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It is Thursday, April 10th, 2025.
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We are live from the temple of technology, the fortress of finance, the capital of capital.
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We faced a terrible DDoS attack likely from a nation state, but we did sort it out.
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Sorry for starting a little bit late, but we got a great show for you.
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Thank you to Ben and our team of engineers.
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This is why people always ask us why why is your team so big?
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Why do you have just shy of 75 people working on the show?
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This is why because it's real business. It's it's serious.
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And you need you need you need the neck beard site reliability engineers. Really? That's right.
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You need full stack engineers.
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You need back end everything.
1:29
I'm looking at uh Ben right now and his neck beard has actually grown out meaningfully in the last hour. Yeah.
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You think you think Oh, a couple prompts.
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Couple prompts will do it. Not yet. Agi 2027.
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Maybe we will have reliable live streaming by then.
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I don't know about paper clipping, but we'll figure it out. Uh anyway.
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Well, it's good to be here, John.
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I'm excited for today's show.
1:50
Let's run through some news.
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Um, we want to start with this Wall Street Journal article about figure AI.
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Uh, and interestingly about the Wall Street Journal, uh, two different headlines.
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Uh, on the internet version of the Wall Street Journal, they say the $40 billion startup mystery shaking up Silicon Valley.
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And in the print edition, the headline is hottest AI startup makes bold claims but earns little.
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So aggressive, little bit little bit shadier on the uh little more mysterious little Yeah, a little more shade coming from the print edition. Uh but we'll see. We'll review this.
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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 big number. Got to back it up. So we'll see. We will dig into this. I'll dive in.
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So, in February, a littleknown startup promising to build futuristic robots set out to raise new cash at a nearly $40 billion valuation.
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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.
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Figure had no revenue last year and just a few dozen robots in production, according to documents shared with investors in recent weeks.
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The documents show figure has signed BMW as its first commercial customer and predict it will generate 9 billion in revenue by 2029.
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Now is that 9 billion from BMW or is that just they figure generally predict they will generate big figure is predicting this and they're putting it in their investor materials. Got it. Okay. Yeah.
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Big number but uh I mean to justify a $40 billion valuation that makes sense.
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Um, also I mean the you're only paying a little over 4x you know 2029 revenue here. Yeah. Yeah.
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4x which feels cheap forward fouryear forward revenue of of the year 2029. Yeah. Yeah. Yeah.
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So it's because forward forward revenue would typically mean like the year ahead.
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So forward revenue would be yeah I'm paying a 5x multiple on this year's full year revenue.
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This is forward forward forward forward revenue. Yes. Um but who knows?
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Hopefully it's extremely high margin revenue when it comes in because that would be great. That would be fantastic.
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I mean, yeah, even even if you if the margin's less than two billion in So here's where it gets interesting.
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On March 24th, Figures founder Brett Adcock wrote that his startup was the number one most soughtafter private stock in the secondary market, which we talked about on the show.
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and he shared a list that put Figure above SpaceX and OpenAI. Yep.
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We were a little bit takenback by that. Yep.
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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.
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Uh it turns out that I guess uh with like modern word processing kind of anyone can put together a list and screenshot it.
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And so I think there was some questions about, you know, was this from just a word processor or maybe it was generated with AI, but uh I would hope that it was generated with AI. Yeah.
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But certainly make a list where we're at the top. Yeah, exactly. Pretty effective. Well, it makes sense.
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AI might be biased towards AI companies and secondary.
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So it pushes that up to the top maybe.
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it pushes that up to the top maybe. uh how much a startup decided it should could it could raise money at a price tag that uh 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
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confounding investors across Silicon Valley uh had adco 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. Um, Adcock, and they give
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Um, Adcock, and they give some background.
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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.
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Adcock didn't respond to requests for comment.
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In a March 31st post, where he shared a video of the slender humanoids working on assembly tasks for BMW, Adcock wrote, "This isn't a test.
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This is what autonomous robots in production operations look like. Turn up the music. Turn it up. Put it to 11. Um, and yes, it does.
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Uh, so they dig into the the BMW deal.
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Uh, and this is a big question of, you know, if you're a hard- techch company, going and getting a partnership with a big company is often a huge milestone. Huge milestone. It is important. And so, guess what?
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The Journal actually reached out to BMW. Yes.
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And they confirmed some details.
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details. So uh on April 1st 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 practice picking up and grasping parts parts during non-production hours in our
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body shop the thing is that because this is this came out this statement was made on April 1st it could have been April Fool's Day and they could have been joking they could have said we actually have thousands but it's hilarious ious to to to April Fools on the Journal. Let's tell the Wall Street Journal that
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Let's tell the Wall Street Journal that we only have three that are just kind of moving some stuff around.
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And actually, the entire car is built by figure we fired all the employees, but you know, since you called us on April 1st, we're just joking around about it. It's possible. That's very Yeah, it is. It is.
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That's the nature of April Fools. I got fooled. Trey Stevens fooled me. I fell for it. It was terrible.
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I got fooled multiple times.
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I they there was some you know it's April Fools but they still get you.
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There was some founder who tweeted like uh oh there's a there's a tech there's a hit piece and Techrunch coming out about my company.
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It's dropping tomorrow and uh and I like made a note of it and then the next day I was like hey like I I didn't see that piece drop but like if it comes out like you should come on TBPN and we should talk about it and I you know I'd love to dig into it as long as it's not like a complete smoking gun on you.
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Um and he was like it was April Fool's John.
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I was like yeah okay I fell for that. I'm sorry.
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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.
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They were being used in non-production and live production situations. That's great.
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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 uh like I'm fine with a smooth gradient of progress.
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I'm fine with a with a just a robotic arm doing stuff.
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I'm fine with teleoperation.
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I think it's fine to go up the learning curve or down the learning curve, whatever. Yeah.
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A lot of the big questions here are not around the potential of humanoids, although there are some questions around the form factor.
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The questions are around the price tag totally being at 3.
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9 billion uh uh 30 sorry 39.
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5 billion uh which at the time when it was announced was more than Ford Motors which had I believe they had roughly 180 billion in 2020 Ford revenue. Yeah. Yeah. Yeah. Yeah. Yeah.
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Uh, I mean, you see what OneX is doing, you see what that that creepy European humanoid company is doing. Yeah.
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And they're both very modestly val uh valued.
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And so that puts a level of uh of scrutiny on those companies that's just wildly different.
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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 1x's valuation is, but I imagine it's much it's much lower.
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And so when 1x uh they did a video with Jason Carman where it was folding laundry, it was teleaoperated.
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They were pretty transparent about that.
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Uh that came out that oh they're doing teleoperation on on humanoid robotics. Still very exciting. It's awesome. Yeah, it's great.
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We love tea a tea operation.
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Uh you know who who doesn't want to be driven around in a teleoperated you know Whimo. That's fine. It doesn't matter.
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Sure there's questions about how does that scale?
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What are the econom what are the economics of that over a long period of time but it's fine in my opinion to get gather training data that way?
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Scale down the learning curve all these different things. Yeah.
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And so one of the big questions uh and one of the issues and potentially one of the reasons why the journal would pay attention to this round is that the investors investing in the round are not the typical big names that you see in these multi-billion dollar rounds.
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So one of the funding rounds biggest investors, Align Ventures, has spent weeks marketing the round and looking for smaller investors to buy in at the startup's valuation.
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According to a term sheet and other documents, the smaller investors would pull their money into an SPV uh reducing the amount that Align itself has to put up for the latest round.
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So Align to our knowledge uh doesn't have uh you know anywhere near the capital um just on standby to lead a round like this.
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Uh but they they are doing an SPV into the round.
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Yeah, it's also an interesting valuation for the amount that's being raised.
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You know the standard round 20% dilution, 15% dilution.
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Uh Mirror Morati 10% dilution.
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She's raising a billion dollars at 10 billion. Two two on 10. Two on 10. Yeah. So 20%. Uh he's raising 1. 5.
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You would expect this to be you know 10 billion 15 billion maybe seven billion.
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Ander even Ander's most recent round I believe was like roughly a 10% delution two something on 20 something.
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Um, and so yeah, like 10% just seems to be like in the ballpark.
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This is much less than that.
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Uh, and so that takes some pressure off the fund raising that a line has to do, but it's still a lot of money to raise if you're not managing a 20 billion venture fund or growth fund or something like that.
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So, uh, in many ways, a bet on figure AI is a bet on its founder.
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Adcock launched a series of companies since he graduated with a business degree from the University of Florida in 2008.
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He sold Vetery, an online hiring platform he co-founded in 2018.
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Then he's then he moved to California and co-founded Archer Aviation, a maker of electric electric powered air taxis.
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Archer went public in 2021 via Spa.
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Uh that company uh is also developing futuristic technology and he's yet to generate meaningful revenue.
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Adcock left the company in 2022.
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And I'm interested to we're we're having the uh the founder of Zipline on to talk about drone delivery.
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And I'm interested to hear how the flying stuff market, flying car market, flying drone market, these clearly bump into each other.
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I'm interested to see how he landed on zipline strategy and how it differs from what Archer is doing.
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Um that was the same year that Adcock launched Figure AI.
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In the early days, Adcock took online AI courses and had books about robots scattered about his desk.
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Former employees said he hired robotics experts, raised 70 million in venture capital, and unveiled its first humanoid robot in 2023.
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And so, getting up to speed about the the industry that you're going, just a little over a year ago, they raised 675 million in funding at a $2.
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6 6 billion valuation uh in which they raised from OpenAI's fund.
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They raised from Jeff Bezos's family office as well as NVIDIA.
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So really a a who's who of hyperscalers of of hyperscalers. Yeah.
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Um you know that that online course thing sticks out.
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Um you know he's sitting there taking online AI courses.
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Um 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 doing this company.
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Like that's pretty common.
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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.
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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. That's right.
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It's very very So anyways, uh Bezos after investing actually visited the company's facility uh and figure was in talks with Amazon on a partnership.
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Amazon obviously employs a lot of people.
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Over time, you can imagine they would employ some humanoids. Yep. Employees.
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Figure worked on a demonstration where the robot could lift heavy objects.
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A few months later, Adcock told staff at an all hands meeting that Figure and Amazon had decided not to move forward.
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And Amazon had bought KA Robotics, which is a robotics company, but uh it's like these they look like Roombas basically.
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Then they kind of slide around on the floor.
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You've probably seen these videos.
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It's really cool and it makes a lot of sense.
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And Amazon's obviously super dedicated to robotic automation.
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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.
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Um, so uh yeah, one of the one of the reasons that uh figure has been top of mind is some of the claims they've been making around their endto-end robot AI which they built entirely in-house.
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They had a partnership with OpenAI.
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OpenAI invested in Figure.
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Uh they broke off that collaboration uh earlier this year and then announced their own Yes.
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Um do you have any sense of what they're kind of claiming around? Yeah.
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When when I heard about the Open AI partnership, I thought it made a ton of sense because clearly Open AI passed the touring test. It's great chatbot.
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They have great whisper models for voice to text basically.
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And so when I think about I want to communicate with a humanoid robot, I want to be able to talk to it.
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I want it to be able to understand me at a level more much better than what Siri can do.
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And I want it 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.
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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.
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Um, now this phrase end to end, I think, is going to become something of a hot button issue in uh robotics and humanoid AI, just like TEA operation has been.
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um where uh you know, we talked about this with with 1X, we talked about this with the Tesla Cyber Cab and uh humanoid robots, the Optimus event, where uh the robots that were serving beers at the at the Tesla event were tea operated and so you would be talking to a real human who would be moving triggering this stuff.
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Uh after that there's actually an interim level um where some of the robotic decision- making and actions are ta are dealt with through AI.
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So the best way to think about this is to go back to how self-driving cars evolve.
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So self-driving cars the first step was let's use AI just to understand the world and create a 3D representation of the world as quickly as possible.
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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.
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Um, 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++.
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written in C++. uh just for example I know it was at cruise but essentially that's written as like business logic if stop sign apply pressure to the brake now Tesla and what George Hos is building at comma they have all wanted to go quote unquote end to end which
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means that the only data that goes into the self-driving car is the camera feed and the output is brake brake pressure and all you take in all the sensors and you just put output the steering and all of that Um, and so Elon made a big splash a couple years ago saying that Tesla was going fully endtoend. And in
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And in that presentation, he was like, "Yes, it's all machine learning code now."
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And one of his engineers was like, "Well, look, like there's still a lot of C++ involved, Elon.
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Like, let's not go that far and make that claim because that's not quite right.
17:48
not quite right. But it is awesome that both in the in the world model like understanding the world and then also the planning they're two different teams at most of these companies um the planning that the the planning process of of understanding okay there's a parked car here I need to go around it
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like that is done with AI as well and so that's that is basically Brett Adcock's claim when I hear he's he has built an endto-end robotic AI system it's that there there is no C++ ++ code or Python code sitting somewhere that says yeah if if beverage grab withhand action number seven. Yeah. So the big the big question Yeah.
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So the big the big question here the thing that's exciting has is has Brett and the Figure AI team Yes.
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had a breakthrough that that Elon and Whimo and and you know many of the other companies Yes.
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uh haven't been able to achieve with billions and billions of dollars because if Adcock and the team had Yeah.
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had Yeah. then it's very possible it'd be worth totally this crazy and that's exactly what happened with open AAI when uh when the transformer architecture and GPT4 got so good that it passed the touring test before that we did have this kind of it wasn't end to end but
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you could have chat bots right but what did the chat bots do they would take in your text and say okay 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 lines. You can tell
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You can tell that you're not talking to an LLM.
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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.
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And if they did this, it is groundbreaking.
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And it is it it's incredible.
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I mean, it really it really is. No, it really is.
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Like and and it and it is.
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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 relying on insane scale and just hoovering up tons of data and then crunching it down.
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This is the bitter lesson that we talk about with Rich Sutton.
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The bitter lesson is look you can do all this crazy stuff where you where you uh like there was a critique of Whimo that they had a cone guy for a while and his whole job was just to was just to write algorithms to detect cones.
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But if you just scale up all the Tesla data and and say, "Oh yeah, 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 the deep learning will learn what a cone is better than that algorithm ever could."
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And so you can pull that out.
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And so getting to end to end on any AIdriven system is almost always the goal.
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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.
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And uh if they've done it, it's remarkable.
20:41
Yeah, totally remarkable.
20:41
Uh so anyway, so in recent months, unsolicited emails from investors claiming to have access to figures funding round have been popping up in inboxes around Silicon Valley.
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They all offered a chance to grab a stake in a preIPO AI robotics company. Mhm.
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Uh people investing as little as $100,000 could participate.
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One of the offers stated one email pitched an investment through Parkway Venture Capital, one of Figur's main backers.
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It said there was an effort to raise more than $80 million for a special purpose vehicle that would get to own Figure shares in the $ 39. 5 billion funding round.
21:14
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.
21:28
Um, 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?
21:37
Well, the only game in town right now is Tesla, and that's a pure easy business with so many cars and tariffs and China and all these different things and batteries and uh so much stuff.
21:50
So, yes, there wasn't a pure play product for this and and uh that could be part of what's driving like the narrative around this stock essentially.
21:59
Um so, so one investor received a notice in January that he could acquire figure shares from a former employee at a steep discount.
22:06
He reached out to Adcock, who responded that the proposed sale was fraudulent and that he could invest in a future fundraising round.
22:12
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.
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The investor asked for financial information that could help him make that decision.
22:24
The company provided access to a data room that contained videos of ADC cop adco talking up the company.
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An investor presentation showcased images of robots doing various activities including working on a car assembly and pouring a glass of milk.
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What the presentation didn't include was audited financials or projections.
22:41
So this is an interesting strategy.
22:43
I was thinking about this like a lot of founders they get bogged down in the in the fundraising process when oh I think Sam Lesson was saying uh the deal goes to die in the data room.
22:53
No one's ever built conviction in a data room.
22:55
So, you know, if you don't want to bother with the data room, but you still need a link to send someone, maybe you what you want to do is just like go to your Twitter feed, your X feed, take all, print it, PDF it, throw that in there, and then when the investor shows up, they just get to see your bangers. Yeah.
23:14
One thing is clear, Adcock is an incredible marketer. Yep.
23:17
And some of the footage just coming out of Figure Broadly has been really astonishing and powerful. Yeah.
23:24
I I think I see why he would lead with that.
23:26
Yeah, I think that's the lesson for anyone who's working over there at Figure.
23:29
You know, we talked to Scott Woo about this.
23:31
Like things are moving so fast.
23:33
The company's growing at an incredible rate.
23:35
They have a new office, new campus every few every few uh weeks, it seems, new new videos, new breakthroughs.
23:42
And so, you know, to those folks who are working there, I would just say like take pictures.
23:46
You know, you're going to want to remember this.
23:49
They're going to write books about this company.
23:50
They're going to make documentaries about this company.
23:51
And so you're going to want to remember that.
23:55
So take pictures, look at the state of things and just witness. Just witness everything. Yeah. I think that's the goal. Yeah. Yeah. You really Yeah. Yeah.
24:04
This is this is history and there's going to be books written.
24:06
So So you're going to want to you're going to want to witness this stuff.
24:09
So um anyway, that's uh that's the story.
24:12
I'm sure we'll be digging in more.
24:13
We'll see what other people have to say and uh what else is going on in the humanoid robotics.
24:18
You know, we got to have the 1X founders on and we got to get someone from the Optimus team on.
24:24
We should do a humanoid day. We should.
24:26
We should have everyone on. All of them.
24:28
It'd be very interesting.
24:29
Back to back to back to back. Yeah.
24:30
They all have different angles. Yep.
24:32
Like I think it's powerful if you just pick a lane and not say, "Hey, we're going to replace all human labor uh in the world right away.
24:39
Sometimes you can start just aim to do laundry, just aim to do dishes."
24:41
some of these um some of these tasks that are maybe less exciting but still equally um powerful and and have tremendous potential and you know we also got to get some humanoid benchmarks on poly market for sure. Yeah.
24:55
Uh I mean the mo the logical one would just be you know Brett Edok spacked his last company.
25:00
Uh he took Archer Aviation public.
25:02
I'd love to see you know figure IPO percentage on Poly Market.
25:08
Um I'm sure there's a lot of other uh even just like those the amount of humanoids deployed at BMW.
25:14
I don't know if that would be auditable in a way that Poly Market could work against and resolve the market.
25:22
Having some sort of humanoid benchmark on poly market would be fascinating dra at least in at least in in terms of like uh uh just sentiment in the market would be very cool.
25:34
Anyway, um should we move on to uh we we've been getting a lot of questions from folks about how to encourage other potential listeners to tune in to TBPN live and we have a little script for everyone.
25:45
Uh yeah, so this is like something it's not quite a battle card, right?
25:50
It's It's not super condensed, but um yeah, if you're out there and you're talking to friends that you know, if you enjoy the show and you want to kind of share it with a friend, you might get some push back, right?
