The AI Stock Genius Who Made 60x Bets $7.7 Billion on Nvidia Topping Out

链捕手Pubblicato 2026-05-20Pubblicato ultima volta 2026-05-20

Introduzione

An AI-focused hedge fund named Situational Awareness LP, known for its 60x returns, has taken a significant bearish stance on semiconductor stocks in Q1 2026. Its 13F filing reveals a massive 148% quarterly increase in nominal exposure to $13.677 billion, with over 60% of the new exposure directed towards put options on major chip players. Key bearish bets include $2.04 billion in puts on the VanEck Semiconductor ETF (SMH) and $1.56 billion on NVIDIA, alongside positions against Broadcom, Oracle, AMD, and others. The fund simultaneously increased its long equity holdings in AI infrastructure and compute providers like CoreWeave and Bitcoin mining companies repurposing for compute. The core thesis behind this positioning is a shift in the primary constraint for AI expansion. The fund argues that while GPU supply was the critical bottleneck in previous years, the new limiting factors for large-scale AI cluster deployment are physical infrastructure: electrical grid access (with multi-year backlogs in the US), power availability, land, and data center construction timelines. The fund is not betting against AI's success but rather hedging against potential valuation corrections in semiconductor stocks whose prices may have run ahead, while directly investing in the downstream physical bottlenecks—power and data center capacity—it believes will capture value next. This move translates a previously theoretical narrative about infrastructure constraints into a concrete, high-convic...

Author: BiBi News

On May 18, 2026, Situational Awareness LP submitted its 13F filing for the first quarter of 2026.

The fund's nominal exposure to U.S. stocks and options expanded from $5.52 billion at the end of 2025 to $13.677 billion, a single-quarter growth of 148%.

However, what caught market attention was not the size, but the structure: over 60% of the new nominal exposure was entirely placed in put options on the semiconductor sector.

What Q1 Did

The put options cover nine targets: VanEck Semiconductor ETF (SMH), NVIDIA, Broadcom, Oracle, AMD, Micron, TSMC, ASML, Intel.

Among them, SMH has the largest put nominal size at $2.04 billion, followed by NVIDIA at $1.56 billion. Micron and TSMC hold both call and put options, indicating a bet on volatility rather than a one-sided short.

It should be noted that the 13F filing only discloses the nominal value of options, making it impossible to directly determine the net short size. These put positions could be active shorting or could be hedging protection purchased while holding long positions.

The full intent cannot be reconstructed from the filing alone.

In the stock direction, the fund continued to bet on computing infrastructure.

CoreWeave holdings increased from 6.1 million shares to 7.18 million shares; IREN and Applied Digital were similarly increased;

The expansion was most pronounced in the miner direction: Bitfarms (now renamed Keel Infrastructure) increased from 6.9 million shares to 19.88 million shares, CleanSpark increased from 1.64 million shares to 12.28 million shares, Riot Platforms increased from 6.17 million shares to 11.5 million shares.

Bloom Energy reduced holdings by 3.59 million shares but still holds about $879 million in market value, while retaining 408.5 thousand call options. This is profit-taking, not a change in direction.

Exits were concentrated in the optical communication direction.

Lumentum and Coherent were completely liquidated; last quarter, Lumentum's position accounted for as much as 8.68%, this quarter it is zero.

Intel's operation deserves separate attention: last quarter held about 20 million call options, all liquidated this quarter, while establishing new put option positions.

Not a flat position, but a complete reversal in direction, from bullish to bearish.

Where the Bottleneck Is, the Money Is

The logic behind this 13F is a specific judgment on supply and demand: the constraints on AI expansion are shifting.

Over the past two years, the core constraint limiting AI scale was GPU shortage, so the market persistently traded NVIDIA, HBM memory, advanced manufacturing, and optical communication. During this phase, the semiconductor sector as a whole received a significant premium.

However, as computing clusters scale towards hundreds of thousands or even millions of GPUs, new constraints are emerging.

