Peiheng Hu – författare

Visar alla böcker från författaren Peiheng Hu. Handla med fri frakt och snabb leverans.

3 produkter

Kategorier

3 produkter

Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvPeiheng Hu,Chi Wang
E-bok
Engelska, 2026
833 kr
Läs direkt efter köp
Large language models (LLMs) are the reasoning engines of modern AI. Today, a major inflection point has arrived: as the world races to deploy AI at scale, model inference has moved to the center of the stack. Welcome to the inference era. Without proper optimization, however, LLMs can be expensive and slow to serve. Hands-On LLM Serving and Optimization is a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on, engineering-focused book, authors Chi Wang and Peiheng Hu combine practical examples, code, and strategies for building robust, performant, and cost-efficient AI token factories. Whether you re building the LLM inference infrastructure or the applications that consume it, a deep understanding of LLM serving will make you a more effective, future-ready engineer as AI transforms how we work and build.Learn the foundations of model serving with core concepts, design paradigms, and industry best practicesUnderstand the common challenges of hosting LLMs at scaleBalance latency and throughput to meet the demands of AI applications and business requirementsHost LLMs cost-effectively with practical, code-backed techniques
Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvPeiheng Hu,Chi Wang
E-bok
PDF, Engelska, 2026
839 kr
Läs direkt efter köp
Large language models (LLMs) are the reasoning engines of modern AI. Today, a major inflection point has arrived: as the world races to deploy AI at scale, model inference has moved to the center of the stack. Welcome to the inference era. Without proper optimization, however, LLMs can be expensive and slow to serve. Hands-On LLM Serving and Optimization is a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on, engineering-focused book, authors Chi Wang and Peiheng Hu combine practical examples, code, and strategies for building robust, performant, and cost-efficient AI token factories. Whether you re building the LLM inference infrastructure or the applications that consume it, a deep understanding of LLM serving will make you a more effective, future-ready engineer as AI transforms how we work and build.Learn the foundations of model serving with core concepts, design paradigms, and industry best practicesUnderstand the common challenges of hosting LLMs at scaleBalance latency and throughput to meet the demands of AI applications and business requirementsHost LLMs cost-effectively with practical, code-backed techniques
Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvChi Wang,Peiheng Hu
Häftad, Engelska, 2026
616 kr
Skickas inom 5-8 vardagar
Large language models (LLMs) are rapidly becoming the backbone of AI-driven applications. Without proper optimization, however, LLMs can be expensive to run, slow to serve, and prone to performance bottlenecks. As the demand for real-time AI applications grows, along comes Hands-On Serving and Optimizing LLM Models, a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on book, authors Chi Wang and Peiheng Hu take a real-world approach backed by practical examples and code, and assemble essential strategies for designing robust infrastructures that are equal to the demands of modern AI applications. Whether you're building high-performance AI systems or looking to enhance your knowledge of LLM optimization, this indispensable book will serve as a pillar of your success.Learn the key principles for designing a model-serving system tailored to popular business scenariosUnderstand the common challenges of hosting LLMs at scale while minimizing costsPick up practical techniques for optimizing LLM serving performanceBuild a model-serving system that meets specific business requirementsImprove LLM serving throughput and reduce latencyHost LLMs in a cost-effective manner, balancing performance and resource efficiency

Peiheng Hu – författare

Visar alla böcker från författaren Peiheng Hu. Handla med fri frakt och snabb leverans.

3 produkter

Kategorier

3 produkter

Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvPeiheng Hu,Chi Wang
E-bok
Engelska, 2026
833 kr
Läs direkt efter köp
Large language models (LLMs) are the reasoning engines of modern AI. Today, a major inflection point has arrived: as the world races to deploy AI at scale, model inference has moved to the center of the stack. Welcome to the inference era. Without proper optimization, however, LLMs can be expensive and slow to serve. Hands-On LLM Serving and Optimization is a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on, engineering-focused book, authors Chi Wang and Peiheng Hu combine practical examples, code, and strategies for building robust, performant, and cost-efficient AI token factories. Whether you re building the LLM inference infrastructure or the applications that consume it, a deep understanding of LLM serving will make you a more effective, future-ready engineer as AI transforms how we work and build.Learn the foundations of model serving with core concepts, design paradigms, and industry best practicesUnderstand the common challenges of hosting LLMs at scaleBalance latency and throughput to meet the demands of AI applications and business requirementsHost LLMs cost-effectively with practical, code-backed techniques
Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvPeiheng Hu,Chi Wang
E-bok
PDF, Engelska, 2026
839 kr
Läs direkt efter köp
Large language models (LLMs) are the reasoning engines of modern AI. Today, a major inflection point has arrived: as the world races to deploy AI at scale, model inference has moved to the center of the stack. Welcome to the inference era. Without proper optimization, however, LLMs can be expensive and slow to serve. Hands-On LLM Serving and Optimization is a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on, engineering-focused book, authors Chi Wang and Peiheng Hu combine practical examples, code, and strategies for building robust, performant, and cost-efficient AI token factories. Whether you re building the LLM inference infrastructure or the applications that consume it, a deep understanding of LLM serving will make you a more effective, future-ready engineer as AI transforms how we work and build.Learn the foundations of model serving with core concepts, design paradigms, and industry best practicesUnderstand the common challenges of hosting LLMs at scaleBalance latency and throughput to meet the demands of AI applications and business requirementsHost LLMs cost-effectively with practical, code-backed techniques
Hands-On LLM Serving and Optimization
Hosting LLMs at Scale
AvChi Wang,Peiheng Hu
Häftad, Engelska, 2026
616 kr
Skickas inom 5-8 vardagar
Large language models (LLMs) are rapidly becoming the backbone of AI-driven applications. Without proper optimization, however, LLMs can be expensive to run, slow to serve, and prone to performance bottlenecks. As the demand for real-time AI applications grows, along comes Hands-On Serving and Optimizing LLM Models, a comprehensive guide to the complexities of deploying and optimizing LLMs at scale.In this hands-on book, authors Chi Wang and Peiheng Hu take a real-world approach backed by practical examples and code, and assemble essential strategies for designing robust infrastructures that are equal to the demands of modern AI applications. Whether you're building high-performance AI systems or looking to enhance your knowledge of LLM optimization, this indispensable book will serve as a pillar of your success.Learn the key principles for designing a model-serving system tailored to popular business scenariosUnderstand the common challenges of hosting LLMs at scale while minimizing costsPick up practical techniques for optimizing LLM serving performanceBuild a model-serving system that meets specific business requirementsImprove LLM serving throughput and reduce latencyHost LLMs in a cost-effective manner, balancing performance and resource efficiency

Peiheng Hu – författare

Hands-On LLM Serving and Optimization

Hands-On LLM Serving and Optimization

Hands-On LLM Serving and Optimization

Peiheng Hu – författare

Hands-On LLM Serving and Optimization

Hands-On LLM Serving and Optimization

Hands-On LLM Serving and Optimization