Peter Singer raises the questions of ethics, given new developments in AI. Eric Schmidt, executive chairman of Google's parent company, the owner of AlphaGo, is enthusiastic about what artificial intelligence (AI) means for humanity. Speaking before the match between Lee and AlphaGo, he said that humanity would be the winner, whatever the outcome, because advances in AI will make every human being smarter, more capable, and "just better human beings." Around the same time as AlphaGo's triumph, Microsoft's "chatbot" – software named Taylor that was designed to respond to messages from people aged 18-24 – was having a chastening experience. "Tay" as she called herself, was supposed to be able to learn from the messages she received and gradually improve her ability to conduct engaging conversations.

Your math teacher lied to you. Sometimes getting your sums wrong is a good thing. So says Joseph Bates, cofounder and CEO of Singular Computing, a company whose computer chips are hardwired to be incapable of performing mathematical calculations correctly. Ask it to add 1 and 1 and you will get answers like 2.01 or 1.98. Pentagon research agency DARPA funded the creation of Singular's chip because that fuzziness can be an asset when it comes to some of the hardest problems for computers, such as making sense of video or other messy real world data. "Just because the hardware is sucky doesn't mean the software's result has to be," says Bates.

Computers may trounce humans at games like chess and Go, but there's one game we've still got a lock on: quantum physics. Scientists who had people play an online video game that mimicked a troublesome quantum mechanical problem found that the gamers were far better than the computers at working out viable solutions. The findings, published in the journal Nature, offer a surprisingly effective method of dealing with still-puzzling problems in quantum mechanics – and show that artificial intelligence may still have a lot to learn from the power of human intuition. Scientists have been working to develop quantum computers, which takes advantage of the bizarre ways in which matter behaves at the tiniest of scales. Quantum computers have the potential to vastly outstrip the abilities of conventional devices, allowing them to perform a wide range of complex tasks, from cracking encrypted codes to operating self-driving cars.

When the performance of an employee is evaluated, ideally there are no externalities to complicate the analysis. If the employee has a computer that is constantly freezing up - or the servers in the company frequently operate slowly - the employee's performance data will reflect the functionality and effectiveness of these systems. If the company occupies a highly competitive market, declining sales data is attributable at least in part to competition rather than the behaviours of employees. If managers implement significant restructuring, the outcomes would be apparent in the performance data of employees. Although it is desirable for performance data to be free of externalities, in practice this scenario seems unlikely. In performance, there is usually "internal association" of data - that is to say, the metrics are attributed to the behaviours of employees internally. But there are also "external antecedents" or determinants outside the direct control of employees. Since a worker tends to exercise little personal autonomy in many modern production settings, it is necessary to recognize how the data collected might be "internally disassociated": it is disconnected from the broader reality of production and also of the individual.

The Netherlands started the experiment to find ways to save fuel and lower carbon emissions. Two trucks traveling 160,000 kilometers (100,000 miles) could save 6,000 (approximately 6800 USD).

Facebook launched a concierge service called M through its Messenger app in 2015. M can purchase items, get gifts delivered, book restaurants, and make travel arrangements for the user. There is an element of the Mechanical Turk about it at the moment as it is powered by a combination of AI and real-life people. Siri has been around for a few years but has been upgraded in that time. It's now capable of showing the user specific photos he or she has taken, ordering things via ecommerce apps and giving directions.

AI Business recently interviewed one of the UK's leading experts in AI for Business, George Zarkadakis. George has a PhD in AI, is the Digital Lead at Willis Towers Watson, and the author of "In Our Own Image: will Artificial Intelligence save us or destroy us?". George is also a keynote speaker at The AI Summit London, presenting on the many different ways that AI will be shaping the business of tomorrow. George answered a number of interesting questions giving us a taster of the insightful presentation to come at The AI Summit on the 5th of May. How do you believe AI will impact business overall and in what ways?

With rotors and radios, we are witnessing the birth of a new sport. Aerial acrobatics, sharp turns and staggering climbs that NASCAR can only imagine, all done on the cheap with toys and remote controls, from woods to warehouses to special courses in Dubai. Welcome to the new age of drone racing, as it moves from backyards to broadcasts. Today, ESPN announced it will livestream the U.S. National Drone Racing Championships, a 3-day drone racing event held on New York City's Governor's Island in early August. And then, in October, ESPN will cover the 2016 World Drone Racing Championships at Kualoa Ranch, Hawaii. The drones are flown by pilots wearing goggles and watching through first person vision cameras.

We consider a statistical inverse learning problem, where we observe the image of a function $f$ through a linear operator $A$ at i.i.d. random design points $X_i$, superposed with an additive noise. The distribution of the design points is unknown and can be very general. We analyze simultaneously the direct (estimation of $Af$) and the inverse (estimation of $f$) learning problems. In this general framework, we obtain strong and weak minimax optimal rates of convergence (as the number of observations $n$ grows large) for a large class of spectral regularization methods over regularity classes defined through appropriate source conditions. This improves on or completes previous results obtained in related settings. The optimality of the obtained rates is shown not only in the exponent in $n$ but also in the explicit dependency of the constant factor in the variance of the noise and the radius of the source condition set.

Scientists have been able to develop artificial intelligence (AI) capable of besting humans at their own games, but a new study suggests that people may have the upper hand when it comes to intuitive thinking. A team of researchers led by Denmark's Aarhus University associate professor Jacob Sherson managed to develop a game based around complex theoretical science in which human players were "able to find solutions to difficult problems associated with the task of quantum computing," whereas computerized numerical optimization failed, according to the scientists' findings published in Nature. "The big surprise we had was that some of the players actually had solutions that were of higher quality and of shorter duration than any computer algorithms could find," Mr. Sherson told the Associated Press. The game, Quantum Moves, is available online for the purpose of helping in the development of quantum computing. While it functions as entertainment, Quantum Moves is built to take quantum physics optimization problems and turn them into a game, the results of which demonstrate fundamental differences between human thought processes and the problem solving of computers.