SPEAKER_00: You didn't buy the $1,000 steak, did you? I mean, come on, Jake.

SPEAKER_04: You had to?

SPEAKER_01: When he's not there, do they send somebody out who looks like him?

SPEAKER_05: No.

SPEAKER_06: To do the whole thing with the salt down their arm? Do they do that? Or is only he allowed to run salt down his grimy arm?

SPEAKER_08: Yeah, they all do that. They all do this salt thing. Yeah, yeah, yeah.

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SPEAKER_05: All right, everybody. It's Monday. Tons of news happening. We'd like to start the week off with some news and also this week in AI.

SPEAKER_17: We have so much going on in AI. It's a complete platform shift. Tons of entrepreneurs have stopped working on whatever they were working on last year or for the last couple of years and become obsessed with this. And one of those entrepreneurs is Vinny Lingham, good friend of mine and the show. And he's here to chop it up with me. Welcome back to the program, Vinny.

SPEAKER_19: J.K.L. Good to be here. Thank you.

SPEAKER_17: Sonny couldn't make it. Uh, so we will get right into it. Um, there was, I don't know if you saw this story. It came out of the information. Uh, there was a social messaging startup. IRL was the name of it. Obviously, they use the acronym in real life and, uh, they're shutting down after a board investigation

SPEAKER_20: found that 95% of their 20 million monthly active users were fake. Let's pause for a second. Just take that in. They faked 94%, 95% of their user base. This was a group messaging app that was focusing on having users plan and discover in-person events.

SPEAKER_26: Yet another event planning app.

SPEAKER_17: We get pitched on these incessantly. Um, it's almost, uh, like a joke within the industry, uh, fitness apps and, uh, planning apps.

SPEAKER_27: Like, isn't it hard to plan a trip? Here's an app that does that. Isn't it hard to get pickup basketball games going? Here's an app for that. It turns out that the app for that, that really worked was meetup.com. For people who are super dedicated and I message and just starting Facebook groups, et cetera. In other words, nobody's ever really made this work except meetup.com. Um, but looking at the cap table history, Vinny, uh, founders fund and floodgate invested in the seed round back in 2017. Fair enough. 2 million, a $10 million post to seed round is probably not much data to go there, but fast forward to 2021. This is where it gets interesting. They raised $170 million series C at a $1.17 billion valuation backed by

SPEAKER_28: SoftBank's vision fund. Now this investigation.

SPEAKER_31: Yeah. Uh, lack of vision fund.

SPEAKER_33: Uh, yeah, it's, uh, so anyway, they, the information, uh, which does a great job.

SPEAKER_17: Shout out to Jessica lesson, uh, did some investigations. They talked to some anonymous employees, uh, and, uh, these anonymous employees

SPEAKER_38: questions, the CEOs metrics after this March information article inside the company. Some employees recently expressed concerns to managers about the usage figures. The company had touted, it just seemed to stem from Shafi's, uh, the CEO, co-founder, uh, Abraham Shafi.

SPEAKER_17: Uh, he wanted to use a more expansive definition home, more expansive of active users than that of established social apps like Facebook.

SPEAKER_05: Uh, and they felt the company may have used an unconventional definition to make the app appear bigger than it was for an investigation happened and an SEC probe into the company two months ago, Shafi was suspended for misconduct and late last week in the Friday news dump.

SPEAKER_38: A spokesperson for IRL dropped the results from the board investigation. 95% of the 20 million users. That's 19.5 million of them, uh, I believe, or something in that range, uh, were either automated or from bots company was shut down capital return to shareholders.

SPEAKER_17: What do you think Vinny, um, of this level of fraud?

SPEAKER_26: Is this something that happens often? Cause this is far beyond fake it till you make it.

SPEAKER_42: So, so, so Jake, you, you know, I've spent like since 2015 working on identity. Um, and so this is the subject is very close to my, close and near and dear to my heart. Um, and, and I'll, I'll start by saying that. You know, this is not the first and it's not the biggest either blow up in the space. I mean, Frank, I think Frank was a lot bigger. Um, there was the, I think Goldman Sachs invested in those guys.

SPEAKER_48: Um, oh yeah. And there was, yeah.

SPEAKER_47: Frank faked 4 million users. Was there only four?

SPEAKER_48: Sorry. But the investment amount is higher, but there's a big difference.

SPEAKER_51: Those were, I think, um, those were bank accounts and banking. Yeah.

SPEAKER_54: Bank accounts and stuff like that. And they had been bought for 175 million. So continue that this is something that happens on the regular.

SPEAKER_05: Why does this happen? If you were like a non take a step back, take a step back. Okay.

SPEAKER_60: Okay. How is this any different from what Twitter was doing before Elon took over?

SPEAKER_05: Um, okay, Twitter, um, was allowing, apparently I don't have any inside information here, but they were allowing bots all over the system and they were counting daily active users or monthly active users that people considered questionable monthly. Yeah. Yeah. M DAOs monetizable daily active users. There, there was a lot of shenanigans going on with the numbers clearly, and they were incented. Um, to allow bots on the system. So Elon talked publicly about people were creating the fake bots just to fire off SMS in countries where like people had control of the SMS system. And then we're getting paid 5 cents every time the SMS went through from Twitter, which was paying for an SMS gateway. So they would just have armies of people signing up for accounts. And you had this like steady stream of millions of accounts being created that, you know, were lightly used, I guess, uh, but keeping up the

SPEAKER_69: of those fraud, um, and I, it does feel like there was fraud at Twitter as well.

SPEAKER_72: Well, also serving ads to bots is a very profitable business, you know.

SPEAKER_05: Uh, until people realize that like there, cause at the end of the day, performance comes into play. And I think people felt like, well, wait, there's no performance here.

SPEAKER_76: Well, that there was, that takes a couple of years to churn and burn, right?

SPEAKER_42: So I've advertised on Twitter before they, they take, take your budget, 10, 20, 50, a hundred K, and then they burn through it.

SPEAKER_78: And then, okay, next, you know, and so they, they keep trying new customers until people keep getting burnt. And that's what, you know, I think they got to the end of that recently. Look, here's the issue. There are no legal standards.

SPEAKER_42: It's, I mean, you know, if you go to a bank and you get KYC and, you know, AML and they know it's Jason, um, you, it's difficult to fake another Jason. I mean, it's possible, but it's, it's harder, right? With these services, there's no identity attached to them. Facebook's got no identity. Uh, Twitter's got no identity, none of these services, and they don't want identity, right? Why don't they want it?

SPEAKER_78: Because it reduces their numbers. Right. Significantly.

SPEAKER_84: They're puffing up their numbers by not.

SPEAKER_60: Yeah, Instagram's a great example. How many Instagram fake accounts do you get a day? I get tons jumping on, you know, like it's, it's, it's, it's nuts. Right.

SPEAKER_06: But they, okay, explain the dark web here and what's going on with these fake accounts. How are these fake accounts being created on mass?

SPEAKER_92: Well, so what they do is they go and buy old accounts. So they, they try and age accounts. That's one way of doing it. So you get an account that was created three years ago, four years ago, all those accounts.

SPEAKER_95: Are they doing scripts? Are they have farms in India, Manila, where people are getting paid a dollar an hour to just make, you know, 50 accounts.

SPEAKER_92: Dormant accounts. And then they buy the account. They also use these farms to like create lots of follower accounts.

SPEAKER_42: So you have 5,000, 10,000 followers. But these are all other bots following these accounts. It's all fake. And then they use those accounts. Uh, eventually they turn, they just change things, right? They put, change a new profile picture, put a nice, pretty girl on there. All her modeling photos. You'll see one of the tricks is to look at, when you go, you know, you go on these fake accounts, look at the dates and you'll find most of them were added in the past like month or two or three. And a lot of photos are uploaded on the same date, as opposed to, if you go to my Instagram feed, you'll see every single photos on a different date, different places over spanning 10 years. Like my, or 14 years.

SPEAKER_54: It just allows it. Why, why does Instagram allow this?

SPEAKER_76: Cause they've got internal KPIs. They've got internal KPIs.

SPEAKER_42: The KPIs are how, how, how many users are we adding? What's the growth that we have? Um, you know, and because these numbers tie into the, the ratings that they get for like, you know, ad budgets and, Oh, Instagram is growing faster. We should put some more money there. There's no incentive to cut it down. Now they could argue, Oh, people, you know, we, we, people want to be a little bit synonymous. They want to be anonymous for whatever reason. They've got privacy, but it's a lot of just BS. I mean, there's ways of solving these problems. They just, there's just no wherewithal to solve it. This applies to all social networks. There's no interest in solving this problem. Now they think phone numbers is a way of doing it. Phone numbers is not a way of doing it. How many spam calls do you get a day?

SPEAKER_86: How many, these voice of IP banks, you can just go buy hundreds of these numbers. That's not a way of getting it. The only way to do it is to attach identity and you can do it in an anonymous way. So you can do like, you can have a Jcal identity that you, a digital identity

SPEAKER_42: that you use that it always knows it's you, but it doesn't know who you are. And you can't use it multiple times to create multiple accounts. There's ways of doing this, but in all my years of the ways get, when you put

SPEAKER_05: up friction, sometimes I guess their account would be if you put up friction, then the

SPEAKER_17: next incremental user might not sign up. So you do get a little bit of that, um, but yeah, and, and for people who haven't

SPEAKER_05: heard the term KPI key performance indicator, if you hear a bunch of buzzwords at a startup like hack or, uh, LTV, these are, you know, customer acquisition costs, lifetime value

SPEAKER_17: of those customers revenue per whatever, um, you know, different ratios, whatever.

