Definition: In artificial intelligence, "Action Tokens" refer to discrete, sequential commands generated by a foundation model to enable robots or physical AI systems to perform actions in the real world. These tokens encode motor instructions or physical tasks, similar to how language models generate text tokens for communication.
How They Work: Just as a large language model (LLM) processes textual prompts to produce text tokens as outputs, a foundation model designed for robotics can process sensory inputs—such as images, environmental data, or verbal instructions—to generate Action Tokens. These tokens instruct robotic systems to perform specific tasks, like picking up objects, navigating spaces, or interacting with their surroundings.
Input Processing:
Inputs can include text (commands), images (environmental cues), or sensory data (real-time feedback).
The inputs are tokenized and analyzed to establish spatial, temporal, and logical relationships.
World Foundation Model: The backbone of this process is a "World Foundation Model," a large AI model trained not just on text but also on physical principles like gravity, friction, and object permanence. It integrates:
Visual Understanding: Recognizing objects and their relationships.
Physics: Predicting how objects behave in the real world.
Geometry & Spatial Awareness: Calculating the positioning and movement of objects.
Action Token Generation:
Instead of generating textual tokens (words or sentences), the model outputs a sequence of Action Tokens.
These tokens serve as motor commands or high-level directives for a robot to execute in the physical world. For example:
"Move arm to coordinate (x, y, z)."
"Grip object with 50% pressure."
"Rotate 90° clockwise."
Execution: The robotic system interprets and executes the Action Tokens sequentially, adjusting actions dynamically based on real-time feedback from sensors.
Applications: Action Tokens bridge the gap between digital intelligence and physical action. Potential applications include:
Autonomous Robotics: Robots executing tasks like assembling parts, performing surgery, or cooking.
Personal Assistance: Home robots performing daily chores.
Industrial Automation: Smart robots in manufacturing and logistics.
The Future of Action Tokens: As robotics and AI continue to converge, Action Tokens promise to make robots more adaptable and intuitive. With the development of comprehensive World Foundation Models, robots will not only follow instructions but also predict outcomes, reason causally, and operate seamlessly in complex environments.
By understanding the concept of Action Tokens, learners can appreciate how AI extends beyond language and decision-making to impact the physical world.
