Thinking Machines Lab previews interaction models for real-time human-AI collaboration
Original titleInteraction Models: A Scalable Approach to Human-AI Collaboration
Thinking Machines Lab announced a research preview of interaction models that take in audio, video, and text continuously and respond in real time without external turn-detection harnesses.
The model, TML-Interaction-Small, is a 276B-parameter MoE with 12B active parameters, paired with an asynchronous background model for sustained reasoning and tool use.
The post reports competitive intelligence scores and lower turn-taking latency against GPT-realtime and Gemini Live models, along with new interactivity benchmarks where baseline models largely failed.
The post explains a time-aligned, full-duplex design and benchmarks against turn-based models, showing how interaction and background reasoning can be split across two cooperating models.
Source: Thinking Machines Lab · thinkingmachines.aiPublished · added here