26:00
You might get some people saying, "Well, I already listen to some technology podcast or I already listen to business podcast."
26:06
So, why don't we run through this live?
26:08
Do you want to kick it off, John? Uh yeah.
26:09
Why don't you play the prospect, I'll play the sales rep, and I'll I'll I'll try and get you across the finish line. Exactly. Yeah. Uh so, kick it off.
26:17
Uh no, you're the sales rep.
26:19
Uh ju just so uh just so you're aware, a lot of listeners ask how we differ from other podcasts.
26:24
Uh one key area is integration.
26:27
Unlike other podcast, TBPN Live connects all business and technology news together into one seamless three-hour daily stream.
26:33
Does that sound like something you'd find useful?
26:37
Possibly, but I already have podcasts I regularly listen to.
26:40
I'm not sure I need another one.
26:42
Okay, so that's understandable.
26:44
But before we dive deeper into TBPN Live, could you tell me a little bit more about your current listening habits?
26:51
Specifically, where do you find the biggest challenges or bottlenecks in staying informed about tech and business news?
26:56
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.
27:04
It can be pretty timeconuming. Exactly. That's a pain.
27:08
That's a pain point we've frequently heard.
27:10
It sounds like your current podcasts aren't quite keeping pace with your needs.
27:14
forcing you to supplement with fragmented sources.
27:16
Uh, roughly how many hours per week do you spend doing that additional research? I don't know.
27:23
I estimate about five or six hours each week, John. Oh, okay.
27:25
Well, TBPN Live is designed specifically to reduce that research workload by at least 50%.
27:32
Potentially saving you hours each week.
27:34
How would you feel about having that extra time back for more strategic activities or even engaging more deeply with our insightful content?
27:41
That sounds good, but I'm a bit concerned about the amount of advertising.
27:45
I'm currently subscribed to premium podcasts behind pay walls and they have fewer interruptions.
27:50
I completely understand that concern.
27:52
Many listeners initially feel that way until they realize that the quality and relevance of the companies we partner with for advertising.
28:00
Could I quickly share an example of how these partnerships have provided values value to listeners similar to you?
28:06
Sure, I'd be interested in seeing that.
28:09
But again, my current podcast lineup already seems pretty good. Absolutely. Absolutely.
28:12
Your current podcast sounds solid.
28:15
Many listeners who've switched over were initially satisfied, too, until they realized TVPN Live offers unique features.
28:23
Would it be helpful if we briefly compared the scrolling news ticker we have at the bottom of our live stream?
28:28
A feature that's exclusive to our podcast.
28:30
Actually, that might be interesting.
28:32
I'd like to see how it works at least. Great. Why?
28:34
How about we set up a quick demo session tuning into the TBPN live stream together?
28:38
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? Sounds good. Let's schedule that.
28:51
So, that's just a great way to get someone on board if they're on the fence.
28:55
They're not ready to take the leap.
28:57
Uh just Great way to at least set up a demo. Yeah. Yeah, for sure. Set up a demo with them. For sure. Yeah.
29:01
You really want to go full uh full SDR mode for us.
29:06
You want to have the discovery call with them, handle the objections, create some counterarguments.
29:10
Uh ideally, if you know what they're create a battle card. Yeah.
29:15
And a lot of the techniques in here you can actually leverage in your own business, in your own sort of day-to-day life in terms of winning and uh you know, overcoming those objections like you said.
29:24
So, uh really great work here, John.
29:26
And uh hopefully I think it's going to convert a lot of prospects. Can really Yeah.
29:31
convert some prospects and help grow, you know, the listener base. Yeah.
29:33
Uh let's run through how Elon Musk rescued X from the brink.
29:38
Uh new uh new uh report from the Wall Street Journal.
29:42
Uh diving deeper into the X and XAI merger.
29:49
Um a crowd of in investigative uh 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.
29:59
Cell phones were a no-go at the January event, and the audience was told to stay seated until ex- chief executive Linda Yakarino and others had left the room after brief remarks and without taking audience questions.
30:09
Banks had planned to sell $3 billion in bonds at 95 cents on the dollar, but ended up selling more than 10 billion at even higher prices.
30:18
It was a testament to X's ability to bring advertisers back to the platform, helped in no small part by TBPN. No.
30:22
Uh by uh Elon Musk's proximity to President Trump.
30:29
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.
30:36
I mean that that is kind of the goal is to bring to shift X back towards more tech and business content, really pull people back in.
30:45
And fun fact, we had a we had a listener or we had a guest on the show who didn't have an account, had never used X, signed up hosting bangers. Yep. Great content. Yep. Fantastic.
30:54
So, also underpinning the debt sale was the possibility that X would one day merge with a hotter ascended company, Musk's X AI.
31:03
In private meetings with Wall Street, Executive said there was a good chance that the social media platform might eventually merge with Musk's artificial intelligence company, which makes the Grock chatbot. Yep.
31:13
The billionaire has said he never lost money for investors, but for a long time, he looked like he was going to with X.
31:20
After Musk bought it in 2022, advertisers fled over content moderation concerns and its loans soured as revenue fell.
31:28
One month after he took over, Musk said the company, formerly known as Twitter, was on the verge of bankruptcy.
31:34
I don't know how this was true.
31:34
Uh I think it was, you know, in part said uh to I don't think he obviously would have ever let it go bankrupt.
31:41
I think it was mostly meant to inspire the team to grind harder and grind harder they did. They did.
31:47
Uh, 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 100 billion.
31:54
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.
32:04
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.
32:14
It is crazy that he's never taken a down round, but it's it's kind of underrated that I don't actually Is it Is it down round or that he just always eventually got higher?
32:26
I mean, I I I guess like down in terms of like did raise a down round, right?
32:31
Or or or no, I guess it got marked down internally, which is not his doing like like anyone could do that at any time.
32:37
Internally, you can mark it down.
32:37
people have definitely panic sold and lost money, but they he's never done, you know, a primary round and uh ended up not returning.
32:45
But I I I think the lesson for like actual entrepreneurs that aren't maybe in his shoes is that uh there there 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.
33:10
Like we never heard rumors about like oh like Elon had to put in a billion of his own money, right?
33:17
And I don't think that happened.
33:18
And so what does that mean?
33:20
It's like yeah, the the whole business shrunk, but it continued to exist.
33:21
And so there's a whole world where if you move quickly, whether it's post SBB crisis and you know you're not going to be able to raise up round and maybe your own VCs have essentially like marked you down.
33:34
If you're at a big enough scale, they might have actually done it.
33:36
Uh if you're probably just some seed or series A bet, they probably didn't remark you.
33:41
Um, yeah, Fidelity was marked it down.
33:44
Yeah, Fidelity has a lot of their traditional investors avoided the markdown because they never lost faith. No, no, no.
33:50
I like like I'm I'm almost certain that the big venture capital firms do not do markdowns in that way, the same way as Fidelity. Yeah.
33:56
Uh although if Fidelity puts something out and says, "Hey, 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.
34:09
Um, but it didn't matter because they're up again, baby.
34:13
Uh, a spokesperson declined.
34:15
No one's talking to the journal about this, but we still got some interesting facts here.
34:18
Musk borrowed 13 billion to complete his 2020 uh2 take private of Twitter, and the loans quickly went bad when advertisers paused their spending.
34:26
He tried to persuade concerned brands to return, at one point, offering steep discounts and threatening advertisers that they would lose verification if they didn't spend enough.
34:34
the company's revenue fell from uh to three billion in 2023 from about 4.
34:40
6 billion the previous year.
34:40
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&D has been done on X right 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.
34:57
You don't need to do a lot on user acquisition.
35:00
Like the the people that are addicted are addicted and they stay. I'm never leaving. Yeah.
35:04
Um, and so you really can run it with a with a smaller team.
35:07
And when you when you have three billion in revenue, which is pretty high margin because it's just ads.
35:13
You have three billion to kind of slosh around and keep this thing going.
35:16
Like that's a lot of money to keep a website going in an app.
35:20
Like that that is what it is.
35:20
Like it's a big one, but it's not it it doesn't have any like crazy unexpected massive costs if you run it effectively.
35:26
And that's and these companies again were always so heavily intertwined, right?
35:30
It was X had a big position in XAI. Yep. Yep. Yep.
35:34
Um, and XAI paid X for data and they would have employees flop back and forth.
35:40
Um, so and and then, uh, staying on the revenue thing, X's revenue dropped again in 2024 to about 2. 6 billion.
35:46
It ticked up in the final quarter of the year according to people familiar with the matter.
35:50
So, uh, they so it might be turning around.
35:53
Uh, but it's going to take a while to build that back up uh because a lot of people have have have left to go to other other platforms.
36:01
But it does seem like, you know, even like Twitter and X have reached their Nadier in my opinion, like in terms of like sentiment and like the people who wanted to leave have left.
36:10
Uh the people who have stayed are staying.
36:14
Um the advertisers who have who wanted to leave have left and so yeah, it still is still producing single-digit billions in in ad revenue and and and monetization. And that's great.
36:22
Um, Musk and his ad advisers had long thought about bringing X and XAI together, but after the election, those plans accelerated, according to people familiar with the matter.
36:31
To do that, they knew they would have to successfully execute several transactions in the right order and get a little lucky.
36:38
But Musk is a pretty lucky guy.
36:40
With Musk's with Musk ascendant after the election, X took a new approach to jinning up the new new ad spending.
36:46
In December, a lawyer from X called a lawyer at advertising conglomerate Interpublic Group, hinting that its recently announced 13 billion deal to merge with rival Omniccom would face trouble from the Trump administration.
36:57
So, he's putting the pressure on them.
36:59
Uh, other advertisers started to raise their spending, including Amazon. com in January.
37:02
Uh Amazon's an interesting one because uh I mean obviously huge huge advertiser but uh 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.
37:22
It's it's almost like an education platform.
37:23
It's not the same experiences as Instagram where you're just browsing different visual elements. You see a product. It makes a ton of sense.
37:30
And I think that's why Ben Thompson's always argued that Explore feed now is just probably the the Hennessy uh what's it called?
37:38
The Cadillac Escalade V Hennessy edition which has00 explore feed of just like the reels is just different videos of of that.
37:48
You can't get it off your mind once you figured out it exists.
37:50
It has been interesting like I'll I'll I'll search I I I find 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.
38:00
I'll be watching Doug Demiro on YouTube and my YouTube feed will be flooded with that and it'll show me all the different like, oh here's Vinwiki, here's, you know, uh, all Hoovie, all the different car YouTubers will kind of flood in because Google picks up on it.
38:14
Instagram I don't use as much, but eventually we'll learn, hey, we showed him one car video and he seems to be more into it than before. That's right. Let's keep it going.
38:23
Um, 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.
38:31
Plus, I pay for like the most premium version that gets rid of all the ads.
38:34
But even when I didn't, I never saw turning the premium off, turning the verification off just so I can get the full flood of ads.
38:42
Um, I wish you could be on the highest tier so you could pay X as much as possible yet still see ads to get them that sort of incremental I like that revenue.
38:51
Yeah, I liked uh I mean for a while you could like pay for the check mark but then turn it off.
38:56
You should be able to do the same thing with ads.
38:58
Pay to remove the ads but then check mark put them back. Yeah.
39:00
Uh but maybe you need a maybe you need a non-account just for that.
39:07
Um anyways, uh I'm excited to see what this combined entity does. Yeah.
39:10
Um a lot of work to do still. Yeah.
39:14
I mean we talked about it before.
39:15
It makes a lot of sense in in a bunch of different ways.
39:18
uh from real- time data when you go to Grock, you're going to want to know about things.
39:22
All the data gets psych sucked into X anyway.
39:23
And so makes sense from a uh data strength perspective.
39:28
Um and and and also just as a distribution vector for Grock.
39:33
Uh it seems like every major um every major foundation model company has found a dance partner.
39:41
Uh, and Google has google.
39:44
com and they're searching and they're sending generative responses into the Google search bar.
39:48
OpenAI has been able to get everyone to download the OpenAI chatgpt app.
39:53
It's in my home row and they've done a great job at that.
39:57
Um, there's been talks about, oh, Perplexity might like merge with someone or anthropic might merge with someone or partner up with someone.
40:03
Uh, so the XAI uh X X and XAI deal makes a lot of sense in that context.
40:08
But if your business is uh is collapsing and advertisers are leaving and you need to cut costs, get on ramp. Time is money. Save both.
40:15
Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place. Ramp. Ramp.
40:19
And we have our first guest of the show, Alex. Welcome to the studio. How are you doing today? One second.
40:28
We are bringing him in from Outtake AI.
40:30
We will give you a little background. How you doing? Big news this week. What's going on?
40:34
Thanks for having me, guys. I'm pumped to be here. Thanks so much. Uh thanks for coming on. Busy week for you guys.
40:40
Uh hypers scaling and announcing the raise all at the same time.
40:45
Uh but be before we dive in uh introduce yourself uh and the company and uh yeah, whatever backstory you want to give for the audience. Yeah, of course.
40:55
Um well, first off, thanks for having me, guys.
40:59
Uh backstory, I spent five years working at Palanteer.
41:01
I worked across a lot of crazy different stuff as as one does at that company. Uh worked abroad. I was in South America. I was in Eastern Europe.
41:08
Um uh eventually started to work on really deep core product things.
41:11
Uh uh towards the end spent a lot of time on what we effectively our experimental product team.
41:17
Uh so 0ero to1 uh new product bets.
41:20
Uh worked directly for the pounder CTO Sham Sunker. Absolute goat. A shout out to him.
41:26
Also one of our angel investors. Amazing.
41:28
And yeah, um, 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 going to live in an increasingly like schizophrenic internet.
41:40
Like, you know, what you see is not necessarily what you what you get online anymore.
41:44
Um, especially the way I think about is the cost to be a shitty person online went to kind of zero dollars over the last like three years.
41:51
Uh, you got infinite text, infinite images.
41:53
That stuff is awesome, super creative.
41:55
Just obviously there's bad people out there that are going to misuse it.
41:58
uh and I wanted to do something about that.
42:00
Uh and that's really what Outtake is focused on.
42:01
We we we we try to preserve au authenticity, identity online. Uh go deeper there.
42:06
Who who are the kind of companies that you're working with today and will be working with?
42:12
Um you know, I'm sure some some you can share, some you can't, etc.
42:17
Yeah, it's it's funny in cyber security there's this like there there's a there's a lot of sensitivity around like what you can and cannot share and but um we've been lucky to work with phenomenal places like uh you know OpenAI is one of our one of our favorite customers really pushed us when you think about the kinds of cyber security threats that they might be dealing with.
42:36
Um really anyone that has a brand big enough to really matter is a brand that can be misused. Right?
42:42
So a fun side effect for us as a company is like our customers are intrinsically people that matter because they're are the ones whose names and brands are being uh misused to manipulate people, right? Um yeah.
42:51
manipulate people, right? Um yeah. Can you talk about so so I feel like everybody's been aware of this threat around AI uh impersonation you know some of these like voice models even video models at some point are getting so
43:06
advanced that it it's becoming a big threat can you talk about um it feels like we haven't um it it we haven't faced like Armageddon yet but I'm sure like uh 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. So can you talk about
43:22
So can you talk about like what's app actually happening in the market because I have this 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 fishing attempt etc.
43:35
Um, 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?
43:43
It doesn't feel like we're completely flooded yet.
43:44
Um, but this thing, you know, this kind of phenomena is scaling. Yeah.
43:48
To to your point, I hope we never see Armageddon.
43:51
Uh, 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.
44:01
Uh 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 whatnot but like we haven't necessarily seen that right.
44:10
Um interestingly a lot of the attacks you know on the other end of the of sophistication are actually really targeting enterprises right and and it kind of makes sense.
44:18
It's like um that's where the money that's where the data is.
44:21
And so what we are seeing is like the quality and volume of let's say like uh inbound email fishing attacks has like gone up considerably.
44:29
And and this just goes back to the idea of like the cost to do that dropped a lot, right?
44:35
Um and so enterprises are are like dealing with an absolute flood of attacks at the moment.
44:39
Um and there and then there's a variety of attacks, right?
44:43
So there's like, you know, there's the good old email security stuff we just mentioned.
44:46
There's just a lot of stuff around social engineering generally, right?
44:49
It's like, here, let me throw together a fake website and then use that to like DM people, uh, to to send emails via that.
44:55
Uh, or let me just get the customers of that company, let's say, and I'm going to use a random name that's not connected to us.
45:01
Let's say it's like, uh, I don't know, the Bank of Bank of Canada in some way, right? It has a website.
45:06
Um, that's going to now be used to scam Canadian citizens in some way.
45:09
Um yeah, this the sophistication is like really one one phrase that I always come back to is like um it's not only that grandmothers are the ones being scammed, it's actually grandmothers can become scammers now.
45:22
And it's because right it's like it's just easier than ever.
45:25
Uh and that's actually the real issue.
45:27
and that's actually the real issue. It's like sometimes people talk about large language models and they're like oh like it could teach someone how to like clone small pox and it's like yeah dude sure it maybe but like it could immediately today tell you how to you know pentest someone's website and and try to get
45:41
into it and so it's just like the barrier to entry is just so much lower than it used to be for all sorts of cyber security attacks that's been Can you talk about like the the scale of you know some of these like things like when I when I think about like you know everybody's in tech is getting like
45:58
a coin based style fishing like hey you know give us a call like you some issue and I just think about like okay if that works one out of a thousand times it's the best business ever like is part of the reason that like you know the sort of um these issues are are scaling so rapidly is just because it's super
46:15
profitable yeah I mean the the like one way to think about it is um we've all seen the tremendous growth of like AI outbound companies right they've done really well um uh it it's it doesn't take a leap of the imagination to understand that like that same sort of like well-intended outbound can be misused, right? Um and so maybe one way
46:35
Um 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 inbound or email inbound.
46:49
Um it's basically been one for one on sort of the darker side of it as well.
46:54
Um um what about the stuff you guys are doing with uh creators?
46:56
I know uh in the announcement you said that you guys are working with Sycom uh the the team behind Human Lab.
47:04
Um what are what are you seeing creators dealing with in terms of impersonation um as these models have have advanced?
47:12
I mean creators were some of our first customers, right?
47:17
And it's actually because they were the ones the first ones to feel the pain.
47:19
I mean to some degree maybe you guys deal with this, right?
47:22
Someone might make a fake handle of your account Yeah, fake versions of your profiles.
47:25
Um there there's a lot of value in impersonating you guys, whether it's a financial endorsement, a startup endorsement, uh just pretending to be you for recruiting and something.
47:34
Um uh the the basically the creators were the first ones to hit because they were the most chronically online, right, is is the short answer there.
47:43
Um 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.
47:50
Um, I think what was really fascinating for us as a company is especially since almost the whole team came from Palunteer, we had this we we had a lot of reps at selling to large enterprises, government and incredibly secure 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 up really really quickly.
48:14
Can you talk a little bit about recent AI model progress?
