In a bold and unprecedented move, Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, now seeks to raise over $2 billion in seed funding—a figure that would eclipse every known early-stage fundraising round in tech history. Investors across the globe have already begun circling the opportunity, signaling a high-stakes belief in what Murati and her all-star team plan to build.
At a time when AI innovation moves at breakneck speed, this potential mega-round does more than break records—it reshapes how the tech world values leadership, team pedigree, and the future of general-purpose AI systems.
Mira Murati’s Bold Return
Mira Murati didn’t walk away from OpenAI quietly. She left her position as CTO in early 2025, after spearheading critical developments behind ChatGPT and the GPT-5 architecture. She didn’t just help build OpenAI’s product roadmap—she defined it.
After exiting, Murati kept a low profile for just a few weeks. Then, news surfaced that she had quietly assembled a new team of elite AI engineers, many of whom had also exited OpenAI and Google DeepMind. This team didn’t intend to create another chatbot clone or productivity plugin—they aimed to push the envelope of autonomous AI systems, with a focus on multi-modal intelligence, autonomous agents, and emotional reasoning in machines.
Thinking Machines Lab: What’s the Mission?
Unlike OpenAI, which focuses heavily on safe deployment and commercial partnerships, Thinking Machines Lab appears laser-focused on pushing the frontiers of intelligence itself. In investor decks and internal documents reviewed by media sources, the company describes its mission as creating “truly autonomous thinking agents” that can interpret, reason, and act independently across digital and physical environments.
The lab has already begun developing an AI foundation model designed to learn continuously, respond contextually, and self-correct without strict human instruction. This approach diverges from current leading models, which rely on pre-trained data sets and require fine-tuning for new tasks.
Thinking Machines also promises to approach AI from a hardware-inclusive angle. Early reports suggest that the company is in talks with custom silicon manufacturers to build chips specifically optimized for their unique model architecture—indicating a vertically integrated strategy similar to Tesla’s AI ambitions.
Who’s On the Team?
Murati didn’t launch this startup alone. She handpicked a dozen engineers and researchers from OpenAI, Google DeepMind, and MIT’s Computer Science and AI Laboratory (CSAIL). Names like Raj Patel, who co-developed OpenAI’s safety alignment tools, and Li Xiaoyu, a former leader in Google’s Gemini project, bring instant credibility.
Investors always bet on the team—and in this case, they’re betting on one of the most experienced AI teams outside of the big three labs. One venture capitalist, speaking anonymously, said, “This team could walk into any Fortune 500 company and build its next-gen AI strategy in a week. They chose to go solo. That’s why everyone wants in.”
Why the $2 Billion Round Makes Sense
On paper, $2 billion might sound absurd for a company with no public product and a few months of runway. But this isn’t a typical seed round.
Here’s what drives investor interest:
- Talent density: Thinking Machines has already assembled a world-class team, making it an instant talent magnet.
- Compute needs: Building large language and multi-modal models requires immense compute resources. $2 billion gives them runway to train, iterate, and deploy at scale.
- First-mover edge: Murati and her team understand the weaknesses of current-gen models. They don’t want to compete—they want to leapfrog.
- Market timing: The AI arms race has begun, and investors know timing matters. The next trillion-dollar company might look like this.
Major VC firms like Sequoia Capital, a16z, and Lightspeed have reportedly expressed interest, with SoftBank and Saudi Arabia’s PIF also evaluating involvement. Industry insiders believe this round may close within 60 days—possibly even faster.
The Bigger Picture: What This Means for AI Startups
This kind of mega-seed funding sends a strong signal to the startup world: AI is no longer a feature; it’s the main event. Founders with the right experience and credibility can bypass traditional funding steps and go straight to multi-billion-dollar launches.
Just last year, AI startups raised seed rounds in the range of $5M–$100M. Today, Thinking Machines raises the bar—literally by orders of magnitude. Other founders may not match Murati’s credentials, but they will follow her roadmap: build deep expertise, gather top-tier talent, and aim for scale on day one.
Risks and Criticism
Despite all the hype, some experts urge caution. AI ethicists worry that such funding and speed could bypass safety guardrails. Critics fear that unchecked innovation, especially with general-purpose AI systems, could cause unintended consequences—especially when founders prioritize speed over oversight.
Meanwhile, traditionalists in the venture world question whether seed-stage companies should access this level of capital before proving product-market fit. One investor called it “a moonshot with blinders on.”
But Murati doesn’t seem interested in slow growth. Her team believes that the next leap in AI won’t come from tinkering—it will come from bold experiments, massive scale, and a relentless push toward cognitive autonomy.
What Comes Next?
Thinking Machines Lab has already started private beta testing for its first research model, nicknamed “TML-1”, with academic collaborators and internal AI agents. If this model delivers on its promise, it could lay the foundation for the startup’s first product launch by early 2026.
In the meantime, the team plans to open offices in San Francisco, London, and Tokyo—global tech hubs where they can tap into diverse talent pools and academic partnerships.
The company also plans to build its own AI research campus, fully equipped with dedicated compute clusters, robotics labs, and simulation chambers—indicating a long-term vision that transcends just software.
Final Thoughts
Thinking Machines Lab hasn’t even launched a public product, yet it already dominates the conversation in venture capital circles and AI innovation spaces. Mira Murati isn’t just starting a company—she’s igniting a movement among AI pioneers who believe in faster, deeper, and more autonomous systems.
Will they succeed? Only time will tell. But one thing is clear: they’re not playing small. They’re swinging for the fences—and if this $2 billion round closes, they might just hit it out of the park.