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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. The AWS deployment architecture makes sure the Python application is hosted and accessible from the internet to authenticated users.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

An example is a virtual assistant for enterprise business operations. Such a virtual assistant should support users across various business functions, such as finance, legal, human resources, and operations. Before migrating any of the provided solutions to production, we recommend following the AWS Well-Architected Framework.

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Discover, Protect and Respond with AWS and Prisma Cloud

Prisma Clud

Organizations are increasingly turning to cloud providers, like Amazon Web Services (AWS), to address these challenges and power their digital transformation initiatives. However, the vastness of AWS environments and the ease of spinning up new resources and services can lead to cloud sprawl and ongoing security risks.

AWS 105
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. You can use AWS services such as Application Load Balancer to implement this approach. They’re illustrated in the following figure.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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Boost productivity by using AI in cloud operational health management

AWS Machine Learning - AI

It uses Amazon Bedrock , AWS Health , AWS Step Functions , and other AWS services. Some examples of AWS-sourced operational events include: AWS Health events — Notifications related to AWS service availability, operational issues, or scheduled maintenance that might affect your AWS resources.

Cloud 97
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Lumigo raises $29M for its cloud-native application monitoring platform

TechCrunch

The company started with a focus on distributed tracing for serverless platforms like AWS’ API Gateway, DynamoDB, S3 and Lambda. But as the team announced today, it is now also expanding its SaaS service to cover containers and virtual machines. Image Credits: Lumigo.