Creating an Agentic Skill Library for Robotics, Computer Vision, and Physical AI (medium.com)

Telekinesis has announced the development of a Large-Scale Skill Library for Physical AI, aimed at enhancing robotics and computer vision capabilities. This initiative comes amidst the rapid evolution of Physical AI technologies driven by Vision Language Action (VLA) models, Robotics Foundation Models, and advanced Reinforcement Learning techniques. These advancements promise to enable robots to adapt to real-world variations, moving beyond traditional limitations in robotic programming and performance. However, initial tests revealed that current VLAs are not yet equipped to address complex industrial challenges, such as precise wire soldering and high-mix manufacturing, highlighting gaps in existing AI capabilities. The Telekinesis SDK consists of a modular library of reusable "Skills," which integrate perception, motion planning, control, and decision-making into self-contained operations. These Skills provide consistent interfaces that allow easier composition across various applications, while Physical AI Agents, often powered by LLMs or VLMs, handle high-level task planning and adaptation in real-time. This separation of duties aims to streamline the workflow in robotics, making it more accessible to developers and hobbyists alike. By fostering a community-driven ecosystem for sharing and improving Skills, Telekinesis aims to democratize robotics, making advanced automation feasible and effective for diverse real-world applications.