Alexandr Wang, Chief AI Officer at Meta and head of the newly launched Meta Superintelligence Labs (MSL), has outlined a bold recruitment strategy aimed at attracting top-tier AI talent. Speaking on the tech talk show TBPN, Wang asserted that Meta possesses all the essential ingredients to achieve superintelligence, emphasizing four pillars: massive computational resources, an elite talent pool, a strategically sized team, and an unwavering commitment to boldness. He stressed that Meta’s business model can sustain investments in compute infrastructure worth hundreds of billions of dollars, a claim backed by the company’s adjusted capital expenditure guidance—raising the lower end of its annual capex range to $66 billion, up from $64 billion, with the upper limit unchanged at $72 billion. This reflects Meta’s aggressive push to scale AI infrastructure amid fierce competition. Wang highlighted that MSL’s team, currently around 100 members, is intentionally small but exceptionally dense with talent. He emphasized that every member must be among the top tier of AI researchers across the industry, a standard designed to maximize innovation and efficiency. This approach aligns with Meta CEO Mark Zuckerberg’s belief that smaller, high-impact teams are better suited for breakthrough research. The team is structured into three core units: research, product development, and infrastructure—ensuring a seamless pipeline from discovery to deployment. Wang underscored that the lab’s ambition is not just to advance AI, but to scale superintelligence globally, making it accessible to every person on the planet. Meta’s recruitment drive has been nothing short of aggressive. In June, the company made headlines by offering $100 million in signing bonuses to secure key AI hires, underscoring the intensity of the talent war. The acquisition of a 49% stake in Scale AI for $14.3 billion further signaled Meta’s commitment to expanding its AI capabilities, with Wang’s recruitment being a central part of that strategy. However, in recent weeks, Meta has paused its hiring spree, citing internal organizational planning. The company described the hiring freeze in its AI division as a necessary step to solidify the structure of MSL after rapid onboarding and annual budgeting. According to the Wall Street Journal, the freeze also restricts internal team transfers, though the duration remains unclear. Industry observers view Meta’s approach as both ambitious and calculated. The focus on elite talent and computational scale positions Meta as a serious contender in the race toward superintelligence, particularly given its vast user base and infrastructure. However, the hiring freeze raises questions about long-term scalability and team cohesion. Still, Wang’s vision—combining technical ambition with strategic restraint—reflects a maturing AI strategy. Meta’s ability to balance rapid growth with structural discipline will be critical in determining whether its superintelligence ambitions become reality.