48:15
I don't know if you read this uh article on less wrong from zero path, but uh just to summarize it, it said recent AI model progress feels mostly like BS.
48:24
Uh they this was from a founder who actually built an AIdriven pen testing company and they said they kept upgrading to the latest and greatest model.
48:35
It would completely destroy the benchmarks, but then they weren't getting real world results.
48:39
And this was a question about benchmark saturation.
48:44
Um, I could imagine that to your point about like the script kitties are better than ever basically because pentesting is democratized now or or or or hacking or scripting is democratized.
48:52
But in terms of the work that you're doing, how important is AI model progress to all that?
49:00
And and what is the shape of the of the of the curve that we're looking at?
49:03
Is it sigmoid or are we going acceleratory to the moon?
49:05
That's such a good question.
49:08
good question. It it goes back to my sort of like gradient of sophistication response which is like um 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 right to um and so my general take is like the models are
49:29
already at a point where they're having serious social engineering attack effects 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, uh sure
49:43
there's all this hype around progress, but I don't actually see uh a model being able to autonomously hack a website because maybe that's at the further end of of the sophistication. But I guess my claim is that like um you
49:52
But I guess my claim is that like um you know uh it's it's something like 85% of critical data breaches happen because of social engineering attacks.
49:59
It's almost like machines are easy to secure these days.
50:03
like we you know there's a massive multi-billion dollar industry that is all of cyber security that focuses on that.
50:08
I I think one of the big contrarian things about outtake was it was really two things.
50:12
was really two things. was like one hey if machines are pretty secure let's actually focus on securing the humans and then two traditionally uh enterprises will like stop at securing themselves right so they'll say hey I have my corporate perimeter um and then my VPN and everything and there is
50:28
really buttoned up and that's great historically cyber security companies have been kind of I I think gunshy of stepping outside their perimeter and saying hey no I'm going to go search for threats out in the world like arbitrary websites social media wherever it is and we're going to go look for those threats and proactively tackle that. That's
50:42
That's intrinsically difficult because you're trying to influence a thing that you you know it's not part of your org.
50:46
Um our ability to like do that and and and actually do the really hard work to get there um is really what helped us stand out is the only answer for a bad guy with an LLM, a good guy with an LLM.
50:57
And what I mean by that is that uh you know captas are not they're they're they're they're deterministic essentially uh and yet they they can thwart a non-deterministic attack from an AI.
51:13
Uh you could imagine arc AGI puzzles becoming the next capture uh or or or in your view do we need just to stay is it is it a uh probabilistic on probabilistic combat from here on out? I I love this question.
51:30
Okay, so yeah, one of my biggest anxieties is that like generally to your point, captions are broken, right?
51:34
Which like, hey, we passed the touring test a while ago.
51:36
For some reason, we just blew past that and don't talk about it enough.
51:39
We all are blowing past uh what effectively was the the like modern version of the touring test, which is just captur.
51:46
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.
51:50
Um and we spent a lot of time thinking about this.
51:55
Um anyway, to get to your actual question of like proistic versus proistic, uh I I think there's a few answers.
52:00
Um I I'll hint at the future of outtake a little bit.
52:03
Uh some of it's still parts of it are still in stealth, but um I think a lot of what we do today is what you're talking about.
52:08
It's probabilistic versus probabistic and we're thinking about hey here's the harm we're seeing and like can we go practically discover it and remove it, right?
52:15
The other half of it though candidly is like can you talk about 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.
52:34
But maybe could you dive in there around like yeah why um 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 um dealing with threats in the real world out on the internet versus internal.
52:53
Yeah, excellent uh point.
52:53
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?
53:05
So like it intrinsically was a task so difficult that only humans can do it.
53:09
Meaning you know let's say we're protecting again the Canadian bank.
53:13
Um you need to uh have have an ability to go like proactively search for every place that you think the threat might emerge.
53:20
You need to be able to adapt to the idea like let's say that bank sells mortgages in the summer, right?
53:24
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?
53:31
Now you and I as humans can get to that pretty quickly.
53:35
uh historically models were not going to just like infer the season and then figure out the like latest trending scam for this particular customer, right?
53:40
Um we are able to do that, right?
53:43
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.
53:50
The other thing is uh deciding what is considered harmful for that particular customer.
53:54
Like there's a lot of nuance there by company.
53:56
I mean celebrities is a great example, right?
53:59
Where it's like there's fan pages, you don't want to remove that stuff.
54:00
Um, and so there's a lot of nuance in how you determine harm.
54:03
Again, a reason why you would train up, you know, uh, a team of people to be like, hey, this is what we consider harmful.
54:09
Uh, there's a lot of mo and frankly figuring that out.
54:11
Uh, 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.
54:18
And then the final bit is um taking over the actual like remediation steps, right?
54:23
Like um, everyone talks about legal AI like we I I think we've built one of the most effective legal workflows, right?
54:29
where we like go out and like interact with third parties to resolve external issues.
54:34
Can can you talk a little bit about the actual monetization or value capture here?
54:38
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 going to be happy then they're going to be unhappy with me if they get scammed even if I had nothing to do with it.
54:50
Um how if you go out and and shut one of these rings down, how are you getting compensated? It's a great question.
54:55
the the way we think about it is um tradition.
55:01
So, so I I guess good for us.
55:03
The customers were thinking about these problems, right?
55:06
They were just at a relatively lower volume historically, right?
55:09
So, like um if you look at the chart of like sort of digital attacks happening on uh let's say social media websites, etc.
55:16
, it sort of like is flat flat flat and then like 2022 2023 it like starts to go exponential, right?
55:20
Um we were, you know, positioned ourselves well.
55:25
We saw where the puck was going and said, "Okay, great.
55:26
all the people that were already managing that low level of attacks. I mean, they existed.
55:31
They just were a cobbled together team of like cyber security analysts and occasionally lawyers at every or every large organization had someone thinking about it.
55:39
Um, but they could sort of manage the one to 10 attacks a week, right?
55:43
Um, they were expensive though because they're, you know, uh, yeah, very very high like uh, hourly wages for these folks.
55:51
And so, um, when the volume spikes, it becomes untenable to use that old system.
55:55
And then it became really clear that Outtake could step in.
55:57
And so to your point about value capture, it really became a question of like, hey, you would be trying to manage this.
56:02
You would be trying to uh have these folks work like 24/7.
56:07
They obviously can't do that nor want to candidly u and slash you wouldn't be able to afford it.
56:12
So let outtake come in do a 10x better solution at onetenth the cost and and this is a really good deal for everyone involved.
56:18
Um can you talk about uh we had Ashk on chief architect at Palanteer uh uh yesterday we were talking about the sort of forward deployed meme.
56:27
Have you taken anything from that approach?
56:31
You obviously were a forward deployed engineer all over the world.
56:33
Uh 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 or is it you know uh less intensive than that?
56:43
No, I think the forward deployed meme is is there there's a lot of truth to it.
56:48
Um the reality is if if you want to if you want to go do something meaningful, you need to go sit by the customer and like make it happen, right?
56:56
I mean a lot of our best product insights have happened because like me or another engineer were actually on site and said, "Okay, like here's how we thought you were doing it, but in actuality you need to do it this way."
57:07
Uh so yeah, for deploy engineering, huge fan. Love it.
57:09
Uh you got anything else? This is great.
57:12
Yeah, I I I wanted to know a little bit about like mechanically how do you shut down a ring of scammers.
57:20
I remember reading this book about Paul Laroo.
57:23
I don't know if you're familiar with this guy.
57:25
He's called the mastermind.
57:27
He people think he might have created Bitcoin and uh back in uh like 2004 or something.
57:31
He was you know those like spam emails you get that are like oh magical pill you know pill mill stuff.
57:40
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.
57:48
But then he went even further and bought a registar so that he could register like new domains for free and you couldn't shut them down at the registar level.
57:56
Not just like he had his own like TLD basically. It was crazy.
57:58
Uh and so some of these some of these like rings are extremely sophisticated.
58:03
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 major major organization here. Yeah. Okay.
58:17
Uh I I have to be careful about what I can share public. Sure. Sure. Sure. But yes, like sure. Yeah.
58:24
We saw with the Mark Robber Mark Robber like busted some fraud scheme in India, right?
58:29
I don't know if you're familiar with that one, but maybe just tell us some historical stories of how this works. Yeah. Yeah.
58:36
So, to your point on the mechanics, like um the the traditional way to like deal with all this is is is purely legal, right?
58:42
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 registar, etc.
58:50
Um that was a key ingredient in the early parts of outtake.
58:56
of outtake. 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 um how do we become the platform that is like trusted by domain registars hosts um social platforms etc to to be a high quality source of reports right
59:15
like that is incredibly incredibly important um 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 yeah that makes a ton of sense uh well thanks so much for joining this is a fantastic conversation and good luck to you. Hopefully you bust
59:27
Hopefully you bust uh you know some massive scamming ring soon every day. Every day I'm sure.
59:33
But uh yeah, you're a new cyber security correspondent. Thank you.
59:37
Uh thank you for all the helps.
59:38
He's he's already been finding you know people impersonating us. It's great.
59:41
So uh appreciate your your your hard work and the whole team and congrats on the new round. Yeah. Thanks a lot guys. Talk to you soon. Cheers. Talk soon.
59:51
Uh yeah, I I actually have gotten multiple times people set up fake John Kugan accounts, copy everything, copy every tweet, and then block me so that I can't see it.
1:00:00
And 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.
1:00:09
I'm sure you've seen this."
1:00:10
And it's like, "Yes, I have seen it."
1:00:11
And then I have to go hunt it down and report it and stuff.
1:00:13
And so, uh it's just like annoying getting like a flood of text being like, "You're you're being impersonated." we are good friends.
1:00:18
But yeah, yeah, yeah, I appreciate it. Thank you.
1:00:22
If you've let people know, but in the future, uh yeah, I mean, still send it to me, but definitely just report it and try and get uh try and get the account taken down if it's out there floating around.
1:00:31
Um next up, we got Quaid coming in the building.
1:00:33
Uh Watches and Wonders is done.
1:00:36
Uh 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 tar tariff chaos.
1:00:44
He's been in Switzerland.
1:00:47
called in uh from Watches and Wonders late night last week and now that the show is over, we're going to get a full deep dive.
1:00:53
Also want to talk to him about how um how the news breaks around uh different watch news and how the how the media cycle works.
1:01:02
So Quaid, welcome to the show. For having me, guys. Excited to be back. Are you back in LA? I am. It's funny.
1:01:11
The the last time I dialed in, the tariffs dropped.
1:01:15
I think the mid I hung up with you guys. So, yeah. Yeah, it was 4 4 p. m. that day, aren't I?
1:01:21
I I was I was in such a haze.
1:01:23
I I think I texted you quite I was like, uh, what's the reaction over in Switzerland and you were like, not good. Not good.
1:01:31
Uh, but now now, you know, we've seen things. There's been a pause.
1:01:34
There's been ups and downs.
1:01:35
Uh, there's still the 10% base tariff. Yes. Correct.
1:01:37
So, so, so what what was the whole journey throughout watches and wonders? Very funny timing.
1:01:44
uh be there on the ground.
1:01:46
Uh take us through the reaction as things developed and where the heartbeat of the industry is right now. Yeah.
1:01:51
And I think you can you can split the conversation kind of between the primary market and the secondary market.
1:01:56
And so I'll intentionally walk through that.
1:01:58
Uh 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.
1:02:10
Um, and I think you can split the reaction from brands kind of by the type of brand they are.
1:02:19
You have like the the giant massive brands that everyone knows like the Rolexes and the Pex and the APS of the world.
1:02:26
Uh, and their reaction is decidedly different than some of the brands that sit kind of in the middle of the market.
1:02:32
the market. um 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 um and whether it was functional products watches that are just parts like they just wanted to move everything to the US
1:02:50
as possible from most of the meetings that I was having um on the larger brand side I think they had the luxury of sitting and waiting and seeing what was going to happen um you saw the Rolex of the world and things like that take their time. And the initial answer that
1:03:03
And the initial answer that that I got from secondary feedback from from 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 want to pass this on to the customer, but we're not going to eat the cost of these tariffs either.
1:03:20
So, we're just going to hold off.
1:03:22
And the main focus point was we'll make it harder to buy outside of your local markets.
1:03:27
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?" Oh, interesting. Go buy that watch there.
1:03:41
The thinking was how do we keep it in the local markets?
1:03:42
Unclear how they'll hold that out, right? So that's really tricky.
1:03:46
Yeah, that's what was happening in the primary market in the moment.
1:03:48
on the secondary market in the US particularly.
1:03:52
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 existing in their in their lots in in the US was was much more valuable than it was, you know, a few minutes before the terrorists were live.
1:04:05
And so on the secondary side, you saw it really came down to like what type of dealer and what your economics are.
1:04:13
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, you had a lot of folks that just saw deals come through in an increase and they just sold them.
1:04:25
Like they moved product and that was like the name of the game.
1:04:27
And then you saw a lot of other dealers try to opportunistically jump their prices, you know, 10 plus% uh to all of a sudden increase that value.
1:04:35
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.
1:04:45
Everyone was out trying to buy those watches.
1:04:46
Uh, and then the prices, I would say a lot of them are 10 15% more than they typically would.
1:04:53
We haven't seen a lot of like the craziness like no one's pricing in selling at 30 plus% to try to match the 31 uh% move.
1:04:59
And then um since they announced the 90-day moment, I think things have chilled out a little bit.
1:05:08
We're still seeing pricing being up 10ish% on a lot of the sales that we're seeing come through.
1:05:12
Um but it's really interesting to see what dealers are going to do.
1:05:16
I think it's a question of if you believe the 31% is going to hold and if you do, I think you're starting to stock up right now.
1:05:27
If you don't believe it's going to hold and it's purely a bargaining chip, then I think you're kind of sitting and waiting out and seeing what happens next.
1:05:33
Are there any uh American watch manufacturers there just like popping champagne like the Hamiltons or the RGMs just being like, I've been waiting for this.
1:05:41
I'm finally going to catch up to Pekk. Uh not a ton.
1:05:46
It was It's very It's very Swissentric while you're there. Swissentric.
1:05:49
Swissentric. But uh it certainly would be a good moment to be but it was like a lot of these brands were lamenting because especially on the independent side like they had just opened up New York boutiques or they had just signed the lease in LA or whatever it is and so uh the question was how do we get
1:06:06
product there and a lot of the independent and smaller brands the answer kind of became like I I'm willing to forget the US market for a second like wow can I come up with other SKs in Europe that make up the revenue I lose in the US or can I just incentiv especially on the six figure plus pieces. Can I incentivize experiential
1:06:22
Can I incentivize 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? Yeah.
1:06:33
And and is that uh I mean obviously that's like probably not completely kosher with the tariffs, but watches are unique and 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?
1:06:46
That's the nature of the game.
1:06:48
I think most people they buy it, they strap it on and they walk out. Yeah, makes sense.
1:06:51
What about uh so one of the big concerns 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 for the Holy Trinity brands.
1:07:04
Uh are they making every single individual part in Switzerland?
1:07:07
I they I've seen those claims thrown around.
1:07:10
it almost is inconceivable, but it seems to be the case that they're not dealing with, you know, the same um reciprocal tariffs from from China or anything like that.
1:07:22
But I I'd love uh to get your point of view there.
1:07:24
point of view there. Yeah, I think for for most of the 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,
1:07:39
$10,000 AOV plus Oh, did we There are a number of brands though that will manufacture or use parts from other places and then yeah, they'll they'll behave with those tariffs 100% especially on like the I hate to say the word cheaper, but but on the the kind of cheaper less expensive less expensive is the right word. You're You're right.
1:07:56
Um what about uh any any further thoughts on the Land Dweller?
1:08:00
Uh were you surprised at at where it's being priced on uh on the secondary market at all?
1:08:06
Where is it being priced?
1:08:06
I think the steel is roughly sitting around high high30s, low 40s. Is that correct?
1:08:10
Yeah, we we actually we haven't seen any come through yet.
1:08:15
So, I'm yet to see like a transaction or a listing on Bezel for it.
1:08:19
So, uh kind of waiting to see where that lands, but uh yeah, I mean double retail I said I think I said that last week.
1:08:27
I think that wouldn't surprise me at all.
1:08:28
I since I I spoke with you all, 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.
1:08:36
I didn't think I was going to like it as much as I did.
1:08:39
Frankly, I didn't want to like it.
1:08:39
Not hater at all, but um it's just Rolex has this thing where they they they drop a model and it it's just always good.
1:08:47
Like there's a there's an executed finesse in everything that they make happen.
1:08:51
And and sometimes it's fun when when it doesn't work out, maybe. And it always works out.
1:08:57
So, it's it's quite nice.
1:08:57
I like the rose gold example better. Yeah.
1:09:01
But what is the base price at retail for a Rolex land dweller?
1:09:04
I think I think the steel example is 14. 14.
1:09:06
So yeah, more than double.
1:09:10
And then uh when the first one comes through, can you talk to me a little about like how you think about that deal on bezel?
1:09:15
Are you going to push that person to do an auction?
1:09:18
uh is that a better move for someone who is sitting on a land dweller who's thinking about selling it or should they just try and price it uh through the normal marketplace?
1:09:27
I think like uh we'll leverage the auction probably to do it.
1:09:31
We did that with the cubitus too like we we sold I think we sold if not the first cubitus at auction one of the first to go cubid eye to come out at auction.
1:09:37
Um and uh I think we'll do the same thing on the land dweller side.
1:09:43
Uh the fun thing is like the the folks that are buying the initial examples of the land dweller are doing so exclusively to be one of the first owners of the land dweller.
1:09:52
I think it's like that is the you'll pay a premium for that.
1:09:55
Certainly the same thing happened with the cubitus and and any of these these like kind of new drops.
1:10:00
If you want to be courtside wearing this watch and and have everyone know that you got it first then obviously you're paying a premium for that.
1:10:09
I don't know where it's going to settle though.
1:10:10
like uh I imagine the premium for the initial examples will be certainly over double retail.
1:10:14
Um but then like is it going to be evaluated like it's an in a Royal Oak kind of like very hyped?
1:10:22
Is it going to settle to be similar to a Datejust where it it you know it trails it's a little bit above retail but it's you know not as exciting. I don't know.
1:10:30
It kind of splits the middle there.
1:10:32
Obviously, I'm I'm leaning more towards the hype train, but yeah, 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.
1:10:42
I think I saw the picture you posted and it just looks great.
1:10:46
It's hard to it's hard to not like uh even if you're not a Rolex guy traditionally.
1:10:51
I liked it when the sentiment around PC right now.
1:10:53
Uh, I felt like the general react that the the felt like the reaction to the Cubitus couldn't have been worse online.
1:11:01
I mean, like so many people just didn't like it. I think it looks fine.
1:11:06
It wears well, but like what what's the feeling around the brand um, you know, last week?
1:11:11
Yeah, I I think like it was cool to see them double down on a lot of like traditionally interesting PC models like they're not they're deviations from the sports models.
