A professor from Carnegie Mellon University will hold a lecture today on the subject of machine learning.

Tom Mitchell will deliver a lecture titled “Does Machine Learning Really Work?” in 283 Coover Hall at 4 p.m. Mitchell’s lecture is part of the computer science department’s colloquium series.

The aim of the lecture is to discuss the recent progress of machine learning, look at research problems and view possible paths of future research.

Machine learning is a branch of artificial intelligence that pertains to methods and techniques for making computers learn.

New developments in research and industry over the past few years have made artificial intelligence a field with many opportunities.

New advancements have made some systems able to detect credit card fraud, enable vehicles to learn to drive autonomously on public highways at 70 mph and learn to assemble a personally customized electronic newspaper.

On a theoretical level, research has found problems that machines can and cannot solve.

Mitchell is a professor of computer science and robotics at Carnegie Mellon, and as been a Fellow at the American Association for Artificial Intelligence since 1990.

His papers have been published in many journals on the subjects of artificial intelligence, machine learning and robotics.

Mitchell also helped found Schenley Park Research Inc., a Carnegie Mellon building that specializes in the commercial applications of machine learning and data-mining.

Mitchell is currently looking into new algorithms that combine prior knowledge with observed data to improve learning accuracy and the applications of machine learning to web-based agents, robotics and data-mining.