Remove Accountability Remove APIs Remove industry standards
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Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

AWS Machine Learning

The solution uses the FMs tool use capabilities, accessed through the Amazon Bedrock Converse API. This enables the FMs to not just process text, but to actively engage with various external tools and APIs to perform complex document analysis tasks. For more details on how tool use works, refer to The complete tool use workflow.

APIs 91
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Security best practices to consider while fine-tuning models in Amazon Bedrock

AWS Machine Learning

The workflow steps are as follows: The user submits an Amazon Bedrock fine-tuning job within their AWS account, using IAM for resource access. The fine-tuning job initiates a training job in the model deployment accounts. Provide your account, bucket name, and VPC settings. Choose Create policy.

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Getting Data from your WFM System

Call Design

Most systems now have a web application and APIs that will allow some, if not all, required data to be collected and aggregated via a webservice. A webservice can minimise this risk by allowing an additional business layer that can handle multiple users and accounts and limit access to only what the webservice requires. Maintenance.

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Here are some features which we will cover: AWS CloudFormation support Private network policies for Amazon OpenSearch Serverless Multiple S3 buckets as data sources Service Quotas support Hybrid search, metadata filters, custom prompts for the RetreiveAndGenerate API, and maximum number of retrievals.

APIs 126
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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Using Agents for Amazon Bedrock to interactively generate infrastructure as code

AWS Machine Learning

This solution uses Retrieval Augmented Generation (RAG) to ensure the generated scripts adhere to organizational needs and industry standards. In this blog post, we explore how Agents for Amazon Bedrock can be used to generate customized, organization standards-compliant IaC scripts directly from uploaded architecture diagrams.

Scripts 138
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Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning

The translation playground could be adapted into a scalable serverless solution as represented by the following diagram using AWS Lambda , Amazon Simple Storage Service (Amazon S3), and Amazon API Gateway. The project also requires that the AWS account is bootstrapped to allow the deployment of the AWS CDK stack.