Subscribe
Share
Share
Embed
TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TVPN. Jordy's juggling. It's Wednesday, 02/18/2026. We are live from
Speaker 2:TVPN. Back.
Speaker 1:The temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com, baby. Times money saved both. Easy use corporate cards, bill pay, accounting, a whole lot more all in one place. We have a great show for you today, folks.
Speaker 1:Specifically, Tyler Cosgrove has been on a little bit of a tear with the market maps. He dropped from market the final market map. Market map. We don't need any more market maps because Tyler made a market map that has every company on it. Let's pull up his latest market map.
Speaker 1:It looks like the
Speaker 2:There was some VC associate out there that was making a market map and was just devastated.
Speaker 1:All my all the companies I was gonna put on the market map are now on this market map, which is in the timeline, by way. And it it's very blue. And you did select Google. Can you walk us through how you built this particular market map of every company on it? It's every company that has a Wikipedia article.
Speaker 1:Correct?
Speaker 3:Correct. Yeah. So the one we're showing that that's the wrong one.
Speaker 1:That Yeah.
Speaker 3:That's for later. So basically, I over winter break, actually, I was interested in this thing where, like, okay, on Wikipedia, there's, like, all sorts of, like Wikipedia is, I think, like, a very underrated data source. And there's, like, all sorts of cool things I think you can do. Right?
Speaker 2:You mean Grokopedia. Right? Well, so Grokopedia is a
Speaker 3:little different because it's, like, generated on the fly. Right? But, basically, you know, whatever. What I ended up doing is I took every Wikipedia article. There's like seven seven and half million English ones.
Speaker 3:And I ran them through an embedding model. It was Quen three embedding four b, I think.
Speaker 1:You speak Chinese?
Speaker 3:Yeah. Woah.
Speaker 1:Woah. He's he's got it. So you
Speaker 3:you But but it was I I I got an embedding for every single article. Right? So it's like basically Mhmm. Every article has a vector. It's like 2,500.
Speaker 1:You did this a while ago. Right? The whole Wikipedia embedding or did you re embed?
Speaker 3:This was like
Speaker 1:A month ago. Month ago. Yeah. Yeah. Yeah.
Speaker 1:I remember.
Speaker 3:So then basically, I took all the articles. I found all the ones that are about companies, enterprises. Right? Which is basically, you can find some direct direction in the embedding space that's like corresponds to how much, like, company ness something has. Right?
Speaker 3:You can find all the ones that Really?
Speaker 1:Oh, you don't you don't filter by, like, Wikipedia's categorization of whether or
Speaker 3:not I use that, but that's not inclusive of every single company.
Speaker 2:Oh,
Speaker 3:interesting. So it's, like, a little bit blurry. Because some things are, like, well, is it a company? Is it not?
Speaker 1:Yeah. I noticed some, like, railroads on here that looked like maybe they're companies, but they're, like, state owned and Yeah. Where does
Speaker 3:that It's get of a blurry thing. You can't just use just what Wikipedia says. Companies. But you can basically find things that are are companies, and then you have a you have an embedding for every single one. Right?
Speaker 3:So it's this big vector, super high dimensional space. Yeah. If you map it down to two d
Speaker 1:Okay.
Speaker 3:You can have this, like, cool two d map, which is basically what I did. Yeah. So so you can see there's these big clusters. Right? So it's, like, in the top left, there's it's all these theater companies or Yeah.
Speaker 3:There's space companies.
Speaker 1:I noticed the aviation companies were pretty far away from the train companies. Is that the Yeah.
Speaker 2:I mean, it's like you knew there was kind of like Yeah.
Speaker 1:Confident rivalry. Yeah. Rivalry. They need to be you gotta keep those apart or it'll just
Speaker 2:start Yeah.
Speaker 3:Like like, when you map something down from, like, you know, there's, like, 2,000 dimensions down to two d. Yeah. It's, like, very hard to keep. Yeah. Like like, a ton of
Speaker 1:things. And it just randomly looked like The United States.
Speaker 3:Yeah. That has nothing to do with
Speaker 1:That's so
Speaker 3:crazy. That was totally random.
Speaker 1:Because I looked at it, was like, oh, okay. There's a lot of companies in Florida, a lot of companies in the Northeast, like
Speaker 3:I didn't even, like, realize. I was like, oh, it kind of looks like.
Speaker 1:And then I was like, what is this what is this enclave in Canada? Why does that is that Alaska or something? But in fact, it has nothing to do with The United States. It just happens to look like The United States.
Speaker 3:Yeah. But this so the it's like actually interactive, you can like look up a company and you can find where it is and
Speaker 1:tylercosgrove.com/wikipedia_map.html. Wow. Really a wordsmith with the with the URLs there, Tyler. Couldn't use a TLD list domain. But there are some fun ones in here.
Speaker 1:Anyway, that's a fun project. All the links take you to Wikipedia. Go check it out. And we market maps are basically done, but a lot of the NeoLabs are not on this market map. Quickly, let me tell you about Restream, one live stream, 30 plus destinations.
Speaker 1:If you wanna multistream, go to restream.com, and let's click over to Tyler's market map of the Neolabs because we've been tracking the Neolab boom. We've had a lot of these founders on the show. We we came out of the world where we were like, okay. There's DeepMind. There's Google.
Speaker 1:There's OpenAI. Now we got Anthropic. There's Thinking Machines, and there's a couple different companies. But the NeoLabs have exploded. They have a term that's been coined.
Speaker 1:Sarah Guo was actually, I think, the per first person that came on the show and sort of broke it down for us around the Christmas episode. But since then, the Neolab, like, taxonomy has evolved, and so we needed to build a market map. So, Tyler, take us through what's going on in the world of Neolabs these days.
Speaker 3:Yeah. So Neolab is kind of this interesting term. Like, it it's very broad. People say, like, Neolab. It's not very clear what they mean Mhmm.
Speaker 3:Because there's like, broadly, I I think it generally
Speaker 1:And this will make it clearer?
Speaker 3:Yes. I think after this, it'll be pretty obvious, like, what, you know, what you should be looking at,
Speaker 2:how how
Speaker 3:to think about these different companies.
Speaker 1:Yeah. I I I don't wanna be more confused at the end of this. Yeah. That would be a disaster if that happened.
Speaker 3:Yeah. So that's not gonna
Speaker 1:happen. This is gonna be easy.
Speaker 3:Okay. Got it. Yeah. Got it. Got it.
Speaker 3:Cool. Okay. So let's just start. Okay. So you have NeoLab.
Speaker 3:Right? Yes. So Neo, you have this prefix. Okay. It has to be relative to something.
Speaker 3:Yes. So Neo is relative to, like, your trad lab. This is your big lab.
Speaker 1:Traditional
Speaker 3:lab. Your yeah. This is your open AI.
Speaker 2:For the big labs.
Speaker 1:Yeah. They didn't get enough credit today. Building data centers Yeah. Spike in CapEx.
Speaker 3:So this is gonna be your open AI, your deep mind, your Anthropic. Yeah. Yeah. XAI.
Speaker 1:XAI kinda fits in there too. Even though it's a newer trad lab, it it fits in with the BigLab. You got a lot of money.
Speaker 3:Dario, I think, he was like, yeah, three, maybe four labs. Right? So the force is is probably
Speaker 1:Probably XAI. XAI.
Speaker 3:Yep. I I think you can also kind of throw in, Mistral in there.
Speaker 1:Okay. Oh, yeah. Mistral's a little bit older.
Speaker 3:Yeah. Yeah. I mean, Mistral there's bunch of these labs that were basically founded in the, like, two or three years before Chekipati and then in the, like, six months after. Yeah. So I think x a i's in there.
Speaker 3:Mistral's in there.
Speaker 1:And these specifically these I feel like those TradLabs, it's like they did a transformer based pretraining run. They have their own base pretrained. Maybe it's not at the frontier, but at least they're playing that game. They're not doing fine tuning. They're not doing something else.
Speaker 1:So that's sort of like you're in the trad lab world when you're thinking about, like, a big pre train run
Speaker 4:loosely.
Speaker 3:Yeah. I mean, especially if you're talking about these big pre trains, it's it's really just these four. No one else is really at that scale. Yep. But then okay.
Speaker 3:So Mystrel kind of brings us down into what I call the sovereign labs.
Speaker 1:Okay.
