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What is TML-interaction-small?

TML-Interaction-Small is a real-time multimodal interaction model developed by Thinking Machines Lab to enable scalable human-AI collaboration through continuous interaction across audio, video, and text. The model is designed to overcome the limitations of traditional turn-based AI systems by allowing humans and AI to communicate more naturally through simultaneous perception, speech, visual understanding, interruptions, and collaborative reasoning. Instead of relying on external dialog management systems or separate real-time scaffolding, TML-Interaction-Small handles interaction natively through a time-aware architecture built around continuous 200ms micro-turn exchanges. This architecture allows the model to process streaming input and generate output concurrently while maintaining awareness of silence, interruptions, overlap, timing, and visual context. The model is capable of responding proactively to spoken and visual cues, enabling interaction patterns such as live translation, contextual interruptions, visual monitoring, simultaneous speech, live commentary, and continuous conversational collaboration. TML-Interaction-Small also coordinates with an asynchronous background reasoning model that performs deeper reasoning, tool usage, web browsing, and longer-horizon tasks while the interaction layer remains present and responsive throughout the conversation. Thinking Machines Lab designed the system to reduce the collaboration bottleneck in modern AI workflows by enabling humans to stay continuously involved in AI-assisted processes rather than being pushed out by fully autonomous systems. The model uses a multimodal streaming architecture with lightweight audio and visual processing pipelines, encoder-free early fusion techniques, optimized streaming inference infrastructure, and batch-invariant kernels for low-latency performance and training stability.

What is Seeduplex?

Seeduplex is a state-of-the-art full-duplex speech large language model that utilizes an innovative “listen while speaking” approach to enable voice interactions that are more natural, fluid, and accurately timed. In contrast to traditional half-duplex systems that alternate between listening and responding, Seeduplex continuously processes and understands user audio, allowing for simultaneous listening and speaking while remaining attuned to the surrounding soundscape. Its sophisticated interference suppression technology effectively distinguishes authentic user input from various background noises, such as music, announcements, navigation prompts, and overlapping dialogues, significantly reducing the chances of incorrect responses and interruptions in complex situations. Additionally, Seeduplex combines both speech and semantic features to achieve dynamic endpoint detection, enabling it to recognize when a user is considering, hesitating, correcting themselves, or has finished speaking. This model showcases its capability to patiently wait through thoughtful pauses, deliver quick replies immediately after a statement, and smoothly halt speech when interrupted, promoting a more engaging conversational experience. By focusing on creating interactions that feel more instinctive and responsive, the Seeduplex design ultimately seeks to elevate the overall user experience in voice communication. Its innovative features not only enhance clarity but also foster a sense of connection between users and technology.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Thinking Machines Lab

Company Location

United States

Company Website

thinkingmachines.ai/

Company Facts

Organization Name

ByteDance

Date Founded

2012

Company Location

China

Company Website

seed.bytedance.com/en/seeduplex

Categories and Features

Categories and Features

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