E165: Vision Pro: use or lose? Meta vs Snap, SaaS recovery, AI investing, rolling real estate crisis

(0:00) Bestie intros! (2:08) Apple Vision Pro breakdown (20:46) Meta vs Snap: god-king CEO, dependent on ad revenue, drastically different performance (32:53) Positive signals indicating a big SaaS bounceback (41:06) VCs are split into three camps on how to approach AI investing (1:12:16) Rolling real estate crisis continues Follow the besties: https://twitter.com/chamath https://twitter.com/Jason https://twitter.com/DavidSacks https://twitter.com/friedberg Follow the pod: https://twitter.com/theallinpod https://linktr.ee/allinpodcast Intro Music Credit: https://rb.gy/tppkzl https://twitter.com/yung_spielburg Intro Video Credit: https://twitter.com/TheZachEffect Referenced in the show: https://twitter.com/Jason/status/1755273518416302522 https://www.macrumors.com/2024/01/29/apple-vision-pro-headset-sales https://twitter.com/Jason/status/1755386651080106166 https://www.google.com/finance/quote/META:NASDAQ https://investor.fb.com/investor-news/press-release-details/2024/Meta-Reports-Fourth-Quarter-and-Full-Year-2023-Results-Initiates-Quarterly-Dividend/default.aspx https://www.macrotrends.net/stocks/charts/META/meta-platforms/net-income https://www.google.com/finance/quote/SNAP:NYSE https://corpgov.law.harvard.edu/2017/05/26/snap-and-the-rise-of-no-vote-common-shares https://www.cnbc.com/2024/02/07/disney-q1-earnings-nelson-peltz-isnt-abandoning-proxy-fight.html https://www.cnbc.com/2024/02/05/snap-to-lay-off-10percent-of-global-workforce-around-500-employees.html https://d18rn0p25nwr6d.cloudfront.net/CIK-0001326801/c7318154-f6ae-4866-89fa-f0c589f2ee3d.pdf https://s25.q4cdn.com/442043304/files/doc_financials/2023/q4/SNAP-2023-Annual-Report.pdf https://cloudedjudgement.substack.com https://twitter.com/chamath/status/1754641005851328553 https://help.openai.com/en/articles/8554397-creating-a-gpt https://twitter.com/ArtificialAnlys/status/1747264832439734353 https://blog.research.google/2009/06/speed-matters.html https://techcrunch.com/2010/05/18/facebook-launches-0-facebook-com-a-mobile-site-that-incurs-zero-data-fees https://artificialanalysis.ai https://chamath.substack.com/p/deep-dive-artificial-intelligence https://twitter.com/danshipper/status/1751005727215301053 https://www.youtube.com/watch?v=7waMPlHugYI https://www.bloomberg.com/news/articles/2024-01-31/new-york-community-bancorp-slumps-on-surprise-loss-dividend-cut https://asia.nikkei.com/Spotlight/Datawatch/Housing-glut-leaves-China-with-excess-homes-for-150m-people

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Jason Calacanis?

  All right, Friedberg 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 Polly Hapatia, 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 Friedberg is back from the metaverse.

• 0:28David Friedberg?

  I missed you guys.

• 0:29Jason Calacanis?

  Welcome home.

• 0:30David Friedberg?

  Thanks for having me.

• 0:32Jason Calacanis?

  What did you discover when you went to Uranus in Google class? Sorry.

• 0:37David Friedberg?

  Have you actually used the Apple Vision Pro, J-Cam?

• 0:40Jason Calacanis?

  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 used them?

• 0:50David Friedberg?

  I ordered one online to be delivered, and it was like delayed by a month. So I went down to the Apple Store and picked one up.

• 0:57Jason Calacanis?

  Okay.

• 0:58David Friedberg?

  And my kids cannot stop using it.

• 1:00David Sacks?

  Really? I went down to the Apple Store, but I got cleaned out by the thief that stole everything, so.

• 1:05Jason Calacanis?

  I went to the Oakland one.

• 1:24Jason Calacanis?

  That was crazy.

• 1:25David Friedberg?

  That was crazy.

• 1:26Jason Calacanis?

  We'll put the video in here. To the idiots who are robbing Apple Stores, all the devices get pricked when you steal them. And they all have GPS in them. Have you tried it, Chuma?

• 1:34Chamath Palihapitiya?

  No, I was too busy working out, making love, and winning.

• 1:37Jason Calacanis?

  Oh, okay, got it. So you were making sweet love, you were watching your portfolio go up, and you were just generally winning. Got it, got it, yeah. Yeah, so Friedberg, the rest of us were being men in the world, accomplishing stuff. But do tell us about your time in the metaverse.

• 1:54Chamath Palihapitiya?

  Do those goggles come with a lifetime prescription of SSRIs?

• 1:59David Friedberg?

  You guys sound like one of these like tech journalists that are actually anti-tech people. You guys are.

• 2:04Jason Calacanis?

  Actually, tech journalists like it.

• 2:06David Friedberg?

  Talking about this 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. 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 I have to get a farmer to come into an office.

• 2:32Jason Calacanis?

  How many iPads?

• 2:33David Friedberg?

  To sell the product. So, so we, we had like.

• 2:36Jason Calacanis?

  No, they were selling climate.com software.

• 2:38David Friedberg?

  We, we had dozens of these sales guys. 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.

• 2:50Jason Calacanis?

  So let's, let's get to brass tacks here. 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?

• 3:00David Friedberg?

  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.

• 3:10Jason Calacanis?

  Okay.

• 3:10David Friedberg?

  If you've used like the Meta.

• 3:11Jason Calacanis?

  Yeah.

• 3:12David Friedberg?

  The Oculus Quest. It like makes me super dizzy, makes my head hurt, makes my eyes hurt. Like you're super disoriented. 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, 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,

• 3:56David Friedberg?

  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, 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.

• 4:22Jason Calacanis?

  It's like Minority Report, yeah.

• 4:24David Friedberg?

