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Knowledge Bases for Amazon Bedrock now supports metadata filtering to improve retrieval accuracy

AWS Machine Learning

Metadata filtering overview Prior to the release of metadata filtering, all semantically relevant chunks up to the pre-set maximum would be returned as context for the FM to use to generate a response. Intelligent search for software developers – This allows developers to look for information of a specific release.

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Introducing automatic training for solutions in Amazon Personalize

AWS Machine Learning

Amazon Personalize enables developers to quickly implement a customized personalization engine, without requiring ML expertise. Solution overview A solution refers to the combination of an Amazon Personalize recipe, customized parameters, and one or more solution versions (trained models). Specify a name for your campaign.

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Improving Content Moderation with Amazon Rekognition Bulk Analysis and Custom Moderation

AWS Machine Learning

It’s based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. visit our developer guide. On the Amazon Rekognition console, you can upload the images you want to analyze and get results with a few clicks.

Analysis 100
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Amazon Personalize launches new recipes supporting larger item catalogs with lower latency

AWS Machine Learning

Solution overview To use the User-Personalization-v2 and Personalized-Ranking-v2 recipes, you first need to set up Amazon Personalize resources. For this post, we follow the Amazon Personalize console approach to deploy a campaign. On the Amazon Personalize console, choose Dataset groups in the navigation pane.

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Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning

The implementation used in this post utilizes the Amazon Textract IDP CDK constructs – AWS Cloud Development Kit (CDK) components to define infrastructure for Intelligent Document Processing (IDP) workflows – which allow you to build use case specific customizable IDP workflows. Testing First test using a sample file.

Metrics 98
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Announcing Rekogniton Custom Moderation: Enhance accuracy of pre-trained Rekognition moderation models with your data

AWS Machine Learning

Solution overview Training a custom moderation adapter involves five steps that you can complete using the AWS Management Console or the API interface: Create a project Upload the training data Assign ground truth labels to images Train the adapter Use the adapter Let’s walk through these steps in more detail using the console.

Training 103
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Knowledge Bases for Amazon Bedrock now supports custom prompts for the RetrieveAndGenerate API and configuration of the maximum number of retrieved results

AWS Machine Learning

Overview and benefits of new features The maximum number of results option gives you control over the number of search results to be retrieved from the vector store and passed to the FM for generating the answer. In the following sections, we explain how you can use these features with either the AWS Management Console or SDK.