SPEAKER_00: We had a really thoughtful argument about, can you trust Facebook or not? You put this as infrastructure, and that is why you would lean towards, hey, you can trust Facebook on this. They've got a good track record. I think I would say as a business partner, no, I don't believe you can trust Facebook. I'd be very cautious if you're a startup of ever talking to that company.

SPEAKER_06: Like an Instagram API, I don't know.

SPEAKER_09: They may take it away from you. Never trust them on APIs, but on infrastructure, they do have a track record.

SPEAKER_00: So to be totally fair, I like to call balls and strikes. Do not, you will strike out with them as a partner, as a business partner. They will slit your throat.

SPEAKER_11: I know because my friends woke up and they're like, hey, J-Cal, you remember you told me

SPEAKER_14: I went to bed with Zuckerberg, I wake up and my throat slit? I'm like, yeah. They're like, I'm in a bed covered in my own blood.

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SPEAKER_19: All right, everybody. Welcome back to This Week in Startups. With me again, my guy, Sonny Madra. It's so great we get to spend this time together every week talking about our jobs and just how fast AI is moving.

SPEAKER_00: This has been a really significant start of the year because here we are. We're in the first half of the year. And so many big sea changes. And of course, Facebook coming out of last place, as we described in the last episode, and now in the top two or three language models, depending on who you believe, is a series of events we did not predict. We did predict, both of us, that open source would win the day.

SPEAKER_22: But I don't think either of us predicted that Facebook would be the one to do it or to do it at this pace.

SPEAKER_24: I will say when they came out with Lama 3 on Thursday, its capabilities, and we're just, you know, we're just three days in, right? It's Monday now. Its capabilities are blowing people's minds. Okay. The way to really think about what they've been able to do, which I think has everybody shook, and I mean shook it in like the best way possible, is that they showed that they were able to build a model that is much smaller and in being much smaller, they were able to, hold on, I'm going to open this up real quick here. This chart right here is really amazing. And so we didn't get to talk about this in the last episode. So I'm going to go bottoms up. What this shows here is Lama 3, 8 billion, the smaller one that they released, is better than the original GPT-4. Okay. Think about that.

SPEAKER_33: Okay.

SPEAKER_07: So GPT-4, everybody lost their mind. Yes.

SPEAKER_00: And thought, hey, that killed a thousand startups, yada, yada. Yeah. There was a lot of brouhaha.

SPEAKER_11: But their light version, in other words, their little eight ounce mini can, mini bottle that you get at a fancy, you know, hotel lobby, you know, them talking about the little

SPEAKER_42: Coke bottles they give you, they pour like the little eight ounce bottle, it looks very dramatic.

David Friedberg: Their mini Coke is better than the two liter bottle that OpenAI is.

SPEAKER_45: And so that is truly significant and what that means. And it's also free. Yes.

David Friedberg: So free and unencumbered. What does that mean practically for businesses when a free and unencumbered

SPEAKER_00: open source model is being decided on nice and light, or you're deciding on chat GPT-4?

SPEAKER_08: These are the following considerations that happen because of it.

SPEAKER_24: One, for your enterprise, you can run this model at scale with a relatively small footprint of hardware. In order to run GPT-4, you need like a significant footprint of hardware to run it. And it's not open source.

SPEAKER_49: So there's no getting in there. One, you can't exactly, two. So I think that's one. Two, because it's open source, to your point, you can have it run within your firewall.

SPEAKER_24: Yes. And so you can be sure it has the same capabilities that we were all raving about, but you have it for yourself privately.

Chamath Palihapitiya: What does one lose by going open source versus going with a commercial product?

SPEAKER_00: In other words, if some giant corporation, GE, General Electric, is meeting with OpenAI and their internal team or a consulting firm is saying, you got to go Lama, you got to go open source.

SPEAKER_55: And then OpenAI comes that afternoon and there's back-to-back meetings with the CTO, the CEO, CFO, all hands on deck. There's two pitches. We understand the open source pitch. Now give me how the chat GPT team, the OpenAI team, or any other commercial product, it could be Oracle, it could be Salesforce, would come in and say, hey, listen, here's why you don't go open source.

SPEAKER_24: Yeah. So typically what has happened in open source, and this is what's going to be unique with Meta, whether it's Linux and Red Hat, I'm going to put these examples together, right? Or, you know, Kafka and Confluent, right? There's always a commercial company that has a majority of the open source developers working for them or on their payroll or something like that, that can provide support, that can

SPEAKER_61: basically take feature requests, and they're the commercialization arc.

SPEAKER_07: Right.

SPEAKER_62: And so the example I always give for that would be, you can host on wordpress.com, or you can download the source code on wordpress.org.

SPEAKER_63: And my friend, Brian Alvey, my former partner, shout out to my bestie, you know, he works at

David Friedberg: WordPress now, and he works on the VIP product. If you're a VIP and you don't want to deal with managing everything, plugins, updates, and you're not going to get into the weeds, you might as well just go with WordPress VIP, which I did for a long time for my blog.

SPEAKER_24: Or like Linux, you can go compiled it yourself, or you can, you're most likely going to go pay Red Hat, right? If you're an enterprise. Got it. And so, you know, and so I think that would be like the one angle you'd say, hey, if you're, you know, if you're a big enterprise and you want support, well, OpenAI can provide you support, or Anthropic can provide you support, or Cohere can provide you support, or Mistral can provide you support, versus I don't think Facebook is going to pick up the phone to XYZ corporation saying, hey, we're having some problems, you know, can you help us fix it? So I think like that, that's one advantage that, you know, you could argue about from a closed source perspective. But the flip side is, I think folks also understand if they go closed source, they'll get locked in, and so they're, you know, companies are going to lean towards, and you know, we brought this up like a couple weeks ago, the A16Z, they did like a little survey, and they said like 82% of enterprises want to work with open source, they don't want to work with closed source, because they've seen what happens on that. Yeah.

SPEAKER_00: Got it. Is there any concern in the marketplace? And then let's get to some demos here, because that's why people are here. If you're not watching the show, you can watch two middle aged men. To show these demos, you can excuse our appearance, but you get to see the actual demos go to YouTube and just type this week in startups, subscribe, put the bell on, you know, we're publishing three or four days a week. God, I need another co-host, help me with this heavy lift. So, is there any concern about Facebook being the person doing this? And I know I've dogged Zuckerberg for decades, just on how he treats partners, because I watched it happen to investments, and I watched it happen to myself, you know, for a period of time, they were promoting these pages, and I had talked to our friends over there, and I started building pages, and then they rug pulled us, and I got really upset about it. I told, you know, Sheryl Sandberg and other friends over there, like, what, why are we investing in these pages? Yeah. And then we get to 100,000 people, and we paid to get those 100,000 people, and then they rug pulled us, and only, like, 1,000 people would see our updates to that page, even

SPEAKER_72: though they were following it, and they said, oh, pay to boost it. Yeah. And I'm like, oh, wait a second.