1:11:23
like you know there was a really badass Katraa that came out in platinum with the salmon dial and it's incredible and I was my favorite watch in all of watches and wonders um to see in the middle uh and they came out with a 40mm cubitus which I think is a is a very fresh take on the cubitus.
1:11:40
The other one is just quite massive and doesn't really feel right in the wrist in in my opinion.
1:11:46
I think the vibe against the cubitus is like similar to Rolex, Pate tends to not miss like they they they kind of bat a thousand when when they do things.
1:11:56
And uh I think everyone wants these big brands to catch an L so they can talk about it and feel like, you know, they're they're able to say that.
1:12:05
Um, so I think the cubitus 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 um collectors.
1:12:23
But uh yeah, I don't know.
1:12:23
I think like I put the 40mm one on. I I liked it.
1:12:25
You know, it's it's like they make great watches.
1:12:31
It's a little bit angular and I'm a bigger fan of like a 5711 Nautilus.
1:12:36
Um, but you know, if I was allocated one of those things, I would certainly wear it and I would rock it. Love it.
1:12:43
What uh any interesting takeaways around the secondary market?
1:12:47
You were on a panel uh specifically about the secondary market.
1:12:50
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?
1:12:58
attended the event? 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 and I think it's you know we entered the space when the secondary market from a brand perception was was kind of like gh don't don't
1:13:15
don't dip your toe into it by primary only and now to see that you know I was in a panel next to Vasheron Constantine I was in Sabes and you have you know a bunch of representatives from all the top brands at the panel Um, it's quite cool to see that these primary brands are now embracing the secondary market is something that's quite interesting. And I think it allows customers to feel
1:13:35
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.
1:13:48
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 of entry to buying your first watch, but also just generally if you don't want to wait on a wait list, you know, come through and transact and buy the things you want.
1:14:07
And that's why like the tariff conversation was super interesting for the secondary market because if the premium from you know on 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.
1:14:26
Do I actually want to wait on a weight list any longer or should I just buy one that's available in the market in the US?
1:14:30
Of course sellers know that and they're pricing it up 10% but it still makes that that difference smaller than it was.
1:14:36
And so all of a sudden, maybe it's not as appealing to wait 2 years to get that Royal Oak versus just buying it right now and and getting it when I want it. Never wait.
1:14:46
Never wait to buy a Royal Oak.
1:14:46
Always buy one just immediately. just do it.
1:14:49
Um, what how does I'm curious uh how does influencer marketing work in the uh 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 um you know does this
1:15:17
athlete always roll out of bed and want to wear a Rolex, you know, like does Tom Brady always want to roll out of bed and wear like the it Rolex, you know, Submariner of the day or uh is there some type of, you know, sort of
1:15:31
transaction happening behind the scenes, whether it's free watches or, you know, it's totally possible that they just love the watches and there's enough of them out there, but but I'm curious if you have any insight there. Yeah, and it
1:15:40
Yeah, and it was a big influencer marketing year for Rolex.
1:15:45
Like I prior to Watches and Wonders, they they hinted that there'd be like a massive announcement and we were all kind of spiraling like is it a new model?
1:15:52
Are they launching a new platform? Like what's going on?
1:15:54
And they just announced Leonardo DiCaprio as an ambassador.
1:15:57
And they dropped the whole like Rolex family page where it talks about like all aspects and touch points of creative entertainment, sports, whatever.
1:16:08
Uh the dominance they have on like really influential people.
1:16:11
Yeah, they they call their they call their family page a celebration of human achievement.
1:16:17
And it's so funny because I didn't see the announcement about Leo, but I just uh Instagram just like serves me pictures of, you know, celebrities wearing watches and I'm always just like that 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.
1:16:36
And everywhere he goes, he's just getting photographed and and it's just sort of like that natural marketing. Yeah.
1:16:42
And it's funny because I mean, Leo was a tag guy for a really long time.
1:16:45
Like there's that that story where the the um in Wolf of Wall Street, he's wearing what looks like a 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 80s like you know stock markety looking watch, but it was it was tag.
1:17:04
So, um, I think the interesting part, you mentioned Tom Tom Brady.
1:17:08
Like Tom Brady was an IWC ambassador for a really long time. I love those brands.
1:17:11
I think like it's a lot easier for those guys to be a Rolex ambassador than maybe another brand that they don't wear as much.
1:17:18
When you ask the initial question of like, do I feel comfortable wearing this everywhere?
1:17:22
I would love to be a Rolex ambassador.
1:17:24
I think they're very lucky because it happens tap happen to the brand that everyone wants to wear a lot of the most.
1:17:28
Same with the APS of the world.
1:17:29
They have a lot of amazing ambassadors there.
1:17:31
Um, but yeah, I think there's undeniably uh a set of collectors that that don't want to be ambassadors because they want to wear a diverse collection, right?
1:17:42
Like I you saw the same thing uh I remember sitting down with with um some early investors in GOAT and they capitalized that in the sneaker space where you had athletes and folks that didn't want to just wear Nikes when they stepped out.
1:17:54
They wanted to wear a more diverse set of street wear and and shoes and whatever it is.
1:17:59
and the goat became the business that allowed you to to catalyze that and wear multiple things.
1:18:05
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 if 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.
1:18:17
So you're making the statement that I like wearing watches but I have a diverse collection.
1:18:24
I'm not necessarily bound to one specific brand.
1:18:25
That being said, not a bad gig to be a Rolex ambassador.
1:18:28
I think it's pretty good.
1:18:30
What What are some of the known unknowns in the watch industry for the rest of the year?
1:18:35
What are the things that we might expect announcements around, but we don't have the final details on?
1:18:42
If we want to be completely dialed in going into the next Watches and Wonders, what should we be tracking today?
1:18:50
Yeah, I think like the immediate term known unknowns is is like uh kind of a general like I don't know what's going to happen with tariffs.
1:18:59
It's going to change everything from from that perspective or is it going to fizzle out and everything's going to go back to normal? Got it.
1:19:03
So we might so we might concretize that by saying something like uh if we see an increase in uh Rolex's stated prices on their website that would be a reaction to the tariffs, right? Precisely. Yeah. Yeah.
1:19:19
um like are those prices going to be passed on to the consumer?
1:19:20
And I think like the consistent known unknowns that are always fun to to you know posit ideas on in the watch community or or like what's coming next, what's being updated next.
1:19:30
Uh 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.
1:19:38
Like Rolex pretty much exclusively drops models that are in catalog in watches and wonders.
1:19:43
So, uh, all year, uh, the watch community is throwing out their ideas, making renderings of what's going to happen next.
1:19:52
Uh, the, uh, introduction of the chat GPT image product has been funny to see, uh, because you're seeing all all of a sudden like anyone can render a, you know, a green whatever GMT or whatever makes happen.
1:20:08
So, um, 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.
1:20:18
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 going to do with that.
1:20:27
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.
1:20:34
and then to go tie this home with the influencer marketing like Federer wore a land dweller somewhere in the Swiss Alps and dropped it on Instagram and it looked unintentional but I'm sure it was intentionally you know very much planned but um so I think a lot of the the known unknowns are like what's coming next what's going to be dropped and then and then what's going to be discontinued and and replaced um that changes the market significantly. Yeah, that's very fun.
1:21:03
Well, it's such a fun market to to follow. It's so interesting.
1:21:05
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.
1:21:12
And so, no one really cares anymore, but it's like within in the watch world, it's like we're going from iPhone 3GS to iPhone 4 like every single year.
1:21:20
So, thanks for coming on and chatting with us. Great to see you, Quaid. You too, guys. Thanks. We'll talk soon. Thanks for the insight. Talk soon.
1:21:27
Our official watch correspondent. I'll be right back. Super important.
1:21:29
Uh, next coming into the studio, we have Robin from Avalanche talking about uh, nuclear energy and fusion in particular.
1:21:37
Um, 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 uh, probably I don't know maybe the smallest nuclear energy product. It's pretty small.
1:21:53
Uh, it's almost the size of a battery.
1:21:55
battery. like you can you can kind of hold this thing and uh but fusion not fision much safer uh 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 uh there have been some announcements and
1:22:11
executive orders um a lot of speculation about what might happen even Keith her boy uh was talking about um long-term looking towards energy deregulation as a potential uh driver of uh innovation we talked to a few people about how energy G production is growing 20% a year in China and 0% in the United States. We We don't love that.
1:22:32
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?
1:22:43
I think we're trying to get audio. Can you talk again? Can you hear me now? We can hear you. How you doing? Awesome. I'm doing very good. How are you? I'm great.
1:22:51
Uh can you start with just quick introduction?
1:22:53
the company and then uh the announcement. Sure.
1:22:55
So, we're Avalanche Fusion.
1:22:58
Uh I like to say we're trying to build the world's smallest fusion machine.
1:23:02
So, we're trying to do a a very SpaceX style test fail fix approach to fusion.
1:23:06
Try to be really capital efficient.
1:23:09
Uh the fusion machines we're building in our lab today are about 12 centimeters in diameter. That's the plasma core.
1:23:15
Um and yeah, uh raised a 40 million series A in, you know, fall of 2022.
1:23:22
Uh that was not an easy time back then and we've been sort of in the lab grinding and and improving these machines ever since.
1:23:29
Um 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 uh which is going to be in Eastern Washington in the Tri Cities area um called the Fusion Works.
1:23:45
And so what the fusion works is is it's basically a facility where you can come test different, you know, fusion technologies.
1:23:54
So we're going to provide the neutron generators with our fusion machines.
1:23:58
We're going to have a broad scope radioactive materials license including the most advanced uh capability to handle tridium that's available commercially.
1:24:05
And so you can kind of think of this like a wind tunnel facility for fusion.
1:24:09
So if you have some, you know, blanket technology you want to come test and see how it does, you can bring it to the Fusion Works and we'll hit it with neutrons from our machine and you can go qualify your hardware and then, you know, off you go.
1:24:23
So I think uh I'm really excited.
1:24:23
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.
1:24:32
And then we've got some really great partners we're going to be working with in Eastern Washington as well.
1:24:36
I remember talking to AJ at Hermus uh building hypersonic planes and one of the main uh hiccups to their progress is just getting wind tunnel time.
1:24:44
Uh and so I haven't heard of anyone building a wind tunnel startup.
1:24:48
Maybe that's a good idea.
1:24:50
Uh 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?
1:25:01
Yeah, so funny should they mention that.
1:25:03
So like uh AJ and and Hermus just recently announced their heat facility, right?
1:25:07
Which which which is like basically so what it sounds like after that conversation what they did was they went and built a hypersonics test facility themselves. Makes sense.
1:25:14
And so the the herbous announcement I think it was a couple weeks ago now was basically they are opening up their test facility to the rest of the DoD because there is a shortage of hypersonics testing. That's great.
1:25:27
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 um you know if it's operating 247 obviously it's going to be a much better facility and you probably don't have enough work to operate this thing at that cadence.
1:25:43
So why don't you open it up?
1:25:45
Um you can 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 and day out getting really good at what it does.
1:25:56
So it turns out that idea uh applies to aerospace and hypersonics and it I think it's also going to apply to fusion at the end of the day.
1:26:03
Yeah, it's commoditizing your compliments.
1:26:04
Okay, I got to ask I got to ask.
1:26:06
New presidential order this morning, zerobased regulatory budgeting to unleash American energy.
1:26:12
Uh there was a whole bunch of mumbo jumbo in here, but it seems it seems important.
1:26:16
Uh would would love your take.
1:26:19
Yeah, uh I read that this morning. Uh I kind of love it.
1:26:25
Um, you know, this idea that every now and then regula a regulation is going to come up for review and it needs to justify his existence is kind of awesome.
1:26:34
I can give you an example of how it applies to fusion.
1:26:36
So, you know, tridium is regulated at the state level if you're in an agreement state.
1:26:42
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 tridium in your system, you have like 30 days to report it as an incident to the NRC that you've like lost 10 curies of tridium.
1:26:59
And to to give you an idea of how small that is, an exit sign has like 25 curies of tridium.
1:27:07
So you know, here you are running your fusion machine.
1:27:09
If you can't account for 20 or 10 cury because it got like absorbed into the walls and it's self shielding, so you can't even measure the X-rays from it.
1:27:17
You just don't know where it went. Yeah.
1:27:19
Uh uh that's a big deal and you need to report that as an incident.
1:27:24
But like if someone like throws an exit sign in the garbage and nobody knows where it went, like nobody cares, right?
1:27:29
There's no like What do you mean an exit sign like like an LED exit sign you see at a theater or like what what do you mean by exit sign?
1:27:39
Is that something that like like an exit sign above the door, right?
1:27:41
Like let's say the fire there's a fire and the lights go out and you have this glowing exit sign like those are powered by 25 curies of tridium. I had no idea. Yeah.
1:27:53
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. Okay.
1:28:00
The safety associated with that was worth the very small risk of having tridium in these exercises. No idea.
1:28:06
We decided, you know, human safety over like some very They're going to freak out Jordy.
1:28:10
He's going to avoid He's going to avoid every exit sign he sees now cuz he's super paranoid.
1:28:15
They're made with microplastics, too. Yeah. Oh, no. We can't have that. Yeah, that's hilarious.
1:28:19
Uh can you give us a There's no agency.
1:28:21
So, there's no agency out there investigating missing Yeah.
1:28:26
exit signs whenever one goes missing, right?
1:28:29
That would be like silly. Yeah. Yeah.
1:28:30
And so, um, you know, I think this NRC 10 cury missing thing is an example of a regulation that maybe made sense at the time, but man, if it had a sunset clause and had to go defend itself, like everyone in Fusion hates this one. Sure. Sure. Sure. unanimously.
1:28:45
Like, I feel like this was an example of something that probably should die.
1:28:48
And, you know, if this uh executive order is a way to get rid of some of that stuff, I'm I'm all for it.
1:28:53
At the same time, it seems like uh my kind of novice understanding of it is that uh on the fision side, we are highly regulatory constrained and there's there's high regulatory risk and relatively low uh high regulatory risk, relatively lower science risk.
1:29:12
In in fusion, we're higher on the science risk and lower on the regulatory risk.
1:29:17
Is that the right frame to think about it?
1:29:19
And and can you just give us a brief overview of how American science scientists broadly are thinking about progress in fusion?
1:29:27
We hear, you know, papers go viral.
1:29:30
Oh, it's solved every couple years.
1:29:32
We're trying to get to uh, you know, net energy created.
1:29:37
Where are we on the path of progress towards uh, you know, this amazing uh, fusion future? Yeah.
1:29:41
So, I mean, we've demonstrated ignition or Q greater than one using lasers, like hitting, you know, a pellet of of dutium tridium with lasers and making more fusion energy in than the laser energy that went out. That's awesome.
1:29:54
And so, there's a bunch of fusion startups that are working on laser approaches to doing fusion energy.
1:30:01
There's another crew that are working on like magnetic confinement or com combinations of that.
1:30:06
That's like what I would consider what we're doing essentially.
1:30:08
uh CFS, Helion or Zap Energy are other companies that are kind of doing that.
1:30:14
Um they have not hit Q greater than one yet, but we're all building machines that have a chance at doing that in the next couple years.
1:30:20
And so I actually think it's going to be really exciting.
1:30:23
There's a chance that one or multiple magnetic confinement fusion companies are going to cross Q greater than one during this administration.
1:30:32
And those machines look a lot closer to what a fusion power plant is going to eventually look like than sort of the laser fusion techniques.
1:30:42
And so if that happens, and I think there's a good chance there is, um, that's going to really change geopolitics around energy.
1:30:47
You're going to see this like amazing, you know, rush to kind of try and commercialize magnetic fusion confinement, which is going to be super exciting. Yeah.
1:30:56
Um to give you an idea of like the regulatory split.
1:31:00
So right now there was a decision about a year ago that um fusion machines are going to be licensed like particle accelerators and specifically on the radioactive materials they produce.
1:31:11
And so what that does is that pushes the regulator you work with to the state level if you're an agreement state.
1:31:17
So in Washington state, it's an agreement state.
1:31:21
We work with the Washington Department of Health to license our fusion machines as particle accelerators.
1:31:26
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.
1:31:33
They come in, they review it, they do a tour, we show them what we've built, they have some suggestions on how to improve it and then a month later I get like a letter in the envel 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.
1:31:52
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 fision has to deal with it's like many many years of uh regulatory work working directly with the NRC.
1:32:05
It's a really really tough process and we haven't actually even licensed any of these small um uh SMRs that we're trying to like build here. Right.
1:32:14
So I hope that Vision gets some regulatory relief in this administration.
1:32:19
They definitely deserve it.
1:32:22
Um, we should probably talk about Texas and Utah that are suing the NRC to try and um get regulatory control over small modular reactors. That's Yeah.
1:32:34
Can you break that down for us?
1:32:34
I saw uh a couple founders tweeting about that, but I didn't really have full context. Yeah.
1:32:39
So, I went to this uh investor event in Dallas, Texas in December uh that Bolyriion Ventures put on, and Rick Perry was the special guest speaker there.
1:32:50
And I almost think I was in the room when this got decided.
1:32:53
But like Rick Perry's advice to all the vision people in the room was you should join up with Texas.
1:33:00
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.
1:33:09
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. Yeah.
1:33:18
And so I I like, you know, Brent Cougs was in there from Last Energy and he's like one of the main parties to the lawsuit.
1:33:24
So I feel like I was like a an observer to history when the fision community decided we're going to sue the NRC and get them out of Texas and uh and and if they if they succeed and Texas becomes the regulator for SMRs, um that's going to be really exciting in in terms of their ability to innovate and go faster. Yeah.
1:33:44
Uh can you talk about the positive sum nature of sort of nuclear broadly?
1:33:52
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.
1:34:00
So maybe it actually creates a dynamic where yeah you don't see energy companies suing each other.
1:34:04
They're suing the government which is very different than what's happening in AI and every other startup.
1:34:09
I don't see a lot of spying going on like we do in B2B SAS.
1:34:13
Seems like a lot friendlier community. It is.
1:34:15
I mean, the fusion people definitely, you know, kind of get rid by the fision people.
1:34:19
It's like, if only you could solve your science, blah blah blah.
1:34:22
Um, but you know, like I want I want my Fision siblings to to, you know, do awesome.
1:34:29
I think there's room for both Fision and Fusion.
1:34:31
I think my personal belief is that Fision is going to go bigger, like hundreds of megawws to gigawatts, and Fusion is going to be really great from the kilowatts to a few megawatts.
1:34:42
Um, and Fusion is going to be really great for mobility and stuff.
1:34:45
So like autonomous vehicles, fusion powered, like a Andro Dive XL or something like that.
1:34:52
Like I think that's going to be a really great application for fusion in defense in space.
1:34:55
I I think the Russians are the only people crazy enough to put a fision reactor on like an autonomous vehicle.
1:35:03
So I don't think that's a thing that's going to happen with vision.