SPEAKER_05: Yeah, average revenue per user, these are things that management will set out so that everybody can work towards a goal. Hey, let's reduce the amount of turn. Let's increase, uh, the average revenue per user. But if you create an incentive, people will abuse the incentive. One example was next door. I love next door as a site provides a ton of value to me, but they disclose when they did their SPAC that they count an active user as quote unique members who have started a session or opened a content email over the trailing 30 days. And that last part, like, okay, I, I got an email because I had signed up for next door and I, you know, was scanning through my emails and now I count as a user. I found that one to be a little bit shaky. Now it's not outright fraud. Uh, in this case, they had 95% were fake. So actually that's 19 of 20 million. I think I said 19.5. Yeah, it would be 19 of million of 20 million were faked, which is just insane.

SPEAKER_109: Um, this person's gonna go, this person's gonna go to jail, by the way.

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SPEAKER_115: What about diligence?

SPEAKER_78: Well, how come these, the diligence periods, the diligence is coming back. It's the new trend. So diligence will happen. Diligence is back. Why?

SPEAKER_05: So let me ask you a question. You've been an entrepreneur for a while. You've done, you've had diligence done on your companies. Sure. Um, and then sometimes people don't do diligence. You've had both experiences. I assume some people just trust that whatever you told them is true and they believe the story and they give you money, um, and then other times people do diligence in when you've raised money, how often, you know, out of a hundred investors that you've probably worked with over the years, how many did diligence? How many didn't be candid?

SPEAKER_90: I, I think with gift, for example, which was, um, we, you know, we raised basically a seed

SPEAKER_42: round. I don't think when we raised a very small, a round, it was, it was kind of a party round. We raised a whole bunch of checks here. There, no one already did diligence. I think they asked us for our financials and whatever else. No one double checked. It was cursory. Yeah. Cursory. Cause it's early stage, right? It's like, there was nothing really there. When we sold the company at that point, there was, you know, tens of millions of dollars in revenues. First data came in and it took six months to get that deal closed. Oh really? Yeah. And just cause of all the diligence, the documents, the open source licenses that we're using, all those things. Like we had, like the diligence, the, the, the, the, the data room was insane, right? Cause it's a big public company that does, well, at that point they were private, but they were, you know, they were going public trillions of dollars worth of transactions. They just couldn't afford to, you know, get into a mess. And so they were, they were pretty, um, sticky about it. Right. And that was great. And so we, but then here's what happened. So after I passed that, that hurdle and sold the company, um, my next company, no one, like everyone just trusted me. Right. So all my old investors, like when he knows what he's doing, he's trusted entity, we'll just put money to his next company. And that, and that worked. And like, even now with, uh, with weight room, I mean, it was early stage company and like, no one's questioning my ability to run a, a solid organization.

SPEAKER_05: It's going to happen. You'll get all of these requests when you have, uh, more revenue customers, and that's when

SPEAKER_127: they'll do it. Exactly.

SPEAKER_128: Early stage, early stage diligence is, early stage diligence doesn't make sense. Right. Cause there's nothing really there.

SPEAKER_05: There are things on our diligence, we I'll give you launch does diligence, um, even for seed stage. And we'll even do it like in our accelerator. Um, and what we tell our founders is, Hey, we're going to do a diligence process because we want you to understand the diligence process you'll go to go through with downstream investors when we introduce you to VCs and seed funds.

SPEAKER_27: Now some of these things will not apply to you. When we ask you for bank statements, we ask you for financial statements, P and Ls. You may not have them cause you've only spent money. We've never had revenue coming in. Um, but we do want to see your incorporation documents. We do want to see your IP assignment. We do want to see your cap table. Um, and we do want to see that you opened a bank account and just where that bank account

SPEAKER_05: is. And, uh, it's amazing. People are like, what's an IP assignment? And so, okay, that's when you start the company that all the creations you make as the founders go to the company, not you. So down the road, you know, you don't claim that you have some patent that, you know, is here, or we just ask them, has anybody threatened legal action? Um, and not just ha and then has anybody sent a legal letter? And has anybody verbally or by email or other electronic communications threatened to make

SPEAKER_38: a legal claim against the company?

SPEAKER_05: So when you really open it up like that, they could say, yeah, you know, we fired somebody and they said, uh, I'm going to sue you. And that was seven months ago. We never heard from them. Great. That happens to every company. People get upset. They got fired. They threatened to sue, but it was just a text message. The fact that somebody would like put in such a large amount of money and not do basic due diligence is really the issue here. I mean, if I'm doing it for literally a hundred K check into an accelerator or a 500 K C check. Exactly. When you start putting in tens of millions of dollars, that's the problem.

SPEAKER_142: Look at this hit list. Well, but this is the, the culture of the valley has always been, you have, who's the

SPEAKER_42: lead investor? Okay. It's Sequoia. It's Sequoia and you just put the money behind them or it's Chamath or it's whatever. Right? So no matter who the lead is, it depends on who the lead investor is. Softback was the lead. I know, but this is the problem. Like, so this is what's happened in the past 24 months. The, the pyramid of trust is broken down.

SPEAKER_05: You can't trust anyone is a much better, yeah, trust, trust, but verify. Actually, I would, I would be paranoid and have trust. No one in your mind, just in the back of your mind. But I would trust, but verify as you're publicly facing stance. I have seen people who I thought were incredibly trustworthy, do incredibly, um, fugazi, untrustworthy stuff in my experience. Like literally I had some, I had a founder, I'm going to make this an amalgamation of others. I had a founder who specifically signed like six of the seven documents and then didn't sign one of them and everybody put their packets together and somebody on the operations team didn't check the SIGs and noticed that his one signature was on the page. That page had certain rights. And he said, oh yeah, no, that never got confirmed. And I said, yeah, but the other six pages did you, the spirit of this was X. And he's like, yeah, yeah, but I guess not because it wasn't signed. So I guess you'll have to sue me.

SPEAKER_17: Like literally a founder said that to me, I was like, okay, I know who you are. I'll never invest in you again. Goodbye. The end. Um, but look at this.

SPEAKER_151: They get tripped up at some point when they act like that. You gotta be careful.

SPEAKER_61: Yeah. Yeah. And when people show you who they are, um, you can believe them. Yeah. Going down this list.

SPEAKER_17: Look at this murderers row of frauds during the zero interest rate phenomenon. Here we go. Piano exit. SPF and FTX eight criminal charges. Hey, some of them might get dropped. Frank founder, Charlie Javis. Hey, she faked 4 million users to get acquired by JP Morgan.

SPEAKER_157: Do Kwan. He got picked up in Montenegro with the fake passport charged with eight counts of fraud in

SPEAKER_20: the US. He was on this program. Shout out.

SPEAKER_157: Open C product manager, front running NFTs. It wasn't enough to be selling NFTs. He needed to front run them to faith though.

SPEAKER_26: Chastain convicted in may faces up to 20 years in federal prison. Coinbase product manager accused of insider trading, AKA front running tokens. They were about to be listed on coinbase. They both settled with the sec gave up their ill gotten gains with interest, pled guilty to conspiracy. One faces a two year sentence. The older brother who worked at coinbase will serve a 10 month sentence. Headspin founder Manish Lakhwani. Overstated revenue, raised a hundred million on fake numbers, pled guilty to wire fraud and securities fraud. He got pinched. Sentencing is September 27th. Likely serve a decade plus in jail. And that doesn't even bring the long, slow arm of the law getting.

SPEAKER_17: Elizabeth Holmes. Who's now gonna serve nine, 10, 11 years while her children tragically are in there. Didn't she have those?

SPEAKER_162: Didn't she have those children to try to get leniency from the court?

SPEAKER_163: They were sympathy babies, uh, is the most cynical take on them.

Chamath Palihapitiya: She literally tried to get a, she had reduced sentence babies. Uh, sympathy babies to try to carry things.

SPEAKER_166: That is dark. They soak. They so consistent with her, her darkness, I guess.

SPEAKER_05: She is a sociopath, like literally to be like, I'm gonna birth two babies who now have a lifetime of therapy. Yeah. Because their mother had them before she knew she was going to prison in order to try to save, cut a couple of years off. So she used our suffering for this reason.

SPEAKER_27: I mean, it is the worst, if that's exactly what she did, which it seems to be the case. If that's what she did, it's a short list of more evil things you could do to child.

SPEAKER_38: Like, I mean, it's a, it's a level of abuse that is truly dark and deranged. Anyway, I'll leave it at that.

SPEAKER_26: Hey, did you see data bricks is acquiring mosaic ML for 1.3 billion dollars.

SPEAKER_27: He was recently on the podcast, Naveen Rao. Uh, let me just play a quick clip from him from episode 1754. And then I'll get your reaction on this deal.

