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The AI Water Use Controversy: How It's Completely Misunderstood · In the Loop AI

0:00
Ejaaz: You've all heard the headlines. AI is draining our water supply.
0:03
Ejaaz: Data centers are stealing drinking water from the communities.
0:07
Ejaaz: ChatGPT is literally drying up the planet. It sounds terrifying and it's also completely fake.
0:15
Ejaaz: Today we're going to bust one of the biggest myths on the internet and walk
0:17
Ejaaz: through the actual numbers which reveal something crazy that the world's largest
0:22
Ejaaz: data center uses about as much water as two burger joints.
0:27
Ejaaz: We're going to walk you through exactly how much water is needed for the biggest
0:31
Ejaaz: data center in the world, Colossus 2, and why the majority of water used is
0:35
Ejaaz: only a fraction of the water used by your local golf club that your friends go to every weekend.
0:41
Josh: So part of the feedback that we've seen as we become more of a presence,
0:44
Josh: a platform in the world of AI, is that there's a lot of narratives that try to take down progress.
0:48
Josh: And the newest and hottest topic has been the topic of water consumption,
0:51
Josh: to the point where when I talk about with my friends about what I'm working
0:55
Josh: on and what I'm interested in, that frequently comes up as the first rebuttal.
0:59
Josh: It's like, this is horrible for the environment. It's using so much water, so much energy.
1:03
Josh: And this episode, we're going to focus on the water, particularly around the
1:06
Josh: public perception versus comparing it to the reality and how far off it really is.
1:11
Josh: We're seeing on the screen a few headlines of people from Utah,
1:14
Josh: very viral publications and headlines that have been talking about this.
1:17
Josh: But the reality is, is it's simply not true.
1:20
Josh: So we're going to methodically and in a very fun way kind of dissect how wrong
1:24
Josh: this actually is, starting with the book that kind of spawned it all.
1:28
Josh: The author's name is Karen Howe. No pun intended.
1:31
Josh: She really, like Karen, Karen seems like a very fitting name as an author called
1:35
Josh: the Empire of AI, claiming a Google data center would use 1,000 times the water
1:39
Josh: of an 88,000 person city.
1:42
Josh: Studies projecting AI will consume 1.7 trillion gallons of fresh water by 2027.
1:48
Josh: These claims are a bit outrageous, but this has been the narrative that people
1:51
Josh: have been using as they discuss their rebuttals against why AI should exist.
1:56
Josh: And this simply is not true. And I guess this is kind of where we got skeptical.
2:00
Josh: We were like, okay, 1.7 trillion gallons, a thousand times more than an 88,000 person city.
2:05
Josh: These numbers are outrageously large, but they're being peddled around as if
2:08
Josh: it is truth in these large publications.
2:10
Ejaaz: The thing is, like, we work in the AI space, Josh.
2:15
Ejaaz: So trillion dollars, trillions, We're kind of like used to it at this point.
2:19
Josh: Trillion here, trillion there.
2:19
Ejaaz: Yeah, right. But what I wasn't used to is a trillion gallons of water.
2:24
Ejaaz: And the first thought I had to my head was, what is this compared to?
2:29
Ejaaz: Like, I can't quite comprehend how much water this is and how much water is
2:35
Ejaaz: used in other industries that aren't AI adjacent.
2:39
Ejaaz: So I started getting skeptical and I came across what I think now is the most
2:44
Ejaaz: important bit of journalism done on data centers by these guys at SemiAnalysis.
2:50
Ejaaz: They are a crazy team of researchers that kind of like dig into all the boring,
2:57
Ejaaz: nitty-gritty, hard data center stuff to bring us the facts about lots of different
3:01
Ejaaz: things, including how much water is consumed at the data center level.
3:07
Ejaaz: And the revealings are super interesting. But what I love most about this,
3:12
Ejaaz: is, Josh, is that not only is it really informative, it's also hilarious.
3:18
Ejaaz: Because... Oh, it's great.
3:19
Josh: I love this post so much.
3:20
Ejaaz: Right. They've compared data center water usage
3:24
Ejaaz: to burger restaurants, specifically In-N-Out. So for some context here,
3:29
Ejaaz: they took the largest data center in the world, which is Elon Musk's Colossus 2.
