B2B Marketers: Meet the Amazon Professor of Machine Learning

 In B2B Marketing, Data Science

“The main thing that has caused companies to fail, in my view, is that they missed the future,” – Larry Page, co-founder Google

Earlier this month, Brandon Butler of Network World interviewed Carlos Guestrin, Amazon Professor of Machine Learning at the University of Washington. The conversation made it clear that machine learning and predictive technologies are more applied sciences than theoretical studies.

What is machine intelligence?

According to Guestrin, “Tom Mitchell, a machine-learning expert at Carnegie Mellon, characterizes it as the ability of a system to improve its performance of a task based on experience and data.” The spam filter on your email is a good example of that. Look into your spam folder today, and you’ll find hundreds of emails blocked. That’s because they look like emails you’ve marked as spam in the past, exhibit language patterns indicative of spam, or are from an email address that is not in your address book. It’s not any one of these attributes that trigger the spam filter to route an email out of your inbox, but a combination of all of them, to reduce the instances of false positives.

What is the business case?

For industry leaders, machine learning is a chance to personalize services to individual customers, whether they are consumers streaming movies or enterprise organizations investing in IT. Think about the recommendations for restaurants or movies you might like.  “Making your customers feel like individuals,” says Guestrin, is now an inherent part of your customers’ expectations and “a huge differentiator [that] machine learning helps [to] automate.”

 What’s next?

If you think machine learning is a fad, you don’t understand where technology is headed. Companies like Netflix, Amazon and Google have cemented dominance in their respective industries through personalization and recommendations, powered by machine learning. These companies, says Guestrin, “use a tremendous amount of data about individuals to inform these decisions and integrate that with data they have about all their other customers…We’re on the cusp of many other industries becoming personalized. Take healthcare: Why should the treatment I get be the same as the one you get if we have different lifestyles and genetics? Personalized medicine could really change how we provide care, and machine learning could fuel it.”

Ready or not, machine learning is fundamentally changing the way we work and live. It’s just a matter of time before everyone realizes it.

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