Abstract: Certain aspects of the present disclosure provide techniques for generating a recommendation of task codes for a user of a task management application. A machine learning model is trained on historical data, which includes task code histories of users and corresponding location data of computing devices the user is accessing. The trained model generates a set of predicted task codes and a respective probability indicating the likelihood a user will select the task code. A subset of task codes are identified, for example, that meet or exceed a probability threshold value. The subset of task codes are included in a recommendation displayed in the application to the user. The selection of a task code by a user not only is included in that user's task code history but is also indicative of feedback for the trained model for further training.

Abstract: Methods and systems for automatically grilling meats and other food items comprise a movable grate and a plurality of burners that are controlled by a PLC-based control system. The control system automatically controls the speed of the movable grate and the temperature of the burners to automatically grill the meets and other food items. Additional components and equipment are provided that simulate the actions and steps that an operator must perform to produce grilled meats in the style of traditional grilling in a continuous manner over prolonged time periods with no interruption. Automation of processes such as seasoning, grilling, turning over and cutting meats, and grate cleaning are also provided. The above arrangement provides a number of environmentally friendly benefits, including lower fuel use, less contamination, and greater energy savings.