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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TBPN.
Speaker 2:Today is Thursday, 09/18/2025. We're back in the TBPN UltraDome, the temple of technology, the fortress of finance, the capital of capital.
Speaker 1:Hello It's been everyone here.
Speaker 2:Bobby Conn.
Speaker 1:Since we have podcasted.
Speaker 2:It has been. We had a bit of a dry spell. We fixed it. We're back. Thank you to everyone in the chat.
Speaker 2:It is to never missing a stream.
Speaker 1:All of you, Andrew Miller, Bobby Cosmick, Parker, Bird.
Speaker 2:Good to see you guys. We yesterday, we were at Meta Connect twenty twenty five, and they launched the Meta Ray Ban displays twelve years since the launch of Google Glass. Google Glass was 2013.
Speaker 1:Did you ever get a pair of Google
Speaker 2:owned them. They were $1,500 at the time. I was dead broke. Could not afford them. Probably would have bought them if I had the money.
Speaker 1:But It would have cut your runway by, like, 15%.
Speaker 2:For sure. For sure. It would have been rough. But I did get to try them in San Francisco at the time. And it was it was cool.
Speaker 2:Very small screen, very limited interaction. Some of the same demos, honestly, messaging, maps, music, the usual, but way less stylish. Way, way less stylish. And and very quickly, the world was not ready for the glass hole, the the Google glassware. Are you familiar with that term?
Speaker 2:It was one of my friends, actually, I think he got I think he got, like, assaulted or something. Or like
Speaker 1:For wearing them.
Speaker 2:I don't know if he actually got, like, punched, but he definitely got accosted at a bar in San Francisco for wearing them. He was an associate in Drusen Horowitz at the time, I believe.
Speaker 1:Would they be perpetually recording?
Speaker 2:No. So it was the same thing
Speaker 3:where you would turn them
Speaker 2:on and record. But they had this vibe to them in the, like, in the world where it was like, oh, this is like the surveillance state, like, every there's gonna be a camera everywhere. And this is before I mean, thirteen years ago, people were twelve years ago, people were not have their phones out taking photos constantly. And so all of a sudden, this idea that you could be in a bar and someone would be taking a video or photo of you automatically was pretty rattling to people. And so it was a pretty severe rejection at the time.
Speaker 1:It's a terrible feeling to be filmed by a stranger, just in general. I was at restaurant a week or so ago Yeah. On a date with my lovely wife. And this person was basically doc documenting like the entire outside of the restaurant. We were sitting at an outdoor table and, like, repeatedly, like, panning over us
Speaker 2:Interesting. While
Speaker 1:we're just sitting there.
Speaker 2:Yeah. It's suspicious.
Speaker 1:It yeah. It's just it it is a violation.
Speaker 2:Yeah.
Speaker 1:It I I'm all good if I'm in the back of the picture of the video that you're taking. But if you're like panning over and I become the subject of the video
Speaker 2:It is a little odd.
Speaker 1:We haven't and we don't Yeah.
Speaker 2:Because it could be that you're the rest of the video is just window dressing for an excuse to actually be filming you for some reason. You're like, why? Why do you wanna
Speaker 3:Yeah.
Speaker 2:What's going on here? Just ask. Yeah. At the same time, I've been on the other side. Like, we were at the airport, and I saw this guy absolutely crushing sales calls with a full on headset on instead of just Bluetooth.
Speaker 2:Most people wear the AirPods with a wired headphones. This guy had a full headset with the microphone down in front of his mouth.
Speaker 1:He was
Speaker 2:locked in. Barking orders, locked in.
Speaker 1:He was a LinkedIn general.
Speaker 2:This is a champion. I love this guy. I'm so into this dude. I should have just asked and gone up and said, like, can I do a professional photo shoot with you? Like, I I love I respect your culture.
Speaker 1:Your rig.
Speaker 2:Can I yeah? Can can I can I check out your rig and and enjoy that? But I I restrained myself and I didn't take a photo. I did I did go up to you and say, hey, you gotta check out this guy, this killer. We got maybe we gotta recruit this guy.
Speaker 2:It's pretty sick.
Speaker 1:No. We we we did take a lap and
Speaker 2:Yeah.
Speaker 1:And and kind of
Speaker 2:Yeah. Investigate the scene. Yeah. He had a he had a he had his fingers and a lot of pies. Much like Rune, we printed a post today.
Speaker 2:We got Rune. He says
Speaker 1:printed a post of our own quote.
Speaker 2:Yes. Rune Rune says, Rune has got his fingers in a
Speaker 4:lot of
Speaker 2:pies from the god whispers of TBPN by Jordi and John. And I I remember saying this, but I don't remember what pies I was referring to. I mean, he has a job.
Speaker 1:We don't even know what what it means. But it is it is certainly provocative.
Speaker 2:But I'm glad he enjoyed it and and and quoted it on the timeline. And, you know, now it's printed forever. Anyway, ramp.com. Save time and money. Time is money.
Speaker 2:Save both. Easy as corporate card bill pay.
Speaker 1:It was absolutely fantastic watching you at your absolute best.
Speaker 2:You guys
Speaker 1:doing a ramp ad right Zach was walking up. I'm watching Zach walk up the stairs. He's feet away from us and you're just ripping. Barking ramp. Just barking ramp.
Speaker 2:I love it. Like a carnival barker. Of course, yesterday, the stream was only made possible by Restream. One livestream, 30 plus destinations, multi stream, and reach your audience wherever they are. Thank you.
Speaker 1:We were actually everywhere. We were running Instagram.
Speaker 2:Yeah. We did our first Instagram.
Speaker 1:At TBP. Livestream.
Speaker 2:We're gonna do a lot more there and build out a full vertical layout. I I think it's gonna make a lot of distribution a lot easier.
Speaker 1:Yep. Get on
Speaker 2:reels, get on TikTok, all these different things. Glad that everyone showed up for return to form t b p n classic. Just just couple of good boys hanging out.
Speaker 1:TBPN at its best right here in the UltraGram.
Speaker 2:Technology brothers. Well, let's go through reactions to Meta Connect twenty twenty five. TJ Parker had a post. Meta execs are twenty years younger than Apple's and still willing to do live demos. Unfortunately, very bearish for Apple.
Speaker 2:It's a good take. There were a few Yeah. I mean,
Speaker 1:the the the wild thing, from from the interviews, obviously, you could find this out, from just doing a little bit of research. But if you were just watching and realizing how young the meta executive team is Yeah. And how long they've been working together.
Speaker 2:Yeah. Because they all were they like were like 22. And they started the company. And they joined like most of the people, the average tenure of person we interviewed was probably fifteen years, and they were all, like, in their forties Yeah. At most.
Speaker 2:But the the drama and the timeline was around the failed demo. I don't know if we wanna play the actual video. We were we were reacting to the keynote live, but we were talking, and we kind of picked up on one of the demo fails. I didn't realize the second demo fail happened. Yep.
Speaker 2:Very bold. But
Speaker 1:Yeah. By the way, we're gonna figure out how to do better keynote sort of like Reactions?
Speaker 2:Yeah. Yeah. It's kinda crazy.
Speaker 1:We were struggling with the audio.
Speaker 2:Like, we wanna give we wanna give you the facts. We wanna let you hear what's happening in the keynote because that's when the news actually breaks. Like, they like, they don't want anyone talking about the fact that the new red meta Ray Ban display is $7.99.
Speaker 1:We kept almost leaving.
Speaker 2:Until Mark says that on stage, so you gotta wait until he says it. So you might as well just watch along. So, anyway, bit of a bit bit of something to Yeah.
Speaker 1:I practice
Speaker 2:in the future.
Speaker 1:It was it was obvious. I mean, we were Yeah. Surprised, especially rewatching the keynote afterwards Yep. Seeing the moments where where the demos failed. We were surprised because we got those demos Yes.
Speaker 1:Multiple times Yes. And they worked. Yep. And so we were kind of trying to we were trying to figure out why that might have been. I think our our theory for why Zach's demo wasn't working on stage is that the glasses were simultaneously live streaming Yeah.
Speaker 1:And trying to carry out the regular functionality.
Speaker 2:The video call.
Speaker 1:So we were we had done the video calling functionality with WhatsApp Yep. Multiple times.
Speaker 2:Didn't have a problem at all.
Speaker 1:Had no problems at all. And so and and the first demo that we did was months ago. Yeah. Right? So surprised that that that happened.
Speaker 1:But also just the the, like, real time live streaming from first person Yep. Is, very cool functionality.
Speaker 2:Yeah. Although, that's not something that they're launching.
Speaker 5:Yeah.
Speaker 2:So it's very odd that But they they successfully live demoed a product that doesn't exist or or a feature that's not live yet, which is live streaming from the glasses.
Speaker 1:And you could tell the OS was, like, thought that the video was already pulled up? Yeah. Yeah. It streaming or
Speaker 2:something like that. I I think that one of the stories is, like, they clearly went super hard on weight reduction. The the display glasses, the the Orion demo that launched last year, which actually also had failed a a botched demo as well. It was it was it was chunky, but still very thin and light. And when you try it on, it feels great.
Speaker 2:Yeah. But this is, like, remarkably lighter, like 69 grams. CarMax I thought CarMax quote was a 100 grams for a headset and a $100. Turns out he was saying 250 grams and $250, which is I mean, 69 grams is way less than $2.50. So you you really can wear these all day without any serious strain.
Speaker 2:They're, like, just slightly chunkier than just normal Ray Bans. And so let yeah. Let's pull up the actual demo and and and see exactly what happened here.
Speaker 1:WhatsApp video call.
Speaker 6:There we go.
Speaker 2:So he's trying to kick off a WhatsApp video call is to Boz.
Speaker 6:Yep. Well, I well, that's what happened.
Speaker 2:This is so bold. And you can't see it because we have
Speaker 6:our ticker But don't know what happened. At
Speaker 2:this point he's done this so many times. Maybe Buzz can try calling me again. Whatever. They're having fun.
Speaker 6:Alright. Well, I got
Speaker 2:a missed video call. Okay. There's the the actual video call.
Speaker 3:And in
Speaker 2:the top corner, when he does the live demos, they put this like massive bubble. This is like, this is a live demo. This is live. We're not faking this.
Speaker 6:You know, it happens.
Speaker 2:Or at least you know you didn't fake it. So anyway Is
Speaker 1:four d chess the demo? Yeah. Let's see. Do think? We'll be prerecorded.
Speaker 1:Oh, yeah. They wanna train. They wanna no.
Speaker 2:I'm kidding. No. No. The real four d chess is that this sets expectations low. It makes you go into it thinking, I'm getting a dev kit like experience, and and then they can over deliver.
Speaker 2:So if you put on a if you put on a pair of these, you're like, okay. Yeah. Like, I'll probably be able listen to some music, but the WhatsApp video call functionality is probably not gonna work. You try it. It works, and you're delighted.
Speaker 1:So so it's a hard product to, like, demonstrate. Right? Yep. Really is something that you have to experience. Yeah.
Speaker 1:Because, like, even when we were talking to Boz, Boz had the display up the whole time.
Speaker 2:That's crazy. Yeah.
Speaker 1:So he got a message from Zach, like, right as he was walking up.
Speaker 2:Really can't see
Speaker 1:the You cannot see the display at all from the outside.
Speaker 2:Yeah. Well, there were some there were some good reactions in the timeline to Yeah. Mark. The the failed demos. But first, let me let us tell you about our newest sponsors, Privy, Wallet Infrastructure for every bank.
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Speaker 2:They're in GA. So let's go to Mark Garmin. Remember face ID? Failed demo, but essentially flawless for users. I wish Apple would go back to live, but I don't think it'll ever happen.
Speaker 2:Much more reach now, and they and they definitely see taking risks for this type of thing is pointless. I don't think they're wrong. But on the flip side
Speaker 1:Then you have the Sharuya. Cybertruck demo.
Speaker 2:Oh, yeah. The Elon Cybertruck demo. That was a crazy one. And you haven't heard about I mean, there's been a lot of, you know, varying responses to the Cybertruck, but no one's complaining about their winds their their their Windshields or their
Speaker 1:Fortunately, you don't have to use you don't have to test your windshields as much as you have to test if your device can handle video calling.
Speaker 2:Yeah. But It's true.
Speaker 1:But yeah. Certainly.
Speaker 2:So, yeah, on the on the flip side, Sharuya says, it takes a lot of courage for someone in Zuck's position to go live and make a fool out of himself. Everybody gangsta in their comfortable controlled environments. It's true. And and you can see here the red pill for live demo in red there, letting you know this is not fake. And there's been a lot of demos that have been sort of faked.
Speaker 2:I mean, we we're coming off the the Apple intelligence where there were a lot of demos that that shipped on varying timelines. There were ads that went out and features were promised. And Mark Gurman wrote that big article, There's Something Rotten Cupertino, really put his whole reputation on the line to to kind of Every
Speaker 1:Apple every Apple focused journalist basically put their
Speaker 2:Yeah. To say anything. It was rough. It was bold. And and and then Google had something similar where they demoed an AI, real time video model that would interpret what you were seeing and then run through Gemini.
Speaker 2:But they but they sped up the the wait time for the LLM, which some people were like, oh, that's not fair. Although, you know, with that, it's like they're gonna speed it up over time. But there's always been there's always been, like, you know, criticism of the various trade offs of keynotes. And I feel like, I mean, this is not as bad as it could have been. It's pretty good.
Speaker 2:And overall, it just felt like being there on the day, it felt like we weren't watching a movie or, like, an ad or a video. We were, like, part of a play because, like, you could Mark Mark Zuckerberg and Diplo go running by you, and then there's, like, the skateboarders, and there's, like, this this, like, demo with the crowd happened in one place, and they move they're moving around in, like while we were on stage, we could see Mark going from one thing to the next, like, actually
Speaker 1:Yeah.
Speaker 2:Very much participating in,
Speaker 5:like Yeah. And I
Speaker 2:the keynote or the, you know, the event, but in a very, like, moving around physically.
Speaker 1:Yeah. It's just tough. It's it's failing failing on stage is tough because no matter what we say, right Yeah. I when I was using when I was demoing the display glasses, I could say, hey, Meta, find me restaurants. What are what are some restaurants that are nearby?
Speaker 1:And on the heads up display, it would pop up some options. I'd be able to select one with the neural band like super super easily.
Speaker 2:Yep.
Speaker 1:And and it would just pull up a map, and then it would give me perfect navigation. I could just walk. It would Yeah. Guide me to it. Right?
Speaker 1:And so having this experience, like, what what they're selling is there's a lot of moments that you need to pull out your phone. Yep. And what if you didn't what if you didn't have to sort of like take yourself out of the moment Yep. And, you know, go go like this. I think it's very telling that The Verge wrote this this morning.
Speaker 1:They said, I regret to inform you Meta's new smart glasses are the best I've ever tried.
Speaker 2:The new Really know your audience. Total old audience capture. Just like
Speaker 1:I'm sorry, guys. Tried a product.
Speaker 2:So tech optimist and such a tech native blog. And Miele Patel, I believe, is, like, still running it. I think he started it. And so, like, I I don't think of The Verge as, like, having this adversary relationship with tech, and yet, like, they had to frame him this way. It's very funny.
Speaker 2:Dylan Field, founder of Figma, had a more positive take. He said, congrats to Meta to the Meta team on today's launches. I saw some of the tech. While it was still in it's still in development, the glasses, AR interface, neural band and overall capabilities are extraordinary. And, yes, live demos can fail.
Speaker 2:We've all been there. The tech is still awesome. Onwards. Dylan is, of course, the CEO of Figma. We're partnered with Figma.
Speaker 2:Think bigger. Build faster. Figma helps design and development teams build great products together. You can get started for free. Ben Thompson also had a positive take.
Speaker 2:He says, live demo fails are good tech karma because if you You get rewarded. You get rewarded Taking the risk. For setting for setting the bar low. I there is a there is a world It's also something to be.
Speaker 1:Yeah. It's it's you also have to understand, like, how confident you have to be in a product to go do a live demo.
Speaker 2:For sure.
Speaker 1:Like, Zoc Zoc didn't go out there being, oh, there's a there's a coin flip, like, 50% chance
Speaker 2:It's shipping in two weeks. It's it's crazy.
Speaker 1:Yeah. And it's just I I can't I can't say it enough. It's so painful that, like, we use this functionality months ago Yeah. At this point. And so That's
Speaker 2:way it goes. But Well, I I was trying to break down, like, we we we talked to a lot of the meta team.
Speaker 1:Wait. Did you did you see the screenshot too of of inside the they're doing the Gaussian splatting
Speaker 2:Yeah.
Speaker 1:Yeah. With Oh, yeah. You can see the Lucy logo.
Speaker 2:This was super cool. Octagon. Three d Gaussian splatting is cool. And now you can capture real worlds real world spaces just by walking around in your Meta Quest headset. We did this demo as well.
Speaker 2:You walk around in the headset. It scans everything. They actually make it into this, like, kind of fun game. It takes about six minutes. So you can recreate your room, recreate anything.
Speaker 2:Tyler made a version of this just using his phone camera. It looked really good. It actually runs in a browser. And but you can imagine this being really fun. But this was such a funny Easter egg that they put my nicotine pouch brand, nicotine gum brand in the Octagon.
Speaker 2:And I don't think this was intentional. I think this is literally just they went and scanned one of the Octagons and, like, our logo's there, which is cool. But but fun to see, and it made me do a double take in the moment. The real time feedback ensures you don't miss a spot. Apple needs to get on this ASAP.
Speaker 2:I agree. I at the same time, like, I was standing in the in the octagon, and it was like it was cool to feel like, okay. If I was here, how high would it be? It gave me a sense of scale, but there there wasn't really, like, a game mechanic to it or anything.
Speaker 1:Yeah. To me, to me, this what I brought up that I I just care about what what kind of why would I why would I want to do this other than pure novelty. Yep. The best example I could think of is is a real estate agent. They go, they scan a property Sure.
Speaker 1:That they're that they're marketing for
Speaker 2:Yep.
Speaker 1:For lease or sale. Yep. And then people can just drop in and experience the home Yeah. Like, actually from
Speaker 2:I see it I see it probably more as, a pipeline to traditional three d games and, like, traditional three d geometry. Years ago, decades ago now, there was this game called True Crime, The Streets of LA, I think it was called. And it was like Grand Theft Auto, nowhere near the level of game mechanics, nowhere near as, like, fun of a game, but they did a full scan of Los Angeles. And so you could go and find, like, the TBPN UltraDome because it was a street by street rep like, replica of of LA. Yeah.
Speaker 2:And I imagine that that if you're able to do Gaussian splatting, you could bring that through to a generative three d geometry pipeline and then create a game out of it. Seeing how these two technologies kinda merge, I think, will be will be pretty important. I I had a lot of fun with it. And and it was, yeah, it was it was it was cool, but, yeah, it's definitely in, like, the novelty demo. I think overall, I tried to synthesize, like, the takes that I was pulling out of the meta team, and I had three one is just that wearables are underhyped because of how much focus there is on AI.
Speaker 2:And so they I feel like they're all the entire Meta team is, like, very happy to swim in that lane where they're, like, doing something cool that's not, like, oh, it's it's gotta be fast takeoff, gotta be god in a box. Like, the expectations are so high. AGI, ASI, it's like it's like, do they look nice? Are they affordable? Do they the the cameras work?
Speaker 2:Like, it's pretty it's pretty low stakes.
Speaker 1:Yesterday, the the display, heads up display is getting more hyped than live AI. Totally. And and even though every gen AI product today is not
Speaker 2:Yep.
Speaker 1:100% reliable and and can have issues, the fact that you're just gonna be able to walk around with this perpetual intelligence humming along, getting to experience everything that you're experiencing Yep. Building that context in your life is underrated and it says a lot that even in the current state, they can run that. You get like an hour of battery life for like the truly live AI, where it's processing everything in real time doing the translation functionality.
Speaker 2:I didn't realize there was a full hour. But The other the other takeaway, we were digging into personal super intelligence, trying to understand what that mean means. This wasn't really a full AI event. This isn't LamaCon, but it feels like personal super intelligence will definitely be a personal shopper. You will be able to take a picture of something, say, order that.
