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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. Conversely, a cache collision happens when multiple prompts are mapped to the same cache location due to similarities in their semantic features.

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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).

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Serverless and Edge Runtime Part 2

Apiumhub

This is the second post in a two-part series exploring the world of Serverless and Edge Runtime. In the previous post, we got familiar with serverless; the main focus of this post will be the Edge Runtime, where it can be useful, and what its caveats are. Edge, the Location: the concept of running servers closer to our users.

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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. All the code for this post is available in the GitHub repo. Review and prepare the dataset.

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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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Build a contextual chatbot for financial services using Amazon SageMaker JumpStart, Llama 2 and Amazon OpenSearch Serverless with Vector Engine

AWS Machine Learning - AI

Advantages of using SageMaker JumpStart With SageMaker JumpStart, ML practitioners can choose from a broad selection of state-of-the-art models for use cases such as content writing, image generation, code generation, question answering, copywriting, summarization, classification, information retrieval, and more.

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Connect the Amazon Q Business generative AI coding companion to your GitHub repositories with Amazon Q GitHub (Cloud) connector

AWS Machine Learning - AI

For example, using an AI-based coding companion such as Amazon Q Developer can boost development productivity by up to 30 percent. GitHub (Cloud) is a popular development platform that helps teams build, scale, and deliver software used by more than 100 million developers and over 4 million organizations worldwide.