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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The integration with Amazon Bedrock is achieved through the Amazon Bedrock InvokeModel APIs.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.

APIs 136
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Run text generation with GPT and Bloom models on Amazon SageMaker JumpStart

AWS Machine Learning

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. The following sections provide a step-by-step demo to perform inference, both via the Studio UI and via JumpStart APIs. JumpStart overview. Solution overview.

APIs 104
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Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart

AWS Machine Learning

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. If you want to jump straight into the JumpStart API code we go through in this post, you can refer to the following sample Jupyter notebook: Introduction to JumpStart – Text to Image.

APIs 107
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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

NLP SQL enables business users to analyze data and get answers by typing or speaking questions in natural language, such as the following: “Show total sales for each product last month” “Which products generated more revenue?” In entered the Big Data space in 2013 and continues to explore that area. Nitin Eusebius is a Sr.

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Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs 94