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<\/a>Too much strength in numbers, however, may not be in anyone\u2019s best interest. The apocalyptic visions of AI in the movies, such as ARIIA in Eagle Eye<\/em>. V.I.K.I. in I, Robot<\/em> or the Robots in the Matrix<\/em> offer up pretty bleak visions of an AI controlled world. To bring such latent fears even closer to home, Google of all people, went so far as to actually warn<\/em> in February 2017 that its AI machine DeepMind begins to use \u201chighly aggressive\u201d strategies when it\u2019s in stressful situations<\/a>. Humm, a gaming machine with a temper? Let\u2019s hope it doesn\u2019t have a gun?<\/p>\nYou can\u2019t say Hollywood didn\u2019t see it coming. As did the famed physicist Stephen Hawking, who recently told the BBC that AI (and by implication the strength all those numbers swirling around in the ether and directed by the computer itself) could spell the end of humanity\u2026 or be the best thing ever! Really, he said that. Maybe it\u2019s time to take up roulette, while there\u2019s still an upside to those swirling numbers! Billionaire Tesla and SpaceX founder Elon Mush is of like mind, telling the Huffington Post \u201cwith artificial intelligence we are summoning the demon.\u201d<\/p>\n
For now, though, most of the serious real-world AI and its dramatic effects remain in the realm of tech giants, university research departments, famous chess, Go and poker players, dramatic news stories and the silver screen. The random number generators in online casinos are heavily regulated, and an aggressive computer helping fly the plane isn\u2019t likely to take the pilot\u2019s spilled coffee personally.<\/p>\n
Poker AI out buffs the world\u2019s best players<\/h2>\n
In 2016, Google\u2019s temperamental DeepMind was able to definitively beat the world\u2019s best players at the game Go by learning from its own moves. To do so it analyzed 30 million Go moves from human players before learning on its own by playing against itself.<\/p>\n Most recently, Libratus, a computer designed to play poker built by researchers at Carnegie Mellon University, successfully out bluffed four of the world\u2019s best poker players. Libratus pulled in approximately $1.8 million in the 20-day match, with professional players Dong Kim, Jimmy Chou, Daniel McAulay and Jason Les left to split the $200,000 purse for their time. Talk about a killing machine, well Libratus sure made a killing.<\/p>\n Referred to as \u201cartificial, artificial intelligence\u201d, Swarm A.I., known as \u201cUNU\u201d is a platform created by the Stanford educated computer scientist and AI researcher Louis Rosenberg and launched by his California based start-up Unanimous A.I. last year. Different from a poll, which combines individuals\u2019 opinions or votes, UNU combines elaborate computer algorithms with the brain power of human groups working together online to form a computer moderated consensus to make predictions and decisions that are, as the website says \u201coften smarter and more insightful than the individuals would be alone\u201d. Political pundits and bookies have a reason to be nervous. Look at the results:<\/p>\n Most recently, UNU beat the music industry\u2019s leading experts at Billboard and Rolling Stone to predict the 2017 Grammy\u2019s in 5 out of 7 categories, with the Grammy\u2019s own fan poll getting a whopping zero out of 7 correct. The swarm and its algorithms also predicted the 2017 Super Bowl score perfectly. Not to mention the 2016 Kentucky Derby winners. UNU\u2019s human based algorithms predicted the first, second, third and fourth place horses in the Derby at 540-1 odds, earning the technology\u2019s inventor Louis Rosenberg $10,842 from a $20 dollar bet. Not bad, hugh? While undoubtedly imperfect as both human beings and machines are want to be, swarm AI still got 11 out of 15 winners correct in the 2016 Oscars. A truly impressive showing.<\/p>\n So while UNU may not yet be the best way to pick your lottery numbers<\/a> and the AI apocalypse may still be far enough away to give you time to play, for bets and decision making that require a degree of human intelligence (above and beyond the bookies) UNU and swarm intelligence may well be worth a closer look.<\/p>\n<\/a>It is however, worth a look back at AI\u2019s slow but steady ascent, which has been pretty dang amazing. In 1996 IBM\u2019s monster AI computer Deep Blue was the first (but not only) machine to defeat world chess champion Garry Kasparov. Quite a feat for hardware and software spinning a bunch of zeros and ones. Not long thereafter, another IBM computer, nicknamed \u201cWatson\u201d, was able to beat all-time Jepardy! quiz show winner Ken Jennings in 2011, after which a pleasantly stunned Jennings remarked \u201cI, for one, welcome our new computer overloards!\u201d<\/p>\nUNU perfectly predicts the 2017 Super Bowl<\/h2>\n
<\/a>So, will AI machines end up with a seat at the table in the world\u2019s casinos? Not likely. But there is another, linked phenomena, that may soon have the book makers up in arms. Enter the SWARM. No, not bees or locusts, crazed gulls, Christmas Island crabs, monarch butterflies or mosquitos, but people! Well, not exactly. People, algorithms and computers. A sort of machine aided group think.<\/p>\n