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(This is Part 1 of a new Sports Analytics series.) The future of sports has been linked with the success of virtual reality and augmented reality. Intel has unleashed their True View virtual reality replay. Since 2016, Microsoft has been touting the future of Super Bowl viewing using its HoloLens. Unfortunately, sports is a spectator sport not a solo one. Especially as you watch the United States college football rivalries. Two words: Toomer's Corner (full disclosure: I am an Auburn fan). Or the European football club blood feuds. Two more words: England fans. Sports means passion. Sports is a shared affinity with communities of people who come from the same city, graduated from the same college, or have a shared pride for a country or region. Sitting around a bar or in a living room with fellow sports affectionados makes up its core. It's not about donning a headset to investigate a play and have no one to shout at the officials with. Another issue for sports going mixed reality is the business models for augmented and virtual reality are failing to generate revenue. As Meta, one of the innovators in augmented reality, is closing its doors due to Trump tariffs and China government intervention. IMAX also announced it is stopping its foray into virtual reality. Sure, both are future looking. Yes, they capitalize on technologies we have been dreaming about for decades. But what's the technologies practical use? What can virtual and augmented reality do above and beyond the traditional two dimensional digital high definition? Yes, it allows you to look around in multiple directions. But can't you do the same thing when you physically attend the game? Here's the rub: note that sports teams need to sell tickets to physical stadiums. If virtual reality real time streaming goes mainstream, ticket sales could suffer. And nothing would look worse than watching a NFL game that has an empty stadium. Have you seen a baseball stadium lately? So what's the savior for the marriage between sports and mixed reality? Recruitment. Traditionally, to get on the radar for a sports team in the United States, you must be on a team whether it's in high school or college. And then your performance must make the rounds of local sports news. A super athlete is really about the stats that they generate (more on this later). Secondly, a super athlete is about the buzz they generate to increase a shared affinity with communities of people. Then a sports organization sends a scout to watch them practice, see their discipline, and see them in action when the game is played. Then, of course, there is the negotiation to get a player to be your sports athlete and not your competitors. But what if you are not in the United States? For example, how does potential NFL super athletes get on the radar? What if NFL linebacker Tamba Hall hadn't immigrated from Liberia when he was child? Or Ezekiel Ansah hadn't come from Ghana? The answer sadly is: nothing. Nothing would have happened. Lost potential. Lost games. What if you can find your next super athlete as aliens found "The Last Starfighter" in the 1984 cult classic? Or what if sports teams followed what the Pentagon has been doing for years? Recruit those who play online games. Can a super athlete can be discovered as a couch potato? No. Can a super athlete be found playing sports in a virtual game theatre? Maybe but probably not. But what if you could link your physical self with a virtual avatar? Enter wearables. A couple of years back I wrote an article that wearable or quantifiable-self is missing the mark on its revenue potential; the article was entitled, "I Love Your Data, Daddy." What if super athletes shared their quantifiable data? With partnerships with Fitbit, Garmin, and Apple Watch – they can safely, securely offer subscriptions to their training habits. How many reps they do with weights? What food do they eat to keep their calorie intake high? How many kilometers/miles they run? And offer a Spotify service of a monthly data subscription to train like your sports heroes. Because sharing your workout routines with family members and close friends can only go so far. Normally it's used to guilt, shame your wife or husband to compete against you around how many steps you did that day. And really, who cares about how many steps? Many use wearables to just keep tabs at where their loved ones go – especially those with Dementia. So how does quantifying one's self become something that affects your reality? Enter mixed reality. Companies such as Gravity Jack, who's motto is "Creating The Future Experience," have been working on augmented reality applications for customers since its inception in 2009. However, these augmented reality applications have been focused primarily on purely marketing efforts or DIY (do it yourself) walkthroughs. At my current company, Qualex where our motto is "See Beyond The Data," we are combining the real-time data that is collected on wearables (via a common API) and feeding them into virtual avatars of the sports fan. Then fans of a particular sport – NBA, NFL, or MLS – can download a sports team's AR app and project a football, a baseball, or soccer field onto any flat surface then play a virtual game with friends who also share their data and have built an avatar. So the more you train, the more you work out, the more you eat healthier and share – the more your virtual avatar is built up. We also ask for them to volunteer game data of playing in the park and league play to fill out the avatar's capabilities. This allows for an augmented reality experience when you are at a coffee shop or in the stadium waiting for the game to start – to see how you would fair against friends. Bar tournaments in local neighborhoods can be set up during half-time or on designated days. On top of that, as we are also aggregating the data from super athletes into animated avatars of themselves. That, in turn, translates into a fan can play against their sports heroes. Note, their