AWS Machine Learning Blog

Category: Amazon OpenSearch Service

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

This post is co-written with Tim Camara, Senior Product Manager at Veritone. Veritone is an artificial intelligence (AI) company based in Irvine, California. Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. It offers solutions for media transcription, facial recognition, content summarization, object […]

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

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.

Unlock personalized experiences powered by AI using Amazon Personalize and Amazon OpenSearch Service

OpenSearch is a scalable, flexible, and extensible open source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 license. Amazon OpenSearch Service is a fully managed service that makes it straightforward to deploy, scale, and operate OpenSearch in the AWS Cloud. OpenSearch uses a probabilistic ranking framework called BM-25 […]

High Level Retrieval Augmented Generation Architecture

Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

May 2024: This post was reviewed and updated in to provide the chatbot application’s infrastructure as code using the AWS CDK. Modern chatbots can serve as digital agents, providing a new avenue for delivering 24/7 customer service and support across many industries. Their popularity stems from the ability to respond to customer inquiries in real […]

Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 1

With the advent of generative AI, today’s foundation models (FMs), such as the large language models (LLMs) Claude 2 and Llama 2, can perform a range of generative tasks such as question answering, summarization, and content creation on text data. However, real-world data exists in multiple modalities, such as text, images, video, and audio. Take […]

Easily build semantic image search using Amazon Titan

Digital publishers are continuously looking for ways to streamline and automate their media workflows to generate and publish new content as rapidly as they can, but without foregoing quality. Adding images to capture the essence of text can improve the reading experience. Machine learning techniques can help you discover such images. “A striking image is […]

RAG -Retrieval Augmented Generation

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

The financial service (FinServ) industry has unique generative AI requirements related to domain-specific data, data security, regulatory controls, and industry compliance standards. In addition, customers are looking for choices to select the most performant and cost-effective machine learning (ML) model and the ability to perform necessary customization (fine-tuning) to fit their business use cases. Amazon […]

Personalize your search results with Amazon Personalize and Amazon OpenSearch Service integration

Amazon Personalize has launched a new integration with Amazon OpenSearch Service that enables you to personalize search results for each user and assists in predicting their search needs. The Amazon Personalize Search Ranking plugin within OpenSearch Service allows you to improve the end-user engagement and conversion from your website and app search by taking advantage […]

Implement smart document search index with Amazon Textract and Amazon OpenSearch

In this post, we’ll take you on a journey to rapidly build and deploy a document search indexing solution that helps your organization to better harness and extract insights from documents. Whether you’re in Human Resources looking for specific clauses in employee contracts, or a financial analyst sifting through a mountain of invoices to extract payment data, this solution is tailored to empower you to access the information you need with unprecedented speed and accuracy.

Semantic image search for articles using Amazon Rekognition, Amazon SageMaker foundation models, and Amazon OpenSearch Service

Digital publishers are continuously looking for ways to streamline and automate their media workflows in order to generate and publish new content as rapidly as they can. Publishers can have repositories containing millions of images and in order to save money, they need to be able to reuse these images across articles. Finding the image that best matches an article in repositories of this scale can be a time-consuming, repetitive, manual task that can be automated. It also relies on the images in the repository being tagged correctly, which can also be automated (for a customer success story, refer to Aller Media Finds Success with KeyCore and AWS). In this post, we demonstrate how to use Amazon Rekognition, Amazon SageMaker JumpStart, and Amazon OpenSearch Service to solve this business problem.