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Announcing New Tools for Building with Generative AI on AWS

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At AWS, we have played a key role in democratizing ML and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. AWS has the broadest and deepest portfolio of AI and ML services at all three layers of the stack.

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Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

AWS Machine Learning Blog

Implementing a multi-modal agent with AWS consolidates key insights from diverse structured and unstructured data on a large scale. All this is achieved using AWS services, thereby increasing the financial analyst’s efficiency to analyze multi-modal financial data (text, speech, and tabular data) holistically.

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

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In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

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AI-powered assistants for investment research with multi-modal data: An application of Agents for Amazon Bedrock

AWS Machine Learning Blog

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. Action groups – Action groups are interfaces that an agent uses to interact with the different underlying components such as APIs and databases.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning Blog

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. In the first post , we described FL concepts and the FedML framework.

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The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning Blog

In this post we highlight how the AWS Generative AI Innovation Center collaborated with the AWS Professional Services and PGA TOUR to develop a prototype virtual assistant using Amazon Bedrock that could enable fans to extract information about any event, player, hole or shot level details in a seamless interactive manner.

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Generate a counterfactual analysis of corn response to nitrogen with Amazon SageMaker JumpStart solutions

AWS Machine Learning Blog

Prerequisites You need an AWS account to use this solution. To run this JumpStart 1P Solution and have the infrastructure deployed to your AWS account, you need to create an active Amazon SageMaker Studio instance (refer to Onboard to Amazon SageMaker Domain ).