Transcribe your podcast
[00:00:00]

All right, everybody. Welcome to your favorite podcast in the world's number one podcast, The All-in podcast. It's episode 1790. Oh, wait, that's just how it feels. Welcome to episode 179. With me today, of course, is your sultan of science. I don't know if that's a movie background or it's just his favorite vegetables. What's going on there? What's the crop?

[00:00:22]

That's AI-generated.

[00:00:23]

It's AI-generated crop.

[00:00:25]

Okay, great. I'm trying AI backgrounds. I'm going to try it out for a while with different crops.

[00:00:28]

Your fans are going to be crushed that you're not doing deep movie polls with us, of course. Man, about town, DC, new products being launched. David Sacks, The Rainman. Yeah, how are you doing, buddy?

[00:00:41]

Good. Good. Yeah, good week. Lots going on.

[00:00:43]

Yeah, Definitely good week. Shabbat Polyhapateya, chairman dictator. He puts the chairman dictator.

[00:00:52]

I would like to take this opportunity to wish my child a happy birthday. I absolutely love you.

[00:01:04]

Well, now the rest of us look like shit.

[00:01:06]

Yeah, great.

[00:01:07]

I've never done that before.

[00:01:09]

Sacks, in your desk is a piece of paper with your children's names and their birthdays. You want to pull it out and see.

[00:01:14]

I got I see birthdays a year, and I've never done one. Let your winners ride.

[00:01:21]

Rainman David Sacks.

[00:01:25]

We open source it to the fans, and they've just gone crazy with it.

[00:01:30]

Love you guys.

[00:01:31]

No, no, no.

[00:01:35]

But I'm saying it rarely lands on the same day. Today is the day. Today is the day.

[00:01:40]

Today is the day. Okay, good.

[00:01:40]

Today is the day.

[00:01:42]

Congratulations, child.

[00:01:44]

Oh, congratulations.

[00:01:45]

How old is Shemoth?

[00:01:46]

No gender name or any other specifications, folks. We can't tip anybody off. No pronouns. No pronouns.

[00:01:52]

Yes, absolutely. How are they, Sam, experiencing their birthday?

[00:01:57]

This child has experienced a wonderful life, and this child is an incredible person for whom I have tremendous admiration and love and compassion and hope for the future.

[00:02:08]

All right. Did you order them some chicken fingers?

[00:02:10]

I cannot comment on who this person is. Chicken fingers.

[00:02:14]

Are you talking, of course, about Phil Helmut?

[00:02:17]

Can we please talk about last weekend's festivities in Vegas? What a disaster he is. Oh, my God. Guys, just so you guys know.

[00:02:28]

We missed you last weekend. We missed you last week.

[00:02:30]

That was so much fun to make.

[00:02:31]

Tomoth, we missed you on Saturday night. Saturday night was really fun.

[00:02:33]

I had such a lovely time coming home, to be totally honest with you.

[00:02:37]

We had a cabana set up on Saturday, played Black Jack by the Pool.

[00:02:41]

I missed you guys, too. I had a phone moment. I saw the videos.

[00:02:43]

It was so fun.

[00:02:44]

Well, you don't have to have too much FOMO because Phil sent the entire group chat to pokernews. Com.

[00:02:50]

They did an article on.

[00:02:52]

Run it twice. Theflop. Org, poker-updated. Oh, my God. Yeah. It was like five stories.

[00:02:59]

He kept tweeting He leaked every single person who's there and the jets and the jet numbers. He's like, Look, here's me and Elon. Elon came by for my dinner. No, it was worse than that.

[00:03:09]

No, it was worse than that. He said, I got to hang out with our guy Elon for 10 minutes and 14 seconds.

[00:03:15]

Wait, what?

[00:03:16]

He intercepted him at the valet.

[00:03:21]

Wait, what? How many minutes? Ten minutes and 14 seconds. He had the exact time down to the second.

[00:03:29]

Oh, my God. Well, I want to wish Phil Helmson happy birthday because I did miss his 60th party.

[00:03:34]

Yeah, it's coming up, actually. His birthday is not for another two months.

[00:03:36]

The good news is it wasn't actually his birthday. It was Bill Gurley's, so he just hijacked Bill Gurley's birthday.

[00:03:41]

I also got to enjoy for my first time ever the experience of Baccarat, which I've decided is the most degen game on Earth. It's literally the most... You just flip a coin. More than craps.

[00:03:52]

It's flipping coins.

[00:03:53]

Well, craps is really... There's a style. You make betting decisions. All you do in Baccarat is you say bank or player, and then you freak yourself out about how you flip the cards. The smartest people I know on Earth are all sitting around this table at 2:00, 3:00 in the morning saying, Turn this corner this way. No, no, no, no, no, The Baccarat sweat is the most incredible performative act in the casino. It's the weirdest thing.

[00:04:22]

Yeah, you're right. Everyone's got their own little technique about how they bend the card. It's all destroyed by the end of the deck. They get thrown up.

[00:04:28]

I go lengthwise. I go like this and I try to see.

[00:04:32]

Oh, like you're crawling your mustache like an evil villain? Yeah, like this. You got to go like this.

[00:04:35]

It's the evil villain.

[00:04:35]

Then you call it, Oh, my God, no spotter. If you see a no spotter. We're two across.

[00:04:40]

Then you get to decide whether the bank turns over their cards and when they turn them over. Then you lose a small house and then you're like, Oh, let's try to get it. Yeah, you're convincing yourself that you have all this control and ways to change the outcome. You're literally flipping a card. It's high card. It's basically high card. That's all it is. It's high card.

[00:04:57]

It's even worse than that. You're basically sitting down at the casino's table and then they tell you whether you've won or lost. In order to convince yourself that that's not what's going on, you have to play with the card.

[00:05:08]

But really, they just tell you you either win or lose.

[00:05:12]

I'm watching the smartest guys we know staring at the window at the little machine that tells you whether a bank or player won, and they're studying it, doing an analysis. It's been four reds. It's got to go black. Helmuth is like, I'm calling it now bank, bank, player, player, player. And all the guys are like, Let's do it. Then everyone gets huge.

[00:05:31]

Heads, heads, tails. Helmuth asked us to play in the high-stakes poker game on PokerGo. It was me, Helmut, Stanley, Sammie, House, and then Jen, Tilly, and nick Airball, and Robel. Most of the guys from the house came plus Jen, Tilly, and nick Airball.

[00:05:49]

Jennifer Tilly is amazing.

[00:05:50]

What a great human and actress. Listen to this hand. Literally the second hand of the actual poker game, Jen Tilly is in the big blind. No, sorry. She's under the gun. She raises. Housenbull, three bets. It comes all the way around to me on the button. I look and I have pocket Kings. I ship the whole cheeseburger, comes back to Tilly, she ships, house ships. Listen to these hands. Jen Tilly has aces. Jeff Housenbold has Kings. I have Kings.

[00:06:28]

Oh, my God.

[00:06:29]

I've never I've seen a cooler hand like this in my life, in the second hand of the game.

[00:06:36]

Anyways, don't worry, guys.

[00:06:38]

I came back and I won.

[00:06:38]

Jen Tilly, she tripled up.

[00:06:42]

She triples up and then into lockdown mode. The first time I ever played with her, I showed up for this game.

[00:06:47]

Then I stacked her. Anyways, I don't want to reveal the game, but it was wonderful, this one.

[00:06:52]

I show up at a mutual friend of ours' game, and there's a beautiful Porsche or something in the driveway. It was a really notable car. I And I noticed on the license plate, it says Degen, but it's spelled with a J. And I'm like, Oh, Degenerate. What a great license plate. I wonder who's that is. I go, It's Jennifer Tilly. The license plate is Degen.

[00:07:08]

She is so cool. She's very charming. She's very cool. She's very charming. Great actress.

[00:07:13]

What was that movie she was in?

[00:07:15]

Bound. Bound. That's what it was. Yeah. You don't have to ask me twice. Yeah, exactly. That is a tour de force.

[00:07:21]

What a great gangster film.

[00:07:23]

Yeah. With Gina Gurchin. Gina Gurchin. That's the word. Oh, Gina Gurchin. That film, oh my God. That film, oh, my Well, let's not get canceled here.

[00:07:31]

It is quite a film. All right. Speaking of action, big week. The AI industrial complex is dominating our docket here. Apologies to Biden, Ukraine, and Nikki Hale, but we got to go AI right now. Open AI, launch chat, GPT 4.0. 4.0. Monday, three days after Samwise came on All In as a programming note, and we'll go to Friedberg about this, we We made a bit of a strategic or tactical era in not postponing his appearance. In fairness, Friedberg, Samwise, did tell us. Originally, he was coming on to talk about those things, but then it got pushed back. Anything you want to add to that as a programming note? Because people are wondering.

[00:08:16]

What happened, I've been talking with Sam for a while- A year. About coming on the show, and every time I see him, we're like, Hey, you should come on the show. He's like, I want to come on the show. Okay, let's find a date. We never got a date that worked. I saw him in March, and he said, Hey, I want to come on the show. I said, Okay, well, come on. Let me know when it works. And a couple of weeks later, he's like, What about this date in May? I'm like, Yeah, that's fine. We can make that work. He's like, Well, I've got a big announcement we're going to be doing. I was like, Perfect. Come on the show. That sounds great. And then the night before, he asked me, he told me, he texted me, he's like, Hey, we're actually not going to have this announcement happen tomorrow. It's going to be delayed. He didn't tell me how long. I'm like, Well, is it GPT-5? He's like, No, it's not GPT-5. And I was like, Okay, well, come on the show anyway. Because he didn't tell me when he's doing the announcement or when it's being pushed to.

[00:09:04]

So it didn't seem like that big a deal. And I thought we were just going to be able to have a good chat anyway. So it's really unfortunate, I think, the fact that the announcement happened two days after and he had to stay quiet about it during our interview. But that's the story. I think in the future, if someone says they've got a big announcement to do, we should probably push them if they have to delay or something like that. Lesson learned. Don't beat yourself on that. But I don't think we're going to be doing a lot of these interviews anyway. I think people clearly don't love them, and it's better for us to just hang out and talk.

[00:09:30]

I think if we had just gotten Sam on the day after the launch of GPT-4 Omni, as opposed to three days before, he could have talked much more freely about it, and it would have been interesting. It would have been great.

[00:09:44]

It was supposed to happen same day. It's unfortunate this all worked out this way.

[00:09:47]

The other little trick is to say you can tell us under embargo, but my understanding is they were still doing the videos over the weekend. I think those videos and stuff, they were still figuring them out. So, yeah, lesson learned. In terms of the interviews on the show, just to recap for people, we've done a dozen. Half of them have been presidential candidates. Sometimes they break out, sometimes they don't. We follow our interest and our passion here on the pod. It's got to be interesting for us, too. So if we think this person is going to be interesting, we do it. We understand you miss a news subject, but yeah, it is what it is.

