Computer vision is helping construction workers keep their social distance. Smartvid.io, a service that focuses on construction sites, offers a tool that recognizes when workers get too close to each other. The tool sends distancing warnings and reports to construction superintendents.

Faced with a classification task, an important step is to browse the catalog of machine learning architectures to find a good performer. Researchers are exploring ways to do it automatically.

Batch normalization is a technique that normalizes layer outputs to accelerate neural network training. But new research shows that it has other effects that may be more important.

Are your scientist friends intimidated by machine learning? They might be inspired by a primer from one of the world’s premier tech titans. Former Google CEO Eric Schmidt and Cornell PhD candidate Maithra Raghu school scientists in machine learning in a sprawling overview.

Unexploded munitions from past wars continue to kill and maim thousands of people every year. Computer vision is helping researchers figure out where these dormant weapons are likely to be.

Glass bottles and crystal bowls bend light in strange ways. Image processing networks often struggle to separate the boundaries of transparent objects from the background that shows through them. A new method sees such items more accurately.

Neural networks revealed both how hard Covid-19 has hit the Chinese economy, and hopeful signs that a renaissance may be underway. Researchers analyzed satellite imagery, GPS signals, and social media to get a multifaceted view of the pandemic’s impact.

How much data do we want? More! How large should the model be? Bigger! How much more and how much bigger? New research estimates the impact of dataset and model sizes on neural network performance.

Machine learning thrives on data, but information about the novel coronavirus and the illness it produces has been either thin or hard to access. Now researchers are pooling resources to share everything we do know.

A simple linear classifier paired with a self-supervised feature extractor outperformed a supervised deep learning model on ImageNet, according to new research.

Which dataset was used to train a given model? A new method makes it possible to see traces of the training corpus in a model’s output.

Machine learning promises to streamline handling of tomorrow’s bureaucratic drudgery — and, it turns out, that of 2,500 years ago. Computer vision is helping researchers at the University of Chicago translate a massive collection of ancient records inscribed on clay tablets.

In small data settings where labels are scarce, semi-supervised learning can train models by using a small number of labeled examples and a larger set of unlabeled examples. A new method outperforms earlier techniques.

Many of this year’s hottest AI companies are taking the spotlight from last year’s darlings.What’s new: CB Insights, which analyzes early-stage companies, published its annual list of the 100 “most promising” startups in AI.

AI may not steal your job, but it can tell the boss when you’re slacking. Drishti, a startup based in Palo Alto and Bengaluru, tracks the productivity of industrial workers by recognizing their actions on the assembly line.