The artificial intelligence algorithm’s capabilities are rewriting gaming development
DeepStack, the artificial intelligence (AI) algorithm, did something most poker players only dream of doing – beating some of the best players in the world. Just like the rest of us, DeepStack had to learn how to play the game first, but DeepStack had a secret weapon. While most players rely on training videos and books or watching thousands of hours of footage of the best players at the felt, DeepStack taught itself how to play. An impressive feat for a software algorithm and made even more impressive in that it learned to play – and win – in only a matter of minutes. The paradigm for gaming development would never be the same.
DeepStack showed that AI can successfully interpret asymmetric information, a category that covers poker, in ways never before possible. It learned how to adapt its strategy through recursive learning, exploring in a blink of an eye the probability scenarios that would give it the best chances of winning. By the time DeepStack had wrapped up its poker sessions, which included 44,852 hands with 33 players, it was winning at a rate that is comparable to that of only a small handful of the greatest poker players around.
This ability to process asymmetric data artificially (and rapidly) is now being adopted to advance the gaming industry in ways that previously wouldn’t have been explored. It’s just the beginning of what’s possible for AI in the gaming industry, and the next few years are going to see even more advancements made. DeepStack raised the bar on AI software development and is only scratching the surface on what’s possible.