Speaker 2:It'll go straight to the brand, maybe a Shopify integration, something like that, check out for you, ship it to you. Or if you just see something on Instagram, you're gonna be able to fire that off. Like, we've seen the agent to commerce, like, outlined in semi analysis. We've also seen just yesterday or the day before, Sam Altman sort of shared a screenshot wherein the dashboard for your ChatGPT app, one of the tabs was orders. And so they're clearly thinking about helping you order things.
Speaker 2:Yeah. That's a huge way to take a cut of commerce on the Internet, extremely valuable, extremely monetizable. So it would be truly shocking if Meta was like, oh, yeah. All of our customers, every brand that advertises, yeah, we don't want to continue the relationship in the AI age. Like, obviously, they're gonna do that.
Speaker 2:Yeah. So they didn't share too much there, but it's but nothing nothing, you know, nothing was shared that felt like that was not on the immediate road map. It felt like it was. Yeah. And then the last the last thing that that I was taking away was that basically, like, Lindy pieces of cinema will be the first real killer app for VR.
Speaker 2:I think your prediction a year ago will wind up being correct. Multiple glasses, you will have something for action sports that plays in the in the Go Pro Yeah. Realm the the surfing, the the the the ski goggles, that type of stuff will be action sports. Then there'll be the heads up display that you're maybe using when you're, you know, walking around, driving, doing whatever, answering messages, listening to music. And then if it's time to sit down, watch a movie, there will be an alternative to the to the TV on the wall at a similar price point.
Speaker 2:Right now, you can get 65 inch TV probably for like $500. I think you'll be in that same territory pretty soon. We talked to James Cameron about this. The, like, the level of fidelity watching his films, Avatar, in three d is just better in VR. He was talking about the Quest three.
Speaker 2:I think he's seen a demo of the Quest four. I think the Quest four is gonna have a screen that is at the level or beyond the level of the Apple Vision Pro, which was phenomenal. But they're gonna bring all of their engineering prowess to they're gonna take the battery out. They're gonna make it plastic. It's not gonna a screen on the outside.
Speaker 2:It's not gonna have all this extra stuff. Maybe they'll do a neural band. So because if they do the neural band the big thing with the neural band is that it takes it's distributing the compute across your body. You don't want all the compute right on your bridge of your nose. That is terrible.
Speaker 2:That's painful. So take the battery, put it in the back. You know those are they called croakies? The things like this. Is that right?
Speaker 5:Yeah.
Speaker 2:Yeah. So, like, I could imagine croakies going over your Metairay bands or your or your Oculus where the battery is actually kinda hanging, dangling it from the back of your head, And you're getting extra battery life out of that. And maybe that runs down your back. You throw it in a pocket like what you do with the Apple Vision Pro. I think that was a good paradigm.
Speaker 2:I think the Apple Vision Pro uses hand tracking as input. But that means it has to have cameras that
Speaker 1:smart look that the charging case for the display, like, folds up flat. So it can act as a as a regular case Yeah. That was cool. If you have it at the right angle Yeah. Like those kind of iPad
Speaker 2:Yeah.
Speaker 1:IPad screen protectors. Yeah. Yeah. Neural band is also underhyped from yesterday. Everybody wants to focus again on like
Speaker 2:Yeah.
Speaker 1:The actual glasses and the display. But Yeah. I said it before and I hope people, you know, you go to a a retail store and and demo these, try them out. But like trying the neural band, realizing how quickly you adapt to this interface, it's like this pretty much the same motions you're used to on an iPhone. You just don't have a phone and it takes a little bit of getting used to.
Speaker 2:Their pitch for it was was, well, because it's not using a camera, you can you can use it out of view of what the camera would be if it was on your face. You can use it behind your back. I don't actually care about that. I I think it's fine to put my hand in front when I'm adjusting the volume. I don't really see a value of putting it behind my back.
Speaker 2:I think the value is that all that like, you need you need some input sensor to capture what's going on with your hand, and it makes sense to just put that right next to the hand. And I think that if even if it's just a couple grams, taking that off the face and putting it on the wrist is way better, way more natural. I do think it was interesting that Boz was saying that long term, the neural band could be an input device for other applications, and eventually, they could open that up to developers. So you could have an app that uses the neural band as an input, or it could be a little bit more platform agnostic at some point. Very unclear where that actually goes.
Speaker 2:We were debating a little bit. We didn't get our firm percentages down. But between voice input, just speech to text versus handwriting, I think most people will be doing speech to text. But I don't know if that's just because I've been so I dictate, like, a ton these days. I open up the ChatGPT app.
Speaker 2:I click on the audio mode, and I just talk and talk and talk. And then even if I'm not a lot of times, my prompt is just, like, clean this up and make sure it's grammatically correct. Like, don't change it. Don't rewrite it. Just reproduce it.
Speaker 2:And then I can just copy that into wherever I need to go if it's a longer thing. I think that long term people will just be comfortable talking and and we you're able to talk in a very low whisper and it picks it up just fine. Yeah. The the the secret handwriting, I don't know how I don't know how popular that that that's gonna be. Maybe like 20% of total input.
Speaker 1:I think it's gonna be popular for short responses. We just need to be like like, hey. Do you want me to grab you a sandwich?
Speaker 2:Yeah. Well, there's also just Want
Speaker 1:me to grab you a coffee? Yes.
Speaker 2:Yeah. Well, there's also, like, the thumbs up. It it it dynamically selects emojis there. You So can just swipe and be like heart or thumbs up or thumbs down. Yeah.
Speaker 2:So I it is, like, in between just, like, send an emoji response, dictate something longer, handwriting's for something in the middle. I don't know how popular it's gonna be. It's definitely like a lift. People are gonna have to learn. It's like an entirely new input medium.
Speaker 2:But then again, speech to text is somewhat of a new input medium, and people have figured that out. So maybe maybe over the few years, people people bring that back. But I I'm not sure I'm not sure if I would be leaning on that all the time. Maybe I'm just a terrible terrible handwriting, so I don't know. Anyway, it was a fun fun event, and thank you all for watching.
Speaker 2:Let me tell you about Vanta, automate compliance, manage risk, prove trust, continuously advances trust management platform, takes the manual work out of your security compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. Tower of Babel?
Speaker 1:Yeah. Let's start there.
Speaker 2:So we were talking to Chris Cox, the chief product officer at Meta. And he said that AI translation is Tower of Babel level. And it was a very funny he used a very funny word, a judgment. He was like, with AI, you can take a judgment and and it was in this clip. It was in this clip.
Speaker 2:Oh, really? AI can be used to scale a judgment. And I and I forgot what word he used, and I asked him, and he didn't remember, and we kind of just moved on in the conversation. But I was but Skooks is saying me when I don't know what the story of the Tower of Babel was about. The Tower of Babel story, of course, is is humanity in in the the book of Genesis used to all speak one language, and then God fragmented the languages.
Speaker 2:But And so I
Speaker 1:think he was he was generally alluding to going back to
Speaker 2:Yeah. Like like, is it hubris for humanity to try and speak all the same language? The the the there's always these Meta loves these nicknames for projects that have Or or if they go either way.
Speaker 1:A a a massive project that collapses under its own weight.
Speaker 2:Yes. Yes.
Speaker 1:The other way to interpret that is, like, okay. Yeah. It's a glass, you
Speaker 2:know Yeah. It it every every code word is a Double edged sword. Is a double edged sword. I mean, every every, you know, Greek myth is a double edged sword. Like, just the Orion headset, their full augmented reality headset.
Speaker 2:Orion is the story of the hunter who has, gets so cocky, so much hubris. He decides he can kill all the animals, and he's, struck down by God and and then sent to, sent to the the the the heavens to exist as a constellation. The the the the the new data center is called Prometheus, which, of course, is stealing fire from the gods. And and there's another Hyperion. In in one of those, the the the perpetrator of the hubris is sentenced to have his kidney or liver eaten by an eagle every day forever.
Speaker 2:There there's a lot of, like, bad endings in these stories, but they all all also are, like, very powerful and cool names. Tyler, what's your favorite metacode word?
Speaker 7:There's a lot. I think there's some Stroussian reading where maybe Zuck is actually a doomer
Speaker 2:Oh, yeah. Secretly. He thinks that Prometheus, he will steal fire from them gods and be smited, Perhaps. I mean, the behemoth thing was crazy because it's it's like behemoth llama. And do you remember the AI generated image that they used to promote it?
Speaker 2:It was like this very like demonic, like like beefy, bulky It was crazy.
Speaker 1:Guys, how did this one get
Speaker 2:And then and then it didn't get out. And then it was actually, like, a it was it was too big to tame. And, like, that is the story of the movie.
Speaker 1:It's simply the image.
Speaker 2:Yeah. The image was crazy too.
Speaker 1:Use this.
Speaker 2:And so, yeah, maybe just stick with, like, the version four, version five. I don't know. But then we get into numerology. Who knows?
Speaker 1:I gotta try to find this. I I I have this I'm I'm putting this image in the chat, guys.
Speaker 2:Do you think that they're subsidizing the cost of this thing? So Joanna Stern said, wow. $7.99 for Meta's new screen equipped Ray Bans and the Neural wristband. I thought that was shocking when they told us on Friday. Ben Thompson was shocked by this as well.
Speaker 2:Everyone's been reacting to just how cheap that is. The Orion headset, when they demoed it last year, the rumor was going around was that it cost $10,000 to produce those. And so people were like, okay. Yeah. So they'll get they'll get twice as, twice as cheap every year for five years or something, and then we'll be in the $7.50 territory.
Speaker 2:But this has a lot of the same deck, and it's $7.99. It's half the price of the of the original Google Glass, which is crazy. Do you think they're subsidizing it?
Speaker 7:It definitely seems like really cheap. I was surprised that it was under a thousand dollars. I don't know enough about the actual technology to tell, like, what the price would be, but it does seem like really cheap.
Speaker 2:There's
Speaker 1:many reasons to make it as cheap as possible. Totally. Right? Just like one, user feedback. Two, it can, help them improve.
Speaker 2:Oh, yeah. There's the llama for behemoth preview.
Speaker 1:Yeah. This is a picture.
Speaker 2:Hey. It's a big llama.
Speaker 1:I'm glad they transitioned.
Speaker 2:I I think it's kind of funny, but it is crazy. It's fun. It's kind of funny. A jack llama. I that's something I would do.
Speaker 1:You think somebody's sleep paralysis monster
Speaker 2:is fun? It was kinda crazy. If they It looks cool. It looks it definitely looks metal. And it had great vibes when you chatted with it.
Speaker 2:It was goofy and laughing about the fact that
Speaker 1:it was Extremely metal.
Speaker 2:But, yeah, it is very it's heavy metal. It's hardcore. Anyway, much like graphite, graphite dot dev, code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster and get started for free. So on the subsidization thing, I mean, they're, like, they're they're saying, like, MetaRadian is the best selling product, but they're at the $300 mark, $400 mark.
Speaker 2:And I don't think they're selling tens of millions of those. They're I think they're selling, like, millions. So if you sell a million and you're subsidizing by $200 a pop, it's like, okay. That's $200,000,000. Like, that's fine.
Speaker 2:Like, Meta has no problem with that. In fact, they can
Speaker 7:That's only two AI researchers.
Speaker 2:Exactly. Exactly. So what they can do is they can say, even if they're even if they're like, let's subsidize this by a thousand dollars, and let's sell a million pairs. It's like, okay. They're gonna lose a billion.
Speaker 2:They probably can't sell 10,000,000 or or 50,000,000 pairs, but they could just do a run of a million pairs at a huge loss and then just cap it and be like, yeah. We're out of stock. V two's coming. V two comes. And then they raise the price, and they say, it's even better and even lighter and even thinner.
Speaker 2:And then they slowly creep together.
Speaker 1:They never need to make money on hardware.
Speaker 2:No. I don't think so.
Speaker 1:Like, they never need to make money here. Sure they will if they keep executing like this. But ultimately, it's just about it's about owning owning the next platform. Signal screenshotted the stream and said Meta is so rich. They have a VP for just fashion partnerships.
Speaker 1:And Michael Miraflor, I don't know if he's in the What chat right
Speaker 7:is the truth?
Speaker 1:Ava Chen has been at Medisince twenty fifteen and is the primary reason why Instagram is Instagram.
Speaker 2:Let's go.
Speaker 1:This should be common knowledge. You do not know ball if you do not know this, especially if you've ever tweeted about tech and taste. I thought I mean, I thought I thought the the post was funny. Signal's post was fine. Obviously, he's a friend of the show, but I thought it was funny purely because Instagram is the most influential platform in the world Yeah.
Speaker 1:For fashion. They generate billions of dollars a year from fashion brands Yeah. Advertising on the platform. Yeah. Like, of course, they should have somebody Of your
Speaker 2:like And you don't have to be any of the most popular VP. We have a VP of logistics, a VP of production, a v we have a chief intern officer.
Speaker 1:We do. CIO.
Speaker 2:And so, you know, you could titles are free. I don't know if you need to worry about that.
Speaker 1:Yeah. I would be I would be bearish if they didn't have somebody that was just focused on building because it's it's on both sides too. It's not just companies. Yeah. It's it's the creators.
Speaker 1:Yeah. Right? Yeah. Talking about the most the biggest creators in the world, many of them are are advertising
Speaker 2:Also, I mean, think about the fashion partnership they've done. It's like a multibillion dollar deal with Luxottica. They've taken a position, a major equity position in the it's it's a serious business to get Rocco on. We can make use a billionaire.
Speaker 1:We're gonna make face computers. Yeah. But they have to look good. Otherwise, people won't wear them. Yeah.
Speaker 1:Should we have somebody that understands the world?
Speaker 2:Sure. Yeah. Also also just in in terms of, like, the VP title, like, you do you want, like, a fashion partner analyst showing up to do a multibillion dollar deal with, like, the number one sunglasses brand in the world? Like, no. You wanna send a VP.
Speaker 2:You wanna send someone with a real title. Anyway, very silly. But but fun. Everyone's having fun on the timeline. We'd love to see it.
Speaker 1:We're promoting Michael Miraflor to vice president of taste.
Speaker 2:Yes. Vice president of taste. Mark Gurman gave his take. He says he has a strong feeling these will be popular. I wonder if this will cause Apple to speed up its timeline.
Speaker 2:Right now, I'm not anticipating Apple Glasses with displays for a few more years. Their first nondisplay model is likely being announced late twenty six, early twenty seven. That is slow. That's a lot of time for Meta to to iterate on this and actually get through. It it it's gonna be a big it's gonna be a big fight.
Speaker 2:Google's talking about doing display glasses.
Speaker 1:Wait. So Gurman is saying they'll do a pair of glasses that just have a camera in them?
Speaker 2:Yes. Yes. A competitor to Meta Ray Bans. Yeah. I know.
Speaker 2:What do you get? Not that much. Bet you you do get slightly tighter integration with Bluetooth. So you will you'll probably be able to pair them and unpair them a little bit more easily because AirPods are a little bit easier to pair reliably than the Meta Ray Bans. But in but as a competitor, Meta Ray Bans, it's camera, headphones, access to AI.
Speaker 2:Okay. So you get the Apple Ray Bans, which won't be Ray Bans. They will look like Apple products. And they will have maybe a better camera, because Apple's fantastic at cameras. Maybe better Bluetooth connectivity and reliability there.
Speaker 2:But you don't get any other Very, very then instead of talking to Meta AI, which is probably gonna ship something really sick out of MSL soon, like you're dealing with Siri and Apple Intelligence, which we don't know the timeline for the v two of that. They're kinda moving slow on an Anthropic partnership or something like that. But even though they have the ChatGPT integration, like, I have not become comfortable using the Siri button to reliably query ChatGPT. I still open my phone, open that app every time.
Speaker 1:Yeah.
Speaker 2:And so there was also a rumor that they might partner with Gemini, which actually would be great because that model is fantastic. And so it'll be interesting to see where they where they pencil out on that. But Meta seems to I I would be surprised if if Apple can just come from behind and dominate Yeah.
Speaker 1:You have to look at Meta's advantages, which is like we own the platforms that you share content on too. Yeah. Right?
Speaker 2:Yeah. Well, julius dot a I, what analysis do you wanna run? Chat with your data and get expert level insights. Julius. We love Julius.
Speaker 2:The AI data analyst that works for you. You can join millions who use Julius to connect their data, ask questions.
Speaker 1:We should have had a cool show up at Metaconnect and then just like hop on the stream Yeah.
Speaker 2:That'd great.
Speaker 1:In the background. Surprise.
Speaker 2:What else? Aaron Slodov He's coming on the saying,
Speaker 1:start collecting training data right now. Put these on every manufacturing worker in America. Good. Yeah. Probably probably smart may as well.
Speaker 1:You could just do that. You don't need the display either. But again, Amazon is already saying that we're putting the they're developing their own pair of glasses to put on their workforce.
Speaker 2:Hopefully, it's not a death knell. When Google Glass pivoted to B2B, it was sort of like going out to pasture because they they were doing Google Glass for consumer. They thought it was gonna be this massive, like, consumer adoption moment. There was a ton of hype. Didn't go anywhere.
Speaker 2:And then pretty soon, it was like Google Glass for enterprise. We'll use it in manufacturing context. That's not what Aaron's saying. But but I would be personally worried if if Meta started talking about, oh, yeah. These are gonna be really great enterprise use cases.
Speaker 2:They're not ready for consumers. Like, no. They need to be ready for the the the Instagram crap. Like, it has to it has to integrate with meta platforms in order for it to be successful, in my opinion. Yeah.
Speaker 2:Let me tell you about Fall, the generative media platform for developers, the world's best generative image, video, and audio models all in one place, develop and fine tune models with serverless GPUs and on demand clusters.
Speaker 1:We should do a soundboard partnership with Fall. Mhmm.
Speaker 2:Oh, yeah. Anyone can Great.
Speaker 1:Can generate TBPN like sound Well,
Speaker 2:we talked about Scott Wu earlier. He's in the timeline showing some love to Mark Chen over at OpenAI. Mark, he said, So insane. You have you guys have no idea how hard this is. Mark Chen said, We wrapped up this year's competition circuit with a full score on ICPC after achieving sixth in the IOI, a gold medal at the IMO, and second at the at coder heuristic context.
Speaker 1:I never I never see you at the heuristic contest,
Speaker 2:John. Contest.
Speaker 1:I was at the heuristic contest, and I didn't know your name.
Speaker 2:No. Yeah. We yeah. We gotta send Tyler to to be our on the ground correspondent at the IMO and the I o I o I next year. I think that'd be great.
Speaker 2:Do some post game interviews for the for the contestants and then get them directly routed into the tier one VC firms. They're already getting calls from from from investors.
Speaker 1:This was probably the biggest news of yesterday, but it went under the radar. It did. There is a Rolex Oyster that that's Domino's Pizza branded.
Speaker 2:And Andrew Reese says he's not a watch guy, but he might get this one. It's a 1970, vintage Rolex Oyster Precision Classic men's Domino's Pizza watch, and we have the story behind it. The Domino's Rolex Air King in 1997. They've done
Speaker 1:a few Well, this is
Speaker 2:years another one. Apparently. So Domino's Pizza founder Tom Monaghan began incentivizing franchisees with Rolex watches when a high earning franchise owner earned the watch off his wrist by hitting a $20,000 sales week. Let's go. Monaghan wrote in his 1986 biography Pizza Tiger.
Speaker 2:What a great name for a biography. Send it straight over to David Senora. I wore a Belova with our Domino low Domino's logo on its face. A franchisee asked what he had to do to get that watch from me. I told him, turn in a $20,000 sales week.
Speaker 2:He did it. And so he won the watch off of his wrist. After that I wonder what
Speaker 1:the what do you think the market value of that watch was at the time? Because he might have might have been an arbitrage Yeah. Just realizing, hey. Well, we're
Speaker 2:about to find out. After that, Monaghan started rewarding top performers with Seiko watches and later upped the stakes by giving away
Speaker 1:Okay.
Speaker 2:Hundreds of $800 Rolexes. So in the eighties, we're talking a couple $100 for these, but that's still a lot of money back then. Initially turning in a $20,000 sales in a week at Domino's would earn a Rolex. However, as Rolex prices increased, so did the challenge. Domino's, Colt, Domino's continue
Speaker 1:every time. So, theoretically, you
Speaker 2:could get 52
Speaker 1:Lexus a year.
