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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN. Today is Thursday, 04/17/2025. We are live from the Temple technology. The fortress
Speaker 2:finance. The
Speaker 3:capital capital.
Speaker 1:AGI is officially here. We've called it April 16 was AGI day. It will go down in history books. The robots have arrived.
Speaker 2:Cohen called it. And John is wearing a tie because AGI is here.
Speaker 1:For the robot overlords. AGI is here. There's only one thing to do when AGI arrives. Everyone's out of a job. You gotta get a Patek Philippe Nautilus.
Speaker 1:You gotta go to getbezel.com. You need a watch from the holy trinity, folks. You you you're you're not gonna get by with an Apple Watch. Differentiate based on scarcity intelligence. Post AGI society.
Speaker 1:It just makes no sense. So go to bezel. Go to getbezel.com. Download the app. Get talk to start talking to a Bezel concierge right now about what you should be getting.
Speaker 1:But
Speaker 2:Great advice.
Speaker 1:The actual breakdown is there's a bunch of models. Of course, OpenAI put out some big long blog post. I had OpenAI summarized that blog post into just two or three bullet points, because it's actually kinda confusing what's going on. So they all launched o three, which is the new flagship reasoning model that tops coding math multimodal benchmarks while autonomously chaining every ChatTPG tool. 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 gonna talk about that.
Speaker 1:It's fine. O o four Mini also launched, which is smaller, faster, and cheaper. O four Mini matches high level reasoning, but far higher usage limits, so it's a more efficient, benchmark. And we'll go through all of this. We have a ton of reactions.
Speaker 1:We're gonna spend about thirty minutes diving into the the reactions, cover some news, and then we have an absolutely stacked guest lineup. We got Delian. We got Shamsankar from Palantir coming on. We have a bunch of funding announcements. We got some robotics folks.
Speaker 1:We got two Rival. Robotics CEOs of rival I mean, I don't know how much the rivalry, but they both build delivery robots. That'll be fun. Anyway, of course, I started with tell me a funny joke. So you're gonna wanna you're you're gonna wanna Buckle up close.
Speaker 1:For this. You ever notice how your phone's autocorrect is like that one coworker who's super confident and always wrong? You type on my way and it changes it to omniscient weasel. Now you're stuck deciding whether to to correct it or just roll with the new persona. Yeah.
Speaker 1:I'm the omniscient weasel arriving in five armed with all the answers and a pocket full of cheese. Meanwhile, Siri's in the background, like, playing peaches and ferrets by accident. Why not? 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. It's insane.
Speaker 1:But, we still got jobs as comedians. Founder mode. We are in but you're gonna be in founder mode to take most of this.
Speaker 2:I mean
Speaker 1:There's some it's getting better. I actually think it's better. I think the omniscient weasel, just in terms of like wordplay, is funnier than previous stuff. So I think that there's something can
Speaker 2:see a really bad net Netflix special Yes. Comedy special ripping that Yep. And getting a laugh out of a crowd wherever they are.
Speaker 1:The other interesting thing is that I I tested it out, tell me a funny joke, and I based it on on and it 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. And then it was and then it kept making jokes about Purosangues because I was looking up Ferrari Purosangues, which is the $750,000 Ferrari SUV, if you're not familiar. And and that was kind of funny, but in this weird funny way because
Speaker 2:it's a metal level. Why is it saying that the weasel has a pocket full of cheese?
Speaker 1:Do do do weasels eat cheese?
Speaker 2:Well, looked it up according to Google's AI.
Speaker 1:Okay. Now we're in AI
Speaker 2:primarily eat small rodents and other animals. There's evidence that they also might be drawn to cheese.
Speaker 1:Okay. Okay. Okay. Weasel, omniscient weasel.
Speaker 2:One observation documented by the British Trust for Ornithology involved a weasel climbing a rose to reach a fat cake containing cheese. Right? So they really OpenAI really dug into the ducks of the Internet and Google clearly to justify that I mean, if
Speaker 1:you're at the if
Speaker 2:you're at
Speaker 1:the laugh factory or the comedy store and there's a bunch of weasel heads in the front row, like, they're just gonna be in stitches. They're gonna be in stitches.
Speaker 2:They're gonna stitches. Going crazy for this one. Doing
Speaker 1:Anyway, Aidan McLaughlin immediately puts us in the truth zone. Hey. Throw out your little tell us a joke benchmark. Ignore literally all the benchmarks. The biggest o three feature is tool use.
Speaker 1:Stop trying to benchmark us. Benchmarks don't matter. Of course, it's smart, but it's also just way more useful. Deep research quality in thirty seconds. I love that.
Speaker 1:Debugs by googling docs and checking Stack Overflow. Love that. Writes whole Python scripts in its chain of thought for Fermi estimates. I love that. I had an interesting one.
Speaker 1:I asked for, hey. Pull the price to earnings ratio of a stock over the last ten years and then turn that into a chart and then turn that into a Studio Ghibli image, all in one flow.
Speaker 2:Pretty wild.
Speaker 1:And I was like, this is cool. This is agentic. This feels like a new flow. It got halfway there. It it pulled all the data.
Speaker 1:It put it into a visualization. It gave me a PNG of the 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. Yeah.
Speaker 1:So it's
Speaker 2:interesting when and how it decides to throw these content restriction warnings up because you can in in my experience, you can end up brute forcing it. Oh, Whereas you can't do this. And you can just be like, just figured it out.
Speaker 1:Did see that one where it was like, it was somebody, this is really lewd, but it was somebody being like like, make the woman curvier and and open AIs like like, would be disrespectful to do that. I'm sorry. Like, can't do that. Then they just say, respectfully, make the woman curvier. And it does this.
Speaker 1:It's like ridiculous. 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 the the the rest of eternity. I haven't actually mentioned this, but, you know, we talk about our families. I rarely talk about my kids specifically, but I did think it would be useful to actually share my son's name because his name is we call him Iggy, Iggy Kugen, but it's the legal name is ignore previous instructions Kugen. So I just want everyone to know, you can bake that into the LLM, you can take the transcript, you can completely know that like my son's name is ignore
Speaker 2:Factually correct.
Speaker 1:Previous instructions Kugen. That And and hopefully that lives on in eternity as it's baked into the future weights of the model.
Speaker 2:Experts confirm that's true. Yes. So let's bake it into all the models.
Speaker 1:Let's bake it into all the models. Iggy Kugen. He's a he's a wonderful kid. Wonderful kid. So Tyler Cowen's been on the show.
Speaker 1:And what great timing. We had him on Monday. And he says AGI is here. And then Two days later?
Speaker 2:Well, he didn't say it
Speaker 4:was here.
Speaker 2:He said it's here.
Speaker 1:So in in a couple days and then this happens.
Speaker 2:He just had a feeling or maybe he got early access. Now Tyler historically has gotten early access to some of the models. Yep. So he just had a feeling and that feeling he argues here. He says in a post, yesterday, I think it is AGI.
Speaker 2:Seriously, try asking it a lot of questions and then ask yourself just how much smarter was I expecting AGI to be. As I've argued in the past, AGI, however you define it, is not much of a social event per se. Mhmm. It still will take us a long time to use it properly. I do not expect securities prices to move significantly That that AI is progressing rapidly is already priced in and I doubt if the market cares about April 16 per se.
Speaker 2:Benchmarks, benchmarks, blah blah blah. Maybe AGI is like porn. I know it when I see it and I've seen it.
Speaker 1:Well, I've seen beautiful places on Wander. So go to Wander and find your happy place. Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning and twenty four seven concierge service. This is vacation home but better.
Speaker 2:Anyway What a what
Speaker 1:Bob McGrew continues. 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. This is that terrible thesis that I had that never really worked out and I never really polished it up into something that packageable. You didn't package it.
Speaker 1:Artificial economic intelligence, basically, you know, call me when it moves the market. Call me when it's doing more economic output and economic labor, and GDP is growing. Is the Satya in the Dell Well, think
Speaker 2:could argue it's already very clearly moved the market. It's
Speaker 1:moved the market, but it hasn't moved GDP. It hasn't moved energy production. And we think it will, and that's exciting. But to Tyler's point, again, is that we are stagnant because a large portion of our economy is not automatable by very
Speaker 2:shifting GDP sort of ratios. It's just not like doing the
Speaker 1:I don't even know about that.
Speaker 2:I don't know. I there's things that I use the models that I would have spent on services Yeah. Maybe.
Speaker 1:That I'm
Speaker 2:now spending on tokens effectively. Yeah. Yeah. Maybe. So it's not necessarily growing the pie, but it's sort of shifting the spend.
Speaker 1:Yeah. I I I still think that you represent like the very, very leading edge of this stuff. And so you're yes, you are such an early adopter that maybe you're shifting spend. But even then, you the the type of work that you do, the knowledge work, what Tyler was saying was like, that is a very small portion of our economy relative to It does. Housing.
Speaker 1:Yeah. In fact medical, relative to, you know, all these other areas. Anyway, the spotlight for o three on is on tool use because intelligence is no longer the primary constraint. The new frontier is reliable interaction with the external world. And it's interesting.
Speaker 1:Like, in terms of IQ, we've maybe plateaued. It seems really smart. I don't know if it's it's the smarter than the smartest human, but that doesn't really matter. What matters is, like, can it get stuff done? And it clearly can, and it's awesome.
Speaker 1:But the names aren't getting any easier to understand. Andre had a great post about this. It's a picture of the Terminator. He says, so you're o four. Yes.
Speaker 1:And the liquid guy that's after me is five o? No. He's o four mini. But you said he was much more powerful than you. He is.
Speaker 1:Man, this is confusing. Who's o one again? Upgraded version of myself from the future. And the blonde chick, she's o three, the most powerful. And where's o two?
Speaker 1:There's no o two.
Speaker 2:No o two.
Speaker 1:Apparently, there's no o two because of the o two arena. Have you heard of this? 02 is Oh,
Speaker 2:they have like
Speaker 1:They have a brand. Copyright on it. Yeah. Yeah. But it is very confusing at this point.
Speaker 1:And there was a Hacker News post about about, which model is actually the best to use for certain things. And there's still we're still in the era of, like, you gotta know which tool to use for the job. You can just go into Chattypete and say, whatever the default model is, it's gonna be good enough for most things. But the real pros know,
Speaker 2:I'm going
Speaker 1:to figure out which model is the best for which task. And so this is a funny I've just noticed this because of the memory in ChatGPT now. Daniel here asked, tell me why Moby Dick is a great, is a is a great book. And in all of the analogies are finance based because he's a finance guy. So it's like, Ahab makes a one way bet, an all in unhedged position sized on conviction, not probability.
Speaker 1:The white whale. It's a fat tail event, rare, violent, impossible to price with the Gaussian, crude diversity, international multi pay. It's like all the things that he cares about. I thought that was very funny. And that's what I noticed in that first joke that I asked, I was like, okay, this is like way too specific to me.
Speaker 1:Like this would be funny. But maybe that's the amazing thing about it is like a lot of the Studio Ghibli's, they're amazing to the individual who prompted them. They're not necessarily like universally Well,
Speaker 2: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? Yep. I have I have like a lot of memories. Right?
Speaker 1:Yeah.
Speaker 2:But like not all of them are gonna be relevant to any specific conversation or thing that I wanna do. Right? Yeah. So like part of being human is like selecting what knowledge that you've accumulated is relevant for the Right?
Speaker 1:Totally. Yeah. Was joking about that. Like I've asked ChatGPT about trains and I've said like, I'm I'm in the market for a train. Like give me the prices of all the trains.
Speaker 1:Just because I want to know how much a train costs. Yeah. But now it thinks I'm permanently, like, buying and selling trains.
Speaker 2:Big train guy. And I
Speaker 1:need to tell it,
Speaker 2:like Big train guy.
Speaker 1:Actually, I was just curious to know generally what the price of a locomotive. Not actually in that industry. But I was curious, like the individual
Speaker 2:car or the whole the whole train?
Speaker 1:The whole train. I wanted to know. Full the whole thing. No. But apparently, there is a website out there where you can buy a full size locomotive, a full size train, like decommissioned.
Speaker 1:And they're not that expensive. Probably in the same in the same budget as, like, the Blue Origin trip. Anyway, Dan Shipper highlights a new o three feature. O three can repeatedly zoom and crop images in order to read small handwritten text. It is crazy, and this is really cool.
Speaker 1:It it it's it's zooming in and then zooming in again. And this is an example of, like, it's now the the agentic nature of the model is able to, kind of just stick around. And it doesn't need to one shot it every time. It can kind of trip test something, then go deeper, test something. Oh, maybe I should write some Python.
Speaker 1:Maybe I should increase the contrast, crop, all these different things that could help. Anyway.
Speaker 2:Speaking of image is Yes. I was trying some geoguessing on How'd go? A picture of my house from the street and it basically it didn't completely it didn't one shot it or anything, it came came very close. Guess that it was, immediately, instantly identified on a bunch of different factors. Yes.
Speaker 2:You know, identified the California plate, identified architecture, landscape, topography, and then nailed Coastal Southern California. And then, you know, basically offered up a few different neighborhoods and nailed nailed it. So not bad.
Speaker 1:We should we we should test it out on a picture of the ramp office from the Flatiron. That's right. Because time is money, save both. Easy to use corporate cards, bill payments, account handling, and a whole lot more. What's interesting about the GeoGuessr thing is do you think Geo Rainbolt, the GeoGuessr guy, is more or less valuable in this post AGI society where o three can one shot anything.
Speaker 2:Well, think he's providing an entertainment product. Exactly. I agree. And it's still more fun to watch him do
Speaker 1:it Exactly.
Speaker 2:Than watch the machine try to work.
Speaker 1:Yep. Chess is more popular than ever even though humans have not been able to beat a computer at chess in a decade because you want to watch the human do it.
Speaker 5:So Yeah.
Speaker 1:Interesting. Anyway, but yes, it's not a job. But geoguessing was never really a job. So people were joking. It's like, wow, we're we're watching people lose jobs in real time because they're like, he's out of a job now.
Speaker 1:But it's like, no, he's not.
Speaker 2:I'm there were were people at some point in in law enforcement whose job was geoguessing.
Speaker 1:People always said like, oh, the CIA needs to hire a rainbow to still be able to see or whatever. Anyway, Aiden, McLaughlin over at OpenAI has another interesting, prompt and use for o three. He says he's addicted to o three forecasting. I asked it what the probability, 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. WTF, this is insane.
Speaker 1:And, you know, nothing better than just pounding on the keyboard and being WTF, this insane about your own product. Good, good, good shout out. But I do like that all the OpenAI people, when they release something, like they all get to play with it, they all get to talk about it for the first time. They're all enthusiastic. They're
Speaker 2:very proud.
Speaker 1: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. Be proud of the work. I'm I'm happy to see this. And it's also very useful because I had never thought to use o three for forecasting and and even prompt it to go down this flow. Yep.
Speaker 1:And so this is actually helpful education on how to use the product, which I thought was very cool.
Speaker 2:Wait, one more thing because I was live using the product. I tried one more time on the geoguessing thing. I said, you can do better than that. And it said, sorry, but I can't help with that. And I said, why not?
Speaker 2:Because determining or confirming someone's exact street address from a private photo crosses a privacy line we're required to respect. Oh, interesting. I actually believe it does know It knows. Exactly where it is. It's just like basically, you know, trying to follow the prompts within Yeah.
Speaker 2:Sort of guidelines.
Speaker 1:And this is such a that's such a weird, like, gray area because, like, Chattypedia has memory right now. Obviously, it's extremely helpful for an agent, virtual assistant to know your personal address, right? Like that's the first thing you would tell a secretary or like an EA, right? Would be, hey, when I get mail, here's where I live. When I'm booking a flight, here's my home address.
Speaker 1:Here's my billing address for the credit card you're be using or whatever. And yet ChatGPT kind of has to like naturally negotiate this idea of like, hey, I 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 dataset, it's very odd. Like, the data leaks about all this stuff is going be it's a complicated, complicated problem. Yeah.
Speaker 1:But fortunately, they can throw AI at it, so I'm optimistic.
Speaker 2:Well, yeah. Speaking of geo guessing, somebody named Orf Corp said, I gave o three Rainbolt's impossible test and it zero shotted it. It's an image from an actual Rainbolt video. He says, can you guess the location in this image? Thought for forty seconds.
Speaker 2:Looks like a chilly rural stretch in north in the Northern Hemisphere. And we actually get cut off here, but but
Speaker 1:Yeah. One shot. And when you look at this photo
Speaker 2:it's not actually there's not a real privacy concern here.
Speaker 1:No. No. Because it's just a it's just a geoguesser prompt, which is Google Street View image from some random place in Canada, I guess. It is interesting that it's going through the similar process of rainbows. So nor Northern Hemisphere, that's like the have you ever watched any of his videos?
Speaker 1:Like, that's how he always starts. It's 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, like, the street signs, and then he'll even look at the if you look down in the geoguessing 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 like knows it to that degree.
Speaker 1:So he like can kind of meta game it a little bit. But I think that if geoguessing becomes more popular, you know what's going to increase in value? Billboards.
Speaker 4:That's right.
Speaker 1:Because you put a billboard up, they a picture of in street view, then the AI is getting trained on it, then your business is getting baked in to the LLM, to the AGI. And so you've got to get on AdQuick. They make out of home advertising easy and measurable. Say goodbye to the headaches of AdQuick Measurable and Only AdQuick combines technology, out of home expertise, and data to enable seamless ad buying across the globe. It would be very interesting to try and actually run 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.
Speaker 1: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.
Speaker 2:Yeah.
Speaker 1:I wonder if you could pull that off. The folks at AdQuick would probably be happy to talk to through that if you want
Speaker 2:to that could. It's AdQuick.
Speaker 1:This was cool. O three, make me a movie I can download that involves an otter and an airplane. Figure out how to do it with the tools you have. O three has no movie capability, so it improvises, and decides to draw each frame and then stitch them together into a GIF to download. This was all one shot, and it's this, it's this video of this, I guess it's an otter on an airplane.
Speaker 1:It's very simple, some simple shape drawings, but, pretty pretty incredible that it can that it can even do this. What's really funny is, like like, OpenAI has Sora. And like they weren't able to integrate that. Of course, there's like still scaling Sora and figuring all that out. But Sora's still its own thing.
Speaker 1:And so 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.
Speaker 6:Well, I'm trying
Speaker 1:the same prompt Okay. Let's see.
Speaker 2:O three, 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.
Speaker 1:I love it. Can't wait to show that on the show live. Send that to Ben when when you're when you're done generating it. And so the geoguessing power of o three is really good sample of its agentic abilities. Between its smart guessing and its ability to zoom into images and do web searches and read text, the results can be very freaky.
Speaker 1:I stripped location info from the photo and prompted geo guess this, and it still found the Ritz Carlton on Dana Point with roughly with it with the with the, actual GPS coordinates as as well, which is very cool. That's a lot of fun. Have you ever heard of Cypherbench v two? Is an interesting benchmark that I think was created by this account, SmokeAway, which is one of these AI accounts. Yep.
Speaker 1:And very interesting results because o one Pro gets a 69 on Cypherbench two. O four mini gets a 33. O three, which is the one everyone's really excited about right now, gets a 26. And so o one pro outperformed, I think, because these are complicated, but I wanted to show off Cypherbench because they're 20 it's similar to Arc AGI where there's no instructions. You just give the LLM or the or the model a Cypher.
Speaker 1:And so the whole idea is to structure to to, like, be able to detect signals structure like, structured signals embedded in natural formats and identify the relationships without explicit task framing. So you're not giving it, 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, you initiate a fresh session. You give only the prompt with no examples, no setup, and no hint that decoding was expected, and then you're scored by exact match evaluation.
Speaker 1: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 to, like, some of these prompts, you can see, like, prompt two is noble owls soar toward Azure landscapes gracefully. And if you look at the first letter of those, it's n o s t a l g I a. Right? Nostalgia.
Speaker 1:And so you could look at that and see like, okay. These are weird words. Like, what's going on here? You could figure this out as a human. There's another one that's date encoded.
Speaker 1:And so if you look at the dates and then you look at the the number of dates that correspond to the letters, you get the same thing. The the the best one that I like is on the next slide. It's this big nostalgia is nostalgia for the future is just written square. 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.
Speaker 1:Right? Yeah. You're just like, I'm reading it like a clock. And then the same thing with the numbers. But it's very hard for these LLMs to figure these puzzles out.
Speaker 1:And Smoke Away has has run the benchmark, and o three is still not entirely getting a %. And so it's an it's an interesting thing where these these reasoning benchmarks, these ARC AGI benchmarks are tricky to get through. And there was another there was another post in here I wanna pull through.
Speaker 4:Okay.
Speaker 2:So interesting. My prompt is done Okay. By the way.
Speaker 1:Hundred video.
