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Fedus leaves OpenAI to pioneer the fusion of AI with materials science, signaling a new era where advanced algorithms could revolutionize how we develop and understand materials.
Liam Fedus, the Vice President of Research for Post-Training at OpenAI, has announced his departure from the company to found a new materials science AI startup. The move, initially reported by The Information, marks a significant shift in Fedus's career and highlights the growing intersection between artificial intelligence and advanced materials research.
Fedus’s transition underscores the increasing importance of AI in materials science, a field that has traditionally relied heavily on experimental methods and empirical data. The application of machine learning algorithms can accelerate the discovery and optimization of new materials, potentially leading to breakthroughs in areas such as renewable energy, electronics, and healthcare. This move also signals a broader trend of top AI talent moving into specialized domains where their skills can drive significant innovation.

In a statement on X (formerly Twitter), Fedus confirmed his departure and shared his vision for the new venture. "My undergrad was in physics, and I’m keen to apply this technology there," he said. "The intersection of AI and materials science is ripe with opportunities, and I believe we can make meaningful contributions to both fields."
Liam Fedus’s move from OpenAI to a materials science startup highlights the growing potential of AI in specialized industries. While the venture faces significant challenges, the opportunity for innovation and market impact is substantial. As the field continues to evolve, it will be crucial to monitor how Fedus and his team navigate these obstacles and capitalize on the vast potential of AI in materials science.
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Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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24 March 2025
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