Speaker 2:I don't know. Yeah. I I imagine if you just, like, pick the right locations, set the right prices, have good traffic, like, you should be able to put up, you know, fantastic numbers.
Speaker 1:It's very motivating.
Speaker 2:The Domino's in, Times Square has gotta do tons and tons of revenue. Right? Domino's continued to give out branded Rolexes, but a franchisee eventually needed to achieve $25,000 in sales per week for four consecutive weeks to win the watch, but the Air King. And these apparently, is one available on Bezel. Go to getbezel.com.
Speaker 2:Your Bezel Concierge is available now to source you any watch on the planet. You can ask them for a Domino's Pizza.
Speaker 1:Meta Meta exec team had some tasteful
Speaker 2:Absolute hitters.
Speaker 8:I clocked.
Speaker 2:Boz had a great watch on. Adamissari. Adamissari had a Nautilus.
Speaker 1:Vintage aqua.
Speaker 2:Aquanaut. The Aquanaut.
Speaker 1:Gold on one on a black Yeah.
Speaker 2:Strap. It was great.
Speaker 7:What do I
Speaker 8:have to
Speaker 7:do to win a a TPPN Air King?
Speaker 2:Oh. I don't know. We'll have to figure that out. Chat, let us know if you have any ideas for for Tyler.
Speaker 1:We were we were actually debating whether or not we should do q four bonuses in watches. And John's, just for the record, John's point of view is that you guys would probably just want cash, but
Speaker 2:It might be delivering watches before out.
Speaker 1:We'll see. In other The clapping. Guys
Speaker 2:See? Like that. Rolexes. Okay. Maybe Jordy's on something.
Speaker 2:I think
Speaker 1:I might be on to something.
Speaker 2:Well, we have our next guest joining in just a few minutes. But first, like, there there's big breaking news yesterday. Disney's ABC is pulling Jimmy Kimmel indefinitely after late night after the late night host's recent remarks about Charlie Kirk. The move comes as ABC affiliate groups told Network, they would be dropping the host. So, this didn't come from top down from Disney.
Speaker 2:It came from the, from some of the affiliates. Nexstar Media is one of the largest the nation's largest TV owners, said it
Speaker 1:would stop their program. AI having a complex corporate structure, but media
Speaker 9:I had
Speaker 1:no idea. Media company.
Speaker 2:Right? Sinclair is also involved. So Sinclair put out a statement. Mike Solana says, so this didn't have anything to do with the FCC. There was a lot of debate over what the FCC's role was in this, who was really putting pressure on there.
Speaker 2:There was a viral video, a clip of of of Kimmel's monologue that went viral on Tuesday after he delivered it Monday night. There was a lot of backlash to that, and then this came up. Jason Kallikanis, the host of the All In podcast said executives at ABC, like those at CBS, wanted to fire these money losing late night franchises for years. Trump has even given them cover. Trump has given them the cover they needed when it was wildly profitable to back these same comedians a decade ago.
Speaker 2:The networks had no problem letting them mock our wonderful, amazing, tremendous, beautiful, brilliant, and astute president Trump, wink, every single night. And so I we we got a little bit of detail on Colbert's financial situation. I have no idea what the financial situation was like at Kimmel.
Speaker 1:Viewership ratings were dropping, though.
Speaker 2:We did hear that,
Speaker 1:like Hill. I think it probably tracks the basically, the the the I mean, the the audience on on these networks is, like, retirement age. Right? And so these audiences
Speaker 2:67 was the median age at CNN, and that was, the the lowest or something. Yeah. Crazy. It does feel like it gets harder to harder harder and harder to monetize an older audience just because they're not as they're not as profligate with their money. They're not just going and spending money on all sorts of things.
Speaker 2:They're not building AI companies. They're not using Turbo Puffer. They're not even in the they're not even in the ICP for Turbo Puffer. They're not using serverless sector and full text search built from first principles in object storage. Fast, 10 x cheaper.
Speaker 1:Loves by
Speaker 2:choice. Sure. No. Scalable.
Speaker 1:Linear. And our friends over at Readwise too. Some very important breaking news. Chinese Joe Weisenthal has hit the timeline. Woah.
Speaker 1:Chinese Joe says
Speaker 2:Familiar with American Joe Weisenthal.
Speaker 1:When we first started raising awareness about Chinese Joe Weisenthal just a few months ago, the legacy media and the corporate establishment laughed in our faces. Something tells me they aren't laughing any longer. Chinese Joe So I
Speaker 2:And Geiger Capital says very bullish China.
Speaker 1:It is. It is.
Speaker 2:They're catching up to The US
Speaker 1:much faster than
Speaker 2:anyone anticipated.
Speaker 1:Every country should have a Joe Weisenthal. They would be lucky to have one.
Speaker 2:Yes. And every every country needs a profound. Get your brand mentioned in Chateappetit. Reach millions of consumers who are using our AI to discover new products and brands. And we have our first guest of the show from Palantir coming into the studio.
Speaker 2:Welcome to the stream. How are doing, Lewis? Good to see you.
Speaker 10:Very good to see you guys. Thank you for having me on.
Speaker 2:Thanks so much. Would you mind kicking us off with an introduction on yourself, little bit of your backstory, history of Palantir, and we'll go into the news?
Speaker 10:Yeah. Sure. So I'm Louis. I run Palantir out here in The UK and Europe. You can tell probably from my accent that I'm British.
Speaker 10:And I've been at Palantir like almost a decade. Wow. So seen a lot of change, a lot of growth out here in The UK and Europe. That journey from a business that was very focused on defense and intel with a tiny bit of corporate to now a business that's serving every bit of the public sector and every corporate sector you can think of.
Speaker 2:And what's the news today or yesterday?
Speaker 10:Well, big news is well, technically no. Technically, it was, early UK time this morning Okay. So you're not out of date.
Speaker 2:There we go.
Speaker 10:We announced a big, big deal with the UK Ministry of Defense. Billion dollars.
Speaker 4:A billion dollar deal.
Speaker 1:A billion. Yes. Dollars. Congratulations.
Speaker 10:Thank you. Thank you, guys. Well, it's the first billion dollar deal that Palantir has done outside The US, so it's a big significant milestone. And alongside that deal, we also announced, a big investment into The UK, dollars 2,000,000,000 over the next five years, the creation of three fifty new jobs. Mhmm.
Speaker 10:And, our European HQ for defense will be in London.
Speaker 2:What does the $2,000,000,000, investment look like? Is that, just the investment in the team, OpEx, CapEx? Like, how are you thinking about that?
Speaker 10:It's all of those. And London is already a little known fact, it's already home to about 20% of Palantir's headcount.
Speaker 2:Oh, wow.
Speaker 10:It's so it's actually our second largest office globally. So we do a lot more than just support, you you know, British customers from this office. Yeah. We do a lot of product development and it serves as a as, yeah, as like the European and and broader EMEA headquarters.
Speaker 1:Yeah. When did you realize that billion dollar deals were possible? Was it ten years ago when you started? Was it five years ago? Was it more recently?
Speaker 1:It's a big number.
Speaker 10:Yeah. I I think I always believed. And I think we're only just getting started. You know, this is you know, we'll look back in five years' time, I think, and we'll think, yeah, those were small deals. You know, the power of the software is such, and it's meeting its moment.
Speaker 10:You know, the significance of this deal is is it's you know, we are the operating system for the modern battlefield. Mhmm. And we've seen The US make that move, and the significance of the news today is is The US's closest ally, The UK, making the same move.
Speaker 2:Yeah. What what's the mood like in The UK relative to the rest of Europe? We talked to doctor Karp. Was that just last week or was it the week before?
Speaker 1:Week before.
Speaker 2:It's About the reception and what's going on in Germany. He, of course, studied in Germany, and he was kind of joking about the lack of entrepreneurial talent and adoption and kind of getting with the program in Germany, but it seems like The UK might be a little bit more forward thinking. Walk me through sort of the view in Europe technology right now.
Speaker 10:I think I think that's spot on. I think The UK is an outlier. Mhmm. We've got, especially here in London, an incredible talent pool, especially in the computer science, software engineering domains. That's why Palantir has so many people here.
Speaker 10:It's why we do product development here. It's really access to the talent. And you've got DeepMind, you've got you know, you've got a key key parts of the of the broader AI supply chain ecosystem are are here. And I think it means UK is is like the only country in the West broadly defined outside The US that does have that kind of talent pool. And obviously, the language helps, speaking English, connection to The US.
Speaker 10:And, you know, we weren't alone, right, today. Palantir is not the only company to have announced investment in UK. Alongside president Trump's visit, we saw Microsoft. We saw NVIDIA. We saw OpenAI.
Speaker 10:We saw Google. A whole raft of big tech make big investments.
Speaker 2:How are you thinking about the work that you'll actually do? How how concrete is it? How much can you share about what's actually in scope for this contract?
Speaker 10:I I can share bits of it. Obviously, a lot of it is sensitive operational details, but a key part of it will be what The UK is calling the digital targeting web. We Palantir will be a component of that. It'll involve many, many other companies and players, And you could think of that a bit like what the Maven Smart System does for The US. Mhmm.
Speaker 10:So it's really your targeting infrastructure, how you connect up all your sensors, your satellites, your drones, all of your various data feeds with your effectors, you know, the stuff that you're gonna use to shoot airplanes, tanks, missiles. It's that data infrastructure that sits in between that. It's the harness in which you then run all of the sophisticated AI and computer vision algorithms and so forth. A lot of it is inspired and frankly lessons learned from the war in Ukraine, where the same technology, our platforms have been, as you'll know, deployed by the Ukrainians day in, day out now for nearly three years, And those lessons are being learned. And, you know, we're seeing the future of warfare play out in real time.
Speaker 10:And, you know, the significance of this is is is the UK government making a multi multi million pound investment in in that.
Speaker 2:What was the what was the precursor technology to Maven? I remember when I when I dug into I mean, it was, like, controversial program here in The United States. And and when I looked into it, it seemed like the precursor to using image recognition and computer vision to identify objects and images was, thousands of air force airmen manually tagging and basically doing something that you would expect like a data labeling firm to do. And it's not like the government wasn't trying to identify images objects and images. They just weren't using technology.
Speaker 2:Is it the same thing over in The UK? Like, what what's the lineage of this?
Speaker 10:Yeah. Exactly. Right. And and if anything, the the the problem is more severe because The UK is smaller and has fewer resources than The US. So, you know, you're never going to have enough eyeballs to watch all of those feeds.
Speaker 10:So, you need to find some way of automating that and surfacing something of interest to the human when that occurs, when that matters. That's how you're gonna scale up.
Speaker 1:Does this type of deal make the next five deals with other Western allies easier? Right? I'm assuming that it would be, you know, given it just becomes much more difficult to coordinate if if allies are operating on different systems, but I don't know if I have the wrong framework for that.
Speaker 10:I think no. I think that's that's a that's a I I mean, obviously, I I hope that's a likely scenario, but it's, you know, it's critical. And, this is a lesson from Ukraine. Right? The interoperability is everything.
Speaker 10:Yeah. The ability to task pass targets seamlessly between between units, between allies. That is that is the way we're gonna, confront and deter the adversaries that we now have in the West.
Speaker 2:When we talked to doctor Carr, he mentioned that, because of the current structure of Palantir, because of the the where we are in the technological adoption curve, artificial intelligence, he did not expect headcount to grow significantly. Does this deal change anything for Palantir's UK office? I imagine it's like a whole lot more business. It might justify some hiring. Are you hiring?
Speaker 2:How do you think about Yeah. You said actually supporting the
Speaker 1:150 new hires, but Sure. That didn't feel like a huge number in the I mean, it just the efficiency of of the platform.
Speaker 10:It it will it will mean we hire. Yep. We will be creating jobs. But the output per head Yep. Is going to grow even more significantly.
Speaker 10:Think Ted Mabry, my colleague who runs The U. S, the global commercial business, was just tweeting today about AI FTEs. So the the forward deployed engineers we had that have historically been human beings are starting to to to replace some of the work they would have done manually in the past with AI. And you can just see a path now where, like, 90% of what used to be the day to day job can be done by AI. So then suddenly you've got 10 FTEs for every one you used to have.
Speaker 10:I mean, the the the exponential here is is crazy.
Speaker 2:It's amazing. Well, congratulations. Thanks so much for coming on and staying up late to join the stream.
Speaker 1:Not at all. Yeah. Billion dollar deal. We have to hit this button for you.
Speaker 2:Overnight success.
Speaker 1:There we go.
Speaker 2:Thanks so much for coming on the show. We'll talk
Speaker 1:to soon, guys. Congrats.
Speaker 11:Thank you.
Speaker 2:Thank you. Soon. Linear. Linear is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product road maps.
Speaker 2:Head over to linear. The bond market has completely rejected the Fed's rate cut. We talked about this a little bit yesterday. Yields have ripped higher following an initial drop on the rate cut announcement. The rate cuts had
Speaker 1:opposite prayer circle at this point.
Speaker 2:Yes. Mortgage rates will now spike. Mortgage rates were creeping down. This is not very good news. We're still talking about point one percent of a move over the last day, but not in the right direction.
Speaker 1:So Yeah.
Speaker 2:Not fantastic. But, of course, that account is from QE Infinity, which is quantitative easing, of course.
Speaker 1:No bias there. Our post earlier Leopold? For on August 10, Leopold
Speaker 2:Aged like a fine wine.
Speaker 1:Yep.
Speaker 2:We went we we were extremely bullish on Leopold and situational awareness. Back in August 10, his fund topped $1,500,000,000 and posted 49% gains just for the 2025. This was from, filings whenever you're, running a fund. You need to
Speaker 1:Remember, at that time, there were some people saying, like
Speaker 2:Long intel?
Speaker 1:What could Is his fund already blown up?
Speaker 2:Yes. Yes. Yes. And so, Swix shares a screenshot of what intel has been doing over the past year. They're up 28 and Swix says, oh my god.
Speaker 2:He's going to destroy h 02/2025 too.
Speaker 1:Good.
Speaker 2:And now Good year to
Speaker 1:have some situational awareness.
Speaker 2:McAleese says everything reminds me of him, and it's all green lines up into the right with a variety of stocks up 50, a 100%. He has fully nailed the AI trade. Will Brown says you could buy so much Diet Doctor Pepper with $2,000,000,000. I don't know if that's like Leopold's favorite drink or something. I don't I don't get the Diet Doctor But Pepper
Speaker 1:This stat was insane and a little disheartening. Yes. The What top 10% of US consumers now account for half of all consumer spending, which is a record high
Speaker 3:Mhmm.
Speaker 1:Up from about a third in the early nineteen nineties. Okay. So Some creeping up over time. Different way to understand Yeah. Wealth inequality.
Speaker 6:Mhmm.
Speaker 1:And it just goes to show if you're if you're building consumer products, you probably wanna be building for that that top 10% that are spending half of all dollars.
Speaker 2:For sure. And you gotta pay your sales tax on Numeral. Numeral HQ. Sales tax on autopilot. Spend less than five minutes per month on sales tax compliance.
Speaker 1:Numeral Now this is announced a new round today
Speaker 2:Oh, yeah. Congratulations.
Speaker 1:300 What? And $50,000,000 Congratulations. Up from their series b earlier this year or series a earlier this year. And we're gonna have Sam on tomorrow live from the studio for his first first ever guest appearance, and it'll be Oh,
Speaker 2:what we're do.
Speaker 1:Pumped for that.
Speaker 2:Still on Intel, funny journey. If you bought $10,000 worth of Intel twenty five years ago, it would be worth $10,000 today. Absolutely zero movement over the past twenty five years, basically. It's a store of value, I guess. It there has been movement, of course.
Speaker 1:It You gotta factor in inflation.
Speaker 2:And then it actually sort of ripped from 2010 up to 2021, but then it fell and went back up. But now it's climbing back up. And the the the the big news on Intel world is that NVIDIA invested $5,000,000,000.
Speaker 1:Marked Trump up.
Speaker 2:They marked up Trump. They marked up The US taxpayer since now we all own Intel shares. But this could be the start of something cool. This was what who was it? John at at Asianometry was proposing the idea that NVIDIA would second source the CPUs from Intel because
Speaker 1:NVIDIA is up 22% today.
Speaker 2:Today? Wow. What is there China news? What what
Speaker 1:Sorry. Sorry. Sorry. Sorry. Not NVIDIA.
Speaker 1:Intel.
Speaker 2:Intel's up 22%.
Speaker 1:I'm so used to saying Okay.
Speaker 2:NVIDIA. Yeah. No. NVIDIA can't be up 22% a day. It's so big.
Speaker 2:It went down 3% yesterday on the China news.
Speaker 1:Back up 3%.
Speaker 2:It's back up three percent?
Speaker 1:Three point seven percent. Not back to where they started.
Speaker 2:Market thinks they're going back into China, baby. The black wells are gonna be shipping the b thirties. They're it's happening. Bobby Cosmic is rooting for Intel and says he
Speaker 1:loves Of course, we're rooting for Intel. We're all rooting for Intel.
Speaker 2:We're having Pat
Speaker 1:Kelsink earlier this soon. Post Fun. Is hilarious. Every AI app today and It's a box truck
Speaker 2:and a bag. With a sprinter van inside. And then inside the sprinter van is a subcompact car. And this is just the nature of recursively calling various API abstraction layers, probably. The agent that calls the underlying LLM.
Speaker 2:Definite.
Speaker 1:South Park delays new episode hours ahead of airtime because creators didn't get it done in time.
Speaker 2:Mhmm.
Speaker 1:They say apparently when you do everything at the last minute, sometimes you don't get it done. Do you think this is because they were about to do something that that was gonna get them taken off the airwaves? Maybe. I think
Speaker 2:It's high stakes right
Speaker 1:a lot of people that are used to joking around are On air. Are understanding that at least in this period of time, jokes can have consequences, blowback. Yep. Cancel culture's back.
Speaker 2:Cancel culture's back. It is remarkable that they that they ship an entirely new episode. That they that that it's a it's a produced animated show, but it's created around the news cycle.
Speaker 1:And so Real time.
Speaker 2:I believe when the when when the Obama election happened, they had I think they prepped two different episodes. And then they were able to air the one that was that corresponded with the the correct winner or something like that. Because they had that episode up, like, the same day that Obama won, which was crazy. But hats off to them. Considering their their track record, it's impressive this doesn't happen more often.
Speaker 1:That's what I'm saying. You really you got a
Speaker 2:Tinfoil hat moment.
Speaker 1:Tinfoil hat moment.
Speaker 2:Yeah. They yeah. I don't know that they've ever missed have they ever missed an episode? They must have at a certain point. And they do go off air for a little bit.
Speaker 2:And I'm sure they have stuff in the backlog. But it's crazy how long they've been at it. This has been, what, twenty, thirty years on the air? It's one of those shows that I keep forgetting about. And then somebody shares like, oh, they did one about AI.
Speaker 2:You gotta you gotta watch this. They did this about the thing that you really focus on. So you gotta do it. So Fin dot ai, the number one AI agents for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on g two. Founder Moe.
Speaker 1:I'm only able to find one other instance where they had a official production delay for a new episode. Really? It was in 02/2013.
Speaker 2:Well, Bryce Roberts says, don't wait for more resources to have kids. John Woo broke it down. Got 9,000 likes almost.
Speaker 1:Yeah. This post went super viral.
Speaker 2:He said, my only regret in life is not having kids earlier. When I was 27, I was going out four nights a week, working twelve hour days, six days a week, waking up at 5AM daily for CrossFit. Kids would have been a breeze. Don't wait for more resources to have kids. Energy is scarcer than money.
Speaker 2:It's a good take. Thanks for blowing this up, guys. Follow me.
Speaker 1:Yeah. The other the other thing here is if you have kids younger, it just means you're younger when your kids are Older. Fully functional and independent. Right?
