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AI Summary: A deep-dive architectural guide to building, fine-tuning, and deploying large language models securely and efficiently within the AWS cloud ecosystem.
AI Summary: A deep-dive architectural guide to building, fine-tuning, and deploying large language models securely and efficiently within the AWS cloud ecosystem.
Cloud infrastructure is the backbone of the modern generative AI boom, and AWS remains the dominant platform for enterprise deployment. This book provides a detailed architectural guide to building and scaling LLM applications using Amazon Bedrock, SageMaker, and AWS Trainium hardware. The authors cover essential patterns for retrieval-augmented generation, parameter-efficient fine-tuning (PEFT), and multimodal deployments. It is a critical resource for cloud architects tasked with running high-performance AI workloads cost-effectively.
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