  Yeah, you have a task list on the right. Cameras are taking images in the middle, QR codes are automatically scanned, data is being ingested, the task list is kind of, you know, 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, 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? To give them a better work experience, to 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

• 5:08David Friedberg?

  part of a workforce setting and not just be a video game and movie tool for consumers. So I'm, 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.

• 5:21Jason Calacanis?

  Enterprise applications.

• 5:22David Friedberg?

  Unbelievable.

• 5:23Jason Calacanis?

  Makes total sense. And also training, training, right?

• 5:25David Friedberg?

  Assembly line workforce, warehouse workers, where you're getting real time kind of task updates, data is being ingested, all in real time. And, 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 with two dimensional video today. So I don't know, I'm, I'm, I'm pretty optimistic.

• 5:54Jason Calacanis?

  Very strange days, right? I don't know, you're, you're a fan of sci-fi, but remember strange days?

• 5:58David Friedberg?

  Totally.

• 5:58Jason Calacanis?

  So Tremoth, what's going to happen first here? Are humans going to 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.

• 6:12Chamath Palihapitiya?

  Figure is the other one.

• 6:13Jason Calacanis?

  Figure, yeah. Which one wins the day? Is it going to be humans having eyes and, you know, data collection like robots? Or robots having appendages like humans?

• 6:24Chamath Palihapitiya?

  Well, let me, let me put two ideas together 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? You know, 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?

• 7:05Chamath Palihapitiya?

  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 byproduct, let's not say it's causal, right? Let's just say it's a correlated byproduct of this entire immersive, almost exclusionary detached world that these folks have grown up in. Taking that to the limit, I'm just going to put out there, it may not be the solution to our problems.

• 7:50Chamath Palihapitiya?

  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 10xing 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, you know, 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,

• 8:35Chamath Palihapitiya?

  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.

• 8:42Jason Calacanis?

  Yeah, I mean, the amount of time you spend on social media is correlated with depression.

• 8:46Chamath Palihapitiya?

  Not just social media, I'm just saying, just this immersive, like, I'm going to detach from the world and live through a microphone and glasses, taken to the limit, I'm not sure is the solution to these kids feeling detached, lonely, isolated.

• 9:00Jason Calacanis?

  Isolated, yeah, yeah. I mean, it correlates, all of these things that we're seeing in this younger generation correlates with the introduction of the smartphone.

• 9:07Chamath Palihapitiya?

  So could it be a good productivity device? Yes.

• 9:09Jason Calacanis?

  Of course.

• 9:09Chamath Palihapitiya?

  Do 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, we're going to compound the systemic issues that these young people have, and I suspect, on the margin, if you were going to 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.

• 9:42Jason Calacanis?

  Abundance.

• 9:43Chamath Palihapitiya?

  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.

• 9:53Jason Calacanis?

  Okay. Sax, I remember when you were starting Craft, 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 start, you know, 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?

• 10:30David Sacks?

  I don't think we're quite there yet.

• 10:33Jason Calacanis?

  Okay.

• 10:34David Sacks?

  We've been talking about VR being a thing for over a decade.

• 10:39Jason Calacanis?

  Yeah, no, more like 30. Remember the Nintendo VR stuff?

• 10:43David Sacks?

  It's like always on the verge of happening. I think that the big complaint about the Apple device is it has a lot of capability, but it's still a pretty huge device to wear on your forehead. It's just not really going to be comfortable enough to be something that people want to use all the time.

• 10:57Jason Calacanis?

  Hmm.

• 10:58David Sacks?

  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.

• 11:33Jason Calacanis?

  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.

• 11:42David Friedberg?

  I don't know. I gotta tell you, I feel like it's pretty damn comfortable. I don't know if you guys, you guys haven't really used it, but.

• 11:46Jason Calacanis?

  That's what I've heard. That's the surprising part. People are online saying it's comfortable.

• 11:50David Friedberg?

  Unlike any other headset I've ever worn, they did an incredible job designing the economics of it.

• 11:54Jason Calacanis?

  Does it feel like ski goggles?

• 11:57David Friedberg?

  It doesn't feel heavy. It doesn't feel pressure.

• 12:00Jason Calacanis?

  Compare it to ski goggles. If you were wearing ski goggles.

• 12:03David Friedberg?

  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.

• 12:17Jason Calacanis?

  I've always felt like when Apple comes into the race, 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, Fortnite, 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 a V1, that is a lot.

• 13:01Jason Calacanis?

  And they're going to sell a half million this year. It's going to be close to like.

• 13:05David Sacks?

  That's not that many.

• 13:05Jason Calacanis?

  Well, it's a couple of billion.

• 13:06David Sacks?

  I mean, Meta sells more.

• 13:08Jason Calacanis?

  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.

• 13:17David Sacks?

  It's a proof of concept. 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 where they can iterate and keep making it better.

• 13:30Jason Calacanis?

  See, I think, and this is, I guess, what I'd ask Friedberg, do you compare this to buying a MacBook Pro, buying an iPhone, or buying the Oculus, you know, whatever, they, 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?

• 13:56David Friedberg?

  You have to have a keyboard to be really productive on it.

• 13:58Jason Calacanis?

  Uh huh.

• 13:59David Friedberg?

  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,

• 14:14Jason Calacanis?

  Who's it for?

• 14:15David Friedberg?

  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.

• 14:23Jason Calacanis?

  Yeah.

• 14:24David Friedberg?

  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 $100 billion of Apple Vision Pros, not this version, but this version plus the next version probably over the next. I would guess for them to get to 100 billion in sales, it'll take them less than five years.

• 14:42Jason Calacanis?

  I think they're going to run the table on everybody. I think they're going to own the entire space.

• 14:45David Friedberg?

  I think everyone's underestimating this 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. 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.

• 15:15Jason Calacanis?

  Disney's all in on it.

• 15:16David Sacks?

  Remember when our parents told us not to sit too close to the TV? Now we're just strapping the thing to our face.

• 15:21Jason Calacanis?

