We are offering grants of $100,000 + Tinker credits to researchers advancing the field of human-AI interactivity. Submit your proposals by June 19th! https://thinkingmachines.ai/news/interactivity-research-grants/…

Announcing Interactivity Research Grants

Source: https://thinkingmachines.ai/news/interactivity-research-grants/ We recently published a research preview ofinteraction models, an approach to AI designed for human collaboration. Collaboration requires interactivity — the capacity of a model to communicate in real time in different modalities in a way that is intuitive for people.

Most AI research in recent years has focused on intelligence and autonomy, with interactivity relegated to secondary importance. We aim to change that — with your help. We are awarding multiple grants of $100,000 (with an additional $25,000 in Tinker credits) for proposals on research that advances interactivity. We encourage you toapplyby June 19, 2026 to[email protected].

Research direction

We are looking for research that lays the foundation for interactivity to scale along with intelligence. There are many potential avenues of interactivity research to pursue, here are some that we are excited about:

• **Evaluations for real-time multimodal interaction.**How do we benchmark the real-time interaction ability of AI systems in real world use cases? The open research community is uniquely positioned to contribute independent, fair evaluations that push this work forward.
• **Ensuring safety for multimodal real-time AI systems.**How do we detect dangerous requests and behaviors from users across modalities and respond in time? These problems pose unique challenges distinct from turn-based text-only safety.
• **Explaining complex information with generative UI.**As AI systems perform increasingly complex tasks, it is important that they can explain their results in a variety of output formats such as SVG or HTML. How do we enable multimodal AI systems to explain their work so that people understand it?
• **Steering agents during long-horizon tasks.**Current agents are optimized to perform long-horizon tasks autonomously without incorporating human feedback. How can humans effectively obtain real-time updates on the agents’ execution and steer it live? We are interested in training approaches and techniques for this capability as well as evals.

We are not limiting our grants to these specific directions. We welcome proposals on any topic that advances this space.

Seehow to applyfor proposal requirements, selection criteria, timeline, and completeterms of servicefor the grant program.

Research on human-AI interactivity is still an emerging field, but we believe in its potential to shape the trajectory of AI development. We’re excited to support this research and look forward to seeing your ideas.