The Number One Educational Resource for the Game Industry
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Overview:
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Personalization is well-known to improve gamer engagement significantly. However, most developers rely on outdated, historical user data for personalization, missing out on rich insights regarding session context from real-time user-game interactions. This is largely due to a) prohibitively high cloud costs of handling and processing real-time session data on cloud and b) difficulty of deploying and maintaining real-time ML models on-device nnWe propose a novel approach to overcome these challenges, using our managed on-device ML platform. The platform executes data processing, inference as well as training on-device to deliver cost-efficient, real-time personalization at scale. This results in significant improvement in gamer experience and conversion, with minimal end-to-end latency and CPU and battery usage spike
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