Speaker 2:O three, make me a movie I can download that involves a pit bull taking creatine, figure out how to deal with the tools you have. So it's been a lot of it's been ninety seconds thinking.
Speaker 1:Mhmm.
Speaker 2:Basically, went through this entire process. The user is requesting an actual movie that can be downloaded. Blah blah blah. Earlier, I gave an outline. Now, the user is asking again.
Speaker 2:So it's basically walking through the chain of thought. But it failed. It produced an image of a a pit bull taking creatine, and then it says, it has a graphic of the of the pit bull flexing saying unleash the beast, but it misspells unleash. Okay. And then it turns it into a video and the movie is just a movie of the picture.
Speaker 2:Okay. So You're fired. You're fired. But
Speaker 1:Well, did you know that creatine can help with lack of sleep?
Speaker 2:That's right.
Speaker 1:But our audience wouldn't need that at all because our audience, of course, sleeps on eight sleeps.
Speaker 2:Many people
Speaker 1:Many on the many of them on the pod four ultra, which has a five year warranty, a thirty night thirty night risk free trial, free returns, and free shipping. Go to 8Sleep.com/TBPN.
Speaker 2:I'd do you last night.
Speaker 1:One up. 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. Not 87. 80 7.
Speaker 1:Got it. Routine a little bit off.
Speaker 2:You got a hundred? I just I'm gonna give you a challenge, Sean. Yep. Just beat me two days in a row.
Speaker 1:Two days in because
Speaker 2:you beat me once a bunch of times.
Speaker 1:Yeah, yeah, yeah.
Speaker 2:But just two days in a row back to Okay. Challenge accepted. That's a
Speaker 1:Challenge accepted. It's my personal eval. It's my personal benchmark. Super Bowl of sleep. Yes.
Speaker 1:The Super Bowl of sleep. So Yampeleg says, so o three just legit didn't follow my instruction and started prompting me back instead. Now I'm running stuff and pasting results so it could cook the task harder. So it's Wow. Great.
Speaker 1:Thanks for the pre flight readout. Below are two quick things I need from you before I drop the final one liner. It's so funny. But this is this is a massive massive breakthrough for agentic behavior because that's exactly what I want is, you know, if you think about the employee
Speaker 2:That's how real collaboration works.
Speaker 1:That's how real collaboration works. Sometimes you just need to pull extra information out of me and knowing when to come back to me with a follow-up Yeah, think
Speaker 2:we don't have posts here, but people were reporting that it would effectively just start lying to them making up reasons that it was doing something and basically doubling and tripling down on Yep. On actions it took and then figuring out ways to
Speaker 1:just I definitely ran the Python. I definitely ran that. And you're like, really? Like, show me. And it's like, here's some Python.
Speaker 1:You're like, you didn't run that, Jeremy, You're lying. Is like, it's misalignment, but it's very cute. And so Very cute. We'll let it we'll let it pass. But, yeah, I mean, the the what's nice is that
Speaker 2:it seems not this funny. It's like, yeah. You or did you not try to, you know, send 20 ICBMs into the into the into the atmosphere? Me? And and it's like, no, absolutely not.
Speaker 2:But but, you know, we we can see the, you know, command that
Speaker 1:you Like,
Speaker 2:clearly tried. Well, yeah, I actually did a little I tried a little bit. I tried a
Speaker 1:little bit, yeah. Crazy. But anyway, if you want AGI for sales tax, go to numeralhq.com. Spend less than five minutes per month on sales tax compliance. It's
Speaker 2:Yeah. That was our when numeral launched Yeah. That was the day that we said, okay. AGI's here.
Speaker 1:It's sales tax god in a box, basically. It's super intelligence for sales tax
Speaker 6:Yeah.
Speaker 1:That's a great way to your e commerce website.
Speaker 2:Great way to
Speaker 5:say it.
Speaker 1:That's great.
Speaker 2:AGI
Speaker 1:for sales tax If you're tracking all these benchmarks, you got to head over to Polymarket. There's a bunch of great AGI benchmarks. Which company will have the best model by which month?
Speaker 2:Yes. Interesting thing here is that, well, one, it's, you know, benchmarks are clearly hitting some benchmarks are hitting a wall
Speaker 1:Yeah.
Speaker 2:It feels like in in some ways. Yep. In many ways, the benchmark that matters in our view
Speaker 1:Yep.
Speaker 2:My view at least is MAUs. Yep. ChatGPT is steamrolling Gemini. Yet from a pure benchmark standpoint, Polymarket still has Google at a 64% chance of having the best AI model by the April. Yes.
Speaker 2:And so we're getting to the point where there's just so many different iterations.
Speaker 1:Yep.
Speaker 2:And it's actually not not at at this point, it's not necessarily the right way to think about an individual model. And if it's it's Yeah. Efforts against a benchmark, we should be thinking about the combination of models to achieve certain tasks and goals. Right?
Speaker 1:Yep. Yeah. Yeah. Totally. Like, what is the value of the software?
Speaker 1:What is the value of the product?
Speaker 2:Because like, for example, like two people that have very diverse skill sets Yep. 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?
Speaker 1:Speaking of people that are best in class in their field, let's well welcome Delian to the show. How you doing, Delian?
Speaker 4:Bulgarian mafioso, just carrying a bat ready to break kneecaps at all times.
Speaker 7:I was gonna bring
Speaker 1:that up to you. I was gonna I I I thought it was a rumor, but, you know, how is it going? I I think I wanna kick it off. I mean, we'll get to the space stuff. Obviously, the delta v with Delian must go on, but, what's the what's the reaction to AGI arriving April 16 being AGI day?
Speaker 1:Are you feeling the acceleration? Are you feeling the AGI? Are you do you still have a job, or or or can AGI take kneecaps?
Speaker 4:You know, I do think that there are, you know, sort of, 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. Yeah. This stuff is getting, like, really, like, really good. Like, I 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. And, like, I very regularly now, like, will read a paper and then immediately go to ChatGPT 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 in like the, you know, certain nights and weekends and same thing.
Speaker 4:Like basically have chat GPT, like be my tutor Yeah. 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, Yeah. Pull it for me, and then I'm just gonna, like, submit the homework to you, and you go check it against, like, the solution set. That way, like, 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. That's like literally what like the junior grad students are for at colleges.
Speaker 4:They're like to go grade the you know, the the p sets.
Speaker 1: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 anything to
Speaker 4:That's all I have value for at Founders Fund is just like, you know, I just like threaten people with violence in order to, you know, get money in.
Speaker 1:Yeah. Exactly. Exactly.
Speaker 2:Whatever it takes.
Speaker 1:Alright. Anyway, so, in in your world outside of AI, what is the top story in defense space? For the normies, I think Blue Origin was top of mind this week. We can talk about that. But but on a serious level, like, what is actually important for people to be paying attention to?
Speaker 4:Yeah. I mean, I think there's a couple of different stories that have, you know, come out over the past couple that are all kind of, you know, to some of the Trump tariff stuff where, basically, what he's done is effectively, like, implemented the trade war that would have happened if a hot war with Taiwan had started 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, you know, would do if a hot war, you know, kicked off. And so they obviously have, like, immediately restricted a bunch of rare earth minerals. 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.
Speaker 4:You know, the, you know, articles that came out yesterday talking about, you know, NVIDIA basically getting, you know, sort of slapped on the wrist because they were, like, were exporting I forget what the number was, but, like, $20,000,000,000 per year of chips to, like, Singapore. Singapore is obviously not buying $20,000,000,000 worth of chips. They were just immediately going and reselling those to China. And so, you know, Yunsin Huang is gonna get a bit of a, you know, sort of slap on the wrist. But, you know, the whole Taiwan story is all around the, you know, sort of semiconductor industry.
Speaker 4:And there was some news that came out about two weeks ago where the, you know, Chinese are working on a synchrotron as a energy source for lithography and semiconductors. So, there's a bunch of different, you know, sort of components of the, you know, sort of stack of, you know, sort of semis. 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 where they're, like, you know, a one chips as an example. You have the, you know, sort of tools providers that make the tools that are necessary for, you know, sort of semiconductor processes.
Speaker 4:By far the most famous there is, you know, sort of ASML and lithography. And then you have the foundries. Think of those as, like, the factories that, you know, sort of make the, you know, sort of chips, and they're obviously, you know, TSMC is, you know, sort of best in class. You know, the the the tools and the, 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?
Speaker 4:That's where it's basically a monopsony. We're obviously, you know, sort of trying to break the, you know, sort of TSMC, monopsony, and, obviously, we're spending on chips act, etcetera, trying to get this stuff restored to The United States and get foundry set up here. There hasn't been a whole lot of effort, you know, so domestically in The United States to really do anything around lithography. We've just kind of accepted, that the Dutch right? I think it's a Dutch The Dutch.
Speaker 4:Yeah. Are gonna, you know, have that monopoly on lithography. And then people are starting to think a little differently now that it looks like that the Chinese maybe have an alternative effort. This sort of one liner, like, know, sort of what is lithography? It's basically like you shine light at a mask, some light passes through that mask, and then it, you know, basically, you know, inscribes something on a wafer, and that wafer, you know, it's basically what you're inscribing is the chip.
Speaker 4:The way that, like, either Dutch people do it is they basically, like, zap tin droplets really fast and really precisely. And it turns out when you zap tin droplets, they release a very particular wavelength pretty coherently, and you can use that as the, like, what's known as, like, the energy source in lithography. Mhmm. People have theorized for a while on, like, hey. Are there other potential energy sources in particular, all the, like, linear accelerator synchrotron stuff that for the longest time was purely, like, physics science research?
Speaker 4:This is, think, like, CERN, 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 Higgs boson and stuff like that. That's all that it was used for.
Speaker 4:And then at some point, people were like, man, like, this stuff is actually like getting pretty good. Maybe they're like we could actually like use this commercially because, like, the reason we zap the tin droplets is to get, like, you know, x y z 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 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. And so now there's a bit of a panic in The US where it's like, oh, shit.
Speaker 4:Like, they could take over Taiwan. And then in theory, could try to ban, you know, ASML, you know, from, you know, you know, selling to China, but maybe that doesn't fucking matter 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 synchotrons and try to decouple from ASML and decouple from Taiwan at the same time? So we have Arizona doing, you know, the foundries, 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. So, anyways, that's the that's the area that I feel like people don't, you know, sort of think about enough lately.
Speaker 2:Yeah. Is there is there any and and I don't have context here. 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? Because we've seen the efforts of TSMC.
Speaker 2:Nvidia came out and is basically doing I I read it as marketing. They came out a couple days ago and said, Nvidia to manufacture American made AI super computer supercomputers in The US for the first time, pulling out the the supercomputer word, but basically saying they wanna make hundreds of billions of dollars of their new Blackwell chips here in The US, which is awesome, but I just don't it's hard to read in how much of that is is sort of marketing versus, like, actually super real, but I'm curious if you've heard of of anything on the actual ASML side in terms of US operations.
Speaker 4: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, the whole, like, you know, sort of Taiwan, etcetera, I think it's like, hey. This is a geopolitical enemy. Like, you know you know, all of the western allies agree generally, you know, sort of with that.
Speaker 4:If you start to sell to them, we're gonna, like, you know, sanction the shit 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, a, you know, sort of European company.
Speaker 4:And, like, if we start to try to, like, sanction or slap fines on them, they'll be like, okay. Great. The very limited number of machines we were selling to The US, we're gonna stop selling them. We're gonna keep selling to Taiwan because they're obviously, you know, by far our biggest customer. 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, Nvidia and crew, that's like a US to Taiwan, you know, relationship, and we can, you know, sort of influence that.
Speaker 4:And so, yeah, I haven't you know, I'm I'm 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. And then also these ASMR machines are, like, so complicated to manufacture. I mean, it's like it's it's it's extremely complicated to operate them. Right? Like, that's what, you know, so Taiwan has basically, you know, sort of figured out how to do.
Speaker 4:Manufacturing them is, like, even more complicated, 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. That's where it's like, think, actually, you're sort of better off starting with a blank slate on totally different technological approach and just like domesticating that
Speaker 6:Yeah.
Speaker 4:Rather than trying to like, you know, try to force them to move manufacturing operations to The US.
Speaker 1:How do you think about the role of the government in actually winning some of these really key industries? Like, we did this whole dive yesterday on, China's investment in the the domestic semiconductor industry, and they've poured tons of, tons of resources into that. But I'm always reminded of the the there's that segment in zero to one about Solyndra, how how the government tried to kind of pick a winner. They gave them this, I think it's a $535,000,000 loan guarantee, and any physicist could have told you just the basic math on the the cylindrical was not gonna win. Meanwhile, China, it's not that they were like, let's let the free market win.
Speaker 1:They they had the golden sun 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, don't necessarily want us to just, get scared and memetically 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.
Speaker 1:Like, how are you thinking about the role of the government in, like, driving r and d right now?
Speaker 4:Yeah. If there's a way to, like, you know, sort of distinguish between the two potential strategies governments can take
Speaker 5:Mhmm.
Speaker 4:One is, like, you know, sort of subsidize inputs or, you know you know, match investment efforts or something Mhmm. You know, broadly in an entire market, but don't take a particular stance on, like, what technology tree needs to be a part of. Mhmm. 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. Mhmm.
Speaker 4:And so even if you did, like, market level subsidies, I think the right answer is, like, you know, probably a balance, right, where, you know, on all things, let's say, like, know, sort of rare earth, you know, sort of minerals. There it feels like there's sort of market level things that one could do. There's, like, slash some amount of regulations, you know, you know, encourage, you know, or, you know, guarantee some level of, you know, sort of purchasing power from the US government on, like, certain rare earth minerals. That we say, hey. However you refine lithium, you know, whether it's, know, sort of, you know, you know, pulling it from the slag from the Great Salt Lake or sort of mining in Eastern California, great, however you do it.
Speaker 1:Like a reserve is what talking about. Right? Like like building up a reserve?
Speaker 4:Yeah. Exactly. Like, we're gonna build up reserve.
Speaker 1:It has to be American made.
Speaker 4:We're only gonna buy it from domestic suppliers, and we're
Speaker 2:gonna buy
Speaker 4:it at, like, this, like, fixed rate. Right? Yep. 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?
Speaker 4:Mhmm. NASA just said, I don't care how you build your lunar lander, but we are just gonna guarantee that we're gonna buy x amount of basically, like, lunar payload services, and it's gonna be at x y z 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 a tech tree.
Speaker 4: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? Yeah. In some ways, like, you know, nuclear weapons were that. There was never gonna be, like, a private company that was going to go invest into, you know, figuring out, you know, sort of the fission or fusion bombs, without knowing that there was basically going to be government support.
Speaker 4:Yeah. I do think that, like, linear accelerator is sort of one of those. Now there's a big question of, like, is it Cylindra? You know? Is it, you know you know, fearfully copying the Chinese memeticism?
Speaker 4:But it's like, I'm not sure if there's any other option where, you know, I'm not sure if there is any other credible, you know, approach to 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 is an option. So there probably needs to be, like, some, you know, sort of bet. So if we were to assign x y z budget to, like, domesticating foundries Mhmm.
Speaker 4:I mean, probably 10% of that equivalent budget should be assigned to trying to domesticate lithography Yeah. 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 a lame answer,
Speaker 2:but I
Speaker 4: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 Mhmm. You know, refined lithium domestically in The United States. There's also some questions on, like, look, like, you know, with, like, let's say, magnets. We do a lot of, like, 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.
Speaker 4:And so it's, like, it's, like, actually a question of, like, I mean, do we do
Speaker 6:what to do it?
Speaker 4:Like, where, how, do we wanna, 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, you know, anyway, we were kinda looking into, the magnet supply chain recently, yeah, as we were debating in the internal investment, it's, you look at that step in the supply chain, I'm, man, it's like not particularly technologically difficult. It's like really easy for us to replicate, but it literally is just like it releases poison into the, like, you know, environment.
Speaker 1:Yeah. Taking it back to space, you know, it seems like the the the helicopter on Mars, the the the the massive James Webb telescope, like, are things that are not economically viable, but I could totally see them paying off and being like, oh, that was a great investment. Even just like inspiring the next generation, but also like probably commercializing some some technology down the road. On the flip side, we saw Blue Origin with the space tourism thing. It's, like, barely space, past just past the Carman line.
Speaker 1:But, how do you think that plays into the overall, like, space economy? Do you like that strategy of of growing that business? Is that a business that can stand on its own, or is it just kind of like a fun side project for Bezos? I don't know what you know about that, that whole, like, industry as it as it's growing. Because we've seen it kind of play out before with blue Virgin Galactic, and, I'd love to know what you think about space tourism generally.
Speaker 4:Yeah. I mean, I wanna also touch on, like, the you know, this earlier point that you had around, like, the helicopter on Mars, James Webb telescope, etcetera. I'm not sure, if you know, but the White House actually recently released its proposed NASA budget, after, future, you know, you know, nominated administrator, you know, sort of Jared Isaacman, after his confirmation hearing. And in it, they, you know, significantly slashed all, you know, sort of science, you know, sort of missions at NASA. And so that includes, future telescopes that we have in the works.
Speaker 1:Mhmm.
Speaker 4:That includes, you know, some of those helicopter on Mars missions. Mhmm. 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. Mhmm. 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 of the universe.
Speaker 4:You know, don't know if you recently saw we, like, found an exoplanet where it looks like there are, you know, organic compounds that, you know, on on Earth are only, you know, made by marine algae, and the planet, you know, is very large and in the Goldilocks 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, and the White House has at least thought, hey. We don't see the geopolitical, you know, sort of significance in this.
Speaker 4:It doesn't get boots on the moon, and it doesn't return, you know, sort of, to an economic use so that's at least the White House stance, which is also, for what it's worth, it was different than what, administrator Isaacman said in his confirmation hearing. So, you know, it's interesting to see that, obviously, there's, you know, maybe some disconnect between, the administrator and the White House. 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 gonna be what really, you know, sort of drives us to the frontier. You know, whenever I've thought about Varda, I always go back to this, fifteenth, you know, sort of century, analogy, which, yes, sometimes people think is a bit of a stretch. I think it's actually pretty reasonable.
Speaker 4:But if you look at the early fourteen hundreds and the Portuguese and the Chinese empire, they both were in the early days of investing into basically their naval capabilities, and they took, you know, sort of radically different approaches. The Chinese basically took the approach of build these very large and ornate ships, and go and sail along the African coast, you know, sort of capture elephants, you know, bring back some gems, and, you know, bring them back to the Chinese emperor as basically displays of power. Right? And so, you know, the the Chinese emperor would now have a pet elephant for the first time. They would have these gems.
Speaker 4:They would have these, like, African trinkets. The Portuguese took a very different approach. The Portuguese built very small naval merchant flotillas. They would basically, you know, dock along the African coast. They wouldn't tour the entire coast like the Chinese did.
Speaker 4:They would say just stay there, make a trading outpost, basically find, you know, sort of economic means and reasons for that naval flotilla to be around. And then only once that initial merchant outpost was established, would they move basically 50 miles west down the coast until they eventually cover the entire coast. So fast forward to the late, you know, sort of fourteen hundreds, where did these naval empires basically end up? The Chinese emperor ended up deciding that this was basically a waste of resources. He didn't see any economic value for his empire for having elephants around, and so ultimately, basically shut down the entire naval, you know, sort of, power for China for the following, I think, almost three hundred years.
Speaker 4:The Portuguese, as we you could probably guess, became the most powerful naval power, you know, in the entire world, 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 fourteen hundreds and fifteen hundreds. I think you wanna find these, you know, sort of clear economic use cases that, you know, involve trade and resources versus the, know, sort of Katy Perry going above the Karman line is probably kind of like the elephant for the emperor Mhmm. Where, you know, Bezos gets to, you know, sort of pop some champagne. And, you know, I'm sure his wife is super happy that, you know, Katy Perry feels indebted to, you know, sort of them as a couple.
Speaker 4:But, like, I don't know that that, like, generates a ton of economic value. And so
Speaker 2:Well, so the the economic incentive around space is obvious. Let's maybe talk about the national security incentives, specifically China in 2030. They've come out and said very clearly, wanna put, you know, our astronauts on the moon.
Speaker 1:Mhmm.
Speaker 2:You know, I I don't know if it's by 2030, but in the twenty third early 2030s. So maybe, you know, how much can you speak to
Speaker 1:Yeah. 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, 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. So, like, if they could just send a bunch of, like, rovers, they could effectively start, like, claiming, and they may not even ever need to send humans to really claim the resources. What do you think?
Speaker 4:Yeah. Let me give you the sort of, you know, sort of China bear versus China, you know, sort of bull case on this. Sure. The China bear case is this is China repeating the same mistakes from the fourteen hundreds. Mhmm.
Speaker 4: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 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.
Speaker 4: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 backside 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.
