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Speaker 1: Hey, Daniel, how many physicists are there in the world

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Speaker 1: right now?

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Speaker 2: Ooh, good question. I think there are about ten thousand

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Speaker 2: physics professors just in the US.

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Speaker 1: WHOA, but that's a lot of physics professors though, And now,

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Speaker 1: how would you rank them if you had to rank them?

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Speaker 2: That depends how you rain by height, by hygiene, by

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Speaker 2: number of Nobel Prizes, so many different directions.

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Speaker 1: I don't think you want to rate them by hygiene.

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Speaker 1: I don't want to be the president who does that survey.

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Speaker 2: I don't know what's more embarrassing most hygienic physicists or at.

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Speaker 1: Least yeah, and which one gives you more cred as

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Speaker 1: a physicist?

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Speaker 2: I want to know the correlation between hygiene and Nobel Prizes.

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Speaker 1: Well, that's a good metric, maybe Nobel prizes. Has anyone

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Speaker 1: won more than one Nobel Prize in physics?

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Speaker 2: One guy won the Nobel Prize twice. John Bardeen won

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Speaker 2: in fifty six and seventy two. And there are some

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Speaker 2: families where fathers and sons wanted.

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Speaker 1: Must be quite a bookcase there in their house. But

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Speaker 1: there must be a huge number of physicists who haven't

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Speaker 1: won a Nobel Prize.

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Speaker 2: Most of us.

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Speaker 1: I guess maybe you could rank yourself as the number

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Speaker 1: one physicists in the world named Daniel Whitson.

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Speaker 2: I mean, I hope so.

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Speaker 3: Have you looked?

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Speaker 1: Are there any other I mean there must be other

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Speaker 1: Daniel Whitson's out there.

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Speaker 3: Could one of them be a physicist?

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Speaker 2: There aren't many of us. I have a distant cousin

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Speaker 2: in the UK named Daniel Whitson who's an artist.

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Speaker 3: And then if they listen to this podcast and the

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Speaker 3: technically they would be physicists too.

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Speaker 2: I have some competition.

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Speaker 3: Yeah, I'll rank you both in the artistic ability.

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Speaker 2: Sounds good.

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Speaker 1: I am Horehemmerk, cartoonists and the author of Oliver's Great

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Speaker 1: Big Universe.

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Speaker 2: I'm Daniel. I'm a particle physicist and until recently I

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Speaker 2: thought I was probably the number one Daniel Whitson particle

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Speaker 2: physicist in the world.

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Speaker 1: Until recently, you mean, like thirty seconds ago. Mm hm,

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Speaker 1: yeah exactly. I just got downgraded. Yeah, well, maybe you

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Speaker 1: need to take out the competition, cut off the podcast

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Speaker 1: so that the other Daniel Whitson can't listen.

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Speaker 2: No, I want to create more physicists, man, I'm just

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Speaker 2: gonna have to work on my artistic skills to round

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Speaker 2: out my portfolio.

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Speaker 3: I thought you were going to say you wanted to

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Speaker 3: create more. Daniel Whitson's how's that going.

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Speaker 2: Well, I'm married to a biologist, so let's see if

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Speaker 2: she can get cloning to work in the lab.

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Speaker 3: Oh man, But if she clones you, would you still

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Speaker 3: be with you? What if she picks a clone? What

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Speaker 3: if she finds you the number two Daniel Whitson version.

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Speaker 2: If we're clones, aren't we all the same? Are you

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Speaker 2: gonna share credit? You know, it's just red me to

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Speaker 2: take care of stuff.

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Speaker 1: I don't know that this is an existential question, Daniel.

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Speaker 1: Once the clone is created and they have a different

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Speaker 1: experience of the world, they're technically a different Daniel.

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Speaker 2: M And that's true. I guess we'll have to ask

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Speaker 2: them what they think.

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Speaker 1: Yeah, or your wife, I guess let's get her on. Well,

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Speaker 1: first she has to clone you, which might be a

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Speaker 1: little tricky and ethically questionable. Absolutely, but anyways, Welcome to

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Speaker 1: our podcast, Daniel and Jorge Explain the Universe, a production

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Speaker 1: of iHeartRadio in which we do our best to clone

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Speaker 1: our curiosity and our joy for uncovering the mysteries of

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Speaker 1: the universe. We want everyone out there to feel like

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Speaker 1: a physicist, to think like a physicist, and to be

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Speaker 1: a physicist, to use your brain to develop mathematical models

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Speaker 1: of how the universe works and to bring it to bear,

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Speaker 1: to master the universe in your own mind.

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Speaker 3: That's right.

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Speaker 1: We serve the entire universe and we try to find

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Speaker 1: the biggest, the baddest, the most interesting questions out there

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Speaker 1: about how everything works and how the cosmos is put

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Speaker 1: together to bring to you here on the podcast.

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Speaker 2: Because everybody deserves to understand the universe and to participate

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Speaker 2: in unraveling its mysteries. Some of the greatest minds in

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Speaker 2: history were not people who were academics or men of

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Speaker 2: the figuring out the way the universe worked. They were

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Speaker 2: just curious people who taught themselves to think about the

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Speaker 2: nature of reality.

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Speaker 3: That's right.

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Speaker 1: There are a lot of amazing questions out there to

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Speaker 1: ask in a lot of minds that have put their

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Speaker 1: amazing powers of observation and experiments to try to figure

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Speaker 1: out these answers. And so it's been an incredible history

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Speaker 1: of humankind trying to find the solution to the biggest

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Speaker 1: questions in the universe.

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Speaker 2: And when we look back at the story of how

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Speaker 2: humans have figured it all out. There are some names

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Speaker 2: that stand out among the others. Of course, there are

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Speaker 2: thousands of people toiling in anonymity, but a few people

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Speaker 2: have really changed the course of science, really pivoted the

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Speaker 2: way all humans thought about the nature of the world.

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Speaker 2: Of course, people like Newton and Einstein and Galileo come

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Speaker 2: to mind, but there are many, many more.

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Speaker 3: Jam as well.

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Speaker 2: Right, I was about to say, cham absolutely, yes, crest

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Speaker 2: me off. It's alphabetical. Okay, maybe not alphabetical, but there

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Speaker 2: are some bold face names that really have changed the

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Speaker 2: way everybody thinks about the nature of our universe.

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Speaker 1: Yeah, a lot of influential scientists out there throughout history,

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Speaker 1: and so a question that you can ask is how

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Speaker 1: do they rank in terms of their influence in science,

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Speaker 1: just like I guess people rank sports stars.

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Speaker 2: Right, there is this whole ridiculous cottage industry of like

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Speaker 2: asking who is the greatest of all time? You know,

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Speaker 2: is it Kobe Bryant, is it Lebron James, is it

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Speaker 2: Michael Jordan? Is it Larry Bird? Everybody's got somebody in

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Speaker 2: their camp arguing for them.

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Speaker 1: Who's the goat, greatest of all time exactly.

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Speaker 2: And mostly I think it's not actually serious. They don't

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Speaker 2: really care who's number one. It's just like a fun

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Speaker 2: way to have a conversation and to talk about these

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Speaker 2: inspiring figures.

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Speaker 1: I think some people care a lot about these rankings

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Speaker 1: and who's the goat in basketball and baseball?

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Speaker 2: So who's the greatest cartoonist of all time?

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Speaker 1: Were he?

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Speaker 2: Well?

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Speaker 3: Cham comes to mind obviously?

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Speaker 2: Which Cham was that again?

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Speaker 3: The famous one?

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Speaker 2: Okay, you mean Cham on Twitter? Whoever that is?

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Speaker 3: Yeah, there's another hoe Cham.

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Speaker 2: You told me there's some other guy who owns atjogete

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Speaker 2: cham on Twitter.

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Speaker 3: Oh no, I think somebody just opened that as me.

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Speaker 2: It could be another hohrgete Cham.

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Speaker 3: They stole me.

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Speaker 1: Yeah no, no, it's pretty clear they're trying to me.

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Speaker 3: Yeah. Yeah, or unless he isn't me, maybe I don't know.

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Speaker 2: Maybe he's your clone. But the back to the question,

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Speaker 2: who is the greatest cartoonist of all time? Other than

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Speaker 2: Jorge Cham? Oh?

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Speaker 1: Well, it probably depends on who you ask, but I

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Speaker 1: would probably say Waterson, Calvin Hobbs.

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Speaker 2: Probably yeah, solid answer.

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Speaker 1: Yeah, Peanuts, maybe Charles Schultz, those are all up there.

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Speaker 1: But yeah, you can also maybe try to do that

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Speaker 1: with scientists.

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Speaker 2: Right, Absolutely, you can, and we're going to try so.

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Speaker 1: To the end of the podcast, we'll be asking the

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Speaker 1: question who was the most influential scientist? Are you trying

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Speaker 1: to make scientists influencers?

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Speaker 3: Daniel?

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Speaker 2: Here, I'm trying to make some scientists as cool as

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Speaker 2: sports stars. You know, there should be like science bars

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Speaker 2: where people drink beer and argue loudly about who was

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Speaker 2: the greatest scientist of all time?

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Speaker 4: Hmm.

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Speaker 1: Interesting Now if that greatest scientist happens to not be

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Speaker 1: a physicist, though, what did you be offended or like?

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Speaker 1: Are we asking scientists in general just greatest physicists?

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Speaker 2: I think scientists Some of the folks that listeners mentioned

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Speaker 2: were scientists before we even really had the concept of

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Speaker 2: what physics was.

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Speaker 3: So we're going broad here.

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Speaker 2: Absolutely.

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Speaker 1: And I noticed you put this question in the past tense,

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Speaker 1: who was the most influential scientist? Do you think maybe

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Speaker 1: the most influential scientists could be alive today or are

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Speaker 1: we only looking at dead people?

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Speaker 2: Oh that's a great point. I hadn't even thought about that.

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Speaker 2: I'm reflecting my own bias here. I guess I was

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Speaker 2: thinking about people who had an impact on history, and

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Speaker 2: it's hard for somebody who just had an idea today

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Speaker 2: to have an impact on history the way Einstein did,

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Speaker 2: for example, So I think it takes a little while

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Speaker 2: for that impact play out well.

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Speaker 1: As usual, we were wondering how many people out there

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Speaker 1: had thought about this question or have an opinion, beer

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Speaker 1: or not about who is the most influential scientist.

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Speaker 2: Thanks very much to everybody who participates in this segment

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Speaker 2: of the podcast. We really appreciate your time, energy, and enthusiasm.

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Speaker 2: If you'd like to share yours for the podcast, please

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Speaker 2: don't be shy. Write to me two questions at Daniel

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Speaker 2: and Jorge dot com. So think about it for a second.

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Speaker 2: Who do you think is the most influential scientist? And

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Speaker 2: I'm going to just give you the little suggestion that

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Speaker 2: maybe I am one of the most influential scientists. But

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Speaker 2: here's what people had to say. My guess would be

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Speaker 2: the mathematician Urdos. I think it was Copernicus.

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Speaker 5: I would say it was Nicholas Fleming, who fond about antibiotics.

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Speaker 2: I would say Einstein.

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Speaker 6: I think it has to be honest with Sonedjate reaction Einstein.

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Speaker 6: But then when you start thinking about it, You've got

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Speaker 6: likes of Faraday and Newton and Baul shortly out what

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Speaker 6: box would you put him in? And could you tell

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Speaker 6: he was in the box without opening it?

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Speaker 3: Galileo Newton and Einstein.

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Speaker 5: Albert Einstein stands out Newton because it all starts with him.

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Speaker 2: Einstein's the winner there.

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Speaker 3: Charles Starwin, Charles Darwin, Bill Ny the Science Guy saying

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Speaker 3: he's the best, with Daniel of course coming in a

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Speaker 3: close second.

