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

AWS Machine Learning

To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle. 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.

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

AWS Machine Learning

Their results speak for themselvesAdobe achieved a 20-fold scale-up in model training while maintaining the enterprise-grade performance and reliability their customers expect. ServiceNows innovative AI solutions showcase their vision for enterprise-specific AI optimization. times lower latency compared to other platforms.

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

AWS Machine Learning

These insights are stored in a central repository, unlocking the ability for analytics teams to have a single view of interactions and use the data to formulate better sales and support strategies. With Lambda integration, we can create a web API with an endpoint to the Lambda function.

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AI Workforce: using AI and Drones to simplify infrastructure inspections

AWS Machine Learning

Each drone follows predefined routes, with flight waypoints, altitude, and speed configured through an AWS API, using coordinates stored in Amazon DynamoDB. API Gateway plays a complementary role by acting as the main entry point for external applications, dashboards, and enterprise integrations.

APIs 100
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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 103
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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. We are looking forward to bringing this valuable capability into the hands of many more large enterprises.” This can make it challenging to scale quality management within the contact center.

Analytics 116
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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.