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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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Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

AWS Machine Learning - AI

AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment. We also demonstrate how to test the solution and monitor performance, and discuss options for scaling and multi-tenancy.

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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. The generative AI playground is a UI provided to tenants where they can run their one-time experiments, chat with several FMs, and manually test capabilities such as guardrails or model evaluation for exploration purposes.

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CodeSOD: The Load Balancer Got Terned Off

The Daily WTF

This mostly works fine for the organization, but one day it started deleting their load balancer off of AWS for no good reason. This is probably a typo that got munged until it was syntactically valid, and when the person writing it ran their tests, it probably worked just fine with the testing parameters they used.

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Responsible AI in action: How Data Reply red teaming supports generative AI safety on AWS

AWS Machine Learning - AI

At Data Reply and AWS, we are committed to helping organizations embrace the transformative opportunities generative AI presents, while fostering the safe, responsible, and trustworthy development of AI systems. Red teaming is a methodology used to test and evaluate systems by simulating real-world adversarial conditions.

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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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Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI

AWS Machine Learning - AI

The following figure illustrates the performance of DeepSeek-R1 compared to other state-of-the-art models on standard benchmark tests, such as MATH-500 , MMLU , and more. Additionally, SageMaker endpoints support automatic load balancing and autoscaling, enabling your LLM deployment to scale dynamically based on incoming requests.