A5 Labs has a white paper on online poker

A5 Labs has a white paper on online poker

There are emerging high-tech solutions that can make poker safer for everyone. A5 Labs is a team of tech entrepreneurs, artificial intelligence scientists, online game operators, and die-hard fans who are committed to shaping the future of online competitive games. Poker.Org is proud to bring you this paper that details the issues that online poker faces, as well as the solutions that will see safe, fair and fun games dominate in the future.

A professor,entrepreneur and executive is the author’s background. He was the leader of a worldwide artificial intelligence research group. After moving to the Bay Area, he went on to help StartX companies with their tech and funding raising as well as build his own companies in the area of Semantic Search, Smart Virtual Assistant and Data-/ai-driven Health Care. Shortly after helping Upwork go public, he decided to pursue his passion in poker. He is co-CEO of A5 Labs and is committed to making poker and online competitive games more high-tech, safe, fair and fun.

The white paper was created with the help of editorial help from John, Vitalii, and Yongtao Ma.

Recent high-profile cheating scandals have shown that online poker has come a long way. Operators are thriving, successful players are earning tens of millions of dollars per year, and there is a vibrant community of good actors and powerful opinion leaders helping to steer online poker in the right direction.

They revealed that online poker is low tech due to security and fairness issues, as well as the non-legitimate use of bots and Real-Time Assistance. It seems online poker is less fun for recreational players due to the dominance of predatory actors, apart from a few sites that are leading the way in their commitment and investment towards game integrity.

Imagine you are playing a game of poker where one player is ghosting, the other two are colluding, and the rest of the players are playing just like bots. On top of that, you are wondering if the operator is applying all the required security standards, such as player hand encryption. There is a lot of terminology to unpack, but what it means is that you are playing a rigged game with a low chance of winning.

Beyond security and fairness, what really drives players to brick-and-mortar casinos is entertainment. The poker community loves the technical aspects of the game. They are motivated by the chance to show off their skills against other skilled players. The industry thrives because it is dependent on the recreational audience that wants to see action, excitement and entertaining games. The majority of poker operators are driven by short-term revenue, mainly attracting the professional players that have a bigger impact on engagement and their bottom line. Tough games and strong competition are what recreational users find enjoyable.

We believe online poker is only viable in the long term when operators are able to provide an experience where users feel secure and safe, know the game is fair, and where there is plenty of action for the recreational audience who have a chance of winning and feeling entertained.

We are optimistic about the future because we are part of a team of experts, elite poker players and successful tech business owners with a passion for poker.

In more detail, we will now discuss the adoption of modern technologies and outline a long-term roadmap we believe will help not only individual operators but the industry at large to ensure secure, fair, and fun experiences for online poker users.

To know the players, to be able to quantify positive and negative behavior, and to be transparent about the underlying mechanics are part of the tech foundation for sustainable poker. The impact is amplified when information is made public so that good actors benefit and bad actors are punished.

We need to create the technology solutions we need for poker to thrive, where are we now? We will discuss future directions as well as highlight some of the improvements we have seen in action.

The data layer is the foundation of the poker tech stack. A data infrastructure that allows data to be stored, processed in batches and managed at scale is one of the components of this. There are trackers that follow users throughout their interactions with the system, collecting contextual data, their use of softwares, their actions and the like.

Operators can gain a rudimentary understanding of their player’s identity, risk and value profile using data collected this way.

Major poker operators have solutions for data tracking. Larger operators have an edge in the metrics and patterns they are able to establish and keep up-to-date over time based on the amount of data they hold and the investment they can make in domain expertise. With these solutions, they are able to combat the lion’s share of foul play, but there is still a long way towards gaining full user trust due to these drawbacks.

Basic solutions in the above category are already having an impact on keeping foul play under control. Game Theory, Artificial Intelligence, and Machine Learning help turn data into actionable insights and enable automated decisions that players cannot circumvent at much greater cost.

