Quadrotors are fast, cheap, and capable, and they're getting smarter all the time. Where they struggle a little bit is with adaptation. Many other kinds of robots can change their structure to better perform different tasks: Humanoids do it all the time, with all those conveniently placed limbs. Hey, wouldn't it be cool if drones had movable limbs too? Someone should figure out how to do that.

The 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE-2018) was held at Concordia University in Montreal, Canada, June 25–28, 2018. This report summarizes the The 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE-2018) was held at Concordia University in Montreal, Canada, June 25–28, 2018.  IEA/AIE 2018 continued the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation a robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace, and human-machine interactions.

ICWSM-18 and HCOMP-if any spots remain open.The organizers Munich, Germany. For information 18 were both successful, with increases of the AAAI/ACM SIGAI Job Fair are about paper submissions, as well as the in attendance. Smith noted that John Dickerson (University of Maryland, planned program, please refer to although we budgeted for a deficit of USA) and Chris Amato (Northeastern icwsm.org/2019.

In neural abstractive summarization field, conventional sequence-to-sequence based models often suffer from summarizing the wrong aspect of the document with respect to the main aspect. To tackle this problem, we propose the task of reader-aware abstractive summary generation, which utilizes the reader comments to help the model produce better summary about the main aspect. Unlike traditional abstractive summarization task, reader-aware summarization confronts two main challenges: (1) Comments are informal and noisy; (2) jointly modeling the news document and the reader comments is challenging. To tackle the above challenges, we design an adversarial learning model named reader-aware summary generator (RASG), which consists of four components: (1) a sequence-to-sequence based summary generator; (2) a reader attention module capturing the reader focused aspects; (3) a supervisor modeling the semantic gap between the generated summary and reader focused aspects; (4) a goal tracker producing the goal for each generation step. The supervisor and the goal tacker are used to guide the training of our framework in an adversarial manner. Extensive experiments are conducted on our large-scale real-world text summarization dataset, and the results show that RASG achieves the state-of-the-art performance in terms of both automatic metrics and human evaluations. The experimental results also demonstrate the effectiveness of each module in our framework. We release our large-scale dataset for further research.

In the early 1970s, a British grad student named Geoff Hinton began to make simple mathematical models of how neurons in the human brain visually understand the world. Artificial neural networks, as they are called, remained an impractical technology for decades. But in 2012, Hinton and two of his grad students at the University of Toronto used them to deliver a big jump in the accuracy with which computers could recognize objects in photos. Within six months, Google had acquired a startup founded by the three researchers. Previously obscure, artificial neural networks were the talk of Silicon Valley.

He's the founder of MetaMind, an artificial intelligence (AI) startup that raised more than $8 million in venture capital backing from Khosla Ventures and others before being acquired by Salesforce in 2016, and he previously served as adjunct professor at Stanford's computer science department, where he also received his Ph.D. (He earned his bachelor's degree at Leipzig University and his master's at Saarland University.) In 2007, Socher was part of the team that won first place in the semantic robot vision challenge. And he was instrumental in assembling ImageNet, a publicly available database of annotated images used to test, train, and validate computer vision models. Socher -- who's now Saleforce's chief data scientist -- has long been attracted to the field of natural language processing, a subfield of computer science concerned with interactions between computers and human languages. His dissertation demonstrated that deep learning -- layered mathematical functions loosely modeled on neurons in the human brain -- could solve several different natural language processing tasks simultaneously, obviating the need to develop multiple models.

The future of the driverless car is going to affect the future of how we travel and what we do in cars. But driverless cars are also likely to transform roads, cities, suburbs, jobs, the economy and daily life. My guest Samuel Schwartz expects it to be a very disruptive technology. Schwartz is the author of the new book "No One At The Wheel: Driverless Cars And The Road Of The Future," which he says is about the good, the bad and the ugly of how driverless cars will change our world. He knows a lot about transportation systems. He served as the traffic commissioner of New York City and chief engineer of the city's Department of Transportation. He now has his own consulting firm and has worked with cities around the world on transportation-related issues. Later in our conversation, after we talk about the future, we're going to talk about traffic problems that plague us today. We're going to use the words driverless car interchangeably with the words autonomous vehicle, or AV. In your book, you write that AVs, autonomous vehicles, will be the most disruptive technology to hit society worldwide since the advent of the motorcar. Give us a couple of examples of industries or jobs or roadways that we might not realize will be profoundly affected by AVs once they start to really dominate. SAMUEL SCHWARTZ: I think everybody is expecting fewer drivers, and, you know, that's no surprise. But it also means that there're probably going to be fewer repair shops because AVs lend themselves to fleet operations, especially if they're going to be offering rides, as opposed to selling maximum vehicles. So car dealerships may disappear. So this is going to have wide impacts. Truckers, of course, are going to be impacted - how we move about in so many different ways.

The question addressed in this paper is: If we present to a user an AI system that explains how it works, how do we know whether the explanation works and the user has achieved a pragmatic understanding of the AI? In other words, how do we know that an explanainable AI system (XAI) is any good? Our focus is on the key concepts of measurement. We discuss specific methods for evaluating: (1) the goodness of explanations, (2) whether users are satisfied by explanations, (3) how well users understand the AI systems, (4) how curiosity motivates the search for explanations, (5) whether the user's trust and reliance on the AI are appropriate, and finally, (6) how the human-XAI work system performs. The recommendations we present derive from our integration of extensive research literatures and our own psychometric evaluations.

When you're trying to come up with gift ideas for someone who likes to cook, you want to find something that's both personal and practical. But finding a gift for a home cook that strikes that balance can be hard, especially if you're the kind of person whose fridge is filled with takeout containers. That's why we've gathered 35 of the best gifts for every type of home cook on your list--from the newbie who just wants to make a good grilled cheese to the home cook who has it all--all of them are available on Amazon, most of them with two-day Prime shipping. ChefSteps Joule Sous Vide, 1100 Watts, All White ($179) They might not think they need a sous vide machine, but that's exactly what makes it a great gift for an experienced chef, who can use it to make always-tender steaks, never-overcooked fish, and even soft-scrambled eggs. Echo Show (Second Generation) ($230) The new generation of the Echo Show has louder speakers and a bigger screen than before, so they can follow along with recipe videos and tutorials from any one of Amazon's partners, or ask Alexa to set a timer.

Facial recognition software has earned a difficult reputation over the past few years, what with its massive privacy implications and ease of being misused by governments and retailers alike, but the technology has just as many beneficial applications. Take the Wheelie 7, for example. While travelling a few years ago, Dr. Paulo Pinheiro was struck by a scene unfolding before him. "I saw a girl at the airport, she was in a wheelchair," he explained to Engadget. "She couldn't move her arms or her legs, her father was helping her with her wheelchair but she had a great smile... so I thought it would be a good idea to try to translate that smile into commands that could move a wheelchair."