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GPT-4o launches, Glue demo, Ohalo breakthrough, Druckenmiller's bet, did Google kill Perplexity?

发布时间 2024-05-18 05:04:19    来源


(0:00) Bestie Intros: Recapping Phil Hellmuth's birthday weekend (7:38) OpenAI launches GPT-4o: better, faster, cheaper (29:40) ...



All right, everybody. Welcome to your favorite podcast in the world's number one podcast, the all in podcast. It's episode 1,790. 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? That's AI generated. It's AI generated crop. Okay. I'm trying AI backgrounds. I'm going to try it out for a while with different crops. 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 Sachs, the rain man. Yeah. How you doing, buddy? Good. Good. Yeah. Good week. What's going on? Yeah. Yeah, definitely good week. Trimoth Polyapotia, chairman dictator. He puts the chairman.
好的,大家。欢迎收听你们最喜爱的播客——世界排名第一的播客,全能播客。这是第1790集。哦,等等,这只是感觉像第1790集。欢迎收听第179集。今天和我一起的是你们的科学苏丹。我不知道那是电影背景还是他最喜欢的蔬菜。那是什么情况?那是AI生成的。是的,AI生成的作物。好吧。我正在尝试AI背景,我会用不同的作物试一段时间。你的粉丝们会很失望,因为你不再和我们一起做深入的电影引用。当然了,这位就是满城风云,DC的新产品推出者,大卫·萨克斯,雨人。你怎么样,兄弟?很好。很好。是的,过得不错。发生了什么?是的,是的,确实是个好星期。Trimoth Polyapotia,主席兼独裁者。他就是那个掌握全局的人。

I would like to take this opportunity to wish. My child a happy birthday. I absolutely love you. Well, now the rest just look like shit. Yeah, great. I've never done that before. Zach, in your desk, in your desk is a piece of paper with your children's names and their birthday. You want to pull it out? I got three birthdays a year and I've never done one. What your winter ride. Rain man, David Sachs. And we open source it to the fans and they've just got a reason. Love you guys. I see. Queen of King. Rob. Going. Oh, yeah. No, no, no, but I'm saying it rarely lands on the same day. Today is the day. Today is the day. Today is the day. OK, yeah. Today is the day. Good. Congratulations, child. Oh, congratulations. Yeah. How old? Jamov. No gender name or any other specifications, folks. We can't we can't tip anybody off. No pronouns.

No pronouns. No pronouns. Yes, absolutely. So how are they? This child experiencing their birthday. 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. All right. And did you order them some chicken fingers? I cannot comment on who this person is. Chicken. Are you talking, of course, about Phil Helmuth's child, Phil Helmuth. Can we please talk about last weekend's festivities in what a disaster he is? Oh, my God. Do you guys you see you guys know? So we missed you last weekend. We missed you so much fun. Come on. We missed you on Saturday night. Saturday night was really fun. I had such a lovely time coming home to be totally honest with you. We had a cabana set up on Saturday, played blackjack.

I miss you guys too. I had a phone. I saw the videos. It was so fun. Well, you don't have to have too much phone mode because Phil sent the entire group chat to poker news.com. They didn't run it twice. The flop. Horg poker dash. Up there. Yeah. It was like he kept tweeting all week. He leaked every single person who's there and the he said he's like, look, here's me and Elon. He's like, Elon came by for my dinner. No, no, no, no, it was worse than that. No, it was worse than that. He said, I got to hang out with our guy, Elon, for 10 minutes and 14 seconds. Hey, what? He died. He intercepted him at the valet. Wait, what? I'm coming. It's 10 minutes and 14 seconds.
我也想你们了。我有手机,看到了那些视频,真是太有趣了。好吧,你们不必太沉迷于手机模式,因为菲尔把整个群聊都发到poker news.com了。他们并没有两次发布,全都是实时的。这一周他一直在发推文,泄露了在场的每一个人,他还说,“看,这是我和埃隆的合照。”“埃隆来参加我的晚餐了。”不,不,不,比这更夸张。他说,“我和我们的好朋友埃隆相处了10分14秒。”你说什么?他是在代客泊车那儿截住埃隆的。等等,什么?我来了,就是这10分14秒。

He had the exact time down to the second. Oh, I got Melissa. And I want to wish Phil home with the happy birthday because I did miss his 60th party. Yeah, it's coming back to his birthday. His birthday wasn't actually his birthday. It was Bill Gurley. So we just hijacked Bill Gurley's birth. I also got to enjoy it for my first time ever, uh, the experience of bakarot, which I've decided is the most DJ DJ game on earth. It's literally. The most you just flip points. It's flipping points. Well, this is crazy. You make many decisions. All you do in bakarot is you say thing or player and then you freak yourself out about how you flip the cards and the smartest people I know on earth are all sitting around the table at two three in the morning saying, turn this corner this way. No, no, no, no, no, turn it this way. Turn it this way. There's two dots and they're debating the right way to flip a part.
他精确地掌握了时间,精确到秒。哦,我联系到了Melissa。我希望能够祝Phil生日快乐,因为我错过了他的60岁生日宴会。对,话题又回到了他的生日。其实,那天庆祝的并不是Phil的生日,而是Bill Gurley的生日。所以我们其实是“劫持”了Bill Gurley的生日。我还第一次体验了百家乐,这让我觉得这是世界上最具有娱乐场感的游戏。它真的很简单,就是翻牌的游戏。你根本不需要做什么复杂的决定,你只需要选择是“庄”还是“闲”,然后就开始紧张地翻牌。我认识的最聪明的人都会在凌晨两三点围坐在桌边,说着“把这个角这样翻”,“不不不,应该这样翻”。他们会为了怎么翻出正确的牌而争论不休。

That's true. No, the sweat is the most incredible performative act in the game. Don't have to say. Yeah, you're right. Everyone's got their own little tech. Take a look at how they bend the card. So exactly destroyed by the end of the deck. They don't. I, you can get me. I go like this and I try to see. Oh, like you're selling your mustache like an e-mail. You got to go like this. And then you call it. Oh, my God. No spotter. If you see a rose. But we're too gross. So. And then you get to decide whether the bank turns over their cards and it. What when they turn over, then you lose a small house and then you're like, yeah, you're convincing yourself that you have all this control and ways to change the outcome. Right. Because you're literally flipping a car. It's high card.

Well, it's all it is. It's high card. 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. But really tell you you either win or lose. And I'm watching the smartest guys we know staring at the window at the little machine that tells you whether bank or player one and they're studying it. Doing a salad. It's been at work. Words. It's not a go black. Hell be like I'm calling it now bank, bank, player, player, player. And all the guys are like, let's do it. And then everyone gets heads, heads, tails. Tell me.

So tell me fast. Us to play in the high stakes poker game on poker go. So it was me, Elmuth Stanley, Sammy, House, and then gently and Nick airball and Roble. So most of the guys from the house came plus. Gently and Nick airball. Jennifer Tilly is amazing. Why not? Listen to this. Well, listen to this hand. Literally the second hand. Of the actual poker game. Gently. Is in the big blind. No, sorry. She's under the gun. She raises. How's them both three bets. It comes all the way around to me on the button. I look and I have pocket kings. Oh, I ship the whole cheeseburger. Comes back to Tilly. She ships house ships. Listen to these hands. Gently has aces. Jeff Hausen, both have kings. I have kings. Oh my God.
所以,快点告诉我。我们要参加Poker Go上的高额赌注扑克游戏。参与的有我、埃尔穆斯·斯坦利、萨米、豪斯、还有Gently和Nick Airball以及Roble。几乎所有房子里的玩家都来了,再加上Gently和Nick Airball。Jennifer Tilly简直太棒了。为什么不来呢?听听这一手牌吧。真的是比赛的第二手牌。Gently在大盲位,不,抱歉,她在早位。她加注,豪斯三次下注,这轮一直到我在按钮位置,我看了一眼,我有一对口袋K。我全押了。到了Tilly,她也全押,豪斯全押。来听听这些牌,Gently的是一对A,Jeff Hausen和我都是一对K。哦天哪。

I've never seen a cooler hand like this in my life. Out and the second in the second hand of the game. Anyways, wow. Don't worry, guys. It's too back. And I want to tell you. She tripled up. She triples up and then interlock them. The first time I ever played with her, I was going to stop this game. Then I stacked her right. Anyway, so I don't want to reveal the game, but it was wonderful. It was wonderful. This one. I show up at a mutual friend of ours game and there's a beautiful Porsche or something in the driveway. It's a really notable car. And the I noticed on the license plate, it says DJEN. But it's spelled with a J and I'm like, oh, degenerate. What a great license. I don't wonder who that is. I go and it's Jennifer telling. She is so cool. She's very charming. She's very cool. Great actress. Great actress. Great actress. She was in Bow. Bow.
我这辈子从没见过这么酷的牌。游戏刚开始的第二回合她就出了局。不过,哇,不用担心,伙计们。一切都能回到正轨。我告诉你,她翻倍了三次,然后把牌组合了起来。我第一次跟她玩的时候,本来打算不玩了,但后来我把她的牌给收了。无论如何,我不想透露是什么游戏,但那真的很精彩,真的很精彩。 有一次,我去参加一个我们共同朋友的游戏聚会,看到车道上停了一辆漂亮的保时捷之类的名车,车牌上写着“DJEN”,用的是J打头,我心想,噢,"degenerate"("堕落者",这词也可以形容爱赌博的人)。真是个好牌照,不知道是谁的。结果进去一看,是珍妮弗在那里。她太酷了,非常迷人,非常酷。她是个很棒的演员。她演过《Bow》(译者注:可能指的是某个作品的名字)。

That's what it was. Yeah. Me twice. Yeah, exactly. Towards the other. What a very gangster film. Yeah. With Gina Gertman. Gina Gertman. That's a little bit. Oh my God. That film. Oh my God. Well, let's not get canceled here. Okay. 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 Haley, but we got to go AI right now. Open AI. Large chat. GPT for oh. 4.0. Monday. Three days after Sam Wise came on all in as a programming note. And we'll go to freeberg about this. We probably made a bit of a surgical or tactical era in not postponing a apparent appearance in fairness. Freeberg Sam Wise did tell us originally he was coming on to talk about those things, but then it got pushed back and it will add to that as a programming note because people are wondering what happened.
那就是意思。对,对,我也是被邀请了两次。对,完全正确。向另一个方向。那么黑帮电影,真是够可以的。对,有吉娜·格特曼出演。吉娜·格特曼。真是让人惊讶。天啊,那部电影。天啊。好吧,我们不要被取消了。好吧,那真是部电影。说到动作。那可是个大事件。这周与AI相关的事情占据了我们的议程。对不起拜登,乌克兰,还有尼基·黑利,但现在我们得先谈AI。Open AI。大型聊天。GPT-4.0。星期一。山姆·怀斯在《All In》节目上出现后的三天。作为一个节目备注,我们得请弗里伯格来谈谈这事。我们可能在没有推迟他来访这件事上,犯了些策略错误。公平地说,山姆·怀斯最初告诉我们他会来谈这些事情,但后来被推迟了,我们会在节目备注里加上这一点,因为人们在好奇发生了什么。

I've been talking with Sam for a while a year about coming on the show and every time I see him I'm 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 works in a couple of weeks later. He's like, What about this date in May? And I'm like, Yeah, that's that's fine. We can make that work. He's like, Well, I've got a big announcement. We're going to be doing. And I was like, Perfect. Come on the show that 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 and I'm like, Well, is it chat? Is it GPT five? He's like, No, it's not GPT five.

