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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVP. Brother. Today is Friday, 05/16/2025. We are live from
Speaker 2:The Temple Of Technology. The Fortress Of Finance. The capital of capital.
Speaker 1:This thing goes in the mouth is really bad.
Speaker 2:Yeah. The amount of microplastics going into our mouth right now is
Speaker 1:Anyway, we got a great show. We got Matt Grimm coming on to the show. Andrew will just did the Murph challenge. He's gonna break it down for us. We got Kevin Weil from OpenAI, Blake Scholl from Boom Supersonic, Tim Fist from IFP, Chris Best from Substack, and Sean Henry from Stord, some legendary founders, some legendary folks, some yappers, some commentators.
Speaker 1:We got a great show. Gonna some good news. But first, let's bring in Matt Grimm if he's in the studio. If not, we can show you some photos. Oh, here he is.
Speaker 1:How are doing?
Speaker 2:Hey, guys. How are you?
Speaker 1:Fantastic. Looking great. Can you break it down for us? What's going on today? How did it go?
Speaker 3:It went, it was a great day. I'm here with, Chris Wiley. Chris Wiley is the executive director of the lieutenant Michael P. Murphy Navy SEAL Museum. So I wanted to give it a second to Chris to talk about, what the MERS challenge is, why we do it, kind of the story behind it, and a little bit of lieutenant Murphy's history.
Speaker 3:So
Speaker 1:Sounds fantastic.
Speaker 4:Thank you for having me on. So what we just accomplished today was a one mile run, a hundred pull ups, 200 push ups, 300 air squats, and another one mile run, all wearing a nice weighted vest, as you can see.
Speaker 5:There we go. Yep. But
Speaker 4:the whole history behind this was that it was Michael's favorite workout when he was deployed. We don't deploy with gym equipment, so you have to kind of improvise and find what you can can use in your area so you can have a good workout. If everybody doesn't know the story of lieutenant Murphy, the blockbuster movie, The Lone Survivor with my Wahlberg and Taylor Kitsch. That was the portrayal of Operation Red Wings and how Michael stepped out into a hail of bullets to make a phone call to try to save everybody. So ultimately, receiving the Medal of Honor after he died that day.
Speaker 4:And just a great workout and a great way to remember all that have sacrificed, I'm sorry, and suffered Yeah. Our own little discomfort today during the the Murph challenge.
Speaker 1:It's awesome. How long has this been going on? Andrew has been a part of this for a couple of years, but can you break down some of the history of this particular event?
Speaker 4:So what happened was after, the helicopter pilot recovered Michael and the other guys on that mountainside, when he got back home, he, heard of Michael's workout and then started doing it on his own, calling it the Murph, and it spread so quickly through the local CrossFit gyms. And then it became, too much for him to handle, and then he involved the family. So this has been going on as the Murph challenge for about twelve to thirteen years now, and it's just growing every single year. We're hoping to, continue having this grow and have the partnership with Andrew because they're amazing amazing partners and, and people here. It's it's been such a touching event today.
Speaker 2:That's amazing.
Speaker 1:Can you talk about Andrew role here? Is this just a bonding event for you guys? Is this for charity? How are you thinking about Androle's involvement in your how many people from Androle came out for this?
Speaker 3:Well, today, had about a 50 Andorilians come out, and it's, for us, it's not just about the team bonding part. That is certainly a part of it, you know, kind of team morale, team bonding, and the team that works together, sweats together, stays together. So is that certainly a part of it? But more importantly than that, like, started Andoril to bring the best possible technology to those who serve in defense of our freedoms and our nation and our allies. And and a part of that extends to supporting the veterans community.
Speaker 3:So we've been pretty active in supporting the veterans community through a couple different ways that I can talk about in a couple minutes. So today was less for us about the morale piece and more about a sort of sort of a signal or a moment to celebrate our veterans, both the work at Andrew and in the community at large, and, our partnership with the Murph Foundation and with Chris himself and and all of that is just a a symbol of that.
Speaker 1:How'd you wind up doing that? Yeah. I mean, I were I tried to do it with you over Christmas break, and I got crushed. Well,
Speaker 2:you guys don't even look like you broke a sweat. What's going on, miss? I I appreciate another one now?
Speaker 3:We we had a we there were a 50 of us out there, and I I noticed there were there were two empty vests out there
Speaker 2:with technology. There we go.
Speaker 3:On the front. Brutal. Guys wanna wanna step up next year, we'd be happy to have you, and you
Speaker 1:can come out in too.
Speaker 3:Out with us.
Speaker 2:We'll do it live.
Speaker 1:Yeah. I did, like, three pull ups today, so I'm getting there.
Speaker 2:You're yourself, miss. You were repping I
Speaker 6:think I
Speaker 1:did a couple sets of five, but not quite at the hundred in a row. Yeah. Exactly. Talk to me about
Speaker 3:Thanks, Chris, for for your time, and thanks for the partnership and your service and everything you do for veterans.
Speaker 5:Thank you so much. Thank you
Speaker 1:so much. Yeah. Thank you. Yeah. We're good.
Speaker 1:Alright. Cheers. Awesome. Matt, talk to me about the role that veterans play at Anderol. People think tech company, military, obviously, there's discipline overlaps, but a lot of times, there's not so many immediate skill overlaps, or do people have that wrong?
Speaker 1:Are you hiring software engineers from the military? Are you hiring hardware engineers? Are you hiring operators and finance people? What are the different types of roles, that veterans are filling at Andoril today?
Speaker 3:Yeah. Happy to talk about, talk about all of that. So we've been, involved in the veterans community since day one of the organization. One of our, one of our cofounders, in fact, is a veteran himself
Speaker 1:Yeah.
Speaker 5:And has helped
Speaker 3:kind of, lay the foundations for those partnerships. Right now, about 13% of our employee base is veterans, which is wildly over the national average, and it's certainly higher than that in in the Silicon Valley kind of technology community. We have a we have a partnership with a great organization called SkillBridge that's a program run by the DOD for helping veterans transition. We have a couple of recruiting relationships with targeted to that kind of transitioning veteran kind of community. And we hire across all roles.
Speaker 3:Everything from Mhmm. Kind of field op tech field ops technicians who are installing our products and training users in the field. Some of our maintenance and repair technicians, some of our production technicians on the factory floor, building products, all the way through some design engineers, Meckies, and EEs doing work. Yes. We have some coders, some CS folks who are, from the from the veterans community and all the way up into the leadership ranks, you know, of our of our leadership ranks.
Speaker 3:We've got, a a pretty high vet veteran representation, everything from flag officers to retired colonels through, through the whole ranks. So it's a big part of our part of our culture. It's a big part of our, kind of the mission of the company, and something that we're proud to support. And beyond that, I would say that, we frequently raise some money for veterans charities. We've got a couple in particular that we support.
Speaker 3:I've got my my my notes here in front of me with that. So on Veterans Day last year, we had our first big, public launch of the swag store, and we had a swag drop that, raised about 60,000 some odd dollars, that went to a Blue Star Families Foundation. A good teaser for you, breaking news here on the Technology Brothers Podcast Network. We're launching our next swag drop on Memorial Day in about ten days.
Speaker 1:Let's go.
Speaker 3:We'll be raising a a whole bunch more money exactly for the foundation that that that Chris runs in, in Lieutenant Murphy's honor. So, everybody be be be on the lookout for that. We've given some money to a great charity called Warriors of Field that is, actually run by one of the annual executives that specializes in, helping veterans kind of in in distress, kinda going through some bad times by doing some mentorship and some outdoor activities and wilderness adventures and hunting and that sort of thing. So trying to build some bonds there to help veterans who are in a tough spot. So, we've been we've been very active through all the years on all this and something that we're looking forward to continuing doing and scaling as the company grows.
Speaker 1:Okay. Give us a take about how to get a job at Andoril.
Speaker 3:Well, we've got a a great website, you know, andoril.com/careers, but more importantly than than the obvious, just apply on the website line, is, like, we look for people with a real mission drive. We look for people who are really driven by the call to service, who are really, interested in protecting, American values and our allies' values, and, and and and the escalating arms race that happening across the world, whether that's artificial intelligence, whether that's drone technology, whether that's any sort of the the kind of the next generation of what the war warfighters story we're gonna face face in the battlefield. Like, we look for people who are just really motivated and really driven and look, you know, wanna come honestly grind and work hard on really challenging and rewarding problems to to help defend our country. So, the the number one thing you could do if you're interested in a job at Androle, obviously apply, but more importantly is, you know, build up that skill set, build up that engineering skill set, that problem solving skill set, and, and that mission drive, and, that's who we look for.
Speaker 1:That's fantastic. Jordan, you got anything else? No. This is great.
Speaker 2:We've to come out for the next one.
Speaker 1:We've to start working. I mean, think it's doable. I don't I think I would have died this year, but I think I could do it next year if I start training today.
Speaker 2:John will John will finish the
Speaker 5:whole week.
Speaker 7:I I the
Speaker 3:winners today finished, in our in our women's division. She finished in about forty five minutes. Our, in our men's division, he finished in thirty five minutes doing 30. A mile run, a hundred pull ups, 200 push ups, 300 squats, and another mile run-in 35, which is, totally ridiculous and and very impressive. And then me, myself, I finished in about, about an hour and eleven, hour and twelve minutes.
Speaker 3:Minutes.
Speaker 1:Not bad. You had
Speaker 2:three vests on?
Speaker 3:But but finished it with the full vest, full wraps,
Speaker 1:all that.
Speaker 3:Pretty pretty pretty happy day.
Speaker 2:That's amazing. Dog. Absolute dog.
Speaker 1:Well, congratulations. Thanks for stopping by. Yep. Love to have you back and talk more.
Speaker 3:And we'll see enjoy the
Speaker 1:rest the day.
Speaker 5:For sure.
Speaker 2:Thanks for putting this on. Alright. Bye.
Speaker 1:I think it's time we take off the mustaches and get down to business. Oh.
Speaker 2:Yeah. A little I I I thought it might be fun to do a little bit of the news in a mustache.
Speaker 8:You guys will you can stay
Speaker 1:in a mustache.
Speaker 2:I'm gonna I'm personally going to keep mine on a little
Speaker 1:bit, John. Well, first up, we got Sam Altman with a big announcement. OpenAI is introducing Codex. It's a software engineering agent that runs in the cloud and does tasks for you like writing a new feature or fixing a bug. You can run many tasks in parallel.
Speaker 1:Starting to roll out to check GPT Pro, Enterprise, and Teams users, and he sent some more info. I think this is interesting because I had this crazy experience with o three the other day where I wanted to know how, how high a desk was actually on the Pat McAfee studio. So I was looking at so I took a screenshot of Pat McAfee standing, and I and I said, okay. Look up how tall Pat McAfee is and tell me how tall is his desk because he seems to have a good thing going where he Yeah.
Speaker 2:Yeah. When you were doing that?
Speaker 1:When? When? Well, when I was thinking? Yeah. Yeah.
Speaker 1:Yeah. Yeah. Yeah. It was struck me when I
Speaker 2:was asked read But
Speaker 1:but this is what's what was crazy is that I thought I thought it would just like look at the image and just kind of guess. It wound up writing like hundreds of lines of code interpreting the pixels in the image and looking at different elements of the image to decide, okay. Well, there's a he has a Coca Cola there. This is how tall a Coca Cola is. Let me expand this.
Speaker 1:All this just to find that it's just a normal sized desk. Just the standard desk which is like like 36 inches.
Speaker 2:Can you imagine giving that task to a human to say like Yeah. Can you can you kind of figure out how high this desk is? Yeah. And they go and they write hundreds of lines of code and you're like It's really easy. Like like, Yeah.
Speaker 2:I guess, like, good job for going above and beyond. Yep. But, like, a simple estimate would have been fine.
Speaker 1:Yeah. And I also and I also had an interesting experience where, today, I kicked off a deep research report asking for some, you know, top news and then put together some some news of the day, like, should I be thinking about? And the deep research report asked me, hey. Do you want me to run this once, or do you want me to run this just, like, every day or every week? I'd be happy to do that for you.
Speaker 1:And I was like, oh, wow. It just it just volunteered to do it on a cron job, which normally you would have to write about. Anyway, any other takeaways from the OpenAI launch? We're talking to Kevin Weil, in a little bit, but Jordan No.
Speaker 2:I I I don't think this should be a huge surprise to anyone. Yep. We, you know, we talked with Sarah Kuo With Sarah Kuo. Yeah. Probably a few weeks ago at this point, she just said, look, to understand where the labs are going, understand what they value, what they find important.
Speaker 2:Code gen has always been one of those things. And so this launch should not be a surprise to anyone. But I'm excited to get in deeper with Kevin
Speaker 1:Yeah. A little bit. I I mean, so many questions for him. But I like this idea of the front door to AI. As the foundation models commoditize, it becomes more about the being the front door to the Internet.
Speaker 1:Are you just laughing at your own mustache? Are you laughing at your own mustache? Laughing at your own jokes. Normally, you think I'd be laughing at you. Every once in while, look over at
Speaker 2:the call while
Speaker 1:we're talking and I just crack up. Or yeah. There there there's other stuff that I'm just
Speaker 2:Well, I didn't really get it. We went right into this, like, formal interview, which
Speaker 1:Yeah.
Speaker 2:Yeah. Normally, we we would have had a a bit longer to laugh at ourselves. So Whatever. Anyways, sorry interrupt.
Speaker 8:I think you look great.
Speaker 1:In fact, I'm not laughing because it's so convincing. It looks natural. It's growing. I mean, it's just normal. Anyway, the the front door to AI, like, they are building a new Google where it's this front front door to knowledge engine stuff, but they need the front door to code gen as well.
Speaker 1:And so this new paradigm of, you know
Speaker 2:Yeah. And the interesting thing is pretty valuable. I highly doubt Kevin can comment on this today. But the immediate question I have is how does this integrate with a potential Windsurf application? Yep.
Speaker 2:This makes me think that Windsurf might end up continuing to be a standalone Yep. App. Yep. And so Yeah. Yeah.
Speaker 1:I mean, it's really blurring the lines. Like, didn't know that I wanted I didn't know that I needed code to decide how tall a desk is. It decided that for me. And I really like that as a product evolution where eventually you go to a you go you open the OpenAI app Yeah. And you ask for something, and it decides, do you do we need to do code for this?
Speaker 1:Do we need to do an image model? Do we need to use four o? Do we need to use three zero three? We need to use deep research? Like, it should decide for me.
Speaker 1:That's a really cool
Speaker 2:And this is why I've always said I don't think OpenAI cares about naming
Speaker 1:Yep. Because they're always in the long It's gonna get tough on Verizon.
Speaker 2:Right. They're just gonna do all the routing Yeah. Based on understanding
Speaker 1:Yeah.
Speaker 2:You know, what is required.
Speaker 1:So Anyway, on the flip side of AI, we have another post from DD DOS. Meta will delay its biggest AI model launch long before Behemoth. Four reasons highlighted, doesn't perform well internally, huge reorg in AI leadership. 11 out of 14 researchers on Llama have left, and we saw that funny post where someone was saying, like, I was on the Llama team. I worked on Llama one, two, three, but not four.
Speaker 1:And they put that on their resume on on LinkedIn. Brutal. All this after admitting that they gained some of the benchmarks. Glad glad Meta can afford to light billions of dollars on fire for open source. And so this is an interesting, like, discussion for me because I think that I don't think open source will win.
Speaker 1:I think you need to build a product around it. I but at the same time, when we talk to people like Aaron Ginn, I think we it would be amazing if America had a rock solid open source offering that was hard coded, you know, or baked into the weights with American values. And that was an option for countries that are maybe deciding between America and China.
Speaker 2:I want my hard to understand what llama's real enterprise adoption looks like. Yeah. Right?
Speaker 1:Yep. You don't
Speaker 2:hear a lot about companies, at least to date.
Speaker 1:There was a big boom for a long time. I think, think the answer lies in that open router data.
Speaker 2:Yeah.
Speaker 1:And there are a lot of open source models running there. Kind of unclear. The Wall Street Journal has more deep dive here. Meta is contemplating significant management changes to its AI product group as a result. Its performance has been hobbled by training challenges.
Speaker 1:And so there is a take here that's like they believed almost too much in scaling laws. Right? Because Behemoth is this massive model. I think it's the biggest context window, even bigger context window than what Google's offering. It's a huge parameter model.
Speaker 1:What is it? Two billions of active 288,000,000,000 active parameters. 2,000,000,000,000 total parameters. We used to be in, like, Falcon nine b was, like, exciting. 9,000,000,000 parameters.
Speaker 1:We're now up in 288,000,000,000 active parameters, 2,000,000,000,000 parameters. The circle has gotten so big from the g p t three circle to the g p t four circle. We are now with a massive circle that's, that's covering everything, but we're not getting better results just from pure scaling because you have to add that RL layer on top, that post training, and that's what OpenAI has been really, really good at with the O models, and that's what DeepSeek got right as well Yeah. With their r one model, the reasoning on top. And it seems like they
Speaker 2:Yeah. And I mean, the main thing here is despite having effectively infinity resources, they're struggling on the team side.
Speaker 1:Yeah. Seems like they actually did There isn't cohesion.
Speaker 2:There there's a lot of churn. Yep. There's former employees that that clearly were talented that are like going out and saying like you said, you know, I'm not, I wasn't involved in this thing.
Speaker 5:Yep. Yep.
Speaker 2:Feeling the need to sort of publicly state that they didn't play a role in that. Yep. And so it doesn't matter how much money they have to spend Yep. And what their CapEx looks like if there's not real cohesion.
Speaker 1:Yeah. I've been thinking about this because the whole meme with pre training was scale is all you need. Just keep scaling the number of tokens and energy and parameters and anything that go data that goes into the model, right? Just 10 x everything, 10 x that, and then 10 x it again, and then 10 x it again.
Speaker 2:You're only a few 10 x's away
Speaker 1:few 10 x from AGI. And you're gross. And that was that was very clearly not the case. It the the the scale scale was not all you needed in a singular context. The the exponential chart was secretly a sigmoid curve.
Speaker 1:Right? It would it would go exponential, and then it would flatten out and see diminishing market returns. And I think that that's true in life. I think that's true in in so much technology development. You need to be on the sigmoid grind set.
Speaker 1:Yes. You need to be understanding that you're gonna go through bursts of explosive exponential growth, but those exponential growth periods will stop. I mean, we've seen this with the show. Like, when we first started quote tweeting, just printing out posts and quote tweeting, we saw exponential growth in the follower count of the show and listenership. And then eventually we played that out and then we got to a plateau and then we said, let's do guests.
Speaker 1:And then we saw another one. And now we're gonna come up with the third act, the fourth act, the fifth act, and you have to be constantly reinventing yourself, finding new paradigms. And if you're in artificial intelligence, you can't just say, I'm going to rely on the pre training scaling law holding forever. You need to go into, okay, how do we scale up reinforcement learning? How do we scale up tool use?
Speaker 1:How do we scale up product use and product functionality to make this a really, really great product? You're not gonna get there purely on one single curve. The arc of technology throughout history has always been a series of s curves. There's been the semiconductor boom, the Internet boom, the mobile boom, the AI boom. And if you wanna make money or participate or understand the the the role of technology as it's evolved over the past sixty years or hundred years, you can't just see it as one linear exponential, like one exponential graph.
Speaker 1:It looks smooth when you zoom out. When you zoom in, it's actually a bunch of s curves.
Speaker 5:Yep.
Speaker 1:There's a boom where everyone's like, mobile is going to the moon. If the trend continues, there will be 10,000,000,000,000 mobile devices. And then what what happens? Oh, it's like a couple billion because there's only a couple billion people.
Speaker 2:Right? That's right.
Speaker 1:And that's just the that's just the way it goes. Anyway, staying in mobile, let's go over to Tim Sweeney. He says Apple's app review team Wait. Should
Speaker 2:have to Sorry. We have to flag
Speaker 1:this Oh, you wanna flag this? Okay.
Speaker 2:Which is just wild. So z says, did they seriously name it Behemoth, the quintessential creature only God contained from the book of Job, and then give it the demon branding. And I gotta say that the the branding here
Speaker 1:Is this a real photo that they used? It is. This is in the journal too. Yeah.
Speaker 2:It is. What a crazy photo of It is a crazy asset. I mean, you gotta respect the development of the delts of the demon.
Speaker 1:I mean
Speaker 2:But it's still We were
Speaker 1:talking about that with with Orion. Right? Like like like the like the story of Orion. Right?
Speaker 2:It's actually the most crazy brand asset that you could choose for something like this. It's like how do we how do we make this as scary as possible for the average Meta Platforms user?