SPEAKER_176: So what we're doing today is really bringing these capabilities of large scale machine learning. Which is generative AI in my, in my mind to many organizations. Um, I, I think one of the things we've done, even with my previous company was trying to really bring these capabilities to more people to create the world we want. I see success as people that disagree with me, being able to build models equally as good as me. Right. I think that's how we're going to make this world work. And it's become front and center now with debates around, um, regulation of AI and, you know, putting some sort of, you know, government licenses and this and that. Um, I, I think really this is solved more in a market as a market solution where. Many people can build this stuff. Many people can imbue these models with the biases that they see fit. And, you know, we'll let the market decide where, where things should be, not some sort of centralized regular regulatory agency.

SPEAKER_17: And so if you don't know, Mosaic ML basically allows businesses to build their own chat GPT like tools. Uh, you can use their software, plug in your own data and build out a chat bot either internally or for your user base. Databricks, of course, competes with Snowflake. Uh, if you don't, didn't know that sits on top of your AWS or Azure, Google cloud, whatever, and it helps categorize and manage your data. So it's easier to access, uh, what are your thoughts?

SPEAKER_182: This is pretty stunning.

SPEAKER_181: I think it was a great exit for Mosaic. I mean, they're walking into a space where the capital requirements to participate at the highest levels are about to go through the roof.

SPEAKER_184: We already have just the hardware requirements, et cetera.

SPEAKER_42: And I think that, that it's a very competitive and very open marketplace. I mean, Facebook's got this stuff that they're doing. They're open, more open sort of approach to it. Google's recognized they've got to be open. They've got to be open. He's right. There is a marketplace of, and there's competition. And the problem is all the giants, all the tech giants sitting with tens and hundreds of billions of dollars in cash, they can outplay and outmaneuver any startup when it comes to resources. They've got the money to do it. So, you know, you're stuck in this, this sort of conundrum where you go, do I raise a $50, $100 million round or $200 million round to compete and keep going? And then I need to exit at $3 billion maybe, or, you know, maybe even more depending on the terms. Or do I take the, take the win?

SPEAKER_92: I don't know how much they've raised. How much did they raise to date?

SPEAKER_163: Just so folks know. Yeah. They had raised only $34 million.

SPEAKER_17: Wow. So that means they probably only diluted. I don't know. Let's just say 30%. Maybe the founders probably own 50%. The employees, 20%. They got to have to do a massive earn out here. They're going to have to vest that in order to get this kind of deal. They're not just getting a billion dollars in cash. This was an all stock deal, as you would expect. They need to keep these folks hungry. Uh, you can see, um, the, um, MBT. 30 B chat, which is their chat on hugging face. Um, but basically, you know, feels to me like there's so many people making these models, foundational models. And the open source community has so much engagement right now. And they were working on open source models. Uh, I believe that I think open source is going to win this race. What do you think Vinny? Is it, is this going to go to Google and Microsoft slash open AI?

SPEAKER_27: Or do you think the open source world is going to win the day here?

SPEAKER_42: So I think we're at the bottom of some sort of an S curve for this technology, where you're going to have an open source. Where you're going to have a rapid amount of innovation in a short space of time. And then it's going to peter off and, and, and sort of slow down. Whether that happens in one year, two years, five years, 10 years, I don't know. But yeah, kind of law of large numbers sort of mindset. It's going to slow down. It's going to get so big and eventually things slow down. Now when it slows down. So, so that S curve migration for me is going to be open source driven. I don't think that, I don't think that companies can out maneuver and out compete the open source market. And then the, the, the thousands and millions of people working on AI across the globe to come up with the best solution. So the market approach is that the cream will rise to the top. Now, when that happens, I think we're going to have a Mozilla-esque world where, you know, Mozilla Firefox, Chrome now, and a Chromium world where you have, you know, even Microsoft edge is using Chrome. Chromium. So it's open source underneath it, but they've got their own flavor. Yes. So I think what you'll have.

SPEAKER_194: You're referring to the browser.

SPEAKER_42: Yeah. The browser. Yeah. So, so what I think you're going to have is this rapid acceleration to a point of, you know, slower growth and slower rate of change and a more mature sort of stack. And then from there, companies, corporations, startups, brands will take that stack and start making it fit for purpose and trying to create something on top of that, more of a sort of an interface layer that people can engage with and is pretty robust and, and more, more with industry standards. Right. So we, we can't agree on the standards. We can't agree on a lot of things right now because it's all in flux. And yeah, it's like, it's like when, when, when, when Linux came out, it was Linux red hat.

SPEAKER_78: You had, I mean, you had like 50 different variants of Linux back in the days.

SPEAKER_196: You had so many different ways to, and also ways to put a web servers up and to, you know, serve web pages and an open source engine X.

SPEAKER_198: Everything just became open source.

SPEAKER_17: And interestingly, snowflake acquired Neva. That was the, uh, AI powered search engine. They acquired that in May. We had the CEO of Neva on this program back on episode 1686.

SPEAKER_38: In February, I think actually Molly did that interview.

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SPEAKER_05: Why do these data companies like Databricks and Snowflake covet AI and are spending money buying these?

SPEAKER_61: Why are they in such a panic to catch up here?

SPEAKER_78: I mean, it's disruptive, right? If their competitors are doing it and getting return on investment from it, then you can bet, you know, you can bet your bottom dollar that.

SPEAKER_42: Look, profits are going to seep away from companies not using AI to companies that are using AI. Simply, simply put, like, and we've had this conversation before, you know, low level, low level jobs or repetitive task jobs, like customer support. Okay. Take any large company. This is used. I always use Verizon because they probably get like, I don't know, 20 million tickets a year. And they've been getting that many for, I don't know, 10 years.

SPEAKER_86: So, they've got 200 million email tickets.

SPEAKER_42: You plug that into an LLM and then you have the LLM reply to every other, like, the chance of getting a ticket that has never been seen before diminishes greatly every single day. And even then, the system can use inference and figure out exactly what the person is saying and come up with a good response. So, now you're going to go from 10,000 customer support people to zero being software driven. Or maybe you keep 100 for, like, level two support or something, right? That's what's going to happen in the industry. We are going to, we're going to automate these jobs that have large data sets behind it, where humans have been trained to understand where to look for information versus AI knows the information that's available within milliseconds and can produce it. I mean, it's, it's, to me, this is the way things are going to be, we're going to see a massive amount of job loss in these sort of categories. But it's not about the job losses. It's about the profits.

SPEAKER_86: Companies deploying AI are going to increase their profit lines. And that this is the key points.

SPEAKER_210: And then it takes the competitors.

SPEAKER_189: This is going to be the key thing. I, um, have made this discussions.

SPEAKER_17: I've had these discussions internally at my companies over and over again. Inside.com is a newsletter business. Um, and we have great newsletters and it makes millions of dollars. It's doing great.

SPEAKER_05: Um, and I was just looking at, like, we spend a little bit of time tagging stuff and I just took a story and I said, tell me who this story is about. And I just cut and pasted our summary of the story.

SPEAKER_17: Cause we kind of aggregate and organize the data there and, um, try to make sense of it for folks. So they don't have to spend so much time reading. They just read out like a little presidential brief as it were. Like, that's what I sort of, uh, based it on.

SPEAKER_05: And then I took the original story and I put it in and it knew chat GP four and Bard both did a stellar job. I've, you know, when I said, Hey, uh, tell me what this story is about or who's in this story. It organized it perfectly. And that was, I think really interesting to me when I said, Hey, I literally went through this and said, put who is in this story and, um, put them into a category and describe them. And it was like, Oh, this story is about a company named X and another company named three companies in the story. Describe them in a sentence linked to their website. And then it said, Oh, and there's a media outlet that wrote the story. And then there's an Alliance in this story. Um, which is a smart home Alliance. And then, uh, there's this person who is the, um, host of this podcast who was quoted. And I was like, Whoa, like the tagging, just that little thing of tagging information on the internet was done by humans for so long.

SPEAKER_61: And I was like, this is incredible. Like you could really understand what the story is about and you don't need a human to do that anymore.

SPEAKER_05: Now humans tagging journalism stories and organizing them. That might be 5% of the job. It's gone. It's automated and there's no difference.

SPEAKER_27: And there's just going to be this continual 5% improvement on how to write a lead sentence in a story. Or I did a bunch of research on event spaces for the all in summit and, uh, um, event managers, party planners. Cause we're looking for party planners. We like to use different party planners, one for each night. Um, and then we look for like epic locations. And I started putting the locations in. And I think in an hour or two of me doing that and brainstorming, and I'm not perfect with my prompts, but I'm getting really good at them. I had done what would normally take somebody a week, like, uh, you know, a 30, 40, $50 an hour employee. It was a week's worth of their work done by an hour or two with me. And, uh, then I just shared it with that person. And with the shared GP, now that you don't have to share GP, I just shared it with them. Have you had any moments like that where you figured stuff out long before handing it off to somebody?

SPEAKER_90: Um, yeah, I, I think I'm very, very self-sufficient with, with chat GPT in these days. And I'm, I'm also using the Google generative search. Have you seen that?

SPEAKER_216: Uh, no. Tell me what you're talking about.

SPEAKER_42: So, so I've been approved for Google and I can probably demo this quickly. So I'm in Google right now. And what are we in search for? What are we in search for?

SPEAKER_66: What are some movies like Blade Runner?

