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Robot named 'Curly' uses AI to beat one of the world's best curling teams at their own game

Daily Mail - Science & tech

An artificial intelligence equipped robot named'Curly' beat one of the world's best curling teams by quickly adapting to changes in the ice, its developers claim. The sport of curling involves constantly changing and uncontrollable environmental conditions - providing the perfect'test bed' for an AI-driven robot. Curly, who delivers the stone but doesn't sweep, won three out of four official matches against the Korean Olympic silver-medal winning women's team. The robot was developed by researchers from Korea University, who said this development narrows the gap between computer simulators and the real world. It's hoped the deep learning techniques developed for Curly could be applied to other robots that need to work'in the real world' and adapt to changing conditions.


Opargo Named Allscripts App of the Month

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In celebration of this announcement, Opargo has partnered with Valor Performance and Allscripts to share best practices on Optimism Conditioning and Controlling the Controllables from Olympian Iris Zimmerman and Valor/Opargo CEOs on an upcoming Allscripts client webcast. Optimism Conditioning is part of Valor's framework on performance mindset, supported by cross-disciplinary research and is the practice of noticing the positive, bouncing back from setbacks and preparing for success. As neuroscience, psychology and social science supports, optimism can be cultivated and isn't a fixed attribute. One of the tenets of Optimism Conditioning is focusing on the critical things that are able to be controlled. Olympic athletes like Valor Coach and fencer Iris Zimmerman have used these principles to train and win in the highest athletic competitions.


Agence Is A Fascinating VR Deep Dive Into Evolving AI

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I watch as he toys with the small group of lifeforms named Agents that curiously ramble around a tiny planet. They're odd three-legged things that go from goldfishing their way from one side of their tennis ball-sized existence to another to staring at me in bemusement to accidentally – and then angrily – bumping into each other. When the call ends, Gagliano – perhaps unknowingly – leaves the stream going for another 10 or so minutes. I sit, slightly transfixed, continuing to observe the Agents that go on existing in the absence of their newfound virtual deity. Agence is a hard thing to pin down. Gagliano, the piece's director, and Oppenheim, the creative producer, label it as a'looping' and'dynamic film', something that starts right back up again the moment it ends.


'NBA 2K21' review: Why should I buy this game (again)?

Washington Post - Technology News

When Kobe Bryant was announced as the third NBA 2K cover athlete earlier this year following his tragic death, NBA fans around the world were elated about the possibilities. I was excited because I figured that a list of challenges would be included, similar to what Michael Jordan received when he graced the cover of "NBA 2K11." Instead, the Mamba Edition gives users a few meaningless in-game tokens like 100,000 virtual coins, 10,000 MyTeam points, MyTeam packs and access to a few Bryant jerseys and shoes for your MyPlayer to sport. As noted earlier, the Mamba Edition does grant an upgrade to the next console generation, so you don't have to buy another copy for PS5 or Series X … but you do have to shell out $40 more dollars when some game franchises are allowing free next-gen upgrades.


AI Is Making Robots More Fun

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The "Curly" curling robots are capturing hearts around the world. A product of Korea University in Seoul and the Berlin Institute of Technology, the deep reinforcement learning powered bots slide stones along ice in a winter sport that dates to the 16th century. As much as their human-expert-bettering accuracy or technology impresses, a big part of the Curly appeal is how we see the little machines in the physical space: the determined manner in which the thrower advances in the arena, smartly raising its head-like cameras to survey the shiny white curling sheet, gently cradling and rotating a rock to begin delivery, releasing deftly at the hog line as a skip watches from the backline, with our hopes. Artificial intelligence (AI) today delivers everything from soup recipes to stock predictions, but most tech works out-of-sight. More visible are the physical robots of various shapes, sizes and functions that embody the latest AI technologies. These robots have generally been helpful, and now they are also becoming a more entertaining and enjoyable part of our lives.


Four steps to accelerate the journey to machine learning - SiliconANGLE

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A good example of solving for the right problems can be seen in Formula One World Championship Ltd. The motorsport company was looking for new ways to deliver race metrics that could change the way fans and teams experience racing, but had more than 65 years of historical race data to sift through. After aligning their technical and domain experts to determine what type of untapped data had the most potential to deliver value for its teams and fans, Formula 1 data scientists then used Amazon SageMaker to train deep learning models on this historical data to extract critical performance statistics, make race predictions and relay engaging insights to their fans into the split-second decisions and strategies adopted by teams and drivers.


A robot triumphs in a curling match against elite humans

#artificialintelligence

A robot equipped with artificial intelligence (AI) can excel at the Olympic sport of curling -- and even beat top-level human teams. Success requires precision and strategy, but the game is less complex than other real-world applications of robotics. That makes curling a useful test case for AI technologies, which often perform well in simulations but falter in real-world scenarios with changing conditions. Using a method called adaptive deep reinforcement learning, Seong-Whan Lee and his colleagues at Korea University in Seoul created an algorithm that learns through trial and error to adjust a robot's throws to account for changing conditions, such as the ice surface and the positions of stones. The team's robot, nicknamed Curly, needed a few test throws to calibrate itself to the curling rink where it was to compete.


Here's how League of Legends Esports plans to keep its players safe from covid-19 at Worlds

Washington Post - Technology News

The overarching situation would have figured to make an in-person event for players a near-impossibility. Riot Games, which publishes League of Legends and runs its competitive league, has dealt with its share of challenges over the past nine championship events, but this year will be a totally new frontier, as it has been for other major sports leagues and tournaments such as the NBA, NHL and MLB. China, like many countries, currently has a hodgepodge of pandemic-related travel policies in place as it gradually eases entry restrictions for some foreign nationals. U.S. citizens are still prevented from applying for tourist visas.


Great Machine Learning Project For Beginners – Predict NBA Player Position

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So now that we've covered the basics of machine learning with regression models, let's move onto something a little more sophisticated: Decision Trees. What is a decision tree you ask? A decision tree is a set of questions you can ask to classify different data points. It's called a tree because it's in a tree like shape, just inverted. If you've got the weather forecast for the day, it'd be pretty easy to look at it and determine if you'd want to go play tennis that day.


4 No-Code Machine Learning platforms you should use in 2020

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Artificial Intelligence (AI) and Machine Learning (ML) are among the most sought after tech skills by companies around the world. There is also a surge in no-code AI platforms. As more and more businesses are looking to leverage the power of AI, companies are accelerating the adoption of these technologies. Building solutions with these technologies require a sound experience and expertise in programming languages, however, there are some no-code visual drag-and-drop tools available to build ML solutions. Now it is an independent macOS application that comes with a bunch of pre-trained model templates.