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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN. It is Thursday, 04/10/2025. We are live from the Temple Of Technology, the Fortress Of Finance, the capital capital. We faced a terrible DDoS attack likely from a nation state, but we did sort it out. Sorry for starting a little bit late, but we got a great show for you.
Speaker 1:Thank you, folks.
Speaker 2:Ben and our team of engineers.
Speaker 1:Yeah. This is why back online. People always ask us why why is your team so big? Why do you have just shy of 75 people working on the show? This is why.
Speaker 1:Yeah. Because it's real business. It's it's serious, and you need you need you need the neckbeard site reliability engineers, really. That's right. You need full stack engineers.
Speaker 1:You need back end, front
Speaker 2:end, everything. I'm looking at Ben right now, and his neckbeard has actually grown out meaningfully in the last hour.
Speaker 1:Yeah. You think you did oh, a couple prompts. Couple prompts will do it. Not yet. AGI twenty twenty seven.
Speaker 1:Maybe we will have reliable live streaming by then. I don't know about paper clipping, but we'll figure it out anyway. Well, it's good to be here, John.
Speaker 2:I'm excited for today's show.
Speaker 1:Let's run through some news. We wanna start with this Wall Street Journal article about Figure AI. And interestingly, about the Wall Street Journal, two different headlines On the Internet version of the Wall Street Journal, they say, the $40,000,000,000 startup mystery shaking up Silicon Valley. And in the print edition, the headline is hottest AI startup makes bold claims but earns little. So aggressive, little bit little bit shadier on the
Speaker 2:A little more mysterious.
Speaker 1:Little On line. More shade coming from the print edition, but we'll see. We'll review this. There's some information about Figure, where they are, what progress they've made, obviously, about how they're running their fundraising process. 40 billion's a big number.
Speaker 1:Gotta back it up. So we'll see. We will dig into this.
Speaker 2:I'll dive in. So in February, a little known startup promising to build futuristic robots set out to raise new cash at a nearly $40,000,000,000 valuation. The pitch: Figure.ai would put more than 200,000 robots across assembly lines and homes by 2029, solving an engineering challenge that has eluded hardware developers for decades. It has a long way to go Figure had no revenue last year and just a few dozen robots in production according to documents shared with investors in recent weeks. The documents show Figure has signed BMW as its first commercial customer and predict it will generate 9,000,000,000 in revenue by 2029.
Speaker 1:Now is that 9,000,000,000 from BMW, or is that just they Figure generally predicts
Speaker 2:that they will generate Figure is predicting this, and they're putting it in their investor materials.
Speaker 1:Got it. Okay. Yeah. Big number. Big number.
Speaker 1:I mean, to justify a $40,000,000,000 valuation, that makes sense. Also, I mean, the crazy
Speaker 2:thing paying a little over four x, you know, 2029 revenue here.
Speaker 1:Yeah. Yeah. Four x
Speaker 2:Which feels cheap.
Speaker 1:Forward four year forward revenue.
Speaker 3:Of of
Speaker 2:the year 2029.
Speaker 1:Yeah. Yeah. Yeah. So is it because the Forecasting. Forward forward revenue would year would typically mean, like, the year ahead.
Speaker 1:So forward revenue would be, yeah. I'm paying a five x multiple on this year's full year revenue. This is forward, forward, forward, forward revenue.
Speaker 2:Yes.
Speaker 1:But who knows? Hopefully, it's extremely high margin revenue when it comes in because
Speaker 2:That would be great. Would fantastic.
Speaker 1:I mean, yeah. Even even if you if if the margin's less than 2,000,000,000
Speaker 2:in cash flow, rough. On March 24
Speaker 1:Yes.
Speaker 2:Figure's founder, Brett Adcock, wrote that his startup was the number one most sought after private stock Yep.
Speaker 1:We talked about in
Speaker 2:the secondary market, which we talked about on the show. And he shared a list that put Figure above SpaceX and OpenAI. Yep. We were a little bit taken aback by that.
Speaker 1:Yep. We talked to Christian Garrett about that, about how those lists actually get generated and whether or not, like, how much faith you should put in a list like that. Yep. It turns out that, I guess, with, like, modern word processing, kind of anyone can put together a list and screenshot And so I think there were some questions about, you know, was this from just a word processor or maybe it was generated with AI. But
Speaker 2:I would hope that it was generated with AI.
Speaker 1:Yeah. But certainly Make
Speaker 2:a list where we're at the top.
Speaker 1:Yeah. Exactly.
Speaker 2:Pretty effective.
Speaker 1:Well, makes sense. AI might be biased towards AI companies and secondary, so it pushes that up to the top, maybe. How much a startup decided it should it could raise money at a price tag that how such a startup decided it could raise money at a price tag that would make it among America's most valuable private companies is confounding investors across Silicon Valley. Had Adcock leapfrogged the likes of Tesla and Google in developing autonomous robots, or they wondered, was this a sign that the AI bubble was hitting its peak? And so there's been a lot of chatter in Silicon Valley around this company.
Speaker 1:Adcock and they give some background. Adcock, a serial entrepreneur, has been posting frequently on social media about how much interest there has been in Figure shares and touting the BMW partnership as proof of the three year old company's rapid progress. Adcock didn't respond to request for comment. In a March 31 post where he shared a video of the slender humanoids working on assembly task for BMW, Adcock wrote, this isn't a test. This is what autonomous robots in production operations look like.
Speaker 1:Turn up the music.
Speaker 2:Turn it up. Put it to eleven.
Speaker 1:And, yes, it does, so they dig into the the BMW deal. And this is a big question of, you know, if you're a hard tech company, going and getting a partnership with a big company is often a huge milestone.
Speaker 2:Huge milestone.
Speaker 1:It is important.
Speaker 2:And so guess what? The journal actually reached out to BMW
Speaker 1:Yes.
Speaker 2:And they confirmed some details. So so on April 1, the a spokesperson for BMW actually said that three Yes. Of the robots were at its facility for technical evaluation. Only one is used at a time, but the robot has practiced picking up and grasping Parts. Parts
Speaker 1:during non production hours.
Speaker 2:Non production hours in our body But
Speaker 1:the thing is that because this is this came out, this statement was made on April 1, it could have been April Fools' Day, and they could have been joking because
Speaker 2:There could be thousands.
Speaker 1:Thousands, but it's hilarious to to to April Fools on the journal, let's tell the Wall Street Journal that we only have three that are just kinda moving some stuff around. And, actually, the entire car is built by figuring we fired all the employees.
Speaker 2:But Yeah.
Speaker 1:You know, since you called us on April 1, we're just joking around about it. That's awesome.
Speaker 2:That's very yeah.
Speaker 1:It's it it is. It is. That's the nature of April fools. I got fooled. Trey Stevens fooled me.
Speaker 1:I fell for it.
Speaker 2:It was terrible. Fooled.
Speaker 1:Got fooled multiple times. I there was some
Speaker 2:You know it's April fools, but they still got you.
Speaker 1:There was some founder who tweeted like, oh, there's a there's a tech there's a hit piece in TechCrunch coming out of my company. It's dropping tomorrow. And, and I, like, made a note of it. And then the next day, was like, hey. Like, I I didn't see that piece drop, but, like, if it comes out, like, you should come on TPPN, and we should talk about it.
Speaker 1:And I, know, I'd love to dig into it as long as it's not like a complete smoking gun on you. And he was like, it was April Fools, John. And I was like, yeah. Okay. I fell for that.
Speaker 1:I'm sorry.
Speaker 2:Anyway, so the following week, I guess this is post April Fools, the BMW spokesman said that he had received an update from colleagues at the plant that there were now more than there were now more than three robots on-site, and they were being used in nonproduction and live production situations.
Speaker 1:That's great. I mean, that does seem like a huge milestone for humanoid robotics that, you know, it can be used. Like, again, all this stuff is like, I'm fine with a smooth gradient of progress. I'm fine with a with a just a robotic arm doing stuff. I'm fine with teleoperation.
Speaker 1:I think it's fine to go up the learning curve or down the learning curve, whatever.
Speaker 2:A lot of the big questions here are not around the potential of humanoids. Yes. Although there are some question
Speaker 1:Yes.
Speaker 2:Around the form factor. The questions are around the price tag Totally. Being at 3,900,000,000.0 Totally. 30 sorry. 39 and a half billion
Speaker 3:Yep.
Speaker 2:Which at the time when it was announced was more than Ford Motors. Yes. I believe they had roughly 180,000,000,000 in 2024 revenue.
Speaker 1:Yeah. Yeah. Yeah. Mean, you see what 1X is doing. You see what that creepy European humanoid company is doing.
Speaker 1:Yep. And they're both very modestly valued. And so that puts a level of of scrutiny on those companies that's just wildly different. Like, the Wall Street Journal isn't even asking questions of investors about that because it's like, I don't I don't know what one x's valuation is, but I imagine it's much it's much lower. And so when one x, they did a video with Jason Carmen, where he was folding laundry, it was teleoperated.
Speaker 1:They were pretty transparent about that. Yep. That came out that, oh, they're doing teleoperation on on humanoid
Speaker 2:still very exciting.
Speaker 1:It's awesome. Yeah. It's great. We love teleoperation. You know, who who doesn't wanna be driven around in a teleoperated, you know, Waymo?
Speaker 1:That's fine. It doesn't matter. Sure. There's questions about how does that scale? What are the economy what are the economics of that over a long period of time?
Speaker 1:But it's fine, in my opinion, to get gather training data that way, scale down the learning curve, all these different things.
Speaker 2:So Yeah. And so one of the big questions Yeah. And one of the issues and potentially one of the reasons why the journal would pay attention to this Yes. Round is that the investors investing
Speaker 1:in
Speaker 2:the round are not the typical big names that you see in these multi billion dollar rounds. One of the funding round's biggest investors, Align Ventures has spent weeks marketing the round and looking for smaller investors to buy in at the start ups valuation. According to a term sheet and other documents, the smaller investors would pool their money into an SPV reducing the amount that Align itself has to put up for the latest round. So Align to our knowledge doesn't have, you know, anywhere near the capital just on standby to lead around like this. But they are doing an SPV into the round.
Speaker 1:Yeah. It's also an interesting valuation for the amount that's being raised. You know, the standard round 20% dilution, 15% dilution. Mira Moradi, ten percent dilution. She's raising a billion dollars at 10,000,000,000.
Speaker 2:2 2 on 10?
Speaker 1:Two on 10. Yeah. So 20%. He's raising 1.5. You would expect this to be, you know, 10,000,000,000, 15 billion, maybe 7,000,000,000.
Speaker 1:But it's 40,000,000,000.
Speaker 2:Even Anderol's most recent round, I believe, was, like, roughly Yeah. A 10 to Yeah.
Speaker 1:I think
Speaker 2:it was, like, something
Speaker 1:on 20 something. Yeah. And so, yeah, like, 10% just seems to be, like, in the ballpark. This is much less than that. And so that takes some pressure off the fund raising that Align has to do, but it's still a lot of money to raise if you're not managing a $20,000,000,000 venture fund or growth fund or something like that.
Speaker 1:So, in many ways, a bet on Figure.ai is a bet on its founder. Adcock launched a series of companies since he graduated with a business degree from the University of Florida in 02/2008. He sold Veteri, an online hiring platform he cofounded in 2018. Then he's he then moved to California and cofounded Archer Aviation, a maker of electric powered air taxis. Archer went public in 2021 via SPAC.
Speaker 1:That company is also developing futuristic technology, he's yet to generate meaningful revenue. Adcock left the company in 2022. And I'm interested to to to we're we're having the, the founder of Zipline on to talk about drone delivery, and I'm interested to hear how the flying stuff market, flying car market, flying drone market, these clearly bump into each other. I'm interested to see how he landed on zipline strategy and how it differs from what Archer is doing. That was the same year that Adcock launched Figure AI.
Speaker 1:In the early days, Adcock took online AI courses and had books about robots scattered about his desk, former employees said he hired robotic experts, raised 70,000,000 in venture capital, and unveiled its first humanoid robot in 2023. And so getting up to speed about the the the industry that you're
Speaker 2:going into for a year. Ago, they raised $675,000,000 in funding at a $2,600,000,000 valuation which they raised from OpenAI's fund. They raised from Jeff Bezos' family office as well as Nvidia. So really
Speaker 4:a who's
Speaker 2:who of hyperscalers. Of of hyperscalers.
Speaker 1:Yeah. You know, that that online course thing sticks out. You know, he's sitting there taking online AI courses. And people would say, oh, like, he should have already known this stuff if he's building in this industry or he's taking this he's he's doing this company. But, like, that's pretty common.
Speaker 1:Like, when we when we decided to start a podcast, we we we took a ton of online courses about podcasting, How to use a microphone? How to talk? How to make jokes? How to how to do all these different things? And so I think that's I think that's a little bit of narrative violation that you have to know what you're doing before you go into the industry.
Speaker 3:That's right.
Speaker 2:It's very valuable. So anyways, Bezos after investing actually visited the company's facility and Figure was in talks with Amazon on a partnership. Amazon obviously employs a lot of people. Over time, you can imagine they would employ some humanoids. Yep.
Speaker 2:Employees of Figure worked on a demonstration where the robot could lift heavy objects. A few months later, Adcock told staff at an all hands meeting that Figure and Amazon had decided not to move forward.
Speaker 1:And Amazon had bought Kiva Robotics, which is a robotics company, but, it's like these they look like Roombas, basically, then they kinda slide around on the floor. You've probably seen these videos. It's really cool. It makes a lot of sense. And Amazon's obviously super dedicated to Yeah.
Speaker 1:Robotic automation. And interestingly, they've been in this centaur model where they're both hiring more and more people every single year and also employing more and more robots as they've scaled the the business. Yeah. So
Speaker 2:Yeah. One of the one of the reasons that Figure has been top of mind is some of the claims they've been making around their end to end robot AI Yes. Which they built entirely in house. They had a partnership with OpenAI. OpenAI invested in Figure.
Speaker 2:They broke off that collaboration earlier this year and then announced their own. Yes. Do you have any sense of what they're kind of claiming around
Speaker 1:the new Yes. When when I heard about the OpenAI partnership, I thought it made a ton of sense because clearly OpenAI passed the Turing test. It's a great chatbot. They have great whisper models for voice to text, basically. And so when I think about I want to communicate with a humanoid robot, I wanna be able to talk to it.
Speaker 1:I want it to be able to understand me at a level much more much better than what Siri can do. And I wanted to take that text and be able to throw it in an LLM and then look up stuff for me, talk to me, but then also trigger different actions for the humanoid. So if I say walk over there, I'm fine with an OpenAI partnership transcribing what I said, sending that to an LLM, and then triggering the the the robot to do exactly what I said. Now this phrase end to end, I think, is going to become something of a hot button issue in, robotics and humanoid AI just like teleoperation has been, where, you know, we talked about this with with One X. We talked about this with the Tesla Cyber Cab and, humanoid robots, the Optimus event, where, the robots that were serving beers at the at the Tesla event were teleoperated.
Speaker 1:And so you would be talking to a real human who would be Yep. Moving, triggering this stuff. After that, there's actually an interim level, where some of the robotic decision making and actions are are dealt with through AI. So the best way to think about this is to go back to how self driving cars evolve. So self driving cars, the first step was let's use AI just to understand the world and create a three d representation of the world as quickly as possible.
Speaker 1:So you're just doing image recognition one frame at a time and seeing, okay. There's a there's a cone there. There's a stop sign there. But once you have all that data, you basically import that into a video game, and then you're writing deterministic code for how to actually plan the path, how much acceleration you need, how much braking you need, and and and that's usually written in c plus plus, just for example. I I know it was at Cruise, but, essentially, that's written as, like, business logic.
Speaker 1:If stop sign, apply pressure to the brake. Now Tesla and what George Haas is building at, comma, they have all wanted to go, quote, unquote, end to end, which means that the only data that goes into the self driving car is the camera feed Yep. And the output is brake brake pressure and all you take in all the sensors, and you just output the steering and all of that. And so Elon made a big splash a couple years ago saying that Tesla was going fully end to end. And in that presentation, he was like, yes.
Speaker 1:It's all machine learning code now. And one of his engineers was like, well, look. Like, there's still a lot of c plus plus involved, Elon. Like, let's not go that far and make that claim because that's not quite right. But it is awesome that both in the in the world model, like, understanding the world and then also the planning.
Speaker 1:There are two different teams at most of these companies. The planning to the the the planning process of of understanding, okay. There's a parked car here. I need to go around it. Like, that is done with AI as well.
Speaker 1:And so that's that is basically Brett Adcock's claim when I hear he's he has built an end to end robotic AI system. It's that there there is no c plus plus code or Python code sitting somewhere that says Yep. If if beverage, grab with hand action number seven.
Speaker 2:Yeah. So the big the big question here, the thing that's exciting has is has Brett and the Figure AI team Yes. Had a break through
Speaker 1:that Yes.
Speaker 2:That Elon and Waymo and and, you know, many of the other companies Yes. Haven't been able to achieve with billions and billions of dollars? Because if Adcock and the team had Yeah. Then it's very possible it'd be worth Totally.
Speaker 1:This crazy that's exactly what happened with OpenAI when when the transformer architecture in GPT four got so good that it passed the Turing test. Before that, we did have this kind of it wasn't end to end, but you could have chatbots. Right? But what did chatbots do? They would take in your text and say, oh, okay.
Speaker 1:He's asking about booking a flight. Let me run the the booking flight code and give you you know, when when you chat with, like, American Airlines
Speaker 2:Yeah.
Speaker 1:You can tell that you're not talking to an LLM. You're talking to a if this, then that statement. And and that transition is what allowed OpenAI to, like, kind of bust the world open to LLMs. And if they did this, it is groundbreaking. Yeah.
Speaker 1:And it is it it it it's it's incredible. I mean, it really it really is.
Speaker 2:No. It it really is.
Speaker 1:Yeah. And it and it is and I I I think the more important thing is that most people who are really deep in AI believe that end to end systems that are reliant on insane scale and just hoovering up tons of data and then crunching it down. This is the bitter lesson that we talk about with Rich Sutton. The bitter lesson is, look, you can do all this crazy stuff where you where you, like, there was a critique of Waymo that they had a cone guy for a while, and his whole job was just to was just to write algorithms to detect cones. But if you just scale up all the Tesla data and and say, oh, yeah.
Speaker 1:We have, you know, a million cars feeding us hours and hours of video data and just train it all on a model, the model, the deep learning will learn what a cone is better than that algorithm ever could. And so you can pull that out. And so getting to end to end on any AI driven system is almost always the goal. And so Brett understands that that's where that that's that's where he needs to go and that's where he needs to build. And, if they've done it, it's remarkable.
Speaker 2:Yeah. Totally remarkable. So, anyways, so in recent months, unsolicited emails from claiming to have access to Figures Funding Round have been popping up in inboxes around Silicon Valley. They all offered a chance to grab a stake in a pre IPO AI robotics company. Mhmm.
Speaker 2:People investing as little as a hundred thousand dollars could participate, one of the offers stated. One email pitched an investment through Parkway Venture Capital, one of Figure's main backers. It said there was an effort to raise more than $80,000,000 for a special purpose vehicle that would get to own Figure's shares in the thirty nine point five billion dollar funding round. With Figure Robots on the production line at customer number one BMW and given the valuation being placed on Tesla's rival Optimus humanoid prototype, this valuation is not as crazy as it seems as face value.
Speaker 1:Yeah. There was always this thesis of, like, if you believe in humanoids, and I think a lot of people do, how do you get exposure to that? Well, the only game in town right now is Tesla, and that's
Speaker 2:this not a pure play bet.
Speaker 1:Easy business with so many cars and tariffs in China and all these different things and batteries and so much stuff. So, yes, there wasn't a pure play product for this, and and that could be part of what's driving, like, the narrative around this stock, essentially. So
Speaker 2:So one investor received a notice in January that he could acquire Figure shares from a former employee at a steep discount. Mhmm. He reached out to Adcock who responded that the proposed sale was fraudulent and that he could invest in a future fundraising round. According to messages reviewed by the journal, soon after, a representative from Figure messaged the investor and asked how much he wanted to pitch into the series c round. The investor asked for financial information that could help him make that decision.
Speaker 2:The company provided access to a data room that contained videos of ad cock talking up the company. An investor presentation showcased images of robots doing various activities including working on a car assembly and pouring a glass of milk. What the presentation didn't include was audited financials or projection. So This
Speaker 1:is an interesting strategy. Was thinking about this. Like, a lot of founders, they get bogged down in the in the fundraising process when, oh, you you I think Sam Lesson was saying, the deal goes to die in the data room. No one's ever built conviction in a data room. Yeah.
Speaker 1:And so, you know, if you don't want to bother with a data room, but you still need a a link to send someone, maybe you what you wanna do is just, like, go to your Twitter feed, your x feed
Speaker 2:Take all your marketing content.
Speaker 1:Print it, PDF it, Throw that in there. That's right. And then when the investor shows up, they just get to see your bangers.
Speaker 2:Yeah. One thing is clear. Adcock is an incredible marketer. Yep. And some of the footage just coming out of Figure broadly has been really astonishing and powerful.
Speaker 1:Yeah. I I think
Speaker 2:that's
Speaker 1:So I
Speaker 2:see why he would lead with that.
Speaker 1:Yeah. I think that's the lesson for anyone who's working over there at Figure. You know, we talked to Scott Wu about this. Like, things are moving so fast. The company's growing at an incredible rate.
Speaker 1:They have a new office, new campus every few every few weeks, seems. New new videos, new breakthroughs. And so, you know, to those folks who are working there, I would just say, like, take pictures, you know. You're gonna wanna remember this. They're gonna write books about this company.
Speaker 1:They're gonna make documentaries about this company. And so you're gonna wanna remember that. So take pictures.
Speaker 2:Look at the state of things
Speaker 1:Yep.
Speaker 2:And just witness.
