Soccer


Covering the World Cup 2018 with AI and automation – Global Editors Network – Medium

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The World Cup 2018 is all over. Germany was kicked out in the group stages, Brazil was beaten by Belgium, football didn't come home to England, Croatia with its population of four million people reached the final for the first time ever, only to lose to France in the end. Beyond being glued to our screens to watch the action on pitch, we've been looking at what newsrooms are doing off-pitch to cover the competition… with automation and artificial intelligence. Fox Sports (US) teamed up with IBM Watson to make AI-powered highlight videos, French publication Le Figaro created automated visual summaries, and The Times (UK) launched its very own World Cup Alexa Skill. The US didn't qualify for the World Cup this year, but that didn't stop Fox Sports from airing all 64 matches and teaming up with IBM Watson to create the World Cup highlight machine.


OpenCV Saliency Detection - PyImageSearch

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Today's tutorial is on saliency detection, the process of applying image processing and computer vision algorithms to automatically locate the most "salient" regions of an image. In essence, saliency is what "stands out" in a photo or scene, enabling your eye-brain connection to quickly (and essentially unconsciously) focus on the most important regions. For example -- consider the figure at the top of this blog post where you see a soccer field with players on it. When looking at the photo, your eyes automatically focus on the players themselves as they are the most important areas of the photo. This automatic process of locating the important parts of an image or scene is called saliency detection.


The World Cup, Artificial Intelligence and Blueberry Muffins! - The Cork IT Network

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When it comes to disruptive technologies, nothing is more on trend right now than Artificial Intelligence or AI as it's commonly known because it's one of those technologies that we know will impact business, economic and social models as well as our own personal lives. AI is just one part of the larger field of Data Science, where at its simplest, is the art of'extracting value or business insights from data'. While Artificial Intelligence is a term first coined by John McCarthy in 1956, the concept of computers performing cognitive functions to mirror those of humans is around for decades. English mathematician Alan Turing's paper'Computing Machinery and Intelligence' published in 1950 posed the question'can machines think?' and introduced the'Turing test', a model for measuring intelligence. Called'the Imitation Game', it gave notion to the idea of machines being able to move beyond just logical thinking and into the realm of cognitive thinking using skills like learning, reasoning, remembering, understanding and deduction/inference.


How Artificial Intelligence is going to disrupt the sports viewing experience- Technology News, Firstpost

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From the goal-line technology used in football to the Hawk-Eye and the Direct Review System (DRS) in India's favourite game – cricket, technology is being used every moment to make decisions on-ground, and to enhance viewer experiences off-ground. Right from marketing, ticketing, merchandise sales, sponsorship activations, athlete training, visual analysis and more, capturing and analysing data has become the life and blood of sporting events worldwide. With technology itself undergoing several transformations, new and disruptive ones are emerging more frequently than ever, and Artificial Intelligence (AI) is gaining popularity as it covers several areas within the sports domain. They did this after running over 2,00,000 scenarios, based on team data and individual player attributes to project-specific match scores and simulate over 1 million variations of the tournament draw to calculate the probable winner. Using Machine Learning (ML) to predict the outcome of the NBA, and leveraging AI to predict the winners in soccer, are other good examples of the trend.


The iPhone App Making the NBA Smarter

WSJ.com: WSJD - Technology

There is nothing unusual about how little he knows about his own history. Almost everyone in the NBA today came of age in the final years that sports were more art than science. But the game has been transformed since then. A technological revolution has swept through basketball and made it possible for high-schoolers to have more data about themselves than even the most progressive NBA teams had until recently. Lin is now an investor in the latest product that's spreading through the sport and getting attention from the league's brightest minds, a new app called HomeCourt, which comes from a tech company focused on mobile artificial intelligence that was founded not long ago by former Apple engineers who were obsessed with basketball and have spent the last year developing the sort of weapon that Jeremy Lin never had.


Reinventing Human Resources: What HR Leaders Need To Know About Workplace AI

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Artificial intelligence has become a part of how people operate on a daily basis. More than two-thirds of consumers use AI today without even really noticing -- usually in the form of navigation, virtual assistants and that annoying yet entertaining feature on your smartphone that auto-fills your text messages. The benefits of AI from the business perspective are clear in the forms of increased efficiencies, robust data mining and analytics and improved customer relationship management. AI has reinvented what we do and how we get it done. Now, human resources leaders must reinvent HR functions to drive effective talent strategies and sustain results -- and they will need AI to do it.


The Morning After: VAR and Roborace

Engadget

You've made it to the middle of the week. We have just enough time to discuss the future of Nest and how VAR impacted the World Cup, along with a significant promise for the future of AI. Oops?Elon Musk apologizes for calling cave diver a'pedo guy' "My words were spoken in anger after Mr. Unsworth said several untruths and suggested I engage in a sexual act with a mini-sub." The ref is still in control.The World Cup showed how VAR will shape soccer's future For the first time ever, FIFA used the Video Assistant Referee (VAR) at its flagship competition. And the tech, for better or worse (depending on which team you cheered on), certainly made a mark.


Big data couldn't get the World Cup results right

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Goldman Sachs' statistical model for the World Cup sounded impressive: The investment bank mined data about the teams and individual players, used artificial intelligence to predict the factors that might affect game scores and simulated 1 million possible evolutions of the tournament. The model was updated as the games unfolded, and it was wrong again and again. It certainly didn't predict the final between France and Croatia. The failure to accurately predict the outcome of soccer games is a good opportunity to laugh at the hubris of elite bankers, who use similar complex models for investment decisions. Tom Pair, founder of the Upper Left Opportunities Fund, a hedge fund, tweeted recently: "Of course, past data don't always predict the future; Goldman Sachs never tells clients to make decisions solely on the basis of its models' findings.


Big data couldn't get the World Cup results right

#artificialintelligence

Goldman Sachs' statistical model for the World Cup sounded impressive: The investment bank mined data about the teams and individual players, used artificial intelligence to predict the factors that might affect game scores and simulated 1 million possible evolutions of the tournament. The model was updated as the games unfolded, and it was wrong again and again. It certainly didn't predict the final between France and Croatia. The failure to accurately predict the outcome of soccer games is a good opportunity to laugh at the hubris of elite bankers, who use similar complex models for investment decisions. Tom Pair, founder of the Upper Left Opportunities Fund, a hedge fund, tweeted recently: "Of course, past data don't always predict the future; Goldman Sachs never tells clients to make decisions solely on the basis of its models' findings.


Goldman Sachs World Cup Analytics Show Limits of Big Data

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If you're a fan of the World Cup, you probably had your sights set on a winner before the tournament kicked off. Maybe you really liked how Spain's team was shaping up (despite the coaching shifts), or you wanted to root for an underdog such as Japan or Croatia. Goldman Sachs, which knows a little something about probability and risk, built a sophisticated data model to predict the World Cup's eventual winner. This model leveraged machine learning to simulate 1 million possible evolutions, and updated throughout the tournament, according to Bloomberg. With that kind of setup, you'd think that the algorithms would get at least a few match outcomes right.