AI Researcher rejects $1.5 billion

The $1.5 Billion Job Offer That Was Turned Down — And What It Says About the Future of AI

What would you do if someone offered you $1.5 billion for a job? That’s billion with a B. Most people wouldn’t hesitate — they’d scream, call their parents, and accept before the other person even finished their sentence. After all, who turns down a fortune like that?

Well, someone just did. His name is Andrew Tul, an artificial intelligence researcher whose work is making waves in Silicon Valley. Recently, Tul was approached with an extraordinary offer from Meta CEO Mark Zuckerberg — a role that could have been worth up to $1.5 billion over six years.

Tul’s answer? “No, thank you.”

The decision has stunned the tech community. Why would anyone reject such a staggering deal? 

From OpenAI to a New Frontier

Our story begins with Mira Murati, the former Chief Technology Officer of OpenAI. Sam Altman, the CEO of OpenAI, was fired for a short time, and Murati took over.. This was a brief but widely noted post.

Last year, she left OpenAI entirely and in 2024 launched her own AI startup called Thinking Machines Lab. The company quickly drew attention for its secrecy and high-profile team members. One of those co-founders was Andrew Tul.

Meta Comes Knocking

A few months ago, Zuckerberg made an offer to Murati to buy Thinking Machines Lab.. Meta, which has been revamping its AI division, is aggressively recruiting top researchers to stay Competing against OpenAI, Google DeepMind, and Anthropic.

Murati refused to sell.

Undeterred, Meta then targeted Andrew Tul directly. That’s when the jaw-dropping $1.5 billion package came into play.

Breaking Down the Billion-Dollar Offer

There wasn't $1.5 billion in cash in a vault waiting for Tul to come along.. Instead, it was spread over six years — roughly $250 million annually — and made up of a mix of cash, stock options, and performance-based bonuses.

If Meta’s stock soared, Tul could potentially walk away with the full amount. But if it underperformed, he’d earn far less. Even so, just the guaranteed portion could have been in the nine-digit range — still enough to retire several times over.

Why Say No to That Kind of Money?

1. Mission Over Money

 AI researchers often see themselves as working on something transformative — the technological equivalent of the Manhattan Project. For Tul, the purpose of Thinking Machines Lab was more important than the promise of Meta's salary.. The startup is reportedly valued at $12 billion, with billions in investor funding. What they’re building remains a closely guarded secret, adding to the sense of purpose among the team.

2. Company Culture

 Startups like Thinking Machines and OpenAI are known for being flat-structured and collaborative, where even junior researchers have a say. Meta, by contrast, has been criticized for internal politics and hierarchical decision-making. For a researcher driven by curiosity and creative freedom, that shift could feel suffocating.

3. Recruitment Fatigue

 Zuckerberg’s interest in Tul wasn’t a one-off approach. Reports suggest Meta has been aggressively trying to poach multiple members from Thinking Machines, creating tension and making the offer feel more like a siege than an opportunity.

The AI Talent Shortage

This isn’t just a quirky anecdote about one person turning down an incredible sum. It’s a symptom of a much bigger trend: top-tier AI talent is scarce. Experts estimate that in Silicon Valley, there are only about 70 to 80 researchers at the very forefront of AI capabilities. Like professional sports, these people are being courted with multi-year contracts, signing bonuses, and even fan bases in the IT industry..

Déjà Vu in the Tech Industry

This talent frenzy isn’t unprecedented. During the early 2000s, network engineers held significant authority.. Now, the crown belongs to AI researchers — specifically those working on artificial general intelligence (AGI), systems that could think and learn as flexibly as humans.

Why AGI Changes Everything

The stakes in AI are higher than in any previous tech boom. Whoever builds AGI first could gain not just a competitive edge but geopolitical power. An AGI system could revolutionize industries, automate vast swaths of labor, and solve — or exacerbate — global challenges.

From that perspective, $1.5 billion for the right mind isn’t just reasonable — it could be a bargain.

The Risk Factor

But here’s the twist: AGI isn’t here yet. Most experts say we’re still years, if not a decade, away from anything resembling true general intelligence. AI businesses are now spending a lot of money with little to show for it right now.. The current phase is more about land-grabbing talent and technology than delivering sustainable business models.

The Human Element in the AI Race

It's simple to overlook that AI research is ultimately a human activity amid the overwhelming data.. People like Andrew Tul aren’t just equations in a spreadsheet — they have personal values, professional loyalties, and visions for the future.

Not everyone has a price, as demonstrated by Tul's choice to reject $1.5 billion. This fact is rarely mentioned in tech stories.

The Bottom Line

Tul’s rejection isn’t just a quirky news item — it’s a snapshot of the intense competition defining today’s AI landscape. As companies throw astronomical sums at a tiny pool of experts, the battle for AGI is becoming as much about culture, vision, and ethics as it is about money.

If AGI is ever achieved, history will likely remember the researchers who made it possible — not the size of their paychecks. And perhaps that’s the real prize in this race.