SPEAKER_06: All right, Freeburg is back. Welcome back to the All In Podcast, episode 160 something, your favorite podcast in the world, yada, yada, yada. With me again, the chairman dictator from off Polyhopeatea, the Rain Man. Yeah, definitely David Sacks is here and back from his time in the metaverse. We found him somewhere out in space in the solar system in his Apple goggles, your favorite, Sultan of Science.
David Freeburg is back from the metaverse.
SPEAKER_05: Hey, I missed you guys. Welcome home.
Thanks for having me.
SPEAKER_06: What did you discover when you went to Uranus in Google class? Sorry, Apple Vision class. Have you actually used the Apple Vision Pro, JCal? I ordered them, I ordered them and I walked by the Apple store and I was gonna go in and try them and there were so many lunatics in there, I was like, yeah, I'm not doing it. But I ordered them, you actually use them. I ordered one online to be delivered
SPEAKER_05:
and it was like delayed by a month. So I went down to the Apple store and picked one up.
Okay. My kids cannot stop using it.
SPEAKER_00:
Oh really? I went down to the Apple store but got cleaned out by the thief that stole everything. So.
SPEAKER_07: I do the Oakland one. I'm going all in.
SPEAKER_02:
We'll let your winners ride.
SPEAKER_02: Rain Man David Sacks.
SPEAKER_01: I'm going all in.
And it said, we open source it to the fans and they've just gone crazy with it.
Love you, Wes. I'm going all in. Queen of Kenwa.
SPEAKER_06: I'm going all in. That was crazy. That was crazy. We'll put the video in here. To the idiots who are robbing Apple stores, all the devices get bricked when you steal them and they all have GPS in them. Have you tried it, Jamal?
SPEAKER_04: No, I was too busy working out, making love and winning.
SPEAKER_06: Oh, okay. Got it. So you were making sweet love.
SPEAKER_06: You were watching your portfolio go up and you were just generally winning. Got it. Got it. Yeah. Yeah. So Freeburg, the rest of us were being men in the world, accomplishing stuff. But do tell us about your time in the metaverse.
SPEAKER_04: Do those goggles come with a lifetime prescription of SSRIs?
SPEAKER_05: You guys sound like one of these tech journalists that are actually anti-tech people. You guys are- Actually, tech journalists like it.
SPEAKER_05: Talking about the next gen computing platform. I remember when the iPad came out and everyone poo-pooed the iPad. I thought it was stupid. I tried to use it. I couldn't get any value out of it.
SPEAKER_05: And in 2010 or 2011, when did it come out? 2010, 2011, we started using it with our sales team selling to farmers. And we gave every sales guy an iPad and they went out in the field with 3G and they were able to close sales in the field, meeting with farmers, which had never been done before. Usually you have to get a farmer to come into an office. How many iPads did you sell? To sell the product.
SPEAKER_05: Oh, so we had like- No, no, no. We're selling client.com software.
SPEAKER_06: We had dozens of these sales guys.
SPEAKER_05: We gave them out to our sales agents as well, the independent agents. They started using them. And it was like a real game changer in how sales was done in agriculture. And I had never even contemplated that when I first used the iPad. So let's get to brass tacks here.
SPEAKER_06: What is the killer app? What do you think in the next five years, people are going to be doing with this thing on a daily basis? Is there a daily use case?
SPEAKER_05: I'll say a couple of things. One is like, I feel the same way I did about the iPad, which is I don't know what it is today, but I can tell that there's something there. And I'll give you an example of something I thought about. First of all, the AR is game-changing. If you've used like the meta, the Oculus Quest,
it like makes me super dizzy. It makes my head hurt, makes my eyes hurt. Like you're super disorienting. What Apple solved is that you're like still in reality, but then you get to interact with these three-dimensional kind of objects in reality. And it's like really well done. It's definitely V1 and there's going to be incredible changes in the next couple of generations, but it gets rid of all that dizziness, disconnected kind of stuff that happens with the full VR experience, which I thought was really incredible. Then last week, and I'm sorry I missed the show, we have a facility with my company in North Carolina. We have this giant greenhouse facility and I was doing meetings with farmers and stuff. I go to the greenhouse facility and there's so much work that the greenhouse techs and lab techs are doing
SPEAKER_05: where they're using an iPhone and a barcode scanner and a printer and they're holding all these pieces of equipment, scanning the QR codes on flowers, taking the pollen out, putting it in the next flower, training each other how to do it. And I was like, I put this Apple Vision Pro on and I was like, man, all the apps and all the tools that we had all these different pieces for that was taking people tons of time, image collection, data collection could all just be done streamlined while you're working. You could have a task list. It's like Minority Report, yeah.
SPEAKER_06: Yeah, you have a task list on the right,
SPEAKER_05:
cameras are taking images in the middle, QR codes are automatically scanned, data is being ingested, the task list is kind of giving folks next steps, they could listen to music while they're working. And I realized for that job, and I met with all the team out there and spent time with them, and I actually did the work that they do to get a better sense for the workflow. And I was like, man, literally every aspect of this job will be massively improved and productivity will go up by 10X with these goggles. Will it happen in the next couple of weeks or months? I don't know, but my engineering team is looking into it. Can we take it? Can we use some software? Can we build some software? And can we put this on folks
SPEAKER_05: to give them a better work experience, increase our productivity, to do automated data capture? So I don't know exactly where it goes, but I could start to see how this can become a more ubiquitous part of a workforce setting and not just be a video game and movie tool for consumers. So I'm reasonably optimistic about where this goes. It's definitely V1. I feel like it's the iPad days where no one's really sure where the applications are, but yeah. Enterprise applications. Unbelievable.
SPEAKER_06:
Makes total sense.
SPEAKER_05: And also training, training, right? Assembly line, workforce, surehouse workers,
where you're getting real time kind of task updates, data's being ingested all in real time. And by the way, the other thing I'll say is training is incredible. There's spatial video recording on it. So it looks like you're living through the experience that someone else had. So you can train someone how to do a difficult task and rather than have a human go spend hours training a workforce, the workforce can be trained by the goggles in a way that you cannot do a two dimensional video today. So I don't know. I'm pretty optimistic.
SPEAKER_06: Very strange days, right? I don't know, you're a fan of sci-fi, but remember strange days? Totally. So Tramath, what's gonna happen first here?
SPEAKER_06: Are humans gonna become more like robots by putting these on and do this factory work? Or is Elon with Optimus and some of Humane, I think is the other one. There's a couple of other people building a general use robots. Figure is the other one. Figure, yeah. Which one wins the day? Is it gonna be humans having eyes and data collection like robots or robots having appendages like humans? Well, let me put two ideas together
SPEAKER_04: and see what you think of this argument.
If you think about the generation of human beings that have as close to any other generation before it
lived in a totally immersive world, I would say the best representation of that are current teenagers and 20 year old people and maybe at the upper edge, the early 30s people.
And why is that? They've lived inside of social media their entire lives. They've lived inside of immersive video games their entire lives. But the question is, are they better off and happier as far as we know from an evolutionary perspective? And I would tell you that the answer is a huge gaping no.
So if you believe that the rise in depression,
the rise in suicide, the dependency on drugs, the dependency on SSRIs, the sexual promiscuity, the lack of marriage, the lack of kids, if all of those things are in some ways
a correlated by-product, let's not say it's causal, right? Let's just say it's a correlated by-product of this entire immersive, almost exclusionary detached world that these folks have grown up in. Taking that to the limit, I'm just gonna put out there,
SPEAKER_04: it may not be the solution to our problems. And so I guess the more directed answer to your question is I would hope that the latter wins so that we take these goggles off and actually learn how to talk to each other and look each other in the eyes,
get married and have children because I think that's actually better for the world.
And I would probably say that it's almost better for the world than a 10X thing of productivity.
Interesting. And then you see the correlation to cancer and disease that is disproportionately higher amongst these young people so I think it's at some point to ask ourselves what is structurally happening in the lives of these 16, 15 to 31-year-olds that is just so poor in terms of outcomes and if you look at some of the environmental variables that they live in and then take some of those and take them to the limit, I think that there's a reasonable argument that their lives get worse before it gets better.
SPEAKER_06: Yeah, I mean the amount of time you spend on social media is correlated with depression. Not just social media, I'm just saying
SPEAKER_04: just this immersive, I'm gonna detach from the world and live through a microphone and glasses
SPEAKER_04: taken to the limit, I'm not sure is the solution to these kids feeling detached, lonely, isolated. Isolated, yeah.
SPEAKER_06:
I mean it correlates all of these things that we're seeing in this younger generation correlates with the introduction of the smartphone. So could it be a good productivity device?
SPEAKER_04: Yes. Of course. So I hope it's a good productivity device, yes, but if we try to make it the panacea for anything and everything, I think we're going to compound the systemic issues that these young people have and I suspect on the margin, if you were gonna bet, all of these things that we see in these young people today will get worse as a byproduct of technology, not necessarily get better. So if you can take a different path like Optimus or the figure AI robots where that work is done, at least we have a different problem, probably maybe even more existential. Abundance.
SPEAKER_04: But a different problem which is now how do you find purpose but maybe you can find purpose through connection and the types of things that humans have been bred over billions of years to actually optimize for.
SPEAKER_06: Okay.
SPEAKER_06: Sax, I remember when you were starting Kraft,
you fired up like a group for VR and you got pretty heavy into it, you made a couple of small bets, I remember. I don't think any of it worked out really, you could tell me if I'm wrong here, but you got in a little bit earlier there. Maybe you could talk about the business case for this and has that changed because you believed, I believed a lot of folks thought, hey, maybe this is the time when Zuck really started, had bought Oculus and they started putting out some good product.
