An Interactive Agent Foundation Model

Stanford University, Microsoft Research, and the University of California just released a new paper, "An Interactive Agent Foundation Model".

Two important fragments from the paper:

• "By training on a variety of task domains and applications, we develop a versatile foundation model that can be fine-tuned for executing optimal actions in a variety of contexts, paving the way towards generally intelligent agents."
• "We note that the capabilities of agent AI models may significantly change at scale."

Those two together carry a powerful meaning.

The new foundation model is designed to process multi-modal information at different levels of abstraction, with a comprehensive understanding of the context and environment, and planning coherent actions.

They defined an Embodied Agent as "any intelligent agent capable of autonomously taking suitable and seamless action based on sensory input, whether in the physical world or in a virtual or mixed-reality environment representing the physical world."

They believe embodied agents require the key components:

• Perception: multi-sensory with fine granularity. This is important for understanding the environment, e.g. visual perception is useful for agents that can parse the visual world, including images, videos, and gameplay.
• Planning for navigation and manipulation: crucial for many tasks, e.g. navigating in a robotics environment and conducting complex tasks.
• Interaction with humans and environments.

What do you think?

I'll come back to you with an explanation after I read it carefully.

Original post: LinkedIn