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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Journey to AI blog

Efforts to further expand the use of emerging technologies to address this ongoing need put responsible artificial intelligence (AI) at the center of possible solutions. IBM ® created an AI assistant named OLGA that offered case categorization, extracted metadata and could help bring cases to faster resolution.

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Discover insights from Amazon S3 with Amazon Q S3 connector 

AWS Machine Learning Blog

Amazon Q is a fully managed, generative artificial intelligence (AI) powered assistant that you can configure to answer questions, provide summaries, generate content, gain insights, and complete tasks based on data in your enterprise. In this example, metadata files including the ACLs are in a folder named Meta.

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Secure your Amazon Kendra indexes with the ACL using a JWT shared secret key

AWS Machine Learning Blog

In the terminal with the AWS Command Line Interface (AWS CLI) or AWS CloudShell , run the following commands to upload the documents and metadata to the data source bucket: aws s3 cp s3://aws-ml-blog/artifacts/building-a-secure-search-application-with-access-controls-kendra/docs.zip. For Metadata files prefix folder location , enter Meta/.

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Search for answers accurately using Amazon Kendra S3 Connector with VPC support

AWS Machine Learning Blog

The Amazon Kendra’s S3 connector supports indexing documents and their associated metadata stored in an S3 bucket. For Description , enter AWS White Paper documentation. Leave Metadata files prefix folder location blank. By default, metadata files are stored in the same directory as the documents. Choose Next.