Generative AI Infrastructure: Scaling and Performance Optimization
Vemula, Anand
- 出版商: Independently Published
- 出版日期: 2024-07-22
- 售價: $870
- 貴賓價: 9.5 折 $827
- 語言: 英文
- 頁數: 70
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798333789389
- ISBN-13: 9798333789389
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相關分類:
人工智慧
海外代購書籍(需單獨結帳)
相關主題
商品描述
"Generative AI Infrastructure: Scaling and Performance Optimization" provides a comprehensive guide to the essential components and best practices for building, maintaining, and optimizing the infrastructure required for generative AI systems. The book is designed for AI practitioners, system architects, and IT professionals who aim to harness the full potential of generative AI technologies in a scalable and efficient manner.
The book begins with an introduction to generative AI, covering its fundamental concepts and the importance of robust infrastructure in supporting AI workloads. It explores various generative models, including GANs and VAEs, and their diverse applications across industries such as healthcare, finance, and creative arts.
A deep dive into hardware for generative AI follows, emphasizing the role of high-performance computing (HPC) and specialized processors like GPUs and TPUs. It also discusses the importance of suitable storage solutions and networking requirements to handle large datasets and intensive computations.
The cloud infrastructure section delves into the offerings of major cloud providers like AWS, Azure, and Google Cloud, and provides practical guidance on setting up and managing AI workloads in the cloud. Topics such as cost management, data management, and the implementation of data pipelines are thoroughly covered, along with the latest storage architectures and data preprocessing techniques.
In the chapters on scalability and performance optimization, readers will learn strategies for scaling AI workloads, tuning generative models for peak performance, and managing resources effectively. This includes insights into load balancing, resource allocation, and troubleshooting common issues.
The book also addresses crucial aspects of security and compliance, providing best practices for securing AI infrastructure and ensuring adherence to regulatory requirements. Case studies in healthcare, finance, and creative industries illustrate real-world applications and the impact of generative AI.
Concluding with a look at future directions, the book highlights emerging technologies and trends that will shape the future of AI infrastructure. With a focus on practical implementation and optimization, "Generative AI Infrastructure: Scaling and Performance Optimization" is an indispensable resource for anyone involved in developing and deploying generative AI solutions.
商品描述(中文翻譯)
《生成式 AI 基礎設施:擴展與性能優化》提供了一個全面的指南,涵蓋了構建、維護和優化生成式 AI 系統所需基礎設施的基本組件和最佳實踐。本書旨在幫助 AI 從業人員、系統架構師和 IT 專業人士以可擴展和高效的方式充分利用生成式 AI 技術的潛力。
本書首先介紹生成式 AI,涵蓋其基本概念以及穩健基礎設施在支持 AI 工作負載中的重要性。接著探討各種生成模型,包括 GANs 和 VAEs,以及它們在醫療、金融和創意藝術等行業的多樣應用。
隨後深入探討生成式 AI 的硬體,強調高性能計算 (HPC) 和專用處理器如 GPU 和 TPU 的角色。還討論了適合的儲存解決方案和網路需求,以處理大型數據集和密集計算的重要性。
雲基礎設施部分深入探討了主要雲服務提供商如 AWS、Azure 和 Google Cloud 的產品,並提供了在雲中設置和管理 AI 工作負載的實用指導。涵蓋了成本管理、數據管理和數據管道實施等主題,並詳細介紹了最新的儲存架構和數據預處理技術。
在擴展性和性能優化的章節中,讀者將學習擴展 AI 工作負載的策略、調整生成模型以達到最佳性能以及有效管理資源的技巧。這包括負載平衡、資源分配和排除常見問題的見解。
本書還涉及安全性和合規性的重要方面,提供了保護 AI 基礎設施和確保遵守法規要求的最佳實踐。醫療、金融和創意產業的案例研究展示了生成式 AI 的實際應用及其影響。
最後,本書展望未來方向,強調將塑造 AI 基礎設施未來的新興技術和趨勢。專注於實際實施和優化,《生成式 AI 基礎設施:擴展與性能優化》是任何參與開發和部署生成式 AI 解決方案的人的必備資源。