Mark Zuckerberg sends introductory mail on all the key employees hired for Meta Superintelligence Labs including one of the top-paid
CEO
Mark Zuckerberg
has now, after weeks of speculation, officially announced the creation of
Meta Superintelligence Labs
(MSL), a sweeping reorganization of the company's
artificial intelligence
efforts aimed at building "personal superintelligence for everyone." The new division will be led by former
Scale AI CEO Alexandr Wang
as chief AI officer, following Meta's $14.3 billion acquisition of his data-labeling startup.
"As the pace of AI progress accelerates, developing superintelligence is coming into sight,"
Zuckerberg
wrote in an internal memo obtained by CNBC. "I believe this will be the beginning of a new era for humanity, and I am fully committed to doing what it takes for Meta to lead the way."
Former GitHub CEO Nat Friedman will partner with Wang to co-lead MSL, focusing on AI products and applied research. Zuckerberg described Wang as "the most impressive founder of his generation" and praised his "clear sense of the historic importance of superintelligence."
The 11 key employees joining Meta's Superintelligence Labs
by Taboola
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The announcement comes alongside the hiring of 11 prominent AI researchers from competitors including OpenAI, Anthropic, and Google DeepMind. According to the memo, Meta has been actively recruiting talent as part of its aggressive push to compete with
OpenAI
and Google in the race for advanced AI systems.
Key new hires include:
Trapit Bansal - Developed reinforcement learning techniques for reasoning models and contributed to OpenAI's advanced o-series systems
Shuchao Bi - Led multimodal training efforts and developed voice capabilities for GPT-4o at OpenAI
Huiwen Chang - Architected image generation systems and created breakthrough text-to-image technologies at Google Research
Ji Lin - Contributed to multiple flagship models and reasoning architectures across OpenAI's product lineup
Joel Pobar - Specialized in AI inference optimization at Anthropic after extensive engineering experience at Meta
Jack Rae - Directed pre-training initiatives for Google's Gemini and led early large language model research at DeepMind
Hongyu Ren - Led post-training research groups and contributed to numerous breakthrough AI models at OpenAI
Johan Schalkwyk - Distinguished Google researcher who helped develop foundational speech and AI technologies
Pei Sun - Advanced reasoning and coding capabilities for Gemini while creating autonomous vehicle perception systems at Waymo
Jiahui Yu - Directed perception research teams and co-led multimodal AI development across OpenAI and Google
Shengjia Zhao - Spearheaded synthetic data initiatives and contributed to foundational conversational AI breakthroughs at OpenAI
Zuckerberg aims for AI frontier leadership with his Superintelligence team
"Meta is uniquely positioned to deliver superintelligence to the world," Zuckerberg said in the memo. "We have a strong business that supports building out significantly more compute than smaller labs. We have deeper experience building and growing products that reach billions of people."
"We're going to start research on our next generation of models to get to the frontier in the next year or so," Zuckerberg stated in the memo. The restructuring consolidates Meta's foundations, product, and FAIR teams under MSL, alongside a new lab focused on developing next-generation AI models.
Zuckerberg notes that the company's AI efforts will focus on building systems that are not only human-capable but "personal," deeply integrated into how people interact with technology.
The CEO emphasized Meta's structural advantages, writing: "Our company structure allows us to move with vastly greater conviction and boldness. I'm optimistic that this new influx of talent and parallel approach to model development will set us up to deliver on the promise of personal superintelligence for everyone."
Meta AI
currently serves more than 1 billion monthly active users across the company's platforms, powering what Zuckerberg described as "an increasing number of agents across Meta that help improve our products and technology."
He concluded the memo by stating: "We have even more great people at all levels joining this effort in the coming weeks, so stay tuned. I'm excited to dive in and get to work." Meta's aggressive AI expansion includes reported acquisition talks with Perplexity and Runway, plus an expected purchase of voice replication startup PlayAI.
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Shuchao Bi Background: Previously at OpenAI Education: Bachelor of Science (BS), Zhejiang University, China Doctor of Philosophy (PhD), University of California, Berkeley, USA Profile: Bi is a leader in multimodal AI, having co-developed the voice mode for GPT-4o and the o4-mini model. His expertise lies in integrating speech and text, enabling AI to understand and generate content across different formats. Bi's work has been crucial in advancing conversational AI and making digital assistants more natural and accessible. Huiwen Chang Background: Previously at Google Research Education: Bachelor of Science (BS), Tsinghua University, China Doctor of Philosophy (PhD), Princeton University, USA Profile: Chang is known for inventing the MaskIT and Muse architectures, which have become foundational in generative image models. She led the GPT-4o image generation team, driving innovations that allow AI to create high-quality, realistic images from text prompts. Her research bridges the gap between computer vision and creative AI applications. Ji Lin Background: Previously at OpenAI Education: Bachelor of Engineering (BEng), Tsinghua University, China Doctor of Philosophy (PhD), Massachusetts Institute of Technology (MIT), USA Profile: Lin has played a key role in optimizing and scaling large language models, including GPT-4o and the o4 family. His work focuses on model efficiency and image generation, making state-of-the-art AI more accessible and cost-effective for real-world deployment. Lin's contributions are highly regarded in both academia and industry. Joel Pobar Background: Previously at Anthropic & Meta Education: Bachelor of Information Technology (Honours), Queensland University of Technology (QUT), Australia Profile: Pobar is a veteran infrastructure specialist with over a decade of experience building scalable AI systems. He has contributed to major projects like HHVM, Hack, and PyTorch, which are widely used in the tech industry. Pobar's expertise ensures that AI models run efficiently at scale, supporting rapid innovation and deployment. Jack Rae Background: Previously at Google DeepMind Education: Bachelor of Science (BS), University of Bristol, UK Master of Science (MS), Carnegie Mellon University (CMU), USA Doctor of Philosophy (PhD), University College London (UCL), UK Profile: Rae is a leading figure in large-scale language model research, having led pre-training for Gemini 2.5 and developed Google's Gopher and Chinchilla models. His work has advanced the understanding of model scaling laws and data efficiency, shaping the next generation of AI systems. Hongyu Ren Background: Previously at OpenAI Education: Bachelor of Science (BS), Peking University, China Doctor of Philosophy (PhD), Stanford University, USA Profile: Ren has contributed to the development and post-training of GPT-4o and the o1/3/4o-mini models, focusing on improving robustness and reliability. His research addresses key challenges in making AI models safer and more trustworthy for widespread use. Johan Schalkwyk Background: Previously at Google Education: Bachelor of Science in Engineering (BS Meng), University of Pretoria, South Africa Profile: Schalkwyk is a Google Fellow and a pioneer in speech recognition, having led the Maya team and contributed to the early development of Google's Sesame project. His innovations have set industry standards in voice technology, powering products used by millions worldwide. 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Shengjia Zhao Background: Previously at OpenAI Education: Bachelor of Science (BS), Tsinghua University, China Doctor of Philosophy (PhD), Stanford University, USA Profile: Zhao is a co-creator of ChatGPT, GPT-4, and o4-mini, and has led research on data synthesis and AI safety. His work has had a direct impact on the reliability and ethical deployment of generative AI, making him a respected voice in the field. AI Masterclass for Students. Upskill Young Ones Today!– Join Now
