Time is Honey

In the early 2000s, Sunil Nakrani felt stuck. Back then, websites crashed all the time. When Sunil noticed this, he decided he was going to fix the internet. But after nearly a year of studying the architecture of the web, he was no closer to an answer. In desperation, Sunil sent out a raft of cold emails to engineering professors. He hoped someone, anyone, could help him figure this out. Eventually, he learned that the internet could only be fixed if he paid attention to the humble honeybee. This is the story of the Honeybee Algorithm: How tech used honeybees to build the internet as we know it. Special thanks to John Bartholdi, John Vande Vate, Sammy Ramsey, James Marshall, Steve Strogatz, Duc Pham, and Heiko Hamann. We found out about this story thanks to our friends at AAAS, who run the one and only Golden Goose Awards. The award goes to government funded science that sounds trivial or bizarre, but goes on to change the world. The Honeybee Algorithm won a Golden Goose Award back in 2016 (https://www.goldengooseaward.org/01awardees/honey-bee-algorithm). Thank you to our friends there: Erin Heath, Gwendolyn Bogard, Valeria Sabate, Joanne Padron Carney, and Meredith Asbury. EPISODE CREDITS: Reported by - Latif Nasserwith help from - Maria Paz GutiérrezProduced by - Maria Paz Gutiérrez, Annie McEwen and Pat Waltersand Edited by - Pat Walters EPISODE CITATIONS: Videos - Golden Goose Award video about 2016 winners (https://zpr.io/eXwTJKGL6F8S) Books - The Wisdom of the Hive: The Social Physiology of Honeybee Colonies (https://www.hup.harvard.edu/books/9780674953765) by Thomas D. Seeley (1995, Harvard University Press) Piping Hot Bees & Boisterous Buzz-Runners: 20 Mysteries of Honey Bee Behavior Solved (https://zpr.io/tNDqkw372Rhr) by Thomas D. Seeley And, Paths of Pollen (https://zpr.io/cqRPpAdGRwMi) by Stephen Humphrey. One of our former transcribers who we recently learned had hidden talents far beyond the invaluable work they did for us. This book is only tangentially related to the content in the episode, but super cool in its own right. Sign up for our newsletter!! It includes short essays, recommendations, and details about other ways to interact with the show. Signup (https://radiolab.org/newsletter)! Radiolab is supported by listeners like you. Support Radiolab by becoming a member of The Lab (https://members.radiolab.org/) today. Follow our show on Instagram, Twitter and Facebook @radiolab, and share your thoughts with us by emailing [email protected]. Leadership support for Radiolab’s science programming is provided by the Simons Foundation and the John Templeton Foundation. Foundational support for Radiolab was provided by the Alfred P. Sloan Foundation.

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  Wait, you're listening.

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  Okay.

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  Alright.

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  Okay.

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  Alright.

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  You're listening to Radiolab.

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  Radiolab.

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  From...

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  WNYC.

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  See?

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  Yep.

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  Lulu? Hello? Hey, should we start? Let's do it. Okay. Alright, so today, we're gonna start with a guy, a very sweet, very tall guy, named Sunil Nakrani.

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  Yeah, hi, I'm Sunil Nakrani.

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  Where did you grow up? And were you just a computer kid? Like, you just love computers?

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  No.

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  Or how did that, how did this all start?

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  So you wanna start from there?

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  Yeah, I mean, a little bit.

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  Yeah, so, I was actually born in Kenya.

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  But he grew up between India and the UK.

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  Right.

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  He studies hard.

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  Bachelor's and a master's degree in electrical engineering.

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  And in 1989, he lands a job at IBM.

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  Just as the world is encountering this new thing called the internet.

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  Welcome. And what about this internet thing? Do you, do you know anything about that? There's loads of useful information in here. You can get news, recipes.

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  So, Sunil is like...

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  Okay, why not go and study communication engineering?

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  He goes to Oxford to get his PhD, and one day, near the beginning of the semester, while he is on one of the desktop computers in the computer lab, his whole department, including him, gets an email from one of his professors, who's an American guy. And the email just says...

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  "Hey guys, America is under attack. Come down to the common room and then watch, right?"

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  It came out of the clear blue sky on a mild fall morning in Manhattan.

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  Oh, it's 2001. Yes, 2001. Sunil's standing there, in horror.

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  Smoke appeared everywhere, as though a mist had suddenly settled.

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  And, I mean, he has a million questions. Like, who did this? Why? Is America at war? So, he goes online.

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  To get any sort of new information.

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  But he just... Can't.

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  A lot of the websites were just not responding.

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  Some websites had just crashed, others would like just keep loading, but then never fully load.

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  There's one point, there, you know, it was such overwhelming demand for, you know, news, that they resorted to serving only text.

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  Plain text.

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  Because there were so many people trying to get to those websites.

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  Because there was just so many people trying to get access.

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  So much hunger of people trying to figure out like, what the hell is going on here?

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  Correct.

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  And he's like, why is it that at the very moment when I in the world want to access something the most, that's when I can't access it?

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  And this used to happen all the time. As millions of people flooded the system.

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  Last week, a picture of a dress was posted on Tumblr.

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  Some website. Healthcare.gov. Or picture.

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  That broke the internet.

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  Or video. Suddenly become popular.

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  Within just 15 minutes, a Pokemon Go launch.