3:35
Ejaaz: It's a data center based in Memphis, and it is the first data center to reach a gigawatt of compute.
3:41
Ejaaz: We actually mentioned this on yesterday's episode. If you haven't seen it,
3:44
Ejaaz: definitely go check that out. It's super cool.
3:46
Ejaaz: So we're talking about $18 billion worth of GPUs here, Josh.
3:49
Ejaaz: So as you can imagine, it's probably using a lot of water, right?
3:53
Ejaaz: So the math that they uncovered was the most revealing part.
3:56
Ejaaz: So Colossus 2 has an annual water footprint of 346 million gallons of water per year.
4:05
Ejaaz: Guess how much the average in-and-out store consumes per year?
4:09
Josh: A lot.
4:12
Ejaaz: 147 million gallons per year. Per store.
4:16
Ejaaz: Per store, sorry, yeah, per store, yes. So that means that the largest data
4:21
Ejaaz: center in the entire world currently today that everyone's complaining about
4:26
Ejaaz: consumes the same amount of water as two and a half In-N-Out stores.
4:31
Ejaaz: Why aren't we protesting In-N-Out?
4:33
Josh: This is super fascinating to me. And it gets even better than this.
4:37
Josh: If you think that's funny, it gets even better.
4:39
Josh: So basically, the report looked at tokens per burger. So we were able to get
4:44
Josh: a metric for how you can actually justify output.
4:47
Ejaaz: Wait, wait, wait. Run that unit by me again.
4:49
Josh: We are breaking the news right here on Limitless. We are measuring water efficiency by tokens per burger.
4:54
Josh: And a single burger's water footprint is about 245 gallons of water.
4:59
Josh: That equals 2.7 billion AI output tokens, which roughly equates to one burger...
5:06
Josh: Being equivalent to using Grok 30 times a day for 668 years.
5:12
Josh: So the numbers are just absolutely astronomical.
5:16
Ejaaz: Wait, wait, wait.
5:17
Josh: Before I'm done, wait, one more thing, one final conclusion to this.
5:21
Josh: There are over 400 in and outs. There's so many of them.
5:25
Josh: And there's what, maybe 10 AI data centers? So the scale and the magnitude at
5:29
Josh: which they are wrong is just so astronomical.
5:33
Josh: I found it really funny like once you actually get into the numbers you realize
5:35
Josh: this is so not a problem that it's.
5:38
Ejaaz: Not even funny wait dude so this is you're telling me so this is incredibly click
5:42
Ejaaz: baity basically um the figures are astronomically
5:45
Ejaaz: wrong and if you compare it
5:48
Ejaaz: to just a casual restaurant we're talking about burgers only here by the way
5:51
Ejaaz: we're not talking about the fries sides and everything else just milkshakes
5:55
Ejaaz: god knows how much one of the milkshakes use we're just talking about the burgers
5:59
Ejaaz: including like their restaurant output and the supply chain for this so the
6:03
Ejaaz: fact of the matter is, this problem isn't really a problem.
6:06
Ejaaz: It's actually massively overblown. But what I'm curious about,
6:09
Ejaaz: Josh, is like, okay, is this a realistic take?
6:13
Ejaaz: Like, I know that data centers use a lot of water.
6:15
Ejaaz: How are they using it? And like, how much of this is renewable versus is actually
6:19
Ejaaz: burned and evaporated into the air and we'd never get it back?
6:23
Ejaaz: Like, what's the comparison?
6:24
Josh: Yes, yes, yes. Okay, so the truth, they are using lots of water.
6:27
Josh: There's hundreds of millions of gallons per year that are going through these data centers.
6:30
Josh: Some of it gets lost, a lot of it gets preserved. And the way they do it is
6:34
Josh: there's two types of cooling.
6:35
Josh: There's dry cooling, and then there's adiabatic cooling, which is the process
6:39
Josh: where air cools down without exchanging heat with its surroundings.
6:42
Josh: So if you remember the old iPhone episode that we did that talked about vapor
6:45
Josh: chamber, you can imagine scaling a vapor chamber to the size of an industrial data center.
