"Our generation will have to deal with tens of millions of jobs replaced by automation like self-driving cars and trucks," Harvard dropout and Facebook founder Mark Zuckerberg told Harvard's class of 2017 during the commencement speech on May 25. He glossed over that number rather casually, as though it didn't effect the people he was speaking to in any discernible way. Just one day earlier, Katja Grace at the Future of Humanity Institute at the University of Oxford and four other researchers published, "When Will AI exceed Human Performance? Source: "When Will AI exceed Human Performance? The researchers surveyed 1,634 of the world's leading experts in the field artificial intelligence in order to determine the time frame for the replacement of human beings by machines.

How a group of off-road pioneers brought the sport of four-wheeling to Vietnam, and along the way became a disaster relief squad. Their fleet of competition-ready, off-roading Toyota Land Cruisers include FJs that span four decades. We go behind the (very busy) scenes /b p Wimbledon's 15,000-seat Centre Court is serene and empty except for the 24-hour security guards protecting the most hallowed patch of grass in world … Long before there were musical instruments, the human voice was used to make beautiful music. It's no surprise that the beauty of singing has been … A good rocket launch site has a few important characteristics. Their stories came out slowly, even hesitantly, at first.

Businesses that put in the effort to create an artificially intelligent business may see amazing returns at first -- but there are good reasons to expect those to diminish. It would be very, very helpful to know what the future holds for artificial intelligence in business. Unfortunately, it is also very, very hard to predict. With this topic, our extrapolation heuristics may not work well. We tend to extrapolate linearly, expecting the pace of past progress to continue unchanged.

As lower-skill jobs are swept away by technology, economists are wondering what kinds of skills workers will need -- and how the economic benefits of automation will be distributed. Perhaps the hottest topic in economics these days is how far robots and artificial intelligence (AI) will go in replacing humans in the workplace -- and how quickly the changes will unfold. For decades, technology has been replacing mid-level jobs in the United States and other advanced economies. But the pace has quickened, with the effects billowing through not just automotive factories and electronics facilities but also law offices, operating rooms, and the roads we drive on. Some economists, including MIT's Erik Brynjolfsson and Andrew McAfee, have argued that, in addition to eliminating jobs, technology will also open the way to new ones.

The challenge we face today is not a "world without work" but a world with rapidly changing work. The pace of progress in AI and machine learning is accelerating rapidly. In the past month alone, these are just a few of the news items I've seen: Deep learning and neural networks have dramatically improved in effectiveness and impact, leading to human-level performance in many aspects of vision, conversational speech, and problem-solving. As a result, industries are in the midst of a major transformation and more is on the way. Median income in America is lower now than in the past 15 years, and wealth is concentrated at the highest levels.

Steve Grand is currently teaching his children how to pee. Rather, he's teaching them to notice that mental niggle with which we're all familiar, the sense of a mounting pressure in some deep place that clues us to the fact that our bladder is full and we need to do something about it, quickly. Grand's children -- this current batch, at least -- have taken their father's name. The Grandroids, as they're known, are bug-eyed, quadrupedal animals. They look a bit like shaven dogs with giant octopus suckers for mouths (although that may radically change in the coming months).

In the days of ever-changing playlists and unlimited Soundcloud mixes it might seem strange that something as simple as a compilation album could change the course of music. And yet that was what happened 25 years ago this month, in July 1992, with the release of Warp Records' first Artificial Intelligence compilation. It was a record that helped to launch the careers of Autechre, Aphex Twin and Richie Hawtin, birthed the genre that would later become known as intelligent dance music (or IDM), and changed the idea of electronic music as merely a tool for dancing. Artificial Intelligence wore its heart on its sleeve: the front cover features an android slumped in an armchair in front of a stereo, with albums from Kraftwerk and Pink Floyd scattered around. Below this, the tagline "electronic listening music from Warp" spelled out the compilation's modus operandi: this was electronic music for the home, not the rave – a notion that was largely foreign 25 years ago.

Germany may soon launch an investigation into Facebook over the social network's broad privacy policy that allows it to collect massive amounts of information from users. They, in part, blame the "fine print" of Facebook's terms of service. The Federal Cartel Office, Germany's national competition regulator, believes Facebook is "extorting" its users by making them agree to terms and conditions they may not fully understand in order to use the popular service. German regulators have also floated the possibility that anti-trust actions could use this angle in the courts. Read: Why Was Google Fined $2.7 Billion By The European Union?

The number of near-misses between drones and aircraft has more than doubled, with more than one occurring each week. As ministers came under pressure from the Solicitor General to crack down on drones after a major scare at Gatwick Airport, industry figures reveal the growing threat posed to passengers by these devices. Pilots warn that a'disaster' is inevitable unless tougher laws are introduced. Latest statistics from the UK Airprox Board, which monitors the risk of mid-air collisions, show there were 33 near-misses between drones and planes or helicopters in the first five months of the year. It means 2017 is on course to become the worst year for close calls on record, despite desperate attempts by pilots to persuade the Government to take action.

Complex systems can be modelled at various levels of detail. Ideally, causal models of the same system should be consistent with one another in the sense that they agree in their predictions of the effects of interventions. We formalise this notion of consistency in the case of Structural Equation Models (SEMs) by introducing exact transformations between SEMs. This provides a general language to consider, for instance, the different levels of description in the following three scenarios: (a) models with large numbers of variables versus models in which the `irrelevant' or unobservable variables have been marginalised out; (b) micro-level models versus macro-level models in which the macro-variables are aggregate features of the micro-variables; (c) dynamical time series models versus models of their stationary behaviour. Our analysis stresses the importance of well specified interventions in the causal modelling process and sheds light on the interpretation of cyclic SEMs.