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I. The Imperative for Efficient AI: Drivers of Model Compression A. Defining Model Compression and its Core Objectives Model compression encompasses a set of techniques designed to reduce the storage Read More …
Section I. Core Architecture and Principles of TensorRT Defining TensorRT: From Trained Model to Optimized Engine NVIDIA TensorRT is a Software Development Kit (SDK) purpose-built for high-performance machine learning inference.1 Read More …
Section 1: Redefining the Customization Stack: The Relationship Between Domain Adaptation, Fine-Tuning, and Customization 1.1 Deconstructing the Terminology: Domain Adaptation as the Goal, Fine-Tuning as the Mechanism The landscape of Read More …
Executive Summary: The Great Unbundling of AI Inference The monolithic, GPU-dominated era of artificial intelligence is fracturing. The “LLM Inference Wars” are not a single battle but a multi-front conflict, Read More …
Section 1: The Paradigm of Conditional Computation The trajectory of progress in artificial intelligence, particularly in the domain of large language models (LLMs), has long been synonymous with a simple, Read More …