The Top 8 AI Trends to Watch Out For in Gaming
The world of gaming has always been about pushing boundaries, challenging norms, and using the latest technology to provide the best gaming experience. From adjusting the game difficulty in real-time to responding to player tendencies and behaviors with dialogue, the advent of Artificial Intelligence (AI) has opened up new possibilities that will revolutionize gaming. AI has already made its presence felt in gaming, but the impact it will have in the coming years is yet to be fully realized.
In this article, we will examine the current trends in gaming and discuss how AI is already making a significant impact, and then explore eight ways that AI will significantly change the way we play games in the future.
Why Should I Care About AI in Gaming?
AI has changed the gaming world forever, allowing gamers to experience previously impossible things.
Developers use AI to create non-playable characters (NPCs) like shopkeepers or game bystanders. NPCs are virtual characters that the player can interact with within the game, and game developers can use AI to make them feel more realistic and intelligent. Artificial Intelligence enables NPCs to recognize and respond to players' actions; for example, the shopkeeper could bargain with you for a valuable item.
Pathfinding determines a virtual character's best route through a game environment. AI pathfinding algorithms such as A* can read the game map and determine the most efficient path for the character, like Google Maps for your avatar. AI has also been used to ease in-game navigation for players.
Adequately trained AI systems can spice single-player games up by adding a bit of challenge. A bland first-person shooter could turn into a timeless masterpiece with the addition of AI systems that can respond to player actions or outsmart them. An example was the AI from Dead Space, which would occasionally try to ambush or flank you to win the game. Similarly, in real-time strategy games, AI virtual opponents can make strategic decisions based on the player's actions, which can surprise the players used to hard-coded enemies. These characters can contribute to more realistic and challenging games that keep players engaged and entertained.
Data mining is another area where AI is used in gaming. Game developers can use AI algorithms to analyze player data and gain insights into player behavior, preferences, and playing styles. They can use these insights to improve their game in several ways.
Game developers can also use AI for content generation, which involves using algorithms to create game content automatically. For example, AI can generate random game levels, characters, and items, providing players with a more diverse and engaging gaming experience.
In addition, UX engineers can use AI to model player experiences. By analyzing player data and behavior, AI algorithms can create personalized experiences for each player, tailoring the game to their preferences and playing style.
Unfortunately, AI isn't only used for good. Hackers can use AI algorithms to create bots that play the game automatically and gain an unfair advantage over human players. However, since AI is great at finding patterns, developers also use AI in anti-cheat software to detect and punish irregular player behavior, making the game fairer for everyone.
8 Possible Applications for AI in Future Games
As AI technology advances, game developers find new and innovative ways to use it in their games. Here are eight ways AI will change gaming:
Synthetic and Dynamic Dialogue Generation
Using Natural Language Processing (NLP) algorithms, games can generate dialogue tailored to the player's choices and actions. In Detroit: Become Human, NPC dialogue is based on the player's choices and interactions with non-playable characters. Each player could play through a unique game, depending on their play style. The AI would generate different dialogue options based on the player's decisions as the game progressed.
This type of technology will only improve with the advent of large language models like OpenAI's ChatGPT and Google's LaMDA. Instead of spending months or years building a content narrative with large choice trees, developers and scriptwriters will now focus on their game’s core mechanics.
Cloud-Based Gaming Integration
Cloud-based gaming allows players to access games from anywhere, using any device, without any drop in performance. Machine Learning algorithms can analyze player data and behavior to optimize server resources and ensure every game runs smoothly. And even further, optimize cloud-based gaming experiences by intelligently managing server loads and minimizing latency.
Cloud-based gaming also opens up opportunities for more complex and engaging games for more platforms. Artificial Intelligence can handle complex calculations and simulations that would otherwise be impossible on some devices.
