WEBVTT - Data Centers: Can't Live With Em, Can't Live Without Em

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<v Speaker 1>Welcome to Stuff you should know, a production of iHeartRadio.

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<v Speaker 2>Hey, and welcome to the podcast. I'm Josh, and there's

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<v Speaker 2>Chuck and Jerry's here too, and we've got our pocket

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<v Speaker 2>protectors and tape on the bridge of our glasses day

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<v Speaker 2>and this is stuff you should know.

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<v Speaker 1>Nice work. Did you just hear something?

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<v Speaker 2>No, not weird. I heard you say nice work. Yeah,

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<v Speaker 2>but then stop abruptly.

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<v Speaker 1>Well I stopped abruptly because I thought I heard a

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<v Speaker 1>little digital glitch.

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<v Speaker 2>Oh no, I didn't hear anything.

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<v Speaker 1>I might be losing my mind, then, I you know, I'm.

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<v Speaker 2>Curious whether we end up editing this out or not.

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<v Speaker 2>Any other podcast on the planet would edit that out

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<v Speaker 2>without even thinking about it. But there's like a fifty

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<v Speaker 2>percent chance that'll stay in with us.

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<v Speaker 1>I mean, this is why we didn't get that Golden

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<v Speaker 1>Globe nomination. That's right, it's kind of classic stuff you

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<v Speaker 1>should know. On professionality.

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<v Speaker 2>It's exactly right in the Italian accent, mispronunciations, there's a

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<v Speaker 2>whole laundry list. Yeah, that's okay, Chuck, I think we're

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<v Speaker 2>golden regardless.

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<v Speaker 1>Agreed.

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<v Speaker 2>So we're talking about data centers, which I had a

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<v Speaker 2>very very rough idea about But actually no, I knew

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<v Speaker 2>that they existed essentially and that they were becoming a

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<v Speaker 2>problem with the rise of AI. Yes, that was about it.

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<v Speaker 2>How about you are you are you d data center Feliac?

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<v Speaker 1>No? You know me, I'm not super technology minded, so

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<v Speaker 1>I don't know a lot about this stuff. I remember

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<v Speaker 1>walking by our server room back in the day when

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<v Speaker 1>we were at Pont City Market and seeing our colleague

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<v Speaker 1>Izzy in there hard at word yeah. And when that

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<v Speaker 1>door was unlocked and open, hearing the were of the

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<v Speaker 1>of the servers and the cooling machines, and you know,

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<v Speaker 1>that's on a smaller scale, that's a data center.

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<v Speaker 2>Absolutely, one hundred percent, that's a data center. It was

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<v Speaker 2>also so a great place to curl up and take

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<v Speaker 2>a nap in.

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<v Speaker 1>The middle of the day, like the warmth of the server.

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<v Speaker 2>Yeah, and the word put right the word yeah, So

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<v Speaker 2>uh yeah, that definitely counts as a data server. If

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<v Speaker 2>you have like one of those little home networking setups

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<v Speaker 2>in like a closet in your house, data center. Sure,

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<v Speaker 2>technically the PC is a data center. Anywhere you can

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<v Speaker 2>store and access data, that's technically a data center. And

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<v Speaker 2>you're like, well, that's stupid. Why did you even say

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<v Speaker 2>that Josh's quibbling, that's quotitian. Shut up and get on

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<v Speaker 2>with data centers. Whoa, whoa, whoa. First of all, don't

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<v Speaker 2>use the S word and then secondly word yes, Wait,

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<v Speaker 2>what did I say? That's the keyword Quoteitian?

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<v Speaker 1>Oh no, that's kW right.

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<v Speaker 2>So the reason that I bring that up, though, Chuck,

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<v Speaker 2>is because that technically is part of the progression of

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<v Speaker 2>data centers. Yeah, it probably goes without saying, but it's

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<v Speaker 2>evolved along with computing, and his computer's kind of gotten

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<v Speaker 2>bigger and bigger. The need to store and access more

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<v Speaker 2>data has gotten bigger so much so, Chuck that just

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<v Speaker 2>wrap your head around this one. In twenty twenty four,

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<v Speaker 2>just over a year ago. Yeah, we used one hundred

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<v Speaker 2>and fifty zetabytes of data. That's what we consumed. And

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<v Speaker 2>consuming is anything from making a video and uploading it

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<v Speaker 2>to TikTok or putting a post up on Instagram. It's

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<v Speaker 2>browsing a website, it's buying a song from iTunes, it's

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<v Speaker 2>doing web analytics, it's buying something with your American Express card.

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<v Speaker 2>All of that is data consumption. And we consumed one

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<v Speaker 2>hundred and fifty zetabytes of data in twenty twenty four.

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<v Speaker 1>Yeah, I don't even know how many big Max that is.

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<v Speaker 1>I know you name dropped a lot of brands. It

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<v Speaker 1>should be like the movies where every time you even

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<v Speaker 1>just say, like buy something on your amex, the bank

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<v Speaker 1>account grows by like ten dollars.

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<v Speaker 2>I agree wholeheartedly. I agree that amex should do that. Amex,

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<v Speaker 2>there's twenty bucks. I'll split it with you.

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<v Speaker 1>Wow, you just bought lunch in nineteen ninety seven.

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<v Speaker 2>That's right. So just real quick, as zeta byte, chuck

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<v Speaker 2>is a trillion gigabytes, So we consumed one hundred and

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<v Speaker 2>fifty trillion gigabytes. That was twenty twenty four.

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<v Speaker 1>That's worldwide, right, yes, yeah.

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<v Speaker 2>That's worldwide. In twenty ten, we consumed two zeta bytes. Jeez. Yeah.

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<v Speaker 2>So it's growing exponentially, which means that data centers are

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<v Speaker 2>growing exponentially. And now they're about to just blow up,

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<v Speaker 2>like truffle up essentially from you know, this kind of

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<v Speaker 2>calm like plateau that they'd reached. It's about to just

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<v Speaker 2>go in hyper drive.

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<v Speaker 1>Yeah, and actively is, and we're going we're gonna get

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<v Speaker 1>to some startling statistics later on in the episode. But

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<v Speaker 1>Kyle helped us out with this our writer over in

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<v Speaker 1>the UK.

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<v Speaker 2>He did a fantastic job.

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<v Speaker 1>He did a really good job. And there's going to

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<v Speaker 1>be some UK specific things in here because Kyle's always keen,

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<v Speaker 1>as they say, to throw that stuff in there.

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<v Speaker 2>Yeah, for sure, Kyle likes to pepper those in Yeah, of.

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<v Speaker 1>Course, and he's not barred from doing so we allow it.

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<v Speaker 1>So since Kyle, you know, is frequenter of the Wayback Machine,

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<v Speaker 1>as are all the wonderful writers that we use, they

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<v Speaker 1>all had the keys to the car. Essentially, he jumped

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<v Speaker 1>in the Wayback Machine to sort of give us a

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<v Speaker 1>little bit of a timeline on data centers and a

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<v Speaker 1>bit on you know, mainframes and PCs.

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<v Speaker 2>He also left all of his used tea bags in

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<v Speaker 2>there too. I don't know if you noticed that.

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<v Speaker 1>Oh it's fine, you know, you can throw those back

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<v Speaker 1>in some hot water and they do just a little

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<v Speaker 1>bit weaker tea.

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<v Speaker 2>Well, if you put like five of them together, it's

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<v Speaker 2>like one.

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<v Speaker 1>Yeah, and Kyle, I mean that thing was full.

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<v Speaker 2>Maybe really what he drinks a lot of tea, he

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<v Speaker 2>really does.

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<v Speaker 1>So if you want to talk about the earliest data

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<v Speaker 1>centers that you could kind of call maybe a data center.

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<v Speaker 1>They were you know, computers, they were electronic computers. Most

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<v Speaker 1>of this stuff that we're going to talk about early

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<v Speaker 1>on was military and and as you'll see, even the

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<v Speaker 1>first when we talk about the UK one that was

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<v Speaker 1>supposedly in that military, they even loaned it to the military,

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<v Speaker 1>which was kind of interesting. But these things were built

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<v Speaker 1>with you know, state of the art technology at the time,

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<v Speaker 1>which meant vacuum tubes and you know, manual switches and

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<v Speaker 1>plugs and things like that. And the first thing that

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<v Speaker 1>we can really talk about as the first programmable electric

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<v Speaker 1>digital computer was the Colossus. And as we'll see, Elon

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<v Speaker 1>Musk has now stolen that for his own purposes that

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<v Speaker 1>name probably because of this, I would imagine, but it

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<v Speaker 1>was at Bletchley Park, of course, during World War Two,

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<v Speaker 1>and they were trying to you know, crack into Hitler's

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<v Speaker 1>messages at the time, and these things were huge and

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<v Speaker 1>kind of to me. The thing that stood out about Colossus,

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<v Speaker 1>which is a neat little factoid, is that where Colossus

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<v Speaker 1>was at Bletchley Park at Block H, it is now

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<v Speaker 1>the National Museum of Computing.

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<v Speaker 2>I want to go to that so bad when we

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<v Speaker 2>do that UK up tour next year. Oh, we got

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<v Speaker 2>to go to that together.

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<v Speaker 1>Okay, okay, are we doing that next year?

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<v Speaker 2>That's what we were talking about. All right, we kind

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<v Speaker 2>of already have promised it. We have to. Now we're

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<v Speaker 2>locked in the punch.

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<v Speaker 1>Why's my voice O high?

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<v Speaker 2>Then? I don't know. You're practicing for the alph Yeah,

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<v Speaker 2>that's right now.

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<v Speaker 1>No, that that'd be a lot of fun. I'd love

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<v Speaker 1>to go to that.

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<v Speaker 2>So that was Colossus. Another one about the same time

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<v Speaker 2>was the Aniac Electrical Numerical Integrator and Computer. So that's

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<v Speaker 2>a quality acronym. Yeah, and it was the first general

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<v Speaker 2>purpose electronic computer. And here's the thing. This is technically

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<v Speaker 2>not data storage yet, it's data processing, right, But these

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<v Speaker 2>things Colossus Aniac, you walked up to them and you said,

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<v Speaker 2>what's the trajectory of this missile if I fire it

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<v Speaker 2>from here? And Aniac would go peep pop, poop, poop,

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<v Speaker 2>and then say, like, uh, whatever a trajectory is described

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<v Speaker 2>in Sure or Colossus. You'd be like, what is Hilter

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<v Speaker 2>saying here to Goebbels And the Colossus would say, Hilter

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<v Speaker 2>is saying that he's a big fan of goebels work,

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<v Speaker 2>but he's suspicious that the rest of the world doesn't

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<v Speaker 2>like either of them. And that was it. After that,

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<v Speaker 2>you'd be like, hey, what was the last answer, and

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<v Speaker 2>they'd be like, what's an answer?

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<v Speaker 1>Yeah, you gotta just tell me what's going on with

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<v Speaker 1>this Hilter business.

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<v Speaker 2>You don't remember from our art Mysteries of the Art World,

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<v Speaker 2>how stuff works are to go? Oh, the title of

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<v Speaker 2>that section was did Hilter do these pain? Oh?

