In 2019, Facebook and CMU beat pros at 6-max Texas Holdem using the equivalent of $150 of computer time
Pluribus achieves this result through several innovations on Libratus, the AI that beat human pros in two-player no-limit Hold’em in 2017, as well as other algorithms and code developed in Tuomas Sandholm’s Carnegie Mellon University research lab. In particular, Pluribus incorporates a new online search algorithm that can efficiently evaluate its options by searching just a few moves ahead rather than only to the end of the game. Pluribus also uses new, faster self-play algorithms for games with hidden information. Combined, these advances made it possible to train Pluribus using very little processing power and memory — the equivalent of less than $150 worth of cloud computing resources. This efficiency stands in stark contrast to other recent AI milestone projects, which required the equivalent of millions of dollars’ worth of computing resources to train.
In 2020, Facebook and CMU published ReBel, a more general AI for games.
In 2019, Morgan Stanley downgraded the long term outlook for online poker because of the potential for bots:
“The (re)emergence of superhuman poker bots in the online ecosystem now appears to be a matter of when, not if,” analyst Ed Young wrote in a note.
According to https://www.pokerscout.com/, as of December 2020 there are over 10 real money poker sites that have had >1000 cash players online during the last 24 hours.