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An AI power play: Fueling the next wave of innovation in the energy sector

#artificialintelligence

Tatum, Texas might not seem like the most obvious place for a revolution in artificial intelligence (AI), but in October of 2020, that's exactly what happened. That was when Wayne Brown, the operations manager at the Vistra-owned Martin Lake Power Plant, built and deployed a heat rate optimizer (HRO). Vistra Corp. is the largest competitive power producer in the United States and operates power plants in 12 states with a capacity of more than 39,000 megawatts of electricity--enough to power nearly 20 million homes. Vistra has committed to reducing emissions by 60 percent by 2030 (against a 2010 baseline) and achieving net-zero emissions by 2050. To achieve its goals, the business is increasing efficiency in all its power plants and transforming its generation fleet by retiring coal plants and investing in solar- and battery-energy storage, which includes the world's largest grid-scale battery energy-storage facility.


Robots are learning to think like humans. Can they meet Amazon's demands for speed?

#artificialintelligence

In a lab at the University of Washington, robots are playing air hockey. As the robots play, the researchers who built them are learning more about how they work, how they think and where they have room to grow, said Xu Chen, one of those researchers and an associate professor of mechanical engineering at UW. "From a robot's viewpoint, artificial intelligence is getting more and more mature," Chen said, referring to the software and algorithms that help a robot take in its surroundings and make decisions. "But if we want a full-scale robot to be able to think very quickly and cleverly, and then be able to do things in the physical space, I don't think we're there yet." The games are a way to get one step closer to taking the robots out of the air hockey arena and into the workforce, asking machines to shoulder tasks like lifting and moving heavy boxes for hours at a time. Robots are already working in warehouses, helping Amazon and Walmart customers get their orders faster, but e-commerce and retail leaders want them to do more.


The Application of Machine Learning Techniques for Predicting Match Results in Team Sport: A Review

Journal of Artificial Intelligence Research

Predicting the results of matches in sport is a challenging and interesting task. In this paper, we review a selection of studies from 1996 to 2019 that used machine learning for predicting match results in team sport. Considering both invasion sports and striking/fielding sports, we discuss commonly applied machine learning algorithms, as well as common approaches related to data and evaluation. Our study considers accuracies that have been achieved across different sports, and explores whether evidence exists to support the notion that outcomes of some sports may be inherently more difficult to predict. We also uncover common themes of future research directions and propose recommendations for future researchers. Although there remains a lack of benchmark datasets (apart from in soccer), and the differences between sports, datasets and features makes between-study comparisons difficult, as we discuss, it is possible to evaluate accuracy performance in other ways. Artificial Neural Networks were commonly applied in early studies, however, our findings suggest that a range of models should instead be compared. Selecting and engineering an appropriate feature set appears to be more important than having a large number of instances. For feature selection, we see potential for greater inter-disciplinary collaboration between sport performance analysis, a sub-discipline of sport science, and machine learning.


Robots are learning to think like humans. Can they meet Amazon's demands for speed?

#artificialintelligence

In a lab at the University of Washington, robots are playing air hockey. As the robots play, the researchers who built them are learning more about how they work, how they think and where they have room to grow, said Xu Chen, one of those researchers and an associate professor of mechanical engineering at UW. "From a robot's viewpoint, artificial intelligence is getting more and more mature," Chen said, referring to the software and algorithms that help a robot take in its surroundings and make decisions. "But if we want a full-scale robot to be able to think very quickly and cleverly, and then be able to do things in the physical space, I don't think we're there yet." The games are a way to get one step closer to taking the robots out of the air hockey arena and into the workforce, asking machines to shoulder tasks like lifting and moving heavy boxes for hours at a time. Robots are already working in warehouses, helping Amazon and Walmart customers get their orders faster, but e-commerce and retail leaders want them to do more.


Maple Leaf Sports and AWS transform experiences for sports fans

#artificialintelligence

Amazon Web Services (AWS) and Maple Leaf Sports & Entertainment (MLSE) are innovating together to transform how some of Canada's best-known sports franchises create and deliver extraordinary sports moments and enhanced fan engagement. The sports franchises include Toronto Maple Leafs, Toronto Raptors, Toronto Football Club (FC) and Toronto Argonauts. MLSE selected AWS as its official cloud provider and official provider of artificial intelligence (AI), machine learning (ML), and deep learning cloud services. MLSE will use AWS's comprehensive portfolio of cloud capabilities, including ML, advanced analytics, compute, database, and storage services to support their teams and lines of business. Innovating together, MLSE will build solutions that will support how teams play on the ice, court, pitch, or field; how players stay healthy; how fans connect with each other and experience games; and how sports franchises operate internally.


Machine Learning as a Service Market Size By 2022 -2029

#artificialintelligence

New Jersey, USA,- we released research materials for "Global Machine Learning as a Service Market Report, Trends and Forecasts for 2022-2029, Inf.


How To Solve Problems With Technology

#artificialintelligence

Inventing what the world needs- that is now Edison described the crux of innovation in technology. Big problems represent even bigger opportunities. To quote famous Canadian ice hockey player Wayne Gretzky, who scored many hits in his time, the trick is not to "skate where the puck is," but to "skate where the puck is going." It has come up with the most scalable solutions which can impact business across the world. Whether it is clean energy, robotics, quantum computing, synthetic biology, telemedicine, AI, or cloud education and NUI software, it can solve all the biggest problems confronting mankind. Creating value means coming up with something people will pay for in the real world. Virtual technologies can open up a window of possibilities, given their widespread application.


Canada's women's hockey reinvents itself after Olympic loss

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Canadians just finished making brisk work of Sweden in the quarterfinal round of the women's Olympic hockey tournament, and yet coach Troy Ryan wasn't prepared to assess just how dominant his team can be. A better time to ask might be Thursday, when the gold medal is awarded. The Canadians are now considered the favorites, having raised the bar of the women's game with a dynamic and relentless, four-line transition attack that has outscored opponents by a combined 44-5 at the Beijing Games.


The Echo Dot has been reduced from £39.99 to just £21.99 thanks to this Amazon deal

Daily Mail - Science & tech

Products featured in this Mail Best article are independently selected by our shopping writers. If you make a purchase using links on this page, MailOnline may earn an affiliate commission. Amazon has continued to drop incredible deals in their New Year sale, and if you're looking to upgrade your smart home, we've found Amazon device deals you won't want to miss. Today the Amazon Echo Dot (3rd Gen) is now 45 per cent off, so you can score the hockey puck-shaped smart speaker for just £21.99 (typically £39.99). This isn't the only Amazon Echo device on sale right now, as the retailer has slashed the Echo Dot (4th Gen) price by 40 per cent to just £29.99.


Counterfactual Memorization in Neural Language Models

arXiv.org Artificial Intelligence

Modern neural language models widely used in tasks across NLP risk memorizing sensitive information from their training data. As models continue to scale up in parameters, training data, and compute, understanding memorization in language models is both important from a learning-theoretical point of view, and is practically crucial in real world applications. An open question in previous studies of memorization in language models is how to filter out "common" memorization. In fact, most memorization criteria strongly correlate with the number of occurrences in the training set, capturing "common" memorization such as familiar phrases, public knowledge or templated texts. In this paper, we provide a principled perspective inspired by a taxonomy of human memory in Psychology. From this perspective, we formulate a notion of counterfactual memorization, which characterizes how a model's predictions change if a particular document is omitted during training. We identify and study counterfactually-memorized training examples in standard text datasets. We further estimate the influence of each training example on the validation set and on generated texts, and show that this can provide direct evidence of the source of memorization at test time.