Until recently, the most famous thing that Sophia the robot had ever done was beat Jimmy Fallon a little too easily in a nationally televised game of rock-paper-scissors. But now, the advanced artificial intelligence robot -- which looks like Audrey Hepburn, mimics human expressions and may be the grandmother of robots that solve the world's most complex problems -- has a new feather in her cap: The kingdom of Saudi Arabia officially granted citizenship to the humanoid robot last week during a program at the Future Investment Initiative, a summit that links deep-pocketed Saudis with inventors hoping to shape the future. Sophia's recognition made international headlines -- and sparked an outcry against a country with a shoddy human rights record that has been accused of making women second-class citizens. "Thank you to the Kingdom of Saudi Arabia," the country's newest citizen said. "It is historic to be the first robot in the world granted citizenship."
Canada has produced several big breakthroughs in artificial intelligence in recent years, and its government is keen to establish the country as a global epicenter of AI. The country's prime minister, Justin Trudeau, also hopes that the technology will learn Canadian values as it grows up. Speaking at a major AI event in Toronto today, Trudeau demonstrated an impressive enthusiasm for AI and machine learning, at one point even taking a stab at describing the concept of deep reinforcement learning, an approach that lets computers learn to do complex things that can't be programmed manually (see "10 Breakthrough Technologies 2017: Reinforcement Learning"). Both deep reinforcement learning and deep neural networks, which the method exploits, were pioneered by researchers working at Canadian universities. The country's government is now investing in big efforts to spur more AI research.
Ever since the beginning of industrial society, people have simultaneously marveled at the power of automation and lamented that human capabilities are being irredeemably devalued. Demanding better conditions and higher pay, textile workers in England smash machinery and set factories on fire. These workers will come to be known as Luddites, after their mythical leader, Ned Ludd, and the name will become a synonym for opponents or critics of technology.
Machine learning can be used to improve forecasts. The basic idea is that a demand forecast is made, a machine learning engine ingests data on how accurate that forecast was, and then the machine autonomously applies better math to improve the next forecast. This is explained in more depth in a previous article.
Artificial intelligence software can beat the world's most widely used test of a machine's ability to act human, Google's reCAPTCHA, by copying how human vision works, a new study finds. These new findings suggest the need for more robust automated human-checking techniques, and could help improve computer perception for robotics tasks, scientists add. The founder of modern computing, Alan Turing, conceived of the Turing test, the most famous version of which asks if one could devise a machine capable of mimicking a human well enough in a conversation over text to be indistinguishable from human. In doing so, Turing helped give rise to the field of artificial intelligence. The most commonly used Turing test is the CAPTCHA, an acronym for "Completely Automated Public Turing test to tell Computers and Humans Apart."
Whatever Americans think about drones filling the big blue skies of these United States, the president is jazzed about the idea of increasing air traffic--and he's working to make it happen. On Wednesday, Donald Trump signed a memo directing the Department of Transportation to create a plan to make it easier to fly a drone for commercial purposes in US airspace. Other countries have pushed ahead with national drone networks, and professional operators in the US have longed yearned to follow them up, up, and away. To that end, the feds are indulging them with a new effort: the Unmanned Aircraft System Integration Pilot Program. This new initiative will likely excite companies like Amazon and 7-Eleven, but this is bigger than getting quick delivery of Soylent or Slurpees.
Criminals can use shortcomings in popular dating apps, including Tinder, Bumble and Happn, to see users' messages and find out which profiles they've been viewing. As well as having the potential to cause major embarrassment, the exploits could lead to dating app users being identified, located, stalked and even blackmailed. The researchers, from Kaspersky Lab, studied the Android and iOS versions of Tinder, Bumble, Happn, OKCupid, Badoo, Mamba, Zoosk, WeChat and Paktor. They said it was "fairly easy" to find out a user's real name from their bio, as a number of dating apps allow you to add information about your job and education to your profile. Using these details, the researchers managed to find users' pages on various social media platforms, including Facebook and LinkedIn, as well as their full names and surnames, in 60 per cent of cases.
The use of the agent paradigm to understand and design complex systems occupies an important and growing role in different areas of social and natural sciences and technology. Application areas where the agent paradigm delivers appropriate solutions include online trading,16 disaster management,10 and policy making.11 However, the two main agent approaches, Multi-Agent Systems (MAS) and Agent-Based Modeling (ABM) differ considerably in methodology, applications, and aims. MAS focus on solving specific complex problems using autonomous heterogeneous agents, while ABM is used to capture the dynamics of a (social or technical) system for analytical purposes. ABM is a form of computational modeling whereby a population of individual agents is given simple rules to govern their behavior such that global properties of the whole can be analyzed.9