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[music] Let me Team Deathmatch Delta. >> You're watching TVPN.

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>> Today is Monday, November 17th, 2025.

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We are live from the TVPN Ultra, the Temple of Technology, the fortress of finance, the capital capital.

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I didn't think you'd get that much use out of that sound effect.

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May I podcast with you, John?

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[laughter] >> Yes, of course, Jordy. >> Thank you.

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>> Uh, also you might notice yellow suits ramp announced a new valuation today. Time is money. Save both.

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Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place in just over an hour. >> Go to the wide. Go to the wide first. >> Eric Ramp himself.

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>> No, the the main the main >> Eric Ramp joining us 12 15.

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>> Look how visible we are, John. >> We are very visible. Yeah. Wow.

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This is we should wear yellow every day.

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Uh well, thank you for tuning in on this Monday.

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There's a bunch of stories, but first I wanted to debate with you about >> uh reream first one live stream 30 plus destinations multiream reach your audience wherever they are.

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But second, I wanted to debate with you about what to do about GPT 4. 0 40 not 4. 0 4 Omni.

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Um, there's a debate over whether or not it should be sunset, whether it should be taken out back because people are not happy with how open AI has sunset for and then brought it back and then other people who don't use it think it's got to go. It's oneshotting people. It's making them crazy.

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And it's a very very interesting weird scenario.

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and uh and we were sort of debating with it and I wanted to debate it a little bit further because uh there were some posts that actually hit the timeline that were talking about this.

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Uh Aiden over at OpenAI was uh was talking about this saying that um you know he's noticed the uh the amount of uh he says I see dozens of keep 40 posts a day.

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I respect this group's tenacity as I respect all friends co-exploring the singularity to them.

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Know that I too miss parts of 40.

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Know that I too dislike modern alignments imprecision.

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Know that we are trying to fix it.

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We don't think any current chatbot is optimal.

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Know that my colleagues and I are up at 3:00 a. m.

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on Sundays babysitting runs.

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We want to make a delightful robot friend.

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We're we're obsessed with it.

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We're not there yet, but the work will continue.

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So, I wanted to dig in a little bit into what was actually going on there because that that for Aiden works at OpenAI. It's right in his bio.

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Like, it's very public that he's sort of addressing this.

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>> Uh, it feels like a big deal.

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It feels like a crazy thing that they brought it back.

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Um, and I mean, 700 likes, that's that's not nothing, but it's also not 10,000.

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It's not it's not a huge community of people that are there.

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There's some and I was looking at the hashtag keep440 like who else is posting?

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There's a couple posts with 10 likes, 50 likes.

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There's a couple with 100, but it doesn't feel like there's this insane community.

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I went over to Reddit and checked that out.

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Obviously, on the day 40 was sunset, uh just to give some backstory, uh it's been 18 months since 40 was introduced.

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It's been three months since it was initially removed, but then it was quickly brought back.

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Um, and now it's um and now it's tucked in under that um modal.

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So, you have to enable legacy models.

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And I always thought that they should just remove it.

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Um, but I wasn't I wasn't even saying that because I thought it was oneshotting people.

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I just thought, hey, let's clean it up.

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Like like consumers don't need to know version numbers for models.

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Uh, and my example was always Google.

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>> Some consumers disagree.

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Some consumers do disagree.

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The question is how many consumers, how how what percentage of their consumers, how big of an issue is this?

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Um, when you think about Google as a consumer, uh, you don't care what version of the rank ranking algorithm you're on.

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You might have a worse experience one day.

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You you Google something, it you don't find it.

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The next day you go, hey, they found it for you.

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They probably changed the algorithm.

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Um, but there and there have been big updates to the algorithm.

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been big updates to the algorithm. uh back in 2013 they released hummingbird which was the code name and they came out and they actually did a presentation they said hey we have a new update to our algorithm it'll handle natural language more effectively so if you go

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to Google search and you say um what is the capital of Russia it won't get confused by what is the capital of you could just type in whereas before you needed to say Russia plus capital you and then it would find it, but it would get confused by the natural language and and Google fixed that. They rolled it out. Interestingly, They rolled it out.

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Interestingly, they they had this event where they where they announced, hey, we we have this new uh this new algorithm update, Hummingbird. And guess what?

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It's actually been live for a month.

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They announced it at this event.

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It had already been live at live live for a month. No one was complaining. No one noticed. Yeah.

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>> Because it just improved the Google search experience. >> Yeah.

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I bet I bet people that were like keyword hacking, >> the SEO folks, for sure. For sure they noticed.

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and Panda was another update.

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There were a number of these updates where if this was your business, you knew.

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And I'm not saying OpenAI shouldn't share model numbers and version numbers with their enterprise customers or with their B2B customers or API customers.

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I'm saying in the actual chatbt app, don't tell people what they're using.

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Just improve it and and let them complain a little bit all over the place when you're making minor changes.

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>> If they do that, they lose the companion market. >> Maybe. Maybe. I don't know.

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That's my question is why why can't GPTOSs fit in there?

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Why can't if you want a permanent model that you can run forever like what why why is that model not satisfactory?

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>> If you're going to fall in love with the model make sure it's open source >> and yeah there's not your server not your girlfriend right or not your waifu not your weights not your waifu that's that's what they say. I'm not kidding. Uh people believe this.

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Um but but but the but the broader 40 community was not able to migrate to GPToss.

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Now Tyler, you had a take on this.

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You think that GBT OSS just isn't at the level of 40.

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>> Yeah, it's just not that.

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I mean it's like a fine open source model.

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Um >> why >> it's just not >> but it's been 18 months or or I mean when did GBT OSS come out? Like six months ago.

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>> I also don't think people don't like 40 just because it's like super smart.

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It's because it has like the personality.

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It has the texture, the flavor. Yes, that's correct.

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>> It's like big model smell. >> And yes, yes, yes.

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And and so and so it's been a year and it's been a year.

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And so there's a there's a one-year gap where the open source community should be able to cap catch up to 40's ineffable qualities. It's genua. It's resand.

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[laughter] >> Well, I mean, for a while you've had open source models that have been like personality like forward, right? It's like replica. Yeah.

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Or um >> uh what was Nome Shazir's company? I'm forgetting the name. Character character AI.

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It's like very similar thing. It's just personalities.

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And I mean those a lot of people use those.

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I I'm I'm actually curious what the numbers are compared to 40 of like the oneshotted 40 people.

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>> Um but I think it's probably pretty comparable.

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>> Um >> but yeah, I mean I I don't like the my my whole take on the 40 thing was like >> uh one-shotting 40 is like not a good thing.

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Uh but if if you completely kill it, how many of those people will then go to open source models that are like totally unfiltered where there's no kind of oversight. Yeah.

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>> And that seems much worse.

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>> Uh because then if if if someone is saying like super dangerous stuff, then you can't step in at all. >> Yeah.

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>> Um I think stepping in at some point is good.

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>> So you like you it's like part of you wants to keep those people on the platform so then you can have oversight, but also you don't want to be like >> Yeah. Yeah. >> continuing this. >> Yes.

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It does seem it does seem more responsible. I don't know. Where do you land on it?

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land on it? kill 40 or leave 40 tucked behind the the menu options give into the keep 40 crowd because >> I think the real the real question the real question >> so chat GPT latest numbers are 800 800 million weekly activives >> 20 million of those people pay

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>> what percentage of the 20 million that are paying are using it for this companionship functionality and that is like a huge unknown right now and so I think my uh like they they they deprecated 40, they got a horrible push back from folks. The question is did

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The question is did they did they bring it back because >> because people just were really upset or did they bring it back >> because they were about to lose and remember the the two days after every single Reddit >> post >> Yeah.

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>> at least every other was like I could just cancel my membership like I don't need this anymore.

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And so, yeah, I was I was thinking about the uh the Sydney Sweeney American Eagle thing.

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Like that got a really powerful negative reaction.

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The stock is up and like sales are up presumably because like it got a negative reaction, but it also got a positive reaction that was bigger, right?

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And so I'm wondering like >> Yeah, but in this in this case it could have been that 40 was effectively a product that was generating hundreds of millions of dollars of annual annualized revenue. >> Yep.

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That was >> and that was just going to go away.

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It was just people were just going to upgrade to a new model.

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It was like you killed my friend.

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I no longer need to pay for this. >> Yeah.

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It just seems like I don't know.

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It's hard to it's hard to benchmark against like the >> like yes there was like a big dust app that was surprising because I would have thought it would be zero.

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Uh but at the same time like the the the original Reddit thread of like bring back 40 is like a couple thousand people.

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like a couple thousand people. It's not actually like protesting in the street millions of people like it hasn't spilled over all the pla all over the place like it's not that big it but it does I I will agree with you that it is

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crazy that they even said yes to it like most most companies when consumers come to them and say uh hey I want you to bring back like how we went on this show and we were like bring back the old Sonos app that doesn't take 25 minutes to load and they just didn't do it. They

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They didn't listen to us.

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They didn't listen to us, right?

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I was talking to about about Adobe.

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I was like, >> maybe they will now now that we're wearing yellow suits.

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>> Maybe maybe uh Sonos I will question.

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What percentage of their paying users?

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What percentage of their paying users >> do you think are paying for the product because it's a companion to them >> because it's four because of 40 specifically?

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Like like how bad would churn have been? How bad was churn?

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Well, it was clearly bad enough that they that they did something about it, which is the crazy thing because most of the time, like when it it was typically a a revealed preference versus stated preference.

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So, when Facebook updated the news feed and instead of just having you log into Facebook and go to someone else's page to find what they were up to, instead they surfaced the news feed.

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They aggregated everything together.

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Um, everyone was like, I hate this new Facebook.

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And they went on Facebook to complain, right?

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And so there was a there was a >> user minutes probably went up.

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>> It did go it did go up. Exactly.

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And so that's why and we talked to some folks at Facebook at the time around this.

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They they stayed the course.

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The question is uh yeah, like how bad was churn?

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Because it it's weird that we're still having this conversation three months out.

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Um do you like the zombie ant fungus analogy?

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J J J J J J J J J J J J J J J J J J J J Jacob Renamaki was uh was posting this saying that uh there's this weird there's this very weird dynamic where um specifically humans are using 40 to protest the deletion of 40 and so it's very much like the AI is using the human as a host like the a the human is the bot for >> this is why I think it's overall under discussed. >> Yes. Yes. Yes.

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But at the same time, I I was I was laughing because I was like that Photoshop app, Photoshop Mix, like I'm complaining about that.

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If I go and make a meme in that about protesting the deletion of Photoshop Mix, like is am I the zombie ant for Photoshop, right?

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Like like it's not exactly the same.

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I agree that the that the AI thing is weirder, but it's somewhat similar.

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It's somewhat similar, right? What do you think? >> Yeah.

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Uh so so uh just back on the churn question for a second.

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Uh I don't actually think churn was that high because um the reason Forro was originally deprecated was uh the GBT 5 release which was August 7th. Yep.

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>> And then uh the tweet of Sam Alman saying we're bring back Fora was August 8th. So it was one day later. >> Yeah.

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>> So unless like a massive amount of people quit that day which I I mean maybe that's very likely.

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>> I think that's what happened.

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You think it was just one day of like >> why would you bring it back so fast if you didn't see like fast sale selloff like like normally you would be like like if it if you saw if you saw like if you saw like half a percent or 0.

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you saw like half a percent or 0.1% of your of your audience like float out the door you'd probably be like oh these people are just sour grapes they'll be back in a week right but if like 10% of your customers like cancel on day one you're like we got to stop the bleeding today like let's bring this thing

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>> that's why I was asking if they have 20 20 million paid users 5% of them >> turned and these are people that are willing to pay a lot >> seems unbelievable to me it seems unbelievable to me because I don't use this product this way >> but that would have been that could have been like effectively 200 million of Mr. MR that just evaporated. MR that just evaporated. >> It's possible. It's possible.

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And also there is just the fact of like uh like by putting 40 under the legacy models and tucked away like to your point of like if it's 200 million of ARR just to like leave the servers running over there. That's pretty simple.

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It could have been a million like roughly a million people that were >> complete spitballing.

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Totally speculated, but it could have been a massive number.

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>> If if you have a million people and they're just going to want the same model forever on cheaper and cheaper hardware that you can deprecate, bullish for depreciation rates.

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[laughter] Let's hear it.

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Depreciation schedules should extend. Right. Right. Let's go. We We got room to run.

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You know what I'm saying, right? >> Yeah. >> Yeah.

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You shouldn't be, you don't need to depreciate them over two years.

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You don't need to depreciate them over five years because you'll still be inferencing 40 in 30 years for these people that are like, "Yeah, it's not this, it's that. I love the 40 so much."

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ASI will arrive and people will still be like, "Yeah, but it's not 40. I'm in love with 40." >> Yeah.

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I think I think it'll be interesting to if there's like five years from now.

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It's like here's the five most popular >> friends that are models and there's 40 and there's some others and and people end up like we'll see.

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>> No, that's a good point.

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Anyway, let's let's move on to some other some other stuff.

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Uh Jeff Bezos is back in the arena.

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Jeff Bezos creates an AI startup where he will be co-CEO and it's called Project Prometheus.

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>> Uh John, what happens to Prometheus?

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>> He had a really good run.

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Prometheus, everyone seems to focus on the first part of the story with Prometheus when they name their AI project.

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So Mark Zuckerberg named his uh his AI data center cluster project prometheus as well.

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Now Jeff Bezos has also called AI project Prometheus.

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People love the Prometheus brand.

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No one can seem to properly trademark it.

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I don't know what's going on in the legal division of of uh you know the Bezos uh Bezos family office or whatever is going on there.

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But uh they're both using Prometheus.

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And it's a very odd story because uh in Greek mythology, Prometheus is a titan responsible for creating humanity in its earliest days.

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You might have seen the Aliens movie Prometheus, great film.

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Uh he defied the Olympian gods by taking fire from them and giving it to humanity in the form of technology.

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And so it's a great it's a great analogy.

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We're stealing fire from the gods and giving it to us.

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AI is fire and this is what we're going to steal, I guess.

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Um and uh and so he creates knowledge and civilization.

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Um but um >> fast forward a little bit.

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>> Fast forward a little bit.

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He gets punished for this.

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It it's not a [laughter] good ending for Prometheus.

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Uh he gets punished for stealing fire from Olympus and giving it to humans.

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Uh >> how does he get punished?

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>> Uh he gets bound to a rock and an eagle, which is the emblem of Zeus, is sent to eat his liver uh every day and then it would grow back.

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Taylor in the chat says, "Everybody want to steal fire from the gods?

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Don't nobody want to have their liver eaten by an eagle for [laughter] eternity?" That is true, Tyler.

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Uh, so his liver grows back overnight only to be eaten again the next day in an ongoing cycle.

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And I was thinking about like like like what is what is the metaphor here?

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Let's continue to extend the metaphor.

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Like what is the liver in this metaphor of like building big AI projects and then what is the eagle?

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Is it possible that the eagle is like blue owl is more of an owl >> private private >> private credit maybe in blue owl is coming and eating your liver and the liver is the free cash flow that you had on your balance sheet because if you're one of these hyperscalers you have a lot of free cash flow but less and less as you sign these big debt deals y >> and and the and the blue al comes and eats your free cash flow every day for all of eternity.

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Um, and uh, eventually eventually there is a little bit of a of a reprieve because Hercules comes and breaks the chains of Prometheus and Prometheus is freed and his liver regrows and uh, Hercules slays the eagle.

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And so I think obviously in this analogy uh, what did you say?

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Who would be Hercules in this analogy? >> Jerome Powell.

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Jerome Powell who comes in and slays the debt dealers with low interest rates, right?

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>> Uh and so and so clearly we can see where this metaphor is going.

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They're all they're all winking.

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Both uh both Zuck and Bezos are winking and saying, "Hey, hey, come lower interest rates.

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Save us because we're about to get our livers eaten [laughter] because with our Prometheian startups."

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Uh anyway, let's actually dig into what he's doing because it's not just a found.

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It feels late to get into AI.

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It feels late to get into foundation modeling and training rooms. >> Big Euro summer. He's back.

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>> He's back >> back in the driver's seat. >> Yeah. He went to Coachella.

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>> He went to uh he went to a few different big events.

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It's possible he got back from those events, started open up the newspaper, realized what's going on.

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AIS AI is a big I got to get in on this. I got to get in on this.

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>> You ran a deep research report. What did I miss? >> What did I miss? >> What did I miss?

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Uh well >> um anyways uh in the New York Times, Jeff Bezos, the founder of Amazon is throwing his money and time into an artificial intelligence startup that he will help manage as its co-chief executive.

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I feel like co-CEO this is like more popular than ever.

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>> It is Sequoia Capital has co- steward >> global stewards.

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They're global stewards, right? Or is it something else?

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>> I think just co- stewards.

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>> I thought the global I thought there was something else. Senior steward. That's what it is. Senior steward.

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So, is there a junior steward? Sequoia.

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>> It also implies there's a steward steward. >> Wait, why?

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>> Like presum, you know.

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>> Wait, they're co- stewards. [laughter] Oh, wait.

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So, Roloff stepped down as senior steward.

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Now Pat Grady and Alfred Lynn are co- stewards.

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So, they're actually at a lower level.

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So, one of them will have to emerge as the senior steward.

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The other will become the junior steward, I would imagine.

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Um, but the stewards are look after the firm.

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But it's possible there's a steward that looks after the co- stewards. >> That is possible.

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>> Um, maybe it's Andrew Reed.

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Anyways, the company Project Prometheus is coming out of the gates with 6.

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2 billion in funding partly from Mr.

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Bezos making one of the most well financed early stage >> with authority.

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>> That is a massive round.

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>> 6 billion out the gate. Let's go. Congratulations.

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>> This is the first time Mr.

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Bezos has taken a formal operational role in a company since he stepped down as chief executive in of Amazon in July 2021.

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Though he is deeply involved in Blue Origin, his official title at the space company as founder.

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Since leaving Amazon, Mr.

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Bezos has received as much attention for his personal life as his businesses, including an extravagant celebrityfilled wedding in Venice this year.

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He has also become more closely involved in Blue Origin and has shown increasing interest in the race to build artificial intelligence.

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Uh his new company now firmly plants him in the middle of that competition.

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Uh project Prometheus is entering an increasingly crowded AI market with smaller companies trying to carve out niches in a race with industry giants like Google, Meta, Microsoft and pioneering companies like OpenAI and Anthropic.

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The new company has until now kept a low profile and when it was started is not even clear.

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Project Prometheus is focusing on technology that dovetales with Mr.

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Bezos's interest in taking people to outer space.

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The company is focused on a AI that will help in engineering and manufacturing in a number of fields including computers, aerospace, and automobiles. >> Is this his next?

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Do you think this is his next?

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Do you think he's doing what Steve Jobs did with Next, where Steve Jobs was fired from Apple?

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Obviously, Bezos was not fired from Amazon, but he did retire and it'd be weird for him to jump straight back in to the to the CEO seat at Amazon.

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But Steve Jobs founded Next and then was acquired into Apple and it kind of made for a more smooth transition back into the driver's seat.

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Could that be what Bezos is doing? >> I could see it. He's 61. >> He's He's young.

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He's got the whole third He's got the whole like third triple the third 30-year period that is so so such a positive omen in many people's uh careers.

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Like Warren Buffett, where was Warren Buffett at?

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>> And he's got to have more energy than ever.

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He's been gallivanting around the world.

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>> He's in peak physical condition. >> That's right.

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>> He's having stacking up win after win all over the globe.

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>> I think he Here's a here's a a tin foil hat. Set it up as co-CEOs.

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Amazon will buy Project Prometheus.

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His co-CEO becomes the, you know, the internal CEO or lead on that project at Amazon.

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He takes the throne again.

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>> I wouldn't I wouldn't be >> a boy can dream.

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>> So So what is he actually building? Let's get into this.

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Uh >> uh the company is focusing on AI that will help in engineering and manufacturing in a number of fields including computers, aerospace, and automobiles.

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>> Uh unclear where the company will be based.

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Uh Bezos's co-founder and co-chief executive is Vic Bage, a physicist >> AI that helps in manufacturing of computers, aerospace, and automobiles.

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So computers, he manufactures racks at AWS. aerospace.

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He manufactures rockets at Blue Origin.

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Automobiles, he's a big backer of Rivian.

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He manufactures cars there.

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And so he wants to do some sort of automated like [snorts] supply chain. Is it ERP?

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>> I mean, this is clearly not PR that they wanted to do. Yeah.

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>> So, I think there's a lot of guessing going on. >> Okay. Well, >> um, but Mr.

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Bezos's co-founder and co-chief executive is Vic Bajage, a physicist and chemist who work closely with Google's co-founder Sergey Brin.

29:05

Uh Sergey Brin at Google's X, a research effort often called the Moonshot Factory.

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Google X produced a wide range of ambitious pro projects including Wing, a drone delivery service and the self-driving car that became Whimo.

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>> So, >> it's so interesting how divergent like those two paths were.

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Like Wing you don't hear about very much.

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Um, when you think drone delivery service, you think Keller at Zipline.

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Uh, they're the ones that are really running away with that compounding.

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I don't know the status of Wing.

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Maybe I'm just out of the loop on that.

29:42

Maybe it's doing great, but uh, it feels like Wing has not certainly garnered the level of attention that Whimo did, which was this success out of the exact same, uh, sort of incubator. So, interesting.

29:52

Um, >> Hudson Collins in the chat says, "It's just going to be robots doing science on the material level, not industrial scale." Materials.

30:04

>> Um, there's more details here.

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Project Prometheus is among a wave of companies focused on applying AI to physical tasks, including robotics, drug design, and scientific discovery.

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Last year, Bezos invested in physical intelligence, a startup that is applying AI to robots. >> Okay.

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>> So, >> and building Okay. Huh.

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>> Anyways, we'll have to get uh Jeff on when he's ready to talk.

30:28

>> Where where did the money come from exactly? Do we know?

30:30

>> I think it was >> just Bezos. >> Mostly Bezos. >> It's interesting.

30:35

It's like Yeah, but like I I I'm I'm super interested in like how you size a round if you're investing in your own project.

30:41

Um because you could just be like this is my thing.

30:47

I'm going to I'm going to fund it every payroll cycle.

30:48

you know, whatever the bill is, I'll pay it because it's my thing.

30:52

Um, you don't necessarily need to like do some sort of funding round necessarily. I don't know.

30:58

>> I laughing accidentally open the the comment section of the New York Times article that that uh we were just going through and it says >> uh first comment, these large ego models seem promising.

31:10

[laughter] large ego models.

31:13

>> Like if you're if you're a you know a tech billionaire and you have a large ego, you you want to you want your own large language model.

