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Revolutionizing earth observation with geospatial foundation models on AWS

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It also comes with ready-to-deploy code samples to help you get started quickly with deploying GeoFMs in your own applications on AWS. For a full architecture diagram demonstrating how the flow can be implemented on AWS, see the accompanying GitHub repository. Lets dive in! Solution overview At the core of our solution is a GeoFM.

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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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Ruby on Rails Audit Complete

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Thanks to the help of X41 D-Sec , GitLab , and the Sovereign Tech Agency , Rails can provide more secure versions of the tools needed for users to create database-backed web applications following the Model-View-Controller pattern. Ruby on Rails (or “Rails”) is an open source full stack web-application framework.

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Build a computer vision-based asset inventory application with low or no training

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Solution overview The AI-powered asset inventory labeling solution aims to streamline the process of updating inventory databases by automatically extracting relevant information from asset labels through computer vision and generative AI capabilities. The function updates the asset inventory database with the new extracted data.

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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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