Speaker 2:Also, I mean, there's just this, like, idea that you, like, oh, you need to, like like, you you don't you actually don't get to stop working when you have kids. Like, you'd actually do go to work and and make more money. And so it's it's, you know, it's not just like, oh, you need to be retirement age or have, like, retirement money before you
Speaker 1:I mean, I think it's entirely a fixation of people have had in their mind forever. This idea of, like, you buy your first you get married, you buy your home Yeah. And then you have kids. And that's so ingrained in the culture that people just don't even consider having kids.
Speaker 2:Yeah. Because of the house.
Speaker 1:Because House
Speaker 2:prices are so high.
Speaker 1:Yeah. They're not in a position to buy a house but I think yeah. Well Kids are nothing more nothing to motivate the grind set like Indeed. Couple of pups.
Speaker 2:Deeply motivating.
Speaker 1:We got John's He's on board he's trigger happy.
Speaker 2:Amit, who we met at Palantir Dev Day said
Speaker 1:Number one Palantir retail soldier.
Speaker 2:Yes. He's an
Speaker 1:imagine He's a brigadier in general.
Speaker 2:Told Jensen that if he didn't pump his intel bags, then he wouldn't be able to sell to China. Then Jensen saw the 60,000,000,000 they had in cash and was like, screw it. Put 5,000,000,000 into intel so we can ship to China.
Speaker 1:You think this solves Jensen's China problem?
Speaker 2:I don't know.
Speaker 1:I don't know if
Speaker 2:there don't know. It's not a Trump issue anymore. It's a Beijing issue.
Speaker 1:It's a
Speaker 2:Beijing issue. Right? Yeah. I don't know what I don't know what Trump has left.
Speaker 1:I mean, Trump up 36% on his first real trade size. Pretty good. Makes you wanna let you makes him wanna get him set up.
Speaker 2:But there's a lot of there are a lot of other, like, chips on the table that Trump can pull. There's rare earths. There's TikTok. There's all sorts of what? What did say?
Speaker 1:Chips on the table.
Speaker 2:Oh, yeah. Yeah. Yeah. Of course. It was an accidental pun.
Speaker 2:But, there are other places where if NVIDIA rises to this to this top of the stack and becomes one of the most important American geopolitical issues and the mood around exporting chips and chip bans just kind of completely cools and China hasn't asked, well, then Trump can art of the deal and say, hey. You gotta let you gotta unban NVIDIA locally. It is funny that we split from from America banning NVIDIA selling to China to China banning NVIDIA selling to China. And it's like they both were at one point were banning, but at different time time horizons and kinda going back and forth. But, anyway, I think Jensen will will figure something out.
Speaker 2:I this is not the end of that story for sure. There's gonna be there's gonna be chips flowing, flowing, flowing, flowing. Near shares that you can just copy trade Leopold's fund and triple your money in a day. The forms are public. It's crazy.
Speaker 2:The 01/16/2026, $24 call that Leopold put on is up 200%. So triple.
Speaker 1:Is that good?
Speaker 2:It's fantastic. Nerse is absolute king. Xayniel, congrats on the extra billion. Anyway
Speaker 1:The Coachella lineup dropped two months early and over 60% of attendees were on payment plans last year.
Speaker 2:What does that mean that it dropped early? I don't understand.
Speaker 1:Yeah. I just I think I think they maybe anticipate it's gonna take longer to
Speaker 2:sell all the tickets. Okay.
Speaker 1:Yeah. Used to be back in my day Yeah. In the heyday. It was weekend one was always fully sold out.
Speaker 2:Fully sold out.
Speaker 1:Maybe the the tickets would be selling at a pretty significant premium Premium. To retail pricing. And so and I think last year, if I remember correctly, you could just basically buy you could basically buy weekend one ticket at below retail. I
Speaker 2:wonder if that's a I wonder if it's like a dynamic around, like, who is actually playing Coachella? Who's hot? Like, are there are there And then
Speaker 1:you drop the lineup. Do you have
Speaker 2:Is the lineup crazy?
Speaker 1:Sabrina Carpenter is headlining day one, Justin Bieber, day two.
Speaker 2:Okay. But it's not Taylor Swift and the Backstreet Boys. They're over at The Sphere. So maybe the Sphere's sucking the energy out because the Sphere tickets are selling great. And they're they're super expensive.
Speaker 2:So maybe people want want something new. Maybe Coachella's washed We
Speaker 1:do a live show from the Empire Polo Club this year.
Speaker 2:I don't even know what that is.
Speaker 1:That is that's where Is that at Coachella? Place.
Speaker 2:Oh. Off in the pull up field. Oh, but not during Coachella? Just like at a different time or during Coachella? You wanna be on stage next to you wanna be going up against a big
Speaker 1:star? Wanna be
Speaker 2:Podcasting next to timeline. Yeah. Next to
Speaker 1:Interesting. Dario went out on stage and said he does not think we should be selling AI chips to China. This is a quote. I think it's completely nuts. It's very important that we defeat China in this technology.
Speaker 1:Well
Speaker 2:Axios event.
Speaker 1:You got what you wanted because Beijing decided to make that decision themselves.
Speaker 2:Yeah. Dario. Anyway, Adio. Customer relationship magic. Adio is the AI native CRM that builds, scales, and grows your company to the next level.
Speaker 2:You can just go for three. Also The
Speaker 1:team just went absolutely wild in here.
Speaker 2:Siegel over at Privy, our latest sponsor, says, wow, OG Privy customer won an Emmy. Shout out Dylan Aberscato and people pleaser doing some serious damage, getting on chain projects represented at the pinnacle of media accomplishment. White Rabbit just became the first crypto project to win an Emmy. Imagine telling
Speaker 1:2021 outstanding innovation in emergent emerging media programming.
Speaker 2:It's cool that they have a new for like, a new award. There has to be a new award. Right? That wasn't that award can't have been around for that long. But people pleaser says, imagine telling twenty twenty one crypto Twitter that in a few years, our producers and ETH would get a shout out on stage at the Emmys.
Speaker 2:Pretty rare.
Speaker 1:Let's pull up this video. Yeah. Let's play the check-in with Europe.
Speaker 2:Let's yeah. Let's play the Check-in with Europe. Wait. Wait. Wait.
Speaker 2:Why Europe?
Speaker 1:Oh, I I I was I was on to the next post.
Speaker 2:Oh, okay. I wanted to watch the Emmys video if we have that one. I wanna see I wanna see exactly how they frame this. But we can watch the
Speaker 1:this I don't think that's the right video.
Speaker 2:I think that's just a different humanoid robot.
Speaker 1:Got the wrong guy.
Speaker 2:Let's pull up the people pleaser Max Siegel post, and I'll tell you about Eight Sleep. 8sleep.com, get a Pod five, five year warranty, thirty hours free trial, free returns, free shipping. It's good Good. To be because you're home and you get to sleep in your eighth sleep tonight. I know.
Speaker 2:Finally. It's always hard being away. Anyway, can we pull up the Emmy's video from the
Speaker 1:time I think that might have just been a screenshot.
Speaker 2:Am I
Speaker 1:off there?
Speaker 2:People pleaser? Okay.
Speaker 1:We'll circle back. Let's pull up this video. I put it in the chat of this humanoid.
Speaker 2:This is Calvin forty, the humanoid developed by the French company Wandercraft. And Chris says Europe is cooked, lol. I I don't know why they're cooked. They're cooking if they're making robots. Let's see.
Speaker 1:Is it bad?
Speaker 2:I didn't actually see the full video. I hope it's not bad. It doesn't okay. It's picking up a tire. This seems fine.
Speaker 2:This is good. This is good performance. What's not to like? Picks up a tire. It seems useful.
Speaker 1:Headless.
Speaker 2:It is weird that it doesn't have a head.
Speaker 1:I mean
Speaker 2:It's not exactly Pixar level cute. It's a wallish It's a wallish shake. Literal clanker. It's clanking around.
Speaker 7:One of the comments is Yeah. Was this trained on folks over 40?
Speaker 2:Yeah. It does seem very slow.
Speaker 1:I mean, I I swear almost every humanoid company today, this has been training on, like, Biden.
Speaker 2:They haven't been trained. Biden. Biden. They're trying to train on Usain Bolt, but, you know, it takes time to integrate all that.
Speaker 1:They want the best of Bolt is holding out. He's saying you can't train you can't train. He's he's
Speaker 2:I'm I'm locking up my training data.
Speaker 1:He's like, you gotta pay up.
Speaker 2:What do think, Tyler?
Speaker 7:I mean, the difference between this and the the unitary demo or the demo on the unitary, I don't think it was unitary that did that where it was it was fighting, and then it flew down and immediately got back.
Speaker 2:Yep. That was crazy.
Speaker 7:Crazy, the difference.
Speaker 2:Yeah. And someone was saying that that robot was, like, not was being teleoperated. Like, there's there's someone in the background with, like, controller controlling it. And and Rune had a good point that was like, well, like, telling it to move forward is, like, the easiest part. Like, the the hard part is, like, actually having a button to press, like, pop up.
Speaker 7:Yeah. Exactly. You're not mainly controlling that motion.
Speaker 2:No. It clearly has some incredible incredible ability, like, and understand its position and hop back up. It's pretty good. Well, I don't know. We'll have to check-in with Wandercraft, see how they do.
Speaker 2:I I you know, this is better than nothing. I don't know. I think they're they're
Speaker 1:It's a good start.
Speaker 2:They could keep going. We have our next guest, Brendan from Merkor coming in the studio. Brendan, welcome to the stream. How are doing?
Speaker 1:I'm doing great. How are you?
Speaker 2:I'm great. Sorry we couldn't, link up on Tuesday. You have some massive news. Introduce yourself. Break it down for us.
Speaker 2:What's the latest and greatest thing?
Speaker 1:Glad you finally you know, it's good you get to the $500,000,000 revenue mark, you decide, alright. I'll do some podcasts.
Speaker 2:Yes.
Speaker 4:Exactly. Yeah. So I'm Brendan, the CEO and cofounder of Merkor. Started the company with my best friends from high school when we were 19. Scaled up a little bit, $2,000,000 revenue run rate, dropped out of college, started working with all of the AI labs, and scaled from 1 to 500,000,000 in revenue run rate in seventeen months.
Speaker 1:Congratulations. Which
Speaker 4:has been pretty wild. Yeah. No. And and super super exciting and surreal, as you can imagine. So very excited about all of the progress with the business, and the best is yet to come.
Speaker 2:What was the first task you did? Like, what was the first data you labeled? What was the first project to get from how did you go from zero to one, basically?
Speaker 1:Yeah. Name every piece of data.
Speaker 4:Well, so I remember the very first oh, let's see. There there were a few. But the first meeting that really jumped out, was when we were hiring Olympiad medalists Mhmm. Because everyone was interested in how the models could become superhuman at Olympiad math. And so we turned around 25 Olympiad medalists in twenty four hours.
Speaker 4:And I I bring up this example because I wasn't completing the task successfully. I was obviously, haven't don't have an Olympiad gold medal in math, but it was it was incredible to just see, like, how capable the models are and this indication of the huge trend underway in the market away from low and medium skilled talent towards this super high skilled sourcing and vetting paradigm ranging from Olympiad math all the way to the THANG software engineers and top investment bankers and consultants that help to push the frontier of models.
Speaker 2:What was the onboarding process for those 25 medalists? Was this just like cold outreach or something? Like, how'd you actually meet these folks?
Speaker 4:Largely through referrals. Because we have a big pool of people that we've already hired on the platform. And so the largest sourcing channel by far is that people we've previously worked with will send the link to their friends, and we'll pay them $250 for a successful referral to help grow the talent network.
Speaker 2:It feels like most of the labs are I mean, we saw this with OpenAI. Mark Chen was just posting that they basically dominated every hard programming and math competition this year. What are the labs interested in next?
Speaker 4:Yeah. I I think the largest transition is and we'll share more about this in one of our product releases soon, but it's away from academic evals Mhmm. Like Olympiad Math or GBQA for PhD level reasoning, and moving towards all of these professional domains of how do we measure what it means to be a great software engineer to build products? How do we measure what it means to be an investment banker that can do thoughtful financial analysis or a consultant that can help to, you know, segment a market? And these end to end evals over all of the professional capabilities, I think, will be one of the largest, most exciting trends in the market over the next year or two.
Speaker 2:What's the shape of that task then? I mean, it's so vague. It's it's so much, like, less quantifiable than what we what your score was on the IMO, although that's incredibly impressive if someone can do that level of math. Go build good software feels really unverifiable, feels really broad.
Speaker 4:Exactly. And so that's why you need humans to define the stasis points. It's so much more difficult to measure. And so one way of doing it could be to build a rubric where the model can use the criteria to score the deliverable that's being produced. Like, imagine you want the model to be really good at building a web app that looks beautiful.
Speaker 4:You could have rubric criteria for, you know, all of the different elements of of said web app or or whatever you're ultimately building. And so having humans define the success criteria and using that, those verifiers, as part of an overall environment to train models iteratively to learn how to optimize for those criteria is one of the enormous trends that we're seeing across all of the frontier labs.
Speaker 1:How do you how do you sort of plan with the team when you have overwhelming it it demand for a current product yet simultaneously need to try to predict future demand in a way that I think normally when companies are doing traditional demand planning, it's like very clear of like just how many customers can we reach with our current set of products and future products. But in your business, it's not always entirely obvious what the needs are gonna look like, you know, even a couple years out.
Speaker 4:Totally. I think that the most important thing is always working on the frontier and understanding what are the leading indicators of what the entire economy is gonna be doing soon and adopting soon. And emphasizing that frontier in all of our product development and all of our investments is one of the most important decisions that we've made historically as sort of a framework for resource allocation.
Speaker 1:That makes sense.
Speaker 2:We were just watching a video of a French company, Wandercraft, making a humanoid robot. People were kind of joking about it. I thought it was pretty impressive. I haven't seen any humanoid robots out of out of France. But can you talk about what the data collection process for humanoid robots looks like now?
Speaker 1:Yeah. Specifically, a lot of you know, we were at Meta Connect yesterday Yeah. Talking with Zac and Boz and the team. And a lot of people saw the announcement, and they've said, okay. A lot more people are gonna have cameras on their faces soon.
Speaker 1:Yeah. How valuable is this? Should should frontline factory workers be, you know, be collecting data today, or or is that not necessary?
Speaker 4:Yeah. It's interesting. The key thing for the models to learn is having a clearly defined reward. And so I'll give, like, a couple of examples of that and sort of the role that humans can play. The first one actually without humans is that I was at the this, like, robotics office where they had robots that were folding laundry, and then they would have a vision model look at the laundry to see if it was folded properly as the reward.
Speaker 4:So, right, having that stasis point where you can have a 100 different model trajectories, see which five trajectories are right, and then reward those trajectories so that the model increases its probability of doing that correctly in the future is very powerful. All the way to another example where models are proposing scientific experiments, and then we need humans that we hire as contractors to run those experiments in the physical world, report on the results, and say how they did. And so I very much believe that models will learn from their experience in interacting with the real economy, but so much of that experience, similar to the way that you or I learn, is curated by humans. And the way that, you know, we help models with running the experiment in the physical world and giving feedback, etcetera.
Speaker 1:You tweeted the letters IPO a while back. What did you mean by that?
Speaker 4:Well, I did I did comment in parentheses below that kiddag.
Speaker 1:Oh, okay. I missed that part. I missed that Yeah. Yeah. Okay.
Speaker 1:That's it. It's all good.
Speaker 4:Well, people people took it seriously because I remember that
Speaker 1:I'm sure you got a lot of, like, frantic calls from bankers being like, Brandon, you told me you'd tell me.
Speaker 4:Yeah. Yeah. Yeah. Well, it's funny because last year when we were a seed stage company, I tweeted IPO by end of year. Yeah.
Speaker 4:And everyone thought I was, you know, a little bit crazy because we'd raised our our $40,000,000 seed round. Or sorry. I tweeted, yeah, Unicorn by end of year. And we, you know, ended up making it happen. And so people thought maybe this time was was real, but I was I was just kidding about the IPO.
Speaker 2:Got to keep What's the what's the shape of the business now? Obviously, there's a huge amount of focus on on these expert networks and and these really high skilled specialized talent getting data from that and working through different problems and all the examples that you gave. Is there still a need from big labs for just the more traditional RLHF? Is this good? Is this bad?
Speaker 2:Thumbs up, thumbs down? Or has that been completely absorbed by just Users of the of the The users or also just the models themselves. Like, is is are GPT five or or, you know, any of the other models, the frontier models, are they able to deliver the the the thumbs up, thumbs down if you need to do some sort of fine tuning on a specific problem?
Speaker 4:Yeah. It depends on the lab. There's definitely still large investments that are happening in RLHF. However, it seems like it's more efficient to collect those via data flywheels in real world. And where you really need expert human involvement that's incredibly valuable is someone that will think about a problem for five hours and come up with this, like, very structured framework for how to evaluate model success in a way that it's difficult to expect users of products to do in a reliable way.
Speaker 2:Is that the is that, like, a reasonable way to think about a task, a single task, like five hours of
Speaker 4:of That might be one way. Yeah. But one thing I'm very excited about is that the time horizons of agentic trajectories will go up dramatically.
Speaker 1:Sure.
Speaker 4:Right? And so I think a lot of people initially think about AI in the context of what can they see on their screen on ChatGPT at any given time. Yep. But over time, it's and maybe using one tool with, like, online research. But over time, we're gonna have the models working on problems that would take a human thirty days to do or ninety days to do that are using 10 different tools, are interacting with various employees in the companies.
Speaker 4:And we need environments for all of that. Right? We need ways to eval and to measure success to define the rewards. And that's gonna be a very exciting problem space to continue pushing the frontier of.
Speaker 2:How does how do you or just humans generally fit into solving the problem of, like, booking a flight or or, you know, ordering DoorDash? We've heard about these simulated environments, RL environments, verifiable rewards. Like, is it is it mostly designing the environment with the reward? Or is there actually a process for someone who's just a fantastic travel agent to, you know, create a a rubric or create a or just actually do a ton of tasks to generate data?
Speaker 4:Yeah. It could be. So one way you would do it for those kinds of browser use workflows Yeah. Is that you could have a simulated application and then a unit test that measures if the model effectively, you know, completed the task to change the state and, like, booking the applicate the flight or whatever the action is.
Speaker 2:Yeah.
Speaker 4:And, ultimately, you do need a human expert to help write what is that unit test. But my guess is that computer use will be solved relatively quickly in the next, like or at least in the next, like, two or three years. And then there's gonna be this much longer tail of sort of the broad space of knowledge work and everything that we wanna do of how do we get the model to build a startup or Yeah. Help help prep for a podcast episode or or whatever the workflow is.
Speaker 2:Yeah. How how do you think about solving problems that take, like, decades? Like, I I always go back to, like, you know, health. There's certain things where, you know, the the FDA does a lot of work to try and understand, you know, if you're consuming this particular ingredient for fifty years, how does that affect you? It feels like until we can simulate the entire human body and and run it at a faster clock rate, like, that seems like something that you just can't really short circuit.
Speaker 2:We're already getting to, like, longer and longer rollouts, and that feels like that might be some sort of, like, damping function on how quickly we can compound. But are there any promising, strategy that you've heard for dealing with, problems that just take a long time to actually understand the reward or understand the did the pass fail?
Speaker 4:Yeah. The concern I would have with that scenario is it's so difficult to perfectly simulate, like, the human body and how that would play forward. And so my guess is that for a very, very long time, models will more so look at empirical analysis. However, models might survey people that took certain Yeah. You know, vitamins or or whatever drugs when they were a certain age and see the impact that that's had in their analysis, but it'll it'll be difficult to simulate in that case.
Speaker 4:There are other cases where it's like a well scoped physics simulation of how well does, you know, this, like, ball roll down the plane or or whatever we're modeling out that'll be easier to simulate and therefore for models to have an accurate understanding of how things will play out in the real world.
Speaker 5:Jordan?
Speaker 1:What's are you guys naturally nine nine six?
Speaker 2:Oh, yeah.
Speaker 1:Do you do you
Speaker 4:I always get
Speaker 8:this question.
Speaker 1:But but I but I feel like you guys are probably more on like a like nine nine seven, like six is almost for the week. You guys are twenty, twenty one, like what what else do you have to do besides besides this?
Speaker 4:Well, it's funny because we have actually never really mandated ours, the company.