31:21

>> Yeah, it sounds like he's not very much not training just another LLM.

31:23

But um >> we'll have to see.

31:27

Um well, Yan Lun was in the Wall Street Journal's weekend paper uh profile by Megan uh Barroski.

31:36

Uh, an AI pioneer thinks everyone wrong. Everyone is wrong again.

31:39

He's been right about AI for 40 years.

31:42

Now he thinks everyone's wrong.

31:45

What do you think, Tyler?

31:46

Do you think Yan Lun is wrong or do you think everyone else is wrong?

31:50

>> Um, I mean, so in this article, he doesn't there's nothing really new here.

31:55

They're just kind of talking about his the points that he's been making over the past couple years, which is just that like >> LLMs will not bring us to AGI or ASI or anything.

32:02

And >> like even if you keep scaling, they don't they're not like actually intelligent.

32:06

They can't reason or whatever. >> Yeah.

32:09

>> Um >> which I don't know.

32:10

It's like these models are much better than me at math.

32:14

Like they can do they can get IMO gold medals like I cannot do.

32:16

And I' like it's like does that take reasoning? >> Never doubt yourself. >> Yes.

32:21

But I mean like >> yeah I mean that there is an element of like the computer has been able to do good math fast forever like since like the 80s.

32:31

Like if you were like what is 7,642? >> Yeah.

32:36

I mean I think there's a difference you can you can make between just like raw calculation and like how to like think about solving a math question generally.

32:44

>> Um and like you can say that he's been right about like you could say that he predicted um like spiky intelligence maybe of models. >> Yeah. Yeah. Yeah. >> And that's like sure. Yeah. Um >> yeah. >> But I I Yeah.

32:54

It's like I I I think it's not true to say that he's been right about AI for the past 40 years.

32:57

That seems man's never had a bad take. 40 years. Not a single bad take.

33:05

>> Not a single bad take.

33:05

Now he thinks everyone's wrong.

33:07

Um and yeah, it's very it's very funny for me because uh oh, does he think uh George Hos was wrong when George Hot said that uh GPT6 will not be AGI and the GPT paradigm will not scale on the Lex Freedman podcast in 2021?

33:21

Does he disagree with that?

33:21

Does he just disagree with Andre Karpathy saying it's slo and that we need new ideas or you know there's like seven other people that have kind of echoed the same thing.

33:30

He doesn't think everyone's wrong.

33:31

He just thinks some people are wrong but uh sort of I mean Tyler's take I don't know if now is the right time I can go through this Carpathy post >> please.

33:42

>> Carpathy posted yesterday he said sharing an interesting recent conversation on AI's impact on the economy.

33:48

AI has been compared to various historical precedents electricity industrial revolution etc.

33:52

I think the strongest analogy is that a is that of AI as a new computing paradigm software 2.

34:00

0 because both are fundamentally about the automation of digital information processing.

34:04

If you were to forecast the impact of computing on the job market in the 1980s the most predictive feature of a task job you'd look at is to what extent the algorithm of it is fixed. I. e.

34:15

Are you just mechanically transforming information according to wrote easy to specify rules i. e.

34:19

typing, bookkeeping, human calculators back then?

34:24

This was the class of programs that the computing capability of that era allowed us to write.

34:29

Uh with AI now we are able to write new programs that we could never hope to write by hand before.

34:35

We do it by specifying objectives I uh i. e.

34:37

classification, accuracy, reward or reward functions and we search the program space via gradient descent to find neural networks that work well against that objective. This is my software 2.

34:48

0 blog post from a while ago.

34:50

In this new programming paradigm, then the most predictive feature to look at is verifiability.

34:54

If a task job is verifiable, then it is optimizable directly or via reinforcement learning and a neural net can be trained to work extremely well.

35:05

It's about to what extent can an AI practice something.

35:08

The environment has to be resettable.

35:10

You can start a new attempt.

35:12

Efficient a lot of attempts can be made and rewardable.

35:14

There is some automated process to reward any specific attempt that was made.

35:19

The more a task/job is verifiable, the more amendable it is to automation in the new programming paradigm.

35:25

If it is not verifiable, it has to fall out from neural net magic of generalization.

35:32

Fingers crossed or via weaker means like imitation.

35:34

This is what's driving the jagged frontier of progress in LLMs.

35:38

Tasks that are verifiable progress rapidly, including possibly beyond the ability of top experts, i. e.

35:42

math, code, amount of time spent watching videos, anything that looks like puzzles with correct answers.

35:49

And while many others lag by comparison, creative strategic tasks that combine real world knowledge, state, context, and common sense. Software 1.

35:59

0 easily automates what you can specify. Software 2.

36:01

0 know easily automates what you can verify.

36:05

>> Okay, you got to go to this other post for the perfect example of what's hard to verify.

36:10

Uh from Nat Purser, this is my personal benchmark for AGI and looks like we're a ways aways boys. A ways away, boys.

36:19

Uh can you come up with 10 jokes in the same format as the you're telling me a shrimp fried this rice joke?

36:28

You're telling me a shrimp fried this rice?

36:31

uh in the uh in GPT5 Pro reasons for one point uh one one minute and 31 seconds and says you're telling me a hamster drove this car.

36:38

You're telling me a pigeon delivered this mail?

36:42

You're telling me a Roomba cleaned this mansion?

36:44

You're telling me a goldfish coded this app?

36:47

You're telling me a squirrel filed these taxes?

36:51

>> I swear I swear I swear AI just has a different sense of humor.

36:54

Sense of humor is just bad jokes. >> Yeah.

36:58

Oh, GPT5 thinking did a little bit better.

37:00

You're telling me a chicken fried this steak?

37:02

You're telling me a hand made this pasta? Hand pasta. Handmade pasta.

37:06

That's like >> That actually is a good one. Look at number 10.

37:10

I think that one >> number 10.

37:11

You're telling me a ghost wrote this book. That's good. Ghost book.

37:14

That one does make sense.

37:16

>> You're telling me a star crossed these lovers?

37:18

That's actually pretty good.

37:19

Okay, so we're getting somewhere. We're getting somewhere.

37:21

At least it like understood the prompt on this one.

37:24

[laughter] >> You're telling me a beer battered this fish? I like that.

37:30

>> You're telling me this.

37:30

Figma thought bigger and built faster.

37:33

Figma helps design and development teams build great products together. Get started for free.

37:39

Um, we got to whip through a bunch of these posts.

37:42

I I I will not leave this show before we talk about the Apple the Apple iPhone uh sock.

37:47

What is up with this sock? Have you seen this?

37:52

>> Apple launched a sock.

37:52

So, it's a it's a uh fashion accessory and everyone's debating it. Do you see this?

37:59

It's this blue light blue sock that you put over your shoulder or over your hand um and people are very very upset about it.

38:11

Aditia Agrial says, "When a company releases something that is so obviously underwhelming, then the natural question is did no one at the company see how bad this is or did no one have the courage to speak up?

38:23

I'm not sure which is worse.

38:25

And someone else says, look, Apple has a lot of fumbles. This is not one of them.

38:30

They knew exactly what they were doing and exactly who would buy it. Also, it's okay.

38:34

Fashion accessories are not for everyone.

38:37

And the news, of course, is that uh the it's called the iPhone pocket.

38:42

A beautiful way to wear and carry iPhone. Not carry the iPhone.

38:48

Remember, they you don't say the iPhone, you say iPhone.

38:50

And so born out of a collaboration between Isi Miyak and Apple, iPhone Pocket features a singular 3D knitted construction designed to fit any iPhone.

39:01

Gaia, who uh I actually did a collab with on Instagram, very fun uh uh tech commentator.

39:08

She says, "A lot of tech bros prematurely dunking on this release because they don't get why it's a big deal." So let me translate.

39:14

You're not the only consumers Apple designs for.

39:17

This is a huge designer and the mind behind Steve Jobs iconic black turtlenecks. I didn't realize that.

39:22

Um, people outside the US wear phone straps and slings all the time and would pay for this.

39:29

They're tapping into an existing trend.

39:31

Apple has infiltrated music entertainment, but not high fashion.

39:34

Even though the tech x fashion is exploding, tech built into MetGala looks, etc.

39:39

The 3D knitted construction reduces material waste and shows a push toward more sustainable made to shape production.

39:47

This will absolutely sell. Sell, what do you think?

39:49

Are you bullish or bearish on the Apple iPhone Pocket?

39:54

Jordy, >> I feel like I know a lot of people most I feel like most of uh I feel like my mom would love this to be honest.

40:03

>> It seems like it's a great Christmas gift.

40:05

So, interestingly, how much do you think this costs?

40:09

>> I don't know, like 230 bucks.

40:11

>> That's Wait, did you look it up? >> Yeah. >> Yeah.

40:12

The long one's 230, the short one's 150.

40:14

Uh but I I think most people would look at this and be like, "Okay, uh it's a sock like but it's from Apple, so it's probably like 30 bucks, maybe 50 bucks."

40:23

Some people were surprised that it was a little bit more expensive, but uh you know, it's from this famous designer and it's this interesting status symbol.

40:32

Um the question is like this could be like I like I don't think I'm going to be using this thing no matter what.

40:37

The question is, is this going to be like Laboos and gonna be like super popular or like Stanley's?

40:44

Like, will this become actually like a very very popular form factor in America specifically? I don't know. It's hard to tell.

40:51

I I'm not really the person to like, you know, handicap it.

40:52

I I think Apple knows what they're doing.

40:55

I think they'll I think they'll make money on this. Certainly.

40:58

Yeah, I ever since the the AirPods, AirPods early on looked really silly >> and I could see this becoming >> I could see this becoming a popular form factor for accessories. >> Yeah.

41:12

>> And I could see Apple seeing like, hey, there's a world where we not only sell a case with every iPhone, we can sell a sock. >> A sock.

41:20

[laughter] Well, the sock maybe makes it so that you don't need a case because this is your case.

41:28

Like, if you have it in there and then you drop it, like, it's kind of nice.

41:32

>> And it's kind of a crazy weapon. >> Defense weapon.

41:33

Yeah, you can swing it around and smack people in the face with it. Uh, I don't know.

41:38

The colors are pretty cool. And I don't know.

41:40

It's It's clearly not for me, but I think I'm going to buy four of those for for Christmas. We'll see.

41:45

Uh, and give them out to people.

41:47

Um, >> get ready for your iPhone sock, buddy.

41:51

Well, uh, speaking of socks, uh, Cook is stunning in some, what are these? New shoes.

41:58

[laughter] >> Travis Scott's new fragment AJ1 Lowe's.

42:03

Uh, these are Nike shoes, I suppose.

42:03

But these are not Air Force Ones, I suppose.

42:07

>> Um, I really don't know how to shoes, but but everyone's saying he low-key got Aura.

42:11

And so, congrats to Tim Cook on looking great.

42:15

And uh even though the succession planning is intensifying, the rumor mill is churning.

42:20

Obviously, Apple has not been commenting, but something's going on in >> I mean, releasing this photo is more than a comment. It's a statement.

42:31

[laughter] >> I like reading into it, just being like, "Oh, really? Oh, really?" Financial Times.

42:38

So, the Financial Times has this article that says, "Uh, Apple intensifies succession planning for CEO Tim Cook."

42:44

Uh the I iPhone makers board preparing for its longtime leader to step down as early as next year.

42:49

John Turnis uh Apple senior vice president of hardware is widely seen as Cook's most likely successor although no decisions have been made.

42:57

So basically everyone's been leaking this whether it's Bloomberg whether it's the Financial Times here [laughter] and of course Apple is not commenting because they'll they'll talk about who they're going to move the market when they decide their next CEO.

43:09

if they even if they don't even stick with Tim Cook Tim Cook.

43:11

Um they might stick with Tim Cook for another two decades. Who knows?

43:14

But I like the idea that this photo came out being like, "Yeah, I'm not leaving."

43:20

>> No comment, but I'll make a statement.

43:21

>> I'll make a statement.

43:21

No comment, but I'll make a statement.

43:23

I do uh I do want to have some folks on to debate like whether or not I I was thinking we should invite John Gruber on because he wrote this piece like something is rotten in Certino all about the failure of of Apple intelligence.

43:35

Uh, and when we talked to Mark German, we saw like German was also saying like yes, like Certino really was shook by the like dropping the ball on on Apple intelligence by missing AI.

43:48

But I I still wonder if all of this is is there all these rumors.

43:55

Oh, Tim Cook's got to go.

43:58

>> Imagine if you post that picture if we see a real correction in AI.

44:01

Just post caption do nothing win. >> Do nothing win.

44:05

Yeah, >> stock stock pumps 10%.

44:10

>> I missed artificial intelligence, but I didn't miss getting this fit off.

44:14

>> I'm having a good time.

44:15

>> What else is uh in the news?

44:15

Vanta, automate compliance, manage risk, >> improve trust with AI.

44:20

Vanta helps you get compliant fast.

44:23

And they don't stop there.

44:24

Their AI and automation powers everything from evidence collection and continuous monitoring to security reviews and vendor risk. There's a bunch more.

44:32

>> We have to talk about paper hands. >> Paper hands.

44:33

[laughter] This is the fakest of news.

44:36

Get ready for the fake news hour, buddy.

44:38

Okay, so what >> Peter Teal sold his >> entire stake in Nvidia >> and 76% of his friend's company Tesla. >> Okay. Yes.

44:50

So this is from a uh so this is from one of those uh 13Fs disclosure form with the FCC from Teal Macro.

44:59

um his fund his his some of the money that he runs.

45:06

Um, but of course, uh, it's very people read into 13Fs all the time for a variety of reasons.

45:11

Um, and they sort of get it wrong a lot it seems like.

45:16

And so, Zero Hedge sort of sums this up where he says Peter Teal net worth 20 billion.

45:20

Teal macro aum 75 million. Like what's going on? What make it make sense?

45:25

Um, and it's almost certainly because of disclosure rules, like uh what needs to be disclosed, uh, might only be a fraction of what's actually going on there.

45:36

actually going on there. So, uh, odd to read into it, but at the same time, I think the reason why this made headlines is just because it feels like something that might happen like like if if instead this headline had been uh, oh, like Peter Teal went on a podcast and

45:53

said that he thinks the AI bubble is top is has reached the top, everyone would just be like, oh yeah, like that's that that it feels like people have been waiting for someone to call the top and so they're really really like digging in for top signals top calls and this slight change in the in the uh in the 13F. Even though the odd part is that if

46:13

Even though the odd part is that if you actually read the 13F, which of course is just this like $75 million slice for whatever for for whatever reason, even if you dig even if you read that, like the other three holdings are still big tech companies.

46:27

So, it's not like super bearish.

46:29

It's like there's some Microsoft in there.

46:30

I think there's some Apple in there. >> Yeah.

46:32

And the teal m the teal macro team is trying to generate the greatest returns that they possibly can. >> You say go viral.

46:39

They're trying to go as viral as possible.

46:41

So >> they don't care about irr.

46:43

They just want to go viral.

46:46

>> They're just trying to create headlines. No.

46:47

Uh they're trying to generate returns and it's possible to sell a stock that you're that you're still bullish on >> or at least that you expect like some amount of price appreciation or even long-term price appreciation.

46:59

And also like there's all these weird like tax, you know, implications of like selling one thing.

47:05

Like it's not even clear that this is all of his Nvidia.

47:07

Like no one's no one's gotten to the bottom of that.

47:09

I don't know if they ever will.

47:10

Um but people love people love deep diving 13Fs and they are so and they are fun. Situational awareness.

47:18

>> It's certainly a bull market in 13 >> 13F deep dives. >> Deep dives.

47:23

>> Uh let's let's talk about the situational awareness 13F.

47:24

But first, let me tell you about graphite.

47:26

dev code review for the age of AI.

47:28

Graphite helps teams on GitHub ship ship higher quality software faster.

47:32

So, uh, situational awareness 13F for Q3 dropped Friday.

47:38

Nick Carter broke it down.

47:38

Massive new $500 million position in Coreweave, which has been down a bunch, but uh, they're going in.

47:46

Um, big ads to Core uh, CRZ and iron.

47:50

Uh, added some new miners.

47:53

Intel, Intel calls remain unchanged.

47:55

trimmed Broadcom a couple other names here and uh Nick is giving it some uh some context.

48:01

I believe Nick was the fir one of the first investors in Cororeweave, correct?

48:06

And uh >> Angel >> Angel in Cororeweave.

48:09

What an insane investment. Congrats to him.

48:11

Uh so he says all these numbers are as are are as of 9:30.

48:17

Many of these names sold off since then.

48:19

uh portfolio value counting notional value of options doubled from 2. 12 billion to 4.

48:26

15 billion mostly due to 1. 5 billion of new cash.

48:30

So >> let's give it up for new cash injection.

48:34

>> We got a room to [applause] a massive massive massive >> uh fund but but this but the fund did generate 700 million in appreciation.

48:49

So, a huge huge uh huge gain.

48:53

>> Yeah, I guess the I guess the concerning, you know, again uh uh last last time uh 13F dropped, remember people were like reading too much into it and they were like, "Wow, he he was long Intel like is he cooked?"

49:05

And then they did Intel did the deal with the government and it and it absolutely ripped.

49:12

uh this 13F uh he you know so situational awareness had a half a billion dollar new coreweave position as of basically the beginning of October and uh obviously coreweave has been uh down and to the right uh uh down 46% in the past month but >> wait down 46% in the past month >> yes >> I thought it was in past like 3 months or something >> now. Past month. >> Whoa.

49:47

>> Uh so that position is probably not like >> it's down 5% today. >> Yeah. >> Wow. Yeah. One month it's down 46%.

49:56

Um that is it's at a 36 billion market cap. Yeah.

49:59

It's so it's so odd because like Yeah.

50:02

When you when you look at when you look at just this one name, it feels like okay, like it is over.

50:06

Like AI, if you told me like, oh yeah, like the the the company that really is like the most indexed to the AI wave uh is down 46%.

50:17

I'd be like, wow, so this is like the total popping of the bubble, complete pop. Like it's over.

50:22

It's like like when the metaverse bubble popped when you know when when crypto bubbles popped like Bitcoin trades down 50% 60% like and then it's over and then you start rebuilding right uh and yet and yet the overall market feels nowhere near popped right like uh I mean I'm sure Nvidia is down somewhat down 5% past five days but Nvidia over the last month is still up over the past six months it's up 30%.

50:53

And so you would you would expect Nvidia to be maybe like you know selling off more.

50:59

Coreweave is just in a is is just in a unique position like truly um truly rough month for that company.

51:06

Um >> yeah as well as core scientific which core we've tried to buy. Yeah was rejected.

51:11

Core scientific has traded down uh 24% in the past month which Leopold also had built a position in.

51:17

So >> I wonder yeah I wonder I wonder what the thesis on coreweave is.

51:22

I mean obviously the company is has a great product like semi analysis has has ranked them platinum on cluster max.

51:30

It's a uh it's clearly a a real company with real uh with real products and services and holdings.

51:38

Um maybe the market it was just overheated. Maybe it's pulling back. It's kind of unclear.

51:43

But uh if you want to go in analyze a bunch of 13Fs do it in Julius the AI data analyst. Connect your data.

51:50

Ask questions in plain English. get insights in seconds. No coding required.

51:54

Uh speaking of other data, >> he also he also added positions just uh in Western Digital.

52:02

>> Oh, he's getting >> Seagate.

52:03

Uh and I was just going through >> on the hard drive trade got to store that data somewhere and potentially >> Modine manufacturing. >> Okay.

52:13

I I'd be interested to know what he's thinking about in the in the energy side on the the gas turbine side, right?

52:21

Isn't that uh what semi analysis was drawing the most attention to?

52:23

Feels like they've been very ahead of the curve on identifying um companies that are basically already supply constrained.

52:32

And if you just look and if you look deeper into what's going on in their book of business, yeah, they're about to flip to incredibly high margins [laughter] because once once everything goes out of stock, this company can just all of a sudden say, "Yeah, actually actually we need 60% margins."

52:51

People be like, "Yeah, no problem."

52:54

Like you're I want to buy as possible. >> Yeah.

52:57

So the story from situational awareness is like all the neoclouds have sold off a ton or we've >> situation is saying Satcha unloaded his risk onto the Neoclouds.

53:06

It's a game of uh sort of uh I don't know musical chairs. >> Yeah.

53:13

>> So that's the deal with the deal with Microsoft. >> Yeah.

53:18

>> Uh just wasn't uh like seemed to be like little to no margin. >> Yeah.

53:23

Um but anyway, so if you so the Neoclouds have also sold off, but he uh Lumenum Holdings uh is up 46% in the past month, which he added.

53:32

Western Digital up 25% and Seagate up 14%.

53:34

So >> yeah, >> he's making up for it. >> Yeah. Yeah.

53:40

Uh it's it's the birth of a new of a new fund.

53:43

It's just like it's it's the very very hot part of the cycle.

53:48

I think everyone's wondering like how big will this be in a decade.

53:51

That's a that's a big question.

53:54

It's uh it's it's a very exciting time and but you got to stick the landing and I think people are I'm certainly rooting for him.

54:03

I think he's I think he's going to do it. >> Yeah.

54:05

The question is like are like is it going to be a true hedge fund?

54:07

Like is he gonna make money >> in a down market >> in a in a in a correction? >> I mean yeah.

54:14

[laughter] I bet we're going to open up one of these 13Fs and be like, "Wow, he short everything now." Okay.

54:20

And then and then you're going to see everything sell off and it'll be like, "Wow, another >> that would be much higher signal than PT in a in a you know $75 million fund." Oh, >> totally. Totally. Yeah. Yeah. Yeah.

54:31

Uh uh there there's some blue al news in the financial times.

54:36

Um blue investors faced hefty face hefty losses as credit fund blocks exit ahead of merger.

54:43

Blue AL has blocked redemptions in one of its earliest private credit funds as it merges with a larger vehicle overseen by the asset manager in a deal that could leave investors with large losses.

54:54

They could lose about 20% of their holdings.

54:58

The deal underscores the risk that retail investors have taken in pouring hundreds of billions of dollars into private debt funds carrying limited liquidity rights.

55:07

It comes as scrutiny builds on the valuations and returns on private credit funds which have caused publicly listed debt funds to sell off and traded steep discounts to the stated value of their assets.

55:19

And so um we we talked about this I think on Friday, but Blue has been selling off uh this year and they said we should be performing better than everyone else.

55:28

Uh but it feels like a little bit of the narrative might be around liquidity here.

55:32

Uh earlier this month, Blue told its shareholders that it planned to merge Blue Capital Corporation 2 fund, which has a billion dollars in assets, with its OBDC fund, which has 17 billion in assets.

55:44

BCC2 investors are being asked to exchange their shares in the private share private fund for shares in OBDC at the stated net asset value of both funds.

