The robotics industry has made substantial progress, but wide spread adoption remains limited due to challenges in control and movement planning. Currently, addressing these challenges involves time-consuming and expensive setup processes, requiring a team of engineers to program paths, trajectories, and specialized algorithms for each application. This approach constrains the accessibility and versatility of robotics across various sectors.

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A potential solution is to leverage modern AI, such as natural language processing (NLP)capabilities of large language models (LLMs) like Chat GPT, to create a more generalized approach to robotics programming. By developing an AI-driven system that learns the mechanics and environment of a robotic arm from blueprints, 3D models, or live camera feeds, setup costs can be significantly reduced, and AI can quickly adapt trajectories as needed.

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Addressing these challenges might be daunting, as AI needs to have a precise physical model of the world to succeed. However, I believe the capabilities of LLMs are already more advanced than what is required. LLMs contain a wealth of knowledge about the world and various domains where robots can be used, making the task potentially more manageable than it initially appears.

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