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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 TBPN. Today is Wednesday, 04/23/2025. We are live from
Speaker 2:the Temple Of Technology,
Speaker 1:the Fortress Of Finance, the capital of capital. We're sharp. We're starting late. We are under attack, folks. Likely by a nation state, likely by a state actor.
Speaker 1:That's why we're six minutes late, seven minutes late. But we gotta
Speaker 2:get you They didn't want us to go live today.
Speaker 1:Didn't. They knew they knew the lineup was too unbelievable. Gonna pull it up on the screen for you folks today. We got a massive lineup. We got funding announcements.
Speaker 1:We got Sam Lesson coming on, yapping about VC stuff. We got Perplexity, big announcement. They're they're going head to head with Siri. They're launching an iOS voice assistant. Durin, physical intelligence, Northwood, we're gonna be covering it all.
Speaker 1:But first, we need to cover Kevin Systrom, the founder of Instagram, has changed
Speaker 2:his An absolute dog.
Speaker 1:Turns out, billion dollar acquisition, it's not enough. He went to court and said, you know what? Testified. Testified and Against his being mean, I guess. So Alex Heath kicks it off with a post here saying, Lord, give me the confidence to sell a company for a billion dollars.
Speaker 1:Basically disappear for seven years. Not true. He built another app. It didn't really go that well and they wind up selling it. But I used it for a while.
Speaker 1:I used it for a while too. News app. News app. Very cool. Wanted that to be like a modern incarnation of Google Reader.
Speaker 1:I thought it would be very cool if it was like AI assisted news reading. They had some summaries. It wasn't quite there. And I think they didn't find their, like, early adopter. It wasn't clear if it was for, like, tech techs tech people or, like, normies.
Speaker 1:And so it didn't really go anywhere, but it was pretty cool at the time. And so he basically disappeared for seven years and then reappeared in court to basically SHIT on my acquirer. And I went back and found a great Sam Par post from five years ago, basically, with some chat logs. You know we love some leaked emails on this show. This is amazing.
Speaker 1:The chat logs from when Zuck was buying Instagram. The highlights, Zuck, I can't get to $2,000,000,000. Systrom, 2 billion was my absolute say yes number. I'll have to think on it. Just two dudes negotiating the best $1,000,000,000 acquisition ever via Facebook Messenger.
Speaker 1:Yeah. The deals go down in the DMs. Doesn't As they do. Deals die in the data room and they flourish in DMs, I Sarah Fryer says, wow. After years of silence from Instagram co founder Kevin Systrom is on the stand in federal court confirming what I reported in my book, including that Zuckerberg starved Instagram's head count around safety issues leading to major problems.
Speaker 1:And so, Alex Kantrowitz posts, Kevin Systrom watching Zuckerberg saying Instagram would be nothing without him. Curious. No. I I I was onto something here. And so there's another funny post from Will
Speaker 2:Do you think Kevin Systrom and Mike Krueger envisioned this when they created Instagram?
Speaker 1:It's chatting with
Speaker 2:AI, chatting with Walter White.
Speaker 1:Yep.
Speaker 3:Or y n. I don't
Speaker 1:know who y n is, 8,000,000 messages. Wow. That's a lot. Anyway, also, Kevin Systrom, apparently, he's on the board of Walmart. Not bad.
Speaker 1:Pretty pretty awesome post exit founder mentality.
Speaker 2:Good place to
Speaker 1:land. Yeah. I grew up with a buddy whose dad was on the board of Walmart. And we'd go to Walmart and and he was just like, buy anything you want. It's customer it's research.
Speaker 1:I was like, that's Well,
Speaker 2:if you think about it for Walmart. The amount of purchasing activity that Instagram drives is obscene.
Speaker 1:That does make sense, actually. Yeah. And and that's why Ben Thompson was saying that Walmart should buy TikTok. Yep. Which seems weird, but it actually makes so much sense when you actually play it out.
Speaker 1:Right? And so this all comes from a report in the New York Times. A trial Instagram cofounder says Meta denied his company resources. Kevin Systrom said during testimony in a landmark antitrust trial that he believed Mark Zuckerberg, Meta's chief executives, viewed Instagram as a threat. Kevin Systrom, a co founder of Instagram, testified on Tuesday.
Speaker 1:He said, quote, Mark was not investigate not not investing in Instagram because he believed we were a we were a he Mark was not investing in Instagram because he believed we were a threat to their growth. They'd already done the acquisition?
Speaker 2:It was interesting. So so I think high level, Systrom is basically saying that Mark wanted to own Instagram and he knew it could be successful, but he didn't want it to be too successful because it would've it was basically, would've would've been damaging to Facebook's metrics.
Speaker 1:Yes. Systrom called it, a buy or bury strategy to illegally cement the social media monopoly by killing off its rivals. The Instagram cofounder made millions when Mark Zuckerberg bought his company, but Systrom sharply contradicted Meta's defense during hours on the stand. So, what I
Speaker 2:Millions is sort of an understatement.
Speaker 1:It was more like a hundred million, think. Couple hundred But but I'm confused about this because once it's a whole co acquisition. Like, he owns the whole thing.
Speaker 3:Yeah.
Speaker 1:Was Zuck optimizing for, like, short term earnings in the public markets? Because, yes, if you funnel everyone over to a lower monetizing product Yeah. This happened with Reels too when they started pulling people away from the feed, which was very pot which was very efficiently monetized. Yeah. They moved people over to Reels.
Speaker 1:Reels wasn't monetizing as well. They had to they had to keep giving guidance to the market and say, hey, Reels is going to get there. It's going to get there. Trust us. It's starting to monetize really The the ARPU is going to be there.
Speaker 1:The retention's there. It's gonna be additive to our business. It's not gonna be destructive. Because there's always a fear of that.
Speaker 2:So maybe it's very possible that Zuck at the same time was being, you know, wanted to be aggressive over the long term in terms of building out a new platform. But short term, you know, wanted to basically be able to control the process, basically. And I think that's a great take being like, hey, we don't wanna move Yeah. A bunch of users over to this app that we're monetizing well on Facebook and move them over somewhere where we just can't make nearly
Speaker 1:the same amount. It's just odd to to to sell your company to Facebook and then you have Facebook stock or cash or some mix of those two and not just immediate and and still have it be like your baby. Like Yeah. I feel like if you're if you sell your company to Facebook, you should be very much on like the Facebook team and you should say, hey, yeah, I have my thing, Instagram, that I want to grow, but really all I care about is the Facebook share price. And so, like, if if if what's best for the Facebook share price, because that's what I own now, is Yeah.
Speaker 1:Slower growth of Instagram, faster growth for Instagram for Facebook, you should be fine with that. So I don't really understand the the problem here. It does seem like he has a bone to pick. Lots of people do. I was listening to Palmer Luckey talk about the Facebook acquisition, and he said that the thing that got him over the line was that Mark told him that, yes, we're gonna acquire you for for, single digit billions, I think 3,000,000,000, something like that.
Speaker 1:But if you let us acquire you, we will invest $10,000,000,000 a year for a decade in VR and AR technology in Reality Labs. And and Palmer was running the numbers and was saying, well, I'd either have to raise a hundred billion dollars to make that happen or I'd need to sell, you know, millions and millions of headsets, like, every quarter to justify that type of R and D investment. And so in terms of, like, making VR a reality in the way Palmer wanted, this was a great option. And, of course, like, Zuck did do that. He did actually back that up.
Speaker 1:He did wind up investing in Reality Labs very heavily. Of course, there was all the political stuff and the fallout from that Yeah. That that left like a bad taste in Palmer's mouth, obviously, but then he built Andrew also, you know, worked
Speaker 2:interested to hear if Adam Messeri Yep. Ends up having to is is basically dragged into this Yep. Because he was head of product at Instagram. This was, you know, I think long after Kevin had left. But but ultimately, was the VP of product management at Facebook Yep.
Speaker 2:During the period in which they were kind of integrating the platforms and then eventually kind of moved over and and focused exclusively on Instagram.
Speaker 1:Yep. Another quote from Systrom here. As the founder of Facebook, he felt a lot of emotion around which one was better, meaning Instagram or Facebook. And I think there were real human emotional things going on there. That's funny because the the the the diss on Zoc during this oh, he has no emotions.
Speaker 1:He's a robot. And now it's like, he's too emotional. Yeah. I don't know. It's hard to pick how He's his favorites.
Speaker 1:It seemed like it all worked out. And it didn't it didn't feel as a consumer like Instagram, oh, they're not investing in this. Oh, they're trying to sunset this. It was like, no. They're trying to monetize this like crazy.
Speaker 1:They're putting more ads. They're adding video, stories, reels, everything. They went crazy with the with with that business and became very, very, very successful.
Speaker 2:Yeah. Mean,
Speaker 1:two words.
Speaker 2:Hands down, one of the best consumer tech acquisitions of all time. Yes. You think of anything bigger or better? It's not like WhatsApp. Like, WhatsApp was significant and
Speaker 1:was probably 19 times the cost.
Speaker 2:And doesn't generate nearly the Very important
Speaker 1:to the strategy. But I'm sure we will have more to talk about on big tech strategy, but we have the founder of Perplexity in the studio. So welcome to the show. How are you doing?
Speaker 3:Thank you. Thank you for having me here, John. Vince.
Speaker 2:What's going on?
Speaker 1:Great to have you. Can you tell us about the announcement today? What are you announcing? Who are you taking a shot at?
Speaker 3:Well, we are gonna be partnering with a OEM. I think Bloomberg's already written about it. Mhmm. The plastic will be preinstalled on the phones of that OEM, and we'll be able to, like, push notify all those users to set Proplexity as the default assistant on the Android phone. This is a pretty big deal because until now, like, people with OEMs would just not even take a meeting with you.
Speaker 3:Mhmm. If you ever go to them and say, hey. Like, what do you think about using an alternative assistant or an alternative search? Yep. Maybe, like, Google is just paying too much money.
Speaker 3:I'm not gonna do anything. So it took this long to actually build something pretty differentiated and new, which is obviously, you know, taking actions. We put out a Twitter announcement today morning too saying we got most of it working on iOS as well. Mhmm. So I feel like this is the next stage, like, you know, moving all these AI chatbots to native assistance on the phone that not just answer your questions, but also help help you get things done.
Speaker 1:Is there any hope that there will be a more open ecosystem on the iPhone? I've used I've used the shortcuts function on the action button. It's pretty janky. Yeah. I'd love to just remap Siri.
Speaker 1:I love Apple. I love my phone, but I don't love that particular product. I'd love to swap it out with one of the more founder led AI companies like yours. Is there any hope there or is Apple just too dominant in that? And do they view it as too valuable?
Speaker 3:I would I would assume the latter. I think my hope is at least, like, let's start with Siri being able to call multiple AI apps.
Speaker 1:Sure.
Speaker 3:You know, they let the user provide some preferences on what apps they like for what different things.
Speaker 1:Mhmm.
Speaker 3:At least we can start with that. And I think calling other apps could be interesting. Mhmm. Most of actually, to be fair to Apple, a lot of it is to expose in the Apple SDK through the events kit. Mhmm.
Speaker 3:So that's how we got things done, like calendar, mail, reminders. These are all part of their SDK. So you can actually call it podcast, Apple Music. That's Apple Maps. All of these are possible to integrate into.
Speaker 3:You cannot do stuff that's more native, like alarms and volume or brightness. You know, people want and everything system at the end of the day.
Speaker 1:Sure.
Speaker 3:So that's their advantage. So I hope, like, you know, what they can do is stuff that's so easy and obvious, like setting an alarm or making a phone call or sending a text message. They can just continue to be pretty reliable there.
Speaker 4:Mhmm.
Speaker 3:But anything that's more multi step in nature, they let the user invoke their favorite AIs to get things done.
Speaker 1:Mhmm. What what lessons have you learned from the antitrust history in big tech? And what are you watching today with the antitrust stories that are unfolding around Google and Meta on Capitol Hill recently?
Speaker 3:Yeah. So our our one of our executives, Dmitry, is testifying today for the Google versus DOJ case.
Speaker 4:Mhmm.
Speaker 3:I've already wrote on next our core points. Mhmm. I don't think Google should be broken up for Mhmm. Two main reasons. One is it's not even in the interest of America for Google to be broken up.
Speaker 3:Mhmm. And number two is it doesn't actually increase competition. It's just gonna, like, transfer from one monopoly to another. Yeah. And actually, they've done a pretty great job at helping other people build browsers.
Speaker 3:Like Edge I mean, if if you wanna use the word wrapper since I get accused of it a lot, Microsoft Edge is a Chromium wrapper. Yeah. Right?
Speaker 2:That's right.
Speaker 3:And Gray was a Chromium wrapper.
Speaker 2:No. That's a great take.
Speaker 3:Everything everything every other browser that's even managed to take even a tiny bit of market share from Google Chrome has been built on technology that Google did. So we should actually credit them for that. And I don't trust another organization to maintain that open source repository in the same way that they have. Yeah. And the other the the other thing, honestly, though, that we're pushing back on against Google is their how they couple OEMs to keep them as a default and don't let the OEMs put in Play Store otherwise.
Speaker 3:So, basically, it's very simple to understand. If if there is, like, an enthusiastic OEM who wants to ship AIs on their phones Yeah. What Google does is, okay, you can do whatever you want. It won't be an approved Android version of Google. And and if it's not, you're not allowed to put maps, YouTube, Play Store.
Speaker 3:The one that affects this the most is the Play Store because nobody can see the phone where you cannot install other apps.
Speaker 5:Yeah.
Speaker 3:And most developers of other companies are not interested in, like, maintaining versions of their apps from multiple play stores. It's a lot of work. Even Samsung couldn't really get Galaxy Store to work.
Speaker 1:Mhmm.
Speaker 3:And Meta, Amazon, all of them tried making their own phones and fail for this very reason. Even if you fork Android and try to make your own phone, you have to convince everybody to actually ship to that particular new Play Store and maintain it and keep improving it. And you're not gonna be able to share the Play Store ad revenue and subscription revenue with with the OEMs that Google can. So this is the primary problem. And but that said, like, you know, the assistant that they have, Gemini, is actually pretty horrible.
Speaker 3:And the model is great, but the product is not.
Speaker 5:Yep.
Speaker 3:And there should be no reason to force people to keep that as a default when you have an inferior product just because you have all these deals and lock ins. So that's what we are pushing back on in our testimony.
Speaker 1:Yeah. Just because you build a great foundation model does not give you a guarantee that you'll win at the application layer. And so these wrappers, although they've been derided, like, that that's the UI layer. That's what's so important to the actual consumer. I wanna talk about, social networking in the context of foundation models.
Speaker 1:We've seen the partnership between the merger between X and XAI. There's been rumors that OpenAI might be thinking about doing some sort of social network. Obviously, Zuck has been able to vend Lama into all of the Meta core products. What do you think the future does every does every AI company need a social media dance partner? Are we gonna see, Pinterest and Snap do things?
Speaker 1:I know some of them have have experimented with AI features, but haven't brokered a huge partnership yet. What does the future look like? Are these two technologies, like, intrinsically linked and destined to be part of one organization, or can an AI company operate independently forever?
Speaker 3:I mean, I I don't I don't know how social AI go hand in hand that it's not it's not that straightforward. Like like, if it was then Meta AI would have already taken off
Speaker 4:Sure.
Speaker 3:Pretty massively. Right? Even though it's not the leading model, you could imagine most of the like, say, let's assume ChatGPT, you know, get, like, a billion queries a day or something. I don't think, like, like, 60 to 70% of them are probably gonna be super simple enough that Meta AI is gonna work for it. Totally.
Speaker 3:You don't need the fancy models. In fact, most people using track speed in the world don't even know there's a model called o one or o three Yep. And and don't even know what the difference is for g p t four. So I would say the main problem is it's not AI is still very single player. Mhmm.
Speaker 3:The only experiment that I feel took off on social is this thing that we did first called ask perplexity bot on x.
Speaker 1:Yep. I remember that. And All the time in the comments. Yeah. It's great.
Speaker 3:X AI also, you know, implemented that with ad Grok and they have way more advantages because they own the platform, no rate limits and like, they can drive installs of their app through that. So it's it's like a pretty good experiment that worked. So I could imagine Meta doing this, like, know, on threads that could be like a at Meta AI and and or it could automatically reply. You could do all sorts of cool things.
Speaker 2:Yep.
Speaker 3:So it's more like the other way where a social network can help you grow usage of an AI app Mhmm. Pretty pretty immensely Mhmm. Compared to like an AI app benefiting from social layer, so far at least. But if you could figure out social for an AI app within the app itself, it can definitely make it more daily usage and high retention, which is what most AI apps struggle with today.
Speaker 2:Mhmm. Can you talk about how you're thinking about your own models going forward versus leveraging the existing models? You guys have Sonar and then Yeah. R seventeen seventy six. I'm curious how you're One of
Speaker 1:a little about that.
Speaker 2:Where where you're looking to focus going forward?
Speaker 3:I think we'll continue to keep the same strategy, is have a version of our product that can run with our own models, but not hinder or disrupt the user from this best experience that we can provide to them. If we are not able to do it with our own model, we'll just use other people's models. We have no problems with that. My our belief is that nobody's gonna have a lead in them having the best AI model for more than a few weeks. The the pace at which the field is moving.
Speaker 3:Like, Anthropic did the 3.7 Sonnet, and then within a few weeks, like, Google did Gemini 2.5 Pro, which was way better. Grok three came out, and then OpenAI has o three and o four. There's always some debate on, like, what is the best model, but they're all looking the same and they're all good for certain specific set of things.
Speaker 2:Yeah. Do think in do you think in five years can the average cons Internet, you know, user will have a favorite model or they just won't even know the underlying model that they're using and they'll just be sort of, you know, the the software application layer will just be serving, you know, the the the most effective model for the task?
Speaker 3:I think it's gonna be more like the second case. The main reason I believe that's gonna be like that because everybody's just chasing the same benchmarks. Everyone has the same set of benchmarks, Elemsys, Elemarena, GAIA, GPQA, and and humanity last exam. And and they're just trying to, like, show their AI is the best. And so they do all the same sort of things that you
Speaker 2:do in
Speaker 3:RHF, and it ends up be making models, like, look similar. Yes. There are some, like, tasteful things some model developers do, like, people like the way Claude responds. Some people like Rock's attire, but these are all, like, easy to build. It's not that hard.
Speaker 3:The difficulty, which is why everybody's working on the difficult problem is making these truly smart and, like, better all these reasoning tasks. And so that's gonna end up making all these models roughly similar looking to the average user.
Speaker 2:That makes sense. When do you and the team decide when something is ready to ship? With the the voice assistant today, One of the massive advantages that I think you guys have is the culture of Apple specifically is about perfection. Right? It's about pixel perfect design.
Speaker 2:You know, it's not it doesn't feel like the culture is sort of comfortable making mistakes. You can see the even iMessage summaries being very embarrassing to them. Right? Whereas, like, as a, you know, a big company now, but but still relatively young, you guys have the advantage of being able to, you know, move quickly, try things, and and iterate.
Speaker 3:Yeah. So I'll literally read out to you with the chat I had with with our engineer who worked on this. We good to launch and announce today, question mark. And then he's like, yes. Still making improvements, but let's launch.
Speaker 3:And me, like, do you wanna address some of the onboarding concerns people had, like, all the which calendar or which maps to use? And he's like, yeah. They're valid concerns, but I'm worried about waiting too long to launch. The Apple engineer in me says to wait until it's perfect. The perplexity engineer in me says that's why Apple has never launched anything.
Speaker 3:Amazing. That's great. And then I said, okay, let's roll.
Speaker 1:Do you have a sound effect for us, Jordy? Found mode. Anyway, I I you posted what what's a social app that doesn't exist yet, but you wish existed, doesn't need to get to a hundred million or a billion users? What did you learn from that? What was exciting, and what do you think, you might stay away from?
Speaker 3:Yeah. Yeah. The major learning was the o g Facebook
Speaker 1:Mhmm.
Speaker 3:And and Usenet. These were the two main ideas. Mark and Reason actually talked to me after that. He's this is like his pet, like like, you know, idea that he always keeps coming back to apparently. And Bloomberg terminal is another interesting thing where Yeah.
Speaker 3:You know, nobody thinks about it as a social network, but it is what it is today. People are not leaving it because of the network it has. Right? And it's very elite because you have to actually pay that much money to get into it. Mhmm.
Speaker 3:But then because of that, the quality of, like, exchanges are also high, or at least that it gives you this feeling of exclusivity, which is what Facebook leaned on to in the early days where they're only in Ivy League colleges and stuff. And so I I think that concept can be explored. Clubhouse definitely tried that and failed.
Speaker 1:Yeah.
Speaker 3:So it's not, like, you know, bulletproof. Mhmm. But that can certainly be explored again. If you wanna build an app that doesn't have, like, too many users, you need to gate it in some way.
Speaker 5:Mhmm.
