Imagine ordering flat-pack furniture but instead of wrestling with confusing instructions, you simply tell an AI assistant to assemble it for you. This is the fascinating goal of a research project that explores how Large Language Models (LLMs) can control industrial assembly. Researchers from Bosch Center for Artificial Intelligence and Tel Aviv University are teaching AI to bridge the gap between natural language instructions and intricate physical actions in industrial assembly scenarios. The challenge is to connect general language understanding with finely tuned robotic skills like carefully inserting a plug into a socket. This project utilizes LLMs not just to interpret your commands (like "Insert the yellow plug") but also to dynamically switch between different specialized skills. It's a hierarchical approach: a central LLM 'brain' determines the overall goal and then delegates fine-grained control to dedicated 'skill' modules when high precision is required. Early results show impressive success in handling straightforward assembly steps, with the robot able to identify and approach the correct parts based on language instructions. But the project doesn’t stop there. The real test lies in building a library of these specialized skills to handle the full complexity of real-world industrial assembly, navigating obstacles like collisions and occlusions. Imagine a future where robots are seamlessly integrated into assembly lines, performing intricate operations simply by listening to our directions – it's a future this research is actively building towards.