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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 Blog

Prerequisites To implement the proposed solution, make sure that you have the following: An AWS account and a working knowledge of FMs, Amazon Bedrock , Amazon SageMaker , Amazon OpenSearch Service , Amazon S3 , and AWS Identity and Access Management (IAM). Amazon Titan Multimodal Embeddings model access in Amazon Bedrock.

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Use language embeddings for zero-shot classification and semantic search with Amazon Bedrock

AWS Machine Learning Blog

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using Amazon Web Services (AWS) services without having to manage infrastructure. AWS Lambda The API is a Fastify application written in TypeScript.

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Retrieval-Augmented Generation with LangChain, Amazon SageMaker JumpStart, and MongoDB Atlas semantic search

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Set up a MongoDB cluster To create a free tier MongoDB Atlas cluster, follow the instructions in Create a Cluster. MongoDB Atlas Vector Search uses a technique called k-nearest neighbors (k-NN) to search for similar vectors. k-NN works by finding the k most similar vectors to a given vector.

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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning Blog

OpenAI launched GPT-4o in May 2024, and Amazon introduced Amazon Nova models at AWS re:Invent in December 2024. The implementation included a provisioned three-node sharded OpenSearch Service cluster. Retrieval (and reranking) strategy FloTorch used a retrieval strategy with a k-nearest neighbor (k-NN) of five for retrieved chunks.

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OfferUp improved local results by 54% and relevance recall by 27% with multimodal search on Amazon Bedrock and Amazon OpenSearch Service

AWS Machine Learning Blog

The listing indexer AWS Lambda function continuously polls the queue and processes incoming listing updates. With Amazon OpenSearch Service, you get a fully managed solution that makes it simple to deploy, scale, and operate OpenSearch in the AWS Cloud. For data handling, 24 data nodes (r6gd.2xlarge.search

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

AWS Machine Learning Blog

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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Power recommendations and search using an IMDb knowledge graph – Part 3

AWS Machine Learning Blog

Many AWS media and entertainment customers license IMDb data through AWS Data Exchange to improve content discovery and increase customer engagement and retention. We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. Background. Solution overview. Prerequisites.

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