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<v Speaker 1>My god, that's a deep cut. I did not remember that.

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<v Speaker 2>Yes, and I think it still says that on that

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<v Speaker 2>oh babilistical Yeah, yeah, I can only hope it's got

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<v Speaker 2>to be Hilter forever. All right.

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<v Speaker 1>So we go into mainframes at this point, and this

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<v Speaker 1>is like the nineteen fifties basically when companies could actually

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<v Speaker 1>have their own computer. It wasn't just the military. These

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<v Speaker 1>were the old punch card computers, and they were called mainframes.

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<v Speaker 1>It wasn't made up for this. Mainframes were originally described

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<v Speaker 1>We're describing like what you would house telecommunication equipment and

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<v Speaker 1>maybe some other sciencey stuff, but it was referencing literally

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<v Speaker 1>the cabinets that held this technology. And it became known

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<v Speaker 1>as just you know, it kind of took over when

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<v Speaker 1>the computer's world started using it as computer only.

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<v Speaker 2>Yeah, but again, this is like you're a company and

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<v Speaker 2>this is where you store and process all of your data,

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<v Speaker 2>and it's in this one room, but it's not going

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<v Speaker 2>anywhere else. It's not for anybody else, and you have

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<v Speaker 2>to physically be in the room to get your answer,

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<v Speaker 2>process whatever data you're looking for. When the PC came along,

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<v Speaker 2>and then the Mac and Tosh came along, they took

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<v Speaker 2>that thing and just made it very small so you

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<v Speaker 2>could put it on all of your employee's desks. And

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<v Speaker 2>now they had, like I was saying, before, their own

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<v Speaker 2>little data center right there. So if you said, like, hey,

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<v Speaker 2>what's the I need to know the Q four reports,

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<v Speaker 2>they'd say, go to Debbie's desk. Debbie's is the one

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<v Speaker 2>who's got that on her computer. And you would go

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<v Speaker 2>over there and say, WI, what's the Q four report?

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<v Speaker 2>And w would give it to you. Right, there was

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<v Speaker 2>no connectivity, but you could still like do a lot

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<v Speaker 2>more stuff than you could when you had a mainframe. Yeah,

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<v Speaker 2>for sure, which makes mainframes feel like really outdated, but

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<v Speaker 2>it turns out they're like totally still in use. Today.

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<v Speaker 1>Oh yeah, absolutely, I do want to jump back in

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<v Speaker 1>time a little bit, because I did. I promised talk

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<v Speaker 1>of lending the military, oh basically your equipment, and that's

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<v Speaker 1>what happened. In nineteen fifty one, there was a T

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<v Speaker 1>shop chain in the UK. I don't know if it's

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<v Speaker 1>still around, Lions Lyns, and they were the very first

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<v Speaker 1>company in the world that used a mainframe. It was

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<v Speaker 1>called the LEO, the l EO, and it was you know,

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<v Speaker 1>like what you would think they've handled, like payroll and

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<v Speaker 1>stock management and stuff like that, but there wasn't a

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<v Speaker 1>lot for it to do at a T shop chain

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<v Speaker 1>except for those couple of things. And so they calculated

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<v Speaker 1>missile trajectories like you were talking about for the Ministry

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<v Speaker 1>of Defense.

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<v Speaker 2>And that actually kind of helped establish like a I

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<v Speaker 2>guess a pay schedule. How people charged for data centers

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<v Speaker 2>to come. Yeah, it was they like you would charge

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<v Speaker 2>them for the time that they used it, or you

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<v Speaker 2>could lease it for a month. And that really started

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<v Speaker 2>to come around when IBM got in the game. They

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<v Speaker 2>became like the main frame leader in the fifties, the

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<v Speaker 2>early fifties, I think they had a unit that you

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<v Speaker 2>could lease for sixteen thousand dollars per month. That's in

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<v Speaker 2>nineteen fifty two money. And then as the things as

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<v Speaker 2>like the processors got better and smaller and faster, that

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<v Speaker 2>price came down dramatically. And then finally in the sixties

0:11:41.600 --> 0:11:46.560
<v Speaker 2>they released the IBM six System three sixty, which not

0:11:46.640 --> 0:11:51.240
<v Speaker 2>only got Apollo eleven to the moon and back, it

0:11:51.320 --> 0:11:54.559
<v Speaker 2>is a It appears in an episode of mad Men apparently.

0:11:55.160 --> 0:11:58.080
<v Speaker 1>Oh really, yeah, you usould have though, right.

0:11:58.400 --> 0:12:00.760
<v Speaker 2>No, I never did. I just saw reference to it

0:12:00.800 --> 0:12:04.960
<v Speaker 2>on the government and you knew it was the show. Yeah,

0:12:05.000 --> 0:12:07.000
<v Speaker 2>but they like you should look up pictures of it.

0:12:07.000 --> 0:12:10.280
<v Speaker 2>It's like those giant burnt orange cabinets with the real

0:12:10.320 --> 0:12:13.079
<v Speaker 2>magnetic tape. It's just beautiful. They're cool to look at.

0:12:13.160 --> 0:12:15.959
<v Speaker 1>Yeah, yeah, I remember. We've referenced the movie War Games

0:12:15.960 --> 0:12:17.839
<v Speaker 1>from our childhood in the eighties a lot, and that

0:12:18.000 --> 0:12:21.520
<v Speaker 1>the whopper for War Games was that was you know,

0:12:21.600 --> 0:12:25.000
<v Speaker 1>at that age, to see the whopper and action and

0:12:25.040 --> 0:12:30.440
<v Speaker 1>to see Matthew almost aid, Matthew Modine, Matthew Broderick hanging

0:12:30.520 --> 0:12:34.480
<v Speaker 1>up his handheld telephone receiver onto a modem to talk

0:12:34.520 --> 0:12:35.400
<v Speaker 1>to the school computer.

0:12:35.520 --> 0:12:38.720
<v Speaker 2>It was mind blowing that, Yeah, that phone in the

0:12:38.720 --> 0:12:41.360
<v Speaker 2>modem made just a really big impression on me.

0:12:41.679 --> 0:12:42.840
<v Speaker 1>Yeah, and a cool sound.

0:12:44.280 --> 0:12:45.320
<v Speaker 2>Peepoop boop.

0:12:46.400 --> 0:12:47.360
<v Speaker 1>Should we take a break?

0:12:48.120 --> 0:12:50.560
<v Speaker 2>Wait, let me talk about mainframes today though, because I

0:12:50.679 --> 0:12:52.440
<v Speaker 2>just want to give a little I don't know if

0:12:52.480 --> 0:12:55.440
<v Speaker 2>a shout out's the right term, but they are still

0:12:55.480 --> 0:12:59.760
<v Speaker 2>around because they're so reliable, Because they're so secure. You

0:12:59.800 --> 0:13:02.520
<v Speaker 2>can make it so that there's information on those things

0:13:02.559 --> 0:13:04.920
<v Speaker 2>that you again have to be physically present in the

0:13:05.000 --> 0:13:07.839
<v Speaker 2>room to access. Sure, you can put all sorts of

0:13:07.880 --> 0:13:11.200
<v Speaker 2>different layers of security. So if you're like Visa, or

0:13:11.240 --> 0:13:16.280
<v Speaker 2>you're a healthcare company, or you're the Census Bureau, you're

0:13:16.280 --> 0:13:19.599
<v Speaker 2>probably still using a main frame because you're protecting information

0:13:20.280 --> 0:13:22.640
<v Speaker 2>as tightly as you can. But those things are also

0:13:22.920 --> 0:13:27.480
<v Speaker 2>super fast and can hold huge volumes of computation at once.

0:13:27.800 --> 0:13:30.920
<v Speaker 1>Yeah, or a non Golden Globe nominated podcast.

0:13:31.640 --> 0:13:34.320
<v Speaker 2>Yeah, we've got our own main frame. Yeah, we've got

0:13:34.320 --> 0:13:36.960
<v Speaker 2>our IBM three sixty that's right.

0:13:37.840 --> 0:13:39.400
<v Speaker 1>What year was that from again, the three.

0:13:39.280 --> 0:13:40.560
<v Speaker 2>Sixty sixty four.

0:13:40.880 --> 0:13:43.679
<v Speaker 1>Yeah, yeah, that's the one. I'll just making sure we

0:13:43.720 --> 0:13:45.679
<v Speaker 1>didn't have the sixty five because that no, no, no,

0:13:45.720 --> 0:13:48.520
<v Speaker 1>the sixty buggy. Yeah, yeah, all right, we can take

0:13:48.520 --> 0:13:51.280
<v Speaker 1>that break now and we're gonna jump out of the

0:13:51.280 --> 0:13:53.520
<v Speaker 1>wayback machine and venture into the modern world.

0:13:53.440 --> 0:13:54.000
<v Speaker 2>Right after this.

0:14:24.440 --> 0:14:26.960
<v Speaker 1>All right, so we are out of the way back machine.

0:14:27.200 --> 0:14:30.280
<v Speaker 1>We're making that uh we're combining all those old tea

0:14:30.320 --> 0:14:34.680
<v Speaker 1>bags and making some still somewhat weaker tea. Yeah, it's

0:14:34.680 --> 0:14:37.160
<v Speaker 1>not too bad. It's a combination of Earl Gray and

0:14:37.480 --> 0:14:40.840
<v Speaker 1>Camma meal, all kinds of fun stuff, but not too bad.

0:14:41.560 --> 0:14:43.240
<v Speaker 1>And now we're going to talk a little bit about

0:14:43.280 --> 0:14:45.600
<v Speaker 1>when things started to ramp up, because it kind of

0:14:45.640 --> 0:14:49.560
<v Speaker 1>happened in fits and starts. And one of the biggest, uh,

0:14:49.680 --> 0:14:51.840
<v Speaker 1>I guess would it be a fitter a start was

0:14:51.880 --> 0:14:54.920
<v Speaker 1>the Internet. Because once the Internet came along, every business

0:14:54.960 --> 0:14:57.520
<v Speaker 1>in the world started using it, and so all of

0:14:57.520 --> 0:15:01.240
<v Speaker 1>a sudden you had to have a lot more data

0:15:01.400 --> 0:15:05.080
<v Speaker 1>storage and bigger data centers and bigger server rooms in

0:15:05.120 --> 0:15:08.080
<v Speaker 1>your companies, which was, you know, a pretty good thing

0:15:08.120 --> 0:15:10.520
<v Speaker 1>at the time. After the dot com bus. There were

0:15:10.720 --> 0:15:13.640
<v Speaker 1>a lot of casualties of that growth, but then things

0:15:13.720 --> 0:15:15.560
<v Speaker 1>kind of you know, the ship kind of righted itself.

0:15:15.920 --> 0:15:19.200
<v Speaker 2>Yeah, and because it was like accessible to basically every

0:15:19.400 --> 0:15:22.960
<v Speaker 2>business now, like you didn't have to buy a mainframe

0:15:23.080 --> 0:15:26.960
<v Speaker 2>you could lease space on someone else's main frame, like

0:15:26.960 --> 0:15:29.280
<v Speaker 2>you're the Ministry of Defense or something, all of a sudden.