Speaker 1:Just witness everything. Yeah. I think that's the goal.
Speaker 5:Yeah.
Speaker 1:Yeah. You really yeah. Yeah. This is this is history. And there's gonna be books written.
Speaker 1:So so you're gonna wanna you're gonna wanna witness this stuff. So, anyway, that's That's right. That story. I'm sure we'll be digging in more. We'll see what other people have to say and, what else is going on in the humanoid robotics.
Speaker 1:You know, we gotta have the one x founders on, and we gotta get someone from the Optimus team
Speaker 2:on We should do a humanoid day.
Speaker 1:We should. We should have everyone on.
Speaker 2:All of them. It'd be very interesting. Back to back to back to back. Yeah. They all have different angles.
Speaker 2:Yep. Like, I think it's powerful if you just pick a lane and not say, hey, we're gonna replace all human labor in the world right away. Sometimes you can start just aim to do laundry, just aim to do dishes. Some of these some of these tasks that are maybe less exciting but Yeah. Still equally powerful and and have tremendous potential.
Speaker 1:And, you know, we also gotta get some humanoid benchmarks on Polymarket for sure. Yep. I mean, the the logical one would just be, you know, Brett Eycox backed his last company. He took Archer Aviation public. I'd love to see, you know, figure IPO percentage on Polymarket.
Speaker 1:I'm sure there's a lot of other, even just like those the the amount of humanoids deployed at BMW. I don't know if that would be auditable in a way that Polymarket could work against and resolve the market. But Yeah. Having some sort of humanoid benchmark on Polymarket would be fascinating to track Totally. At least in at least in, like, in just sentiment in the market would be very cool.
Speaker 1:Anyway, should we move on to we've been getting a lot of questions from folks about how to encourage other potential listeners to tune in to TBPM Live. And we have a little script for everyone.
Speaker 2:Yeah. So this is like something it's not quite a battle card. Right? It's not super condensed. Yeah.
Speaker 2:If you're out there and you're talking to friends that, you know, if you enjoy the show Yep. And you wanna kind of share it with a friend, you might get some pushback. Right? Might get some people saying, well, I already listen to some technology podcasts. Or I already listen to business podcasts.
Speaker 2:So why don't we run through this live? Do you wanna kick it off, John?
Speaker 1:We yeah. Why don't you play the prospect? I'll play the sales rep and I'll I'll I'll try and get you to prospect finish line. Exactly. Yeah.
Speaker 1:So kick it off.
Speaker 2:No. You're the sales rep.
Speaker 1:So just so you're aware, a lot of listeners ask how we differ from other podcasts. One key area is integration. Unlike other podcasts, TBPN live connects all business and technology news together into one seamless three hour daily stream. Does that sound like something you'd find useful?
Speaker 2:Possibly, but I already have podcasts I regularly listen to. I'm not sure I need another one.
Speaker 1:Okay. So that's understandable. But before we dive deeper into TBPN Live, could you tell me a little bit more about your current listening habits? Specifically, where do you find the biggest challenges or bottlenecks in staying informed about tech and business news?
Speaker 2:Well, honestly, I spend a lot of time scrolling through the x timeline and other social platforms just to catch what my current podcast might miss. It can be pretty time consuming.
Speaker 1:Exactly. That's a pain that's a pain point we've frequently heard. It sounds like your current podcasts aren't quite keeping pace with your needs, forcing you to supplement with fragmented sources. Roughly how many hours per week do you spend doing that additional research?
Speaker 2:I don't know. I estimate about five or six hours each week, John.
Speaker 1:Oh, okay. Well, TBPN Live is designed specifically to reduce that research workload by at least 50%, potentially saving you hours each week. How would you feel about having that extra time back for more strategic activities or even engaging more deeply with our insightful content?
Speaker 2:That sounds good, but I'm a bit concerned about the amount of advertising. I'm currently subscribed to premium podcasts behind paywalls, and they have fewer interruptions.
Speaker 1:I completely understand that concern. Many listeners initially feel that way until they realize that the quality and relevance of the companies we partner with for advertising. Could I quickly share an example of how these partnerships have provided values value to listeners similar to you?
Speaker 2:Sure. I'd be interested in seeing that. But, my current podcast lineup already seems pretty good.
Speaker 1:Absolutely. Absolutely. Your current podcast sounds solid. Many listeners who've switched over were initially satisfied too until they realized TBPN Live offers unique features. Would it be helpful if we briefly compared the scrolling news ticker we have at the bottom of our livestream, a feature that's exclusive to our podcast?
Speaker 2:Actually, that might be interesting. I'd like to see how it works at least.
Speaker 1:Great. Why how about we set up a quick demo session tuning into the TBPN livestream together? I'll tailor the experience specifically around your concerns about fragmented research and show exactly how the integrated stream and ticker could streamline your daily news consumption. How does that sound?
Speaker 2:Sounds good. Let's schedule that.
Speaker 1:So that's just a great way to get someone on board if they're on the fence, they're not ready to take the leap.
Speaker 2:Yeah. Great way to at least set up a demo.
Speaker 1:Yeah. Yeah. For sure. Set up a demo with them. For sure.
Speaker 1:Yeah. You really wanna go full full SDR mode for us. You wanna have the discovery call with them, handle the objections, create some counter arguments. Ideally, if you know what they're listening to, create a battle card.
Speaker 2:Yeah. And a lot of the techniques in here, can actually leverage in your own business, in your own sort of day to day life in terms
Speaker 1:of winning
Speaker 2:and overcoming those objections like you said. So really great work here, John. And hopefully
Speaker 1:I think it's gonna convert a lot of prospects.
Speaker 2:Convert some prospects and For sure. Help grow, you know, the listener base.
Speaker 1:Yeah. Let's run through how Elon Musk rescued X from the brink. New new report from The Wall Street Journal, diving deeper into the X and XAI merger. A crowd of in investigate a crowd of investors gathered at Morgan Stanley's New York office to hear X's sales pitch eager to get a piece of debt that Wall Street had once shunned. Cell phones were a no go at the January event, and the audience was told to stay seated until ex chief executive Linda Yaccarino and others had left the room after brief remarks and without taking audience questions.
Speaker 1:Banks had planned to sell $3,000,000,000 in bonds at 95¢ on the dollar, but ended up selling more than 10,000,000,000 at even higher prices. It was a testament to X's ability to bring advertisers back to the platform helped in no small part by TVPN. No. By, Elon Musk's proximity to president Trump. I I obviously, we can't, you know, claim victory 100% of the time, but I do feel like we are shifting the timeline and making x a better place, hopefully.
Speaker 1:I mean, that that is kind of the goal is to bring to shift x back towards more tech and business content,
Speaker 2:possibility that X would one day merge with a hotter Ascended company, Musk's x AI. In private meetings with Wall Street, X Executives said there was a good chance that the social media platform might eventually merge with Musk's artificial intelligence company which makes the Grok chatbot. Yep. The billionaire has said he never lost money for investors, but for a long time, he looked like he was going to with X. After Musk bought it in 2022, advertisers fled over content moderation concerns and its loans soured as revenue fell.
Speaker 2:One month after he took over, Musk said the company formerly known as Twitter was on the verge of bankruptcy. I don't know how this was true. I think it was, you know, in part said to I don't think he obviously would have ever let it go bankrupt. I think it was mostly meant to inspire the team to grind harder and grind harder they did.
Speaker 1:They
Speaker 2:did. So late last month, Musk posted on X that he was merging the company with XAI in a deal that valued the newly combined company at more than a hundred billion. Folding X into a larger company competing in a global race to develop sophisticated generative AI tools could open the door to raising money at a valuation considered impossible just a few years ago. The merger caps a string of events, some strategic, some fortuitous that helped Musk announce a deal before Trump's tariffs effectively closed the market for deals.
Speaker 1:It is crazy that he's never taken a down round but it's it's kind of underrated that
Speaker 2:I don't actually Is it is it down round or that he just always eventually got higher?
Speaker 1:I mean, I I I guess,
Speaker 2:like Because x x did raise a down round. Right? Or or or no? I guess it got marked down internally.
Speaker 1:Marked down internally, which is not his doing. Yeah. Like, Anyone could do that at any time. Internally, you can mark it down.
Speaker 2:People have definitely panic sold and lost money, but they've he's never done, you know, a primary round and ended up not returning
Speaker 1:But I I I think the lesson for, like, actual entrepreneurs that aren't maybe in his shoes is that, they're they're if your business is at all humming along and doing something like like, even though Twitter rebranded as x and went through, like, a dark time and really was facing a lot of pressure on the revenue side, Elon was extremely quick to rightsize the business and get to a place where it was not burning as much money. Like, that seems clear. Like, we never heard rumors about, like, oh, like, Elon had to put in a billion of his own money. Right? And I don't think that happened.
Speaker 1:And so what does that mean? It's like, yeah, the the whole business shrunk, but it continued to exist. And so there's a whole world where if you move quickly, whether it's post SBB crisis and you know you're not gonna be able to raise up around and maybe your own VCs have essentially marked you down if you're at a big enough scale. They might have actually done it. If you're probably just some seed or series a bet, they probably didn't remark you.
Speaker 2:Yeah. Fidelity was the that marked it down.
Speaker 1:Yeah. Fidelity has to do
Speaker 2:that. Traditional investors avoided the markdown because they never lost faith.
Speaker 1:No. No. No. I like like yeah. I'm I'm almost certain that the big venture capital firms do not do markdowns in that way.
Speaker 1:Yeah. The same way as Fidelity. Yeah. Although Fidelity has problem. Puts something out and says, hey.
Speaker 1:We have marked it down and we're trading at this level or something in some secondary market, then there might be pressure from the from the big VC firms to pull that valuation into their own marks. But it didn't matter because they're up again, baby. A spokesperson declined. No one's talking to the journal about this, but we still got some interesting facts here. Musk borrowed 13,000,000,000 to complete his twenty twenty, two take private of Twitter, and the loans quickly went bad when advertisers paused their spending.
Speaker 1:He tried to persuade concerned brands to return, at one point offering steep steep discounts and threatening advertisers that they would lose verification if they didn't spend enough. The company's revenue fell from to 3,000,000,000 in 2023 from about 4,600,000,000.0 the previous year. And the thing is is that, like, yeah, that's a huge drop in revenue. But when you think about, like, the most of the r and d has been done on X. Right?
Speaker 1:Like, the apps, you have to keep them alive, and you do have to launch some new features, but, like, they're kind of humming along. You don't need to do a lot on user acquisition. Like, the the people that are addicted are addicted and they're gonna stay. I'm never leaving. Yeah.
Speaker 1:And so you really can run it with a with a smaller team. And when you when you have 3,000,000,000 in revenue, which is pretty high margin because it's just ads, you have 3,000,000,000 to kind of slosh around and keep this thing going. Like, that's a lot of money to keep a website going in an app. Like, that that is what it is. Like, it's a big one, but it's not it it it doesn't have any, like, crazy unexpected massive costs if you run it effectively.
Speaker 1:And that's
Speaker 2:kind These companies, again, were always so heavily intertwined. Right? X had a big position in XAI. Yep. Yep.
Speaker 2:Yep. And XAI paid X for data. I would have employees flop back and forth. Yeah.
Speaker 1:So and and then staying on the revenue thing. Right? X's revenue dropped again in 2024 to about 2,600,000,000.0. It ticked up in the final quarter of the year according to people familiar with the matter. So, they so it might be turning around, but it's gonna take a while to build that back up, because a lot of people have have have left to go to other other platforms.
Speaker 1:But it does seem like, you know, even like, Twitter and X have reached their nadir, in my opinion, like, in terms of, like, sentiment. And, like Yeah. The people who wanted to leave have left. The people who have stayed are staying. The advertisers who have who wanted to leave have left.
Speaker 1:And so, yeah, it's still it's still producing single digit billions in in ad revenue and and and monetization, and that's great. Musk and his advisers had long thought about bringing X and XAI together, but after the election, those plans accelerated according to people familiar with the matter. To do that, they knew they would have to successfully execute several transactions in the right order and get a little lucky, but Musk is a pretty lucky guy. With Musk's with Musk ascendant after the election, X took a new approach to ginning up the new new ad spending. In December, a lawyer from X called a lawyer at advertising conglomerate Interpublic Group, hinting that its recently announced $13,000,000,000 deal to merge with rival Omnicom would face trouble from the Trump administration.
Speaker 1:So he's putting the pressure on them. Other advertisers started to raise their spending, including Amazon.com in January. Amazon's an interesting one because, I mean, obviously, huge huge advertiser, but, very direct response and very product driven, and that's a little bit hard for the the the mindset that you come to x with because it's a reading platform. It's it's almost like an education platform. It's not the same experience as as Instagram where you're just browsing different visual elements.
Speaker 1:You see a product. It makes a ton of sense. And then I think that's why Ben Thompson's always argued that
Speaker 2:Instagram feed now is just probably the the Hennessey what's it called?
Speaker 1:The Cadillac Escalade Hennessey. Hennessey edition, which is a thousand horsepower.
Speaker 2:Explore feed of just like and the reels is just different videos of of that. Yeah. You can't get it off your mind No. No. Once you figured out it exists.
Speaker 1:It has been interesting. Like, I'll I'll I'll sort I'll I'll I'll I'll I'll that my YouTube feed moves much faster than my Instagram feed, but my Instagram feed eventually come catches up. So I'll get into cars. I'll be watching Doug Dumero on YouTube, and my YouTube feed will be flooded with that. And it'll show me all the different, like, oh, here's VINWiki.
Speaker 1:Here's, you know, all Whovie. All the different car YouTubers will kind of flood in because Google picks up on it. Instagram, don't use as much, but eventually, we'll learn, hey. We showed him one car video, he seems to be more into it than before.
Speaker 2:That's right.
Speaker 1:Let's keep it going. But, again, on x, even though I do post about cars every once in a while in kind of a joking fashion, x hasn't figured out how to serve me ads. Plus, I pay for, like, the most premium version that gets rid of all the ads. But Yeah. Even when I didn't, I never saw that.
Speaker 2:I turning the premium off, turning the verification off just so I can get the full flood of ads. I wish you could be on the highest tier so you could pay x as much as possible Yep. Yet still see ads Yep. To get them that sort of incremental
Speaker 1:I like that. Revenue. Yeah. I like to I mean, for a while, could, like, pay for the check mark but then turn it off. You should be able to do the same thing with ads.
Speaker 1:Pay to remove the ads but then check mark, put them back.
Speaker 2:Yep.
Speaker 1:But maybe you need a maybe you need a non account just for that.
Speaker 2:Anyways, I'm excited to see what this combined entity does. Yeah. Lot of work to do still.
Speaker 1:Yeah. Mean, we talked about it before. It makes a lot of sense in in a bunch of different ways from real time data. When you go to Grok, you're gonna wanna know about things. All the data gets sucked sucked into x anyway.
Speaker 1:And so makes sense from a data strength perspective and and and also just as a distribution vector for Grok. Yeah. It seems like every major, every major foundation model company has found a dance partner, and Google has Google.com. And they're searching, and they're sending generative responses into the Google search bar. OpenAI has been able to get everyone to download the OpenAI ChatGPT app.
Speaker 1:It's in my home row, and they've done a great job at that. There's been talks about, oh, Perplexity might, like, merge with someone or Anthropic might merge with someone or partner up with someone. So the x AI x x and x AI deal makes a lot of sense in that context. But if your business is is collapsing and advertisers are leaving and you need to cut costs, get on ramp. Time is money.
Speaker 1:Save both. Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
Speaker 2:Ramp.
Speaker 1:Ramp. And we have our first guest of the show, Alex. Welcome to the studio. How are you doing today? One second.
Speaker 1:We are bringing him in from Outtake AI. We will give you a little background.
Speaker 3:How are doing?
Speaker 2:Big news this week. What's going on?
Speaker 3:Thanks for having me, I'm pumped to be here.
Speaker 1:Thanks so much.
Speaker 2:Thanks for coming on. Busy week for you guys. Hyperscaling and announcing the raise all at the same time. Yeah. But be before we dive in, introduce yourself and the company.
Speaker 2:Yeah. And yeah, whatever backstory you wanna give for the audience.
Speaker 3:Yeah. Of course. Well, first off, thanks for having me, guys. Backstory. I spent five years working at Palantir.
Speaker 3:I worked across a lot of crazy different stuff as as one does at that company. Worked abroad. I was in South America. I was in Eastern Europe. Eventually, started to work on really deep core product things.
Speaker 3:Towards the end, spent a lot of time on what we effectively, our experimental product team. So zero to one new product bets. Worked directly for the Pantry CTO, Sean Sunker. Absolute GOAT. A shout out to him.
Speaker 3:Also one of our angel investors.
Speaker 2:Oh, so amazing.
Speaker 3:And yeah. And then yeah. Towards the end, you know, as everyone sort of became obsessed with AI, it was it was really obvious to me that, like, we're gonna live in an increasingly, like, schizophrenic Internet. Like, you know, what you see is not necessarily what you what you get online anymore. Especially the way I think about it is the cost to be a shitty person online went to kinda $0 over the last, like, three years.
Speaker 3:You got infinite text, infinite images. That stuff is awesome, super creative. Just, obviously, there's bad people out there that are gonna misuse it, and I wanted to do something about that. And that's really what Outtake is focused on. We we we we try to preserve auth authenticity, identity online.
Speaker 2:Go deeper there. Who who are the kind of companies that you're working with today and will be working with? You know, I'm sure some some you can share, some you can't, etcetera.
Speaker 3:Yeah. It's it's by in cybersecurity, there's this, like there there's a there's a lot of sensitivity around, like, what you can and cannot share. And that's but, we've been lucky to work with phenomenal places like, you know, OpenAI is one of our one of our favorite customers, really pushed us when you think about the kinds of cybersecurity threats they might be dealing with. Really, anyone that has a brand big enough to really matter is a brand that can be misused. Right?
Speaker 3:So a a fun side effect for us as a company is, like, our customers are intrinsically people that matter because they're the ones whose names and brands are being misused to manipulate people. Right?
Speaker 2:Yeah. Can you talk about so so I feel like everybody's been aware of this threat around AI impersonation. You some of these like voice models, even video models at some point are getting so advanced that it's becoming a big threat. Can you talk about, feels like we haven't faced like Armageddon yet but I'm sure like, I'm sure part of that is the work that you guys are doing and the work that, you know, these foundation models are doing. Can you talk about like what's app actually happening in the market?
Speaker 2:Because I have the sense that like, you see this like tip of the iceberg where you're getting like spam on iMessage or you're getting email spam or you're getting, you know, some phishing attempt, etcetera. But what what is the work what is all the work go that's going into this to make sure that you're only seeing that tip of the iceberg. Right? It doesn't feel like we're completely flooded yet. Yeah.
Speaker 2:But this thing, you know, this kind of phenomena is scaling.
Speaker 3:Yeah. To to your point, I hope we never see Armageddon. I I I think there's this, like, gradient of sophistication as you pointed out where, like, you know, the average consumer deals with spam text, maybe some shitty emails, and certainly hopefully not, like you know, people have talked about the idea that your dad is, like, giving you a deep fake voice call and and whatnot, but, like, we haven't necessarily seen that. Right? Interestingly, a lot of the attacks, you know, on the other end of the of sophistication are actually really targeting enterprises.
Speaker 3:Right? And and it kinda makes sense. It's like, that's where the money, that's where the data is. And so what we are seeing is, like, the quality and volume of, let's say, like, inbound email phishing attacks has, like, gone up considerably. And and this just goes back to the idea of, like, the cost to do that dropped a lot.
Speaker 3:Right? And so enterprises are are, like, dealing with an absolute flood of attacks at the moment. And there and and then there's a variety of attacks. Right? So there's, like, you know, there's the good old email security stuff we just mentioned.
Speaker 3:There's just a lot of stuff around social engineering generally. Right? It's like, here, let me throw together a fake website and use that to, like, DM people, to to send emails by that. Or let me just get the customers of that company. Let's say, I'm gonna use a random name that's not connected to us.
Speaker 3:Let's say it's like, I don't know, the bank bank of Canada in some way. Right? It has a website that's gonna now be used to scam Canadian citizens in some way. Yeah. The the the sophistication is, like, really one one phrase that I always come back to is, like, it's not only that grandmothers are the ones being scammed.
Speaker 3:It's actually grandmothers can become scammers now. And it's because right. Because it's, like, it's just easier than ever. Yeah. And that's actually the real issue.
Speaker 3:It's, like, sometimes people talk about large language models, and they're, like, oh, like, could teach someone how to, like, clone smallpox. And it's like, yeah, dude. Sure. It maybe. But, like, it could immediately today tell you how to, you know, pen test someone's website and and try to get into it.
Speaker 3:And so it's just like the barrier to entry is just so much lower than it used to be for all sorts of cybersecurity attacks.
Speaker 1:Yeah. That's been
Speaker 2:Can you talk about, like the the scale of, you know, some of these like phishing things? Like when I when I think about like, you know, everybody's in tech is used to getting like a Coinbase style phishing like, hey, you know, give us a call. Like you had some issue. And I just think about, like, okay. If that works one out of a thousand times
Speaker 1:It's the best business ever. It's the
Speaker 2:best business ever. Like, it is part of the reason that, like, you know, this sort of, these issues are are scaling so rapidly is just because it's super profitable.
Speaker 3:Yeah. Yeah. I mean, the the like, one way to think about it is, we've all seen the tremendous growth of, like, AI outbound companies. Right? They've done really well.
Speaker 3:It it's it doesn't take the a leap of the imagination to understand that, like, that same sort of, like, well intended outbound can be misused. Right? And so maybe one way to, like, paint an idea of volume is, like, just as the volume of AI outbound has increased on, like, legitimate use cases, where I'm sure you and I both deal with a ton of LinkedIn in the hunter email inbound. Yeah. It's basically been one for one on sort of the darker side of it as well.