SPEAKER_00: If I had built a mailing list with this, you know, one or two dollars per subscriber, I would own them, and I wouldn't have you mitigating them.

SPEAKER_72: So, I really got very upset at Facebook, I'll be totally honest, as an entrepreneur. Mark Zuckerberg did it to my friend, Mark Pincus, and Mark Pincus is friends with Zuckerberg. So, if you have Mark Pincus, and Zynga, and this is all public knowledge, I'm not speaking out of school here, this is, you can just look it up, and throttle their traffic, et cetera, and all those businesses that were built inside of Facebook on the dev program, they screwed them.

SPEAKER_09: So, is it possible in any way for Facebook to screw people here, like they've done every other time?

SPEAKER_79: Navigating the B2B maze can feel really tough, huh?

SPEAKER_82: You're trying to hit the mark with all those top-tier executives, you want them to pay attention to your enterprise product, but where can you find all those big fish, the whales, the ones who call the shots and make buying decisions for corporations, for startups, and everybody in between? Well, here's where LinkedIn ads is going to solve that problem for you, and I've used this. It is one of my secret weapons. LinkedIn means business, business equals LinkedIn in people's minds. When you're on LinkedIn, you're in the business mindset, so you're going to really be thinking about business products and services. You're open to those opportunities, and LinkedIn recently passed a billion users. 180 million of those billion are senior executives, 18%, but hey, we all know about the 1%, 10 million C-suite executives. That's your CFO, CTO, CIO. These are the people who are always looking for a new product or service to make their organization run better, but they are on LinkedIn. That's why LinkedIn's ad platform delivers two to five times greater return on investment compared to other social media platforms. So easy to understand why this is, because this is where all the business people are, and they're in that business mindset, super easy, call to action, make your B2B marketing, everything it can be, and get $100 credit on your next campaign. Go to linkedin.com slash thisweekinstartups to claim your credit. That's linkedin.com slash thisweekinstartups, no spaces, no dashes, terms and conditions apply, because they're giving you a hundi.

SPEAKER_85: I'm going to give some examples here.

SPEAKER_24: Three big projects that Facebook has really changed, you know, the shape of the open community around are the open compute project, where they basically-

SPEAKER_90: We talked about this last episode, explain this, yeah. Exactly.

SPEAKER_24: So what Facebook ended up doing was open sourcing their designs for everything you see here, cooling environments, data centers, networking gear, racks, security, server storage. Wow. And so, yeah. And so they basically, you know, and look, like, they really believe in this, and it helped create an ecosystem and a supply chain.

SPEAKER_92: Explain to people why Facebook would do the open compute project, and if they had an innovation

SPEAKER_00: saying cooling computers, lowering energy consumption, or maximizing storage, they would share that with competitors. Why would they do that? Why would they give away their innovations?

SPEAKER_08: I would say, because ultimately, they didn't view that as, like, their differentiation is in,

SPEAKER_24: they're not a data center company, they're a social network, right? And so they knew that if they open sourced it and other people picked it up, it would improve the supply chain, it would make it such that they could buy more and they wouldn't have to be, like, the sole proprietary bespoke vendor. So I think it was, like, a really smart call on their part.

SPEAKER_28: Right.

SPEAKER_85: And said another way, the more innovation they gave away, the more innovation would come in.

David Friedberg: So while it might seem to be, in the short term, not wise to tell your competitors, like Google or Amazon, AWS, they're all watching the open computer project, they see some great innovation in maximizing storage or reducing heat, you know, in a server rack, and they take it, quote, unquote, steal it, and they leverage it. Well, that's a bummer, right? You just lost an advantage. But for every 10 things they give away, the concept here is they might get back 20, 30, 40, you know, a multiple of innovations.

SPEAKER_99: Am I correct?

SPEAKER_09: Yep.

SPEAKER_24: And look, like, they've been able to really become a leader in data centers because of that, right? They have some of the best in the world. I'm going to give two more examples really quickly here. React.js. So they created this framework so that you could have basically a common code base for your web and native applications, and they created it, and they open sourced it, and many, many companies use this framework to do web and mobile apps out of the same code base.

SPEAKER_00: Which is why, at a period of time, when people use React, a lot of the libraries that were available, the default libraries, etc., everything started to look like a Facebook app, I think, right? Like, there were some, so a lot of the buttons or UX, UI experiences you might have might have

SPEAKER_105: come from libraries that are React, yes.

SPEAKER_00: And again, they give this away, they don't consider the interface, they don't consider the hard drives or the energy or the cooling systems as where the value lies in their business.

SPEAKER_09: They see both of these things as costs and friction. Great. Yep. Let's keep going.

SPEAKER_87: And the last one is PyTorch. Okay, I know about this. Yeah. So PyTorch is the tool that is used to create models. Hmm.

SPEAKER_109: And it's based on Python. It's based on Python.

SPEAKER_24: That's why it's called PyTorch. Exactly. And so this is what's, you know, this is what models are written in. This is what's used to train models.

SPEAKER_87: And so what I would say is when it comes to this whole AI revolution, they've been at the core of it and they've been pushing this technology. And if it wasn't for what they've done, you know, we wouldn't see as much advances as we see across the board.

SPEAKER_24: So these are some examples where these are fundamental components to the modern internet as we have it today. And, you know, Facebook slash meta has been at the core of them all.

SPEAKER_102: Great. Awesome.

SPEAKER_07: So they have a history. You put this into the bucket of not partnerships or using the social graph and the social network and the ad network. You put this as infrastructure.

SPEAKER_00: Infrastructure. And that is why you would lean towards, hey, you can trust Facebook on this. They've got a good track record. I think that you've won the argument here. You know, I was putting it up there to make sure we had a really thoughtful argument about can you trust Facebook or not? I would say as a business partner. No, I don't believe you can trust Facebook. I'd be very cautious if you're a startup of ever talking to that company.

SPEAKER_06: Like if they made like an Instagram API, I don't know.

SPEAKER_09: They may take it away from you.

SPEAKER_00: Never trust them on APIs, but on infrastructure, they do have a track record. So to be totally fair, I like to call balls and strikes. Do not. You will strike out with them as a partner, as a business partner. They will slit your throat. Conversely, on open source, they'll be delightful. Listen, I'm saying it, not you. Yeah.

SPEAKER_11: Okay. Because I know because my friends woke up and they're like, hey, J-Cal, you remember you told me I would, if I went to bed with Zuckerberg, I'd wake up with my throat slit.