Speaker 3:So, I mean, you know, if you kinda look at this, it's basically just labs that are not in America. Mhmm. But I think also that there actually is is a meaning to this. So, like, Mistral, you've seen Mistral become kind of the the leader in in European AI. Right?
Speaker 3:So I think European. It Sweden maybe? They're bringing a new data center? Yeah. Sweden.
Speaker 3:So they're kind of becoming
Speaker 1:That's like stuff going on in France,
Speaker 3:Macron is always talking about Mistral. It's a big leader. Cohere is also kind of I think it has like a very Canadian. It's a Canadian company.
Speaker 1:But also has done their No own pre trained.
Speaker 2:Ties to the curling team, though.
Speaker 1:Male Oh, okay. Okay.
Speaker 2:Male No ties.
Speaker 3:So I
Speaker 2:don't want them
Speaker 1:Male Yeah, yeah. It's important to put some distance between that scandal.
Speaker 3:Yeah. Then can go down. Can kind of see all your Chinese open source labs. This is your Quan, DeepSea, Kimi. Unitree is also in there, right?
Speaker 3:Unitree, I think so as we'll see later, there's also I have a section for, like, robotics labs. Sure. But this is very clearly, you know, this is the Chinese.
Speaker 1:Yeah. Take us back in time now. Was going on before the Trad Labs broke out?
Speaker 3:Yeah. So here I have this section, legacy labs.
Speaker 1:Okay.
Speaker 3:So these are ones that were kind of more entrenched in these big enterprises. Yep. So you have stuff like Microsoft Research. Sure. AT and T or Bell Bell Labs.
Speaker 3:Right?
Speaker 1:Oh, Bell Labs. Yeah. I forgot about Bell Labs. Yeah. That's right.
Speaker 1:After you know what you know how you know why they call it Bell Labs?
Speaker 3:Why do they call it Bell Labs?
Speaker 1:Alexander Graham Bell. Yeah. It was founded by him.
Speaker 3:Yeah. Bell Labs. Okay. But but also, you got stuff like you you have FAIR Yeah. Facebook AI research.
Speaker 2:Mhmm.
Speaker 3:This was like I mean, there there's so many, like, OG research papers that that came out of FAIR. Yep. This is what Yan Lakun used to be head
Speaker 1:of
Speaker 3:Mhmm. Before it to
Speaker 2:To MSL.
Speaker 3:To yeah. MSL. Okay. So so then I think let's move up here. Around your your trad lab, you'll still have post lab.
Speaker 3:Right?
Speaker 1:Yes.
Speaker 3:T o a s t.
Speaker 1:Yes. These are posters.
Speaker 3:Yeah. These are labs where you get a lot of posters. Yes. Right? So, obviously, this is OpenAI.
Speaker 3:You got Roon. Yes. Anthropic. A lot of, you know, Sholto. Yep.
Speaker 3:Got posters over posters. Prime Intellect. Think
Speaker 1:They're great posters.
Speaker 3:Brown. Yeah. A bunch of Anans at Prime Intellect doing great stuff over there.
Speaker 1:For sure.
Speaker 3:And then you kinda get into
Speaker 1:The proper Neo Lab.
Speaker 5:Yeah. The proper
Speaker 3:Neo Lab. Okay. So this is also a bit hard to identify because, like, what is actually the core of a NeoLab? What are these different kind of offshoots? Mhmm.
Speaker 3:I think PrimeIntellect is kind of the prototypical, like, quintessential NeoLab Okay. When you think of it, where you basically have it's, like, fairly recent. Yeah. It's still very much research focused. Okay.
Speaker 3:Like, sure, they have enterprise, like, you know Yeah. Thinking about different stuff. But at the core of it, you're still, like, trying to find these, like, new It's novel research. You're hiring researchers. It's not just, like, engineers, sales guys, etcetera.
Speaker 3:Mhmm.
Speaker 2:Let's Wouldn't Sakana be more of, like, a sovereign lab?
Speaker 3:Yeah. Yeah. I mean, so so a lot of these can can fit in all different places. Sakana would be, yeah, Japanese, maybe.
Speaker 1:Okay. And you put MSL in here because it's a new project.
Speaker 3:Yeah. This one was also a bit hard. It it doesn't feel like a trad lab because Mhmm. I mean, maybe it has the scale, but it's it's just
Speaker 1:It's newer. It it yeah. They haven't shipped yet. Yeah.
Speaker 3:Neo new lab. Yeah. Yeah. Yeah. I mean, it's it's so recent.
Speaker 1:Definitionally. Thinking machines is my classic go to Neo lab.
Speaker 3:Yes. I
Speaker 1:feel like it's post OpenAI exodus and sort of OpenAI is nothing without its people. You get the spinouts and you think thinking machines and SSI are two of, like, the first case studies that sort of set the tempo for, Okay, it's possible to do some research outside of the big trad labs. And so that's where you get the neo lab boom from. And then a lot of the other companies I feel like are saying, Okay, we're going to do something similar to Thinking Machines or SSI. We're going to commercialize early or late.
Speaker 1:But we're following in that, and we're benchmarking to that. Oh, raised $2,000,000,000 We're raising $200,000,000 It's easier. There's a 10% chance that we you know, are are at their scale, so you can underwrite it that way.
Speaker 3:Yep. So so Thing Machines also brings us to what I call the trad SaaS lab. Okay.
Speaker 2:So you
Speaker 3:have SaaS lab. You've trad SaaS lab. So I think the the way I think about this is the trad SAS Labs Yes. Are are trying to basically use the the data Mhmm. That's inside these big enterprises, pull them out with AI.
Speaker 1:Okay.
Speaker 3:So this is Thing Machines. Right? Yep. The the rumored idea, right, is they're doing RL for enterprise. Yep.
Speaker 3:Yep. A bunch of these are are doing fairly similar things where it's kind of chatting with your data, using the data that's very valuable to a company, but it it's gonna be inside the company. You can't really, pull it out anyway Mhmm. Besides having the the AI be, like, internal. So you have applied compute.
Speaker 3:You have poolside doing
Speaker 1:Mhmm.
Speaker 3:All kind of similar things in this in this Yeah. Like, enterprise LLM field.
Speaker 1:Yeah.
Speaker 3:And then that brings us to neo SaaS.
Speaker 1:Not full base pre trains for those companies, mostly fine tuning or RL on top of Yes. A particular company's
Speaker 3:Yes.
Speaker 1:Use case.
Speaker 3:Yeah. And then I have Neo SaaS lab.
Speaker 1:This is
Speaker 3:different than than TradSaaS. I think these are are different in that they're not really pulling they're not going enterprise specific, maybe. I think that's one way to look at it. They're also much more of, like, a startup focused.
Speaker 1:But they're making a product that is sold effectively as SaaS. Yeah. So Cursor, Cognition Yeah. WindServe.
Speaker 3:I have Ramp Labs.
Speaker 1:Ramp Labs. These are seat based sort of, consumption based. But it's a product that's bended into a and the product is what you get and then sort of customizes as you integrate it, but it's not you it doesn't the the conversation doesn't start with a with a with a business development relationship.
Speaker 3:Yeah. And, of course, I mean, these lines are are pretty blurry. Yeah. But then okay. Let's go down to the post lab.
Speaker 3:Okay. Post lab after This is after the lab. Yes. So that means, like, basically, they train the models, and then these labs are working on top of those models. That's how I'm
Speaker 1:thinking of it.
Speaker 3:Right? So you have METER, you have EPOC. These are gonna do evals. Yep. You have Pangram.
Speaker 3:They're seeing, is the the model producing slop? Yes. Or is it producing text that Yes. You're using in some
Speaker 1:These are purely eval. They they don't have necessarily AI products themselves. They don't necessarily sell to big businesses.
Speaker 3:So the consumers train models. Right? Like Pangram is training models that sit on top
Speaker 1:of the true. So it counts as a lab. Yeah. Makes sense.
Speaker 3:Okay. What else we got? Maybe that brings us down to the safety lab. Yes. So these are pretty interesting.
Speaker 3:Anthropic kinda fits in this. Right?
Speaker 1:Yeah. Cool.
Speaker 3:A big safety team. They're doing
Speaker 2:a lot
Speaker 3:of, mechanistic interpretability. Mhmm. You have Goodfire. I think they just raised at, like, 1,250,000,000.00, and they're just doing mechanistic interpretability. Let's go.