Virtual Reality Movement Tracking
Virtual reality (VR) gaming is enjoyable, and AI can significantly enhance the VR experience for users and enthusiasts. For example, the Oculus (Now Meta) Quest 2 VR headset uses AI and cameras to track the user's hand motions and adjust the display seamlessly. While Meta’s hand-tracking algorithm is impressive, Artificially Intelligent systems are also used for Full-Body Tracking.
Full-Body Tracking AI can track and translate a player's movements into actions within a game, allowing for more precise movements and interactions with virtual objects. You may have experienced a simple version of this technology in games that supported Xbox Kinect. Still, the increase in AI computing efficiency means we are probably not far away from an advanced version of the Kinect’s tracking capabilities in every game. If you ever felt like being ‘inside’ the games you played, it may be a reality soon.
Level Design and Generation
In the past, game developers had to design and test each level of their games manually. That type of development is a time-consuming process that could lead to repetitive gameplay and burnout. However, AI algorithms have revolutionized game design by creating randomized levels based on player data and feedback.
An excellent example of this type of development is Hello Games' No Man's Sky. Even though a relatively small indie studio created it, its universe features 16 quintillion AI-generated planets, each with unique terrain, creatures, and resources.
The procedural generation AI algorithm creates infinite planets, ensuring the game world remains fresh and exciting for players. With the help of AI, game developers can focus on creating more innovative gameplay mechanics while the algorithm generates new content to keep the game engaging and challenging.
While automatic level generation is convenient, game developers must balance AI-generated content with human-created content to ensure that the game retains its creative vision and is not solely dependent on AI-generated levels.
Player Sentiment Analysis
Player sentiment analysis involves analyzing player feedback, reviews, and other data to gain insights into player preferences and behavior.
Developers can use AI algorithms to analyze player feedback. Instead of sifting through thousands of reviews, a sentiment analysis algorithm can give developers an insight into what players enjoy the most when playing their games.
This technology may get much better soon. Developers may be able to use extensive data analysis to fine-tune this process, allowing them to understand what levels, menu elements, or enemies users like the most. They may soon be able to integrate data collection and AI so closely into their games that they will know precisely how to build the next version of the game to appeal to more people.
Audio Recognition Games
AI voice recognition will enable developers to build games that respond to player voice commands. Using Artificial Intelligence models like Whisper, developers will create video games that use the users’ voices as input to play the game. This mechanism would make game dialogue more natural since users can chat with their game as with a friend.
Game developers could also use AI to create games that respond to environmental sounds, which can be used to generate randomness or to simulate your room in the game.
AI can help developers to improve their games by analyzing feedback forms or player behavior. After these algorithms identify performance issues, they could use other users’ data to predict the best settings for each device.
Games could also use AI systems to optimize game mechanics and balance. Developers will use AI to support their game economy and systems, keeping the game as balanced as possible.
Cheats and Anti-cheats
Game developers aren’t the only ones using AI in gaming. Game hackers have used AI-enabled cheats in almost every game - from Chess to Geometry Dash to Call of Duty. An example could be systems that use computer vision to identify and snipe enemies from across the map.
Game hackers try to evade anti-cheat software by increasing the complexity of their cheats. A lot of hacks now use software that doesn’t run on the target computer, so anti-cheat software that analyses running programs on the computer won’t be able to detect them.
Hackers are also using AI to make the effects of their cheating harder to detect, even going as far as simulating human errors and mouse movement to prevent the AI from flagging them.
This is why most modern online multiplayer games also feature a bundled AI anti-cheating system. These systems monitor your game activities, flag any irregular behavior, and allow developers to punish you for using cheats in the game. As game developers get more user data and AI advances, these systems will analyze more variables and catch cheaters more effectively.
Conclusion: The Next Steps for AI Gaming
Artificial Intelligence is here to stay. It is a valuable tool for developers because most games already have some AI algorithms behind the scenes. We may not understand what is possible in this field; AI is an active field being introduced into new games. The full ramifications of its integration into gaming may not become apparent for several years.
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