Remove Authentication Remove Lambda Remove Scalability
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. This request contains the user’s message and relevant metadata.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. For Authentication method , choose API Keys (Max.

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Building a virtual meteorologist using Amazon Bedrock Agents

AWS Machine Learning - AI

Although weather information is accessible through multiple channels, businesses that heavily rely on meteorological data require robust and scalable solutions to effectively manage and use these critical insights and reduce manual processes. Solution overview The diagram gives an overview and highlights the key components.

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

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. This scalability allows for more frequent and comprehensive reviews.

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Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker

AWS Machine Learning - AI

Annotators can precisely mark and evaluate specific moments in audio or video content, helping models understand what makes content feel authentic to human viewers and listeners. Pre-annotation and post-annotation AWS Lambda functions are optional components that can enhance the workflow. Give your job a name.

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Build scalable Low-Code backends with Booster

The Agile Monkey

However, these tools may not be suitable for more complex data or situations requiring scalability and robust business logic. In short, Booster is a Low-Code TypeScript framework that allows you to quickly and easily create a backend application in the cloud that is highly efficient, scalable, and reliable. protocol for authentication.