OpenAI’s Sora Engineers Bet Everything on Artificial Superintelligence

According to Business Insider, OpenAI engineer Will DePue, a core contributor to the company’s text-to-video model Sora, announced on Wednesday that he’s returning to OpenAI after a long break to start a new team focused on artificial superintelligence. DePue will be joined by fellow Sora engineers Troy Luhman and Eric Luhman in what he describes as an “incredibly high-risk bet that has a small, but significant, chance of leading to ASI.” The team plans to remain small but is seeking “high-slope researchers & engineers interested in making progress in uncharted territory.” DePue first joined OpenAI in July 2023 after studying computer science at the University of Michigan, where he subsequently dropped out, and his work included training ChatGPT models and developing Sora before his recent break. This development comes as OpenAI shifts focus beyond artificial general intelligence toward superintelligence, setting the stage for one of the most ambitious AI research efforts to date.

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From Video Generation to Superintelligence

The composition of this new team is particularly revealing. These aren’t theoretical researchers but practical engineers who delivered one of 2024’s most impressive AI demonstrations. Sora’s ability to generate coherent, physically plausible video sequences represents a significant leap in AI’s understanding of temporal dynamics and world modeling. This practical experience with multimodal systems that must maintain consistency across time gives them unique insights into the challenges of building more advanced AI systems. The transition from creating convincing simulations of reality to potentially creating intelligence that surpasses human reasoning represents a natural, if ambitious, progression path for this technical talent.

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The High-Stakes Nature of Superintelligence Research

DePue’s characterization of this as an “incredibly high-risk bet” deserves serious consideration. Research into superintelligence carries profound safety concerns that extend far beyond typical AI development risks. Unlike narrow AI systems designed for specific tasks, superintelligence by definition would operate beyond human comprehension and control. The very researchers pursuing this goal acknowledge they’re working in “uncharted territory” where established safety protocols may prove inadequate. This creates a fundamental tension between acceleration and caution that has divided the AI community for years, with some experts arguing we should pause such research until proper safety frameworks are established.

OpenAI’s Strategic Pivot

This team formation signals a significant evolution in OpenAI‘s research priorities. While the company has always maintained AGI as its north star, creating a dedicated team specifically targeting superintelligence suggests they believe foundational AGI may be closer than publicly acknowledged. CEO Sam Altman’s January blog post about looking beyond AGI to superintelligence now appears to be more than theoretical positioning. The company seems to be making concrete organizational investments toward this goal, potentially putting them ahead of competitors who remain focused on incremental improvements to existing models rather than paradigm-shifting breakthroughs.

The Intensifying AI Talent Competition

The recruitment strategy for this team—seeking “high-slope researchers & engineers”—highlights the extreme selectivity occurring at the frontier of AI research. As evidenced by DePue’s own background (dropping out of university to join OpenAI) and his LinkedIn profile showing rapid career progression, the competition for elite AI talent has become increasingly detached from traditional credentials. Companies are prioritizing demonstrated capability and innovative thinking over formal education, creating a market where young, unconventional thinkers command extraordinary influence and compensation. This trend is likely to accelerate as the race for advanced AI intensifies.

The Immense Technical Hurdles Ahead

While the ambition is compelling, the path to superintelligence remains fraught with unsolved problems. Current AI systems, including advanced generative pre-trained transformers, excel at pattern recognition and content generation but struggle with true reasoning, causality, and common sense. Bridging this gap requires fundamental breakthroughs in architecture, training methodologies, and possibly entirely new paradigms beyond the transformer models that currently dominate AI. The team’s experience with Sora provides valuable insights into temporal reasoning and world modeling, but scaling these capabilities to human-level and then superhuman intelligence represents multiple orders of magnitude increase in complexity.

Broader Implications for AI Development

This development will likely trigger similar initiatives across the industry as competitors respond to OpenAI’s ambitious positioning. The concentration of top AI talent into small, focused teams pursuing high-risk breakthroughs could accelerate the field but also create fragmentation in safety standards and research priorities. As an engineer-led initiative rather than a purely research-driven effort, this team’s approach may prioritize practical demonstrations over theoretical frameworks, potentially leading to faster but less predictable progress. The coming months will reveal whether this represents a new model for pursuing AI breakthroughs or an isolated experiment in high-risk, high-reward research.