Meta CEO Mark Zuckerberg announced that Shengjia Zhao, a well-known AI researcher and one of the co-creators of ChatGPT and GPT-4, has joined Meta as the Chief Scientist of its new Meta Superintelligence Labs (MSL).
Zhao, who was a former lead scientist at OpenAI, helped build ChatGPT, GPT-4, and several other models, including GPT-4.1 and o3. He also worked on synthetic data research at OpenAI, which helps train AI models better.
Now, at Meta, he will work closely with Mark Zuckerberg and Alexandr Wang, Meta’s newly appointed Chief AI Officer. Alexandr Wang is also the founder of Scale AI, the startup where Meta recently invested over $14 billion.
Mark Zuckerberg shared the news in a Threads post, saying, “In this role, Shengjia will set the research agenda and scientific direction for our new lab, working directly with Alex and me.” He also called Zhao a “pioneer” in the AI field who has led several major AI breakthroughs.
Zhao’s appointment is part of Meta’s larger plan to develop Artificial Superintelligence, often called ASI. Meta recently launched the Superintelligence Labs to focus on this goal. The lab will build powerful AI systems that are safe and helpful for humans.
It will also work on improving Meta’s Llama models, which have not yet performed as expected. Zhao is now a co-founder of the Superintelligence Labs, which will operate separately from FAIR, Meta’s original AI research team led by deep learning expert Yann LeCun.
Meta has been working hard to build up its AI team, and this effort is becoming more visible with each passing month. The company has recently hired many researchers from OpenAI, Anthropic, and Google DeepMind. Among them are the three researchers who started OpenAI’s Zurich office — Lucas Beyer, Alexander Kolesnikov, and Xiaohua Zhai. With these moves, Meta MSL is clearly shaping itself into a major force in the artificial intelligence race.
These researchers also previously worked at Google DeepMind, bringing deep experience in advanced AI systems. With these new hires, Meta MSL is building a strong and focused team to support its long-term plans in AI development. The direction suggests that the company is not only hiring talent but also trying to reshape its internal research culture around cutting-edge innovation.
Meta is investing huge amounts of money to lead in AI, and this strategy links closely with the growth of Meta MSL. The company has invested $14.3 billion in Scale AI. It also offers high salaries and strong benefits to attract top AI talent.
Some reports say Mark Zuckerberg personally emailed AI researchers. He also invited them to his home to convince them to join Meta. These actions show how aggressively leadership supports Meta MSL.
However, not everyone agrees with Meta’s hiring strategy. In a recent podcast, Sam Altman, the CEO of OpenAI, said, “The degree to which they’re focusing on money and not the work and not the mission—I don’t think that’s going to set up a great culture.” He said Meta’s large salary offers to his employees are “crazy.” Such comments reflect the growing debate around how Meta MSL is assembling its talent pool.
Demis Hassabis also shared his thoughts on the topic in a podcast with Lex Fridman. In that discussion, he said, “Meta right now is not at the frontier, maybe they’ll manage to get back on there. It’s probably rational what they’re doing from their perspective because they’re behind and they need to do something.” His remarks highlight both skepticism and recognition of the urgency driving Meta MSL’s current strategy.
Overall, Meta MSL appears to be positioning itself as a serious contender in the global AI race, using aggressive hiring, heavy investment, and strategic leadership moves to catch up and possibly surpass its competitors in the future.
Meanwhile, a shortage of highly skilled AI researchers exists in the world. In this context, Naveen Rao compared the situation to finding a top basketball player. He explained, “It’s like looking for LeBron James.” Furthermore, he estimated that fewer than 1,000 people worldwide can build advanced AI models.
As a result, companies are trying different ways to attract AI talent. For instance, they offer stronger computing power and run AI hackathons. In one example, Aravind Srinivas said he tried to recruit a Meta researcher. However, the researcher told him to return when the company had “10,000 H100s,” referring to powerful AI training GPUs.
Overall, the AI talent war continues to intensify. In response, Meta is pushing strongly to gain an advantage. Notably, its Superintelligence Labs differs from its earlier AI division, FAIR. While FAIR continues research and development work, MSL focuses on building large-scale future AI models. Ultimately, these models aim to match or even surpass human intelligence.