0:15:29.560 --> 0:15:32.720
<v Speaker 2>So that led to this huge proliferation that gave the

0:15:34.080 --> 0:15:38.480
<v Speaker 2>foundation for web commerce. E commerce, that's what they used

0:15:38.520 --> 0:15:40.920
<v Speaker 2>to call it. That's an old timey term now, but

0:15:41.120 --> 0:15:44.320
<v Speaker 2>it created the ability for e commerce to start and flourish.

0:15:44.360 --> 0:15:48.920
<v Speaker 2>So this data center's scaling up to meet the needs

0:15:48.960 --> 0:15:51.640
<v Speaker 2>of the Internet and then to kind of give people

0:15:51.680 --> 0:15:53.800
<v Speaker 2>all sorts of new space and room to come up

0:15:53.840 --> 0:15:57.200
<v Speaker 2>with new stuff. That's where the digital economy came from,

0:15:57.280 --> 0:15:57.760
<v Speaker 2>right there.

0:15:58.120 --> 0:15:59.960
<v Speaker 1>Yeah, all of a sudden, you could hop on webvan

0:16:01.000 --> 0:16:02.960
<v Speaker 1>for an order a SACA groceries.

0:16:04.200 --> 0:16:08.120
<v Speaker 2>I have a friend who was all in about that.

0:16:08.760 --> 0:16:11.840
<v Speaker 1>Well man, yeah, yeah, I think I had a friend

0:16:11.840 --> 0:16:13.840
<v Speaker 1>who was pretty heavily invested.

0:16:15.200 --> 0:16:18.160
<v Speaker 2>It's but clearly it was ahead of its time. I mean, sure,

0:16:18.840 --> 0:16:22.520
<v Speaker 2>let's see, it's a post Mates and.

0:16:22.440 --> 0:16:24.160
<v Speaker 1>Well there's a lot of several of them now that

0:16:24.320 --> 0:16:25.040
<v Speaker 1>have succeeded.

0:16:25.200 --> 0:16:26.760
<v Speaker 2>Well name them, will get ten bucks each?

0:16:27.000 --> 0:16:30.600
<v Speaker 1>Well, well you just got ten for post Mates, and

0:16:30.880 --> 0:16:31.840
<v Speaker 1>you got to split that with me.

0:16:31.880 --> 0:16:33.280
<v Speaker 2>You know, I will, all right.

0:16:34.440 --> 0:16:37.600
<v Speaker 1>Cloud computing was the next big jump. When cloud computing

0:16:37.640 --> 0:16:40.520
<v Speaker 1>came around the early two thousands, or do they call

0:16:40.560 --> 0:16:44.920
<v Speaker 1>that the early oughts? I do, okay, I thought i'd

0:16:44.920 --> 0:16:47.080
<v Speaker 1>heard that come from your mouth. But that is when

0:16:47.400 --> 0:16:50.280
<v Speaker 1>you know, that was the real game changer because things

0:16:50.320 --> 0:16:53.600
<v Speaker 1>were still I mean, when cloud computing came along, people

0:16:53.640 --> 0:16:56.800
<v Speaker 1>thought of it if they didn't look too hard into it.

0:16:56.800 --> 0:16:58.680
<v Speaker 1>They thought it was just you know, floating up in

0:16:58.680 --> 0:17:01.880
<v Speaker 1>the ether somewhere. Yeah, it's it's still being stored on stuff,

0:17:01.880 --> 0:17:05.280
<v Speaker 1>it's just not being stored locally. So all of a sudden,

0:17:05.640 --> 0:17:08.920
<v Speaker 1>things were just going somewhere else for someone else to

0:17:09.000 --> 0:17:12.359
<v Speaker 1>worry about all that storage. And more importantly, they could

0:17:12.400 --> 0:17:15.000
<v Speaker 1>they could link everything together and store a lot of

0:17:15.000 --> 0:17:16.399
<v Speaker 1>stuff from a bunch of different people.

0:17:17.000 --> 0:17:21.240
<v Speaker 2>Right, So now you have data centers not just available

0:17:21.280 --> 0:17:24.400
<v Speaker 2>to somebody like a huge bank or something like that,

0:17:24.680 --> 0:17:26.920
<v Speaker 2>or the government in a shop then a bank, yeah,

0:17:27.000 --> 0:17:31.280
<v Speaker 2>or a t shop, and then to e commerce businesses.

0:17:31.440 --> 0:17:34.879
<v Speaker 2>Now it's available to you and me. So it's really

0:17:34.920 --> 0:17:38.040
<v Speaker 2>hard to remember back because the world has changed so much.

0:17:38.080 --> 0:17:41.359
<v Speaker 2>But Chuck, like two thousand and eight, two thousand and nine,

0:17:42.119 --> 0:17:46.040
<v Speaker 2>they were given us like VPN, little things that like

0:17:46.400 --> 0:17:48.400
<v Speaker 2>you could go home and work and like you would

0:17:48.520 --> 0:17:51.280
<v Speaker 2>it would never work. I'd never understood how to make

0:17:51.320 --> 0:17:53.880
<v Speaker 2>it work. Yeah, but that was like the very beginning

0:17:54.160 --> 0:17:55.960
<v Speaker 2>of how you could take your work home with you

0:17:56.119 --> 0:17:59.679
<v Speaker 2>and work from home and do things remotely like we

0:17:59.720 --> 0:18:02.720
<v Speaker 2>can now. Like it's nothing, but this led to the

0:18:02.800 --> 0:18:06.840
<v Speaker 2>rise of businesses like Dropbox. Right. So Dropbox goes to

0:18:06.960 --> 0:18:09.880
<v Speaker 2>Amazon Web Services and say, hey, we want to buy

0:18:09.880 --> 0:18:12.520
<v Speaker 2>a bunch of your cloud, right, which means that they're

0:18:12.560 --> 0:18:15.080
<v Speaker 2>going to use a bunch of like different servers and

0:18:15.119 --> 0:18:17.760
<v Speaker 2>different data centers all over the place. And then Dropbox

0:18:17.760 --> 0:18:20.360
<v Speaker 2>turns around to you and says, hey, if you give

0:18:20.400 --> 0:18:23.880
<v Speaker 2>me nineteen ninety five a month, you can have one

0:18:24.000 --> 0:18:27.800
<v Speaker 2>terabyte of data. Right. You can consume one terabyte of data, right,

0:18:28.119 --> 0:18:31.760
<v Speaker 2>and then hopefully you don't use all of that, so

0:18:31.880 --> 0:18:35.000
<v Speaker 2>they don't have to pay Amazon Web Services for stuff

0:18:35.040 --> 0:18:37.840
<v Speaker 2>they didn't use. But you're paying that nineteen ninety five

0:18:37.880 --> 0:18:40.800
<v Speaker 2>a month rather whether you use that whole terabyte or not.

0:18:41.080 --> 0:18:44.440
<v Speaker 2>It's a pretty smart business model. Would not exist at

0:18:44.480 --> 0:18:47.120
<v Speaker 2>all if the cloud didn't exist.

0:18:47.480 --> 0:18:49.680
<v Speaker 1>Yeah, as funny as you were talking about two thousand

0:18:49.680 --> 0:18:51.399
<v Speaker 1>and eight and how quaint that is, now, that's what

0:18:51.440 --> 0:18:53.800
<v Speaker 1>the year we started the show I know, I know,

0:18:53.920 --> 0:18:56.240
<v Speaker 1>it's crazy to think about it really.

0:18:56.040 --> 0:18:59.280
<v Speaker 2>Is, but imagine like working from home at that time,

0:18:59.359 --> 0:19:01.680
<v Speaker 2>it was just didn't you could know.

0:19:02.040 --> 0:19:04.280
<v Speaker 1>It was kind of great you went home and you homed.

0:19:04.600 --> 0:19:07.359
<v Speaker 2>That's exactly right. That was a big difference I remember.

0:19:08.040 --> 0:19:11.600
<v Speaker 1>But these data centers have now come together in such

0:19:11.600 --> 0:19:13.679
<v Speaker 1>a big way now that they the largest ones are

0:19:13.680 --> 0:19:18.600
<v Speaker 1>called hyper scale and they host more than five thousand servers,

0:19:18.640 --> 0:19:23.040
<v Speaker 1>like servers, not individual persons. Data. It's like, it's incredible,

0:19:23.080 --> 0:19:25.480
<v Speaker 1>how big is how big they've gotten Googles. And we'll

0:19:25.480 --> 0:19:27.520
<v Speaker 1>go over some of the kind of square footage and

0:19:27.520 --> 0:19:30.320
<v Speaker 1>then later talk about the elephant in the room, which

0:19:30.320 --> 0:19:34.040
<v Speaker 1>is energy and water usage. But Google's first data center

0:19:34.080 --> 0:19:36.560
<v Speaker 1>was built in two thousand and six, just but two

0:19:36.680 --> 0:19:38.520
<v Speaker 1>years before stuff you should have launched. And this is

0:19:38.560 --> 0:19:42.680
<v Speaker 1>an Oregon and they are still expanding that thing beyond

0:19:43.160 --> 0:19:48.199
<v Speaker 1>one point three million square feet. Meanwhile, in China they're like,

0:19:48.840 --> 0:19:53.720
<v Speaker 1>hold my tea, I guess, because China Telecom has a

0:19:53.840 --> 0:19:58.080
<v Speaker 1>ten point seven million square foot data center in Inner Mongolia.

0:19:58.280 --> 0:19:59.880
<v Speaker 2>It's two hundred and fifty acres.

0:20:01.600 --> 0:20:06.359
<v Speaker 1>That is a warehouse full of worrying servers heating up

0:20:06.359 --> 0:20:07.000
<v Speaker 1>and being cool.

0:20:07.520 --> 0:20:10.160
<v Speaker 2>Yeah, which is a big problem for any data center,

0:20:10.200 --> 0:20:14.719
<v Speaker 2>it turns out. But the whole expansion this jump starting

0:20:14.760 --> 0:20:18.320
<v Speaker 2>in twenty seventeen thanks to cloud computing, because again, cloud

0:20:18.359 --> 0:20:20.840
<v Speaker 2>computing just means all your stuff isn't on one server

0:20:20.920 --> 0:20:23.000
<v Speaker 2>and one data center, it's broken up into pieces and

0:20:23.040 --> 0:20:25.840
<v Speaker 2>spread all over the place. That's the cloud. That's basically it.

0:20:26.440 --> 0:20:30.240
<v Speaker 2>Even though it's way more advanced and intricate than that.

0:20:30.240 --> 0:20:32.760
<v Speaker 2>That's like all you really need to know for the

0:20:32.800 --> 0:20:36.800
<v Speaker 2>purposes of this episode, right. It led to a huge jump,

0:20:36.800 --> 0:20:39.520
<v Speaker 2>a huge need in data centers, and it also expanded

0:20:39.560 --> 0:20:43.360
<v Speaker 2>all the stuff we can do now, and COVID actually

0:20:43.359 --> 0:20:47.840
<v Speaker 2>gave it another bump, made building a data center very

0:20:48.400 --> 0:20:51.159
<v Speaker 2>economically attractive thing to do if you had the money.