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  And you get this crash of people.

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  Traffic had already passed initial predictions.

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  This flash flood.

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  And it breaks the internet. And this situation.

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  A demand that is beyond what they planned for.

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  Sunil became kind of obsessed with it.

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  And so I ended up looking at websites, how they architect some of these infrastructures.

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  And he's like, there's gotta be a way to fix this.

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  Yeah, like, what can I apply to solve that problem?

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  Meanwhile, Sunil's wife is working in Atlanta.

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  We were doing back and forth between Oxford and Atlanta.

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  And at a certain point, he's having kind of a hard time with this internet problem.

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  Because how do you design a system for the future when you don't know what the future is?

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  And one day, he just thinks to himself, Georgia Tech is down the street. Maybe someone there could help me.

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  Point me to some direction that I could take.

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  So he just emails some people in the engineering school.

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  I said, oh, I'm a PhD student, looking to, you know, discuss some ideas. Can I come and see you? And that was basically it. I didn't describe the problem in my email. I didn't really expect anything, anything substantial, but.

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  Within 30 minutes, he gets a response from a guy named Craig Tovey.

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  Saying, come by my office. And then a very tall guy knocks on my door. And it says, oh, you know, I'm looking for Craig.

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  This, of course, is Craig Tovey.

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  Hi, good to meet you.

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  Craig's a systems engineer.

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  Operations research.

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  His job is to make huge operations run smoothly. Factories, shipping routes, that kind of thing.

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  So anyway, I. Walked into his office, we sat down, we started talking, I started describing the problem.

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  So Sunil is like, "Look, I'm trying to fix the internet. I'm trying to stop it from breaking every time one of these internet flash floods happen."

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  He didn't say a lot, actually, at the beginning. He just kept listening. And then 25, 30 minutes later, you know, suddenly Craig Tohvi said, "Oh, oh, oh, wait."

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  Craig stands up.

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  And then went back to his desk and pulled out a paper.

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  And he plops it down in front of Sunil. It is called "The Pattern and Effectiveness of Forager Allocation Among Flower Patches by Honeybee Colonies."

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  So at the time, I thought, "Oh, why are we talking about honeybees?"

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  Yeah, why are we talking about honeybees?

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  Well, Craig had this hunch that bees had something to teach Sunil, and all of us, really. Because it turns out bees are sort of a model of how to thrive in an uncertain world.

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  Hmm, okay.

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  So that's the story I want to talk about today. The story of how a multi-billion dollar tech industry used a trick they learned for millions of years of honeybee evolution to build the internet as we know it.

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  Okay, giddy up.

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  Okay, so Craig and his bee study, it really began with his collaborator.

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  I'd like you to refer to me as Tom.

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  Dr. Tom Sealy.

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  You could introduce me as doctor or professor, but let's quickly switch to Tom.

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  He's a retired professor of neurobiology at Cornell and one of the world's top experts on honeybees.

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  I did pretty much pioneer the study of how honeybees live in the wild on their own.

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  And he started doing that work more than 60 years ago, when he was a kid.

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  Yep, a swarm of bees moved into a large black walnut not far from my parents' house.

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  And Tom says he would watch those bees flying in and out of this knothole in the tree.

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  Like shooting stars, zooming off in all directions.

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  And he'd see them and he'd be like, "Where are they, where are they going?" Like, he kind of knew where they were going.

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  There were fields of a dairy farm up on the hillside.

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  With lots of flowers, full of nectar and pollen for them to eat.

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  And they're probably going up to that.

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  Like, I know where they're going, but how do they know where they're going? Like, what, what is going on here?

• 6:43Speaker 10

  Um, are they, they're not, are they, aren't they just like flying? And if they see some pollen or nectar, they, they bring it home?

• 6:52Speaker 01

  No, no, it's way, way harder and more complicated than that.

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  Why? How so?

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  There's many different reasons, and this is all stuff Tom would eventually learn in college and grad school. Okay, so like first, flower patches are not evenly or clearly distributed. They're not just everywhere.

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  Okay, fair.

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  They're also not all blooming at the same time.

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  Okay.

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  So there might be flowers that are blooming at certain times of the year or even certain times of the day. Also, you need to find the flowers in bloom that still have nectar.

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  Hmm.

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  Because you're, you're in competition with all these other pollinators.

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  Right.

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  And you have to do all your food gathering before winter comes. Cause you know, then all the flowers go away.

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  Huh.

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  And, and you have to get something like, for, guess how many flowers? If you're a bee, guess how many flowers you have to hit to get like a little bottle of honey that you would find in a grocery store?

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  Oh, oh, okay. Like one of those bear little squeezy bottles?

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  Yeah, one of those little bear squeezy bottles.

• 7:55Speaker 10

  How many flowers went into that? That's such a nice question. Uh, I don't know, like 10,000?

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  2 million.

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  2 million?

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  2 million. And the hive needs like the equivalent of 200 squeezy bottles of honey to survive through the winter.

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  Wow.

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  All of this is an efficiency game. Like you only have so much time when the sun is shining, when these flowers are blooming that you can, you can hit them.

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  Okay.

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  Okay, so they, they have to do all of this. It's really hard. And they have, like, nobody, they have no boss. Nobody is in charge.

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  Queen bee isn't in charge?

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  So that's the thing. So, so back in Aristotle's time, that was the idea.

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  For many, you know, centuries, people thought the queen was a ruler, but no, that's not correct.

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  The queen's whole job is to make babies.

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  Yeah.

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  She's not telling anybody else what to do.

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  Nobody is.

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  The colony is intelligent in some way that the individual bees are not.

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  And when Craig found out about this.

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  It started with NPR.

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  From a radio story.

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  Tom Seeley talking about honeybees.

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  He was just like. What?

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  I was just in awe.

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  Because at the time, Craig was working on robots. He was trying to get a group of them to build a car.

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  It was an unsolved problem.

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  And he was kind of stumped.

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  I've no idea how to get these robots to work together to be as a group, like, more intelligent than the individual stupid robots. But here were these honeybees.

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  Doing exactly that.

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  And I'm thinking, wow, let's understand how the bees are doing that. Now we can copy that and apply it to robots.

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  And Craig thought this would be pretty straightforward.

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  I thought that biologists had figured out everything.

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  But turns out, they hadn't.

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  That's right.

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  If somebody asked me how much we know about how a honeybee colony works, I'd say 50%.

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  And, you know, 50% is not nothing. They knew, for example, about the waggle dance, which you might have heard of.

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  Yes, I've heard that bees will waggle. And what is the waggle, though?

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  I mean, it's quite sophisticated. It's a dance that bees do to sort of show other bees where they just came from.

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  Oh, so it's like a choreographed map? It's like a map dance?

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  It's like a map dance. And this is like a piece of the puzzle.

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  Oh, yeah. Von Frisch won the Nobel Prize. But what the biologists had not figured out.

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  Is the bigger picture. What Tom would call.

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  The wisdom of the hive.

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  And that is what Tom was working on when Craig called him.

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  And Tom said, well, you know, come help me run these experiments.

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  And the two of them would end up doing an experiment together that would give us a little peek into that wisdom of the hive and would eventually become the paper that many years later Craig would slap down in front of Sunil in his office.

• 10:56Speaker 11

  It's still vivid in my memory. I mean, in fact, this is one of the best weeks of my life. It's July 1991. Okay, now, this is in the Adirondacks, upstate New York. Like, way upstate. Close to the Canadian border. Craig had to drive on these dark, back roads. For an hour and a half, two hours. Looking for a little sign for this research station. Cranberry Biological Station. Cranberry Biological Station, okay. Cranberry Lake, I'm sorry, Cranberry Lake. Cranberry Lake. Yeah.

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  I'm always amazed that he pulled it off, that he found this biological station up in the middle of the woods, deep at night.

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  And the reason Tom studies bees at this place, way out in the middle of nowhere, is because... There are no naturally occurring honeybee colonies.

• 11:42Speaker 10

  What? Wait, why would you study bees in a place where there are no bees?

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  Right, cuz the absence of bees lets you set up, kind of, controlled experiments without any other bees messing it up.

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  That's right.

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  It's a BYOB, Bring Your Own Bee, setup. So, Tom brought an experiment, you know, a little colony of about 4,000 bees. Okay. And, you know, after breakfast, we go out to where the hive is that Tom has set up. A wooden box. Two feet high. Kind of like a beekeeper would have, but with one big difference. The front is all glass. Basically, a transparent hive. Yeah. So, you can watch the bees inside. And each bee had to be individually recognizable. How do you do that? So, you put a little two-digit number on their thorax and a little dab of paint on their abdomen.

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  Until they're painted, they're anonymous members of a colony. But, once they're painted, you get to know them. Some are nervous nellies, others come right in.

• 12:45Speaker 11

  Really?

• 12:45Speaker 09

  Yeah.

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  They have little personalities?

• 12:47Speaker 09

  Oh, definitely, definitely. Some get up in the morning and get things going, others hang out till 11 o'clock.

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  Anyway, when the sun comes out on that first morning, a big wave of painted bees whooshes out.

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  Except for those slackers who are sleeping in.

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  Fine, except for the lazy ones who sleep again. But pretty quickly, the ones who have gone to work, they start flying out to these feeders, these fake flower patches that Tom has put out for them.

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  Imagine a glass Petri dish where we have high-sugar content water.

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  It's a little buffet for them.

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  Yeah, that's right.

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  And so the way the experiment works is that there are two fake flower patches. But they're not equal. One is better than the other. And what they want to see is like, how do the bees suss that out? And how do they make it kind of a collective decision to send more bees to one rather than the other?

• 13:44Speaker 10

  Whoa, okay. Oh, so this is it. This is where you see maybe it's not just random. Like, they might get to glimpse hive intelligence.

• 13:54Speaker 01

  Yeah, because remember, this is the whole thing, right? Like, winter's coming, they're on a clock. And let's see how they prioritize how they make that decision.

• 14:02Speaker 10

  Huh. Wait, and then how do they make one fake flower patch better than the other?

• 14:08Speaker 01

  Well, there's lots of ways.

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  You know, we can put 1.5 molar sugar.

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  One feeder might have sweeter sugar water than the other.

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  We can change it from 1.5 to 2 and see how the behavior of the bees changes.

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  Or one might be bigger and one smaller.

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  If you had a lot of bees coming to the same feeder, some of them would have to wait.

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  But Craig says, for the purposes of explaining this, just imagine this situation.

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  One feeder, which is close.

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  About five minutes from the hive. And another one that's.

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  10 minutes to fly out to the flower patch, fill up her stomach with nectar and fly back.

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  A little further away.

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  Okay.

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  So.

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  Tom is at the hive, recording each bee as it leaves the hive and each bee as it comes back.

• 14:49Speaker 01

  Also, are you afraid? Have you ever? I mean, probably not. But like, have you ever been stung by a bee? Are you afraid of bees at all?

• 14:56Speaker 11

  I am somewhat allergic to bees.

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  Oh, I did not know that.

• 15:01Speaker 11

  But, so I am scared of them. But ordinarily, honeybees are not all that aggressive.

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  Anyway, right away, the guys notice.

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  There are a lot of bees going to this five-minute feeder.

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  The feeder close to the hive is blowing up. And when they follow those bees back to the hive.

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  To my eyes, it just looks like chaos. But if you're Tom Sealy, you'll spot. The waggle dance. A waggle dance.

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  The bee effectively saying.

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  Hey, go that way.

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  And pretty soon, they see another bee from that close by feeder come in and dance.

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  Hey, go that way.

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  And another.

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  Hey, go that way.

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  And another.

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  Hey, go that way.

• 15:38Speaker 01

  And each time those bees dance, they're bringing more bees back to the five-minute patch.

• 15:43Speaker 00

  Hey, go that way. Hey, go that way, go that way, that way.

• 15:47Speaker 01

  And as all that's happening, every now and then.

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  Hey, go this way.

• 15:51Speaker 01

  A bee comes in and dances for the 10-minute patch.

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  Hey, go this way.

• 15:57Speaker 11

  But.

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  Go that way, go that way, hey, go that way.

• 16:01Speaker 11

  There will be more bees going to that five-minute patch.

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  And there will be fewer bees going to the 10-minute patch.

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  Hey, go this way.

• 16:10Speaker 11

  Just because the bees coming back twice as often.

• 16:14Speaker 00

  Hey, go this way. Hey, go that way.

• 16:20Speaker 04

  Oh, okay, so the closer flower patch gets more bees saying, go that way, that way, that way. And so more bees go that way instead of this way.

• 16:30Speaker 01

  Right.

• 16:31Speaker 11

  So now here comes one of the beautiful parts of it.

• 16:33Speaker 01

  And this is where it gets really interesting.

• 16:35Speaker 11

  If there are a lot of bees going to this five-minute patch.

• 16:40Speaker 01

  Eventually, Craig says.

• 16:41Speaker 11

  There will be more and more depleted flowers.

• 16:44Speaker 01

  This patch, it starts to run out of nectar.

• 16:46Speaker 00

  Hey, go that way, go that way, go that way.

• 16:48Speaker 11

  That means that a honeybee, she's gonna take longer to fill her stomach.

• 16:54Speaker 01

  Right.

• 16:54Speaker 11

  So a five-minute patch, if it's crowded. Is no longer a five-minute patch.

• 17:00Speaker 01

  Right.

• 17:01Speaker 11

  It might become a seven-minute patch.

• 17:03Speaker 01

  And as the patch gets more and more picked over.

• 17:06Speaker 11

  Eight-minute patch.

• 17:07Speaker 01

  Hey, go that way. And then...

• 17:08Speaker 11

  A 10-minute patch.

• 17:09Speaker 01

  And... Hey! At that point... Go this way. It's taking the bees the same amount of time... Go that way. ...to go to the close-by patch as it is to go to the one that's further away. Go this way. And because of the dancing, the hive is sort of evening out the number of bees it's sending to each patch. Go that way. Go this way.

• 17:27Speaker 11

  Go that way.

• 17:28Speaker 01

  Go this way.

• 17:29Speaker 11

  Then you're in equilibrium.

• 17:35Speaker 11

  Even though the bees don't have stopwatches, they equalize the round-trip time.

• 17:41Speaker 01

  The hive has taken into account distance and crowdedness and figured out the way to get the most nectar in the least amount of time. And in the real world...

• 17:54Speaker 11

  The bees may very well be going to five different patches.

• 17:57Speaker 01

  Or a dozen.

• 17:58Speaker 11

  Not just two.

• 17:59Speaker 01

  And dealing with actual nature, which means taking into account different types of flowers and weather and predators. But no matter how many other variables the bees have to deal with...

• 18:11Speaker 11

  The allocation...

• 18:13Speaker 01

  Of bees...

• 18:13Speaker 11

  Amongst the flower patches...

• 18:15Speaker 01

  Is astonishingly efficient.

• 18:19Speaker 01

  It... It looks like there's an air-traffic controller or like the hive is thinking.

• 18:28Speaker 09

  Yeah, that's... That's right. I think, though, when we use the words like "thinking," we're thinking in human terms. But if you say "thinking," it's just a matter of taking in information, processing it to make decisions. Then I think that definition of thinking applies.

• 18:42Speaker 01

  And the way that they were processing this incredibly complex set of information was by following one simple rule.

• 18:54Speaker 11

  If one flower patch has a smaller round-trip time than the others...

• 18:57Speaker 01

  Send more bees there. Like whichever patch bees are coming back most quickly from... Go that way. That's where you send more bees. And that's it.

• 19:11Speaker 11

  It's gorgeous, isn't it? A friend of mine once said it's very zen.

• 19:20Speaker 01

  But it's also weirdly, it's a very bottom line. Like, it's like, I don't care where you're going. I don't care what you're... Like, it's like, what really matters is when you show up with the goods. Like, show up with the goods and then we'll talk.

• 19:37Speaker 11

  And then we'll negotiate.

• 19:39Speaker 01

  So this system Craig and Tom observed at Cranberry Lake, Craig wrote it up as math. He called it-

• 19:45Speaker 11

  The honeybee algorithm.

• 19:46Speaker 01

  What does it look like on paper?

• 19:50Speaker 11

  Equations I wouldn't want to show a fourth grader. F sub n of x sub n, F sub n of x sub n divided by x sub n is equal to F sub m.

• 20:02Speaker 01

  And when Craig tried to use this algorithm on his car building robot problem-

• 20:07Speaker 11

  It didn't apply.

• 20:08Speaker 01

  It was completely unhelpful.

• 20:10Speaker 11

  It was such a different problem.

• 20:12Speaker 01

  Which is why it was so exciting to him when Sunil walked into his office more than a decade later with this other problem, the internet problem, which, to Craig, anyway, looked basically the same as the one the bees were facing.

• 20:27Speaker 11

  And so after 15 minutes, I said to Sunil, "Let's imitate the bees."

• 20:36Speaker 01

  How could imitating the bees help Sunil stop the internet from breaking?

• 20:40Speaker 04

  I am desperate to finally understand this, but first we need to take a quick break.

• 20:45Speaker 01

  All right, we'll be right back.

• 20:51Speaker 04

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• 21:16Speaker 12

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• 21:34Speaker 13

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• 22:18Speaker 13

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• 22:23Speaker 14

  This week on The New Yorker Radio Hour, will House Democrats try once again for impeachment?

• 22:28Speaker 15

  Let's not make a fetish out of impeachment. Let's not make a taboo out of impeachment. We understand it's not a panacea, but it is an essential tool in the constitutional toolbox that's always there.

• 22:39Speaker 14

  Congressman Jamie Raskin joins us next time on The New Yorker Radio Hour from WNYC. Listen wherever you get your podcasts.

• 22:56Speaker 10

  Boo doo doo doo doo doo. Ha. Lulu?

• 22:59Speaker 01

  Latif.

• 23:00Speaker 10

  Radio Lab?

• 23:01Speaker 01

  Back with...

• 23:01Speaker 10

  Beez.

• 23:04Speaker 01

  Yeah.

• 23:04Speaker 10

  Um, and you were going to tell us how they're like in our internet or something?

• 23:09Speaker 01

  Yeah, basically, pretty much. But to do that, I needed an example. So I found something in my own life, which I apologize in advance for how annoying this is gonna be.

• 23:20Speaker 10

  Okay.

• 23:21Speaker 01

  Do you remember the hamster dance?

• 23:24Speaker 04

  Uh, no, I don't think I do. Is this like a website?

• 23:28Speaker 01

  Yeah, yeah, yeah, yeah, yeah. Okay.

• 23:29Speaker 04

  Okay.

• 23:30Speaker 01

  I'm kind of surprised you don't remember it. It was a very early web kind of thing. It was, but all it was, it was just a song with a webpage and the webpage was just a bunch of gifs of cartoon hamsters dancing. It's the most annoying song that you will ever-

• 23:43Speaker 04

  Can you still sing it?

• 23:44Speaker 01

  I can. Would you like to hear it?

• 23:45Speaker 04

  Yes, please.

• 23:46Speaker 01

  It was, um, dee da dee da dee da doo doo, dee da dee dee dee. Dee de de de de de de. Anyway, something like that.

• 23:57Speaker 01

  It's very, very annoying.

• 23:59Speaker 04

  Okay.

• 24:00Speaker 01

  And I remember when I was like in high school, I thought it was so funny. And one day I tried to show it to my cousin, because I was like, oh, this is so funny. You have to see this. And I remember it like taking a really long time to load. And I was like, oh, because there's so many people who are-

• 24:14Speaker 04

  Who need to get their eyes on this.

• 24:16Speaker 01

  Right. And so what was happening behind the scenes was, well, okay, so like basic internet 101.

• 24:21Speaker 04

  Yeah.

• 24:21Speaker 01

  Every website on the internet, uh, like for example, what was at the time, hamsterdance.com, exists geographically somewhere.

• 24:31Speaker 04

  Like in, in the cloud or?

• 24:34Speaker 01

  No, no, like a single earthbound computer. The owner of the website paid for it to live there. And that computer, which is called a server, is not in a house or an office. It is in a special building dedicated to servers, the server farm, right? Or a data center.

• 24:55Speaker 04

  Okay, so it's at a data center in like Ohio?

• 24:57Speaker 01

  Yeah, wherever it is.

• 24:58Speaker 04

  Okay.

• 24:58Speaker 01

  These server farms are all over the world and connected together, they more or less make up the internet.

• 25:03Speaker 04

  Oh.

• 25:04Speaker 01

  And so-

• 25:04Speaker 03

  When you, when the request comes in, um-

• 25:06Speaker 01

  When, you know, young me types in hamsterdance.com and presses enter, that server-

• 25:13Speaker 03

  The actual infrastructure that's holding it.

• 25:15Speaker 01

  Who is just sitting around in Utah or whatever on the server farm, gets a little notification.

• 25:20Speaker 16

  Oh, someone wants to see that hamsterdance.com website. All right, not too busy with anything else.

• 25:28Speaker 01

  So it does a little computation.

• 25:30Speaker 16

  Go ahead and get that for you.

• 25:31Speaker 03

  Some execution of some Java code or something.

• 25:33Speaker 16

  Let me see here. I think it's around here somewhere.

• 25:36Speaker 03

  And then push that content back to you via internet.

• 25:38Speaker 16

  Here you go.

• 25:40Speaker 01

  Where it pops up on my family's desktop computer back in 1999. And then, dee de de de, and enjoy it.

• 25:48Speaker 01

  Then the server just goes back to hanging out on the server farm. But then.

• 25:53Speaker 17

  Oh, another person wants to see that website. All right, let me just go ahead and get that for you. There you go.

• 26:00Speaker 17

  All right, where was I? Man, I just love this country. Oh. Oh.

• 26:07Speaker 17

  Oh, no.

• 26:11Speaker 01

  And as it starts to go viral.

• 26:12Speaker 03

  A number of people are all bombarding with requests.

• 26:15Speaker 01

  Till that one server is like, oh, my God.

• 26:18Speaker 17

  Would somebody help?

• 26:20Speaker 01

  Can no longer serve up this website in a timely manner.

• 26:23Speaker 03

  And so now people have to wait in a queue, right?

• 26:25Speaker 01

  And this would happen all the time because back then the way servers were allocated was like, you'd get how many servers you paid for.

• 26:32Speaker 03

  Right.

• 26:33Speaker 01

  Like the owner of the Hamster Dance website probably would have been like, hey, I'll just pay for the one server.

• 26:38Speaker 03

  Because I don't expect my website to experience a lot of demand.

• 26:40Speaker 01

  And how wrong they were.

• 26:43Speaker 03

  Right.

• 26:43Speaker 01

  Do you remember what that was like, though?

• 26:45Speaker 04

  Yes, I do. The like slow loading and the like, ah.

• 26:49Speaker 03

  If something took longer than five seconds, generally the human psychology was that people give up on the website.

• 26:54Speaker 01

  So as Sunil saw, the problem was relatively simple. There are a bunch of servers.

• 26:59Speaker 03

  And sometimes they can be not very busy.

• 27:01Speaker 01

  Sometimes they're just sitting around doing nothing, but other times.

• 27:04Speaker 03

  They could be overly busy.

• 27:06Speaker 01

  And so how, in a system that is changing so quickly, do you get those servers who are doing nothing to help those servers who are doing too much?

• 27:14Speaker 03

  Start moving these servers around where they needed.

• 27:17Speaker 01

  And this is the problem that Sunil brought to Craig.

• 27:20Speaker 03

  Yeah, hi, I'm Sunil.

• 27:21Speaker 11

  And I mean, heck, within 20 seconds, I saw that the problem was similar to the honeybee problem.

• 27:28Speaker 04

  Like immediately, like that fast?

• 27:30Speaker 01

  Yeah, because to Craig, it was like he'd been holding on to this rusty old key that he was holding for more than a decade. And Sunil showed up with something that looked like it might be the exactly matching lock.

• 27:43Speaker 11

  Yeah.

• 27:43Speaker 03

  Yeah. Evolution has solved this problem in some way, right? And now you're saying, OK, can it do it in the artificial domain? And so.

• 27:52Speaker 01

  They got to work.

• 27:53Speaker 03

  Right. F sub N of X sub N.

• 27:55Speaker 01

  Dusted off that old math equation.

• 27:57Speaker 03

  Mapping the two structure of the, you know, what the bees are doing.

• 28:00Speaker 01

  And sitting there, they started to connect all of these dots like.

• 28:04Speaker 03

  Collection of bees make up the Beehive. Collection of servers make up the Internet server farm. Yes, exactly.

• 28:09Speaker 01

  And wait, so that would mean, oh, my God, the stuff on the Internet are.

• 28:14Speaker 03

  Flower patches.

• 28:14Speaker 01

  Oh, bingo.

• 28:15Speaker 03

  At that point, things got really exciting.

• 28:17Speaker 10

  Wait, I'm sorry, just please stop that.

• 28:20Speaker 01

  Sorry.

• 28:21Speaker 10

  How is what the bees are doing anything like what the server's doing? Like, lay out the parallel.

• 28:28Speaker 01

  OK, um, why don't we, OK, let's, why don't we cranberry lake this thing? OK, so instead of a meadow filled with wildflowers.

• 28:38Speaker 10

  Yeah.

• 28:38Speaker 01

  OK, picture the entire Internet.

• 28:42Speaker 10

  Got it.

• 28:42Speaker 01

  Um, it's the beginning of the day. You're just signing on your computer. And the first thing you decide to do on there.

• 28:52Speaker 01

  Is watch a video of a baby biting his older brother's finger, naturally, right?

• 28:57Speaker 10

  Yes, OK, how I love to start my day.

• 29:00Speaker 01

  My procrastinating, of course. Um, OK, so you watching this video is like a flower opening in the meadow, right? The meadow of the Internet.

• 29:10Speaker 10

  Why is me watching analogous to a flower opening?

