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How to Launch a Knowledge Management System (KMS)

CSM Magazine

Success in business today is becoming more dependent on a company’s ability to acquire, manage and utilize important information that is relative to their products, services, vendors, competitors, customers and potential customers. The best tool that businesses can use to fully manage this data is a knowledge management system (KMS).

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Large language model inference over confidential data using AWS Nitro Enclaves

AWS Machine Learning

In this post, we discuss how Leidos worked with AWS to develop an approach to privacy-preserving large language model (LLM) inference using AWS Nitro Enclaves. In this post, we discuss how Leidos worked with AWS to develop an approach to privacy-preserving large language model (LLM) inference using AWS Nitro Enclaves.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

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Get to production-grade data faster by using new built-in interfaces with Amazon SageMaker Ground Truth Plus

AWS Machine Learning

Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. Separately, all the projects used the same IAM role for accessing data.

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

AWS Machine Learning

The AWS Well-Architected Framework provides best practices and guidelines for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework.

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Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector database on AWS Marketplace

AWS Machine Learning

Despite their wealth of general knowledge, state-of-the-art LLMs only have access to the information they were trained on. Therefore, it’s crucial to bridge the gap between the LLM’s general knowledge and your proprietary data to help the model generate more accurate and contextual responses while reducing the risk of hallucinations.

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How Mendix is transforming customer experiences with generative AI and Amazon Bedrock

AWS Machine Learning

This post was co-written with Ricardo Perdigao, Solution Architecture Manager at Mendix, a Siemens business. Since 2005, we’ve helped thousands of organizations worldwide reimagine how they develop applications with our platform’s cutting-edge capabilities. Mendix has been named an industry leader by Gartner and Forrester.