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Executive Summary The artificial intelligence landscape is currently undergoing a foundational paradigm shift, transitioning from the era of passive Generative AI—characterized by static prompt-response interactions—to the era of Agentic AI. Read More …
1. Introduction: The Era of “Omni-Modal” Intelligence The evolution of artificial intelligence in 2024 and 2025 has been characterized by a decisive shift from disparate, loosely coupled systems toward unified, Read More …
I. The Entropy of Consensus: Reevaluating the Cost of Digital Trust The fundamental innovation of the Nakamoto consensus, introduced with Bitcoin in 2009, was not merely the creation of a Read More …
1. Introduction: The Paradox of Overparameterization In the contemporary landscape of deep learning, a singular, pervasive dogma has dictated the design of neural architectures: scale is the primary driver of Read More …
Executive Summary The rapid ascendancy of Transformer-based Large Language Models (LLMs) has outpaced our theoretical understanding of their internal operations. While their behavioral capabilities are well-documented, the underlying computational mechanisms—the Read More …
Executive Summary The evaluation of Artificial Intelligence, specifically Large Language Models (LLMs) and autonomous agentic systems, has entered a period of profound transformation. We are currently witnessing a decoupling between Read More …
1. Introduction: The Post-Training Paradigm and the Alignment Challenge The contemporary landscape of artificial intelligence has been irrevocably altered by the emergence of Large Language Models (LLMs) trained on datasets Read More …
1. The Epistemological Crisis of Artificial Intelligence The widespread deployment of Large Language Models (LLMs) and generative artificial intelligence has precipitated a fundamental shift in the global digital economy, transitioning Read More …
1. Introduction: The Economic Nature of Distributed Security In the realm of centralized computing, security is binary and architectural. A system is secured by firewalls, access control lists, and encryption Read More …
1. Introduction: The Unreasonable Effectiveness of Overparameterization The theoretical understanding of deep neural networks has undergone a fundamental transformation over the last decade. Historically, statistical learning theory relied on concepts Read More …