June 30 EST: Meta Platforms Inc. has launched its most ambitious AI initiative to date: a dedicated division aimed at artificial general intelligence (AGI) — and possibly superintelligence — under the newly formed Meta Superintelligence Labs (MSL).
The unit will be led by Alexandr Wang, the 28-year-old founder of Scale AI, following Meta’s $14.3 billion acquisition of a 49% stake in the startup, largely to bring Wang in-house. Nat Friedman, former GitHub CEO and respected figure in applied AI, will co-lead the group.
The goal: to build “personal superintelligence” — AI systems that can outperform humans in reasoning, planning, and perception — and plug them into Meta’s sprawling infrastructure of apps, smart glasses, and advertising engines. Internally, the initiative is described as nothing short of a moonshot.
One Vision, Two Leaders, Nine-Figure Offers
MSL formalizes a shift that has been building for months. Meta has been quietly assembling talent across the AI landscape, reportedly poaching researchers from OpenAI, DeepMind, Anthropic, and Google, with some compensation packages reportedly exceeding $100 million. Sources told Axios that CEO Mark Zuckerberg personally reached out to prospects through WhatsApp and in-person meetings.
Wang and Friedman now sit at the center of Meta’s AI universe, with teams relocated close to Zuckerberg’s own office. MSL will operate with near-autonomy, reflecting Zuckerberg’s increasing hands-on role in shaping Meta’s AI roadmap.
Why Now — and Why This Big
Meta’s internal models, including Llama 4, have failed to gain traction outside AI research circles. At the same time, Apple, Google, and OpenAI have raced ahead with tightly integrated AI experiences that make Meta’s own offerings feel secondary.
Meta’s prior moonshot — Reality Labs and the metaverse — has cost nearly $60 billion since 2020, with little to show in the short term. Investors are now watching whether this latest pivot delivers return or repeats past misfires.
The AGI push comes as Zuckerberg recalibrates his long-term product vision. If the metaverse was about where people go, this is about what powers it — and who owns the interface.
Cultural and Technical Risks
Not everyone inside Meta is sold. Yann LeCun, Meta’s own chief AI scientist, has publicly questioned whether current architectures can achieve anything close to AGI. Others within the company are wary of the talent war mentality — suggesting that throwing money at researchers is no substitute for organizational focus or technical clarity.
One insider told Wired the current recruitment blitz “feels more like a defensive reaction than a long-term strategy.”
Meta’s vision for AGI goes beyond research papers. The plan is to build models that run across products — from WhatsApp to Ray-Ban smart glasses — while tying directly into Meta’s ad-driven revenue streams. This isn’t about a chatbot. It’s about owning the next computation layer.
The AGI Arms Race
While Microsoft backs OpenAI and Google continues investing in DeepMind and Gemini, Meta’s new bet signals it no longer believes it can catch up from the outside. Instead, Zuckerberg is attempting to bring the frontier in-house — fast.
Whether that pays off depends on more than headcount. Meta will need to prove it can deliver breakthroughs while maintaining its privacy promises, product velocity, and cost discipline. Investors have already shown signs of fatigue with long-tail innovation.
For now, MSL is operational, heavily funded, and in Zuckerberg’s direct line of sight. The question isn’t whether Meta’s serious — it’s whether it’s right.
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A Wall Street veteran turned investigative journalist, Marcus brings over two decades of financial insight into boardrooms, IPOs, corporate chess games, and economic undercurrents. Known for asking uncomfortable questions in comfortable suits.