Speaker 3:Whether it's by pay to play or, like, some other kind of elite miscreiterion, it's not clear. Yeah. But then what after you get in should also be thought about. Yeah. The quality of exchanges should be high.
Speaker 3:Like, in in some sense, Elon has turned x into some something like that. Mhmm. There are lot of pros, a lot of random accounts, and all that stuff. But be by forcing people to have the blue mark and paying $8 a month and and all that stuff, I think he's already made it, like, much better than it used to be. Mhmm.
Speaker 3:So a more aggressive version of that could be explored. He could explore it himself. Like, if there's a super premium version where you only get to, like, respond to some people if you're paying even more. Mhmm. How how would that make the quality of exchanges on the platform?
Speaker 3:It's not clear because the other side of the story where some people like Bill Ackman come and respond to random people on x. Yeah. And and the reason he gives us, like, I like the attention. I like I like and I'm I'm even on a vacation, I wanna come in, like, keep replying. I like the dopamine hits of, like, getting notifications.
Speaker 3:You know? So it's not like if you get billionaires, they wanna stay with the other billionaires or stay exclusive. I think they actually like using a product, like, x to stay connected to the normal people. Yeah. Okay.
Speaker 3:I I track the idea yet.
Speaker 1:I wanna pitch you an idea that we've been kicking around here. It might be terrible. But in terms of, like, the LLM research AI driven social network, I find myself doing a lot of very niche deep research reports sometimes. I did a whole, deep dive on, deep research report on Toma Bravo, and then I did another one on the the the story of Johnny Carson, the the the a new original host of The Tonight Show. Fascinating.
Speaker 1:I don't know how I wound up down that rabbit hole. I really enjoyed it. If I'm on perplexity and I find some and I ask some really interesting question, because asking interesting questions is often more more challenging than getting a great answer, what if I just could just, click a button and share publish it to an internal network and then Jordy can follow me on Perplexity that he can see my most interesting Not not gonna see the whole feed because maybe I'm asking about a health care issue. But if I choose to share it, I'm just sharing my result, and then they can click in, oh, John was interested in, you know, this specific thing. Maybe I'll take a tour down his research result.
Speaker 1:Is that an interesting option, or is there something I'm missing that's like, that's actually a terrible idea?
Speaker 3:No. It's not a terrible idea. We've exact we've considered this exact idea Awesome. And, you know, obviously, we have the more I keep working on features, I people ridicule me that what are you doing when your core product is failing and buggy and, like, going down, and, like, you're going down the drain and, like, you're taking the company down. So all I I read all the stuff too.
Speaker 1:Don't let the haters get to you. Don't let the haters get to you. It can
Speaker 3:more than ever.
Speaker 4:I think that
Speaker 3:some some of them have a valid point, though. Like, you Sure. More features you keep in using to the product Yeah. You just lose sight of the core focus. Why the product even exists in the first place and making it, like, a pretty bad experience.
Speaker 3:And then Yeah. You and you win on neither of these things. But I do agree with you. Like, it'd be great to share the the perplexity threads or, like, that that you create. We have this thing called Discover.
Speaker 3:Yeah. And and we're trying to increase the volume of content on Discover.
Speaker 4:Mhmm.
Speaker 3:And once we do that in an automatic way with curation to users' interest, like, we're gonna let some of the users pub try to, like, publish it to Discover on their own just like a creator on YouTube does it.
Speaker 1:Yep.
Speaker 3:And and then if a few people engage with the, like, the TikTok algorithm, we're gonna try to surface it to more people. That is the long term idea. That's why I'm even having the Discover product. People even ask me why why does this thing even exist? Yeah.
Speaker 3:Because I I wanna keep it as the optionality to, like, have a social product within perplexity.
Speaker 1:Yeah. That makes a ton of sense.
Speaker 2:If you have another minute, I'm curious how you're thinking about shopping. How much time you and the team are are putting into this. It's obviously a very exciting opportunity. Yeah. And I know you've shared some about what you guys are doing before.
Speaker 3:Yeah. So last year, towards the end of last year, launched Perplexity Pro shopping where you can and once once you do a shopping query, we're not just giving you the the answer, but giving you the product cards, and we could even let you buy it directly from there. Some of the things we surface from Shopify with their API and, like, let you buy with Shop Pay, and some of the things we ourselves integrated with some merchants and, like, did the checkout flow ourselves. And you wouldn't even have to go and check out on the merchant side. You can just do it directly on Perplexity.
Speaker 3:We thought this would be the best innovator dial my angle against Google because Google, even if Gemini gives you shopping answers, they have no incentive to like let you transact Because, like, the they lose they they make money by sending you merchant sites. That's why Google flights doesn't let you book flights on Google. You have to book it on Expedia or Booking.com. Hotels, same thing. So I think that's that's why we worked on travel and shopping where we let people try to book directly.
Speaker 3:We have some ideas on how to incentivize it, like free shipping or, like, x percent off on hotel bookings done on perplexity. And but but what we learned the hard way is people actually want really good results for us. That's why they're even coming here. They don't care if they transact here or not. It's it's a secondary thing.
Speaker 3:That is only if the result quality is so good. Are they interested in the last step? And we didn't quite get that right in the whatever we did November. So that's what we spend time on the first quarter is to just improve the UI, improve the latency, improve the relevance, make sure the cards are, like, up to date, high quality, filter all the low merchants, like, low quality merchants. Make sure, like, even images for every card is present.
Speaker 3:Like, this is all a lot of boring work that LLMs don't solve. Same thing with hotels, like, TripAdvisor data is great. We work with them, but, like, there are so many other places on the web where there are good reviews that people wanna know.
Speaker 1:Mhmm.
Speaker 3:And you gotta, like, aggregate all of that. And this is why I think, like, model companies are not guaranteed to win the application layer because you have to work on all these boring things. And then sometimes when people book a hotel on perplexity, like, when you actually go to the hotel, like, they say the booking never came through. So there's a lot of real world problems you hidden, like packages might not get delivered. You don't have a way to track the package because the merchant still does the shipping.
Speaker 3:We don't do that. So Mhmm. TikTok, if you noticed, TikTok has a shop tab, which literally looks like Amazon now, and I heard that they even have their own fulfillment in Seattle. Mhmm. They hired people from Amazon and, like, they're doing their own shipping.
Speaker 1:That's crazy.
Speaker 3:So that's my lesson from this is you wanna go to a vertical. Have to go all in and like nail, like like be prepared to like play the long game there.
Speaker 2:Mhmm. How do you think about manufacturing viral moments? You guys had a cool experiment with your Super Bowl activation. I'd love to get a postmortem on that. But then you're also not afraid to go, and you did this sort of Squid Games campaign that I saw getting a lot of attention as well.
Speaker 2:How do you how do you think going forward sort of balancing these more like scrappy kind of organic activations versus, you know, going big and and working with, you know, global celebrities to build the brand? Mhmm.
Speaker 3:I think we should keep being scrappy. The thing it's it's by the way, like, he's a pretty global star like, well known star. Like, people recognize his face pretty quickly, but he's also not, like, as expensive as Hollywood people. And so Yeah. That's why we decided to work with him.
Speaker 3:And the other other things, like, it's a concept that matters at the end. Right? Like, coming up with the right concept is more important than, like, who you work with. And we we we will still try to keep doing these one off viral moments. It's all it's take about taking bets, not all of them land.
Speaker 3:Yeah. The Super Bowl was good. Like, in fact, like, I I don't the retention from people who came to the Super Bowl exceeded my expectations. And again, like, whether it's better than doing Instagram ads, it's not clear to me yet. We are we we have to explore all these different platforms.
Speaker 3:But I do think there's, like, you know, two things you benefit from. Right? Like, we did this thing with Ben Shapiro over in his podcast. Like, he pulls up perplexity and ask questions. I think, like, that doesn't actually convert.
Speaker 3:Like, you cannot track performance. Mhmm. But it it it it does lead to more brand awareness. Like, if they're like, he has a lot of listeners and, like, it's a different way of doing ads on a podcast Yep. Where you're not actually, like, having him say Perplexity is awesome, go and install it.
Speaker 1:Yep.
Speaker 3:It's more like watching him use it and then you learn what the product is and how what it's meant to be used for. Kind of inspired by Joe Rogan's pull it up Jamie where all the time Google is being used there.
Speaker 1:Yep. Yeah. We do that with Polymarket. We pull up Polymarkets all the time and recommend that people go and download and install.
Speaker 3:Yeah. That that that's pretty awesome. Yeah.
Speaker 1:It works really well.
Speaker 2:I'm I'm curious. You mentioned earlier, you know, people sort of yapping on x, you know, trying to trying to sound in on on your product strategy. How do you how do you balance, like, you know, on x, it's like an echo chamber of people that are in Silicon Valley working on AI. But, like, perplexity in theory doesn't really care about people on like, you know, in San Francisco or or New York or the suburbs. Right?
Speaker 1:It's like The final market.
Speaker 2:You care a lot more about like, you know, some, you know, random person in in Arkansas is like Yeah.
Speaker 1:You know
Speaker 2:you know, wanting to wanting an answer about something and using the app. How do you how do you personally kind of like Yeah.
Speaker 1:Everyone in Silicon Valley could switch to DuckDuckGo and Google would be unaffected. That's like the lesson from the last era. And so you could do the same thing. But, yeah, I'm interested to hear your take.
Speaker 3:I think this is both my, like, weakness and strength. I I I spend a lot of time on this platform, so I understand it But then, like, we are living in a bubble, like, there there most people are only using ChatGPT and and they don't they haven't even heard about, like, most of the other apps. I think Elon has managed to break that a little bit because he has 200,000,000 followers. So essentially, he reaches a lot of people. But that's kinda why we wanna do more of these Instagram related things with the commercials, Super Bowl.
Speaker 3:Like, these are our attempts. Actually, if you notice the Super Bowl tweets didn't actually matter on x. Like, most people made fun of it or didn't even engage with it. Mhmm. But it did help us get a lot of, like, mainstream normal people become aware of the app and use it.
Speaker 3:Same thing with the Legion j commercial, like, helped helped increase our usage in other countries outside, you know, countries that don't even use x. So I believe the platform that has the most people in the world is Instagram for good or bad. Like, if you go to any city outside the Bay Area, just watch which app, like, people are having on their phone. It's mostly Instagram or It's not really x.
Speaker 1:Yeah.
Speaker 2:Do you spend a lot of time thinking about AGI or is there just enough consumer application features to build that that it's it's almost a distraction?
Speaker 3:I do spend time thinking about it. In some sense, it's a unique opportunity to have, like, the ability to have the front end, which people can feel the AGI, let's say.
Speaker 2:Mhmm. Yeah.
Speaker 3:So you do wanna think about experiences where people can be made to feel the AI and that creates that jaw dropping magical end consumer experience. So that we so that's kinda why we worked on all these pro searches, it is voice assistance agents. We're working on the browser browser agents. You can only do all that if you're, like, making some predictions of where these models could potentially get to and try to build before even they get there. You don't wanna be late.
Speaker 3:You wanna build at the right moment where like, kinda like how we book Perplexity around the GPT 3.5 time, not GPT four time. It would it would have been too late then. Mhmm. You need to do pick your moments, so you do need to think about AGI. That said, I'm not a believer in, like, you know, fear mongering.
Speaker 3:I I just think it's already happened. Like, the genie is out of the bottle. China versus America. That race is already going on. Nobody's gonna slow down, and everybody wants glory.
Speaker 3:No. Nobody cares about the other people or something. Everybody wants glory and and and some kind of power to control the future. So let's just like like accept the truth and move on and try to like make sure everyone knows how to use the AI so that their livelihood doesn't get affected.
Speaker 2:That makes sense. You're I I was thinking about it. I don't know of another $10,000,000,000 plus AI startup founder who's not constantly promising that AGI is, like, two months away to get, you know, that you're just like, you know, let's focus on our users and focus on the opportunity.
Speaker 1:Probably the right thing. I mean, speaking of the the the foundation models on a more practical level, where are you seeing the most interesting vectors of optimization? You know, people are focused on, large context windows Yeah. Huge pre training runs, but there's been some debate about, are we hitting a pre training wall? Are we hitting a data wall?
Speaker 1:RL is very hot right now.
Speaker 3:Yeah.
Speaker 1:Where do you think the Foundation Model Labs need to go? And and what are you specifically excited about? I imagine that, you know, it'd be a cogeneration model, not super important to your business, but something that's more knowledgeable and hallucinates net less about facts, extremely valuable. So what do you wanna see?
Speaker 3:I think RL is the place where most investments are gonna go to, especially with with models like o three that are able to do tool calls pretty natively rather than being prompt engineer to do that or bit like, for example, before o three, the way we built, like, our agents is there would be one model that gave came up with a plan for the query, another model that would execute the plan by converting the plan to, like, smaller queries, filtering links, calling searches.
Speaker 6:Sure.
Speaker 3:And then another summarization model that actually takes all the results of the planner and the router and, like, summarize things. Now it's all, like, one single model. Mhmm. That's great. Like, that that that that means, like, you have to, like, rebuild it.
Speaker 3:You have to throw away lines of code and rewrite it. But we've been doing this since the beginning. Like, people think, like, perplexities remain a stagnant code base or something. It's always changed as soon as, like, models became more capable. But the interesting thing about the native tool call kind of models is that if we want, like, a sonar version of the product that runs on our own setup, we also not see need to start doing post training beyond just training for instruction following and summarization, but, like, also, like, two calls and and and and completing tasks using RO.
Speaker 3:And and we hope to collect all this interesting data through the browser platform where, like, people are giving tasks on on our browser, and then we obviously, some of some of the agents will fail there, where we'll collect all the data and, like, try to create, like, positive trajectories, create, like, eval suites, and then do our post training on that. And so the the nice thing is a lot of open source code bases exist on how to replicate g r p o or p p o Yeah. And post training these models. And we've been doing that work already. So, that's where we plan to invest more resources into for this year.
Speaker 1:How are you thinking about advertising in the context of search? It's historically been an ad driven business, but we're seeing a lot of AI product companies just charge $20 a month, $200 a month, $2,000 a month. Who knows? Is there a future where if you search for what's the best corporate card, it's gonna ramp, it's gonna show up at the top if they bid bid on that?
Speaker 3:Hopefully not. I I think that's that's the main reason why people like using AIs. They they think it's giving them something that Google doesn't offer. Mhmm. And and so I think the subscription revenue is very healthy and positive.
Speaker 3:Like, OpenAI is being 10,000,000,000 a year or something like that. Right? Or 7,000,000,000, something like that. So definitely, that's only gonna grow. And and if AI start doing things, not just answering questions or or writing code, people will pay even more because they'd kind of think about it as hiring somebody.
Speaker 3:Mhmm. If you look at the amount of people people pay for personal assistance, chiefs of chief of staffs, personal chief of staff, estate managers, nannies, like, you know, it's a lot of money. And there are, like, a lot of people who can afford all that. And we're talking about doing something hundred x cheaper and also economically 10 to hundred x more valuable in terms of end output. So I I think the subscription TAM is way bigger than what it is today.
Speaker 3:I I believe, like, you can do a lot of interesting things with memory where once you understand the user deeply enough, the user can probably trust you if you show them relevant sponsored content as long as it's super personalized and hyper optimized for that user. Instagram has shown some stats where the engagement time on their platform reduces if if they remove the ads because that's level of personalization of the ads. So if if any of the AI companies can do that, I think that could be, like, a thing where brands could pay a lot more money to advertise there.
Speaker 1:Yeah.
Speaker 3:So that's yet to be explored. But in order to crack that, you need to crack memory properly. That's kind of one of the other reason we wanted to build a browser. It's like, we wanna get data even outside the app to better understand you. Because some of the problems that people do in these AIs is purely work related.
Speaker 3:It's not, like, that personal.
Speaker 1:Yep.
Speaker 3:On the other hand, like, what are the things you're buying? Which hotels are you going? Where are you which restaurants are you going to? What are you spending time browsing? Tells us so much more about you that we plan to use all the context to build a better user profile.
Speaker 3:And and maybe, you know, through our discover feed, we could show some ads there.
Speaker 1:Makes no sense.
Speaker 2:How quickly do you wanna launch Comet? Do you have a do have a launch date of mine at I'm doing soon you wanna launch this afternoon.
Speaker 3:Yeah. It was supposed to be out by now. We got delayed. I think partly because we underestimated the difficulty of the project and partly because we try to do multiple things. And so we've tried to scope it down and we're we're aiming to get it out by mid May.
Speaker 2:Awesome. Good luck. Last last question I have. Yep. You posted ByteDance of America is worth building.
Speaker 2:I'm assuming you're you're building the ByteDance of America.
Speaker 3:Hope to be able to, but we need to earn the right to do that. So let's first, like, you know, I wanna succeed with the common browser. I think that'll be of, like, the real second product of Perplexity. Everything else we launched like the assistant or the, like like, apps, platforms is all, like, just different versions of the same thing.
Speaker 1:Mhmm.
Speaker 3:Yeah. The comet will be the first really truly different product. And I think if we can do that a second time, I believe, like, we can and and Discover. That's the other product we're trying. Though it's within the app right now, but you could imagine spinning it out as a separate app too.
Speaker 3:You could imagine us, like, earning the right to do that. I think there's a lot. Like, I've spoken to the founder of ByteDance, one thing he told me is they're they're structured in a very different way. It's not like, like, CapCuts or TikTok have, like, different growth teams. They they do have their own growth teams, but there's one team by Dance that takes care of infrastructure for all their companies.
Speaker 3:One team that takes care of growth for all their companies. One team that takes care of front end mobile development for all their apps. And so they share knowledge across apps very quickly. Mhmm. It's insane.
Speaker 3:So that sort of structure doesn't exist in in in The US. Like, take Google is actually the closest to ByteDance of America, if you think about it. They have so many different apps in one umbrella, but they they don't share lessons. Mhmm. Like, the YouTube team is so different from the Gmail team, so different the Chrome team and that that's why it takes so much time to collaborate.
Speaker 3:So you need a very different leadership structure and a culture to make it happen in America.
Speaker 1:Yeah. That makes sense.
Speaker 2:Every time I ask you one more question, get one more question and this I promise is the last. That's
Speaker 3:like all people use perplexity.
Speaker 2:Yeah. Yeah. It's great. Without violating any NDAs, what what's going on with with TikTok speaking of ByteDance? We there was a big flurry.
Speaker 2:Everybody was submitting, you know, bids and then it's been quiet. Is there any do you have any insight that is not necessarily confidential?
Speaker 1:Yeah. What does
Speaker 3:pipeline I really don't. We we we've submitted our bid. We never expected to be the leading candidate or anything. We're a very small company compared to them. Our bid was more interesting in the sense that everybody else who bid for them did not wanna do anything to do with the algorithm.
Speaker 3:But I felt like the core problem is fact that, like, the algorithm is controlled by China in some form or the other.
Speaker 2:Yep.
Speaker 3:Even if they say, okay, the Chinese app is separate. Apps running outside The US and outside China, like European countries are all sharing the same code. And so they can get to, like, use that data and influence, you know, what feeds people in America see. So I think, like, that's where we wanted to do some real work, and the search bar is another place where we wanna do some real work. We thought our proposal was pretty interesting.
Speaker 3:But there are some, you know, we're not a data center company. We cannot guarantee them security and all that. Oracle can. So we'll see what happens. I think they've delayed the decision, decision and it's probably gonna be coupled with the tariff situation too.
Speaker 4:Yep.
Speaker 2:That makes sense. Well, thank you so much for coming on. Thank you for wearing a suit as well. Yeah. You look fantastic.
Speaker 2:And You
Speaker 3:guys are you guys are killing it like
Speaker 1:Thank you.
Speaker 3:Technology brothers. I I like the name. Yeah.
Speaker 1:It's awesome.
Speaker 2:Well, it's great to have you on, fellow technology brother, and come back on anytime when you have news.
Speaker 1:Yeah. We'll talk to you soon. Thanks, everybody. Bye. On Polymarket, who will acquire TikTok?
Speaker 1:Applovin has shot to the top of the charts. But on low vol, they have about $10,000 in a $2,000,000 market, in terms of volume. But AppLovin is at 20%. Oracle, Larry Ellison combined, if you consider them one entity Over. 21%.
Speaker 1:Oracle's at 12. Larry Ellison's at nine. Microsoft's at eight. Amazon's at eight. Tim Stokely at eight.
Speaker 1:Frank McCourt at eight. Alexis Ohanian at six. Perplexity is down at 4% right there next to mister beast at 4% as well. Walmart at 3%, who we discussed earlier, would actually be the the Ben Thompson choice.
Speaker 2:We should get ourselves in the mix and
Speaker 1:submit a fake bid just to go viral to
Speaker 2:bid on anything on Polymarket, but No.
Speaker 1:But but we should We should
Speaker 2:throw our arms
Speaker 5:in the app. TikTok.
Speaker 2:Yeah. We should just bid on TikTok.
