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Ever since Mira Murati departed OpenAI last fall , many have wondered about the former CTO’s next move. Well, now we know (or at least have a rough idea).
Murati took to X today to announce her new venture Thinking Machines Lab , an AI research and product company with a goal to “advance AI by making it broadly useful and understandable through solid foundations, open science and practical applications.”
Murati posted: “We’re building three things: Helping people adapt AI systems to work for their specific needs; Developing strong foundations to build more capable AI systems; Fostering a culture of open science that helps the whole field understand and improve these systems.” Thinking Machinea’ team of roughly two dozen engineers and scientists is stacked with other OpenAI alums — including cofounder and deep reinforcement learning pioneer John Schulman and ChatGPT co-creator Barret Zoph — which could position the startup to make significant strides in AI research and development.
As of the posting of this article, the company’s newly-launched X account @thinkymachines had already amassed roughly 14,000 followers. Model intelligence, multimodality, strong infrastructure
Thinking Machines — not to be mistaken with the now defunct supercomputer and AI firm of the 1980s — isn’t yet offering specific examples of intended projects, but suggests a broad focus on multimodal capabilities, human-AI collaboration (as opposed to purely agentic systems) and strong infrastructure. The goal is to build more “flexible, adaptable and personalized AI systems,” the company writes on its new website .
Multimodality is “critical” to the future of AI, Thinking Machines says, as it allows for more natural and efficient communication that captures intent and supports deeper integration. “Instead of focusing solely on making fully autonomous AI systems, we are excited to build multimodal systems that work with people collaboratively,” the company writes.
Going forward, the startup will build models “at the frontier of capabilities” in areas including science and programming. Model intelligence will be key, as will infrastructure quality. “We aim to build things correctly […]
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