The Hottest 00s Generation on Wall Street

marsbitPubblicato 2026-05-31Pubblicato ultima volta 2026-05-31

Introduzione

"Wall Street's Hottest '00s Phenom: The 25-Year-Old Fund Manager Who Bet on AI's 'Boring' Backbone" At just 25, Leopold Aschenbrenner, once fired by OpenAI, now runs a hedge fund worth $13.7 billion. His strategy? Betting against the consensus. While others chased AI chips, he invested early in the physical infrastructure powering the AI boom: electricity, data centers, and energy. Expelled from OpenAI's safety team in 2024, Aschenbrenner foresaw the coming bottleneck. He argued that AI progress would be limited not by algorithms, but by power, chip capacity, and space. Acting on this, he founded Situational Awareness LP to go long on these "old economy" assets. His bets have paid off spectacularly. His fund's assets soared from $255 million in late 2024 to $13.7 billion by Q1 2026. His portfolio is a direct reflection of his thesis: major long positions in fuel cell company Bloom Energy and data center/bitcoin mining firms like CleanSpark and Riot Platforms, which control critical land and power resources. Conversely, he holds massive put options against overheated semiconductor giants like NVIDIA and AMD. A notable exception was his bullish bet on storage company SanDisk, which surged ~160% in Q2. Aschenbrenner's vision is materializing. Tech giants like Amazon, Alphabet, and Meta are ramping up colossal capital expenditure on data centers. Global data center power consumption is projected to skyrocket, with AI accounting for over half by 2030. The demand for enabling t...

"I was early, but I wasn't wrong."

The protagonist in the movie "The Big Short" would surely resonate deeply with these words, much like the youngest hedge fund manager on Wall Street today.

In 2024, a notice from OpenAI sent 23-year-old Leopold Aschenbrenner packing. Soon after, he turned around and founded a hedge fund, positioning himself against the prevailing consensus—he didn't go all-in on the then-sizzling hot AI chips and semiconductors, but instead went long on electricity, data centers, computing power infrastructure, and energy infrastructure. These were seen as slow, clunky "old-school" assets at the time.

His early calculation soon proved prophetic. Today, tech giants are pouring huge investments into AI infrastructure, and the capital markets have enthusiastically crowned new AI kings in areas like storage and optical modules. Leopold won. His fund's portfolio value had already reached $13.7 billion (approx. RMB 90 billion) by the end of Q1 this year, and his personal wealth has skyrocketed.

And he's only 25. In the AI era, the genius narrative is simply too compelling.

Graduated from University at 19

Fired by OpenAI Two Years Ago

His youth shouldn't be too surprising, considering he started university at 15.

This German teenager from a family of doctors showed exceptional academic talent. In 2021, at age 19, Leopold earned three degrees in Mathematics, Statistics, and Economics, graduating as the valedictorian from Columbia University, and subsequently worked at two funds.

Not long after, he joined OpenAI's Superalignment team. This was a star-studded team, co-led by OpenAI co-founder Ilya Sutskever, with the goal of solving the superintelligence alignment problem within four years—essentially ensuring highly intelligent AI remains under human control.

The drama came when Leopold was very publicly fired by OpenAI.

The trigger was an internal memo written by the OpenAI board warning of insufficient safety measures at the company. This memo, however, sparked tensions between management and the board. In April 2024, OpenAI dismissed Leopold, citing information leaks.

Experiences shape choices and hone foresight.

Shortly after being fired, Leopold published a profound, lengthy essay that almost predicted the current direction of AI development and investment trends. In it, he mentioned that by 2027, large models would be capable of doing the work of AI researchers or engineers.

To achieve this, the key constraints wouldn't be at the algorithmic level, but in electricity, chip manufacturing capacity, and physical space. The power consumption of a single training cluster would leap from megawatt scale to gigawatt scale, approaching the output of a large nuclear power plant.

Based on this prediction, at the end of 2024, Leopold chose to start a business—founding the hedge fund Situational Awareness LP, dedicating himself to going long on the energy and computing power infrastructure needed for AI development, while avoiding the crowded bubbles in chips and the application layer.

Shorting Nvidia

But Buying Into the High-Flier SanDisk

Thus, Wall Street's new genius trader was born.

