Game theory plays a fundamental factor in modern artificial intelligence(AI) solutions. Specifically, deep reinforcement learning(DRL) is an area of AI that embraced game theory as a first-class citize. From single-agent programs to complex multi-agent DRL environments, gamifying dynamics are present across the lifecycle of AI programs. The fascinating thing is that the rapid evolution of DRL has also triggered a renewed interesting in game theory research. The relationship between game theory and DRL seems trivial.

By now you've seen the big news about the world's largest fast-food chain by revenue. It was a bit shocking that it took this long to happen, but McDonald's (MCD) is finally embracing advanced technologies like artificial intelligence to boost sales. The guy credited with the turnaround at the 65-year-old restaurant behemoth since 2015, Steve Easterbrook, was behind the technological push that saw McDonald's not only embrace digital innovation but acquire two AI companies this year. This is big news for a few reasons. Before this year, it had been nearly two decades since the company made its last acquisition of a mediocre fast-food chain called Boston Chicken.

Smart cities are no longer a utopian dream of the future. Thanks to a slew of innovative and game-changing technologies, they are already active and growing quickly. Smart cities could be described as the junction between three main areas, namely digital transformation, environmental sustainability and economic performance. They can be described as a framework made up of connected technologies designed to address the challenges of rapid urbanisation and promote more sustainable, smarter practices. And the more urbanisation soars, standards of living sustainability become more than pipe dreams, but rather calls for action.

There's been significant growth in the AI for Drug Discovery sector this year. In the last quarter, the number of R&D centers increased by 5, companies increased by 20, collaborations increased by 30, and investors increased by 50. There are now 400 investors investing in AI for Drug Discovery including Google Ventures, Tencent, WuXi, Andreessen Horowitz, Khosla Ventures, and Sequoia Ventures. This week, Deep Knowledge Analytics Pharma Division published Landscape of AI for Drug Discovery and Advanced R&D Q2 2019. This report is the most comprehensive analytical report on the AI for Drug Discovery sector to date.

In a classic start-up setting -- in a former textile plant four miles from where the first hockey match was played a century and a half ago -- a group of high-tech computer engineers are changing Canada's most revered pastime. There -- in sterile cubicles amid lots of wood and windows, with a jelly-bean dispenser and the inevitable dog, all planted in a gentrifying Jewish section of Montreal where Mordecai Richler set his landmark 1970 novel "St. Urbain's Horseman" -- they examine the 4,000 motions they detect players make in the course of each 60-minute game. The result is millions of data points unavailable to fans in the stands, but indispensable for coaches and, ultimately, players. The work being done here is changing the world of sport.

Every element of the city starting from residential facilities to health IT to security everything is to be made smart and simple to call it a smart city. With our products like Hawkeye - Smart Surveillance System most of the tasks ranging from daily activities to industrial operations are automated reducing the chance and risk of errors by reducing human intervention at most of the places.

A research collaboration between LBNL, PNNL, Brown University, and NVIDIA has achieved exaflop (half-precision) performance on the Summit supercomputer with a deep learning application used to model subsurface flow in the study of nuclear waste remediation. Their achievement, which will be presented during the "Deep Learning on Supercomputers" workshop at SC19, demonstrates the promise of physics-informed generative adversarial networks (GANs) for analyzing complex, large-scale science problems. In science we know the laws of physics and observation principles – mass, momentum, energy, etc.," said George Karniadakis, professor of applied mathematics at Brown and co-author on the SC19 workshop paper. "The concept of physics-informed GANs is to encode prior information from the physics into the neural network. This allows you to go well beyond the training domain, which is very important in applications where the conditions can change." GANs have been applied to model human face ...

Artificial Intelligence is getting a lot of attention these days. It's a technology with the potential to transform everything… I mean literally EVERYTHING. The importance of AI has risen among investors and innovators. Considering its importance, UAE appoints its first minister of Artificial Intelligence and it's the first country to do so. The sectors of transportation, healthcare, logistics, finance, and industrial manufacturing, among a plethora of others, would undergo an immense transformation under the influence of AI and they would evolve to be more productive and cheap and, more importantly, provide better services.

Fiction is full of robots with feelings. Like that emotional kid David, played by Haley Joel Osment, in the movie A.I. Or WALL•E, who obviously had feelings for EVE-uh. Robby the Robot sounded pretty emotional whenever warning Will Robinson of danger. Not to mention all those emotional train-wreck, wackadoodle robots on Westworld. But in real life robots have no more feelings than a rock submerged in novocaine.

Streamlining multiple targeting sensors to destroy long-range targets, arming forward- positioned robots to penetrate enemy defenses and receiving organized weather-specific terrain mapping from nearby drones - are all emerging combat dynamics increasingly made possible by AI-enabled weapons and technologies. New applications of AI are consolidating data from otherwise disparate sensor systems, analyzing seemingly limitless amounts of targeting data in seconds and instantly sifting through hours of drone video to massively improve attack options and shorten "sensor-to-shooter" time. "We are developing an AI stack regarding how we pull together the sensors, computing layer and analytics to manage the data," Col. Doug Matty, Army AI Task Force Deputy Director, told Warrior in an interview. New algorithms, AI-enabled computer processing and high-speed networking are all specific elements of work now underway with the Army's AI Task Force, an emerging Army effort to collaborate with industry and academia, find technology breakthroughs and develop new applications for AI, Matty explained. The Task Force is now working on prototyping systems for integration onto UH-60 Black Hawk helicopters, Long-Range Precision Fires systems and the Army's emerging fleet of Next-Gen Combat Vehicles, he said.