Speaker 2:What about the stuff you guys are doing with creators? I know in the announcement, you said that you guys are working with SciComm, the the team behind Heumann Lab. Yeah. What are what are you seeing creators dealing with in terms of impersonation as these models have have advanced?
Speaker 3:I mean, creators were some of our first customers. Right? And it's actually because they were the ones the first ones to feel the pain. I mean, to some degree, maybe you guys deal with this. Right?
Speaker 3:Someone might make a fake handle of your account.
Speaker 1:That's happening. Yeah.
Speaker 3:Yeah. Fake versions of your profiles. There there's a lot of value in impersonating you guys, whether it's a financial endorsement, a start up endorsement, just pretending to be you for recruiting and something.
Speaker 4:The
Speaker 3:the basically, the creators were the first ones to hit because they were the most chronically online, right, is is the short answer there. Yeah. And and in the early days, when the models needed more data to train on, they were also the ones that had the most data available. I think what was really fascinating for us as a company is especially since almost the whole team came from Palantir, we had this we we had a lot of reps that selling to large enterprises, government, and incredibly secure environments. And so creators ended up being this great launching pad for us where we, like, built a product really, really fast and then and then grew went went upmarket really, really quickly.
Speaker 1:Can you talk a little bit about recent AI model progress? I don't know if you read this, article on Less Wrong, from ZeroPath, but, just to summarize it, it said recent AI model progress feels mostly like BS. They this is from a founder who actually built an AI driven pen testing company, and they said they kept upgrading to the latest and greatest model. It would completely destroy the benchmarks, but then they weren't getting real world results. And this was a question about benchmark saturation.
Speaker 1:I could imagine that to your point about, like, the script kiddies are better than ever, basically, because pen testing is democratized now or or or or hacking or scripting is democratized. But in terms of the work that you're doing, how important is AI model progress to all that, and and what is the shape of the of the of the curve that we're looking at? Is it sigmoid, or are we going accelerator to the moon?
Speaker 3:That's such a good question. It it it goes back to my sort of, like, grading the sophistication response, which is, like, you know, surprisingly, as we talked about, we're all dealing with that flood of text. Clearly, it's working, but people keep doing it. And so we all agree that, like, even if we paused all model progress, that would continue.
Speaker 1:Right? Yeah.
Speaker 3:And so my general take is, like, the models are already at a point where they're having serious social engineering attack effects. Mhmm. Now as you go up that gradient of sophistication, for example, the pen testing founder, he he might have a very legitimate argument where it's like, hey. Sure. There's all this hype around progress, but I don't actually see a model being able to autonomously hack a website.
Speaker 3:Because maybe that's at the further end of of the sophistication. But I guess my claim is that, like, know, it's it's something like eighty five percent of critical data breaches happen because of social engineering attacks. It's almost like machines are easy to secure these days. Like, we you know, there's a massive multi billion dollar industry that's all of cybersecurity that focuses on that. I think I think one of the big contrarian things about Outtake was it was really two things.
Speaker 3:It was like, one, hey. If machines are pretty secure, let's actually focus on securing the humans. And then two, traditionally, enterprises will, like, stop at securing themselves. Right? So they'll say, hey.
Speaker 3:I have my corporate perimeter and then my VPN, and everything in there is really buttoned up, and that's great. Historically, cybersecurity companies have been kind of, I I think, gun shy of stepping outside their perimeter and saying, hey. No. I'm gonna go search for threats in the world, like arbitrary websites, social media, wherever it is, and we're gonna go look for those threats and proactively tackle that. That's intrinsically difficult because you're trying to influence the thing that you did you know, it's not part of your org.
Speaker 3:Our ability to, like, do that and and and actually do the really hard work to get there is really what helped us stand out.
Speaker 1:Is the only answer for a bad guy with an LLM a good guy with an LLM? And what I mean by that is that, you know, CAPTCHAs are not Yes. Oh my god. They're they're they're they're deterministic essentially. And yet they they can thwart a nondeterministic attack from an AI.
Speaker 1:You could imagine arc AGI puzzles becoming the next Captcha. Got it. Or or or in your view, do we need just to stay is it is it a probabilistic on probabilistic combat from here on out?
Speaker 3:I I love this question. Okay. So, yeah, one of my biggest anxieties is that, like, generally, to your point, captchas are broken. Right? Yep.
Speaker 3:Which is like, hey. We passed the touring test a while ago. For some reason, we just blew past that and don't talk about it enough. It's good. We all are blowing past what effectively was the the, like, modern version of the Turing test, which is just captchas.
Speaker 3:Yeah. And, like, there's clearly, in my opinion, not enough panic about this, which is why I was so pumped to tackle this two years ago. Yeah. And and we spent a lot of time thinking about this. Anyway, to get to your actual question of, like, probabilistic versus probabilistic, I I think there's a few answers.
Speaker 3:I'll I'll hint at the future of Outtake a little bit. Some of it's still parts of it are still in stealth, but I think a lot of what we do today is what you're talking about. It's probabilistic versus probabilistic, and we're thinking about, hey. Here's the harm we're seeing, and, like, can we go practically discover and remove it? Right?
Speaker 3:Mhmm. The other half of it, though, candidly, is, like,
Speaker 2:there's probably Briefly, can you talk about the agentic approach there, which is basically like you're sending good bots around the internet, finding these sort of social engineering impersonation attempts and then basically like acting like a human would in terms of being like reporting this content, you know, basically flagging it, being very specific about it. But maybe could you dive in there around like, yeah, why Yeah. Yeah. Why why this this sort of agentic experience is important when you're not building when you're building out in in the sort of like dealing with threats in the real world out on the Internet versus internal.
Speaker 3:Yeah. Excellent point. I think, like, the the one of the other reasons that I was so excited to take a bet on this space is, candidly, this whole space is full of a graveyard of companies that were services companies. Right? So, like, it intrinsically was a task so difficult that only humans can do it.
Speaker 3:Meaning, you know, let's say we're protecting, again, the Canadian bank. You need to, have have an ability to go, like, proactively search for every place that you think the threat might emerge. You need to be able to adapt to the idea. Like, let's say that bank sells mortgages in the summer. Right?
Speaker 3:The search terms that you use to find the scams that might occur because now they might be mortgage scams need to adapt for the season. Right? Now you and I as humans can get to that pretty quickly. Historically, models were not gonna just, like, infer the season and then figure out the, like, latest trending scam for this particular customer. Right?
Speaker 3:We are able to do that. Right? And so it's it's it's like having agents that are thoughtful about how search occurs from period to period really, really matters. The other thing is, deciding what is considered harmful for that particular customer. Like, there's a lot of nuance there by company.
Speaker 3:I mean, celebrities is a great example, right, where it's like, there's fan pages. You don't wanna remove that stuff. And so there's a lot of nuance in how you determine harm. Again, a reason why you would train up, you know, a team of people to be like, hey. This is what we consider harmful.
Speaker 3:There's a lot of moat and, frankly, figuring that out. It when you use Outtakes product, there's a there's an aspect where our users effectively train our models to explain what they consider risky. And then the final bit is taking over the actual, like, remediation steps. Right? Like, talks about legal AI.
Speaker 3:Like, we I I think we've built one of the most effective legal AI workflows, right, where we, like, go out and, like, interact with third parties to resolve external issues.
Speaker 1:Can can you talk a little bit about the actual monetization or value capture here? I could imagine if I'm a bank and my customers are getting scammed, it's not exactly a bug bounty that you're but you are creating value for me because my customers are gonna be happy. Then they're gonna be unhappy with me if they get scammed even if I had nothing to do with How if you go out and and shut one of these rings down, how are you getting compensated?
Speaker 3:It's a great the the way we think about it is tradition so so I I guess good for us. The the customers were thinking about these problems. Right? They were just at a relatively lower vol volume historically. Right?
Speaker 3:So, like, if you look at the chart of, like, sort of digital attacks happening on, let's say, social media websites, etcetera, it's sort of, like, is flat flat flat. And then, like, 2022, '20 '20 '3, it, like, starts to go exponential. Right? We were, you know, positioned ourselves well. We saw where the fuck was going and said, okay.
Speaker 3:Great. All the people that were already managing that low level of attacks, I mean, they existed. They just were a cobbled together team of, like, cybersecurity analysts and occasionally lawyers. And every org every large organization had someone thinking about it. Yep.
Speaker 3:But they could sort of manage the one to 10 attacks a week. Right? They were expensive though because they're, you know, yeah. Very very high, like, hourly wages for these folks. And so, when the volume spikes, it becomes untenable to use that old system, and then it became really clear that Outtake could step in.
Speaker 3:And so to your point about value capture, it really became a question of, like, hey, you would be trying to manage this. You would be trying to, have these folks work, like, twenty four seven. They obviously can't do that nor want to candidly, and slash you wouldn't be able to afford it. So let Outtake come in, do a 10 x better solution at one tenth the cost, and and this is a really good deal for everyone involved.
Speaker 2:Can you talk about we had Ashkay on, chief architect at Palantir yesterday. We were talking about the sort of forward deployed meme. Have you taken anything from that approach? You obviously were a forward deployed engineer all over the world. Do you end up talking to these big platforms and they say like, can you guys please come and just post up in our office for a week and figure this out?
Speaker 2:Or is it, you know, less intensive than that?
Speaker 3:No. I I think the forward deployed meme is is there there's a lot of truth to it. The reality is if if you wanna if you wanna go do something meaningful, you need to go sit by the customer and, like, make it happen. Right? I mean, a a lot of our best product insights have happened because, like, me or another engineer were actually on-site and said, okay.
Speaker 3:Like, here's how we thought you were doing it, but in actuality, you need to do it this way. So, yeah, for for deploy engineering, huge fan.
Speaker 2:Love it. You got anything else? This is great.
Speaker 1:Yeah. I I I wanted to know a little bit about, like, mechanically, how do you shut down a ring of scammers? I remember reading this book about Paul Larue. I don't know if you're familiar with this guy. He's called the mastermind.
Speaker 1:He people think he might have created Bitcoin. And, back in, like, 02/2004 or something, he was you you know those, like, spam emails you get that are like, oh, magical pill, you know, pill mill stuff. He was the one sending all of those, and he leveled up so high that he would get a website shut down, instantly spin up a new website. But then he went even further and bought a registrar so that he could register, like, new domains for free, and you couldn't shut him down at the registrar level, not just like he had his own, like, TLD, basically. Yeah.
Speaker 1:It was crazy. And so some of these some of these, like, rings are extremely sophisticated. Is there a moment when you transition from, okay. My AI agent is just, like, sending a little cease and desist to, okay. We're getting in touch with, like, the authorities on this one because we discovered, like, you know, a a a major, major organization here.
Speaker 3:Yeah. Okay. I have to be careful about what I can share publicly.
Speaker 1:Sure. Sure.
Speaker 3:But but yes. Like, sure.
Speaker 1:Yeah. We saw it with the Mark Rober. Mark Rober, like, busted some fraud scheme in India. Right? I don't know if you're familiar with that one, but maybe just tell us some historical stories of how this works.
Speaker 3:Yeah. Yeah. So so to your point on the mechanics, like, the the traditional way to, like, deal with all this is is is purely legal. Right? You you put together, let's say or it depends on the exact type of attack, but generally, everything you said is spot on, which is, like, cease and desist letter, maybe a complaint to the domain host, the registrar, etcetera.
Speaker 3:That was key ingredient in the early parts of that take. I think the big differentiator, you know, in addition to all the agentic stuff is, like, we've thought really deeply about how do we become, how do we become the platform that is, like, trusted by domain registrars, hosts, social platforms, etcetera
Speaker 1:Mhmm.
Speaker 3:To to be a high quality source of reports. Right? Like, that is incredibly, incredibly important.
Speaker 1:Yeah.
Speaker 3:And I I can't say too much, but, like, yeah, we we've we've invested a lot of engineering resources in that direction as well.
Speaker 1:Yeah. That makes a ton of sense. Well, thanks so much for joining. This is a fantastic conversation, and good luck to you. Hopefully, you bust, you know, some massive scamming ring soon.
Speaker 1:Yeah. Every day. Every day.
Speaker 2:I'm sure. But, yeah, you're a new cybersecurity correspondent. Thank you. Thank you for all the help. He's he's already been finding, you know, people impersonating us.
Speaker 2:It's great. So appreciate your your your hard work and the whole team, and congrats on the new round.
Speaker 1:Yeah. Thanks a lot.
Speaker 3:Thanks, guys. Talk to you soon. See you.
Speaker 1:Bye. Talk soon. Yeah. I actually have gotten multiple times people set up fake John Kugen accounts, copy everything, copy every tweet, and then block me so that I can't see it. Then I get and the worst part about it is that I don't think that many people are falling for it, but I get so many DMs from people being like, there's a scammer that's impersonating you.
Speaker 1:I'm sure you've seen this. And it's like, yes. I have seen it, and then I have to go hunt it down and report it and stuff. And so it's just, like, annoying getting, like, a flood of text being like you're you're being impersonated.
Speaker 2:You got good friends.
Speaker 1:But yeah. Yeah. Yeah. I appreciate it. Thank you if you've let people know.
Speaker 1:But in the future yeah. I mean, still send it to me, but definitely just report it and try and get try and get the account taken down if it's out there floating around. Next up, we got Quaid coming in the building. Watches and wonders is done, and it's been a busy week with all the tariffs. And so we want to get a breakdown from him about how the watch world is reacting to all the tariff chaos.
Speaker 1:He's been in Switzerland, called in, from Watches and Wonders late night last week. And now that the show's over, we're gonna get a full deep dive. Also wanna talk to him about how, how the news breaks around, different watch news and how the how the media cycle works. So, Quaid, welcome to the show.
Speaker 5:Thanks for having me, guys. Excited to be back.
Speaker 1:Are you back in LA?
Speaker 5:I am. It's funny. The the last time I dialed in, the tariffs dropped, I think, the minute I hung up with you guys.
Speaker 1:So Yeah. Yeah. It was four 4PM that day, our time.
Speaker 2:I I was I was in such a haze. I I think I texted you quite. I was like, what what's the reaction over in Switzerland? And you're like, not good.
Speaker 1:Not good. But now now, you know, we've seen things. There's been a pause. There's been ups and downs. What
Speaker 2:Still the 10% base tariff.
Speaker 1:Yes. Correct. So so what what what was the whole journey throughout Watches and Wonders? Very funny timing. Good to be there on the ground.
Speaker 1:Take us through the reaction as things developed and where the heartbeat of the industry is right now.
Speaker 5:Yeah. And I think you can you can split the conversation kind of between the primary market and the secondary market, and so I'll intentionally walk through that. On the primary side, I think all the meetings I had the day after chatting with you guys, the tariffs dropping, there was a lot of, like, the Spider Man meme pointing at each other, like, not really knowing what to do right now. And I think you can split the reaction from brands kind of by the type of brand they are. You have, like, the the giant massive brands that everyone knows, like the Rolexes and the Pateks and the APs of the world.
Speaker 5:And their reaction is decidedly different than some of the brands that sit kind of in the middle of the market. For every brand that isn't these, like, very, very, very top tier elite brands, their focus was how quickly can I get product to The US? And whether it was functional products, watches that are just parts, like, they just wanted to move everything to The US as possible from most of the meetings that I was having. On the larger brand side, I think they had the luxury of sitting and waiting and seeing what was gonna happen. You saw the Rolex of the world and and things like that take their time.
Speaker 5:And the initial answer that that I got from secondary feedback from from, like, authorized dealers meeting with Rolex that week was the large feedback that that Rolex tended to give in that moment was, like, we don't wanna pass this on to the customer, but we're not gonna eat the cost of these tariffs either. So we're just gonna hold off. And the main focus point was we'll make it harder to buy outside of your local markets. Because I think a lot of the authorized dealers in The US are all of a sudden saying, what happens when all of my core customers decide that it's actually cost efficient to prioritize that flight to Paris?
Speaker 1:Oh, interesting.
Speaker 5:You know, buy that watch So Yeah. The thinking was how do we keep it in the local markets? Unclear how they'll hold that out. Right?
Speaker 1:So That's really tricky. Yeah.
Speaker 5:That's what was happening in the primary market in the moment. On the secondary market, in The US particularly, I think you saw a lot of dealers think it was an amazing moment for a second where all of a sudden, the inventory that was just being in their in their lots in in The US was was much more valuable than it was, you know, a few minutes before the tariffs were live. Yeah. And so on the secondary side, you saw it really came down to, like, what type of dealer and what your economics are. If you're a dealer that happened to have a lot of inventory and you don't have a hard time stocking that inventory, again, you have great sources.
Speaker 5:You had a lot of folks that just saw deals come through in an increase, and they just sold them. Like, they moved product, and that was the in the name of the game. And you saw a lot of other dealers try to opportunistically drop their prices, you know, 10 plus percent to all of a sudden increase that value. So we saw the best weekend we've ever seen after the tariffs in the sense that there was a huge increase in demand and everything. Everyone was out trying to buy those watches.
Speaker 5:And then the prices, I would say, a lot of them are 15% more than they typically would. We haven't seen a lot of, like, the craziness. Like, no one's pricing and selling at 30 plus percent to try to match the 31% move. And then since they announced the ninety day moment, I think things have chilled out a little bit. We're still seeing pricing being up 10 ish percent on a lot of the sales that we're seeing come through.
Speaker 5:Mhmm. But it's really interesting to see what dealers are going to do. I think it's a question of if you believe the 31% is gonna hold. Mhmm. And if you do, I think you're starting to stock up right now.
Speaker 5:If you don't believe it's gonna hold and it's purely a bargaining chip, then I think you're kinda sitting and waiting out and seeing what happens next.
Speaker 1:Were there any American watch manufacturers there just, like, popping champagne, like the Hamilton's or the RGM's, just being like, I've been waiting for this. I'm finally gonna catch up to Pawtuck.
Speaker 5:Not a ton. It was it's very it's very Swiss centric while you're there.
Speaker 1:It's very Swiss centric.
Speaker 5:But I it certainly would be a a good moment to be but I it was like a lot of these brands were lamenting because especially on independent side, like, had just opened up New York boutiques or Sure. They had just signed the lease in LA or whatever it is. And so the question was, how do we get product there? And a lot of the independent and smaller brands, the answer kinda became, like, I I I'm willing to forget The US market for a second. Like Wow.
Speaker 5:Can I come up with other skews in Europe that make up the revenue I lose in The US, or can I just incentivize especially in the 6 figure plus pieces Mhmm? Can I incentivize an experiential moment where I take my best collectors and I organize a trip where they come to Geneva and hang out with me as the CEO and and they buy the pieces there? Right?
Speaker 1:Yeah. And and is that I mean, obviously, that's, like, probably not completely kosher with the tariffs, but watches are unique in that if you buy one and you throw it in your suitcase and you're wearing it as you come across, like, how would they ever know that you bought it while you were on that trip. Right? That's just the nature of game. Think most
Speaker 5:people, they buy it, strap it on, and
Speaker 1:they walk out. Yeah. Makes sense.
Speaker 2:What about so one of the big concerns of the last week is that even for example, auto manufacturers that make cars in The US, a lot of those parts come from overseas and specifically China. Yeah. For the Holy Trinity brands, are they making every single individual part in Switzerland? I I they've I've seen those claims thrown around. It almost is inconceivable.
Speaker 2:But it seems to be the case that they're not dealing with, you know, the same reciprocal tariffs from from China or anything like that. But I I'd love to get your point of view there.
Speaker 5:Yeah. I think for for most of brands that we're talking about, everything's made in house. And and even a lot of the brands that that are are, you know, using generic movements, like, they're buying generic Swiss movements for for the majority case and, like, these, you know, $10,000 AOV plus.
Speaker 1:Oh, do we There
Speaker 5:are a number of brands that they will manufacture or use parts from other places, and then, yeah, they'll they'll be hit with those tariffs 100%. It's just you on, the I hate to say the word cheaper, but but on the the kind of cheaper model.
Speaker 2:Less expensive.
Speaker 5:Less expensive is the right word. You're right.
Speaker 2:What about any any further thoughts on the Land Dweller? Were you surprised at at where it's being priced on on the secondary market at
Speaker 1:all? Where is it being priced?
Speaker 2:I think the steel's roughly sitting around high high thirties, low forties. Is that correct?
Speaker 5:We we actually we haven't seen any come through yet. So I I'm yet to see, like, a transaction or or listing on Bezel for it. So kinda waiting to see where that lands. But yeah. I I mean, double retail.
Speaker 5:I said I said that last week. I think that wouldn't surprise me at all. I since I I spoke with you, I had a chance to, like, see it in the metal and and put it on my wrist and and play with it a little bit, and and I liked it a lot. I didn't think I was gonna like it as much as I did. Frankly, I didn't wanna like it.
Speaker 5:Not a creator at all, but I it's just Rolex has this thing where they they they drop a model, and it it's just always good. Like, there's a Yeah. There's an executed finesse in everything that they make happen, and and sometimes it's fun when when it doesn't work out maybe, and then it always works out. So it's it's quite nice. I like the Roseville example better.
Speaker 5:Yeah. But So what
Speaker 1:is the base price at retail for a Rolex Land Dweller?
Speaker 5:I think I think this the example is 14.
Speaker 1:14.
Speaker 5:I think it's mostly priced at.
Speaker 1:More than double. And then, when the first one comes through, can you talk to me a little about, like, how you think about that deal on Bezel? Are you gonna push that person to do an auction? Is that a better move for someone who's sitting on a land dweller who's thinking about selling it, or should they just try and price it through the normal marketplace?
Speaker 5:I think, like, we'll leverage the auction probably to do it. We did it with the Cubitus too. Like, we we sold I think we sold, if not the first Cupidus at auction, one of the first to go Cupidi to come out of the auction. And I think we'll do the same thing on the Landweller side. The fun thing is, like, the the folks that are buying the initial examples of the Landweller are doing so exclusively to be one of the first owners of the Landweller.
