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Today is Monday, September 8th, 2026.
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We are live from the TVPN Ultradome, the temple of technology, the fortress of finance, the capital.
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>> You know what time it is, John? >> Ramp. com time. Time is money. Save both.
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Easiest corporate cards, bill pay, accounting, and a whole lot more all in one place.
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Uh, >> I need my countdown. >> I need my countdown. There it is.
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Road to Christmas 107 days.
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>> December 25th flying by >> today. >> It's flying by. >> Made only possible. >> 107 days.
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Time is flying till Christmas.
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The road to Christmas is going strong.
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>> Start scoping out Christmas trees. >> Yep. Now's the time.
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>> Once we Once we get under 100, >> hopefully you've already planned >> open season. >> Open season. Does math matter? That's the big question.
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I was debating this with Tyler today.
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Uh lots of lots of lots of tension on the timeline over Navier Stokes the Millennium Prize math problem.
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There has been a millennium prize math problem that was solved before the point care conjecture in the preAI era.
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These are very very difficult math problems that all PhD mathematicians all sorts of uh elite uh the upper echelon of math has been grappling with for years and AI is starting to knock these down.
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Remember last year was the year of the IMO gold medals from both Google Deep Mind and OpenAI.
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We talked to Scott Woo about this who's coming on the show later today. Huge race for cognition.
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And Scott made the prediction on TBPN uh early in 2025 that he believed that artificial intelligence would be able to achieve gold at the IMO, the International Math Olympiad in 2025. And he was right. He nailed it. Progress continued.
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Uh but debate remained around uh cool calculator bro is the is the critique.
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I mean people just they don't feel empowered by a system that's really good at math.
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It just people already a TI83 can do more complex math than most people can do.
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And so, uh, when you say, "Oh, there's another level of math that you don't know about and you don't care about, and computers are good at it."
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A lot of people, their eyes glaze over.
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And so, uh, the bigger question here for me is all about the the public perception.
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What actually matters here?
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I think they're cool benchmarks.
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I think they're interesting stories.
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Obviously, there's a lot of drama over this race.
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It feels like it was neck andneck.
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Now, there's uh a bunch of debates going back and forth with a mathematician who works at Google and a mathematician who's independent who worked alongside an anthropic researcher who were both working on it.
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And they were apparently texting back and forth and going back and forth on did they steal the the data, did they copy each others, do they have different approaches?
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Um and so lots of different back and forth.
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And I think someone summed it up well by saying that um uh these uh these math models have discovered the the hardest problem of advanced mathematics which is authorship uh contribution.
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Who actually did the work?
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Who gets lead left on the paper?
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Um but yeah, there was a there was a drama last year 2025 during the IMO.
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um OpenAI and Google Deep Mind and I believe Harmonic the math uh AI lab that we had on the show last week uh were all working on solving the International Math Olympiad.
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Uh remember there's six questions.
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Question six, no AI model could solve.
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It was more complex, but uh both teams got a 35 out of 42 even though they only got five questions out of six right.
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That's good enough for gold.
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It's the bare minimum, but they did it.
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Um, but there was a bunch of back and forth because OpenAI validated with former IMO gold medalists.
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While Google's result was graded by the official rubric that year, which is internal to the organization, we called it at the time.
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It's like they ran the fastest 100 meter sprint in the parking lot while the while the actual Olympics is going on in the stadium.
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And so, uh, a lot of these are just, you know, bibe wars races.
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Who does what does it even matter?
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Um, the interesting thing about Navier Stokes is, does it matter, Tyler? You think it does?
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I'll debate you on this a little bit.
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It seems like it doesn't because uh the equations themselves are known.
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They're just not fully proven.
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Engineers and physicists already solve them numerically all the time for particular situations.
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So, air flow around a wing, you might have to use some of these equations.
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weather models, uh, water through a pipe.
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These are critical things.
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Uh, they are boring, but you can imagine that there would be cause for optimism.
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You know, better weather models save lives during hurricane season.
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Uh, increased air flow across a airplane wing that could lead to more efficiency, longer ranges, cheaper flights, lower carbon emissions.
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There's a bunch of reasons why you could solve all that and be excited.
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But that's not actually what >> one of the reasons I'm excited.
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I I believe we agreed last week that if anyone solved Navier Stokes, Tyler would shave his head. >> Oh, that's right. Didn't we do that? We said something.
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>> No, no, that was about the details. We have details down.
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Get ready to shave your head.
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But uh but yeah, this is a big moment.
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>> Yeah, I think it was actually it was if any if any AI progress happens at all, Tyler shaved to say. >> Yeah. Yeah.
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>> But do you have a steel man for why this matters?
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So, I I think I agree that like I don't think the the breakthrough, you know, this new stuff that's going on is like practically super useful.
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I don't think you're going to feel it when you're when you're on an airplane.
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You're not going to feel like less turbulence now because of this.
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>> But I think like, you know, these are like the most important open math problems.
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I think like the these are more close to like, you know, a beautiful painting or or something than like >> some like practical engineering >> breakthrough. Yeah.
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>> Like this is like pure math.
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This is like the, you know, this is the peak of the mountain of like >> same month.
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>> Same month that AI solved this incredibly difficult math problem.
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I saw someone used Chachi Pit to book a haircut. So equivalent.
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No, I mean in terms of the actual economy, the actual impact of these things.
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impact of these things. uh like practically using these tools for something that people enjoy that's not just spinning their wheels that's not just optimizing endless things that's actually uh generative and moving things forward not just defending against cyber attacks doing
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>> winsome says uh if he gets Millennium prize you all have to get bowl cuts >> oh bowl cuts >> bowl cuts are interesting >> that's really really ridiculous you do get a million bucks so you know there's that um that's not nothing but in the AGI high race where trillions are being deployed. Uh it is it is very minimal
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Uh it is it is very minimal but um the it sounds like cause for optimism that Navier Stokes would improve air flow over a wing, something like that.
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But that's not really how it will work.
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work. um uh proving this uh this these equations uh is unlikely to actually have any measurable measurable impact and that's sort of agreed upon and physicists have sort of chimed in with this take that uh this doesn't this won't actually move the discipline of
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engineering forward at all but it is a cool demo um engineers already solve the equations numerically as I mentioned uh so clearly it matters for hype and vibes solving our math problems is good heristic to show how quickly models are progressing. Uh but
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Uh but >> yeah, and and to to me it just comes down to humans are able to use machines that humans built to further humanity's general knowledge. >> Yeah. Yeah. It's good.
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Um and but I feel like benchmarks and if you're just trying to measure AI progress, benchmarks and raw inputs and raw metrics of the model sort of do the same thing.
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thing. like the number of people who will be convinced that AI is progressing exponentially uh because they see this result and then you look at the number of people that are that that would be equally convinced of AI progress just by hearing oh
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there's you know 10 gigawatts coming online or the new model has 10 trillion parameters or it was trained with a billion dollars of compute or something like that like >> the thing is the average person is probably more impressed by Sora than by this >> totally Totally. It's way more visceral
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It's way more visceral to actually see something.
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And that's why the weekend was very much Blender and people showing 3D renders and remodeling their houses and building small games and web games.
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And that feels much more like a uh okay breakthrough. People are having fun.
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They're vibe coding stuff, but they're also doing 3D modeling, which is like a new skill.
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We've had image generation, video generation, but uh there's something much more uh I don't know like grounded in watching a uh from just a few images watching a Blender model come to life.
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You can walk around inside of it and it can be something that you know the model doesn't exist.
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I saw a few demos that were like a train and it was like, "Oh wow, it modeled this amazing train."
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But there are perfectly modeled trains out there that you can just go grab from the internet.
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That's not that impressive.
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When you actually see your uh your specific house or your car or something that doesn't already exist out there perfectly modeled, you're like, "Wow." >> Sorry to interrupt.
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John Anderson says, "Why are we only seeing the calendar days for Road to Christmas?
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Can we please get a weekdays and work days breakdown for Die Hard?"
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Yeah, we need we need a full full screen graphic.
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So, let's let's work on that. Thank you. >> Good. Thank you, John. >> Good comment. Good comment.
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>> Good comment. Good comment. Um let's uh um yeah so uh in terms of field the AGI uh computer use definitely one of these uh Astra particularly faster at computer use for like really really mundane things also just uh interesting to just have a very different interface to your
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computer like configurations all the things where you just have to dig through dig through a bunch of set settings maybe set something on the command line maybe find a control panel, you can just ask codeex or any AI agent to go and do it and it'll just do it and come back to you. >> One of the use cases that I'm excited
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>> One of the use cases that I'm excited about is getting, you know, when you get a parking ticket and then you're like, I got this parking ticket, I want to deal with it, and then it's like, well, the ticket is not in the portal yet.
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>> Being able to go into chat and say, hey, this once this ticket is live in the system, please pay it. >> Parking.
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>> And so you can just forget about it.
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Yeah, >> parking ticket super intelligence.
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>> It it is >> it feels like we're close.
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>> Um so yeah, I I think that uh the Millennium Prizes will get solved or proved or you know uh delivered probably this year if not like this week.
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It feels like all of the different labs are like put a million dollars of inference on this, put a million dollars of inference on this.
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Uh there it's going to be a back and forth and and the labs are going to very quickly solve basically all of these problems.
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uh and then there'll be a search for new problems, but the the conversation will move back to curing cancer almost certainly uh because that's the one that's so grounded.
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That's the one that's, you know, supposed to be uh tractable.
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It's been messaged from various labs for so long that people will will will want that.
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But there will be a longer flywheel from actually designing a cure for a specific cancer, running tests, seeing that it was effective.
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It's not it it you you can't do it with a million dollars of inference over a weekend, I think.
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But that's I I my my prediction is like the conversation will go back to biotech after we basically solve math, which is a crazy thing to say, but it feels like we're there. What do you think? >> Yeah.
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Uh all the conversation >> Yeah. People say loudly stop. >> Yeah. Yeah.
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So one, the pharmaceutical industry has been curing curing >> forms of cancer or or making progress against various forms of cancer for a very long time and like yeah zero credit worst reputation of any category of businesses >> on the planet. >> Yeah.
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And so I don't think that that's like this like you know that I don't think that's the solution to >> uh sentiment around the technology industry. >> Yeah.
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I know I saw and setting up this idea like imagine how underwhelming it will be if any AI lab comes out and makes like >> 20% progress towards one >> one specific type of cancer, right?
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uh that doesn't that's not going to come across as like oh wow they cured cancer.
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It's like okay they sort of advanced understanding and and and maybe the uh treatment process and and this type of thing is happening all the time.
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Anybody who's had a family member uh that's that's um suffered from cancer has heard about hey there's this thing in trials it's showing promising results >> trying to get you into it or whatever.
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Uh so that's happening all the time. Yeah. Right.
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And it's not going to suddenly change how people feel about >> the technology industry broadly.
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>> No, it'll diffuse slowly and people will be back in like the what have you done for me lately?
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Uh I mean I just saw I just saw a real where we were basically the thrust was like what has the the pharmaceutical industry done for us lately?
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And I was like GLP1's like sort of cured obesity like it's sort of a big deal.
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Um, and for a lot of people, GLP-1s have been like a really really key intervention in helping them fight diabetes, fight obesity, fight a whole bunch of knock-on effects that come from that.
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But it's not so much as like the speeding train was coming towards them and the industry pulled them off the tracks at the last second.
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And it's something where okay, if you're living at a healthier weight over from your 30s to 60s, you will probably be healthier at 60, but uh you're you're not seeing that like it saved a life today.
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Like a GLP1 has yet to get that type of credit. So, I don't know.
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Uh it's going to be it's going to be back and forth forever.
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But uh anyway, in the meantime, somebody gave Astra a paintbrush, a robot, and a camera, and asked it to paint the Golden Gate Bridge in real life.
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It figured out how to control the robot and progressively got better throughout its attempts. The time lapse is sick.
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Here's a one minute time lapse of uh co uh I I don't know how to pronounce this, but uh his account painting the Golden Gate Bridge.
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How would you rate this, Jordy?
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>> It appears better than I could do.
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>> Better than you could do.
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How long are you giving yourself?
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>> I'm saying at least by the by the the later attempts. >> Okay.
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The later attempts because it gets better.
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The first one was not quite not quite there in my opinion.
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>> Still pretty impressive. >> Yeah.
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Somebody was talking about uh potential for a 3D printer boom with all the 3D modeling.
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the idea that you could you can design I saw someone else uh designed a a system where you can from a prompt go from prompt to Lego kit basically in one go.
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So it it takes your prompt whatever you gave it >> like look at this John >> that looks solid >> that's pretty solid.
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Uh I think you could do better with enough time.
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I don't know how long that took but it is impressive.
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It's a fun fun demo and again it like lives in the real world.
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It's not abstract at all.
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So you can just watch it work. Watch it do the thing.
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And uh uh it's very very interesting.
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A lot of times uh what's interesting is that when you're using these models when they have to do a task like that, they will write a deterministic piece of software to execute it.
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Like I built a game where you it was basically Tony Hawk, but uh you would play as a pelican on a bike and you'd be able to do tricks and back flips.
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And the game worked really well. It was fun.
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and it built it in GDAU, the open- source uh framework for game development.
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And then I had it go and try and get the high score.
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And instead of actually using computer use to go and play it, it wrote a script that would play the game flawlessly.
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And it looked really mechanical because it wasn't there was no variation in it at all like watching a normal person play.
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Um but it did get a very high score.
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So I I could see it doing the same thing where it generates the image and then maps the X and Y axes and the plan into code and then runs that.
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Uh and so there's like this process of what the model can do.
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The model might also write software to do that same thing.
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So there's this like iteration process there. Yeah.
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And of course people are uh uh looking at Bach bench which is uh the uh the skill in writing a piece of music and it is the actual meme for my robot.
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Can a robot write a symphony?
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Can a robot turn a blank canvas?
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Take a blank canvas and turn it into a masterpiece.
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And I don't know people are calling this a masterpiece but they're pretty pretty impressed with >> it was pretty good. I listened to this. >> It was good.
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you're you're you're a fan of this lily pond uh four-part corral in the style of Bach.
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>> One of the best reactions to Astra's release last week was Josh who's over at uh Sentry, his company was acquired by Sentry.
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He said after Astra's release yesterday, scoring 99% on ARC AGI 3.
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I think it's become clear that AGI is no longer some distant hypothetical.
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About 15 minutes after the benchmarks came out, I booked the first flight I could find to Jackson Hole.
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And he goes on to say, uh, he's also looking into purchasing a horse.
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At this point, horses remain one of the only major transportation platforms with no API, no OTAA updates, and no realistic path to MCP support.
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So glad to see more people >> getting into horses.
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>> Getting into the horse game.
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bull market in the equestrian lifestyle.
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>> Yeah, it seems like he was uh joking, but a lot of people were like this unironically.
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I want to, you know, touch grass, I suppose. >> Did you see this?
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Uh >> uh Bojan posted it's over.
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Our last line of defense has fallen.
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>> Uh Astra beat all 48 levels of the I'm not a robot game. >> Yeah.
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What is >> And this was crazy to watch.
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I I wasn't sure if this was sped up.
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It seems like it's maybe sped up a little bit.
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>> You have to play tic-tac-toe, too. It's pretty good. >> Yeah. >> What? Yeah.
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The the capture defeat is going to be um whole new level of problems.
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At the same time, it feels uh like sort of remarkable that Pangram is as effective as it is given how advanced text models are.
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And so uh if you I mean there's a world where it's you know indefensible. Was that Waldo bench?
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>> Was that find the where?
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>> It was finding Waldo not creating >> finding Waldo.
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How are we doing on Waldo bench?
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That's a good thing to test out >> for Astra.
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>> Yeah, we got to see because I I bet that there's a way to to have Astra generate like the the proper tiles because the problem when we >> Yeah.
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You can like iterate on it more. >> Exactly.
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And the problem is that when we try and use an AI image generator to generate a where's Waldo, it always gets the scale wrong, I feel like, or there's like two there's like bigger characters in the foreground.
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>> Yeah, perspective is wrong.
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>> The isometric display is what's what makes a Waldo and uh um but but there's probably ways to solve that with a little little sprinkling in of deterministic code generation or Waldo generation.
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Um but Waldo bench might be saturated now. I don't know.
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So, it can't be really saturated.
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It's not a real benchmark.
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But, um, lots of lots of back and forth in the benchmark world.
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It does feel like we're getting to the end of it and the and the results are either big challenge like uh like a math problem or uh just a cool demo like this.
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>> Uh, another good demo uh from somewhere Astra.
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He says, "Astra and I are working on making my contact form as difficult as possible.
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You actually have to fighting battle >> uh in order to in order to hilarious >> contact them. >> That's amazing.
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>> This looks like a I might try and contact some Where we after this. This is pretty fun. I like this.
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Um yeah, the uh the the defeat of all of the captas uh is is somewhat linked to the the Instinct news.
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Did you see that this weekend, Jordy? >> Oh, yeah. The resi bands. >> Yeah.
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So, Instinct is a uh personal assistant AI focused on consumer.
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You link it with your email, your text messages, and we've seen a lot of investors sharing posts about >> how for what it's worth, I would be surprised if anyone in the audience hasn't already heard of Instinct. >> Yeah.
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And we talked about it before, >> but thank you for Thank you for reintroducing it.
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>> But but I but I think it's worth like explaining like how it works because uh it does seem like it triggered some bands.
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There was one report of an individual who got banned from resi because they were absolutely spamming to get reservations to restaurants.
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>> And there was another example of somebody who was at the US Open was on the fan cam and then wanted footage >> and uh as the user experience would have been absolutely incredible, right?
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You're sitting there and you're like, "Hey, I appeared on the screen for a moment.
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Can you can you go and find this?"
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I've had that idea so many times like, "Oh, go find someone on the on the on the fan."
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>> But I think what Instinct was doing in the background was being absolutely relentless and it seems like it was reaching out to hundreds of people aggressively, you know, following up, >> emailing the media contact, but they did wind up getting the video.
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Yeah, it worked >> and it was mutually beneficial.
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And you could imagine if the other side has agent intermediation and filtering and can process things that are spamlike, but there's actually a reasonable action to take that could make it through a filter and not actually annoy anyone on the other side.
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So that was a very that was probably a glimpse into the future and like a cause for optimism.
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I could see I could see that being um uh popular.
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But people are doing all sorts of stuff.
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The the classic example is like go save money, get refunds, do that sort of stuff.
22:50
But people are are having fun fun with that.
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Um people are so many so many demos.
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Uh this 3D website that pulls apart the male anatomy into 200 2,234 modeled pieces.
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I shared this with a friend who I was trying to like explain in one video uh what to get like their wheels turning.
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I think this is a good example.
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Um, I wonder how much of this was like individually modeled versus pulled from an existing model and then just animated, but uh certainly works certainly works well.
23:23
Um, yeah, I wonder uh oh, Anish made a game that's fun. Uh, Astra's Opus 4.
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5 for games made Contra but photo realistic this weekend.
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Link to play below and it's uh it's up on Versell.
23:38
Um I wonder if we will get an actual boom in um in Steam.
23:44
It feels like Steam will be uh going through something similar to the uh the Kindle direct publishing store where they where they will be flooded with inbound.
23:55
Didn't we see this with the app store too where there were like a disproport like like the number of of app store submissions for Apple like 10xed >> totally overwhelmed their systems >> but no real breakout apps like the top of the app store is still like Chad GPT and like free money or whatever.
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>> Yeah, it's evolved a little bit.
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The the company that I'm confused that's been consistently in the top 10 is this company Vinted. >> What's Vintage?
24:22
>> Pre-loved marketplace.
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Buy sell and buy secondhand clothes.
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People are buying clothes. It's true. Shopping app. Everyone needs clothes.
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So >> big TAM, >> you make it to the top of the store.
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Um, but yeah, like the like you'll be able to vibe code a game.
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You'll be able to get it on Steam or, you know, in the app store.
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How do you get the distribution flywheel going?
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How do you innovate to actually break through?
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How do you make something that, you know, goes viral gets traction?
24:47
Because the like the the long tail is going to get a lot long lot longer. What do you think?
24:52
I I feel like for a lot of these games though, you should just put them on keep like keep them on web because it's much more accessible. Not everyone has Steam.
24:59
You have to actually download like a >> I feel like web games are still like not that fun.
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>> There were some web games I was playing this weekend.
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>> I played under Did you play more web games this weekend or did you play more Oculus VR, MetaQuest VR when you had the VR headset for an unlimited amount of time, but let's call it a weekend. Uh, okay.
25:23
I was probably playing more VR. >> VR?
25:27
>> I was playing Call of Duty.
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>> You played Call of Duty in VR? >> Yeah. >> How How long? Like a couple hours?
25:31
>> Yeah, probably a few hours. Not bad.
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>> I But I was playing Well, when I was making a game, too, this weekend on Astra, I I spent a lot of time. >> Yeah.
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>> So, does that count as playing the game? >> No.
25:40
>> Can you drop it in the chat for everyone to play?
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to play? I think I think uh I mean I I I I do think that playing a game that's uh more you designed yourself or for a small group chat it's the same thing as the images like the AI images I generate are not broadly beautiful they're not going in the MoMA but like they will
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often be funny to me and three other people right >> yeah low TAM but that's the beauty is that with lower cost you can go after lower TAM opportunities and so I mean this happened uh what a couple months ago know somebody sent us I mean Jeremy Gon simulator is the the classic example
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someone sent us Jeremy Gon simulator version two which was very low TAM in the sense that it was just in jokes with me and a couple friends uh and and uh and the long tale of these things will will continue to flourish and then of course people will use them in you know
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real businesses built on IP built with distribution >> you know what time it is John >> what time is it time for an ad console >> console builds AI Agents can automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. >> It's trailer time. >> It's trailer time.
26:50
>> Okay, it's trailer time.
26:51
>> We got two trailers that hit >> the timeline.
26:54
Let's start with Nathan Fielder. >> Mhm.
26:57
>> And his new film featuring none other than Elizabeth Holmes.
27:01
>> Elizabeth Holmes filmed before she went to prison.
27:04
>> I can promise you that. >> A24.
27:08
>> I don't have anything to deceive you on.
27:09
Of course, I'm not deceiving you.
27:12
I'm engaging with you as a human being. Why would I deceive you?
27:20
There's no there's no reason for me to do that. >> Okay.
27:29
>> The acting is so good. >> Okay. Good shot.
27:45
How long is this being real right now? >> Always being real. The team is stoked. Looks beautiful. good sound design.
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>> Uh saw a post somebody saying it feels like I'm living in a simulation because this media product is like perfectly >> with you would think that you would you would think that a movie like this wouldn't get made by >> I don't know A24 specifically because it feels like the TAM is just like >> like 20,000 people but but in >> the Theo story was really big.
28:31
Yeah, >> she was on the cover of Time magazine, I believe, and cover of major magazines.
28:37
Uh, it was all over the news when it happened.
28:39
>> No, it it's a lot bigger than you would.
28:41
>> The John Keroo book is just a fascinating read. It's a real page turner.
28:45
And so, I think a lot of people read the book.
28:47
The uh the the the adaptation of the actual playby-play story, not the documentary, but the what do they call it? Biopic, I guess.
28:57
Um, that I think did not break through in the same way.
