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>> Today there is uh a chart that is tearing up the internet about AI adoption potentially going down. This is from the census.
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Uh the census says that the AI adoption rate by firm size.
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They do this poll every two weeks.
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Um and Apollo the uh giant private >> Apollo management. >> Yeah.
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Apollo um on their Apollo Academy blog has a post AI adoption rate trending down for large companies.
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The US Census Bureau conducts a bi-weekly survey among 1. 2 million 1. 2 million firms.
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And one question is whether a business has used AI tools such as machine learning, natural language processing, virtual agents or voice recognition to help produce goods or services in the past two weeks.
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Recent data by firm size shows that AI adoption has been declining among companies with more than 250 employees. So >> is that good?
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>> It's I mean I >> it's good for your job.
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>> There there are a bunch of different reads on this.
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So I think it potentially could be good. I don't know.
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Um I'll walk through kind of my my thinking on it.
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U but there's a bunch of interesting stuff in here.
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So, um, so this, uh, like the charts going viral because kind of everyone's been feeling that AI has been like overhyped and like the valuations are crazy and so people are hunting for top signals as we have, you know, a month ago. >> Top signal enjoy.
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We put out we put out uh, we got to play the video. >> Oh, yeah. Yeah. The hype cycle. >> It's released. >> Oh, it is. It is. Yeah. Let's pull that up. Let's pull up.
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>> So, let's pull up the video.
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>> The video that uh, Tyler just posted.
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Did you post it from the TVPN account? >> Yes. of the hype cycle. We'll play that.
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But people have been hunting for bearish signals about AI because it feels too good to be true.
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Everyone's getting rich and you aren't.
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It has the same sort of economic trends as the as the crypto boom as a few other booms.
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And so um people are are are hunting for data points and this is one of them.
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But let's first review the Gartner hype cycle video that we just put out.
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>> I think Nvidia is undervalued.
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It may not mean nothing to y'all, but understand nothing was done for me.
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So I don't plan on stopping at all. I want this forever. Might never mind. Never mind.
2:29
Shut your down in the mall. It's girl. She the one for me.
2:32
And I ain't even planning to call.
2:36
I want this forever mind. Never mind. Yeah.
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So, everyone's been hotly debating where we are in the Gartner hype cycle.
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It feels like >> some people call it the TBPN hype cycle.
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>> We'll give Gardner their credit for this one.
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Um, so people have been hunting for for potentially bearish signals, bearish data points.
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Uh, there was that uh that uh result for meter that showed that developers that were using AI uh coding tools were actually less productive.
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They thought they'd be 20% more productive.
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>> And I saw something I saw something else.
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I I don't know if this was misinformation, fake news, somewhat real or or or just anecdotal, but there was somebody that was saying uh uh devel developers are producing more like a lot more code, but but like an order of magnitude more security vulnerabilities.
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>> Yeah, something like they're producing twice as much code, but 10 times as many uh 10 times as many security vulnerabilities.
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And I know the post you're going to talk about now, it is in the stack, but it's deep. post.
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I'm going to I'm going to try to find it, but it's it's somebody searched like vibe coding cleanup specialist and there's people on on LinkedIn now that are that are finding employment around cleaning up vibe coded product.
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>> And so if you're worried about losing your job to uh to vibe coding, pivot to vibe coding cleanup to bull market.
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There's always a bull market somewhere.
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>> Um guys, can we pull up the chat on the uh TV if possible?
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Um anyway, let me uh run through this.
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So uh from the data uh the chart is going viral because it's dropping off and it looks bearish for AI and thus for tech America for humanity broadly.
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Um everyone is saying please consult the Gartner hype cycle graph.
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Uh there is a question on where we are on the Gartner hype cycle.
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Um I've been saying that maybe we still have a ways to go up.
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I I can't tell if I'm on the left side or the right side of the graph at this point.
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like I've kind of already been through the trough of disillusionment.
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And so >> when was that for you?
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>> That was probably 2024.
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2024 was was when it felt like everyone was saying AI is so insane.
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AI >> you were you were going like this in the mirror like the Joker >> a little bit because uh you know AI is so insane.
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so insane. But then you know you go back to the chat GPT moment that was 2023 >> uh Whimo you know really like rolling out to general that was 2023 >> there there wasn't as much there was a lot of hype but there wasn't as much like actual progress it felt like it felt I don't know um so maybe now we
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didn't have 5,000 AI agents for blank >> I don't know just just as I process the last few weeks I feel like I'm climbing up the slope of enlightenment I don't feel like >> posting red posting and showing how he's getting value across >> that feels like the plateau of product
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that feels like >> that that's plateau we're plateauing and we're being productively >> exactly and and even the narrative of oh is AI progress plateauing that's not is it going to crash yeah that's not the trough of disillusionment that's the plateau of productivity so anyway people people love to you know give their takes
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anyway >> I think that I think the um the real an interesting study I'm sure there'd be flaws with it but but if you went to companies and you'd say like how much would I have to pay you to not use AI for the next 12 months >> across your entire company? >> Yeah. I I think you could argue that >> Yeah.
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>> Yeah. I I think you could argue that like in engineering orgs specifically in terms of like things like fraud detection and areas that uh there's probably a lot of money but it's very possible that in certain organizations but then but then
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you get the question of like okay does trans you know does like sales call transcription count as AI right well I will tell you Jordy because um 90% of American businesses told the census that they do not use AI at including transcription. >> So they would take a lot of money to
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>> So they would take a lot of money to >> they would take a dollar.
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>> They take a dollar to >> they would take any amount of money because it's all net positive.
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But there's a lot going on in this data that we should run through.
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So um >> and I thought I thought I thought people didn't trust data from >> the census.
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>> Well, yeah that that Ara Krazian has a good uh a good take about the size of the data set and how spend and where AI is actually having an impact. We'll run through that.
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But uh so first off, small firms haven't declined even by this metric.
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So if you're a firm that has one to four employees, you're a very small firm.
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You're still increasing in in in AI adoption.
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Should we uh should we switch over to these?
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>> By the way, guys, we are testing some new microphones >> so that we can walk around the old >> boys wanted the the mics back. They're coming back hot.
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We can't top till Darwash ships ships his book.
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>> He already He already shipped his book.
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I thought I I I got a preview.
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It was Yeah, that doesn't make any sense. I don't know. Darkesh's book. >> It's released. >> Oh, yeah.
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That came out on on straight press.
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Like, we had them on the day it was like on sale, right?
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>> Oh, maybe it hasn't shipped, but I got an advanced copy. I printed it out.
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Um maybe maybe it hasn't fully like actually delivered, but uh the first time we had him on the show was because of >> Yeah, it's still a pre-order.
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>> Still a pre-order on >> Oh, it's still a pre-order. Okay. Okay.
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>> It's going to be released on October 8th.
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So, >> so um >> yeah, market Nvidia, please don't nuke until uh Dark Cash can get the book out. >> Yeah.
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Uh so uh the main headline number in this census data set is that firms with over 250 employees are declining in their self-reported AI usage. Um it's not a huge drop.
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It went goes from like 12% 14% to 12%.
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It's a little blip, but the chart does look scary. We can pull it up.
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It's like the third slide.
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Um so I think what's going on here is the following.
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Small firms see bottomup adoption of AI tools.
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like can I literally directly use chatpt for this?
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like you run a twoperson company at various times.
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A lot of times you're just thinking, okay, I got to I got to select an accountant or something like let me like chat it, right?
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And and and and this kind of bottom up adoption just happens very naturally.
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Whereas if you're in a larger firm, you're going to get sold on some crazy AI transformation uh needs a whole training program and is everyone up to date up to speed at the same time?
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same time? you need a bunch of consultants and they sort of misunderstand what AI even is and they fall into a bunch of weird analogies like we'll hire a hundred AI agents and like that's very different from just hey Google exists chatpt exists we expect
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you to use both at this company um and so this is where I thought the data was really really weird because if you look at the data for chatbt adoption um we're way off of what this 10% % number is for for business adoption of AI tooling. So
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So um there so this this data says that about 10% of companies are using AI at all at work which is crazy because there was a data point back in March that said 52% of US adults use AI large language models like Chachi PT.
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So think about what that means.
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It means like there out of a 100red million Americans, there's 100 million Americans that that are like, "Yeah, I use AI tools."
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Like there's maybe 200 million adult Americans or something.
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There's 340 total Americans, but let's call it let's call it a 100 million Americans that are using AI tools just like Americans. >> Yeah, chat. What kind of Americans? The chat Americans.
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Um and then 80 million of those are just like no, not at work, though. >> That makes no sense. That makes zero sense.
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And so >> doesn't work like that.
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>> There's got to be something weird going on with this data.
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And I think it's a matter of the definition.
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And so the census defines AI is like it makes no sense that 10% of companies would fit this definition.
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>> What did what did uh you said AR at RAM was chiming in on this. >> Yeah. Yeah.
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He we have he has a post in the in the deck. >> Yeah.
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So the definition >> Yeah.
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He says these sample sizes are extremely small for these large firm breakouts, extremely volatile survey to survey, which is why he's using the six survey moving average.
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business AI adoption is back up in the most recent read.
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So I feel like that's important.
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Um I yeah it's one of those things I feel like payments providers like like RAMP right uh would would have better insight here just like obviously ramp is a sample of companies in the United States but it's at a scale now where they could see like okay what percentage of companies are paying for any type of AI products. Yep.
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That's better than are you adopt are you using more or less AI than you were last time? >> Yes. Yes.
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Um the the question is like how power law distributed is it right and then >> so so the ramp estimate of share of US businesses with paid subscriptions to AI models platforms and tools is 43%. >> 43%.