0:20:51.400 --> 0:20:56.159
<v Speaker 2>Because remote working finally finally established itself as like, no,

0:20:56.400 --> 0:21:00.560
<v Speaker 2>we're doing this, stop calling us back to the office, ye,

0:21:00.760 --> 0:21:04.320
<v Speaker 2>which is what they're doing now. I know, I hope

0:21:04.359 --> 0:21:07.520
<v Speaker 2>it doesn't work because I remember when all of that

0:21:07.560 --> 0:21:10.399
<v Speaker 2>started and everybody was so nervous, like management was all

0:21:10.440 --> 0:21:12.439
<v Speaker 2>so nervous that people were just going to totally like

0:21:12.520 --> 0:21:15.840
<v Speaker 2>mess around and everything. It just it didn't happen. I

0:21:15.880 --> 0:21:19.439
<v Speaker 2>don't know anybody who's even been like gotten a talking to,

0:21:19.760 --> 0:21:23.280
<v Speaker 2>let alone, been fired for just messing around at home.

0:21:23.480 --> 0:21:25.359
<v Speaker 2>As a matter of fact, like you were saying, it

0:21:25.480 --> 0:21:26.640
<v Speaker 2>just makes you work more.

0:21:27.680 --> 0:21:29.520
<v Speaker 1>Yeah, I mean, do you know how many times in

0:21:29.560 --> 0:21:32.320
<v Speaker 1>our old offices I would see Jonathan Strickland just wandering

0:21:32.320 --> 0:21:34.200
<v Speaker 1>aimlessly through the office chatting with people.

0:21:34.520 --> 0:21:37.359
<v Speaker 2>Yes, I do, because he would chat with me a lot.

0:21:37.800 --> 0:21:38.120
<v Speaker 2>He did.

0:21:38.160 --> 0:21:41.000
<v Speaker 1>He did that in front of God and everybody, as

0:21:41.040 --> 0:21:43.080
<v Speaker 1>they say, right there in the office. So I can't

0:21:43.080 --> 0:21:44.440
<v Speaker 1>imagine what happened with him at home.

0:21:44.600 --> 0:21:47.520
<v Speaker 2>Yeah, like it was a sorority mixer or something.

0:21:49.840 --> 0:21:51.800
<v Speaker 1>We love Strickland. He's still around everyone. By the way,

0:21:51.840 --> 0:21:54.960
<v Speaker 1>he retired from tech stuff, but he's still with a company.

0:21:54.680 --> 0:21:57.440
<v Speaker 2>Which is great. We love Strickland all right.

0:21:57.480 --> 0:21:59.760
<v Speaker 1>So now we're onto AI data centers and that was

0:21:59.800 --> 0:22:04.119
<v Speaker 1>the I mean to call it a game changer. Seems

0:22:04.200 --> 0:22:07.680
<v Speaker 1>quaint compared to the rise of cloud computing and everything,

0:22:07.760 --> 0:22:10.600
<v Speaker 1>because it is off to the races in a way

0:22:10.640 --> 0:22:14.560
<v Speaker 1>that seemingly cannot be stopped. The genie has left the bottle,

0:22:14.560 --> 0:22:17.399
<v Speaker 1>as they say. Starting in twenty twenty two, when chat

0:22:17.480 --> 0:22:21.159
<v Speaker 1>GPT was released by open Ai, all of a sudden,

0:22:22.320 --> 0:22:26.439
<v Speaker 1>the need for these data centers became exponentially greater in

0:22:26.560 --> 0:22:29.359
<v Speaker 1>size in the speed at which they need these things

0:22:29.359 --> 0:22:36.040
<v Speaker 1>built because AI requires a ton of computing power to operate.

0:22:36.760 --> 0:22:39.280
<v Speaker 2>So much so that they don't even use the standard

0:22:40.600 --> 0:22:44.040
<v Speaker 2>what's called the compute machine. So compute is like all

0:22:44.080 --> 0:22:47.400
<v Speaker 2>of the processing power, the networking, all of that stuff,

0:22:47.760 --> 0:22:51.040
<v Speaker 2>and traditionally with a computer that's done on a CPU. Right,

0:22:52.080 --> 0:22:54.760
<v Speaker 2>that's how all of this gets done, right, everything else

0:22:54.800 --> 0:22:57.240
<v Speaker 2>is infrastructure. The CPU is doing all of the work.

0:22:58.400 --> 0:23:01.960
<v Speaker 2>Those are so like they still work like. Most data

0:23:01.960 --> 0:23:05.840
<v Speaker 2>centers are running on CPUs for AI, just not fast enough.

0:23:06.800 --> 0:23:11.159
<v Speaker 2>They use GPUs graphic processing units, which are associated with

0:23:11.720 --> 0:23:14.040
<v Speaker 2>video games for most people, right, you need a good

0:23:14.080 --> 0:23:19.240
<v Speaker 2>graphics card to run your video game, I guess, but

0:23:20.640 --> 0:23:23.600
<v Speaker 2>they the reason that for AI data centers that they

0:23:23.680 --> 0:23:26.640
<v Speaker 2>use GPUs is because they're really good at parallel processing.

0:23:26.680 --> 0:23:28.840
<v Speaker 2>They can run a bunch of different operations at once.

0:23:29.320 --> 0:23:31.399
<v Speaker 2>So you're like, cool, you just throw a GPU in

0:23:31.400 --> 0:23:33.720
<v Speaker 2>a data center and you can run an AI. No,

0:23:34.200 --> 0:23:38.080
<v Speaker 2>you need hundreds of thousands of these things strung together,

0:23:38.720 --> 0:23:41.760
<v Speaker 2>and instead of like a CPU running like a couple

0:23:41.800 --> 0:23:45.200
<v Speaker 2>of servers or something like that. At data center. All

0:23:45.240 --> 0:23:48.959
<v Speaker 2>of them are strung together to form one giant supercomputer

0:23:49.600 --> 0:23:51.320
<v Speaker 2>that the AI operates on.

0:23:52.000 --> 0:23:55.600
<v Speaker 1>Yeah, like chat GPT itself was trained on twenty thousand

0:23:55.720 --> 0:24:00.320
<v Speaker 1>of these GPUs a GPU, you know, the sort of

0:24:00.320 --> 0:24:02.639
<v Speaker 1>the biggest name in the game. There's a couple, but

0:24:02.680 --> 0:24:06.320
<v Speaker 1>the biggest one obviously is the Navidia. But the Navidia

0:24:06.440 --> 0:24:09.840
<v Speaker 1>H one hundred that is the standard right now. If

0:24:09.880 --> 0:24:13.000
<v Speaker 1>you look this thing up, it it fits in your hand.

0:24:13.480 --> 0:24:16.960
<v Speaker 1>It's not like some gigantic thing. H twenty thousand of

0:24:17.000 --> 0:24:19.960
<v Speaker 1>them linked together or one hundred thousand of them linked together.

0:24:20.040 --> 0:24:22.760
<v Speaker 1>Who knows how many, you know, hundreds of thousands are

0:24:22.760 --> 0:24:26.640
<v Speaker 1>eventually going to be linked together to end the world.

0:24:26.680 --> 0:24:28.960
<v Speaker 1>That's where all the power comes from, like you were saying,

0:24:29.000 --> 0:24:33.800
<v Speaker 1>But it's you know, it's just a little rectangular handheld

0:24:33.800 --> 0:24:36.000
<v Speaker 1>thing that's like, oh, that looks like something that maybe

0:24:36.000 --> 0:24:40.639
<v Speaker 1>came out of a computer. And Navidia is what are

0:24:40.640 --> 0:24:43.240
<v Speaker 1>their stock jumped over a couple of years, like nine

0:24:43.320 --> 0:24:46.320
<v Speaker 1>hundred percent over twenty twenty three and twenty twenty four

0:24:46.640 --> 0:24:47.200
<v Speaker 1>something like.

0:24:47.119 --> 0:24:50.040
<v Speaker 2>That, Yeah, nine hundred percent increase.

0:24:51.240 --> 0:24:53.720
<v Speaker 1>Yeah, and we'll talk about why all of this is

0:24:54.160 --> 0:24:56.879
<v Speaker 1>super like scary and dangerous because it really is.

0:24:57.119 --> 0:24:59.199
<v Speaker 2>Well, yeah, if you want a really good explanation of

0:24:59.240 --> 0:25:01.879
<v Speaker 2>this about and like you said, how many GPUs you

0:25:01.920 --> 0:25:05.800
<v Speaker 2>string together before we end the world? Nate Sores and

0:25:06.119 --> 0:25:08.840
<v Speaker 2>Eliezer Yukowski In that book, I keep referencing that I

0:25:08.880 --> 0:25:12.159
<v Speaker 2>think everybody should read. If anyone builds it, everyone dies.

0:25:12.359 --> 0:25:15.879
<v Speaker 2>About the current state of AI. They talk about this

0:25:16.119 --> 0:25:20.160
<v Speaker 2>in depth, but in a really understandable way. It's really fascinating.

0:25:21.119 --> 0:25:23.399
<v Speaker 2>But that's essentially one of the things they say is

0:25:23.440 --> 0:25:26.760
<v Speaker 2>like we keep stringing together tens and tens of thousands

0:25:26.760 --> 0:25:31.600
<v Speaker 2>more GPUs, that just makes the supercomputer smarter and smarter

0:25:31.760 --> 0:25:35.200
<v Speaker 2>and more capable. And eventually, what's going to happen. We're

0:25:35.200 --> 0:25:38.520
<v Speaker 2>going to reach some point potentially where we just put

0:25:38.520 --> 0:25:41.040
<v Speaker 2>that extra last GPU in there and all of a sudden,

0:25:41.040 --> 0:25:43.600
<v Speaker 2>the balance is tipped and the thing becomes super intelligent.

0:25:44.119 --> 0:25:46.960
<v Speaker 1>That's right. Also a time for me because you're always

0:25:47.000 --> 0:25:48.800
<v Speaker 1>too shy to to plug the end of the world

0:25:48.800 --> 0:25:53.040
<v Speaker 1>with Josh Clark, your fantastic limited series, of which AI

0:25:53.359 --> 0:25:55.600
<v Speaker 1>is one of the central focuses or one of was

0:25:55.640 --> 0:25:56.320
<v Speaker 1>it eight things?

0:25:57.560 --> 0:26:00.320
<v Speaker 2>Ten? Well, there was ten episodes.

0:26:00.040 --> 0:26:03.240
<v Speaker 1>Ten episodes, right, thanks baby? Well but one of the

0:26:03.240 --> 0:26:06.440
<v Speaker 1>episodes was just like you talking about Jimmy Buffett Records.

0:26:06.119 --> 0:26:06.920
<v Speaker 2>And that's right.

0:26:07.960 --> 0:26:11.680
<v Speaker 1>You had to lighten the mood yep Should we take

0:26:11.720 --> 0:26:13.600
<v Speaker 1>a break or should we keep going for a minute.