In May 2026, as Leopold's hedge fund disclosed its latest U.S. stock holdings (13F filing) for the first quarter of the year, the astonishing expansion of this 00s-generation manager's wealth came into view:

The total market value of his portfolio had skyrocketed from $5.52 billion at the end of 2025 to $13.7 billion. At the end of 2024, the fund's size was merely $255 million. This speed is nothing short of meteoric.

Beyond his resume and genius stories, global onlookers were more interested in what he bought.

Looking at his latest holdings, Leopold maintained his long positions in AI infrastructure while establishing new short option positions worth $8.45 billion as a hedge against tech and semiconductors. As of the end of Q1, his top five holdings were all put options. These included put options on the VanEck Semiconductor ETF valued at around $2 billion, put options on Nvidia valued at around $1.6 billion, as well as put options on Oracle, Broadcom, and Advanced Micro Devices (AMD).

This portfolio clearly signaled wariness towards overheated chip stocks. An exception was that by the end of Q1, he had exclusively increased his holdings of SanDisk by 86,000 shares and established call options on SanDisk worth $390 million. SanDisk's subsequent performance undoubtedly became the envy of many; since the start of Q2 alone, SanDisk has risen approximately 160%.

The main action was on the long side, where Leopold heavily invested in critical infrastructure assets for the AGI era.

His top long holding was the fuel cell company Bloom Energy. Leopold holds nearly 6.5 million shares of the company, with a position value of about $879 million. More precisely, Bloom Energy makes fuel cells, which can efficiently convert natural gas directly into electricity.

Simultaneously, in Q1, Leopold also increased his holdings in companies like CleanSpark, Riot Platforms, Applied Digital, and IREN—firms involved in data centers or crypto mining, possessing land, power resources, data center capabilities, or grid permits.

"The speed of AI development is determined by physical bottlenecks, so you should invest in the bottlenecks themselves." Looking across these trades, they precisely correspond to the underlying logic Leopold had when founding the fund.

Of course, for ordinary investors, copying these moves comes a bit late. Holdings reports typically have a 45-day delay, and by the time the public sees what the big players have bought, the most lucrative part of the rally has often already passed.

The End Point of the AI World

"The whole world is starting to value AI infrastructure assets."

In just the past few months of this year, the sectors Leopold bet on—power supply, data center computing power, semiconductor optics—have fully demonstrated their potential and immense demand.

Take electricity, for example. IEA data shows that in 2025, global data centers consumed 485 TWh of electricity, with AI accounting for 170 TWh (35%). It's projected that by 2030, total global data center electricity consumption will reach 950 TWh, with AI consuming 510 TWh (54%), exceeding Japan's total national electricity consumption. China's figures are equally staggering: in 2025, AI electricity consumption reached 450 billion kWh (3.8% of total societal electricity use), and it's expected to reach 600 billion kWh (5%) in 2026, nearly matching the annual electricity consumption of China's entire steel industry.

Then look at "light." As AI competition rapidly evolves from a battle of computing power to one of connectivity, traditional copper wire connections are long overburdened, leading to explosive growth in demand for "optical links."

According to data from UK-based commodity research firm CRU, global data center fiber optic cable usage reached 69.6 million core kilometers in 2025 and is expected to exceed 100 million core kilometers in 2026. Their estimates suggest that by 2027, AI-driven fiber demand will account for 35% of total data center fiber demand. For optical modules, Goldman Sachs has significantly raised its 2026 sales forecast for 800G optical modules from an initial 25 million units to 33.5 million units, a 58% increase.

Unsurprisingly, tech giants have already begun building their AI infrastructure moats.

In 2026, capital expenditure plans from Amazon, Alphabet (Google's parent), Meta, and others have grown substantially, with massive funds directed towards building new data centers and a long list of equipment including AI chips, network cables, and backup generators. Domestically, the latest development is rumors that ByteDance is discussing a spending plan of up to $70 billion (approx. RMB 474.7 billion) this year, primarily for building data centers and other AI infrastructure.

This wave of AI infrastructure frenzy is even more directly and violently reflected in the capital markets.