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>> The US government's estimate is 8%.
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>> This data is weird right?
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Also like look at listen to how broad this definition of like are you using AI at your business.
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It's anything in this list if you're using any of these buzzwords you count as an AI user.
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So it should be very high based on this.
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Machine learning, natural language processing, virtual agents, predictive analytics, predictive analytics, literally just like a linear regression forecast of like, oh, we did 1 million, then 2 million, then 4 million.
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Looks like we're growing exponentially.
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Next year, we're predicting that we're going to do 8 million. That counts as AI. Uh, which is ridiculous.
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>> There's a legend out there that doesn't that doesn't do any of that mumbo jumbo. >> Yeah. Yeah. Exactly.
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>> Maybe they're just considering it.
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They're doing it in their heads.
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So, it's like organic intelligence.
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>> So, yeah, seriously, I mean, it's in you can do that in a spreadsheet.
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Uh machine vision, voice recognition, decision-making systems, data analytics, just if you're using data analytics at your business, not even like powdered.
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No, no, that would be the next step.
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Just just if you're analyzing data, you count.
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And the last one is image processing.
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If you're processing images, that counts as AI.
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And so that's basically any SAS tool like any consumer LLM product used by employees should count and it should be really easy to fulfill this this definition.
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fulfill this this definition. I'm thinking of like if you're using RAMP obviously when you scan a picture of a receipt that uses image processing your business technically >> you're telling me the people that that are responsible for the department of
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motor vehicles are getting into measuring the usage of AI >> in the workplace and we should all >> this is incredibly botched like you say it back to me >> but it but but it but but it's it's it is really funny because one post like this it's a timeline and you have people like Daniel just saying it's over. Obviously, he's joking. Obviously, he's joking. >> Runs runs on me. It's over. >> He's having fun.
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>> Um, but I am I am very interested to see the results of uh of hype uh hype. tvbpn. com.
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>> Go fill it out, please. Uh hype. tbpn.
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So, uh I was trying to dig into this more and was wondering like is this chart bearish? And I don't think so.
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Uh I think that there's a big shift that's going to happen.
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the number of business owners who pick up the call from the census and actually say yes I'm using AI that will go down but the real number will actually go up.
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So if you're using Stripe there's a machine learn there's machine learning running under the hood to do fraud detection.
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So you are an AI user but it's happening at a different layer in the stack.
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Yeah, >> if you use RAMP, our sponsor, save time and money. Go to ramp. com.
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Um, when you scan a photo of your receipt, that is processed using AI, but you aren't thinking about yourself as like an AI user.
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You're just using software that happens to be AI enabled.
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Uh, and the same thing will happen, you know, with your email.
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Like, it doesn't matter what email client you use.
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You could use uh you could use Google apps, you could use Outlook.
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Like there's going to be AI baked in there.
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You're going to be an AI user.
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When you even when you just go to Google, you're going to see search overviews that are LLM powered.
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You're going to be using Chat GPT.
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Like AI is going to be 100% used.
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And yet everyone will say, "No, I don't use AI at my company because I'm not an AI company."
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And there's this weird disass.
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>> Yeah, I use I use software basically.
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It's like it's like, "Are you specifically a a software company?"
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And that's and that's and that's part of the way that people have been waking up recently being like wait AI is SAS and it's like has has been >> it's the same thing with like like non- relational databases or like in-memory caching.
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>> AI had to become SAS in order to destroy it. >> It really really did.
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Uh, and so, uh, I think AI is going to seep into every crack of the small business data of small business day-to-day operations, but the operator won't be proudly telling the census worker, I'm all in on on AI for much longer.
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I think that trend will continue and less and less people will be saying, I have adopted AI, even though they will have.
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Uh, which is just a weird it's just a weird dynamic.
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Um, but, uh, it certainly certainly tracks. >> So, I'm Bora. This is Jerry.
16:04
We're co-founders of Reacher and the outfits are because we help brands reach more creators. >> Okay.
16:11
>> And make viral content to help them reach more people.
16:13
>> How how do you do that?
16:13
Like what is the actual product? >> Yeah.
16:17
So, we build AI agents to help brands find the right creators, personalize the outreach. Okay.
16:22
>> Get them to respond, pay them, and then also generate scripts and hooks so that they can make viral content.
16:26
>> We have some lightning round questions.
16:28
Uh favorite entrepreneur. What you got? >> Oh, go. >> You can say anybody. >> Yeah, I know.
16:33
I was going to say Elon, but I think it's uh Jensen. There we go. Yeah. The first Jensen.
16:37
Let's start counting him up. >> I'm Bruno.
16:40
Uh we're building Gaus a personal AI investment analyst for retail investors. >> Oh, interesting.
16:44
You know, B2C, if you invest in stocks, you're welcome to join our platform.
16:49
>> Uh yeah, I mean, there's been a ton of moves in the in the retail world.
16:51
Tons of meme stocks going on.
16:53
Is this going to help me find the next great meme stock or avoid getting caught up in the meme stock?
16:58
Is it more for the retail investor who doesn't want to get burned or the retail investor >> to not make mistakes? Exactly.
17:04
That's actually our number one use case.
17:06
We want retail investors to make less emotional mistakes. Emotal mistakes.
17:11
>> So right now we're focusing on thesis driven investors.
17:13
So not the the meme stock buyers.
17:15
Uh so you have a clear thesis.
17:17
You want to monitor the market, but you're a busy professional.
17:19
You don't have time to know keep track of everything that's happening.
17:22
We can find opportunities.
17:24
you know, you connect your portfolio to us and we can start giving tailored advice.
17:29
>> Favorite entrepreneur we've been asking everyone who comes to mind uh throughout history.
17:34
>> Um I have to say David from New Bank.
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He's an inspiration for me.
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He challenged you know the most traditional industry in Brazil, big banks and he managed to create a a generational company I really like. >> Introduce yourselves. Who are you? What are you building? >> Cool.
17:47
So my name is Jason Cornelius. Uh this is Steve. >> Hey, what's up guys?
17:50
Steve with Perseus Defense. >> What's up?
17:52
And we're building 16inch missiles to shoot down drones.
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>> 16in missiles to shoot down drones. Okay. >> Okay.
17:59
>> Uh what what like do we not have 16 do we not have 16inch missiles in the arsenal currently?
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Is this something that's like like we're familiar with like the Patriot and then the bullet?
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>> How much do they cost and how do you fire them?
18:12
>> Yeah, it's a good question.
18:12
So there are some existing solutions for like the counter UAS problem, right?
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We see >> walk through the Yeah, walk through the solutions >> for sure.
18:18
So there's, you know, electronic warfare, so GPS jamming, which is unreliable, right?
18:24
>> There's there's easy ways to defeat them.
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You know, you can make a more advanced drone.
18:26
And this is what we have the fiber optic cables, >> fiber optics, and this is like already defeating some of those solutions that we have.
18:32
And then there's like the Death Star laser beam, which is very expensive, immobile, very heavy, requires a lot of power. There's AI machine guns.
18:39
So like there's a million solutions.
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And we >> Who's your buddy that does that?
18:42
Uh >> uh ACS control gun on the truck. Yeah.
18:47
And so there's some really good solutions out there for different use cases and we we need more and they all have pros and cons and they have like a layered.
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So some of them like ACS is very short range.
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Some of them like a Patriot is very long range.
18:57
And so we looked at it who's going to fill this gap that's in between when we don't want to spend a $10 million missile to shoot it at 10 miles away, but we also don't want it to get so close to us that it's, you know, right on top.
19:08
>> So what's what's the range? It's a 16inch missile. Half mile.
19:12
>> Half mile lightning round.
19:12
Uh favorite entrepreneur.
19:14
Who do you look to for advice or uh or as a role model?
19:20
>> We're looking at Dino at Seronic right now and trying to match that trae growth trajectory that they're having a lot.
19:26
>> Introduce yourself for the stream. Who are you? What are you building? >> Yeah. Uh I'm Prenav.
19:28
Um we're building Meteor and this is for Han.
19:31
Uh the AI native browser that's going to kill Google Chrome. >> Oh, okay.
19:35
We got the browser wars going.
19:42
>> Are you guys going after Comet, too? >> Yeah, absolutely. Everyone. Yeah. >> Okay. Okay. Yeah. Well, what's the plan?
19:47
I mean, everyone has installed Chrome at this point. Everyone runs it.
19:49
It's so hard to rip it out.
19:51
How do you How do you create a solution that's 10x better? >> Yeah.
19:55
Well, I mean, we all spend seven or eight hours every day on our browser, right?
19:59
We spend we do most of our work on the browser. Yep. >> Right.
20:01
Most of it is redundant work. >> Yep.
20:04
>> We're saying we can automate all of that away. Okay. >> Right.
20:06
We're saying we want AI we want to spawn AI agents that work with you as your co-pilot to the web.
20:09
Um that can do your work for you so you don't have to waste your seven eight hours. >> Okay.
20:14
But but but like what does that look like as I use the product?
20:16
How do you pitch it to somebody who says Chrome works well enough for me? >> Right?
20:20
Chrome does work well enough for you if you're okay wasting many hours a day.
20:23
What we're saying is we're giving you time savings.
20:25
It's sort of like people pay thousands of dollars for personal assistants, >> right?
20:29
People pay thousands of dollars for employees to hire like to create automations.
20:33
>> We're saying we want to create virtual employees >> that run on your browser, right? And that's Meteor.
20:38
So like let's say you want to handle your calendar, right?
20:41
just automate all like meeting creation and you know based on your your emails.
20:45
>> Who's your favorite entrepreneur?
20:46
>> It's got to be Steve Jobs. >> Steve Jobs. Okay.
