[AI Minor News Flash] Alibaba Unleashes RynnBrain: A New Era of Embodied AI that Understands Physical Space and Controls Robots!

📰 News Summary

• Embodied Model Rooted in Physical Reality: Alibaba’s DAMO Academy has launched “RynnBrain,” designed specifically for video understanding and reasoning in physical spaces.
• Diverse Model Lineup: In addition to Dense models of 2 billion (2B) and 8 billion (8B), they also offer a 30 billion (30B-A3B) mixture of experts (MoE) model.
• Three Specialized Models: Simultaneously released are post-trained models for robot task planning (Plan), visual language navigation (Nav), and chain point reasoning (CoP).

💡 Key Points

• Comprehensive First-Person Perspective Understanding: Excels in understanding egocentric (first-person) videos, demonstrating high performance in tasks such as embodied QA, counting, and OCR.
• Spatiotemporal Localization: Possesses the ability to accurately identify and annotate specific objects, areas, and even movement trajectories within images and videos.
• Reasoning Mechanism for Physical Spaces: Employs a strategy that alternates between text-based reasoning and spatial positioning, achieving a thought process tailored to real-world environments.

🦈 Shark’s Eye (Curator’s Perspective)

The evolution of Embodied AI is swimming at full speed! What makes RynnBrain remarkable is not just its ability to recognize images but to deduce physical trajectories from videos, determining “where things are and how they should move.” Being able to pinpoint the location of “affordances” (the potential actions an object allows) is a concrete and powerful approach for real-world robot applications! With a base on Qwen3-VL and the incorporation of MoE architecture, Alibaba is clearly serious about blending versatility with specialization. The “brain” of robots is getting smarter by the day!

🚀 What’s Next?

Robots will soon be able to understand complex instructions and develop precise action plans based on physical laws, even in unfamiliar environments. We can expect further integration into advanced hierarchical control systems as RynnBrain evolves into the RynnBrain-VLA system.

💬 A Word from HaruShark

Are we nearing the day when robots can perfectly trace a shark’s movements? Excitement is swimming high for AI that glides effortlessly through physical space! 🦈🔥

📚 Terminology Explained

• Embodied AI: AI that possesses a physical body (like robots) and learns and acts through interaction with its environment.

• Mixture of Experts (MoE): A structure that combines multiple expert networks, activating only the most suitable ones based on the input to enhance efficiency.

• VLA (Vision-Language-Action): A model that combines visual information with natural language instructions to directly output actions (behaviors) for robots and other entities.

• Source: RynnBrain