Our graphical and visual solution is the key to connecting NLP, vision, and motion spatial modules,  integrating inputs like sensors and actuator outputs. But the secret sauce is to include reinforcement learning in the process. This creates machines that learn at "every step" they take, while the coder can train and supervise movements, object detection, mapping areas or functions using a graphical approach closer to human natural understanding ."

This way, a coder can focus on developing true robotic solutions instead of struggling with code. This saves time and improves results according to the desired objectives.