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such as healthcare, finance, cy- bersecurity, and autonomous vehicles, where they interact dynamically with external knowledge sources, retain memory across sessions, and autonomously generate responses and
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quality, greenhouse gas fluxes, and emergency response capacity. Yet, current modelling approaches are incapable of inference from diverse sensory data, too computationally demanding for real-time use, and
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dynamically with external knowledge sources, retain memory across sessions, and autonomously generate responses and actions. While their adoption brings transformative benefits, it also exposes them to new and
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dynamics in urban environments. Gas dynamics shape air quality, greenhouse gas fluxes, and emergency response capacity. Yet, current modelling approaches are incapable of inference from diverse sensory data