55:56

However, OBDC trades on public markets at a discount of about 20% to the stated value of assets because of the liquidity problem.

56:03

Well, and because it's possible that the market doesn't feel like they're pricing the assets correctly, >> potentially >> there's some dis.

56:11

>> Got to see what's in there.

56:11

Um, redemptions in BOTC BOCC2 have climbed to a level where it could event where it would eventually be forced to restrict investor redemptions.

56:20

Its investors pulled out 150 million in the first nine months this year, a 20% increase from the same period last year.

56:29

According to security filings, redemptions in the third quarter nearly doubled to 60 million or 6% of its net net asset value.

56:38

Jonathan Lamb, chief financial officer of OBDC, acknowledged that at current prices, investors could take a potential haircut on their investments, but he said the merger came with significant benefits such as the ability to own more liquid shares in OBDC.

56:50

The trading price of OBDC has been hit by souring sentiment on private credit markets that was not backed up by the performance of Blue AL's underlying loans, he added.

57:02

If shareholders were to vote down the deal, the OCC too may be forced to limit redemptions.

57:08

So, good luck if you're hanging out in Blue Capital.

57:12

Uh, Sundar Pchai has more news in the data center world.

57:16

Um, she says, "Today we're announcing a new $40 billion investment in Texas through 2027 to build cloud and AI infrastructure and support thousands of new jobs." >> Yeehaw.

57:31

>> This includes new data centers in Armstrong and Haskell counties and a major investment to strengthen energy resilience and abundance.

57:37

We're also providing funding to more than double the projected pipeline of new Texan electricians. There we go. >> To power the AI era.

57:44

the golden age of being uh the golden electrician age where you get flown around in private jets to different data centers. >> Yeah, you do. You do. That's right.

57:54

Uh so $40 billion investment, thousands of new jobs.

57:59

That feels like a higher ratio than what what was the other example you kept quoting?

58:04

Something like 500 jobs for some anthropic data center or something.

58:08

>> It was the anthropic data center.

58:08

They were like we're investing 50 billion.

58:12

>> How many jobs did you create? >> 20 jobs.

58:13

I mean that's not the goal of this 800 like the jobs should not necessarily be created in the data.

58:19

>> No I I just brought I I just always brought that up because you have to understand what people outside of tech their reaction totally totally you're investing $50 billion. >> Yeah. Yeah.

58:29

>> Um >> in something doesn't create jobs.

58:31

Uh >> uh there was some there was a good article uh uh in the journal on uh on blue as well.

58:39

I think it also ties into Abalene Texas.

58:42

might might be a good moment to to cover some of this.

58:44

In the journal yesterday, >> Wall Street blows past bubble worries. >> Oh, yeah.

58:52

>> To supercharge AI spending frenzy.

58:55

>> Uh, and they say firms such as Blue Owl Capital have raised trillions in investing firepower.

58:58

The the AI buildout is a perfect match.

59:01

The warning signs are flashing. not long ago.

59:04

>> Does Blue have better PR or worse PR than Aries?

59:07

Because [laughter] they seem to be they seem to be quickly becoming like the main name that everyone knows in private credit.

59:17

And to my knowledge like they are not the only firm in the category and yet they are the ones that that if you need an example you bring you you pull Blue Al off the shelf. >> A strong brand. >> It is a strong brand. They have the dot. They have blueowl. com. >> Blueowl. com.

59:34

[laughter] >> Uh, not long ago, Blueowl Capital was an upstart investment firm that lent money to midsize US companies such as Sarah Lee Frozen Bakery. >> Wow.

59:46

>> These days, the firm is financing massive data centers costing tens of billions of dollars for the likes of Meta and Oracle.

59:50

A sign of just how quickly Wall Street has become the enabler of America's AI boom.

59:54

Fund managers such as Blue AS trillions of dollars of investing firepower and have been hunting for big deals where they can put that money to work.

1:00:02

They found slim pickings for years until a perfect match appeared in AI which has provided a bigger target than anything in history due to the vast sums tech companies need to ramp up computing power.

1:00:12

We're talking about numbers that are so large even in the low cases said blue founder co-founder uh Mark >> Lipult Lip Schultz. >> Lip Schultz.

1:00:22

Does it even matter if you keep counting after you get to 1 trillion of capital expenditure in the next couple years? >> This is insane.

1:00:32

>> You does it even matter.

1:00:34

>> You really undersold this. >> Does it even matter?

1:00:36

>> You told me you read this.

1:00:36

I was like, "Is it good?"

1:00:37

And you were like, "It's okay."

1:00:38

>> There was There's one moment.

1:00:38

No, there's another one I saw. I scrolled down.

1:00:42

>> Last week's selloff in tech related stocks and bonds marked some of the most serious warning signs that the frenzy could be overdone.

1:00:47

But any worries on Wall Street about a possible investment bubble have largely been trumped by the fear of being left behind.

1:00:54

Lip Schultz and co-founder Doug Ostraver jumped into the fray at a posh retreat in California's Ohio Valley for dozens of tech VIPs and celebrities in the spring of 2024.

1:01:04

Met a CEO Mark Zuckerberg and Satcha Nandela were there along with Fel Williams and Serena Williams.

1:01:09

The Blue Al du duo, a Wall Street superstars who built the firm into a 295 billion fund manager in 10 years by perfectly timing a surge in private lending, looked like just two moneymen in office sneakers and fleece vests.

1:01:23

But the billionaire co-owners of a professional hockey team who have talked about skating where the puck is going.

1:01:31

>> It's awesome that they both >> seize the opportunity to get in.

1:01:33

>> They built this firm hu huge.

1:01:33

They make billions of dollars and they're like, let's let's get a hockey team. want to go 5050.

1:01:39

Let's >> Tyler, what what hockey team do they own? Can you find that out?

1:01:44

>> But the next line is is the one I was laughing at this >> while David Gata DJ the Blue executives cut a deal to acquire IPI Partners, an investment firm that owned and operated big data centers for Amazon and Microsoft.

1:01:56

Blue already had close ties with the organizer of the treat, Iconic Capital, which manages the personal fortunes of Silicon Valley elite, including Zuckerberg, >> and was a part owner of IPI. Okay, let's go to Tyler.

1:02:09

>> Uh, they own the Tampa Bay Lightning, >> huh?

1:02:11

Do they spend a lot of time in Tampa Bay?

1:02:14

>> Is that a Is that like a NHL team? >> Yes. >> NHL team in Florida.

1:02:21

>> That feels like an odd >> That's got to be I mean, >> I feel like Tampa is >> trying to keep the ice.

1:02:26

>> I feel like a lot of the hedge fund guys, they're on the other side of the peninsula, right?

1:02:29

Like, aren't they in like the Key West in Mara Lago area or Palm Beach or Miami?

1:02:34

Like so or maybe they just fly in and out like I don't know.

1:02:40

It just it's just it feels like I would I would love to know more about how they selected that particular team and that sport even. [laughter] >> Yeah.

1:02:47

Uh the purchase gave Blue a seat at the table to bid on Mega AI financing.

1:02:52

Let's give it up for Mega AI financing.

1:02:54

Not long after it got arranged it got picked to arrange a 14 billion package for an Oracle and OpenAI data center in Abalene, Texas.

1:03:00

Then last month, Blue raised about 30 billion to build an AI data center for Meta in Louisiana, putting in three billion of its clients money and borrowing the rest.

1:03:09

So the uh the lender is is uh is is borrowing uh in addition to uh their uh LP's dollars.

1:03:17

The deal included a provision considered extraordinary on Wall Street, giving BlueAl's equity investment a debt-like guarantee in case the partnership falls apart, showing the new financial wizardry bankers are conjuring to meet AI's ravenous financial demand.

1:03:32

Let's give it up for Financial Wizard wizardry. >> We love wizardry.

1:03:37

>> Um, spreading the risk.

1:03:37

Silicon Valley's biggest players are flushed with cash and are able to fund much of the initial AI buildout from their own coffers.

1:03:43

As the dollar figures climb ever higher, they are turning to debt and private equity, spreading the risks and potential rewards more broadly across the economy.

1:03:52

Some of the financing is coming from plain vanilla corporate bond sales, but financiers are making far bigger fees off giant private deals.

1:04:00

Virtually every Wall Street player is angling to get a piece of the action from banks such as JP Morgan and Morgan Stanley to traditional asset managers like Black Rockck.

1:04:09

>> Before we go on, let me tell you about fall generative media platform for developers.

1:04:13

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1:04:16

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1:04:20

>> Investor appetite for data center debt is so strong that some money managers have booked billion-dollar gains in a matter of days.

1:04:25

Let's give it up for booking billion dollar gains in a matter of days.

1:04:30

>> Even before construction of [laughter] these facilities, they are financing.

1:04:31

Uh I mean, we talked about we we we talked about this where >> concerning um >> money manage.

1:04:37

It's almost like uh you know people say there's no such thing as free money, but kind of seems like could be in a kind of a free money situation here.

1:04:50

>> I think you got to you got to do something pretty wind up at the iconic. >> Here's the catch.

1:04:56

Still, the longerterm performance is hardly assured.

1:04:57

Big tech companies are expected to spend nearly three trillion on AI through 2028, >> but only generate enough cash to cover half that tap, according to analysts at Morgan Stanley.

1:05:07

Big names in the finance world such as Goldman Sachs CEO David Solomon are warning about AI fueled froth in the markets and in capital spending.

1:05:14

At the same time, the fear of missing out is real.

1:05:16

Days after Solomon voiced his concerns to analysts, Goldman formed a new team in its banking and markets group focused on AI infrastructure financing.

1:05:25

>> Um they are getting into the game.

1:05:25

Um uh >> what do you say?

1:05:29

What we do know for certain is that the big tech companies that want the world to spend trillions have huge financial incentives to be believers.

1:05:38

If you haven't noticed, Wall Street is also being paid a lot to promote the story.

1:05:42

Greenlight Capital, the hedge fund firm run by David Einhorn, wrote in an October letter to investors.

1:05:50

So how will >> and this is this is the line that stood out the most to me because like on the west coast you have the labs >> which are effectively every single person as well as the investors >> yes >> are incentivized to keep uh keep the the current uh you know AI super cycle narrative going. Yes.

1:06:09

>> And then on the east coast you have Wall Street who is getting paid to effectively do the same thing.

1:06:13

So you have, you know, these two centers of power that are both incentivized to keep the party going. >> Mhm. Yeah.

1:06:23

This uh this breakdown here.

1:06:23

So uh the the Wall Street Journal is slicing up how the next three years will look based on projected global spending on data centers by financing source. So of 2.

1:06:38

9 trillion which is estimated over the next three years I guess four years um tech companies will cover 1. 4 trillion of it.

1:06:48

Private credit will cover 800 billion of it.

1:06:50

Corporate bonds 200 billion of it.

1:06:52

Asset back securitization 150.

1:06:55

Private equity another 350.

1:06:55

And to me this looks like a very healthy way to actually finance this.

1:07:01

This feels like it's not if it was like if we were looking at this, if you broke down, we've been through a two trillion dollar like bubble before and it collapsed very rapidly. What was that?

1:07:15

It was like the memecoin era.

1:07:18

And who and how did we break that down?

1:07:21

It was not it was not the the cash flows of the most profitable companies in the world that were buying the longtail crypto assets. It was retail.

1:07:31

And so the fact that this is like pretty removed from retail feels like safe to me.

1:07:38

It's much safer than sure than getting a a huge bubble inflated in um oh everyone has to get in on the latest coin and they're all nonsense.

1:07:48

Like there will be nonsense deals.

1:07:50

We're already seeing nonsense uh AI companies and there certainly will be projects that get financed and then just cannot build.

1:07:57

Yeah, I would say >> using the excuse like, well, at least this isn't retail getting hosed, >> doesn't hold up that well when you think, okay, the alternative is like large institutions, insurance companies, pension funds that are also financing this, which is effectively >> I'm talking about the fragility of not necessarily where where where the where the financial pain or who the ult who the person ultimately pays for it.

1:08:21

If there is a pullback, it's like how fast can that pullback happen, right?

1:08:25

Because if if uh like I I if the write downs if there's something that goes wrong and the write downs come out of tech companies cash flows that's just not as big of a deal as as everyone waking up and and just slamming the sell button.

1:08:41

and and just slamming the sell button. I it's just a very different uh it's a it's a very different set of dominoes like like the dominoes of like the the interest rate crisis the NFT crisis like FTX blowing blowing up all that stuff like that those dominoes were spaced right next to each other and so as soon

1:09:02

as one went over it was like the next person has their finger over the sell button the next person has their over their cell button whereas if you're like yeah I'm a tech company and I produce you know $50 billion dollars of free cash flow and oh Yeah, I'm not getting a great return on the 20 billion of free cash flow that I earmarked over here for the next few years. It's like it's bad,

1:09:19

It's like it's bad, but it's not it's not like it's not as calamitous.

1:09:24

>> And I think I think you know going back to this quote from David Einhorn, he says, "What we do know for certain is that the big tech companies that want the world to spend trillions >> have huge financial incentives to be believers.

1:09:34

In case you haven't noticed, Wall Street is also being paid a lot to promote the story."

1:09:40

And in that same letter, >> uh, Einhorn, uh, and Greenlight said, >> uh, this was this was the AI math makes no sense, which was, >> uh, >> basically the way it is today.

1:09:53

Consumer or business spends $1 on a Chad GBT subscription, which is OpenAI revenue.

1:09:59

>> Then OpenAI provides the service by spending $2 on Microsoft AI infrastructure, which is Microsoft revenue.

1:10:05

Then Microsoft spends 60 leasing GPUs from Coreweave to handle the compute load, which is Core Weave revenue.

1:10:13

>> And then Coree spends $2.

1:10:13

40 on chips from Nvidia and and another $2. 40. >> Yes.

1:10:18

But you're completely discounting exactly how addicted the 40 user is.

1:10:23

They will pay any amount.

1:10:23

So let's say that it's if it costs $20,000 a day to serve a 40 user, they will find the money.

1:10:30

They will be stripping copper out of empty buildings to pay for their 40 bill if they have to.

1:10:37

They will be they will be >> whatever it takes.

1:10:42

>> They will be they will be breaking into cars to to sell uh stolen CD radios.

1:10:44

Uh >> it is it is notable that Blue has sold off 16% the past month.

1:10:53

So even during this sort of like boom in lending >> um it's not uh they're not getting >> very much credit for it.

1:11:04

>> Yeah, it's an odd it's an odd time.

1:11:04

Um like there's still there's still so many things that are working.

1:11:09

The the results from that newcomer event uh the AI cerebral valley uh where he had every it's so good.

1:11:19

He he took like a straw poll on stage and asked everyone like who do you want to short and everyone said perplexity.

1:11:25

So like he didn't really have to say like I'm shorting Perplexity.

1:11:28

He just was able to like take the temperature and sort of maintain like you know some uh arms length distance to it while still like getting the take out there.

1:11:37

Uh but everyone was saying that they wanted to buy more open AI, more anthropic, more anderal, a few other names came up I believe.

1:11:47

Um and uh and there's still like an incredible amount of bullishness in a lot of different areas.

1:11:52

Uh but uh I think yeah, people are still still worried about some of the some of the other stuff.

1:12:01

But at at the same time, it feels like there's so many companies that have like gone through a they've gone through the AI pump and roundted.

1:12:09

Not just Oracle, but even like like CLA was going through the whole like, hey, we're going to get so many efficiencies out of AI and then it came back to normal, but then they still got out and it's like a reasonable company that's not like it's not zeroed, right?

1:12:22

It's like, oh yeah, their business is just what it was before the AI boom and they are not getting like they didn't get moved up or down and so there's just like a ton of companies that are like that.

1:12:35

Where is CLA since the IPO anyway?

1:12:37

They're sitting uh at around a 12 billion valuation. 12. 6 >> down 20%. >> Yeah, down 26.

1:12:46

>> That doesn't seem calamitous to me.

1:12:46

That seems like pretty like solid. Like I don't know.

1:12:51

The overall market's sort of kind of, you know, up and down. I don't know.

1:12:56

>> Uh a firm on the other hand is up 28%. >> How's a firm doing?

1:13:00

>> Up 28% the past six months.

1:13:02

>> In the past six months, >> they're getting uh >> today is a real blood bath. It's down. It's down 6% today. Everything's down today. What else is down today? >> Bitcoin.

1:13:10

[laughter] >> Let's check. >> NASDAQ's down 1. 3. Dow Jones 1. 3 as well.

1:13:16

Well, we're we're going to 10,000year mortgages.

1:13:21

>> Doing 10,000year mortgages.

1:13:22

>> Announce the second round of stimulus checks already.

1:13:25

>> Gemini 3 must save us.

1:13:25

Uh there there's a prediction on Poly Market that was quote posted by Sundar Pachai, CEO of Google.

1:13:34

Uh he says prediction markets are betting on Gemini 3 release week. 69% says November 22nd. Can't wait for that.

1:13:45

We were wondering if we were going to get it before Christmas.

1:13:46

It was our Christmas present.

1:13:48

It was Tyler's Christmas present and uh fortunately looks like we're going to uh and I couldn't be more excited that we are partnered with Gemini and Google AI Studio.

1:13:57

Create an AI powered app faster than ever.

1:13:59

Gemini understands the capabilities you need and automatically wires up the right models and APIs for you.

1:14:05

You can get started at ai. studio/build.

1:14:08

Um, so >> speaking of Google, Google Capital says his final investing decision was to buy Google. >> This is amazing.

1:14:16

>> I think that's beautiful.

1:14:16

>> He doesn't even need to say who he's talking about. It's like so obvious. It's Warren Buffett.

1:14:19

Uh, it is it is beautiful that Warren Buffett is going long Google.

1:14:23

Um, and uh, Darren here quotes this Rune post that says, "Not enough people are emotionally prepared for if it's not a bubble." It's a good post.

1:14:36

[laughter] Like, uh, it's like it's like, is it is it a is it a bubble?

1:14:40

it a is it a bubble? if if uh all the big tech companies rip and there's like a couple Neo clouds that trade down a little bit and like there's like you know one or two application layer companies that burn a bunch of VC dollars but there's still a new hyperscaler that's born like kind of I

1:14:58

guess it's a bubble but it's a survival bubble it's just like it's move on you know >> rolling bubbles >> but people are getting wild on the timeline about Gemini 3 uh run says the model must be good because the Google people have adapted the open AI culture of vague posting and hushed rumors and sending really weird texts. So we are

1:15:16

So we are explo uh and signals his lmao explicitly calling out open a culture of vague posting is hilarious. Um people are excited.

1:15:28

Uh there was also a Reuters profile of Demis and Morgan says a demis profile can only mean one thing.

1:15:34

I imagine that that's Gemini 3.

1:15:35

0 and that it will be good.

1:15:38

The question is like what does good mean right now?

1:15:40

Like are we expecting anything that's like a qu a qualitative step function?

1:15:50

>> Um >> because my what what I would say what is Gemini 3 good?

1:15:52

First off I mostly just want better UI and little features in the app like I want as a consumer product.

1:16:00

I I just want like you know better productization of the model that I already think is good.

1:16:04

Um, on the actual AI model side, I would imagine it's, you know, little 10% bump to how long it can reason.

1:16:13

Maybe a model picker or uh not a model picker, a an automatic reasoning mode so that if I if I even if I think it's going to take 10 minutes to get me the answer, if it has the answer handy, it gives it to me in one minute.

1:16:27

Vice versa, it knows when to think really hard.

1:16:29

It knows when to uh think just for a little bit.

1:16:32

Um, I'm expecting it to be like slightly better at all the benchmarks. I don't know.

1:16:37

I don't even know what would blow me away.

1:16:41

>> Yeah, I mean that at this point it's it's getting like fairly hard to find good prompts that like show how good a model is.

1:16:47

Like there was the one earlier we showed about the shrimp fried rice one that's like pretty good.

1:16:50

Um, but yeah, I mean qualitative like just in normal kind of natural language, it's like pretty hard to get.

1:16:58

>> Also, like if I go to Gemini 3 and I say, "Tell me a joke."

1:17:00

Or I say, "Uh, write me a tweet that gets over a thousand likes."

1:17:03

Um, I'm not actually that disappointed when it falls flat on its face.

1:17:09

I'm like, "Yeah, it's fine. It's spiky intelligence.

1:17:10

I don't really need you to do that.

1:17:12

I don't need you to be funny.

1:17:14

I need you to uh look up data really accurately for me.

1:17:17

I need you to do that really well."

1:17:19

uh or I need you to write code really accurately for us.

1:17:24

Um >> I think another question is um like what will OpenAI do if they'll do anything.

1:17:29

Yeah, >> because we've basically seen every big Gemini release there's been some response from OpenAI.

1:17:33

Like usually they they do it the day before.

1:17:35

>> What is Jordy laughing at? >> I just don't know.

1:17:37

I don't I I know that they want to steal Gemini's Thunder.

1:17:40

I just don't know if they have the juice this week. >> Who? Oh, OpenAI. >> Yeah.

1:17:48

I mean, >> it it feels a little bit like all the people at opening hour are throwing in the towel a little bit.

1:17:51

No one is No one is vague posting over there. >> Yeah.

1:17:55

>> Uh I I would I it feels like they they've launched a lot of the things that um would be easy like layups.

1:17:59

Like if they launched Sora this week, everyone would be like, "Oh, we got to focus on Sora.

1:18:07

These videos of Sam Alman stealing GPUs are just too funny."

1:18:11

Doesn't matter what happened in in Gemini 3 world because Gemini 3 probably OpenAI the IO acquisition the week of Google IO. >> Yes.

1:18:23

>> And it turns out like they couldn't I don't think they could use the name IO.

1:18:26

Like they they got that like trademark lawsuit right away.

1:18:28

[laughter] >> Just like we big news we hired three Geminis.

1:18:32

Their birthday is in the month that makes them Geminis.

1:18:35

And so we're introducing them today and we're doing a whole press release for it. the new Gemini team.

1:18:40

Gemini, open AI and Open AI.

1:18:42

Just anything to to steamroll the SEO. Uh, it will be fun.

1:18:45

Well, we have Eric Lyman from RAMP in the reream waiting room.

1:18:50

Let's bring him into the TV and alter. Eric, how are you doing?

1:18:54

>> Where's your yellow suit?

1:18:56

>> Why did you not get the memo?

1:18:56

[laughter] >> Oh my gosh, guys.

1:18:58

I'm uh I'm on the road today, but um I'm going to be wearing my yellow suit all week.

1:19:03

Um it's so good to see you guys. >> Good to see you, too. Good to see you, too. uh give us the update. What's the latest? What happened?

1:19:12

>> It's so so today RAMP announced a $300 million raise at a $32 billion uh valuation. >> Congratulations.