Speaker 1:It's just gonna be we're gonna no more slop content. It's just We considered doing a
Speaker 2:press release around it. It it never, never hit the It
Speaker 1:played out pretty quickly. Anyway, let's do some timeline while we wait for our next guest. Tyler, says, Scoop, I found TBPN's hidden warehouse. Nice try. And he finds a picture of the brother's supply.
Speaker 1:I wonder where this is. But we always love when fans share fun photos.
Speaker 2:You found us, Tyler.
Speaker 1:You caught us. We are in the Catch. In the market for a new studio, hopefully moving into one soon. And, this this brick building looks like it's, fireproof. Been it's Lindy.
Speaker 1:It's been around for a long time. Probably safe. Probably great to record a show there.
Speaker 2:We love a fireproof.
Speaker 1:Luffy says, there there was this news yesterday in TechCrunch. Ex meta engineer raises 14,000,000 for Lace AI, a revenue generation software startup.
Speaker 2:And This was shaking up the timeline.
Speaker 1:Everyone was quote tweeting this.
Speaker 2:Luffy says, hey, Lace. Make a hundred million ARR software for me. Do not make any mistakes. Fantastic prompt, by the way. Use it.
Speaker 2:Use it on any of any of your preferred model. It'll it'll work.
Speaker 1:Don't people why don't more people do this?
Speaker 2:I don't I don't know. It it seems like one of those Seems obvious. Thielian sort of secrets.
Speaker 1:Secrets, I suppose. Yeah.
Speaker 2:For sure. No. But Lace Lace, I guess, is is focused on maximizing revenue for your call center with zero extra It's
Speaker 1:more just like the TechCrunch, like headline went weird. Yeah.
Speaker 2:But again, TechCrunch is just so Yeah. Lot of startups don't generate much revenue. Yes.
Speaker 1:Yes. So they're like, hey, we will our our business is revenue generation. Yep. But, yeah, TechCrunch is back. I don't know if this is accidental, but I feel like again and again, we're seeing more TechCrunch headlines post acquisition.
Speaker 1:So they're doing well.
Speaker 2:It's great to see.
Speaker 1:Great to see. Patty, I just wanted to give Patty a shout out because he's a friend of Patty. He says he's proud to announce he's starting a profitable startup. VCs, my DMs are open. So, yeah, if you wanna get in
Speaker 3:touch with
Speaker 1:Patty, he's a free agent. He could be picked up at any moment.
Speaker 2:Japan, live streaming.
Speaker 1:Could be picked up by a venture capitalist or a company, but we left Patty on this stream.
Speaker 2:This post from East Village Guy is thirty too late for me to lock in. My brother Ray Kroc was a 52 year old traveling salesman when he met the McDonald brothers. Get a grip.
Speaker 1:It's awesome.
Speaker 6:And I
Speaker 2:thought this was worth highlighting. There's so many great stories of this. Yep. Enzo Ferrari is another. He was 45 Yep.
Speaker 2:When he started Ferrari. Granted, he had spent a couple decades in automotive racing.
Speaker 1:Founder of Zoom, founder of Workday, both sixties, fifties when they started their companies.
Speaker 2:Red Bull founder too. Right?
Speaker 1:Yeah. Dietrich.
Speaker 2:Yep. I think
Speaker 1:he was pretty old. Founder of Monster. Very old. Which was very funny because it's a very dumb brand.
Speaker 2:Estee Lauder founder.
Speaker 1:Yeah. There's tons of these examples. Never too late to start doing your life's work and start a generational company. Just do it. Why don't why not?
Speaker 2:Estee Lauder was 38 years old.
Speaker 1:Why not just start a power law company? More people should do that for sure. Anyway, we have this bizarre TikTok or YouTube video. It's the third most viewed video on YouTube this week. It's an AI generated short of a pug that saves a baby from a plane crash, and then they try surviving on an island.
Speaker 1:Can we play this? It's it's, this is the future, folks. This is this is entertainment now. It's great. Parachute.
Speaker 1:It does have a compelling narrative. You know? Inciting inciting element, inciting action, you know? Turn of events. Will he save the baby?
Speaker 1:The sound effects are It's really well designed. It's so optimized for now.
Speaker 2:It's got 400,000,000 views?
Speaker 1:400,000,000 views. Yes. 400,000,000 views. Feeds the baby, starts cooking over the coconut, cooks fish. Oh my god.
Speaker 2:That is adorable.
Speaker 1:Feeds the baby some sort of fish stew and then writes SOS in the sand. They're of boys. And then for some reason the military shows up and they like have like guns and stuff. Overnight success. And they've overnight success.
Speaker 1:And they rescue the baby and the pug and then it just ends. It's like the ultimate like, don't expect it to end
Speaker 5:so you
Speaker 2:don't watch That is fine art.
Speaker 1:It's the future. It's the future. Again, you know, clearly some some human element in there figuring out what's viral about it, but pretty sloppy. Pretty sloppy.
Speaker 2:Little sloppy. Well, you know what's not slop? AI grant batch one. That's Absolutely insane. Jeff Huber, who we had on the show shared this.
Speaker 1:I didn't realize this was a throwback.
Speaker 2:Yeah, so going off the initial batch This
Speaker 1:is crazy.
Speaker 2:Complexity Yep. Was in there. Cursor. I
Speaker 1:know Chroma. Wombo. Wombo. Who else do we know in here? Pretty cool.
Speaker 1:Pixel cut, Dust, Forefront. Just so early. I wonder when AI grant batch one was. This is the Nat Friedman project. Correct?
Speaker 5:Yeah.
Speaker 1:Very, very cool. Little, like, under the radar. I guess, was it structured as a grant? It wasn't even it wasn't even YC style? Or was it did they take equity?
Speaker 2:No. It's an investment via no cap, no discount MFN safe.
Speaker 3:Okay. Yeah.
Speaker 1:Yeah. Pretty standard.
Speaker 2:So pretty standard investment. And you can imagine they've done pretty well.
Speaker 1:Yeah. I think some other cool I I'm I'm almost sure Julius went through a later batch. I saw some other folks go through. Pretty pretty cool.
Speaker 2:Yep. Julius was in batch two.
Speaker 1:We have our next guest here. Let's bring him in.
Speaker 2:You guys told us you yearned for the minds, so we brought the man himself. You doing, Ted? Miner. What's
Speaker 4:going great. How are you, John? Jordy.
Speaker 2:Fantastic. What's happening?
Speaker 1:You're looking great in that suit. Welcome to the show.
Speaker 4:Thank you. It's Technology Brothers. You need to Yes. You need to dress up.
Speaker 1:You gotta dress There you go.
Speaker 2:For sure. And I love the map too. That's the only market map that I care about personally.
Speaker 4:Yes. This is this is our target market, at least That
Speaker 1:is our market map. What what's actually going on with that map? What what are the different colors represent?
Speaker 4:Yeah. This is a geological map showing kind of the common rock types in a given area. And you can see the Central and, Eastern US are not quite as exciting as the Western US, and that's where all the minerals are.
Speaker 1:Interesting. Can you give us a brief overview of you and your company just to kick us off?
Speaker 4:Yeah. Absolutely. So I'm Ted Feldman, founder of Juran, started the company about a year ago. We are building and operating automated diamond drill rigs used in mineral exploration. So I'll start out kinda high level what how does mineral exploration work and kinda get into what is the actual problem we're solving.
Speaker 4:So, basically, building a mine is, in many cases, a billion dollar endeavor, incredibly expensive. In order to justify this CapEx, you never really get understanding of what's actually going on underground. And so you have this kind of decade long exploration process where you'll start out, maybe geologists walking around. They're seeing some interesting rocks. You can do geophysics, look for a magnetic anomaly, a gravity anomaly, or do some seismic surveys.
Speaker 4:If you do soil sampling, kind of pick up some drill down some kind of tiny holes, see if there's kind of trace elements of what you're looking for. But, really, in order to understand what's underground, you gotta drill. And the main type of drilling used in neural exploration is called diamond drilling or core drilling. This is basically your where you're collecting cylindrical core samples of the rock anywhere from a few hundred meters to a kilometer or more underground, generally a few inches wide. You pull it up in three meter intervals.
Speaker 4:But really, once you collect these core samples, you send them off to the lab. The lab will tell you exactly what the composition is. You do that every foot or every meter across hundreds of holes. You plug all this data into a three d model, and you have a kind of, yeah, three d model of the the subsurface. You can visualize where is the mineral deposit, see how large is the resource, what's the grade, the kind of percent of the metal you're looking for within that deposit, and then make a determination on whether it's economic to mine or whether you need to collect more data in order to make that determination.
Speaker 4:Can you answer the problem here. Mhmm. Go ahead.
Speaker 2:Before you go into the next segment, can you talk about the value chain? Is there different Yes. Groups that are doing, you know, the core Yeah. Of like research, and then do they sell the rights? Basically say like, hey, this is worth spending a billion dollars, but like, we're not gonna spend a billion dollars, like, should do it, and they sort of like sell access to it effectively.
Speaker 4:So so the way this will normally work is you have an exploration company or junior explorer, junior miner. They either own the land outright. They have rights to lease the land, or they have some claim on federal land. But they have the rights to to mine in a given area. And they basically have a hypothesis within geology that there is some valuable deposit underground.
Speaker 4:And they raise capital primarily from public markets. Many of these companies go public extremely early on on the TSXV or the ASX, and they raise capital and spend most of that capital on drilling to actually collect more data. And so then this constant cycle of raising capital, spending most of it on drilling, analyzing those drill results, updating the geological model until they can either raise enough capital, raise a billion dollars equity and debt to actually build the mine, or what happens more often is sell the mine or sell the deposit to a larger miner that will actually have the money on the balance sheet in order to develop the assets.
Speaker 2:Why
Speaker 4:And so you
Speaker 2:Why public markets versus private? Is it just because you need to raise so much money? You need to be able to basically effectively market
Speaker 1:It sounds like biotech. Like, what happens with biotech companies going early, earlier out?
Speaker 2:Yeah. And are these, like, typically, like, penny stocks where they're just trading? Yeah. You know? Exactly.
Speaker 2:And it's some random
Speaker 4:Mine Yeah. Yeah. Is historically a penny stock industry. We used to have kind of small exchanges in Denver or Phoenix in The US, but in North America, this is dominated by Vancouver and Toronto where a lot of these exploration companies are based. Canada, has a lot more capital flowing into mining than The United States does today.
Speaker 4:And it's really just how it's been done historically. These investors, largely kind of smaller retail investors. Historically, they want liquidity, and they they can't can't can't just be called up for a private placement if you're Joe with a hundred bucks to throw into a gold project.
Speaker 2:Did you ever speaking of mining, did you ever join a call with a VC early and have them be like, sorry. I I thought this was like crypto That
Speaker 4:has happened a lot. It has happened less now than a year or eighteen months ago, which I think is a very promising trend.
Speaker 2:Got it. That's good.
Speaker 1:How much of the business is kind of just you need to take off the shelf technology and just go do the thing versus you need to build new technology and and is that more in like the hardware world or the software world or are you just like going and doing the actual exploring? Like, can you concretize
Speaker 4:what you're Yeah. So I'll get into what is Duren actually doing. So we're a drilling contractor. We are building rigs from scratch and and operating them for exploration companies. We're starting our first pilot with the Gold Explorer in Nevada in a little over a week.
Speaker 4:We'll be out in the field for that. We started building this rig about four months ago. And so we get paid basically per meter that we drill for our clients. And so we're not taking on the geology risk.
Speaker 1:Yeah. Yeah. And why are you building the rig yourself? Yourself? I imagine that is that just built you're buying different pieces of equipment and then piecing them together?
Speaker 1:I mean, you've raised money, but not that Exactly. Like, imagine you're not reinventing
Speaker 2:the Plus,
Speaker 1:it's probably Yeah. There's good drills out there. I imagine you don't need to build a new drill. Or do you?
Speaker 4:Yeah. So the initial idea was let's retrofit a rig. That could maybe save us a lot of money, and there this was the avenue I was pursuing for about six months. And we really had two options. We could buy a Chinese rig for less than a hundred grand, and we need to add a whole bunch of sensors.
Speaker 4:I talked to a lot of the operators. These things fall apart. They are not high quality. So we rolled that out. Or you could buy a Western rig for half a million bucks, and you they need to hack into the firmware and probably put a warranty, which you do not want to do on a half million dollar piece of equipment or partner with a manufacturer and figure out how to actually pull data from it.
Speaker 4:We tried that with a couple of manufacturers. They were incredibly slow. And all the manufacturers, they sort of have their own half hearted efforts on autonomy, and so they didn't seem particularly eager to partner up to partner with us. And so almost out of necessity, we had to design our own. And now the way the Trig operates is really similar to every other sort of rig.
Speaker 4:All all these drill rigs are basically two hydraulic rams pushing what is called the drill head, which is what provides a rotary motion to the the drill rods into the ground. So all drilling is really so have a bunch of pipes that you screw together and then push and twist into the ground, and you have bit on the end to make sure you get a a clean-cut. And so we are we're the off the shelf parts that we're buying is with the drill head. That's what grips onto the rods and rotates them. If other part called the foot clamp, which just clamps down onto the bottom part of the drill string, it make it easy to load a new rod in and then ramps to push it into the ground.
Speaker 4:And then the structure is ours. And then in order to actually retrieve the core sample from the bottom of the hole, think about it like this. You have your drill bit, and then you have which is a cylinder. That's what our logo is actually. And then your drill rods coming up from that.
Speaker 4:But inside of that bottom rod, you have another tube called the inner tube. There's a latch on the top of that. So, basically, once that inner tube fills up with rock when you've gone down five feet, you can grab a tool called the overshot, lower it down on a wire line. It latches into place. You could pull up the inner tube, get in the core sample, and then that's what you send to the lab to be analyzed.
Speaker 2:Great. How how mature is the venture backed mining market? Like, are there market maps that exist and are are
Speaker 4:There's a few. It is And and were
Speaker 2:you when you're surprised everybody wants to go to space, nobody wants to look, you know, beneath our feet and and go down, has it been surprising how how little investment has gone into the actual technology side of the industry?
Speaker 4:It's there's been very little surface area between mining and particularly Silicon Valley historically. Australia has a bit of a more mature mining technology ecosystem, but not nearly as much capital as we have over here. And so there's been a few, kind of billion dollar or multi hundred billion dollar mining tech companies over the last decade or so, but just a few. And, like, mining overall is a 2 to $3,000,000,000,000 industry kind of, yeah, overall market size. Mining tech is a small portion of that.
Speaker 4:But, it's a difficult industry to sell into. It's really why it's difficult to start a tech company here. Building a mine is incredibly CapEx intensive, and you're basically making a bet on technology early and then utilizing that equipment or software system for a decade plus. And so these companies are risk averse. They don't wanna bet that the farm on a on a new new technology.
Speaker 4:Where I think we come in, there's a few other companies with a similar model, is as a contractor. So we're just replacing a separate service provider, and any sort of innovation that we're creating is done internally. So we are a more efficient, safer, and more cost effective drilling contractor because of the autonomy that we're building. But it's really no rush to the customer. We get paid just like any other contractor to them.
Speaker 2:What's been the industry's reaction to the trade war? China very early came out and said that they were restricting access to various rare earths. Is that Yeah. You know, what's been your read on the situation? How are how are US players kind of reacting?
Speaker 4:Yeah. Rare earths are very close to my heart. Prior to starting Turin, I worked for MP Materials, which operates the only rare earths mine in The United States for about a year and a half. Their mine is in California, about three hours away from where we are right now in LA. They MP produces about 15% of the global air supply.
Speaker 4:They refine about half of it domestically right now. They announced last week that they're seizing shipments to China, so keeping it all domestic. We're going to Japan, Korea, which they have some off take with through Sumitomo. It's it's I think it's certainly a tailwind for the Western producers, but there is fear because we don't have everything in The United States. Rare earths, we would be almost self sufficient on, but we really need to ramp up the the processing.
Speaker 4:The problem is that within this group of rare earths, about 15 different elements, you have some rare earths that we have a good chunk of at Mountain Pass, like neodymium and prasiodium. But then you have heavy rare earths, like terbium or dysprosium, which we do not have enough of. And empty materials, it's very heavily weighted towards these light rare earths, and it's very little of these heavy rare earths. And so we really need to partner with countries like Brazil or Vietnam, or the two that I point to for rare earths that are potentially allies, and maybe we'll get closer to them over the next few years. We're gonna need to import.
Speaker 4:There are no other decent rare earth deposits in The United States that we can just spin up production at.
Speaker 1:That we know of. You never know. We could
Speaker 2:find US has a long history.
Speaker 1:We have a long history. Bunch of gaps in that map in Ohio. We'll find rare earths there. I'm sure.
Speaker 4:That's that's that's where we come in, is that in order to find that hundred deposit, you gotta spend $100,000,000
Speaker 1:everything, every suburban neighborhood, just drop a Durin miner in the back of my backyard and start finding stuff.
Speaker 4:What we'll do first is fly fly planes over to do some sort of magnetic survey. The USGS is a pretty cool program for Earth MRI where they're mapping a lot of the country with tighter spacing than they have previously with these geophysical surveys. But we need to be doing a lot more on that because that's really the top of funnel that narrows down the, potentially, might have sites. You talk
Speaker 1:oh, sorry. Can you talk a little bit more about autonomy? I'm seeing the first prototype rig, can core 300 meters around a thousand feet deep Yeah. Two and a half inch diameter. And these rigs can run unattended for something like two to three years.
Speaker 1:So what is the math on that? Is the rig moving around, or does it just take that long to get a single core sample out?
Speaker 4:Yeah. So, basically, I I'll tell you kind of how it's done today, what we have now, and then where we're gonna be in twelve months. So today, you have a rig these things weigh into 10 tons. You're normally track mounted, so basically on tank treads. You have you put them on a truck as close to the side as you can, then you have a guy with a remote control driving it in the rest of the way.
Speaker 4:You generally three operators on a rig. You have the driller. He's the guy listening to it and looking at a bunch of gauges, and he's really sort of interpreting what is the kind of rock that we're going through that through at that time. Mhmm. And from that, adjusting RPM, the amount of weight applied to the drill bit, the pressure of a fluid that you're pumping down hole to clear the cuttings and keep the bit cool.
Speaker 4:She's kind of constantly adjusting these parameters. Then you have another one or two guys go helpers, and they're doing a lot of the manual work. They're loading the rods into place because you're normally they're using five or 10 foot rods. They are grabbing the overshot, lowering it down to pull up the inner tube, tapping on the inner tube with a hammer to actually take the core out, putting it in boxes for the customer, greasing the rods, adding additives to the the mud mixture because you gotta adjust the viscosity of the fluid that you're pumping down hole. And And so you really have this this sensing problem, this controls problem of adjusting these drilling parameters, then you have this more so robotics problem of just grabbing the rods, putting them into place, grabbing the core samples, etcetera.
Speaker 4:So on this first rig, we have basically the ability to collect a whole bunch of data, but everything that's going on on the rig at any given time, we're gonna use that data to build a sort of v one autopilot system, deterministic at the start, move to machine learning when we get enough data. There really are not datasets available for this online. And so we've gotta gotta do a whole lot of drilling before we can actually get to Pulaskami. So follow-up. The rod hand.
Speaker 1:How long does it actually take to drill a thousand feet deep?
Speaker 4:Yes. So a good shift is about 50 feet in a day, and so twelve hours, fifty feet, a thousand foot pole, 20 shifts, ten days from
Speaker 2:the 20 That's traditional, like, you know, human operated, so that's like
Speaker 1:a monthly work, Exactly. Exactly. Like a month on one hole.
Speaker 7:Right, wow.
Speaker 4:Yeah. And you're losing about a hundred dollars a foot.
Speaker 1:Yeah, okay. Yeah, that's a lot. Interesting.
Speaker 2:Yes. How are you
Speaker 4:so Really, what what what we're trying to do is we're we built this first rig, manually operated at the start. We'll have some automation in terms of rod handling and kind of a d one of this drilling parameter adjustment system. But then on the next version, which we're start building in just a couple months, We'll we'll kind of add add on to the rod handling system to actually be able to cover the core sample, design our own mud mixer that can dump in the additives separately, and then get most of the way there in terms of kind of removing these jobs on-site. And it's really it's it's yes. But I think we can save a lot of money because labor is incredibly expensive here, but it's more so about availability.
Speaker 4:We are in a workforce crisis in the mining industry right now. I heard someone say, well, like, we don't have a an autonomy problem in the mining industry, but labor problem. We just don't have enough people. And so Is Minecraft not
Speaker 2:providing the pipeline that one would
Speaker 4:No. I think the the problem here is you play Minecraft when you're like eight to 14 or something or or maybe later. And then then you have this kinda eight year gap between a sort of high school and finishing college to where you're not involved in the mining industry.