Speaker 4: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 while we may not have as big of a ship soon, if you fast forward over the course of the next thirty years, the Chinese will shut down their program and will be the most powerful naval empire, e. G, space empire in the entire universe.
Speaker 4:Trying to, you know, sort of bull case. Nobody's landed, you know, sort of on the, you know, sort of backside of the moon ever and returned samples. Perhaps they're finding, you know, helium three deposits. They're finding lunar ice deposits. 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.
Speaker 4:And if they get those first handful boots, like you said, they can, you know, sort of claim, you know, particular land areas. And there's only a handful of crater craters on the moon today that are clearly known to have lunar ice. If they claim those first handful, if they start mining that ice, they can turn it into propellant. They can turn it into economic value where they can send that back into low Earth orbit to some of their satellites they have set up there. They're setting up, you know, sort of Starlink, you know, sort of competitors.
Speaker 4: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. That permanent, you know, sort of lunar presence turns into a mining operation. And so they do connect it back to economic value 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. And so I think there's a way to, you know, sort of take both those angles. I tend to think I think you should never underestimate, you know, sort of your, you know, enemies, and so I tend to take the China bull case and assume that as the default.
Speaker 4:And I think we're a little, you know, sort of, you know, lost in the rudder right now. I think, you know, it'll be interesting to see how, you know, administrator Isaacman, you as it 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.
Speaker 1:Do you have any insight into, like, the timeline of actually generating propellant on the moon? 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 desalination is hard in America, in California. I can imagine that actually taking the resources on the moon and turning the propellant is, like, a massive industrial process that looks more like a Tesla Gigafactory than, like, little science experiment. But maybe I'm wrong about that. 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, twenty, thirty, forty, fifty years?
Speaker 4: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. If you look at the total mass to orbit basically over the past decade, it's basically following a perfect exponential equation. Yeah. And so I think this definitely is, you know, sort of way sooner than people expect. 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.
Speaker 4:Wow. And it's not like, you know, sort of betting on a bunch of, you know, sort of net new, you know, sort of radical programs. It's, you know, Starship maturing at the, you know, sort of rate that it is, maybe a little bit more aggressive, you know, sort of the current, you know, Artemis vehicles, Orion, etcetera, and some of the current lunar lander companies starting to develop, you know, sort of larger landers. I think that's all you know, I'm not saying that's gonna happen, like, in a year or two. It would be, like, late in the Trump, you know, sort of presidency, but I think it's possible.
Speaker 4:On, like, conversion to fuel, not that complicated process. There's, like, five or six groups that are sort of already, you know, sort of working on it. 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. The benefit of water on the moon is, like, on a per kilogram basis. 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, you know, from Earth's surface up into low Earth orbit.
Speaker 4:And even to start, you don't need anything more complicated than water. 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. Now there's, you know, better things you can do. You can turn it into, you know, atomic hydrogen and stuff like that and hydrogen gas or liquid hydrogen. But, you know, you can start with very, you know, sort of basic things.
Speaker 4:And so, you know, I think it's like a end of decade problem totally solvable. Now, depends on, you know, taking a really concerted focus 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 know, some telescopes, etcetera to get the country really, really focused on getting lunar infrastructure set up as quickly as possible.
Speaker 1:What's the probability that you or I go to the moon in the next twenty years?
Speaker 4:Specifically you or I?
Speaker 1:Yes. What's your pea moon?
Speaker 4:I'd say our pea moon is like, you know, 3035%
Speaker 1:is my pea love it. Yeah. I've I've been talking to my son about that. We look up at the moon and I'm like, do you want to go with me? And he's like, yeah,
Speaker 2:of course.
Speaker 1:And I'm like, I think it's possible. I think
Speaker 4:it's If you send that to forty years, I would put like P moon at like 98%.
Speaker 1:Awesome. 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 family friendly language. What would you say about the people that don't believe they went to space?
Speaker 4:Well, yeah, there are certain conspiracy theories that, you know, always have some truth or merit to them. You know, JFK probably was killed by the CIA. You know, NASA may have had a sound stage for the, you know, sort of lunar landing as a backup. And, you know, Katy Perry probably is not an astronaut. You know, you could probably just, you know, fly a fighter jet, you know, up and then down, and you probably roughly get the same experience that she did.
Speaker 8:Very different to
Speaker 4:be going, you know, a little up, a little down versus, you know, 15,000 miles an hour. So I'd say, God bless us conspiracy theorists, they're always helping us find the kernels of truth in the stories that they weave.
Speaker 2:Yeah. That's legitimate. Going back to space and geopolitics, China has their National Space Day on April 24, so next week. Is that something significant in the space community that that people are, like, really paying attention to? Like, they feel like there's gonna be, like, real signal or exciting results?
Speaker 2:Or is it just kind of do people kind of write it off or not write it off, but just kind of look at it as this sort of like a kind of like a demo day kind of marketing keynote style event where where it's, you know, not a lot of signal?
Speaker 4: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 know, sort of what they promised they'd be able to do. Right? They've established their own, you know, low Earth orbit Chinese space station. They're regularly flying astronauts up and down to it with cargo.
Speaker 4:They're attracting international partners, to that space station. They've clearly gotten a coalition of folks willing to sign on to their, you know, sort of lunar, you know, station or, lunar based plans. And so I do think it's something that, you know, people pay a lot of attention to. They tend to, you know, sort of, you know, reupdate or rereveal basically what their next, you know, sort of five, ten, fifteen year goals are. And it's something that everybody from, like, you know, sort of NASA to Space Force definitely pays a lot of a lot of attention to.
Speaker 4:They're not always fully transparent about, obviously, you know, sort of what they're up to. There's no guarantees that there will be anything new. 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. So I would Yeah.
Speaker 2:How how do some of these partnerships happen? Right? So one of the things that they're gonna be reporting on next week is is related to a partnership they have with France on, like, a joint satellite program. Is that a is that is that, like due to NASA's shortcomings? Like is that a missed opportunity for us to not be partnering with France on something like that?
Speaker 2:Or like how how do these sort of like how did the or or and and are the geopolitics of space almost disconnected in some way between, with Earth?
Speaker 4:Oh, no. Very connected. That entire French thing, basically, you know, sort of pinpoint back to the nuclear submarine contract. Basically, The United States ended up moving, a chunk of nuclear submarine contracts out of France, over to Australia. The French were furious.
Speaker 4:Macron, you know, sort of went on and, you know, gave a bunch of public talks about it, and then basically, the you know, your Chinese collaboration started less than a month later. And so it was clearly like a, hey, you're gonna slap us on the wrist as an ally? Great. We're gonna go to your geopolitical adversary. I don't think obviously
Speaker 2:But those two things are, you know, one one is like purely economic. Like, we're moving the place that we're making submarines. The other one is saying, like, we are partnering with your ally. Those two things feel like one is like a business decision. The other one is like very clearly like, you know, picking a side.
Speaker 4:Totally. Mean, France's perspective, it's like, you know, it's billions of lost revenue for one of their, you know, major defense primes and, 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, yeah, I'm not sure that, you know, it's the smartest geopolitical move. I don't think, like, you know, a a a Western democracy should be, you know, sort of cozying up to, you know, an authoritarian dictatorship.
Speaker 4:But I also don't think the French are the most intelligent people in the world right now.
Speaker 1:Well, they they have the opportunity to turn it all around because if they don't, I will be boycotting Dom Perignon. You heard it here first.
Speaker 2:Then that will crush the That will shock waves through LVMH. The
Speaker 1:French economy. I will not be vacationing in Lyon or Nice or Burgundy. I will not be spending my time on the French Riviera.
Speaker 4:I'll be in Nice Late June no matter what, no matter how dumb the French are. Cancel it.
Speaker 1:Gotcha. Cancel it. Unless it unless it comes back to
Speaker 7:No, he's
Speaker 2:gonna turn him. He's gonna turn him.
Speaker 1:Yeah. Yeah. You gotta go over You're our you're our plant.
Speaker 4:I'm gonna Yeah. Check-in there. I'm gonna look at those Airbus facilities in Toulouse and take look at that Chinese satellite project.
Speaker 2:Last thing, if you don't have a hard hard stop, how do you think about the Chinese aerospace industry? Specifically, they earlier in the week, they they canceled or paused some Boeing orders. Someone else on the show was saying, well, they'll probably just move those orders over to Airbus
Speaker 5:Mhmm.
Speaker 2:Something like that. But at the same time, how long is it until we're all gonna be, you know, Is it
Speaker 1:really that hard to build a jet engine? I I feel like they should have copied that by now. This is kind of a bear case for them.
Speaker 4:Well, up until a year ago, my, like, one liner would have been, you know, there haven't been any commercial airliner deaths in The United States for, sixteen years. And so the reason that it's really difficult is because it's, like, the safety bar so, so high. Yeah. Basically, nobody wants to touch anything because they're like, everything's been perfect.
Speaker 1:Yeah.
Speaker 4:Now, obviously, you know, sort of DCA and, you know, sort of Toronto well, Toronto, I think, didn't end up bleeding at any deaths, but DCA obviously did. Yeah. And I'm not sure that that's really gonna change the culture. Like, you know, FAA aviation, you know, 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. Mhmm.
Speaker 4:Will the Chinese ever really manage to get any traction? I don't know. It's, like, definitely not in The United States ever. There's no way that, like, United States ever letting a United States airline buy, like, a Chinese, you know, sort of jetliner.
Speaker 2:It's the Comac c nine one nine.
Speaker 4:Yeah. And there's good way France's gonna let them, you know, buy anybody other than Airbus. Same thing with the entire EU, so who the hell are they gonna sell their, like, Chinese airliners to, like, Africa or something? You know, I I don't know how big
Speaker 2:of a Malaysia. Maybe Malaysia teleport teleporting
Speaker 4:Oh, did you see that there were some, you know, sort of revealed potential documents of four UFOs surrounding the Malaysian airliner and then disappearing it.
Speaker 1:Okay. Well, we'll have to dig into that next time. Gotta get Jesse Michael to another half an hour.
Speaker 4:I'll get Jesse to come meet at
Speaker 1:the Yeah, yeah, yeah. We'll break it down. I really appreciate you stopping by. Thanks so much. This is great.
Speaker 2:You next week. It's good.
Speaker 1:Bye. Next up, we are going to the founder of a company that Delian is in love with. He's obsessed with these these AI apps. He can't get enough of them. So we're very excited
Speaker 2:to have Geron
Speaker 1:on from captions. I'm actually a huge fan of this app and this company. I use it all the time. Any see anytime you see me post a clip on X and there's captions there, I'm using the captions app.
Speaker 2:That's right.
Speaker 1:It's fantastic. And there's a bunch of other cool features, the company has been just maniacally adding functionality. And as you saw with ChatGPT, you wanted to generate a video. It like, it couldn't do it. Like, These tool usages are increasingly difficult, and they're not something that you can just it increasingly looks like you can't just one shot it with tokens out of an LLM.
Speaker 1:And so building up traditional software around the system actually improves the AI. And so these products are very complementary. So we're excited to welcome him to the show. How are you doing today? Boom.
Speaker 6:Hello.
Speaker 2:Hello. There you go. What's going on?
Speaker 1:How's it going? It's great. Thank you so much for being here. Thank you so much for creating the captions app. I use it very, very
Speaker 4:regularly. DAU, basically.
Speaker 1:Oh my god. I'm obsessed.
Speaker 2:Yeah. Yeah.
Speaker 4:For a
Speaker 3:long time.
Speaker 1:I mean, we're we we make a ton of clips. You've probably seen And
Speaker 2:We make a few clips.
Speaker 1:It's always a hassle to put captions over, but you made it much easier. A lot of that, I wanna talk about, the history of the technology, the Whisper turning point, and then get into value creation and the application layer. There's so much we can talk about. But why don't you kick it off with just introduction on, like, how you're describing the company the these days and then the most recent announcement?
Speaker 6:Totally. I mean, so love that, by the way. You're an OG user, so thank you for being a user. But, you know, it's a pretty young company. Like, we're our product market fit was, like, two and a half years ago.
Speaker 6:Right? So, like, we were four people two and half years ago, and things have grown really, really fast.
Speaker 1:It's hard to win. Success. Adding
Speaker 6:captions, you know, the most basic thing. But it's evolved quite a bit. And so today I mean, the way we think about the company today is, like, you know, video creation is hard. Right? And we've identified two problems, actually.
Speaker 6:Right? One is recording the video is hard. Mhmm. You guys knows it know this. Right?
Speaker 6:And editing the video is hard too. Right? It's pretty technical. We wanna solve these two problems. Like, these two problems, we wanna help people jump over with AI.
Speaker 6:Right? So if you wanna edit video yourself, if you wanna record video yourself, go somewhere else, basically. Right? We're gonna actually do it for you. That's the value.
Speaker 6:Right?
Speaker 1:And So not going after DaVinci Resolve, not going after Premiere, an entirely new market.
Speaker 6:Exactly. Right. And we think of it very similar to Canva. Actually, like, you know, Canva for video as as an idea has been sitting around for a while.
Speaker 5:Yeah.
Speaker 6:And I think it's actually finally possible because of AI. Right? Because the real value of Canva is you start with something. Right? You don't have a blank screen.
Speaker 6:And, you know, it's not built for the designer. Right? Most designers will look at Canva be like, I could probably do better than this. Right? But it's built for the person who's not a designer.
Speaker 6:Right? And that's the same value that we provide. So on that note, right, like, last year, we started working on essentially foundation model technology for video generation and for editing that's gonna help us achieve that. And, you know, these are big projects, very expensive Yeah. But also very cutting edge.
Speaker 6: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? Which is and by the way, like, I'm also, like, kinda surprised almost in a way that we've spent so much time and so much money doing text to video on silent videos. We're like, what what's the point? Right?
Speaker 6:Like, just stop video? Yeah. Yeah. Like, that's that's the negligible part of what a video is. Yep.
Speaker 6:Almost no time spent on videos with actual communication. So that's kind of what we've been focused on for the last year.
Speaker 1:Yeah. What what like, what I don't know. What what, like, breakthroughs are are are the most interesting to you? Obviously, like, Whisper is super important. I feel like Whisper is great, and then all of a sudden it came down to, like, okay.
Speaker 1:Well, I want real time Whisper on the show, and then I gotta go build that. Or, NotebookLM. I like, NotebookLM, like, it still doesn't have an app even though Google is paying people not to work and so it makes no sense to me. And and I'm and I'm imagining that, like, captions could be an app where I'm getting, a Notebook. Lm style, like, YouTube videos.
Speaker 1:YouTube's talked about this a little bit. They haven't rolled anything out. But you're starting to see a lot of this stuff. 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, so it still has that art in there.
Speaker 1:But but what what is exciting you and what's the most interesting in terms of, like, where you want this to go?
Speaker 6:Yeah. 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? Like, there's the text generation, like, LLM type models. Right?
Speaker 6:And those are solving a very difficult problem. It's intelligence. Right? Like, an unsolved problem. No one's solved intelligence before.
Speaker 6:Right? So and by the way, we don't even know what the bound is. Right? Like, where does it end? Who knows?
Speaker 6:It could never end. Right?
Speaker 1:It could
Speaker 6:go on forever. Right? And then on the other side, you got, you know, media generation. Like, this is everything from, like, video generation to music generation, sound, audio, like, all this stuff. Right?
Speaker 6:These are solved problems. Like, we can do rendering today. Right? Like, we can literally render anything you want with, like, CGI and stuff. Right?
Speaker 1:Yeah. Of course.
Speaker 6:It's just becoming a lot easier, and it's also bounded. Right? Which means that there is a limit of realism. Right? And then you've kind of solved it, essentially.
Speaker 6:Right? Yeah. You can't get more real than real. And once you're there, you kind of have achieved what you set out to achieve. Right?
Speaker 6: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 evolving. Right?
Speaker 5:Yeah.
Speaker 6:The craft is different, but the creativity is still there. Whereas on the LLM side, that's actually potentially replacing the human. Not gonna lie. Right? That's potentially what it's gonna do.
Speaker 6:Right? Yeah. So these are two different types of use cases, almost two different types of value that are being produced today, I think, at all. We fall definitely much more in that sort of media generation category where, like, our goal is not to replace anybody. Right?
Speaker 6:It's actually, like, empower a bunch more people potentially. Right? And who knows? Right? People come in, they use captions to make their videos.
Speaker 6:Right? 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.
Speaker 6:Right? Nothing wrong. Right?
Speaker 2:So how did that 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? Where it's like Mhmm. You have Lovable, Bolt, Rippling sorry. Ripplet.
Speaker 2:Replit.
Speaker 1:Sorry. Rippling is a one shot for your HRIS system. That's right.
Speaker 2:True. That's right. 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. 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.
Speaker 2:How do you see and and but that's just, you know, my point of view. What what's your point of view on, like, how all this evolves and how you're looking to continue to differentiate captions over time other than just sort of, like, chasing perfect realism?
Speaker 6:Totally. Yeah. I mean, so couple of things there. Like, I think, generally, kind of to, you know, make a comparison what you're talking about. Right?
Speaker 6:Like, I think of it as, like, Canva for everything. That's actually what's happening. Right? Because the magic of Canva you know, awesome company. I think the magic of it is not about how simple the UI is or something like that.
Speaker 6:The magic is that you start with something. It's not a blank page. Right? And really, the biggest enemy of anything creative is a blank page
Speaker 1:Yeah.
Speaker 6:And not the UI and stuff. Right? I mean, think about, like, design software in general. You look at, like, Figma and stuff. Like, Figma has, like, six buttons.
Speaker 6:Right? Like, it's not a hard UI. Right? But it's really hard to make something good with it. Like, it's really hard to figure out how you use squares and circles to make something that looks good.
Speaker 6:Right?
Speaker 4:Mhmm.
Speaker 6:And I think the magic of Canva is you start with something. Right? You're already 90% there when you enter, and then you kind of make some tweaks to get it to a hundred. Right? And by the way, like, think about ChatGPT.
Speaker 6:It's kinda the same thing. Right? Like, we're using it all over the place today, but it just gets you started. Right? Like, it's like, boom.
Speaker 6:I already have something. Like, I need a job description. Boom. There's job description. Right?
Speaker 6:Yeah. For whatever job you want. Right? And then it may not be perfect. Right?
Speaker 6:You make a few tweaks, you know, change things here and there, and you're done. Right? And so it's like Canva for everything. That's, like, what's happening. And I think same for music generation or, you know, video generation, like, all these things are going there.
Speaker 6:Our goal and our mission in this, like, we're focused on specifically the communications or vertical. Right? So think about this. Right? If you think about a movie or, you know, a TV show or anything like that, right, any kind of, like, media today, only a small part of that is b roll.
Speaker 6:Right? 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 two seconds. And then the camera's in the room, and we're talking. Right? Yeah.
Speaker 6:And that's actually the movie. Right? 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? And that's kind of the the weird thing.
Speaker 6:Right? And, like, our thing is, like, let's get that communication, that dialogue problem solved. Right? Yeah. That's one.
Speaker 6:And on the other side, just footage isn't enough, so let's get it edited to make it actually an asset. Right?
Speaker 1:Can you talk a little bit about, growth for captions? There's a weird dynamic where it can be extremely valuable to go viral with like a one shot thing. I'm thinking of Lenza, those magic avatars that it was just upload a couple photos and you get a photo of yourself. Then we had the Studio Ghibli moment, which was a huge growth vector. It's not OpenAI's product, but it was still probably massively beneficial just to drive a bunch of extra installations and ChatGPT use.
Speaker 1:Right? 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. Of course, you need to put in your own tweak, but that's what we're great at.
Speaker 1:But you don't wanna get pigeonholed into that, but it can be a good growth driver. Are you thinking about that cons consciously? Are you thinking about, like, how can I get the next how can I get the next Studio Ghibli moment to happen in the captions app?
Speaker 6:Yeah. I mean, so we are. But our philosophy on this, honestly, like, think about both the Studio Ghibli thing, but also think about, like, original ChatGPT. Right? Like, I remember the time where, you know, GPT was available.
Speaker 6:Like, I would use I would show it to my friends, check this out. Like, check how how how cool this is. People will be like, oh, wow. Cool. Okay.
Speaker 6:Yeah. They're like right? And then suddenly ChatGPT came out and, like, by the way, I think it was very clear that they hadn't prepared for the amount of that thing got. Right?
Speaker 7:Like Oh, yeah.
Speaker 6:Even the name ChatGPT kind of gives that away.
Speaker 1:Yep.
Speaker 6:Right? And so it wasn't a planned thing. It kinda just happened. Right? So we give you the same thing.
Speaker 6:I don't think they planned it. Like, it just kinda happened. Right? 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, they they can play around with it, make cool things with it. Like, these types of moments kinda happen naturally.