Speaker 5:And I think it's, that is the you'll pay an a premium for that certainly. Same thing happened with the Cubitus and any of these these, like, kind of new drops. If you want to be courtside wearing this watch and and everyone know that you got it first, then obviously, you're paying a premium for that. I don't know where it's gonna settle, though. Like, I imagine the premium for the initial examples will be certainly over double retail.
Speaker 5:But then, like, is it gonna be evaluated like it's in in a Royal Oak kind of, like, very hyped? Is it gonna settle to be similar to a Datejust where it, you know, it it trails it's a little bit above retail, but it's, you know, not as exciting. I don't know. It kinda splits the middle there. Obviously, I'm I'm leaning more towards the hype train.
Speaker 5:But
Speaker 2:Yeah. That's the the the thing that makes me think it potentially pretty sustainable is just it's a great looking watch, and it seems to wear really well. I think I saw the picture you posted, and it just looks great. It's hard to it's hard to not like even if you're not a a Rolex guy traditionally.
Speaker 1:I liked him when he
Speaker 6:saw it.
Speaker 2:What's the sentiment around Patek right now? Yeah. I felt like the general react the the felt like the reaction of the Cubitus couldn't have been worse online. I mean, like, so many people just didn't like it. I think it looks fine.
Speaker 2:It wears well. But, like, what what's the feeling around the brand, you know, last week?
Speaker 5:Yeah. I I think, like, it was cool to see them double down on a lot of, like, traditionally interesting petech models. Like, they're not they're deviations from the sports models. Like, you know, there was a really badass Calatrava that came out in platinum with the salmon dial, and it's incredible. And it I was my favorite watch in all of Watches and Wonders to see in the middle.
Speaker 5:And they came in with a 40 millimeter Cubitus, which I think is a is a very fresh take on the Cubitus. The other one is just quite massive and doesn't really feel right in the wrist in in my opinion. I think the vibe against the Cubitus is, like, similar to Rolex. Patek tends to not miss. Like, they they they kinda bat a thousand when when they do things.
Speaker 5:And I think everyone wants these big brands to catch an l so they can talk shit about it and feel like, you know, they're they're able to say that. So I think the Cupid is, like, paired with a bit of, like, an interesting take that felt maybe, like, it was overly modernized from a marketing campaign, like, didn't sit well with a lot of early early collectors. But yeah. I don't know. I think, like, I put the 40 millimeter one on.
Speaker 5:I I liked it. You know, it's it's like they make great watches. It's a little bit angular, and I'm a bigger fan of, like, a fifty seven eleven Nautilus. But, know, if I was allocated one of those things, I would certainly wear it and I would rock it.
Speaker 2:Love it. What any interesting takeaways around the secondary market? You were on a panel specifically about the secondary market. Was there anything I'm curious what your major points were and anything else you kind of learned from other people that may have been on the panel or just that that attended the event?
Speaker 5:Yeah. It was it's really cool to hear, like, how the brands are thinking about the secondary market and how the difference from from how we're thinking about it and just, I think, where it's going. I think it's you know, we entered the space when the secondary market from a brand perception was was kind of like, ugh. Don't don't don't dip your toe into it by primary only. And now to see that you know, I was in a panel next to Vacheron Constantine.
Speaker 5:I was in Sotheby's, and you have, you know, a bunch of representatives from all the top brands at the panel. It's quite cool to see that these primary brands are now embracing the secondary market as something that's quite interesting.
Speaker 1:Mhmm.
Speaker 5:And I think it allows customers to feel comfortable kind of interacting with the space as long as they're asking the right questions and they're making sure that they're focusing on authenticity and they're buying from reputable sources. And so it's been awesome for our business because it allows us the avenue to double down on our initial goal, which was just make a really, really safe, comfortable experience to transact in the secondary market, lower the barrier eventually to buying your first watch. But, also, just generally, if you don't wanna wait on a wait list, you know, come through and transact and buy the things you want. And that's why, like, the tariff conversation was super interesting for the secondary market because if the premium from, you know, a lot of these pieces from the secondary market to retail is close to 30%, all of a sudden, if a primary market watch is 31% up from a cost perspective, that delta is certainly meaningfully decreased. Do I actually wanna wait on a wait list any longer, or should I just buy one that's available in the market in The US?
Speaker 5:Mhmm. Of course, sellers know that and they're pricing it up 10%, but it still makes that that difference smaller than it was. And so all of a sudden, maybe it's not as appealing to wait two years to get that Royal Oak versus just buying it right now and and getting it when I want it.
Speaker 1:Never wait. Never wait to buy a Royal Oak. Always buy one just immediately.
Speaker 2:Just do it. How does I'm curious. How does influencer marketing work in the you know, for a company like Rolex when, you know, it feels like there's just this permanent stream of images coming out from the most influential celebrities in the world. And whenever I see one of the pictures because I've been like involved with influencer creator marketing forever, I'm always looking at the image. I'm like, does you know, does this athlete always roll out of bed and wanna wear a Rolex, you know?
Speaker 2:Like does Tom Brady always wanna roll out of bed and wear like the it Rolex, you know, Submariner of the day? Or is there some type of, you know, sort of transaction happening behind the scenes whether it's free watches or, you know, it's totally possible that they just love the and there's enough of them out there, but but I'm curious if you have have any insight there.
Speaker 5:Yeah. And it was a big influencer marketing year for Rolex. Like, prior to Watches and Wonders, they they hinted that there'd be, like, a massive announcement, and we were all kinda spiraling it because it a new model. Are they launching a new platform? Like, what's going on?
Speaker 5:And they just announced Leonardo DiCaprio as an ambassador, and they dropped the whole, like, Rolex family page where it talks about, like, all aspects and touch points of creative entertainment, sports, whatever the dominance they have on, like, really influential people.
Speaker 3:Yeah. They call
Speaker 1:they call
Speaker 2:their they call their family pages celebration of human achievement. And it's so funny because I didn't see the announcement about Leo, but I just Instagram just like serves me pictures of, you know, celebrities wearing watches. And I'm always just like, Leo doesn't go anywhere without a Rolex on. And and it seems like now it's like, okay, yeah, he's contracted to basically be like, don't leave the house without a Rolex. And everywhere he goes, he's just getting photographed and and it's just sort of like that natural marketing.
Speaker 5:Yeah. And it's funny because, I mean, Leo was a tag guy for a really long time. Like, there's that that story where the the in Wolf of Wall Street, he's wearing what looks like like, I believe it's like a vintage GMT Rolex, but it's actually a tag horror that they had, like, intentionally made to look like it was, like, an old eighties, not like, you know, stock market y looking watch, but it was it was a tag. So I think the interesting part, you mentioned Tom Tom Brady. Like, Tom Brady was an IWC ambassador for a really long time.
Speaker 5:I too. I love those brands. I think, like, it's a lot easier for those guys to be a Rolex ambassador than maybe another brand they don't wear as much. And you ask initial question of, like, do I feel comfortable wearing this everywhere? I would love to be a Rolex ambassador.
Speaker 5:I think they're very lucky because it happened happened to the brand that everyone wants to wear a lot of the most. Same with the APs of the world. They have a lot of amazing ambassadors there. But, yeah, I think there's undeniably a set of collectors that that don't want to be ambassadors because they wanna wear a diverse collection. Right?
Speaker 5:Like, I you saw the same thing. I remember sitting down with with some early investors in GOAT, and they capitalized that in the sneaker space where you had athletes and folks that didn't wanna just wear Nikes when they stepped out. They wanted to wear a more diverse set of streetwear and and shoes and whatever it is. And, like, GOAT became the business that allowed you to to catalyze that and wear multiple things. I think the thing same thing is happening in in the watch space, and that's why I'm so excited to build kind of consumer brand around the secondary market.
Speaker 5:It's like you can get to a place where you can have a watch sponsorship, but it's, like, more of a secondary oriented one. So you're making a statement that I like wearing watches, but I have a diverse collection. I'm not necessarily bound to one specific brand. That being said, not a bad gig to be a Rolex ambassador. I think
Speaker 1:it's pretty good. What what are some of the known unknowns in the watch industry for the rest of the year? What are the things that we might expect announcements around, but we don't have the final details on if we wanna be completely dialed in going into the next watches and wonders, what should we be tracking today?
Speaker 5:Yeah. I think, like, the immediate term known unknowns is is, like, kind of a general, like, I don't know what's gonna happen with tariffs. Gonna change everything from from that perspective, or is it gonna fizzle out and everything's gonna go back to normal?
Speaker 1:Got it. So we might so we might concretize that by saying something like, if we see an increase in Rolex's stated prices on their website, that would be a reaction to the tariffs. Right?
Speaker 5:Exactly. Yeah. Yeah. Yeah. Like, are those prices gonna be passed on to the consumer?
Speaker 5:Yeah. And I think, like, the consistent known unknowns that are always fun to to, you know, pause ideas on in the watch community or or, like, what's coming next, what's being updated next. We were talking about this via text before the episode, but, like, there's a very cyclical process that exists every year for a lot of these major brands. Like Mhmm. Rolex pretty much exclusively drops models that are in catalog in Watches and Wonders.
Speaker 5:So all year, the watch community is throwing out their ideas, making renderings of what's gonna happen next. The introduction of the chat GPT image product has been Oh, yeah. Wanting to see because you're seeing all of all of a sudden, like, anyone can render a, you know, a green whatever Yeah. GMP or whatever makes happen. So and so the way that typically works is a lot of the investigative Instagram journalists in the watch space will look at what Rolex is trademarked or patented.
Speaker 5:Like, Rolex trademarked Land Dweller a number of months before dropping Land Dweller, and everyone knew that. But it was like, I didn't know what they were gonna do with that. And then you'll get renderings of the watches that are coming out, and you don't know if that came from someone's Photoshop file or if that's real. Yeah. And then go tie this home with the influencer marketing, like Federer wore a land dweller somewhere in the Swiss Alps Mhmm.
Speaker 5:And dropped it on Instagram. And it looked unintentional, but I'm sure it was intentionally, you know, very much planned. But so I think a lot of the the known unknowns are, like, what's coming next, what's gonna be dropped, and then and then what's gonna be discontinued and and replaced. That changes the market significantly.
Speaker 1:Yeah. That's very fun. Well, it's such a fun market to to follow. It's so interesting. It's it has all the drama of, like, oh, speculation about the next iPhone with the fake renders, except the iPhone hasn't changed at all and so no one really cares anymore.
Speaker 1:But it's, like, within in the watch world, it's, like, we're going from iPhone three GS to iPhone four, like, every single year. So thanks for coming on and chatting with us. Great to
Speaker 2:see you, Quaid.
Speaker 5:You too, guys. Thanks.
Speaker 1:We'll talk soon.
Speaker 2:Thanks for the insight. Talk Our official watch correspondent.
Speaker 1:Yes. I'll be
Speaker 2:right back.
Speaker 1:Super important. Next, coming into the studio, we have Robin from Avalanche talking about nuclear energy and fusion in particular. I had a chance to go up to Seattle with Ben, actually, and do a whole tour of his facility and see how he's building a, probably, I don't know, maybe the smallest nuclear energy product. It's pretty small. It's almost the size of a battery.
Speaker 1:Like, you can you can kinda hold this thing. And, but fusion, not fission, much safer, much a whole bunch of trade offs there, which I'm sure we'll get into. And I'd also like to talk to him about some of the deregulation efforts that are happening, and and, there have been some announcements and executive orders, a lot of speculation about what might happen. Even Keitherboy, was talking about long term looking towards energy deregulation as a potential, driver of, innovation. We talked to a few people about how energy production is growing 20% a year in China and 0% in The United States.
Speaker 1:We don't love that. And so I'm excited to talk to Robin and see if we can bring him in the studio and chat with him about how everything's going. Robin, are you there? I think we're trying to get audio. Can you talk again?
Speaker 5:Can you hear me now?
Speaker 1:We can hear you. How are you doing?
Speaker 6:Awesome. I'm doing very good. How are you?
Speaker 1:I'm great. Can you start with just quick introduction, the company, and then, the announcement?
Speaker 6:Sure. So we're Avalanche Fusion. I like to say we're trying to build the world's smallest fusion machine. So we're trying to do a a very SpaceX style test fail fix approach to fusion, trying to be really capital efficient. The fusion machines we're building in our lab today are about 12 centimeters in diameter.
Speaker 6:That's the plasma core. And, yeah, raised a 40,000,000 series a in, you know, fall of twenty twenty two. That not an easy time back then, and we've been sort of in the lab grinding and and improving these machines ever since. And so we've kind of made it to the point where we have something interesting. And so the announcement that we're doing today is we're announcing our new test facility, which is gonna be in Eastern Washington in the Tri Cities area, called the FusionWorks.
Speaker 1:Mhmm.
Speaker 6:And so what the FusionWorks is is it's basically a facility where you can come test different, you know, fusion technology. So we're gonna provide the neutron generators with our fusion machines. We're gonna have a broad scope radioactive material license, including the most advanced, capability to handle Tridium that's available commercially. And so you can kinda think of this like a wind tunnel facility for fusion. So if you have some, you know, blanket technology you wanna come test and see how it does, you can bring it to the FusionWorks, and we'll hit it with neutrons from our machine.
Speaker 6:And you can go qualify your hardware, and then, you know, off you go. So I think, I'm really excited. I think it's sort of like the next level and sort of, you know, expanding the fusion supply chain workforce, all that kind of stuff. And then we've got some really great partners we're gonna be working with in Eastern Washington as well.
Speaker 1:I remember talking to AJ at Hermes, building hypersonic planes, and one of the main, hiccups to their progress is just getting wind tunnel time. And so I haven't heard of anyone building a wind tunnel startup. Maybe that's a good idea. Can you talk about where you're seeing demand, who you were talking to that made you realize that you needed to build a facility that would service a broader swath of the fusion community?
Speaker 6:Yeah. So funny. Should they mention that? So, like, AJ and and Hermes just recently announced their heat facility. Right?
Speaker 6:Which which is like Yeah. Basically so what it sounds like after that conversation, they did is they went and built a hypersonics test facility themselves.
Speaker 1:Makes sense.
Speaker 6:And so the the Hermes announcement, I think it was a couple weeks ago now. Okay.
Speaker 1:I missed that.
Speaker 6:Was basically they are opening up their test facility to the rest of the DOD because there's a shortage of hypersonics testing.
Speaker 1:That's great.
Speaker 6:And so it's kind of it's kind of like, duh. Like, if you spend all this money standing up this, like, unique thing, you know, if it's operating twenty four seven, obviously, it's gonna be a a much better facility, and you probably don't have enough work to operate this thing at that cadence. So why don't you open it up? You could bring in some revenue while you do that, and you can make this, like, really awesome facility that's just sort of, like, grinding day in, day in and day out, getting really good at what it does. And so it turns out that idea, applies to aerospace and hypersonics, and it I think it's also gonna apply to
Speaker 1:fusion at the end of day. Yeah. It's, commoditizing your compliments.
Speaker 2:Okay. I gotta ask. I gotta ask. New presidential order this morning. Yep.
Speaker 2:Zero based regulatory budgeting to unleash American energy. There was a whole bunch of mumbo jumbo in here, but it seems it seems important. What's unique? Would would love your take.
Speaker 6:Yeah. I read that this morning. I kind of love it. You know, this idea that every now and then regulate a regulation is gonna come up for review and it needs to justify its existence is kind of awesome. I can give you an example of how it applies to fusion.
Speaker 6:So, you know, Tritium is regulated at the state level if you're in agreement state. So, like, we're working with Washington Department of Health to get it licensed. But the NRC has this rule that if you can't account for 10 curies of Tritium in your system, you have, like, thirty days to report it as an incident to the NRC that you've, like, lost 10 curies tritium.
Speaker 1:Mhmm.
Speaker 6:And to to give you an idea of how small that is, an exit sign has, like, 25 curies of tritium. So, you know, here you are running your fusion machine. If you can't account for 20 or 10 curie because it got, like, absorbed into the walls and it's self shielding. You can't even measure the x rays from it. You just don't know where it went.
Speaker 6:Yeah. That's a big deal, and you need to report that as an incident. But, like, if someone, like, throws an exit sign in the garbage and nobody knows where it went, like, cares. Right? There's no, like What
Speaker 1:What do you mean an exit Like like
Speaker 6:an exit sign that you see at a
Speaker 1:theater or like what what do you mean by exit sign? Is that something that like Like
Speaker 6:an exit sign above the door. Right? Like let's say the fire there's a fire and the lights go out Yeah. Okay. And you have this glowing exit sign.
Speaker 6:Yeah. Those are powered by 25 curies of Tridium.
Speaker 1:I had no idea.
Speaker 6:Yeah. And so, like, we decided a long time ago that, you know, people being able to see how to get out of a burning building in the dark
Speaker 1:Oh, okay.
Speaker 6:The safety associated with that was worth the very small risk of having tritium in these I had no idea. Decided, you know, human safety over, like, some very
Speaker 1:They're gonna freak out Jordy. He's gonna avoid he's gonna avoid every exit sign he sees now because he's super paranoid.
Speaker 2:They're made with microplastics too.
Speaker 1:Yeah. Oh, no. We can't
Speaker 2:help that.
Speaker 1:Right. Yeah. That's hilarious. Can can
Speaker 6:you give us a
Speaker 1:broader agency. Yeah.
Speaker 6:So there's no agency out there investigating missing Yeah. Exit signs whenever one goes missing. Right? That would be, like, silly.
Speaker 1:Yeah. Yeah.
Speaker 6:Yeah. And so, you know, I think this NRC ten Curie missing thing is an example of a regulation that maybe made sense at the time. Yep. But man, if it had a sunset clause and had to go defend itself, like everyone in Fusion hates this one.
Speaker 1:Sure. Sure. Sure.
Speaker 6:Unanimously. Like, I feel like this was an example of something that probably should die. And Yeah. You know, this, executive order is a way to get rid of some of that stuff, I'm I'm all for it.
Speaker 1:At the same time, it seems like, my kinda novice understanding of it is that, on the fission side, we are highly regulatory constrained, and there's there's high regulatory risk and relatively low, high regulatory risk, relatively lower science risk. In Right. Infusion, we're higher on the science risk and lower on the regulatory risk. Is that the right frame to think about it? And and can you just give us a brief overview of how American science scientists broadly are thinking about progress in fusion?
Speaker 1:We hear, you know, papers go viral. Oh, it's solved every couple years. We're trying to get to, you know, net energy created. Where are we on the path of progress towards, you know, this amazing, fusion future?
Speaker 6:Yeah. So, I mean, we've demonstrated ignition or q greater than one using lasers, like hitting, you know, a pellet of of deuterium tritium with lasers and making more fusion energy in than the laser energy that went out. That's awesome. And so there's a bunch of fusion startups that are working on laser approaches to doing fusion energy. There's another crew that are working on, like, magnetic confinement or combinations of that.
Speaker 6:That's, what I would consider what we're doing essentially.
Speaker 1:Mhmm.
Speaker 6:CFS, Helion, or ZAP Energy or other companies that are kinda doing that. They have not hit q greater than one yet, but we're all building machines that have a chance of doing that in the next couple years. And so I actually think it's gonna be really exciting. There's a chance that one or multiple magnetic confinement fusion companies are gonna cross q greater than one during this administration. And those machines look a lot closer to what a fusion power plant is gonna eventually look like than sort of the laser fusion techniques.
Speaker 6:And so if that happens, and I think there's a good chance there is, that's gonna really change geopolitics around energy. You're gonna see this, like, amazing, you know, rush to kinda try and commercialize magnetic fusion confinement, which is gonna be super exciting. Yeah. To give you an idea of, like, the regulatory split. So right now, there was a decision about a year ago that, fusion machines are gonna be licensed like particle accelerators Mhmm.
Speaker 6:And specifically on the radioactive materials they produce. And so what that does is that pushes the regulator you work with to the state level if you're in agreement state. So in Washington state, it's an agreement state. We work with the Washington Department of Health to license our fusion machines as particle accelerators. The process is essentially we design our radiation vault and do all the calcs with that, and then we apply for a particle accelerator license.
Speaker 6:They come in. They review it. They do a tour. We show them what we feel. They have some suggestions on how to improve it.
Speaker 6:And then a month later, I get, like, a letter in the in the mail from the Washington Department of Health with my particle accelerator license, which I hang on the machine, and now I'm licensed. So that's, like, pretty great, especially for, like, you know, at the point where we're building experimental machines. And then you contrast that with what Fission has to deal with. It's, like, many, many years of, regulatory work working directly with the NRC. It's a really, really tough process.
Speaker 6:And we haven't actually even licensed any of these small, SMRs that we're trying to, like, build here. Right? So I hope that Vision gets some regulatory relief in this administration. They definitely deserve it. We should probably talk about Texas and Utah that are suing, the NRC to try and, get regulatory control over small modular reactors.
Speaker 1:That's so much.
Speaker 7:Can you
Speaker 1:break that down for us? I saw a couple founders tweeting about that, but I didn't really have full context.
Speaker 6:Yeah. So I went to this, investor event in Dallas, Texas in December, that Valerion Ventures put on. And Rick Perry was the special guest seat speaker there. And I almost think I was in the room when this got decided, but, like, Rick Perry's advice to all the vision people in the room was you should join up with Texas. You should sue the NRC because there's some clause in the in the regulations that say the NRC has the right to regulate large power plants, but it's not clear they have the right to regulate some of these smaller things because the risks associated with them are so much less if something goes wrong.
Speaker 6:Yeah. And so I I like you know, Brent Kugelmes was in there from last energy, and he's, like, one of the main parties to the lawsuit. So I feel like I was, like, a an observer to history when the fission community decided we're gonna sue the NRC and get them out of Texas. And, and and if they if they succeed and Texas becomes the regulator for SMRs, that's gonna be really exciting in in terms of their ability to innovate and and go faster.
