Abstract: A text prediction system for providing personalized text suggestions for different customers is disclosed. For a text message being composed via an application for an intended recipient, the system receives a portion of the text message based upon a current cursor position in the text message. The system identifies a customer associated with the intended recipient and identifies a customer-specific model for the customer. The system predicts text to be suggested for type-ahead insertion at the current cursor position using the customer-specific model and based upon the portion of the text message. The suggested text may include one or more data variables that are replaceable with values determined from data stored for the customer. The data variables provide further customization to the suggested text by presenting suggestions are more personalized for the recipient of the text message. The system causes the suggested text to be output via the application.

Abstract: Techniques for suggesting a candidate layout based on historical characteristics are disclosed. A system trains a machine learning model to suggest layouts for three-dimensional spaces. The system obtains sets of historical characteristic data, including spatial characteristics of a particular three-dimensional space and layout characteristics including information indicating items present in the particular three-dimensional space and positioning information indicating a position of each item within the particular three-dimensional space. The system trains the machine learning model based on the sets of historical characteristic data. The system receives a first request for a layout suggestion from a first user, including at least a first set of spatial characteristics for a first three-dimensional space.