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Executive Summary and Strategic Recommendations The deployment of state-of-the-art Large Language Models (LLMs) is fundamentally constrained by their extreme scale, resulting in prohibitive computational costs, vast memory footprints, and limited Read More …
Part I: Foundational Principles of Sparse Architectures Section 1: Introduction – The Scaling Imperative and the Rise of Conditional Computation The trajectory of progress in large language models (LLMs) has Read More …
Section 1: The Principle of Conditional Computation and the Genesis of Mixture of Depths The development of the Mixture of Depths (MoD) architecture represents a significant milestone in the ongoing Read More …