Consciousness is approached not as Descartes' systematic doubt but as organisms finding their way in the world by detecting affordances—possible uses of features that are beneficial or harmful. Affordances are indefinite, unordered, non-listable, and not deducible from one another. Biological adaptations arise either from heritable variation and selection or, faster, from organisms finding novel uses. This leads to five conclusions: artificial general intelligence based on universal Turing machines is impossible because they cannot find novel affordances; brain-mind is not purely classical physics; brain-mind must be partly quantum, supported at 6.0–7.3 sigma; mind actualizes potentia (quantum possibilities) into actuals, supported at 5.2 sigma, experienced as qualia enabling perception of uses; and trans-Turing systems beyond quantum computers are discussed.
Wetware Network-Based Artificial Intelligence (WNAI) proposes building autonomous cognitive agents from synthetic chemical networks, shifting wetware neuromorphic engineering from disembodied computation and biological mimicry to reticular chemical self-organization. The framework integrates network cybernetics, autopoietic theory, and enaction to treat cognition as a materially grounded, emergent phenomenon. WNAI complements embodied AI and xenobiotics by expanding artificial embodied cognition into fully synthetic domains and exchanges with neural network architectures to advance cross-substrate principles. It offers a roadmap for chemical neural networks and protocellular agents, aiming for robotic systems requiring minimal, adaptive, substrate-sensitive intelligence, thus expanding artificial cognition beyond silicon and biohybrid systems.
Consciousness is approached not as Descartes' doubt but as how organisms find their way in the world by discovering beneficial or harmful uses of features—'affordances.' The number of uses of any thing is indefinite, unordered, and not deducible from one another. All biological adaptations arise from seizing affordances. From this, the authors conclude: artificial general intelligence based on universal Turing machines is impossible because they cannot find novel affordances; brain-mind is not purely classical physics; brain-mind must be partly quantum-supported (evidence at 6.0 to 7.3 sigma); mind actualizes quantum potentia (supported at 5.2 sigma), and these actualizations of entangled brain-mind-world states are experienced as qualia, enabling perception of uses. Computers cannot jury-rig. Trans-Turing systems are discussed.