In a recent LinkedIn post, Linasbeliunas highlights the remarkable story of Leopold Aschenbrenner, a former OpenAI researcher who, after being fired at 22, has gone on to achieve significant success in the AI investment space. Linasbeliunas uses Aschenbrenner’s journey to illustrate a compelling thesis about the future of artificial intelligence and its infrastructure needs.
Linasbeliunas introduces Aschenbrenner’s background, noting his early academic achievements and his time on OpenAI’s Superalignment team. According to Linasbeliunas:
His AI hedge fund is up ~270% after fees this year through May & more than 1,000% since inception 😳
The post details Aschenbrenner’s trajectory after his departure from OpenAI, emphasizing his decision to publish a detailed manifesto predicting the advent of Artificial General Intelligence (AGI) and a subsequent surge in AI infrastructure spending. This prediction, shared in June 2024, laid the groundwork for his investment strategy.
Aschenbrenner’s Infrastructure-Focused Investment Thesis
Linasbeliunas explains that Aschenbrenner’s hedge fund, Situational Awareness LP, did not focus on AI applications or the major model developers. Instead, as Linasbeliunas points out, the fund made a strategic decision to concentrate on the essential physical infrastructure supporting the AI boom.
This strategic focus is a key element of Aschenbrenner’s approach. Linasbeliunas elaborates on the specific sectors Aschenbrenner targeted:
- Power generation (citing companies like Bloom Energy)
- AI compute clouds and GPU hosting (mentioning CoreWeave and Nebius)
- Bitcoin miners transitioning to AI data centers (including Core Scientific and IREN)
As Linasbeliunas relays Aschenbrenner’s core argument, the ultimate constraint in the scaling of AI will not be the sophistication of the models or algorithms themselves. Instead, the bottleneck will be the availability and capacity of physical resources.
His thesis is simple: As AI scales, the real bottleneck won’t be the models or algorithms. It will be power, electricity, data centers, and connectivity.
The Control of the Physical Layer
Linasbeliunas underscores Aschenbrenner’s view that the ultimate determinant of success in the AI race will be control over the foundational physical layer. This includes the massive energy requirements—gigawatts—and the stability of the electrical grid needed to support advanced AI operations.
In Linasbeliunas’s telling, Aschenbrenner, at the young age of 24, has already strategically positioned himself and his fund to capitalize on this predicted demand. This foresight and bold positioning are what Linasbeliunas finds particularly noteworthy.
A Visionary Approach to AI Investment
Linasbeliunas frames Aschenbrenner’s story as exceptional, moving from a researcher focused on AI safety to a hedge fund manager making substantial bets on the physical underpinnings of AI’s rapid expansion. The narrative presented by Linasbeliunas highlights a contrarian approach to AI investment, focusing on the often-overlooked but critical infrastructure components rather than the more visible software and model development.
Linasbeliunas concludes by emphasizing the significance of Aschenbrenner’s strategy and its potential implications for the future of AI development and investment. The insights shared by Linasbeliunas offer a unique perspective on the essential, yet often understated, elements driving the AI revolution forward.
📝 About This Content
This article is based on insights shared by Linasbeliunas on LinkedIn.
📅 Originally posted on June 13, 2026 | View original post on LinkedIn →