Seemed like it was a false start. Is this the actual starting pistol and is this the start of the VR AR adoption race?
SPEAKER_00: I don't think we're quite there yet. Okay.
We've been talking about VR being a thing for over a decade.
SPEAKER_06:
Yeah, no, more like 30. Remember the Nintendo VR stuff?
SPEAKER_00: It's like always on the verge of happening. I think that the big complaint about the Apple devices has a lot of capability, but it's still a pretty huge device to wear on your forehead. This is not really gonna be comfortable enough
to be something that people want to use all the time.
SPEAKER_00: I mean, there's also a question of use cases, but they're getting there with the use cases.
In any event, I do think that Apple Vision Pro is, it's like I said last week, it's a useful prototype or proof of concept and it will get better. So I'm glad they did it, because I think you need to start somewhere and then just keep iterating. But eventually for this to, I think, really take off, you need to shrink the form factor, miniaturize the technology, just every version of it make it simpler, lighter, easier to use.
SPEAKER_06: Yeah, I mean, eventually it'll feel like sunglasses. And so that is, I guess, if they become like regular glasses I think we all agree it becomes the next computer platform. I don't know, I gotta tell you,
SPEAKER_05: I feel like it's pretty damn comfortable. I don't know if you guys, you guys haven't really used it, but that's what I've heard. That's the surprising part is people are online saying
SPEAKER_06: it's comfortable. Unlike any other headset
SPEAKER_05: I've ever worn, they did an incredible job designing the ergonomics of it. What does it feel like?
SPEAKER_06: Does it feel like ski goggles?
SPEAKER_05: It doesn't feel heavy, it doesn't feel pressure. Compare it to ski goggles. If you were wearing ski goggles. It's less constricting than ski goggles, it's more comfortable. It like floats on you a little bit. They did a great job with this cushioning device they built and the band you put on. It feels very natural. It's Apple design, right? It's like a really well-designed product that's unlike anything else you've ever tried. I've always felt like when Apple comes into the race,
SPEAKER_06:
that's the starter's pistol. And I think this is it because I've heard the same thing from everybody. You have to try it. It feels like different than Oculus and some of those versions that came out previously.
And they have the app ecosystem.
And I would not discount that when, you know, the ability to monetize the app ecosystem and have all the people who are already building the com app, the Uber app, whatever notion, you know, all the stuff that people use and love, Spotify, YouTube, and then port it over here for tonight, whatever.
I think that's going to be the magic. And the statistics are not lying here. I mean, this is unbelievable. They've sold already 200,000 units, which doesn't seem like a lot, but for V1, that is a lot. And they're going to sell a half million this year.
It's going to be close to like, that's not that many.
SPEAKER_00:
Well, it's a couple of billion.
SPEAKER_00: Meta sells more.
SPEAKER_06: They do. Yeah. But you know, this is $4,000. This isn't 500. So to sell that many of a $4,000 device is incredible. It's a proof of concept.
SPEAKER_00: It's not like a regular Apple product that is a mass market device that tens or hundreds of millions of people are going to buy, but it puts them on a path to where they can iterate
SPEAKER_00: and keep making it better.
SPEAKER_06: See, I think, and this is, I guess, what I'd ask Freeberg, do you compare this to buying a MacBook Pro,
buying an iPhone or buying the Oculus, you know, whatever, the, you know, $500 unit, because everybody I see talking about online is comparing it to the purchase of a laptop
because of the desktop. And you can kind of do your coding or surf the web and do all that. Where do you put this? Is it buying a TV? Is it buying a laptop? Is it buying a smartphone? What would you say the analogy is? You have to have a keyboard to be really productive on it
SPEAKER_05: if you're going to use it for writing purposes or coding purposes. So it doesn't really work with just the headset,
but you could do that.
Yeah, it's definitely like buying a new computing device, but people felt the same way about the iPad. Go back to 2010 when the iPad came out
and everyone was like, who is it for?
SPEAKER_05: It's a whole new computer. Who's it for? You already have a phone. You already have a computer. Why do you need an iPad? And then they sell tens of millions a quarter now.
SPEAKER_05: So I really, as I do the math on this, I was just kind of doing some back of the envelope stuff. I think they're going to sell a hundred billion dollars of Apple vision pros, not this version, but this version plus the next version probably over the next.
SPEAKER_05: I would guess for them to get to a hundred billion in sales, it'll take them less than five years.
SPEAKER_06:
I think they're going to run the table on everybody. I think they're going to own the entire space. I think everyone's underestimating this
SPEAKER_05: as a new computing platform. And once these applications, particularly in the enterprise setting, start to kick in. And I will say that the movie watching experience is way better than watching on a TV in your living room. My kids cannot stop asking me to use the goggles to watch instead of an iPad or TV.
SPEAKER_05: Because you see 3D, like all Pixar movies are natively 3D. And so you've got the Disney plus app on there. You watch a Pixar movie and you're watching in 3D. The kids are blown away. So I think we're all going to be surprised by how this goes.
SPEAKER_00: Disney is all in on it. Remember when our parents told us not to sit too close to the TV.
Now we're just strapping the thing to our face.
SPEAKER_06:
Yeah.
I had the most Silicon Valley moment ever. I go to buy a cup of coffee. I was going for a little walk. I see blue bottle. I'm like, oh, you know what? I'll get myself a mocha. I lost a little bit of weight. I'm going to treat myself. $9 for a mocha. Number one, that tilted me. In the city?
$9 for a mocha? It was $8 and then I gave a dollar tip. And then I felt cheap giving a dollar tip. It's $8.99 for a carton of clover milk, all organic.
SPEAKER_04:
SPEAKER_04:
You can make infinite lattes at home. Anyway.
SPEAKER_06: Where did you go for your $9 mocha?
SPEAKER_06: I'm in Palo Alto right now because we lost power. So it's like the blue bottle?
SPEAKER_06: Yeah. I posted this. I'm like $9. What am I doing? You know, I just, I felt like buying a chocolate bar. Look at the stain your dirty lips left on the cup.
SPEAKER_04:
Oh my God. Look at that.
SPEAKER_06: You know what? You're a little obsessed with my lips. Take it easy though.
SPEAKER_04:
SPEAKER_06: So anyway, then there's a kid in the place wearing the goggles with the keyboard. No, stop. He's pounding. He's getting work done. This kid was doing work. And I tell you the truth.
SPEAKER_04:
He was putting in the hours. He was putting in the hours.
SPEAKER_05:
No one looks at your laptop. No one looks at your screen. That's what I love about it. You can do all your work without anyone seeing what you're doing. This kid had four desktops up.
SPEAKER_06: This guy was probably on Pornhub, Spotify, writing code.
SPEAKER_04: How many words did this person say to another human being while you were there? No, zero. And you know what? But when they're on a laptop, they're the same.
SPEAKER_06: What's the difference? He's coding. Nobody but it and I. I think they're gonna run the table on this. I think it's 100 billion in sales. 100 billion sales under five years. I take the over. I take the over.
SPEAKER_06: What do you, you got the over or the under? Because even if they keep it at three grand,
SPEAKER_05: they gotta sell 30 million units to get to 100 billion. They're gonna make up a lot of money in this app store too, by the way.
SPEAKER_04: I think that you guys are right that it's gonna be successful in terms of revenue. What I'm asking is a more societal question is do you guys actually think it's better?
SPEAKER_06: No, I don't want my kids in this all day, no. And I can see this becoming super addicting.
SPEAKER_04:
Hey, Freeberg, can I buy three for your kids? Just have them walk around with them? No, I have a no iPad in the house rule as well.
SPEAKER_04: But wait a minute, hold on. What about productivity, Freeberg?
SPEAKER_04: My kids aren't trying to be productive.
SPEAKER_05: They're using it to burn cars. It's called childhood.
SPEAKER_04: You don't even have a productive childhood. It's supposed to be not productive. You guys understand that at some point, you guys will be the only six kids
whose parents haven't given them the stupid thing to put on their face? No, this is gonna be time restricted.
SPEAKER_05: I have a no iPad, no phone, no, like, I let them use the headset because we got it for them.
SPEAKER_04: No, no, it burns their brain away.
SPEAKER_05: It burns their brain away, it's terrible.
SPEAKER_04:
Man, absolutely not.
SPEAKER_05: I totally agree with you. Social interaction, the loss of our ability to communicate as humans is critical and it's a fail point. I do think that there are applications where these things create great unlocks. I think this is an enterprise device.
SPEAKER_04: Can you imagine giving the field sales team on the farms to go there? They can take off their sweaty headset when the sun is shining and then give it to the farmer to put on. And then he can put it on and feel the sweat and the headband will be wet. No, that's not the use case.
SPEAKER_05:
It doesn't, by the way, it's a very personal device. In order to log in, it does like a eye scan
or you have to have like a login like you do with your phone but then you gotta reset the eye because it automatically sets the eye position.
So when you put on someone else's headset, you gotta reset the eye, it's a whole thing. So it's not a transferable device. It's a very personal computing kind of thing. So I don't think it's gonna be the same as like an iPad or a phone. It's a very different kind of thing. I don't know what it's gonna look like yet. I say next week we do the show inside of these
SPEAKER_06: or at least me and you, Freebird, will be, is there a zoon app for this? It would actually be very funny.
