The major hurdle for any machine learning model to succeed, in the majority of cases, is the lack of adequate data. If the model fails even for an instance, for sure the team would be looking for a new set of data that is compatible with the context. One particular type of data that can help ML engineers is dark data. One may have many questions like, what is dark data? How is it different from big data?

It is not surprise for machine learning models to provide decent prediction accuracy of soccer games outcomes based on various objective metrics. However, the performance is not that decent in terms of predicting difficult and valuable matches. A deep learning model is designed and trained on a real sequential trading data from the real prediction market, with the assumption that such trading data contain critical latent information to determine the game outcomes. A new loss function is proposed which biases the selection toward matches with high investment return to train our model. Full investigation of 4669 top soccer league matches showed that our model traded off prediction accuracy for high value return due to a certain ability to detect dark horses. A further try is conducted to depict some indicators discovered by our model for describing key features of big dark horses and regular hot horses.

A platform that crowdsources the insights of experts to make predictions on events has come up short in its second attempt to call the Kentucky Derby. It got last year's race exactly right. Unanimous A.I., a company touting the power of collective intelligence to provide insights into the future, correctly predicted the top four finishers of the 2016 Derby: Nyquist, Exaggerator, Gun Runner, and Mohaymen. Anyone who bet their prediction of the top four finishers would have scored a so-called "superfecta" that paid out on odds of 540 to 1. That success earned Unanimous this year an official handicapping partnership with Churchill Downs, the racetrack where the Kentucky Derby is held, and the company once again used its AI platform to analyze input from "some of the best racing minds in the world."

AI is changing the world. In our lifetimes, we have seen a cloud revolution come in, then came in the mobiles. Now is the time for AI revolution. Similar sentiment was expressed by Sundar Pichai recently, when he said "I think we will evolve in computing from a mobile-first to an AI-first world" The key question is where is this change happening? When it comes to tech revolutions, we have been conditioned to assume that all is happening in the west.

The news that Christina Grimmie -- the 22-year-old singer who, as a New Jersey teen, made a name for herself on YouTube before broadening her fame in 2014 on Season 6 of "The Voice" – was shot and killed Friday while signing autographs for fans after a concert in Orlando, Fla., is tragic. But for fans of "The Voice" who watched Grimmie show off, during her time on the show, not only her impressive vocal chops and stage presence, but also her musical creativity, willingness to experiment and upbeat resilience, the loss must be heartbreaking. Those who watched Grimmie turn four chairs during her blind audition and then stick around to finish third on the show, behind only sweet, shy, country-singing runner-up Jake Worthington (of Team Blake Shelton) and silky-soulful winner Josh Kaufman (of Team Usher), knew she was an unusual talent. Grimmie's coach, Adam Levine, believed in her so fiercely that, at one point, he promised the audience she would end up winning the show. Then, when she didn't, he announced that he planned to sign her to his own label.