Part 9/12:
The HPT architecture resembles a transformer-based system familiar from NLP advancements. The stems process raw, diverse input data into tokens, while the trunk captures the relationships between these tokens. The heads then translate this understanding into actionable commands.
This design allows the system to handle multiple robots simultaneously, treating all data as parts of one expansive neural network. When tested, HPT showed faster learning curves and higher accuracy in various tasks compared to models trained from scratch, with performance further improving as the data scale increased.