SPEAKER_05:
There's an avatar thing. So what it does, it scans your face while you're talking. It looks ridiculous. And all four of us can see each other as the avatar. Yeah.
SPEAKER_04:
Let's do it. It'll be hilarious. I had a moment this week in parenting. I had a moment this week where I told one of my children that when I send a text message, I expect an immediate response.
SPEAKER_04: Otherwise I am going to cancel that child's phone and take it away. And then separately, when they respond, it has to be in structured, well thought out, perfectly formatted English.
And then third, I said every single email I see from you interacting with your teachers or anybody else that's there to help you needs to be incredibly well written and formatted. And if I see garbage English, I'm gonna take your phone away.
SPEAKER_05: Oh, okay. So you don't want them on their phones, but they have to respond right away.
SPEAKER_04: Well, they have very strict rules on what they can use. They're there for literally, all they can do is communicate. Like they can use iMessage.
But it is shocking to me that despite the lack of games that they have or whatever, how poor they are in being able to communicate and what little access to devices they have, have already made them orders of magnitude
less able to communicate than frankly, I was able to when I was their age. And so I can just imagine what happens
when you become even more ensconced in something that you can cocoon yourself with and not have to interact with the rest of you. I don't disagree with you. I don't disagree with you. Not to say that it's not gonna be a revenue generator, but I think that you could just as easily, frankly,
SPEAKER_04: instead of impacting Apple's revenues, you can probably go along the makers of SSRIs, pot.
Here comes a spread trade. Pot.
Bumble and Tinder, and you'll get to the same place economically.
SPEAKER_06: All right, here we go. We've got a lot on the, what a great leap forward for humanity.
SPEAKER_04: I can't wait.
SPEAKER_06:
I just see this as a laptop replacement.
Okay, I wanted to talk a little bit about
what apparently is gonna be the spread trade of the last year. Meta has continued their unbelievable run and Snap dropped like 30%. Here's a chart for y'all of Snap versus Meta. You can take a quick look at it here. And just for context, both companies did great during COVID and ZERP, hit all time highs in 2021, but they both got crushed due to the ad spend pullback, obviously. But then Meta started to get less focused on their headsets and more focused on AI. Started doing their reduction in head count, 22% year over year from 86,000 to 67,000
the last quarter for Meta. And their quarterly profits have increased to an all time high of $14 billion. That's profits folks in Q4 for Meta.
All time high for the stock price $470 a share, $1.2 trillion market cap. Snap down 60% from its closing price on its IPO day in 2017. Let me just jump to Chamath before I get into more charts and everything. You pointed out Chamath and maybe you could explain to the audience just how ridiculous the voting rights were
and the massive dependence that the Snap team
and the executives had on stock based comp. Two issues for you Chamath.
SPEAKER_04: Well, I mean, I think I said it before. I think that case studies have been written
about how tilted the governance is in Snap.
I think the point is that they basically have infinite to zero voting power over common shareholders. So there's no real feedback loop. And I think that that has probably adversely affected
the types of people that traffic in their stock. Now, look, activists and short sellers
sometimes have a very bad reputation.
But if you steel man their side of it, what they are there to do is to shine a light on inefficiency and in the short seller case, sometimes in propriety, but it should all lead to companies being better run.
I think Meta had this example where they had a really big hiccup and everybody including us sort of pointed out the levels of spend that they were making
really didn't make any sense. I think we had a chart that compared the level of spend of Meta second only to
like the spaceship program, right? Just like bonkers, an enormous amount of money. And look, Mark got the message.
He heard it loud and clear.
I think he got fed up with whatever was going on there and he fixed it and it's in the numbers.
Now, I don't know Snap because to be honest with you, I've never taken more than one second to look at that company.
And the reason is there's just zero ability for me to have any useful say. So I've never honestly looked at its performance. I've never studied a single characteristic. I've never trended it.
And I think the point is that I am probably where a lot of other reasonably smart folks who could give a reasoned opinion on how to make it better land.
And part of the reason is because there is no feedback loop that matters. And when you know that, why would you waste your time? At least in the Meta- There are other options, right? There are other options and Meta was another one. You can write a letter, it gets picked up on CNBC
SPEAKER_04: and Bloomberg and whatever, and all of a sudden they kind of pay attention. And I think, and you look at Disney, Nelson Peltz goes and gets Ike Perlmutter shares, buy some more, takes a large position. Thank you, Nelson Peltz, yeah.
SPEAKER_04: We'll see whether that fixes itself. The point is that in all of these other cases, people are investing the time because they think that there's even a small shred of a chance that the company listens. But if you literally have no say,
you couldn't even do a proxy, you couldn't vote the shares, why would you bother? And I think that that's more of an example where maybe there is a, so I don't even know why Snap did poorly. And again, I'm not gonna really take the time because it's like, why bother taking the time?
SPEAKER_06: Saq, should they unwind this like, no voting common shares, super voting shares nonsense? And should this go away as a concept in the stock market?
SPEAKER_00: Well, I mean, Facebook or Meta has a pretty similar concept. I mean, I guess Zuckerberg has 60% of voting control, whereas Evan Spiegel has 99%. So Snap is more egregious. The difference is that Zuckerberg is listening and Spiegel is not.
The reason why Snap is doing poorly is not because its revenue has deteriorated. So I looked up, let's put it this way, I asked ChatGPT for their key metrics. So assuming GPT is not hallucinating,
if you compare 2021 to 2023, their total revenue went up from 4.1 to 4.5 billion and gross profit went from, call it 2.4 to 2.5 billion. So not a huge increase, but revenue and gross profit were slightly up. But if you look at operating expenses, they went from 3 billion to 4 billion a year. And that is why their operating income or operating loss went from a $700 million loss
to $1.4 billion loss in two years. So that's the source of the problem is that they increased their operating expense
by a billion dollars a year from 2021 to 2023.
SPEAKER_06: It's pretty simple. They seem like they're the last ones to get the memo.
SPEAKER_00:
Yeah, they were the last ones to get the memo and just to finish the point. So you saw that a few days ahead
of this quarterly announcement, where their stock got crushed, they put out a press release saying they're gonna cut their headcount 10%.
Ahead of them.
It's too little, too late. Yeah, they knew, right? They knew they had a problem. So they released the press release saying, oh, we're gonna cut. Well, you should have done what Zuckerberg did. Zuckerberg did a 20% cut last year. He got serious. He got lean and fit. And instead, these guys held out, did nothing. Then when they know that the market's gonna crush them, they put out this lame announcement 10%. No, not 10%. Really, if you just wanna get back
SPEAKER_00: to where you were two years ago in terms of operating expense,
you need a 25% reduction.
Yeah.
SPEAKER_05: Yeah, but it's more than that. If you look at the numbers, let's use operating cashflow, it's 165 million for SNAP for the quarter. So their operations generated 165 million of profit. But for the entire year, because they lost money in the quarters prior, they generated free cashflow of only $35 million. So the business net, it produced $35 million of incremental cash. You know how stock-based comp accounting works? The charge happens when it vests. So this is what employees are vesting. During the year of 2023, employees vested $1.3 billion of stock-based comp. So that means new shares or options were issued that on an accounting basis, the options are valued using Black-Scholes and the shares are valued based on the share price. So they issued 1.3 billion of stock-based comp. So they generated 35 million of free cash and they used $1.3 billion to compensate employees beyond their objects. So that means that they paid employees 40 times the free cashflow that was generated for shareholders during the year, which is also equivalent to 10% of the enterprise market value of this company. So the enterprise value of the company is $15 billion. 10% of that was issued to employees to compensate them. Now, let me give you the story of another city, Meta. And by the way, Snap's share count, because they issued all the stock, the number of shares outstanding increased by 4% during the year. During the year, Meta's number of shares outstanding decreased by half a percent because they used cash to go and buy back stock. So they were able to reduce the shares outstanding. Now, as you guys talk about, Meta cut employee count by 22% and Snap cut employee headcounts by 3% during the year. But here's the crazy difference in performance. The stock-based comp expense for Meta during that year was about $14 billion that vested that year. That company generated $71 billion of operating cash flow. So while Snap gave employees 40 times the free cash flow, Meta gave employees about 20% of the free cash flow. And then Meta went around and they used some of that extra cash to buy back $20 billion of stock. So they bought back more shares than what the employees were issued that year were. So it shows such a difference in looking out for shareholders. So if I'm an investor, and by the way, Meta's creating like 25 times free cash flow, which is not a crazy multiple, given all the new businesses that they have in Lama 2 and the progression to cloud and other things that they might do. If I'm looking at those two businesses as a shareholder, you got this guy that controls the whole stock. He's giving employees a billion three of shares a year when he's only making $30 million of free cash flow a year. And then the other guy is issuing $14 billion of shares, buying them all back, and he's making 70 billion of free cash flow a year. I don't know, it's very hard to decide which one to go after.
SPEAKER_06: Spigal brought it up in an interview I saw, and a lot of the layoffs were top heavy. So he got rid of a lot of the top people who had these huge comp packages. And then what I'm hearing from a lot of executives is cutting these highly stock comped executives who also have big cash comp, cutting them, putting lieutenants in charge, and then moving more jobs to other locations where people don't expect stock-based comp. If you're in India or you're in South America, whatever, stock-based comp is not like the obsession it is here. So as everybody optimizes these businesses, I mean, Facebook even did a dividend. But why do they need 5,000 employees?
SPEAKER_00: So they announced roughly 500 job cuts out of what, 5,500 employees.
SPEAKER_07: That's crazy. I mean, should that company be operating
SPEAKER_00:
with 2,000 employees?
