AI experts convened to discuss how to combat the coronavirus crisis. An online conference hosted by Stanford University’s Institute for Human-Centered AI explored how machine learning is being deployed to address this pandemic — and prepare for the next one.

Chatbots designed to recognize Covid-19 symptoms dispense alarmingly inconsistent recommendations. Given the same symptoms, eight high-profile medical bots responded with divergent, often conflicting advice.

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.

The business world continues to shape deep learning’s future. Commerce is pushing AI toward more efficient consumption of data, energy, and labor, according to a report on trends in machine learning from market analyst CB Insights.

Chinese tech giants have opened their AI platforms to scientists fighting coronavirus. Alibaba Cloud and Baidu are offering a powerful weapon to life-science researchers working to stop the spread of the illness officially known as Covid-19: free access to their computing horsepower and tools.

A company that analyzes online information to predict epidemics spotted the upsurge in coronavirus at least a week ahead of public-health authorities. Canadian startup BlueDot alerted customers to the outbreak in he Chinese city of Wuhan on New Year’s Eve.

As black-box algorithms like neural networks find their way into high-stakes fields such as transportation, healthcare, and finance, researchers have developed techniques to help explain models’ decisions. New findings show that some of these methods can be fooled.

Google spent the past year training an AI-powered health care program using personal information from one of the largest hospital systems in the U.S. Patients had no idea — until last week.

From blue collar laborers to lab coated professionals, is any job safe from AI? AI will exceed human performance at a wide range of activities. Huge populations will become jobless.

Weak supervision is the practice of assigning likely labels to unlabeled data using a variety of simple labeling functions. Then supervised methods can be used on top of the now-labeled data.