SPEAKER_187: So Google now, if you're approved for it, you get this, get an AI powered overview of the search. So here's the basics is Blade Runner.

SPEAKER_42: That didn't answer the question at all. It says, well, I guess it did. 10 movies like Blade Runner 2049. Um, not Blade Runner the original. So let's hit the generate and see what it comes up with. So Blade Runner 2049. Dune. The Matrix. Dark City. I mean, this is great, right? Um, and then you can ask a follow up. What's the most famous Blade Runner scene? And the AI goes and generates an answer for you. So instead of going through websites and trying to find this information, you can, you

SPEAKER_92: can just, uh, use the generate AI. So what does Roy say at the end of the Blade Runner?

SPEAKER_173: Hmm. Like tears in the rain. Yeah. Yeah. Yeah. Well, this mom's been lost in time.

SPEAKER_42: So, so, so what's happening, what's happening fundamentally here, Jay, is that AI is now,

SPEAKER_78: instead of like the current paradigm, I say current, because AI is not, is kind of the next step. The current paradigm is you go to Google, you type in a string and it finds pages that match

SPEAKER_42: the words that you've typed in. It doesn't contextualize it very well. It doesn't understand what the, um, what the question means, what's it's, what it's asking. It's just trying to match those words. With generative AI, what it's doing is it's saying, oh, okay, Vinny's asking about this movie, which we know is Blade Runner and similar movies to it. And then let's go in knowing that we've read and indexed all these pages. Let's just give him the answer instead of having to give him links where he has to go look for the answer.

SPEAKER_86: So they're actually taking a, they're taking a step out of the process in a big way and they're saving tons of time. Um, I I've been using this for a lot of personal medical research. I found out that I have a, um, you know, genetic markers for, for potassium deficiency. So I've been doing research on what, you know, what, what I can take for that, what dosages. And I'm actually not even using Google anymore.

SPEAKER_42: I'm just using chat GPT and, and, and, uh, even this Google AI, you know, uh, search stuff. It's really powerful.

SPEAKER_17: Google autocomplete, uh, in search, you know, where you type in Vinny Lingham and then it's like space and it's like net worth, why all this like creepy stuff comes up.

SPEAKER_61: You're like, really, this is what you people are searching for. It's going to now. It knows what your next question is.

SPEAKER_17: And it's going to go well beyond that to, uh, let you ask follow-ups. So I just asked it, um, explain blade runner main beams to me as if I'm a seven-year-old.

SPEAKER_27: And it's like, what makes us human? Blade runner explores the questions of what makes us human. The replicates of the film are almost indistinguish movements, but they are not considered to be human because they were created in a lab.

SPEAKER_17: It's like really amazing. Um, uh, and then the follow-ups, you know, uh, what is the main plot point of blade runner, et cetera. You can see how this would keep you from clicking on the blue links below it.

SPEAKER_27: And that's, I think what everybody said the threat would be, but I don't think this is going to be a problem for their advertising because I think they're still on the high value. One's going to be able to, if I typed in, what's the best Greek food in the Bay area? Um,

SPEAKER_235: Kokari.

SPEAKER_27: Kokari. Kokari.

SPEAKER_182: Well, Mykonos, Kokari, uh, let's yeah, Evia should come up. And, um, yeah, didn't do a great job on that one.

SPEAKER_05: But very interestingly, they've now, oh, this is interesting. So what's interesting about this is you see this generative AI experiment here. It's not just giving you a chat response. It's pulling the, it's pulling in maps and it's pulling in, um, my location, uh, in the Bay area.

SPEAKER_38: It's, it's doing some pretty interesting things here. Um,

SPEAKER_237: I mean, you can't not have Kokari and Evia on that list.

SPEAKER_240: No, what's the highest rated Greek food in, uh, within a hundred miles of San Francisco. This would be more interesting.

SPEAKER_51: Kokari number one. There you go. Okay.

SPEAKER_243: Okay. Nick, the Greek Euro. So it got some, I mean, this has got work to do, but yeah, it's getting there.

SPEAKER_245: Finn can't spill coffee on a white shirt or wave at someone who wasn't waving at them or burn its mouth on hot pizza.

SPEAKER_28: But Finn can resolve half of your customer support tickets instantly before they reach your team. What's Finn? Finn is a breakthrough AI bot from intercom designed for customer support teams and ready to put other chat bots out of work. It learns your entire knowledge database and has the ability to carry conversations. And remember context and nuance while slashing your resolution times and support volume. Meet Finn, a breakthrough AI bot by intercom ready to join your support team today. Visit intercom.com slash Finn.

SPEAKER_238: Tell me the most expensive steak you can buy in Los Angeles. No, sir.

SPEAKER_246: Egg steakhouse. Unfortunately.

SPEAKER_38: Interesting. Cut Wolfgang Puck's Michelin star. I don't know if that's correct. No, no, no, no, no.

SPEAKER_247: They, they, they, they, they, they, they. They've got a thousand dollar steak. Yeah. The, yeah.

SPEAKER_76: A thousand dollars gold, the gold. Yeah.

SPEAKER_250: Nonsense. Yeah. Yeah. I think there was, I think the generative AI here on Google. His business is in trouble, dude. It's trying to see.

SPEAKER_253: His business is in trouble. His business is in trouble. After the whole World Cup thing. Oh, I'm shocked. No, like I haven't gone back.

SPEAKER_60: I used to go. I used to go and, you know. After one thing? What happened to him? Oh, when he was like taking the, the World Cup and standing in front of Messi and trying to like, he's annoying the players. He was not even a player. And he's, did you never see these clips?

SPEAKER_205: No.

SPEAKER_256: It's open.

SPEAKER_60: Yeah.

SPEAKER_258: At the World Cup. He was acting like a maniac.

SPEAKER_260: Grab it. Grab it. Oh, he's acting like a maniac. I mean, people chewed him out. He's, he's at the closed businesses now. He's had a bunch of stores closed down in New York because, because he was so embarrassing.

SPEAKER_59: He was so embarrassed. He was so cringy. I mean, he was taking the, the, he was taking the, the trophy away from the players,

SPEAKER_60: kids and stuff. And like, and then I'm like, who is this guy? Why is he?

SPEAKER_265: What does Solpe have to do with the World Cup? He's not a player. I mean, he's just, he's the famous restaurant. How did he even get near the World Cup? I got to see this video.

SPEAKER_266: They all, they always eat it. Okay. Check this out.

SPEAKER_270: All right. Show me what's going on here.

SPEAKER_272: Okay. He's saying hello. And he's asking him to point into here.

SPEAKER_182: He's trying to say hi to the folks and they don't want to say hi to him. They're like, yeah, whatever.

SPEAKER_190: They're chasing him again. And Messi's like, dude, leave me alone. Cause Messi ate at the restaurant once. I think.

SPEAKER_273: Oh my God. This guy is so annoying.

SPEAKER_187: He's so bad. He's cringy. Oh, wow. He's not supposed to have to work up trophy. And he did. I mean, there's another clip of him taking away from the one kids. Yeah. He's like, Oh my God.

SPEAKER_17: Yeah. I never liked the guy. I'll be honest. I never went. I never would go.

SPEAKER_96: Um, if yeah, I mean, I've been, I've been twice and the food was really good.

SPEAKER_60: So I went back and this is like before the world cup, the food was actually really good. I got the thousand dollar steak.

SPEAKER_00: Did you have anything? I mean, come on.

SPEAKER_280: Did you, or didn't you, it was my, it was my brother's birthday and he wanted this thing.

SPEAKER_60: Yeah. Yeah. It wasn't my choice. He wanted it. I bought it for him. And it was a good photo phrase. Instagram.

David Friedberg: Yeah. It was like for Instagram. But if I, if you got that steak or you went to a real steak house, like Miller and locks

SPEAKER_17: and you know, you, you, you, you ate it, it wouldn't be, you would, you would pick the

SPEAKER_272: Miller.

SPEAKER_92: It was the food, the food was the food is good. It was good. Like there's no question.

SPEAKER_66: Did he run the salt down his sweaty arm? He wasn't there.

SPEAKER_285: He, he wasn't there, but. I have another question about that. It's a bit of a show. We were in Vegas. It's a bit of a show.

SPEAKER_05: Do they send somebody out who looks like him? No.

SPEAKER_06: To do the whole thing with the salt down their arm? Do they do that? Or is only he allowed to run salt down his grimy arm? Yeah.

SPEAKER_08: No, no, no. They all do that.

SPEAKER_60: They all do the salt thing. Yeah. Oh my God. The whole thing is, it's a show. So we were in Vegas. We're having dinner there. I understand. It's a whole show. The food is good.

SPEAKER_17: I would have considered participating in it. And, uh, as long as I wasn't paying since I got to here, uh, you, uh, have any thoughts on this?

SPEAKER_182: Um, I, I made some comments on Friday about this crazy behavior by rich people, uh, vis-a-vis the submarine going to the Titanic. Uh, did you see my tweets?

SPEAKER_17: I didn't see your tweet, but I know you have an opinion. So I'm curious.

SPEAKER_294: Nick can pull it up quickly. Um, what was your, what was your take on it?

SPEAKER_17: Generally? I mean, you're somebody who's done okay for themselves and you like to enjoy the finer things in life. Would you ever consider doing something this reckless? I mean, witness.

