Company’s ambitious push into artificial general intelligence faces early turbulence as key researchers defect to rivals

Meta’s ambitious pursuit of artificial intelligence supremacy is facing early challenges as at least eight employees—including researchers, engineers, and a senior product leader—have departed less than two months after CEO Mark Zuckerberg announced the launch of the new Meta Superintelligence Labs (MSL).

The departures, which include both veteran Meta AI infrastructure builders and recent high-profile hires, represent a significant setback for the social media giant’s most expensive AI bet yet: a $14.3 billion investment in Scale AI that brought 28-year-old founder Alexandr Wang to Meta as chief AI officer.

The Exodus Begins

Recent departures include Avi Verma, Ethan Knight, and Rishabh Agarwal, with Verma and Knight returning to OpenAI where they previously worked. Knight had originally joined Meta from Elon Musk’s xAI before departing again.

The most notable exit came from Chaya Nayak, the director of generative AI product management at Meta, who worked at Meta for nearly a decade and is leaving the company to join OpenAI to work on special initiatives. Her departure signals that even longtime Meta veterans are questioning the company’s AI direction.

Rishabh Agarwal’s departure message on social media captured the sentiment of many leaving researchers: “It was a tough decision not to continue with the new Superintelligence TBD lab, especially given the talent and compute density. But after 7.5 years across Google Brain, DeepMind, and Meta, I felt the pull to take on a different kind of risk”.

The Scale AI Gamble

Meta’s AI troubles stem partly from the disappointing reception of its latest Llama 4 model. Following Llama 4’s lackluster debut, Meta conducted a reorganization of its GenAI unit, leading Zuckerberg to make his biggest AI bet: securing Scale AI’s Wang to lead Meta’s superintelligence efforts.

The deal values Scale AI at $29 billion, with Meta taking a 49% stake for approximately $14.3 billion—the company’s second-largest investment ever, trailing only its $19 billion WhatsApp acquisition. Wang, who dropped out of MIT to co-found Scale AI, now leads Meta’s newly restructured AI division alongside former GitHub CEO Nat Friedman.

The choice of Wang represents a strategic shift. Wang hasn’t led an AI lab of this sort before, however, and he doesn’t have the same AI research background that many other AI lab leaders do, like Safe Superintelligence’s Ilya Sutskever or Mistral’s Arthur Mensch. Instead, he brings business acumen and infrastructure expertise from building Scale AI into a critical data provider for major AI systems.

Organizational Upheaval

Meta is splitting its newly formed artificial intelligence group into four distinct teams and reassigning many of the company’s existing AI employees under the Meta Superintelligence Labs umbrella:

  • TBD Labs - Led by Wang, focused on training Meta’s largest models including the mysterious “Omnimodel”
  • Fair - Meta’s original research lab founded by Yann LeCun, now funneling breakthroughs to TBD
  • Products & Applied Research - Led by Nat Friedman, embedding AI into Meta’s products
  • MSL Infra - Led by Aparna Ramani, handling massive compute infrastructure

The restructuring consolidates power under Wang, with even AI heavyweights like LeCun now reporting through the new hierarchy.

Hiring Freeze Amid Talent Wars

Meta Platforms has paused hiring for its AI division, ending a spending spree that saw the company acquire a wave of high-priced AI researchers and engineers. The freeze, which went into effect last week, represents a dramatic shift from the company’s aggressive recruitment campaign.

The hiring freeze follows weeks of poaching more than 50 AI researchers and engineers from competitors, with Meta reportedly offering compensation packages worth hundreds of millions of dollars to secure top talent.

The aggressive hiring strategy has created internal tensions. The influx of highly paid new hires has fueled tensions, particularly among longtime employees who were at Meta before the superintelligence initiative began.

The Broader AI Arms Race

Meta’s struggles reflect the intense competition in artificial intelligence. The talent churn at Meta mirrors wider patterns in the AI sector. OpenAI itself has seen significant departures, including safety researchers like Ilya Sutskever and Jan Leike.

The company faces pressure to catch up with rivals who appear further ahead in both foundational models and consumer applications. Despite seemingly unlimited resources, Meta has been falling behind foundation labs in model performance, struggling to match the impact of ChatGPT or compete with Google’s AI integration.

Meta’s approach differs from pure AI companies in that it follows what analysts call an “AI Incrementalism” strategy, enhancing existing products rather than pursuing revolutionary breakthroughs. However, when measuring GenAI consumer app traction, Meta and Google meaningfully lag ChatGPT in its reach and engagement.

What This Means for Meta’s Future

The early turbulence at Superintelligence Labs raises questions about Meta’s ability to execute its ambitious AI vision. The company plans to spend up to $65 billion on AI infrastructure this year alone, building massive data centers to train increasingly powerful models.

Despite the setbacks, Meta’s consolidation strategy could pay off. Rather than having AI research scattered across different teams, the new structure puts all efforts under unified leadership with a clear mission: achieving superintelligence before competitors.

The success of Wang’s leadership will be crucial. As one former Scale AI manager noted: “Alex is a great recruiter, a really savvy commercial person. Who knows if it’ll work out? Maybe he builds a better AI team into something Herculean, maybe not, but you’re gonna bet on someone to do it”.

The Road Ahead

Meta says it will share more details about the new organization and additional hires in the coming weeks, suggesting the restructuring is just the beginning of major changes ahead. However, the company faces significant challenges in retaining talent and delivering on its superintelligence promises.

The departures serve as a cautionary tale in Silicon Valley’s AI gold rush. In an industry where talent is the ultimate currency, Meta’s ability to stabilize its Superintelligence Labs and deliver breakthrough AI capabilities will determine whether Zuckerberg’s $14 billion bet pays off or becomes another cautionary tale of AI hype outpacing execution.

For now, the exodus continues, with competitors like OpenAI happy to welcome back their former researchers. As the AI arms race intensifies, Meta must quickly prove that its massive investments in talent and infrastructure can translate into the superintelligent systems it promises to build.

This article incorporates reporting from Business Insider, Wired, CNBC, Bloomberg, and other industry sources.