6:49
Josh: And that's roughly how the adiabatic cooling works.
6:52
Josh: So it evaporates the water, the water leaves the system, and that's where they
6:56
Josh: lose about 267 million gallons per year.
6:58
Josh: And then the second loss function is the flush and discharge.
7:02
Josh: So one thing that I learned in preparing for this episode is that,
7:05
Josh: I mean, there's a lot of mineral buildup in the water that they use.
7:07
Josh: And 67 million of those get discharged as waste water per year.
7:12
Josh: But those are the two ways they do it.
7:13
Josh: It's dry and it's adiabatic. And there are promises in 2027 and 2028 from a
7:19
Josh: lot of the major AI labs to decrease this waste to about 95%.
7:23
Josh: Currently, it sits about 90%. So 90% gets recycled, 10% gets lost.
7:27
Josh: Those numbers are going to increase incrementally until about 2030 when the
7:31
Josh: number is actually net positive.
7:33
Ejaaz: Okay, so it sounds like the classical way of thinking about how data centers
7:37
Ejaaz: get cooled is you run a bunch of water in pipes through all these different GPUs,
7:43
Ejaaz: and it removes the heat from these GPUs so they are able to perform at optimal levels, right?
7:49
Ejaaz: And part of this water evaporates, never to be seen again, and some of this
7:54
Ejaaz: water gets kind of recycled over and over again. And the adiabatic system,
7:59
Ejaaz: I think is what you said, is kind of a hybrid of both of these things.
8:02
Ejaaz: But most importantly, it's more of a closed loop system.
8:05
Ejaaz: So we've kind of got like the majority of the water being renewed.
8:07
Ejaaz: So there's a comparison between water being renewed and water being consumed,
8:13
Ejaaz: which means lost forever. Do I have that right?
8:16
Josh: Yeah, so there's, you could think of a closed-loop system, going back to that vapor chamber.
8:21
Josh: If a vapor chamber is 100% efficient at being closed-loop, where water reaches
8:25
Josh: the processor, it heats up, it evaporates. As it evaporates, it dissipates the heat.
8:29
Josh: This is that at scale, although with some sort of a loss function at the end,
8:33
Josh: where some of that evaporated water does currently exit the system.
8:36
Josh: It sits now at about 10%, and that's where that loss comes from.
8:39
Ejaaz: But I'm guessing it's not 1.7 trillion gallons of water a year. Yeah, it's a
8:43
Josh: Far cry from the 1.7 trillion number. And then there's a second aspect to this
8:48
Josh: that gets a lot of criticism, which is the actual power generation,
8:50
Josh: how much water gets used in the generation of energy through these turbines
8:54
Josh: that are natural gas, some solar.
8:56
Josh: And the answer to that is, in the case of Colossus 2, 0%. There is no meaningful
9:00
Josh: water consumption of power generation at all.
9:02
Josh: The entirety of it comes from cooling the GPU system, which is closed loop and done with water.
9:08
Josh: So maybe we just go into where that 1.7 trillion number even came from.
9:12
Josh: Because this is the source of
9:14
Josh: a lot of the narrative that we've seen play out over the last few weeks.
9:17
Ejaaz: Exactly. So I'm showing all of you folks who are watching a scientific paper
9:23
Ejaaz: from UC Riverside titled Making AI Less Thirsty.
9:27
Josh: When you say scientific, you have to do air quotes.
9:30
Ejaaz: Yeah, sorry, sorry. Pseudoscience. From this university called Making AI Less
9:35
Ejaaz: Thirsty, uncovering and addressing the secret water footprint of AI models.
9:40
Ejaaz: Now, this paper is the source of a lot of the clickbait headlines and TikToks
9:46
Ejaaz: that you watch online. It's this one number.
9:49
Ejaaz: 1.7 trillion gallons of water will be consumed by AI data centers alone by 2027.
9:55
Ejaaz: That's around the corner. We're talking about next year here, right?
9:58
Ejaaz: And so a bunch of people kind of like threw up their hands and started protesting
10:01
Ejaaz: data centers because they were like, that is so much water.