28:59
But uh it certainly like continued to elevate her persona and then the the posting has been like kept her relevant.
29:06
Like there's a >> Yeah, there was some speculation that maybe it was Nathan that got access to the account.
29:16
>> I completely disagree with that.
29:16
I do not think that's all.
29:18
I think that would violate some tenant of what it means to do a documentary.
29:23
I mean, Nathan blurs lines all the time in terms of how he interacts with his subjects.
29:28
Um, so it's certainly possible, but I just don't I just don't think that's reasonable at all.
29:34
I I think they're her >> How much do we know outside of the trailer though? Like we don't know.
29:39
>> Well, this was leaked uh something like a year ago from a journalist who got the story and it was widely denied that it was happening and uh he was very upset that he wasn't getting enough credit for being correct here. he ultimately was.
29:52
But yeah, all we know is that they filmed the documentary in the leadup to her actually going to prison after sentencing.
30:01
There was a pretty large gap between before when she had to report to the prison. She gets out in 2030.
30:05
So coming up three years, four years away.
30:11
Um and so uh I believe even in a week you can get a lot of footage if you're spending the full, you know, every day with someone.
30:19
And then there were a number of visits to the facility by Nathan that were recorded, probably talking through glass or talking at a table, something like that.
30:29
So I think some flexibility there.
30:30
Maybe some phone calls, maybe some correspondence in the aftermath.
30:34
But um uh we don't know what I'm thinking. >> What? >> SPF Nathan Fielder. >> Sequel to this one. >> Yeah.
30:43
>> This just becomes like a >> The problem is that he's already in jail.
30:46
So the the question is just what else does Nathan for Nathan Fielder have in the can because he's obviously thinking years ahead since he filmed that exact scene in I believe 2022 or 2023 and so who knows there there's a rumor that he's secretly running a like a boy band right now.
31:08
There's this rumor that that there's a boy band that's popular on t this is real that's popular on Tik Tok that's entirely invented by him as a boy. Yeah.
31:18
Are you familiar with this? >> Really?
31:21
>> I thought you were going to say he's Nathan Fielder is SD kit. >> Uh yeah.
31:28
Um the So yeah, I don't know.
31:28
I mean we'll we these projects will emerge and obviously they're taking longer and longer because they're bigger they're bigger films now.
31:37
But >> yeah, after the rehearsal, >> it was hard to imagine how he would one up himself. >> Yeah.
31:44
>> And it feels like he may have done it. >> Yep.
31:47
>> He found a new tall mountain.
31:50
>> We're still stay with us in the trailer zone.
31:52
When we come back, we're going to be talking about artificial.
31:56
>> Let me tell you about the New York Stock Exchange.
31:58
Want to change the world?
32:00
Raise capital at the New York Stock Exchange. Just do it.
32:05
Pull up artificial >> artificial >> trailer dropped just this morning.
32:19
>> What is the image of the future that you see? >> Wait, pause. Was that a Valkyrie? >> Yeah. >> Okay, continue.
32:32
So, the visuals are already incredible. >> They They really are.
32:38
I'm pretty sure that's a Valkyrie. It might be a Vala. >> Is that Lucas Singer? >> No, >> no, no, no. >> No way.
32:44
>> No, >> no, because you can see the um the suspension >> that that front section. >> Okay. >> Anyways, continue.
32:54
>> What is the image of the future that you see?
33:01
We've created a machine that will solve the world's problems. >> We don't teach it. >> Gate check. Gate check. >> You nailed it. >> Gate check.
33:10
Oh, the gate >> for sure.
33:14
>> We open Pandora's box together. The future's inevitable. Countries will fall.
33:22
Industries are going to collapse.
33:25
>> The voice is still Eduardo Sverin.
33:29
But the styling and the crazy thing is I have that exact backpack.
33:31
You >> get to be the ones.
33:34
>> I think I got it recommended by MKBHD >> to shepherd people in to this new world. >> Lots of cameos.
33:44
Not cameos, but I'm so excited to see it.
34:01
dramatic >> dramatic >> be interesting.
34:02
It'll be interesting to see the the takeaway people in the chat are uh back and forth. Is it too soon? Is it unnecessary?
34:10
Is it going to be uh something that like the social network is divisive but also like it's oddly inspiring to a certain cohort of entrepreneurs? Uh we'll see.
34:21
We'll see what the reactions are. >> Yeah.
34:24
Do you think that was uh do you think Hollywood took away any lesson from the social network in that they were trying to frame Mark Zuckerberg as this like generally, you know, uh troubled person and then a lot of people came away feeling like, wow, I want to be like Mark Zuckerberg. >> Yeah. Sort of a Yeah. Yeah.
34:44
unintended consequence of it. I don't know. Um I don't know.
34:50
No, I mean they're going back for a second second scoop of the ice cream with the social network, the social reckoning.
34:55
Is there a trailer out or just images?
34:57
I think I think we saw that, too.
34:59
Um, so it'll be interesting to see what uh what happens there.
35:03
>> But get your tuxes ready going back to back artificial social reckoning and then capping it off.
35:11
>> You can see everything. >> Yes.
35:12
And then also uh the uh the to catch predator movie.
35:18
That's going to be a good one, too. >> Yeah.
35:21
Outside of tech tech world.
35:22
>> Yeah, I guess you're right. Yeah.
35:24
>> But still uh triple feature. >> Yeah.
35:26
It just feels like it's a it's a year of like niche movies that I expect to be breakouts.
35:31
I guess like along with like Back Rooms and Obsession and these two movies and then the documentaries.
35:39
There's a lot of things that are like oddly specific, but uh I would expect they do well, but I don't know. We'll see.
35:46
The Social Network did very well at the the box office.
35:48
So, >> and while we're at it, Yeah.
35:51
>> Let's stay in the trailer zone and let's pull up The Social Reckoning. Okay. The official teaser.
36:00
>> Tyler >> Colbertson is calling it pure cinema. >> Pure cinema.
36:06
But I am I am here to help Facebook, not hurt it.
36:10
Okay, >> you send me a message.
36:11
What would you like to talk about?
36:18
>> The chairman gavels a session to order.
36:22
You'll read your opening statement, which we'll skip past for now.
36:24
That's a separate session. Which one is this about? >> Questioning.
36:29
>> I don't I don't think this is based on the politics.
36:31
It's not Cambridge analytics.
36:34
It's the Francis Hogan >> and your occation >> teenage girl whistleblower thing, which honestly looks a lot different in the backdrop of the addiction trials.
36:45
>> I wonder if they were trying to get this out before the trials. >> Hang on.
36:48
I don't understand what you're saying.
36:49
>> Aren't you a tech reporter?
36:51
>> Is >> these guys are counting on the next round of congressional testimony to make you likable, Mark.
36:56
I'm happy to lend a hand, but I think you're doomed.
37:03
This company and that guy are playing an unprecedented role in our lives.
37:10
>> The fire hose of bad information you are injecting into the air supply is becoming jet power.
37:14
>> I'm a free speech absolutist.
37:14
I'm not the one who's lying and I'm not stopping them from seeing someone who is.
37:21
>> Anxiety, depression of teenage girls got worse as a result of time spent on the platform.
37:26
>> Senior leadership knows and is doing nothing.
37:29
>> I know there are easier enemies to make.
37:30
The mafia would be an easier enemy to make.
37:34
So what would you need >> to stand up the story? The internal documents.
37:37
>> This is a material violation of my NDA.
37:39
>> We're twice as big as the biggest country on earth.
37:40
We're not frightened of Congress.
37:42
We're post government around here. Please.
37:43
Who is that supposed to be?
37:46
>> Please let me poke that.
37:47
>> We have 102 hours to get everything.
37:50
>> She's going to get sued into small pieces.
37:52
>> I don't want to be made an example of by a guy with unlimited resources.
37:55
>> H I promise you, is >> Yeah.
37:57
So Chad is calling it out, but I don't think that I think this one >> I think this one's going to flop out of a dorm room anymore because of the lack of well lack of supercars and this is just not top this story is no longer top of mind. >> Sure. >> Yeah.
38:14
People want to hear about like the talent wars.
38:16
They don't want to hear about like this kind of stuff.
38:18
>> They do the talent wars.
38:18
Al if there's no Alex Wang character, I'm not I'm not paying good money.
38:24
SAS chain says, "Ooh, technology so scary." >> Yeah. I don't know.
38:33
Yeah, they I mean they should do more tech movies.
38:35
Maybe uh maybe Ces says it will flop because no Brazilian jiu-jitsu.
38:40
Yeah, this was in the pre >> That's true. Make it in the script. Yeah. UFC.
38:46
Uh, >> if there's the the social network 3 and all the scenes where Zach is talking in the middle of >> how how is it 2026 and we don't have a Salesforce movie?
38:58
>> Seriously, >> like the the the comeback, the SAS apocalypse >> or at least a documentary on the relationship that he has with the dolphins. >> That would be great. That would be great.
39:07
>> And the and the wildlife generally. >> Yeah.
39:08
I'd like a Crowdstrike movie.
39:08
I'd like a MongoDB movie. Let's do it. MongoDB.
39:13
What's the only thing faster than the AI market?
39:15
your business on MongoDB.
39:17
Don't just build AI, own the data platform that powers it. >> Here's a concept. Dolphin Force. How one man tamed. >> It's a good story. >> Wild dolphin.
39:28
>> It's maybe the best origin story of a tech company ever.
39:31
I don't know if there's a better one. It's the best.
39:35
It's just pure bliss, you know, pure pure pure positivity.
39:39
For those that don't know, >> spite company, >> Ben off famously conceived the vision for Salesforce in 1999 while swimming with a pod of roughly 100 dolphins off the coast of Hawaii during a sbatical.
39:52
Feeling one with the pod, he envisioned cloud delivered enterprise software, leading him to quit Oracle and secure 2 million in seed funding from his mentor, Larry Ellison. >> Yeah, >> incredible. >> Be great. Be great.
40:05
Anyway, uh in other news, uh lots of craziness in the AI world, lots of new models, but the jobs apocalypse has been officially postponed by the economist. An AI jobs boom is here.
40:21
And uh people have a wide range of takes on this. Is it just postponed?
40:25
Is it permanently postponed?
40:28
Uh Kevin Bryan summed it up well. He said, "I am shocked." Shocked.
40:32
So he's being sarcastic, of course, shocked to find out that a productivity enhancing investment supporting technology is good for workers.
40:41
Knowing nothing else, this should be your prior because this is how productivity and competitive markets almost always works.
40:46
A new technology comes out. It supports investment.
40:49
It enhances productivity.
40:50
Everyone hires to go after all the all the different uh battles.
40:55
But the economist breaks it down in a lot more detail with a bunch of charts and a bunch of data.
40:58
Oh, they say perhaps AI will eventually make many humans unemployable, but there's no sign of it yet.
41:05
On September 4th, the Bureau of Labor Statistics reported that the American economy added 162,000 jobs in August, far above expectations.
41:13
The unemployment rate just 4.
41:15
1% lower than almost 90% of months over the past 50 years.
41:23
Young workers, often cast as AI's first victims, are holding up remarkably well.
41:29
The gap between unemployment among 20 to 24 year olds, and the overall rate is close to a multi-deade low.
41:35
Some companies and workers are being severely disrupted by AI.
41:40
Hiring professional and business services is running 10% below the average from 2015 to 2019.
41:44
Tech giants like Microsoft and Meta are trimming headcounts as they reorganize their businesses around the technology.
41:51
Smaller firms such as Block, which is sort of a crazy mog, smaller firms, but it is smaller than Microsoft and Meta.
41:59
Block, the owner of Square and Cash App, and into it, the maker of Turbo Tax and Quickbooks, are replacing people with bots.
42:05
American companies have announced some 16,000 AI related job cuts a month on average so far this year, according to Challenger Gray Christmas, an employment consultancy.
42:15
What a funny name for for a consultancy.
42:17
Um but AI related layoffs get lost in the churning job markets where so you remember that number.
42:25
So 16,000 AI related job cuts a month in a typical month the US workforce just churns 1.
42:35
7 million jobs and then they add 1. 8 million jobs.
42:38
So there's net gains, but you're looking at less than 1% of the layoffs that happen in the economy or job losses or firings.
42:48
Uh less than 1% is AI AI related, which is what the economist is pointing out here.
42:56
Um and the evidence so far is that AI is already creating a lot of jobs to replace those as to replace those as it has destroyed.
43:04
The vast sums pouring into data centers and power generation have set off a race for construction and infrastructure workers.
43:09
AI startups are hiring like there's no tomorrow.
43:11
Uh incumbents are racing to keep up with new AI roles and making some workers more productive.
43:17
Uh AI may be increasing the demand for their services.
43:20
Add it all up and the economist estimates that AI so far has created around 1 million new jobs in America.
43:27
That easily exceeds the roughly 200,000 layoffs attributed to AI since mid2023 and it appears more than enough to offset weaker hiring in many back office roles.
43:38
Uh America's AI infrastructure splurge has created many of them.
43:43
The spending on the kit needed to make AI run from chips and servers to data centers, cooling systems and power is roughly $500 billion a year above what it was in 2022 when the world got to know Chhat GPT calculates Goldman Sachs a bank.
43:57
Thank you, The Economist.
44:00
Uh, data center construction alone is proceeding at an annual rate of more than 75 billion dollars, nearly 60% higher than a year ago, according to Census Bureau data.
44:08
That building spree requires armors of workers, electricians to wire them, HVAC specialists to stop racks from overheating, grid engineers to hook them up to the power supply, and technicians to install and maintain the machines.
44:20
The hiring boom is visible in the numbers.
44:23
The economist tracked five industries at the heart of the data center buildout.
44:26
From electrical contracting to equipment manufacturing, since 2023, employment in them has risen by roughly 320,000 more than broader construction and manufacturing trends would suggest.
44:37
The BLS expects utilities to be the fastest growing big sector between now and 2035.
44:44
Not all those jobs owe their existence to AI.
44:46
Grid upgrades and other factory building matters too, but lots of them do indeed.
44:50
Uh, a jobs website finds that data center vacancies have more than doubled in two years as job postings overall have fallen.
44:59
Um, LinkedIn a social network for stvers. These are so funny. >> Just fire.
45:06
>> Goldman Sachs, a bank.
45:06
LinkedIn, a jobs website, a social network for strivvers, estimates that nearly half a million data center jobs were created between 2023 and 2025 in America.
45:16
The scramble for workers is showing up in paychecks, too.
45:21
who indeed finds that installation maintenance jobs at data centers advertised wages about 40% higher than comparable work elsewhere.
45:27
Official wage data tell a similar story.
45:30
In the year to June, average hourly earnings rose more than 13% in electrical equipment manufacturing and nearly 8% among electrical contractors.
45:40
Even with the pay gains, workers are still not easy to find.
45:43
On a recent visit to a transformer factory, Donald Livvens of the National Electric Manufacturers Association asked the company's chief executive what help she needed most.
45:52
"Can you come in here and help run one of our lines for me?" she replied.
45:57
"Uh, it's not just hard hats that are proliferating.
45:59
AI is also creating a new class of white collar jobs.
46:03
Engineers build the models.
46:03
Data annotators Tyler's clapping for the white label for the white collar job creation.
46:09
Data annotators label their inputs and judges and judge their answers.
46:14
Forward deployed engineers adapt them for customers and newly minted heads of AI decide what companies should do with the technology.
46:21
And there's some interesting reporting in the journal about uh Google and Accenture teaming up to do more forward deployed engineering.
46:28
Uh they they're deploying some I think there's a thousand people on this one team.
46:32
That's just an example of like new roles for AI diffusion.
46:38
Some of these roles barely existed until recently, says the economist.
46:42
Many are quickly growing in number.
46:44
Postings for heads of AI, AI engineers, and directors of AI have roughly doubled since 2023, 2024.
46:49
The numbers are starting to add up.
46:54
Preliminary research uh by economist Gad Levvenon at the Burning Glass Institute uses the research outfits career history database um to identify jobs that would not exist without AI, whether at AI native firms or because they are AI specific roles at other companies.
47:11
He reckons roughly 1% of PE professional jobs are now AI jobs on the order of 1 million positions in America in computer occupations and life sciences including researchers using AI to discover new drugs.
47:25
The share is four and four to 5%.
47:28
LinkedIn's own analysis points to roughly 640,000 new AI specific jobs between 2023 and 2024. So Jevans paradox.
47:37
The economist tracked employment in professional occupations closest to the AI boom, engineers, software developers, mathematicians, and data scientists, and compared their growth since 2022 with professional employment overall.
47:50
These roles have added roughly 730,000 jobs above the trend in recent years.
47:55
AI will not have created every single one of them, but it almost certainly created quite a few.
48:02
Third source of job comes from productivity gains.
48:04
AI allows lawyers to draft contracts faster and analysts to comb through financial filings in minutes.
48:10
If higher productivity lowers the cost of professional services, it is possible that demand for them can rise enough to create more work overall.
48:18
Um, Nikia Beer was talking about this this weekend.
48:22
He used Astro to create three different potential deck remodels, redesigns, building uh expansions to his home.
48:32
And uh it was interesting because it's a lot of work that you could say is like oh that's going to displace an architect.
48:41
I don't think the models are at a place where you would trust a deck that's built in Blender from even the best model.
48:48
Uh I was finding in my Blender modeling tests a lot of you know misaligned beams and not things that weren't quite right.
48:56
But in terms of visualization, in terms of getting excited about a project and getting to that next stage of saying, "Hey, okay, I have a really solid vision here, I can imagine what I want to do.
49:07
Let me actually go and do that."
49:09
Uh there's this odd diffusion that happens in the economy.
49:14
I was talking to Sager and Jetty about this, the credit card effect where credit cards had a big effect on the economy in a very very boring way.
49:23
They just slightly lubricated the machinery of of the >> global commerce ba >> global commerce basically.
49:29
So you're just like, okay, if I if I send a wire, I'm not going to be able to get the money back, but if I put down my credit card and it doesn't show up, I can probably get a charge back.
49:39
And so that instilled just a little bit more confidence that what you're buying is accurate and uh and it and it enabled more commerce, right?
49:47
And so the same thing uh is is starting to be true here where people can say, "Okay, I'm ordering shoes.
49:54
Let me find the shoes that fit me perfectly, that are the right price, that will come on time, that are uh from a reliable manufacturer, aren't going to fall apart.
50:04
And if you get a very solid report back that gives you confidence, you make that purchase just a little bit sooner.
50:11
And if everyone is doing that, it it it winds up speeding up the machinery of global commerce, which is incredibly boring, but incredibly valuable. >> Totally.
50:22
>> Because you're >> Yeah.
50:23
The one one of my favorite examples is you you were looking at a number of different houses, all of which were not necessarily in the condition where you're like, great, I want to, you know, move in here. Yep.
50:34
>> And you just dropped the Zillow links into Codeex and it made you an entire website that you could walk through with before. Yep.
50:42
>> Before the current state and exactly how they would evolve based on your stylistic preferences. >> Exactly.
50:48
So oftent times you'll like a fully remodeled house will command a 20% premium, but you can get sort of sucked into okay well the newer the one that's already been through the remodel.
50:58
It's just visually more striking.
51:00
So you're like, "Oh, I want to necessarily pay up."
51:03
when in fact you might want to buy the cheaper house, do the remodel, and then wind up with the same end product and maybe capture some of that value yourself.
51:11
And so there's a lot of different places uh you know, and a lot of times the the conclusion is very underwhelming.
51:18
I mean, we were talking to Nick about this where he was taking a picture of his room and I saw a lot of people doing this online.
51:22
Take a picture of the room, make sure I've decorated it properly, that the bed is in the right spot.
51:28
And I think the result for you was like, "Yeah, it's basically as best you could do." Like, "Good luck, dude."
51:33
Uh, which is hilarious, but at least it gives you confidence that, okay, yeah, like I really shouldn't order a bigger bed.
51:41
I the bed I got is the right one.
51:43
And if you do that on the way in, you you you you wind up uh moving things faster.
51:48
Uh, we covered we covered Navier Stokes.
51:51
I don't know if there's more to cover there.
51:53
The chat's asking about it.
51:55
We we covered it at the top of the show.
51:57
Um, I mean, we also have Greg Brockman joining the show, so we'll ask him about advances in math, what's going on with Navier Stokes, the back and forth there.
52:06
He's joining at 1:10 uh p. m. Pacific. So, stay tuned.
52:09
Uh and we have Scott Woo as well who is an IMO gold medalist and a fantastic mathematician.
52:15
He can of course comment about this because he at Cognition is in a unique position of both being incredible at math but also like Cognition's whole business is not in the theoretical math space. It's in AI diffusion.
52:30
It's in getting work done in the enterprise for real companies.
52:35
And so I think he's in a unique position to both ground the conversation around what it actually means.
52:41
How impressed is he by these solutions um and then also what does it actually mean for you know Boeing like will they be able to make more planes more efficiently more reliably like that is a valuable uh thing that we actually want to see in the real world.
52:58
So, >> uh, something happening in the real world.
53:01
Uh, former F1 CEO Bernie Ecklestone, uh, was stopped in Portugal at the airport for, uh, >> bringing in a shotgun from Switzerland.
53:13
>> He's 95 years old, and this is actually the second time he's been >> stopped uh, at an airport.
53:18
Uh, in 2022, he was arrested in Brazil for illegally carrying a gun while boarding a private plane to Switzerland. Mhm.
53:27
>> Uh and was ordered to pay a€,000 fine to local authorities.
53:30
So rough weekend for Bernie.
53:34
Um but at this point I I think he's like sorry I'm I'm 95.
53:39
I'm not going to stop bringing guns everywhere I go on on on planet Earth. >> I got to do it.
53:47
Well, let me tell you about Codeex.
53:48
Codex is a powerful workspace for getting work done with AI agents.
53:52
Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to >> says just let grandpa carry his gun. That's all.
54:04
>> Um, >> in other news, Wimbledon does not plan on providing credentials to influencers next summer in hopes of avoiding the issues that affected this year's US Open. >> What were the issues? >> We didn't influence.
54:14
>> Players have called for spectators to follow the sports etiquette after matches were interrupted.
54:17
They specifically call out taking a picture of the court and putting logos all over it using AI and then posting that on X and getting a couple hundred likes. >> Looking at you, Nick. >> He's locked in. >> Looking at you. >> He's working.
54:32
>> We're We're just making jokes at your expense. Don't worry about it. You're good.
54:35
Um >> uh what was there anything specific that was tied to this?
54:42
>> I I think it was a number of issues.
54:42
Uh there were also complaints of of um one of the players was complaining about the smell of um marijuana really in the stadium >> uh which is uh interesting.
54:54
>> Um >> but uh >> but yeah, next year Tyler will be going to the US Open in disguise.
55:02
>> So >> full Hollywood makeup.
55:03
>> Yeah, you can look forward to that.
55:05
>> Yeah, I wonder what what what are they going to do?
55:06
Just not give free tickets to influencers or actually block people who are influencers?
55:10
I think what was happening is they were probably giving like media slash trespasses to influencers.
55:16
>> I think the influencers were like doing too much stuff like getting in the way of fans creating scenes because they're sort of like running around with like gonzo film making equipment as opposed to like something that's a little bit more cordoned off and like polished.
55:29
>> It's different when you have a red carpet and you're doing uh you know proper interviews that that that sort of lands a little bit better.