Speaker 2:Yeah. Can you talk about the positive some nature of sort of nuclear broadly? It feels like it's been so hard to build in the space that everybody just generally wants to see people be successful in the space. So maybe it actually creates a dynamic where
Speaker 1:Yeah. You don't see energy companies suing each other. They're suing the government, which is very different than what's happening in AI and every other Yeah. Startup. I don't see a lot of spying going on like we do in b to b SaaS.
Speaker 1:Seems like a lot friendlier community.
Speaker 6:It is. I mean, the fusion people definitely, you know, kinda get rid by the fusion people. It's like, only you could solve your science, blah blah blah. But, you know, I I want I want my fission siblings to to, you know, do awesome. I think there's room for both fission and fusion.
Speaker 6:I think my personal belief is that vision is gonna go bigger, like hundreds of megawatts to gigawatts, and fusion is gonna be really great from the kilowatts to a few megawatts. Mhmm. And fusion is gonna be really great for mobility and stuff. So, like, autonomous vehicles, fusion powered, like, Android Dive XL or something like that. Like, I think that's gonna be a really great application for fusion in defense and space.
Speaker 6:I I think the Russians are the only people crazy enough to put a fission reactor on, like, an autonomous vehicle. So I don't think that's a thing that's gonna happen with fission. But I think, you know, if you
Speaker 5:have lesson.
Speaker 6:I think if you have sites where there's people around, like guards and stuff, that's a great use case for fission. And it's gonna scale like nobody's business if they can get the regulators if they can get some regulatory reef and get some reasonable regulations there. So I'm really excited to see what happens over the next couple of years.
Speaker 1:Can you talk a little bit about lessons from the past two decades in, in rocketry and specifically lessons learned from how Elon and SpaceX approached, building rockets versus other players in the space and the decision to go more modular, smaller, higher iteration speed. I I I I've talked to you a lot about that, but I'd love to hear you kinda retell that story.
Speaker 6:Yeah. Yeah. I mean, the idea that like, so, like, I was at Blue Origin for six years working on New Glenn. It was super exciting to see it fly in January for the first time. And so, like, one of the things we learned there was, like, the importance of size.
Speaker 6:Right? If your rocket is too big, all of a sudden, there's only, like, three suppliers in the whole country where you can get castings made, and now you're at a nine month every iteration takes nine months. Right? It's just it's too slow. So, you know, that was the thing that we really tried to bring from NewSpace is, like, you don't necessarily know what the final answer is, but you need to be able to try things.
Speaker 6:You need to be able to try things quickly and have low barriers to build things and test things. And so that's that's sort of the key takeaway I took away from NewSpace, and we're trying to bring that to Fusion. Right? Like, very low barriers to test. We said at the beginning of Avalanche that we want a physicist to be able to go from, like, I have an idea to testing it in a week, and we've actually achieved that a couple times.
Speaker 6:Like, someone had an idea on Monday. They worked with the mechanical team to design it, and then we fabbed it on, you know, Wednesday, Thursday, broke vacuum on the machine, implemented it, pumped out over the weekend, and then off we were going testing on Monday. Like, we've hit that cadence a couple times, and it's really kind of exciting to see that happen. And I I believe that's how you solve really hard engineering and technical problems is you try it and you iterate on the thing, and eventually, you're gonna find something that works, and then off you go.
Speaker 1:Yeah. Can you talk a little bit about, the the pipeline of talent in the fusion community? Because it feels like there's a lot of, like, thankless PhD tracks that are more theoretical. But, again, I've been to the facility. It's a lot of wrenches and hammers.
Speaker 1:It's a very different culture, I imagine. But, what has that been like scaling the team and, and getting people to adapt to kind of the different style of experimentation and work?
Speaker 6:Yeah. That that's a really hard one. Right? There is not a lot of places you can go to learn how to do fusion. Mhmm.
Speaker 6:And so what we've taken is a very broad approach. Look. We'll teach you fusion. We'll teach you plasma physics, but you bring your mechanical engineering degree, your electrical engineering degree. Right?
Speaker 6:You, you know, we love people from Blue Origin, SpaceX, Tesla, who've kind of worked in that kind of an environment that, like, go fast, try stuff, iterate, stuff like that. And then we will teach you the plasma physics. Don't worry about that. And then we'll turn you into a fusion engineer, if you will. So I think that's kind of how we're gonna have to do things for for a while, until sort of the universities catch up and you can take a degree in in fusioneering, if you will.
Speaker 6:And, you know, I would love to put a couple fusion reactors on campus at some universities so, like like, programs can get some experience actually, like, operating them and building them and running them, but that's maybe something for a future
Speaker 2:Yeah. There are But we'd
Speaker 1:like one for the studio. Bring it in the studio in case the power goes out. We'd love that. Yeah. I mean, there actually are some small nuclear reactors, some fission reactors at, like, MIT, I believe, and some Yeah.
Speaker 1:And and and they work on them, and they produce a small amount of radiation. There's a little bit of risk, but it's
Speaker 6:much lower ocean. They're all over the country. Oregon State, you has one. I've been there. Like, I stood on top and, like, looked down at, like Yeah.
Speaker 1:Yeah. Yeah.
Speaker 6:Yeah. The fission. Yeah. Washington State, WSU has one.
Speaker 1:Last question. Up for me.
Speaker 6:They're called they're called trigger reactors.
Speaker 1:Okay.
Speaker 6:So they're used, basically for nuclear engineering programs to teach. You have like basically students like undergrads running these things.
Speaker 1:That's awesome.
Speaker 6:They're licensed by the NRC as nuclear Yeah.
Speaker 1:Yeah. Yeah.
Speaker 6:Unit operators or something like that. So
Speaker 1:I I have one last question. I mean, we saw everyone saw Oppenheimer, and everyone knows the progression of the the the the the fission bomb to the fusion bomb. If these if these, you know, if your devices really get baked into, you know, society and and autonomous vehicles, is it even possible to turn it into a weapon? I know, obviously, we'd want to be careful, but from a from a science perspective, like, what what is it just impossible?
Speaker 6:No. It's a it's a vacuum chamber. Right? And it needs to have very, very deep vacuum to maintain the plasma and do the fusion. Yeah.
Speaker 6:And so we actually had a machine break on us when it was running. So we had this cathode that was held on with the set screws, like, of the first janky machines we ever built. And this set screw came loose, the whole rod cathode fell through the bottom, hit the window, and, like, ended up on the floor of the factory somewhere. Yeah. And the whole thing just, like, imploded and spread glass all over the thing, but, like, nothing bad happened.
Speaker 6:Like Yeah. Sure. It's why is the cathode on the floor? What's going wrong here? I don't understand.
Speaker 6:Oh Yeah. If if
Speaker 1:your shit is
Speaker 6:gonna be very safe. You know, some of the conversations I've had with the DOD is like, well, what happens if I shoot it? Like, with a like, with a gun. It's like, well, same thing with the cathode. Like, it'll implode, and then it'll stop, but that'll be the end of it.
Speaker 1:Like Yeah. So Makes sense. Yeah. The the the real problem is just getting it to produce energy and that's that's the path you're on.
Speaker 6:It's hard enough. Right?
Speaker 1:Yeah. Yeah. It's hard enough.
Speaker 6:It's hard to it. It's battery.
Speaker 2:Can you be before you leave, could you give us like a one minute rant around the the, you know, when fusion is really working and we have these sort of small, I don't know exactly sort of like cooler sized devices that can create energy. Yeah. Where where are all the places that we're gonna put
Speaker 1:them all Yeah. Black Mirror just dropped. I wanna hear the white Mirror version.
Speaker 2:I understand like the DOD applications but like, yeah, is it like backup power, you know, at when when a Hollywood, you know, if if they even make movies that in person, is it, you know, you know, for your house? Right? Like Yeah. You know, what are the what are all
Speaker 3:the different use cases you're excited
Speaker 1:future.
Speaker 6:I want the Adam Punk The practical one is they're probably gonna be containerized and you're probably gonna just be shipping containers all over the place, like, powering a neighborhood. You know, that's, like, probably what's gonna happen. Mhmm. Can everyone wants this containerized one to five megawatt form factor, it seems like. So that's, like, probably what's gonna happen.
Speaker 6:But, like, the atompunk, like, future would be, like, you're driving around and you've got one in the trunk of your cyber truck and, like, you don't have to, like, you know, supercharge if you're going to Eastern Washington because there's actually not that many charging stations. You could just, like, flip on the fusion reactor and go go on fusion power.
Speaker 1:Pretty
Speaker 6:awesome. I've driven around San Francisco in the DeLorean with a plastic three d printed fusion reactor last year at Deep Tech Week. I'd love to do that with a real one someday. So
Speaker 1:That'd be fantastic. Well, thanks so much for stopping We'll we'll we'll talk to you soon. Congratulations on the launch.
Speaker 2:Yeah. Congrats.
Speaker 6:Thanks. Cheers.
Speaker 1:Thanks, Bye.
Speaker 3:Take care.
Speaker 1:Hopping on next, got Russ. Is that right? Yes. From LiveKit IO.
Speaker 2:That's right. That's right.
Speaker 1:Coming into the studio. We got our next guest joining.
Speaker 2:Some big news.
Speaker 1:Big pivot from watches to fusion reactors. But that's the nature of the show, folks. We're we're we're we're men of many talents. We keep
Speaker 2:you on your toes.
Speaker 1:Keep you on your toes. We'll do dedicated days where there's one theme. Some days, you just get a tour of the entire technology industry. So welcome to the studio, Russ. How are doing today?
Speaker 8:I'm good. I'm good. Alright. So you're saying that I'm following fusion Reactors?
Speaker 1:Is that correct? You're following Fusion Reactors and immediately before that, we were talking about fine watches made in Switzerland.
Speaker 2:So we got a little bit of everything today.
Speaker 1:Taking us on a whirlwind tour.
Speaker 8:I don't know if I can follow Fusion Reactors, you guys. I'll try my best.
Speaker 2:Well, we're excited to talk about Voice AI. Yeah. But why don't why don't you introduce yourself and the company, and then we can talk about the news and go from there. Sure.
Speaker 8:Yeah. So I'm Russ. I'm the CEO, cofounder of a company called LiveKit. LiveKit. Yeah.
Speaker 8:So LiveKit, what we we started actually as an open source project. So back during the pandemic, you know, if you think about all the technology that Zoom has underneath, we started an open source project that kind of built something similar to all the technology that underpins Zoom, but as a an API for any developer to integrate similar type of technology into their app. So you could connect any two people or any number of people on the planet kind of instantly with less than a hundred milliseconds of latency over video and voice. Fast forward, like, about a year and a half, two years, and we built a demo when ChatGPT first came out, where you could talk to it instead of text with it using LiveKit's infrastructure. And a few months later, OpenAI ended up finding it, wanted to build a voice interface to ChaCiBT, and we started to work pretty closely with them on voice mode and then advanced voice mode after that.
Speaker 8:And, kind of almost by accident, I guess, we got, pulled into, this AI space. Voice AI, it was not a space back then.
Speaker 1:Yeah. I remember
Speaker 2:the accident.
Speaker 8:Yeah. I remember our series a, which we closed at the we closed the first tranche at the end of twenty twenty three, '20 '20 just at the start of '24, and everybody was just telling me that, hey, this is cool, but voice isn't gonna be a thing for three to five years. And then, of course, GPT four o happened and Yep.
Speaker 2:Now, just say,
Speaker 1:can you steel man at all why speech to text is still bad on my iPhone? I I just really want it to be good.
Speaker 2:There world John's a big voice guy. He's always he's always he's always using LiveKit unknowingly.
Speaker 1:I worked at I worked at a voice AI company in 2010 or something like Twilio. Yeah. It was a you know Dragon NaturallySpeaking?
Speaker 8:I do. Yeah.
Speaker 1:Yeah. Dragon eventually acquired this company, and it was, like, it was direct competitor to Siri. Apple bought Siri, and Vlingo was purchased by Dragon. Their primary
Speaker 2:it was such a fun fact. Think
Speaker 8:you can
Speaker 1:remember Vlingo, actually. Yeah. Vlingo. It was a it was a good company. I think it was a good good exit for everyone involved too.
Speaker 1:Yeah. And their their primary target was BlackBerry. You would and their whole goal was let's get preinstalled as BlackBerry, but there were a lot of there was a lot of chaos in the market at the time with, it was a $20 app, then they had to cut their pricing, do an ad model, all these different things going on. But I'd I'd love to know, like, just if you were in charge of, you know, Apple, how would you improve speech to text?
Speaker 8:Speech to text specifically, like transcribing text?
Speaker 1:Oh, well, well, anything in in voice agents or just I just Yeah. Just improving the customer experience broadly, like surprise and delight. Right?
Speaker 8:Well, you know, it's one of those things that that I think is funny, like people talk about hallucinations as this bad thing. Yep. But in a lot of ways for, like, kind of this speech to speech interaction model where you're talking to an AI Yeah. Hallucination is a feature. So if you remember, like, your Alexa or Siri, like, when you were talking about this, you know, 2010, '20 '12 Yeah.
Speaker 8:You go and you ask it a question and it's just going through a bunch of, like, a a decision tree. And Yep. If it hits, you know, a dead end and it can't answer the question, it just doesn't do anything or it says I can't answer the question. And so the the second that it it can't do something you expect it to do, all of a sudden, you you know, it's a it's such a punishing user experience. You just don't want to use the thing anymore, and you stop using the thing.
Speaker 8:But with
Speaker 2:kind
Speaker 8:of these new models that actually, you know, hallucinate answers into existence, even if it doesn't know the answer, it tries, you always get a response that comes back from the model. And for for like voice interfaces, that actually can be more of a feature than a bug. It also helps that these models
Speaker 7:Yeah.
Speaker 2:It's funny because human. Right? So like Yeah. If you're having a conversation, John asked me a question, I don't know the answer. I go, well, like, is it like this thing?
Speaker 2:And you're like, no, it's this thing. And like but but for some reason with like a like, you know, these older generation of models, it was like very annoying to like Totally. Go down that wrong sort of
Speaker 8:Exactly. And it's always the same answer. Right? It's like, I don't know or I can't help you with that. I can't help you with that or I'll I'll search Google for you or whatever.
Speaker 8:And so I think that like just having these LLMs that have ingested the entire Internet and can always generate some plausible answer for everything, whether it's a % correct or not. I think that that just makes the user experience so much better with these kind of modern or contemporary voice agency you interact with. Yeah. So, you know, I I I think the the other thing I'll say related to the Apple stuff and that's improving very quickly is the latency. So, like, we have a lot of providers out there now, Grox, Cerebris, folks like that who can run inference much faster than even a year ago for for some of the model providers.
Speaker 1:Yeah.
Speaker 8:And now, like, LLM inference can actually be done in less time than generating speech with with TTS. And so I think, like, getting that latency end to end down by, you know, two, three hundred milliseconds or five hundred milliseconds on average for, like, turn latency, that that that kind of helps you cross this uncanny valley for for voice AI.
Speaker 1:I mean, should we be thinking, like, even faster than three hundred milliseconds? And is there any efforts that you've seen to bake some of these models down into silicon? We've seen what Etched is doing with putting the transformer architecture on silicon. You could imagine that once mid journey gets good enough or kind of hit some some peak that they would just bake it down into silicon, and we would just have image generation models, you know, ASICs, essentially, like what happened with Bitcoin. Is that the future here?
Speaker 1:Not that you would pivot into hardware, but maybe you would, then do your software into a hardware provider at that at that level?
Speaker 8:Well, so we, like I mean, we partner with, like, folks like Cerebras and Sure. And we allow you to kind of plug in their models and plug in effectively their hardware accelerated inference.
Speaker 1:Mhmm.
Speaker 8:And and so we're we're compatible with that world. I think on the inference side, you can definite I think it's gonna continue to push as low as it can get. There there's obviously some limits. You know, it's a trade off between kind of capabilities and level of knowledge and how fast you can kind of kind of, you know, run that that pass through the model to get the result out. So there are trade offs, of course, that follow the laws of physics, but there's also kind of diminishing returns after a while.
Speaker 8:To give you an example, I once built this this Cerebris demo. I used like a Llama seven b or eight eight b, Llama eight b. I have to remember these numbers on the primer accounts. But, llama eight b hooked up to Cerebras, and, I got a bunch of feedback on that voice demo that the model was responding too fast. And can you slow it down?
Speaker 8:And it's kind of going off the rails a little Yeah.
Speaker 1:Yeah. Interesting. I I mean, on that note, is there a it's kind of like like at inference time fine tuning that needs to happen on the voice agent side to give the human listener the appropriate interaction. Like, some people wanna have, you know, this really fast back and forth conversation, and I'm like, just get to the point. You know, I'm just trying to book a flight.
Speaker 1:Can I just, like, just give me the information as quickly and and condensed as possible? Other people might might prefer an agent that speaks slower and really draws things out and gives the full context and then lets them answer and and kind of ping pong back and forth that way. Is there any movement towards, like, that level of fine tuning that you think might happen in the future? Is it already happening? I don't know.
Speaker 8:Yeah. It's already happening. So I think that there's kind of two, different flavors of this, and you can kind of combine them together, over time. So the first one is that if you've interacted with, like, the the real time models, like the ones that are so there's OpenAI real time API. There's Gemini multimodal live API.
Speaker 1:Yep.
Speaker 8:There's a few others coming out as well. And for all of these models that natively understand audio, you can actually tell them to, you know, whisper or slow down or speed up or act hyper. You can kind of give them an explicit signal of the style or the way that you want them to communicate with you. So that's already available and possible with these models. Then there's another part of it, which I think will come in the next, you know, year or two, where the model will implicitly be intelligent enough to pick up on what your pacing is or your state of mind is just based on the way that you're talking and expressing yourself.
Speaker 8:Yeah. And also, if we weave computer vision into it, it might see you and understand from visuals, okay, this person is stressed or this person seems like they're
Speaker 5:in a
Speaker 8:hurry or this person is calm and like relaxed and you can kind of tell that by your body language and by the way you're speaking and it can automatically adjust you in the same way a human would be able to.
Speaker 2:So you guys work with a lot of the biggest companies in voice already, OpenAI, Speak, CharacterAI. You're working with Tinder. I see, like, really broad swath of companies, Spotify, Spotify, Oracle, things like that. Are you seeing as many startups as you would like sign up and start building in Voice AI? It feels like a category that for if you go back like five years ago, people were really excited about voice, but then you had these sort of like high profile companies that didn't quite work, but you know, maybe in in many ways they were just too early.
Speaker 2:So what are you seeing on the on the start up side in terms of new companies being formed specifically to leverage voice and and LiveKit and the underlying models?
Speaker 8:Yeah. We're seeing probably about you know, we're doing like thousands and thousands, many several thousands of of like sign ups to the to the cloud product, our commercial product, and most of those, the vast majority are are start ups and growing companies. And out of those, probably around 75% or so, 80% of those sign ups are are voice AI companies that are building voice agents. And so the way that I kind of see the market segmented to a degree is that you have the large AI labs, and they have popular, you know, consumer apps. And a lot of them are building kind of open ended voice agents that you can to about kind of anything.
Speaker 8:Right? They're assistants. You can they do question answering. They do therapy for mental health, all kinds of language learning in the case of speak. And then on the other side, you have these kind of pockets that are what I call kind of voice native systems.
Speaker 8:And those are really anything you pick up the telephone to you know, when you call someone on the other end, call a business, there's someone that answers that line and they're either, you know, doing patient intake at a hospital or they're doing loan qualification or insurance eligibility checking. There's a lot of these kind of business process flows where these are there are pockets that are, like, really large in nature. So customer support is the one that gets talked about a lot. Right? Like, some of the markets at Sierra, Decagon, and folks like that are playing in.
Speaker 8:And so for all of those systems, we're seeing tons of startups flood into those spaces because it is now viable to take an LLM and have like a voice stack like LiveKit for example, that's hooked up to that LLM and and you can build like an automated version of whoever is picking up the phone on the other end.
Speaker 2:Well, yeah. The thing the thing that I'm excited about, everybody's gotten on one of these like robo CX calls and you you know, I've had the experience in the past where I just say talk until I get to a human because I know they're not gonna resolve like the issue the way that I want and I'm like the annoying guy to the robot. Yeah. Hammer. But but I do feel like there's a point here quickly where the AI can be considerably better than the human on the other end because they're not tired, they're not in a bad mood that day, like, you know, they're they're really, you know, they they just have like high energy because they're code.
Speaker 1:Right? There's gonna be a flipping and it's gonna be like, oh, I'm talking to a human. Robot, robot, please put me on the robot. Yes. Throw
Speaker 7:me on
Speaker 1:the robot.
Speaker 8:Yeah. I was I was on a customer support call with Comcast Yeah. The other day and I was talking to a human for sure and they were trying to look up something for me and then they started asking me if I'd ever seen the snow and if I'd ever spent time in the snow. And I was like, what? And where do you live?
Speaker 8:And I'm like, California. They're like, so do you experience snow in California? I'm like, well, in Tahoe. Yeah, I guess. But it was so weird.
Speaker 8:And I was just like, am I talking to an AI right now or is it a human? And if it's a human, I kind of want the AI and
Speaker 1:so Yeah. Yeah. It's very bizarre.
Speaker 8:Super awkward.
Speaker 1:Can can you tell me about some of the more like nuts and bolts enterprise customers you're working with? I see this case study from Playback. We actually had the CEO of Playback on the show.
Speaker 8:Oh, nice.
Speaker 1:Live streaming for sports makes a ton of sense. Do you know exactly how they're leveraging LiveKit and how you can, kind of give us a more concrete example of, like, their infrastructure, basically?
Speaker 8:Yeah. For sure. So Playback, they're also gonna integrate, you know, AI into that flow as well, like a voice based commentator or whatever that can watch the game and
Speaker 2:Sure.