[00:10:21]

And to your point, a lot of the people that come on, and increasingly, a lot of people ask to come on because they know we're not journalists. And so for all of those folks that expect us to be journalists, that's not what we are. We're for entrepreneurs, we're for business people, we're for friends, we're for technologists, we're for curious people, we're for poker players. But we're not for journalists. We're going to ask whatever we feel like asking. Sometimes those things will touch a cord because it's what you wanted to have asked. Sometimes we won't go to a place, whether we didn't have time to or whether we forgot or whether we chose not to. I think it's important to have that disclaimer. We have day jobs, and this is what we do to coalesce a bunch of information in the way that we're thinking about the world. We are not journalists, so please don't have that expectation.

[00:11:13]

I think what that means is that if the guest doesn't want to talk about something, we're not going to start peppering him with got you questions and things like that. I appeared at a conference a couple of days ago to promote Glue, which we'll get to. And the first half of the conversation was a normal conversation about what we were launching. And then the second half was basically the reporter peppering me with fastball questions, which is fine. I knew what I was signing up for. It's a totally different style. It's a totally different style than coming on the pod and just having a normal conversation. But it's not really our job to make somebody open up if they don't want to talk.

[00:11:48]

What was the spice of this question, Sacks? What was the fastball? Anything come close to your head?

[00:11:53]

No, it's not worth really getting into. You can watch it if on- Yeah, I was just curious. Look, I like sometimes when reporters pitch me fastballs because you can strike out or you can hit it out of the park when they do that.

[00:12:04]

That's an important part here. I think as a former editor-in-chief journalist myself, I sometimes like to ask, I would say, a challenging question in a respectful way. I did that, for example, vague, just clarifying his thoughts on trans and gay rights. Wasn't disrespectful? Was thoughtful? Would you consider it spicy or hardcore? I don't think it was hardcore. He likes to talk about it.

[00:12:28]

No, but that's because you asked it from a position of curiosity. You weren't trying to catch the guy.

[00:12:32]

No. You see the difference? I'm actually interested in his opinion.

[00:12:35]

This is my point. That's why it comes out differently, and that's why I think people enjoy these conversations. Sometimes we don't get to the other answer because I'm not interested in trying to got you somebody that's working hard.

[00:12:46]

I always have the same conditions when I do interviews, which is I don't clear questions and I don't let people edit it. But everybody's got a different view on how to do interviews and fiva la difference. If you like it, you like it. If you like Lex Friedman's version or Tim Ferrace's version, or you prefer Fox or CNN, go watch those interviews there. You can have a whole range of different interviews and interview styles available to you in the media landscape. We are but one. Sam Weiss mentioned on the pod last week that the next big model might not be called GPT-5. So on Monday, they launched GPT-4. O. The O stands for Omni. It's everything you love about tech. It's faster, it's cheaper, it's better. But from my perspective, the real show was the massive amount of progress they made on the UI/UX. The O stands for Omni, as in omnivore. It takes in audio, text, images, even your desktop, and video from your camera to inform what it's doing. We can consider it like 360 Degrees AI. Producer nick will show a couple of videos while I describe them here before we go to the besties for the reaction to the announcement.

[00:13:51]

First, they made great progress in solving the CB problem we mentioned last week. That's where when you use Siri or any of these tools, you say, Hey, ChatGPT, what's two plus two? Over, and you have to wait. And then if you talk over each other, it breaks. They now have that working much smoother. They did an example of counting where they said, speed up, slow down. They did a translator that worked really well.

[00:14:13]

I would like you to function as a translator. I have a friend here who only speaks Italian, and I only speak English. Every time you hear English, I want you to translate it to Italian. If you hear Italian, I want you to translate it back to English. Is that good?

[00:14:26]

Perfecto.

[00:14:30]

Mike, she wonders if whales could talk, what would they tell us?

[00:14:41]

They might ask, How do we solve linear equations?. Certainly, yes.

[00:14:57]

Great. It looks like it works.

[00:15:00]

I think Duingo stock took a hit during that. Most impressive, to me at least, and also I had Sandeep Madra on my other podcast, and we talked about it, was their desktop and iOS app. What this app does is fascinating. It watches your desktop on your Macintosh or on your iPad or iPhone. It does things like adaptive learning. Here's a clip of Sal Khan from Khan Academy. His son basically using a drawing app to do some arithmetic or geometry. It does adaptive learning and basically makes a personal coach because the app is watching his son try to solve a problem.

[00:15:39]

I'm here with my son, and I love you to tutor him on this math problem, but don't give him the answer.

[00:15:46]

You can ask questions and nudge him in the right direction, but I really want to make sure he understands it himself.

[00:15:52]

He's here in the room, so you can talk to him directly.

[00:15:54]

Can you first identify which sides of the triangle are the opposite, adjacent, and hypotenuse relative to angle Alpha? All right. I'm pretty sure this is the angle Alpha right here, right? Fict. That's correct. Now, looking at the triangle, which side do you think is the hypotenuse? Remember the hypotenuse? I'm not totally sure. I think it might be this one, but I really am not sure. This side AC.

[00:16:29]

You're close. Actually, side AC is called the adjacent side to the angle Alpha.

[00:16:35]

The hypotenuse is the longest side of a right triangle and is directly opposite the right angle.

[00:16:42]

Can you find which one is the hypotenuse?

[00:16:44]

Oh, okay. I see. So I think the hypotenuse is this really long side from A to B. Would that be correct?

[00:16:53]

Exactly. Well done.

[00:16:55]

It can also participate in Zoom calls, explain charts, all that great stuff. And so it's going to be your guide on the side. It's going to be a present personality while you're using your apps. It's really impressive, I have to say. I guess let's start, Friedberg, with your takeaways on all of these innovations that we saw.

[00:17:14]

I think it's become quite apparent that there's an evolution underway in model architecture. I think you may remember we talked about this briefly with Sam last week, but we're moving away from these very big bulky models that are released every couple of months or quarters and cost a lot of money to rebuild every time they get rereleased towards a system of models. This multi-modal system, basically, basically leverages several models at once that work together or that are linked together to respond to the inputs and to provide some generative output, and that those individual models themselves can be continuously tuned and or continuously updated. Rather than have, Hey, there's this big new release that just happened. This new model just got trained, cost $10 million to train it. It's been pushed. These models can be upgraded with tuning, with upgrade features, and then linked together with other new smaller models that are perhaps specialized for specific tasks like doing mathematics or rendering an image or rendering a movie. I think what we're going to see is soon more of an obfuscation of the individual models and more of this general service type approach where the updates are happening in a more continuous fashion.

[00:18:36]

I think this is the first step of OpenAI taking that architectural approach with GPT 4.0. What's behind the curtains, we don't know. We don't know how many models are there. We don't know how frequently they're being changed, whether they're being changed through actually upgrading the parameters or whether they're being finetuned. This seems to be pretty obvious. If you look at this link, one of the criticisms that initially came out when they at least GPT 4.0, was that there was some performance degradation. Stanford actually runs this massive multitask language understanding assessment. They publish it, I think daily or pretty frequently, on how all the models perform. You can see the scorecard here that GPT 4.0 actually outperforms GPT 4. This goes counter to some of the narrative that in order to get some of the performance improvements and speed improvements they got in 4.0, that they actually made the model worse. It seems actually the opposite is true, that the model has gotten slightly better. It still underperforms cloud 3, Opus, which you can see here, ranks top of these charts. But there's lots of different charts. All the companies published on charts, they all claim that they're better than everyone else.

[00:19:42]

But I like Stanford because it's independent.

[00:19:44]

Chamab, any thoughts after seeing it in combination with our interview? Do you think ChatGPT is running away with the consumer experience, or do you think this is neck and neck with some of the other players?

[00:19:57]

Not to tell tales out of school, but somebody that we all know in our group chat posted something about the fact that the consumer growth had stalled. I don't know how they knew that, that maybe they got some data or maybe they're an investor. You guys know what I'm talking about. They said that they're trying to reinvigorate growth into the consumer app at OpenAI. Any insights as to why it might be plateauing in your perspective? I wrote this in my annual letter, but there are these phases of growth When you look at social networks as a perfect example, Frenster was magical when it was first created. Then you had MySpace that just ran circles around them because Frenster didn't really invest the money and the quality that it took to create a moat. Then my space really wasn't able to compete. Facebook, we were the eighth or ninth when we showed up on the scene and we ran circles around everybody. I think what it means is that there are these phases of product development, which exist in many markets. This market, I think, is going through the same thing. Right now, we're in the first what I would call primordial ooze phase, which is everybody's running around like a chicken with their heads cut off.

[00:21:14]

There's all these core basic capabilities that are still so magical when you see them. But we all know that 5 and 10 years from now, these things will be table stakes, right? And what Friedberg just showed is a table of many companies and many trillions of market cap all effectively running to the same destination. I think where we are is probably within two years of where the basic building blocks are standardized. Then I think the real businesses get built. I will maintain my perspective here, which is the Facebook of AI has yet to be created.

[00:21:50]

Okay. Here it is ChatGPT web visits, as you can see, have plateaued. This data is similar web. I would agree with you, Jamath. It seems like the use cases and the lucky-loos who were just trying this software because they heard about it, they've gone away, and then we have to find actual use cases. Sacks, I'm wondering.

[00:22:11]

But our friend Jason, just to complete that, said something about the premium conversion It's paid version, right? That's what he said. I don't know how he knew that. Yes, paid.

[00:22:17]

To be clear, paid versus free.

[00:22:20]

Then what Sam said on the podcast last week was it seems like whenever they come out with something new, the old stuff becomes free. In my talk with Sunny this week, he You mentioned that these new models are so much more efficient that you actually can throw the old model in the garbage because it's so inefficient. These are now becoming about 90% cheaper every year, which means every two years, these things are going to be 99% cheaper and better. It might be that OpenAI, Sacks, on a strategic level, is going to make all this free or close to free and maybe just charged for a multi-player version. That seems to be where it's heading. You don't have to log in to use 3.5. You don't have to log in to use Google. No, you do have to log in still on Google services. But I think these are going to just be free. So on a product basis, what are your thoughts? And then maybe you could talk about free to pay. Do you think everybody in the world is going to pay 20, 30, 40 bucks, 500 a year, 200 a year to have one of these, or are they just going to all be free?

[00:23:21]

Well, I think you're assuming there that the long term business model of OpenAI is in B2C subscriptions. And I think that's probably the least attractive business model they have available to them. It's the first one and the most obvious one because they put out ChatGPT, and then it's pretty easy just to roll out a premium version. But in my experience, B2C subscriptions, it's just not a very attractive business model because consumer Customers just aren't willing to pay a lot, and they have high churn rates, and there's no possibility of expansion, really. So I suspect they're going to move in more of a B2B direction over time because that's where the real money is. And probably the way they do that is by monitoring monetizing all the apps that are built on top of it. I think that in that sense, GPT 4.0 is a really important innovation. By the way, the O stands for Omni, which I think it stands for Omnichannel. I think you may have said omnivore.

[00:24:16]

Well, I'm making a joke. It's omnichannel, which means all the different media types are currently coming in. That's the difference. It's not like you just give it an image or give it a video. It's absorbing all those at the same time in parallel, I believe.