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Speaker 1: Every all right, some interesting answers and a lot of

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Speaker 1: names you might expect Isaac Newton, Einstein, Galileo Darwin, Bill Ny,

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Speaker 1: the science guy, Bill Ny, who's not actually a scientist

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Speaker 1: by training.

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Speaker 3: He's an engineer, which I think makes him even cooler.

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Speaker 2: Mmm. Wow, that's pretty influential.

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Speaker 1: But yeah, a lot of common names you might expect.

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Speaker 1: Aristotle as well. Was he technically a scientist or a philosopher?

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Speaker 2: Yeah, there's a long debate about when the science began

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Speaker 2: and who's doing science and who's doing philosophy and the

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Speaker 2: exact distinction between them, which always comes down to arguing

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Speaker 2: about definitions.

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Speaker 1: So how are we going to rank people then if

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Speaker 1: we don't even have a solid definition of science.

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Speaker 2: I think most of the time in these conversations is

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Speaker 2: spent arguing about how to argue about it. Really, that's

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Speaker 2: the core question. It's like, how do you measure this?

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Speaker 2: I know?

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Speaker 1: Yeah, yeah, I guess that happens in sports too, like

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Speaker 1: most trophies, most the games, more points.

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Speaker 2: Can you really be the greatest of all times if

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Speaker 2: you never want a championship even if you have the

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Speaker 2: scoring record? You know, how is Einstein's dribble against Galileo's rebounding?

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Speaker 2: This kind of stuff?

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Speaker 4: Yeah?

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Speaker 1: Yeah, And so what are we going to use on

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Speaker 1: the podcast here today? Where are we just going to

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Speaker 1: argue about how to measure the influence?

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Speaker 2: Well? I thought I was kind of looking forward to

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Speaker 2: arguing about how to measure it.

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Speaker 1: Yeah, you might have some opinions, So I see, we're

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Speaker 1: not actually going to answer the question of the episode

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Speaker 1: as usual.

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Speaker 3: I want to argue got it now?

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Speaker 2: I think probably lots of people have different opinions about

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Speaker 2: who might be the most influential, But to me, I

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Speaker 2: think the question is like who has shifted the course

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Speaker 2: of human history or human thought the most? Who would

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Speaker 2: have the most impact if you'd like deleted them from the.

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Speaker 3: Historical record, assuming that nobody else would have figured it out.

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Speaker 2: I guess, well, that is the question. You know, if

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Speaker 2: you figured out something awesome, but there were ten people

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Speaker 2: right on your tails about to figure it out, then

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Speaker 2: did you really have a singular impact on the field.

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Speaker 2: You just sort of like in first place, by zero

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Speaker 2: point oh one seconds, you didn't really have that much

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Speaker 2: of an impact on human history by that metric. But

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Speaker 2: there might be some people who had a singular vision,

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Speaker 2: who had an idea that nobody else was capable of,

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Speaker 2: and if you deleted them from human history, it might

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Speaker 2: take hundreds of years before we figured that thing out.

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Speaker 1: It sounds like you're also just kind of thinking in

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Speaker 1: terms of our thoughts and our theories about science and

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Speaker 1: how the world works. I wonder if you thought about

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Speaker 1: maybe like live say that could be another way to

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Speaker 1: measure the impact of a scientist.

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Speaker 2: Or you could also go darker and think about lives lost.

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Speaker 2: You know, some of our most influential scientists helped develop

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Speaker 2: nuclear weapons technology, for example, or other kinds of weapons

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Speaker 2: technology that resulted in lots of deaths.

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Speaker 1: Oh, we're also going dark We're also maybe consider during

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Speaker 1: the warst scientists I mean.

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Speaker 2: We just said influential, We didn't say have a positive influence, right.

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Speaker 2: For example, if you create a doomsday device and destroy

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Speaker 2: the entire planet, that's pretty influential.

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Speaker 3: Right right right, you'd be the vote, the worst of

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Speaker 3: all time.

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Speaker 2: It's just the magnitude, not the sign that matters here.

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Speaker 1: I feel like though, just by posing the question, we're

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Speaker 1: implying some sort of positive influence.

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Speaker 2: Yeah, I think so. I mean, most scientists out there

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Speaker 2: are trying to improve our lives, either specifically through developing

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Speaker 2: some technology that makes life easier or more productive, or

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Speaker 2: just in sheer understanding the nature of the universe. I

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Speaker 2: think science overall has a positive goal, and most scientists

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Speaker 2: have had a positive impact on.

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Speaker 3: Our experience, right right. Nobody wants to be the vote.

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Speaker 2: Nobody wants to be the vote.

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Speaker 1: Although I noticed you said most scientists want to have

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Speaker 1: a positive impact.

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Speaker 2: Yeah, most of us at all. Not all. I mean,

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Speaker 2: there's the guy who invented lead in gasoline, for example,

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Speaker 2: he made a whole generation dumber.

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Speaker 3: M Maybe he was the most influential signer.

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Speaker 2: It could be, or it could have been the guy

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Speaker 2: who figured that out and saved the next generation afterwards.

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Speaker 2: There's so many ways to measure it. You know, within academia,

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Speaker 2: we have our own metrics. Like if you're a professor

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Speaker 2: and you're going up for promotion, then there are ways

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Speaker 2: they measure your performance, all of which are deeply flawed,

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Speaker 2: you know, like number of papers or number of citations

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Speaker 2: of your paper. And then they have fancy metrics. One

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Speaker 2: of them is called an H index, which is number

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Speaker 2: of papers that have at least that many citations. So

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Speaker 2: if you have an H index of one hundred, it

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Speaker 2: means you have one hundred papers with at least one

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Speaker 2: hundred citations for example.

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Speaker 1: Yeah, it's a famous index in academia. Have you measured yours, Daniel.

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Speaker 2: Oh, I have a ridiculous H index because I have

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Speaker 2: more than a thousand papers because I'm a member of

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Speaker 2: the Atlas collaboration without dozens and dozens of papers every year.

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Speaker 2: So it's just totally a broken metric for somebody like me.

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Speaker 1: But if you exclude those crazy collaboration papers, isn't there

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Speaker 1: like an adjustment factor or like a handicap.

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Speaker 2: So my official H index is two hundred and eight,

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Speaker 2: which is pretty bonkers.

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Speaker 3: That's including the big collaboration papers.

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Speaker 2: Yeah, that's including the big collaboration papers. So it's not real.

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Speaker 2: I mean, just to calibrate. Somebody like Ed Witten, probably

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Speaker 2: the smartest guy on the planet right now, has an

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Speaker 2: h index of one eighty seven.

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Speaker 3: I haven't heard of him, so I guess he maybe's

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Speaker 3: not that influential.

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Speaker 2: He basically invented string theory and won the Fields Medal,

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Speaker 2: which is the best prize in mathematics as a physicist,

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Speaker 2: So definitely a smart dude.

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Speaker 1: Well, that's another way to measure things with prizes. You

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Speaker 1: said there's a physicist who's won it twice.

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Speaker 2: Yeah, there is one physicist who's won the Nobel Prize twice,

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Speaker 2: and overall there are only like two hundred physicists who've

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Speaker 2: ever won the Physics Nobel Prize.

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Speaker 1: But only one that has won it twice. M yeah,

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Speaker 1: maybe this person is the goat. Maybe, But the Nobel

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Speaker 1: Prize is famously a flawed metric. I mean, super smart people,

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Speaker 1: very well deserving like Vera Rubin and Jocelyn Burnell never

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Speaker 1: won the Nobel Prize, probably because it's by a panel

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Speaker 1: of dudes, and so it's famously biased against women and

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Speaker 1: other underrepresented minorities. So maybe not the best metric, right.

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Speaker 3: It's also biased against Daniel Whitson, which means it totally

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Speaker 3: flawed obviously.

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Speaker 2: No, it's probably actually biased towards me being a white

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Speaker 2: male Jew. So if I haven't won the Nobel Prize

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Speaker 2: so far, it's just my fault.

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Speaker 3: Well, who's this person who's won it twice? I mean,

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Speaker 3: what did they win it for?

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Speaker 2: Well, he was a physicist and an electrical engineer. He

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Speaker 2: won it in fifty six for the invention of the

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Speaker 2: transistor and then in seventy two for a theory of

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Speaker 2: super conductivity. So definitely a smart guy. What's his name,

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Speaker 2: John Bardeen?

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Speaker 1: John Bardeen invented the transistor, won the Nobel Prize for that,

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Speaker 1: and then he invented super conductivity.

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Speaker 2: He invented a theory to explain super conductivity. It's called

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Speaker 2: the BCS theory. He's the b and BCS theory.

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Speaker 1: So without this person, maybe we wouldn't have transistors, which

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Speaker 1: means we wouldn't have computers.

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Speaker 2: Yeah, pretty influential.

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Speaker 1: Wow, Okay, I would put him pretty high up on

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Speaker 1: the Goad list, especially because he is an engineer, which

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Speaker 1: automatically makes him great.

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Speaker 2: That does score him a lot of points. Yes. Also,

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Speaker 2: based on his picture from Wikipedia, he looks like he

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Speaker 2: has pretty good hygiene.

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Speaker 3: Oh oh boy, Yeah, that must be his engineering side.

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Speaker 2: Obviously. I have to say, having been to an engineering

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Speaker 2: conference or two, engineers definitely dress better than physicists.

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Speaker 3: Oh it's not that hard. He's sitting in a little bar.

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Speaker 2: Yeah, I appreciate that. Yeah, there's just a lot more

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Speaker 2: ties and clean shirts at engineering conference.

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Speaker 3: Yeah, blazers. Engineers are big into blazers.

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Speaker 1: All right, Well, this is a big question. Obviously, we

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Speaker 1: can spend several hours just talking about how to rank these.

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Speaker 1: But Daniel, you happened to interview a writer who wrote

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Speaker 1: a book sort of about this idea of who is

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Speaker 1: the most influential scientist?

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Speaker 2: That's right. I spoke to Ananio Baticharia. He's the author

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Speaker 2: of a recent book called The Man from the Future,

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Speaker 2: and in this book he lays out the case that

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Speaker 2: John von Neumann might be the most influential scientist who

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Speaker 2: ever lived.

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Speaker 1: Interesting, and John van Neuman was a scientist or an

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Speaker 1: or an engineer or.

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Speaker 2: He's definitely a physicist. I don't know if he has

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Speaker 2: any engineering credentials, but he has incredible impact over like

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Speaker 2: abstract areas of mathematics, fundamental questions and quantum mechanics, he

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Speaker 2: invented the architecture of the modern computer. He basically wrote

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Speaker 2: the book on game theory. This was definitely a smart

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Speaker 2: and influential guy.

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Speaker 3: Hmmm interesting.

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Speaker 1: All right, Well, here's Daniel's interview with author Ananio Badicharia,

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Speaker 1: author of The Man from the Future.

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Speaker 2: So then it's my pleasure to welcome to the podcast.

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Speaker 2: Onna know about Acharia. He has a PhD in biophysics

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Speaker 2: from Imperial College in London. He's been a science correspondent

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Speaker 2: at The Economist and editor at Nature and medical researcher.

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Speaker 2: Welcome to the podcast.

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Speaker 5: Thanks very much, Daniel, it's a pleasure to be here.

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Speaker 2: So you have a background in biophysics and you work

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Speaker 2: as a science journalist. Help me understand why you decided

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Speaker 2: to write a book about von Neuman.

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Speaker 4: Ah.

