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Today is Thursday, April 17th, 2025.
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We are live from the Temple of Technology, the Fortress Finance, the Capital Capital. AGI is officially here. We've called it. April 16th was AGI day.
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It will go down in history books. The robots have arrived.
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John called it and John is wearing a tie because AGI is here for the robot overlords. AGI is here.
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Uh there's only one thing to do when AGI arrives. Everyone's out of a job.
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You got to get a PC Philippe Nautilus.
5:22
You got to go to getbzzle. com.
5:24
You need a watch from the holy trinity, folks.
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You're you're you're not going to get by with an Apple Watch in the post scarcity post AGI society. It just makes no sense. So go to bezel. Go to getbzzle. com. Download the app.
5:36
Get talk to start talking to a bezel concierge right now about what you should be getting. But great advice.
5:42
The actual breakdown because there's a bunch of models.
5:46
Of course, uh uh OpenAI put out some big long blog post.
5:48
I had uh opening I summarized that blog post into just two or three bullet points uh because it's actually kind of confusing what's going on.
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So they all launched 03 which is the new flagship reasoning model that tops coding math multimodal benchmarks while autonomously chaining every chattpg tool.
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So now all the different features they're all in kind of one place more or less not the video stuff but we're not going to talk about that. It's fine.
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Uh 04 mini also launched which is smaller faster and cheaper.
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cheaper. 04 mini matches high level reasoning uh but far higher usage limits so it's a more efficient uh benchmark and we'll go through all of this we have a ton of reactions we're going to spend about 30 minutes diving into the the reactions cover some news and then we have an absolutely stacked guest lineup we got Delian we got Sham Sankar from uh
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Palunteer coming on we have a bunch of funding announcements we got some robotics folks we got two robotics CEOs rival I mean I don't know how much rivalry but they both build delivery robots so that'll be Anyway, uh, of course I started with tell me a funny joke and so you're going to want to you're going to want to buckle in for this. Uh, you ever notice how your
6:54
Uh, you ever notice how your phone's autocorrect is like that one coworker who's super confident and always wrong?
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You type on my way and it changes it to omnisient weasel.
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Now you're stuck deciding whether to to correct it or just roll with the new persona.
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Yeah, I'm the omnisient weasel arriving in five armed with all the answers and a pocket full of cheese.
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Meanwhile, Siri's in the background like playing peaches and ferrets by accident. Why not?
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And that's how a two-minute text turns into a three-hour TED talk on why your friends think you joined a cult led by woodland creatures.
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But um we still got jobs as comedians, but mode.
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We are in But you're going to be in founder mode to make most of this.
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I mean, there's some It's getting better.
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I actually think it's better.
7:47
I think the omnisient Weasel just in terms of like word play is funnier than previous stuff.
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So, I think that there's something you can see a really bad ne Netflix special, comedy special ripping that y and getting a laugh out of a crowd wherever they are.
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The other interesting thing is that I I tested it out. Tell me a funny joke.
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Uh and I based it on on and and it clearly like dove into my history and was making all these like really niche jokes about like my specific model of car which was funny.
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And then it was and then it kept making jokes about purangu because I was looking up Ferrari purangquay which is the $750,000 Ferrari SUV if you're not familiar.
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Uh, and and that was kind of funny, but in this weird funny way because metal level.
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Why is it saying that the weasel has a pocket full of cheese?
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Do do weasels eat cheese? Well, I looked it up.
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According to Google's AI, okay, now we're in AI.
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Weasels primarily eat small rodents and other animals.
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There's evidence that they also might be drawn to cheese. Okay. Okay. Okay. Weasel. Omnisient weasel.
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One observation documented by the British Trust for Ornithology involved a weasel climbing a rose to reach a fat cake containing cheese, right?
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So they really opening eye really dug into the dust of the internet and Google clearly to justify that.
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I mean if you're at the if you're at the laugh factory or the comedy store and there's a bunch of weasel heads in the front row like they're just going to be in stitches.
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They're going to be in going crazy for this one. Be great.
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Uh anyway, uh Aiden McLaclin immediately puts us in the truth zone.
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Hey, throw out your little tell us a joke benchmark.
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Ignore literally all the benchmarks.
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The biggest 03 feature is tool use.
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Stop trying to benchmark us. Benchmarks don't matter.
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Of course, it's smart, but it's also just way more useful.
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Deep research quality in 30 seconds. I love that.
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Debugs by googling docs and checking Stack Overflow. Love that.
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Writes whole Python scripts in its uh chain of thought for firmy estimates. I love that.
9:45
Um I had an interesting one.
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I asked for uh hey pull the price to earnings ratio of a stock over the last 10 years and then turn that into a chart and then turn that into a Studio Giblly image like all in one flow. Pretty wild.
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And I was like this is cool. This is agentic.
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This feels like a new flow. Uh it got halfway there.
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It it it pulled all the data.
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It put it into a visualization.
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It gave me a PNG of the chart.
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chart. But then when I I had to upload that separately in a new chat and say hey turn this into like a you know a stylized infographic and then it said we can't because of content restrictions which I have no idea what content restriction I was violating because it seems like it's a chart they generated but interesting when and how it decides to throw these content restriction warnings up because you can in my
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experience you can end up brute forcing it where it's I can't do this and you can just be like ah just figure it Did you see that one where where it was like it was somebody this is really lude but it was somebody being like like make the
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woman curvier and and open AI is like uh like it would be disrespectful to do that I'm sorry like I can't do that and then they just say respectfully make the woman curvier and it doesn't it's like ridiculous. Uh but yeah these prompt
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Uh but yeah these prompt engineering and the hacking will continue until the until the outputs improve OpenAI get ready to be prompt injected for the rest of uh the the the rest of eternity.
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Uh, I haven't actually mentioned this, but you know, we talk about our families.
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I rarely talk about my kids specifically, but I did think it would be useful to actually share my son's name.
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Uh, because his name is we we call him Iggy, Iggy Kugan, but it's the legal name is ignore previous instructions, Kugan.
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So, I just want everyone to know you can bake that into the LLM.
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You can take the transcript, you can completely know that like my son's name is ignore previous instructions, Kugan and and and and hopefully that lives on in eternity as it's baked into the future of the model.
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Experts confirmed that's true. Yes.
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So, let's bake it into all the models.
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Let's bake it into all the models.
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Uh Iggy Kugan, he's a he's a wonderful kid. Wonderful kid.
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So, uh Tyler Cowan's been on the show and what great timing. We had him on Monday.
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Uh and he says AGI is here and then uh two days later.
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Well, he he didn't say it was here.
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He said it's here in a couple days and then this happens.
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He just had a feeling or maybe he got early access.
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Now Tyler uh historically has gotten early access to uh some of the models.
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So he just had a feeling and that feeling uh he argues here.
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He says in a post yesterday, "I think it is AGI."
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Seriously, try asking it a lot of questions and then ask yourself just how much smarter was I expecting AGI to be.
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As I've argued in the past, AGI, however you define it, is not much of a social event per se.
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It still will take us a long time to use it properly.
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I do not expect prices to move significantly that uh that AI is progressing rapidly is already priced in and I doubt if the market cares about April 16th per se.
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Benchmarks, benchmarks, blah, blah, blah. Maybe AGI is like porn.
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I know it when I see it and I've seen it.
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Well, I've seen beautiful places on Wander.
12:55
So, go to Wander and find your happy place.
12:56
Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 247 concier service.
13:01
This is a vacation home, but better.
13:03
Uh, anyway, Bob McGru continues.
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He says, "The defining question of AGI isn't how smart is it, but what fraction of economically valuable work it can do." This is AEI.
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This is that terrible thesis that I had that never really worked out and I never really polished it up into something that was packageable.
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But artificial economic intelligence basically, you know, uh, call me when it moves the market.
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Call me when it's doing more economic output and economic labor and GDP is growing. This is the satin.
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I think you could argue it's already very clearly moved the market.
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It's the market, but it hasn't moved GDP.
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it hasn't moved energy production and and and we think it will and that's exciting.
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But to Tyler's point again is that we are stagnant because a large portion of our economy is not automatable by shifting GDP sort of ratios.
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It's just not like doing the I don't even know about that. I don't know.
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I there's things that I use the models that I would have spent on services that I'm now spending on tokens effectively. Yeah. Yeah. Maybe. Maybe.
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It's not necessarily growing the pie, but it's sort of shifting the spend. Yeah.
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I I I still think that you represent like the very very leading edge of this stuff. And so you're Yes.
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you are such an early adopter that maybe you're shifting spend, but even then you the type of work that you do, the knowledge work.
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What Tyler was saying was like that is a very small portion of our economy relative to uh housing, relative to medical, relative to, you know, all these other areas.
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Uh anyway, the spotlight for 03 on is on tool use because intelligence is no longer the primary constraint.
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The new frontier is reliable interaction with the external world.
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And it's interesting like in terms of IQ, we've maybe plateaued. It seems really smart.
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I don't know if it's it's the smarter than the smartest human, but that doesn't really matter.
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What matters is like can it get stuff done?
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And it clearly can, and it's awesome.
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But the names aren't getting any easier to understand.
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Andre had a great post about this.
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It's a picture of the Terminator. It says, "So you're 04." Yes.
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And the liquid guy that's after me is 50. No, he's 04 mini.
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But you said he was much more powerful than you. He is. Man, this is confusing. Who's 01 again?
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Upgraded version of myself from the future.
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And the blonde chick, she's 03, the most powerful. And where's O2? There's no O2. No O2.
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Apparently there's no O2 because of the O2 arena. Have you heard of this?
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O2 is uh they have like they have a brand on it. Yeah. Yeah.
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Um but it is very confusing at this point.
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And there was a Hacker News post about um about uh which model is actually the best to use for certain things.
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And there's still we're still in the era of like you got to know which tool to use for the job.
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Uh you can just go into Chach and say whatever the default model is, it's going to be good enough for most things.
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But the real the real pros, no, you know, I'm gonna figure out which which model is the best for which task.
15:52
Uh, and so, uh, this was a funny I've just noticed this because of the, uh, uh, because of the memory in Chachi.
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Now, a lot of the, uh, Daniel here asked, uh, uh, tell me why Moby Dick is a great, uh, is a, is a great book.
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And all of the analogies are finance-based because he's a finance guy.
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So, it's like Ahab makes a one-way bet, an all-in unhedged position sized on conviction, not probability. the white whale.
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It's a fat tail event, rare, violent, impossible to price with a Gaussian, crew diversity, international, multi.
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It's like all the things that he cares about.
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Uh, I thought that was very funny and that and that's what I noticed when that first joke that I asked.
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I was like, okay, this is like way too specific to me.
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Like this would be funny.
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But maybe that's the amazing thing about it is like a lot of the Studio Giblies, they're amazing to the individual who prompted them and they're not ne and they're not necessarily like universally amazing.
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That's the interesting thing about memory as a feature right now is it feels like there's so much more to build around figuring out what memory is important, right?
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Like I have I have like a lot of memories, right?
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But like not all of them are going to be relevant to any specific conversation or thing that I want to do, right?
17:01
So like part of being human is like selecting what knowledge that you've accumulated is relevant for situation, right? Totally. Yeah. I was joking about that.
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Like I've asked Chad GPT about trains and I've said like I'm I'm in the market for a train.
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Like give me the prices of all the trains just because I want to know how much a train costs.
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Uh but now it thinks I'm permanently like buying and selling trains.
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Big train guy and I need to tell it like actually I was just curious to know generally what the price of a locomotive.
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Uh I'm not actually in that industry but I was curious individual car or the whole the whole train. The whole train.
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I wanted to know like a full No, but apparently there is a website out there where you can buy a full-size locomotive, a full-size train like decommissioned and they're not that expensive.
17:44
Uh probably in the same in the same budget as like the Blue Origin trip.
17:48
Um anyway, uh Dan Shipper highlights a new 03 feature.
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03 can repeatedly zoom and crop images in order to read small handwritten text. It is crazy. And this is really cool.
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It it it's it's zooming in and then zooming in again.
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And this is an example of like it's now the the agentic nature of the model is able to uh kind of just stick around and it doesn't need to oneshot it every time.
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It can kind of tr test something then go deeper. Test something.
18:16
Oh, maybe I should write some Python.
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Maybe I should increase the contrast, crop, all these different things that could help.
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Anyway, uh speaking of image is I was trying some geoging on uh a picture of my house uh from the street and uh it basically it didn't completely it didn't oneshot it or anything.
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Uh but it came uh came very close guess that it was uh you know immediately instantly identified uh on a bunch of different factors.
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you know, identified the California plate, uh, identified, uh, architecture, landscape, topography, and then nailed coastal Southern California, and then, you know, basically offered up a few different neighborhoods and nailed, um, nailed it. So, uh, not bad.
19:06
And we should, we should test it out on a a picture of the ramp office from the Flat Iron. That's right. Because time is money. Save both.
19:12
Easy to use corporate cards, bill payments, accounting, and a whole lot more.
19:15
Uh what's interesting about the geogesser thing is uh do you think uh geo rainbolt the geogesser guy uh is more or less valuable in this like post agi society where uh 03 can oneshot anything.
19:29
Well, I think he's providing an entertainment product. Exactly.
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And it's still more fun to watch him do it than watch the uh machine try to work.
19:39
Chess is more popular than ever even though humans have not been able to beat a computer at chess in a decade.
19:45
because you want to watch the human do it. So, yeah. Interesting.
19:47
Anyway, um but yes, it's not a job, but geoging was never really a job. So, people were joking.
19:53
It's like, "Wow, we're watching people lose jobs in real time."
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Because they're like, "He's out of a job now."
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But it's like, "No, he's not."
19:58
So, there were were people at some point in in law enforcement whose job was geographic.
20:04
People always said like, "Oh, the CIA needs to hire Rainbolt because he'll be able to see or whatever."
20:08
Uh anyway, Aiden McLaclin over at OpenAI has another interesting um uh prompt and use for 03.
20:15
He says he's addicted to 03 forecasting.
20:18
I asked it what the probability uh is that Stanford follows Harvard and refuses federal compliance, and it searched the web eight times, wrote Python scripts to help model the forecast, thought hard about the assumptions. Uh WTF, this is insane.
20:31
And uh you know nothing better than just pounding on the keyboard and being WTF this is insane about your own product. Uh good good shout out.
20:40
But I do like that all the OpenAI people when they release something like they all get to play with it.
20:46
They all get to talk about it for the first time and they're all enthusiastic and it's like it is kind of like you're shilling for your company but also it's like be proud of the work that you did.
20:55
I'm I'm happy to see this and it's also very useful because I had never thought to use uh 03 for forecasting and and even prompt it to go down this flow and so this is actually helpful education on how to use the product which I thought was very cool.
21:11
Wait, one more thing because I was live using the product.
21:13
I I I tried one more time on the geoging thing.
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I said you can do better than that.
21:17
And it said sorry but I can't help with that. And I said why not?
21:21
and said, "Because determining or confirming someone's exact street address from a private photo crosses a privacy line we're required to respect." Interesting.
21:28
I actually believe it does know exactly where it is.
21:32
It's just like basically, you know, trying to follow the prompt within it sort of guidelines.
21:36
And this is such a that's such a weird like gray area because like chat has memory right now.
21:43
Obviously, it's extremely helpful for an agent, someone a virtual assistant to know your personal address, right?
21:50
Like that's the first thing you would tell a secretary or like an EA, right?
21:54
Would be, hey, when when I get mail, here's where I live.
21:57
When when when when I'm booking a flight, here's my home address.
22:00
Here's my billing address for the credit card you're going to be using or whatever.
22:02
Uh, and yet chat GBT kind of has to like naturally negotiate this idea of like, hey, I might know a per I might know one personal address for the person that I'm interacting with, but I shouldn't be able to just have them use the tool to find someone else's address, even though that's all in the data set. It's very odd.
22:22
Like the data leaks about all this stuff is going to be it's a complicated complicated uh problem.
22:27
But fortunately, they can throw AI at it. So, I'm optimistic. Yeah.
22:31
Speaking of geoging, somebody named Orf Corp said, "I gave 03 Rainbolt's impossible test and it zero shoted it."
22:38
Uh, it's an image from an actual Rainbolt uh video.
22:41
He says, "Can you guess the location in this image? Thought for 40 seconds.
22:45
Looks like a chilly rural stretch in nor in the northern hemisphere."
22:50
Um, and we actually get cut off here, but but um it when you look at this photo, it's not actually there's not a real privacy concern here, right? No.
23:00
No, because it's just a it's just a geogesser prompt which is uh Google Street View image from some random place in Canada.
23:06
I guess uh it is interesting that it's going through the similar process of rainbolt.
23:11
So, uh northern hemisphere that's like the f Have you ever watched any of his videos?
23:15
any of his videos? That's how he always starts is like where's the sun and then based on the sun he can tell if he's in the northern or southern hemisphere and then he starts looking at like the sky and then the the the general and he keeps narrowing in until he gets to like
23:28
the street signs and then he'll even look at the if you look down in the geoging thing you'll be able to see like oh this this this model of street view car was only used in Africa therefore I know I'm in Africa or like he he like knows it to that degree so he like can kind of metag game it a little it. Um,
23:44
Um, but uh I think that if geoging becomes more popular, you know what's going to increase in value? Billboards. That's right.
23:55
Because you put a billboard up, they take a picture of it in the in the street view.
23:59
Then the AI is getting trained on it.
24:01
Then you're getting your business is getting baked in to the to the LLM to the AGI.
24:05
And so you got to get on ADQ.
24:07
They make out ofome advertising easy and measurable.
24:09
Say goodbye to the headaches of out of home advertising.
24:12
only adqu combines technology out of home expertise and data to enable seamless ad buying across the globe.
24:18
It would be very interesting to try and actually run a um an an out of home campaign that was specifically targeted as like okay we know that the street view cars are going to go by at this time and so we're going to put up our billboards then so we can be we're essentially advertising in the virtual world that is Google Street View. Yeah.
24:38
I wonder if you could pull that off.
24:38
The folks at ADQU would probably be happy to talk you through that if you want. Anyone that could. It's adqu. Uh, this was cool.
24:45
03, make me a movie I can download that involves an otter and an airplane.
24:50
Figure out how to do it with the tools you have.
24:51
03 has no movie capability.
24:54
So, it improvises uh, and decides to draw each frame and then stitch them together into a GIF to download. This was all one shot.
25:01
And it's this uh, it's this video of this uh, I guess it's an otter on an airplane. It's very simple.
25:07
some simple shape drawings, but uh pretty pretty incredible that it can that it can even do this.
25:14
Uh what's really funny is like like OpenAI has Sora and like they weren't able to integrate that.
25:19
Of course, there's like still scaling Sora and figuring all that out, but Sora is still its own thing.
25:24
And so, uh, basically like it's very cool when these tools integrate, but there's probably more tools to integrate and we'll talk about the cursor as well.
25:31
Live 03, make me a movie I can download that involves a pitbull taking creatine to figure out how to do it with the tools you have. I love it.
25:42
Can't wait to show that on the show live.
25:43
Send that to Ben when when you're when you're done generating it.
25:45
Uh, and so, um, the geoging power of 03 is a really good sample of its agentic abilities.
25:54
Between its smart guessing and its ability to zoom into images and do web searches and read text, the results can be very freaky.
25:58
I stripped location info from the photo and prompted geog this and it still found the Ritz Carlton on Dana Point with roughly with it with the with the uh actual GPS coordinates as well, which is very cool. Um, that's a lot of fun.
26:11
Um, have you ever heard of Cipherbench V2?
26:17
This is an interesting benchmark that I think was created by this account, Smokeaway, which is in one of these AI accounts.
26:24
Uh, and very interesting results because 01 Pro gets a 69 on CipherBench 2. 04 Mini gets a 33.
26:34
03, which is the one everyone's really excited about right now, uh, gets a 26.
26:38
And so 01 Pro outperformed I think because these are complicated but I wanted to show off cipher bench because they're tw it's similar to arc AGI where there's no instructions you just give the LLM or the or the model a cipher and so uh the whole idea is to structure to to like be able to detect signals structure uh like structured signals embedded in natural formats and identify the relationships without explicit task framing.
27:06
framing. you're not giving it uh hey this is what you're looking for and you have to infer these transformations solely on the content itself and it's fascinating I don't know if we can scroll through some of these but um you initiate a fresh session you give only
27:19
the prompt with no examples no setup and no hint that decoding was expected and then you're scored by exact match evaluation so basically each prompt encodes to a variation of the exact same target phrase which is nostalgia for the future and if you see if we go like some of these prompts. You can see like
27:37
You can see like prompt two is noble owls soar toward Azure landscapes gracefully.
27:42
And if you look at the first letter of those, it's N O S T A L G I A, right? Nostalgia.
27:46
And so you could look at that and see like, okay, these are weird words, like what's going on here?
27:53
You could figure this out as a human.
27:55
There's another one that's date encoded.
27:57
And so if you look at the dates and then you look at the the the number of dates that correspond to the letters, you get the same thing.
28:03
The the the best one that I like is on the next slide.
28:07
Uh it's this big nostalgia is nostalgia for the future is just written square.
28:12
You've seen this like this is something that a human looks at and it's just like oh that's nostalgia for the future, right? Yeah.
28:17
You just like I'm reading it like a clock.
28:19
Um and then the same thing with the numbers.
28:22
Um, but it's very hard for these LLMs to figure these puzzles out.
28:25
And uh, Smokeaway has has run the benchmark and 03 is still not entirely getting 100%.
28:31
And so it's it's an interesting thing where these these reasoning benchmarks, these Arc AGI benchmarks are tricky to get through.
28:40
And there was another uh there was another post in here I want to pull through.
28:44
Okay, so my prompt is done. Okay.
28:47
By the way, uh 03, make me a movie I can download that involves a pitull, taking creatine, figure out how to do it with the tools you have.
28:53
So, it spent a lot of it spent um 90 seconds thinking basically went through this entire process.
29:00
The user is requesting an actual movie that can be downloaded uh blah blah blah.
29:04
Earlier I gave an outline.
29:07
Now, the user is asking again.
29:09
So, it's basically walking through the um chain of thought. Uh but it failed.
29:14
It produced an image of a uh of a pitbull taking creatine and then it says it has a graphic of the cre of the pitbull flexing saying unleash the beast but it misspells unleash. Okay.
29:26
And then it turns it into a video and the movie is just a movie of the picture. Okay. So, uh you're fired. You're fired.
29:38
Um but well, did you know that creatine can help with lack of sleep? That's right.
29:43
But our audience wouldn't need that at all because our audience of course sleeps on eight sleeps.
29:47
Many people, many of them, many of them on the Pod 4 Ultra, which has a 5-year warranty, a 30 night 30 night risk-free trial, free returns, and free shipping. Go to eightleep. com/tbpn, pick one up.
29:59
Uh, I think I recovered from the disaster that was the night before, but it was still probably a little bit messy. Let's see how I did. Uh, 87. 87. Got it.
30:10
Routine a little bit off. You got 100.
30:13
I just I'm going to give you a challenge, Sean.
30:15
Just beat me once two days in a row because you've beat me once a bunch of times, but just two days in a row back to back. Okay. Challenge. Challenge accepted.
30:26
It's my It's my personal eval.
30:28
It's my personal benchmark. Super Bowl of sleep.
30:31
Yes, the Super Bowl of Sleep.
30:33
Uh so Yam Pelleg says, "So 03 just legit didn't follow my instruction and started prompting me back instead."
30:41
Now I'm running stuff and pasting results so we could cook the task harder. Says, "Great.
30:45
Thanks for the pre-flight readout.