10:04
Ejaaz: We're not going to be, we humans aren't going to be left with enough water to
10:07
Ejaaz: consume ourselves. Right?
10:08
Ejaaz: But here's what this study actually says. It claims 1.7 trillion gallons of
10:14
Ejaaz: water are used for withdrawal.
10:17
Ejaaz: That's a fancy term of saying recycled.
10:20
Ejaaz: So imagine like the water being taken, used to cool down the systems,
10:24
Ejaaz: the GPs that we just mentioned, and then recycled again and again and again.
10:29
Ejaaz: So it's not net new water we're talking about here.
10:32
Ejaaz: Josh, do you want to know the actual consumption that is being like permanently
10:36
Ejaaz: removed, the ones that we should be trying to protest?
10:39
Josh: Yeah, well, I mean, based on that, it's what? It's at least a full order of
10:42
Josh: magnitude off than what is projected.
10:43
Ejaaz: No, it's 100 to 158 billion, not trillion, billion gallons of water. That's 10%.
10:51
Ejaaz: Actually, it's less than 10% if you take the lower bound of the reported number.
10:56
Ejaaz: So the water that's actually being used by the data centers is only kind of like 10 to 15% of that.
11:01
Ejaaz: And okay, so some people then go like, what about the drinking water?
11:04
Ejaaz: Like what percentage of that is being affected from the study that was being
11:07
Ejaaz: made? It's only 3% of the headline number.
11:11
Ejaaz: So everyone took 1.7 trillion gallons of water and assumed all of that water
11:15
Ejaaz: was being wasted, never to be seen again, used again, and it was pulling from
11:19
Ejaaz: other resources when that strictly isn't being true. So the point I'm making,
11:23
Ejaaz: and I'm going to reiterate it again,
11:24
Ejaaz: The water, the 1.7 trillion gallons of water isn't being consumed.
11:28
Ejaaz: Think of it like this. Like imagine diverting a river to run through a mill. We do that today, right?
11:34
Ejaaz: And it flows back into the river. That's called withdrawal. That's the 1.7 trillion
11:38
Ejaaz: number that I'm pulling out here.
11:40
Ejaaz: So most of the power plant water is being reused over and over again.
11:46
Ejaaz: So that's only the first major kind of bit of pseudoscience that we needed to bust.
11:50
Ejaaz: But there's this second thing, and Josh, you mentioned it earlier from,
11:54
Ejaaz: ironically, Karen Howe, who wrote this famous book called...
11:58
Josh: Our favorite author.
11:59
Ejaaz: ...called The Empire of Air. Let me get this up here so everyone can see this book.
12:03
Ejaaz: It has been rated over 1,300 times on Amazon, but more importantly,
12:09
Ejaaz: it has been quoted directly by The Economist, The New York Times, and so much more.
12:15
Ejaaz: For this specific stack, it says Google's data center will use 1,000 times the
12:21
Ejaaz: water of an 88,000-person city.
12:25
Ejaaz: Guess what? It was off by a factor of not 1,000 times, 4,500 times.
12:31
Ejaaz: Josh, can you run me down these stats? Because it's just insane, dude.
12:36
Josh: No, that stat actually makes me sick. It's horrible. So instead of comparing
12:39
Josh: it to Google, we're going to start with golf courses because that's just...
12:42
Josh: If you want to come at it, you got to start with the golf course.
12:45
Josh: The average golf course, 312,000 gallons of water.
12:49
Josh: Desert golf course is 1 to 2 million. A Google data center in Virginia is 400,000.
12:54
Josh: Now what does that 400,000 give you?
12:57
Josh: That powers Gmail, Google Drive, YouTube, the entire G Suite for billions of
13:03
Josh: people around the world with the equivalent of 1.2 golf courses worth of water for billions of people.
13:09
Josh: Google's global data center that powers 4 billion accounts,
13:14
Josh: equals 43 golf courses. And in the state of Arizona, there are 370.
13:19
Josh: So if you're comparing apples to apples here, that is the Lufx comparison. And it's just so off.
13:26
Josh: This essay that was reported, this book that was published, it's off by like
13:30
Josh: several orders of magnitude. It's not even close.