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Speaker 5: Yes, Well, my undergraduate degree was physics, so I've always

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Speaker 5: kind of flitted from field to field. I moved from

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Speaker 5: one thing that I knew something about into a new

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Speaker 5: field that I've known nothing about. This book was pretty

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Speaker 5: much the same. But the longer answer, I guess is

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Speaker 5: that I'd been through a few journalism jobs. I'd worked

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Speaker 5: at Nature, and then I ended up at the economist,

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Speaker 5: and over the years, I found myself hearing von Neuman's

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Speaker 5: name in all of these incredibly different contexts. So you'd

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Speaker 5: have economics correspondence talking about the latest No Bell winner

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Speaker 5: in economics, and that there would be the game theories

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Speaker 5: of von Neuman's name would come up. There, there were

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Speaker 5: people on the tech paths of the magazine and we're

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Speaker 5: talking about quantum computing, and again you'd have von Noyman's

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Speaker 5: name mentioned in that context. And then there was artificial intelligence,

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Speaker 5: and you know the people that were writing stories of

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Speaker 5: artificial intelligence. Yeah, you know, you kind of have a

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Speaker 5: have to look at what von Noyman did back back then.

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Speaker 5: So there was this guy who turned out been dead

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Speaker 5: for seventy years almost and his name was coming up

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Speaker 5: more than ever. So I really wanted to understand why

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Speaker 5: that was. And when I looked into the why of this,

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Speaker 5: rather than look around for his biography, I discovered that

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Speaker 5: there hasn't really been an attempt to try and string

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Speaker 5: all of his ideas together and explain the relevance of

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Speaker 5: this person to the twenty first century. And so that's

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Speaker 5: what I set out to do.

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Speaker 2: Well. I think he did it very well. It's a

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Speaker 2: really fun tour of all the amazing intellectual impacts that

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Speaker 2: von Norman has had. And in the book you make

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Speaker 2: a pretty strong case for him being one of the

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Speaker 2: smartest people in the twentieth century, maybe one of the

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Speaker 2: smartest people ever, which is pretty astounding. I thought it'd

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Speaker 2: be fun for us to take the listeners on a

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Speaker 2: little bit of a tour of some of his greatest accomplishments.

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Speaker 2: And I want to start with something that we talk

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Speaker 2: about on the podcast all the time, which is quantum mechanics.

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Speaker 2: You're writing the book about how he didn't invent wave

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Speaker 2: based quantum mechanics or matrix based quantum mechanics, but he

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Speaker 2: did something maybe even more difficult, which is that he

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Speaker 2: unified them. Help us understand why that was important and

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Speaker 2: why it was so difficult.

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Speaker 5: Right, So this is kind of von Neumann's post doc.

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Speaker 5: Right he's at the University of Gerzingen, and he's right

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Speaker 5: straight after his PhD. I think he's twenty two at

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Speaker 5: this stage. And when he turns up at Gerzegan, I

439
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Speaker 5: think on a fellowship from the Rockefeller he's there to

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Speaker 5: do maths, you know, he's not there to do physics.

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Speaker 5: So he's there because David Hilbert is the leading figure

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Speaker 5: in mathematics of the of the day and he is

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Speaker 5: head of the maths department at Kersingham, and so von

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Speaker 5: Norman comes as kind of his apprentice, although in a

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Speaker 5: way the apprentice has already begun to outshine the master.

446
00:21:34,000 --> 00:21:37,440
Speaker 5: But at the same time as von Neuman's there, there's

447
00:21:37,480 --> 00:21:43,040
Speaker 5: another kind of vonder kind, which is Heisenberg. And Heisenberg

448
00:21:43,119 --> 00:21:48,320
Speaker 5: has recently invented this new science called quantum mechanics, the

449
00:21:48,400 --> 00:21:53,840
Speaker 5: science I guess of atoms and atomic behavior. And his

450
00:21:54,119 --> 00:21:59,760
Speaker 5: approach is through these matrices, which are grids of numbers. Now,

451
00:22:00,520 --> 00:22:05,240
Speaker 5: Heisenberg wasn't actually deeply concerned with what these matrices were

452
00:22:05,359 --> 00:22:10,760
Speaker 5: saying about the underlying nature of what was going on

453
00:22:10,800 --> 00:22:15,520
Speaker 5: in the atom, right, So he had started with atomic spectra,

454
00:22:15,640 --> 00:22:20,120
Speaker 5: which are like what happens when you excite an atom

455
00:22:20,400 --> 00:22:25,119
Speaker 5: of neon or whatever. If you give an electric shock,

456
00:22:25,359 --> 00:22:28,119
Speaker 5: the electrons get excited, they drop back down, and they

457
00:22:28,200 --> 00:22:31,880
Speaker 5: release a photon of light of a particular wavelength. And

458
00:22:31,920 --> 00:22:34,520
Speaker 5: so you had all these spectra of different atoms, and

459
00:22:34,560 --> 00:22:38,920
Speaker 5: he was kind of trying to understand those, and that's

460
00:22:38,960 --> 00:22:43,760
Speaker 5: how quantum mechanics really began trying to mathematize this. So

461
00:22:43,800 --> 00:22:45,680
Speaker 5: he had these grids of numbers that told you about

462
00:22:45,720 --> 00:22:49,439
Speaker 5: these different energy levels that the electrons were jumping between. Now,

463
00:22:49,560 --> 00:22:52,920
Speaker 5: within a few months of this version of quantum mechanics

464
00:22:52,960 --> 00:22:55,920
Speaker 5: coming out, there was another one, and that was by Schrodinger,

465
00:22:56,400 --> 00:23:01,120
Speaker 5: and that was based on waves, which physicists were much

466
00:23:01,160 --> 00:23:08,480
Speaker 5: more comfortable with than Heisenberg's matrices. In fact, nobody initially

467
00:23:08,520 --> 00:23:11,679
Speaker 5: understood what matrices were or why they should be useful

468
00:23:11,680 --> 00:23:14,840
Speaker 5: in this way, and it took some digging around to

469
00:23:15,359 --> 00:23:18,119
Speaker 5: find out. And now matrices are kind of discussed in

470
00:23:18,440 --> 00:23:22,959
Speaker 5: high school. Now, what von Neuman began to work on

471
00:23:23,200 --> 00:23:27,680
Speaker 5: was uniting these two visions because people were like, well,

472
00:23:27,720 --> 00:23:29,760
Speaker 5: you know, you've got these waves on the one hand,

473
00:23:30,280 --> 00:23:32,680
Speaker 5: and you've got matrices on the other. You've got sort

474
00:23:32,680 --> 00:23:37,840
Speaker 5: of electrons jumping around from between energy levels in Heisenberg's

475
00:23:37,880 --> 00:23:42,080
Speaker 5: theory and enschroedingers you've got this idea that maybe particles

476
00:23:42,520 --> 00:23:45,159
Speaker 5: have wave like properties. So which one is it? And

477
00:23:45,200 --> 00:23:47,320
Speaker 5: what von Neuman does is he digs down to maths

478
00:23:47,320 --> 00:23:51,120
Speaker 5: and he proves mathematically that these are essentially two sides

479
00:23:51,960 --> 00:23:55,000
Speaker 5: of the same coin. And this is kind of like, and.

480
00:23:55,040 --> 00:23:56,960
Speaker 2: Was it clear to everybody that that was going to

481
00:23:57,040 --> 00:23:59,520
Speaker 2: be possible. I mean, I remember reading that this was

482
00:23:59,560 --> 00:24:01,920
Speaker 2: sort of an acrimonious to be there was no love

483
00:24:01,960 --> 00:24:06,119
Speaker 2: lost between Heisenberg and Schrodinger. I remember reading that Heisenberg

484
00:24:06,359 --> 00:24:09,800
Speaker 2: found schrodinger theory called repulsive, you know, and was like

485
00:24:09,840 --> 00:24:12,560
Speaker 2: offended by what Schrodinger was writing about the importance of

486
00:24:12,840 --> 00:24:16,520
Speaker 2: visualizability of these ideas exactly.

487
00:24:16,680 --> 00:24:20,119
Speaker 5: So Heisenberg, in fact, if you excuse the language, so

488
00:24:20,280 --> 00:24:25,400
Speaker 5: basically Schrodinger's theory was crap and.

489
00:24:24,520 --> 00:24:26,400
Speaker 2: In the original German somehow he said.

490
00:24:28,480 --> 00:24:30,399
Speaker 5: Exactly. There was no lot of lost between them, and

491
00:24:30,480 --> 00:24:34,400
Speaker 5: Heisenberg thought it was almost deeply unscientific to look beyond

492
00:24:35,040 --> 00:24:37,800
Speaker 5: what the maths was telling you because you couldn't see

493
00:24:37,920 --> 00:24:43,080
Speaker 5: inside an atom. And Schrodinger was hated matrices, so he

494
00:24:43,200 --> 00:24:48,320
Speaker 5: just hated this mathematical formalization, and most physicists actually were

495
00:24:48,400 --> 00:24:50,560
Speaker 5: very uncomfortable with it, so they were quite glad when

496
00:24:50,560 --> 00:24:53,560
Speaker 5: Schrodinger came along with his waves. But what people could

497
00:24:53,720 --> 00:24:58,399
Speaker 5: understand is why are these two incredibly different formalizations giving

498
00:24:58,440 --> 00:25:01,520
Speaker 5: the same answers Who's right? And it turned out that

499
00:25:01,600 --> 00:25:05,200
Speaker 5: they both were and physicists now will tend to use

500
00:25:05,800 --> 00:25:12,480
Speaker 5: the matrix approach when a problem is more tractable with matrices,

501
00:25:12,560 --> 00:25:16,040
Speaker 5: or they'll use waves when the Schrodinger equation, as it's known,

502
00:25:17,160 --> 00:25:21,760
Speaker 5: gives you better results. So but van Noyman did this

503
00:25:21,840 --> 00:25:24,560
Speaker 5: theoretical thing, and then he goes on and builds on that.

504
00:25:25,320 --> 00:25:27,960
Speaker 5: And he builds on that in two ways. One he

505
00:25:28,640 --> 00:25:34,000
Speaker 5: spins out this entire theory of how the operators, which

506
00:25:34,040 --> 00:25:36,600
Speaker 5: is like I guess the functions, the stuff that tells

507
00:25:36,640 --> 00:25:39,159
Speaker 5: you what to do to the maths, like if you

508
00:25:39,200 --> 00:25:41,239
Speaker 5: want to find the energy, what do you do to

509
00:25:41,280 --> 00:25:43,879
Speaker 5: the Schrodinger? What do you do to the description of

510
00:25:43,920 --> 00:25:46,800
Speaker 5: the equation. He looked at the entire maths of this,

511
00:25:46,880 --> 00:25:50,600
Speaker 5: and this in itself, this operator theory of Ornyman algebras

512
00:25:51,200 --> 00:25:55,200
Speaker 5: is now really it's at the cutting edge of mathematics again.

513
00:25:56,359 --> 00:25:59,359
Speaker 5: And then on the other hand, he went and laid

514
00:25:59,359 --> 00:26:05,320
Speaker 5: out the entire high kind of mathematical groundwork of quantum mechanics,

515
00:26:05,880 --> 00:26:11,520
Speaker 5: and by doing so he allowed people to ask philosophical

516
00:26:11,560 --> 00:26:16,560
Speaker 5: more philosophical questions, which again where we're now coming back to,

517
00:26:16,600 --> 00:26:19,800
Speaker 5: because if you want to build a quantum computer, for example,

518
00:26:20,200 --> 00:26:23,280
Speaker 5: you want to know, well, will we ever be able

519
00:26:23,320 --> 00:26:26,560
Speaker 5: to string cubits together? Will we ever be able to

520
00:26:26,640 --> 00:26:30,520
Speaker 5: kind of entangle these cubits and be able to do

521
00:26:30,640 --> 00:26:37,320
Speaker 5: real useful calculations with them? And to answer that question

522
00:26:37,480 --> 00:26:40,959
Speaker 5: you have to go back to what von Neumann showed

523
00:26:41,400 --> 00:26:47,239
Speaker 5: we could know with the maths. So these in some

524
00:26:47,280 --> 00:26:50,399
Speaker 5: ways what he was doing at the time was became

525
00:26:50,520 --> 00:26:55,520
Speaker 5: unfashionable in the sort of sixties, and I think it's

526
00:26:55,560 --> 00:26:58,120
Speaker 5: all come back now, which is why his name kept

527
00:26:58,119 --> 00:26:59,240
Speaker 5: coming up in this field.