The foundation of poker is the Game Theory. The optimal poker strategy can be found in the Nash equilibrium, where each player knows the optimal strategies of the other players, and no player can gain by changing their strategy. When playing a GTO strategy, a player becomes unexploitable and will make a profit when other players deviate from that strategy.

We can use solvers to quantify GTO deviations/mistakes in every player’s strategy. We can answer questions such as how close a player is playing from the optimal strategy, and where there were deviations, if it resulted in an unexpected gain for other players at the same table. It’s very important to identify RTA and bot usages as well as colluding among players. This is not straightforward for a number of reasons.

Machine learning can be used to model game play. It takes a lot of domain expertise and manual involvement of experts to be fully operational in a GTO-based solution. Machine Learning-based solutions have the potential to be plug-and-play, enabling automated decisions with little manual intervention.

Significant progress in Deep Learning helped transform the modeling and automated recognition of images, speech/utterances and languages. To establish a task-independent/universal model that can be fine-tailored to specific tasks and goals, the idea is to automatically learn the underlying “latent” representation.

A language model can predict the most likely answer to a question with a few words. We can use game data to build a model that predicts the next action given a sequence of actions and board texture. We can predict the most profitable action using actual data and winnings.

We can predict and quantify how well a player will perform in a game in terms of how many hands they win. Whether a player belongs to a bot group, how similar their action is to known collusion behavior, or if their behavior is consistent across different sessions are just a few of the inferences that can be made from the successful adoption of DL.

The State-of-the-Art solutions are superior to their predecessors because they are non-invasive, produce reliable actionable insights, and cannot be circumvented at a significant cost. Bad actors can’t change their behavior without having a negative impact on their profit. Without being comprehensive, we would like to highlight these successful applications.

We have covered solutions at the frontier of poker tech and it is based on their successful applications in practice that gives us high confidence and optimism about the future of online poker. The work outside of the scope of what individual operators can do is what remains to further eliminate the remaining micro-percents of bad actors and change the public perception.

We have to rethink the platform and embrace more radical solutions in order to achieve the next stage of advancement. It is not an effort to preach Web3 because it is impractical for many industries to move away from the centralized power of Big Tech and there will be strong resistance from the few but large major players. igaming, and especially the online poker industry, is a special case where the adoption of certain Web3 technologies is easier and will have large practical benefits to urgent problems.

Major online poker operators do not rely on monetizing and owning the user data, and they benefit more from sharing the data and being more transparent to gain user trust and confidence. Online poker users are in a position of power that is different from industries where the battle is already lost. Poker operators will run out of business if they fail to make users understand why their platform is secure, safe and fun. We will talk about technologies and directions that will allow them to do so.

Our thoughts on Future Solutions and the call for a moreholistic revamping of the current centralized and inward-looking Web 2.0 platform, smarter incentives, and the push for joint effort outside of the boundaries of individual operators is quite aspirational. Operators are likely to continue to run their business as usual, and they are maybe right to be reluctant because big changes will also have implications on the way they work with partners (for example, terms with affiliates and technology providers are often based on simple revenue-based metrics). The long-term vision can help guide poker players. The poker community is active and influential. There are a lot of smart and powerful opinion leaders who know the balance of power is in their favor and will use that to push the poker industry in the right direction.

Poker has come a long way. Powerful models for modeling value and risk have made it possible for operators to successfully tackle security and fairness issues. When the community works together towards adopting open standards, pushing for industry-wide identity and reputation, and working towards greater transparency, there is still a lot more to be gained for both operators and players. What we think will push the operators in the right direction and help users gauge their level of investment and commitment is what we conclude.

If operators are not willing to come clean, are hand-wavy or lack plausibility in answers to any of the above questions, we should take that as a clear signal for their lack of commitment and ability to ensure secure, fair, and fun games.

The mission to make online poker safe is explained at A5labs.co. Over the next few weeks, Poker.org will be running a series of articles around the issues and solutions detailed by A5 Labs, and we will be getting some of the biggest and most trusted poker players involved to debate the future of online poker.