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Carnegie Mellon’s AI Program Aims to Better Prepare Students for the Changing Workforce

Carnegie Mellon University is revamping the way it teaches artificial intelligence.

The university’s computer science department debuted Tuesday its CMU AI initiative intended to better prepare students for entering the workforce.

The goal is to train students to build complex software systems or powerful robots that utilize multiple different AI technologies, whether it be machine learning tech to help those systems learn from data or technology that helps robots see and perceive the world similar to humans.

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“There is a real science to building these things,” said CMU dean of computer science Andrew Moore.

While it’s common for students or faculty members to concentrate on one specific subset of AI, like machine learning, those subsets represent only one portion of a finalized product, like a robot or digital assistant like Apple’s (AAPL) Siri.

However, there hasn’t been a standardized way to develop these complex projects that require multiple AI technologies to function together. Similar to how building a skyscraper requires people with expertise in diverse fields like structural engineering and concrete mixing, building powerful software like Siri or robots requires people with expertise in many different areas of AI.

“We have done a good job of covering all the component parts,” Moore said of teaching different subsets of AI like machine learning and computer vision. “We need to be thinking very seriously about the science of putting it all together.”

Students who know how to piece together all the various AI components into functioning software will have better chances at landing high-caliber jobs. Moore said that when he worked at Google (GOOG)—where he was once a vice president of engineering and a director in Google’s Pittsburgh office—he learned “how rare and how desperate it was to find people who have these skill sets.”

Moore says he hopes the new AI initiative will better train students to fill the labor pipeline.