Speaker 3:Very interesting. Cool. Luthor AI is a similar kind
Speaker 1:of I know Luthor.
Speaker 3:Yeah. Yeah. Very cool. There there are also a lot of these are are also kind of in the open source space.
Speaker 1:Yeah. I think stable diffusion came out of Luthor AI.
Speaker 3:Yeah. There's another label that I I think I could have put on, but it's so hard to get everything to, like,
Speaker 1:work Yeah.
Speaker 3:But a lot of these are also, like, the core of the company is is doing open source stuff. Sure. Sure. Right? So Prime Intellect Yeah.
Speaker 1:Fair. Was a good example.
Speaker 3:Almost all Of
Speaker 1:course. OpenAI back in day. A lot of these have bled together where OpenAI has an OSS model but also a lot of consumer and enterprise. Yeah, it
Speaker 3:makes Yeah. Okay. So then contrast to Post SaaS lab.
Speaker 1:Yeah.
Speaker 3:We have the Consumer Lab.
Speaker 1:Okay, Consumer Lab.
Speaker 3:So these are focused on consumers. Right?
Speaker 2:So we
Speaker 3:have Eureka Labs. This is Andre Karpathy's Oh, yeah. Project here. I don't think there's anything been released from it yet.
Speaker 1:Education,
Speaker 3:though. But, yeah, education
Speaker 1:Makes sense.
Speaker 3:It's four people. Have
Speaker 1:Wait. Humans It's four people, not four individuals working there.
Speaker 3:It's four people. Yeah.
Speaker 1:It might be four people. It might be one person. Who knows? He's pretty good.
Speaker 3:Yeah. You have humans and.
Speaker 1:Okay.
Speaker 3:Right? This is the think phrase, it's like humanity focused. You're
Speaker 5:gonna turn
Speaker 1:human into sand?
Speaker 3:Human sand.
Speaker 1:Human sand.
Speaker 2:Yeah. We we got to hang out with the founders at the Super Bowl. But they're but but yeah. Focus on creating models that work better alongside people. Sure.
Speaker 3:Sure. You have a lot of, like, companions Okay. These kind of ideas. Right? You have character AI also Oh, yeah.
Speaker 1:Do they really own c.ai? What a great domain, if that's true. I don't know. Anyway.
Speaker 3:So then that that brings us down to the Visual labs. Visual labs. Right? So there's a lot of either multimodal Yeah. Models or they're actually, like, producing video or images.
Speaker 3:Right?
Speaker 1:We've talked to a lot of these founders.
Speaker 3:Yeah. I feel like almost all of them have been Yeah. Mean, World Labs raising today Yeah. Or fundraise announcement today.
Speaker 1:Yeah.
Speaker 3:Midjourney, etcetera. Leads are pretty obvious. You have your Neo Auditory Lab.
Speaker 1:Midjourney is the is the sailboat logo?
Speaker 3:Correct.
Speaker 1:It's a good logo.
Speaker 3:Yeah. Okay. You have a media reality labs on there too.
Speaker 1:Oh, okay. Right? Yeah. Yeah. Yeah.
Speaker 1:Yeah. Yeah. That makes sense. They're visual. Not not fully AI yet, but they're getting there.
Speaker 3:Yep. You have okay. You have neo auditory lab.
Speaker 1:Okay.
Speaker 3:Right? So this is gonna be anything that has to do with vocals
Speaker 1:Yes.
Speaker 3:Or voice or music. Right? Eleven Labs. Eleven Labs, of course. TBPN.
Speaker 3:Thank you. Suno. Right? Making music.
Speaker 1:Suno.
Speaker 3:Okay. Gemini also released a new model Yes.
Speaker 1:From Lyria three. I didn't even know there was a one or two. It's a trilogy already. They just got secret models that they're hiding from us.
Speaker 3:Yeah. Okay. So this is a very interesting field. And then you have your legacy auditory as opposed to your new auditory. Right?
Speaker 3:So this is your old ones. This is well, John, do you wanna talk about Nuance?
Speaker 1:Nuance Dragon NaturallySpeaking. This is the original box software. You buy it, install it on a Windows computer. You can talk into a microphone, and it will it will write down what Dictate you it. Yeah.
Speaker 1:Using some AI, not a large language model at the time, not a transformer based architecture, but became a very large company. I think it's part of Microsoft now or something. I think it's been acquired a few times. Yeah. But, yeah, very, very interesting company.
Speaker 1:A lot of really solid. Fruity Loops. Yeah. That's a know, you're in the lab making beats, I guess. Yep.
Speaker 1:Makes sense.
Speaker 3:Okay. So so now moving up. I think this is really the a very interesting section. So this is Okay. Neo Trad Lab.
Speaker 3:Yes. So I think what is a Neo Trad Lab?
Speaker 1:So the simple this is a simple definition, clearly. Yeah. Okay. So does it even need explaining? I think I think everyone gets
Speaker 2:it. Your head, by the way. Yeah. Know. It's coming really close.
Speaker 1:You might wanna be on
Speaker 2:the other side. To the team.
Speaker 3:Okay. So neo trad lab. Yes. It's a neo lab Yes. But it's trad.
Speaker 1:Okay.
Speaker 3:Okay. So what does that mean? So, basically, the way I I think about a lot of these labs is that, they're extremely research focused.
Speaker 1:Okay.
Speaker 3:They're also, largely They're on, like, kind of a single idea. Yeah. So if you think of, like, OpenAI Mhmm. Very research focused, obviously, but they're doing a lot of different things. Yeah.
Speaker 3:Right? So they have
Speaker 1:Consumer and Yeah.
Speaker 3:Consumer, but it's even, like, on the product or on the research side, right? They're doing their video images.
Speaker 1:Sora images.
Speaker 3:Yeah. But even even within, like, language models, I'm sure they have a, you know, continual learning Yep. Team or or all these, like, weird things where I think a lot of these Neotrad labs are basically focused on one single moonshot idea. Mhmm. Okay.
Speaker 3:So example, flapping airplanes. Yes. Right? They just came on. They're talking about data fittency.
Speaker 3:Mhmm. This is kind of the one kind of moonshot idea. Right? Obviously, it's like a very general broad. Of different ways
Speaker 1:you tackle it, but they're like, that's the problem that we're going at.
Speaker 3:One specific thing they're working on. Yep. And, I mean, they they talked about, oh, you know, if we figured out, there'll be some some value, but we're not actually sure how it's gonna come out Yeah. Like, now.
Speaker 1:And we're not sure how we're we're gonna productize it necessarily. Yeah. But we have a but we have really
Speaker 3:strong pieces. So so the idea is, like, if if say, if if these labs can figure out, like, the core research idea Mhmm. Then the value will will appear. Mhmm. So this is you also heard this out of Ilia with SSI.
Speaker 3:Right? Yep. Not sure how they're gonna get revenue, but it'll come Yep. If they figure out
Speaker 2:A breakthrough.
Speaker 3:Continue to
Speaker 2:that they will come.
Speaker 3:Yes. Yep. Worked before. A lot of interesting things here. So we can look at, like, okay, general intuition.
Speaker 1:Yes.
Speaker 3:They're basically doing a lot of multimodal training where they can basically take video game data and try to figure out how to map that onto LMs or world models or these types of things.
Speaker 1:Okay.
Speaker 3:You have Inception. I believe they're doing
Speaker 1:Dream tech.
Speaker 3:Wait. Okay. I'm thinking of logical intelligence. They're doing, like, diffusion models.
Speaker 1:Okay.
Speaker 3:Right? So diffusion but but for LMs.
Speaker 1:But for text. Yeah. We've seen a demo from Google on
Speaker 3:that Yeah. Okay. Inception is doing, I think they're doing the energy based models, which is kind of this weird thing. Okay. Wait.
Speaker 3:I have both of those companies flipped again. But it's Yan Lakun is
Speaker 1:into It's so simple. I mean, I don't know why you're flipping stuff around. Like, this is literally just NeoLab one zero one. You're doing a basic breakdown.
Speaker 3:Point is that they're doing these, like, kind of weird architectures where, like, energy based model, it's, like, kind of different than a normal LM where you have this normal back prop, stuff like this. But the the point is that, like, these are all, like, very kind of weird, like, architectures that they're working on. Yeah. So maybe the big labs have, like, small teams that are working on this stuff. Okay.