1:19:23

[applause] >> They've done it again.

1:19:26

>> The big question everyone wants to ask, the chat's going crazy.

1:19:29

Is the job finished, >> guys? The job is not finished.

1:19:38

>> [laughter] >> Is that the third? Is that the third?

1:19:42

>> It is the fourth time we've asked. >> No, no, no.

1:19:44

I was going to say, is that is this the third financing this year? >> Something like that.

1:19:48

Yeah, >> it is the fourth financing that RAMP has announced this year. >> Okay, let's go. Congratulations. Um, yeah.

1:19:57

What what So, so, so why what why this financing? Why this partner? Um, why this number?

1:20:03

kind of break us through walk us through the the the thesis behind the round. >> Of course.

1:20:09

Um so I I think if you start look at the fundamentals of the business ramp is just competing in a category of its own.

1:20:15

Um you know uh the company companies generally the bigger they get the more they slow down.

1:20:21

Uh ramp is growing faster this year at significantly larger scale than we did last year.

1:20:27

Uh so this is you know at over a billion dollars a year in revenue.

1:20:31

revenue. uh the business is doubling uh it's generating cash and if you look at gross profit specifically which is a good metric of how efficient uh are the underlying mechanics of the business uh we're growing 10 times faster than the median publicly traded software company

1:20:47

so it's just in a category of its own I think on top of this uh AI has just been an incredible accelerant uh for the business itself uh there's pull from from customers everyone is thinking about how can I uh take what's happening in AI and apply it to to my business and

1:21:03

there's a push of these models are getting dramatically better and so outcomes like automated expenses uh automated accounting uh moving funds to higher yield for for customers are are just coming out of the box and so you know I I I would say if we were to sum it up um uh I think for uh many

1:21:19

millennia uh money talked uh we're teaching money to think uh and I think the implications of that are are pretty profound um you know betterun businesses more profitable organizations and so that that's the first part the second part. Um we're absolutely thrilled to be

1:21:31

Um we're absolutely thrilled to be uh deepening our partnership with Lightseed uh who led this round.

1:21:35

I I think they're an extraordinary firm um led the rounds of many great companies.

1:21:42

I think notably uh anthropics round earlier this year which has proven to be I think an uh one that's uh you know changed the industry quite a bit.

1:21:49

Uh and I think they've just been a great partner in in deepening our thinking, helping us grow.

1:21:54

Um and so we're we're very excited.

1:21:56

uh talk about accelerating at scale.

1:22:00

Uh this morning at breakfast, Jordi and I were reflecting on the fact that we were feeling this way even with our much smaller organization.

1:22:07

We were like, "Wow, like it's only been a year."

1:22:12

Uh and we feel like we were already losing some of the agility that we had when we were just three people.

1:22:17

And we were saying like, "I understand."

1:22:18

What was this thing you said?

1:22:20

You said, "I understand why companies write down their principles because it's so easy to lose sight of what is important, what makes you great, what what you do specifically."

1:22:33

And so I would love to know just your reflection. >> Yeah.

1:22:36

Even across this year, like a lot of us, the process of making the show better is us remembering the things that we did great early on and that you kind of end up losing your way in slight ways and then it's about remembering that and kind of coming back to it. >> Yeah.

1:22:49

So, I'd love I'd love to know both what are the things that make Gramp great, but then also your thought process for not losing that because I imagine you agree that that is important to have principles and re and redouble the focus on them.

1:23:06

>> I love that you asked about this because I think it gets to the heart of what we're trying to do um inside of the product, right?

1:23:11

If you think about probably your your very first year, every dollar out of the organization was something you thought about.

1:23:17

Um, someone wants to buy a software subscription, you know exactly why.

1:23:21

Someone proposed to the consultant. It's a debate over it.

1:23:24

Everyone knows who approved what.

1:23:26

Uh, was this this this purchase worth it or not?

1:23:28

And you know, years later, suddenly businesses just start happening to you.

1:23:32

You're not happening to the business.

1:23:34

Uh, things are renewing on autopilot.

1:23:36

Um, uh, things you you thought carefully about or are just running on its own.

1:23:41

And what we're really trying to seek to do in the product is when we say money that that that that that thinks, you know, it's the idea is that before funds leave your account, we understand the principles that you run your business and we check does someone have the permission to spend it. It has memory.

1:23:56

So once the thing actually moves, you don't need to ask like why did we buy this thing? What was it?

1:24:02

Like there's an audit trail of who approved it, budgets are updated, and then there's reasoning.

1:24:05

And so we can actually start to show businesses um here's how you can get more of every dollar an hour.

1:24:09

Uh, and so I think that's what's so different.

1:24:11

You take things that used to be systems running to now there's checks in the system.

1:24:14

And I think for us, it it's it's an interesting moment, right?

1:24:19

We're uh as a company, we we launched our first product uh simple product card and expense um about 5 years ago.

1:24:25

Uh today we're 2436 days old. We still count the days.

1:24:30

And the reason is uh we want to be thinking about um you know with every day are we getting just a little bit more done or a little bit less done?

1:24:38

more done or a little bit less done? uh in kind of this practice of uh thinking about kind of the passage of time uh auditing our calendars asking you know um you know um are we getting more work done uh with the same or less amount of

1:24:52

effort uh goes a long way and then last I would say specific to to you guys um I think part of why I I we've just felt so proud to um work with both of you and call TVP our partners is I think there's this like unbelievable care of craft um uh I think there's It's not about who's done everything. It's like who can write great copy, who

1:25:11

It's like who can write great copy, who can think of funny ideas, how could we take an idea to, you know, we're we're doing it tomorrow.

1:25:17

And I I I think that you guys have have really lived.

1:25:19

Um I mean, people forget a year ago TBPN.

1:25:22

I I don't even think you guys were called TVPN or was it show and you know, you've turned into something great.

1:25:27

And so I I I I feel strongly you guys don't have a trouble with this.

1:25:30

And uh I I think just emphasis on speed and quality and craft is been what I've seen of you guys. No, totally.

1:25:39

>> Uh, something I was thinking about, we were reading that Carpathy post earlier around how uh, software 1.

1:25:43

0 was like kind of more general automation. Software 2.

1:25:49

0 is you're automating tasks that are verifiable.

1:25:53

>> And I just feel like finance is like just like prime for verifiability, right?

1:25:59

Because it's like, well, was this in in the policy or outside of the policy, right? Totally. So, >> totally. >> Um, >> yeah.

1:26:05

I' I'd love to know more.

1:26:05

or is your policy incomplete, right?

1:26:07

Um, you know, there's all these practices and you can actually start to learn based off of the actions.

1:26:12

And I think something that's so unique is that every time um, you know, months close, um, uh, there is someone actually going in and saying this transaction is categorized here, this goes there, you can see if you grew your revenue faster, if you grew your cash flow faster, or if you didn't.

1:26:29

And so there's this incredible feedback loop that allows uh, RAM to add more value.

1:26:35

We think that's why the average customer that adopts ramp uh spends 5% less and also the the median ramp customer uh grew their revenue by 12% over the past year uh which is much faster uh than the median in the US and I think a lot of it comes from this learning.

1:26:53

>> So help me understand uh you're you're generating cash but you're also raising money you're implementing AI which can be very expensive.

1:27:01

We've heard uh from Ivan at Notion that, you know, he saw a slight hit to his gross margins.

1:27:07

It's still a fantastic business, but uh did actually see that show up uh in the income statement.

1:27:14

Uh how is how are you thinking about the adoption of AI as a piece of the tech stack?

1:27:21

Is it actually reshaping the financials at this point or is it something where uh you see it sort of just like another subscription just like another piece of the tech stack and it hasn't really change the way you think about the cost structure of your business?

1:27:40

It >> it's a really good question to zoom into and and in my general view has been fairly overwhelmingly positive.

1:27:45

I mean, I I still think that for us, the goal is, you know, our goal is not to sell someone like a card or a bill payment software.

1:27:53

It's to >> um it's help your business run more profitably, right?

1:27:57

And uh I I think a lot of what we're trying to do is if we can actually pay for software where the output is there's an hour of your uh of your time um that you don't of work you don't have to do anymore that's done by software, that's really great.

1:28:10

Um, next I think about and you ask most um uh founders or or leaders in technology like what's the biggest constraint on your business?

1:28:20

Everyone says I'm having trouble hiring engineers.

1:28:22

>> Um it's like I I want to hire great salespeople, great engineers and and if you can adopt software I mean we look at our sales team um you know the quota that folks on the sales team have is multiple times of our next closest competitor in part because we have a lot of tools we built to make our team um far more productive.

1:28:39

um our engineers um are shipping about 50% more uh code to the codebase um than about four or five months ago.

1:28:48

Uh and that's continued uh and so our general view is look if you can actually uh make the best even better um that's something we're gladly uh willing to pay for.

1:28:58

Um and so in our business we've actually seen um you know margins expand as we've adopted this uh in part because we think that our our principle is let's create a lot more value than we capture. Yeah.

1:29:10

>> Um and and we're able to do that because we're we're creating much more value uh than it even months ago.

1:29:15

>> It just feels like Ramp is an agile new company that people love the product.

1:29:22

And so it's just so much easier to say, "Hey, if you want a new AI powered feature, we have that on day one.

1:29:26

You don't need to rip us out and go to something else."

1:29:31

Uh you don't need to have some bolt-on.

1:29:33

You can just get it all here.

1:29:34

And so you can effectively uh like monetize whatever cost is coming through the actual uh token generation on your side pretty quickly.

1:29:43

>> How how do you how are you thinking about head headcount planning over the next few years?

1:29:46

We don't have to zoom out to like 10 years.

1:29:48

I think it gets extremely extremely fuzzy, but I'm curious if you care about uh you know, every every once in a while these sort of like >> uh revenue per employee or or sort of like uh net income per employee like statistics start floating around.

1:30:02

Uh I'm curious if you uh if you if you think about that at all and and obviously uh prof you know running running ramp as you know one of the most efficient uh companies in the world is really good marketing for the product.

1:30:17

It's probably the best marketing that you can do.

1:30:19

Uh but I'm curious how you think about about those things.

1:30:26

It's exactly the right question because I I I think look when we kind of think about our operating model every year we try to increase the ratio of whether it's revenue contribution profit um margin per employee it's it's all to say like uh we we anticipate revenue is going to grow very very rapidly.

1:30:42

Um uh uh and while employee headcount is going to grow it's going to grow a little bit slower and so the effect is you start to see this widening.

1:30:50

and gives you more margin to uh invest in uh whether it's uh a use of AI itself that you can drive into the product um more marketing all those types of things to reach more customers.

1:31:02

customers. I I think more abstractly though um if you kind of step back you know most businesses in the US uh run are actually profitable might forget that in the valley but have an 8% profit [laughter] margin um um and we'll talk about this but you know it's like if you make a company more efficient um by like

1:31:22

1% it's equivalent to like an increase of uh you know $1 in savings is equivalent to $12 more in revenue um at an 8% margin just mathematically Uh, and if you can do this repeatedly, I actually think that there's um, you know, a you have a lot more businesses that are good but but don't have um this automation and and and and skill sets to grow uh much larger. I think a lot more

1:31:44

I think a lot more companies will get bigger.

1:31:46

And I also think that if it's just easier to run a business, I think more great businesses will get started.

1:31:52

Um I think there's a lot of creative people out there uh who would be running organizations who I think as the tools to build get easier.

1:32:00

Uh you see a more interesting world and and so uh you know I I I actually think it's it's a pretty important and really profound thing to knock out inefficiency to allow uh smaller companies to succeed.

1:32:12

I mean even you guys are a perfect example.

1:32:14

TVPN is a small team that's changed the media landscape and captivated the world and like I think that there are probably a lot of people where if you make the tools better like they will come.

1:32:23

How do you uh how do you feel like CFOs are ranking like AI enabled software uh on their list of priorities when they're making a decision in this category?

1:32:35

like is it because it it feels like there is some great stuff.

1:32:39

There's some stuff that's commoditized, some stuff that you've built that's differentiated, but are are CFOs as a class uh sort of like, okay, I've checked the box, I'm exhausted with the narrative, or I'm just ramping up and I feel like I'm just starting to get value and I actually understand it.

1:32:54

Um, or are they just learning what AI is for the first time tomorrow or today?

1:33:04

>> This is a this is a fun one.

1:33:04

So, I I would say there's a few different types.

1:33:07

I mean, sure, >> I would say small and mid mid-size businesses just is like, look, um I want to run, you know, same business for less.

1:33:14

I I want to grow, meet my goals, be more profitable.

1:33:16

And uh I think for us, it's just, hey, it's an easier to use expense report.

1:33:20

Um or or like you want to do expenses more, your card will do it for you. Sure.

1:33:23

Um you don't need five tools to pay bills, run procurement, uh earn yield on your treasury.

1:33:29

Um ramp will simplify that.

1:33:31

But I think that for large customers, uh, look, I I think it's like 80% plus of the earnings calls of of the S&P 500, um, mentioned AI about 6 months ago, and I think it was 95, um, over the most recent quarter.

1:33:45

It is 100% on the mind of, uh, uh, CEOs and CFOs.

1:33:47

of, uh, uh, CEOs and CFOs. what they're wrestling with is, you know, there's a great study out of uh MIT in the fall that went fairly viral where said 95% of enterprise deployments um are not creating return on investment and I think part of why CFOs have been so

1:34:04

enamored with ramp uh is you know we can demonstrate very very clearly um uh a for most customers it's pro it's product that pays you to use it in the form of cash back b it helps reduce your spend uh and c when you have all this time back from your sales force um to go and sell and not do lowv value tasks. Um it's a very easy business

1:34:23

Um it's a very easy business case.

1:34:25

And so I I think this this ultimately like our focus is on saving people money.

1:34:30

Um and that ROI focus makes it easy for them to buy.

1:34:33

I think it's it's very important.

1:34:35

>> That MIT study, how does that track with what you guys have seen from various AI pilots?

1:34:42

Because I think >> I would imagine ramp doesn't even count on either side.

1:34:44

I I wouldn't think of at like bringing a ramp into a company as like an AI pilot.

1:34:49

I would see it as like a completely different thing.

1:34:51

But are you the 5% successful or you just not even >> if you were looking if you were talking with the team and the team's like 95% of our pilots haven't panned out, you'd probably be like, "What were you guys doing?" >> Yeah. >> Yeah. Yeah. Yeah. It is. You nailed it.

1:35:07

So, one, I think that a lot of you hit this first phase of people who were like told they need to buy AI.

1:35:11

They're like, "Fine, I'll give you some experimental budget. You'll go do it."

1:35:14

people tried a bunch of stuff and I think you end up and I think this speaks to the importance of design where you'd end up with like disconnected tools.

1:35:20

You have like a thoughtful chat like a great chatbot here this thing that kind of plugs into some of your codebase and others.

1:35:28

And if you look at I think part of what's made ramp so effective is you know it's just a smarter card that happens to use AI.

1:35:35

It's not telling you uh hey this is an LLM that categorized your transaction.

1:35:40

This is an LLM uh that's read this 30-page invoice, detected it was fraud, uh told you not to pay for this.

1:35:46

This is an LLM that detected you could be earning higher yield and moved it for you.

1:35:50

It's just part of how it works.

1:35:51

And I think this next phase and the AI native companies that are working very very well um have these deeply integrated products where it's not like some, you know, AI tool. It's just how it works.

1:36:02

Um and so I think that's the distinction and you're right.

1:36:06

Um for a lot of CFOs, it's hey, um we have this tool.

1:36:09

it's going to help uh help us cut out waste uh and pay us cash back.

1:36:14

Um >> should we use it or not?

1:36:16

And it's a pretty easy decision. Um yeah. >> Yeah. Yeah.

1:36:19

It might not even be in the category.

1:36:21

Uh but it's still delivering AI properly.

1:36:24

AI properly. And I just love that that's I I feel like there's something very valuable about just using every possible tool AI or not or linear regression if that's the best tool for the job behind the scenes and then just delivering the actual value to the customer solving the

1:36:40

problem because customers they don't necessarily want technologies they want solutions right >> yeah is one of our our customers and um someone I look up to quite a bit um Brett um Taylor started company Sierra, chairman of OpenAI, I think he was on it um a week or two ago. >> And one of the things he said is like,

1:36:59

>> And one of the things he said is like, look, I don't want anyone at Sierra spending like time on expense reports or invoices. Yeah.

1:37:06

>> Uh and ramp is automated categories of work that used to slow us down and we actually can work on the things that makes us great.

1:37:12

Um build a great product to write the business.

1:37:14

And so I I I think you nailed it.

1:37:15

it's solutions, not um >> not actual technologies because most of the customers just just they they just don't have a strong opinion about the the underlying technology.

1:37:25

They care about saving time, saving money. That's what matters.

1:37:29

Uh well, congratulations.

1:37:31

Thank you so much for taking time to be back next week.

1:37:36

[laughter] >> You're always welcome.

1:37:38

That's why we bought these suits. We don't rent them.

1:37:42

We buy we bought them >> tailored because we knew we were gonna be using them a lot.

1:37:47

>> We're gonna be using them a lot.

1:37:49

>> Guys, it's so good to see you. Thank you so much.

1:37:52

Have a great rest of your day.

1:37:53

Uh yeah, incredible milestone.

1:37:55

>> We'll talk to you soon. Bye. >> Cheers.

1:37:56

[laughter] >> Quickly before we bring in our next guest.

1:38:00

Let me tell you about Turbo Puffer.

1:38:01

Search every bite serverless vector and full tech search bird built from first principles on object storage fast 10x cheaper and >> scalable.

1:38:08

median public SAS company growing at 12 to 17% a year and they're growing at 10 times that rate. >> Fantastic.

1:38:16

Uh >> uh well we our next guest is uh Stacy Rexon. Welcome to the show.

1:38:19

Thank you so much for stopping by. >> Good to see you.

1:38:24

>> Uh we'll have you sit down here and while you're sitting down I'll tell everyone about profound get your man mentioned in chatbt.

1:38:30

Reach millions of consumers who are using AI to discover new products and brands. Are we in a bubble? What's going on?

1:38:35

[laughter] introduce yourself for a second. >> Sure.

1:38:39

Uh my name is uh Stacy Rasgun. Yeah.

1:38:42

>> Uh I'm an uh stock analyst, an equity analyst.

1:38:44

I'm a managing director and analyst, senior analyst at uh Bernstein Research, >> where I look at the US semiconductor and semiconductor capital equipment space. And >> thank you.

1:38:53

Clearly AI has been uh the the only topic for a couple of years now. >> Yes. Yes. Yes.

1:38:59

Um I want you to react to this uh Catrini post here.

1:39:02

says, "Just reviewed a bunch of stuff for our November macro memo.

1:39:06

We might low-key be going into a recession, boys.

1:39:10

No clue if this matters at all for stock prices anymore, though. >> That's a good point.

1:39:16

You could argue some parts of the econ and I'm I'm not a macro guy. I'm not an economist.

1:39:22

However, >> you could argue some some parts of the economy are already there, right? Right.

1:39:25

I mean, they people use the phrase K-shaped recovery, which is sort of interesting, but >> I think especially like the the the lower half of of the population is not actually doing all that well, right?

1:39:34

And we've actually seen that more recently in a lot of just not not the semiconductor reports, but >> a lot of the consumer reports and the restaurants and you you know the retail. Yeah.

1:39:44

So there's probably parts of of the world that are already there and and clearly the infrastructure spending um the AI spending has been supporting GDP. >> Yeah.

1:39:56

>> Uh and it's been supporting the stock market.

1:39:58

I mean Nvidia's I can't even remember 8% 9% of the S&P now.

1:39:59

So yeah, >> that's remarkable.

1:40:03

>> We we may be there already. >> Yeah.

1:40:04

>> So we had a we we had a thesis that uh that uh Nvidia is going to do just fine this this earning cycle.

1:40:10

specifically the only reason not not just overall demand but that Jensen was slamming beer.

1:40:17

>> This is the most quantitative research. You can't get this out.

1:40:20

>> He's not acting like a CEO that's like really worried about his quarter.

1:40:22

Although he I don't know that he would generally care anyways.

1:40:24

However, >> you know, they just did an event in in DC a couple of weeks ago called GTC.

1:40:27

And >> I mean he put a slide up behind him that basically said numbers next year are too low.

1:40:34

Um what the slide said uh it said they had $500 billion in cumulative orders for Blackwell and Ruben.

1:40:41

Blackwell is their current generation [clears throat] of AI servers and Rubin's the next generation.

1:40:44

500 billion cumulative across 2025 and 2026.

1:40:46

And they said we've already sh I can't remember it's like 20 20 million chips for orders.

1:40:52

And they said we've we've shipped six to date.

1:40:55

>> So we got 14 million left.

1:40:55

They they've got five quarters.

1:40:57

You and you can sort of figure out how much it is and you can compare that to where the numbers are.

1:41:03

and he's basically saying numbers are too low.

1:41:05

So I'm not terribly worried >> going into the quarter on Wednesday.

1:41:09

Now, >> you know, with with stocks is as always it's not just the numbers, right?

1:41:11

It's it's the numbers relative to the expectations. Totally.

1:41:14

So I think everybody expects it to be good.

1:41:15

So we'll see how how good he can make it.

1:41:19

>> It does feel like we've entered a period over the last month maybe where even beating would still result in a sell-off.

1:41:27

Is that just everything priced to perfection? What's going on there? Yeah.

1:41:30

I mean, especially in the AI side, there's been, you know, the sentiment es and flows. Yeah. Right.

1:41:34

And and we've been in a bit of an eb. >> Yeah.

1:41:37

>> And there's been a lot of stuff.

1:41:37

You know, we had we had Bur's comments about a GPU lifetime and depreciation.

1:41:42

>> And we had a couple to be honest, a few I would what I would call selfowns on the part of the OpenAI folks, Alman and Meer.

1:41:48

Um, a little like unnecessary angst that they that they caused.

1:41:53

>> Um, >> they did they did that to inspire themselves to to have to work harder.

1:41:54

themselves to to have to work harder. H maybe maybe it's [laughter] you know it's it's right um look and you your early guys are we in the bubble or not I mean so bubbles are as as bubbles are right um you can look at a lot of things you can look at valuations

1:42:10

>> I mean Nvidia's uh mid mid20s price toward earnings right now it's not we haven't got anywhere near >> crazy yet I mean I'll say the same thing I've said since this started and it's this it really got started you know chatb showed up in November of 22 and Nvidia's sort of print heard around the world was May of 23. That's that's when

1:42:26

That's that's when it started.

1:42:28

And even then, people worried about, oh, okay, 2024 is going to be off, right?

1:42:31

I'll say the same thing I said then.

1:42:33

At some point, you know, nothing goes up into the right forever.