55:34
Um anyway, uh Sheil Monot is calling for a revisitation of the Catrini piece.
55:42
Agents become the default demand side interface and transfer economic rents from incumbent intermediaries to whoever controls the agent, which does seem correct.
55:51
Um and so with instinct, uh who should you be long, who should you be short?
55:56
Um there's an interesting dynamic where um anytime something happens in AI, there's a lot of people that go I I think Buco uh post uh pointed this out that everyone will go and ask AI, okay, what are the longs, what are the shorts and so that creates an amplification in the market.
56:13
People are oh piece together this new trend I want exposure to this trend and so things get overheated much more quickly.
56:19
Um but yes, this idea that uh if it's a if it's a restaurant booking platform and your AI agent can call the restaurant and get a booking just as easily as they can go through a platform.
56:31
Uh now resi has exclusives so that creates more of a complex scenario but by default if you can just write an email or make a phone call or send a text message an AI agent should be able to disintermediate those platforms.
56:43
But that's not true for Uber.
56:45
That's not necessarily true for Door Dash where there like it's very difficult to find a person to go and pick your food up or pick you up personally.
56:54
Uh because they need to be very close if you want the car right then.
56:59
So uh Sheil says how after you in an agent disintermediating world completely depends on how much you control how much control you have over supply.
57:09
To answer your question buo you may not have a choice in whether you allow bots.
57:13
Expedia can book agent can block agents, but it doesn't control the hotel inventory.
57:17
If Expedia stops letting agents book, they'll go through booking. com, Google, or direct.
57:21
Resi has more leverage via exclusives.
57:24
And I'm sure Expedia has some exclusive program, I imagine.
57:28
Uh, but if agents become a major source of diners, restaurants will want to be bookable via agents and reservation systems and support agents will win supply.
57:36
Someone will come along with a cheap direct booking sell.
57:38
AI can disintermediate discovery and customer ownership, but resi can survive.
57:42
But can resi survive as the restaurant's reservation infrastructure.
57:46
Uh, but that's a much smaller rent pool unless the inventory network remains differentiated.
57:52
Uber has much hard is much harder to disintermediate.
57:55
It actually controls a valuable network of drivers, dispatch, pricing, and payments.
57:59
Why would they allow agents is basically they can afford not to.
58:02
uh after an AI agent takes over your consumer interface, how much economically essential stuff are you doing that only you can provide for Expedia? It seems tough to me.
58:12
So Sheil is worried about Expedia.
58:14
Anyway, was there anything in the chat you wanted to run through?
58:17
Because we have our next guest joining in just a few minutes.
58:19
We have Dan Wright coming back on the show from Armada building modular AI supercomputers in a shipping container.
58:28
A supercomputer in a shipping container.
58:30
>> Uh >> Apple's coming out with new phones.
58:32
We're getting a folding phone probably this week.
58:35
>> It's going to be exciting.
58:37
>> I think it'll sell well and it's been a while since there's been a visually differentiated Apple product.
58:41
So >> yeah, I think it's a pretty easy sell.
58:44
Hey, you use this thing for three to eight hours a day or if you're Taylor Loren's 18 hours a day.
58:51
Would you like a bigger screen?
58:55
I think a lot the answer for a lot of people.
58:56
And would you like to have some differentiation versus your peers that have just one simple screen?
59:03
>> Yeah, >> I think a lot of people are going to opt into that.
59:06
>> I wonder how it's going to look.
59:06
I've seen a lot of like leaked renders.
59:08
>> It looks a lot of the renders look squareish. >> Yeah. Not good. >> Just throwing me off. >> Yeah.
59:13
Not I I feel like they they're going to surprise us with something.
59:17
They've they've it feels like the the news and the facts and things that can go over text message sort of leak out.
59:26
And Mark German is like I saw a stat from Eric Newcomer that Mark German has an order of magnitude more scoops than the next biggest journalist on tech meme or something like that. Yeah.
59:37
>> He's like the power law tech freak out seriously.
59:42
>> Um but it feels like people might >> journalistic force >> discuss things with Mark and say oh yeah we're not working on a car anymore keep that off the record but I'm letting you know and he'll report it out.
59:53
But people will stop short of sending him an image of the new phone.
59:59
And I think he's been pretty good about that.
1:00:02
>> It was actually Josh over uh who says, "We don't talk enough about how Mark German is the most cited, most market moving tech journalist by nearly an order of magnitude.
1:00:13
>> The whole industry of Apple reblogs and day traders live off of his scoops.
1:00:15
It'd be like if LeBron won 40 championships."
1:00:22
>> That's a That's a really good post.
1:00:25
Well, we love Mark German.
1:00:25
Um, well, there's one more story we got to cover before we go into our guests.
1:00:30
A man drove a Ferrari Puro Sanguay from South America to Alaska.
1:00:35
This is a crazy crazy story.
1:00:40
Uh, this the transame race has been talked about a long time.
1:00:44
It's really really difficult with the Darian gap, the the the gap of like wild forest that exists between North and South America.
1:00:51
You usually have to uh put your car on a boat to get around that part and I think it still counts.
1:00:55
But it's still a very treacherous road, a lot of weather conditions.
1:00:59
If you break down, you might be very far from anything.
1:01:01
Uh but a man named MJ has taken a Ferrari Perway far beyond where most owners would ever consider driving one.
1:01:08
His goal was to travel the length of the Americas, taking the V12 Ferrari from South America all the way to Alaska.
1:01:16
He's now attempted the journey three times, putting roughly 800,000 kilometers on the Puro Sangway in the process.
1:01:23
His dog joins him for the journey.
1:01:25
Uh the first attempt uh ended after an accident.
1:01:28
He brought the car to a dealership in Santiago.
1:01:31
Uh on his second try, they made it all the way to Alaska.
1:01:36
For the third, he reversed course with an even bigger goal, attempting to set a record from Alaska to Argentina before a major road closure forced the run to end in just two days.
1:01:46
Through dirt, snow, and thousands of miles of pavement, the Purus has effectively become a long-distance expedition car with Rico, his dog, riding alongside him through it all.
1:01:57
What a >> heartwarming >> heartwarming story.
1:02:00
>> A beautiful ad for this naturally aspirated V12. >> For sure. For sure. >> Look at that. Look at that shot. So good.
1:02:08
>> Oh, I didn't realize it was a Chihuahua. That's funny.
1:02:10
That's probably a more convenient dog to have in a in a car for a really long You don't want a big dog that needs to stretch his legs.
1:02:15
You want the dog to be able to just run around the cabin, I think, if you're it's a good good road trip, I think.
1:02:21
Uh anyway, we have our first guest of the show, Dan Wright from Armada in the waiting room.
1:02:28
Let's bring him in to the TVP Ultradome. Dan, how you doing? >> There he is. >> I'm doing great. How you guys doing?
1:02:34
We're doing fantastically. Welcome to the show. Welcome back.
1:02:37
>> What is new in your world?
1:02:39
>> Walk us through the latest and maybe just uh since it's been a while, sort of reintroduce the the shape of the company, the mission, and uh where you guys have gone in the last year. >> Yeah.
1:02:51
So, Armada is the hyperscaler for the edge.
1:02:53
We build the infrastructure for the 70% of the world that doesn't have the big hypers scale data centers today. Mhm.
1:03:00
>> The mission of the company is to bridge the digital divide and make sure that we have AI everywhere, wherever we need it.
1:03:06
Uh but first, you got to have the infrastructure there.
1:03:07
And so that's what we're doing. We've been very busy.
1:03:09
We just raised uh earlier this year 230 million at a 2 billion pre.
1:03:13
Um we launched Gallion Forge 1, which is a factory with our partner Johnson Controls in Gilbert, Arizona, where we're now continuously manufacturing these modular AI data centers called gallions that we've built. Yeah.
1:03:28
How ho how is power usually solved for when you deploy these? >> Yeah.
1:03:34
So, a lot of times we're deploying them where there's already stranded power. >> Sure.
1:03:39
>> A good example of this is a couple of weeks ago I was in New York and we did an event at the New York Stock Exchange where we were uh sort of fast following on Jensen's announcement that uh compute is now an asset class.
1:03:52
It's a new asset class and um the New York Stock Exchange is actually making that now like something that you can invest in the same way that you can invest in electricity or other types of commodities.
1:04:03
Um and we were there with our customer in Norway called >> Fossafal >> that has tons of distributed sites all over Norway.
1:04:13
I'm actually going to be in Norway with them next week, but they also have them in Finland and in Sweden.
1:04:19
And it is largely renewable energy.
1:04:19
So it's 99% hydro electricity.
1:04:26
>> They can just plug in our AI factories and then scale up quickly.
1:04:29
And one of the things that um you know makes that easier is that we've recently announced some larger form factors.
1:04:35
Last year we announced Leviathan which is 2 megawatts per unit.
1:04:40
Um and when I was in New York we announced Orion which is our newest form factor.
1:04:45
That's 10 megawws uh per unit.
1:04:48
When I was, you know, launching Leviathan, everybody said, "That's great, but how do we scale up even faster?"
1:04:53
And so now Armonic can incredibly say wherever you have power, we can plug in and we're the fastest from 0 to 200 megawatts anywhere in the world.
1:05:02
>> Uh talk about why, for example, you know, one of these companies needs to have that compute actually at the edge and why it matters across different industries.
1:05:13
>> So one is latency and this comes up in a lot of conversations.
1:05:17
I'll give you another uh real world example.
1:05:18
We work with the state of Alaska. >> Mhm.
1:05:22
>> And they don't have the big hypers scale data centers there.
1:05:24
So the first data centers deployed were ours.
1:05:27
Um we did this last year and we're still working closely with them and kind of scaling up with them.
1:05:33
They had 28 hours of latency to process data from drones >> for emergency response for avalanches and floods.
1:05:41
Um, we also deployed last year with the Navy in the middle of the ocean very similar types of use cases where if you have a large distance between the source of the data where the data is being generated and then where it's being processed, >> the data sort of becomes worthless because avalanches and floods and threats and battlefield scenarios, they don't wait days or even minutes.
1:06:03
You have to be able to use the data in real time.
1:06:08
>> Another big drive driver of this is sovereignty.
1:06:10
Uh the the shorthand for our value prop is the three S's.
1:06:13
Speed, scale, and sovereignty.
1:06:15
And the sovereignty piece is really important.
1:06:19
There's this global trend that's going on around sovereign AI.
1:06:21
Everybody wants to be able to take the latest models, but they want to be able to fine-tune them to really sensitive data sets that they wouldn't send to the cloud and then um you know have like a sovereign AI infrastructure that they actually own and that's what Armada enables.
1:06:38
>> So yeah, speed of delivery.
1:06:38
Yeah, that makes a lot of sense.
1:06:40
Is hydro electricity under discussed right now?
1:06:44
Is there an opportunity there in America or abroad?
1:06:47
I mean, we talk a lot about solar where it feels like there there aren't as many like big winners yet or big like hot startups that exists in nuclear. That's very exciting.
1:06:59
I've, you know, we've heard about wind, but no one is really talking about like let's just do another Hoover Dam or something. Is that possible?
1:07:07
Are you optimistic about uh >> I think so.
1:07:09
I think I think it should be talked about more and I think in general stranded energy should be talked about more.
1:07:15
Um >> we're doing these projects all over the world as an example.
1:07:18
You know the the ners are playing in Australia this week and we're doing an event there uh with another partner called WindC that we work with there and they've got a huge amount of stranded wind and solar energy.
1:07:34
Australia's big in wind and solar.
1:07:36
Norway's big in hydroele electricity, but this is happening all over the world.
1:07:39
There's these stranded pockets of energy and they last year had to curtail 7.
1:07:44
2 terowatt hours of energy in Australia because the grid's completely overloaded, but they have this stranded power that we're just bringing the infrastructure directly to and then you can scale up into the hundreds of megawatts and then ultimately uh same with phosphol.
1:07:59
They'll they'll scale to over a gigawatt over the next few years and we can scale with them. >> Yeah.
1:08:03
How flexible do you want to be around uh like the actual chips that go into the systems?
1:08:11
Because when I hear latency, I feel like Cerebrus Grock, these like faster systems, there's Talis, which I think AMD just bought, where uh you're baking the weights on and you can actually get to a an inference speed for certain AI workloads that would actually benefit from saving a 100 milliseconds.
1:08:30
Whereas if you're putting a bunch of NVL72s in a data center, uh you're going to be waiting while it's cooking, >> right?
1:08:39
>> And the last mile is going to be negligible. >> Yes.
1:08:42
So again, it's all about speed, scale, and sovereignty.
1:08:45
And then giving the customer the choice.
1:08:47
So we say, okay, well, what workloads are you trying to run? >> Yeah.
1:08:53
>> And then based on that, you can sort of rightsize the the infrastructure to the the actual need and where they expect it to go.
1:08:59
And a lot of what our customers want to do is they want to try different things.
1:09:02
>> They want to try, you know, >> uh, obviously the the GBs, but now they're looking at the Beer Rubins.
1:09:08
They're looking at things from, >> uh, other, you know, chip companies as well.
1:09:12
And so the nice thing about our our gallions, again, we're manufacturing these.
1:09:17
It's not like construction.
1:09:17
And so as you want to try different things, we can just make, you know, quick iterations on the design, then ship them out.
1:09:24
So they can try different things and then what they like they just order more of and we scale up with the demand versus with a traditional data center. Yeah.
1:09:31
>> The downside is not just as we were talking about the power.
1:09:33
You got to figure out the power situation.
1:09:34
We take advantage of the power that's already there but what we also allow them to do is scale up with demand so that they don't overbuild or build the wrong thing.
1:09:44
How are you thinking about, you know, staying aligned to, I guess, like why and and how the company started and the focus around this edge compute versus the natural pull from the market where if somebody comes to you and says like, "Okay, now I want the 1 gigawatt data center and we think you guys can can do it like just running the numbers on that and and resource allocation.
1:10:04
And I imagine there's a natural pull to go bigger and bigger when uh and anyways I think that's kind of a >> good problem good problem to have but um will be interesting.
1:10:17
>> It was actually super simple for us because one of our company values is heal the customer's pain first.
1:10:20
We're like obsessed with customers and what their what their pains are and how do we solve those.
1:10:25
And so um the the kind of evolution of our gallion product line has all come out of conversations with existing customers where they've said okay I want to use your edge gallions the smaller ones say sub sub a megawatt for inference but then they came to us and said I also want to do fine-tuning of all these models latest open source models closed models my own models uh on these proprietary data data sets without sending them to the cloud.
1:10:57
And so what we enable is sovereign AI factories where they can do both.
1:11:03
They can take the latest models, open source models, you probably saw what you know Nvidia just did with hugging face and with poolside.
1:11:11
I think we're going to see a lot more around open source.
1:11:12
They can take models from the open AIS and the anthropics of the world.
1:11:15
Uh we can help them fine-tune those to these sovereign data sets and then push them to all the edge nodes to run.
1:11:22
And then you can do what's called federated learning. >> Yeah.
1:11:25
where you're actually fine-tuning that model on that data at the site and then you're using it to improve your core model and then pushing the updated model out to all the sites. >> Yep.
1:11:36
>> Which has the benefit of it's more cost- effective, >> it's more secure and it enables you to take advantage of lots of different models, experiment with different things and see what works. >> Yeah.
1:11:49
>> Well, congratulations on the progress.
1:11:50
Thank you so much for coming on. >> Great update.
1:11:52
>> We'll talk to you soon.
1:11:53
>> Great to see you guys. >> Great to see you.
1:11:53
Congrats on the progress.
1:11:56
>> Let me tell you about Shopify.
1:11:56
Shopify is a commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. Who do we have next? Jordy >> the Souvenator.
1:12:09
>> We got Eric Seer, the founder of Mobile Dev Memo live with us on TBPN on YouTube, not on Netflix yet.
1:12:15
Should we be considering switching teams?
1:12:19
Eric, just just just for for what it's worth, every time you you you come on the show, I call John afterwards and I'm like Eric Eric Eric's in my Eric's in my top three alltime guests on the show.
1:12:30
It just fires us up to uh talk with you every time. >> Good to see you.
1:12:36
>> And it's great to see you.
1:12:37
>> Yeah, good to see you.
1:12:37
Uh so I I told my wife >> I'm going back on TVPN >> and she said, "Is that the show with the two handsome hosts?"
1:12:44
Oh, and I said I said, "Yeah, but when I'm on there's there's three handsome men." >> That's right.
1:12:54
>> And it was like that meme with Natalie Portman where she's looking at the guy and I was having to say, "Right, >> right.
1:13:01
>> There's like three handsome guys on the show." Right.
1:13:02
So, I I think you're ready for Netflix.
1:13:04
I think Netflix would be happy would be lucky to have you.
1:13:08
>> But what would the uh what would the economic dynamic be?
1:13:10
cuz Netflix and YouTube are both going for exclusives now.
1:13:14
What's actually playing out?
1:13:14
How much are they at each other's throats?
1:13:19
How much are they going to converge in the way that like Tik Tok and Instagram and YouTube are all converging?
1:13:23
Is there going to be another convergence or is there or is there actually a stress point there where YouTube is trying to be both Instagram and Netflix and they maybe can't do both? >> Well, yeah.
1:13:34
I mean, they are converging.
1:13:35
So, this is a really fascinating dynamic right now in streaming.
1:13:36
Um, I've been following it with a series called Netflix's YouTube Opportunity for roughly a year, right?
1:13:42
And so, >> um, what I wrote about first was they brought Miss Rachel on, right?
1:13:46
And so what they did was they brought Miss Rachel on, but they didn't give her, uh, they they didn't, uh, they didn't buy new content, right?
1:13:54
They just paid her to bring her existing content over.
1:13:55
So, you've got this proven base of content that has however many billions of views.
1:14:00
I know my children probably account for some several billion, but you've got this proven case of uh, you've got this proven base of content where there's essentially no risk.
1:14:06
like you know there's an audience, you know it's popular um and you pay some amount of money to bring over this existing content.
1:14:13
So what's actually really great for the content creator too because they don't have to produce anything new.
1:14:15
They just have to chop they chopped up the existing content into like a season.
1:14:18
So they packaged it like a season.
1:14:20
Um and they also did that with Danny Go and they also did that with Mark Robber.
1:14:23
And so my point was look they've you know Netflix had been op they had been executing tremendously well for the past several years.
1:14:31
They had had they had commanded extreme pricing power, right?
1:14:36
The the premium service is going at almost 30 bucks a month in the United States.
1:14:39
Now they've been they've been uh the the advertising tier price has been tracking what I think is the Arboo differential to make it equivalent to the next highest tier.
1:14:46
So they've been doing a good job of maintaining that pricing power.
1:14:49
My sense is they did too good of a job, right?
1:14:51
And so they made it really hard to compete in the space and that pushed everybody to the bottom.
1:14:57
That made everyone take the exact opposite approach which is like, okay, let's go fast.
1:14:59
let's go free ad supported television.
1:15:01
Now Netflix has an even bigger problem on its hands, right?
1:15:05
Because they may have reached a ceiling with what they can charge. Certainly premium.
1:15:08
I don't know how much higher you can go than $30. Um there's not much.
1:15:11
They they've probably extracted all of the net additional subs they can from password sharing crackdowns.
1:15:16
Um now they're faced with, okay, we just have to bring in a lot of live events and sports.
1:15:21
Uh things like the Beyonce Bowl that uh you know and and the the um the January uh NFL games, it's really expensive, right?
1:15:28
And so, are you going to compete on content or are you going to go the opposite direction, race to the bottom and try to get UGC on there?
1:15:35
And I think that's probably what they're they're they're trying to sort of thread that needle because if you listen to Netflix's leadership, they say, "Look, we can never go pure fast because that would have a dealerious uh effect on the brand.
1:15:45
We're seen as a premium service."
1:15:47
But how can you maintain that when you see Roku and TB joining forces, right?
1:15:52
when you see all of the pressure that Amazon is putting on your business because Amazon is the identity spine for advertising across all of fast.
1:15:58
All of Fastct CTV is Amazon with these data deals doing all the providing all the identity for the buying, right?
1:16:06
And so I think they're facing like this opposite problem now where they had too much pricing power.
1:16:11
They pushed everybody in the opposite direction to go fast.
1:16:12
And now I think honestly if you believe the reporting that the New York Times did that they're going to be offering up these subscription bundles.
1:16:19
How can you not go fast and do that?
1:16:21
Are you going to be willing to accept paying $30 a month for a premium Netflix tier seeing content in your Netflix app on your TV and having it say and if you want this you have to pay even more to subscribe to this other channel. I wouldn't.
1:16:32
I think the only way they can do the bundling is if they adopt fast >> that Arpoo gap uh from the premium ad free tier to ad supported it feels like are I is there a reason why the gap doesn't make up the full $30?
1:16:49
Is there some economic reason or did they just get stuck in this weird place?
1:16:54
Because it feels like if they got even a little bit more juice out of the ad model, they could just offer a free ad supported tier.
1:17:04
But maybe that would create more churn because mentally you're going from $30 to $10 is different than going from $30 to $0.
1:17:12
But do you understand more of like what they're grappling with?
1:17:16
Did they get unlucky or is there something about the the structure of Netflix that would would would really make it difficult for them to do just a fully free and not supported tier?
1:17:29
>> No, I think it's just a reservation they have.
1:17:31
Maybe it's almost like a superstition, right?
1:17:32
I mean, keep in mind they were saying for the longest time they would never do ads.
1:17:34
Uh, you know, you Reed Hastings said like >> they always do. Yeah, >> they always do.
1:17:40
>> They always do until until they don't, right? Until they change it.
1:17:42
But like he I mean Reed Hastings said ads were like a blight.
1:17:45
Uh I said personalized advertising was a cancer.
1:17:47
Uh and so I mean you know then they changed the tune but I mean I think he said just that if I'm remembering the wording correctly but but the thing is like I think so there's there's three tiers, right?
1:17:54
So there's there's the it used to be basic.
1:17:58
Now it's standard with that standard and then and then premium, right?
1:17:59
So the standard uh is what they have to make up the arpoo gap with premium includes a lot of stuff.
1:18:04
Um and so maybe you can make the case, right?
1:18:06
For a high- income household it's worth paying for the higher uh streaming quality and the more uh the more devices that you can on board.
1:18:13
board. My sense is with standard though um that that revenue that arpoo gap is just they they just they just index it to the ads arpoo but the thing is like the question is like just internally what is the resistance to going fast and
1:18:25
my sense is it's that perceived quality that they would lose if they went fast but I mean what can the market moved in that direction they pushed the market in that direction and so I think they're going to have to capitulate. Have you
1:18:33
Have you been surprised that uh that Amazon Prime Video hasn't seen more UGC?
1:18:37
Because I was looking up randomly, what does it take to publish a film?
1:18:44
And uh you can you can submit to Amazon Prime Video that goes through a review process, but the the cost to submit is dimminimous and you can get a a video product up there, but it hasn't actually seen a ground swell.
1:19:01
And I'm wondering if that's because Amazon specifically has partnerships that that scratch that edge.
1:19:09
>> Yeah, I think that might that might be the case.
1:19:11
I mean, keep it like like I said, I mean Amazon has all of these identity partnerships that essentially make it the data spine and the identity spine for fast like broadly, >> right?