Speaker 3:But, basically, these people go out of the big lab. A lot of them come are coming out of the big labs
Speaker 5:Sure.
Speaker 3:And they're starting these new projects. Okay.
Speaker 2:Like, coming out of a trad lab or a or a neo lab or a neo Or
Speaker 1:legacy lab.
Speaker 2:A neo SaaS lab. Exactly. Yeah.
Speaker 1:Okay. Got it.
Speaker 3:Yeah. Okay. So now, let's move up a little bit. We have neo lab lab. Neo lab lab.
Speaker 3:Okay. Lab So this is Okay. Yeah. I like this one. So these are a lot of companies that are focusing on They're also, like, very research focused, but the the point of the research is to build essentially like a a researcher.
Speaker 3:So they're recursive. Right? Okay. You have recursive
Speaker 1:and recursive.
Speaker 3:Yeah. You have actually two that are recursive and recursive. So you have Richard Socher. You have Periodic Labs where they're not they're a little bit more focused on the hardware. Okay.
Speaker 3:But the whole point is that they have this kind of closed loop
Speaker 6:Okay.
Speaker 3:Where you can basically build a lab Yeah. Within the lab. Right? That's the whole point. You know, lab, lab.
Speaker 3:Yep. Building a lab.
Speaker 1:Got it.
Speaker 3:Okay. Unconventional AI, similar thing. Think they're they're
Speaker 1:just The product will be a lab. They're they're in the lab manufacturing business.
Speaker 3:Correct.
Speaker 1:Got it.
Speaker 3:Okay. Moving up, we have MathLab. Yes. So there's these are pretty interesting. Axiom and Harmonic.
Speaker 3:Yes. And then you have MatLab. Yes. But but these are pretty cool. They've there's been a lot of good breakthroughs recently.
Speaker 3:I think there's a bunch of Erdos problems that are are being solved or maybe they're just being proven in some But there's a lot of, like, interesting research coming out of these.
Speaker 1:Harmonic is Vlad Tenev, the founder of Robinhood.
Speaker 3:Yes.
Speaker 1:Correct?
Speaker 3:Yes.
Speaker 1:Yes. Wet labs?
Speaker 3:Yeah. Wet labs.
Speaker 1:Okay.
Speaker 3:So these are your bio labs.
Speaker 1:Oh, you got LabCorp. Yeah. I'm familiar with LabCorp.
Speaker 3:LabCorp. But there's there's a lot of, like, biology focused
Speaker 1:Yes.
Speaker 3:Labs. It's actually, like, I didn't know a lot of Yeah. I didn't know a lot about a lot of these. But there's all sorts of interesting research. So isomorphic labs, this was spun out of, I believe, Gemini or at least Google.
Speaker 1:Yeah, that's right. They're working on longevity and just drug Yeah. Development
Speaker 3:some of these are very focused on specific forms of drug development. Some of them are just like broader where they're very focused on longevity stuff. Yeah. Cool. And then, yeah, let's Yeah, go to
Speaker 2:what's going on up top?
Speaker 5:What's going
Speaker 3:on Oh, yeah, top we have Labrador.
Speaker 1:Oh, that's really important. If you wanna understand labs So you got you
Speaker 3:gotta understand These, got your your foundation. The white lab, your black lab, your chocolate lab.
Speaker 1:The chocolate lab. Yeah. Chocolate labs are important
Speaker 3:Yep.
Speaker 1:If you wanna understand labs broadly.
Speaker 3:Yeah. Okay. Then moving back down, we have the Neo Kinetic lab.
Speaker 1:Okay.
Speaker 3:So these are gonna be your your labs that are more focused on robotics. Yes. So you have a bunch you have Project Prometheus.
Speaker 1:Yes.
Speaker 3:This is Bezos's Oh. Lab. It's still kind of in in stealth, which is why there's not even a logo for it. Yeah. You have Figure.
Speaker 3:You have Skilled AI.
Speaker 1:Skilled AI is the Luke Metro project? Yes. Got it.
Speaker 3:Yes. Physical intelligence, Sonday. Right? These these are all your your kind of NeoConnect labs. Right?
Speaker 3:These are Mhmm. Started fairly recently in the past, like, maybe four or five years Yes. Broadly.
Speaker 1:The Neo Neo Lab.
Speaker 3:Neo Neo Lab. Right? Okay. So one x is building Neo robots. So there's Got it.
Speaker 1:Neo Neo Lab. Makes sense. Yeah.
Speaker 2:Yep. And
Speaker 1:then Legacy Kinetic is the previous.
Speaker 3:Legacy Kinetic is kind of the old gen. Yeah. But Cooking.
Speaker 1:They're cooking. Yeah. Waymo's cooking. Yeah. Cruise and Boston Dynamics have been a little bit behind.
Speaker 1:Yeah. Zook's also another self driving
Speaker 3:car There's a bunch in here that I I could have
Speaker 1:There's another
Speaker 3:one with
Speaker 1:stealth, I think, that never really Yeah. Hit inflection. Okay.
Speaker 3:Yeah. And then you have your
Speaker 1:Mostly vehicle focused.
Speaker 3:You have your dark lab.
Speaker 2:Yes. So this is Working
Speaker 1:with the government.
Speaker 3:I have yeah. I have ShieldAI. I also have DARPA.
Speaker 1:DARPA is a lab. Yeah. They invented the Internet. Right?
Speaker 3:Yeah.
Speaker 1:GPS.
Speaker 3:Yeah. Yeah. DARPANET.
Speaker 1:Yes. That's good. And then simulation lab. I think
Speaker 3:that Simulation lab. Yes. So we just had them on
Speaker 2:SpaceX, you could you could put up there because aren't aren't they working on this Yeah. The drones. Pentagon.
Speaker 1:Yeah. Where's Rocket Lab? Rocket Lab needs to be on there. That's a lab.
Speaker 3:There's a lot of labs.
Speaker 1:There's lot
Speaker 3:of labs. I mean, yeah. Lab is very very broad term.
Speaker 1:Very broad term. Well, I at least it's crystal clear now for everyone.
Speaker 3:Yeah. So I I think this should be pretty obvious to anyone who's thinking about neo labs. Like, how should we thinking about them now?
Speaker 1:Yeah. If you've been paying attention, this is all second nature to you.
Speaker 2:Yeah. Did you add up how much all the companies have raised? It's gotta be in the north of 200,000,000,000.
Speaker 3:Yeah. It's a lot. I mean, so so I I didn't do that, but, for a while, I was
Speaker 2:trying to figure out
Speaker 3:how to include valuations on the map.
Speaker 1:Yeah. I was too confident.
Speaker 3:You didn't wanna
Speaker 2:you didn't feel like you could do the math?
Speaker 1:No. We don't know how.
Speaker 3:Well, it's also a a lot of them are are rumored. Yeah. It's actually, like, kind of hard to find out because a lot of these are are still really in stealth. Like, a lot of these NEOTRID labs Yeah. They basically because the whole point is that they're they're doing this, research stuff.
Speaker 3:Yeah. They're they're not gonna, like, productize early.
Speaker 1:Yeah. And, also, how much do you put in the DeepMind bucket? That's a huge amount of investment, and it's not exactly disclosed. Do you count the TPU? Do you count Google Cloud?
Speaker 1:Like, different allocations. You can go really deep in the stack to understand the impact of, like, the broad AI build out. But, yeah, I mean, if you just total this up, you can really just do x AI, OpenAI, Anthropic and get, like, 90% of the way there, and it's probably, like, 200,000,000,000.
Speaker 3:Yeah. It's also hard because it's, like, evolving so fast. Right? So David Silver's lab Yeah. He was used to be at DeepMind.
Speaker 3:Well, like ineffable. Ineffable intelligence. Word. Yeah. I think that was means.
Speaker 3:Rumored today. Yeah. It's indescribable. Yeah. It's good news.
Speaker 3:But these things are coming out like you
Speaker 2:put the typos in just to prove that What typos? Humans are like Sovereign Lab and then intelligence also has a typo. And so I I just wanna make sure I wanted to make sure that you put yeah. You put the typos in so that it was proof that you made it.
Speaker 1:Yeah. Yeah. So in.
Speaker 3:I don't want
Speaker 1:Well, yeah. I I whatever you built this in doesn't have spell check, I guess. Anyway, fantastic report. Thanks for breaking it down.
