LLM Inference Optimization: State-of-the-Art Research (Generative AI LLM Theory & Research)
by David Spuler
LLM Inference Optimization explores the research and theory behind improving inference for large language models. With a focus on generative AI, it offers a research-oriented look at state-of-the-art optimization approaches and the broader considerations involved in making LLM systems more efficient.
About This Book
LLM Inference Optimization examines the theory and research surrounding efficient inference for large language models.
The book focuses on generative AI systems and the challenges involved in improving how models produce results.
It presents a research-oriented perspective on state-of-the-art approaches to inference optimization.
Designed for readers interested in large language model theory, research, and practical efficiency considerations.
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