A young man who once abandoned his secondary education has demonstrated how modern technology can radically alter the trajectory of a life. After leaving high school, Gabriel Petersson educated himself in the complex field of machine learning almost entirely through conversations with ChatGPT. Today, remarkably, that same self-taught student serves as a research scientist at OpenAI, contributing to the development of Sora—a project that typically requires advanced academic credentials and years of formal expertise.
Appearing on the podcast *Extraordinary*, released on a recent Thursday, Petersson reflected on his unconventional path and the role that AI-assisted learning played in it. He emphasized that his current position, which is usually filled by doctorate holders, became attainable because he could acquire the necessary theoretical and practical knowledge independently. By leveraging ChatGPT as both a mentor and an interactive textbook, he discovered that access to foundational understanding in machine learning was no longer restricted to universities. In his words, institutions no longer possess an exclusive claim to the world’s intellectual foundations; today, almost any curious mind can obtain essential knowledge instantly through AI. He explained that his learning process was inherently recursive: one begins with a concrete problem and gradually unpacks it layer by layer, using inquiry to move deeper until comprehension crystallizes.
According to his LinkedIn profile, Petersson joined OpenAI’s Sora division in December. Prior to this, he gained experience as a software engineer at both Midjourney and Dataland. His journey began when he walked away from high school in Sweden in 2019 to participate in a small startup. Faced with the immediate need to contribute to product development, he was forced to learn programming on the job. He recalled how the early days at the startup required the creation of real systems—from product recommendation engines to web scraping tools and third‑party integrations—each posing a tangible challenge that demanded applied learning rather than theoretical abstraction.
For Petersson, the advantage of working in a practical environment was clear: real problems provide real motivation. He believes individuals master new disciplines fastest when they start from a goal-oriented perspective—a so‑called top‑down approach—rather than passively absorbing abstract theory. This same philosophy guided him when he transitioned to studying machine learning. Beginning with a specific project idea, he would consult ChatGPT to identify what kind of software to build and to generate the initial code framework. When inevitable bugs and errors appeared, he relied on the model’s assistance to debug and refine his code. As he progressed, he systematically explored each subsystem, studying the algorithms and logic behind them until the overarching structure of machine learning made intuitive sense. Eventually, as he put it, foundational understanding emerged naturally, allowing him to bypass the traditional bottom‑up educational process.
On the topic of career success, Petersson maintains that results matter far more than academic credentials. According to him, companies, especially in the technology sector, primarily seek individuals who can drive innovation and profitability. Demonstrating competence—by building functional products, generating value, and proving one’s technical ability—is, in his experience, a far more compelling credential than any diploma.
This philosophy aligns with a broader trend reshaping the technology landscape. Increasingly, college dropouts have become prominent innovators, aided by accessible AI tools that make sophisticated experimentation possible without formal degrees. OpenAI’s own chief executive officer, Sam Altman—a Stanford dropout—recently voiced his admiration for the current wave of self‑taught, entrepreneurial young people. In an interview at the DevDay conference in October, Altman remarked that he envies today’s generation of twenty‑something creators, as the technological possibilities available to them are vast and unimaginably open.
This cultural shift has not gone unnoticed by venture capitalists either. In a March blog post, the prominent investment firm Andreessen Horowitz observed that the field has been leveled for young innovators, declaring that the present era represents the most advantageous moment in a decade for ambitious dropouts or recent graduates to launch new companies. The message is clear: barriers to entry are collapsing, and intellectual drive now outpaces formal credentials as a determinant of success.
Moreover, some corporate leaders have begun to actively challenge the relevance of traditional education. Alex Karp, CEO of Palantir, stated in an interview on CNBC that much of what is taught about how the world works is fundamentally misguided. To reinforce this belief in merit over pedigree, Palantir inaugurated the Meritocracy Fellowship—a four‑month paid internship program designed specifically for high school graduates who have chosen not to pursue college. This initiative highlights a growing recognition that capability, creativity, and determination can emerge outside conventional academic frameworks.
Gabriel Petersson’s story encapsulates this shift perfectly: a once‑overlooked high school dropout who, through curiosity, persistence, and the intelligent use of AI tools, ascended into one of the most selective research roles in the global technology industry. His experience stands as compelling evidence that in the age of artificial intelligence, the potential to learn, innovate, and succeed is no longer confined to the walls of any institution.
Sourse: https://www.businessinsider.com/high-school-dropout-openai-chatgpt-learn-ai-gabriel-petersson-2025-11
