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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. An interactive chat interface allows deeper exploration of both the original document and generated content.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help. In this post, we demonstrate how to leverage the new EMR Serverless integration with SageMaker Studio to streamline your data processing and machine learning workflows.

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Leveraging Serverless and Generative AI for Image Captioning on GCP

Xebia

Leveraging Serverless and Generative AI for Image Captioning on GCP In today’s age of abundant data, especially visual data, it’s imperative to understand and categorize images efficiently. TL;DR We’ve built an automated, serverless system on Google Cloud Platform where: Users upload images to a Google Cloud Storage Bucket.

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Unleash the power of generative AI with Amazon Q Business: How CCoEs can scale cloud governance best practices and drive innovation

AWS Machine Learning - AI

With Amazon Q Business , Hearst’s CCoE team built a solution to scale cloud best practices by providing employees across multiple business units self-service access to a centralized collection of documents and information. User authorization for documents within the individual S3 buckets were controlled through access control lists (ACLs).

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

As successful proof-of-concepts transition into production, organizations are increasingly in need of enterprise scalable solutions. For latest information, please refer to the documentation above. VectorIngestionConfiguration – Contains details about how to ingest the documents in a data source.

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability.

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Software infrastructure 2.0: a wishlist

Erik Bernhardsson

Truly serverless. Serverless doesn't mean it's a burstable VM that saves its instance state to disk during periods of idle. I'm dreaming of a world where things are truly serverless. Eventually, it evolves into its own super-custom DSL with its own documentation. Can't wait. I don't want to pay for idle resources.