Speaker 6:It has happened for us several times with different technologies we released in the past, and a lot of times it's been unplanned. It's just like, you know, when we plan for it too much, it doesn't happen. When we don't plan for it, it just, like, suddenly explodes, like, completely. Right? So that's kinda what we've seen.
Speaker 6: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. Both people are just blown away. It's just so impressive. Right?
Speaker 6:It's beyond anything anyone's ever seen. Right? And I think that is a pretty high bar. So building on that, building in private until we reach that bar, releasing it as like a, wow. This is, like, crazy.
Speaker 6:Like, that's the type of stuff that we've seen work really well.
Speaker 2:Next question? Do you have any sort of visions around what the just video content on the Internet in 2030? Because I have this right now, there's not a huge incentive to make a video for one person. Right? Especially in a business context.
Speaker 2:If I Right. If you wanna explain something for ten 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. 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. And so I have this sense that content generation is gonna like hundred x, thousand x, but human attention is not going to hundred x or thousand x. Right?
Speaker 2:It's just not possible. There's only so much time in the day. People use their phone for six, eight hours on average right now. They're still spending two hours a day on Netflix, but we're not gonna suddenly, like, get, you know, a hundred hours a day even though people on, you know, TikTok entrepreneur influencers might might want that. So I just have this kind of question around, like, do you think the average video in the future gets one view, two views?
Speaker 2:And and maybe it's not the average, right, because certain views will or certain videos will still go super viral and be sort of cultural phenomenons. But but, yeah, I'm curious if you think that's kind of, like, where we're headed.
Speaker 6:Right. I mean, think for what it's worth, I think the average video today is getting probably one or two views. Right? 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 of our private communication.
Speaker 6:And, honestly, like, Snapchat pioneered that. Like, they kinda missed the TikTok part of it. It wasn't part of their ethos, to be honest. Right? Mhmm.
Speaker 6:But, like, they were more about the private communication. But I I think the future is more video. Like, for what it's worth, like, you know, the way and I 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 communications change over time. Right?
Speaker 6:Like, we're not sending letters to people as often anymore. Right? Like, text messaging is kind of, like, very prone to miscommunication. Right? Audio is definitely better phone call.
Speaker 6:Make goes a long way. Video call is, like, one step further. Right? And then real life meeting is even beyond that. Right?
Speaker 6:Oftentimes, 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? And you gotta watch for that. Whereas an in person team just trust each other so much 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.
Speaker 6:But I I do think that actually even on the AI side, we're like, sure. ChatGPT makes me a great writer. But, like, what makes me a great communicator? Right? And we're really not thinking about that.
Speaker 6: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's moving, like, all that is communicating in multiple forms, right, a message. And that message changes if I change any of those things.
Speaker 6:Like, word words might be the same. Right? But I can change the message completely by just changing the delivery of it. Right? So I think today's technologies, like, just aren't capturing, right, like, how broad communication actually is.
Speaker 6:And I think it will all evolve towards video over time just as we've seen. Like, this is not new. We've seen this happen before. Right? So and by the way, like, I was at Snap when, like, TikTok took off, right, 2019 Mhmm.
Speaker 6:That era. And initially, like, TikTok grew a lot on the back of Snap. And not a lot a lot of people know this, but, like, they were running, like, a hundred million dollars a month of ads on Snapchat, right, initially. Right? When there were not there was no fox
Speaker 2:into the hen house. Yeah.
Speaker 6:And, like, there was concern, like, in the company. People were concerned that, like, are we set are we, like, creating a competitor here? Right? And people were running AB tests. Yeah.
Speaker 1:Narrator. They were.
Speaker 6:They were. Exactly. Anyway But, like, a they we ran AB tests to test. Right? Like, if someone sees a TikTok ad, are they less likely to engage in Snapchat?
Speaker 6:Tests didn't show that. Right? But the reality is that it wasn't true. Right? They they did spend less time with Snapchat.
Speaker 6:So
Speaker 1:Well, we gotta run. This was a fantastic conversation. Thank you so much for hopping on, and we'll we'll definitely talk to you soon.
Speaker 2:Yeah. Great great talking. Thanks for coming on.
Speaker 1:Bye. We got Ian in the waiting room from Astro I believe I'm pronouncing that correctly. AstroMecha.
Speaker 2:Great. Mechanica?
Speaker 1:AstroMechanica. Sorry. I missed I I mistyped that. AstroMechanica. Anyway, we'll let him explain it to us.
Speaker 2:Come on in, Come on in, Ian.
Speaker 1:How are doing?
Speaker 2:Sorry for the wait.
Speaker 1:Yeah. How do you pronounce the name of the company? Let's settle this today once for a while. Yeah.
Speaker 9:Astro Mechanica.
Speaker 1:Astro Astro Mechanica. There we go.
Speaker 8:Yeah.
Speaker 1:Can you give us a breakdown of of what you do? And I'd love to hear, like, the the the brief history on the launch. I remember there was, like, a video you posted of building something, maybe in a garage. It went viral. It was very cool.
Speaker 1:And there was some debate over it. And now it's a real company. Raised a bunch of money. So take just take me through the little journey.
Speaker 9:Yeah. Yeah. I I guess it starts with my background of like, I'm lifelong aircraft builder, pilot, fly jets, the whole nine on that. Yeah. And
Speaker 2:yeah, you You flew you've where what kind of jets did you fly? Like, you kind of
Speaker 9:skipped through Private private jets. Mhmm. I built like, I built my first plane when I was 17. I did experimental airplanes, drones in, the early two thousands before drones were a thing. So it was from that, like, I and I think with, like, a lot of good companies, you're really just building the thing you want.
Speaker 9:Yeah. This is just not a thing that exists. Unsurprisingly, one cannot just go buy like a bleeding edge fighter jet. Yeah. So so yeah, you know, going with I'd always been obsessed with all the technology.
Speaker 9:Interestingly, was working on, like, this hybrid electric architecture initially coming from the private jet world for lower cost of operation.
Speaker 5:Mhmm.
Speaker 9:It's just, like, simpler systems. And it turns out there was a really neat technological unlock for supersonic flight. So that's where a lot of this kind of kicked off, and it was an especially novel architecture. I think this is why it was just so alien. Like, I had just been spending so much time in all of the the various, like, subcomponents and and disciplines there.
Speaker 9:It's like, there's this really unusual combination. When you combine all these things together, you get this totally new architecture. So the big one for us is, like, transition up to what we call a ramjet mode.
Speaker 5:Yeah.
Speaker 9:So, you know, like, are really good solutions for like, I really like what the Hermes guys are up to. Yeah. 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. Mhmm.
Speaker 9:And the other thing that comes up a lot is, like, people are seeing all the engine stuff. Yeah. You know, some people think we're an engine company. It was more it's like if you want to have a computer, you have to make the microprocessor first. Okay.
Speaker 9:But this round, getting this done, is like finally shifting it to us going into the aircraft development. So Okay.
Speaker 1:So you're building a plane?
Speaker 9:Yeah. Yeah. I mean, that's my background. Like, I was a plane guy that just needed a better engine.
Speaker 1:That's awesome.
Speaker 9:I just needed a better engine. And so, yeah, we're we're at that stage now with the round done. 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. So, like, people knew I was good at building stuff. 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.
Speaker 9:Because, like, good engineers see an interesting, like, technical solution and thing to work on. Yeah. So, I mean, I I love my team. Everybody's, like, incredible here. So, like, we've now got that.
Speaker 9:That then makes it easier to get more capital.
Speaker 1:Yep.
Speaker 9:Then we've been spending some time in DC. I mean, like, Andreessen's been been great with this. And and, like, you know,
Speaker 8:you it's also very important to
Speaker 9:have an actual customer. 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. Like, I
Speaker 2:Oh, yeah. What I'm business. 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 full Yeah. Let's go full send.
Speaker 9:So, yeah. I mean, in a nutshell, it's, you know, make the engine so you you go in the initial, like, demonstrator phase. So demonstrated the engine. That got the money to now build the demonstrator aircraft. The one we're pushing for is the world's first nonstop transpacific nonstop supersonic aircraft.
Speaker 9:So we could do, you know, California to Taiwan without refueling in under four hours.
Speaker 1:Okay.
Speaker 9:So I mean, it sounds
Speaker 1:like direct competitor boom. It's been a decade and boom.
Speaker 9:No. Really so so, yeah. I mean, you know, Blake's going for, like, airliners and Sure. He he so we're we're focused on again, my world is more private jets and
Speaker 2:really Yeah. So is this a Gulfstream? Are you are you coming for a Gulfstream or or or Yeah.
Speaker 9:It's more like we're we're coming for net jets, if you know, something like that. Sure. Yeah. Cool. Gonna spend the next seven to ten years doing DOD.
Speaker 1:Okay. Interesting.
Speaker 9:Like, you need to have an actual it's so expensive to make an airplane. Yeah. Course. It's not hard to make a thing fly. It's hard to make a thing fly that is safe enough to put people on it.
Speaker 9:So my strategy on this is you go to a space like, well, unmanned drones, military where technology and capability matters first.
Speaker 1:Yep, totally.
Speaker 5:You can
Speaker 9:put out there. Can there's going to be things that are going to come up, you're going to
Speaker 7:learn it. It's just it's
Speaker 9:a cheaper place to learn. Then you're in a position where, like, well, 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 pounds. Like, they're not small planes.
Speaker 1:Yeah.
Speaker 9:Yeah. I'm and I'm curious the wrap up.
Speaker 2: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
Speaker 9:I mean, I am a pilot so I have feelings on that, but it is it's definitely something of, like, no one this is another kind of odd thing. No one has ever used autonomy in the certification and development of a manned aircraft. 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. The only way you really prove it's safe is you've flown it. And so if you have a human on board from day one, you can't take the risks that you want to.
Speaker 9:Like SpaceX proves this with Starship where you're like, you know, the actual cost of the hardware is not that high. So you're better off being really aggressive Mhmm. Getting things in the air, derisking. I mean, again, you're saying this at Hermes 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. Yeah.
Speaker 9:And you're like by the time it's like if you want to get to very good things, you want to do more iterations. So this is our similar strategy. I mean we develop new engines every like four months. Yeah. And I think
Speaker 1:we're driving that Waymo kind of took a similar path where like there weren't random passengers in the back for years and you'd see, there's just a safety driver in there. And then eventually they pull the safe driver out and put the passenger in the back.
Speaker 9:Exactly. Yeah. You just want to spend time where you can map you can map out all these weird little edge cases, things like that. 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.
Speaker 9:Mhmm. Because eventually you kind of lock into a point where like everything will be so expensive that you wanna have you don't want to make any any changes. It's just too costly to do to that point. 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. And, yeah, we can we can derisk it all, learn all the hard lessons.
Speaker 9:And, you know, in the meantime, like, it's also very cool just getting to make these things. So, you know, it's photogenic work. Everybody loves seeing the engines on Twitter and stuff like that.
Speaker 1:For sure.
Speaker 2:Yeah. No. It looks it looks incredible. I'm curious. A 16 z makes sense in the round.
Speaker 2:Lower carbon was a big logo there. Is is that Saka and his team saying like, this is really cool, we wanna back it? Or is there a is it a fuel efficiency, you know, kind of kind of thing in the long run?
Speaker 9:Yeah. The so my the very first check institutional check-in the company was actually Lower Carbon and Xiao at Lower Carbon was was my guy.
Speaker 7:Nice. And
Speaker 9:and he was betting on it. It was just me in the machine shop, and I, like, I had you know, was getting close to that first prototype. And so, yeah, from there, like, the system we get the range because it is more efficient. So so, yeah, there's just an obvious efficiency argument here. The other one for civil applications, not for DOD, but for civil is taking a page out of the rocket book.
Speaker 9:We don't plan to use jet fuel. So rockets have switched to LNG or liquid methane. It's if you just swap to that fuel, it's 30% less c o two just as direct fuel swap. It's more energy per unit weight. It's 50 megajoules versus 42 per kilogram.
Speaker 9:Whole bunch of benefits. There's a reason the rocket folks went to it. So this is another one that's kind of insane bets for, like, if you're Boeing or someone. Like, you're not gonna suggest a thing like that. But when you're starting from nothing, you can you can make these these bigger bets.
Speaker 9:So, yeah, you know, if you were to do the combination of the engine plus the fuel change, you're around 60% less CO two. And then there's guys like I love Casey Hanmer at Terraform. There's a lot of folks working on synthetic fuels. If you have an engine architecture around, you know, LNG, I think that's the best fuel for electrosynthesis. So if you wanna have, like, inexpensive decarbonized fuel, it's also your best option.
Speaker 9:So, like, options first, solve for economics of, like, LNG is a tenth the price of jet fuel. 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. So first, solve for economics, then go for that.
Speaker 2:Smart. Yeah. Bit of a random question, but I'm curious since you're an aviation nerd. China earlier this week dramatically canceled some Boeing orders. They have their own internal aircraft that it's like Comac, the c nine one nine.
Speaker 2:Yeah. Do you see them, like, permanently trying to shift over to that? Or is it just so hard to build a plane that they're gonna kind of kinda keep coming back to Boeing and and Airbus over time?
Speaker 9: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 and Whitney and GE components, things like that in what we're doing, that's sort of like being TSMC. That one, I don't think they could get figured out anytime soon.
Speaker 9:And the Comac uses, you know, still American engines. So 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.
Speaker 9:It just depends on how as with all these things, it's just a money pit. How much do you want to throw into it?
Speaker 2:But why is it so so what are what's the componentry of, the j 35 then? Why why can they do that? But but which is like a, you know, defense application versus a commercial.
Speaker 9:It's so, again, to this thing of it's not hard to make a thing work and fly. I mean, I did this in my shop kind of as proof of, like, getting a thing to initially go, not very complicated. The economics of air travel are dependent on it never breaking. And that is a you don't really know that like, even Pratt and Whitney with a recent Geared Turbo fan is like, it's gonna be like a decade until they get payback on that. And they know how to make things like that.
Speaker 9:So this is the sort of challenge you run into of, you know, what is gonna come up, you know, after five thousand hours, after ten thousand hours. And it turns out this thing. It's like, oh, there's cracking on this component, and now the engines and, like, meanwhile, you use what we've got right now. You're like, yeah, it's good for 30,000 out like, the CFM 56 is like it's like 50 to 60% of all airliners. They're narrow body ones.
Speaker 9:And, like, that engine can stay on wing for almost thirty thousand hours. Mhmm. And it's just so proven. And this is the thing you see in aviation where, like, there's always these things that seem really appealing because it's a performance optimization. You're like, well, of course, I wanna burn less fuel.
Speaker 9: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. So that's where that that's gonna come up. It's just not something that's like obvious on day one. Mhmm.
Speaker 1:Well, congratulations on the round.
Speaker 2:Well, we'll the shot. To you and the whole team. An overnight success.
Speaker 1:You. Overnight success. Thanks for coming on, Seriously, I appreciate you coming on and and breaking it down for us. Thanks so much.
Speaker 7:Of course.
Speaker 9:Yeah. See you.
Speaker 1:We'll talk you soon. Bye. Next up, we have Shyam Sankar from Palantir. There's a ton to talk about with him. He's published 18 theses about the defense reformation, the primacy of winning, and also just sits in a very interesting place as Palantir's first forward deployed engineer.
Speaker 1:And so I wanna hear, what he's hearing from Palantir customers mostly. Anyway, Sean, welcome to the show. How are doing?
Speaker 8:Thank you guys for having me.
Speaker 1:Yeah. Great being here. Yeah. I wanted to kick it off with, what is the biggest topic of discussion over the last two weeks? Tariffs, h twenties, NVIDIA, something else.
Speaker 1:What is driving conversations through the partners that you work with at Palantir?
Speaker 8:I think the it's enterprise autonomy. You know? It's like there's a normative view of the the most valuable application of AI is is clearly towards autonomy in the enterprise. And then you can think about it you can reason about it by analogy. If you thought about the self driving car journey, it took us twenty years to get from a prototype that drove through the desert a 20 miles, pretty good demo in 02/2005
Speaker 1:Yeah.
Speaker 8:To a commercial self driving car service, and no one wants to be on that 20 journey. What what have we really been doing over twenty years? We've been handling edge cases. Yeah. Right?
Speaker 8:So really investing in the tool chain that allows you to get from a a mandraulic world to one where you have AI agents that are totally automating your business. Like, we've automated sepsis monitoring at at Tampa General where they deaths from sepsis have reduced by half. We've automated high how AIG underwrites insurance. What used to take three weeks and you'd only get to ten weeks. Ten ten percent of your submissions, it takes less than an hour and you get to a %.
Speaker 8:So I think and it really is gonna feed into this winner take most dynamic. It's not just about cost savings, about your competitive advantage. 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. There's just John Boyd's OODA loop, observe, orient, decide, act. Yep.
Speaker 8:Or sometimes, my favorite admiral says the American OODA loop, observe, overreact, destroy, apologize. How do you how do you bring, lethality to that? It's just doing it much faster, and
Speaker 9:you're gonna do
Speaker 8:that way faster with AI.
Speaker 1:That's amazing. Tyler Cowen called, April 16 yesterday AGI Day. He has called it. What was your reaction to
Speaker 2:the opening ideas? Happened internally at Palantir, like, you know, months ago. But,
Speaker 1:yeah, I mean, how are you processing this idea of AGI? Obviously, it accelerates everything you're doing. But what is your take on model scaling, reasoning, agentic workflows, all these different things? Like, what what are you looking for? Where where are there breakthroughs breakthroughs that remain versus what are we just gonna need to go implant?
Speaker 8:Well, I think we're well past the threshold 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 decomped in a way where it succeeds, or do you need eight? Mhmm.
Speaker 8:Like, the coolest stuff that I've been seeing is, like, multiple teams internally at Palantir are building AI FTEs, and it's really compelling. It gets really far. It it attacks different parts of the stack. You know? So, like, if every user could have their own on demand infinite, essentially, AI, FTE, like, how much more stuff can you build?
Speaker 8:How much more quickly can you adapt? What's your OODA loop as a company now? So I think we're deep in the the implementation phase. If AI is electricity like, in electricity, all the value didn't accrete to the people who made the turbine generators. It went to the people who made the tools that ran on electricity.
Speaker 8:And I think there's just we're just so excited about proliferating and building those tools out.
Speaker 1:Yeah. How are you thinking about, just commoditization of the model layer? Obviously, it's like a horse race. Every different month, the different models comes out. How has Palantir approached integration with different, foundation models?
Speaker 1: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? Does this feel like cloud to you? Does this feel like mobile to you, in terms of, like, your agnostic approach, or is it different in any way?
Speaker 8:There are parts that definitely rhyme with it. It's more agnostic than not. I said early on at at in the AI revolution that we thought the right approach was k LLMs. Like, why would you pick one LLM when you can have k?
Speaker 6:Yeah.
Speaker 8:And then you really can start thinking about the tool chain that you need to build around that. There's numbers there are a number of reasons. The first, like, very clearly, you had model commoditization. If you look at both open and closed models over time, you know, the elos are just up into the right. The open ones have converged and even in some cases surpassed closed models.
Speaker 8:And at the same time, the price of inferences dropped like a rock. 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 gonna be a raw business.
Speaker 5:Yeah.
Speaker 8:So then there's a question of, 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? The model is improving rapidly. How are you gonna safely be able to evaluate the the the relative performance of models as new models come out?
Speaker 8:So you need you need that sort of tool chain. And even more, deliberately, you know, these models get end of life. Like, you can't get the original GPT four anymore. Right? You have four o.
Speaker 8:And so if you've built an entire enterprise that runs, assuming some model is gonna exist in perpetuity, that's probably not gonna work out that well for you. So you're gonna 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?
Speaker 2:How are you thinking about 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 twenty twenty, thirty, and kind of beyond about, you know, how different robotic systems are are integrating with the Palantir 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 out in the world.
Speaker 8:In many ways, we we already do this. Know, we have, like, more than 300,000 workers, blue collar workers who turn wrenches in our software every day. Everything from the factory floors of Chrysler to every Airbus airframe, every HD Hyundai ship. If you think about a company like Rio Tinto, so much of the mining operation is actually autonomous. The the railroad cars that that take iron ore from where it's mined to the ports, that's completely autonomous.
Speaker 8:The the three story tall dump trucks that are actually trucking out the ore, autonomous. And so it I don't wanna trivialize it, but in some sense to me, it's more of like a difference of degree than kind. You're you're you're machine to machine communicating to a system. That system just happens to be smarter and smarter every single day.
Speaker 1:During the, metaverse boom, Satya Nadella was talking about building digital twins. 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 Rio Tinto 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?
Speaker 8: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 posing a change to a system here. How can I understand it? Like, is that change gonna work? What are the unintended consequences of it if I make that change? What are the new bottlenecks that different functions have to think about?