SPEAKER_14: I'm like, yeah. They're like, I'm in a bed covered in my own blood. Ooh. Sorry for the metaphor, folks. I'm just calling balls and strikes here.

SPEAKER_09: All right. It's a little spicy. Today, it's Monday. We're off to the races. All right. Okay. Taping on Maduro Monday's release on Terrific Tuesdays. Okay. Go ahead.

SPEAKER_121: Terrific Tuesdays. All right. Okay.

SPEAKER_24: Let's get into one more small piece of news because it's important with a lot of things going on the world today and then we'll, we'll, we'll get right into the demos after that.

SPEAKER_123: Okay. I hope this doesn't have to do with Ukraine or Trump.

SPEAKER_124: Uh, it's like somewhat related. Okay. Here we go.

David Friedberg: But I think it's worth talking about. It's a bite by inbox and my DMs are filled with people saying you have to stop Saks from talking about Ukraine. All in is being ruined by politics. And then another group of people saying, why didn't you cover these three political stories?

SPEAKER_126: I want Saks' opinion on this. It's hilarious.

SPEAKER_132: You guys should just do an offshoot show. Where it's all politics. I think a politics round table would be hilarious.

SPEAKER_11: Uh, and then we could all wrote into it if we want to. And I would, I would do it with Saks. Me, Saks, all in politics, me, Saks. And then like, uh, just, you know, that's a great idea. Let me, let me float that with Saks.

SPEAKER_132: Because imagine it was me and Saks and then a Democrat and then maybe somebody in the middle. And then I moderate. That would be pretty dope. Um, okay. Yeah.

SPEAKER_87: So let's keep moving. All right. So look, this is just a quick one. Um, this came out on Friday or maybe it was even earlier in the week, which is the U.S.

SPEAKER_47: Air Force did a dog fight with a, uh, F-16, I believe that was being flown by AI. It had some people sitting inside of it. They showed right here. But, um, um, but you know, and, and it participated in a dog fight against a human flown F-16. And so. I think we know who won.

SPEAKER_11: They didn't share the results. Probably for obvious. That's fairly obvious. This is what's going to happen.

Chamath Palihapitiya: I mean, if we play video games, the AI, you know, obviously trounces humans over time. And, uh, the AI adapts. So this would be a great way to train our humans is have the AI train them and look for flaws. And yeah, you'll probably have pilots up there and they'll click the AI button. And then you have the pilots as a backup.

SPEAKER_146: And I got FSD 12 yesterday.

Chamath Palihapitiya: Yeah. And I've done two rides on FSD 12.

SPEAKER_147: It's your personal F-16.

Chamath Palihapitiya: Well, I'll just say, I don't think like you could turn on the network tomorrow. Right. I always like to call balls and strikes here. Everybody knows the rules.

SPEAKER_63: Even though I might have friends over, uh, at a certain company, I'm always going to tell it to you straight.

Chamath Palihapitiya: FSD is not taking the steering wheel out this year or next year, but like, uh, cruise or Waymo, um, I think if you put a safety driver in, they could launch. And we'll find out on August 8th, when the robo taxi launches, I do think FSD 12 represents something significant in terms of improvement. It feels a little more human than the previous I was on, you know, I've, I've been using autopilot since day one. And I did a couple of drives and there were a couple of intersections where it had to intervene, um, and a human had to take over and it was a little dicey, but you know, very few, like maybe two per ride, maybe one, every 10 minutes, one. And this is street driving on the highway. It's bulletproof. So I'd say on highway, no disengagements, but on streets, which is where a lot of those rides are going to occur, it needs interventions like once every 10 minutes, I think. Okay. Driving around the peninsula. And so I do think they'll iron those out very quickly. I could see robo taxis starting next year sometime with a safety driver and I could see them removing the safety driver and having remote interventions, which is how cruise did it. And I believe that's how Waymo is doing at a human intervention, maybe, you know, 2026, that would be the timeline I would be on humans in it 2025, no humans in it 2026.

SPEAKER_105: And then maybe the network expands 2728.

SPEAKER_161: Wow. Okay, everybody. It's your boy J Cal here. And I've talked a lot on this week in startups about how the smartest startups are shifting their engineering firepower to Latin America to boost their efficiency.

SPEAKER_85: It just makes sense. You just think about how many amazing developers there are in Latin America and they're on the same time zone. And of course you're going to save money. The cost of living is completely different and the salary structures are different. So this is where curatec comes in C-U-R-O-T-E-C, curatec. When you partner with their team, they get you up and running quickly and they give you the ultimate flexibility to scale up or down as you need to. Curatec takes the headache out of things like payroll and compliance, and they just connect you with the best talent out there. They are trusted by industry leading innovators like Automatic, the makers of WordPress and Comcast. Find out why at curatec.com slash twist. Stop waiting and be proactive about hiring the right people. Head over to curatec.com slash twist. C-U-R-O-T-E-C dot com slash T-W-I-S-T. And get ready to boost your team's productivity with an elite Latin American engineering team at a fraction of the cost of a US developer. And you'll get 20% off your first month.

SPEAKER_164: How generous. Thanks to the team at Curatec. Have you tried the Waymo's in the city? I haven't used it yet.

SPEAKER_72: They got a bunch of invites, but I know enough people who've used them to say, hey, look on a small grid. Yes. Without like anything too crazy, like suburban driving or, you know, one and a half lane roads.

SPEAKER_86: The person jumping on the hood and smashing the windshield.

SPEAKER_00: I mean, it does seem to be doing a great job.

SPEAKER_80: And Cruz was doing a great job until they got kicked out of the city and they were doing some fugazi stuff. It looks like they're a little edgy. Yeah.

SPEAKER_72: Your point about this F-16 is AI is ready for prime time.

SPEAKER_24: AI is ready for prime time. It's going to be everywhere in our own lives. Okay. Yeah. Let's get, let's get into it. So actually a really good transition. We don't spend a lot of time talking about this product, but they've had some significant improvements. So I'm going to bring up Grok with a K.

SPEAKER_172: Oh, okay.

SPEAKER_24: Here we go. What, what I've found in my most recent efforts is that Grok with a K in regular mode is awesome.

SPEAKER_28: Elon's Grok. Elon's Grok is awesome for first party research.

SPEAKER_70: What does first party research mean?

SPEAKER_28: Define that.

