Simply put, we (humans) can’t possibly process all of the data in the world, which is why computers are so useful — and why algorithms have become so necessary.

In this mini-episode, we go back to the basics. We talk to Georgia Tech computer programming lecturer Kantwon Rogers, a self-declared “eternal optimist,” who breaks down where algorithms came from and where they might be taking us. 



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Algorithms (BYTE)

Google has become our yellow pages, our atlas, our library, our medical consultant, our shopping guide. Which means it is, basically, a giant, virtual confession booth. It knows our most intimate secrets and our most mundane desires. Which has some really amazing upsides; we get a smorgasbord of answers in milliseconds. But behind the scenes of every search, there’s a bidding war going on. Whoever wins that war has the power to shape not just how we spend our money, but also, perhaps, our political views, and maybe even our will to live. We talk to Patrick Berlinquette, a search engine marketer and certified Google partner, about how our searches are, literally, for sale, and get some perspective on the world of digital advertising from NYU’s Vasant Dhar.



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The Answer Machine

What exactly is memory? And why is it so important to how our devices work today? Friend of the show and Georgia Tech computing lecturer Kantwon Rogers breaks it down into bits and bytes — and hints at what kinds of clouds the future may bring.

BONUS: Andrea offers up her global solution to solve the issue of tailgating.



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Memory (BYTE)

It’s 2019, and machine learning is everywhere. It might not be Skynet, but it can still sound a little scary. If the robot apocalypse isn’t around the corner, what is? We talk to Kantwon Rogers, a lecturer at Georgia Tech and frequent guest of the show, to demystify this increasingly omnipresent technology. We learn about about how the heck machine learning actually works, how it’s being used to improve our lives, and what should be keeping us awake at night when it comes to this powerful technology. (Hint: It’s not because of killer robots. Not yet...)



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Machine Learning (BYTE)

In the world of computer science, being a hacker means you know what’s up, and you have street cred. Outside of technology circles, though, hacking is more associated with things like data breaches, ransomware, and malware. So where does the term come from, and why does it have different meanings to different people? In our conversation with Meredith Broussard, a professor at New York University, we explore the roots of hacking, and what it says about society’s relationship with technology today.



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Hacking (BYTE)

Imagine a life without the Internet. No email, no Instagram, no texting, no Google maps, no Netflix...what would you do? A “normal” life would be next to impossible. But huge numbers of Americans face this very problem. Access to high-speed Internet is still an enormous challenge for a lot of people. We talk with Nicol Turner Lee, a fellow at the Brookings Institution, about what it means to be “digitally invisible,” and the toll lack of access takes. It’s a complicated problem, and one with no easy answers. And, for some context, we take a trip through time to see how America tackled a similarly dire issue at the height of the Great Depression.



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The Digital Divide

When humans predict something, it’s basically an educated guess, based on our experiences. When a machine makes a prediction, it uses data and math. And we are increasingly relying on machine prediction to help make decisions in everything from banking to insurance to education. But Meredith Broussard, a professor from New York University, argues that this has all gone too far, especially when you look at what data are being used in machine predictions. And that the “futures” that machines predict should be taken with large grains of salt.



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Prediction (BYTE)

Originally broadcast in April 2019. As we approach the end of 2019, the Financial Times recognizes Shoshana Zuboff's "The Age of Surveillance Capitalism" as one of the best business books of the year.

Shoshana Zuboff doesn’t mince words when it comes to the data economy. According to Zuboff, author of the recent book *The Age of Surveillance Capitalism, *our very souls are at stake. But the seeds of surveillance capitalism were planted rather innocently, back in the heady days of the dotcom bubble. As Zuboff tells it, it all began with Google. When the young company entered crisis mode, they needed to find new ways to make money. And a whole new economic logic was born — one that has now spread across every sector of the economy, and has invaded every facet of our online lives. Zuboff warns that surveillance capitalism threatens much more than just our privacy.



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About Us, But Not For Us (Repost)

A podcast about how information becomes power. Hosted by Mike Osborne and Andrea Mustain.

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