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

AWS Machine Learning

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

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Improving asset health and grid resilience using machine learning

AWS Machine Learning

In this blog post, we demonstrate how Duke Energy , a Fortune 150 company headquartered in Charlotte, NC., This goal will further help Duke Energy to improve grid resiliency and comply with government regulations by identifying the defects in a timely manner. Lower recall can lead to outages and government regulation violations.

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Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

This is a guest blog post cowritten with athenahealth. In the artificial intelligence (AI) space, athenahealth uses data science and machine learning (ML) to accelerate business processes and provide recommendations, predictions, and insights across multiple services.