20:49
>> Introduce yourself in the company. >> Um cool. I'm Haz Hobble. I'm the founder of Pali.
20:52
We're bringing every contact and every conversation from every platform into one place. Okay.
20:57
>> And using AI to help you keep track.
20:59
>> Who's your favorite entrepreneur who you learning a lot from?
21:02
>> Uh my favorite entrepreneur of all time actually would be like Richard Branson.
21:06
>> And here's a fun story.
21:06
So when I was I dropped out of high school and I remember when I was like 14 15 speaking to my mom mom about this I pointed to him as someone who was successful who dropped out.
21:16
>> Did he drop out of high school though? >> Oh wow.
21:18
>> And then 10 years later I was invited to spend a week on his island with him. No way.
21:23
>> And I spent actually time with him on Necro Island and so it was like a very cool full circle moment.
21:25
Um he's been a great great like mentor over the years. >> That's amazing. That's amazing. Introduce yourself. What do you do?
21:32
>> Yeah my name is Petra. I'm the CEO of MCPUs.
21:33
Uh we help people use MCP of course build open source dev tools and infrastructure first.
21:38
>> I was going to say what's the open source strategy.
21:40
>> Yeah open source I mean is a no brainer >> strategy is to open source >> license everything is free.
21:46
>> Okay everything's free and then there's probably GitHub repo that's growing and some measured by stars or something like that.
21:51
>> 7k stars on it for 7k stars. Congrats.
21:53
Uh and then uh at some point do you want to be more like Red Hat Linux like who are you looking to in terms of well-run is a GitLab like >> superbase. >> Superbase. Okay.
22:03
breakdown uh how will their business model look like yours?
22:07
>> Yeah, because they they have a bottom up approach.
22:08
They get developers and then those developers introduce inside the company the tool. >> Uh and I love it.
22:14
>> Who is your favorite entrepreneur or someone in business that you look up to?
22:17
>> Yeah, Brian Chesy, I think. >> Brian Chesy. >> There we go.
22:21
>> Introduce yourself for the stream. Who are you? What do you do?
22:23
What do you >> Everyone I'm the CEO of Closera and we build AI agents for commercial real estate. >> Oo. Okay.
22:29
>> Oo. Okay. um what what part of the commercial real estate stack the actual transaction do you sit on the buyer side the seller side like administration there's so much that in commercial real estate >> exactly it's a huge industry so uh yeah my co-founder and I our families actually grew up uh in the commercial real estate space both our families are developers um
22:50
>> Thank you for the developer building we like >> developers developers say that in a different context exactly yeah um but yeah we we kind of did a survey of the whole market and we realized actually the most insane amount of manual, tedious, boring work that of course can be automated with AI agents um is actually done by brokerages and so that's where we decided to focus. >> Favorite entrepreneur, someone you look
23:10
>> Favorite entrepreneur, someone you look up to.
23:11
>> Yeah, I think you know classic answer definitely Steve Jobs.
23:13
Like reading that biography in middle school is like what got me to want to move to the valley, go to Stanford, DYC.
23:17
So >> the Walter Isacson book fantastic book.
23:21
>> Introduce yourself for the stream. Who are you? What are you building? How's the day going? >> Yeah. Hi.
23:25
Do I look at you or do I look whatever you want?
23:27
Okay, I'm going to look at you. Fantastic. >> I'm Anson.
23:29
Um, we're building normal and we're automating hardware testing and compliance.
23:33
>> Hardware testing and compliance. Any specific verticals?
23:35
Are we talking like semiconductors, rockets, spaceships, cars? >> Yeah. Yeah.
23:39
We're starting with like robotics and drones and other any electrical components that have like a radio >> Yeah. Yeah. >> part to it. So, that's mostly it.
23:46
>> Who is your favorite entrepreneur? Someone you look up to. >> Can be anyone. >> Favorite founder.
23:51
>> Favorite founder throughout history. Anyone? >> Sir John A. McDonald. >> Who's that?
23:55
uh first prime minister of Canada. >> Okay.
23:58
>> Company started he can start Canada. >> Okay.
24:03
We don't have any buttons for Canada. >> Yeah.
24:05
I I this is somewhat American.
24:05
I don't know if I can fully endorse it, but it's it's outside the box and I appreciate it for that reason. >> Introduce yourself. What do you do? What are you building?
24:14
>> So, I'm Aiden, the CTO of Fegov.
24:14
We're doing the AI operating system for local governments.
24:19
Starting with the 311 in a box. >> 311.
24:22
What do you is that information hotline?
24:24
Yes, the theformational u counterpart to 911. Okay.
24:29
>> So, interestingly, only around 2% of cities have a 311 line, even though every city has 911.
24:36
>> And what we're doing with our first product is uh creating 24/7 call center that's available to >> anyone from if you're in San Francisco. >> Yeah.
24:46
>> Or if you're in like a city of 10,000 in the middle of Iowa, like you should have the same level of service.
24:50
call 311, it automatically routes you to your service and then uh if I'm in my city, it'll give me information.
24:57
What What are the What's the Obviously, everyone knows textbook 911 call?
25:00
Someone's breaking into my house.
25:02
What's the textbook 311 call?
25:04
>> Yeah, I think >> is this road open or when does a trash pickup come? Stuff like that. Stuff like that.
25:10
It definitely varies a lot more city to city.
25:12
So, we're live in Florida and we're taking calls about alligators roaming around the city. Yeah. Yeah.
25:18
>> And it can kind of route and and I'm sure you've set this system up so that you can route to 911 if you need to or write to animal control, kind of sit above the rest of the stack of all the different city services. >> Yeah.
25:29
And that's kind of why we started with this is because it gives us a really great insight into what are the calls and services that the city's providing.
25:36
So now we can go down and actually handle these workflows end to end with our agents.
25:40
>> Who is your favorite entrepreneur of all time?
25:42
Someone you look to for advice.
25:44
Um, Peter Teal, >> first first person to see.
25:51
>> Uh, so yeah, why why is this sitting here? What do you do? Introduce yourself. Who are you? >> Yes, my name is Zane.
25:55
I'm the founder of Knox Metals and we cut metal.
25:56
So, we're trying to build the most efficient metal service centers in America to empower every factory in America to work with better margins to move faster. >> Okay. There's a lot of ways. >> He's doing the meme. He's doing the meme. He's doing the meme. He's re-industrializing.
26:10
>> Who's your favorite entrepreneur, Alex Karp, >> of all time? Alex Karp.
26:12
We've had him on the show last week. >> Introduce yourself. Who are you? What are you building?
26:17
>> Yeah, so hi, my name is Vhar.
26:17
Um, and we're building Orange Slice.
26:19
We're basically AI search infra to help you find customers that already want your product.
26:25
>> Who is your favorite entrepreneur of all time?
26:29
>> Oh, that's a good one.
26:29
I'm not I don't actually know that many entrepreneurs in general.
26:33
>> Someone that you read a biography of or look up to or maybe just saw a recent interview with and thought was I could learn something from them.
26:40
>> He's Lisan Algib of Enterprise SAS.
26:40
He doesn't need his blank slate.
26:42
He doesn't need any influence.
26:45
>> Well, honestly, I I don't think um I I don't draw that much inspiration just because I think the biggest motivating factor, and this might be contrarian, is not actually inspiration, but like the fear of mediocrity of it not working out has been way bigger for us.
26:57
That's biggest reason I don't have that much inspiration.
27:01
But Eric from the RAM from RAM, my co-founder used to work at RAMP.
27:05
>> So, I mean, they are absolutely killing it.
27:09
Royal uh >> introduce yourself what who are you? What do you do? >> Uh my name is Arlon.
27:14
I am building Nomio which is an API uh that gives more context to agents. >> Okay.
27:19
>> So if you're cursor user, you can pretty much just go to cursor index any documentation or codebase and give it as a context to an agent.
27:26
>> We uh what exactly is happening?
27:26
I I I know cursor does kind of rollups of what's happening.
27:31
There's there's some rag infrastructure that's popular.
27:32
What else is going on in in the actual product to unlock value? Yeah.
27:37
So the two reasons I built this is because like I was so pissed when I would like go to Google, copy paste all the docs and paste them right in the cursor. Yeah.
27:47
The memory is not persistent.
27:47
So they will forget that in like 2 seconds.
27:50
And second one is that you also pollute context window which like causes context rot.
27:54
It's actually a study done by Chroma which is like a company.
27:56
Oh yeah, we know Jeff well. Yeah.
27:57
Saying like post 4,000 tokens I think like the performance of any LM goes like this. Yep.
28:02
>> So that's like the reason I built this.
28:04
>> Who's your favorite entrepreneur of all time? >> Yeah.
28:06
Who the the most money bro? Like Elon Musk. Yeah. Yeah.
28:07
He's the richest man, bro. Yeah. >> Yeah.
28:10
>> But otherwise, yeah, Brian Chesky is my go. I love Brian Chesky. >> Brian Chesky. Founder mode.
28:15
>> Would you mind introducing yourself and your company? >> Uh, hi everyone. I'm Allesia.
28:18
Um, VFlow is the all-in-one solution to build production ready apps in no code. >> Okay.
28:24
Uh, we've seen a lot of news recently that, uh, there's now a whole industry of Vibe Code cleanup specialists. What's your reaction?
28:30
Can Vibe coding ever make it to production? >> Uh, no. >> No. Not now.
28:35
At least like all the solutions out there are really broken and they can they give you this wow effect in the front end but on the back end side there is so much uh to do and there is a huge need people are like they have hair on fire problems and they need to solve these problems the market is huge.
28:51
>> Who's your favorite entrepreneur of all time?