Speaker 1:Yeah. So so so Facebook's Meta's latest virtual reality, augmented reality headset, the glasses that everyone's raving about, is called Orion. And the Greek myth of Orion tells the story of a mighty hunter, sometimes portrayed as a giant, who is eventually killed and placed in the sky as a constellation. It's like the worst possible metaphor you would want for a giant tech company trying to do something new and ambitious. Right?
Speaker 1:It's a very, very weird pick. But he thinks about the Roman empire all the time, so maybe he's interpreting that myth differently and there's a different reading. But I would love to know how they wound up with that, but different versions of the myth, detail his life and death, including how he was blinded, restored, but hit by his sight his sight by the sun, and possibly killed by either Scorpion or Artemis, the goddess of the hunt due to jealousy or a trick up by Apollo. And so, if you read the map, the metaphor of Orion, it's like, it's not good for a matter
Speaker 2:of Behemoth and Wikipedia is a beast from the biblical book of Job and is a form of the chaos monster created by God at the beginning of creation.
Speaker 1:Such a very weird choice. You should actually, you should just call it six seven b two. That's fine. We like those names. Let's just stick with those names.
Speaker 1:Four o is a great name. Three is a great name.
Speaker 2:Orion and Behemoth sound cool.
Speaker 1:Yeah. They sound cool until you peel back Yeah. The attention the metaphor is like bizarre. And so, yeah, Behemoth has not only been a very large model, but it has very been a very large problem for and it has been hard to tame and hard to get to produce, fantastic results over there. But good luck to the team over there.
Speaker 1:Hopefully, there's some new blood, some new folks come in, and they produce a great fantastic product for the meta team. We're rooting for you. Anyway, let's go over to Tim Sweeney. Apple's app review team should be free to review all submitted apps promptly and accept or reject accordingly to according to the plain language of their guidelines. App review shouldn't be weaponized by senior management as a tool to delay or obstruct competition, due process, or free speech.
Speaker 1:And so
Speaker 2:Naval said Apple continues to mock the court.
Speaker 1:So this is, of course, Apple should need to approve Fortnite because Fortnite has a third party checkout where you can go and buy Fortnite V Bucks, without paying the 30% App Store fee. Of course, you have to go off the app, and there's a pop up warning that comes up, and Apple's being very aggressive about that. But Apple is pushing the limits. They are they're going one mile an hour under the speed limit. They're they're it's certainly not the it's certainly not the spirit of the law, but they are following the letter of the law, or at least they would argue that.
Speaker 1:And who knows, maybe there'll be another court, another another battle in court. But anyway.
Speaker 2:No, this feels like they're setting themselves up for another potentially separate lawsuit around the approval process.
Speaker 1:Yeah. The approval process. Because
Speaker 2:because Epic can can actually say, this is costing us. Yeah. This might have cost them already 9 figures. Totally. Right?
Speaker 2:Can imagine when it goes back in the app store, the amount of the flood of demand and new revenue. And so delaying that by even a, you know, a few days would be would be damaging. So
Speaker 1:Yeah. Unfortunate to Journal says Epic Games Fortnite claims Apple block submission now unavailable on iOS. The claim is the latest in a long running feud between Epic Games and Apple. The legal began it. So I agree with you.
Speaker 1:There could be another case, but do you know how long it's been for the first case? This is we're coming up on the five year anniversary. Yeah. Started in August thirteenth of twenty twenty. Epic implemented a a direct payment system within Fortnite's iOS version circumventing Apple's thirty percent commission fee.
Speaker 1:This action violated apps Apple's App Store guidelines leading to Fortnite's removal from the App Store. In response, Apple, Epic filed an antitrust lawsuit against Apple in the United States District Court for the Northern District of California challenging Apple's restrictions on alternative in app payment methods. It took five years. And so, yes, they might have taken a couple pennies or millions of dollars out of Fortnite's pocketbook by delaying a few days. But if they can turn this into a five year lawsuit, that's five years of 30% fees.
Speaker 1:Right? Yeah. So that could be the calculus. It's like, yeah. Let's just let's just let's just play the court game.
Speaker 1:That's fine.
Speaker 2:Crazy.
Speaker 1:Anyway, other news. Hostile. Novo Nordisk has their CEO has stepped down. This is the maker of Ozempic, and the stock has been on an absolute tear. I would love for you to pull it up on public.
Speaker 1:Let me know what it's doing. But we have an we have a post from an I'm an on a non risk addict.
Speaker 2:No. You're you're saying a tear downward. Right?
Speaker 1:Well, it was on a tear upwards for a long time during the GLP one boom.
Speaker 2:But it's down 50 over the last year.
Speaker 1:Oof.
Speaker 2:Yeah. Not
Speaker 1:good. So, yeah, may maybe makes sense. But a non risk addict has a take here. No idea if he has done a good job as CEO or if the change makes sense based on expectations going forward, but firing a CEO for highlighted reasons is obscene. Novo traded at 50 XPE.
Speaker 1:The market going crazy and then being a little less so is not the CEO's fault. So if you're running a company and it becomes kind of a meme stock and it runs up to an insane multiple and then it pulls back a little bit, but you're still way above where you started as CEO, can you really be hit with, hey. The stock's down 50%. We've seen there was Palantir. Palantir was extremely hot, and then, of course, it pulled back a little bit.
Speaker 1:We see this with Tesla too. Tesla pulled back a little bit, but it's still, like, a really solid company, really, really incredible market caps and and great private great great price to equity, ratios. And so, the highlighted reasons here are during his eight year tenure as CEO, Novo Nordisk sales profits and share price have almost tripled. Novo Nordisk has clear strategy, a strong portfolio product portfolio and an experienced leadership team. The changes are, however, made in the light of recent market challenges Novo Nordisk has been facing, and they have.
Speaker 1:They they there are because this is an older technology as we talk to some of those biotech folks, we've seen that there has been more competition than usual. Normally, you create some breakthrough, you're able to lock it down for years. That hasn't been the case in the GLP one
Speaker 2:scenario. Hypercompetitive from not only other scaled pharma companies, but the, you know, the compounding and and Yep.
Speaker 1:Considering the recent market challenges, the share price decline, and the wish from Novo Nordisk Foundation, the Novo Nordisk board, and Lars Fuegard Fuegard Jorgensen have jointly concluded that initiating a CEO succession is in the best interest of the company and its shareholders. Yeah. Very rare that you see a CEO, go out while the stock is still trading at 50 XPE, doing really well overall, even if it is down 50% recently. I mean, that's not good.
Speaker 5:But Yeah.
Speaker 1:Anyway, know what Nova should do? They should get a ramp, obviously. That should be the first thing that they do with the new CEO. They should bring in ramp. Ramp.
Speaker 1:Ramp. Ramp. Ramp. Time is money saved both easy to use corporate cards, bill payment, accounting, and a whole lot more all in one place. They should also be using Figma.
Speaker 1:We should talk about Figma. Think faster. Build faster. Figma helps design and development teams build great products together. You can get started for free.
Speaker 2:The best. Figma is Figma for Figma. You can do a lot with it. You can generate marketing assets. You can generate apps.
Speaker 2:You can create websites and a whole lot more.
Speaker 1:Yeah.
Speaker 2:Thank you to Figma for supporting the show.
Speaker 1:They should also get on Vanta. Automate compliance, manage risk, improve trust continuously. Vanta's trust management Back to back. It takes manual work out of your security compliance process Cool. And replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program.
Speaker 1:Anyway
Speaker 5:Thank you.
Speaker 1:The other news is, Semi Analysis is talking about the AI deals that have been happening in The Middle East. Dylan Patel coming on the show in a couple weeks. US strikes a deal with The United Arab Emirates and The Kingdom Of Saudi Arabia, a five gigawatt data center, the Humane g 42 diversion, and American AI wins. Dylan Patel breaks down. He says The US Saudi slash UAE AI deals are complete wins.
Speaker 1:Everything is there to win over The Middle East and accelerate infrastructure spend. So American companies, AI companies are gonna be making more money from this because we have a new customer. The main subtext here is that China is locked out of Middle East AI infrastructure investments. There's a different world. There's a different path where, yes, there were some controversial moments in Trump's tour of The Middle East, but there is a different world where we are watching Xi Jinping do that tour and we're watching from the sidelines.
Speaker 1:That's not what happened. What happened is is our president went there
Speaker 2:We would have struck a
Speaker 1:bunch of deals.
Speaker 2:For the first time on the show
Speaker 1:if we were watching. Instead Sam Altman and Elon Musk and Alex Wang, it could have been the founders of Huawei and DeepSeek and Highspire. Yeah.
Speaker 2:Can imagine there's an alternative timeline where, you know, the QIA is investing
Speaker 1:Yep.
Speaker 2:You know, a hundred billion dollars. Yep. Not actually a hundred, but massive amount of money into Manus. Right? Or or DeepSeek or some of these other players.
Speaker 1:Are you talking about Manus? Manus? Manus? Oh, we talk open We can talk about Manus. Open source AI agents with Manus.
Speaker 2:With Manus, you're gonna make me put my mustache, in fact, on, John.
Speaker 1:No. No. No. We have a we have a very important person coming on the show, Jordy. Just put that mustache
Speaker 8:down.
Speaker 2:Put that mustache down.
Speaker 1:Put that mustache down. We have the chief operating officer of or chief product officer of OpenAI coming into the studio. And so, The UAE ruling family used headline grabbing investment numbers, deals with Trump's family businesses, and ties with tech executives to score an NVIDIA deal, and it's all looking good. Let's see if we have Kevin in the studio. Let's bring him in.
Speaker 1:He's here. Fantastic. How are doing?
Speaker 5:Yeah. Is wild. I just, like, joined a Zoom and I'm live with you guys.
Speaker 2:We're live. Yeah. It's great to
Speaker 5:have you.
Speaker 1:Welcome. I
Speaker 5:I was watching you on x and thinking how weird it was that in thirty seconds, I was gonna be on the screen. This is awesome.
Speaker 1:We're leveraging this thing. It's called the Internet and technology. But we we'd love to get you up to speed on it since
Speaker 2:It's funny. A funny story. So Tyler Cowen called into the show before one of your guys' earlier releases and he was like, AGI is here. Like, he was basically saying like, it's a couple days out, but he couldn't get his camera working. And it was this like funny funny dichotomy of like There was an AGI is here, but like Yeah.
Speaker 2:The internet is still actually
Speaker 1:There was actually another day when we had to basically take the whole show down because Zoom and both both Zoom and Google Hangouts just went completely down, like Yeah. Nationwide. And so we were like, well, we can't do our show now, I guess.
Speaker 2:That's very rough.
Speaker 5:The running joke is that audio video is like ASI complete.
Speaker 2:Yes. Yeah. Yeah.
Speaker 5:Well, everything else in the world is solved.
Speaker 1:Yeah. Wait. So, I mean, I think, long term for the show, we need to go proprietary. We need to build our own video streaming stack. Can you can you help with that?
Speaker 1:Codex. Codex won't You
Speaker 5:know what can help with that? Yeah. Codex can help with that.
Speaker 1:Break it down. How would I use Codex?
Speaker 5:And by the way, you get to talk about AI and then you're gonna have Blake from Boom here. So you get to talk about supersonic flight afterwards. You guys have the coolest lives ever.
Speaker 2:Thanks. Full stack. Thank you. Technology.
Speaker 1:But, yeah, can can you can you take us through the announcement, break down exactly what launch, when it's available, to who, what you're excited about, and then we'll go into some of the trade offs in the product design and development.
Speaker 5:Yeah. Let's do it. So we just launched this morning, Codex, which is a cloud based software engineering agent that can work on many tasks in parallel. So a lot of folks are used to the kinda cursor windsurf style, you know, GitHub Copilot style of AI development, which is really more about augmenting a single engineer. Right?
Speaker 5:You're you're writing code in your IDE and you can press tab, tab, tab, it'll auto complete and you're, you know, ten, twenty, 40 percent faster.
Speaker 1:Yep.
Speaker 5:With Codex, you actually have a software agent that runs in the cloud that can do entire tasks for you. So you give it a task, it goes off and does it, and suddenly you have a PR and you didn't work on it at all. And it's powered by a version of o three that we fine tune specifically to be really good at these kind of hard software tasks. We're super excited about it. It launched today inside ChatGPT.
Speaker 5:Mhmm. So you can use it if you're it's rolling out now to pro, to enterprise, to teams. Well, it'll make its way to plus in the coming weeks.
Speaker 9:Mhmm.
Speaker 5:But the cool thing is it's a it's an agent it's a software agent in the cloud. So, you know, you're using it today from ChatGPT. You can imagine using it in the future from, you know, your terminal, your IDE, all kinds of other places. And even, you know, hooking it up via API to your bug queues and just having this software agent churn through every single bug that you have. You know, for each one, look at the context of the bug, understand your code base, and then suggest proactively how you would fix that bug and give you a PR that you can review.
Speaker 1:Mhmm.
Speaker 5:So the the world of software is changing. We're super excited about it. It's a research preview. It's not perfect yet, but I think this is the future.
Speaker 1:Yeah. So Incredible. I mean, I've already noticed that ChatGPT has been writing code for me for a while. It seems to be writing more and more code. I was telling Jordy about how I wanted to know the height of a desk in an image, and I knew how tall a person next to it was.
Speaker 1:And I thought that it would just use images in ChatGPT to kind of one shot this or guess. Yeah. But it wound up spinning up and looking at the individual pixels with a bunch of Python code. I think it wound up writing, like, 5,000 lines of code or 500 lines of code, and it got it really right, unsatisfactory because it was just an average sized table. It was, like, literally the standard size, but it really knew it.
Speaker 1:But but so I'm wondering, like like, is this something that will will feel like a deep research project where or deep research functionality where I click a button to say, hey. Let's use codex for this. I'm giving you the hint, or is this something that can be automatically triggered just from a text interaction like images in ChatGPT?
Speaker 5:Yeah. So it's a I mean, by the way, you you never know if that desk was actually, like, 38.2 inches.
Speaker 2:Yeah. It's worth it. Totally worth it. Write the 500 lines of code.
Speaker 1:Yeah. Why not? It's too cheap to meter.
Speaker 5:Actually, that's been one of the big The coolest thing about o three, o three personally for me, has been a kinda feel the AGI sort of moment using that model. The things that it can do. Yeah. And it's a lot of it comes from the fact that it can use tools while it reasons. Yeah.
Speaker 5:So it's thinking. And in the process of thinking, it can do some web searches and then it can take what it learned from a web search and write some code. And then after that code, it can do image analysis and then it can write some more code and do another web search. And then finally, with all of that context that will output the answer, It's like it's really been an unlock for a huge number of use cases. And that's the kind of thing that enables codecs here.
Speaker 5:Because you're right, ChatGPT has been able to write code for a while. Right? You can can just go to ChatGPT and type in like, here's a, you know, write me code to sort this array of integers that I have. And it can give you the code and it's gonna be great at it. The difference here is Codex is built to work on big complex code bases.
Speaker 5:So you're not just saying like do this little task for me, write this function. You're saying, have a bug and I don't know where it is. There's a, you know, hundred thousand line code base. Can you please go understand my code base and and try and fix this bug? Or I'm a new engineer at a new job.
Speaker 5:I'm trying to understand what the heck is going on in this code base. Can you explain to me where the code does x or y or z? And very quickly, it'll look through the code and give you an explanation of how something works. You know, it's funny. I've even seen examples where people go, hey, Codex.
Speaker 5:Find a bug in this code base and fix it.
Speaker 1:Just find one randomly. Just just get it.
Speaker 5:That's amazing. Complex stuff and do do do hard work on a huge amount of existing context Yeah. That differs from what you've been able to do in ChatTPT for a long time.
Speaker 1:Yeah. Wild. From a personal perspective, I I used to write Python pretty regularly. I haven't written much code, so I haven't really gotten into cursor windsurf world. Obviously, I've been writing code via ChatGPT now.
Speaker 1:I noticed recently I kicked off a deep research report, and it's and it prompted me to put it on an effectively a cron job. It was like, do you want me to just run this for you every week? And I said, yeah, that sounds awesome. That's great. But if I'm like a I don't have a repo, but I could set one up.
Speaker 1:Is there a world where me as kind of like a prosumer nontechnical user should set up a repo to house the custom code that Codex writes for me to make it a better experience for all the little custom software and tools and random stuff I use? Or should I just live in the o three world where the code is pretty much ephemeral?
Speaker 5:I think it depends what you're looking to do. You know, for simple things where you just wanna like quickly put together a script or something
Speaker 1:Yeah.
Speaker 5:Running it inside ChatGPT and not using version control and all of that is fine. But if you're if you're gonna do something, you know, that you expect to be longer lived, like it's the basis for something you actually wanna build for yourself and maintain, then I think setting up a quick GitHub repo and using codecs on it makes a ton of sense. By the way, I I so I used to be an engineer. I haven't you know, I still dabble and screw around on the side and write code, but nothing major. And I hadn't written any code at OpenAI.
Speaker 5:I've been there about a year and haven't checked in a thing.
Speaker 1:Yeah.
Speaker 5:Like, Tuesday Tuesday night, I think, I was I was doing, you know, the rest of my work and I was like, I I wanna fix a couple bugs. And so I went and found a couple really basic bugs because I don't wanna screw anything up and sent Codex off to work on both of them in parallel. Check back in a few minutes and I had two PRs. They looked right. So I submitted them, got them code reviewed by somebody, you know, who's actually a good engineer.
Speaker 5:They were submitted and now I've got a couple of commits in the code base. It's just it's like
Speaker 1:is stolen valor though. This is stolen valor. Didn't write that code.
Speaker 5:But it's cool like I I actually just kept, you know, other than just like getting to play around with the product and and offering a little bit of feedback on on a couple things. I was off doing the rest of my work.
Speaker 1:Mhmm.
Speaker 5:And I had this software agent working for me in the cloud writing code.
Speaker 1:Yeah.
Speaker 5:Kind of awesome.
Speaker 2:Talk about I I'm I'm so curious to hear about the kind of internal testing process and when when you guys decided the right time to actually roll this out as a research preview. Because I imagine you've been using codecs in one form of another internally for, like, a very long time. Maybe you didn't have a name or anything like that, but I'm sure that ChatGPT has been, you know, contributing to the effectively, the ChatGPT code base, you know, almost since the beginning in some form or another.
Speaker 5:Yeah. For sure. I mean, we're we're big users of our own tools. There was a there was a version for a while that that was mostly about the kind of how do you come up to speed quickly in a big code base that, was good at at understanding our code base and answering questions about it. That was really popular with new engineers on the team.
Speaker 5:And then once you kind of, you know, get to understand it, you might not use that tool as often unless you're exploring a new area of the code base. So that was like a proto version of this. Yeah. But we've been working a lot over the last six months at improving the ability of our models to code. Like, you've got GPT 4.1, which we released a little while ago, which is kinda which is very quickly become a a really popular model.
Speaker 5:It's now, I think, default in Windsurf. It's increasingly a large percentage of of cursor users coding. You know, that's that came from focusing on the things that matter in creating a really good coding model that you can rely on. It means really good instruction following, longer context, you the ability to, like, not just make the changes, but to make the changes a way a developer would. So don't add a bunch of extraneous stuff, don't add weird comments, make surgical precise changes that accomplish the job.
Speaker 5:So there's a style element to writing good code, not just a correctness element. And we've been focusing on all of this. And then you you kinda bring that together with o three and all of the the things that we were you know, that o three's ability to tool call and to reason and suddenly you can put together a really good coding model. So we've been thinking about this for a long time. This is the first time when we're like, okay.
Speaker 5:This is now good enough that we think it it deserves being a product for the rest of the world and we're excited to see how people use it.
Speaker 1:Can you talk a little bit about product design, product like, inspiration product design? I I noticed that the very first iOS app had these incredible haptics when the tokens were streaming through that I hadn't really seen anyone do. I just opened the app last night and saw that when you're using voice mode to dictate to it, it has a different modal now. It feels like there's a very strong design language evolving. At the same time, there was, you know, people complaining, oh, I can't even I'm using Chatuchipedia.
Speaker 1:I can't even stay logged in. That, that bug obviously got crushed pretty quickly. But but what what is the actual product design inspiration? Are there people that are pulling from certain schools of thought or anything? Or, like, is there someone driving that internally or is it just, like, baked into the culture?
Speaker 5:Yeah. For sure. Ian Silber leads our design. I was fortunate to work with him at Instagram. He's an incredible designer.
Speaker 5:It's building for for ChatGPT is a really interesting thing because we have, you know, well over 500,000,000 weekly active users at this point. So it's a it's a big scaled product.
Speaker 1:Yeah.
Speaker 5:And so for products of that size, one of the most important things is to simplify. Right? You're not just serving power users at that point.