Speaker 2:Great stuff.
Speaker 1:I learned a lot, and I hope you did too. And let me tell you about a lab Gemini three Pro. It's Google's most intelligent model yet. State of their reasoning, next level vibe coding, and deep multimodal understanding. And I'm also gonna tell you about Sentry.
Speaker 1:Sentry shows developers what's broken and helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working.
Speaker 2:Yeah. It's one show, two maps. One show,
Speaker 1:two maps.
Speaker 2:Strong start.
Speaker 1:Should we break down five wildly obvious fixes that will explode consumer LLM adoption? They don't want you to know this over at the big labs, but, I have some ideas. Basically, everyone's been really focused on agentic coding and the SaaSpocalypse and what's happening in the business to business world and the and the enterprise world. I've just been sort of, like, thinking back on, you know, basic improvements to the chat apps that I use all the time, because there's some really obvious stuff that I think I think is in the works, I think it's coming. But I wanted to just sort of like get it all down in one place to think about what the next iteration or the next breakout moment when people are like, Oh, I'm using them even more.
Speaker 1:I'm having a better experience. What would that look like? So the first thing is that I realized that I've asked ChatGPT just when was OpenAI founded three different times. It's the exact same query. Like, it doesn't need to light the GPUs on fire for that question.
Speaker 1:The answer literally never changes. You can cache the result. And that's what Google does with those knowledge queries, knowledge panels. And there's a whole bunch of different ways to deliver results that are sort of precached. And so if you just look down, when an LLM launches, basically every question has never been asked before.
Speaker 1:But now there's a lot of people that are just showing up with the exact question. Give me the history of the Roman Empire. Give me the history of this company. And you might not be the first person to ever ask that question exactly. But also, you do a little bit of fuzzy if you do a little bit of, like, fuzzy search over it, you there are probably hundreds of thousands of people that have asked the exact same thing.
Speaker 1:So cache those results, give them to the user instantly. And I think this instantaneous feeling of LLMs, they felt slow for a really long time. They actually got slower. It was always sort of slow. You watch the token stream in.
Speaker 1:But then once the reasoning models and the thinking models and the deep research and the o three pro came out, it was, like, really slow. It was like, close your phone and come back in twenty minutes. That doesn't have to be the end state, and I don't think it will be. And I have no better example than the number two on my list, which is cerebris inference. So ChatGPT currently has a model called 5.2 instant, and it is not instant at all.
Speaker 1:I fired off a prompt of 5.2 instant, and I said, no reasoning. Tell me the history of LLMs. It took thirty eight seconds to deliver the full response, so for, like, all the tokens to stream in. And it does a good job. It it shows you images and stuff, and it is a cool it is a cool illustration.
Speaker 1:But then I went over to Codec's desktop, and I fired up GPT 5.3 Codec Spark Low, which is a crazy name, which we'll get to, and it responded in under two seconds because it's, from what we know, Spark is
Speaker 2:incredibly Credibly not quick.
Speaker 1:Cerebris and it's very, very fast. And so everyone's obsessed with like the fast models in the agentic coding world because you're waiting half an hour for something to get back to you. You're waiting five minutes for something to get back to you and you're actually losing your train of thought. But I think that applies in consumer as well. And I think the interaction of sending a message and then just immediately getting a response before you actually think, oh, well, like, it's it's waiting.
Speaker 1:I'll close the app. I'll check my messages. Oh, I got an Instagram notification. Let me go over there. Like instant responses will keep people in the apps longer, and user minutes will actually increase once that rolls out.
Speaker 1:So pretty simple implementation for, I think, most companies. My big question is, I know Google has a huge advantage with TPU, but I don't know if they have, like, an answer to Cerebris specifically. And NVIDIA just brought Grok, which can do, I think, some of the same things. So I'm I'm curious to know how every lab solves the, like, fast responses question because that feels like an important piece of the puzzle. It's not the only piece of the puzzle, but it's an important feature.
Speaker 1:And I think we're gonna see it rolling out to consumer LLMs very, very soon. And I do think it'll be an interesting moment for people to both ask a question and just boom, it's as fast as going to Wikipedia and just seeing, like, okay, everything's rendered, it's thoughtful, it's what you want. And on the flip side, I think that it could make people a lot more chatty with them, like actually asking follow-up questions, because you don't feel that cost of like, Oh, if I ask you to follow-up and tell me more or go a different direction, like I have to wait. I have to wait. So I might Speaking just close the of GPT 5.3 Codec Spark Low, no more model names.
Speaker 1:Like truly, no more model names in consumer AI LLM chat apps like ever. Like just bury them so deep in the UI that you never see them. And people will complain. People will be like, I wanted it to be easier to pick. I like picking between pro and thinking and fast and instant.
Speaker 1:I know what I want for everything. People complain. But it will all inspire the model routing team to grind harder, and the model routing team has a hard job to do, but they will eventually figure it out. And eventually, you should be able to just talk to the model. You can already do this in ChatuchPity.
Speaker 1:You can say, hey, think really hard about this question and give me a really thorough answer. And it'll go it'll switch from instant to thinking. I don't know that you can trigger pro from that. I haven't actually experienced that. I did try and trigger a deep research report.
Speaker 1:I said, hey. Please deep research the Roman Empire for me. And it does not fire off a deep research report. Deep research is buried under, like, a plus button, and you have to select it and say, okay. I actually want you to do this thing.
Speaker 1:And then it takes you down the deep research, like, workflow, which I understand is, like, for inference reasons, they don't just want you firing off deep research reports all the time. But I think in the future, like, the model router should be very intelligent about, Okay, this is a question that people have asked thousands of times. Let's just go get it from a database, which is crazy to think in the age of AI that you wouldn't even be hitting a GPU, but I think that's going to be real. And then I think on the other side, you should it should detect, like, Okay, this person wants something that's far beyond anything that we've ever worked on before. We got to go search the Internet.
Speaker 1:We got to write some code. We got to do
Speaker 3:a whole ton of stuff. I'm going
Speaker 2:need let's 10
Speaker 1:fire up deep research. Right? Fourth, ads. We've talked about this, but we've got to get them in the LLMs. We've got get them everywhere because I was thinking about the death of Google Reader.
Speaker 1:I don't think you were ever a Google Reader guy, were you? But it was amazing. Could take all these RSS feeds from all these different blogs. During the blogosphere, could put Marginal Revolution, Tyler Cowen's blog, all these different stuff all these different things in there, and just kinda scroll through them really quickly. And Google wound up killing it, and everyone was, like, really upset.
Speaker 1:And the reason was, I I think, because they never really got on the Google ad flywheel where there was real, like, revenue generation and
Speaker 2:Yeah. And was that just that it didn't hit a a scale that enabled it to make sense?
Speaker 1:The failure of every Google project that has failed is always a question of, like, was it because they weren't making money from it, or was it because they hadn't monetized it yet? And Or it just never got big enough. Never got big enough to monetize.
Speaker 2:A million Yeah. Weekly actives Yeah. It's not probably worth keeping around.
Speaker 1:Totally. Totally. But my my my takeaway from Google's surface area of products that are successful and loved, Google Search, Google Google Maps, Chrome, Android, like these are all direct funnels for the ads flywheel. And so you can see that they're driving the bottom line. There's a whole bunch of folks on the team that are getting excited when they're hitting their numbers, when they're making more money for the business.
Speaker 1:And so they just get more and more resources, more and more engineering effort, everything gets better. I think that not only are ads the best way to deliver high quality products to the broadest possible audience, but they just make products better top to bottom. And yes, there's the stated versus revealed preference thing, and yes, you might want to pay to not have ads like you do on YouTube. Many people do. But I do think that that ads flywheel is going to be really, really important as inference gets released.
Speaker 2:And right on time, Perplexity ends ads experiment. I saw that. This was the news from this morning and the information from Catherine. He says Perplexity is no longer offering ads, an executive told the Financial Times. The AI search startup is pulling back from this line of business as Rival OpenAI started showing its users ads in ChatGPT earlier this month.
Speaker 2:The company said it worried ads would undermine users' trust in their platform, with an executive saying the challenge with ads is that a user would just start doubting everything. I don't buy this
Speaker 1:That's weird.
Speaker 2:At all. Arvind has a history of kind of just like trying to provoke OpenAI at every turn
Speaker 1:Yeah.