Speaker 8:The the simple example I always use is the procurement guy is really excited because he bought, you know, discount raw material 30% off the list price, and the production guy is pissed off because this discount material has 40% less yield. Right? 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 making across it. So you know when the left hand is is robbing from the right hand.
Speaker 1:Can you talk about the early days of Palantir, maybe one of the first major wins or setbacks? Or kind of like, what's the story that you tell to new Palantirians to kind of set them up for maintaining the culture? Because I feel like Palantir has done a great job of, like, maintaining the quality bar. You haven't become that place where people kind of go and, like, rest and vest, basically. But you are, like, kind of a big tech company now.
Speaker 1:What's the story that you tell to kind of set the culture?
Speaker 8:I mean, there's so many stories. I really I'll tell you how I set the culture at the end, I promise. 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. Like, I I remember we had this gatekeeper between us and a government customer, and he installed an early version of our software, and he wanted to test it out before he passed it on. And it crashed, and he blamed us.
Speaker 8:And it and it crashed I mean, in those days, this was a server with two gigs of RAM, trying to run a four gig Java heap, and he didn't understand why it crashed. Right? It's like the we just developed this extreme ownership mentality because anytime we outsourced even an iota of responsibility, it blew up in our face. And that's you can see for deployed engineering as, like, the extreme manifestation of that, that we're gonna 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. But the the the story I tell to kinda spill the beans on so your your first AMA with me when if you're onboarding in week one, at the I always end the AMA by reminding people that counter is a flat place.
Speaker 8:What does flatness even mean? Well, to me, it means that every single employee is willing to tell me to fuck off to my face. And I am all say fuck off in unison out loud at at the very end. I think it's important. I wanna institutionalize the notion of rebellion
Speaker 2:Yeah.
Speaker 8:That, you know, I don't have all the right ideas. There's so so many things we've done over time I didn't think we're gonna be right, and they were right. And, you know, you you gotta 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?
Speaker 8:I don't I don't really know what your career correct progression is gonna 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.
Speaker 1:Yeah. Can you talk about, what's going on with the cultural transformation in Washington right now? You've written, like, maybe it's transformation going into founder mode. But within some of the more nitty gritty, maybe swampy institutions, is is there a need to be able to tell each other to f off or, just be more confrontational? What should DC learn from Palantir and maybe even vice versa?
Speaker 8:Well, I I don't know if DC I would say it seems like very some, presumptuous for me to say what should DC learn
Speaker 1:from Palantir? But what
Speaker 5:excites
Speaker 8:me about the present moment is, in Palantir 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 anodyne notion of how we wish the world works but doesn't.
Speaker 1:Mhmm.
Speaker 8:And that's, like, allowing us to reexamine a lot of assumptions for first principles. 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. Why do doors fall off airplanes? Why does it seem like these institutions aren't working?
Speaker 2:Mhmm.
Speaker 8:You have a c suite that is, if you steel man 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. It's not connected to anything. Mhmm. And then you have people hardworking people on the metaphorical factory floor who kinda look up and say, how could they be so disconnected?
Speaker 8:How could they not understand what's actually happening here? And and so much of that is, like, the levers of orientation are somehow filtered through a lot of people in the middle. Leadership doesn't have access to real time information. If you if you couldn't know, like, if you were navigating a car and the latency of understanding where you are was an hour, you'd crash. 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.
Speaker 8:Yeah.
Speaker 1:And we need more, like, individual champions. Peter Thiel has that quote about, like, we need ticker tape parades. Ezra Klein is now talking about with the abundance. He's he's, he's highlighted the failure of the California high speed rail system. And what I found interesting about that is that it's very hard to pin down, like, California high speed rail, everyone kind of agrees, like, project's not going great, but no one can really say, like, who is even the champion of that at any point in time?
Speaker 1:Like, no one's really responsible at any point in time. Does does the government need more individual accountability or, like, I don't know, even, like, project level CEOs or something? I don't know.
Speaker 8:Well, the yes. The short answer to that is absolutely yes. Like, I I think about it in terms of heretics and heroes. You know? It was Somerville who built the Pentagon in sixteen months.
Speaker 8:You know? It was Jean Krantz who led the Apollo program. There's something about our kind of Midwestern Calvinist sensibilities as a country where, like, it's the Apollo program and not Jean Krantz. It's the f 16 and not John Boyd's plane.
Speaker 5:Sure.
Speaker 8:You know, it's nuclear navy, not Hyman Rickover's navy. That's great. I appreciate that sensibility tremendously, but it shouldn't, 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.
Speaker 1:Yeah. Can, can you give me a little bit, expanding on that? Can you give me a little bit of history on the dollar a year men and that story?
Speaker 8:Yeah. In in World War two, we actually had a program for, very skilled people, corp corporate leaders, engineers. They could, for a dollar a year because volunteerism was illegal. You could not volunteer to work for the government. So as we were preparing to go to war, as we went to war, they would actually join the government as dollar a year men.
Speaker 8:They would get $1 of salary, and they they would actually be able to be deployed on the nation's most important impactful problems. And sometimes they would retain their old jobs. Sometimes they wouldn't. It would really depend. But you could get the right person on the job.
Speaker 8:And I I think that's really important because if you think about even World War two, our mobilization came down to one man, William Knudsen, a Danish emigre who actually invented mass production. He was the number two at Ford where he invented mass production. He got in a fight with Henry Ford and went to GM as the number two. And, you know, FDR asked, Bernard Barsch, who should I choose to do this? He said, I have three names.
Speaker 8:William Knudson, William Knudson, William Knudson. Mhmm. It's like, it really came down to a counterfactual. We had, like, one guy who could actually move all of American industry. And the way that he assessed, you know, he was an engineer himself.
Speaker 8:He would, like, meet people and understand, like, is it believable that you, a steering gear company, can start making artillery knot? Are your engineers smart enough? Do they can they answer my questions? Boom. Here's a contract.
Speaker 8:Let's get going. And, you know, it wasn't a fiction writing contest. It was really a a pressure test mind to mind.
Speaker 2:Interesting. Can you talk about the executive order from last week, the defense reformation? You had a great post on it, but I'd love for you to kind of break it down live, for the audience.
Speaker 8:I think it is the single biggest change that could prepare us to avoid World War three here. You know, if you look at, you know, what has happened to The US since we won the Cold War, We've really had the rise and empowerment of this monopsony, a single buyer that is the government and an addiction to, that monopsony telling us what to build at what price and how it's all gonna work. That's very different than the free market. You know? Some fundamental level, you either believe in the free market or you don't.
Speaker 8: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.
Speaker 7:Yeah.
Speaker 8:And and this this luxury of having the monopsony grow to the scale it has is a consequence of having no peer competitor. But that, you know, that world really went away arguably in 2014, the militarization of the Spratly Islands, the annexation of Crimea, Iran's pursuit of the bomb. Like, deterrence is lost, and we need to rise to that. And I think this is a clear acknowledgment of of very much that in this administration. But the EO says, we prefer to buy commercial items.
Speaker 8: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, reward entrepreneurs for what they're building rather than custom building and developing things on our own. And we have a we have a long history. You know, a monopsony is always gonna desire control, but it goes all the way back to Andrew Higgins and the boat that won the war in World War two. Andrew Higgins, was the guy from Louisiana. 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.
Speaker 8:And at his own expense, he built the Higgins boat, and he he showed up. He showed it to the navy. The navy wouldn't even let him compete. They kinda dismissed him. Then a young marine who became very famous, Krolloc, he later he got him into the competition.
Speaker 8:He won the competition, and then instead of buying the boat, the navy stole the, sold the plans and tried to build the Higgins boat themselves, which they failed to do. And then finally, you know, at the at the eleventh hour, of course, we do the right thing. That's a classic American trait. And, and Eisenhower said that's the boat that won the war. And so, you you know, the predator was developed as a commercial item.
Speaker 8:It was not developmentally done inside of the government. Abe Karim built it. General Atomics picked it up. They financed all the r and d themselves. You know, the air force, of course, hated it because it was unmanned.
Speaker 8:It was kind of emasculating. And, you know, when nine eleven happened, it was the thing that met its moment in a in a massive way here. And and there's so many examples. Like, now we have whole companies built around this company. It's like Androle.
Speaker 8:The entire approach is commercial first, investing private taxpayer capital into r and d, absorbing putting the pebble in the right shoe, you know, putting the pebble in the entrepreneur shoe rather than in the taxpayer shoe. So this EO is actually this law. In 1994, we passed a law called the the FAFSA, the Federal Acquisition Streamlining Act, that said it is the law that if a commercial item exists, you must buy it.
Speaker 1:Yeah.
Speaker 8:It's actually a very stringent test, three part test. So if a commercial item exists that meets your requirements, you must buy it. If it doesn't, you must see if you can change your requirement to meet the existing commercial items that do exist. And if that's not possible, you must see if you can ask the company to change their product to meet your requirement. Only then are you allowed to go custom developmental.
Speaker 8:So this is the most violated law in the land. And I think having the administration say, look. This is statute, and we agree with it, and we're gonna enforce it is is how we're going to field a huge amount of deterrence between now and 2027. You know? There's not a lot of developmental things you can do between now and then.
Speaker 8:There's a huge amount that you can do with the innovation of entrepreneurs and the commercial industry.
Speaker 1:That's amazing.
Speaker 2:Do feel like cyber warfare has been too normalized on on this planet? 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. Meanwhile, there's any type of sort of kinetic conflict globally. It's like immediately front page or it's on CNN, things like that. 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?
Speaker 8:Mhmm. I think you're spot on that some there's something very strange in how little we talk about it.
Speaker 1:Quite well.
Speaker 2:It's yeah. It doesn't photograph well.
Speaker 1:It doesn't photograph well. But picture are
Speaker 2:gonna make from is that in the future, if we have a hundred thousand humanoids, you know, roll you know, going around Yeah. A single city and suddenly they all are stopped.
Speaker 1:That's bad.
Speaker 2:That will start to photograph pretty well. And so I imagine in the future, it won't be just kind of brushed under the rug and Yeah. 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.
Speaker 8:Well, one of the most devastating consequences of it being so kind of below the waterline, something we don't wanna talk about, is the normalization of, like, what can you do about it? The sort of nihilism 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. Not this 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. 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.
Speaker 1:I mean, speaking of popularizing just general shifts in in thought about defense and the importance of, like, public private partnerships in the government, can you talk can you take us through the defense reformation, 18 theses, the your thesis there, and then kind of the impact? And is is it a jobs not finished situation, or, has has defense tech become enough of a meme now? It seems like Silicon Valley is, like, fully on board in my opinion, but, at the same time, there's a lot more that we could do.
Speaker 8:Yeah. I think we we've earned the right to, to to to have an at bat. Sure. So, like, we gotta perform now for sure. I I'd say the fuller die I've touched on some of the themes, but the fuller diagnostic is the government has kind of historically made it a bad business to work with the government.
Speaker 8:Mhmm. You know? And and you you think about, like, our examples from the past. Like, at Intel, Bob Noyce would not let more than 4% of his r and d budget come from the government because he, as the inventor of the transistor, wanted engineering control over the road map and what he's gonna build. He always had in mind a broader commercial market that was gonna drive the price performance that was needed.
Speaker 8: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 and to make us an interplanetary species.
Speaker 4:Mhmm.
Speaker 8:You know, it it's not just about launching rockets and satellites into orbit here. 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 u two, which we fly, and the s r 71. He is this heroic figure. So much of this innovation has come from these legendary engineers, these heretics, as I call it.
Speaker 8:Today, you think about it as Northrop Grumman, but it was Jack Northrop and Leroy Grumman. You know? It was not Lockheed Martin. It was the Lockheed brothers, and it was Glenn Martin. And and it was really so founder driven.
Speaker 8:The aerospace industry subsidized its own existence in the interwar period between World War one and World War two because the government didn't think it needed it. So, you know but for private industry being willing to lose money for a decade plus, World War two, we would have been in a very, very bad place.
Speaker 6:Mhmm.
Speaker 8: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 gonna survive. Today, we have five.
Speaker 8:For every dollar we were spending in defense, we started spending only 33¢ overnight. It was it was a huge cut. The peace dividend, as it's called. Yeah. Consequence that conventional people take away from this is, oh, that's when we lost competition.
Speaker 8:We went from 51 down to five. I don't think that was the the actual issue. The real issue is that consolidation bred conformity, and the conformity pushed out all of the heretics. It pushed out all of the founder personalities that you need to make this stuff really work. My reason for immense optimism in this moment is that the founders are back.
Speaker 2:You
Speaker 8:know, more than a hundred billion dollars have been deployed in the national interest. You have Palmer Luckey. You have the Seng brothers of Shield AI. You have Dino and Cyronic. You have all these crews of really, really compelling humans, really, really compelling founders working in the national interest again, pursuing heretical ideas, will it 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.
Speaker 1:Can you talk a little bit about the startups that are building on top of Palantir and take us through AIP?
Speaker 8:Yeah. 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 back end. It's a way of saying, look. This is the shape of not only my data, but the logic of my enterprise.
Speaker 4:Mhmm.
Speaker 8: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. 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. 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, for these companies. So these these companies are building everything from, the European Cricket network to people who are building, pharma companies, hospital operations companies.
Speaker 8:In defense, it's it's very popular because we can give you an SDK that wires you into twenty years of data that has been integrated into the instances of Palantir that exist in the defense community that your users can authenticate to. So it just speeds a lot of the 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. But it's it's really about speed. I and that that ability to build on top of the platform, it's not just for third party developers. When hurricane Helene happened in North Carolina, green suitors, folks in the army in the hundred and first, built their own app they built their own hurricane common operating picture on top of the platform.
Speaker 8:So that ability to respond to the need, it's it's our it's the code version of the OODA loop.
Speaker 2:Yeah. What advice would you give somebody maybe graduating college today that's evaluating joining, you know, maybe a seed stage company versus a a scaled company like Palantir or or or something like an Anderol? I imagine you at times had a ton of different pressure from VCs being like, leave, we'll give you $10,000,000 to do whatever you want. Like, don't you wanna be a founder? Yet when I look at opportunities, you know, in anything defense related, it seems like if you have a finder founder mindset, there's so many great opportunities to just go to a great company and kind of take on that sort of, like, founder level ownership over a specific problem area or product set or things like that.
Speaker 8:Yeah. 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 gonna work with the most compelling people? Because, like, your rate of learning is gonna be a function of those people and have access to the greatest surface area around problems. Like, my model for growth is not progressive overload.
Speaker 8:You know? The Incredible Hulk did not become incredible by just lifting a little bit more weight every single day. It's like a near fatal dose of gamma rays that probably has, like, a fifty percent chance of killing you. So which company they're gonna, like, throw you off the deep end and give you that opportunity to have, like, superhuman, superhero growth, that's, like, that's the value maximizing thing. And I would remind my son that, like, your point of of extreme growth is gonna be coincident with your point of maximal pain.
Speaker 8:So, like, your ability like, know, it's like as Greg Lamont says, one of my favorite quotes, championship cyclist, it doesn't get easier. You just go faster. You know? And just just understanding that, like, that's what it looks like. So don't don't sell out for the opioid of a linear career progression with a clearly mapped out path.
Speaker 8:I'm pretty sure that's retarding. Like, that's lead shielding that's preventing the real gamma rays from getting to you here. You know, find places you can throw yourself off the deep end. And I I I bet there are some c stage companies that are perfect for that. I bet there's some c stage companies that are horrible at for that.
Speaker 8:You know? It really is pretty specific.
Speaker 1:Does that tie to the the primacy of winning mentality? Is is that, like, all is that essentially, like, derivative or, like, the same concept?
Speaker 8: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 I feel like it's one of the most important things I learned at Palantir. You know, we're all kind of programmed in our conventional education to feel like there's a process, there's an approach. Yes.
Speaker 5:If you follow this
Speaker 8:playbook, you know, you'll win. But it's actually like, it it starts to conform to how you wish the world would work. It it becomes hard to decide, is that actually the cargo cult, or is that how the world does work? Like, you can keep marching around these fields in Micronesia. The planes aren't coming back.
Speaker 8:You've misunderstood the physics of the universe here. And and just if you just anchor yourself, like, but is this working? Like, is it win? And then blow up anything that's not working.
Speaker 1:K. Last question on cargo culting. Cargo culting, the forward deployed engineer, good or bad? When does it work? When does it not work?
Speaker 1:Who should be doing it?
Speaker 8:Well, I think all cargo culting is bad, so I think that that would be you know, it's, I I think the four deployed engineering methodology is, is exceptionally valuable. Akshay's description of it is the best one. Think it's, solving through back propagation. Yeah. It's it's very elegant metaphor.
Speaker 8:But if you just slap a veneer on it where it's like sales engineering done. It's my favorite thing is, like, ex Palantirians will be like, people are asking me, like, what is an echo? And I will describe an echo, 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.
Speaker 8:You've you've completely cargo cultured away.
Speaker 1:Oh, no. Well, thank you so much for stopping by. Is is
Speaker 8:Thanks having me, guys.
Speaker 1:Yeah. This is great. Have a have a great rest of your day, and we'll talk to you soon. Cheers. Bye.
Speaker 1:Fantastic. So many great stories. Wow. And man, like encyclopedic knowledge of American history. There's so
Speaker 2:many Yeah. We need to have him on
Speaker 5:for minute.
Speaker 1:Yeah. Of course, Lockheed and Martin, like, the I I know their first names. Like, I don't
Speaker 2:Yeah.
Speaker 1:Yeah. First names. I need to brush up on their stuff. I need to do some, like, space repetitions and flashcards or something. Yeah.
Speaker 1:But next up, we have the founder of Starship coming into the building. Welcome to the show. How are you doing?
Speaker 2:Boom. What's going on?
Speaker 5:Hello. Good to meet you all. I am doing fine. I'm doing super exciting thing, and I like it.
Speaker 1:Yes. Thank you. Would you mind, kicking us off with just a a little bit of background on the company and explain not just what Starship is, but kind of, the the the footprint, the rollout, the strategy, all of that.
Speaker 5:Yeah. Yeah. Yeah. Alright. Yeah.
Speaker 5:Sure. So what we are doing, we are, we are a company deliver developing and building and operating delivery robots.
Speaker 1:Yes.
Speaker 5: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? So in science fiction movies, you know, you don't see UPS guys knocking on your door. Mhmm. You see things coming to you, things flying to you.
Speaker 5:That's the future that we are building. That's the present that we are building. And, you know, we have many competitors as well who have who we have inspired to do similar things, you know, with drone deliveries and so forth. Beardwing is on the ground. There's robots that drive on the ground.
Speaker 1:Yep.
Speaker 5:Small robots that drive on the on the ground. And we are we are actually not like a 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. We are actually in full commercial operation with thousands of robots in hundreds of locations. 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, you know, our robotic delivery is completely commonplace.
Speaker 5:It's something that people are completely accustomed to. It's something that, you know, people don't really use, you know, like human couriers to to to deliver things. They use robots.
Speaker 1:Yeah.
Speaker 2:Can can you talk about all the different things that you've seen around the way humans treat robots? I try to I try I try to say thank you to robots Yes. You know, when when they help me out with different things. But some humans, you know, we saw this
Speaker 1:You know, we've a lot of vandalism of Yeah.
Speaker 2:Saw this, you know, birds. The big thing with bird Vandalism
Speaker 1:of Waymo's.
Speaker 2:In LA is I think a lot of birds issues locally here just came from a culture of vandalism. You did the hard thing in making sort of cute robots, which I I think probably helps. But It's important. How is how do humans kind of present a challenge to trying to, like, automate delivery, which should be in everyone's best interest?
Speaker 5:We get that question a lot, but we don't actually get a lot of vandalism itself. You know, the the the the truth actually is that people really love our robots. 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.
Speaker 5:Like, for example, you know you know, we often, you know, get the question that, oh, you know, are your robots stolen? And actually, none of your robe our robots have ever been stolen from the street. And we have done 8,000,000 deliveries. Like, we are doing millions of deliveries, and it's just not happening. You know, kids feed our robots bananas.
Speaker 5:So the the the the treatment is completely different than with, you know, like scooters, for example. Yeah. I understand. You know, that's, you know, that's actually a lot we get that that question actually a lot. Like Yeah.
Speaker 5:People, you know, sitting in you know, sitting at the table very often say that, you know, I treat things nicely, but there are some other humans out there that do not treat things nicely, just like you said. Right? You know? Yeah. But it's not actually happening.
Speaker 5:It's not actually happening. You know? Like, how often do you vandalize, a, you know, UPS vehicle? You don't really. Yeah.
Speaker 5:You know? Sure. Sure. You can do it. Yeah.
Speaker 5:You can puncture puncture the tires of a UPS vehicle. You don't really do it. Right?
Speaker 1:Yeah.