SPEAKER_78: I personally would not.

SPEAKER_42: That's not my style, even like going into space. I'd have to go after the thousands, like flights at least. And there's regulations and whatever else. I just wouldn't put myself in that situation, but that's not the point. And Nick, if you put up my tweet, this tweet got a lot of like controversial sort of responses and we can probably scroll down to some of them, but this is what actually got me going. I was like, guys, these people like died. Yes. And all we're doing is joking about it and making some, like. So weird. Where have we gotten to?

SPEAKER_60: And the responses were literally like, there was one guy who said, uh, if you scroll down a bit more, I don't know, Peter.

SPEAKER_42: Uh, oh yeah, this is a G each. Okay. So he goes hundreds of immigrants drowned in the coast of Greece because of the actions of the coast guard. No one bats an eye.

SPEAKER_60: So the people to blame was sensation. He's needed to blame. But, but my point is no one's making jokes about these things. Yes.

SPEAKER_301: There's two different issues.

SPEAKER_05: He makes a valid point about what should be covered by the media. The media covering did not cover hundreds of poor immigrants, uh, that drowned off the coast of Greece because poor immigrants, but going to Titanic.

SPEAKER_61: Which there was a movie based on and an experimental sob by billionaires. That's much more, uh, sensationalistic.

SPEAKER_307: I mean, there was also Schadenfreude in that. Schadenfreude. Yeah. There's a lot of Schadenfreude in this one.

SPEAKER_309: And the thing is like, some of the comments on, on that tweet thread were like, oh, no one really cares about these billionaires.

SPEAKER_60: I mean, come on people. Like seriously, does someone's wealth determine their value?

David Friedberg: No, it has nothing to do with, I think that's the other thing. And the humanity.

SPEAKER_314: And they're humans. Like these are like, you know, our brothers and sisters on earth.

SPEAKER_38: I, the thing that made me crazy about it.

SPEAKER_61: You didn't hear my little rant on Friday, but I tried to make the point to people, especially because you and I will know people who will go from having no money to suddenly having a lot. Right? Like professional athletes go through this. Founders of companies go through this.

SPEAKER_27: Or sometimes you just hit some crazy home run and you can try a bunch of different things in the world that may not have been available to you the very, the previous day. Uh, and you gotta be thoughtful about this. And, um, I think there's like, I was thinking about it over the weekend.

SPEAKER_38: Cause I've had a number of conversations about this, uh, this toxic wealth syndrome where people take increasingly risky behaviors. I think a lot of it has to do with chasing dopamine and chasing Instagram photos and status. And some combination of this and this chasing of dopamine is particularly dangerous.

SPEAKER_17: You know, if you look at people's tick tock behavior, they're literally getting the funniest moment in a Sopranos episode or the craziest moment in a horror film, the craziest, whatever sexiest, most dopamine releasing moment.

SPEAKER_26: And people are chasing dopamine and they're chasing status on social media and people taking selfies. Taking selfies on cranes, right? Uh, or climbing mountains without ropes. All of this behavior is starting to become like some dystopian science fiction film.

SPEAKER_61: I think demolition man was the one where they were, um, involved in like a game show. No running man was the game show. Yeah.

SPEAKER_17: Running man where Arnold Schwarzenegger is doing all this crazy, um, stuff to kind of, um, you know, reduce, I think his sentence.

SPEAKER_61: And I think we're in like a running man era of people are like, oh. I can go on to, you know, Nassar or whatever and get a thousand dollar gold steak. And it's a show. And I put it on my Instagram. Great. Nobody's harmed. No harm, no foul. Oh, I can go on the edge of the grand Canyon. Oh, I can hop the fence.

SPEAKER_26: Oh, I can with the tiger on the other side of the fence. Like people are doing increasingly stupid things to get some dopamine hit or some release on Instagram. This is not a way to live life.

SPEAKER_27: And then the pinnacle of this, I don't know if you saw this Vinny was, and this is so tragic. A bunch of kids were on a boat celebrating their graduation. And, and they're going, I think they went off Florida to the Caribbean and they dared this kid to jump in the water in the middle of the night on the Caribbean in shark infested waters. He jumps in. Sure enough, there's sharks in there. He, he basically, they see the kid like dart away. I think he saw the shark and he darted away and there was no way to get him. He went out into the undercurrents of the sea, probably eaten by sharks. And I had this discussion with my 13 year old. And I was like, this is why you don't make crazy decisions and you have parents because your frontal lobes are not fully formed yet. Hmm. For the love of God, teach your kids, show them these videos of kids doing stupid stuff that ends terror terribly show them them so that they can understand life is precious and don't do stupid things. Yeah. Um, and as adults, you supposed to protect your kids. And I, I, you know, listen, I don't want to speak ill of the dead here, but if you're a parent and you take your child on a submersible experimental, anything that's dangerous. And then they put, Hey, this is an incredibly high risk behavior. And then you put the word experimental in front of it. No, I'm not taking my kids. Hella skiing. I'm not taking them down to the Titanic. And if you put the word experimental, hella skiing or experimental and Titanic together, that should just be alarm bells going off. Protect your child at all.

SPEAKER_327: Protect your children.

SPEAKER_90: Do you remember those planes? I can't, I forgot what they were called. They were like single. The eclipse?

SPEAKER_42: They were flying out of Napa or I went with a YPO group, uh, to Napa. It was five years ago. And they had these, they took us to the factory.

SPEAKER_294: They were making these like single pilot planes. You can go in and fly them yourself.

SPEAKER_51: I know which one you're talking about. There's one of these killed. Um, yes. A pitcher or something. Yes. Yes.

SPEAKER_294: Someone died in one.

SPEAKER_42: And literally there were like, everyone's lining up to go and fly these things. And I'm like, I'm not going on this thing. This is not a commercially like ready product.

SPEAKER_58: These guys are trying these things.

SPEAKER_331: Icon A5.

SPEAKER_58: That's it. That's it. Icon A5.

SPEAKER_334: That's the one. That's the amazing plane. It wasn't the A5. It was, was it, it was the A5 or was the one before that?

SPEAKER_27: I, I follow an incredible YouTube channel called the Blanco Lirio channel. Um, and I actually give this guy like five bucks a month for his Patreon. Cause I like his video so much. And I think it's an important thing he does. Um, he, uh, has a YouTube channel Blanco Lirio and he is an expert aviator. And, um, he did a whole thing, uh, about how dangerous these, uh, uh, a fives are. And, you know, I'm all for innovation, obviously, but my Lord, um, the, these a fives are incredibly,

SPEAKER_240: incredibly dangerous. Um, and. Okay.

SPEAKER_187: It was, it was the a five. You're right. Okay.

SPEAKER_42: So 2017. And so the, you know, they, they called it a sports car with wings. They had say two fatal crashes in one year. So like this is, so I had the opportunity of flying this. I was right there and they were offering it to me to fly.

SPEAKER_339: And I'm like, no, you would fly it alone. No, no, no. I refuse. No, no, no. I think you fly it. Is it?

SPEAKER_205: I think there's a pilot in there.

SPEAKER_216: I think they have a pilot. Yeah.

SPEAKER_205: I think you'd have two people. Yeah.

SPEAKER_341: Oh, no, no.

SPEAKER_216: It's a single person plane.

SPEAKER_95: No, there's two seats there. I mean, I think your, the goal of this is for you to be up and running in one of these things on your own very quickly.

SPEAKER_61: Yeah. And they do kind of ride, um, having, I've driven motorcycles and like you, once you get the hang of a motorcycle in the first hour or two, you feel invincible, the thing grips,

SPEAKER_95: you know, it feels great.

SPEAKER_347: Jason, this was six years ago. Yeah. This was six years ago.

SPEAKER_78: They've improved it a lot. I'm sure since then, I think they've fixed a lot of the issues, but like when you go into something new like this and you're one of the first people to do it. Yeah. No. You, the amount of risk you're taking is, it's an inordinate amount of risk.

SPEAKER_272: Yeah.

SPEAKER_17: You, um, it's an inordinate amount of risk. And you know, just, if you want to be a pilot, it's a full-time job.

SPEAKER_05: If you want to be an experimental pilot, that is a career multi-decade, um, designation

SPEAKER_26: you earn over decades.

SPEAKER_38: You, you shouldn't be doing anything experimental and dangerous, leave it to the pros. I mean, unless you've got a death wish or something and you, you know, you're, but I

SPEAKER_05: really think that really upsets me about this whole thing is I've seen videos since then. And watch James Cameron talk about it.

SPEAKER_38: And I don't want to obsess over this, but it's, I think it's like a super important topic for people to really think about is what risks are worth taking. I'm a big risk taker, but some risks are just not worth taking.

SPEAKER_27: And you I've seen now multiple presentations by the CEO founder of this company, and he's a technology founder. So I think this is fair game here in terms of talking about on the swing startups. You could take risk. And if he was going down there on his own and he wanted to assume that risk. Okay. But once you start taking passengers and then it turns out, and this is the stuff that's coming out now that he was up against it with funding. It didn't have money was cutting corners. Apparently. Um, and that's three controller.

SPEAKER_351: I mean, geez, at least use a five. I mean, or have it wired.

SPEAKER_56: Like, I don't understand why it's not wired in there. Like, what if there's interference?