[00:24:29]

That's There's three big innovations with this model. One is omnichannel, which means text, audio, video, and images. Second, it's more conversational. It understands the tone of people talking. It understands sentiment in a way it didn't before. And then the third thing, which is really important, is that it's just much faster and more performant than the previous version, GPT-4 turbo. In the speed test, they say it's twice as fast. We've played with it at Glue. We can talk about that in a minute, and it feels 10 times It is much faster. But it's the combination of all three of these things that really makes some magical experiences possible. Because when you increase the speed of processing, you can now actually have conversations with them in a much more natural way. Before, the models were just too slow, so there'd be a long delay after every prompt. So now, like you showed, it can do things like you point the camera at a blackboard or something with math equations on it, and it can walk you through how to solve that problem. Or two people can be talking and it does real-time translation. There's that old saying that every Star Trek technology eventually becomes true.

[00:25:40]

They've just basically invented the whole natural language, real-time, universal translator. Anyway, so those are some interesting use cases. But I just think they're going to be able to unleash a whole lot of new applications. If they're metering the usage of the models and providing the best dev tools, I think there is a business there.

[00:26:00]

This thing is moving so fast. They're in Leonardo DiCaprio mode. Every two years, they throw the old model away. Okay, let's keep...

[00:26:08]

Thank you, Sacks.

[00:26:10]

Is this thing on? Did you write that ahead of time? I was in the moment.

[00:26:16]

That was good. Just one point on that is there are a whole bunch of startups out there that we're creating virtual customer support agents. They've been spending the last couple of years working on trying to make those agents more conversational, quicker, more responsive. I think their product roadmaps just became obsolete. Now, that's not to say there isn't more work for them to do in workflow in terms of integrating the AI with customer support tools and doing that last mile of customizing the model for the vertical specific problems of customer support. But my guess is that hundreds of millions of dollars of R&D just went out the window. Probably this is the best time to be creating a customer support agent company. If you're doing it two years ago, five years ago, your work has just been been obsolete. That is the thing of this pace.

[00:27:11]

You used to have to throw away client server stuff or whatever. You had a web-based thing, you get an app out, you throw away some of the old code. But this is like every 18 months, your work has been replaced.

[00:27:22]

If you're an app developer, the key thing to understand is where does model innovation end and your innovation begin? Because if you get that wrong, you'll end up doing a bunch of stuff that the model will just obsolete in a few months.

[00:27:36]

I think you're totally right. I think that's such a really important observation. That's why I think the incentive for these folks is going to be to push this stuff into the open source. Because if you solve a problem that's operationally necessary for your business, but it isn't the core part of your business, what incentive do you have to really keep investing in this for the next 5 and 10 years to improve it? You're much better off, like Klarna, for example. We We talked about the amazing improvement and savings that Klarna had by improving customer support. Release it in the open source, guys. Let the rest of the community take it over so that it's available to everybody else. Otherwise, you're going to be stuck supporting it. Then if and when you ever wanted to switch out a model, GPT 4.0, 4 to 4.0 to Claude to LLaMA, it's going to be near impossible and it's going to be costly. I also think, Sacks, the incentive to just push towards open Of course, in this market, if you will, is so much more meaningful than any other market.

[00:28:36]

Listen, I think you were there at Facebook when they did the Open Compute project and they just were like, Oh my God, talk about torching an entire market. Explain what it is.

[00:28:47]

There was this moment where when you were trying to build data centers, you'd have these one-u rack mounted machines that you used. What Facebook observed was there was only a handful of companies that provided it, and so it was unnecessarily expensive. Facebook just designed their own and then released the specs online. Just said, Here it is. They went to these Taiwanese manufacturers and other folks and said, Please make these for your cost plus a few bucks. It was revolutionary in that market because it allowed this open platform to embrace this very critical element that everybody needs. I think there's going to be a lot of these examples inside of AI because is the costs are so extreme, so much more than just building a data center for a traditional web app, that the incentives to do it are just so meaningful.

[00:29:39]

Yeah, and I just showed it on the screen. Sacks, you've actually been dancing along this line. Last night, I was using your new slack killer or co-exister. I'm not sure. It feels like a slack killer to me because I'm moving my company to it on. Over the weekend, we're moving to Glue. You and I were doing some very... I may need to wet my peak on this one.

[00:29:58]

We want you to wet your peak.

[00:29:59]

I It feels like a hundred bagger to me. I'm in.

[00:30:02]

I need to slide in. It is slack killer. That's the way we're thinking about it.

[00:30:05]

It feels killer-esque because... Jake L, can you do that again in Christopher Walkin voice, please?

[00:30:10]

I need to wet my peak. It feels like a 100X. Sliding A hundred. Wow. Sacks, tell me about product decisions. Where does the AI end? And your product begin.

[00:30:25]

Yeah, well, it's a good point. I think where the AI ends, we want to use the most powerful AI models possible, and we wanted to focus on enterprise chat. You could think of us as, for sure, a slack killer or slack competitor. It says that slack wasn't built for the AI era. Glue is AI native. What does that mean? No channels. I showed this to Jamal. The first thing he said is you had me in no channels. People are so sick of channels. You have to keep up with all these hundreds and hundreds of channels. And the real problem with channels is there's one thread in a channel that you want to see. In order to see it, you have to join the whole channel, and now you're getting all this noise. People just want the threads. So if you look at what's the chat model inside of ChatGPT, it's just threads, right? You create a topic-based thread in ChatGPT. The AI comes up with a name for it, puts it in the sidebar, and then if you want to talk about something else, you create a new chat. That's exactly the way that Glue works.

[00:31:19]

It's just multi-player. You just put the groups and individuals you want on the thread. Let me just show you real quick. Here's my Glue here. And you can see that in the sidebar, I've got all the threads that that I've been involved in. And like I said, you can address them to multiple people or groups. And then you've got the chat here. Now, we've also fully integrated AI. Nick, who's our producer, just in this thread, said, at Glue AI, what countries does Sacks talk about most in episodes? Episodes is a group we created to be the repository of all of the transcripts of our episodes. So, Glue did a search and it said, David Sacks frequently discusses Ukraine the most. What? Yeah. Really? Then nick said, be more specific about Sacks' stance on Ukraine-Russia war. Oh, boy. It's going to overload the server. Well, it said here, David Sacks has articulated a nuanced and critical perspective on the Ukraine-Russia war across various episodes of the All-In pod. Here are some key points encapsulating his stance. It nailed it. It's talked about prevention through diplomacy, opposition to NATO expansion, humanitarian concerns, skepticism of military intervention, peace deal proposal.

[00:32:27]

I'll copy and paste this onto Twitter X later today. But the point is it nailed it across all these different episodes. And then this is a feature of Glue. It provided sources. It cites where it got all the information from. Imagine we're doing this for the all-in pod, but you could imagine that instead of it being transcripts of a podcast, it could be your work documents. You now have in your main chat the ability just to ask, Hey, at Glue AI, remind me where we left that project, or tell who the expert is on this subject matter, or who's contributed the most to this project. I've actually figured out using Glue AI who's contributed the most deal flow at Kraft. It's pretty amazing. Now, let me show you some of the-What's the answer?

[00:33:12]

I'm not going to say here.

[00:33:14]

I think it's Brian.

[00:33:15]

Brian is my guy. Brian is my guy.

[00:33:19]

I want to hire Brian. If I got to get Sacks, I go Daniel and Brian.

[00:33:22]

Boom, boom, boom.

[00:33:23]

That's how I get Sacks on the line.

[00:33:25]

Okay, you take Daniel. I'll hire Brian.

[00:33:27]

I will reconstitute Kraft.

[00:33:29]

We'll call it graft.

[00:33:33]

All right, look, let me show you a couple.

[00:33:35]

Hold on a second. Sacks, I just looked at the ChatGPT for Omni server, and when you did that query, it actually rolled its eyes. Keep going.

[00:33:45]

Okay. So we talked about how ChatGPT 4.0 understands sentiment in conversations, and I think this is a really good example. Evan, who's my co founder at Glue, was testing this for us, and he asked, What is each besties personality based on conversations and episodes. First of all, it figured out who the besties are. We didn't program that. It just figured it out on its own, which is pretty impressive. And here's what it said about each bestie's personality. So it says, Jason Calcandis, roll. The moderator and entertainer. Personality traits, charismatic, humorous, lively, and the glue of the group. Say more. Often pray for his ability to make the podcast entertaining and keep the conversation flowing. Jason's energy and ability to bring humor into discussions are key elements that define his role in the podcast. Comments he has acknowledged for his role in bringing the group together. Chamath Polyhapateya, the visionary and hustler, personality traits, insightful, driven, persistent. Chamath's relentless drive and ability to hustle or admire by his peers, making him a core part of the podcast in intellectual discussions. I'll skip me, but does Friedberg, It's a pragmatic scientist and realist, pragmatic, methodical, and a bit reserved.

[00:34:49]

Oh. Friedberg is often the voice of reason, bringing a scientific and realistic perspective to the discussion. He focuses on analysis, logical reasoning. Then it cites where it got this from. It says Overall, the dynamic between the four besties creates a well-rounded and engaging podcast with each member bringing their unique strengths and personality traits to the table. I think that's pretty incredible. How woke is this?

[00:35:09]

Have you put any rails on or is this just pure ChatGPT 4.0 combined with the data?

[00:35:18]

What we're doing here is we're wrapping ChatGPT 4.0 with blue features that we've implemented to get the most out of the conversation. There's things we have to do to scope the prompt. Then we're using a retrieval augmented generation service called RAGI, which does RAGI as a service that basically slurps in our transcripts and makes them accessible to the AI. That's basically the stack that we're using. But as the models get better and better, glue just gets better and better. Can I just make a comment on this?

[00:35:50]

It's just so clean. Jcal was the key for me in abandoning Slack. He told me two or three years ago, he called me and he said, I have... You can tell me the exact channels. I eliminated some channels that were-Random. There was two or three channels that your band, that your Slack instance wasn't allowed to have. I was like, This is genius. I went in and I was like, all of our companies should just eliminate these channels. We could only get 20% or 30% compliance. But it really started to turn me off slack because I would get caught in these threads that were just so totally useless. I thought, why aren't people still working. And this is really great because you cannot blather on about nonsense in glue, which I find really useful.

[00:36:36]

Well, this is what happens when slack-We use it at 80, 90, just so you know.

[00:36:40]

We got into the early adopter beta.

[00:36:42]

When you get into slack too much, people start to think Slack is the job, and replying to Slacks and having conversations is the job when there's actually a job to be done.

[00:36:50]

There's a job to be done.

[00:36:51]

Yeah. And so it's important. And what I liked about this implementation fax was it's like the ability to make a feed or a data source inside of your communication platform. So the fact that you imported all of the episodes and the transcripts is great. But what I want is our HubSpot or our CEL CRM. I want our ZenDesk. I want our LinkedIn jobs and our LinkedIn job applications. I want our Notion. I want our Coda to each have the ability. And when I was using it last night, what you do is you use the at symbol to evoke and to summon in a way. It's like summing Beetlejuice. You summon your AI, but then you tell it what data set you want to go after. You say at AI, let's talk about, I don't know, how do you manage your deal flow at Kraft? Do you use software, like CRM software, to manage deals?