528
00:27:00,000 --> 00:27:03,520
Speaker 2: It's sort of amazing the impact that mathematicians have had

529
00:27:03,760 --> 00:27:06,760
Speaker 2: on physics, just sort of like during their coffee breaks.

530
00:27:07,240 --> 00:27:10,639
Speaker 2: You know, this is like not something Neuman was targeting.

531
00:27:10,720 --> 00:27:12,800
Speaker 2: This is not like the central task of his life,

532
00:27:13,320 --> 00:27:15,840
Speaker 2: and yet he made this enormous contribution. It reminds me

533
00:27:15,880 --> 00:27:18,879
Speaker 2: of you know, Emmy and Another's theorem. It's just something she

534
00:27:18,920 --> 00:27:20,680
Speaker 2: was sort of doodled, you know, while she was being

535
00:27:20,680 --> 00:27:24,320
Speaker 2: distracted by her actual hard math problems, comes in and

536
00:27:24,400 --> 00:27:29,040
Speaker 2: makes a fundamental impact on the whole shape of modern physics.

537
00:27:29,720 --> 00:27:32,520
Speaker 2: Is that how we should understand Noyman's impact, That he

538
00:27:33,040 --> 00:27:35,520
Speaker 2: is such a genius that essentially he can make this

539
00:27:35,600 --> 00:27:37,480
Speaker 2: impact in a field that's not even his.

540
00:27:37,359 --> 00:27:43,640
Speaker 5: Own, right, So this is I find absolutely fascinating about

541
00:27:43,720 --> 00:27:44,280
Speaker 5: von Neumann.

542
00:27:44,520 --> 00:27:44,680
Speaker 2: Right.

543
00:27:45,000 --> 00:27:48,440
Speaker 5: So he writes later on this essay called The Mathematician,

544
00:27:48,800 --> 00:27:53,320
Speaker 5: where he set out his philosophy of mathematics, and he

545
00:27:53,400 --> 00:27:57,600
Speaker 5: really deeply felt that if mathematicians stray too far from

546
00:27:57,680 --> 00:28:01,200
Speaker 5: physics and the physical world and they're looking for problems,

547
00:28:02,040 --> 00:28:06,160
Speaker 5: he says that mathematics becomes baroque. I guess he means

548
00:28:06,160 --> 00:28:11,639
Speaker 5: it becomes not beautiful, not interesting, too self absorbed. So

549
00:28:11,760 --> 00:28:16,240
Speaker 5: he was constantly looking around at the world for ways

550
00:28:16,280 --> 00:28:21,000
Speaker 5: to apply mathematics. And he had this extraordinarily logical mind,

551
00:28:21,440 --> 00:28:26,000
Speaker 5: and he would kind of set something up in logical

552
00:28:26,080 --> 00:28:29,280
Speaker 5: terms and formal logical terms and then kind of bulldoze

553
00:28:29,320 --> 00:28:32,040
Speaker 5: his way through it, and a problem that it seemed

554
00:28:32,160 --> 00:28:37,040
Speaker 5: completely complicated or intractable would suddenly become simple in his hands.

555
00:28:37,280 --> 00:28:41,040
Speaker 5: And that was his approach. So from roots in looking

556
00:28:41,120 --> 00:28:44,440
Speaker 5: at abstruse mathematical logic, which is where he started, he

557
00:28:44,600 --> 00:28:49,600
Speaker 5: ends up applying kind of logic to almost every area

558
00:28:49,920 --> 00:28:53,400
Speaker 5: of cutting edge science that you can think of.

559
00:28:53,920 --> 00:28:56,800
Speaker 2: It is really amazing the impact he's had, and sometimes

560
00:28:56,800 --> 00:28:59,040
Speaker 2: his impact seems to be so great because of his

561
00:28:59,120 --> 00:29:04,040
Speaker 2: reputation that's almost closed off areas of research. Something I'm

562
00:29:04,080 --> 00:29:07,240
Speaker 2: really fascinated by is his impact on the philosophy of

563
00:29:07,280 --> 00:29:10,760
Speaker 2: quantum mechanics and these hidden variable theorems. He arrived at

564
00:29:10,760 --> 00:29:13,800
Speaker 2: this big result, this no go theorem, essentially claiming that

565
00:29:13,800 --> 00:29:16,880
Speaker 2: there could be no hidden variables in quantum mechanics. The

566
00:29:16,920 --> 00:29:20,960
Speaker 2: quantum mechanics was absolutely random. There was no possibility for

567
00:29:21,280 --> 00:29:23,880
Speaker 2: the outcome of these experiments to actually be determined by

568
00:29:24,000 --> 00:29:28,560
Speaker 2: some hidden piece of information. And that shut off basically

569
00:29:28,640 --> 00:29:31,840
Speaker 2: everybody from exploring that area and for decades until Bell

570
00:29:31,920 --> 00:29:34,400
Speaker 2: and other folks Hermann for example, discovered that there was

571
00:29:34,440 --> 00:29:37,840
Speaker 2: actually a flaw in his logic, right, that he had

572
00:29:37,920 --> 00:29:40,880
Speaker 2: essentially made a mistake. Do you see that result as

573
00:29:40,920 --> 00:29:43,400
Speaker 2: a sort of an embarrassment or a mistake or what

574
00:29:43,400 --> 00:29:44,840
Speaker 2: does that tell us about von Neumann?

575
00:29:45,400 --> 00:29:48,040
Speaker 5: So this is really interesting. So I explored this actually

576
00:29:48,200 --> 00:29:52,560
Speaker 5: in my chapter on quantum mechanics, and I get reasonably

577
00:29:52,640 --> 00:29:56,880
Speaker 5: tube into it, And the truth is, there's actually believe

578
00:29:56,920 --> 00:30:00,440
Speaker 5: it or not. All these years later, there's still debate

579
00:30:01,000 --> 00:30:04,720
Speaker 5: about what von Noyman meant. So let's unpack it a

580
00:30:04,720 --> 00:30:09,600
Speaker 5: little bit. Hidden variables theory. So imagine you were a

581
00:30:09,640 --> 00:30:13,000
Speaker 5: physicist back in I don't know, the nineteenth eighteenth century,

582
00:30:13,080 --> 00:30:16,280
Speaker 5: and you were interested in the properties of a gas, right,

583
00:30:16,800 --> 00:30:20,600
Speaker 5: so you might posit as they did, that there are

584
00:30:20,600 --> 00:30:25,160
Speaker 5: these particles bouncing around inside a box, and when you

585
00:30:25,240 --> 00:30:28,120
Speaker 5: warm them up, they bounce around even faster, and that

586
00:30:28,160 --> 00:30:31,080
Speaker 5: gives rise to the properties that you can see, like

587
00:30:31,320 --> 00:30:34,560
Speaker 5: whatever pressure and things like that you know in the

588
00:30:34,600 --> 00:30:37,640
Speaker 5: temperature of the gas. And they're hidden because at the

589
00:30:37,680 --> 00:30:42,920
Speaker 5: time nobody knew that these molecules really existed. Right now,

590
00:30:43,040 --> 00:30:47,160
Speaker 5: in quantum mechanics, we still haven't found those hidden variables. Ultimately,

591
00:30:47,320 --> 00:30:49,920
Speaker 5: what we know about quantum mechanics is it's still random.

592
00:30:49,960 --> 00:30:52,800
Speaker 5: But you're a physicist and I'm sure you'll feel me

593
00:30:52,840 --> 00:30:55,800
Speaker 5: in but deed down, it's random.

594
00:30:55,800 --> 00:30:55,920
Speaker 4: Now.

595
00:30:55,960 --> 00:31:00,400
Speaker 5: What von Noyman actually showed with his theorem wor that

596
00:31:01,120 --> 00:31:04,840
Speaker 5: if you approached quantum mechanics in the way that he did,

597
00:31:05,640 --> 00:31:08,080
Speaker 5: and to be fair to him, it is the only

598
00:31:08,200 --> 00:31:13,600
Speaker 5: self consistent mathematical approach that we know of. In a way,

599
00:31:15,120 --> 00:31:17,240
Speaker 5: he shows that if you use his maths, if you

600
00:31:17,400 --> 00:31:19,960
Speaker 5: if it's a Hilbert space, as he called it, even

601
00:31:20,000 --> 00:31:22,040
Speaker 5: though he'd done all the math. It's a Hilbert space

602
00:31:22,120 --> 00:31:25,800
Speaker 5: type theory. There's no theory that's a Hilbert space type

603
00:31:25,840 --> 00:31:30,400
Speaker 5: theory can be a hidden variables theory that explains this

604
00:31:30,560 --> 00:31:33,880
Speaker 5: kind of randomness and strange you know what, you know,

605
00:31:34,120 --> 00:31:38,000
Speaker 5: entanglement I hate you know, everybody hates it when I

606
00:31:38,080 --> 00:31:41,240
Speaker 5: say this, especially physicists. But it's what Einstein referred to

607
00:31:41,320 --> 00:31:43,600
Speaker 5: as you know, spooky action at a distance and so

608
00:31:43,640 --> 00:31:46,200
Speaker 5: on that you know, beyond that, you know, you just

609
00:31:46,240 --> 00:31:47,000
Speaker 5: have to accept that.

610
00:31:48,760 --> 00:31:50,680
Speaker 2: Let's just remind the listeners what we're talking about here

611
00:31:50,680 --> 00:31:54,360
Speaker 2: in terms of entanglement. Right, you have some situation where

612
00:31:54,400 --> 00:31:57,600
Speaker 2: like a photon decays the two particles, and so you

613
00:31:57,720 --> 00:32:00,480
Speaker 2: know something about the pair of particles. You know, because

614
00:32:00,520 --> 00:32:02,920
Speaker 2: the photon is spin zero that then the two particles

615
00:32:02,920 --> 00:32:05,160
Speaker 2: have to preserve that angle momentum. And so if one

616
00:32:05,200 --> 00:32:06,840
Speaker 2: is spin up, the other one is spinned down. And

617
00:32:06,880 --> 00:32:10,000
Speaker 2: we've talked on the podcast several times about how even

618
00:32:10,000 --> 00:32:12,720
Speaker 2: if those particles are now far apart, if one is

619
00:32:12,760 --> 00:32:14,680
Speaker 2: spin up, the other has to be spinned down, and

620
00:32:14,760 --> 00:32:18,000
Speaker 2: so measuring one of them tells you about the other one.

621
00:32:18,320 --> 00:32:21,760
Speaker 2: And the debate was about whether those things are already

622
00:32:21,800 --> 00:32:24,720
Speaker 2: determined when the particles are created and they're flying apart,

623
00:32:24,800 --> 00:32:26,920
Speaker 2: and the fact that you don't know whether one is

624
00:32:26,960 --> 00:32:28,880
Speaker 2: spin up or spin down just reflects your lack of

625
00:32:28,920 --> 00:32:31,720
Speaker 2: knowledge that it actually is already determined, or if the

626
00:32:31,800 --> 00:32:36,080
Speaker 2: universe essentially waits, if it's undetermined and it's only fixed

627
00:32:36,200 --> 00:32:39,200
Speaker 2: when you make the measurement, which is bizarre because if

628
00:32:39,240 --> 00:32:42,560
Speaker 2: you're then measuring one particle far away from the other one,

629
00:32:42,600 --> 00:32:45,880
Speaker 2: somehow they're both determined the moment you're measuring one of them.

630
00:32:46,080 --> 00:32:48,880
Speaker 2: And so von Neuman's claim is to have proven that

631
00:32:48,920 --> 00:32:52,040
Speaker 2: it's impossible to have any hidden information that actually determines this.