Looking domestically, the "Yi-Zhong-Tian" trio of optical module giants have seen their stock prices double since last year, especially InnoLight Technology, which soared from a low of 66 yuan per share in April last year to over 1,000 yuan, with a market cap now nearing 1.3 trillion yuan.

Similarly, since the memory cycle rally began in the second half of last year, stocks like Longsys, Deming Li, and Biwin Storage have surged in sync. Dapu Micro, which just went public in April, multiplied its IPO price nearly 20-fold in just one month.

In contrast, one can't help but reflect: the internet was once imagined as a weightless world, yet it gave rise to server rooms, fiber optic cables, and undersea cables. Now AI might seem even lighter, but when it comes to actual implementation, it equally relies on electricity, land, chips, networks, and cooling systems.

A grand future always grows from those silent assets.

This article is from the WeChat public account "Investment Community" (ID: pedaily2012), author: Feng Yuchen

Domande pertinenti

QWhat was the core investment thesis behind Leopold Aschenbrenner's hedge fund, Situational Awareness LP, when he founded it?

AThe core investment thesis was to go long on the physical infrastructure necessary for AI development—such as power, data centers, compute capacity, and energy infrastructure—while avoiding the crowded and potentially overvalued bets on AI chips and semiconductors. He believed that the speed of AI advancement would be limited by these physical bottlenecks, so investors should own the bottlenecks themselves.

QWhat major positions did Leopold Aschenbrenner's fund hold in Q1 2026 according to the 13F filing, and what did they indicate about his market view?

AIn Q1 2026, his fund's largest holdings were put options (bearish bets), primarily on semiconductor and tech companies like the VanEck Semiconductor ETF, NVIDIA, Oracle, Broadcom, and AMD, indicating a strong caution towards overheated valuations in the chip sector. Conversely, he held significant long positions in companies like Bloom Energy (fuel cells), CleanSpark, and other data center/crypto mining firms with energy and infrastructure assets, reflecting his bullish thesis on AI infrastructure.

QWhy was Leopold Aschenbrenner fired from OpenAI, and how did that experience influence his subsequent career path?

AHe was fired from OpenAI in 2024 for allegedly leaking an internal memorandum where the board warned of insufficient safety measures, which heightened tensions between management and the board. This experience, coupled with his work on superintelligence alignment, helped shape his foresight. He later published an essay predicting AI's physical infrastructure needs, which directly led him to found a hedge fund focused on investing in that very sector.

QWhat does the article suggest are the key physical constraints on the rapid development of AI, based on data cited?

AThe article identifies electricity/power and optical connectivity ('light') as key physical constraints. It cites IEA data showing AI's massive and growing share of global data center electricity consumption. It also references forecasts for surging demand in fiber optics and optical modules within data centers, driven by AI's need for high-speed connections that copper wires cannot support.

QAccording to the article, how have capital markets and tech giants responded to the growing demand for AI infrastructure?

ACapital markets have responded by dramatically driving up the stock prices of companies in relevant sectors, such as Chinese optical module manufacturers ('Yizhongtian') and memory chip makers, with some seeing multi-fold increases. Tech giants like Amazon, Alphabet, Meta, and reportedly ByteDance are making massive capital expenditure plans, significantly increasing investments in building new data centers and purchasing related equipment like AI chips and network cables to secure their AI infrastructure moats.

Letture associate

Review of Cathie Wood's Masterstroke Operation on Circle

A Recap of Cathie Wood's Masterful Trading in Circle's IPO This article analyzes the strategic moves made by ARK Invest's Cathie Wood around the IPO of Circle (CRCL). Despite her typical long-term, narrative-driven investment style, Wood executed a textbook "buy low, sell high" trade. Wood secured a core position of approximately 4.49 million shares at the $31 IPO price. The stock debuted at $69, surged to a high of $299 in June 2025 fueled by stablecoin regulatory news (the GENIUS Act), and then entered a prolonged decline. During this rally, ARK systematically sold around 1.7 million shares at an average price near $210, driven partly by internal fund rebalancing rules triggered by the stock's soaring weight. This move locked in substantial profits. As the stock later fell due to lockup expirations, new share issuance, and interest rate concerns—even dipping below $50—Wood began repurchasing shares. Starting in November 2025 around $86, she continued buying on the way down, eventually rebuilding her position to roughly the original size by Q1 2026. Key takeaways include: 1) Having a strong, independent long-term thesis (viewing Circle as critical digital dollar infrastructure). 2) Trading in tranches instead of trying to time exact tops or bottoms. 3) Maintaining strict position-sizing discipline, using rules to force profit-taking and preserve buying power. For most retail investors, chasing the dramatic "pop" at open is dangerous, as the subsequent 83% drawdown showed. Wood's success hinged on pre-IPO access, a clear investment thesis, and disciplined execution.