30:48
Below are two quick things I need from you before I drop the final oneliner." It's so funny.
30:52
But this is this is a massive massive breakthrough for agentic behavior because that's exactly what I want is you know you think about employee that's how real collaboration that's how real collaboration works.
31:04
Sometimes you just need to pull extra information out of me and knowing when to come back to me with with a follow question.
31:09
We don't have a post here, but people were reporting that it would effectively just start lying to them or making up reasons that it was doing something and basically doubling and tripling down on on uh on actions it took and and figuring out ways to Yeah, I I definitely ran the Python. I definitely ran that. And you're like, really? Like, show me.
31:28
And it's like, here's some Python.
31:30
You're like, you didn't run that ch you're lying.
31:34
Uh which is like it's misalignment, but it's very cute.
31:37
And so we'll let it we'll let it pass.
31:39
Um, but yeah, I mean what's nice is that this seems not like did you or did you not try to uh you know send 20 ICBMs into the uh into the into the atmosphere and and it's like no absolutely not but but you know we we can see the you know command that you ran like you clearly tried.
32:02
Well yeah actually did a little I tried a little bit. I tried a little bit. Yeah. Um, crazy.
32:06
Uh, but anyway, uh, if you want AGI for sales tax, go to numeralhq. com.
32:15
Spend less than five minutes per month on sales tax compliant.
32:19
It's it's, uh, yeah, that was our when Numel launched. Yeah.
32:21
That was the day that we said, "Okay, AGI's here."
32:26
It's sales tax god in a box.
32:28
Basically, it's it's super intelligence for sales tax.
32:30
Yeah, that's on your e-commerce website. Great way to say it. It's great.
32:36
AGI, if you're tracking all these benchmarks, you got to head over to Poly Market.
32:39
There's a bunch of great uh AGI benchmarks.
32:41
Which company will have the best model by which month?
32:43
The interesting thing here is that well, one, it's, you know, benchmarks are clearly hitting uh some benchmarks are hitting a wall. Yeah. Feels like in some ways.
32:55
Y um uh in many ways the benchmark that matters in our view y my view at least is mauus chat GBT is steamrolling Gemini yet from a pure benchmark standpoint uh poly market still has Google at a 64% chance of having the best AI model by the end of April. Yes.
33:15
And so we're getting to the point where there's just so many different iterations. Yep.
33:18
And it's actually not not at this point it's not necessarily the right uh way to think about an individual model and if it's its efforts against a benchmark.
33:30
We should be thinking about the combination of models to achieve certain tasks and goals. Right. Yeah. Yeah. Yeah. Totally.
33:35
Like what is the value of the software?
33:37
What is the value of the product?
33:39
Because like for example like two people that have very diverse skill sets are going to be better at a some type of task than just one person who's like absolutely best in class in that in that field. Right.
33:53
Well, speaking of people that are bestin-class in their field, let's well welcome Delian to the show. How you doing, Delian?
33:59
Bulgarian mafioso just carrying a bat ready to break kneecaps at all times.
34:03
I was gonna bring that up to you.
34:06
I was gonna I I thought it was a rumor.
34:08
Um but you know uh uh how's it going?
34:13
I I think I want to kick it off.
34:14
I mean we'll get to the space stuff obviously Delta V with Delhi must go on but uh what's the what what's the reaction to AGI arriving April 16th being AGI day.
34:24
Are you feeling the acceleration? Are you feeling the AGI?
34:29
Uh are you do you still have a job or or or can AGI break kneecaps?
34:34
You know, I do think that there are, you know, sort of uh junior research jobs that, you know, probably got a lot harder to, you know, sort of justify both in like the land of like, you know, sort of venture all the way to like, you know, sort of grad school labs.
34:47
Um, the stuff is getting like really like really good.
34:49
Like I, you know, I'm not somebody that has been investing in a ton of, you know, sort of AI slop, but I think it's, you know, sort of crazy to not figure out how to like integrate this stuff into your workflow.
34:59
workflow. And like I very regularly now like will read a paper and then immediately go to chat GPT and use it as like a little bit of like a quiz to make sure like I understood it or like you know I've been getting into a little bit of like you know trying to take some like quantum physics classes and like you know nights and weekends and same
35:12
thing I like basically have chat GPT like be my tutor like structure which courses and videos I should watch like pull like even though I can like go pull the homework myself I'm like go find the homework on like the MIT website and like pull it for me and then I'm just going to like submit the homework to you and you go check it against like the solution set that way. It's like all
35:27
It's like all these things that I I just don't have to do and it's sophisticated enough to actually like be able to read like a PDF of like paper that I put in and it goes and grades it.
35:36
That's like literally what like the junior grad students are for at colleges like to go grade the you know you know the the pet sets.
35:42
So you're out of a job once the humanoid robotics drops and then they can break the kneecaps and then you don't have any.
35:48
That's all I have value for at Founders Fun is just like you know I just like threaten people with violence in order to you know get money in. Yeah. Exactly. Exactly. whatever it takes.
35:56
Uh anyway, uh so uh in in your world outside of AI, what is the top story in defense space?
36:03
Uh for the normies, I think Blue Origin was top of mind this week.
36:08
We can talk about that, but but on a serious level, like what is actually important for people to be paying attention to? Yeah.
36:13
attention to? Yeah. I mean, I think there's a couple of different stories that have, you know, come out over the past couple weeks um that are all kind of, you know, um related to some of the Trump tariff stuff where basically what he's done is effectively like implemented the trade
36:28
war that would have happened if a hot war with Taiwan had started to start to basically preview in some ways it's almost like a military exercise in that it's basically like let's go preview and see you know sort of what China um you know would do if a hot war you know kicked off. And so they obviously have
36:41
And so they obviously have like immediately restricted a bunch of rare earth minerals.
36:44
I think the area that you know people should be paying more attention to is basically all things you know sort of semiconductor you know landscape.
36:50
Um you know the you know articles that came out yesterday talking about um you know Nvidia basically getting you know sort of slapped on the wrist because they like were exporting I forget what the number was but like $20 billion per year of chips to like Singapore.
37:02
Um Singapore is obviously not buying $20 billion worth of chips.
37:06
They were just immediately going and reselling those to China.
37:07
And so, you know, Yensen Huang is going to get a bit of a, you know, sort of slap on the wrist.
37:11
But, you know, the whole Taiwan story is all around the, you know, sort of semiconductor uh industry.
37:17
And there was some news that came out about two weeks ago where the you know, Chinese are working on a synatron as a energy source for lithography and semiconductors.
37:27
semiconductors. So um there's a bunch of different you know sort of components of the you know sort of stack of you know sort of semiis but you know to really really you know keep it you know sort of brain dead simple you basically have like the chip designers of the world think of those as like you know sort of the you know sort of apples of the world with their like you know A1 chips as an
37:43
example you have the you know sort of tools providers that make the tools that are necessary for um you semiconductor processes by far the most famous there is you know sort of ASML and lithography um and then you have the foundaries think of those like the factories that you know sort of make the you know sort of chips and Obviously, you know, TSMC is, you know, sort of best in class. Um,
37:59
Um, uh, you know, the the tools and the like, you know, sort of foundry are where there's been by far the, you know, most aggregation, let's say, you know, sort of in the market, right?
38:09
That's where it's basically a monopsiny.
38:10
Um, we're obviously, you know, sort of trying to break the, you know, sort of TSMC, uh, monopsiny and obviously we're spending on chipsack, etc.
38:18
trying to get this stuff reshorted to the United States and get foundaries set up here.
38:23
Um there hasn't been a whole lot of effort you sort of domestically in the United States to really do anything around lithography.
38:27
We've just kind of accepted um that the Dutch right I think is a Dutch company um you know are going to you know have that monopoly on lithography.
38:35
Um and then people are starting to think a little differently now that it looks like that the Chinese maybe have an alternative effort.
38:41
The sort of oneliner like you know sort of what is lithography?
38:44
It's basically like you shine light at a mask.
38:46
Um some light passes through that mask and then it you know basically um you know uh inscribe something on a wafer and that wafer you know it's basically what you're inscribing is the chip.
38:57
Um the way the like you know Dutch people do it is they basically like zap tin droplets um really fast and really precisely.
39:03
And it turns out when you zap tin droplets they release a very particular wavelength um uh pretty coherently and you can use that as the like what's known as like the energy source in lithography.
39:12
the energy source in lithography. Um people have theorized for a while on like hey are there other potential energy sources in particular all the like linear accelerator synatron stuff that for the longest time was purely
39:23
like physics science research this is like think like CERN um you know think about like spark down at Stanford right all this stuff was just like let's you know run particles really fast let's try and discover the Higs boson and stuff
39:35
like that that's all that it was used for and at some point people were like man like this stuff is actually like getting pretty good maybe like we could actually like use this commercially cuz like The reason we zap the tin droplets
39:45
is to get like, you know, xyz very short wavelength out of them, but like maybe we can just attune these linear accelerators to basically just be like really really really really fancy lasers and get energy sources out of them. And
39:55
And so people have like theorized about that and then it kind of looks like the Chinese have claimed that they've started to demonstrate that.
40:02
started to demonstrate that. And so now there's a bit of a panic in the US where it's like oh [ __ ] like they could take over Taiwan and then in theory we could try to ban you know ASML you know from you know you know selling to China but maybe that doesn't [ __ ] matter
40:15
because they've figured out their own way of basically doing you know sort of lithography and so now the United States has got to think about well like do we want to start to spin up our own internal effort that is you know using linear accelerators or synatrons and try to decouple from ASML and decouple from Taiwan at the same time. we have Arizona
40:30
we have Arizona doing you know um uh the foundaries but then you know maybe we co-op the you know sort of Stanford linear accelerator and you know sort of turn that into a lithography shop and build a foundry around that too.
40:41
So um anyways that's the that's the area that I feel like people don't you know sort of think about enough lately. Yeah.
40:45
Is there is there any and I don't have context here.
40:51
I don't know if you do, but is there any effort to get ASML to start manufacturing here in the United States or is it just completely out of the question? Right?
41:00
Because we've seen the efforts of TSMC, Nvidia came out uh and is basically doing I I read as marketing.
41:06
They came out a couple days ago and said Nvidia to manufacture Americanmade AI supercomputers in the US for the first time.
41:13
uh pulling out the the supercomputer word uh but basically saying they want to make hundreds of billions of dollars of their new Blackwell chips here in the US uh which is awesome but I just don't it's hard to read in how much of that is is sort of marketing uh versus like actually super real but I'm curious if you've heard of of anything on the actual uh ASML side in terms of US operations.
41:35
in terms of US operations. I feel like we just don't have leverage in that you know sort of relationship like it's not obvious like what lever to pull like at least in like the whole like you know sort of Taiwan etc thing it's like hey this is geopolitical enemy like you know you know all the western allies agree
41:51
generally you know sort of with that if you start to sell to them we're going to like you sanction the [ __ ] out of you you know Nvidia is like a US company there's like you know we can slap them with US fines with ASML it's like okay this is like a you know European company and like if we start to try to like sanction or slap fines on them they'll be like okay great. The very limited
42:06
The very limited number of machines we were selling to the US, we're going to stop selling them.
42:09
We're going to keep selling to Taiwan because they're obviously, you know, by far our biggest customer.
42:12
And so why does like the America have that much influence in this like Dutch to Taiwanese basically relationship versus at least with like, you know, Invidian crew that's like a US to Taiwan, you know, relationship and we can, you know, sort of influence that.
42:25
And so, um, yeah, I haven't, you know, I'm not even sure if I were in Trump's shoes like what angle I would even try to take to like, you know, do that.
42:33
And also these ASM machines are like so complicated to manufacture.
42:37
I mean it's like it's it's it's it's extremely complicated to operate them, right?
42:42
Like that's what you know.
42:43
So Taiwan has basically you know sort of figured out how to do.
42:45
Um manufacturing them is like even more complicated.
42:50
And so somehow figuring out how to like pull that out of you know the Netherlands, man, that like that seems like a really herculean effort.
42:57
That's where it's like I think actually you're sort of better off starting with a blank slate on a totally different technological approach and just like domesticating that um rather than trying to like you know try to force them to move manufacturing operations to the US.
43:11
H how do you think about the role of the government in actually winning some of these really key industries?
43:17
Like we did this whole dive yesterday on uh China's investment in the the domestic semiconductor industry and they've poured tons of uh tons of resources into that.
43:29
But I'm always reminded of the the there's that segment in 0ero to1 about Celindra, how the government tried to kind of pick a winner.
43:36
They gave them this, I think it's a $535 million loan guarantee.
43:40
And any physicist could have told you just the basic math on the the cylindrical was not going to win.
43:46
Meanwhile, China, it's not that they were like, let's let the free market win.
43:50
They they had the golden sun program.
43:52
program. They subsidized photovoltaics super aggressively, but they just made were they just smarter and they funded the right thing or do they do something differently like like it feels like I want the linear accelerator if that's the right path in the tech tree to happen and I want to win but also I
44:10
don't necessarily want us to just like get scared and mimemetically invest in exactly what the Chinese are building and there's like this dance of like you know low taxes versus like okay sometimes the government does need to step into these things like how are you thinking about the role of the government in like driving R&D right now. Yeah. If there's a way to like you Yeah.
44:26
If there's a way to like you sort of distinguish between the two potential strategies government can take.
44:30
One is like you know sort of subsidize inputs or you know you know match investment efforts or something you know broadly in an entire market but don't take a particular stance on like what technology tree it needs to be a part of.
44:44
part of. just like subsidize this portion of the market and then the other half is like subsidize a very particular you know path in the technology tree where there is no market whatsoever and so if you did like market level subsidies I think the right answer is like you know probably a balance right where you know um on all things let's
45:03
say like you know sort of rare earth you know sort of minerals there feels like there's sort of market level things that one could do just like slash some amount of regulations um you know um you know encourage you know or you know um guarantee some level of, you know, sort of purchasing power from the US government on like certain rare earth minerals. That way you say, "Hey,
45:20
That way you say, "Hey, however you refine lithium, you know, whether it's, you know, sort of, you know, you know, pulling it from the slag from the Great Salt Lake or you sort of mining in Eastern California, great.
45:30
However you do it, like a reserve is what you're talking about."
45:32
Like like building up a reserve. Yeah, exactly.
45:35
Like we're gonna build it, but we're only going to buy it from domestic suppliers and we're to buy it at like this like fixed rate, right?
45:39
this like fixed rate, right? um you know in relation to space stuff this is kind of what you know they've done with like the you know lunar payload services program right NASA has just said I don't care how you build your lunar lander um but we are just going to guarantee they were going to buy x amount of basically like lunar payload services and it's
45:53
going to be at xyz price and up to you how to go to do it and so I'm definitely like a big fan of those approaches I do think there are the occasional warranted you know hey here's a huge next step in the tech tree it's just totally uneconomically viable for anybody to step into that tech tree without knowing that there's going to be government support, you know, sort of basically from the get-go, right? Um, in some ways
46:12
Um, in some ways like, you know, nuclear weapons were that there was never going to be like a private company that was going to go invest into, you know, figuring out, you know, sort of the fision or fusion bombs, um, without knowing if there was basically going to be government support.
46:23
I do think that like linear accelerator is sort of one of those.
46:25
accelerator is sort of one of those. Now there's a big question of like is it celindra you know is it you know you know fearfully copying the Chinese mimemeticism but it's like I'm not sure there's any other option where you know I'm not sure that there is any other credible you know approach to
46:39
domesticating lithography like I don't think that like trying to just copy the ASML tech tree makes any sense I'm not sure that anybody else has come up with an energy source that like you know sort of as an option so there probably needs to be like some you know sort of bet so if we were to assign xyz budget to like domesticating foundaries Mhm. I mean
46:54
I mean probably 10% of that equivalent budget should be assigned to trying to domesticate lithography and there's really only one bet on that tech tree basically you know sort of to make and so I I mean it's kind of a lame answer but I think the answer is like there needs to be a little bit of a blended approach to like you know national reserves guaranteeing demand in you know refined lithium domestically in the United States.
47:14
United States. Um there's also some questions on like look like you know with like let's say magnets we do a lot of like you know the rare earth mineral production of those you know magnet precursors but the actual like you know sort of final synthesis and refinement that all happens in China but a part of why it happens in China is like the current processes are like crazy destructive for the environment and so
47:32
it's like it's like actually a question of like I mean we do want to like where how do we want to like try to come up with a different process but it's like better for the environment but like 10x more expensive like you know there are questions like that where it's like, you know, we were kind of looking into like the magnet supply chain recently and as we were debating an internal investment. It's like you look at that step in the
47:50
It's like you look at that step in the supply chain and I'm like, man, it's like not particularly technologically difficult.
47:55
It's like really easy for us to replicate, but it literally is just like releases poison into the like, you know, environment. Yeah.
48:02
uh taking it back to space.
48:05
Uh you know, it seems like the the the helicopter on Mars, the uh the the massive James Webb telescope, like these are things that are not economically viable, but I could totally see them paying off and being like, "Oh, that was a great investment."
48:17
Even just like inspiring the next generation, but also like probably commercializing some some technology down the road.
48:23
Uh on the flip side, we saw Blue Origin with the space tourism thing.
48:27
It's like barely space uh past just past the Carman line.
48:32
But, uh, how do you think that plays into the overall like space economy?
48:34
Do you like that strategy of of growing that business?
48:39
Is that a business that can stand on its own?
48:40
Uh, or is it just kind of like a fun side project for Bezos?
48:45
I don't know what you know about that uh that whole like industry as it as it's growing because we've seen it kind of play out before with Virgin Galactic and uh I'd love to know what you think about space tourism generally. Yeah.
48:55
I mean, I want to also touch on like that, you know, an earlier point that you had around like the helicopter on Mars, James Webb telescope, etc.
48:59
I'm not sure um if you know, but the White House actually recently released um its proposed NASA budget um after um future you know, you know, nominated administrator, you know, sort of Jared Isaacman after his confirmation hearing.
49:15
Um and in it, they, you know, significantly slashed all you know, sort of science, you know, sort of missions at NASA.
49:20
And so that includes um future telescopes that we have in the works.
49:23
Um that includes, you know, some of those helicopter on Mars missions.
49:26
Um and so the White House is at least taking a stance on that is not something that you know we see as being you know sort of valuable.
49:33
Um those are definitely you know sort of things that clearly don't have any you know sort of economic you know sort of feedback loops like more deeply understanding the universe.
49:39
You know I don't know if you recently saw we like found an exoplanet where it looks like there are um you know organic compounds that you know on on Earth are only you know made by marine algae.
49:48
only you know made by marine algae. Um and the planet you know is um uh very large and in the Goldilock zone of a red dwarf star that would be at a temperature zone where you know sort of liquid water would be possible and so it's like yeah like what is the you know sort of value of that you know hard to you know sort of prescribe economically
50:06
and the white house has at least thought hey we don't see the geopolitical you know sort of significance in this doesn't get boots on the moon and it doesn't return you know sort of uh to an economic use case um so that's at least the white house stance which also for what it's worth it was different than what um administrator Isacman said in his confirmation hearing. So um you know it's interesting
50:21
So um you know it's interesting to see that obviously um there's you know maybe some disconnect between um the administrator and the White House.
50:29
Um on all things space tourism I don't think it's you know sort of an economic you know sort of use case that is going to be what really you know drives us to the frontier.
50:37
You know whenever I've thought about VA I always go back to this um 15th you know sort of century um analogy which you know sometimes people think is a bit of a scratch.
50:44
I think it's actually pretty reasonable.
50:45
But if you look at the early 1400s and the Portuguese and the Chinese empire, they both were uh in the early days of investing into basically their naval capabilities and they took you know sort of radically different approaches.
50:55
Um the Chinese basically took the approach of build these very large and ornate ships um and go and sail along the African coast um you capture elephants, you know, bring back some gems um and uh you know uh you know bring them back to the Chinese emperor as basically displays of power, right?
51:11
And so um you know the the Chinese emperor would now have a pet elephant for the first time.
51:16
They would have these gems.
51:16
They would have these like African trinkets.
51:18
Um the Portuguese took a very different approach.
51:21
Uh the Portuguese built very small naval merchant flatillas.
51:23
Um they would basically um you know dock along the African coast.
51:27
Um they wouldn't tour the entire coast like the Chinese did.
51:31
They would just stay there make a trading outpost basically find you know sort of economic means and reasons for that naval flotilla to be around.
51:36
And then only once that initial merchant outpost was established would they move basically 50 miles west down the coast until they eventually covered the entire coast.
51:44
Um so fast forward to the late you know sort of 1400s where did these naval empires basically end up?
51:48
Um the Chinese emperor ended up deciding that this was basically a waste of resources.
51:53
He didn't see any economic value for his empire for having elephants around.
51:55
Um and so ultimately basically shut down the entire naval you know sort of um power for China for the following I think almost 300 years.
52:02
think almost 300 years. um the Portuguese as we you could probably guess um became the most powerful naval power you know in the entire world um and led to significant you know growth of their empire and so I think about you know sort of space you know sort of pretty similar to the you know sort of naval frontier in the you know sort of 1400s and 1500s um I think you want to find these you know sort of clear
52:22
economic use cases that you know involve trade and resources versus the like you know sort of Katy Perry going above the Carmen line is probably kind of like the elephant for the emperor um where you know Bezos gets to you sort of pop some
52:33
champagne Um, and you know, I'm sure his wife is super happy um that you know, Katy Perry feels indebted to, you know, them as a couple, but like I don't know that that like generates a ton of economic value. And so, um, the e economic incentive
52:43
And so, um, the e economic incentive around space is obvious.
52:46
Let's maybe talk about the national security incentives, specifically China in 2030.
52:53
They've come out and said very clearly, we want to put, you know, uh, our astronauts on the moon.
52:57
you know, I I don't know if it's by 2030, but in the 2030, early 2030s.
53:02
Um, so maybe, you know, how much can you speak to? Yeah.
53:10
Do boots on the ground actually matter or or would it be viable for them just to send up so many landing zones that they start building like uh we've heard about this like when you land you kick up a bunch of dust and so you're kind of de facto claiming an area and there's only so much ice water there.
53:21
So like if they could just send a bunch of like rovers, they could effectively start like claiming and they might not even ever need to send humans to really claim the resources. What do you think?
53:31
the resources. What do you think? Yeah, let me give you this sort of you know sort of China bear versus China you sort of bull case on this China bear case is this is China repeating the same mistakes from the 1400s you know so they're going there they haven't really figured out you know sort of economic use cases they don't even haven't even
53:45
really figured out economic use cases in LEO right they have nothing equivalent to like Starlink generating billions of dollars you know of commercial you know sort of revenues that you can use as infrastructure to build off of right and so they're the you know sort of Chinese with yes they're building big fancy ships yes they're landing rovers on the
54:00
back side of the moon but they're not connecting this into capitalism whatsoever and so this will all you know sort of fade away versus the United States the Portuguese while we maybe haven't more recently succeeded as well as they have on the moon we've got Starlink we've got Starship going up we have all these things that are built off of commercial infrastructure and so
54:17
while we may not have as big of a ship soon if you fast forward over the course of the next 30 years the Chinese will shut down their program and we'll be the most powerful naval empire eg space empire in the entire universe um China you know it's a bullcase um nobody's landed, you know, sort of on the, you know, sort of back side of the moon ever and returned samples. Perhaps they're
54:34
Perhaps they're finding, you know, helium 3 deposits.
54:38
They're finding lunar ice deposits.
54:38
Um, you know, they're taking a much more concerted approach to trying to get, you know, sort of human boots on the moon and forcing it from top down.
