Learn about why the US once launched millions of copper needles into space; why bikes don’t fall down when you ride them; and 3 ways big data can predict what you really like to watch or listen to. In this podcast, Cody Gough and Ashley Hamer discuss the following stories from Curiosity.com to help you get smarter and learn something new in just a few minutes: The US Once Launched Millions of Copper Needles Into Space — https://curiosity.im/2tIFdWW 3 Ways Big Data Predicts What You Really Like to Watch and Listen To — https://curiosity.im/2tF1dBZ Additional resources discussed: How do bikes balance when we ride them? — https://scienceline.org/2007/11/ask-ashford-balancingbikes/ How does a bike stay upright? Surprisingly, it’s all in the mind | The Conversation — https://theconversation.com/how-does-a-bike-stay-upright-surprisingly-its-all-in-the-mind-59829 If you love our show and you're interested in hearing full-length interviews, then please consider supporting us on Patreon. You'll get exclusive episodes and access to our archives as soon as you become a Patron! https://www.patreon.com/curiositydotcom Download the FREE 5-star Curiosity app for Android and iOS at https://curiosity.im/podcast-app. And Amazon smart speaker users: you can listen to our podcast as part of your Amazon Alexa Flash Briefing — just click “enable” here: https://curiosity.im/podcast-flash-briefing.
Learn about why the US once launched millions of copper needles into space; why bikes don’t fall down when you ride them; and 3 ways big data can predict what you really like to watch or listen to.
In this podcast, Cody Gough and Ashley Hamer discuss the following stories from Curiosity.com to help you get smarter and learn something new in just a few minutes:
Additional resources discussed:
If you love our show and you're interested in hearing full-length interviews, then please consider supporting us on Patreon. You'll get exclusive episodes and access to our archives as soon as you become a Patron! https://www.patreon.com/curiositydotcom
Download the FREE 5-star Curiosity app for Android and iOS at https://curiosity.im/podcast-app. And Amazon smart speaker users: you can listen to our podcast as part of your Amazon Alexa Flash Briefing — just click “enable” here: https://curiosity.im/podcast-flash-briefing.
Find episode transcript here: https://curiosity-daily-4e53644e.simplecast.com/episodes/bike-balancing-how-big-data-knows-what-you-like-and-millions-of-copper-needles-in-space
[MUSIC PLAYING] CODY GOUGH: Hi. We're here from curiositydotcom to help you get smarter in just a few minutes. I'm Cody Gough.
ASHLEY HAMER: And I'm Ashley Hamer. Today, you'll learn about why the US once launched millions of copper needles into space and three ways big data can predict what you really like to watch or listen to. We'll also answer a listener question about why bikes don't fall down when you ride them.
CODY GOUGH: Let's satisfy some curiosity. Hey, remember that time the US launched millions of copper needles into space?
ASHLEY HAMER: No, because I was not alive.
CODY GOUGH: Me neither. But it's a thing that happened and this is not a conspiracy theory. For a couple of months in 1963, the Earth had something in common with the planet Saturn, a ring. Now, again, I'm not kidding. It was all in the name of technology. Here's the story. In the 1950s, people were able to communicate long distance like never before.
You could get a message across the ocean or to the other side of the continent in a matter of minutes. But that was thanks to giant undersea cables and over-the-horizon radio that bounced the signal off the ionosphere. And during the Cold War, those cables could be disrupted by enemy agents and long distance radio signals could be disrupted by both terrestrial and solar storms.
That's why the US decided to try a new method of long range communication. An Earth-sized ring of copper to conduct transmissions fast as lightning no matter what the weather was like. It was supposed to work like this. A rocket would dump hundreds of millions of tiny copper fillings into low Earth orbit. And that would give the radio signals something else to bounce off of besides the ionosphere.
And it worked sort of. Within days of the mission, communications were being sent from California to the East Coast at a then staggering speed of 20 kilobytes per second. The mission was a rousing success for about four months. But that copper ring was a little less effective once those needles started to fall out of orbit or worse, clump together. And that's where the real trouble started.
When you're going around the planet at 5 miles or 8 kilometers per second, the tiniest piece of debris can have a really big impact. Even if they're only a centimeter across, bits of space junk can severely damage and even destroy advanced modern spacecraft. The copper filaments were only about a quarter of the width of a human hair. But the funny thing about metal in a vacuum is that it will instantly weld to any identical metal with no heat required.
That means that all those tiny copper wires that didn't crash land at the North and South poles back in the day have the potential to fuse with each other to become major obstacles. In 2001, a study suggested that the several dozen clumps still in orbit were likely to stay right there for decades to come. So the next time Elon Musk sends a roadster into orbit, he should keep an eye out for any errant shards of copper on the way. All that in the name of science.
ASHLEY HAMER: I mean, their heart was in the right place.
CODY GOUGH: Well fire that under, it seemed like a good idea at the time.
ASHLEY HAMER: Yes. We got a listener question from Shashank in India who wants to know why bicycles fall down when no one's riding them but remain balanced while they're moving. Great question, Shashank. I've got a simple answer and a complicated answer. The simple answer is that when a wheel is in motion, it turns into a gyroscope-- that's a wheel that's been so fast that it's difficult to change its orientation. That forward spinning of the wheel creates a force in the direction of its spin.