skills usually will be no match, but it inspires fans and future super athletes to train harder, become more disciplined, and get more active. And the virtual fields that they play on become an opportunity to advertisers. Virtual partners around going to specific sports retail outlets, vitamin supplement stores, and gyms can partner to give discounts and offer faster upload times for their skillsets. As a service like this goes more international, potential super athletes from Latin America, Southeast Asia, Oceania, and Africa can get on the radar for recruitment. As avatars of fans versus avatars of super athletes play out on virtual playing fields in restaurants and bars – it helps sports teams pinpoint those with statistical success. Sure, there will be false positives. Those that put their wearables on their dogs or cats and allow them to add to their steps or pay persons to work out for them to gain skill. Regardless, it begins to build stronger affinity for teams and outcomes. It disrupts the current era of stats only fantasy leagues. Imagine being able to subscribe to your fantasy league players and play out simulations. These simulations can be played out in virtual reality headsets or via mobile devices. Now a solo activity has become a team sport. And now the future of sports has been irrevocably been linked with the success of virtual reality and augmented reality. How? Because we make you the future. Article written by Gary Jackson Image credit by Getty Images, E+, Anton5146 Want more? For Job Seekers | For Employers | For Influencers
From more efficient data processing to streamlined machine learning, the data industry reflects on innovations from the past year and discuss trends to look out for 2019. 2018 was an unmatched year for the tech industry, with several sectors including artificial intelligence (AI), big data, and analytics garnering increased investment and innovation. With 90 percent of enterprises already investing in AI technologies, the steady momentum shows immense opportunities for growth – for both technology providers as well as the customers they serve. On the horizon for 2019 Databricks, a unified analytics company founded by the original creators of Apache Spark, sees 2019 as the year that more companies solve the world’s toughest data problems that have hindered AI initiatives across industries. This perspective is shared by data thought leaders who advise on AI, big data, and analytics trends that inspired them in 2018, and those on the horizon for 2019: Talent continues to be a focus for AI: According to Bradley Kent, the AVP of program analytics at LoyaltyOne, "The lack of talent is the biggest factor in the path to production. Talent is hard to find, expensive, and often asked to be ‘unicorns’ in their organization. That core issue won’t go away but more vertical-specific solutions will come up and frameworks will seek to automate more of the process." Data processing still the biggest challenge: "As an industry we tend to believe that data scientists are spending the majority of their time developing models," shares Databricks CEO and co-founder Ali Ghodsi. "Truth be told, data processing remains the hardest and most time consuming part of any AI initiative. The highly iterative nature of AI forces data teams to switch between data processing tools and machine learning tools. For organizations to succeed at AI in 2019, they have to leverage a platform that unifies these disparate tools." Streamlining machine learning workflow: "Machine learning is a data challenge," according to Matei Zaharia, chief technologist and co-founder at Databricks. "Large tech companies with unlimited data, resources, and talent have invested significantly in the development of custom machine learning platforms. But, what about the rest of us? Developing tools to standardize the machine learning process – essentially, making it repeatable regardless of data sets, tools or specific deployment methods – will definitely impact if and when organizations achieve AI." AI gets leveraged across the business: "AI has been inspiring in showing what's possible," according to the head of data science at Quby, Stephen Galsworthy. "There are numerous examples spanning sectors of how AI can be truly transformative. However, there are continuing business realities and internal scaling and process challenges. So, I see the need for a lot of innovation around the less sexy stuff: Cost optimization tools, automated accounting, and administration of big data/analytics platforms." Developing trust with ‘Explainable AI’: 2018 saw an intensified focus on data bias, trust, and transparency in AI – an idea that has implications socially, economically, and commercially. According to Mainak Mazumdar, chief research officer at Nielsen, "It is critical to develop AI that is explainable, provable, and transparent. This journey towards trusted systems truly starts with the quality of data used for AI training. This renewed focus in 2018 on labeled data that can be verified, validated, and explained is exciting. It is exciting that ‘Explainable AI’ can lay the foundations for AI systems that can be both generalized across use cases and be trusted." Innovations with real-time data: Stephen Harrison, a data scientist for Rue Gilt Group says "Streaming in and of itself is not really brand new. But Rue Gilt Groupe is planning to leverage streaming data for significant innovations in 2019, like real-time recommendations based on up-to-the-minute data from our order management, click tracking, and other systems. This is especially important for us because we’re a flash sale retail site, with products and online browsing and purchase behaviors changing by the minute." Deep learning pays dividends: Says Kamelia Aryafar, chief algorithm officer at Overstock, "Deep learning innovations will create a lot of new AI applications, some of which are already in production and making massive changes in the industry. We’re currently using deep learning on projects, from email campaigns with