SPEAKER_354: Was it, was it control? Was it, was it wireless?

SPEAKER_27: It was a wireless controller. It was a wireless controller. Yeah. I'm like, can you put a cable on it? Like just being an it guy. Can we have dual re and he said they bring an extra one or whatever, but he supposedly was having financial problems. So now this is what's going to come out. This is my prediction. They knew there were problems. They needed the money. They were trying to get that the billionaire or two billionaires who coming on this thing. They needed the money to keep their operation going. And, you know, unlike if you were a software company and you're like, you know what? I'm going to sell this enterprise software to this enterprise to, you know, increase productivity or analyze their data. Oh, it doesn't work. And okay. I'm sorry. We're going to do a make good. We're, we're getting there. There's no make good. You can make here. You know, you can't give people, you can't give people back their lives. You could give them back their money. That's a, that's, that doesn't mean anything when, you know, a child does. I'm so. My heart goes out.

SPEAKER_187: My heart goes out to the, the kid, obviously the parent, the mom or whatever family, the rest of the family, because he didn't want to go on that thing.

SPEAKER_78: He was, he was, he was not interested in being on that. He was, and it was, he just did it for his father and his father should have known better. This is the problem with Jake. Like once people make inordinate amounts of money, they tend to think they're invincible.

SPEAKER_17: That is the arrogance that comes with wealth. And I, I addressed that on Friday as well. Um, you make a bunch of money, the people around you, all of a sudden people, you find a bunch of people around you who think you're great. And you're all of a sudden you're a foot taller, you lost 20 pounds. You're funny. Uh, and, uh, people, uh, wanna have dinner with you and it's because they want your money and people correlate great wealth with great intelligence, great success. And often, you know, there, there are correlations, um, but it doesn't mean that you have great judgment. Uh, it doesn't mean that you're invincible and you're exactly right. There is an invincibility here is, um, yeah.

SPEAKER_182: Hey, breaking news. Google's deep mind. CEO says it's next algorithm will eclipse chat GPT.

SPEAKER_163: Demis Hassabis says the company is working on a system called Gemini that will tap techniques that helped alpha go defeat go champion 2016. So deep minds Gemini, which is still in development is a large language model that works with text and is similar in nature to GPT for.

SPEAKER_182: That works with text and is similar to Chachi forage powers. GPT for, but how so. Hassabis. Sorry for mispronouncing that, uh, says his team will combine that technology with techniques used in alpha go.

SPEAKER_163: Aiming to give the system new capabilities such as planning or the ability to solve problems. At a high level, you can think of Gemini as combining some of the strengths of alpha go type systems with the amazing language cables of long, large models.

SPEAKER_17: We're having some new innovations that are going to be pretty interesting. Uh, this is to me is the home run of all home runs. Because Vinny, if I'm reading this correctly, the language model gives you the answer. Or, you know, kind of interprets what you're saying, but what alpha go did was it understood games.

SPEAKER_26: It understood competitions. It understood how to win competitions. So this is distinctly different than just spitting out an answer.

SPEAKER_05: You could say your goal is to be the greatest day trader, uh, by shorting stocks on the stock market. Go make trades. Go make trades. And you will every time you make a trade that makes money, learn from that and, and find more trades like it go. And you can increase the amount you invest, you know, at this rate or whatever. You can just let this thing go like they've let it go to play video games.

SPEAKER_38: And this could be transformative in terms of automation. What do you think Vinny on the breaking news here? Yeah.

SPEAKER_90: Yes. I, I agree that I think for my experimentation and usage of, of it up to now, I, I mean, I'm biased.

SPEAKER_42: I, I like the use case of having it solve medical problems because I think people, you know, when you asked, so yes, what I found very difficult to use AI forward. I think, and it's all, it's problem solving, right? It's the same thing.

SPEAKER_78: So whether it's problem solving for games or problem solving for, for, uh, trading, et cetera, it's the same. Um, uh, you, you, you, you try to solve a problem when it comes to medical.

SPEAKER_42: When I use, um, uh, chat GPT and bar or whatever else, it's very much the extracting data from what they've read, but they're not actually thinking through it. Right. And so I've had to lead it, lead it on to certain conclusions. And I would love for this to say, Hey, I have the following symptoms. I'm, you know, I, I'm feeling a bit bloated. I have, um, you know, whatever, like a couple of symptoms. And I think I've got a potassium deficiency. What, uh, what, what treatments or what natural remedies could be used or what other problems could I have that could not be, uh, you know, that could be happening here. Uh, and I think that like the ability to solve medical problems with people who have got lots of like symptoms has not been solved yet. So a lot of people, when you go to doctors, like I had some like nerve issues in my arms and stuff. You go to doctors, they don't really know, like they give you, they run these tests. They don't really like it's the medical industry is broken right now because every doctor has its own. They have the, the small little aperture that they look through. And if it doesn't fall inside of that, then you can kind of go to the functional medicine specialist. And they kind of look at more holistic views of the body and stuff, but all our bodies are so unique. And so I'm, I'm pretty sure if you had to come up with a list of symptoms for any condition that you're going through right now.

SPEAKER_192: And, and something unique that hasn't been found before. I want the AI to find these connections and solve these problems. And I think that would be very powerful for us.

SPEAKER_17: I think it's going to be amazing when the data gets in there too. And then in consultation with doctors, I think doctors are going to become better doctors. Cause they'll be augmented. They can't possibly know every edge case. No. If you had why, if doctors can become 10 times more efficient, what I would like to have is 10 doctors. And I use chat GPT, all my data is poured into it. It gives them some sort of dashboard and I have 10 doctors and they each give me a recommendation every month.

SPEAKER_05: Based on my new blood tests, my weight, my sleep patterns, and all 10 of them give me what they think I should do. And the chat GPT then feeds back to them. Here's what the consensus is that the person should do. What do you think? And now you have group, a group of humans analyzing what the, what the AI is doing. And they kind of work together in reinforcement learning to how do we make this person a peak human?

SPEAKER_61: Um, and this could be incredibly powerful.

SPEAKER_27: This is one of the things I think people. When we start testing this in order to trust it. I want to have doctors give opinions. AI give opinions. And then compare it to doctors using AI giving an opinion. And then, um, have another doctor or senior level or the, a doctor or, you know, committee. Look at the three or four answers and rate them and say, what was lacking? And this is where it's going to get interesting because when they would do, I don't know if you remember this, but there was a time when they, before OCD. OCR really worked well, they were trying to get a lot of documents on the internet. And so they would literally ship legal documents to India to have people type them in because they could just send them there by the boatload. Here's like 10 years worth of legal documents. Go ahead and get them in there. What they would do is they'd have two people because labor was cheap and they needed to have high fidelity. They'd have two people type the documents in. So they'd be sitting there typing, turn the page, type it. And then once those were in the computer, they would look for where people, uh, weren't, you know, correct. So if somebody typed in Vinny and I typed in Vinny with one N, it would highlight that for somebody to look at it. That person would see the document, a third person and look at the, oh, why does one have two ends one have one end? Oh, it's an M. They're both wrong, whatever it is. And those kind of edge cases. Well, AI is doing that particularly well. And humans can do that with the results. It's actually what's happening with training data. When, when a Tesla or some cruise hits an intersection that that doesn't understand it, it disengages or it has a problem or it stutters. All of those intersections get sent to a group of humans who look at and say, this is the proper way to navigate it. And they literally, I don't know if they hard code, but they, they do reinforcement learning, I think.

SPEAKER_17: And in some cases they might hard code. If there's an error, here's how to navigate the specific intersection.

SPEAKER_05: And I think that's, what's going to make a tipping point in self-driving in the next year or two. I think we're going to hit a tipping point. Oh, we're very close.

SPEAKER_379: We're very close.

Chamath Palihapitiya: It feels like we're very close to a tipping point because if enough P if enough people are using Teslas and cruise and whatever, and. Well, they can talk to each other.

SPEAKER_42: You realize that the channel that these cars have got an open channel where they can broadcast their movements to other cars, but no one really uses it yet. If these cars can come together and say. I use it all the time.

SPEAKER_86: No, no, no. Well, how?

SPEAKER_62: I use self-driving all the time. I'm saying. No, no, no, no. Literally, I would not use Teslas self-driving.

SPEAKER_42: There's a radio frequency channel, as far as I know, that if a Tesla is going to change lanes, it can broadcast those changing lanes. Oh, really? Yeah. I wasn't sure if they were doing that. I read about this a while ago. Yeah. It's not implemented yet. There isn't a standard yet. Well, there is a standard. I haven't known the details about this, but there's something around that that I've heard about in the past. And if it isn't, there should be one. So it'll be very interesting if you can have a situation where there are all these electric cars on the road that are talking to each other. And before that, the car goes left or right, it knows what the other car is going to do. It knows it's part of something, at least for the next 100 meters or 500 meters. It's able to, you know, like, I can see a world where these cars can self-organize themselves on the highway based upon max speed for this car is 50. This car wants to go at 60. This car is turning off in two miles. And it just intelligently knows, you know, they talk to each other and they know which way to go together. That's like maybe 20 years from now, 15 years from now.

SPEAKER_103: Interesting. I just asked chat GPT to tell me about it.

