AWS Machine Learning Blog

APRIL 3, 2024

We detail the steps to use an Amazon Titan Multimodal Embeddings model to encode images and text into embeddings, ingest embeddings into an OpenSearch Service index, and query the index using the OpenSearch Service k-nearest neighbors (k-NN) functionality. Virginia) and US West (Oregon) AWS Regions.

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K-nearest Neighbors AWS Machine Learning Machine Learning 102

Flipboard

NOVEMBER 17, 2023

This type of data is often used in ML and artificial intelligence applications. 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. As always, AWS welcomes feedback.

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K-nearest Neighbors AWS Clustering Database 126

AWS Machine Learning Blog

APRIL 19, 2024

We stored the embeddings in a vector database and then used the Large Language-and-Vision Assistant (LLaVA 1.5-7b) We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this post, we demonstrate a different approach. The models are enabled for use immediately.

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AWS ML ML Database 103

AWS Machine Learning Blog

NOVEMBER 9, 2023

Formally, often k-nearest neighbors (KNN) or approximate nearest neighbor (ANN) search is often used to find other snippets with similar semantics. In these two studies, commissioned by AWS, developers were asked to create a medical software application in Java that required use of their internal libraries.

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AWS Natural Language Processing K-nearest Neighbors AI 84

AWS Machine Learning Blog

FEBRUARY 10, 2023

We design a K-Nearest Neighbors (KNN) classifier to automatically identify these plays and send them for expert review. Prior to AWS, he obtained his MCS from West Virginia University and worked as computer vision researcher at Midea. He is broadly interested in Deep Learning and Natural Language Processing.

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ML ML Machine Learning Machine Learning 66