Speaker 1:Mhmm.
Speaker 5:And so and so you're you're serving people that are just trying to get something done in their day. They don't want they don't care about the complexity. They don't care what the models are called. They just have a task and they wanna complete it and you wanna help them.
Speaker 1:Mhmm.
Speaker 5:But then on the other hand, we have folks who are super deep AI enthusiasts and wanna, you know, digest in every single new model that we use and try it out in all these different ways. And so we wanna both and we want them to we don't wanna sort of soften the edges of their experience. We want them to to be able to do everything they possibly can to experience all of, you know, the power of AI. And so we both want to like simplify the experience for for a lot of our users and we wanna provide the people that want it all of the bells and whistles. And so we try and we try and balance that.
Speaker 5:You know, so we you try and make it so that you don't need to worry about things like the model picker as much. You don't need to, like, have a bunch of AI knowledge in the background to do what you wanna do in OpenAI or in ChatGPT. But if you have that, you should be able to expose the sharp edges and, test the different new features and stuff. And so we we really actually try and get both of those things right and it's a delicate balance.
Speaker 9:How do you Is
Speaker 2:that why is that why you guys don't seem to put too much emphasis into perfectly naming products just because in the on a long enough time horizon, it doesn't really matter. I just come to, you know, ChatGPT, and I work with it to get the outputs and the results that I want. And I'm not regardless of my experience level, I don't necessarily care
Speaker 1:which is a very, very untamable, you know, demon
Speaker 2:Demon monster.
Speaker 1:Potentially a disaster. So we are now long four o and o three, and we just decided I just you know The names
Speaker 2:are great. Only sick only six months ago, a new model would get announced, and people are like, oh, it's so confusing, blah blah blah. Yeah. But it just it seemed to me, you know, as an observer that you guys like, it wasn't like, oh, this is a problem, and we need to fix it. It was just more so like, let's just keep making really great models Yeah.
Speaker 2:And make them easier to access in really intuitive ways.
Speaker 5:Yeah. I mean, in all in all seriousness, it comes from our focus. We we have this principle of iterative deployment that we really believe in, which is that these are new these models are new systems. Right? They're each one, each model has capabilities that we understand somewhat and and also we discover new things about it.
Speaker 5:And we believe that no matter how many smart people we have inside of our walls, there are way more smart people outside our walls. And the best thing we can do in a world of AI evolving so quickly is to kinda co evolve with society, to ship stuff early and ship often and learn together. And so one of the reasons that we have this explosion of models is we're trying to build new capabilities rapidly. And sometimes the easiest way to do that is to build it into a new model that's really good at one specific thing or a handful of specific things, but can't do everything. And so you end up with this, like, perfusion of models that do different things well.
Speaker 5:Like, 4.1 is really good at coding and instruction following, but it's like not as chatty. Mhmm. And so we're asking about other things you might prefer four o for some things and 4.1 for others.
Speaker 1:Mhmm.
Speaker 5:Seems totally natural. You'd go like, well, why don't you just build one that's, you know, good at coding when you're coding and good at chatting when you're chatting. And we will do that. That's what we're trying to get to with GPT five where we're trying to bring more of these things together. But if we tried to do that from the beginning, we wouldn't have been able to launch as fast.
Speaker 5:And so we've we've opted for, like, launching fast, having a little bit of, you know, confusion that comes with it, but we learn faster. And then over time, you sort of integrate and simplify.
Speaker 1:Guess, like, the the meta question, though, is, like, is the future just you're already using mixture of experts within the models. Is the future, like, a mixture of mixture of experts models? And so I I I go to one there's one command line. Text is the universal interface, not drop down model pickers. And and and it routes me.
Speaker 1:It says, hey. This person doesn't wanna chat. They wanna write code. Okay. We're using four zero one.
Speaker 1:Yeah. That seems kind of logical. And already, this is kind of happening with the model picker becoming like just the UI is getting less and less in your face, and it's a little bit easier to just have a natural interaction. But how do you see it evolving?
Speaker 5:Yeah. I think over time, the the capabilities that that have existed for a little while, you sort of learn how to bring them into a general model.
Speaker 1:Yeah.
Speaker 5:And and but you're always gonna have these new frontier capabilities
Speaker 1:Yeah.
Speaker 5:That you're gonna wanna be able to iterate on really quickly and you might wanna do specialized things to to make them all really great at some new frontier capability. And so I think, yes, ideally, you have a you have a a sort of model, you know, a a layer above the models that's doing the choosing for you.
Speaker 1:Yeah.
Speaker 5:But that is you know, it's a hard problem, especially it goes back to the the building for simplicity versus building to enable power users.
Speaker 1:Sure.
Speaker 5:As a power user, you might be the only one that knows for a particular question you're asking, whether you want a 80% good answer immediately or you'll wait a minute for a 95% good answer. Yeah. Or whether you wanna do deep research and wait twenty minutes and get an amazing answer.
Speaker 1:Yeah. Mean, you could theoretically like train the user on that a little bit like like
Speaker 2:Well, it's
Speaker 1:Because there are problems train with
Speaker 2:Yeah. The comp that I or like my personal framework is like when you're working with people on your team Mhmm. Or teammates, 's certain people you'd work with that you would have to explain effectively like the exact tool set that they should use to accomplish the task. Mhmm. You should get the CRM, and you should go in the CRM, and do this and that.
Speaker 2:And then there's people that are maybe have greater intelligence or experience or context, you just sort of like discuss the task with them. And you're not even thinking about the underlying sort of like toolkit to accomplish the It's just sort of this higher level. Yeah. You know, conversation.
Speaker 1:I I I wanna talk about AB testing versus personalization. You choose like a default model or the default prompts when you open up ChatGPT, it says create an image, write a Python script, make up a story, what's in the news. There's a couple options there. There's a lot of personalization going on, but you could also imagine doing AB testing to understand what will drive churn down or retention up. How are you thinking about balancing act between those two techniques of product development?
Speaker 5:I don't think they're really in at odds in any way. We do both. Yeah. So we we definitely AB test a lot of things, because we're trying to learn what works and and, you know, how how we can help people understand this new kinda strange world of AI. It's a funny it's a funny product.
Speaker 5:Right? You're we're used to products where, you you have a UI, like, computers before AI needed very specific inputs. Like this button does this specific thing and that button does this other thing. And if you wanted to do a third thing and there wasn't a button for it, you probably just couldn't do that thing. Right?
Speaker 5:But then every time you hit the button, you got the same output. It was very consistent.
Speaker 1:Yep.
Speaker 5:LLMs are basically the opposite. Right? You can give them input that is the that has the full complexity and nuance of the human language, and you have no limits on what you ask. And then also what you get out is not the same from one thing to the next. It might be substantially the same but the words are not identical.
Speaker 5:Right? Mhmm. And so it's just a it's a totally different way of building product. And when someone comes to ChatGPT for the first time, if they just hear from their friends, hey, this AI thing is super cool. It can do all this stuff for me.
Speaker 5:And they show up at the front door of ChatGPT, they're a new user. Like what's the mental model? Because it it flies in the face of almost every thing that you've learned using computers over the last however long. So we we really think a lot about how we get people going, and how we teach them all of the different capabilities, which, you know, by the way, the capabilities are changing every month or two too. So it's a it's a really challenging problem, but something that we care a lot about because that's you know, if you go from, being a novice JATTP user to being a power user, it can really change your life.
Speaker 5:It can save you a ton of time. It can accomplish a lot of tasks for you, and that's only increasing. So the the upside of us being able to teach people well is also increasing.
Speaker 2:Mhmm. Yeah. I feel like a decade from now, people are gonna look back at this moment and realize that the people that fully understood the capability, like the full capability set of the models just had this ridiculous sort of extreme advantage.
Speaker 1:It was the same thing with social media. Like the people that really understood and took social media seriously early on are like famous now. Like Yeah. Actually famous. Interesting.
Speaker 1:What what is your postmortem on the sycophancy thing? I feel like that like that made news because it was kind of blanketly like, it was kind of like everyone was experiencing or at least all the power users were experiencing it. But I could imagine a situation where some people really like that type of interaction, and it was beneficial, and it actually may improve their lives. And so if you go to the YouTube algorithm right now and you only search and click on positive content that reassures you, you can have a sycophantic experience, and that can be good for everyone involved. So how do you, what is your postmortem on it, and how do you think that, the personalization, will play out in the future?
Speaker 5:Yeah. It's a this was a really important issue. I mean, we so we the the story for people who don't know, we we rolled out a new version of GPT four o, which is something we do pretty regularly. There's There were always, you know, to your point about AB testing.
Speaker 1:Yeah.
Speaker 5:We're testing new versions of GPT four o that are incremental improvements over previous versions. So we rolled out a new one and, you know, we they'd be tested in the past. So we, you know, the the metrics look good. It looked like a really solid model, had some new stuff around personalization. And then as it got out there, we saw that a number of of use cases, not like super widespread, but enough use cases where we saw the model sort of, overly, like like, just being some of it was, like, glazing, what people called glazing Yeah.
Speaker 1:We call it that. I think we used that term.
Speaker 5:Yeah. But then but then there were other cases that were more more serious
Speaker 1:Totally.
Speaker 5:Where someone had real problems.
Speaker 1:Yeah.
Speaker 5:And, you know, maybe they they were having mental issues and the model was sort of validating them in ways that didn't really comport with reality. And that's like a that's a real thing. And we took that super seriously. So we rolled the model back and then, basically, I've spent the last few weeks diving into, where this is coming from and what we need to do to to make sure it doesn't happen again. And we've tried to be super transparent about it.
Speaker 5:So, you know, we tweeted as soon as we were rolling it back and then immediately put out a postmortem like, you know, within a day or so and then put out a second after we had done a bunch of deep dives. And so we've gone through, we've like the the team did some great work. We've got evals now that measure this. We understand a bunch of the root causes from where this came from, you know, as always with these things, they're not it's never just one thing. It's like a little bit of this combined with a little bit of that, and then this unexpected thing happened.
Speaker 5:And together, they created something that that, you know, wasn't up to the standards that we set for ourselves.
Speaker 1:Yeah. So It's I yeah. Sorry. I I I just have a interesting realization with the product. So we've been hearing this this, like, this request for feature on social media for a while of, like, I wish I could just reset my algorithm, start fresh, because I feel like it's funneled me in some sort of echo chamber and I don't like that echo chamber and I want to start fresh.
Speaker 1:And I don't know if social media feeds actually have that feature, might just be buried, but I've noticed that with the Chachapiki Memories, early on, I was really aggressive about prompt engineering and and basically, like, prompt hacking. And so to get the best responses, if I was trying to learn about trains, I would say, like, I am a world expert in trains. I own multiple train lines and railroads. Give me a breakdown of the market map of trains. Basically lying to it.
Speaker 1:And then it remembered that. And so now it's like, well, as a train conductor, you'll probably wanna eat this for dinner. And I'm like, oh, okay. I I I have to back up. I wasn't being completely honest with you, ChatGPT.
Speaker 1:But the good news is that the saved memories are there and I can delete them all and so I can kind of reset my experience. But was that a learning from the demand that people are seeing in the not the stated preference on social media for resetting? Or do you think that that's important? Or what other lessons are you learning from from how social media has played out? Because you obviously have a lot of experience there and a lot of people at the team have experience in social media.
Speaker 5:Yeah. It's personalization is a is a really powerful thing that I think we're just at the very beginning of. Like, you want I mean, in the same way that we we know each other a little bit.
Speaker 1:Yeah.
Speaker 5:You have you have best friends that you know super well who you're really comfortable with and then you have strangers and your, you know, your level of comfort in interacting with them is very different.
Speaker 1:Yeah.
Speaker 5:You want your if you have a super assistant in your life in ChatGPT, you want it to know you really well. You want it to know your habits and how you like to do certain things and you know, even down to like, do you want, you know, more flowery supportive language or do you want crisp analytical terse language, things like that. I've I was messing around last night with ChatGPT trying to do trying to give my son some math homework and he I just said, hey, can you design 10 math problems for Matthew? And the model knew Matthew was my son, knew he was 10 years old and developed a bunch of, like, grade level appropriate escalating, you know, and it was like that was super cool. And it even it was like, oh, he likes Legos and Kevin, you're a runner.
Speaker 5:And so a bunch of these program or the bunch of the questions were like Lego themed and you're going on a run with your dad and this. And so like, okay, that's just really cool.
Speaker 2:It's truly making me emotional. It's like the coolest thing. As like a parent, to be to give your children a truly bespoke magical experience is like almost priceless. Yeah. Even in the context of something like homework, right?
Speaker 2:And so to that and and even knowing that, like, kids today, like, both of our all of our you know, we've we've got five kids be between the two of us. And knowing that they'll grow up only knowing the sort of world in which this kind of technology exists where a parent can just, like, generate magic for them in, like, seconds is Yeah. Just unbelievable.
Speaker 5:I mean and and think of the world. This thing designed 10 math problems. So I used o three. It designed 10 math problems for my 10 year old that were escalating in difficulty across a range of different things. It could easily if he was entering in the answers, could easily realize over time where you know, what what concepts he understood and what concepts he didn't and just, yeah, become a personalized tutor for every single kid.
Speaker 5:And remember, I mean, this is free. Right? We don't charge for JaiGBT. You can you can get a subscription, but you can also use it for free. Basically, you know, you even need an account.
Speaker 5:You need an Android phone anywhere in the world for free and you can, you know, get this thing that's starting to be more and more of a personalized tutor. I just like I think it's incredibly powerful.
Speaker 2:Totally.
Speaker 5:Every every study I've ever seen says that when you pair, you know, traditional learning with personalized tutoring, the it's like a standard deviations of improvement. So I'm with you. I think the future is gonna be very different and there's a lot of reasons to be optimistic about what the next generation is gonna be able to do with AI.
Speaker 2:Need to be more honest
Speaker 1:with Jesse.
Speaker 2:How you explain the rate of AI progress to, let's say, like a family member of yours that's not in tech?
Speaker 5:That's a good question. I think the only way, honestly, because you can talk about it, but it's like you can't you can't get fit by reading about going to the gym. Like, you can't use it.
Speaker 1:Yeah.
Speaker 5:And so I've been trying to get any of my family members who aren't using it, just just try it. Start asking, you know, for everything that you're doing, ask why couldn't I use ChatGPT for this? And you start to realize that there are more things that you can say yes to there and you can start using ChatGPT. Mhmm. And then, you know, the more you use it, the more you realize the value and and off you go.
Speaker 5:It's really hard to explain in the abstract. Right? People go, agents. I'm hearing so much about agents. What is it?
Speaker 5:And then you use deep research or you use Codex and you're like, oh, wow. That just saved me a ton of time or did something I couldn't have even done. Yeah. Yeah. That's the promise of the future.
Speaker 5:I think we're all gonna be much more productive. We get to not focus as much on the doing of particular things. We get to focus on the outcomes and what we do once once some of the labor itself is is taken care of. And that's that's a super exciting future for me.
Speaker 2:Couple more. Help talk to us about HealthBench.
Speaker 5:Yeah. So, a huge amount I mean, people are increasingly using ChatGPT for health. I've done it any number of times. My son had a small surgery that was supposed to be 99.9% innocuous, 0.1% bad. And we got the results back from the doctor before I could talk to the doctor and they look scary.
Speaker 5:And it's full of a bunch of medical jargon that even as a former scientist, didn't understand. And I put it in chat GPT and said, this looks weird. What is this? Is this should I be worried? And it said, no no no.
Speaker 5:Don't don't worry, it's fine. And I was like, okay, explain it like I'm five. And it did. And you know, I couldn't get ahold of the doctor for another seventy two hours. Would have been a bad seventy two hours for me if I was sitting there like stressed out about my son and ChatGPT gave me the peace of mind.
Speaker 5:Yeah. So we always try and say with anybody, anybody asks about anything medical, you know, this isn't a substitute for actually seeing a doctor. ChatGPT is not a doctor, but here it is. Here's the understanding of what's going on there. And it's really valuable.
Speaker 5:For all of us, for me it saved me seventy two hours of anxiousness.
Speaker 1:Stress, yeah.
Speaker 5:For somebody else who doesn't have access to a doctor, it might be a totally different thing. So anyways, we care a lot about this. We wanna make if people are using ChatGPT for this, we wanna make sure that the answers that it gives are really good answers. And so we're putting a lot of effort into improving chat GBT's ability to act as or to to answer medical questions. And the only way that you really know if you're doing it right is if you have a benchmark.
Speaker 5:Right? You've gotta have something to test against to show that you're getting better. And we figured if we've done a lot of work to put this benchmark together, then, you know, others could benefit from it outside of us. And so we we we open sourced it.
Speaker 2:Last question. Can you give us the thirty seconds on why you were excited to join Cisco's board of directors?
Speaker 5:Oh, yeah. Totally. So, I mean, Cisco is an is an incredible company, like, iconic Silicon Valley software and hardware company. We all use it every day in in a hundred different ways. And they're at this really interesting point because I think AI can transform their business, and they can either be transformed like, it can either happen to them or they can get ahead of it and build some really amazing software and tools and become, you know, sort of a even an even more powerful leader for the next gen, the next generation.
Speaker 5:And I I think that's not unique to Cisco. I think a lot of companies are at that turning point, but Cisco really realizes it. By the way, they're actually a launch partner today for us with Codex. So they're one of our early partners. They're looking a lot at how AI can can help them get more done, you know, faster, more cheaply, etcetera.
Speaker 5:So it's just AI is gonna really impact their business over the next, you know, three to five years, and I'm excited to be a part of that and hopefully help them navigate, this transition gracefully.
Speaker 2:Amazing.
Speaker 1:Well, I have, like, five more hours of questions, but we will let you go. Let you go.
Speaker 2:There you go. It's We'll come up to ask Most
Speaker 1:questions can be answered by chat GPT, but there's certain questions you gotta go to the source.
Speaker 2:Organic farm farm to table.
Speaker 5:Yeah. Yeah. Well, thanks so much for having me on. It's good to see you guys.
Speaker 2:Very good to see you, Kevin.
Speaker 5:About supersonic jets that I wish I could stay for
Speaker 1:that one. Yeah, we'll talk to you soon. Great to see you. Cheers. See you, bye.
Speaker 1:Kevin is the But you know what else is the man? Linear is the man. Linear is a purpose built tool for planning and building products. Meet the system for modern software development. Streamline issues, projects, and product road maps.
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Speaker 2:Sam said too low.
Speaker 1:Too low? You're
Speaker 2:not bullish enough on sales tax, AJ.
Speaker 1:It's on record or not. Well, it's live.
Speaker 2:Posted. No. He he no. No. He posted this.
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Speaker 1:Okay. So we're not we're not
Speaker 2:scooping anyone here. We're not scooping We
Speaker 1:have Blake from Boom Supersonic in the studio. Welcome to the show, Blake. It's been too long.
Speaker 2:We've been wanting to do this for a while.
Speaker 1:Yeah. Ideally, from a supersonic plane, we're we're we're aviation aficionados. We like traveling. But the hard thing with the show is that it takes us six hours to get across the country. We podcast for three hours a day.
Speaker 1:The math just doesn't make sense, so we're happy that you're working on a solution for us.
Speaker 6:Indeed. Well, thank you for thank you for having me. Yeah. It will be fun to do the first ever supersonic webcast. Maybe we should just agree to do that.
Speaker 1:I'm a % on board.
Speaker 2:Let's do it.
Speaker 1:Count me in. Can you give us just the general update? Obviously, explain, like, what you're building, but what's, what's the latest news in the world of Boom Supersonic?
Speaker 6:Yeah. Well, think for if anybody's not been following this story, you know, the goal is to really pick up where Concord left off, foment a supersonic renaissance, ultimately deliver, faster travel for our everybody from the president on down to every family. Mhmm. And so it's a it's a decades long mission, you know, ultimately to replace subsonic with supersonic for every passenger on every route. But but building building companies like Boom is it's like building an iceberg from the bottom up.
Speaker 5:Yeah.
Speaker 6:And I feel like this year is the year that the iceberg has, like, really emerged from the the surface of the water. Yeah. In January, we broke the sound barrier with our test airplane, the XP one.
Speaker 1:Broken the sound barrier. We love to see it.
Speaker 6:Right? And then and then in February, we did it again, and arguably, we broke it permanently. Double Fantastic.
Speaker 5:That's great news.
Speaker 1:Yeah. You said you broke it permanently? Is that what you said?
Speaker 6:Yes. Because we proved we could do it reliably with no audible sonic boom.
Speaker 1:Oh, there you go. Okay.
Speaker 2:They said it couldn't be done. Said it couldn't be done.
Speaker 6:People people the way, it turns out that, like, people have been telling me this for decades.
