Generative Data Intelligence

Tag: Active Learning

Investing in Coactive

Understanding what’s in an image — one of the simplest cognitive tasks for most humans — is a stubbornly difficult problem for artificial intelligence...

Using Amazon SageMaker with Point Clouds: Part 1- Ground Truth for 3D labeling

In this two-part series, we demonstrate how to label and train models for 3D object detection tasks. In part 1, we discuss the dataset...

Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

In recent years, advances in computer vision have enabled researchers, first responders, and governments to tackle the challenging problem of processing global satellite...

High-accuracy Hamiltonian learning via delocalized quantum state evolutions

Davide Rattacaso1, Gianluca Passarelli2, and Procolo Lucignano11Dipartimento di Fisica ``E. Pancini'', Università di Napoli Federico II, Complesso di Monte Sant'Angelo, via Cinthia, Napoli 80126,...

Palo Alto Networks Xpanse Active Attack Surface Management Automatically Remediates Cyber Risks Before They Lead to Cyberattacks

SANTA CLARA, Calif., Dec. 12, 2022 /PRNewswire/ — Cyberattackers today use highly automated methods to quickly find and exploit weaknesses in target organizations — sometimes...

6 Tips for Boosting Learning Retention Rate In eLearning Courses

As a training coordinator, you must know what makes for an excellent eLearning experience, such as engaging, well-designed, relevant, and informative content. However,...

Why we will always need humans to train AI — sometimes in real-time

Customizable, real-time data labeling pipelines that can continuously receive and process unlabeled data are necessary to train and perfect the AI that impacts our lives and daily conveniences.

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