SPEAKER_24: I guess like, like I'm doing research myself and I need to get a, like a, an understanding of like. From like a broad range of topics and I want it summarized so I can read it myself. And so I've done the work. What I'll say is like, and you know, maybe you can pull up an example too, if you want, but I did this. It's like, what are people saying about Lama three? And I'm just going to read this for everyone that's not watching. It says people are expressing a range of opinions about Lama three. Some are excited and enthusiastic about its capabilities, praising its performance. And the fact that it can be run on personal machines. We were just talking about this. Yeah. The highlight of the model's length and quality responses, and some even compare its performance favorably to much larger models like GPT-4. Users are sharing their experiences using Lama three with some describing as incredible, the most capable, open the available LLM to date. However, there's some curiosity and skepticism with users asking those performance on private benchmarks and whether it can compete with larger models. Right. There's a surprise amongst users at the lack of discussion on Lama three on Twitter, despite its release.

SPEAKER_87: It's a really interesting, you know, what I find for topics that are very timely, which, you know, you and I have to think about when we're doing the pod.

SPEAKER_24: You have to think about it when you're doing your other pods. It is the best that's out there because it does not have to go out to the open internet to go and research these things. Yeah.

SPEAKER_00: And here's mine. I just asked it. How are the Knicks doing in the playoffs? And, you know, hallucinations and your data in are still a problem. Yeah. I did too, but you had it in fun mode. Oh, so I have to take it out of fun mode. Cause in fun mode, it says the Knicks have started their playoff journey with a solid performance, securing a 2-0 lead over the first round series against Philadelphia. Okay. So that's wrong.

SPEAKER_183: It's 1-0. Okay.

SPEAKER_105: So let me just put it in regular mode here. Yeah. Put it in regular mode.

SPEAKER_72: Okay. And then I got to ask the question again, I guess. So in the first sentence it had the thing wrong, but then it had a lot of actually real good stuff.

SPEAKER_00: Josh Hart's critical three pointer in the fourth quarter, sealing the deal. And then it says, looking to game two, the Knicks are aiming to build on their lead and maintain the home court advantage. So that's all true too. What I like is it gives you the actual tweets below where it's pulling that information from. Yes. Yeah. And so I was about to say, where are the sources and here are the sources.

David Friedberg: So I think Grok is got, again, we talked about how data is the new oil and here, even in regular mode, it must have this 2-0 lead wrong again, because it's pulling in. If it's a future, let's place a bet. Exactly. Well, it is true. We're going to win the second game tonight. The point here I think I'm making is the data on Twitter or X formerly known as Twitter has a huge advantage. It's real time, but it's going to take the model a long time to understand what's spam in that system, because Elon made a very brave decision. And I don't really talk about this stuff too much because then everybody thinks I have some inside information or I'm trading on Elon's name.

SPEAKER_99: So I'm always a little bit cautious about talking about this, but let me just give you my two cents on what Elon did in terms of freedom of speech. It's not what I would have done if I bought Twitter.

SPEAKER_00: I'll tell you that. I would have not done that. I would have made it into an entertainment platform. And that was my vision for it. Not that my vision cares, but I thought, you know, doing a Twitter comedy festival, a Twitter music festival, you know, just build up the entertainment and have it be like a competitor to Disney with the social network or competitor to NBC.

SPEAKER_55: That's what I would have done. But that's me. I'm a media guy.

David Friedberg: Yeah. I mean, what Elon did going for free speech is the greatest mitzvah you could do for humanity and democracy, but there is a price for it. And the price is you have a lot of anonymous accounts.

SPEAKER_00: And so you've got, you know, wall street bets came co with the great, this one, that one, tons of these anonymous accounts that are getting huge followings that could be controlled by state media. It could be some dude in their basement getting paid by some organization who knows what organization's paying them. Or it could just be somebody who's a partisan. It could be somebody who's mentally ill. It could be somebody who's three or four of those things put together. So when you have freedom of speech and you allow the Overton window to open, what happens? More people are going to say more risky, crazy, insightful things. So you get more noise. And then somewhere in that noise could be incredible signal.

SPEAKER_72: In other words, the next Pulitzer, the next whistleblower will happen on X or Twitter. But you'll also have a lot of false positives where Alex Jones says Sandy Hook parents are actors, right? So you're going to, you're going to 100 X the number of conspiracy theories. And then you will get with that some amazing moments where you break news before anybody else, or you're on a story that's super important before anybody else. Yeah. What does that mean for this language model in your mind, Sonny? What does that do to the language model when you have all the conspiracy theorists, a lower window for posting and not having things being taken out?

SPEAKER_86: Yeah. I'm going to share again.

SPEAKER_24: Okay. And I asked, you know, again, because this has a mix of people saying a bunch of things, especially this weekend with all the releases. When is GPT-5 coming? So what are people saying about GPT-5? And it's going to give me a bunch of things here. And people are saying, Hey, maybe it won't be as significant as a jump. And so you're, you're getting the, like you said, the reference from what people are saying there, which is awesome. And then you can say, when will it be released? And it says, Hey, I really like this. The release date for GPT-5 has not been officially announced yet. However, there is speculation and rumors that it might be released mid 2024, possibly during the summer. It's important to note that these are based on reports and insider information rather than official statement. So what I think. Wow. That was, you nailed that. Yeah. So like for me, I find that there is a treasure trove of incredible information on Twitter. Okay. Twitter search sucks. Yes. It's totally unusable.

SPEAKER_87: And what I found with, you know, grow up with a K is that it now gives the ability to look through all that signal and noise and pull up the valuable information.

SPEAKER_206: Yeah. So that's what the language model is going to have to learn.

SPEAKER_82: Don't you love that warm, fuzzy feeling when a business appreciates you and then they treat you like you're their most important customer, you know, VVVIP. I love that. And that's why I love Zendesk because they're going to let you do that for your customers. They offer a suite of tools made just for startups. Now, of course, big companies use it too, but they are really focused on startups. So you can start building relationships with your customer through amazing support experiences. And without growing your head count, there's less money in the ecosystem.

SPEAKER_209: Everybody's got to be efficient right now. And it's so easy to set up. It's made to scale as you grow. So if you've got a hundred customers or a hundred thousand, it's going to work just perfectly. And they give you all these great metrics. So your reporting is easy. This keeps you and your business agile and your investor ready. The best investors are going to ask you about your customer support, how you're doing it, what comes up. So here's one of their great customers at Zendesk.

SPEAKER_82: It's called openly.com and they are an insurance startup and all their agents answer chats and calls in 30 seconds or less. That's so fast.

SPEAKER_209: And when you get that kind of response time, you are going to delight your customers. They're all going to feel like VIPs. And openly is achieving a 96% customer satisfaction score. Guess what openly started on the Zendesk for startups program, but they've grown so much with the support of Zendesk that they recently raised a hundred million in funding. So congrats to openly.com. Hey, you got a little plug there in the Zendesk. Well done. So here's your call to action. It's very simple. Apply for the Zendesk for startups program and get six months free. Yes. Six months free of Zendesk and get ready to scale with the best in customer support.

