Machines won't become intelligent unless they incorporate certain features of the human brain. Europe's massive €1 billion project has shifted focus from simulation to informatics By Megan Scudellari Large-scale brainlike systems are possible with existing technology--if we're willing to spend the money By Jennifer Hasler Researchers in this specialized field have hitched their wagon to deep learning's star By Lee Gomes Running algorithms that mimic a rat's navigation neurons, heavy machines will soon plumb Australia's underground mines By Jean Kumagai Artificial intelligence might endow some computers with self-awareness.

You can tell a lot about a company's values and its priorities by the way it spends its money. Each October on ZDNet we do a special report on how business leaders are planning to spend their tech budgets for the year ahead. In our survey of 2018 plans, we found that nearly two-thirds of decision makers are increasing their technology budgets in 2018, and almost a quarter of them are boosting their tech spend by 10% or more. SEE: Tech Budgets 2018: A CXO's Guide Aside from specific tech projects, 35% of leaders said they are investing in training existing employees and 29% said they are investing in hiring new employees. We also polled TechRepublic's CIO Jury, where 83% said their IT budgets would increase or stay the same in 2018.

Algorithmic decision making process now affects many aspects of our lives. Standard tools for machine learning, such as classification and regression, are subject to the bias in data, and thus direct application of such off-the-shelf tools could lead to a specific group being unfairly discriminated. Removing sensitive attributes of data does not solve this problem because a \textit{disparate impact} can arise when non-sensitive attributes and sensitive attributes are correlated. Here, we study a fair machine learning algorithm that avoids such a disparate impact when making a decision. Inspired by the two-stage least squares method that is widely used in the field of economics, we propose a two-stage algorithm that removes bias in the training data. The proposed algorithm is conceptually simple. Unlike most of existing fair algorithms that are designed for classification tasks, the proposed method is able to (i) deal with regression tasks, (ii) combine explanatory attributes to remove reverse discrimination, and (iii) deal with numerical sensitive attributes. The performance and fairness of the proposed algorithm are evaluated in simulations with synthetic and real-world datasets.

We are moving rapidly towards a world where robots and artificial intelligence (AI) systems are connected to and influenced by social media, the Internet of Things (IoT) and big data. Technological developments are moving fast, and AI has many governments concerned. Given the pace of technological advancement, how do rule-makers set legislation for AI while allowing the safe evolution of technology? Who thinks about and enforces these guidelines, and what work is being done, or should be done, with governments to craft AI policy? Moves by the European Parliament to consider granting some form of legal status to AI have revived questions of liability and responsibility.

Ahead of China's own autonomous train reveal, mining corporation Rio Tinto have given the world its first fully-autonomous train, and it's currently in operation in Western Australia. Mining corporation Rio Tinto, which also developed the train, announced earlier this week the train had successfully completed its first unmanned mission, traveling nearly 100 kilometers (62 miles) without a person on board. "Rio Tinto is proud to be a leader in innovation and autonomous technology in the global mining industry which is delivering long-term competitive advantages as we build the mines of the future," said Rio Tinto Iron Ore Chief Executive Chris Salisbury, in a statement. "New roles are being created to manage our future operations and we are preparing our current workforce for new ways of working to ensure they remain part of our industry." The mission, located at Rio Tinto's iron ore operations in the Pilbara region of Western Australia, is the first big step in the company's plans to have a fully autonomous train network.

This year marks the 10th anniversary of Mint's win at the first ever TechCrunch Startup Battlefield competition (back then – lost in the mists of time – it was known as TechCrunch 40). But what is less known about founder Aaron Patzer is that he's one of the pioneers of AI. Now based in the Southern Hemisphere, he's coming to speak at Techcrunch Battlefield Australia. In January this year, he started Vital Software, with Dr. Justin Schrager of Emory University, which makes software for hospital emergency rooms. When you include the fact that it's a mobile patient check-in for patients, and automatically creates electronic medical records designed for doctors and nurses, with the aim being to cut ER wait times in half, you start to understand the AI heritage it's come from. Patzer will join us as a speaker at TechCrunch Battlefield Australia in partnership with ELEVACAO, on November 16th at Australian Technology Park in Sydney.

Every year, artificial intelligence (AI) software bots compete and battle it out in the video game Universe of StarCraft. But a new player representing (of all things) Facebook entered into this arena -- CherryPi, an AI player designed by a team of eight people from or involved with Facebook's AI research lab. This foray into multiplayer gaming established Facebook as direct competition for others, like Google and even individual hobbyists (three of whom finished in the top three places). Gabriel Synnaeve, a researcher at Facebook, described CherryPi as a "baseline" prototype to learn and build from, he said, "We wanted to see how it compares to existing bots, and in particular test if it has flaws that need correcting." Some expect Facebook and Google to lag behind independently-designed bots for awhile, despite the tech giants' inexhaustible resources; "For a couple of years I predict the hobbyist, mostly rule-based bots, will still do well," said David Churchill, a professor of the Memorial University of Newfoundland, which organized AIIDE, an academic conference that includes contests like the StarCraft competition.

AI has been a hot topic among loyalty marketers in recent years, and even more this year. Can AI transform and elevate a loyalty marketer's approach to customer experience? A new study from Emarsys, conducted by Forrester Consulting, examines Artificial Intelligence (AI) marketing readiness in the retail and e-commerce industries. The study, "Building Trust and Confidence: AI Marketing Readiness in Retail and e-Commerce," sought to understand if there is still a gap between the readiness of AI marketing solutions to execute on real-time B2C marketing campaigns, and the readiness of marketing tech users and business decision makers to adopt AI marketing technology. The study surveyed companies in the U.S., U.K, Germany, France, and Australia that each had revenue of at least $50 million upward to $5 billion.

How far will AI take us in areas such as healthcare? Will we see medical pods like this one featured in science fiction film Prometheus to treat future patients? CIO veteran and industry consultant, Geoff Wenborn, sees enormous opportunity for artificial intelligence (AI) in healthcare - identifying 35 use cases alone for robotics and AI at places like UnitingCare Queensland. Wenborn, who provides IT transformation consulting to several organisations including UnitingCare Queensland and Starlight Children's Foundation Australia (and built some proof of concepts), said the sky's the limit in terms of use case possibilities. At UnitingCare, he was the interim CIO charged with doing transformation, and is currently the chair of the Starlight IT Advisory Board.

How far will AI take us in areas such as healthcare? Will we see medical pods like this one featured in science fiction film Prometheus to treat future patients? CIO veteran and industry consultant, Geoff Wenborn, sees enormous opportunity for artificial intelligence (AI) in healthcare - identifying 35 use cases alone for robotics and AI at places like UnitingCare Queensland. Wenborn, who provides IT transformation consulting to several organisations including UnitingCare Queensland and Starlight Children's Foundation Australia (and built some proof of concepts), said the sky's the limit in terms of use case possibilities. At UnitingCare, he was the interim CIO charged with doing transformation, and is currently the chair of the Starlight IT Advisory Board.