So when it came to tapping historical and streaming data stores to improve operational efficiency, as well as predict and circumvent potential issues in its production facilities, the company went for the most cutting-edge machine learning technology on offer: IBM's Watson. Speaking at the recent Chief Analytics Officer Forum in Sydney, Woodside's principal data scientist, Elsa Jordan, shared with attendees the company's journey to build a data science capability from scratch in one year that could be utilised by employees right across the organisation. Woodside established its data science practice in January 2015 and as part of its approach, is running the largest commercial instance of the Watson advisor engine. "Our premise was think big, prototype small, scale fast," Jordan said. "Key to that was using machine learning algorithms. What appealed was that we could learn from history, predict from streaming data and keep on learning as new information becomes available."

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

In 2025, in accordance with Moore's Law, we'll see an acceleration in the rate of change as we move closer to a world of true abundance. Here are eight areas where we'll see extraordinary transformation in the next decade: In 2025, 1,000 should buy you a computer able to calculate at 10 16 cycles per second (10,000 trillion cycles per second), the equivalent processing speed of the human brain. The Internet of Everything describes the networked connections between devices, people, processes and data. By 2025, the IoE will exceed 100 billion connected devices, each with a dozen or more sensors collecting data. This will lead to a trillion-sensor economy driving a data revolution beyond our imagination. Cisco's recent report estimates the IoE will generate 19 trillion of newly created value. With a trillion sensors gathering data everywhere (autonomous cars, satellite systems, drones, wearables, cameras), you'll be able to know anything you want, anytime, anywhere, and query that data for answers and insights. SpaceX, Google (Project Loon), Qualcomm and Virgin (OneWeb) are planning to provide global connectivity to every human on Earth at speeds exceeding one megabit per second. We will grow from three to eight billion connected humans, adding five billion new consumers into the global economy. They represent tens of trillions of new dollars flowing into the global economy. And they are not coming online like we did 20 years ago with a 9600 modem on AOL. Existing healthcare institutions will be crushed as new business models with better and more efficient care emerge. Thousands of startups, as well as today's data giants (Google, Apple, Microsoft, SAP, IBM, etc.) will all enter this lucrative 3.8 trillion healthcare industry with new business models that dematerialize, demonetize and democratize today's bureaucratic and inefficient system. Biometric sensing (wearables) and AI will make each of us the CEOs of our own health. Large-scale genomic sequencing and machine learning will allow us to understand the root cause of cancer, heart disease and neurodegenerative disease and what to do about it. Robotic surgeons can carry out an autonomous surgical procedure perfectly (every time) for pennies on the dollar. Each of us will be able to regrow a heart, liver, lung or kidney when we need it, instead of waiting for the donor to die. Billions of dollars invested by Facebook (Oculus), Google (Magic Leap), Microsoft (Hololens), Sony, Qualcomm, HTC and others will lead to a new generation of displays and user interfaces.

Business documents written in foreign languages are no longer the problem they once were thanks to technologies like Google Translate, but what about contracts written in legalese? That's where LawGeex hopes to help with an AI-based online tool. LawGeex offers what it calls the world's first contract review platform based on artificial intelligence. The goal, it says, is to help businesses and individuals "get a fair deal" before signing an agreement. Toward that end, it combines machine-learning algorithms with crowdsourced data, text analytics, and the knowledge of expert lawyers to make in-depth contract reviews accessible to everyone.

Photographs used in Tsvetkov's study. You may think you do, but a recent experiment by a Russian photographer suggests otherwise. In a project entitled, "Your face is big data," Rodchenko Art School student, Egor Tsvetkov, began by photographing about 100 people who happened to sit across from him on the subway at some point. He then used FindFace, a facial-recognition app that taps neural-network technology, to try to track them down on Russian social media site VK. It was ridiculously easy to find 60 to 70 per cent of the subjects aged between 18 and 35 or so, he found, although for older people it was more difficult.

This time last year Steve Wozniak was sounding a cautionary note about the future of Artificial Intelligence (AI), warning that computers would one day take over from humans and joking that we might even end up as their pets. In a recent interview with Australia's ABC TV's Lateline the engineering genius appeared more sanguine about the future of self-aware, super-intelligent Artificial Intelligence and much more concerned with the real world killer robots that are all but with us: Lethal Autonomous Weapon Systems (LAWS). The Apple co-founder maintains that human-level Artificial Intelligence won't happen for "a very long time": It might take 200 years before they are really fully able to operate all of their needs in the world, until then they're going to need human beings … I'm not really worried at all. It's very scary to make autonomous weapons that are just following some programmed set of instructions … even when you're driving a car there is no one set of rules … if a lane is closed off you have to do something against the rules … I don't think it's a good idea at all. I don't think we can really stop it.

Which industries will come to the fore in the next decade, and beyond, and become hubs of innovation? According to former State Department official Alec Ross, they won't be the industries that have dominated technology thus far. Instead, artificial intelligence (AI), genomics and robotics will lead the way. On Tuesday, the Italian Embassy in Washington, D.C., held an event to discuss Ross' recently published book, The Industries of the Future. He expounded on the book's themes and highlighted what it will take for individuals, companies and countries to harness the changes that he sees coming to the global economy.

Quietly, Australian postal engineers are building the future. Delivery drones were born first as whimsy and then as marketing, lofty ambitions placed on clumsy, flying toys. We saw them in commercials as gimmicks and on 60 Minutes as a promise of the future. And then, slowly, the flash faded. Amazon's multirotor machine gained a bulky, plane-like body.

Visitors to Australia's federal parliament are often surprised by the robust verbal confrontation between the government and the opposition – technically known as questions without notice, more commonly as question time. A theatrical highpoint of every sitting day, question time is part intellectual cage fight, part kindergarten spat – and all psychological warfare. Political journalists watch the hour-long question time as drought-stricken farmers view the clouds. They look for signs, they read the climate. But what if you were interested in facts?

In the study of argumentation-based reasoning, argument justification has received far more attention than statement justification, often treated as a simple byproduct of the former. As a consequence, counterintuitive results and significant losses of sensitivity can be identified in the treatment of statement justification by otherwise appealing formalisms. To overcome this limitation, we propose to reappraise statement justification as a formalism-independent component. To this purpose, we introduce a novel general model of argumentation-based reasoning based on multiple levels of labellings, one of which is devoted to statement justification. This model is able to encompass several literature proposals as special cases: we illustrate this ability for the case of the ASPIC+ formalism and provide a first example of tunable statement justification in this context.