The rise of the AI is inexorable. Artificial Intelligence has become a part of everyday lives in some form or the other. It has massive potential to drive innovations and considerable improvements in this data-driven world. From predictive analytics, chatbots, to assistant-enabled homes to self-driving cars and cybersecurity, AI is everywhere. It has become viable for almost all sectors.

Eliu Huerta is harnessing AI and high performance computing (HPC) to observe the cosmos more clearly. For several years, the astrophysics researcher has been chipping away at a grand challenge, using data to detect signals produced by collisions of black holes and neutron stars. If his next big design for a neural network is successful, astrophysicists will use it to find more black holes and study them in more detail than ever. Such insights could help answer fundamental questions about the universe. They may even add a few new pages to the physics textbook.

In 1997, The Simpsons prophesized that for future wars, "most of the actual fighting will be done by small robots" with soldiers only responsible to "build and maintain those robots." Though the cartoon's track record with predictions is debatable, few will argue that robots have played a critical role in combat over the past decade. Whether it is a Predator drone patrolling a No-Fly zone or a Packbot diffusing a bomb, robots have made their presence known on the battlefield. The U.S. military and coalition forces use the base, located in an undisclosed location, to launch airstrikes against ISIL in Iraq and Syria, as well as to distribute cargo and transport troops supporting Operation Inherent Resolve. The Predators at the base are operated and maintained by the 46th Expeditionary Reconnaissance Squadron, currently attached to the 386th Air Expeditionary Wing.

PHOENIX – Banner Health is implementing applied artificial intelligence technology that will help doctors quickly treat patients suffering from a stroke. Arizona's largest hospital network has partnered with Viz.ai, which is an FDA-cleared computer-aided triage system that cuts down the time doctors use to look over imaging. "Every second someone is having a stroke, we estimate 32 thousand brain cells are dying," Dr. Jeremy Payne, Director of the Stroke Center at Banner University Medical Center Phoenix, told KTAR 92.3 FM Tuesday. It notifies doctors "where a stroke is happening, how much damage has been done and how much tissue is still salvageable before the patient has left the CT scanner," Payne said. Images and notifications are also sent directly to a doctor's phone, making it easier and faster for doctors to make lifesaving decisions.

As part of the Next Generation Internet Policy Summit, Amsterdam and Helsinki launched beta AI registries that show how the government in each locale uses algorithms to provide services. Currently, the Amsterdam registry includes a small number of algorithms, but it will be expanded after feedback is gathered at the summit, which was organised by the City of Amsterdam and the European Commission. The algorithms in the registry come with a description of how they are used, what humans do with the information they provide and how it they are analysed for possible risks and biases. Citizens of Amsterdam can offer feedback and contact information for the individual deploying each algorithm is available. Amsterdam is well on its way to becoming a global AI hub.

Artificial Intelligence is a rapidly growing technology that finds applications and uses cases in all aspects of industry and life as well: within smart factories that use AI technology to enhance their capabilities and in smart assistants found in smart phones. Similarly, the pharmaceutical industry is finding innovative and smart ways to use this modern technology to resolve some of the significant issues facing pharma sector today. Along with AI-powered analytics, big data has brought a radical shift in the paradigm of the pharma. Artificial intelligence has the potential to promote innovation, while at the same time increasing productivity and providing better results. In addition, Artificial Intelligence develops the value proposition of pharmaceutical companies by creating new and latest business models.

So far, few deepfakes have been used this political season. It's not because they aren't a potential threat, but because simpler deceptive tactics are still effective at spreading misinformation. So far, few deepfakes have been used this political season. It's not because they aren't a potential threat, but because simpler deceptive tactics are still effective at spreading misinformation. Despite people's fears, sophisticated, deceptive videos known as "deepfakes" haven't arrived this political season.

Volvo Cars, a Swedish company that's owned by a Chinese billionaire and builds vehicles at a plant in the American South using crucial parts made in Mexico, is a poster child for how globally interconnected the auto industry became in an era of increasing free trade. When Volvo opened its factory in Charleston, S.C., in 2018 with ambitious plans to export cars to China, it was the pinnacle of a push to showcase its reemergence as a global brand with a manufacturing presence on three continents. Then the U.S.-China trade war forced Volvo to abandon its export plans. And this spring, as the coronavirus spread around the globe, the factory was plagued by a shortage of components and had to halt production three times. To make matters worse, U.S. car buyers' preferences have shifted rapidly toward sport utility vehicles and away from the sedans Volvo makes in Charleston.

Theories of public trust in chatbots in the public sector are presented. An online experiment was conducted to test the hypotheses. The public's initial trust in chatbots depends on the area of enquiry. Initial public trust was lower in the area of parental support than waste separation. Communicating certain purposes for using a chatbot is slightly trust-enhancing.

While classification of arbitrary structures in high dimensions may require complete quantitative information, for simple geometrical structures, low-dimensional qualitative information about the boundaries defining the structures can suffice. Rather than using dense, multi-dimensional data, we propose a deep neural network (DNN) classification framework that utilizes a minimal collection of one-dimensional representations, called \emph{rays}, to construct the "fingerprint" of the structure(s) based on substantially reduced information. We empirically study this framework using a synthetic dataset of double and triple quantum dot devices and apply it to the classification problem of identifying the device state. We show that the performance of the ray-based classifier is already on par with traditional 2D images for low dimensional systems, while significantly cutting down the data acquisition cost.