[00:37:45]

Brian, Daniel. We just do it all in Glue. But we do it all in glue, so it's already right there. But you're right. The first thing that Glue AI has access to is all of your chat history, which is amazing because you get... Then we can look at all your attachments, and we've got I think six integrations at launch. There'll be more. So yeah, all of your enterprise data will be there. In the short term, you're right, you have to sum in the repository by app mentioning because the AI needs a little bit of help of where to look. But in the future, it's going to figure it out on its own. So it's going to become more and more seamless.

[00:38:15]

It'll insert itself. So we have a discussion about sales, and then you might have a sales bot that says, Hey, by the way, nobody's called this client in three months.

[00:38:23]

Well, that's where I want to go with it, is I call that promptless, which is I want the AI just to chime in when it determines It determines that it has relevant information and can help the team, even if it hasn't been summoned yet. But we need some model improvement for that, frankly. I mean, we'll be able to get there by GPT-5, but that's totally where this is headed. I'll show you just one more fun example. If I could, let me just show to do this. I asked it to write a letter to Lena Khan to be a guest at the All-In summit, and I told it, mention positive things we've said about Lena Khan in episodes of the All-In pod. And so it wrote this letter, Dear Chair Khan, we hope this message finds you well. On behalf of the host of the All-In pod, we are excited to send an invitation for you to speak at the upcoming All-In summit. And then it says, In our conversations, we have frequently highlighted your impressive credentials and the impactful work you've undertaken. For example, in episode 36, we acknowledge your trailblazing role. And so the letter was able to quote episodes of the All-In pod just without anyone having to go do that research and figure out what would be the best, because I We told it, only say positive things, don't say anything negative.

[00:39:33]

Then it said, warm regards, and it said who the four besties were. Again, we never told it who the besties are. We just said, write us a letter. It's pretty incredible. Now, this is an example of the all in pod. Think about any work context where the AI has access to your previous work documents. It's pretty amazing what it can do.

[00:39:53]

Well, I mean, it is in the name. This is glue, put you together, and Slack is where you slack up. It makes total sense. The brands give you a little bit of a tip. We should have seen it coming with slack.

[00:40:03]

Totally.

[00:40:06]

We have a breaking news story. It's a breaking news story. It's an all-in exclusive today on the program. I got breaking news coming in. Friedberg, your life's work. Sacks did his product review. Now it's your turn, Friedberg. We got breaking news coming in.

[00:40:23]

I did promise you that when O'Hallo decides to come out of stealth and explains what we've done what we're doing. I would do it here on the All In pod first before the- And All In exclusive. All In exclusive. Basically, by the time this pod airs, we're going to be announcing what O'Hallo has been developing for the past five years and has had an incredible breakthrough in, which is basically a new technology in agriculture, and we call it boosted breeding. I'm going to take a couple of minutes just to talk through what we discovered or invented at O'Hallo and why it's important and the significant implications for it. But basically, five years ago, we had this theory that we could change how plants reproduce. In doing so, We would be able to allow plants to pass 100% of their genes to their offspring rather than just half their genes to their offspring. If we could do that, then all the genes from the mother and all the genes from the father would combine the offspring rather than just half the genes from the mother and half the genes from the father. This would radically transform crop yield and improve the health and the size of the plants, which could have a huge impact on agriculture because yield The size of the plants, ultimately drives productivity per acre, revenue for farmers, cost of food, calorie production, sustainability, etc.

[00:41:52]

This image just shows generally how reproduction works. You've got two parents. You get a random selection of half of the DNA from the mother and a random selection of half the DNA from the father. You never know which half you're going to get from the mother or which half you're going to get from the father. That's why when people have kids, every kid looks different. Then those two halves come together and they form the offspring. Every time a new child is born, every time a plant has offspring, you end up with different genetics. This is the problem with plant breeding. Let's say that you have a bunch of genes in one plant that are disease resistant, a bunch of genes in the other plant that are drought resistant. Resistant, and you want to try and get them together. Today, the way we do that in agriculture is we spend decades trying to do plant breeding, where we try and write all these different crosses, find the ones that have the good genes, find the other ones that have the good genes, and try and keep combining them. It can take forever, and it may never happen that you can get all the good genes together in one plant to make it both disease-resistant and drought-resistant.

[00:42:52]

What we did is we came up with this theory that we could actually change the genetics of the parent plants. We would apply some proteins to the plants, and those proteins would switch off the reproductive circuits that caused the plants to split its genes. As a result, the parent plants give 100% of their DNA to their offspring. The offspring have double the DNA of either parent. You get all the genes from the mother, all the genes from the father. Finally, after years of toiling away and trying to get this thing to work and all these experiments and all these approaches, we finally got it to work. We started collecting data on it, and the data is ridiculous. The yield on some of these plants goes up by 50 to 100% or more. Just to give you a sense, in the corn seed industry, breeders that are breeding corn are spending $3 billion a year on breeding, and they're getting maybe one and a half % yield gain per year. With our system, we are seeing 50 to 100% jump in the size of these plants. It's pretty incredible. Here's an example. This is a little weed that you do experiments with in agriculture called a rabidopsin.

[00:44:00]

It's really easy to work with. You can see that what we have on the top are those two parents, A and B. Then we applied our boosted technology to them and combined them, and we ended up with that offspring called boosted A, B. You can see that that plant on the right is much bigger, it's got bigger leaves, it's healthier looking, et cetera.

[00:44:16]

Friedberg, can I ask you a question? Does that mean that the boosted one has twice the number of chromosomes as A and B?

[00:44:21]

Exactly right.

[00:44:22]

Is that a new species then?

[00:44:25]

Yeah.

[00:44:26]

How does it survive with twice the number of chromosomes?

[00:44:28]

Yeah, it's called It's polyploidy. We actually see this happen from time to time in nature. For example, humans have two sets of chromosomes, so does corn, so do many other species. Somewhere along the evolutionary history, wheat doubled and then doubled again. You end up actually in wheat having six sets of chromosomes. Wheat is what's called a hexeuploid. Potatoes are a tetraploid. They have four sets of chromosomes. And strawberries are an octuploid. They have eight. And some plants have as many as 24 sets chromosomes. Certain plant species have this really weird thing that might happen from time to time in evolution where they double their DNA naturally. What we've effectively done is just applied a protein to make it happen and bring the correct two plants together when we make it happen.

[00:45:17]

This could only happen for a plant, right? This could never happen with an animal?

[00:45:20]

It wouldn't work in animals. It works in plants. One way you can think about plant genetics is all the genes are tools in a toolbox. The more tools you give the plant, the more it has available to it to survive in any given second, to deal with drought or hot weather or cold weather, et cetera. Every given second, the more tools or the more genes the plant has that are beneficial, the more likely it is to keep growing and keep growing. And that plays out over the lifetime of the plant with bigger leaves and grows taller. But more importantly, if you look at the bottom, the seeds get bigger. And in most crops, what we're harvesting is the seed. That's true in corn and many other crops. Seeing Having over a 40% increase in seed in this little weed was a really big deal. But then we did it in potato. And potato is a crazy result. Potato is the third largest source of calories on Earth. And so we took two potatoes that you see here in the middle, A, B, and C, D. We applied our boosted technology to it, to each of them, and put them together, and you end up with this potato, A, B, C, D.

[00:46:20]

That's the boosted potato. As you can see, these were all planted on the same date, and the boosted potato is much bigger than all the other potatoes here, including a market variety that we show on the far right. That's what's typically grown in the field. Now, here's what's most important. When you look under the ground and you harvest the potatoes, you can see that that A, B potato only had 33 grams, C, D had nine grams. Each parent had 33 and 9 grams potato. But the boosted offspring had 682 grams of potato. The yield gain was insane. You could see this being obviously hugely beneficial for humanity. Potatoes being the third largest source of calories, Indian When potato farmers are growing one acre of potato. In India, they eat potato two meals a day. In Africa, potato is a food staple. So around the world, we've had a really tough time breeding potatoes and improving the yield. With our system, we've seen incredible yield gains in potato almost overnight.

[00:47:16]

How big are those potatoes?

[00:47:18]

Those are normal-sized potatoes that you see there. Those are like table potatoes. Basically, that looks like a rusted potato right there. That's like a normal-sized russet. I can tell you, you got something in it.

[00:47:28]

It started as a little creamer potato, basically, and you blew it up into a russet potato.

[00:47:32]

Is that a word? Yeah. The genetics on A, B, you can see they're like little purple, tiny little purple potatoes. The genetics on C, D are like these little white, tiny little ball potatoes. But when you put those two together with boosted and you combine all the DNA from A, B, and all the DNA from C, D, you get this crazy high yielding potato, A, B, C, D, which, by the way, is higher yielding than the market variety that's usually grown in the field on the far right.

[00:47:55]

Why not just grow russet potatoes then?

[00:47:58]

We are. We're working on doing this with Russet. We're working on doing this with every major potato line. Sorry, the improvement you'll see is actually in yield. So it's not the size of the potato, it's the number of potatoes that are being made. So you'll see- For hectare acre or something like that, like the Dworak week projects in the '60s and '70s.

[00:48:15]

You know how you can tell? Friedberg's onto something here. He got David Sacks to pay attention during it. This is going to be a deck of cord if Sacks is awake. Sacks is like, How do I wet my vehicle?

[00:48:26]

Sacks is interrogating the potato lines. I've never heard.

[00:48:30]

What's going on? I think Sacks is interesting. But so have you tried these potatoes? Do they taste different?

[00:48:34]

Oh, no, they're awesome. Yeah, they're potatoes. We do a lot of analysis.

[00:48:38]

You haven't sprouted any horns yet or anything like that?

[00:48:40]

No. I mean, again, one of the other advantages Of the system that we've developed. Let me go back here, and I just want to take 2 seconds on this. One of the other things this unlocks is creating actual seed that you can put in the ground in crops that you can't do that in today. So potatoes, the third largest source calories. But the way we grow potatoes, you guys remember the movie The Martian, you chop up potatoes and you put them back in the ground. Because the seed that comes out of a potato, which grows on the top in the flour, every one of those seed is genetically different because of what I just showed on this chart. You get Half the DNA from the mother, half the DNA from the other. So every seed has different genetics. So there's no potato seed industry today. And potato is like $100 billion market. With our system, not only can we make potatoes higher yielding and make them disease resistant, what we also is perfect seed. Farmers can now plant seed in the ground, which saves them about 20% of revenue, takes out all the disease risk, and makes things much more affordable and easier to manage for farmers.

[00:49:40]

It creates entirely new seed industries. We're going to be applying this boosted technology that we've discovered across nearly every major crop worldwide. It'll both increase yield, but it will also have a massive impact on the ability to actually deliver seed and help farmers and make food prices lower and improve sustainability. Is it more No, it's actually cheaper. So higher yield, lower cost.

[00:50:04]

Do you need more water?

[00:50:06]

Less water, less land, less energy.

[00:50:09]

Do you need more fertilizer?

[00:50:12]

Fertilizer usually scales with biomass, but these sorts of systems should be more efficient. So fertilizer use per pound produced should go down significantly as we get to commercial trials with all this stuff. We're doing this across many crops. There's a lot of work to do in terms of how do you scale the production in the field.

[00:50:30]

Tell us about the patents and how important patents play a role in this, because isn't it like one of Monsanto's big things, like they just go and sue everybody into the ground or whatever?

