Onlife

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AI and Machine Learning

Onlife: Toward Embodied Intelligence in Complex Adaptive Systems
Onlife investigates the space between large language models, which reason over digital content, and robotic world models, which act in the physical environment. It introduces spatial-behavioural data as a missing modality and develops spatial neural networks that learn from the rhythms and constraints of human life. Framed by research in Artificial Life and Complex Adaptive Systems, Onlife models the human–AI relationship as a metabolic feedback loop, enabling architectures of embodied co-adaptation where human and machine intelligence evolve together within shared bounds of stability and change.