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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

Managing bias, intellectual property, prompt safety, and data integrity are critical considerations when deploying generative AI solutions at scale. Because this is an emerging area, best practices, practical guidance, and design patterns are difficult to find in an easily consumable basis.

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Demystifying machine learning at the edge through real use cases

AWS Machine Learning

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. Agriculture, mining, surveillance and security, and maritime transportation are some areas where far edge devices play an important role. Edge computing.

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Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning

This movie is a masterclass in storytelling, with a deep sense of history and culture that will transport you to Middle-earth and leave you wanting more. He supports strategic customers with AI/ML best practices cross many industries. Outside of work, he enjoys reading and traveling.

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Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

About the Authors Charalampos Grouzakis is a Data Scientist within AWS Professional Services. He has over 11 years of experience in developing and leading data science, machine learning, and big data initiatives. Her skills and areas of expertise include data science, machine learning, and big data.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes.

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The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

Avaya

In fact, research shows that about 90% of all data in the world today was created in just the past few years (2.5 billion GB of data were being produced every day in 2012 alone!) Ultimately, end-to-end segmentation transforms your network core into an automated and intelligent virtualized transport.

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

AWS Machine Learning

Amazon Cognito for user authentication with Transport Layer Security (TLS). Data must be utilized, stored, and accessed in specific ways, and we have embedded robust processes to ensure our practices comply with our legal obligations as well as align with industry best practices.