  Yeah. I had the most Silicon Valley moment ever. I go to buy a cup of coffee. I was going for my little walk. I see Blue Bottom. I'm like, oh, you know, I get myself a mocha, you know, I lost a little bit of weight. I'm going to treat myself. $9 for a mocha, number one, that tilted me. $9 for a mocha? Well, it was $8 and then I gave a dollar tip and then I felt cheap giving a dollar tip. You know, it's $8.99 for a carton of Clover Milk, all organic.

• 15:47Chamath Palihapitiya?

  I mean, you can make infinite lattes at home.

• 15:50Jason Calacanis?

  Anyway.

• 15:51David Friedberg?

  Where did you go for your $9 mocha?

• 15:53Jason Calacanis?

  I was, I'm in Palo Alto right now because we lost.

• 15:55David Friedberg?

  So it's like the blue bottle?

• 15:57Jason Calacanis?

  Yeah, I posted this, I'm like, $9, what am I doing? You know, I just, I felt like buying a chocolate bar.

• 16:03Chamath Palihapitiya?

  Look at the stain your dirty lips left on the cup. Oh my God, look at.

• 16:08Jason Calacanis?

  You know what, you're a little obsessed with my lip. Take it easy there. So anyway, then there's a kid in the place, wearing the goggles with the keyboard.

• 16:17Chamath Palihapitiya?

  No, no, stop, stop, stop.

• 16:18Jason Calacanis?

  He's getting work done. This kid was doing work. And I tell you the truth.

• 16:23Chamath Palihapitiya?

  Putting in the hours, he was putting in the hours.

• 16:25David Friedberg?

  No one looks at your laptop, no one looks at your screen.

• 16:27Jason Calacanis?

  That's what I love about it.

• 16:28David Friedberg?

  Work without anyone seeing what you're doing.

• 16:30Jason Calacanis?

  This kid had four desktops up. This guy was probably on Pornhub, Spotify, writing code.

• 16:36Chamath Palihapitiya?

  How many words did this person say to another human being while you were there?

• 16:39Jason Calacanis?

  No, zero. And you know what?

• 16:41David Friedberg?

  But when they're on a laptop, they're the same. What's the difference? He's coding.

• 16:44Jason Calacanis?

  Nobody, Bada and I, I think this is gonna, they're gonna run the table on this.

• 16:48David Friedberg?

  I think it's a hundred billion in sales. A hundred billion sales, under five years, yeah.

• 16:52Jason Calacanis?

  I take the over, I take the over. What are you, you got the over, the under?

• 16:55David Friedberg?

  Cause even if they keep it at three grand, they gotta sell 30 million units to get to 100 billion. They're gonna make up a lot of money on this app store too, by the way.

• 17:02Chamath Palihapitiya?

  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?

• 17:10Jason Calacanis?

  No, I don't want my kids in this all day now. And I can see this becoming super dicking.

• 17:13Chamath Palihapitiya?

  Hey, Friedberg, I, can I buy three for your kids? Just have them walk around with them.

• 17:16David Friedberg?

  No, I have a no iPad in the house rule as well.

• 17:19Chamath Palihapitiya?

  But wait a minute, hold on. What about productivity, Friedberg?

• 17:22David Friedberg?

  My kids aren't trying to be productive. They're using it to burn cars.

• 17:24Jason Calacanis?

  It's called childhood. You don't have a productive childhood. It's supposed to be not productive.

• 17:29Chamath Palihapitiya?

  You guys understand that at some point, you guys will be the only six kids whose parents haven't given them this stupid thing to put on their face?

• 17:37Jason Calacanis?

  No, this is gonna be time restricted.

• 17:39David Friedberg?

  I have a no iPad, no phone, no, like, I let them use the headset because we got it.

• 17:44Chamath Palihapitiya?

  For them, it's so good.

• 17:45David Friedberg?

  No, no, it burns their, burns their brain away. Burns their brain away. It's terrible. 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.

• 18:00Jason Calacanis?

  I think this is an enterprise device.

• 18:01Chamath Palihapitiya?

  Can you imagine giving a 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.

• 18:14David Friedberg?

  No, that's not the use case. It doesn't, by the way, it's a very personal device. In order to log in, you know, it does like a eye scan. Or you have to have like a login, like login like you do with your phone, but then you got to reset the eye because it automatically sets the eye position. So when you put on someone else's headset, you got to reset the eye. It's a whole thing. So it's not a transferable device. It's a very personal computing, you know, kind of thing. So I don't think it's going to 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 going to look like yet.

• 18:40Jason Calacanis?

  I don't know. I say next week we do the show inside of these, or at least me and you Free Bird will be, will be, is there a zoom app for this?

• 18:47David Friedberg?

  This would actually be very funny. There's a, there's an avatar thing. And so what it does, it scans your face while you're talking.

• 18:53Jason Calacanis?

  It looks ridiculous.

• 18:54David Friedberg?

  And all four of us can see each other as the avatar. Yeah.

• 18:56Chamath Palihapitiya?

  All right, 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. 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, 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 going to take your phone away.

• 19:34Jason Calacanis?

  Oh, okay.

• 19:35David Friedberg?

  So you don't want them on their phones, but they have to respond right away?

• 19:38Chamath Palihapitiya?

  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 the world.

• 20:14David Friedberg?

  I don't disagree with you. I don't disagree with you.

• 20:16Chamath Palihapitiya?

  Not to say that it's not going to be a revenue generator, but I think that you could just as easily frankly, instead of impacting Apple's revenues, you can probably go along the makers of SSRIs.

• 20:27Jason Calacanis?

  Here comes the spread trade.

• 20:30Chamath Palihapitiya?

  Bumble and Tinder and you'll get to the same place economically.

• 20:35David Friedberg?

  All right.

• 20:36Jason Calacanis?

  All right, here we go. We've got a lot on the...

• 20:38Chamath Palihapitiya?

  What a great leap forward for humanity. I can't wait.

• 20:41David Friedberg?

  Sorry.

