Collaborating Authors


Some sports teams explore facial-recognition tech, hope it will help with contactless admission

FOX News

Several sports teams are exploring the use and implementation of facial-recognition technology in their stadiums, an effort that would help reduce risks from the coronavirus when fans return, the Wall Street Journal reported. The initial outbreak of coronavirus appeared to accelerate due to high-occupancy sports venues in Europe acting as super-spreaders – most notably soccer stadiums in Italy, and matches in the Champions League involving Spanish teams. With some areas seeing the pandemic under control, sports teams are looking to bring back fans in a safe and controlled way. The use of facial-recognition technology may allow sports venues to bring back small numbers of fans – most likely season-ticket holders or VIP guests – suggested Shaun Moore, chief executive of Trueface, a facial-recognition supplier. Moore indicated that the primary concern is that even scanning ticket bar codes could help to spread the virus.

How and why I built Machine Learning model to predict tennis table matches results


I'm a Data Professional who loves building data products to solve problems. I'm currently working together with professionals from various backgrounds to provide new analytical insights in industry. I'd love to combine my passion for open data to continue contributing to change people lives in a better and analytical world. A customer reached me out to help him building a profitable machine learning model to predict tennis table matches results based on the historical data. After starting the project I have noticed that the challenge was bigger than expected because the data provided, which was collected before using web scraping, was not reliable enough to train a good model. First of all I have chosen Python as the language for the project since python provides many libraries and documentations to support with any challengs during this milestone.

How Machine Learning Made Me Fall in Love with the WNBA


I had one of those daydreams that come to you from out of nowhere. Before my eyes fell the image of an all-star women's sports team. Like Mario Kart except instead of Mario, Princess Peach, and Toad you have Serena Williams, Lisa Leslie, and Katelyn Ohashi all playing on the same platform. I realized that I could make this vision a reality by using data science and machine learning tools to design the best teams and predict what it would look like if they were to play against each other. However, as with all big dreams (and big data), I decided to start with a subset of the women's sports world and work my way up towards acquiring data from other women's sports.

The (Un)ethical Story of GPT-3: OpenAI's Million Dollar Model


Back on October 12, 2019, the world witnessed a previously unimaginable accomplishment- the first sub-two-hour marathon was run in an incredible time of 1:59:40 by Kenyan native Eliud Kipchoge. He would later say in regards to the amazing achievement that he "expected more people all over the world to run under 2 hours after today" [1]. While Kipchoge set new records in long distance running, across the world a team of natural language processing (NLP) experts at OpenAI, the Elon Musk-backed AI firm, published a new transformer-based language model with 1.5 billion parameters that achieved previously unthinkable performance in nearly every language task it faced [2]. The main takeaway from the paper by many experts was that bigger is better-the intelligence of transformer models can dramatically increase with the scale of parameters. In March of 2020, this theory gained support with OpenAI's release of version three of the model or GPT-3 which encapsulates a staggering 175 billion parameters and achieved even more remarkable performance than version 2, despite sharing, quite literally, the same architecture [3].

How AI is democratizing innovation in esports and beyond


It's no secret now that esports are taking over both real and virtual worlds with a global audience nearing half a billion spectators. And esports industry statistics are earth-shattering, with annual growth rates as high as 20 per cent and revenues exceeding 1 billion USD per year. But what about the technology that makes the esports multiverse so compelling? This was the question explored by a recent AI for Good webinar as part of the Global Dialogue on Esports. Featuring expert panellists hailing from Singapore, Toronto, Manchester and more, the diversity of speakers and attendees demonstrated how esports is truly a global phenomenon.

Texas stadiums helping fight coronavirus with disinfectant-spraying drones

FOX News

The Cotton Bowl is the first stadium in Texas to take a chance on the technology, which has the capability of disinfecting a 92,000 person stadium within 4 hours. DALLAS -- Stadiums are looking for ways to bring fans back to the stands in time for fall sports despite the coronavirus outrbreak, leading some Texas facilities to turn to drones for help. Cotton Bowl senior marketing director Julian Bowman describes the feeling of seeing the iconic Cotton Bowl Stadium in Dallas empty for the last few months, saying, "It is a weird feeling." "The Cotton Bowl opened up in 1930, so this was our 90th year and it was set to be our best year ever and unfortunately with COVID we are not able to do that," Bowman said. "It has really affected how we have been able to connect with our sports community and our entertainment community." The last event the Cotton Bowl was able to host was in January of 2020, before COVID-19 shut them down.

Coaching in 2030: How Artificial Intelligence Will Change Our Profession - SimpliFaster


"Simply put, for the last 200 years, advisers have worked on the principle of information asymmetry, where they have better information than their clients. Today, we are at the point where machine intelligence is gaining information asymmetry over advisers, and that's only going to get more acute and asymmetrical as time goes on. The only possible hope for human advisers is that they co-opt machine intelligence into their process." For better or worse, we are living in a rapidly changing time. Only 20 years ago, as I moved from Australia to the U.S. and made my first trip to Disney World, I vividly remember the view into the future provided by the ride "Spaceship Earth."

Who's the greatest golfer of all time? This data-led project might have the answer


What do you do if a global pandemic means you can't stage one of the world's most famous golf tournaments? For The R&A, organisers of The Open, the answer was to use a combination of data and video to create a virtual tournament of golfing greats from the past 50 years. While the virtual tournament was no replacement for the excitement created by a real-life Open, it did allow golf fans to enjoy something that might previously have been considered impossible: to watch the greatest golfers from the past 50 years compete against each other in a single championship. Known as The Open for the Ages, the event took place from the 16 to 19 July, when the 149th staging of The Open was due to take place. It used archive footage to play out a data-led tournament that included some of golf's greatest players, including Seve Ballesteros, Tiger Woods, Rory McIlroy, Jack Nicklaus and Tom Watson.

GPT-3 Creative Fiction


What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.

The NBA will use Microsoft Teams to virtually seat fans courtside


When the National Basketball Association (NBA) restarts its season on July 30th, it will use Microsoft Teams to recreate the atmosphere of a packed arena without any fans physically present. As part of its ongoing partnership with Microsoft, the league plans to use the software's recently released Together Mode to put more than 300 fans in the stands (via The Verge). The feature utilizes AI to segment your face and shoulders and put you in a shared digital space with other people. The NBA will equip arenas with 17-foot tall LED screens that surround the court. The displays will allow players to see and hear the people who are watching them via Teams.