In an era where billion-dollar valuations and nine-figure compensation packages have become the new arms race in artificial intelligence, one story out of Silicon Valley has taken even hardened tech veterans by surprise: Meta META -1.50% ▼ CEO Mark Zuckerberg reportedly offered more than $1 billion to a single AI expert — and was turned down.
According to Wired, which broke the story, Meta has been relentlessly courting AI scientists from Thinking Machines Lab (TML), an elite AI startup co-founded by former OpenAI CTO Mira Murati. In its most brazen effort yet, Meta allegedly floated an eye-watering $1 billion compensation package to a single individual — a sum to be paid over several years. The response? A polite but firm “No, thanks.”
Zuckerberg, it seems, is pulling every lever possible to accelerate the buildout of his new AI division — Meta’s Superintelligence Labs — in a frantic attempt to catch up with rivals like OpenAI, Google DeepMind, and Anthropic. But the refusal by TML’s team — not one of whom accepted any offer — paints a telling portrait of the current AI climate: money isn’t everything, even when the checks have nine zeros.
Meta’s effort to poach elite AI talent stems from its broader push into developing what Zuckerberg has dubbed “personal superintelligence.” The company is racing to become a leader in AGI (Artificial General Intelligence), launching its Superintelligence Lab earlier this year with splashy announcements and big names.
According to Wired and confirmed by Meta spokesperson Andy Stone, the company made several offers to Thinking Machines Lab employees. Stone disputed the $1 billion figure but did not deny the aggressive recruitment campaign. In addition to hefty salaries, insiders say Meta dangled enormous equity grants and bonuses — some of the most lavish offers ever made in the tech world.
The company is “putting its chips on the table,” according to The New York Budgets, pumping billions of dollars into computing infrastructure, AI models, and research teams in hopes of catching up to more advanced competitors.
In one leaked message obtained by Wired, Zuckerberg personally wrote to a recruit:
“We’ve been following your work on advancing technology and the benefits of AI for everyone over the years. We’re making some important investments across research, products and our infrastructure in order to build the most valuable AI products and services for people.”
But the recipients of those messages — and the money — have largely said no.
Why They Turned It Down
Despite Meta’s immense offers, Thinking Machines Lab employees have remained loyal — a rare move in an industry where “exit packages” and stock grants often win over even the most mission-driven minds.
Multiple factors explain the mass refusal.
1. Leadership Concerns
Sources told Wired that many TML scientists are skeptical of Meta’s newly appointed AI leaders — most notably Alexandr Wang, the 28-year-old founder of Scale AI, who was brought in to help lead Superintelligence Labs.
Wang’s leadership style was described as “questionably experienced” for a project of such scale, and insiders were worried that his “move fast” startup mentality could clash with the rigorous demands of cutting-edge AI research.
2. Meta’s PR & Trust Problem
Meta’s recent stumbles — including the botched rollout of its LLaMA 4 language model — have damaged its reputation among AI researchers.
According to The Verge, Meta allegedly manipulated benchmark scores for its AI model to appear more competitive than it actually was. That undermined confidence in the company’s transparency and scientific rigor — values deeply held within AI research communities.
3. TML’s Own Success
Thinking Machines Lab is no underdog. In just 12 months, the company has raised the largest private AI funding round in history, reaching a $12 billion valuation. With ample capital, it can afford to pay its top talent generously and stay competitive without losing its soul to a corporate behemoth.
A Broader Bubble?
Zuckerberg’s billion-dollar offer is more than a headline — it’s a signal of what some analysts fear is becoming a bubble in AI.
In interviews with The Wall Street Journal, venture capitalists and economists warn that the current investment frenzy feels eerily reminiscent of the dot-com bubble of the late ’90s. Companies are making enormous bets on models and infrastructure that are still far from producing significant revenue — or, in many cases, even working reliably.
Meta’s desperation to hire top-tier talent reflects a fear of missing out on what may be the defining technological revolution of the century. But this gold rush mentality also suggests some companies — Meta chief among them — may be sacrificing long-term stability for short-term wins.
Is Zuckerberg Losing His Touch?
The optics of Zuckerberg — one of the richest and most powerful men in tech — offering a billion dollars to a startup employee only to be turned down may raise questions about his current influence and Meta’s direction.
Once a juggernaut that could acquire or hire anyone it wanted, Meta is now struggling to retain trust, especially in areas as ethically and philosophically charged as artificial intelligence. Some in the AI world still associate Meta with surveillance capitalism, political controversy, and internal leaks that have revealed a troubling culture of “build first, ask later.”
The Power Has Shifted
The incident with Thinking Machines Lab reflects a larger truth: the power dynamic has flipped. Top AI researchers are now the prize — and they are choosing where to go, who to trust, and how they want to contribute to the future of intelligence.
One former OpenAI engineer, speaking anonymously to TechCrunch, said:
“We don’t want to just build smarter systems. We want to build responsibly, with values. And that means saying no — even to a billion dollars.”
Zuckerberg may yet succeed in staffing up his Superintelligence Lab. But this high-profile rejection shows that even unlimited funds can’t buy loyalty — or vision.
And for once, Silicon Valley is learning that a bigger check doesn’t always get the yes.