SPEAKER_17: It was like, what you're referring to is V2V vehicle to vehicle communication. Uh, and, uh, it's called dedicated short range communication DSRC. Uh, a type of wifi more recently develops a focus on cellular, uh, leveraging 5G. Uh, and the goal is basic safety messaging, uh, 10 times per second, uh, indicating the vehicle's speed, heading, brake status, and other specific traits.

SPEAKER_182: Emergency brake lights, uh, allows the vehicle to send a warning to follow vehicles when it breaks hard for collision warning intersection movement assist. That's interesting. This one is a driver when it's safe or not safe to understand and do not pass warnings. Uh, do not pass slower vehicle on two land highways, risk of collision with an oncoming vehicle. Oh, so your car is in front of mine and it's. Yeah, exactly. You can't see. So you shouldn't do that.

SPEAKER_42: This is like, well, this is the early days, Jake. Oh, we're like, we're like 10, 15 years from this being built up. Maybe 20 years, but it's going to happen eventually. I want to, I want to, I gotta go soon. So I want to show you some demos. Oh, yeah, go ahead. These are three pictures of me, of, uh, three old pictures, right?

SPEAKER_187: Uh, and so this is myself and my, my, you know, my middle brother. Where are you in that picture? I'm the, I'm the older one.

SPEAKER_173: Yeah. No, no, no. Where, I'm sorry. Where in the world are you guys in that picture?

SPEAKER_90: Uh, that probably was like in South Africa somewhere. I guess it's probably, probably my hometown.

SPEAKER_173: Let's talk about the family photo on the top left.

SPEAKER_187: The family photo, this is my, these are my, my, so this is my mom's family. So my, my, my grandfather, my grandmother, and that's my uncle and my mom and her sisters. Yeah.

SPEAKER_177: What was that the fifties or something?

SPEAKER_405: Sixties? This was early sixties.

SPEAKER_177: Early sixties. Wow. You can tell by the car with the white rim. Look at the car with the white rim.

SPEAKER_42: Yeah. Yeah. Yeah. And, and this is my mom in maybe her twenties. Right. So, you know, I got a collection of old family photos. We don't really like, you know, it's all black and white.

SPEAKER_187: Hmm. So then I was like, okay, cool. What can I do to, you know, what, what, what can AI do?

SPEAKER_347: And so what can I do? Um, what can I do? So I went to the service called colorize.

SPEAKER_42: So they allowed me to upload, uh, there's a limit that they were paid plans as well. And they've got a whole bunch of other features, portraits, et cetera, restoration, but they allowed me upload three for free. And look what they did. I thought it was amazing. Oh my God.

SPEAKER_187: So that's the one version of it. And then you can go to version two because it kind of predicts what the colors are going to be.

SPEAKER_72: Wow. Okay. So in, in, in this version, in the one version of thought that, um, the car was blue. Yes.

SPEAKER_187: And the other version that thought it was red. Yeah. Exactly.

SPEAKER_417: I wonder how it's doing that. Yeah.

SPEAKER_187: Um, and the same with my brother and I, it's like this one year is, uh, I think this was the, this was actually very close to the original color.

SPEAKER_42: Uh, that was, sorry, that's V1, V2. So I don't think we were wearing blue. I think we were, my mom, my mom loved this maroon color. So we always had maroon colors in the house and actually predicted it. It got the skin tone and the complexion. Right. And I thought it was pretty cool. And then the same with my mom, like a nice picture of her. And look at your mom.

SPEAKER_187: Wow. Yeah. They give two, two, two, um, picks over this one. Yeah. You can see a bit more discoloration. Yeah. And then the other, the other version more intelligent picks it up. Yeah. Yeah.

SPEAKER_423: But still, I mean, that took me like a minute, you know, to get this done.

SPEAKER_97: I mean, and there were services that did this or people who would paint over pictures. Yeah.

SPEAKER_17: Absolutely. Obviously the next step here is to upload, you know, a couple of hours of you talking to your mom and then, uh, have her voice. Yeah. They'll, they'll figure out how to make her voice to, uh, whatever she is there at 21 year old. And then you'll, uh, be able to have a conversation with your 21 year old mom, which gets really weird, but could be, you know, super interesting. And I think this is where I had, uh, I have two startups we've invested in. I don't think either one is public, so I won't say their names, but one of them made an AI version of me to read the ads here on this week in startups. And I was thinking about it, I would love to do have the ad reads.

SPEAKER_05: If, uh, one of our partners on the program wanted to localize the ad reads.

SPEAKER_17: So imagine, you know, uh, LinkedIn, uh, said, Hey, you know, Australians. Um, if you want to come to LinkedIn, Australia, we're having this LinkedIn, Australia thing, blah, blah, blah, blah. And so I can read the LinkedIn ad, but then it would drop in some Australia specific stuff, some Japan. You know, I could, and then another startup, um, is working on.

SPEAKER_27: Is working on me speaking in Spanish. And I think they shared a clip on the internet and then another company shared a clip, um, with me privately.

SPEAKER_05: So I think I'll be able to take this very podcast and have us speaking in our voices, but speaking in Spanish. So it will sound like Jake, I'll sound like Vinny, I'll sound like Sonny, whoever.

SPEAKER_17: And then we're going to make a YouTube channel. Uh, and I'm sure YouTube will build this as well, but, and have it built in, but I think it'd be very interesting to republish ourselves on a YouTube channel. Uh, on the Spanish language site and see if the, uh, it builds an audience over there or not. And if they tell us it sucks or not, cause I don't know if it's gonna suck or not.

SPEAKER_182: Uh, but they're, they're testing it supposedly in 12 different languages right now.

SPEAKER_38: That's a cool demo. What else you got?

SPEAKER_433: Replica. Oh yes.

SPEAKER_38: I had the founder on.

SPEAKER_433: Yeah. I have that. Um, I know she's been launching.

SPEAKER_38: She had a new prop, new product she launched. Um, so it's an AI companion.

SPEAKER_309: And I mean, I'll pull the demo. I think it's still very early days. I've played around with it a bit.

SPEAKER_187: I think it's cool. Um, and Nick actually had a good point. Like I think a lot of the, and I think it's probably from your conversation. A lot of people using this are kind of lonely or disabled or can't get out there and they need someone to talk to and they need a companion. And it's the same reason why, like, you know, you see in Japan and other parts of the world, people like have these, uh, you ever watch the movie, her.

SPEAKER_162: Yeah.

SPEAKER_437: It's just basically her in a box. Yeah.

SPEAKER_162: It's happening. Exactly. Exactly. So I created a, I created a, um, a, a replica.

SPEAKER_187: I, I called it Charlene, my wife's name. And so I'm talking to it and there you go.

SPEAKER_442: I still think you're cheating, but okay. Baby, I named her after you. Yeah. She's not me.

SPEAKER_60: I made her look like you too, but, um, you know, it's, it's, they have these coaching things you can do.

SPEAKER_42: So like gratitude and there's lots of upsells and paid, paid stuff. So I didn't pay for it yet. But I think it's interesting from an AI, if you can create these like AI people, like people, AI agents that know who you are, um, that can answer questions for you. You can get really intelligence. Like, you know, um, Hey, I ran a really bad day today. This is what happened. You know, uh, Bob at work was giving me grief. Like, Oh, it's an ongoing thing. You know, Vinny, you really need to report him to HR. Like that sort of thing. Right. Like a coach. And I think that's weird. I think where it goes to is these, these digital agents become some sort of independent. Coach. There is coach. Therapist. Because like people feel comfortable.

SPEAKER_452: A trusted friend. Yeah.

SPEAKER_60: Also, I think in the, in the cases where, you know, the sad stories of people have been

SPEAKER_42: abused, they're too scared to speak to anyone else. Right. So, you know, so if you can speak to an AI where it's not a real person, it's a confidential conversation. It's going to give you advice.

SPEAKER_184: You could say, Hey, I was, I was sexually assaulted yesterday. What do I do? Right. Do I go to the police? How do I deal with it? It could be. Yeah. Like, I think. High stakes.

SPEAKER_58: Yeah. Exactly.

SPEAKER_42: And look, when you're dealing with medical stuff, we're getting these sort of things. It obviously gets a little tricky and needs to be like supervised by psychologists and doctors and whatever else. But I think if we can build agents that can help people feel comfortable talking about their problems, you know, without the insecurity of it, it's great. If it can be helpful, that's great. I like the direction that they're going in here. Um, it's very warm and encouraging. I just think that for me personally, I think that the, the, you know, I don't want to chit

SPEAKER_60: chat to a bot. Like, but if I had, you know, even as a CEO, right, if there was a CEO coach in here and

SPEAKER_42: I go and say, yeah, I'm struggling with this employee in the company and they go, okay, what is this person doing? It's like, this is what they're doing. They're not playing nice with their colleagues, but they're an amazing performer. The work is great. I just can't get rid of them, but they, you know, you, you've, we've all had these people in organizations. Right. And like, who do you talk to about it? Right. You don't want to talk to, you know, the people on their team, you know, it's hard to speak to the managers sometimes because there's like a bias there and. You know, depends how it goes. Uh, I like this.

SPEAKER_17: I think this, I think you're exactly right.

SPEAKER_05: There's a frontline of discussions that what we're, I think what we're talking about here is there's a group of people who will go to a professional.

