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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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Why you should care about debugging machine learning models

O'Reilly Media - Data

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. We’ll review methods for debugging below. Random attacks can reveal all kinds of unexpected software and math bugs.

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This week in AI: Amazon ‘enhances’ reviews with AI while Snap’s goes rogue

TechCrunch

So until an AI can do it for you, here’s a handy roundup of the last week’s stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own. This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality.

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Are you ready for MLOps? 🫵

Xebia

The time when Hardvard Business Review posted the Data Scientist to be the “Sexiest Job of the 21st Century” is more than a decade ago [1]. Both the tech and the skills are there: Machine Learning technology is by now easy to use and widely available. Why is that? … that does not make things easier.

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AI & the enterprise: protect your data, protect your enterprise value

CIO

For example, employees might inadvertently broadcast corporate secrets by inputting sensitive company information or source code into public-facing AI models and chatbots. Maintaining a clear audit trail is essential when data flows through multiple systems, is processed by various groups, and undergoes numerous transformations.

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Integrate foundation models into your code with Amazon Bedrock

AWS Machine Learning - AI

In this post, we explore how to integrate Amazon Bedrock FMs into your code base, enabling you to build powerful AI-driven applications with ease. For this post, we run the code in a Jupyter notebook within VS Code and use Python. This client will serve as the entry point for interacting with Amazon Bedrock FMs.