Importance

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Abstract

Embodiments include technologies that use machine learning to control mobile machines as well as to adjust settings of mobile machines in real time (e.g., agricultural machine settings, construction machine settings, forestry machine settings, or landscaping machine settings). Some embodiments include a method that includes using a mobile machine to perform work in a field using first machine settings and recording performance information. The performance information indicating a performance of the mobile machine while performing the work in the field. Also, the method includes using a computing system to input the performance information into a trained deep learning model and to receive new machine settings information from the trained model, and using the computing system to control the machine according to the new settings information.

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First Claim