Leopold Aschenbrenner, the former OpenAI researcher who departed the lab in 2023 and subsequently published lengthy analyses on artificial general intelligence timelines, disclosed concentrated short exposure to Nvidia and Oracle through his newly launched hedge fund's first 13F filing. The positions totaled approximately $47 million in notional value across puts and short positions, with Nvidia comprising the largest single bearish allocation at roughly $28 million. Oracle accounted for an additional $12 million in short exposure, with smaller positions against Broadcom, AMD, and Taiwan Semiconductor Manufacturing appearing in the same filing.
The disclosure marks the first public visibility into Aschenbrenner's capital allocation since launching the fund in late 2024. The timing is notable—Nvidia closed the quarter ending December 31, 2024 near all-time highs, trading at roughly $140 per share before the recent selloff. Oracle similarly reached record valuations in the same period, benefiting from multi-year cloud infrastructure contracts and database licensing tied to AI training workloads. The 13F shows the positions were established during Q4 2024, when consensus around AI capital expenditure remained firmly bullish and hyperscaler guidance pointed to sustained infrastructure build-out through 2026.
What makes the positioning particularly sharp is Aschenbrenner's public record on AGI development. His June 2024 essay "Situational Awareness" argued that algorithmic progress and compute scaling would converge toward AGI-level systems by 2027, a timeline implying continued heavy investment in GPU clusters and training infrastructure. The short positions appear to reflect not skepticism about AI progress itself, but rather a view on valuation compression or tactical mean reversion after the sector's 180% rally from January 2023 lows. Alternatively, the positions may hedge long exposure in private AI companies or reflect a thesis that inference economics will shift away from Nvidia's current architectural dominance as custom silicon and edge deployments mature.
The Oracle short is less intuitive given the company's database moat and its positioning as infrastructure for both training and inference workloads. One plausible read: Aschenbrenner sees Oracle's 42x forward earnings multiple as unsustainable relative to its 12% revenue growth in cloud services, particularly if AI-driven database demand plateaus or migrates toward open-source alternatives. The inclusion of Taiwan Semiconductor and Broadcom in the short book suggests a broader thesis on semiconductor margin compression rather than company-specific operational concerns.
Allocators should track whether Aschenbrenner adds to these positions in the Q1 2025 filing due in mid-May, especially if Nvidia and Oracle continue to trade near current levels of roughly $115 and $138 respectively. Also worth monitoring: whether the fund discloses long positions in private AI labs or inference-focused startups in future filings, which would clarify whether this is a relative-value trade or an absolute bearish stance. The next catalyst for position updates will be Nvidia's April earnings call, where management typically provides forward guidance on datacenter revenue and H100/H200 shipment trajectories.
Fund flows into AI-exposed equities have moderated since late 2024, with institutional allocators rotating toward selectively profitable software plays and away from pure infrastructure exposure. Aschenbrenner's filing provides a named example of that rotation occurring at the sophisticated end of the capital stack.