Speaker 1:We need Minecraft for I
Speaker 2:have to ask, how are you so goaded at marketing? You have, like, one of the most unique sort of like hard tech brands every time I I I think like Yeah. It's very it's very common for people to copy what Anderle does and it's very hard to do something that feels like new and fresh and like super opinionated and I've loved your out of home ads and this segment is brought to you by Adquick. But you I I think you've been extremely strategic. I saw this hiring billboard that you had that you can't have rocket science without rock science and sort of like placing these strategically in in Hawthorne.
Speaker 2:Where does that come from? When did you figure out that you had a a knack for this? Because I'm assuming it's I'm I'm assuming your your team helps, but oftentimes marketing this good typically is is very founder led.
Speaker 4:It's it's we've got an incredible team. My head of operations has really helped a lot with the the marketing. We have a few incredible designers that help us out part time with all this as well. Hiring is a life bread life blood of any any company, particularly a company with as as PortaVision as what we're trying to accomplish. And so we need to get the word out and have kind of this massive funnel of people that have heard of us.
Speaker 4:Some of them will be interested, and some of them we are going to want to hire. And so we I think we need need a cool brand for people to hear about us, both in kind of the the the build world across from SpaceX. Obviously, we wanna pull pull incredible talent from SpaceX. But also, like, there are very few companies in the mining industry that really care about I think they don't care about their brand. There are very few that are particularly
Speaker 2:good brand.
Speaker 4:About creating a cool brand. And so, like, we get, like, we we get good, great engineers in LA reaching out to us because they they like our stuff, but even more so, drillers and geologists in the mining industry who are like, you're the only cool company in the mining industry. I mean, we've hardly put anything out yet. And so both kind of in both of those sides, the the engineering and for kind of the mining customer and talent acquisition, we wanna be very intentional about it, and there is much more to come. Once we get this first rig in the field in about a week or so, there'll be some really cool videos of us actually drilling and showing some hardware in the field.
Speaker 2:Love it.
Speaker 1:Can you talk us through the path to full autonomy? I imagine it's like a walk crawl or crawl roll walk run situation. Yeah. Is teleoperation a big deal here as you get towards a fully autonomous autopilot system?
Speaker 4:Yeah. So it's we we need a whole lot of data for this. And so it's mainly controlled at the start. You can have a a driller there with an iPad or laptop. Yeah.
Speaker 4:The the infrastructure is there, but it's really like a Tesla full self driving sort of system. Like, you build the the software to actually control it, a drill by wire system is what we're calling it. Yeah. And then you need data. And so we're gonna have a driller on-site operating it initially, collect this data.
Speaker 4:We need them there to actually test the robotic side of this in case anything goes wrong. And I think we're on handling. We should have down over the next few months, so the extraction system by the end of the year. There's a bunch of little stuff, like, how are how are you gonna grease the rock to to figure that out. We're dumping additives into the the mud mixer.
Speaker 4:And so we're we're going about this incrementally. We'll have three guys at the rig initially, get out of two, then hopefully have one, can operate it from a self safe distance. And if something goes wrong, bring another guy in. But we're gonna get a point where you don't need at least someone on-site, at least not over the next five years. You need a flat surface to drill on.
Speaker 4:You have guys out there with dozers clearing these drill pads. You need to dig a sump pit to put the the water into after you use it. You need to deliver your consumables, your water, your fuel. You need to pick up the core samples to deliver to your customer, the exploration company. And so there's always gonna be things to do.
Speaker 4:Like, you need someone to get the rig there and then maintain it. But the point is, like, we don't need someone there listening to the rig and loading rods into place. Like, they're they're they're they're time operating a fleet of rigs.
Speaker 2:Two weeks ago, it came out that that China was limiting rare earth exports. Chamath chimed in. He said, this may be a good moment to let everyone know that I control one of, if not the largest rare earth supplies outside of China. At full capacity, it can be 25% of what the world needs, all located within countries allied with The US and The US itself. A lot of people push back on this.
Speaker 2:They said, okay, what's the company? He said it was in stealth. I wanna give him the benefit of the doubt and and say, you know, it sounds very it sound sounds almost unbelievable that a stealth company could control 25% of the world's rare earth supplies. Is that is that possible? Could could there have been some sort of like roll up behind the scenes?
Speaker 2:What was your reaction to that Perhaps.
Speaker 4:I haven't heard anything about Shamat's involvement in any Rare project beyond he helps back, can't be materialist five or so years ago. Yeah. I haven't heard anything. Maybe he does. I hope he does.
Speaker 4:That would be great.
Speaker 2:I hope he does. Some
Speaker 4:master Rare mind that that, yeah, myself and the friends with rare earths analysts haven't heard of. And so I want them to surprise us, but I haven't heard anything.
Speaker 1:Sure. Cool. Can you talk about the challenges of putting a sensor a thousand feet underground? Like, I just imagine if there's, like, dirt and grime and crust and whatever else is down there, plus like a diamond tipped drill churning everything up, like, even putting like a thermometer down there is going to be difficult. How are you actually collecting data?
Speaker 1:Is the has does does this exist off the shelf? Is this something, like, oil explorers do? I imagine that's mature.
Speaker 4:So the short answer is we're not collecting any data underground at this point. Everything we are measuring, you can measure from the surface.
Speaker 1:Just like the human does, right? Because the human's listening to everything and collecting that data from above
Speaker 4:Exactly. Structures.
Speaker 1:Got it. Okay.
Speaker 4:And vibration. We're not even using vibration right now. So you can measure your your weight on bit, basically, how much force are you pushing into the ground with.
Speaker 1:Got it.
Speaker 4:Your RPM, how fast are you spinning.
Speaker 1:Okay.
Speaker 4:Pressure going into the hole. Yep. Your rate of penetrations, just how quickly you're moving into the ground. Your torque, you can do that through a secondary pressure reading. Yep.
Speaker 4:But there are you can put sensors downhole. There's a whole kind of field of study within the in the gas industry primarily called MWD or OWD, measurement while drilling, logging while drilling. But you can put sensors downhole. It's something we're gonna be looking into. One of the the things that you'll do when you're doing this sort of drilling, the mineral exploration, is you can send on a survey tool that can tell you just sort of exact position.
Speaker 4:Because your whole you wanna drill it straight. It's not always gonna go straight. It might deviate a degree degree or two every hundred meters. And if you're trying to hit a 50 foot target, 500 feet underground, it's you might miss. And so making sure you know exactly where the tip of the drill is at all times is paramount.
Speaker 4:So you can lower a tool down either every run or every 50 meters, really whenever you want, and that'll tell your exact position. It makes you get a gyro probe. And so if we can integrate that into our core barrel downhole, that would be cool. Not doing that yet. Or or doing some sort of survey or XRF to scan the core or the sides of the walls as you're actually drilling, that'd be great.
Speaker 4:We're not doing it yet. It's gonna be done soon.
Speaker 1:Are cave ins a problem? Like, as you dig down Yes. You you you get, you know, you have a two inch hole that you're digging. And then if you pull up the rods to send something else down, and then all of a sudden it collapses on itself, that seems like a problem.
Speaker 4:You're you're thinking like a driller. That is a huge problem in this space. Basically, what you do, as you're drilling through the first, call it hundred feet of kind of unconsolidated sediment or looser rock in the surface, what you'll do is you'll drive casing. And so casing is basically a wider diameter pipe that you'll drill down with and then drill through that hole. And that basically prevents if there's some sort of collapse near the surface.
Speaker 4:It goes around the casing. And if your casing gets stuck, but at least it's not around your drill string, and that continue drilling through that. The problem is what if you don't try the casing deep enough or there's some sort of fracture downhole, 500 feet down or whatever that does collapse in? And you'll basically what you're trying doing then is try a whole bunch of different RPMs, pull up with maximum force, but sometimes you get stuck. There's really two options.
Speaker 4:You could try to if you try to guess where the caving is, you can actually use tools to cut the steel above that and just recover everything above that. You lose some some steel in the ground.
Speaker 5:Sure.
Speaker 4:Oh, well, you're out $10.20 grand at least. Or you can, you know, say you're stuck, but you can actually drill through it. So there are tools that they can literally drill through your previous tools that were downhole at a smaller diameter, and should get some steel in the steel in the inner tube, which is pretty cool to see. Let you continue the hole. You don't have to abandon it.
Speaker 4:You're decreasing the diameter, not as valuable data, and you are still gonna lose some equipment. And so, basically, don't wanna don't wanna push it too hard to to avoid risk any cave in.
Speaker 2:Last question on my side. Just curious. How has the have have, I'm assuming throughout history, the the sort of drill bits, diamond drill bits were just actual diamonds that people pulled out of the earth, then at some point they were lab grown, or were they always? So What what's the history there?
Speaker 4:Yeah. So the way these droplets work is you have a it's primarily iron. So the soft iron matrix with diamond particles and strip board impregnated into it. And so Yeah. You can, like, kinda see I I wish I have brought a droplet over here to show you all.
Speaker 4:That would have been cool. You can see the tiny diamond particles. It looks like glitter on it. Yeah. And then as it as it cuts the diamonds, the hardest material on earth, but they do wear.
Speaker 4:They dull. And so the bits are designed such that as the diamonds dull, the iron wears at approximately the same rate to reveal sharp Very
Speaker 2:cool. Very cool.
Speaker 1:Last question for me. Armageddon. In the plot of Armageddon, they say it's too hard to teach drilling to an astronaut. They got to teach going to space to the drillers, to the miners. Realistic or unrealistic based on what you know about how complex mining is, is, would you have trained the drillers to go to space, or would you have trained the astronauts to drill?
Speaker 4:I think we're doing both here. We are Okay. We're teaching space xers how to drill
Speaker 1:Yeah.
Speaker 4:And drillers how to how to participate in a high functional high functioning engineering organization. Yeah. And so I think you gotta do both. If you're trying to trying to build a pretty large organization and manufacture thousands of these rigs over the next five, six years, become a leading drilling contractor.
Speaker 1:Yeah. They really didn't bring any space any astronauts on that trip. It's all drillers. No. That movie
Speaker 4:I I don't think that's realistic.
Speaker 1:Okay. Anyway, this is a fantastic conversation. Thanks so much for joining.
Speaker 2:Ted, I'm very excited for you and the team. It's been awesome watching you guys over the last few months and congratulations on all the progress in the new round.
Speaker 4:We're excited to be on. Just a quick message for everyone. We are hiring jobs.durin.com. Brilliant engineers, please apply or reach out to me. Thank you all for having me.
Speaker 1:Beautiful. Have a great rest
Speaker 2:your Talk
Speaker 1:Talk soon. Bye. Cheers. Let's go back to the timeline. Durin did run a great out of home ad brought to by Adquick.
Speaker 1:There's also news on the timeline about a series a that was announced by Artisan, apparently a Y Combinator company. Announced their series a with a massive billboard. And if we can pull this billboard up, it's the previous slide, I believe. Celine is just commenting on it, but Tish says, what's going on here? And So it's the two founders there.
Speaker 1:And are
Speaker 2:they the actual founders? I thought they were
Speaker 1:Those are the founders. Those are the founders. The founders are Jasper Carmichael Jack and his co founder Sam Stallings, a former IBM product manager. But the way they're looking at each other in this photo makes me look like they're in love or something.
Speaker 2:It's Maybe they're married, but
Speaker 1:I don't know. We we often look at each other like that longingly and fondly during during photo shoots. So it's understandable. But very funny to put out a billboard about your series a
Speaker 2:With your own face on it.
Speaker 1:With your own face on it. But I guess,
Speaker 2:you know With no information about What the company guess they have the whole team there, presumably? Or
Speaker 1:are those the AI SDRs? Because I think this
Speaker 2:AI You don't know. This is my representative. Yeah. I thought these were just two Avatar.
Speaker 1:AI They're
Speaker 2:not. Employees?
Speaker 1:Those are the founders.
Speaker 2:Are the founders. For sure. They're stoked.
Speaker 1:They're stoked.
Speaker 2:Yeah. I this, you know, every once in a while, the timeline starts talking about taste. Yeah. This is a very specific kind of taste.
Speaker 3:I mean
Speaker 1:also, look, founder? They Absolutely jacked. The guy's diced. We love it.
Speaker 2:He's diced.
Speaker 1:Let's hear it. Let's hear it for Jasper. Guy is looking looking peeled. Activate gold golden retriever mode. TechCrunch shows We love commenter day one ventures, HubSpot ventures, Oliver Jung Fellows Fund participated as well.
Speaker 1:They closed a $12,000,000 round in September, and now they got a $25,000,000 series They're they're running a marketing campaign, stop hiring humans. Very viral. They I I think they just get it. They get it. I think they
Speaker 2:get it. They're They're playing five d Yep.
Speaker 1:Yep. They're gonna frustrate a lot of people.
Speaker 2:And this they knew this billboard would get Celine
Speaker 1:Totally. To post about Look at this. Celine, CEO of Loyal, says, I cannot believe a startup bought a billboard on the 101 to advertise their ...series a and671 likes. And so, yeah, out of home advertising, consistently underrated. We've said this.
Speaker 1:Go to adquick.com. Out of home advertising made easy. And measurable. And go yeah. And measurable.
Speaker 1:And go go viral. Just do it. As long as you can come up with something that's gonna infuriate enough people on the timeline term move. Will get attention. That's right.
Speaker 1:Andrew McCallop says, I think company towns are going to make a comeback.
Speaker 2:We've been exploring this. We've been exploring a town.
Speaker 1:Yeah. I was actually thinking about So I think if I think if things go really, really well for TVPN, what we're doing here in Los Angeles people a lot of people say, oh, why are you building in Los Angeles?
Speaker 6:Like Yeah.
Speaker 1:You should be in Silicon Valley. And I think that we could potentially make Los Angeles like the Silicon Valley of media, like a Silicon Valley of television almost. And we could create a whole boom. And I think a number of years, you could see some massive media companies Entire film and television industry. Possible.
Speaker 1:Right? It's totally possible. And I think it could all start right here. And so what I would say is to folks is like, let's check back in five or ten years, see the market cap of all the media companies that are built in Los Angeles and
Speaker 2:Yep.
Speaker 1:You know, maybe it's in the hundreds of billions if we add it all up.
Speaker 2:I it could it could even bigger. Possible. Yeah.
Speaker 1:We are in
Speaker 2:company John's onto something here. Yeah. Are in a company town.
Speaker 1:Los Angeles. I call it the Silicon Valley of news.
Speaker 2:Yeah. It's interesting. I mean, it it actually is very I think the experience of living in Los Angeles has become worse as the entertainment industry has struggled.
Speaker 1:Right? Yeah.
Speaker 2:There there's, you know, the the number of restaurants that can be supported has just gone down.
Speaker 1:Yep. And the interesting thing about this post is is that he's saying specifically company towns. So there's obviously industry towns. You know? New York is a finance hub.
Speaker 1:Silicon Valley is a tech hub. LA is a media hub. Miami is like a Yeah. NFT hub. But Ripley is trading towns.
Speaker 2:For Foster City.
Speaker 1:They are. Remember? Oh, I didn't know that. Oh, yeah. Yeah.
Speaker 1:Yeah. That's right.
Speaker 2:That's They left SF, they went to Foster City. They were like, we're going to focus. It's nicer to live I mean,
Speaker 1:Meta and Facebook were kind of doing that in Palo Alto to some degree. They were like building housing for employees and stuff. But I think I think what he's getting at is that things like Starbase, where a company can't just be in the hub of a main city, so they go somewhere really bizarre and off grid, and then the infrastructure builds up about the around that. We were talking about like the Stargate facility. Like, if $500,000,000,000 really does pour into one data center, there's going to be infrastructure around that.
Speaker 2:Welcome to Abilene, Texas.
Speaker 1:Abilene, Texas is going to Home and data center. There's going to be people that are like, yes, it's going to be low headcount because it's just data centers. But like, you're talking about so many data centers. There's going to be people that are working on the air conditioning, working on the power. Going to need an air wand for sure.
Speaker 1:They're definitely going to need an air wand. And so, yeah, I I was I was talking to a real estate guy. I was like, maybe you should just go to Abilene, Texas and then just start doing deals because they're like, the construction's gonna be going on for a decade. There's gonna be a lot of people that settle there after the fact. They're gonna need an Erawan.
Speaker 1:You could sell them the property for the Erawan. They're gonna need gas stations and all sorts of different there's gonna need to be a hardware store. Right? They're gonna need hammers, all these different things. So it'll be interesting to see, if if this happens.
Speaker 1:I think it'll be a long, long journey to get to new company towns, but, I love that. We have a post from Adam Rosenblum. This is my nomination for the next TBPN AI deep dive live from the forge of fine tuning, the MCP monastery,
Speaker 2:the eye of AGI. Waits are sacred. The context is cash. The vibes are auto regressive.
Speaker 1:Tune in now.
Speaker 2:I messaged Adam. I think he's over at Cal. I said, maybe you should write for TBPN. Seriously. Open invite, Adam.
Speaker 2:You absolutely cooked and we love being live from the eye of AGI.
Speaker 1:I like it. I like it. We we yeah. We need to we need to spice up the intros, keep iterating on them. I think people enjoy the Institute of Iron, the Palace Of Pump, the Hall Of Hypertrophy.
Speaker 1:But there will be more. We're doing a Crypto Day. We'll have to come up with some new jingles for that. That'll be fun. Anyway, Google co founder, Sergey Brin, pulled up in Downtown Miami in his $450,000,000 Founder.
Speaker 1:Founder.
Speaker 2:4 hundred and 50 million dollar, 4 hundred and 60 5 foot yacht.
Speaker 1:That's less than a million dollars a foot. Yeah. At that price,
Speaker 2:it's They're giving these yachts away, be honest.
Speaker 1:I mean, it's a lot of money, but it's a
Speaker 6:lot of yachts.
Speaker 1:A of yacht. It is a lot of yacht. It's a of yacht. And you can't sell a house or a mid sized series b company.
Speaker 2:That's right. Mike Solana says, I honestly can't figure out why everyone is attacking him for this. Sorry. Yachts are awesome. Pirate wires will absolutely have one in a few years.
Speaker 2:I completely agree with People will be laughing their champagne in hand before the waving flags. When you come for us, enjoy your bike ride.
Speaker 1:One of the greatest posters of all He he
Speaker 2:cooked them, John.
Speaker 1:Generational poster for sure. Fantastic. Good friend of the show. Yeah. I love it.
Speaker 1:Beautiful beautiful yacht, and why not? I mean, Google co founder Sergey Brin has generated probably a trillion dollars of value for the economy. Right?
Speaker 2:So enjoy your little yacht. I get a I support big tech. I love big tech. Would take a
Speaker 1:bullet for big tech.
Speaker 3:I'm in
Speaker 2:theory, take a bullet for big tech.
Speaker 1:I would scale a castle wall
Speaker 2:for big tech.
Speaker 1:Yeah. I would fight in a trench war. I would dig a tunnel under a castle with a spoon
Speaker 2:for big tech. I would work years in the mines for big tech.
Speaker 1:Yes. I would fight a decades long trench war. Would be in list in the hundred year war.
Speaker 2:The hundred years war. We got our next guest. Every year.
Speaker 5:We got
Speaker 1:our next
Speaker 2:guest. To join us.
Speaker 1:Welcome to the studio. How are you doing?
Speaker 7:We are doing well.
Speaker 1:Hey. We got both of you.
Speaker 2:That's fantastic. What's happening?
Speaker 1:I'm so happy. Welcome to the
Speaker 7:tech. You can ask him about how it was.
Speaker 1:Yes. Yes. I mean, maybe that's a great way to start. We are huge fans. We were just singing Big Tech's praises, saying that we would do anything to support big technology.
Speaker 1:And yet, you left Big Tech. Why did you leave, and what are you building now?
Speaker 5:We are building physical intelligence. We want to build a model that can control any robot to do any task.
Speaker 1:Mhmm.
Speaker 5:This is something I did explore in big tech before. Mhmm. It's just much more fun to do it in a startup. Way more fun. Also a little quicker.
Speaker 5:A little quicker.
Speaker 1:A little faster paced. Yeah. I mean, need to it's
Speaker 2:been crazy. Anything's become clear in the last few weeks. We need the robots now. Yes. We can't really wait twenty years.
Speaker 2:And if Big Tech was, you know, fully responsible, we probably would have to wait something like that.
Speaker 1:Yeah. For sure. So can you walk me through the most recent announcement? I I saw the video. Fantastic.
Speaker 1:But but how would you break it down in terms of, like, what the milestone represents?
Speaker 5:Yeah. So the biggest challenge in robotics so far hasn't really been agility or dexterity, what the robots can do
Speaker 4:Yep.
Speaker 5:But then generalization. Yep. Kind of similar to what we've seen in in language before where it was really, really hard to get it to to do tasks where you just ask it to do something and and see if it can work. And what we tried to do for the past six months or so is to get to the next level of generalization for these models for robots. Mhmm.
Speaker 5:So the challenge we set for ourselves is to take a robot to a completely new home it's never seen before and ask it to do a complex long horizon task, like clean a bedroom or clean a kitchen. And there is so many details that go into cleaning a kitchen that you need to understand when you're in a new home, and you only start appreciating it when you try to do it with a robot where, you know, everything is different. Like, the countertop looks very differently. You don't know where the drawers are. You don't know how to open them.