That's a good question, yeah. And Elon cut the number of Twitter employees from 8,000 to 1,500.
SPEAKER_05:
When you look at the number of apps that they're running and the number of products that they're running compared to Meta, right? Meta has far more apps, far more infrastructure. Meta is serving 3.2 billion daily active users. Snap is about 400 million. So Meta is 8x the users with many more applications and much more infrastructure.
So I think it's another great kind of ratio to look at the performance of these two. I think you're exactly right. Exactly, yeah.
SPEAKER_00:
The other advantage that Meta has is because they're so profitable, they have the resources to go big in AI. Big time.
SPEAKER_00: Which is very expensive. So yeah, so they are the leader.
SPEAKER_05: You get all this option value at Meta, which you don't get at Snap. There's all this infrastructure that they can leverage, much like Amazon did with AWS, into things like cloud, AI tools for third-party developers, third-party applications. And then obviously, Meta is the biggest advertising platform next to Google in the world now.
And there's much more that they can start to do to extend further into the platforms.
SPEAKER_06: They did get an awesome save. Remember Apple screwed them and was like, you can't track devices now. And that just took a massive hit in the ad network.
And it was all those headwinds. They were like, okay, we're just gonna use AI to optimize ads. And supposedly the AI optimization of ads, I was talking to somebody on the inside. They said, yeah, we got it all back. We gained it back. We've got massive AI advertising optimization going on. Totally. And that's great that Tim Cook kicked us in the nuts, but we don't care.
SPEAKER_05:
By the way, that's a great point, Jay Tal. It really says a lot about how Meta was able to respond to that change, which a lot of people speculated would destroy the advertising business. And the fact that they were able to engineer solutions to drive advertising revenue up to $40 billion, it's just mind blowing.
It's a really kind of impressive outcome for the team. And I think it speaks a lot to the quality of the engineers there. I think it's a great point. Sax, you tweeted that you're seeing a little SaaS bounce
SPEAKER_06: back all of a sudden. That's interesting. I am seeing something similar. Last year, last two years, you had a ton of people cutting their SaaS spend, maybe removing the number of SaaS vendors they had consolidating vendors. You tweeted many public and private software companies are experiencing accelerating growth after six to seven quarters of deceleration. SaaS recession appears to be over according to the SaaS
master, David SaaS.
You want to pack this for us?
SPEAKER_00: Well, it's still pretty early because not everyone's reported. But if you looked at the big tech cloud performance in Q4, you could see that there's a bounce back in here. This is net new ARR added for AWS, Azure, and Google Cloud. So you see here in Q4 that there's a huge increase in net new ARR for the big cloud computing platforms.
And then I think another bellwether is Atlassian. So we're still waiting to hear from HubSpot, Salesforce, Zoom, Adobe, companies like that. They haven't reported yet. But if you look at Atlassian. Atlassian makes Jira amongst other products.
SPEAKER_06: They're based in Australia. Yeah, exactly. Collection of SaaS companies, right? It's a collection of SaaS products.
SPEAKER_00:
Yeah, so net new ARR would be the amount of growth in that quarter.
And this is on a year over year basis. So you can kind of see Q4 of 21 was the absolute peak.
And then it plummeted.
And then it actually went negative for about a year.
SPEAKER_06: That's tough to be in a company with net new ARR going
negative.
SPEAKER_00: Yeah, that doesn't mean, by the way, the company is shrinking. It just means that the amount of net new ARR, which is the amount of growth, is actually smaller than that same quarter a year before.
SPEAKER_00: And then in Q4, you could see there's some acceleration here. That they're starting to add more. They added more net new ARR, I guess 33% more in Q4 than they did over the previous year.
SPEAKER_06: And part of that SaaS is because the comps are lower. And they kind of bottomed out. Yeah.
SPEAKER_00: They bottomed out. Now they're accelerating. So we're starting to see this in some of my board meetings as well, where in 2022, everybody was missing their numbers and re-forecasting down. And then they would miss the re-forecast. So by 2023, the forecasts were very, very conservative. And I would say now I'm seeing companies beat the lower forecasts in Q4.
SPEAKER_00: This wasn't happening earlier in the year. But finally, I think people are starting to beat their lower forecasts for Q4.
SPEAKER_04: That's the question that I was curious about. What do you actually think is happening? Is that we've re-baselined these businesses. So now what would have looked like just a massive miss over the last two years now looks like a beat because we've just completely reset expectations. Is it that? Or is it that the economy is actually expanding and we can count on some reasonable growth rates?
Is it a combo of the two? What do you think it actually is?
SPEAKER_00: Yeah, I mean, it's definitely a new baseline in the sense that, and if you go back to 2020 or 2021, we considered good growth to be 2 to 3x year over year.
And now if it's going from 60% to 80% growth year over year, you're happy. So there's definitely been a lowering of expectations. That being said, you still see in these numbers there has been a bottoming out. And we're starting to now grow from this new baseline.
So for example, I think with Atlassian here, we are seeing an increase in spend basically in growth. So the way a recession is typically defined is two quarters of negative growth. We had six to seven quarters of decelerating or negative growth.
SPEAKER_06: In SaaS, in tech. In SaaS, which is why I called it the SaaS recession or B.
SPEAKER_00: Yeah, it was actually kind of a depression, you're right.
SPEAKER_00: But now we're seeing quarter over quarter growth. So growth is re-accelerating. Growth is higher than it was. So is it going to get to where it was? That probably will take some time. But it feels like the problems in the ecosystem work themselves out. And now we're back to growth again.
SPEAKER_06: Yeah, I can add psychologically because I'm on a couple of SaaS boards as well. And psychologically, it felt like you tell me if I'm right SaaS, if you saw the same thing. There were two years of calling up customers. And they were like, we're consolidating vendors. And by the way, we did a RIF. And so we need 20% less seats. So we're going to have 20% less SaaS companies that we're buying from. And we're going to have 20% less seats. So you start putting that all together. Man, everybody was just in psychological triage mode. We cannot spend money. I don't want to lose my job. So if you're a procurement person or you're the CTO, you don't want to lose your job. You don't want to have more cuts. So you're like, well, I can cut some software costs. Do I get points for that? And the points you would score for the last two years was cutting costs. With the market ripping and you now got a really efficient company, you're like, hey, can we spend a little bit on SaaS to make the remaining employees even more productive?
OK, maybe that's a reasonable discussion. And then people are playing ball in terms of negotiating prices. So that's the other thing I see is like people are like, well, we'll take your software, but here's what we want to pay. And then they're coming to the board and saying, can we do this deal? Would have been a million dollar deal, but it's a $200,000. It's like, yeah, take the money.
Take the money. Let's bear hug that customer.
SPEAKER_00: The market is generally an escalator on the way up and elevator on the way down. So the recovery is going to take a long time. But at least we've bottomed out and we're in recovery as opposed to continuing declines.
SPEAKER_00: By the same token, if you're a startup and you're not seeing improvement in your Q4 sales, then you no longer have a macro excuse for why you're not doing well.
SPEAKER_06:
Interesting. And then, Freeberg, you added, you're like, I'll make my own software. You said some SaaS software is too expensive.
I'll put a developer on it. And so how's that working out for you? Are you still in that mindset of like, yeah, maybe we just build our own software?
SPEAKER_05: Yeah, I mean, it's not just us. I think we're seeing a lot of companies pursuing this path.
A couple of engineers can rebuild the functionality of core applications, particularly because I think if you think about the business model that
makes SaaS so great is they could value share. Rather than charge the cost of an engineer plus some margin, the great business model, the equity value that comes in software, is you can build something once that creates $100 of value. You could probably charge your customer $30, $40 for that product because it's saving them $60, $70, and they'll make that switch to software.
So the ROI-driven value share model in SaaS has made it incredibly valuable. The problem now is that an engineer can be hired to build the replacement, and so it creates price compression. So the SaaS company can no longer capture that much value because the savings is actually less than that because the enterprise might say, hey, I'm going to hire someone, and instead of spending $60,000 a year on your software, I'm going to allocate a quarter of an engineer's time to build that software, and it's going to replace that cost.
So I think that that's still the case. So while there might be bookings,
which are driven largely by a search for efficiency gains, a search for more profitability, for more productivity within an enterprise, there are other options for that enterprise to realize that productivity gain today, and that's what's going to cause, perhaps, price compression and more competition than has been the case. But I don't think that the adoption of software is going to slow down. It certainly seems to be re-accelerating, which is great. More competitive, right?
SPEAKER_06: We're moving into a hyper-competitive market, especially with AI. It's a mix of internal software. It's a mix of internal software.
SPEAKER_05:
As you guys know, there are very few traditional non-tech enterprises now that don't have a software team that can write code. So now that so many companies have software teams that write code, they're all going to be asking the question, should we be buying the software or should we be building something internal? Yep.
SPEAKER_06:
It's a classic buyer build situation.
All right. Let's talk a little bit about VCs and how they're investing in AI. There seems to be three camps shaping up here, Chamal.
You know, one group is like, the incumbents are going to win. You know, Microsoft, Google, Amazon, everybody. They're going to win the day.
So they're going to wait and see.
Then there's another group who is sitting it out because they're like, hey, open source is going to win. Metas committed to open source and collaborative platforms. I've been playing with Hugging Face with Sandeep as well as Youtumoth. And it's pretty amazing what's happening over there. And then a bunch are obviously placing bets right now. The valuations are absurd.