predictive taxonomies to personalization modules that infer user style with deep learning. Deep learning will continue to improve core AI and machine learning algorithms." Bringing data teams together Solving the world’s toughest data problems starts with bringing all of the data teams together within an organization. Data science and engineering teams’ ability to innovate faster has historically been hindered by poor data quality, complex machine learning tool environments, and limited talent pools. Additionally, organizational separation creates friction and slows projects down, becoming an impediment to the highly iterative nature of AI projects. Much like in 2018, organizations that leverage unified analytics will have a competitive advantage with the ability to build data pipelines across various siloed data storage systems and to prepare labelled datasets for model building, which allows organizations to do AI on their existing data and iteratively do AI on massive data sets. Article published by Anna Emery Image credit by Getty Images, Moment, Matt Anderson Photography Want more? For Job Seekers | For Employers | For Influencers
In my late teens, I was a huge fan of "Choose Your Own Adventure" books. I especially liked the ones that came out for identifiable franchises like "Indiana Jones" because I knew the motivations of the characters and I had already seen Indiana Jones play out scenarios where he won – based on the films. But just in case, I always kept my finger on the page where I had to make my choice in case my decision was a poor one – and pretend it never happened. As a pre-New Year's gift to its subscribers, Netflix used a fake reveal and later a trailer to let the cat out of the bag that "Black Mirror's Bandersnatch" was going to be the first ever choose your own adventure film by using an open source technology called Twine. "Bandersnatch" delivered, allowing the viewer if using the appropriate device (devices were identified by having a red banner with a star on it to let you know that it will allow for you to make decisions). If you didn't have the appropriate device, it would allow only the teaser to play. "Bandersnatch" began like any other streaming film. Then five to seven minutes into the film it offered choices underneath the frame with a 10-second time limit to decide as the actors kept playing out the scene. ** Spoiler Begins ** For example, after deciding which cereal the lead, Stefan Butler, would eat and the cassette he would listen to while riding the bus to the interview for the video game company (I chose Thompson Twins), Stefan is given the opportunity to work for the company he is interviewing for. Even the video game creator rock star, Colin Ritman, is in the room when he is offered the opportunity. Stefan acts out anticipation and excitement about the role as you are giving a 10-second count to make a decision to accept or decline. The answer is easy, duh. Stefan is in awe of the company and working alongside his idol! But when you choose accept, the next scene transitions to months in the future, the game is finished but reviewed poorly. Finally, ending your choice. ** Spoiler Ends ** So is it truly your own adventure? Wasn't a lot of the premises like the one above false 'smoking guns' to get you to choose paths that led to dead ends? Without context, how can you make choices for a character if you don't understand his or her motivations? Isn't the purpose of a film and a television show to get you to forget about choices? Detach yourself from reality? And are we forgetting the "chill" part of Netflix because they are so engrossed in choosing paths for fake characters? They forget about the fun in interacting physically with one another. With interactive films, Netflix doesn't care about the chill. Nor does it care about the story, really. The only motivations they are interested in are yours as a viewer. Netflix is using the choices you make as a data science experiment to gather all the mundane choices to fuel future content, commercial, and technology partnerships. So will interactive films soon become the norm? Too late, it already has. Executive producers and filmmakers will gain more funding than virtual reality filmmaking in the upcoming months. But not for good reasons. Interactive films allow corporate executives to go head to head with creatives about ideas and both win. A creative (writer/director or both) can disagree with corporate about a film direction, script plot point or how it should end – but give money to produce all. Who funds it? The advertisers and technology partners paying for the data. One day we might talk about a past where storytelling was about generating viewpoint and empathy from a perspective you might not normally agree with. For example, in the future, Hamlet as an interactive statement, "To be or not to be" creates a whole new story line. Most films of the past created a cultural collective. If everyone watches a film, but everyone has different experiences there is no affinity built when you share the experiences, attitudes, and feelings about the outcomes. The only true community for interactive films are for those that find themselves on Reddit to flowchart the choices. This January and February as the Golden Globes and the Oscars go on, think of a future where merely 45% of all films start moving towards interactive – how will they be judged? Purely on the acting? Premise? Or will writers have to create multiple award-winning endings and allow for films to win multiple categories – for Drama and Comedy? Note that no "Choose Your Own Adventure" book has ever won the Pulitzer Prize. So let's keep our finger right here, turn the page, and watch it play out. If interactive films become the new creative abyss, no problem. We can just go back to where we were, make another decision, and pretend it never happened. Article written by Gary Jackson Image credit by Mohamed Hassan Want more? For Job Seekers | For Employers | For Influencers
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