons here

You can make NFL prop bets on Robinson, Justin Jefferson and others with the Underdog Fantasy promo code CBSSPORTS2. Pick at Underdog Fantasy and get $50 in bonus funds after making a $5 wager:

Week 2 NFL props for Buccaneers vs. Texans on Monday Night Football

After analyzing Texans vs. Buccaneers props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Bucs quarterback Baker Mayfield goes Under 235.5 passing yards (-114). While Houston has questions regarding its offense, there’s little worry about the team’s pass defense. In 2024, Houston had the second-most interceptions, the fourth-most sacks and allowed the fourth-worst passer rating. Since the start of last year, and including the playoffs, the Texans have held opposing QBs under 235.5 yards in 13 of 20 games. The SportsLine Machine Learning Model forecasts Mayfield to finish with just 200.1 passing yards, making the Under a 4-star NFL prop. See more NFL props for Buccaneers vs. Texans here

You can also use the latest FanDuel promo code to get $300 in bonus bets instantly:

Week 2 NFL props for Chargers vs. Raiders on Monday Night Football

After analyzing Raiders vs. Chargers props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Chargers quarterback Justin Herbert goes Under 254.5 passing yards (-114). The Raiders’ defense was underrated in preventing big passing plays a year ago as it ranked third in the NFL in average depth of target allowed. It forced QBs to dink and dunk their way down the field, which doesn’t lead to big passing yardages, and L.A. generally prefers to not throw the ball anyway. Just four teams attempted fewer passes last season than the Chargers, and with L.A. running for 156.5 yards versus Vegas last season, Herbert shouldn’t be overly active on Monday night. He’s forecasted to have 221.1 passing yards in a 4.5-star NFL prop bet. See more NFL props for Chargers vs. Raiders here

How to make Week 2 NFL prop picks

SportsLine’s Machine Learning Model has identified another star who sails past his total and has dozens of NFL props rated 4 stars or better. You need to see the Machine Learning Model analysis before making any Week 2 NFL prop bets.

Which NFL prop picks should you target for Week 2, and which quarterback has multiple 5-star rated picks? Visit SportsLine to see the latest NFL player props from SportsLine’s Machine Learning Model that uses cutting-edge artificial intelligence to make its projections.





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In the News: Thomas Feeney on AI in Higher Education – Newsroom

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“I had an interesting experience over the summer teaching an AI ethics class. You know plagiarism would be an interesting question in an AI ethics class … They had permission to use AI for the first written assignment. And it was clear that many of them had just fed in the prompt, gotten back the paper and uploaded that. But rather than initiate a sort of disciplinary oppositional setting, I tried to show them, look, what you what you’ve produced is kind of generic … and this gave the students a chance to recognize that they weren’t there in their own work. This opened the floodgates,” Feeney said.

“I think the focus should be less on learning how to work with the interfaces we have right now and more on just graduate with a story about how you did something with AI that you couldn’t have done without it. And then, crucially, how you shared it with someone else,” he continued.



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