Speaker 1:Yeah.
Speaker 6:Boom. And mostly the claims are it's, like, really hard. You have to, like, change the aerodynamics of the airplane and dah dah dah dah. It no. It's a software fix.
Speaker 1:Really? How? Explain that. Me
Speaker 2:just Everything is computer, John.
Speaker 1:That's it. Everything is computer.
Speaker 6:If you fly the airplane at the right altitude at the right speed for the current atmosphere, the boom makes a u-turn in the sky and never touches the ground.
Speaker 1:No way.
Speaker 6:That's so
Speaker 5:But
Speaker 1:you need to be able to calculate that
Speaker 6:That's right.
Speaker 2:In real time.
Speaker 1:You need, like,
Speaker 6:decently good weather data Yes. And and and ironically, algorithms that were developed for computer gaming.
Speaker 1:Wow. Oh, that makes sense. Yeah. So it's a it's a physics simulation.
Speaker 6:It's it's it's ray it's ray tracing.
Speaker 1:You're running Unreal Engine. Almost. I'm sure you have a proprietary system. What does that need to go through FAA approval to use that, or is that separate from the rest of the aircraft authentic wait. What what's it called?
Speaker 1:Qualification or, like, approval?
Speaker 6:So you need to certify an airplane Certify. Carry passengers.
Speaker 5:Yeah.
Speaker 6:You know, basically, you gotta prove you meet all the safety standards.
Speaker 1:Yeah.
Speaker 6:Yeah. And this this is separate because we we have one of the dumbest regulations ever created.
Speaker 7:Mhmm.
Speaker 6:In 1973, we banned supersonic flight in the Like, literally, there's a regulation that says, thou shalt not exceed Mach one.
Speaker 1:Yeah. And it's speed limit, not sound limit. Right?
Speaker 6:Right. It's really stupid. It's really stupid. And and so no you know, we could, like, make it play Mozart when it flies over Yep. And you're still not allowed to do it.
Speaker 6:And that's why that's why those coast to coast flights are still stuck at six hours. It's why no one's done this already. And and so we're we're working really hard to get that, changed. We had a big something that,
Speaker 1:like, the EO would just drop, and it would be like, oh my god. He just tweeted it out or put it on truth social, and it happened. Like, love him or hate him, but, like, the guy definitely, like, likes to rip a crazy idea on short notice for everyone. Are you optimistic that there will be change? Does this need to go through the house and senate, or is this something that could just happen in EO?
Speaker 6:So we've had good conversations at FAA. Bipartisan bill dropped in the house and the senate that does it. Cool. And Elon endorsed it. Jared Isaacman endorsed it.
Speaker 6:Right. We've got bipartisan support. Great. Some people think this could get through the senate unanimously. Amazing.
Speaker 6:I think that's probably a little ambitious. Mhmm. But, but even the even the idea that that's possible, I think, is pretty cool.
Speaker 1:Yeah. Some lawmakers like traveling slower because it inspires them to grind harder. More time on the plane, more time to prep their filibusters. They don't wanna go fast.
Speaker 2:I get that's right. The the bear case for supersonic
Speaker 1:flight is The fast plane is
Speaker 2:there. I get so much email done
Speaker 1:on a I do get lot of email done on a six hour flight.
Speaker 2:And if I got there faster, I do less
Speaker 1:email was texting Jordy when we were flying to DC. I was like, this is incredible. I've never been more productive. But Well, I
Speaker 6:think faster flights were just forced us all to be more efficient with our time. Right?
Speaker 2:That's right.
Speaker 1:Yeah. But but, I mean, break down the actual scope of the problem here. How much is engineering? How much is regulatory? How are you staffing against that?
Speaker 1:Do you have a massive government affairs team and lobbyists? Or I imagine there's still a ton of engineers on the you're not just taking some, like, white labeled plane and then doing a bunch of lobbying, and that's the endgame. Right?
Speaker 6:Yeah. I mean, the most surprising thing is that we don't have to invent anything fundamentally new. This is not a science project. It's not a technology project. It's really just an engineering project.
Speaker 7:Sure.
Speaker 6:In fact, we're taking 20 year old seven eighty seven technology
Speaker 1:Mhmm.
Speaker 6:Basically reshaping the airplane, making it long and skinny, putting twice as many engines. Mhmm. And so there's a lot of engineering and testing that goes into that, but there's no science and there's no new technology. Yeah. And there's only one regulation that needs to change.
Speaker 6:Mhmm. Just the speed limit. Small numbers of great engineers. I'm a big believer in, like, tiny teams
Speaker 5:Yeah.
Speaker 6:That are very focused. Like, did we we built XB one, our test supersonic jet, with just 50 people.
Speaker 1:50 people. Wow. 50 people. The overall company is not that much bigger. Right?
Speaker 6:Right. We're, one fifteen now, and, like, we're growing very slowly. Like, if a team does not complain about being understaffed, I know they're overstaffed.
Speaker 1:Yeah. Yeah. I mean, we we were joking about, like, white labeling a plane. Obviously, you are standing on the shoulders of giants using some off the shelf technology, using some technology licensed from other firms. Can you take me through the journey of engine development, the decisions that you made?
Speaker 1:Have you changed course on any of those decisions? What would you recommend to the next generation of aircraft builders?
Speaker 6:Yeah. Well, I'll go broader than that. Like, if you're if you're thinking about doing hardware at all, my my my advice or frankly, any start up. Any start up all start ups are hard. I don't think any are easy.
Speaker 6:I think the difficulty level is set by founders because we tend to run at our own red line, and if somehow it gets easier, well, does it make the job harder again? Like like like, Brian, you know, Brian just decided to, like, you know, double what Airbnb is.
Speaker 1:Yeah.
Speaker 6:You know? Because I guess the old thing got too easy.
Speaker 1:Yeah. Yeah.
Speaker 6:And and so it's what I what I've found along the way is I'm far more successful if I pick a mission that deeply inspires me and makes it worth being at my red line. So I never get up in the morning and think, is it worth Mhmm. Okay. Great. So now now probably building supersonic jets is, like, you know, the ultimate hard mode.
Speaker 6:And but what I have found along the way is people around the company from the legacy industry will have all these stories about all these things that are impossible to do. You know, you can't build your own jet engine. Like, only a big company could do that. There's tons of proprietary technology, blah blah blah blah blah blah. It's all bullshit.
Speaker 6:Mhmm. It's all bullshit. Like, I'll tell you one story. Like, we were trying to get, high temperature super alloys for our engine, And, you know, we thought we needed to go license it from one of the big three. We get into this licensing conversation, and they're like, oh, we can't give you this thing because there's a trade secret.
Speaker 6:I'm like, don't tell me the trade secret. I'll give you the part. Just make me the part, hand me the parts back and don't tell me the secret. And they said,
Speaker 9:no no no no.
Speaker 6:You'll find the secret. So we can't do that. And for for like two weeks, we're like, oh shit. Like how do we ever get this engine built? But eventually, just went into the supply chain and we found the trade secret.
Speaker 2:We found
Speaker 6:it. And I'll tell you the trade secret.
Speaker 1:Okay.
Speaker 6:There is no trade secret.
Speaker 1:Oh, interesting. The
Speaker 6:thing that was theoretically proprietary is an open source material developed by NASA where all the specs are public. The trade secret is
Speaker 1:that they're using open source.
Speaker 2:That was the trade secret.
Speaker 6:The trade secret was there is no trade secret.
Speaker 1:There's no trade secret.
Speaker 6:And because there's all this fake proprietary.
Speaker 1:And that,
Speaker 6:you know, everybody's telling you why you have to work with them, why you have to use their stuff, why you couldn't create it yourself. Yeah. And, you know, and it just nine times out of 10, it's just not true. And so we we we found you know, we probably heard Elon talk about the idiot index, which is like how much a finished part cost is divided by the raw materials cost. We found a thing that's more important.
Speaker 6:It's called the slacker index. Slacker index is how long it takes to get something divided by how long it takes to actually make it.
Speaker 2:Mhmm.
Speaker 6:Wow. And and so we've got these turbine blades. We're three d printing turbine blades for our engine, and we go quote it out of the traditional aerospace supply chain. It's gonna cost a million dollars for one engine's worth of parts, and it's gonna take six months.
Speaker 2:Mhmm.
Speaker 6:I was like, well, how long does it take to print a blade? Well, it's like actually about twenty four hours. So why does it take six months to get one? Well, they were like printing them like one at a time and then you gotta wait for your turn on the machine, all this not okay. What's the machine cost?
Speaker 6:$2,000,000. How long does it take to get a machine? Well, actually, they've got them in inventory. You get them in a couple weeks. So for the price of two engines worth of blades, we got the three d printers and the blades, and we could and and and we beat the lead time of just outsourcing it.
Speaker 1:Wow.
Speaker 6:And that and that pattern exists everywhere in this business.
Speaker 1:Can you talk about the current fundraising market for hard tech companies? There's a bunch of companies raising a ton of money. There's other it's feast and famine out there. Yeah. The f 35 costs a trillion dollars.
Speaker 1:Somehow, I feel like trillion dollar raise is on the table soon based on the current market.
Speaker 2:Yeah. We'd like we'd personally like to see you do one t on five t.
Speaker 1:I'd love to see that. I'd love to see that. On five t.
Speaker 2:That should be the new the new goal.
Speaker 1:But but, I mean, there is there is a world where a plane company comes out and raises just massive money and just dumps it all into subcontractors and takes a very different approach. Why wouldn't that work? And and and what advice would you give to the next generation of hard tech founders in aviation or otherwise?
Speaker 6:Yeah. So the the key difference so so there's this mythology that hardware companies are more capital intensive. Mhmm. And if you go look at, like, how much money did Uber raise? How much did Lyft raise?
Speaker 6:How much did Stripe raise? How much did Airbnb raise? Like, these, like, theoretically capital light businesses consumed billions in venture capital Yep. Before IPO. So wait wait.
Speaker 6:What? And if you go look at, like, SpaceX or Andrill, like, you know, the theoretically hard tech companies, like, oftentimes, they raise less money.
Speaker 1:Mhmm.
Speaker 6:So, you know, WTF. And I I think that the difference is, if you are building, say, Uber or Airbnb, you have an idea that sounds really counterintuitive, like invite strangers from the Internet to sleep on your couch.
Speaker 1:Mhmm.
Speaker 6:Right? It doesn't sound like a good idea, but it's actually really cheap to test. Yeah. And and and so what happens in most Internet businesses is very small amounts of capital allow you to test whether your product market fit, and and you and you test it by means of building and shipping the product. We can't build a supersonic airliner as a means to testing whether anybody wants a supersonic airliner.
Speaker 6:Right? So so what you have to do in a hardware business is is find a capital light way to demonstrate that you're a product market fit, and the answer can't be shipping the product. Mhmm. So so so, you know, our strategy was preorders.
Speaker 1:Yep.
Speaker 6:So we, you know, we got United American to make like deposits, like nonrefundable deposits on airplanes against a specific design.
Speaker 1:Mhmm.
Speaker 6:So it's not just like, okay, here's, you know, here's a dollar that says, you know, supersonic is cool. It's like, nope. Here's a significant multimillion dollar deposit, a whole further deposit schedule against a very specific airplane with very specific specs. And and and then so we can go to investors and say, if we build this, there's obviously a gigantic market, and this is gonna be like a thousand
Speaker 2:guys are already getting paid for it.
Speaker 6:That's right. Yeah. So all you all you have to all you have to believe is we'll actually ship the product.
Speaker 1:Mhmm.
Speaker 2:What was the I wanna ask you what was the worst week building boom, and what was the best week? I'm guessing the best week was this year.
Speaker 6:Yeah. I think the I'll give you the best moment. The best moment was the day that we broke the sound barrier for the first time, but it wasn't actually the moment of breaking the sound barrier. We'd done so much testing at that point. I knew if we flew that day, were gonna break the sound barrier.
Speaker 6:What I didn't know is whether we'd have the weather to do it. And, and like I'd gotten up that morning, it was extra cloudy, and like we can't, you know, we can't do it on a cloudy day. And, and so the team was kinda debriefing, checking the weather, and and one of our safety culture rules is, like, no top management are in the safety briefs. It's the team making an independent go no go decision with no no nobody's senior putting their thumb in the scale and telling them they need to go and pressurizing So the team so I'm like in the hangar waiting, and the the team the team walks out, and I could just tell from the energy like it was go time. Like, nobody had to say anything.
Speaker 6:It's just like I see him walking over the airplane, they're like hooking up hooking it up to the hooking the tow bars up like we're gonna go. And at that moment, I I really teared up because I I knew I knew it was gonna happen. And then then then then then like when it actually happened, everybody was jumping up and down and screaming, I was sort of like, yeah, of course. So that was the I think that was the best moment. The worst moment, we have near death experiences like basically every year, and at this point I just expected, I'm like, okay, you know, every year we're gonna get the start up equivalent of a cancer diagnosis.
Speaker 6:And you know, if I'm lucky, it's stage two, not stage four. But you know, we we we've had like some like, we we like survived stage four startup cancer. We had an extremely difficult fundraise. I think we got down to a week of cash. Wow.
Speaker 6:Like, the lawyers had a plan to shut the company down. I remember calling one of our investors when we were sort of three weeks away, and he's like, usually when people tell me you're three weeks away, you're telling me you're gonna shut the company down. And I was like, of course, we're not shutting the company down. We're talking about how we get through this little knothole here. And, like, I'm gonna
Speaker 1:Who are like who have, like, twelve months of cash, and they're like, I'm out of this. I've been doing this for a year. I'm gonna go be a PM in Big Tech.
Speaker 6:Oh, I've I've done the PM at Big Tech. I don't ever wanna do that again.
Speaker 2:No. Think I'll never go back.
Speaker 1:You can never make me go back. No. Can't go back.
Speaker 2:The the thing the thing with your with for you and your team and I and I'm sure the entire cap table, it's like, if we don't do this, we have to be if we're not successful here, we're gonna be reminded multiple times a year
Speaker 1:Every time you multiple times.
Speaker 2:Like yeah. Every time you get on a plane, every time you you know, it like is one of the very few companies on earth that can bend reality into, into an, you know, bend time, right? And I, and I just think, I feel like humanity is fortunate that you are running this company because so many people would have gotten the stage four diagnosis and just said, alright, like, we we took a good shot, we did our best, and that's it.
Speaker 6:I mean Well, it's it's my biggest wish for other founders, is pick the startup where if you got the stage four diagnosis, you say, screw it. We're beating this.
Speaker 1:Mhmm.
Speaker 6:And that and that's that you know, for me, that's supersonic flight, but every for every founder, it's something different. Mhmm. But it's I think there's this founder market thing and if if or founder mission thing, and if you get that really in alignment, then, like like, then then then you can run through brick walls.
Speaker 1:Yeah. In many I would
Speaker 2:run through brick walls for a note taking app. I
Speaker 1:would too. The in in many ways, could think of boom as being a very logical, obvious next step in commercial aviation, long haul travel, that type of thing. Yeah. What about the flying car market? I've often said we have flying cars.
Speaker 1:They're just helicopters. But the problem with helicopters is that they're not evenly distributed. Not everyone has a helicopter. But if everyone had a helicopter on their house, they could fly to work. And, yeah, you need air traffic control and stuff.
Speaker 1:We don't need to be good pilots. But if a company could drop the cost of a helicopter by 100x and make it 100x safer, yeah, we'd probably basically say, yeah, we solve flying cars. And yet that hasn't happened. So what is your take on the boom of helicopters whether or the boom of flying cars or anything else in There
Speaker 6:are great people working on that, actually. And it's actually way harder than supersonic flight. Way harder. Why? But oh, zillion reasons.
Speaker 6:Like, one is you need a whole new set of regulations. Mhmm. Right? Because these the the electric vertical takeoff and landing, so Joby and Archer, who are really the two leaders in this
Speaker 1:Yeah.
Speaker 6:They're they're it's not technically or regulatorily a helicopter. So there's a whole new set of rules. They need a whole new set of infrastructure because you need
Speaker 1:to have a mistake. What what I'm saying is, like, is, like, what if what if I started a flying car company that was perfectly regulated as a helicopter? Just like, there there are these companies now that are regulated as Seagliders, Billy, Fallon,
Speaker 6:or Yeah. Yeah. Oh, yeah. Billy and Region
Speaker 1:are doing great work. Yeah. Like, a Yeah. Yeah. I'm sure you love it.
Speaker 1:Right? It's like legally a boat, but it's like a plane, but he has but he's designated in one way, so it's a lot easier. And I feel like there's almost like this regulatory arbitrage, regulatory hack that the hard tech founders might need to think through.
Speaker 6:So it's this is if the regulations were done well, your idea would be exactly on point. Mhmm. The problem is we have we have too many regulations that are prescriptive about exactly how something has to be done Sure. Rather than setting a safety bar or a noise bar. Right?
Speaker 6:And so and so, like, if you look at the regulations for helicopters, they tell you how you must build your helicopter.
Speaker 1:Okay. Yeah. So if
Speaker 6:you wanna build an electric helicopter with distributed rotors, well, it doesn't have the parts that the regulations tell you how to design. That makes sense. You know? Or, like, how do you treat know? Or that you're allowed to have, like, a wing on the thing too.
Speaker 6:So so that, like, the better helicopter is that doesn't fit the regulations for helicopters.
Speaker 1:Yep. Yep. So so, yeah, it'd almost be better
Speaker 6:to just bug in the regulations.
Speaker 1:Yeah. Almost just to regulate against, like like, if if flying things are crashing at a a rate above more than, like, one in a billion, it's no go. Doesn't matter how you build it, instead of saying Right. You have to have this this screw in this place.
Speaker 6:Right? That's that that that's right. And for actually for large transport aircraft, it's actually a bit better. Yeah. One in one in a billion is actually the regulatory safety bar.
Speaker 4:Yeah.
Speaker 6:And are and yet there are also still some things that are, like, prescriptive, but there's a there's a mechanism to get around the prescription called equivalent level of safety. So we can go to FAA and say and say, like, you know, you you say that our throttle has to be built in such and such and such a way, but the real thing is a reliable throttle. Let me show you my reliable throttle that's done differently. And you can get an equipment level of safety finding, you can go forwards. But the if you look at, like, going from a helicopter to an electric vertical takeoff and landing, you know, a flying car, Like like, the whole thing is different.
Speaker 6:Mhmm.
Speaker 2:What's your what's your timeline to eVTOLs being in American skies?
Speaker 1:Who wins? Who goes first? Will I be on a Boon SuperSonic or or a eVTOL?
Speaker 2:Yeah. I mean, just a just kind of a wild guess. Is it like before 2030? Seems unlikely to me. Is it is it 2040?
Speaker 2:Is it
Speaker 6:I I I I don't I feel uncomfortable speaking for other people's timelines. Yeah. That's bad. I think I think the technology is gonna be ready
Speaker 1:Yeah.
Speaker 6:Before the infrastructure and the regulatory environment are are laid flat. Yeah. The the the stated timelines for EV toll are like super near term.
Speaker 1:Yeah.
Speaker 6:And but I I suspect it's optimistic. I don't know. Yeah. And, I
Speaker 9:don't know.
Speaker 6:May maybe we've made the mistake of being more realistic, and and now it just sounds worse. You know? So our our timeline is 2029 Yeah. For being ready for the first passenger.
Speaker 1:I mean, there's also, like, incredible things happening in EVs haul that are unmanned. You look at what ZipLine's doing. We talked to the founder of ZipLine, we were blown away by the progress there. And that was one of the things where they had to go to another country to get favorable regulatory treatment and kind of figure things out, but then have really been able to accelerate.
Speaker 6:Yeah. I mean, Keller's crushing it. Like like, I love Zipline. It's crazy. Amazing founder, amazing company, great success story for how you do these things.
Speaker 6:The the they're they're brilliant. Keller is brilliant at, like, finding the first market
Speaker 1:Yep.
Speaker 6:That was, like, the the soft target. Yep. The the the small and uncrewed are radically easier Yeah. Than large and crude. And the and the the the reason for both is safety.
Speaker 6:If you go big
Speaker 1:Yep.
Speaker 6:Even if it's uncrewed, you have a problem because if the thing crashes, it can hurt somebody on the ground.
Speaker 1:Yep.
Speaker 6:Right? And so there there's a threshold, you know, somewhere around, I think, 55 pounds. Yep. Like above which, like, it's radically harder.
Speaker 1:Yep.
Speaker 6:And then if you put a human on board, like, obviously, you know, you don't wanna hurt anybody. And so and so in building x b one, like, the the the most surprising things were about, this were the second order effect of our our our choice, to put a human on board from day one and and not to have an ejection seat. Like, we we basically put everything on hard mode Mhmm. But we learned a lot more from that.