And I was like, Okay, well, you know, come on the show anyway, because he didn't tell me when he's doing the announcement and when it's being pushed to 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 him. If they if they have to listen, don't be. 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 kind of hang out and talk.

I think I think if we had just gotten Sam on the day after the launch of GPT four on the, as opposed to what was it three days before, you could have talked much more freely about it. It would have been great. Yeah, it was supposed to happen same day. So it's unfortunate. This all worked out this way. Yeah, I think a little trick is to say you can tell us under embargo. But my understanding is they were still doing the videos over the weekend. So I think those videos and stuff, they were still figuring them out. And so yeah, lesson learned in terms of the interviews on the show.

Just a recap for people. We've done a dozen half of them have been presidential candidates. Sometimes they break out. Sometimes they don't. But 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. Yeah, we understand you miss a news subject, but yeah, it is what it is. 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. And so we're going to ask whatever we feel like asking. Sometimes those things will touch a chord because it's what you want it to have asked. And 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. And I think it's important to have that disclaimer. Like 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. So we are not journalists.

So 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 gotcha questions and things like that. I appeared at a conference a couple of days ago at remote glue, which we'll get to. And the first half of the conversation was like 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.
所以,我的理解是,如果嘉宾不愿意谈论某件事,我们不会强行用刁钻的问题逼迫对方回答。几天前我在Remote Glue的一个会议上发言,稍后会提到具体内容。开头部分的对话像是正常的谈话,主要讨论我们将要发布的内容。然后到了后半部分,记者开始不断抛出尖锐的问题给我,这毫无问题,因为我知道这是我需要面对的。这种风格和来我们的播客节目进行正常对话是完全不同的。但如果有人不愿意谈论某个话题,我们也没必要让他们勉强开口。

That was the fastest question, Sax. That was the fastball. Anything come close to your head? No, I mean, it's not worth really getting into. You can watch it. I was just curious. Look, I kind of like sometimes when reporters pitch me fastballs because, yeah, you can strike out or you can hit it out of the park when they do that.

That's an important part here. I think, you know, as a former editor and chief journalist myself, I sometimes like to ask, I would say a challenging question in a respectful way. I did that, for example, vague, you know, 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.

No, but that's because you asked it from a position of curiosity. You weren't trying to catch the guy. No, I'm actually interested in his opinion. No, this is my point. That's why it comes out differently. And that's why I think people enjoy these conversations. And sometimes we don't get to the other kind of answer because I'm not interested in trying to got you somebody that's working hard.

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, you know, everybody's got a different view on how to do interviews and feel like different if you like it, if you like Lex Friedman's version or Tim Ferriss's version or you prefer, you know, 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.
我在做采访时总有相同的条件,就是我不提前知道问题,也不让人编辑采访内容。但是,你知道,每个人对采访的方式都有不同的看法。如果你喜欢 Lex Friedman 或 Tim Ferriss 的风格,或者更喜欢看 Fox 或 CNN 的采访,那就去看他们的吧。在媒体环境中,有各种各样不同的采访和采访风格可供选择。我们只是其中一种。

Sam Weiss mentioned on the pilot last week that the next big model might not be called GPT five. So on Monday, they launched GPT four. Oh, the O stands for Omni. It's everything you love about tech. It's faster. It's cheaper and it's better.
萨姆·魏斯上周在试播节目中提到,下一个大型模型可能不会叫做 GPT-5。所以他们在周一发布了 GPT-4.O。这里的O代表全能(Omni)。它包含了你喜欢的所有科技特点:更快、更便宜、更好。

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 an omnivore. It takes in audio, text, images, even your desktop and video from your camera to inform what it's doing. You can consider it like 360 degree 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.

First, they made great progress in solving the CB problem we mentioned last week. That's where like we use Siri or any of these tools, you say, you know, hey, Jatchy P.T., 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.
首先,他们在解决我们上周提到的CB问题上取得了很大进展。就是说,比如我们使用Siri或其他类似工具时,你说“嘿,Jatchy P.T.,二加二等于多少”,然后需要等待。如果你和它同时说话,这个过程就会中断。现在,他们已经让这个过程变得更加顺畅了。他们还做了一个计数的示例,在那个示例中,他们说“加快速度,减慢速度”来调整。

They did a translator that worked really well. I would like you to function as a translator. I have a friend here who only speaks Italian and I only speak English. And every time you hear English, I want you to translate it to Italian. And if you hear Italian, I want you to translate it back to English. Is that good? Perfecto. Mike, you're my kid. Celebrate the letter. I want you to read it. Mike, she wonders if Wales could talk. What would they tell us?

They might ask, how do we solve linear equations? I would like to read the letter to you. I would like to read the letter to you. I think to lingo 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. And it does.
他们可能会问:我们如何解线性方程?我想把这封信读给你听。我觉得在那期间,Lingo Stock 公司遭受了打击。这对我来说,至少是非常令人印象深刻。此外,我在另一个播客上邀请了 Sandeep Madra,我们讨论了他们的桌面和 iOS 应用程序。这款应用程序非常有趣,它会监控你在 Mac 电脑、iPad 或 iPhone 上的桌面操作。

Things like adaptive learning. Here's a clip of Sal Khan from Khan Academy and his son basically using a drawing app to do some arithmetic or geometry. And it does adaptive learning and basically makes a personal coach because the app is watching his son try to solve a problem. I'm here with my son and I love you to tutor him on my website. I'm here with my son and I love you to tutor him on this math problem. But don't give him the answer. You can ask questions and nudge him in the right direction. But I really want to make sure he understands it himself. And he's here in the room so you can talk to him directly.
像自适应学习这样的东西。这里有一段影片,是来自可汗学院的Sal Khan和他的儿子,基本上他们在用一个绘图应用程序做一些算术或几何题。这个程序具有自适应学习功能,基本上可以成为个人教练,因为应用程序在观察他的儿子如何尝试解决问题。我在这里和我的儿子一起,我希望你在我的网站上辅导他。我在这里和我的儿子一起,我希望你可以辅导他解决这个数学问题。但不要直接告诉他答案。你可以提问并引导他走向正确的方向,但我真的想确保他自己理解问题的本质。他就在房间里,所以你可以直接和他说话。

Can you first identify which sides of the triangle are the opposite, adjacent, anti-pontinus relative to angle alpha? Alright, so I'm pretty sure this is the angle alpha right here, right? Ficked. Confirmed. Now looking at the triangle, which side do you think is the hypotenus? Um. Remember the hypotenus? I'm not totally sure. I think it might be this one, but I really am not sure. This side AC. Your close. Actually, side AC is called the adjacent side to the angle alpha. The hypotenus is the longest side of a right triangle and is directly opposite the right angle.

Can you find which one is the hypotenus? Oh, okay, I see. So, um, I think the hypotenus is this really long side from A to B. Would that be correct? Exactly. Well done. 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, you know, personality while you're using your apps. It's really impressive, I have to say. So I guess let's start Freeburg with your takeaways on all of these innovations that we saw.

I think it's become quite apparent that there's an evolution underway in model architecture. And 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 re-released. Towards a system of models. So this multimodal system 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.

So rather than have, you know, hey, there's this big new release that just happened, this new model just got trained cost $10 million to train it and 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. And so 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 in a more continuous fashion.

I think this is the first step of open AI taking that architectural approach with GPT 4.0 and 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 fine tuned. And so this seems to be pretty obvious. If you look at this link, one of the criticisms that initially came out when they released GPT 4.0 was that there was some performance degradation.
我认为这是开放AI在GPT 4.0中采用这种架构方法的第一步,幕后发生了什么我们并不清楚。我们不知道有多少模型,也不知道它们被改变的频率,是通过实际升级参数还是进行微调。所以这似乎是显而易见的。如果你看这个链接,当他们发布GPT 4.0时,最初出现的批评之一就是性能有所下降。

And Stanford actually runs this massive multitask language understanding assessment. And they publish it, I think, daily or pretty frequently on how all the models perform. And you can see the scorecard here that GPT 4.0 actually outperforms GPT 4. And so 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. And it seems actually the opposite is true that the model's gotten slightly better. It's still underperforms Cloud 3.0. Opus, which you can see here at ranked top of these charts. But there's lots of different charts. All the companies publish it on charts. They all claim that they're better than everyone else. But I like Stanford because it's independent. Trim up any thoughts after seeing it in combination with our interview.
斯坦福实际上运行着一个大规模的多任务语言理解评估系统。他们发布这个评估结果的频率很高,我记得是每天或者非常频繁地发布各个模型的表现。你可以在这里看到成绩单,GPT 4.0 其实比 GPT 4 表现得更好。这和一些说法相反,有些人认为为了提升性能和速度,GPT 4.0 其实变得更差了。但实际上,似乎情况相反,GPT 4.0 的表现稍有改善。尽管如此,它还是不如 Cloud 3.0 和排名表首位的 Opus 表现好。不过有很多不同的排行榜,各家公司都发布自己的榜单,声称自己最好。但我更喜欢斯坦福的评估,因为它是独立的。结合我们的访谈,你有什么看法吗?

Do you think chat GPT is running away with the consumer experience? Or do you think this is like neck and neck with some of the other players? Not to tell tales out of school, but somebody that we all know in our group chat hosted something about the fact that the consumer growth had stalled. I don't know how they knew that, that they maybe they got some data or maybe they're an investor. You guys know what I'm talking about. And they said that they're trying to reinvigorate growth into the consumer app into. I don't open AI. I mean, any insights as to why it might be plateauing in your perspective?
你认为 Chat GPT 在用户体验方面是否遥遥领先,还是和其他竞争者不相上下?不想在背后议论别人,但我们群聊中有个朋友提到用户增长停滞了。我不清楚他们是从哪里得来的消息,可能是通过数据或者他们是投资人。你们明白我在说什么。他们还提到 OpenAI 正在试图重振其消费应用的增长。对于你来说,为什么增长可能会趋于平稳,有什么见解吗?

