Machine learning and AI Applications Make Machines Smarter

AI are investing in virtual training programs to help machines to become more intelligent and efficient. A new machine learning technique is using to help robots sharpen their cutting skills.

The new program uses a computer vision and ML algorithm to test cutting models to better determine how effective the skills are. Cutting is often considered an automatic function of machine learning. Without testing the skills, it would be impossible to know if a machine can turn a leaf or cut through a tree trunk. Using machine learning, computers can predict how the tasks will turn out, and then make sure they are accurate.

Many human designers believe that cutting is the most complicated assignment a robot can perform; therefore, they imagine one, but not many, approaches to designing cutting algorithms. This program is at the forefront of AI innovation by providing a toolbox with algorithms that give assistance in increasing precision, and in turn reducing error, in cutting tasks.

A prototype of the cutting simulator is currently built to help test out how well robots can imitate the more intricate tasks like picking up single branches. As more research methods are developed, they will then be used to test out more complicated tasks like drilling through concrete and removing deep needles. The program is being applied to a range of hand tools, such as saws, drills, generators, saws, wood-turning knives, car washers, and furniture saws. As robots become more skilled, many industries will try to bring them into the workplace to automate labor.

Article credit: Writing by James Dana/Visit Boston/Getty