Neuroscience

Grounded world models in biological organisms and future embodied AI

Giovanni Pezzulo, Davide Nuzzi, Marco D'Alessandro, Riccardo Proietti, Roberto Bottini, Paul Cisek

Featured July 19, 2026

AI-generated analysis — This is SciGrove's AI interpretation of the paper, not peer-reviewed content. Always refer to the original paper.

Simply

Unlike today's AI that learns mostly from words, living things build their understanding of the world by actively moving and interacting, which then helps them understand language and think smarter.

In depth

The paper argues that biological intelligence builds grounded world models through active, embodied interaction with the environment, which then provides the semantic scaffold for higher cognition and language. This contrasts with current embodied AI, which often uses language as the primary scaffold for learning, leading to a lack of true grounding in physical and social reality. The authors highlight how biological systems leverage intrinsic dynamics and action-perception loops to develop robust, flexible, and socially aligned world models.

Key Takeaways

1
Biological intelligence develops grounded world models through active, embodied interaction, providing a foundation for language and higher cognition, unlike current AI's language-first approach.
2
Neural circuits in organisms support diverse grounded world modeling functions, including spatial and conceptual navigation, affordance-based perception, and self-other distinction.
3
Future embodied AI could benefit from incorporating biological principles like intrinsic dynamics, autonomous experience, and social interaction to build more robust and human-aligned world models.

Conceptual Flow

HIGH LEVEL

Biological World Model Construction

Living things learn about the world by doing things and seeing what happens, building a deep understanding from their experiences.

Body & Brain

Environment

Act & Sense

Internal Model

Understand World

Impact on AI Development

Using this 'learn by doing' idea could help robots understand the world better, act smarter, and even talk more like humans.

Current AI (Words First)

Biological Way (Experience First)

Inspire AI Design

Smarter Robots

Better Interaction

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