Generative AI on Aws: Building Context-Aware Multimodal Reasoning Applications (Paperback)
暫譯: 在 AWS 上的生成式 AI:構建具上下文感知的多模態推理應用程式 (平裝本)

Fregly, Chris, Barth, Antje, Eigenbrode, Shelbee

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商品描述

Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. In this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, machine learning practitioners, business analysts, data engineers, and data scientists find a practical way to use this exciting new technology.

You'll learn the generative AI project lifecycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation (RAG), reinforcement learning from human feedback (RLHF), model quantization, optimization, and deployment. You'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and video. You'll also be able to make better-informed decisions for your company regarding generative AI and learn how to build working prototypes quickly. While the focus is on AWS, this book is a great resource for learning generative AI fundamentals and applying these models to real-world applications.

  • Apply generative AI to your business use cases
  • Determine which generative AI models to use based on the task
  • Perform prompt engineering and in-context learning
  • Fine-tune generative AI models on your datasets
  • Align generative AI models to human values with reinforcement learning from human feedback
  • Use techniques like retrieval-augmented generation to augment your model
  • Explore libraries such as LangChain and React to develop agents and actions
  • Learn about multimodal models such as Stable Diffusion for image and video generation
  • Get hands-on with Amazon Bedrock, the AWS generative AI managed service

商品描述(中文翻譯)

公司如今正迅速將生成式人工智慧整合到他們的產品和服務中。然而,對於這項技術的影響和潛力存在著大量的炒作(和誤解)。在這本書中,來自AWS的Chris Fregly、Antje Barth和Shelbee Eigenbrode幫助首席技術官(CTO)、機器學習從業者、商業分析師、數據工程師和數據科學家找到實用的方法來使用這項令人興奮的新技術。

您將學習生成式人工智慧的專案生命週期,包括用例定義、模型選擇、模型微調、檢索增強生成(RAG)、來自人類反饋的強化學習(RLHF)、模型量化、優化和部署。您將探索不同類型的模型,包括大型語言模型(LLMs)和多模態模型,例如用於生成圖像和視頻的Stable Diffusion。您還將能夠為您的公司做出更明智的生成式人工智慧決策,並學習如何快速構建可運行的原型。雖然重點在於AWS,但這本書是學習生成式人工智慧基礎知識並將這些模型應用於實際應用的絕佳資源。

- 將生成式人工智慧應用於您的商業用例
- 根據任務確定使用哪些生成式人工智慧模型
- 執行提示工程和上下文學習
- 在您的數據集上微調生成式人工智慧模型
- 通過來自人類反饋的強化學習使生成式人工智慧模型與人類價值觀對齊
- 使用檢索增強生成等技術來增強您的模型
- 探索如LangChain和React等庫以開發代理和行動
- 了解如Stable Diffusion等多模態模型以生成圖像和視頻
- 實際操作Amazon Bedrock,AWS的生成式人工智慧管理服務