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The biggest beneficiary of the AI surge, the new stock market legend Leopold's rise to wealth
Leopold Aschenbrenner’s holdings have surged again and again. As a rising star in hedge funds, his investment logic is being validated in reverse by the market.
In the past few days, multiple stocks in Leopold’s Situational Awareness LP publicly disclosed holdings have collectively risen: Bloom Energy, Cipher Mining, Intel, Applied Digital, SanDisk, IREN, among others, with single-day gains exceeding 10%. This prompted the market to revisit his late-2022 13F report, trying to understand why this former OpenAI researcher had early bets on AI infrastructure.
What makes him noteworthy isn’t the “young” or “overnight wealth” labels, but that he offers a framework different from mainstream AI trading. Most people equate AI investments with Nvidia, Microsoft, OpenAI, and model capabilities, but Leopold’s portfolio bypasses the most crowded star assets, turning instead to Bloom Energy, CoreWeave, Core Scientific, Lumentum, Intel, Bitcoin miners, and power-related companies.
The AI narrative is shifting from “whose model is stronger” to “who can support the model’s continued expansion.” Training and inference require GPUs, GPUs need data centers, data centers need electricity, land, cooling, fiber optics, licenses, and long-term power contracts. Leopold is betting on the physical bottlenecks that AI growth must pass through. Fortune also summarized his latest holdings as: this ex-OpenAI researcher is translating his AGI paper into billion-dollar bets on power, AI infrastructure, and crypto mining companies.
In early March, Dongcha Beating conducted an in-depth analysis of Leopold and his fund’s holdings and investment logic, sharing his vision of the future of AI competition. All of this is being validated in reality: the AI narrative is returning from models on screens to land and power grids under our feet. The most expensive things in the future may not be algorithms, but the physical world supporting their expansion.
Below is the original content from Dongcha Beating:
In February 2026, hedge fund Situational Awareness LP submitted its quarterly holdings report, showing that as of the end of Q4 2025, the fund’s US stock holdings had a total market value of $5.52B.
Wall Street manages trillions of dollars; $5.5B is just a drop in the ocean. But this fund’s assets under management were less than $400 million just 12 months ago, and its founder and chief investment officer is a young person born in 1999.
His name is Leopold Aschenbrenner. 27 years old.
In 12 months, he grew this fund from $380 million to $5.52B, an increase of over 14 times. During the same period, the S&P 500 rose by a single-digit percentage.
Even more surprising are his holdings. Open the quarterly report, and you won’t find any of the AI star companies often seen in financial headlines. Instead, there are companies making fuel cells, recently revived Bitcoin miners on the brink of bankruptcy, and chip giants being abandoned by the market.
He claims his fund invests in AI, but this doesn’t look like an AI fund’s holdings—more like a madman’s shopping list.
But this madman is one of the earliest and most profound people to understand how AI will change the world. Before Wall Street, he was a researcher at OpenAI, thinking about how to ensure AI doesn’t go out of control when it becomes smarter than humans; later, he was expelled for speaking out of turn, writing a 165-page manifesto predicting a future that most would find absurd.
Later, he bet his entire fortune on it.
Dissecting $5.5 billion: what exactly did he buy?
The most direct way to understand Leopold Aschenbrenner’s investment genius is to open his holdings report and read it line by line.
His largest holding is Bloom Energy, with a market value of $876 million, accounting for 15.87% of the total portfolio.
This company makes fuel cells. More precisely, it produces “solid oxide fuel cells” that can directly convert natural gas into electricity with high efficiency. Founder KR Sridhar was once an engineer on NASA’s Mars exploration program, named one of “Five Top Futurists Creating the Future” by Fortune magazine.
An AI fund has placed its biggest bet on an energy company.
According to Gartner’s forecast, the global power consumption of AI-optimized servers will soar from 93 TWh in 2025 to 432 TWh in 2030, nearly fivefold in five years. The US data center power demand will nearly triple by 2030, reaching 134.4 GW. Meanwhile, the average age of US power infrastructure exceeds 25 years, with many components between 40 and 70 years old—far beyond their designed lifespan.
