Division of Biological Sciences, University of California San Diego, La Jolla, California 92093 USA Abstract: Deep learning networks have been trained to recognize speech, caption photographs and translate text between languages at high levels of performance. Although applications of deep learning networks to real world problems have become ubiquitous, our understanding of why they are so effective is lacking. These empirical results should not be possible according to sample complexity in statistics and non-convex optimization theory. However, paradoxes in the training and effectiveness of deep learning networks are being investigated and insights are being found in the geometry of high-dimensional spaces. A mathematical theory of deep learning would illuminate how they function, allow us to assess the strengths and weaknesses of different network architectures and lead to major improvements. Deep learning has provided natural ways for humans to communicate with digital devices and is foundational for building artificial general intelligence. Deep learning was inspired by the architecture of the cerebral cortex and insights into autonomy and general intelligence may be found in other brain regions that are essential for planning and survival, but major breakthroughs will be needed to achieve these goals. This book was written as a satire on Victorian society, but it has endured because of its exploration of how dimensionality can change our intuitions about space. Flatland was a two-dimensional world inhabited by geometrical creatures. The mathematics of two dimensions was fully understood by these creatures, with circles being more perfect than triangles. In it a gentleman square has a dream about a sphere and wakes up to the possibility that his universe might be much larger than he or anyone in flatland could imagine.

Recent research on reinforcement learning in pure-conflict and pure-common interest games has emphasized the importance of population heterogeneity. In contrast, studies of reinforcement learning in mixed-motive games have primarily leveraged homogeneous approaches. Given the defining characteristic of mixed-motive games--the imperfect correlation of incentives between group members--we study the effect of population heterogeneity on mixed-motive reinforcement learning. We draw on interdependence theory from social psychology and imbue reinforcement learning agents with Social Value Orientation (SVO), a flexible formalization of preferences over group outcome distributions. We subsequently explore the effects of diversity in SVO on populations of reinforcement learning agents in two mixed-motive Markov games. We demonstrate that heterogeneity in SVO generates meaningful and complex behavioral variation among agents similar to that suggested by interdependence theory. Empirical results in these mixed-motive dilemmas suggest agents trained in heterogeneous populations develop particularly generalized, high-performing policies relative to those trained in homogeneous populations.

A bionic arm capable of handling eggs and playing the piano developed to mimic the human hand could'speed up the introduction of robots into our every day lives'. Developer Dr Hyunmin Do from the Korea Institute of Machinery and Materials says the incredibly dexterous hand is also able to pour water and handle scissors. The device consists of four fingers, each with three joints - making them as flexible as a human hand but with a stronger grip. It uses 12 motors to enable it to move in various directions and the grip can be changed depending on the item it is holding or manipulating. The team say it could be used in factories or industry and will allow robots to'physically interact with the world in a more meaningful way'.

As Valentine's Day approaches and the aroma of love turns even devout singletons into frenzied love-seekers, many will invariably turn to dating apps for help. But caving in and venturing into the murky world of Hinge, Tinder and Bumble is a poisoned chalice, doomed to fail even if it works, a new study reveals. Academics have found people who have success in the fickle world of virtual swiping perceive themselves to be desirable as a result of their conquests. This sense of self-desirability, it has been proved, makes a person more likely to cheat when they eventually settle down into a serious relationship. Dr Cassandra Alexopoulos of the University of Massachusetts led the research and quizzed 395 participants on their dating app use.

Researchers at the University of Buffalo have received a $316,000 grant from the Defense Advanced Research Projects Agency (DARPA), an agency funded by the US Department of Defense, to develop an artificial intelligence capable of controlling swarms of up to 250 drones. To created the experimental AI, scientists from the university's Artificial Intelligence Institute will study video game players as they pilot autonomous swarms of digital military units in real time strategy games like StarCraft, Stellaris, and Company of Heroes. The team will collect data on how the players react to a wide variety of different tactical challenges as well as watching how they react to unexpected changes in the terrain or terms of battle. Researchers at the University of Buffalo's Artificial Intelligence Institute will study the way video game players make choices in real time strategy games like StarCraft and Company of Heroes to develop an AI that can control swarms of up to 250 drones'We don't want the AI system just to mimic human behavior; we want it to form a deeper understanding of what motivates human actions,' University of Buffalo's Souma Chowdhury told the school's news site. 'That's what will lead to more advanced AI.' The team will also collect a range of biometric data from the players, through eyetracking software and electroencephalograms, which monitors brain activity while they play.