1:35:06
But I think you know if you have lesson um I think if you have sites where there's people around like guards and stuff uh that's a great use case for vision um and uh it's going to scale like nobody's business if they can get the regulators if they can get some regulatory reef and get some reasonable regulations there.
1:35:25
So I'm really excited to see what happens over the next couple years.
1:35:29
Can you talk a little bit about lessons from the past two decades in um in rocketry and specifically lessons learned from how Elon and SpaceX approached uh building rockets versus other players in the space uh and the decision to go more modular, smaller, higher iteration speed.
1:35:50
I I I've talked to you a lot about that, but I'd love to hear you kind of retell that story. Yeah. Yeah.
1:35:54
I mean the idea that like so like I was at Blue Origin for six years working on New Glenn.
1:36:00
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 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 9month every iteration takes nine months right and it's just it's too slow.
1:36:17
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.
1:36:27
You need to be able to try things quickly and have low barriers to build things and test things.
1:36:30
And so, that's that's sort of the key takeaway I took away from New Space.
1:36:34
And we're trying to bring that to Fusion, right?
1:36:37
Like very low barriers to test.
1:36:37
We said in 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.
1:36:47
And we've actually achieved that a couple times.
1:36:49
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 down over the weekend and then off we were going testing on Monday.
1:37:01
Like we've hit that cadence a couple times and it's really kind of exciting to see that happen.
1:37:05
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 going to find something that works and then off you go. Yeah.
1:37:16
Can you talk a little bit about um uh 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.
1:37:31
But again, I've been to the facility.
1:37:33
It's a lot of wrenches and hammers.
1:37:35
Uh it's a very different culture, I imagine.
1:37:37
But uh what has that been like scaling the team and uh and getting people to adapt to kind of the different style of experimentation and work?
1:37:45
Yeah, that that's a really hard one, right?
1:37:47
Um there is not a lot of places you can go to learn how to do fusion.
1:37:52
Um and so what we've taken is a very broad approach.
1:37:56
Look, we'll teach you fusion.
1:37:58
We'll teach you plasma physics, but you bring your mechanical engineering degree, your electrical engineering degree, right?
1:38:03
You uh 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.
1:38:14
And then we will teach you the plasma physics. Don't worry about that.
1:38:17
And then we'll turn you into a fusion engineer, if you will.
1:38:20
So, I think that's kind of how we're going to have to do things for for a while.
1:38:24
Um, until sort of the universities catch up and you can take a degree in in fusionering, if you will.
1:38:31
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.
1:38:41
But, that's maybe something for a future. Yeah.
1:38:44
But, we'd like one for the studio. Yeah. Yeah.
1:38:46
Bring it in the studio in case the power goes out. We'd love that. Um, yeah.
1:38:49
Yeah, I mean there actually are some small nuclear reactors, some fision reactors at like MIT, I believe, and some and and and they work on them and they produce a small amount of radiation and there's a little bit of risk, but it's much people don't realize they're all over the country. Uh Oregon State has one.
1:39:03
I've been there like I've stood on top and like looked down at like the vision. Yeah.
1:39:07
Uh Washington State, WSU has one.
1:39:10
Um last they're called they're called trigger reactors.
1:39:15
So they're used uh basically for nuclear engineering programs to teach you have like basically students like undergrads running these things.
1:39:23
They're licensed by the NRC as nuclear human operators and stuff like that.
1:39:28
So uh I I have one last question.
1:39:30
Uh I mean we saw everyone saw Oppenheimer and everyone knows the progression of the the the the fision bomb to the fusion bomb.
1:39:37
I if these if these uh you know uh if your devices really get baked into you know society and and autonomous vehicles, is it even possible to turn it into a weapon?
1:39:48
I know obviously we'd want to be careful, but from a from a science perspective, like what is it just impossible?
1:39:54
No, it's a it's a vacuum chamber, right?
1:39:57
And it needs to have very very deep vacuum to maintain the plasma and do the fusion. Yeah.
1:40:04
And so we actually had a machine break on us when it was running.
1:40:08
So, we had this cathode that was held on with this set screw.
1:40:10
It was like one of the first janky machines we ever built.
1:40:14
And this set screw came loose and the whole rod cathode fell through the bottom, hit the window and like ended up on the floor in the factory somewhere and the whole thing just like imploded and spread glass all over the thing.
1:40:25
But like nothing bad happened.
1:40:27
Like it's just like why is the cathode on the floor? What's going wrong here? I don't understand.
1:40:32
So fusion is going to be very safe.
1:40:35
Uh, you know, some of the conversations I've had with the DOD, he's like, "Well, what happens if I shoot it like with a like with a gun?"
1:40:42
It's like, "Well, same thing with the cathode.
1:40:44
Like, it'll implode and then it'll stop and that'll be the end of it." Like, yeah. So, makes sense. Yeah.
1:40:50
The the real problem is just getting it to produce energy and that's uh that's the path we're on. It's hard enough, right? Yeah. Yeah.
1:40:55
It's hard enough to just shut it down.
1:40:57
Can you be before you leave, could you give us like a one minute uh 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.
1:41:14
Where where are all the places that we're going to put that mirror just dropped.
1:41:17
I want to hear the white mirror version.
1:41:19
version. I understand like you know the DoD applications but like uh yeah is it like backup power you know at when when a Hollywood uh you know if if they even make movies then uh in person uh is it you know uh you know for your house right like you know what are the what
1:41:36
are all the different use cases future I want I mean the practical one is they're probably going to be containerized and you're they're probably going to just be shipping containers all over the place like powering a neighborhood you So that's like probably what's going to happen. Uh
1:41:49
Uh cont everyone wants this containerized 1 to 5 megawatt form factor it seems like.
1:41:56
So that's like probably what's going to happen.
1:41:58
But like the atom punk 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.
1:42:10
You could just like flip on the fusion reactor and go go on fusion power. Um pretty awesome.
1:42:14
I've driven around San Francisco in a Delorean with a plastic 3D printed fusion reactor last year at Deep Tech Week.
1:42:23
I'd love to do that with a real one someday. So, that'd be fantastic.
1:42:28
Uh, well, thanks so much for stopping by.
1:42:29
We'll we'll we'll talk to you soon.
1:42:31
Congratulations on the launch. Yeah, congrats. Thank Cheers. Take care.
1:42:37
Hopping on next, we got Russ. Is that right? Yes. From LiveKit IO. That's right. That's right.
1:42:41
Coming into the studio, we got our next guest joining. Some big news today.
1:42:47
Big pivot from watches to fusion reactors.
1:42:48
But that's the nature of the show, folks.
1:42:50
We're we're we're men of many talent. Keep you on your toes. Keep you on your toes.
1:42:55
Uh we'll do dedicated days where there's one theme.
1:43:00
Some days you just get a tour of the entire technology industry.
1:43:02
Um so welcome to the studio, Russ. How you doing today? I'm good. I'm good. All right.
1:43:09
So you're saying that I'm following fusion reactors.
1:43:10
We're following Fusion Reactors and immediately before that we were talking about fine watches made in Switzerland.
1:43:18
So we got a little bit of everything today.
1:43:19
Taking us on a whirlwind tour.
1:43:19
I don't know if I can follow Fusion Reactors, you guys. I'll try my best.
1:43:25
Well, we're excited to talk about Voice AI. Yeah.
1:43:27
Uh 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. Yeah. Um so I'm Russ.
1:43:37
I'm the CEO co-founder of a company called Live Kit. live kit.
1:43:39
Um so LiveKit uh what we we started actually as an open source project.
1:43:45
So uh back during the pandemic, you know, if you think about all the technology that Zoom has um underneath, we started an open source project uh 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.
1:44:08
So you could connect any two people or any number of people on the planet kind of instantly with less than 100 milliseconds of latency over video and voice.
1:44:16
Um, fast forward like about a year and a half, two years and uh we built a demo when chat GPT first came out uh where you could talk to it instead of text with it using live kits infrastructure and a few months later OpenAI ended up finding it.
1:44:35
uh wanted to build a voice interface to uh Chachi BT and we started to work uh pretty closely with them um on voice mode and then advanced voice mode after that and uh kind of almost by accident I guess we got uh pulled into uh this AI space AI it was not a space back then accident yeah I remember our series A
1:44:58
which we closed at the uh we closed the first trunch at the end of uh 2023 2020 just at the start of 4 and uh everybody was just telling me that hey this is cool but voice isn't going to be a thing for 3 to 5 years and uh then of course GPT40 happened and yep can you steal man at all why speech to text is still bad on my iPhone? I I
1:45:21
I I just really wanted to be good is John's a big voice guy.
1:45:28
He's always he's always he's always using LiveKit unknowingly.
1:45:30
I worked at I worked at a voice AI company in 2010 or something. Twilio. Yeah.
1:45:35
It was you know Dragon naturally speaking. I do.
1:45:39
Dragon eventually acquired this company and it was like it was direct competitor to Siri.
1:45:43
Apple bought Siri and Vingo was purchased by Dragon and their primary it was such a fun startup.
1:45:52
I think I remembering Blingo.
1:45:52
It was it was a good company.
1:45:54
I think it was a good good exit for everyone involved too.
1:45:57
Um and their their primary target was Blackberry.
1:45:59
you would and their whole goal was let's get pre-installed as Blackberry, but there were a lot of there was a lot of chaos in the market at the time with uh it was a $20 app then they had to cut their pricing, do an ad model, all these different things going on.
1:46:12
Um but um I' I'd love to know like just if you were in charge of, you know, Apple, uh how would you improve speech to text?
1:46:24
Um speech to text specifically, like transcribing text.
1:46:27
Oh, well well anything in in voice agents or just just just improving the customer experience broadly like surprise and delight, right?
1:46:36
Well, you know, it's one of those things that I think is funny like people talk about hallucinations as this bad thing.
1:46:41
Um but in a lot of ways for like kind of this speechtoech interaction model where you're talking to an AI, right?
1:46:48
Hallucination is a feature.
1:46:48
So, if you remember like your Alexa or Siri, like when you were talking about this, you know, 2010, 2012, you go and you ask it a question and it's just going through a bunch of like a decision tree and 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."
1:47:05
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.
1:47:15
You just don't want to use the thing anymore and you stop using the thing.
1:47:18
But with kind of these new models that actually, you know, hallucinate answers into existence, even if it doesn't know the answer, it tries, um, you always get a response, uh, that comes back from the model.
1:47:29
And for for like voice interfaces, that actually can be more of a feature than a bug.
1:47:33
Um, it also helps that these models, it's funny because it's it's human, right?
1:47:38
So like if you're having a conversation, John askked me a question, I don't know the answer.
1:47:43
I go, well, like is it like this thing?
1:47:44
And you're like, no, it's this thing.
1:47:46
And like but but for some reason with like you know these older generation of models it was like very annoying to like go down that wrong sort of Exactly.
1:47:54
And it's always the same answer, right?
1:47:55
It's like I don't know or I can't help you with that.
1:47:57
I can't help you with that or I'll search Google for you or whatever.
1:48:00
Um 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 100% correct or not.
1:48:13
I think that that um just makes the user experience so much better with these kind of modern or contemporary uh voice agents that you interact with.
1:48:20
So, you know, I I I think the the other thing I'll say related to the Apple stuff and um that's improving very quickly is a latency.
1:48:30
So, like we have a lot of um providers out there now, Grock, Cerebrris, folks like that who can run inference much faster than um even a year ago for for some of the model providers.
1:48:42
And now like LLM inference can actually be done in less time than generating speech with with TTS.
1:48:50
And so um I think like getting that latency end to end down you know to 300 milliseconds or 500 milliseconds on average for like turn latency um that that that kind of helps you cross this uncanny valley for for voice AI.
1:49:04
I mean, should we be thinking like even faster than 300 milliseconds?
1:49:09
And is there any efforts that you've seen to bake some of these models down into silicon?
1:49:13
We've seen what Etched is doing with putting the transformer architecture on silicon.
1:49:19
Uh you could imagine that once midjourney gets good enough uh or kind of hit some some peak that they would just bake it down into silicon.
1:49:25
We would just have image generation models, you know, AS6 essentially like what happened with Bitcoin.
1:49:30
Uh is that the future here?
1:49:33
Not that you would pivot into hardware, but maybe you would like vend your software into a hardware provider at that at that level.
1:49:39
Um, well, so we like I mean we partner with like folks like Cerebrus and Grock.
1:49:43
Um, and so we allow you to kind of plug in their models and plug in effectively their hardware accelerated inference.
1:49:50
Um, and and so we're we're compatible with that world.
1:49:55
I think on the inference side, you can defin I think it's going to continue to push as low as it can get.
1:50:01
Um there there's obviously some limits.
1:50:04
You know, it's a trade-off between uh kind of capabilities and level of knowledge and how fast you can kind kind of, you know, run that that pass through uh the model to get the result out.
1:50:14
So there are trade-offs of course that follow the laws of physics, but there's also kind of diminishing returns after a while.
1:50:22
To give you an example, I once built this uh this cerebrous demo.
1:50:24
I used like a llama 7B or 8 8B. Uh llama 8B.
1:50:30
Have to remember these numbers on the printer counts.
1:50:32
But uh llama 8b hooked up to cerebrus and I got a bunch of feedback on that voice demo that the model was responding too fast and can you slow it down and it's kind of going off the rails a little bit. Yeah. Yeah. Interesting.
1:50:47
I I mean on that note uh is there a 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.
1:51:02
Like some people want to have, you know, this really fast back and forth conversation and I'm like just get to the point you're I'm just trying to book a flight.
1:51:08
Can I just like just give me the information as quickly and condensed as possible?
1:51:12
Other people might might prefer an agent that speaks slower and really trs things out and gives the full context and then lets them answer and and kind of ping-pong back and forth that way.
1:51:23
Uh 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.
1:51:31
Yeah, it's already happening.
1:51:31
So, I think that there's kind of two uh different flavors of this.
1:51:34
Um and you can kind of combine them together uh over time.
1:51:38
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 open AAI realtime API there's Gemini multimmoal live API um there's a few others coming out as well and um for all of these models uh that natively understand uh audio um you can actually tell them to you know whisper or slow down or uh speed up or act hyper.
1:52:04
you can kind of give them an explicit signal of um the style or the way that you want them to communicate with you.
1:52:13
So that's already available and possible with these models.
1:52:16
Um then there's another part of it which I think will come uh in the next you know year or two uh 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.
1:52:35
Uh, 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 in a hurry or this person is calm and like relaxed and it can kind of tell that by your body language and by the way you're speaking and it can automatically adjust to you in the same way a human would be able to.
1:52:54
Um, so you guys work with a lot of the biggest companies in voice already.
1:53:01
Open AI, Speak, Character AI.
1:53:01
You're working with Tinder.
1:53:04
I see like really broad swath of companies, Spotify, Oracle, things like that.
1:53:08
Are you seeing as many startups as you would like sign up and start building in voice AI?
1:53:13
It feels like a category that for if you go back like 5 years ago, people were really excited about voice, but then you had these sort of like high-profile uh companies that didn't quite work, but you know, maybe in many ways they were just too early.
1:53:29
So what are you seeing on the on the startup side in terms of new companies being formed specifically to leverage voice and and LiveKit and the underlying models?
1:53:37
Yeah, we're seeing uh probably about um you know we're doing like thousands and thousands many several thousands of um of like signups to the to the cloud product, our commercial product.
1:53:48
And um most of those the vast majority are are startups and growing companies.
1:53:53
And out of those probably around 75% or so 80% of those signups are uh are voice AI companies that are building voice agents.
1:54:02
And so the way that I kind of see the market uh 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 talk to about kind of anything, right? They're assistants.
1:54:21
you can they do question answering, they do therapy for mental health, all kinds of language learning in the case of speak.
1:54:28
Um, and then on the other side you have these kind of pockets that are what I call kind of voice native systems.
1:54:35
And those are really anything you pick up the telephone uh 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.
1:54:54
Um there's a lot of these kind of business process flows where um these are there are pockets that are like really large in nature.
1:55:04
So customer support is the one that gets talked about a lot, right?
1:55:07
Like some of the markets that Sierra Decagon and folks like that are playing in.
1:55:10
Um, and so for all of those systems, we're seeing tons of startups flood into those spaces because it is now viable to take um, 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. Well, yeah.
1:55:31
The thing the thing that I'm excited about, everybody's gotten on one of these like robo uh CX calls and you you know I've had the experience in the past where I just say talk to a human until I get to a human because I know they're not going to resolve like the issue the way that I want and I'm like the annoying guy to the robot.
1:55:49
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.
1:55:57
They're not in a bad mood that day.
1:55:59
like, you know, they're they're really, you know, they they just have like high energy because they're code, right?
1:56:05
There's going to be a flipping and it's going to be like, "Oh, I'm talking to a human.
1:56:07
Robot, robot, please put me on with the robot."
1:56:09
Yes, throw me on the robot. Yeah.
1:56:11
I was uh I was on a customer support call with Comcast uh the other day and um 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?"
1:56:29
and like, "Where do you live?"
1:56:29
And I'm like, "California."
1:56:30
They're like, "So, do you experience snow in California?"
1:56:33
I'm like, "Well, in Tahoe, yeah, I guess."
1:56:35
But, uh, it was so weird.
1:56:35
And I was just like, "Am I talking to an AI right now, or is this a human?"
1:56:39
And if it's a human, I kind of want the AI.
1:56:41
And so, it's very bizarre. Super awkward.
1:56:45
Uh, can can you tell me about some of the more like nuts and bolts uh enterprise customers you're working with?
1:56:50
Uh, I see this case study from Playback.
1:56:52
We actually had the CEO of Playback on the show.
1:56:53
Uh, live streaming for sports. Makes a ton of sense.
1:56:56
uh do you know exactly how they're leveraging LiveKit and how you can uh kind of give us a more concrete example of like their infrastructure basically? Yeah, for sure.
1:57:06
Um so Playback uh they're also going to integrate uh you know AI into that flow as well like a voice-based commentator or whatever that can watch the game and provide an overlay for for fans.
1:57:16
But they use us for a pretty different use case.
1:57:19
In that case, they um they have these kind of courtside cameras at like NBA games, MLB games and all of that.
1:57:27
And these cameras are, you know, the way that you watch sports on TV.
1:57:31
Um, 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.
1:57:51
Like you're seeing plays before they are sometimes up to like 30 seconds or a minute before.
1:57:56
And so the technology that we use for live broadcasts of sports games is not true real-time technology.
1:58:03
is not true real-time technology. Not everyone is synchronized in the same way that in 1969 when the you know the lunar landing um everybody saw that at the same time because there's a server that is sending all these kind of broadcasts out over uh TV antennas that are receiving these things and uh it is truly a shared experience and so playback what they do is they ingest uh
1:58:26
the the video feed from these cameras uh at courtside or at the MLB game and that's they're ingesting it using LiveKit that goes into a single system and then LiveKit's cloud network effectively everybody who's watching that that NBA game for example uh we are effectively shuttling those bytes from that camera uh in a synchronized way to every single person that's watching that game. So when like Steph syncs a three,
1:58:52
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.
