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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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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