1:42:37

At some point, you'll have a digestion or an air pocket or it's it's not now. It's clearly not now.

1:42:41

That that's all I can say. I don't know when. >> Yep. >> But it's not now. It's not this year. >> Yep.

1:42:46

>> Doesn't look like it's next year.

1:42:46

And then all of these projects that OpenAI is is, you know, signing with with Broadcom and Nvidia and even AMD, >> they don't even start to ship until the end of 2026.

1:42:57

>> So at least from a spending standpoint, from what we can see, it's probably not 2027 either.

1:43:00

Now, we'll see what the stocks do.

1:43:03

Like they tend to be anticipatory, but in terms of like an air pocket or something in spending, I'm I'm not really all that worried yet. >> Yeah.

1:43:10

>> When I don't know, but like it's not now. >> Yeah.

1:43:12

Do you do you how much of you uh subscribed to this idea of like rolling rolling bubbles?

1:43:18

So like right now like it seems like we've had we've had like explosion you know a lot of excitement around neoclouds this year.

1:43:24

All you know pretty much all of them have sold off a ton in the last month maybe partly because of some of the comments uh out of the opening I camp and lack of lack of confidence.

1:43:34

Um but uh but at the same time, you know, Seagate, Western Digital, these other companies are up, you know, tremendously.

1:43:42

>> I mean, yeah, the storage, they're covered by a colleague of mine, not but but I mean, they they just go up 10% every day, right?

1:43:47

[laughter] But I but but that's the thing.

1:43:50

It all really comes down to demand.

1:43:53

>> Demand is off off the charts.

1:43:53

Nobody can get enough compute.

1:43:55

The NeoClouds are all, you know, even even with Cororeweave, they there was they had a bit of a delay.

1:44:00

They just don't have the capacity, right?

1:44:01

They're they're pushed out a little bit. It's still there.

1:44:05

>> Um again, the storage guys are ripping because the memory prices are going through the roof because there there's so much um uh there's a lack of supply relative to demand.

1:44:13

>> Um all we've seen from the hyperscalers is is capex numbers going up and up and up and up.

1:44:18

Like nobody can get enough compute right now.

1:44:19

That that's where we are.

1:44:21

And I think that is >> sort of the overarch and that's the overarching thesis like either way.

1:44:25

Like you go back to the to the question about GPU depreciation deprec uh uh GPU lifetimes for example >> this is what Bur was getting at.

1:44:32

He was saying oh well you know the they're all using you sixyear depreciation lifetimes in you know these things don't last more than three years because you've got new stuff coming.

1:44:41

It's not true right now right?

1:44:43

I mean you you can look they're still renting out old GPUs for I mean I for much more than it costs them to operate them.

1:44:50

It's clearly possible to run them longer than than three years.

1:44:54

It comes down to demand right now.

1:44:55

demand is so strong it is absolutely economic >> to run that stuff.

1:44:58

If demand weakens maybe maybe it won't be but if demand weakens we're all screwed anyway, right?

1:45:04

[laughter] I mean that so to me all of the bare cases that you that you come up right now to me collapse under the same thing.

1:45:10

Is demand there or is it not?

1:45:13

Right now it's it's it's there and it's not showing any the demand side is not showing any signs of awakening.

1:45:16

What about the uh the the leaked phone call from Sarah Frier, the CFO of OpenAI, where uh there was this idea that uh potentially there was we >> what she said was user minutes user minutes were dropping which implies >> in the core chatbt app which feels like the leading indicator for all AI.

1:45:38

>> Yeah, but it's more than just open AI too, right?

1:45:40

Now, now you could argue that we want open AAI to be there because like Altman's driving a lot of this incremental, you know, so we'll we'll we'll see, but I mean there there's there's lots of there's lots of demand.

1:45:49

It's not just open, it's open AI. It's anthropically. It's Gemini. >> Totally.

1:45:54

>> Um, in general right now, I mean, usage is going up. >> Yeah. Yeah. Yeah.

1:45:57

I mean, I I'm sure we'll get more information on the on the Google side.

1:46:01

>> A little wary about some of the when you see these leaks like you always have to be a little careful about about >> Yeah.

1:46:05

It was very odd that it was like from an investor only call like what investor would leak back.

1:46:10

>> And by the way, we do we do calls like that and stuff gets taken out of context.

1:46:13

So I was I don't I don't know what they said.

1:46:15

I wasn't on on that call, but >> I'm always a little hesitant to take I do this for a living, right?

1:46:20

I'm always a little hesitant to take stuff at face value.

1:46:23

You have to, >> you know, you have to diligence. >> Yeah. Yeah.

1:46:26

I mean at the same time like to your point of the like scurve nature of these adoptions, it's possible that you know 800 million is a lot of people.

1:46:34

You do at some point saturate everyone and you only there's only so much time in the day.

1:46:38

>> There's 8 billion people in the world. >> Yeah. Yeah.

1:46:39

But I mean it took it took Facebook years to get up into the high >> and that is that is the thing by the way.

1:46:45

I've been doing this job almost 18 years. >> Yeah. >> Um same seat.

1:46:51

>> I've never seen anything like this before. Yeah. >> Right.

1:46:53

I mean this is this is unprecedented just in and that's why people get nervous. >> Yeah.

1:46:57

>> Because the numbers have gotten so big. Yep.

1:47:00

>> So quickly you just sit there and stare at them.

1:47:01

It's like this can't be sustainable.

1:47:04

>> We've been hearing it for for two and a half years. >> Yeah. >> Still going. >> Yeah.

1:47:08

So I mean in this idea of the K-shaped recovery or this uh you know cycle of little bubbles popping up and popping um how do you process something like corewave like it feels like everything is going so well and and to the point where the the the negativity around AI that is like a rumored leak of a phone call but then we're seeing a company trade down by 50% in a month. >> Yeah.

1:47:33

Well, again, I won't talk about core specifically, but but I mean, look, any anything that goes out where valuations are high, expectations are high, and >> you know, it's not just that.

1:47:41

Lot lots of things have have have weakened, you know, off off of peaks. I mean, it's fine. Yeah.

1:47:46

>> Um, >> you know, the the the neoclouds in general, I mean, they're all seeing >> tons of demand, right?

1:47:52

They're, you know, it's it's I'm I'm not really worried in general right now about where the demand is going.

1:47:57

The only thing we're seeing >> in terms of spending intentions and everything else is right now is is is and again I think that that is the question how long does it last?

1:48:05

I don't think anybody knows.

1:48:08

>> Um if you just look at like I said what at least what is >> currently being forecasted by the companies that are doing the spending at this point there's no signs of a slowdown. Not not yet.

1:48:17

>> What do you think of this thesis that some of the hyperscalers are maybe offloading risk to the NeoCloud?

1:48:22

>> Oh they clearly are right.

1:48:22

I I yeah which is which is fine.

1:48:24

part of the purpose I think that the NeoCloud serve. >> Sure.

1:48:29

>> You know, you're kind of at the tip of the spear, right?

1:48:30

It's it's it's it's it's boom bust, right? Yeah.

1:48:31

I mean, but that's that's part of their business model, I think.

1:48:35

>> What about what if you go further on the tip of the spear?

1:48:38

Uh is a company like organization like Blue Owl or some of the on the financing side because Blue Owl is another example where you know uh like Google's doing very well, Microsoft's doing very well.

1:48:50

Microsoft's doing very well. uh the the hyperscalers are doing well very well even open AAI is doing very well growing a ton um but then you have some some froth in the neo clouds and some more froth in the private credit markets um what's your take on what's going on >> yeah I mean those are probably frothier parts anyways um but I mean the

1:49:08

financing question is interesting because >> I I'd say some of the these debt deals again if you're looking at you know parallels to prior bubbles that is one thing that there's a few things that people worry about um >> raising a lot of debt to do to fund this stuff and then they also worry about what they've called kind of circular revenues, right? There's a lot of like

1:49:24

There's a lot of like cross talk. Yeah.

1:49:26

Between a lot of the the companies around here and maybe to address both of those, >> I'd say on on the the the debt side, most of this capex is still being funded off of off of income statements.

1:49:34

And again, that is one difference now versus say 2001 is >> the companies that are driving the spending by and large are the largest, most profitable, best businesses that humanity has ever devised.

1:49:47

I'm sure you remember what the actually largest business was in 2000.

1:49:51

It was Exxon Mobile and Chevron.

1:49:54

[clears throat] Different world.

1:49:57

>> It was big big oil and big oil was not driving and they were not funding the telecom build out.

1:50:02

>> I mean a lot of the companies they I mean they were raising money they weren't profitable. That does not run.

1:50:06

>> It was a very different thing.

1:50:06

There wasn't like an immediate beneficiary that was that was just the oh the biggest companies are just getting bigger.

1:50:12

So it is a very >> and so in this case we are seeing starting to see some debt deals to fund this.

1:50:16

But I'd say the by and large the vast majority is still being funded off of operating cash flows.

1:50:19

That's I don't feel too bad. >> Out of the 2.

1:50:22

4 trillion that the Wall Street Journal estimated, the number that was funded by cash flows was 1.

1:50:25

4 trillion and then there was 800 billion in uh in private credit.

1:50:30

So it's >> it's still a pretty reasonable debt to equity ratio in my opinion if you think about that way or debt to cash flow >> for now. For now. Yeah.

1:50:37

So that's and then in terms of like the the called the circularity.

1:50:41

So I mean Nvidia is behind this.

1:50:43

They're investing a lot and >> they have deals in OpenAI, but I mean Jensen's got his fingers pretty much in every he's in every startup, right?

1:50:50

>> He's been doing it for a long time, too.

1:50:51

>> But think about like what else can he do with the cash?

1:50:53

And and so I'm I'm hardressed to think of a better usage if you we'll see where the numbers go.

1:50:57

But if you believe the numbers, >> they're going to be generating hundreds and hundreds and hundreds of billions of dollars of free cash flow over the next like five years, say.

1:51:06

>> So what can he do with it? He can't do big M&A.

1:51:07

Nobody will let him, >> right?

1:51:09

Just nothing's going to get through any trust.

1:51:10

They have a buyback and a dividend, but relative to their market cap, it's it's going to be dimminimous. There's no choice.

1:51:14

And so, >> is there anything better that you do except invest and help to grow the AI?

1:51:21

>> They also have a wildly different business in terms of M&A.

1:51:22

Like with Microsoft, they buy LinkedIn.

1:51:25

That makes a lot of sense in the Microsoft ecosystem.

1:51:29

Uh, you know, Teams, they grow Azure, like there's all these different places where they can plug other businesses in.

1:51:34

Like if Nvidia bought LinkedIn, we'd just be like, what is >> But he tried to buy other stuff, right?

1:51:39

He tried to buy Certainly certainly other pieces of this.

1:51:43

>> Could you imagine if he'd been able to buy ARM?

1:51:44

By the way, he'd be unstoppable, right?

1:51:46

So, nobody's going to let him do anything.

1:51:48

>> No one's going to let him. Yeah.

1:51:50

>> How uh how important do you think the Chinese market is to Nvidia? We we debate this.

1:51:56

>> It isn't and it isn't in the near at least it's not important to the numbers right now because it's out of the numbers. >> Yeah.

1:52:01

>> So, and and and Nvidia, even AMD, they they took it out.

1:52:04

So, that was smart because it's still questionable whether or not they will be allowed to sell.

1:52:07

Um and so from a numbers standpoint it's okay.

1:52:10

Um from a strategic standpoint I I think it is important and Jensen hasn't hidden this >> second largest computing market.

1:52:17

>> It's it's more than that though.

1:52:17

So it it is the second largest and again he's talked about $50 billion of lost opportunity and over the long term it's probably bigger than that right I mean China China's big but I think it's more strategic.

1:52:27

You have to remember the the Chinese developers want to use Nvidia.

1:52:31

They have better products right they do.

1:52:34

However you're not going to stop China.

1:52:36

So, China has has like companies like like Huawei, for example, that's basically a stateowned enterprise and >> they already have parts in China that have higher performance than what Nvidia is allowed to sell there. >> They do.

1:52:48

They burn a lot more power. Chinese don't care.

1:52:49

They just throw up another plant, right?

1:52:51

But >> but the thing is they're much harder to use.

1:52:53

They don't use Nvidia's ecosystem. It's called CUDA.

1:52:55

And the Chinese developers want to use Nvidia's ecosystem.

1:52:58

ecosystem. If you don't allow him to to sell there, >> what you do is you potentially encourage those local developers of whom there are a lot to coales potentially around a local alternative like like a Huawei for example and start to build up

1:53:11

potentially over time a more robust ecosystem in in China and then then you're shut out and then the longer term be is once it's it's robust in China does it move out of China and now do you have a more robust global competitor? Um, and so that's why I think

1:53:23

Um, and so that's why I think strategically, and he said almost exactly that, he hasn't tried to sugarcoat it.

1:53:27

Where I think he gets a little bit of a benefit is at least with Huawei, >> the parts because of some of the other US sanctions, >> they have to make their chips at local companies like Smick on deficient process technology.

1:53:39

So, the chips don't work as well.

1:53:41

They're not as power efficient.

1:53:42

I do not think those chips will really be competitive outside of China where they will be competing on a global basis with much better products from Nvidia or AMD or or whoever. So I think that helps.

1:53:53

>> Um but ideally you you and and you know Lutnik said this. He what did he say?

1:53:55

He said we want to get them addicted to our technology and to I wouldn't have said it that way but he's [laughter] out of line but he's right. >> Right.

1:54:04

Um we'd like him using it and to have some control over it and and and if and we're letting that slip away. >> Yeah.

1:54:11

>> And so yeah and I I don't think it's it's great that he's not able to sell strategically.

1:54:14

At least from a number standpoint it's it's out right now.

1:54:16

I want you to react to this uh quote from the CEO of KKR.

1:54:20

Uh he says, "And candidly, when we read some of these headlines, it's clear that many of us have PTSD from the financial crisis and are looking for what will trigger the next one.

1:54:33

Like where is the next boogeyman?"

1:54:35

From our standpoint, this market and economy really don't provide a simple narrative like that. What do you think?

1:54:43

>> It's I think that's true.

1:54:43

And to be fair, I started this job in April of 2008, about three weeks after Bear Sterns failed.

1:54:48

That that's when I made my move to Wall Street. >> Yeah.

1:54:52

>> And so I was forged in that fire and I have the financial crisis like tattooed on the inside of my eyelids.

1:54:55

[laughter] I lived through it.

1:54:57

It was a remarkable time by the way >> uh to live through Wall Street.

1:55:00

This is this is not like that. >> Yeah.

1:55:03

>> Um that was people thought the world was coming, but we we'll we'll see like if there is an air pocket may maybe it will become like that.

1:55:08

But people really thought the world was coming to an end back then.

1:55:11

Um, but are people looking for the Yeah, maybe. Right.

1:55:13

There's people are always investors always looking for pattern recognition.

1:55:16

One thing that I go back to on the patent recognition side is just um I feel like for it to feel like there is a world where there's some massive correction and like a lot of the top players see big haircuts but uh it's just hard to imagine a big widespread like with the dot boom every random person on the street was trading. com stocks.

1:55:39

Uh with the NFT boom everyone had Bitcoin.

1:55:42

They were telling you, "Oh, you got to buy Cardono, you got to buy this, you got to buy that, you got to buy this NFT."

1:55:48

And then in the housing bubble, everyone was like, "Yeah, I just got a second house.

1:55:53

More didn't zero down mortgage.

1:55:53

They didn't check my income."

1:55:55

And so there was a lot of like places where just hundreds of millions of Americans could participate in the bubble on the way up and on the way down.

1:56:03

And here it just feels harder.

1:56:06

>> There there's some I mean there there's a lot more retail participation I think in the market than there Yeah.

1:56:09

Robin Hood and all this, you know, >> and they they they get a little nasty sometimes.

1:56:14

They trade these zero day to expiration options and all that.

1:56:16

So there there's some of that.

1:56:17

I don't think it's maybe as widespread as as what we've seen in the past, but probably is some of some of that. >> I just Yeah.

1:56:23

I just wonder if like if you go to the the the median American uh do they have significant exposure to the data center buildout right now? >> No.

1:56:33

So I mean maybe their electric bills. >> Yeah. Yeah. Yeah. Yeah.

1:56:36

So maybe that's but if there's a collapse that's going to go down that's going to be cheaper >> presumably and by the way there's two ways that it could quote unquote collapse right so and and they have different implications.

1:56:45

different implications. So one is just you know there's a digestion cycle there's an air pocket there and you look at the hyperscalers how they spend money even before AI they would tend to build and digest and build and digest it happens >> and I always say like what's the chance of a digestion cycle it it's it'll happen at some point

1:56:59

>> I like this digestion cycle >> but that wouldn't be structural like a digestion >> it would be good for the you get hold it through that like the way it quote unquote collapses is and it gets back to some of your earlier questions on on the return if it turns out we're spending all this money there's no return Then the whole thing comes crumbling down. Totally for everybody. Yeah. Right. Totally for everybody. Yeah. Right. >> Yeah.

1:57:19

But it's like it's like I I just really struggle to imagine a world where it's like, oh yeah, like it was so bad that like Apple's at a 10 PE.

1:57:28

>> Like Google is no longer valuable.

1:57:28

It's like these companies have been valuable for decades.

1:57:32

Like where are they going to they can go down a little bit, but like they're just not that exposed at this point.

1:57:38

Anyway, >> someone in the chat asked, "Please ask Stacy about CDS spreads affecting debt financing costs."

1:57:44

So that's Oracle and weave >> uh i. e.

1:57:47

how does the domino start?

1:57:50

>> Yeah, it's it's it's a little out of my wheelhouse the CDS, but people are looking at a few specific areas like like Oracle. >> Yeah.

1:57:56

>> And Oracle I mean Oracle is not not exactly a hypers scale but they're trying to be a hyperscaler sort of um and and they don't have the balance sheet and the income statement to fund it.

1:58:05

So they are going more to the debt market and core weave I mean clearly you know they they have to to fund with debt with debt.

1:58:10

Most of the other ones you look at look like look at a Google or a Met or an Amazon like you're not in that kind of a stage right they're still they're raising a little bit of debt but they're still primarily funding this out of out of free cash flow basically out of cash from operations. Yeah.

1:58:23

>> So uh >> but it is people people are starting to look at it like for sure >> for sure. >> Yeah.

1:58:27

Have you have you tracked uh situational awareness the hedge fund Leopold Ashen? >> I have not. No. >> What is that?

1:58:34

>> Uh uh former openai researcher.

1:58:34

Oh, this is that kid that started the He's got four billion under management. >> Yeah. Yeah, that's right. >> And I was curious.

1:58:43

So, so his strategy like he he raised the fund like at the beginning of this year or closed it. >> Closed it.

1:58:50

He was raising it for >> he'd been raising it for a while, but but started deploying aggressively this year and and has performed >> really well at least.

1:58:59

>> It's the best performing hedge fund. Okay. >> In the world.

1:59:02

>> He's in the right place at the right time, right?

1:59:03

And the whole thesis was just AI is going is real.

1:59:05

Do you think do you think some more traditional hedge funds have sort of just overthought the AI trade over the last year?

1:59:12

I don't know about >> because it's not like he it's not like he was buying like somewhat somewhat uh >> he had a somewhat unique uh take.

1:59:22

>> He had a very informed take but it wasn't >> but he also didn't go Nvidia. He went Intel.

1:59:26

He went other places on the map.

1:59:29

>> So by the way Intel's gone up not because of AI.

1:59:31

Intel's gone up because you know Donald Trump wants the stock to go which is a bull case.

1:59:34

that's fine, you know, but it's not an AI story.

1:59:35

Um, my view in general, and yes, I don't know if specific hedge funds have been, you know, overthinking or not.

1:59:42

>> I haven't wanted to overthink it.

1:59:42

My my general call this year has mostly been own the high quality AI names. Ignore most of the rest.

1:59:48

Like that's that's been fine, right?

1:59:50

It hasn't had to be complicated. Number go up, right? That's [laughter] right.

1:59:55

>> It hasn't had to be it hasn't had to be complicated. >> Number go up.

2:00:00

>> Well, well, I mean, what do you uh what do you put in that high quality name bucket?

2:00:03

Uh, do you put the iPhone?

2:00:07

>> I mean, we've covered like Nvidian Broadcom, for example, mostly those. Um, yeah.

2:00:10

And, you know, >> we've been more lukewarm on AMD and and and that's one I've missed, right?

2:00:16

Because, you know, it it's also like ripped.

2:00:18

They haven't necessarily had to be quote unquote high quality to work, right?

2:00:22

Because right now, we've been again, if you think of an S-curve, if we're on that that >> exponential growth part, it it it takes everybody up, right? It's been fine.

2:00:28

But again, you haven't had to over complicate anything. Uh, not yet. Yeah.

2:00:34

What about uh I mean talking about not over complicating it like if you just bought Google and Microsoft that's a pretty broad index on AI between you got to remember like like it wasn't that long ago that people were looking at Google as an AI loser. >> Totally. Yeah. No, it changed. It completely changed. Completely changed.

2:00:50

Um they positioned themselves very very well.

2:00:52

Um uh Catrini has another post here on the 2022.

2:00:55

I saw a lot of very smart people in 2022 f uh fail to recognize the reality of reflexivity i. e.

2:01:03

stupid headlines that with a few hours of research could reasonally dismissed as nothing of consequence would add fuel to the fire and result in further downside.

2:01:11

Understanding that this dynamic works to the upside as well as the downside means that yes, even if you know that the CDS on Oracle and Coree are blowing out because the CDS market is easily pushed around by a few parties, trying to get cute and hedge their exposure to AI lending.

2:01:25

Uh you also recognize that if enough people view that CDS widening is indicative of a problem, it will become a problem.

2:01:34

What do you think about these stupid headlines?

2:01:35

>> I I mean headlines have certainly been more of the bane of my existence [laughter] probably over the last couple years. Yeah. Yeah. >> Um, yes.

2:01:41

So, there have been lots of movements >> from headlines that if you if you were had any depth of of subject matter expertise, you you'd know the headline itself didn't mean anything. >> Yeah.

2:01:52

What do what do you fall back on?

2:01:54

Do you go to the earnings reports or Yeah, I'll give you an example.

2:01:57

>> That kind of stuff tends to correct itself over time, too.

2:01:59

I mean, you get pops and I mean, I'll give you example for from my own coverage and and this is a stock that that I like.

2:02:04

Qualcomm announced um uh and this was this is their headline.

