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Create a multimodal chatbot tailored to your unique dataset with Amazon Bedrock FMs

AWS Machine Learning Blog

In this post, we show how to create a multimodal chat assistant on Amazon Web Services (AWS) using Amazon Bedrock models, where users can submit images and questions, and text responses will be sourced from a closed set of proprietary documents. For this post, we recommend activating these models in the us-east-1 or us-west-2 AWS Region.

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

Founded in 2013, Octus, formerly Reorg, is the essential credit intelligence and data provider for the worlds leading buy side firms, investment banks, law firms and advisory firms. Along the way, it also simplified operations as Octus is an AWS shop more generally.

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Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning Blog

Yes, the AWS re:Invent season is upon us and as always, the place to be is Las Vegas! Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. are the sessions dedicated to AWS DeepRacer ! are the sessions dedicated to AWS DeepRacer !

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning Blog

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities.

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Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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Learn how to assess the risk of AI systems

Flipboard

While it might be easier to start looking at an individual machine learning (ML) model and the associated risks in isolation, it’s important to consider the details of the specific application of such a model and the corresponding use case as part of a complete AI system. In this post, we focus on AI system risk, primarily.

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Build a multi-interface AI assistant using Amazon Q and Slack with Amazon CloudFront clickable references from an Amazon S3 bucket

AWS Machine Learning Blog

Click here to open the AWS console and follow along. Developed by Todd Gamblin at the Lawrence Livermore National Laboratory in 2013, Spack addresses the limitations of traditional package managers in high-performance computing (HPC) environments. About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services.

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