I wrote this in my annual letter, but there are these phases of growth. And when you look at like social networks as a perfect example, Friendster was magical when it was first created. Right. And then you had my space that just ran circles around them because Friendster didn't really invest the money and the quality that it took to to create a moat. And then my space really wasn't able to compete. So we were, you know, 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.
我在年度信中写过这些内容:成长是分阶段的。以社交网络为例,当初 Friendster 刚推出时非常神奇。但随后 MySpace 迅速超越了他们,因为 Friendster 没有在资金和质量上做足够的投入来形成护城河。而后 MySpace 也无法继续竞争。这样一来,当我们 Facebook 出现在市场时,我们是第八或第九名,但我们最终超越了所有竞争对手。这表明,许多市场中的产品开发都有类似的阶段性。

This market, I think is going through the same thing. And right now we're in the first, what I would call primordial ooze phase, which is everybody's kind of like running around like a chicken with their heads cut off. There's all these core basic capabilities that are still so magical when you see them, but we all know that five and 10 years from now, these things will be table sticks. Right. And what Freeburg just showed is a table of many companies and many trillions of market cap all effectively running to the same destination. So I think where we are is probably within two years of where the basic building blocks are standardized. And then I think the real businesses get built.

So I will maintain my perspective here, which is the quote unquote Facebook of AI has yet to be created. Okay. And here it is. Chat, CPT web visits, as you can see, have plateaued. This data is similar web. I would agree with you, Jamaf. It seems like the use cases and the lucky lose who were just trying the software because they heard about it. They've gone away and then we have to find actual use cases. Sax, I'm wondering, but our friend Jason, just to kind of completely said something about the premium conversion. Right. That's what he said. I don't know how he knows that paid paid. Well, pay it.

So to be clear, paid versus free. And 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. And in my talk with Sonny this week, he 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. And these are now becoming about 90% cheaper every year, which means every two years these things would be 99% cheaper and better. Yep.

And it might be that opening eye sacks on a strategic level is going to make all this free or close to free and maybe just charge for multiplayer version. That seems to be where it's heading. You don't have to log into 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? Well, I think you're assuming there that the long term business model of open AI is in B to C subscriptions. And I think that's probably the least attractive business model they have available to them. It's sort of the first one and the most obvious one because they put out touch EPT and then it's pretty easy to roll out premium version.

But in my experience, B to C subscriptions, since I'm very attractive as a small because consumers disarmamentally 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 B to B direction over time because that's where the real money is. And probably the way they do that is by monetizing all the apps that are built on top of it. And 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 stands for Omni channel.
根据我的经验,B到C的订阅模式由于我是一个小企业,这点非常吸引人,因为消费者通常不愿意支付太多,并且他们的流失率很高,实际上也没有扩展的可能性。因此,我怀疑他们将会随着时间的推移转向B到B的方向,因为那里才是真正的利润来源。而且他们可能会通过将所有基于其构建的应用程序变现来实现这一点。我认为,在这个意义上,GPT 4.0是一个非常重要的创新。顺便说一句,O代表Omni,我认为这表示全渠道。

I think you may have some omnivore. Well, I think it's Omni, which means all the different media types 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 power, I believe. That's right. So there's three big innovations with the small. One is Omni channel, which means text, audio, video and images. Second, it's more conversational. Like it understands the tone of people talking and understands sort of 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 GLU. We can talk about that in a minute. And it feels 10 times as fast. It is much faster. But it's the combination of all three of these things that really makes some magical experience as possible because when you increase the speed, of processing, you can now actually have conversations within a much more natural way.
第三点,也是非常重要的一点,就是它比之前的版本——GPT-4 Turbo——快得多,性能更强。在速度测试中,据说它的速度是之前的两倍。我们在GLU也试用了它,可以稍后再谈。用起来感觉速度快了10倍,确实快了很多。但真正神奇的体验源于这三点的综合,因为当处理速度提高后,你就可以进行更加自然的对话。

Before the models were just too slow, so they'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. They've just basically invented the whole natural language real-time universal translator. So anyway, those are some interesting use cases. But I just think they're going to be able to unleash a whole lot of new applications. And if they're metering the usage of the models and providing the best dev tools, I think there is a business model there. And the next thing is moving so fast there in Leonardo DiCaprio mode. Every two years they throw the old model away.

Okay, let's keep saying sex. But I'm being. Hey, is this thing on? Did you write that ahead of time or? I was in the moment. That was good. Just one point on that is there are a whole bunch of startups out there that work creating virtual customer support agents. And 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. And 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 obsolete.
好的,让我们继续说性。呃,我是说。嘿,这东西在运作吗?你是提前写好的吗还是?我是在当下即兴的。那很好。只是要指出一点,现在有大量初创公司在致力于创建虚拟客户支持代理。过去几年里,他们一直在努力使这些代理更具对话性、更快捷、更响应。我认为他们的产品路线图已经过时了。不过,这并不意味着他们在工作流程方面没有更多的工作要做,比如将 AI 与客户支持工具集成,并为客户支持的特定问题量身定制模型。但我猜,数亿美元的研发费用就这样打水漂了。而且现在可能正是创建客户支持代理公司的最佳时机。如果你是在两年前、五年前做这件事,现在你的工作已经过时了。

Well, I mean, that is the thing with this pace. 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. 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 wrong, you'll end up doing a bunch of stuff that the model will just obsolete. 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 five and ten years to improve it?

You're much better off like Klarna, for example. 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 404 to 404 to Claude to Lama, it's going to be near impossible and it's going to be costly. I also think, Zach, the incentive to just push towards open source in this market, if you will, is so much more meaningful than any other market. Listen, you were there. I think you were there. Facebook, when they did the Open Compute project, and they just were like, Oh my gosh. Talk about torching an entire market. Explain what it is. There was this moment where when you were trying to build data centers, you'd have these one-year rack-mounted machines that you used.
你会赶上一大截,比如Klarna。我们谈到了Klarna通过改善客户支持而取得的惊人进步和节省。把它开源吧,伙计们。让其他社区成员接手,这样大家都能用上。否则你会被自己支持的系统困住。如果你以后想更换模型,比如从GPT 404到Claude再到Lama,几乎是不可能的,而且成本高昂。我还认为,Zach,在这个市场上推动开源的动机会比其他市场意义更大。你知道的,Facebook做开放计算项目的时候,真的搞砸了整个市场。解释一下这是什么情况。曾经有一段时间,当你试图建立数据中心时,你会使用这些一年一换的一体机。

What Facebook observed was there was only a handful of companies that provided it. It was unnecessarily expensive. Facebook just designed their own and then released the specs online. 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 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.

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 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. Nice. And when I were doing some very, I make our mini to wet my beak on this one. We want you to wet your beak. I feel like a hundred bagger to me. I'm in. It's a Slack killer. That's the way we're thinking about it. Killer S because, Jake, can you do that again in Chris for a walk in voice, please? I get to wet my beak. It was like a hundred X slide in 500. Wow.
是啊,我刚刚在屏幕上展示了这一点。Sacks,你昨晚其实一直在这一行上跳舞。我在用你的新Slack替代品,或者我也不确定。不过对我来说感觉它就是个Slack杀手,因为这个周末我就要把我的公司迁移过去。我们要换成Glue。不错。当我在做一些事情时,我也想从中沾点好处。我们也希望你能从中受益。这对我来说就像是个百倍回报。我参与了。这就是个Slack杀手,我们也是这么想的。Jake,你能用Christopher Walken的声音再来一遍吗?我能从中沾点好处。这就像是百倍回报,500倍的幻灯片。哇。

Sacks, tell me about product decisions. Where does the AI end? And your product begin. Yeah. Well, it's a good point. I mean, I think where the AI ends, we want to use the most powerful AI models possible. And we want to focus on enterprise chat. So you could think of us as for sure, a Slack killer or Slack competitor. This is that Slack wasn't built for the AI era. Glue is AI native. What does that mean? No channels. You know, I showed this to Jonathan. First thing he said is you had me in no channels, right? 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 chat GPT, it's just threads, right? You create a topic based thread in chat GPT. 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. It's just multiplayer. 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 have been involved in. 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.
所以,如果你看一下 ChatGPT 内部的聊天模型,它其实就是线程,对吧?你在 ChatGPT 中创建一个以主题为基础的线程。AI 会给它起一个名字,并将其放在侧边栏中。如果你想讨论其他话题,你就创建一个新的聊天。这正是 Glue 的工作方式,只是它是多人参与的。你只需要将你想要的群组和个人加入到线程中。让我快速示范一下。这是我的 Glue,你可以看到在侧边栏上,有我参与的所有线程。就像我说的,你可以将它们发给多个个人或群组,然后你就可以在这里聊天了。现在我们也已经完全整合了 AI。

And so Nick, who's our producer, just in this thread, said, at glue AI, what countries to SACs talk about most in episodes. Episodes is a group we created to be the repository of all of the transcripts of our episodes. And so, glue did a search and it said, David SACs frequently discusses Ukraine the most. What? So then Nick said, be more specific about SACs stance on Ukraine, Russia, war. Oh boy. And basically. It's going to overload the server. Well, here it said here, David SACs has articulated a nuanced and critical perspective on the Ukraine, Russia, war across various episodes. The all in pod.
因此,Nick,我们的制片人,在这个对话中提到,在Glue AI上,哪些国家是SACs在节目中最多谈论的。Episodes是我们创建的一个组,用来存放我们所有节目的转录文本。于是,Glue进行了搜索,结果显示David SACs最常谈论的是乌克兰。什么?然后Nick说,能具体说一下SACs对乌克兰和俄罗斯战争的立场吗?天哪。这基本上要让服务器超载了。这里的结果是,David SACs在各种节目中,对乌克兰和俄罗斯战争表达了一个细致而批判的观点。这是在All In Pod中。

Here's some key points encapsulating his stance. And it like nailed it. It's talked about prevention through diplomacy, opposition to the expansion, humanitarian concerns, skepticism, military intervention, peace, still proposal. You know, I'll copy and paste this onto Twitter, X later today. But the point is it like nailed it across all these different episodes. And then this is a feature of glue. It provided sources. So it cites where it got all the information from. So imagine, you know, 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 me who the expert is on this subject matter or who's contributed to the most of this project. I've actually figured out using glue AI who's contributed the most deal flow at craft is pretty amazing. Now, let me show you like. What's the answer? What? What's the answer? I'm not going to say here. I make it's Brian. Brian's my guy. Those two. Brian's my guy. I want to know if I got to go Daniel and Brian. Boom. I want to go. That's how I get sacks on them. Okay. You take Daniel all higher, Brian. I don't think I'll do a substitute craft. We'll call it a raft.
现在你的主聊天里可以直接问:“Hey, Glue AI,提醒我我们这个项目进展到哪儿了”或者“告诉我这个主题的专家是谁”、“谁对这个项目的贡献最大”等等。我实际上已经用Glue AI弄清楚了谁在Craft里贡献了最多的项目流量,这真是太神奇了。现在,我给你展示一下答案。答案是什么?答案是什么?我在这里不说。我会说,是Brian。Brian是我的人,就是他了。如果我得找Daniel和Brian,那就是他。我想去找,我就是这么锁定目标的。好,你把Daniel提拔,我会把Brian放在更高的位置。我不认为我会用替代Craft,我们叫它Raft。 这样翻译应该更容易读懂。

Let me show you a couple of seconds. Sax, I just looked at the chat JPT for Omni server. And when you did that query, it actually rolled its eyes. Keep going. OK. Hey, so so we talked about how chat to be T40 understand sentiment in conversations. And I think this is a really good example. So Evan, who's my co-founder, Glue was just testing this for us. And he asked, what is each besties personality type based on conversations and episodes? And first of all, it figured out who the besties are. Like we didn't program that. It just figured it out on its own, which is pretty impressive.