Speaker 1:Yeah. Is there is there an easy mode version of the boom story where you go to some country with lax regulations? You say, we're going uncrewed. We're going smaller. Maybe it's like a ISR reconnaissance application.
Speaker 1:You're only flying over the water, counting on fish or whales or something, and and it's just much easier to actually get flying on a routine start to fly whale like Zipline did.
Speaker 5:I mean,
Speaker 8:you could
Speaker 6:go you know, like, there are people doing kinda what you're describing that I think are smart, like Hermes. Hermes is smart.
Speaker 1:Yeah. Totally.
Speaker 6:And, you know, but what is what what is Hermes doing? They're they're basically building a hypersonic bomber.
Speaker 1:Yeah.
Speaker 6:And, you know, and it's kinda okay if the trips were one way. Sure. You know, and and yet and so I think they'll have a great business, and there are great people working on that. And I you know, I'm I'm cheering for them. They'll probably get to Mach five long before I get to Mach five.
Speaker 6:Yeah. But the, but doing that and then and then later putting a human on board is extremely difficult. Like, you look at the history of development of aircraft platforms, you find that defense technology makes it into commercial technology, but there are basically zero cases of a defense product becoming a commercial product. But the but the reverse is not true. There are many cases of commercial products becoming defense products.
Speaker 1:Yeah.
Speaker 6:So the the Boeing seven zero seven became the KC one thirty five. The seven sixty seven became the KC 46. The the the seven thirty seven is turned into a whole bunch of command and control airplanes and anti submarine airplanes. Mhmm. So the I think the reason is if when you're commercial, you have to worry about safety and you have to worry about noise, and neither of those things is retrofittable.
Speaker 6:Mhmm. They're actually foundational to product architecture. Mhmm. And so technology can go in either direction, but products go in one direction because safety and noise are fundamental to product architecture.
Speaker 1:You mentioned AJ at Hermes. When are we gonna see the foot race? I want the two founders of the supersonic companies to race each other to see who's faster in the real world on the ground, and then we'll race the planes in the sky.
Speaker 6:I mean, think AJ AJ and I have been telling each other the other one's gonna win the race. So I don't know. I think I think I think it'd be like the most, at least for me, it would be like the most pathetic race ever. I'm like I I am like not a runner at all. Well, we'll we'll
Speaker 2:Well, we'll do it as a pay per view. We'll raise some non dilutive capital. You guys can maybe split it
Speaker 1:based on Let's actually make it a little bit less about the running. Let's just do the Murph. Yeah. We'll do the Andrew and Murph together.
Speaker 2:Well, we're gonna hold you to being the first people to podcast Supersonic. Yep. I I would love to have you back on the show many times between now and then because this conversation has been extremely insightful, and, we are just grateful for the work that you and the team do.
Speaker 1:It's great. Thank you so much, Blake.
Speaker 6:That was so much fun. Thank you.
Speaker 1:We'll talk to you
Speaker 2:soon. Cheers.
Speaker 1:And in the meantime, we will tell you about public investing for those who take it seriously, multi asset investing, industry leading yields, trusted by millions.
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Speaker 2:Putting up the new pod four ultra.
Speaker 1:Pod five ultra.
Speaker 2:Pod five ultra.
Speaker 1:With a with a blanket with the same heating and cooling technology. You gotta pick it up.
Speaker 2:Can't wait
Speaker 5:to pick the blanket.
Speaker 1:Anyway, we got Tim Fist from, IFP in the studio. We remember he was here when we were under attack and all of Zoom
Speaker 2:That was devastating.
Speaker 1:That was devastating.
Speaker 2:An interesting conversation. We were technically
Speaker 1:Yeah. It was awful. So he's at the Institute for Progress. We'll bring him into the studio and talk, to him. How are doing, Tim?
Speaker 2:Welcome back.
Speaker 9:Good. Thanks for having me, guys. We made it.
Speaker 1:We made it. Thank you so much for for bearing with us.
Speaker 2:That was such a weird you know?
Speaker 1:It was weird.
Speaker 2:The first time a nation state
Speaker 1:We'll see
Speaker 2:what happens. Down TBP. Yeah.
Speaker 1:We start talking, and we get spicy, and all of a sudden the connection gets fuzzy. It might happen again. We don't know.
Speaker 9:Yeah. We had Tencent was pretty upset at the h 20 allegations. So prime suspect number one.
Speaker 1:Take us through the allegations again, break down what you guys published, and then we'll go through some of the the reaction and the fallout from the piece.
Speaker 9:Yeah. So I've got so much has happened since this was in the news. It feels like there's five different things in export controls that have gone on since. Yeah. But, yeah, basically, this was the h 20 inference chip from NVIDIA, which some might remember was designed to be compliant with the export controls.
Speaker 9:So is this the chip they sold about reportedly 1,000,000 of them into China in 2024. And, yeah, there was a lot of outcry at the time for the Bureau of Industry and Security who's, you know, the part of government that administers and enforces export controls to do something about this because, you know, 2024 was the period where everyone realized that inference compute was perhaps, you know, the most important strategic input to frontier AI development because of, you know, test time compute scaling, reinforcement learning, and synthetic data generation is the key things. And, yeah, you know, earlier this year, there was reporting that, you know, NVIDIA had a huge number of additional sales plan to, like, big Chinese companies. And a bunch of people, including us, sort of said, hey. Is this really what we wanna be doing?
Speaker 9:Do we would want to sort of allow, you know, China to get access to millions more of these chips? And, yeah, the government ended up taking action on this and issued some guidance, basically saying, hey. No. You can't make these sales. NVIDIA reportedly was left holding the bag to the tune of about 5,500,000,000.0.
Speaker 9:Yeah. And now, you know, since then, we've seen
Speaker 2:for ants for NVIDIA. It's barely a flesh wound.
Speaker 1:Well, they made up for it with deals in Saudi Arabia. Right?
Speaker 9:Yeah. Indeed. Yeah. So that that's the new thing. Right?
Speaker 9:It's the administration, walking back on the diffusion rule, the speaking framework, and then the series of deals that have been announced, over in The Gulf.
Speaker 1:And yeah. And what's your reaction to the diffusion rule and the deals in Saudi Arabia? Is this a step forward? Are you excited about this? Is this positive news?
Speaker 9:Yeah. So it really depends on the details of all this. So I think on the deals, I guess, fundamentally, you know, what do we want? We need The US AI tech stack to Yep. Win the global competition against China.
Speaker 9:And I think a big part of that is locking in these early adopters and big spenders, especially like The United Arab Emirates. But I think we need to be thinking about how to structure deals like this to sort of get The US the outcomes at once, which is, you know, US tech diffusion, the concern kind of, like, Chinese tech stack locked out in a way that, you know, we couldn't handle with five g, like, won sort of, like, the five g battle globally. And then appropriate national security guardrails in place. Yeah. And it's pretty unclear, like, what the trade offs that have been made for this deal are.
Speaker 9:So I think, like, the high level specs that we've gotten is a five gigawatt AI data center campus to be deployed over some time period in Abu Dhabi, and then reports of 500,000 chips per year to be exported with maybe four fifth of those for US firms who are building data centers over there and one fifth for g forty two, this big tech conglomerate in The UAE. And kind of depending on how quickly that all happens and whether they're referring to, you know, a hundred thousand of today's chips or a hundred thousand of, like, chips in, you know, five years time, this could be the difference between, you know, one x to a hundred x in terms of, like, different differential in compute. So, yeah, I think that really makes the difference. And I think the key question here is, you know, do we want an AI lab in, you know, an authoritarian country to have the biggest clusters or close to the biggest clusters in the world? And, you know, this is a country that does collaborate with China in areas like drones and five g and military technologies.
Speaker 9:And so you need to sort of be careful with giving them access to sort of frontier scale compute here.
Speaker 1:Yeah. Yeah. So there's kind of like a huge Can
Speaker 6:you talk about
Speaker 2:I'm curious if you have insight on capital flows from The UAE and Saudi into Chinese AI. How how much investment activity is there? Do have any insight?
Speaker 9:I don't have stats on this. I suppose the interesting thing to say on this, you guys might remember there was this $1,500,000,000 deal between Microsoft and g forty two a couple of years ago that's not on this stuff. So this was essentially, you know, Microsoft making investment in the g forty two and starting to build data centers in collaboration with them. And Department of Commerce got really involved in this, and part one of their requirements was to divest from Chinese companies in the kind of AI stack for g forty two, which is, you know, this huge tech conglomerate that is funded through the nation's sovereign wealth fund, which is the second largest in the world. So pretty serious money.
Speaker 9:We're talking trillions of dollars. And, yeah, reportedly, what they did is they had a bunch of passive investments in Chinese companies, including, you know, hyperscalers and AI companies. And, reportedly, g forty two did divest from those companies, but then basically moved the investments over to another fund called Lunate that was sort of also owned by this, you know, big sprawling tech conglomerate that's ultimately funded by, you know, the sovereign wealth fund. So the big question marks about how much are they actually decoupling from China and, like, how costly is this to them? Like, are they actually burning bridges that are hard to reverse?
Speaker 1:Yeah. There's some element of, like, we have a smooth gradient of friendship with different countries. Obviously, there's the five eyes, like the closest allies. We sell nuclear submarines to some countries. Mhmm.
Speaker 1:But then there's countries that are more jump balls and could go either way. As the diffusion rule goes away, do we need firmer rules around, hey. We're willing to sell to you, but don't immediately set up a reseller and start selling just passing these on to China because you could imagine if the natural economic forces take hold, and I was in some country that was just about to get 500,000 chips, it's pretty easy to just immediately start reselling these if I and and just print money, basically.
Speaker 9:Yeah. And there's there's kind of two ways to do that. Right? One is you can just unsell the chips, so you kind of smuggle them into China. And the other way that's pretty straightforward is set up your own data center and rent it out as cloud
Speaker 1:compute. Exactly.
Speaker 9:So, yeah, I think that's what you're referring to. And, yeah, currently, there's not great guardrails around either of those things. And I think the administration wants to set up better versions of this. Sure. But, yeah, I think this needs to be part where there's sort of, like, countries that are really willing to, you know, buy hundreds of thousands to millions of chips.
Speaker 9:You kind of want these structured deals that have these guardrails in place, and I think the Trump administration is really really well positioned to strike these kind of smart bespoke deals that get us the right possible outcome across each of these dimensions. And, hopefully, that's what they're pursuing.
Speaker 2:Yeah. Can we talk about the news today, or maybe it came out late yesterday, that NVIDIA to set up research center in Shanghai, maintaining foothold in China. Basically, they're they're opening this r and d center in a as almost like an olive branch to China is kind of how I would describe it. They they say they're gonna use it to understand Chinese customer demands and design US compliant products. And they're basically doing this to just kind of navigate sorry.
Speaker 2:Navigate export controls and compete with companies like Huawei. This, to me I mean, there's so much to unpack here. I'm I'm I'd love your kind of initial take, and then I wanna kind of maybe move more high level. And to me, this signals that that maybe Jensen doesn't take national national security concerns about, like, an AI war as seriously as even some of the US Foundation model labs talk about it.
Speaker 9:Yeah. I'd say that's an accurate assessment, and, you know, I think it's really hard to design, you know, sanctions, export controls, like these kinds of things in a way that it's not that sort of can't easily be escaped from. But it's kind of like the spirit of the rule in that, like, hey. We're worried about China, you know, beating The U N US in, like, the most strategically important technology of this century, and we don't want you selling to them. But then, you know, you can do all these addition you can do all these things to sort of, like, actually be cooperating around the scenes, like design compliance chips or whatever.
Speaker 9:And to be fair to NVIDIA, know, like, I think they say, you look look, if the if the speed limit is 60 and we're going 55, like, we're not breaking the law. Like, we should be allowed to do this. And if you think, like, the strategic perspective for them is also a lot of their customers are, like, these big US hyperscalers. Right? Mhmm.
Speaker 9:And all of these hyperscalers are developing their own custom silicon. So, you know, we know Google has their TPU, you know, that they use for both training and inference. We know Amazon has, like, training and Inferentia that they're also using for training and inference. Microsoft is developing their own stack. And so, you know, huge source of revenue for NVIDIA is potentially at risk.
Speaker 9:So it kind of makes sense for them to wanna be, you know, diversifying to other parts of the world and not just be selling to US hyperscalers. So they're certainly in, like, a difficult position overall. And, yeah, what you think is right here depends really on how much you buy this kind of argument that, hey. Over the next five years, AI as a technology that will, like, reshape the global balance of economic and military power is a thing and will be a really big deal.
Speaker 1:Yep. It seems like the speed limit is getting lower and lower, though. Mhmm. We went from the h 100 to the h 20. Now NVIDIA is preparing to release a modified version of the h 20 chip for the Chinese market after your piece and the changes to the h 20 restrictions.
Speaker 1:Is there a point where the restrictions are so are so onerous that no one wants to buy a car that goes nine miles an hour. You know? And at a certain point, NVIDIA will just lose the market share because, Huawei Ascend chips will just be outperforming. Are you tracking any of that?
Speaker 9:Yeah. So here, it becomes an interesting conversation. I I think the kind of crux of the matter is if, you know, Huawei has better chips than NVIDIA in the Chinese market and is able to sort of capture that market, How bad is that? Like, should we sort of set export controls such that NVIDIA is always slightly ahead of Hawaii, for example, and sort of, like, raise those limits over time? Mhmm.
Speaker 9:And here, I think there's two sort of dimensions to it. One is that, know, in AI, the quality of the chips matter, so how sort of individually performing each chip is, but also the quantity really matters. So, you know, you can have a million chips each that are, you know, like, half as good and sort of, like, substitute for, like, 500,000 chips, for example. And so, you know, this is a crude approximation, but you both want the sort of best chips and as many of them as possible. And where we're trying to squeeze China, like, we being, like, the US government is across this whole supply chain.
Speaker 9:So not just on, you know, being out of procure chips directly, but also being able to manufacture their own. So having, like, the semiconductor manufacturing equipment and the fabs and everything there. And so I think the goal of the US government has to be re really to restrict the quantity of AI chips that China, so, like, SMIC and Huawei is, like, the key firms here are able to produce. And so by this logic, you know, even if, you know, you, NVIDIA has a chip that's only slightly better or slightly worse than Huawei's, you still might wanna restrict it because you would prefer them not to have access to 10 times as many chips than they otherwise would have. Like, you don't want them to have access to essentially, like, know, TSMC's production capacity of, like, being able to do many, many millions more chips than you could otherwise produce.
Speaker 9:So I think, yeah, these are, like, hard trade offs to make. I think where it really matters is in foreign availability. I think, you know Mhmm. Where Huawei is accessing foreign markets and outperforming US chips, that's really bad. And we should sort of make sure that that is not the case and is you know, it is US chips that are being used globally in countries that aren't China.
Speaker 2:Yeah. Do you think Huawei will ever go public, or do they not want people to know they they want people to know as little about their business as possible?
Speaker 9:Yeah. I'm clear. It depends what the CCP wants. And it's inversely gonna take organization.
Speaker 1:Yeah. Interesting. What is your take on open source AI? We were talking to Aaron Ginn about this idea that, if America does not provide a state of the art, open source stack to countries that wanna build their own AI products off on top of fine tuned or post trained LLMs that meet their definition of, free speech or or ideals or morals. The stack by default will be Huawei Ascend, DeepSeek, Manus.
Speaker 9:Mhmm. Yeah. I totally buy this. I think that being able to sort of have the best open source models in the world be American is really important for similar reasons as, like, the chip stack and the data centers and the cloud services. I think there's a question about how sticky is this ecosystem actually.
Speaker 9:So you talk to people who are like, yeah. We really need to, like, lock in the tech stack globally. Like, American open source models need to be sort of like the rails that the world runs on. But then if you look at sort of how AI developers work, they are very happy to switch between different base models for their application depending on which happens to be the best. You know, you look at, like, the revenue of Frontier Labs and, you know, when they have the best model, it's up here or when they're doing it down here.
Speaker 9:Like, everyone is switching every day depending on, like, you had who has the best model. So it's yeah. Like, you wanna diffuse American open source is why this is possible, but, like, what about it makes it sticky? And my hypothesis would be that it's probably the secure security and reliability side of things. Reliability side of things.
Speaker 9:Mhmm. So, you know, everyone's worried about, you know, the fact that you can insert, like, backdoors to create sleeper agents into open source models, and there's no way to actually detect these. I think, you know, The US wins if it can prove that it has the most trustworthy and reliable models over China, similar to how I think US cloud computing companies compete over, you know, Huawei and Alibaba cloud. Like, often, and Alibaba are coming to the market with a cheaper option, but The US is just more trustworthy in terms of, you know, data privacy, security, etcetera. So I think trying to figure out those technical problems around security, reliability, interpretability, and sort of proving that US models win across those dimensions is probably the way to make the kind of open source models from The US more sticky or just sort of be way better.
Speaker 9:And, you know, this is where of most of the effort is currently going and definitely support those efforts as well, like, you know, building up more domestic compute, for example, and, like, finding more training datasets.
Speaker 1:Yeah. How do you think about the dynamic between the importance of the application layer versus the foundation model layer? We've seen efforts on the foundation model layer at the national level all over the place, but let's just use Mistral as an example. Mistral has a consumer app called Le Chat. Mhmm.
Speaker 1:It is a direct competitor to ChatGPT. And I think that's great for the French, and they could potentially have a fine tuned model that meets their standards and guidelines. But if at the end of the day, the French consumers, 90% of them are using Google and 90% of them use OpenAI, well, then all of that is kind of worthless. And, sure, maybe Mysteral will be cheaper in the enterprise and be implemented in French businesses or European businesses, but in terms of, like, control of the population, that feels like the diffusion of American ideals in Europe, which doesn't seem extremely controversial because American and European ideal or or ideals are pretty similar, but you can see how this would play out in other countries.
Speaker 9:Yeah. Totally. And the economics are pretty brutal here. Right? Like, we're in a regime where the amount of compute being used to train a model goes up five x every single year.
Speaker 9:Yep. We're moving from, you know, a hundred million dollars to train a model, you know, last year to rapidly approaching the billions. If you are a company committing to this and you're only sort of just slightly better or worse than, you know, one of these huge tech companies, you can't keep sustaining this over time. You have to you have to check you have to check out eventually.
Speaker 1:Yeah. And we've seen that with a lot of the early stage foundation model companies that have raised, trained something, but never been on the frontier, and now they're, you know, falling out of favor more or less.
Speaker 9:Yeah. Totally.
Speaker 2:Interesting. Has there been any conversation on the on the ground in DC, or have you heard any chatter around the Manus investment that that definitely kicked the that Benchmark made, kicked the hornet's nest a little bit in the hornet's nest of American Dynamis.
Speaker 1:A little deli in Asperuov, it's Irishman.
Speaker 2:But but to to give Benchmark a little bit of credit, you you if you're gonna be mad at Benchmark for making investment in Manus, you also in some ways I think have to be mad at Jensen for going up and setting up a research and design, you know, r and d center in Shanghai Right now? Explicitly to work on developing products for the Chinese AI ecosystem and in some way direct the CCP directly.
Speaker 9:Yeah. Yeah. I it's a bit hard to evaluate. I think, you know, one, you know, the one of The US advantages is, like, very deep capital markets. Right?
Speaker 9:And so being able to exert financial control over setups overseas by sort of, like, acquiring stakes is potentially a way to, you know, have you sort of a better sort of fairer sort of more aligned, like, global system overall. I think this is high when it comes to Chinese companies.
Speaker 2:But does America benefit from having American capital allocators in ByteDance? I don't think we have much
Speaker 9:Yeah.
Speaker 2:Influence or control over what ByteDance does.
Speaker 9:Yeah. Exactly. So I think for big companies, especially those that are part of this, you know, Chinese sort of state industrial military complex, this is a pretty poor prospect. This is why, you know, the treasury department has outbound investment restrictions in a bunch of different industries, which have been expanded to AI over time relatively slowly, though. So, yeah, one one thing that they've been sort of working on is trying to figure out whether to apply these outbound investment restrictions more solidly to commercial AI developers and commercial AI cluster operators.
Speaker 9:Like so, like, in investments coming from VCs actually restricting investments of those kinds into China. And, yeah, this is complicated by the fact that just, like, due diligence is really hard. Like, let's say you're investing into an application developer who's doing something pretty innocuous, like, you know, automated code agents or, you know, search or something along these lines. You don't have any get control over it. You know?
Speaker 9:Are they going to work with the Chinese military in the future? Are they going to be sort of, like, an instrument of state backed surveillance over the local population? They're not gonna tell you that. They might not not have plans to do that, but they can certainly be compelled to do that in the future. So the due diligence question is super hard.