If you had a bike with no rider and you were able to push it fast enough, it would probably stay upright from gyroscopic forces alone, at least, for a little while. But here's the complicated answer. Scientists have realized that once you're on the bike, the weight of your body on the seat and the force of your hands on the handlebars pretty much cancels out any gyroscopic forces from the wheels.
I mean, that makes sense, right? If bike stayed upright on gyroscopic forces alone, we wouldn't crash so much while learning how to ride a bike. Instead, riders learn to make small adjustments to their balance to stay upright. You can see this in a brand new rider. They're all wobbly and they make wide turns right and left to keep from toppling over.
Experienced riders are still wobbling. But because they've learned exactly what it takes to stay upright, those wobbles are so tiny that they're almost imperceptible. In fact, humans are so good at riding bikes that scientists have tried over and over to make a bicycle that's totally unreadable. It's almost impossible. Once you know how to ride a bike, riding any bike is like, well, riding a bike. Thanks for your question, Shashank, and for your really nice email. If you have a question, send it in to podcast@curiosity.com.
CODY GOUGH: You're probably vaguely aware that algorithms and big data can figure out what you like to watch and listen to. But what does that mean? Today, we want to demystify exactly how that works. As reported by the conversation, there are three major ways big data predicts what you enjoy was seeing and hearing. And the reason why, sometimes, algorithms can predict your behavior better than you can, is because of a thing economists call hyperbolic discounting.
That, basically, says that what people say they'll do in their free time is usually not what they actually do. Like, when you say you'll stay at home and get some work done but you end up playing video games instead, guilty as charged.
ASHLEY HAMER: Cody.
CODY GOUGH: I know. Shocking. So back to three major forces helping algorithms predict human behavior. The first thing is what's called the long tail. If you work in marketing, then you've, probably, heard of this. It, basically, says that there's a small number of products that are super popular but lots of other products that sell in small quantities. Think about smartphones. Tons of people have an iPhone. But there are literally hundreds of phones out there and they all have a market. They're just a lot smaller.
Similarly, a network TV station might greenlight a show they think will be really popular with a massive audience, but a company like Netflix will pick up a show with a more niche audience. House of Cards was actually rejected by TV networks but Netflix data at the time when they picked up the show, showed that they had a fan base for people who liked Director David Fincher and Actor Kevin Spacey. So they picked it up.
The internet is what makes it possible to find long tail products. From obscure items on Amazon to niche TV shows on streaming services. The second big data trick is social influence. Companies can mine data from sites like Facebook and Twitter to track what people say about a movie show, song, whatever in real time. And they can adjust their marketing appropriately.
One study showed that just by paying attention to social media buzz, a movie studio can predict how much money a film will make with 31% more accuracy than when they don't. And finally, consumption analytics feed that big data machine. This is big with books. You know how you can highlight passages from a book on your Kindle or e-reader?
Well, if most of the highlights in a book come later in that book, then people are reading more of the book. And that helps companies like Amazon figure out which books to recommend to potential readers. I mean, if all the highlights in that book are from the first 10 pages, then well, not that many people are making it past page 10. And it wouldn't be surprising if Pandora and Spotify did this with how much of a song you listen to. So there you go. Welcome to the future. It knows you better than yourself.
ASHLEY HAMER: Creepy.
CODY GOUGH: Hey, before we go, I've got some news. Have you ever heard an episode of Curiosity Daily and tried to find it later and not been able to? Always--
ASHLEY HAMER: Yes. Yes, I have, Cody.
[LAUGHTER]
CODY GOUGH: Well have I got some good news for you? We have a brand new website, at curiositydaily.com where you can search our entire archive for any episode that you're trying to find. We built curiositydaily.com to help people find our show more easily. So it would be a huge help if you could link to it in any social media posts you make in the near future or send them out in a newsletter, or put it on your website.
Anywhere you can put a link to curiositydaily.com, that'll help people see it. And again, you can find any of our episodes there. There's a search bar on the side of the website that you can use and put in any term and whether you're looking for productivity tips or stories on quantum physics or conspiracy theories, whatever it is, you can find it there. Every episode has its own page.
ASHLEY HAMER: Oh, I'm so excited.
CODY GOUGH: Yeah. curiositydaily.com. Thanks. Before we wrap up, we want to give a special shout out to two extra special contributors for their generous support on Patreon. Thank you so much to this episode's executive producers-- Dr. Mary Yancey and [INAUDIBLE] We could not have made this show without you.
ASHLEY HAMER: If you're listening and you want to support Curiosity Daily, then visit patreon.com/curiositydotcom, all spelled out. We're producing special podcast episodes and offering other exclusive perks to show our appreciation for your support. One more time, you can learn more at patreon.com/curiositydotcom.
CODY GOUGH: Join us again tomorrow with the award-winning Curiosity Daily and learn something new in just a few minutes. I'm Cody Gough.
ASHLEY HAMER: And I'm Ashley Hamer. Stay curious.
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SPEAKER: Speaking on the Westwood One Podcast Network.