Founders Fund and Andreessen Horowitz, two notable firms, are approaching it differently. Founders Fund bought into OpenAI at a $29 billion valuation. But aside from that investment, they're generally avoiding the AI deals. On the other hand, Andreessen is betting heavily.
Character AI, Replit, 11 Labs,
Mishrel, you're also in Replit, Sax.
So what do you think? Is open source going to win the day? You've been picks and shovels the whole way. You've been talking about compression. Maybe this isn't actually a good market.
What's your thinking as a capital allocator, Chamal?
SPEAKER_04: I think foundational models will have no economic value. I think that they will be an incredibly powerful part of the substrate
and they will be broadly available and entirely free. Wow. So if you think about that, any closed model, especially a closed model that operates on the open Internet, is not very valuable.
And any open source model that trains on the open Internet
will make that so.
So in that world, things like Mistral and Llama
will essentially decay the market to zero.
So if you're looking at any economic value that has been captured up until today, if it has been captured by having a proprietary closed model trained on open data,
that economic value will go away.
And I think Google and Microsoft and Facebook and Amazon
and all these startups have a deep economic incentive actually to make that so.
So now you can evaluate what that means. So if you get an open model from Hugging Face that's just kick-ass, where do you spend money?
Well, you're going to have to spend money to actually train it,
to fine-tune it, maybe to have some pretty zippy inference.
And all of that means that there's a new kind of substrate that has to be built, which is all around the way that the tokens per second are provisioned to the apps that sit on top of the model. What that means is you need to go back to 2006 and seven and say, okay, when we first created the cloud,
who made money?
And fast forward 18 years later, it's the same people that are still making money. So the people that made money in 2006 and seven were Amazon principally because of EC2 and S3.
The perfect analogy of EC2 and S3 in 2024 is the token per second provider. Now, there you have to double click and say,
okay, well, what does a token per second provider need to do to make a lot of money?
And I think the ultimate answer is you need your own proprietary hardware. So who is in a position to do that?
Amazon has announced that they have an inference and training solution. For training, Cerebrus has announced a pretty compelling solution. Google obviously has TPU. Then there's a handful of startups, including one that I helped get off the ground in 2016 that I funded called Grok.
All of those companies are in a position to build a tokens per second service. Then you have companies like Together AI, which basically just go and take venture money and wrap NVIDIA GPUs.
And you can debate what the advantage will be there. One could say, well, it's not really a huge advantage over time. So my refined thoughts today are sort of what my initial guess was when we started talking about AI a year ago, which is the picks and shovels providers can make a ton of money. And the people that own proprietary data can make a ton of money. But I think open source models will basically crush the value of models to zero, economically, even though the utility will go to infinity, the economic value will go to zero. Did any of you guys see Chamath's interview
SPEAKER_05: with Jonathan Ross?
SPEAKER_04:
Nope, not yet.
SPEAKER_04: You put it out, right, Chamath? You made it public? You know, I did it just for my subscribers, but Jonathan is the founder and CEO of Grok, the company that I just mentioned. And the quick version of that story is
I would pour over the Google earnings results in the mid teens of 2000, because I was pretty actively investing in a bunch of different public equities. And Sundar said in a press release, he mentioned that they had rolled their own silicon for machine learning called TPU.
And I was like, what is going on that Google thinks that they can actually roll their own silicon? What must they know that the rest of us don't know? And so it took me about six or nine months, but through Sunny, I got introduced to Jonathan. And then we were able to get Jonathan to leave Google
and he started, and Jonathan was the founder of TPU at Google
and then he started Grok, which I was able to lead that funding round in 2016,
so eight years ago.
Anyways, I did a spaces with Jonathan, talking about the entire AI landscape and AI acceleration to my subscribers, but it was so good. I gotta say he was so impressive
that we kind of like figured out a way
to just play the space and tape it.
And then we published it to everybody. So it's on my Twitter for anybody that wants to listen to it. It is amazing. He is really impressive.
SPEAKER_05:
I was sitting on the 17 going to Santa Cruz, not moving for an hour and a half and I listened to it. So it kept me alive, but I thought it was really great.
What did you think?
SPEAKER_04:
SPEAKER_05: He's great, no?
He's great. He had some great insights. And I think he's very compelling in arguing
SPEAKER_05: why some of the big cloud providers today that are offering infrastructure for AI model training and inference are gonna be challenged
if someone can build full stack and do it successfully. So it was a really good interview. I actually think it's really worth listening to,
but I enjoyed it. Yeah, thanks for putting it out there. I was like literally just sitting in the car, browsing Twitter and I saw your thing and I clicked on it and then I just ended up listening to the whole thing. It's a little hard actually
SPEAKER_04:
when you do a space for your subs, you can't actually just flip a switch and then release it to all of your followers. So we actually had to literally play it
and then just capture the audio out and then republish it. But anyways, despite that inconvenience,
if anybody's interested in learning about AI hardware, he is very compelling and he's very educational.
SPEAKER_06: So Sax, your thoughts on just how you're approaching investing in AI, if you're specifically investing in the underpinnings of AI, picks and shovels, yada yada, or if you're just looking on the application level and it's that kind of approach.
SPEAKER_00: Well, we divided the space into three categories. One is the models themselves, the foundation models, which can be either open source or closed source.
There's infrastructure. So like Jamal was saying, it could be like model training.
It could be vector databases, tools that developers use to create the AI stack, typically inside their enterprise. And then the third would be applications, which can be things like copilots or it could be a pre AI app that's using AI to kind of turbocharge its capabilities. Most SaaS would be in the application bucket. And so that's principally where we're focused. Although we do look at infrastructure plays and models. However, I do think there is an argument for, I mean, really with the question of commoditization, well, like all the model companies just get totally commoditized.
Really we're talking about open AI, right? Because we're the leader. So the question is, can they maintain their lead?
I do think there is an argument that open AI will stay in the lead and actually do quite well.
And I think there's a few points there. One is that if you're a consumer, you just wanna use the best GPT.
SPEAKER_06: You wanna use Google.
SPEAKER_00: It's just like search, right? If Google is a little better or the perception is, it's a little better than Bing or the other search engines. You don't win a plurality of search traffic. You actually end up winning it all because consumers just want the very best one. So most of the tests show that open AI is still ahead of the open source models. And I think even people in the open source movement will tell you that open AI is, call it six months ahead. They have no doubt that open source will get to where open AI is now in six months. Nonetheless, if open AI just maintains a little bit of a lead over open source,
SPEAKER_06:
SPEAKER_00: then it could compound.
SPEAKER_00: It can basically win the vast, vast majority of the call it consumer search or consumer GPT market. So that's point number one. Point number two is now that open AI has these hundreds
SPEAKER_00: of millions of consumers using it, that's a pretty attractive audience for developers to want to reach. And open AI has done a really good job creating a platform for developers to create what are called custom GPTs. So most developers don't want to go through the hassle
of training a model, fine tuning a model, doing all of that work that you would have to do in the open source ecosystem. They just want to point ChatGPT at a repository of data or documents, information, have it learn what it needs to learn, fine tune it in that way, maybe add some lightweight functionality using open AI's platform to create a custom GPT. That's what I think most developers want is they just want a simple stack to work with and they're gonna prize, again, simplicity and the power of the developer tools over the theoretical control they get by rolling their own models, training and fine tuning their own models in open source. And so I think what you're seeing now is, I mean, how many custom GPTs have already been created on the open AI platform? I mean, thousands.
SPEAKER_06: It might be tens of thousands. I mean, there's so many. Yeah, it's so easy to create them, yeah.
SPEAKER_00:
So you have a classic developer network effect where you've got open AI aggregating hundreds of millions of consumers because they perceive that ChatGPT is the best. Then you've got developers wanting to reach that audience. So they build custom GPTs on the open AI platform. That actually gives ChatGPT more capability. And that's something that open source can easily catch up with.
SPEAKER_00: Well, actually, actually the flywheel.
SPEAKER_06: Just to finish the point. So yeah, so it is a flywheel where,
SPEAKER_00: classic operating system developer network effect
where you wanna use the operating system that has the most programs written for it.
SPEAKER_06: Yeah, and interestingly, Hugging Face has realized this and Hugging Face released this week, their own version of GPTs, which is really interesting. And you can pick SACs, which open source project you wanna use to make it. So unlike GPTs on ChatGPT, we have to pick theirs. On the Hugging Face one, you could pick, Llama or whichever one you want.
SPEAKER_04: There's an account called artificial analysis that you can follow. The thing to keep in mind SACs is that for any of this to be true, these APIs need to be usable. I mean, I don't know if you remember, but when we were building apps, even as back as the late 2000s and early 2010s, one of the things was there was a pretty important paper that was published by Google about attention span. And it would look at page load times in a cold cache environment. And it basically said you have to be at like 150 milliseconds. That's like best in class performance or faster. And I remember when we read that at Facebook, we went crazy. So much so that at one point, a small team and I kind of actually launched a stripped down version of Facebook to compete with Facebook. If there's a, Nick, you can probably find this article on TechCrunch and we did it without telling you it was called like Facebook Zero. Anyways, the point is speed matters. Because in the absence of having very snappy response, you could have the best model in the world. But if it takes 10, 20, 30 seconds to basically initiate and get back data from a fetch request, it's an impossible thing to do.
So I think one of the things that you have to keep in mind is that there are these two things that need to move at the same time. One is the quality of how the model is, but two is the speed and its responsiveness, which is a function of, again, hardware and your ability to basically tokenize tokens per second very, very quickly. So that developers are incentivized to not just play around in a sandbox, but to actually build production code. And I don't think we've seen that second thing happen because nobody is delivering it. And that's the big thing that nobody talks about. For example, like AWS, if you look inside of how expensive it is to build an app there, I've tried, even when they give you credits, the credits they give you aren't sufficient enough to even pay for half the power.
