DAMO Academy was opened in October 2017, is a global research institute established by Alibaba. With the vision of "Tech to the Future," it positions itself as "a research institution committed to unraveling the mysteries of science and technology, driven by the vision of advancing humanity." This commitment is grounded in research spanning fundamental sciences, groundbreaking technologies, and practical, applied solutions. It stands for "The Academy for Discovery, Adventure, Momentum and Outlook".

In recent years, DAMO Academy has successfully built up a strong R&D system, and successfully incubated a number of well-known technical products such as Tongyi, T-Head, Xiaomanlv and many others.

Gao Junlong, who holds a Ph.D. from the Institute of Automation, Chinese Academy of Sciences, is currently the Chief Architect of the Embodied Intelligence Lab at DAMO Academy. With years of experience in robotics development, he previously served as the Technical Product Architect at the DAMO Autonomous Driving Lab. He led the product design and development of the logistics autonomous vehicles "Xiaomanlv" and "Damanlv," and spearheaded the commercialization of the world's first large-scale unmanned logistics vehicle fleet operating nationwide. He has published more than ten research papers and holds over ten granted or pending patents. Additionally, he has contributed to several Chinese national key research projects.

Synopsis

Embodied Intelligence: An Inevitable Arena for Artificial Intelligence

The scaling law serves as the first principle of current AI development, with data, computing power, and models being its three core components. Robotics can be seen as an extension of the scaling law into the physical world. In terms of intelligence generation and modeling principles, AGI/ASI can take two fundamental forms: one based on static knowledge and reasoning via large models, and the other through autonomous learning driven by dynamic behavior and environmental interaction. Intelligent robots represent the latter path, aligning with the way human intelligence develops, making it a first-principles approach to achieving ASI. Based on this, we developed the RynnBot Embodied Intelligence Platform, and open-sourced the RynnBot Brain models as well as RynnRCP, the robotics counterpart of MCP, providing end-to-end development support for embodied intelligence developers.