13:32
Ejaaz: I mean, I'm looking at some of the things that they got wrong because someone
13:36
Ejaaz: did a breakdown of this book that's been quoted so many times and that's behind all these headlines.
13:41
Ejaaz: The book reported 5 million liters as the city's annual water use,
13:46
Ejaaz: but that was misconstrued.
13:48
Ejaaz: What she actually meant was 5 billion cubic meters.
13:52
Ejaaz: For understanding here...
13:54
Josh: Liters and cubic meters are very different things.
13:57
Ejaaz: Very, very different things. So she confused liters with cubic meters,
14:01
Ejaaz: which is already 1,000x error.
14:03
Ejaaz: But then she said the data center would actually use 3% of the municipal water system, not 1,000x.
14:09
Ejaaz: That's where we led to the 4,500x factor off that she was.
14:15
Ejaaz: So basically, it is an absolute incorrect piece of reporting that has been spread
14:21
Ejaaz: by some of the most important and popular media publications that we've seen.
14:24
Ejaaz: Josh, I want to kind of take your golf course thing a little further because
14:30
Ejaaz: I actually quite like that.
14:31
Josh: Okay, we'll keep going on the golf courses.
14:33
Ejaaz: So what's the number one state that's been getting a lot of protests about data centers? Arizona.
14:38
Ejaaz: Let's just look at the golf courses in Arizona. Arizona has 370 golf courses.
14:45
Ejaaz: Each golf course consumes about 1 to 2 million gallons of water per day.
14:50
Ejaaz: So that's around 400 to 800 million gallons per day for an Arizona golf course,
14:55
Ejaaz: right? For all the Arizona golf course.
14:57
Ejaaz: If you compare that to data centers that consume 905 million gallons,
15:02
Ejaaz: or rather 0.12% of county water,
15:07
Ejaaz: That's like just in Arizona alone. So golf courses in Arizona,
15:10
Ejaaz: 29 billion gallons per year.
15:12
Ejaaz: And a data center, the biggest one in Arizona, or actually collectively all
15:16
Ejaaz: of these, actually, my correction, is just 0.12% of that.
15:21
Ejaaz: 900 million gallons per year. So it's obvious that there's just a lot of misinformation out there.
15:28
Ejaaz: And I think it's really important to just bust this wide open completely. It's just wrong.
15:32
Ejaaz: And part of me thinks that a lot of the hatred, if I'm being honest,
15:36
Ejaaz: Josh, I think comes from people kind of equating AI to enriching people that they don't maybe like.
15:43
Ejaaz: Like, I get it. Like, AI will be used as a tool to enrich billionaires even further.
15:48
Ejaaz: It's so wasteful. I don't use it. What people don't realize is the average activity
15:52
Ejaaz: that you do on a weekend or the average bit of food that you might consume,
15:56
Ejaaz: buying a burger, 668 years straight of using Grok 30 times a day.
16:01
Ejaaz: People don't do that that often.
16:03
Ejaaz: It's just, it's important to level set, in my opinion.
16:06
Josh: Yeah, there are a lot of valid criticisms. This is unfortunately not one of them.
16:10
Josh: But there are some instances in which it does, or it has in the past actually
16:14
Josh: affected localized effects where very small towns have actually felt an impact of this.
16:19
Josh: They date most recently back to 2022.
16:22
Josh: There actually hasn't been many sources recently that have determined that it
16:27
Josh: is making a problem, but there have been some instances.
16:29
Josh: The first one was in Oregon, where a Google data center It consumed 29% of the
16:32
Josh: town's local water supply.
16:34
Josh: There's another one from 2019 in Virginia.
16:36
Josh: Virginia, famously, that's where a lot of the internet data center runs.
16:40
Josh: I think a majority of the data center is run from these Virginia AWS servers.
16:44
Josh: It consumed 63% of Lodon County in Virginia in 2019.
16:49
Josh: But since then, there really hasn't been that much of an interference with the local water supply.
16:54
Josh: And there have been solutions proposed from the companies who are most responsible for.
