Core Insights - The event on February 10 showcased the strategic collaboration between multiple leaders in the field of embodied intelligence, focusing on the launch of the Dexbotic 2.0 framework and the RLinf reinforcement learning framework [1] Group 1: Company Developments - The collaboration involves key figures such as Xia Lixue, CEO of Wunwen Xinqiong, and other prominent academics from Tsinghua University, indicating a strong partnership between industry and academia [1] - The aim of the collaboration is to create an efficient and user-friendly infrastructure for developing embodied intelligence using PyTorch, which will lower the development barriers for researchers and developers [1] Group 2: Technological Advancements - The introduction of Dexbotic 2.0 and RLinf is expected to facilitate algorithm innovation and breakthrough applications in various scenarios, highlighting the focus on enhancing research capabilities in the field [1]

Core Insights - The company, Yuanli Lingji, has launched three core products: the first embodied native large model DM0, the embodied native development framework Dexbotic 2.0, and the embodied native application mass production workflow DFOL, emphasizing that 2026 will be the year of embodied natives rather than just embodied intelligence [1][3] Product Launch - DM0 is the world's first embodied native large model, designed to operate in complex environments and complete human tasks accurately from its inception, integrating multimodal internet information and unique embodied scene data such as driving behavior and robot operations [3] - Dexbotic 2.0 features a modular architecture that allows developers to build their embodied applications in a Lego-like manner, offering five core advantages over its predecessor, including independent upgrades and replacements of components [3][4] - DFOL introduces a data feedback mechanism that enables continuous evolution of the system through a closed loop of cloud training, on-site execution, data feedback, and model updates, enhancing flexibility and adaptability in real-world environments [4][5] Strategic Collaborations - The company has partnered with prestigious institutions like Tsinghua University and Princeton to create a unified infrastructure for embodied intelligence, similar to what PyTorch has done for deep learning, aiming to lower development barriers and foster innovation [4]