Speaker 2:It was
Speaker 1:just that That's how I figured, but there's like, if you're ramping revenue from one to five hundred million in
Speaker 4:It's a lot of work. Yeah.
Speaker 1:In a little bit of time.
Speaker 4:Exactly. So I think it the way it started was our initial core team was working, like, seven days a week. And everyone was in the office, like, super late, all this stuff. And so we initially gave that rough guidance because we wanted people to have a little bit more balance in going home earlier, etcetera. But obviously, as the company's developed, I think it's important to be able to hire people that have families.
Speaker 4:And even though they'll work hard on the weekends, they might still be at home. And so there's there's some of that as well, still emphasizing a lot of intensity and, you know, moving mountains for customers, but at the same time, not necessarily being as input oriented and and much more focusing on outputs.
Speaker 2:How big is the team now? Like, the full time core, not the network.
Speaker 4:Relatively large. We're 250 people now. Wow.
Speaker 7:Congratulations.
Speaker 4:Fast. Yeah. Exactly. Across The US and India and then a a little bit across Latin America and The UK as well. But, yeah, it's it's been exciting.
Speaker 4:Certainly, a crazy feeling to start having all of these people on our our new SF office and and new faces that I have to meet. So lots of What
Speaker 1:kind predictions are you gonna make? Any numbers you're throwing out? You you said unicorn by end of year last year, but what about what about going forward? Anything you're willing to willing to to take out?
Speaker 4:We could say decacorn by end of year this year. So
Speaker 1:No. It feels like you might might already have it in the bag, but
Speaker 2:I'll take it. Yeah. We'll have to call Arfurak to get this over there. Congratulations. We'll talk to you soon.
Speaker 1:Great. Good to get the update on. Good to catch Cheers.
Speaker 4:We'll talk to Bye.
Speaker 2:Up next, we have Darren Mowry from Google Cloud coming in. Big Google announcement today. Big event, over Google in the, global startups at Google Cloud world. Let's bring in Darren. How you doing, Darren?
Speaker 2:Good to see you.
Speaker 6:Cool spot here in Mountain View,
Speaker 2:so it's great
Speaker 6:to be able to spend a few minutes with you.
Speaker 2:Thanks so much for hopping on
Speaker 1:the sharp as well. Thank you for wearing a wearing a suit.
Speaker 6:Thank you. I had to brush off the suit. I had to kinda dust off. It looks fantastic. Somewhat presentable today, guys.
Speaker 2:Yeah. It looks great. Take us through the what what, the the event, what's going on today, what's been announced, who's there, everything.
Speaker 6:Yeah. That's great. So we're actually gonna in a couple hours, we're gonna be kicking off our first global AI builders summit. And so we're gonna have a couple 100 founders and builders here in this room, which I can tell you about if you're interested.
Speaker 9:Little bit
Speaker 6:of cool Google history here.
Speaker 2:Yeah. That'd awesome.
Speaker 6:And then we're gonna have a few actually, tens of thousands of startups and builders around the world joining us digitally as well. And so today, we're having customers like Lovable, Reflet, Fireworks, and others on stage talking about, you know, the problems they're trying to solve, but how AI is actually helping them complete you know, completely revamp the industries that they're in. We also have some Google Cloud and some DeepMind folks joining us as well to talk about kinda how quickly we've seen the evolution, where we are now, and we'll look around the few corners into what's coming. So some really great sessions today over the next few hours. So we're we're excited about that.
Speaker 2:That's great. Tell me about the history of the building. You said that there was something special about it.
Speaker 6:Yeah. So we're actually in this place called Charlie's Cafe, believe it or not. And you guys probably know Google has been known for having good food, good cafeterias for a long time. This was our first cafeteria named after our fifty seventh employee, Charlie Iyers. And so in all seriousness, although it is a little bit of an urban legend, we actually do deeply believe in creating great spaces for people to come together and challenge each other, have good conversation, and eat a little bit of good food too.
Speaker 6:I'll definitely admit that. But we're here in this space. We thought it's a perfect spot to kinda bring everybody together, talk about building and innovation. So, it'll definitely be a great few hours.
Speaker 1:What give give us a high level on what the last year has looked like in your role specifically around, you know, supporting startups that just have an insatiable demand for inference and, you know, all the other infrastructure needed to scale these types of applications?
Speaker 6:No. It's a really good question. You know, you guys should know I've been in cloud computing for a while. I was at another hyperscaler for a long time at the early days of cloud, and I thought we were moving fast then until we've entered this AI revolution, right, which I think the compression and the speed is like nothing I've ever seen before. Over the last eighteen months, we've definitely felt what I think we would really call like a seismic shift, frankly.
Speaker 6:The old school way of thinking about cloud through the lens of infrastructure as a service. All of a sudden, people talking about all layers of AI from chips and infrastructure. Right? Are we gonna use NVIDIA chips? Hey, Google.
Speaker 6:What's up with this TPU concept that Anthropic is relying on? Kinda what does that mean? When you get to the model level, you know, the fact that Gemini and what we're releasing with VO, these are first class citizen models as I think you guys can see in terms of performance, cost, efficiency. But the fact that we're building and gonna continue to innovate on our models, but also partner with, you know, folks like Anthropic, folks like Meta to make sure Lama and Sonnet and others are also first class products that startups that are building on Google are able to use in a super integrated fashion. And then this concept more recently, right, which is this this agentic, this in agent AI, this is not a theoretical pursuit.
Speaker 6:I think it's interesting that when we talk to founders and they give us some feedback, the feedback they're telling us is the agent capability from Google Cloud is a real capability. It's not a planned release of products hopefully in the future. Right? It's a fully integrated stack where startups have an SDK and an ADK. They can build these agents, as I said, using first party and third party models.
Speaker 6:They can publish them, distribute them, and we can even help them go to market. Right? So to this to your point, the last eighteen months, breakneck speed, I think we're all learning quite a bit as we go. But I would say the feedback that we're getting from founders and builders especially are, a, telling us we're on the right track, doing the right things, and, frankly, they're saying go even faster. Right?
Speaker 6:Help us do even more even more quickly. So with Nano Banana, you guys may have seen that was released recently. These are things that are coming out of our DeepMind team, and there's gonna be further announcements again around agents and new models fairly shortly that are gonna keep us very top of mind and very much a part of what startups are building every day.
Speaker 2:Yeah. It's fantastic. Google's always been very is a great partner to the startup ecosystem giving out credits. Do do you feel like startups are burning through credits faster now in the AI age? I feel like, I remember going through Y Combinator and getting some huge amount of credits and not really knowing what to do with them.
Speaker 2:Exact yeah. I'm good. Oh, they usually expire after a year. But I feel like with with AI, like, you can you can actually accelerate much faster. What what what's the mood been like from startups that you work with?
Speaker 6:You know, it's a really good point. When you think of our Google Cloud for startups program, which does have a credit component, an engineering component, a support component, training, etcetera, we definitely have had a dramatic increase in the amount of startups coming to the platform. So that's, first and foremost, a really good signal. To your point though, which I think definitely shows you understand this space, is getting into these programs is one thing. Even being approved for credits is another thing.
Speaker 6:But actively consuming the credits and building value, that's what the startups care about, and that's what we care about. Right? So what I've seen now over my almost five years at Google Cloud is in the last eighteen months, not only do we have more startups than ever in the program, they're consuming the credits extremely quickly. And more importantly, for us at least, and I think for these startups, they're staying with us. Right?
Speaker 6:This concept of I'm gonna jump from one platform to another to use credits, worked in a commoditized cloud world where you could go from a virtual machine to a virtual machine to a virtual machine. Now that I'm able to come to these startups and do what we talked about a moment ago of GPU, TPU, Gemini, Cloud, Sonnet, Lama, agents wrapped in Google Cloud, we're finding these startups. They're using the credits, but then they're like, I'm not going anywhere. Right? And so I think that is the true business case and value proposition behind these credit programs.
Speaker 2:That's great. Anything else, Jordy?
Speaker 1:No. Thank you for joining, and, have fun out there. Wish wish we were, gonna be able to catch some of the talks ourselves, but, we'll have to be there next time.
Speaker 2:Yeah. We'll catch up with you soon.
Speaker 6:Thanks so
Speaker 2:much for taking the time.
Speaker 6:Yeah. That's alright. Great seeing you guys.
Speaker 2:Have a good day. Talk to you soon. Cheers, Darren. Have a good
Speaker 6:Yeah.
Speaker 2:Up next, we have Kvon from Macroscope coming in the studio. Also the founder of Periscope. We will bring him in in just a minute. In the meantime, let me tell you about public.cominvesting. For those who take it seriously, multi asset investing, industry leading yields are trusted by millions.
Speaker 2:I like that voice mails. Thank you, Jordy. What were you about to say?
Speaker 1:Periscope was acquired by Twitter.
Speaker 2:Yes.
Speaker 1:And did that become
Speaker 2:Live streaming.
Speaker 1:Live streaming.
Speaker 2:We'll get it from Kvon directly. Let's bring him in to the TBP and Ultradome from the Restream waiting room. Kvon, how are doing? Welcome to the show.
Speaker 9:Hey, guys. Great to meet you.
Speaker 2:Clarify Jordy's question. Did tell us the story of Periscope. We'll work through to Macroscope, but I'm super interested in in some of the Silicon Valley lore here. Tell yeah. Just kick us off.
Speaker 1:By the way, huge opportunity for somebody to buy up all the
Speaker 2:documents with
Speaker 1:scope at the end. Just every English word. So you're next company, you're gonna be like, I gotta I gotta keep double down.
Speaker 9:I might have I might have already done it. Oh.
Speaker 2:You never know.
Speaker 9:I gotta I gotta tell you actually. Please. Funny funny thing. Yeah. Nine years ago, almost to the day, nine years ago, we launched a feature called Periscope Producer
Speaker 2:Mhmm.
Speaker 9:Which is the same infrastructure that is powering this very broadcast right now. Wow. And our our dream when we built Periscope Producer was literally for a show like TVPN to exist. It's sort of like the the perfect blend of high production
Speaker 2:Yeah.
Speaker 9:Live streaming content blended with the conversation of what's happening on And, you know, it took a while for that to to come to fruition, but it just, like, makes me so happy and Yeah. Proud in a very emotional way to see everything you guys have done and to see it happening on on Twitter slash x.
Speaker 1:That's awesome.
Speaker 9:Awesome. Congrats on everything you have
Speaker 1:you for for building the bedrock.
Speaker 2:Yeah. I mean, I I I wanna get to Macroscope, but tell me more of the lore. What were the early days of Periscope like? What was the first, like, go to market motion? There's this there's all these famous back then, there was the era of, like, go to South by Southwest.
Speaker 2:This is the story of of a bunch of social apps, including Twitter, where you get the early you kinda create a groundswell of tech early adopters. What what was the first product build? What was the story back then? How'd you launch the product?
Speaker 9:Well, I mean, if wanna go way back, the very first version of Periscope, a, it it wasn't called Periscope. It was called Bounty. Yeah. And b, it wasn't it wasn't actually live streaming. Our first prototype was essentially I I sort of think of it as like a reverse marketplace for for Google Maps.
Speaker 9:Like, you would you would drop a pin somewhere in the world and someone would take a photo. You would you would you would have some prompt. Like, you would put a bounty on, know, what's happening at the Tokyo Fish Market right now. Okay. And someone would respond with a photo.
Speaker 9:And that to us was like a really cool way of trying to attempt to build like a teleportation device. That's cool. We didn't know how to we didn't know how to actually build teleportations.
Speaker 2:There was so many fascinating Good to see app social mobile local apps at that time. It was a big it was a big trend and there were a whole bunch of different ideas that were experimented with. Was such a fascinating time.
Speaker 1:Well, and it's yeah. Interestingly enough, like, Instagram has, like, delivered effectively that functionality now or Snapchat where you can Yeah. Teleport and see Yep. How what's the vibe at this restaurant right now?
Speaker 2:And if you click on the location that you tagged, I can see who else put pictures there if they're public. So Yeah. Yeah, those features, you were clearly very early.
Speaker 9:Yeah. I think Snap Map actually was, like, probably one of the best manifestations of that early on. The R Stories feature really brought that use case to life. For Periscope's journey, you know, we we when we build that prototype, we realized it's it just wasn't really interesting, and b, you have this, like, liquidity problem if you're just dropping pins randomly in the world. And c, it didn't really feel like teleportation because the static photos by definition old by the time you see it.
Speaker 9:Yeah. So that's that's when we were like, let's flip this and make it press a button go live. And and rather than not using static photos, let's try making it live video. And so that was one key thing that we did. And then the second key thing that we did that really made Periscope click was the the floating hearts.
Speaker 9:I don't know if you guys remember, but, Yeah. It was the first social network we had seen where you could have an infinite form of expression. It wasn't just, like, pressing a button to like it. It was sort of an infinite infinite amount of love. Yeah.
Speaker 9:And, you know, we had this beta of 20 users. It was just, our friends, basically, and some, you know, family and investors. And when we when we ship that version of the of the build that has live video with the floating hearts, it just it just was so clear to us that there was something here. And one of the early beta users happened to work at corp dev at Twitter. She invited Jack and Dick, who was the CEO at the time, and that sort of, like, put us on the radar with Twitter.
Speaker 9:And so we actually ended up getting acquired before we launched the product. Like, there was no go to market motion Thanks, that got us. And it was just, a beta of 30 people, and Twitter was, like, the thirty first user.
Speaker 2:Yeah. That team was crazy about the early acquisitions. I mean, Vine had launched, but they acquired Vine as well. They were, like, very aggressive about picking stuff up early.
Speaker 9:Top tier picking companies. Yep. Not top tier at landing the plane on the integration. That's my TLDR.
Speaker 2:Someone called it a clown car, but we're not gonna get into that.
Speaker 9:Someone you met with yesterday
Speaker 2:called it
Speaker 9:a clown car that fell into a gold mine.
Speaker 2:Gold mine, which is a great a great quote. Anyway Yeah. I wanna know, like, what do you think about livestream monetization? Like, we've we we we have we have ads running on a ticker. We've we've we've we've brought through a bunch of, like, the TV era aesthetics, but then we also do just host red ads.
Speaker 2:We don't really, that I'm aware of, get a big share of, like, programmatic ads. We don't do I know Twitch, you can do, like, I'm going to an ad break, and it will play programmatic ads. We haven't done that. We've heard a ton of stories about TikTok shop and the live streaming sales stuff. We've joked that we wanna be like that for enterprise SaaS.
Speaker 1:Live commerce for macros. I got one license. I got
Speaker 2:one license. You got one license. Here. Pick it up.
Speaker 1:Go right here. I got five seats left. Five seats left.
Speaker 2:Buy now. I got 25 credits over here. I got an SDR on one. Bye.
Speaker 9:I I think you guys are an interesting place where you can you can sort of benefit from all of these models. Right? You can do the pre roll. You can do the mid roll. You've got obviously incredible brand placements from some of the best tech companies in the world.
Speaker 9:And then I think also you have a unique vibe going where you can benefit from a lot of the monetization techniques that, like, have been become popularized on, you know, Twitch and TikTok and, you know, even Periscope early on. We had this thing called Super Hearts, which was, like, people could pay for it in app purchases to, you know, fly Ferraris off the screen on the screen or whatever. And, like, I think you have enough super fans that watch this show that there's like an end user monetization component on you know, in addition to what you're able to do with the big brands. I don't think there's many types of content that can benefit from all of those Yeah. Forms of monetization.
Speaker 1:Did you did you feel like you were at at at what point like, now it feels like Periscope was like extremely early. Even though even though, like, I think people anticipated live streaming would be big. But I feel like only in the last few years, people, at least the tech world, has, like, woken up to how big live streaming is even outside more more so outside of tech. Right?
Speaker 2:And on mobile too. I mean, that that that was one of the unique insights. Like, there there there were there was a there was a host of companies that were really focused on solving, like I mean, Flickr existed, and then Instagram, that was huge. And then there were a whole bunch of video apps. Vine, one of them.
Speaker 2:Like, YouTube existed, but no one had cracked it on mobile. And it required actual deep insight into the user experience and also the engineering to understand how to get it to work on a phone, which wasn't as powerful as a laptop back then. But yeah.
Speaker 9:Yeah. I mean, I think there's a lot of tech there were a lot of technological problems to making mobile based live streaming work well at the time. A lot of those problems are just solved now and and and somewhat commoditized. I mean, there's just, like, SDKs that let you do this really easily. I think my my big takeaway and, you know, call me somewhat jaded on this, but I I I think what we learned the hard way is that a live focused social network on mobile that's, like, short form live video, isn't tenable.
Speaker 9:Right? And that's what Periscope was. It was live only. As distinct from, like, Instagram or Facebook live at the time that was live was a feature amongst the social network that let you communicate and keep in touch with people asynchronously. And I think it took us longer to build async forms of connection than it did take Instagram and Facebook building all of our features into their existing platforms.
Speaker 9:And so that was our sort of, like, hard lesson learned. Because, you know, we had a parallel track where we were trying to make Periscope integrate into Twitter. Was the whole thesis of the integration, and it just took us way too long for for reasons that we can get into if you're interested to to make that integration come to life. And so as much as we, you know, we grew from zero to a 100,000,000 users in, a year and a half is insane, but just everyone else built all the feature
Speaker 2:Yeah.
Speaker 9:Everyone else built all the features, you know, quickly.
Speaker 2:Yeah. What what what do you think about the lack of sorry. Last question on Periscope. I I just
Speaker 1:I wanna talk about macros.
Speaker 2:Periscope. I know. But lack of screen sharing API on mobile, I felt like during the clubhouse era, that was something that was sort of missing was, like, you go to Twitch. Yes. You're watching someone livestream, but a lot of the work is done by the video game that they're playing or the video that they're reacting to.
Speaker 2:And being able to put something else on the screen so that someone doesn't need to just stand there and do an eight hour stand up routine with no support for eight hours straight, that helps. And I felt like Apple kinda nerfed that or never really and maybe it was just a hardware thing. But, what was your take on, like like, how important that was? Am I misunderstanding that? And and, like, how how how would it played out if it was easy to screen share?
Speaker 9:I don't know the state of the current APIs, but I know at the time, and this is probably, like, 2018, I wanna say. Yeah. We did a lot. We we actually built a bunch of integrations that let you share your screen including from mobile. I think that just the reality is it's such an edge case
Speaker 1:Sure.
Speaker 9:Relative to what peep like, the the vast majority of the use case for our product was people just was people talking to people. Right? It was like Yeah. Yeah. Yeah.
Speaker 9:98% was that type of broadcasting Yeah. And 2% was what you guys are doing, which is like professional broadcast,
Speaker 4:whether
Speaker 9:it's from the NFL or TVPN or anything in between. And so I I just I don't think that would have had a material impact
Speaker 2:for
Speaker 9:us as a use case.
Speaker 2:Good to know.
Speaker 9:But I don't know if the if if Apple if Apple didn't even nerf those APIs. That's Yeah. That's news to me.
Speaker 2:Yeah. I talked to a YC company once that was trying to do mobile Twitch, so you would screen share from the phone. Now people do that with, like, you take the video feed out of USB C. You write it through a PC. There are huge mobile gaming Twitch streamers, but they basically, like, are screen recording with a third party device.
Speaker 2:It's very complicated. It's not something they can do on the go. Anyway, sorry. I wanna move on. Jordy, what do you got?
Speaker 1:I I I I wanna continue that conversation
Speaker 2:It's fascinating.
Speaker 1:Limited time. Let let's, yeah, let's switch gears to MacroScope. What give give us the I don't know. Give us a hybrid investor slash customer pitch. Yeah.
Speaker 1:I want kind of a bit of both, kind of long term vision as well as, like, why somebody should sign up today.
Speaker 9:Yeah. Totally. So I'll start with the, like, the sort of customer focused angle because it's it's I think what resonates the most with me. You know, we think of Macroscope as x-ray vision for your company. You know, we help you understand what's happening.
Speaker 9:How is the product changing? How's the code base evolving? What's everyone working on? But just answered automatically, and answered via the source of truth, which is the code base. If for any company that builds software, the source of truth is the code base.
