Following its autonomous food delivery launch in Miami and Fairfax, Virginia, Uber Eats will soon be offering the same robotic service in Japan -- its first outside the US. It is once again collaborating with Google alum startup Cartken, with local compliance help from Mitsubishi Electric, to bring a fleet of Model C sidewalk delivery robots to select areas in Tokyo in March. Uber Eats Japan CEO Shintaro Nakagawa says the autonomous delivery service will solve the local labor shortage issue, while complementing the existing human delivery methods "by bicycle, motorbike, light cargo, and on foot." Cartken's six-wheeled Model C uses six cameras and advanced AI models for autonomous driving plus obstacle detection, and remote control mode is available when needed. With guidance from Mitsubishi, the robot has been modified to suit local needs in Japan.

Starting today, Uber Eats customers in Fairfax, Virginia can get their next meal delivered by a robot. In an expansion of the company's existing partnership with Cartken, Uber has begun offering automated deliveries in the city's Mosaic District. With today's announcement, a select number of the more than 40 restaurants in the area have begun transporting their food aboard Cartken's six-wheeled robots. Among the restaurants participating in the pilot include Our Mom Eugenia, Pupatella and RASA. Uber has been testing autonomous delivery robots in a handful of markets throughout the US.

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The State of Virginia, Fairfax County, and Dominion Energy recently launched Relay, a free self-driving, and 100% electric public transportation shuttle, that will circulate between the commercial hub of Mosaic District in Merrifield, Virginia, and the Dunn Loring Metrorail Station.

Evidence-based reasoning is at the core of ma ny problem - solving and decision-making tasks in a wide variety of domains. Generalizing from the research and development of cognitive agents in several such domains, this paper presents progress toward a computational theory for the development of instructable cognitive agents for evide nce-based reasoning tasks. The paper also illustrates the application of this theory to the development of four prototype cognitive agents in domains that are critical to the government and the public sector . Two agents function as cognitive assistants, one in intelligence analysis, and the other in science education . The other two agents operate autonomously, one in cybersecurity and the other in intelligence, surveillance, and reconnaissance. The paper concludes with the directions of future research on th e proposed computational theory.

In the first days after a fleet of 25 delivery robots descended on George Mason University's campus in January, school officials could only speculate about the machines' long-term impact. The Igloo cooler-sized robots from the Bay Area start-up Starship Technologies -- which were designed to deliver food on demand across campus -- appeared to elicit curious glances and numerous photos, but not much else. It was clear, officials said at the time, that more time and more data would be necessary to understand whether the robots would actually change the campus culture or become a forgettable novelty. Today, some of that data emerged for the first time. In the two months since the robots arrived at the Fairfax, Va.-based school, an extra 1,500 breakfast orders have been delivered autonomously, according to Starship Technologies and Sodexo, a company that manages food services for GMU on contract and works closely with the robots.

The Northern Virginia Technology Council's inaugural Impact AI 2019 summit on March 21 will gather technologists in government and tech executives from companies in the region making advancements in artificial intelligence. The all-day event kicks off 7 a.m. at the Inova Center for Personalized Health Conference Center in Fairfax, Virginia, and will open with keynote speaker Toni Townes-Whitley, president of U.S. regulated industries at Microsoft. Midmorning keynote speaker Rumman Chowdhury, global lead for responsible AI at Accenture Applied Intelligence, will discuss building ethical, responsible AI. Impact AI will also feature Tech Talks -- NVTC's version of TED Talks. The MITRE Corp.'s Jay Crossler, chief engineer of operations, will present a cyber Tech Talk, and Booz Allen Hamilton's Kirk Borne, principal data scientist and executive adviser, will talk about the real power of AI and how it can help us better understand our data.

Currently, college-going students are taking longer to graduate than their parental generations. Further, in the United States, the six-year graduation rate has been 59% for decades. Improving the educational quality by training better-prepared students who can successfully graduate in a timely manner is critical. Accurately predicting students' grades in future courses has attracted much attention as it can help identify at-risk students early so that personalized feedback can be provided to them on time by advisors. Prior research on students' grade prediction include shallow linear models; however, students' learning is a highly complex process that involves the accumulation of knowledge across a sequence of courses that can not be sufficiently modeled by these linear models. In addition to that, prior approaches focus on prediction accuracy without considering prediction uncertainty, which is essential for advising and decision making. In this work, we present two types of Bayesian deep learning models for grade prediction. The MLP ignores the temporal dynamics of students' knowledge evolution. Hence, we propose RNN for students' performance prediction. To evaluate the performance of the proposed models, we performed extensive experiments on data collected from a large public university. The experimental results show that the proposed models achieve better performance than prior state-of-the-art approaches. Besides more accurate results, Bayesian deep learning models estimate uncertainty associated with the predictions. We explore how uncertainty estimation can be applied towards developing a reliable educational early warning system. In addition to uncertainty, we also develop an approach to explain the prediction results, which is useful for advisors to provide personalized feedback to students.

A fleet of 25 robots started delivering Blaze custom pizzas, Starbucks lattes and Dunkin' Donuts pastries to students at George Mason University's Fairfax, Va., campus last week. But their quiet presence on campus raised an interesting question: What are the rules for robots delivering food? It turns out those guidelines, mostly involving safety and customer service, are largely unwritten. But that hasn't stopped the experts from thinking about them. Did you say robots delivering food?

At most universities, meal plans allow college students to take advantage of on-campus cafeterias or chow down at local restaurants. Now, thousands of students at George Mason University will have another dining option at their disposal: on-demand food delivery via an autonomous robot on wheels. The school has received a fleet of 25 delivery robots that can haul up to 20 pounds each as they roll across campus at four miles per hour, according to Starship Technologies, the Estonia-based robotics company that created the delivery vehicles. The company -- which claims its robots can make deliveries in 15 minutes or less -- says the Fairfax, Va.-based school is the first campus in the country to incorporate robots into its student dining plan and has the largest fleet of delivery roots on any university campus. "Students and teachers have little free time as it is, so there is a convenience for them to have their food, groceries and packages delivered to them," said Ryan Tuohy, Starship Technology's senior vice president of business development.