Speaker 5:You don't know where the objects are. You don't know
Speaker 3:what's I don't
Speaker 2:even when I try to wash dishes in my house, I'm always I'm like, I can't where's this? Where's the spot? I don't know where the soap is. I don't where do I put this? So It's
Speaker 1:a mess.
Speaker 2:So now you
Speaker 1:can't even realize. Yeah. Guess. Challenge Really,
Speaker 5:really hard. And on top of, like, knowing all of those things, then you also need to connect it to motion. You actually need to get the robot to do the right thing.
Speaker 3:Mhmm.
Speaker 5:And it turns out that with with pipe o five, which we which we just released yesterday, we we can do that. And it it doesn't work all the time. It's not that I can just give it to you and it will work in your kitchen every single time, but it works quite often quite well. Mhmm. So we bring it to a new home, and it can do those things maybe, like, 50% of the time, sometimes 80% of the time.
Speaker 7:Big increase from 0%
Speaker 4:of the time.
Speaker 5:But, yeah, big increase from what we've seen before where the the previous state of the art was basically, if you want to show a robotic demo, you need to collect data in that specific environment for those specific tasks, and that's where you show it. But now we can, for the first time, bring it somewhere else, and Mhmm. That kinda works. It understands what it needs to do.
Speaker 2:Do you think that consumers will generally be more patient around reliability with robotics? Because if I you know, let's say I have some type of robot in my home and I say, hey. Do the dishes. Right? And 50% of the time it does it perfectly and like, you know, the other 50% of the time I have to kind of interject.
Speaker 2:Whereas if I'm like booking a flight and only 50% of the time it like books the flight, it's like, well, I'm just gonna do it myself. Right? Because like it's only gonna take me a minute whereas like the dishes could take twenty minutes. Right? So how how do you think about kind of the sort of threshold of reliability in order to, like, really deliver value for consumers?
Speaker 7:Yeah. I think the the like, we don't think right now about delivering value for consumers, and it's kind of why we structured the company the way we did. We're a research lab. We're trying to solve this problem of physical intelligence. We really like these consumer oriented tasks, and I think people tend to as well, like, when they think about laundry being folded for them.
Speaker 7:I think there'll be a point at which it gets good enough that we can deploy it to consumers, but it's not gonna be, like, 50%. It's gonna be closer to 98, 90 90 nine percent. And there, I think we can harp on self driving cars where there'll be a period of of interventions. Right? Like, if it doesn't work, it's not that it just will stop and do nothing for a while.
Speaker 7:We could have a human teleoperator intervene and finish the task. But I think the other cool thing about the home and consumer use case is there's so much that could also just happen overnight. There's, like, while you're sleeping, your laundry is folded. Your your your meals are cooked for, like, the you know, they're prepped for the week ahead. Your house is tidied.
Speaker 7:So consumer is still a little far away, but making a lot of progress.
Speaker 1:Can you talk about the, just the path in terms of the underlying technology to go from a Roomba? We're pulling up the video here on the stream of, what you've actually built. What were the foundational turning points in terms of the, like, the different models and different breakthroughs? I imagine the transformer was really important, but there's probably a ton of other, developments that excited you Please explain that. Now is the time.
Speaker 1:Like, we're ready to go.
Speaker 5:Yeah. There's been a lot of things that we are we are building on top of. Things like transformers, things like vision language models, the concept of pretraining and post training.
Speaker 1:Mhmm.
Speaker 5:A lot of those things transfer to the robotics world
Speaker 1:Mhmm.
Speaker 5:But they're they're not as well understood. We are still in the process of figuring out what that recipe should be like. We we kind of have to rediscover this some of the steps that that language people had to do initially and see how we can map them onto the robotics world. Mhmm. We don't have the the privilege of having an open Internet full of data.
Speaker 5:Yep. We need to collect that data ourselves, which on on one hand is is a big challenge. Like, the data isn't there. You can't e trade nearly as fast. On the other hand, it also gives you more freedom in figuring out what kind of data is the most important and what data to collect.
Speaker 5:For for this particular I o five advancement, what we had to do is, one, collect very diverse dataset, large diverse dataset that involves not only model manipulators in homes, but also static robots in the office or data of the Internet. And it turns out if you collect very diverse data across many different tasks from many different form factors, they all contribute to each other, and that they contribute to to a better understanding for the model of what actually is happening and how to utilize all of the data to figure out what to do. Mhmm. So that was a really, really big component. And then there's also a lot of architectural things, a lot of details that we need to get right to make sure that we take full advantage of that data.
Speaker 5:Interestingly, most of the data is actually not the the model manipulators in many different homes. It's a very, very small percentage of it. So it gives us also a lot of hope that we can leverage the data off from the Internet or from other platforms where it's easier to collect it to to get to that kind of generalization.
Speaker 1:Can you talk a little bit about, simulation, like, data generation through simulation? I imagine it's very easy to procedurally generate, like, a million different floor plans or a trillion different floor plans, to try and navigate those in, you know, kind of two dimensional space. But at the same time, when you get into the manipulating of a sheet, all of a sudden, that's a physics calculation. It's probably harder to simulate. There are it's not like with self driving cars, there's, you know, Grand Theft Auto you can train on.
Speaker 1:I haven't maybe there's a game where you clean up your house, but I certainly haven't played it. How effective has simulation been in generating data, and is it useful? Is that a is that a viable path here?
Speaker 5:Yeah. It's been so far really, really useful for locomotion, for robots walking around.
Speaker 1:Yep.
Speaker 5:And the reason for this is that for that kind of problem, the main difficulty is modeling your own body. Like, how do you place your foot? How do you how do you walk? And that you can do once when you, you know, you model your robot really, really well, and then it works. It works across many different terrains.
Speaker 5:You can easily, you know, randomize that and and figure out the gate that is robust. It hasn't worked nearly as well for manipulating objects or working with your hands.
Speaker 1:Mhmm.
Speaker 5:And I think the reason for that is then the difficulty isn't about, like, how do you move your hands. It's more about the world that you're manipulating. And that is much harder to simulate. You don't just do it once. Like, every object you interact with is different, and you have to model each one of those.
Speaker 5:And it's really, really hard to to figure out all the different physical parameters to make it to make it good. Mhmm. So and and this is kind of the data that is the most important, the data of of physical interactions, because this is the data that is not on the Internet. This is the data that is not even describing language. This is something that comes really natural to you.
Speaker 5:You just you just know how to do it. You don't even sometimes know how to describe it in words. So I think it's kind of like the a really bad combination where it's the hardest thing to do for SIM and is the data that we need to send the most for.
Speaker 1:Mhmm.
Speaker 5:What we discovered so far is that, basically, looking at the past successes of machine learning of of AI, it seems that the the best successes are where you you take real world data and large diversity of that data and and learn directly on that. You don't try to find some kind of proxy or some kind of simulated environment that reflects what you actually want to do. You just go after the problem head on. Mhmm. And that's what we're doing here.
Speaker 5:So we're collecting a ton of data ourselves in the real world. We can collect very diverse data this way. It's also very easy to collect it across many different scenes, many different objects. We don't need to, you know, create them in SIM. We can just buy them and bring them in and and start interacting with them.
Speaker 5:And that so far has been actually easier than we had initially thought.
Speaker 1:Yeah. I mean, you you you say you're collecting a lot of data, but I I imagine, like, there's only so many of those robots in that demo video that you can manufacture. There's only so many houses that are like, yeah. Come try your 50% robot in my house. Is is is that a key is is that scaling as you'd like?
Speaker 1:Or or or or is this more like you're going to build a physical, you know, demo like demonstration unit, like and then be manipulating it in a warehouse, or is the plan to be more like, let's roll this out and just have beta testers kind of dog food it for us?
Speaker 7:All of the above. Okay. Basically, where we find there's benefits to scale at this stage, we'll scale it. We'll figure out a way. And whether that's producing more robots, giving them to people, whether it's scaling up our our operations team and the folks that teleoperate these robots ourselves
Speaker 5:Yeah.
Speaker 7:Whether it's going out and commercially deploying these into environments where they're doing economically useful or viable viable tasks Yep. To to the training dataset collection, we'll do it. We also think there's there's so much, though, to do on just the algorithmic development that that can make the data far more useful, that can reduce the necessities of scale, but we're structured such that we can go and pursue every avenue required.
Speaker 4:That's awesome. What you
Speaker 5:guys both mentioned there is that was one of the big questions before Pio five where it kind of was unclear. You know, do we have to visit million homes? Do we have to visit, you know, hundreds of thousands? And at some point, it becomes kind of not feasible or really, really hard, and maybe we need to find a different path.
Speaker 1:Mhmm.
Speaker 5:But so far, we've been quite surprised by how few different environments you need to see to be able to generalize to a new one.
Speaker 1:It's awesome. Awesome.
Speaker 5:We actually got really reassured that this path could could really work.
Speaker 2:Would you guys like to see way more early stage, like, robotics companies? It feels like there's, you know, the the optimist, the one x. You've got, you know, figure making noise. But it feels like, you know, we we just covered this, I think, Monday, the the Chinese humanoid marathon. I'm sure you guys Yep.
Speaker 2:Followed that. They've got a lot of people working on this problem. It it it seems like there's a tendency and venture to think that, okay. There's a bunch of heavily funded players now. I shouldn't go build in that space.
Speaker 2:But at the same time, the when you look at some of these TAMs, maybe we should have 10 times the amount of, you know, early stage robotics companies getting started?
Speaker 7:It's extremely early. We work with, I'd say, probably most of the new robotics companies starting in The US and abroad. If you're starting a robotics company, reach out to us. We'd love to work with you. You can build the body.
Speaker 7:We'll build the brain. But, yeah, then we need to see a lot more robotics companies, particularly in The US.
Speaker 1:That's awesome. I wanna talk did you ever interact with the Google Arm farm?
Speaker 5:Yes. Yeah. One of one of my cofounders actually started that project.
Speaker 1:I have a feeling. Do you have your own version of an Arm Farm? Or can you describe for people that might not know, what was the genesis of the Arm Farm? What was the purpose? What was the takeaway?
Speaker 1:And is that does every robotics company need ARM farm, or is it just you? Or, and and what will that look like in the context of what you're building specifically?
Speaker 5:Yeah. So back then, that was few years ago. Mhmm. The idea was that for robots to learn to to to acquire those kind of skills, to manipulate the world around them, you can't really prescribe it. You can't just code it all up.
Speaker 5:Yeah. The world is too diverse. You can't, you know, have a lot of if statements describing what you should do in every single situation. They need to learn it the same way as as we do. Mhmm.
Speaker 5:And, the idea of the farm ArmFarm was to set up many different stations where you have static robots, static robotic arms where they just practice, and they learn from experience. So in that particular case, they were trying to learn how to grasp objects. Mhmm. So they just had a bin in front of them with lots of different objects that are very diverse, and the arm was just going down and trying to figure out how to grasp it. Mhmm.
Speaker 5:And over a long period of time and gathered enough experience to actually learn from it and get and become really, really good at grasping objects, like, remarkably remarkably good and way better than any kind of prescribed systems that people that people design by hand. And on on one hand, it was a big success because of that, because, you know, it was it was clear that this learning approach is something that can truly work and and understand the nature of grasping and truly nail that skill. On the other hand, that was also disappointing in that it took really long time. It needed a lot of data, and especially a lot of data at the beginning was kind of just like, the arm wandering around and not knowing what to do. So it seemed like a lot of that time was just kind of wasted with the arm figuring out the simplest things.
Speaker 4:Mhmm.
Speaker 5:And one thing with I o five that we are really excited about is that we are now at the stage where the robots kind of get the the sense of what they should be doing in that environment. So they are no longer in this space where, you know, you just, like, arrive in a new home and you start with just, like, moving your arms around not knowing what to do and hoping that you you do something that is useful, and then you learn from that. You start at a point where you kind of know more or less what you can do. It works some of the time. You just now need to get it to work every time and really, really well.
Speaker 1:Can you talk about the path to or the importance of end to end learning in the context of robotics? My understanding is that teleoperation is great, and as long as it's economical, we should do it. And then, having a deterministic code, like, you know, control system that's written in c plus plus, that's also great. As long as it works, It's sometimes more debuggable. But the reason that we wanna get to end to end AI systems is that then you're on the scaling law, then you're just data bound.
Speaker 1:And the more you can manufacture, the more you can produce the actual robots. You're on this flywheel and you're now bound by actual productive, you know, like getting the cars into the on the roads, getting the robots into the world, that will naturally create a flywheel. That's what everyone's hoping for in self driving. But but what does that path look like now, and how ridiculous is it to claim that end to end robotics will be here by the end of the year or something like that?
Speaker 5:So end to end robotics is already here. Everything we've we've shown so far is fully end to end where you take camera input in and few other sensors and output actions directly.
Speaker 1:Wow.
Speaker 5:I think there's another reason to do end to end learning, which is this is, I think, the only thing that has a chance of working.
Speaker 1:Yep.
Speaker 5:But, like, if if there was a way to just preprogram your robot and write a really good c plus plus code to to get it to do all kinds of different things like folding laundry, we would have done it long time ago. Totally. That's not for the lack of trying. Many people have tried it for a very, very long time.
Speaker 1:Yep.
Speaker 5:But it's just the world is too complex. Yeah. There's too many things that you will never see, you will never predict, and you can't really write that code. And, I think the only way to get there is to is for for AI to figure it out from experience. This is similar to what we've seen in language or in vision where and people have tried to write chatbots with writing different instructions and prescribing logical steps of how you should proceed, but it turned out that that the intelligence you need is much more messy.
Speaker 5:It just like, you give it a lot of text, you let it figure out all the different patterns and analogies. And there is many, many more of them than, you know, the ones that we can express in code or in language. And I think something very, very analogous is gonna happen here, and that's what we start seeing. Like, demonstrations that we that we've shown so far here at at Physical Intelligence are of tasks that were not possible before. Like, things like folding laundry, you can't really there is no program that I've ever seen that could that could do that.
Speaker 5:The same with arriving in a new home and making the bed. There's just too many variables there to do it any other way.
Speaker 1:Can you talk about, some of the experiences that you both have had in your careers? Google and Stripe, in some ways, companies that maybe move slower than a small startup. But at the same time, both of those organizations, I feel like the time from, hey. We're starting the company to we have a product that it it wasn't a research organization for years. What have you learned from those organizations?
Speaker 1:What are you taking into this experience?
Speaker 7:Greg really taught me everything I need to know about building a a robotics research lab. It's just lessons galore. I'd never worked in a research environment. I so I I don't have priors. I don't know what a research environment actually looks like.
Speaker 7:I just know what our research environment looks like.
Speaker 2:Mhmm.
Speaker 7:I feel like we whatever it looks like, maybe it operates exactly like startups. Like, maybe grad programs are exactly like startups. So we feel like every other company I've worked with that moves extremely quickly and has a clear set of goals and direction and just has a bunch of people that work behind it and work extremely hard to solve whatever it is that that we're setting our our minds towards. And and, there's so much I learned from Stripe that informed that, but a lot of it's just the the obvious stuff. Right?
Speaker 7:It's like, commit hire exceptional people, set a really high bar for it, don't compromise, set a very clear set of goals for everyone, really align people. Actually, I think that's one thing I really took from Stripe is you want an extremely aligned set of people. Mhmm. And I've never seen more alignment than I've seen at Pie. We we talk about the alignment tax.
Speaker 7:Like, when we're bringing someone on, how much work is there to align them around our mission, our way of seeing the world? And almost everyone that joins, there's, like, basically nothing. Most of the people that work here have dedicated their lives towards robotics or robotic learning or AI in some form or another, hardware, whatever it might be. And that just allows us to move so much quicker. And it's like we need to communicate a fraction of what the average company needs to communicate to someone.
Speaker 7:We don't really need to inspire people or motivate them because they're so inspired and so self motivated. I think that's probably one of the things that's worked best for us today.
Speaker 2:How have you seen your customers react to all the news and chaos around the tariffs? I think a lot of these companies are not in full commercial production yet, so it's not like, hey. We we're no longer making money. But how are they thinking kind of, like, long term just given how much of the supply chain is based in in Asia? And and are there opportunities for, you know you know, new US kind of, like, subcontractors and and manufacturing companies to sort of service this new industry?
Speaker 7:Yeah. The good thing is I mean, good and bad. It's also subscale right now. Yeah. Like, most of the money is being spent on r and d rather than scaled production.
Speaker 7:And so it's not as if, there's a hundred thousand robots that everyone's buying, and it's now just twice as expensive. I think the good thing is that given its subscale, there's a lot of time to build out US supply chains, and it's putting a lot of focus on figuring out can we get US Actuators. Can we can we start to create companies that are developing those and all the other critical supply elements of the supply chain. So it's actually just getting people into gear, and maybe it's the right time for
Speaker 1:it. Can you talk a little bit about, what you're excited about on the data center side? Is there a moment where you're, like, really pulling for Stargate to come together and we need the the the hundred gigawatt data center to crunch, you know, all of the data that you've collected in, you know, kind of a GPT five class training run? Or is that something that's, like, so far out that you'll always be able to just, you know, tag along on the residual capability from the large language model labs?
Speaker 3:Yeah. We are we are not
Speaker 5:there yet in terms of, like, having a full scaling law the way as we've seen for LLM companies where you can just translate prog compute to progress
Speaker 2:or compute
Speaker 5:to capability. We are we are searching really, really really heavily for that. We we are trying to figure out what is the recipe that would scale like this, but we are not there yet.
Speaker 7:Mhmm. We do,
Speaker 5:at the same time, generate a ton of data. I think that's one thing that that I realized since starting the company is that robots generate a ton of data, and you don't need that many to generate data that is close to the levels that LLM companies use for for their models. And there is no ceiling to it. Yeah. Right?
Speaker 5:Not that we run out of the the day the data that the robot's gonna collapse. It's not like the Internet.
Speaker 4:Yep.
Speaker 5:So I think over time, it's quite likely that that, the the places are gonna switch a little bit where most of the models, including, you know, LLMs and BLMs, are gonna be using real world data collected through robots because that's the data that has no ceiling, and it's very active as opposed to just passive observations of what people wrote on the Internet. And I think at that point, probably the the question about data centers and compute is gonna is gonna be a big one. But for our models, we are not there yet. We are not bottlenecked by you know, if only we had hundred times more compute, everything would have worked so much better.
Speaker 2:Yeah. How do you guys think about demos long term? We joked on the show recently after seeing the the Chinese humanoid marathon. Like, I wanna see humanoids doing, like, big wave surfing, cliff jumping, you know. At at what point is that, like, worth even doing or exploring just because of the amount of attention that it would bring to the industry?
Speaker 7:What do you think we should demo?
Speaker 2:I think I'd like to see one of your robots surf Jaws. I think
Speaker 1:that's that's really was saying I wanna see a robot do the 900 on a half pipe, Tony Hawk style. That was really a foundational moment in, you know, my childhood and American skateboarding culture.
Speaker 2:Like really life or death stuff.
Speaker 1:Exactly. It's gotta be high stakes.
Speaker 7:Yeah. What about with with hands? What about manipulation?
Speaker 1:Juggling for sure. Rubik's cube for sure. Juggling Rubik's cubes. You can do that. I can do the Rubik's cube.
Speaker 1:Jordy can juggle. We need to learn each other's skills so we can do both at the same But, yeah, I mean, these stunts, when they're done right, they can draw a bunch of attention. Although, you guys have plenty of attention. I don't know if that's really what's Yeah.
Speaker 2:But it's an interesting thing where it's like you have the the intention of the entire industry. But then at some point, you know Yeah. To basically inspire the next, you know, however many thousand robotics companies.
Speaker 1:I I I would love to know about obviously, with any AI project, there's always the public perception of, like, job displacement, dystopia, AI doom, etcetera. But when I look at the demo that you just posted, I'm like, that thing is gonna be fighting on my team in the singularity. Like, this is a friendly robot that will be defending me. But how do you think about the, like, tuning the language interaction, so that it it like, do do you see a world where, yes, it's doing my laundry or or making my bed, but if I happen to just also ask it, hey. Tell me about the news.
Speaker 1:I can just have a chat with it. Is that something that's even, in your mind in terms of, like, human computer interaction?
Speaker 7:It's not a big focus of ours right now, really. We're so focused on on manipulation and economically valuable tasks. And and and more so than that, the fundamental building blocks that we think gets us from here to physical intelligence. I think it's inevitable that everyone has robots in their homes, their workplaces, just, like, in their lives. And I think they'll want robots that are more useful than just doing things, whether it's companionship or, like, it's the best Amazon Alexa that can actually then go, like, cook the recipe that you ask it for.
Speaker 7:It's a place we focus around the interaction, but right now, it's more understanding the intent of clean my kitchen and then breaking that down into tasks. But Yeah. It's pretty straightforward to go from do the thing to tell me about the thing. Let's have a conversation about the thing. And so it's it's it's on the the horizon, but not the greatest priority.