And here's what I said about each besties personality. So it says Jason Cowcanis roll the moderator and entertainer personality trace, charismatic, humorous, lively, and the glue of the group. Same. And praise often praised for his ability to make the podcast entertaining and keep the conversation flowing. Jason's energy and ability to bring humor and discussions or keelness that defines role in the podcast comments. He's acknowledged for his role, bringing the group together. Shema, Polly, Hapatia, the visionary and hustler personality traits and insightful, driven, persistent, shema relentless drive and ability to hustle her and my or my peers, making the corporate podcast and lecture discussions.
这就是我对每个朋友性格的评价。比如说,杰森·考柯尼斯担任主持人兼娱乐者的角色,性格特点是有魅力、幽默、生动,是团队的粘合剂。他常常因为能够让播客变得有趣并让讨论顺利进行而受到赞赏。杰森的精力和幽默感让讨论充满活力,这是他在播客中的重要作用。他也因能把团队凝聚在一起而得到认可。 雪玛·波莉·哈帕提亚是一个有远见且能干的人,性格特点是洞察力强、驱动力强、坚持不懈。雪玛不懈的努力和推动能力不仅激励着她自己,也激励着我的同行们,使得我们的企业播客和讲座讨论更加精彩。

I'll skip me, but does freeberg the pragmatic scientists and realists pragmatic and methodical and a bit reserved. Oh, freebers. Often the voice of reason bringing a scientific and realistic perspective that discussion he focuses on analysis, logical reasoning. And then it cites where it got this from. And it says here 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? Have you, uh, have you put any rails on or is this just pure? Chats EPT 40. Comparing with the data. Yeah. Yeah. So what we're doing here is we're wrapping Chats EPT 40 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. And then we're using a retrieve augmented generation service called Ragi, which does RAG as a service that basically slurps in our transcripts and makes them accessible to the AI.
这个有多“觉醒”(woke)?你有没有加上任何限制,还是完全自由的?这是 Chats EPT 40 和数据进行对比的结果。对,我们在这里做的是给 Chats EPT 40 加上我们实现的蓝色功能,以便最大化对话效果。我们需要做一些事情来限定提示的范围。然后我们使用了一种叫做 Ragi 的检索增强生成服务。这种服务基本上会吸收我们的对话记录,并使其对 AI 可用。

So that's basically the stack that we're using. But as the models get better and better, glue just gets better and better again. Can I just make a comment on this? It's just so clean. J Cal 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 like two or three channels. Yeah. The random channel, your Slack instance wasn't allowed to have. And I was like, this is genius.
所以,这基本上就是我们在使用的技术栈。但随着模型的不断改进,Glue 也在不断变得更好。我能发表个意见吗?它真的非常简洁。J Cal 是让我放弃 Slack 的关键人物。两三年前,他给我打电话,他告诉我可以具体地删除哪些频道。我取消了一些随机频道,有两三个吧。是的,随机频道在你的 Slack 实例中是不允许存在的。我当时觉得,这真是天才之举。

And I went in and I was like, all of our companies should just eliminate these channels. And we could only get like 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. And I thought, why aren't people working? And this is really great because you cannot blather on about nonsense include, which I find really useful. Well, this is what happens when Slack, we use it at 80 90, just so you know, so we were the when we got into the early get into Slack too much.
我进去后说,我们所有的公司都应该取消这些频道。但是我们只能得到大概 20% 或 30% 的配合,这让我对 Slack 这种工具开始反感。因为我经常被困在一些毫无意义的讨论中,我就在想,人们为什么不去工作呢?这真的很棒,因为这样你就不能胡说八道了,我觉得很有用。这就是我们在使用 Slack 时的经历,我们大约有 80% 到 90% 的时间在用它,以至于我们一开始都陷进去了。

People start to think Slack is the job and replying to Slack and having conversations is the job when there's actually a job to be done. There's a job to be done. Yeah. And so it's important. And what I liked about this implementation facts 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 like our HubSpot or our cell CRM. I want our Zendes.

I want our LinkedIn jobs and our LinkedIn job applications. I want our notion. I want a 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 summoning Beetlejuice. So you summon your AI, but then you tell it what data set you want to go after. So you say, you know, at AI, let's talk about, I don't know, how do you manage your deal flow at craft? Do you use software like CRM software to manage deals?

Brian just do it on. Daniel, but we do it all in glue. So it's already right there, but you're right. So so the first thing that glue AI has access to is all of your chat history, which is amazing because you get like, you know, that we can look at all your attachments and we've got, I think six integrations at launch a little bit more. So yeah, like all of your enterprise data will be there. In the short term, you're right. You have to summon 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.
Brian 就直接做了。Daniel,但我们用的是Glue。所以它已经完全具备了,但是你说的没错。那么,Glue AI首先可以访问的就是你所有的聊天记录,这很棒,因为你知道,我们可以查看你所有的附件。我们在上线时有大约六个集成,稍微多一点。所以,是的,你所有的企业数据都会在那里的。短期来看,你说的没错,你需要通过在应用中提到来调用存储库,因为AI需要一些指引来知道去哪里查找,但未来它会自己弄清楚的。

So it's just going to become more and more seamless, but 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. Well, that's where I want to go with it is I call that promptly, which is I want the AI just to chime in when 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 five, but that's totally where this headed.
所以,这个过程将变得越来越无缝,但是它会介入进来。比如,我们在讨论销售时,可能会有一个销售机器人提示说:“顺便提一下,已经三个月没有人联系这个客户了。” 这正是我想要的——我称之为“及时提醒”,即我希望AI在判断出有相关信息并能帮助团队时,即使没有被召唤,也能主动参与进来。但是,坦率地说,我们需要一些模型改进才能实现这一点。到GPT-5的时候,我们应该能够做到,但这确实是发展的方向。

I'll show you just one more fun example. If I could, let me just show you this. So 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, the All in Pod. We're excited to see the 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 like, what would be the best? Cause I told it, only say positive things. Don't say anything negative. Right.
让我给你再展示一个有趣的例子。如果可以的话,让我向你展示这个。我让它写一封信给莱娜·汗,邀请她作为嘉宾参加All in Summit。我告诉它,在信中提到我们在All in Pod节目中对莱娜·汗的正面评价。于是它写了这封信:“亲爱的汗主席,希望您一切安好。谨代表All in Pod的主持人们,邀请您在即将到来的All in Summit上演讲。”信中还提到:“在我们的对话中,我们经常强调您的出色资历和您所做的有影响力的工作。例如,在第36集节目中,我们认可了您开创性的角色。”这封信甚至引用了All in Pod的具体集数,而无需任何人去做研究、找出最合适的内容。因为我告诉它,只说正面的,不说负面的。对吧。

And 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. So it's pretty incredible. Now, this is just an example with the All in Pod. Or think about any work context where the AI has access to your previous work documents. It's pretty amazing what it can do. Well, I mean, it is kind of in the name. Like this is glue, put you together and slack is where you slack. Makes all sense. The brands give you a little bit of a tip. We should have seen it coming with slack. Totally. We have a breaking news story. It's a free news. It's a long way to lose it. I got breaking news coming in. Friedberg, your life's work sachs did his product review. Now it's your turn, Friedberg. We got breaking news coming in.
然后它在信尾写了“致以温暖的问候”,并写出了四个最好的朋友是谁。我们从未告诉它谁是最好的朋友,仅仅是让它写一封信。所以这真的很不可思议。这只是一个关于All in Pod的例子。再想想任何工作场景,如果AI能够访问你之前的工作文档,它能做的事情真的很惊人。我的意思是,这也符合它的名字。这像粘合剂一样把你们连接在一起,而Slack是你工作的地方。这些品牌名给了你一点提示。我们应该早就能从Slack的名字上看出来。完全正确。我们有一个突发新闻。这是一个免费新闻,我们还有很长的路要走。我刚收到突发新闻消息。Friedberg,这是你一生的心血,Sachs完成了他的产品评审。现在轮到你了,Friedberg。我们刚收到突发新闻。

I did promise you that when Ohalo decides to come out of stealth and explains what we've done and what we're doing. I would do it here on the All in Pod first before the all in exclusive. So basically by the time this pod airs, we're going to be announcing. What Ohalo 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 Ohalo and why it's important and the kind of significant implications for it. But basically five years ago, we had this theory that we could change how plants reproduce.
我确实承诺过,当Ohalo决定公开我们所做的工作和正在做的事情时,我会首先在“All in Pod”上公布,而不是先在其他地方独家披露。所以基本上,当这期节目播出时,我们将会宣布Ohalo在过去五年中开发并取得重大突破的成果,这是一项关于农业的新技术,我们称之为“增强育种”。我将花几分钟时间来谈谈我们在Ohalo发现或发明的东西,为什么它很重要,以及它带来的重大影响。基本上,五年前,我们有一个理论,认为我们可以改变植物的繁殖方式。

And in doing so, we would be able to allow plants to pass a hundred percent of their genes to their offspring rather than just half their genes to their offspring. And if we could do that, then all the genes from the mother and all the genes from the father would combine in the offspring rather than just half the genes from the mother and half the genes from the father. And 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, et cetera.