0:26:13.640 --> 0:26:15.960
<v Speaker 1>Let's keep going for a minute, okay, because you talked

0:26:16.000 --> 0:26:18.000
<v Speaker 1>about investment, and you know, if you have the money

0:26:18.000 --> 0:26:20.639
<v Speaker 1>to open one of these things, and that's what these

0:26:20.720 --> 0:26:24.679
<v Speaker 1>tech companies are doing, like to perhaps they're great peril.

0:26:24.680 --> 0:26:27.800
<v Speaker 1>At some point we'll see. Microsoft has invested eighty eight

0:26:27.800 --> 0:26:31.480
<v Speaker 1>billion dollars in data centers just in twenty twenty five.

0:26:32.160 --> 0:26:34.720
<v Speaker 1>Amazon is pledged over the next fifteen years one hundred

0:26:34.760 --> 0:26:39.040
<v Speaker 1>and fifty billion dollars. And Google and Meta together about

0:26:39.200 --> 0:26:41.280
<v Speaker 1>you know, not working together, but they are expected to

0:26:41.280 --> 0:26:44.439
<v Speaker 1>spend about seven hundred and fifty billion dollars just on

0:26:44.760 --> 0:26:49.320
<v Speaker 1>equipment over the next two years. And Stanley Morgan says

0:26:49.920 --> 0:26:53.119
<v Speaker 1>to Morgan, Stanley, what I say, Stanley Morgan, Yeah, I

0:26:53.119 --> 0:26:54.200
<v Speaker 1>think we should leave that in there.

0:26:54.320 --> 0:26:54.800
<v Speaker 2>Okay.

0:26:55.440 --> 0:26:58.160
<v Speaker 1>Stanley says, Hey, you know, guys.

0:26:58.160 --> 0:26:59.920
<v Speaker 2>Maybe you might like Stanley Kamma boar.

0:27:00.680 --> 0:27:04.560
<v Speaker 1>Yeah, Stanley Kumo Morgan. Over five years between twenty five

0:27:04.640 --> 0:27:09.240
<v Speaker 1>and twenty thirty, Morgan, Stanley says about three trillion dollars

0:27:10.040 --> 0:27:12.479
<v Speaker 1>is going to be spent just on the data centers

0:27:13.080 --> 0:27:15.760
<v Speaker 1>about I mean, half of which is the hardware and

0:27:15.880 --> 0:27:17.520
<v Speaker 1>half of which is just building these things.

0:27:17.680 --> 0:27:22.720
<v Speaker 2>Yeah, just in what the next four years. Yeah, So

0:27:22.880 --> 0:27:24.760
<v Speaker 2>think about it. If you're in Nvidia and you're the

0:27:24.840 --> 0:27:27.840
<v Speaker 2>industry leader for GPUs and everybody's like, we're gonna spend

0:27:27.880 --> 0:27:31.920
<v Speaker 2>one point five trillion dollars on this on the infrastructure

0:27:32.000 --> 0:27:35.320
<v Speaker 2>in the GPUs, you're looking pretty good down the.

0:27:35.359 --> 0:27:38.440
<v Speaker 1>Road, Yeah, for sure. And you know they're doing this

0:27:38.560 --> 0:27:41.160
<v Speaker 1>because there's a demand right now for use at least

0:27:41.280 --> 0:27:45.360
<v Speaker 1>because things like OpenAI and other AI creators are using

0:27:45.400 --> 0:27:48.480
<v Speaker 1>them like crazy. But these companies are also using them

0:27:48.520 --> 0:27:51.120
<v Speaker 1>for their own AI research, right.

0:27:51.359 --> 0:27:56.879
<v Speaker 2>Yeah. So like Xai has that Colossus machine that you

0:27:56.960 --> 0:28:00.639
<v Speaker 2>were talking about earlier, which is two high hundred thousand

0:28:00.720 --> 0:28:05.880
<v Speaker 2>GPUs strung together. I'm not sure if it's fully online yet, Tennessee. Yeah,

0:28:06.119 --> 0:28:08.760
<v Speaker 2>And it's just for that. It's they're not doing any

0:28:08.800 --> 0:28:13.040
<v Speaker 2>they're not calculating missile trajectories for the Ministry of Defense

0:28:13.119 --> 0:28:16.000
<v Speaker 2>or anything like that. Like, it's just for that AI.

0:28:16.600 --> 0:28:18.520
<v Speaker 2>And yeah, I think Meta is doing the same thing.

0:28:19.119 --> 0:28:22.000
<v Speaker 2>Open ai I don't think is building their own because

0:28:22.040 --> 0:28:25.600
<v Speaker 2>they're so in cahoots with Microsoft. I think they run

0:28:25.640 --> 0:28:28.600
<v Speaker 2>their stuff on Microsoft's data centers. But yeah, yeah, if

0:28:28.640 --> 0:28:31.280
<v Speaker 2>you have an AI essentially right now, which means like

0:28:31.400 --> 0:28:35.240
<v Speaker 2>God and everybody, you probably have your own data center

0:28:35.359 --> 0:28:36.119
<v Speaker 2>dedicated to it.

0:28:36.800 --> 0:28:41.120
<v Speaker 1>Yeah. I And this isn't some some moral stand I'm

0:28:41.160 --> 0:28:43.960
<v Speaker 1>taking by saying that I have never used AI. And

0:28:44.520 --> 0:28:46.960
<v Speaker 1>trust me, I know that every part of my life

0:28:47.040 --> 0:28:49.720
<v Speaker 1>is now touched by AI, so I am inadvertently using.

0:28:49.560 --> 0:28:51.760
<v Speaker 2>It touched by an AI, that's right.

0:28:53.080 --> 0:28:56.840
<v Speaker 1>But I've never I've never used like you know, chatbots

0:28:56.920 --> 0:29:00.840
<v Speaker 1>or or large language models or inning like that, just

0:29:01.320 --> 0:29:04.719
<v Speaker 1>mainly because I'm just I'm fine doing things like they

0:29:04.760 --> 0:29:07.400
<v Speaker 1>are for now, and not in a luddite sort of way.

0:29:07.560 --> 0:29:10.440
<v Speaker 1>I just everything's going along great for me in my

0:29:10.560 --> 0:29:12.080
<v Speaker 1>job and how I live my life, so I just

0:29:12.160 --> 0:29:13.160
<v Speaker 1>I don't have a need for it.

0:29:13.520 --> 0:29:15.440
<v Speaker 2>I do the same thing. And I think also both

0:29:15.520 --> 0:29:18.240
<v Speaker 2>of us are like if somebody else wants to do

0:29:18.360 --> 0:29:20.600
<v Speaker 2>it the other way, that's fine. Like we're certainly not

0:29:20.680 --> 0:29:24.400
<v Speaker 2>gonna criticize them or be crimudgeony about it or say

0:29:24.480 --> 0:29:26.640
<v Speaker 2>that you know that's stupid.

0:29:27.440 --> 0:29:31.240
<v Speaker 1>Right, But as you'll see. You know, and again this

0:29:31.400 --> 0:29:35.000
<v Speaker 1>isn't yucking someone's yum, but everyone should know what they're

0:29:35.000 --> 0:29:36.840
<v Speaker 1>a part of, and that's part of what the episode

0:29:36.880 --> 0:29:37.200
<v Speaker 1>is about.

0:29:37.360 --> 0:29:41.200
<v Speaker 2>That's right. Yeah, no, I totally do. Before we take

0:29:41.240 --> 0:29:45.480
<v Speaker 2>a break. I think it's a small kind of side issue,

0:29:45.600 --> 0:29:49.160
<v Speaker 2>but it's worth pointing out that it sucks because these

0:29:49.280 --> 0:29:53.480
<v Speaker 2>Nvidia chips are so in demand from these massive companies.

0:29:53.800 --> 0:29:57.360
<v Speaker 2>It has driven the price for just the average Nvidia

0:29:57.480 --> 0:30:01.240
<v Speaker 2>graphics card sky high. So if you're a gamer and

0:30:01.360 --> 0:30:04.680
<v Speaker 2>you're like trying to improve your system, like you pay

0:30:05.360 --> 0:30:08.600
<v Speaker 2>way more than you used to for the same graphics

0:30:08.680 --> 0:30:11.600
<v Speaker 2>card that you could have bought for like a quarter

0:30:11.760 --> 0:30:14.200
<v Speaker 2>of the price, you know, a couple of years ago.

0:30:14.760 --> 0:30:17.280
<v Speaker 1>Yeah, and I wasn't even looking like I didn't even

0:30:17.320 --> 0:30:18.800
<v Speaker 1>know that you could just buy This is how little

0:30:18.840 --> 0:30:21.000
<v Speaker 1>I know about all this before. This was like, could

0:30:21.080 --> 0:30:24.760
<v Speaker 1>you just buy a Navidia Gpu? But I was just

0:30:24.840 --> 0:30:26.840
<v Speaker 1>researching the size and like what do these things look like?

0:30:27.360 --> 0:30:29.360
<v Speaker 1>And it, you know, it's one was on eBay for

0:30:29.480 --> 0:30:31.600
<v Speaker 1>twenty thousand dollars and I was like, oh my god,

0:30:31.760 --> 0:30:33.480
<v Speaker 1>I didn't Oh I didn't know that was the deal?

0:30:33.680 --> 0:30:34.160
<v Speaker 2>Is that right?

0:30:35.200 --> 0:30:36.920
<v Speaker 1>Yeah, and I don't know if that's accurate. I don't

0:30:37.280 --> 0:30:39.800
<v Speaker 1>know anything about it, so I could easily be corrected

0:30:39.840 --> 0:30:43.040
<v Speaker 1>on all this, but that's what the Internet told me.

0:30:43.240 --> 0:30:45.400
<v Speaker 2>Okay, well the Internet never lies.

0:30:46.960 --> 0:30:48.600
<v Speaker 1>Oh one thing before we break real quick, because we

0:30:48.640 --> 0:30:50.760
<v Speaker 1>did promise a little UK specific stuff and I didn't

0:30:50.760 --> 0:30:55.080
<v Speaker 1>want to short shrift our brit listeners or Kyle. The

0:30:55.280 --> 0:30:58.200
<v Speaker 1>UK is right now like the third largest nation for

0:30:58.320 --> 0:31:00.880
<v Speaker 1>data centers. The US is first, I think Germany a second,

0:31:01.680 --> 0:31:04.120
<v Speaker 1>and they signed what was called the Tech Prosperity Deal

0:31:04.200 --> 0:31:07.240
<v Speaker 1>with the giants, the tech giants of the United States,

0:31:07.920 --> 0:31:11.600
<v Speaker 1>And right now Microsoft has announced a thirty billion dollar

0:31:11.680 --> 0:31:15.520
<v Speaker 1>investment in UK data centers, and I think like one

0:31:15.600 --> 0:31:18.400
<v Speaker 1>hundred new AI data centers are planned in the UK

0:31:18.520 --> 0:31:19.600
<v Speaker 1>at this point moving forward.