• 20:42Jason Calacanis?

  I just see this as a laptop replacement. Okay. I wanted to talk a little bit about what apparently is going to be the spread trade of the last year. Meta is 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 headcount, 22% year-over-year from 86,000 to 67,000 the last quarter for

• 21:25Jason Calacanis?

  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.

• 22:07Chamath Palihapitiya?

  Well, I mean, I think I said it before. I think that case studies have been written about how

• 22:14Chamath Palihapitiya?

  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

• 22:36Chamath Palihapitiya?

  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, right? 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

• 23:21Chamath Palihapitiya?

  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 is 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.

• 24:02Jason Calacanis?

  Yeah.

• 24:02Chamath Palihapitiya?

  And when you know that, why would you waste your time? At least in the meta.

• 24:06Jason Calacanis?

  There are other options, right?

• 24:06Chamath Palihapitiya?

  There are other options and Meta was another one. You know, you can write a letter. It gets picked up on CNBC 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.

• 24:23Jason Calacanis?

  Thank you, Nelson Peltz, yeah.

• 24:24Chamath Palihapitiya?

  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'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 going to really take the time because it's like, why bother taking the time?

• 24:54Jason Calacanis?

  Sack, should, should they unwind this like no voting common shares, super voting shares nonsense? And, and should this go away as a concept in the stock market?

• 25:03David Sacks?

  Well, I mean, Facebook or Meta has a pretty similar concept. I mean, I guess Zuckerberg has 60% voting control, whereas Evan Spiegel is 99%. So Snap is more egregious. The difference is that Zuckerberg is listening and Spiegel is not. The, 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.

• 25:45David Sacks?

  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.

• 26:21Jason Calacanis?

  Yeah, they seem like they're the last ones to get the memo.

• 26:24David Sacks?

  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 going to cut their headcount 10%. It's too little, 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 going to cut. Well, you should have done what Zuckerberg did. You know, 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 going to crush them, they put out this lame announcement, 10%. No, not 10%. Really, if you just want to get back to where you were two years ago in terms of operating

• 27:09David Sacks?

  expense, you need a 25% reduction.

• 27:12David Friedberg?

  Yeah, but it's more than that. If you look at the numbers, let's use operating cash flow. It was 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 cash flow of only $35 million. So the business net 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.

• 27:56David Friedberg?

  So they issued 1.3 billion of stock-based comp. So they generated 35 million of free cash and they used 1.3 billion dollars to compensate employees beyond their OpEx. So that means that they paid employees 40 times the free cash flow that was generated for shareholders during the year, which is also equivalent to 10%.

• 28:16David Friedberg?

  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 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 headcount 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.

• 29:01David Friedberg?

  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, you know, about a 20% of the of the free cash flow. And then 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 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 is trading at like 25 times free cash flow, which is not a crazy multiple. Given all the new businesses that they have in Llama too, 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.

• 29:45David Friedberg?

  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.

• 30:01Jason Calacanis?

  Spiegel 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 comp executives. Who are, you know, 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. You know, if you're in India or you're in South America, whatever, you know, stock based comp is not like the obsession it is here. So as everybody. Optimizes these businesses. I mean, Facebook even

• 30:39David Sacks?

  Why do they need 5,000 employees? So they announced roughly 500 job cuts out of, what, 5,500 employees?

• 30:48Jason Calacanis?

  That's crazy.

• 30:49David Sacks?

  I mean, should that company be operating with 2,000 employees?

• 30:54Jason Calacanis?

  It's a good question.

• 30:55David Sacks?

  Elon cut the number of Twitter employees from 8,000 to 1,500.

• 30:59David Friedberg?

  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 a, it's another great kind of ratio to look at the performance of these two.

• 31:23Jason Calacanis?

  12 times as many.

• 31:24David Friedberg?

  Exactly, yeah.

• 31:26David Sacks?

  The other advantage that Meta has is because they're so profitable, they have the resources to go big in AI.

• 31:33Jason Calacanis?

  Big time.

• 31:33David Sacks?

  Which is very expensive. So yeah, so they are the leader.

• 31:36David Friedberg?

  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, the, you know, 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.

• 32:01Jason Calacanis?

  They did get an awesome save. Remember, Apple screwed them and was like, you can't track devices now? And like, that just took a massive hit in the ad network and was all those headwinds. They were like, okay, we're just going to use AI to optimize ads. And supposedly, the AI optimization of ads, I was talking to somebody on the inside. They said like, yeah, we got it all back. We gained it back. We've got massive AI advertising optimization going on. So

• 32:25David Friedberg?

  Totally.

• 32:25Jason Calacanis?

  Yeah, that's great that Tim Cook, you know, kicked us in the nuts, but we don't care.

• 32:30David Friedberg?

  By the way, that's a great point, Jake 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 is just mind-blowing. It's a really impressive outcome for the team and I think it speaks a lot to the quality of the engineers there. Yeah. I think it's a great point. Yeah.

• 32:53Jason Calacanis?

  Sacks, you tweeted that you're seeing a little SaaS bounce 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 Sacks. You want to pack this for us? What are you seeing?

• 33:24David Sacks?

  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 it.

• 33:59Jason Calacanis?

  Atlassian makes Jira amongst other products. They're based in Australia. Yeah.

• 34:03David Sacks?

  Yeah, exactly.

• 34:04Jason Calacanis?

  Collection of SaaS companies, right? It's a collection of SaaS products.

• 34:07David Sacks?

  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.

• 34:25Jason Calacanis?

  That's tough to be in a company with net new ARR going negative.

• 34:30David Sacks?

  Yeah. That doesn't mean, by the way, the company's 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.

• 34:42Jason Calacanis?

  Yeah.

• 34:44David Sacks?

  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.

• 34:55Chamath Palihapitiya?

  And part of that SaaS is because the comps are lower and they kind of bottomed out.

• 34:59David Sacks?

