Revolutionizing Web3 Gaming with AI & Machine Learning
The most talked about topic in 2023 has probably been Artificial Intelligence. With OpenAI, MidJourney, Bard, Netomi, and, most recently, AutoGPT, we’re seeing a giant shift in many industries. Doors are opening to a unique and exciting future. Perhaps one of the most exciting area’s AI will have its impact is the Web3 gaming industry.
AI And ML Take The Lead
Artificial Intelligence (AI) and Machine Learning (ML) are two of the most powerful technologies of our time, and they are rapidly transforming the way we interact with the world around us. The use of AI and ML enables game developers to create an immersive and engaging gaming experience. It opens up new possibilities for players that were previously unimaginable due to simple programming constraints. There’s a big picture coming from AI and ML.
AI and ML can be used to generate realistic worlds, as well as to provide players with new levels of customisation and control over their gaming experiences in real-time fashion. Another impactful area is how it will be used to improve game fairness and combat cheating, as well as to provide developers with insights into player behaviour. Despite the worries of AI in many spaces, almost every game developer is jumping at the opportunity to use AI to optimise game design and monetise their work.
Where Can AI and ML Be Used?
Here are some ways in which AI and ML are reshaping Web3 gaming experiences.
Procedural generation:
Procedural generation was implemented into the popular “No Man’s Sky.” Procedural generation is used to create an entire universe with 18 quintillion planets, each with its own unique flora, fauna, and terrain. The game uses AI and ML to generate these planets on the fly, meaning that players can explore an almost infinite number of worlds that are completely unique.
This creates an endless variety of gameplay experiences, making No Man’s Sky a game that players can continue to explore for hundreds of hours without ever encountering the same world twice.
With Web3 games, AI and ML will be used to generate unique game worlds, characters, and objects that can provide an endless variety of game experiences for players.
Personalisation
AI is a fantastic way to learn about players’ gaming preferences and behaviours to individually personalise game experiences. This can include recommending games, creating custom levels, changing difficulty accordingly, and providing tailored rewards.
Let’s say a player takes on a quest to save the kingdom from an evil sorcerer. Along the way, the AI in the game learns about the player’s preferred playstyle, from their preferred weapons to their favourite spells.
Using this information, the game generates custom levels that are tailored to the player’s abilities, ensuring that the challenge is perfectly balanced. Additionally, the game provides rewards that are tailored to the player’s achievements, making every victory feel truly way more meaningful.
Fraud/Cheat Detection
Machine Learning will turn into one of the fastest and greatest ways to detect cheating. ML can help detect and prevent fraud in gaming transactions. This can prevent cheating, improve fairness, and protect the integrity of the game.
Valve famously uses a flawed “Valve Anti-Cheat” as their way to prevent cheaters in the game. CSGO is one of the most popular games in the world. However, as with any competitive game, it has a massive cheating problem. To combat this, CSGO developers should be using ML to detect fraudulent behavior, such as aim botting and wallhacking.
The ML system can detect new ways in which players try to circumvent its system. This helps to ensure a fair and competitive environment for all players, preserving the integrity of the game.
Monetisation
A hard-working developer has a fair reason to make a living from their work. AI and ML can be used to bring monetization to Web3 games in a variety of ways. One of the most significant ways in which these technologies can be used to generate revenue is through the creation of personalized in-game purchases.
In Web3 gaming, players truly own their in-game assets, and this means that they can be traded, bought, and sold on the open market. By using AI and ML to learn about each player’s preferences and behaviours, developers can create customized in-game items that are tailored to the player’s interests. These items can then be sold to players, either directly by the game developer or through a marketplace, creating a new revenue stream for the game.
Conclusion
Overall, the use of AI and ML is transforming Web3 gaming in numerous ways, and the potential for future innovation in this field is vast. As technology continues to evolve, we can expect to see even more exciting developments in the world of Web3 gaming in the years to come.