28:53
>> My favorite entrepreneur is Taylor Swift.
28:55
>> Taylor Swift big fan and she is amazing.
28:59
>> Introduce yourself for the stream. Who are you? What are you building?
29:02
>> Well I'm Joshua March.
29:02
I'm the co-founder and CEO of Veritus Agent.
29:04
We build AI agents for the consumer lending industry. >> Okay.
29:10
>> So, interfacing with borrowers to help help doing sales, servicing, collections for like fintexs, banks, credit unions, services, that kind of thing.
29:18
>> Who's your favorite entrepreneur of all time?
29:20
>> So, um there's this guy Felix Dennis >> who was a who was a British entrepreneur and he wrote this book called How to Get Rich, >> which I think is the best book on entrepreneurship. >> What you actually do. >> Yeah. My name is Kevin.
29:33
I'm the CEO and co-founder of the prompting company and we help product get mentioned in chat GPT. >> Okay. >> Okay. Okay.
29:40
>> Not just another generative engine optimization tool, but yeah. Yeah.
29:42
How do you how do you uh differentiate? >> Yeah, for sure.
29:46
So, we play in the infrastructure layer.
29:47
We're not just creating articles for you.
29:48
Um we create shadow sites for our companies to, you know, influence all of them.
29:53
>> Who is your favorite entrepreneur of all time in history? >> In history.
29:56
I mean, >> anyone alive or dead, >> dude. Uh Steve Jobs. >> Steve Jobs.
30:00
No, that's a great good answer. >> Introduce yourself. Who are you? What do you do? >> Bob. >> Hi, I'm Bob.
30:05
Welcome to the show, CTO of Embed.
30:07
We build coding agents for firmware. >> Okay.
30:09
Coding agents for firmware. >> Firmware. Yeah.
30:12
>> What what device are you embedding done?
30:14
>> So, we do microcontrollers, Linux computers.
30:15
So, think about any microcontroller you can think of.
30:16
SDM32, ESP, uh TI, NXP, any any manufacturer.
30:22
>> When did you when did you learn you wanted to do agents for coding agents for firmware?
30:26
>> That's a good good question.
30:26
So, I did hardware all my life.
30:28
hardware all my life. started like you know started when I was small doing robots moved into more professional stuff in high school in college I built >> school let's go >> in college I yeah in college I built humanoids and then um uh went to a startup did medte stuff and then went to
30:43
Tesla worked on robo taxi >> so we kind of saw I saw this problem from like you know a re like a 10% research lab to a trillion dollar company >> yeah who's your favorite entrepreneur of all time >> Elon has introduce yourself what do you do >> hey uh my name is Scion. Uh we're Kinda. Uh we're Kinda. >> That's a great name.
31:02
>> Um we're basically a deep research for class action law firms. >> Okay. Interesting. >> Yeah.
31:06
Let's give it up for litigation. >> Litigation.
31:10
>> Uh what's the secret sauce?
31:10
Is it is it just the the D bad data in, bad data out?
31:15
You got to get private data that's maybe behind some sort of wall.
31:16
It's not scraped into the the pre-training weights of GPT5.
31:20
And so you have some cornered resource in the data.
31:22
Or is it something in the architecture or something at the UI level?
31:25
like where where's the interesting >> kind of like most startups at YC like a lot of it sits on the application layer. >> Sure.
31:32
>> Um most of it for for class action law firms is the scale at which they do things.
31:37
You know they can have maybe 10 million pages for litigation. >> Oh wow.
31:41
>> So with that kind of scale you can't obviously just toss into >> Yeah.
31:44
Be a hassle to just click upload another PDF. Upload another PDF. Upload another PDF. Yeah.
31:48
And then the kind of second thing is like most of the data sort of sits sits in silos and kind of aggregating it all and making it sort of, you know, comprehensive like human would is >> Who is your favorite entrepreneur of all time? >> Sam Alman. >> Samman.
32:01
>> Just just because I've met him twice, but he's >> he's a goat. >> Introduce yourself.
32:05
>> Uh we haven't pitched yet. >> Who are you? What do you do? >> I'm Raph Garcia. Uh founder of Kernel.
32:10
We're crazy fast browsers in the cloud for your AI agent. >> The browser wars.
32:14
>> The browser wars are on. typically computer use.
32:17
So it's an API to go and interact with the website. >> Yeah.
32:21
So nowadays a lot of AI agents, you want to hook them up to the exact same tools that humans use.
32:27
>> And the browser is one of the main tools that we use on a day-to-day basis.
32:29
And so >> we're powering automations in healthcare, fintech, uh QA, >> lots of different use cases that >> uh AI is really good at. >> Yeah.
32:39
Who is your favorite entrepreneur in history?
32:41
>> Um >> who do you look to >> favorite entrepreneur?
32:43
I mean, how far back are we going? You can go live or dead.
32:46
Literally thousands of years if you want. You can go.
32:49
>> Somebody has somebody has mentioned Jesus Christ.
32:50
Somebody has mentioned Eric Lyman at RAM.
32:52
So >> I didn't make the comparison, but it was made today. >> I mean cliche.
32:57
I'll have to go Steve Jobs.
32:58
I mean I I grew up reading >> that was Jord's answer too >> and studying Apple.
33:01
Like that was my first computer as a kid. So >> who are you? What do you do? Explain yourself. >> My name's Audi.
33:08
I'm a co-founder of Agent Mail.
33:10
It's the first email provider built for AI agents. The key distinction. There you go.
33:13
The key distinction is we're not AI for your email. We're email for your AI. >> Okay. >> Wow. >> Oh, interesting.
33:20
Like browser news for agents. Okay.
33:22
I was wondering about this because I go to agent mode and oftent times it hits a wall where it's like, okay, it should just now it should just email the person to actually kick off that process and it can't do it. >> Yeah.
33:33
>> How much money are you making?
33:35
>> How much money are we making? >> Yeah.
33:36
Did you share a KPI at demo day? Did you share progress? >> What KPI?
33:40
>> We did not, but we love our customers. >> Okay. Okay.
33:42
There are but you customers plural so I know that there's more than one. >> Yes. >> Okay. I'm learning. I'm learning. They keep going. Okay.
33:48
>> Did you come in with this idea or did you pivot to it?
33:51
>> So we were trying to get rich quick.
33:54
>> Is that why you're Is is somebody vlogging out there or is that someone else?
33:57
I was like exactly like husting that YouTube.
34:00
You're getting that YouTube. >> I know a question. >> Let's go.
34:04
>> So we wanted agents to go on the internet, make us money, farm free trials. Um and then interesting. >> Exactly.
34:10
And we realized, okay, it's kind of hard to give agents their own inboxes, but they should have them.
34:13
Sequoa's talking about him.
34:13
Lang Chain's talking about him.
34:15
Agents need their own email inboxes.
34:17
>> Who's your favorite entrepreneur in history, alive or dead?
34:20
>> I like Warren Buffett. >> Warren Buffett. >> Yeah. >> Interesting.
34:23
>> I think he's one of those guys who's like actually humble. >> Yeah. >> Right.
34:26
Like it's not like, okay, hey, I'm worth 100 million. I'm driving.
34:28
I think he just genuinely is in it for the love of the game. >> He does.
34:32
He's for the love of the game.
34:34
>> Hopefully one day, you know, I could be like that. >> Who are you? What do you do? >> Hey, uh, I'm Alith.
34:37
uh building riff which is cursor for music production. >> Oo, that's fun.
34:41
Uh are you sitting So cursor sits on top of an open- source IDE?
34:46
Are you sitting on top of Ableton or something?
34:49
>> That doesn't exist for music.
34:49
So we actually built everything from scratch.
34:52
Uh trained our own models.
34:52
We have our own like editor.
34:54
It kind of looks like GarageBand, but you can use AI tools to generate sounds. >> Okay. Interesting.
34:58
Uh do you bring your own like samples or do do you plug into a sample library like where or is all the are all the samples AI generated?
35:06
Yeah, we have like a user community of samples, but we also like let you generate your own. >> Cool.
35:11
>> And also like lots of bells and whistles to make it easier.
35:13
Like for example, um you can hum out a melody and we'll play it on an instrument for you. >> That's very cool.
35:17
Favorite entrepreneur in history, live or dead. >> Dr. Dre. >> Dr. Good. I knew I had to ask you.
35:24
Anyway, thank you so much for coming on. >> Introduce yourself. Great to have you. >> Who are you? What are you building? >> I'm John Ferrara.
35:30
I'm building JXA, which is a GPS alternative that can track anywhere on Earth with no hardware.
35:37
>> I feel like I've seen this on X.
35:38
>> You might have seen our We had a pretty cool launch video. >> Very cool. Yeah. Okay.
35:40
So, uh, how does it work?
35:42
I we that there there's some company that spun out of Google that just sold that does something similar like magnetics.
35:46
But what what how do you how are you doing it? >> Yeah.
35:49
So, we basically use simulated technology to basically render any environment using satellite imagery or indoor floor plans into 3D.
35:55
>> So, you're doing geoger.
35:57
>> You could you could put it that way. Yeah.
35:58
We should name the company that way. Yeah.
35:59
And then we simulate millions of people or objects moving throughout space, simulate their sensor measurements like accelerometers, gyroscopes, and then train models on that and then basically deploy a software and we can leverage the IMUs which are like sensors that are already into every phone and most other devices today to track you.
36:15
>> It's adjacent to that like like I can see you through your Wi-Fi.
36:17
Lots of people love this. >> Yeah.
36:20
If you've seen that film in like the Dark Knight, there's like a scene where Batman kind of you know that's how you can envision it. >> Yep.
