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Previously on artificial intelligence and its importance to eSports, we highlighted some aspects including competition management, player development all the way to improved coaching methods. We found out that players can improve on their skills with AI-based training tools, as well as provide coaches feedback to improve on their performances, and help detect any form of malicious activity.
Today we will like to highlight some aspects in which artificial intelligence is helping to improve eSports; technologies and machine learning programs associated as eSports continues to be on the rise:
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Personalization
AI can help in eSports with their overall user experience through the use of personalization. Its definition in the field is to tailor content to suit players’ needs and interests, to which they will be able to get what they want from the gaming experience. GOSU.ai is one of such programs to help with giving players a real-time AI personalized experience, playing its role as a voice assistant for gamers to have conversations in-game, adapting to their habits and abilities displayed in-game.
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Predictive Analysis
eSports organizations through AI-powered technology can analyze player performance, predicting whether a player may win or lose a match. Data gathered using these tools can also be used to determine if players will stay with teams or leave soon. Gemmo.ai is one of such tools to help with analysis of this kind as it also does that for aspects such as automatic clips and event detection. This analysis helps organizations to know who to keep in the teams rather than playing guess games.
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Data Analysis
With analysis appearing twice in the text, one may ask how this is the case. Well the points showing as two different things should be the first to notice. Also data analysis in eSports centers more data gathered from competitions, players and their respective teams. Because this comes in large amounts, there is the need to have tools to be able to help players and teams find insights and improve on their performance. Through the use of AI tools such as SenpAI which provides in-depth history of players, this can be used as a guidance to improve one’s game.
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Automation
eSports through the use of AI-powered automation can help customers enjoy a flawless experience using such platforms. The signing up for an account, winning, losing, and the activities during in-game. Fans get to be provided social media content just as they enjoy live streaming services with automation through the use of tools like Open AI Five, which has been seen in action in Valve’s Dota 2.
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Data Mining
To be able to identify strategies such that work for certain situations in games, you can use data mining tools to help you out with that. Data mining is used to gain insights by finding hidden patterns and applying those patterns in new situations; predicting the turnout of events due to similar instances witnessed earlier. Some data mining tools that can be of assistance include MonkeyLearn, Knime and RapidMiner.
Quite the number of aspects covered huh? And yet there is more to be explored because gaming will continue to experience changes through updates and other modifications that will make the gaming experience more realistic than ever.
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Written by Jeffrey Osei-Agyeman
