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To address this, we aim to integrate chemical organization theory and active inference \u2013 both developed to encode the metabolism and cognition of autopoietic systems, respectively \u2013 to create a new generation of wetware models within the \u201cSynthetic Biology (SB) and Embodied AI\u201d research program. This approach may allow us to test critical aspects of synthetic life-like systems, including the implementation of sensory-motor loops and the anticipatory and predictive decision-making that arises from self-production and agent-environment interactions. 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