36:26
Uh who's your favorite entrepreneur in history, live or dead? Oh my god.
36:28
Um, I would say I would say I know the Rift guys just said Dr.
36:34
Dre, but I'll say Drake because he just came out that Amazon store and Drake's my favorite artist. So, there Amazon store.
36:41
>> You haven't seen this?
36:41
He's >> This is his actual plot to take over Amazon Music as a distribution platform, but he's working with Amazon to sell all of his merch and all of his goods through their storefront and basically facilitate all their distri distribution through there.
36:52
So, that's my copout answer, but I just love Drake.
36:55
>> And we have a special guest with us opening the show.
36:57
Introduce yourself for the stream.
36:59
>> My name is Peter Tuckman.
36:59
I'm known as the Einstein of Wall Street.
37:02
>> Einstein of Wall Street.
37:02
And uh >> I'm not that smart.
37:03
I just look like Who was the first person?
37:06
Did you give yourself >> Aaron Bernett gave me that?
37:07
And I've been I've had a show on her show now on CNN for the last four months.
37:11
Ever since the beginning of the sort of mini crash that uh was sort of self-induced by our our the new leader, the new the new leader, the new sheriff in town. Terrible. Correct. And she called me in.
37:24
So she used to work on the floor with CNBC. >> Sure.
37:27
and she nicknamed it probably 20 years ago and called me Einstein and that sort of picked up.
37:32
>> But your latest your latest collaborator uh is not on TV but on streaming. Correct. >> Correct.
37:37
So I had the fortunality of actually meeting I show speed, right?
37:42
Young 20-year-old kid who I got invited.
37:44
So there's a team that's doing his stream thing.
37:45
There's a young guy named Adam Faze.
37:48
>> We knew he came to our He came to our event.
37:50
Uh we were here about a month and a half ago. He came to it. >> Really?
37:53
So Adam Adam's something special.
37:55
He found me about 4 years ago and asked me if I would uh let him shoot me uh every day walking out of the stock exchange for 30 days and just do what I do.
38:04
And we did this whole Tik Tok thing called Einstein Elementary went viral like me and like marching bands from Brooklyn and walking around with a 50 lb Hershey's kiss and doing all this crazy stuff.
38:14
So he called me last week asked if I could bring speed to the floor and it didn't seem appropriate at the time and he said, "Well, how can I get you to meet him?"
38:21
And I said, "Come up with an idea." And he's an idea guy.
38:22
So he called me on Thursday morning.
38:24
He said, "We're gonna be at the bull." >> Yeah.
38:28
>> Guys, >> he's gonna be at the bull.
38:29
Would you come and welcome him to Wall Street? I said, "Absolutely."
38:32
So I they gave me a police escort.
38:34
I went down there and met this young guy and talked about some of the sticktick I do, you know, investing in stocks and not stuff and about, you know, the fact that um, >> you know, that everything that his life is based on is actually a publicly traded company.
38:48
and that instead of, you know, buying the next iPhone, he could probably buy a couple shares of Apple and that maybe, you know, he could invest in his future.
38:55
Besides the amazing future set up, >> he received it be totally.
38:59
He talked about it a couple days down the road.
39:04
So, I got the message across and uh and I've blown up. I've got literally 200.
39:09
So, I have now I came in at 260,000 followers on Thursday and now I have 419 and counting and I've got 40 million views on some of my posts. 7,000 DMs. >> 7,000 DMs.
39:23
>> I actually just did a video to answer that.
39:24
Anyway, >> uh what was the first stock you ever bought? >> Oh, you know what?
39:29
I very rare I did not ever buy a share of stock until recently.
39:33
I went through most of my career because I'm a registered trader broker on the floor.
39:37
And I'm not allowed to be in a stock for a customer and for myself in a 30-day period.
39:41
And so I built a trading strategy 20 years ago trading the S&P 500 based on information that I have as a broker on the floor.
39:50
And I trade all 347 names in the S&P every day.
39:53
So basically, I made a decision years ago, you know, and also money does a funny thing.
39:57
if I'm in a stock for myself and I get an order for a customer, it's going to impact the way I trade.
40:02
And I didn't want that to ever be the case.
40:04
So, I I do well enough here as a commission broker that I said, "You know what? I'll invest in my kids.
40:08
I'll put them through college."
40:10
And they they both graduated without any debt.
40:12
And that's where my money went. >> Fantastic.
40:15
What about some of the first stocks that you were brokering?
40:18
>> First stocks that I broker. So, we're here.
40:19
We're talking about IPOs, right?
40:21
And so, you know, I probably have traded more IPOs than anybody on Earth.
40:23
I've been in the crowd on all of them.
40:24
I mean, I the first IPO I think I traded was LinkedIn, right?
40:28
It it was priced at 30, it opened at 60, ran up to 180 same day.
40:34
And that was where I got the sense of how how amazing the enthusiasm around an IPO because it's based on confidence, right? Nobody knows it.
40:40
And then and so one of I've had so many fun experiences in IPOs.
40:45
Jack Ma Alibaba IPO, which was one of the biggest that we've ever had here. He and I bonded.
40:50
We spent so IPOs here take probably four or five hours.
40:54
We just opened CLA, right?
40:54
And the process behind that which we do better than anyone in the world is the price discovery process that what goes on.
41:02
It's kind of like building a building.
41:04
>> The way you open a stock, the way we open a stock takes time because it's a matter of the information going back and forth. It's a public offering.
41:10
So the public has to understand what's going on.
41:14
And so we go back and forth with our customer.
41:16
It's kind of like if you put the bricks and the mortar in the right place and you the way a stock opens if it's built correctly is going to proport the way it trades forever.
41:23
Now, it doesn't guarantee it's going up, but it will have structure and foundation.
41:27
And you know, you go to NASDAQ, nothing against NASDAQ, but if you go to NASDAQ, it's fully electronic.
41:33
So, it it opens when the buyers and sellers meet in an electronic marketplace. Here, it's different.
41:38
So, then you're going to see what you see in NASDAQ.
41:40
It'll go up, it goes down.
41:42
There's no there no guard rails, right?
41:44
So here things are a lot different.
41:46
So Jack Ma and I spent four hours together in the IPO. He and I are very short.
41:50
So we bonded on the fact that we were the shortest people in the crowd.
41:53
We were on the same level, not not financially uh cuz he became a very wealthy guy again on that day.
42:01
>> Someone on our team actually was here uh IPOP as well. >> Amazing time.
42:04
And then we've had look then you know the the the whole landscape has changed when we worked completely blew up the whole IPO market and that affected >> Yeah.
42:13
tell us that story because I remember the S1 going out but then did they get out? What happened?
42:18
>> Well, well, what what ended up happening?
42:19
Look, as I said, it's built on confidence and when you know everybody there was huge money put into Weiwork.
42:23
Weiwork. He was lorded by now he came down to the floor many times and it wasn't until the night before everyone needs to know this that on the end of the road show is when all the financials are given out to the public and it turned out that it was all smok and mirrors and he had spent all the money
42:37
on on prostitutes and blow and that the company had nothing no basis behind it and so it was aborted the deal was aborted and what that did was it changed amazingly enough that one stock could change the landscape of IPOs for years it literally everyone say great idea windows closed. That's what closed it. That's what closed it.
42:55
>> That's what closed it on Mad Money was saying we don't want this.
42:58
We don't want that quote.
43:01
>> And so to think that you know something about what's going on and we didn't know anything on literally until the night before made such a huge impact on the market.
43:10
It literally has taken a couple of years to grow out of that.
43:12
The night before that we had had some really wonderful robust years.
43:16
Remax and a bunch of stocks they would open the huge premiums. We were trading.
43:21
>> Give us a quick history.
43:21
Give us a quick history on CLA, right?
43:23
Cuz Clarna's tried to get out a couple times. >> Okay.
43:27
So, I don't know the history about CLA.
43:29
All I know is that I watched how it opened here.
43:31
So, it did take a little while.
43:33
It did open at 52, I think. Right. And so, it's not traded. You know what? It's hard to know.
43:37
So, what's important about it is where the bids are, where the offers are, and how the foundation looks.
43:43
So, where the bodies are buried within a stock when it opens, right?
43:46
There was enough stock at 52 bid on balance. It's what it's called.
43:49
So stocks pair off that are priced accordingly.
43:53
So 4 something million shares open.
43:55
That means that they were market orders.
43:57
They had no limits to them.
43:59
And that's they that was they paired themselves off.
44:01
It was a 52 bid for 300,000 on balance meant that there was a stabilizing bid whether it was by the Goldman Sachs, the company or or the banker or not.
44:10
But that's what made it open at 52.
44:12
If there had been more to buy at the market, it would have opened higher or more to sell, it would have opened lower. It opened at 52.
44:17
It did trade up to 5720 on a small bit.
44:19
70,000 shares traded up and then it came in.
44:24
It's trading at a couple dollars lower which is reasonable.
44:26
It does not have the power and the impact that Figma and um and Bullish did. Figma and Bullish did.
44:33
So, so, so, but but all three of these are relatively like is there a specific strategy that that these IPOs have had in terms of like pricing at a at a a at a at at what feels like uh >> uh very reasonable like >> so you know what they're they they they're pricing it based on the reaction to to what the what the investment community is willing to give it is.
44:55
So, some of the other ones got priced at 30.
44:59
There was over supply over demand at 30. They upped it to 3235. That's how it will go.
45:04
So the night the last night when they go out to the road show to give out allocations, they will get a sense of where that valuation should be and then that's where they will give it up.
45:12
They left some talk on money on the table as did those other IPOs.
45:14
The other ones opened at 90 and went to 117.
45:16
That was B that was uh bullish and Figma also traded at a huge premium.