  Yeah. They bottomed down, now they're re-accelerating. So we're, you know, 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, and now I'm seeing companies beat their, the sort of the lower forecast in Q4. This wasn't happening earlier in the year, but finally, I think people are starting to beat their, sort of their lower forecast for Q4.

• 35:33Chamath Palihapitiya?

  That's the question that I was curious about. What do you, 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?

• 36:01David Sacks?

  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, you know, two to three X 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, in growth, right? So the way a recession is typically defined is two quarters of negative growth, right?

• 36:43David Sacks?

  We had six to seven quarters of decelerating or negative growth.

• 36:48Chamath Palihapitiya?

  In SaaS, in tech?

• 36:49David Sacks?

  In SaaS, which is why I called it the.

• 36:52Jason Calacanis?

  SaaS depression.

• 36:53David Sacks?

  Or B that, yeah, it was actually kind of a depression. You're right. 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 worked themselves out and now we're back to growth again.

• 37:11Jason Calacanis?

  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 point you would score for the last two years was cutting costs.

• 37:55Jason Calacanis?

  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, you know, productive? Okay, 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, 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. So yeah, take the money. Take the money. Let's bear hug that customer.

• 38:25David Sacks?

  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.

• 38:37Jason Calacanis?

  Yeah.

• 38:38David Sacks?

  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.

• 38:48Jason Calacanis?

  Interesting. And then Friedberg, you added, you know, you're like, I'll make my own software. You said, you know, 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?

• 39:03David Friedberg?

  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, if you can build something once that creates a hundred dollars of value, you could probably charge your customer thirty, forty dollars for that product because it's saving them sixty bucks, seventy bucks, and they'll make that switch to software. So, you know, the ROI-driven value share model in SaaS has made it incredibly valuable.

• 39:48David Friedberg?

  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 sixty grand 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 that cost. So I think that that's still the case. So while there might be bookings, there's still, 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.

• 40:28David Friedberg?

  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.

• 40:41Jason Calacanis?

  More competitive, right? We're moving into a hyper-competitive market, right? Especially with AI.

• 40:46David Friedberg?

  It's a mix of internal software. It's a mix of internal software. 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?

• 41:03Jason Calacanis?

  Yep. It's a classic buy or 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, Chuma. 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.

• 41:22Jason Calacanis?

  Then there's another group who's 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 Yu Chamath. 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, Mistral, you're also in Replit, Saks. So what do you think? Is open source going to win the day?

• 42:06Jason Calacanis?

  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, Chamath?

• 42:14Chamath Palihapitiya?

  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.

• 42:27Jason Calacanis?

  Wow.

• 42:28Chamath Palihapitiya?

  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 operates on the, that trains on the open internet will make that so. So in that world, things like Mistral and Llama

• 42:51Chamath Palihapitiya?

  will essentially decay the market to zero. So if you, 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.

• 43:06Chamath Palihapitiya?

  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.

• 43:49Chamath Palihapitiya?

  What that means is you need to go back to 2006 and '07 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 '07 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 tokens 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

• 44:34Chamath Palihapitiya?

  for training, Cerebras 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 rap.

• 44:58Chamath Palihapitiya?

  Nvidia GPUs.

• 45:01Chamath Palihapitiya?

  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.

• 45:34David Friedberg?

  Did any of you guys see Chamath's interview with Jonathan Ross?

• 45:37Chamath Palihapitiya?

  No, not yet.

• 45:38David Friedberg?

  You put it out, right Chamath? You made it public?

• 45:41Chamath Palihapitiya?

  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 was, I would, 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.

• 46:26Chamath Palihapitiya?

  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.

• 46:37Chamath Palihapitiya?

  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 is, he was so impressive.

• 46:50Chamath Palihapitiya?

  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 it's on my Twitter for anybody that wants to listen to it. It is amazing. He is really impressive.

• 47:05David Friedberg?

  I was sitting on the seventeen going to Santa Cruz, not moving for hour and a half, and I listened to it. So I kept me alive. But I thought it was really great.

• 47:15Chamath Palihapitiya?

  What did you think? He is great, no?

• 47:17David Friedberg?

  He's great. He has some great insights. And I think he's very compelling in arguing why some of the big cloud providers today that are offering infrastructure for AI model training and inference are going to 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 I was sitting in the car browsing Twitter and I saw your thing and I clicked on it and then I just ended up listening.

• 47:52Chamath Palihapitiya?

  Well, yeah, it was a little it's a little hard, actually, 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 like 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.

• 48:16Jason Calacanis?

  So Sacks, 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, you know, that kind of approach?

• 48:30David Sacks?

  Well, we divided it 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 co-pilots, or it could be a pre-AI app that's using AI to kind of turbocharge its capabilities. Yeah. 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

• 49:15David Sacks?

  is an argument for, I mean, really with the question of commodization, well, like all the model companies just get totally commoditized. Well, really, we're talking about OpenAI, right? Because they're the leader. So the question is, can they maintain their lead? I do think there is an argument that OpenAI 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 want to use the best GPT. You want to use Google. Exactly. 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

• 50:00David Sacks?

  best one. So most of the tests show that OpenAI is still ahead of the open source models. And I think even people in the open source movement will tell you that OpenAI is, call it six months ahead. They have no doubt that open source will get to where OpenAI is now in six months. Nonetheless, if OpenAI just maintains a little bit of a lead over open source, then it could Compound. Yeah. It could 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 OpenAI has these hundreds of millions of consumers using it, that's a pretty attractive audience

• 50:43David Sacks?

  for developers to want to reach. And OpenAI has done a really good job creating a platform for developers to create, you know, 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 OpenAI'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.

• 51:28David Sacks?

  And they're going to 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 OpenAI platform?

• 51:45Jason Calacanis?

  I mean, thousands, it might be tens of thousands. I mean, they're so easy to create.

• 51:48David Sacks?

  Maybe millions.

• 51:49Jason Calacanis?

  Yeah, it's so easy to create them, yeah.

• 51:50David Sacks?

  So you have a classic developer network effect where you've got OpenAI 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 OpenAI platform. That actually gives ChatGPT more capability.

