Mark Zuckerberg has a history of restructuring the entire industry and making bold bets to beautifully lose when not exposed. After burning US$46 billion in Metaverse, Meta’s CEO is doubling with an even more ambitious bet: Superintelligence AI.
However, this time there is a high stake, the competition is more intense, and the potential rewards are more transformative than what Meta has previously attempted.
Even with the 9-figure reward package and investment in infrastructure that blows up Metaverse spending, Zuckerberg’s Superintelligence AI Gamble represents the war of Silicon Valley’s most expensive talent.
The birth of Meta Superintelligence Labs
The formation of Meta Superintelligence Labs shows a shift for the social media giant. In an exclusive interview with information“The most exciting thing this year is that we are beginning to show early glimpses of self-improvement with models,” Zuckerberg told founder Jessica Lessin in TITV’s live streaming program.
This vision has driven the company to rebuild its entire AI division, with an ambitious goal of providing what Zuckerberg calls “personal superintelligence to everyone in the world.” The creation of the lab follows a period of internal struggles in Meta’s AI division, including management struggles, employee terminations and flattened product releases.
Rather than gradually improving existing systems, Zuckerberg chose to go through a complete overhaul, bringing external leadership and rethinking the company’s approach to AI development.
Have we witnessed the most expensive war on talent in technology history?
At the heart of Meta’s Superintelligence AI Ambitions is the talent acquisition strategy that sent shockwaves through the industry. Zuckerberg set out on the existence of spending to create a new lab that offers nine-figure pay packages to hire top researchers from companies such as Openai, Google, Apple, and Anthropic.
when Information Lessin questioned the report on the US$108 million compensation package, Zuckerberg said “many of the reported details are not accurate in and of itself.” But it’s a very hot market.
Meta AI’s talent acquisition strategy goes beyond financial incentives. Zuckerberg said, “Essentially, doing the most calculations per researcher is a strategic advantage not only to do the job, but also to attract the best people.” This approach reflects the understanding that talent density is more important than team size in a super-intelligence AI race.
Alexandr Wang Acquisition: US$14.3 billion gambling
The heart of Meta’s talent strategy was gaining scale AI leadership. In June, the company invested US$14.3 billion in AI startups, which was founded and led by Wang. Under the agreement, Meta acquired a 49% stake in the company, with One and top-scale employee teams joining Meta in leadership roles.
At just 28 years old, Alexandre Wang is now the Chief AI Board of Meta, leading the company’s renamed “Meta Super Intelligence Lab.” In the large AI division, Wang leads a team of about 12 newly hired researchers, a small number of agents for scale AI, and former CEO of Github, Nat Friedman.
We integrated Wang’s team as a reimagining how Meta approaches AI development. The group has worked in silent office spaces from the rest of the company next to Zuckerberg, highlighting the importance imposed on the initiative.
Philosophical Shift: From Open Source to Closed Development
Perhaps the most important development born out of Meta Superintelligence Labs is the potential abandonment of the company’s long-standing open source philosophy. Last week, a small group of top lab members, including Wang, discussed abandoning the company’s most powerful open source AI model called Behemoth in support of the development of a closed model.
This represents a departure from the historical approach of meta. For years, Meta has chosen to open source AI models and publishes code that other developers can build. Meta executives argue that technology should be publicly available, as AI development will move faster and more developers can access it.
This shift reflects concerns about competitive positioning in AI races. Meta has stopped supplying data to its Behemoth model (training), but is delaying its release due to poor internal performance. The set-off prompted a serious rethinking of the company’s approach.
Infrastructure as a competitive advantage
Beyond talent acquisition, Meta is making infrastructure investments to support its close ambitions. Zuckerberg has revealed that the company is a pioneer in new construction methods, including “constructing multiple multi-gigawatt data centers” and “weatherproof tents” to accelerate deployment.
The scale of these investments is incredible. Hyperion, one of Meta’s new data centers, said “we will expand up to 5 gigawatts in the coming years,” and “the site size covers a significant portion of Manhattan’s footprint in terms of space.”
Infrastructure spending is possible due to the strong financial position of Meta, and Zuckerberg says that “basically this can be funded all of the company’s cash flow.”
Personal Super Intelligence Vision
What distinguishes meta’s approach from its competitors is to focus on “personal tensions” rather than centralized AI systems. During an interview with Information Lesson, Zuckerberg explained that while other labs focus on “wanting to automate all of the economically productive work of society,” Meta’s vision is “what people care about in their lives… relationships and creativity, and fun and fun.”
The vision extends to Meta’s hardware ambitions, particularly its AR glasses initiative. In an interview with the same TITV, Zuckerberg predicted that “if you don’t have AI glasses, you’re at a cognitive disadvantage,” explaining a future scenario where your AI peers can “observe what’s going on in your life and follow up for you.”
Industry impact and competitive dynamics
Meta’s Superintelligence Push meaning extends beyond the company. META’s AI talent acquisition strategy creates pay inflation in the industry, forcing competitors to fit or exceed meta pay levels to retain researchers.
When asked about his interactions with his competitors in Sun Valley, Zuckerberg acknowledged the competitive landscape, saying, “We’re not trying to target any of the top researchers in the industry. We want to know all of the industry’s top researchers.”
The diplomatic approach fundamentally hides what is zero-sum competition for a finite pool of top-notch ultra-intelligence AI talent. The potential shift from open source development indicates a broader industry trend towards a more unique approach to AI development.
Conclusion: The crucial moment of meta
Meta’s Superintelligence initiative represents a reimagining of the company’s future. After a costly metaverse experiment failed to produce results, Zuckerberg has placed an even bigger bet on AI, allowing for investments of over USD 100 million in the future.
The success or failure of Meta Superintelligence Labs could determine not only the future of the company, but also the trajectory of the broader AI industry. The stakes are high as some employees expect “Exodus of AI talents who are not chosen to join Wang’s Superintelligence team.”
It remains to be seen that Zuckerberg is assuming whether META’s AI talent acquisition campaign will create groundbreaking technology. What’s certain is that Silicon Valley’s most expensive war on talent has begun.
See: Apple loses important AI leaders to Meta
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