Speaker 9:If it's not in the code base, hasn't happened yet. And if it's in the code base, we you know, AI and state of the art LMs can do a really good job of articulating how things work, who did it, when it happened. And sort of our observation having worked in many companies, both small start ups that we've started and, you know, very large companies like Twitter is it's actually extremely hard to answer these basic questions. Like, the classic, what did you get done this week, which is ironically very relevant to Twitter's history
Speaker 1:Yeah.
Speaker 9:Is something that every leader thinks about constantly. Like, so much of my job as a head of product at Twitter was literally just understanding what the fuck people were working on. Yeah. And usually, it's like the state of the art solution to this problem is meetings, issue management systems, spreadsheet trackers, just bugging engineers and asking them, and sort of multiply that out by an organization that's hundreds, if not thousands of engineers. There's a lot of human capital waste that goes into this problem.
Speaker 9:And so our thesis is that this is silly. Like, in a world of LLMs, you know, there's a lot of amazing AI tools tools built for engineers, not a lot of great AI tools built for leaders. And so that's what MacroScope is trying to do. It's trying to be an be an an understanding engine for your company that simultaneously gives leaders clarity while saving time for engineers. Right?
Speaker 9:It's sort of this interesting hybrid where we're solving problems that are paper cuts that engineers, you know, feel 50 times a day, whether it's automating their PR descriptions, doing AI code review, avoiding them having to go to status updates or write status updates, which, like, there's nothing the engineer hate more than, you know, getting distracted from building something and instead reporting status through some game of telephone. And so we are simultaneously helping the leadership team get automated visibility while saving engineers a bunch of time. And we think that, like I mean, we're obviously biased, but, like, there's just no way every company in in five years, like, every company is gonna have a tool like this, whether it's Macroscope or some other tool. It is just complete insanity to imagine that we are doing this the old fashioned way.
Speaker 1:So so when when did you actually start the company? Because you announced around yesterday with Lightspeed, our friend Michael, but imagine and you've been at it for a while.
Speaker 9:Yeah. We started the company in July 2023. We raised a seed round from our mutual friends at Thrive Capital and Adverb and GV and some amazing angels. Nice. And then and then, yeah,
Speaker 1:So we just but but to go back at that point in time, at that point, the the the the AGI pilled folks were saying AGI by 2025, SaaS is not gonna matter, Fast takeoff. So did you always did you never lose faith in enterprise SaaS? Feels feels like you had you had conviction that this type of thing was gonna be important for a long time.
Speaker 9:I I think there's a lot of dramatization that goes into, like, the shifting of the, you know, landscape and and they make for great great headlines and all that. I I actually think that as every engineer gets turbocharged by AI and as, like, coding agents completely revolutionize how software gets written, I think this problem, the problem that Macroscope is solving, only becomes more important. Right? Like, if if we if companies are writing 10 x more code and humans are writing less of it and humans are reviewing less of it, then it becomes even more challenging to understand what's happening. And ultimately, like, humans are still accountable for the outputs of what a company is shipping and building.
Speaker 9:And so I think having this AI air traffic control system and understanding engine for what's happening in your company becomes even more imperative.
Speaker 1:So I think So the company's built Yeah. Like assuming that agents will get better and better and better and that humans will just stay at this, like, more and more at this global level of just kind of witnessing, okay. What are what are all my what are what's my whole team doing? What what what's this player doing? It doesn't really matter if they're a person or or an agent.
Speaker 9:Yeah. Today, it's like 95% of the use cases are what are my humans building assisted with AI. And in tomorrow, five years from now, it might be you know, 90% of it might be what are what have all my agents produced? And maybe 10% of that is, like, what have humans produced. But I think the the problem that's being solved is still fundamentally the same, which is what changed, what impact did it have, and, you know, and where do we go from here?
Speaker 9:Like, that's that's a never ending thing that is the highest leverage thing a leader, whether an engineering leader or a product leader or a CEO, like, those questions are always on your mind.
Speaker 2:How do you think about the level of integration to the systems that you wanna pull data for? Like, I could imagine, like, a a Slack bot that talks to every it effectively acts as a middle manager, literally asking people, what did you do this week? And then they write their little status update, and that gets rolled up. And then that can be queried. I could also imagine something like, you know, a screen recorder super integrated into everything the employee is doing, and you can query, did my employee do send this email?
Speaker 2:You have full transparency and then a wide swath of trade offs in between for the level of abstraction and integration you want into the systems.
Speaker 9:Yeah. I well, like, the first thing I'll say is, like, we're not we're not big fans of the there's a surveillance
Speaker 2:state Panopticon.
Speaker 9:Yeah. We're not fans of that angle, and, like, the last thing we wanna build is a is a spy tool. So we don't we don't imagine, you know, doing stream reporting or anything like that. Yeah. But I do think having sort of extensive integrations with the the stack that a company uses to build and manage their product is really important.
Speaker 9:Like, today, we started with a few systems. We integrate with GitHub. GitHub. We integrate with your issue management system. So whether you use Jira or linear, we integrate with Slack.
Speaker 2:Yep.
Speaker 9:And we think that those are the critical starting points, but it's just the beginning. Because, you know, the code base can tell you what you did and how it works. Like, how does our billing system work?
Speaker 2:Yep.
Speaker 9:The code base can answer that question. It can't tell you why you did something. Like, what customer problem we where we solving with this feature is not in the code base. But it's probably in a Google Doc or a Notion. It might be in a in a linear ticket.
Speaker 9:Yep. Likewise, like, who can see this feature is not necessarily in the code base. Right? You might have a LaunchDarkly flag or a static flag that tells you, oh, this is available to 1% of users in Japan. But, like, the the code base can be the glue that then stitches into all these other systems, and we're building Macroscope in a way that allows it to be a conversational interface to all those questions and answers.
Speaker 9:Like, today, have a Slack bot that lets you ask a question like the one I asked. Like Yeah. Have we launched this feature? If so, who can see it? And we imagine over time building all these other integrations that let you essentially get more insight into what's happening and how things work.
Speaker 1:How do you how are you kind of setting goals with the team and forecasting? With Periscope, you built like a viral consumer app. And so and and today, even in developer tools, like, there's this intense like, you know, a lot of companies are growing ridiculously fast, pretty unprecedented for for b to b products. And so there's this intense pressure to like, you know, show massive traction and adoption quickly. But Macroscope feels like a pretty complicated product that you're still gonna need to be like iterating around and and figuring out where different types of companies are getting value.
Speaker 1:So how do how do you how do you kind of like set set goals with the team and and what does success look like over the next twelve months?
Speaker 9:Yeah. I mean, it's a good question. It's obviously early days for us. If you really sort of simplify our product down in two components right now, there's really two pieces. We have a code review feature, which is, relatively speaking, it's a it's a more mature space.
Speaker 9:Right? Like, we are not the first code review tool, but code review is an enormously important problem for for companies to solve. And I think that the sort of, like, heuristics around whether our product is working well for them are are are much easier to quantify. Right? Like, we we released a benchmark, as part of our launch yesterday, which sort of is one indicator of what we use to evaluate whether our code to retool is working.
Speaker 9:Like, how what percentage of bugs can we detect, in a customer's pull request. And so, like, we think about goals very differently for a product area like that where we can measure ourselves very in a very quantifiable way relative to competitors. Yeah. Then we do the other part of our product, which we sort of refer to as status. Like, we help you understand the status of anything happening in your product development process.
Speaker 9:That's way more greenfield. Right? Like, it's we're not aware of really any other products, like technological solutions to that problem. And so both our road map and how we think about goals for for that part of the business is a little bit more greenfield. Yeah.
Speaker 9:We're just sort of excited to push the envelope on where this goes and how we can solve bigger and bigger problems for customers.
Speaker 2:Talk to me about where the budget is coming to buy Macroscope. It feels like with even zooming out broader to just the AI enabled SaaS market, there's there's a lot of products that don't neatly fit in with, okay. I'm gonna rip out this and replace. It's a lot of adding something on top. We're seeing a lot of, like, the SaaS pocalypse, the seat based models going away, but it feels like it would be hard to quantify this with, like, value based pricing.
Speaker 2:Like, how are you thinking about justifying a budget internally if you're dealing with a larger customer who's trying to kind of underwrite the value that Macroscope brings relative to the cost?
Speaker 9:Yeah. Well, so our, you know, our buyer is I would say half the time, it's the engineering leader. So this would be like a CTO or a head of engineering, and the other half of the time, it's the CEO.
Speaker 2:Yep.
Speaker 9:And, you know, I think I think from a from a value standpoint, like, you're an engineering leader, you'd want your team spending as little time reviewing code, and and as little time dealing with production issues as a result of shipping bugs into production as possible. And so, like, the the value of even catching one production incident from an AI code review tool, I think, is intuitively very easy to understand. Like, we don't we don't see customers asking the question of, is a code review tool valuable? What they wanna know is, like, why is this tool better than all the competition? So I think, you know, and that's just gonna become that's gonna be more and more true over time just given what's happening in the AI coding landscape.
Speaker 9:I think for the other aspect of our product, which is the sort of understanding layer, it is you know, relatively speaking, it's it's it's green it's greenfield. Right? There there is no product solution that are ripping out with ours. And so what we've seen resonate with with our customers is you can you'd have an intuitive feel for how much time your team is spending in meetings and dealing with all the bullshit work around the work. And so I think the the the value proposition really is, do I do I buy that this tool is gonna help my team focus more on building and less on doing that work around the work?
Speaker 9:And is that is that worth the the the, you know, the per the price of entry, which from our standpoint, like, again, the the the questions that our customers are asking are is not like, is this valuable? The question is, does it work the way you say it does? Yeah. And but but, obviously, that's where we have to do our job well. But I think anyone who's worked at a big company and you know, invested in solving this problem the old fashioned way knows that it's like the worst part of working at big companies, and they would gladly pay any amount of money to solve the problem if it actually works.
Speaker 2:Yeah. How do you think about generative UI? Or actually, like, I could imagine some people want a text result of they want to chat and ask, well, you know, how how are things going? Someone in the chat said, this is more of a progress bar. And I could imagine someone wants to see a dashboard, a progress bar, stats.
Speaker 2:Like, do do you think in the future you'll be able to, like, instantiate exactly what the particular manager wants to see kind of like a a dashboard of of what's going on in the organization?
Speaker 9:I think there's there's lots of interesting vectors here. One is just oftentimes we're describing in in words how a product is changing, and there's nothing more powerful than just showing how the product is changing. Right? So whether that's, like, integrating with Figma and showing you the intended mock up that just got shipped or whether it's actually running the code. Like, lot of time like, think about what an engineer does when they ship a feature.
Speaker 9:They ship the feature, they go into Slack, and they literally record their local branch and, like, a mock up of the product, and they post it in Slack and say, hey. I just shipped this thing. It merged into staging. We should just automate that. Right?
Speaker 9:We should literally automatically run the product and show you the thing that just got shipped and save the engineer the time from having to do all that. So it's like one angle that this can take. And the other is sort of what you what you were saying, which is kind of like in the appropriate time generating dashboards or some other visual manifestation of some status update. I think all of these things are are possible. We have to sort of pick our punches in terms of where we start.
Speaker 9:But but, yeah, humble beginnings.
Speaker 2:Well, thanks so much for coming on the show. Was great catching
Speaker 1:up with you. Back on again anytime.
Speaker 2:Yeah. I I love I love Silicon Valley lore, and I I'm very excited about what you're building. Congratulations.
Speaker 9:Thanks for having me, guys.
Speaker 2:We'll talk to you soon. See you. Public.com, investing for those to take you seriously. I already told you about public. So I'm gonna tell you about ad.com.
Speaker 2:Out of home advertising made easy and measurable. Timed the double call
Speaker 1:button perfectly.
Speaker 2:You did. Say goodbye to the headaches of out of home advertising. Only ad quick combines technology, out of home expertise, and data to enable efficient seamless ad buying across the globe. We have our next guest in the Restream waiting room, Makund from Emergent AI. How are doing?
Speaker 11:Hey. I'm doing good. How are you guys?
Speaker 2:Welcome to the show. How are doing?
Speaker 1:What's happening?
Speaker 11:Super excited to be here.
Speaker 2:What's going on today?
Speaker 11:We actually launched our product three months back, and one of our goals was to be on KPPM. No way. Yes. I love the
Speaker 2:Thanks so much. Break it down for us. What are you building?
Speaker 11:Yeah. So I'm, Mukun, at Emergent, we are building world's most advanced white coding platform for consumers. For nontechnical users, they can come in, prompt an idea, and get a fully built live app that they can take to production. And we launched few months back. Over a million users have tried the platform.
Speaker 11:More than a million and a half apps have been built so far. We're growing pretty crazily right now.
Speaker 2:How do you think about sub like like beachhead markets and frac like like, submarkets? There are platforms that focus on get an iOS app in TestFlight, build a game, vibe code, a a website. Like, are are the people that are signing up saying, I'm gonna start a business. I'm gonna build an app that will be the foundation of, like, you know, some monetary thing, or there is it you know, are we in the era of, like, vibe coding apps as memes somewhere in between? Are you still exploring?
Speaker 2:What do you think?
Speaker 11:Yeah. So, I mean, we we are the only platform that supports web app, mobile app, and back end all integrated in one. And we have consumers coming from all all parts of life. We have business owners trying to digitize their business. We have entrepreneurs building their start up on on emergent right now.
Speaker 11:A lot of people are building apps that are monetize monetizable right now, and they are shipping them. And so so it's like it's a crazy spectrum of ideas on the platform right now.
Speaker 2:It's amazing. A million users is a lot. Like, what's the what's the acquisition funnel? Like, how do you actually get people? It's it's a it's a biz it's a buzzy space.
Speaker 2:It's a cool tech, but I imagine it's hard to get people to go to your specific website. Like, what's working?
Speaker 11:Yeah. So I think people really really love our product. I think that's what's sort of working really well for us. Lot of the acquisition is word-of-mouth today for us. The people are referring each other on the platform.
Speaker 11:As they get successful app, they refer each other. We also do bunch of influencer marketing. So we use TikTok, Instagram, x to promote our our brand. And we partner with influencers, and they're able to sort of create stories which resonates with their audience. That's something that is working really well for us
Speaker 2:as well. That seems to be working really well these days. I feel like there's this interesting flywheel where maybe for the first time we're seeing influencers drive drive software adoption, software downloads. I mean, we've all seen, like, VPN ads, but we're in a new age where people are are pushing like
Speaker 1:VOD. What is what how what what's good retention in your view? Because obviously, a bunch of people are gonna come in, create stuff, and then but, you know, twelve months from now, how many of these people what what does success look like in terms of recruiting?
Speaker 2:Now I'm a I'm a real business. You can hire
Speaker 1:a detective. I think I think the beauty of these things is somebody can come in in twenty, thirty minutes Yep. An hour. They can create something very cool.
Speaker 2:Yep.
Speaker 1:You don't need to retain all of them. You don't even need to retain the majority of them. But how how are you thinking and kind of planning around that?
Speaker 11:Yeah. So we we have good retention on the platform. With month three, like, roughly 50% of the users are still on the platform. We have a very strong power user behavior where top 10% of the users are spending a lot more money on the platform who are building serious apps. They are taking them to production.
Speaker 11:And there, our retention is north of, like, 80% right now. So so we think it's still early days, but I think what's gonna happen is, like, a lot of people are gonna come on the platform. Lot of because we also take care of deployment. We host these apps on our platform. They're gonna stay with us on on the platform.
Speaker 11:And what's also happening is as they build more, they they want to add more feature. As they get more feedback from their users, they come back to build more on the platform. Still sort of early sort of days, but but we think that, you know, like, you can build a a pretty large business around these power users who are trying to launch their app, launch a new business, or a new idea to the world.
Speaker 2:What do you think for business model? Consumption based? Do you want to get people to spin up an app, subscribe, and then you're acting as their hosting provider long term? A lot of people build websites, then they're happy with them, and they don't actually have a lot of feature requests. We've seen Squarespace and a bunch of other companies.
Speaker 2:They're templated based, but they wind up being great businesses because people are happy to continue managing on WordPress or Squarespace. What business model makes sense in the in the vibe coding AI era?
Speaker 11:Yeah. So for us, like, almost most of our apps are actually, like, full stack web apps, which has back end databases Yeah. On some mobile apps. So what we are seeing, you know, is is a lot of users coming and adding adding features to them and building them. I think in a steady state, like, a lot of these users you you'll have a power law where, like, you know, top top x percent of users are gonna deploy big apps, have breakout success on the platform, and those are gonna be continuing to be on the platform, and and the business is gonna get built around those people.
Speaker 1:Do you expect enterprise vibe coding or consumer prosumer vibe coding to be more competitive in the long run? And do you think that companies should try to do both or pick a lane?
Speaker 11:I mean, we are very focused on consumer. We think these are two separate markets, require separate separate sort of for example, like, lot of our users, they call GitHub, GitHub. Right? So we have to, like, really, you know, like, think think through, like, we are catering to. We have a lot of education baked into the product, which tells them what what is API, like, you know, how to sort of, you know, look through errors and things like that.
Speaker 11:So I think these are two different sort of swim lanes. And, of course, there's a intersection in the middle where, like, small teams use us as well. But but largely, like like, we are very focused on consumer market right now.
Speaker 2:Very cool.
Speaker 1:That's refreshing to hear because we've had a number of of other platforms on the on the platform. And they always say, oh, yeah. We're we're doing consumer, but we're really, like, you know, a lot of you know, basically, not not really admitting that they're two separate markets
Speaker 2:Yeah.
Speaker 1:My feeling.
Speaker 2:Yeah. There's a lot of growth masking, like, a lack of actually understanding what the product will be when it's mature. What the long term market looks like. Exactly.
Speaker 11:Yeah. Mean, when we started, we we we thought, like I mean, a relation that we had that, like, a billion people have ideas in their head, like, around how do we sort of bring that out, how do we sort of help them launch. And we think it's gonna sort of new sort of economy, and we just want to, you know, be part of that.
Speaker 2:Well, congratulations. Thanks for
Speaker 1:Great to
Speaker 2:have you on. Coming on the show. We'll talk to you soon.
Speaker 1:Keep us posted on the progress.
Speaker 2:Have a good rest of your day. Cheers. Vittorio has a post here. It's happening. For the first time in history, AI designed a complete genome, and it has been proven functional in the lab.
Speaker 2:Many of the most My Samuel King. Yes. This is gonna get a lot of people going. Many of the most complex and useful functions in biology emerge at the scale of whole genomes. Today, Samuel King is presenting the preprint generative design of novel bacteriophages with genome language models where they valid validate the first functional AI generated genome.
Speaker 2:Fascinating.
Speaker 1:In other news, Dylan Field
Speaker 2:Yes.
Speaker 1:Shared a leaderboard of ranking a bunch of different vibe coding tools. Figma Make came in second place, number one in our hearts Yes. But also featuring Lovable at three, Bolt at five, base 44 at eight, and v zero, and Replit, of course. So
Speaker 2:This is so interesting. I didn't know that you could that you could do, like, rankings here, but I guess they they did blinded pairwise matches. So I guess they're human judged as an as an eval. They they sent them out to the last prompts or something like that? Yeah.
Speaker 2:And it's like how much do you yeah. So so various prompts and then and then show two two results to This
Speaker 7:is just like how LM Arena works.
Speaker 2:It's LM Arena for for vibe coded websites.
Speaker 5:Yeah.
Speaker 2:Very cool. Well, congrats to Dylan Field, over at Figma. Rune has a great post here, talking about the the anthropic mea culpa. Sholto posted, we're sorry and we'll do better. We're working hard on making sure we never miss these kinds of regressions and building trust with you.
Speaker 2:And, Rune says, Shoto has a Japanese sense of honor to his customers. I love it.
Speaker 1:Love it. Such a fun Yeah. The comment the comments
Speaker 2:Yeah. You were saying that people were really, really upset about Anthropic. And and it's interesting because Yeah.
Speaker 1:Was hard to suss out. Was it, like, extreme power users or was the average user actually mad?
Speaker 2:What was yours your take, Tyler?
Speaker 7:I think it was definitely, like, power users, like API
Speaker 2:So if you, like, kind of built a business on top of Anthropic and then there's regression, you have downtime. Unreliable. Got it.