So 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. So 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. And then those two halves come together and they form the offspring. So every time a new child is born, every time a plant has offspring, you end up with different genetics.

And 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. 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 run 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. And 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.

So what we did is we came up with the 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. And as a result, the parent plants give a hundred percent of their DNA to their offspring. So the offspring have doubled the DNA of either parent. You get all the genes from the mother, all the genes from the father. And finally, after years of toiling away at trying to get this thing to work and all these experiments and all these approaches, we finally got it to work.

And we started collecting data on it and the data is ridiculous. Like the yield on some of these plants goes up by 50 to 100 percent or more. Just to give you a sense, like 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 percent yield gain per year. With our system, we are seeing 50 to 100 percent jump in the size of these plants. It's pretty incredible. Here's an example. This is a little weed that we that you do experiments with in agriculture called a rabbit doppes. So it's really easy to work with. And you can see that what we have at the top are those two parents, A and B. And then we applied our boosted technology to them and combined them.

And we ended up with that offspring called boosted AD. So you can see that plant on the right is much bigger. It's got bigger leaves. It's healthier looking, et cetera. If you were to ask your question, does that mean that the boosted one has twice number of chromosomes as A and B? Exactly. Right. So is that like a new species then? Yeah. So it's called. How does it survive with twice number of chromosomes? Yeah, it's called polyploidy. So we actually see this happen from time to time in nature. For example, humans have two sets of chromosomes, right? So does corn. So to many other species. Somewhere along the evolutionary history, wheat. Doubled and then doubled again. And you end up actually in wheat having six sets of chromosomes.

Wheat is what's called a hexapploid. Potatoes are a tetraploid. They have four sets of chromosomes and strawberries are an octoply. They have eight and some plants have as many as 24 sets of chromosomes. So certain plant species have this really weird thing that might happen from time to time and evolution where they doubled their, their DNA naturally. And so what we've effectively done is just kind of. Applied a protein to make it happen and bring the correct two plants together when we make it happen. And so this is going to only happen for a plant, right? This can never happen with an animal. It wouldn't it wouldn't work in animals. It works in plants. OK. And one way you can think about plant genetics is all the genes are sort of like tools in a toolbox.

The more tools you give the plant, the more it is. It has available to it to survive in any given second to deal with drought or hot weather or cold weather, etc. And so 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, bigger leaves and bigger, you know, gross, 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. And, you know, corn and many other crops. And so seeing 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. That's the boosted potato. And as you can see, these were all planted on the same date. And the boosted potatoes, 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, CD had nine grams. So each parent had 33 and nine grams potato.
土豆是地球上第三大卡路里来源。所以,我们选择了两颗土豆,你可以在中间看到A, B和C, D。我们对它们分别应用了增强技术,并将它们组合在一起。结果得到了这个土豆,A, B, C, D。这就是增强版土豆。如你所见,这些土豆都是在同一天种植的,而增强版土豆比这里所有其他土豆都大,包括我们在最右边展示的市场常见品种,也就是通常在田里种植的那种。 现在,最重要的是,当你查看地面下的情况并收获土豆时,你会发现A, B土豆的重量只有33克,而C, D土豆的重量只有9克。也就是说,每个“父母”土豆的重量分别是33克和9克。

But the boosted offspring had 682 grams of potato. The yield gain was insane. And so you could see this being obviously hugely beneficial for humanity. You know, potatoes being the third largest source of calories. Indian 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. And the potatoes, those are normal size potatoes that you see there. Those are like, you know, table potatoes. Basically, that looks like a russet potato right there. That's like a normal size.

But it started as like a little, it started as like a little creamer potato. Basically, and you blew it up into a russet potato. Yeah. So the genetics on A, B, you can see they're like little purple, tiny, little purple potatoes, the genetics on CD or like these little white, you know, 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 CD, 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.

So why not just grow russet potatoes then? We are. And so we're working on doing this with Russet. We're working on doing this with every major potato line. Sorry. Um, the, 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. Um, and so you'll see. You're a hacker or something like that. Like the work. Exactly. You know, projects in the 60s or 70s. Shmoist. Yeah. You can tell freebergs onto something here. You got David's sex to pay attention during it. Yeah. Yeah. This is the, it's gonna be a deck of cord and sacks is awake. So actually like, how do I wet my big glasses? Is that you interrogating the potato lines? I've never had. What's going on? I think it's an accident.

But so have you tried these potatoes? They taste different. Oh, no, they're awesome. Yeah. They're, they're potatoes. And we do a lot of analysis. You want to spread it any horn, Seattle or anything like that? No, no. You got it. 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 two 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 of 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 and the flower, every one of those seed is genetically different because of what I just showed on this chart, right? 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 a hundred billion dollar market. With our system, not only can we make potatoes higher yielding and make them disease resistant, what we also make is perfect seed. So farmers can now plant seed in the ground, which saves them about 20% of the revenue, takes out all the disease risk and makes things much more affordable and easier to manage for farmers.

So it creates entirely new seed industries. So 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. No, it's actually cheaper. So high yield lower costs. Do you need more water? Less water, less land, less energy. Do you need more fertilizer? 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 these stuff. And we're doing this across many crops. So there's a lot of work to do in terms of like, how do you scale and tell us a production in the field. Tell us about the patents and how important patents play a role in this, because isn't it like like one of Monsanto's big things, like they just go and sue everybody into the ground or whatever? Like, I'm going to answer you one second. I'm just going to switch my head to it. Just died. Wow.

We went from sacks as bots to freebergs crops. I'm glad we're doing him second because all of a sudden, like group chat doesn't seem very important. Yeah. Wow. He just, he just saw the whole Ukraine crisis here. I would be able to grow wheat in the desert and in the race, solve the world food problem. Yeah, Saks. What did you do for the last six months? Yeah, we made enterprise chat a little better, but we added AI to enterprise chat. We cleaned up your slack. So yeah, when you invest, we've invested a ton of money. This was stealth for five years. We put a ton of money into this business. So when you invest, like, um, I mean, north of 50 north, north of 50, yeah, 50 million five years and you don't have a product in market yet. Wow. That's a we actually have some product. Yeah.

So I haven't talked about the way we've been making money in some of the business. We've been doing. Okay. Let me just make sure this is like clear. So that last photo you showed with the different types of potatoes, you had created the super huge ones, but you're saying that the, 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 potatoes doesn't change. You can control for that when you breed. So 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, the design of which plants do you want to combine? Okay.

Cause your goal is not to turn like a russet potato into like a watermelon or something like that. No, 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. Like 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.

You mentioned something briefly there about where different crops can be planted. You know, we had these big talks about wheat and corn. They're only available in very specific parts. You know, north of the equator, the champion jungles, camping, obviously polar or desert extremes. So if you're successful, what would this do for on a global basis, where these crops are made? Because there are a whole discussion about you. Also, totally. Wheat belly of Europe, the cradle of wheat. 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 close to somewhere between 800 million and a billion people that are malnourished. That means they are living on less than 1200 calories a day for more than a year. But on average, we're producing 3500 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 sort of 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, but through the system, we can actually move significantly where things are grown and improve food access in regions of how free.

But when you look at a potato, how do you figure out what part of their DNA is the drought resistant part? Yeah. And then how do you make sure that that's turned on? So even if you inherit that chromosome, is there some potential interaction with the generally if we can. 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.
但是,当你观察一个土豆时,如何确定它的DNA中哪个部分是抗旱基因呢?是的,那你又如何确保这个基因被激活呢?即使你继承了那个染色体,是不是还会有一些潜在的相互作用呢? 一般来说,如果可以的话,这些被称为标记,基因标记。因此,有已知的标记与已知的表型(即植物的物理特征)相关联。我们已经为我们种植的每种作物找到了很多标记,比如抗病标记、抗旱标记、大型植物标记、矮小植物标记等等。

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 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 bring like why mutts are healthier and live longer than purebred dogs because they have more genetic diversity. So there's a lot of work now in what's called quantitative genomics, where you actually look at the statistics across all the genes, 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.

So how do you want to make money, Freeburg, are you going to sell the seeds? Are you going to become the direct farmer? Are you going to become food as a service? Like how do you make the most money from this? We're not going to farm. Farmers are our customers. And so 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. And then there's other industries like in potato where we're building our own business of making potato seed, for example. So every crop and every region is actually quite different. So it becomes a pretty complicated business to scale. We're in the earlier days. We're already revenue generating.

I would like a sweeter blueberry. No comment, no comment. Yeah. I get tilted by the quality of the Driscoll's blueberries. Let me tell you something about the Driscoll's blueberries. 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. Yeah. Now you want the European small ones or the Japanese ones from Hokkaido? Because they're rich and sweet and they're not these like monstrosity of giant flavorless strawberries. What's that about? A seedless? Could you do a seedless mango? Yes, no, cut it. She just cut it. Oh my God. How great would that be? Smooted out work for a bite on a mango is like the worst ratio. Yeah.

Well, somehow we made it about us. Yeah. No, no, look, I think that's it. It is all about you guys. Now tell us about the blueberries. Sorry. Well, not every year Driscoll's puts out a special labeled package called sweetest batch and they just had the sweetest batch of strawberry and blueberries. I don't know if they're still in the stores, but they only last for like a week or two. And that's the best genetics only grown on a small number of acres. What? Really? I'm going to go in as soon as this is the see if they have it. So I got it a few weeks ago. It's quite delicious.
好吧,我们不知怎么回事把话题转到了我们自己身上。嗯,对,不,不,听着,我认为就是这样。这完全是关于你们的。现在告诉我们关于蓝莓的事情。抱歉。每年Driscoll's(德瑞斯科尔公司)都会推出一个特别标签包装,叫做“最甜批次”(sweetest batch),他们刚刚推出了最甜批次的草莓和蓝莓。我不知道它们是否还在店里,但这种包装只会持续一两个星期。这些是最好的品种,只种在少量的土地上。什么?真的吗?一会儿我就去看看他们有没有。我几周前买到了,很美味。

Anyway, we know let's just say we know the Berry market very well. Mike co-founder, CTO, Judd Ward, who's who's brilliant idea of 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. And so we started the business with Judd and Judd ran molecular breeding at Driscoll. So we have a lot of Driscoll's people that work at O'Hollow. We know that the market really well.
总之,我们非常了解浆果市场。Mike 是我们的联合创始人兼首席技术官,Judd Ward 是多年前提出“增强育种”这一绝妙创意的人。我是通过看到《纽约客》上关于 Judd 的文章才认识他的。我给他打了一个冷call,请他来给我们做了一次技术分享。我们开始交流,Judd 提出了“增强育种”的这个想法。于是,我们和 Judd 一起创办了这家公司。Judd 之前在 Driscoll 负责分子育种,所以我们有很多曾在 Driscoll 工作过的人加入了 O'Hollow。我们非常了解这个市场。

Can you go back to the patent stuff like are you? Oh, yeah. Sorry. That was the question. Some seed person. So we spent we spent 50 million bucks on, you know, plus on this business today. So we have filed for IP protections 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 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. Cause farmers will keep buying that seed every year, provided it delivers the best genetics. And so our business model is really predicated on how do we build advantages and moats and then keep extending them rather than try to leverage IP. So I'm a big fan of like building business model advantages.

