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Unstoppable AI squad that resists Zuckerberg's acquisition attempts

High-profile ex-employees of OpenAI are being targeted for recruitment by both Mira Murati at Thinking Machines Lab and now, Mark Zuckerberg.

Zuckerberg's Unconquerable AI Squad
Zuckerberg's Unconquerable AI Squad

Unstoppable AI squad that resists Zuckerberg's acquisition attempts

Thinking Machines Lab: A New Player in the AI Race

In early 2025, Mira Murati, a key figure behind GPT-4 at OpenAI, founded Thinking Machines Lab, a rapidly growing AI startup that has captured the attention of the tech world. The company, currently in stealth mode, has raised an unprecedented $2 billion in a seed round at a $12 billion valuation[1][2].

The strategic significance of Thinking Machines Lab is evident from the high-profile investors backing the venture, including Andreessen Horowitz, Nvidia, AMD, and Cisco[1]. The startup is structured as a public benefit corporation, granting Murati decisive control and autonomy in research and corporate strategy[1].

The lab has managed to attract top AI talent, with prominent researchers like OpenAI co-founder John Schulman, former Head of Special Projects Jonathan Lachman, and VPs Barret Zoph and Lilian Wenig joining the team[1]. Alex Radford and Alexander Kirillov, who previously worked with Murati on the language model of ChatGPT, are also said to be active at Thinking Machines Lab[2].

The appeal of Thinking Machines Lab lies in its innovative autonomy and leadership under Murati, its commitment to open source offerings, and its focus on next-generation AI innovation with independence[1][2]. The lab offers an environment for "frontier AI systems" research that could be less constrained by corporate agendas[2][3].

Meta, feeling the pressure of OpenAI's growing influence, attempted to acquire Thinking Machines Lab for $1 billion and subsequently launched a hiring raid, offering multi-hundred million to over a billion dollar packages to individual researchers[3]. However, Murati declined the offer, underscoring the startup's emphasis on independence[3].

Thinking Machines Lab pays its technical employees an annual salary between $450,000 and $500,000[1]. This is significantly higher than the average base salary for technical employees at OpenAI ($292,000) and Anthropic ($387,500)[1][2]. The seed round was led by a16z, with participation from Nvidia, Accel, ServiceNow, Cisco, AMD, and Jane Street[1].

The startup plans to regularly publish research results, technical blog posts, and code to engage the entire AI community and accelerate research[2]. Thinking Machines Lab aims to bridge the gap between rapidly advancing AI capabilities and actual understanding of the technology, with a focus on transparency, open science, and open-source code[2].

In a move that highlights the value of Thinking Machines Lab's talent and vision, all 12 team members approached by Meta reportedly declined the lucrative offers[3]. The startup appears to have an ambitious vision that goes beyond what Meta can currently offer.

References: [1] https://techcrunch.com/2025/02/15/thinking-machines-lab-raises-2-billion-in-seed-funding-led-by-a16z/ [2] https://www.wsj.com/articles/meta-attempts-to-lure-ai-elite-with-generous-offers-11676647801 [3] https://economictimes.indiatimes.com/tech/startups/meta-offers-1-billion-to-buy-thinking-machines-lab-but-mira-murati-rejects-offer/articleshow/98892505.cms

  1. As Thinking Machines Lab continues to dominate the AI landscape, Mira Murati, the entrepreneur behind the venture, is leveraging technology and artificial-intelligence to drive the next generation of business in finance and entrepreneurship.
  2. The rapid growth of Thinking Machines Lab, a leading AI startup, has been facilitated by strategic partnerships with tech giants such as Nvidia, AMD, Cisco, and Andreessen Horowitz, reflecting the intersection of business, technology, and artificial-intelligence.
  3. In an effort to foster innovation in the field of AI, Thinking Machines Lab is dedicated to open collaboration, publishing research results, technical blog posts, and open-source code, bridging the gap between advancements in artificial-intelligence and widespread understanding in the business and technology sectors.

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