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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. Opportunities for innovation CreditAI by Octus version 1.x

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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! are the sessions dedicated to AWS DeepRacer ! Generative AI is at the heart of the AWS Village this year. You marked your calendars, you booked your hotel, and you even purchased the airfare. And last but not least (and always fun!)

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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. Solution components In this section, we discuss two key components to the solution: the data sources and vector database. There is also an automated ingestion job from Slack conversation data to the S3 bucket powered by an AWS Lambda function.

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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning Blog

You may check out additional reference notebooks on aws-samples for how to use Meta’s Llama models hosted on Amazon Bedrock. You can implement these steps either from the AWS Management Console or using the latest version of the AWS Command Line Interface (AWS CLI). Solutions Architect at AWS. Varun Mehta is a Sr.

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Designing generative AI workloads for resilience

AWS Machine Learning Blog

Consider the following picture, which is an AWS view of the a16z emerging application stack for large language models (LLMs). Ingesting from these sources is different from the typical data sources like log data in an Amazon Simple Storage Service (Amazon S3) bucket or structured data from a relational database.

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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

Overall, implementing a modern data architecture and generative AI techniques with AWS is a promising approach for gleaning and disseminating key insights from diverse, expansive data at an enterprise scale. AWS also offers foundation models through Amazon SageMaker JumpStart as Amazon SageMaker endpoints.