Argus exploits a Multi-Agent Reinforcement Learning (MARL) framework to create a 3D mapping of the disaster scene using agents present around the incident zone to facilitate the rescue operations. The agents can be both human bystanders at the disaster scene as well as drones or robots that can assist the humans. The agents are involved in capturing the images of the scene using their smartphones (or on-board cameras in case of drones) as directed by the MARL algorithm. These images are used to build real time a 3D map of the disaster scene. Via both simulations and real experiments, an evaluation of the framework in terms of effectiveness in tracking random dynamicity of the environment is presented.

The Predictive Normalized Maximum Likelihood (pNML) scheme has been recently suggested for universal learning in the individual setting, where both the training and test samples are individual data. The goal of universal learning is to compete with a ``genie'' or reference learner that knows the data values, but is restricted to use a learner from a given model class. The pNML minimizes the associated regret for any possible value of the unknown label. Furthermore, its min-max regret can serve as a pointwise measure of learnability for the specific training and data sample. In this work we examine the pNML and its associated learnability measure for the Deep Neural Network (DNN) model class. As shown, the pNML outperforms the commonly used Empirical Risk Minimization (ERM) approach and provides robustness against adversarial attacks. Together with its learnability measure it can detect out of distribution test examples, be tolerant to noisy labels and serve as a confidence measure for the ERM. Finally, we extend the pNML to a ``twice universal'' solution, that provides universality for model class selection and generates a learner competing with the best one from all model classes.

The Immigration Services Agency plans to strengthen its eligibility standards for Japanese-language schools, it was learned Saturday. The move comes as Japanese-language schools have been under fire for accepting many foreign students whose purpose is to work in Japan. The number of Japanese-language schools recognized by the government grew 1.6 times over the past five years to 749 as of April 2. The government late last year outlined plans to improve the quality of Japanese-language schools as part of efforts to bring in more foreign workers to the country. Under the agency's plan, the requirement for the average student attendance rate would be revised from the current 50 percent or more in a month to 70 percent or more in a period of seven months. Schools failing to meet the requirement would not be allowed to accept foreign students.

Artificial-intelligence researcher Oren Etzioni has suggestions for keeping enough AI faculty members around to train the next generation.Credit: Bret Hartman/TED Oren Etzioni is chief executive of the non-profit Allen Institute for Artificial Intelligence (AI2) in Seattle, Washington, and is on leave from the nearby University of Washington. He offers some recommendations for how to stem the outflow of artificial-intelligence (AI) researchers from academia to industry -- a loss that is damaging academia's ability to teach incoming undergraduates. It is a very sizeable trend for fresh PhD graduates and faculty members. In machine learning, you see some significant departures. Industry compensation packages are highly variable.

In early March, Pittsburgh Mayor William Peduto signed an executive order mandating that firms testing self-driving vehicles submit materials outlining their testing methods every six months to the city's newly formed Department of Mobility and Infrastructure (DOMI). Findings from the first of these were quietly published this week, compiled in a survey ("Self-Driving Vehicle Testing in Pittsburgh Summary of Findings") to be issued once a year. According to the report, five companies -- Aptiv, Argo AI, Aurora, Carnegie Mellon University, and Uber -- are testing 55 driverless cars in 32 of Pittsburgh's neighborhoods and suburbs, with the greatest concentration in the city's Strip District and Lower Lawrenceville. The test vehicles range from modified BMW 540is and Chrysler Pacifica PHEVs to Ford Fusion Hybrids, Lincoln MKZs, Cadillac SRXs, and Volvo XC90s, all of which contain no fewer than five disengagement mechanisms including buttons in the consoles and steering wheels. Most of the cars fall under the Society of Automotive Engineers (SAE)'s level 4 designation, meaning that they're capable of performing all driving functions autonomously under certain conditions, and they drive on public roads mostly during weekdays (both during the day and at night) with occasional testing on weekends "only during favorable weather conditions."

Artificial intelligence (AI) is proving to be a double-edged sword. While this can be said of most new technologies, both sides of the AI blade are far sharper, and neither is well understood. These technologies are starting to improve our lives in myriad ways, from simplifying our shopping to enhancing our healthcare experiences. Their value to businesses also has become undeniable: nearly 80 percent of executives at companies that are deploying AI recently told us that they're already seeing moderate value from it. Although the widespread use of AI in business is still in its infancy and questions remain open about the pace of progress, as well as the possibility of achieving the holy grail of "general intelligence," the potential is enormous.

Worker activists at Google held a "town hall" on Friday where they alleged that the company regularly retaliates against employees who speak out about workplace problems and announced plans for a "company-wide day of action" on 1 May. The meeting, livestreamed for Google employees in offices around the world, was announced after two of the organizers of the November 2018 global walkout circulated a letter internally alleging they were being punished for their activism. The two employees, Meredith Whittaker and Claire Stapleton, provided further details of their cases during the Friday event. Their statements, along with anonymous reports of retaliation of 11 other Google employees, were published in internal documents seen by the Guardian. "I didn't walk out because I'm against Google, I walked out because I'm for it – because I wanted to make it better," Stapleton said in her written statement.

With the rapid development of knowledge bases(KBs),question answering(QA)based on KBs has become a hot research issue. In this paper,we propose two frameworks(i.e.,pipeline framework,an end-to-end framework)to focus answering single-relation factoid question. In both of two frameworks,we study the effect of context information on the quality of QA,such as the entity's notable type,out-degree. In the end-to-end framework,we combine char-level encoding and self-attention mechanisms,using weight sharing and multi-task strategies to enhance the accuracy of QA. Experimental results show that context information can get better results of simple QA whether it is the pipeline framework or the end-to-end framework. In addition,we find that the end-to-end framework achieves results competitive with state-of-the-art approaches in terms of accuracy and take much shorter time than them.

The number of people who fear artificial intelligence is on the rise. A new poll of 1,004 registered voters in the U.S. found that 57 percent of them believe AI is a'threat to the human race.' The findings demonstrate the increasing skepticism around AI, which has made its way into many of the devices we use today, from cars to cellphones. The number of people who fear AI is on the rise. A new poll of 1,004 registered voters in the U.S. found that 57 percent of them believe AI is a'threat to the human race' The survey was conducted from April 17th to 18th by political analyst and pollster Scott Rasmussen and market research firm HarrisX.

Construction work on a moonbase could begin within the next decade as China reveals its timeline for future missions to the lunar surface. Zhang Kejian, the administrator of the China National Space Administration (CNSA), announced the plans in a recent speech. The research facility will be located near the moon's ice-rich south pole and will be shared with multiple countries, Mr Zhang said. Ice will be needed on the moon to provide water for both human consumption and as a component for rocket fuel. The small step of a lunar base could serve not only as a platform for research but also as a refuelling station for giant leaps out into the solar system.