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Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock

AWS Machine Learning - AI

Given the increasing need for efficient and cost-effective AI solutions, we present a serverless read-through caching blueprint that uses repeated data patterns. With OpenSearch Serverless, you can establish a vector database suitable for setting up a robust cache system.

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Serverless is more than AWS Lambda

Stackery

Too often serverless is equated with just AWS Lambda. Yes, it’s true: Amazon Web Services (AWS) helped to pioneer what is commonly referred to as serverless today with AWS Lambda, which was first announced back in 2015. Lambda is just one component of a modern serverless stack.

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Serverless and Edge Runtime

Apiumhub

This is the introductory post in a two-part series, exploring the world of Serverless and Edge Runtime. The main focus of this post will be Serverless, while the second one will focus on an alternative, newer approach in the form of Edge Computing. Scalability Of course, going serverless is not only for small projects.

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The Future of Serverless is … Functionless?

Stackery

Lately, I’ve seen some talk about an architectural pattern that I believe will become prevalent in the near future. I first heard about this pattern a few years ago at a ServerlessConf from a consultant who was helping a “big bank” convert to serverless. DynamoDB Tables and Aurora Serverless Databases).

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help. In this post, we demonstrate how to leverage the new EMR Serverless integration with SageMaker Studio to streamline your data processing and machine learning workflows.

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Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning - AI

In this post, we show how to build a contextual text and image search engine for product recommendations using the Amazon Titan Multimodal Embeddings model , available in Amazon Bedrock , with Amazon OpenSearch Serverless. The following diagram illustrates the solution architecture. You then display the top similar results.

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Build cost-effective RAG applications with Binary Embeddings in Amazon Titan Text Embeddings V2, Amazon OpenSearch Serverless, and Amazon Bedrock Knowledge Bases

AWS Machine Learning - AI

Today, we are happy to announce the availability of Binary Embeddings for Amazon Titan Text Embeddings V2 in Amazon Bedrock Knowledge Bases and Amazon OpenSearch Serverless. The OpenSearch Serverless kNN plugin now supports 16-bit (FP16) and binary vectors, in addition to 32-bit floating point vectors (FP32). without reranking).