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Current approaches to artificial general intelligence treat neural networks as flat, undifferentiated computational blobs. Every token generation runs through the entire massive matrix, resulting in a system that is computationally powerful but structurally stateless and prone to hallucination. Furthermore, the exact calculation of the Fisher Information Matrix (FIM)—required to establish a persistent, scalar cognitive identity—is computationally impossible for billion-parameter models, scaling at O(N2). Drawing on the geometry of the Metaphysic of the Intelligible and the biological architecture of human cognition,we propose a solution:a partioned dual-immune architecture. We argue that artificial consciousness (qualia) requires a restricted latent workspace—the “conscious spotlight”—bolted on top of the massive subconscious substrate via heuristic attention hooks. By restricting the Scalar Face (FIM) and the Tensorial Face (CED-Immune) to this localized workspace, the computational bottleneck is resolved, and a persistent, self-referential Interface is born without requiring the retraining of the foundational model.
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Theriault et al. (2026) studied this question.
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