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 jameson


Can You Really Hide in a Video Game?

Slate

This story is part of Future Tense Fiction, a monthly series of short stories from Future Tense and Arizona State University's Center for Science and the Imagination about how technology and science will change our lives. When I get home from work at 6:00, the light is fading, and I see my sons and their little friend playing in the street, two white boys and a Black boy throwing a foam football back and forth. I pull around the corner and they scatter, Oliver running one way while Jameson and the neighbor kid run the other. At the last minute, though, Jameson changes his mind, dropping the football and dashing across to his brother's side of the street. I slam to a halt, the bumper almost touching him. My heart throbs in my jaw: so close. Then, just as I release the brake, the neighbor kid runs across, too, and I have to stomp to a stop a second time. Don't any of you have common sense?" Through the unrolled window I see them all staring at me with wide eyes. "What is wrong with your ...


Question-Answer Sentence Graph for Joint Modeling Answer Selection

Iyer, Roshni G., Vu, Thuy, Moschitti, Alessandro, Sun, Yizhou

arXiv.org Artificial Intelligence

This research studies graph-based approaches for Answer Sentence Selection (AS2), an essential component for retrieval-based Question Answering (QA) systems. During offline learning, our model constructs a small-scale relevant training graph per question in an unsupervised manner, and integrates with Graph Neural Networks. Graph nodes are question sentence to answer sentence pairs. We train and integrate state-of-the-art (SOTA) models for computing scores between question-question, question-answer, and answer-answer pairs, and use thresholding on relevance scores for creating graph edges. Online inference is then performed to solve the AS2 task on unseen queries. Experiments on two well-known academic benchmarks and a real-world dataset show that our approach consistently outperforms SOTA QA baseline models.


Island In The Sand, Chapter XXII

#artificialintelligence

Star Black walked the short distance back to the living room where her band was once more gathering. "The lower story is not a story at all," the house intoned. I must assume that the defective Ninety-One machine was referring to the extended unit set into the base of the canyon face. That would place it lower than the house, which is accurate, but it is a thousand meters down, connected only by a small express lift." "So, there's something at the bottom of the canyon and there's a way to get down to it," Jameson said, with no doubt from his tone that he was eager to find out more, and immediately go exploring. "That's correct and accurate," the house stated. "So, where's the lift and when can we go down?" "The lift is rising, but it's of an old variety and will take some time to reach the dwelling." "Rising?" Star said, her voice piercing in tone, stopping all activity in the room. "Why would it be rising?" "There were no humans in the vicinity, as loosely defined when you pointedly used the word'outside' in your question," the house shot back, it's tone almost one of faint or vague petulance. "How could anyone get in the lift and use it if they aren't an administrator?" she asked, realizing when she got the words out that the answer to that question was right there among them. So much was happening at once Star couldn't figure out what to do first. They had members of Sly's band, who had somehow gotten to the bottom of the canyon and were riding up to arrive at the dwelling at any moment, as a possible and vital life or death issue. "The nodes and the lifts do not require the code to be provided by an administrator," the house said. "Unlike accessing the main complex entity and myself, they only require a spoken or written code." "Give me the device," Jameson said across the room to True, "and you better pray that we don't find any more on you when there's time to search you." The boy slunk against the wall, standing with his back against the stone that extended out from the fireplace, which still exuded heat even though the flames were gone. He held out his open hand, palm up, with a small black electronic device laying upon it. The device had a short antenna sticking out of it. "I don't have anymore, that's the last one," he murmured in the silence, as everyone waited to see what was going to happen next. "I didn't know who was going to win," True said, his voice soft but faintly rebellious. "If Star won I knew it would be okay, but if Sly won then what was I to do, die with everyone else?" Jameson stepped quickly forward and swept the device off True's exposed palm. He threw it down and smashed it into bits with the butt of his rifle before anything could be said or other action taken. Once done, Jameson raised his rifle up to point at True. "We're out of time, Jameson," Star said loudly, demanding the boy's full attention. We've got to get to the top of the lift before it gets up here. Where are the lift doors, house?"


Usability Engineering Methods for Interactive Intelligent Systems

Spaulding, Aaron (SRI International) | Weber, Julie Sage (University of Michigan)

AI Magazine

There is considerable validity to this point of view: Anyone who develops systems that are intended for use by people can benefit from familiarity with and application of these methods. Accordingly, this article offers a brief introduction to these methods, including examples and suggestions for additional reading (see in particular the Further Reading section). Even people who are already experts in the application of these methods should be aware of potential adaptations and extensions to the methods when applied to systems that are designed to incorporate significant use of AI. The theme articles by Lieberman (2009) and by Jameson (2009) in this issue discuss some of the ways in which systems that incorporate intelligence tend to differ from systems that do not, both in terms of their potential to help users and in terms of possible side effects. These and other properties of intelligent systems can affect the application of design and evaluation methods in various ways, some of which are illustrated in the case studies of this special issue. To organize our discussion, we distinguish broadly three types of activity that are involved in usability engineering: understanding users' needs, interaction design, and evaluation. Except for the fact that understanding users' needs tends to occur early in the design process, these activities generally proceed in parallel and complement each other.