Researchers have developed a new approach called Jupyter Agents, which trains large language models (LLMs) to reason with Jupyter notebooks. This allows LLMs to understand and interact with the code and data in notebooks, enabling more effective collaboration between humans and AI systems. The system uses a combination of reinforcement learning and meta-learning to teach the LLMs how to navigate and execute notebook code. According to the developers, this could have significant implications for areas such as education and scientific research. --- Why it matters: This matters because it enables LLMs to better understand and interact with complex data and code, which is a major challenge in many AI applications. Source: https://huggingface.co/blog/jupyter-agent-2