16:59
Josh: Creating that strain. And that is Google, Amazon, Meta, and Microsoft,
17:03
Josh: who all committed to be water positive by 2030 using new cooling techniques.
17:08
Josh: So that vapor chamber that we were talking about earlier will be done at an
17:11
Josh: industrial scale and will actually be able to preserve 100% of the closed loop
17:16
Josh: water supply. And I think that's going to be a really big deal.
17:19
Josh: That paired with direct to chip cooling is also going to make a big difference.
17:23
Josh: If you remember our Vera Rubin episode, where we talked about how the new chips
17:27
Josh: are cooled, the actual cooling temperature, if I remember right,
17:30
Josh: it was like 115 degrees Fahrenheit that it could be.
17:33
Josh: So now you could actually cool these ships with hot water. It requires much less.
17:37
Josh: Air cooling is getting a little more interesting.
17:40
Josh: There's a lot of solutions coming along the way that will make this a lot more
17:43
Josh: resource or a lot less resource intensive.
17:45
Ejaaz: Cool. So if I were to summarize some takeaways for this myth busting episode,
17:51
Ejaaz: there's a few that come to mind. Number one,
17:54
Ejaaz: The numbers just don't support the panic that people are putting out there.
17:58
Ejaaz: The fact is, AI data centers currently today, they might change later,
18:02
Ejaaz: Use a fraction of what golf courses, agriculture, the t-shirt that you're wearing consumes to produce.
18:10
Ejaaz: So even if we tripled AI water usage today, it would still pretty much be a rounding error.
18:15
Ejaaz: Number two, the context matters. You can't confuse 1,000 liters with 5 billion
18:22
Ejaaz: or whatever the number was, cubic meters of water.
18:26
Ejaaz: That is super important. And comparing water consumption for AI data centers
18:31
Ejaaz: and your average burger joint might just be the comparison that you need to
18:34
Ejaaz: kind of like set you straight and be like, okay, well, maybe this isn't that
18:37
Ejaaz: important going forward.
18:38
Ejaaz: And then the third thing, which I think is kind of underspoken about quite a
18:42
Ejaaz: lot is, I think, if I were to guess, we're moving towards a world where we end
18:47
Ejaaz: up actually using less water for data centers, right?
18:51
Ejaaz: Part of it is due to the different systems, like the adiabatic system that you mentioned, Josh.
18:55
Ejaaz: But also, I think a lot of these AI companies are going to start building water
18:59
Ejaaz: recycling plants to kind of push that 90% water renewability figure that we
19:04
Ejaaz: mentioned earlier much, much higher.
19:05
Ejaaz: I think Colossus 2 and Elon is doing that right now for Colossus 3,
19:10
Ejaaz: actually. They're building out a water recycling plant.
19:13
Ejaaz: So I think overall, this is a nothing burger, pardon the pun.
19:16
Ejaaz: And we're going to look back on this. Yeah, we're going to look back on this
19:19
Ejaaz: in the future and realize that we're consuming water in much faster ways in
19:24
Ejaaz: so many other industries that we aren't currently protesting.
19:26
Ejaaz: So keep quiet, eat your burger, and let the AI flow.
19:31
Josh: So if you had to guess what the next narrative would be, that has a negative
19:34
Josh: spin on it. Do you have any ideas? I think my answer is going to be energy.
19:38
Josh: I think they're going to start to converge on the correct argument,
19:42
Josh: which is the energy consumption on a localized scale, starting to actually impact
19:46
Josh: the cost per kilowatt of the average person's home.
19:50
Josh: And how does that get offloaded? Well, a lot more natural gas turbines, a lot more solar panels.
19:55
Josh: And the process of scaling that up is happening, but it's happening slower than
19:59
Josh: the scale at which they're consuming.
20:01
Josh: So when you take a gigawatt data center like Colossus 2, that is consuming the
20:06
Josh: equivalent collective output of San Francisco localized to a small town in Tennessee,
20:11
Josh: there are impacts there that are real.
20:13
Josh: It's just a matter of time until those kind of get uncovered and then get dealt with.
20:18
Josh: I mean, they are dealing with it quickly, but there is a real strain happening
20:22
Josh: on some grids that are localized to where these data centers exist.
