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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. As you continue to innovate and partner with us to advance the field of generative AI, we’ve curated a diverse range of sessions to support you at every stage of your journey.

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Architect a mature generative AI foundation on AWS

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Generative AI applications seem simpleinvoke a foundation model (FM) with the right context to generate a response. Many organizations have siloed generative AI initiatives, with development managed independently by various departments and lines of businesses (LOBs). This approach facilitates centralized governance and operations.

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Build a scalable AI assistant to help refugees using AWS

AWS Machine Learning Blog

As organizations worldwide seek to use AI for social impact, the Danish humanitarian organization Bevar Ukraine has developed a comprehensive virtual generative AI-powered assistant called Victor, aimed at addressing the pressing needs of Ukrainian refugees integrating into Danish society.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. The following diagram illustrates the conceptual architecture of an AI assistant with Amazon Bedrock IDE.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

The landscape of enterprise application development is undergoing a seismic shift with the advent of generative AI. This intuitive platform enables the rapid development of AI-powered solutions such as conversational interfaces, document summarization tools, and content generation apps through a drag-and-drop interface.

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Llama 4 family of models from Meta are now available in SageMaker JumpStart

AWS Machine Learning Blog

Virginia) AWS Region. These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

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Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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