1:19:20
And so if you think about I remember people saying, I bet Amazon's going to buy Roku.
1:19:23
And I remember thinking like why would they?
1:19:24
They've already got this identity partnership with Roku where they get access to the best impressions.
1:19:28
if they bought it, they'd just be getting everything else that they don't already buy, right?
1:19:30
And so my sense was always that like well they they're already picking over the stuff that they're not buying.
1:19:35
Why would they want to own it?
1:19:37
>> Um and so like my sense is yeah, maybe it competes with the fast channels that they're partnered with or maybe maybe they have similarly like uh you know some sort of perceived quality bar or hurdle.
1:19:46
Um but but I I think like the UGC thing is is is a little bit of a distraction because you know I don't think Netflix is ever going pure UGC.
1:19:55
like they are very selectively curating the YouTube creators they bring over, but they brought over a lot and they went on a shopping spree this summer, too.
1:20:01
They bought a lot of stuff this summer or and and now now YouTube's pushing back.
1:20:04
>> I saw some post about how uh the results of that of that shopping spree that Netflix went on with YouTube creators had a significant power law where there were some creators that were really performing well on Netflix.
1:20:17
Is that because of the way the Netflix algorithm works? Is that true?
1:20:22
Or do you think that there's a okay, if somebody's getting a billion views on YouTube, we can pull them over and get X views and there's some multiplier or is there something special about the way Netflix is like actually rolling out these deals?
1:20:37
>> Well, I think there's a there's a couple pieces there.
1:20:38
I think like they've got more than YouTube certainly has like more Rexus agencies.
1:20:41
So, they have more opportunities to push people into this content than Netflix does.
1:20:44
Netflix has less stratified um less deep catalog, right, than than YouTube does.
1:20:49
So, that's that's that's one piece.
1:20:51
But then you do you just you do just see like even with Miss Rachel like season 2 performed substantially worse than season 1 in terms of >> uh view hours per per minute of of of content.
1:21:01
And so um you know it's maybe it's just uh consumer preferences or they had other stuff to prioritize.
1:21:05
I mean Netflix has invested a lot into its own recommendation algorithm and so it just it depends on like what they they feel the need to promote at any given point in time and they they have to you know they they just have to exclude stuff that doesn't fit that purpose. >> Yeah.
1:21:18
Yeah, you have to imagine that someone like Miss Rachel, if she's doing a deal with Netflix, she as part of the deal, it's not just going to be money.
1:21:24
It's going to say, "Hey, are you going to actually give us impressions so that we have the chance to be successful here and get real viewers that go into the rest of the funnel, show up to the live shows, buy the merch."
1:21:33
Like, it's not enough for you just to pay and stuff us off in a corner.
1:21:36
If we do this, we want to do it.
1:21:38
I wonder I wonder if Netflix has an opportunity to just basically take all the best UGC from YouTube because you I think YouTube has a massive AI.
1:21:47
Yeah, that's that's seemingly what they're doing, but underappreciated maybe how big of like an AI like AI is probably like seemingly a net good for YouTube right now because there's more >> you mean specific.
1:21:59
>> There's more content for all the the longtail like something will happen and I'll get served a video and the voice sounds good now.
1:22:06
sounds good now. maybe the script sounds okay and then you realize like okay this channel was just created two months ago and it's not really um and and YouTube is has an incentive to just constantly be serving new creators >> in theory Netflix review I generally
1:22:21
want to consume content from creators that have been >> uh are either new and extremely passionate and dedicated um I even saw a creator uh over the weekend that that started years ago using like AI voices and just stopped and said >> interesting that YouTube is so flooded with AI content now. He's just
1:22:38
He's just >> and he's he's not American, but he he makes all of his English isn't his first language, so he has an accent, but it's appealing because you're like, "Okay, this guy's actually making this content.
1:22:50
It's not just like fully generated, right?"
1:22:53
And so I think YouTube or Netflix's opportunity is to like try to carve out all like actually have a filter again and like be a curator and take the the best content um >> that historically would have just been on YouTube and and try to bring it over. >> Yeah. But still big. >> Well, yeah.
1:23:10
But I mean, so YouTube absolutely does not want that to happen, right?
1:23:13
So I mean keep in mind like that the dominant platform for YouTube in the United States is the TV. Yeah. >> Right.
1:23:18
And so so they they are I've called it a CTV behemoth.
1:23:19
that is their dominant platform by by view time.
1:23:21
And so they they compete directly with Netflix for engagement.
1:23:25
It's actually really problematic if Netflix is able to just poach their best creators, the top like the the sort of like the the the cream of the crop and then push them into Netflix uh and and then to justify the subscription price, right?
1:23:36
So like what they've done is they've they're now inking deals to keep people exclusive for a period of time.
1:23:42
And they're also saying, "Look, we're going to punish you if you move.
1:23:45
We're going to depprioritize you in our recommendation systems.
1:23:47
promote stuff that's not going to share in revenue.
1:23:53
So, it's actually what Netflix has done for YouTube to apply a lot of the curation pressure and incentives that YouTube always didn't want to do.
1:24:03
They always wanted to resist being that kind of channel.
1:24:06
They said, "Look, you know, just look, this is just an open market.
1:24:09
Like, people compete and you get you get views if you outperform, but now they're having to sort of put their thumb on the scale in certain ways to keep the best creators." >> Yeah.
1:24:16
mask very much a mask off moment for the for the platform that wants to position itself as like we're just this friendly platform for creators and we just want to support creators and they're like if you even put one of your videos over here you're not getting any more money and you're not getting any more views and we will end your career like that's basically that's basically >> be a shame if anything happened to your audience. >> Yeah.
1:24:39
Be a shame if something were to happen to your reach.
1:24:41
what is going on at Apple around services, ads that give me a little bit of the history there.
1:24:49
Apple's obviously had some some sharp words about advertising in the past, wound up building a great ad platform.
1:24:57
>> So John sent me a screenshot.
1:24:57
I it looks like it's from mobile.
1:25:00
>> It's from mobile dev memo.
1:25:00
And the screenshot says, "The Schiller exit is a bit more notable.
1:25:04
Apple's app marketplace is loved by many consumers but often criticized by developers and subjected to increasingly ownorous regulations.
1:25:11
But there's a bit more to the story.
1:25:13
I'm told turnis and service chief Eddie Q want to make even more money from the app store and figure out how to ways to raise margins and squeeze additional recurring revenue from the platform.
1:25:23
Schiller on the other hand seems to believe that such moves would only further irk developers and governments.
1:25:28
And John said first piece of good news from Apple under Turnis.
1:25:32
Certino will finally be focused on app store margin expansion.
1:25:35
I've been pulling my hair about out about about this for years.
1:25:38
Feels good to be vindicated. Better late than never. So obviously joking.
1:25:43
>> So that quote >> that quote from German.
1:25:45
That was that was me quoting German. Got it.
1:25:46
So that was from German's newsletter.
1:25:48
But yeah, we got a new a new era, right?
1:25:52
Schiller's out apparently.
1:25:52
He stepped away from the app store.
1:25:54
Eddie Q is taken over with Turnis and apparently they want to squeeze more money out of the app store which makes sense because it's undermonetized. >> But why not ads? Is that it can't?
1:25:59
Can't be anything but ads.
1:26:03
No, it can't be anything but ads. What else could it be?
1:26:06
I asked this question on Twitter yesterday. What else could it be?
1:26:08
What could it possibly be besides ads?
1:26:09
What other opportunity is?
1:26:11
Are they going to increase the commission? Are you nuts?
1:26:14
How would they increase the commission?
1:26:16
The incre the the commission.
1:26:17
>> Wait, you said it's under you said it's undermonetized, but you believe it's undermonetized purely on the ad side.
1:26:22
The commission side is people's totally at their limit. >> Totally. >> Yeah. Yeah.
1:26:25
Commission can't go anywhere.
1:26:27
Certainly, it's not going to go up.
1:26:28
They'd be lucky if they could maintain the commission.
1:26:29
maintain the commission. Y I mean they're probably going to have to uh you know so basically I I think what I think is going to happen so they um replied with their in the epic uh v Apple drama which is interminable apparently uh they made their latest proposal which is that they'll apply a 15% commission on the
1:26:46
link out right so they're they're having so in if you remember just go back a little bit the epic vap case epic essentially lost on every 10 of the 11 uh points but uh what they did went on is that Apple does have to allow linkout right so I'm you're in the app the developer can put a link in the app to a website that allows them to monetize there, right? So, they have to be able
1:27:04
So, they have to be able to do that.
1:27:05
Now, what Apple responded with was saying, "Okay, yeah, but we're going to apply a commission um that when you add in the Stripe fee is essentially just as much as 30%."
1:27:12
And also, you have to do all this reporting and also if you have someone clicking out and going to a website, they're probably not going to be as likely to convert, right?
1:27:18
So, you probably all this commission, all these frictions that like, okay, it's never going to there's never going to get any traction.
1:27:23
Now, what they've proposed is like, okay, we'll accept a 15% commission on this, but you still have to go through all the reporting.
1:27:28
That makes it interesting.
1:27:29
Now, we'll see if the judge accepts that, right?
1:27:31
She might not, but like Epic was fighting this.
1:27:35
They want zero commission on Linkout, but Epic wants zero commission on anything. Yeah.
1:27:38
Um, but so like if if that happens and the commission drops even further, you're going to push a lot more revenue outside of the app store onto the web, which actually a lot of it's already fled to the web.
1:27:46
I mean, like go to any subscription app, go on the Facebook library, find your favorite subscription app, Strava, whatever.
1:27:52
Look up their ads and see where they link to.
1:27:56
guarantee you it's to the website.
1:27:58
>> Almost every subscription app spends the vast majority of its of its advertising on web uh web destination ads.
1:28:02
So they're sending you to the web, you you register on the web and then you download the app, you log in and so all of the monetization has happened on the web.
1:28:11
There was never any monetization the app in the first place.
1:28:13
Games have started adopting that too.
1:28:14
And so they've already lost a lot of this inapp monetization to the web.
1:28:18
The commission's already under a tremen tremendous amount of pressure.
1:28:21
And it's not, you know, you've got the EU at the DMA.
1:28:24
uh they seem to have come to a resolution there.
1:28:27
Although uh you know Epic also thinks that's not true.
1:28:29
Um but uh you've got Japan, you've got Brazil.
1:28:33
I mean you're going to see increasing cases where a government step in and say you have to offer alternative inapp monetization um and you have to offer alternative app stores.
1:28:40
And so if you think about what does the app store have that can't really be taken away that's probably undermonetized.
1:28:46
It's a lot of engagement.
1:28:49
It's I if I remember correctly like the last touch point where they released any data was 600 million uh no it was 900 million weekly active users.
1:28:57
So they uh JTP reached parody with that at some point a couple like roughly a year ago.
1:29:01
900 million weekly active users.
1:29:04
That's a lot of engagement.
1:29:06
And what do you do when you have a lot of engagement, a lot of eyeballs, a lot of attention?
1:29:08
You monetize it with ads.
1:29:09
I think they have no >> with the app store.
1:29:13
Every time I search for something, I'm seeing a seemingly seeing a bunch of ads.
1:29:18
>> But you can see way more.
1:29:18
Like imagine you go to a website, you go to an app in the app store, you're browsing, you don't purchase the app, and then the next morning when your alarm clock goes off, instead of notification, >> no, just the replace the alarm clock sound with an ad that says, "Please download this app. Are you ready to go?
1:29:33
Retarget me throughout the day.
1:29:33
I open up the iMessage before I see an ad."
1:29:40
Where I was going with this is at what at what point does Apple if they actually want to grow their ad business not start to compete with an app loven and start offering like bringing their bringing their ad network into the actual apps, >> right?
1:29:55
>> Well, I mean they do essentially I mean they've got ads in the search results, right?
1:29:59
They just added a second uh slot the second placement in the search results recently a couple months ago.
1:30:04
Um, you know, they've got like re recommended apps where you can find the placement in an app store page.
1:30:09
>> They could do like you have to pay to get organic results.
1:30:11
Like you search and then it's just 10 ads and then unlock unlock unlock premium unlock organic results.
1:30:18
It's a dollar 99 cents to see what you're actually searching for.
1:30:21
No, but what what I was saying is like like you know like basically a user comes they search for a game let's say >> then they see an ad but then they end up downloading a game.
1:30:32
And then I'm saying like all the surface area that's potenti like the real opportunity is every time someone opens up that game they're getting an Apple ad.
1:30:40
And >> no, I think they I think they should. I think they will. I think they will.
1:30:43
I don't know what else they could do.
1:30:45
I mean I think they're going to do that.
1:30:46
I think they're going to have some sort of ecom ads offering.
1:30:48
I mean I predicted a year ago that they put ads in maps because it just made sense.
1:30:51
They've got a lot of engagement there and they they just did that a couple weeks ago.
1:30:54
Um, but keep in mind, I wrote about this uh when they so they took their um ads uh service down for a while.
1:31:04
Usually they do that when they're making a change, right?
1:31:06
Uh right before they did that um and that's when they implemented ads in maps, but they also they they they created a whole new campaign optimization API to accommodate maps now and all the other placements that they have.
1:31:18
So this unified campaign optimization API, right?
1:31:20
Now it's al that's extensible.
1:31:22
You could extend that to anything, right? Right.
1:31:24
So, they're already putting in place the scaffolding to support that, but they're also putting in place the policy scaffolding.
1:31:30
So, they also uh made all advertisers uh uh like sort of reertify their approval of the of the uh Apple ads uh service agreement and that gives them permission now to serve ads on websites and apps they don't own.
1:31:44
And I think that was the big sort of signal here.
1:31:47
Now, they've done a lot of other things too.
1:31:48
They rebranded SK ad network to um the ads attribution kit.
1:31:52
uh they renamed the whole thing from Apple search ads to Apple ads.
1:31:55
I mean all of this sort of points towards a more generalized ads product, but I think opening up that services agreement to say we can place ads on thirdparty properties probably does signal that they intend to do that. >> Yeah.
1:32:05
Uh yeah, I mean that seems like a huge way to grow services revenue.
1:32:09
Uh I I don't know if you have the exact size of the project.
1:32:14
>> Ads come for everyone.
1:32:15
>> What about uh what about new Siri?
1:32:15
Uh, I mean, looking at the CHACHPT ads hitting a billion dollars, you've been very optimistic about the potential of ads in LLMs and that it's a logical end state.
1:32:30
Uh, do you think that they'll do Siri?
1:32:32
What what else are you tracking in the development of uh AI and ads?
1:32:38
>> Well, I mean, we can talk about chatbot ads.
1:32:39
Um, you know, I have a lot of thoughts on that, but I mean I just going back to Siri.
1:32:42
Siri is tough because it's only voice, right?
1:32:43
And so, I think you need >> there is an app where you can chat. That's true. So >> that's true. That's true.
1:32:48
I think once you have the chatbot interf and and they do have that.
1:32:50
I think once you get a lot of usage there, ads become an opportunity.
1:32:53
I just do think you need a visual component to make ads work. Yep.
1:32:57
>> Um it's also why I just don't think ads to agents is ever going to take off.
1:33:00
First of all, I think there's like a lot of incentive conflict there.
1:33:01
I just don't think that you can show ads to agents because you you wouldn't know who to trust and who's getting paid in that case and who's paying, right?
1:33:07
So that's there's like a lot of uh incentive conflicts there.
1:33:10
But um I also just think there's a there's a there's a visual component to ads that's necessary, right?
1:33:14
because that's, you know, that's what ad creative is.
1:33:16
That's the that's the principal way that you do messaging, that you do brand positioning, um that you you you create affinity.
1:33:23
And so I think if you're just doing voice, it's really tough.
1:33:24
I think in the chatbot experience, you can my sense is how they want to I think how they want to monetize AI generally on their hardware is uh is is uh through essentially a deal similar to what they struck with Google search, right?
1:33:38
Like you have to pay to be the the model that gets uh by default gets attached to these services.
1:33:44
Um, >> and I think that that could be very very lucrative to them.
1:33:46
And they've already sort of again they've already set up they've already kind of created the the the environment for that to happen with uh the sort of the core AI framework um access to the models going through private cloud compute.
1:33:57
They've already created the the the conditions for that to happen. >> Yeah.
1:34:01
And I think uh I think Demis at Deep Mind was saying that like there won't be ads in Gemini or like the core Gemini models, but he's out and over time you could imagine that the ad gets baked into the actual Gemini response and then that is monetized on the Google DeepMe side which then justifies the pool of of capital that gets traded to Apple in exchange for that entry point. Uh makes a lot of sense.
1:34:27
What do you think OpenAI needs to do to get from one to 10 billion on the ads product?
1:34:31
Uh they have billion users.
1:34:34
The technology does not seem that complicated to me.
1:34:37
I know it's deeply complicated but it feels like when you have the machine that can you know solve math and write endless code like just writing a matching algorithm serving up the UI like that feels tractable.
1:34:49
But is it uh is it a supply side thing?
1:34:52
They need to get more small businesses like what Facebook did where you know Ridge wallet and every small company and medium-sized company is on there.
1:35:00
Uh actually do they need to go after e-commerce gaming?
1:35:03
Like where do you see this going?
1:35:07
>> Well, first of all, famous last words that it doesn't seem that complicated.
1:35:10
Uh >> to build No, no, you're right.
1:35:10
Because because like you and Ben Thompson were talking about like, oh, they they've said they're going to do this and it still took months to actually get out.
1:35:19
>> Well, yeah, but they're doing it, right?
1:35:21
I think they just need to keep doing what they're doing.
1:35:22
I think the opportunity is vast and immense and I think they're executing at a at a blistering pace.
1:35:26
I I So they just opened up to more countries.
1:35:28
Now there are more than 40 that they're available and they just opened up to 31 more countries.
1:35:32
This was like two weeks ago, okay, or a week ago.
1:35:34
So I mean this is like re I mean so they're expanding.
1:35:35
I mean it's just it takes time.
1:35:37
Look, I think >> what they will be I think you you you start you start to see the growth inlect um when they in integrate true uh conversion optimization.
1:35:49
That means you're bidding a specific amount for a specific outcome.
1:35:52
Like you're still doing CPC optimized conversions.
1:35:53
Um once you are bidding against a specific outcome, then the growth in flex and I think you know they'll be off to the races.
1:36:02
That's the gap from 1 to 10 and then 10 to 100 is just continuing to onboard you know every SMB possible. >> Yeah.
1:36:08
Uh where do you sit on Instinct and the personalized agent? >> Yeah. And some breaking news.
1:36:12
So Meta just released an Instinct clone called Muse and it's a new standalone app.
1:36:16
It's not the Meta AI app.
1:36:19
It's a new >> uh personal agent app that's in the app store. >> Muse from Meta.
1:36:24
It says your personal agent that takes things off your plate.
1:36:28
Approve what gets sent or spent.
1:36:28
Track ticket prices and book reservations. Connect all your apps.
1:36:34
>> Get ideas for what your agent can take on, which I think is is smart because a lot of people just don't really fully understand what agents can can do yet.
1:36:45
Um but yeah, let's talk about Meta's current AI strategy.
1:36:48
In the moment, they're they're, you know, have started uh uh a pricing war.
1:36:52
It's unclear what how much the meta AI app matters to the whole strategy.
1:37:01
It's they're doing Muse now. They're doing coding.
1:37:05
>> They're throwing a lot at uh the wall. Uh but what's your view?
1:37:10
I think I so I like to sort of just I think I just I'm I'll hone on I'll hone in on thing.
1:37:15
Yeah, they are throwing a ton of stuff at the wall.
1:37:16
I'll hone in on the things that I think are like where there's there's there's like a a a true like uh thematic strategy.
1:37:22
So, uh couple things, right?
1:37:25
Uh Muse agent interesting Open Claw kind of thing like we'll see. Instinct kind of thing.
1:37:30
We'll see where that goes.
1:37:32
I think there's going to be a lot of those and I think those get more and more domain specific over time.
1:37:35
Um but you know, we'll see. That's interesting.
1:37:37
it could get more consumer adoption on uh desktop. So, we'll see.
1:37:40
It's going to be a standalone app.
1:37:41
I was just reading Bos's uh tweet about it before we hopped on. >> Yeah.
1:37:44
And it's it's interesting to me that they own WhatsApp, which has billions of users, and they wouldn't just try to clone Instinct in WhatsApp, and just like try to get like actual crazy adoption there versus launching a standalone app. >> Yeah.
1:37:58
Like a button inside of WhatsApp as opposed to a separate app.
1:38:01
This is always the trade-off.
1:38:05
>> You can interact with it that way.
1:38:05
You can interact with it from WhatsApp. Totally, totally.
1:38:07
But the the friction of getting people to download a new app instead of >> it was always different when it was just like if you open Instagram, you get stories now like there's no separate there's no step.
1:38:18
It's coming to you whether you like it or not cuz we believe in stories and we are going to get that to a billion now very quickly and they did. >> Yeah.
1:38:27
Yeah, I mean you have to you have to keep in mind like there's still a lot of reluctance to this on the consumer side and there's still a lot of mistrust from Meta on the consumer side.
1:38:32
And so I think you know if you just if you just integrated this as a force download and WhatsApp you might get a lot of ch you might get a lot of telegram adopters.
1:38:40
Um my sense though is like if you look at a couple different things there's there's a there's a there's a thread that you can sort of parse like one is >> meta AI right?
1:38:48
So okay here's here's an interesting enterprise use case.
1:38:51
What if you had the go-to AI for managing all ad campaigns within your company?
1:38:55
The go-to AI app for managing all campaigns within your company.
1:38:59
Cuz I'll tell you how people do it now. They use Codeex.
1:39:01
Codex's not purpose-built for that. They use Claude.
1:39:03
Claw's not purpose built for that. >> Yep.
1:39:05
>> Meta AI now does that.
1:39:05
They've added that as as a as a whole feature set.
1:39:07
I think that gives you a strong indication of where they want to go with this.
1:39:10
Who knows campaign optimization better than Meta.
1:39:15
Why do they not have the right to win that?
1:39:17
So even if you just said this only applies the enterprise use case here only applies to op to to to optimizing meta ads that's still a massive opportunity for revenue not and and that's just on a on a on a on a first order perspective not even considering like well that actually might result in more ads.
1:39:32
That's why I was I was somewhat excited about Manis because I was like, "Okay, they're buying this enterprise agent.
1:39:37
They can point it they can point it at Meta Ads and if the agent is only good and it's actually >> not getting like if Meta saying, "Yes, we want you to spend we want you to optimize ads with this product and we're fully endorsing this. We're supporting it.
1:39:54
It's not computer use or any of these other things." >> Yeah.
1:39:57
But I mean like I mean that Yeah, that was exciting, you know, got rolled back.
1:40:00
But but I mean Meta AI now does it.
1:40:02
they've introduced that functionality to meta.
1:40:03
Now, if you're an if you're a performance marketing team, you're saying, "Well, I need a tool to optimize my meta campaigns."
1:40:09
>> Um, which one am I going to use?
1:40:09
Am I going to continue to use codeex?
1:40:11
Again, it's not built for that. Yeah.
1:40:13
>> Like, I don't think that they've devoted resources to making that a primary use case for it.
1:40:17
And so, Meta AI has done that.