Speaker 7:Sometimes it's, like, really slow. Sometimes responses are just, like
Speaker 2:Yeah. They don't work. And they not say that this was like they ran out of GPU capacity, something like that. Right? This is this was more in like they shipped a new version, and it resulted in downtime.
Speaker 2:Right? So it was it was very much, like, not on the not on the CapEx side of the business. It was more on the actual, like, development that they did.
Speaker 7:Yeah. I think so. I mean, they made it they made it very clear, like, we do not we will not degrade
Speaker 2:Yeah.
Speaker 7:Performance of the model just to serve more people. So I think there might have been some aspect of there being, like, not like, just not enough GPUs.
Speaker 2:Yeah. I mean, it's certainly been like, demand's been skyrocketing. Brown paper bag in the chat says Claude code subs are mad.
Speaker 1:Big mad.
Speaker 2:Big, big mad. Well, you know what's not down? Wander. Find your happy place. Book a wander with inspiring views, hotel grade amenities, dream beds, top tier cleaning, and twenty four seven concert.
Speaker 2:So this is a vacation home but better. Also, in other news, LimeWire has acquired the Fyre Festival brand for two hundred and forty five thousand dollars, and liquidity said my phone got a virus from reading this tweet. That is I I have no idea what's going on here. We need to do a deep dive on LimeWire. We need to get the red string out and figure out if we're, like, what is LimeWire still doing?
Speaker 2:What is their business? Why are they acquiring the Fyre Festival brand? What are they gonna do with that? I feel like there's something to be done with the Fyre Festival brand. Like, Fyre Festival is a big enough brand.
Speaker 2:There's been a documentary at this point. People know it. But, like, if you were able to buy the brand for 245 k, you could potentially do a marketing stunt with it that would generate half a million dollars in value, maybe. But it does seem like it's gotta be really, really inspired because Fire Festival. The tech conference.
Speaker 2:The brand is pretty bad. Like, the brand is associated
Speaker 1:with Yeah. It's one of those things that if you're gonna put all the effort into getting to creating a a real world event that's not embarrassing. Yeah. Why not just kind of create a new brand that
Speaker 2:Totally.
Speaker 1:It's not toxic.
Speaker 2:I mean, you could
Speaker 1:It's attention getting. Yeah. But, yeah, the I mean, this had this had been on the market for a while. It was
Speaker 2:like Wait. The
Speaker 1:brand? Fyre Festival. Oh, I had no idea. It was on the it was on the market. Billy McFarland.
Speaker 2:Did you did you go to Fyre Festival, Tyler?
Speaker 7:I did not. No? But I I think the main like, whenever I see stuff like this
Speaker 1:He was too poor, and then he was too rich.
Speaker 7:But I I think you could see some kind of, like, Enron thing where it's like
Speaker 6:Yep.
Speaker 7:It's a marketing thing, and then it's
Speaker 1:A coin. Crypto.
Speaker 6:Yep. Yeah.
Speaker 2:Oh, be careful out there. Watch out for Fyre Festival coin. How is Enron doing?
Speaker 1:The The meme coin?
Speaker 2:Yeah. The meme it was meme coin. It was a publicity stunt. Taylor Lorenz did some crossover video production with them. The team behind it seemed like genuinely great, like, comedian videographers.
Speaker 2:But then it it it took a really odd turn as as things always do when they turn into into meme coins. And it it was a funny bit for a little bit. It was it was a funny idea, you know, leaning into to Enron. Certainly fertile ground for jokes. Everyone's familiar with with Enron.
Speaker 2:I I saw people having like like, buying old Enron merch, like, years before this, like, brand revitalization. You could see them doing something funny with Fyre Festival. Or you or you could honestly see the value of that brand just being, like, producing more content about the failure of Fyre Festival, like, instantiating that. Like, there's been a documentary, but maybe you buy the brand, you get the rights to do more with it. And so you can you you you can monetize that way and not and and actually lean into the fact that it's a it it has a it has a lot of baggage.
Speaker 2:It's like a negative. It's a negative association.
Speaker 1:Yeah. You you would have hoped they could have done something more with this this iconic brand.
Speaker 2:Yeah. Did you see this comparison of the thickness of recent iPhone cameras next to each other? We are really in the bulky iPhone era. The iPhone five completely flat, no bump. The iPhone six gets
Speaker 1:Spoking season.
Speaker 2:The iPhone six, they called they they they said it was a camera bump or something, and we didn't know what we were in store for. This is a well, now it's called the plateau. That's the official
Speaker 1:term. The plateau.
Speaker 2:I I don't think Applecoms wants you to call it a bump.
Speaker 1:I just ordered I just You ordered it. I just ordered What color? Bro, I I just got the silver.
Speaker 2:You got the silver.
Speaker 1:I think I think the the orange If it was
Speaker 2:in ramp yellow, it would have been done deal. Done deal. Deal. Orange is a lot.
Speaker 1:Yeah. I kind of liked the orange less and less as time went on. Yeah. Unfortunately, I ordered it late. Now I have to wait till, like, mid October.
Speaker 2:Oh, they're they're selling out. That so that's bullish for Apple.
Speaker 1:Bull. I think so. Like we like it for the stock.
Speaker 2:Yeah. I mean, that seems good. What about you, Tyler? You you itching for one? Are you satisfied?
Speaker 2:He just got
Speaker 1:a new yeah. I just a new phone.
Speaker 2:So you're happy?
Speaker 7:Yeah. I mean, I was at I was I had an 11 before, so is a
Speaker 2:Oh, yeah. You jump forward in the future, like, seven years.
Speaker 7:Yeah.
Speaker 2:That was great. 17 Pro looks pretty good. Did you see the the latest on the OpenAI brand exploration?
Speaker 1:The latest. This is from February 2023.
Speaker 2:That's a decade ago in AI terms. Yeah. I like Area. I'd never heard of this firm before, but really, really
Speaker 6:cool work.
Speaker 2:John Palmer's Yeah. Firm. Amazing.
Speaker 1:That it hit a has has a crypto company Okay. Backed by Insights and
Speaker 2:So ARIA says brand exploration for OpenAI with Sam Altman, February 2023. Two logo concepts, a circle and a monogram alongside broader exploration for ChatGPT across brand and product. And this just, like, threw me back to the nineties. Like, it's just remarkable. It feels like old Microsoft, old Apple, old Mac.
Speaker 2:I kinda get why they didn't go this direction, but, like, sort of beautifully nostalgic. And, Sam Altman commented on it. He said, fun to look back at this exploration with area on the OpenAI brand. This work partially inspired the circle that we use and love in our products. The the Serif OpenAI font just feels like a boxed piece of software.
Speaker 2:This feels like we'd throw this logo on it, sell it at Best Buy. One ChatGPT, please. I'll take version five, and I'm good for the next two years. They got a CD key in there. Lock it in.
Speaker 2:But the the OAI logo on the on the right there, on the top right, is is wild. This is Oh, yeah. It's a very loud design
Speaker 1:I think they should re release these as as like merch for
Speaker 2:the That'd be great. Yeah. Yeah. It's a it's a little like of of like yeah. It's just so retro in my opinion.
Speaker 1:You see this post from Kaz over at Opendoor
Speaker 2:Kaz. In East Cooking.
Speaker 1:This morning, we filed an eight k to say that my and Opendoor's x accounts would be used to talk with our investors. We've also parted ways with our former external PR agencies. When we want when we want to talk, you will hear from us, not paid professionals who don't share our mission.
Speaker 2:I didn't realize that you had to actually disclose that in the eight k that you're planning to post. Should be It's time to God given right. But, yeah, Kaz is on a tear. I'm excited to hear more from him and
Speaker 1:his The top comment, you're a god. He says, I'm not. There's only one god. I'm just praying very hard that he gives me the power and the perseverance so I can fulfill his will. Let's go, Kaz.
Speaker 1:Good job. Rallying retail. We have a Did you did you see this
Speaker 2:What else?
Speaker 1:This this movie coming down the line?
Speaker 2:Oh, I I I haven't seen the movie. I saw
Speaker 1:Well, hasn't it hasn't released yet.
Speaker 2:Doll said, ladies and gentlemen, we see we have what seems to be an absolute banger on our hands. The movie is called One Battle After Another. It stars Leonardo DiCaprio. It's in theaters Team Movie 26. That's what I was thinking.
Speaker 2:In IMAX.
Speaker 1:So Get the tuxes ready, boys.
Speaker 2:Task for the team, guys. Figure out when we can all go see this movie together in IMAX. Get the tickets today. And Get us
Speaker 1:Without further ado, we have our next
Speaker 2:We have our next guest Noah. In the restream waiting
Speaker 1:Got carried away. To the VPN also. Sorry to keep you waiting, Noah.
Speaker 2:Welcome to the stream, Noah.
Speaker 1:Are you doing? Lost.
Speaker 2:We got lost in the timeline. Good. Are you going to the Google event today? Break it down for us.
Speaker 5:Oh, not right now. I got busy with work.
Speaker 2:But Okay.
Speaker 5:I'll be at the dinner tonight.
Speaker 2:Fantastic. Fantastic.
Speaker 1:Too locked in.
Speaker 2:Locked in. Well, well, what what are you locked in on? What are you building?
Speaker 5:So at Softinn, we're building computer use agents.
Speaker 2:Okay.
Speaker 5:So we're training foundation models on how to use a computer like a human
Speaker 2:Yeah.
Speaker 5:To really automate any type of work.
Speaker 2:What's what's the secret sauce? How do you differentiate it? It's a it's a it's a complicated industry.
Speaker 1:You train the model and then you say, hit the keys in the right order to make me a $100,000,000. Don't make mistakes.
Speaker 2:Don't make mistakes.
Speaker 5:Yeah. Exactly. We don't allow it to make mistakes.
Speaker 2:That's the secret.
Speaker 1:There's there's big consequences.
Speaker 2:But, I mean, right now, is is the is the barrier to computer use to scale? Is it algorithms? Is it data? Like, what are the key inputs to getting good results?
Speaker 5:It's really a mix from what we've seen a lot of these things kind of combined, but a big, part of it is actually the data. There's not a lot of, like, really good data to
Speaker 2:use. Mhmm. Where do you get more data? Who are gonna call?
Speaker 5:Well, I think a lot of it can be synthetically generated. Like, we we worked on these pipelines back in April for our first model release where, like, pretty much our entire dataset was just synthetically generated.
Speaker 2:Yeah.
Speaker 5:And then I think, like, obviously, you have things like you can label your own data. You can collect it, or you can get it from products. So you need to use a combination of everything.
Speaker 2:Computer use is so broad. I mean, it can mean everything from, like, you know, ordering DoorDash to playing a video game. What's the low hanging fruit? Like, what what what is the next step that, you know, feels solvable in, like, the twelve to eighteen month time horizon?
Speaker 5:Yeah. I think the first few tasks they really need to solve are these monotonous type of tasks, which are, like, pretty easy for a human to do, like cleaning up your email inbox to, like, scheduling your calendar Sure. To finding all of your receipts in your email. Like, things that are very low level, which, like, cognitively, it's not, like, super advanced.
Speaker 2:Why do you need a why do need a computer usage in for that? I feel like email, calendar, these products have existed for decades. They have APIs. Like, they can be interacted with via JSON.
Speaker 5:Yeah. There's actually a lot of, like, software out there which, like, either has really bad APIs or things or different types of products where you need to use computers to really interact with it efficiently. Mhmm. Usually because they might just have broken APIs straight up.
Speaker 2:So do you expect in the future people will be, like, a a thing into their email on a virtual machine and then letting you hang on to the the the the cookie or the login in in some VM for, like, a long period of time? Because it feels like Apple's not gonna let an AI agent run on my app, and that's how I use email mostly.
Speaker 5:You know, I think, like, I think what we're going to see is, like, we're going to see a mix between, like, the current LLM paradigm where it's, you use things like structured outputs, you use APIs together with computer use. And, like, in the future, I think, like, you're going to like, models are going to jump between both, and they're going to do so, like, really efficiently. So it will just kinda depend on what the input is.
Speaker 2:How do you think about your place in the stack? Do you wanna partner with Google? I know you're you're you're talking to them. Is is, is the goal to build applications on top or or stay as this, like, point solution work with foundation model companies? Like, how do you see your customers developing over time?
Speaker 5:The way I view it is that, like, computer use is still very new.
Speaker 2:Yeah.
Speaker 5:So there hasn't been, like, any product that has really taken off in the space. Like, was ChatGPT operator. Yep. There was a cloud computer use, but, like, none of these have really taken off, like, immensely, like, just normal chat GPT. And I think, like, initially, it's going to just be that you provide an API to a very good computer use model, which you sell to enterprises, you sell to startups that are working on in different industries really across with different customers and different vendors.
Speaker 5:And then eventually, like, what we're looking at is, like, if this can somehow transition into a more consumer facing product as well.
Speaker 2:Well, it sounds like the dinner tonight will be a steak dinner, a sales dinner. Hopefully, you can get some customers. Thank you for stopping by.
Speaker 1:Yeah. Thanks for get
Speaker 2:back to your busy day. We'll talk to you soon.
Speaker 1:Cheers.
Speaker 2:Have a good one. Did you see the Arizona iced tea account posted? Legendary link up. Arizona founder stick as the Costco CEO. And then just inflation what?
Speaker 2:Because Arizona is always 99Ā¢, and then the Costco hot dog's always 99Ā¢. Look at these two. The founder of Arizona is still cooking too. And the Costco CEO, they're just boys.
Speaker 1:Inflation literally doesn't exist.
Speaker 2:It doesn't. It's fake.
Speaker 1:It's made up.
Speaker 2:It's in the computer.
Speaker 1:You're making that.
Speaker 2:You can just not print a sign that says the hot dog costs more. Yeah. And it will stay the same the same cost.
Speaker 1:Just hard code the pricing into the into the register.
Speaker 2:Yeah. Look at this. Costco. Don. Don and who who and and Rob.
Speaker 2:Don and Rob.
Speaker 1:Dream that.
Speaker 2:If you know them, introduce us. We wanna have them on the show.
Speaker 1:Had you ever seen this picture before? Tracy Allaway.
Speaker 2:This is iconic. I had no idea this existed.
Speaker 1:Well, financial crisis crises most iconic picture.
Speaker 2:This is a fantastically iconic
Speaker 1:picture. She, at like, like Hamming it up
Speaker 2:a little bit? I think a little bit. I mean, it's not like she
Speaker 1:lost But chart everything's looking red.
Speaker 2:If anything, you know, crises are are are pretty good when you're in the news business, but we love to see Tracy in an iconic photo. What a fantastic what a fantastic insight with the Dell computer rocking the Dell. She was in the trendy The The trendy And it's unclear what she's looking at some sort of Bloomberg terminal, but it's just all red. But I have no idea. It doesn't look like a stock chart that's red.
Speaker 2:It just looks like a lot of red cells in a spreadsheet or something. Have no idea. We'll have to ask her what she was actually looking at and and how real this was. I mean, it was a stressful time for everyone, even if you're in even if you're in media and you have more to report on as the financial crisis is unfolding. Like, I remember reading The Wall Street Journal every day during the global financial crisis trying to understand what was going on.
Speaker 2:And, like, the the there was no there was no there was no lack of news. There was tons of interesting things happening as people understood what was going on at Bear Stearns, what was going on at Lehman Brothers. Like, these are storied institutions that are collapsing. You wanna hear about what was what were the decisions made by the board members? Who was who was involved?
Speaker 2:Like, what was the plan for the bailout? What's the government's response? But it's still stressful no matter what job you're in. But what an iconic picture. What do we have next?
Speaker 2:Ryan Peterson is in Arena Mag. You gotta go subscribe to Arena Mag. Ryan's world.
Speaker 1:I saw this. I thought I was looking at the cover of GQ. Looks fantastic. At the cover.
Speaker 2:Max Meyer stepped into right Ryan's world's Flexport CEO, Ryan Peterson, on the craziest year for global trade. With trade chaos and the rush for companies to implement AI, there are few executives in higher demand than Ryan Peterson. Flexport builds technology for logistics freight forward. He's been on the show a bunch. The Flexport office is full of curios from the worlds of from the world of logistics.
Speaker 2:I love a curio. We have a lot of curios in our museum of business.
Speaker 1:We do.
Speaker 2:The hallways are decorated with posters that Ryan Peterson himself generated by ChatGPT on the Engineering Floor.
Speaker 1:We got a It's cardboard
Speaker 2:model of the Ever Given that that you remember the Ever Given story? Is that
Speaker 1:Back back to your point Yeah. On on Relics. Dylan was saying that the a friend of his, the only Zuck signature signed object that he's aware of that traded hands traded at at a 100 k.
Speaker 2:Oh, yeah.
Speaker 1:So so some there was a Zuck signature Yes. Hands for about a 100 k, which would put the the game hit Gong probably in the
Speaker 2:$8.08 figures, I'm thinking
Speaker 1:But for sure. You never sell it. Yep. Because it's going it's going in the round.
Speaker 2:We did have a plan to engrave on the Gong a contract and not show him that. When he was signing the
Speaker 1:the Gong older style.
Speaker 2:He would accidentally be signing a contract to onboard ramp. That would be the real goal. I don't think that would go over well.
Speaker 7:Nathan I don't think don't think
Speaker 2:Ramp needs to in the comedy sketches, I suppose.
Speaker 1:We'll have have much problem there. Yeah. Built Rewards built their own TV show, short form series called Roomies. They released on TikTok and Instagram. I'm gonna guess that Adam Faze did this.
Speaker 2:Oh, yeah?
Speaker 1:Because he does he does these types of
Speaker 2:things for
Speaker 1:companies. I'm gonna message him.
Speaker 2:I gotta I yeah. I gotta meet him. I'd be I key his name keeps coming up, and and I and I wanna know more.
Speaker 1:Yeah. We should have we should
Speaker 2:actually Yeah. I'd love to have him on show and meet him. But, yeah. Built Built Rewards founded by Ankur Jain. Cashback or what credit card points on paying your rent is the pitch.
Speaker 2:Yeah. But pretty pretty remarkable to actually get get a, like, a scripted series actually running. It's pretty hard to do. Most people that can do this level of
Speaker 1:All right. We'll see how quickly he gets back.
Speaker 2:Get him on the show right now. We'll see.
Speaker 1:Derek Thompson says AI is overrated. He says, my baseline case is that the AI being built right now is overrated. Soon it will be a disappointment, then it will be a bubble. And by the twenty thirties, it will be world changing. Self driving cars are a model for this.
Speaker 1:In 2015, I heard autonomy was five years away from taking over the roads. In 2020, they were nowhere. Even in 2022, you could say they were a huge disappointment. Now they're quietly a revolution. Driverless taxi usage in California grew eight x in one year, and Waymo is expanding to other cities.
Speaker 2:Truth zone, Tyler Cosgrove, what do you think?
Speaker 7:He's not just wrong. He's unpatriotic.
Speaker 2:Woah. Oh.
Speaker 1:Shots fired. Where's it? Where where are the shots fired? Amateur over here. First time first time First time.
Speaker 1:First time on the decks. Yes. You're now you're just hitting random stuff. That's that's that's that's offensive. Alright.
Speaker 1:Alright. Easy. Don't go.
Speaker 2:Well, mean, it's not that crazy. It does feel like we're in some sort of like the last 1% takes 99% of the time. You know, we got 80% of the value and but that's not enough. And so the the last 20% is gonna gonna take 10 times as long.
Speaker 7:I know. I mean, we we don't have a Dyson sphere. How are we getting 80% of the value? We're we're we're only getting, a 10,000
Speaker 2:something So so what's your timeline for a Dyson sphere? You think we're gonna have a Dyson sphere in in two years?
Speaker 7:Two is a little close.
Speaker 2:He's saying 2030. That's only five years away. I guess he said the twenty thirties.
Speaker 7:Yeah. So that's a whole
Speaker 2:What's your what what's your Dyson sphere timeline?
Speaker 7:In my lifetime?
Speaker 2:In your lifetime?
Speaker 7:I yeah. Okay. Well yeah.
Speaker 2:Oh, so so if you lose the bet, won't be around to make do? You won't be
Speaker 7:yeah. In my lifetime.