0:31:19.920 --> 0:31:21.840
<v Speaker 2>Yeah, and I saw there's at least one in Wales

0:31:21.920 --> 0:31:26.720
<v Speaker 2>that's being smartly done. They took an old radiator factory

0:31:26.880 --> 0:31:31.920
<v Speaker 2>plant campus and they're revitalizing that as AI data center.

0:31:32.040 --> 0:31:35.160
<v Speaker 2>So it does sound like I get why the UK

0:31:35.360 --> 0:31:37.360
<v Speaker 2>is doing it, but there's a lot of people in

0:31:37.440 --> 0:31:39.280
<v Speaker 2>the UK and elsewhere who are like, these are not

0:31:39.520 --> 0:31:42.920
<v Speaker 2>this is not a good investment for local governments or

0:31:42.960 --> 0:31:46.240
<v Speaker 2>even national governments. There's a big problem with all this,

0:31:46.480 --> 0:31:50.280
<v Speaker 2>Like there is a AI boom going on. Data centers

0:31:50.320 --> 0:31:52.800
<v Speaker 2>are just one part of it. Like people are throwing

0:31:52.920 --> 0:31:57.360
<v Speaker 2>money at AI like it's nineteen ninety nine, and a

0:31:57.400 --> 0:31:59.760
<v Speaker 2>lot of people are like, there's another it's not a

0:32:00.400 --> 0:32:04.360
<v Speaker 2>bubble this time, but it's a AI bubble. Yeah. One

0:32:04.400 --> 0:32:06.840
<v Speaker 2>of the reasons why some people are pointing to it

0:32:06.920 --> 0:32:11.560
<v Speaker 2>as an AI bubble is that it's just not clear

0:32:12.000 --> 0:32:14.400
<v Speaker 2>how much money is going to be made from AI

0:32:14.920 --> 0:32:18.800
<v Speaker 2>and when that's going to start. Yeah. I think the

0:32:18.920 --> 0:32:21.760
<v Speaker 2>Financial Times called Open AI a money pit with a

0:32:21.840 --> 0:32:25.400
<v Speaker 2>website on top. Yeah, not great, no, because people are

0:32:25.480 --> 0:32:27.760
<v Speaker 2>just pumping money into this stuff, but they're not getting

0:32:28.440 --> 0:32:32.360
<v Speaker 2>they're not seeing results from it, not yet. It's not

0:32:32.480 --> 0:32:35.400
<v Speaker 2>necessarily a bad bet that AI is going to completely

0:32:35.480 --> 0:32:38.960
<v Speaker 2>revolutionize the world and like revolutionize economies and going to

0:32:39.040 --> 0:32:42.880
<v Speaker 2>make some people a lot of money, but there's just

0:32:43.000 --> 0:32:45.240
<v Speaker 2>no clear path to it right now, which makes some

0:32:45.320 --> 0:32:46.120
<v Speaker 2>people nervous.

0:32:46.800 --> 0:32:50.840
<v Speaker 1>Yeah, there's about five percent, just five percent of pilot

0:32:50.920 --> 0:32:56.480
<v Speaker 1>AI programs right now in business secure returns on their investments,

0:32:56.800 --> 0:32:58.080
<v Speaker 1>you know, like they make the money.

0:32:58.520 --> 0:33:03.360
<v Speaker 2>But Stanley Morgan is predicting revenues of a trillion dollars

0:33:03.400 --> 0:33:05.480
<v Speaker 2>by twenty twenty eight, that's.

0:33:05.320 --> 0:33:08.440
<v Speaker 1>What they're saying. I mean, we'll see Navidia. I mean,

0:33:08.560 --> 0:33:11.280
<v Speaker 1>Kyle's also keen to point out that there's sort of

0:33:11.680 --> 0:33:14.400
<v Speaker 1>a circular economy within all this going on. That's a

0:33:14.440 --> 0:33:17.920
<v Speaker 1>little bit like troubling maybe because Navidia is investing in

0:33:18.040 --> 0:33:21.520
<v Speaker 1>open AAI, but that depends on their purchase of those

0:33:21.600 --> 0:33:26.160
<v Speaker 1>Navidia chips. So, you know, everyone from you know, just

0:33:26.360 --> 0:33:28.600
<v Speaker 1>people who are smarter than us as far as the

0:33:28.640 --> 0:33:31.560
<v Speaker 1>stuff goes, are warning people right down to the IMF,

0:33:31.680 --> 0:33:36.160
<v Speaker 1>the International Monetary Fund are flashing the warning signs saying

0:33:36.280 --> 0:33:39.120
<v Speaker 1>like this could be you know, it could make a

0:33:39.200 --> 0:33:41.440
<v Speaker 1>trillion dollars by twenty twenty eight, or it could like

0:33:41.520 --> 0:33:42.680
<v Speaker 1>wreck the global economy.

0:33:43.040 --> 0:33:49.000
<v Speaker 2>Yeah for sure. Yeah, we have no idea, although I

0:33:49.080 --> 0:33:52.040
<v Speaker 2>have seen people argue against it, that say like this

0:33:52.240 --> 0:33:55.120
<v Speaker 2>is nothing like Yeah, a lot of these AI companies

0:33:55.160 --> 0:34:00.560
<v Speaker 2>are probably overinflated, but it's nothing like it was with

0:34:01.000 --> 0:34:03.560
<v Speaker 2>like the two thousand and eight meltdown or the dot

0:34:03.640 --> 0:34:07.120
<v Speaker 2>com bubble, Like this is we're a lot we're a

0:34:07.160 --> 0:34:09.560
<v Speaker 2>lot more seasoned, or investors are a lot more seasoned.

0:34:09.600 --> 0:34:12.000
<v Speaker 2>Than they were before. The problem is one of the

0:34:12.080 --> 0:34:16.600
<v Speaker 2>problems is that the financing is expected to come in

0:34:16.800 --> 0:34:21.360
<v Speaker 2>large part from private credit, which is essentially an investment

0:34:21.480 --> 0:34:25.400
<v Speaker 2>vehicle for investors to go lend money to say like

0:34:25.600 --> 0:34:28.960
<v Speaker 2>companies that want to build data centers. Right, and this

0:34:29.239 --> 0:34:33.520
<v Speaker 2>is largely unregulated. It's very shadowy. We don't know how

0:34:33.600 --> 0:34:37.600
<v Speaker 2>many how much debt exists in the world on private

0:34:37.680 --> 0:34:40.320
<v Speaker 2>credit because they don't have to report this stuff. And

0:34:41.040 --> 0:34:42.759
<v Speaker 2>you know, as we learn from the two thousand and

0:34:42.760 --> 0:34:48.040
<v Speaker 2>eight meltdown, when there's like a massive speculation among finances

0:34:48.400 --> 0:34:52.759
<v Speaker 2>that involves debt's that can go really bad.

0:34:53.440 --> 0:34:57.239
<v Speaker 1>Yeah for sure. And speaking of going bad, I guess

0:34:57.320 --> 0:34:59.560
<v Speaker 1>we're at the sort of environmental piece of this whole thing.

0:35:00.280 --> 0:35:01.719
<v Speaker 1>And this is what I was talking about when I

0:35:01.760 --> 0:35:03.600
<v Speaker 1>said that, you know, people should just be aware of

0:35:03.680 --> 0:35:05.880
<v Speaker 1>what they're taking part in. And again this is not

0:35:05.960 --> 0:35:09.120
<v Speaker 1>to shame anybody who uses AI for their job or

0:35:09.320 --> 0:35:13.320
<v Speaker 1>just to make funny fake videos, but but you know,

0:35:13.960 --> 0:35:16.320
<v Speaker 1>everyone is sort of tied together to make this what

0:35:16.440 --> 0:35:19.400
<v Speaker 1>it is. Who's using that stuff, And I get if

0:35:19.400 --> 0:35:21.000
<v Speaker 1>someone says, like, hey, if I quit this thing, it's

0:35:21.040 --> 0:35:23.920
<v Speaker 1>not going to make any difference. But that's sort of

0:35:23.960 --> 0:35:26.879
<v Speaker 1>the the age old. Like, you know, if I don't

0:35:26.920 --> 0:35:30.560
<v Speaker 1>recycle my ten can, my aluminum can, ten cans, my

0:35:30.640 --> 0:35:33.000
<v Speaker 1>aluminum cans, then it's not gonna make that big of

0:35:33.080 --> 0:35:36.080
<v Speaker 1>a difference. But the idea of everyone getting together to

0:35:36.160 --> 0:35:38.680
<v Speaker 1>do something for the common good, that's where change happens,

0:35:39.840 --> 0:35:44.880
<v Speaker 1>or where negative change happens. So as far as AI

0:35:45.040 --> 0:35:48.759
<v Speaker 1>data centers go, the main you know, aside from just

0:35:49.000 --> 0:35:51.080
<v Speaker 1>you know, the land use and everything else in the

0:35:52.120 --> 0:35:55.640
<v Speaker 1>hardship on the local economies and towns in certain ways

0:35:55.680 --> 0:35:59.120
<v Speaker 1>that we're going to get to, it's really just a

0:35:59.320 --> 0:36:05.480
<v Speaker 1>sucubus of electricity and water usage. Yeah, psychobus is not

0:36:05.560 --> 0:36:06.320
<v Speaker 1>the right word.

0:36:06.360 --> 0:36:08.560
<v Speaker 2>No, but it makes sense. It's like a bunker down.

0:36:10.160 --> 0:36:12.520
<v Speaker 1>Yeah, But I say psychibis to mean just like a

0:36:12.640 --> 0:36:14.839
<v Speaker 1>bottomless pit. But I know that's not what it means,

0:36:14.880 --> 0:36:15.400
<v Speaker 1>by the way.

0:36:15.360 --> 0:36:18.839
<v Speaker 2>A giant sucking thing, right right, And it is. It's

0:36:18.840 --> 0:36:21.440
<v Speaker 2>sucking tons of electricity and water up. Like some of

0:36:21.520 --> 0:36:25.640
<v Speaker 2>these AI data plants use the same amount of electricity

0:36:25.680 --> 0:36:28.719
<v Speaker 2>as a town of fifty thousand yeah, and about the

0:36:28.800 --> 0:36:31.479
<v Speaker 2>same amount of water is a town of fifty thousand people.

0:36:31.520 --> 0:36:34.440
<v Speaker 2>This is a data center we're talking about, and it's

0:36:34.480 --> 0:36:37.760
<v Speaker 2>not even necessarily an AI data center. Just any hyper

0:36:37.840 --> 0:36:42.879
<v Speaker 2>scale data center uses a ton of electricity and water.

