The best minds in the business--Yann LeCun of Facebook, Luke Nosek of the Founders Fund, Nick Bostrom of Oxford University and Andrew Ng of Baidu--on what life will look like in the age of the machinesThe traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.

This week, in a public test, we put the Triage capability of babylon's new AI function to test against some of the UK's top triage nurses and junior doctors. Professor Irwin Nazareth, The Academic Doctoral Research Committee Chair of the Health Education England and NIHR examined one of Britain's most senior A&E nurses, an Oxford-educated Junior Doctor and babylon's new'Check' feature to see who provided the most accurate and fastest triage assessment in front of the UK's top consumer, health and technology media. This was a live demonstration of an extensive set of tests published in an academic research paper, that showed babylon's'Check'feature to be safe in 100% of cases, 13% more accurate than a doctor, 17% more accurate than a nurse, and performing significantly faster 89% of the time. "Check a Symptom" is already the most popular feature on the babylon app. In the UK alone, it has been used around 20,000 times in just three weeks (that is about 3% of the usage of nhs 111 nationally in the same period).

Already busy dealing with customers in phone stores, train stations, and departments stores, Pepper the robot has now been put to work in two hospitals in Belgium. The android, which can understand and respond to a range of human emotions, started assisting visitors at two health facilities in Ostend and Liege on Monday. Pepper launched to great fanfare in Japan exactly a year ago, with the first batch of 1,000 units snapped up in just 60 seconds. The creation of Japanese telecom giant SoftBank and French robotics company Aldebaran SAS, the robot is being marketed as an assistant for businesses and also as a companion for families and those living alone. Standing 120-cm tall, Pepper can converse in a number of languages and also communicate via its torso-based tablet.

Chatbots can order flowers for you on Facebook. An intelligent assistant can schedule a meeting. Now, a new update for your iPhone will be packed with new automations to make our lives easier and maybe even reduce stress, and it won't cost you a cent when it debuts this fall (unless you need to get a new iPhone). This week at a developer conference in California, Apple announced iOS 10 and focused mostly on how to make your phone "think differently" by thinking for you and saving time. There are some brilliant new updates, but here are the ones that impressed me the most and offer the most automation.

Everyone seemingly is complaining about the spread of ransomware, and now somebody is trying to do something about it using machine learning-based behavioral analytics techniques to track suspicious behavior on company networks. As the scale of the ransomware threat grows, including ransom payments by hospitals and universities and growing fears that it will soon spread to other sectors, a Silicon Valley security intelligence firm has rolled out an approach for detecting ransomware via machine learning. Exabeam, a specialist in user and "entity" behavior analytics based in San Mateo, Calif., unveiled its analytics approach to detecting ransomware attacks during a security conference this week. The early warning system is touted as being able to spot ransomware activity on corporate networks without relying on third-party security controls. The platform also can spot suspicious activity within cloud services, servers and, increasingly, personal devices connected to corporate and other enterprise IT infrastructure.

Apple is stepping up its artificial intelligence efforts in a bid to keep pace with rivals who have been driving full-throttle down a machine learning-powered AI superhighway, thanks to their liberal attitude to mining user data. Not so Apple, which pitches itself as the lone defender of user privacy in a sea of data-hungry companies. While other data vampires slurp up location information, keyboard behavior and search queries, Apple has turned up its nose at users' information. The company consistently rolls out hardware solutions that make it more difficult for Apple (and hackers, governments and identity thieves) to access your data and has traditionally limited data analysis so it all occurs on the device instead of on Apple's servers. But there are a few sticking points in iOS where Apple needs to know what its users are doing in order to finesse its features, and that presents a problem for a company that puts privacy first.

The market research firm expects the attach rate of AI-based systems in new vehicles to increase from 8 percent in 2015 (the vast majority of today's AI systems in cars are focused on speech recognition) to 109% in 2025. IHS sees multiple AI systems of various types to be installed in many cars. In the human-machine interface in vehicles, IHS believes AI will play a role in speech and gesture recognition, eye-tracking, driver monitoring and natural language interfaces. In the autonomous car, AI will advance machine vision systems, while it will also migrate in sensor fusion electronic control units (ECU). In a phone interview with EE Times, Luca De Ambroggi, principal analyst, automotive semiconductors at IHS told us, "AI is viewed as a key enabler for real autonomous vehicles. Everyone in the automotive supply chain is getting pretty bullish."

Qiwen Cui tries out the'Farpoint' VR game during the opening day of the Electronic Entertainment Expo at the Los Angeles Convention Center. LOS ANGELES -- The experiences on display during the Electronic Entertainment Expo are only the beginning. During this week's showcase of the video game industry's future, publishers revealed the first big wave of games leveraging the VR platform. However, it's still too early in the life of VR to tell what experiences will push consumers to strap on a headset and dive in to these digital worlds. "VR, as well as AR, are in very early days of adoption," says Digital World Research analyst P.J. McNealy.

Another big part of the food supply comes from ranches and farms that raise and slaughter various livestock. While ranching is sometimes bundled with agriculture, I discussed farming in Big Data in Agriculture, so we'll focus on ranching this time around. Somewhat surprising is that big data usage in ranching appears more limited than in farming. That said, there are a number of novel uses of technology and data in animal husbandry. At a high level, the goals of ranching and farming are the same as any business: increase yields and lower costs. Production maximization has long played a role in large operations.

As the Director of Data Science for an advanced analytics company, Sean brings machine learning automation into business applications to help organizations build core strategies around data. Having worked across diverse industries, and alongside many talented professionals, Sean has seen the blend of approaches required to successfully convert raw data into real world value. Sean holds his doctorate in scientific computing where he used advanced mathematics, parallel computing and optimization to solve challenges in nanotechnology, chemistry and renewable energy. After completing his Ph.D. Sean started his own Data Science consulting practice, helping companies automate decision-making and uncover the underlying patterns that drive business environments. Sean has since worked for global consulting firms and silicon valley startups to help bring the advances in machine learning to business applications.