Regular FIFA players may have noticed that the better they play in matches, the more difficult the next game gets. This wasn’t the case in the earlier versions of the popular virtual football game. This has been integrated through FIFA’s Dynamic Difficulty Adjustment system, made possible by AI algorithms.
AI is being used in various facets of gaming, from game development to the gaming experience. It is also used in all sorts of games, from cash rummy to fantasy sports. AI is used to develop new strategies in online rummy, defining NPC behaviour in action games and addressing a host of off-game areas as well.
Another major area where AI and behaviour analytics are actively used is in identifying and resolving issues in gaming.
AI Revolutionises Gaming
When it comes to analysing large data and getting things done quickly and accurately, no one doubts the machines. Back in 1997, IBM’s computer Deep Blue defeated the reigning chess world champion Garry Kasparov. For all of Kasparov’s brilliance, here was a machine that could analyse a million possible chess moves in a second. That’s artificial intelligence in gaming, except that it now covers a wider ground in the industry’s landscape.
Developing the ‘perfect game’ has been a perennial challenge for game developers. The use of AI in game creation has now enabled developers to generate and simulate countless game levels and challenges and test them for dynamism. AI can create intricate game environments quickly, which can include new avenues, treasures and encounters within the game.
Thanks to AI, procedural generation has reduced the manual effort involved in gaming content creation. Game designs are now more proactive, where the game mechanics, challenges and content are aligned with the expectations of the gamers.
Many companies have come up that provide AI-centric services to gaming studios. Latitude, one such company, specialises in AI-generated infinite stories for video games. The company even raised more than $3.3 million in funds.
AI is also being utilised in many post-development activities in gaming. AI tools are used to devise game design and monetisation strategies based on data-driven decisions. Behavioural analytics are also used for predictive data analysis to forecast player needs, retention and churn rates. Companies like Gosu Data Lab analyse game data through AI insights to enhance player skill levels.
Next-Level Analytics
With more than 2 billion gamers across the world, more than 50TB of data is generated every day. The market leaders in the industry have to host 2.5 billion unique gaming sessions in a month, which can amount to 50 billion minutes of gameplay. They must, and do, invest in advanced analytics and data processing tools that are built to robustly handle diverse datasets and index them efficiently.
Another problem faced by game developers is the need to handle cross-platform data. Developers need to collect, integrate and store gaming data from PCs, mobile devices, and gaming consoles. With the use of advanced AI-powered data integration tools, normalising, cleansing and indexing data has become more efficient and safer.
Addressing real-time issues and threats has been a constant challenge for game developers. Modern games are expected to personalise the gaming experience. The recommendations, advertisements and in-game offers presented to the gamers must be based on their engagement patterns. AI-based behavioural analytics has been crucial in this regard. AI has helped game developers optimise their monetisation strategies through well-analysed player engagement data sets.
In games like rummy online, the detection of fraud elements is very important. Cash rummy attracts hackers and cheaters that platforms like RummyTime try their best to avoid. The use of AI has provided these gaming platforms with real-time insights and information on anomalous behaviours and patterns.
A Versatile Weapon
AI and behavioural analysis tools are revolutionising the gaming landscape with their versatile utility. AI-driven testing and debugging tools help developers detect bugs, identify errors, and find fixes almost instantly. These tools conduct player sentiment analysis based on their feedback, responses and behaviours.
Player Experience Modelling (PEM) is another upcoming service AI tools deliver. It mathematically models a player’s experience and predicts their probable liking or disliking of a game. PEM can accordingly modulate the game’s mechanism in real time and make it more adaptive for an individual.
Companies like NVIDIA are using AI to upscale the graphics and frame rates in games. Gamers playing games like Cyberpunk 2077 may have noticed that they can alter a scene while the game retains a high-resolution graphic display and improved frame rates.
If there is an area waiting to be addressed in gaming, chances are that it can now be done with AI tools and analytics.
Increasing Prominence
Cloud gaming, AR and VR, blockchain and NFTs are some of the many areas of gaming that AI has enhanced. AI has extended beyond problem-solving and has grown to deliver the next level of gaming experience. But its importance in analytics and off-game problem-solving remains as vital as ever.
