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AWS takes on Nvidia and Amazon shares are loving it

Dataconomy

Amazon Web Services (AWS) announced the launch of a new AI supercomputer, Project Rainier, constructed from its proprietary Trainium chips, aiming to rival Nvidia’s dominance in the AI chip market. Matt Garman, CEO of AWS, stated, “Today, there’s really only one choice on the GPU side, and it’s just Nvidia.

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Enhanced observability for AWS Trainium and AWS Inferentia with Datadog

AWS Machine Learning Blog

AWS AI chips, Trainium and Inferentia, enable you to build and deploy generative AI models at higher performance and lower cost. The Datadog dashboard offers a detailed view of your AWS AI chip (Trainium or Inferentia) performance, such as the number of instances, availability, and AWS Region.

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AWS Lambda

Dataconomy

AWS Lambda is revolutionizing how developers approach cloud applications by enabling them to run code in response to events without the need for server management. With features that automatically adjust to workload demands and an efficient billing model, AWS Lambda is a game changer in cloud computing. What is AWS Lambda?

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Unlocking the power of Model Context Protocol (MCP) on AWS

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If youre an AI-focused developer, technical decision-maker, or solution architect working with Amazon Web Services (AWS) and language models, youve likely encountered these obstacles firsthand. Why MCP matters for AWS users For AWS customers, MCP represents a particularly compelling opportunity. What is the MCP?

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning Blog

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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Implement RAG while meeting data residency requirements using AWS hybrid and edge services

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In this post, we show how to extend Amazon Bedrock Agents to hybrid and edge services such as AWS Outposts and AWS Local Zones to build distributed Retrieval Augmented Generation (RAG) applications with on-premises data for improved model outcomes.

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