Speaker 2:In your lifetime?
Speaker 7:I think so.
Speaker 2:Yeah. I could see I could see it by 2100, potentially. But it's a lot of work. A lot of lot needs to happen to get to get the Dyson sphere up there. It's gonna be a lot of rockets going to the sun.
Speaker 1:Well, we have Dan.
Speaker 2:Let's bring in our next guest.
Speaker 1:Show from What do we do? Regular. What's going on, Frank?
Speaker 2:How are doing?
Speaker 3:It's such a pleasure to be here. I've asked Sequoia what to prepare for, and they've told me that this should be the most fun, exciting, fast paced interview. So I'm, you know, just like, shoot at me.
Speaker 2:Let's keep it quick. Introduction. What do you do?
Speaker 3:We are irregular. We just came out of stealth yesterday. We are the first Frontier AI security company out there. Our goal is to be the counterpart to the OpenAI's and Ontropic and GDMs of the world. We're already working with all of them and to create the security stack of the future.
Speaker 2:Yeah. What what what does that mean? I mean, there's already a ton of security companies out there. I see them when I run walk through the airport. They're all thinking about AI.
Speaker 2:How are you positioned differently?
Speaker 3:Yeah. It's a great question. So the the thing that we're actually building is a high fidelity simulator that allows you to put in any model in it and essentially just, like, see how different scenarios in order to attack the model or whether the model can attack other targets. So for example, we were the first in the world to see jailbreaking that AI was doing to another AI Mhmm. Or alternatively, just like seeing how AI can bypass things as Windows Defender in order to just, like, hop from one endpoint to the other.
Speaker 10:Interesting.
Speaker 3:What is unique and different about us is that we're working very closely with the labs out of the assumption that what AI is doing right now is simply not a story. And and security is about to have a huge paradigm shift moment, which if you think about it, it makes sense. Right? Because enterprises are probably going to look very different in the next five ten years. So naturally, the the security stack is also going to look very differently as well.
Speaker 3:So we are using this high fidelity simulator to find the the novel attacks and to build the next generation of defenses a few years in advance.
Speaker 2:Why do labs don't wanna do this internally? It feels like something that they have responsibility for. They have tons of I mean, get questions on Capitol Hill about this. Like, if they outsource it, that seems like a a very tricky thing.
Speaker 1:Yeah. But at that I mean, it's not it's not entirely outsourcing it. Like, they have to care about these same Sure. Same thing that, you know, every I think every every company does. It's like you wanna have your own Yeah.
Speaker 1:Security practices and protocols, but simultaneously have partners that can help you see things in a different way. But what do you think, Dan?
Speaker 3:Exactly. It's it's a great question if you think about it. You know, there is a thriving security industry already that is very mature, and, you know, most companies are using, you know, the great of the security world right now, the Palos, you know, just like the clouds, like, etcetera, even though they're external to the companies. And the reason is that we're about to encounter what is potentially the greatest security challenge ever just because we're innovating at such a fast pace, and there's so much work to do. So we kind of think about it in terms of, like, the differentiation from the inside to the outside is that there are some defenses that you would want to put on the models themselves baked into the neural nets, and that's clearly lab territory.
Speaker 3:But some defenses are going to happen on the AI agent side, and some defenses will have to be in the environment. Just because if you believe that we won't be able to do secure by design to AI, that means that some of the defenses will have to be implemented on the enterprise side in the environment. Otherwise, you won't have any defenses beyond what the frontier companies are going to bake into the models. And because of so many different verticals and scenarios and context that you need to put in, there is a lot of effort that needs to be created in order to create defenses across the entirety of the stack, and we're working side by side in order to make sure that whatever the labs are not doing, we are going to do in order to create the next powerhouse of security.
Speaker 1:What is this what does a regular look like over time? Is it is one way to think about it is like a a network to, like, detect, like, like, rogue agents. Right? Is that a is that a potential kind of scenario that that you guys would be helpful in in preventing? Or or what what is, like, the surface area of the product look like over time?
Speaker 3:Yeah. Thanks for the question. So I'll say that's indeed one of the scenarios that we are covering. Already today, we are doing things as understanding and monitoring AI network systems in order to see if they go out of bounds. But our view is that something deeper is going on here and that the entire infrastructure will need to be replaced.
Speaker 3:I'll give a concrete example around that. So, you know, just like anomaly detection, that's a huge part of the security stack right now. Right? But how does it work? You have a baseline, and you're seeing whether a model is or just like whatever you're trying to monitor is doing something which is outside of what you would expect as the normal behavior.
Speaker 3:But if you don't know how an attack is going to look like, you don't have a proper baseline. And as an outcome of that, our view is that the first order thing to do is to create a strong research infrastructure that would allow you to essentially figure out and map the novel attacks that are unique to AI, what are the gaps in the current security stack, and start to fill them in from where and just, like, build a new platform that's going to be the platform to secure the agents of the future. So our hope and our ambitions are high. We believe that there is a place to create a huge company that is new around security, very much like, you know, we started as part of the transition to the cloud. And, you know, Checkpoint started early on just like a few decades back when people started to implement and it's like networks in enterprises.
Speaker 3:And usually when infrastructure is changing, you have a just like a window of opportunity to create the company that's is going to be able to create the platform to secure that infrastructure end to end, and that's our goal, and that's what we want to do around AI.
Speaker 2:Do you think it's more are are you more worried about the, like, rogue AI, the the AI that just randomly decides independently to try and break out of its environment or more bad actors thinking that if they can get an LLM to do something inside of an OpenAI environment or inside of a Google DeepMind environment, that they can extract some sort of value? Like, who is inciting the attack?
Speaker 3:So ultimately, it's both. I think in the near term, it's the latter. So it's much more likely that we'll need some human interaction in order to elicit AI capabilities to push them into more dangerous scenarios. And I'm much more concerned right now about, you know, it's like, tell organizations getting access to advanced AI system that are already you if you look at, like, the system cards of OpenAI and Ontopic, they put the capabilities of around bio and chemicals, so models being able to just, like, actually help in order to produce them at higher risk levels over time, which makes me personally just, like, you know, concerned about what happens if some bad actors are going to have access. That's also true on the commercial side, that the more that we delegate to AI, if malicious actors are going to gain gain access, there is potentially going to be a whole new wave of viruses.
Speaker 3:And I think the near future is AI augmenting attackers and being used as part of, you know, just like the attack surface.
Speaker 2:Yeah.
Speaker 3:Over a longer horizon of time, we need to also make sure how we take care of just like rogue actions that are done by the AI itself.
Speaker 2:Sure. Well, good luck to you. Thank you so much for hopping on the show. We will
Speaker 1:come come back on. I I expect in the next at least in the, you know, the next two years, probably the next year, there's gonna be some type of event and we're gonna think we gotta call Dan to break this down. But hopefully, prevent it before it ever happens. Yeah. So
Speaker 3:It would be it would be my pleasure both to prevent it, but also to come back on the show.
Speaker 2:Thank you so much. Do it. We'll talk
Speaker 3:about some
Speaker 1:progress. Thank you. Cheers, Dan.
Speaker 2:Bye bye. Jensen Wong is a huge Nano Banana fan. Love to see that. And Sundar Pachai quote posts him and says, mine too. I it made his day.
Speaker 2:They're both very happy. Also, Joe Gebbia is is shouting out Breathe Realm.
Speaker 1:Yes. I threw this in here. Yeah. New air freshener company. The team, when we moved in the studio, bought a bunch of air fresheners.
Speaker 1:You're really said good the trash. Throw those away. They release a bunch of, you know, toxic chemicals in Yep. Air that you then breathe that then go throughout your body. Sarah Yeah.
Speaker 1:My wife actually invested in this company years ago. So it took Really? A while to get out to
Speaker 2:No way.
Speaker 1:Launch. But cool to
Speaker 2:see The new standard of air care. Go check it out. The world. Saffron Citrus and Verbena Santal.
Speaker 1:Sounds delightful. Delightful. Well, next up we have Ben from Braille coming in the studio, working on stablecoin infrastructure. And into
Speaker 2:the TV here at Ultradown. Welcome the stream, Ben. How you doing? What's happening?
Speaker 8:I'm doing good. Good to see you guys. Thanks for having me.
Speaker 1:Great to have you. Kick us off with an introduction. Good to see you again. Actually, I think the last time we spoke was probably twenty twenty two. It feels like a decade ago.
Speaker 8:Yeah. I think I might have been trying to, like, chill you on doing something with stablecoins, and
Speaker 9:we were
Speaker 8:trying to get started, to be honest. You know? Yeah. Were off. Takes a minute as as you know.
Speaker 1:Yep. Yeah. Catch us up to I mean, since it's your first time on the show, quick history on yourself, and then we'll get into Braille and everything you've been working on.
Speaker 8:Yeah. Cool. Well, hey, guys. I've been building fintech companies for, I think, longer than fintech's been a word. I worked on one for about ten, twelve years.
Speaker 8:Took a couple of years off, kinda went for a long walk in the woods, and then kinda started trying to think about what's next. And when we were workshopping ideas, it became pretty obvious that, you know, like, blockchains were going to surpass traditional databases, in terms of, like, speed and cost, which is great for financial transactions. And stablecoins were the obvious way to fill the space, but they were just super expensive to actually create. And so when we started, it was kinda like the litmus test or the baseline was, like, a $100,000,000 in two years to create one of these things. It took us two and a half years to do it, but we got it down to a dollar in a minute to where any business or anyone that wants to go launch a stablecoin can go launch it.
Speaker 8:And basically, the reason people love these things is because it reduces cost and, makes revenue.
Speaker 1:Okay. First question, why why do we need Infinity stablecoins? I'm sure you have a good answer.
Speaker 8:I mean, it's why do we need anything? It's like, there are lots of different types of t shirts in the world. Why do we need so many different types of t shirts? People like to customize things. And I think that we now live in a world where customizing your own type of money is possible.
Speaker 8:Some group of people are going to do it because it's just fun. Other people are going to do it because it's a good business decision to reduce costs. Other will do it because it's a good business decision, and they're gonna make a bunch of revenue. And so generally speaking, the reason people, I think, are gonna create more of these things once the beer comes down to actually create more is just that they're fun, they reduce costs, and they make money.
Speaker 1:What what is the actual mechanics if somebody goes to braille.xyz today and creates a stablecoin? Like, what's happening what's happening under the hood?
Speaker 8:You know, it looks and feels a lot like using, like, a traditional fintech product. It's almost like you're just depositing money. If you've ever used, PayPal, if you've ever used Venmo, if you've ever used Coinbase, if you you have a Circle Mint account, it's the same for all these tools. You just put money in. And in our case, you get a custom stablecoin back out.
Speaker 8:And then you can go use that in your business. You can exchange it with any number of other stablecoins. You can use it on, I don't know, ten, twelve different blockchains, and it's compatible with our assets, Circle access assets, Paxos assets. So it's like it just works with all the popular stablecoins.
Speaker 1:And so and then once it's created, let's say somebody creates a thousand dollars worth of a new stablecoin, how does, like, swap functionality work when you have these sort of, like, new pairs?
Speaker 8:So it's all actually built in. So when a new stablecoin gets created and deployed, it's all reverse compatible. So let's say that you go create your own stablecoin. You got a thousand bucks sitting there. You can use the APIs to swap it in between, you know, 50 other stables.
Speaker 8:Again, some even that we don't issue at really no cost, and you can swap it at the speed of basically the chain confirmations. So there's no slippage. And it's, you know, like, we we think pretty ideal in that way. And then, obviously, as these programs start to grow out into DeFi, there's a need to work with customers to set up different liquidity pools and things like that to make sure that they maintain peg, work with them on on ramps and off ramps for building into fintech apps and all that good stuff. But, you know, all solvable problems, all these things are, like, impossible to imagine five years ago, and now all the tech is sort of, like, right there off the shelf to use for people.
Speaker 1:What are the what are the key kind of customers that you're excited about working with today? Kind of what are the categories?
Speaker 8:We work a lot with blockchain, ecosystems. So we just launched, Lightspark. We're doing a lot of work right now with Canton, which is like an institutional privacy, focused blockchain, and, you know, there are, like, eight more of these in development. I think we've done another 12. And then there's there's kind of, like, a fast follow once the chains are implemented to what are the use cases on the chain.
Speaker 8:For us, a lot of that is, like, payments. People love these things because reduces costs, increase revenue. It's like a revenue source the neighborhood had had access to in a pretty stable coin world. There are embedded finance applications, which is just like building on blockchain infrastructure instead of kind of the last version of things. And then there are all these other kinds of trailing use cases, but right now, we see a ton in the blockchain ecosystems, a lot in payments, and a lot in embedded finance.
Speaker 8:Financial institutions as well, but let's be honest, those are a little bit more hypothetical, I think,
Speaker 1:at the moment.
Speaker 2:Do you have status of those, like, state based stablecoins?
Speaker 1:And you mean, like, US states?
Speaker 2:Yeah. Yeah. Wasn't it Montana that launched one? And it seemed like, well, America already has this stablecoin USD. I was kinda confused.
Speaker 1:Wyoming, I think.
Speaker 2:Wyoming, maybe?
Speaker 8:Yeah. You got it. It's it's I think it's f r n t in Wyoming. And, you know, it's even like once you can launch these things, states want to launch them themselves. Banks want to launch them themselves.
Speaker 8:Fintech companies wants to want want to launch them. And the rationale for it is always the same. Like, reduce costs, make money, you know, and maybe the fun side is customization. You know, developers like to customize. And so I I think that's why we really believe, like, there's just gonna be a number of these things, and one of the challenges is just making it interoperable between the deployments and making it easier for developers to build it into their app.
Speaker 8:And, you know, our our sort of, like, value add is we just take care of the regulation and we just take care of the tech so that you can build whatever product you wanna build on top of the new stable coin.
Speaker 1:What any any predictions on on stablecoin market caps over the next few years? I mean, there's a lot flying around from, you know, TradFi trying to just understand the opportunity to people that are, you know, more crypto native that are that are super bullish themselves. But but how are you thinking about it?
Speaker 8:Yeah. I mean, I think the number goes up, gentlemen. It's like you you guys know how big certain, like, name brand fintech apps are. As these name brand fintech apps roll out their own blockchains and their own stablecoins, the market cap of crypto generally is going to move. And so suddenly, these new, like, corporate chains, they're gonna be top 10, top 20 chains the day they're rolled out, at least in terms of, like, AUM and stablecoins deployed on that chain.
Speaker 8:And so in a world where most of the world is still off chain, it's like, imagine what happens when the repo market comes on chain. It like, you can't even compare what's possible in in terms of where we're at. At least I don't think so.
Speaker 1:Yep. That makes sense.
Speaker 2:Well, thank you so much for hopping on the show. We'll talk soon. Congratulations.
Speaker 1:On the lunch. It's It's great to see you.
Speaker 2:Have a good day.
Speaker 5:Good to see you, Ben.
Speaker 1:Talk Good
Speaker 5:to see you.
Speaker 2:Bobby Cosmic in the chat has a point that I think I agree with. All the all these different coins remind me of pre 1863 currency in The US before the National Banking Act of 1863. Banknotes were issued by thousands of different state chartered banks which often had weak oversight and issued notes that could lose value or be difficult to exchange outside their local areas. And I do wonder if there's some sort of, like, you know, network effect. I mean, it's like everyone spins up their own stablecoin, and then you need interaction between all of them.
Speaker 2:So then, like, someone's trying to take an extra cut at some point, and and and you would, and may maybe, like, it all trades through and everyone gets lower cost. But if there's one standard for, like, inter chain exchange, then they could take a then they could take a a cut. It is it is it is odd that we're in this, like, explosion of stablecoins at this point. But no one want everyone's sick of paying high transaction fees, I suppose.
Speaker 1:Yeah. I think I think the you know, my immediate thought is I can understand why every institution and company wants a stablecoin if you're a fintech company and you're moving a lot of money. I can understand that.
Speaker 2:I yeah. I mean, at the same time,
Speaker 8:it's like There's
Speaker 1:a lot of there's a lot of different types of companies where, of course, they would want a stablecoin, but are they providing value to the users? Right?
Speaker 2:Yeah. Yeah. The the the the the promise of many stablecoin projects, though, was like, hey. Use ours. It's low fees.
Speaker 2:So it's like, are are we is is that the arbitrage? Do you go even lower fees below? Because it's not 3%. Right?
Speaker 8:Yeah.
Speaker 2:So and I know that I mean, that was the original pitch for Bitcoin was like, it should cost nothing to it's electronic money. It costs nothing to And
Speaker 1:they're definitely they're definitely going lower. You know, Braille's going lower in the Right?
Speaker 2:Yeah.
Speaker 1:It's like Circle was like, here's we're gonna we're gonna issue the stablecoin, and we're gonna give you infrastructure to
Speaker 2:Yeah.
Speaker 1:To leverage them. And then this is going, you know, a layer deeper and just saying, we'll just make you the the stablecoin itself.
Speaker 2:In other breaking news, Clearly, mentioned us in their blog on going viral and, and shared some stats about TBPM posting a lot of clips, with views ranging from five k to as high as 500,000. There's a reason for this. Some of the content does not deserve to go viral. Roy Lee is stressing the idea that you cannot inherently make an undeserving tweet go viral. ViralSense gets you from one to a 100, not from zero to one.
Speaker 2:He's stressing like the importance of being able to identify viral concepts. Obviously, they put a ton of work into the content that they post. But the interesting takeaway here is what are the benefits of going viral? There are only two, top of funnel for your users two, to get your mission seen by potential hires. Importantly, virality does not equal top of funnel.
Speaker 2:Only converting content will get you downloads, and you must make sure your viral bets are converting or at least have a chance to be in the future, which is interesting with Cluelly because it's a two step act. They go they need to go viral and entertain and create something that's, like, funny or or controversial or something that everyone watches. But then they also have to get you to go to the website, download, and pay for the for the product. Sure. And and that and and
Speaker 1:that's update here. Where does Cluelly stand? Cluelly has more than enough consistent usage that we can reliably test every single one of our new features against a pool of users and know where the product is retentive and where it is not. Clearly, it's post PMF in a few areas, interviews, certain quizzes, and homework that require an undetectable AI. Students, that's enterprise clients who've spent time building out custom workflows for.
Speaker 1:But conquering any of these will not end in the grander vision. We have our eyes on the ultimate computer interface for multimodal AI.
Speaker 2:Same
Speaker 1:vision that Zach has his eyes on.
Speaker 2:Yes. With AI mode for the middle advance.
Speaker 1:On live AI. Yeah. We need faster Roy says we need faster magic moments and larger tangential consumer markets. At that end, we spent the last few months working on making sure the product works for our more general users. There's a magic moment that exists with Cluely, but does not exist for all the markets that interest us yet.
Speaker 1:The truth is it is actually quite hard to build software that feels truly magical to everyone. It takes a lot of time.
Speaker 2:That feels honest.
Speaker 1:That feels honest, and I don't think anybody would would disagree.
Speaker 2:There's an interesting stat in here. He says, in fact, some of our meme viral videos, the most views, 50,000,000 views generated almost zero downloads despite being viral. So conversion, if you're using viral marketing, conversion actually matters. There's probably a question about, you know, Built Rewards, did that big TikTok campaign. They have 88,000 followers, 1,400,000 likes on their Roomies series, and and and and the the headline numbers look really good.
Speaker 2:This could be extremely high converting. It could be extremely low converting. It it's an it's an open question as to and when you're doing viral marketing, you have to understand that the bottom of the funnel matters just as much as the actual views and top of funnel.
Speaker 1:Totally.
Speaker 2:Any other breaking news you wanna cover?
Speaker 1:I don't think so. I think everybody's relaxing after a busy day yesterday.
Speaker 2:Yes. Well, we will see you tomorrow.
Speaker 1:Can't wait to get back to Mike.
Speaker 2:Fantastic day.
Speaker 6:And
Speaker 2:We'll see you on Friday.
Speaker 1:Thank you, folks.
Speaker 2:Have a good rest of your day.
Speaker 1:Great to see all your names. We'll see you tomorrow.
Speaker 2:Goodbye.
Speaker 1:Bye.