Only day two of the Heidelberg Laureate Forum and the term machine learning or “ML” has been popping up throughout talks and in conversations with young researchers and the laureates. Machine learning uses statistical techniques to give computers the ability to learn without them having to be explicitly programmed. The goal is for a program to learn by itself without any human intervention.

In a discussion with Jeffrey A. Dean, the winner of ACM’s 2012 Prize in Computing and the current head of Google’s AI Division, he repeatedly mentioned and stressed the importance of machine learning. Google AI currently has an open source machine learning platform called TensorFlow which Dean said is “used for training computing vision models” as well as a ML Kit beta which brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.

Dean emphasized the importance that every student should understand and be exposed to machine learning, probably because he had been surrounded by 200 students at HLF for two days at that point, but none-the-less, his point was clear. “All students should take a machine learning class, since it is clear that ML is going to impact many fields.” When asked what role he sees for academic research in Artificial Intelligence (AI), Dean repeated the importance of ML. “We need to educate the next generation of students, we need more ML experts so we can continue to move forward in AI.”

So next semester when you are signing up for classes, or advising students on which classes to take, think about adding a ML class. The writing is on the wall that it will probably pay off in the end.