[00:50:42]

I'm going to answer you one second. I'm just going to switch my headset. It just died.

[00:50:45]

Wow. We went from Sacks as bots to Friedberg's crops.

[00:50:49]

I'm glad we're doing him second because all of a sudden, group chat doesn't seem very important. Yeah. Wow.

[00:50:55]

He just solved the whole Ukraine crisis here. We're going to be able to grow wheat in the desert and in the rainforest.

[00:51:03]

He solved the world food problem.

[00:51:05]

Yeah, Sacks, what did you do for the last six months?

[00:51:07]

We made our price chat a little better.

[00:51:09]

We added AI to enterprise chat. We cleaned up your slack.

[00:51:13]

So, yeah, when you invest We've invested a ton of money. This was still for five years. We put a ton of money into this business. So when you invest like... I mean, north of 50. Yeah.

[00:51:26]

50 million, five years, and you don't have a product in market yet.

[00:51:29]

Wow, that's some We actually have some product. I haven't talked about the way we've been making money in some of the business we've been doing. Okay.

[00:51:34]

Let me just make sure this is clear. That last photo you showed with the different types of potatoes, you had created the super huge ones, but you're saying that the yield benefit here is just you create a much bigger, hardier plant that's capable of producing many more potatoes. But the size of the potatoes doesn't change?

[00:51:54]

You can control for that when you breed. The selection of what plants you put together in the boosted system allows you to decide. Do you want small, medium, large. That's all part of the design of which plants do you want to combine.

[00:52:04]

Okay, because your goal is not to turn a russet potato into a watermelon or something like that.

[00:52:09]

No, the goal is to make more russet potato per acre so that we use less water, we use less land. Farmers can make more money, people pay less for food. That's the goal. And so it's all about yield. It's not about changing the characteristics. There are some crops where you want to change the characteristics. You might want to make bigger corn kernels and bigger cobs on the corn, which is another thing that we've done. And that's actually been published in our patent. And the reason, by the way, I'm talking about all this is some of our patents started to get published last week. And so when that came out, the word started to get out. And that's why we decided to get public with what we've done, because it's now coming out in the open.

[00:52:43]

You mentioned something briefly there about where different crops can be planted. We had these big talks about wheat and corn. They're only available in very specific parts north of the equator, the Campion jungles, Campion, obviously polar or desert extremes. If you're successful, what would this do for, on a global basis, where these crops are made? Because remember this whole discussion about Ukraine and the wheat belly of Europe, the Cradle of Wheat.

[00:53:16]

It's a great question. I'm so glad you asked it because that's one of the key drivers for the business is that we can now make crops adapted to all sorts of new environments that you otherwise can't grow food. Today, there's somewhere between 800 million and a million people that are malnourished. That means they are living on less than 1,200 calories a day for more than a year. But on average, we're producing 3,500 calories per person worldwide in our Ag systems. The problem is we just can't grow crops where we need them. And so by being able to do this system where we can take crops that are very drought resistant or can grow in sandy soil or very hot weather and adapt cooler climate crops to those regions through the system, we can actually move significantly where things are grown and improve food access in regions of- How, Friedberg, when you look at a potato, how do you figure out what part of their DNA is the drought resistant part?

[00:54:10]

Then how do you make sure that that's turned on? Even if you inherit that chromosome, Is there some potential interaction with the- Generally, if we can...

[00:54:18]

So these are what are called markers, genetic markers. And so there are known markers associated with known phenotypes. A phenotype is a physical trait of a plant. And so we know lots of markers for every crop that we grow. Markers for disease resistance, drought resistance, markers for big plants, short plants, etc. And so what we do is we look at the genetics of different plants that we might want to combine into the boosted system, and we say, These ones have these markers, these ones have these markers. Let's put them together, and then that'll drive the results. One of the other interesting things we're seeing, which I didn't get too much into in the slides, it's not just about combining traits, but it turns out when you add more genes together, biology figures out a way to create gene networks. These are all these genes that interact with each other in ways that are not super well understood, but it makes the organism healthier and bigger and live longer. This is like when you Why mutts are healthier and live longer than purebred dogs? Because they have more genetic diversity. There's a lot of work now in what's called quantitative genomics, where you actually look at the statistics across all the genes.

[00:55:27]

You use a model, and the model predicts which two crosses you want to make out of hundreds of thousands or millions of potential crosses that the AI predicts, here's the two best ones to cross because you'll get this growth or this healthiness.

[00:55:41]

How do you want to make money, Friedberg? Are you going to sell the seeds? Are you going to become the direct farmer? Are you going to become food as a service? How do you make the most money from this?

[00:55:52]

We're not going to farm. Farmers are our customers. There are different ways to partner with people in the industry who already have seed businesses or already have genetics and help them improve the quality of their business. Then there's other industries, like in potato, where we're building our own business of making potato seed, for example. Every crop in every region is actually quite different. It becomes a pretty complicated business to scale. We're in the earlier days. We're already revenue-generating.

[00:56:20]

I would like a sweeter blueberry.

[00:56:23]

No comment. I get tilted by the quality of the Driscoll's strawberries. Let me tell you something about the Driscoll's Blueberries.

[00:56:30]

Also, the Driscoll, I've had only one batch of a Driscoll's strawberry that was just off the charts, and every 19,847 other batches I bought have been total shit.

[00:56:41]

Now, you want the European small ones or the Japanese ones from Hakeido because they're rich and sweet, and they're not these like, monstrosity of giant flavorful strawberries.

[00:56:52]

What's that about, Friedberg? Can you do a seedless mango?

[00:56:56]

Yes, don't cut it.

[00:56:57]

She can just cut it, Friedberg. Oh, my God.

[00:56:59]

How great would that The amount of work per bite on a mango is the worst ratio.

[00:57:04]

Yeah. Oh my God.

[00:57:05]

Well, somehow we made it about us.

[00:57:07]

Yeah, no, look, I think it is all about you guys.

[00:57:10]

Tell us about the strawberries. Sorry.

[00:57:11]

Well, no, every year, Driscoll's puts out a special label package called Sweetest Batch. They just had the sweetest batch of strawberry and strawberries. I don't know if they're still in the stores, but they only last for a week or two. And that's the best genetics, only growing on a small number of acres. What? Really incredible blueberries.

[00:57:29]

I'm going to have to go in as soon as this is done.

[00:57:31]

See if they have it. I got it a few weeks ago. It's quite delicious. Anyway, let's just say we know the Berry market very well. My co founder, CTO, Judd Ward, whose brilliant idea Boosted Breeding was many years ago, who I met because they had a New Yorker article on Judd. I cold-called him and said, Hey, will you come in and give us a tech talk? We started talking, and Judd came up with this idea for Boosted Breeding. We started the business with Judd, and Judd ran molecular breeding at Driskill. We have a lot of Driscoll's people that work at O'Halo.

[00:57:59]

We know the market really well. Can you go back to the patent stuff? Are you- Oh, yeah, sorry. That was the question. Will some seed person sue you?

[00:58:05]

We spent 50 million bucks plus on this business today. We have filed for IP protection so that people can't just rip us off. But I would say, I think that the real advantage for the business arises from what we call Trade Secrets, which is not just about taking patents and going out and suing people. That's not a great business. The business is how do you build a moat, and then how do you extend that moat? The The great thing about plant breeding and genetics is that once you make an amazing variety, the next year the variety gets better, and the next year the variety gets better, and so it's hard for anyone to catch up. That's why seed companies generally get monopolies in the markets, because farmers will keep buying that seed every year, provided it delivers the best genetics. Our business model is really predicated on how do we build advantages in moats and then keep extending them rather than try to leverage IP. I'm a big fan of building business model advantages.

[00:58:58]

This is going to be incredible, Sacks. If you When you think about, geopolitically, what's going on in Somalia, Sudan, Yemen, Afghanistan, those places have tens of millions of people, I think hundreds of millions, collectively, who are at risk for starvation. If you could actually make crops that could be farmed there, Friedberg, it would change humanity. Then all these people buying a farmland in America, that could devalue that farmland if that wasn't as limited of a resource. You have Friedberg?

[00:59:25]

No, I think... First of all, farmland in America is mostly family-owned. It's got 60% rented, actually. A lot of families own it, and then they rent it out because they stop farming it. But the great thing that we've seen in agriculture, historically, is that the more calories we produce, the more food we produce, the more there seems to be a market. It's like any other economic system.

[00:59:47]

What about wheat and rice?

[00:59:49]

Yeah. Those are calorie sources one and two. There's certainly opportunity for us to apply our boosted systems there. The big breakthrough with potato is we can potato seed using our boosted system in addition to making better potatoes.

[01:00:03]

Mcdonald's is the largest buyer of potatoes, yeah.

[01:00:06]

In the US, 60% of the potatoes go to French fries and potato chips. Mcdonald's buys most of the fries. Pepsico, under Frito Le, buys most of the potato chip potatoes. 40% are table potatoes. In India, 95% of the potatoes are table potatoes. They're eaten at home. The Indian potato market is three to four times as big as the US potato market. In Brazil, it's 90% table potato. So All around the world, potato is different. The US is unusually large consumers of French fries and potato chips.

[01:00:36]

I speak on behalf of J. Cal, and I said, We will gladly invest a million at a 10 cap in both of your businesses.

[01:00:44]

Absolutely. Yes, we will break our way into J.

[01:00:47]

Cal and I will do the deal. We'll wire the money. We'll wire the money. A little million to each of you guys at a 10 Cap. Thank you.

[01:00:53]

Absolutely.

[01:00:54]

It may not be a 10 Cap, though, but yes. You're in. Breaking news.

[01:00:58]

Chamonix and J.

[01:00:59]

Cal have secured the bag. It's a breaking news.

[01:01:02]

Chamonix and Jcal have secured the bag from the besties actually doing work. Yeah. Well, I appreciate you guys letting me talk about it. Yeah, congratulations. I'm excited to share it. It's a lot of congratulations to both of you. I love it. It's been... Yeah, building stuff is hard. There's always risk. It's a lot of work and a lot of setbacks. But man, when you get stuff working, it's great.

[01:01:21]

We're each doing the things we do best. Friedberg is solving the world's hunger problem, and I'm cleaning up your slack.

[01:01:29]

I'm Make your enterprise chat a little better. All progress counts. All right. Stanley Druckin Miller has got a new boyfriend. Druckinmiller has got a boyfriend, and his name is Javier, and they've a to Argentina. Druckin Miller professed his love. Tom Cruise on Oprah's couch in a CNBC interview this week. The only free market, quote, Leader in the world right now, bizarrely, is in Argentina of all places. He cuts Social Security 35 %. If he came to office, they've gone from a primary deficit of 4 or five % to a three % surplus. They've taken a massive hit in GDP, basically a depression for a quarter, and his approval rating has not gone down. Truckin Miller has explain how he invested in Argentina after seeing Mallet's speech at Davos, which we covered. Here's a 30-second clip. Play the clip, nick.

[01:02:23]

By the way, do you want to hear how I invest in Argentina? It's a funny story. I wasn't at Davos, but I saw the speech in Davos, and it was about one o'clock in the afternoon in my office. I dialed up perplexy and I said, Give me the five most liquid ADRs in Argentina. It gave me enough of a description that I followed the old Soros rule, invest and then investigate. I bought all of them. We did some work on them. I increased my positions. So far, it's been great, but we'll see.

