Interactive Embodied Intelligence of Machines

This paper discusses how intelligent machines have replaced humans in tasks requiring, heavy, and repetitive labor, whilst being better suited to the requirements of these jobs. The increased capacity for brute force computation has facilitated increased collaborative innovation between man and machines. For example, the intelligent farming machines have overcome the confines of computational power, algorithms, and data, and the next generation of intelligent farming machines is expected to interact, learn, and grow autonomously. In the future, in addition to self enhancement, humans are expected to teach machines to learn and work. Scientists and engineers will collaborate with machines to accomplish invention, discovery, and creation. For “embodied intelligence” in the farming machine context, we propose (1) deep learning should be performed iteratively via real-time interactions with the external world; (2) embodied control and self-regulation can ensure coordination between behaviors of machines and their environment; (3) intelligent farming machines are characterized by the ability to interact, learn, and grow autonomously.