0:36:43.200 --> 0:36:47.200
<v Speaker 2>The reason it uses water is because all of these processors,

0:36:47.320 --> 0:36:50.160
<v Speaker 2>the CPUs that are doing all this work, and just

0:36:50.280 --> 0:36:52.400
<v Speaker 2>all of the networking that's going on with it, it's

0:36:52.520 --> 0:36:56.960
<v Speaker 2>generating heat, and computing happens faster when it's cooler. So

0:36:57.120 --> 0:36:59.919
<v Speaker 2>to keep the place cool they use evaporative cooling, where

0:37:00.120 --> 0:37:06.520
<v Speaker 2>they funnel waste heat air through wet pads essentially, like

0:37:06.800 --> 0:37:09.680
<v Speaker 2>they just buy old mattresses and doze them with water

0:37:10.120 --> 0:37:12.359
<v Speaker 2>and then they run the heat through there and through

0:37:12.400 --> 0:37:16.600
<v Speaker 2>evaporative cooling, it cools it off. It uses a little

0:37:17.040 --> 0:37:22.279
<v Speaker 2>electricity than air cooling, but it uses water a lot

0:37:22.400 --> 0:37:22.840
<v Speaker 2>of water.

0:37:23.600 --> 0:37:26.040
<v Speaker 1>Yeah, I mean, I assume most people know this. But

0:37:26.280 --> 0:37:28.560
<v Speaker 1>like your laptop has a tiny fan in it, Like

0:37:28.960 --> 0:37:31.000
<v Speaker 1>every computer in the world has a little fan in

0:37:31.080 --> 0:37:33.719
<v Speaker 1>it that cools it down. So when you've got all

0:37:33.760 --> 0:37:35.799
<v Speaker 1>this stuff together, you know it's going to generate tons

0:37:35.840 --> 0:37:38.480
<v Speaker 1>and tons of heat. That was the whirrying of the

0:37:38.520 --> 0:37:41.839
<v Speaker 1>server room that you used to sleep in. Those were

0:37:41.960 --> 0:37:44.399
<v Speaker 1>all fans, you know, And you know there's some other

0:37:44.520 --> 0:37:47.399
<v Speaker 1>sounds coming but mostly those fans trying to cool everything down.

0:37:48.280 --> 0:37:49.919
<v Speaker 1>We've got a lot of stats here that are pretty

0:37:49.920 --> 0:37:53.520
<v Speaker 1>eye popping. But there are eleven roughly eleven thousand data

0:37:53.520 --> 0:37:56.920
<v Speaker 1>centers around the world. Most of these are not AI obviously,

0:37:57.000 --> 0:37:59.920
<v Speaker 1>but they're the most you know, robust sort of u

0:38:00.040 --> 0:38:03.000
<v Speaker 1>users of the energy. But they use between one and

0:38:03.160 --> 0:38:05.759
<v Speaker 1>one point five percent, which it doesn't sound like a lot,

0:38:06.200 --> 0:38:11.360
<v Speaker 1>but of the entire world's electricity usage. I know on

0:38:11.520 --> 0:38:13.560
<v Speaker 1>planet Earth goes to data centers right now, and in

0:38:13.640 --> 0:38:17.840
<v Speaker 1>certain places like Ireland, data centers use about twenty percent

0:38:17.960 --> 0:38:19.120
<v Speaker 1>of the country's electricity.

0:38:19.280 --> 0:38:22.360
<v Speaker 2>Yeah, and if you dive into different places around like

0:38:22.760 --> 0:38:25.920
<v Speaker 2>the world where data centers are like that's collectively, right,

0:38:26.280 --> 0:38:27.719
<v Speaker 2>all of them in Iran and all of them in

0:38:27.800 --> 0:38:30.280
<v Speaker 2>the world. If you kind of zoom into the towns

0:38:30.800 --> 0:38:35.279
<v Speaker 2>where these things are located, there's well, there's something called

0:38:35.400 --> 0:38:40.560
<v Speaker 2>Data Center Alley in northern Virginia outside of DC, where

0:38:40.760 --> 0:38:45.680
<v Speaker 2>there's this huge concentration of large data centers, probably the

0:38:45.719 --> 0:38:49.319
<v Speaker 2>biggest concentration in the world. Those data centers use about

0:38:49.360 --> 0:38:52.799
<v Speaker 2>the same amount of electricity as sixty percent of all

0:38:52.840 --> 0:38:54.880
<v Speaker 2>the households in the state of Virginia.

0:38:55.280 --> 0:38:58.920
<v Speaker 1>Yeah, here's another one. By twenty thirty, they're predicting. This

0:38:59.040 --> 0:39:03.080
<v Speaker 1>is Barclay's Bank is predicting that data center energy use

0:39:03.120 --> 0:39:06.360
<v Speaker 1>in the United States would make up about thirteen percent

0:39:06.480 --> 0:39:10.400
<v Speaker 1>of the entire electricity demand of the United States. And

0:39:11.360 --> 0:39:13.680
<v Speaker 1>Meta has there. They all have silly names, but they're

0:39:14.000 --> 0:39:17.520
<v Speaker 1>data centers called Hyperion. They're all you know, one was

0:39:18.200 --> 0:39:20.560
<v Speaker 1>where are the where's that list? They're all these kind

0:39:20.600 --> 0:39:23.080
<v Speaker 1>of sci fi sounding names.

0:39:23.480 --> 0:39:28.560
<v Speaker 2>Yes, Stargate, Yeah, Jupiter, Prometheus. God, I'm sure all of

0:39:28.560 --> 0:39:30.360
<v Speaker 2>those nerds are like, what do you mean silly?

0:39:31.120 --> 0:39:32.759
<v Speaker 1>If I opened up a data center, I'd call it

0:39:32.840 --> 0:39:33.400
<v Speaker 1>Old Bessie.

0:39:34.480 --> 0:39:38.920
<v Speaker 2>Bessie's I hope so bad that somebody's listening to this

0:39:39.040 --> 0:39:42.319
<v Speaker 2>and they open a massive hyper scale data center named

0:39:42.360 --> 0:39:42.920
<v Speaker 2>Old Bessie.

0:39:43.680 --> 0:39:46.719
<v Speaker 1>That would be great. But Meta's Hyperion data center will

0:39:46.800 --> 0:39:49.680
<v Speaker 1>consume by the time it's finished, about five gigawatts. And

0:39:49.719 --> 0:39:54.440
<v Speaker 1>if you're like, what's five gigawatts? That is about half

0:39:54.600 --> 0:39:55.560
<v Speaker 1>of the peak load.

0:39:55.440 --> 0:39:57.440
<v Speaker 2>Of all of New York City, the most that it

0:39:57.480 --> 0:40:00.240
<v Speaker 2>can possibly it can possibly be demanded.

0:40:00.120 --> 0:40:02.480
<v Speaker 1>Right, Yeah, the very toplope probably, I guess in New

0:40:02.560 --> 0:40:06.400
<v Speaker 1>York City on the hottest day of the year, with

0:40:06.640 --> 0:40:10.120
<v Speaker 1>all the lights on at night or something. Yeah, and

0:40:10.200 --> 0:40:13.560
<v Speaker 1>that Rocketfeller tree just they just there's a summer version.

0:40:13.400 --> 0:40:17.160
<v Speaker 2>That puts it over the edge that's right blackout. So

0:40:17.320 --> 0:40:20.640
<v Speaker 2>you can imagine that when you're using all this electricity

0:40:20.800 --> 0:40:24.080
<v Speaker 2>and using all this water, if you're starting to build

0:40:24.120 --> 0:40:26.920
<v Speaker 2>these massive data centers, you're looking for places that have

0:40:27.120 --> 0:40:32.080
<v Speaker 2>like cheap land, cheap electricity, and because electricity is often

0:40:32.320 --> 0:40:36.200
<v Speaker 2>more expensive than water, they'll go to places. They'll build

0:40:36.239 --> 0:40:39.239
<v Speaker 2>them in places that are like water scarce, that have

0:40:39.560 --> 0:40:43.720
<v Speaker 2>cheap electricity. I'm the premise that, like, we're a massive

0:40:43.960 --> 0:40:48.960
<v Speaker 2>multinational corporation, we can push around this little county and

0:40:49.320 --> 0:40:51.000
<v Speaker 2>use up all of their water and what are they

0:40:51.040 --> 0:40:51.920
<v Speaker 2>gonna do? Nothing?

0:40:52.840 --> 0:40:55.560
<v Speaker 1>Yeah, And I mean that's literally happening. There's one right

0:40:55.600 --> 0:40:58.520
<v Speaker 1>here in Georgia, in Newton County. It's a metadata center

0:40:58.920 --> 0:41:03.480
<v Speaker 1>that's using tenth of the local water use. And like

0:41:03.600 --> 0:41:06.200
<v Speaker 1>you said, water is a is a resource that isn't infinite.

0:41:06.239 --> 0:41:08.360
<v Speaker 1>We've talked about the dangers in the future of like

0:41:08.760 --> 0:41:10.400
<v Speaker 1>you know, perhaps the wars of the future will be

0:41:10.480 --> 0:41:14.080
<v Speaker 1>fought over water, and this could get us there. I

0:41:14.160 --> 0:41:18.200
<v Speaker 1>think in Phoenix, Arizona, you know, known for their abundant water.

0:41:19.239 --> 0:41:23.280
<v Speaker 1>Meta and Microsoft use seven million gallons of water every

0:41:23.480 --> 0:41:25.160
<v Speaker 1>single day for their data centers.

0:41:25.239 --> 0:41:27.640
<v Speaker 2>Yeah, every day, you said.

0:41:28.120 --> 0:41:30.160
<v Speaker 1>Every day, seven million gallons of water.

0:41:30.320 --> 0:41:33.839
<v Speaker 2>That's insane. Yeah. And when I saw this, I was like, oh,

0:41:33.960 --> 0:41:37.600
<v Speaker 2>here we go. In the UK, data centers used ten

0:41:37.880 --> 0:41:45.040
<v Speaker 2>billion leaders of drinking water every year. L I. T R. E. S. Yeah,

0:41:45.080 --> 0:41:46.680
<v Speaker 2>that's right. Uh.

0:41:46.960 --> 0:41:50.120
<v Speaker 1>But you know you mentioned some of these towns. Not

0:41:50.239 --> 0:41:52.919
<v Speaker 1>only are some there like using let's say ten percent

0:41:52.960 --> 0:41:56.320
<v Speaker 1>of the local water here in Newton County in Virginia

0:41:56.640 --> 0:41:59.359
<v Speaker 1>where data center Alley is, some of these places are

0:41:59.520 --> 0:42:01.319
<v Speaker 1>like some of these towns are running out of water,

0:42:01.480 --> 0:42:03.359
<v Speaker 1>Like they go to turn on their water and water

0:42:03.480 --> 0:42:04.640
<v Speaker 1>doesn't come out because of this.

