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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

Professionals in a wide variety of industries have adopted digital video conferencing tools as part of their regular meetings with suppliers, colleagues, and customers. Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

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Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning

Note that these APIs use objects as namespaces, alleviating the need for explicit imports. API Gateway supports multiple mechanisms for controlling and managing access to an API. AWS Lambda handles the REST API integration, processing the requests and invoking the appropriate AWS services.

APIs 99
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

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From innovation to impact: How AWS and NVIDIA enable real-world generative AI success

AWS Machine Learning

Its inspiring to see how, together, were enabling customers across industries to confidently move AI into production. To give their users even more flexibility, Perplexity complements their own models with services such as Amazon Bedrock , and provides access to additional state-of-the-art models in their API.

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Enhance customer service efficiency with AI-powered summarization using Amazon Transcribe Call Analytics

AWS Machine Learning

To address these issues, we launched a generative artificial intelligence (AI) call summarization feature in Amazon Transcribe Call Analytics. Simply turn the feature on from the Amazon Transcribe console or using the start_call_analytics_job API. You can upload a call recording in Amazon S3 and start a Transcribe Call Analytics job.

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

AWS Machine Learning

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We also look into how to further use the extracted structured information from claims data to get insights using AWS Analytics and visualization services. Extraction phase.

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Track LLM model evaluation using Amazon SageMaker managed MLflow and FMEval

AWS Machine Learning

SageMaker is a data, analytics, and AI/ML platform, which we will use in conjunction with FMEval to streamline the evaluation process. It functions as a standalone HTTP server that provides various REST API endpoints for monitoring, recording, and visualizing experiment runs. We specifically focus on SageMaker with MLflow.