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Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI

AWS Machine Learning - AI

In this post, we show you how to build a speech-capable order processing agent using Amazon Lex, Amazon Bedrock, and AWS Lambda. Solution overview The following diagram illustrates our solution architecture. This can be done with a Lambda layer or by using a specific AMI with the required libraries. awscli>=1.29.57

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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning - AI

The following diagram illustrates the solution architecture. Amazon SQS enables a fault-tolerant decoupled architecture. The WebSocket triggers an AWS Lambda function, which creates a record in Amazon DynamoDB. Another Lambda function gets triggered with a new message in the SQS queue.

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Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning - AI

API gateways can provide loose coupling between model consumers and the model endpoint service, and flexibility to adapt to changing model, architectures, and invocation methods. In this post, we show you how to build an internal SaaS layer to access foundation models with Amazon Bedrock in a multi-tenant (team) architecture.

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Building Generative AI prompt chaining workflows with human in the loop

AWS Machine Learning - AI

In this blog post, you will learn about prompt chaining, how to break a complex task into multiple tasks to use prompt chaining with an LLM in a specific order, and how to involve a human to review the response generated by the LLM. It invokes an AWS Lambda function with a token and waits for the token.

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Dynamic Routing with AWS Lambda@Edge

LaunchDarkly

Originally published by on TrueCar’s blog, Driven by Code , on April 11th, 2019. Not only did TrueCar need to move their domain DNS entries, they also needed to revamp their entire architecture, software, and operational practices. We also included a range key for the URI part of the request.

Lambda 72
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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning - AI

The following architecture diagram illustrates how you can use the Amazon Titan Multimodal Embeddings model with documents in an Amazon Simple Storage Service (Amazon S3) bucket for image gallery creation. An Amazon S3 object notification event invokes the embedding AWS Lambda function.

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Announcing GA of DataFlow Functions

Cloudera

DFF provides an efficient, cost optimized, scalable way to run NiFi flows in a completely serverless fashion. Now, they can use DataFlow’s no-code UI to be more productive – they can quickly design new NiFi flows and then run them as functions in AWS Lambda, Azure Functions, and Google Cloud Functions. DataFlow Deployments.