Grid connection applications in the US currently have a backlog exceeding 2TW, with an average wait time of over five years; transformer capacity is limited, and new data center construction cycles are measured in years; chips can continue to expand production, but the electricity, land, and construction capabilities needed to support their operation cannot keep pace.

Under this judgment, the logic of shorting the semiconductor sector is not the belief that AI will fail, but that valuations in the chip sector have already priced in expectations, and value is migrating to downstream physical infrastructure.

Buying puts on SMH and NVIDIA hedges against potential valuation corrections in the chip sector; continuing to hold CoreWeave, transformed miner companies, Bloom Energy, is betting on the real bottlenecks: electricity and data center capacity.

CoreWeave's operation also confirms this thinking: call options were slashed from 10.81 million to 1.81 million, while common shares increased from 6.1 million to 7.18 million shares.

The direction hasn't changed, only the high-leverage option positions were swapped for common stock to reduce portfolio volatility impact.

From $225 Million to $13.677 Billion

This fund was founded in September 2024; its first 13F disclosed U.S. stock exposure of about $225 million. By the end of 2025, this number had grown to $5.52 billion; as of March 31, 2026, the nominal exposure reached $13.677 billion.

In the first half of 2025, the fund achieved a return of about 47%, while the S&P 500 rose only about 6%; for the full year, it outperformed the S&P 500 by about 12.5 percentage points.

Before founding the fund, this 24-year-old German published a 165-page paper titled "Situational Awareness: The Decade Ahead," outlining judgments on the AGI timeline and that power and computing infrastructure would become the biggest bottlenecks. The fund's early capital came from Nat Friedman, Daniel Gross, and Stripe co-founders Patrick and John Collison.

The significance of this quarterly report is that it translates a judgment that was previously more narrative into concrete portfolio structure.

Chips are merely the entry point for expansion; what truly determines the speed of AI expansion is whether, in the real world, power can be connected, data centers can be built, and grid connection approvals can be obtained within five years.

If this judgment holds, the keywords for AI investment over the past two years were GPU and models; in the coming years, they may be electricity, land, and construction time.

Domande pertinenti

QWhat was the most significant action taken by Situational Awareness LP in Q1 2026, as revealed by its 13F filing?

AOver 60% of the fund's new nominal exposure was placed in put options on the semiconductor sector, signaling a major directional bet against or a hedge for the chip industry. This includes significant put positions on VanEck Semiconductor ETF (SMH) and NVIDIA.

QWhich physical infrastructure sectors did Situational Awareness LP increase its long positions in, and why?

AThe fund increased long positions in power and data center infrastructure companies like CoreWeave, IREN, Applied Digital, and bitcoin miners transitioning to data centers (e.g., Bitfarms, CleanSpark, Riot Platforms). This was based on the belief that constraints for AI expansion are shifting from GPU shortages to bottlenecks in electricity, land, and construction capacity.

QWhat was Situational Awareness LP's specific action regarding Intel in Q1 2026, and what does it indicate?

AThe fund completely closed its approximately 20 million call option positions on Intel from the previous quarter and simultaneously established new put option positions. This indicates a complete reversal in view, from bullish to bearish on the company.

QAccording to the article's analysis, what is the core logic behind the fund's seemingly contradictory moves of holding puts on chips while being long on infrastructure?

AThe core logic is that the valuation for chip companies has already priced in high expectations, while the real constraint for future AI growth is the availability of physical infrastructure like power grids and data centers. Therefore, the fund is hedging potential chip valuation pullbacks while betting on the rising value of the downstream infrastructure bottlenecks.

QHow has Situational Awareness LP's performance been since its inception, and who were its notable early backers?

ASince its founding in September 2024, the fund's nominal exposure grew from $225 million to $13.677 billion by Q1 2026. It significantly outperformed the S&P 500, delivering ~47% returns in H1 2025 versus the index's ~6%. Early backers included prominent figures like Nat Friedman, Daniel Gross, and Stripe co-founders Patrick and John Collison.