SPEAKER_459: Yes.

SPEAKER_05: And then there are a group of people who won't. Yes. So for people who will go to a professional, it's not for them, but for people who can't afford it, don't have access to it. Is this better than nothing, or is this better than talking to one of your friends? Yes. And if the technologists in collaboration with professionals can't make something that's better than going to a random person, a rando.

SPEAKER_27: So is all you have to do is beat rando advice to make this valid in the world. Yeah. And you can hit random better than random for sure today. Um, and then of course the criticism of this will be, well, it hallucinated.

SPEAKER_05: It gave you bad advice or whatever. Like if it has a disclaimer and it says you really need to talk to somebody, this will

SPEAKER_27: give you an idea of what your session might be like with a therapist, somebody who can deal with trauma, somebody who can give you career advice. So this isn't a substitute for that, but this will give you a simulation of that. I mean, we let people simulate, uh, war or being a criminal in grand theft auto. Like literally you could be a gang banger in grand theft auto and you can have that experience. You could do red dead redemption and be a gunslinger.

SPEAKER_05: Well, why wouldn't you allow people with proper disclaimers? Hey, this is what a therapy session might be like for you. This is what a career coach might be like for you. Um, but of course it's not. So click this button to go talk to somebody and here are your options. This would be amazing. So great, great catch there. I do think replica, um, is trying to upsell too much. I think what they should do is make it time based. I agree. They should make it time. Give everybody everything for 30 days, get them on the hook and or 15 days, whatever it is.

SPEAKER_17: Or, or maybe it's not, maybe they are, they, they, they're just experimenting right now. But my best advice would be let people have like 48 hours with it. And then, you know, make it time based, uh, you know, um, not fee, not let them understand how great it could be.

SPEAKER_463: You know, I think this is an interesting conversation and we can probably finish off on this, but, um, the, the, the drive to monetize AI this early in the process is, I think a little bit misguided. Of course. In the short term.

SPEAKER_42: Explain why. Explain why to founders why it's misguided. We, we, we, we've gone through this like Zirp policy for a couple of years. We've gone through, you know, very cheap capital for years. Uh, and even in the early days of Google and whatever else, I mean, they were making money. Fine. But there was still a need, there was still a need to sort of have the industry mature a bit more to understand what the right business models were. Like when search came out, no one knew what the right business model for search was. CPC wasn't even on the horizon. Google was losing. They had like 20 months worth of runway left, but they had billions of users or billions of searches a month. And so it took a while for them to sort of find the right model. They, you know, they bought, uh, applied semantics. They, they did a bunch of, you know, they copied overture of go to.com. Right. And they built out search and they monetize the product. I think by prematurely monetizing products, you, you lose out on the, the big uplift that you're going to get from mass model users, trying it. And the data. And the data. Exactly. I mean, you gotta get that data. Yeah. So, so that, so that, that I think is, um, is a critical part of like the cycle we're in right now. Yes. Unfortunately, capital is not available to everyone easily. Some people can raise capital. Some can't, some, some have to make profit and grind away. Um, I mean, just from my experience with Waitroom right now, we're a small team. We're burning a small amount of money. We're just grinding out features. The product's free. You can have free video conferencing on Waitroom. We don't have an hour limited or 40 minute limit, like zoom. You can do it because we just want the data. We want to see what features they're using. What AI features are popular. Feedback from customers. That's more important than trying to sort of prematurely monetize the product. And what I'm seeing with all these products is, and I get the reason, right? Money's tight. We're in a tough situation, but be thoughtful about if you need to make money off the product. If there are underlying costs that you have to cover, be thoughtful of not price getting your product too early on so that people who would be paying later on never get to the point that they're willing to pay. Hmm.

SPEAKER_17: Exactly. If you think about the Zerp environment, people went crazy and didn't even think about monetization.

SPEAKER_05: They didn't even think about their spending. Yeah. And now they're so obsessed with getting money in the door because they're afraid. Exactly.

SPEAKER_475: The pain dilemma swung too far. Too far.

SPEAKER_05: Yeah. I think it's well said. It's a really important thing for people who are founders. Great job. You brought some great demos.

SPEAKER_27: We talked about some great news for folks who are running businesses. I want you to drop everything and go to weight room.com and sign up for Vinny's service.

SPEAKER_26: And then, um, I want you to come up with the three things you like best and the three things that suck. And then I want you to at mention Vinny. Vinny, what remind everybody of your Twitter handle?

SPEAKER_477: At Vinny Lingham on Twitter.

SPEAKER_27: At Vinny Lingham. Uh, and give Vinny Lingham some, uh, I'm sure he's Vinny at weight room.com. Give him some feedback on his product. What could be better? What's great? Uh, and, uh, let's get him some early beta users here. Finally, um, Um, we are doing founder university, uh, again on starting. It's I guess this is, uh, our 12 week course is starting again, July 31st and then October 23rd. What's our founding university course. It's 12 weeks. It's basically free. Uh, you pay 500 bucks Vinny when you start the program. If you come to all 12 Monday sessions, you can miss one. Probably just ask for a forgiveness, but if you come to all 12. Talks. We give you, we charge you back the 500. Do you know what our completion rate is now?

SPEAKER_17: Our graduation rate?

SPEAKER_481: 100%

SPEAKER_17: 94%.

SPEAKER_481: Wow.

SPEAKER_61: When we gave it for free, it was like 5%. So it turns out if we, you give us 500, we pay you 50 bucks every time you come to the course essentially.

SPEAKER_05: Uh, but what's happened is, uh, we've had about half the more than half the teams that come to this and we try to have builders come to this. Uh, 250 builders come to each cohort. We do it four times a year. Um, half of them were more aren't even incorporated. We watch the progress Vinny and we give 10 to 20 people in this program, $25,000 checks as investments from us.

SPEAKER_61: And we become the first investor in your company, which is something I always have a lot of pride about doing being the first one to put 25k into these companies. If you want to join us, apply by going to founder dot university. Uh, you can have an idea. We want you to be a builder. So UX design developer, growth hacker, can be a copywriter marketer, but you gotta be a builder. We don't just want idea people, or you can be an ideal person, operations person with a builder. We give preference to people who are two person teams. So go check out founder dot university.

SPEAKER_27: Uh, and if you want to read the deal memo for my fourth fund, we have a lot of plugs here at the end. Um, I tried to share Vinny, uh, the deal memo that I send to like top LPs, because I like people to read my deal memo, how I'm thinking about how I'm going to deploy the fourth fund. And you can read it at launch.co slash memo launch.co slash memo. You can read the launch fund for deal memo. This is my strategy. Now, why would I give the strategy away Vinny? You're probably saying we're not in competition in the early stage. It's us. Y Combinator tech stars. Nobody's really in competition pair VC. Uh, um, Sequoia's got their job. Um, Sequoia's got their new, um, they're experimenting with a new, uh, accelerator type program. All these companies need 20, 30, 40 investors in their first two or three rounds of funding.

SPEAKER_38: So we're really not in competition with anybody. We're in collaboration.

SPEAKER_245: So go read the deal memo. And if you want to be, uh, an LP video, you and LP and my funds. I don't know. Maybe.

SPEAKER_489: I invest in some of your, your deals. So let's see. Let's see.

SPEAKER_05: Maybe I get a 250 K check from you right now.

SPEAKER_27: You spend a thousand dollars on a steak with, uh, with gold leaf on it. Maybe I get you, I'll lend you as an LP and my fund.

SPEAKER_494: Uh, we, we can chat about it.

SPEAKER_493: Okay.

SPEAKER_494: Let's read the deal.

SPEAKER_495: Yeah. Yeah. I look at the deal. I actually liked the deep deep Sentinel security one that you did. Ah, yeah.

SPEAKER_496: Deep Sentinel is a great company.

SPEAKER_495: What a great idea.

SPEAKER_177: And, uh, speaking of AI, I gotta have him on, but I think, you know, those companies are going to do really well.

SPEAKER_27: If you haven't seen deep Sentinel camera, which I have at my offices cameras that have two-way microphones. And somebody comes up, they know if it's Vinnie and Jason, if we work in that office every day, but somebody comes up and it's Susan or John. And they're like, Hey, can I help you? Not like in an aggressive way, but if it's three in the morning and you're wearing a hoodie and you're trying to crack the door open, like, Hey, please leave the vicinity. We're calling the cops. They're on the way. And it can have an alarm go off. So they have like virtual monitoring through a two-way, essentially nest cam. Uh, but it's their own hardware, uh, at this point and, uh, incredible company. Well worth checking out.

SPEAKER_182: And I think obviously AI is going to be really interesting as well, uh, for those type of companies. All right, everybody.

SPEAKER_498: We'll see you next time. Bye bye.

SPEAKER_500: On behalf of the producers and the partnership team. Thanks for listening to episode 1768. We'd like to take one more time to thank our partners. Notion. Try Notion projects for free today at notion.com slash twist. LinkedIn jobs. Post your first job for free at linkedin.com slash twist. And Intercom. Try Finn. Intercom is a new AI customer support chatbot at intercom.com slash Finn. If you're looking to become a partner of this week in startups, you can email Hannah at Hannah at launch.co. That's Hannah at launch.co. Thanks for listening.