0:42:04.920 --> 0:42:07.480
<v Speaker 2>Well. Plus also, like we talked about how gamers are

0:42:07.520 --> 0:42:11.560
<v Speaker 2>getting the short end of the stick when it comes

0:42:11.600 --> 0:42:14.880
<v Speaker 2>to buying graphic cards because they are in such high demand,

0:42:15.200 --> 0:42:18.120
<v Speaker 2>same thing happens with electricity. So in addition to this

0:42:18.320 --> 0:42:20.600
<v Speaker 2>data center coming to town and using up all your water,

0:42:20.920 --> 0:42:24.239
<v Speaker 2>they're also jacking up your electricity prices because there's only

0:42:24.360 --> 0:42:28.360
<v Speaker 2>so much that your local electrical company can produce, So

0:42:28.480 --> 0:42:31.399
<v Speaker 2>because of supply and demand, your price is going to rise,

0:42:31.440 --> 0:42:35.640
<v Speaker 2>and I guess around Data center Alley in Northern Virginia,

0:42:36.000 --> 0:42:39.600
<v Speaker 2>electricity prices have increased two hundred and sixty seven percent

0:42:40.280 --> 0:42:45.359
<v Speaker 2>since twenty twenty. And that also is affecting Maryland, which

0:42:45.440 --> 0:42:48.280
<v Speaker 2>is getting little to no benefit from Data center Alley

0:42:48.440 --> 0:42:50.960
<v Speaker 2>and is just helping pay the price for it. This

0:42:51.120 --> 0:42:56.359
<v Speaker 2>is subsidization of these data centers, like they are subsidized

0:42:56.400 --> 0:42:58.719
<v Speaker 2>in just about every single way you can imagine.

0:42:59.239 --> 0:43:02.239
<v Speaker 1>Yeah, for sure. And if you say like, oh, well sure,

0:43:02.280 --> 0:43:04.520
<v Speaker 1>but they create jobs, right, so that's great for the

0:43:04.560 --> 0:43:09.720
<v Speaker 1>local economy. Kyle gives an example here of Northumberland, England.

0:43:10.120 --> 0:43:13.640
<v Speaker 1>There's a ten billion pound data center there or I

0:43:13.680 --> 0:43:16.719
<v Speaker 1>guess it's coming and you'd think, oh, great, that's that's

0:43:16.760 --> 0:43:19.560
<v Speaker 1>going to employ probably like five thousand people, right, it's

0:43:19.600 --> 0:43:22.240
<v Speaker 1>going to employ four hundred people with full time jobs.

0:43:22.600 --> 0:43:25.919
<v Speaker 2>Yeah, a ten billion dollar or ten billion pound data

0:43:25.960 --> 0:43:29.120
<v Speaker 2>center four hundred jobs. Because these things are so efficient

0:43:29.520 --> 0:43:33.040
<v Speaker 2>and everything is just so advanced, they don't really need

0:43:33.120 --> 0:43:36.359
<v Speaker 2>that many people to keep an eye on it. Right. Plus, Also,

0:43:37.400 --> 0:43:40.000
<v Speaker 2>the money from that data center, if they're not going

0:43:40.040 --> 0:43:42.439
<v Speaker 2>to spread it around the UK, it's going to flow

0:43:42.680 --> 0:43:45.200
<v Speaker 2>right back to the US, to the parent company.

0:43:46.200 --> 0:43:49.359
<v Speaker 1>Oh yeah, for sure. And you know, we also didn't

0:43:49.440 --> 0:43:52.960
<v Speaker 1>point out that a lot of these these energy grids

0:43:53.400 --> 0:43:56.319
<v Speaker 1>like are literally going to buckle under pressure at some point,

0:43:56.440 --> 0:43:57.480
<v Speaker 1>like they're not built for this.

0:43:57.840 --> 0:44:00.720
<v Speaker 2>Yes, and we're not so we're I know, it sounds

0:44:00.760 --> 0:44:03.800
<v Speaker 2>like we're just like and this and that. How terrible

0:44:03.840 --> 0:44:08.360
<v Speaker 2>are data centers like There's they're they're incredibly important and

0:44:08.520 --> 0:44:12.759
<v Speaker 2>they support an amazing array of really great stuff, right

0:44:13.160 --> 0:44:17.520
<v Speaker 2>and they they are the foundation that the next expansion

0:44:17.680 --> 0:44:20.879
<v Speaker 2>of the digital economy and the world culture are going

0:44:20.960 --> 0:44:23.759
<v Speaker 2>to grow on. Like, they're incredibly important, but they have

0:44:24.080 --> 0:44:27.000
<v Speaker 2>a lot of problems with them that need to be addressed.

0:44:27.280 --> 0:44:31.160
<v Speaker 2>They're not being addressed because every government from like the

0:44:31.320 --> 0:44:36.120
<v Speaker 2>local city council up to the leaders of the free world,

0:44:37.560 --> 0:44:41.200
<v Speaker 2>like are just giving these people whatever they want. That's

0:44:41.280 --> 0:44:45.279
<v Speaker 2>what's going on now. There's no checks going on at all,

0:44:45.440 --> 0:44:46.880
<v Speaker 2>right now, that's the problem.

0:44:47.520 --> 0:44:50.120
<v Speaker 1>Yeah, And that's that's because the flow of money is

0:44:50.239 --> 0:44:54.440
<v Speaker 1>so great at this point to a certain segment of

0:44:54.480 --> 0:45:00.120
<v Speaker 1>the population. Only they're protecting their their own investment, you know,

0:45:00.200 --> 0:45:01.719
<v Speaker 1>they're watching their own backsides.

0:45:01.840 --> 0:45:04.040
<v Speaker 2>That's definitely I would say ninety nine percent of it.

0:45:04.440 --> 0:45:06.840
<v Speaker 2>But I think there's also chuck, a little factor of

0:45:06.960 --> 0:45:11.920
<v Speaker 2>like g whiz, Like these these titans of the AI

0:45:12.120 --> 0:45:17.680
<v Speaker 2>industry are good at like razzle, dazzling elected officials into

0:45:17.760 --> 0:45:20.200
<v Speaker 2>doing whatever they want by I think making them feel

0:45:20.200 --> 0:45:24.920
<v Speaker 2>included in this new frontier. Essentially, I think there's a

0:45:25.080 --> 0:45:25.960
<v Speaker 2>certain element of that.

0:45:26.880 --> 0:45:30.080
<v Speaker 1>I think you're probably right. It's hey, maybe it'll all

0:45:30.120 --> 0:45:30.680
<v Speaker 1>work out great.

0:45:30.840 --> 0:45:35.080
<v Speaker 2>Sure, it probably will. It usually does astoundingly, it usually

0:45:35.200 --> 0:45:37.239
<v Speaker 2>does work out well.

0:45:37.520 --> 0:45:39.440
<v Speaker 1>True as far as the world hasn't ended.

0:45:39.760 --> 0:45:43.480
<v Speaker 2>That's exactly what I mean. Yeah, yeah, yeah, So I

0:45:43.520 --> 0:45:45.359
<v Speaker 2>think that's it. We said yeah like four or five

0:45:45.440 --> 0:45:48.560
<v Speaker 2>times in secession. I think we accidentally triggered listener, ma'am.

0:45:51.280 --> 0:45:54.960
<v Speaker 1>That's right. This relates to our history of the BBC episode,

0:45:55.120 --> 0:45:58.600
<v Speaker 1>and this is from Erica, and Erica says, hey, guys,

0:45:59.000 --> 0:46:01.320
<v Speaker 1>I really love the episode and left me reflecting on

0:46:01.400 --> 0:46:03.320
<v Speaker 1>how I've come to understand the country through both the

0:46:03.400 --> 0:46:06.800
<v Speaker 1>content the BBC produces and the people's reactions to the BBC.

0:46:07.000 --> 0:46:09.720
<v Speaker 1>But more recently, my work as an academic has enabled

0:46:09.760 --> 0:46:12.040
<v Speaker 1>me to be involved in creating programs for the BBC

0:46:12.600 --> 0:46:15.520
<v Speaker 1>across TV, radio and online. Because there's one awesome fact

0:46:16.000 --> 0:46:18.960
<v Speaker 1>about the BBC that wasn't included. For over fifty years,

0:46:19.000 --> 0:46:22.239
<v Speaker 1>the BBC has partnered with the Open University OU, which

0:46:22.239 --> 0:46:26.680
<v Speaker 1>specializes in accessible and distance education. The partnership started in

0:46:26.719 --> 0:46:30.359
<v Speaker 1>the nineteen seventies to provide learning at scale, including facilitating

0:46:30.480 --> 0:46:33.360
<v Speaker 1>university level lectures at night on public television. Today, the

0:46:33.400 --> 0:46:38.279
<v Speaker 1>partnership facilitates access to academic consultants to co produce high

0:46:38.360 --> 0:46:43.080
<v Speaker 1>quality and form content across platforms, including some of the

0:46:43.400 --> 0:46:44.600
<v Speaker 1>David Attenborough.

0:46:44.400 --> 0:46:45.319
<v Speaker 2>Nature stuff nice.

0:46:46.320 --> 0:46:50.560
<v Speaker 1>Additionally, the Open University creates supplementary materials to enable people

0:46:50.600 --> 0:46:55.080
<v Speaker 1>to continue their learning journey and explore topics in more detail. So,

0:46:55.200 --> 0:46:57.640
<v Speaker 1>whether viewers or listeners realize it or not, this partnership

0:46:57.760 --> 0:47:01.000
<v Speaker 1>enables the public to benefit from special US knowledge and

0:47:01.120 --> 0:47:06.200
<v Speaker 1>accessible ways. And that is from Erica from the Open University,

0:47:06.280 --> 0:47:08.399
<v Speaker 1>who is a professor of medical anthropology.

0:47:08.640 --> 0:47:11.640
<v Speaker 2>Oh wow, that's an awesome Erica. You got to send

0:47:11.719 --> 0:47:15.479
<v Speaker 2>us some topic ideas too, totally right up your alley

0:47:15.600 --> 0:47:18.600
<v Speaker 2>and congratulations. That's pretty neat making stuff in conjunction with

0:47:18.680 --> 0:47:21.399
<v Speaker 2>the BBC. That's gotta be a neat high water mark,

0:47:21.640 --> 0:47:25.000
<v Speaker 2>you know, agreed, And I think, Chuck, I'm curious to

0:47:25.080 --> 0:47:28.440
<v Speaker 2>see if we go look at our account, we'll see

0:47:28.440 --> 0:47:31.920
<v Speaker 2>a little line item from open University and one from BBC.

0:47:33.520 --> 0:47:35.360
<v Speaker 1>Well, it would be like seven pounds or something. I

0:47:35.400 --> 0:47:36.600
<v Speaker 1>don't know the exchange rate, right.

0:47:36.600 --> 0:47:40.279
<v Speaker 2>That sounds about right? All right, great, well, thanks again, Erica,

0:47:40.320 --> 0:47:43.480
<v Speaker 2>and please do send us some medical anthropology ideas because

0:47:43.520 --> 0:47:45.960
<v Speaker 2>that just sounds like it'll knock our socks off. And

0:47:46.040 --> 0:47:47.719
<v Speaker 2>if you want to be like Erica and try to

0:47:47.800 --> 0:47:51.520
<v Speaker 2>knock our socks off, good luck, you can send it

0:47:51.640 --> 0:47:55.279
<v Speaker 2>off to us at stuff podcast at iHeartRadio dot com.

0:47:58.480 --> 0:48:01.320
<v Speaker 2>Stuff you Should Know is a production of iHeartRadio. For

0:48:01.480 --> 0:48:05.600
<v Speaker 2>more podcasts my heart Radio, visit the iHeartRadio app, Apple Podcasts,

0:48:05.760 --> 0:48:07.560
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