45:22
My gut is that the sectors that they were in, there's a lot of pressure on this sector right now and and so those those sectors were more iCloud and and and and AI based, right?
45:35
And so I think that's why there was a little more pop to it.
45:37
>> Well, we know you have to get out of here.
45:38
Thank you so much for stopping by the show.
45:40
We'd love to have you back sometime. >> Anytime.
45:42
I'm always going to talk for another two hours. >> To the moon. Let's go. To the moon. Love it. >> Let's go.
45:48
>> We need to dive into the Apple and the iPhone announcement briefly.
45:51
Obviously, this has been talked about.
45:53
It happened a couple days ago.
45:54
Um, but the the post that stuck out to me, there were a few about the design, but the big one was that the iPhone 17 Pro now has more graphics power than an M2 MacBook Air.
46:03
I I I have I This is a MacBook Air.
46:06
I don't know if this might be the M3 or M4 version.
46:11
>> Would have clocked you as an Air.
46:13
>> I just went for it because I was like, I'm traveling more.
46:14
I'm less of like in workstation mode and uh and so like, let me give this one a try. Uh, and let me see.
46:21
I have the I have the M4.
46:21
So I I think I have more power here than the iPhone 17 Pro.
46:26
But even just two years ago, it's crazy to think how quickly the chips are shifting from uh workstation which is huge uh you know you know laptop to phone and so I wanted to talk about what the downstream implications of this are.
46:42
And >> did you did you see the uh camera functionality?
46:47
Apparently, if you take a you can take a photo holding your phone vertically and it will give you the lens >> horizontal.
46:53
Yeah, because again, it's I think it's for I think it's a square sensor that's maybe 48 megapixels.
46:59
>> How are you feeling about the the orange?
47:00
Do you think this is this is Tim Cook signaling that he's a BTC Maxi?
47:05
>> Oh, I thought it was him talking giving a little nod to Gary Tan, my combinator.
47:08
>> That's one of one of one or the other.
47:10
>> Clearly, I I >> had to be one or the other. >> Yeah.
47:12
Um >> it is the color the colors. Uh I like I like orange.
47:16
I think it's a under underrated color in general, but >> uh still the color options were interesting. Like no matte.
47:22
You would have thought they would have done a matte black.
47:27
>> They didn't do matte black this year. They just Wow.
47:29
Uh they have a silver and a like a blue.
47:31
I think something like that. I like orange.
47:33
I I I think it's a cool bold color.
47:35
I think I think it's one of the ways to stand out.
47:36
Um it's McLaren orange, you know. McLaren orange. >> Looks like F1.
47:41
Maybe it's a nod to that. Who knows?
47:43
Um but they're they're having fun with it.
47:45
Hopefully next year, the color I'm pulling for, ramp yellow.
47:47
Can you imagine the ramp yellow iPhone?
47:49
Uh, it just might happen.
47:52
Maybe we'll we'll make it happen.
47:53
Um, but on the tech side, you know, people were pretty uh like there were a couple takes early that were pretty like bearish, like, oh, like nothing changed. Nothing changed.
48:03
And uh, Ben Thompson summed it up pretty well.
48:06
>> Tim Cook, >> you had a funny banger about this.
48:08
>> I mean, Tim Tim Cook posted um, >> he did post >> Yeah.
48:12
the morning of and he was like days like this make Apple, >> you know, like like basically like hyped it up as if as though it was going to be this sort of dramatic announcement and and I think people were pretty >> pretty let down >> at this point like if it's not a change in the overall form factor like you're going to folding phone, it's not going to be as easy just to talk about completely.
48:34
Um, but at the same time it has a bunch of uh it has a bunch of improvements that I think will have downstream effects that might be interesting and might actually have kind of these like viral moments.
48:43
And I'll get into my thesis here.
48:46
So, uh, has a vapor chamber in it that allows it to cool.
48:50
So, if you're in the sun or you're running, you know, you're running some heavy duty app, um, you're not going to get your your phone's not going to be as hot anymore. Uh, 50% more RAM.
49:00
Obviously, that's important for AI.
49:00
And then they have a new chip that's designed with the LLM transformer architecture in mind.
49:05
So the Apple A series of chips, they've always been somewhat AI optimized, but um more for just broader machine learning tasks.
49:13
Now >> they're doing the same thing that OpenAI is doing with NVIDIA and Broadcom on chip design.
49:20
Same thing that Google DeepMind TPU team is doing over at Google and uh Anthropics working with Amazon and Tranium. >> Here's my post.
49:27
Introducing iPhone 4000, a newer, better iPhone that's lighter, faster, newer, and better by >> How many Where did this land?
49:36
>> Uh, how many likes did this wind up getting? >> Six >> 6,000. >> 6,000.
49:43
>> And the funny story here, the the little inside baseball.
49:45
Uh, Jordy posted this exact post like five minutes earlier.
49:51
>> Well, so so I originally had this post as a draft and then I altered it. Yep.
49:55
and I posted it and it completely I had a different picture and I did iPhone 472 >> and it was just completely flopping.
50:00
It got like one like on like 300 impressions. Like people hated it.
50:04
The the timeline hated it.
50:06
I just went back to this version, posted it and then it it completely ripped. So never give up. Never give up.
50:13
>> You think you have a good bit.
50:13
But the the the the funny thing here, I mean, obviously just funny that Apple always comes out and like it's our most powerful iPhone ever because it's like, well, if it was a less if you if you guys messed up and accidentally created a less powerful iPhone, you would just keep selling the current one.
50:26
You're not you're never going to come out and be like, this year we're selling one, the latest iPhone, but it's less powerful because just sell the last one then.
50:36
Just be like, no new iPhone because we couldn't make it any more. >> We actually made it. We made it perfect. >> We made it perfect.
50:41
So, we're what are how are you feeling about the Air?
50:44
I think that's going to sell >> incredibly well. >> I don't know.
50:49
I I'll need to like feel it and and uh and try it.
50:50
I've never had any iPhone that's not just like the biggest and most of like the the biggest screen, the maxed out one.
50:58
I've always gone for like the the most power, the biggest one.
51:02
I've actually considered carrying an iPad mini just as a phone because I'm so big that my pockets are big enough to carry an iPad mini >> back pocket. >> Yeah. No, no.
51:13
I I was feeling it and I was like you can get it with cell service and so I think you can get a phone number on there and so you can just have like pull out your giant iPad mini.
51:23
Uh but uh but I never did that.
51:26
I've always just stuck to like the Pro Max, the big one with the big screen. But it it's it's easy.
51:30
Uh the uh I don't know the the interesting thing about the uh the iPhone Air was this uh you know the whole computer is in the camera bump now and basically everything that drops down is just battery and screen battery and screen all the way down.
51:45
Um and so people are wondering like you know they could clearly take out the battery and the screen and maybe make like a pin like they're they're getting so good at miniaturaturizing like what it means to be a computer uh that they can put that in all sorts of different things.
51:58
I would be would have been really excited to have an iPhone that doesn't that will sit flat on a surface without a case on it.
52:06
I haven't used cases in in many years.
52:08
I just like the the feeling of the phone.
52:11
>> It is crazy that they >> so funny that just perpetually like un you know just give me like a flat surface.
52:16
Like I'm happy for the phone to be as thick as necessary to just give me a flat surface.
52:21
>> And it looked like they were going to do that with the iPhone Pro because it has this wider notch.
52:24
So, at least if you did if you did the notch evenly all the way up.
52:29
>> Might be nice if it's kind of like sitting at an angle. >> That's fine, I guess. I don't know.
52:33
>> But it's al it's also so funny the the idea of like you have this incredible camera. >> Yeah.
52:38
>> And then you're just like putting it on like they really want you to buy a case.
52:41
Like it's it's like >> a lot of the product design seems driven by your >> I don't think that's the real I don't think that's the real reason.
52:48
I think it's a I think it's >> I think it's I I think it's genuinely like people don't like heavy phones and so you have to balance like you need you need the optics of a camera that's this certain thickness and then you need the phone to be thin so that people actually carry it around and aren't like this thing's heavy.
53:02
Um tin foil hat yes is case I I just I do you think they make from cases a year?
53:11
>> I mean they're adding What percentage of people do you think when they go to that buy an iPhone buy an Apple case?
53:14
I would I would estimate that it's less than 1% of their overall revenue >> is basis. Yeah. >> Less totally.
53:22
But you're talking to the goat of profit maximization, Tim Cook.
53:26
>> There's just so many other ways.
53:26
I feel like you can sell 1% more iPhones if you if you actually choose this odd choice because people are like, well, yeah, it's it's the lightest iPhone.
53:36
It's lighter than the Samsung one. It's it's thinner. It's lighter. It's it it looks great.
53:42
Um, and then there might be something about like the notch kind of holding on your finger.
53:45
Um, and so you can actually hold the phone easier with that as opposed to if it was just like fully fully smooth.
53:50
Um, >> anyway, but uh yeah, I mean when you start thinking of uh >> when you start like the the incremental sales from from like design driven decisions like this. >> Yep.
54:06
>> I do think I do think would be significant.
54:08
But anyway, anyway, >> uh, huge keynote filmed on an iPhone, obviously a lot less graphics this time around.
54:14
around. My take on the iPhone Pro was you're we're getting to the point where um you could run an LLM on device and even if it's not Apple intelligence, you know, through that API, um just the ability to actually distill something that's like GPT4 level and have it be
54:33
free, not even an API call that you need, not even cheap on a per token basis, um but actually just have something that you can basically drag and drop >> the energy cost of the energy and no one thinks about it because they charge on the edge because they charge their phone every night anyway. So, I was talking to
54:47
So, I was talking to Tyler about this earlier.
