Use no-code machine learning to derive insights from product reviews using Amazon SageMaker Canvas sentiment analysis and text analysis models

According to Gartner, 85% of software buyers trust online reviews as much as personal recommendations. Customers provide feedback and reviews about products they have purchased through many channels, including review websites, vendor websites, sales calls, social media, and many others. …

How United Airlines built a cost-efficient Optical Character Recognition active learning pipeline

In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active learning framework on AWS to automate the processing of passenger documents.

“In order to deliver the best flying experience for

Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

Multi-modal data is a valuable component of the financial industry, encompassing market, economic, customer, news and social media, and risk data. Financial organizations generate, collect, and use this data to gain insights into financial operations, make better decisions, and improve …

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 …

Build a secure enterprise application with Generative AI and RAG using Amazon SageMaker JumpStart

Generative AI is a type of AI that can create new content and ideas, including conversations, stories, images, videos, and music. It’s powered by large language models (LLMs) that are pre-trained on vast amounts of data and commonly referred to …

Enhancing AWS intelligent document processing with generative AI

Data classification, extraction, and analysis can be challenging for organizations that deal with volumes of documents. Traditional document processing solutions are manual, expensive, error prone, and difficult to scale. AWS intelligent document processing (IDP), with AI services such as Amazon …

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning. Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. Amazon Rekognition is a fully …

AWS offers new artificial intelligence, machine learning, and generative AI guides to plan your AI strategy

Breakthroughs in artificial intelligence (AI) and machine learning (ML) have been in the headlines for months—and for good reason. The emerging and evolving capabilities of this technology promises new business opportunities for customer across all sectors and industries. But the …

Interactively fine-tune Falcon-40B and other LLMs on Amazon SageMaker Studio notebooks using QLoRA

Fine-tuning large language models (LLMs) allows you to adjust open-source foundational models to achieve improved performance on your domain-specific tasks. In this post, we discuss the advantages of using Amazon SageMaker notebooks to fine-tune state-of-the-art open-source models. We utilize Hugging …

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