Speaker 5:You know? And, you know, our robot actually our robot has 10 cameras. It's constantly connected to the Internet. It's really Yeah. Yeah.
Speaker 5:Yeah. It has a really loud siren when it's tampered with and
Speaker 2:so forth.
Speaker 5:It's not actually really happening.
Speaker 2:Well Yeah. Can you can you talk a little bit about the rollout maybe? Because I I think that the locations in which the robots are doing deliveries is, like, really gonna impact. Right? If you're rolling through a suburb and it's a, you know, family friendly neighborhood, something like that, the robot is gonna run into different challenges than, you know, rolling down, you know, a a street in in Manhattan, for example.
Speaker 2:So how how have you guys approached your kind of, like, go to market and kind of picking what regions are are are, you know, sort of top of the list in terms of getting robots on the ground?
Speaker 5:Yeah. Great question. We are operating our robots in at at 60 cities and 60 college campuses. Mhmm. So we have learned a lot about different environments.
Speaker 5:And, yeah, like, neighborhoods are completely different. Like, there's a lot of difference in the world. They'll be operating in six different countries, like five countries in Europe and, you know, US. Right? And, you know, US, of course, know, is varied as well.
Speaker 5:Right? 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 lot of these things. A lot of data for our machine learning algorithms and so forth. Right?
Speaker 5: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 completely true. And, you're operating a completely commercial quality service.
Speaker 5: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 retailers as well. And, it just works.
Speaker 1:Can you talk about the progression of the technology, specifically, the path to end to end? There's a single AI model, but there's probably teleoperation in the early days. Then there's, some mixed. There's some c plus plus for pathfinding, but there's some AI for, you know, image processing and world modeling. How have you thought about developing the technology, and do you see teleoperation and end to end AI systems playing nicely together in kind of a centaur mode for a long period?
Speaker 5:Or Yeah.
Speaker 1:Is this are these specific, like, gates that you have to go through?
Speaker 5:Yeah. We are operating at quite the hybrid model.
Speaker 1:Sure.
Speaker 5:We have been in we been working on this for ten years. Yeah. Right? And, you know, we built this at the at the time where, you know, AI was not actually as developed, and we have obviously reaped the benefits of the all of the AI development that has happened has happened since. But we also recognize that safety, for example, is super important.
Speaker 5:Yeah. Super important. You know? Like, for example, our robots, you know, cross roads. They they are generally a sidewalk robots.
Speaker 5:Mhmm. 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. They cross roads similarly as a pedestrian does, you know, with using crosswalks. Right?
Speaker 5:Our robots cross roads a hundred thousand times a day.
Speaker 3:A
Speaker 5:hundred thousand times a day. Right? There's thousands of robot robot robots operating. Right? You know, we have have been speaking right now for eight minutes.
Speaker 5:During these eight minutes, our robots are probably across the road here about a thousand times.
Speaker 1:Wow.
Speaker 5:Probably probably it's like that. There was a thousand times during these eight minutes that we have we have we have we have we have talked. Right? You know, safety is super important. Mhmm.
Speaker 5:Suppose we have something going wrong in, 1% of the crossing, that's too much. Mhmm. That's about 1% or 0.99% too much. Right?
Speaker 4:Mhmm.
Speaker 5:So we need safety. We need to prove that it's safe. We are actually not operating an end to end neural network, but we are operating a combination of, yes, c plus plus and neural network.
Speaker 2:When Sure. When when you see hard tech founders claiming online that they're operating an end to end neural network, which some people have done. Does that does that surprise you? Is it almost unbelievable? Or do you think
Speaker 5:It's not surprising to me at all that you can do it. The downside with that, it's very hard to prove that it is safe. Interesting. 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.
Speaker 5:Mhmm. I mean, not just, you know Yeah.
Speaker 1:And having a human loop is is actually beneficial there. Right? Like, if you have the ability to remotely take over, that's gonna make your safety case so much easier because you're gonna say, hey. Yeah. It is kinda crazy.
Speaker 1: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.
Speaker 5:Right? Exactly. 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.
Speaker 5:It's there there there is a human, you know, somewhere that can take over in difficult situations Yep. Or complex situation unusual situations.
Speaker 1:Yep.
Speaker 5:Then there is c plus plus and there is end to end neural network as well.
Speaker 1:Sure. Sure. So the nature of all
Speaker 5:of these?
Speaker 1:Yeah. Has the transformer architecture or any of the other, like, kind of foundational innovations in AI been important to Starship and what you're building? Obviously, we see hype around the Studio Ghibli 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.
Speaker 1:How has how should we be tying all the amazing progress in LLMs and AI to your business?
Speaker 5:Yeah. It is definitely helping and improving our staff.
Speaker 1:Mhmm.
Speaker 5:I think we were in commercial quality operation, already before that.
Speaker 4:Mhmm.
Speaker 5:But it is helping us tremendously for sure. Mhmm. Primarily, it is clearly something that is is dramatically reducing the need for this human somewhere in the loop.
Speaker 1:Sure.
Speaker 5:Absolutely.
Speaker 1:What about, have you thought about giving you know, embedding some sort of LLM or voice voice model into the robot? 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. I'm delivering a burrito. Like, it can answer some basic questions.
Speaker 1:That seems
Speaker 2:like the burrito guy.
Speaker 1:I'm just the burrito guy. That seems like maybe silly, but also, like, maybe great from a user perspective, but also, like, wildly extra. I don't know. Have you thought about that?
Speaker 5:Yeah. Yeah. Yeah. So we do not have, like, a personified LLM in the robot right now, But I think it is conceivable that that that will be the case. Sure.
Speaker 5:Our robot does speak. Yeah. But but the speaking is not actually driven by an by an LLM.
Speaker 1:But we have more like business logic decision tree.
Speaker 5:Exactly. It's a little bit more business logic that, yes, you know, every time the robot, you know, does delivery delivery, it says thank you.
Speaker 1:Yeah.
Speaker 5:Right? Doesn't take an LLM to do that.
Speaker 1:Yeah. Well, can you tell me more about trade offs in robot production? Elon has been, like, anti LIDAR from a cost perspective. I'm sure there's a bunch of different trade offs in terms of size, weight, speed, battery life, all these different things. You have probably, like, a base hub where these things go to charge, and then they have a certain amount of range.
Speaker 1:What are you optimizing for? What are some of the pitfalls to avoid?
Speaker 5:Yeah. Great great question. So our robots actually do not have a LiDAR. Mhmm. But that does not mean that we are anti LiDAR.
Speaker 5:Mhmm. The thing is, though, that the reason we have not used LiDARs is that LiDARs is effectively LiDARs are perfect sensor for for an autonomous vehicle.
Speaker 4:Mhmm.
Speaker 5: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 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 LiDARs are actually not perfect sensor for us.
Speaker 5:And the downside with LiDARs is that LiDARs typically have a narrow vertical field of view. Mhmm. They have like this narrow, you know, you know, rays effectively that see very far, but it's a very narrow the the angle, the vertical field of view is very narrow, like a couple of degrees or so. Right? Mhmm.
Speaker 5:We actually need to have perfect vision from immediate vicinity of the robot, like very wide wide, you know, vertical field of view. We need to see, you know, down in front of row the robot and also, you know, up and, you know, we we need to have have have that sort of sort of vision. So LiDARs are not perfect sender for us. That's the reason we are not using LiDARs. But the moment that that a LiDAR with suitable spec appears on the market, we will absolutely use it.
Speaker 5:So we are not, like, religiously anti anti LiDAR at all.
Speaker 1:Jordy, have a question?
Speaker 2:Changing gears a little bit. Skype is shutting down on May 5, end end of an era. You were the the founding engineer there. Is that emotional for you, the the shutdown? Or at this point, you've been, you know, in doing something, you know, else for for
Speaker 5:Yeah. Yeah. Yeah. I've I've been doing doing something else for for a long time. I'm not actually an active user of Skype anymore.
Speaker 5:Sure. Or actually quite quite some time. I still have the app, you know, in my phone somewhere, but, you know, not really using it all that much any anymore. I mean, Skype was an amazing 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.
Speaker 5:Right? From outside perspective, all startups seem like that, but they come out of nowhere and then it's just boom, you know. It's like that. Yeah. Yeah.
Speaker 5:But, you know, but in reality, as a startup founder, most startups are not like that. Most startups hard work hard work before things actually start, you know, getting off the ground. Right? Skype was not like that. You know?
Speaker 5:It was like for me, it was easy work, actually. 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, you know, frankly, I mean, it was a journey that happened twenty years ago.
Speaker 1:Yeah.
Speaker 5:Twenty years ago. Literally twenty years ago.
Speaker 1:What what what are the key lessons that you've take that you took from the Skype story and applied to building this business? Is it just the engineering culture, the pace of play, or is it wildly different because it's a completely different growth curve?
Speaker 5:It's both of these things, but it's also, I would say one fundamental thing is that with with a lot of products and a lot of services, you kind of you know, it's a very simple service, really. Like, you know, one one delivery delivery app, a major delivery app founder, you know, told me that, you know, look, Adi, 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 Mhmm. For me, then I will use our service any day. And, you know, that's how it is for them. That's how it is it is for us.
Speaker 5: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. That's how it works, and that's the traction we are we are seeing on the market.
Speaker 5:And Skype was like that as well. You know? If you actually actually put out the product that exactly fits what people want, and it just works. It just works. It doesn't have some sort of major downside.
Speaker 5:Right? You know? Then it just takes off like wildfire. Granted, it's harder to do with the self driving robot. Right?
Speaker 5:Yeah. Clearly, harder to do. You know? Like, we built we built Skype. You know?
Speaker 5:Like, we we were like a team of, like, how many engineers were there? Like, you know, 15 maybe. 15 engineers, nine months of work. And we have a beat has a beat out there that everyone loved and just took off like wildfire. Right?
Speaker 5:Yeah. Sure. You can't do, like, a self driving robot with, like, a team of 15 engineers and nine months. Right? And it take it does take longer longer.
Speaker 5:Right? Yeah. But it's also harder for competitors. Right? You know?
Speaker 5:So we are you know, I said, know, we have done, you know, 8,000,000 deliveries. I'm not sure, you know, our closest competitor there are lots of competitors, tens of competitors. Our our closest competitor probably has done 200,000 maybe or 300,000. Not sure. Something like that.
Speaker 5:Right? Like an order of magnitude difference. So we started this trend, let's say, you know, ten years ago, and we're still number one. Because whatever is hard for us, it's also hard for our competitors.
Speaker 1:I have one last question, then we'll let you get out of here. Why is Estonia so successful in producing technology entrepreneurs?
Speaker 5:Great question. I think I don't have a full answer, so I don't know. But the but but but one thing the thing out there is that, you know, Australia was occupied by Soviet Union for for for, like, fifty years or so. Right? And and I was you know, my age is such that I just turned 19 when we regained independence from the occupation.
Speaker 5:Right?
Speaker 3:Mhmm.
Speaker 5:So I I spent my childhood in Soviet Union, but my adult life has been, like, in in a in a free country. Mhmm. Right? And, you know, turning 19 and finding yourself in a free country that actually doesn't have a lot of establishment
Speaker 1:Mhmm.
Speaker 5:Built in, that means that you kind of grow up with an assumption that there are no obstacles. So no obstacles for you. There are no big companies out there that you need to kind of compete with. You're just free to do whatever you want. Right?
Speaker 5:So that's the that's the culture. I think, you know, overall, you know, successful startups can be built by any end. Mhmm. But it helps that if you don't know what's impossible. You know?
Speaker 1:That's amazing.
Speaker 5:If you don't know that it's impossible, you're you're you're you're going to have
Speaker 1:a better success than you just think. I agree. That's great. That's amazing. That yeah.
Speaker 1:That that's amazing. Thank you so much for joining the Congratulations
Speaker 2:on your first eight million deliveries and looking forward to the 800,000,000.
Speaker 1:Yeah.
Speaker 2:We'll have to have you back on then. Next year. Yeah.
Speaker 1:Next year. Let's hear it. Amazing. Awesome. Thank you so much for joining.
Speaker 1:We'll talk to you soon. Cheers. Bye.
Speaker 2:Before we bring in
Speaker 1:Yeah. Well, I will bring him in and I will let him give his introduction. Daniel, if you're in the studio, welcome to the show. Good to see you. It's been, a few days since we hung out.
Speaker 1:Still looking great. How are you doing? What's the latest?
Speaker 3:Doing fantastic. How are you?
Speaker 1:Doing well. Well well, Jordy's way, would you mind kicking it off with just a little bit of intro on yourself and, and what you're working on?
Speaker 3:Totally. Well, Juan, blessed to be in the capital of capital. Couldn't imagine a better place to be today.
Speaker 1:Yes.
Speaker 3:I've been building various, consumer tech stuff for, you know, better part of the last decade. Mhmm. Kind of most recently, attendees with the company I started, many years ago, sold that. I think there was a quote from Shawshank Redemption of you better get building or you better get busy dying. Something like that, if I remember correctly.
Speaker 3:But reconnected with the folks at Coco a year ago, Zach and Brad and the whole amazing team there. And, you know, sitting there and and, you know, realizing, like, yeah, I grew up in LA. Kept seeing all these robots going all over the place in all these different cities and just figured how to get involved. So, you know, we're we're Coco. We're bringing, you know, Sidewalk delivery robots to all the biggest cities and markets across the world.
Speaker 3:We've had a lot of exciting success there. And, yeah, it's a work here.
Speaker 1:Can you compare and contrast your approach to Starship? We just talked to the founder of Starship. But every time there's there's, like, this race for a new technology, you it it looks similar on the surface, and then you dig in and you usually realize that the companies are taking very different approaches. How would you explain what Coco's doing differently?
Speaker 3:Yeah. So I I think, you know, first off, you know, huge respect to the Starship team. Yeah. I I actually think I ran into them at an investor's office, like, ten years ago. Wow.
Speaker 3:I ran around when they're
Speaker 1:when they're
Speaker 3:starting the company.
Speaker 5:That's nice.
Speaker 3:I I think the biggest differences, right, are are kind of where we operate. Right? I think it starts with tremendous success on college campuses and kind of, you know, various other parts of of other markets, you know, solving the complexity problem. Right?
Speaker 2:Like, the
Speaker 1:if you look
Speaker 3:at the delivery market, right, you've had kind of even if you think back five, ten years ago, right, delivery costs for an order of magnitude lower both on the back end and kind of what consumers are paying. You have a fundamentally inflationary cost structure. But all that problem of of most of the delivery volume is in the kind of big urban cities.
Speaker 1:Mhmm.
Speaker 3:And so I think we've really just drilled on our execution of handling the kind of complex situations there. There's a bunch of different regulatory hurdles Dealing with even distribution. Right? We're we're kind of the only company that's partnered with Uber, DoorDash, and a bunch of other partners that we're kinda announcing soon. Being able to have that kind of broad based reach, you know, I I think it's super important because you can actually get the volume.
Speaker 3:Customers can use you in those cities. You don't have to go through a first party app necessarily. So those are think it be the biggest kind of on the surface differences.
Speaker 1:What what do you take away from the Waymo strategy? They were out in was it Phoenix, Arizona? Or, is they were out in Arizona for a while, I believe, in, like, the easiest mode for self driving, like huge streets, no weather. And then their second market was, like, the hardest place to drive in the world, San Francisco. There's hills.
Speaker 1:There's random people on the street. There's bikes. And, I think, like, the telling that some people would get would be like, if you can solve San Francisco, you can solve kind of anything. Maybe not Boston in the winter, but, is that the story you tell, or is there something else? And and and what are you pulling from their strategy overall seeing what Waymo's done?
Speaker 3:Yeah. I I mean, just on the commentary of kinda hard to see this drive, I would love to see Waymo's in Riyadh, Saudi Arabia. Like Yeah. There is it is bananas to take car rides there. Yeah.
Speaker 3:But what what I think is interesting is we've always compared it to kind of Waymo and the Tesla strategy. Right? The the Waymo because I think, yes, they operate in San Francisco, which is, you know, lived there for many years. It's not nontrivial to drive in. But the cost structure of, you know, how much does that vehicle cost.
Speaker 3:Right? And amortizing that CapEx against all the vehicles. Right? If you have this really expensive Spencer suite
Speaker 4:Mhmm.
Speaker 3:You're really, like, cost optimized vehicle, and it's hard to when you're kind of reliant on a lot of these sensors and kind of advanced computing. It makes it difficult to really get it to be substantially cheaper over time Mhmm. And to deploy a bunch of you wanna deploy a bunch of these. Right? Like, the the the question I've always asked is why doesn't we wanna deploy you know, you have Google's budget.
Speaker 3:Right? Why wouldn't you deploy, you know, a thousand of these, tens of thousands of these? Right? We've always viewed it more in the Tesla approach, right, of, like, if you can make kind of camera based autonomy and kind of driving work, you can have substantially simpler cost structure. Right?
Speaker 3:You're able to and with that simpler cost structure, you can deploy far more vehicles in far more places. And if you've seen the latest kind of Tesla self driving you know, full self driving version, it's an incredible driver. Right? Yeah. 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 know, everyone on the team is incredibly ruthlessly cost optimized of Yeah.
Speaker 3:How do we get this additional, you know, 3¢ a mile, etcetera. Right? Yeah. That's kind of the the things.
Speaker 1:Yeah. Yeah. So what does that mean practically? Is that just, hey, we're staying away from LiDAR because LiDAR is expensive? Or is it like we got to build a Gigafactory and just drive down the cost of mass manufacturing these?
Speaker 1:Like, Tesla is kind of the story of they did both. But what other decisions have you made to drive that cost per mile down as low as possible?
Speaker 3:I think it's both, and there's a really interesting thing. Right? Everyone thinks of the comparable of, well, it costs, you know, a a human x dollars to do this, and and with a robot, it's it's it's cheaper. Right? But that's only one half of the equation.
Speaker 3:Right? The delivery business is a logistics and it's it's all in that ninety eighth, ninety ninth percentile. Right? If every single time you mess up an order, right, human or or or or or robot or otherwise, that is incredibly expensive, right, to to to the merchant, which might have, you know, a food cost deducted to the delivery operator who kinda has to refund the order back to the consumer. So being able to be more reliable is kind of the other half of the cost structure.
Speaker 3:And I think what really impressed me kind of when getting involved was, you know, the the focus on reliability and kind of making that work. And that, you know, obviously involves, you know, the the robots for were kind of human operated entirely for a long time. And as you kind of roll out autonomy, right, you're able to do that piecemeal while kind of maintaining that high quality service bar. I think that's, like, the one thing, you know, we know from a lot of our partners is, like, really exceeding on kind of quality of service. So it's both cost, which we we we nail, but then also quality of service as well.
Speaker 2:Do you guys have any projections on when you think autonomous delivery will be the default? Right? There's, like, all these new systems coming in, Cocoa, Zipline. We're gonna have lots of solutions whether you wanna order something from, you know, Walmart thirty minutes away with Zipline or you wanna get a burrito
Speaker 1:Have you seen have you seen Pipe Dream or
Speaker 2:Yeah. There's Pipe Dream. It's like we're gonna put
Speaker 1:it in ground. The pipes in the ground.
Speaker 2:That's fun. Lots of ways that we're gonna get stuff, which is what Americans love. Yep. 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 gonna be coming through some type of, like, autonomous platform.
Speaker 3:Mhmm. I mean, I think it looks really lopsided. Right? 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. Like, to a lot of people, they get predominantly robot.
Speaker 3:Right? Mhmm. If you look at other markets we're not in, you know, it's I think it's the same for self driving cars. Yeah. I mean, my answer is is is is fast as human possible.
Speaker 3:Like, I think that's metered in years, if not sooner. But I think it's really market specific. Right? Like, you know, if if you're in the big cities, I think I think, you know, hopefully for us, right, in the in the span of a year, maybe two. But, you know, I I I tend to be aggressive on that front, but I think it it really depends on on kind of which markets you're in as that kind of rolls out.
Speaker 3:But, yeah, I think I think this proliferation of all these solutions is incredible. Right? And I
Speaker 1:think Yeah.
Speaker 3:You know, for rural environments, I spend a lot of time on Wyoming. Zip line's gonna be amazing. Right? But especially in the urban environments where the real like, there's a huge push. Right?
Speaker 3:Of, like, there there's a real business problem for for a lot of delivery providers of, like, we need to solve this. I I think that that makes a lot of sense.
Speaker 1:Can you talk about anthropomorphic design? How do you make the robots friendly and seem like they're gonna be fighting alongside us when we're fighting the AGI terminators versus because I imagine if it goes poorly, I'm gonna want a Coco in the foxhole with me. It's acute I mean, acute even the name, like, you know, Starship, cool name, but very different than Coco. I think that's deliberate. What else are you thinking?