Speaker 2:And so coming out. Perplexity, in my view, like, that this is just, like, somewhat bearish. Right? They're trying to serve as many people as possible Yeah. All over the world.
Speaker 2:Yeah. The best way to do that is gonna have an have an ad supported tier of bailing on this moment. I don't know. Maybe it's not worth reading too much into it, but a little bit early to throw in the towel on the economic engine that has driven the internet for its entire history.
Speaker 1:Yeah. I mean, we talked to a lot of founders who have brands and they love advertising. And I think that's another side of this, which is that when like, a lot of entrepreneurs and also people who work at businesses want to grow their businesses, and they have fond memories or affiliations with Facebook and Google because that's how they grew their companies. And when you talk to somebody like Sean Frank at The Ridge, he's like, I'm going to be first in line to advertise on ChatGPT. I can't wait for that.
Speaker 1:It's converting so well already. I want more of that business. And we didn't really hear that with the Perplexity ad product. We didn't hear people lining up to to buy ads in that product. So maybe it was not going as well
Speaker 2:as they thought. So according to the information, Perplexity started testing advertising in 2014. Less than a year into its test, Taz Patel, the executive leading the ads effort, left the company and Perplexity had only let in less than half a percent of the brands that wanted to advertise on So there was like a bunch of demand. They barely let anybody use it, and then they bailed on it. Interesting.
Speaker 2:And so Interesting.
Speaker 1:Well, the last one is somewhat related to OpenCLaw. But I think way down the funnel, beyond the twenty minute deep research project, you probably wanna be able to fire off something that looks like Cloud Code or OpenCLaw or Codex to write lots and lots of code and and solve a really, really hard problem. And so many reasoning models can already write some Python and execute it, but it's clear that everyone wants to go further, hence the Mac mini boom. And I'm not actually sure how important access to the local file system is to most consumers. Like, when I when I think about what's like, most of the data in an average Internet user's life is mirrored in the cloud.
Speaker 1:I think they care about their camera roll. They care about their email, their messages. And almost everything's in the cloud. I've noticed this when I move from one computer to the next or I move from a phone. I'm like, wait, I didn't actually there was a time when it was like, oh, you're moving computers?
Speaker 1:Like like, get an external hard drive. Like, make sure you drag all your folder all your files over. Most of the stuff's mirrored to iCloud. That can be accessed via an API. It requires a business development deal, probably.
Speaker 1:But it does seem feasible. And a lot of the LLMs have hooks into Gmail already. I think all three major LLM apps have Gmail integrations already, and more integrations are coming, clearly. And so I'm not sure that you need to replicate OpenCLaw and have it running on a dedicated piece of hardware, even like cloud hosted, but I do think people will want to be able to fire off something that writes tons of lines of code to solve a particular problem, even if it's something as mundane as like getting you a restaurant reservation at a place that doesn't have an API. Like if there's a restaurant that just has a Web form and you basically want to deploy agent mode, that might look like writing a web scraper and writing something that actually does like a headless Chromium browser and clicks it, and that might be generated from something that looks a lot more like OpenCLaw or ClawCode than something that is just a couple lines of Python in a reasoning model.
Speaker 1:Anyway, there are also a bunch of nice to haves. These aren't really on the list, but these apps, they still occasionally fail to return results when you're in areas of patchy cell phone service. There's like little UI things. Some of them botch text to speech requests when you'll fire off a deep research report and they'd be like, Read this to me. And then it'll read for like a minute and then it just stops.
Speaker 1:Some of the apps don't let you listen to the deep research reports, but they let you listen to the normal reports. So there's always like little fine details in the UI that I think are causing more churn and people can just chop away at. It's unclear if what is required to make an amazing product is just AB testing all of these things and just optimizing. Or is it taste? I have no idea.
Speaker 1:But if you wind up doing this is my recommendation for anyone who's working on this stuff if you're just going to run an AB test to figure out what is the correct user interface and you've and you run the you run the AP test, you you find out that the button should be blue instead of green, don't tell your boss you ran the AP test. Tell them it was taste. Say that it's all about taste.
Speaker 2:Good call. And that
Speaker 1:you have taste.
Speaker 2:It's all about taste.
Speaker 1:Because then you'll have a job forever. Yeah. But but if you say, I'm the guy who runs AB tests really well great. Probably. Probably.
Speaker 1:Taste It's is true. AI the AI models can't taste. They can't taste. They can't taste a five Wagyu. They can't taste a Cabernet Sauvignon.
Speaker 1:Only you can do that. So make that dinner reservation and enjoy a nice glass of red wine because the models can't. They just can't. There's just no way. There's no way.
Speaker 2:Alpha. Alpha. Alpha.
Speaker 1:Anyway, let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it.
Speaker 1:And let me also tell you about Lambda. Lambda is the super intelligent cloud building the AI super computers for training and inference that scale from one GPU to hundreds of thousands.
Speaker 2:Robinhood says, historically investing in private markets was limited to institutions and the elite but not anymore. With Robinhood Ventures, you can now get exposure to private companies like the ones listed They have a new fund that has Databricks, Mercor, Revolut, Airwallex, Boom, Supersonic, Ramp, Aura and Stripe, which is signed and pending close. Very curious which of these companies, if any, were actually on board and excited about being part of this lineup?
Speaker 1:I think Ramp was. I saw Fax Herbert from Ramp posting about it.
Speaker 2:And he is that but that doesn't mean the That's company not relations.
Speaker 1:Okay. He said, we are excited to partner with Sarah, Shiv, Chan, and the broader Robinhood Ventures team on their inaugural fund. On a personal note, I'm revealed I'm relieved to finally have an answer for family and friends who have been asking, how do I get exposure to ramp equity? And so if this is coming out from your head of Investor Relations, it's not exactly a Matt Grimm style response. So I think most of the companies that are in the press release at least and saying, hey, you can use our logos are cool.
Speaker 1:We'll see where it goes. There are folks that are that might get funneled in there and they don't want to be and there might be a whole bunch of different debates and back and forths. What is on
Speaker 2:Shiel Shiel shared kind of some of the the cost basis from the prospectus.
Speaker 1:Mhmm.
Speaker 2:They bought Databricks at a $150 per share, now trading at 204, ramp at 90, now trading at 98. Airwallex, $21. It's now trading at 18.8, and then Merkor at $7.14 now trading. So already seen a little uptick. Anchor came in and was sharing some of his insights insights for end of the show.
Speaker 2:He says a single close end fund that gives you exposure to some of the top private startups. My thoughts, people want access to private markets. Of course, so much wealth creation in America happens in startups and people desperately want access. You can see this with the insane, silly fees people are paying for Anthropic, SpaceX, and OpenAI SPVs. Mhmm.
Speaker 2:He says, too, the structure of this fund is broken.
Speaker 1:As a
Speaker 2:closed end fund, the price here can diverge very significantly from the net asset value of the underlying assets. With FOMO from access, this could easily trade at a very high multiple Yeah. To NAV leading to a lot of retail investors getting their face ripped off. It ends up being less of a venture fund versus a speculative product to ride private market sentiment.
Speaker 1:It's a great disclosure.
Speaker 2:Disclosure, long Robinhood but will not
Speaker 1:be He's long Robinhood but he's like, I don't Yeah. Like
Speaker 2:So we actually have the founder of
Speaker 1:Destiny coming on the
Speaker 2:show today.
Speaker 1:So Hel Prasad is coming on at one p. M. And they're sharing their Q4 results. They have exposure to Anthropic Chaos Industries, Hermes positioning Destiny as a New York Stock Exchange listed vehicle democratizing retail access to high growth
Speaker 2:Yeah. Destiny has suffered from the same problem. They were super early. They got this fund out in almost two years ago exactly or close. And immediately, it spiked.
Speaker 2:There's a lot of demand to get exposure to these assets. And it's sort of come back down to earth since then. But excited to get the update from him and understand
Speaker 1:Yeah. Let's pull up the rest of the linear lineup to show you who's coming on the show today because we have Blake Dodge from PirateWires, Freddie DeBoer from Substack, Sohail, as we mentioned, from Destiny, Travis from Mesh Optical, and then Evan Spiegel, the cofounder and CEO Linear, of of course, is the system for modern software development. 70% of enterprise workspaces on Linear are using agents. Moving on. Elon Musk announced that XAI is moving away from traditional academic benchmarks like Humanities Last Exam to focus Grok on maximal utility for real world engineering and software development.