Speaker 5:And then one thing there I would say is with the models we've been releasing, they're actually built on top of vision language models.
Speaker 1:Mhmm.
Speaker 4:So these
Speaker 5:are the models that are truly what they call multi model, where you can talk to it. You can ask it what they see in the image. And every now and then, you can ask it to perform actions too.
Speaker 1:That's cool.
Speaker 5:And what we what we start to realize is that all of these different data sources contribute to each other. They give you just, like, a bigger picture of what the world is like and better understanding. And it just turns out that robot actions is just, like, yet another language that these models can speak, and they just need to learn it and see enough examples of it. So the model that we have already is the model that you can talk to, and it works, you know, just as well as as open source VLMs. But on top of that, it can also have that understanding be very embodied, and it and, you know, it's it understands what it sees in front of it, and it's a much deeper understanding when it knows how to how to move its arm to actually accomplish a task.
Speaker 1:We were kinda joking before the show about the obvious comparison between, robotics and self driving cars. But can you explain to me, like, I'm a five year old or, like, a venture capitalist? Like, why is that a bad analogy? Why don't you love that that analogy?
Speaker 7:I feel like it's it's it's not that you don't love it. It's just that it, it can put you down a bunch of wrong directions. There's a lot of parallels, but, I mean, even like the Waymo Tesla thing. Right? Like, Tesla has this incredible advantage with how much data they're collecting and passively, yet Waymo is so much better so far, and it has so many fewer cars on the roads.
Speaker 7:There's useful things about it, but there's also aspects that that don't transfer in the analogy. And it, I think the the like, the reason why we were joking about it is it's the number one question.
Speaker 1:Yeah.
Speaker 7:We don't talk to many five year olds, but, like, investors and VCs ask us since we have to go down this rabbit hole where we're breaking down all of the assumptions and correcting some of them and validating some of them.
Speaker 1:I mean, is that a so so should VCs, if they're looking at the robotics market, just throw out that analogy entirely? Or should
Speaker 4:they be saying, like, there
Speaker 1:are a set of robotics companies that are in the Waymo category, and there's a set of robotics companies that are in the Tesla category, and those are reasonable, like, an an an ontology to map to?
Speaker 7:Yeah. No. It's a there's a lot of very useful stuff in the analogy. I think I I think one thing that's interesting is that there are all these self driving companies that have died, over the past fifteen years. And one thing that we actually like to remind people is that this is not coming tomorrow.
Speaker 7:You log on to Twitter, and you'll see all of these crazy robotics demos, most of them teleoperated or most of them being, like, robots doing back flips, which is a much easier problem than actually a robot folding laundry. And the thing we really try and and remind everyone that looks at investing in us or is thinking about investing in us is this is not a problem we're gonna solve tomorrow. There's fundamental research breakthroughs that that we need to make. And much like self driving had a it's what? Like, a fifteen year arc at this point, there is a very high likelihood that robotics is the same way.
Speaker 7:Like, we we think our greatest competition is science itself. It's not like this company or that company. It's just maybe we can't pull it off in our lifetimes. We think we'll be able to. It's looking more and more likely, but it's, it's not a tomorrow thing.
Speaker 1:I have one last question. I know you enjoy food and cooking. What is the final eval, the Mount Rushmore, the Mount Everest of cooking that you expect will be the last the last dish that a robot will be able to cook? What's the hardest dish for a robot to cook?
Speaker 7:The Don Angie lasagna.
Speaker 1:Oh, yeah? Yeah. Okay.
Speaker 7:So very difficult.
Speaker 1:So so when when when when they cook that, AGI achieved?
Speaker 7:It's game over.
Speaker 1:Yeah. It's game over. That's amazing. Amazing. There there was actually a recent AGI AGI benchmark.
Speaker 1:Someone shared shared a screenshot, and, it was a very old definition of AGI. It said, it'll be able to describe a sheep, tell you three things that are larger than a lobster. And all of and AGI is here by that definition. But one of the one of the things that it can't do is bake you a cake. And and we just thought it was funny that, like, that was the that was the last thing that the that the computer can't do.
Speaker 1:But maybe soon. Maybe future. But thank you so much for coming on the show.
Speaker 2:This was great. This was
Speaker 1:a fantastic conversation.
Speaker 2:Thanks for making
Speaker 1:the time guys. Best of luck to you and and and thank you so much for for building this. This really important technology. Yeah. We're excited.
Speaker 2:Put a put a robot in the studio Yeah.
Speaker 4:When you're ready.
Speaker 1:Send it over. It's a mess. I have clothes all over here that need to be folded, so we'd love to have one.
Speaker 5:Awesome. Cheers. Love demo. See Bye.
Speaker 1:Next up, we got Sam Lesson coming in the studio, venture capitalist yapping about venture capital. We will bring him in when he's ready. In the meantime, I will do some ads. We'll talk to you about Wander. Find your happy place.
Speaker 1:Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, twenty four seven concierge service. It's a vacation home, but better, folks. We can also tell you about ramp. Time is money. Save both.
Speaker 1:You heard me slip it into the Perplexity interview. I'm gonna try and slip more ads in. We've been hearing a lot of feedback that there aren't enough ads on the show. We are working hard to remedy that. But we have Sam Lesson here in the studio.
Speaker 1:Welcome to the show, Sam. How are doing?
Speaker 6:I'm doing great. How are you guys doing?
Speaker 1:We're doing fantastic. We just had a fantastic conversation with Carol Hussman and Locky Groom over at Physical Intelligence. Did you see the demo of their their cleaner robot? The the room No.
Speaker 6:I I love Locky. I haven't seen him in a bit. I know he is this the folding robot? Been folding They've folding shit in like a warehouse for a Yep.
Speaker 1:Well, they're doing the real world now. The demo was they they they sent the robot out into the field. It cleans someone's house. They say it's about 50% accurate. They're getting ready to deploy it once it gets to 99%
Speaker 6:accurate. What does a 50% accurate cleaning robot do? Like, 0% the time
Speaker 1:Yeah. It it can fold half of your shirts proper properly and half of your shirts improperly.
Speaker 6:Look, in fairness, that's probably better than I could do. I'm not much of a folder myself.
Speaker 1:I'm terrible at it. I'm terrible at it. So, you know Yeah.
Speaker 2:I would be terrible laundry robot, personally. Yes. Great to see you, Sam.
Speaker 6:Always fun. You guys are crushing it. I'm loving the vibe. You have a you're both full time now. Like, you've ads.
Speaker 1:Yeah. Ads. Yeah. We We can
Speaker 2:just never never side hustle. Yeah. That's our never side hustle. Always full hustle. Yeah.
Speaker 2:What's what's going on in your world?
Speaker 6:You know, I don't know.
Speaker 7:I've been traveling a bunch, but
Speaker 6:I'm I'm back and Traveling is a venture capitalist?
Speaker 1:How does that work?
Speaker 6:Oh, just for fun.
Speaker 1:Guys, not
Speaker 6:for work. Please.
Speaker 1:Yeah.
Speaker 6:No. I just But I would imagine
Speaker 1:that such a prestigious career path is so demanding that you would never be able to take a day off.
Speaker 6:Never. No. I Interesting. I I am a slave to Zoom. I just sit
Speaker 1:here and
Speaker 6:and Zoom back
Speaker 1:to You seem have cracked the code.
Speaker 2:What's your stance on Zoom? Do you invest much purely over Zoom or are you just meeting everybody at this point?
Speaker 6:You know, it's a really interesting question. I personally think Zoom Zoom's had like a really interesting impact, I think, on venture capital. Because initially people were all bold up on how Zoom and was like no meetings in person was gonna open the funnel. And people would like invest all over the country and we break down walls because all of a sudden physicality like there was like this kind of euphoric Zoom will be democratizing type thing going on. And I it's interesting.
Speaker 6:I do think that Zoom means that people like me and venture capitalists are willing to take more meetings than we otherwise would be on, like, interesting topics with people that like, again, like, it's just, like, the barrier is lower. You'll meet with more people. Now does that actually result in more investments? Unclear. I I think it might invest in, like, broader sets of first meetings just because the barrier's lower.
Speaker 6:And, like, if the meeting gets boring after fifteen minutes, I can just do my email and say, uh-huh. Right? So, like, it's like there is some breakdown in, like, access, but it's not clear to me how much that resolves to, like, actually broader access means. And in fact, I think that's one of the big things that's interesting about AI broadly right now is, you know, there's this narrative like with auto scripting, I get the number of pitches I get that are like half written by AI or written by AI is like out of control, right? I don't know what people think they're doing with those because they're all just gonna get deleted, right?
Speaker 6:And if anything, the irony is the fact that the barrier now is so low to those emails means that even the ones that actually are legitimate just get archived because like on the margin they're probably spam. And so there's this interesting thing where AI is actually leading making venture capital, I would argue, more insular, right, than it was before, not less insular. Right? So there's all these, like, unintended consequences going on of Zoom, of AI, of all this type of stuff in VC.
Speaker 1:Yeah. Email, you just gotta use it like text messaging. Just no subject, no body at all, just whatever you have to say, just put it in the subject and send.
Speaker 6:Look, I I actually am a huge I'm like probably I'm old. I'm like 41, right? So I'm like a huge I love email. I think it's great. And I'm an inbox zero guy.
Speaker 6:I'm like Okay. But I also like run aggressive filters on my email. Sure. And like am fine not responding. Like I don't consider email a contract that because you sent me something, I'm required to send you something back.
Speaker 6:I think
Speaker 7:you just have to treat it differently.
Speaker 2:What about on text? Are you an inbox zero on text?
Speaker 6:Text, take pretty seriously, actually. So that is like, I I kinda have a pretty quick SLA on text and I that, I use an OpenPhone phone number for a lot of things where you wanna put it up on screen. It's great. It's like a second text inbox. That's not really the purpose of a company.
Speaker 6:It's more sophisticated than that, but I I like it for that.
Speaker 1:That's great. We should
Speaker 2:we should set open Yeah. Yeah. Yeah. Yeah.
Speaker 1:We should. Yeah. We would
Speaker 2:have Yeah. For me, I I like to think of the hierarchy of, like, you know, inboxes. Right? Email. But then now it's like, okay, you have xDMs, iMessage, WhatsApp, Signal.
Speaker 1:If wanna get in touch with me, show up and grab me by the collar.
Speaker 2:Yeah. Shake me like
Speaker 6:a joke. Until I
Speaker 1:hear what you have to say. That's
Speaker 2:only option.
Speaker 6:I I I so I have, like my stack is text is incredibly important and serious. That's like a one hour SLA Mhmm. But it's limited.
Speaker 1:Yeah.
Speaker 6:Email, I take very seriously. Like, I really care about email. But then people are like, you should be in my Discord server or, like, Slack. I'm like, abso fucking lutely not. Like, I think those things are disasters.
Speaker 6:I refuse to engage with them. I hate everything about them. Despite the fact Slow was one of the seed investors in in Slack. And so I have to thank Stuart for making us some money. But like, I just like can't deal.
Speaker 6:Yeah. I refuse to deal.
Speaker 2:Yeah. Let's let's Yeah.
Speaker 1:Take us through that.
Speaker 2:Should we talk about venture capital? I actually wanna start and go back to your 2023 piece Sure. Which is on the timeline. You called out this is 10/16/2023. The shutdown of the VC factory line and the death of the factory farm unicorn narrative.
Speaker 2:Mhmm. The awkward crowd into seed investing by multi stage firms. Mhmm. The mirage of AI and LLM startup investing. The post pandemic fundamental cultural change impacting startups.
Speaker 2:What which one those Yourself. Yeah. How would you how would you grade
Speaker 6:your I obviously grade myself excellently at all. The the no. I mean, think, like, look, I try to pull up every few years and especially in times of uncertainty, it's like, what is going on? Like, where should we be spending time and attention? I think, you know, two years ago, you know, those were the big themes for me, is, one, we were very used to, for ten years as a fund, effectively operating on this factory line.
Speaker 6:We take in companies at a certain stage, we know what metrics they have to hit, we give them the money, we then package them and send them on to our friends at Series A, who then send them on to B and da da da da. And the whole thing works beautifully because at the end we pop them out into the public markets and retail investors buy them and life is good. And I was just saying, like, after the pandemic, you know, people wanted that to come back. And I was like, this is not coming back. Like, this whole the market is it's a mixed up market.
Speaker 6:You know, we've basically produced a bunch of these things which are on paper unicorns. But, like, they're not fundamentally important businesses. And more importantly, there's been this huge release, which is the biggest platforms in the world can just keep getting bigger. Like, remember a time when, like, a hundred billion dollar company was a huge company. Right?
Speaker 6:People thought there was a limit to how big the biggest could get. And so there was this constant hunger in the public market for what's the next $3,000,000,000 company that's gonna grow really fast. And there was coverage for that. People cared about it. And now the obvious answer is just like put more money into Amazon, put more money into Meta.
Speaker 6:Like, there is no upper bound. And so I just think the markets have shifted, demand from consumers have shifted, the public has kind of rippled back to the ecosystem. You know, what we have now, and, you know, I have this in the 2025 version, is what I'm calling zombiecorns. Right? So there's all you know, people thought people friends of mine were like, oh, we're gonna see this mass extinction of these unicorns.
Speaker 6:They're all gonna die because, you know, they're gonna run out of money, no one's gonna fund them, the liquidation preferences are huge, they can't go public. They actually mostly didn't die, right? What they did do is they basically sacrificed growth, they cut their burn a lot, they kind of got marginally profitable, they can kind of exist. And they're kind of zombies. They're just they're out there, they're not going anywhere, but they're also not going public.
Speaker 6:There's no market for them. No one knows how to buy them. The liquidation preferences are set up so that no one wants to deal with them, and they're just gonna kind of exist.
Speaker 2:So the the factory line is broken at the late stage because there's no off ramp, But in many ways in many ways, this sort of early stage pre seed to seed to series a is still accelerating as though there's an off ramp.
Speaker 6:I don't think I don't think it is, actually. I think this is, like, one of the I think the part of the 2025 deck or trying to think about what's going on. I actually think what we now have, weirdly, is effectively several markets for companies that are pretty decoupled from each other and kind of have their own logic and exist in their own vacuum. So, like, there is a public market. Like, the public market exists.
Speaker 6:It's the biggest. Right? There is a private market now. There are companies that are private and will, like, probably never go public or never for various reasons. The way that companies are valued by the late stage private and the public are actually just different.
Speaker 6:Like, what's valued is different, how people think about them is different. Large LPs actually invest in both, so they don't care. They're like but there's basically, like, running two parallel universes that don't have a lot of operability. Now at the early stage, I actually think the same thing is going on, right? Which is like there is a kind of seed to pre seed esque market that exists.
Speaker 6:And people compete and people get excited and there's kind of a market clearing price for startups and invest sure. But then when you say, well, what do you what does it take to hop from an early stage, call it like precede seed, maybe sneaking into A, to like a legitimate B and Beyond growth round, there's no more like magic numbers you hit and like a valuation framework that's consistent. It's actually much more about belief. You know, I say in the deck it's a lot about this kind of new math of people want downside protection and then an option on infinity. And so like what's the average of infinity and zero?
Speaker 6:It's infinity. Right? And so the way people are backing into valuate is so the entire factory is predicated on $1,000,000 in ARR equals series A at price blah blah with 30, you know, 30% growth and $10,000,000 in ARR. Like, triple triple double double, you can come up all these frameworks. Yeah.
Speaker 6:Everyone kind of agreed on shit, and there was just, like, market clearing action and prices. And now I actually think there's just, like, distinct markets of belief that are really hard to move between.
Speaker 1:Yeah. Does this necessitate, like, a different model around growth? We kind of saw this with, like, the crossover investors like Tiger, but a lot of growth funds have this downside protection mandate, no zeros. But let's underwrite to a three x. Yep.
Speaker 1:And and, yes, I mean, I hear the I hear your infinity thing that does happen every once in a while, but I think in general, a lot of growth investors are saying, no zeros, and let's triple our money, over this deal. But should you have more later stage growth investors that are thinking more like portfolio construction at the seed stage?
Speaker 6:I I look. I think that the answer to that basically is I don't even know when they talk about we're underwriting to a three x
Speaker 1:Yeah.
Speaker 6:Who's buying? Right? Like, everything is about the marginal buyer. Right? There is no value on anything.
Speaker 6:Right? It's all about
Speaker 1:losing like a DCF. I mean, you you could you could justify the cash flows. Right? You could comp to the public market.
Speaker 6:The prop the prob but the problem with the first of all, comping to the basically nothing at late stage is trading comp to the public market, really. Right? And we can get we can get into, like, why and I think I think that look, the DCF comp to the public market
Speaker 1:Mhmm.
Speaker 6:That way that is the factory model. Right? It's basically saying like, hey, I have a late stage thing. I put money in. Yep.
Speaker 6:It's gonna triple. The DCF looks like this. It's has this much profit margin. Like, this is the story. Package, sell to the public market.
Speaker 6:The public market buys on that same story. Like, that that was the mentality that persisted for a long time, and it was a great system for a lot of for money making for a lot of people. Right? I actually think that, again, the public market now is like, well, if I kinda just want those types of metrics, why don't I just buy more of the Mag seven? Like, I don't I don't even wanna dick around with your subscale offering.
Speaker 6:Like, I don't care. Right? Like, I think and there's reasons for that. It's because the big LPs are bigger. It's because of meme stocks.
Speaker 6:There's a whole bunch of stuff going on there, right, that kind of makes that happen. But the net outcome is there is no off ramp. So then the question is, when you're underwriting at a late stage, you're not you also have to underwrite to someone buying from you, right? And like, the question is, what are they buying and why are they buying it, right? And I think this is where it gets a little bit squirrely, because I do think, you know, I'm not the only one saying this, but like, private to private transactions are gonna happen way more, right?
Speaker 6:Like, you're gonna look -Yeah, it's in private equity. -Yeah. -Like, funds will sell to funds. Then the question is, well, what is the buying fund paying, right? They're gonna pay They need some margin.
Speaker 6:They need to have a framework in their heads about how they're gonna sell, right? So then they're going to you're going to be pay you as an early stage fund are no longer underwriting to some late stage, to some DCF, to the public market. You're really underwriting to who's going to buy from you. What's their narrative on buying? Like why do they want to hold this, Right?
Speaker 6:Like what's their time horizon? What's their purpose? And like the irony of the whole thing is like honestly those prices are gonna probably be much lower than what the DCF might otherwise imply. Right?
Speaker 2:How do you think about how do you think about funds, you know, selling an entire fund? And I'm talking about venture funds, maybe selling to other, you know, kind of like, not continuation vehicles, but just other secondary buyers versus trying to sell off and kind of like prune the portfolio and say like
Speaker 6:Well, in the end of the day, look, I I think it look, the funds signed to funds, you're just gonna take some massive discounts on that shit. Right? Because at the end of the day, like if someone's buying a fund from you, they're really only buying the winners and the rest is bullshit. Right? They're and like, so in an ideal world, just carve out the pieces they want.
Speaker 6:Like, I want this position and this position and this position because I care about these companies, or I have an infinity thesis on them. Like, everyone has to have I actually think the infinity thesis really matters in terms of how people are thinking about how big things can get and whether they matter or not in the world. And then everything else, it's like, it's basically worth zero. Right? You know, we were joking at our firm about like, we were joking about sharding right off co.
Speaker 6:Right? Because that's the other funny thing that happens, right? Is you just kind of give up on positions and you sell them for a dollar to take the tax advantage, right, on it. Every once in a while, the hilarious part is you sell something for a dollar because you give up on it and it turns out being worth something. Right?
Speaker 6:So like there's a whole business
Speaker 1:We love a comeback story.
Speaker 6:Hoovering up irrelevant positions. But I don't know. Like does it happen? Yes. Do GPs sell piece to the GP?
Speaker 6:Yes. But that's complicated because the reality is at least the public market only really values the fees, right? Which means, like, so it's basically I've been having trouble because I wrote this 2023 thing that I was pretty proud of and I think was honestly pretty accurate about what was going on. Understandably, it's been two years. I wanted to update it and be like, well, where are we now?
Speaker 6:And like, there are things I think I got mostly right. There are things that I think are wrong. But I think the the real story is end of factory model, the factory's over.
Speaker 1:-Mm
Speaker 6:What the the the yada yada yada is we're now, I think, entering this period where, like, you don't even think about it as one integrated capital system. They're just, like, different parallel universes. Like, everything in the world is regionalizing and fractionalizing. This is happening with globalization. We're having a deglobalization moment.
Speaker 6:This is happening with all sorts of things. I think it's happening with capital, too. There are just literally distinct ecosystems, and people play in multiple of them, right? But they have their own valuation logic, etcetera. And then I think, like, the way people value companies as a result has changed.
Speaker 6:What you should be looking for has changed. The types of CEOs you wanna back has changed. It's just a new world.