This is going to be a credible sax. If you'd think about, you know, 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 farm there, Friedberg, you would change humanity. And 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, like, no, I think, um, so first of all, like farmland in America is mostly family owned. That's 60% rented actually. So 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, wheat and rice.

Yeah. So those are calorie sources one and two. And there's certainly opportunity for us to apply our boosted systems there. The big breakthrough with potato is we can make potato seed using our boosted system in addition to making better potatoes. McDonald's is the largest buyer of potatoes. Yeah. So in the US, 60% of the potatoes go to French fries and potato chips. McDonald's buys most of the fries. PepsiCo under Frito lay buys most of the potato chip potatoes. 40% or table potatoes. In India, 95% of the potatoes are table potatoes. They're eating at home and the Indian potato markets three to four times as big as the US potato market in Brazil. It's 90% table potato. So all around the world, potatoes, different the US is, you know, unusually large consumers of French fries and potatoes.

I speak on behalf of Jay Kalan. I said, we will gladly invest a million out of 10 cap in both of your businesses. Absolutely. Yes. We will point our way into a cow. Jay Kalan. I will do the deal or wire the money. A little million to each of you guys at a 10 cap. Thank you. Absolutely. You're in. It may not be a 10 cap though, but yes. You're in. And Jay Kalan has secured the bag. It's a ranking news. I'm out to Jay Kalan 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. I'm excited to share it. You're in the both of you. I love it. It's been a, 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. We're doing the things we do best. Freiberg is solving the world's hunger problem and I'm making, I'm cleaning up your slack. Yeah. I'm making your enterprise chat a little better. Or progress couch.
我代表Jay Kalan发言。我说过,我们很乐意在你们两家企业中,每家投资一百万,占总资本的10%。绝对没问题。我们会一步步走向成功,Jay Kalan。我会完成交易或汇款。每家给你们一百万,占总资本的10%。谢谢。完全没问题。你们加入进来了。虽然可能不是10%的份额,但你们确实加入了。Jay Kalan已经搞定了。这是一个重要消息,我特意出来宣布,因为Jay Kalan完全搞定了,都是因为最好的伙伴们一起努力。是的,我很感谢你们让我分享这个消息。祝贺你们。我很激动,很高兴分享这个成果。你们两家都加入进来了。我很爱这个项目。这一路走来不容易,建造东西总是充满风险,需要很多工作和承受很多挫折。但当你让事情顺利推进时,那感觉太棒了。我们在做我们最擅长的事。Freiberg在解决全球饥饿问题,而我在整理你的Slack,让你的企业聊天环境更好。或者说在优化你的工作流程。

All right. Stanley Druckenmiller has got a new boyfriend. Druckenmiller's got a boyfriend and his name is Javier. And they've a low to Argentina. Druckenmiller 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 an Argentina of all places. He cut social security at 35% if he came to office. They've gone from a primary deficit of like four or 5% to a 3% surplus. They've taken a massive hit in GDP, basically a depression four quarter and his approval rating has not gone down. Druckenmiller has explained how he invested in Argentina after seeing Malay's speech at Davos, which we covered.

Here's a 30 second clip. Play the clip. Nick, 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 perplexity and I said, give me the five most liquid ADRs in Argentina. It gave me enough of a description that I follow 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. Yeah, that's quite interesting. He, quick note, you hear Druckenmiller mention ADRs. For those of you who don't know it, 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 chamois and then he's going to figure it out later. Tell us your thoughts on this love affair, this bromance. There's a great clip of Malay. 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? The full on French kissing each other. It's hilarious. Yeah, I mean, like Soros 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 much of a reaction to that.

I think that the thing with Argentina that's worth taking away is when you've spent decades investing 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. And so the thing we need to take away is if we don't get our sh** together, that's probably what we're going to have to do. Saks, the influence of Malay 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? Probably not. I mean, not until we're forced to.
我认为,阿根廷的经验值得借鉴。当你花了几十年的时间错误投资和分配资本,并将经济搞砸时,解决方法其实很简单:削减福利,重振经济。所以,我们需要明白的是,如果我们不尽快振作起来,可能也会陷入同样的境地。 至于马来西亚对美国政治的影响,会有吗?看起来他在做的事情和埃隆在推特以及扎克伯格在脸书的做法是类似的。你认为他在那里削减工作人员和部门的做法会传到美国政治中来吗? 可能不会,除非我们被逼到那个地步。

What Malay 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 does practically overnight. He just slashes government 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 and inflation goes away and people start investing in the country. Magic. It's 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 you're spending exceeds your income, eventually you got to pay it back or you go broke. And the only reason we haven't gotten broke or experienced hyperinflation is because we're the world's reserve currency. So there's just a lot of room for debasement. And there's not already 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 5 and a half percent. 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? 7 and a half percent now? Yeah, 6%, 7%, depending on how much net worth and your credit rating. 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 rates can be higher. The inflation rate actually doesn't take into account any of those things.

Remember, Larry Summers did that study where he said that 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. So people are hit really hard when interest rates go up in terms of big purchases they need to make with debt. And 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. Yeah. And so eventually the pace of innovation will go down. And Druckenmiller 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. So interventions 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 Druckenmiller's view of binomics and actually, I mean, this is what I said way back in 2021. Victory lap. Here we go. Well, Dave's Sacks Victory lap. We need a little graphic for that. Druckenmiller used the word binomics 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 referring economy.
我完全赞同德鲁肯米勒对“拜登经济学”的看法,实际上,我在2021年早就这么说过了。可以说是胜利时刻到了。这里是戴夫·萨克斯的胜利时刻。我们需要一个小图标来庆祝这个时刻。德鲁肯米勒用了“拜登经济学”这个词, 并表示给这些人打个不及格,因为即使我们处于复苏中的经济,他们还在像处于经济萧条时一样印钞和花钱。


And when they started doing this back in 2021, you know, I tweeted it, by an omics equals pumping trillions of dollars of stimulus into a reporting 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. Yeah. You don't do deficit spending when the economy is already doing well. So this spending, there's no reason for it. Yeah.


It's like showing up to like a party that's going crazy and being like putting gasoline on the fire. And 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 is now the time, of course not, to do student loan forgiveness, or do we wait for inflation to temper a bit is now the time. You know, so there's just a lot of these examples that it actually, the opposite should be true. But none of all of those things get you votes.


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


Let me just make one comment, Jake, how before we move on about the Drucken Miller investment statement? Of course. And I just wanted to say like, I think what it highlights about Drucken Miller and call it a rift in investing philosophy or a 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.
杰克,在我们继续讨论前,我先发表一个关于德鲁肯米勒投资声明的评论,可以吗?当然可以。我想说的是,这其实突显了德鲁肯米勒在投资哲学或技能上的一个分歧,那就是精准与准确之间的区别。 我的意思是,精准指的是你做了大量详细的分析,确保你了解每一个具体的细节,包括什么是做对的,什么有可能出错。这意味着,你可能会对一家公司进行大量的尽职调查,确保你理解每一美元、每一个利润点,以及公司发展周期中的所有具体细节。但问题是,你可以非常精准,但却非常不准确。


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 and consumers were simply that's not possible in the analysis, but they were doing it. Let's be honest, Freeburg, nobody could make that stupid of a trade to say Macy's versus Amazon over the next 10 years. Oh, yeah. And so like, and then, and Jacob. Do you want to show that? No, no, no, no. Do not hope the tiger. Let's not get into it. The other five guys. The worst spread trade in history. Yeah, let me just finish the statement.

No, but the other one is being accurate and accurate means you get the, yeah, the right bet, the right sentence, 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 a guy like Druckenmiller 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.

And to build on your thoughts, having watched this movie a couple of times, and I overthought the Twitter investment as about one example, I had the opportunity to invest in Twitter when it was like a single digit millions company. And I just thought, you know what, this thing is only like the headline. And I told that like it's the headline. It's not like the entire blog post, Nick, a co-opany of idiots, this thing is going to be chaos. And I was right, but I was wrong, right? 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, right? Which is Evan Williams, great entrepreneur, Jack great entrepreneur, Twitter taking off like a weed, just make the bet. Right? And I think as you knew too much about journalism, you knew too much about the space they were trying to disrupt and that can be a mistake. Correct.
让我来补充一下你的想法,之前看过几次这部电影,我也曾经对投资推特这件事情想得太多。我当时有机会投资推特,当时这个公司市值只有几百万美元。我当时认为这东西只是个头条新闻而已,不算是整个博客文章的重要内容。我还说过,像联合体一样愚蠢,这东西会变成一团糟。事实证明我对了一部分,但也错了一部分。可以说这是一个很好的赌注,但我对它的分析是错的。 因此,你可以在卖出股票或加码投资等其他方面更加精准,但必须掌握大趋势,即:埃文·威廉姆斯是个很棒的企业家,杰克也是,推特如野草般迅速崛起,只需要下注就好。而如果你对新闻业的了解太多,对它们试图颠覆的领域了解太多,这反而可能成为一个错误。正确的。

We did PayPal, no, it's not anything about payments. That was one of the reasons we were successful. All the payments experts told us it couldn't be done. Right. So that happens a lot. I had never even know, I didn't even know what a Facebook was when I joined Facebook. It's an American college phenomenon. No serious? You don't have that. Yeah, Canada. But you knew Zach and you saw some growth charts and you saw some precision in his ability to build product and that's the way to go. The great thing about network effect business 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.
我们做过PayPal,不,不是和支付有关。这正是我们成功的原因之一。所有支付专家都告诉我们这是不可能的。对,这种情况经常发生。在加入Facebook之前,我甚至不知道Facebook是什么。这是美国大学里的一种现象。真的吗?你们加拿大没有这个。但你认识扎克(指Mark Zuckerberg),你看到了增长图表,也看到了他在产品开发方面的精确能力,这就是成功的方向。网络效应业务的伟大之处在于,它有一条可以持续的趋势线,因为如果网络效应适当,它会不断增长。所以你可以准确地选择合适的网络效应业务。只要趋势线正确,你愿意耐心持有投资,你就不需要通过所有这些尽职调查来完全确认营收和利润结构的成熟度。

I think Drucken Miller's point is incredible. He took a look. He very quickly made a macro assessment from a macro perspective. What Millay is doing is significantly different than what we're seeing in any other emerging market, let alone mature market with respect to fiscal austerity and appropriateness in this sort of inflationary global inflationary environment. And 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. And 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.