SPEAKER_213: Go to Zendesk.com slash startups Zendesk.com slash startups.

SPEAKER_62: You know, you could ask it like a really spicy question.

Chamath Palihapitiya: And I guess this is what the team over there has got to work on. So there's a more spicy one. Listen, I hate to bring Trump into it, but he's the trial started today. And I just asked a very basic question. Is President Trump being framed by corrupt prosecutors? And this is a really weird answer.

SPEAKER_62: The press perspective that President Trump is being framed by corrupt prosecutors is present in the information provided.

SPEAKER_218: I'm not sure what information being provided is, but maybe it's maybe the links below. Yeah.

SPEAKER_219: Some sources and individuals express skepticism and allegations regarding the fairness of the legal proceedings against him.

SPEAKER_62: For instance, there are claims suggesting a political motivation behind the charges with opinions stating that the legal actions are part of an effort to undermine Trump's political career and influence. Additionally, there are allegations of misconduct and bias within the justice system, with some individuals questioning the impartiality of the prosecutors involved.

SPEAKER_00: That's pretty down the middle, right? Because it's saying it's opinions. Yeah. That's not inaccurate. It's a little kludgy, some of the sentence structure there. However, it is essential to consider that these views are not universally held and are often presented without direct evidence to support the claims of framing or corruption. That's true, actually. Very well done. The legal system operates on the principle of due process and individuals are presumed innocent until proven guilty. That's true. The allegations of framing or corruption should be evaluated critically considering the evidence presented in court and the legal process that are in place to ensure a fair trial. I agree with that too. In summary, while there are opinions and claims suggesting that the president is being framed by correct prosecutors, these perspectives should be approached with caution and examined in the broader context of legal proceedings. Okay. So it kind of punted on that.

SPEAKER_09: When I see it punting like that, is that a, um, what did you call that layer that's above the language model, the rules, the guides?

SPEAKER_229: Content moderation, you know. This has heavy content.

SPEAKER_185: This is heavy guardrails, right? Yeah. There's an intervention that says we're actually talking about Trump or trials. I don't know. I don't think so. You don't think there's guardrails.

SPEAKER_207: If you stick with sort of Elon's whole thinking around hope. Yeah.

SPEAKER_24: I think that's like, so here's my view and why I wanted to bring it up.

SPEAKER_47: I think it's actually aggregating the large, uh, corpus of data and giving you the average of what it sees there. Interesting.

David Friedberg: And that is the average of what it saw. Okay. So I think it's gonna be really interesting to monitor this because I would like to see the same answer based upon Facebook data, based upon LinkedIn data and based upon just Google news, you know, and, and if you had four LLMs just based on those four different perspectives and then podcasts. Yeah. It'd get really interesting. And I think there was, um, and this is where the blue checks, uh, decision that Elon made. And I understand why he made that as well. It was like a two tier system of like, these are the elites. And then these are the P you know, the peasants. There was something beautiful about the blue check mark system, which at least you knew it was who you said it was gonna be. And the blue check mark system means, you know, it's a paid person. They have a credit card in the system or they're paying on their iPhone, but you don't know if it's actually that person. And you know, that can lead to confusion. They could, if they still have the data and they might be doing this, know who the journalists are in the system, who the government organizations and politicians are. They probably know that data. And then how could you use that to program at LLM?

SPEAKER_00: If you said you have journalists from verified publications, you have politicians who are verified. You have people who work for those politicians. You have non-government organizations. Would you be able to make a better product by knowing the identity of the input?

SPEAKER_237: And do you think they're doing that yet?

SPEAKER_23: That's a really good question.

SPEAKER_24: I mean, yeah, technically, like basically like the best type of training data for an LLM is like a textbook. Follow it like a, like how a textbook is structured, which is some bunch of theory. And then a bunch of Q and a, like, you know, the, the question and answers that you get in the chapter. Sure. And so if you can take the data and formulate that. And so you can be like, here's a bunch of things that, you know, J Cal wrote. And then a Q and a that happens over it so that it can get a better understanding of that data. So if you can do that, you can create really, really powerful, you know, constructs that can be used to, whether to determine if someone's fake. If, if, if someone's written something in a fake way, or if. Yeah.

SPEAKER_239: You know what we think this person's opinion may be based on past history, those types of things. Yeah.

Chamath Palihapitiya: And I will also would encourage the team over there to look at, if they haven't already, it seems obvious. I'm sure they have. How long has this account been around?

David Friedberg: Who follows this account? What's their follower ratio? Just like signals of, should this person's opinion be put into this response? Right?

SPEAKER_62: Yeah. So this first person who is quoted here is not a blue check mark. So this is where I think it's going to get super interesting is who are they referencing? So you can see my screen here. The first link was a person named Michael Bertot. Yeah. He, uh, said on April 15th, 2024, very recent, um, this week, is there a human out there with a brain who still believes Democrat prosecutors aren't going after DJ T simply to keep him from beating up on grandpa Joe and the green dreamers.

David Friedberg: He enables with charges. They would never dare bring on anyone else. Please.

Chamath Palihapitiya: Okay. Let's just. What's your guess? It's got, it's only got 44 views. So why this one is being cited with only 44 views. I wonder if it should be included. Like maybe there should be a minimum number of views.

David Friedberg: So I knew that now I want to ask you, cause I clued it off here with the 44 views. When do you think this member joined Twitter and how many followers do you think they have?

SPEAKER_245: Well, less than a hundred and. Okay. Less than a hundred followers. And I'd say after 2016. Okay.

SPEAKER_00: So you think they've, they're under eight, they're eight years old or younger on the platform and they have under a hundred followers. I'd say under 500 followers, maybe under, yeah, I'll say under 500. Yeah. I'll say under 500 for sure. Okay.

SPEAKER_09: And I think this is a four year old account. Let's take a look. Okay. Click on their profile page here. Let's go.

SPEAKER_00: See what we got. Let's see. All right. He has. Oh wow. 2014. 10 years old. Okay. 966 followers. Okay. He's an economist, Louisiana defender.

SPEAKER_254: Yeah. He's Maria's husband. Mel coach Billy.

SPEAKER_255: Oh, he's a dad. So he's been around a long time.

SPEAKER_254: Maybe that's why the algorithm.

SPEAKER_72: Maybe that's why he's in the answer. Yeah. So, okay, good job there. Okay. And then here, this one, Jordan, President Trump supporter verified account. Yeah. Take a look.

