Synthetic datasets can inherit flaws in the real-world data they’re based on. Startups are working on solutions. Generating synthetic datasets for training machine learning systems is a booming business.

In this work-from-home era, who hasn’t spent a video conference wishing they could read an onscreen document without turning their eyes from the person they’re talking with? Or simply hoping the stream wouldn’t stutter or stall? Deep learning can fill in the missing pieces.

Amazon’s digital assistant is using its eyes as well as its ears to figure out who’s talking. At its annual hardware showcase, Amazon introduced an Alexa skill that melds acoustic, linguistic, and visual cues to help the system keep track of individual speakers and topics of conversation.

An ambitious company is using deep learning to extract and find associations from all the information on the internet — and it isn’t Google. Diffbot built a system that reads web code, parses text, classifies images, and assembles them into what it says is the world’s largest knowledge graph.

A neural network is helping credit card users continue to shop even when the lender’s credit-approval network goes down. Visa developed a deep learning system that analyzes individual cardholders’ behavior in real time to predict whether credit card transactions should be approved or denied.

An aviation startups is using neural networks to put air freight on autopilot.What’s new: Xwing, a California startup, is test-flying an autonomous pilot system aboard cargo aircraft with an eye toward crewless commercial flights in 2022.

Marketers are using computer vision to parse customers by skin color and other perceived racial characteristics. A number of companies are pitching race classification as a way for businesses to understand the buying habits of different groups.

The same technology that has bedeviled Hollywood stars and roiled politics is easing corporate communications. Synthesia generates training and sales videos featuring photorealistic, synthetic talking heads that read personalized scripts in any of 34 languages.

Companies in Africa and the Middle East are building AI capacity in very different ways, a new study found. AI is growing fast in both regions despite shortages of talent and data.

Computer vision has been learning how to spot manufacturing flaws. The pandemic is accelerating that education. Companies like Instrumental and Elementary are making AI-powered cameras that automate the spotting of damaged or badly assembled products on factory assembly lines.

Football clubs are turning to computer vision for winning insights. Acronis, a Swiss cloud storage and security company, offers AI services designed to give a boost to some of the world’s top football clubs (soccer teams, to Americans), Wired reported.

Some tech companies boast that their AI will change the world. Apple’s latest just aims to make your life a little easier. Apple unveiled a flock of modest conveniences powered by machine learning at its annual developer conference.

Three of the biggest AI vendors pledged to stop providing face recognition services to police — but other companies continue to serve the law-enforcement market.

Conversational agents have a tough job following the zigs and zags of human conversation. They’re getting better at it — thanks to yesterday’s technology. Amazon recently improved the Alexa chatbot’s ability to identify the current topic of conversation.

Machines took another step toward doing the work of journalists. Microsoft laid off dozens of human editors who select articles for the MSN news service and app. Going forward, AI will do the job.