This Company Won Big With Bitcoin and AI. Why It’s Now Favoring One Over the Other
3 min
Austin, Texas, company Core Scientific went from bankruptcy to stock market darling this year by betting on two technologies: Bitcoin mining and AI data centers. Shares are up 400%.
But if given the choice of whether to invest more in one business over the other, executives answer without hesitating: the data centers.
“We really just value long-term, stable cash flows and predictable returns,” Chief Operating Officer Matt Brown said in an interview. The company began life as a Bitcoin miner. Even though Bitcoin has been a great asset lately, it’s very volatile. By comparison, Core Scientific can earn steady profits for years by hosting servers owned by companies that sell cloud services to AI providers, Brown said.
This year, you couldn’t go wrong betting on either. Bitcoin is up 116%, and data centers are in high demand because tech companies need them to power their AI applications.
The two technologies seem to have little in common, but they both depend on the same thing: access to reliable power. Core Scientific has a lot of it, operating nine grid-connected warehouses in six states with access to so much electricity they could serve several hundred thousand homes. Other Bitcoin miners have similarly transitioned to data center hosting , but few with quite so much success.
Core Scientific’s business didn’t look quite so good at the start of the year. The company started 2024 under the shadow of bankruptcy protection. It had too much debt on its balance sheet after going public through the SPAC process in 2022 and succumbed to a Bitcoin price crash. But the company’s fortunes quickly turned around after it emerged from bankruptcy on Jan. 23 with $400 million less debt.
The company started the year focused entirely on crypto mining, but quickly pivoted as it saw demand surge for electricity for AI data centers.
In June, the company signed a deal with a company called Coreweave to lease data center space for AI cloud services. Coreweave has since agreed to lease 500 megawatts worth of space. Core Scientific says it will get paid $8.7 billion over 12 years under the deal.
Privately held Coreweave is one of the fastest-growing companies behind the AI revolution. It was once a cryptocurrency miner, but has since transitioned to offering cloud services, with a particular focus on artificial intelligence. It’s closely connected to Nvidia , which has invested money in Coreweave and given the company access to its top-end chips. Coreweave expects to be one of the first customers for Nvidia ’s upcoming Blackwell GPUs.
Core Scientific’s quick success in this new world has surprised even the people who are driving it.
“Every once in a while I need to pinch myself, to see I’m actually not dreaming,” Brown said.
Core Scientific’s success does create a high bar for the stock to keep rising. The company is expected to lose money this year, largely because of a change in the value of stock warrants—an accounting shift that doesn’t reflect underlying earnings. Analysts see the company becoming profitable in 2025, when more of its data center deals start to hit the bottom line. They see EPS jumping tenfold by 2027. Shares trade at about 13 times those 2027 estimates.
The data center opportunity should only grow from here, as tech companies build more powerful AI systems. Of the 1,200 megawatts worth of gross power capacity Core Scientific has contracted, about 800 megawatts are going to data center computing deals and 400 megawatts toward Bitcoin mining.
Brown said the company has good relationships with its power suppliers and can potentially add more capacity without having to buy more real estate. It expects to be able to secure about 300 more megawatts worth of power at existing sites, perhaps by the end of the year.
It’s also in the hunt for new sites, including at “distressed” conventional data centers that have lost their tenants. Core Scientific has figured out how to quickly spiff up bare-bones data centers and turn them into high-tech sites with resources like liquid cooling equipment and much higher levels of electricity.
A single server rack in a standard data center might need 6 or 7 kilowatts of power. A high-performance data center can use as much as 130 kilowatts per rack; Core Scientific is working on increasing capacity to 400 kilowatts. The company likens the process of upgrading the warehouses to turning a ho-hum passenger vehicle into a Formula One racing car.
Core Scientific’s transformation from a broken-down jalopy to a hot rod has been a wild story. Its fate next year will depend on just how quickly the AI revolution unfolds.
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Nvidia’s earnings will test Wall Street’s confidence in the AI boom.
3 min
Chip makers are fighting to assure investors that the artificial-intelligence boom is racing forward. Wall Street might not believe it until Nvidia’s NVDA -0.98%decrease; down pointing triangle Jensen Huang says so.
When Huang steps up to the mic for his company’s earnings call Wednesday, he will have the world’s attention. What he says about Nvidia’s present will preview the future of AI, dictate the path forward for a tech-crazed stock market and influence an American economy increasingly tethered to hopes that the boom won’t go bust.
