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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

AWS Machine Learning

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. It uses the Vector Search index and performs a semantic search on the vector data store.

APIs 115
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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

Before you get started, refer to Part 1 for a high-level overview of the insurance use case with IDP and details about the data capture and classification stages. In Part 1, we saw how to use Amazon Textract APIs to extract information like forms and tables from documents, and how to analyze invoices and identity documents.

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Design secure generative AI application workflows with Amazon Verified Permissions and Amazon Bedrock Agents

AWS Machine Learning

Agents automatically call the necessary APIs to interact with the company systems and processes to fulfill the request. The App calls the Claims API Gateway API to run the claims proxy passing user requests and tokens. Claims API Gateway runs the Custom Authorizer to validate the access token.

APIs 83
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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 81
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How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

When the message is received by the SQS queue, it triggers the AWS Lambda function to make an API call to the Amp catalog service. The Lambda function retrieves the desired show metadata, filters the metadata, and then sends the output metadata to Amazon Kinesis Data Streams. Data Engineer for Amp on Amazon.

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MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

To implement ML pipelines, data scientists (or ML engineers) use SageMaker Pipelines. A SageMaker pipeline is a series of interconnected steps (SageMaker processing jobs, training, HPO) that is defined by a JSON pipeline definition using a Python SDK. This pipeline definition encodes a pipeline using a Directed Acyclic Graph (DAG).

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Exploring The Restaurant of Tomorrow at FSTEC

Interactions

Although they still own the two largest shares of this fragmented market, there’s a definite trend toward more open providers – particularly those that were born in the cloud (like Toast or Upserve ). A big point of discussion during breakout sessions and over drinks (yes, really!)

APIs 70