A bizarre drone designed to take the hassle out of walking your dog is being advertised by an online retailer. Drones Direct say that they have modified a popular automated aerial vehicle to allow owners to take their pet for a stroll completely hands free. The device uses GPS to lead dogs along a programmed route. Their DJI Phantom 4 Dog Drone, which the firm insists is a genuine product, costs twice the price of the regular model at £1,999 ($2,590). A bizarre drone designed to take the hassle out of walking your dog is being advertised by an online retailer.

These and other findings are from the McKinsey Global Institute Study, and discussion paper, Artificial Intelligence, The Next Digital Frontier (80 pp., PDF, free, no opt-in) published last month. McKinsey Global Institute published an article summarizing the findings titled How Artificial Intelligence Can Deliver Real Value To Companies. McKinsey interviewed more than 3,000 senior executives on the use of AI technologies, their companies' prospects for further deployment, and AI's impact on markets, governments, and individuals. McKinsey Analytics was also utilized in the development of this study and discussion paper. The current rate of AI investment is 3X the external investment growth since 2013.

Robots across the world help out in factories by taking on heavy lifting or repetitive jobs, but the walking, talking kind may soon collaborate with people, thanks to European robotics researchers building prototypes that anticipate human actions. 'Ideally robots should be able to sense interactional forces, like carrying a table with someone,' said Francesco Nori, who coordinates the EU-funded An.Dy project which aims to advance human-robot collaboration. '(Robots) need to know what the human is about to do and what they can do to help.' In any coordinated activity, whether dancing or lifting a table together, timing is crucial and that means a robot needs to anticipate before a person acts. 'Today, robots just react – half a second of anticipation might be enough,' said Nori, who works at the Italian Institute of Technology which is renowned for its humanoid robot called iCub, that will be educated in human behaviour from data collected during the An.Dy project.

The robotics work programme implements the robotics strategy developed by SPARC, the Public-Private Partnership for Robotics in Europe (see the Strategic Research Agenda). EuRobotics regularly publishes video interviews with projects, so that you can find out more about their activities. ILIAD is driven by the industry needs for highly flexible robot fleets operating in spaces shared with humans. The main objectives are care-free, fast, and scalable deployment; long-term operation while learning from observed activities; on-line, self-optimising fleet management; human-aware fleets that can learn human behaviour models; compliant unpacking and palletising of goods; and a systematic study of human safety in shared environments, setting the stage for future safety certification. ILIAD's focus is on the rapidly expanding intralogistics domain, where there is a strong market pull for flexible automated solutions, especially ones that can blend with current operations.

Scyfer was established about four years ago at Amsterdam Science Park as a spinoff of the University of Amsterdam. The company works with the latest and most advanced technologies in the field of deep learning. Founder and CEO of Scyfer is Max Welling, professor of Machine Learning at the Faculty of Natural Sciences, Mathematics and Informatics at the University of Amsterdam. He is also employed at the University of California Irvine, the Canadian Institute for Advanced Research (CIFAR).

With threats, bribes, diplomacy and sanctions, American presidents of both parties have sought for 25 years to try to halt, or at least slow, North Korea's quest for a nuclear arsenal -- to no avail. Though the brinksmanship of the last few weeks has subsided, President Trump still faces the prospect of a madman -- Kim Jong Un -- in control of a nuclear arsenal. What the United States and its allies must now do is find options between conventional war, or even nuclear holocaust, on the one hand, and appeasement on the other. The answer could be robotic, cyber, and space weapons -- if we have the will to deploy them. They already have been used for pinpoint strikes on terrorist leaders and insurgent forces in the Mideast.

Henri Waelbroeck, director of research at machine learning trade execution system Portware, says rather poetically that the system "reads the tea leaves" in market data to distinguish different sorts of orders and execute trades more efficiently. Portware uses artificial intelligence to help traders select the best algorithm for particular market conditions, asset class, broker, venue etc., interacting with the order flow and computing a mind-boggling array of variables in real time. Say you are buying a stock, and you predict there is likely to be more orders hitting the bid side of the spread in the next five minutes, you should be able to operate an efficient algorithm that only posts limit orders and collects the spread as it executes. Using an algorithm that crosses the spread in this instance would be wasteful since you expect order flow to be coming your way. Waelbroeck, formerly a professor at the Institute of Nuclear Sciences at the National University of Mexico, whose specialisms include genetic algorithms and chaos theory, said: "Just throwing machine learning at problems usually doesn't give a very good answer. You need to have a good analytical understanding of what's going on and this usually gives you a baseline model and then you find opportunities to insert machine learning tactically to exploit opportunities to improve the models."

Last year, the Japanese company SoftBank opened a cell phone store in Tokyo and staffed it entirely with sales associates named Pepper. This wasn't as hard as it sounds, since all the Peppers were robots. Humanoid robots, to be more precise, which SoftBank describes as "kindly, endearing, and surprising." Each Pepper is equipped with three multidirectional wheels, an anticollision system, multiple sensors, a pair of arms, and a chest-mounted tablet that allows customers to enter information. Pepper can "express his own emotions" and use a 3-D camera and two HD cameras "to identify movements and recognize the emotions on the faces of his interlocutors."

SITTING IN AN office in San Francisco, Igor Barani calls up some medical scans on his screen. He is the chief executive of Enlitic, one of a host of startups applying deep learning to medicine, starting with the analysis of images such as X-rays and CT scans. It is an obvious use of the technology. Deep learning is renowned for its superhuman prowess at certain forms of image recognition; there are large sets of labelled training data to crunch; and there is tremendous potential to make health care more accurate and efficient. Dr Barani (who used to be an oncologist) points to some CT scans of a patient's lungs, taken from three different angles.

Undoubtedly, over the next few decades, artificial intelligence (AI) will begin to shape the world as Industry 4.0 prevails. Two of the world's most powerful businessmen Mark Zuckerberg and Elon Musk are already debating the merits of this phenomenon. Musk claims that AI is a "fundamental risk to the existence of civilisation", whilst Zuckerberg is presenting more of a positive stance. Whilst this claim may prove to be true or not, as the use of AI imprints on society further, time will reveal its benefits and shortcomings. Hopefully not before it is too late, as some report that technology is now growing faster than humans are adapting to it. This article will explore some artificial intelligence solutions to some of the most pressing challenges the world faces today.