The tech giant has just recruited Ruoming Pang, Apple’s former head of AI and leader of its Foundation Models team, to play a major role in shaping Meta’s next big bet: Superintelligence Labs. With his background in developing scalable AI systems at Apple, Pang brings serious firepower to Meta’s renewed push to compete head-to-head with OpenAI, Google DeepMind, and Anthropic.
But Pang isn’t joining alone. Meta has also onboarded Alexandr Wang (ex-CEO of Scale AI) as Chief AI Officer and tapped former GitHub CEO Nat Friedman to help integrate cutting-edge AI into consumer-facing products. Together, they form an all-star lineup—and they’re stepping into a lab that’s now become central to Meta’s AGI (artificial general intelligence) ambitions.
So why the hiring spree now?
Earlier this year, Meta’s Llama 4 model—despite its open-source ethos—didn’t quite move the needle the way company leadership had hoped. It was technically impressive but failed to capture the excitement of LLM fans and researchers alike. And with several senior scientists exiting the company, Meta found itself scrambling to reset both its roadmap and its recruiting game.
Their approach? Big money. Reports say Meta dangled compensation packages worth up to $100 million in front of top OpenAI researchers. But no one bit.
The reason: in today’s AI landscape, money isn’t the only motivator. Engineers and researchers are increasingly drawn to environments like Anthropic and DeepMind, where mission-driven cultures and a sense of purpose—not just prestige or paychecks—guide the work.
So while Meta’s wallet is still one of the deepest in the business, its influence is no longer a given. That said, the company is adapting. Rather than just chase OpenAI staff, Meta is looking wider—pulling in brilliant minds from across tech who might be ready to help reimagine what AI can do, with fewer guardrails and bigger ambitions.
Superintelligence Labs is now the testing ground for that strategy. With leaders like Pang, Gross (formerly of Safe Superintelligence), and Wang at the helm, Meta’s betting that scale, speed, and access to billions of users will give it the edge.
Whether that gamble pays off depends on more than just model performance. In the race toward AGI, the culture that shapes the research might matter as much as the research itself. Meta’s next chapter in AI is still being written—but with these moves, the pen is definitely back in its hand.
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