Since Mike Tyson's Punch-Out was released on the NES in 1987, millions of players have undertaken millions of digital matches against one of the hardest video game bosses ever: Tyson himself (or, later, the reskinned "Mr. Only a small percentage of those players could survive Tyson's flurry of instant-knockdown uppercuts and emerge victorious with the undisputed World Video Boxing Association championship. Even fewer had fast enough fingers to take out Tyson in the first round. In all this time, no one has been able to register a TKO on Tyson in less than two minutes on the ever-present in-game clock (which runs roughly three times as quickly as a real-time clock). At least that was true until last weekend, when popular speedrunner and speedrun historian Summoning Salt pulled off a 1:59.97 This story originally appeared on Ars Technica, a trusted source for technology news, tech policy analysis, reviews, and more. Ars is owned by WIRED's parent company, Condé Nast.

Traffic speed forecasting is an important task in intelligent transportation system management. The objective of much of the current computational research is to minimize the difference between predicted and actual speeds, but information modalities other than speed priors are largely not taken into account. In particular, though state of the art performance is achieved on speed forecasting with graph neural network methods, these methods do not incorporate information on roadway maintenance work zones and their impacts on predicted traffic flows; yet, the impacts of construction work zones are of significant interest to roadway management agencies, because they translate to impacts on the local economy and public well-being. In this paper, we build over the convolutional graph neural network architecture and present a novel ``Graph Convolutional Network for Roadway Work Zones" model that includes a novel data fusion mechanism and a new heterogeneous graph aggregation methodology to accommodate work zone information in spatio-temporal dependencies among traffic states. The model is evaluated on two data sets that capture traffic flows in the presence of work zones in the Commonwealth of Virginia. Extensive comparative evaluation and ablation studies show that the proposed model can capture complex and nonlinear spatio-temporal relationships across a transportation corridor, outperforming baseline models, particularly when predicting traffic flow during a workzone event.

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The robots have arrived in downtown Springdale, in a black warehouse at 317 E. Meadow Ave., directly behind Tyson's Emma Street technology center. Designed to move chicken legs and packaging, the robots will eventually end up in processing plants across the country. But before that can happen, they will be tested in the new Tyson Manufacturing Automation Center, which opened Thursday. The center offers a space for employees to develop in-house manufacturing processes with suppliers, and to learn how those processes and equipment work. "It is another exciting day in Springdale," Tyson Foods Chairman John Tyson told a crowd at the facility Thursday.

Robotics Professor Ken Goldberg is the first to acknowledge the public anxiety about what automation and AI might mean for future jobs. Singularity--the hypothesis that AI will become increasingly powerful, decimating professions and remaking civilization--is becoming a mainstream concept. All one has to do is read news headlines about robot-driven factories, watch movies like "Ex Machina," and listen to public figures like Elon Musk stating that AI poses our greatest existential threat. Yet at a recent Blum Center Faculty Salon on the Digital Transformation of Development, Goldberg, UC Berkeley's Department Chair of Industrial Engineering and Operations Research and the William S. Floyd Jr. Distinguished Chair in Engineering, argued that such fears are exaggerated. He is among computer scientists and roboticists who believe there is inadequate evidence to support the mass unemployment theories, such as the often cited Oxford University study that estimated 47 percent of U.S. jobs are at risk of computerization.

The future has arrived and it's your first day at your new job. You step across the threshold sporting a nervous smile and harboring visions of virtual handshakes and brain-computer interfaces. After all, this is one of those newfangled, modern offices that science-fiction writers have been dreaming up for ages. No, it's not one of the ubiquitous glass walls, but the harsh reality of an office that, at first glance, doesn't appear much different from what you're accustomed to. A kitchenette stocked with stale donuts lurks in the background. And, by the way, you were fifteen minutes late because the commute is still hell.

Richard Lifton, filmmaker Laura Mulvey, artificial intelligence pioneer Judea Pearl, Jazz musician Willie Ruff, and Rowan Williams, the 104th Archbishop of Canterbury, joined Tyson and Bassett in receiving honorary degrees from the school this year.

Artificial intelligence and automation are not likely to cause vast unemployment, but that doesn't mean we shouldn't be concerned about the impact on jobs. "I'm not worried about technological unemployment," said Laura Tyson, a prominent economist at the Haas School of Business at the University of California, Berkeley. "But I am worried about the quality of jobs created and the location where they are created." Speaking this week at EmTech Digital, an annual AI conference organized by MIT Technology Review, Tyson suggested we look the effects of increasing automation over the last 30 years. What we know, says Tyson, is that automation has taken away many routine jobs.

After they were all seated, Tyson had the lights dimmed, and then promptly undermined why the panelists were there in the first place. Tyson played a video from Boston Dynamics showing two four-legged robots, one with a long arm that opened a door for the other. The crowd murmured and cheered as the robots overcame the obstacle. Tyson implored the audience to read the comments on the video at home later. "The first comment was'We're all going to die!' but then the second comment was'Those were polite robots!'" he said.

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