Star AI researcher departs $12B-valued startup he co-founded with former OpenAI CTO Mira Murati, citing “personal reasons”
Andrew Tulloch, co-founder of the highly anticipated AI startup Thinking Machines Lab, has left the company to join Meta Platforms, according to reports from The Wall Street Journal, marking a dramatic reversal for the researcher who famously rejected a $1.5 billion offer from Meta CEO Mark Zuckerberg just eight months ago.
AI researcher Andrew Tulloch reportedly announced his departure to employees in a message on Friday, bringing an abrupt end to his tenure at the startup he co-founded in early 2025 with Mira Murati, the former Chief Technology Officer of OpenAI.
A Thinking Machines Lab spokesperson confirmed Tulloch’s departure to the WSJ, saying he “has decided to pursue a different path for personal reasons,” though the move raises significant questions about the startup’s trajectory and the intense competition for top AI talent among tech giants.
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The $1.5 Billion Rejection: A Deal That Didn’t Stick
The move is particularly striking given that Tulloch turned down a reported $1.5 billion acquisition offer from Meta earlier this year when Thinking Machines Lab was still in its infancy, choosing instead to build his vision for reasoning-focused AI systems alongside Murati.
That rejection captured headlines globally as one of the most audacious decisions in the AI talent wars, with industry observers questioning whether any startup opportunity could truly be worth foregoing such a massive immediate payday.
The decision to now join Meta, reportedly in a standard employment capacity rather than through acquisition, suggests that circumstances or priorities shifted significantly for Tulloch over the intervening months, though specific details about his new role at Meta have not been disclosed.
Industry insiders speculate that the reversal may reflect challenges in building a competitive AI startup in 2025’s increasingly capital-intensive environment, where even well-funded startups struggle to match the computational resources and infrastructure available at tech giants.
Thinking Machines Lab: Rapid Rise, Uncertain Future
Thinking Machines Lab, founded in early 2025, had quickly gained traction for its focus on “thinking” AI systems that emphasize reasoning over raw data processing, positioning itself at the cutting edge of efforts to move beyond pattern-matching toward genuine machine reasoning.
The startup secured a stunning $12 billion valuation despite not yet launching a product, reflecting extraordinary investor confidence in the team’s pedigree and vision for next-generation AI systems that could surpass current large language model capabilities.
That valuation placed Thinking Machines Lab among the most valuable AI startups globally, competing with established players like Anthropic and Cohere despite having no commercial offerings or demonstrated technology beyond the reputations of its founding team.
With Tulloch’s exit, co-founder Mira Murati now faces the challenge of maintaining that momentum and investor confidence while navigating the loss of a key technical co-founder who brought deep expertise in machine learning optimization and systems.
Andrew Tulloch: From PyTorch to Thinking Machines
Andrew Tulloch’s career trajectory exemplifies the path of elite AI researchers moving between academia, tech giants, and startups in pursuit of breakthrough artificial intelligence capabilities.
An Australian computer scientist and machine learning expert, Tulloch previously worked at Meta (then Facebook) where he contributed to the development of PyTorch, the deep learning framework that has become industry standard alongside Google’s TensorFlow.
In 2023, he joined OpenAI to contribute to GPT-4’s development, working on the optimization and infrastructure challenges involved in training and deploying massive language models at scale.
His decision to leave OpenAI to co-found Thinking Machines Lab in early 2025 signaled ambitions to pursue AI research directions that might not align with OpenAI’s current product-focused trajectory under CEO Sam Altman.
The brief stint at Thinking Machines Lab—lasting less than a year—now appears to have been an exploratory detour rather than the long-term commitment that the $1.5 billion rejection suggested.
Mira Murati’s Leadership Challenge
Tulloch’s departure places significant pressure on Mira Murati, who left her position as OpenAI’s Chief Technology Officer to co-found Thinking Machines Lab amid reported tensions with Sam Altman over OpenAI’s increasingly commercial direction.
Murati’s departure from OpenAI had been characterized as a mission-driven decision to pursue more fundamental AI research focused on safety and reasoning capabilities rather than rapid product deployment and commercialization.
The loss of her technical co-founder just months into the venture raises questions about whether Thinking Machines Lab can maintain the technical leadership and execution capabilities that justified its extraordinary valuation and investor enthusiasm.