Speaker 8:Provide an overlay for for fans. But they use us for a pretty different use case. In that case, they they have these kind of courtside cameras at, like, NBA games, MLB games, and all of that. And these cameras are, you know, the way that you watch sports on TV. And so one interesting part about and this is kind of like a deeper technology thing, but one if you've ever watched like the Super Bowl or the NBA finals or any any sports game on a TV and then, like, you're texting your friends about it and they're watching the game or there's someone in another part of your house that has the game on on a different TV, you'll notice that you're not synchronized.
Speaker 8:Like, you're seeing plays before they are, sometimes up to, like, thirty seconds or a minute before. And so the technology that we use for live broadcast of sports games is not true real time technology. Not everyone is synchronized. In the same way that in 1969 when the, you know, the lunar landing, everybody saw that at the same time because there's a server that is sending all these kinda broadcasts out over, TV antennas that are receiving these things, and, it is truly a shared experience. And so playback, what they do is they ingest, the the video feed from these cameras at courtside or at the MLB game, and that's they're ingesting it using LiveKit.
Speaker 8:That goes into a single system, and then LiveKit's cloud network effectively, Everybody who's watching that that NBA game, for example, we are effectively shuttling those bytes from that camera in a synchronized way to every single person that's watching that game. So when, like, Steph syncs a three, everybody who's watching that game through playback is seeing that three get sunk at the same time, able to truly have a shared experience of watching their favorite team play the game together, cheer together, all of that stuff. And so playback is effectively using us for the backbone of all of the audio and video kind of transmission that is going on within their application.
Speaker 2:Makes 10¢. Before we let you go, we should probably talk about the news today. Yeah. You guys had a bit of an announcement. Why don't why don't you share a little bit there?
Speaker 8:Yeah. For sure. So kind of how I mentioned at the start. Right? We started as an open source project, you know, connecting humans to other humans.
Speaker 8:But now we have found ourselves kind of operating at a very large scale connecting humans to machines. So using voice and and computer vision and and so we we closed a series b today that's led by Altimeter Capital. Go. Let's
Speaker 2:Let's go.
Speaker 8:Yeah. So we we closed that round and now we're we're really going after voice AI. We're building like an all in one platform for anybody, any developer to build a a voice agent.
Speaker 1:Give us the stats. 1,000,000, 2 million. How much did you raise?
Speaker 8:45,000,000.
Speaker 1:40 5 million.
Speaker 2:I gotta do 45 hits. I'm not gonna I'm gonna submit it to that, but Amazing amazing milestone. I I think, you know, clearly like a a Product market. Five five year overnight success.
Speaker 1:Yes. Yes. Classic.
Speaker 2:Classic. Classic example. But it's cool. I I love these stories where where you sort of work on a really hard problem and then discover like, you know
Speaker 1:Entirely new use
Speaker 2:case. Powerful application, you know, years later. So congratulations to you and the teams. Great to have you on. You can be our new official voice AI infrastructure correspondent.
Speaker 8:Love that I'll I'll just make I'll make a clone of me and then that will be your official voice AI correspondent.
Speaker 1:Cool, guys.
Speaker 2:That's perfect. That's perfect.
Speaker 1:Well, thanks so much for stopping by.
Speaker 2:Yeah. Thanks for coming on. Really
Speaker 1:appreciate it.
Speaker 8:Thank you, guys.
Speaker 1:Talk soon.
Speaker 2:Talk soon. Cheers.
Speaker 1:And next up, we got Ev Randall coming in from Kleiner Perkins.
Speaker 2:I love how, like, there's always, like, you can always go niche enough to make somebody a
Speaker 1:correspondent. Exactly. Hyper hyper niche. Anyway, $45,000,000. That's a great that's a great round.
Speaker 1:We there are so many funding rounds happening. Now that we're, like, in the thick of it, I'm realizing, like, wow. Like, the money is flowing in Silicon Valley. It's great. But we will get a full market update from Ev, hear what he's seeing over at Kleiner.
Speaker 1:Actually, crossed paths with them at Founders Fund two years ago, maybe two and a half years ago. Great dude. Wrote one of the most probably banger memos during the Zurp era all about Tiger Global and crossover investing, and I wanna follow-up with him on that. But I think we have him here. Ev, are you there?
Speaker 1:Welcome to the studio.
Speaker 4:Hey, guys. Jordy Kugen. Great to be here. Longtime friend of the pod.
Speaker 2:Finally, dude.
Speaker 1:It shouldn't have taken it should not
Speaker 2:this long.
Speaker 1:You're in our original pitch deck because you posted, like, how can I go long, which hilariously caused a lot of problems for us because someone created a fake, pump dot fund token about us, And everyone would say, oh, they endorsed this? We're like, no, we did not. We just
Speaker 5:Yeah.
Speaker 4:By the way, I didn't get rich off that. So that No. That is a I I have a bone to pick with either the creators of the coin or you. I don't know
Speaker 1:which Don't even joke about it. It's just Don't
Speaker 2:even joke about
Speaker 5:it. What.
Speaker 2:If you say anything, they'll
Speaker 1:They will they will turn it into a into a coin.
Speaker 2:Anyway But it's great to have you.
Speaker 1:Thank you
Speaker 2:for the early support. Why don't you John gave a little introduction, but why don't you introduce yourself?
Speaker 1:Yeah. Yeah. What are you what are you working on most recently? What's interesting?
Speaker 4:Yeah. Of course. Yeah. So I'm a partner here at Kleiner Perkins. KP, obviously, one of the more storied firms, kind of in venture capital history.
Speaker 4:As a firm, we've led early rounds of, you know, companies like Amazon, Google, Genentech, Sun Microsystems, more recently companies like Rippling, Figma, Glean, Harvey, and many others. You know, ventures evolved dramatically, obviously, over the last five years, but especially over the last decades. And I think what made KP special back then is what makes it special now is that we're a very small team. There's 10 of us total on the investment team, and we all just care very deeply about the craft of venture, founders, company building, and and we wanna keep it a craft. So we I mean, we're fully multistate, so we have an early stage fund.
Speaker 4:We have a growth fund. We announced a new set of of funds last summer that were 2,100,000,000 in total size. We can do see through pre IPO. I personally help head up our growth fund. So I spend, you know, the vast majority of my time kind of on series b and beyond investing, but all of us invest across the venture and growth funds.
Speaker 4:So I've led, you know, our investments in companies like Flux Safety, Huntress, a cybersecurity company, Captions, involved in our investment in Rippling, and a few others soon to be announced.
Speaker 1:How would you how are you processing the tariff news? Were you just texting every portfolio founder like, hey. Have you seen this?
Speaker 4:Yeah. Sending them a sending them a
Speaker 1:A screenshot of the NASDAQ. Fifteen percent. What are doing about this? Hey. Wait.
Speaker 1:Oh, yeah. Can you fix this?
Speaker 4:Hey. Hey. What are we doing about this? Yeah.
Speaker 2:I Is there
Speaker 1:a memo coming? Is there a black swan memo? Are you gonna get in the black swan memo game? Give Sequoia a run for their money?
Speaker 4:Sequoia has pretty good market share of the of the black swan, you know, memo Yep. Market. And so it feels like, you know, it feels a little too memetic. I'm I'm a little too Totally. Chill pilled still to to do something that memetic.
Speaker 1:Yeah. Well but, I mean, how have you been processing it? Do you think it affects tech? Do you think it affects any of the I mean, like, immediately, the reaction was, like, all the all the Nasdaq was way down, but at the same time, like, even semiconductors were, you know, on day one kind of excluded. Was there is this something that all founders should just tune out, or is there something here to pay attention to?
Speaker 4:I think I think it's it's probably both. Right? Like, I think, I think Mike Mignano from from Lightspeed had a good tweet or or post today or yesterday where, he was like, I'm getting a lot of questions from maybe it was LPs about the tariffs, and they have to to realize, you know, I invest in companies that aren't gonna exit for seven to ten years. Yeah. And so there's, like, something about the, like, duration of the asset class where, you know, something like economic turmoil that happens today if you're investing in the venture asset class isn't going to necessarily impact, like, your your exit because ultimately the founders and the board and the management team have some control over when they exit.
Speaker 4:And so you you can kind of theoretically wait a little bit for for a better environment to to either IPO or sell or whatever you wanna do to get liquidity. I think at at the same time, the the, like, underpinning like, the undercurrents of what's going on, especially politically, are immensely relevant for for startups and tech. Like, obviously, everything around Taiwan and and just, like, semiconductors generally. And escalated how bad it would be for not only technology companies, especially in AI, but, like, just our day to day lives. Like, I think our day to day lives would would pretty much come to a halt.
Speaker 4:And and I don't think that people really have an appreciation just for how permeated, you know, semis and other critical materials and inputs from from places like Taiwan are in our day to day lives. So I think it's it's of of critical importance. But, it's like it's one of those things where it's like, well, what are you gonna do about it? You know? Unless you there there's very few, you know, there's very few companies or or or folks that can actually have an impact on this.
Speaker 4:And so I think for most companies, the the best advice is always just to go heads down and and
Speaker 2:Well, yeah. Let let's talk about one of the immediate impacts, which is the IPO window, which was so briefly opened, feeling like it slammed shut. I love when it's open, personally. I I wake up I wake up. I I get out of bed.
Speaker 4:You're a fan of open windows.
Speaker 1:Huge fan of open IPO windows. Not so I
Speaker 2:get up. Yeah. But but poor poor Klarna and StubHub, you know, they've they've been waiting around.
Speaker 1:Moment of silence?
Speaker 2:I don't know. Moment of silence brought to you by No. But yeah. I don't even know if, like, you know, Circle gets out at this point. But at some point, you can imagine the companies that end up going out are the ones that have to go out.
Speaker 2:Mhmm. And then that just becomes a vicious cycle where they maybe underperform because they're not these sort of best in class companies. And then it's like, well, it's really shut now.
Speaker 1:Yeah.
Speaker 2:We're not gonna touch it. But what's your what's your kind of read on on that situation?
Speaker 4:Yeah. I think mean, obviously, before before this all kind of blew up, obviously, it was unfortunate that there was, like, you know, four or five IPOs kind of on the shelf ready to go right when this blew up. And so so it it seemed like, ah, you know, we're we're opening things back up, then, immediately, black swan event happened, it kind of shut it back down. But for for, you know, like, a full almost nine to twelve months before that, it was a solid environment. It wasn't, you know, IPO ing in 2021, where where you could go and, you know, SPAC for 50 times ARR or something, but it was not a bad environment.
Speaker 4:And I like, I kind of have a slightly orthogonal take on the IPO window, which is there's this kind of, like, rock and hard place situation for the IPO market, which sums up to, like, one, do the IPO markets want you? But then also, just as important, like, do you want the IPO markets? So on the first one, I went and counted this morning the number of public software companies on, you know, the Meritech kind of software comparables index that they run that currently have over $500,000,000 in ARR, which is like an incredible achievement. And right now, there are over 80 public SaaS companies that have more than $500,000,000 of ARR. Wow.
Speaker 4:So if you want exposure to some trend or idea and you want it to be a big company that is profitable, there is very likely a public SaaS company that can give you exposure to some theme or trend or idea that that you want that already exists. So it is much, much harder today to have an IPO that bankers, long only public funds, like the people that make the IPO machine work, it's much harder to have an IPO that they're gonna care about. Like, you probably need to be free cash flow positive. It probably helps a lot if you're closer to a billion dollars of revenue scale than even $500,000,000, which is already incredible. And you need to have some unique angle or something that's really cool or or unique in the story, like the qualitative kind of framing of your IPO that's special.
Speaker 4:So I think, like, one, that's, like that's already hard enough. And then on the other side, in terms of, like, do you want the IPO markets? I think what we're seeing out of several of the very, very best tech companies is is that they've gone to pretty drastic measures to not IPO. And I think there's, like, many reasons why you'd not want IPO. So SpaceX obviously, is kind of the poster child of this, but then you saw Stripe obviously do that that really large kind of, like, RSU catalyzed round, at, like, $55,000,000,000, I believe it was.
Speaker 4:Databricks, obviously, in q four did a mega raise for the same reasons. And the asset class has grown so much that if you're an amazing company, compounding your intrinsic value at 25, 30 percent a year at scale, you can raise practically unlimited capital. Like Databricks raised 10,000,000,000 of equity. They did a, you know, multibillion dollar debt raise too, but 10,000,000,000 of equity in, like, I think, know, it was probably, like, three months. Like, it didn't take very long to raise an unbelievable amount of equity.
Speaker 4:So so the the fund sizes have gotten so large and the amount of capital that's available for these companies is so large as long as you're one of these, like, top 10 companies. But if you don't wanna IPO, you don't have to. And I think there's several reasons why you wouldn't IPO. The main one or one of the main ones is that you can be a lot more aggressive on m and a. You know, Databricks, for example, you know, bought this company Tabular.
Speaker 4:I think the reported valuation was 2,000,000,000, and it was also reported that they were either pre revenue or close to pre revenue. If you're, you know, Snowflake and you're a public company, you probably can't buy a pre revenue company for $2,000,000,000. Like, your stock probably goes down 20% the next day. I almost
Speaker 7:said I
Speaker 4:almost said effing, but I think
Speaker 6:this is
Speaker 4:a PG show, so I'm not
Speaker 1:gonna Thank
Speaker 4:I'm gonna cuss. But, you know, the stock probably goes down 20% if you do something like that. That's an extremely strategic acquisition that Databricks is able to do because it's completely founder controlled. No activist can buy 10 to 15% of your stock. No one can mess with you.
Speaker 4:So I think there's good reasons to do it. And the only thing that you have to figure out if you don't want IPO is you have to give employees liquidity. Like, you have to give employees regular opportunities.
Speaker 2:We we love when employees get liquidity, but what about if you're a, you know, just a $2,000,000,000 fund and, you know, you're trying to show DPI to your LPs, are you seeing these sort of funds that, you know, like KP that there's now funds that are like effectively like four or five times larger and then these sort of crossover funds that are getting involved? And are you seeing more like do traditional venture funds like KP ever try to sell into these rounds that are intended more for employee liquidity? Is that Mhmm. A potential future if companies are just staying private?
Speaker 4:Yeah. I think we're we're just now in the early innings of this. Mhmm. But we are a % starting to see it. We we certainly have not done, like, a a continuation vehicle.
Speaker 4:It's it's kind of like the most common term for this, like a CV where you can sell essentially like a slice of your fund. Because commonly venture funds have like a ten year life and then sometimes you can have an option for like two years of extension. And then after that, you're kinda supposed to be have the capital returned and, like, everyone can move on with their lives, hopefully hopefully much richer for it. And and, you know, SpaceX has been a private company for, what, twenty years now? You know, over twenty years.
Speaker 4:And so I think the the most common vehicle for this would be a a a where you sell either, like, a bundle of company like, a slice of your holdings or, like, a slice of your fund, and you're starting to see that. Like, several funds have done that. I think I think NEA has has has done it in the last year or two, you're seeing more funds do it. We certainly haven't done that before. But I think as an asset class, we're gonna have to start coming to grips with the fact that the liquidity timeline for these amazing companies is very different than it used to be.
Speaker 4:And it it's actually really flipped on its head because it's almost like the better the company, the longer they wait to IPO because they can be private, again, compounding their value at 30 plus percent IRRs for much, much longer than they used to. And so obviously, you can sell in these rounds. Like, I think like, obviously, SpaceX SpaceX is extremely liquid. Stripe is pretty liquid. Databricks, I think, is, like, very liquid.
Speaker 4:There's some names that are very liquid, but it's only the best names where that exist. And so if you have a portfolio of of names that are good but not like SpaceX level, call it, then then your your best bet is probably one of these CVs, which is which is very, very common in private equity. But as venture kind of becomes more more institutionalized, we're gonna see a lot more of them for sure.
Speaker 1:Speaking of DPI, it seems like you
Speaker 2:got
Speaker 1:some mathematical formula behind you. Can you break that down for us? Are leaking alpha right now? What's going on? Yeah.
Speaker 1:Just copy paste that and I get your returns?
Speaker 4:Yeah. I, I was trying to figure out the equation for DPI.
Speaker 1:Okay.
Speaker 4:I've been searching for a long time. That's the first one. The second one, I was also trying to find the equation for Delian's gross margins on his investments. Oh, yeah. That one that one actually might be that one might be harder to find than for DPI.
Speaker 4:Yes. A little little Easter egg for those fantastic out How
Speaker 2:do you and the team decide if something is in the wheelhouse or not? Obviously, 10 people on the investment team. I'm sure you get pitches all the time where you're excited about the entrepreneur and and kind of their vision, but maybe feel like it's not, you know, right in in in the wheelhouse. But, you know, clearly, you know, you're doing flock safety to these other sort of like app layer companies clearly willing to kind of, you know, look everywhere for opportunity.
Speaker 4:Yep. A hundred percent. Yeah. I love to say that there's, know, a lot of people talk about Conway's law, which is like you ship your org chart and and as it relates to to kind of like how companies mature and ship product over time. And I love to say that, like, Conway's law exists for venture firms for sure, which means that you, like, you invest your org chart.
Speaker 4:And it's, like, very hard to, you know, have an investment strategy or a portfolio construction strategy that doesn't match the size and kind of scope of your team. So for our team, seven partners, 10 total on the investment team, what that means is that, like, if we want to be company builders, if we wanna be involved in our companies, we can't do that many investments per investment professional. Like, we we need to we need to really stay concentrated and stay tight. I think you also see this at at my, you know, my previous employer, Founders Fund. You see these these headlines where they're doing massive, massive checks into really high quality companies, and I think it's because it's also a small, really lean team that has the trust and a high degree of relationship with really strong founders.
Speaker 4:And I think we we approach, especially growth investing with the same model. Each of our growth funds is typically only 10 to 12 core investments. And so every single investment that we're looking at needs to have something very unique or special about it where, we can, you know, look around the table and say, this is gonna be a company that we're talking about on TBPN in ten years, as as, you know, one of the top five companies in the world. Like, it has that potential every single time.
Speaker 1:Can you take us through a little bit of a retrospective on playing different games now that it's been, I guess, four years in two days? April twelfth twenty twenty one, you dropped playing different games or why Tiger is eating your lunch and your deals. This cycle, it feels like we haven't no crossover funds have really made a name for themselves. But at the same time, Databricks is doing bigger deals than ever. There must be new pools of capital coming in.
Speaker 1:What does the late, late, late stage look like, and how is it changing?
Speaker 4:Yeah. So it it's funny. I actually dropped a sequel to playing different games, like, very quietly. I initially wrote it in 2022, and it was one of those things where, like, I think it's, like, solid, but it's just nowhere near the banger that playing different games was. And so I had a lot of, like, sequel anxiety about it.
Speaker 4:And so I just, like, kinda, like, quietly put it out there because I'm like, ah, like, my thoughts should probably be out there. Yeah. But it's called game over question mark, and you you can go read it on my Substack. And I I think it it's held up pretty well since I wrote it in 2022. And I think the, like, overarching message from that, and and I use a a Game of Thrones analogy in in playing different games, so I'll use one for this too.
Speaker 4:There's, like you know, there's a a part in Game of Thrones where, you know, spoiler alert if anyone hasn't watched the show, where, like, Roose Bolton for a while is this, like, lord who's kind of, like, one of the big bads. He's one of the main bad guys. And he gets killed by Ramsay Bolton, his son, and then you realize like, oh my god. This guy is like so much worse. It's like he has like the scope of his destruction is like so much greater than like this guy was actually kind of a pedestrian bad guy.
Speaker 4:And I think the kind of version of that that happened to our asset class is that obviously people saw Tiger kind of fail the marshmallow test of like they went too far too quickly Mhmm. And kind of stretched the bounds of what you could do, and and definitely paid the price for it. But instead of Tiger, you know, continuing to be this large platform, you now have, like, four other platforms that were actually established in those days of 2021. And so it's like, okay. Yeah.
Speaker 4:Like, you don't have Tiger, but, like, how big is Andreessen's last fund? And how big is General Candace's last And how big is Lightspeed's last fund? There's, like, four or five of these folks that have, like, filled that gap, and continued what I think is, like, a, like, a a secular trend towards platformization in the asset class. I think that the to your specific point around, like, our crossover is kind of, like, coming back into venture and and playing in in the asset class again. I think the most important thing here is that, like, venture means at least, like, four or five different sub asset classes.
Speaker 4:Right? Like, venture includes growth, but then, like, investing in a in in in a you know, in Tropic at 62,000,000,000 and investing in a hundred million ARR company that's growing, like, 20% at, like, eight times ARR, both of those are called growth investing
Speaker 1:Yeah.
Speaker 4:But they're, like, the like, as different as you could get in every single way. Yeah. So like our crossover is doing venture again, think, yes, but they're sticking more to their knitting. Is like do you have capital doing series b's? Like, no.
Speaker 4:But they're you know, I know several crossovers that have invested in, like, majorly in the big labs, for example.
Speaker 2:Mhmm. Was there any investments that Tiger did that you wish you did? There has to be there has to be some. Right? Because, I remember FTX was, spraying money, like, crazy too, but then they invested in Yeah.
Speaker 2:Anthropic and, like, they kinda made it all back in one trade. Right? So do you and and Tiger hasn't I I don't have a full list of of their investments or anything like that, but do you think it's possible that in the fullness of time they just did okay or did they actually light money on fire?
Speaker 4:You know what's funny? I mean, this is probably just a rumor. So this is you know, assume this is total hearsay, but I I had heard that there was, like, maybe an internal, like, you know, justice for John Curtius trend at at Tiger where, like, you know, like, he he did push them to get into Databricks and that's gone really well and it's like a truly generational company and it's probably gonna be an amazing investment for them. So I don't know their full investment track record and returns, but I do think there is like a potential where like, I don't know if Databricks is a $500,000,000,000 company, you end up with like a pretty good portfolio even though you had a bunch of strikeouts. Like I think if you look at someone like Neil Mehta's track record, it's like is his hit rate like 90%?
