Former OpenAI chief technology officer – and briefly interim CEO – Mira Murati has vaulted back into the spotlight, announcing that her new venture, Thinking Machines Lab, has closed a stunning $2 billion funding round only five months after launch.
The deal, one of the largest first round financings ever raised by a technology start up, places an early valuation of roughly $12 billion on a company that has yet to ship a product.
Andreessen Horowitz led the round, joined by a marquee roster of strategic investors that include Nvidia, AMD, Accel, ServiceNow, Cisco, and trading powerhouse Jane Street. The combination of deep pocketed venture capital and top tier chip makers gives Murati both the cash and the compute supply she will need to compete in an increasingly GPU constrained market.
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Murati left OpenAI last September after helping steer the organization through its most turbulent period, including Sam Altman’s brief ouster and reinstatement. She incorporated Thinking Machines in February, quietly hiring dozens of ex OpenAI and Google researchers. Nearly two thirds of the fledgling team are said to be alumni of frontier model projects such as GPT 4, Gemini, and Llama.
In her first public post since February, Murati framed the start up’s mission as building “multimodal, collaborative general intelligence” that interacts with users through speech, vision, and shared context. The technology, she insisted, should “serve as an extension of individual agency” and be distributed as widely and equitably as possible.
To underscore that philosophy, Thinking Machines’ first product, scheduled to debut within the next couple of months, will include a significant open-source component. Murati also pledged to publish the lab’s “best science” so external researchers can study the safety and capabilities of its forthcoming models.
The funding round highlights the breakneck pace – and shifting norms – of AI investing. U.S. startups have already raised more than $160 billion in the first half of 2025, with roughly two thirds of the total flowing into artificial intelligence companies. Venture firms now routinely back pre revenue, pre product ventures at multibillion dollar valuations if those companies can demonstrate star talent and a credible plan to secure hardware.
Investors say Murati’s track record at OpenAI – where she oversaw the launch of ChatGPT, DALL E, and key safety initiatives – makes Thinking Machines a blue-chip wager despite its early stage. For Nvidia and AMD, both desperate to lock in next generation AI customers, the stake offers guaranteed demand for their newest accelerators. The alliance also ensures Murati a reliable GPU pipeline at a time when supply constraints are beginning to slow some competitors.
Thinking Machines joins a growing club of AI labs founded by former OpenAI executives. Anthropic, co run by another OpenAI veteran, recently raised a similar war chest and has positioned itself as a safety-first alternative to its former parent. Ilya Sutskever’s Safe Superintelligence, launched in June, has adopted an ultra-stealth approach focused exclusively on research. With such well-resourced players vying for talent and hardware, the battle for artificial general intelligence mindshare is intensifying.
Murati’s strategy is to differentiate between openness and user agency. Where OpenAI and Anthropic have moved toward more guarded release cycles, Thinking Machines is promising a hybrid model: proprietary systems that can be integrated into commercial applications, and parallel open-source releases aimed at academics and smaller startups. If successful, the approach could help defuse mounting criticism that frontier model research is consolidating into a handful of opaque, privately controlled silos.
For now, the spotlight shifts to the company’s forthcoming debut product, which Murati says will showcase multimodal reasoning and conversational abilities aligned with how people naturally interact. If the software delivers on its promise – and if Thinking Machines can scale safely – Murati’s return may prove to be one of the most consequential second acts in the short but explosive history of generative AI.