Well, speaking of bets, Jay-Kal, you told me this week that you just met your largest investment ever. Tell us about that. Yeah. So 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. So that happened with TK, Uber and the Cloud kitchens that happened with Raul from a report of then superhuman. And 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 he said, hey, you were the first investor in Thumbtack. Well, you'd be the first investor in our next company, Athena. And I said, sure, what do you do? And he explained it to me. And we put a seven figure bet in, which is rare for us as a seed fund, right? Normally our bet sizes are 100k, 250, it's a $50 million fund.
好的,说到赌注,Jay-Kal,你这周告诉我你刚刚完成了你有史以来最大的投资。能跟我们讲讲吗? 是的。我现在非常幸运,因为在我早期作为红杉资本侦察员进行投资的几个批次中的许多创始人,现在回来创建了第二、第三家公司。比如说,当时的TK、Uber和Cloud Kitchens,还有Raul,从A Report of到Superhuman。这些都发生过。 最近就在过去的一年,我的朋友乔纳森,他是Thumbtack的联合创始人,邀请我去吃晚饭。他说,嘿,你是Thumbtack的第一位投资者。你愿意成为我们下一家公司Athena的第一位投资者吗?我说,当然,能介绍一下你们在做什么吗?他向我解释了一下。于是我们进行了一笔七位数的投资,这对我们的种子基金来说很罕见。通常我们的投资规模是10万到25万美元,因为我们有一个5000万美元的基金。

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 Robinhood when we were investing in intensive millions of dollars. It's a very simple concept. When Thumbtack was building their marketplace, they used researchers in places like Manila, etc., in the Philippines knowledge workers. And what they realized was the point 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 AthenaWow.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 kind of 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 kind of chief of staffish and this company is growing like a weed. So I am working with them on the product design as well. So imagine having two or three of these incredibly hard working 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 kind of 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. You've hooked me up so I will be guinea picking the service. Yes. Soon. And I have two of them. And so it is just the greatest that you can have an operation. Are these people powered by AI tools as well? Yeah. So that's the kind of 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.

So we have an investment team with researchers and analysts in it. We have a due diligence team and then you have like executive functions in our fund. They have now started shadowing, you know, you know, highly paid Americans in an investment firm ours and then train them up. And now our due diligence, our first level screening, you know, 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. So 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.

And so you're 80, 90. So 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 tenth of the cost, we say, oh, you just 80, 90 did. Correct. So we're ending the investment team. I'm 80 and 90 and 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.

The way that companies will work in five and 10 years, I don't think guys, any of us are going to recognize what it's going to look like. No. Yeah. Like watching Saxa's 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 the eye. Totally. Totally. It's so obvious.

Can you imagine how long it would have taken John to write a letter to Lena Kahn to what like if we said John invite Lena Kahn, but be sure to reference all the nice things we said about her on episodes of the pod. I mean, 10 hours of work. You got to go find the episodes. Yeah, listen to them to figure out what the best quotes are. You got it done in five seconds. It's incredible. Totally. And this is building that same sort of capability into a very specific vertical application that's specific to some business function. And you can probably spend a couple minutes or an hour building that function. And then it saves you hours a day in perpetuity.

Yeah. And 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 write their entire business functions. I got myself and my co-founders at 8090. We get this stream of emails of companies that are like, or people that are like, we have this product idea or we have this small product. One of the emails I got, this is crazy, was from a guy that's like, oh, we've 8090 Photoshop. So like we have like a much, much cheaper version of Photoshop. And the guy was doing like a few million bucks of a VAR and growing really nicely. But then it turned out that somebody saw that and then 8090 did. So that there's a lot of that thing.

And so to your point, Fibri, none of these big company standard chance. Yeah. It's everything. It's not because they're not because the products aren't good, but like Jake, I was going to go off an experiment with this. Sax going to go off and build a product. You know, as 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. And the optics 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. And that's just going to create the ability for these companies to sell those products cheaper. So it's a massive deflationary tail.
翻译如下: “所以,Fibri,你说得对,这些大公司的标准机会是不存在的,对吧。这涵盖了一切。这不是因为他们的产品不好,而是像Jake那样,我本来打算尝试一下这个实验。Sax打算自己去开发一款产品。每当我们处于边界条件时,都会考虑,或许我们可以用AI来做这件事,也许我们不应该雇用人手,不是因为我们想要刻意苛刻,而是因为这是自然的选择。而公司的光环也会因此减弱,这意味着公司的规模会缩小,所需的资金量也会减少,这就使得这些公司能够以更低的价格出售产品。因此,这将带来巨大的通缩影响。”

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 subset 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? And 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? And that's 80, 90, something like 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.
我们之前在计算方面也遇到过同样的情况,现在这种情况发生在组织内部。我在我的博客上写了一篇关于这个问题的帖子,名为 ADD。这是我提出的一个框架。我告诉我的整个团队,每周回顾你们完成的工作,并且问自己三个问题:如何自动化这项工作?如何弃用这项工作?如何委托他人完成这项工作?其中,自动化部分指的是人工智能和你在做的事情,大卫;委托部分是指 AthenaWOW.com。至于弃用,就是要仔细思考,你在做的事情中哪些是不需要的?大约有80%到90%的产品功能实际上并不需要。产品的核心功能是什么?让它尽可能地实惠。

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, like there was somebody who was working on very small software. I want to get pitched on very niche ideas. I want to create something where people can find people to play pickleball with, right? 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? And now you've only got to clear that number to be profitable.

So a lot more small businesses, a lot more independent. All these little niche ideas will be able to be built. And a VC who says, I'm not giving you $5 million to build that app will be like, but I will give you $500k. 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.

Did you guys see the Google thing? Did you guys see the Google AI Gemini stuff? Chat GPT, Omni launched at the same time, or perhaps strategically right before Google dropped its latest AI announcements at IO. The biggest announcement is that they are going to change search. This is the piece of the puzzle on the kingdom that they have been very concerned with and they're going for it. The new product and they have like 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.
你们看到谷歌的那个东西了吗?你们看到谷歌的AI Gemini的那些东西了吗?Chat GPT和Omni几乎在同一时间发布,甚至可能是为了在谷歌发布最新的AI公告之前有意赶在前面。最重要的宣布是他们要改变搜索功能。这是他们一直非常关注的领域,现在他们要大干一场了。新的产品,其实他们有大约20种不同的产品,你可以在labs.google网站上看到所有这些产品。但最重要的就是这个,他们称之为AI概览。基本上来说,对大多数用户来说,这就是perplexity(注:一个语言模型)了,预期在今年年底他们就会推出这个功能。

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 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, you know, the issue of people getting upset. And as I predicted, they're going to have targeted ads. There's the things you need in order to clean your couch. You can only use this if you're using your Gmail account. If you use like a domain name on Google Docs, it won't work there. So go to labs.google, but they're doing citations.
以下是它的工作原理,您可以在屏幕上看到。如果您在 YouTube 上观看我们,您会看到一个示例:如何清洁布艺沙发?通常情况下,这会给您提供10个蓝色链接,而现在会给您逐步的指导,并附有引用和链接。他们提前解决了人们可能会不满的问题。正如我预测的那样,他们将会有针对性的广告。这些是您清洁沙发所需要的东西。您只能在使用 Gmail 帐户时使用此功能。如果您在 Google 文档中使用域名,这个功能将无法使用。所以请访问 labs.google,不过它们确实提供引用。

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 SAC a new company that clears this content. So that Google can do answers like this. 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 the effective. Well, wouldn't it be great if like, you know, the AI assistant were able to find all the receipts and then aggregated them and put them in a folder and then also actually generated an expense report or like a spreadsheet on the fly?

It's crazy. I got to say, I think that it's free to change your mind. And so it's good to do that. Oh, and I think that Chama and a rare moment of reflection might do a, are we going to have a re underwriting? Is this a re underwriting? I change my mind all the time. I just, I mean, you know, because I'm the gentleman breaking news. I think the Google thing is pretty special between last week's announcement of isomorphic labs, which let's be honest, that's a, that's just a multi-hundred billion dollar company. So you're saying there might be many.
这太疯狂了。我得说,我认为改变主意是免费的。所以改变主意是好的。哦,我觉得Chama可能会有一个难得的反思时刻,我们会重新承保吗?这是重新承保吗?我经常改变主意。只是,我的意思是,你知道的,因为我是那个揭露新闻的人。我认为谷歌的事情非常特别,上周宣布的等构实验室(Isomorphic Labs),老实说,这是一家价值数千亿的公司。所以你说可能会有很多。

Think about it this way, right? Multi-billion dollar opportunities sitting there dormant inside of Google that AI unlocks. Look at a company like Royalty Pharma. So if Royalty Pharma with a pretty, it's a phenomenal business run by a phenomenal entrepreneur, Pablo La Guretta. But what is that business? That's buying two and three percent royalties of drugs that work. And you can see how much value that those guys have created, which is essentially 90 percent, a bit margin business. It's outrageous because they're in the business of analyzing and then buying small slivers.
这样想一想,对吧?谷歌内部有数十亿美元的机会原本处于休眠状态,现在被人工智能激活了。看看像Royalty Pharma这样的公司。Royalty Pharma是一家由出色企业家Pablo La Guretta管理的优秀企业。那么这家公司的业务是什么呢?它是购买那些有效药物的2%到3%的版税。你可以看到,他们创造了多么大的价值,基本上是一个90%利润率的业务。这简直太不可思议了,因为他们的业务是先分析,然后购买这些小部分。

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. So if you, 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. So I think that the reports of their death were premature and exaggerated. Absolutely. And the report of their death, Freiburg, was based upon people don't need to click on the ads. But as I said on this very bogus, 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, right, for medium rare, it's going to anticipate your next three questions better.

And 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 chamois 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, Freiburg? You work there. And when we look at the, the, the future of the company and the stock price, Nick, we'll pull it up. Man. If you had held your stock, yeah, I don't know. Did you hold? I think I bought some, um, during the original stock during the war, okay. I said, Oh, no, I sold all my stock back when I started climate because I was a startup entrepreneur and needed to live. So which, you know, I, I, I did the math on it. It was pretty, it'd be worth, it'd be worth a lot. It would be worth billions or tens of billions. No, no, would it would have been a billion or no? No. Okay. You know, I was not like a soup. I was not a senior exact for anything. I think what you said is, is probably true.