1:40:19
And if I even if it was just for metas now, now imagine that it's the go-to for all ads optimization. >> Okay.
1:40:24
Well, now it's an even bigger commercial opportunity for them, an even bigger enterprise opportunity, right?
1:40:28
Yeah, keep in mind Meta launched the Robin media mix model uh as an open source framework.
1:40:32
Uh so it's basically like a measurement apparatus that helps you do like probabilistic measurement across all of your campaigns that you're running like online, offline, whatever, out of home.
1:40:39
Um the reason they did that I think was because they felt they were being underattributed right now.
1:40:43
If you if you thought if you had this if you had the sort of same mindset with the uh AI enablement layer, the tools that people were using to do the optimizations, yeah, then this makes a ton of sense.
1:40:53
this might end up with more revenue flowing to them because the the optimization ends up preferencing them.
1:40:58
Not with the thumb on the scale, but just because it was actually underoptimized before.
1:41:01
So that might be a reason to do this.
1:41:03
If you genuinely thought people were spending less than they should be to be optimizing their ad spend on your platform, then you would do this.
1:41:09
And if that's the case, this could have this could have like dramatic second order effects to you. So that's one thing.
1:41:14
The other thing is business AI.
1:41:15
And business AI, I think, is like underappreciated.
1:41:17
I've been following this for like quite a while.
1:41:18
Uh I had their uh VP of business on the podcast maybe a year ago and we talked about this but they launched a business AI which basically was a chatbot that you integrate on your website.
1:41:28
They said okay that's kind of boring who cares but what people were doing is they were going they were clicking an ad going to someone's website and then they were they were using the chatbot to say like what's the what's the bestselling product like stuff like that has a lot of opportunity there like even if it's just surfacing basic data like that there was no way for a lot of SMBs to do that.
1:41:44
Now what they've done is they've introduced like an AI enabled pixel which can automatically uh you know sort of tune itself requires no inte the advertiser side.
1:41:54
Imagine all the other stuff they could do if they have access to your landing page.
1:41:57
Imagine landing page optimization. Imagine personalization.
1:42:00
It's all driven by Metaone systems.
1:42:02
And the advertiser could say look um I'm an SMB.
1:42:04
I don't have time to AB test uh or I don't have the resources to do like constant AB testing, constant experimentation on my landing page to to optimize conversion.
1:42:13
I know if my conversion was better, I'd be able to spend more money on Meta and get more sales.
1:42:17
So, if Meta can offer that to me, I'm okay to surrender that capability to them.
1:42:22
Imagine they penetrate even deeper into the customer experience on the website.
1:42:25
Certain brands will say, "No way."
1:42:26
But a lot of SMBs, which is that big bulk of their advertiser base, will say, "Yes, please do anything you can do to optimize conversion for me because that's going to result in more revenue for me, which I'm then going to reinvest in more ad spend."
1:42:38
So I think like business AI is really really valuable to them and they've integrated that deeply into WhatsApp.
1:42:43
So that is going into the WhatsApp experience where people are able to communicate with business to directly get a chatbot you know understand these things about the the the catalog understand these things about the business and the the core product offering.
1:42:53
I think that stuff has a ton of potential and I think that's probably undervalued if you look at um if you look at Meta's AI initiatives.
1:42:58
I think people focus too much um probably on like the output >> of you know TBD um but but like I think u and that's important too.
1:43:07
I mean look the the the model that they just released is competitive like no one people left them for dead six months ago but now they're actually producing competitive models.
1:43:15
I think that's important too but if you think about the integrations in the surface area they could just apply even commodity uh AI to it's there's a lot of value left to gain.
1:43:24
>> Yeah we never book an no. Yeah.
1:43:24
And and what you're saying to to me it's like >> it would be I think it would be thrilling for shareholders if they saw MSL actually focused on applying AI in the business and not like oh coding's a hot category.
1:43:42
We should we should introduce a coding tool or or oh let's let's try to ramp Muse API revenue to to hundred billion dollars right or or whatever these things are that they're trying to do.
1:43:53
Um, and so yeah, it's like it's products, it's like net new products that are consumer products like Muse that I think are interesting and it makes sense that they'll take a crack at this category because it will probably be, you know, multi- trillion dollar category.
1:44:06
It's aligned to their existing business.
1:44:09
Uh, and then and then some of these other things of like actually applying AI instead of >> personal super intelligence, it's small business super intelligence.
1:44:16
That would be a huge opportunity.
1:44:18
And small business owners, like small business owners, I feel like are people that generally they may have a little bit of a lovehate relationship with with Meta and that they're they're like, I I'm dependent on Meta.
1:44:29
If I turn off Meta ads, my business, you know, revenue drops 50%.
1:44:33
But at least they're like, I need Meta.
1:44:35
Like they're dependent on it.
1:44:37
Whereas average consumers, you look at the comments and people are like, okay, Meta is talking about privacy with their new agent.
1:44:43
It's like nobody nobody's like buying the the meta and suddenly is privacy focused narrative, right? >> Yeah.
1:44:49
I mean, look, a lot of the SMBs, they understand that they wouldn't exist, but for meta.
1:44:52
I mean, there's not there's not a lot of animosity towards the company that uh provides your right to exist.
1:44:58
It's like the oxygen that they rely on.
1:45:00
I don't think there's a whole lot of hostility to that.
1:45:01
I mean, it's it's what always bothers me about, you know, um these discussions is like to just not recognize that DOC would not exist absent Meta.
1:45:09
if if if if Beta's ads platform hadn't like evolved in the way it did, there would be no DTOC category, right?
1:45:14
category, right? And so it's like it's it's it's ridiculous to say first of all, I think one one I mean let me know if you're we're up on time here, but like one issue like a lot of people look at the index like so if you look at like
1:45:25
the the advertising a share of GDP, it's basically it sits within like a narrow band like over time historically going back really hundreds of years and people say look that proves that that advertising is is is not driving the economy. It's it's it's almost like a
1:45:36
It's it's it's almost like a drag, you could say, because it's just this costbased.
1:45:39
But like the thing is when when a when an advertising format when advertising enables new business, the fact that I'm still maintaining a share of my revenue as as my ad spend doesn't mean that that ad spend would exist or that my revenue would exist without the ad spend, right?
1:45:54
And so if you create these new opportunities for commerce, like it doesn't matter that the share that you reinvest back in advertising stays the same.
1:46:01
That's not an indication of the value to the economy.
1:46:04
economy. it's creating that chunk of the economy and so I think that you you get that gets missed in these discussions like if you it actually impacts economic growth it's it's indogenous there and so it's an input to the economic growth and so you can't say that the fact that it
1:46:16
remains within this narrow band as a percentage has is some way to evaluate its importance to the economy and when you are creating new opportunities to transact that are entirely derived from advertising then you are creating that section at that segment of the economy >> totally totally >> do you think that What is this? What is
1:46:32
What is the state of affiliate marketing?
1:46:36
Because when I think about a product like Instinct or this new meta product, an agent that will go and buy things, it feels like that would be easier to bootstrap in theory than an advertising platform that you need, uh you need scale and and a demand side or supply side for.
1:46:52
And so, uh you could in theory when even on day one of Instinct, I ask to go order a pair of shoes and it uses an Amazon affiliate link and they're making money.
1:47:02
Is is that going to persist or is that like a dying a dying monetization path or is it just small?
1:47:10
>> No, I mean I think there's some upper limit now but I think it's something that'll persist you know indefinitely.
1:47:14
I mean you look at there's big companies that do essentially affiliate raquten is one of them.
1:47:20
It's a successful company.
1:47:21
I think the thing though is like is at subscale yeah affiliate makes sense but this is the argument I made when when chatt introduced instant uh checkout like that's not going to that's not the optimal way to monetize that attention.
1:47:32
The optimal way is to do conversion based conversion optimized uh advertising because that introduces the auction mechanic.
1:47:38
You actually deliver the value that a person's bidding and then so the more value you give to people, the more they bid and the more revenue you make, right?
1:47:43
You don't get that with affiliate.
1:47:44
Affiliate tends to do the opposite.
1:47:46
It tends to preference the lowest cost but highest converting goods.
1:47:50
And so it's kind of you're promoting like the worst stuff, the cheapest stuff, right?
1:47:53
The Shane stuff, the tamu stuff.
1:47:54
And the thing is when you unlock sort of like the the latent value with the auction mechanism and bidding especially second price bidding then you get uh you get growth with uh with uh performance and so that's how you scale the platform.
1:48:08
You on board longtail SNB advertisers. >> Mhm.
1:48:12
Well uh thank you so much Jordan.
1:48:14
Do you have anything else? >> No always a pleasure. >> Always a great time.
1:48:17
Always always a great time hanging out.
1:48:19
Thank you so much for coming on the show. >> Great to see you. >> Have a great week.
1:48:22
>> The third technology brother >> and we'll see you soon. Have a good day.
1:48:26
>> Let me tell you about public.
1:48:26
com investing for those that take it seriously.
1:48:29
You got stocks, options, bonds, crypto, treasuries, and more with great customer service.
1:48:33
Uh we ran long there, so we're shifting Harry Melup from Antioch to the end of the show.
1:48:40
We're going to be joined by Scott Woo from Cognition in just a minute or two. Huge >> news.
1:48:46
While we were live with Eric, Meta came out with Muse Agent.
1:48:50
So Tyler, >> download it. Got it. Already got it. I already got it. Look at that. Look at that.
1:48:56
Uh excited to uh see what you think.
1:49:01
>> Um >> build me an equestrian simulator. >> Uh I don't know.
1:49:06
>> I don't think I don't think it's focused on vibe coding.
1:49:07
It's like it's the whole book me reservation, book me a flight. >> Okay.
1:49:12
>> Um it's so Can you Can you imagine >> table at the Beverly Hills Hotel, please?
1:49:16
Can you imagine being like resi or open table and and having, you know, trillions of dollars, watching trillions of dollars of capex and people are like, "One day you're going to be able to just tell your agent, you know, book me, book me this reservation."
1:49:30
And they're sitting there being like, "It's two clicks, sir. Sir, it's two clicks."
1:49:36
Because you go into resi.
1:49:36
I mean, it's it's uh it really is uh it really is quite quick.
1:49:41
Um, >> uh, apparently we have to ask Scott about the number 46.
1:49:45
Do you get this reference? I don't know.
1:49:48
Okay, we're going to ask him because he's here in the waiting room.
1:49:52
And let's bring in Scott Woo, founder, CEO, Cognition. Welcome to TVN.
1:49:58
Scott, how are you doing?
1:50:00
>> Great to tell us about having me. Slow, slow news day.
1:50:03
I was going to say huge news you guys to talk about.
1:50:07
>> Congratul Yeah, crazy news day.
1:50:07
We're going to talk about math.
1:50:09
We're going to talk about AI.
1:50:10
We're going to talk about fundraising business, but first the number 46.
1:50:13
I was I was told to ask you about this. Why? >> Oh, that's funny. >> That's funny.
1:50:18
Well, so the my Twitter handle is Scottoo46. Okay.
1:50:20
The the reason my u my handle my my I'm like Scott46 on basically all these platforms.
1:50:26
Um is um because when I was in like elementary school, I uh the the biggest thing I knew of was this middle school competition, math counts, which is now made a bit more famous because people have seen these videos of math counts and stuff.
1:50:38
Um, and in the math counts, there's like a written proportion and then when you do well enough on that, you go to the actual like head-to-head, but a perfect score in the written portion is 46. >> 46.
1:50:47
>> Uh, and so then what ended up happening is with this particular round, we actually ended up pricing it at 46 pretty partially for the meme, partially because, you know, ended up being the right kind of all that, but yeah. >> Yeah.
1:50:58
Yeah, you have to imagine that certain VCs are like, "Okay, we've agreed to this number."
1:51:02
But are there any insider meme references that would save us even 3% here?
1:51:06
Let's do a deep dive to see if we can get the founder to give us a little >> Yeah. No. Uh, but congratulations.
1:51:13
Tell us about the fundraising round.
1:51:15
You got every investor in the world on the cap table at this point. Is that right? >> Um, yeah.
1:51:21
Yeah, look, you know, it's it's an exciting time for cognition, obviously.
1:51:24
And I mean, I think the the the biggest thing I would just call out is like agents and are just getting really really good, you know, and I think two years ago, uh, by the way, we're not not that old company two and a half years ago.
1:51:35
Uh, so so two years ago, you know, was when we kind of did the Devon launch and back then, as you remember, is like, you know, it went pretty viral and so on, but but it was really just like a prototype.
1:51:42
I would not >> there was so much skepticism.
1:51:44
People were like, they are coining a buzzword that will never exist. agents.
1:51:48
They're just hyping this up and now it's like everything is agents. >> Yeah.
1:51:54
>> I remember thinking about this because I just think, man, it's it's great that Devon actually works because if it didn't, we would just look so dumb right now for making but so so that was two years ago.
1:52:02
Uh and like we didn't have customers, you know, it was very much just like a prototype and like here's what we're building towards and so on, right?
1:52:08
towards and so on, right? um one year ago I would say it was very um you know that the the product existed it worked it was it was for very specific use cases um you know that that you would kind of have it work and have it do it end to end but I think most people in the world hadn't really gotten across to
1:52:25
the idea of using a background agent now I would say it's it's um I mean especially in our circles it's like you know it's becoming a more and more commonplace thing and a lot of it is just the the capabilities are just so good that obviously you should go and delegate to something that just does the task entire entirely right and be able to manage these and so on. So, so, so
1:52:40
So, so, so that's been the biggest thing >> we Yeah, I mean the the agentic era arrived, the importance of harnesses like Devon arrived.
1:52:48
Um, how how do you think about orchestration?
1:52:51
It feels like we saw a glimpse of that with with Gas Town that went viral.
1:52:56
Now uh whenever you fire off a prompt in any modern AI system, you can see the harness and the lead agent sort of talking to sub aents and delegating things.
1:53:08
Uh is there I is is uh is orchestration a meaningful leg up?
1:53:17
Is it another exponential in the sense that we went from LLMs to reasoning?
1:53:21
That was an order of magnitude.
1:53:23
Then we went to the agentic era.
1:53:25
uh have we always been in the orchestration era or is this a new era?
1:53:29
Is this a new meaningful change?
1:53:29
Are there new disciplines that need to be be explored in the world of orchestration? >> Yeah.
1:53:35
No, so so it's a it's a really important question.
1:53:37
I think there's there's definitely a lot of like uh what's the word there?
1:53:40
There's there's definitely a lot of kind of like um uh you know misconceptions I think out there about it.
1:53:46
I will say that there's a sense that people get of like oh like if you just say the magic words to the model it will suddenly become 15% smarter or something like that.
1:53:54
That's much less of a thing especially now because the models are all RL on very specific capabilities and these kinds of tasks and so on.
1:54:01
I think what is much more the case is if you um number one if if you go and bring in all of the context and the information and the systems that you need.
1:54:09
For example, you know, in coding, a very simple example is like a model and an agent that can go and test its own code and click through its website by itself and then go and look and say, "Okay, that was right. That part was wrong. Let me go fix that."
1:54:21
Is obviously going to be way more capable than something that can oneshot it on its own. Right?
1:54:24
a model that can go, you know, an agent that can go look up at in in the data dog what went wrong in the logs is like much more powerful than than something that can't.
1:54:30
Um, so so that's one is just like being able to bring in all the tooling, the context and so on.
1:54:35
You all this kind of like messy real world stuff.
1:54:38
How do you navigate a big code base?
1:54:39
How do you get through, you know, all all the the secure systems that are, you know, that a company will have on its software?
1:54:44
And then number two, I would say, is combining the strengths of the different models and the things that they're good at, right?
1:54:50
And so, you know, I I mean, everybody's talking about price performance of models.
1:54:53
everybody's, you know, showing the charts of the paro curve and so on and this model is like really cheap but is good enough for this percent of tasks and this model is like the way expensive one and it's, you know, this much percent better and whatever, right?
1:55:04
Um, but obviously what that means is that by combining the the different models, as long as you know which use case to route to each model, then then you can do a lot better than any one alone.
1:55:14
>> How permanent is that task, that job of picking the right model at the right price point?
1:55:20
because we see there's a lot of attention from the from the big labs and it's very clear that they're that every big lab is going after building beautiful slides front end backend cyber security bio like math there they're all working on these and there's this trade-off between a certain model might be really good at something else and then the new big model comes out and it's better than everything at everything at every price point.
1:55:43
Um, but how and and I I think the risk is that you can you can wind up in a situation where you're like, "Oh, well, if I just wait two weeks, I'll just be able to use the the the major hammer because everything will look like a nail."
1:55:57
But it feels like there's also always going to be this cost optimization, speed optimization.
1:56:03
So that optimization problem, is that sticking around forever?
1:56:07
Is that what you want to build the core of cognition around? Nailing that?
1:56:11
>> I think it's sticking around. Yeah.
1:56:11
>> I think it's sticking around. Yeah. I mean I think it's if anything it's going to be a bigger thing as time goes on because for a lot of these use cases the intelligence is is is really not the bottleneck anymore right and so so uh obviously it's been been another hot thing for the last few months but but I mean I would say it's like you know chat GBT for example new bigger smarter comes
1:56:29
out you know smarter model comes out it doesn't necessarily change their retention metrics all of a sudden because most of the things people ask chat GBT you know turns out the models are good you know they already go and get them right right and like now what you care about is is is not just pure IQ cute for for any task, you know, whether it's coding or or legal or or customer service or whatever. Um, you know, it's
1:56:45
Um, you know, it's it's it's it's not just okay, what is the raw logical intelligence of the model that I'm working with.
1:56:51
It's like, okay, well, does it does it know all of the details of what I'm dealing with?
1:56:56
Does it do things in the style of how I want it to do? Is it fast? Is it cheap? Is it effective?
1:57:00
Is it is it trained specifically on my subset of use cases?
1:57:04
Or, you know, all all of these things like that.
1:57:06
Um, and basically what that means is I think there there should be this this frontier where people start to much more aggressively use all these different models rather than, you know, relying on the single biggest one, right?
1:57:16
Like I think a year ago that that was more of a phenomenon of of of a year a year and a half ago because there were a lot of use cases that were just on the cusp of possible, you know, and when that was the case, of course, you want to go use, you know, the very smartest model that you have out there like Sonnet 3.
1:57:30
7 or whatever it was, you know, a year and a half ago.
1:57:31
Um but now because all the models are really good you know what that means is you can be a lot more judicious.
1:57:38
>> Uh kind of a question going around I think on different people's minds.
1:57:42
Uh coding agents are now incredibly capable but is the quality of software around the world actually increasing and so I wanted to get your view on uh you know you guys are working with a lot of the biggest companies in the world.
1:57:56
uh do you feel like their the quality of their software is increasing or are they just doing more?
1:58:02
Are they doing back-end migrations that consumers don't even experience?
1:58:08
>> Um because you've had this I I I guess question for a while which is like okay when I when I download an app for like at a big airline >> Yeah.
1:58:15
I was chirping at Rune about this.
1:58:17
I was like, "Oh, if the AI models are so good, why is it annoying to use the United Airlines app?"
1:58:21
And he was like, "Have you tried to use it recently?
1:58:23
It's actually pretty good."
1:58:25
And then I did try it and I was like, "Yeah, actually maybe it is better." But I don't know.
1:58:29
Where do you sit on this?
1:58:30
>> Yeah, I think short answer is definitely yes, it is better.
1:58:32
I think to the extent that that there's more to do, a lot of that is is much more like um it's much more a function of these practical problems like going out and getting distribution going and doing that.
1:58:42
distribution going and doing that. And I mean I think I think people you know people in our ecosystem understand this intuitively but it's worth kind of calling out loud that you know a 50 50,000 person software org is not going to figure out how to use coding agents overnight the same way that like a threeperson YC company is going to right and so so there are steps in the process
1:59:02
that need to go happen there's like a lot of kind of like you know onboarding and education that has to be done there's figuring out the right systems there's of course getting through folks like you know the the the security guard rails and the and the reviews and the walls that people have to make sure all of that is tight and and something that they want to have operating in their ecosystem. Um but uh um but you know
1:59:18
Um but uh um but you know once that's there we we very much see that that's that's clearly the case across all these industries.
1:59:24
And I mean I think you know it's like between like yeah go ahead.
1:59:30
>> So so I can imagine if I'm if I'm selling cognition there's a few different pitches I could give.
1:59:33
One is uh I go to a company and say look you don't have an ER pieces or you don't have a an an e-commerce system.
1:59:38
we're going to come in and and build that and it's going to be done by the time we're complete and you're going to have this it's going to live forever but it's a new capability.
1:59:49
Other is we're going to give every person in your organization a co-pilot uh and we will help transform the organization.
1:59:58
And then third might just be like look we're just giving you access to dev and it does good stuff like you know go and and and you couldn't you couldn't get it at this scale but now you can because we're working together.
2:00:09
um what's resonating the most these days? >> Yeah.
2:00:13
No, I mean I think folks are rightly by the way are are very focused on at this point on on just like what are the actual use cases that that it's going to drive and what is it going to mean?
2:00:22
You know, I think there was a there was a period where was very much all right, we're in the token maxing world, how how many tokens are my engineers using, how that was, you know, that lasted for all of like four months or so.
2:00:32
Uh you know, great times.
2:00:32
or so. Uh you know, great times. Um but but um uh but but but now you know I think there's much more kind of like there's much more clarity of thought I would say from from folks in the industry about okay well look AI is great let's talk about what use cases that we actually care about like what what are the top three four priorities
2:00:46
we care about as a company like you said maybe it's this this killer new feature that we want to put out it's this app that we want to make way better it's whatever um and let's talk about how we actually go and measure that and improve on that you know and I think the the biggest thing if anything I think is is is kind of like yeah like how how can you show it in the concrete results right? Like the the value should be
2:01:03
Like the the value should be there obviously because AI is so good, you know, and it's so smart.
2:01:06
But but like unless you're tracking that, you're making sure you're using it for the things that are effective versus aren't effective.
2:01:13
You know, you're you're looking at the the productivity on a case- by case basis, obviously, it's like you you'll never actually know which things you're doing are working versus not, right?
2:01:20
And I think that's been a big big theme for folks.
2:01:24
>> How do you predict that the router market is going to evolve?
2:01:26
Uh we've seen a lot of moves recently. Ramp has a router.
2:01:30
Stripe, you know, bought Open Router.
2:01:32
There's a bunch of other players.
2:01:33
Everyone wants to be in that token stream.
2:01:36
Uh, but how do you see this sort of like category evolving? >> Yeah.
2:01:41
No, look, I mean, I think it kind of makes sense.
2:01:43
I mean, it's it's, you know, a lot of these companies that you're mentioning, for example, are they think of themselves as like the center for finance on the internet, right?
2:01:49
And, you know, what are people going to be spending money on in the internet in five or 10 years?
2:01:53
I think a lot of it is going to be tokens and models and agents and whatever you call it.
2:01:56
So, so I I think from that perspective, I think it's super reasonable.
2:01:59
Um, and I I think the the the routing part is a big piece, but but to your point, I think the entire kind of like um infrastructure around how you do payments, around how you do spend management, all these things I think are still going to exist and basically need to be redone in the world of agents.
2:02:15
And so I I I frankly think that there are a lot of products to go and build in that space.