• 52:09Jason Calacanis?

  Yeah.

• 52:09David Sacks?

  And that's something that open source can't easily catch up with.

• 52:12Jason Calacanis?

  Well, actually, actually.

• 52:14David Sacks?

  Just finish the point. So, yeah, so it is a flywheel where, you know, classic operating system developer network effect where you want to use the operating system that is the most programs written for it.

• 52:27Jason Calacanis?

  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, Sax, which open source project you want to use to make it. So unlike GPTs on ChatGPT, we have to pick theirs, on the Hugging Face one, you could pick, you know, Llama or whichever one you want.

• 52:48Chamath Palihapitiya?

  There's an account called Artificial Analysis that you can follow. The thing to keep in mind, Sax, is that for any of this to be true, these APIs need to be usable, right? I mean, I don't know if you remember, but when we were building apps even as back as the late 2000s. 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, right? And it basically said you have to be at like 150 milliseconds, right? 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.

• 53:34Chamath Palihapitiya?

  If there's a Nick, you can probably find this article on TechCrunch and we did it without telling anybody 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.

• 54:18Chamath Palihapitiya?

  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?

• 55:01Chamath Palihapitiya?

  And the reason is because you could build the best experience in the world that runs on localhost, but if all of a sudden you actually try to launch it as an app and the thing takes thirty-five and forty seconds to generate something, it's DOA. And I don't think enough people ask those questions or understand that that's true. So thi- 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.

• 55:36Jason Calacanis?

  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.

• 55:50David Friedberg?

  Yeah, it was a key metric from day one at Google. Marissa Mayer, she ran all the consumer-facing products at Google during this, you know, earlier era. She was like, beat it into the team. I mean, if you guys remember, one of the first, the, 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.

• 56:11Jason Calacanis?

  Yeah, they show you that. Yeah, they, 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?

• 56:19David Friedberg?

  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.

• 56:40Jason Calacanis?

  McDonald's learned this, right? I mean, if you look at the, if you ever see the movie The Founder where they explain the McDonald's process, they learned it too.

• 56:46Chamath Palihapitiya?

  Guys, look at this. This is really interesting on this analysis.

• 56:49David Sacks?

  I mean, Chamath, are you saying that you don't think OpenAI can achieve the necessary levels of performance?

• 56:54Chamath Palihapitiya?

  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 going to 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 going to converge to the same quality in the next probably 12 to 18 months. That's point number one.

• 57:35Jason Calacanis?

  Your belief there is there's enough data in those pools that everybody reaches parity.

• 57:40Chamath Palihapitiya?

  No, did you guys, okay Nick, did you, so I published this primer on AI.

• 57:45Jason Calacanis?

  Yeah, we saw the primer, yeah.

• 57:46Chamath Palihapitiya?

  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 are, you know, develop habits, it'll be very sticky and I think it'll get better and better.

• 58:31Chamath Palihapitiya?

  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.

• 58:59Chamath Palihapitiya?

  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 tax, it starts to start to show you like, where do you want to be? You want to 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 want to use the model that's the cheapest.

• 59:37David Sacks?

  Or most convenient.

• 59:39Chamath Palihapitiya?

  Well, who's going to pay for that? If you, if you and your LPs want to 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.

• 59:53David Sacks?

  I don't know. I mean, I think that there's a lot of business problems inside companies where people just want to 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, right? Strong presumption, this is just the one you go to when you have a question. Step two, these same people, these same consumers now want to use ChatGPT at work because there's some

• 1:00:38David Sacks?

  research they want to do. So OpenAI has just rolled out both enterprise licenses and teamwork spaces. So you can work collaboratively on the same queries in a teamwork space. Step three is rolling out a very easy use dev platform that allows developers to again, create custom GPTs by just pointing OpenAI at repositories. Okay. And so let's say that you're the customer support team. And you want to create a GPT to help customer support answer cases. You could basically then train.

• 1:01:18David Sacks?

  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 its act together and figure out how to train an open source model on the same thing, but do you really want to wait for that? Or do you just want to get going? You know, 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 going to be those super paranoid Fortune 500 companies that will insist on doing, on owning everything and, and doing it, doing it open source.

• 1:02:00Chamath Palihapitiya?

  Let me build on your example. 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, 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 the model. And it's wonderful, except I can't run

• 1:02:45Chamath Palihapitiya?

  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, right, where I want to 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.

• 1:03:29Chamath Palihapitiya?

  It's just very hard. And I'm not saying it's not going to 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.

• 1:03:44David Sacks?

  You wrote this on OpenAI Stack? You wrote a custom GPT?

• 1:03:48Chamath Palihapitiya?

  Yeah, built myself.

• 1:03:49Jason Calacanis?

  Yeah, and you can do the monogging face now. It's gonna be a lot of options.

• 1:03:53David Sacks?

  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.

• 1:04:05Jason Calacanis?

  Yeah, yeah, Sunny showed me that this week on the pod.

• 1:04:08David Sacks?

  Yeah, in ChatGPT, you can now at mention a custom GPT to kind of invoke it.

• 1:04:14Jason Calacanis?

  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, you know, the results here and you're kind of pulling that up.

• 1:04:26David Friedberg?

  Just to the point about about where data advantages lie and that's ultimately going to 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.

• 1:04:44Chamath Palihapitiya?

  Say YouTube.

• 1:04:45David Friedberg?

  Say YouTube.

• 1:04:46Chamath Palihapitiya?

  Yeah.

• 1:04:46David Friedberg?

  It is.

• 1:04:47Chamath Palihapitiya?

  Drinking game.

• 1:04:48David Friedberg?

  So here's, here's the numbers. I pulled this up. You guys know like GPT-3 and 3.5 were trained with a heavy weighting on Common Crawl, which is this open source.

• 1:04:58Jason Calacanis?

  Yeah.

• 1:04:58David Friedberg?