1:58:58
able to truly have a shared experience of watching their favorite team play the game together, cheer together, all of that stuff.
1:59:05
And so, um, playback is effectively using us for the backbone of all of the audio and video, um, kind of transmission that is going on within their application. Makes sense.
1:59:15
Uh, before we let you go, we should probably talk about the news today.
1:59:19
You guys had a bit of an announcement.
1:59:21
Uh, why don't why don't you share a little bit there? Yeah, for sure.
1:59:24
Um, so kind of how I mentioned at the start, right?
1:59:27
We started as an open source project, you know, connecting humans to other humans.
1:59:31
Um, but now we have found ourselves kind of operating at a very large scale, um, connecting humans to machines, so using voice and and computer vision.
1:59:39
And, uh, and so we, uh, we closed a series B today.
1:59:44
Um, that's led by Alimter Capital. Um, let's do it. [Music] Let's go. Let's go. Um, yeah. Yeah.
1:59:56
So, we we closed that round and uh now we're we're really going after voice AI.
2:00:00
We're building like an all-in-one platform for anybody any developer to build a voice agent. Give us the stats. 1 million 2 million. How much did you raise? 45 million. 45 million.
2:00:11
I got I got I got to do 45ion.
2:00:16
I'm not going to submit to that.
2:00:16
But, uh congrating amazing milestone.
2:00:18
I I think uh you know uh clearly like a a fiveyear overnight success. Yes. classic classic example. But um it's cool.
2:00:28
I I love these stories where where you sort of work on a really hard problem and then discover like you know the entire most powerful application you know years later.
2:00:39
So congratulations to you and the teams.
2:00:43
Great to have you on your new official voice AI infrastructure correspondent. You love that line.
2:00:48
I'll just make I'll make a clone of me and then that will be your official Yeah. voice AI correspondent. Cool guys. That's perfect. That's perfect.
2:00:55
Thanks so much for stopping by. Thanks for coming. Really appreciate it. Have a great one. Talk soon. Talk soon.
2:00:58
And next up, we got Ev Randall coming in from Kleiner Perkins.
2:01:03
I love how like there's always like you can always go niche enough to make somebody a correspondent. Yeah, exactly. Hyper hyper niche. Uh anyway, $45 million.
2:01:13
That's a great That's a great round.
2:01:14
We There are so many funding rounds happening now that we're like in the thick of it.
2:01:17
I'm realizing like, wow, like the money is flowing in Silicon Valley. It's great.
2:01:21
But we will get a full market update from EV hear what he's seeing over at Kleiner.
2:01:26
Uh uh actually crossed paths with him at Founders Fund two years ago, maybe two and a half years ago. Uh great dude.
2:01:35
Wrote one of the most probably banger memos during the Zerp era all about Tiger Global and crossover investing and I want to follow up with him on that, but I think we have him here. Ev, are you there? Welcome to the studio.
2:01:46
Hey guys, Jordy Kugan, great to be here.
2:01:51
long time friend of the pod.
2:01:51
Finally, dude, it shouldn't have t It should not It should not have taken this long.
2:01:56
You're in our original pitch deck because you posted like, "How can I go long?"
2:02:00
which hilariously caused a lot of problems for us because someone created a fake uh pump. Fun token about us.
2:02:04
And everyone was saying, "Oh, they endorsed this."
2:02:09
And we were like, "We did not. We just Yeah.
2:02:11
By the way, I didn't get rich off that."
2:02:12
So that that is I I have a bone to pick with either the creators of the coin or you. I don't know which one.
2:02:17
Don't even joke about it.
2:02:17
It's just don't even joke about it.
2:02:19
You say anything, they'll they will they will turn it into a into a coin.
2:02:22
Anyway, but it's great to have you.
2:02:24
Thank you for the early support.
2:02:25
Um why don't you John gave a little introduction, but why don't you introduce yourself? Yeah. Yeah.
2:02:31
What are you uh what are you working on most recently? What's interesting? Yeah, of course. Yeah.
2:02:34
So, I'm a partner here at Kleiner Perkins KP obviously one of the more storied firms um kind of in venture capital history.
2:02:42
Um as a firm we've led early rounds of you know companies like Amazon, Google, Janentech, Sun Micro Systemystems, more recently companies like Ripling, Figma, Glean, Harvey and many others.
2:02:51
Um you know ventures evolved dramatically.
2:02:54
Um obviously over the last 5 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.
2:03:04
There's 10 of us total on the investment team.
2:03:05
Um, and we all just care very deeply about the craft of venture, founders, company building.
2:03:12
Um, and and we want to keep it a craft.
2:03:14
So, we um, I mean, we're fully multi-stage.
2:03:16
So, we have an early stage fund, we have a growth fund.
2:03:17
Uh, we announced a new set of, uh, of funds last summer that were $2. 1 billion in total size.
2:03:23
We can do seed through preIPO.
2:03:25
I personally help head up our growth fund.
2:03:27
Um, so I spend, you know, the vast majority of my time kind of on series B and beyond investing.
2:03:31
Um, but all of us invest across the venture and growth funds.
2:03:35
Um, so I've led, you know, our investments in companies like Flock Safety, um, Huntress, a cyber security company, Captions, uh, involved in our investment in Rippling, and a few others soon to be announced.
2:03:45
How would you how were you processing the tariff news?
2:03:49
Were you just texting every portfolio founder like, "Hey, have you seen this?" Yeah.
2:03:54
Sending them a sending them a uh screenshot of the 15%.
2:03:57
What are we doing about this? Hey, wait. Yeah. Can you fix this?
2:04:01
Hey, what are we doing about this? Yeah. Is there a memo coming?
2:04:03
Is there a black swan memo?
2:04:05
Are you going to get in the black swan memo game?
2:04:06
Give a run for their money.
2:04:08
Sequoa has pretty good market share of the of the black swan, you know, memo market.
2:04:12
And so it feels like, you know, it feels a little too mimedic.
2:04:16
I'm I'm a little too chill pill still to to do something that mimemetic. Yeah.
2:04:20
Uh well, but uh I mean, how have you been processing it?
2:04:22
Uh do you think it affects tech?
2:04:24
Do you think it affects any of the I mean like immediately the reaction was like all the the NASDAQ was way down but at the same time like even semiconductors were you know on day one kind of excluded.
2:04:35
Uh was there is this something that all founders should just tune out or is there something here to pay attention to?
2:04:40
I think I think it's it's probably both, right?
2:04:42
it's probably both, right? Like I think um I think Mike Mcdano from from Lightseed had a good tweet um or or post today or yesterday where uh he was like I'm getting a lot of questions from maybe it was LPs about the tariffs um and they have to to realize you know I invest in companies that aren't going to exit for 7 to 10 years and so there's
2:05:01
like something about the like duration of the asset class where um 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. Um and so
2:05:18
Um 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 want to do to get liquidity.
2:05:26
want to do to get liquidity. I think at the same time um the the like underpinning like the undercurrents of what's going on um uh especially politically are immensely relevant for for startups and tech like obviously everything around Taiwan and and just like semiconductors generally um and and if that escalated how bad it would be
2:05:46
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 um and I don't think that people really have an appreciation just for how permeated um you know semis and other um critical materials and inputs um from from places like Taiwan are in our day-to-day lives. Um so I think it's
2:06:08
Um so I think it's it's of of critical importance, but again it's like it's one of those things where it's like well what are you going to do about it, you know, unless you uh there there's very few um uh you know there's very few companies or or or um folks that can actually have an impact on this.
2:06:22
And so I think for most companies it the best advice is always just to go heads down and and well yeah let let's talk about one of the immediate impacts which is the IPO window which was so briefly open uh feeling like it slammed shut.
2:06:33
Uh I love when it's open personally I wake up I wake up I I get out of bed of open window huge fan of open IPO windows.
2:06:41
Not so poor poor CLA and StubHub you know they've they've been uh waiting around. Yeah.
2:06:50
A moment of silence brought to you by RAMP.
2:06:52
Um, no, but uh, yeah, I don't even know if like, you know, Circle gets out at this point.
2:06:57
Um, but, uh, at some point you can imagine the companies that end up going out are the ones that have to go out 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. Yeah.
2:07:15
We're not going to touch it.
2:07:15
But what's your what's your kind of read on on that situation?
2:07:19
on that situation? Yeah, I think I 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 um ready to go right when this blew up and so so
2:07:31
it seemed like ah you know we we're opening things back up and then uh immediately some black swan event happened and it kind of shut it back down but for for you know uh like a full almost 9 to 12 months before that it was a solid environment. It wasn't, you
2:07:43
It wasn't, you know, IPOing in 2021, um, where where you could go and, you know, spack for 50 times AR or something, but it was not a bad environment.
2:07:51
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?
2:08:06
Um, but then also just as important, like do you want the IPO markets?
2:08:08
Um so on the first one I went and counted this morning the number of public software companies on um you know the merit kind of software comparables index that they run um that currently have over $500 million in ARR um which is like an incredible achievement and right now there are over 80 public SAS companies that have more than $500 million of AR.
2:08:29
Um, 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 SAS company that can give you exposure to some theme or trend or idea that that you want that already exists.
2:08:41
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.
2:08:51
Um, it's much harder to have an IPO that they're going to care about.
2:08:55
Like you probably need to be free cash flow positive.
2:08:57
It probably helps a lot if you're closer to a billion dollars of revenue scale than even $500 million, which is already incredible.
2:09:02
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.
2:09:12
So, I think like one that's like that's already hard enough.
2:09:14
And then on the other side in terms of like do you want the IPO markets?
2:09:18
I think what we're seeing out of several of the very very best tech companies um is is that they've gone to pretty drastic measures to not IPO.
2:09:26
And I think there's like many reasons why you'd not want IPO.
2:09:29
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 um at like $55 billion I believe it was.
2:09:42
Data Bricks obviously in Q4 did a mega raise for the same reasons.
2:09:45
And the asset class has grown so much that if you're an amazing company compounding your intrinsic value at 25 30% a year at scale, you can raise practically unlimited capital.
2:09:55
Like data bricks raised 10 billion of equity.
2:09:57
Um they did a you know multi-billion dollar debt raise too but 10 billion of equity in like I think you know it was probably like 3 months.
2:10:04
Like it didn't take very long to raise an unbelievable amount of equity.
2:10:08
Um, so, so the the fund sizes have gotten so large and the amount of capital that's available for these companies, um, is so large, as long as you're one of these like top 10 companies that if you don't want to IPO, you don't have to.
2:10:18
And I think there's several reasons why you wouldn't IPO.
2:10:21
Um, the main one or one of the main ones is that you can be a lot more aggressive on M&A.
2:10:25
Um, you know, Data Bricks, for example, you know, bought this company Tabular.
2:10:28
Um, I think the reported valuation was 2 billion and it was also reported that they were either pre-revenue or close to pre-revenue.
2:10:34
Um, if you're, you know, Snowflake and you're a public company, um, you probably can't buy a pre-revenue company for $2 billion.
2:10:42
Like, your stock probably goes down 20% the next day.
2:10:43
Um, almost said effing, but I think this is a PG show, so I'm not going to not going to cuss.
2:10:50
Um, uh, but, you know, the stock probably goes down 20% if you do something like that.
2:10:54
That's an extremely strategic acquisition that Data Bricks is able to do because it's completely founder controlled.
2:11:00
No activist can buy 10 to 15% of your stock.
2:11:01
No one can mess with you.
2:11:03
So, I think there's good reasons to do it.
2:11:04
And the only thing that you have to figure out um if you don't want IPO is you have to give employees liquidity.
2:11:09
Like you have to give employees regular opportunities.
2:11:11
We we love when employees get liquidity but what about if you're a you know just a $2 billion fund and you know you're trying to show DPI to your LPs.
2:11:26
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 uh employee liquidity?
2:11:50
Is that a potential future if companies are just staying private?
2:11:54
Yeah, I think we are we're just now in the early innings of this.
2:11:56
Um, but we are 100% starting to see it.
2:11:58
We we certainly have not done like a a continuation vehicle um is is kind of like the most common term for this like a CV where you can sell essentially like a slice of your fund.
2:12:10
Um because you know commonly venture funds have like a 10-year life and then sometimes you can have an option for like two years of extension. Yeah.
2:12:18
And then after that, you're kind of supposed to be have the capital returned and like everyone can move on with their lives.
2:12:23
Um hopefully hopefully much richer for it.
2:12:25
Um and uh and you know, SpaceX has been a private company for what 20 years now.
2:12:31
Um you know, over 20 years.
2:12:33
Um and so I think the most common vehicle for this would be a a CV um where you sell either like a bundle of company, like a slice of your holdings or like a slice of your fund.
2:12:45
And you're starting to see that like several funds have done that.
2:12:47
I think I think NEA um has has has done it in the last year or two and you're seeing more funds do it.
2:12:52
We certainly haven't done that before, but I think as an asset class, we're going to 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.
2:13:02
Um and it's actually um 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, you know, again compounding their value at 30 plus% IRRs for much much longer than they used to.
2:13:15
And so um obviously you can sell in these rounds like I think like obviously SpaceX SpaceX is extremely liquid. Stripe is pretty liquid.
2:13:23
Data bricks I think is like very liquid.
2:13:24
There's some names that are very liquid but it's only the best names where that exist.
2:13:27
And so if you have a portfolio of names that are good but not like SpaceX level call it um then then your your best bet is probably one of these CVs which is um which is very very common in private equity.
2:13:38
Um but as venture kind of becomes more more institutionalized um we're going to see a lot more of them for sure.
2:13:44
Speaking of DPI, it seems like you got some mathematical formula behind you.
2:13:48
Can you break that down for us?
2:13:48
Are we are we leaking alpha right now? What's going on?
2:13:52
Just copy paste that and I get your returns.
2:13:54
Yeah, I um I was trying to figure out the equation for DPI.
2:13:58
I've been searching for a long time. That's the first one.
2:14:01
The second one um I was also trying to find the equation for Delian's gross margins on his investments.
2:14:07
Oh yeah, that one that one actually might be that one might be harder to find than the equation for DPI.
2:14:12
Um yes, a little little Easter egg for uh for um how do how do you and the the team uh decide if something is is in the wheelhouse or not?
2:14:24
obviously 10 10 people on the investment team.
2:14:26
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.
2:14:42
Clearly willing to kind of, you know, look uh everywhere for opportunity. Yeah, 100%. Yeah.
2:14:47
opportunity. Yeah, 100%. Yeah. I love to say that there's um you know a lot of people talk about um Conway's law which is like you ship your org chart um and as it relates to to kind of like how companies mature and ship product over
2:15:01
time uh and I love to say that like Conway's law exists for venture firms for sure which means that you like you invest your work chart um 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. Um, so for our team,
2:15:17
Um, 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 want to be involved in our companies, we can't do that many investments per investment professional.
2:15:31
Like we we need to we need to really stay concentrated and stay tight.
2:15:33
I think you also see this at at my, you know, my previous employer, Founders Fund.
2:15:37
Um, you see these these headlines where they're doing massive massive checks into really high quality companies.
2:15:42
And I think it's because it's also a small really lean team um that has the trust and a high uh degree of relationship with really strong founders.
2:15:50
And I think we we approach especially growth investing with the same model.
2:15:54
Each of our growth funds is typically only 10 to 12 core investments.
2:15:57
Uh and so every single investment that we're looking at needs to have something very unique or special about it where um we can you know look around the table and say this is going to be a company that we're talking about on TVPN in 10 years.
2:16:09
um as as you know one of the top five companies in the world like it has that potential every single time.
2:16:16
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 12th 21 you dropped playing different games or why Tiger is eating your lunch and your deals.
2:16:31
your deals. uh this cycle it feels like we haven't no crossover funds have really made a name for themselves but at the same time data bicks is doing bigger deals than ever there must be new pools of capital coming in what does the late late late stage look like and how is it changing yeah so it's funny I actually dropped a sequel to playing different
2:16:53
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 SQL anxiety about it and so I just like kind of like quietly put it out there because I'm like ah like my thoughts should probably be out there. Um but it's called game
2:17:07
Um 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 um and and I use a Game of Thrones analogy in in playing different games so I'll use one for this too.
2:17:24
um that 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.
2:17:36
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.
2:17:41
And 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.
2:17:48
And I think the kind of version of that that happened to our asset class is that um obviously people saw Tiger kind of fail the marshmallow test of like they went too far too quickly and kind of stretched the bounds of what you could do um and and definitely paid the price for it.
2:18:02
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.
2:18:11
And so it's like, okay, yeah, like you don't have Tiger, but like how big is Andre's last fund, and how big is General Cat's last fund, and how big is Lightseed's last fund?
2:18:18
There's like four or five of these folks that have like filled that gap um and continued what I think is like a um like a a secular trend towards platformization in the asset class.
2:18:29
Um I think that the to your specific point around um like our crossovers kind of like coming back into venture and playing in in the asset class again.
2:18:37
I think the most important thing here is that like venture means at least like four or five different subasset classes, right?
2:18:43
Like venture includes growth, but then like investing in an in in you know entropic at 62 billion and investing in a 100 million AR company that's growing like 20% at like eight times AR.
2:18:55
Both of those are called growth investing. Yeah.
2:18:57
But they're like like as different as you could get in every single way.
2:19:01
Um so like are crossovers doing venture again?
2:19:04
I think yes, but they're sticking more to their knitting like is like do you want capital doing series B's?
2:19:08
Like no, but they're you know I know several crossovers that have invested in like majorly in the big labs for example.
2:19:14
Was there any investments that Tiger did that you wish you did?
2:19:19
There has to be there has to be some, right?
2:19:22
Because like I remember FTX was like spraying money like crazy too, but then they invested in Anthropic and like they kind of made it all back in one trade, right?
2:19:31
So do and and Tiger hasn't 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?
2:19:42
You know, it's f I mean, this is probably just a rumor.
2:19:46
rumor. Um, 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 Curtis trend at at Tiger where like, you know, like he did push for them to to get into data bricks and like that's gone really well and it's like a truly generational company and like, you know, it's
2:20:05
probably going to be an amazing investment for them and like uh and so I I I don't know their their full investment track record and returns, but I do think there is like a potential where like I don't know if data bricks is a $500 billion 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
2:20:20
Like I think if you look at someone like Neil Meta's track record, it's like is his hit rate like 90%.
2:20:23
No, there's like a ton of flame outs in there.
2:20:25
Um but he's just invested in situations where he's put you know 400 in and gotten 5 billion out and it turns out like if you just do that at even at the growth stage like the power loss still exists and you still have like an amazing track record.
2:20:38
So I mean they're they're huge investors in Whimo.
2:20:40
This is Tiger would love to be in Whimo.
2:20:42
Um I think I mean it's like an unbelievable technology company.
2:20:45
Obviously, they they're huge investors in data brick, so I'm sure there's lots of investments like that for them.
