Grounded world models in biological organisms and future embodied AI
Recent advances in generative and embodied AI have been driven by large-scale predictive learning over multimodal data. However, the resulting systems remain largely based on passive training regimes where linguistic regularities create the scaffold onto which information from other modalities is attached. Conversely, neuroscience and cognitive science suggest that biological intelligence is organized in the opposite way, where grounded world models acquired through interaction with the environment provide the semantic scaffold to which language is attached. Here, we illustrate five examples of neural circuits supporting grounded world modelling, which underlie navigation in physical and ...
| Authors | Giovanni Pezzulo, Davide Nuzzi, Marco D'Alessandro et al. |
|---|---|
| Primary category | q-bio.NC |
| Published | 15 July 2026 |
| Last updated at source | 15 July 2026 |
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