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Amazon Personalize extends limits to support more users and longer histories of interactions

We are excited to announce that Amazon Personalize has extended limits to support datasets with up to 100 million users and 3 billion interactions. Amazon Personalize enables developers to improve customer engagement through personalized product and content recommendations – no ML expertise required. Amazon Personalize trains custom models for each customer using their unique data. Previously, these models could consider up to 50 million users in training. By doubling this limit, Amazon Personalize improves model performance for large customers by allowing them to train on a more diverse set of data. For customers with larger user bases that may exceed this limit, Amazon Personalize samples an optimal set of users before training. Previously, models trained by Amazon Personalize would also consider a maximum of 500 million of the latest interactions between users and items. Customers now have the option to increase their training time to consider up to 3 billion interactions. This can improve model performance by capturing more historical data for customers with a large user base or a high velocity of interactions. To increase the number of interactions considered by your model, simply request a service quota increase via the Service Quota console.

Source:: Amazon AWS