Some professors have had 20+ years to digest an enormous amount of information. Keep in mind they have 2 major advantages over people in industry when learning

Some professors have had 20+ years to digest an enormous amount of information. Keep in mind they have 2 major advantages over people in industry when learning this stuff. At universities that offer PhDs, being a professor forces you to develop a strong theoretical foundation, which makes it easier to grasp the theory of related subjects. Example: If you have a deep understanding of math/statistics theory, it's much easier to understand a paper on machine learning, even if you're not a computer science professor. Professors at research oriented universities supervise PhD research students and each student tends to be a multiplier on their supervisor's knowledge since each PhD is a collection and extension of an existing research area. A good PhD student is basically a massive funnel of information. I'll also say, don't ascribe more abilities or skills to a professor than what you see in the presentation. Sometimes having a strong theoretical orientation/experience comes at the expense of a practical one. Don't assume that having a strong theoretical foundation in Stats/ML automatically makes you a good Data Scientist or ML Engineer.