Remove AWS Remove Examples Remove Serverless
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Serverless, it can help you brew beer

Xebia

Plus, when you have a practical example, it’s also easier to explain to my wife and friends. How does Serverless help? Due to this requirement, I used the API Gateway service from AWS. Conclusion Real-world examples help illustrate our options for serverless technology. But some steps can be automated!

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning - AI

For example, searching for a specific red leather handbag with a gold chain using text alone can be cumbersome and imprecise, often yielding results that don’t directly match the user’s intent. Store embeddings : Ingest the generated embeddings into an OpenSearch Serverless vector index, which serves as the vector database for the solution.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. The AWS deployment architecture makes sure the Python application is hosted and accessible from the internet to authenticated users.

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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 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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Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

This post discusses how to use AWS Step Functions to efficiently coordinate multi-step generative AI workflows, such as parallelizing API calls to Amazon Bedrock to quickly gather answers to lists of submitted questions. Our pricing model varies depending on the project, but we always aim to provide cost-effective solutions.

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How AWS sales uses Amazon Q Business for customer engagement

AWS Machine Learning - AI

Earlier this year, we published the first in a series of posts about how AWS is transforming our seller and customer journeys using generative AI. The following screenshot shows an example of an interaction with Field Advisor.

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