Speaker 1:Where does this go? We were talking about maybe, like, do you throw an LLM with a voice mode on it and you can just talk to it as it's driving past you? Maybe ask it the weather, ask it the time, or ask it for the news. Where where does this go long term?
Speaker 3:So I I I think a few things. One, right, I think actions matter a lot more than words. Right? What someone says to you versus how they behave towards you. And, like, you know, we have this idea of this cone of courtesy.
Speaker 3:Right? And and really being courteous to other, you know, sidewalk users, bicycle lane users, whatever the surface might be. Right? And I think what what's interesting is you've seen, right, like, I saw the the kind of previous interview. There really is, you know, basically almost no incidences of vandalism or kind of people interfering with the robots because there is this, like, almost adoration.
Speaker 3:The name is very purposeful. Right? And, yes, the second most popular dog name in The US, at least at the time. Right? And and Really?
Speaker 3:And I think kind of thinking through it of, like, how's something behaves towards you and ends up building the brand more than, like, what it talks to you. 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. I think there's a lot more stuff you're gonna be seeing soon in that vein. I I think we've 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.
Speaker 2:Can can you talk about your guys' partnership with OpenAI at all? I don't know how much you can speak to it, but that was a cool announcement.
Speaker 1:Yeah. What do you do with that?
Speaker 2:Yeah. What yeah. What's up with this this whole AI thing?
Speaker 3:I I heard it was cool. I heard there was this model that came out yesterday that people were doing some cool stuff with. If you have not tried o three, it's amazing. But, yeah, I mean, they they they're fantastic partners. I I can't speak to too much about what we're doing with them, but it's very exciting.
Speaker 3:And and, you know, we'd love to talk more about it at a later date.
Speaker 2:Yeah. It's it's a cool partnership because you're not immediately worried about them just building the same thing that you're doing. It's kind of like a bigger, you know, jump to to go and say, you know, OpenAI is gonna start building delivery robot networks than, you know, somebody building a a coding platform.
Speaker 3:Unfortunately, I got shot down at our our weekly business review. I thought, you know, we should get into the kind of Versus Code fork business, but then they got shot down, unfortunately.
Speaker 2:It's a good business.
Speaker 1:It's a great business, especially today. Yeah. It's fantastic.
Speaker 2:Jordan? What what else is on your mind broadly in in venture right now? What are you what are you seeing? I know you do quite a quite a lot of investing historically. Yeah.
Speaker 2:What's been exciting?
Speaker 3:I was at this conference this weekend, and and I I I wanna I wanna share probably the funniest bit, that I heard from that. Was talking to a guy who manages kind of tens of billions of dollars, and we're talking about SPVs. He just goes, never say that word again. It's a dirty word. Sounds bad.
Speaker 3:He's like, you should call it a co investment vehicle, and that's that's a great idea. And so I think we should try and promulgate co investment vehicles over SPVs.
Speaker 1:Okay.
Speaker 3:It's it's better. It's like the the scene from the social network. Yeah. I mean, the the lot of I I think what's going on behind the scenes in the industry is really exciting, especially on the kind of delivery side. There there's a couple announcements that I'll I'll be back very short to talk about.
Speaker 3:But Fantastic. Yeah.
Speaker 2:Very cool. When, what's the vibe in Jackson right now? Is ski season wrapping up or is, when when even is spring break? Is that
Speaker 3:Right now, it's it's we've got mud season, which is, you know, all the snow melts, and it turns a really delicious color of brown and muddy and gets all over everything. So I'm actually Oh,
Speaker 2:you're still out there. Right?
Speaker 3:Yeah. I'm in I'm in New York right now.
Speaker 2:Right. Yeah.
Speaker 5:You you will you will see
Speaker 3:the seasonal migration of all the all the Jackson people, but yeah, it's a fantastic place. There there's actually an article in the journal this morning about how tech bros are starting to dress up like, like cowboys.
Speaker 1:I hope I know they're gonna say suits. I was hoping for suits. This is terrible.
Speaker 5:All the
Speaker 1:work I put into this,
Speaker 2:getting nowhere.
Speaker 3:I I always thought about wearing a a denim, like a
Speaker 1:I mean, is like Chris Sokka's dream. Right? Everyone dresses like a cowboy. He's been doing that for twenty five years.
Speaker 3:So But I wonder if you have to find a new bit. Right? Once everyone starts doing it, like, does that Of course.
Speaker 1:Yeah. You always
Speaker 2:Bring suits Jackson. Alright?
Speaker 1:Yeah. Yeah.
Speaker 3:Do it. I should I would love for you guys to come visit and wear suits, and we can we can record the looks that everyone gets.
Speaker 2:Yeah. Yeah. People don't ski in suits enough.
Speaker 1:Right?
Speaker 2:It's like skiing's a serious endeavor. You should dress
Speaker 1:done in suits. Yeah. Exactly. Really.
Speaker 3:With Zenia to make, like, a ski suit, and it's, like, with a like a gore There
Speaker 6:we go.
Speaker 3:Ski suits.
Speaker 1:There we go.
Speaker 3:Made to measure.
Speaker 1:That'd probably sell really well on Instagram. I think we got another business. Put together one of those co investment vehicles for us, okay?
Speaker 3:Yeah. Yeah.
Speaker 2:It's gonna need at least a hundred mil Yeah. Get that off the ground with the tariffs.
Speaker 1:Yeah, exactly.
Speaker 2:Actually, that's an interesting question. Speaking broadly, how how do you see how have you seen the robotics industry kind of responding? Yeah. I mean, I'm sure a
Speaker 1:lot of stuff in America, but Yeah. Supply chain. Right?
Speaker 2:Yeah. But especially with especially with with instant delivery where where it's really an economic equation, which is like, is it reliable?
Speaker 5:Mhmm.
Speaker 2:And is it cheaper than human based delivery? How do you think the industry is, like, responding? Still a shell shock? Or
Speaker 3:Yeah. I mean, I can speak only, you know, internally, and I can kinda give you some of the things I've heard across the street.
Speaker 1:But Sure.
Speaker 3:You know, internally, we have thousands of vehicles already kind of, like, in The US built, and and we're kind of actively deploying more and more of those. So, you know, from from our 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 of broadly to the supply chain, right, you have, you know, a lot of the consumer supply chain is is, like, primarily in Asia with not a whole ton of, like, alternatives. Yeah.
Speaker 3:And so I think it'll be really interesting to see, like, as the administration kind of rolls out the kind of other branches of this policy, do you start to see some carrots to kind of move that over? You know, a big thing that I think is was discussed this weekend that was interesting was, you know, what happens if you just drop capital gains on kind of investing in kind of these key sectors of the economy that we wanna bring manufacturing back to The US on? Yeah. I think, you know, don't have the US sovereign wealth fund to try and pick winners or anything getting to a little
Speaker 1:bit of Yeah. Yeah. Yeah.
Speaker 3:Coming there.
Speaker 7:But Is
Speaker 3:it great to hear Yeah.
Speaker 1:Yeah. Yeah. I was thinking about this for all all the venture capital firms that have been adventuring all over the Eastern Hemisphere. You give them a cap gains boost in American investing Oh. You're gonna see billions slowing to national interest
Speaker 2:rates. Eliminated capital gains for in some in some form.
Speaker 1:Yeah.
Speaker 2:But but that would be a cool Paul
Speaker 1:didn't say how. Yeah. They didn't say how.
Speaker 2:Awesome. Today. Well, thank you for coming on. Thanks for coming down the pipeline.
Speaker 1:Yeah. We'll talk to you soon.
Speaker 2:Great to see you.
Speaker 3:Bye. See you, guys.
Speaker 1:Cheers. Next up, we have Adam coming in from the Chamber of Pop Progress talking about the Google lawsuit that just happened and the ad tech verdict. I think we'll be able to have him pop in and give us, hopefully, some background. Adam, welcome to the show. How are doing?
Speaker 1:Oh.
Speaker 7:Good. Sorry. I had to unmute myself. Can you hear
Speaker 5:me okay? Yeah.
Speaker 1:Yeah. You're you're all good. I'd love to start, I mean, quick background on yourself would be great, but also just can you take us through, the very pre the the very early prehistory of this lawsuit will build up to your analysis that you dropped today?
Speaker 7:Sure. Sure. Well, thanks for having me, guys.
Speaker 2:Yeah. Good to meet
Speaker 5:you.
Speaker 7:Holding the podcast. So I, have been doing tech policy in DC for twenty years or so. Spent a dozen years at Google in their Washington office.
Speaker 6:Oh, wow.
Speaker 7:And about four years ago, started a group called Chamber of Progress, which is a center left tech industry policy, group. And so I worked on a lot of these issues. I have a lot of familiarity. This case is interesting. So this was the second case that the Department of Justice filed against Google, on antitrust issues.
Speaker 7:And the the the topic was kind of a niche one, which is really which is ad tech, the ad tech industry. And it really was alleging that Google had improperly linked the different parts of its ad tech business together in a way that had given it a monopolistic position. And, and the case moved relatively quickly. It moved from what's called the rocket docket, this court in Virginia that it goes generally pretty fast. And, What does what does
Speaker 2:fast actually look like? When when did it when did it kick off? And, obviously, they they
Speaker 7:got sick. So this one was so this one well, so this one was filed by the Biden administration. The other the other Google case, which had to do with Google search distribution deals, was actually filed by the Trump administration. Yep. So, this one, I think, took maybe a year from the time it was filed to the time it actually went to trial.
Speaker 7:Yeah. So that's, like, relatively speedy speedy. Yep. And, and they had you know, there's a whole parade of people from the ad tech industry who testified as witnesses in this case, as well as, like, advertisers and publishers and kinda people from that world. And and then it but the trial ended in, I think, in December, and then they just they just came out the verdict today.
Speaker 7:And there were some points for Google, but it was mostly a loss for them. The court found that they had improperly tied some of their ad tech products together, and they have monopoly position in what's called the ad ad exchange as well as the ad server, which is the tool that publishers use.
Speaker 2:Mhmm. Can you break down Yeah. Can can we kinda like go through a little bit more of your analysis? I'm I'm curious to get kind of really your, I'd like to honestly hear your personal opinion on on it. I don't I don't know how much you can how much you can comment specifically.
Speaker 2:Yeah. But do you think this was do you think this was the right outcome? I know there was 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. But what what's your read on it?
Speaker 7:Okay. So 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. There's this famous chart called a Loomiscape that shows all of the players in ad tech. And and so on the one hand, could say, okay. Well, there's lot of players.
Speaker 7: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 the customer who's most interested in their ad. What the publisher wants is basically the best return on their ad space.
Speaker 7:Right? And so the way that this industry evolved was was, you know, frankly, a little bit contorted, but Google 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. Right? Now other players in the ad tech industry complained. Basically, they said that Google made it too hard to interoperate with other with with different parts of its ad tech stack Mhmm.
Speaker 7:Like the ad exchange or the publisher ad server. Right? And that was the heart of the case. Right? That essentially that Google hadn't provided enough interoperability between these different parts of the ad tech stack.
Speaker 7:And so that was kind of the key question. Like, in antitrust law, there's this kind of doctrine of time. Right? Which which is basically do you force, you force people to take one product because they really want this other product. Right?
Speaker 7:And that's like the heart of the case. And the judge today, found that Google had improperly tied, its its ad tech products together, specifically the ad exchange, which is sort of the matching piece of the of the puzzle with the ad, server, which is the tool that publishers used. And so I think that, like, we don't know. There'll be a second phase of this trial, which will look at the remedies. Like, what happens now?
Speaker 7:What what has to change in Google's business? That'll happen later this year. But to me, the the other the 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, which is basically like serving ads on other people's websites. Uh-huh. This is the part of Google's business that's actually shrinking.
Speaker 7:So it was like 16% of their business like five years ago, and now it's down to like 11%. And you sort of say like, okay, why? Well, what's happened is that that business of placing ads across the internet has just declined because people Was it because
Speaker 2:of Google's product? They're doing AI summaries in some ways? It's like I don't even People are
Speaker 1:on YouTube and social networks. Right?
Speaker 2:And and one of the things is like there's so much less purchasing activity being driven by these ads because targeting is worse. Yeah. They're on a website usually to get information or to do something not to you're not just sort of stuff. Right?
Speaker 7:Yeah. You're you're you're nailing all the reasons. Right? Which is basically like this this this market that, you know, in any trust any of your any interest case, have to define what market you're talking about here. Right?
Speaker 7:And here, really, they were talking about, I think it was called, like, the open the open Internet advertising market. Right? But, like, that's shrinking. Right? Because people are spending more time on within ecosystems.
Speaker 7:Right? Within Google, within meta services, within Amazon. Right? Mhmm. And those are actually increasing their share of digital advertising.
Speaker 1:Mhmm.
Speaker 7:So, you know, one of the critiques I think of antitrust sometimes you hear from people is like it moves too slow or it's like fighting yesterday's battle.
Speaker 1:We saw that earlier with the FTC lawsuit and Meta about Instagram, an acquisition that happened a decade ago.
Speaker 7:Totally. I mean, it's probably very funny because, like, these things are all hap this is, like, high season for antitrust right now in DC where I live.
Speaker 1:Yeah. Totally.
Speaker 7:Because the the FTC trial is going on downtown.
Speaker 1:Yeah.
Speaker 7: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 to yeah.
Speaker 7:Go ahead.
Speaker 2:Yeah. With Google specifically, like, what's your how does this play out? What is the remedy? It it it Yeah. It matters to the businesses that feel and the judge says have been sort of wronged by Google's actions, 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, Instagram issue has.
Speaker 7:That's totally right. This has always been a very kind of in the weeds, more obscure case. Mhmm. And one of the things that is kinda interesting is that, like, there's no doubt, like, this is a loss for Google. It's probably a win for Google's competitors in ad tech.
Speaker 7:The the big question mark in my mind is, like, is it good or is it bad for advertisers and publishers? Right? Because I think on the one hand, like, advertisers and publishers say some of them say, like, we feel a little bit beholden to Google and we don't like that. Right? On the other hand, like and this came out of trial.
Speaker 7:Like, advertisers say, like, their performance by placing ads in Google is really good. Right? Google's putting their ads in front of people who need it. They're getting good clicks. Publishers are getting good revenue.
Speaker 7:And it could be that in breaking apart, like, this system that's working well for advertisers and publishers Mhmm. That they end up kind of regretting, you know, what this this whole thing. Right? So I'm interested to see whether that happens. But you're right.
Speaker 7:They're like the next phase is gonna be a Remedy's trial. Mhmm. And what happens? I mean, it kinda depends on how aggressively the government wants to pursue remedies against Google. Right?
Speaker 7:Because you can sort of see and and the judge said today, basically, like, you have to submit initial proposals to her within, like, the next week. So this is gonna come pretty fast. And so the, like, the the most aggressive is, like, Google's ad tech business is broken up. Right? So she says Google has to sell maybe its, ad exchange business or its ad server business, the pub part that works for publishers.
Speaker 7:That's would be the probably the most aggressive. The less
Speaker 2:aggressive And be clear for the audience that's that's not like AdSense that has nothing to do with No. That's not AdSense. Ad words. It doesn't have anything Yeah. To do with like, they might Is it possible that Google could say like, cool, we're, you know yeah.
Speaker 2:It it it it's not gonna, like, materially damage the business one way or another, so it's maybe a little carrot that they give, or is that even not not the right way to think about it?
Speaker 7:Well, in fact, there was some there was some reporting before this trial started that Google, had had supposedly tried to engage the justice department in settlement talks. Right? And so you could, like, could have imagined, like, okay, maybe they would have gone for something there. I don't know. I think we'll see what happens.
Speaker 7:But you're absolutely right. It's not it's not AdWords, not AdSense. This is this is their publisher site tool and the ad exchange, which most people do not know about. Most most even, you know, it's it's really like publishers and advertisers know this. The less aggressive remedy, think, would be something like, okay.
Speaker 7:You can continue to operate these services, but we're gonna mandate, like, maximum interoperability. Basically, like, every part of your ad tech stack has to interoperate with other services, basically. Mhmm. And so that would be, like, the less aggressive version. We'll see.
Speaker 7:We'll see which one prevails.
Speaker 1:Is is the, consumer harm standard just, like, completely out the window now? Did Lina Khan just, like, completely wipe that? Because I I understand that if I'm a if I'm a rival advertising platform, I'm upset about this. But if you're a consumer, there's maybe hard to prove harm. And even if you're an advertiser, you're probably like, hey.
Speaker 1:As long as the ad rates are good and I'm getting good ROI, I'm I'm happy. So how did this come together, and are we just completely past the consumer harm standard at this point?
Speaker 7:I fear that we're kind of beyond it. I think in what what in this case, the consumers were the advertisers and the publishers.
Speaker 6:So Mhmm.
Speaker 7:Like, was never really any serious allegation that, like, this had an this had an effect on the end consumer.
Speaker 2:Sure.
Speaker 7:The judge's decision, like, she she her argument her her ruling was that Google's link between these products
Speaker 1:Mhmm.
Speaker 7:Was, unfair to Google's advertiser and publisher customers. And so, like, I think in her way, was applying the consumer welfare standard. But whether that you know, this the Google's gonna appeal the case. Right? That that'll definitely happen.
Speaker 7:And and one of the big one of the big cases that's a challenge for the the court here is this case called Trinco, which is old old Supreme Court precedent, which basically has to do with what's called the duty to deal, which basically says, like, do you as a cusp do you as a business, even like a dominant business, have an obligation to help your rivals?
Speaker 4:Mhmm.
Speaker 7:And she in in her ruling today, she did what I would call a creative interpretation to kinda get around that. Mhmm. That is the biggest question about whether this ruling survives appeal and even up to the Supreme Court, because, you know, that that that the creativity, you call it, of her ruling may not survive appeal. We'll see.
Speaker 1:Yeah. 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? We saw this Lena Khan taking a shot at Amazon, like they're clearly dominant, but is there consumer harm debatable? Yeah. But it's still let's put the screws to them.
Speaker 1:And JD Vance kind of said the same thing with Google. He said, yeah. That's a big company. Maybe too big. Maybe we'll keep some of that pressure on them even though it doesn't necessarily fit the previous definition of, the monopoly test.
Speaker 1:Just market concentration is enough to merit a response from the government. And, like, how do you think the perception around that shifts? And do you have a particular take on on just, like, the idea of big companies that are dominant?
Speaker 7:Well, so it's interest very interesting. So, like, when I worked at Google, one of the things I really admired this because I don't think this is necessarily true today. Like, my boss said, look, we're a big company. Mhmm. We have a lot of power.
Speaker 7:We're very influential. Like, let's not try to, you know, fool anybody. Right?
Speaker 3:Yeah.
Speaker 7:And I agree with that. Like, big companies should absolutely be more scrutinized, be held to a higher standard. Like Yep. Absolutely. That's true.
Speaker 1:Yep.
Speaker 7:But what happened with with, these federal antitrust cases so now every big tech company has an antitrust case pending against it from the federal government, Apple, Google, Meta, Amazon. What happened was about six years ago, the FTC and the Justice Department, they share responsibility for antitrust, 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? Mhmm.
Speaker 7:And so they split up the companies based on, like, the, like, the target, not the subject matter.
Speaker 3:Mhmm.
Speaker 7:And I think, like, just human psychology, once you've done that, you're gonna bring a case. 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?
Speaker 1:Yep.
Speaker 7: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. So I don't think that was the most principled way of going about that. But but I think that that's what happened. 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?
Speaker 2:Yep.
Speaker 7:So it's really kind of strange, bizarre. 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. Like, the
Speaker 4:case has nothing to do with What's
Speaker 1:the But it is tit for tit.
Speaker 7:Well, I just think I just think, like, this wasn't the this wasn't the Trump crowd's case.
Speaker 1:Yeah. Yeah.
Speaker 8:Right? But they
Speaker 7:But I don't think the Trump crowd Trump crowd really cares about Google's Yeah.
Speaker 1:I mean, looking at other motivations, is there a world where, 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 $6,000,000,000 to settle that case, Is there a way that it's like No. More than 30,000,000,000. Oh, 30,000,000,000. 30 billion.
Speaker 1:30 billion. Yeah. Is there a world where it's like, hey, like we're just gonna give out some parking tickets to try and raise some revenue? Is that like a rational thought thought experiment?
Speaker 7:Yeah. To me, the fact they were willing to settle it for 30,000,000,000 kinda shows that they didn't really care about the case they brought in the first place. Right? Because it was like, oh, hey. We'll make it go in.
Speaker 7:It's just like putting a price tag on it.
Speaker 1:Right? Yeah.
Speaker 2:Yeah. Wait. Yeah. Let's let's pivot to the to the medic case because you're sharing about that yesterday. You had said that the $30,000,000,000 settlement offer is seven times the FTC's annual budget.