  We talked about this before. Gil Elbaz runs it. Open source crawling of the web. The total amount of data in Common Crawl, which I think accounted, and I could be off on this, something like 40 to 60% of the weighting in GPT-3 or 3.5. I'm off on this probably. So the total amount of data in that Common Crawl dataset 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.

• 1:05:42David Friedberg?

  So if you assume like over time, the definition of the video has 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. It has video, it has image, it has audio, it has text, it has everything. And it is growing. So if you were to take a bet or build a thesis around this point, that the data advantage is going to drive value creation,

• 1:06:27David Friedberg?

  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 this thesis, that AI value is going to accrue to the data owner.

• 1:06:47Chamath Palihapitiya?

  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, Freiburg, and all of these third-party benchmarks of these models.

• 1:07:03David Friedberg?

  All using the same data sets.

• 1:07:04Chamath Palihapitiya?

  It's all using the same data set. 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 going to 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, that's much easier to underwrite because you don't have to underwrite it being a differentiator in five years. But if you have a startup with equity value tied to a model, I think it's very...

• 1:07:42Chamath Palihapitiya?

  It's much more of a tenuous place to be in the absence of proprietary data.

• 1:07:46David Friedberg?

  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.

• 1:08:04Chamath Palihapitiya?

  Well, it is public facing though, so. It's not just true for text, it's also true for, you know, all of the image generation.

• 1:08:11David Friedberg?

  That's what I'm saying. They can train more than just an LLM on it, right? They can build all sorts of.

• 1:08:17Chamath Palihapitiya?

  Yeah, go ahead. No, no, no, I was just gonna say like 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 like 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. 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, Big Table, BigQuery, you know, TensorFlow,

• 1:09:03Chamath Palihapitiya?

  the versions that you had access to via GCP was always one or two generations behind what the Google employees got to use. Right?

• 1:09:13Chamath Palihapitiya?

  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.

• 1:09:40Jason Calacanis?

  And you know, to your point, Friedberg, 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 of privacy around that.

• 1:10:01David Friedberg?

  But maybe there's a difference there, but I honestly can't think of the quantum coming close to YouTube, not even close.

• 1:10:07Chamath Palihapitiya?

  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, 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. To click a button where all of a sudden now, all of that stuff in 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, every document, that's a huge edge.

• 1:10:49David Friedberg?

  Yeah, totally.

• 1:10:50Chamath Palihapitiya?

  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 had 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, that are like the next version of a knowledge base that we've always wanted inside of a company.

• 1:11:13Jason Calacanis?

  Right? 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, 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.

• 1:11:36Chamath Palihapitiya?

  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. Yeah, the HR department. Information gets put into the training model. Very dangerous. Or subset A of a company is working on a proprietary chip design that 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. Yeah, brave new world.

• 1:12:16Jason Calacanis?

  So there's been a lot of discussion, real estate. You shared a video with us. Why don't you kick it off for us here, Friedberg? What's going on in commercial real estate? And Sax, you've got holdings and a lot of thoughts as well. So let's kick up the commercial real estate challenges of the moment.

• 1:12:28David Friedberg?

  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 U.S. Nick, if you'll pull up this chart, the total estimated market value of commercial real estate in the U.S. across different categories is about $20 trillion, with about $3 trillion being in the office market, which is specifically what he was talking about. And he was saying that in the U.S., we're seeing people not coming back to work, and

• 1:13:12David Friedberg?

  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 apiece. The rest of these categories seem relatively unscathed in comparison, industrial, hospitality, healthcare, you know, those, those real estate sectors are probably pretty strong. Data centers, obviously, growing like crazy. Self-storage is a 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.

• 1:13:57David Friedberg?

  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 going to be able to pay the debt on retail going to 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 you know is marked on everyone's books as $3 trillion of market value, he thinks it's probably worth closer to 1.8 trillion.

• 1:14:39David Friedberg?

  So there's 1.2 trillion dollars 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 dollars 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 2/3 of their value, 2/3 of their investment. And who owns all of that? Most of that, 60 plus percent, call it 2/3 of that is likely owned by private equity funds and other institutions where the end beneficiary is actually pension funds and

• 1:15:24David Friedberg?

  retirement funds. And so if 2/3 of the value has to be written off in these books and it hasn't happened yet, what's going to 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 2/3 write down on the value in these funds, most of that being pension funds, you're not going to see governments let that happen. Yeah, to yell and bail, right? There's going to be some action at some point. And it's unlikely the office market is going to suddenly rebound overnight. If this stays the way it is, who's going to fill that hole for retirees and pensioners? Because we're not going to let that all get written down. Someone is going to step in and say, we've got to do something about this. And there's going to need to be some sort of structured solution to support retirees and pensioners.

• 1:16:09David Friedberg?

  Because 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 three trillion to 1.8 trillion. And then I tried to connect the dots and what that actually means. And ultimately, there's going to be some pain felt by retirement funds. That's going to need to be dealt with somehow. So Sax, I don't know if that sits right with you.

• 1:16:30David Sacks?

  I mean, I think the big picture is right. I think you're applying a lot of averages.

• 1:16:33David Friedberg?

  Right.

• 1:16:34David Sacks?

  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.

• 1:16:42David Friedberg?

  Right.

• 1:16:43David Sacks?

  So that'd be point number one, which makes the situation worse.

• 1:16:45David Friedberg?

  Even worse, yeah.

• 1:16:47David Sacks?

  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 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 Friedberg, I think the point is just the pain from this is not just going to be on the equity holders, but also on these banks, which can't afford to lose very much.

• 1:17:27David Friedberg?

  It's not evenly distributed. Yeah, right. Yeah.

• 1:17:29David Sacks?

  Right.

• 1:17:31David Friedberg?

  And we saw this in San Francisco where some of these buildings have 70% debt to equity ratios. And, you know, the value puts them in the hole and equity is wiped out completely. And the debt holders have to take ahead. And normally, you know, that debt is not really written off very often.

• 1:17:45David Sacks?

  Well, this is why the debt holders, the debt holders don't want to foreclose. They don't want to get these buildings back because when they do, they're going to 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.