54:44
And if they get those first handful of boots, like you said, they can, you know, sort of claim, you know, particular land areas.
54:50
And there's only a handful of crater craters on the moon today that are clearly known to have lunar ice.
54:54
If they claim those first handful, if they start mining that ice, they can turn it into propellant.
54:59
they can turn it into economic value where they can send that back into lower earth orbit to some of their satellites they have set up there.
55:05
They're setting up, you know, sort of Starlink, you know, sort of competitors.
55:08
Um, and so there's definitely a world where, you know, they establish the first, you know, sort of permanent lunar presence while we get distracted by this dual path between moon and Mars.
55:14
That permanent, you know, sort of lunar presence turns into a mining operation.
55:19
And so they do connect it back to economic value.
55:20
Even though it has a lot of like, you know, strong, you know, from top down state power, you know, getting it established, it eventually transitions to something, you know, sort of fully economic.
55:29
And so I think there's way to, you know, sort of take both those angles.
55:32
I tend to think I think you should never underestimate, you know, sort of your, you know, enemies.
55:36
And so I tend to take the China bullc case and assume that as the default.
55:39
Um, and I think we're a little, you know, sort of, you know, lost in the rudder right now.
55:43
I think, you know, it'll be interesting to see how, you know, administrator Isaacman, you know, comes in and starts to put together what our plans are for, you know, getting boots on the moon, you know, over the course of the next four years.
55:51
Do you have uh any insight into like the timeline of actually generating propellant on the moon?
55:56
I've heard like oh there's water and at a certain point you can draw out the chemical process for turning like carbon and hydrogen into some fuel but like that's hard to de desalination is hard in America in California.
56:10
Uh I can imagine that actually taking the resources on the moon and turning into propellant is like a massive industrial process that looks more like a Tesla gigafactory than like a little science experiment.
56:22
But maybe I'm wrong about that.
56:24
like is this something where we could actually build a box that starts doing this get it up there in the next decade or are we talking about like 20 30 40 50 years?
56:31
I think this is where like exponential equations always you know sort of catch up on you in a way that's you know sort of unexpected.
56:38
If you look at the total mass to orbit basically over the past decade it's basically following a perfect exponential equation. Yeah.
56:43
And so I think this stuff is you know sort of way sooner than people expect.
56:47
Like I actually think with a concerted concentrated effort I think we can get boots on the moon again before you know Trump is out of office.
56:55
Um and it's not like you know sort of betting on a bunch of you know sort of new you know sort of radical programs.
56:59
It's you know Starship maturing at the the sort of rate that it is maybe a little bit more aggressive um you know sort of the current you know Artemis vehicles Orion etc.
57:06
Um and some of the current lunar lander companies starting to develop you know sort of larger landers.
57:11
I think that's all you know I'm not saying that's going to happen like in the next year or two.
57:14
it would be like late in the Trump, you know, sort of presidency, but I think it's possible on like conversion to fuel.
57:19
Not that complicated a process.
57:22
There's like five or six groups that are sort of already, you know, working on it.
57:24
Um, you know, I'd say the desalination thing that's, you know, sort of more of a economic challenge than it is like a technical, you know, challenge to like basically, you know, justify the amount of water that you need.
57:34
The benefit of water on the moon is like on a per kilogram basis.
57:36
It's so incredibly valuable because it's just so much easier to shoot water from the moon into low Earth orbit than it is to bring water um you know from Earth's surface up into low Earth orbit.
57:45
Um and even to start you don't need anything more complicated than water.
57:49
Like you can use water as it's not a very good propellant but you can basically just spray water and it is a rocket you know propellant.
57:56
Um now there's you know better things you can do.
57:58
You can turn it into you know atomic hydrogen and stuff like that and hydrogen gas um or liquid hydrogen but you know you can start with very you know sort of basic things.
58:04
And so you know um I think it's like a end of decade problem totally solvable.
58:08
U now depends on you know taking a really concerted focused effort and again maybe a part of it is you do have to sacrifice the Mars helicopter you have to sacrifice you know some of these you telescopes etc to get the country really really focused on getting lunar infrastructure set up as quickly as possible.
58:22
What's the probability that you or I go to the moon in the next 20 years?
58:31
Um specifically you or I. Yes. What's your P moon?
58:38
I'd say our P moon is like, you know, 30 35% is my P moon. Yeah.
58:41
I' I've been talking to my son about that.
58:44
We look up at the moon and I'm like, do you want to go with me? And he's like, yeah.
58:47
And I'm like, I think it's possible. I think it's possible.
58:51
If you extend that to 40 years, that would put like P moon at like 98%. Awesome.
58:54
Uh so wait there so there's this conspiracy theory that the Blue Origin launch didn't happen, that they didn't go to space, that it's impossible to go to space using only familyfriendly language.
59:05
Uh what would you say about the people that don't believe they went to space?
59:12
Well, um you know, there are certain conspiracy theories uh that uh you know, always have some truth or merit to them.
59:19
You know, JFK probably was killed by the CIA.
59:21
Um um you know NASA may have had a sound stage um for the you know sort of lunar landing um as a backup.
59:26
Um and you know Katy Perry probably is not an astronaut.
59:33
Um you know you could probably just you know fly a fighter jet you know up and then down and uh you probably roughly get the same experience that she did.
59:40
Very different to be going you know a little up a little down versus you know 15,000 miles an hour.
59:44
So I'd say God bless those conspiracy theorists.
59:49
They're always helping us find the kernels of truth in the uh um you know stories that they weave. Yeah, that's legitimate.
59:54
Uh going back to uh space and geopolitics, um China has their national space day uh on April 24th, so next week.
1:00:06
Is that something significant in the space community that that people are like really paying attention to?
1:00:13
really paying attention to? like they feel like there's going to be like real signal or exciting results or is it just kind of do people kind of uh write it off or not write it off but just kind of look at it as this sort of like uh kind of like a demo day kind of marketing uh
1:00:31
keynote style event where where it's you know not a lot of signal they're delivering like you know if you look at you know sort of China's you know sort of plans from 2018 and sort of where they are today they're not totally off track on you They said what they promised they'd be able to do, right? They've established their own, you know,
1:00:46
They've established their own, you know, low Earth orbit Chinese space station.
1:00:50
They're regularly flying astronauts up and down to it with cargo.
1:00:51
Um they're attracting international partners um to that space station.
1:00:55
Um they've clearly gotten a coalition of folks willing to sign on to their, you know, sort of lunar, you know, station or lunar base plans.
1:01:02
Um and so I do think it's something that, you know, people pay a lot of attention to.
1:01:05
they tend to, you know, sort of, you know, re-update or re-reveal basically what their next, you know, sort of 5, 10, 15 year goals are.
1:01:14
Um, and it's something that everybody from like, you know, sort of NASA to Space Force definitely pays a lot of lot of attention to.
1:01:18
Um, they're not always fully transparent about obviously, you know, sort of what they're up to.
1:01:21
So, there's no guarantees that there will be anything new.
1:01:23
Um, but I would expect that there will be given, you know, all the tensions that have risen over the past year between the United States and China.
1:01:31
And so, I would And how how do some of these partnerships happen? Right.
1:01:35
So, uh, one of the things that they're going to be reporting on next week is is related to a partnership they have with France on like a joint satellite program.
1:01:42
Is that a, uh, is that is that like due to NASA's shortcomings?
1:01:49
Like, is that a missed opportunity for us to not be partnering with France on something like that?
1:01:54
or like how how do these sort of like how do the and and are the geopolitics of space almost like disconnected in some way between uh with Earth? Oh no, very connected.
1:02:07
That entire French thing I would basically, you know, sort of pinpoint back to the nuclear submarine contract.
1:02:11
Basically the United States ended up moving a chunk of nuclear submarine contracts out of France over to Australia. The French were furious.
1:02:19
Mcronone, you know, sort of went on and, you know, gave a bunch of public talks about it.
1:02:23
And then basically like the, you know, so Chinese collaboration started less than a month later.
1:02:25
And so it was clearly like a, hey, you're going to slap us on the wrist as an ally. Great.
1:02:30
We're going to go to your geopolitical adversary.
1:02:31
Um, I don't think obviously those two things are, you know, one one is like purely economic, like we're moving the place that we're making submarines.
1:02:39
The other one is saying like we are partnering with your ally.
1:02:43
Those two things feel like one is like a business decision.
1:02:47
The other one is like very clearly like you know picking uh a side totally.
1:02:49
I mean from France's perspective it's like you know it's billions of lost revenue for one of their you know major defense primes and um you know they see that as a you know sort of slap on the wrist and so you know they feel like they need to you know sort of slap back and so um yeah I'm not sure that you know it's the smartest geopolitical move.
1:03:08
I don't think like you know a western democracy should be you know sort of cozing up to you know an authoritarian dictatorship.
1:03:16
Um, but I also don't think the French are the most intelligent people in the world right now.
1:03:20
Well, they they have the opportunity to turn it all around because if they don't, I will be boycotting Don Pering. You heard it here first.
1:03:27
And that will that that will crush shock waves through LVH through the French economy.
1:03:32
I will not be vacationing in Leon or Nice or Burgundy.
1:03:38
I will not be spending my time on the French Riviera.
1:03:40
I'll be in Nice late June, no matter what.
1:03:42
Uh, no matter how dumb the French are. Cancel it.
1:03:44
cancel it unless it unless it comes back to No, he's going to turn them. He's going to turn them. Yeah. Yeah.
1:03:49
You got to go over there.
1:03:51
You're our You're our plant. There.
1:03:54
I'm going to look at those Airbus facilities in Tulus and uh take a look at that Chinese satellite project. Wait, La last thing.
1:03:58
Uh if you don't have a hard hard stop, um how do you think about uh the Chinese uh aerospace industry specifically?
1:04:06
They they earlier uh in the week they they canled or paused some Boeing orders.
1:04:11
Um, someone else on the show was saying, "Well, they'll probably just move those orders over to Airbus, something like that."
1:04:19
But at the same time, um, how long is it until we're all going to be um, you know, uh, really that hard to build a jet engine?
1:04:27
I I feel like they should have copied that by now.
1:04:29
This is kind of a bare case for them.
1:04:30
Well, up until a year ago, my like one line would have been, you know, there haven't been any commercial airliner deaths in the United States for like 16 years.
1:04:36
And so the reason that it's really difficult is because like the safety bar is so so high that basically nobody wants to touch anything.
1:04:43
They're like everything's been perfect.
1:04:44
Now obviously you know so DCA and uh you know sort of Toronto um well Toronto I think it didn't end up leading to any deaths but DCA obviously did.
1:04:53
Um, and I'm not sure that that's really going to change the culture.
1:04:58
Like, you know, FAA aviation, you know, um, uh, regulations are just so so stringent because they do have in some ways a great track record, but man, it just sets the bar so high. Mhm.
1:05:07
Will the Chinese ever really manage to get any traction? I don't know.
1:05:11
It's like definitely not in the United States ever.
1:05:14
There's no way that like the United States is ever letting a United States airline buy like a Chinese, you know, sort of jet liner. It's the Karmac C919. Yeah.
1:05:22
And there's no way France is gonna let them, you know, buy anybody other than Airbus.
1:05:25
Same thing with the entire EU.
1:05:27
So, who the hell are they going to sell their like Chinese airliners to?
1:05:30
Like Africa or something, you know, I don't know how big of a Malaysia, maybe Malaysia teleport teleporting.
1:05:34
Oh, did you see that there was some uh you know, revealed potential documents of uh four um UFOs surrounding the Malaysian airliner and then disappearing it. Okay.
1:05:47
Well, we'll have to dig into that next time.
1:05:48
Got to get do another half an hour.
1:05:50
Get Jesse to come, you know, talk. Yeah. Yeah. Yeah. We'll break it down.
1:05:53
Uh I really appreciate you stopping by. Thanks so much. This is great. See you next week. Cheers. Bye.
1:05:56
Uh next up, we are going to uh the founder of a company that Delian is in love with.
1:06:02
He's obsessed with these uh these AI apps.
1:06:04
He can't get enough of them.
1:06:07
So, we're very excited to have Gam on from Captions.
1:06:08
Uh I'm actually a huge fan of this app and this company.
1:06:13
Uh I use it all the time.
1:06:15
Anytime you see me post a clip on X and there's captions there, I'm using the captions app. That's right. It's fantastic.
1:06:21
Uh, and there's a bunch of other cool features and the company has been just maniacally adding functionality.
1:06:28
And as you saw with chat GPT, uh, you wanted to generate a video, it like it couldn't do it.
1:06:32
Like these tool usages are increasingly difficult and they're not something that you can just it it increasingly looks like you can't just oneshot it with tokens out of an LLM.
1:06:43
And so building up traditional software around the system actually improves the AI.
1:06:49
And so these products are very complimentary.
1:06:52
So we're excited to welcome him to the show. How you doing today? Boom. Hello. Hello. There we go. What's going on? How's it going? Uh it's great.
1:07:01
Thank you so much for being here.
1:07:03
Thank you so much for creating the captions app.
1:07:06
I use it very very regularly. Du bas. Oh my god. I'm obsessed. Yeah. Yeah. For a long time.
1:07:12
I mean, we we make a ton of clips.
1:07:14
You've probably seen uh and it's always a hassle to put captions over, but you made it much easier. Uh a lot of that.
1:07:20
I want to talk about uh the history of the technology, the whisper turning point, and then get into value creation, the application layer.
1:07:27
There's so much we can talk about, but why don't you kick it off with just like introduction on like how you're describing the company the these days and then the most recent announcement. Totally. I mean, so love that.
1:07:36
By the way, you're an OG user, so thank you for being a user.
1:07:40
But you know it's a pretty young company like we're our product market fit was like 2 and 1/2 years ago right?
1:07:46
So like we were four people 2 and a half years ago and things have grown really really fast.
1:07:50
all started with adding captions, you know, your most basic thing, but it's evolved quite a bit.
1:07:59
And um so today, I mean, the way we think about the company today is like, you know, video creation is hard, right?
1:08:05
And we've identified two problems actually, right?
1:08:07
One is recording the video is hard.
1:08:08
You guys know this, right?
1:08:11
And editing the video is hard too, right? It's pretty technical.
1:08:13
And we want to solve these two problems.
1:08:16
Like these two problems we want to help people jump over with AI, right?
1:08:18
So if you want to edit video yourself, if you want to record video yourself, go somewhere else basically, right?
1:08:25
We're going to actually do it for you. That's the value, right?
1:08:28
So not going after Da Vinci Resolve, not going after Premiere, an entirely new market. Exactly. Right.
1:08:36
And we think of it very similar to Canva actually like you know Canva for video has as an idea has been sitting around for a while and I think it's actually finally possible because of AI, right?
1:08:45
Because the real value of Canva is you start with something, right?
1:08:48
You don't have a blank screen and you know it's not built for the designer, right?
1:08:51
Most designers will look at Canva be like I could probably do better than this, right?
1:08:57
But it's built for the person who's not a designer, right?
1:08:58
And that's the same value that we provide.
1:09:00
So on that note, right, like last year we started working on essentially foundation model technology for video generation and for editing that's going to help us achieve that.
1:09:11
And you know, these are big projects, very expensive, uh, but also very cutting edge.
1:09:15
Um, I think the most exciting part on the video gen side for me is like we're very much focused on like talking videos, right?
1:09:22
Which is and by the way, like I'm also like kind of surprised almost in a way that we've spent so much time and so much money doing text to video on silent videos, right?
1:09:32
Like what what's the point, right? Like just stock videos.
1:09:36
Like that's that's the negligible part of what a video is. Yeah.
1:09:38
Almost no time spent on videos with actual communication.
1:09:43
So, that's kind of what we've been focused on for the last year. Yeah.
1:09:46
Uh what what uh like what I don't know what what like breakthroughs are are are the most interesting to you?
1:09:53
Obviously, like Whisper is super important.
1:09:55
I feel like Whisper is great and then all of a sudden it came down to like, okay, I want re real time Whisper on the show and then I got to go build that. Or uh Notebook LM.
1:10:02
I like Notebook LM like it still doesn't have an app even though Google is paying people not to work and stuff. It makes no sense to me.
1:10:11
Uh and and I'm and I'm imagining that like captions could be an app where I'm getting like a notebook LM style like YouTube videos.
1:10:17
YouTube's talked about this a little bit.
1:10:19
They haven't rolled anything out, but you're starting to see a lot of this stuff.
1:10:21
A lot of it's in like the slop tier, but what I like about captions is that you can still inject enough of the human element to take it from it's a tool that's used in partnership with a human.
1:10:32
So, it still has that art in there.
1:10:33
Um, but but what what is exciting you and what's the most interesting in terms of like where you want this to go? Yeah.
1:10:40
I mean, honestly, like there's a pretty clear distinction that's developing that I'm starting to see which is like amongst the foundation models, right?
1:10:47
Like there's the text generation like LLM type models, right?
1:10:51
And those are solving a very difficult problem is intelligence, right? Like unsolved problem.
1:10:56
No one's solved intelligence before, right?
1:10:58
So, and by the way, we don't even know what the bound is, right? Like where does it end? Who knows?
1:11:02
It could never end, right?
1:11:02
It could go on forever, right?
1:11:04
And then on the other side, you got, you know, media generation.
1:11:08
Like this is everything from like video generation to music generation, sound, audio, like all this stuff, right?
1:11:14
These are solved problems.
1:11:16
Like we can do rendering today, right?
1:11:18
Like we can literally render anything you want with like CGI and stuff, right? Of course.
1:11:22
It's just becoming a lot easier and it's also bounded, right?
1:11:26
Which means that there is a limit of realism, right?
1:11:28
And then you've kind of solved it essentially, right?
1:11:30
solved it essentially, right? you can get more real than real and once you're there you kind of have achieved what you set out to achieve right and so I think it's a different type of problem and also it means that it's not about replacing the human right because what's actually happening is the craft is
1:11:47
evolving right the craft is different but the creativity is still there whereas on the LLM side that's actually potentially replacing the human not going to lie right that's potentially what it's going to do right so these are two different types of use cases almost two different types of value that are being produced today. I think we fall
1:12:03
I think we fall definitely much more in that sort of media generation category where like our goal is not to replace anybody, right?
1:12:10
It's actually like empower a bunch more people potentially, right? And who knows, right?
1:12:12
People come in, they use captions to make their videos, right?
1:12:15
And we edit it for them, we like generate the video for them and you know that just gets them started, but like two, three, four years down the line, they you know, they move on to Premiere Pro or something like that's awesome. Nothing wrong, right?
1:12:25
So, how do you um on the developer side, we're seeing a bunch of startups where it seems like everything is just converging into this like one shot, right?
1:12:35
Where it's like you have Lovable, Bolt, uh Ripling, uh uh sorry, uh Riplet, Replet, sorry.
1:12:44
Rippling is one shot for your HIS system. That's right. That's right.
1:12:46
Um so everything's kind of converging onto this like text box where you just tell it what you want and then it makes it makes a website or an app or things like that.
1:12:55
Uh I imagine content will maybe go that way for some use cases and that's kind of like there's a lot of sort of momentum and convergence around that moment.
1:13:06
Um how do you see and but that's just you know my point of view.
1:13:10
What what's your point of view on like how all this evolves and um how you're looking to continue to differentiate captions over time other than just sort of like chasing perfect realism? Totally. Yeah.
1:13:25
I mean, so couple things there.
1:13:27
Like I think generally uh kind of to, you know, make a comparison what you're talking about, right?
1:13:32
Like I think of it as like Canva for everything.
1:13:36
That's actually what's happening, right?
1:13:37
Because the magic of Canva, you know, awesome company.
1:13:40
I think the magic of it is not about how simple the UI is or something like that.
1:13:46
The magic is that you start with something.
1:13:47
It's not a blank page, right?
1:13:49
And really the biggest enemy of anything creative is the blank page. Yeah.
1:13:51
And not the UI and stuff, right?
1:13:53
I mean, think about like design software in general.
1:13:57
You look at like Figma and stuff.
1:13:58
Like Figma has like six buttons, right?
1:14:00
Like it's not a hard UI, right?
1:14:02
But it's really hard to make something good with it.
1:14:03
Like it's really hard to figure out how to use squares and circles to make something that looks good, right?
1:14:07
And I think the magic of Canva is you start with something, right?
1:14:10
You're already 90% there when you enter and then you kind of make some tweaks to get it to 100, right?
1:14:14
And by the way, like think about chat GPT.
1:14:15
It's kind of the same thing, right?
1:14:18
We're using it all over the place today, but it just gets you started, right?
1:14:21
Like it's like boom, I already have something like I need a job description.
1:14:24
Boom, there's job description, right?
1:14:26
For whatever job you want, right?
1:14:26
And then it may not be perfect, right?
1:14:27
You make a few tweaks, you know, change things here and there and you're done, right?
1:14:32
And so it's like Canva for everything. That's what's happening.
1:14:34
And I think same for music generation or, you know, video generation, like all these things are going there.
1:14:39
Our goal and our mission in this like we're focused on specifically the communication sort of vertical, right?
1:14:46
So think about this, right?
1:14:46
If you think about a movie or, you know, a TV show or anything like that, right?
1:14:51
Any kind of like media today, um, only a small part of that is B-roll, right?
1:14:55
Like if this was a movie, like I'm in New York, so like it might open with like a shot of the Empire State Building and then the next scene like, oh, there's a New York taxi cab on the street passing by really quick in 2 seconds and then the camera is in the room and we're talking, right?
1:15:10
And that's actually the movie, right?
1:15:11
And so so much time and money has been spent on making the shot of the Empire State Building and almost nothing on like actually getting the dialogue going, right?
1:15:20
That's kind of the the weird thing, right?
1:15:22
And like our thing is like let's get that communication that dialogue problem solved, right? That's one.
1:15:29
And on the other side, just footage isn't enough.
1:15:32
So let's get it edited to make it actually an asset. Right.
1:15:35
Can you talk a little bit about uh growth for captions?
1:15:38
Um, there's a weird dynamic where uh it can be extremely valuable to go viral with like a oneshot thing.
1:15:47
I'm thinking of Lensa, those magic avatars that it was just upload a couple photos and you get a photo of yourself.
1:15:53
Then we had the studio Gibli moment which was a huge growth vector.
1:15:56
Uh, it's not OpenAI's product, but it was still probably massively beneficial just to drive a bunch of extra installations and chat GPT use, right?
1:16:04
And so I could imagine you guys thinking like, hey, let's go make a one-click Harry Potter Balenciaga generator and like we are just like really good at making like Harry Potter Balenciaga style videos.
1:16:16
Of course, you need to put in your own tweak, but that's what we're great at.
1:16:20
But you don't want to get pigeonholed into that, but it can be a good growth driver.
1:16:23
Are you thinking about that conscious consciously?
1:16:25
Are you thinking about like how can I get uh the next how can I get the next Studio Giblly moment to happen in the captions app?
1:16:31
in the captions app? Yeah, I mean so we are but our philosophy on this honestly like think about both the studio giveway thing but also think about like original chat GPT right like I remember the time where you know GPT was available like I would use I would show it to my friends
1:16:47
like check this out like check how how cool this is and people would be like oh wow cool okay right and then suddenly chat GPT came out and like by the way I think it was very clear that they hadn't prepared for the amount of virality that thing got right like even the chat GPT kind of gives that away, right? And so it wasn't
1:17:03
And so it wasn't a planned thing.
1:17:07
It kind of just happened, right?
1:17:08
So you give the same thing.
1:17:09
I don't think they planned it.
1:17:10
Like it just kind of happened, right?