[01:02:53]

Yeah, that's quite interesting. Quick note, you hear Drucker Miller mention ADRs. For For those of you who don't know, and I was one of them, they stand for American depository receipts, basically a global stock offered on a US exchange to simplify things for investors. Yeah, I mean, he didn't sign a prenup here. He just went all in and he bought the stock, Chamath, and then he's going to figure it out later. Tell us your thoughts on this love affair, this bromance.

[01:03:21]

There's a great clip of Millay. He goes on this talk show in Argentina, and the talk show host, she's just so excited. And greets him, and then they start making out. Have you guys seen this? What? They're just full on French kissing each other. It's hilarious. Yeah, I mean, Souris has been very famous for this invest and investigate thing. It's like a smart strategy for very, very liquid public market investors that have the curiosity that he does. I mean, I don't have a bunch of a reaction to that. I think that the thing with Argentina that's worth taking away is when When you've spent decades casting about and misallocating capital and running your economy into the ground, the formula for fixing it is exactly the same. You cut entitlements and you reinvigorate the economy. The thing we need to take away is if we don't get our shit together, that's probably what we're going to have to do.

[01:04:22]

Sacks, the influence of Mallet on American politics. Will there be any? It seems like he has paralleled what Elon did at Twitter, Facebook, and Zuck did at Facebook. Do you think that this experiment he's doing down there of just cutting staff, cutting departments, will ever make its way into American politics?

[01:04:47]

Probably not. I mean, not until we're forced to. But what Mallet did, he comes in and they've got a huge budget deficit and they've got runaway inflation and they're debasing their currency. And just practically overnight, he just slashes government spending spending to the point where he has a government surplus. And then as soon as he gets credibility with the markets, that allows them to reduce interest rates, inflation goes away, and people start investing in the country.

[01:05:10]

Magic.

[01:05:11]

It's magic. So there is a path. It's obvious. Listen, I mean, You can't run deficits forever. You can't accumulate debt forever. It's just like a household. If your spending exceeds your income, eventually you got to pay it back or you go broke. The only reason we haven't gone broke or experienced hyperinflation is because we're the world's reserve currency. So there's just a lot of room for debacement. And there's not a ready alternative yet. I mean, everyone's trying to figure out what the alternative will be. So we've been able to accumulate more and more debt, but it's reaching a point where it's unsustainable. And what we've already seen is that the feds had to jack up interest rates from very low, practically nothing to five and a half %. And that has a real cost on people's well-being. Because now your cost of getting a mortgage goes way up. I mean, mortgage rates are over, what, seven and a half % now?

[01:06:03]

Yeah, six, seven %, depending on how much networth and your credit rating.

[01:06:08]

Right. And so it's much harder to get a mortgage now. It's harder to make a car payment if you need to borrow to buy a car. And If you have personal debt, the interest rate is going to be higher. The inflation rate actually doesn't take into account any of those things. Remember, Larry Somers did that study where he said the real inflation rate would be 18 % or would have peaked at 18 % if you include a cost of borrowing. That's why people don't feel as well off as the unemployment rate would normally suggest. People are hit really hard when interest rates go up in terms of big purchases they need to make with debt. Then, of course, it's really bad for the investment environment because when interest rates are really high, that creates a higher hurdle rate and people don't want to invest in risk assets. Eventually, the pace of innovation will go down. Druckin Miller made this point in his next set of comments, he said that, Treasury is still acting like we're in a depression. It's interesting because I've studied the depression, and you had a private sector crippled with debt, basically with no new ideas.

[01:07:12]

So interventional policies were called for and were effective. He said the private sector could not be more different today than it was in the Great Depression. The balance sheets are fine, they're healthy. And have you ever seen more innovation ideas that the private sector could take advantage of, like blockchain, like AI? He says all the government needs to do is get out of the way and let them innovate. Instead, they spend and spend and spend. And my new fear now is that spending and the resulting interest rates on the debt that's been created are going to crowd out some of the innovation that otherwise would have taken place. I completely endorse Drucker Miller's view of binomics. Actually, this is what I said way back in 2021.

[01:07:50]

Victory lap. Here we go. A little David Sacks victory lap. We need a little graphic for that.

[01:07:55]

Drucker Miller used the word Bidenomics and said, I give these guys an F because they're still printing money and spending money like we're in a depression, even though we're in a rip-roaring economy. And when they started doing this back in 2021, I tweeted, Bidenomics equals pumping trillions of dollars of stimulus into a rip-roaring economy. I'm not going to pretend like I know what's going to happen next, but never tried this before. What happened next was a lot of inflation, and that jacked up interest rates. According to even Keynesian economics, the reason why you have deficit spending is because you're in a recession or depression. And so use the government to stimulate and balance things out. You don't do deficit spending when the economy is already doing well. So this spending, there's no reason for it.

[01:08:34]

It's like showing up to a party that's going crazy and putting gasoline on the fire. Yeah.

[01:08:39]

I mean, more importantly, it should limit the approval or action of certain programs that you might otherwise want to do in a normal environment. But in an inflationary environment, you don't have the flexibility to do them. Student loan forgiveness is a really good example. It's now the time.

[01:08:59]

Of course not.

[01:08:59]

To do student loan forgiveness, or do we wait for inflation to temper a bit? Is now the time... So there's just a lot of these examples that actually the opposite should be true. Yeah, but none of...

[01:09:10]

All of those things get you votes.

[01:09:12]

Before we move on from this, look, what we have coming out of Washington here is a contradictory and therefore self-defeating policy. You've got the Fed jacking up rates to control inflation. You move across town and you've got Capitol Hill on the White House spending like there's no tomorrow, which is inflationary. Why would you do both those things? Choose what your policy is going to be.

[01:09:30]

It's like driving with your foot on the break and the gas at the same time. It's not a great idea for the car.

[01:09:35]

Let me just make one comment, J. Kal, before we move on about the Druckenmiller investment statement. Of course. I just wanted to say, I think what it highlights about Drucker-Miller, and call it a rift in investing philosophy or skill, is the difference between precision and accuracy. What I mean by that is precision really references that you do a lot of detailed analysis to try and make sure you understand every specific thing that is going right or could go wrong. But the problem, and so that means you, for example, might do a ton of diligence on a company and make sure you understand every dollar, every point of margin, all the specifics of the maturation of that business and where they are in their cycle. But you could be very precise, but be very inaccurate, for example, if you miss an entire trend. Someone could invest in Macy's back when Amazon was taking off and have done a lot of precise analysis on Macy's margin structure and performance and said, This is a great business. But they missed the bigger trend, which is that e-commerce was going to sweep away Macy's. Consumers were simply, That's not possible in the analysis that they were doing.

[01:10:40]

Let's be honest, Friedberg, nobody could make that stupid of a trade to say Macy's versus Amazon over the next 10 years.

[01:10:46]

Well, yeah. And so like...

[01:10:49]

Do you want to show that? No, no, no, no.

[01:10:51]

Do not poke the tiger. Let's not get into it with other podcasters.

[01:10:55]

The worst spread trade in history. Yeah, let me just finish the statement. But the other one is being accurate. And accurate means you get the right bet, the right sentiment, the right friend. The problem with being accurate, you could have said in the year 2000, Hey, the internet's going to take off. And you could have put a bunch of money in. But the problem was you were right, you just had to have the necessary patience. And so accuracy generally yields better returns, but it requires more patience because you can't necessarily time how long it will take for you to be right. So it A guy like Druckin Miller is making an accurate bet. He bets correctly on the trend, on where things are headed. He doesn't necessarily need to be precise, but he has the capital and his capital structure that allows him to be patient to make sure that he eventually gets the return.

[01:11:44]

And to build on your thoughts, having watched this movie a couple of times, and I over thought the Twitter investment as but one example. I had the opportunity to invest in Twitter when it was a single-digit millions company. I just thought, You know what? This thing is only the headline And I told Eve, It's the headline. It's not like the entire blog post. It's a cacophony of idiots. This thing is going to be chaos. And I was right, but I was wrong. Great bet, but my wrong analysis. And so you can add precision to other aspects, like when you sell your shares or when you double down. But you have to get the trend, which is Evan Williams, great entrepreneur, Jack, great entrepreneur, Twitter taking off like a weed, just make the bet.

[01:12:24]

The problem is you knew too much about journalism. You knew too much about the space they were trying disrupt, and that could be a mistake. We did PayPal. None of us knew anything about payments. That was one of the reasons we were successful. All the payments experts told us it couldn't be done.

[01:12:38]

Right.

[01:12:39]

Absolutely. That happens a lot.

[01:12:41]

I didn't even know what a Facebook was when I joined Facebook. It's an American college phenomenon. No, seriously? You don't have that in Canada.

[01:12:48]

But you knew Zack, and you saw some growth charts, and you saw some precision in his ability to build product, and that's the way to go.

[01:12:55]

The great thing about network effect businesses is there's a trend line that sustains because it builds if it's an appropriate network effect. So you can be accurate about buying into the right network effect business. You don't need to use all of this diligence to be perfectly sound around the maturation of the revenue and the margin structure and all that stuff as long as the trend line is right and you're willing to be patient to hold your investment. I think Drucker Miller's point is incredible. He took a look, he very quickly made a macro assessment. From a macro perspective, what Mallet is doing is significantly different than what we're in any other emerging market, let alone mature market, with respect to fiscal austerity and appropriateness in this global inflationary environment. He said, You know what? I don't see any other leader doing this. This is a no brainer bet. Let me make the bet. As long as he's willing to hold this thing for long enough, eventually the markets will get there and call it a spread trade against anything, he'll be proven right.

[01:13:53]

But speaking of bets, Jekal, you told me this week that you just made your largest investment ever. Tell us about that.

[01:14:00]

I've gotten very lucky now because a lot of my founders from the first couple of cohorts of investing I did when I was a Sequoia Scout have come back and created second and third companies. That happened with TK Uber and the Cloud Kitchens. It happened with Raul from, report of then Superhuman. Then it happened recently, just in the past year, my friend Jonathan, who's the co founder of Thumbtack, asked me to come to dinner and said, Hey, you were the first investor in Thumbtack. Will you be the first investor in our next company, Athena? I said, Sure, what do you do? He explained it to me. We put a seven-figure bet in, which is rare for us as a seed fund. Normally, our bet sizes are 100K, 250. It's a $50 million fund. Why did you do it? Yeah, it's very simple. It's the fastest-growing company I've ever seen, and I'm including Uber in that, it has been growing at a rate that I'll just say is faster than Uber and Robin hood when we were investing in them, tens of millions of dollars. It's a very simple concept. When Thumbtack was building their marketplace, they used researchers in places like Manila, et cetera, in the Philippines, knowledge workers.

