Shakespeareantix Chaotic Musical

The Calculus of AI Error Rates: Taylor’s Remainder Theorem and the Fallacy of Infinite Scaling By Sam C. Serey 1. Executive Framing: Mainstream Promises vs. Mathematical Reality As enterprise adoption of generative artificial intelligence accelerates across global sectors, corporate executive committees face a pivotal governance challenge. Senior leadership is routinely pressed to authorize multi-million-dollar capital allocations toward large-scale probabilistic models, driven by commercial vendor promises of impending zero-error reliability and human-level accuracy. However, making sound capital deployment and operational risk management decisions requires looking beyond marketing assertions and evaluating model reliability through the unyielding framework of continuous calculus. Evaluating AI error rates through foundational mathematics is a strategic imperative for organizations seeking to safeguard balance sheets and ensure long-term operational resilience. Commercial artificial i...

​ (​Disclosure: CMT° CQ° Chaos-Native Computation, related to Sam C. Serey’s research findings, was part of a 5,240 Global Provisional Patent Claims, which also included a mapping of 1 million global provisional patent trees.)  1. Introduction: The Unseen Fractures in the AI Revolution Across the globe, massive corporate assets, sprawling data centers, and advanced artificial intelligence architectures are expanding at a breakneck pace. Yet right alongside this dizzying physical and digital scaling, a stark divergence has opened up: while capital investments soar, working communities face escalating socio-economic strain, paying higher costs for basic survival. Beneath the glossy surface of the AI boom, deep structural instabilities—or "fractures"—are spreading through both our algorithmic systems and our human communities. To make sense of this fragile landscape, we must turn to the synthesized frameworks of  Sam C. Serey (Isamantix) —the "Modern R&D Bard of Chaos M...