SPEAKER_00: What this stolen crooked and evil administration, the crooked DAs, judges, and other liars have done to President Trump is in fact criminal. President Trump is innocent, but those prosecuting and persecuting and prosecuting him are actually guilty of as the crimes they accused President Trump of. 1100 views. Yeah.

SPEAKER_245: And she's got a MAGA hat on. Well over 10,000 followers. 10,000 followers.

SPEAKER_00: And then when was her account created? Oh, here we go. Oh wow. I got 100,000 followers. 122,000 followers. But she's following 60,000.

SPEAKER_105: So she doing the reciprocal follower there. Yeah. Yeah. Trying to follow it.

SPEAKER_63: I support President Trump. Greatest president we've ever had. I am a daughter scissor.

SPEAKER_267: So here we go. Let's take the third. Okay. Last one. Last one. Last one. Last one. You do understand that those were federal agents trying to frame Trump.

SPEAKER_62: All right. 34 follower, 34 views. And yeah, he joined in 2014. 2014 as well. Wow.

Chamath Palihapitiya: I think actually I'm going to give some credit here. They did say they were doing conspiracy theories. I didn't say conspiracy. I did say, do you think he's being unfairly prosecuted?

David Friedberg: So they looked for tweets of people who on average were eight or ten year old accounts with decent follower accounts and two out of the first three citations. So I actually think they probably are using a really good algorithm. We'll ask Elon to do this. And yeah. Interesting. Okay. Cool. All right. Let's do some demos. Grok is, I think this is big picture. I have a question for you.

SPEAKER_277: Where's the Reddit LLM and how much is that company worth when they launched their LLM? Well, didn't someone license their data? Yes. 60 million from, uh, from Google. Yeah.

SPEAKER_00: But that doesn't preclude them from having their own. Yeah. And if there was a Reddit language search, and when you came to there, there was an AI search on the top level, like meta.ai. Yeah. What's the value of that company? And is there a J trade here?

SPEAKER_283: Ooh. I need to know if there's going to be a language model. Anybody who's listening to this, let me know if there's a language model coming.

SPEAKER_24: Yeah. I don't know. I, and look, I would say the fact that they license their data to someone like Google doesn't give them a chance to create something that can be uniquely differentiated. Yeah.

SPEAKER_286: That's my tape. Yes. They will be able to do one that's unique, right? Cause they have a lot more data.

SPEAKER_00: No, they will not be able to, cause they license all their data to Google. I know, but they have the real time in the community there. So I don't know if you saw, I was in the music community this weekend. Yeah. Listening to my crazy headphones I got from my friends at headphones.com. It's not an ad, but I never accept free product. And these crazy guys at headphones.com were like, Jake, how you inspired us with this weekend startups over the last decade, whatever.

SPEAKER_237: Can we send you a pair of headphones? Yeah. The guy wrote such a nice note. I was like, no, it's cool. I'll just buy them. He's like, no, it would mean a lot for me if I could send you them. Okay. I said, okay, pal, you can send them. Cause my wife told me like, you know, be a little open-minded. If somebody wants to send you, buy you a drink, you can do it. I don't know. I have a thing like where I grew up. I never like a handout. Yeah. So anyway, the guy tells me how much he's making at headphones.com. I was like, okay, fine. Send me these. He sends me this focal F.O.K. Focal brand headphones. They're incredible. Okay. I get back from my trip to us and broken tooth the whole thing. I tell the guy, listen, I use these bathys, you know, with the, with the deck built in. They're incredible. Thank you so much. These things cost $800. Oh my God. Yeah. He's like, did you try the other ones? I'm like the other ones. He's like, I sent you these other ones. I said, okay. I open up. He sends me a 5,000 pair of the top of the line ones that have these thick cables. They plug into this giant deck, not giant deck, a headphone deck. Yeah.

SPEAKER_267: Yeah. And so I was listening to the war on drugs, my favorite, like new band, not new, but new

Chamath Palihapitiya: to me, uh, for the last couple of years. And, um, I went to the music one and I said, here's what I'm listening to. I, you know, I get like hundreds of comments back.

SPEAKER_132: I'm thinking when I do that kind of, uh, thing on a late on a Saturday night, when the kids are in bed, what could the LLM do in real time?

David Friedberg: Yeah. And that's where it gets really interesting. I think the LLM should be going out there. When I talk about the war on drugs, it should say, here are other conversations about the war on drugs. Yeah. There are other bands like the war on drugs. Here are other discussions about headphones that you mentioned. Here's other things about the music service.

Chamath Palihapitiya: I signed up for this music service. That's like a high res music service called Cuba's Q O B U Z. Anyway, it should pick those things up and be doing real time things about the discussion in the sidebar. So let's just leave it at that. Let's go to demo. Okay. I think Reddit, you know, now that it's come back down to earth, I think it's down back down to like a $6 billion company, uh, five times maybe revenue. I think it becomes a buy when it's at three or four times revenue based on the possibility that they could do something in AI. So I haven't put the J trade on yet. Okay. I'm thinking about putting a J trade. I'm thinking about a J trade.

SPEAKER_132: And then we talked about the J trade on meta. Haven't acted on that because the stock is crazy right now, but, uh, I do think it's a

SPEAKER_11: possibility.

SPEAKER_312: What is it on today? I didn't even see it today.

SPEAKER_267: Let's take a look at the meta stock here. Yeah. Uh, meta stock price today. I'm doing it as well. It's up 0.77.

SPEAKER_22: It's at 484. Okay.

SPEAKER_192: Okay. I think it's, everything's going to be waiting on earnings, but you know, if you look at

SPEAKER_105: the five year, you have, you had that three 78 in a 21 go down all the way to the nineties when I bought it, uh, in September, summer. All right.

SPEAKER_314: Let's demo.

SPEAKER_24: Jacob. We're going to run out of time. Okay. All right. Here we go. It's really cool. Marble is. Marble is. So basically it's prompt to fully deployed app. And so it takes a few minutes because you have to fill it out. They give some examples here. I did one, you know, previously someone made like a Airbnb like site. You can make it a Twitter clone. You can make your own Asana. And so I went through the process of making a Twitter clone because, you know, we were, we were going through it. And so I gave it some prompts and you know, it has my app ready. And there you go. Okay. I have a section that had like a user feed. I can post messages. I can create a profile.

SPEAKER_87: And so what's awesome about marbleism is it's taken all the little pieces that we've been talking about over the last year and just end to end platform.

SPEAKER_318: Love it. Yeah.

SPEAKER_08: So this would fall into the agent category as opposed to the co-pilot and tool. Yeah. So your type. This is not even beyond that. This is no, this is like end to end. Project manager. So this is like hiring a consulting firm. Exactly.

