A team of international researchers is urging people to share their selfies in order to help teach computers how to read faces and identify people with rare diseases. The Minerva and Me project - being led by Oxford University with the help of international researchers like WA Health clinical genetist Gareth Baynam - is seeking to use technology to spot rare diseases faster and more accurately. The crowd-sourced research initiative wants to build a database of photographs so the researchers can develop facial recognition software using machine learning algorithms that can identify rare diseases. The software would be able to suggest a disease condition and prompt further tests that could be used to help settle on a diagnosis - potentially reducing the instances of incorrect diagnosis. "We think computers can be used to help diagnose individuals who have particular diseases. To do this we are training computers to look at photographs of peoples' faces to try to identify combinations of subtle changes that might together be indicators of a specific disease," the researchers say.

A computer is being developed that rates how much pain someone is in by detecting small changes to their facial expressions. Such a system could help doctors determine how to treat patients and may save the prescription of painkillers. Study author Dr Jeffrey Cohn from the University of Pittsburgh, said: 'These metrics might be useful in determining real pain from faked pain.' People experience and express pain differently, which makes it difficult for doctors to gauge the extent patients are suffering based on self-reported scores. The researchers hope the system could one day be available as an app that doctors have on their smartphones.

Callaghan Innovation will establish the Digital Energy Hub, an initiative to encourage early adoption and commercialisation by the energy sector of the next wave of digital technologies – namely Artificial Intelligence (AI), Big Data, Blockchain, Cloud Analytics and Internet of Things. The scale and speed of the disruption from such technologies presents challenge and opportunity for many businesses in the energy sector – from start up to established – and for those in adjacent sectors such as Information Technology, transport and manufacturing. More to on this to follow. In an interview with Idealog, Stu Christie explains that he sees the biggest opportunities for Artificial Intelligence (AI) technologies being in agriculture, manufacturing, infrastructure and transportation. Stu is investment manager at NZ Venture Investment Fund and now Chair of the recently launched AI Forum.

When Nicole Stark set about writing a new video game, she took inspiration from an unusual subject: her autistic teenage daughter who was battling bullies. "I was fed up with power fantasies for male teenagers," says Stark, one half of Noosa-based family studio Disparity Games. Sick of seeing female protagonists who behaved "exactly like the male character but with large boobs", Stark, with help from her daughter, created Gemma, a 16-year-old ninja pizza delivery girl who must navigate a dystopian world of sky-high slums, exploitative mega-corporations and the cruelest of adversaries: her own peers. "It was important to make Gemma look like a 16-year old," says Stark, recalling her career as an artist when she would routinely make the breasts smaller on female characters – only for male colleagues to routinely make them bigger. Launched in 2015, Ninja Pizza Girl received favourable reviews.

From virtual assistants to driverless cars, technology imitating human intelligence is on the rise. But at what ethical cost and how do boards future-proof their organisations in the face of rapid change? Earlier this year, a Japanese insurance company made headlines for doing something that company executives and directors around the world have been anticipating - and fearing - for years. Fukoku Mutual Life Insurance made 34 of its staff redundant and replaced them with artificial intelligence (AI) system IBM Watson. Japanese newspaper The Mainichi reported the company will be using Watson to determine payout amounts and check customer cases against their insurance contracts. Other Japanese insurance companies have announced they are looking at or are already using AI for similar purposes and The Japan Times reported in April that the country's Ministry of Economy, Trade and Industry was planning to trial AI to help government workers write draft answers for questions put to Cabinet ministers.

In recent years we have seen a surge in the way companies have leveraged technology to drive new revenue streams and create a unique competitive advantage in the marketplace. The companies that have been the most successful are the ones using Artificial Intelligence (AI). AI is already being used by hundreds of companies all over the world. We have seen retailers being able to predict what their customers will order based on their previous order history, car manufactures using vehicle data to provide a better driving experience and even locally in Australia we have seen Domino's using AI to help grow their sales and store numbers. But what does this have to do with cybersecurity…….? Whether you are an organisation not yet using AI, or you are already experimenting with it, is important to protect the intellectual property that provides your organisation with the competitive edge.

The last few years have seen huge amounts of research and development invested in machine learning and AI. This will continue to be a focus for businesses of all sizes- from emerging startups to major IT companies. More and more of these early adopters will bring this technology into use for their consumer-facing services.

Beachgoers in Australia can be a little less panicky about shark attacks this summer, because artificial intelligence-equipped drones will be monitoring the water for big scary fish. Developed by researchers at University of Technology Sydney, the AI system--dubbed Sharkspotter--can identify sharks and notify beachgoers when they're nearby. An Australian drone company called Westpac teamed up with the school to outfit its battery-powered Little Ripper Lifesaver unmanned helicopters with the technology in an effort to, hopefully, offer swimmers and surfers better protection. The AI-equipped drones will patrol "many main beaches in Australia" this summer, the school said in a news release. "The system will give an overhead warning to swimmers/surfers when a shark or a potential risk is detected, using an on-board megaphone attached to the drones," Professor Michael Blumenstein, head of the UTS School of Software, said in a statement, adding that the system "will create a positive impact for the public, making beach recreation much safer." Sharkspotter uses "cutting-edge deep neural networks and image processing techniques" to examine live video feeds in real time and detect the presence of sharks, and distinguish them from other marine life and objects, the school said.

Australia's first driverless shuttle trial turned a year old this week, during which the bus has clocked up more than 4200 km in autonomous mode. The RAC Intellibus has made around 1500 thirty-minute trips, carrying more than 4300 passengers around its route on open road in South Perth. The autonomous bus – which can reach speeds of 45km per hour, but averages at around 25km per hour – is fully electric and uses light detection and ranging (LIDAR), stereovision cameras, GPS, odometry and autonomous emergency braking to detect and avoid obstacles and maintain its course. It is considered to have'Level 4' automation (as defined by SAE International standards) which means the vehicle can perform all safety critical driving functions without any occupants. Nevertheless, the bus has a'chaperone' whom can take the wheel (actually a Playstation controller) if needed.

Since the days of Da Vinci's "Ornithoper", mankind's greatest minds have sought inspiration from the natural world for their technological creations. It's no different in the modern world, where bleeding-edge advancements in machine learning and artificial intelligence have begun taking their design cues from the most advanced computational organ in the natural word: the human brain. Deep learning neural networks -- the likes of which power AlphaGo as well as the current generation of image recognition and language translation systems -- are the best machine learning systems we've developed to date. They're capable of incredible feats but still face significant technological hurdles, like the fact that in order to be trained on a specific skill they require upfront access to massive data sets. What's more if you want to retrain that neural network to perform a new skill, you've essentially got to wipe its memory and start over from scratch -- a process known as "catastrophic forgetting".