Speaker 1:Do you think regulators or the American government needs to be thinking about the pretraining scaling law potentially not holding or reaching some sort of diminishing marginal return. We've seen the data from GPT 4.5. It feels like, GPT five might not just be a hundred x bigger than GPT 4.5. It might actually be some sort of mixture of experts, different models, and more of almost like a product challenge than just a scaling and just get the more chips challenge. At the same time, OpenAI is also investing in in Stargate, and and there's still a drumbeat of ever larger data centers in The United States.
Speaker 1:But, the the overall tone of of AI research labs in America seems to have shifted away from just the ever bigger transformer. And there seems to be a somewhat of a resignation to this idea that there might be more challenges on the path to ASI than merely scaling up the architecture that we have right now?
Speaker 9:Yeah. I think there's a few things here. One is that, you know, obviously, these companies are still making huge investments in clusters and energy to get to the next order of magnitude of scale. So there's some level of just, you know, financial buy in to the idea that, you know, pretraining scaling will continue, but also a recognition that, you know, we've got this other scaling law, this sort of test time compute scaling law, and now, like, reinforcement learning as a paradigm that seems to really be working for language models where a lot of companies are starting to put more of their compute resources overall. So I think the rough balance now seems to be around sort of eighty, twenty pre training compute and then post training.
Speaker 9:Mhmm. And I expect what we might see as we see sort of, you know, companies who are building out these clusters and these energy sources to support them, where are they going to sort of, like, balance the compute allocation across those. The calculus seems to be that, yeah, pretraining compute is relatively less promising than before and putting more of your resources in a relative sense into RL, which is sort of but very much at kind of, like, the early stages of scaling up is the better strategy at the moment.
Speaker 1:Yeah. I mean, the the other side of this is, like, as even even beyond post training and RL as reasoning tokens and just more test time compute, more inference cost increases, maybe the real way to get a GDP boost or a competitive advantage out of AI is just to make sure that there is an h 100 or equivalent for every member of your society or every every citizen because everyone will need to be inferencing at a very high level, very large model, basically constantly. And so even if you've trained the greatest model, if you can't have every single one of your citizens constantly inferencing it all day long, you're not gonna see the benefits of
Speaker 9:the need
Speaker 2:to know. AI companion constantly on.
Speaker 1:I mean, we do need we do need, you know, code gen, and we need research, and we need answers. And if we're if we're timing out, it's not just Well, code
Speaker 2:and deep research are gonna be competing with the AI companions for inference. Yeah. Probably.
Speaker 9:Yeah. But yeah. Just to, I guess, maybe push back on
Speaker 1:Please.
Speaker 9:Maybe hypothesis underlying that. I am very confused about where most of the compute is going to be spent and how that is going to be distributed across people. So I can easily imagine a world, like, in two years where most people in the world still aren't really using simple tools like ChatGPT. Like, you know, my grandma still, like, never heard of And but at the same time, you have some companies at the frontier who are deploying millions to billions of agents internally. So you had this really, like, unequally distributed use of compute overall.
Speaker 9:Yeah. So, yeah, I I kind of buy the idea that there'll be just, like, massively uneven sort of, like, usage of these kinds of resources and, like, really, like, located in particular countries and within particular companies.
Speaker 1:Yes. Agree in the sum total of the importance of inference and compute allocated and available for inference, but potentially disagree on the distribution of that. And I I I think now that you now that you hash that out, I think that makes a lot of sense. You already see that just in the prosumer versus consumer market. I'm probably kicking off, like, three to five deep research reports using a lot of tokens.
Speaker 1:I'm getting my $200 worth, and there's a lot of people that are, you know, just land on it every once in a while to toy around with it. That makes a ton of sense. What what's next, Jordy? What should we talk about?
Speaker 2:How have you guys had success explaining the potential for AI, you know, AI's potential progress in the next few years in in Washington broadly? Do you feel like lawmakers have fully kind of fully understand the potential? Right? Nobody has a crystal ball. We can't predict the future, but if you sort of extrapolate trends and even just use the products today, do you feel like do you feel like Washington is is pricing it in, or is it still you know, or or are people gonna be, you know, extremely surprised in the next few years?
Speaker 9:Yeah. My bet is 100% extremely surprised. I am, I think, consistently disappointed with how the lack of kind of level of AGI killed people in DCR, even with sort of, like, current capabilities and, like, where the sort of trend is obviously going. I think, like, there's a lot that just isn't being priced in about kind of how weird the world is, you know, in five years time. There's also, I think, a sense of which, you know, there's a real loss here in that if you look at technologies like the Internet, which, you know, as you probably know, like, came from up in it, like this with this, like, DARPA funded project, as well as, you know, early sort of genomics with the human genome project.
Speaker 9:These were technologies where the government sort of saw what was coming and took sort of a really active role in shaping the development of the technology through basic r and d. So with ARPANET, for example, the focus was really on creating, you know, a resilient network system that could survive a nuclear bomb, But, also, they sort of, like they were able to take that sort of secure network infrastructure and apply the notion of kind of, like, openness and freedom of information to create, like, a scaled global network that really represented American values and was, like, very secure. We don't see, like, an equivalent kind of level of basic r and d investment in The United States around AI, and that would be really cool to see because it's basically a bunch of problems where, you know, right now, industry is focused on where the money is, which is, you know, b to b SaaS apps and chatbots. But there's, like, a huge space of just, like if you accept that over the next few years, we'll have these incredible new AI capabilities. There's all these massive important societal and scientific problems in areas like, you know, materials discovery, drug discovery, etcetera, where the government could be placing essentially huge bets that could pay off, you know, within a few years, and we're kind of not doing that because we're sort of DC at least failing to see sort of where the future is going and therefore what the role for this kind of basic r and d is.
Speaker 9:So, yeah, I'm there's a congressional coalition that's just started called the American Science Acceleration Project, which we're really excited about and try to build hype around. But then I think I have the right the right idea around this. But, you know, there's a deficit of this kind of thinking in DC at the moment.
Speaker 1:Last question for me. How has Meta's reputation changed in DC over the last few years? Famously, Zuck goes to Capitol Hill. They don't even understand how his business model works. He says, senator, we sell ads.
Speaker 1:He was castigated for being too left than too right and, very a lot of political hot button issues around the Facebook app and the type of content it's servicing. Obviously, a big vibe shift there. But now it seems like Meta is increasingly a very important tool in the American foreign diplomacy AI tool chest with LAMA. LAMA is, of course, in their open source model that's, you know there's defense LAMA now. The DOD is partnered with NEDA on this, and yet, today, we learned that their behemoth model is struggling to improve capabilities.
Speaker 1:They're facing setbacks. Has the has the tune changed in DC to say, hey, Zac. Like, sell more ads, please. Like, do more stuff. We gotta we gotta get you pumping because, like, you're a national champion now.
Speaker 9:Yeah. I'd say, like, by and large, you know, there's there's different factions in DC who care about different things. Obviously, sort of Meta is going through this big, like, antitrust case at the moment as well. Yeah. Like, it has been going through it.
Speaker 9:Yeah. On the AI side, I guess, it's interesting as well. Like, Meta is very much seen as kind of like the darling of, you know, open source Mhmm. Supremacy for The US. I think it's kind of awkward for a lot of meta fans to see see the latest batch of models and then really not be that impressive and also potentially a bit of gaming with leaderboards and sort of what models they're releasing there.
Speaker 9:Obviously, they've executed the strategic pivot to appeal to the current administration with, you know, getting rid of fact checking and bringing in, like, the community notes type approach, and that seems to have been pretty effective. But, yeah, I think they've certainly got a lot of backers here. Yeah. And the open source approach, it's, like, really good to have, like, a really well capitalized company, like, really, like, pursuing the strategy overall. But, yeah, I think they're copying a bit of heat for not actually delivering on the promise to some extent.
Speaker 9:And, also, people there's sort like, another faction that's pretty worried about open source models with capabilities that could be significantly misused, especially in the cyber domain being, like, freely available to the whole world. But that's less less of a concern while they're behind.
Speaker 1:Yeah. It was very interesting in the in the in the press release around this in the in the the management of the the news that they were delaying the rollout. They didn't say, oh, it's it's too dangerous to release. They could have easily said that. That's always an easy out for the AI labs to say, it's just too good.
Speaker 1:Trust us. We we we we we can't trust you with it. We're we're doing more safety research. Instead, it seems like there's a little bit of an admission that, it's just not at the level we want it to be.
Speaker 2:Jordy? This might be out of scope for you, but do you think that AI is our is at a much is being used in nefarious ways in the context of social engineering attacks at a greater scale than people sort of realize today? This was top of mind just due to the the Coinbase news this week, the leak that they had. And I think people broadly, anecdotally reported that they just felt like they had a huge uptick in like sort of inbound calls or and social engineering attacks. My my question is is AI is already when you're using tools like Sesame and and some of these lower you know, Sesame is obviously state of the art, but even some of these lower latency video models should already be capable at and more better at social engineering attacks than, a PhD level person globally that that even even if English wasn't their first language Totally.
Speaker 2:And and and and you know. So anyways, I I'm curious if you have
Speaker 1:Cybersecurity, social engineering
Speaker 2:Any sort of like insights there? Regulation around it.
Speaker 9:Yeah. No insights into the true extent. I would note that it is surprising to me that we don't seem to see more of this. My impression is that from sort of GBT 3.5 onwards, we've had LLMs that
Speaker 1:can
Speaker 9:produce better text, more convincing text than the kind of median phishing email, which, as you know, is often, like, pretty poorly written. Maybe that's deliberate. But, yeah, like, it's kind of weird to me that we haven't seen mass sort of spear phishing campaigns of the kind that have been possible for, like, several years now yet, or at least they haven't been widely reported. Maybe it's the, yeah, existing sort of filters and defensive approaches work. Maybe, like, we shouldn't expect actually that be that many people who are trying to pick this low hanging fruit.
Speaker 9:They're not technically sophisticated enough. Or maybe it's like it's like happening and not being reported on. But, yeah, I find that it's
Speaker 2:I think there's potential that it's happening, but it's happening to a demographic that doesn't even know it's happening. Right? Like, I don't pick up random calls. Right? I just don't I'm not gonna answer the
Speaker 1:know of. Maybe the last time I called you, it was actually a bot.
Speaker 2:Yeah. That's That's true, John.
Speaker 1:You do pick up non random calls, but that's the point of them. Yeah. I mean, the same thing happened with the crypto stuff. Like, there were a lot of the victims of cryptocurrency scams, like, weren't profiled in the New York Times. And so we just didn't really hear about them because, like, people that with the loudest microphones didn't fall for the scams.
Speaker 1:Yeah. Tricky. Anyway, thank you so much for joining, Tim. This was fantastic. I'm glad we survived the attacks from the nation state actors that don't want us to gap We kept the
Speaker 2:stream up.
Speaker 1:A stream together. We really appreciate it. We'd love to have you back, and this was fantastic. Yeah.
Speaker 9:Thanks for coming on. We'll talk soon.
Speaker 2:Have a great weekend.
Speaker 1:Next up, we're bringing Chris Best from Substack. But first, let me tell you about Adquick. Adquick dot com. Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising.
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Speaker 8:Doing good. That jingle is unstoppable.
Speaker 2:Unstoppable. We gotta get a jingle for Substack. What's the Substack jingle?
Speaker 1:What? Do you have a tagline? What what what's your what's your landing page hero hero text?
Speaker 2:The app for independent voices.
Speaker 1:There we go. Same same same melody.
Speaker 8:I go with take take back your minds. Take back your minds.
Speaker 1:Take your minds. Okay.
Speaker 2:Take back your minds.
Speaker 8:Yeah. With that of a jingle.
Speaker 1:How is the process of taking back minds going?
Speaker 8:It's going pretty well. Okay. Can't complain. Yeah. Across 5,000,000 paid subscriptions.
Speaker 8:Wow. That's a lot. Wow. Awesome. Apps blown ahead of,
Speaker 1:I think, all of the, like,
Speaker 8:legacy media apps combined.
Speaker 1:Amazing. Chris and I were in the same YC batch. Winter eighteen.
Speaker 2:Another one.
Speaker 5:Another one.
Speaker 2:So so my biggest thing with John is is it's actually probably good. If John had just invested in in in his batch, he would have been too post economic to start a podcast, and we wouldn't be here.
Speaker 1:It's like Coinbase, Instacart, Zapier, Even what was the other one? The the the crypto exchange that absolutely ripped the NFT marketplace. OpenSub was in RBC.
Speaker 8:You know? Fanta, Replid.
Speaker 1:Yeah. Yeah. Yeah. Yeah. Remarkable companies.
Speaker 1:Those are good times. So, yeah, I mean, take me through the the the history and evolution of Substack and where you're going next. Next?
Speaker 8:Yeah. I mean, we started we were in winter winter twenty eighteen together. Yeah. The basic theory is we're building a new economic engine for culture. Mhmm.
Speaker 8:You know, we wanna harness the power of technology, the power of world's, you know, Internet scale networks combined with a business model that actually powers independence.
Speaker 1:Mhmm.
Speaker 8:The version of that the simple version of that that we started with is basically make it dead simple to do a paid email newsletter. Mhmm. But as the years have gone by, we've grown that into multi format. You can do you could write, you can do a podcast, you can do live video. Yep.
Speaker 8:We've got this network and this app. You can get the Substack app from the App Store and discover this whole universe of the smartest, best independent media and culture on the Internet. And that's what we're building next, basically. I mean, I'm we're building a bunch of video tools. We've got this live, you know, live tool that lets you do something that feels like a FaceTime call and then AI magically turns it into like a produced podcast and series of clips.
Speaker 8:So if not everybody is the brilliant, you know, YouTube sensations that you guys are, if you're just someone that has something to say Yeah. We make it dead easy.
Speaker 1:That's very cool.
Speaker 2:Super
Speaker 1:power. Was Ben Thompson really an inspiration? He kind of tells that story. I don't know if that's true that Sir Techery and he kind of pioneered this like independent newsletter creator really scaled the business. But had you been reading him at the time?
Speaker 1:Had you taken lessons away from Strathecari when you built Substack?
Speaker 8:Yeah, I do. There was a few people doing it, right? Was like because we had this cockamamie scheme where like, hey, bet you people would subscribe to, you know, things they deeply value if if if you had something great. Mhmm. And there was a handful of people that were doing it.
Speaker 8:Mhmm. You know, Andrew Sullivan did this with kind of like the Daily Dish back in the day. Oh, yeah. Ben Thompson had Stratakuri. And here's this guy, you know, writing a email newsletter from his bedroom in Taiwan making, by our calculations, millions of dollars a year.
Speaker 1:Yeah.
Speaker 8:We're like, you know, that that sounds pretty sweet. Like, why does why do more people not do that, basically?
Speaker 1:Yeah.
Speaker 8:And, you know, the answer to that had to be turned out to be, it's way too hard. So what if we made it way easier?
Speaker 1:Yeah. I mean, he's he's he's invested immensely in technology to build up passport and what he's done, and now there's a few other companies that run on it. But, yeah, where does this all go? I mean, I guess the big question is, like, ads product, you know, is is tied to the written media. Wall Street Journal has subscriptions and ads.
Speaker 1:New York Times has subscriptions. And even after you subscribe, you still get ads. We are an ad powered show. Ads feel very, they get a lot of negative attention, a lot of negative stated preferences, but the revealed preference is almost always people don't mind ads and scroll right past them on Instagram and sometimes even get value from them. We've been very pro ads, but what has your, take been on ads generally in, in the Substack world?
Speaker 8:The thing that's actually different about Substack
Speaker 1:Mhmm.
Speaker 8:Is kind of creator ownership and a model that rewards quality and value. Mhmm. So the fact on Substack that you you know, people don't subscribe to Substack. They subscribe to you. Yep.
Speaker 8:You know, you can make you if you make something truly great and it well, Bones, you will value it, they come. All those things are what actually sets Substack apart. You know, the formats are are similar to what you see elsewhere. You get you can you can write a long form article. You can write make a podcast.
Speaker 8:You can do a video. Like, those are those are not novel things. The thing that's novel is this business model that powers independence. The fact that you own the you know, it's your business. You're getting the upside.
Speaker 8:You want to invest in the quality. And I think there are methods of doing sponsorships and advertising that are that that that work with that. Mhmm. Right? The fact that people, you know, people are paying premium for you guys to advertise on this program Mhmm.
Speaker 8:Not because you're getting like the most clicks ever that gets sold at a market, like at some market rate for the demographic, but because you're making something special and you have tremendous, you know, jingle skills. But the the audience is like is is magical. Anyway, there are a bunch of people today, we're doing all subscription. We're powering that thing. That actually works really well, shockingly well, much better than people thought it was gonna work.
Speaker 8:People are consistently surprised by how well that business model can work for them. But there are also people on Substack who are doing sponsorships and doing tremendously well. Yeah. And so I do think that model can and should coexist with high quality media endeavors.
Speaker 1:Do you believe the medium is the message? We we we've kind of felt this where we decided to go live for somewhat of a, like, a technical reason, just that the way YouTube's organized, it kind of made things easier. But then once we were live, we realized, well, we're faster. We're not there's no delay between us recording and uploading. And so we can react to the news.
Speaker 1:We could we could open up x right now and and read a headline that just dropped with you and get your reaction, and it's kinda changed the nature of the show. What's even your, processing of, the McLuhan ideology?
Speaker 8:I'm a huge believer in live for that exact reason. Know, we're building this video product that you that is live within Substack. Yeah. And I think it's almost like a hack that sets the social expectation. The fact that you're gonna be able to sit down, make this thing, ship it off.
Speaker 8:It's not necessarily the case that the majority of the audience is gonna watch live.
Speaker 1:Totally.
Speaker 8:It's great that those of you are here, but it's, you know, it's gonna be there's gonna be a VOD. There's gonna be clips. Those might be the places that actually get the distribution. But as a hack to make the thing, the fact that the, you know, the social expectation between us right now is we're sitting down having a live conversation makes it easier, makes it faster. It does feel different.
Speaker 8:Like, don't know if you have this, I feel, you know, feeling of being live is a little bit more energizing than than otherwise.
Speaker 1:Definitely. And then also it just builds I mean, we we we like it because it builds trust with you. Like, yes, there will be clips, but we're not gonna edit we can't edit out what you're So if you wanna make your case in some way, we can't be like, oh, we didn't wanna put that in. Know?
Speaker 8:Yeah. Could I could go back to the tape and say, well, here's here's the full context.
Speaker 1:Right. Exactly. Exactly. It's always there.
Speaker 2:Can you talk about this? So so one, I I want your help kind of framing something because there there's in my mind, there's this stages of of substack. Right? Like our audience, at least the initial core audience is this sort of like terminally online x, you know, tech enthusiast.
Speaker 1:Genius, wealthy. That that that's a core audience. But yeah. Average net worth is You could say terminally online too.
Speaker 2:Know Yeah. 20 to, you know
Speaker 1:Goated. Definitely. Or like in the conversation.
Speaker 2:Definitely in the conversation. No. But but to me there's been these stages of Substack where like, I don't know if it was like a year ago at this point that I noticed that Substack had not become a household name, but it had been becomes Outside
Speaker 1:of tech.
Speaker 2:Outside of tech.
Speaker 1:Emily Oster, for example.
Speaker 2:But had just become something that that kids I went to college with that aren't in tech were Yep. Subscribed to probably three substacks. Yeah. And it was like part of that
Speaker 1:It wasn't just all like was part
Speaker 2:of the corner fans. Like clearly part of popular
Speaker 1:Totally.
Speaker 2:Culture online. Yeah. Yeah. Which one would be Was there a note Was there a moment? Is that like the wrong analysis and I just wasn't paying attention outside of our bubble?
Speaker 2:Or did you feel something like that too?
Speaker 8:I get this question a lot, and I think people because it kinda grows in pockets. Right? Like, it'll be there'll be, you know, this bunch of crypto people that all join at the same time, or a bunch of politics people, or a bunch of finance. Like, there's sort of like these you know, next adjacent market pockets as it grows. Mhmm.
Speaker 8:And so all along, there's I've sort of had people ask me this, but like, it feels like Substack is suddenly blowing up.
Speaker 1:Like, what
Speaker 8:does that feel like? Has your life changed? And internally, like, it's just been growing really consistently, really steadily. Like, the curve just looks like a steady exponential curve. And so it is kind of always true.
Speaker 8:Like, this is this is the most exciting time. I have had I've you know, I do feel it too. Like, I I I get less blank looks when I tell people I'm working on Substack than I used to. But yeah, it's been a it's been a steady march.
Speaker 2:How has kind of the war with with X, maybe the war is not the right word for it, but obviously removing links
Speaker 1:Platform changes.