The Norwegian oil company Aker BP ASA has announced it will bring aboard the infamous robotic watchdog Spot on the company's ships in the Skarv region of the Norwegian Sea. According to Aker, Spot will be charged with sniffing out hydrocarbon leaks, inspecting ship equipment, taking mechanical readings, generating reports, and completing inspections in areas that might be too dangerous for human workers. Spot was developed by the Massachusetts-based robotics company Boston Dynamics, which specializes in developing autonomous and humanoid machines. The Norwegian oil company Aker BP ASA announced it will begin using Boston Dynamics' robotic watchdog on Spot (pictured above) to help monitor equipment on its ships in the Norwegian Sea'These things never get tired, they have a larger ability to adapt and to gather data,' Aker BP ASA's Kjetel Digre told Bloomberg. The announcement is part of the Aker's new emphasis on'digitalization,' which it hopes will make its ships safer and more productive.

Robots are said to take over some 200,000 jobs on Wall Street over the next decade and a new study suggests this prediction could soon become a reality. Following the analysis of 76,000 reports from seven different robo-analysis firms, researchers determined that the technology is able to make recommendations similar to their human counterparts - but faster and more accurately. Because the automation is less subject to behavioral biases and conflicts of interest, it can produce a more balanced distribution of ratings, which includes investment's risk and suggestions whether to hold, sell or purchase. Looking at the robot portfolios, the study found their buy recommendations earned returns from 6.4 percent to 6.9 percent, while those of its human counterparts only ranged from 1.2 percent to 1.7 percent. Although robo-analysis sounds like it could weed out human investors, researchers believe that as long as there are people that need human interaction, 'the buy-side, the sell-side will still be around.' Because the automation is less subject to behavioral biases and conflicts of interest, it can produce a more balanced distribution of ratings, which includes investment's risk and suggestions whether to hold, sell or purchase (stock photo) The study was conducted by a team at Indiana University, who wrote: 'Our study provides the first comprehensive analysis of the properties of investment recommendations generated by'Robo-Analysts,' which are human-analyst assisted computer programs conducting automated research analysis.

According to a new scientific study, a nuclear attack of 100 bombs could harm the entire planet including the aggressor nation. Since the creation of the atom bomb, the threat of nuclear war has loomed. Endless films and books have dealt with the nuclear apocalypse and its aftermath, but what would a nuclear apocalypse really look like? Rutgers University Professor Alan Robock spoke with Fox News about the Armageddon and his team's new study regarding a nuclear war's effects on ocean life. If you live in a major city when a nuke hits, needless to say, you're in big trouble.

And as the injury toll has mounted, veterans groups and others have levied criticism at the White House, in part because, in January, President Trump dismissed the injuries as "not very serious." "I heard that they had headaches and a couple of other things," Mr. Trump said at a news conference Jan. 22 in Davos, Switzerland. "I don't consider them very serious injuries relative to other injuries I have seen." At least a dozen missiles were fired during the attack, which was a retaliation for the killing of a top Iranian general, Qassim Suleimani, by an American drone strike in Baghdad on Jan. 3. The Trump administration at first said there were no injuries, but a week later said several service members were evaluated for possible concussions.

As the deadly 2019-nCov coronavirus spreads, raising fears of a worldwide pandemic, researchers and startups are using artificial intelligence and other technologies to predict where the virus might appear next -- and even potentially sound the alarm before other new, potentially threatening viruses become public health crises. "What we're doing currently with Coronavirus is really trying to get an understanding of what's happening on the ground through as many sources as we can get our hands on," says John Brownstein, chief innovation officer at Boston Children's Hospital and a professor at Harvard Medical School. After SARS killed 774 people around the world in the mid-2000s, his team built a tool called Healthmap, which scrapes information about new outbreaks from online news reports, chatrooms and more. Healthmap then organizes that previously disparate data, generating visualizations that show how and where communicable diseases like the coronavirus are spreading. Healthmap's output supplements more traditional data-gathering techniques used by organizations like the U.S. Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO).