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Speaker 1: If everything is quantum fields, how do their ripples make

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Speaker 1: banana peels?

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Speaker 2: What's the mutation rate for the common cold? Does the

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Speaker 2: virus change moving through my household?

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Speaker 1: Is their mass? In pure information? Do I get heavier

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Speaker 1: with more education?

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Speaker 2: Whatever questions keep you up at night, Daniel and Kelly's

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Speaker 2: answers will make it right.

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Speaker 1: Welcome to another Listener Questions episode on Daniel and Kelly's

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Speaker 1: Extraordinary Universe.

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Speaker 2: Hello. I'm Kelly Wienersmith, and I study parasites and space,

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Speaker 2: but not parasites in space.

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Speaker 3: Not yet, at least that's all right.

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Speaker 4: Hi.

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Speaker 3: I'm Daniel.

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Speaker 1: I'm a particle physicist, and I want to figure out

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Speaker 1: the problems of the universe before the aliens come and

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Speaker 1: spoil the story by telling.

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Speaker 2: Us, oh, interesting, you know. The intro sort of makes

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Speaker 2: it sound like maybe this is going to be an

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Speaker 2: episode about Bigfoot or something. We both have gotten a

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Speaker 2: little bit out there with our intros this morning, but

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Speaker 2: we're going to bring it down to Earth, which reminds

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Speaker 2: me of an interesting talk that I gave on Earth. Well,

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Speaker 2: I don't know if it's interesting. It was my talk,

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Speaker 2: the talk that I gave for Western University Space Day

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Speaker 2: recently and I was giving my usual City on Mars

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Speaker 2: talk and up in the balcony was an entire Girl

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Speaker 2: Scout troop boom.

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Speaker 1: Do you think they were looking to plan an expedition

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Speaker 1: to space?

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Speaker 2: I don't know. Girl Scouts can do anything. Many maybe

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Speaker 2: they were. Maybe they're planning on taking over the world,

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Speaker 2: but they want to know how to take over space too.

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Speaker 2: They did bring delicious cookies, so that was great.

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Speaker 3: Do they ask good questions?

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Speaker 2: That's what I was going to say. They asked the

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Speaker 2: greatest questions, so they asked fantastic questions. And I was

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Speaker 2: a little bit nervous because I hadn't planned on there

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Speaker 2: being kids. So I have a whole section about how

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Speaker 2: the process of expanding family size might be indited by

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Speaker 2: the space environment. And the first question that I got

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Speaker 2: was one of the girls from the Scouts raised her

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Speaker 2: hand and said, in your section on reproduction. And I

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Speaker 2: immediately was like, oh God, this is not a good start.

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Speaker 2: I don't want to give the birds and the bees chat.

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Speaker 2: And she said something about the image you used on

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Speaker 2: that slide had two adults in spacesuits holding two babies

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Speaker 2: in spacesuits. Wouldn't it be expensive to make spacesuits.

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Speaker 1: For babies, all right, it's an engineering question.

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Speaker 3: Yeah, And I think I.

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Speaker 2: Said something like I am so relieved that that's what

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Speaker 2: you asked, And then I explained, like, you know, sometimes

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Speaker 2: it's hard using arts to explain concepts, because we didn't

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Speaker 2: actually mean that people will probably be bringing babies in

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Speaker 2: space suits out on the surface because space radiation. You

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Speaker 2: probably wouldn't want to expose your baby to that on

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Speaker 2: the Martian surface.

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Speaker 1: And then you need like constantly new spacesuits as they grow.

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Speaker 1: I know, as a parent of children who once grew

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Speaker 1: very rapidly, that's very frustrating how quickly they outgrow all

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Speaker 1: their stuff.

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Speaker 2: Oh my gosh. Yes, but I mean eventually we will

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Speaker 2: need different shapes and sizes of space suits for the

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Speaker 2: diversity of body types that will be up there. But

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Speaker 2: my question for you is, have you ever worked with

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Speaker 2: an artist or use some art that didn't at all

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Speaker 2: portray what you had intended and you didn't realize it

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Speaker 2: would be taken seriously because you just meant it to

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Speaker 2: be like a cute, funny image about families in space,

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Speaker 2: for example.

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Speaker 1: Well, the stuff that I write about usually is pretty

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Speaker 1: family friendly, but often it's kind of abstract, and I

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Speaker 1: struggle sometimes to describe it accurately with words, and then

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Speaker 1: I wonder, like, hmmm, how is my illustrator friend going

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Speaker 1: to put this into a picture? Like what visual can

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Speaker 1: you use to describe quantum fields and tie this all together?

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Speaker 1: But I've been lucky to work with very talented illustrators

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Speaker 1: who do a great job of making these exceptional visuals,

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Speaker 1: taking the abstract and making a concrete so that the

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Speaker 1: reader can understand the concepts.

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Speaker 2: To be clear, I think my artist collaborator, slash husband

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Speaker 2: does a great job. But I think sometimes you just

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Speaker 2: assume that the audience will get that this is just

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Speaker 2: like a fun artistic image, as like a palette cleanser

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Speaker 2: for the difficult stuff we just told you. But you

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Speaker 2: know it doesn't always go over the way that you intended.

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Speaker 1: Yeah, well, there's another fine line there, which is sometimes

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Speaker 1: you want to make jokes to lighten the mood, right.

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Speaker 1: I remember in our first book, we talked about what

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Speaker 1: space can do, and I'd written this space can bend,

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Speaker 1: it can expand, it can ripple, and Jorge drew a

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Speaker 1: hilarious little doodle of space bending and expanding and rippling,

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Speaker 1: and then he added a fourth one of like space breakdancing,

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Speaker 1: and you always got to wonder like, okay, is that

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Speaker 1: ridiculous enough that people get Okay, that's obviously a joke

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Speaker 1: to lighten the mood, or somebody out there being like, well,

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Speaker 1: I don't know if space can ripple and expand maybe

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Speaker 1: it could breakdance.

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Speaker 3: What does that mean?

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Speaker 1: We are the equations of breakdancing.

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Speaker 2: Yep.

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Speaker 1: So you always gott to walk that fine line.

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Speaker 2: Zach and I have had so many of those conversations

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Speaker 2: where he's like, people are going to get it's a joke,

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Speaker 2: and I was like, maybe they won't. There are humorless

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Speaker 2: people out there who will be confused.

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Speaker 1: And sometimes the reality is so ridiculous people might think

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Speaker 1: you're making a joke. In our latest book about what

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Speaker 1: science Aliens Might do, we talk about how people tried

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Speaker 1: to communicate with aliens, and there's a guy who wrote

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Speaker 1: letters in the sand and set them on fire hoping

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Speaker 1: that Martians would read them. And that sounds like I'm

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Speaker 1: made up ridiculous example. So I remember adding a footnote

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Speaker 1: being like, I know, we make a ridiculous example sometimes

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Speaker 1: for humor. This is not one of those cases.

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Speaker 2: Yes, everyone while humans are just so crazy you need

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Speaker 2: to be like, no, this isn't a joke. I'm not

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Speaker 2: going into fiction here.

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Speaker 1: Amazing And if anybody's interested in that book, it's coming

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Speaker 1: out in November. It's called Do Aliens Speak Physics? By

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Speaker 1: it anywhere you get books, and.

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Speaker 2: I read an early copy and I can tell you

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Speaker 2: it's amazing.

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Speaker 3: And we're gonna be talking about it a lot until

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Speaker 3: it comes out.

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Speaker 2: Yep. Yeah, nice to have a platform. You know what

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Speaker 2: else is awesome?

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Speaker 3: What's that?

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Speaker 2: Our listeners, they are so awesome and they ask such

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Speaker 2: amazing questions. And we've got like a question from kids

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Speaker 2: theme going on today, and so let's start with our

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Speaker 2: first ques question from Ryan and thirteen year old Grace

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Speaker 2: from the best states in these United States.

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Speaker 1: I'm confused, they're not from California.

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Speaker 3: What are you.

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Speaker 2: Talking about, oh, Daniel.

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Speaker 1: Despite their coming from Virginia, Let's hear about Grace's question.

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Speaker 4: Hey, Daniel and Kelly. My name is Ryan and I

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Speaker 4: have my thirteen year old daughter, Grace here with me.

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Speaker 4: We live in Virginia, and she came up with an

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Speaker 4: interesting question after we discussed your episode on particles and

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Speaker 4: the current understanding that they are ripples in fields?

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Speaker 5: Hi, this is Grace, and here's my question. I don't

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Speaker 5: understand how ripples make things. For instance, how do a

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Speaker 5: bunch of ripples in a field somehow all add up

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Speaker 5: to make a person or banana or sloth? Thanks for

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Speaker 5: taking my question. We love the podcast all.

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Speaker 2: Right, Daniel, As someone who is a huge fan of sloths,

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Speaker 2: I now desperately want to understand how ripples help make

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Speaker 2: up a sloth.

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Speaker 1: I love this question because this is the whole point

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Speaker 1: of physics, to take our everyday experience and explain it

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Speaker 1: in terms of the microscopic stuff that's happening. To like

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Speaker 1: pull back the veil and say what's really going on underneath?

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Speaker 1: And it's cool to say, oh, what's going on underneath?

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Speaker 1: Is this complicated thing with fields and particles and waves

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Speaker 1: and whatever. But Grace is exactly right that the second

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Speaker 1: part of that is to weave it together so that

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Speaker 1: it does explain our everyday experience. You've got to give

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Speaker 1: a path sort of like an intellectual ladder, from the

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Speaker 1: microscopic explanation back to the macroscopic to show how they

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Speaker 1: come together. So thank you Grace for asking this question.

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Speaker 2: It's a fantastic question, and I love that both banana's

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Speaker 2: and sloughts got featured exactly because what good is physics

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Speaker 2: if it's not explaining biology.

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Speaker 1: And maybe there's a banana sloth out there, oh that

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Speaker 1: we could explain.

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Speaker 2: One day, delicious and easy to catch.

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Speaker 3: Probably why they went extinct.

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Speaker 1: So let's get to particles and ripples and quantum fields

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Speaker 1: and all that. Grace's question is how ripples make things.

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Speaker 1: So let's zoom all the way back down to ripples,

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Speaker 1: and then let's walk our way back up to the

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Speaker 1: macroscopics to the sloth in the banana. So like one

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Speaker 1: hundred years ago, we were trying to understand what stuff

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Speaker 1: is made out of. We started taking stuff apart, and

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Speaker 1: we realized it's made out of elements, and those elements

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Speaker 1: are made out of atoms, and eventually we had little

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Speaker 1: particles protons and neutrons and electrons, and back then, I

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Speaker 1: think people were still thinking that those were little bits

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Speaker 1: of stuff that you could like pack together like legos

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Speaker 1: to make bigger stuff that was the sort of microscopic

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Speaker 1: to macroscopic, Like the legos were super duper tiny, almost

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Speaker 1: incomprehensibly tiny, and there were so many of them. You know,

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Speaker 1: Avogado's number is a big number. But if you click

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Speaker 1: them all together, you made macroscopic stuff. And that was

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Speaker 1: our understanding, right.

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Speaker 2: And on the plus side, you can step on them

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Speaker 2: and it doesn't hurt.

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Speaker 3: The a particle legos.

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Speaker 1: Yes, But then we learned, oh, they're not really little

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Speaker 1: bits of stuff. Actually, they're like waves. And quantum mechanics

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Speaker 1: came around and told us that they don't have specific

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Speaker 1: locations and maybe these particles are actually tiny zero volume points.

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Speaker 1: And then quantum mechanics grew up and said, those waves

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Speaker 1: are actually even more important because the particles themselves are

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Speaker 1: just waves and quantum fields.

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Speaker 3: And so that's where.

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Speaker 1: We are now that we understand that all the matter

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Speaker 1: that's out there, the electron, the quarks inside the proton

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Speaker 1: and the neutron, all these things are actually just ripples

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Speaker 1: in quantum.

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Speaker 3: Fields, all right.

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Speaker 2: And there are a bunch of different kinds of fields.

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Speaker 2: We've talked about those before, right, And so are we

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Speaker 2: talking about a very particular kind of field that makes

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Speaker 2: up bananas and slots or are all the fields relevant?

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Speaker 1: So you're right, there are lots of different kinds of fields.

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Speaker 1: Every particle has a field. So the electron is a field,

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Speaker 1: the muon has a field, the cow has a field,

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Speaker 1: the top qrk has a field. Every different kind of

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Speaker 1: particle has a field. We don't understand why there are

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Speaker 1: so many. There're dozens of these fields. Every bit of

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Speaker 1: space that's out there has all these fields sitting on

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Speaker 1: top of each other in the same chunk of space.

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Speaker 1: It's kind of hard to wrap your mind around because

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Speaker 1: if you're thinking of like blankets, you know, blankets you

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Speaker 1: stack because they can't be in the same location. But

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Speaker 1: these fields are all in the same place, and they

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Speaker 1: can all oscillate independently. And you asked, which fields are

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Speaker 1: we talking about in this case, we're talking mostly about

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Speaker 1: the fields that make up us, which are electron fields,

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Speaker 1: and two of the cork fields, the upfield in the downfield.

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Speaker 1: So there are dozens of those fields out there, and

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Speaker 1: there's like big fundamental questions about what that means and

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Speaker 1: how do we unify them, and it can be simplified,

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Speaker 1: et cetera. But most of the matter in the universe

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Speaker 1: is made out of particles which are oscillations in three

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Speaker 1: of those fields, the electron field and then the up

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Speaker 1: and down cork fields which make the proton and the neutron.

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Speaker 1: And how do you understand like a particle being an

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Speaker 1: oscillation of a field, what does that really mean?

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Speaker 3: What are we talking about?

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Speaker 1: Well, when we say an oscillation of a field, we

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Speaker 1: really mean that it's vibrating, like the value of the

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Speaker 1: field is going up and down, and so because it's moving,

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Speaker 1: it can have kinetic energy. And as it has different values,

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Speaker 1: it can have potential energy. The way they like a

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Speaker 1: book on a shelf has a different potential energy if

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Speaker 1: it's on a high point of the shelf or a

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Speaker 1: low point on the shelf. Right, you like store energy

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Speaker 1: in a book by moving to the top of the shelf,

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Speaker 1: you release energy from the book when it falls off

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Speaker 1: the shelf. The same way these fields oscillate. They go

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Speaker 1: up and they go down, They slosh back and forth

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Speaker 1: between tential and kinetic energy, and so there's energy stored

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Speaker 1: in the field. So you should think of the particles

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Speaker 1: as like not a little dot of stuff, but instead

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Speaker 1: a little vibrating blob of energy in the field.

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Speaker 2: Oh way, already, like where this is going, I'm a

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Speaker 2: vibrating field of energy or made up of vibrating fields

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Speaker 2: of energy, and If so, why are the sloths so slow?

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Speaker 3: Exactly, they are filled with energy.

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Speaker 2: They should be all right.

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Speaker 1: So now we have these little vibrating fields of energy.

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Speaker 1: Grace's question is how do you put that together to

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Speaker 1: make a banana.

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Speaker 3: Or a sloth?

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Speaker 1: Basically, these things are super duper tiny, but they're not

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Speaker 1: like little volume cubes like legos. How do you put

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Speaker 1: them together to make something big?

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Speaker 3: Right?

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Speaker 1: Well, here's the crucial insight. You need the volume that

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Speaker 1: we experience. The reason things take up space is not

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Speaker 1: from the stuff that they make, but from their interactions

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Speaker 1: with each other. So it's not like you have two

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Speaker 1: particles and they have surfaces and those surfaces click together,

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Speaker 1: or even that they're like two tennis balls that you're

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Speaker 1: packing into a space and their surfaces are particles have

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Speaker 1: interactions with each other. They exchange energy. This energy we

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Speaker 1: were talking about slashing in the electron field or slashing

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Speaker 1: in the quarkfield. That energy can slide from one field

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Speaker 1: to another. That's when an interaction is so. For example,

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Speaker 1: an electron moving through space will also make ripples in

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Speaker 1: the electromagnetic field the photons field because those two fields interact.

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Speaker 1: There's a connection between those two fields and the ripples

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Speaker 1: in the electromagnetic field will then push or pull on

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Speaker 1: other electrons. So how do two electrons interact with each other?

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Speaker 1: Why do they repel? Because they are both making ripples

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Speaker 1: in the electromagnetic field, which has the capacity to affect

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Speaker 1: other electrons.

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Speaker 2: So I'm going to try to tie this back to biology.

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Speaker 2: So I'm thinking, you know, Christmas has ended and I'm

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Speaker 2: feeling like my body could do with fewer interactions. Is

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Speaker 2: there is there a way to think about it, like

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Speaker 2: as you go into calorie deficit, can you think about

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Speaker 2: it as like electrons sort of leaving the electric field?

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Speaker 2: Or am I just making this too complicated?

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Speaker 1: I think there's a Christmas analogy if we can do

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Speaker 1: use to understand here. Think about what happens at a

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Speaker 1: Christmas party. Right when you put people into a room

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Speaker 1: at a Christmas party, do they stack like sardines against

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Speaker 1: the wall or like physically phase on top of each

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Speaker 1: other and occupy the same space. No, they talk to

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Speaker 1: each other and they get like a comfortable distance from

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Speaker 1: each other. Right, So you're at a party, people are

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Speaker 1: sort of scattered.

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Speaker 3: Through a room.

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Speaker 1: You're all sipping your Christmas cocktails or whatever, and they're

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Speaker 1: not squeezed and touching each other. Right, there's this comfortable

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Speaker 1: distance because people are talking to each other and they

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Speaker 1: respect each other's personal space. The reason that we can

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Speaker 1: generate volume in a banana from a bunch of tiny

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Speaker 1: little particles, which are actually ripples in the fields, is

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Speaker 1: for the same reason that they have their own little

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Speaker 1: personal space. Their interactions keep them apart, and so like

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Speaker 1: inside your banana, are a bunch of little ripples that

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Speaker 1: are keeping their space between them because of their interactions.

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Speaker 1: So the volume of the material comes from the bonds

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Speaker 1: between these particles, these little ripples, not from like the

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Speaker 1: inherent volume of them, as they're stacked together on top

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Speaker 1: of each other. So let's zoom all the way in

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Speaker 1: and then out again, just to make sure it all

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Speaker 1: makes sense. We zoom as far in as we understand

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Speaker 1: the nature of the universe. We have these little ripples

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Speaker 1: and fields which are just little buzzing blobs of energy. Right,

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Speaker 1: particles are not little scoops of universe stuff. They are

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Speaker 1: little blobs of buzzing energy in the field, and the

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Speaker 1: fields interact with each other. So buzzing energy in the

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Speaker 1: electron field also means buzzing in the electromagnetic field, and

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Speaker 1: also in the Higgs field and all sorts of other fields.

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Speaker 1: Whatever the electron interacts with and interactions between those fields

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Speaker 1: keep these little buzzing blobs in harmony and in balance

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Speaker 1: and allow you to build up bigger things. So they're

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Speaker 1: not little lego bricks that you click together, but they

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Speaker 1: little buzzing blobs sort of in balance with each other,

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Speaker 1: keeping their space. And that's where the volume comes from.

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Speaker 1: So you zoom all the way out and you look

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Speaker 1: at a banana, should think of it as like a

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Speaker 1: matrix of these buzzing blobs that are all somehow in

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Speaker 1: balance with each other because of their interactions.

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Speaker 2: It doesn't sound beautiful, but you know, I study dumb

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Speaker 2: trucks full of dead fists, so who are to judge?

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Speaker 1: No, but I think that is like peeling back a

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Speaker 1: layer of reality, like seeing the matrix and like, oh,

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Speaker 1: this is what makes up the banana. And you know,

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Speaker 1: what's a banana in your mind is your experience the banana,

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Speaker 1: poking on it, pushing on and tasting it, whatever, chasing

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Speaker 1: that sloth, all these experiences of what build your sort

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Speaker 1: of your mental construct of the banana. But it's nice

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Speaker 1: to know, like mathematically, how that comes from the littlest

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Speaker 1: bits it's made out of. So thank you Grace for

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Speaker 1: asking that question. And we're curious if this answered your

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Speaker 1: question and if you have follow ups, So we'll ship

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Speaker 1: this off to Grace and we'll hear what she.

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Speaker 3: Has to say.

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Speaker 2: I also don't think answers have to be beautiful, but

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Speaker 2: maybe that's because I'm a biologist. Our answers are rarely.

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Speaker 3: Beautiful, but often they're insightful.

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Speaker 2: Yeah, I wasn't implying they weren't, Daniel. I don't know

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Speaker 2: why you felt you needed to say that, well.

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Speaker 1: Because that's where the beauty comes from, right the inside. Like, oh, no,

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Speaker 1: I understand this in a way I didn't before. Yeah,

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Speaker 1: it can still be gooey, it's true.

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Speaker 5: Hi, Daniel Keilly, thank you so much for answering our question.

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Speaker 5: I'm still not sure I understand all of it, but

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Speaker 5: it was really helpful here you explain it.

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Speaker 6: I agree, it's clear I need to change my mental

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Speaker 6: model of ways and particles stecking up like lego bricks

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Speaker 6: to make things like sloths and instead think about blobs

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Speaker 6: of energy. Thank you for all that you both do

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Speaker 6: to help educate us and break down complex topics and

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Speaker 6: have fun while doing it. I rate your answer a

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Speaker 6: solid A plus.

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Speaker 5: Thank you so much.

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Speaker 7: Bye.

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Speaker 2: All right, we're back and the next question is from

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Speaker 2: a listener who, when they emailed us, was working through

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Speaker 2: a very miserable cold. I believe they're feeling better now.

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Speaker 2: But here is their question.

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Speaker 8: A common COLDE seems to have a lot of variants,

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Speaker 8: But how quickly does it mutate? Such as for the

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Speaker 8: common I'm suffering with at the moment, Is there a

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Speaker 8: quantifiable percentage of my sneezing and coughing that I accidentally

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Speaker 8: spew onto others noticeably different compared to my original infection?

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Speaker 8: Or are the variants pretty rare? But given the billions

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Speaker 8: of us who get a cold that can create variants,

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Speaker 8: a big number times a small percentage can have a

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Speaker 8: surprisingly noticeable number.

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Speaker 1: Help me out, all right, this is a great question,

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Speaker 1: and it's sort of similar in spirit to the previous one, Right,

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Speaker 1: getting a microscopic understanding of a common experience, in this case,

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Speaker 1: the common cold. So let's see if biology can provide

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Speaker 1: the insights to give you that sense of understanding, even

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Speaker 1: if we are talking about mucus.

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Speaker 2: Well, let's give it a shot, all right, So it

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Speaker 2: gets complicated right from the beginning. The common cold. According

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Speaker 2: to the Centers for Disease Control, this is defined as

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Speaker 2: a viral infection of the upper respiratory track. Okay, okay,

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Speaker 2: but it turns out it's not caused by just one

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Speaker 2: kind of virus. It's caused by something like over two

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Speaker 2: hundred different kinds of viruses. But depending on the time

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Speaker 2: of year, between fifty to eighty percent of the common

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Speaker 2: colds that people have are caused by a group of

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Speaker 2: viruses called the rhinoviruses. So we're going to answer Tim's

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Speaker 2: question based on data that we've gotten in labs that

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Speaker 2: have looked at rhinoviruses.

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Speaker 1: So this is like asking, why is my house infected

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Speaker 1: with insects? Well, it turns out there's lots of different

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Speaker 1: kind of insects that couldn't infest your house.

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Speaker 2: That's right, that's right. And so to answer your question

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Speaker 2: without taking too many lifetimes, we need to narrow down

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Speaker 2: on an example. So we're narrowing down on the rhinoviruses.

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Speaker 1: And so for those of us who are not biologists,

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Speaker 1: remind us, like, what is a virus and how does

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Speaker 1: it work?

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Speaker 3: What is its plan?

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Speaker 2: Yeah, So what viruses do is when they get inside

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Speaker 2: of you, they have this way of injecting themselves into

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Speaker 2: your cell. So they've got like some machinery that helps

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Speaker 2: them move around, and then when they get to a cell,

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Speaker 2: they clamp down and then they inject genetic material into

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Speaker 2: the cell.

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Speaker 1: This is amazing. It's empazing. It sounds so mechanical.

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Speaker 2: It does. Yeah, I know, sometimes biology is just as

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Speaker 2: good as Sci Fi, maybe better. So they hijack the

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Speaker 2: cell's machinery and they get the cell to start replicating

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Speaker 2: the virus. And this is part of where Tim's question

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Speaker 2: comes in. As the virus replicates, sometimes mistakes are made,

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Speaker 2: and cold viruses tend to not correct these genetic mistakes

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Speaker 2: very often, and so we're going to get to that

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Speaker 2: in a little bit more detail layered. So the host

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Speaker 2: cell replicates the virus many times, and then the virus

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Speaker 2: breaks out of the cell and goes and completes that

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Speaker 2: cycle again.

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Speaker 1: So the element of the cell that is taking over

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Speaker 1: is the bit where it replicates the genetic material. That's

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Speaker 1: what the virus can't do for itself. Yes, so this

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Speaker 1: is like a hacker breaking into a publishing house. And

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Speaker 1: getting it to print his personal manifesto instead of whatever

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Speaker 1: it was going to print otherwise.

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Speaker 2: That's right, yep. Print it's pamphlets over and over and

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Speaker 2: over again. And then through some mechanism that sort of

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Speaker 2: breaks the metaphor, it sneaks into another publishing house and

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Speaker 2: does the same thing over and over and over again

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Speaker 2: until you stop sneezing. So anyway, so it goes through

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Speaker 2: this process, and it is finding cells in particular in

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Speaker 2: like your nasal passage and your lungs, and it's replicating

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Speaker 2: in there. And as it replicates, your immune system sort

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Speaker 2: of amps up and starts attacking it. And this cold

442
00:20:19,600 --> 00:20:21,720
Speaker 2: process can last for about a week, and so you

443
00:20:21,800 --> 00:20:24,600
Speaker 2: get a build up of virus particles and then your

444
00:20:24,600 --> 00:20:27,280
Speaker 2: immune system starts to get it in control, and the

445
00:20:27,280 --> 00:20:29,280
Speaker 2: density of virus goes down over time.

446
00:20:29,680 --> 00:20:31,800
Speaker 1: And so if I've had the common cold and my

447
00:20:31,800 --> 00:20:34,280
Speaker 1: immune system has figured out how to combat it, why

448
00:20:34,280 --> 00:20:36,400
Speaker 1: do I then get the common cold again the next

449
00:20:36,480 --> 00:20:38,520
Speaker 1: year or three weeks later when my kids come back

450
00:20:38,520 --> 00:20:39,280
Speaker 1: with a different one.

451
00:20:39,359 --> 00:20:42,800
Speaker 2: Well, that great question brings me to mutation rates. So,

452
00:20:43,240 --> 00:20:46,840
Speaker 2: as I mentioned, the virus doesn't correct mistakes as often

453
00:20:47,000 --> 00:20:50,600
Speaker 2: as for example, human cells do. And so the question

454
00:20:50,680 --> 00:20:52,960
Speaker 2: that we want to ask here to really address Tim's

455
00:20:53,080 --> 00:20:55,840
Speaker 2: question is how many mutations do you tend to get

456
00:20:55,880 --> 00:20:58,080
Speaker 2: and how much do they build up? So I found

457
00:20:58,240 --> 00:21:02,199
Speaker 2: estimates that the mutation rate is you get something like

458
00:21:02,520 --> 00:21:05,240
Speaker 2: ten to the negative three to ten to the negative

459
00:21:05,280 --> 00:21:08,360
Speaker 2: five mutations, and ten to the negative three is one

460
00:21:08,400 --> 00:21:11,600
Speaker 2: in a thousand, one in a thousand. Yeah, per nucleotide,

461
00:21:11,640 --> 00:21:15,160
Speaker 2: per genome replication event. Don't worry about all of those numbers.

462
00:21:15,160 --> 00:21:18,960
Speaker 2: The point is that a virus is about seven two

463
00:21:19,040 --> 00:21:22,200
Speaker 2: hundred pieces long, and each time it replicates, you usually

464
00:21:22,280 --> 00:21:25,879
Speaker 2: end up with about one mutation on average in that

465
00:21:25,960 --> 00:21:26,760
Speaker 2: genetic code.

466
00:21:26,920 --> 00:21:28,920
Speaker 1: So it's getting the cell to replicate it, but it's

467
00:21:28,920 --> 00:21:30,280
Speaker 1: not a perfect copy.

468
00:21:30,040 --> 00:21:31,960
Speaker 2: That's right, and then it doesn't get corrected, and so

469
00:21:32,080 --> 00:21:35,199
Speaker 2: that error goes on to the next cell and that

470
00:21:35,320 --> 00:21:37,080
Speaker 2: gets replicated over and over again.

471
00:21:37,240 --> 00:21:40,720
Speaker 1: So already the initial virus that infected Tim, all of

472
00:21:40,760 --> 00:21:43,960
Speaker 1: its little babies likely are different than it was by

473
00:21:44,080 --> 00:21:46,360
Speaker 1: one nucleotide.

474
00:21:45,560 --> 00:21:47,320
Speaker 2: That's right. And so then the question you want to

475
00:21:47,320 --> 00:21:49,800
Speaker 2: ask yourself is does that matter? And I think a

476
00:21:49,800 --> 00:21:51,520
Speaker 2: lot of the time it's not going to matter. So

477
00:21:51,600 --> 00:21:54,639
Speaker 2: a lot of mutations don't change the kind of protein

478
00:21:54,680 --> 00:21:56,760
Speaker 2: that ends up getting made, or they don't have any

479
00:21:56,800 --> 00:22:00,960
Speaker 2: meaningful change based on this one little that flips to

480
00:22:01,000 --> 00:22:01,720
Speaker 2: a different value.

481
00:22:01,880 --> 00:22:02,000
Speaker 3: Right.

482
00:22:02,000 --> 00:22:04,440
Speaker 1: It's not like the common cold suddenly becomes a completely

483
00:22:04,480 --> 00:22:07,119
Speaker 1: different disease measles all of a sudden with one slip

484
00:22:07,200 --> 00:22:07,639
Speaker 1: or something.

485
00:22:07,840 --> 00:22:10,280
Speaker 2: Right. But you know, as Tim noted in his question,

486
00:22:10,400 --> 00:22:12,879
Speaker 2: if this is happening many many times in your body,

487
00:22:13,240 --> 00:22:15,520
Speaker 2: and then it's happening to many many people, these changes

488
00:22:15,520 --> 00:22:18,560
Speaker 2: can add up over time. Amazingly. This all seems to

489
00:22:18,600 --> 00:22:21,199
Speaker 2: also be temperature dependent. And I have a lot of

490
00:22:21,240 --> 00:22:23,680
Speaker 2: friends who will say things like, oh, don't go outside

491
00:22:23,720 --> 00:22:26,200
Speaker 2: without a coat on. It's cold out, and then you're

492
00:22:26,200 --> 00:22:28,720
Speaker 2: gonna get sick. And that's not quite how it works.

493
00:22:28,760 --> 00:22:33,280
Speaker 2: But there is some evidence that at colder temperatures, cold

494
00:22:33,400 --> 00:22:36,880
Speaker 2: viruses do replicate more quickly in mice. I don't think

495
00:22:36,880 --> 00:22:38,760
Speaker 2: this has been done in humans. It's always in mice.

496
00:22:39,240 --> 00:22:41,720
Speaker 2: But it's not because that's better for the virus in

497
00:22:41,760 --> 00:22:44,199
Speaker 2: some way, which I think is implied when they're like, oh,

498
00:22:44,200 --> 00:22:46,520
Speaker 2: don't go outside without your coat on. It's because the

499
00:22:46,560 --> 00:22:50,320
Speaker 2: immune systems in mice seem to react less strongly at

500
00:22:50,359 --> 00:22:54,200
Speaker 2: low temperatures. So these replication rates that we're talking about here,

501
00:22:54,240 --> 00:22:56,359
Speaker 2: they're all a little bit handwavy, and they depend on

502
00:22:56,400 --> 00:22:58,640
Speaker 2: what temperature you're at, and so Tim, I hope you're

503
00:22:58,640 --> 00:23:01,320
Speaker 2: staying nice and warm. Yeah, So what do we know

504
00:23:01,520 --> 00:23:04,760
Speaker 2: about how much the cell replicates inside of a host?

505
00:23:05,160 --> 00:23:09,159
Speaker 2: And the answer is well as complicated. So at a

506
00:23:09,200 --> 00:23:11,600
Speaker 2: lot of our data come from what I think of

507
00:23:11,640 --> 00:23:14,439
Speaker 2: as the wrong kinds of cells in the lab. And

508
00:23:14,480 --> 00:23:16,840
Speaker 2: so the cells that are often used in these experiments

509
00:23:16,840 --> 00:23:19,600
Speaker 2: are HeLa cells. So these are I think ovarian cells

510
00:23:19,640 --> 00:23:23,000
Speaker 2: collected from a woman named Henriette Lex a long time ago.

511
00:23:23,000 --> 00:23:24,560
Speaker 2: They were collected without her permission.

512
00:23:24,960 --> 00:23:26,360
Speaker 1: Bad bad biologists.

513
00:23:26,440 --> 00:23:26,760
Speaker 3: Bad.

514
00:23:27,119 --> 00:23:31,240
Speaker 2: Yeah, yeah, no, bad biologists. You're right, I'll take that one.

515
00:23:31,560 --> 00:23:33,080
Speaker 1: I mean, we've never gotten consent from any of the

516
00:23:33,080 --> 00:23:35,040
Speaker 1: protons we've destroyed, but I don't think they are the

517
00:23:35,040 --> 00:23:35,520
Speaker 1: same rights.

518
00:23:35,600 --> 00:23:38,680
Speaker 2: Yeah, no, it's you're right. This was not a bright

519
00:23:38,760 --> 00:23:42,200
Speaker 2: spot in the history of biology. So we stole those cells.

520
00:23:42,240 --> 00:23:44,159
Speaker 2: There's a whole very interesting book on that which I

521
00:23:44,200 --> 00:23:47,040
Speaker 2: recommend people check out. But anyway, so these cells are

522
00:23:47,040 --> 00:23:49,320
Speaker 2: really great at surviving in the lab, and so we

523
00:23:49,400 --> 00:23:52,360
Speaker 2: will infect them with cold viruses and see how they replicate.

524
00:23:52,440 --> 00:23:54,800
Speaker 2: But the problem is they're ovarian cells. They're not like

525
00:23:54,880 --> 00:23:58,280
Speaker 2: nasal passage cells, and the body is complicated. So just

526
00:23:58,280 --> 00:24:00,040
Speaker 2: because something happens in a petri dish, does it I

527
00:24:00,040 --> 00:24:02,359
Speaker 2: mean it would happen the same in a body. So

528
00:24:02,560 --> 00:24:06,360
Speaker 2: when a cell explodes, how many baby viruses are made?

529
00:24:06,560 --> 00:24:09,679
Speaker 2: And the answer is probably something like one hundred thousand,

530
00:24:09,760 --> 00:24:12,760
Speaker 2: maybe even more than that. And then how long is

531
00:24:12,800 --> 00:24:16,480
Speaker 2: the cycle of infection before you get an explosion? And

532
00:24:16,840 --> 00:24:20,320
Speaker 2: you know, we don't really know. It's probably longer than minutes,

533
00:24:20,400 --> 00:24:22,800
Speaker 2: but less than weeks, which is a pretty big timeframe.

534
00:24:22,880 --> 00:24:25,760
Speaker 2: And thank you so much to Katrina Whitson for giving

535
00:24:25,840 --> 00:24:28,520
Speaker 2: us this information, because I was having trouble sort of

536
00:24:28,640 --> 00:24:31,480
Speaker 2: narrowing down the numbers to use for this question, and I.

537
00:24:31,400 --> 00:24:33,760
Speaker 1: Think Coatinia would probably want me to emphasize that these

538
00:24:33,920 --> 00:24:36,919
Speaker 1: are very fuzzy numbers because it's a research question. Nobody

539
00:24:36,960 --> 00:24:38,840
Speaker 1: knows the answer to these things, which is sort of

540
00:24:39,080 --> 00:24:42,040
Speaker 1: shocking and amazing, but it's hard to measure. And she

541
00:24:42,119 --> 00:24:44,760
Speaker 1: was also telling me that sometimes a virus wants to

542
00:24:44,800 --> 00:24:47,200
Speaker 1: slow down how long the process takes because it wants

543
00:24:47,200 --> 00:24:50,119
Speaker 1: the cell to get like stronger and fatter before it explodes.

544
00:24:50,480 --> 00:24:52,359
Speaker 1: So sometimes they like beef up the cell, sort of

545
00:24:52,400 --> 00:24:54,159
Speaker 1: like fattening a calf before you kill it.

546
00:24:54,200 --> 00:24:56,000
Speaker 2: That's right, And so as a group effort, I would

547
00:24:56,040 --> 00:25:00,119
Speaker 2: say the Whitesn Research Institute plus adjunct faculty member or

548
00:25:00,160 --> 00:25:04,880
Speaker 2: Kelly Wiener Smith decided that the virus that you sneeze

549
00:25:04,880 --> 00:25:07,320
Speaker 2: out sort of towards the end of your cold probably

550
00:25:07,359 --> 00:25:10,240
Speaker 2: has something like twenty mutations and is about one percent

551
00:25:10,320 --> 00:25:13,520
Speaker 2: different than the virus that you were infected by GO team.

552
00:25:15,440 --> 00:25:18,119
Speaker 2: But Tim wanted to know if it was noticeably variable,

553
00:25:18,200 --> 00:25:20,760
Speaker 2: and we've mentioned that it really depends where those mutations

554
00:25:20,760 --> 00:25:23,960
Speaker 2: are happening. But over time this is adding up. The

555
00:25:24,000 --> 00:25:27,800
Speaker 2: cold virus does end up being noticeably variable enough that

556
00:25:27,840 --> 00:25:30,560
Speaker 2: it's really hard to make a vaccine for the cold.

557
00:25:31,000 --> 00:25:33,080
Speaker 2: And this is for a couple reasons. So one, we've

558
00:25:33,119 --> 00:25:35,720
Speaker 2: already mentioned that there's like something like two hundred different

559
00:25:35,800 --> 00:25:39,359
Speaker 2: kinds of viruses that can cause colds. Additionally, each strain

560
00:25:39,400 --> 00:25:42,480
Speaker 2: of the cold virus is replicating pretty rapidly, so from

561
00:25:42,520 --> 00:25:44,399
Speaker 2: one season to another it might be different enough that

562
00:25:44,440 --> 00:25:47,760
Speaker 2: the vaccine wouldn't work. And additionally, colds don't tend to

563
00:25:47,760 --> 00:25:50,800
Speaker 2: be as serious as something like the flu, So there's

564
00:25:50,840 --> 00:25:53,400
Speaker 2: not a lot of impetus to try to create a vaccine,

565
00:25:53,440 --> 00:25:56,520
Speaker 2: even though I sure would love to have not spent

566
00:25:56,920 --> 00:25:59,320
Speaker 2: oh my gosh, when my kids started elementary school, I

567
00:25:59,320 --> 00:26:01,399
Speaker 2: think I spent like sixty percent of my time at

568
00:26:01,400 --> 00:26:03,480
Speaker 2: home with a cold. I would have loved to have

569
00:26:03,560 --> 00:26:06,520
Speaker 2: had that time back. But what are you gonna do?

570
00:26:06,840 --> 00:26:10,440
Speaker 1: And that's interesting because colds are varying constantly and it's

571
00:26:10,560 --> 00:26:13,560
Speaker 1: hard to maintain immunity against them. Yet they mostly feel

572
00:26:13,560 --> 00:26:15,720
Speaker 1: the same, right, Yeah, yeah, you got a head cold

573
00:26:15,760 --> 00:26:17,600
Speaker 1: or a chest cold or whatever. But it's not like,

574
00:26:17,880 --> 00:26:20,600
Speaker 1: oh wow, this one makes my head green, or now

575
00:26:20,640 --> 00:26:23,440
Speaker 1: my thumb is swollen or something. It's basically the same disease,

576
00:26:23,480 --> 00:26:24,280
Speaker 1: it feels like to me.

577
00:26:24,480 --> 00:26:26,240
Speaker 2: Yeah, no, it feels that way to me as well.

578
00:26:26,520 --> 00:26:28,879
Speaker 2: And just to be clear, the flu viruses are also

579
00:26:28,960 --> 00:26:30,959
Speaker 2: doing quite a bit of mutating, but I think they

580
00:26:31,040 --> 00:26:33,240
Speaker 2: mutate a little bit less. But every year, the reason

581
00:26:33,240 --> 00:26:35,960
Speaker 2: you get a new flu vaccine is because that vaccine

582
00:26:36,040 --> 00:26:38,080
Speaker 2: is meant to replicate the strains of the flu that

583
00:26:38,119 --> 00:26:39,919
Speaker 2: we think are going to be most common in a

584
00:26:39,920 --> 00:26:42,880
Speaker 2: given year, Given like mutations that we've seen in those

585
00:26:42,920 --> 00:26:44,879
Speaker 2: flu virus strains in the past.

586
00:26:45,280 --> 00:26:47,040
Speaker 1: Yeah, And I think there's a lot of detective work

587
00:26:47,040 --> 00:26:49,320
Speaker 1: and guesswork that goes into the flu. Right, they're like

588
00:26:49,359 --> 00:26:51,880
Speaker 1: thinking about what it might be because they obviously don't

589
00:26:51,880 --> 00:26:54,480
Speaker 1: have the examples for the flu that's gonna come.

590
00:26:54,320 --> 00:26:54,840
Speaker 3: In the future.

591
00:26:54,960 --> 00:26:57,679
Speaker 2: Yep, exactly. I mean they're making their guests based on

592
00:26:57,800 --> 00:26:59,800
Speaker 2: years of data, looking at trends and how this stuff

593
00:26:59,800 --> 00:27:01,560
Speaker 2: plays out. But you're right, at the end of the day,

594
00:27:01,600 --> 00:27:03,760
Speaker 2: you just need to guess which flu strains are going

595
00:27:03,800 --> 00:27:06,000
Speaker 2: to be the most important ones to make vaccines against.

596
00:27:06,400 --> 00:27:07,320
Speaker 2: And I hope you got it.

597
00:27:07,359 --> 00:27:10,520
Speaker 1: Right thanks to folks working on the front lines of

598
00:27:10,520 --> 00:27:11,120
Speaker 1: public health.

599
00:27:11,200 --> 00:27:13,720
Speaker 2: Yes, oh my gosh, they're the best. All right, Tim,

600
00:27:13,800 --> 00:27:16,000
Speaker 2: We hope you're feeling better, and let's find out if

601
00:27:16,080 --> 00:27:17,600
Speaker 2: we were able to answer your question.

602
00:27:18,080 --> 00:27:21,560
Speaker 9: Yes, that answer my question. And wow, that is rather

603
00:27:21,640 --> 00:27:24,639
Speaker 9: terrifying that two hundred variants out there make up the

604
00:27:24,960 --> 00:27:27,840
Speaker 9: cold virus. I don't know if I'm going to sleep

605
00:27:27,840 --> 00:27:29,800
Speaker 9: well at night knowing that fact on top of all

606
00:27:29,880 --> 00:27:33,440
Speaker 9: the other mutation rates. But luckily we feel a little

607
00:27:33,440 --> 00:27:51,480
Speaker 9: bit on the safe side.

608
00:27:54,800 --> 00:27:55,200
Speaker 3: All right.

609
00:27:55,240 --> 00:27:58,200
Speaker 1: And our last question comes from Mark in Newcastle, who

610
00:27:58,240 --> 00:28:02,280
Speaker 1: asks a very heavy question about something very ephemeral.

611
00:28:02,680 --> 00:28:06,120
Speaker 10: Hi guys, it's Markia from Newcastle upon Tyne in the UK,

612
00:28:06,320 --> 00:28:08,959
Speaker 10: and I've got a question for you about data. I

613
00:28:09,000 --> 00:28:11,919
Speaker 10: was recently working on a project with my orduino writing

614
00:28:11,960 --> 00:28:15,040
Speaker 10: to some SD cards and of course when you switch

615
00:28:15,119 --> 00:28:16,880
Speaker 10: off the power and switch it back on, the data

616
00:28:16,920 --> 00:28:20,880
Speaker 10: is retained. So these cards do store something. This storing

617
00:28:21,000 --> 00:28:26,000
Speaker 10: charge and charge is electrons. Electrons have mass, So does

618
00:28:26,119 --> 00:28:30,200
Speaker 10: data have mass? Would an SD card full of data

619
00:28:30,400 --> 00:28:33,920
Speaker 10: way more than an SD card that didn't I guess

620
00:28:33,920 --> 00:28:36,320
Speaker 10: this is an extra opulation of this question, how much

621
00:28:36,359 --> 00:28:39,000
Speaker 10: does the Internet Way? Book pops for another day.

622
00:28:39,440 --> 00:28:41,480
Speaker 2: This is such a great question because, well, for a

623
00:28:41,520 --> 00:28:44,000
Speaker 2: variety of reasons. But I love this question because in

624
00:28:44,040 --> 00:28:46,280
Speaker 2: the past on this show you have said that when

625
00:28:46,320 --> 00:28:49,920
Speaker 2: a Tesla battery is charged, it weighs more than when

626
00:28:50,000 --> 00:28:53,960
Speaker 2: it's not charged, And that makes sense now, but at

627
00:28:54,000 --> 00:28:56,440
Speaker 2: the moment it totally surprised me and I didn't expect that.

628
00:28:56,600 --> 00:28:59,240
Speaker 2: And so, yeah, how much does the Internet Way.

629
00:28:59,160 --> 00:29:02,760
Speaker 3: Daniel seven at weighs seven?

630
00:29:02,880 --> 00:29:04,840
Speaker 2: Oh good, I was going to guess forty two.

631
00:29:04,960 --> 00:29:08,320
Speaker 1: Yeah, remember that mass as a measure of internal stored energy,

632
00:29:08,680 --> 00:29:11,400
Speaker 1: So if you increase the internal stored energy of an object,

633
00:29:11,800 --> 00:29:13,480
Speaker 1: then you are increasing its mass.

634
00:29:13,880 --> 00:29:14,720
Speaker 3: Like if you have a.

635
00:29:14,720 --> 00:29:16,480
Speaker 1: Rock and use zapp it with a photon and it

636
00:29:16,520 --> 00:29:19,800
Speaker 1: gets hotter, it also has more mass. Now, so when

637
00:29:19,800 --> 00:29:22,680
Speaker 1: you charge your Tesla battery, you're giving it more energy,

638
00:29:23,040 --> 00:29:25,920
Speaker 1: not because you're adding more electrons, you know, like physically

639
00:29:25,920 --> 00:29:29,000
Speaker 1: adding more scoops of universe stuff. Just giving more energy

640
00:29:29,040 --> 00:29:31,880
Speaker 1: to that configuration does increase the mass of the battery.

641
00:29:32,120 --> 00:29:35,160
Speaker 1: Since equals mc squared and C squared is a really

642
00:29:35,160 --> 00:29:37,880
Speaker 1: big number, you need an enormous amount of energy to

643
00:29:37,920 --> 00:29:41,120
Speaker 1: make a tiny increase in mass. So nobody really notices this,

644
00:29:41,440 --> 00:29:44,320
Speaker 1: and that's why. But Mark's question is sort of related.

645
00:29:44,560 --> 00:29:48,440
Speaker 1: He's asking about whether the arrangements to configuration of information

646
00:29:49,040 --> 00:29:52,520
Speaker 1: on his SD card or on your hard drive or

647
00:29:52,520 --> 00:29:55,800
Speaker 1: in your brain also has mass, which is a really

648
00:29:55,840 --> 00:30:00,400
Speaker 1: fascinating question and touches on deep concepts about information and entropy.

649
00:30:00,600 --> 00:30:04,080
Speaker 2: And we luckily have someone who is part computer scientist,

650
00:30:04,120 --> 00:30:07,920
Speaker 2: part physicists who is absolutely prepared to answer this question

651
00:30:08,000 --> 00:30:08,360
Speaker 2: for us.

652
00:30:09,600 --> 00:30:12,320
Speaker 1: Yeah, so information is really fascinating. It's hard to think

653
00:30:12,360 --> 00:30:16,560
Speaker 1: about like whether information has mass because information seems sort

654
00:30:16,600 --> 00:30:20,080
Speaker 1: of subjective, right, like, if you have a hard drive

655
00:30:20,360 --> 00:30:23,400
Speaker 1: and it has just random ones and zeros on it,

656
00:30:23,440 --> 00:30:25,800
Speaker 1: does it have more or less information than if you

657
00:30:25,840 --> 00:30:28,560
Speaker 1: put a picture of your dog on the hard drive? Well,

658
00:30:28,600 --> 00:30:31,080
Speaker 1: it depends, like do you consider the picture of your

659
00:30:31,080 --> 00:30:33,720
Speaker 1: dog to be useful or information in some way?

660
00:30:33,840 --> 00:30:34,040
Speaker 3: Right?

661
00:30:34,680 --> 00:30:37,000
Speaker 1: Or like did you encrypt the picture of your dog?

662
00:30:37,360 --> 00:30:41,200
Speaker 1: Because the best encryption algorithms make data that's valuable it

663
00:30:41,200 --> 00:30:44,320
Speaker 1: has some information look like random noise. So you can

664
00:30:44,360 --> 00:30:46,280
Speaker 1: imagine a scenario where you, like, you take a picture

665
00:30:46,280 --> 00:30:47,680
Speaker 1: of your dog, you put it on the hard drive,

666
00:30:47,920 --> 00:30:50,640
Speaker 1: looks like your dog, then you encrypt it. Somebody else

667
00:30:50,680 --> 00:30:53,000
Speaker 1: coming along is like, no, that's just random noise. There's

668
00:30:53,000 --> 00:30:56,000
Speaker 1: no information. And what if you, like, lose the password,

669
00:30:56,120 --> 00:30:59,640
Speaker 1: has the information decreased? And so information turns out to

670
00:30:59,640 --> 00:31:03,120
Speaker 1: be a fascinatingly subjective concept, which makes it very hard

671
00:31:03,160 --> 00:31:05,600
Speaker 1: to link to masks because mass is something physical and

672
00:31:05,680 --> 00:31:08,480
Speaker 1: invariant that everybody agrees on that you can like measure

673
00:31:08,560 --> 00:31:10,840
Speaker 1: without knowing about dogs or passwords?

674
00:31:10,960 --> 00:31:14,080
Speaker 2: Should I be thinking about information differently than I think

675
00:31:14,120 --> 00:31:17,200
Speaker 2: about like you know, before I put my PowerPoint presentation

676
00:31:17,280 --> 00:31:21,280
Speaker 2: on my SD card, it has fifty megabytes of data

677
00:31:21,360 --> 00:31:23,760
Speaker 2: and after the PowerPoint presentation is on there, it has

678
00:31:23,760 --> 00:31:29,280
Speaker 2: one thy fifty. So how is information different than megabytes?

679
00:31:29,760 --> 00:31:31,360
Speaker 1: Yeah, if you have an empty disc and then you

680
00:31:31,400 --> 00:31:34,560
Speaker 1: put files on there, it's counting, like how much of

681
00:31:34,560 --> 00:31:38,080
Speaker 1: the drive has information you've put on there. There could

682
00:31:38,160 --> 00:31:40,840
Speaker 1: also be information on the other bits that it's not counting,

683
00:31:41,200 --> 00:31:42,840
Speaker 1: maybe somebody else put it on there, but then you

684
00:31:43,000 --> 00:31:45,320
Speaker 1: format it the drive, so you consider it to be empty.

685
00:31:45,520 --> 00:31:47,880
Speaker 1: So it's a different question of like when you're filling

686
00:31:48,000 --> 00:31:50,400
Speaker 1: up the drive, right, because it's just like using some

687
00:31:50,480 --> 00:31:53,560
Speaker 1: of the bits for this rather than considering them unused.

688
00:31:53,880 --> 00:31:56,560
Speaker 1: But the question of information is subtle, and we're going

689
00:31:56,600 --> 00:31:58,880
Speaker 1: to have to dip into our understanding of entropy in

690
00:31:58,960 --> 00:32:00,880
Speaker 1: order to understand it, because it's turns out these two

691
00:32:00,920 --> 00:32:02,320
Speaker 1: concepts are closely related.

692
00:32:02,720 --> 00:32:05,800
Speaker 2: So okay, So just to clarify, then, information is not

693
00:32:06,440 --> 00:32:11,000
Speaker 2: how much stuff is on a card, it's how informative

694
00:32:11,360 --> 00:32:12,560
Speaker 2: is the thing?

695
00:32:12,920 --> 00:32:14,480
Speaker 1: Yeah, Because you could take a card and just fill

696
00:32:14,520 --> 00:32:17,320
Speaker 1: it with random ones and zeros, right, there's no information

697
00:32:17,400 --> 00:32:19,280
Speaker 1: there for you. So just because you put a big

698
00:32:19,280 --> 00:32:21,160
Speaker 1: file in your hard drive doesn't mean you add a

699
00:32:21,160 --> 00:32:23,360
Speaker 1: lot of information. It's about the contents and this seems

700
00:32:23,400 --> 00:32:27,400
Speaker 1: really subjective, and physics is all about equations and crisp definitions.

701
00:32:27,760 --> 00:32:30,400
Speaker 1: So how do we think about information from the point

702
00:32:30,400 --> 00:32:33,440
Speaker 1: of view of science and physics. So Claude Shannon defined

703
00:32:33,480 --> 00:32:35,200
Speaker 1: this in the middle of the last century. He was

704
00:32:35,200 --> 00:32:37,480
Speaker 1: thinking about this and he came up with something of

705
00:32:37,520 --> 00:32:40,800
Speaker 1: an arbitrary but very useful definition of information, and he

706
00:32:40,840 --> 00:32:43,680
Speaker 1: defines it as how much you have learned, how much

707
00:32:43,760 --> 00:32:47,520
Speaker 1: surprising information you have gained. So he was imagining like,

708
00:32:47,680 --> 00:32:50,120
Speaker 1: I'm communicating to you by sending you symbols across some

709
00:32:50,240 --> 00:32:53,000
Speaker 1: channel ones and zero's on a hard drive or you know,

710
00:32:53,160 --> 00:32:56,240
Speaker 1: text on a phone or whatever, and you want to

711
00:32:56,240 --> 00:32:59,080
Speaker 1: measure how much information is in these messages from Daniel

712
00:32:59,440 --> 00:33:02,960
Speaker 1: and to his definition, if when you learn something surprising,

713
00:33:03,360 --> 00:33:06,120
Speaker 1: that's high information. If you learn something you already know,

714
00:33:06,320 --> 00:33:09,640
Speaker 1: that's low information. So for example, let's say every day

715
00:33:09,680 --> 00:33:11,760
Speaker 1: I text you and I say, hey, Kelly, the earth

716
00:33:11,760 --> 00:33:14,240
Speaker 1: didn't explode last nightew every day you look at it

717
00:33:14,240 --> 00:33:17,760
Speaker 1: and you're like, Okay, that's not a surprise, right, this

718
00:33:17,800 --> 00:33:19,480
Speaker 1: has happened every day so far in my life.

719
00:33:19,560 --> 00:33:22,000
Speaker 2: I'm changing my phone number. Leave me alone, Daniel.

720
00:33:23,800 --> 00:33:26,200
Speaker 1: Why a physicists text me about the planet's exploding.

721
00:33:26,800 --> 00:33:27,520
Speaker 3: What did I do wrong?

722
00:33:27,640 --> 00:33:28,320
Speaker 2: Low information?

723
00:33:28,560 --> 00:33:32,400
Speaker 1: Low information exactly because it's something you expected to happen.

724
00:33:32,680 --> 00:33:34,800
Speaker 1: So the fact that it happened you didn't really learn much.

725
00:33:35,040 --> 00:33:36,520
Speaker 1: If one day I texted you I was like, by

726
00:33:36,600 --> 00:33:39,320
Speaker 1: the way, at two am, the Earth exploded, you'd be like, wow,

727
00:33:39,360 --> 00:33:41,800
Speaker 1: that's news to me, right, this is big information.

728
00:33:41,920 --> 00:33:44,120
Speaker 2: But wouldn't that also be low information because I would

729
00:33:44,200 --> 00:33:46,280
Speaker 2: have been exploded and I would have also been like,

730
00:33:46,520 --> 00:33:48,320
Speaker 2: thanks for being late to the party, Daniel.

731
00:33:48,480 --> 00:33:52,200
Speaker 1: Don't use the practical details of my analogy to confuse you, audience.

732
00:33:53,320 --> 00:33:56,000
Speaker 2: Okay, whoa, Oh no, I didn't know that, Daniel.

733
00:33:56,440 --> 00:33:58,720
Speaker 1: You're living in a city on Mars in this example.

734
00:33:58,880 --> 00:34:01,240
Speaker 1: All right, So let's put Kelly on Mars. She and

735
00:34:01,240 --> 00:34:04,160
Speaker 1: her cute babies in their baby spacesuits, and her and

736
00:34:04,200 --> 00:34:07,160
Speaker 1: the girl Scout troop are camping up there on Mars awesome.

737
00:34:07,240 --> 00:34:09,440
Speaker 1: And every day I wake up and my job is

738
00:34:09,480 --> 00:34:11,960
Speaker 1: to text you about whether the Earth exploded. So the

739
00:34:12,040 --> 00:34:13,920
Speaker 1: day that you get a text that the Earth exploded,

740
00:34:14,239 --> 00:34:17,279
Speaker 1: that's big news. Why because it was unlikely and so

741
00:34:17,320 --> 00:34:19,920
Speaker 1: the fact that it happened is a lot of information.

742
00:34:20,600 --> 00:34:21,360
Speaker 2: Major bummer.

743
00:34:22,520 --> 00:34:24,560
Speaker 1: So This is fascinating because it means a bits of

744
00:34:24,600 --> 00:34:26,600
Speaker 1: information like did the Earth explode?

745
00:34:26,680 --> 00:34:27,080
Speaker 3: Yes and no.

746
00:34:27,239 --> 00:34:29,600
Speaker 1: It feels like one bit like either value should be

747
00:34:29,680 --> 00:34:33,080
Speaker 1: equal amounts of information, but they're not because information depends

748
00:34:33,200 --> 00:34:36,760
Speaker 1: on context, so bits of information are not created equally.

749
00:34:37,200 --> 00:34:40,600
Speaker 1: And so Shannon said, let's define the amount of information

750
00:34:41,200 --> 00:34:45,120
Speaker 1: to be the inverse of the probability for that to happen. Right,

751
00:34:45,160 --> 00:34:47,640
Speaker 1: so if a high probability of it happens, one over

752
00:34:47,680 --> 00:34:49,640
Speaker 1: that number is a small number, so it's a small

753
00:34:49,680 --> 00:34:52,920
Speaker 1: amount of information. And if a very unlikely thing happened,

754
00:34:52,920 --> 00:34:55,360
Speaker 1: then one over that number is a very big number,

755
00:34:55,560 --> 00:34:59,080
Speaker 1: so that's a lot of information. And he called this surprisal.

756
00:34:59,239 --> 00:34:59,680
Speaker 2: That's cute.

757
00:34:59,719 --> 00:35:01,600
Speaker 1: And to make it well, behave we have the logarithm

758
00:35:01,640 --> 00:35:05,359
Speaker 1: of it. So he defines information as log of one

759
00:35:05,480 --> 00:35:08,440
Speaker 1: over the probability for something to happen, which just means

760
00:35:08,520 --> 00:35:12,880
Speaker 1: that like more probable, lower information, less probable, more information.

761
00:35:13,320 --> 00:35:15,759
Speaker 1: So now we have like a definition of information. And

762
00:35:15,800 --> 00:35:18,680
Speaker 1: again this is just something Claude Shannon made up, but

763
00:35:18,719 --> 00:35:21,480
Speaker 1: we're gonna see in a moment that actually connects with

764
00:35:21,800 --> 00:35:23,120
Speaker 1: other concepts in physics.

765
00:35:23,600 --> 00:35:27,560
Speaker 2: Would you be like taking the expected value of surprisal

766
00:35:27,600 --> 00:35:29,920
Speaker 2: after accounting for the fact that people might differ in

767
00:35:29,960 --> 00:35:32,920
Speaker 2: how surprised they are about some like would you have

768
00:35:33,000 --> 00:35:36,399
Speaker 2: to average different people's surprisal to really get a good

769
00:35:36,480 --> 00:35:37,840
Speaker 2: sense of the information.

770
00:35:38,200 --> 00:35:38,960
Speaker 3: That's really cool.

771
00:35:39,040 --> 00:35:41,120
Speaker 1: Yeah, so something might be information to me but not

772
00:35:41,200 --> 00:35:43,839
Speaker 1: to you, right Like, what if I'm the one who

773
00:35:43,880 --> 00:35:46,000
Speaker 1: destroyed the earth and then somebody texts me like the

774
00:35:46,080 --> 00:35:48,000
Speaker 1: earth blew up today, I'm like, yeah, dude, I know.