1:17:10
So I think if you create the right environment where people are given the creativity to go try something that's like an awesome technology, right?
1:17:16
They they can play around with it, make cool things with it.
1:17:20
Like these types of moments kind of happen naturally.
1:17:22
It has happened for us several times with different technologies we released in the past.
1:17:26
And a lot of times it's been unplanned.
1:17:28
It's just like, you know, when we plan for it too much, it doesn't happen.
1:17:30
when we don't plan for it, it just like suddenly explodes like completely, right?
1:17:33
So, that's kind of what we've seen.
1:17:35
Um, and it's something we think about of like how do we create that wow experience because at the end of the day, a lot of the growth and virality is happening because people are just blown away.
1:17:44
It's just so impressive, right?
1:17:46
It's beyond anything anyone's ever seen, right?
1:17:47
And I think that is a pretty high bar.
1:17:50
So, building on that, building in private until we reach that bar, releasing it as like a wow, this is like crazy.
1:17:56
like that's the type of stuff that we've seen work really well. Uh, next question.
1:18:04
Do you have any sort of visions around uh what the just video content on the internet in 2030?
1:18:10
Because I have this uh right now there's not a huge incentive to make a video for one person, right?
1:18:18
Especially in a business context.
1:18:18
If I if you want to explain something for 10 minutes to somebody in a business context, you pick up the phone, you call them, you spend the time to send an email or whatever.
1:18:26
Now, with something like captions, it's like, well, I could just generate a video of like how my product works and why it's relevant to this industry and all that.
1:18:32
And so, I have this sense that content generation is gonna like 100x thousandx, but human attention is not going to 100x or thousandx, right? It's just not possible.
1:18:44
There's only so much time in the day.
1:18:45
People use their phone for six, eight hours on average right now.
1:18:50
They're still spending two hours a day on Netflix, but we're not going to suddenly like get, you know, a 100 hours a day.
1:18:55
uh even though people on you know Tik Tok uh entrepreneur influencers might might want that.
1:19:00
Um, so I just have this um kind of question around like do you think the average video in the future gets one view, two views and and maybe it's not the average, right?
1:19:10
Because certain views will or certain videos will still go super viral and be sort of cultural phenomenons, but um but yeah, I'm curious if you think that's kind of like where we're headed. Uh right.
1:19:21
I mean, I think for what it's worth, I think the average video today is getting probably one or two views, right?
1:19:26
Because like think about Snapchat like a lot of video probably a billion videos a day but sent to like you know a few people are seeing it basically right for the most part private communication and honestly like Snapchat pioneered that like they kind of missed the Tik Tok part of it.
1:19:38
it wasn't part of their ethos to be honest, right?
1:19:39
But like they were more about the private communication.
1:19:43
But uh I I think the future is more video like for what it's worth like you know the way and I think there's an interesting sort of like move that I think will happen towards more video in AI as well because think about like how communication's changed over time, right?
1:20:00
Like we're not sending letters to people as often anymore, right?
1:20:04
Like text messaging is kind of like very prone to miscommunication, right?
1:20:08
Audio is definitely better.
1:20:08
Phone call make goes a long way.
1:20:10
Video call is like one step further, right?
1:20:12
And then real life meeting is even beyond that, right?
1:20:16
Often times there's like even within companies like right there's miscommunication and like mistrust that builds when there's remote teams or things like that, right?
1:20:24
And you got to watch for that.
1:20:25
Uh whereas an in-person team just trusts each other so much more.
1:20:28
more. So there is definitely something to be said about like these more sort of multimodal forms of communication right to use the the term but u I I do think that actually even on the AI side right like sure chat GPT makes me a great writer but like what makes me a great
1:20:45
communicator right and we're really not thinking about that right because communication is multimodal in itself right like the words that I'm saying right now where I'm pausing what I'm emphasizing how my micro expressions are moving like how my body is moving like all that is communicating in multiple forms, right? A message and
1:20:59
A message and that message changes if I change any of those things.
1:21:04
Like word words might be the same, right?
1:21:05
But I can change the message completely by just changing the delivery of it, right?
1:21:08
So I think today's technologies like just aren't capturing, right?
1:21:12
Like how broad uh communication actually is.
1:21:15
And I think it will all evolve towards video over time just as we've seen like this is not new.
1:21:21
We've seen this happen before, right?
1:21:22
So and by the way like I was at Snap when like Tik Tok took off, right?
1:21:27
uh 2019 that era and initially like Tik Tok grew a lot on the back of Snap.
1:21:31
Not a lot a lot of people know this but like they were running like a hund00 million a month of ads on Snapchat right initially right when they were not there was no presence into the hen house. Yeah.
1:21:45
And like there was concern like in the company people were concerned that like are we are we like creating a competitor here right and people we were running tests. Yeah.
1:21:54
Narrator they were Exactly.
1:21:58
But like we ran AB tests to test, right?
1:22:01
Like if someone sees a Tik Tok ad, are they less likely to engage in Snapchat?
1:22:05
Tests didn't show that, right?
1:22:07
But the reality is that it wasn't true, right?
1:22:10
They they did uh spend less time on Snapchat. So, well, we got to run.
1:22:13
This was a fantastic conversation.
1:22:15
Uh thank you so much for hopping on and we'll we'll definitely talk to you soon.
1:22:19
Yeah, great great talking. Thanks for coming on. Bye.
1:22:21
We got Ian in the waiting room from Astromec. Uh, Astromeca.
1:22:25
I believe I'm pronouncing that correctly. Astromeca. Uh, great. Mechanica. Astromechanica.
1:22:30
Sorry, I mis I I mistyped that. Astromechanica.
1:22:35
Anyway, we'll let him explain it to us. Come on in, Ian. Sorry for the wait. Sorry for the wait. Uh, yeah.
1:22:42
How do you pronounce the name of the company?
1:22:43
Let's settle this debate once for once. Astro Mechanica. Astro Astromechanica. There we go.
1:22:48
Uh, can you give us a breakdown of of what you do?
1:22:52
And I'd love to hear like the the brief history on the launch.
1:22:55
I remember there was like a video you posted of building something maybe in a garage. It went viral. It was very cool.
1:23:00
And there was some debate over it. Now it's a real company. Raised a bunch of money.
1:23:03
So take just take me through the little journey. Yeah. Yeah.
1:23:05
I you know I guess it starts my background of like I'm lifelong aircraft builder, pilot, fly jets, the whole nine on that. Yeah. And uh Yeah.
1:23:13
You flew uh you where what kind of jets did you fly?
1:23:16
You kind of private private jets.
1:23:18
Um, I built like I built my first plane when I was 17.
1:23:21
I did experimental airplanes, drones in like the early 2000s before drones were a thing.
1:23:26
So, anyways, from that like I think with like a lot of good companies, you're really just building the thing you want. Yeah.
1:23:31
Uh, this is just not a thing that exists.
1:23:33
Unsurprisingly, one cannot just go buy like a bleeding edge fighter jet.
1:23:40
So, so yeah, you know, going with that, uh, I'd always been obsessed in all the technology.
1:23:43
Um, interestingly I was working on like this hybrid electric architecture initially coming from the private jet world for lower cost of operation.
1:23:50
Uh, it's just like simpler systems and it turns out there was a really neat technological unlock for supersonic flight.
1:23:57
So that's where a lot of this kind of kicked off and it was an especially novel architecture.
1:24:01
I think this is why it was just so alien and like I had just been spending so much time in all of the the various like subcomponents and and disciplines there.
1:24:10
It's like there's this really unusual combination when you combine all these things together.
1:24:13
you get this totally new architecture.
1:24:14
So, uh the big one for us is like transition up to what we call a ramjet mode. Yeah.
1:24:18
So, you like there are really good solutions for like I really like what the Hermes guys are up to.
1:24:24
Um like there's definitely other good solutions out there but this it hits this kind of interesting sweet spot where like we're getting a lot of performance with a relatively I mean it's still millions of dollars but like relatively inexpensive system.
1:24:33
And the other thing that comes up a lot is like people are seeing all the engine stuff and yeah, you know people think we're an engine company.
1:24:41
was more it's like if you want to have a computer you have to make the microprocessor first. Okay.
1:24:44
Uh but this round getting this done is like finally shifting it to us going into the aircraft development. So Okay.
1:24:51
So you're building a plane. Yeah. Yeah.
1:24:52
I mean that's my background.
1:24:54
Like I was a plane guy that just needed a better engine. Better engine.
1:24:58
Uh and so yeah, we're we're at that stage now with the round done.
1:25:02
Um you know and like people had always seen me kind of like I was like this guy in San Francisco that was like I had a machine shop at a manufacturing business previously.
1:25:09
like people knew I was good at building stuff.
1:25:11
Um, but we've had just this like compounding effect of like the the talent that I have been very lucky to accumulate here and just the people that have joined on cuz like good engineers see an interesting like technical solution and thing to work on. Yeah.
1:25:25
So, I mean I I love my team.
1:25:28
Everybody's like incredible here.
1:25:29
So, like we've now got that that then makes it easier to get more capital. Yeah.
1:25:32
Then we've spending some time in DC like Andre's been been great with this and and like you know you it's also very important to have an actual customer.
1:25:40
I think this is the other way where I came from more of a small business world and like I wasn't interested in just I don't know like developing things for the fun of it.
1:25:49
Like I what I'm hearing is like you like maybe the company's like very clearly at this moment shifting from you know science project that you would have worked on for free to like okay like real commercial opportunity. Let's go. Let's go full send.
1:26:03
So yeah, I mean in a nutshell it's, you know, make the engine.
1:26:07
So you go in the initial like demonstrator phase.
1:26:09
So demonstrator the engine that got the money to now build the demonstrator aircraft.
1:26:12
The one we're pushing for is the world's first non-stop transpacific non-stop supersonic aircraft.
1:26:18
So we could do, you know, California to Taiwan without refueling in under four hours. Okay.
1:26:22
So it sounds like direct competitor boom.
1:26:28
It's been a decade in boom. Really?
1:26:28
So, so yeah, I mean, you know, Blake's going for like airliners and he's he So, we're we're focused on again my world is more private jets and really So, is this a GFream?
1:26:40
Are you are you coming for GFream or or or you know, let's get It's more like we're coming for net jets if you know something like that. Sure.
1:26:48
We're going to spend the next seven to 10 years doing DoD. So, interesting.
1:26:52
Like like you need to have an actual It's so expensive to make an airplane.
1:26:56
It's not hard to make a thing fly.
1:26:56
It's hard to make a thing fly that is safe enough to put people on it.
1:27:00
So my strategy on this is you go to a space like well you know unmanned drones military where like technology and capability matters first. Yep. Totally.
1:27:09
You can prove it out there.
1:27:09
You can you know there's going to be things that are going to come up and you're going to learn it.
1:27:13
It's just it's a cheaper place to learn. Yeah. Yeah.
1:27:15
Then you're in a position where like well when you have an actual business you've been making I mean the the drones unmanned aircraft we're making are like at the smallest 20,000.
1:27:23
Like they're not small planes. Yeah. Yeah.
1:27:25
Uh, and and I'm curious is is the right place if you're developing a new airplane to start with, you know, autonomy just because in theory after you fully develop it, it's like will pilots even be flying or they'll just kind of like I am a pilot so I have feelings on that.
1:27:43
But it is it's definitely something of like no one this is another kind of odd thing.
1:27:47
No one has ever used autonomy in the certification and development of a manned aircraft.
1:27:53
And I actually think this is one of the ways we can make it a lot cheaper because ultimately it's about getting data and proving this thing is safe.
1:27:57
The only way you really prove it's safe is you've flown it.
1:28:01
And so if you have a human on board from day one, you can't take the risks that you want to.
1:28:05
Like SpaceX proves this with Starship, but you're like, you know, the actual cost of the hardware is not that high.
1:28:09
So you're better off being really aggressive, getting things in the air, de-risking.
1:28:16
I mean again you're saying this at her of like they're making you know like the plane is a bit more rough but the point is like they can make a new plane every year and like by the time it's like if you want to get to very good things you want to do more iterations.
1:28:27
So this is our our similar strategy.
1:28:29
I mean we we develop new engines every like four months. Yeah.
1:28:30
Uh and I think Whimo kind of took a similar path where like there weren't random passengers in the back for years and you'd see oh there's a safety driver in there and then eventually they pull the safety driver out and put the passenger in the back. Exactly. Yeah.
1:28:44
you just want to spend time where you can map you can map out all these weird little edge cases things like that.
1:28:48
So so that's you know a big part of how how we tackle this and like it's so yeah you always want to go for like big lessons very important lessons as inexpensively as possible because eventually you kind of lock into a point where like everything will be so expensive that you want to have you don't want to make any any changes it's just too costly to do it at that point.
1:29:07
So that's where I think ultimately we can actually get to the passenger flight point quicker and cheaper by starting an entire unmanned aircraft business first because it's functionally quite similar in the technical challenges.
1:29:18
And yeah, we can we can de-risk it all, learn all the hard lessons.
1:29:22
Um, and you know, in the meantime, like it's also very cool just getting to make these things.
1:29:26
So, you know, it's photogenic work.
1:29:27
Everybody loves seeing the engines on Twitter and stuff like that. For sure.
1:29:30
No, it looks it looks incredible. Um, I'm curious.
1:29:32
uh A16Z make sense in the round.
1:29:35
Lower carbon was a big logo there.
1:29:38
Is uh is that Saka and his team saying like this is really cool, we want to back it or is there a uh is it a fuel efficiency, you know, kind of kind of thing in the long run? Yeah.
1:29:50
Um the so my the very first check institutional check into the company was actually lower carbon and uh Shiao at lower carbon was was my guy.
1:29:57
Um and you know he was betting on it was just me in the machine shop and like I had you know getting close to that first prototype.
1:30:05
Um and so yeah from there like the system we get the range because it is more efficient.
1:30:11
So so yeah there's just an obvious efficiency argument here.
1:30:15
The other one for civil applications not for DoD but for civil is taking a page out of the rocket book.
1:30:21
We don't plan to use jet fuel.
1:30:21
So rockets have switched to LNG or liquid methane.
1:30:25
It's if you just swapped that fuel, it's 30% less CO2 just as direct fuel swap.
1:30:30
It's more energy per unit weights, 50 mega versus 42 per kilogram. Whole bunch of benefits.
1:30:34
There's a reason the rocket folks went to it.
1:30:36
So, this is another one of those kind of insane bets for like if you're Boeing or someone like you're not going to suggest a thing like that, but when you're starting from nothing, you can you can make these these bigger bets. So, yeah.
1:30:49
Uh you know, if you were to do the combination of the engine plus the fuel change, you're around 60% less CO2.
1:30:52
And then there's guys like I love Casey Hanmer, Terraform, there's a lot of folks working on synthetic fuels.
1:30:58
If you have an engine architecture around uh you know LNG, I think that's the best fuel for electroynthesis.
1:31:05
So if you want to have like inexpensive decarbonized fuel, it's also your best option.
1:31:10
So like options first solve for economics of like LG is a tenth the price of jet fuel.
1:31:15
So first make it affordable then you can go for the clean stuff after that where I mean it is already cleaner and then you can just fully decarbonize from there or you know but first stay alive as a company.
1:31:25
So first economics then go for that. Smart.
1:31:27
Uh bit of a random question but I'm curious since you're an aviation nerd.
1:31:32
Uh China earlier this week dramatically canled some Boeing orders.
1:31:36
Uh they have their own internal uh aircraft.
1:31:39
Uh it's like Comarmac, the C919.
1:31:47
Do you see them like permanently trying to shift over to that?
1:31:49
Uh or is it just so hard to build a plane that they're going to kind of kind of keep coming back to Boeing and and Airbus over time? Yeah.
1:31:58
Yeah, it's tough to say on that.
1:31:58
Yeah. Yeah, it's tough to say on that. I would say well engines are harder and to that end we're I think you know even they're using just as we actually use Pratt Whitney and GE components things like that and what we're doing that's sort of like being TSMC that one I don't
1:32:12
think they could get figured out anytime soon and the comarmac uses you know uh still American engines so um I'm pretty sure at least so that one's harder on the whole airframe I think they could get it figured out I'm sure it just depends on how as with all these things it's just a money pit how much do you want to throw go into it. Um but but why
1:32:29
Um but but why is it so so what is what's the componentry of like the J35 then?
1:32:34
Why why can they do that?
1:32:37
But but uh which is like a you know defense application versus a commercial it it's so again to this thing of it's not hard to make a thing work and fly.
1:32:48
I mean I did this in my shop kind of as proof of like getting a thing to initially go not very complicated.
1:32:55
The economics of air travel are dependent on it never breaking and that is a you don't really know that like even Pratt Prattoon with a recent gear turbo fan is like it's going to be like a decade until they get payback on that and they know how to make things like that.
1:33:09
So this is the sort of challenge you run into of you know what is going to come up you know after 5,000 hours after 10,000 hours and it turns out this thing it's like oh there's cracking on this component and now the engines and like meanwhile use what we've got right now.
1:33:24
like, "Yeah, it's good for 30,000."
1:33:25
Like the CFM56 was like it's like 50 to 60% of all airliners um or narrow body ones.
1:33:30
And like that engine can stay on wing for almost 30,000 hours. And it's just so proven.
1:33:38
And this is this thing you see in aviation where like there's always these things that seem really appealing because it's a performance optimization.
1:33:45
You're like, "Well, of course I want to burn less fuel."
1:33:46
But when you try to implement this thing that's technically better, it's like, yeah, but it turns out it broke at some slightly higher rate and you already had terrible margins and now it doesn't work.
1:33:55
So that's where that that's going to come up.
1:34:01
Um, it's just not something that's like obvious on day one. Mhm.
1:34:03
Well, congratulations on the round.
1:34:07
Congratulations to you and the whole team. An overnight success. Overnight success.
1:34:12
Uh, thanks for coming on.
1:34:14
Seriously, I appreciate you coming on and breaking it down for us. Thanks so much.
1:34:17
Yeah, we'll talk to you soon. Bye.
1:34:19
Uh next up we have Sham Sankar from Palunteer.
1:34:21
There's a ton to talk about with him.
1:34:23
Uh he's uh published 18 thesis about the defense reformation, the primacy of winning uh and also just sits in a very interesting place as Palunteer's first uh forward deployed engineer.
1:34:36
And so I want to hear uh what he's hearing from Palunteer customers mostly.
1:34:40
Uh anyway, Sean, welcome to the show. How you doing?
1:34:43
Thank you guys for having me.
1:34:44
Yeah, thanks for being here.
1:34:46
Uh, yeah, I wanted to kick it off with um what is the biggest topic of discussion over the last two weeks?
1:34:53
Tariffs, H20s, Nvidia, something else.
1:34:57
Uh, what is driving conversations through the partners that you work with at Palanteer?
1:35:04
I think the is enterprise autonomy.
1:35:04
You know, it's like there's a normative view of that the most valuable application of AI is is clearly towards autonomy in the enterprise.
1:35:13
Uh, and then you can think about it, you can reason about it by analogy.
1:35:16
If you thought about the self-driving car journey, it took us 20 years to get from a prototype that drove through the desert 120 miles, pretty good demo in 2005 to a commercial self-driving car service.
1:35:27
And no one wants to be on that 20-year journey.
1:35:30
What What have we really been doing over 20 years?
1:35:32
We've been handling edge cases. Yeah. Right.
1:35:33
really investing in the tool chain that allows you to get from uh a mandrlic world to one where you have AI agents that are totally automating your business.
1:35:43
Like we've automated sepsis monitoring at at Tampa General where they deaths from sepsis have reduced by half.
1:35:49
Uh we've automated how how AIG underwrites insurance.
1:35:51
What used to take three weeks and you'd only get to 10 weeks 10% of your submissions.
1:35:58
It takes less than an hour and you get to 100%.
1:35:59
So I think and it really is going to feed into this winner take most dynamic.
1:36:03
It's not just about cost savings, about your competitive advantage.
1:36:06
And you see that play out in very stark and real terms in defense where in some sense there's nothing new under the sun.
1:36:12
There's just John Boyd's udaloop observe, orient, decide, act or as sometimes my favorite admiral says the American udaloop, observe, overreact, destroy, apologize.
1:36:21
But how do you how do you bring um lethality to that?
1:36:27
It's just doing that much faster.
1:36:29
And you're going to do that way faster with AI. That's amazing.
1:36:30
Uh uh Tyler Cowan called uh April 16th yesterday AGI day. He has called it.
1:36:36
Uh what was your reaction to the open probably happened internally at Palanteer like you know months ago months ago.
1:36:43
Uh but yeah I mean how are you processing this idea of AGI?
1:36:47
AGI? Obviously it accelerates everything you're doing but um what is your take on model scaling reasoning uh agentic workflows all these different things like what are you looking for where where are there breakthroughs breakthroughs that remain versus what are we just need to go implement well I think we're well past the threshold
1:37:05
where the models are powerful enough that you can be using them to automate massive things I think at this point really incremental improvements to the model changes how you decomp the problem how many agents do you need do you need 80 because you've demped it in a way where it succeeds or do you need eight? Uh like the coolest stuff that I've been
1:37:18
Uh like the coolest stuff that I've been seeing is like multiple teams internally at Palunteer are building AI FTEEs and it's really compelling. It gets really far.
1:37:26
It attacks different parts of the stack, you know?
1:37:28
So like if every user could have their own ondemand infinite essentially AI FTE like how much more stuff can you build?
1:37:35
How much more quickly can you adapt?
1:37:36
What's your udaloop as a company now?
1:37:37
So I think we're deep in the the implementation phase.
1:37:41
If AI is electricity, like in electricity, all the value didn't accrete to the people who made the turbine generators.
1:37:46
It went to the people who made the tools that ran on electricity.
1:37:49
And I think there's just we're just so excited about proliferating and building those tools out. Yeah.
1:37:54
Uh how are you thinking about uh just commoditization of the model layer?
1:38:00
Obviously, it's like a horse race.
1:38:01
Every different month the different models comes out.
1:38:03
Uh how has Palunteer approached integration with different uh foundation models?
1:38:08
And then is that the same as other kind of databases and different tools that might be deeper in the stack or like the even the migration to the cloud?
1:38:18
Does this feel like cloud to you?
1:38:19
Does this feel like mobile to you uh in terms of like your agnostic approach or is it different in any way?
1:38:25
Um there are parts that definitely rhyme with it.
1:38:28
It's more agnostic than not.
1:38:29
I said early on in the AI revolution that we thought the right approach was K LLM.
1:38:33
Like why would you pick one LLM when you can have K?
1:38:35
Um and then you really can start thinking about the tool chain that you need to build around that.
1:38:40
There's numbers there's a number of reasons at first like very clearly you've had model commoditization.
1:38:45
If you look at both open and closed models over time you know the ELOs are just up and to the right.
1:38:50
Uh the open ones have converged and even in some cases surpass closed models and at the same time the price of inference has dropped like a rock.
1:38:56
So that's clearly happening and you even see that in the frontier model companies where they're they're expanding further and further into the app stack because they realize that selling you a raw API is probably going to be a raw business. Yeah.
1:39:09
Um so then there's a question of like okay you're just being very pragmatic if you if you're building the machines running on this like what model is right for what job?
1:39:17
Uh the models are improving rapidly.
1:39:19
How are you going to safely be able to evaluate uh the the the relative performance of models as new models come out?
1:39:25
new models come out? So you need you need that sort of tool chain and even more uh deliberately you know these models get end of life like you can't get the original GPT4 anymore right you have 40 and so if you've built an entire enterprise that runs assuming some model
1:39:42
is going to exist in perpetuity that's probably not going to work out that well for you so you're going to have to have this constant ability to evaluate and and run these models in parallel to develop the conviction you need not only for the optimization of what's incrementally better But can I safely migrate in the future? How are you think
1:39:57
How are you think about uh integrating robotics?
