In early May, New York-based tech startup Agolo completed its first seed round of funding, pulling in over $3.5 million in investments from Microsoft Ventures and CRV, with participation from Point72 Ventures and Franklin Templeton. But how did this entrepreneur go from Egypt to snagging such overwhelming corporate interest in the heart of the Big Apple? An interview with Mohamed AlTantawy - Egyptian, AUC graduate, and co-founder of Agolo - reveals how the startup progressed from ideation to actualization. AlTantawy's AI-powered startup provides machine summarisation software that gathers documents from around the web and breaks down key points for the user, eliminating the need to spend hours sifting through information to find the most important details, and works through natural language processing technology. "This is the area of computer science where algorithms try to make sense of human language," the entrepreneur explains.

First, Symantec revealed that hackers--probably based in Russia, although the security firm didn't go so far as to name names--had hacked more than 20 power companies in North America and Europe, and in a handful of cases, had direct access to their control systems. And then Equifax confessed it had been the target of a breach that stole 143 million Americans' data, one of the worst data spills ever, and one that raises questions about data centralization, particularly for Social Security Numbers. Megabreaches aside, Facebook admitted that a Russian troll farm had spent $100,000 on influence ads during last year's election. Google patched a flaw in Android that would allow a nasty "toast overlay" attack to take control of devices. WIRED dug into the long-running series of scams and theft plaguing new currencies in the cryptocoin economy.

People get up to weird things in New Zealand. At the University of Auckland, if you want to run hours upon hours of experiments on a baby trapped in a high chair, that's cool. You can even have a conversation with her surprisingly chatty disembodied head. BabyX, the virtual creation of Mark Sagar and his researchers, looks impossibly real. The child, a 3D digital rendering based on images of Sagar's daughter at 18 months, has rosy cheeks, warm eyes, a full head of blond hair, and a soft, sweet voice. When I visited the computer scientist's lab last year, BabyX was stuck inside a computer but could still see me sitting in front of the screen with her "father." To get her attention, we'd call out, "Hi, baby. Look at me, baby," and wave our hands. When her gaze locked onto our faces, we'd hold up a book filled with words (such as "apple" or "ball") and pictures (sheep, clocks), then ask BabyX to read the words and identify the objects.

Passengers' baggage is collected by robots, they relax in a luxurious waiting area complete with an indoor garden before getting a face scan and swiftly passing through security and immigration - this could be the airport of the future. It's a vision that planners hope will become reality as new technology is rolled out, transforming the exhausting experience of getting stuck in lengthy queues in ageing, overcrowded terminals into something far more pleasant. The changes also represent major challenges that could upend decades-old business models at major airports, with analysts warning operators may face a hit to their revenues to the tune of billions of dollars. Facial scanning in particular is generating a lot of buzz. Changi in the affluent city-state of Singapore, regarded as among the world's best airports, is set to roll out this biometric technology at a new terminal to open later this year.

A new computer algorithm, developed by researchers at Stanford University, can correctly determine someone's sexuality with up to 91% accuracy just by analysing a photo of their face. It's the robotic equivalent of a "gaydar" and it's sure to stir up a minefield of discussion, but first, a few caveats. The study used 35,326 photos from a US dating site and the artificial intelligence only distinguished sexuality between two photos (always one straight, one homosexual) of people of the same gender – the study did not include transgender or bisexual people. The photos used were portraits of faces, so the AI's judgments are made based on a "faceprint" determined from things like eyebrows, cheeks, hairline, neckline and nose, rather than clothing or hairstyle. Among men the system was accurate 81% of the time, and with women it was 71% accurate, but when given repeated photos of the same man (and so, more data) the accuracy increased to 91%.

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Artificial intelligence can figure out a person's sexual orientation by analysing a picture of their face, a controversial new study claims. According to its authors, who say they were "really disturbed" by their findings, the accuracy of an AI system can reach 91 per cent for homosexual men and 83 per cent for homosexual women. The study also concludes that homosexual men and women tend to have "gender-atypical facial morphology, expression, and grooming styles". The paper, titled Deep neural networks are more accurate than humans at detecting sexual orientation from facial images, was co-authored by Stanford University's Yilun Wang and Michal Kosinski, and first spotted by the Economist. In it, they claim to "show that faces contain much more information about sexual orientation than can be perceived and interpreted by the human brain".

When Katharine Rubin has a spare moment on the way to school, she helps a big-name tech company smarten up its artificial intelligence. Rubin, a 22-year-old accounting major at New York City's Baruch College, is part of a growing workforce that spends anywhere from 5 minutes to 40 hours a week increasing the I in AI. Specifically, Rubin and others provide training data for machine learning algorithms, a form of AI that can be taught from experience. For an autonomous car to recognize pedestrians and stop signs, it's typically fed thousands or millions of photos, all hand-labeled. To nail a conversation, a digital assistant needs to be told over and over when it's failed.

Anthony Falvo, tells The Associated Press that "no civilians were anywhere near the site." He says he does not have the identity of the al-Shabab member killed.

How did one Harley-Davidson dealership in New York City go from selling one or two bikes a week to selling 15 in a weekend? Owner Asaf Jacobi took a risk on Adgorithms' 'Albert', an artificial intelligence (AI) driven marketing platform that works across digital channels. The results saw the dealership increasing leads by 2930% by the third month and driving Jacobi to set up a new call centre to handle all the new business. Albert can learn as he does and is able to "identify the audiences most likely to convert, eliminate low-value audiences, apply insights gained from one channel to other channels", according to Harley-Davidson NYC. The AI works with campaign creative and KPIs provided by the brand to autonomously execute holistic digital ad and marketing campaigns.