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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 (AI) has precipitated a fundamental shift in the global digital economy, 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 …
1. Introduction: The Strategic Imperative of AI Robustness The deployment of Large Language Models (LLMs) has transitioned rapidly from experimental chatbots to critical infrastructure capabilities, powering autonomous agents, code generation Read More …
1. The Synthetic Data Imperative: Beyond the Data Wall The trajectory of Large Language Model (LLM) development has historically been defined by the aggressive consumption of human-generated data. Scaling laws, Read More …
1. Introduction: The Epoch of Infinite Context The trajectory of Large Language Model (LLM) development has undergone a seismic shift, moving from the parameter-scaling wars of the early 2020s to Read More …