And then the way that they schedule and the way that they try to orchestrate you to use hardware
makes building production apps, unless you are willing to spend millions and millions of dollars for a very slow app, unfeasible.
And so if you go back to a startup economy raising money here, the venture investor should start asking the question,
well, what is the speed and usability of these services that I'm funding?
And the reason is because you could build the best experience in the world that runs on local hosts, but if all of a sudden you actually try to launch it as an app and the thing takes 35 and 40 seconds to generate something, it's DOA. And I don't think enough people ask those questions or understand that that's true. So this is why I think you have to sort of be looking at both of these two things at the same time, but this account is interesting because it kind of just
strips things down to the bare facts and they start to allow you as a third party to understand what you can do.
SPEAKER_06: Yeah, speed is just such a critical component of this and what Google found was, as you know, free brokers, you were there every time they lowered a certain number of milliseconds, the usage went up, right? People did more searches, which makes sense if you get your results back faster.
SPEAKER_05: Yeah, it was a key metric from day one at Google, Marissa Mayer, she ran all the consumer facing products at Google during this earlier era. She was like, beat it into the team.
I mean, if you guys remember one of the first, the first kind of early feature of the Google results page was the amount of time it took to load the results. They'd show you how many milliseconds it took. Yeah, they'd show you that.
SPEAKER_06: Yeah, they literally put your North Star metric exposed to the consumer, which that must have lit a fire under the asses of all the developers and server people, yeah?
SPEAKER_05:
Well, I mean, they were kind of showing off the quality of the infrastructure and the way they did indexing and everything, but the result really played out in usage.
The faster the results, the more frequently you would use the search engine and the more likely you were to come back. And it's amazing how much consumer behavior drifts based on milliseconds. Like you have a few milliseconds of delay. McDonald's learned this, right? I mean, if you look at the, if you ever see the movie,
SPEAKER_06: The Founder, where they explain the McDonald's process, they learned it too.
SPEAKER_04: Guys, look at this. This is really interesting on this analysis.
SPEAKER_00: I mean, Chamath, are you saying that you don't think OpenAI can achieve the necessary levels of performance?
SPEAKER_04: No, I'm saying two things. OpenAI is three different businesses. OpenAI has a closed model that's trained on the open internet. I think economically, it's gonna be very hard to sustain that unless they start buying all number of apps so that they can get some fine tunes that they control that are proprietary to them. So for example, if OpenAI were to buy all of Reddit,
that would be a really interesting development that would improve the quality of OpenAI in a unique and differentiated way relative to where things like Llama and Mistral will get to at the same time, as well as X's Grok. I think they're all gonna converge to the same quality in the next probably 12 to 18 months. That's point number one. Your belief there is there's enough data in those pools
SPEAKER_04: that everybody reaches parity. No, did you guys, okay, Nick, did you, so I published this primer on AI.
Yeah, we saw the primer, yeah.
SPEAKER_04: There is a slide in there, Nick, that you can pull out, but it just shows you that there is a converging
in the quality of the results as the number of the parameters of the model gets higher and higher. And what it effectively shows you is that we are already in the land of diminishing returns when models are trained on the same underlying data. So if you are using the open internet, Llama, Mistral, OpenAI, they're all getting to the same quality code point, and they will be there within the next six to nine months.
So that's business number one on OpenAI. Business number two is a consumer-facing app called ChatGPT that has a lot of legs, because I think people develop habits, it'll be very sticky, and I think it'll get better and better. And then the third business that they're in is selling enterprise services to large Fortune 500s.
In fact, if you look at their OpenAI data, what they talk about is they sell, they've sold already to like 94% of the Fortune 500. What does that mean? I think what that actually means is they've sold a lot of test environments and sandboxing, but again, in order to translate that into functional production code that's used by Bank of America, right, or Boeing in production,
you have to have zippy, zippy fast SLAs and a level of performance that no cloud provider yet has delivered, none, nobody. So Nick, if you just go to that, please the thing, I just wanted to show you this, because it's a really interesting chart. This is not mine, this is theirs. If you look at quality versus price acts, it starts to show you like, where do you wanna be? You wanna be in the upper left quadrant in their analysis. Right?
And so the point is, what you can see is that a ton of different models are getting to this same place.
And so obviously you'd wanna use the model that's the cheapest. Or most convenient.
Well, who's gonna pay for that? If you and your LPs wanna pay for that,
the person that figures out the way that it's the cheapest to give you the same answer will actually end up winning because you will run out of money and they will not.
SPEAKER_00: I don't know, I mean, I think that there's a lot of business problems inside companies where people just wanna very quickly set up their own,
again, custom GPT without having to go through
the time, the cost, the hassle of trying to do model training or fine tuning. So let's just back up. Here's the path that OpenAI is on. So step one, get hundreds of millions of consumers using it and getting them to view OpenAI or ChatGPT as the Google in this area. Strong presumption, this is just the one you go to when you have a question.
Step two, these same people, these same consumers
now wanna use ChatGPT at work because there's some research they wanna do. So OpenAI has just rolled out both enterprise licenses and team workspaces. So you can work collaboratively on the same queries in a team workspace. Step three is rolling out a very easy to use dev platform that allows developers to, again, create custom GPTs by just pointing OpenAI at repositories. And so let's say that you're the customer support team
and you wanna create a GPT to help customer support answer cases.
You could basically then train ChatGPT on,
ChatGPT on let's say every customer support ticket
and email that the company has ever produced, right?
Now you could wait for the company's IT department to get us to act together and figure out how to train an open source model on the same thing. But do you really wanna wait for that or do you just wanna get going? And now OpenAI has given you the enterprise license that you need to pacify the concerns about security
and privacy and all that kind of things. To some degree, there's always gonna be those super paranoid Fortune 500 companies that will insist on owning everything and doing it open source. Let me build on your example.
SPEAKER_04: So I run a small software company during the day called Hustle. And we saw a lot of tickets related to this specific
legislation that exists whenever you're texting or you're doing auto dialing stuff called 10 DLC.
And so we wanted to eliminate those tickets, right?
So I actually went and I built a GPT,
which was called the Privacy Policy Generator because a lot of these trouble tickets were because the privacy policies were bad. And we trained them using a handful of ones that were good
and a handful of ones that are bad with a bunch of rules. And I trained them on.
And it's wonderful, except I can't run it in production because it's not the kind of thing that is usable in that way right now.
It's still very difficult. And so all I'm saying is I'm happy to keep spending a few hundred dollars a month, a few thousand bucks a month, whatever it is that I'm spending, I don't quite exactly know.
And I agree with you. It was very easy. I think OpenAI does an excellent job
of getting off the ground. But what I'm also saying is that when you actually translate that into a mainline use case, where I wanna now give it to my support team and say, this is now a tool you can rely on. It's integrated into your workflow, into your other tools. It's integrated into how you pipe out data into Salesforce or what have you.
It's just very hard.
And I'm not saying it's not gonna get fixed. I'm saying we're just not there yet. And one of the rays in which it's not there is that there is no place I can go, including OpenAI,
that actually makes it fast enough to be usable in production.
SPEAKER_00: You wrote this on OpenAI stack. You wrote a custom GPT?
SPEAKER_06: Yeah, built myself.
Yeah, and you can do them on Hugging Face now. It's gonna be a lot of options.
SPEAKER_00: In terms of integrating into your workflows, I think that's a really interesting point because I saw a demo somewhere where now,
actually I think OpenAI announced this, that you can at mention a custom GPT. Yeah, yeah, Sonny showed me that this week on the Podoon.
SPEAKER_00: Yeah, in chat GPT, you can now at mention a custom GPT to kind of invoke it.
SPEAKER_06: Yeah, so how it works is you would say, hey, I'm heading to New York. What flights can I get at Expedia, at Kayak, whatever?
And then it gives you the results here
and you're kind of pulling that up.
SPEAKER_05: Just to the point about where data advantages lie and that's ultimately gonna drive value.
I cannot, I've tried to think a lot about this. I cannot think about a better data advantage
that is orders of magnitude better than anything else.
Say YouTube. YouTube. Say it, yeah. YouTube. Drinking game. So here's the numbers. I pulled this up.
SPEAKER_05: You guys know like GPT-3 and three and a half were trained with a heavy weighting on common crawl, which is this open source. Yeah, we talked about this before. Gil El-Baz runs it. Open source.
SPEAKER_05: Crawling of the web. The total amount of data in common crawl, which I think it counted, and I could be off on this, something like 40 to 60% of the weighting in GPT-3 or three, five, I'm off on this probably. So the total amount of data in that common crawl data set is about 10 petabytes, okay?
Based on YouTube's public statement recently, they're seeing about 500 hours a minute of video uploaded or 720,000 hours a day. And if you assume somewhere between, you know, just under 1080p on that video, we're talking about probably one to two petabytes of data being uploaded to YouTube per day.
So if you assume like over time, the definition of the video's gotten better and the amount of uploads gotten up, you could probably assume that there's roughly, I'm guessing, there's probably somewhere between 2,000
and 3,000 petabytes of data in YouTube growing by one to two petabytes per day, which makes YouTube's data repository 300 times larger than common crawl, which makes it bigger than anything else that anyone else has. And here's the amazing thing about it.
SPEAKER_05: It has video, it has image, it has audio, it has text,
it has everything, and it is growing.
