TL;DR
Thinking Machines, led by Mira Murati, announced development of ‘interaction models’ that allow AI to respond in real time across audio, video, and text. The company plans a limited research preview soon, aiming for a wider release later this year.
Thinking Machines, the AI company founded by Mira Murati, announced on May 11, 2026, that it is developing ‘interaction models’ designed to enable real-time, multi-modal AI responses, marking a major advancement in human-AI collaboration.
The company describes these ‘interaction models’ as systems that can process and respond to audio, video, and text inputs simultaneously, allowing for more natural and continuous interaction with users. Unlike current models that wait for user input to finish before responding, these new models aim to interpret ongoing inputs and respond dynamically, reducing the communication bottleneck.
Thinking Machines provided examples such as real-time translation, listening for specific mentions in conversations, and providing immediate feedback like alerting users when they are slouching. The firm plans to launch a ‘limited research preview’ in the coming months, with a broader release targeted later this year.
Mira Murati, who founded Thinking Machines in February 2025 after leaving OpenAI, emphasized the goal of making AI more interactive and human-like, stating that current models experience a narrow channel of communication that limits effective collaboration. The new models aim to bridge this gap by enabling AI to perceive and respond continuously across different modalities.
Why It Matters
This development is significant because it addresses a fundamental limitation of current AI systems, which often operate in a one-way, turn-based manner. Real-time, multi-modal interaction could revolutionize applications ranging from customer service to creative collaboration, making AI more intuitive and effective in everyday use. For industry and users alike, this could lead to more seamless human-AI partnerships, potentially transforming how we work and communicate with machines.
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Background
Mira Murati’s departure from OpenAI in early 2025 was notable, and her new venture, Thinking Machines, has attracted attention for its ambitious focus on interactive AI. The company’s emphasis on real-time, multi-modal models represents a shift from traditional AI that relies on static inputs and delayed responses. The announcement comes amid broader industry efforts to enhance AI responsiveness and contextual understanding, with competitors also exploring real-time interaction capabilities.
“Our interaction models will enable AI to collaborate with humans in a way that feels natural and immediate, breaking through the bandwidth bottleneck of current systems.”
— Mira Murati, CEO of Thinking Machines
“We believe this technology will transform how humans and AI work together, making interactions more intuitive and responsive across any modality.”
— Thinking Machines spokesperson
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What Remains Unclear
It is not yet clear when the limited research preview will be available or what specific applications it will initially support. Details about the technical capabilities, scalability, and potential commercial deployment remain under development. Additionally, the extent to which competitors are pursuing similar real-time, multi-modal AI models is still uncertain.
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What’s Next
Thinking Machines plans to release a limited research preview in the coming months, with a wider commercial rollout later this year. Monitoring updates from the company will be essential to understand the practical capabilities and adoption of these interaction models.
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Key Questions
What are AI interaction models?
They are AI systems designed to process and respond to multiple types of inputs—such as audio, video, and text—in real time, enabling more natural and continuous human-AI interaction.
When will the public or developers be able to test these models?
Thinking Machines plans to open a limited research preview in the coming months, with a broader release expected later this year.
How do these models differ from existing AI systems?
Current models typically wait for users to finish speaking or typing before responding, whereas these new interaction models aim to interpret ongoing inputs and respond dynamically, facilitating more seamless collaboration.
What applications could benefit from this technology?
Potential applications include real-time translation, virtual assistants, customer service, creative collaboration, and any domain requiring fluid, multi-modal interaction with AI.
