When it comes to AI and Machine Learning there are 3 major types of Machine Learning that is being adopted and adapted to various parts of the Entertainment industry (and all industries really). These 3 methods of Machine Learning include Supervised Learning, Unsupervised Learning, and Reinforced Learning.
With Supervised Learning, there is a “teacher” that provides example inputs and what the output should be based on the inputs. The AI is being taught very specifically with input to output mappings. With Unsupervised learning there are not labels applied to the inputs, the AI has to find it’s own structure and this can end up discovering hidden patterns not noticed with supervised learning but also lead to a lot of mismappings and irrelevant data as well. Unsupervised learning is the best way for the AI to explore out of box scenario’s, mappings and really explore a wider array of results or outcomes. Reinforced Learning is when there is a dynamic environment with a specified goal, but there is no clear supervision on whether the AI produced the desired outcome or reached the goal. When it comes to training AI for playing games, reinforced learning is typically the method used.
Whether it is movie entertainment, video games, or some of the best online casino websites – they all are adopting AI and Machine Learning as quickly as possible to take advantage of key features that can help keep visitors coming back, create more customized reward programs and keep them informed and optimize the best types of offerings that bring in the most engagement all while maximizing revenue. Imagine yourself, based on your gaming routine you suddenly get a free bonus only because you surpassed the average monthly expenses. Sounds great, isn’t it? Also, these include using AI and Machine Learning for Voice Recognition which can help better train responses from Voice activated Smart TV’s, Alexa, Smart Phones…etc. Also, interactive online games such as video poker or simply speaking on what you want to watch, play or doing voice activated commands are all examples here. Another area of benefit in nearly every industry of AI and Machine learning is Flaw Detection, such as online games that use reward systems and making sure there isn’t mistakes in the payout rates, or percentages or algorithms that determine rewards. Also, it surely increases the security level if there’s such a thing as voice recognition.
AI and Machine Learning is used to see how people consume content and better predict and offer up similar types of content or ads that match the user’s interest as well. Netflix uses AI, same as Siri and Alexa to show users what to watch next based on viewing patterns, online casino’s may detect patterns in a user’s play style to know they may be quitting soon by seeing slow downs, lowering balances and offer an incentive or reward to revitalize interest and trigger a reaction to keep them playing and engaging longer…etc.
AI will continue to adapt and be used for the sole purpose of collecting information for further engagement, after all the more you can get users to consume your services the more revenue it ends up being even if passive revenue like from watching ads between play or watch segments.