Meta has reportedly recruited two more senior artificial intelligence scientists from OpenAI, escalating the ongoing battle for elite AI talent. Jason Wei, an OpenAI researcher specializing in chain-of-thought reasoning and reinforcement learning, is joining Meta's newly established super intelligence lab according to industry sources.
Wei's professional website details his contributions to OpenAI's o3 model and Deep Research initiative. Before joining OpenAI in 2023, he conducted research at Google focused on training AI systems to decompose complex problems through sequential reasoning. His expertise in reinforcement learning – training models through reward/punishment systems – aligns precisely with Meta's super intelligence team's research priorities.
Fellow researcher Hyung Won Chung will also transition to Meta. Internal sources confirm both researchers' Slack accounts at OpenAI have been deactivated. Chung collaborated with Wei on multiple projects including the o1 model and Deep Research, with his work concentrating on reasoning and agents. LinkedIn profiles reveal both scientists previously worked at Google before simultaneously joining OpenAI.
This recruitment follows Meta's established pattern of acquiring entire research teams. The company previously hired three former Google scientists from OpenAI's Swiss office for its super intelligence division. The move coincides with Meta's intensified talent acquisition campaign offering compensation packages reportedly reaching up to $3 million annually over four years ($215.4 million equivalent).
Meta CEO Mark Zuckerberg recently outlined the company's AI roadmap in internal communications, noting that many new recruits originate from OpenAI. The talent competition continues escalating, with OpenAI countering last week by hiring four senior engineers from Tesla, xAI, and Meta.
In a Tuesday social media post, Wei reflected on reinforcement learning principles: "Imitation is necessary in life and AI training. But surpassing your teachers requires forging your own path – taking environmental risks and harvesting rewards."