• 29:14Speaker 01

  You watching is like the flower filling up with nectar. It's your desire, which they can capitalize on, basically.

• 29:20Speaker 10

  Oh, me watching is money for, it's, oh, oh.

• 29:24Speaker 01

  It's money.

• 29:24Speaker 10

  My eyes on the video.

• 29:26Speaker 01

  Your eyeballs and your attention, that's like the server company's nectar.

• 29:30Speaker 10

  Oh, OK, I get it. I get it. We are the flowers.

• 29:33Speaker 01

  Yeah, and as more and more people watch and then share this video with their friends who watch it too, and share it with their friends who watch it too, that's like more and more flowers opening in the flower patch. And the server hosting that video is like a single bee being like. Holy mother. Bonanza of Nectar over here. I'm gonna need some backup.

• 29:56Speaker 10

  Oh, so now it has to recruit more bees, AKA more servers.

• 30:01Speaker 01

  Yeah, so it does like a computer version of a waggle dance. This server to server digital nudge. Okay, let's call it a ping. That means, hey, I need some help. Come get some of this stuff.

• 30:13Speaker 10

  Okay.

• 30:13Speaker 01

  And so servers buzz over to the Charlie Bitme video and start servicing all of these flowers, right? Helping all these people to watch this video. And then it kinda keeps going, right? The video popularity grows. Flowers keep opening. More bees needed, more servers needed. And very quickly, all these servers are just servicing the Charlie Bitme video.

• 30:33Speaker 10

  Okay.

• 30:33Speaker 01

  But then, wait a second. Now there's a ping, but it's not for the Charlie Bitme video.

• 30:42Speaker 01

  Now, everybody wants to see pictures of this huge boat on the BBC website.

• 30:49Speaker 01

  That just got stuck in the Suez Canal.

• 30:50Speaker 10

  I remember that. I was a flower.

• 30:53Speaker 01

  Right, right. So like you, all these flowers opening up all over the world. All of a sudden, the servers that are serving up these boat pictures, now they're the ones who are saying, hey, we need backup. And again, there is this server to server, peer to peer, B to B waggle dance recruitment ping calling out to the idle servers to come help. And those servers come, and they ping out. And those servers, who are no longer needed with the Charlie Bitme thing, are now like, oh, man, I gotta go help with this Suez Canal thing.

• 31:23Speaker 10

  Okay, got it. But then, in the, in the actual internet, this is happening times like a gazillion, right? All the time. Literally billions of people, billions of flowers. So could this algorithm, this little fix, like actually work?

• 31:41Speaker 01

  Well, that, they had to figure that out.

• 31:44Speaker 03

  You know, initially, excitement kind of sets in, but then, then you, you go to prove what you, what, what you thought would be a good solution, right?

• 31:52Speaker 01

  And to test this idea, Sunil and Craig decided to compare it to another algorithm they invented.

• 31:58Speaker 03

  That algorithm, we named it omniscient, where if it could see the future. What would it do?

• 32:04Speaker 01

  Like, if you knew ahead of time everything that everybody would want to see on the internet, how would you organize your servers to meet that demand? It's basically god mode.

• 32:14Speaker 03

  This is the best you can do. You can't do better than that.

• 32:16Speaker 01

  So they compared this perfect model to the way humans had been allocating servers already.

• 32:21Speaker 04

  Like the guessing?

• 32:22Speaker 01

  Right. And they compared it as well to the bees' algorithm version. And what they found was that the bees...

• 32:30Speaker 03

  Even without knowing the future, they were coming within like 20, 15% of the optimal behavior.

• 32:36Speaker 01

  Wow. In a bunch of their tests, the human algorithms didn't even come close.

• 32:41Speaker 04

  Whoa.

• 32:42Speaker 03

  Yeah, turns out that...

• 32:43Speaker 01

  At least theoretically.

• 32:44Speaker 03

  It worked really well.

• 32:46Speaker 01

  So based off these results, they publish a little paper, and then Sunil goes back to Oxford to defend his thesis.

• 32:51Speaker 03

  I presented the results to the committee.

• 32:54Speaker 01

  He tells them about the problem he's seen with the internet and how the bees could help solve it, talking for like...

• 32:59Speaker 03

  Forty-five minutes to an hour.

• 33:00Speaker 01

  And when he's finally done, the first question that he gets is...

• 33:05Speaker 03

  Have you patented this idea or not?

• 33:10Speaker 04

  Oh, wow. That's a good question to get.

• 33:13Speaker 01

  But he was like, well, I just published it.

• 33:16Speaker 03

  You can't patent your own thing if you published.

• 33:19Speaker 04

  Oh, no.

• 33:21Speaker 01

  And so he did not patent it.

• 33:23Speaker 04

  Oh, he gave it away.

• 33:24Speaker 01

  He gave it away for free to everybody. And over the following months and years, server farms all over the world worked this bee algorithm into the internet.

• 33:33Speaker 04

  Wow.

• 33:34Speaker 03

  You know, the honeybee algorithm made it 10, 20% more efficient.

• 33:38Speaker 01

  Which means we have the bees to thank for the internet being this place where...

• 33:43Speaker 06

  US climber Alex Hunnold stunned crowds in his cage.

• 33:46Speaker 01

  You can get whatever you want.

• 33:48Speaker 06

  Video from outside the Capitol shows the beginning of the storm.

