The article discusses the evolution of generative AI from version 1.0 to 2.0, highlighting the transition from large language models (LLMs) to more complex agent-based systems. It emphasizes the importance of understanding foundation models, prompt-engineering techniques, and the integration of multi-modal models. The next phase involves creating agent systems that can autonomously execute complex tasks by chaining multiple AI functionalities together. The article also mentions the upcoming AI Impact Tour event focused on auditing AI models.
Ken Goldberg, a professor at UC Berkeley, discusses the future of robotics, highlighting the role of generative AI in transforming the field. He also explores the potential of multi-modal models and expresses newfound optimism about humanoid robots and legged robots. Goldberg predicts that manufacturing and warehouses will see increased robot adoption, and he believes that affordable home robots capable of decluttering will be available within the next decade. He emphasizes the importance of robot motion planning and addresses the issue of robot singularities, which disrupt robot operations. Goldberg co-founded Jacobi Robotics to develop algorithms that guarantee the avoidance of singularities, enhancing reliability and productivity for all robots.