[01:15:09]

And what they realized was the 0.1% of those knowledge workers were as good or better than, say, Americans at doing certain jobs. And so they've created this virtual EA service. You can go see it at ethinawau. Com. And we now have two of them inside of our company. It turns out Americans don't want to do the operations role. So it's like AWS. You just give them $36,000 a year. They give you essentially an operations or an EA. And they have ones that are cheap of staff-ish, and this company is growing like a weed. I I'm working with them on the product design as well. Imagine having two or three of these incredibly hardworking people who are trained with MBA class-level curriculum. They spend months training these people up. They pay them two or three times what they would make at any other company, and then they pair them with executives here. And it's been an underground secret in Silicon Valley because it's only by invitation right now because they can only train so many people. But if You've tried to hire an executive assistant. I don't know if anybody's tried to do that recently.

[01:16:18]

You hooked me up, so I will be guinea picking this service soon.

[01:16:22]

I have two of them. It is just the greatest that you can have an operations person on board.

[01:16:29]

Are these people powered by AI tools as well?

[01:16:31]

Yeah. That's the secret sauce here is they're training them and they watch you work, and then they will learn how you do your job, and then how quickly you can delegate and get stuff off your plate is the name of the game. We have an investment team with researchers and analysts in it. We have a due diligence team. Then you have executive functions in our fund. They have now started shadowing highly paid Americans in an investment firm, ours, and then train them up. Now our due diligence, our first-level screening, and our tracking of companies is being done by these assistants for what I'll say is a third to a fourth of the price I was paying previously. What that does in an organization is we're just delegating away and then moving our investment team to doing in-person meetings and doing higher-level stuff.

[01:17:21]

Yeah, you're 80/90. At 80/90, we have this funny thing where we've made it a verb. Whenever you see somebody doing high-quality work at a quarter to a 10th of the cost, we say, Oh, you just 80/90-ed it. Correct. So you're 89-ing the investment team.

[01:17:36]

I'm 89-ing the investment team. And you know what? It was scary as hell for them because they're like, Am I going to lose my job? It's like, No. You now get to, instead of doing a check and call once a month, you can do a check and call every other week or every week. Or instead of doing 15 first-round interviews a week, you can do 25 because you have this assistant with you doing all the repetitive work.

[01:17:55]

The way that companies will work in 5 and 10 years, I don't think, guys, any of us are going recognize what it's going to look like. No.

[01:18:01]

This is where I go.

[01:18:03]

I mean, like watching Sacks as demo earlier, how much progress and how seamless that product works with the features it has enabled by the underlying models, you just get to thinking how all of these vertical software applications become completely personalized and quickly rebuilt around AI. Totally. It's so obvious.

[01:18:26]

Can you imagine how long it would have taken John to write a letter to Lena to invite. If we said, John, invite Lena Con, but be sure to reference all the nice things we said about her on episodes of the pod.

[01:18:36]

It'd be 10 hours of work. You got to go find the episodes, listen to it.

[01:18:39]

Listen to them to figure out what the best quotes are.

[01:18:41]

You got it done in five seconds. It's incredible. Totally. Then imagine building that same capability into a very specific vertical application that's specific to some business function. You can probably spend a couple of minutes or an hour building that function, and then it saves you hours a day in perpetuity. Correct. I think that's why these tools companies or the tools products that Google, Microsoft, Amazon, and a few others are building are actually incredible businesses because so many enterprises and so many vertical application builders are going to be able to leverage them to rewrite their entire business functions.

[01:19:19]

I got myself and my cofounders at 8090, we get this stream of emails of companies or people that are like, We have this product idea, or, We have this small product. I was like, One of the emails I got, this is crazy, was from a guy that's like, Oh, we've 8090 Photoshop. We have a much, much cheaper version of Photoshop. The guy was doing a few million bucks of ARR and growing really nicely. But then it turned out that somebody saw that, and then 80/90 it. So then there's an open source version of that. To your point, Friedberg, none of these big companies stand at chance.

[01:19:55]

Yeah.

[01:19:56]

It's everything is going to get cheaper and faster. Not because they're Not because the products aren't good, but like, Jcal is going to go off and experiment with this. Sack is going to go off and build a product. Every time that you're at a boundary condition, we're all going to explore, well, maybe we could do this with AI, maybe we shouldn't hire a person, not because We're trying to be mean about it, but it's because the normal natural thing to do. The OpEx of companies is just going to go down, which means the size of companies are going to shrink, which means the amount of money you need is going to go down. That's just going to create the ability for these companies sell those products cheaper. It's a massive deflationary tailwind here.

[01:20:35]

We had the same thing happen with Compute, and now it's happening inside of organizations. I wrote a blog post about this on my Substack called ADD. This is the framework I came up with. I told my entire team, Look at what you got done every week, and I want you to ask three questions. How can I automate this? How can I deprecate this? How can I delegate it? The automate part is AI and what you're doing, David. The delegate part is athenawow. Com. And then the deprecate is, Hey, just be thoughtful. What are you doing that you don't need to do? That's '80, '90ing something. There are things inside these products that you don't actually need. What's the core functionality of the product? Make it as affordable as possible. And then what's going to happen for people who think this is bad for society? You've got it completely wrong. We're going to have more people be able to create more products and solve more problems. The unemployment rate is going to stay very low. We're just going to have more companies. So the idea The idea, there was somebody who was working on very small software.

[01:21:34]

I get pitched on very niche ideas. I want to create something where people can find people to play pickleball with, like a pickleball marketplace. Now, that wouldn't typically work because you would need $5 million a year to build that product. But if you can build it for $500,000 a year, well, now you've only got to clear that number to be profitable. So a lot more smaller businesses, a lot more independence. All these little niche ideas will be able to be built. And a VC who says, I'm not giving you $5 to build that app, will be like, But I will give you $500, okay? And that's what I'm seeing on the ground in startups. The same startups that had a request of $3 million in funding five years ago are now requesting $500 to a million. It's deflationary all the way down. It's going to be incredible.

[01:22:17]

Did you see the Google thing? Did you guys see the Google AI Gemini stuff?

[01:22:21]

Chatgpt Omni launch at the same time, or perhaps strategically, right before Google dropped its latest AI announcement at I/O. The biggest announcement is that they are going to change search. This is the piece of the puzzle in the kingdom that they have been very concerned with, and they're going for it. The new product, and they have 20 different products, you can see them at labs. Google, where they put all their different products. But this is the most important one. They call it AI Overviews. Basically, it's perplexity. For most users, by the end of the year, they're going to have this. Here's how it works, and you can see it on your screen. If you're watching us, go to YouTube. Here, they gave an For example, how do you clean a fabric sofa? This normally would have given you 10 blue links. Here, it gives you step-by-step guide with citations and links. So they're preempting the issue of people getting upset. And as I predicted, they're going to have target Look at it, it adds. Here's the things you need in order to clean your couch. You can only use this if you're using your Gmail account.

[01:23:22]

If you use a domain name on Google Docs, it won't work there. So go to labs. Google. But they're doing citations. And I think that we're going to see a major lawsuit here. Those people who are in those boxes are going to look at the answer here and realize maybe they don't get the click through and that this answer was built on that. And now we're going to have to have a new framework. There's going to need to be, Sacks, a new company that clears this content so that Google can do answers like this.

[01:23:48]

The workflow stuff in Gmail also kicked ass. The demo that they showed was you get a bunch of receipts and the person giving the demo, she said something to the effect of, Well, wouldn't it be great If the AI assistant were able to find all the receipts and then aggregated them and it put them in a folder and then also actually generated an expense report or a spreadsheet on the fly? Why not? It's crazy. I got to say, I think that it's free to change your mind. It's good to do that. I think that Chamath, in a rare moment of reflection, might do a...

[01:24:25]

Are we going to have a re-underwriting?

[01:24:26]

Is this a re-underwriting? I change my mind all the time. I mean, because I'm- Ladies and gentlemen, breaking news.

[01:24:33]

Chamath is re-underwriting his Google train.

[01:24:36]

Sorry, I know, to blow your ears out.

[01:24:39]

I think the Google thing is pretty special. Between last week's announcement of Isomorphic Labs, which Let's be honest, that's just a multi-hundred-billion-dollar company.

[01:24:50]

So you're saying there might be many- Think about it this way, right? Multi-billion-dollar opportunities sitting there dormant inside of Google that AI unlocks.

[01:24:57]

Look at a company like Ruralty Pharma. So if Royalty Pharma, it's a phenomenal business run by a phenomenal entrepreneur, Pablo Lagoretta. But what is that business? That's buying 2 and 3% royalties of drugs at work. You can see how much value that those guys have created, which is essentially 90% EBITDA margin business. It's outrageous because they're in the business of analyzing and then buying small slivers. I think something like Isomorphic ends up being of that magnitude of margin scale, but at an order of magnitude or two orders of magnitude higher revenue. If you fold that back into a Google, if you think about what they're doing now on the search side, these guys may be really kicking some ass here. I think that the reports of their death were premature and exaggerated.

[01:25:46]

Absolutely. The report of their death, Friedberg, was based upon people don't need to click on the ads. But as I said on this very podcast, my belief is that this is going to result in more searches and more knowledge engagement because once you get how to cook your steak and get the right temperature for medium rare, it's going to anticipate your next three questions better. So now to say, Hey, what wine pairing would you want with that steak? Hey, do you need steak knives? And it's just going to read your mind that you need steak knives, and Chamot likes to buy steak knives, but maybe you like to buy mock meats, whatever it is. It's going to drive more research and more clicks. So while the monetization per search may go down, we might see many, many more searches. What do you think, Friedberg? You work there, and when we look at the future of the company and the stock price, nick will pull it up, man, if you had held your stock, I don't know, did you hold it?

[01:26:40]

I bought some- No, your original stock. During the Wokey, I thought- Did you clear it at some point? No, I sold all my stock back when I started Climate because I was a startup entrepreneur and needed to live. Which I recently did. In hindsight? I did the math on it. It'd be It would be worth a lot.

[01:27:02]

It would be worth billions or tens of billions?

[01:27:04]

No, no.

[01:27:05]

Would it have been a billion?

[01:27:06]

No, no. Okay. I was not a senior exec or anything. I think what you said is probably true. So that's accretive. I think the other thing that's probably true is a big measure at Google on the search page in terms of search engine performance was the bounceback rate, meaning someone does a search, they go off to another site, and then they come back because they didn't get the answer they wanted. Then the One Box launched, which shows a short answer on the top, which basically keeps people from having a bad search experience because they get the result right away. A key metric is they're going to start to discover which vertical searches, meaning like, hey, cooking, recipes, that stuff, like you're referencing- Travel, sports. Travel. There's lots and lots of these different types of searches that will trigger a snippet or a One Box that's powered by Gemini that will provide the user a better experience them jumping off to a third-party page to get that same content. Then they'll be able to monetize that content that they otherwise were not participating in the monetization of. I think the real victim in all this is that long tail of content on the internet that probably gets cannibalized by the Snippet One box experience within the search function.

[01:28:19]

Then I do think that the revenue per search query in some of those categories actually has the potential to go up, not down.

[01:28:26]

Explain. Give me an example.