The $5 trillion chip maker has provided the key building blocks for AI since the launch of ChatGPT in 2022 set off a race for dominance among OpenAI, Anthropic and established Silicon Valley giants. Now, as Nvidia backstops sprawling data-center projects and an exotic money pipeline to boost chip demand, the company’s influence is arguably bigger than ever.
But there are signs of trouble ahead. Political pushback to AI is growing. A bond selloff propelled borrowing costs to their highest levels in years. The hyperscalers that include some of Nvidia’s key customers—once cash-printing machines—are relying more on debt. OpenAI recently told investors its revenue rose by a tepid 18% in the second quarter while its losses deepened.
Nvidia is increasingly stepping in to shore up potential weak points across the market. Earlier this month, the company teamed up with six of Wall Street’s biggest firms on a $500 billion AI-financing plan, pledging to backstop lending to customers that can’t afford its chips otherwise. The chip maker last week also took a stake in Cloverleaf Infrastructure, which arranges power for data centers, and struck a $6 billion deal with startup Poolside aimed at developing a powerful open-weight AI model.
After watching shares in other chip makers and the so-called Magnificent Seven tech companies swing wildly in recent months, Wall Street is hoping Nvidia can beat expectations—again. The countdown is on.
“It’s kind of becoming more and more like the World Cup final than the Super Bowl at this point,” said Brian Mulberry, chief market strategist at Zacks Investment Management. “It’s just gotten to be that big.”
The company has smashed analysts’ earnings estimates for each of the 14 quarters since the AI boom kicked into high gear. Nvidia posted 210% annual growth in net income in its last three-month period, according to FactSet, making Wall Street’s 126% projection look pedestrian.
Expectations for a blowout second quarter have risen rapidly over the course of this year. All Nvidia will have to do to beat this target: outrun 95% annual earnings growth to more than $51.5 billion. Analysts project the chip maker will report record sales of $92 billion for the period, up from a forecast of $78 billion at the start of this year.
In July, big-tech earnings sparked volatility. Concerns about runaway capital spending spread across the sector after Alphabet’s and Tesla’s results, driving a $890 billion wipeout that contributed to the unwind of hedge fund Situational Awareness. Microsoft posted the largest one-day gain in market capitalization by any company, ever, after a quarter proving that it could still show investors the money. SpaceX rocketed higher after a record-breaking initial public offering, only to see $1 trillion in value evaporate.
Surging memory prices and borrowing costs have fueled fears that those and other companies will be unable to keep plowing more money into supplies including Nvidia chips. Shaia Hosseinzadeh, founder of OnyxPoint Global Management, has recently bought dips in AI-infrastructure stocks when Wall Street has strained to absorb massive debt issued by Silicon Valley.
“The macro data is really quite robust,” he said. “Of course, there’s a level at which everything breaks.”
Investors have kept pumping money into the AI trade despite concerns around chip consumers—and to the benefit of chip producers. That is why Nvidia’s outlook for semiconductor demand could send ripples through counterparts such as Micron Technology and Sandisk, developers of the data centers in which their chips reside, and a supply chain of power producers, contractors and other specialists that underpin the globe-spanning AI build-out.
“We joke internally that we’re all Nvidia analysts now,” said David Lefkowitz, head of U.S. equities at UBS Global Wealth Management.
The irony is that investors have tended to sell Nvidia stock immediately after blockbuster earnings, with shares falling each trading session after its four past quarterly reports. Some are betting that will be the case this time around, too.
The options market is pricing in a 5.3% swing, higher or lower, in Nvidia shares during the session following earnings, according to Option Research & Technology Services. That is higher than the 4.8% average move in Nvidia’s stock over the last 12 months after the company reports quarterly results.
In recent days, some of the most actively traded Nvidia options have been put contracts tied to the stock falling from its Friday value of $214.75 to $205 and $210 apiece, according to Cboe Global Markets data. Put options give the right to sell a stock by a set price and typically represent a bearish wager.
Many analysts remain optimistic. Frank Lee, global head of tech hardware and semiconductor research at HSBC Global Investment Research, recently raised his price target for Nvidia shares to $360 from $325, citing, among other things, Nvidia’s strategic partnerships with suppliers and its role as a top contributor to open-source AI.
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