Chatbots and self-driving trucks are revolutionising the way we live, work and travel. In today's reality, using artificial intelligence (AI) bots such as Alexa, Cortana, or Siri, have become the new normal. Technology is so integrated in our daily lives, that we almost can't imagine a life without it. It helps individuals and companies to streamline activities, save time and organise schedules, to work faster and more efficient and live in new places around the world. In a world with no boundaries, AI chatbots and self-driving trucks amongst other technology are part of the future of HR and global mobility.

A group of young kids is entranced -- all the more so because Sella is not actually there. Her likeness is being beamed in the form of an interactive and moving hologram, part of a first-of-its-kind exhibition debuting this weekend at the Illinois Holocaust Museum, which aims to preserve accounts of a fast-disappearing generation. "She has their undivided attention," said teacher Samantha O'Neill of Chicago's Northside Catholic Academy. "It really does look like she is sitting on the stage in front of you." The exhibit uses voice-recognition technology and machine learning to let visitors ask questions about survivors' World War II ordeals and hear answers that will grow more relevant as the technology learns.

In addition, the Internet Society was asked to send written comments, which are reprinted here. AI is not new, nor is it magic. "Intelligent" technology is already everywhere – such as spam filters or systems used by banks to monitor unusual activity and detect fraud – and it has been for some time. What is new and creating a lot of interest from governments stems from recent successes in a subfield of AI known as "machine learning," which has spurred the rapid deployment of AI into new fields and applications. It is the result of a potent mix of data availability, increased computer power and algorithmic innovation that, if well harnessed, could double economic growth rates by 2035. So, governments' reflection on what good policies should look like in this field is both relevant and timely.

The UAE has appointed Omar Bin Sultan Al Olama, aged 27, as the country's first minister of State for Artificial Intelligence (AI) as part of a cabinet reshuffle. Earlier, Sheikh Mohammed bin Rashid Al Maktoum, vice president, prime minister and ruler of Dubai, announced the UAE Strategy for artificial intelligence, a major part of the UAE Centennial 2070 objectives. The AI initiative aims to improve government performance and create an innovative and highly-productive environment by means of investing in AI. "We initiated electronic services 16 years go and today we are launching a fresh stage relying on Artificial Intelligence," Sheikh Mohammed said. "We are seeking to adopt tools and methodologies related to artificial intelligence to expedite and ensure more efficiency for government services at all levels." In the last significant structural change, Sheikh Mohammed announced in February last year that the UAE will outsource most government tasks to the private sector and cut the number of ministries.

As questions continue to mount about the Niger firefight that killed four U.S. soldiers in early October, here's a timeline on what happened based on new details from the Department of Defense. U.S. military officials sought permission to send an armed drone near a patrol of Green Berets before a deadly ambush Oct. 4 in Niger, but the request was blocked, raising questions about whether those forces had adequate protection against the dangers of their mission. New information shows the Green Beret team was part of a larger mission, one potentially more dangerous than initially described, and one believed to merit an armed drone. But the request was blocked in a chain of approval that snakes through the Pentagon, State Department and the Nigerien government, according to officials briefed on the events. One focus of military investigations into what happened in Niger will be what a military official now says were two changes in the mission of the Green Beret team--from initially training Nigerien forces, to advising on a mission to capture or kill a wanted terrorist, to investigating the terrorist's abandoned camp.

Kumar discusses the guiding ideas behind his research on micro unmanned aerial vehicles, gives his thoughts on the future of robotics in the lab and field, and speaks about setting realistic expectations for robotics technology. Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering with appointments in the Departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. Dr. Kumar received his Bachelor of Technology degree from the Indian Institute of Technology, Kanpur and his Ph.D. from The Ohio State University in 1987. He has been on the Faculty in the Department of Mechanical Engineering and Applied Mechanics with a secondary appointment in the Department of Computer and Information Science at the University of Pennsylvania since 1987. In his time at the university, Dr. Kumar has held numerous positions including director of the GRASP Laboratory, Chairman of the Department of Mechanical Engineering and Applied Mechanics, and Deputy Dean for Education in the School of Engineering and Applied Science.

Background: Statistical mechanics results (Dauphin et al. (2014); Choromanska et al. (2015)) suggest that local minima with high error are exponentially rare in high dimensions. However, to prove low error guarantees for Multilayer Neural Networks (MNNs), previous works so far required either a heavily modified MNN model or training method, strong assumptions on the labels (e.g., "near" linear separability), or an unrealistic hidden layer with $\Omega\left(N\right)$ units. Results: We examine a MNN with one hidden layer of piecewise linear units, a single output, and a quadratic loss. We prove that, with high probability in the limit of $N\rightarrow\infty$ datapoints, the volume of differentiable regions of the empiric loss containing sub-optimal differentiable local minima is exponentially vanishing in comparison with the same volume of global minima, given standard normal input of dimension $d_{0}=\tilde{\Omega}\left(\sqrt{N}\right)$, and a more realistic number of $d_{1}=\tilde{\Omega}\left(N/d_{0}\right)$ hidden units. We demonstrate our results numerically: for example, $0\%$ binary classification training error on CIFAR with only $N/d_{0}\approx 16$ hidden neurons.

Some people are afraid that heavily armed artificially intelligent robots might take over the world, enslaving humanity--or perhaps exterminating us. These people, including tech-industry billionaire Elon Musk and eminent physicist Stephen Hawking, say artificial intelligence technology needs to be regulated to manage the risks. But Microsoft founder Bill Gates and Facebook's Mark Zuckerberg disagree, saying the technology is not nearly advanced enough for those worries to be realistic. As someone who researches how AI works in robotic decision-making, drones and self-driving vehicles, I've seen how beneficial it can be. I've developed AI software that lets robots working in teams make individual decisions as part of collective efforts to explore and solve problems.

Elizabeth LaPensee received nearly $3,300 from Minnesota's Arts and Cultural Heritage Fund to create "Thunderbird Strike ." She worked then at the University of Minnesota Duluth but took a job last year at Michigan State University.

The right to due process was inscribed into the US constitution with a pen. A new report from leading researchers in artificial intelligence cautions it is now being undermined by computer code. Public agencies responsible for areas such as criminal justice, health, and welfare increasingly use scoring systems and software to steer or make decisions on life-changing events like granting bail, sentencing, enforcement, and prioritizing services. The report from AI Now, a research institute at NYU that studies the social implications of artificial intelligence, says too many of those systems are opaque to the citizens they hold power over. The AI Now report calls for agencies to refrain from what it calls "black box" systems opaque to outside scrutiny. Kate Crawford, a researcher at Microsoft and cofounder of AI Now, says citizens should be able to know how systems making decisions about them operate and have been tested or validated.