632
00:32:52,520 --> 00:32:55,880
Speaker 2: But there's an important distinction right between local hidden variables

633
00:32:55,880 --> 00:33:02,080
Speaker 2: and global hidden variables, right, isn't that the issue between Okay.

634
00:33:01,680 --> 00:33:05,120
Speaker 5: Well, I'm going to leave that with you, But I

635
00:33:05,160 --> 00:33:07,880
Speaker 5: think the sticking point is that what was von Nouman

636
00:33:07,920 --> 00:33:12,320
Speaker 5: trying to show, So people now argue, was he really

637
00:33:12,400 --> 00:33:16,840
Speaker 5: ruling out all possible theories, all possible invariable theories, or

638
00:33:16,880 --> 00:33:22,000
Speaker 5: was he just ruling out a subset? And Okay, I'm biased.

639
00:33:23,480 --> 00:33:28,040
Speaker 5: I go with the historians and the physicists who are arguing,

640
00:33:28,240 --> 00:33:32,320
Speaker 5: actually he was just ruling out an important subset. But

641
00:33:32,400 --> 00:33:35,880
Speaker 5: I think you should tell people about the Bells estined

642
00:33:37,200 --> 00:33:42,720
Speaker 5: that it seems you know so far that you know this,

643
00:33:42,720 --> 00:33:46,840
Speaker 5: this view has kind of survived quite well in a way.

644
00:33:47,080 --> 00:33:50,360
Speaker 2: Yeah, that's right. The idea that there's local information that

645
00:33:50,520 --> 00:33:53,520
Speaker 2: moves with the particles is ruled out by Bell's experiment,

646
00:33:54,520 --> 00:33:57,040
Speaker 2: and so by Nooman was certainly right about that. I

647
00:33:57,080 --> 00:33:59,600
Speaker 2: think what Bell was astounded by is that his experiment

648
00:33:59,680 --> 00:34:02,880
Speaker 2: and all Nouman's theories don't rule out global hidden variables,

649
00:34:02,880 --> 00:34:05,160
Speaker 2: the idea that there could be like some pilot wave

650
00:34:05,320 --> 00:34:08,239
Speaker 2: controlling the universe. And I agree with you, that's a

651
00:34:08,400 --> 00:34:11,920
Speaker 2: very strange idea of the universe. On the other hand,

652
00:34:11,960 --> 00:34:14,640
Speaker 2: it's not ruled out by these experiments, right, it could

653
00:34:14,680 --> 00:34:18,200
Speaker 2: actually be our universe. What's fascinating to me is the

654
00:34:18,239 --> 00:34:21,560
Speaker 2: impact one man can have on the field. Whether he

655
00:34:21,640 --> 00:34:24,600
Speaker 2: intended to rule out global hidden variables or not. That

656
00:34:24,760 --> 00:34:27,319
Speaker 2: was the understanding. People were like, oh, well, you can't

657
00:34:27,320 --> 00:34:30,000
Speaker 2: go there. Noman's been there, and you know he doesn't

658
00:34:30,000 --> 00:34:32,919
Speaker 2: get stuff wrong. So if he shut the door, don't

659
00:34:32,920 --> 00:34:33,920
Speaker 2: even bother opening it.

660
00:34:34,480 --> 00:34:37,880
Speaker 5: Yeah, I mean, and that was purely based on his

661
00:34:38,080 --> 00:34:43,400
Speaker 5: reputation for just coming in and solving problems, just solving

662
00:34:43,440 --> 00:34:47,880
Speaker 5: these intractable problems. So you know, partly it's his fault

663
00:34:48,040 --> 00:34:52,560
Speaker 5: because he never done worked back and said, well, actually,

664
00:34:52,640 --> 00:34:55,440
Speaker 5: you know, that's not what I meant, because he's already

665
00:34:55,480 --> 00:34:59,040
Speaker 5: moved on to something else. But there's a really interesting

666
00:35:00,080 --> 00:35:03,520
Speaker 5: passage in Boehm, who came up with Bohemian you know,

667
00:35:03,560 --> 00:35:07,280
Speaker 5: the Bomian sort of wave theory, which is hidden variable's theory,

668
00:35:07,600 --> 00:35:09,560
Speaker 5: and he says he gave his lecture in front of

669
00:35:09,640 --> 00:35:14,800
Speaker 5: von Neuman, and von Neuman didn't contradict me. So even

670
00:35:14,880 --> 00:35:19,200
Speaker 5: Bohm is in awe of von Momen. Yeah, quite right.

671
00:35:19,320 --> 00:35:22,040
Speaker 2: Yeah, it tells something about the power of personality. So

672
00:35:22,320 --> 00:35:25,160
Speaker 2: let's move on to a completely separate topic where von

673
00:35:25,200 --> 00:35:28,600
Speaker 2: Neuman made a huge impact, and that's two computers. As

674
00:35:28,640 --> 00:35:31,080
Speaker 2: I think you were saying earlier, every computer we're using,

675
00:35:31,200 --> 00:35:35,480
Speaker 2: almost every computer ever built, follows a von Neumann architecture.

676
00:35:36,200 --> 00:35:38,279
Speaker 2: What does that mean? Why is it so influential?

677
00:35:39,080 --> 00:35:39,200
Speaker 5: All?

678
00:35:39,280 --> 00:35:39,440
Speaker 3: Right?

679
00:35:39,480 --> 00:35:43,280
Speaker 5: Well, in short, it was the first description, the first

680
00:35:43,320 --> 00:35:47,840
Speaker 5: logical description of a modern programmable computer, right, and it

681
00:35:47,880 --> 00:35:50,160
Speaker 5: came out, I think with his first draft of a

682
00:35:50,239 --> 00:35:53,440
Speaker 5: report on the DVAC, which I believe was nineteen forty six.

683
00:35:55,160 --> 00:36:00,480
Speaker 5: So before this there were computers, but there were kind

684
00:36:00,520 --> 00:36:03,640
Speaker 5: of plugboard type things, and if you wanted them to

685
00:36:03,680 --> 00:36:07,200
Speaker 5: do something else, then you had to switch around the

686
00:36:07,239 --> 00:36:11,960
Speaker 5: wires and unplug them. And this was a pretty involved job. Now,

687
00:36:12,239 --> 00:36:15,040
Speaker 5: our smartphones don't work that way, our laptops don't work

688
00:36:15,080 --> 00:36:19,480
Speaker 5: that way. They run programs. And what Fulnoyment described was,

689
00:36:19,880 --> 00:36:23,000
Speaker 5: in broad terms, a machine that would have a very

690
00:36:23,080 --> 00:36:28,160
Speaker 5: large working memory. It would have a kind of control

691
00:36:28,239 --> 00:36:32,640
Speaker 5: unit central process, so that would shuttle instructions back and forth,

692
00:36:34,120 --> 00:36:37,120
Speaker 5: and you know, input and output and so on, and

693
00:36:37,840 --> 00:36:43,520
Speaker 5: that general architecture, general description of what a computer should

694
00:36:43,560 --> 00:36:47,239
Speaker 5: look like, despite it having drawbacks. Right, there's something called

695
00:36:47,239 --> 00:36:50,840
Speaker 5: the von Nooyment bottleneck. So if your computer ever freezes

696
00:36:51,400 --> 00:36:55,680
Speaker 5: and you know, you see, you know, whatever whatever they

697
00:36:55,760 --> 00:37:00,000
Speaker 5: have nowadays, if it's a whirling clock face or something

698
00:37:00,280 --> 00:37:02,800
Speaker 5: like that, then it's got stuck in the full Noyment bottleneck.

699
00:37:02,840 --> 00:37:05,239
Speaker 5: And that's because instruction. Too many instructions are trying to

700
00:37:05,760 --> 00:37:08,880
Speaker 5: go in and out between the memory and the central

701
00:37:08,920 --> 00:37:11,799
Speaker 5: process or at the same time. But we haven't really

702
00:37:11,800 --> 00:37:16,279
Speaker 5: found a better way to do computing. I mean, people

703
00:37:16,320 --> 00:37:18,719
Speaker 5: are working on it and sure there's attempts to do

704
00:37:18,760 --> 00:37:23,120
Speaker 5: parallel computing, and of course deep neural networks don't work

705
00:37:23,160 --> 00:37:26,480
Speaker 5: that way. But in terms of almost all the computers

706
00:37:26,480 --> 00:37:28,759
Speaker 5: that we're likely to use, they still work on the

707
00:37:28,760 --> 00:37:29,920
Speaker 5: ful noiment architecture.

708
00:37:30,239 --> 00:37:33,359
Speaker 2: Yeah, it's hard to overestimate the influence of this kind

709
00:37:33,400 --> 00:37:34,960
Speaker 2: of piece of work. And when you're at the very

710
00:37:35,000 --> 00:37:37,399
Speaker 2: beginning of the field, you can sort of like set

711
00:37:37,440 --> 00:37:41,719
Speaker 2: the whole direction of the international community by making these

712
00:37:41,760 --> 00:37:44,120
Speaker 2: choices about like how much memory do you have and

713
00:37:44,160 --> 00:37:47,160
Speaker 2: how do instructions get moved from memory to the CPU,

714
00:37:47,200 --> 00:37:49,960
Speaker 2: and the whole idea of having like a central processing

715
00:37:50,080 --> 00:37:53,120
Speaker 2: unit and memory that seems so basic to us, But

716
00:37:53,160 --> 00:37:54,840
Speaker 2: it could have gone another way, right, it could have

717
00:37:54,840 --> 00:37:57,399
Speaker 2: been if we didn't have of Unknoyment or somebody else

718
00:37:57,520 --> 00:38:01,360
Speaker 2: organized computers, our entire computer are chitecture could be different.

719
00:38:01,800 --> 00:38:04,319
Speaker 2: It's fascinating to dig into these details that really at

720
00:38:04,320 --> 00:38:07,560
Speaker 2: the foundation of our entire technological society.

721
00:38:08,160 --> 00:38:12,400
Speaker 5: Yes, and of course, you know, I try and unpack

722
00:38:12,480 --> 00:38:17,279
Speaker 5: these things in the book to show that unlike in

723
00:38:17,320 --> 00:38:21,120
Speaker 5: many biographies of you know, in inverted coom as great men, right,

724
00:38:21,280 --> 00:38:25,879
Speaker 5: von Neuman was influenced by others, and he influenced others, right,

725
00:38:26,320 --> 00:38:28,279
Speaker 5: So I do think, and I tried to show that

726
00:38:28,320 --> 00:38:31,360
Speaker 5: he came out with these nuggets these he was in

727
00:38:31,400 --> 00:38:34,240
Speaker 5: the right place at the right time. But his ideas

728
00:38:34,239 --> 00:38:36,959
Speaker 5: were built upon by lesions of people, and he drew

729
00:38:37,120 --> 00:38:39,480
Speaker 5: also on the ideas of legions of people, and of

730
00:38:39,520 --> 00:38:41,680
Speaker 5: course that got him into trouble. I mean, when you

731
00:38:41,719 --> 00:38:45,320
Speaker 5: look at the Vat report, he was working with the

732
00:38:46,320 --> 00:38:51,120
Speaker 5: group who had invented the Aniac computer. Now, the Aniac

733
00:38:51,520 --> 00:38:53,800
Speaker 5: you have to get you know, your string of adjective

734
00:38:53,800 --> 00:38:55,720
Speaker 5: is right when you come to describe these things. Otherwise

735
00:38:55,719 --> 00:39:00,320
Speaker 5: computer historians get very annoyed with you. But it wasn't

736
00:39:00,480 --> 00:39:06,360
Speaker 5: strictly programmable, but it was digital, it was electronic. It

737
00:39:06,440 --> 00:39:09,640
Speaker 5: had lots of things going for it. But it was

