Skin conditions are the fourth-largest cause of nonfatal disease worldwide, but access to dermatological care is sparse. A new study shows that a neural network can do front-line diagnostic work.

AI startups are being scooped up at an accelerating pace, many by companies outside the tech sphere. A report by CB Insights shows that, as of August, 2019 was on track to surpass last year’s record number of AI startup acquisitions.

Construction projects require teams of surveyors who continually map blueprints to precise, real-world locations. Drones might do it faster, saving time and money.

Advances in computer vision and robotic dexterity may reach the field just in time to save U.S. agriculture from a looming labor shortage. CNN Business surveyed the latest crop of AI-powered farmbots.

Creating a virtual representation of a scene using traditional polygons and texture maps involves several complex operations, and even neural-network approaches have required manual preprocessing. Researchers propose a new deep-learning pipeline that visualizes scenes with far less fuss.

Microscopes outfitted with AI-driven augmented reality could improve the accuracy of cancer diagnoses. Google Health developed an attachment for analog microscopes that outlines signs of breast and prostate cancer in real time.

Deep learning models can be unwieldy and often impractical to run on smaller devices without major modification. Researchers at Facebook AI Research found a way to compress neural networks with minimal sacrifice in accuracy.

Neural networks are good at making predictions, but they’re not so good at estimating how certain they are. If the training data set is small and many sets of model parameters fit the data well, for instance, the network may not realize this explicitly, leading to overly confident predictions.

Automatic license plate readers capture thousands of vehicle IDs each minute, allowing law enforcement and private businesses to track drivers with or without their explicit consent.