So that's a creative. 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 bounce back 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. And 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. So a key metric is they're going to start to discover which vertical searches, meaning like a cooking recipes, that kind of stuff, like the reference, 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 than them jumping off to a third party page to get that same content.

And then they'll be able to monetize that content that they otherwise were not participating in the monetization of. So 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. And then I do think that the revenue per search query in some of those categories actually has the potential to go up, knocked out. Explain. Explain. Give me an example. You keep people on the page so you get more search volume there. You get more searches because of the examples you gave. And 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.

So for example, selling the steak knives is another is, you know, it's kind of a good example or booking the travel directly and so on. So 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. 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 trying 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.

And it's actually all missing. To my point, a lot of these call options like isomorphic labs. I can tell you meta and Amazon. What meta and Amazon do not have an isomorphics lab and Waymo sitting inside their business that suddenly pops to a couple hundred billion of market cap and Google does have a few of those. So other bets could actually pay off these are maybe I look, I mean, there's Calico. No one talks about Calico. I don't know what's going on over there. My extension. Yeah. Let me get sacks involved in discussion sacks. Then 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 steak. Those 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 didn't get your permission to do this, but we're doing it anyway. What do you think is the resolution here? Does all of 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 wire cutter or these other sources that are not behind a payroll and just give you the goddamn answer.

Well, like this is the same conversation we've had two or three times. We're going to need the courts to figure out what fair use is. And depending on what they come up with, it may be the case that Google has to cut them in by 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 puck 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. I had a call with him yesterday and you and I will be on that cap table together once again. Good night. Yeah.

So I don't want to say who it is because we can't 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 OG 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 kind of sucked. Then they started inching towards with one box, but it wasn't you didn't get the one box very often. It's very clear now that Gemini powered one box is the future of Google search. People just want the answer.

I think 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 be more searches because search gets more useful. There's fewer blue links to click on, but maybe they'll get, you know, compensated through those like relevant ads. Just say you're probably right that Google ultimately benefits here, but let's not pretend this was a deliberate strategy on their point. They got drag kicking and screaming into this by innovation and perplexing other companies. They had no idea. They got caught completely flat footed and they've now I guess caught up by copying perplexity and sex or perplexity.

I think they're kind of screwed now unless they get it's over an acquisition deal. But perplexity came up with the idea of having citations in your comprehensive search results. Yeah, which was something search results with citations and related questions. And they did it extremely well. And quite frankly, all Google had to do was copy them. Now they've done that. Yeah. I think it does look like a killer. 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 neighbor and down in Korea.

They were the first ones to do this. You know, a chamap, because there were only three or four markets where Google couldn't displace the number one. Korea, Russia, Japan, Russia had was a Russian search engine. God, I can't remember it now. Japan had Yahoo Japan, which Masayoshi San had carved out. It was never part of it. And they were loyal to that and very nationalistic Koreans and very innovative folks had down in neighbor just made search that was so amazing. You do a search and you'd be like, here's music, here's images, here's answers, here's Q&A. It was awesome.

But you know, it just shows you like 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 to humans not AI because AI didn't work 15 years ago. One thing I would say about big companies like 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. Remember and they like they screwed up the whole smartphone mobile phone era. And it didn't matter. Didn't matter. Satcha 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 you know, they had. Black George Washington. Black George Washington. 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 now. Sorry, $5 trillion company.

It reminds me, you know, the greatest product creation company in history. I think we all know who that was and take a look down memory lane. Here are the 20 biggest felt Apple products of all time. The police, Mac and Thomas 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.

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 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. He's blunders. But what makes us successful is that we learn from the failures and, you know, we make the right next decision.

Yeah. But I say, if you're a startup and you make big failures, you usually squat a business. One and done. Yeah. But this is how you say this, 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 just don't. I just, you can't just hide.

You have to do things that you're going to fail at. Right. Remember this boom. This is one of the huge different stream 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.
你必须去做那些你可能会失败的事情。对的,记住这一点。这是初创公司和大公司之间的一个巨大区别: 大公司可以拥有一系列的产品组合。他们有一系列的赌注,其中一些会成功,而这些成功的产品能够维持公司的运营。而初创公司则必须全力投入到他们最好的想法中。

Totally. I always tell founders, just go all in on your best idea. They're always asking me for permission to pivot. And I always tell them, do go for the best idea. Don't, don't hedge. Don't try to do five things at once. Just go all in on your best idea. Yeah. Yeah. And if it doesn't look at 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 guesses week. Just all bestie 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 learned a live Q&A with your besties coming at you in the next couple of weeks.
可以这么翻译: 可以这么说,又一集精彩的节目完成了。小伙子们心情都很好。你们得到了你们喜欢的精彩节目。这周没有嘉宾,全程都是好朋友的互动。还有非常重要的一点,“百万订阅”计划已经走到一半了。感谢粉丝们的支持,我们在YouTube上达到了50万订阅。这意味着在接下来的几周内,你们将会迎来一次和好朋友们的直播问答环节。

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. Who knows what could happen on a live show. And by the way, I just want to let you know that Phil Hellmuth breaking news. Phil Hellmuth and Dre Monghre and just resigned from open AI.
我们将在YouTube上直播。所以如果你不是前500名之一,赶快加入吧,这样你能收到提醒。我们会现场回答你的问题。这次会很刺激。有什么问题吗?没有问题?谁知道直播时会发生什么。顺便说一下,我还有个最新消息,Phil Hellmuth和Dre Monghre刚刚从OpenAI辞职了。

We didn't get into that, but the open AI resignations continue. Phil Hellmuth has tweeted. He's no longer with open AI. You guys like my baby cashmere pink sweater. That's pretty great. Are we going to get summer chamatsu? Now the buttons coming down. Are you going to go out and linen? The when is linen chamat show up? The unbuttoning is about to happen in the next two or three weeks.
我们没深入讨论那个话题,但开放 AI 的辞职潮还在继续。Phil Hellmuth 发推文说他已经不再和开放 AI 合作了。你们觉得我这件粉色的羊绒毛衣怎么样?挺不错的吧。我们会有夏季的Chamatsu吗?现在纽扣开始解开了。你接下来会穿亚麻布衣服吗?几周内就会看到我解开纽扣的造型了。

The great unbuttoning. The great unbuttoning. It's kind of like Groundhog Day. You know that summer's here. When almost your voice. Almost your most memorial day. When after Memorial Day, the button can come down. Yeah, we're going to go three buttons down. I'll still wear my black tea. Sax will still be blue blazer, blue shirt, red tie. And freeburg in fields of gold.

Look at freeburg in fields of gold. Taking us out, staying in fields of gold. Coming at you two for Tuesday. See all the next all the pod for the Sultan of Science. The rain man did socks and chairman dictator. I am the Z 100 morning zoo DJ. We'll see you next time. Love you, boys. Bye. Bye. Bye. Bye. We'll let your winners ride. Rain man, David. Sax. I'm going all the way. And it said we open source it to the fans. And they've just gone crazy with it.

Love you, guys. I'm the queen of Kinwah. I'm going all the way. What? What? I want to ride. I want to ride. I want to ride. Besties are gone. Go 30. That is my dog taking a nice, near driveway. Sax, wait it on. Oh, man. My husband, Jasher, we meet me at Wood and Sun. We should all just get a room and just have one big huge org because they're all just like this like sexual tension. But we just need to release it out there. What? You're the beat. What? You're the beat. You're the beat. What? We need to get merges.

I'm going all the way. I'm going all the way. And now the plugs be all in summit is taking place in Los Angeles on September 8th 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 slash at all in which search all in 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. So look for that as well.
我要全力以赴。我要全力以赴。现在,All In峰会将于9月8日至10日在洛杉矶举行。你可以在 summit.allinpodcast.co 申请门票。奖学金也即将开放。如果你想看这个播客的视频,可以去YouTube,搜索“all in podcast”,然后点击通知铃,这样我们每次发布内容时你都会收到更新。当我们的订阅用户达到一百万时,我们还将在拉斯维加斯举办一个派对,所以也期待一下吧。

You can follow us on x x.com slash the all in pod. Chiktok is all underscore in underscore talk Instagram, the all in pod and on LinkedIn just search for the all in podcast. You can follow chamat at x.com slash chamat and you can sign up for a sub stack at chamat.substack.com. I do free bird can be followed at x.com slash free bird and oh, hollow is hiring. Click on the careers page at oh, hollow genetics.com and you can follow sacks at x.com slash David sacks. Sacks recently spoke at the American moment conference and people are going crazy for it.
你可以在 x.com 上关注我们,网址是 xx.com/theallinpod。我们的 Chiktok 账号是 all_in_talk,Instagram 账号是 theallinpod,在 LinkedIn 上你只需搜索 the all in podcast 即可找到我们。你可以在 x.com/chamat 上关注 Chamat,并可在 chamat.substack.com 注册订阅。你可以在 x.com/freebird 上关注 Free Bird,另外 Oh Hollow 正在招聘,点击 ohhollowgenetics.com 的职业页面查看详情。你可以在 x.com/davidsacks 上关注 Sacks。最近,Sacks 在 American Moment 会议上发表了演讲,获得了广泛好评。

It's pinned to his tweet on his ex profile. I'm Jason Calicannis. I am x.com slash Jason. And if you want to see pictures of my bulldogs and the food I'm eating, go to Instagram.com slash Jason in the first name club. You can listen to my other podcast this week and startups to search for it on YouTube or your favorite podcast player. We are hiring 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, et cetera.
这段话翻译成中文,尽量易读: “这条推文被置顶在他的前社交平台账号上。我是 Jason Calicannis,我的账号是 x.com/Jason。如果你想看我的斗牛犬和我吃的食物照片,请访问 Instagram.com/Jason。在 YouTube 或你喜欢的播客播放器上,你可以找到我的另一个播客,名叫‘本周创业’。我们正在招聘一名研究员。如果你对从事初级研究、与我和制作人 Nick 一起工作、处理数据和科学研究、金融等感兴趣,可以申请这个职位。”

All in podcast.co slash research. It's a full time job. I'm working with us the besties and really excited about my investment in Athena. Go to Athena. Wow. See you in a while dot com and get yourself a bit of a discount from your boy, Jake Al. You know, while dot com. We'll see you all next time on the all in podcast.
在 podcast.co 斜杠 research 上的全职工作。我和我们的团队 Besties 一起工作,对我在 Athena 的投资感到非常兴奋。前往 Athena 哇哦,看一下 while dot com,从你的小伙伴 Jake Al 那里获得一些折扣。再见 while dot com。我们下次在 All In 播客上见。