54:49
Uh, try and put into context how powerful a an an LLM running on device could be with this next iPhone because currently people have done it.
55:03
I feel like people have distilled models to the point where they can run locally on phones, but they're not fast or they're not smart.
55:08
But it feels like we might be at a point where you get like to just some sort of like touring touring test passing plus not waiting for >> Pat is asking if it's Nico Rossberg the F1. >> It is Nico Rosberg.
55:23
>> It is >> the former F1 world champion >> and now a capital allocator.
55:28
>> Now a capital allocator.
55:28
Uh so yeah uh Tyler, what what is your take as this gets into people's hands?
55:32
Um, how solid do you think the actual interactions with LLMs could be on on device? >> Uh, yeah.
55:40
So, I think um I think it's 12 GB now up from eight. Yep.
55:45
>> Um, so you can probably run like a >> like very solid like 7 billion parameter like not super quantized model.
55:52
>> Um, we've had those for a long time that are like very solid like obviously they they're going to pass touring tests, whatever. >> Sure.
55:58
Um, you're probably not going to be using it for like doing your your like hard physics homework. >> Yeah.
56:05
>> Um, but like most like things that you want from like a non-device model like helping look at your emails or like doing stuff that like you would think of like like a really good Siri product would do.
56:17
>> Y >> I think it's like totally capable of doing that.
56:19
>> Um, >> I mean it's like I don't think that Apple intelligence was bad because the hardware was lacking.
56:26
It was like like I mean you can it'll be a little bit slower probably to run on cloud maybe.
56:34
Um >> yeah I mean with with with my experience with Apple intelligence was it was just just instantiated in very odd ways.
56:40
It was they they didn't really have like a killer app there.
56:44
Uh and it was like a bunch of different things that kind of piped in and you could like highlight text and then just say rewrite this.
56:50
uh all sort of like very incremental gains. >> Botch summaries. >> Yeah. What?
56:57
Oh, the summaries are botched.
56:58
But sometimes that's might be the best feature.
57:00
Actually, it's hilarious.
57:01
>> It's a feature, not a bug.
57:02
>> We just saw you just saw one in our in our group chat where I posted a uh some fake news and uh Apple summarizes it as like >> Gabe says, "Shouldn't be shouldn't Tyler be back in school?"
57:12
Gabe, you must have missed uh the episode, but he's taking a gap. Taking a gap semester. He is riding with us. >> Yeah.
57:20
Uh, and so I I think it's I think there's like there's something magical about getting the ability to inference a GPT4 level model on the edge for free.
57:33
Like you can you can quibble about the level of intelligence that is, but it is actually too cheap to meter because you won't even have to set up an API key.
57:42
And so you can vend in a a GPT4 level model and then go viral and not have a bill show up and not need to think about monetization, not need to think about anything that's a drag on your just pure virality.
57:57
You can have a free app that just grows and grows and grows and figure out the monetization later.
58:00
And I feel like this sets us up for maybe something interesting to happen in consumer.
58:07
We haven't really had that that moment of you remember the Lensza moment, the magic avatars, you upload your picture and it uh it turns you into Superman or something and then the Studio Giblly moment.
58:18
We haven't had that many like viral apps that are purely based on LLM interactions, like text interactions.
58:26
Uh there's been a couple like there was one called like generative dungeon. Do you remember this?
58:31
It was like a dungeon crawler text thing.
58:34
So it would say like you walk up to uh the dragon's layer. what do you want to do?
58:38
And you could just type like I I brandish my sword and then it would say like the dragon. >> That was like GPT2.
58:44
>> That Yeah, that was super low level, right?
58:46
So imagine that plus like but but you can do it on device at a reasonable level and and you can bring in some other UI elements from the iPhone, bring in the camera, bring in GPS, bring in you know all the other tools that are available just in the iOS like Swift like you know developer kits. uh the SDKs.
59:07
I feel like there will be a ton of people that are just building cool interesting things on the iPhone that could potentially like go viral and and then become real businesses.
59:17
>> Yeah, I I don't think this will be that like meaningful for like Apple intelligence cuz it's not like that's like a product issue.
59:24
It's not like a hardware issue.
59:25
But yeah, I definitely think for >> like third party developers, this will be like pretty big.
59:30
You can do like in you know, if you make some random game, you can now have like avatars or whatever. >> Yeah.
59:35
Like if you make the SDK really easy where like it's very easy to inference an LLM, you don't have to like >> figure out how to like download and then do inference and all that stuff.
59:42
If they like abstract that away, I think it could be interesting.
59:46
>> And I just feel like we've seen so many there's been so many companies, we talked to some folks at Demo Day who are doing this where they were like, we have this cool uh AI agent that like scrapes your emails and does this and it all is pre it all it's all predicated on you installing a Mac app which is a really really hard thing to do. Whereas like >> Yeah.
1:00:04
How many Mac apps do you think you've installed this year? >> Oh, it's super rare. It's super rare.
1:00:06
A uh you know, I got something to put the decks together.
1:00:11
Uh like I literally have a Chrome.
1:00:16
Like that's the one I installed.
1:00:17
I'm looking at my home row and it's like it's just Chrome.
1:00:20
>> Well, and this is why everybody's obsessed with the browser. >> Truly. Truly.
1:00:23
Because if you can get people over there that then you're there.
1:00:26
Um but but I have installed apps and I've installed little tiny apps.
1:00:29
We were talking about the the the workout tracking app.
1:00:32
strong that I saw my friend at the gym.
1:00:35
He was using an app to track his workouts.
1:00:37
I said, "What app is that?" I went and downloaded.
1:00:38
You went and downloaded it.
1:00:40
It was very easy for that app to like loosely go viral.
1:00:43
And it's a free app, but it doesn't have any like AI.
1:00:45
It doesn't really need any AI, but but you could imagine that the the viral coefficient of of someone downloads an app, they have a magical experience with some twist on top of an LLM, something storytelling, something astrology. Who knows what it'll be? I can't predict it.
1:01:01
It's as hard to predict as Instagram or Uber, but it's unlocked by having this having this ability for free on the iPhone.
1:01:08
And then people are sharing screenshots of, oh, I had this hilarious interaction or this was incredible or I love this app.
1:01:15
They create some viral loop.
1:01:17
They do some Nikita beer type stuff and then and then everyone's downloading the app and then it gets actually really really big.
1:01:21
And I don't think it's going to be a compet I don't think it's going to compete with Chachi PT.
1:01:27
I think it's gonna be a completely different thing and it's very hard to predict but but it feels like we might be seeing it. Yeah.
1:01:32
And and and and it's going to require some like really, you know, cracked level of of creativity like what we saw with Harry Harry harry potter Balenciaga where it's like the technology existed and then someone came up with with the great idea to actually go like instantiate it.
1:01:46
So if you're going to be mocking that app up, you're going to do it in figma. com.
1:01:52
Think bigger, build faster.
1:01:52
Figma helps design and development teams build great products together.
1:01:55
you can get started for free.
1:01:57
Um, the Wall Street Journal was also covering the Apple's iPhone Air.
1:02:02
They had a whole interview.
1:02:02
Uh, they they they they had really good coverage of the of the iPhone event.
1:02:07
Um, there was a few there was one thing in uh the uh the reporting from the Wall Street Journal.
1:02:15
I don't have I don't have this particular article actually but uh they did an article with the Wall Street Journal and uh Apple revealed that I I believe they said the majority of iPhones 51% or more uh that are shipping to America are going to be made in India and I'm not sure if it was this cycle but it seemed like they were taking the tariff stuff really seriously moving the uh the actual manufacturing capacity around.
1:02:42
Obviously, Foxcon, their their manufacturing partner is a Taiwanese company and so they're worried about geopolitical risk as well.
1:02:47
And so, uh, just another another data point around uh Tim Cook.
1:02:54
He is not loudly shouting like America, I'm all in, re-industrialize, but he is making moves.
1:03:03
>> What was the number he threw out at the dinner last week?
1:03:04
Wasn't it in >> I don't know if he had a number because uh who was it?
1:03:08
It was uh Zuck had a number and did Apple have a number too that was 600 billion or something.
1:03:14
Apple has thrown out a number at one point. You're completely right.
1:03:18
Um my my my point is that uh we've seen data points. Oh yeah. Yeah.
1:03:24
The number of Thank yous is a lot.
1:03:26
Um but but but we've seen he's invested in uh in some semic some rare earth uh developments in the United States and starting to think about manufacturing internationally.
1:03:37
And you know the the the prob bullish bet on Tim Cook is that like if he was able to set up this in China and he's the reason he can set it up somewhere else because he's the guy who did it.
1:03:49
And so, uh, even though he hasn't been really loud about >> his moves, because obviously if he says like, >> "Yeah, I'm not going to be manufacturing in China anymore," then like his important business partners over there are probably going to be like, "Well, yeah, like we're not going to take your business seriously anymore."
1:04:06
Uh, there are a ton of different geopolitical considerations.
1:04:10
>> Such such an iconic line from the dinner.
1:04:11
Cook says, "I've always enjoyed dinner and interacting." >> Yeah.
1:04:18
If you're getting dinner this weekend with one of your boys, just tell >> how to say something that like no one can, you know, cancel you for.
1:04:23
It's like, I've always enjoyed dinner and interacting. >> Interacting.
1:04:30
>> Two things I've enjoyed.
1:04:32
>> He's a dinner enjoyer.
1:04:32
>> He's not saying I've always enjoyed dinner with you. Yep.
1:04:35
>> And interacting with you.
1:04:35
He's just saying, "I've always enjoyed dinner."