738
00:39:09,640 --> 00:39:15,200
Speaker 5: initially invented to calculate where shells would land during the war,

739
00:39:15,239 --> 00:39:17,839
Speaker 5: which was a huge problem, and it was also a

740
00:39:17,920 --> 00:39:21,360
Speaker 5: problem during the First World War. But by the time

741
00:39:21,800 --> 00:39:24,200
Speaker 5: the NIAC was ready to run, the war was over

742
00:39:24,320 --> 00:39:26,960
Speaker 5: and so they needed other problems for it to solve,

743
00:39:27,480 --> 00:39:31,680
Speaker 5: and there had been some talk within the group. So

744
00:39:31,800 --> 00:39:36,640
Speaker 5: Mockley and Ekert were the designers of the original Eniac

745
00:39:37,280 --> 00:39:40,400
Speaker 5: and there were some too, well, we really should you

746
00:39:40,719 --> 00:39:44,840
Speaker 5: have a big memory, and Ekert invented this big new memory,

747
00:39:44,880 --> 00:39:49,000
Speaker 5: the Mercury delay line. And but what von Neuman did was,

748
00:39:49,239 --> 00:39:53,239
Speaker 5: using this incredible logical mind that he had, was coalesced

749
00:39:53,239 --> 00:39:56,759
Speaker 5: these ideas into a single document and then without his

750
00:39:56,880 --> 00:39:59,680
Speaker 5: permission or the permission of the team, of course, this

751
00:39:59,800 --> 00:40:05,560
Speaker 5: was circulated widely across the world to every group, practically

752
00:40:05,600 --> 00:40:07,880
Speaker 5: every group in the world that was working on a

753
00:40:07,960 --> 00:40:12,279
Speaker 5: kind of Nassin computer. And that was Goldstein who was

754
00:40:13,000 --> 00:40:16,040
Speaker 5: involved in the any App project. And then there's this

755
00:40:16,120 --> 00:40:20,839
Speaker 5: acrimonious falling out. But then Van Norman moves and he

756
00:40:21,120 --> 00:40:24,120
Speaker 5: sets up his own computing project at the Institute for

757
00:40:24,160 --> 00:40:27,040
Speaker 5: Advanced Study, and he puts all of the patterns in

758
00:40:27,080 --> 00:40:31,320
Speaker 5: the public domain. But even more importantly, when they're building

759
00:40:31,360 --> 00:40:34,880
Speaker 5: this computer, which is it's one of the first program computers,

760
00:40:34,920 --> 00:40:39,640
Speaker 5: but it's not the first, he sends every single report,

761
00:40:39,840 --> 00:40:44,480
Speaker 5: every progress report along the way is published. And this

762
00:40:44,800 --> 00:40:48,759
Speaker 5: in fact proves to have an even bigger impact on

763
00:40:49,239 --> 00:40:53,480
Speaker 5: computing than the EDVAC report where he describes this architecture.

764
00:40:53,840 --> 00:40:56,600
Speaker 5: So it's kind of a true ProMED attack. And I

765
00:40:56,719 --> 00:40:59,320
Speaker 5: say in the book that. Wow, I asked, more or

766
00:40:59,360 --> 00:41:01,319
Speaker 5: less ask the question. It makes I think it makes

767
00:41:01,360 --> 00:41:05,440
Speaker 5: him the godfather of open source computing as well, in

768
00:41:05,480 --> 00:41:12,799
Speaker 5: a way becaus had Mocklely and Eckert succeeded in patenting

769
00:41:13,200 --> 00:41:15,880
Speaker 5: the computer. It might be it might be a different world.

770
00:41:15,880 --> 00:41:17,480
Speaker 5: Progress might be slower. Who knows.

771
00:41:17,719 --> 00:41:20,200
Speaker 2: Who knows, because Van Norman is not just like a

772
00:41:20,239 --> 00:41:23,880
Speaker 2: smart guy in some rooms scriveling with equations. He's a

773
00:41:24,000 --> 00:41:27,200
Speaker 2: very clever man, right in terms of strategy, as you

774
00:41:27,200 --> 00:41:31,200
Speaker 2: were saying, essentially invented game theory, starting from like analyzing

775
00:41:31,239 --> 00:41:33,960
Speaker 2: how living room board games go all the way up

776
00:41:34,000 --> 00:41:37,760
Speaker 2: to thinking about nuclear strategy. Tell us about the impact

777
00:41:37,880 --> 00:41:39,080
Speaker 2: he made on game theory.

778
00:41:39,880 --> 00:41:43,560
Speaker 5: Yeah, so some people see game theory as the product

779
00:41:43,600 --> 00:41:48,040
Speaker 5: of a of a fairly cynical mind, and so he's

780
00:41:48,040 --> 00:41:50,960
Speaker 5: had to bad press for that. But the more I

781
00:41:51,080 --> 00:41:55,040
Speaker 5: kind of dug into his personality, the more I felt

782
00:41:55,080 --> 00:41:57,440
Speaker 5: that that was a bit simple minded in a way,

783
00:41:57,440 --> 00:42:01,040
Speaker 5: it was. It was a very complex person. So you

784
00:42:01,120 --> 00:42:03,880
Speaker 5: have to bear in mind that he's Jewish, and he

785
00:42:03,960 --> 00:42:09,120
Speaker 5: starts his life in a very wealthy, privileged Jewish family.

786
00:42:09,280 --> 00:42:12,360
Speaker 5: Is dad's a banker. He's kind of used to living

787
00:42:12,440 --> 00:42:15,959
Speaker 5: the good life. And I get the feeling that from

788
00:42:16,000 --> 00:42:22,120
Speaker 5: his youth. Really he thinks more or less the best

789
00:42:22,120 --> 00:42:24,600
Speaker 5: of people. He doesn't really understand people. He has a

790
00:42:24,680 --> 00:42:31,359
Speaker 5: fairly you know, he's a mathematician, and he's extremely an

791
00:42:31,400 --> 00:42:36,480
Speaker 5: extremely able mathematician, but I don't think he was completely

792
00:42:36,520 --> 00:42:40,280
Speaker 5: ofa with how other people thought or felt.

793
00:42:40,560 --> 00:42:40,759
Speaker 2: Right.

794
00:42:41,600 --> 00:42:44,279
Speaker 5: But then what happens is there are two things. One

795
00:42:44,440 --> 00:42:48,920
Speaker 5: is that in his native Hungary, in Budapest, a communist

796
00:42:49,719 --> 00:42:55,319
Speaker 5: government installs itself after the First World War, and it's

797
00:42:55,360 --> 00:42:59,839
Speaker 5: pretty brutal. But then they get overthrown by a kind

798
00:42:59,880 --> 00:43:04,919
Speaker 5: of reactionary, sort of right wing government, and that that's

799
00:43:04,960 --> 00:43:07,840
Speaker 5: even more bruce. Although in there are hangings in the street.

800
00:43:08,320 --> 00:43:13,719
Speaker 5: It's just awful. And his message from this is like,

801
00:43:13,920 --> 00:43:18,040
Speaker 5: I don't like totalitarianism at all. So he's he already

802
00:43:18,080 --> 00:43:22,080
Speaker 5: begins to come out against that. And then by nineteen

803
00:43:22,120 --> 00:43:25,600
Speaker 5: thirty he's already seeing something terrible is happening in Germany.

804
00:43:25,640 --> 00:43:27,800
Speaker 5: He just censors it and in his letters start to

805
00:43:27,840 --> 00:43:31,919
Speaker 5: get filled with premonitions of disaster, of a second World War.

806
00:43:32,000 --> 00:43:35,560
Speaker 5: He thinks some you know, Germany, which he kind of

807
00:43:35,760 --> 00:43:39,560
Speaker 5: sees as the center of the intellectual universe. Really he

808
00:43:39,600 --> 00:43:43,879
Speaker 5: sees it beginning to go strive with anti Semitism, and

809
00:43:43,920 --> 00:43:47,160
Speaker 5: so Princeton offers him a job in nineteen thirty and

810
00:43:47,160 --> 00:43:51,760
Speaker 5: he's gone right, and he sees what's happening from Afar,

811
00:43:53,120 --> 00:43:57,080
Speaker 5: and he hates the Nazis. He hates the Nazis, he

812
00:43:57,120 --> 00:44:03,000
Speaker 5: hates Communism. He really really spises what's happening there. And

813
00:44:03,040 --> 00:44:05,319
Speaker 5: he loses as a result of the Nazis. You know,

814
00:44:05,360 --> 00:44:08,720
Speaker 5: this this great country that he saw, Germany, he sees,

815
00:44:08,800 --> 00:44:14,040
Speaker 5: you know, the people getting behind Hitler or many of them,

816
00:44:14,440 --> 00:44:18,400
Speaker 5: and he loses. He completely loses in someways his faith

817
00:44:18,640 --> 00:44:24,120
Speaker 5: in human nature. So game theory is kind of the

818
00:44:24,160 --> 00:44:27,880
Speaker 5: product of somebody who's trying to understand human nature and

819
00:44:27,960 --> 00:44:31,239
Speaker 5: trying also to apply his logical mind to it, but

820
00:44:32,040 --> 00:44:35,520
Speaker 5: almost in a kind of I can't really go know

821
00:44:35,560 --> 00:44:39,000
Speaker 5: what's going on inside you, So I'm just going to

822
00:44:39,040 --> 00:44:41,120
Speaker 5: try and do my best with what I've got, which

823
00:44:41,160 --> 00:44:43,799
Speaker 5: is how you behave And the way that you've behaved

824
00:44:44,200 --> 00:44:51,080
Speaker 5: recently is not that great, so you know, And famously

825
00:44:51,840 --> 00:44:55,759
Speaker 5: his first wife divorces him, Marriott, she's also from a

826
00:44:55,760 --> 00:44:58,200
Speaker 5: fairly wealthy Jewish background, and then she goes on to

827
00:44:58,320 --> 00:45:02,760
Speaker 5: kind of great things herself. She becomes this amazing science

828
00:45:03,320 --> 00:45:07,480
Speaker 5: administrator who sets up brooke Haven Lab. I think. She

829
00:45:07,560 --> 00:45:11,600
Speaker 5: leaves him because he spends too much time thinking. She

830
00:45:11,680 --> 00:45:14,600
Speaker 5: runs off for the post talk I think, and ends

831
00:45:14,680 --> 00:45:20,400
Speaker 5: up getting married. So but their agreement for their daughter

832
00:45:21,000 --> 00:45:27,160
Speaker 5: is still with us today, thankfully. Marina is that for

833
00:45:27,239 --> 00:45:31,319
Speaker 5: the first fourteen I think years, she will spend most

834
00:45:31,360 --> 00:45:35,879
Speaker 5: of her time with her mum, and then only spend

835
00:45:35,920 --> 00:45:40,120
Speaker 5: the holidays with her dad, and then at fourteen, when

836
00:45:40,120 --> 00:45:44,200
Speaker 5: she kind of reaches the age of maturity. From fourteen onwards,

837
00:45:44,239 --> 00:45:47,120
Speaker 5: she'll stay with her dad most of the time and

838
00:45:47,239 --> 00:45:50,680
Speaker 5: visit her mom and her stepdad shuring the holidays. Now,

839
00:45:50,880 --> 00:45:56,200
Speaker 5: vol Nouman remarries pretty quickly to another Hungarian Jewish lady,

840
00:45:56,520 --> 00:46:01,960
Speaker 5: Clara Dan, who ends up becoming the first modern computer programmer. Book.