20:25
Ejaaz: I agree with you. And I actually think the numbers that will be quoted on headlines
20:29
Ejaaz: about that specifically will actually be closer to home and to the point because
20:35
Ejaaz: It's simple enough to kind of scale new water techniques to kind of cool stuff down.
20:41
Ejaaz: Like we reported on a previous episode, I think like two weeks ago,
20:44
Ejaaz: that they're not even using cold water anymore.
20:47
Ejaaz: They're using warm water, 45 degrees Celsius or Fahrenheit, which is super warm.
20:51
Ejaaz: I think it's like 90 degrees Fahrenheit to cool these systems down.
20:55
Ejaaz: I think it's a different game with energy where we actually do have limited constraint.
20:59
Ejaaz: It takes so much more work and expertise to scale that. and we're going to have
21:04
Ejaaz: to tap into like town supply or city supply. So I agree with you.
21:08
Ejaaz: I'm looking forward to kind of like unpicking that one in the future.
21:11
Josh: Yeah, we'd be good at this. We should design the next PSYOP against our own industry.
21:15
Josh: I think that would be much better to consult with the experts prior to doing this next time.
21:21
Ejaaz: That's hilarious.
21:21
Josh: But yeah, I guess that concludes the Mythbusters episode on the first one that
21:25
Josh: we'll be dealing with, which is the water consumption and the new metric that
21:30
Josh: is burger or tokens per burger.
21:33
Josh: And in the case of our tokens per burger metric, the cost is very low.
21:38
Josh: And I don't think this is anything to actually worry about.
21:41
Ejaaz: That was the end of the episode, but I'm actually curious whether you guys enjoyed
21:45
Ejaaz: this. We hope you guys learn something new from this.
21:48
Ejaaz: Josh and I kind of like went back and forth on this, whether we should do this episode.
21:51
Ejaaz: We realized like a myth-busting series could be really cool because there's
21:55
Ejaaz: just a lot of myths and false claims out there and we face it every day.
21:59
Ejaaz: We try and unpack it, spend all of our time figuring this stuff out.
22:01
Josh: And I love that show growing up. It was great.
22:03
Ejaaz: Yes, same. Actually, dude, maybe we need to, we need to come back with some
22:07
Ejaaz: glasses for the next myth-busting episode. maybe a trench coat,
22:10
Ejaaz: like a fedora, if we really lean into it.
22:13
Josh: I'll write in my magnifying glass.
22:15
Ejaaz: Exactly. But yeah, if you found this informative, if you found this interesting,
22:18
Ejaaz: and you aren't subscribed to us, which apparently is around 70% to 80% of you,
22:23
Josh: Please do so. It's a percentage that is far too high.
22:25
Ejaaz: It's way too high. It is actually almost as high as these false headlines that
22:29
Ejaaz: we keep seeing about water usage for data centers.
22:31
Ejaaz: So if we're describing you currently, it takes two seconds. Please subscribe.
22:36
Ejaaz: Please turn on notifications.
22:37
Ejaaz: If you're listening to this on Spotify, Apple Music, or wherever the hell you
22:41
Ejaaz: listen to this on, please also do the same and give us a rating.
22:44
Ejaaz: It helps us out massively and puts our videos out to way more people so that
22:49
Ejaaz: we get more eyeballs on this and we can keep producing better videos for you. I think that's it, Josh.
22:55
Josh: Anything from you? Yeah, and just a small reminder about the newsletter.
22:57
Josh: Today, we just dropped a new piece that coincided with the roundup,
23:01
Josh: which was a weekly roundup of the five most important, noteworthy things that
23:04
Josh: you want to be informed on.
23:06
Josh: We post that twice a week, once every Wednesday, one's every Friday,
23:09
Josh: one's a thought piece, one's a recap.
23:11
Josh: So you can join 100,000 other people who are also subscribed to getting the
23:14
Josh: info prior to these episodes dropping.
23:16
Josh: And I think that concludes it. That just wraps it up. So thank you so much for
23:20
Josh: watching as always. And we will see you guys in the next episode.
23:23
Ejaaz: See you guys.