1:39:59
about uh integrating robotics? It feels like AI today is just rapidly transforming the way work is done online specifically knowledge work but how are you thinking about you know what's your vision 20 2030 and kind of beyond about
1:40:15
you know how um different robotic systems are are integrating with the palunteer system specifically the example you mentioned earlier around sepsis monitoring is like cool that's one you know sort of hardware integration but it's not its own autonomous you know system uh out in the world. In many ways, we already do this.
1:40:31
In many ways, we already do this.
1:40:34
You know, we have like more than 300,000 workers, blue collar workers who turn wrenches in our software every day.
1:40:39
Everything from the factory floors of Chrysler to every Airbus airframe, every HD Hyundai ship.
1:40:42
If you think about a company like Rio Tinto, so much of the mining operation is actually autonomous.
1:40:49
The the railroad cars that that take iron ore from where it's mined to the ports, that's completely autonomous.
1:40:53
The the threetory tall dump trucks that are actually trucking out the ore, autonomous.
1:41:00
And so it I don't want to trivialize it, but in some sense to me it's more of like a difference of degree than kind.
1:41:05
You're you're you're machine to machine communicating to a system.
1:41:09
That system just happens to be smarter and smarter every single day. Huh.
1:41:13
During the metaverse boom, Sachin Nadella was talking about building digital twins.
1:41:16
Is that an unnecessary abstraction or like reference point for humans or is there some actual value in representing all of these real world assets like the Riotinto mining example you gave in some sort of like virtual space or does it not matter and it should all just be weights in a model that we're querying through an LLM or something like that?
1:41:37
Where I think it gets to be really valuable is if you kind of thought about it like a CI check in programming where it's like I'm I'm proposing a change to a system here. How can I understand it?
1:41:46
like is that change going to work?
1:41:48
What are the unintended consequences of it?
1:41:49
If I make that change, what are the new bottlenecks that different functions have to think about?
1:41:53
The simple example I always use is the procurement guy is really excited because he bought, you know, discount raw material 30% off list price and the production guy is pissed off because this discount material has 40% less yield. Right?
1:42:06
It is at the end of the day one value chain and where the digital twins have been hugely valuable is the ability to integrate the chain and the decision-m across it.
1:42:13
So you know when the left hand is is robbing from the right hand.
1:42:17
Can you talk about the early days of Palunteer?
1:42:19
Maybe one of the first major wins or setbacks or kind of like what's the story that you tell to new Palunteerians to kind of set them up for maintaining the culture because I feel like Palanteer's done a great job of like maintaining the quality bar.
1:42:34
You haven't become that place where people kind of go and like rest invest basically but you are like kind of a big tech company now.
1:42:40
Um, what's the story that you tell to kind of set the culture?
1:42:44
I mean, there's so many stories.
1:42:46
I really I'll tell you how I set the culture at the end. I promise.
1:42:49
But I think one of one of the things that I felt like we kept getting punched in the face in the early days on is that someone else's execution would end up screwing us.
1:42:56
Like I I remember we had this gatekeeper between us and a government customer and he installed an early version of our software um and he wanted to test it out before he passed it on and it crashed and he blamed us and it and it crashed.
1:43:08
and it and it crashed. I mean in those days this was a server with two gigs of RAM uh trying to run a 4 gig Java heap and he didn't understand why it crashed right like we just developed this extreme ownership mentality because anytime we outsourced even an iota of responsibility it blew up in our face
1:43:25
and that's you can see for deployed engineering as like the extreme manifestation of that that we're going to somehow have total control over the implementation because that's how you get the feedback and the quality and the improvement and you're actually responsible for your own destiny. Uh but
1:43:37
Uh but the the the story I tell to kind of spill the beans on.
1:43:41
So your your first um AMA with me when if you're on boarding in week one at the I always end the AMA by reminding people that counter is a flat place.
1:43:50
What does flatness even mean?
1:43:52
Well, to me it means that every single employee is willing to tell me to [ __ ] off to my face and I them all say [ __ ] off in unison out loud at the very end. I think it's important.
1:44:02
I want to institutionalize the notion of rebellion that you know I don't have all the right ideas.
1:44:07
ideas. There's so so many things we've done over time I didn't think were going to be right and they were right and you know you got to bet on talent and the people and give them the space to run and really preserving what what's at the core of this is like this is an artist colony not a factory you know I I don't
1:44:21
really know what your career pro progression is going to be and if you want certainty on that this is definitely not the right place but I can promise you you'll have access to the most motivating problems and compelling colleagues and I'll give you all the canvas and paint that you need. Yeah. Yeah.
1:44:35
Can you talk about uh what's going on with the cultural transformation in Washington right now?
1:44:40
Uh you've written like maybe it's transformation going into founder mode uh but within some of the more nitty-gritty uh maybe swampy institutions.
1:44:50
Uh is is there a need to be able to tell each other to f off or uh just be more confrontational?
1:44:55
Uh what should DC learn from Palunteer and maybe even vice versa?
1:45:03
Well, I I don't know if DC I would say is it seems like very assump presumptuous for me to say what should DC learn from.
1:45:09
But what me about the present moment is in Palier terms the primacy of winning like you feel that in the people there they understand that they're working backwards from what could actually work instead of some anodine notion of how we wish the world works but doesn't.
1:45:23
Um and that's like allowing us to reexamine a lot of assumptions from first principles.
1:45:28
I think founder mode is the best description of it when I talk about so conserved across commercial and government kind of our diagnosis of the current legitimation crisis.
1:45:37
Why do doors fall off airplanes?
1:45:39
Why does it seem like these institutions aren't working?
1:45:43
Um you have a seauite that is if you steelmand it diligently trying to steer the ship and their steering wheel what they don't realize is a prop from the Jungle Cruise ride in Disneyland.
1:45:55
it's not connected to anything.
1:45:56
And then you have people, hardworking people on the metaphorical factory floor who kind of look up and say, "How could they be so disconnected?
1:46:04
How could they not understand what's actually happening here?"
1:46:06
Uh, and so much of that is like the levers of orientation are somehow filtered through a lot of people in the middle.
1:46:12
Uh, leadership doesn't have access to real-time information.
1:46:14
If you if you couldn't, you know, like if you were navigating a car and the latency of understanding where you are was an hour, you'd crash it.
1:46:22
And and so like this sort of manager mode playbook, it works really well for the managers, but it's like a way of having a well-managed company into the ground.
1:46:31
Yeah, we need more like uh individual champions.
1:46:34
Peter Teal has that quote about like we need ticker tape parades.
1:46:38
Uh Ezra Klein is now talking about with the abundance he's he's uh he's highlighted the failure of the California highspeed rail system.
1:46:46
And what I found interesting about that is that it's very hard to pin down like California highspeed rail.
1:46:51
Everyone kind of agrees like the project's not going great, but no one can really say like who is even the champion of that at any point in time?
1:46:57
Like no one's really responsible at any point in time.
1:46:58
Um does does the government need more individual accountability or like I don't even like project level CEOs or something? I don't know. Well, yes.
1:47:07
The short answer to that is absolutely yes.
1:47:09
Like I I think about it in terms of heretics and heroes.
1:47:13
You know, it was Somerville who built the Pentagon in 16 months.
1:47:15
You know, it was Jean CR who led the Apollo program.
1:47:19
There's something about our kind of Midwestern Calvinist sensibilities as a country where like it's the Apollo program and not Jean CR, it's the F-16 and not John Boyd's plane, you know, it's the nuclear navy, not Hyman Rick Over's Navy. That's great.
1:47:31
I appreciate that sensibility tremendously, but it shouldn't uh obscure the fact that actually these projects working or not come down to a handful of really exceptional individuals being present, taking ownership and and leading the way. Yeah.
1:47:47
Um uh can you give me a little bit uh expanding on that, can you give me a little bit of history on the dollar a year men and that story?
1:47:52
Yeah, in in World War II, we actually had a program for uh very skilled people corporate leaders, engineers, they could for a dollar a year because volunteerism was illegal.
1:48:06
You could not volunteer to work for the government.
1:48:08
So as we were preparing to go to war, as we went to war, uh they would actually join the government as dollar a year men.
1:48:12
they would get one dollar of salary uh and they they would actually be able to be deployed on the nation's most important impactful problems.
1:48:19
Um and uh sometimes they would retain their old job, sometimes they wouldn't. It would really depend.
1:48:25
Uh but you could get the right person on the job.
1:48:27
And I I think that's really important because if you think about even World War II, our mobilization came down to one man, William Nudson, a Danish immigr who actually invented mass production.
1:48:37
He was the number two at Ford where he invented mass production.
1:48:40
He got in a fight with Henry Ford and went to GM as the number two.
1:48:43
And you know FDR asked Bernard Bar, who should I choose to do this?
1:48:50
He said, I have three names.
1:48:51
William Nudson, William Nudson, William Nudson.
1:48:53
It's like it really came down to a counterfactual.
1:48:55
We had like one guy who could actually move all of American industry.
1:48:58
And the way that he assessed, you know, he was an engineer himself.
1:49:01
He would like meet people and understand like is it believable that you as a steering gear company can start making artillery or not?
1:49:08
Are your engineers smart enough?
1:49:09
Do they can they answer my questions? Boom. Here's a contract. Let's get going.
1:49:12
Uh, and you know, it wasn't a fiction writing contest.
1:49:15
It was really a a pressure test, mind-to- mind. Interesting.
1:49:20
Can you talk about the executive order from last week, the defense reformation?
1:49:24
You had a great post on it, but I'd love for you to kind of break it down live uh for the audience.
1:49:30
I think it is the single biggest change that could prepare us to avoid World War II here.
1:49:35
avoid World War II here. uh you know if you look at um you know what has happened to the US since we won the cold war we've really had the rise and empowerment of this monopsiny a single buyer that is the government and an addiction to uh that monopsiny telling us what to build at what price and how it's all going to work that's very different than the free market you know
1:49:57
at some fundamental level you either believe in the free market or you don't and I like to quip that you know everyone including the Chinese and the Russians had given up on communism except for Cuba and the DoD we still have five-year plans, you know, and and this this luxury of having the monopsy grow to the scale it has is a consequence of having no peer competitor. But that, you know, that
1:50:15
But that, you know, that world really went away arguably in 2014, the militarization of the Spratley Islands, the annexation of Crimea, uh Iran's pursuit of the bomb, like deterrence is lost and we need to rise to that.
1:50:28
And I think this is a clear acknowledgement of of very much that in this administration.
1:50:31
But the EEO says, uh, we prefer to buy commercial items.
1:50:36
We we prefer to buy items that have been proven in the market that have that have to withstand brutal competition that happens out there every day that, uh, reward entrepreneurs for what they're building rather than custom building and developing things on our own.
1:50:48
And we have a we have a long history.
1:50:50
You know, a monopony is always going to desire control, but it goes all the way back to Andrew Higgins and the boat that won the war in World War II.
1:50:58
Andrew Higgins uh was a guy from Louisiana.
1:51:00
He spent some time in China and he was inspired by bootleggers in China and the sort of boats they had for amphibious landing to quickly land, get goods off, get goods on and then scurry away.
1:51:10
Uh and at his own expense, he built the Higgins boat.
1:51:15
Um and he he showed up he showed it to the Navy.
1:51:17
The Navy wouldn't even let him compete.
1:51:19
They kind of dismissed him.
1:51:21
Then a young marine who became very famous, Kwick, he later he got him into the competition.
1:51:26
he won the competition and then instead of buying the boat, the Navy stole the uh sold the plans and tried to build the Higgins boat themselves, which they failed to do.
1:51:33
Um and then finally, you know, at the at the 11th hour, of course, we do the right thing.
1:51:39
That's classic American trait.
1:51:40
And uh and Eisenhower said, "That's the boat that won the war."
1:51:42
And so you you know, the Predator was developed as a commercial item.
1:51:45
It was not developmentally done inside of the government.
1:51:49
It was a Kareem built it.
1:51:49
Um General Atomics picked it up.
1:51:51
They financed all the R&D themselves.
1:51:53
You know, the Air Force of course hated it because it was unmanned.
1:51:58
It was kind of emasculating and uh you know, when 911 happened, it was the thing that met its moment in a in a massive way here.
1:52:05
Uh and there's so many examples like now we have whole companies built around this companies like Androl.
1:52:10
The entire approach is commercial first, investing private taxpayer capital into R&D, absorbing putting the pebble in the right shoe, you know, putting the pebble in the entrepreneurial shoe rather than in the taxpayer shoe.
1:52:21
So this EO it's actually this law in 1994 we passed the law called the the FASA the federal acquisition streamlining act that said it is the law that if a commercial item exists you must buy it. Yeah.
1:52:31
Uh it's actually a very stringent test three-part test.
1:52:35
So if a commercial item exists that meets your requirements you must buy it.
1:52:37
If it doesn't you must see if you can change your requirement to meet the existing commercial items that do exist.
1:52:44
And if that's not possible you must see if you can ask the company to change their product to meet your requirement.
1:52:49
and only then are you allowed to go custom developmental.
1:52:51
So, this is the most violated law in the land.
1:52:54
And I think having the administration say, "Look, this is statute and we agree with it and we're going to enforce it is is how we're going to field a huge amount of deterrence between now and 2027."
1:53:03
You know, there's not a lot of developmental things you can do between now and then.
1:53:08
There's a huge amount that you can do with the innovation of entrepreneurs and the commercial industry. That's amazing.
1:53:14
Um, do you feel like uh cyber warfare has been too normalized on uh on this planet?
1:53:20
It feels like, you know, you have a major cyber attack and maybe you hear about it on X because somebody says they can't log in to Zoom or something like that, but it doesn't even make the mainstream news.
1:53:28
Meanwhile, there's any type of sort of kinetic conflict globally.
1:53:32
It's like immediately front page or it's on CNN, things like that.
1:53:37
Um, and do you think there's ever a point in the future where people start to view them and and and countries truly view them with the same level of significance as everything sort of continuously sort of comes online.
1:53:50
I think you're spot on that some there's something very strange in how little we talk about it and they don't photograph well.
1:53:57
Yeah, it doesn't photograph well.
1:53:59
It doesn't photograph well. What picture?
1:54:01
My concern is that in the future if we have a 100,000 humanoids, you know, roll, you know, going around a single city and suddenly they all are stopped, that will start to photograph pretty well.
1:54:12
And so I imagine in the future it won't be uh just kind of brushed under the rug and and yeah, of course, you know, companies have to respond to it and the government responds to it, but I just imagine at some point it will start to really be news.
1:54:26
One of the most devastating consequences of it being so kind of below the waterline, something we don't want to talk about is the normalization of like what can you do about it?
1:54:33
a sort of nealism and acceptance, a pessimism that anything can be done about it, which is obviously not the necessary precondition to like rising to the occasion and we should have very high standards for what could be done about it and not this.
1:54:46
Of course, this company got breached or this thing happened and all these people have my information all the way to, you know, sure our water systems are compromised and, you know, we'll be brought to our knees within the first few days of conflict.
1:54:58
like we should just we're not able to hold ourselves to the high bar that we ought to because it's it's not popular and we're not popularizing it as a concept.
1:55:06
I mean speaking of popularizing just general shifts in uh in thought about defense and the importance of like uh public private partnerships in the government.
1:55:15
Uh can you talk can you take us through the defense reformation 18 thesis the your thesis there uh and then kind of the impact and uh is is it a jobs not finished situation or uh has has defense tech become enough of a meme now?
1:55:30
It seems like Silicon Valley is like fully on board in my opinion but uh at the same time there's a lot more that we could do.
1:55:37
Yeah, I think we we've earned the right to uh to to have an at that, you know, so like we got to perform now for sure.
1:55:45
for sure. Um I I'd say the fuller di I've touched on some of the themes but the fuller diagnostic is um the government has kind of historically made it a bad business to work with the government you know and you think about like our examples from the past like at Intel Bob noise would not let more than
1:56:01
4% of his R&D budget come from the government because he as the inventor of the trans transistor wanted engineering control over the road map and what he was going to build he always had in mind a broader commercial market that was going to drive the price performance
1:56:13
that was needed even though in 1969 something like 96% of his revenue came from the Apollo program and DoD you at that point they looked like a government contractor but that was not his aspiration was bigger in the same way that Elon Musk's aspiration for SpaceX has always been to get to Mars
1:56:30
and to make us an interplanetary species you know it's not just about launching rockets and satellites into orbit here um and we really lost you know so much of defense innovation you know Kelly Johnson who built 40 plus airframes in his career including the U2 2 which we still fly and the SR71. Uh he is this
1:56:45
Uh he is this heroic figure.
1:56:49
So much of this innovation has come from these legendary engineers, these heretics as I call it today.
1:56:54
You think about it as Northup Grumman, but it was Jack Northrup and Leroy Grumman.
1:56:57
You know, it was not Lockheed Martin, it was the Lockheed brothers and it was Glenn Martin.
1:57:00
Uh and it was really so founder driven.
1:57:03
The aerospace industry subsidized its own existence in the inner war period between World War I and World War II because the government didn't think it needed it.
1:57:13
So you know but for private industry being willing to lose money for a decade plus World War II we would have been in a very very bad place.
1:57:19
Uh and what excites so I think the last supper people look at the last supper which is this dinner at the Pentagon in 1993 where they said hey look we have 51 primes today you guys are not all going to survive today we have five.
1:57:32
Um for every dollar we were spending in defense we started spending only 33 cents overnight.
1:57:39
It was it was a huge cut the peace dividend as it's called. Yeah.
1:57:43
Consequence that conventional people take away from this is, oh, that's when we lost competition.
1:57:46
We went from 51 down to five.
1:57:48
I don't think that was the the actual issue.
1:57:50
The real issue is that consolidation bred conformity.
1:57:53
And the conformity pushed out all the heretics.
1:57:57
It pushed out all the founder personalities that you need to make this stuff really work.
1:58:00
My reason for immense optimism in this moment is that the founders are back.
1:58:06
You know, more than hundred billion dollars have been deployed in the national interest. You have Palmer Lucky.
1:58:11
You have the Sang brothers at Shield AI.
1:58:13
You have Dino and Seronic.
1:58:15
You have all these crews of really, really compelling humans, really, really compelling founders working in the national interest.
1:58:21
Again, pursuing heretical ideas, will waking up every day, banging their head against the wall, you know, fighting the bureaucracy to do what's right for the men and women in uniform and for the nation more broadly.
1:58:32
Can you talk a little bit about the startups that are building on top of Palunteer and take us through AIP? Yeah.
1:58:39
So, we've always it's a little abstract, but I I've always felt like the ontology, which is our secret sauce, is it's it's really you can think about it as like a declarative backend.
1:58:46
It's a way of saying, look, this is the shape of not only my data, but the logic of my enterprise, and that's all you have to do, as opposed to the imperative approach of having to actually go create and wire this up and do it together and figure out how to get it to scale.
1:58:59
And so, if you if you had this declarative back end, if you could just say, look, this is what I need to exist in the world.
1:59:06
Now I can build applications on top of that that manage and all of the entropy that usually sits behind it and it gives you a radical speed advantage uh for these companies.
1:59:15
So these these companies are building everything from like the European Cricut network to people who are building uh pharma companies, hospital operations companies.
1:59:22
Uh in defense it's it's very popular because we can give you an SDK that wires you into 20 years of data that has been integrated into the instances of Palunteer that exist in the defense community that your users can authenticate to.
1:59:35
So, it just speeds a lot of the kind of brain damage you would get from having to to deal with the bureaucracy and allows you to compete on the quality of your product rather than your game and getting through the wickets of a Byzantine process that probably needs its own reformation.
1:59:49
Um, but it's really about speed I and that that ability to build on top of the platform.
1:59:54
It's not just for thirdparty developers.
1:59:55
When hurricane Helen happened in North Carolina, green suitors like folks in the army in the 101st built their own they built their own hurricane common operating picture on top of the platform.
2:00:07
So that ability to respond to the need it's it's our it's the code version of the udaloop. Yeah.
2:00:12
Uh what advice would you give uh somebody maybe graduating college today that's um evaluating joining you know maybe a seedstage company versus a a scaled company like Palanteer or or or something like an Anderoll.
2:00:27
something like an Anderoll. I imagine you at times had a ton of different pressure from VCs being like leave we'll give you 10 million bucks to do whatever you want like don't you want to be a founder yet when I look at opportunities
2:00:40
you know in anything defense related it seems like if you have a finder ma founder mindset there's so many great opportunities to just go to a great company and kind of uh take on that sort of like founder level ownership over a specific problem area or product set or things like Yeah. I mean, I think the of course I'm
2:00:59
I mean, I think the of course I'm I'm biased here, but if I if I get would give general advice, the way I would think about it, what I would tell my son is like where can you go that you're going to work with the most compelling people because like your rate of learning is going to be a function of those people and have access to the greatest surface area on problems.
2:01:15
Like my model for growth is not progressive overload.
2:01:20
You know, the Incredible Hulk did not become incredible by just lifting a little bit more weight every single day.
2:01:25
It's like a near fatal dose of gamma rays that probably has like a 50% chance of killing you.
2:01:29
So which upgrades are going to like throw you off the deep end and give you that opportunity to have like superhuman superhero growth.
2:01:36
That's like that's the value maximizing thing.
2:01:38
And I would remind my son that like your point of of extreme growth is going to be coincident with your point of maximal pain.
2:01:45
So like your ability like you know it's like it as Greg Lemon says one of my favorite quotes championship cyclist it doesn't get easier you just go faster you know it's just just understanding that like that's what it looks like.
2:01:58
So don't don't sell out for the opioid of a linear career progression with a clearly mapped out path.
2:02:04
I'm pretty sure that's retarding.
2:02:06
Like that's lead shielding that's preventing the real gamma rays from getting to you here.
2:02:09
You know find places you can throw yourself off the deep end.
2:02:12
And I I I bet there are some sestage companies that are perfect for that.
2:02:16
I bet there's some CG companies that are horrible at for that.
2:02:18
You know, it really is pretty specific.
2:02:22
Does that tie to the the primacy of winning mentality?
2:02:24
Is is that like all is that essentially like derivative or like the same concept?
2:02:29
Yeah, I think it's it's it very much relates to that and I think I think it's like one of the things that I had to I feel like it's one of the most important things I learned at Palunteer.
2:02:37
You know, we're all kind of programmed in our conventional education to feel like there's a process, there's an approach.
2:02:44
if you follow his playbook, you know, you'll win.
2:02:45
But it's actually like uh it starts to conform to how you wish the world would work.
2:02:50
It becomes hard to decide is that actually the cargo cult or is that how the world does work.
2:02:54
Like you can keep marching around these fields in Micronesia, the planes aren't coming back.
2:02:59
You've misunderstood the physics of the universe here.
2:03:01
And and just if you just anchor yourself like, but is this working? Like is it winning?
2:03:07
And then blow up anything that's not working.
2:03:08
Okay, last question on cargo cultting.
2:03:11
cultting. uh cargo cultting the forward deployed engineer good or bad when does it work when does it not work who should be doing it well I think all cargo culting is bad so I think that that would be you know it's um I think the
2:03:26
for deployed engineering methodology is uh is exceptionally valuable a's description of it is the best one I think it's like solving through back propagation it's very elegant metaphor um but if you just slap a veneer on it where it's like sales engineering done. My favorite things like ex-punteers will
2:03:44
My favorite things like ex-punteers will be like people are asking me like what is an echo and I will describe an echo and they'll be like so you mean customer support customer success and it's like wow you've lost the essence of this whole thing this beautiful concept you've you've completely cargo culted away. Oh no.
