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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning - AI

For more information on Mixtral-8x7B Instruct on AWS, refer to Mixtral-8x7B is now available in Amazon SageMaker JumpStart. Another challenge with RAG is that with retrieval, you aren’t aware of the specific queries that your document storage system will deal with upon ingestion. This identity is called the AWS account root user.

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What’s Free at Linux Academy — March 2019

Linux Academy

By adding free cloud training to our Community Membership, students have the opportunity to develop their Linux and cloud skills further. Each month, we will kick off our community content with a live study group, allowing members of the Linux Academy community to come together and share their insights in order to learn from one another.

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The Definitive Guide to Achieve AWS Cloud Certification

Linux Academy

Getting AWS certified can be a daunting task, but luckily we’re in your corner and we’re going to help you pass. We offer tons of AWS content for the different exams, but this month the Cloud Practitioner will be our focus. First, you should determine why you want to get AWS certified. AWS’ own recommendations.

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Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock

AWS Machine Learning - AI

In this post, we demonstrate a solution using Amazon FSx for NetApp ONTAP with Amazon Bedrock to provide a RAG experience for your generative AI applications on AWS by bringing company-specific, unstructured user file data to Amazon Bedrock in a straightforward, fast, and secure way. Install the AWS Command Line Interface (AWS CLI).

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

Reduced operational overhead – The EMR Serverless integration with AWS streamlines big data processing by managing the underlying infrastructure, freeing up your team’s time and resources. Runtime roles are AWS Identity and Access Management (IAM) roles that you can specify when submitting a job or query to an EMR Serverless application.

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New Features and Benefits with AWS

Apps Associates

As such we wanted to share the latest features, functionality and benefits of AWS with you. Amazon EC2 now supports sharing Amazon Machine Images across AWS Organizations and Organizational Units – Previously, you could share AMIs only with specific AWS account IDs. Please see highlights below. GB* of data transferred.

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