[01:28:27]

You keep people on the page so you get more more search volume there. You get more searches because of the examples you gave. Then when people do stay, you now have the ability to better monetize that particular search query because you otherwise would have lost it to the third-party content page. For example, selling the steak knives is another... It's a good example, or booking the travel directly and so on. By keeping more of the experience integrated, they can monetize the search per query higher, and they're going to have more queries, and then they're going to have the quality of the queries go up. So I think it's all in. There's a case to be made, and I haven't done a spreadsheet analysis on this, but I guarantee you, going back to our earlier point about precision versus accuracy, my guess is there's a lot of hedge fund type folks doing a lot of this precision type analysis, trying to break apart search queries by vertical and try to figure out what the net effect will be of having better AI-driven one box and snippets. And my guess is that's why there's a lot of buying activity happening in the stock right now.

[01:29:28]

And I think they're probably all missing, to my point, a lot of these call options like Isomorphic Labs. I can tell you Meta and Amazon- Waymo. Meta and Amazon do not have an Isomorphic Lab and Waymo sitting inside their business. That suddenly pops to a couple of hundred billion of market cap. And Google does have a few of those.

[01:29:47]

So other bets could actually pay off.

[01:29:49]

These are long. There may be. Look, I mean, there's Calico. No one talks about Calico. I don't know what's going on over there.

[01:29:53]

Life extension. Let me get Sacks involved in this discussion. Sacks. When we show that example, it's obvious Google is telling you where they got these citations from and how they built their... How to Clean your Couch, How to Make your Stake. They were in a very delicate balance with content creators over the past two decades, which is, Hey, we're going to use a little bit of your content, but we're going to send you traffic. This is going to take away the need to send traffic to these places. They're going to benefit from it. To me, this is the mother of all class action lawsuits because they're putting it right up there. Hey, we're using your content to make this answer. Here's the citations. We We didn't get your permission to do this, but we're doing it anyway. What do you think is the resolution here? Does all these content go away because there's no model? Does Google try to make peace with the content creators and cut them in or license their data? What's going to happen to content creation when somebody like Google is just going to take Wirecutter or these other sources that are not behind a paywall and just give you the goddamn answer?

[01:30:53]

Well, look, this is the same conversation we've had two or three times where we're going to need the courts to figure out what fair use is. Depending on what they come up with, it may be the case that Google has to cut them in by doing licensing deals. We don't know the answer to that yet. By the way, I do know a founder who is already skating to where the fuck is going and creating a rights marketplace so that content owners can license their AI rights to whoever wants to use them. I think that could be very interesting.

[01:31:20]

That's smart.

[01:31:20]

I had a call with him yesterday, and you and I will be on that cap table together once again. Okay, good.

[01:31:25]

I don't want to say who it is because I'm going to let him announce his own round, but I'm only participating in the seed round. Look, stepping back here, it's interesting. If you go back to the very beginning of Google, the Ogie Google search bar had two buttons on it, right? Search, and I feel lucky. I feel lucky was just tell me the answer, just take me to the best result. And no one ever did that because it sucked. Then they started inching towards with Onebox, but you didn't get the Onebox very often. It's very clear now that Gemini-powered Onebox is the future of Google Search. People just want the answer. I think that that this feature is going to eat the rest of Google Search. Now, it's a little bit unclear what the financial impact of that will be. I think, like you guys are saying, there'll be probably more searches because search gets more useful. There's fewer links to click on, but maybe they'll get compensated through those relevant ads. Hard to say, you're probably right that Google ultimately benefits here. But let's not pretend this was a deliberate strategy on their point.

[01:32:27]

They got dragged, kicking and screaming into this by innovation of perplexity in other companies. They had no idea. They got caught completely flat-footed, and they've now, I guess, caught up by copying perplexity. And it sucks for perplexity. I think they're screwed now unless they get an acquisition deal. Yeah, it's over. But Perplexity came up with the idea of having citations in your- Having a comprehensive search result, yeah, which was something- Search result with citations and related questions. They did it extremely well and Quite frankly, all Google had to do was copy them. Now they've done that. And I think it does look like a killer product.

[01:33:05]

And by the way, this was all something that I saw 15 years ago when I did Mahalo, which was my human-powered search engine, and which I had copied or been inspired by Naver and Daum in Korea. They were the first ones to do this. You know what came up? Because there were only three or four markets where Google couldn't displace the number one. Korea, Russia, Japan. Russia had... What was the Russian search engine? God, I can't remember now. Japan had Yahoo Japan, which Masayoshi Son had carved out. It was never a part of it, and they were loyal to that. And very nationalistic Koreans and very innovative folks at Daum and Naver just made search that was so amazing. You do a search and be like, Here's music, here's images, here's answers, here's Q&A. It was awesome. But it just shows you you need to have a lot of wherewithal and timing is everything as an entrepreneur. My timing was 10 years too early. And the wrong technology. I used humans, not AI, because AI work 15 years ago.

[01:34:02]

One thing I would say about big companies like a Google or Microsoft is that the power of your monopoly determines how many mistakes you get to make. So think about Microsoft completely missed iPhone iPhone, remember? And they screwed up the whole smartphone, mobile phone era.

[01:34:18]

And it didn't matter.

[01:34:19]

It didn't matter. Satya comes in, blows this thing up to a $3 trillion public company. Same thing here with Google. They completely screwed up AI. They invented the transformer, completely missed LLMs. Then they had that fiasco where they have- Black George Washington. Black George Washington. It doesn't matter. They can make 10 mistakes, but their monopoly is so strong that they can finally get it right by copying the innovator, and they're probably going to become a $5 billion company I'm sorry, $5 trillion company.

[01:34:46]

It reminds me the greatest product creation company in history. I think we all know who that was. Take a look down memory lane. Here are the 20 biggest felt Apple products of all time. The Apple Lisa, Macintosh Portable. We all remember the Newton, which was their PDA, the 20th anniversary, Macintosh Super Sexy. People don't remember. They had their own video game.

[01:35:10]

I was at a conference a couple of years ago that Jeff Bezos spoke at. I think he's given this talk in a couple of other places. You could probably find it on the internet. But he talks about Amazon's legacy of failure and how they had the fire phone and the fire this and the fire that. And he's like, Our job is to fail. Big swings. We have to make these blunders. But what makes us successful is that we learn from the failures and we make the right next decision.

[01:35:38]

Yeah, but I say if you're a startup and you make big failures, you usually just go out of business.

[01:35:41]

One and done.

[01:35:43]

Yeah, but this is how you But this is how you stay competitive. If you're a big founder-led tech company, the only way you're going to have a shot at staying relevant is to take big shots that you're going to fail at. I remember this one, the iPod, Hi-Fi, remember this boombox? You have to do things that you're going to fail at.

[01:36:00]

Remember this boom box? This is one of the huge differences between startups and big companies is that big companies can afford to have a portfolio of products. They have a portfolio of bets. Some of them will work, and that keeps the company going. Startup really has to go all in on their best idea. Totally. I always tell founders, just go all in on your best idea. They're always asking me for permission to pivot. I always tell them, Go for the best idea. Don't hedge. Don't try to do five things at once. Just go all in on your best idea.

[01:36:26]

And if it doesn't work out, you reboot and start with a new You're going to go all in. So to speak, another amazing episode is in the can. The boys are in a good mood. You got your great episode. No guests this week. Just all besty all the time. And very important, the March to a Million continues halfway there. You got us there, fans. We hit 500,000 subbies on YouTube, which means you all earned a live Q&A with your besties coming at you in the next couple of weeks, we're going to do it live on YouTube. So if you're not one of the first 500, get in there now so you get the alert. We're going to take your questions live. It's going to be dangerous. Any questions, no questions are off. Who knows what could happen on a live show. And by the way, I just want to let you know that Phil Helmuth, breaking news, Phil Helmuth and Draymon Green just resigned from OpenAI. We didn't get into that, but the OpenAI resignations continue. Phil Helmuth has tweeted he's no longer with OpenAI.

[01:37:26]

You guys like my baby cashmere pink sweat?

[01:37:29]

It's pretty great. Are we going to get summer chamat soon? Are the buttons coming down? Are you going to go with Linnon? When does Linnon chamat show up?

[01:37:36]

The unbuttoning is about to happen in the next two or three weeks.

[01:37:39]

The great unbuttoning. This is how you know. It's like Groundhog Day. You know that summer's here when we lose chamat buttons.

[01:37:46]

Almost here. No, it's Memorial Day. When after Memorial Day, the button can come down.

[01:37:50]

Yeah, we're going to go three buttons down. I'll still be wearing my black T. Sacks will still be blue blazer, blue shirt, red tie, and Friedberg in fields of gold. Look at Friedberg in fields of gold, taking us out. Sting, fields of gold coming at you. Two for Tuesday. See you all in the next solid pod for the Sultan of Science. The Rainman, David Sacks and Chairman Dictator, I am your Z100 Morning Zoo DJ.

[01:38:17]

We'll see you next time. Love you, boys.

[01:38:19]

Bye. Bye.

[01:38:22]

We'll let your winners ride.

[01:38:26]

Rainman, David Sacks.

[01:38:30]

And it said, We open source it to the fans, and they've just gone crazy with it.

[01:38:34]

Love you, Westies.

[01:38:35]

I'm doing all it.

[01:38:38]

What your winner's like? What your winner's like?

[01:38:43]

Besties are gone.

[01:38:45]

That's my dog taking it. I don't understand your driveway sex.

[01:38:49]

Oh, man.

[01:38:52]

My haberdasher will meet me as what it says. We should all just get a room and just have one big huge orgy because they're all just useless. It's this sexual tension that they just need We're going to release our mouth.

[01:39:01]

What? You're the bee.

[01:39:03]

What? You're the bee. We need to get merches on that.

[01:39:08]

I'm going all in.

[01:39:15]

I'm going all in.

[01:39:19]

Now the plug. The All-in Summit is taking place in Los Angeles on September eighth. Through the 10th, you can apply for a ticket at summit. Allinpodcast. Co. Scholarships will be coming soon. You can actually see the video of this podcast on YouTube, youtube. Com/@allin, or just search Allin podcast and hit the alert bell and you'll get updates when we post. And we're going to do a party in Vegas, my understanding, when we hit a million subscribers. Look for that as well. You can follow us on x, x. Com/theallinpod. Tiktok is all_in_talk. Instagram, the Allinpod. And on LinkedIn, just search for the All In podcast. You can follow chamoth@x. Com/chamoth, and you can sign up for a sub stack at chamoth. Substack. Com. I do. Friedberg can be followed at x. Com/freeberg. And O'Halo is hiring. Click on the careers page at ohalogenetics. Com. And you can follow Sacks at x. Com/davidsacks. Sacks recently spoke at the American Moment conference, and people are going crazy for it. It's pinned to his tweet on his ex-profile. I'm Jason Kalicanis. I am x. Com/jason. And if you want to see pictures of my Bulldogs and the food I'm eating, go to Instagram.

[01:40:34]

Com/jason in the first-name club. You can listen to my other podcast this week in Startups. Just search for it on YouTube. We're your favorite podcast player. We are hiring a researcher, a a researcher, apply to be a researcher, doing primary research and working with me and producer nick, working in data and science and being able to do great research, finance, etc. All in podcast. Co/research. It's a full-time job working with us, the besties. And really excited about my investment in Athena. Go to ethenawell. Cienawwell. Com and get yourself a bit of a discount from your boy, J. Cal, ethenawell. Com. We'll see you all next time on the All In podcast.