Intelligent Behaviour as Adaptive Control Guided by Accurate Prediction

We build on the predictive processing framework to show that intelligent behaviour is adaptive control, driven by accurate prediction and uncertainty reduction in dynamic environments with limited information. We argue that adaptive control arises through a process of re-concretisation, where learned abstractions are grounded in new situations via embodiment. We use this as an explanation of why AI models often generalise at the cost of detail while biological systems manage to tailor their predictions towards specific environments over time. On this basis, we utilise the notion of embodied prediction to provide a new distinction between biological intelligence and the performance illustrated by AI systems.