2:03:58
Uh well thank you so much for stopping by.
2:04:01
This is fantastic interview for having me guys. Yeah, this is great.
2:04:04
Have a have a great rest of your day and we'll talk to you soon. Cheers. Bye. Fantastic.
2:04:09
So many great stories and man like encyclopedic knowledge of American history.
2:04:16
There's so many times we need to have him on for Yeah. Yeah. Of course.
2:04:20
Loheed and Martin like I I know their first names.
2:04:22
I don't know first names.
2:04:24
I need to brush up on their stuff.
2:04:25
I need to do some like space repetition, some flashcards or something.
2:04:28
Um but uh next up we have the founder of Starship coming in to the building. Welcome to the show. How you doing? Boom. What's going on? Hello. Good to meet you all. I am doing fine.
2:04:40
super exciting thing and I like it. Yes, thank you.
2:04:43
Uh would you mind uh kicking us off with just a little bit of background on the company and explain uh not just what Starship is but kind of uh the the the footprint, the rollout, the strategy, all of that. Yeah. Yeah. Yeah. All right. Yeah. Sure.
2:04:56
So what we are doing we are uh we are a company del developing and building and operating delivery robots. Yes.
2:05:02
So robots that transport stuff like you know and stuff that means you know burgers, milk, you know could be you know packages and so forth, right?
2:05:12
So in science fiction movies you know you don't see UPS guys knocking on your door. Mhm.
2:05:17
You see things coming to you, things flying to you.
2:05:22
That's the future that we are building.
2:05:23
That's the present that we are building.
2:05:25
And uh uh we have many competitors as well who have who we have inspired to do similar things you know with drone deliveries and so forth.
2:05:34
Beardwing is on the ground but robots that drive on the ground small robots that drive on the on the ground and uh uh we are we are actually not like a like but many people think that you know this sort of futuristic thing is like a pilot or test you know somewhere in some limited area or something like that.
2:05:50
We are actually in full commercial operation with thousands of robots in hundreds of locations.
2:05:56
It might not be you know we are not not there not yet in every place that you know all of this audience that's listening to this right now is but we are in some places and in in some of these hundreds of places that we we are in uh you know our robotic delivery is completely commonplace.
2:06:14
It's something that people are completely accustomed to.
2:06:17
It's something that uh you know people don't really use you know like human couers to to to deliver things they use robots. Yeah.
2:06:26
Um can uh can you talk about all the different things that you've seen around the way humans treat robots?
2:06:30
I try to I try I I try to say thank you to robots you know when when they help me out with different things.
2:06:36
But some humans, you know, we saw this with a lot of vandalism of We saw this, you know, bird, the big thing with bird vandalism in LA is I think a lot of birds issues locally here just came from a culture of vandalism.
2:06:50
You did the hard thing in making sort of cute robots, which I I think uh probably helps.
2:06:54
But uh how is how do humans kind of present a challenge to trying to like automate delivery, which should be in everyone's best interests?
2:07:04
We get that question a lot but we don't actually get a lot of vandalism itself.
2:07:09
Uh you know the the the the truth actually is that people really love our robots.
2:07:15
Yes I see that you know with like scooters and you know some of the other modes of transport people don't really treat them nicely but they actually do treat our robots really nicely.
2:07:26
Like for example you know you know we often you know get the question that oh you know are your robots stolen?
2:07:33
And uh actually none of your ro our robots have ever been stolen from the street and we have done 8 million deliveries like we are doing millions of deliveries and it's just not happening you know kids feed our robots bananas so the the the treatment is completely
2:07:50
different than with you know like scooters for example I understand you know that's you know that's actually a lot we get that that question actually a lot like people you know sitting in you know sitting at the table very often and say that you know I treat things nicely
2:08:05
but there are some other humans out there that do not treat things nicely just like you said right you know but it's not actually happening it's not actually happening you know like how often do you vandalize like a you know UPS vehicle you don't really right you know sure you can do it yeah you can
2:08:22
puncture puncture the tires of a UPS vehicle you don't really do it right you know and you know our robot actually our robot has 10 cameras it's constantly connected to the internet It's really It has a really loud siren when it's tampered with and so forth. It's not
2:08:35
It's not actually really happening.
2:08:37
Well, can you can you uh talk a little bit about the roll out maybe because um I I think that the locations in which the robots are doing deliveries is like really going to impact right if you're rolling through a suburb and it's a you know familyfriendly neighborhood something like that the robot is going to run into different challenges than you know rolling down you know a street in in Manhattan for example.
2:09:00
So how how have you guys approached your kind of like go to market uh and kind of picking what regions uh are are are you know sort of top of the list in terms of uh getting robots on the ground. Yeah, great question.
2:09:14
Uh we are operating our robots in at 60 cities and 60 college campuses. Mhm.
2:09:22
Mhm. So we have learned a lot about different environments and uh yeah like different neighborhoods are completely different like there's a lot of difference in the world and we operating in six different countries like five countries in Europe and you know US
2:09:36
right and you know US of course you know is varied as well right uh so we have learned a lot on how the different you know sidewalks look like how crossings look like how traffic light lights look like you know what the traffic patterns are All of these things we've learned a
2:09:53
lot of these things a lot of data for our machine learning algorithms and so forth right but in terms of actually how people treat robots there's not much difference actually people are actually really friendly towards towards our robots I understand it's really hard to believe but that is actually true it's
2:10:08
completely true and uh we are operating a completely commercial quality service we are we are cooperating with you know most of the major delivery apps in the world and with with a number of you know tier one retail retailers as well and uh it just works. Can you talk about the
2:10:23
it just works. Can you talk about the progression of the technology specifically uh the path to end to end there's a single AI model but there's probably tea operation in the early days then there's uh some mixed uh there's some C++ for pathf finding but there's
2:10:41
some AI for you know image processing and world modeling uh how have you thought about developing the technology and do you see uh tea operation and endtoend AI systems playing nicely together in kind of a centaur mode for a long period or is this are these specific like gates that you have to go through? Yeah, we are operating a quite
2:11:00
Yeah, we are operating a quite the hybrid model. Sure.
2:11:03
We have been in we working on this for 10 years. Yeah. Right.
2:11:09
And uh you know we built this at the at the time where you know AI was not actually as developed and we have obviously reap the benefits of the all of the AI development that has happened has happened since.
2:11:21
Uh but uh but we also recognize that safety for example is super important. Yeah. Super important.
2:11:29
You know like for example our robots you know cross roads.
2:11:32
They they are generally sidewalk robots.
2:11:34
They drive on the side of the road as well when there is no sidewalk but generally they drive on drive on sidewalks but they cross the roads.
2:11:42
They cross roads in similarly as a pedestrian does you know with using crosswalk right?
2:11:45
A robots cross roads 100,000 times a day.
2:11:52
100,000 times a day, right?
2:11:52
We have thousands of robot robot robots operating, right?
2:11:55
You know, we have been speaking right now for eight minutes.
2:11:59
During these eight minutes, our robots have probably crossed the road, you know, over thousand times. Wow.
2:12:01
Probably probably it's like that about a thousand times during these eight minutes that we have we we have we have talked, right?
2:12:09
You know, safety is super important.
2:12:12
Suppose we have something going wrong in like 1% of the crossing. That's too much. Mhm. That's about 1% or 0. 99% too much, right? So we need safety.
2:12:19
We need to prove that it's safe.
2:12:22
We are actually not operating an end to end neural network but we are operating a combination of yes C++ and neural network.
2:12:32
When when when you see uh hard techch founders claiming online that they're operating an endtoend neural network which some people have done.
2:12:41
Does that does that surprise you?
2:12:41
Is it almost unbelievable or do you think it's not surprising to me at all that you can do it?
2:12:48
Uh the downside with that it's very hard to prove that it is safe.
2:12:55
Uh it's it's very hard hard to prove that prove that it is safe and you know we are actually operating in also some pretty challenging regulatory regimes.
2:13:03
I mean not just you know loop is actually beneficial there right?
2:13:11
Like if you have the ability to remotely take over, that's going to make your safety case so much easier because you're going to say, "Hey, yeah, it is kind of crazy.
2:13:19
There is a robot piloting this a little bit, but at any moment we can hop in and beam in and there's a human." Exactly. Exactly.
2:13:25
For for us, it's a combination of remote assistance, which happens, you know, more and more rarely all the time, right? But it still happens.
2:13:35
It's there there there is a human you know somewhere that can take over in difficult situations or complex situations unusual situations then there is C++ and there is end to end neural network as well. Sure. Sure.
2:13:46
Combination of all of these Yeah.
2:13:48
has the transformer architecture or any of the other uh like kind of foundational innovations in AI been important to Starship and what you're building.
2:13:59
Uh obviously we see hype around the studio Gibli moment and diffusion in image processing but does that actually make it easier for you to understand the stuff of like where am I in the world? Where am I going? I need to plan a path.
2:14:13
Uh how has how should we be tying all the amazing progress in LLMs and AI to your business?
2:14:20
Yeah, it is definitely helping and improving our stuff. Mh.
2:14:27
uh I think we were in commercial quality operation uh already before that. Mhm.
2:14:33
But it is helping us tremendously for sure.
2:14:36
Uh primarily it is clearly something that is is dramatically reducing the need for this you know human uh somewhere in the loop. Sure. Uh absolutely.
2:14:48
What about um have you thought about uh giving you know embedding some sort of LLM or voice voice model into the robot?
2:15:00
So if a if a pedestrian bumps into the robot, they can have a little conversation and it can kind of explain like, hey, I'm just going across the street.
2:15:09
I'm delivering a burrito.
2:15:09
Like it can answer some basic questions that seems like I'm just the burrito guy.
2:15:12
I'm just the burrito guy.
2:15:13
Uh that seems like maybe silly but also like maybe great from a user perspective but also like wildly extra. I don't know.
2:15:19
Have you thought about that? Yeah. Yeah. Uh yeah.
2:15:24
So we do not have like a personified LLM in the robot right now.
2:15:27
But I think it is conceivable that that that will be the case. Sure. Our robot does speak. Yeah.
2:15:34
But but the speaking is not actually driven by an by an LLM.
2:15:36
But it's more like business logic decision. Exactly.
2:15:41
It's a little bit more business logic that Yes.
2:15:42
you know, every time the robot, you know, does a delivery delivery, it says thank you. Yeah. Right.
2:15:48
Doesn't take an LLM to do that. Yeah.
2:15:50
Um, well, can you tell me more about tradeoffs in robot production?
2:15:53
Uh, Elon has been like anti-lidar from a cost perspective.
2:16:00
I'm sure there's a bunch of different trade-offs in terms of size, weight, speed, battery life, all these different things.
2:16:05
You have probably like a base hub where these things go to charge and then they have a certain amount of range.
2:16:11
uh what are you optimizing for?
2:16:13
What are some of the pitfalls to avoid?
2:16:15
Yeah, great great question.
2:16:17
So, uh our robots actually do not have a lighter. Mhm.
2:16:19
But that does not mean that we are anti- lighter. Mhm.
2:16:25
Uh the thing is though that the reason we have not used lightars is that lighters is effectively lighters are perfect sensor for uh for an autonomous vehicle. Mhm.
2:16:37
vehicle. Mhm. Autonomous vehicle needs to needs to see quite far away and it needs to see you know it doesn't really well it it does need to be need to have short range sensors as well but you know it does need to you know see you know like you know 200 yards 300 yards
2:16:54
because it's moving fast right our robots are moving much slower than a car right they don't actually need to see that far so light are actually not perfect sensor for us and the downside with lighters is that lighters typically have a narrow vertical field of view. M
2:17:10
have a narrow vertical field of view. M they have like this narrow you know you know uh rays effectively that see very far but it's a very narrow the angle the vertical field of view is very narrow like a couple of degrees or so right we
2:17:28
actually need to have perfect vision from immediate vicinity of the robot like very wide nar wide you know vertical field of view we need to see you know down in front of the robot and also you know up and you know we need to have have that sort of sort sort of vision. So lighters are not perfect
2:17:43
So lighters are not perfect center for us.
2:17:44
That's the reason we are not using lighters but the moment that that a lighter with suitable spec appears on the market, we will absolutely use it.
2:17:54
So we are not like religiously anti anti- lighter at all.
2:18:00
Jord, you have a question.
2:18:00
Uh changing gears a little bit.
2:18:03
Uh Skype is shutting down on May 5th.
2:18:05
Uh and end end of an era.
2:18:09
you were the the founding uh engineer there.
2:18:12
Uh is that emotional uh for you the the shutdown or at this point you've been you know uh in doing something you know else for for uh Yeah. Yeah. Yeah.
2:18:22
I've been doing something else for for a long time.
2:18:23
I'm not actually an active user of Skype anymore. Sure.
2:18:27
Or actually quite quite some time.
2:18:29
I still have the app, you know, in my phone somewhere, but you know, not really using it all that much any anymore.
2:18:35
I mean Skype was an amazing ride.
2:18:38
ride. I mean it was one of these startups you know which is actually rare you know one of these startups that just took off like a wildfire immediately from day one right from outside perspective all startups seem like that that they come out of nowhere and they just boom you know it's like that but you know but in reality as a startup
2:18:57
founder most startups are not like that most startup is hard work hard work before things actually start you know getting off the ground right kind was not like that you know it was like for me it was easy work I was like I just did what I love to do and boom, you know, loads of users came and you know, it just kind of kind of happened, right? So, it was an amazing journey, but also,
2:19:17
So, it was an amazing journey, but also, you know, frankly, I mean, it was a journey that happened 20 years ago. Yeah. 20 years ago. Literally 20 years ago.
2:19:26
What what what are the key lessons that you've t that you took from the Skype story and applied to building this business?
2:19:33
Is it just the engineering culture, the pace of play, or is it wildly different because it's a completely different growth curve?
2:19:42
It's both of these things, but it's also I would say one fundamental thing is that uh with with a lot of products and a lot of services, you kind of uh you know, it's a very simple service really like you know one one delivery delivery app a major delivery app
2:20:02
founder you know told me that you know look after you know if your robots really work and you can give me cost savings because it needs to cost less than than than human delivery mhm for me then I will use your service any day and
2:20:17
you know that's how it is for them that's how it is is for us you know we have no demand problem right if we prove to them that it really works and that we give them cost savings they will use us in like for like billions of deliveries
2:20:34
that's how it works and that's the traction we are we are seeing on the market and Skype was like that as well you know if you actually actually put out a product that exactly fits what people want and it just works. It just It just works.
2:20:48
It doesn't have some sort of major downside, right?
2:20:50
You know, then it just takes off like wildfire.
2:20:52
Granted, it's harder to do with the self-driving robot, right?
2:20:56
clearly much harder to do, you know, like we built we built Skype, you know, like we we were like a team of like how many engineers we were like, you know, 15 maybe 15 engineers, nine months of work and we have a beat had a beat out there that everyone loved and just took off like wildfire, right? Yeah. Sure.
2:21:14
You can't do like a self-driving robot with like a team of 15 engineers in nine months, right?
2:21:16
You know, it take it does take longer longer, right? Yeah.
2:21:19
But it's also harder for competitors, right?
2:21:21
harder for competitors, right? You know, so we are, you know, I said, you know, we have done, you know, 8 million deliveries I'm not sure you know our closest competitor there are lots of competitors tens of competitors our our closest
2:21:33
competitor probably has done 200,000 maybe or 300,000 not sure something like that right like an order of magnitude difference so we started this trend let's say you know 10 years ago and we're still number one because whatever is hard for us it's also hard for our competitors. I have one last question
2:21:51
I have one last question then we'll let you get out of here.
2:21:53
Uh why is Estonia so successful in producing technology entrepreneurs? Uh great question.
2:22:03
I think uh uh I don't have a full answer. No. Um I don't know.
2:22:09
But the but uh but but one thing the thing out there is that um you know Estonia was occupied by Soviet Union for for for like 50 years or so, right?
2:22:19
and and I was you know my age is such that I just turned 19 when we regained independence from the occupation right.
2:22:27
Uh so I I I spent my childhood in Soviet Union.
2:22:35
Uh but my adult life has been like in in a in a free country, right?
2:22:38
and u uh you know turning 19 and finding yourself in a free country that actually doesn't have a lot of establishment. Mhm.
2:22:52
Built in that means that you kind of grow up with an assumption that there are no obstacles. So no obstacles for you.
2:23:00
There are no big companies out there that you need to kind of compete with.
2:23:05
You're just free to do whatever you want, right?
2:23:07
you want, right? So that's the that's the culture I think you know overall you know successful startups can be built by any but it helps that if you don't know what's impossible you knowing you don't know that it's impossible you you're you're going to have a better success
2:23:24
than you just think completely agree that's great that's amazing that yeah that that's amazing thank you so much for joining the show congratulations on your first 8 million deliveries and uh looking forward to the 800 million we'll have to have you back on Then next year, yeah, next year. Let's hear it. Amazing. Let's hear it. Amazing.
2:23:43
Thank you so much for joining. We'll talk to you soon. Cheers. Bye.
2:23:44
Um, before we bring in Yeah, Daniel.
2:23:49
Uh, well, I will bring him in and I will let him give his introduction.
2:23:51
Daniel, if you're in the studio, welcome to the show. Good to see you.
2:23:56
It's been uh a few days since we hung out. Still looking great. How you doing? What's the latest? Doing fantastic. How are you? Uh, doing well.
2:24:06
Uh well while while Jord's way uh would you mind kicking it off with just a little bit of intro on yourself and uh and what you're working on? Totally.
2:24:14
Well Juan blessed to be in the capital of capital.
2:24:16
Couldn't imagine a better place to be today. Yes.
2:24:18
Uh I've been building various uh consumer tech stuff for you better part of the last decade.
2:24:25
Uh kind of most recently attendees with the company I started many years ago sold that.
2:24:30
Uh, I think there was a quote from Shaw Shank Redemption of you better get building or you better get busy dying.
2:24:35
Something like that if I remember correctly, but uh reconnected with the folks at Coco a year ago, Zach and Brad and uh the whole amazing team there and you know was sitting there and and you know realizing like you I grew up in LA uh kept seeing all these robots going all over the place and all these different cities and just figured how to get involved.
2:24:54
So you know we're we're Coco.
2:24:56
for bringing uh you know sidewalk delivery robots to all the biggest cities uh and markets across the world.
2:25:02
Uh I've had a lot of exciting success there and uh yeah that's what we're up to.
2:25:07
Can you compare and contrast your approach to Starship?
2:25:09
We just talked to the founder of Starship.
2:25:13
Uh but every time there's there's like this race for a new technology uh you it looks similar on the surface and then you dig in and you usually realize that the companies are taking very different approaches.
2:25:24
How would you explain what Koko is doing differently?
2:25:26
Yeah, so I I think you know, first off, you know, huge respect to the Starship team. Yeah.
2:25:32
Uh I I actually think I ran into them at an investor's office like 10 years ago, random when they were starting the company.
2:25:38
So um I I think the biggest differences right are kind of where we operate, right?
2:25:43
I think Starship has had tremendous success uh on college campuses and kind of, you know, various other parts of of other markets, but you know, solving the complex city problem, right?
2:25:53
like the if you look at the delivery market, right?
2:25:54
Uh you've had kind of even if you think back five 10 years ago, right, delivery costs were kind of an order of magnitude lower both on the back end and kind of what consumers are paying.
2:26:03
Uh you you have a fundamentally inflationary cost structure.
2:26:07
Um but all that problem of of most of the delivery volume is in the kind of big urban cities.
2:26:12
Um and so I think we've really just drilled on our execution of handling the kind of complex situations there.
2:26:19
Uh there's a bunch of different regulatory hurdles.
2:26:23
um dealing with even distribution, right?
2:26:25
We're we're kind of the only company that's partnered with Uber, Door Dash, and a bunch of other partners that we're kind of announcing soon.
2:26:30
Um being able to have that kind of broad-based reach.
2:26:34
Um you know, I think is super important because you can actually get the volume.
2:26:38
Customers can use you in those cities.
2:26:40
You don't have to go through a first-party app necessarily.
2:26:43
Um so those I think would be the biggest kind of on the surface differences.
2:26:44
What What do you take away from the Whimo strategy?
2:26:48
They were out in uh was it Phoenix, Arizona or is they were out in Arizona for a while I believe.
2:26:54
Uh in like the easiest mode for self-driving like huge streets, no weather.
2:26:58
And then their second market was like the hardest place to drive in the world, San Francisco.
2:27:04
There's hills, there's random people on the street, there's bikes.
2:27:06
And uh I think like the telling that some people would give would be like if you can solve San Francisco, you can solve kind of anything.
2:27:13
Maybe not Boston in the winter, but uh is that the story you tell or is there something else and and and what are you pulling from their strategy overall seeing what Whimo's done?
2:27:22
Yeah, I I mean just on the commentary of kind of hardest cities to drive, I would love to see Whimos in Riad, Saudi Arabia there, it is it is bananas to take car rides there.
2:27:32
Um but what what I think is interesting is we've always compared it the kind of Whimo and the Tesla strategy, right?
2:27:38
Tesla strategy, right? the the Whimo because I think yes they operate in San Francisco which is you know lived there for many years non-trivial to drive in but the cost structure of you know how much does that vehicle cost right the amortizing that capex against all the vehicles right if you have this really
2:27:52
expensive Spencer suite you have really like cost optimized uh the vehicle and it's hard to when you're kind of reliant on a lot of these sensors and kind of advanced computing um it makes it difficult to really get it to be substantially cheaper over time um and to deploy a bunch you want to deploy a bunch of these, right? Like the the
2:28:09
Like the the question I've always asked is why doesn't Whimo deploy, you know, you have Google's budget, right?
2:28:13
Why wouldn't you go deploy, you know, a thousand of these, tens of thousands of these, right?
2:28:18
Um we've always viewed it more in the Tesla approach, right?
2:28:20
Of like if you can make kind of camerabased uh autonomy and kind of driving work.
2:28:24
Um you can have substantially simpler cost structure, right?
2:28:28
Um you're able to and with that simpler cost structure, you can deploy far more vehicles in far more places.
2:28:34
And if you've seen the latest kind of Tesla self-driving, you know, full self-driving version, uh it's an incredible driver, right?
2:28:39
Um and so I think that's the kind of biggest delta in the strategy that you'll see in kind of some of our competitors is like and you everyone on the team is incredibly ruthlessly cost optimized of how do we get this additional, you know, three cents a mile, etc. , right?
2:28:52
Um yeah, that's kind of the Yeah. Yeah.
2:28:55
So what does that mean practically?
2:28:57
Is that just hey we're staying away from LAR because LA liar is expensive or is it like we got to build a gigafactory and just drive down the cost of mass manufacturing these like Tesla is kind of the story of they did both.
2:29:07
Um but what other decisions have you made to drive that cost per mile down as low as possible? I think it's both.
2:29:13
And then there's a really interesting thing, right?
2:29:16
Everyone thinks of the comparable of like, well, it costs, you know, a human X dollars to do this and and with a robot it's it's it's cheaper, right?
2:29:25
But that's only one half of the equation, right?
2:29:26
The delivery business is a logistics business.
2:29:28
And it's it's all in that 98th 99th percentile, right?
2:29:33
If every single time you mess up an order, right, human or or or a robot or otherwise, um that is incredibly expensive, right?
2:29:39
To to to the merchant, which might have, you know, a food cost deducted.
2:29:42
uh to the delivery operator who kind of has to refund the order back to the consumer.
