In the neo-noir sci-fi classic, protagonist Neo is able to learn kung fu in seconds after the martial art is'uploaded' straight to his brain. Researchers from HRL Laboratories, based in California, say they have found a way to amplify learning, only on a much smaller scale than seen in the Hollywood film. They studied the electric signals in the brain of a trained pilot and then fed the data into novice subjects as they learned to pilot an aeroplane in a realistic flight simulator. The study, published in the journal Frontiers in Human Neuroscience, found that subjects who received brain stimulation via electrode-embedded head caps improved their piloting abilities and learnt the task 33 per cent better than a placebo group.

Microsoft has created an artificial intelligence chat bot that is designed to become smarter the more people talk to it on social media sites such as Twitter. The bot, whose Twitter handle is'Tayandyou', has been dubbed by its creators as an "AI fam from the internet that's got zero chill." It has been created to allow researchers to help AI develop conversational understanding and and communicate in a human way. As well as being on Twitter it is also on messaging platforms Kik and GroupMe. It is explicitly aimed at 18-24-year-olds and speaks like a Millennial by incluidng emojis in its conversations.

In the neo-noir sci-fi classic, protagonist Neo is able to learn kung fu in seconds after the martial art is'uploaded' straight to his brain. Researchers from HRL Laboratories, based in California, say they have found a way to amplify learning, only on a much smaller scale than seen in the Hollywood film. They studied the electric signals in the brain of a trained pilot and then fed the data into novice subjects as they learned to pilot an aeroplane in a realistic flight simulator. The study, published in the journal Frontiers in Human Neuroscience, found that subjects who received brain stimulation via electrode-embedded head caps improved their piloting abilities and learnt the task 33 per cent better than a placebo group.

Organisations have begun to shift their analytical efforts to back office operations and away from more customer-facing processes in a search for greater competitive advantage, according to a new report. More than two thirds of companies, based on feedback from 600 operations executives surveyed as part of a report from Capgemini Consulting's digital transformation institute, revealed there is now a greater focus on operational analytics initiatives, in order to boost efficiency behind the scenes. Anne-Laure Thieullent, head of big data, Europe, for Capgemini's insights and data global practice, said: "Organisations are pivoting towards operational analytics as it can both increase the efficiency and performance of the back office as well as boost the customer experience in the front office. However, despite the focus, there are factors limiting the success of these projects; specifically siloed datasets, fragile governance models, inability to harness third party data sources, and an absence of a strong mandate from leadership teams." The four levels of maturity for operational analytics, as decided by Capgemini Consulting, are'Game Changers' - those who have both integrated analytics and realised its benefits, 'Optimisers' - those who have seen basic success but not yet scaled-up efforts, 'Strugglers' - who have adopted the analytics strategy without seeing the benefits, and'Laggards' - who are just beginning to focus on operational analytics.

Depending on who you talk to, artificial intelligence (AI) will either be the saviour or nemesis of mankind. Elon Musk, of PayPal, Tesla Cars and SpaceX (sometimes described as a real life Iron Man) has likened AI to "summoning a demon" – i.e. once it's truly here it can't be controlled. Meanwhile, Demis Hassabis (himself referred to as a superhero of AI), founder of DeepMind Technologies – a British AI start-up acquired by Google in 2014 for 400 million – is on a quest for what he calls "the meta-solution to any problem" through AI. Debate will rightly rage about the future of AI, but what about the now? Research and development (R&D) into artificial intelligence has been going on for decades.

We don't yet understand either how to set or govern the rules of the new autonomous vehicle driving era – we need public debate before AV technology becomes widespread on our streets. On the 10 February 2016 the US National Highway Traffic Safety Administration agreed to classify Google's artificial intelligence system as the legal'driver' of its automated vehicles (AVs). With this regulatory recognition, artificial intelligence and navigation systems' future role on our streets seems assured. But I believe we don't yet understand either how to set or govern the rules of this new driving era. To date, safety has been the main concern. How will the AVs interact with pedestrians, cyclists and human driven vehicles?

Somewhere in a Cupertino warehouse, a giant labors with robotic precision, its 29 arms singularly focused on one thing: an iPhone. But instead of putting pieces together, this robot is pulling pieces apart. It disassembles iPhones at the rate of one handset every 11 seconds--less time than it takes you to fish your phone out of an overcrowded bag. Apple calls the machine Liam. The project was kept secret for three years, says Mashable deputy tech editor Samantha Murphy Kelly, who was allowed a sneak preview of Liam in action.

We hear a lot about the Internet of Things on the consumer side. The oft trotted out example of the'smart' refrigerator that tells consumers when they've run out of the milk, and so on. But more serious potential for IoT -- and potentially seriously big wins -- are likely to be on the enterprise side where connected sensors can be deployed to automate at scale. The company took in a 6 million Series A round in December, which it's just announcing now -- and which includes, on top of that, a 3 million convertible seed, bringing its total raised to date to 9 million. Investors in the business include Jabil Circuit, Stanford StartX Fund, Founder.org

In recent years, global business leaders have increasingly embraced the power of the cloud, with its 24/7 availability, scalable performance and variable costs. But the merger of these on-demand capabilities with artificial/machine intelligence (AI/MI) is a new phase in digital innovation that has not yet been sufficiently appreciated by senior management. New research from the Leading Edge Forum (LEF) shows how the combination of cloud computing and machine intelligence is shaping the business models of the future, marking a new phase in digital innovation. AI advances used to stem mostly from academic investigations and the expert system initiatives of large organisations, but there's been a fundmental shift in recent years and progress is now driven by the consumer marketplace. See also: The droids you're looking for: the AI tech that will make up the intelligent enterprise'Virtually every type of human intelligence is becoming the basis of a scalable, cloud-based, global business model.

Over July 4th weekend in 1981, several hundred game nerds gathered at a banquet hall in San Mateo, California. Personal computing was still in its infancy, and the tournament was decidedly low-tech. Each match played out on a rectangular table filled with paper game pieces, and a March Madness-style tournament bracket hung on the wall. The game was called Traveller Trillion Credit Squadron, a role-playing pastime of baroque complexity. Contestants did battle using vast fleets of imaginary warships, each player guided by an equally imaginary trillion-dollar budget and a set of rules that spanned several printed volumes. If they won, they advanced to the next round of war games--until only one fleet remained. Doug Lenat, then a 29-year-old computer science professor at nearby Stanford University, was among the players. But he didn't compete alone. He entered the tournament alongside Eurisko, the artificially intelligent system he built as part of his academic research. Eurisko ran on dozens of machines inside Xerox PARC--the computer research lab just down the road from Stanford that gave rise to the graphical user interface, the laser printer, and so many other technologies that would come to define the future of computing. That year, Lenat taught Eurisko to play Traveller. Doug Lenat says his common-sense engine is a new dawn for AI. The rest of the tech world doesn't really agree with him.