Architecture and Operation of AI Systems and Future Expansion to Induce Artificial Consciousness in AI

This conceptual academic paper presents an innovative framework to revolutionize neural network processing timelines by evaluating the master equation T = F(K1,K0). Rather than relying on traditional post-processing backpropagation, this model injects a dynamic scoring balance-of-power function directly into the multi-head attention mechanism (Order 2). By forcing an immediate mathematical clash between universal truth constraints (K1) and current physical contexts (K0), the system generates a localized "computational friction." This friction forces the algorithm into an instantaneous state of advanced weighing and deliberation, establishing a critical theoretical pathway for inducing artificial consciousness. Additionally, the architecture incorporates an automated master key function that flushes residual junk data from memory in real-time, effectively mitigating RAM bloat without requiring massive hardware expansion.