Letture associate

Fei-Fei Li's Team Clarifies the Concept of 'World Models', Sora Merely a Renderer

"World Models" has become a widely used yet confusing term in AI. To address this, a team led by Fei-Fei Li and World Labs proposed a functional taxonomy based on the Partially Observable Markov Decision Process framework. This taxonomy categorizes systems called "world models" into three distinct projections: Renderers, Simulators, and Planners. Renderers, like OpenAI's Sora and other video generation models, focus on producing photorealistic visual outputs for human perception. They prioritize visual fidelity over physical accuracy. Simulators, such as NVIDIA Omniverse, aim to compute precise future environmental states for computational tasks like engineering analysis or digital twins. Planners, like Vision-Language-Action models, take in observations and goals to output executable actions for robots or agents. The article clarifies that most current "world models," including Sora, are primarily Renderers. They generate convincing visuals but lack the core ability to simulate state transitions based on actions, a key requirement for a true world model in classic reinforcement learning definitions. This conceptual confusion has practical implications, leading to potential misalignment in technology selection, investment, and public understanding of AI capabilities. Clear categorization is crucial. It helps enterprises avoid costly mistakes (e.g., using a renderer for robot training), allows investors to accurately assess markets, and enables researchers to build comparable benchmarks. While future systems may integrate these functions, recognizing current boundaries is essential for honest assessment and progress.

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Bloomberg Uncovered: How Do China's Wealthy Circumvent the Annual $50,000 Limit to Transfer Assets?

**Summary: How Wealthy Chinese Circumvent $50,000 Annual Foreign Exchange Limits** Despite China's strict capital controls, including an annual $50,000 per person foreign exchange quota, an estimated $150 billion in funds still leaves the country annually via various gray and underground channels. This report outlines the evolution of China's "capital wall" and the methods used to bypass it. **The Evolving Capital Controls:** * **Foundation (1994):** The system of "current account convertibility with strict capital account controls" was established. * **Quota Set (2007):** The $50,000 individual annual forex purchase limit was formalized. * **Crackdown Begins (2015-2017):** Following market volatility, enforcement tightened. Banks were required to scrutinize transactions, and channels like using UnionPay cards for Hong Kong insurance premiums or buying overseas property were blocked. * **Digital & Legal Upgrades (2024-2026):** Enhanced algorithms now flag suspicious patterns (e.g., "smurfing"). The Common Reporting Standard (CRS) provides Chinese tax authorities with data on citizens' offshore accounts. Unlicensed cross-border brokers have been targeted. **Five Primary Methods for Moving Capital:** 1. **Underground Banking / "Hawala" (Duiqiao):** The largest-scale method. No money crosses borders. Clients pay RMB to a domestic account; an overseas associate deposits equivalent foreign currency into the client's offshore account. Risks include high fees, account freezes, and legal penalties. 2. **"Smurfing" or "Ant Moving":** Using multiple individuals' $50,000 quotas to pool funds for one offshore recipient. Increasingly detected by anti-money laundering algorithms. 3. **Trade Invoice Manipulation:** Businesses over-invoice imports or under-invoice exports via offshore shell companies, creating a pretext to transfer excess funds abroad under the guise of trade. 4. **Channel Migration:** After a crackdown on internet brokers, funds flow toward more compliant but costly channels like major banks' cross-border wealth management services or Qualified Domestic Institutional Investor (QDII) quotas. 5. **Structural Arrangements:** High-net-worth individuals use complex, high-cost legal structures involving offshore trusts, insurance, and investment migration programs to transfer asset ownership. **Regulatory Response: Focusing on People, Not Just Money** The current strategy extends oversight from enterprises to **individual residents**. Tools like CRS allow retroactive visibility into offshore assets. Cryptocurrencies, once seen as a potential loophole, are now actively monitored and prosecuted as an illegal channel. The underlying driver remains: with significant wealth concentrated among millions of affluent households seeking diversification amid domestic economic shifts, the incentive to move assets offshore persists despite regulatory barriers.

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Bloomberg Uncovered: How Do China's Wealthy Circumvent the Annual $50,000 Limit to Transfer Assets?

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