Podcast: Prof. Nick Feamster Explains Machine Learning for Telcos

Machine learning is primed to help service providers run more efficient and effective networks, but first the good ideas have to make their way from the lab to the real world – and that's a big challenge, according to the University of Chicago's Nick Feamster.

Phil Harvey, Editor-in-Chief

August 13, 2019

2 Min Read
Podcast: Prof. Nick Feamster Explains Machine Learning for Telcos

Data science 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 world, 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.

On this episode, Feamster discusses the everyday tasks service providers can use with machine learning to help broadband subscribers solve their technical issues and avoid calling customer service. With hundreds of encrypted video streams traversing their networks, carriers can't be on the hook for how each application performs, but they can build a model that generalizes across several different services and helps troubleshoot problems before they become customer complaints and a drag on the business.

He also hints at some advanced services -- like how activity recognition could be tied back to a health or security monitoring service. Bridging the gap between having the information and using it is the challenge, Feamster said. As you'll hear on the podcast, measuring networks and gathering data are the first steps, but finding out what data is most important -- and telling the service provider or the customer to take action -- is the key to unlocking new services.

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Phil Harvey, US Bureau Chief, Light Reading

About the Author(s)

Phil Harvey

Editor-in-Chief, Light Reading

Phil Harvey has been a Light Reading writer and editor for more than 18 years combined. He began his second tour as the site's chief editor in April 2020.

His interest in speed and scale means he often covers optical networking and the foundational technologies powering the modern Internet.

Harvey covered networking, Internet infrastructure and dot-com mania in the late 90s for Silicon Valley magazines like UPSIDE and Red Herring before joining Light Reading (for the first time) in late 2000.

After moving to the Republic of Texas, Harvey spent eight years as a contributing tech writer for D CEO magazine, producing columns about tech advances in everything from supercomputing to cellphone recycling.

Harvey is an avid photographer and camera collector – if you accept that compulsive shopping and "collecting" are the same.

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