by: DAAguilar

Ian Fellows dubbed his creation Fell Omen 2. A play with words but with far more significant/sinister meaning, Fellowmen, along with the ominous consequences such creation may entail. Ian Fellows was not the first in the field to come up with a Poker Frankenstein, but he’s one of the first to open the floodgates of possibilities, even beyond the sport.

The endeavour has been compared in parallel to the chess prodigy project, Deep Blue. It was news then, a computer that can interpret chess moves and tactics and counter it with its own logical calculations. Gary Kasparov, king of the chess hill tested it. The man beat the machine the first time they met. Then Deep Blue beat Kasparov in 1997 with 1 game, 3.5 to 2.5. It was a great moment for science and technology when it exploded, but it didn’t have a lingering afterglow. The consequences of a tool that can be both beneficial and dangerous like fire is seductive or paranoia inducing, since we are entering a world where technology can detect patterns and catch us where we’re going. Practical applications where it can be incorporated are something that we have embraced. Like when search engines suggest what we want to search for as we type it in. Many then toyed with the idea of smart homes, smart cars, and smart appliances all for our convenience. Machines in turn, become smarter than most humans because they can understand and predict where we want to be while we, the average man, can barely understand them and its schematics. With a pokerbot, perfecting the algorithm that can detect bluffs and read tells, the possibilities are endless. Imagine, a machine that can tell a man’s sincerity? We’d have more convincing political debates that way!

With poker in full bloom over the last decade, it’s but natural for technology to come in. Like chess, it challenges you to know where you’re opponent is taking you while he reads the many possibilities of where you’re taking him. All the information is on the table and out on the board. With poker, the war is won with the information and the misinformation that you lay on the table. This is what makes it harder to deduce. That’s why those who pledge by the efficiency of a poker bot says that they broke-in their bots with a good number of games (about 2500 games)for them to reap the dividends of their investment. But that’s a very long rope to pull to get to a point where one starts to earn 2 US$/hour. You can’t really get greedy with it because it’s like tagging a red flag on your bot. And it’s not cost efficient to use multiple cards and identities just so you can hawk out a decent amount. This is the reasons why major on-line poker rooms belittle its supposed unfair advantage. But despite that, some sectors believe that a rough estimate that 1 out of 12 player, on average, that play on an online poker room are poker bots. (continue reading…)