Meta hires two AI talents from OpenAI: Jason Wei and Hyung Won Chung join Zuckerberg’s Superlab

The arrival of Jason Wei and Hyung Won Chung at Meta changes the balance in global AI research labs.

Meta brings into its research team two key figures who have driven progress at OpenAI and Google, intensifying the race for dominance in deep learning, reasoning, and superintelligence technologies.

Jason Wei and Hyung Won Chung, among the most recognized profiles in AI research, have left OpenAI to join the Meta Superintelligence Lab. Their simultaneous move highlights the increasing competitive pressure among research labs and marks a significant step in the ongoing “talent war” that is transforming the distribution of high-level expertise in the sector. Meta’s decision, focused on personalities capable of bringing radical innovation to the architectures and paradigms of artificial intelligence, redefines the balance of power and underscores the centrality of individuals in the race for technological advancement.

Jason Wei brings advanced reasoning and reinforcement learning to the table.

Jason Wei’s “step by step” approach has helped transform the way language models tackle complex problems, demonstrating that innovation is born from the ability to break down reality into intermediate steps and to learn autonomously through continuous rewards and experimentation.

Jason Wei’s career is marked by insights that have truly transformed the AI sector. After beginning his journey at Google—where he contributed to developing the “chain-of-thought” methodology, a process that guides models in the sequential elaboration of complex reasoning—Wei quickly established himself as one of the most authoritative voices on the international scene. Joining OpenAI allowed him to put these ideas into practice, applying them to the development of new models capable not only of emulating human behavior but also of learning autonomously through increasingly sophisticated reinforcement learning techniques.

His work has enabled a new generation of AI systems capable of tackling complex problems and offering novel solutions, moving beyond mere imitation of training data. Wei’s philosophy, centered on the value of experimentation and the courage to face uncertainty, has deeply influenced the evolution of today’s most advanced language systems.

Hyung Won Chung’s journey strengthens Meta’s focus on symbolic research.

Hyung Won Chung’s work stands out for his ability to integrate symbolic logic, intelligent agents, and a long-term vision aimed at building truly autonomous AI architectures capable of facing complex scenarios and making independent decisions regardless of traditional inputs.

In recent years, Hyung Won Chung has established himself as one of the leading experts in symbolic reasoning as applied to artificial intelligence models. After an initial period at Google—where he developed his expertise in close collaboration with Jason Wei—Chung continued at OpenAI, specializing in the study and implementation of intelligent agents: systems capable of interacting with dynamic environments and learning through observation and deduction.

His research has broadened the scope of AI applications, demonstrating how symbolic logic can become the key to building models that are not only high-performing but also transparent and explainable. Chung’s arrival at Meta adds scientific depth and a long-term perspective to the company’s AI development strategy, strengthening Meta’s ability to tackle new challenges in superintelligence and advanced algorithm governance.

Meta Superintelligence Labs opens a new era of research and development in AI.

The creation of a laboratory entirely dedicated to superintelligence marks a step change in Meta’s ambition, with the goal of attracting the brightest minds and investing unprecedented resources to place itself at the heart of future technological revolutions.

Meta’s decision to establish the Superintelligence Labs marks the beginning of a phase where AI research surpasses traditional boundaries and embraces theoretical and practical scenarios with global reach. The lab, located in the heart of Silicon Valley, was founded with the mission of developing superintelligence architectures capable of redefining the very concept of machine learning and solving problems still beyond the reach of conventional models.

Meta’s strategy is based on integrating multidisciplinary approaches and recruiting world-renowned scientists and engineers, with the clear goal of anticipating the great challenges of artificial intelligence in the coming years. In this context, the arrival of Wei and Chung is a move that confirms Meta’s determination to accelerate both fundamental and applied research, consolidating its position as a global leader in AI innovation.

The AI talent war among the big players is changing the rules of competition.

Multi-million dollar offers, personalized contracts, and increasingly aggressive retention policies have become central tools in the competition among labs, turning researcher recruitment into a true global battle for the future of artificial intelligence.

In recent months, the AI sector has seen an unprecedented rush to secure the best available talent. Leading tech companies have deployed huge resources to attract scientists, engineers, and researchers, offering signing bonuses, accelerated growth paths, and ever more substantial compensation packages.

This phenomenon has led to a rapid circulation of expertise among major players, sparking competition that is no longer just about technology quality, but also about the ability to create interdisciplinary teams that can work quickly and inventively on novel projects. Against this backdrop, Meta has opted for a particularly ambitious strategy, investing heavily in both human capital and infrastructure in an attempt to build durable and resilient leadership in the face of any competitive challenge.

Meta invests in advanced infrastructure to support the growth of its models.

The construction of next-generation data centers and the enhancement of computing platforms reflect Meta’s determination to provide its researchers with all the tools they need to tackle the challenges posed by the future of AI, with a focus on sustainability, efficiency, and scalability.

The exponential growth in AI model complexity requires technical infrastructure equal to these new challenges. Meta has responded with a series of targeted investments in cutting-edge data centers, featuring innovative cooling technologies, low-impact energy systems, and ultra-broadband interconnection networks.

These compute centers are designed to support massive workloads and quickly adapt to evolving research needs, all while ensuring remarkable energy efficiency. These new investments form a fundamental pillar for the development of increasingly sophisticated models, allowing Meta to position itself as a pioneer in creating environments where advanced experimentation can flourish without structural or logistical limits.

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A new philosophy drives research: autonomy and risk become the cornerstones of innovation.

Meta’s stated goal is to develop artificial intelligence capable of truly learning from experience, taking calculated risks, and learning through continuous experimentation in order to produce original and adaptive solutions that go beyond simply imitating observed data.

The arrival of Wei and Chung marks the start of a phase in which AI research frees itself from the constraints of imitation and replication, embracing a philosophy founded on the ability to learn from the environment and adapt to new and unpredictable situations.

This new approach is based on a vision that recognizes the value of error and experimentation, promoting the growth of systems that evolve over time thanks to direct engagement with reality. Innovation is thus seen as the result of an active journey of discovery, where artificial intelligence not only responds to stimuli but learns to take initiative, explore alternative possibilities, and develop increasingly refined strategies over time.

The synergy between advanced research and practical applications defines the new challenge.

Meta aims to transform laboratory superiority into tangible solutions that impact users’ lives and redefine standards for companies in every sector, further cementing its role as a leader in the global artificial intelligence market.

With the arrival of new prominent figures in its labs, Meta is working to strengthen the integration between theoretical breakthroughs and high-impact applications. The goal is clear: to anticipate sector evolutions and deliver innovations with real-world effects, both for businesses and in everyday user experiences. Investing in people, infrastructure, and research processes translates into an ability to generate platforms and tools that go beyond laboratory experimentation, ultimately shaping how companies and citizens use AI in real life.

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