Speaker 2:Did you dabble much internationally? This was a very 2021, '20 '20 '2 thing with funds thinking that you know, they'd they'd win a deal in, like, you know, like, 10,000 miles away. And and then, like, in hindsight, it's like, you have to think, like, why did you win this deal? Why didn't you know, why are you, you know, so lucky to have the opportunity to back this company, and then a lot of them just, you know, are derivative and and
Speaker 6:The only yeah. The only we've invested in Israel when it made sense. I think the The US Israel relationship is strong. I think there's a lot of good technology. There's a lot of reasons that make sense.
Speaker 6:And so that's always been a thing we've done. We know it well enough to like be confident investing there. I, again, I think that's the thing for us historically is yes, in a Zoom world you'll take the meeting in Europe, right? Because like, it's interesting and like, you know, no one's accounting for your time as a venture capitalist. So if you're interested in something in Europe and they really want to talk, like, sure, you'll do it.
Speaker 6:But we're so lazy, right, that like, I don't want to deal with like, there's always an exception. Like, we have done a handful of deals that are kind of outside the wheelhouse. But it's of of looking at but I kind of believe that there's really something to, you know, be New York, be San Francisco focused, pick a few geos, understand them, understand how they fit into the global capital world, etcetera. So no, we didn't get drawn in too much here.
Speaker 1:What is what what is your interpretation of the rumor around OpenAI potentially buying Windsurf for 3,000,000,000? It's the it's not an AI cherry on top business. It's a rapper. Is it bull market for rappers now? Are we gonna see tons more acquisitions?
Speaker 1:Yeah.
Speaker 2:Slow is gonna FOMO into a bunch of rappers business.
Speaker 1:FOMO into every rapper because they're just gonna get hoopered up. I mean, my my take was maybe, you know, OpenAI buys one, then Anthropic needs one, then Amazon needs one, then Google needs one, and all of a sudden you have, like, seven unicorns getting bought. Everyone's making money. Everyone's generationally wealthy. That's the good ending.
Speaker 1:Right?
Speaker 6:I don't look, I really am pretty cynicaldon't think that we're going to see a lot of acquihire AI type stuff in this era. I think there's a few reasons to that. One is like, what are you really buying, right, in some of these things? Like you could are you buying talent? That is not unreasonable.
Speaker 6:But, you know, and we've seen that. We've seen people like effectively quote unquote buy companies that are literally just for like the one person they want to pay $200,000,000 to because they really think they're special because they need an Look, some people are gonna get massively overcompeted. That will happen. I don't think it's an investment thesis. It is what it is.
Speaker 6:And I think it won't happen that much, but we'll see. I think there's gonna be, are you buying technology? It's like the thing about AI and a lot of where we're going is like, why? Right? Like, software's getting commoditized.
Speaker 6:Like, what is it? Like, if you're buying technology, you gotta be buying some really important technology. Right? And I think that's like an, the third thing you in theory can buy is just distribution, right? Which is like if someone really has, know, for whatever reason got their hooks into a few key contracts or like, you know, they have a tailwind, like fine, you buy distribution and that can be worth something.
Speaker 6:But look, honestly, it just seems like all very squirrelly to me at this moment. You know, the thing I'd say in venture capital is there will be random walks. Some random stuff will happen. Right? And like I think you can't get too, you know, twisted around that.
Speaker 6:You certainly shouldn't be chasing random walk. But no, don't I don't personally see it. And if anything I'd say like, was part of this. You know, my first company was acquired by Facebook in the era of acqui hires, And I think there, and I say this with some humility but also perspective, is like I think when you go back and look at like what was really bought there and was that a good use of capital by most of the aqua hiring companies, I think the answer is probably not. You know, like that era is kind of over, people aren't that special.
Speaker 6:You know, the big companies, just because they have such incredible access to capital and distribution at this point, they can kind of just build whatever they need anyway, right? So anything that does happen will be highly bespoke as opposed to like some industry wide trend is my personal view.
Speaker 2:Mhmm. How do you think right now about the dynamic between 30 to $50,000,000 early stage funds versus you know 30 plus billion dollar AUM funds? In in some ways they the the the the tiny, you know, upstart funds benefit from these big platform funds coming in and sort of marking up deals. Right? The returns look good, but And
Speaker 6:it may be. I just think they're completely like they're two completely different business models. Right? Like, I think it's the thing this goes back to my poll about, like, rationalization and fragmentation of what capital even is. Right?
Speaker 6:If you're running a $50,000,000,000 venture fund, you can't possibly be deploying that well early. Right? And actually, you're paid to move gross dollars. The problem you're solving for LPs is you have some massive fucking LPs. So like, I want exposure to private markets.
Speaker 6:It's really hard for me to go find how to do that. I would love you to deploy as much capital as possible. And like effectively the way you get paid is on fees. You're not getting paid on carry. Like this, you know, if you have a $50,000,000,000 fund, making 3x on that so you're making money on carry is like extremely difficult to impossible.
Speaker 6:Like the numbers just don't add up. You're getting paid to deploy. And that means your business model is attracting more capital. You have to return enough to justify it, right? But like you're not actually shooting for maximum DPI or actual returns.
Speaker 6:You're just shooting for And by the way
Speaker 2:But doesn't the big doesn't the big you know, I just see this all the time where I have friends with funds that that are maybe sub $50,000,000 funds and they're investing into like, even if the big platform's just periodically dipping down into seed when when they have a real you know, really like the founder or whatever. And then suddenly the round is like, you know, six on 40. And then Yeah. And that's just the and then the tiny fund is like, you could get a bunch of bangers and you just do the math and you realize like Mhmm. They're not making they're not gonna be making DPI either, and they're not gonna be doing the The
Speaker 6:late stage what happened after 20 in 2023 era, which I I wrote about then, is, like, the late stage capital allocators who, again, are paid fees to deploy gross, They're like they're weight deployers. They're mass capital deployers. They got they couldn't deploy. So a bunch of their junior people in particular are like, well, I need to do something to justify my paycheck. So they started dipping into seed, right?
Speaker 6:Because, like, they're bored, right? And they're like, we can't deploy big checks, we might as well deploy small ones. And by the way, no one cares, right? Like it's such small amounts of money, it's irrelevant either way. That completely messed up the seed markets because it got super undisciplined, right?
Speaker 6:And like it did because it's candidly, we do the same thing at slow to like the angel market. Right? Whereas we we are it's a recursive problem. Like we will write hundred thousand dollar checks off a meeting because it's kind of irrelevant to us and it's just relationship building and like whatever. But there's some poor angel who's out there trying to price it properly, and we don't care, and then we fuck it up for them.
Speaker 6:So, like, it's it's a recursive problem. That did happen. I think mostly, honestly, the late stage guys with AI have a narrative where they can put billions of dollars to work and do their actual jobs. So they've mostly pulled out of fucking up the early stage markets because they have better things to do with their time that's actually what they get paid for, right? And just to make a finer point on that, you know, lot of these late stage public platforms, they really are like setting themselves up to go public.
Speaker 6:Here's the thing about that. When they go public, the actual way REITs, like the public markets value these funds has absolutely nothing to do with returns. It is 100% the fee base, right? And so their structure and their incentive structure is 1000% about earning fees and just making enough returns to justify the fees they charge and raise more money. Like, that's what they do.
Speaker 6:Then there's the early stage market. Here's the thing about those $50,000,000 funds, right? Ultimately, you got to eat. You got to actually deliver DPI, not just marks. Right?
Speaker 6:And so marks are nice. Like, they're fine. But I think what we're going find in a lot of ways is the gulf between I have on paper made a bunch of money or these deals look good versus like, oh no, I actually returned capital. I like made you money. You should give me more money, and I made myself money doing it.
Speaker 6:That's a pretty big gulf. And I think what we're gonna find is that, you know, a, the market most of those funds are going away because they don't have that and they're not going to. B, there could be a world where late stage funds start saying, okay, at some discount to the last round I'll buy out these seed funds effectively and give them some DPI, etcetera. But then the problem for the seed funds is that mark they were using to be like, look how smart I am, that's not what they're getting paid. Right?
Speaker 6:That's like, that's like the high watermark some investor invested later for primary. And when you come around and say, hey, by the way, would you like to buy my shares? I I and they're like, well, we'll take more, it'll lower our average cost base.
Speaker 2:Mhmm.
Speaker 6:They're not paying what they what they paid for the primary. Right?
Speaker 2:They're looking at their portfolio and they're like, I need to do this for 80% of my bets, basically, in order to like actually Yeah. And then it's like, you know Yeah. That's right.
Speaker 6:Yeah. And so look, mean, the the upshot, the really simple way to think about it is like, you're an early stage investor, you have to make money. Like, that is actually what you are paid for and you're people are saying, hey, I'm gonna allocate a small amount of money to you. By the way, it's not efficient, right? Because if you're even a medium sized LP, someone's running a $50,000,000 fund, what are you gonna give them?
Speaker 6:Like, a few million bucks? You don't care unless they make you a shit ton of money. Right? And so, like, if you make them a shit ton of money, you're doing your job, you get to keep playing. If you don't, forget it.
Speaker 6:And that's just in a completely different game than what it means to be a late stage capital allocator in the private markets.
Speaker 1:Yeah. I have a kind of a random topic, but there's there's two early stage kind of publicity stunts going on this week. One is by Roy Lee. He launched Cluey Clue Lee, Cheat on Everything. I'm not sure if you saw this, but he
Speaker 7:was very I
Speaker 1:did see this. Very controversial. And he's kind of like a troll, almost like a Nathan Fielder type, really kicking the bear. And then there's also this, artisan, company announcing their $25,000,000 series a with a billboard on the wall.
Speaker 6:But I love billboards, as you know.
Speaker 1:Yeah. We love billboards We're sponsored by Adquick. We love billboards. But, you know, the the the positive take on this is that, hey. Like, they're breaking through.
Speaker 1:They're getting attention. Attention's valuable. Distribution's important. The counter to that is, should they even need to do that? Shouldn't they just be heads down building?
Speaker 1:Where do you sit on that continuum?
Speaker 6:I I guess the question I would ask is, what percent what is the track record of companies
Speaker 2:I'll give you
Speaker 4:an example.
Speaker 2:So the challenge with going super viral early, and I had this with Party Round, is that people get a fixed idea a lot of people get a very fixed idea of what your business does
Speaker 1:Yep.
Speaker 2:And then you run into this, like, product marketing challenge which, you know, people are aware of your business, but they're aware of it for something that you may not even do anymore. And that's why I was talking with Cluely Yep. Founder yesterday of like, you need to be committed to like iterating and basically burning the whole brand down because you might find in two months that
Speaker 1:You're completely different.
Speaker 2:The real opportunity is something else.
Speaker 6:Yeah. I think that's a really good point. And like, I I'll I'll do it a step further, which is I In my experience, really successful things, you actually want fairly high barriers to entry so that the people who show up as your early customers are like deeply in need of it and true believers. Right? Because if they're deeply in need of it, they're gonna put up with a lot of crap to get what it is you're offering out of it because they're deep because they really care.
Speaker 6:Like, they showed up first, and they, like, have a real stake in it. And then they become true believers in that cult that advocates. I think if you have too much attention too quickly from distracted, you have to deal with a bunch of the wrong stuff, people are flighty. Like and so I think there's this irony, which is, like, it all how you get your first one hundred thousand, ten thousand people and the barriers to entry there are like And I'll give you a kind of counter example, which actually kind of is a marketing stunt if you get into it, which is quite by accident. You know, Ikram and I kind of started this jelly jelly Mhmm.
Speaker 6:Meme coin, which blew way the hell up and went crazy, but was supposed to be like a component of this app, Jelly Jelly, we've been working on. Mhmm. The app's super cool, but like, the app was not ready. Yeah. Right?
Speaker 6:Like, when and what's been really interesting to watch is, because the app wasn't ready, you got a bunch of people in, most of them balanced, they're like, this isn't ready, this is weird, whatever. But you did attract a kernel of, like, crazy true believers that are really engaged with it, and then it's kind of like a fire. Like, you kind of blow on the coals of that, right, and you kind of keep iterating and working. So I guess that's a long winded way of saying, I think the history of companies that start with a marketing stunt and blow up big is pretty poor. There probably is a way to like, be very inefficient and like blow up something big or say something, funnel out 99% of the noise Yep.
Speaker 6:Somehow find that kernel 1% Yep. Work with that 1%, and like treat it like kind of the embers of a fire, right, and grow up. That's kind of the the mental model.
Speaker 1:It's like how you handle it. Got it. Yeah.
Speaker 2:Last question. How cooked is Tesla?
Speaker 6:I mean, look. I I I've been in the camp of like Tesla's a meme stock for a long time. Right? And I think Tesla's a meme stock. Right?
Speaker 6:You know? And so I
Speaker 2:Yeah. You posted, maybe it was yesterday. No. It was this morning. If Elon can move Tesla stock up by seven and a half percent by saying he's stepping back from Doge against the backdrop of profits and revenue they just reported, then yes, he probably deserves the $56,000,000,000 difference as a pay package.
Speaker 2:That is what the market says his attention is worth. I thought that was pretty on the nose.
Speaker 6:Yeah. Look, it's it's it's Elon is the greatest marketer of our generation. He's the greatest capital raiser of our generation. You know, he is the greatest, I think, storyteller. I mean, there's a lot that he's really, really, really good at.
Speaker 6:Right? And, you know, I think he's the ultimate cult influencer in a lot of ways, right? And he's built a lot of cool companies doing that, but it is so belief driven. And I think this is kind of the thing where it's like, you know, what does Tesla work from perspective? We talked about public markets and how you value these things.
Speaker 6:Not a fraction of what it's traded at, right? But it is absolutely he is great at the Infinity story, right? The Infinity story is so big, and Infinity plus zero equals big number. Everything's about the marginal buyer, and it's incredibly loved because retail investors want something to believe in. Like, they want something that can that can go to infinity.
Speaker 6:Same thing with the Mars thing. It's like look, again, I find the whole Mars thing in SpaceX so frustrating. I love SpaceX. It's like, you know, I think it's an amazing company. Like, what they do is incredible, right?
Speaker 6:And there's a lot I love in the whole nine yards. The Mars narrative is so frustrating because it's so disingenuous on one hand, right? Like, it's just like the predictions are out of control. Like, it doesn't make any sense from, like, a fundamentals perspective. But my god, people need something to believe in.
Speaker 6:Right? And so
Speaker 1:That's a good point.
Speaker 2:Believe in something.
Speaker 1:Well, I think Tesla's coming back. I think they're gonna put a naturally aspirated v 12 with a gated manual in a new car. They're gonna sell 700,000,000 cars in a single quarter.
Speaker 6:I would fucking love that. If Tesla did that, I would be even I would buy Tesla stock just because that would be
Speaker 1:awesome. We cracked it. We cracked it. It's gonna happen. You heard it here first.
Speaker 1:Thanks for stopping by, Sam. This is fantastic. You, Sam.
Speaker 6:Were gonna
Speaker 5:talk to
Speaker 2:you on.
Speaker 6:Gotcha. Next
Speaker 1:up, we have Bridget Medler of Northwood Space coming into the studio. Very exciting. I believe $30,000,000 series a from Andreessen Horowitz in partnership. I think Founders Fund and a bunch of other folks got in the round, so we'll talk to her about that. Bridget, welcome to the show.
Speaker 1:How are you doing?
Speaker 2:Hey. Hey.
Speaker 8:What's going on? What's up? I haven't been on podcast before, so am am I on? It is
Speaker 1:You're you're on you're not only on a podcast, but you're also live. Woah. There's no there's post, post editing, but hopefully we got the facts right, but you can break it down for us. Tell us, what does, Northwood Space do, and tell us about the $30,000,000 funding round that just was announced.
Speaker 8:Yeah. We're we're building the ground network for the industrialized space economy. Mhmm. You know, we view it kind of as the third critical pillar of infrastructure for space where
Speaker 3:you need
Speaker 8:to get things into space on rockets. You need to have things to put into space, which are satellites, and then you need a way to actually communicate with them and use them once they're up and operational. And so we're focused on that last third part and building the the shared infrastructure that the whole industry can take advantage of, really drawing parallels to the cellular industry and to the Internet where shared infrastructure is just a big enabler for being able to push technology forward.
Speaker 2:Yeah. Talk about what companies have had to do historically.
Speaker 1:Absolutely.
Speaker 2:You know, we've heard a lot about satellite companies that send a satellite up and they're like, it's working, but we don't know where it is. You know, so it's like a kid Yeah. You know, kind of critical aspect of, you know you know, maintaining Yeah.
Speaker 1:What was the status quo prior to you starting the company?
Speaker 8:Oh, yeah. Yeah. I mean, it's not just prior to us starting the company. It's, like, ongoing. You know, we talked to companies, I think, like, last week that are just not getting enough coverage, and so they're endeavoring to build their own ground stations themselves.
Speaker 8:And, you know, our our cofounder, Shar, it was actually interesting. During our first fundraise, he was still working at his old company, and he was woken up two times in the middle of the night. There were a total of four ground failures just in the course of one evening while he was manning their operations at all different locations, all different ground networks. One was a site that had already been down and just, like, not even notified the company that they weren't gonna be able to make their contact. Talked to another company last week that had been out of con contact with their satellite for twenty eight hours.
Speaker 8:It's like, you know, you're not just tossing, a $50 piece of equipment up there. It's, like Yep. Tens or hundreds of millions of dollars. So it's very stressful, and we're we're excited to, you know, pursue setting a new standard there.
Speaker 2:Yeah. People get stressed out when Slack's down for like five minutes. And imagine having like, you know, this hundred million dollar billion dollar device that you don't have contact with. What what is I'm curious. What does scale look like for Northwood?
Speaker 2:You know, how many different, you know, ground stations, you know, do you hope to kind of get to within the next, call it, decade?
Speaker 8:Oh, decade. That's a long horizon, but that's fun. We are looking at scale both from, like, a network level and a site level. So when you think about, like, why do you need to have a global network to begin with with space? Like, the reason why you need to have a global network is because satellites orbit the Earth.
Speaker 8:And so maintaining contact with them, requires having, you know, locations all over the earth to make sure that you can be in contact all the time. So think of it kinda like when you're using a cell phone and you're driving on the freeway and you're passing different cell towers. You need to have maintain contact with cell towers in order to maintain connection, same with space. And so for us, there's, like, two verticals. One is coverage.
Speaker 8:So you wanna have enough coverage. So, basically, like a cell tower, you're, like, you're always in contact no matter where you are. And then the the other one is throughput. That's, like, density. And so kind of gold standard for this is SpaceX, where they have hundreds of ground stations to, not just have global coverage, but to be able to serve millions of users in different regions.
Speaker 8:So when they're wanting to, like, service a region that has a lot of customers, they need to put a lot of ground stations in that region in order to support that much capacity. And so we wanna be able to offer that to other folks so that they can have, like, that kind of gold standard of, connectivity through space. So, we're gonna be putting, you know, ground stations in different regions as well as ground stations densifying in the same regions. And one of the things that we think about with scale is really, like, how can we put as many ground stations to support as much capacity as possible at a single region. So our kind of, you know, sub near term goal goal is 500 sites.
Speaker 4:You take me through some of the Yeah.
Speaker 1:Can you take me through some of the history of these ground stations? Maybe explain it in really, really simple terms, like, maybe, like, I'm a venture capitalist or something. Yeah. Something like, how do we communicate with the Hubble Telescope? Is this like a big satellite dish like what I saw in Contact with Jodi Foster?
Speaker 1:Is that how we communicate with the Hubble, or is there a different network of ground stations? What what what was kind of the gold standard ten, twenty years ago?
Speaker 8:Yeah. I have to just say, like, us ground nerds in space, we do not often get asked these questions. Thank you very much. Like, the ground is just generally, like, the not sexy part of space. Good.
Speaker 8:Sounds very fun. So yeah. I mean, what you're doing is, you know, generally using RF to contact a satellite that is, like, hundreds of kilometers away. Mhmm. You need to concentrate enough power to be able to do that.
Speaker 8:So that's why you see, like, the big parabolic dishes. It's concentrating power. Got it. And so when you're, you know, further away, that requires more tower more power. So, actually, if you're, you know, in the Palo Alto area, you go by the, the Stanford dish is kind of a well known one.
Speaker 8:I imagine, like, some folks, if they're watching might know of that. It's massive. It's a a giant dish that's used to make that contact. And so it's interesting because, like, the legacy of space, it's more exploratory. It's more research based, where, like, booking an antenna was kinda more like booking a telescope, you know, where it's like a an individual piece of equipment where, you know, they're located at these different locations around the world.
Speaker 8:You book the time. You're kind of in control of how that functions and how it operates. But as the space industry has been scaling, that's not really a sustainable model to think of, like, as you're needing to coordinate, you know, tens or hundreds of different sites to think about that individual booking and coordination. And with that, we kinda like to analogize analogize to network routing for the Internet, where it's like you're not thinking of every single, you know, router and network switch. You kind of trust in a a network that can reliably deliver that data.
