Part 8/12:
The research team leveraged training strategies inspired by large language models. In NLP, models are pre-trained on vast text corpora, developing a broad understanding before being fine-tuned for specific tasks. Similarly, HPT is pre-trained on a wide array of robot and human data, giving it a broad foundational knowledge that can be quickly adapted to new tasks with minimal additional training.
This approach means that when facing a new task, the robot can leverage its prior knowledge, greatly accelerating learning and enhancing flexibility. As a result, the pursuit of plug-and-play robotic systems that can be instantly deployed with minimal setup becomes more attainable.