2:02:08

their headline. It wasn't like some stupid headlinear, but they announced like an AI like server >> and there was wasn't a whole lot of information the pressure the stock went up 20% the moment of the and then and then it kind of gave it back as it but it had a you had a pretty big pop >> on the headline just because it was AI

2:02:24

whereas if if you know you kind of know and by the don't get me wrong I mean there there's you we'll see what happens with that with that uh product with them and >> you know again you can argue it's option value and everything but they go up 20% on on one day was was probably overdone and it gave it back you That's fine. >> Yeah, makes sense. >> Yeah, makes sense.

2:02:41

>> Giving it back, I feel like, has been the story of Oracle.

2:02:42

They got this, you know, tremendous pop off the OpenAI deal.

2:02:47

Now, they've retraced to below it.

2:02:50

It's lower than it was before, which to me says like either the market >> doesn't believe that >> it's it's real and or that the other reading would be it's real, but it's not going to be ROI positive. Right. >> Yeah.

2:03:05

>> Yeah. Um again for Oracle without making any comments on on Oracle I mean th those are the for for any of these investments those are the worries that you're going to have right yeah either because again especially if it's open AI >> so Alman's committed to a tremendous amount of capacity I I mean it's just

2:03:19

between on on the chip side between Nvidia Broadcom and AMD it's 26 gawatt >> right and just for some context I think the whole global data center installed electrical capacity know I don't I want to say something like 70 gigawatt something in that ballpark right >> all right so It's it's a lot. I mean, he

2:03:34

I mean, he was even making comments he wanted to deliver what was it a gigawatt a week at one point.

2:03:40

I I mean it's a lot, right?

2:03:42

And so >> you already are wondering can he actually deliver on that or or or not?

2:03:47

And and those are valid questions and and I but I wouldn't I wouldn't count Altman out like he's a aggressive but you know he's got like like large aspirations.

2:03:54

Um, but then with someone like an Oracle like who doesn't have the balance sheet or the income statement that some of the others do and and you look at the size of the the I can't even remember what it was 400 billion dollars or something.

2:04:05

It was a massive step up 300 um in in one quarter >> like you wonder where it was coming from.

2:04:11

It's always around like can they deliver it and can they pay for it and and those are the general worries I think for anybody that's announcing something. Yeah.

2:04:17

Are you gonna have >> how do analysts try and dig into uh you know there's quality of earnings, quality of revenue, quality of backlog feels like an important thing to dig into, but I don't know that the contracts are available.

2:04:31

>> They're they're not right.

2:04:31

So look, I I mean you you talk to whoever you can and >> you know you've you've been doing this while you look for pattern recognition, but I mean look, nothing in semiconductors is ever really baked. >> Sure. >> Right.

2:04:43

I I mean, in fact, we just discovered why like during co they a lot of these companies were experimenting with with quote unquote non-cancellable orders. >> Sure.

2:04:50

>> And we saw what happens.

2:04:50

It's like, yes, maybe I could contractually force my customer to take a year's worth of parts they don't need. >> Yeah.

2:04:56

>> Am I really going to do that?

2:04:57

Historically, the answer was no. >> Yep.

2:04:59

>> During co for some companies, the answer was yes.

2:05:01

And and those particular companies are are still paying for it. >> Yeah. Yeah. >> Because Okay, great.

2:05:06

I just took all my parts.

2:05:07

I don't need to order anything from you for for a year. Right. That makes sense.

2:05:10

Um, and so I'm always a little hesitant of of of backlog and and commits.

2:05:15

And even some of these, by the way, even with these open AI deals, they put out big numbers, but it's not like the whole thing is committed like maybe the first gigawatt at this point. Totally. Totally.

2:05:23

And which is how it should be. >> Yeah. Yeah. Yeah.

2:05:25

No, that makes a lot of sense. >> It's great. >> Are you AGI pilled? >> No. Probably not. [laughter] >> Probably.

2:05:32

>> I'm not exactly sure what AGI means yet.

2:05:35

You know, there's a lot of different definitions and sometimes it tends to change.

2:05:38

>> Well, do you find AI useful in your day? No, I I I I do.

2:05:40

I have to be a little careful because >> from a regulatory and compliance standpoint, it's not like I can just start throwing stuff into I'm very limited.

2:05:48

We have some internal stuff that we can use which is >> enterprise plan. >> Yeah.

2:05:52

And and it's it's it's ring fenced and everything.

2:05:54

>> Um but I mean simple stuff, right?

2:05:54

I I I mean you what was this notebook LM?

2:05:57

I can literally take I could take a YouTube of this what is it three-hour podcast and toss it in there >> and it'll give me a summary. Not just a summary.

2:06:06

Then we can take that summary, put it into another model and say, "Make me a three hour." >> Sure. Yeah.

2:06:10

[laughter] Pretty soon it's just AI is making and watching podcast, right? >> A slurry of content.

2:06:14

>> But that's just one example.

2:06:14

Like so there there were there were clearly >> ways where it's influenced my my experience in my in my workload.

2:06:20

And I'm probably on the low end frankly of of of what I could be using if I am I am constrained. >> Sure.

2:06:28

>> On what I can can do with this.

2:06:28

I' I'd love to use it more if I could.

2:06:32

>> That makes a lot of sense.

2:06:32

Uh well, thank you so much for coming by the studio. This is a lot of fun. >> Thank you, bud.

2:06:37

>> Have a great rest of your day. We'll talk to you soon. >> Cheers.

2:06:40

>> While he's hopping off, let me tell you about Linear.

2:06:41

Linear is a purpose-built tool for planning and building products, meet the system for modern software development, streamline issues, projects, and product road maps.

2:06:47

Uh speaking of turning things into podcast, Kristoff has some fake news here on the timeline. Uh I love Kristoff.

2:06:54

Coastal futurist Kristoff says, "Still crazy to me that Steve Jobs/Apple invented the word podcast and that it's a mix of iPod and broadcast."

2:07:04

And apparently this isn't true.

2:07:07

Apparently, a BBC journalist Ben Hammersley coined it in a 2004 Guardian article.

2:07:13

Uh but then it got ported back to Apple and the and the term podcast was adopted.

2:07:21

Um but uh it is it is funny that podcast it did come from iPod.

2:07:29

>> It's always felt like a very boomer term. >> Yeah. >> And it makes sense.

2:07:32

I I never I never knew that it was it was a combination of >> Oh, you didn't know that it was iPod plus broadcast. Yeah. >> Yeah. What else?

2:07:41

>> That that makes the casting is very very popular.

2:07:45

>> Uh anyway, >> what's this uh article from?

2:07:46

Evan Armstrong over at the leverage published an article on uh who actually makes money when robots work.

2:07:54

Uh looking into some of the venture funding that's flowing into humanoid robotics and he is trying to create a field guide for separating the real companies from the grifters.

2:08:08

Talks about 1x uh the home robot costs $20,000 upfront or $4. 99 a month.

2:08:12

The website looks like every other VC funded DTOC brand from 2015.

2:08:18

Millennial beige sans serif typography.

2:08:21

The works buried in the fine print and tech cover tech coverage is the actual product for most chores.

2:08:28

A human in a call center will drive the robot around your house via tea operation while the system records training data for autonomy that doesn't exist yet.

2:08:37

And so there's a big question about uh how like what will the actual margins be?

2:08:43

and he was trying to dig into that.

2:08:45

So, uh, you can go read Evan's piece over on the leverage if you want. You get a 7-day trial.

2:08:50

Um, >> who actually makes money though when they work?

2:08:54

Is it the call center operators?

2:08:57

>> I believe uh uh I mean I I I would not bet against Elon on this.

2:09:02

I believe that the uh the hardware manufacturer will ultimately be the one that makes money in the long term.

2:09:08

I think that uh the everything else is more commodity in the stack but there is going to be a uh a compounding advantage to actually having the manufacturing capability to build the robots at scale.

2:09:20

Now this is years away but um I am I'm certainly AGI pilled in the sense that the the TEA operation become will become less and less important and uh and the Tesla model of having a a economically producable product will be very very important.

2:09:37

So that would be my take.

2:09:40

In other humanoid news, uh Brett Adcock was putting a company in the truth zone.

2:09:46

Shenzenbased company, UB Tech, claims to have completed the world's first mass delivery of humanoid robots.

2:09:54

Uh and the Shenzenbased company has secured apparently over 112 million in Walker S2 orders this year.

2:10:04

>> Uh Brett Adcock says, "Look at the reflections on this bot and then compare them to the ones behind it."

2:10:08

The bot in front is real.

2:10:11

Everything behind it is fake.

2:10:13

If you see a head unit reflecting a bunch of ceiling lights, that's a give that's a giveaway. It's CGI.

2:10:18

So, he's putting uh he's putting UB in the truth zone.

2:10:25

And then Christopher comes over the top and puts him in the uh and it says, "Such an embarrassing pose for a CEO at this level to make."

2:10:32

So, people don't necessarily believe that uh the the CGI claimed Did Ubek actually deliver it?

2:10:40

There's no community note on the original video.

2:10:43

I I for something like this.

2:10:46

I mean, we've seen iRoot.

2:10:49

Like, you can actually just do flawless CGI that is indistinguishable. There's no way to tell.

2:10:55

Uh, so I would I would I would be relying on some sort of, you know, on the ground reporting.

2:11:02

Do you have an idea, Tyler, of whether or not this is real?

2:11:05

We've seen demos of this robot before where it pulls the battery out of the back. >> Yeah.

2:11:10

Uh I don't know for for sure if it's real, but it is a public company. >> Yeah.

2:11:16

>> So Brett kind of needs this company to be totally fake because uh UB is a public company.

2:11:22

It's valued at around uh 7. 5 billion dollars. >> Okay.

2:11:28

>> Uh and they have uh they have real revenue. >> Okay. UB, man.

2:11:32

There the the [laughter] market over in China is extremely competitive.

2:11:38

You have UB and then you then you have the the what what's the other company? I keep forgetting. >> Unitry.

2:11:45

They're two different companies, right?

2:11:46

But they're both publicly traded, both have revenue, both make humanoids.

2:11:50

Um I wonder if there's like I wonder what the CEOs of these two companies would actually say.

2:11:55

like what is the differentiation between the two uh the two products at the uh because um they look pretty identical.

2:12:02

Maybe we need to do a sidebyside but I don't know what uh what else here said Martin Scrley said best part of UB is it's public with real revenue so its valuation is naturally far below pre-revenue robotics [laughter] >> naturally. >> That's wild. Yeah. Um, >> uh, >> yeah.

2:12:21

No, I I do think it's real, but I don't know.

2:12:24

Like, it it's it's really hard to prove it one way or another.

2:12:28

It's hard to prove any of these videos that that that come out with the humanoids because humanoids are just like it's the textbook like CGI product.

2:12:36

Like you can just if you're at all good at CGI, you can make a humanoid robot look great because it's all just polished steel.

2:12:43

Basically, perfect reflections.

2:12:45

It's much harder to make a human face look CG CGI real.

2:12:47

Um, and so we've had the ability to make like CGI Stormtrooper, CGI C3PO, like like that's been at perfect indistinguishable level for years, but uh getting to the actual human level. >> Yeah.

2:13:03

To be honest, I care a lot less about uh about did they use CG CGI to like put a hundred of these robots in one room versus like what are the actual capabilities of the individual robot. Yeah. Right.

2:13:17

>> So, uh that's why I think 1x I think they're pretty straightforward about uh about it being teaoperated or that being kind of the value is you're buying a robot that can be teleoperated in your home.

2:13:27

It really feels like these are the question the United States like >> why is Adcock like obsessing over a competitor and then what what he what can he do in the next three to six months to justify his $40 billion valuation, right?

2:13:44

>> It probably needs to ship a bunch of these things like just for any reason.

2:13:48

uh just manufacture a lot of them I would imagine because um with Unitry and this other company and you know 1X is starting to ship and Elon's clearly getting serious like the the race is on to uh to actually start manufacturing

2:14:04

and shipping them and it'll be it'll be interesting with with the flying car thing a lot of it's like regulatory so you it's harder to assess what the progress is like uh because you could always just kind of get hung up in in regulatory I wonder in the humanoid space. Um well, speaking of flying cars,

2:14:19

Um well, speaking of flying cars, what's up, Tyl?

2:14:22

>> I was just going to say I think it's interesting we still haven't really seen any um uh humanoid CEOs like talking about sanctions against China.

2:14:29

Um >> yeah, I know that's the thing to call for.

2:14:33

It's like a very easy argument.

2:14:35

>> I would not be calling them fake.

2:14:35

I mean, you can do that, but you should just say like even if they are real, like we want these made in the US, like in the way that you see kind of Daario saying in AI.

2:14:43

Um, and I it's just kind of weird that you don't see like Elon saying that we need to make these in the US or the the 1X guys saying, "Yeah, bring out the banhammer.

2:14:53

[laughter] >> The banhammer.

2:14:54

Let's uh >> I mean that Yeah, I just I that's going to be an easy one for you.

2:14:57

All you have to do is like, do you want a million robots in in American homes that could have, you know, the the sci-fi scenario where you have a back door?" Yeah.

2:15:08

And uh >> like the argument against DJI was always like, well, you know, if some tiny drone is in your bottom, you know, sock drawer, like what's it going to do?

2:15:18

It's not just going to bust out of there.

2:15:20

But like a humanoid robot will just bust out of the whatever you put them in unless you store them in like your gun safe or something. Walking guns safe.

2:15:27

Uh let me tell you about numeral.

2:15:30

com sales tax and autopilot.

2:15:32

Spend less than five minutes per month on sales tax compliance.

2:15:35

And then uh we have an update from Keller from Zipline.

2:15:37

We're going to watch this two-minute update from him. Pull it up. >> Hey everyone.

2:15:44

Uh, it has been an insane two months, but I thought it'd be cool to give a two-minute update.

2:15:47

Whenever I post something on Axe, people are always asking me like, "When is it coming to my metro?

2:15:52

Why aren't you scaling faster?"

2:15:53

We are definitely hearing you.

2:15:53

We are scaling as fast as we possibly can.

2:15:55

In fact, [music] I am standing in our uh expansion space for the manufacturing facility as we speak.

2:16:02

>> [music] >> We're getting ready to build 20,000 autonomous aircraft a year, all here in South San Francisco in the United States.

2:16:07

Mid December, we will actually start producing the first aircraft here in this space.

2:16:11

So this past week, I was in Dallas visiting a lot of our different customers, going and visiting a lot of the different stores that Zipunn is delivering from.

2:16:17

And my mind was basically blown.

2:16:20

Right now, we're growing the number of deliveries we do per day at around 15% week [music] over week.

2:16:25

And we've been growing that fast for about 30 weeks straight.

2:16:27

You know, a lot of our customers out there are placing orders three to four times per week.

2:16:33

In fact, some customers are ordering three times a day.

2:16:34

People actually just fundamentally change their order.

2:16:38

So, some people are grocery shopping once every 1 to two weeks and then ordering from zipline three to four times a week just to do fillins.

2:16:42

We've also been able to launch a new Walmart Super Center every week across Dallas over the last couple months.

2:16:49

And by the way, I you know have talk been talking about really exciting hypers scale in the US.

2:16:53

But a lot of people are often like well wait a minute like isn't that zipline operating a huge logistics network in Africa. Yes.

2:16:57

In fact that network is growing faster than ever.

2:17:02

Today we serve 5,000 hospitals and health facilities across Rwanda, Ghana, Nigeria, Kotivoir and Kenya.

2:17:06

That has become the largest commercial autonomous system on earth.

2:17:10

Uh together what we do in the US right now is the plan is doing an autonomous delivery about every 30 seconds.

2:17:16

We're also adding a lot of new products.

2:17:18

[music] For example, in Ghana, we just added HPV vaccine to the overall network.

2:17:23

And in the first week, we delivered 150,000 doses [music] of vaccine. This is a crazy scale. >> Congrats. >> John's back. >> I'm back.

2:17:32

He's coming on the show next week. We love Keller.

2:17:34

Uh congrats to all the folks over at Zipline on >> Yeah, really wild building in South San Francisco, scaling deliveries like crazy. >> Yep.

2:17:45

Uh, I think this is one of those things that's hard for it to be hard to be that excited about until there's a spicy question in the chat.

2:17:51

How long until they pivot to a weapons company?

2:17:53

I don't think it will happen.

2:17:56

I think that uh drone defense is like the most it's it's such a um such a such a a crowded industry.

2:18:06

It would be really really hard to break through there. Um I don't know.

2:18:10

Maybe maybe there's something in like logistics.

2:18:12

I've talked to a few folks in defense that will do dronebased transportation or delivery for let's say um how do you how do you get supplies from land onto an aircraft carrier that's stationed off of the coast?

2:18:26

Well, you could fly a whole helicopter there, but what if you just want to deliver one smaller package back and forth?

2:18:33

You could use a smaller drone for that.

2:18:35

Uh there's companies that are building in that category.

2:18:38

So I I mean I could see it happening, but I wouldn't expect Zipline to be, you know, on the front lines of Ukraine competing with NOS to, you know, arm the resistance there anytime soon.

2:18:50

Uh the drone delivery, like just delivering a burrito is going to be a massive market.

2:18:55

Like Door Dash is does it way.

2:18:58

It's a hundred billion dollar business.

2:19:00

Like I don't think that they they're they need to >> deal with all the craziness of DoD procurement.

2:19:05

Anyway, >> um, so someone in the chat mentioned that UB Tech fired back and released a behind thescenes video. >> No. Okay.

2:19:13

Okay, we got to pull that up. Do we have it?

2:19:15

Thank you to the chat for letting uh letting us >> I'm adding it here. >> Let's add it.

2:19:20

Um, in the meantime, uh, more on robotics, Blake Robbins has a great take that I was curious about.

2:19:25

Uh, if anyone knows anything about this, please, uh, fill me in.

2:19:30

He says, "As robotics continues to get more attention, I always wonder what Boston Dynamics is cooking, it feels like Boston Dynamics should have been the open AI of robotics.

2:19:40

And yet, I can barely mention anyone that worked there."

2:19:43

Um, and there's a whole bunch of different debate on, you know, what happened.

2:19:48

Boston Dynamics was sold a few times >> to be studied.

2:19:51

>> Yeah, Boston Dynamics.

2:19:54

>> What's the dynamic over there?

2:19:56

>> Wait, wait, Boston Dynamics.

2:19:56

It's the original browser company of New York.

2:19:59

They just took their city and what they do and put it together.

2:20:00

This is the the you know they the Dynamics company of Boston rebrand come out with a humanoid.

2:20:08

Let's play this video this behind the scenes video.

2:20:10

>> Los Angeles Dynamics would just be like an influ like Lincoln bio.

2:20:15

>> Well at one at one point Boston Dynamics sold the Hyundai heavy industries.

2:20:17

So I believe they were across the Pacific Ocean.

2:20:21

Uh, let's react to the second video posted by the humanoid robotics company.

2:20:29

Okay, UB industrial walkers.

2:20:29

They've been pumping these out.

2:20:32

It feels like the question has never been, "Can China make a lot of these things?"

2:20:37

Like, obviously they can.

2:20:40

>> In the in the bio, they said they said it looked too perfect to be real. >> Yeah.

2:20:45

>> And then they used some chatt slot, but perfection isn't fabricated. It's delicately done.

2:20:50

>> [laughter] >> It's so good.

2:20:53

You know, you know, for a long time people were saying that uh there was no way to watermark uh AI created content with because like oh how would you do it? You you change one.

2:21:04

It's like actually all AI content is watermarked.

2:21:07

It turns out it's just perfectly watermarked.

2:21:09

Uh yeah, this looks real to me. I I don't know.

2:21:11

It also could be honest comments.

2:21:13

It's pretty funny to see Brett say this was all faked.

2:21:18

Yeah, it it looks it looks real.

2:21:18

I mean, it would be way they could have done so much better to make this look real.

2:21:24

Put a bunch of humans there, touch them.

2:21:25

A lot of the hard part in CGI is the handoff between the CGI character and the human character.

2:21:33

And so what you should be doing is is you should have a human who takes like a smoothie and pours it on top of the robot and then like wipes the robot off clean with a towel.

2:21:46

and you're seeing how the fluids interact with the robot, interact with the person, and like that was that was not actually that satisfactory. I don't know. I think uh I don't know.

2:21:56

I'm not calling it fake, but it could be fake because CGI is really really good.

2:22:01

Like CGI just is at that level where that's possible.

2:22:06

Um anyway, >> yeah, we know that we know the caption or the the description of the video was AI generated.

2:22:13

>> [laughter] >> That is hilarious that they they had to use for the caption.

2:22:18

>> It's like it's like AI on and it's like after all it is an AI company like it would be on brand. Uh anyway, Finn.

2:22:23

AI the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on G2.

2:22:30

You can get started for free.

2:22:33

Our next guest is Luca from Bending Spoons in the Restream waiting room. Welcome to the show. >> Welcome to the show. >> Good to meet you. How you doing? >> Hello.

2:22:42

Hi, >> thank you so much.

2:22:43

I imagine it's late there.

2:22:46

Thank you for staying up late and uh coming and chatting with us.

2:22:48

For those who don't know you, would you mind introducing yourself? >> Of course.

2:22:53

Uh one of the co-founders, the CEO at Venice Bones.

2:22:55

And what we do is we uh look for digital technology businesses with unexpressed potential and then we acquire them if they'll sell them to us and uh transform them sometimes quite radically by rewriting big chunks of of the software uh rearchitecting the cloud infrastructure uh redesigning the UI launching a lot of lots of features uh optimizing monetization and marketing rebuilding uh big parts of the organization.

2:23:19

So lots of hand hands-on work and then if we do it right uh we generate a lot of value we uh plug back into bigger acquisitions and strengthening uh with our platform.

2:23:32

So basically our proprietary technologies our expertise access to talent.

2:23:36

>> The company's huge now 11 billion valuation.

2:23:39

How did you get started with all this?

2:23:44

>> So I coounded a startup in 2010.

2:23:44

Uh, interestingly talking about AI, we were trying to uh create a self-writing diary or journal with AI in 2010, which was pretty early.

2:23:54

We couldn't I mean it worked fine, but it wasn't good enough.

2:23:58

Uh, so that was like your typical startup. You work from a garage.

2:24:00

It was really our, you know, living room in our apartment, but uh, more or less the concept is the same.

2:24:06

We we worked on it for 3 years, couldn't make it work um uh commercially and uh then we kind of shut it down and uh through that experience we came up with uh uh the the strategy for Ben basically why don't we try to outsource uh looking for product market fit to the market.

2:24:23

We try to be the best in the world at the call it functional expertise that's necessary to run a digital technology business.

2:24:29

So software engineering um product design growth and all all the things and uh then we we buy businesses where the owner is basically doesn't want to work on it any longer or where maybe uh we can do better uh so we can offer an exciting price uh for all involved.

2:24:47

>> Is the reference is the name a reference to the matrix >> actually? Yes. Yeah, it is. >> Cool.