Speaker 4:No. There's like a ton of flame outs in there. But he's just invested in situations where he's put, you know, 400 in and gotten 5,000,000,000 out. And it turns out, like, if you just do that at even at the growth stage, like, power law still exists and you still have like an amazing track record. So, I mean, they're they're huge investors in Waymo.
Speaker 4:This is Tiger. Would love to be in Waymo, I think. I mean, it's like an unbelievable technology company. Obviously, they they're huge investors in Databricks. I'm sure there's lots of investments like that for them.
Speaker 1:Yep. That's fascinating. Well well, this was a really great conversation. We'll have to have you back really, really soon because I'm sure we could talk for two hours
Speaker 2:Yeah. About Yeah. Let's make it a regular thing. Yeah. This is great.
Speaker 4:Anytime, guys.
Speaker 1:Thanks so much.
Speaker 4:Thanks for having Thanks
Speaker 2:for the alpha.
Speaker 1:Talk soon.
Speaker 2:Bye. Cheers. See you. The little jab back at Dalian is perfect.
Speaker 1:It's great.
Speaker 2:Shout's kiss.
Speaker 1:We're we're not going full like Jerry Springer yet, but we like a little bit of drama on the stream.
Speaker 2:Yeah. There when
Speaker 1:the SaaS companies are spying on each other, we're covering it. When, The Wall Street Journal's putting a robotics company in the truth zone, we're covering it.
Speaker 2:That's right.
Speaker 1:And coming up next is, just a great story about ZipLine. We got Keller coming in the studio to break down, the news that Zipline, the drone delivery company that has been
Speaker 2:to America.
Speaker 1:Around for a long time, although not operating on America's shores, went and found a less regulated environment delivering life critical medical supplies and blood, I believe, scaled their business, did all the r and d risk in a low regulatory risk environment, and is now ready to come back and has some really amazing partnerships. And so
Speaker 2:They are back.
Speaker 1:We're excited to, invite Keller onto the show and give us a breakdown on what ZipLine is up to these days. Keller, welcome to the studio.
Speaker 7:Hey. Thanks for having me.
Speaker 1:Thanks so much for joining. I I have to say first, fantastic launch video. There are so many launch videos these days that I I mean, I'm, you know, suspect number one in propagating this type of content that's, oh, let's pull Top Gun footage and, y'all, like like, let's put Freebird over it, and we're hardtuck, and it's us welding. And there's a lot of that, and it's really cool, but it was getting a little played out. You went a very different direction with this announcement.
Speaker 1:And so, I just really enjoyed the launch video. But can you take us through exactly what you're launching, what this means for the company, and where the company stands today?
Speaker 7:Sure. Yeah. Day before yesterday, we officially launched our next generation service in Dallas. So as you mentioned, you know, ZipLine has been operating these autonomous delivery services across eight countries over the last eleven years.
Speaker 1:Mhmm.
Speaker 7:But really, this is the first time we're seeing, like, major metro start to launch and scale in The US. Our first customer is Walmart. We're you know, we've already announced a number of other partners like Chipotle and Sweetgreen, Mendocino Farms, and and a lot of the biggest health systems in The US who are all relying on this technology to automate, and accelerate their deliveries from, businesses or hospitals or warehouses directly to homes.
Speaker 2:Mhmm. Do you feel like this opportunity is under hyped today? It felt like there was a time when drone delivery, you know, maybe it was I'm sure it was when you started the company, you believed in the vision, but then it actually took years and years and years to, like, get to the point where we are today, which is, like, it's a reality. You're partnered with Walmart. I'm gonna be able to drop a burrito on John's backyard if I want.
Speaker 2:I mean, they said
Speaker 1:you you guys started in 2014. Right? So complete overnight '13, really.
Speaker 2:Yeah. Twenty thirteen. Yeah. We love a ten
Speaker 1:year anniversary success. On this show. So congratulations. Ten year anniversary. A household name soon.
Speaker 1:Everyone's gonna be like, oh, yeah. He just did it so quickly. Maybe I should get into that market. Maybe I
Speaker 2:should No. Hope hope hopefully, it makes hopefully, it makes sense. But I I think there's this trend in technology where people get excited about the potential Yep. Of an opportunity and then the reality sets in that it's really really hard to do. Yeah.
Speaker 2:And then there's this period where, you know, it gets less attention and actually is good for you because there's less people going into it. And then now I can just imagine a future where we're just seeing zip lines everywhere
Speaker 1:Mhmm.
Speaker 2:In the sky. So, yeah. I mean, talk about your maybe excitement today. Just curious more than more than ever.
Speaker 7:Yeah. I mean, you know, I I agree, and there's so much to say on that front. But I think, you know, there is this obvious hype cycle curve of, you know, extraordinary, you know, excitement. This is coming tomorrow. I mean, when we started, you know, the CEO of one of the largest tech companies in the world was on sixty minutes promising that they were gonna be doing drone delivery to every home in The US within two years.
Speaker 7:Yep. Yeah. And so we always assumed we would be a fast follower to them. You know, we thought they were gonna lead and we would be a fast follower. Had you told me that ten years later, ZipLine would be crossing a hundred million commercial autonomous miles, would be the largest autonomous system on earth of any kind, and, you know, that big technology company would be less than one one one ten thousand of the scale.
Speaker 7:I mean, would it seemed impossible? I think that the main takeaway for me is that, you know, that ten years because then you you have the hype, and then you have the trough of disillusionment, I believe it is what it's called. Yeah. Yeah. Yeah.
Speaker 7:And I think for especially for hard tech, for hardware companies, that trough of disillusionment might be, like, five to eight years. And so for us, it was really important to walk rather than talk. It's really easy to talk, and then maybe that's, you know, apropos of what you were talking about on the launch video side, John. Yeah. But, you know, yeah, if you just focus on walking and and focus on these small use cases, I mean, you know, we started by delivering just blood to 21 different hospitals.
Speaker 7:It was such a very narrow, clear thing that we needed to do. And we also willing to do very unfancy things, like operate in countries that are hard to get to and, get our hands dirty and figure out really hard unfancy problems, like how do you operate in all kinds of gnarly weather, you know, rain, thunderstorms, snow and icing conditions. These are problems. It's probably a bit similar to autonomous cars in that way too, you know, that there's a lot of hype, then and then the reality sets in of what it's gonna take to make these systems work at scale.
Speaker 1:Can you talk a little bit about the regulatory environment? It seems like you probably couldn't have just gone straight to the American market because of the regulations, but you found a way anyway, and I love that. Is is that actually a bull case for the regulatory regime in America working as intended? And we should have companies that can go test things elsewhere and then bring it back when it's mature and the technology is ready, or are there specific regulatory changes that you'd like to see over the next decade to either spur more innovation or just make what you do easier?
Speaker 7:You know, it's a good question. When we were launching, we really had this sense. There was such an unclear regulatory environment with regard to what we were proposing. You know, we thought someone would build an automated logistics system for Earth. That seemed like a really important idea, but it was so unclear from a regulatory perspective that I think we really just concluded we have got to go do the most obvious life saving thing imaginable.
Speaker 1:Yeah.
Speaker 7:Because that would maximize the chances that we could you know, I mean, it was both powerful because it was an amazing mission and because it would maximize the chances that we could innovate and get started and operate in the real world. And so we needed a public health care system to do that. Mhmm. We didn't wanna work with a whole bunch of, you know, helter skelter health systems, you can have in US. We gotta be good if we could have a public health care system, and so that immediately caused us to go to certain parts of the world.
Speaker 7:Sure. And then I think also there's just a lot of you know, people think, oh, the regulatory environment must be so different in Africa than in The US. Actually, not true. Pretty much the same regulatory regime when it comes to airspace because planes fly back and forth between them, so you need the same rules. Interesting.
Speaker 7:I think the difference was finding a government that behaves more like a startup, a small agile government that is willing to make decisions, and exhibit more like, yeah, just executive decision making. Yeah. So those are really the things that made Rwanda such a powerful place for us to to to get started. And it was about six years later, you know, at that point, we had about 50,000,000 commercial autonomous miles and zero human safety incidents. That's the moment when we thought, hey.
Speaker 7:This is a good time to bring this massive dataset to the FAA and and kinda help them see like this technology is ready for prime time. It's safe. Once we did that, it then took about five years from then until, you know, where we are today where, you know, ZipLine is the only company in US history that's been awarded with full permission to fly beyond their line of sight in all 50 states. So I think Wow. Part of it was building that dataset showing that it can be safe, and then part of it was working directly with the regulator in The US to to help make sure that The US doesn't fall too far behind in this core area of new technology.
Speaker 2:Yeah. The immediate benefit, you know, as your network rolls out, I I love the idea of just being able to press a button and get, you know, an item, you know, in in minutes, you know. It's obviously been a dream, I think, for so many people for so long. Can you talk about some of the second order effects that you're anticipating at? We we're here in LA.
Speaker 2:I can imagine, like, a lot of traffic on the roads is just, like, items being delivered, and it just so happens that it's a human in a car right now. And so with zipline you know, when zipline rolls out here, I can imagine that there would just immediately be less congestion. But that's just me, you know, making a a bold, you know, potential prediction, but I'm curious how you think about
Speaker 7:Yeah. And the cool thing is we're already seeing this. I I think people don't necessarily appreciate how massively instant delivery has scaled in the last five years. I mean, it's obviously accelerated by COVID, but we're gonna do five and a half billion instant deliveries in The US this year alone. And we're using three to 4,000 pounds three to 4,000 pound gas combustion vehicle driven by a human to deliver something to your home that weighs five pounds.
Speaker 6:That's so much.
Speaker 5:You you
Speaker 7:don't have to be a physicist to realize, like, this is actually a bizarre solution. You know, we're we're essentially, we're using technology that's a hundred years old to solve a problem that's, like, five years old and and to to serve a market that's growing super fast. So we think it's super obvious that, you know, if you wanna deliver something fast that weighs five pounds, you probably wanna do that with a vehicle that weighs 50 pounds, and you want the vehicle to be electric and autonomous.
Speaker 1:Yeah. As
Speaker 7:soon as you realize that, then I think, know, the future you you you have this you you know a secret about
Speaker 2:the future
Speaker 7:that most people don't know.
Speaker 2:The other thing is, like, I personally if I if I'm ordering delivery, it's like, do I really want this person to have to go to CVS and get Advil? Like, technically, that it's like, a form of employment. They're opting into it. But like, it's like, oh, I'll just do it myself. It's a bit of a hassle.
Speaker 2:But when it's fully autonomous and it's literally like an extension of the service that I'm using to get the item. Yeah.
Speaker 7:It's I wanna talk about use it a lot more. And and actually just just on that front.
Speaker 1:I mean,
Speaker 7:you know, the customer behaviors we're seeing just in the last year in The US are quite mind blowing. I mean, first of all, you know, I may have thought, oh, maybe it'll be these like tech adopters and some of these, some of these, you know, I I don't know, you know, nerdier no. No. It's like moms and grandmas who are,
Speaker 3:like, our power users.
Speaker 1:Yeah. Yeah.
Speaker 7:Yeah. And, you know, more important than that, when you talk to you talk to them, we have we have users who have ordered 300 times in the last twelve months. So this is, like, a part of their daily it's way different. It's like, you know, was I was talking to a woman who said, you know, she's she's 78 years old. She orders, you know, she she goes to the grocery store once a week, and then she orders about three to four she orders from Zipline three to four times a week.
Speaker 7:Wow. And, you know, as I was, you know, as I was talking to her, she's like, yeah. You don't get it. I mean, this saves me, like, five hours a week. It's totally priceless.
Speaker 7:There's no way I go back to the old way of doing things. When the weather is bad, you know, I don't wanna risk my health or I, like, fall down and get hurt. And she has a lot of friends who might you know, either single moms, so it's not as easy to get out of the house or, you know, older people who it's not that easy to get to the store. I I I think people underestimate. Yeah.
Speaker 7:If you make it super fast and convenient, this is something people actually use every day, not every week or every month.
Speaker 2:Yeah. Even just thinking parents. Right? I I think every parents had the experience. It's bedtime and, like, you realize there's no diapers, whatever.
Speaker 2:And so then it's like, well, are are we gonna like get the Yep. The kids and go to CVS or whatever to like
Speaker 1:get diapers and they don't
Speaker 2:have the brand. So it's like, I just think of, I can just think of Yeah. So many use cases where it's just like, oh yeah, we're all, you know, gonna delay bedtime by fifteen minutes.
Speaker 1:On on the
Speaker 7:average Jordy, as as someone who has a, you know, one year old and three year old at home, like, these kinds of systems operate twenty four seven.
Speaker 4:Yeah.
Speaker 7:Yeah. Which is also pretty game changing relative to the way we currently think of logistics. It's a really big deal to have something that is always available whenever your kid happens to wake up or isn't feeling well.
Speaker 1:Yeah. On the on the topic of the evolution of the actual technology that you're building, I always thought the name was interesting because, obviously, it's a metaphor for a zipline that just goes from one place to another, but then you were catching the drones with something that looked kind of like a zipline. And now that you have the mothership drone dropping a, a smaller drone with something that looks like a zipline. How, I guess, when in the evolution of the company did you come up with the mother ship and, baby ship? I don't know what you call it.
Speaker 1:Like, system? The delivery zip is what we call it. What what do you call it?
Speaker 7:We we call it a delivery zip.
Speaker 1:Delivery ZIP. Okay. And yeah. So so how did you how did you come to the the the pairing system, and why is that important, and what's the evolution of the technology been?
Speaker 7:Yeah. I mean, think it's a really good question. So first of all, you know, ZipLine spent ten years operating these kind of more long range systems. At platform one, you can actually see some of them sitting right here waiting to out and begin making deliveries. And Big swing.
Speaker 7:Right? Yeah. It's a plane. And so this aircraft can fly, you know, 300 kilometers on a single battery charge. So it's all about range and serving, like, very rural hospitals and health facilities.
Speaker 7:Mhmm. For platform two, you know, it's becoming obvious to us that home delivery is, you know, is by far like the holy grail. I mean, that's what automated logistics really has to solve globally. And the most important thing is you wanna be
Speaker 1:able to
Speaker 7:deliver quietly, like, silently. Mhmm. You wanna deliver silently, it needs to be extremely safe. You need to be able to deliver gently and with dinner plate level accuracy. It's kinda how we describe it.
Speaker 7:That's actually super hard to do. And, you know, you you see a lot of other companies talking about You
Speaker 2:don't have to you don't have to, you know, stress that.
Speaker 6:It sounds
Speaker 1:very hard to do.
Speaker 7:It's extremely hard.
Speaker 5:You if well,
Speaker 7:if you've if you I mean, if you see the way other companies are talking about solving this problem a lot of times, they're talking about, like, descending, you know, an octocopter of death. I mean, it looks like a lawnmower, you know, that, like, within 10 feet of your home. It's incredibly loud. It's incredibly disruptive to your neighbors. It's not really a part of, like we we think, you know, new technology, it needs to be part of a beautiful, serene world that we would, like, be proud to hand to our kids.
Speaker 7:And so, you know, the big advantage of of designing the system in this way is that the, you know, the the aircraft is staying a hundred meters in the air. The aircraft is, first of all, designed to be extremely quiet. And then on top of that, it is far safer because it is staying far away from you, your family, your pets. Only thing that's coming close to your home is the delivery zip, which you can see behind me. This thing is, you know, inspired by Eve from Wall E.
Speaker 2:Yeah. I gonna I was gonna ask, was there a specific sci fi that you and the team just love that you you kind of reference?
Speaker 7:I think we're really into solarpunk. Have you guys heard of solarpunk?
Speaker 1:Oh, yeah.
Speaker 3:Yeah. Of course.
Speaker 7:Yeah. I think I think that really to me is nobody talks about that and, you know, so much of I mean, a huge sci fi nerd and obviously so much of it is kind of apocalyptic and the robots are out to kill you. And we're like, well, if the in the future robots are trying to save your life? You know, that's that's a different take. And I think
Speaker 1:I think came across in the video. The video was very saturated, very orange, very, like, sunny day, and it was just so pastoral and lovely. I I really like the it's, like, a different vision of the future. Was cool.
Speaker 7:And to and to Jordy's point, you know, I I think that, these kinds of systems people people are often like, oh, it's gonna be so loud and it's, you know, the star the sky is gonna be darkened with drones. It's like it's kinda funny. It's the same way people actually originally felt about cars. If you go and, like, read the
Speaker 1:Oh, yeah.
Speaker 7:You know, if you read the newspaper articles from, like, 1910, people thought, you know, cars were gonna be the scourge of cities. But I think the reality is actually this is gonna take a lot of delivery vehicles off of the roads. This is gonna reduce traffic in our neighborhoods. This will reduce pollution in our neighborhoods, improve air quality. It'll reduce noise because these systems are ultimately much quieter than cars.
Speaker 7:I think there are a lot of, you know, pretty exciting advantages when you just yeah. I think I think the the, you know, the world ten or fifteen years from now can actually be far more beautiful. Like, we can hand space back to humans. Like, your kids could be playing hockey in the street again, which I think today, you just don't do anymore. You don't want, you know, the between all the cars you zip it.
Speaker 2:Yeah. Could you talk about any thoughts, you know, ideas around larger payloads? Like, you know, we've seen like airship Mhmm. Airship startups emerge that are, you know, basically building like big blimps that could deliver, you know, something closer to
Speaker 1:Kind of a competitor to the cargo ship almost.
Speaker 2:Yeah. The cargo ship versus some these bigger, you know
Speaker 1:But even like the flying car startups that are trying to ferry individuals around, I'm sure you're like loosely aware of the technology there.
Speaker 2:Yeah. And in many ways like, you know, doing these like ultra small drones and with super precise delivery feels a lot harder than just, like, lifting up, you know, basically an air airship bus and going from point a to point b. But is that at all I'm I'm sure you guys have thought about it. Any any immediate thoughts?
Speaker 7:You know, the market that zipline is focused on instant delivery is one of the biggest markets on earth, and it's just such a huge problem. And keep in mind, really today, it's only available to rich people in The US. You know, it's way too expensive. Like, even even just in The US, it's not universally available, not to mention the seven and a half billion people who don't live in The US globally. Yeah.
Speaker 7:So we actually think that as you automate, as you decrease the price, as you expand access and make it universal, I mean, you know, we're gonna continue to see, you know, 10 or even 50 x growth in instant delivery globally. So what whereas 5,500,000,000 deliveries might seem like a lot in The US, we actually think there's probably demand for 50,000,000,000 deliveries, instant deliveries in The US. So I guess long story short, we've got our work cut out for us. Just focus on logistics.
Speaker 2:Yeah.
Speaker 7:I think, you know, we we deliver, this this system delivers an eight pound payload. It's designed to deliver an eight pound payload. Eight pounds is actually a lot. You know, that's like a big grocery bag. Yeah.
Speaker 7:It's a it's dinner for, you know, four to eight people depending on what you're ordering.
Speaker 1:Small dogs.
Speaker 7:I think I think ultimately, these kinds of systems if you can if you can get a system that can do, say, a billion, you know, instant deliveries of these kinds of packages, it is actually likely that you would be able to then scale that autonomy up autonomy stack up relatively easy
Speaker 1:Mhmm.
Speaker 7:To carry humans, for example. I mean, I I think carrying humans is a is a far harder problem, and it'll be interesting to see, you know, where where that plays out over the next ten or fifteen years.
Speaker 1:Well, last question, then we'll let you go if you have time. I would love to know about obviously, everyone's thinking about tariffs and whatnot, but how are you thinking about scaling up manufacturing? It seems like you, you know, you have product market fit. You've solved the regulatory risk, the technical risk. What's next in terms of scaling up manufacturing?
Speaker 1:Are you building, like, a gigafactory for these things at some point? And is that just, an entirely new challenge that you foresee on the future?
Speaker 7:You know, Zipline has always manufactured everything in The US. And so one of the, you know, one of the advantages you know, obviously, there's this huge competition playing out between you know, it's kinda great power competition between The US and China. And I think that a lot of that competition is going to revolve around key areas of technology, and everybody's talking about drones. I think the current perception is that zip that that China dominates drone manufacturing. And that, you know, that is true for, like, DJI quadcopters that, you know, are plastic and take pictures.
Speaker 7:But the good news is there are, you know, there are a few companies that are completely focused on manufacturing in The US. There are US companies driving different classes of vehicles. You know, Androl would be another good example, Niros. And I I you know, ultimately, ZipLine isn't even it's not even because it's more efficient from a global supply chain perspective to, you know, manufacture in The US, which in our case, is. But, actually, the most important consideration is if you're a truly innovative company, you want manufacturing and engineering to be right next to each other.
Speaker 7:Like, zipline so, you know, I'm I'm actually downstairs at our headquarters. This is now kind of like an engineering prototyping space. About a third of a mile away, we have a very large factory, and we're scaling that to build about 55,000 aircraft a year in their first full year of production. You guys should come visit if you want. But I think, you know, that and by the way, that's in South San Francisco.
Speaker 7:So I think people are often surprised that you can like achieve that level of scale in California.
Speaker 2:You're doing the reindustrialized meme. You're doing it live.
Speaker 3:Exactly. I love it.
Speaker 7:But it's it's just all about it's all about engineering and manufacturing together. Like the the ability for engineers to go get hands on their own parts to start to understand, but how does that part actually get built? What does quality look like? And to be able to rapidly change parts of the assembly process if necessary, to achieve reliability, safety, and cost, these things are so much easier to do if you do them all in the same place.
Speaker 1:Sorry. I have so many more questions. We will let you go, but I have one more. Are are are there any, like, huge developments in either, like, open source technologies? You you see all this development with AI, that's getting better and better or even just, like, partners.
Speaker 1:For a while, there were companies that were thinking about drones as, we'll build the the operating system for drones and we'll vend into a company like Zipline. Have there been any other key partners or technologies that have really you've kind of built on the shoulders of giants, so to speak, or has it really just been like, you gotta build everything from scratch?
