Название: GenAI on Google Cloud: Enterprise Generative AI Systems and Agents (Early Release)Автор: Ayo Adedeji, Lavi Nigam, Sarita Joshi, Stephanie Gervasi
Издательство: O’Reilly Media, Inc.
Год: 2025-06-10
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
In today's AI landscape, success depends not just on using large language models but on moving them into production in a way that's scalable, compliant, and cost-effective. GenAI on Google Cloud: Enterprise Generative AI Systems and Agents is your hands-on guide to bridging that gap. Whether you're an ML engineer tackling your first multi-agent application or a product leader responsible for scaling a GenAI strategy, this book offers a practical game plan for taking your LLM applications from promising prototype to enterprise-grade solution.
Written by practitioners with deep experience in MLOps, data engineering, and GenAI infrastructure, this guide takes you through real-world workflows using Google Cloud's Vertex AI—from training and deployment to monitoring and integration. With concrete examples, field-tested frameworks, and honest insights about what actually works, you'll learn how to build production systems that deliver measurable business value.
The objective for this first chapter is to introduce you to the unique complexities of building and deploying applications powered by large language models (LLMs). We hope this chapter will prepare you for subsequent deeper discussions of LLM operations (LLMOps) - really, a specialized type of machine learning operations (MLOps), which includes the behind-the-scenes work and set of best practices for managing the entire lifecycle of LLMs, from building and testing to deploying and responsibly maintaining these powerful AI language models in production.
Bridge the prototype-to-production chasm that stalls 75% of LLM projects using systematic frameworks developed across hundreds of deployments
Navigate the unique complexities of LLM operations through practical guidance on data orchestration, evaluation frameworks, and responsible AI practices
Build enterprise-grade multimodal systems that handle text, images, and video with robust agent architectures and tool integration
Implement proven optimization strategies for cost management, performance tuning, and production monitoring at scale
Apply battle-tested patterns from practitioners who've guided organizations through both breakthrough successes and costly failures
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