2:20:48
Yeah, that's fascinating.
2:20:50
Well, well, uh this was a really great conversation.
2:20:51
We'll have to have you back really really soon because I'm sure we could talk for two hours about Yeah, let's make it a regular thing. This is great. Anytime, guys. Thanks so much. Thanks. Thanks for the alpha. Talk soon. Cheers. See you.
2:21:03
The uh the little jab back at Dallion is perfect. It's great. Chef's kiss.
2:21:06
Uh we're not going full like Jerry Springer yet, but we like a little bit of drama on the stream.
2:21:11
When the when the SAS companies are spying on each other, we're covering it.
2:21:15
When uh the Wall Street Journal's putting a robotics company in the truth zone, we're covering it. That's right.
2:21:21
And coming up next is uh just a great story about Zipline.
2:21:26
We got Keller coming in the studio to break down uh the news that Zipline, the drone delivery company that has been around for a long time.
2:21:33
uh although not operating on America's shores went and found a less regulated environment delivering life critical medical supplies and blood I believe uh scaled their business did all the R&D risk in a low regulatory risk environment and is now ready to come back and has some really amazing partnerships and so they are back we're excited to uh invite Keller on to the show and give us a breakdown on what Zipline is up to these days.
2:22:03
Keller, welcome to the studio.
2:22:05
Hey, thanks for having me.
2:22:07
Thanks so much for joining.
2:22:09
Uh I I have to say first fantastic launch video.
2:22:12
There are so many launch videos these days that I I mean I'm you know uh suspect number one in propagating this type of content that's uh oh let's pull Top Gun footage and uh oh like like let's put Freeird over it and we're hard techuck 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.
2:22:32
you went a very different direction with this announcement and so uh 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. Sure.
2:22:43
Um yeah, day before yesterday we officially launched our next generation service in Dallas.
2:22:48
So as you mentioned, you know, Zipline has been operating these autonomous delivery services across eight countries over the last 11 years.
2:22:57
Um, but really this is the first time we're seeing like major metros start to launch and scale in the US.
2:23:04
Our first customer is Walmart.
2:23:07
We're, you know, we've already announced a number of other partners like Chipotle and Sweet Green, Mendescino Farms and and a lot of the biggest health systems in the US who are all relying on this technology to automate uh and accelerate their deliveries from uh businesses or hospitals or warehouses directly to homes. Mhm.
2:23:24
Uh do you feel like this opportunity is underhyped today?
2:23:28
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.
2:23:44
You're partnered with Walmart.
2:23:46
I'm going to be able to drop a burrito on John's backyard if I want.
2:23:48
Um I mean, they start you guys started in 2014, right?
2:23:53
So complete overnight 2013. Really? Yeah. Yeah. We love a 10.
2:23:55
We love an overnight success on this show. So congratulations.
2:24:00
You're going to be a household name soon.
2:24:02
Everyone's going to be like, "Oh yeah, he just did so quickly.
2:24:04
Maybe I should get into that market. Maybe I should." No.
2:24:05
Hope hopefully it makes hopefully it makes sense.
2:24:08
But I think there's this trend in technology where people get excited about the potential of an opportunity and then the reality sets in that it's really really hard to do and then there's this period where you know it gets less attention.
2:24:19
and it 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 in the sky.
2:24:26
Um so yeah, I mean talk about your maybe excitement today.
2:24:32
I'm sure it's more than more than ever.
2:24:34
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 ex extraordinary you know excitement this is coming tomorrow.
2:24:46
I mean, when we started, you know, the CEO of one of the largest tech companies in the world was on 60 Minutes promising that they were going to be doing drone delivery to every home in the US within 2 years.
2:24:56
And so, we always assumed we would be a fast follower to them.
2:24:58
You know, we thought they were going to lead and we would be a fast follower.
2:25:01
Had you told me that 10 years later, Zipline would be crossing 100 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 11 one,000th of the scale.
2:25:14
I mean, would have seemed impossible.
2:25:16
I think that the main takeaway for me is that you know that 10 years because then you you have the hype and then you have the trough of disillusionment I believe is what it's called.
2:25:26
And I think for especially for hard tech or hardware companies that trough of disillusionment might be like 5 to eight years and so for us it was really important to walk rather than talk.
2:25:36
important to walk rather than talk. It's really easy to talk and maybe that's you know apppropo of what you were talking about on the launch video side John 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
2:25:52
hospitals it was such a very narrow clear thing that we needed to do um and we're also willing to do very unfancy things like operate in countries that are hard to get to and uh 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 hard problems. These are hard problems.
2:26:15
It's probably a bit similar to autonomous cars in that way, too.
2:26:16
You know, that there's a lot of hype and then and then the reality sets in of what it's going to take to make these systems work at scale.
2:26:22
Can you talk a little bit about the regulatory environment?
2:26:25
It seems like you probably couldn't have just gone straight to the American market because of the regulations.
2:26:31
Uh, but you found a way anyway, and I love that.
2:26:34
Uh, is is that actually a bullc 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 technolog 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?
2:27:00
Yeah, it's a good question.
2:27:00
When we were launching, we really had this sense.
2:27:05
There was such an unclear regulatory environment with regard to what we were proposing.
2:27:09
You know, we thought someone would build an automated logistics system for Earth.
2:27:12
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 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.
2:27:36
And so, uh, we needed a public health care system to do that.
2:27:38
health care system to do that. uh we didn't want to work with a whole bunch of you know helter skelter health systems which you kind of have in the US we thought it'd be good if we could have a public healthare system and so that immediately caused us to go to certain parts of the world um and then I think
2:27:51
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 I think the
2:28:04
difference was finding a government that behaves more like a startup a small agile government that is willing to make decisions um and exhibit more like yeah just executive decision-m so th those were really the things that made Rwanda such a powerful place for us to to to get started and it was about 6 years
2:28:24
later you know at that point we had about 50 million commercial autonomous miles and zero human safety incidents that's the moment when we thought hey this is a good time to bring this massive data set to the FAA and and kind of help them see like this technology is ready for prime time it's safe. Once we
2:28:37
Once we did that, it then took about 5 years from then until you know where we are today where, you know, Zipline's the only company um in US history that's been awarded full permission to fly beyond vigilant sight in all 50 states.
2:28:51
So, I think part of it was building that data set showing that it can be safe and then part of it was working directly with the regulator in the US um to to help make sure that the US doesn't fall too far behind in this core area of new technology. Yeah.
2:29:03
the uh immediate benefit, you know, as your network rolls out.
2:29:08
I love the idea of just being able to press a button and get, you know, an item uh you know, in in minutes.
2:29:11
Uh you know, it's obviously been a dream, I think, for so many people for so long.
2:29:20
Can you talk about some of the second order effects that you're anticipating? We we're here in LA.
2:29:23
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.
2:29:32
And so with Zipline, you know, when Zipline rolls out here, I can imagine that there would just immediately be less congestion.
2:29:36
Um, but that's just me um, you know, making a bold uh, you know, potential prediction, but I'm curious how you think about it.
2:29:46
And the cool thing is we're already seeing this.
2:29:47
I think people don't necessarily appreciate how massively instant delivery has scaled in the last 5 years.
2:29:54
I mean, it was obviously accelerated by co, but you know, we're going to do 5 12 billion instant deliveries in the US this year alone.
2:30:03
And we're using 3 to 4,000 lb 3 to 4,000lb gas combustion vehicle driven by a human to deliver something to your home that weighs 5 lb.
2:30:14
So, you don't have to be a physicist to realize like this is actually a bizarre solution.
2:30:20
you know, we're essentially we're using technology that's 100 years old to solve a problem that's like 5 years old and and to to serve a market that's growing super fast.
2:30:27
So, we think it's super obvious that, you know, if you want to deliver something fast that weighs 5 lbs, you probably want to do that with a vehicle that weighs 50 lbs and you want the vehicle to be electric and autonomous.
2:30:37
As soon as you realize that, then I think you know the future you you have this you you know a secret about the future most people don't know.
2:30:44
The other thing is like I personally if if I'm ordering delivery it's like do I really want this person to have to go to CVS and get Advil.
2:30:49
Like technically that it's like you know a form of employment.
2:30:54
They're they're opting into it but like it's like oh I'll just do it myself.
2:30:58
Like it's a bit of a hassle but when it when it's fully autonomous and it's literally like an extension you know of of the service that I'm using to get the item.
2:31:05
It's you'll use it a lot more.
2:31:05
And and actually just just on that front, I mean, you know, the customer behaviors we're seeing just in the last year in the US are quite mind-blowing.
2:31:15
I mean, first of all, you know, I may have thought, oh, maybe it'll be these like tech adopters and some of these um some of these, you know, I don't know, you know, nerdier.
2:31:25
No, no, it's like moms and grandmas who are like our power users.
2:31:29
And, you know, more important than that, I mean, you talk to you talk to them and we have we have users who have ordered 300 times in the last 12 months.
2:31:36
So, this is like a part of their daily. It's way different.
2:31:38
It's like, you know, I was I was talking to um a woman who said, you know, she's she's 78 years old.
2:31:46
She orders uh 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. Wow.
2:31:53
And you know, as I was, you know, as I was talking to her, she's like, "Yeah, you don't get it.
2:31:59
I mean, this saves me like 5 hours a week. It's totally priceless.
2:32:01
There's no way I go back to the old way of doing things when the weather is bad.
2:32:04
you know, I don't want to risk my health or I like fall down and get hurt.
2:32:07
You she has a lot of friends who might, you know, either single moms who 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.
2:32:15
I mean, I think people underestimate Yeah.
2:32:17
If you make it super fast and convenient, this is something people actually use every day, not every week or every month. Yeah.
2:32:23
Even just thinking parents, right?
2:32:25
I think every parent's had the experience.
2:32:27
It's bedtime and like you realize there's no diapers, whatever.
2:32:31
And so then it's like, well, are we going to like get the the kids and go to CVS or whatever to like get diapers and they don't have the brand.
2:32:38
So it's like I just think of I can just think of so many use cases where it's just like, oh yeah, we're all, you know, we're going to delay bedtime by 15 minutes on the Jordy as as someone who has a, you know, one-year-old and three-year-old at home, like these kinds of systems operate 247. Yeah.
2:32:54
Which is also pretty gamechanging relative to the way we currently think of logistics.
2:32:58
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. Yeah.
2:33:05
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 mother ship drone dropping a a smaller drone with something that looks like a zipline.
2:33:24
Um h how uh I guess when in the evolution of the company did you come up with the mother ship and uh baby ship I don't know what you call it uh like system the delivery zip is what we call it. What do you call it?
2:33:37
We we call it a delivery zip. Delivery zip. Okay.
2:33:41
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?
2:33:48
Yeah I mean I think it's a really good question.
2:33:51
So, first of all, you know, Zipline spent 10 years operating uh these kind of more long range systems at platform one.
2:33:57
You can actually see some of them sitting right here waiting to out and begin making deliveries and swing, right?
2:34:02
Um yeah, it's a plane and so this aircraft can fly, you know, 300 kilometers on a single battery charge.
2:34:09
So, it's all about range and serving like very rural hospitals and health facilities.
2:34:12
For platform 2, you know, it's becoming obvious to us that home delivery is, you know, it's by far like the holy grail.
2:34:18
I mean that's what automated logistics really has to solve globally.
2:34:21
And the most important thing is you want to be able to deliver quietly like silently.
2:34:27
You want to deliver silently.
2:34:30
It needs to be extremely safe.
2:34:31
You need to be able to deliver gently uh and with dinner plate level accuracy is kind of how we describe it.
2:34:37
That's actually super hard to do.
2:34:39
And you know you see a lot of other companies talking about you don't have to you don't have to you know stress that sounds very hard to do if you if well if you 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 octoopter of death.
2:34:53
I mean it looks like a lawn mower you know that like within 10 ft of your home. It's incredibly loud.
2:34:57
It's incredibly disruptive to your neighbors.
2:35:01
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.
2:35:09
And so you know the big advantage of of designing the system in this way is that the you know the uh uh the aircraft is staying 100 meters in the air.
2:35:19
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.
2:35:26
Only thing that's coming close to your home is the delivery zip, which you can see behind me.
2:35:30
This thing is, you know, inspired by Eve from Wall-E.
2:35:32
I was gonna I was gonna ask, was there a specific sci-fi that you and the team just love that you you kind of reference?
2:35:39
Uh, I think we're really into solar punk.
2:35:41
Have you guys heard of solar punk? Oh, yeah, of course. Yeah.
2:35:45
course. 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 what if the in the future robots are trying to save your life you know that's that's a different take and I think that completely came across in the video the
2:36:04
video was very saturated very orange very like sunny day and it was just so pastoral and lovely I I really like that as like a different vision of the future it was cool and to and to Jord's point you know I think that uh these kinds of systems people people are often like oh it's going to be so loud and it's you know the star the sky is going to be darkened with drones. It's like it's
2:36:23
It's like it's kind of funny.
2:36:25
It's the same way people actually originally felt about cars.
2:36:26
If you go and like read the you know if you read the newspaper articles from like 1910 people thought you know cars were going to be the scourge of cities.
2:36:33
Um but I think the reality is actually this is going to take a lot of delivery vehicles off of the roads.
2:36:39
This is going to reduce traffic in our neighborhoods.
2:36:42
This will reduce pollution in our neighborhoods. improve air quality.
2:36:46
It'll reduce noise because these systems are ultimately much quieter than cars.
2:36:50
Um 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 10 or 15 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.
2:37:06
You don't want you know between all the cars zipping. Yeah.
2:37:10
Could you talk about any thoughts, you know, ideas around larger payloads?
2:37:16
Like, you know, we've seen like airship uh airship startups emerge that are, you know, basically building like big blimps that could deliver, you know, something closer to kind of a competitor to the cargo ship almost.
2:37:27
Yeah, the cargo ship or some of these bigger, you know, but even like the flying car startups that are trying to f individuals around, I'm sure you're like loosely aware of the technology there. Yeah.
2:37:37
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?
2:37:48
I'm sure you guys have thought about it.
2:37:51
Any any immediate thoughts?
2:37:55
You know, the market that Zipline is focused on, instant delivery, is one of the biggest markets on Earth.
2:38:00
And it's just such a huge problem.
2:38:02
And keep in mind really today it's only available to rich people in the US.
2:38:07
You know, it's way too expensive.
2:38:09
Like even even just in the US it's not universally available.
2:38:12
Not to mention the 7 and a half billion people who don't live in the US globally.
2:38:16
So we actually think that as you automate, as you decrease the price, as you expand access and make it universal, I mean you we're going to continue to see you 10 or even 50x growth in instant delivery globally. So whereas 5.
2:38:29
5 billion deliveries might seem like a lot in the US, we actually think there's probably demand for 50 billion deliveries, instant deliveries in the US.
2:38:36
So I guess long story short, we've got our work cut out for us. Just spoke on logistics.
2:38:40
I think you know that we deliver uh this this system delivers an 8 lb payload.
2:38:45
It's designed to deliver an 8 lb payload. 8 lb is actually a lot.
2:38:49
You know, that's like a big grocery bag.
2:38:51
Um it's it's dinner for, you know, four to eight people depending on what you're ordering. Um and small dogs.
2:38:58
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 to carry humans for example.
2:39:17
I mean, I think humans is a farer problem and it'll be interesting to see, you know, where that plays out over the next 10 or 15 years.
2:39:27
Well, last question, then we'll let you go if you have time.
2:39:29
Um, I would love to know about obviously everyone's thinking about tariffs and whatnot, but how are you thinking about scaling up manufacturing?
2:39:35
It seems like you, you know, you have product market fit, you've solved the regulatory risk, the technical risk.
2:39:40
Uh, what's next in terms of scaling up manufacturing?
2:39:43
Are you building like a gigafactory for these things at some point?
2:39:46
And is that just like an entirely new challenge that you foresee on the future?
2:39:52
You know, Zipline has always manufactured everything in the US.
2:39:54
And so one of, you know, one of the advantages, you know, obviously there's this huge competition playing out between, you know, it's kind of great power competition between the US and China.
2:40:04
And I think that a lot of that competition is going to revolve around key areas of technology and everybody's talking about drones.
2:40:10
I think the current perception is that zip uh 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.
2:40:21
But the good news is there are you know there are a few companies that are completely focused on manufacturing in the US.
2:40:27
Uh there are US companies driving different classes of vehicles.
2:40:32
Um, you know, Anderl would be another good example, Nuros.
2:40:37
And 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 it 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, like zipline.
2:40:58
So, you know, I'm I'm actually downstairs at our headquarters.
2:41:00
This is now kind of like an engineering prototyping space about a third of a mile away.
2:41:04
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.
2:41:09
You guys should come visit if you want.
2:41:11
But I think you know that uh and by the way that's in South San Francisco.
2:41:15
So I think people are often surprised that you can like achieve that level of scale in California.
2:41:20
You're doing the re-industrialized meme. You're doing love it.
2:41:25
But it's it's just all about it's all about um engineering and manufacturing together.
2:41:28
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?
2:41:35
What does quality look like?
2:41:35
Um and to be able to rapidly change parts of the assembly process if necessary um to achieve reliability, safety and cost.
2:41:45
These things are so much easier to do if you do them all in the same place.
2:41:48
Sorry, I have so many more questions.
2:41:50
We'll let you go, but I have one more.
2:41:51
Um uh are are there any like huge developments in either like open source technologies?
2:41:56
uh you you know see all this development with AI uh that's getting better and better or even just like partners uh for a while there were companies that were thinking about drones as uh we'll build the the operating system for drones and we'll vend into a company like Zipline.
2:42:10
Uh 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 got to build everything from scratch? Yeah, it's interesting.
2:42:23
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.
2:42:31
You know we used an offthe-shelf um IMU off-the-shelf GPS system.
2:42:35
We used we we're using something called RTK differential GPS.
2:42:40
We uh were using even for the first few uh months we were using off-the-shelf autopilot.
2:42:46
Like all of these systems kind of failed.
2:42:48
And I would say it's actually very similar.
2:42:52
You know, when Tesla got started, they were like, "Oh, we're going to use an off-the-shelf Lotus Elise chassis and an off-the-shelf battery pack that we're buying.
2:42:57
We just combine them together.
2:42:58
We're gonna have a good product." Yep.
2:42:59
Turns out like they were wrong.
2:42:59
Like to actually build a great electric vehicle, they had to design the battery pack from scratch.
2:43:05
They had to design the entire car around the battery.
2:43:06
Zipline found itself in a very similar position where no one is building electric aircraft at commercial scale.
2:43:13
Zipline is the only company that is operating a full fleet of commercial aircraft at this scale.
2:43:18
And so it means we had to design the battery completely from scratch.
2:43:20
We had to design a flight computer completely from scratch.
2:43:23
We had to design the motor completely from scratch.
2:43:25
Um because you know ultimately what all of our customers care about is just teleportation.
2:43:31
They just want something to go from point A to point B fast enough to save a human life.
