Unlocking the power of Model Context Protocol (MCP) on AWS

Favorite We’ve witnessed remarkable advances in model capabilities as generative AI companies have invested in developing their offerings. Language models such as Anthropic’s Claude Opus 4 & Sonnet 4 and Amazon Nova on Amazon Bedrock can reason, write, and generate responses with increasing sophistication. But even as these models grow

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Shared by AWS Machine Learning June 4, 2025

Fast-track SOP processing using Amazon Bedrock

Favorite Standard operating procedures (SOPs) are essential documents in the context of regulations and compliance. SOPs outline specific steps for various processes, making sure practices are consistent, efficient, and compliant with regulatory standards. SOP documents typically include key sections such as the title, scope, purpose, responsibilities, procedures, documentation, citations (references),

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Shared by AWS Machine Learning June 3, 2025

Streamline personalization development: How automated ML workflows accelerate Amazon Personalize implementation

Favorite Crafting unique, customized experiences that resonate with customers is a potent strategy for boosting engagement and fostering brand loyalty. However, creating dynamic personalized content is challenging and time-consuming because of the need for real-time data processing, complex algorithms for customer segmentation, and continuous optimization to adapt to shifting behaviors

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Shared by AWS Machine Learning June 3, 2025

Bridging the gap between development and production: Seamless model lifecycle management with Amazon Bedrock

Favorite In the landscape of generative AI, organizations are increasingly adopting a structured approach to deploy their AI applications, mirroring traditional software development practices. This approach typically involves separate development and production environments, each with its own AWS account, to create logical separation, enhance security, and streamline workflows. Amazon Bedrock

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Shared by AWS Machine Learning May 31, 2025

Using Amazon OpenSearch ML connector APIs

Favorite When ingesting data into Amazon OpenSearch, customers often need to augment data before putting it into their indexes. For instance, you might be ingesting log files with an IP address and want to get a geographic location for the IP address, or you might be ingesting customer comments and

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Shared by AWS Machine Learning May 31, 2025

Architect a mature generative AI foundation on AWS

Favorite Generative AI applications seem simple—invoke a foundation model (FM) with the right context to generate a response. In reality, it’s a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG)

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Shared by AWS Machine Learning May 31, 2025

Going beyond AI assistants: Examples from Amazon.com reinventing industries with generative AI

Favorite Generative AI revolutionizes business operations through various applications, including conversational assistants such as Amazon’s Rufus and Amazon Seller Assistant. Additionally, some of the most impactful generative AI applications operate autonomously behind the scenes, an essential capability that empowers enterprises to transform their operations, data processing, and content creation at

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Shared by AWS Machine Learning May 31, 2025