SPEAKER_05:
So if you were to take a bet or build a thesis around this point that the data advantage is gonna drive value creation, if Google gets its act together and leverages the data repository at YouTube, it is an insurmountable moat that will only continue to extend because the quality of the YouTube experience and the network effects continue to accumulate for them. So I think it's the most valuable asset in the world today based on the thesis that AI value's gonna accrue to the data owner.
SPEAKER_04: I think you're making such an important point. This is why the counterfactual is true
and it's actually showing up in the data. And Nick will show you this slide again from the AI primer, but that is why we're seeing these diminishing returns freeburg in all of these third-party benchmarks of these models. We're all using the same datasets. It's all using the same dataset. So what we are proving is not that the underlying hardware can't scale, nor that transformers are only efficient to a point. That's not what all of this convergence is showing. It's that in the absence of proprietary data, you're just gonna get to the same model quality, and we're seeing a bunch of different models get to a very early finish line, which again, if people like Facebook are doing for free,
SPEAKER_04: that's much easier to underwrite because you don't have to underwrite it being a differentiator in five years.
SPEAKER_04: But if you have a startup with equity value tied to a model, I think it's very,
it's much more of a tenuous place to be in the absence of proprietary data.
SPEAKER_05: And everyone in the world has a camera and a microphone in their pocket and high-speed internet now from the phone in their pocket, and more and more people are uploading that content, that data that's being generated. YouTube's got this free data vacuum, and they're just out in the world, and most of it's getting uploaded to YouTube. Well, it is public-facing, though, so.
SPEAKER_04: It's not just true for text. It's also true for all of the image generation. So if you look at- That's what I'm saying.
SPEAKER_05: They can train more than just an LLM on it, right? They can build all sorts of-
SPEAKER_04:
Yeah, go ahead. No, no, no, I was just gonna say the version of common crawl for training these image models also exists, and so to your point, it's like we are all operating from the same brittle, very fixed, small quantum of training information.
And so that is why I think Facebook and Google
are doing a really important job by deciding that these models should be free, right?
And then being able to, so then the question that- That just accentuates their data advantage.
SPEAKER_04: It does, and I think that it allows them to decide how much to leak out. So for example, whenever like, if you were using a lot of Google services like GFS, Bigtable, BigQuery, you know, TensorFlow,
the versions that you had access to via GCP was always one or two generations behind what the Google employees got to use, right?
But it was still so much better than anything else that we could get anywhere else that you would still build to those endpoints. And I think there's a similar version of this where Facebook and Google probably realized like, look, we'll have version five running internally to optimize ads and all of this other stuff that makes our business that much better, and we'll expose version three to the public. But version three is still trained on so much proprietary data that it's so much better than version 10 and anything else that's just operating on the open internet.
SPEAKER_07: Right.
SPEAKER_04:
And you know, to your point,
SPEAKER_06: Freiburg, that's the outward facing stuff. YouTube is a collection of things people want to share. What Google also has is Google Docs and Gmail, things that people say privately. So they have another data resource there that they can tap, you know, and there'll be regulations and privacy around that.
But maybe there's a difference there,
SPEAKER_05: but I honestly can't think of the quantum coming close to YouTube, not even close.
SPEAKER_04: Well, the thing to Jason's point, which is really interesting is like, you know, there's a modality in AI called rag, where you can actually just augment
with very specific training on a very specific subset of documents to improve. It's like a hacked version of a fine tune. But the beautiful thing about that is like, if you have a Google workspace, my entire company runs on Google workspace. In fact, most of my companies do at this point,
SPEAKER_04: to click a button where all of a sudden now,
all of that stuff and all of my G drives, all of a sudden is trainable. So that the N plus first employee comes in and has an agent that's tuned on every deck, every model, spreadsheet. That's a huge edge.
SPEAKER_04: Huge edge. By the way, and as a CEO, if you gave me that choice, I don't think anybody underneath that reports to me has any right to make that decision. But as a CEO, I would click that button instantly. And I have that right as a CEO. And so like, that's the CEO pitch. It's like, look, I can just give you these agents that are like the next version of a knowledge base that we've always wanted inside of a company.
SPEAKER_06: Notion has this, you know, they've basically, you can start asking your entire Notion instance questions about Notion, which is incredible. And yeah, you can just, and as a CEO, you can see across everything, Chamath. Because as you know, with Google Docs, if you're in a compliance based industry like finance, you can see everything, every message, every email, every document, and you can search.
SPEAKER_04: The security model and the data model becomes
very complicated in all of that stuff. Like for example, like, how do you know that this spreadsheet is actually, you should learn on it,
but who gets to actually then have that added to the subset of answers, right? All of a sudden, like salaries, right? The HR information. Information gets put into the training model, very dangerous. Or subset A of a company's working on a proprietary chip design, but they actually, like the way that Apple runs, highly, highly segregated teams where nobody else can know. So there's all kinds of complicated security and data model and usage questions there, but.
SPEAKER_04: Yeah, Brave New World.
SPEAKER_06: So there's been a lot of discussion in real estate. You shared a video with us. Why don't you kick it off for us here, Freeburg? What's going on in commercial real estate and Saks, you've got holdings and a lot of that as well. So let's kick up the commercial real estate challenges
of the moment.
SPEAKER_05: Well, I mean, I think we're teeing off of Barry's comments at this event last week. He and I met backstage because I spoke right before him. And then he gave this talk, which is available on YouTube, where he talked about the state of the commercial real estate market. And particularly he talked about the office market.
Just to take a step back, to talk about the scale of commercial real estate as an asset class in the US. Nick, if you'll pull up this chart, the total estimated market value of commercial real estate in the US across different categories is about $20 trillion, with about $3 trillion being in the office market, which is specifically what he was talking about. He was saying that in the US, we're seeing people not coming back to work and all these offices are empty. And we've talked a lot about these offices being written down. So how significant of a problem is this? So $20 trillion asset class, obviously the multifamily market is probably not as bad as office and retail, which are the most heavily affected, each of which are about $3 trillion a piece. The rest of these categories seem relatively unscathed
in comparison, industrial, hospitality, healthcare. Those real estate sectors are probably pretty strong. Data centers obviously growing like crazy, self storage, the great market. If you pull up the next image, so it turns out that of the $20 trillion of market value, there's about $6 trillion of debt. So you can kind of think about that $20 trillion being $6 trillion owned by the debt holders
and $14 trillion by the equity holders. And the debt is owned roughly 50% by banks and thrifts. And this was this concern that we've been talking about
with higher rates. Is the debt on office actually gonna be able to pay, the debt on retail gonna be able to pay when half of that debt is held by banks and thrifts that as we've talked about have such a close ratio
to deposits that you could actually see many banks become technically insolvent if the debt starts to default. Barry's point that he made was if you look
at the office market, which is marked on everyone's books
as $3 trillion of market value, he thinks it's probably worth closer to 1.8 trillion.
So there's $1.2 trillion of loss in the office category.
And if you assume 40% of that 3 trillion is held as debt, you're talking about $1.2 trillion of office debt, a reduction from 3 trillion to 1.8 trillion means that the equity value has gone down
from 1.8 trillion to 600 billion. So they've lost equity holders in office real estate have probably lost two thirds of their value, two thirds of their investment. And who owns all of that?
Most of that 60 plus percent, call it two thirds of that is likely owned by private equity funds and other institutions where the end beneficiary is actually pension funds and retirement funds. And so if two thirds of the value has to be written off in these books and it hasn't happened yet, what's gonna happen to all these retirement funds? And this is where going back to my speculation a couple of months ago kind of gets revisited. If you're actually talking about a two third write down on the value in these funds, most of that being pension funds, you're not gonna see governments let that happen.
You're gonna see the federal government, there's gonna be some action at some point
SPEAKER_05: and it's unlikely the office market is gonna suddenly rebound overnight. If this stays the way it is, who's gonna fill that hole for retirees and pensioners because we're not gonna let that all get written down. Someone is gonna step in and say, we've got to do something about this. And there's gonna need to be some sort of structured solution to support retirees and pensioners.
Cause that's ultimately who ends up holding the bag in this massive write down. He didn't go all the way there in his statements. He was talking more about his estimate of 3 trillion to 1.8 trillion. And then I tried to connect the dots and what that actually means. And ultimately there's gonna be some pain felt by retirement funds. That's gonna need to be dealt with somehow. So, Sax, I don't know if that sits right with you.
SPEAKER_00: I think the big picture is right. I think you're applying a lot of averages. I think in the office market in particular, the typical office deal is more like one third equity and two thirds debt. There's just a lot more leverage. So that'd be point number one,
which makes the situation worse. Even worse, yeah. So I would say that there's a huge amount of equity that's been written off. But in addition to that, there's a lot of debt holders
SPEAKER_00: who are in trouble too. And that debt is held by regional banks. So these commercial loan portfolios are significantly impaired. That's what we saw with Community Bank of New York is that their stock cratered when they reported
higher than expected losses in their commercial real estate portfolio.
So, Freiburg, I think the point is just the pain from this is not just gonna be on the equity holders, but also on these banks,
which can't afford to lose very much. It's not evenly distributed.
SPEAKER_05: Yeah, right.
SPEAKER_05: Yeah.
SPEAKER_00: Right.
SPEAKER_05: And we saw this in San Francisco where some of these buildings have 70% debt to equity ratios and the value puts them in the hole
and equity's wiped out completely and the debt holders have to take a hit. And normally, that debt is not really written off very often.
