Data science, machine learning and artificial intelligence may help service providers speed up service provisioning, provide better network performance and more comprehensive security. But none of that matters if the models used in research labs don't work in the real work, according to researcher Nick Feamster. Feamster is just starting his new gig as director of the Center for Data and Computing (CDAC) at the University of Chicago. He was previously a professor in the Computer Science Department at Princeton University. One of his jobs now is to find out what kinds of machine learning and data science can be applied in real networks today, at scale. In this podcast, Feamster speaks with Light Reading's Phil Harvey and Kelsey Ziser about his upcoming work with CDAC, his observations on how machine learning can help telcos now and where we, as consumers, might see a difference when networks become more intelligent.

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