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.

AI will play an increasingly important role in the top three business objectives often cited by CEOs -- greater customer intimacy, increasing competitive advantage and improving efficiency. From the 1980s Lisp machines and Deep Blue in 1997 to the debut of IBM's Watson in 2010s, AI in various forms has been around for a long time. But commercial uses of AI are in specialised industry-specific applications such as actuarial forecasts and medical diagnosis -- making CIOs understandably cautious about promoting AI's potential business value. Savvy CIOs are experimenting jointly with business peers to discover top uses and ROI for AI to evaluate its potential to disrupt markets and remake existing business models. This is been done at a pace that has left many CIOs hurrying to build an AI strategy and investment plan appropriate for their enterprise.

With the advent of chatbots, personal assistants, and robo-advisors, it may not be too hard to imagine that the next wave of technology could revolutionize the traditional style of banking. An Accenture report recently indicated that within the next three years, banks will deploy Artificial Intelligence (A.I.) as their primary method to interact with customers. In early 2016, Swedish-speaking Amelia became the first non-English deployment of IPsoft's AI platform at SEB, one of Sweden's largest bank. The bank adopted "digital employee" Amelia to integrate into its front-office. The cognitive agent solves problems just like humans "but in a fraction of the time", interacts just like humans and even senses emotions.

Much has been written about the rise of autonomous vehicles with testing being conducted globally and the increasing number of consumers who are already enjoying the benefits. One of my colleagues, who juggles his time between our office in Cupertino and the vineyard and olive orchard he runs in Sonoma County (Trattore Farms), tells me he's taken full advantage of his Tesla's autopilot feature for his drives. It's not just the hands off driving potential that impresses him though; it's the way that his car, as part of a network of cloud-connected vehicles, is learning as the car documents data points and uploads them to the cloud in real time. So for example, if several Teslas log information at the same GPS point where their driver taps the brakes if their car approaches a dip in the road too fast, the algorithm directing autopilot through that location will automatically update and all the Teslas using autopilot at that location will automatically slow down. I've not had the chance to experience the Tesla autopilot for myself but I'm also seeing the power of data sharing and the IoT with my drone flying.

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.

Machine learning is fast becoming a reality for forward-thinking organizations. But for most businesses, the best way to take advantage of the capabilities of machine learning technologies remains something of a mystery. Still, the drumbeat to experiment keeps getting louder. And the truth is, your competitors may already be laying the groundwork. IDC forecasts revenues for AI systems worldwide will almost double to $12.5 billion this year, and keep growing at a similar rate until they hit $46 billion in 2020.

Mozilla has long been one of the strongest champions for openness in technology -- from the software it produces to the web standards it adopts. As new technologies emerge, the battle over closed versus open systems continues to be one of the most important factors for a range of concerns that are critical to a healthy information ecosystem -- innovation, competition, privacy, security, consumer protection -- and even civil rights. With new advances in artificial intelligence -- particularly in the fields of machine learning and sensor technology -- questions of "open" versus "closed" have arisen again. However, what is becoming quickly clear is that the traditional open strategies, such as permissive licensing and code/documentation publication, may not work as well or even at all. Consider deep learning, one of the key AI techniques driving advances such as automated speech recognition.

Public anonymity is quickly becoming a thing of the past. Coming soon to an airport in Dubai is an artsy, colorful video security and customs tunnel that scans your face, adds you to a database, indexes you with artificial intelligence, and decides if you're free to leave -- or not. By the end of summer 2018, Dubai International Airport's Terminal 3 will have replaced its security clearance counter with a walkway tunnel filled with 80 face-scanning cameras disguised as a distracting immersive video. Travellers' eyes will roam the enclosed tunnel and its virtual shimmering aquarium as they head to their gate, while their biometric data is seamlessly collected, compared, and stored .... somewhere, under unknown terms and conditions. According to officials presenting the security and customs tunnel at the 37th Gulf Information Technology Exhibition (GITEX) Technology Week at the World Trade Centre in Dubai, its video shows will not be limited to chicken of the sea.

Microsoft announced AI for Earth back in July as a way of demonstrating how artificial intelligence can help the planet. Under the program, Microsoft is awarding grants to research organisations that develop compelling ideas to protect elements of the environment. The most promising concepts, which use AI to push the boundaries of their research, are granted AI and cloud computing resources on Microsoft's Azure platform. The EU Oceans Award is available to European-based research groups that are looking at ways of protecting the oceans. Oceans and the habitats they harbour require massive amounts of computing power to accurately model.

Is it only humans that can possess knowledge? There's a widely held view that computers can't have knowledge: that a computer can only hold information, while it is the humans who programmed the computer who have the knowledge. The AKI model of David Williams correctly, in my view, explicitly ties knowledge to action. Any system that can perform autonomous actions in response to environmental cues is knowledgeable. The structures (biological, mechanical, and/or electronic) that determine responses are its knowledge.