• 33:51Speaker 01

  Right now.

• 33:53Speaker 11

  The hurricane pushed Lake Pontchartrain deep.

• 33:59Speaker 04

  I mean, that is just a moment for nature that that could outperform so many thousands of human brains working on solving all kinds of problems. And just like, evolution had figured this out through its own longer timeline of trial and error.

• 34:20Speaker 01

  Yeah. And not only that, this honeybee algorithm, or variations of it, have been lifted into so many other industries. I have found people researching how to use it to forecast exchange rates, design electric cars, detect defects in wood before using that wood for construction, even for sharpening MRI images to better detect breast cancer tumors.

• 34:43Speaker 04

  Bless that, little bumblebee. I mean, I guess what's so... I think about humans, one of our gifts and our curses is that we can jump to the future, or the past. We can jump out of the present, but we can worry. And that's like, entire industries, prediction, forecasting, whether it's weather, or money, or whatever. But we spend time worrying about the future, but it feels like what this, the elegance, it's like, not only to me is it beautiful that it came from bees, because I'm a nature lover, and I love it when nature outsmarts us, or has more elegance in its design, but

• 35:24Speaker 04

  it's also like, one of the insights, if you wipe away all the technicalities, is like, it's throwing away the future. It's not basing its decision of where to move based on a guess about the future. It is only responding to the present.

• 35:43Speaker 01

  Hmm. Right, right. It's kind of at this very subtle, like, it's like, right at the line between responding to the clues of the moment and predicting the future.

• 36:00Speaker 04

  It's on the edge of the present?

• 36:03Speaker 01

  It's at the edge of the present. And it's like, all we gotta do is like, pay attention to what's happening now, and then, and like, build it into these feedback loops so that we can, yeah, so that we can address just the next moment, like, just the next moment, and just the next moment after that, and just the next moment after that, and just the next moment after that.

• 36:20Speaker 04

  I mean, that's, if anything, that might be a thing I like.

• 36:25Speaker 04

  Take a round with me.

• 36:53Speaker 01

  This episode was reported by me, Latif Nasr, with reporting help from Maria Paz Gutierrez. Production by Maria Paz Gutierrez, Annie McEwen and Pat Walters. Edited by Pat Walters and facts checked by Diane Kelly.

• 37:07Speaker 10

  We also got a lot of help for this episode from Radiolab and Terrestrials resident bug correspondent, Sammy Ramsey, and we couldn't have done this one without his help. Big thank you to you, Sammy. And if you want to hear more about bees and hear Sammy talking about them, we have a Terrestrials episode called "The Crystal Ball." Honeybees who predict the future. You can go listen to him over there.

• 37:28Speaker 01

  Other major thank yous to John Bartholdy, John Vandevate and James Marshall. As well, we want to thank the folks at AAAS who administer the one and only Golden Goose Award. If you remember, the award goes to government-funded science that sounds kind of silly or bizarre, but then goes on to change the world. This research won a Golden Goose Award back in 2016, which is how I first heard about it. So, thank you to all our friends there. Erin Heath, Gwendolyn Bogard, Valeria Sabate, Joanne Padron Carney and Meredith Asbury.

• 37:59Speaker 10

  And bees. We barely scratched the surface of how amazing they are. If you want to learn more, read any of Tom Seeley's books. His most recent one is the incredibly titled memoir, "Piping Hot Bees and Boystrous Buzzrunners."

• 38:14Speaker 01

  I think that should be it. But if you are still here, let me leave you with this bit of tape that has been haunting me.

• 38:24Speaker 01

  To Neil, like dude, over the last 20 years, I have used the internet a lot. If, if the internet today took the same amount of time as the internet in the 90s, like, like you, I can easily imagine.

• 38:42Speaker 01

  Not just minutes, like, I mean, hours, full days of my life, like, you know, a second at a time that this could have saved.

• 38:53Speaker 03

  You're right, but also what most internet service company wants is stickability for you to keep using the service, right?

• 39:00Speaker 01

  Okay, so you're saying the opposite. You have made the internet so enjoyable that you have cost me days and hours, potentially even years of my life, so I should be mad at you.

• 39:11Speaker 03

  Yeah.

• 39:17Speaker 01

  And that's it.

• 39:20Speaker 01

  See you next week.

• 39:23Speaker 02

  Hi, I'm Gabby. I'm from San Francisco, and here are the staff credits. Radiolab is hosted by Lulu Miller and Latif Nasser. Soren Wheeler is our executive editor. Sarah Sandback is our executive director. Our managing editor is Pat Walters. Dylan Keefe is our director of sound design. Our staff includes Jeremy Blum, W. Harry Fortuna, David Gable, Maria Paz Gutierrez, Sindhu Nainasambandan, Matt Keelty, Mona McGawker, Annie McEwen, Alex Neeson, Sarah Kari, Rebecca Rand, Anissa Vitza, Arianne Whack, Molly Webster, and Jessica Young, with help from Gabby Santas. Our fact checkers are Diane Kelly, Emily Krieger,

• 40:05Speaker 02

  Natalie Middleton, Angeli Mercato, and Sophie Semai.

• 40:12Speaker 02

  Leadership support for Radiolab's science programming is provided by the Simons Foundation and the John Templeton Foundation. Foundational support for Radiolab was provided by the Alfred P. Sloan Foundation.