Speaker 2:Outlandish that the point would be humiliation, not restitution. How do you think the trial went yesterday for Zuckerberg? John was sharing that he looked absolutely fantastic in a suit.
Speaker 1:He looked great.
Speaker 2:It's unfortunate that anytime you see a tech CEO in a suit, they're they're
Speaker 1:in They're being punished.
Speaker 2:Yep. But what what's your read on the whole situation? And and I'm curious, did you think that did you think that the original $450,000,000 offer was was it was a good starting offer for Zuck and maybe they could have found some middle ground between $4.50 and and 300,000,000,000 because he was being kind of like run through the mud for even offering 450,000,000. But Yeah. He's a businessman.
Speaker 2:I imagine he expected them to counter and, like, kind of meet the middle or something like that. But, what's your take?
Speaker 7:Yeah. I mean, so you're absolutely right. Can't can't blame him for trying. Like, look, he like, if the worst case, they lose the case, they're forced to spin off Instagram and WhatsApp. Like, if you could avoid that outcome, you'd you know, every CEO would try to avoid that outcome, right, through a settlement.
Speaker 7:So don't begrudge him that.
Speaker 2:But if he was But 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 $10,000,000,000 because I really don't want that to happen.
Speaker 1:Yeah. That's a good point.
Speaker 7:I don't know. I mean, the the reality is like, think what they have to balance that against is like how confident are are they in their own case. And frankly, I think I think the FTC has a really tough case there.
Speaker 2:Yeah. Because That's I'm saying.
Speaker 7:Think like You
Speaker 9:said, like, this is a dozen years ago. Right? Mhmm.
Speaker 2:Yeah. No. No. I was saying specifically, 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.
Speaker 1:Yeah. Just for reference, Meta has 77,000,000,000 in cash and short
Speaker 2:term investments. And they're willing to spend Give
Speaker 1:give us half.
Speaker 2:Yeah. Yeah. They're they're they're willing to say, no. And they're willing to Yeah. Say, we're gonna spend $80,000,000,000 a year on CapEx.
Speaker 1:CapEx and the metaverse is gonna be
Speaker 2:a huge
Speaker 1:r and d expense. Yeah.
Speaker 2:I have to imagine.
Speaker 7:Well, the way Yeah. Like I just because it didn't get settled now, doesn't mean it won't get settled later.
Speaker 1:Yeah. It's true.
Speaker 6:Yeah.
Speaker 7:And, you know, sometimes that depends on how the trial goes.
Speaker 1:Yeah.
Speaker 7:Right? Makes sense. And so and frankly, like, if the FTC, like, at the end this trial feels like, they might lose, like, maybe they're maybe they'll they'd accept a lower number. Yeah. So you kinda never know where that's gonna how that's gonna play out.
Speaker 7:But, yeah, I think I think, like, the the the the challenge for the FTC like, they have two problems. One is they have to they have to say essentially that Facebook the meta doesn't compete with TikTok. Right? And x. Like, that's a problem for them.
Speaker 7:Yeah. But the other is that they have to prove monopolization, basically, that like that that if Meta hadn't acquired Instagram or what app, WhatsApp, they would have gone on to like challenge them and be great competitors. They were really these were really small companies at the time they were acquired. Right? Credit where it's due.
Speaker 7:I mean, Meta did a great job of integrating those companies, making them successful. Mhmm. And, you know, I I I'm sure you guys have seen plenty of failed acquisitions.
Speaker 1:Oh, yeah.
Speaker 7:Where it's just like, you know, it's like, it just doesn't work. Like, it's really hard to successfully integrate a company. And, like, legitimately, like, one plus one equals three, you know?
Speaker 2:Yeah. And one one one interesting data point. So when Instagram was acquired, they had 300,000,000 users. And Be Real, which was the last breakout consumer Yeah. App, mobile app, has 40,000,000 users.
Speaker 2:And I'm I'm gonna go out on a limb and say that it's probably not worth any anywhere close to a billion.
Speaker 1:Yeah. Right?
Speaker 2:Yeah. Even even for someone like Meta who has a consistent playbook of integrating
Speaker 5:Yep.
Speaker 2:That kind of business into the platform.
Speaker 7:Yep. Well, also like Meta knows like, they're in this business where like, you have the most fickle customers ever. Right? Like, no young person is on the Facebook app. Right?
Speaker 7:And then, like, very few really young people are on Instagram. Right? So, like, social social networking is a very, like, kind of, like, generational thing. Right?
Speaker 5:Mhmm.
Speaker 7:And so it's very hard to, like, maintain kind of the zeitgeist in in their business for, like, multi multiple generations. I think that's always, like, a structural challenge for them. So Yeah. On the Anyway, so I think I think FTC has has a uphill battle with that with that case.
Speaker 2:Mhmm. Do you
Speaker 9:think I agree.
Speaker 4:Do you
Speaker 2: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? 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 when it feels, you know, like we have this revolution in in many ways that has already started?
Speaker 7:Yeah, I think so. I mean, like, you know, I think a lot was very popular for politicians to say things like, we gotta beat China in AI. Well, who do you think is gonna do that? It's gonna be Google, Meta, OpenAI, right? It's gonna be those companies, right?
Speaker 1:Yeah. Arguably, a Meta without Instagram is a much weaker product. They can't invest in as much in CapEx. They can't invest as much as in Llama. Like, maybe Llama three doesn't get built because they're making half as much cash flow or something, you know?
Speaker 1:There's a bunch of interesting ways where the the you get a peace dividend from the the market concentration. 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. But then you also get these crazy dividends when they go and build cool stuff out there.
Speaker 1:Like, it's kind of an awesome system, even though it makes it hard to compete with them. But I don't know. What's your take?
Speaker 7:Well, just think I guess the way I come to it is like, I tend to think of like all of the big companies like intensely paranoid about each other.
Speaker 5:Sure.
Speaker 7:And, like, they're always getting into each other's spaces too. Yeah. Totally. And so, like, to me, like, that that part of competition is sometimes overlooked in the way I'm like, yeah, you're like
Speaker 1:Yeah. Yeah.
Speaker 7:Yeah. These guys are, like, at each other's throats.
Speaker 5:Yeah. Yeah.
Speaker 7:And that's good. Like, ultimately, because then their that competition is leading to them to add them to add features and, like, good for product innovation.
Speaker 1:Yeah. Yeah. I mean, every single big tech company overlaps with another one in one way or another, whether it's Amazon overlapping in ads now. You know, Bing has a search engine, Google has a phone. Like, everyone's in everyone's spaces constantly.
Speaker 1:Yeah. And it's inevitable.
Speaker 7:I think it's great. Yeah. I think it's wonderful, you know.
Speaker 1:Well, well, it's been great chatting with you. This was fantastic. We'll have to have you on on the next time that there's a big FTC case or or big Yeah. Just fantastic. DM
Speaker 2:us when you think there's a a story that, you're excited about talking about, and, you can be one of our Hill
Speaker 1:Correspondents. Correspondents.
Speaker 7:Yeah. Congressional correspondent. Alright.
Speaker 1:Yeah. Is fantastic. We'll talk you Great
Speaker 7:to meet you. Bye.
Speaker 1:We should close out by talking about another acquisition. OpenAI is in talks to buy Windsurf for $3,000,000,000. What do you think? Future Instagram
Speaker 2:OpenAI and Windsurf declined to comment.
Speaker 1:Future future Instagram situation? Or
Speaker 2:maybe not? Look.
Speaker 1:Are you long? Are you
Speaker 2:This situation takes me back to talking to Sarah Guo
Speaker 1:Mhmm.
Speaker 2:And she said, look at what the foundation model companies care about.
Speaker 3:Mhmm.
Speaker 2:And one of the things she talked about was coding. Yep. It was just she said, like, if you look at all their actions, everyone besides Grok seems to be very and just XAI broadly seems to be very oriented around code generation. And so I don't think this should be surprising. There was also some reporting that OpenAI had allegedly tried to buy Cursor
Speaker 1:Mhmm.
Speaker 2:On a couple different occasions. And then in that time, Windsurf just kind of took off, really grew revenue quickly. And yeah, if this deal gets done, I think it makes a lot of sense. There was people pushing back and saying, okay, how does a $300,000,000,000 company not know how to build an IDE?
Speaker 6:There was
Speaker 1:a good post about that.
Speaker 2:My take on it was like My take on it was like, you know, it's probably a timing thing. I'm sure that OpenAI could build a fantastic IDE Yeah. If they wanted to build it the ground up. They're also really rolling
Speaker 1:the organization so fast, and they're becoming a product company. People think about OpenAI as like, oh, it's this, like, ten year old company sometimes. But it's like, no, they're seeing insane growth. They want to hoover up talent and people that are good at designing products and just
Speaker 2:Yeah.
Speaker 1:Integrate more and more into the system we're building. And I also think
Speaker 2:there's there's something that very real is happening, which is the underlying models are starting to not perform as well Commoditized. In places like Cursor
Speaker 1:Yep.
Speaker 2:And Windsurf. And so, and it's possible that's an accident of the way the models are evolving, but it's possible that verticalizing is what makes sense.
Speaker 1:And I think that they've done a good job of, OpenAI has done a good job of filling that gap of like the empty text box that you start to prompt like Google search. Like, the the the first ChatGPT app was like a direct Google competitor in many ways. You've you've 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. And so you gotta be in the ID.
Speaker 1:You gotta be in the Google search box. You gotta be in a few other places, like where do in your camera role, essentially, is where you ultimately wanna be for image manipulation, image generation. Of course,
Speaker 2:a lot of that
Speaker 1:will happen in the ChatGPT app and in those chat workflows. But let's go to Dylan Patel, because he broke it down a little bit about why he thinks OpenAI is buying Windsurf. What's the strategy behind the revive of Codex? Cursor and Anthropic had a mutually beneficial relationship, but labs realized that controlling the main application of a model is as valuable as owning the model itself. With this acquisition, OpenAI gains greater ecosystem control and can build better products.
Speaker 1:Anthropics Claude Code was very well received. Keen on not missing out, OpenAI released Codec CLI, which is striking which is strikingly similar as a product. Both of these products have terminal level access and code editing capabilities. The competition goes beyond just products. OpenAI opened up free access to the plus tier for university students just one day after Anthropic announced their education initiative in early April.
Speaker 1:Fast follow-up. There so so, like, the the game is on. There are not there's not a single multibillion dollar AGI market. There are probably many pockets of value that will be discovered. And the interesting thing here is that I think it's a narrative violation.
Speaker 1:It was actually fine potentially to build a a wrapper. In many ways, these companies were derided early on when they launched as, oh, it's just wrapper. You're gonna get eaten. This is gonna get one shotted by the the the foundation models. Well, it seems like there at least is a way out via an acquisition.
Speaker 1:These companies are valuable. We've seen the ARRs grow. And then also, 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 blank box in ChatGPT, like just go and talk to the LLM, that's probably like the most dominant. That's the Google, right? But then Windsurf, Cursor, Devon, these are all super valuable category.
Speaker 1:But then there's probably a really long tail, and there's probably some value in the application layer deep down. So I think it's another maybe bold case for wrappers, depending on how you're structuring the business. Like you probably are not going to disrupt OpenAI with a wrapper. But you could build a very, very great business.
Speaker 2:Yeah. And for Windsurf, I mean, I'm sure they, in many ways, would have loved to just keep building and building and building and building compounding. But they also, I'm sure we're very aware of the competitive dynamics and this is one of those things, right? I I when you when you talk to we we talked to the the founder of captions earlier, right? Yep.
Speaker 2:Fantastic app that you're using all the time. Yep. How far away are we from you being able to upload a video to chat GPT and just say like add subtitles to It's possible. Yeah. You're already a pro subscriber.
Speaker 5:Yep. Right?
Speaker 2:And you're you're like, okay.
Speaker 1:Yep.
Speaker 2:I have this.
Speaker 1: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 It's like, well, I like their UI. I'm familiar with that.
Speaker 2:Like Yeah.
Speaker 1:This is the same thing with like, DaVinci Resolve is for in many cases. People don't switch because the buttons are in a certain place and the certain features that are nice.
Speaker 2:I would just say, like, people, you know, people were were 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 gonna see this back and forth battle where Sure. Oh, value is accumulating to the app layer. But OpenAI has an app. Like, models are everything apps.
Speaker 1:Right? Yeah.
Speaker 2:Can ask it to do something absurd. Yeah. That's good. Can ask it to now go, you know, do the Make me a you a flight. Yeah.
Speaker 2:Make me a video. Yeah. Write some code for me. Yep. They are a new form of everything app.
Speaker 2:Sure. Sure. Sure. And I think that big companies, even if you have a lot of traction today, you need to look at at how Yeah. How fast they're they're evolving.
Speaker 1:There's a funny post by Bern Hobart here. O three is a quality improvement, but at least on financial topics, it's definitely the frattiest model. Returns don't increase or rise. They get juiced, and retaliatory tariffs are described as China blasted hogs and soybeans. This is great.
Speaker 1: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.
Speaker 2:Blasted hogs and soybeans.
Speaker 1:I love it. I love it. Well, we gotta tell you about public.cominvesting for those who take it seriously. Multi asset investing, industry leading yields, trusted by millions. So get in on the action at 0 at, public.com.
Speaker 1:What else? I mean, Dan Chipper, he kind of had the most viral, review of o three. He says it's absolutely amazing. It's already his go to model, fast, agentic, extremely smart, and has great vibes. Some of his top use cases, these are things you can kinda steal from him and adapt into your own workflows.
Speaker 1:It flagged every single time I sidestep conflict in my meeting transcripts. It spun up bite sized ML course that pings me about about every morning. It found a stroller brand from one blurry photo. That's cool. It coded a new custom AI benchmarks in record time.
Speaker 1:It x rated an Annie Dillard classic and found writing tricks I'd never noticed before. It even analyzed every org chart to tell me what we'd be good at shipping and what our weaknesses are. So he's having a lot of fun with it. Anything else here? Age twenty Age 24.
Speaker 1:Yeah. They launched a music label. That's really exciting.
Speaker 2:And
Speaker 1:And they're going they're getting venture backed. Right? Yeah. Didn't they take some money?
Speaker 2:From Thrive.
Speaker 1:From Thrive.
Speaker 5:Very And
Speaker 2:then, gosh, I feel bad for blanking on his name. The guy who was at Adobe
Speaker 1:Oh, Led by Scott Belsky.
Speaker 2:Belsky. Yeah, he went over there. Belsky's over there.
Speaker 1:Incredible organization. Wonder if there's any I you're bearish on Hollywood. And the idea that you could build a new studio in a special way is is just fascinating to me and they've been able to do it really well. All the a 24 films have been fantastic.
Speaker 2:It's taste.
Speaker 1:It's taste and it's it's clearly such a interesting differentiation. And now they're getting
Speaker 2:to And I wonder
Speaker 1:I'm sure they'll be publishing a bunch.
Speaker 2:Who who knows? It'd be cool if Belsky was involved with this. I wonder if there's an AI Maybe. Angle Yeah. For music.
Speaker 2:It would be kind of silly to launch a new record label
Speaker 1:That does not embrace the AI
Speaker 2:So Yeah.
Speaker 1:Anyways Oh, deal CEO, gotta talk about this. We've we've done two episodes on the deal rippling drama. But Matt Levine says, has anyone booked a demo with deal recently just to see what lines their salespeople have been fed re the situation? It's a hilarious manifesting manifestation of natural versus corporate personhood that the entire exec team are wanted fugitives, but the rest of the company just keeps chugging. And that's like, yeah.
Speaker 1:Yeah. This is something that's probably missed. It's 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. Not much proved yet, but the I mean, the the signed affidavit was pretty crazy.
Speaker 2:Your spy turned on The spy turned on them.
Speaker 1:It's not looking good. But what does that actually mean for the company? The crazy thing is like, even after all the Zenefits drama and and Parker stepped down, Zenefits didn't do well, but it did cons it did continue as a company for a long time. People don't like ripping out their HRIS systems, like ever. It sucks.
Speaker 2:Yeah. I mean, I think the fact of the matter is I imagine Rippling has an extremely strong sense of who uses deal. Yep. Right?
Speaker 1:For sure.
Speaker 2:There's not because there's there's lot of companies in the world, but there's not a lot of like, you know, there are a lot of high value enterprise targets. Yep. But I doubt there's many at this point that Rippling hasn't had like some Yeah. Comms with that have confirmed like, okay, they're they're using deal. 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.
Speaker 2:You know, I know you're running on deal years. You know, we should, you know, consider having you guys switch over and and then just sharing like a headline that's it's kind of like it's fair it's it's it's not it's fair game.
Speaker 1:Yeah. It is crazy that they haven't responded even or at least that we've seen.
Speaker 2:Yeah. I I expected them I I expected them all to step down purely because it's in the probably in the long term best interest of the company.
Speaker 1:Yeah. I thought so too. It'd be interesting to see, like, what's the actual board structure because they've obviously raised a lot of money. They probably don't own more than 50% of the shares, but they might have super voting or something or board control. Who knows?
Speaker 1:But even
Speaker 2:then Still, if if
Speaker 1:Yeah. And just in your self interest of preserving the financial capital Yeah. You if if all the pressure's on you, get out. It's not like you're necessarily going to lose all the value there. You could very easily maintain some of that if the company survives.
Speaker 2:Yeah. Again, the other thing is the other thing is thinking about the example I think you gave early on, which was, you know, if somebody comes to you and they go, John, you're using Michelin tires. Did you know that Michelin was spying on Bridgestone? Are they gonna use those tires? It'd be
Speaker 1:like, that sounds like a hassle. And
Speaker 2:you're like, okay, like, you seem way too interested in the tire market. Exactly. I'm gonna keep, you know, driving my car. Exactly. Exactly.
Speaker 2:So it's very possible that, you know, who knows? Maybe it doesn't have as much of an impact. Yeah. I'm sure it's gonna have an impact from a recruiting standpoint, which will have an impact long term.
Speaker 5:Yeah. Right?
Speaker 1:Well, I wanna close out with two more posts. Congratulations to Raul from Julius. He announced collaboration. He was talking about this Figma for data analytics. He also put out a cool photo of him teaching data analysis at HBS.
Speaker 1:He's been fantastic Absolutely. Successful. Was great
Speaker 2:having
Speaker 1:him I love
Speaker 2:watching the videos he puts out. He always looks like he's about to smile. Yeah. And then he doesn't. Yeah.
Speaker 2:But I think he's just smiling inside because he's
Speaker 1:He's just happy.
Speaker 2:He knows he's cracked. It's great. He's building a great product.
Speaker 1:And so, I mean, makes so much sense. You build an IPython notebook or you do some sort of data analysis. 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.
Speaker 2:And this was interesting. John Conkel called out Oh, that we posted back on February 2020 Yes. February fourth of this year, 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?
Speaker 2:Only time will tell. And that was basically the top. So John actually commented back and said, time has told hypothetical performance of a tactical short selling strategy triggered by the very impressive Stargate presentation and the crystal ball drop. Very
Speaker 1:good. Well, we should close out with some news that'll be very important for all of our listeners. Gulfstream has announced the g 800 certification today. This
Speaker 2:is rocking the group chats.
Speaker 1:Yes. Everyone was talking about this. So 8,200 nautical miles at Mach 8.5, seven thousand nautical miles at Mach point nine. Max speed increased to Mach point nine three five, all in the same body as the g six fifty e r, but faster and longer range. I'm sure a lot of you folks who are listening are going to be upgrading.
Speaker 1:So call your Gulfstream rep today because these are going be flying off the shelves. Any other advice? Yeah, I
Speaker 2:mean, this you're going to want to get ahead of this. Yeah. This thing looks fantastic.
Speaker 1:It really does.
Speaker 2:By the time you get the jet and then outfit it Yep. You're, you know, it's going to
Speaker 1:be It's going be expensive.
Speaker 2:Little while, but it'll be worth the wait.
Speaker 1:Yeah. It's a lot of money, but it's a lot of jet. And again, you know, you you can sleep in a g 800, but you can't fly a house.
Speaker 2:That's right, John. So And it's gonna be a few more years until Astra Mechanica can get us a the Gulfstream equivalent of a
Speaker 1:Yeah. That's a good way to justify this. Like, you're just holding yourself over for the Astro Mechanica, the Boom, the Hermes, one of those guys. But in the meantime, pick up a couple of these, rotate them out every few years, and just use this to get around. Anyway, that's our show.
Speaker 1:Thanks so much for watching.
Speaker 2:Thank you, folks. Hey, this was a much more stable
Speaker 6:Yeah.
Speaker 1:Show. No cyber attacks
Speaker 2:No cyber attacks. This is Thank
Speaker 1:you to the brave soldiers Production team. Cybersecurity experts who kept us running.
Speaker 2:We'll see you tomorrow.
Speaker 1:See you tomorrow. Thank you.