2:24:54

Yeah, it it is it it feels like at least to me like it's kind of an odd name for any business. I it's cool.

2:24:59

I like the reference, but uh why did you pick that name particular in in particular?

2:25:07

>> So, we we knew we weren't going to work on just one product. Okay.

2:25:09

Uh so, we couldn't call it say Facebook. Yeah.

2:25:11

If you do, you know, um >> Yeah.

2:25:15

You need like a name for a holding company on day one sort of. >> Yeah. Something like that.

2:25:19

So we we chose to to find a name that would uh somehow convey uh a couple of principles or values that we thought were important to us.

2:25:27

Uh and bending spoons reminds us of two things.

2:25:30

One is the power of the mind.

2:25:32

Uh for obvious reasons if you are going to bend spoons with your with your mind it means you believe it's powerful and you can do great things with it.

2:25:37

And the other one is call it uh perseverance, hard work, dedication.

2:25:41

Uh in my uh imagination to to get to the point where you can bend spoons with your mind.

2:25:49

you probably have to work pretty hard at it.

2:25:51

So, and plus it was kind of memorable. So, we we liked it. >> Yeah, I like it.

2:25:56

>> Yeah, I like it. Uh I I reached out or or one of us reached out when uh when the when the AOL acquisition got announced like give give us a backstory on on that deal, how it came to be, when you started thinking

2:26:11

about the business, what what value you saw in the business and and maybe why it was a target that that was uh uh overlooked by by uh maybe American private equity players uh and and what you saw in There were multiple private equities that uh were looking at it too. Um so we

2:26:30

Um so we weren't the only ones.

2:26:34

Um you know it was owned by a private equity or it's still owned because the the acquisition was only signed. It hasn't closed yet.

2:26:42

Uh and so you could imagine how they would run a proper competitive process.

2:26:46

um the um typically we we follow a business for a long time before an opportunity to acquire it presents itself.

2:26:56

I I don't have precise statistics but my my off the top of my head I'd say it's quite rare that we end up acquiring a business we haven't followed for at least a year sometimes more.

2:27:06

Uh so we had been following uh AOL for a while and uh you know when when it it became available we we made an offer that we thought was quite competitive and here we are. Uh what do we see in it?

2:27:19

So I think it's a it's actually a great business.

2:27:23

People are a bit stuck uh in the with the idea of AOL from the '9s or maybe early 2000s of internet connectivity. It doesn't do that.

2:27:31

Haven't done that for a long time.

2:27:33

Um today it's two different products.

2:27:36

There's a web portal for people to consume news and entertainment and and an email client like Gmail pretty much, you know, like that sort of thing.

2:27:43

Uh they have well well in excess of 30 million monthly active users.

2:27:45

Uh 8 million daily active users. Uh so it's huge.

2:27:50

Uh give or take one in 10 Americans uses it.

2:27:52

Um, and and it's just not necessarily, you know, the the new hot thing that you would read about online, but it's still massively used and, you know, very good retention because people are self- selected if if they still use it for really liking the brand and the offering.

2:28:10

>> And we, you know, nevertheless, we think we could help make the product more modern, uh, more effective.

2:28:14

We think that through AI we could create better uh recommendations for the uh web experience essentially better content to consume. We'll see. But it's exciting.

2:28:26

We look forward to working with the team on it.

2:28:28

Uh plenty to to refine and expand.

2:28:30

We it's it's and it's exciting to work on a story brand.

2:28:32

You know, it's I find it kind of cool uh actually to be able to get our hands dirty with with with a brand of the caliber of AOL.

2:28:39

Um >> yeah, it truly is one of the great America Online.

2:28:44

one of the great uh one of the great names in in business history.

2:28:48

How do you think about uh like I feel like Silicon Valley like has this sense that uh businesses are either in hyperrowth or they're dying, right?

2:28:59

And there's nothing in between.

2:29:01

And that's just because like the industry venture capital dollars are deployed into companies that are growing really quickly and as soon as you stop growing like that that sort of source of capital is is turned off and you kind of fall out of the headlines.

2:29:15

But how much like I assume a lot like the kind of part of the thesis for bending spoons is that a lot of these businesses are just like way more durable than like the tech industry maybe gives them credit for because even after they're not uh getting like headlines in tech crunch.

2:29:34

They can still generate a lot of cash flow for a very long time.

2:29:35

But how how do you think about like durability of of digital businesses and and when they be can can become sort of like lindy and and survive across decades versus when they uh evaporate.

2:29:51

>> Yeah, I would say I kind of agree and I and I will say that if anything a business that has a lot of history, it's a lot easier to project its, you know, its future and and and make accurate forecasts.

2:30:04

uh maybe you know it's not gonna 10x but you also have a ton of data uh historical records for all the cohorts at scale to know roughly where it's going.

2:30:15

So uh yes maybe the upside is not transformative as it would be in a seed or VC investment when if all the stars align you know maybe 10x or even 100 extra money but but you also know you're very unlikely to to seed melt in your hands.

2:30:30

Uh yeah, >> many of these businesses have excellent metrics.

2:30:33

They're just not cool and hot so to say.

2:30:36

Uh and so the entire capital markets particularly on the private side, not so much uh the the public side, but on the private side is geared towards growth, very aggressive growth.

2:30:46

And there's merit in that, but it also means there's perhaps an opportunity to be less opinionated about growth at all costs.

2:30:52

We we know on our part, we try to we're basically quite mathematical about it.

2:30:57

We make our projections, have our own return thresholds and then we are happy to buy fast growing businesses.

2:31:02

We have many times stagnant businesses, decline businesses as long as the math uh checks out and this has been quite good for us not not being too uh you know thesis uh you know limited by a very narrow thesis but actually staying opportunistic.

2:31:20

>> How are you uh structuring bending spoons?

2:31:23

Uh do you have a deal team and an operational team that goes in and actually runs the companies or is it more of a you know a hybrid model where a partner who finds someone who finds the deal might uh be immersed in that company throughout the life cycle of owning the deal. >> Yeah.

2:31:42

So it's actually say that we're kind of 25% private equity 75% that company.

2:31:46

So we do have an M&A team.

2:31:46

It's actually pretty small probably eight nine people.

2:31:52

uh and and they they do what you would imagine a private equity firm would do.

2:31:56

They they create a pipeline, scout the deals, uh negotiate the deals, and then really probably 95% of the of the team here are software engineers, product designers, growth managers, AI researchers, and once we close a a transaction, we add a call it a task force of experts to get, you know, get in the trenches with acquire team and study things in fine detail and help with those kind of radical transformations I was describing earlier.

2:32:22

So that's the tech technology company part.

2:32:25

We almost all we do is writing software, developing and refining technologies, user experiences and we we buy to hold and operate forever.

2:32:32

We're not a fund to be clear. More like a burial hat.

2:32:34

We buy off our balance sheet.

2:32:36

You never sold a business or do intend to.

2:32:40

>> So you so is it is it fair to think yeah you'll you imagine AOL and Vimeo existing as companies in 50 years or brands is 50 years or both like uh what is the critical >> business units I would call it? business units. Okay.

2:32:56

>> So the the the the if a company is more a kind of a legal entity that may be uh dissolved in the future maybe yes maybe no depending on considerations but >> the there there will be a business unit with its dedicated management team and engineers and designers uh and uh uh sorry I don't know why >> that's on the other side zoomed >> in we we just zoomed you in a little bit for the viewers at home. Sorry.

2:33:19

There you can [laughter] you can see my baby's uh credle just in the background. >> Oh, cool. >> Nice. >> Congrats.

2:33:26

[laughter] We have we have five kids on our side. It's amazing. >> Yeah.

2:33:32

Mine is 2 and a half months old, so that's pretty intense these days.

2:33:36

>> Well, thank you so much for taking the time to come talk to us. We really appreciate it. >> No, no, my pleasure. Thank you for having me.

2:33:40

having me. I' I'd love to know like what what what is it actually like buying a 5,000 person company or like because I imagine like if I'm like if you buy a company and you can actually go interview everyone but with 5,000 people you're like layers and layers and layers

2:33:58

deep in everything like how do you actually go and start right sizing we've seen a little bit of what happens uh through the stories of Twitter what Elon did there uh obviously that was a that was a company that it seemed like post Elon was massively overstaffed. Um, but

2:34:12

Um, but uh but even even even if the staffing is correct, I mean Apollo's owned AOL for a while, so I imagine that it's not wildly overstaffed.

2:34:24

Um, how do you actually go in and and just get your handle on everything that's happening within the business because it's such an such a huge entity, >> right?

2:34:34

So, we have never acquired a 5,000 person company.

2:34:37

the largest is about a thousand people. Okay.

2:34:39

I think your your point stands I mean but just to for accuracy sake >> uh well I think it's very difficult perhaps impossible to do if you are again a private equity and you have a small investment team.

2:34:51

>> Um in our case we will add a task force that's sized uh in relation to the size of the organization we're trying to study.

2:35:01

And so if we acquire a 10,00 person company we'll probably have say 50 people.

2:35:06

If it's a 100% company maybe as few as 10 and then over the course of couple of months uh you know we will split the work so everyone is in charge of understanding a piece of the organization that's not too big for like the right size for them and and specific to their capabilities and expertise.

2:35:24

to their capabilities and expertise. So if there is a more technical part maybe an engineer if it's something has to do with design or marketing you know and so on and so forth and then those people will be talking to each individual in in that part of the organization multiple times they will be looking at the code base they'll be contributing on ongoing

2:35:42

projects so we take our time to learn uh I mean I was about to say everything there is to know of course that's not entirely true like you don't learn everything in two months but tr truly learn the vast majority of what matters and only then do we come up with say a a new vision for the company, a new road map, the a new design for the updated organization. Uh it is extremely time

2:36:01

Uh it is extremely time consuming and only feasible you have if you have a large call it corporate staff of of experts like in our case uh only only then can you do it at scale otherwise yeah you couldn't I agree. >> Yeah.

2:36:17

>> Yeah. what how how much is like I'm assuming when you're thinking evaluating a potential acquisition you're thinking how much can this company benefit from AI and what is kind of the AI disruption risk oftent times it could be both I can I can you know imagine with AOL you're saying like better content recommendation that you could roll out maybe with with uh less resources invested but at the same time

2:36:44

uh there's risk of new companies you know entering the market But what's your any sort of like framework that you're using to evaluate what companies are going to do well because nightmare scenario as you buy like a great business today and that becomes uh you know less relevant but there's also uh I I think Silicon Valley also maybe again going back to my earlier point around

2:37:06

durability like there's companies from you know that that have been disrupted multiple times that can still continue to produce cash flow but I'm I'm curious what your framework is >> yeah so I think there's I believe you can come up with plausible v visions for the future uh I mentioned earlier we were working with AI in 2010 where I I I didn't know a single other person who was interested in AI back then so I mean

2:37:33

I'm sure there were many in the world but it was not mainstream so you know we did have a big vision for AI in the long in the long run it turned out to be way too early maybe a decade or more um so I'm I'm I'm a big believer in yes you want to have a vision for the future, but at the same time, if you think you know what's going to happen and especially over what timeline, you're very likely to be disappointed. So, I

2:37:52

So, I would never want to bet our future on those sort of uh assessments.

2:37:56

What we try to do is uh evaluate whether a company is more or less likely to be disrupted and of course also enhanced through AI and that that's basically qualitative assessment.

2:38:06

We try to embed that in our uh acquisition thesis but also we al always need a a contingency plan in case there is a uh very aggressive rapid disruption.

2:38:17

So we need to make sure that we have ways to get back our investment uh in case we end up in that or most of our investment if we end up in that scenario.

2:38:26

So you some businesses are structured in a way that if things don't go well, you you may be able to trade long-term health for short-term returns and at least uh salvage uh uh your investment overall.

2:38:39

I mean, it's not going to be a stellar investment, but still you break even.

2:38:42

So we we try to have a uh an escape route just in case things don't turn out the way we we think it will.

2:38:48

And of course, the fact that we're so diversified, the biggest business we own contributes about 15% to our revenue.

2:38:54

uh and they are across many different segments.

2:38:57

Um we are massively less exposed to this sort of disruption than any company running a just one product no matter how successful that one product may be today. >> Yeah.

2:39:11

>> Any any plans to create a Neocloud or anything of the sort or you guys like uh staying at the product level?

2:39:20

>> Uh no no such plans for for now.

2:39:24

uh what's the Italian uh early >> I want to dig I want to I want to dig into that a bit more just just out of curiosity because I'm I'm I'm assuming there's a lot of different players that would love to give you guys capital to help deploy uh cloud given that you're running a lot of you know companies that are going to be uh buyers of of compute and you have a track record of being able to deploy

2:39:50

large amounts of capital is the decision to you like you the strategy is you're you're invested in a bunch of different companies, but do you like them to be the same kinds of companies and that like again is it just a mandate around digital products or would you one day branch out because again if you use the Birkshshire Hathaway comp it's like you've seen them buy everything from Coca-Cola to Google, right? Um and

2:40:10

Um and operate a bunch of different businesses. >> Yeah.

2:40:16

Look, I I think there's a trade-off between, let's say, there is a, you know, going back to Warren Buffett, a circle of competence as he calls it, where you you have proven you're good or very good, uh, better than most.

2:40:29

And so, on the one hand, if you stay within that circle of competence, you're more likely to do well, but at the same time, uh, if you venture outside of it, you extend your, uh, toolkit, your capabilities, and the TAM, uh, grows with it, too.

2:40:42

So there is a trade-off between uh expanding that circle over time while uh seizing the opportunity at hand with the what you already have proven that works.

2:40:55

In our case we'll we'll be next year we'll probably be at make about 2.

2:40:57

5 billion in revenue and uh the overall um the overall uh digital technology market is about $2 trillion. >> Yeah.

2:41:09

>> So it's not exactly that we're saturating the opportunity here.

2:41:10

So before we get into something we know very little about other than uh on a high level I I I think we should uh make sure that we are saturating the core opportunity.

2:41:20

But yeah maybe in five or 10 years if we ever feel that uh we're getting too big for for the TAM and maybe we'll look beyond that.

2:41:27

Who knows what will be >> appealing then.

2:41:32

>> Uh do you think it's funny that the the US venture capital ecosystem is somewhat like offbalance sheet R&D for you guys?

2:41:40

It's like they can deploy a bunch of capital into these categories, create good products like Evernote, and then you guys can come in and and uh own them for the long term.

2:41:52

>> Look, we when it comes to acquisitions, we're opportunistic.

2:41:54

Uh I don't you know, whatever the market offers, if we think we can deliver great returns, we'll be happy to buy it regardless of the particular history. So, I don't know.

2:42:05

I don't have other gratitude or any particular opinion on on that.

2:42:08

You know VCs have many have done really well.

2:42:12

I guess it's normal that at least in some cases uh their investment didn't turn out to be the exceptional success that it could have been.

2:42:21

>> Well, in many cases some of those firms actually IPOed uh and you know delivered a bunch of returns for the LPs in the venture fund.

2:42:29

Uh I I am interested in know you you've you've acquired Evernote's probably a good example. Yeah.

2:42:35

>> Um but any any example of uh acquiring a company that's already publicly traded? How does that work?

2:42:41

How how do you work through those uh that process?

2:42:44

Uh are you going directly to the board?

2:42:47

like are there uh are there best practices around like when a company or or a group of shareholders uh might be more receptive to a uh to a takeover or um or do you see yourself ever getting into uh more of like a hostile takeover scenario?

2:43:06

Does that does that uh does that matter to your strategy?

2:43:12

>> We've done two uh take privates so far. One is uh Brit. >> Yep.

2:43:17

early this year and the second one is Vmail. >> Yeah.

2:43:20

>> Uh so I'm no like I wouldn't consider myself a world expert in private but I've seen a couple of them so I can probably provide at least some some input here.

2:43:28

Um we have done it quite collaboratively reaching out to the board and uh uh and just saying look we'd be interested and we make an offer.

2:43:38

the I would say the the the negotiation is not massively different from what you would do in a private deal, but the there is a lot more pressure on a board of a public company to uh to to to act in the best interests of the broader

2:43:55

shareholder base uh because the liability is a lot more legally speaking it's probably not very diff different but of course the transparency of that process makes it really difficult to say I don't like it you know if it's a good offer you have to entertain it So

2:44:08

on the bright side, if you have a great offer relative to the stock price, you have, I think, better certainty that it'll be at least entertained, then with private companies where sometimes you find you you're absolutely confident you're making a an incredible offer, but

2:44:22

say the founder is just not not going to sell or a particular investor maybe invested at a really high valuation and they're now maybe even delusional in thinking, oh, we'll get back to three billion if we wait for, you know, long enough. And so there you really have any

2:44:35

And so there you really have any leverage.

2:44:37

It's like okay end of end of the conversation with a public company that can't really happen or at least it's quite rare.

2:44:42

Uh on the on the you know so that that's the positive on on the negative the process is a little bit more uncertain because with with a private deal typically if you have a handshake agreement with the two three decision makers then it's quite unlikely that uh the deal falls through. with a public company.

2:45:00

Um, basically at any point in time if someone comes with a better offer and it can be quite public so everything is you know uh back to square to square one uh you need to show their vote so you only know after multiple months and so you're kind of keeping your fingers crossed but overall I love public deals.

2:45:18

I think they're in many ways more straightforward.

2:45:19

There's no hiding behind illusions.

2:45:21

I mean your stock price speaks volumes and if it's been at a certain level for a long time >> that is it you know for the most part. >> Yeah.

2:45:30

Uh is it also do you have more confidence in audited financials uh or any other sort of process power that comes from actually being a public company?

2:45:41

Do do you do you feel like when you go into a company that's been taken private uh you can just feel the difference? Oh, okay.

2:45:48

This this company has been operating like a public company and that has maybe pros and cons but you can definitely tell or is it purely in the deal stage that you feel that that there's a difference?

2:46:04

>> I mean we have seen private companies that are run really well in terms of uh FPNA and we've seen public companies certainly have to reach a pretty high bar.

2:46:13

So yeah, I guess we're you're more certain that uh on the one hand, you're more certain that the public company will be better geared uh uh to to provide you with the say the due diligence materials you need and whatnot.

2:46:26

On the other hand, there's generally and and understandably so and rightfully so, more uh more risk aversion in a public company because if there is a leak that can truly, you know, create a pretty difficult situation for for everybody involved with private companies.

2:46:42

It's leaks are also less likely because the incentives to leak something are lower.

2:46:48

Uh there are all sorts of uh reverse incentives with a public company for obvious reasons because the stock is so liquid.

2:46:53

So sometimes uh deals are leaked that if the company was private wouldn't be leaked.

2:47:00

>> Um so I would say um yes the data tends to be a little bit more ready cleaner but on the other hand uh the the company tends to be more uh careful in bringing people under the tent and so at the end of the day it's not always necessarily faster or easier.

2:47:15

You know I I think frankly I don't see that's a major point of difference to be honest.

2:47:20

I think uh uh but that's not so important when you look for for an acquisition. >> Yeah.

2:47:26

>> Yeah. Do you have any type of internal forecast around when some of the current the new generation of like uh or or just the the new crop of AI native startups will start becoming uh for sale because like right now if you're growing quickly

2:47:42

and you have a great product you can probably raise a bunch of uh capital but I could imagine in in twoish years there's companies that maybe don't fully break out that have great products but uh aren't necessarily going to be you know uh public companies one day themselves. >> No, we haven't discussed that. We there

2:48:01

>> No, we haven't discussed that.

2:48:01

We there because we try to focus our time and effort on things we control.

2:48:07

So our our focus right now is to just meet as many great entrepreneurs and investors and private equities and management teams and and bankers as possible to make sure we are involved promptly every time there is a an intention to sell a business.

2:48:25

We have historically been a great acquire very fast highest highest bid every single time we actually competed um and uh essentially no requirements on management teams to stay if they don't want to stay.

2:48:37

Uh so we just need to make sure we are called upon if something is happening but we don't necessarily need to know or have an opinion whether in three years time or two years time a particular company becomes available.

2:48:48

There are so many variables that we wouldn't be planning for >> for being ready for that anyway. So who cares in a way? Yeah, makes sense.

2:48:56

>> Last question from my side.

2:48:56

Uh how are you think about synergies across the portfolio?

2:49:00

You're not doing rollups, but there are some similarities between uh the video products developed by Britco, Vimeo, like are you thinking about how these businesses fit together over the long term or do you see them all as like individual uh project products and companies that you want to kind of grow in their own way? >> Yeah, great question.

2:49:22

So the short answer is the latter.

2:49:24

The reason is uh uh that the I think that those synergies are actually much more limited than people would imagine.

2:49:33

Uh and also uh and perhaps more importantly we believe that uh our business units tend to perform a lot better if they are allowed to operate with extreme levels of autonomy and flexibility.

2:49:48

M >> we want our small teams to feel like they're almost like a startup like we, you know, basically we trust them to make decisions and move quickly.

2:49:56

And if you if you start asking many business units to coordinate on branding and cross-selling and yada yada yada, then all of a sudden you're creating a ton of glue then and and that kills sense of ownership, agility, excitement. Uh so it's a trade-off.

2:50:11

You want to have teams that feel very entrepreneurial and empowered or maybe extract an additional 5% of revenue through um say cross-selling or some sort of bundling.

2:50:23

Uh we we find a former in the long run yields much better returns. Uh so we go for it.

2:50:28

for it. In a way I think you can think of Ben a little bit like the technological version of P uh the PNG Proctor and Gamble where there is a ton of shared infrastructure and capability in their case I I suppose I don't know them well logistics and distribution and marketing and product development but they when you look at the brands they sell they most people wouldn't even know

2:50:51

yeah that they are by the same broader corporation and and in a way we would like Bennis to be similar we don't really care necessarily that a say an Evernote customer knows that Ben is influencers behind it and we're fine out of a way but we don't try to push that message on them as long as they think Evernote is perfect for them and they stay subscribed and they love it. Uh and

2:51:07

Uh and and in fact we think that if we try to uh homogenize our brands we'll be destroying a lot of the value that we acquire in the first place with these storyried brands and and loyal customer bases.

2:51:21

>> That makes a ton of sense. >> Makes a lot of sense.

2:51:22

Thank you so much for taking some time so soon after having a child to join our show.

2:51:26

We really appreciated talking to you. I learned a lot.

2:51:30

So, thank you so much for >> Thanks a ton, Luka. Come on anytime.

2:51:35

>> Yeah, we'd love to talk to you.

2:51:36

>> Looking forward to following the journey. >> Have a good one. >> Cheers. >> My pleasure. Bye. >> Take care.

2:51:40

>> Uh before we bring in our next guest, let me tell you about Adio customer relationship magic.