SPEAKER_00: Well, this is why the debt holders don't wanna foreclose. They don't wanna get these buildings back because when they do, they're gonna have to write down the loan. As long as the loan is still outstanding and they haven't foreclosed, they can pretend that the value of the building is not impaired.
SPEAKER_06: Kick the can down the road is the best strategy for them.
SPEAKER_00:
So, it's called pretend and extend. So, what I'll do is they'll work out a deal
SPEAKER_00: with the landlord, the equity holder, that the equity holder will say,
listen, I can't pay the interest. So, they'll just tack on the interest basically as principle at the end of the loan
and they'll extend out the term of the loan.
SPEAKER_06: Which would wipe out the equity at a certain point, yeah.
In all likelihood.
SPEAKER_00: Well, what it does is it allows the equity holders to stay in control, own the building, right? Because, yeah, the equity holder can't make their debt payments today, but they're gonna postpone those debt payments till the end of the loan.
SPEAKER_00: And again, in the meantime, just kinda hope that the market recovers.
SPEAKER_06: Yeah, but couldn't that debt at some point, since they have so little equity in these buildings, typically just exceed the value of the property and it's like, I'm just working for the bank now and why am I even putting this work in?
SPEAKER_00: Because everyone kinda hopes that the market will recover and the value of their equity will go up
and they'll be able to make their debt payments again. So, if you're the equity holder, you'd rather hold on and have a chance of your equity being worth something in recovery, then definitely lose the building. And if you're a regional bank, you'd rather blend and extend or pretend and extend
SPEAKER_07:
SPEAKER_00: as opposed to having to realize the loss right now and showing the market that your solvency may not be as good as you thought. The same thing happened with government bonds. Remember that with SBB and these other banks, they had these huge held to maturity bond portfolios.
SPEAKER_00: These are mostly just T-bills that were worth, I don't know, 60 cents on the dollar when interest rates spiked from zero to 5%. But they didn't have to recognize that loss as long as they weren't planning to sell them.
SPEAKER_06: Right, and then when they had the bank run,
SPEAKER_00: they had to sell. Well, yeah, that's right. So, when depositors left because they needed their money or because there was a run or because they could get higher rates in a money market fund,
all of a sudden these banks had to sell their held to maturity portfolios and they had to recognize that loss. And that's when everyone realized, oh, wait a second, they're not actually solving.
SPEAKER_06: Okay, so, Jamaa, supply demand matters in real estate. We have a tale of two cities here. On one side in real estate for commercial real estate, no demand for office space, which is in way too much supply. Paradoxically, on the other side, we have this incredible market for developers, which is, gosh, there's not enough homes. I think we need seven million more homes and the demand is off the charts for homes, yeah?
Yeah, I mean, I think you're basically right.
SPEAKER_00: I keep trying to explain residential is not a great market either because interest rates have spiked up. So, there's not a vacancy problem. Multifamily developers are still able to lease the units. They're still able to rent. The problem is their financing costs have shot through the roof. So, again, let's say you were a developer who built multifamily in the last few years. You took out a construction loan. That construction loan might have been at 3, 4%.
Now, you wanna put long-term financing on it. But if you can even find debt right now because there's a credit crunch going on, you might have to pay 8, 9, 10%.
Yeah, but at least you can find a renter.
You can find a renter, that's true, but only at a certain price. And let's say you underwrote that property to, I don't know, like a five cap, like a certain yield. But now your financing costs are much higher than you thought. You might be underwater.
Meaning that even if you're fully- That situation isn't as bad as what's happening in-
SPEAKER_00: Why? I think it's worse in some ways. I think it's worse. If you're fully rented and your building is underwater
SPEAKER_00: because now your debt payments are much higher than you expected, then there's no business model.
SPEAKER_06: Yeah, but are we seeing that?
SPEAKER_04:
Are we seeing tons of multifamily go under?
SPEAKER_04: Can I make two points? One, I think David is right, which is that I don't know this market very well, but just as a bystander, here's what I observed. It seems that the residential market has a feature,
SPEAKER_04: and I don't know whether it's good or bad, but that feature is that you reprice
to market demand every year. So to the extent that supply demand is changing and default rates are up or whatever,
that's reflected in rents. And you see that because rents change very quickly and most human beings are signing six months to one year leases. So that reset happens very quickly, so it can more dynamically adapt. So to the extent that a market segment is impaired, you see the impairment quickly. On the office side, what I see is that there's been a structural behavior change in COVID that has reset in every other part of the world, except for the United States, where there are these, frankly, typically younger, typically more junior employees that have held many of these companies hostage in a bid to return back to office space. And so we know that there is this vacancy cliff that's gonna hit commercial real estate. We just don't know when, because they're in long-term leases, they're canceling these leases over long periods of time, so the reset cycle is longer. That's just my observation as an outsider. I don't know what that means for prices or anything else, but it just seems that at least the residential market can find a bottoming sooner, because you can reset prices every year, but commercial just seems like a melting ice. Directionally correct to you, Sax?
SPEAKER_04: That assessment?
SPEAKER_00: Commercial has both a demand problem and a financing problem. Multifamily just has a financing problem, but it's important to understand- You mean office.
SPEAKER_05: We're talking about office. Office, yeah. Because there's retail, and then there's office,
SPEAKER_05: and then there's other industrial. Did you guys see in China,
SPEAKER_06: China has 50 million homes ahead of schedule.
50 million additional supply that can house 150 million people. So as acute as our issues are, the China issue might be much, much, yeah, seismic.
SPEAKER_00: Can I just give you an example on the multifamily side? Okay, let's say that you buy a building. Okay, let's say you bought a building in 2021, the absolute peak of the market, and you could get debt at, say, 4%, okay? And you penciled out, let's call it a 6% yield that with the debt you're getting, so let's say you did two thirds debt at 4%, you could now lever up that 6% yield to 10%, okay? That's like sort of the math, right?
Now all of a sudden, and to get there, you'd have to do some value added work on the property. You have to spruce it up, okay?
Now it's a few years later, and your short-term financing is running out, and you need to refi, and you've done your value added work, but here's the problem. The overall valuations in the market have come way down, before the bank was willing to give you two thirds loan to value, now the values come way down. You may not even be able to get two thirds loan to value, so you're gonna have to do what's called an equity in refinancing. You're gonna have to produce more equity, you're gonna have to pony up more money, so instead of taking equity out, like when the deal goes well, you're gonna have to put equity in. You may not have that equity if you're the developer.
The other thing is that your financing cost now might be 10%,
so now you've got negative leverage. You're generating a 6% yield, but you're borrowing at 10% to generate that 6% yield. So the debt no longer makes sense. Again, you're not positively leveraged, you're negatively leveraged. So you're not gonna wanna take out that debt, and if you do take out that debt,
the building's gonna be underwater. It's not gonna be generating net operating income, it's gonna be generating losses. So that's why even categories like multifamily,
where you don't have a vacancy problem, there's strong demand,
SPEAKER_00: those properties still don't make sense. If you had long-term debt on your multifamily, if you were able to lock in that 4% loan for 10 years, you're fine. But for all the people who are refinancing now, who are coming up this year, last year, next year, they're in deep trouble. And that's why there's a rolling crisis in real estate, is because the debt rolls over time. It's not like everybody hits the wall and has to refinance at the same time.
SPEAKER_06: Well, thank God, right? I mean, this would be cataclysmic if it was. Can you imagine if Silicon Valley and San Francisco had to say, here's actually the reality, anybody wanna actually pay for this office all in the same year?
SPEAKER_00: Right. That would be insane. But the crisis is growing, is as the leases roll, and those old rents that were higher than market roll off, and now you have to take on new leases, if you can even get them.
SPEAKER_06: It's gonna be balanced. At a much lower rate. Let's be honest.
SPEAKER_00: And as the old loans roll that were at a much lower interest rate, you have to get financing even if you get it at a much higher interest rate. That's when all of a sudden these buildings go from being basically solvent to insolvent.
SPEAKER_06: Yeah.
I mean, Janet Yellen's just gonna bail these folks out. That means you won't bail out the banks themselves, but you'll bail out the creditors, obviously the people holding the bag.
They'll get bailed, yeah? That's everybody agrees? Janet Yellen?
Yellen.
SPEAKER_04:
Our Treasury Secretary.
SPEAKER_05: I don't know if she's gonna be the one to do it. There's gonna be congressional action on this stuff.
SPEAKER_06:
Yeah. I mean, they tend to lead it soon.
All right, for the Sultan of Science, David Preberg and David Sacks, and Chumaf Palihapitiya, the Chairman Dictator, I am the world's greatest moderator. We'll see you next time on the All-In pod. Bye-bye.
SPEAKER_01: Bye-bye. Bye-bye.
We'll let your winners ride.
SPEAKER_02: Rain Man David Sacks.
SPEAKER_01: I'm going all in. And it said, we open sourced it to the fans and they've just gone crazy with it.
Love you, West Coast. The queen of Kinwah.
I'm going all in. I'm going all in. Let your winners ride. Let your winners ride. I'm going all in. Besties are gone. That's cold 13.
That's my dog taking a notice in your driveway. So, we're gonna win.
SPEAKER_03: Oh, man. Oh, man. Oh, man. My appetizer will meet me at Glenstone. We should all just get a room and just have one big huge order because they're all just useless. It's like this sexual tension but they just need to release them out.
SPEAKER_01: What? You're a B.
What? You're a B. You're a B. What? We need to get merch. Besties are back.
SPEAKER_07: I'm going all in.
I'm going all in.