Speaker 8:Mhmm. And so that's something that we're starting to think about about, you know, how the space industry is gonna evolve in terms of communication, going from booking an antenna like you book a science telescope to having the outcomes through a global network where you can you can have a lot of observability and control into that network, but it's much more like software defined, and controlled kind of like modern Internet infrastructure.
Speaker 2:Question. For now, I think there's obvious opportunity to serve existing space companies. What kind of companies do you think, are potentially enabled by your technology and network that, may not have been smart to start five years ago if you didn't have kind of the resources of of SpaceX?
Speaker 8:Yeah. There's a company that we were recently talking to that I get really excited about. You know, in LA, we had the wildfires a couple months ago and, absolutely devastating. You know, really difficult to figure out where to route resources with a really fast moving fire. If you're trying to get a sense of, like, the scale and and the direction of that fire with a hell a a helicopter, it's often, like, not safe or not even permitted to go into those regions because there's just so much debris.
Speaker 8:And so satellites are a really interesting application where if you're able to have enough revisit rate, which is what, you know, in the space industry, they call, like, being able to go over a region again if you're, like, a a low Earth orbit satellite where you basically just need to have, like, a bunch of satellites that pass over and take turns because it takes time to orbit the Earth. Yeah. So having enough revisit rate to where you can actually, like, regularly track the movement of a fire is pretty revolutionary. Like, you can you could stop fires much more rapidly and be able to detect the movement. The challenge with with that is if you don't have your your latency down low enough to to be able to give the information, it's pretty much useless.
Speaker 8:Right? Like, if you deliver information, like, an hour later, then
Speaker 4:Yeah.
Speaker 8:You can't you can't deliver anything actionable and helpful towards firefighters on the ground. Like, they're gonna go into
Speaker 2:wrong are on the line. I remember Yeah. John and I I live in Malibu. John lives in Pasadena. I remember the watch the watch fire.
Speaker 2:Watch duty. Watch duty went down for like an hour. I was like, was looking I was looking at the mountain behind my house just like being if the fire comes over the hill, I just wanna have eyes on it quickly. And that was like, you know, very
Speaker 1:brief that
Speaker 2:it was down.
Speaker 1:I I I have a follow-up question. Yeah. Again, maybe a stupid question, but, what is going on in the various, different orbits? We talked to Albedo about v Leo. Obviously, LEO is kind of the hot one with Starlink.
Speaker 1:But, do you need different ground station technology or scale to hit something in high Earth orbit? We talked to, Astronis, which is maybe partnering with Impulse to kind of boost to higher orbits. What are the challenges in, or or benefits to different orbits when you're thinking about it from a ground communication perspective?
Speaker 8:Yeah. No. That's a great question. You know, VLEO, like, you're getting closer to Earth, so you're able to get, more, like, high fidelity imagery or, like, sensor, things like that. If you go up to LEO, like, that's useful both from that perspective, but also from, like, a latency perspective when you're talking about, like, trying to hit Internet similar kinda latency timelines, just the time it takes to go with those altitudes.
Speaker 8:There's also operators in, like, NEO, which is you know, middle or thorough bit that are supporting Internet use cases. And then if you go out to Geo, the benefit of that is, like, it's geostationary. That's what the name means. You're fixed at a certain location, and you're able to have really continuous coverage over a wider area cause it can see so much of of the globe. This is a super interesting area and an area that we're actually, like, really enthusiastic to be working in is is servicing multiple orbits.
Speaker 8:Mhmm. And, yeah, I think it's it's both of interest on the commercial side and also on the government side. You know, they have a lot of assets that stretch up into higher orbits, and they're looking to have, you know, more capacity, more coverage, more resiliency. Like, there's really a shortfall of ground assets in the higher orbits, actually. Mhmm.
Speaker 8:And so that's something that we didn't enter into the business planning on, but that's something that has been, like, a a very large driver of activity in our business over the past, like, eighteen months of existence. And, yeah, I I think, like, the more dynamic movement is also a really interesting point where it's not like you're just hanging out in one orbit. Right? Like, that's kind of impulse impulse's really exciting proposition with prop is that they're able to, you know, maneuver between orbits in in new ways. And, you know, in space economy, rendezvous proximity operations, like, that's something that's definitely going to be picking up and and very significant in the coming years.
Speaker 1:I feel like Middle Earth orbit is like super ripe for a Tolkien named Yeah. Startup, some some No. I mean, I would love to hear where the name Northwood came from. Yeah. Tell me where where where the name come from, and then I do have a follow-up question that's more serious.
Speaker 8:Yes. That's a very serious question. The name came from the lake house where, we first did our prototyping of antennas during pandemic, and it was the very origin of becoming a ground nerd. Oh, there you go. And so, yeah, that's that's kind of the history of the name.
Speaker 8:I mean, that that lake house, my great grandparents got it in 1945. It's just a little shack in New Hampshire, and That's awesome. It's been kind of the all all the companies that I've had have had some affiliation to it.
Speaker 1:Got it. So on the business side, can you walk me through where you're playing in kind of the value chain? I imagine that there's a fair amount of equipment that's available off the shelf. You might or correct me if I'm wrong, but do you need to build the equipment from scratch? Is this a project where you're gonna be building, like, a a gigafactory like what we've seen for the Starlink units at some point, or is it more about, assembling different components and then being really strategic about placing them and then building a network on top of that and really, like, the services side of the business?
Speaker 8:Great question. Something that our head of manufacturing, Thomas, thinks about a lot. We're definitely going to be leveraging outsourcing in early days. We we are a vertically integrated company. Like, we we design all of the different, components.
Speaker 8:Mhmm. We have those outsourced and then, you know, brought in. We're not we're not, you know, like, making our own circuit boards at this point in time. Sure. There's certain things that are, like, more efficient efficient to insource versus outsource.
Speaker 8:So largely leveraging outsourcing initially, I think, you know, we're really focusing on modular units and making our our units designed for manufacturing. So making sure that we can parallelize development, making sure that we can have things ready to be integrated at, like, kind of the final hour is is the thought process just to accelerate our manufacturing capability. And then gradually, over time, when we figure out, like, what is actually cost efficient and time efficient, we bring it in house entirely.
Speaker 1:I wanna know more about actually the mechanics of setting up a ground station somewhere. Oh, man. I imagine you could do a
Speaker 2:Yeah. We've been looking
Speaker 1:Yeah. Yeah. We're we're thinking about doing Setting up my backyard. You know? I have some extra space.
Speaker 8:I'm go pay There's a lot of ham radio amateur folks that do that.
Speaker 1:I I have a I have a friend a family friend who their family has some land in Napa, and I think they monetize it by, selling a cell phone tower right on top of it. Yeah. Is that is that is that the the the one of the folks that you'd buy land from or, or is it on federal land? Like, do you think about placing these? Do we need them to be equidistant across The United States and beyond?
Speaker 1:Mhmm. Are there other countries? Are you placing them in allied countries? Like, how do you think about the the coverage map? The I wanna see the Verizon map with all the different coverage points.
Speaker 1:Right? How does that grow over time?
Speaker 8:Yeah. No. It's it's real. We do that modeling in house.
Speaker 2:So Okay.
Speaker 8:Cool. Yeah. We we think in terms of, like, the coverage mapping and, the metrics that we're prioritizing hitting for customers. Also, shout out to Christian Adastranas, who has his own amateur radios. Awesome.
Speaker 8:We had a fun time talking
Speaker 2:tune in. Yeah.
Speaker 8:Yeah. But in terms of where you put sites, it's a great question. Basically comes down to three things.
Speaker 1:Mhmm.
Speaker 8:Land, fiber, power. Mhmm. So you just need to optimally be able to make your sites you know, we we prioritize making our sites as generic as possible, really, so that, like, we have the most optionality possible. We are also prioritizing, like, really high throughput backhaul. So Yeah.
Speaker 8:Data centers honestly become, like, a good spot to to put them at because they have the power in the backhaul
Speaker 4:Yep.
Speaker 8:Already set up. And, you know, generally try to just make sure that the land is, like, easy to deploy. One advantage of the way that we're building our systems is we don't need to lay, like, a concrete pad, which can add weeks to months to your time frame, especially when you need to, like, do permitting and all that. So our goal is to make it so that, you know, the the tech bros of the world can just, you know, have one in their in their backyard very easily, deployed easily. And yes, it is it is a global effort that
Speaker 7:we're Yeah.
Speaker 1:I remember Andoril did something similar with the with the sensor tower. They didn't wanna pour the concrete pad because of permitting, so it's on wheels saying it's completely unnecessary. Unnecessary. You could just drill it in the ground, but then it's way more complicated.
Speaker 2:Do your how do your timelines work? A lot of, you know, I'm assuming a lot of your customers are kind of planning around like launches and that means those are kind busy moments for you guys, I imagine. But at the same time, you can serve a lot of existing companies that have assets in orbit already. How do you think about kind of the advantages that you guys have of like, being on the ground and not needing to plan your entire business around SpaceX?
Speaker 8:Oh, yeah. It's very convenient. We can work on our own schedule. I mean, we have different challenges because, you know, you're going to different countries and they have their own local regulatory regimes and all that. But we're we are not constrained by launch schedules, which is great.
Speaker 8:And then the first part of your question was what was the first part?
Speaker 2:No. You answered it. You answered it already. Okay.
Speaker 1:We I have a I have a I have another somewhat random question. We ask a lot of artificial intelligence founders about their p doom. We ask a lot of space founders about their p moon. What is the probability that you will visit the moon in the next thirty years, let's call it? Would you go if the capability was there?
Speaker 1:Let's say there's been 100 people or 1,000 people or 10,000 people up. Are you going? And then what's the likelihood that you think the space economy and the flywheel that gets us to the moon happens based on your insider knowledge of the industry?
Speaker 8:I would absolutely go to the moon if I had the opportunity. I I did hear from, like, an astronaut one time just how life changing that experience was. And, yeah, I mean, I I feel like that would be definitely a thing for the bucket list. As a mom now, I think that's honestly, like, the only thing that holds me back You
Speaker 1:gotta bring the kids. You gotta bring the kids. It's gonna be Disneyland on the moon. That's the first decade of year's history.
Speaker 2:Talked about this too. Like He
Speaker 8:was love that. Do to
Speaker 2:we do we go on a Blue Origin flight? It's 250 k. Yeah. Do we just go and podcast in space? John was John was all in.
Speaker 2:I was like, my wife will absolutely kill me. I don't if it's worth it. It's definitely part of the calculus.
Speaker 8:I know. To be to be young and wild and free. Yeah. And then, like, the the lunar economy, I'm very bullish on it. I think yeah.
Speaker 8:I think we'll hopefully see that within our lifetime.
Speaker 1:Somewhat related to space tourism, the Blue Origin flight did just happen last week. I wanna know, specifically, what are the challenges with, with, again, connectivity? Because it seemed like we lost the video feed while they were at the apex of their kind of trajectory. It was only three miles or three kilometers up or something. It wasn't that high, and yet we still lost the live video feed.
Speaker 1:Is that something it's a moving object, but satellites move too. What does it take from a ground station perspective to, you know, be able to watch Netflix on your Blue Origin flight consistently?
Speaker 8:Yeah. That was actually something that we talked about, like Yeah. In the very early days, like preforming Northwood was like, being able to watch Netflix in space. And we're like, oh, wouldn't that be, like, such a cool feature? I mean, to accomplish that, like, there's multiple different kinds of the communication going on.
Speaker 8:There's, like, how do you actually make sure that the rocket is going where it's supposed to go and it's safe? And, like, we talked to someone the other day who was concerned about, like, a rocket trajectory not going the direction it was supposed to and winding up, like, landing on another country and needing to deal with kind of, like, the catastrophe that falls out of out of that and managing that. So, like, you really need to know where your spacecraft is going Yep. Because, yeah, the the consequences that fall out of that are serious. But then, yeah, having actual, you know, humans on board, needing to have some kind of communications on board, yeah, it's it's going in a different trajectory than a satellite that is just kind of conventionally, like, orbiting.
Speaker 8:And that's something that we're excited about with our technology as well is being able to vary our beam width. So if you think about, like, you know, the the signal as you get further away is kinda like a if you were to shine a flashlight on a table, and, like, the the the area that the flashlight Yeah. Spotlight covers changes depending on how far away the the flashlight is. It's the same thing with an object going up in space. Like, it's changing the actual signal propagation depending on how far away the spacecraft is.
Speaker 8:And so you need to be able to have, like, some way of of tracking that. And we're excited through, you know, the the tech that we're developing to be able to to track the beam with us as it changes for more dynamic trajectories.
Speaker 1:Can you talk a little bit about the long term, mix of customers? I mean, we've all been following Deleon's trajectory with BARDA. It it was he was talking about ZB LAN at one point, then it was Yeah. Far pharma. Now there's some DOD mixed in there, some government contracting.
Speaker 1:It feels like a lot of these companies that are doing stuff in space or doing stuff in hard tech, it's dual use. Is there a government angle here at some point, or is that just something you're thinking about in the future?
Speaker 8:No. It's it's very near term. It's very real term. Very real term. Very very real.
Speaker 1:Very real.
Speaker 8:Very real. Yeah. Across a number of different applications. I mean, they're dealing with the same challenges, like, if not even more so, where, like, they have aging assets that are kind of infrequent. Like, there's, you know, certain networks that just don't have a lot of assets, and they're old, and they're vulnerable to outages, whether it's, like, an intentional outage, you know, by somebody targeting that site or not.
Speaker 8:And so there's been a lot of interest in how that they can leverage commercial to get, sites deployed quickly. Like, for us in the conversations we're hap having, we're really emphasizing, like, we can deploy capability quickly, and we can serve up capability that's, like, quite scalable. So if one of those outages happens, you'll have that that backup and that resiliency. And so as, you know, government use cases, like, so much of our world runs on space in a way that I think people don't really realize. And so, it was you know, that's been a refrain that you're hearing more and more through government stakeholders where there's this concern on, you know, if anything goes down in space or or through the ground connectivity, it has ripple effects through, like, a lot a lot of our critical infrastructure.
Speaker 8:And so for us to be able to, you know, deploy capability that can enable resilience there is something that's definitely resonating.
Speaker 2:This might be a silly question. Are you guys already making hardware that's actually on satellites? And if not, is that something you would do at some point? Because I imagine when it comes to, you know, reliable communication, you're somewhat reliant on the technology that's actually on the craft.
Speaker 8:Yeah. That's a it's a great question. I think, like, so far, we've been pursuing partnership there. But, like, if the need presented itself to stretch onto that side, we have amazing engineers that would be, very capable of of doing something like that. But, yeah, for now
Speaker 1:There's kind of a decomposition happening right now where there's a, there's one company that just makes the satellite buses. And so you could imagine that there's a different company that makes, oh, just downlink connectivity and then you kind of vend all that together and then you do the important thing and you can focus your company a little bit more.
Speaker 8:Exactly. Exactly. Like Makes sense. That's the vision where, you know, in the same way that a developer doesn't need to think about, their Yep. You cloud or services or networking or any of it.
Speaker 8:It's just like you just focus on building and, yeah, the rest is is kind
Speaker 1:of focus on that key value creation. When did you initially start researching or, like, catch the space bug? When did you get into this?
Speaker 8:I mean, honestly, it was around that that time of the, you know, prototypes that we were making. My husband, Griffin, is our CTO.
Speaker 1:Oh, cool.
Speaker 8:And so, you know, we were just working on those prototypes during the pandemic, and I feel like I don't pursue things
Speaker 2:does. Yes. This one does. What? Some people were, you know, baking
Speaker 1:sourdough bread, but, you know, rocketry and
Speaker 8:Lot of, like, new founders coming out of the pandemic, too. Yeah. Too much time on your hands. We were fortunate to be in that position. But, yeah, just can't do something casually.
Speaker 8:I was just like, alright. And then after we did that, we kinda, like, you know, wrote a white paper with commercial folks, and then we did another one with some government stakeholders. And like, damn, like, this is a really critical vulnerability in the space industry. It kinda took off from there.
Speaker 1:Five years of work to get here. Can we play the overnight success sound? Success. But congratulations on the funding round.
Speaker 6:Really, really
Speaker 2:Really great conversation. Milestone and congrats to you and the whole team.
Speaker 8:Coming
Speaker 2:out next time you What
Speaker 8:you guys drinking over there? Is that a Yerba Mate?
Speaker 1:That's a Yerba Mate.
Speaker 2:I am. Am.
Speaker 1:Yeah. The Guayaqui.
Speaker 2:Big Yerba Yerba Mate. I got a seltzer. John's, you
Speaker 3:know, have
Speaker 8:balsamic chicken. Wait. This is like endorsement or something. But Yeah. Yeah.
Speaker 8:We have the trifecta, the holy trinity of
Speaker 1:energy drink.
Speaker 3:What are you drinking?
Speaker 8:Red Bull.
Speaker 1:Oh, Red Bull. A classic. Very Lindy. Lindy. The trinity of of energy drinks.
Speaker 1:Anyway, have a have a great rest of your day. Thank you so much for coming on the show. We'd love to have you back when there's more news. Thank you so much. Bye.
Speaker 2:Cheers. Bye.
Speaker 8:Alright. Have a good one.
Speaker 1:Bye. Let's close out with some timeline. What else we got? Oh, Mike Newt, former guest on the show, has released the results from OpenAI's o three model, which everyone's raving about on Arc AGI. And so his takeaway is that o three medium, because there's a million different varieties now for how in how intense and how long running these, these reasoning models can run for, but o three medium is the industry leading AI reasoning system by a large margin, two x the score and one twentieth the cost compared to the next leaning leading chain of thought system as measured by ARC v one semi private set scoring, 57% for $1.50 per task.
Speaker 1:That's interesting because we talked to Sean, Swix, about how Google was dominating in this Pareto frontier of model capability versus cost, and they'd really we talked about this with Logan too, how Google has been dominating in these benchmarks and then cost. But a Arc AGI is this completely separate benchmark from MMLU and LM Arena and Humanities Last Exam and all these other things that are Arc AGI, it's so simple as these puzzles, but it's in some ways harder to game or harder to optimize for, apparently. And so he says his key question for released o three, is it more like o one slightly better than pure LLM on novel tasks or more like o three preview? I love OpenAI's naming scheme. Keep it keep it simple, guys.
Speaker 1:It makes it really hard to do my job. Qualitatively new capability to solve problems outside training data. And so, we are gonna be following the Arc AGI development very closely. He closes by saying Arc v two, which is the latest puzzle eval that he released, Arc v two still has a long way to go even with the great reasoning efficiency of o three. New ideas are still needed.
Speaker 1:He called this when he came on the show. He said, we haven't evaluated the new OpenAI models yet. We heard rumors about them. We think they're great. Obviously, very economically valuable.
Speaker 1:Obviously, amazing tools. We love them. But in terms of ARC ARC v two, they're not solving that fundamental problem, and it raises questions about, is it AGI? Is it ten minute AGI? Is it it's it's AGI that can do, like IMO level math, but it can't solve a puzzle that a kid can solve.
Speaker 1:It's a different type of intelligence. And I think that's great. I think it's amazing for the economic impact, but we still got our edge.
Speaker 2:Still got it.
Speaker 1:We still got it. Humanity's not done yet. But anyway, let's move on to some news. You The United States banned artificial dyes from all food products effective yesterday.
Speaker 2:Yeah. This is big. We gotta get Callie Yeah. Callie Maritz, co founder on, to come break this down. I don't have full context.
Speaker 2:It seems like it's gonna be incredibly disruptive to big CPGs. Can you imagine how you reformulate M
Speaker 1:and M's? Like, M and M's, they've been making this
Speaker 2:for a hundred Get ready to have some gray M and M's, folks. They're still gonna taste the same. Actually, we'll see if they taste the same if they're not, you know, the color of the rainbow. Yeah. But I I I think this is good.
Speaker 2:There's plenty of evidence that these different dyes like have really terrible impacts on health and especially considering that kids consume these and they don't have the same ability to reason.
Speaker 1:I have a different take.
Speaker 2:Think
Speaker 1:natural immunity of the human body is incredibly resilient. And so as
Speaker 2:long as you
Speaker 1:build up a tolerance to the poison, you're gonna do fine. So, I would say just start slowly, microdose the M and M's, build up your tolerance, and then you can a ton of artificial dye. No amount of artificial dye could do anything to me at this point. I have consumed so much Celsius and so many processed foods that I am invincible. Some people say hubris.
Speaker 1:Yes. Thank you. Thank you, everyone. Thank you. Yes.
Speaker 1:I'm unkillable by the American food industry.
Speaker 5:Let's end the
Speaker 2:let's end the show there. We gotta get on with Taipei. We do. But we will see you guys tomorrow.
Speaker 1:See you tomorrow. It's great show. Thank you.
Speaker 2:Thank you for tuning in.
Speaker 4:We'll see
Speaker 2:you tomorrow. Thank you to the incredible corporations that make this show possible.
Speaker 1:Thank you.