775
00:35:49,800 --> 00:35:52,800
Speaker 1: Then that's not information to me because I already knew happened,

776
00:35:52,800 --> 00:35:54,759
Speaker 1: but it is information to you. And that kind of

777
00:35:54,800 --> 00:35:56,840
Speaker 1: makes sense, right, Like, the same bit is not the

778
00:35:56,840 --> 00:35:58,960
Speaker 1: same amount of information for everybody, depending on what they

779
00:35:59,000 --> 00:36:02,320
Speaker 1: already knew. God, But there is a concept of expected

780
00:36:02,360 --> 00:36:05,600
Speaker 1: a surprisal. So if you take the kind of surprise

781
00:36:05,640 --> 00:36:07,719
Speaker 1: you might get from all the different messages you might

782
00:36:07,760 --> 00:36:10,359
Speaker 1: get from Daniel, and you average them over how likely

783
00:36:10,400 --> 00:36:13,279
Speaker 1: you are to get those messages, you get this other formula.

784
00:36:13,360 --> 00:36:16,120
Speaker 1: And this formula is fascinating because it looks just like

785
00:36:16,480 --> 00:36:19,880
Speaker 1: the formula we have in physics for calculating entropy.

786
00:36:20,560 --> 00:36:21,719
Speaker 3: Remember a few.

787
00:36:21,520 --> 00:36:24,520
Speaker 1: Episodes ago, we talked about what does entropy mean? And

788
00:36:24,560 --> 00:36:27,640
Speaker 1: we said that entropy was a ratio between basically how

789
00:36:27,719 --> 00:36:29,960
Speaker 1: much you know and how much you don't know. How

790
00:36:30,000 --> 00:36:32,360
Speaker 1: many ways can you configure the micro states of a

791
00:36:32,400 --> 00:36:35,320
Speaker 1: system to be consistent with the macro state you see,

792
00:36:35,520 --> 00:36:37,520
Speaker 1: So you see that there's particles in a box at

793
00:36:37,560 --> 00:36:39,880
Speaker 1: a certain temperature. How many ways can you arrange the

794
00:36:39,880 --> 00:36:43,680
Speaker 1: particles inside? How many different configurations can there be that

795
00:36:43,760 --> 00:36:46,680
Speaker 1: are consistent with the measurement that you made. And the

796
00:36:46,719 --> 00:36:49,000
Speaker 1: relationship between the micro states and the macro states is

797
00:36:49,040 --> 00:36:52,040
Speaker 1: also related by the formula with exactly the same structure

798
00:36:52,400 --> 00:36:57,000
Speaker 1: as Shannon's formula for average surprisal. So Shannon showed this

799
00:36:57,120 --> 00:37:00,319
Speaker 1: formula to John von Neumann, famous physicist and mathematics, and

800
00:37:00,360 --> 00:37:03,799
Speaker 1: he said, oh, you should call this information entropy for

801
00:37:03,880 --> 00:37:06,719
Speaker 1: two reasons. One because the formula looks the same. It

802
00:37:06,719 --> 00:37:08,960
Speaker 1: looks like the formula for entropy, and it's conceptually sort

803
00:37:09,000 --> 00:37:12,680
Speaker 1: of similar. And two because nobody really knows what entropy means,

804
00:37:12,719 --> 00:37:13,880
Speaker 1: and so they can't argue with you.

805
00:37:15,680 --> 00:37:19,080
Speaker 2: I like that anything that makes it impossible for people

806
00:37:19,080 --> 00:37:22,440
Speaker 2: to argue with me, I'm down for exactly.

807
00:37:22,520 --> 00:37:28,200
Speaker 1: And so in Shannon's information entropy, low information means low entropy.

808
00:37:28,600 --> 00:37:30,600
Speaker 1: So if you're getting a bunch of signals from Earth,

809
00:37:30,920 --> 00:37:34,279
Speaker 1: and you're always getting the same high probability message, like

810
00:37:34,360 --> 00:37:36,680
Speaker 1: the Earth didn't explode today, The Earth didn't explode today.

811
00:37:37,000 --> 00:37:40,400
Speaker 1: That's low information entropy. You're always getting the same one.

812
00:37:40,560 --> 00:37:43,040
Speaker 1: But if you're always getting a different message, like maybe

813
00:37:43,080 --> 00:37:45,640
Speaker 1: instead of getting texts from Daniel about whether the Earth exploded,

814
00:37:45,880 --> 00:37:49,759
Speaker 1: you're getting pictures from probes that landed on exoplanets, And

815
00:37:49,840 --> 00:37:51,480
Speaker 1: every time you open one of those, you're like, I

816
00:37:51,480 --> 00:37:54,080
Speaker 1: have no idea what to expect. Anything I see is

817
00:37:54,120 --> 00:37:56,480
Speaker 1: going to be new to me, right, and like this

818
00:37:56,520 --> 00:37:58,600
Speaker 1: one has rocks, and that one has like lava, and

819
00:37:58,640 --> 00:38:00,520
Speaker 1: that one has aliens on it, and like what is

820
00:38:00,640 --> 00:38:02,799
Speaker 1: this over here? Oh my gosh, the way like every

821
00:38:02,800 --> 00:38:04,680
Speaker 1: time we turn on a new telescope we see something

822
00:38:04,760 --> 00:38:08,200
Speaker 1: weird and surprising in the universe. Right, that's very high

823
00:38:08,200 --> 00:38:12,399
Speaker 1: information content because there's lots of different possible outcomes, each

824
00:38:12,480 --> 00:38:15,400
Speaker 1: of which are equally likely, instead of there being like

825
00:38:15,520 --> 00:38:19,240
Speaker 1: one very likely outcome. So that's high information entropy.

826
00:38:19,560 --> 00:38:21,920
Speaker 2: Okay, so now let's try to connect to mass. So

827
00:38:21,960 --> 00:38:25,680
Speaker 2: I'm wondering if an internet made of cat memes, which

828
00:38:25,680 --> 00:38:29,719
Speaker 2: would be low information, would weigh less than an Internet

829
00:38:29,800 --> 00:38:33,200
Speaker 2: that reconciles relativity with quantum mechanics, which would be a

830
00:38:33,239 --> 00:38:36,839
Speaker 2: high information internet. How do you compare those?

831
00:38:38,440 --> 00:38:41,759
Speaker 1: Yeah, so now we have a definition of information, right,

832
00:38:42,120 --> 00:38:44,200
Speaker 1: we know how to measure information into something that's low

833
00:38:44,200 --> 00:38:45,320
Speaker 1: information or high information.

834
00:38:45,440 --> 00:38:46,000
Speaker 3: And you're right.

835
00:38:46,160 --> 00:38:47,640
Speaker 1: If you get on the Internet and you see the

836
00:38:47,640 --> 00:38:50,000
Speaker 1: same cat memes you're always seeing, then that's low information.

837
00:38:50,520 --> 00:38:52,840
Speaker 1: If somebody says something really new and clever and surprise

838
00:38:52,880 --> 00:38:55,879
Speaker 1: and you're like, whoa, my gosh, that's high information. That's

839
00:38:55,920 --> 00:38:58,759
Speaker 1: more entropy. And we're talking about in terms of entropy

840
00:38:58,880 --> 00:39:01,040
Speaker 1: because we're trying to get a graph on the physical

841
00:39:01,160 --> 00:39:03,160
Speaker 1: nature of this and the consequences for it.

842
00:39:03,200 --> 00:39:04,360
Speaker 3: Like does it have mass?

843
00:39:04,719 --> 00:39:07,840
Speaker 1: Because we know entropy is connected to energy, right, and

844
00:39:08,000 --> 00:39:10,799
Speaker 1: energy is connected to mass. So can we somehow draw

845
00:39:10,840 --> 00:39:14,239
Speaker 1: a dotted line between information, cat memes and the weight

846
00:39:14,320 --> 00:39:20,520
Speaker 1: of the Internet. No, unfortunately not, because increasing the information

847
00:39:20,600 --> 00:39:23,560
Speaker 1: doesn't increase the mass or the energy of the system.

848
00:39:23,760 --> 00:39:26,440
Speaker 1: The information content is relative to what you already know,

849
00:39:26,600 --> 00:39:29,560
Speaker 1: depends on the context. You can arrange a set of

850
00:39:29,600 --> 00:39:31,919
Speaker 1: sticks or bits on the hard drive to mean one

851
00:39:31,920 --> 00:39:34,800
Speaker 1: thing or another. It doesn't change the mass or the energy.

852
00:39:35,000 --> 00:39:36,480
Speaker 1: So it has to do with how you interpret the

853
00:39:36,560 --> 00:39:39,680
Speaker 1: arrangement of the system and what you already know. It

854
00:39:39,719 --> 00:39:43,080
Speaker 1: does require some mass and some energy to store that information.

855
00:39:43,600 --> 00:39:45,279
Speaker 1: You want to put bits on a hard drive, you

856
00:39:45,320 --> 00:39:47,360
Speaker 1: want to write numbers in the sahara and filled them

857
00:39:47,400 --> 00:39:50,919
Speaker 1: with kerosene. That definitely costs energy, right, And all stored

858
00:39:51,040 --> 00:39:55,000
Speaker 1: energy does have some mass, But increasing the information on

859
00:39:55,040 --> 00:39:58,680
Speaker 1: something doesn't increase its mass. So connecting back to Mark's question,

860
00:39:58,960 --> 00:40:01,279
Speaker 1: he's asking does data have mass? And data does not

861
00:40:01,360 --> 00:40:03,680
Speaker 1: have mass? Right, And remember that when you're putting a

862
00:40:03,719 --> 00:40:06,080
Speaker 1: picture of your dog onto the SD card, you're not

863
00:40:06,120 --> 00:40:08,719
Speaker 1: like downloading electrons and not flowing onto there. You're just

864
00:40:08,800 --> 00:40:12,000
Speaker 1: moving electrons up or down. You're just flipping switches on

865
00:40:12,120 --> 00:40:14,600
Speaker 1: that card, so you're not adding matter to it in

866
00:40:14,640 --> 00:40:17,200
Speaker 1: any way. You're not changing the energy of the card.

867
00:40:17,440 --> 00:40:20,200
Speaker 1: You're just flipping a switch, which doesn't require any more

868
00:40:20,280 --> 00:40:22,719
Speaker 1: or less energy. It requires energy to build a card,

869
00:40:22,960 --> 00:40:25,520
Speaker 1: and it requires energy to change things on the card.