David Friedberg: Yeah. Okay. Now we've got a new thought you can hire. You can have a co-pilot work with you. Yeah. The base level of using a language model is asking it a question. The next level is having a co-work with you as a co-pilot.

SPEAKER_267: The next is having an agent where the agent goes out and does things for you. And then the next phase is the maestro or consulting firm where it puts the whole thing together. And here is our first example. Yeah. Where it's doing that. Wow.

SPEAKER_182: Okay. So you can post messages.

SPEAKER_87: And like I said, I just did it end to end. And look, this is a running app. I can send you the URL. Incredible. You can go to it. Wow. It's wild. You know, some of these examples here where you're getting, it's, you know, builds a database. It builds everything that's required for it. Incredible. And so really impressive, really impressive. Yes. And I think you can make use of this within the, you know, launch slash, you know, twist ecosystem.

SPEAKER_62: Oh, incubator, accelerator. Yeah. So I do like more people.

David Friedberg: Yeah. I think this would be more for founder university. So let's put this person in touch with Kelly for producers. Okay. Let's touch with Kelly. Yes. I want this person to come speak at founder university and show it. Because at founder university, we only accept multiple teams with a developer because we want to see the product improve every week.

SPEAKER_192: We don't want to just see ideas. And they typically, the people don't have the bankroll to hire a firm. And if you hire a firm, you're kind of don't have, you're not collecting the talent inside of your own company.

SPEAKER_267: Now.

SPEAKER_192: So that's the interest in Silicon Valley. So we kind of take a Paul Graham approach at launch and founder university accelerator, where we want multiple teams because they go further.

SPEAKER_267: So we ideally want three, but we'll take two. And we rarely take a solo founder, but we do sometimes one in 50, maybe. Um, but we want to have a developer on, uh, we want builders on that founding team, writing the code. Yeah.

SPEAKER_00: So here, I think you could have people making MVPs and little products.

SPEAKER_192: You know, we had great success with people using bubble as, but one example of a no code platform and, uh, webflow and other ones like that inside of founder university. So very cool. You can apply to founder.university.

SPEAKER_267: If you want to learn, be one of 200 people learn how to build a company. Yeah.

SPEAKER_24: All right. Yeah.

SPEAKER_08: I mean, I'll tell you why, because we've been waiting for this and the first person gets the highest grade here.

Chamath Palihapitiya: This person beat the rest of the class out. We have people who are doing UX design. We have people who are writing code.

David Friedberg: We got people who are provisioning servers and doing all that to abstract it and put it into a maestro consulting category. This is big time. This is big time.

Chamath Palihapitiya: This is like having, and somebody could do this by the way, for marketing or growth. We say, make me a marketing plan and execute it. Yeah.

David Friedberg: And it says, okay, my marketing plan is to do ads on Google. Yeah. Here's your Google ads. Facebook ads. Maestro. TikTok stories. And you do the maestro just goes, boom, here's your seven part. And here's your PR. Here's your contacts. You should go after and just lays out the whole thing for you. And that's actually the next level of this, which is giving it a multi-stage complex project. Right? Yeah. And I think if each of the components comes back with relatively clean code, that means you're able to connect the pieces.

SPEAKER_267: Correct?

SPEAKER_354: 100%.

SPEAKER_87: What grade do you give it? Yeah.

SPEAKER_24: I mean, um, you know, I, I was in like the B plus, A minus, uh, only because I would like to see it be a, like, I'm an engineer, so I'm a builder. So it was like a little bit like, oh, I wish I could do these other things with it, but they can add those features. Right. But, but overall, the fact that you can go from prompt to deployed app and they kind of did all the orchestration behind the scenes. Yeah. So I'll, I'll go to A minus. I'll, I'll give it an A. Sounds good. Awesome. We got one more demo. Let's do it. So this one is really cool. This is a Y Combinator company, and you're going to have an appreciation for this. It kind of gave me like AI mahalo vibes.

SPEAKER_87: What they've done is this team has created a vertical search engine with AI and products.

SPEAKER_24: Okay. And so Lumona, right. That's, I guess that's how we would say it. Yeah. So I'm just going to pick one of their, you know, pre-selected ones here. And then it's like, before we begin, you can get some more information. Tell them what the search engine was. Oh, sorry. Yeah. I did. I was going to go back here. How do I get rid of acne on my forehead? Okay. That's really a super common question for teenagers. Right. And so now it, it gives me a bunch of high level insights that I can dive a bit more into, which is.

SPEAKER_33: Yeah. It tells you if you have oil control, non. Yeah. Gen. Exactly.

SPEAKER_47: So, and I can go into these things a bit more if I want to, which I think is exciting.

SPEAKER_24: Or you can just say, you know what? Forget all that. Show me the product result. And what it's done is it's gone and it's scraped. It's exactly what you said.

SPEAKER_87: It's scraped Amazon reviews, YouTube videos. Yeah. And Reddit. And it put it all together. And now it's given me a page. That's like. Exactly what we did. Yeah.

SPEAKER_362: Exactly.

SPEAKER_87: Mahalo style page.

SPEAKER_318: But for skincare and it went in and it, but it did all the work with AI. Amazing. I was like, that's impressive.

SPEAKER_45: Well, it's 15 years later after Mahalo, we couldn't do this when we had Mahalo.

Chamath Palihapitiya: We did this manually with a Wikipedia style approach where people would edit the pages. Yeah.

SPEAKER_129: And so the pages would get stale. And so then we'd have these rushes where I'd have everybody come in and say update all the pages.

David Friedberg: Yeah. I just had literally people getting paid 40, $50,000 out of school 15 years ago, which is a pretty good salary, by the way. Yeah. And I just hired people at college. I literally have 50 people in a warehouse in Culver city writing. I would say it was a lot of fun. Yeah. Yeah. Shout out to all the people who did that. And we were making $10 million a year in Google search ads, but then Google took us that index because yeah, they're sharp. Yeah. Breaking news right now. Meta opens up its VR OS called horizon OS to third parties and says. Asus and Lenovo are both planning meta horizon OS compatible headsets. So I think meta is behind with their headsets because of apple. I think they consider the vision pro such a competitor. Yeah. And here we go. Boom.

SPEAKER_105: They are now going to let everybody use their OS to try to compete and do the, what Microsoft did with Dell and HP. You know, you guys are getting fit.

SPEAKER_120: Just put it out there and see what happens.

SPEAKER_375: Put it out there. Let other people. Yeah.

David Friedberg: Yeah. This has been great. I give that one a B.

SPEAKER_375: Oh, a B.

David Friedberg: Oh my God.

SPEAKER_00: No, I mean, I'll be honest. I think anybody can hack this together in 60 days. Okay. And so what we need to see out of this is proprietary data, how they're going to get users. I mean, B is not bad for just graduating Y Combinator and having this thing out in public.