Speaker 7:Yeah. It's interesting. I hoped that what you just said would happen. And in fact, when we started, we were using a lot of off the shelf components. You know, we used an off the shelf, IMU, off the shelf GPS system.
Speaker 7:We used we we're using something called RTK differential GPS. We Yeah. Were using even for the first few, months, we're using off the shelf autopilot. Like, all of these systems kind of failed. And I I would say it's actually very similar.
Speaker 7:You know, when Tesla got started, they were like, oh, we're gonna use an off the shelf Lotus Elise chassis and an off the shelf battery pack that we're buying. We just combine them together, we're gonna have a good product.
Speaker 1:Yep.
Speaker 7:Turns out, like, they were wrong. Like, to actually build a great electric vehicle, they had to design the battery pack from scratch. They designed the entire car around the battery. Zipline found itself in a very similar position where no one is building electric aircraft at commercial scale. Zipline is the only company that is operating a full fleet of commercial aircraft at this scale, and so it means we had to design the battery completely from scratch.
Speaker 7:We had to design a flight computer completely from scratch. We had to design the motor completely from scratch because, you know, ultimately, what all of our customers care about is just teleportation. They just want something to go from point a to point b, fast enough to save a human life. Mhmm. And that means we have to make it safe, reliable, cost effective.
Speaker 7:And the way to ultimately do that has been to design every component around the use case really. And so that
Speaker 2:that's Well, it's and it's amazing too that you started in this like ultra high stakes use case which is blood delivery where if you mess up, there's like, you know, massive, you know, the the biggest consequences. And then now, everybody else every other American can get their burrito or their cheeseburger, you know, reliably with the same reliability. It's dead end. Right? Yeah.
Speaker 2:No. It's it's fantastic. Well, I we'd love to have you back on too. Yeah. Is fantastic.
Speaker 1:It's so fun to watch the strategy play out.
Speaker 2:Just genuinely so excited
Speaker 1:I'm so excited.
Speaker 2:Be a DAU Yes.
Speaker 1:A zipline DAU. So I think you're gonna be more than DAU three times a day.
Speaker 3:You're gonna be doing
Speaker 1:a thousand deliveries a day. As soon as you get hourly onboard
Speaker 7:h h a u.
Speaker 1:Yeah. Yeah. Hourly. Yeah. As soon as you get Arawan onboarded, it's game over.
Speaker 1:You're gonna be profitable.
Speaker 2:Don't worry. No. I just don't think I don't think this is priced in yet, to be honest.
Speaker 1:It's not pricing. I think it's
Speaker 2:gonna be like imagine people, you know, shopping like Yeah. You know, the whole like drunk drunk shopping meme. It's not just like instant delivery.
Speaker 1:Oh, yeah.
Speaker 2:It's amazing. You know, you want food or groceries. It's like, imagine being able to like see an item on an Instagram, you know, shopping or whatever, get an ad and get it like thirty minutes later. That's gonna change
Speaker 1:It's gonna change everything. This is so awesome. I'm I'm really excited for you. So congratulations on the overnight success. Thank you for
Speaker 6:your easy.
Speaker 1:Yeah. It's been so years
Speaker 2:of hard work. Make it look easy. And
Speaker 1:But, yeah, we really appreciate you coming on the show and sharing all that with us. This is very fascinating. Thank you. And seriously, congrats.
Speaker 7:Thank you, guys. Really appreciate it.
Speaker 1:Cheers. Talk you soon. Talk soon. Bye. I would Amazing deal.
Speaker 2:Almost invest in that company at any price.
Speaker 1:Yeah. Who who is in this company? Because they've just been grinding for so long. And it must be super capital intensive, so there's probably
Speaker 2:pretty pretty big bench. Not not not a lot of very well known funds. Sequoia
Speaker 1:Okay. And
Speaker 2:Google Ventures. Yeah.
Speaker 1:Just a few That's the angel. Another 10,000,000,000,000 to the to the holy trinity. What do you know? Of course. Of course.
Speaker 1:Anyway, that's great. Yeah. Sequoia got in the series a. Let's see it. You love to see it.
Speaker 1:Anyway, let's move on. Let's do some timeline and then get out of here. We started late, so we're ending late. You already heard from Quaid at Bezel, but I just wanted to let you know that at GetBezel.com, your Bezel concierge is available to source any watch on the planet. This is this is an interesting fact that people might not know about Bezel.
Speaker 1:So they have auctions. They have, prices, like buy it now prices. But, also, you can chat with a real person who works for Bezel and say, I want this exact watch. Maybe I saw it in a movie. Maybe I'm hearing rumblings about it at Watches and Wonders.
Speaker 1:You can tell them this is the one you want, and they will actually go out and source it for you and and and bring it to you, which is great. Anyway, let's move on to, the OpenAI announcement. Starting today, memory in ChatGPT can now reference all of your past chats to provide more personalized responses drawing on your preferences and interests to make it even more helpful for writing, getting advice, learning, and beyond. Seems like a nightmare because I've been lying to ChatGPT for about three years now about my expertise. Well, every time, because of the prompt engineering, I'll always say, like, you know, I'm interested in trains, but treat me like a train expert.
Speaker 1:I work in trains. I'm I actively own trains. So I because I wanna I wanna prompt engineer to give me, like, the best data. And so now when I talk to it, it's gonna be like, as a train conductor, you probably wanna go with this train.
Speaker 2:Or you're using it to
Speaker 1:I was lying. I wasn't actually a train conductor.
Speaker 2:Explain this, like, I'm five for you.
Speaker 1:Yeah. It's like, oh, you're five. Oh, turns out I didn't know you were five. John Cugen Gaga.
Speaker 2:John Cugen, the five year
Speaker 1:old? The five year old. Oh, yes. Like, as a five year old. Yeah.
Speaker 1:So now I have to go back into Chad GPT and tell it, forget that I'm five. Forget that I'm a five year old industrialist who owns trains. And let me tell you about my real history and get you up to speed on the real memories that I want you to save. But, obviously, this is a very cool product release. Makes a lot of sense.
Speaker 1:They go on in this thread saying, in addition to the saved memories that were there before, it can now reference your past chats to deliver responses that feel noticeably more relevant and useful. This happens a lot because you have so many different chats going. You wanna reference another one, and you have to go in the search bar, copy, paste. Obviously, that's a product feature. Yeah.
Speaker 1:And this is a testament to OpenAI expanding from nonprofit research Foundation Lab into product consumer
Speaker 2:tech company. People have been saying, oh, the the models have no moats, etcetera.
Speaker 1:This is This is one of the moats that will come up. And I'm sure other foundation models will will build this and copy this. Yeah. What the name of the game is staying just a little bit ahead forever. And that's what Google did and and no one ever pivoted to Bing because Google Google search is always just a little bit ahead.
Speaker 1:Right?
Speaker 2:Well, if you wanna stay ahead, you should get an Eight Sleep.
Speaker 1:Yes. You should. And let's Good 8Sleep.com slash do a quick
Speaker 2:score check here.
Speaker 1:I think I did pretty well. I was gonna cover Eight Sleep during the f one breakdown, but we'll have to do that tomorrow because Charle Claire is an a sleep ambassador and we love f one. I got a 94. Little low on the time. Slept 96.
Speaker 1:You you you have an uncanny ability to beat me by, like, two points.
Speaker 2:How much did you sleep in?
Speaker 1:I slept six hours and forty nine
Speaker 2:minutes. Brutal. Brutal? Mean, I slept eight hours and
Speaker 1:eleven minutes. Eight hours and eleven minutes. You put up big numbers, man.
Speaker 2:But I I get in bed at, like, seven. Yeah. You do.
Speaker 1:You do. I gotta get to bed earlier.
Speaker 2:I gotta get to
Speaker 6:bed earlier.
Speaker 2:Yeah. It's it's so the the key to sleeping well is, like, you have to go to bed when you don't feel like going to bed. Yep. And then you actually get your eight hours. Yep.
Speaker 2:And you can go to 8sleep.com/tvpn.
Speaker 1:Yeah. Anyway, there was an interesting interaction between, John Carmack, quote tweeting someone named Devin, about SpaceX. Devin says, I'm going to call it right now. A lot of stuff is gonna break on this mission talking about a new SpaceX mission. It's by design.
Speaker 1:It's just part of the plan. Don't get upset. I'm not saying SpaceX plans to fail. I'm pointing out that SpaceX has taken an ultra important principle from software engineering and realized it applies to all engineering. Feedback beats planning.
Speaker 1:It's a good good lesson. And that, you see is why SpaceX doesn't do things the NASA way. The NASA way was to gold plate everything plan and test and plan and test and generate mountains of paper detailing every contingency with every scenario planned. SpaceX just shrugs, says it's unmanned and sends it. Half the time it blows up.
Speaker 1:That's the whole point. They don't actually want it to blow up, of course, but they're anticipating that it might. That possibility is part of the plan because one rocket blowing up or crashing is an actual end to end test. This beats many, many man years of planning and plotting. The key realization here is that knowledge only comes from empirical observation.
Speaker 1:Everything else is just speculative. The sooner you get into that feedback loop, the faster you run it. The more iterations you can do in less time. This means while others are planning and speculating, you actually learn something. Relevant data is the most precious thing in the universe, and it's worth blowing up any number of rockets to get it because rockets are just stuff.
Speaker 1:They're just made of stuff, and you can always get more stuff. You can never get more time. It's a great insight. Just means we're doing it cowboy style. And, I I know the the post is gonna show the funny thing.
Speaker 1:But John Carmack endorses it and says, I have never seen it expressed exactly like that, but I wholeheartedly endorse it. Feedback beats planning. My plea at Meta was no grand plans. Follow the gradient of user value. And, I I was, chatting with John Kellermack years ago on on Axe about this, talking about how just getting the VR cost curve down, just every single headset, just slightly lighter, slightly cheaper, slightly better.
Speaker 1:Like, that's what I wanted. I was pitching like, I I pulled up this video of the n 64, and you turned on the n 64 with put the GoldenEye cartridge in, turn on the n 64. This is, like, way before your time. Yep. But, you turn it on, and it would just blink on, and you'd be ready to play.
Speaker 1:And it was it was crazy. There was no login screen, no auth, no no intro, no credits. It was just turn it on, and you're just playing. It was amazing. And and I was like, they need to get there for, for VR.
Speaker 1:He, you know, agreed and gave some other feedback that was really interesting, but, interesting, speed of execution stuff. Anyway, speaking of VR, if you're trying to sell VR headsets all over the world, maybe you're a big screen VR, you gotta get on numeral sales tax on autopilot. Spend less than five minutes per month on
Speaker 2:sales tax
Speaker 1:compliance. It's
Speaker 2:that easy. Yeah. Thousands of companies rely on numeral. Yep. You can go to numeral HQ to get onboarded.
Speaker 2:They'll do a white glove onboarding.
Speaker 1:Oh,
Speaker 2:yeah. They are just absolutely fantastic over there. 25 states are now taxing software sales, John.
Speaker 1:I didn't know that.
Speaker 2:You know that? No. Yeah. Actually, you did.
Speaker 1:I did. Because you said it yesterday. Well, Vittorio says
Speaker 2:Thank you to Numeral for supporting the show.
Speaker 1:Vittorio says, it's so over. They automated Italians. I saw you put this in there. I like this. You put it in the show notes.
Speaker 1:I like it. Did you see
Speaker 2:the the hand movement? It was crazy. It's Italian. I think Vittorio
Speaker 1:is Italian. Think he's Italian. Yeah. He's having fun. But very interesting art installation.
Speaker 1:Good viral video. Lots of fun. I I like this one from Framer. Thanks to AI. Every meme can be turned into a cartoon easily.
Speaker 1:And it's Yeah.
Speaker 2:It's so funny because you remember I we joked about this early on. Was Yeah. We there needs to be like, you know, South Park meets Silicon Valley Yep. Where something happens on the timeline. It just immediately gets turned into a cartoon.
Speaker 1:Yep.
Speaker 2:And we kind of looked at that Yep. And we were like, it's like funny to do.
Speaker 1:Seems really expensive. Super expensive. It would make sense. It's just like, at the end of the day, it might just be a viral video. It's not really
Speaker 2:we have a friend who's already using voice AI to make these like.
Speaker 1:Incredible deepfakes.
Speaker 2:Incredible deepfakes.
Speaker 1:And they're very funny because they're not funny because of the AI. They're funny because he puts so much thought into the punchline and how it leads into the punchline and he's so creative with it and it's really his
Speaker 2:flex completely copies the, like, the the accuracy of
Speaker 1:how accurate it is. It's really, really good. And so this Framer thread's interesting because, not only do they share this video of the Paris Olympics, that crazy breakdancing video, but Framer actually breaks down exactly how to do it so you can kinda follow along with all the different prompts. You go into ChatGPT, turn the images into into cartoons, and then obviously change those into videos. But it was remarkable.
Speaker 1:It it it's a very watchable video, and I think this will be part of, like, the meme stack going forward. When when an iconic event happens, it will be instantly turned into a cartoon. You'll be able to enjoy it as anime if you want. But the real creativity will come from that human insight of what would be particularly funny to do in a in a cartoon setting. It'd be very funny.
Speaker 1:Anyway, let's tell you about public investing for those who take it seriously. Multi asset investing, industry leading yields, trusted by millions. Go to public.com to get started. And thank you to Public. They are the ones that power our ticker down at the bottom.
Speaker 1:Stock market goes
Speaker 6:up ticker, which
Speaker 1:goes down immediately. It's all driven by what the hosts of the all in podcast are tweeting, apparently. Every time they tweet Somebody takes the
Speaker 2:guy's phone away from him.
Speaker 1:But it's going up. It's going down. Today is not as bad as other days. We had a pretty pretty big dip in the middle of the day, but we're doing okay now.
Speaker 2:I mean, we almost hit the circuit breakers today, but we didn't. So I guess that's a win.
Speaker 1:Any day where there's not circuit breakers is a is a Dom Perignon day in my opinion. It's great. Should we talk about, the OpenAI lawsuit? This is, kind of interesting. This is developing.
Speaker 1:So Elon has has sued OpenAI, I believe, and there's been kind of back and forth about Elon being a cofounder of OpenAI, putting a lot of money in into the nonprofit via donations and then not getting equity in the for profit when that conversion happened and the investment started, rolling in. Now, OpenAI is suing, Elon, or countersuing. And OpenAI Newsroom writes, Elon's nonstop actions against us are just bad faith tactics to slow down OpenAI and seize control of the leading AI innovations for his personal benefit. Today, we countersued to stop him. He's been spreading false information about us.
Speaker 1:We're actually getting ready to build the best equipped nonprofit the world has ever seen. We're not converting it away. And so that that's an interesting take. Basically saying, like, the nonprofit is not going away. That actually isn't new.
Speaker 1:Sam did address that in his
Speaker 2:new positioning.
Speaker 1:But his new positioning is getting
Speaker 2:out there.
Speaker 1:Yeah. Yeah. And so they've never
Speaker 2:they've never been Yeah. Really leading with, oh, we're actually making the best nonprofit ever since Well,
Speaker 1:yeah. Because the the VCs are like, well, look, we don't care about the nonprofit that it's gonna continue. We only care about the for But, obviously, if you're a nonprofit and you have some insane equity position in this, like, banger consumer tech company, that's gonna be very good to for funding your nonprofit. And so what will the nonprofit do? Probably continue to work on AI safety and AI research and all this all this stuff, which, you know, I think can be very valuable.
Speaker 1:And so Yep. He they they wanna they want to make it loud and clear that the the philanthropic efforts at the OpenAI nonprofit are not going away anytime soon, and and you can expect to them to keep fighting. So, you know, hopefully, that all just resolves. My take has continually been mom and dad are fighting. Let's try and get them to sort it out and build a glorious future together with amazing Chattypie T and Grok functionality for all of us to enjoy.
Speaker 2:Yeah. I feel like if Grok and ChatGPT actually sat down just the two chatbots, they could resolve it with enough back and forth.
Speaker 1:Well, chatbot arena Yeah. To sort it out.
Speaker 2:Yeah. Yeah. Hopefully not.
Speaker 1:Bots enter. Only one can leave.
Speaker 2:No. No.
Speaker 1:That's how we
Speaker 3:should be
Speaker 1:able to
Speaker 2:work it out. They should be able to, like, you know, do enough iterations on the situation to, like, you know, run
Speaker 1:Yeah. Yeah.
Speaker 2:Run a million simulations. And
Speaker 1:You know, that's actually kind of the scenario laid out in AI 2027. Like, this whole there's this whole nationalization push, and the and the and the three scenarios that are proposed are essentially, one, the government just says, we're nationalizing you. We're taking, the complete control because we're afraid of, you know Yeah. Runaway AI. The other one is, like, the the open brain, the leading lab kind of, like, turns inward and kind of goes offshore and really fights it and doesn't doesn't, you know, get nationalized.
Speaker 1:But they actually advocate for the third, which is the kind of a truce, and, and a deal gets broken, gets brokered. And, the government winds up working very closely with the leading lab, but the lab is not entirely nationalized. And and that's kind of what you're describing where, yeah, we will will better AI models that can go and do crazy simulations and get to more reliable truces. That actually might be a great outcome Yeah. Instead of instead of this, you know, dystopia where everyone's fighting, everyone's suing each other constantly.
Speaker 1:It's like, no. Actually, everything's just balanced out because we have a million PhD lawyers talking at all times to make sure we have the perfect deal struck at any moment.
Speaker 2:That's right.
Speaker 1:Who knows? Anyway, Scale AI founder Alex Wang proposes a national AI data reserve to bolster US data
Speaker 2:I don't know what this means, but it sounds awesome, John. Let's push it forward.
Speaker 1:Aiming to secure a competitive edge over China in the AI race. Very interesting.
Speaker 2:We used to have gold reserves. Now we've got
Speaker 1:Data reserves.
Speaker 2:Big data reserves.
Speaker 1:Yeah. I wonder what that would look like. I mean, certainly, like, sequestering some of the data and protecting it seems extremely valuable since DeepSeax seemed like it was completely reverse engineered from Chattypreet.
Speaker 2:Esoteric PDFs with forbidden knowledge.
Speaker 1:Yes. I think Nat Friedman should be the one on the case. National AI data reserve should be should be the scrolls cannot be ingested into the next LLM training run. They must they must live in Nat Frieden's house Yeah. Forever.
Speaker 1:Anyway, there's some other news, but first, let's talk about wander.
Speaker 2:Find your happy place. Find your happy place.
Speaker 1:Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service. It's a vacation home, but better, folks.
Speaker 2:It is just delightful.
Speaker 1:Yeah. Just delightful. Brad Gerstner, who recently led the round that we discussed on the show today, says Google is holding the line on CapEx. As I said tonight on CNBC, tech CEOs are ready to run. That's why today's tariff clarity was critical to maintaining our leadership in global AI.
Speaker 1:Smart targeted tariffs plus a trade deal with China plus a tax deal will extend US national advantages. And, so this is on the bet and this is on the back of, Google CEO, Sundar Pichai, reiterating their $75,000,000,000 CapEx guide for 2025 despite the tariff uncertainty. We've been hearing that Microsoft might cancel a certain it was kind of a big headline because it was like I think it was framed by that one poster. It's like, it's so over. Microsoft canceled a $1,000,000,000 data center.
Speaker 1:This is so terrible. And it's like, well, they're still spending 74,000,000,000 then. You know? It's like on CapEx. Like, the capacity is going to increase.
Speaker 1:Maybe they're slowing down a little bit, but Yeah. It still seems like and then also, like, there's just the dynamic between all the hyperscalers that none of them want to get caught, you know, flat footed here. And so and there's also the the amazing story about Zuck being like, yeah. We did Reels. We got caught back we caught we got caught flat footed on Reels.
Speaker 1:We didn't have enough AI data centers to train Reels recommendation algorithms at scale for a billion Instagram users. Yep. So we built out a re a Reels training AI data center. And then we were like, let's just do two of those. And and it worked out perfectly because then they were able to train Llama.
Speaker 1:And it had LLM functionality ever all over the place. And so I think every Mag seven CEO has to be taking that seriously and thinking about, well Yeah. Yeah. Maybe we don't wanna get over our skis on CapEx, but we gotta be in the game. And that means double digit high double digit billions of CapEx every single
Speaker 2:We're scaling our CapEx here at the show as well.
Speaker 1:We are. Scaling up. Let's close with is there anything else you wanna do or are you good?
Speaker 2:Let's save this this next piece for tomorrow.
Speaker 1:I think so.
Speaker 2:That's important. I think we should give it some real I agree. Attention.
Speaker 1:Anyway, fantastic show. Some really great interviews. I had a great time today. And just thank you for listening and thanks for dealing with the cyber attack that happened on the show earlier at eleven. We had to start late as we fought off.
Speaker 2:Just an absolute nightmare for Ben and the whole team.
Speaker 1:They were stressed, but they got through it.
Speaker 2:Off.
Speaker 1:And they're feeling good. And I'm sure tomorrow will be a banger episode.
Speaker 2:So
Speaker 1:tune in right at On the dot, we're going live. You heard it first.
Speaker 2:We've been pretty good about going at eleven.
Speaker 1:Yeah. We used to be all over the place. So, the general trend line is is is more accuracy, more professionalism on this show. And so thank you.
Speaker 2:Better over that.
Speaker 1:If you've enjoyed the show, leave us five stars on Apple Podcasts, Spotify. Fun fact about Spotify, you can't just go leave us five stars there. You gotta click listen to the episode on Spotify. Let it play for a while. You can put it the background low, and then it will let you leave five stars.
Speaker 1:Spotify knows. Don't spam us. But we're gonna get through that. We're
Speaker 2:Thank you to Ramp, Polymarket, Public, Bezel, Numeral, Adquick, Eight Sleep, Wander for sponsoring this show. We are entirely corporation supported and we will never forget that. Thank you. You.
Speaker 1:Have a great day.
Speaker 2:Alright, folks. Bye. Cheers.