Industry observers will watch closely to see whether Murati brings in additional co-founders or technical leadership to fill the gap left by Tulloch’s departure, or whether this signals broader challenges for the young company.
Meta’s AI Talent Acquisition Strategy
For Meta, securing Tulloch represents a significant win in the increasingly fierce competition for elite AI researchers, though the circumstances of his hiring differ dramatically from the company’s initial $1.5 billion offer.
Meta has been aggressively building its AI capabilities under CEO Mark Zuckerberg’s directive to make artificial intelligence central to the company’s products and competitive positioning against rivals like Google, Microsoft, and Apple.
The company’s approach has combined internal development of large language models like Llama, strategic acquisitions of AI talent and startups, and massive infrastructure investments in the computational resources required for frontier AI research.
Tulloch’s expertise in optimization and systems will likely be deployed on challenges related to making Meta’s AI models more efficient, capable, and cost-effective as the company scales AI features across its platform portfolio.
The AI Talent Wars Intensify
Tulloch’s decision to join Meta after rejecting a $1.5 billion offer highlights the unprecedented intensity of competition for elite AI researchers, where companies are willing to offer extraordinary compensation packages and resources to secure expertise.
The AI talent market has become increasingly irrational from traditional employment perspectives, with top researchers commanding compensation packages that can exceed $1-2 million annually through combinations of base salary, equity, and retention bonuses.
Beyond pure compensation, researchers are evaluating opportunities based on access to computational resources, quality of collaborators, research freedom, and potential impact—factors where established tech giants often have advantages over even well-funded startups.
The talent dynamics are further complicated by philosophical differences about AI development approaches, with some researchers preferring the mission-driven cultures of startups and nonprofits while others seek the resources and scale only available at major technology companies.
Implications for the Startup Ecosystem
Tulloch’s departure from Thinking Machines Lab reflects broader challenges facing AI startups in 2025’s environment, where the capital and computational requirements for frontier AI research increasingly favor established technology giants.
While AI startups have attracted record venture capital funding, the gap between startup resources and big tech capabilities continues widening as training costs for cutting-edge models escalate and the importance of proprietary data and existing user bases becomes more apparent.
Several high-profile AI researchers who initially joined startups have subsequently moved to tech giants, suggesting that the startup path to AI breakthroughs may be more difficult than the wave of AI startup founding in 2023-2024 anticipated.
This pattern raises questions about whether the future of AI development will be dominated by a small number of tech giants with the resources to compete at the frontier, or whether innovative startups can find defensible niches and alternative approaches.
What’s Next for Thinking Machines Lab?
The company’s immediate challenge is maintaining credibility and momentum with investors, potential customers, and remaining team members following the departure of a high-profile co-founder.
Thinking Machines Lab has not publicly disclosed its technical roadmap or product plans, making it difficult to assess how significantly Tulloch’s departure impacts the company’s ability to execute on its vision.
The startup’s $12 billion valuation creates enormous pressure to demonstrate breakthrough technology and commercial viability, particularly now that questions about team stability have emerged.
Industry observers expect Thinking Machines Lab to make announcements in coming weeks about new technical leadership, product direction, or research achievements to reassure stakeholders that the company remains on track despite this high-profile departure.
Conclusion: The High-Stakes Game of AI Talent
Andrew Tulloch’s move from Thinking Machines Lab to Meta encapsulates the extraordinary fluidity and complexity of the current AI talent market, where even multi-billion-dollar commitments can prove temporary as researchers navigate rapidly evolving opportunities.
The reversal from rejecting a $1.5 billion offer to joining Meta as an employee suggests that the calculation of where to pursue AI research ambitions involves factors beyond pure financial considerations, including access to resources, clarity of technical direction, and personal circumstances.
For the AI industry, Tulloch’s trajectory illustrates how the concentration of talent at major technology companies continues even as startups attract record funding, potentially shaping the future development of artificial intelligence in ways that favor established platforms over innovative newcomers.
As the AI revolution accelerates, the movement of researchers like Tulloch between organizations will continue signaling where the most promising opportunities for breakthrough work are perceived to exist, making talent flows a key indicator of shifting competitive dynamics in the race to develop transformative AI capabilities.