![]() The online betting customer is apparently more valuable than a sports betting customer. SEE: Metaverse cheat sheet: Everything you need to know (free PDF) (TechRepublic)ĭraftKings has also been looking to diversify away from business that concentrates around the sports season. Shares of DraftKings, which went public via a SPAC merger, for instance, have risen 350% since the start of the coronavirus’ spread, valuing the company at about $22 billion. During the pandemic, as casinos shuttered their doors and consumers looked for activities to eat up their free time, online gambling and sports betting took off. That decision arrived just in the nick of time. Supreme Court cleared the way for states to legalize the practice, striking down a 1992 federal law that largely restricted gambling and sports books to Nevada. Not many years ago, sports betting sat in a legally dubious place in the U.S. “And the quants are kicking the - out of the suckers.” “Horse racing gambling is basically the suckers against the quants,” Rossi said. He now consults for people in the horse-racing world, including what he described as teams of quantitative analysts who use machine learning to game the races betting billions annually and making big bucks–some of it from volume rebates on losing bets by the tracks who encourage the practice. He’s the horse betting expert who helped build a thoroughbred data system that was eventually bought by the horse racing information conglomerate DRF (Daily Racing Form). ![]() In his article, Smith interviewed Chris Rossi. It also sheds light on the dark side of ML and gambling. ![]() So much so, in fact, that Smith doubled his money using an ML recommendation model Akkio created in minutes. Turns out it’s also helpful for Smith’s purposes. Akkio is not designed for gambling but rather for business analysts who want insights quickly into their data without hiring developers and data scientists. His goal? To show how their approach can foster AI adoption and how it is already improving productivity in mundane but important matters. To test the efficacy of ML and horse racing, he tried Akkio, a no-code ML service I’ve written about a few times before. In this example, the regular person is Craig Smith, a noted former New York Times foreign correspondent who left journalism to explore AI/ML. I came across an intriguing example of a regular person using ML to see if they could do better at the racetrack betting on the ponies (a $15 billion annual industry in the U.S.). That might be true, so far as it goes, but there is another side to this argument. The casino industry will argue that AI/ML helps gamblers by identifying cheats faster. SEE: Research: Increased use of low-code/no-code platforms poses no threat to developers (TechRepublic Premium) But any way you choose, over time you almost certainly go broke. The money you bet allows you to earn back about 95 to 98 cents on the dollar (the card game blackjack, by the way, is your best bet). You are essentially renting access to their game. Go to any casino in person and the best odds you can get range from the house taking from 1.5% to 5% off the top (craps, baccarat, slot machines and Big Six can take more than 20%). So, let’s take a look at how one person used ML to fight back. Still, understanding the odds helps you understand the potential risks involved as the gambling industry consolidates. SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)įor one thing, more and more you may be betting against machine learning algorithms, and if the “house always wins” in the offline world, guess what? It’s even worse in an ML/ artificial intelligence-driven online gambling world. What if you are online, and you like to gamble? Who’s on the other side? You have no idea, and that might be more of a problem than you might suspect. Why? Because it captured the upsides and downsides of online anonymity. “On the Internet, nobody knows you are a dog,” is easily one of the top 10 New Yorker cartoons of all time. Hiring Kit: Artificial Intelligence Architect Image: iStock/Igor Kutyaev More must-read AI coverageĨ most innovative AI and machine learning companiesģ questions to separate AI from marketing hype How machine learning is skewing the odds in online gamblingĬommentary: The house always wins in gambling, and the house is getting even tougher through machine learning.
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