Speaker 2:Yeah. Platform changes obviously frustrated a lot of the core creators who had been building an audience in both places. But from my view, it seems like they maybe, you know, created a monster, like, in the sense that Yeah. Maybe made you guys react and be like, and and it maybe it was like a short term win, but, will maybe be a mistake long term and that maybe it's kind of pushed you guys to think even bigger about what Substack is.
Speaker 1:The the I mean, the funny thing here is that Ben Thompson credits his early growth with LinkedIn and sharing links on LinkedIn. And then LinkedIn had an algorithm change, and he had said that he it wouldn't be possible to build Strictechery the way he did in the modern LinkedIn era. So there was kind of like a LinkedIn vibe too. But, I'm interested to hear how you've been processing. Just all the platform changes, really.
Speaker 8:So, I mean, this has always been my theory is if you wanna build one of these businesses, you need a model that supports independence. You need people to be able to subscribe to you. Mhmm.
Speaker 5:And then
Speaker 8:you also need, like internet scale networks to grow on. Yep. And in the old days of Substack, it would be, you know, at the very start, like trajectory, you'd have this newsletter, this website, but then you'd have to go on Twitter to promote it or go on LinkedIn or go on Instagram or where wherever. We always want you to be able to do that. We want you to be able to publish.
Speaker 8:It's not a walled garden, like put it everywhere, put it on the RSS feeds, put it on YouTube, whatever. But you're totally at the mercy then of these other platforms that don't necessarily you know, sometimes they go to war with you, like Elon got pissed off at us. But a lot of the time they just they don't care. Mhmm. Right?
Speaker 8:Zuck can turn around and say, we're not doing politics for a little while because people got mad at us. And if you're somebody that writes about politics, that's really bad for you. Mhmm. And so we always knew that we need to we needed to make our own network, our own place. Fucking Zoom reaction time.
Speaker 8:I gotta turn that off.
Speaker 1:I think that's just space time. It's at the OS level.
Speaker 8:I feel like I've turned this off a thousand times, and it sometimes still comes back. If we could just shoot whoever built that feature,
Speaker 4:that would be perfect.
Speaker 8:Anyway, we had to build a network. We knew we had to build a network. You know, it doesn't make sense. It's not like, you know, Facebook or LinkedIn or X or anybody's TikTok's job to help you, like, you know, take your audience and own it and make something independent. It's never like been their main thing.
Speaker 8:So we knew we had to do that. That's why we built, you know, the Substack app in the first place, which is why Elon got so mad at us. He felt like we were, you know, competing. But ultimately, we just knew these independent places need their own network that actually wants them to grow and thrive. Mhmm.
Speaker 8:It was a big painful thing for people that were on the platform. It sucked that you're like links didn't work. Super annoying. But it was a it was a very small fraction of traffic. Like it didn't slow down the business or the numbers at all.
Speaker 1:Yeah. There was
Speaker 8:a lot of stir and drang. It was very like Mhmm. That, you know, for people that are like had a big Twitter presence and were trying to make a sub stack, it was very painful and stressful. But it didn't slow down the growth at all.
Speaker 2:That's cool. What's you your yours and the team's sort of decision making process? It feels like at a bunch of different points with Substack, you could make a product decision that might drive immediate basically make the number go up, but maybe wasn't aligned with the kind of platform that you wanted to be and and maybe not even aligned with humanity. And on that note, there's sort of this, like, interesting thing where every platform, maybe other than Substack, is sort of, like, converging on being the same app, the sort of, like, short form slopification of of social media where it's, like, you know, doing a slot machine with information. And it feels like Substack is orienting around long form content.
Speaker 2:We had Jason Fried on yesterday.
Speaker 1:Yeah.
Speaker 2:So that's sort of rambling.
Speaker 1:No, no. I completely agree. I was going to ask the same question. I feel like if I land on a Substack link, it's gonna be written by a human. It's not gonna be particularly sloppy.
Speaker 1:I might not like the particular topic or something, but I feel that it's gonna have, like, this premium, like, vibe to it, I guess. And I'm wondering if there's is there are we just early and there's a coming wave of slop or that you're gonna have to fight? Or or Well,
Speaker 8:mean, here's my take on this is know, I think if you put yourself in a the position you described where it's like, hey, we've got this business, we're trying to make the number go up, and we either need to make the number go up or we need to make something that's good that we believe in, and we kind of have to like make that choice. Mhmm. I think as soon as you have to make that choice, that already sucks. Mhmm. Because both of those choices suck.
Speaker 8:Mhmm. Right? It sucks if you kind of give up your principles and make the number go up. But it also sucks if you stick with your principles and the business like it hurts the business and the business doesn't thrive. Ultimately, the business of Substack needs to grow and support the thing we're making.
Speaker 8:And so the thing that we've tried to do is yoke the success of the business. Set up the business model and the fundamental way that it works, so that in order to make the number go up, we have to do the thing that's actually good. So an example of this is, know, the way that we make money is it's completely free to publish on Substack to any size audience. You guys should cross publish on Substack by way. That'd be sick.
Speaker 8:I know. And then we only make money when you make money. Right? So we're trying to help you grow. We make money when you make money.
Speaker 8:And so, you know, we have an algorithm the same way that Twitter or TikTok has an algorithm. We even support short form video. You can see clips. You can read long form stuff. You can watch a long form podcast.
Speaker 8:But it turns out that when you're tuning the algorithm to introduce thing people to things that they deeply value and might pay for, the emergent effect of that is very different than if you take the same technology and point it at the goal of get people to spend as much time here as possible.
Speaker 1:Yeah. That makes sense. Because I I I I might pay and then be satisfied, close the app, but that's a win for the algorithm. Yeah.
Speaker 8:Our algorithm says great. Right? Whereas, you know, Elon's been public about the links thing. It used to be just Substack. Now it's everyone.
Speaker 8:He's like, yeah. If you're scrolling your feed, you click into a long form post, you go and read that thing and get deep value from it. You just tank the metrics.
Speaker 1:Yeah.
Speaker 8:You're not seeing any ads. Like, what are we doing?
Speaker 1:Yeah. Yeah. Yeah. Yeah. It makes sense.
Speaker 1:How is the health of the overall creator economy? There was a big boom where venture capitalists were investing in the creator economy. That's kind of died down. But, how healthy is the creator economy? Broadly.
Speaker 2:We were joking yesterday Eirwon in many ways in LA is a product of the creator
Speaker 1:There has
Speaker 2:to be double digit percentage of Eirwon's revenue. It's just creator revenue, you know, that that flows in in different ways and
Speaker 1:then goes into lot of flows in there for sure. A A lot of g wagons in the parking lot.
Speaker 8:It's the l l a equivalent of like the.com bubble. Yep.
Speaker 1:It's airwad bubble bubble.
Speaker 8:Never liked I've never liked the term creator economy. Even the term content creator kind of gives me hives. Here's the thing that I think is not going away.
Speaker 2:Mhmm.
Speaker 8:Is, you know, the the media landscape is shifting. The legacy models have been eaten up by Internet things that don't necessarily support, you know, the old businesses. And there's this shift to a shift in power to independent creators. Mhmm. People like you that can just set up, start a thing, make something that matters
Speaker 1:Yeah.
Speaker 8:Earn the trust of people by building going direct, building an audience. I think that trend is extremely robust. I think that thing is gonna is sort of inevitably gonna happen at this point. But I do think it's sort of undecided which version of that future we get. And so we see our you know, the thing we're working on at Substack is to try to bring about kind of like the best and most valuable version of that future.
Speaker 8:But I think the I think that shift is not going away.
Speaker 1:Yeah. I mean, you talking about the the, content creator as a bad term, do you prefer journalist, writer, like, more specific scalpel like terms? Is that what you're getting at? Or what specifically don't you like about the idea of the word content or the word content creator, the phrase?
Speaker 8:It's it's pretty rational, man. It just kind of feels it it it feels like a slop version. Right? Yeah. Sure.
Speaker 8:You're a journalist. You're a writer. You're a podcaster.
Speaker 1:An analyst. Thinker.
Speaker 8:Analyst, broadcaster
Speaker 1:Yeah.
Speaker 8:Filmmaker, you know, comic. There's a million things you can be. And I listen, I've I've made my peace with creator. Like, it's it's a good generic term. Yeah.
Speaker 8:But I think there was I think there was a moment where we kind of like cargo culted the creator economy and everybody got really sort of hyped up about it in a fluffy way
Speaker 1:Mhmm.
Speaker 8:And missed the the the deeper thing that Well, is actually still happening.
Speaker 2:What actually happened is that there was like a specific data point, which is that VCs realized that creator content creators were the fastest growing SMB category. Mhmm. And they were just like, okay, we should deploy like a billion dollars.
Speaker 1:We gotta make money off this.
Speaker 2:We gotta make we gotta make money on this. And the the thing that the thing that people missed is that that had been a sort of they were it was sort of like a decade into that trend. And so people funded a lot of businesses that were like banks for creators. But a creator is like, you know, why would a creator not just use rent? You know, we use Ramp.
Speaker 2:Right? Like, or why would a creator not just go to Bank of America and just get a bank account? Right? Yeah. And so I think the the sort of interesting investable opportunities were the Substax, which is like a new economic, you know, not to use your tagline, but like an economic creating a new economic engine for media.
Speaker 1:They should have invested in Erewhon because that's, like, the grocery store
Speaker 2:for creators. Or It's all down
Speaker 1:They should have just bought stock in Mercedes because they make the the the small SUV for the for the for the creator economy. I wanna talk about, the value of curation versus instantiation of ideas. I'm not sure if you've been following, Ben Thompson's erosion of, like, the evolution of, like, the printing press to the Internet making distribution, zero marginal cost to the instantiation of ideas with, GPT and deep research and language models. It's become easier and easier to create a deep research report. The writing is good.
Speaker 1:It still feels like you can tell when it's AI written. Yeah.
Speaker 8:It's at least fine.
Speaker 1:Yeah. It's at least fine. But I guess the question is, are there any, are there any sub stackers out there that are openly using AI tools to write, but the value that they bring in the human element is just curation? Because sometimes I I feel like, I should just share all the deep research reports that I put together because they're cool, and they're I'm asking interesting questions. And the and the humanness comes from the question that I'm asking, and very few people would think to ask that question to deep research, and the the answer is less important than the question versus just the general trend in in language models, if you have any takes there.
Speaker 8:Yeah. I mean, the way I think of it is, you know, we even before AI, we already lived in a world of infinite content. Mhmm. You can't get bored. You can't run into stuff to see or watch.
Speaker 1:Yeah.
Speaker 8:And so the limiting factor is like your attention in your life.
Speaker 1:Mhmm.
Speaker 8:Like what what should you pay attention to? Mhmm. Who are you gonna trust? What matters?
Speaker 1:Mhmm.
Speaker 8:Like, it's sort of it's an it's the human alignment problem. Like, this is what culture is. It's not just getting what you want, it's figuring out what to want in the first place. Mhmm. And that's the thing that's actually valuable.
Speaker 8:Even before AI, nobody's subscribing to Substack because it's like, oh, I don't have enough emails to read and I wanna pay money for that. You're subscribing for a perspective. You're subscribing for some connection, some piece of trust, some piece of curiosity. And so I think all of these these technology tools that just give people superpowers kind of supercharge both sides of that. There's now there's a, know, a thousand times Infinity content.
Speaker 8:There's more than you could even more. But also the people who who have those relationships can have so much creative leverage. And I I I think like literally writing for me is the is one that's not that exciting yet, although it's not impossible. But like yeah, help me do the research. Help me figure this thing out.
Speaker 8:Help me you know, put the pieces of this together. I think there's, you know, there's even people that have you know, Lenny Wachitsky has his Lenny bot that people subscribers can talk to.
Speaker 1:Yeah.
Speaker 8:I think all that stuff is awesome.
Speaker 1:Talk about growth hacks. If someone out there is starting a Substack today from zero, they have no audience, what can they do to turbocharge their business in the short term?
Speaker 8:The biggest growth hack I often have to give people is just start the start the thing. Mhmm. A lot of people I talk to are thinking about, oh I should do this. Should I write 10 things? Should I come up with this plan?
Speaker 8:Should I do this? Everybody that succeeds that I see just goes, just gets going, just starts writing, starts publishing. You know, try to make something good, try to share with people, and really just have a very strong bias towards action, towards thinking and moving in public. And then kind of like correct based on feedback rather than trying to come up with some genius scheme. All that said, know, make great stuff, share with people.
Speaker 1:Have you been able to dig into any of the quantitative metrics around the most successful substacks? Like, is there a correlation between posting weekly and and revenue or length of post? Can a deep dive ever be too long on substack or too short? Or is are there any patterns that you've seen amongst the the top performers?
Speaker 8:You know, there is a there is a trend that says, look, all else being equal, being consistent at publishing pretty frequently really does help.
Speaker 1:Yep.
Speaker 8:It's it's a lot easier, you know, if you're publishing multiple times a week consistently for a long period.
Speaker 1:Yep.
Speaker 8:Your chances of success really do skyrocket. Other than that though, we sort of have the problem you see this in marketing too, where sometimes the like the opposite of a good idea is a good idea.
Speaker 1:Yep.
Speaker 8:Where it's like one thing works, but also like the opposite of that thing also works. You just gotta find something that's sort of good and differentiated. So, yeah. Make something that's interesting, authentic, that you actually like, and then make a lot of it is Yeah. I mean, we
Speaker 1:found that 100%. I mean, fifteen hours a week, three hours a day. And not only that, but, I mean, I think we posted on X 20 times yesterday and, like, 10 clips. And, like, some of them don't do very well, but you just set the quality bar where you set it, and then you just try and get those, you know Oh, yeah. Let the winners ride, basically.
Speaker 8:Well, I'll tell you what. You cross stream to Substack.
Speaker 1:We'll do it. We're powered in.
Speaker 8:Got AI auto clips.
Speaker 1:You can
Speaker 8:make your own, but also people will just find them.
Speaker 1:I love it. Let's hear it for that.
Speaker 2:Let's hear it for that. I like the sound of that. No. I'm excited to get over there. To be honest, we've been so you know, the core challenge for TBPN is that we're a startup.
Speaker 2:But we're, you know, John and I are the founders, but we happen to be live for three hours a day. And then we have to spend like a couple hours prepping the show. And so there's just like, and we've built out We're individual contributors. We're amazing team Yeah. But it's just about adding these other channels.
Speaker 2:But I I see a ton of opportunity on Substack. And I just love how thoughtful you guys have been about, you know, building the platform and staying true to your values. It's awesome to see.
Speaker 1:I have one last question, and then we'll let you go. Lessons from Lulu going direct. What'd you learn from working with her? What have you learned from the most recent Lulu ideology and what it means to communicate as a CEO to an audience of investors, employees, customers, etcetera?
Speaker 8:I'm a huge Lulu stan. I've learned a lot from her. Maybe one thing that is is non obvious that I got from working with her that I wouldn't have necessarily picked up on just from the output is Mhmm. Kinda like the in in many cases, the the principles and the morals and the facts come first.
Speaker 1:Mhmm.
Speaker 8:The most important part of the go direct comms thing is not just how do I spin this or how do I posture it or how do I say it? It's like, are you doing the right thing? Mhmm. Are you, you know, are you are you willing to stand behind the message that you're coming with? Mhmm.
Speaker 8:I think that thing matters
Speaker 5:a lot.
Speaker 1:Yeah. That's great. Well, thank you so much for joining. We'll
Speaker 2:listen to awesome. We'll back on again soon.
Speaker 1:We'll talk to you soon. Cheers.
Speaker 2:Great to
Speaker 1:catch Substack.
Speaker 2:We'll see you over there.
Speaker 1:Bye. Let's tell you about Bezel. Get bezel.com. Your Bezel Concierge is available now to source you any watch on the planet. Seriously, any watch.
Speaker 1:Also, potentially, creator economy startup. A lot of creators getting watches. Yeah. Lots of folks in tech getting watches.
Speaker 2:Their cap table is absolutely stacked.
Speaker 1:It is. We talked about Lots of creators
Speaker 2:Talk about numerals benchmark series a. Yeah. Talk about a stacked cap table.
Speaker 1:Anyway, our next guest is here. We have Sean from stored announcing a a major size gong moment. Welcome to the stream. Sean, how you doing?
Speaker 9:Good to be here. Thank
Speaker 7:you guys for having me.
Speaker 1:Kick it off with the funding announcement. What's going on? What's new with you?
Speaker 7:Yeah. We're excited today to announce that we've raised $200,000,000 across our series e.
Speaker 1:Congratulations. Series e. Wait.
Speaker 7:Series e. Been waiting for that Gong moment.
Speaker 2:That's amazing. Let's go. We're gonna hit more. We're gonna hit
Speaker 1:More sound effects. Sound effects. Give me the Ashton Hall. Give me the Ashton Hall. Success.
Speaker 1:Overnight success. Yeah. How long have you been doing this?
Speaker 7:I'm a few months away from my ten year anniversary with Stories. Wow. Overnight Overnight success.
Speaker 2:Classic overnight success.
Speaker 1:That's great. But introduce the company. Break it down for us. What do you do?
Speaker 7:For sure. So we're building a commerce enablement platform that's entirely designed to level the shipping experience for brands of all sizes with Prime. Over the last two decades, retail has changed where you don't walk in a store and swipe your credit card and walk out with the product. You swipe your credit card online, you walk out with trust. Trust that you're gonna get the right product when the brand is said.
Speaker 7:You're gonna have easy returns. And these massive giants like Amazon have realized that is what's driving today's buying behavior. And so they've invested tens of billions of dollars into building out this competitive advantage. Meanwhile, every other brand is kind of in the stone age where if it's take cloud computing, they're still building their own data centers, managing their own racks in their office. And so we give them a scalable platform that combines an end to end physical fulfillment network that ships over 30,000,000 packages a year.
Speaker 7:Last year, we hit about 15% of US households. We powered over 1% of Black Friday, Cyber Monday. But then all of the technology, not only that runs that network, but that also speaks to the consumer. So there's a high probability to either yourselves or people listening who've actually delivered you a package before, powered that tracking link you may never even have known.
Speaker 1:Wow. So talk about how asset heavy or asset light the business is. What do you own? Do you own warehouses, trucks, planes, boats? What are you sitting on top of?
Speaker 1:Who are your key partners to make this happen?
Speaker 7:Yeah. Great question. Our three pillars are really a network, software, and scale. We give economies of scale across a network of assets. Some of those we run ourselves.
Speaker 7:So we do now operate 13 fulfillment centers.
Speaker 1:Okay.
Speaker 7:Employ about 2,000 individuals across those fulfillment centers.
Speaker 1:There you go. Congratulations. That's huge.
Speaker 6:It's crazy.
Speaker 7:It's sales wide. Planes all the time, constantly going to a different city. Then about 70% of our business is an entirely asset light network. Existing warehouses, existing trucks
Speaker 4:Mhmm.
Speaker 7:Particularly existing last mile carriers where we manage a network of about three dozen of them. But then all of that overlaid with our technology so the customer has one consistent experience no matter where we deploy their inventory.
Speaker 1:We talked to Harley at Shopify. How important are, small businesses to your business versus going after the scaled ecommerce players, obviously, not Amazon, but maybe Walmart or, you know, Macy's and, like, the really big players?
Speaker 7:Great question. I'd say we're kinda squarely in the middle where we serve a lot of mid market brands, about 500 of today's market leaders. So we power all of the deliveries for brands like Athletic Greens, Seed Health, True Classic Tees, Proactive the skin care, Quip the toothbrushes, Billy the razors.
Speaker 1:Okay.
Speaker 9:It's a
Speaker 7:lot of today's kinda multi hundred million revenue leading brands, the types of companies you'd see walking the aisles of a Target, for example.
Speaker 1:Yeah. Is that is that mostly founder led? I imagine that a lot of the founders of those companies kind of in your boat, been in business maybe a decade, raised a bunch of money, and kind of at the same conferences. Is that how you're doing biz dev? Do have a massive Salesforce, or you're outbound?
Speaker 1:What's working? What's not?
Speaker 7:Yeah. We are one of the flattest founder led sales cultures you're you'll find. We actually sell I mean, last year, we were 9 figures of new sales. This year, we're 9 figures of new sales in terms of how we're growing. We have a seven rep sales team.
Speaker 7:And so, we are we are on the plane all the time meeting with our different brands, meeting with these customers. And I think that's actually one thing that blew away investors in this round. If you look at our last four quarters of sales beats, I mean, we were three x our q one goal this q one alone, and we hit most of the year. We have a fraction of a kind of percent of revenue on sales and marketing and r and d to a lot of peer companies, yet a lot of ROI.