870
00:40:25,760 --> 00:40:27,440
Speaker 1: But the card is not heavier because you put a

871
00:40:27,440 --> 00:40:29,600
Speaker 1: picture of a dog rather than a picture of the

872
00:40:29,600 --> 00:40:32,239
Speaker 1: Earth or a picture of an exoplanet, or like the

873
00:40:32,239 --> 00:40:35,120
Speaker 1: equations of quantum gravity, which wuld be very surprising that

874
00:40:35,200 --> 00:40:38,360
Speaker 1: anybody to find have a lot of information but wouldn't

875
00:40:38,360 --> 00:40:41,080
Speaker 1: have any more mass than any other arrangement of those

876
00:40:41,120 --> 00:40:45,160
Speaker 1: electrons or bits or sticks or flaming letters in.

877
00:40:45,120 --> 00:40:46,440
Speaker 3: The Sahara course lots.

878
00:40:46,560 --> 00:40:50,000
Speaker 1: But there is one other fascinating connection between information and

879
00:40:50,200 --> 00:40:53,000
Speaker 1: mass which people may have heard about. It's called the

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00:40:53,040 --> 00:40:57,120
Speaker 1: beckensteam bound, which talks about the amount of information you

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00:40:57,160 --> 00:41:00,200
Speaker 1: can have in a space, because it turns out there

882
00:41:00,239 --> 00:41:02,799
Speaker 1: is a limit to how much information you can put

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00:41:02,840 --> 00:41:05,560
Speaker 1: in a volume of space, and it turns out that's

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00:41:05,560 --> 00:41:09,440
Speaker 1: a black hole. Right, The most information dense arrangement of

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00:41:09,560 --> 00:41:13,120
Speaker 1: matter or energy is a black hole. So black holes

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00:41:13,120 --> 00:41:17,160
Speaker 1: have the maximum amount of information. It's called the Beckenstein bound.

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00:41:17,239 --> 00:41:20,040
Speaker 1: Beckenstein is a student who work with Stephen Hawking. Doesn't

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00:41:20,040 --> 00:41:22,680
Speaker 1: get enough credit for hawking radiation and all the black

889
00:41:22,680 --> 00:41:26,399
Speaker 1: hole work that he did with Hawking, but super genius guy. Now,

890
00:41:26,400 --> 00:41:28,960
Speaker 1: this doesn't mean, as you often hear in popular science,

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00:41:29,200 --> 00:41:31,960
Speaker 1: that if you have too much information something will collapse

892
00:41:31,960 --> 00:41:35,040
Speaker 1: into a black hole. Like if you download enough amazing

893
00:41:35,120 --> 00:41:37,359
Speaker 1: pictures of dogs under your computer, it's going to turn

894
00:41:37,400 --> 00:41:40,280
Speaker 1: into a black hole. That's not the problem. It means

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00:41:40,320 --> 00:41:43,280
Speaker 1: that if you need to store a huge amount of information,

896
00:41:43,760 --> 00:41:45,520
Speaker 1: the only way to do it is a black hole.

897
00:41:45,560 --> 00:41:49,080
Speaker 1: A black hole is like the most information dense system

898
00:41:49,160 --> 00:41:49,680
Speaker 1: you can have.

899
00:41:49,840 --> 00:41:50,640
Speaker 3: So if you need to.

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00:41:50,600 --> 00:41:53,279
Speaker 1: Increase the amount of information you're storing, you might need

901
00:41:53,320 --> 00:41:55,759
Speaker 1: to increase the mass of your system so much so

902
00:41:55,840 --> 00:41:57,080
Speaker 1: that you get a black hole.

903
00:41:57,520 --> 00:41:59,960
Speaker 2: Well, you know, DNA is also supposed to be very

904
00:42:00,080 --> 00:42:02,160
Speaker 2: information dents, and there are people who are arguing that

905
00:42:02,200 --> 00:42:05,440
Speaker 2: when we can easily print DNA sequences, we might want

906
00:42:05,440 --> 00:42:08,680
Speaker 2: to start storing data in DNA and sticking it in freezers.

907
00:42:09,080 --> 00:42:12,279
Speaker 2: That sounds complicated to me, but we'll see what the

908
00:42:12,280 --> 00:42:12,880
Speaker 2: future holds.

909
00:42:12,960 --> 00:42:15,160
Speaker 1: Yeah, but DNA is an amazing storage system because it

910
00:42:15,239 --> 00:42:17,440
Speaker 1: lasts for a long long time compared to hard drives.

911
00:42:17,680 --> 00:42:19,319
Speaker 1: You put something on a hard drive, you think, oh,

912
00:42:19,320 --> 00:42:21,440
Speaker 1: it's there, but five years later you come back, it

913
00:42:21,480 --> 00:42:24,640
Speaker 1: could be totally degraded. So if you have like really

914
00:42:24,760 --> 00:42:27,040
Speaker 1: valuable information the secrets to quantum gravity are on a

915
00:42:27,120 --> 00:42:30,080
Speaker 1: hard drive in your closet, make sure you're upgrading those

916
00:42:30,160 --> 00:42:32,360
Speaker 1: every couple of years because that stuff fades.

917
00:42:32,640 --> 00:42:35,480
Speaker 2: You are making me very nervous about the videos from

918
00:42:35,480 --> 00:42:37,640
Speaker 2: my PhD that are still sitting in the closet a

919
00:42:37,640 --> 00:42:40,279
Speaker 2: decade on that need to be analystt We.

920
00:42:40,239 --> 00:42:42,719
Speaker 1: Have a real problem with digital storage. People think it's

921
00:42:42,719 --> 00:42:44,960
Speaker 1: forever because it's ones and zeros, but it's not, and

922
00:42:45,040 --> 00:42:47,319
Speaker 1: actually a lot of the old analog systems we have

923
00:42:47,719 --> 00:42:51,360
Speaker 1: last longer. Like my favorite story is computer punch cards.

924
00:42:51,719 --> 00:42:54,399
Speaker 1: My dad did his graduate thesis on the computer using

925
00:42:54,400 --> 00:42:56,520
Speaker 1: punch cards. I remember being in the computer room as

926
00:42:56,520 --> 00:42:58,239
Speaker 1: he would like insert them and pick them up.

927
00:42:58,280 --> 00:43:00,840
Speaker 3: And the cool thing about punch cards is totally resilient.

928
00:43:00,880 --> 00:43:04,480
Speaker 1: They'll last a long long time, right, yea, So he

929
00:43:04,560 --> 00:43:06,799
Speaker 1: still has like stacks of punch cards that you could

930
00:43:06,800 --> 00:43:09,560
Speaker 1: still run if the computer was around. But nobody has

931
00:43:09,560 --> 00:43:12,400
Speaker 1: a hard drive from like nineteen eighty four that still works.

932
00:43:12,840 --> 00:43:15,399
Speaker 1: So back up all your stuff, folks, and don't create

933
00:43:15,440 --> 00:43:17,880
Speaker 1: black holes. The Mark, you can keep adding pictures of

934
00:43:17,920 --> 00:43:20,400
Speaker 1: your dog to your SD card without making it heavier.

935
00:43:21,000 --> 00:43:23,320
Speaker 1: So let's check in with Mark see if that answered

936
00:43:23,320 --> 00:43:23,880
Speaker 1: his question.

937
00:43:24,360 --> 00:43:27,719
Speaker 10: Thanks for answering my question, guys. I think I'm fundamentally

938
00:43:27,760 --> 00:43:30,919
Speaker 10: more enlightened now. I found it interesting how the view

939
00:43:30,960 --> 00:43:35,400
Speaker 10: on data and mass extended into information value and information

940
00:43:35,640 --> 00:43:40,560
Speaker 10: entropy and also information density. Pops Bekenstein can have a

941
00:43:40,600 --> 00:43:46,240
Speaker 10: side hustle selling high density branded SD codes. Anyway, Thanks

942
00:43:46,280 --> 00:43:48,080
Speaker 10: again and keep up with the good work.

943
00:43:48,520 --> 00:43:50,960
Speaker 2: All right, everyone, thanks for listening today. If you have

944
00:43:51,040 --> 00:43:52,960
Speaker 2: a question you want to ask us right to us

945
00:43:53,000 --> 00:43:55,840
Speaker 2: at Questions at Daniel and Kelly dot org. We answer

946
00:43:55,880 --> 00:43:58,120
Speaker 2: every question we get, some of them end up on

947
00:43:58,160 --> 00:44:00,000
Speaker 2: the show, and we'd love to know what you're thinking about.

948
00:44:00,320 --> 00:44:03,239
Speaker 1: We really do, because it's not just our curiosity it

949
00:44:03,239 --> 00:44:06,520
Speaker 1: fuels this show. It's your curiosity, your desire, your deep

950
00:44:06,640 --> 00:44:10,319
Speaker 1: need to understand the nature of this extraordinary universe. So

951
00:44:10,400 --> 00:44:13,120
Speaker 1: right to us two questions at Daniel and Kelly dot org.

952
00:44:20,040 --> 00:44:23,880
Speaker 2: Daniel and Kelly's Extraordinary Universe is produced by iHeartRadio. We

953
00:44:23,920 --> 00:44:26,480
Speaker 2: would love to hear from you, We really would.

954
00:44:26,640 --> 00:44:29,400
Speaker 1: We want to know what questions you have about this

955
00:44:29,600 --> 00:44:31,240
Speaker 1: extraordinary universe.

956
00:44:31,320 --> 00:44:34,280
Speaker 2: We want to know your thoughts on recent shows, suggestions

957
00:44:34,280 --> 00:44:37,279
Speaker 2: for future shows. If you contact us, we will get

958
00:44:37,320 --> 00:44:37,719
Speaker 2: back to you.

959
00:44:38,000 --> 00:44:41,520
Speaker 1: We really mean it. We answer every message. Email us

960
00:44:41,560 --> 00:44:44,000
Speaker 1: at Questions at danieland Kelly.

961
00:44:43,840 --> 00:44:45,920
Speaker 2: Dot org, or you can find us on social media.

962
00:44:46,000 --> 00:44:49,799
Speaker 2: We have accounts on x, Instagram, Blue Sky and on

963
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Speaker 2: all of those platforms. You can find us at d

964
00:44:52,280 --> 00:44:53,840
Speaker 2: and Kuniverse.

965
00:44:54,040 --> 00:44:55,560
Speaker 3: Don't be shy, write to us.