BYU Engineer Creates Unsupervised Machine Learning Algorithm

Machine learning is the newest thing at BYU, thanks to the work of engineer Dah-Jye Lee, who has created an algorithm that allows computers to learn without human help. According to Lee, his algorithm differs from others in that it doesn’t specify for the computer what it should or shouldn’t look for. Instead, his program simply feeds images to the computer, letting it decide on its own what is what.

Photo courtesy of BYU Photo.
Photo courtesy of BYU Photo.

Similar to how children learn differences between objects in the world around them in an intuitive way, Lee uses object recognition to show the computer various images but doesn’t differentiate between them. Instead, the computer is tasked with doing this on its own. According to Lee:

“It’s very comparable to other object recognition algorithms for accuracy, but, we don’t need humans to be involved. You don’t have to reinvent the wheel each time. You just run it.”

Advertisements

Machine Learning Exemplified By The Never Ending Image Learner

Photo courtesy of Coursera

Meet NEIL, the Never Ending Image Learner. Its mission? To scour the Internet, 24 hours a day, seven days a week, building and strengthening its database. Its goal? To teach itself common sense.

Photo courtesy of Coursera
Photo courtesy of Coursera

Of course, computers can’t think, reason, or rationalize in quite the same way as humans, but researchers at Carnegie Mellon University are using Computer Vision and Machine Learning as ways of optimizing the capabilities of computers.

NEIL’s task isn’t so much to deal with hard data, like numbers, which is what computers have been doing since they first were created. Instead, NEIL goes a step further, translating the visual world into useful information by way of identifying colors and lighting, classifying materials, recognizing distinct objects, and more. This information then is used to make general observations, associations, and connections, much like the human mind does at an early age.

While computers aren’t capable of processing this information with an emotional response–a critical component that separates them from humans–there are countless tasks that NEIL can accomplish today or in the near future that will help transform the way we live. Think about it: how might Computer Vision and Machine Learning change the way you live, work, and interact with your environment?