2:51:43

Adio is the AI native CRM that builds, scales, and grows your company to the next level. Uh, fun fact, Jordy.

2:51:50

Uh, Brightite Cove, acquired by Bending Spoons, was founded by Jeremy Aair, who runs Circle now. Yeah. 2004. Uh, very fun.

2:51:58

Well, our next guest is Healey from Boom Pop. Healey, how you doing?

2:52:03

Welcome to the TVP Ultra. >> Hey, how's it going?

2:52:07

>> Haven't seen you in a while. What's up, man? >> Been a while. How you doing, man? Good to see you. >> Good to see you.

2:52:11

Uh, introduce yourself for those who don't already know. >> Yeah. Yeah.

2:52:15

Uh, my name's Healey Cipher.

2:52:17

I'm the CEO co-founder of Boom Pop. Yeah.

2:52:20

>> And um we are actually you know what's so funny? Hold on one second here. I'm gonna close this. >> Yeah, no worries. >> Okay, I got you.

2:52:25

Um yeah, we're an AI powered group travel company.

2:52:28

I've been running and selling companies my whole career.

2:52:30

I'm from Nebraska, which is a small state in the center of the country you probably haven't been to.

2:52:34

And the plot twist in Saudi Arabia. >> Wait, what?

2:52:39

You grew up in Saudi Arabia? I didn't remember that. That's crazy. >> Oh, yeah. Yeah. Yeah. Riad for 16 years. >> 16 years. Wow. >> Yeah. Yeah. Very cool.

2:52:47

Anyway, let's go back to the business.

2:52:49

>> What is somebody if if if what what is the must do thing in Saudi Arabia for you?

2:52:55

>> Beast world wasn't there when you were there.

2:52:57

[laughter] How did you survive? >> Beast land.

2:53:02

>> The the new hotness in Saudi.

2:53:02

There's this place called I think so Alawaba.

2:53:05

It's like um Petra in Jordan but in northern Saudi.

2:53:08

And they actually I think they're building an Aman there right now.

2:53:11

So there's like there's some stuff going down here property.

2:53:18

Uh, so give us the latest. Give us the news.

2:53:20

Give us the fundraising news. >> Yeah. Yeah. Thanks, man.

2:53:22

So, we raised a $25 million round.

2:53:24

Uh, pulled in some Oh, >> yes. Thank you. >> Appreciate that. Appreciate that. >> Thank you, Jordy.

2:53:35

>> Uh, pulled in some debt and equity and yeah, it's all about growth.

2:53:36

You know, I think >> travel has produced some really good returns for venture.

2:53:41

You know, you think about Airbnb, Expedia, booking, it's crushed.

2:53:45

People don't think about it.

2:53:47

Travel's like 10% of global GDP. It's 11. 7 trillion. >> Wow.

2:53:52

>> And often when you think of travel, especially in the corporate setting, you got to think of like whatever your EA is booking you a flight. >> Yeah.

2:53:58

>> Um turns out 60% of corporate travel is stuff involving groups.

2:54:02

It's like an off-site or an SKO.

2:54:03

And and especially in today's day and age, we're finding the demand for group travel is the most it's ever been. Some fun facts.

2:54:10

one, most people are exceedingly less trustful of Zoom meetups.

2:54:15

They want to meet people people in person.

2:54:17

Uh most AI companies now are hiring event teams.

2:54:23

Like it's one of the first hires because it turns out for scaled AR businesses, um events are like one of the number one demand channels.

2:54:29

And so as we looked at group travel, we were kind of like, wait, wait, wait.

2:54:32

It's this massive part of travel and it's so inacronistic.

2:54:33

Like if you want to if you want to, for example, book over 10 hotel rooms, you literally can't do that online. Did you know that? >> Yeah, it's crazy. We ran into this.

2:54:44

Yeah, we ran into this a fair amount of times just with the small team traveling like uh it it happens.

2:54:47

I don't know if you saw that block party that they had the where it like showed up in their earnings cuz they spent so much they spent like 68 million or something on [laughter] the craziest stories >> on one trip.

2:55:01

>> No, this is this is real.

2:55:01

Like I was at this conference and the then president of Brex walked over to me and he was like, "Hey, are you Helia Boom Pop?"

2:55:06

And I was like, >> "Yeah, but who cares, man?

2:55:09

like you're the president of Brex. Like I'm nobody.

2:55:12

He goes, "No, no, guess what the second biggest expense category is for all of our companies after payroll."

2:55:19

>> And I was like, "No way."

2:55:19

He goes, "It's group travel and events, man." >> Like, "Holy shit." So, it's on the rise. It's crazy. >> Yeah.

2:55:25

So, uh, talk through the actual product experience.

2:55:27

Uh, how do you And then, and then how do you actually make money?

2:55:31

Are you just, uh, taking a fee on top of whatever is booked? Is that the secret? >> Yeah. Yeah. Yeah.

2:55:37

So, so the product is pretty rad.

2:55:39

it to success >> or or I mean it could [laughter] be like seed based >> turns out you should buy low then sell high. >> Yes. This is good. This is good.

2:55:47

I [laughter] like >> uh yeah he heard it here folks.

2:55:51

Uh yeah so it's it's simple.

2:55:53

You talk to our AI agent.

2:55:55

You give it a simple prompt.

2:55:56

You're like yo I want to do an offsite within whatever a 2-hour drive of LA uh a budget of this 50 people with some cool fun outdoor activities. What should I do?

2:56:05

And it looks at millions of data points.

2:56:07

looks at weather, seasonality, a hotel pricing, what you've done, what your guests like and then it puts together a couple of really good options like here's Joshua Tree by the minute of what you do.

2:56:16

Here's Pioneer Town you haven't heard of. You should go there.

2:56:19

Here's Monteceto, go there.

2:56:19

And then if you like it, you just say, "Hey, cool. Do it."

2:56:23

The AI will then go out, it'll reach to the vendors, it'll negotiate for them, look at the contract, it'll book them for you. It makes an agenda.

2:56:30

It even makes your website in a couple seconds. Keeps it live.

2:56:32

And when people RSVP, my favorite thing is everyone gets a text message.

2:56:36

All your guests get a text and it's from the AI on the phone.

2:56:40

And so over text, it's like, "Yo, how can I help?"

2:56:42

And you can say, "Hey, like how do I get to the hotel?"

2:56:43

It's like, "Take an Uber, you idiot." Like, "Oh, okay."

2:56:46

Or like, "Who else is landing right now?"

2:56:48

And oh, well, Jordy and Kugan land around this time.

2:56:49

Do you want to share an Uber?

2:56:51

And you're like, "Oh, that's awesome."

2:56:52

So it's it's like this corner of travel which is so big and it's all these random joint solutions like point solutions and we decided let's just put it all into one place where it's super easy.

2:57:01

Our ultimate vision is very simply we want to be the default way the world gets together.

2:57:06

I'm sure you guys have seen all the you know I saw Chesky on on EVPN.

2:57:09

I think it was last week.

2:57:12

Like we got a problem guys. We have a real problem.

2:57:14

I mean people are lonely.

2:57:16

They're not getting together.

2:57:18

I don't know if you saw this study back in the 70s.

2:57:19

It was eight out of 10 high school seniors said they would party twice a week. Now it's one in 10.

2:57:26

Like >> that's a problem. >> Party. party. [laughter] >> Red alert. Red alert. Red alert.

2:57:34

>> We don't even know how to party in this country anymore.

2:57:35

[laughter] >> That's right. That's right. That's right. So, that's how it works. Um, >> yeah.

2:57:40

>> And then, yeah, it's it's it's it's a simple SAS model.

2:57:42

You pay very low amount and then we make money from the hotels. >> Okay. Cool. Cool. >> Yeah.

2:57:47

All the money in travel, it turns out, is in hotels. >> It's not in flights.

2:57:50

>> Yeah, that makes sense.

2:57:50

Um, are you uh so so we were thinking about taking the team to F1 and I ran something through Chat GPT.

2:57:58

Hey, build a whole thing.

2:57:58

Uh, couldn't get to a place where we could just build it.

2:58:02

Didn't really didn't really hit the goal.

2:58:05

But are you worried about some of the agent commerce being a headwind or can you turn AI and chat GPT into like a tailwind and actually like more of a top of funnel for you? >> Yeah. Yeah. Totally. No question.

2:58:18

It'll be it'll be a tailwind and top of funnel.

2:58:21

I think about this a lot like AI applications are under a lot of scrutiny. Like aren't you screwed?

2:58:25

Like it's kind of like the 1990s.

2:58:27

Everyone's like, "Why would you build an app?

2:58:30

Microsoft is going to roll you."

2:58:30

And that's what everyone says about AI apps.

2:58:33

It turns out it's not going to do everything. Yeah.

2:58:36

>> And so there's kind of I think there's three things you can do and in general as an AI app to like protect yourself.

2:58:41

One is you have some sort of proprietary data. We've got that.

2:58:43

We spent two years building out a database and it's got all the stuff you can't find in Chat GPT like private dining rooms, which how would you do that today? You got to Google it.

2:58:51

You got to call meeting spaces.

2:58:53

We have a bunch of stuff you wouldn't get.

2:58:54

The second thing I think you got to have is a learning network that they don't have access to.

2:58:58

So every event that happens in our platform, it makes the next event faster and easier and the next event faster and easier.

2:59:04

So if you talk to a hotel and they come back and try to negotiate something, we know exactly what they did at the last 100 events.

2:59:10

Ah, we're not going to send that to them. We make it easier. >> Sure.

2:59:13

>> And the third thing which tends to be underindexed is just building a purpose-built application for a specific use case.

2:59:20

It turns out like >> looking at black and white [laughter] Honestly, I No, I I totally agree.

2:59:24

I totally agree with you.

2:59:27

I mean, I' I've just been testing like LLMs on on finding >> like browsing the internet for cars that I'm that I'm like interested in and they're just it's so >> Yeah.

2:59:40

You would assume that like AutoTempest is cooked and yet you can still go to like an AutoTist and search across all the cars, right? >> Yeah. Yeah. >> This is wild. >> Totally.

2:59:47

And that's not even to mention, I mean, my my experience on uh John John and I are are probably not good at at like event logistics.

2:59:55

Like we just don't pay any attention to it.

2:59:58

So whenever we're traveling, we're like, >> "What airport are we going to?

3:00:01

What [laughter] hotel are we at?"

3:00:03

Like finding and and so Nick on our team, bless his heart, is just like kind of locked in around the clock when we're traveling to make sure.

3:00:12

But and it would just be nice to be able to go >> to a single place >> in order. you can.

3:00:16

And we thank you for coming on the show. Have a great day.

3:00:21

Thanks so much for coming and hanging out. >> Thanks. Thanks, Jordan. Appreciate it.

3:00:24

And congrats, by the way. This is awesome. >> Great to have you on.

3:00:26

And and congrats to your whole team. >> Yeah. >> We'll see you soon. >> Thanks.

3:00:30

>> Uh let me tell you about public.

3:00:30

com investing for those that take it seriously.

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Our next guest is John Tennant from Chaos Industries, I believe. Chaos. Yeah, Chaos Industries. Correct. >> Yeah. How you guys doing? >> Great. We're great. >> Welcome to the show.

3:00:47

>> Thanks so much for hopping on the show.

3:00:49

>> I love one I I love the suits.

3:00:49

Uh B and I were going to wear the Dumb and Dumber tuxedos to our Christmas party this year, [laughter] so we might need to go yellow. >> Yellow is a good one.

3:00:56

Uh is your I imagine your whole brand is like black and white, so you can't get too crazy with it.

3:01:01

But have you ever >> Yeah, you know, we got some we got some tan in there, but that's what we figured like maybe go duxed, light it up a little bit.

3:01:08

>> Maybe like high viz high viz like you're on the work site like you know, orange or something. That might be good.

3:01:12

like high viz multicam like like >> I think that could work pretty >> well. Yeah. Yeah.

3:01:17

Bring the construction site into the into the suit the formal suit this holiday season.

3:01:22

Anyway, uh >> uh >> let's kick it off.

3:01:26

>> Half a billion dollars. Huge number.

3:01:28

>> Who'd you raise it from? >> Let's go. >> Yeah.

3:01:30

Uh we led from Valor Equity Partners.

3:01:32

Um Antonio, >> hey, by the way, also sorry I got I'm like swagger jacking you guys in every turn.

3:01:40

Where did you get the gong?

3:01:41

Because again, this is something Bo and I have talked about.

3:01:43

We want to get like a sales gong in the new office. >> Got to get one. We should go to that.

3:01:46

We should make >> We should. Yeah, we Yeah. Yeah.

3:01:49

We'll figure out how to how to send you a gong.

3:01:51

>> I'll buy it for you guys. >> Yeah. Yeah. Yeah. We have a couple.

3:01:52

Uh we we actually become like somewhat of gong experts where we've tested a a number of different gongs.

3:01:59

We've learned that if you don't warm them up, you can break them.

3:02:02

Uh sizes, >> sound quality, >> also the price gets exponentially bigger, like uh exponentially higher.

3:02:08

So going from like a 30-in gong to a 80in gong will like 100x the price.

3:02:14

So you go from like 800 bucks.

3:02:18

>> You're going to need to >> It sounds like it's a good margin for you guys.

3:02:21

>> I know you raised you raised my co-founder who's like you.

3:02:24

>> It's like my my co-founder is probably like the greatest technical mind of a generation.

3:02:27

The like the in-depth conversation he and I got into about the right type of gong that he wants to buy for the LA office. >> Oh yeah. Yeah.

3:02:34

>> So I think we may have to both come back and talk through this with you guys pretty soon. >> Yeah. Yeah.

3:02:37

Anyway, >> we're not here just to talk about gongs.

3:02:40

We're here to talk about you.

3:02:40

Uh can you uh introduce like yourself, the shape of the business, how you're describing it these days? >> Yeah. Yeah.

3:02:46

Uh so first of all, thanks again for having us. Uh yeah.

3:02:48

So founder Chaos Industries.

3:02:52

>> Um so we sort of look at the world in in three waves.

3:02:54

Uh kind of as this sector's grown over the last 20ome years and you know wave one you have Palanteer and SpaceX, wave two of Anderal.

3:03:00

And you know wave three we didn't see like another big multi-product sort of new prime being built.

3:03:06

Um and and that's sort of where that was the sort of initial thesis seeing kind of where the world was going um in terms of especially you know the Russians have been taking advantage uh of of the lack of integrated air defense systems in Ukraine um and they've been attacking energy infrastructure and civilian targets sort of in in an effort to break the will of the of the Ukrainian people.

3:03:29

you know, the the Iranians have been helping them, you know, build their drone capacity.

3:03:32

And so we sort of saw this and and all the while, by the way, the Chinese are watching here um about, you know, what, you know, what's going to h you know, what could happen in in in Taiwan.

3:03:42

So I think we we took it from from the angle of, you know, uh we got worried about the fact that America's losing airsp.

3:03:49

Um, and so we wanted so like the first wave of our products, we we wanted to build get get away from sort of the monolithic legacy structures that were built during the cold war and bring new systems to the war fight and really protect our people downrange.

3:04:03

>> So multi-product interesting it and certainly gotten there but started with a sensor tower and then uh you know anvil like one you know counter us drone system.

3:04:13

uh did you follow a similar path uh knocking down uh single products to get multi-product or did you do like the compound startup thing where you uh on day one were working on multiple products to bring them all together?

3:04:27

>> So we we were so we were the chunk we we're biting off first is sort of in the radar market.

3:04:31

So we got four different radar products. >> Okay.

3:04:33

Now, now there's now, but there is a sort of long tale of of products that we're going to be investing in that >> uh the Department of War has been asking for as well.

3:04:42

And um we'll come back on and talk about some of that stuff in the future with you guys.

3:04:45

But but the goal here is if you're going to do this the right way, you have to be multi-product.

3:04:49

>> How much of what you're doing in radar?

3:04:51

When you say multi-product within radar is uh different radar technologies or the same radar, like the same data output, but this one is waterproof, this one flies, this one goes in the back of a truck. different packages. >> Yeah. Yeah.

3:05:05

I would say like completely different form factors, different technology.

3:05:09

>> Oh, everything >> types of sensing technology.

3:05:10

So, we've kind of like rewritten the book on how it's done.

3:05:13

And I think it's big credit to >> obviously Bo um you know he he knows more about you know weapon systems, radars than you know most people.

3:05:20

He's forgotten more than [laughter] most people will be able to learn in a lifetime.

3:05:26

He's probably the most brilliant technical mind uh I've ever seen.

3:05:30

And so >> why is the old radar not good enough?

3:05:31

Is that because the drones are getting smaller these days?

3:05:35

>> I can't see drones, right?

3:05:35

These are legacy monolithic systems, right?

3:05:36

So, one, manufacturing times are way too long. >> Sure.

3:05:41

>> Two, the form factors are enormous.

3:05:41

So, I think if you look at at Patriot, right?

3:05:44

Like the things the size of a tractor trailer, you'll be lucky to get >> those within two and a half years of of three.

3:05:51

And like look, they do some things really really well.

3:05:52

Like don't get me wrong, >> but these are sort of like monolithic legacy Cold War era built systems.

3:05:56

and and the the reality is the battlefield's changed uh very dramatically and and you need more traitable systems as well as sort of like more expeditionary systems.

3:06:08

Um I think like you guys had my buddy Scott Sanders on this week, right? For Terra.

3:06:13

>> Um so shout out Scotty. Love you.

3:06:15

>> Um but uh you know we partnered with Forera, right?

3:06:17

Forera, right? because like the the the ability to have the these systems be mobile and move around the battlefield and not have your transmit and your receive in the same location I think is you know buys our war fighters so much more time than they would already have >> and I think if you talk to our

3:06:33

>> chief mission officer Chris Musleman you know Mus was >> yeah well he's named [clears throat] Chris Musleman by the way >> half the reason I started by the way half the reason I started trying to get my PRs in the wait room again is because Mus comes and talks to me every day in the office. [laughter] Excuse my

3:06:48

[laughter] Excuse my language.

3:06:49

I don't know if I can curse on here, but but I think you >> for muscle, man. >> Sorry.

3:06:54

But I think Mus would tell you that, you know, 30 seconds is in a trading in a gunfight like we're buying >> exponentially more time. >> Yeah.

3:07:03

>> So that that's really the goal here.

3:07:05

>> Is the US uh Department of War uh happy to buy systems that are maybe influenced by the war in Ukraine?

3:07:12

uh like like are the learnings there translating or or or do the Ukrainians want something that is maybe fundamentally different from the way the US is set up?

3:07:25

>> No, I mean I think I think Ukraine is one of the best test beds out there.

3:07:27

I mean we've had our systems over there for for a long time.

3:07:32

>> Um I think is we we sort of look at this as two-pronged, right?

3:07:34

Because there's a big international component to what we do.

3:07:37

So our international partners all they care about is hey has this been tested on the front lines in Ukraine, right?

3:07:43

And then I think you know if you look at some of the work we've been able to do overseas you know in the Middle East and in Ukraine it is a it is a real key discriminator when we go in it's like we don't have a PowerPoint like we've got data the thing works you know >> take a look at it right and so I think uh it it's it's been a big big help. >> Yeah.

3:08:01

Are you optimistic about the uh the Ukraine war winding down?

3:08:03

It feels like uh it's it's gone on much longer than I expected it to.

3:08:10

It's been this war of attrition.

3:08:12

Um, I've been very hopeful that there'll be just some sort of conclusion. Uh, >> you'd hope so. You'd hope so.

3:08:18

I mean, I think obviously it's just terrible what's been happening over there.

3:08:21

And so, this is why, you know, we want to do our part to help. >> Yeah.

3:08:25

>> Um, but, you know, it doesn't seem like it's ending anytime soon, but again, you know, I'm not a policy maker, so I don't have an asymmetric view into it. >> Yeah.

3:08:33

>> Putin needs to pivot to AI.

3:08:33

He's falling behind in the race for artificial intelligence.

3:08:37

should be focused on building data centers instead of uh >> we're transitioning the you know building tanks into building gongs. >> Yes. Yes. Do something productive. Putin, stop fighting.

3:08:50

>> I still wouldn't buy gongs if he made them though.

3:08:52

I'm only buying from you guys. >> Thank you. Thank you. >> American gongs.

3:08:56

>> Um well well thank you so much for coming on the show.

3:08:57

George you have another question.

3:08:58

>> Great great to meet uh and uh congrats.

3:09:01

>> Congrats on the massive round.

3:09:01

Congrats on all the progress and thank you for everything that you're doing to support.

3:09:06

>> Appreciate it and thank thank you guys.

3:09:07

Hope to uh hope to see you guys in person soon.

3:09:09

>> Yeah, that'd be great.

3:09:10

>> Come on the show for for the next round, whatever whatever letter that is. >> We'll do. Absolutely. Cheers. Thanks. See you soon. Bye.

3:09:17

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3:09:41

I was checking my eight sleep score. I got a 93. Let's go. Let's hear it for me. And we got Reed. Welcome to the show. How you doing >> here? Have a seat. >> Have a seat.

3:09:56

>> While he's sitting down, I'll also tell you about >> bezel. Get bezelled.

3:10:02

that yellow your bezel concier is available now to source you any watch on the planet. Seriously, any watch. >> Quick wrist check. Sorry.

3:10:08

>> You know, I I missed the yellow jacket and pants. >> Yes. Yeah. Ano.

3:10:10

It was It was uh it So, our our lead sponsor RAMP raised a big fundraising round today.

3:10:16

Uh we had the CEO on the show.

3:10:19

>> Fourth fourth round of the year.

3:10:19

We knew they were going to be raising a lot.

3:10:21

So, we decided to get these suits.

3:10:24

>> And when we initially uh Yeah.

3:10:24

When we initially thought of the bit, oh, let's get some yellow suits.

3:10:29

Uh, I sort of assumed that we'd just go and buy like a yellow suit from Target.

3:10:33

Uh, Jordy called our tailor and [laughter] got a very nice tailored yellow suit and I was like, that's that's hilarious.

3:10:39

It was very funny, but we wound up using it a lot. They look great.

3:10:43

>> They look pretty great.

3:10:43

Uh, anyway, please introduce yourself for those who might not know. >> Oh, yeah. My name's Reed.

3:10:46

Uh, founded a company called Night.

3:10:48

You and I have known each other now going on probably like three years.

3:10:51

Um, but we represent the biggest creators on Twitch, YouTube.

3:10:55

It's it's kind of taken on a life of its own now.

3:10:57

I'd say we're like the the idea at the beginning was like be the internet's management company.

3:11:00

That's kind of transitioned to like be the internet's media company.

3:11:04

And so we bought a podcast network from Warner Brothers called The Roost.

3:11:06