Former OpenAI CTO Mira Murati has announced the launch of Thinking Machines, a new AI research and product company.
With a mission to democratise access to AI and create systems that are both customisable and capable of working collaboratively with humans, the startup is setting ambitious goals to transform how AI integrates into everyday life and industry.
“We’re building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals,” the company explains.
Bridging gaps in the current AI landscape
Thinking Machines aims to address key gaps in the current AI landscape. While AI capabilities have advanced dramatically, there remain significant challenges in making these technologies accessible and practical for widespread use.
Currently, knowledge about cutting-edge AI systems is concentrated among a select few research labs, which limits public understanding and hinders broader innovation. The company highlights that systems today are also challenging to customise for individual needs and values, a critical hurdle for real-world adoption.
Thinking Machines sees the solution in creating AI systems that are more widely understood, customisable, and capable. The company plans to combine intellectual openness, advanced infrastructure, and innovative AI safety practices to empower both researchers and end-users.
Murati’s team brings formidable expertise to this mission, comprising scientists, engineers, and technologists responsible for creating some of the most widely used AI tools, such as OpenAI’s ChatGPT, Character.ai, and open-source frameworks like PyTorch and OpenAI Gym.
A human-centric approach to AI
A key cornerstone of the company’s philosophy is collaboration. Thinking Machines intends to maintain a culture of openness by sharing research papers, technical blog posts, and code with the wider AI community.
“Scientific progress is a collective effort,” the company states. “We believe that we’ll most effectively advance humanity’s understanding of AI by collaborating with the wider community of researchers and builders.”
This open research ethos reflects a broader trend in the AI sector, where transparency and community engagement are increasingly seen as drivers of not just innovation, but also societal trust in AI technologies.
Unlike many organisations focused purely on creating autonomous AI, Thinking Machines is also putting a strong emphasis on human-AI collaboration.
Multimodal systems – AI capable of working with a combination of formats like text, video, and imagery – are central to this human-centric vision. These systems are designed to interact seamlessly with people, helping users leverage AI to achieve specific goals and solve meaningful problems.
The focus on personalisation also sets Thinking Machines apart. The team envisions AI systems that go beyond narrow-use cases, enabling diverse applications across fields ranging from scientific research to engineering and creative work.
The company is particularly interested in creating AI tools that adapt to individual expertise and situations, allowing users to “make AI work for their unique needs and goals.”
Thinking Machines will prioritise strong foundations
While many AI startups are rushing to deploy systems, Thinking Machines is aiming to get the foundations right. This rests on two major pillars: model intelligence and high-quality infrastructure.
Murati’s team is building frontier AI models capable of pushing the boundaries of fields like programming and scientific discovery. These advanced technologies could enable revolutionary applications, from uncovering new scientific insights to achieving engineering breakthroughs.
Equally, the company is committed to designing efficient, secure, and user-friendly infrastructure to drive productivity and support the next generation of AI systems.
Rather than opting for shortcuts, Thinking Machines is taking a patient, methodical approach to maximise long-term impact.
Advanced multimodal capabilities are another area of focus. By integrating modalities like language, imagery, and sensory data, the company aims to build systems capable of richer communication and deeper real-world integration.
Ethical AI through product-driven learning
Thinking Machines also plans to intertwine research and product design, an approach that not only informs innovation but also ensures relevance and usability.
Products will drive iterative learning, enabling the team to gain insights from real-world deployment. Meanwhile, real-world testing will further solidify the company’s commitment to AI safety, blending proactive research with rigorous post-deployment monitoring.
Murati’s team outlines three key principles for advancing AI safety:
- Maintaining a high safety bar to prevent misuse while preserving user freedoms.
- Sharing best practices with the industry for building secure AI systems.
- Accelerating external research on AI alignment by providing access to code, datasets, and model specifications.
The team also recognises that the most meaningful breakthroughs often come from “rethinking our objectives, not just optimising existing metrics.”
By measuring real-world value, Thinking Machines hopes to create AI systems that truly benefit society across a wider array of use cases.
Thinking Machines: A fresh AI startup, guided by experience
The launch of Thinking Machines signifies the next chapter for Mira Murati, who played a crucial role in leading some of OpenAI’s most successful projects.
Murati’s wealth of experience, alongside a team of world-class AI creators, puts the new venture on solid footing to make a significant impact on the sector. By affirming a commitment to openness, collaboration, and long-term thinking, the startup may provide an antidote to common criticisms of the fast-moving AI world, from opacity to ethical risks.
The mission is clear: to empower people in every industry to harness AI’s transformative potential—on their terms.
(Photo by Nejc Soklič)
See also: Grok 3: The next-gen ‘truth-seeking’ AI model
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