2:02:18
What has your reaction been to the recent progress in math when you I think the very first time you came on the show, you predicted correctly that the IMO gold medal would fall.
2:02:30
Uh Google and OpenAI both scored just barely gold, not 46.
2:02:39
I think it was 38 or something.
2:02:39
It was like they missed the sixth question, but they but they did achieve gold.
2:02:44
Uh now >> 42 by the way 42 is a gold in in in the in the math Olympiad which is slightly different.
2:02:51
You have to remember it's it's different numbers for every competition.
2:02:54
Um yeah so so I'll tell you what my my honest thoughts on it uh which are um look first of all I think it's it's it's actually insane.
2:03:02
>> I there's there there's a lot of controversy and there's discussions arguments whatever but I feel like the most important thing to call is that guys we just solved Navier Stokes with AI.
2:03:11
Like that is it's absurd and and and I don't think it's going to stop obviously.
2:03:15
I mean I think the like uh you know what's funny?
2:03:17
I actually have money and this is my this will be my only AI bear view that I ever express to you guys.
2:03:22
I actually had money uh on a bet that the rebound hypothesis will not be solved by the end of 2026. Okay.
2:03:30
>> Um we'll see as you know three and a half more months but I'm pretty sure if not 26 it will be solved in 27.
2:03:33
I think it might get done in 26.
2:03:35
Uh but but I think it's less than 50%. We'll see.
2:03:37
Uh but but no, I mean I I think all of this stuff is is just gonna get done.
2:03:41
And I I mean I think it's like um it's it's kind of insane.
2:03:47
It's it's hard to put into words.
2:03:48
I think if you're if you're not familiar with the the the kind of scale of this, but like you know Navier Stokes, for example, is like a very fundamental problem about like fluid dynamics and such and it's been around for forever basically and lots of people have sunk lots and lots of time into it >> and you know the fact that this could even just be done in like a week >> Yeah.
2:04:07
of models just going and working around in a system and orchestrating it's it's just it's it's it's insane. Yeah.
2:04:11
just it's it's it's insane. Yeah. Um I think on on the point of the controversy I mean it's kind of funny but but similarly I think a lot of people who aren't as familiar with the the math academia world might not know that you
2:04:22
know this is actually just always what happens in in in math academia like literally Newton versus Linets on the founding of Caligulus was the is is still by the way is one of the biggest arguments that people have you know this is back in like the 1600s or so. Um and
2:04:34
Um and and so in practice I think like uh you know I'm sure look I I I I believe that both sides meant well.
2:04:42
I think the accomplish itself is going to be the biggest thing that we all remember from this.
2:04:48
We could debate you know what what exactly shapes up and and what what it means for folks.
2:04:52
Um but but but but it's it's you know the rest I would say it's kind of the the AI the AI accomplishment itself is the biggest thing by far.
2:04:58
The rest kind of feels part for the course to be 100% honest. >> Yeah.
2:05:03
So uh it it seems exciting for the the world of math.
2:05:06
It's certainly exciting as sort of like a a researcher recruitment.
2:05:12
This is where progress is happening.
2:05:14
It's also sort of a useful benchmark like I could imagine in the future uh like two weeks in the future but just a few weeks in the future if you're training you know uh Muspark 1.
2:05:22
you're training you know uh Muspark 1.5 you want to just throw Navier Stokes at it and say don't search the internet don't look at the result can you solve it because that's a good benchmark right um but but I want to know about your philosophy because you went viral with
2:05:38
the Devon launch like what matters to your customers your recruitment because uh there's a world where you're like oh I I I I want to put my throw my hat in the ring and duke it out for different math uh challenges, but that doesn't seem critical path to the growth of your business. Certainly hasn't been because
2:05:53
Certainly hasn't been because you're growing very quickly, but um how do you how do you think about the value of when you're talking to your actual customers, what is important to get across? >> Yeah, for sure.
2:06:04
It's kind of, by the way, it's kind of a hilarious thought also that, you know, we're just going to be like I I actually still think that one of the things that's that that I've never gotten over is like one of the token benchmarks that people do when they're going and training models and doing runs and stuff is a IME.
2:06:16
Like a Amy um and uh I think people don't necessarily know what it is, but basically the AME was uh it's a high school math competition.
2:06:25
It's one of the the hardest math competitions and it basically selects like the top few hundred kids in the US to go qualify for the next level to actually compete for the US team and everything.
2:06:34
Like I took all this, you know, every year as as a kid and it's kind of funny cuz it's like yeah dude your model can't even get a 15 on the Amy.
2:06:40
It's it's out of 15, you know?
2:06:42
It's like what what are you even doing?
2:06:43
But like no human can do that, you know, and we're already someday it'll just be like wow you can't you can't even solve the remon hypothesis.
2:06:50
Like what did your model even do?
2:06:50
Like you must have totally messed up your your pre-training run or something. >> I get it.
2:06:55
You're trying to save money.
2:06:56
So you're using a model that can't solve reman.
2:06:58
Like look, not everyone has token budgets right now.
2:07:02
So you got to pinch pennies. It's cool.
2:07:03
It's probably good at Photoshop. >> But yeah. No.
2:07:08
So for for us, what I would say is obviously like a lot of what matters is show showing the the real best.
2:07:14
Don't get me wrong, be sick if Devon went and solved the Remon hypothesis.
2:07:18
I don't currently expect that that's what's going to happen because it's much less, you know, this this kind of like fundamental, you know, basic science research is much lesser focused as opposed to to kind of going and doing real world use cases.
2:07:27
And so we see, you know, it's like when we show benchmarks, it's like, okay, here's a benchmark on how it does at finding security vulnerabilities in real world code bases.
2:07:35
Here's a benchmark on how it does. Yeah. Right.
2:07:36
And a lot of it is basically just like >> making sure we're speaking to the thing that that that that folks care about and folks need.
2:07:44
But >> so yeah, I mean uh related to that last question, uh how big is the cyber security side of the business?
2:07:48
How much demand is that driving?
2:07:50
Obviously, that's been a huge story this year. >> Yeah. Yeah.
2:07:54
Uh no, I mean it's been it's been a massive thing for us.
2:07:56
Obviously, everyone, I think, is is really thinking about this and thinking about I mean, everyone's kind of freaking out, I guess, is is like the honest way to put it.
2:08:04
Um which is probably correct.
2:08:04
Um I I think cyber security is going to uh you know, it's I I think there's going to be real threats that happen.
2:08:11
I I mean again you know when we say it's like these big orgs take time to adapt and to use new technologies and so on.
2:08:17
Obviously these hackers out there like small teams that are going and using the best of the models are doing their own who knows what they're doing like they're not waiting you know and and and a lot of these capabilities keep getting way better.
2:08:29
Um and so no it's a small but meaningful part of of our business.
2:08:31
It's probably in the neighborhood of like um um you know around 10% of of the Devon sessions or the Devon ACUs that get spent today are on security.
2:08:40
But but we see it growing pretty quickly.
2:08:41
I mean, our security products only like two months old. So, >> I love it.
2:08:45
Well, congratulations on the fund raise. I got to ring the gong. >> Amazing update.
2:08:50
>> A whole bunch of >> There we go.
2:08:54
>> Great to see you, Scott.
2:08:54
Please go please go take out some open problems just for fun.
2:08:58
Don't don't distract the team.
2:09:00
Like, don't don't rope them into it, but just >> we'll faster the next prime. >> Yeah. Yeah. Exactly. Spin up spin up a swarm. Just you and the swarm. >> Great to see you. >> Great to see you. >> Cool. Cool. Thanks for having me. >> Cheers.
2:09:12
>> Well, we were talking about security.
2:09:12
No better time to tell you about CrowdStrike.
2:09:16
Your business's AI, their businesses securing it.
2:09:19
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2:09:21
We will be joined by Greg Brockman, the co-founder and president of OpenAI in just a minute.
2:09:28
In the meantime, uh the Deart uh the Decart acquisition, there were talks that Enthropic was buying Deart.
2:09:37
Um and it seems like they have walked away.
2:09:41
This is an exclusive in Bloomberg, but >> say it.
2:09:45
>> They put Deart before Deorse.
2:09:45
That's the funniest quote tweet by Shashant Roman here on the timeline. Um, >> yeah.
2:09:53
Story uh stories come out that that maybe one of the stick is totally, you know, I I don't I don't know how true this is, but it sounds like one of the sticking points was maybe >> reloc happily building in in Tel Aviv, not wanting to um uh move over to the US. Who knows?
2:10:09
Uh Dean at is incredibly talented.
2:10:14
>> It was a very fun demo.
2:10:14
He came on the show and used his AI image model, his video model. >> Yeah.
2:10:20
his willingness to do just a live demo of technology that seemingly was better than anything else >> that we have seen.
2:10:28
>> I mean, it was it was it was low res, but it it showed you a glimpse into the future.
2:10:33
He would, you know, be prompting it while he was on the call with us talking about what's behind him.
2:10:37
Now I'm in a wizard castle.
2:10:40
Now I'm in a sci-fi, you know, cyberpunk city.
2:10:43
And all of that was uh very very fun to see.
2:10:45
So, uh, I'm sure that they will continue cooking and we will have to check in with them soon.
2:10:53
But we have Greg Brockman, the co-founder and president of OpenAI with us.
2:10:56
Welcome to the show, Greg. How are you doing? >> Doing great. Thank you for having me.
2:11:02
>> Thanks for hopping on. Uh, huge day.
2:11:02
Can we start with the with the math advances?
2:11:06
What is what what is happening? Why is this important?
2:11:08
Uh there's a lot of back and forth in the timeline, but I'd love for you to just set the table for us on what actually happened with uh Navier Stokes today.
2:11:19
>> Well, uh it's always a huge day uh in uh AI and modern scientific progress.
2:11:22
I would say yeah, today we announced that our model had solved the Navier Stokes uh problem.
2:11:31
uh that we found a uh a counter example or an a sort of proof that you can actually uh that these these uh theoretical equations do have a singularity or kind of break down under certain circumstances.
2:11:44
And this is a problem that has been open for a very long time.
2:11:47
It's one of the seven millennium problems which are kind of some of the deepest most important problems in mathematics.
2:11:52
And I I think that the problem itself is important, right?
2:11:56
This is new knowledge for humanity that the proof itself is actually very elegant and beautiful.
2:11:59
And I think that there's a lot to learn from it. Yeah.
2:12:03
And the the equations have lots of application in fluid dynamics in other areas.
2:12:08
But to me, what's even more important is about what this represents about where we are in terms of model capabilities and the fact that we can actually generate new knowledge that we can learn from these models to and have them help us solve problems that are otherwise outside of reach or would take us a very long to solve. >> Yeah.
2:12:24
I mean, where should I actually go with this?
2:12:26
Is this going to help me book a flight?
2:12:27
Is this going to help me cure cancer?
2:12:30
Is this just going to help you recruit researchers who are fascinated by this stuff?
2:12:34
Uh because I think that there's this is, you know, taken over the technology world.
2:12:39
Uh but I imagine that this will not be something that gets talked about at backyard barbecues with friends and family that are three clicks removed from outside of >> Yeah. Yeah.
2:12:49
Well, look, I think that there's first of all the applications of this specific result or the equations themselves, right?
2:12:56
Which are things that let us better understand phenomena from ocean currents to air flow around aircraft uh around, you know, turbulence and things like that.
2:13:03
But it's really about the broader insights and methods that can help scientists and mathematicians further accelerate their research.
2:13:10
And I think that again representative of if we have models that can help solve this kind of problem then what happens from here like what other problems that are immediately applicable and I think that talking about curing diseases and new medicines we're going to be able to develop all of that starts to become much more real when you have models that are at this level of assistance and capability.
2:13:33
And I do think that there are going to be real changes to to think about in terms of we can have so much more ambition with the kinds of of challenges that we can hope to tackle now. >> Yeah.
2:13:45
I I mean I think uh even even if this doesn't break through to the broader uh the broader world uh the weekend definitely will because it seemed like everyone was talking about Blender, talking about Astra building stuff.
2:14:00
uh take us through the launch of Astra, what the feedback has been, what you've learned.
2:14:05
It seemed like there were a couple resets, the model scaled very well.
2:14:09
Uh how was this launch different than previous launches?
2:14:14
>> Well, first of all, I've just been blown away by the community reaction to Astra.
2:14:18
It's been really amazing and very humbling honestly to see all the creativity and the different ways that people have been applying the model.
2:14:24
And I think that it's very clear that we've reached a new threshold of computer use.
2:14:30
So this model is able to I really work with different kinds of applications in a way that was not previously possible and people are taking full advantage of that fact and really thinking about how to create I lots of people showing off 3D creations and >> mapping out physical locations and turning them into into these 3D models and thinking about can you use this for >> design of physical parts.
2:14:52
Someone talked about how they were designing some mechanic for catching hair in a shower drain and that they were able to super cool, right?
2:15:02
That that they're now able to actually manufacture that >> shower hair super intelligence. >> Yeah.
2:15:06
No, that stuff's so mundane, but it's so important.
2:15:08
I I feel like uh a lot of this stuff gets lost, right? >> Exactly.
2:15:12
>> Exactly. And I think there's a core there that's very important which is that >> we are talking about these grand challenges sometimes or very esoteric applications but really the every day the number of problems that you have in your life that you would love to solve it's now possible right that that we're
2:15:28
really trying to empower the individual to make it so that you can be >> you can have superpowers that you can accomplish more and I think that that >> you know really trying to benefit people empower people build tools that can really help you and help you in your your daily life um And that's all part of what we're we're we're working on. >> So yeah, I mean it seems like a huge
2:15:45
>> So yeah, I mean it seems like a huge number of people in uh in tech uh effectively rebuilt their entire house in Blender and plan a remodel this weekend.
2:15:56
Uh thanks Ashra and but I am wondering about the merge and how you bring together codecs work chatt on desktop.
2:16:04
I have a gaming PC now with a Nvidia card in it. I have a Mac Mini.
2:16:09
like I have all these things and I can imagine that I'm just I'm doing that unnecessary or like it's fun for me but uh that early adopter work of going and unhobbling it a little bit here and there but in the future this will all just be tucked in one you know prompt box and it might build a 3D Blender model for to answer my question of should I remodel my house or not.
2:16:30
Um, but how do you see the capabilities that we saw on display from sort of light power users over the weekend actually making their way into uh consumers who might not even know what Blender is.
2:16:44
>> Well, I think you're exactly right that we really want to shift these tools from requiring kind of low-level sort of >> access or guidance to really having the human be able to fly, right?
2:16:58
to really be empowered for you to be able to set the goals and the objectives and that you still should feel like you can get into those details and you can understand them.
2:17:07
understand them. you can provide that oversight because ultimately you should feel accountable for the outcomes but you have this this absolute amplifier right like a trampoline or like a you know rocket ship for the mind like however you want to to to analogize it and I think what that means at a
2:17:21
practical level so first of all this year we've been really seeing this shift from just pure chat use cases to gentic use cases but I would also keep in mind that chat is alive and well I mean we're we're now well over a billion users every week that you can see that the market share of chat GBT is starting to
2:17:37
climb once again because we've been investing so hard in in so many use cases that are important for people in education and health and a variety of other areas and then at the same time these productivity deep knowledge work use cases those are really taking off we've had this like almost vertical wall
2:17:53
of agentic adoption since we launched chat GBT work and I think that the fact that these are two distinct modes that that is actually a point in time that is something that we're continuing to unify and merge and that we're starting to see that there's a new emerging form factor for how people want to consume AI. And I
2:18:06
And I think that it's almost like that the promise of AI has always been that you have something that you can talk to and really delegate work to that's proactive and persistent.
2:18:17
And that I what we were promised if you were to rewind five 10 years ago was never a low-level language model.
2:18:25
You have to think about context windows and you have to select thinking strength and you have to select different models.
2:18:30
Like none of that none of that is is the future.
2:18:32
And so I think that we're moving towards real amplification, real giving you time back, real having computers that are able to operate according to your goals, to your desires.
2:18:42
And I think that that is a core of it.
2:18:45
We're developing this safely.
2:18:48
That's that's one of the core commitments that that we make and how we think about this.
2:18:51
Um but but we really see the power of these tools starting to really um really start to increase in terms of what people are capable of and that under the hood utilizing tools like blender so that that is almost a detail that fades into the background is absolutely the direction of travel.
2:19:06
absolutely the direction of travel. It feels like in AI particularly there's been a almost like a first mover disadvantage in that billions of people have tried Chad GBT and and some percentage of them tried it for the first time and have a certain impression of the product and what it can do and then you know even in the last few weeks there's been new agents and and products
2:19:28
that come online and people try it and their mind is just completely blown and I think it's funny because I'm like well as somebody who's like you know trying to get the absolute max out of Chad GBT I'm like, well, I've been running like, you know, I've had like an agent running that, for example, will tell me every time a SpaceX launch is going to happen and if it gets delayed, right? These
2:19:45
These sort of like persistent agents that are running the background.
2:19:48
Um and but but strategically I feel like it's a it's a new kind of challenge because you have this the as capability has been been scaling first movers need to be almost like constantly reminding the the market of um all these just like new ways >> overhang.
2:20:07
Yeah, we we think about this a lot and I think that there's this discovery problem that we as a field need to really encounter in a first class way and we haven't done it fully yet, but I think we have a real shot at solving it better than any product before because >> the the thing that that right now we kind of rely on.
2:20:28
You think about chat GBT, chat GBT work, these are both text boxes, right?
2:20:32
And it's like, well, this new text box is way more powerful than the old text box.
2:20:35
And but oh, oh, there are some reasons that you still want to use the old text box.
2:20:38
It's not, you know, it's like far too confusing.
2:20:41
People just want something that can help them solve their problem.
2:20:43
The whole point is to get your time back, not for you to have to go and become an expert in all these these internal details.
2:20:47
But at the same time, we also have a model that understands what you're trying to accomplish, right?
2:20:53
That you're explaining to it, here's what I want.
2:20:54
It has a lot of context on you.
2:20:56
has a lot of context on you. And so it should also be able to proactively say to you, hey actually if you ask me this other way or if you add added this connector or if you authorize me to do this or if you you know hook up your credentials in this in this way I can go and do this other thing for you and so
2:21:12
we're thinking a lot about that self-nowledge that onboarding process and I think that is a huge huge opportunity and I think that there is both the the disadvantage that you cite of people tried it they form an impression and it's changed that it's something new but there's also an
2:21:26
advantage I in chat chatbt like over a billion users every week like that is unique no one has that kind of use on on these on these models and I think that the number of people who have tried chatbt before I think it's it's another you know billion billion and a half something like that and so that's a huge
2:21:43
opportunity as well for us to go back to those users and say hey we can now solve the problem for you we can now help you in ways that you didn't see before and I think that it's it's true it's real you look at how many people use chat for health 300 million people every single week with health queries, right? And
2:21:57
And that that's really making a difference in people's lives and that of their loved ones.
2:22:01
And so we have such opportunity.
2:22:03
>> Can you stay there with with health and and and explain where one note before that?
2:22:07
Something that I think is really interesting and I think something that OpenAI can can do a lot better is like when people talk about like everyone in AI wants to be like the Apple of AI from a marketing standpoint.
2:22:18
when they when you think like Apple marketing, you're thinking like Mac versus PC or you're thinking 1984, these big branding campaigns.
2:22:25
But the actual thing that Apple does really really well with marketing is they just hammer really really specific details about their products, right?
2:22:34
They're like >> they're advertising the new camera.
2:22:36
They're advertising Mimoji, right?
2:22:39
They're advertising like >> certain features in Safari, right?
2:22:40
And so it's like with AI, the surface area of like things that you need to communicate is actually like an order of magnitude greater because it could do so many different things.
2:22:50
And so I think there's such an opportunity >> um for the company to focus advertising.
2:22:56
The brand campaigns are awesome and like the the launch video for Astro was amazing, but it's like there should be billboards running of like very specific things that Chach can do to give you back your time.
2:23:06
Um >> yes, this this has actually been a real sort of realization or just like something that I have really come to over the course of of of this year.
2:23:13
And if you look at even for example the you know we just announced chat GBT images 2.
2:23:19
5 >> and if you look at the launch video there the thing that I love about it is it shows here's someone creating an image and here's like a bunch of different variations of it and then here's them taking their favorite one and having it in the world.
2:23:32
like someone said, "Here's a cool like little sketch of a candle holder."
2:23:36
You see an awesome visualization of it and then you see the physical candle holder and you're just like that's what you want, right?
2:23:41
It's like you it speaks to you immediately.
2:23:45
And I think that that really showing people here's a use case.
2:23:46
And the thing that was also a little surprising to me is that we've sometimes highlighted esoteric use cases, something that appeals to someone in particular and it's amazing for that person, but people don't then say, "Oh, because it's this powerful, I can also do this other powerful thing I've been waiting on."
2:24:03
like that connection is is is is something that is less sort of easy to make than I than I'd realize and it makes sense.
2:24:08
What you want is to for there to be use cases where people say I actually want that particular thing now let me go try it myself and then from there you start exploring and you start to find I actually do have this powerful use case that I didn't even realize was tip at the top. >> Yeah.
2:24:21
Probably like the best example of that working really really well.
2:24:25
>> The other thing is is reminding people to ask the AI what it's capable of.
2:24:30
Yeah, like I was I was having lunch with a buddy who's a real estate developer and he is using chat all day long for different like deal memos and to understand like projects that he's working on, all this stuff.
2:24:40
And he'll ask me he'll ask me all the time, can can Chad GPT do this or that?
2:24:43
And I'm like, I'm happy to I'm happy to answer you, but like you have the thing that will just explain exactly how to do the thing that you want to do or or maybe not, but it probably can.
2:24:55
>> Yeah, I I I did the same thing.
2:24:55
I was kicking off this Blender thing and I was like, should I run this as a local codeex thread or in the cloud?
2:25:00
Let me know which one's better based on my system and it gave me a good answer and I was able to go for it.
2:25:07
>> On on images, uh when when images 2 came out, I had some moments where I thought, okay, images is solved.
2:25:13
Like where do you where do you think images actually go as a category?
2:25:16
because it felt uh like this has been something that has maybe ones me more than anything else.
2:25:23
specifically with like when when it released, I was I was um >> uh spending hours like like on a Saturday trying to design furniture, right?
2:25:33
And just going through like you know hundreds and hundreds of prompts.
2:25:36
But how how far can image models go and where are they going and what are the ways in which you think they can um they can be applied?
2:25:44
We were talking earlier too about the downstream impact of of image models.
2:25:48
If you can take, you know, a a physical space somewhere and take a picture of it and imagine it as all these other variations, there's so much like real world activity that will be driven from that because people can see this thing. >> Yeah.
2:26:01
>> Visually and say like I now I want to go make that reality which I think is really cool.
2:26:06
>> Well, I think that's exactly the right way to think about it is as you hit new thresholds of capability, my experience has always been that fundamentally new applications become unlocked in ways that you almost wouldn't have thought about ahead of time.
2:26:17
And so I think that within for example knowledge work, professional work, marketing, all those areas, you just need to be above a quality threshold.
2:26:25
If you're below it, it's a cool concept, but you can't actually use the final material, right?
2:26:30
That that then means that you you haven't really solved the problem.
