Abstract: A method of streamlined selection and application of a makeup look involving personalized makeup look recommendations with respective step-by-step makeup routine instructions for executing a selected makeup look. A predictive model identifies one or more makeup look recommendations from a database of makeup looks to present to a user. Recommendations are generated from a combination of user demographic data, user-input preferences, social networking analytics (e.g., frequently used makeup looks among users such as “trending” makeup looks), and user behavioral history data obtained from a smart device application and a smart cosmetic device system. Each respective makeup look can be executed from a respective detailed tutorial guide comprising step-by-step instructions on how to apply cosmetic substances to achieve the respective makeup look.

Abstract: A system for the recommendation of a makeup look to a user in response to data corresponding to a smart cosmetic device, wherein the recommended makeup look is presented to a user for application using the smart cosmetic device. The smart cosmetic device collects user behavioral history such as cosmetic substance usage (e.g., color and formula of a particular cosmetic substance), design configuration (e.g., spray canister, pen, and so on), and usage pattern (e.g., frequency of use for a particular cosmetic substance at a particular time of the day, a particular day of the week, or a particular event). Data associated with user behavioral history is processed by the system to generate at least one user-personalized makeup look recommendation for presentation to the user.

Abstract: A system for the processing of one or more makeup look recommendations for the recommendation of a respective output makeup look recommendation, wherein the respective output makeup look recommendation is renderable in a particular rendering environment (e.g., physical world, augmented reality world, or a metaverse virtual reality world). The system allows for iterative generation of makeup look recommendations within a single rendering environment (e.g., generating new physical world makeup look recommendations from previously user-selected physical world makeup look recommendations) or interreality feedback loop generation of makeup look recommendations within a plurality of rendering environments (e.g., generating a new physical world makeup look recommendation from previously user-selected augmented reality makeup look recommendations.

Abstract: Technology is described for synchronization of data between a robotic device and a cloud storage service. The method can include identifying data from a robotic device to be synchronized to the cloud storage service. A synchronization request and the data can then be sent to a robotic synchronization service on the robotic device, and the data can be stored on the robotic device's storage system. A further operation can be sending the data to cloud synchronization service. The data can be stored on the cloud storage service.