Microsoft and Intel have a novel approach to classifying malware: visualizing it. They're collaborating on STAMINA (Static Malware-as-Image Network Analysis), a project that turns rogue code into grayscale images so that a deep learning system can study them. The approach converts the binary form of an input file into a simple stream of pixels, and turns that into a picture with dimensions that vary depending on aspects like file size. A trained neural network then determines what (if anything) has infected the file. ZDNet noted that the AI is trained on the huge amount of data Microsoft has collected from Windows Defenders installations. The technology doesn't need full-size, pixel-by-pixel recreations of viruses, which makes sense when large malware could easily translate to gigantic pictures.

Adoption of artificial intelligence is on the rise: According to research firm Gartner, 37 percent of organizations have now "implemented AI in some form," and adoption is up 270 percent over the past four years. Schools are following suit: Technavio's "Artificial Intelligence Market in the US Education Sector 2018-2022" report predicts a nearly 48 percent growth rate for AI tools over the next three years. As noted by MIT Technology Review, the rapid development and uptake of AI solutions has created an environment where companies may "obfuscate and oversell" AI abilities even as organizations race to implement new solutions and keep up with the competition. The key to AI success is specificity. It is crucial to define key needs AI tools can meet and shortcomings it can address.

Keeping in mind the overall trustworthiness of the website itself--and checking its Wikipedia page, if it has one--is a good step for regular people, too. For example, in August, Facebook and a cybersecurity firm announced they'd uncovered "inauthentic" news coming out of Iran. One of the websites associated with Iran was called the Liberty Front Press; they called themselves "independent" but appeared to actually be pro-Iran. And tellingly, the site does not appear to have a Wikipedia page. Of course, the MIT research group aren't the only ones using AI to analyze language like this: a Google-made AI system called Jigsaw automatically scores the toxicity of reader comments, and Facebook has turned to AI to help augment its efforts to keep hate speech at bay in Myanmar.

That's what an experimental app is offering to do for conservationists seeking to identify and track primates in the wild. It could even help wildlife crime investigators recognise individuals that have been killed or trafficked. While some researchers in the field are able to identify individual primates in the small populations they are studying, recognising them quickly in other contexts is very difficult, says Serge Wich at Liverpool John Moores University, who was not involved in the work. "We put camera traps out or …