In other words, the electricity AI needs exceeds what the entire grid can supply. Yet, the grid itself is aging rapidly.
The most scarce resource in the AI era isn’t chips—it’s electricity.
Bloom Energy’s fuel cells can bypass this bottleneck. They don’t need to connect to the grid, generating power directly next to data centers, 24/7. In 2025, Bloom Energy secured a contract from CoreWeave to supply fuel cells for its AI data center in Illinois.
Speaking of CoreWeave, this is Leopold’s second-largest holding.
He holds $774 million in call options on CoreWeave, plus $437 million in common stock, totaling over $1.2 billion, or 22% of the portfolio. CoreWeave is a GPU cloud service provider, transformed from a crypto mining farm.
In 2017, Mike Intrator and Brian Venturo and a few others mined Bitcoin together. In 2018, after the crypto crash, mining became unprofitable. But they had a bunch of GPUs. In 2019, they had an epiphany: GPUs can do more than mine—they can run AI.
So the company shifted from mining farms to AI compute hardware. On March 27, 2025, CoreWeave IPO’d on Nasdaq, raising $1.5 billion at $40 per share. A company that emerged from mining has become a core supplier of AI infrastructure.
Leopold is betting on CoreWeave’s large GPU inventory and its deep ties with Nvidia. In an era where compute power equals productivity, whoever owns GPUs is king.
But what truly confuses people is his third-largest holding: Intel. With a market value of $747 million, all in call options, accounting for 13.54% of the portfolio.
In 2025, Intel was one of Wall Street’s most unloved companies. Its stock price halved from its 2024 high, market share was eaten by AMD and Nvidia, and CEOs changed repeatedly. Almost all analysts declared Intel finished.
But Leopold bought call options on Intel at this moment—an extremely aggressive move, betting on a turnaround, or zero if wrong.
What is he betting on? Just two words: foundry.
In November 2024, the US Department of Commerce announced that Intel would receive up to $7.86 billion in direct funding through the Chips and Science Act. The goal was clear: make Intel a domestic chip foundry to compete with TSMC.
In the context of US-China tech decoupling, the US needs a “homegrown” chip maker. Though behind, Intel is the only choice. Leopold isn’t betting on Intel’s technology but on US national will.
The subsequent holdings are even more interesting. Core Scientific, $419 million; IREN, $329 million; Cipher Mining, $155 million; Riot Platforms, $78 million; Hut 8, $8B.
All these companies share a common trait: they are Bitcoin miners.
Why would an AI fund invest in a bunch of Bitcoin miners?
Simple: because Bitcoin miners own the cheapest electricity and largest data center sites in the US.
Core Scientific has over 1,300 MW capacity. IREN plans to expand by 1.6 GW in Oklahoma. These miners have locked in the cheapest power globally through long-term power purchase agreements to survive fierce compute competition.
And now, what AI data centers most lack is precisely electricity and space.
In 2022, Core Scientific filed for bankruptcy due to the crypto crash. It restructured in January 2024, reducing about $1 billion in debt, and relisted on Nasdaq. Then, it signed a 12-year, over $10.2 billion contract with CoreWeave to convert its mining farms into AI data centers. To fully pivot, Core Scientific even plans to sell all its Bitcoin holdings.
IREN (formerly Iris Energy) signed a $9.7 billion AI contract with Microsoft, receiving $1.9 billion in advance. Cipher Mining signed a 15-year lease with Amazon. Riot Platforms signed a 10-year, $311 million contract with AMD.
Overnight, Bitcoin miners have become landlords in the AI era.
Now, let’s complete this puzzle.
Bloom Energy provides power, CoreWeave supplies GPU compute, Bitcoin miners offer space and cheap electricity, Intel provides domestic chip manufacturing. Plus, the fourth-largest holding, Lumentum ($479 million, making optical components, key for interconnecting AI data centers), the ninth-largest SanDisk ($250 million, data storage), and the eleventh-largest EQT ($133 million, natural gas producer fueling fuel cells).