841
00:46:02,280 --> 00:46:06,320
Speaker 5: But it's kind of quite a tense household, as Marina says,

842
00:46:06,400 --> 00:46:10,799
Speaker 5: it's it was quite naive of these two people to

843
00:46:10,880 --> 00:46:14,120
Speaker 5: imagine that the teenage years are the age of rationality

844
00:46:14,160 --> 00:46:20,279
Speaker 5: and reason, but that's what ended up happening, and so

845
00:46:20,600 --> 00:46:23,880
Speaker 5: kind of game theories formulated to try and make some

846
00:46:23,880 --> 00:46:27,920
Speaker 5: some sense, because you have to remember that before for Neumann,

847
00:46:28,480 --> 00:46:31,479
Speaker 5: you know this, this was just considered impossible. And now

848
00:46:32,120 --> 00:46:36,200
Speaker 5: game theory has become more complex and has tried to

849
00:46:36,200 --> 00:46:41,560
Speaker 5: take into account real human behavior, right, but until for

850
00:46:41,760 --> 00:46:45,480
Speaker 5: Neuman's early proofs, there was nobody had made any inroads

851
00:46:46,080 --> 00:46:46,799
Speaker 5: on this at all.

852
00:46:47,320 --> 00:46:50,080
Speaker 2: I think it's really impressive when people tackle a completely

853
00:46:50,120 --> 00:46:53,080
Speaker 2: new field and try to bring it to heal mathematically

854
00:46:53,480 --> 00:46:57,839
Speaker 2: something which seems maybe impossible to describe our ability any

855
00:46:57,880 --> 00:47:00,680
Speaker 2: success to you know, describe the physical universe in all

856
00:47:00,719 --> 00:47:04,440
Speaker 2: of its incredible complexity, using simple mathematical laws. I'm in

857
00:47:04,480 --> 00:47:06,800
Speaker 2: awe of it when somebody can take the first stab,

858
00:47:06,880 --> 00:47:10,120
Speaker 2: you know, that's like that's really doing science. And so

859
00:47:10,280 --> 00:47:12,640
Speaker 2: in your book and some of the opening passages, you

860
00:47:12,719 --> 00:47:16,040
Speaker 2: make this comment that many people think that von Neumann

861
00:47:16,120 --> 00:47:20,280
Speaker 2: is smarter than Einstein, smarter than godel I actually pulled

862
00:47:20,280 --> 00:47:22,480
Speaker 2: some of my listeners and I asked them, said, who

863
00:47:22,480 --> 00:47:24,760
Speaker 2: do you think is the most influential scientists of all time?

864
00:47:25,280 --> 00:47:27,480
Speaker 2: And you know, the results are basically what you would expect.

865
00:47:27,480 --> 00:47:30,440
Speaker 2: Einstein gets a lot of mentions, Newton got Leo Darwin,

866
00:47:30,680 --> 00:47:34,080
Speaker 2: somebody said Aristotle, somebody commented Bill kni a science guy.

867
00:47:34,600 --> 00:47:40,000
Speaker 2: You know, Noimen wasn't up there. What do you think

868
00:47:40,040 --> 00:47:43,520
Speaker 2: about this comparison? What's your argument that Norman was essentially

869
00:47:43,520 --> 00:47:45,120
Speaker 2: one of the smartest people ever, one of the most

870
00:47:45,160 --> 00:47:48,279
Speaker 2: influential scientists, And why do you think he hasn't penetrated

871
00:47:48,320 --> 00:47:50,279
Speaker 2: to the wider public consciousness?

872
00:47:50,840 --> 00:47:53,680
Speaker 5: So some people just get better pressed, right, I mean,

873
00:47:55,280 --> 00:47:58,680
Speaker 5: Einstein had gray hair, think later in his life, and

874
00:47:58,800 --> 00:48:04,600
Speaker 5: so people tend to forgive him various interesting parts of

875
00:48:04,640 --> 00:48:09,040
Speaker 5: his personal life and so on. And you know, nobody

876
00:48:09,080 --> 00:48:12,480
Speaker 5: remembers Paul Poincare, who had come up with quite a

877
00:48:12,520 --> 00:48:16,640
Speaker 5: lot of the special theory of relativity before before Einstein,

878
00:48:16,760 --> 00:48:20,040
Speaker 5: and you know, lots of names care forgotten and Gaus.

879
00:48:20,080 --> 00:48:22,040
Speaker 5: You know, how could you not how could you not

880
00:48:22,080 --> 00:48:25,960
Speaker 5: watching gas Yeah, exactly exactly, And I think I think

881
00:48:26,640 --> 00:48:29,680
Speaker 5: part of the reason is, I think in the public

882
00:48:29,719 --> 00:48:33,560
Speaker 5: mind there's this view of the great genius, right, they're

883
00:48:33,600 --> 00:48:39,040
Speaker 5: working alone, they're usually a theorist, and Einstein just fits

884
00:48:39,160 --> 00:48:42,439
Speaker 5: into this category brilliantly, doesn't he. And you can name

885
00:48:42,480 --> 00:48:45,719
Speaker 5: what Einstein did, it's relativity, you know, And if if

886
00:48:45,760 --> 00:48:48,760
Speaker 5: you're lucky, you remember a couple of years equals mc squared.

887
00:48:48,880 --> 00:48:52,160
Speaker 5: I wanted von Neuman do Okay, if you get somewhere,

888
00:48:52,200 --> 00:48:54,160
Speaker 5: you go, oh, he had something to do with the

889
00:48:54,280 --> 00:48:57,399
Speaker 5: programmable computer. But the story is complicated. But he did

890
00:48:57,440 --> 00:49:01,399
Speaker 5: all of these other things, and I think stringing those

891
00:49:01,440 --> 00:49:04,480
Speaker 5: together and making sense of them is a difficult task.

892
00:49:04,520 --> 00:49:06,680
Speaker 5: And I promise you I spent two half years on this.

893
00:49:07,360 --> 00:49:10,680
Speaker 5: It wasn't easier. Mathematicians have told me told me this

894
00:49:10,719 --> 00:49:15,880
Speaker 5: as well, So so it's a complicated story and making

895
00:49:15,920 --> 00:49:20,480
Speaker 5: some sense of that is hard. And then I think

896
00:49:20,600 --> 00:49:23,920
Speaker 5: von Neumann more than more than many. You have to

897
00:49:23,960 --> 00:49:26,360
Speaker 5: tell the whole story. You have to show his influence,

898
00:49:26,440 --> 00:49:28,359
Speaker 5: you have to follow it down to the present day,

899
00:49:28,760 --> 00:49:33,600
Speaker 5: because for many years, in fact, what you got was

900
00:49:33,960 --> 00:49:38,240
Speaker 5: von Neuman's, you know, stories of kind of arithmetical brilliance.

901
00:49:38,640 --> 00:49:40,879
Speaker 5: So he'd turn up at some party and somebody would

902
00:49:40,880 --> 00:49:44,160
Speaker 5: ask him, you know, some crazy puzzle and he'd solve

903
00:49:44,239 --> 00:49:48,480
Speaker 5: it just like that. But that doesn't really tell you

904
00:49:49,200 --> 00:49:51,960
Speaker 5: the deep stuff that he did, the fact that he

905
00:49:52,120 --> 00:49:56,480
Speaker 5: was so ahead on so many things, from the computer

906
00:49:56,600 --> 00:50:02,200
Speaker 5: to game theory, all of which really has aped modern life.

907
00:50:02,280 --> 00:50:04,880
Speaker 5: So you know, we were just talking about game theory,

908
00:50:04,920 --> 00:50:07,960
Speaker 5: and it's a little known fact that Google, Amazon, all

909
00:50:08,000 --> 00:50:12,839
Speaker 5: of these companies their algorithms. You know, what gives them

910
00:50:13,080 --> 00:50:18,360
Speaker 5: eighty percent of their profits is advertising, often and the

911
00:50:18,680 --> 00:50:23,080
Speaker 5: algorithms that run their advertising platforms a game theoretical, right,

912
00:50:23,239 --> 00:50:26,200
Speaker 5: So Vonnoima is responsible for that eighty percent, and then

913
00:50:26,239 --> 00:50:29,680
Speaker 5: the other twenty percent comes from computing. That's the other

914
00:50:30,560 --> 00:50:33,560
Speaker 5: as is responsible for that other twenty percent two. But

915
00:50:33,680 --> 00:50:36,680
Speaker 5: to get there to truly appreciate that, you know, it's

916
00:50:36,719 --> 00:50:39,000
Speaker 5: a it's a tough story, I think, and it's a

917
00:50:39,040 --> 00:50:41,880
Speaker 5: tough sell. You can't just go, ah, yeah, it was

918
00:50:41,920 --> 00:50:46,719
Speaker 5: this and this and it's how science works. But I

919
00:50:46,760 --> 00:50:52,279
Speaker 5: don't think many people even now are ready to appreciate

920
00:50:52,480 --> 00:50:56,279
Speaker 5: how science really works. And to appreciate Vonnoima properly, I

921
00:50:56,280 --> 00:50:58,719
Speaker 5: think I think you need to kind of acknowledge that, yes,

922
00:50:59,280 --> 00:51:02,440
Speaker 5: he was, as I say, one of the smartest people.

923
00:51:02,600 --> 00:51:06,880
Speaker 5: Maybe you know, Einstein was in some ways a deeper thinker,

924
00:51:07,000 --> 00:51:11,719
Speaker 5: and you know, he had a degree of scientific imagination,

925
00:51:11,760 --> 00:51:14,879
Speaker 5: which I think von Norman envied. But then that wasn't

926
00:51:14,880 --> 00:51:17,319
Speaker 5: what von Noyman was about. Von Norman was about distilling,

927
00:51:17,480 --> 00:51:23,600
Speaker 5: almost like magic, the essential logic of particular things. And

928
00:51:23,640 --> 00:51:26,319
Speaker 5: that's also a gift, and you know he was a

929
00:51:26,360 --> 00:51:28,360
Speaker 5: mathematician and not a theoretical physicist.

930
00:51:28,360 --> 00:51:42,640
Speaker 4: So yeah, well.

931
00:51:42,480 --> 00:51:44,959
Speaker 2: What do you think is the value in this sort

932
00:51:45,000 --> 00:51:48,520
Speaker 2: of like ranking the greatest genius in history? Is it

933
00:51:48,560 --> 00:51:50,000
Speaker 2: sort of the way we talk about, you know, who

934
00:51:50,080 --> 00:51:53,360
Speaker 2: was the best footballer ever? Was it Jordan or Lebron?

935
00:51:53,440 --> 00:51:55,480
Speaker 2: The best basketball player ever? Is it just like a

936
00:51:55,480 --> 00:51:58,720
Speaker 2: fun conversation or do you think there's like real historical

937
00:51:58,840 --> 00:52:01,960
Speaker 2: or intellectual value in like trying to put these people

938
00:52:02,560 --> 00:52:03,560
Speaker 2: on a spectrum?

