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R1-Omni


Introduction

R1-Omni is the industry’s first application of Reinforcement Learning with Verifiable Reward (RLVR) to an Omni-multimodal large language model. We focus on emotion recognition, a task where both visual and audio modalities play crucial roles, to validate the potential of combining RLVR with Omni model.









R1-Omni

R1-Omni is an advanced AI assistant developed by Rabbit Inc., designed to redefine the way we interact with technology through natural language and intuitive interfaces. It operates on top of Rabbit’s Large Action Model (LAM), enabling it to control apps and perform tasks on behalf of the user—without needing traditional apps or APIs.

Key Features of R1-Omni:

  1. Large Action Model (LAM): Unlike conventional AI assistants, R1-Omni understands not only language but also user interfaces. It can interact with digital environments just like a human would—clicking, scrolling, and navigating apps visually.

  2. Voice-first Interaction: Designed for voice-driven commands, users can simply talk to R1-Omni to manage tasks like booking rides, editing documents, or ordering food.

  3. Device Integration: Paired with the Rabbit R1 handheld device, R1-Omni brings a physical dimension to digital AI, enabling always-on, context-aware interaction wherever you go.

Use Cases:

  • Digital Task Automation: From managing your calendar to posting on social media, R1-Omni handles app-based tasks smoothly without requiring APIs.
  • Personal Productivity: Helps streamline daily routines—organize to-dos, send messages, or set reminders through voice or touch.
  • Universal App Control: Works across different platforms by learning user actions visually, allowing control of any app interface.
  • On-the-Go Assistance: With the R1 device, get portable AI help for navigation, translation, and quick answers anytime, anywhere.

In essence, R1-Omni reimagines the AI assistant as an action-capable agent that doesn’t just understand what you say—it knows how to get things done across any app or platform, just like you would.