Speaker 1:This is such a funny interview because not only is it live, which is obviously a little higher stakes, but there's also a very chaotic soundboard potentially throwing you off.
Speaker 2:Well, I mean, there's so many I every single I I I don't wanna throw you off. I just
Speaker 1:It's good news.
Speaker 2:That's my personal reaction.
Speaker 6:But if you can
Speaker 1:make it through a TPN interview, like Bloomberg or CNBC is gonna be a walk in the park. Walk in
Speaker 5:the park, two minutes,
Speaker 1:no sound board, really easy. You got a question?
Speaker 2:What was the dynamic? I mean, imagine the last, you know, five, six weeks have been intensely stressful just because of what your underlying customers have been going through. Did the round get kind of done before that, or were you simultaneously navigating trade? I imagine you were navigating a trade war and a new financing. Yeah.
Speaker 2:Just sounds sounds intense, but but what what did the timeline look like?
Speaker 7:Yeah. We kinda come to the principle that everything crazy happens at once at Storr, and so it's, it's never a time time off. I'd say that we were laying the groundwork for some of this before the trade war really started, and it kinda threw a big wrench into the fundraise in terms of some people realized how good it was for us, and some people got really scared. Thankfully, and I'm so fortunate to say, store grew massively at other issues, take COVID. Take war breaking out.
Speaker 7:Take UPS or Canada Post strikes. All those are a reason for a brand to say, you know what? I'm not gonna face this on my own. I don't have the economies of scale to stay flexible. I don't want all the risk on my business.
Speaker 7:Let me go to a network like stored. And so, thankfully, very similar here where there's really two tariff issues going on. One is anything that comes into the ports from other countries in large quantities, and that's kind of a standard tariff people are talking about. The other one is the de minimis, IMAX, section three two one. All these ecommerce brands sending small packages into The US, not via a container on the water, just a small package where if it's under $800, they haven't paid taxes or tariffs on the import.
Speaker 7:That was really made for people like us, individuals traveling internationally, sending products back to families, and it got exploited into this massive program where about half of Shopify's top 100 ecommerce businesses were shipping from outside The US. And so when that changed, all of a sudden, all these brands had to have this influx of volume into The US, and these traditional providers, again, back to kind of the data center analogy, are telling them, oh, we can get you live and set up a new fulfillment center for you in six to eight months. We had a case study with that true classic T shirt brand, multi hundred million revenue retailer. Took them live from meeting us and signing to fully outbound shipping in eighteen days, and that's only possible on a tech driven network.
Speaker 1:How much of the business is international versus domestic?
Speaker 7:About 9% of our revenue would be either packages leaving The US or actually holding inventory internationally.
Speaker 1:Okay. I have another question. Go for it. And then I I noticed that the the raise is a mix of debt and equity. What are you using debt for?
Speaker 1:And how do you think about is this the first time you've really included debt in a big fundraise? And then I have more questions that we can riff on after that.
Speaker 7:Yeah. I think for the story, we're at a late stage where part of what we announced in this round is profitability, which I think is a lot rarer in a category like ours. We've spent multiple quarters in a row now consistently profitable, and that's compared to venture times when you're in a rapid delivery business and people are wondering, are we using venture dollars to subsidize fast deliveries? Well, I think the the proof is in our unit economics and in that profit. But at the same time, we still had a strong balance sheet from the 300 plus million dollars we had raised prior.
Speaker 7:And so when we looked at this round, we kinda said, let's raise the right amount of equity, but let's also use the scale, the profitability to complement the balance sheet with the right cost of capital and the right flexibility. And part of it comes down to we actually have been acquisitive in the past as well. We've acquired three businesses over the last few years. All existing fulfillment centers because we've just seen if we onboard existing infrastructure to our technology, we can multiply the success of those customers, the profits of the the the acquired business, and more. And so plan to be on the lookout for more opportunities like that as we keep growing, which I think funny enough, we started that, our first one in 2020, very not in vogue for venture backed businesses to be making acquisitions.
Speaker 7:Now with this kinda AI wave and more, there's actually some specific funds that are just being built to roll up traditional businesses and apply technology to them.
Speaker 2:What are you seeing that's exciting around actual fulfillment automation and robotics? This has been obviously a tough challenge that, again, the major players have invested billions of dollars at this point into. And yet oftentimes, fulfillment is still a very manual sort of process.
Speaker 1:Yeah. It feels like if you're building a 3PL from the ground up, it's maybe easier to think robotics first. If especially if you're a tech company young, you're obviously aware of everything that's happening in AI. But, at the same time, hard to replace a human. They're pretty versatile.
Speaker 7:Yeah. We're very excited about both AI and robotics because labor and humans are one of the biggest costs in the business like store.
Speaker 9:Mhmm.
Speaker 7:And going all the way back to day one starting even back then, we were seeing peer startups in in different cohorts and accelerators more that we're building drones for inventory scanning and all these robotics. And it oftentimes shocks someone when you step back and you say, hey. You realize over 60% of US warehouses aren't even using a digital WMS? They're doing pen and paper based picking. It sounds like it's made up.
Speaker 7:It doesn't sound possible, but it's true. And so then you kinda look at this gap of where the industry is, and if they can't even get to that kinda threshold one, getting to humanoid robots or AI deployed on how to slot in a warehouse is essentially impossible. And so there's such a fundamental advantage when we've built an entirely vertically integrated tech stack of we're really the only ones like Amazon when we're making you that promise in the cart. Hey. Order now.
Speaker 7:You'll get it by 5PM tomorrow or the next day. We're actually going through not only the front end consumer tech, the order management layer, the transportation management layer. We're looking at we actually have this unit in Las Vegas right now. We can get it to California by tomorrow if we ship it right now. And so we're connecting that vertically integrated system, which just gives us so much more opportunity to deploy robotics, AI, and more.
Speaker 7:And so a lot of it's on the AI wave right now. How do we use it to optimize demand planning, inventory placement, parcel selection, promise to the consumer, and more. And the next phase is we've been using some robotics, particularly around the conveyance slotting and picking in the facilities. But when you can go from static with a moving arms to both moving arms and moving legs with a humanoid, it gets really interesting.
Speaker 1:On other big tech trends, what are you most optimistic about across, kind
Speaker 6:of the
Speaker 1:eVTOL package delivery that we're seeing from zipline to, something like automated trucking, self driving trucks to, maybe even something just like really, really robust language model driven AI agents, just doing some of that paperwork, for example, but 100% reliably? Like, what technologies are you the most optimistic about? And if you have any timelines, I'd be interested to hear them.
Speaker 7:Oh, timelines is always the question mark because even some of the ones you just mentioned, there's been a heavily debated and now disproven timelines over the last decade already. So I I struggle to make promises.
Speaker 2:But
Speaker 1:But which one would have the biggest impact on the customer experience? Which one should we be really rooting for in terms of just speeding up the the time to delivery and reducing the cost?
Speaker 7:I think any form of autonomous delivery, whether the amazing teams over at Zipline and that kinda localized rapid last mile, Some things that failed even at Amazon, like the driverless kinda sidewalk robots. Anything that helps connect that last mile autonomously bends the cost and speed curve so dramatically that that's probably where we remain the most hopeful and excited. But with a model like Storr being the network, essentially, what we're doing is aggregating the demand and putting it on one form of tech. But a lot of these businesses you're mentioning are actually key partners of ours where somewhere in our network, we're able to kinda test this net new technology. So same thing with one of the major grocery and kind of food delivery platforms.
Speaker 7:We have a pilot in a few cities for same day delivery for some of our brands, two hour or less type delivery. But you wouldn't assume if you looked at stores that we're working with that type of company because it's buried in the network. So anything autonomous last mile, anything humanoid in a facility, and really anything around demand planning with AI, I think that is the most critical. Because if you talk to brands, demand planning is the thing that really only enterprises will say they do well. And I think most of them are a little self infatuated when they say they're doing it well.
Speaker 7:Demand planning is the biggest struggle in anything physical supply chain and speaks to, the problem our friends at, Peloton had during COVID. It's really hard.
Speaker 1:I'm looking at the bottom of our ticker. It's, Polymarket has The US recession in 2025 dropping like a stone. Let's hear it for The US economy. But my question for you is, are you seeing data on the health of The US consumer? How how is, demand in The US economy?
Speaker 7:Yeah. We have a really interesting kind of front line to the consumer across a lot of industries. We've purposely positioned to very macro resilient industries, things like health and beauty. You still keep the same makeup and skincare in bad times. Things like nutrition and supplements, very similar.
Speaker 7:A lot of subscription orders that we fulfill, almost 50% of the volume we ship. And so, thankfully, our brands have been pretty well insulated. We actually saw an interesting trend in April, which was an uptick for many of them. And And we were questioning it saying, is this consumers buying because they think prices are about to go up, or what is this signal? And so so far, we haven't seen a kind of bullwhip from that negatively in May.
Speaker 7:And so year to date, our our metrics and kind of markers to the consumer have actually remained pretty strong even though there's a lot of kind of fear and uncertainty when you when you watch the news and look at the macro.
Speaker 1:Let's go. Let's hear it for the American consumer. Okay. Endlessly relentless. Undefeated.
Speaker 2:This has been this has been fascinating. Thank you for coming on. I remember the first time I heard about you and Stord was from John at Strike, I think in 2021. And he was just so incredibly bullish on you, and I can see why. So thank you for coming on, and congrats to the whole team on the milestone.
Speaker 7:Means a ton. We're very proud to have Strike led, and I think something like 50% of the store investor base has has joined TBPN so far. Saw Nick Kleiner, Chad and Sousa.
Speaker 1:So Oh, yeah.
Speaker 5:Super thankful
Speaker 1:for not only their more.
Speaker 2:Yeah. Well, come back on when you have when you have interesting data too. Doesn't you don't need to come on just for fundraising news if you're seeing stuff that
Speaker 1:Yeah.
Speaker 5:That'd be great.
Speaker 2:You think would be interesting to us and and the audience. Yeah.
Speaker 5:We'd love
Speaker 2:to have you back on.
Speaker 1:Thanks so much.
Speaker 7:We keep the news fluent, so we'll reach back out soon. Thanks, guys.
Speaker 1:Talk to you soon.
Speaker 2:Cheers, Sean.
Speaker 1:See you. A little soundboard spice up. We to elevate the energy at the end of a long week. It's Friday, but that doesn't mean we can't listen to the Ashton Hall sound effect, I haven't gotten enough of.
Speaker 2:We're going into the timeline, John.
Speaker 1:Timeline. Okay. Welcome to the TBPN timeline where we review the best post.
Speaker 2:Many people said, oh, it's almost five on the East Coast.
Speaker 1:They're gonna stop They're gonna stop streaming.
Speaker 2:They're gonna
Speaker 9:stop podcasting.
Speaker 1:Podcast for more seventeen hours a week. We did it. We did We did multiple four hour streams this week.
Speaker 2:Yeah. Big. Big.
Speaker 1:Big week.
Speaker 2:Never podcast weekly, always podcast strongly.
Speaker 1:Always podcast strongly and daily. Scientists use CRISPR to rewrite DNA inside a living baby fixing c p s one, a rare lethal liver disorder. No transplant, no viruses, just three tiny LNP CRISPR doses, gene design dose to design, to dose in less than six months. Personalized personalized gene therapy is finally a reality today, says Didi, the world's first personalized CRISPR therapy given to baby with genetic disease. What, what a white pill.
Speaker 1:What a fantastic story.
Speaker 2:The footage from this is really, really sweet.
Speaker 1:So there's a whole video about this. You should go and watch it this weekend. But Didi goes on to say, right now, this is applicable to single cell single gene well mapped mutations in organs that can safely be reached, which affect thousands of babies every year. It costs under $5,000,000 now, so that's obviously expensive. It'll need to come down further further, and it was covered in, you know, all the mainstream media.
Speaker 1:But what a what a fantastic, piece of news. A baby's life was saved by CRISPR. I remember learning about CRISPR, back when my cofounders were at Caltech, and it was kind of this hot technology. There'd been actually a few previous technologies to edit DNA. Zinc finger nucleases was one of them.
Speaker 1:And and all the hot PhD research being done in in bio and biophysics back in this was like 2012, '20 '13 at at Caltech, their bio division was all about CRISPR. There were a couple people that spun out companies around this technology. Jennifer Dudno won the Nobel Prize and has a fantastic biography written by Walter Isaacson all about that journey. It's a it's a very interesting technology. It took so long to get here, but it's finally having an impact.
Speaker 1:I mean, it already has in many ways, but very, very exciting to follow. Good story. Also out of the scientific community
Speaker 2:Wonder if we could get gene therapy to make us closer, even closer, even closer to
Speaker 1:Golden dreamers. Golden dreamers. You're gonna go there. Absolutely. Permanently change my DNA so I can only be friendly.
Speaker 1:Yeah. Just turn off the unfriendly gene entirely. Yes. And also make me hotter and dumber because that's key. You can't just be friendly.
Speaker 1:You also have to be hot and dumb if you're gonna go full golden retriever mode. Anyway, I love this I love this headline from the Wall Street Journal. Forget humanoids. At MIT, worms and turtles are inspiring a new generation of robots.
Speaker 2:Pull this image. This This
Speaker 1:is such a great image. Yeah. Look at this turtle robot. He's so proud of his turtle robot. It's great.
Speaker 1:So CSAIL, which is their artificial intelligence laboratory, envisions robots beyond humanoids, including soft, flexible, and even edible designs.
Speaker 2:Edible robots.
Speaker 1:Eat your robot.
Speaker 2:You're gonna be able to eat your robot.
Speaker 1:Live in the pub.
Speaker 5:Is what
Speaker 1:Eat the robot. Bugs.
Speaker 2:Is what Joshua was talking about, right? Yeah, Like, let's explore every potential magical form factor of Doing
Speaker 1:soft robots like a sea turtle.
Speaker 2:Acquiredrobot.com this week too.
Speaker 1:Oh, yeah, so They
Speaker 2:came out with it.
Speaker 1:Edible robots for noninvasive surgery. So you eat the robot, it crawls around inside you and cleans you up, fixes you up, sews you up. I mean, yeah. I mean, if you have internal bleeding or something, yeah, eat a robot. It'll sew you up, I guess.
Speaker 1:Russ's lab is also using new types of AI models inspired by the neural networks of worms to power robot brains. What a fun story. Anyway, and this is something that's actually gone on before. I found a different video, from a different group. It says we have created a robot based on the leatherback sea turtle, which is alive today, leisurely swimming in motion.
Speaker 1:Next, we plan to modify it to an ancestor of the leatherback sea turtle that remains as a meso Mesozoic fossil to make it swim. And I think this is just like, I don't know, robust robo robo sucky. I don't know. Very interesting. He's just swimming around.
Speaker 1:Just made a made a robot turtle. Fun. People like
Speaker 2:turtles, I We
Speaker 1:talked about a few of this. What are the other funny posts? I mean, more more kit more fallout from Google, the design lead.
Speaker 2:Android Auto. This guy this is somebody's LinkedIn profile if you're on audio. Yeah. This person says, spent 40% of my time arguing with the worst PM I ever worked with, 20% managing and coaching amazing designers, and 40% on the inefficient overhead of simply working at Google. It's wild to see ideas we talked about in 2015 finally coming out in 2020, but they happened.
Speaker 1:Yeah. And, this is, of course, a quote post from Daniel. Says it's amazing how good Gemini is and how bad every product manager at Google is. Is it are the I feel like the PMs aren't that bad. It's more just like the organizational you ship your org chart, and they just they they just can't move fast enough to, like, position the products correctly.
Speaker 1:Like, the products are good. They're just not they're just not positioned correctly or or or talked about properly. I don't know. Sundar Pichai did an interview with the All In podcast. He sat down with Dave Friedberg.
Speaker 1:I'm excited to listen to that this weekend and dig into how he's thinking about product design and AI generally. I'm sure there's a lot of good insights in that interview, so go check it out. We have a new landing page for GREPITAL. GREPITAL.
Speaker 2:This is not gonna come up. I I just thought this was a fantastic website.
Speaker 1:Okay. Okay. And AI It's hard to viewer. Catch three x more bugs, merge four x faster, 100% code based content.
Speaker 2:We gotta pull up the I'm gonna share I'm gonna share it.
Speaker 1:It's a fun name. These AI companies, these SaaS companies, sometimes they sometimes they get wild.
Speaker 2:Wiggles dot in the chat.
Speaker 5:Let's pull this great
Speaker 1:great SaaS name.
Speaker 2:You got to see the animation though because the static image.
Speaker 1:So the so so the the reptile, the the lizard is is
Speaker 2:eating Catching bugs.
Speaker 1:Oh, that's good. Little on the nose of the metaphor. Do
Speaker 5:got it?
Speaker 2:Do we got it?
Speaker 1:But we respect it.
Speaker 2:Oh. Look at this.
Speaker 1:Cute. Very cute.
Speaker 2:That is a fantastic website.
Speaker 1:I like it.
Speaker 2:That's fun. I love to see it.
Speaker 1:That's great. Dan Romero giving us a shout out.
Speaker 2:Little shout out. I'm I'm excited to have Dan on the show.
Speaker 5:Yeah. Getting him locked in.
Speaker 1:TBPN format works because it generates daily content flowing out of the forty eight hour timeline zeitgeist that can be cross posted in video favoring algos on every major social network. Weekly podcast is too slow and stale in comparison. The only live competition is CNBC, and they are too slow boomer downstream compared to Twitter. Interesting. A good hour timeline.
Speaker 1:We we were it was the Daily Show. We do we're on a twenty four hour
Speaker 5:timeline.
Speaker 2:No. We sometimes catch stuff a little late.
Speaker 5:It's true.
Speaker 2:Right?
Speaker 1:Yeah. We gotta be more on top of it.
Speaker 2:We gotta spend more time on We're maxing, folks.
Speaker 5:So thanks
Speaker 1:for the
Speaker 2:shout out. Again, thank you for a wonderful week. Yeah. I hope everybody has a fantastic weekend.
Speaker 1:Do you wanna talk about the the public.com vibe investing?
Speaker 2:Yeah. We should actually cover This
Speaker 1:is very cool. So public.com, obviously, sponsor of the stream, has launched the ability to create synthetic portfolios around basically any investment idea you have. And then
Speaker 2:back test them against the broader market Yes. Which is where it gets really interesting.
Speaker 1:So we have a couple of these pulled up that we can share with you. The first one is Founders Fund funded companies that have graduated, and gone public. How did they do in the public markets? And you can see companies that were backed by Founders Fund have done 659% return over this, test versus a 50% in the S and P. Sequoia's done similarly, little up and down here for Sequoia, hundred and twenty three percent, versus one forty seven in the S and P 500.
Speaker 2:Yeah. A little bit rockier, but you have to It's done
Speaker 1:very well. 589% versus one fifty in the S and P. A 16 z has also done well with four hundred and six six percent total return versus 150% in the S and P.
Speaker 2:And this is where it gets really interesting, John, the F1 index. These are companies that sponsor F1 teams.
Speaker 1:Yes.
Speaker 2:And they have dramatically outperformed Yes. The S and P. 317 total returns versus a 47%
Speaker 1:Yes.
Speaker 2:For the S and P over
Speaker 1:the time periods. The best portfolio that they tested is the size compensation size lords. These are highly paid CEOs, often controversial. 2000% return based on investing in CEOs that get paid a lot Sucks. Versus a 76% in the S and P over the backtest period.
Speaker 2:That's actually insane.
Speaker 1:All right.
Speaker 2:Turns out when CEOs get paid well Yeah. Shareholders benefit.
Speaker 1:Outperform. And also who else outperforms? Bald CEOs. Bald CEOs Let's give it up for the bald CEOs. Hundred and thirty three percent versus a hundred and fifty in the S and P.
Speaker 1:Fascinating. Bezos probably doing a lot of heavy lifting there.
Speaker 5:Lot of
Speaker 2:heavy lifting. Yeah. But you got the Brian Armstrongs? Yeah. Right?
Speaker 2:Strong. Yeah. Strong. He's got a good I mean, this is insane. I'm I'm interested to just continue tracking this over time because it really tells an interesting story.
Speaker 1:Yeah. Not investment advice, obviously, but
Speaker 2:Never investment advice. Always entertainment advice.
Speaker 1:Steve Balmer, another bald CEO. There's a ton of them. Yep. A lot of good a lot of good bald CEOs out out there. So shout out to your bald friends.
Speaker 1:Anyway, thank you for watching. Leave us five stars on Apple Podcasts and Spotify, and we will see you on Monday. Thanks for watching.
Speaker 2:Cannot wait.
Speaker 1:We'll see you soon.
Speaker 2:Bye. Cheers.
Speaker 1:Have a good weekend.