939
00:52:03,800 --> 00:52:05,880
Speaker 5: Yeah, I'm not a fan of it. I'm not a

940
00:52:05,920 --> 00:52:09,839
Speaker 5: fan of it, but you want to draw people into

941
00:52:10,560 --> 00:52:14,440
Speaker 5: absolutely fascinating stories. And the way that I approach this

942
00:52:14,560 --> 00:52:18,120
Speaker 5: story is more is almost a technological history of the

943
00:52:18,200 --> 00:52:21,880
Speaker 5: twentieth twenty first century, right, So von Noyman is to

944
00:52:22,000 --> 00:52:24,719
Speaker 5: me the essential thread that runs through everything from the

945
00:52:24,760 --> 00:52:31,000
Speaker 5: atom bomb to game theory to his proof that machines

946
00:52:31,040 --> 00:52:36,120
Speaker 5: can reproduce, which I fear we may yet think of

947
00:52:36,239 --> 00:52:42,080
Speaker 5: as his most important work yet. So I think if

948
00:52:42,160 --> 00:52:45,400
Speaker 5: we you know, you start ranking, it's a fun parlor game,

949
00:52:47,000 --> 00:52:50,279
Speaker 5: but with the best of it, you start to probe, well,

950
00:52:50,280 --> 00:52:54,239
Speaker 5: what do we actually mean by that? And you know

951
00:52:54,280 --> 00:52:57,719
Speaker 5: who uses relativity day to day. We all use computers, right,

952
00:52:57,840 --> 00:53:01,319
Speaker 5: I know, relativity is yes, everybody's to jump down my

953
00:53:01,400 --> 00:53:05,960
Speaker 5: throat and say GPS blah blah blah setting satellites up. Yes, yes, yes,

954
00:53:06,280 --> 00:53:09,920
Speaker 5: but you know the stuff that affects us from the

955
00:53:10,040 --> 00:53:15,680
Speaker 5: economy to the way even though we think about optimizing

956
00:53:15,719 --> 00:53:18,880
Speaker 5: our lives as if it's some game theory algorithm, you know,

957
00:53:19,200 --> 00:53:24,320
Speaker 5: as if we're maximizing utility, right, that's the way. Certainly

958
00:53:24,360 --> 00:53:27,600
Speaker 5: many people in Silicon Valley tend to think about these things. Well,

959
00:53:27,680 --> 00:53:30,120
Speaker 5: hang on, what are the mathematical assumptions I underlie this

960
00:53:30,480 --> 00:53:33,799
Speaker 5: how we ended up here of all places?

961
00:53:34,120 --> 00:53:34,359
Speaker 1: Right?

962
00:53:34,960 --> 00:53:39,960
Speaker 5: And so if we start to have those discussions, then great,

963
00:53:40,160 --> 00:53:44,080
Speaker 5: rank away. But you know, if it's otherwise, it's just

964
00:53:44,120 --> 00:53:45,799
Speaker 5: like a rather sterile debate, isn't it.

965
00:53:45,920 --> 00:53:48,040
Speaker 2: Yeah. Well, I think the real value is in just

966
00:53:48,200 --> 00:53:51,280
Speaker 2: understanding the impact that one person can have on the world,

967
00:53:51,640 --> 00:53:54,360
Speaker 2: and that just with your mind, just thinking, just solving

968
00:53:54,400 --> 00:53:58,480
Speaker 2: puzzles and being curious, you can change the whole future

969
00:53:58,600 --> 00:54:01,799
Speaker 2: history of the human race. Incredible. I hope that inspires

970
00:54:02,080 --> 00:54:04,200
Speaker 2: young people out there, you know that who is the

971
00:54:04,239 --> 00:54:07,400
Speaker 2: next von Neuman? It makes me wonder Well, thanks very

972
00:54:07,480 --> 00:54:09,799
Speaker 2: much for joining us on the podcast today. It Brooke

973
00:54:09,880 --> 00:54:12,120
Speaker 2: was really fun. I learned a lot about physics and

974
00:54:12,160 --> 00:54:16,000
Speaker 2: technology and history. Tell everyone where they can find it.

975
00:54:16,560 --> 00:54:20,600
Speaker 5: Yeah, it is available in all good bookshops and online.

976
00:54:21,040 --> 00:54:22,440
Speaker 5: It's called A Man for the Future.

977
00:54:22,600 --> 00:54:24,400
Speaker 2: All right, thanks very much for joining us today.

978
00:54:24,719 --> 00:54:25,880
Speaker 5: Thank you very much, Saniel.

979
00:54:26,600 --> 00:54:28,520
Speaker 3: All Right, Well, he makes a pretty good case for

980
00:54:28,800 --> 00:54:29,360
Speaker 3: von Neuman.

981
00:54:29,800 --> 00:54:32,480
Speaker 2: Yeah. One thing about von Neuman is that people who

982
00:54:32,560 --> 00:54:35,600
Speaker 2: knew him tended to consider him the smartest person they

983
00:54:35,680 --> 00:54:38,719
Speaker 2: ever met. Even people who like New Einstein and New

984
00:54:38,760 --> 00:54:42,000
Speaker 2: Girdle and New Nuther and stuff like that. There's something

985
00:54:42,040 --> 00:54:45,040
Speaker 2: about this guy that, just like Reedy, it's smartness when

986
00:54:45,080 --> 00:54:49,560
Speaker 2: you talk to him, and that should count. I don't

987
00:54:49,560 --> 00:54:52,080
Speaker 2: know if that should count, but it's one reason why

988
00:54:52,280 --> 00:54:55,919
Speaker 2: he's so well respected among academics that I have met him,

989
00:54:56,360 --> 00:54:58,719
Speaker 2: who have met him, Yeah, exactly. And the lore of

990
00:54:58,800 --> 00:55:01,160
Speaker 2: von Neuman has also probably it through the field. I mean,

991
00:55:01,200 --> 00:55:03,319
Speaker 2: in the interview we talked about that one time he

992
00:55:03,400 --> 00:55:06,480
Speaker 2: made a claim about quantum mechanics which was technically incorrect

993
00:55:06,680 --> 00:55:09,400
Speaker 2: and shut down a whole area of research for decades

994
00:55:09,480 --> 00:55:12,560
Speaker 2: and decades because everybody was like, well, von Neuman figured

995
00:55:12,600 --> 00:55:14,680
Speaker 2: that out, So I'm sure he was right even though

996
00:55:14,680 --> 00:55:16,320
Speaker 2: he was actually wrong in that case.

997
00:55:16,840 --> 00:55:19,839
Speaker 3: And so what he was wrong, Yeah, that doesn't sound

998
00:55:19,880 --> 00:55:20,920
Speaker 3: like positive influence.

999
00:55:21,480 --> 00:55:23,520
Speaker 2: Well, Anania makes the case that he wasn't wrong, he

1000
00:55:23,600 --> 00:55:26,960
Speaker 2: was just misunderstood. He was proving something else. So this

1001
00:55:27,640 --> 00:55:30,680
Speaker 2: is a long debate in philosophy ex science about what

1002
00:55:30,760 --> 00:55:33,879
Speaker 2: exactly von Norman was proving and whether people misunderstood him

1003
00:55:33,920 --> 00:55:36,120
Speaker 2: or whether he made a mistake or whatever.

1004
00:55:36,800 --> 00:55:40,600
Speaker 1: And remind me how many Nobel prizes did he win?

1005
00:55:40,920 --> 00:55:41,240
Speaker 2: Zero?

1006
00:55:42,160 --> 00:55:44,080
Speaker 3: Zero? That's too less than my guy.

1007
00:55:45,719 --> 00:55:47,600
Speaker 2: Yeah, that's right. And now that he's dead, he can't

1008
00:55:47,640 --> 00:55:50,279
Speaker 2: ever win any Nobel prizes, so he'll never catch up

1009
00:55:50,280 --> 00:55:50,960
Speaker 2: to your dude.

1010
00:55:51,440 --> 00:55:52,239
Speaker 3: Yep, yep.

1011
00:55:52,440 --> 00:55:54,239
Speaker 2: But that's only because he died young. He died in

1012
00:55:54,360 --> 00:55:56,720
Speaker 2: nineteen fifty seven, so he didn't really have a chance

1013
00:55:56,880 --> 00:55:59,200
Speaker 2: because you know, you can't win the Nobel Prize posthumously.

1014
00:55:59,400 --> 00:56:01,560
Speaker 2: So he had this huge impacts on science, and then

1015
00:56:01,600 --> 00:56:03,759
Speaker 2: he died, the Nobel Prize didn't really have a chance

1016
00:56:03,800 --> 00:56:04,960
Speaker 2: to give him any of these prizes.

1017
00:56:06,560 --> 00:56:08,560
Speaker 1: Well, I guess that's one thing you should add to

1018
00:56:08,560 --> 00:56:11,120
Speaker 1: your agenda is stay alive as long as possible to

1019
00:56:11,120 --> 00:56:13,600
Speaker 1: increase your chances of being the greatest of all time.

1020
00:56:14,080 --> 00:56:17,520
Speaker 2: Step one, figure out something awesome. Step two, stay alive

1021
00:56:17,560 --> 00:56:19,799
Speaker 2: to collect prizes. I'm still working on step one.

1022
00:56:19,880 --> 00:56:22,080
Speaker 3: Well no, now you have to figure out three amazing

1023
00:56:22,160 --> 00:56:24,080
Speaker 3: things to be my guy.

1024
00:56:24,280 --> 00:56:24,920
Speaker 2: True.

1025
00:56:24,840 --> 00:56:31,520
Speaker 1: Yeah, all right, Well, an interesting discussion about influence and science,

1026
00:56:31,680 --> 00:56:35,000
Speaker 1: about big ideas and how sometimes that influence can be

1027
00:56:35,080 --> 00:56:36,280
Speaker 1: positive or negative.

1028
00:56:36,600 --> 00:56:39,200
Speaker 2: Either way, everybody who's thinking about the universe is having

1029
00:56:39,200 --> 00:56:41,920
Speaker 2: an impact on the human experience. So go out there,

1030
00:56:42,080 --> 00:56:45,440
Speaker 2: keep thinking, asking questions, and pushing forward the forefront of

1031
00:56:45,520 --> 00:56:46,720
Speaker 2: human knowledge.

1032
00:56:46,320 --> 00:56:48,520
Speaker 3: And let the universe influence you.

1033
00:56:48,880 --> 00:56:51,719
Speaker 2: Even if you'll never be number one on his list.

1034
00:56:51,680 --> 00:56:53,480
Speaker 1: You can be number two, Daniel. You can be the

1035
00:56:53,560 --> 00:56:55,640
Speaker 1: number two Daniel Watson I've ever met.

1036
00:56:55,760 --> 00:56:58,279
Speaker 2: I don't want your pity. No thanks, I'm gonna earn it.

1037
00:56:58,360 --> 00:56:58,520
Speaker 4: Man.

1038
00:56:58,840 --> 00:57:02,120
Speaker 3: Wait, no, it's a great What are you talking about?

1039
00:57:02,200 --> 00:57:03,279
Speaker 2: Number two of two?

1040
00:57:03,560 --> 00:57:08,399
Speaker 3: Wow, it's better than being zero of two.

1041
00:57:09,520 --> 00:57:11,719
Speaker 2: Now zero is the first place, man, I count from zero.

1042
00:57:11,719 --> 00:57:12,680
Speaker 2: I'm a computer scientist.

1043
00:57:13,880 --> 00:57:17,720
Speaker 3: I thought you were a physicist. I don't think you

1044
00:57:17,760 --> 00:57:18,960
Speaker 3: have a degree in computer science.

1045
00:57:18,960 --> 00:57:21,000
Speaker 2: Then I have a Bachelor of Science and computer science.

1046
00:57:21,200 --> 00:57:22,000
Speaker 2: Oh all right, all.

1047
00:57:21,960 --> 00:57:27,560
Speaker 1: Right, all right, so yeah, all right, you're accredited. But anyways,

1048
00:57:27,600 --> 00:57:30,600
Speaker 1: we hope you enjoyed that. Thanks for joining us, See

1049
00:57:30,640 --> 00:57:31,200
Speaker 1: you next time.

1050
00:57:35,920 --> 00:57:39,160
Speaker 2: For more science and curiosity, come find us on social media,

1051
00:57:39,240 --> 00:57:43,800
Speaker 2: where we answer questions and post videos. We're on Twitter, Discord, Instant,

1052
00:57:43,840 --> 00:57:47,520
Speaker 2: and now TikTok. Thanks for listening, and remember that Daniel

1053
00:57:47,560 --> 00:57:50,960
Speaker 2: and Jorge Explain the Universe is a production of iHeartRadio.

1054
00:57:51,280 --> 00:57:55,160
Speaker 2: For more podcasts from iHeart Radio, visit the iHeartRadio app,

1055
00:57:55,440 --> 00:58:02,560
Speaker 2: Apple Podcasts, or wherever you listen to your favorite shows.