marsbit3 h fa

Review of Cathie Wood's Masterstroke Operation on Circle

marsbit3 h fa

Sharplink CEO: Ethereum's Future is Unfolding Now

In an article titled "Sharplink CEO: Ethereum's Future is Unfolding," Joseph Chalom, a former BlackRock executive and current Sharplink CEO, argues that the current debates surrounding the Ethereum Foundation (EF) and ETH price miss the bigger picture. He asserts that Ethereum's long-term institutional adoption is secured by its foundational strengths: trust, security, and liquidity. Chalom highlights Ethereum's dominance in settling stablecoin value, tokenizing real-world assets (RWA), and facilitating high-value DeFi transactions as evidence of its winning position. He defends the Ethereum Foundation's focus on rigorous protocol development and a decade-long track record of major upgrades (The Merge, EIP-1559, Dencun, etc.), viewing its upcoming technical roadmap as the most ambitious in the industry. Contrary to critics, Chalom posits that Ethereum's decentralization and reliable neutrality are core strengths for institutional adoption, not weaknesses, as they prevent control by any single entity. Drawing a parallel to Amazon's early days, he suggests that ETH's intrinsic value is tied to the expansion of its network, which is poised for a step-change in transaction volume across stablecoins, RWAs, DeFi, and agentic finance. Chalom advocates for a "be greedy when others are fearful" approach, citing historical examples from Warren Buffett and his own experience at BlackRock during the crypto winter. He concludes that while the EF should remain focused on core protocol attributes (CROPS: Censorship Resistance, Capture Resistance, Open Source, Privacy, Security), there is a leadership gap in market outreach. Chalom calls for ecosystem participants, including Sharplink and other key players, to become more vocal advocates to support the coming institutional adoption supercycle, asserting that "Ethereum's future is unfolding now."

marsbit3 h fa

Sharplink CEO: Ethereum's Future is Unfolding Now

marsbit3 h fa

6 Questions to Understand the Business Trends of AI

The AI industry has entered its "summer" phase, according to a six-dimensional scoring framework assessing its development cycle. Each dimension—narrative vs. delivery, system connectivity, delivery capability, ROI rationalization, common industry trends, and capital environment—scores 1 point, totaling 6 points. This places the industry firmly in summer (5-7 points), characterized by a coexistence of grand promises and tangible deliverables, with increasing pressure to demonstrate value and profitability. Key signals mark this shift. ByteDance's Doubao launched paid subscriptions, while OpenAI introduced an advertising platform. These moves are driven by dual forces: immense cost pressures from scaling user bases and massive compute requirements, and the maturation of commercial opportunities. Major players like Anthropic report explosive growth, highlighting AI's transition into core productivity infrastructure. For businesses, the path forward involves three strategic steps. First, identify a small, high-impact use case to quickly demonstrate a closed-loop value proposition, such as automating customer service or content generation. Second, systematically replicate successful pilots across the organization by standardizing processes, building shared AI capabilities, and aligning talent, incentives, and leadership. Finally, move beyond simply adding AI to existing workflows and undertake systemic reconstruction—redesigning processes for parallel AI-human collaboration, implementing real-time dashboards, and establishing automated trigger chains. The era where storytelling alone secured funding is over. The focus has shifted to delivering measurable efficiency gains, cost savings, and new revenue streams, as evidenced by real-world implementations in companies like Semir, Anta, and Midea. Success now depends on starting with a focused proof point, scaling it organization-wide, and ultimately allowing AI to redefine operational paradigms.

marsbit9 h fa

6 Questions to Understand the Business Trends of AI

marsbit9 h fa

Trading

Spot
Futures
活动图片