A pioneer in dishwashing robots is reaching into commercial kitchens. Dishcraft Robotics uses machines equipped with computer vision to scrub dirties for corporate food services and, soon, restaurants.

The latest update of the acclaimed real-time object detector You Only Look Once is more accurate than ever. Researchers at Taiwan’s Institute of Information Science Academia Sinica offer YOLOv4 — the first version not to include the architecture’s original creators.

The for-profit research organization OpenAI has a new supercomputer to help achieve its dream of building the world’s most sophisticated AI. Microsoft engineered the new hardware network to train immense models on thousands of images, texts, and videos simultaneously.

Few-shot learning seeks to build models that adapt to novel tasks based on small numbers of training examples. This sort of learning typically involves complicated techniques, but researchers achieved state-of-the-art results using a simpler approach.

Like nurses who can’t decipher a doctor’s handwriting, machine learning models can’t decipher medical scans — without labels. Conveniently, natural language models can read medical records to extract labels for X-ray images.

Facebook’s AI can’t spot Covid-19 disinformation on its own. But with human help, it can slow the spread. Facebook uses a combination of humans and neural nets to crack down on messages that make false claims about Covid-19, which may have deadly consequences.

Cameras that detect face masks are helping French authorities to evaluate citizens’ adherence to government mandates intended to fight Covid-19. Starting this week, everyone riding public transportation in France is required to wear a face mask.

An algorithm indexed photos, ads, and other images embedded in 170 years of American newspapers. Created by researchers at the University of Washington and U.S. Library of Congress, Newspaper Navigator uses object recognition to organize visual features of newspapers dating back to 1789.

Human teachers can teach more effectively by adjusting their methods in response to student feedback. It turns out that teacher networks can do the same.

A machine learning model is scanning the oceans for the glint of garbage. Researchers from the UK’s Plymouth Marine Laboratory trained a model to identify ocean-borne refuse.

Recognizing stop signs, with their bold color scheme and distinctive shape, ought to be easy for computer vision — but it turns out to be a tricky problem. Tesla pulled back the curtain on what it takes to train its self-driving software to perform this task and others.

Deep learning promises to help emergency responders find their way through disaster zones. MIT researchers developed a tool that maps where hurricanes and other calamities have wiped out roads, helping to show aid workers the fastest ways to get to people in need.

Robot vacuum cleaners are pretty good at navigating rooms, but they still get stuck in tight spaces. New work takes a step toward giving them the smarts they’ll need to escape the bathroom.

Given real-world constraints on memory and processing time, images are often downsampled before they’re fed into a neural network. But the process removes fine details, and that degrades accuracy. A new technique squeezes images with less compromise.

It’s time to stop flushing valuable data down the toilet. The Precision Health Toilet, a suite of sensors that attach to an ordinary commode, monitors human waste for input for signs of disease. It identifies individual users by scanning where the sun doesn’t shine.