2:26:32
and that having precise edit control, being fast, and really being creative, and having a diversity of different results, and also being able to >> have this this good interplay back and forth with a person.
2:26:44
I think that that really unlocks whole new use cases.
2:26:46
And I think there's a huge market there.
2:26:48
And even for example, the kinds of things you may not think of naively, but actually start to be really important applications we're seeing happening is slide creation or making awesome websites, right?
2:27:00
Being able to have that image generation capability in the middle is something that's very unique to OpenAI relative to to some of our competitors.
2:27:08
And I think that you're able to then produce much better artifacts downstream.
2:27:11
And so we really view images, we view voice, we view coding, all of these capabilities as one package that are going to come together to create an AI that empowers you.
2:27:22
That means you can create anything that you imagine.
2:27:26
And I think it's going to be something that's just unlike anything out there. Let's go back to health.
2:27:29
I think most people already are aware that you can synthesize some lab data with some sleep scores, but your vision that you laid out recently for where that product goes is much more complex, much deeper.
2:27:46
So uh tell me where uh ChhatBT Health is going in the future.
2:27:52
>> Well, I would think of it as there are three sides to what we do on health.
2:27:56
There's the consumer side again 300 million people every week with health queries.
2:28:01
>> There's the clinician side which is bottoms up >> and that's really about think of it a chatbt that's really tuned for clinicians that gives them direct citations to medical literature things like that.
2:28:14
>> There's a third pillar which is the enterprise side of selling directly to hospitals and them enabling it.
2:28:18
And you can see things like we have an integration within Epic and really trying to bring each of these three pillars the best possible service independently.
2:28:28
But you think about as those really build momentum that you actually are able to get synergies across them, right?
2:28:34
that there's something that actually makes the health experience and the ability to really transform health care in America and the world on the table because there's so many think about how much work you as a patient have to do if you're talking to different specialists.
2:28:46
You have to carry your medical record from one to the other.
2:28:49
You have to explain again here's the issue and that ultimately you're on the hook.
2:28:53
You're the doctor who has to make the decision whether you like it or not.
2:28:55
and actually being able to have just good sharing of of that information across different providers that becomes possible if everyone's on one platform or think about clinical trial enrollment.
2:29:04
That's a huge bottleneck to drug development and finding people who are eligible and will benefit from being involved in a particular trial.
2:29:09
And if you have that kind of of data, if people are willing to sort of, you know, entrust you with that information uh that that's something can actually really benefit them and benefit the world at the same time.
2:29:20
And so what I view us as building is really trying to build the world's best healthare platform to really be able to bring healthare into the AI age.
2:29:27
And I think that it's something that is going to be absolutely transformative to many people's quality of life, really uplift so many people.
2:29:36
And we're seeing it already in such concrete ways.
2:29:38
Some of my favorite stories about chatbt are people who say, "Hey, information I got from chat helped me save my own life.
2:29:46
helped me save that of a loved one that there was this medical issue that someone had and that I if you know the doctor told me one thing I was able to to double check that and understand what they were saying and be able to to push back on it and got to a good outcome and that happens every single day.
2:29:59
So I think that health with these AIs is something that it we're still just scratching the surface of what's possible and I think it's one of the most positive applications of AI that that you can you can think of.
2:30:09
Yeah, I'm very interested to see how uh the advancements in memory intersect with health because I expect that uh chatbt with where memory has gone where I'll be in a new thread and it will bring up just the right information or tie back to a thread that maybe happened three weeks ago.
2:30:29
When you actually apply that to like health related queries, it may be able to like pick up patterns that sometimes would take a human years to figure out like a certain ailment or something like that where it's like, hey, you're asking about all these different things and maybe you thought they were not connected.
2:30:44
Turns out they they actually are and you should go down this sort of like rabbit hole. >> Last question. I'm sorry. Please.
2:30:52
>> I was I was going to say I think that's absolutely right.
2:30:53
We're seeing that very concretely and we've seen, you know, just in my own personal life, my my wife, you know, we talked about some of her her medical conditions publicly, but I it was really this five-year journey of talking to many specialists, each one who was kind of touching one part of the elephant and would try to address that one part.
2:31:09
And it was only finally her allergist who said, "Hey, I think all these symptoms you're seeing are connected and you have this uh genetic condition that affects all of your subsystems."
2:31:18
And that's the kind of thing where it's really hard to say how many people have similar kinds of conditions and just never find out.
2:31:25
How many people have these >> areas where it's like if you just sort of are functionally specialized that you're never going to bring together the whole diagnosis.
2:31:34
And I think that is one of the powers and potentials of an AI that really deeply is able to help you across all parts of your life and also is a deep domain expert in all areas of medicine. >> Yeah.
2:31:45
Uh I have one last question.
2:31:45
Uh what how do you tell the story of operator?
2:31:50
It feels like it was a failure or a side quest, but it feels incredibly important now given the advances in computer use.
2:31:58
Is there a clear lineage there?
2:32:01
What was operator does that still exist somewhere within chat GPT?
2:32:05
H how does how did how did computer use get solved? >> Yeah.
2:32:11
Well, look, I would look at all these things as timing and all about iterative deployment. Yeah. >> Right.
2:32:16
>> Right. that that there's a moment where you need to where the capabilities aren't quite there but actually learning from real world deployment is very helpful right and the I think operator was just kind of below threshold in terms of the model capabilities uh it was a cloud-based system that operated
2:32:33
with computer use it was slow it wasn't fully accurate it was like pretty painful to to use some people got value but it really wasn't above threshold and if you look at what's happened that the team like one thing openai does very well is we make long-term investments on
2:32:46
things that really matter and we do the grind and that the team this year I think really started to build momentum that we put in a lot of effort to go and sort of burn down a long list of issues were able to really focus on solving computer use and I think that they delivered in a significant way and
2:33:02
there's more to do never done all those things but it's a true milestone I think people are really appreciating what's possible because we've been in a world with these agents using computers through connectors right through these very painstakingly coded systems that are so different from how humans use computers. Whereas humans can
2:33:18
Whereas humans can already use everything on a computer, right?
2:33:22
Everything's designed for people.
2:33:24
So if you have an AI that can operate that way and even from the very beginning of OpenAI, we had a dream that one day we could create such an AI, it becomes able to help you across everything that you would be able to do with a computer yourself.
2:33:35
And so I think we're there with Astra.
2:33:37
I think that there's just so much more that people are going to uncover in terms of applications where this can go.
2:33:42
But it's an example of long-term focus, doing the work, and not giving up even when the going gets tough. >> Yeah.
2:33:50
And it feels like Astra, my view is it really felt like all these different bets coming together, you know, at the right at the right time, right?
2:33:57
The the advancements in in the model itself, the the computer use, voice, all these things.
2:34:01
Um, and it uh it's all it's all making sense. So, >> yeah.
2:34:07
>> Um, >> together, it's focus.
2:34:07
It's uh it's something that I think this company does extremely well when we really put a challenge in front of us and think about how to accomplish it safely well and uh to to really deliver the value we're doing thing. >> Yeah.
2:34:19
>> Yeah. put different differently, it felt like when you look at last year, it felt like OpenAI was uh operating like a big company and it and it was a big company but but the way in which like product experimentation was happening was you
2:34:33
know when you think of like a hyperscaler they'll launch a new product thinking okay if there's a 20% hit rate or even a 10% or 5% chance that's okay and then this year it feels like actually the entire company switched
2:34:46
back into actual startup mode which is like you know focus focus focus all these things need to come together the whole team needs to be rowing in the same direction and then the difference in momentum and growth and all these
2:34:58
things uh coming from that and and uh actually taking the company from like operating and shipping more like a big company to shipping again and focusing like a startup has been uh feels like an impossible task and it's been uh incredible to watch. So
2:35:11
So >> yeah, >> thank you.
2:35:14
No, it's been a real real effort from many many people at OpenAI to really bring together and something that that I really value that I think we really value as a company and I think that we're just so laser focused on our mission and really thinking about every piece of what we do should add up to helping us accomplish it.
2:35:29
>> Well, thank you so much for taking the time to come chat with us. >> Great to see you.
2:35:32
>> We'll talk to you soon, Greg. >> Thank you.
2:35:33
>> Talk the rest of your day. Goodbye.
2:35:36
>> Let me tell you about Cisco.
2:35:36
Critical infrastructure for the AI era.
2:35:38
unlock seamless real-time experiences and new value with Cisco.
2:35:43
And we have our next guest already here.
2:35:46
We're running behind, but we'll bring in Sah here from Forest, the founder and CEO. Welcome to the show. How you doing? >> Good. Good to see you guys. >> What's going on? >> Sorry we ran. >> Tough act to follow.
2:35:57
>> Introduce the company. Tell us the news.
2:36:00
I want >> You're headlining for Greg Brockman right now. >> There we go. >> Yeah, no pressure. >> Great opener. >> Yeah, opener. >> It's a lot of news. >> Yeah. Yeah.
2:36:09
I mean, last time I was here in May, we had just introduced for us publicly as the AI network for medicine. Yeah.
2:36:14
And announced at a $1 billion valuation.
2:36:16
I'm back here now four months later and we're announcing our $150 million series C at a $3 billion valuation.
2:36:27
>> And the biggest change for us is scale, right?
2:36:29
We're now supporting millions of people across all 50 states.
2:36:30
Horses already used by Dr.
2:36:33
Street patients in 85% of US residential zip codes.
2:36:34
and we're now working with nine of the top 15 global biioarma companies to help them advance medicines.
2:36:42
>> What is the most helpful thing you can do for global biofarma companies?
2:36:44
We were just talking about uh trial patient recruitment, but then there's also like the much more fundamental research.
2:36:54
There's even just general having a coding agent around can be useful to a biotech company.
2:36:59
But what are you seeing move the needle for them? Yeah.
2:37:01
I mean, so there's an enormous amount of capital and talent going into using AI to discover new molecules. Right.
2:37:07
And that is going to work. Yeah.
2:37:09
We're going to generate more potential medicines for more diseases faster than we ever have before. Yeah.
2:37:15
>> But discovery is really that only the beginning piece, right?
2:37:17
It still takes more than a decade and billions of dollars to turn a new molecule into an approved medicine.
2:37:21
And you have to develop it. You have to launch it.
2:37:22
You have to get to the right doctors, secure coverage and distribution and ultimately get it to patients.
2:37:27
The network that we are building is really intended to help provide both the insight and visibility and the connectivity to kind of support all those steps. Right?
2:37:36
So once a new molecule is ready to test some people, you need to identify the right clinical trial sites and recruit the right patients.
2:37:42
As you prepare to launch, you need to understand which physicians have patients who look like the patients best in the phase three trials.
2:37:47
How should the medicine reach them?
2:37:49
What coverage and distribution need to look like?
2:37:50
Once it's on market, you need to understand, you know, who's receiving it, where adoption or access is breaking, whether people are staying on it, what side effects or positive results we're hearing.
2:37:59
The way that our platform works, it gives us increasing visibility into how medicines are performing nationwide, as well as kind of the clinical and practice behavior of patient physicians across the country.
2:38:10
So, for example, a new drug that came out earlier this year back in March for an autoimmune disease, 40% of all people who have ever taken that drug came through our platform. >> Whoa.
2:38:20
Imagine like that level of visibility is unprecedented, right?
2:38:22
The FDA doesn't have that.
2:38:24
The company that made the drug doesn't have that.
2:38:26
The HR companies don't have that.
2:38:28
And so we have more clarity on what's happening on that medicine. How impactful is it?
2:38:34
Where is it getting stuck than anybody has before?
2:38:35
And that can help these farmer companies not just drive the process more quickly and efficiently, but actually make it more predictable. Right?
2:38:43
And I think kind of the bigger picture in our minds is that as you kind of get this process faster, cheaper, but more predictable, you can actually change the economics of creating medicine.
2:38:53
Uh you can actually make it so these companies can afford to invest in more drugs for more diseases because you have this huge bottleneck between the number of medicines that are theoretically being discovered as molecules and the total number that are actually coming out to market. Right?
2:39:07
It's kind of like the movie industry where there's thousands and thousands thousands of screenplays, but the number of movies actually get produced and become blockbusters that premiere is very small.
2:39:14
And so that's really what our goal is really.
2:39:16
How can you increase the number of medicines that make it to market every year by an order of magnitude? >> Yep.
2:39:21
>> Uh people within the tech industry talk about the AI labs just needing to cure cancer and that will fix the uh or help fix the public.
2:39:31
>> People love data centers then like put one in my bag.
2:39:33
What does the pharma industry think about that sort of like line of thinking?
2:39:37
They're sitting you guys are sitting over there actually doing doing the work not not oneshotting a a blanket cure for all different forms, but at least making, you know, consistent progress towards a bunch of these different uh types of cancer.
2:39:50
So, I'm I'm very curious. >> Yeah.
2:39:55
I was literally talking to the CEO of a top 10 pharma about this a couple weeks ago at a conference where I was like, it's kind of crazy that you guys have such a bad rap. Yeah.
2:40:03
>> And yet the people who have the worst rap in the game right now are thinking that being more like you >> did great.
2:40:12
>> And he was like, "Yeah, it's it's super hard for them to process like what these people are thinking." Yeah.
2:40:17
Um >> and at the same time, I think it's a little bit of a wakeup call like maybe you need to reclaim the story a little bit. Totally. Right.
2:40:24
Because >> uh I mean until we become immortal, medicine is going to become this like it's this permanent industry to invest in.
2:40:32
increasingly become the most important thing that's happening, you know, advanced society.
2:40:36
And these companies are at the root of creating all these amazing cures, amazing treatments >> are villainized uh because people don't understand their position.
2:40:45
Even the way that people refer to them as like manufacturers, you know, versus like, creators, whatever is I think tough.
2:40:50
Um but, you know, they're also at the same time feeling really eager to invest in AI.
2:40:57
I mean, part of the reason we've seen such dramatic uptake is because most of these leaders are like, well, we need to reinvent our businesses because we are already actually doing so much of the complicated and and gamechanging R&D.
2:41:08
And yeah, we're going to benefit from some of the tools that people are going to sell us to help us do some of that molecule research faster, but we need to reclaim the story and and accelerate how much we're pushing kind of through the market.
2:41:17
I mean, even like GLP1's, like how much credit are they getting?
2:41:21
>> I was just saying this. Yeah, >> totally. >> Totally. Yeah.
2:41:22
It's like you sort of cured obesity pretty close to it.
2:41:24
That was a huge problem for >> Yeah.
2:41:28
But what have you done in the last day?
2:41:29
>> I'm just imagining like like like in uh you know amnesia you wake up and you're the CEO of Fizer and you're like what do I do for a living?
2:41:36
It's like you help sick people and they're like I must be loved.
2:41:40
Like actually quite the opposite crazy time.
2:41:44
>> The story around GP1 itself is like I think even still underrated.
2:41:46
We've such an influx in applications from beriatric surgeons wanting jobs in technology and trying to kind of move out of medicine because GOP ones have basically eliminated that specialty as like something that matters in the country which is so crazy. >> Yeah, it's crazy. Uh last question.
2:42:03
Well, what is uh the biggest insight that you gained from working at Oscar Health that you carried into today?
2:42:08
Like like what is the thing that you're like okay I understand the structure of the industry or I understand this thing or this >> healthcare is easy. Is that >> Yeah.
2:42:20
I mean, I think the thing that really clicked for me there is how much discontinuity and heterogeneity there is in the system, which prevents any individual player from really like even tracking what's happening, let alone having control over the process. Yeah. >> Right.
2:42:35
Is actually what I think makes this problem so interesting and and and beneficial to to to focus on with agents. Yeah. Right.
2:42:43
There's like no standard case in the system.
2:42:45
Every doctor's office has different systems and processes.
2:42:48
Every insurance company has different rules.
2:42:50
Every drug has different clinical and coverage and distribution requirements.
2:42:53
And even individual patients have their own financial situations, medical history, eligibility, and insurance circumstances.
2:42:59
And so the level of uh you know difficulty in actually making progress before this technology um was kind of hard to uh under um underwrite.
2:43:15
And what we've seen is like not only can you use the tech to kind of dramatically change how quickly and efficiently these processes occur, you can actually because you were the first company to actually see the full process and control the full process like create new market power and change things that historically would have only been in the hands of the insurance companies and hospitals to really operate. >> Yeah.
2:43:33
Well, congrats on the progress. Amazing news. >> Really wild progress.
2:43:38
>> Bank Capital, love them. They needed a win. >> No, we love them.
2:43:41
Uh, thank you so much for coming on the show. We'll talk to you soon. >> See you soon. >> Goodbye.
2:43:47
>> Let me tell you about Railway.
2:43:47
Railway is the all-in-one intelligent cloud provider.
2:43:51
Use your favorite agent to deploy web app, servers, databases, and more.
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2:43:59
We have our next guest in the waiting room.
2:44:03
We have a few other changes to the schedule, but we're moving on to Andrew from Split. Pay Andrew. How you doing? >> What's going on? >> Good. Thanks for having me. Welcome to the show.
2:44:13
Uh, since it's your first time in the show, >> great to finally meet you, by the way.
2:44:16
I've heard heard a lot about you from uh >> We know a lot of people in common. >> Yeah, I know.
2:44:20
Bunch of people that Andrew used to work with, used to work on Party Round. >> Oh, that's right. Amazing.
2:44:24
Well, uh, good to have you here.
2:44:27
Let's, uh, let's start with a little bit of an introduction of the company and then I want to hear the news. >> Sure. Yeah.
2:44:33
I mean, I think there's, uh, there's two parts to the story.
2:44:35
There's sort of the what we do and and then how we do it.
2:44:38
Uh, and they're they're very different.
2:44:40
I think that what we do is quite simple.
2:44:41
We like to say that banks move money and we move time.
2:44:46
>> And the basic premise of the company is um essentially to create like a net 90 but for consumers.
2:44:51
So kind of start with this idea that you know what do wealthy people have first and foremost?
2:44:56
Um it's time time to make you know good financial decisions and avoid bad financial decisions, right?
2:45:02
Everyone uses debt but the wealthy can use it to their advantage and uh you know people who are less less well off often get trapped in this sort of death spiral.
2:45:10
So the idea is how do we create sort of um uh you know essentially uh room float uh around an average American whereby to the extent that they're paying for things and you know the biggest things people pay for housing and autos and you know insurance student loans um how do we let them sort of pay it on their schedule?
2:45:29
Um, and you know, right now we're at 30 days.
2:45:32
Our goal is to get to 90 90 days of sort of float where they can shift all these dates around.
2:45:36
And what we found so far, uh, and we now have a million people using us, um, is that this is actually all financial anxiety is downstream from this.
2:45:46
>> Once you have a little bit of room, and it doesn't it doesn't have to be a lot, just just a couple of weeks to kind of move your bill uh, payments around so that it better sort of cycles with your paychecks and other source of income, you just breathe better. >> Yeah.
2:45:58
Um, what does actual customer uh adoption look like? What is it? Where does it come from?
2:46:05
Are is this direct response advertising?
2:46:06
Are you partnered with uh mortgage lenders and uh and uh rental buildings to offer this service?
2:46:15
Is there some integration that you need on the other side?
2:46:17
We've seen uh there's been companies that have done like pay your rent on a credit card or pay your mortgage on a credit card and that's always felt like sort of crazy.
2:46:25
like I can't imagine being like okay I have to take a 3% cut now.
2:46:27
Um so how have you solved all of that?
2:46:32
>> Yeah so this is the sort of the what there's two pillars to I think what we've built and and it's taken us some time to build it.
2:46:37
So I think for the first two years of our existence I think we're more like a lab but we built our own foundation model first and foremost for underwriting and it's a cash flow based model.
2:46:45
Um it's entirely trained on in-house data and then we apply deep learning to it.
2:46:49
So um you know the performance is pretty stunning.
2:46:51
I think we're the best cash flow underwriting uh model in the country today and I think AI underwriting >> and with that do you mix in credit card uh like credit data credit reports because I imagine that those will at least be helpful a little bit they're not helpful at all or is that a cost savings thing?
2:47:10
>> We feel we feel very strongly that it's not helpful at all and we tried everything.
2:47:13
We tried we started with FICO.
2:47:15
We tried every offtheshelf model. >> Wow. >> Yeah.
2:47:17
Unless you put your own money at risk and you train your own model.
2:47:19
It kind of gets into that sort of sovereign model. world, right?
2:47:22
Um, you really don't get the alpha FICO. I mean, it's crazy.
2:47:24
I I you know, I didn't set out to sort of try and destroy FICO, but just increasingly you start to realize how ridiculous the whole >> I mean, I you know, it's it's a sacrifice have to make, but but you know what it is, if you just think about it, it's it's it's a rating, right?
2:47:38
It's like you're an Uber driver and you're just like you're you're driving people around in this case, like you're doing deals with lenders and if a lender likes you, they give you, you know, five stars.
2:47:47
If they don't like you, they give you one star.
2:47:49
But because it's the only way that people get access to credit throughout their entire lifetime, um it's really impactful and I think increasingly what we find and we believe is that it's outdated.
2:48:02
>> Um and the people that suffer is anyone under 40.
2:48:06
>> So our model is really is really tuned to what we think is sort of like the the core constituency these days, which is millennials.
2:48:13
By the way, millennials are 36 now, right? On average.
2:48:14
So our customers are sort of in the, you know, 35 to 40.
2:48:18
They're most sort of productive period of our life where like, you know, they make more money every single year, which you think would be amazing for your credit score, but as you guys know, it isn't.
2:48:28
Not unless you're you're doing deals all the time.
2:48:32
>> This this company sounds like a working capital nightmare for you.
2:48:34
Uh where is the money coming from?
2:48:37
Is it venture dollars that wind up uh dealing in creating this float or do you have a lender or a bank that So we have we have uh we have sort of a layer cake of facilities in that sense.
2:48:49
I think our our capital structure is very similar to like of a BNPL like a firm and Max Lechon is an investor.
2:48:54
So you know we've learned we have some great people that have sort of set us on this path but I actually want to go back to just really quickly.
2:49:00
I didn't realize I didn't address the uh the distribution piece.
2:49:04
The thing that we created that's really kind of fun.
2:49:05
So you again I'll use a firm as an example.
2:49:07
You probably heard of his concept of like a creditback debit card. >> Yeah. >> Right.
2:49:11
where you use a debit card, but it has actually a little bit of float attached to it and it's sort of dynamic.
2:49:16
You could swipe it even if you don't have money on it.
2:49:17
It'll sort of sort of stretch to fit whatever you're trying to bill.
2:49:21
So, we built this for a >> and it's really nutty.
2:49:23
So, so you to ask, do we partner with any? We don't.
2:49:28
>> Uh you can use split pay to pay any bill anywhere that takes a >> m >> and what it will do is we will in real time dynamically >> investments the next a Um yeah, who is writing all these checks?
2:49:44
This is not what we built this company for.
2:49:48
>> I mean, one of my bigger bets. >> Well, it's funny.
2:49:52
AC, right, is 10 times bigger than a credit card network.
2:49:55
It's the biggest payment network in the country >> and it is like painfully old school and insecure and very very slow.
2:50:01
But we managed to augment it so it actually acts like a credit card.
2:50:06
So we have a concept essentially like an off um and a capture and a settlement over a and it just breaks down all walls for us.
2:50:12
So we um we're everywhere.