SPEAKER_129: But I mean, the design is terrible. I'll be honest. Like this looks okay. On a design. If I was going to give this a rating on a design, I give it like a five or a four out of 10. Okay. A terrible design.

SPEAKER_275: I mean, the formatting is terrible. The, I thought it was pretty useful. No, the logo is terrible. The UX is terrible on this.

SPEAKER_224: Maybe it's because we're looking at it on the desktop, but the content seems like they did exactly what you're looking for, which is to just give you a top level overview of everything that's out there.

SPEAKER_192: And the goal is how quickly can I get you the knowledge you're looking for from a disparate set of, a disparate set of sources.

SPEAKER_00: And on that they've succeeded. Just hire somebody for, I would hire four designers for a thousand dollars each to redesign that one page. This is my secret to doing great design cheaply. Okay. Allocate $5,000. You give three people $1,000 to just design one or two screens of your app. Okay. Most designers charge 50 bucks an hour. So that's 20 hours of work. 20 hours. Okay. Pretty, pretty fair deal. Okay. So now I take those three. You drop the weakest where you take the top two, you give them feedback. You say, Hey, for another thousand dollars, I want you to make a new version. Here's my feedback on your first version. So you did 3000. Then you did 2000. And then you pick the best of those two. And you have that person become your designer on an ongoing basis. So it took you $5,000. You got three different looks, got two 2.0 versions. You got a final version that you then work on with the one who was the best to work with. So for $5,000, instead of giving it to one designer, do your whole website, you give it to three and you do three, you do two rounds or three rounds of bake offs.

Chamath Palihapitiya: You can adjust it to your liking. But the other thing I find is some develop, some designers disappear. Cause you know, they're designers. Sometimes they're a little flaky. So sometimes you hire five for $1,000 each, only three of you get you the product that you're looking for the date. You say, I just need the product by this date. So anyway, it's, and that's fair for designers too. They like these like quick jobs. Okay.

SPEAKER_33: Great job. What do you give it? I thought it just hit on like, again, good execution, end to end, verticalize.

SPEAKER_47: And I feel like that could be the future for us. My letter grade is B plus. Okay.

SPEAKER_239: There you go.

SPEAKER_62: B plus. All right, everybody.

SPEAKER_00: Uh, if you want to see all of our bets this week in startups.com slash bets, when Sonny and I make bets, uh, and then you can see all the, uh, AI playlist this week in startups.com slash AI should redirect you either to a landing page or to the YouTube playlist. We have an AI playlist there. Yep. All right, Sonny, you're amazing. Thank you, sir. You put so much energy into this. You have so many deep insights.

SPEAKER_192: And I always like to give Grock a plug. You can go to console.brock.com and, uh, you can follow x.com slash Sandeep on x.com slash Jason.

SPEAKER_00: If you are applying to Y Combinator, congratulations, but no, only 1% of people get in. So what I love to do is just tell the audience, uh, if you have your application, it's sitting there in your inbox, you've already got it all cleaned up, ready to go. Email yc at launch.co launch.co. We don't have the M drop the M.

David Friedberg: yc at launch.co forward us your application. If they reject you, that's okay. They reject 99% plus for the elite program. Guess what? I have a program too.

SPEAKER_00: We accept 1%. So if you just forward us your application, that's good enough for us. We'll get you on the phone with one of our team members. You do a quick introductory call. You explain us your vision. I'm going to guarantee anybody who emails yc at launch.co gets that introductory call. You meet one of my amazing team members and they're going to hear your vision out. They're going to share it with our team. And then, Hey, if it's a fit for you and for us, we'll do a second meeting. And then if you get past the second meeting, I'm the third meeting. And then you get to hang out with me and I invest in a hundred companies a year. And one of the great delights is I get to hang out with those folks every quarter. Basically I do in-person stuff. So you can fly out and see me when I'm in New York, Austin, Miami, LA, or San Francisco. And we hang out for a half day, get some ribs, get some pizza, whatever, some sushi, some dim sum, whatever it is. It's all about the food for me. And we hang out and we work on your business.

David Friedberg: Great delight for me to get to work with founders. So yc at launch.co for to share application. And by the way, I'm watching them come in. And sometimes I just hit reply.

SPEAKER_192: If I really like one before my team, anything gets to it. And I just give them some thoughts on what I think. Yeah. And Hey, we accept just under 1%. So if you put the 1% together, now you've got, instead of a one in a hundred chance of getting into a program and getting 125K, you got a one in 50. You got a 2% chance. Now you doubled your, you doubled your efficacy.

SPEAKER_47: All right. And product insights too. I will say, I've seen Jay Kellen action. Amazing product insights. Thanks pal. Been in the game a minute.

David Friedberg: I've been in the game for a long time. I've, I've seen over 10,000. I've done 10,000 in-person pitches from founders.

SPEAKER_00: And what happens when you do 10,000 of them is you'll see the same ideas over and over again, or the same customer base over and over again, the same, you know, business models, techniques. And, and yeah, you, you will see some mistakes and you will be able to give some insights. Many times I'm meeting with a founder and I'm like, Hey, do you know about these three companies? They're like, no. I'm like, Oh, okay. You're 25 years old in web 2.0.

SPEAKER_192: There was like, there was this company in web 1.0 on the doc America called web van. And then there was this other company called postmates.

SPEAKER_11: And then there was this company and I'll tell them about companies and we'll pull up the Wikipedia page or like, we'll go to the way back machine and look at their landing pages. And they're like, Oh my God, somebody had the exact same idea as me. I'm like, ideas are easy. Execution is everything. How are you going to execute better than these people who failed? And Hey, do you know those people and why they failed? They're like, no. I'm like, you ever think you want to email one of them?

SPEAKER_192: Tell them you have the same idea they had 15 years ago. And Jake, I'll told you to email them. And then maybe they'll tell you why they failed. And it's such a great unlock.

SPEAKER_00: Just like when I saw Lamona today, I could, I mean, I could tell them like their pages are not designed well enough for people to come back. Right. They need to be designed a little bit better. So that's like a mahalo.

SPEAKER_412: She's a feedback. Yeah.

SPEAKER_78: I would love to have him on the show.

SPEAKER_412: Yeah. I'd love to meet him. Sonny, anything, um, did you make a rock.com slash startups yet?

SPEAKER_414: That's what should be on your punch list. Okay.

SPEAKER_402: It'll be, it'll be there.

SPEAKER_414: All right.

SPEAKER_237: We'll see y'all next time. Bye.

SPEAKER_162: Bye. All right. Great job. Bye. Bye. Bye.