Speaker 1:So actually, I don't think HLE is a great measure of usefulness. We're moving away from these benchmarks.
Speaker 2:So Andy Scott says, so it's bad, question mark.
Speaker 1:Who said that?
Speaker 2:I think it's totally fair to just focus on real world utility. But, of course, people are still gonna ask. Well, I still wanna know how it does.
Speaker 1:Yeah. It's interesting. I mean, the the Tyler, give us the update on 4.2 that came out today. So Grok four has already been out. This is a minor revision.
Speaker 3:And 4.1.
Speaker 1:4.1. So now we're at 4.2. And and is it is it focused on benchmarks, or have have they carved out a particular particular niche yet?
Speaker 3:Yeah. So I I think historically, especially when Grok four came out, people were, like, very very quick to say it was like, oh, this is so benchmarked or whatever. I think they've definitely retreated from from that, like, at least path with 4.2. It doesn't look like outrageously benchmarked or anything. Mhmm.
Speaker 3:They did this kind of interesting thing where when you so I it's still not like fully out. It's still like in in beta if you go on the the Grok like interface. They did this kind of interesting thing where there's like four agents.
Speaker 1:Okay.
Speaker 3:Like every time you actually do a prompt, there's like four agents. The agents specifically have like distinct roles.
Speaker 1:Okay.
Speaker 3:Where it it's almost kind of like you have four instances of the same model, but they have different system prompts. Yeah. So you can try to get, like, okay, this one is, like, focused on doing, like, qualitative things.
Speaker 1:Instead of mixture of experts, mixture of agents.
Speaker 3:Yes. Yeah. Yeah. But, you know, mixture of experts is like a that's like Within the architecture. Yeah.
Speaker 3:Of the model.
Speaker 1:Within the architecture.
Speaker 3:This is You train the model, then you kind of add this as almost like a harness type thing.
Speaker 1:Yes. Yes.
Speaker 3:Yes. So it's kind of an interesting path. Yeah. We'll see like, yeah. Again, this is still not like the actual 4.2 Yeah.
Speaker 3:Full full release
Speaker 1:Oh, okay.
Speaker 3:I believe. Yeah. But we'll see.
Speaker 1:Yeah. I wonder I wonder what the bull case is here for for x AI. They they they there's a world where they carve out some sort of niche, you know, Anthropics, like, focused on coding very specifically and and and, you know, had some major major gains there. What else is there to
Speaker 3:I mean, I think with macro hard, they're going very hard on computer use.
Speaker 1:Okay. Computer use. Yeah. See, that that would be an interesting thing where they could, jump to the front of that. And if that's the important the important technology for a couple months, that could be really good vibes.
Speaker 1:Yeah. Also, it is interesting to think about with the Cerebras news and with the value of like high speed inference on one the whole model on one chip, is that something that Tesla's chip team can can iterate towards on a faster time horizon than other chip companies? I don't really know. But they I mean, they they do custom silicon, they've done it for a long time. And they've got an entire self driving model that runs on a car.
Speaker 1:So, you know, they have some experience there. And they obviously design in fab or they don't fab it themselves, but they design it themselves. And so we'll be we'll be interesting to see how they how they carve that out. Let me tell you about Vanta, automate compliance and security. Vanta is the a leading AI trust management platform.
Speaker 1:Let me tell you about Applovin. Profitable advertising made easy with action.ai. Get access to over 1,000,000,000 daily active users and grow your business today.
Speaker 2:Tariq says, I'm proud to share that Humane has invested $3,000,000,000 into XAI's Series E round just prior to its historic acquisition by SpaceX. Through this transaction, Humane became a minority shareholder in XAI. Investment builds on our previously announced 500 Megawatt. Megawatt AI infrastructure partnership with XAI in Saudi Arabia, reinforcing Humane's role as a strategic development partner. So, yeah, interesting.
Speaker 2:Maybe, you know, would have wanted to get this out before before the SpaceX acquisition, but better Wait. Late
Speaker 1:Wait. Wait. Wait. Wait. They said they got in before the acquisition.
Speaker 1:I know. But You mean the news?
Speaker 2:But, like, you know, this round got announced a while ago? Yeah. So maybe they would they're they're coming out with this news today.
Speaker 1:Yeah. But they're saying, hey. We got in before the acquisition. So we got we got SpaceX shares.
Speaker 4:Yeah. I don't know.
Speaker 1:It is it odd that better it's the
Speaker 2:late than never.
Speaker 1:Yeah. You mean on, like, a comms front. But, like, from a financial perspective, like, that that was the right time to invest. Right? Yep.
Speaker 1:I think that's I I think that's what's going on. I wonder I wonder why the announcement was delayed. Maybe it's it's, like, regulatory approval Yeah. Because it's a international investment. Yeah.
Speaker 1:Let's play this clip from Jeff Bezos. His space company Blue Origin will move heaven and earth to get to the moon before rival SpaceX, the CEO Dave Limp said.
Speaker 7:Recently, Jeff Bezos, never tweets, this was his first tweet of 2026, posted a photo of this, like, black tortoise, which goes along with blue
Speaker 2:orange and this
Speaker 7:big motif of slow and ferocious, methodical. Arcturus viewed it as a warning shot to Elon Musk, really was focused on SpaceX going to Mars, and now he's saying we're gonna focus on the moon. What do you make of that tweet, and what is the competition right now? Do you think you're gonna be the first?
Speaker 8:Well, it gives me an opportunity to put on a t shirt for you. So there you go. That's the nothing else. Let me do that.
Speaker 1:We're
Speaker 7:Am I good to keep this?
Speaker 8:Yeah. That's all yours.
Speaker 7:Oh, really?
Speaker 8:And that's the first one off the presses too, by way. I think everybody's gonna want one of those.
Speaker 2:He t shirt Mark Bloomberg.
Speaker 8:To lose for Blue to succeed. What The US needs is it needs two SpaceXs. It needs two launch companies that are competing vigorously against each other to try to give us the most capabilities as a country, commercially, civilly, from a defense perspective, because our adversaries aren't standing still. And so we need we need to be moving very quickly.
Speaker 7:Healthy competition. But I think a lot of people read into that as the tortoise being Blue Origin and the hare being Elon Musk and SpaceX. Because it also comes after secretary Duffy had said that SpaceX is behind. So they were opening up for everyone in terms of Artemis. And Jared Isaacman, who's now the administrator, also said, essentially, yeah, whoever can get there first is gonna get the contracts.
Speaker 7:So do you think you're gonna get there first?
Speaker 8:I I think if asked, we will make it we we'll we'll give it a run for our money. I I like our architecture. I I like our odds of getting there very quickly. I I don't I don't have a crystal ball into what SpaceX is doing. I I think, again, Gwen and Elon are competent, and they show it every day by launching rockets.
Speaker 8:Elon. But I love the fact that The US would compete us against each other. They are for sustainability on Lunar. We're talking about who could get there in 2028. If asked, we will step up and we will move heaven and earth to get to the moon first.
Speaker 2:Move heaven and earth Powerful line. First.
Speaker 1:The moon race is gonna be fun. I think it's the it's shaping up shaping up well. I mean, yeah, a little bit of a come tortoise in the hair story, little bit of come come from behind. I I'm not buying the as ferocious
Speaker 2:Yeah. I don't love I don't really love the I don't really love the analogy. Like, I don't I don't I don't don't think it's the best comp strategy. Like, I I like the vague posting Mhmm. Out of out of Jeff.
Speaker 2:It gets it gets the people going. Mhmm. But at the same time, just imagining SpaceX as a hare Mhmm. Just like running running a bunch of laps around the tortoise just kind of
Speaker 1:Okay. They need to take this way further. Elon needs to wear tortoise shell glasses. Be like, I turned your tortoise into my glasses. And Elon and Bezos needs to start carrying a rabbit's foot for good luck.
Speaker 1:That would be the hare. Like, I got your foot. You know? I want I want much more. I want more battles here.
Speaker 1:This is great. Well, let me tell you about Okta first. Sorry. Okta helps you assign every AI agent a trusted identity so you get the power of AI without the risk. Secure every agent.
Speaker 1:Secure any agent.
Speaker 2:According to Calci according to Calci, Blue Origin will Blue Origin land on the moon before SpaceX? So if Blue Origin lands an uncrewed moon lander on the moon before SpaceX before 01/31/2030, the market will resolve the yes. So currently, it's at a 7070%.