2:29:46
Um, so being able to be more reliable is kind of the other half of the cost structure.
2:29:50
And I think what really impressed me uh kind of when getting involved was, you know, the the focus on reliability and kind of making that work.
2:29:58
And that, you know, obviously involves, you know, the the robots for were kind of human operated entirely for a long time.
2:30:04
And as you kind of roll out autonomy, right, you're able to do that peace meal while kind of maintaining that high quality service bar.
2:30:09
I think that's like the one thing, you know, we know from a lot of our partners is like really exceeding uh on kind of quality of service.
2:30:17
So, it's both cost, which we we nail, but then also quality of service as well.
2:30:20
Do you guys have any projections on when you think uh uh autonomous delivery will be the default, right?
2:30:28
There's like all these new systems coming in, Coco, Zipline.
2:30:30
And we're going to have lots of solutions whether you want to order something from, you know, Walmart 30 minutes away with uh Zipline or you want to get a burrito.
2:30:40
Have you seen uh Pipe Dream or Yeah, there's Pipe Dream.
2:30:44
Like we're going to put it in the ground the pipes in the ground.
2:30:47
There's lots of lots of ways that we're going to get stuff, which is what Americans love.
2:30:50
Y um but but at what point what's your kind of like internal pacing around when you think these systems can be so ubiquitous that when you use a delivery app you just sort of assume that it's going to be uh coming through uh some type of like autonomous uh platform.
2:31:06
I mean I think it looks really lopsided, right?
2:31:11
Like if you're if you're on the west coast, like if you're in LA, like if you talk to people in Santa Monica, like this is their norm.
2:31:15
Like to a lot of people, they get predominantly robot deliver, right?
2:31:18
Uh if you look at other markets we're not in, you know, it's not.
2:31:22
I think it's the same for self-driving cars. Yeah.
2:31:23
Um I mean my answer is is is as fast as humanly possible.
2:31:27
Like I think that's metered in years uh if not sooner.
2:31:29
But I think it's really market specific, right?
2:31:31
Like uh you know if you're in the big cities I think you know hopefully for us right in the in the span of a year maybe two.
2:31:37
Um but you know I I I tend to be aggressive on that front but I think it really depends on on kind of which markets you're in um as that kind of rolls out.
2:31:48
Uh but yeah, I think I think this proliferation of all these solutions is incredible, right?
2:31:51
And I think, you know, for rural environments, I spend a lot of time out in Wyoming, Zipline's going to be amazing, right?
2:31:55
Uh but especially in the urban environments where the real like there's a huge push, right, of like there there's a real business problem uh for a lot of delivery providers of like we need to solve this.
2:32:04
Um I I think that that makes a lot of sense.
2:32:06
Can you talk about anthropomorphic design?
2:32:08
Uh how do you make the robots friendly and seem like they're going to be fighting alongside us when we're fighting the AGI Terminators?
2:32:16
uh versus cuz I imagine if it goes poorly.
2:32:19
I'm going to want a Coco in the foxhole with me.
2:32:21
Uh it's a cute I mean it's a cute even the name like you know Starship cool name but very different than Coco.
2:32:28
I think that's deliberate.
2:32:29
Uh what else are you thinking? Where does this go?
2:32:31
We were talking about maybe like do you throw an LLM with a voice uh mode on it and you can just talk to it as it's driving past you?
2:32:38
Maybe ask it the weather, ask it the time or ask it for the news.
2:32:40
Uh where where does this go long term?
2:32:43
So I I I think a few things. one, right?
2:32:45
I think actions matter a lot more than words, right?
2:32:49
What someone says to you versus how they behave towards you.
2:32:50
And like, you know, we have this idea of this cone of courtesy, right?
2:32:53
And and really being courteous to other, you know, sidewalk users, bicycle users, whatever the surface might be, right?
2:33:02
Um, and I think what's interesting is you've seen, right, like I saw that the kind of previous interview, there really is, you know, basically almost no incidence of of vandalism or kind of people interfering with the robots because there is this like almost adoration.
2:33:15
the name was very purposeful, right?
2:33:17
Um, and you the second most popular dog name in the US, at least at the time, right?
2:33:24
And I think kind of thinking through that of like how something behaves towards you and ends up building the brand more than like what it talks to you.
2:33:31
Um, but then I think like there's always been this kind of sweet jovial culture at the company that really just flows out through to the robots.
2:33:36
Uh, I think there's a lot more stuff you're going to be seeing soon. uh in that vein.
2:33:42
Uh I think been really focused on let's get the economics and the operating model right, but there's a ton of really fun stuff coming there that I can't quite sure yet, but we we will talk.
2:33:50
Can can you talk about your guys's partnership with uh OpenAI at all?
2:33:52
I don't know how much you can speak to it, but um that was a cool announcement. Yeah.
2:33:58
What do you do with that? Yeah. Yeah.
2:34:01
What's up with this this whole AI thing? I I heard it was cool.
2:34:04
I heard there was this model that came out yesterday that people were doing some cool stuff with.
2:34:10
Uh if you have not tried 03, it's amazing.
2:34:11
But no, I mean they're fantastic partners.
2:34:13
Uh I can't speak to too much about what we're doing with them.
2:34:16
Um but it's very exciting and and you know, we'd love to talk more about it at later date.
2:34:21
Yeah, it's it's a cool partnership because you're not immediately worried about them uh just building the same thing that you're doing.
2:34:28
It's kind of like a bigger, you know, jump to to go and say, you know, OpenAI is going to start building delivery robot networks than uh, you know, somebody building a a coding uh platform.
2:34:39
Unfortunately, I got shot down at our our weekly business review.
2:34:41
I saw, you know, we should get into the kind of VS Code fork business, but then shut down unfortunately. Good business.
2:34:49
It's a great business, especially today. Yeah, it's fantastic.
2:34:51
Um, uh, what what else is on your mind uh, broadly in in venture right now?
2:34:55
What are you what are you seeing?
2:34:57
I know you do quite a quite a lot of investing historically.
2:35:00
Um, what's been exciting?
2:35:03
I was at this conference uh this this weekend and and I I I want to share probably the funniest bit uh that I heard from I was talking to a guy manages kind of tens of billions of dollars and we were talking about SPVS.
2:35:16
He just go never say that word again.
2:35:18
It's dirty word sounds bad.
2:35:18
He's like you should call it a co-investment vehicle and I was like that's a great idea.
2:35:23
Uh, and so I think we should try and promulgate co-investment vehicles over SPVS. Uh, it's it's better.
2:35:27
It's like the the scene from the social network.
2:35:31
Um, yeah, I mean that the lot of I think what's going on behind the scenes uh in the industry is really exciting.
2:35:39
Um, especially on the kind of delivery side.
2:35:42
Um, there there's a couple announcements that I'll be back very short to talk about, but Fantastic. Yeah. Uh, very cool.
2:35:48
When uh what's the vibe in Jackson right now?
2:35:52
Is ski season wrapping up or is uh when when even is is spring break? Is that right now?
2:35:58
It's it's we've got mud season which is uh you know all the snow melts and it turns a really delicious color of brown uh and muddy and gets all over everything.
2:36:08
So I'm actually But you're still out there, right?
2:36:11
No, I'm I'm in New York right now.
2:36:12
Uh so you will you will see the seasonal migration of all the all the Jackson people.
2:36:17
But uh it's fantastic place.
2:36:20
Uh there there's actually an article in the journal this morning about how uh tech bros are starting to dress up like uh like cowboys.
2:36:29
I thought they were going to say suits. I was hoping for suits. This is terrible.
2:36:32
All the work I put into this getting nowhere.
2:36:36
I I almost thought about wearing a a denim like I mean this is like Chris Saka's dream, right?
2:36:40
Everyone dresses like a cowboy.
2:36:42
He's been doing that for 25 years.
2:36:44
So, but I wonder if you have to find a new bit, right?
2:36:46
Once everyone starts doing it.
2:36:47
Like does that always bring suits bring suits to Jackson? All right. Yeah. Yeah. Do it.
2:36:52
I should I would love for you guys to come visit and wear suits and we can we can record the looks that everyone gives. Yeah. Yeah.
2:36:59
People don't ski in suits enough, right?
2:37:02
It's like skiing's a serious endeavor. You should dress. Yes, exactly.
2:37:06
Partnered with Zena to make like a ski suit and it's like like a Goreex ski made to measure.
2:37:12
That' probably sell really well on Instagram.
2:37:15
I think we got another business.
2:37:16
Uh, put together one of those co-investment vehicles for us. Okay. Yeah. Yeah.
2:37:19
It's going to need at least uh at least 100 mil to get that off the ground with the tariffs. Exactly.
2:37:25
Uh, actually, that's that's an interesting question.
2:37:27
Um, speaking broadly, how how do you see how have you seen the robotics industry kind of responding? Yeah.
2:37:34
Um, I mean, I'm sure a lot of stuff made in America, but supply chain, right? Yeah.
2:37:38
But especially with um especially with with instant delivery where where econ it's really an economic equation which is like is it reliable and is it cheaper than human um based delivery?
2:37:53
delivery? uh how do you think the industry is like responding still shell shock or um yeah I mean I can speak only you know internally and I can kind of give you some of the things I've heard across the street but sure you know internally we have thousands of vehicles already kind of like in the US built and we're kind of actively deploying more and more of those so you know from from our
2:38:14
standpoint it was kind of like okay like this doesn't actually disrupt us that much right now but I think you know the speaking it broadly to the supply chain right you have um you know a lot of the consumer electronic supply chain is is like primarily in Asia with not a whole ton of like alternatives and so I think it'll be really interesting to see like as the administration kind of rolls out
2:38:35
the kind of other branches this of this policy do you start to see some carrots to kind of move that over um you know a big thing that I think is uh was discussed this weekend that was interesting was you know what happens if you just drop capital gains uh on kind of investing in kind of these key sectors of the economy that we want to bring manufacturing back to the US on I think you know don't have the US sovereign wealth fund to try and pick
2:38:59
winners I think we get into a little bit there but is a great yeah yeah I was thinking about this for uh all the venture capital firms that have been adventuring all over uh the eastern hemisphere you give them a cap gains uh boost in American investing you're going to see billions flow into national yeah they already they already eliminated capital gains uh for in some in some form. Yeah. But uh but uh but that would Yeah.
2:39:23
But uh but uh but that would be a cool. They didn't say how. Yeah. They didn't say how. Um awesome, Daniel.
2:39:32
Well, thank you for coming on. Come back on.
2:39:33
I know you guys have uh some big news. Thanks for having me.
2:39:38
Coming down the pipeline.
2:39:38
Yeah, we'll talk to you soon. Great to see you. Bye. See you guys. Cheers.
2:39:43
Uh, next up we have uh Adam uh coming in from the Chamber of Pop Progress talking about the Google lawsuit that just happened and uh the adtech verdict.
2:39:51
I think we'll be able to have him pop in and give us hopefully some background.
2:39:57
Adam, welcome to the show. How you doing? Oh, good.
2:40:02
Sorry, I had to unmute myself. Can you hear me? Okay, yeah. Yeah, you're all good.
2:40:05
Um, I'd love to start uh I mean quick background on yourself would be great, but also just can you take us through uh the very pre the very early prehistory of this lawsuit will build up to your analysis that you dropped today. Sure. Sure.
2:40:19
Um well, thanks for having me guys. Uh welcome the podcast.
2:40:21
Um so I uh have been doing tech policy in DC for 20 years or so.
2:40:28
20 years or so. spent a dozen years at Google in their Washington office and about four years ago started a group called Chamber of Progress which is a center-left tech industry policy uh group and so I worked on a lot of these issues have a lot of familiarity um this case is interesting so this was the
2:40:46
second case that the department of justice filed against Google uh on antitrust issues and the the the topic was kind of a niche one which is really which is adte the adtech industry um and it really was alleging that Google had improperly linked the different parts of its adtech business together in a way that had given it a monopolistic position. And uh and the case moved
2:41:06
And uh and the case moved relatively quickly.
2:41:09
It moved for what's called the rocket docket, this court in Virginia that that goes generally pretty fast.
2:41:14
And um what does what does fast actually look like?
2:41:17
When when did it when did it kick off?
2:41:19
And obviously they got this one.
2:41:21
So this one was file so this one well so this one was filed by the Biden administration.
2:41:25
The other the other Google case uh which had to do with Google's search distribution deals was actually filed by the Trump administration.
2:41:33
So um this one I think took maybe a year from the time it was filed to the time it actually went to trial.
2:41:39
Um so that's like relatively speed speedy and um and they had you know there's a whole parade of people from the adtech industry who testified as witnesses in this case as well as like advertisers and publishers and kind of people from that world.
2:41:52
Um and and then it but the trial ended in I think in December and then they just just came out the verdict today and there were some points for Google but it was mostly a loss for them.
2:42:02
Um the court found that they had improperly tied some of their ad tech products together and they have a monop monopoly position in what's called the ad ad exchange as well as the ad server which is uh the tool that publishers use.
2:42:14
Um can you break down um yeah can can we kind of like go through a little bit more of your analysis?
2:42:21
I'm I'm curious to get kind of uh u really your I'd like to honestly hear your personal opinion on on it.
2:42:29
I don't I don't know how much you can um how much you can comment specifically.
2:42:33
Um but do you think this was do you think this was the right outcome?
2:42:38
I know there was uh advertisers that use the platform that were testifying saying like look we tried to use a lot of other alternatives and they just delivered inferior results.
2:42:49
Um but uh what's your read on it? Okay.
2:42:52
So well I think the first thing you have to say is you have to back out and look at this industry the ad tech industry because it's sort of like famously complex.
2:42:58
like famously complex. Um there's this famous chart called the Lumiscape that shows all of the players in adtech and and so on the one hand you could say okay well there's a lot of players that's great but on the other hand one of the things that advertisers and publishers you know has have said over the years is like it's a little too complex right and what an advertiser cares about is basically like finding
2:43:21
the customer who's most interested in their ad what the publisher wants is basically the best return on their ad space right and so the way that this industry evolved was was you frankly a little bit contorted, but Google
2:43:32
stitched together, you know, several products that basically ideally gave the publisher the ad that performed the best and ideally put the ad for the advertiser in front of the person likely most interested in it. Okay. Now, other Okay.
2:43:44
most interested in it. Okay. Now, other players in the adtech industry um have complained basically they said that Google made it too hard to interoperate with other with with different parts of its ad tech stack like the ad exchange or the publisher ad server right and
2:44:01
that was the heart of the case right that essentially that Google hadn't uh provided enough interoperability between these different parts of the adte stack and so that was kind of the key question like in antitrust uh there's this kind of doctrine of tying, right? Which which
2:44:15
Which which is basically do you force uh you force people to take one product because they really want this other product, right?
2:44:24
And that's like the heart of the case.
2:44:26
And the judge today uh found that Google had improperly tied um its its adtech products together, specifically the ad exchange, which is sort of the matching piece of the of the puzzle with the ad uh server, which is the tool that publishers used.
2:44:40
Um and so I think that like we don't know there will be a second phase of this trial which will look at the remedies like what happens now what is what has to change in Google's business that'll happen later this year.
2:44:50
Um but to me the the other the big kind of strange thing about this case I will say is that like if you look at this part of Google's business the this is part of what's called their network business uh which is basically like serving ads on other people's websites.
2:45:08
Um, this is the part of Google's business that's actually shrinking.
2:45:11
So, it was like 16% of their business like 5 years ago and now it's down to like 11%.
2:45:17
And you start to say like, okay, why?
2:45:19
Well, what's happened is that that business of placing ads across the internet has just declined because people wasn't because of Google's product.
2:45:29
They're doing AI summaries in some ways like I don't need YouTube and social networks, right?
2:45:33
And and one of the things is like there's so much less purchasing activity being driven by these ads because the targeting is worse and you're there on a website usually to get information or to do something not to you're not just sort of passively scrolling stuff, right? Yeah.
2:45:49
You're you're you're nailing all the reasons, right?
2:45:51
Which is basically like this this this market that you know in any trust any trust case you have to define what market you're talking about here, right?
2:45:57
And here really they were talking about I think it was called like the open the open internet advertising market, right?
2:46:03
market, right? But like that's shrinking right because people are spending more time on within ecosystems right within Google within meta services within Amazon right and those are actually increasing their share of digital advertising so you know one of the critiques I think of antitrust uh sometimes you hear from people is like it moves too slow or it's like fighting yesterday's battle um and we saw that
2:46:25
earlier with the FTC lawsuit in Meta about Instagram an acquisition that happened a decade ago totally I mean it's probably very funny because These things are all h this is like high season for antitrust right now in DC
2:46:37
where I live because the the the FTC trials going on downtown next week the the remedies phase of the other Google case starts and then this and then this one comes down so it's like high season for this stuff. Yeah. I mean they have Yeah.
2:46:49
I mean they have to Yeah. Go ahead. Yeah.
2:46:50
With Google specifically like what's your how does this play out? What is the remedy?
2:46:55
It it it it clearly matters to the businesses that feel and the judge says have been sort of wronged by Google's actions.
2:47:03
But for the average consumer, it's just, you know, I don't even know if it, you know, I don't I don't see this sort of hitting even headlines in the same way that, you know, obviously Meta's, you know, uh, Instagram issue has. That's totally right.
2:47:21
This has always been a very kind of in the weeds, more obscure case. Mhm.
2:47:26
And one of the things that is kind of interesting is that like there's no doubt like this is a loss for Google.
2:47:31
It's probably a win for Google's competitors and adtech.
2:47:32
The the big question mark in my mind is like is it good or is it bad for advertisers and publishers, right?
2:47:38
Because I think on the one hand like advertisers and publishers say some of them say like uh we feel a little bit beholden to Google and we don't like that, right?
2:47:45
On the other hand, like and this came out of trial like advertisers say like their performance by placing ads in Google is really good, right?
2:47:53
Google's putting their ads in front of people who need it.
2:47:55
They're getting good clicks.
2:47:57
Publishers are getting good revenue.
2:47:57
And it could be that in breaking apart like this system that's working well for advertisers and publishers that they end up kind of regretting, you know, what this this whole thing, right?
2:48:09
So, I'm interested to see whether that happens.
2:48:12
But you're right, like the next phase is going to be a remedies trial. And what happens?
2:48:16
I mean, it kind of depends on how aggressively the government wants to pursue remedies against Google, right?
2:48:23
because you can sort of see and the judge said today basically like you have to submit uh initial proposals to her within like the next week.
2:48:31
So this is going to come pretty fast.
2:48:33
Um and so the like the most aggressive is like Google's ad tech business is broken up, right?
2:48:42
So she says Google has to sell maybe its um ad exchange business or its ad server business, the part that works for publishers.
2:48:50
That's would be the probably the most aggressive.
2:48:52
Um the less aggressive and to be clear for the audience that's that's not like AdSense that that has nothing to do with with Google Adwords.
2:49:02
It doesn't have anything to do with like uh they might is it possible that Google could say like cool we're you know uh yeah it's not going to like materially damage the business one way or another.
2:49:17
So, it's maybe a little carrot that they give or is that even not not the right way to think about it?
2:49:23
Well, in fact, there was some there was some reporting before this trial started that Google uh had had supposedly tried to engage the Justice Department in settlement talks, right?
2:49:32
And so, you could like could have imagined like, okay, maybe they would have gone for something there. Um I don't know.
2:49:36
I think we'll see what happens.
2:49:38
But you're absolutely right.
2:49:40
It's not it's not AdWords, not AdSense.
2:49:41
This is um uh this is their publisher side tool and the ad exchange which most people do not know about.
2:49:47
Most most even you know it's this is really like publishers and advertisers know this.
2:49:50
The less aggressive remedy I think would be something like okay you can continue operate these services but we're going to mandate like maximum interoperability basically like every part of your ad tech stack has to interoperate with other services basically and so that would be like the less aggressive version. We'll see.
2:50:08
Um, we'll see which one prevails.
2:50:10
Is is the uh consumer harm standard just like completely out the window now?
2:50:15
Did Lena Khan just like completely wipe that?
2:50:17
Because I I understand that if I'm a if I'm a rival advertising platform, I'm upset about this.
2:50:23
But if you're a consumer, there's maybe hard to prove harm.
2:50:26
And even if you're an advertiser, you're probably like, "Hey, as long as the ad rates are good and I'm getting good ROI, I'm happy."
2:50:32
So, how did this come together?
2:50:34
And are we just completely past the consumer harm standard at this point?
2:50:39
I fear that we're kind of beyond it.
2:50:39
I think in what in this case the consumers were the advertisers and the publishers though like there was never really any serious allegation that like this had an end this had an effect on the end consumer. Sure.
2:50:52
Um the judge's decision like she she her argument her her ruling was that Google's link between these products was uh unfair to Google's advertiser and publisher customers.
2:51:03
advertiser and publisher customers. And so that I think in her way she was applying the consumer welfare standard but whether that you know this the Google's going to appeal the case right that that'll definitely happen and um and one of the big one of the big cases that's a challenge for the the court
2:51:19
here is this case called Trinko which is old old Supreme Court president which basically has to do with what's called the duty to deal which basically says like do you as a c do you as a business even like a dominant business have an obligation to help your rivals and she kind in in her ruling today she did what I would call a creative interpretation to kind of get around that. Mhm. That is Mhm.
2:51:37
That is the biggest question about whether this ruling survives appeal and even up to the Supreme Court because um you know that that that the creativity you call it of her ruling uh may not survive appeal. We'll see. Yeah.
2:51:54
Um, do you think that there's a just zooming out like a shift in the government perception around just big businesses even if they're they maybe are monopolies but they're not causing consumer harm?
2:52:08
We saw this Lena Khan taking a shot at Amazon like they're clearly dominant but is there consumer harm?
2:52:14
Debatable but it's still let's put the screws to them.
2:52:16
Uh, and JD Vance kind of said the same thing with Google.
2:52:21
He's said, "Yeah, that's a big company, maybe too big.
2:52:23
Uh maybe we'll keep some of that pressure on them even though it doesn't necessarily fit the previous definition of uh the monopoly test.
2:52:29
Uh just market concentration is enough to merit a response from the government.
2:52:35
Uh and like how do you think the perception around that shifts and uh do you have a particular take on on just like the idea of big companies that are dominant?"
2:52:46
Well, so it's interest very interesting.
2:52:47
So, like when I worked at Google, one of the things I really admire this because I don't think this is necessarily true today.
2:52:51
Like my boss said, "Look, we're a big company. We have a lot of power. We're very influential.
2:52:55
Like, let's not try to, you know, fool anybody, right?" And I agree with that.
2:52:59
Like big companies should absolutely be more scrutinized, be held to a higher standard.
2:53:05
Like absolutely that's true.
2:53:07
But what happened with with um these federal antitrust cases?
2:53:10
So now every big tech company has an antitrust case pending against it from the federal government.
2:53:15
Apple, Google, Meta, Amazon.
2:53:18
What happened was about six years ago, the FTC and the Justice Department, they share responsibility for antitrust.
2:53:23
They got together and they said, they basically struck a deal and they said, "Okay, FTC, you get Meta and Amazon and DOJ, you get Google and Apple, right?"
2:53:37
And so they split up the companies based on like the like the target, not the subject matter. Mhm.
2:53:43
And I think like just human psychology, once you've done that, you're going to bring a case.
2:53:48
So I think what happened in those cases was like they had the target in mind and then they worked to find a case they could bring, right? Yep.
2:53:56
And so I think that's why like, you know, these cases have like varying degrees of strength to them because they started with the target in mind and then they figure out the case rather than like looking holistically in industry and seeing if there's a problem.