2:43:34
And that means we have to make it safe, reliable, cost effective.
2:43:39
And the way to ultimately do that has been to design every component around the use case really.
2:43:45
really. And so that that's well 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
2:43:59
can get their burrito or their cheeseburger you know reliably with the same reliability right yeah no it's it's fantastic well I we'd love to have you back on soon fantastic so fun to watch the strategy play out I'm just genuinely so excited to be a DAU, a zipline DAU. So, I think
2:44:15
So, I think you're going to be more than DAU. Three times a day.
2:44:21
Be doing a thousand deliveries a day.
2:44:23
As soon as you get average H AU. Yeah. Yeah. Hourly. Yeah.
2:44:29
As soon as you get AON on boarded, it's game over.
2:44:31
You're going to be profitable.
2:44:32
Don't No, I just don't think I don't think this is priced in yet to be honest.
2:44:35
I think I think it's going to be like imagine people, you know, shopping like, you know, the whole like drunk drunk shopping meme.
2:44:41
It's not just like instant delivery on uh you know you want food or groceries.
2:44:46
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 30 minutes later. That's going to change.
2:44:57
It's going to change everything. This is so awesome.
2:44:59
I'm I'm really excited for you.
2:45:01
So, congratulations on the overnight success.
2:45:02
Thank you for your service. Yeah.
2:45:05
Thanks for the 11 years of hard work. You make it look easy.
2:45:08
And uh but yeah, we really appreciate you coming on the show and sharing all that with us.
2:45:14
This is very fascinating. Thank you. And seriously, congrats. Thank you guys. Really appreciate it. We'll talk to you soon. Talk soon. Bye.
2:45:22
Oh, I would almost invest in that company at any price. Yeah.
2:45:25
Who who is in this company?
2:45:27
Because they've just been grinding for so long and it must be super capital intensive.
2:45:31
So there's probably pretty not not a lot of very well-known funds.
2:45:36
Seoia recent Google Ventures. Yeah. That happens sometimes.
2:45:45
Another 10 trillion to the to the Holy Trinity. What do you Now? Of course. Of course. Anyway, uh that's great.
2:45:51
Yeah, Sequoa got in the series A. Let's see it. You love to see it.
2:45:56
Uh anyway, let's move on.
2:45:59
Let's do some timeline and then get out of here.
2:46:00
We started late, so we're ending late.
2:46:02
Uh, you already heard from Quaid at bezel, but I just wanted to let you know that at getbbezzel.
2:46:06
com, your bezel concierge is available to source any watch on the planet.
2:46:11
This is this is an interesting fact that people might not know about bezel.
2:46:16
So, they have auctions, they have uh 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.
2:46:25
Uh, maybe I saw it in a movie, maybe I'm hearing rumblings about it at Watches and Wonders."
2:46:30
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.
2:46:36
Um anyway, let's move on to uh the OpenAI announcement.
2:46:40
Starting today, memory in chat GPT 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.
2:46:51
Seems like a nightmare because I've been lying to ChatGpt for about three years now about my expertise.
2:46:57
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. I work in trains.
2:47:04
I'm I actively own trains.
2:47:06
So, I because I want to I want to prompt engineered to give me like the best data.
2:47:10
And so now when I talk to it, it's going to be like as a train conductor, you probably want to go with this train. I was lying.
2:47:16
I wasn't actually a train conductor.
2:47:18
Explain this like I'm five for. Yeah.
2:47:20
It's like, oh, you're five. Oh, turns.
2:47:22
I didn't know you were five. John Gaga. John, the 5-year-old. The 5-year-old. Oh, yes. Like as a 5-year-old. Yeah.
2:47:29
So, uh, now I have to go back into Chad PT and tell it, "Forget that I'm five.
2:47:33
Forget that I'm a 5-year-old, uh, industrialist who owns trains."
2:47:38
And, uh, let me tell you about my real history and get you up to speed on the real memories that I want you to save.
2:47:44
But, obviously, this is a very cool product release. Makes a lot of sense.
2:47:47
uh 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.
2:47:55
This happens a lot because you have so many different chats going.
2:47:58
You want to reference another one and you have to go in the search bar, copy paste.
2:48:02
Obviously, that's a product feature.
2:48:04
And this is a testament to OpenAI uh expanding from nonprofit research foundation lab into product consumer.
2:48:11
No, and this is the thing people have been saying, oh, the models have no moes, etc.
2:48:15
This is this is one of the modes that will come up.
2:48:17
And I'm sure other foundation models will will build this and copy this, but what the name of the game is staying just a little bit ahead forever.
2:48:23
And that's what Google did.
2:48:25
And and no one ever pivoted to Bing because Google Google search is always just a little bit ahead, right?
2:48:30
Well, if you want to stay ahead, you should get an eightle. Yes, you should.
2:48:35
And uh let's take let's do a quick score check here.
2:48:38
I think I did pretty well.
2:48:39
Uh I was going to cover eight during the F1 breakdown, but we'll have to do that tomorrow because uh Charlotte is an eightle ambassador and we love F1. I got a 94.
2:48:49
Little low on the time slapped 96.
2:48:52
You You have an uncanny ability to beat me by like two points.
2:48:57
How much did you sleep though?
2:48:57
I slept 6 hours and 49 minutes. Brutal.
2:48:59
I slept I mean I slept 8 hours and 11 8 hours and 11 minutes.
2:49:04
You put up big numbers, man.
2:49:05
But I get in bed at like seven. Yeah, you do. You do.
2:49:08
I got to get to bed earlier. I got to get to bed.
2:49:11
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. Yeah.
2:49:18
And then you actually get your eight hours. Yep.
2:49:19
And you can go to eightleep. com/tvpn. Yeah.
2:49:22
Uh anyway, uh there was an interesting interaction between uh John Carmarmac uh quote tweeting someone named Devin uh about SpaceX.
2:49:29
Uh Devin says, "I'm going to call it right now.
2:49:32
A lot of stuff is going to break on this mission."
2:49:35
Talking about a new SpaceX mission. It's by design.
2:49:36
It's just part of the plan. Don't get upset.
2:49:38
I'm not saying SpaceX plans to fail.
2:49:40
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.
2:49:49
This is a good good lesson.
2:49:52
And that you see is why SpaceX doesn't do things the NASA way.
2:49:53
The NASA way was to goldplate everything, plan and test and plan and test and generate mountains of paper detailing every contingency with every scenario planned.
2:50:01
SpaceX just shrugs, says it's unmanned and sends it.
2:50:06
Half the time it blows up. That's the whole point.
2:50:08
They don't actually want it to blow up, of course, but they're anticipating that it might.
2:50:11
That possibility is part of the plan because one rocket blowing up or crashing is is an actual endto-end test.
2:50:16
This beats many, many man years of planning and plotting.
2:50:20
The key realization here is that knowledge only comes from empirical observation.
2:50:24
Everything else is just speculative.
2:50:26
The sooner you get into that feedback loop, the faster you run it.
2:50:30
The more iterations you can do in less time.
2:50:31
This means while others are planning and speculating, you actually learn something.
2:50:34
Relevant data is the most precious thing in the universe.
2:50:36
And it's worth blowing up any number of rockets to get it because rockets are just stuff.
2:50:42
They're just made of stuff.
2:50:44
And you can always get more stuff.
2:50:44
You can never get more time. It's a great insight.
2:50:47
It just means we're doing it cowboy style.
2:50:49
And uh I the post is good.
2:50:52
You should read the full thing.
2:50:52
But John Carmarmac endorses it and says uh I have never seen it expressed exactly like that, but I wholeheartedly endorse it. Feedback beats planning.
2:51:01
My plea at Meta was no grand plans, follow the gradient of user value.
2:51:06
And uh I I was uh chatting with John Kellmarmac years ago on on X about this uh talking about how just getting the VR cost curve down just every single headset just slightly lighter, slightly cheaper, slightly better.
2:51:22
Like that's what I wanted.
2:51:22
I was pitching like I I pulled up this video of the N64 and you turned on the N64 with put the Golden Eye cartridge in, turn on the N64.
2:51:33
This is like way before your time.
2:51:34
Um, but uh you turn it on and it would just blink on and you'd be ready to play. And it was it was crazy.
2:51:40
There was no login screen, no off, no no intro, no credits.
2:51:42
It was just turn it on and you're just playing. It was amazing.
2:51:46
And and I was like, they need to get there for uh for VR.
2:51:48
He, you know, agreed and gave some other feedback that was really interesting, but uh interesting uh speed of execution stuff.
2:51:56
Anyway, um speaking of VR, if you're trying to sell VR headsets all over the world, maybe you're uh big screen VR, you got to get on numeral sales tax on autopilot.
2:52:03
spend less than five minutes per month on sales tax compliance. It's that easy.
2:52:07
Yeah, thousands of companies rely on Numeral.
2:52:12
Um you can go to Numeral HQ to uh get onboarded.
2:52:15
Uh they'll do a white glove onboarding.
2:52:18
Oh yeah, they are just absolutely fantastic over there.
2:52:19
25 states are now taxing software sales. John, I didn't know. Did you know that? No. Yeah, actually you did.
2:52:25
They did because you said it yesterday.
2:52:29
Well, Vtorio says, "Thank you to numeral for supporting the show."
2:52:31
Vtorio says, "It's so over. They automated Italians.
2:52:34
I saw you put this in there. I like this.
2:52:36
You put it in the show notes. I like it.
2:52:39
You see the uh the hand movement, which is crazy. It's the Italian.
2:52:42
I think Victoria, he's Italian. Yeah, he's having fun.
2:52:47
But uh very interesting art installation. Good viral video. Lots of fun.
2:52:51
Um I I I like this one from Framer.
2:52:54
Thanks to AI, every meme can be turned into a cartoon easily.
2:52:56
And it's Yeah, it's so funny because you remember I we joked about this early on.
2:53:00
It was, yeah, we there needs to be like, you know, South Park meets Silicon Valley where something happens on the timeline, it just immediately gets turned into a cartoon. Yep.
2:53:10
And we kind of looked at that and we were like, h it's like funny to do. Seems really expensive. Super expensive. It wouldn't make sense.
2:53:19
It's just like it at the end of the day, it might just be a viral video.
2:53:20
It's not really We have a friend who's already using voice AI to make these like incredible deep fakes. Incredible deep fakes.
2:53:28
And they're very funny because they're not funny because of the AI.
2:53:32
They're funny because he puts so much thought into the punch line and how it leads into the punch line and he's so creative with it and it's really his life.
2:53:39
Completely copies the like the the I can't believe it is. It's really really good.
2:53:45
And so this framer thread is interesting because uh not only do they share this video of the Paris Olympics, that crazy breakdancing video, but uh Framer actually breaks down exactly how to do it, so you can kind of follow along with all the different uh prompts.
2:54:00
You go into chat, turn the images into into uh cartoons, and then obviously change those into videos.
2:54:05
But uh it was remarkable.
2:54:08
it it's a very watchable video and I think this will be part of like the meme stack going forward when an iconic event happens.
2:54:14
Uh it will be instantly turned into a cartoon.
2:54:18
You'll be able to enjoy it as anime if you want.
2:54:20
Uh but the real creativity will come from uh that human insight of what would be particularly funny to do in a uh in a cartoon setting. Um it' be very funny.
2:54:29
Uh anyway, let's tell you about public investing for those who take it seriously.
2:54:35
Multiasset investing, industryleading yields, trusted by millions. Go to public. com to get started. And thank you to public.
2:54:39
They are the ones that power our ticker down at the bottom.
2:54:42
Uh stock market immediately.
2:54:45
It's all driven by what the hosts of the All-In podcast are tweeting apparently.
2:54:50
Uh every time they tweet phone away from him, but it's going up, it's going down.
2:54:56
Today is not as bad as other days.
2:54:59
We had a pretty pretty big dip in the middle of the day, but we're doing okay now. Yeah.
2:55:03
I mean, we almost hit the circuit breakers today, but we didn't.
2:55:07
So, I guess that's a win.
2:55:10
Any day where there's not circuit breakers is a is a Dom Perry day in my opinion. It's great.
2:55:14
Uh, should we talk about the OpenAI lawsuit?
2:55:17
This is, uh, kind of interesting. This is developing.
2:55:21
Um, so Elon has has sued OpenAI, I believe.
2:55:24
Uh, and there's been kind of back and forth about Elon being a co-founder of OpenAI, uh, putting a lot of money into the nonprofit via donations and then not getting equity in the forprofit when that conversion happened and the investment started uh, rolling in.
2:55:39
Now, uh, OpenAI is suing, uh, Elon or counter suing.
2:55:43
And OpenAI newsroom writes, uh, Elon's non-stop actions against us are just bad faith tactics to slow down Open AI and seize control of the leading AI innovations for his personal benefit.
2:55:54
Today, we counter sued to stop him.
2:55:56
Uh, he's been spreading false information about us.
2:56:00
We're actually getting ready to build the best equipped nonprofit the world has ever seen.
2:56:03
We're not converting it away.
2:56:06
And so, that that's an interesting take.
2:56:07
basically saying like the nonprofit is not going away. That actually isn't new.
2:56:10
Sam did address that in that it's new positioning, but it's new positioning. It's getting out there. Yeah.
2:56:16
And so they've never they've never been really leading with, oh, we're actually making the best nonprofit ever since. Well, yeah.
2:56:23
Because the VCs are like, look, we don't care about the nonprofit that it's going to continue.
2:56:28
We only care about the for-profit.
2:56:28
But uh obviously if you're a nonprofit and you have some insane equity position in this like banger consumer tech company uh that's going to be very good to for funding your nonprofit.
2:56:39
And so what will the nonprofit do?
2:56:41
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.
2:56:46
And so uh they they want to they want to make it loud and clear that uh the the philanthropic efforts at the OpenAI nonprofit are not uh going away anytime soon.
2:56:58
and uh and you can expect to for them to keep fighting.
2:57:01
So uh you know hopefully that all just resolves.
2:57:03
My take has continually been mom and dad are fighting.
2:57:06
Let's try and get them to sort it out and uh build a glorious future together with uh amazing chatbt and Grock functionality for all of us to enjoy.
2:57:17
Yeah, I feel like if Grock and Chat GBT actually sat down just the two chat bots, they could resolve it with enough back and forth.
2:57:25
Well, chatbot arena to sort it out. Yeah. Yeah.
2:57:27
Two bots enter, only one can leave.
2:57:30
No, no, they should be able to work it out.
2:57:32
They should be able to like, you know, do enough iterations on the situation to like, you know, run a million simulations.
2:57:40
And 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 runaway AI.
2:57:59
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 but they actually advocate for the third which is kind of a truce and uh and a deal gets broken gets brokered and uh the government winds up working very closely
2:58:20
with the leading lab but the lab is not entirely nationalized and uh 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 truses that actually might be a great outcome instead of instead of this, you know, dystopia where everyone's fighting, everyone's suing each other constantly. It's like,
2:58:40
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. That's right. Who knows?
2:58:52
Anyway, scale AI founder Alex Wang proposes a national AI data reserve to bolster US data.
2:58:56
I don't know what this means, but it sounds awesome, John. Let's push it forward.
2:59:01
Aiming to secure a competitive edge over China in the AI race. Uh, very interesting.
2:59:05
Uh, we used to have gold reserves.
2:59:08
Now we've got data reserves. Big data reserves.
2:59:11
Yeah, I wonder what that would look like.
2:59:13
I mean, certainly like sequestering some of the data and protecting it seems extremely valuable since Deep Seek seemed like it was completely reverse engineered from CHP.
2:59:21
Esoteric PDFs with forbidden knowledge.
2:59:24
Yes, I think Nat Friedman should be the one on the case.
2:59:28
a national AI data reserve should be should be the scrolls cannot be ingested into the next LLM training run.
2:59:33
They must they must live in Natan's house forever.
2:59:38
Anyway, uh there's some other news, but first let's talk about wander. Find your happy place. Find your happy place.
2:59:47
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It's a vacation home but better, folks. It is just delightful.
2:59:58
Yeah, Brad Gersonner, who uh recently led the round that we discussed on the show today, uh says, "Google is holding the line on capex.
3:00:05
As I said tonight on CNBC, tech CEOs are ready to run.
3:00:07
That's why today's tariff clarity was critical to maintaining our leadership in global AI.
3:00:13
Smart targeted tariffs plus a trade deal with China, plus a tax deal will extend US national advantages."
3:00:21
And uh so this is on the back this is on the back of uh Google CEO uh Synindra Pachchai reiterating their $75 billion capex guide for 2025 despite the tariff uncertainty.
3:00:31
Uh 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 is like it's so over Microsoft c canceled a1 billion dollar data center.
3:00:44
this is so terrible and it's like well they're still spending 74 billion then you know it's like on capex like the capacity is going to increase maybe they're slowing down a little bit but uh it still seems like and then also like there's just the dynamic between all the none of them want to get caught you know
3:01:03
flatfooted here and so and there's also the amazing story about Zuck being yeah we reels we got caught back we caught we got caught flatfooted on reels we didn't have enough uh AI AI data centers to train uh reals recommendation algorithms at scale for a billion Instagram users. Uh so we built out a re a reals training
3:01:19
Uh so we built out a re a reals 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 and uh and add LLM functionality all over the place.
3:01:32
And so I think every uh Mag7 CEO has to be taking that seriously and thinking about well yeah maybe we don't want to get over our skis on capex but we got to be in the game and that means double digit high double digit billions of capex every single year.
3:01:44
We're scaling our capex here at the show as well. We are scaling up.
3:01:49
Um well let's close with is there anything else you want to do or you good?
3:01:54
Let's save this this next piece for tomorrow.
3:01:56
important and I think we should give it some real I agree attention.
3:02:00
Anyway, fantastic show, some really great interviews.
3:02:03
I had a great time today.
3:02:05
Uh and just thank you for listening and thanks for dealing with the uh cyber attack that happened on the show earlier at 11:00.
3:02:10
We had to start late as we fought off just an absolute nightmare for Ben and the whole team.
3:02:18
They were stressed, but they got through it and they're feeling good.
3:02:19
And I'm sure tomorrow will be a banger episode.
3:02:24
So, tune in right at 11 on the dot.
3:02:26
We're going live narrative first.
3:02:29
We've been pretty good about going at 11.
3:02:31
Yeah, we used to be all over the place.
3:02:32
So, uh, the general trend line is is is more accuracy, more professionalism on this show. And so, thank you.
3:02:38
If you've enjoyed the show, leave us five stars on Apple Podcast, Spotify. Fun fact about Spotify.
3:02:41
You can't just go leave us five stars there.
3:02:46
You got to click listen to the episode on Spotify. Let it play for a while.
3:02:47
You can put in the background low and then it will let you leave five stars.
3:02:53
Spotify knows don't spam us, but we're gonna get through that.
3:02:56
We're going to get through that first.
3:02:57
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3:03:02
Uh we are entirely corporation supported and we will never forget that. Thank you. Thank you. Have a great day deck.