OpenAI's 'Teacher-Student Curriculum Learning' is a machine learning technique designed to enhance the training of artificial intelligence models. The core concept involves a more advanced 'teacher' model guiding a 'student' model through a structured learning path. Instead of exposing the AI to all data at once, the curriculum learning approach gradually introduces more complex tasks and information, mirroring how humans learn.

This method aims to make the training process more efficient and effective, helping the AI model to learn faster and achieve better performance on complex tasks. By structuring the learning environment, the 'teacher' helps the 'student' avoid common pitfalls and focus on acquiring foundational knowledge before moving to advanced concepts. This research is significant because it addresses the challenge of training large-scale AI models, which can be computationally expensive and time-consuming.

The technique represents a step forward in developing more capable and efficient artificial intelligence systems, potentially reducing the resources needed for future AI development and improving the robustness of models deployed in real-world applications.