1:04:39
>> And he putting out a claim.
1:04:39
I I feel like for watching some of these like I was watching the Tucker uh Sam Alman interview and um there's a certain level of polish that some of these some of these uh CEOs have when they get to a certain level of media training and public speaking experience where I think of them more as like word rotators than word cells or shape rotators.
1:05:01
They can they can so quickly like shift a sentence to be like like that like so perfectly balanced where you're like wow every word in that sentence was calculated so that it's the rides this perfect line like uh like Sam was going back and forth with Tucker and Tucker's I didn't accuse you. I didn't accuse you.
1:05:23
and you and if you run back the transcript, you're like, "Yeah, technically he didn't."
1:05:25
And he was it was not an accusation.
1:05:27
But then, you know, they're they're rotating the sentences around to try and like pin each other.
1:05:32
It's like watching a wrestling match. It's crazy.
1:05:35
>> Tim Cook said they would be investing $600 billion. >> 600 billion. Yeah. Uh, okay.
1:05:38
So, Apple says the majority of iPhones shipped to the US are now assembled in India, meaning they face no tariff.
1:05:44
Yet, Indian suppliers aren't yet capable of delivering as many of the Pro models that US consumers demand.
1:05:51
So most of those still come from China.
1:05:53
Uh so this is the majority of iPhones in total because uh Apple makes a ton of those but they can't they can't make the leading edge.
1:06:01
And then the other thing that everyone always talks about with this like assembled in India is not the same as fully manufactured in India.
1:06:08
Obviously, the ad the the advantage to Chinese manufacturing uh prowess is that you walk across the street and there's a CNC shop with 25,000 CNC machines that can just immediately uh make you any part and make a million of those parts if you need.
1:06:23
if you need. So um obviously it's going to be a long road for them to set up manufacturing anywhere other than uh other than China but uh it does seem >> serious to understand Tim's actual strategy here because I don't think he's
1:06:41
saying I'm going to invest >> he's not going to be in a huge hurry to invest that 600 billion right uh he may you know he may not actually believe it's it's at all the right decision for Apple and he's just feeling like he needs to Yeah. >> And then if and then in 2028 comes
1:06:55
>> And then if and then in 2028 comes around and you just can pull back or pull out.
1:07:01
>> There's also like so much to 600 billion of capex over what 5 years or something like that.
1:07:07
Like that includes HQ that includes data centers for iCloud that need to be local.
1:07:12
uh if you're streaming the F1 movie on Apple TV Plus, you don't want that stream coming from a data center across the world necessarily.
1:07:22
It needs to be cash locally.
1:07:24
So there are like so many different pieces of the business.
1:07:28
Building more Apple stores like that counts as capex if they build them and they you know there.
1:07:32
So 600 billion doesn't necessarily mean like yes like we're building like the one plant because you know this is like a rainforest of complexity that actually delivers the the iPhone.
1:07:41
It's not just it's not just like one iPhone factory, please.
1:07:46
It's like a whole network of things.
1:07:47
Um, battery life appears to be a challenge for the Air.
1:07:50
Uh, Apple always says like all day battery life, but people are like, >> allegedly, >> what kind of all day are we talking?
1:07:56
Are we talking scrolling for 18 hours? >> Doom scroll.
1:08:00
>> Are we talking a proper scroll?
1:08:02
>> Uh, proper doom scroll.
1:08:02
U, Apple announced the accessory that will attach to the air.
1:08:08
Um, and obviously that's it no longer as thin.
1:08:11
Uh, the company added what it calls a plateau on the back of the Air and Pro models, adding thickness at the top of the device to fit bigger and hotter chips.
1:08:20
>> Not a bump, it's a plateau. >> It's a plateau. Yeah.
1:08:22
Oh, they're they're rebranding.
1:08:24
>> Maybe they're signaling that we're Maybe this is Gartner hype. Plateau productivity.
1:08:29
I mean, they have plateaued in productivity for sure.
1:08:30
The hype cycle, they they've been through it.
1:08:34
They're like, "First hype cycle. First hype cycle. I've been here. I'm I'm I'm plateauing.
1:08:39
I'm I'm getting productive.
1:08:43
Open AAI, the nonprofit, is going to control its for-profit arm and own equity valued at $100 billion.
1:08:48
I believe this will make it the most highly valued nonprofit or like the most profitable nonprofit in world history, the best funded nonprofit, right?
1:08:58
Uh and it is remarkable to think about what that will be like.
1:09:03
People have kind of written off the nonprofit as like it's going away.
1:09:08
Like it is not going away.
1:09:08
like it will continue to be incredibly back.
1:09:12
>> It's it's incredibly back uh funded forever essentially to do a ton of interesting things.
1:09:18
I think we're going to see interesting things about uh come out of that organization.
1:09:20
Uh but anyway, the news, this is from the journal and we'll and we'll break this down, but Nick has it summarized here.
1:09:26
OpenAI LLC will be converted into a Delaware public benefit corporation.
1:09:32
OpenAI nonprofit retains control of the new public benefit corporation.
1:09:36
The nonprofit will hold a hundred billion dollars plus of equity in the public benefit corporation.
1:09:42
The PBC structure enables raising large amounts of capital for the mission.
1:09:47
Um, which obviously they're already doing.
1:09:49
Uh, they're still aligned with ensuring AGI benefits all of humanity. That's good.
1:09:53
But also just aligned with like your shareholders.
1:09:58
Like if you're just a normal CC Corp.
1:09:58
I know they're a public benefit corporation, but if you're just a normal CC corp, like shareholders are humans.
1:10:04
Let's make sure it benefits the shareholders.
1:10:06
that will by definition benefit humanity, but specifically they're saying all of humanity, even if you're not a shareholder, AGI should still benefit you, which is a noble cause.
1:10:14
Um, OpenAI and Microsoft signed a non-binding uh for the next phase of the partnership.
1:10:20
A definitive agreement is still being negotiated.
1:10:21
OpenAI says it's engaging in Delaware.
1:10:24
>> As it stands, Microsoft gets 20% of OpenAI's revenue >> for the big man.
1:10:30
Something like >> big man Satia, something like that.
1:10:31
uh which I it felt like a stretch to me that that that would be sustainable given the uh looming costs that uh OpenAI needs to incur.
1:10:42
Obviously, they're ramping revenue really quickly. Yeah.
1:10:46
>> But you have Broadcom to pay, you have Oracle to pay, you have all these >> But it is revenue, you know, it's not the same as being like crazy. Yeah. It's not fake. Exactly.
1:10:56
Um but but still it's a lot of you know the the there's these companies are under margin pressure already >> and and wasn't the original deal that it would it would be 20% up until they paid hundred billion or something like that.
1:11:12
There was something where like it eventually ran its course.
1:11:13
I believe it had an ending and I think that's what's justifying a lot of the underwriting because the lesson from Google, the lesson from Facebook, the lesson from uh you know Microsoft and the rest of the hyperscalers was that >> you needed your DCF models to be 20 or 30 years into the future, right?
1:11:32
And so if you just if you if you didn't take into account the third decade of growth, you were undervaluing.
1:11:43
>> It was originally reported 20% through 2030.
1:11:46
>> Okay, >> which still is.
1:11:47
>> I don't think a lot of investors are scared by thinking about value in 2035.
1:11:52
I think they're fine with that now.
1:11:52
I think they're saying like, yeah, I have a 10-year fund and realistically all the best venture investments, SpaceX, is still hanging out in the portfolio 20 years later.
1:12:00
They got continuation funds.
1:12:02
I think that a lot of investors are actually fine to say, "Yeah, this company's going to be like, you know, maybe a financial mess for 10 years, but if I'm super confident it's going to be a money printing machine in 20, I'll do the deal all day." >> Yeah.
1:12:17
>> I think that's the >> It's still insane to think that the deal ever got done in the first place. >> The Microsoft deal. >> Yeah.
1:12:24
If you were if if if you talked to a founder and they were like, "Yeah, I was running a fund raise and like, >> you know, ended up taking this deal.
1:12:29
I got the valuation I wanted, but ultimately it gave up 20% of revenue off the top, too.
1:12:36
So, not 20% of like profits, but like a 20% tax on gross revenue. >> Yeah.
1:12:43
>> Uh just for the just till 2030.
1:12:46
>> Yeah, that would be >> and and the founder's like, well, it doesn't matter that much cuz I'm in this for like 20 years.
1:12:49
You're >> pay most get the pass on that. >> Yeah.
1:12:53
Very few businesses, very few businesses in the world, especially like highly competitive, you know, categories, >> uh, can sustain a 20% tax off the top. >> Yep.
1:13:04
>> Um, and still really produce any profits or be functioning at all.
1:13:07
Obviously, >> I'll push you off.
1:13:09
What if your what if your business is uh mobile games in the app store?
1:13:14
you've effectively been paying Apple at 20% 30% tax off the top >> for sure.
1:13:20
>> There's a bunch of examples like Nvidia could do this too, right?
1:13:24
>> And they sort of are through through this kind of deal. >> I I don't know.
1:13:26
I I I mean I agree with you like it is it is a crazy crazy deal.
1:13:30
Unprecedented in a million ways, but everything about the entire OpenAI story is unprecedented.
1:13:34
Unprecedented to start as a nonprofit.
1:13:37
Unprecedented to have who are the co-founders?
1:13:39
Elon Musk, Peter Teal, like you have like seven different co-founders who have uh bunch of co-founders have gone off and start direct competitors.
1:13:46
That doesn't happen very often.
1:13:47
Usually people are like, I got bags in the category.
1:13:49
I'm going to go work on something else.
1:13:51
Yeah, there's a bunch of weird stuff. [Music]