• 1:18:00David Friedberg?

  Kick the can down the road is the best strategy for them.

• 1:18:02David Sacks?

  So it's called pretend and extend. So what they'll do is they'll work out a deal 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 principal at the end of the loan. And they'll extend out the term of the loan.

• 1:18:20Jason Calacanis?

  Which would wipe out the equity at a certain point, yeah.

• 1:18:24David Sacks?

  Well, what it does, it allows the equity holders to stay in control, own the building, right? Because, yeah, the equity holder can't pay, make their debt payments today, but they're going to postpone those debt payments till the end of the, of the loan. And again, in the meantime, just kind of hope that the market.

• 1:18:41Jason Calacanis?

  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, of the property? And it's like, I'm just working for the bank now and, you know, why am I even putting this work in?

• 1:18:53David Sacks?

  Because everyone kind of hopes that the market will recover, the value of their equity will go up, and they'll be able to make their debt payments again.

• 1:19:00Jason Calacanis?

  Yeah.

• 1:19:00David Sacks?

  So if you're the equity, if you're the equity holder, you'd rather hold on and have a chance of your equity being worth something in recovery than definitely lose the building. And if you're a regional bank, you'd rather blend and extend or pretend to extend as opposed to having to realize the loss right now.

• 1:19:18Jason Calacanis?

  Yep.

• 1:19:18David Sacks?

  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 SVB and these other banks, they had these huge held to maturity bond portfolios?

• 1:19:32Jason Calacanis?

  Yep.

• 1:19:33David Sacks?

  These are mainly 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.

• 1:19:47Jason Calacanis?

  Right. And then when they had the bank run, they had to sell.

• 1:19:50David Sacks?

  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 had to recognize that loss. And that's when everyone realized, oh, wait a second, they're not actually solving.

• 1:20:08Jason Calacanis?

  Okay, so Jamar, 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?

• 1:20:33Chamath Palihapitiya?

  Yeah, I mean, I think I think you're basically right.

• 1:20:35David Sacks?

  It's not, 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 want to 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%.

• 1:21:10Jason Calacanis?

  Yeah, but at least you can find a renter.

• 1:21:13David Sacks?

  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.

• 1:21:26Jason Calacanis?

  Yeah, that situation isn't as bad as what's happening in office space.

• 1:21:31David Sacks?

  I think it's worse in some ways. If you're fully rented and your building is underwater, because now your debt payments are much higher than you expected, then there's no business model.

• 1:21:43Jason Calacanis?

  Yeah, but are we seeing that? Are we seeing tons of multifamily go under?

• 1:21:46Chamath Palihapitiya?

  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, 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-month 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.

• 1:22:30Chamath Palihapitiya?

  On the, 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 going to hit commercial real estate. We just don't know when because there are, they're in long-term leases, they're canceling these leases over long periods of time. So the reset cycle was longer. That's just my observation as an outsider. I don't know what that means for, for prices or anything else, but it just seems that

• 1:23:12Chamath Palihapitiya?

  at least the residential market can find a bottoming sooner because you can reset prices every year, but commercial just seems like a smelting iceberg.

• 1:23:20David Friedberg?

  Direction correct to you, Sax? That assessment?

• 1:23:23David Sacks?

  Commercial has both a demand problem and a financing problem. Multifamily just has a financing problem, but it's important to understand.

• 1:23:31David Friedberg?

  We're talking about office. Cause there's retail and then there's the office and then there's other industrial.

• 1:23:35Chamath Palihapitiya?

  Did you guys see in China? China has 50 million homes ahead of schedule. 50 millions additional supply that can house 150 million people. So as acute as our issues are, the China issue might be much, much, yeah, seismic.

• 1:23:51David Sacks?

  Can we 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.

• 1:24:35David Sacks?

  The overall valuations in the market have come way down. So 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 going to have to do what's called an equity in refinancing. You're going to have to produce more equity. You're going to have to pony up more money. So instead of taking equity out, like when the deal goes well, you're going to have to put equity in. You may not have that equity if you're the developer. The other thing is that your financing costs 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. You're, again, you're not positively leveraged, you're negatively leveraged.

• 1:25:18David Sacks?

  So you're not going to want to take out that debt. And if you do take out that debt, the building's going to be underwater. It's not going to be generating net operating income, it's going to be generating losses. So that's why even categories like multifamily, where you don't have a vacancy problem, there's strong demand.

• 1:25:38Jason Calacanis?

  Yeah.

• 1:25:38David Sacks?

  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.

• 1:26:05Jason Calacanis?

  Without God, right? I mean, this would be cataclysmic if it was. If ever, and can you imagine if Silicon Valley and San Francisco had to say, here's actually the reality, anybody want to actually pay for this office all in the same year?

• 1:26:17David Sacks?

  Right.

• 1:26:18Jason Calacanis?

  That would be insane.

• 1:26:20David Sacks?

  But the crisis is growing. It's 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.

• 1:26:30Jason Calacanis?

  It's going to be bad.

• 1:26:31David Sacks?

  At a much lower rate. 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 insolvent.

• 1:26:45Jason Calacanis?

  Yeah, I mean Janet Yellen is 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.

• 1:26:56David Friedberg?

  Janet Yellen?

• 1:26:57Jason Calacanis?

  Yellen.

• 1:26:58David Friedberg?

  Our Treasury Secretary. I don't know if she's gonna be the one to do it. I think there's gonna be congressional action on this stuff.

• 1:27:05Jason Calacanis?

  Yeah, I mean, they tend to lead it, so. All right, for the Sultan of Science, David Friedberg and David Sacks and Sharmar Pahlavi Patea, the Chairman Dictator, I am the world's greatest moderator. We'll see you next time on the All In Pod. Bye bye.

• 1:27:19David Friedberg?

  Bye bye.

• 1:27:52Chamath Palihapitiya?

  They should all just get a room and just have one big, huge orgy because they're all just, it's like this like sexual tension that they just need to release somehow.