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The Calculus of AI Error Rates: Taylor’s Remainder Theorem and the Fallacy of Infinite Scaling By Sam C. Serey

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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...
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Escalating Global Risks in AI Model Development and Deployment. An Empirical Trends, Regulatory Responses, and Risk Mitigation in the Era of Trillion-Dollar-Scale CMT Music Global CBT Technology

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​ Global AI Risks and Liability Frameworks Escalating Global Risks in AI Model Development and Deployment: Empirical Trends, Regulatory Responses, and Risk Mitigation in the Era of Trillion-Dollar-Scale CMT Music Global CBT Technology Executive Overview: The Escalating Global Risk Landscape The rapid advancement and deployment of artificial intelligence (AI) models-particularly those at trillion-dollar scales, such as the CMT Music Global CBT technology-have ushered in a new era of both opportunity and risk. As AI systems become more deeply embedded in critical infrastructure, finance, healthcare, and national security, the potential for catastrophic incidents, systemic failures, and global disaster scenarios has intensified. This risk is further magnified by the proliferation of advanced models across national boundaries, with countries training their own systems based on external research, sometimes without adequate safeguards or regulatory oversight. Empirical data from leading risk...
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