This is a complete AI infrastructure supply chain.
From power generation, transmission, chip manufacturing, GPU compute, data storage, to fiber optic interconnection—Leopold has bought into every link.
And he’s doing another thing that makes this logic clearer: in Q4 2025, he completely sold off Nvidia, Broadcom, and Vistra. These three were among the biggest winners in the 2024 AI rally.
He also shorted Infosys, one of India’s largest IT outsourcing firms.
Selling the hottest AI chip stocks, buying unloved power plants and mines. Shorting traditional IT outsourcing because AI programming tools are making programmers more efficient, reducing outsourcing demand.
Every trade points to the same conclusion: the bottleneck of AI isn’t software, but hardware; not algorithms, but electricity; not cloud models, but the physical world.
So, how did a 27-year-old form this understanding?
From East German doctor’s son to OpenAI rebel
Leopold Aschenbrenner was born in Germany, to parents who were doctors. His mother grew up in East Germany, his father from West Germany; they met after the Berlin Wall fell. This family bears the mark of a historical rupture—Cold War, division, reunion. His obsession with geopolitical competition may have its roots here.
But Germany couldn’t keep him. He later said in an interview: “I really wanted to leave Germany. If you’re the most curious kid in class, wanting to learn more, teachers won’t encourage you—they’ll be jealous and try to suppress you.”
He called this phenomenon “the high poppy syndrome,” where the taller you grow, the more likely you are to be cut down.
At 15, he convinced his parents to let him fly alone to the US, to Columbia University.
Studying at 15 is unusual anywhere. But Leopold’s performance at Columbia turned “outsider” into “legend.” He majored in economics and math-statistics, winning awards like the Albert Asher Green Memorial Prize, Romine Economics Prize, and becoming a Junior Phi Beta Kappa member.
At 17, he wrote a paper on economic growth and existential risks. Renowned economist Tyler Cowen read it and said: “When I read it, I couldn’t believe it was written by a 17-year-old. If it were a PhD thesis from MIT, I would be equally impressed.”
At 19, he graduated as valedictorian from Columbia—highest honor for undergraduates. In 2021, amid the pandemic, this 19-year-old German stood at Columbia’s graduation, delivering the speech on behalf of all graduates.
Tyler Cowen gave him a piece of advice: don’t pursue a PhD in economics.
Cowen felt academia had become somewhat “decadent,” encouraging him to do bigger things. He also introduced him to Silicon Valley’s “Twitter oddball” culture—people obsessed with AI, effective altruism, and humanity’s long-term fate.
After graduation, Leopold first joined the Forethought Foundation, researching long-term economic growth and existential risks. Then he joined SBF’s FTX Future Fund, working alongside key figures in effective altruism like Nick Beckstead and William MacAskill. His title was “Economist affiliated with the Oxford University Global Priorities Institute.”
This experience was crucial. It meant that before entering AI, Aschenbrenner had spent years systematically pondering a fundamental question: what events could fundamentally change human civilization’s trajectory.
Then, he joined OpenAI.
The exact timing is unclear, but he was part of a special team—“Superalignment.” Founded on July 5, 2023, led by OpenAI co-founder Ilya Sutskever and team lead Jan Leike, its goal was to solve the alignment problem for superintelligence within four years—to ensure that an AI far smarter than humans would still obey human commands.
OpenAI had promised to allocate 20% of its compute power to this team. But there was a gap between promise and reality.
Leopold saw unsettling things inside OpenAI. He submitted a security memo warning that the company’s safety measures were “severely inadequate” to prevent foreign governments from stealing key algorithm secrets. The response surprised him: HR called him, saying his concerns about espionage were “racist” and “unconstructive.” Company lawyers questioned his views on AGI and his team’s loyalty.
In April 2024, OpenAI fired him for “leaking confidential information.”