2:50:16
>> Yeah, that makes a lot of sense.
2:50:16
Uh well, you have the credit facilities.
2:50:17
Uh you're also raising equity.
2:50:20
Tell us about the latest round.
2:50:24
>> Yeah, so we um you know really unleashed the product in earnest about a year ago.
2:50:29
Uh and then you know we we we did a million run rate in the first month and we're just about to cross 80 uh 80 million today and I think today is actually the team's on it right now.
2:50:39
Today is our biggest origination day ever. >> Wow.
2:50:41
>> It's great to be here. Yeah. Um um yeah.
2:50:47
So so what's been really interesting is that no one scaled the lending business this quickly before.
2:50:51
uh because it's truly really really hard because you have this interplay where you have to acquire customers in order to raise venture dollars in order to close credit facilities and you have to be doing this basically permanently.
2:51:05
You're constantly scaling and so in our case that meant that you know we we did you know we we launched a product with basically a venture debt facility and then grew it really quickly and then closed our series A led by Coastal Ventures.
2:51:17
Um, and then you know within within you know 5 months we were 5x bigger and so we closed the series B with with Kla and so they've been with us along the way and uh you know I think I'm I'm like I've been in permanent fundraising mode for sort of 12 months.
2:51:32
I think I'm starting to feel you know I understand what uh what Eric at at RAM sort of feels but but I think he's like he's sort of uh he he loves the grind.
2:51:43
So I don't know for me it's like I want to cry sometimes. Yeah.
2:51:46
>> Well, get ready to do more of it.
2:51:48
>> I don't think I'm resigned to it now. >> Job's not finished. That's what we say. As Eric would say. As Eric would say.
2:51:54
Well, thank you so much for coming on the show. Progress. Talk to you soon. Have a good one. >> Awesome. I'll be back. >> Goodbye. >> Can't wait.
2:52:01
>> Uh, quickly, let me tell you about Figma agents. Meet the canvas.
2:52:03
Your AI agents can now create and modify your Figma files with design system context.
2:52:08
And we have our next guest, Harry from Antioch.
2:52:15
He was supposed to be on earlier.
2:52:15
We brought him to the end of the show, but we're very excited to be joined by Harry, the co-founder and CEO of Antioch. Welcome to the show.
2:52:22
Sorry for the switch up on the scheduling.
2:52:26
Thank you for being flexible. How are you doing? >> What's going on? >> Doing great.
2:52:31
Thank you guys so much for uh for having me and excited to to close this out with you both. >> Yes.
2:52:36
Excited to have you here. Uh please uh break down.
2:52:38
Well, we'll get to the news, but I want to I want to understand how you got into the business of training robots in simulation.
2:52:45
A bunch of questions about the sim toreal gap and all of this stuff.
2:52:48
What's going on in the broader ecosystem, but where have you been focused?
2:52:53
Where are you focused now? >> Yeah, 100%.
2:52:57
So, our co-founding team at Antioch all met at Stanford working on physical AI, applied AI.
2:53:02
I spent some time at the autopilot team at Tesla as well and then kind of went into a bit of a company building mode with many of the same team that we have today.
2:53:12
>> And so I think you know our observation really looking at the industries that have kind of moved the fastest over the last couple of years is that these are the industries that have sort of unlocked recursive self-improvement. Right.
2:53:25
Like earlier today we talked about >> Yeah. >> Exactly.
2:53:27
>> Exactly. math Navia Stokes uh Scott was on uh I think you know Cognition and Devon have done a fantastic job of this in the world of software and I think our observation is that you know automating the physical world is really the defining economic opportunity of our
2:53:42
time right you look at the GDP that's tied up in that opportunity but we don't have that recursive self-improvement and so really at Antioch everything that we do is built around this idea of how we unlock RSI how we unlock goal mode you know for physical autonomous systems. >> So yeah, how do you do that? I mean, I
2:53:59
>> So yeah, how do you do that?
2:53:59
I mean, I don't know what the status quo is.
2:54:00
We saw a bunch of people using Blender.
2:54:02
I know you can make an inverse kinematic model in Blender. We have Unreal Engine.
2:54:08
You can do some simulation stuff.
2:54:08
It look I I I can play a video game and watch a robot walk around.
2:54:12
It looks like you could learn from that, but clearly you need to go deeper.
2:54:15
So what's missing from just build your robot in Unreal Engine, have it press a bunch of the keys until it learns to walk around?
2:54:25
>> Yeah, it's a great question.
2:54:25
And so I think you know broadly the the the market today is a spectrum defined by two ends.
2:54:32
One end is kind of exactly what you're describing.
2:54:33
So it's these classical you know like almost video game like engines with with really high fidelity.
2:54:38
And on the other end I think we're seeing a really promising landscape of world models kind of come to the four right >> and I think our observation at Antioch is that both of those approaches today experience a a reasonably substantial simtoreal gap. Right?
2:54:53
there's a fidelity issue.
2:54:55
That means that if you're relying on one of those approaches in a singular sense, you're going to be missing some of the real stuff about the real world and you're going to experience a a bit of a rough landing in reality.
2:55:05
So, our view is that, you know, the reason why that is in the the sort of like classical world of video game style simulation is it's just really hard to encode everything about the real world in software, right?
2:55:17
Like you go out to the real world, you find out, hey, actually wind matters now.
2:55:20
Now, I need to add wind into my simulation.
2:55:22
And it's this long tale of whack-a-ole.
2:55:26
>> Whereas on the sort of like end to end learn side, you actually experience a very similar thing, but it's about a data accumulation strategy.
2:55:31
And in the world of physical AI, we don't have infinite data, not even close.
2:55:36
And so, you know, we believe that these world models are going to be the right approach, but we just need to kind of play the game on the table right now to actually help, you know, real companies building real things in the present day.
2:55:49
And so our approach is a bit of a hybrid where we use that classical simulation where it works and we kind of learn the gaps.
2:55:55
We learn where it doesn't and it's helping us sort of move our customers along, you know, that spectrum essentially eventually towards these world models.
2:56:03
You know, we've seen some incredible launches from World Labs and others and and that's an incredibly exciting future.
2:56:07
We think that's where the puck is headed, but we need to kind of like help shift real companies in that direction over time as the technology kind of becomes completely ready.
2:56:16
talk about your various robotic timelines uh on on the autonomous driving side.
2:56:22
Every time I've asked any automotive technology executive, >> some someone came on the show and said like 2050, >> it was more like 2040 for a major supplier of of technology for pretty much every car.
2:56:38
I'm not going to say too much cuz people will guess it, but he he basically wouldn't give an answer.
2:56:42
He was like, man, may maybe >> we've had people on the show that think we're getting Dyson's fear before this guy thinks we're getting full self-driving cars.
2:56:50
That's the range of predictions we're dealing with on this show. >> Yeah.
2:56:55
And so that's a category where like we see close to full self-driving already with with, >> you know, Tesla and Whimo and all this things.
2:57:04
So the technology actually exists and you have industry executives saying like, "Yeah, it's going to give give me 15 years minimum."
2:57:08
Um, but I'm curious for you from your lens, I I expect a lot of this stuff to come, you know, real advancements to come from, you know, new companies.
2:57:17
Um, and and I'm curious your view.
2:57:21
>> Yeah, I mean, I think now it all comes down to the sort of data flywheel, right?
2:57:25
And so I think the advantage that autonomous driving has, and by the way, I don't think it's it's 2050, right?
2:57:28
I mean, I think we've we've seen Tesla and Whimo and also companies like Wave actually now doing these deployments that work extremely well. Totally.
2:57:36
And so the reason why is these companies have built this incredible data accumulation flywheel, right?
2:57:42
So Tesla's is particularly brilliant because if you buy one of those cars, you're essentially paying to help them train this system and get kind of more and more data into that engine.
2:57:52
And I think now we've kind of got good line of sight on architecturally what are the models need to look like that sort of unlock that autonomous future.
2:57:59
And so bringing that to new industries is really just a function of are you able to get the data at the scale and also in the kind of right categories not only when things work well but also really importantly when things are not working well and so I think that timeline is going to be purely a question of how how quickly can you build that flywheel.
2:58:18
We've obviously got a bit of a chicken and egg kind of scenario in the world of robotics, in the world of, you know, industrial automation and these types of things where deployments are a little bit nent.
2:58:29
And so that's kind of really one of our key bets at Antioch is like if you want to bootstrap that incredible opportunity, you need to figure out a way to be much more sample efficient than we are today.
2:58:39
And so again, that's our hybrid simulation approach, right?
2:58:43
That's like we can take a small amount of data from the real world, use that to train improvements to simulation.
2:58:47
That simulation then trains a better version of the robot in the physical world.
2:58:51
You can scale your deployments faster and it becomes this kind of virtuous flywheel effectively.
2:58:58
>> I can't wait for robotics companies to be uh playing the benchmark game, right?
2:59:03
Instead of the pelican will be like mon juggle five balls, juggle six balls, juggle seven balls, juggle eight balls, >> Mona Lisa bench.
2:59:10
will be like, "It still can't make me a good sandwich." >> Yeah, 100%.
2:59:17
>> It put the mustard on the top and I like it on the bottom. It's not here.
2:59:21
>> Possibilities are endless, right?
2:59:21
I think we saw this with with Micro Duck in the last couple of weeks, too, right?
2:59:26
Like Micro ridiculous benchmarks of ducks, you know, balancing balls and and and things like that.
2:59:32
We're going to see a proliferation and explosion of this.
2:59:36
>> How many customers are in your TAM?
2:59:39
because we've had a few humanoid robotics companies.
2:59:41
There's like a few names.
2:59:43
Uh obviously there's the self-driving car companies.
2:59:45
There's some industrial stuff that's happening.
2:59:47
But like are you in the absolute top of your CRM?
2:59:52
Are we talking about like a hundred companies?
2:59:54
Are there thousands of these companies?
2:59:56
Like I can imagine building a great business selling to 20 robotics winners, right?
3:00:01
But like how how big is this market and where is it going?
3:00:06
>> Yeah, it's it's a great question.
3:00:06
So I think a couple of responses to that.
3:00:08
So, so one is like even present day it's massive.
3:00:12
Like we're talking tens of thousands of companies.
3:00:14
There's all the ones that you'd think about, right?
3:00:15
So the humanoid type companies, self-driving, all the same kind of stuff that you described, but for example, today we we announced our partnership with with uh Amazon and in particular the Ring team at Amazon, right?
3:00:25
And so this is smart security devices.
3:00:26
And so, you know, essentially it's any system that has this hardware, software, machine learning component where testing in the real world is really difficult and really expensive and you need to kind of get that recursive self-improvement flywheel.
3:00:42
And so, I think it's there are a ton of companies here that you probably wouldn't typically think about as being physical, but really are. >> Yeah.
3:00:50
Everything from a robotic vacuum cleaner to like robotic drone, camera drone, sports, like there's there's just going to be robotic pieces.
3:00:57
Even if it's not a robot, a humanoid in every category, there will be something that benefits from this. Uh, fascinating.
3:01:06
>> Well, uh, what a great, uh, what a great industry to be in. Very excited.
3:01:09
So glad that you have some fresh funding and good luck with the journey. We'll talk to you soon.
3:01:16
>> Yeah, great to meet you, Harry. >> Amazing. >> Come back on. >> Thanks, guys.
3:01:18
>> Have a great rest of your day. Appreciate it. >> Goodbye.
3:01:19
Up next, we have a surprise guest, Rohan, who connected GPT6 Astra to a wearable he built for back pain, and it's giving him real time back pain physical therapy.
3:01:34
We're going to bring him in.
3:01:36
I saw some people in the chat asking, chanting for Rohan.
3:01:41
>> Let's see if he can handle foot pain because I destroyed my foot surfing this weekend.
3:01:46
Uh, what's going on, Rohan? >> How you doing?
3:01:49
>> Hey, how are we doing, guys? Nice to meet you guys. How you doing? Yeah, great to meet you.
3:01:52
Glad to have you pop on here.
3:01:54
>> Busy, busy day in the in the world of um of technology, but you managed to break through. >> Yes. Huge.
3:02:00
>> Yesterday, little Sunday ripper. >> Yeah, absolutely. Uh, yeah. Break us down. What was your process? How long did this take? What was your goal? Set the stage for us. >> Yeah. Yeah. Yeah, for sure.
3:02:10
So, like, um, actually goes back to I was 13.
3:02:12
Had back pain for like a decade in and out of care.
3:02:16
I don't know if you guys been to PT, but like >> yeah, >> you know, like >> PT doesn't have the kind of classic modern like measure care measure again.
3:02:23
It's just like they kind of look at you and they're like, "All right, here's some exercises. I'll see you next. Let's see how it goes."
3:02:28
Um had back pain at uni, decided like this is this is not it.
3:02:32
Moved to my childhood bedroom, built something, found like a thread on Twitter saying who's running angel checks for hardware. Just DM'd everyone.
3:02:41
um moved from Boom Supersonic.
3:02:44
Actually got back to me, got on a call.
3:02:46
First call I ever kind of took. He brought me a check. I was like, "Oh, wow.
3:02:48
Okay, this is something." Moved to China.
3:02:51
I basically just took that check to China.
3:02:52
Just slept in a practice in Shenzhen smoke.
3:02:55
>> Wait, we met we we met I just realized that uh we we met before. Yeah.
3:02:57
Sorry, I I I didn't put it together. We we had a phone call. We had a phone call. Yeah.
3:03:03
Will Will was Will introduced me and was like, "You got to meet this guy. He's crazy. He's living in China.
3:03:06
He's solving solving solving back pain." >> It's amazing.
3:03:11
a very Chinese time in my life.
3:03:15
>> Smoking cigarettes, I'm sure.
3:03:19
>> Highly recommend >> with AI, we will invent the smart cigarette that tells you exactly >> I saw a LinkedIn cigarette somewhere which is I think hilarious. >> Wow.
3:03:32
>> Anyway, sidrack >> anyway. Sidrack.
3:03:36
So yeah, um built this MVP, shared it on Reddit, uh got like, you know, really really good reception there, met our first customer. That's me now. There we go.
3:03:44
And yeah, basically took that, came to the valley, put together some money, and like was like, "Okay, like let me try build this thing."
3:03:50
And it was like really kind of it's just me, one man team, >> like taught myself how to build hardware, moved to China, build all myself. Same with the code.
3:03:57
And it's like it's just honestly nice to see the fruits of my labors.
3:04:00
fruits of my labors. people like people have been coming like text me they okay I've had back pain I've had ankulospondilitis other congenital condition how can that be used like for for their conditions and it's just really interesting because I'm like okay well this is great I'm really just kind of humbled by it and really want to double down and really kind of like bring this out to the world and hopefully help many many more people
3:04:22
just >> Okay so quick timeline you spent a long time actually building this wearable getting it manufactured so you effectively had a data feed, maybe an API, something spitting out data, and then over the weekend you visualized it
3:04:37
in this particular way and and wired up a 3D model to the data that you were already collecting, but the plans to sell the device that collects the data that then will be enabled by AI and everything else. >> Yeah. Yeah. Basically, it's like Yeah. >> Yeah. Yeah.
3:04:49
Basically, it's like Yeah.
3:04:52
Like it very fundamentally, yes.
3:04:52
It's like for consumers, it's for people with back pain to understand the road. Yeah.
3:04:57
Because like >> Jordy, you said you have foot pain.
3:04:59
Hopefully your PT works out, but it's like wouldn't it be nice that if you go to one or two or three PTs, you have like a grand like okay like my my foot's getting better or was not so this PT is working for me and these two aren't.
3:05:10
That's what I want to give people with backpack pain care. Yeah.
3:05:12
pain care. Yeah. And then the kind of greater take there is really I think that you know with what these models can do now we can build pretty much whatever we want on the software side and >> really it's the data it's the data collection that really rules because it's like okay what does the AI need to make intelligent decisions about about
3:05:30
my body like we'll have an AIP in our pocket >> but it needs to understand like what's going on with our body right now and I'm really excited to like kind of bring out this form factor of patches that you stick to your body because I think that that can really nicely scale like we've only done wrists and fingers if you think about it. Um and like now heads
3:05:45
Um and like now heads heads are kind of coming to get come into play.
3:05:48
Um we can cover the rest of the body and like kind of basically collect every bio market that we might need for our AIPCP to make great decisions about our health day today.
3:05:57
>> What's the plan to sell a lot of these I can imagine everything from Facebook ads to working to infomercials and late night.
3:06:08
>> That's a great question.
3:06:08
infomercials or Shark Tank.
3:06:11
>> Infomercial, you're smoking Chinese cigarettes.
3:06:13
>> No, I mean like there's a lot of different ways to you can get reviewers and sponsor podcast >> full ironic sense.
3:06:18
Infomercials would rip actually >> probably, right?
3:06:20
I mean, you're sitting there your back might be hurting maybe.
3:06:24
And I bet you the inventory is really cheap nowadays. >> I mean, yeah.
3:06:27
And also live selling is like infomercials before dead. >> Sure. Sure. Sure. Yeah.
3:06:31
>> Like candidly like one of my investors Justin May wrote his great book Traction uh if you know. Yeah.
3:06:36
Uh, and I've like basically over the this is actually how this came about.
3:06:40
This kind of viral moment.
3:06:42
>> That's a broth guy, right? >> Hammering. Sorry. >> That's a broth guy.
3:06:47
>> We love a good friend.
3:06:48
>> If anyone knows anything about setting a lot of like a product himself, right?
3:06:52
And uh basically just been hammering out like a process of like, hey, let's just see what channel works. Sure.
3:06:57
Doing a bit of like just testing out. Tried page.
3:07:00
I was like, okay, let's now try Twitter.
3:07:01
This is actually the results of me trying Twitter, which is lovely.
3:07:04
kind of like snowboarding and like we'll just see how far it goes and really make sure that we are where our customers want us to be.
3:07:12
>> So people are joining the wait list at yourback hurts. com. Give me a timeline.
3:07:19
>> When can people actually buy this?
3:07:19
Are you going to take are you going to take deposits and then ship or do you want to go straight to order and then ship?
3:07:25
Uh is this going to be the Tesla Roadster of back pain? >> Good question.
3:07:31
Uh I think we're aiming to ship January at the start of January.
3:07:36
Um, we'd like to make it a lot more affordable in Tesla Rosa. Uh, and I think we can.
3:07:41
We've done like this I spent so long building this like I've done with a lot of engineering in the back to actually just shove down, you know, economics. >> Cool.
3:07:47
>> To basically we I'm trying to I'm trying everything I can to charge less basically >> and still make it work for people.
3:07:52
So yeah, like aim to ship in January, sign up your um your backhurts.
3:07:56
com >> and do basically and we'll open the wait list to our first customers. Very cool.
3:08:06
>> Well, great to uh great to see you face to face. Yeah. And uh come back on. >> Yeah.
3:08:11
Come back when you launch. We'll talk to you soon. >> Yeah. All right. Take it easy. >> Have a good one. Thanks, bro.
3:08:16
>> Uh we have the first results of Waldo Bench.
3:08:18
Tyler, put them together. Let's see.
3:08:21
Let's see how chat GPT images 2. 5 is doing.
3:08:24
What did you make, Tyler? You made OpenAI dev day.
3:08:28
Wait, actually, this is sort of hard.
3:08:31
I It looks good, but I can't find Waldo. I need to zoom in. Where is Waldo?
3:08:37
Is there only one Waldo here? >> Yeah. >> Okay, I found him. Yeah.
3:08:41
Uh, it needs to be a little bit more detailed when I zoom way in.
3:08:46
If I zoom way in, faces start getting garbled.
3:08:49
But man, some of this zoomed in text is really, really good.
3:08:54
It's uh pretty high fidelity.
3:08:54
I think we're getting close.
3:08:57
I want to see I want to see this paired with Astra tiled.
3:09:04
A lot more reasoning put into it.
3:09:04
Let's finally solve Waldo bench.
3:09:07
I think it's possible with modern AI. What do you think?
3:09:14
>> Yeah, I can't find Waldo. >> So, you gave up.
3:09:17
>> That seems like a good >> You gave up. >> I took a quick look.
3:09:20
>> What about in the second one? The second?
3:09:22
>> Honestly, I was getting distracted by the beach one. >> The beach one. Pull up the beach one.
3:09:26
Everyone can take a take a quick gander. Try and find Waldo.
3:09:29
I think this one's pretty easy. >> Close it. Close it.
3:09:32
You only had five seconds. >> Okay, you fail. No.
3:09:35
Uh I think this one's not dense enough. >> Yeah, too easy. >> It's too easy. This one's too easy.
3:09:40
Uh this is about one quarter of a real Waldo.
3:09:45
For the real Waldo heads out there, they're not they're going to be a This is not This is not soda.
3:09:49
Actually, I guess it is state-of-the-art, but it's not super intelligence for Waldo generation.
3:09:56
It's pretty good, though. Looks pretty good. I like it.
3:09:58
And then uh what what is this animation?
3:10:01
Explain the animation that you shared.
3:10:04
>> Uh yes, this is like stopotion animation, but this with the new image model. Okay.
3:10:08
And then uh I just had to ask for make it into a video. >> Oh, cool.
3:10:12
>> So, the it's much more consistent.
3:10:13
That's like one of the big >> consistency >> big improvements. >> Very fun.
3:10:16
Well, I look forward to getting Jordy sending me AI images at 3:00 am when he's up vibe designing the next piece of great furniture or something like that.
3:10:26
Um, no, it's a lot of fun.
3:10:28
Anyway, uh, there are there are other stories >> and we're going to get to them tomorrow.
3:10:34
>> Tomorrow, >> but I'm glad we cracked the fourth hour.
3:10:38
We're in the fourth hour. It's been a while. >> In the fourth hour. >> It's been a while.
3:10:42
>> Uh, we got through summer. We did it.
3:10:42
We did Summer's famously a little slow news day. Slow news season. We're back. It's September.
3:10:50
We're going in the fourth hour. Get ready. >> 108 days and hours. >> Fifth hour.
3:10:56
>> I got a text from a buddy. >> Yeah.
3:10:59
>> Who saw or sorry, 107 days.
3:10:59
He said he already got his tree up.
3:11:04
I can't tell if he's messing with me, but I but but I but I'm just going to pretend that that um >> if you put up your Christmas tree 107 days early, you you have some serious botany to do.
3:11:14
Like you need to keep that thing alive.
3:11:16
You got to be watering that thing regularly. There's a lot going on.
3:11:21
Like I don't know that a Christmas tree is meant to survive 177 days.
3:11:22
It's sort of like a new level of challenge.
3:11:25
Just say you haven't cut a hole in your floor and gone down to the dirt and just you constantly are growing a tree.
3:11:33
So, you're cutting it and pruning it, whatever.
3:11:36
But it's just a living tree in your home.
3:11:38
Just say you haven't done that.
3:11:40
>> There are some houses that have little tree areas inside the home.
3:11:41
Maybe maybe this is the future Christmas home.
3:11:46
Design your entire house around around being able to grow grow a Christmas tree constantly on a never- ending cycle.
3:11:54
Anyway, thank you for tuning in to TBPN.
3:11:56
We will be back tomorrow at 11:00 a. m. Sharp >> rolling flash.
3:12:02
>> Five stars on Apple Podcast, Spotify.