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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

With this solution, you can interact directly with the chat assistant powered by AWS from your Google Chat environment, as shown in the following example. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message.

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Streamlining Workflows with Feature Branches and Logical Stacks

Xebia

This blog explores how to optimize feature branch workflows, maintain encapsulated logical stacks, and apply best practices like resource naming to improve clarity, scalability, and cost-effectiveness. This example applies to the more traditional lift and shift approaches. Simple: In the example, we needed an RDS instance.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, a marketing content creation application might need to perform task types such as text generation, text summarization, sentiment analysis, and information extraction as part of producing high-quality, personalized content. An example is a virtual assistant for enterprise business operations.

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

AWS Machine Learning - AI

We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

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WordFinder app: Harnessing generative AI on AWS for aphasia communication

AWS Machine Learning - AI

Overview of the solution The following screenshot shows an example of navigating the WordFinder app, including sign in, image selection, object definition, and related words. Amplify is a set of tools and services that enable developers to build and deploy secure, scalable, and full stack apps.

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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning - AI

Without a scalable approach to controlling costs, organizations risk unbudgeted usage and cost overruns. This scalable, programmatic approach eliminates inefficient manual processes, reduces the risk of excess spending, and ensures that critical applications receive priority.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

Although the principles discussed are applicable across various industries, we use an automotive parts retailer as our primary example throughout this post. The Lambda function runs the database query against the appropriate OpenSearch Service indexes, searching for exact matches or using fuzzy matching for partial information.

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