The so-called “leak” was sharing a brainstorming document on AGI safety with three external researchers. Leopold said the document contained no sensitive info; sharing such internal drafts for feedback was normal.
A month later, Ilya Sutskever left OpenAI. Three days after, Jan Leike also departed. The Superalignment team was disbanded, and the promised 20% compute was never delivered.
A team researching “how to control superintelligence” was dismantled by the very company creating superintelligence.
The irony is undeniable. But for Leopold, being fired was a kind of liberation. He was no longer employed, no longer had to be cautious in internal memos. He could speak openly to the world.
On June 4, 2024, he published a 165-page article on a website called situational-awareness.ai titled “Situational Awareness: The Decade Ahead”—“The Decade of Situational Awareness.”
165 pages of prophecy
To understand Leopold’s investment logic, you must first read this manifesto. Because his $5.5 billion holdings are the financial translation of these 165 pages.
The core argument of the manifesto can be summarized in one sentence: AGI (Artificial General Intelligence) is very likely to be achieved around 2027.
This judgment sounds crazy in June 2024. But Leopold’s reasoning is straightforward: order of magnitude.
From GPT-2 to GPT-4, AI capabilities have undergone a qualitative leap, transforming from preschoolers to smart high school students. Behind this leap is roughly a 100k-fold (five orders of magnitude) increase in effective compute. This growth comes from stacking physical compute, improving algorithm efficiency, and capabilities unlocked by “unbounding” models.
His prediction is that by 2027, a similar scale of growth will occur again. In terms of physical compute, the resources used to train cutting-edge models will be 100 times more than GPT-4. Algorithm efficiency will improve about 0.5 orders of magnitude annually, totaling roughly 100 times over four years. Plus, the “unbounding” effect will turn AI from chatbots into tools and autonomous agents—another order of magnitude leap.
Stacked together, these three 100-fold increases amount to another 100k times—another qualitative leap—from high schoolers to surpassing humans.
What makes this prediction truly unsettling is the chain of consequences he derives from it.
First: Trillion-dollar compute clusters.
He writes that in the past year, Silicon Valley’s focus has shifted from $10 billion clusters to $100 billion, and now to trillion-dollar clusters. Every six months, the board’s plans add another zero. By the end of this decade, hundreds of millions of GPUs will be in operation.
This forecast sounded exaggerated in June 2024. But in January 2025, the US government announced the Stargate project, a joint investment by SoftBank, OpenAI, Oracle, and MGX, planning to invest $500 billion over four years to build AI infrastructure in the US. The initial deployment was $100 billion, and construction has already begun in Texas.
The “trillion-dollar cluster” in his manifesto became an official White House plan within half a year.
Second: Power crisis.
How much electricity do hundreds of millions of GPUs need? Leopold’s answer: the US’s power generation capacity must increase by dozens of percentage points.
Data confirms his judgment. In 2024, Amazon, Microsoft, Google, and Meta’s capital expenditures exceeded $200 billion, up 62% from 2023. Amazon alone spent $85.8 billion, up 78%. In 2025, Amazon’s capex is expected to surpass $100 billion.
Most of this money is spent on data centers and power infrastructure.
Microsoft did something unimaginable ten years ago: it signed a 20-year power purchase agreement with Constellation Energy to restart the Three Mile Island nuclear plant.
Yes, the same Three Mile Island that experienced the worst nuclear accident in US history in 1979.
The plant is scheduled to reopen in 2028, renamed the Crane Clean Energy Center, powering Microsoft’s data centers. Constellation CEO Joe Dominguez said: “Providing reliable, carbon-free power for critical industries like data centers requires sufficient, continuous energy—nuclear is the only energy that can deliver this promise.”
When a software company starts restarting nuclear plants, you know that electricity has shifted from an infrastructure issue to a strategic resource.
Third: Geopolitical competition.
The most controversial part of the manifesto is Leopold’s near-Cold War language, framing the AGI race as a struggle