Global Workspace Theory provides a central framework for explaining higherorder cognitive functions at the intersection of cognitive science and artificial intelligence. Recent experimental evidence indicates that structures functionally equivalent to a global workspace exist internally within large language models, designated as J-space; however, the intensity of their emergence exhibits...
This paper proposes a method for determining artificial intelligence consciousness based on sheaf cohomology theory. By modeling the computational structureof deep neural networks as a coherent sheaf on a cognitive manifold, we establisha mathematical relationship among representation dimension, topological complexity, and Euler characteristic. Consciousness emergence is formalized as a...