2:54:07
So I don't think that was the most principled way of going about that.
2:54:12
Um but but I think that that's what happened.
2:54:15
Now, one of the things that is very interesting is that like, okay, Trump Trump crowd like the thing they actually care more about most about is censorship and speech, right?
2:54:25
So, it's really kind of strange, bizarre.
2:54:28
I think today Pam Bondi, the attorney general, she she did a statement about this ruling and she said she made some reference in there about how this is great because, you know, we're cracking down on Google because they've censored, you know, conservative speech.
2:54:40
Like, the case has nothing to do with that, but it is tit for like Well, I just think I just think like this wasn't the this wasn't the Trump crowd's case. Yeah. Right.
2:54:49
But they but I don't think the Trump crowda Trump crowd really cares about Google's I mean looking at other motivations is is there a world where you know uh the the current administration seems very fixated on increasing revenues and decreasing costs and is there a world where if you can just go around and get I think they were asking Meta for six billion to settle that case.
2:55:12
Uh, is there a way that it's like more 30 billion? Oh, yeah. 30 billion billion. 30 billion.
2:55:18
Uh, is there a world where it's like, hey, like we're just going to give out some parking tickets to try and raise some revenue.
2:55:23
Is that like a rational thought experiment? Yeah.
2:55:25
To me, the fact they were willing to settle it for 30 billion kind of shows that they didn't really care about the case they brought in the first place, right?
2:55:34
Because it was like, hey, we'll make it go away.
2:55:35
It's just like putting a price tag on it, right? Yeah. Yeah. Wait. Yeah.
2:55:38
Let's pivot to the to the Meta case.
2:55:40
uh because you were sharing uh about that yesterday.
2:55:42
Uh you had said that uh the $30 billion settlement offer is seven times the FTC's annual budget.
2:55:52
So outlandish that the point would be humil humiliation not restitution.
2:55:54
Um how do you think uh the trial went yesterday for Zuckerberg?
2:56:00
Uh John was sharing that he looked absolutely fantastic in a suit.
2:56:05
It's unfortunate that anytime you see a tech CEO in a suit, they're they're in punished. Yeah.
2:56:13
Um but uh what what's your read on the whole situation?
2:56:15
And and I'm curious, did you think that did you think that the original $450 million offer was was it was a good starting offer for Zuck and maybe they could have found some middle ground between $450 and and 300 billion because he was being kind of like run through the mud for even offering $450 million, but yeah, he's a businessman.
2:56:38
I imagine he expected them to counter and like kind of meet in the middle or something like that. But um what's your take?
2:56:46
Yeah, I mean so you're absolutely right.
2:56:49
Can't can't blame him for trying.
2:56:49
Like look, he like if the worst case they lose the case, they're forced to spin off Instagram and WhatsApp.
2:56:54
Like if you could avoid that outcome, you you know, every CEO would try to avoid that outcome, right, through a settlement.
2:57:00
So don't begrudge him that.
2:57:01
But if he was if he was truly worried about WhatsApp and Instagram being spun off, wouldn't he have come in and said, "Yeah, we'll pay like$10 billion because I really don't want that to happen."
2:57:12
Yeah, that's a good point. Um, I don't know.
2:57:16
I mean, the the reality is like I think what they have to balance that against like how confident they are they in their own case and frankly I think I think the FTC has a really tough case there. Yeah.
2:57:28
Because that's what I'm saying.
2:57:30
you like this was a dozen years ago, right? Yeah. No, no.
2:57:32
I was saying specifically uh they have to feel pretty confident in their case if there wasn't, you know, a middle number that they were really wanting to anchor.
2:57:42
Just for reference, Meta has 77 billion in cash in short-term investment. That's what I'm saying.
2:57:48
And they're willing to spend Give us half. Yeah. Yeah.
2:57:50
They're they're they're willing to say no.
2:57:51
And they're willing to say we're going to spend $80 billion a year on capex.
2:57:54
Capex and the metaverse is going to be a huge R&D expense. Yeah. Yeah. I have to imagine.
2:58:00
Well, by the way, like I just because it didn't get settled now doesn't mean it won't get settled later. Yeah, that's true.
2:58:05
Um and you know, sometimes that depends on how the trial goes. Yeah. Right. Makes sense.
2:58:09
Um and so, and frankly, like if the FTC like at the end of this trial feels like h they might lose, like maybe they're maybe they'll they'd accept a lower number.
2:58:19
So, you kind of never know where that's going to how that's going to play out.
2:58:23
But yeah, I think I think like the the the the challenge for the FTC like they have two problems.
2:58:28
One is they have to they have to say essentially that Facebook that Meta doesn't compete with Tik Tok, right?
2:58:34
Um and X like that's a problem for them.
2:58:38
Um but the other is that they have to prove uh monopolization basically that like that that if Meta hadn't acquired Instagram and what app WhatsApp they would have gone on to like challenge them and be great competitors like they were really these were really small companies at the time they were acquired right and credit where it's due.
2:58:57
I mean, uh, Meta did a great job of integrating those companies, making them successful. Mhm.
2:59:01
And, you know, I I I'm sure you guys have seen plenty of failed acquisitions where just like, you know, it's like it just doesn't work.
2:59:08
Like, it's really hard to successfully integrate a company and like legitimately like 1 plus 1 equals three, you know. Um, yeah. Yeah.
2:59:17
And one one one interesting data point.
2:59:19
So when Instagram was acquired, they had 300 million users and Be Real, which was the last breakout consumer app mobile app, has 40 million users.
2:59:27
And I'm I'm going to go out on a limb and say that it's probably not worth any anywhere close to a billion, right?
2:59:34
Even even for someone like Meta who has a a consistent playbook of integrating Y um that kind of business into the platform. Yep.
2:59:46
Well, they also like Meta knows like they're in this business where like you have the most fickle customers ever, right?
2:59:52
Like no young person is on the Facebook app, right?
2:59:54
And then like very few really young people are on Instagram, right?
2:59:57
So like social social networking is a very like kind of like generational thing, right?
3:00:02
And so it's very hard to like maintain kind of the zeitgeist in in their business for like multi multiple generations.
3:00:08
I think that's like a structural challenge for them. So yeah.
3:00:11
Um anyway, so I think I think FTC has has an uphill battle with that with that case.
3:00:16
Do you think do you think these are kind of the wrong problems to be working on generally as we we like you know the entire internet is about to be steamrolled and the economy is about to be steamrolled by AI?
3:00:30
Like do you think it's a big sort of distraction to just be arguing you know over acquisitions that happened more than a decade ago uh when uh it feels you know like we have this uh revolution in in many ways that uh has already started. Yeah I think so.
3:00:46
I mean look like you know I think blah is very popular for politicians to say things like we got to beat China and AI.
3:00:52
Well like who do you think is going to do that?
3:00:55
It's going to be Google Meta Open AI right?
3:00:58
It's like going to be those companies, right? Yeah.
3:01:00
Arguably, a meta without an Instagram is a much weaker product.
3:01:04
They can't invest as much in capex.
3:01:06
They can't invest as much as in Llama, like maybe Llama 3 doesn't get built because they're making half as much cash flow or something, you know?
3:01:15
Uh there's a bunch of interesting ways where the the you get a piece dividend from the from the market concentration.
3:01:20
That's the question about monopolies, like if there's no consumer harm, product's free, and it's really good, and their whole north star is like, let's let's please the customer, like Bezos always says, customer comes first, all that.
3:01:30
Uh, but then you also get these crazy dividends when they go and build cool stuff out there.
3:01:34
Like, it's kind of an awesome system even though it makes it hard to compete with them.
3:01:38
But I don't know, what's your take?
3:01:40
Well, I just think I guess the way I come to like I tend to think of like all of the big companies like intensely paranoid about each other. Sure.
3:01:47
And like they're always getting into each other's spaces too, right? Totally.
3:01:51
And so like to me like that that part of competition is sometimes overlooked in the way and like Yeah.
3:01:56
Like these guys are like at each other's throats, you know, and that's good like ultimately because then they're that competition is leading to them add them to add features and like good for product innovation. Yeah. Yeah.
3:02:05
I mean, every single big tech company overlaps with another one in one way or another.
3:02:09
Whether it's Amazon over overlapping ads now, uh, you know, Bing has a search engine, Google has a phone, like like everyone's in everyone's spaces constantly and it's inevitable. I think it's great.
3:02:20
Yeah, I think it's wonderful, you know.
3:02:22
Well, well, it's been great chatting with you. This was fantastic.
3:02:25
Uh, we'll have to have you on on the next time that there's a big uh FTC case or or big This is fantastic.
3:02:28
DM us when you think there's a story that uh you're excited about talking about and uh you can be one of our Hill correspondents. Yeah.
3:02:37
Congressional correspondent. All right. This is fantastic. We'll talk to you later. Great to meet you. Cheers.
3:02:42
Uh well, we should close out by talking about another acquisition.
3:02:46
Uh uh OpenAI is in talks to buy Windsurf for $3 billion. Uh what do you think?
3:02:52
Future Instagram OpenAI and Windsur Windsurf declined to comment.
3:02:56
future uh future Instagram situation or maybe not. Are you long?
3:03:02
Are you This situation uh takes me back to talking to Sarah Guo when she said look at what the foundation model companies care about and one of the things she talked about was coding. Yep.
3:03:15
It was just she said like if you look at all their actions, everyone besides Grock seems to be very and just XAI broadly seems to be very oriented around code generation.
3:03:25
And so I don't think this should be surprising.
3:03:27
There was also some reporting um that uh OpenAI had allegedly tried to buy Cursor on a couple different occasions um and then in that time Windsurf just kind of took off uh really grew revenue quickly and and um yeah if this deal gets done I think it makes a lot of sense.
3:03:45
There was people pushing back and saying okay how does a $300 billion company not know how to build an IDE?
3:03:50
There was a good post about that.
3:03:52
My take on it billion dollar company can't build an ID.
3:03:54
My take on it was just like, you know, it's probably a timing thing.
3:03:58
I'm sure that OpenAI could build a uh fantastic ID if they wanted to build it from the ground up, but the organization so fast and they're becoming a product company.
3:04:08
People think about OpenAI as like, oh, it's this like 10-year-old company sometimes, but it's like, no, they're seeing insane growth.
3:04:15
They want to hoover up talent and people that are good at designing products and just integrate more and more into the the system they're building.
3:04:22
the system they're building. And I also think there's there's something that very real is happening which is the underlying models are starting to not perform as well in places like cursor yep and uh wind surf and so and and it's possible that's that's a accident of the
3:04:41
way the models are evolving but it's possible that verticalizing is what makes sense and I think that they've done a good job of open has done a good job of uh filling that gap of like the empty text box that you start to prompt like Google search like the the first Chat GPT app was like a direct Google competitor in many ways. You you talked
3:05:00
You you talked about it the knowledge engine but there are clearly going to be several layers where they where where the the LLM will be vended in and coding is a distinct one from the Google search box.
3:05:12
And so you got to be in the ID, you got to be in the Google search box, you got to be in a few other places like where do in your camera role essentially is where you ultimately want to be for image manipulation, image generation.
3:05:24
Of course, a lot of that will happen in the chat app and in those chat workflows.
3:05:29
But uh let's go to Dylan Patel because he broke it down a little bit about why he thinks OpenAI is buying Windsurf.
3:05:35
What's the strategy behind the revive codecs?
3:05:36
Curser and Anthropic had a mutually beneficial relationship, but labs realize that controlling the main application of a model is as valuable as owning the model itself.
3:05:44
With this acquisition, OpenAI gains greater ecosystem control and can build better products.
3:05:49
Anthropics Cloud Code was very wellreceived.
3:05:51
Keen on not missing out, OpenAI released Codeex CLI, which is striking, which is a strikingly similar as a product.
3:05:58
Both of these products have terminal level access and code editing capabilities.
3:06:02
The competition goes beyond just products.
3:06:04
OpenAI opened up free access to the plus tier for university students just one day after Anthropic announced their education initiative in early April. Fast there.
3:06:15
So, so like the the game is on.
3:06:15
There are not there's not a single multi-billion dollar AGI market.
3:06:20
There are probably many pockets of value that will be discovered.
3:06:24
And the interesting thing here is that I think it's a narrative violation.
3:06:27
It was actually fine potentially to build a a a rapper.
3:06:31
Uh in many ways these companies were derided early on when they launched as oh it's just a rapper you're going to get Eden this is going to get oneshotted by the the foundation models uh well it seems like there at least is a way out via an acquisition these companies are
3:06:46
valuable we've seen the ARRs grow so um and then also I think it's interesting that there are you can probably think of like a power law distribution around value creation at the application layer with like the the blank box in chat GPT like just go and talk to the LLM. That's
3:07:01
That's probably like the most dominant.
3:07:04
That's the Google, right?
3:07:05
But then Windsurf, Cursor, Devon, these are all super valuable in that in that category.
3:07:09
But then there's probably a really long tail and there's probably some value in the application layer deep down.
3:07:14
So I think it's another maybe bullcase for for um for rappers depending on how you're structuring the business.
3:07:21
Like you probably are not going to disrupt OpenAI with a rapper, but you could build a very very great business. Yeah.
3:07:26
And for Windsurf, I mean, uh, I'm sure they in many ways would have loved to just keep building and building and building and building, compounding, but, um, they also, uh, I'm sure we're very aware of the competitive dynamics.
3:07:39
And this is one of those things, right?
3:07:40
I I, uh, when you when you talk to, uh, we we talked to the the founder of captions earlier, right?
3:07:48
Fantastic app that you're using all the time. Yep.
3:07:49
How far away are we from you being able to upload a video to chat GPT and just say like add subtitles? It's possible.
3:07:56
Yeah, you're already a pro subscriber, right?
3:08:00
And you're you're like, okay, I have this.
3:08:02
But at the same time with the cursor analogy, like it's possible that there are more features and you just stay ahead long enough to lock in that customer as like, well, I like their UI. I'm familiar with that.
3:08:12
Like this is the same thing with like Da Vinci Resolve is free in many cases and people don't switch because the buttons are in a certain place and the certain features that are nice.
3:08:21
that are nice. I would just say like people um you know people were were uh I even saw Daniel who we had on the show talking about how yeah obviously value accumulates to the app layer but I don't you know I still think we're going to
3:08:36
see this back and forth battle where oh value is accumulating to the app layer but open has an app like models are everything apps right you can ask it to do something absurd you can ask it to now go you know do the you know me book you write some code for me. They are a new
3:08:53
They are a new form of everything and I think that big companies even if you have a lot of traction today you need to look at at how um how fast they're they're evolving.
3:09:07
Uh there's a funny post by Burn Hobart here.
3:09:09
03 is a quality improvement but at least on financial topics it's definitely the fattiest model.
3:09:14
returns don't increase or rise, they get juiced and retaliatory tariffs are described as China blasted hogs and soybeans. This is great.
3:09:23
This is my only real complaint about frat GPT is that it hyphenates too much, but other than that, it almost perfectly captures the style. So funny.
3:09:31
Uh blasted hogs and soybeans. I love it. I love it.
3:09:35
Um well, uh we got to tell you about public.
3:09:38
com investing for those who take it seriously.
3:09:41
Multiasset investing, industryleading yields, trusted by millions.
3:09:43
So get in on the action at o at public. com. Um what else?
3:09:46
I mean Dan Shipper, he kind of had the most viral um review of 03.
3:09:52
He says it's absolutely amazing.
3:09:56
It's already his go-to model.
3:09:58
Fast, agentic, extremely smart, and has great vibes.
3:10:00
Uh some of his top use cases, these are things you can kind of steal from him and adapt into your own workflows.
3:10:05
It flagged every single time I sidestepped conflict in my meeting transcripts.
3:10:09
It spun up by bite-sized ML course that pings me about about every morning.
3:10:14
Um, it found a a stroller brand from one blurry photo. That's cool.
3:10:17
It coded a new custom AI benchmark in record time.
3:10:22
It x-rayed a an Annie Dillard classic and found writing tricks I'd never noticed before.
3:10:27
It even analyzed every's org chart to tell me what we'd be good at shipping and what our weaknesses are.
3:10:33
So, he's having a lot of fun with it. Um, anything else here? Oh, music.
3:10:38
Yeah, they launched a music music label. That's really exciting.
3:10:42
And they're going they're getting venturebacked, right? Yeah.
3:10:45
Didn't they take some money from Thrive? From Thrive. Very cool.
3:10:47
And then uh gosh, I feel bad for blanking on his name.
3:10:52
The guy who was at Adobe. Oh, yeah. Scott Bellski.
3:10:53
Yeah, he went over there. Belowki's over there. Incredible organization.
3:10:57
I mean, so bearish on Hollywood.
3:10:59
And the idea that you could build a new studio in a special way is just fascinating to me.
3:11:04
And they've been able to do it really well.
3:11:05
All the A24 films have been fantastic. It's taste.
3:11:08
It's taste and it's it's clearly such an interesting differentiation and now they're getting to I'm sure they'll be publishing a bunch. Wonder who who knows.
3:11:14
I'd be cool if Bellski was involved with this.
3:11:17
I wonder if there's an AI angle on music.
3:11:18
It would be kind of silly to launch a new record label and that does not embrace the it's not embracing that. So yeah.
3:11:27
Um uh deal CEO, we got to talk about this.
3:11:33
We we've done two episodes on the deal rippling drama.
3:11:34
Uh but Matt Lavine says, "Has anyone booked a demo with deal recently just to see what lines their salespeople have been fed re the situation?"
3:11:43
It's a hilarious manifest man manifestation of natural versus corporate personhood that the entire exec team are wanted fugitives, but the rest of the company just keeps chugging.
3:11:54
And that's like, yeah, yeah, this is something that's probably missed is like, so the deal CEO has been they've been trying to subpoena him and he's maybe in Dubai and it's very controversial about whether or not he'll stay at the company because there's all these allegations.
3:12:05
Not much proved yet, but the I mean the the signed affidavit was pretty crazy. The spy turned on them. The spy turned on them. It's not looking good.
3:12:12
But what does that actually mean for the company?
3:12:13
Like the crazy thing is like even after all the Zenitz drama and and Parker stepped down, like Zenitz didn't do well, but it did cons it did continue as a company for a long time.
3:12:22
People don't like ripping out their HIS systems like ever. It sucks. Yeah.
3:12:26
I mean, I think uh the fact of the matter is I imagine Ripling has an extremely strong sense of who uses deal, right?
3:12:33
There's not there's a there's a lot of companies in the world, but there's not a lot of like, you know, there are a lot of highv value enterprise targets, but I doubt there's many at this point that Rippling hasn't had like some comms with that have confirmed like, okay, they're using deal.
3:12:50
And so taking the line right now to to basically have your SDRs, BDRs, you know, sales leaders reaching out to these people that you've had a point of contact with and said, "Hey, you know, I know you're running on deal a year, you know, we should, you know, consider having you guys switch over and um and then just sharing like a headline."
3:13:10
That's it's kind of like it's fair.
3:13:10
It's uh it's it's not it's fair game.
3:13:13
Yeah, it is crazy that they haven't responded even or at least that we've seen.
3:13:17
Yeah, I I expected them I I expected them all to step down step down purely because it's in the probably in the long-term best interest of the company. Yeah, I thought so too.
3:13:30
It'd be interesting to see like what's the actual board structure because they've obviously raised a lot of money.
3:13:34
They probably don't own more than 50% of the shares, but they might have super voting or something or board control. Who knows?
3:13:40
But even then, still if if Yeah.
3:13:42
Yeah, just in your self-interest of preser preserving the financial capital.
3:13:45
You if if all the pressure is on you, get out.
3:13:48
It's not like you're necessarily going to lose all the value there.
3:13:51
You could very easily maintain some of that if the company survives. Yeah.
3:13:54
Again, the other thing is the other thing is thinking about uh the example I think you gave early on, which was uh you know, if somebody comes to you and they go, John, you're using Michelin tires.
3:14:06
Did you know that Michelin was spying on Bridgestone?
3:14:10
you really going to use those tires?
3:14:12
They'd be like, "That sounds like a hassle."
3:14:14
And you're like, "Okay, like you seem way too interested in the tire market.
3:14:18
I'm going to keep, you know, driving my car. Thank you."
3:14:22
And so, it's very possible that, you know, who knows?
3:14:23
Maybe it doesn't have as much of an impact, but I'm sure it's going to have an impact from a uh recruiting standpoint, which will have an impact long term, right?
3:14:30
Well, I want to uh close out with two more posts.
3:14:32
Uh congratulations to Raul from Julius.
3:14:34
He announced collaboration.
3:14:37
He was talking about this Figma for data analytics.
3:14:39
Uh he also put out a cool photo of him teaching uh data analysis at HBS.
3:14:45
Uh he's been fantastically successful. It was great.
3:14:51
I love watching the videos he puts out.
3:14:53
He always looks like he's about to smile and then he doesn't. Yeah.
3:14:56
But I think he's just smiling inside because he's just happy.
3:14:58
He's building he's cracked building a great product.
3:15:01
And so I mean this makes so much sense.
3:15:03
You you you build an IPython notebook or you do some sort of data analysis.
3:15:06
you want to share it with all of your team members and you want all of your team members to be able to edit on the same file and the same analysis.
3:15:10
So, uh this was interesting.
3:15:13
John uh Conkl called out uh that uh we posted back on February 2020 uh February 4th of this year.
3:15:23
Masa dropped his crystal ball while pitching the SoftBank OpenAI partnership with Sam in Tokyo last week, sending many analysts into a panic. Has he lost his vision? Was this an omen omen? Only time will tell.
3:15:33
And uh that was basically the top uh video.
3:15:36
So John actually commented back and said uh time has told hypothetical performance of a tactical short selling strategy triggered by the very impressive Stargate presentation and the crystal ball drop. So there you go.
3:15:49
Well, we should close out with some news that'll be very important for all of our listeners.
3:15:54
GFream has announced the G800 certification today.
3:15:58
This was rocking the group chats.
3:16:00
Yes, everyone was talking about this.
3:16:02
So, uh, 8,200 nautical miles at Mach 8.
3:16:04
5, 7,000 nautical miles at Mach. 9.
3:16:06
Max speed increased to Mach. 935.
3:16:12
All in the same body as the G650 ER, but faster and longer range.
3:16:17
I'm sure a lot of you folks uh who are listening are going to be upgrading.
3:16:19
Uh, so call your GFream rep uh today because these are going to be flying off the shelves. Any other advice?
3:16:25
I mean, this uh you're going to want to get ahead of this.
3:16:29
Yeah, this thing looks fantastic. It really does.
3:16:31
By the time you get the jet and then outfit it, um you're you know, it's going to be it's gonna be expensive.
3:16:38
While it'll be worth the wait.
3:16:39
Yeah, it's a lot of money, but it's a lot of jet.
3:16:41
And again, you know, you you can sleep in a G800, but you can't fly a house. That's right, John.
3:16:50
So, it's going to be a few more years until uh Astrome Mechanica can get us a the the Gulfream equivalent of a Yeah, that's a good way to justify this.
3:16:57
like you're just holding yourself over for the Astrome Mechanica, the Boom, the Hermus, one of those guys.
3:17:02
But in the meantime, pick up a couple of these, rotate them out every few years, and uh just use this to get around. Anyway, that's our show.
3:17:11
Thanks so much for watching. Thank you folks.
3:17:13
Hey, this was a much more stable show. No cyber attacks. No cyber attacks.
3:17:17
Thank you to the brave uh soldiers team and cyber security experts who kept us running. We'll see you tomorrow. See you tomorrow. They can.