Speaker 1:So they think the moon race
Speaker 2:9% in March. Course, like, the
Speaker 1:race isn't over. Like, the finish line is not get get one lander to the moon. It's like develop an economy on the moon and get lots of people there. So, you know, it was just one read on this market, but it is interesting. And and certainly, I mean, you can see the market was not pricing this a year ago, and I don't think anyone was.
Speaker 1:I think everyone thought that Blue Origin was kind of just a side project that was sort of just like doing space tourism. And now it seems like they might be going to the moon, which is pretty cool. We have some breaking news.
Speaker 2:What's that?
Speaker 1:Claude Oauth is officially not allowed in OpenCLaw. So Anthropic is responding to the OpenCLaw, OpenAI news. And Andrew Warner shares that this would be a great time for Sam Altman to step in and let us use OpenAI subscriptions with OpenCLOS. So in the Cloud Code docs, OAuth authentication, which is used with the free Pro and Max plans, is intended exclusively for Claude code and Claude dot ai using OAuth tokens obtained through Claude free pro or max accounts in any other product, tool or service, including the agent SDK, is not permitted and constitutes a violation of the consumer terms of service. So if you're on the consumer plan with Anthropic Claude, like you just signed up for a normal plan on your app, and then you get excited.
Speaker 1:You wanna sign up for you wanna set up OpenCLOD on your Mac Mini. You do that. And then when you're in the login flow, you say, hey, I'd like to use my CLOD tokens over here. It's gonna say, no. You gotta set up an enterprise plan.
Speaker 1:You gotta set up a correct?
Speaker 3:Yeah. I This is not news, though. This was, like, a couple weeks ago. I think, like, a week after OpenClaw got, like, super big, they they stopped. Because you can still I mean, I I'm pretty sure you can still use API like, an API key.
Speaker 1:An API key? Yeah. And will that use your Right
Speaker 3:now, plan? Was you could have a Cloud subscription.
Speaker 1:Okay.
Speaker 3:And then with that, you get a certain amount of of, like, basically, Cloud Code Yeah. Tokens. Yeah. Yeah. Yeah.
Speaker 3:But they're soup they're, like, massively subsidized
Speaker 1:Okay.
Speaker 3:Versus the API. It's, 10 x
Speaker 2:Yeah.
Speaker 3:Yeah. Yeah. For the Cloud Code tokens. Got it. So then they were basically using those in OpenClaw.
Speaker 1:Yeah. Or So that was in other agents.
Speaker 3:Yeah. That was for OpenClaw. Yep. Not actually OpenClaw. Yeah.
Speaker 3:Yeah. Sorry. I'm getting
Speaker 1:Yeah. I know.
Speaker 3:But I think it's a similar
Speaker 1:25 different names. Yeah. Yeah. So the chat is saying that this is this is news that, like, the particular OpenClaw integration maybe broke today. Peter from OpenClaw has responded and says that OpenAI has already publicly said that OpenAI subscriptions will work and continue to work in OpenCLaw.
Speaker 1:And so it's a little odd because, yeah, I mean, you can just use the API. That's not that if you're technical, that's not a problem. But for the sort of pseudo technical folks who are setting up OpenClaw instances on their Mac Minis, they might be a lot more encouraged to set up the system if they're able to just log in with OAuth with their cloud accounts because they're like, yeah, I already have the app and I use the app and I have some extra tokens. Why don't I use them over here?
Speaker 2:Yeah. Thomas says the news is that they're applying it to the SDK.
Speaker 1:Yes. So there we go.
Speaker 2:Anyway, Moving on.
Speaker 1:You about Console. Console builds AI agents that automate 70% of IT, HR and finance support, giving employees instant resolution for access requests and password resets.
Speaker 2:Out of the journal. Yes. The fossil fuel tycoon teaming up with the Rockefellers to fight energy poverty. I'm sure the online conspiracy community will love
Speaker 4:But this
Speaker 2:we love tycoon. Tycoons. We were trying to bring the word tycoon back. We're happy to see the journal using this. EQT chief executive Toby Rice is starting a nonprofit to tackle a lack of access to modern energy infrastructure in poor countries.
Speaker 2:Toby Rice made his fortune unlocking a gusher of natural gas in Appalachia. Has a bold new ambition, bringing energy to millions of people in impoverished nations. Rice, the chief executive EQT, one of the largest natural gas producers in The US, is a co founder of Energy Corp, a nonprofit Energy Corp, a nonprofit that helps developing nations such as Ghana, Zambia, and Burundi build out their energy infrastructure and prosper. Unlike other philanthropic incentives that emphasize renewables to energize impoverished societies. Energy Corps sees a role for a broader spectrum of solutions from fossil fuels to solar panels and nuclear plants.
Speaker 2:Notably, this approach has been endorsed by the Rockefeller Foundation, one of and richest foundations
Speaker 1:They really opened up the flood gates with this. The Rockefellers, you know, wasn't John D. Rockefeller the richest person in human history? You see how much he's putting in this project? 200 g's.
Speaker 1:200 k. Go solve it. Go solve energy globally. $202,100 k. Here you go.
Speaker 2:Best I can do is is $200. I got I got you. I'm super excited about
Speaker 1:this. This. I think I think McCrone deserves a victory lap at this point.
Speaker 2:Yeah. I mean, his McCrone's size is looking Yeah.
Speaker 1:It's size. It's size compared to this. No. No. Obviously, they're they're they have a lot of other donors.
Speaker 1:The Rockefellers are just a fancy name because Toby and his wife have personally contributed $3,000,000 and the initiative is raising $10,000,000 this year from energy companies, family offices and private individuals. And his perch from his perch at Pittsburgh based EQT, a company with a market cap of 36,000,000,000, Toby Rice has preached the benefits of selling more American natural gas across the globe to reduce emissions and strengthen security of The US and its allies. Now he's waiting into a debate. Should impoverished societies be encouraged to rely on polluting fossil fuels to improve their fortunes, or leapfrog to intermittent renewables? There was this question about should Brazil be allowed to clear cut the Amazon rainforest, to pull forward industrialization?
Speaker 1:It's the world's lungs. Everyone suffers if that happens, but they would certainly benefit in the short term. So there's a there's a hot debate here, and he is engaging in it. Anyway, let me tell you about Cisco. Critical infrastructure for the AI era.
Speaker 1:Unlock seamless real time experiences and new value with Cisco.
Speaker 2:David Holes has hit the timeline. He says 5,000,000 humanoid robots working twenty four seven can build Manhattan in six months. Now just imagine what the world looks like when we have 10,000,000,000 of them by 2045. Now imagine the year 2100. Dyson sphere.
Speaker 1:Dyson sphere. Dyson sphere by 2100 is the is the correct, like, debate. Like, is it before? Is it after? But it's like around there.
Speaker 2:Keep keep going back to my land thesis. Yeah. It's like when when armies of of robots can build anything Yeah. Anytime, what what is actually scarce? In this case, think with 10,000,000,000 of them, I don't even think land will be scarce anymore.
Speaker 2:It's like, hey, we're making we're gonna build an island.
Speaker 1:We're gonna build another moon. We're building the moon. New moon alert. There's there's no New moon alert. Just build another earth and just throw it on the other side of the solar system.
Speaker 2:Yeah. Yeah. I mean, it's it's you know, right now we're talking about what businesses are unsloppable. Yeah. The next meta will obviously be unclankable.
Speaker 2:Unclankable. Other businesses.
Speaker 1:What's unclankable?
Speaker 2:What's actually unclankable when It needs send, you know, an army
Speaker 1:Well, figure out what's unsloppable, figure out what's unclankable, and then go invest in it on public.com. Investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service.
Speaker 2:Richard says SF guy eating a delicious blueberry. In eighteen months, everything will be blueberries.
Speaker 1:This is a perfect contrast to the to the other post. Just
Speaker 2:The hot dog the hot
Speaker 1:dog SF discourse. No. No. No. David Holes.
Speaker 1:David Holes is like, he's because I did David's seen humanoid robots. Like, he's he's he's lived in SF and and been around this stuff. Like, he's he's he's a true believer, and he's and he's sort of saying, like, I've seen what they can do, and I understand the exponential here. And now imagine 10,000,000,000 of them in a hundred years. Like it's gonna be crazy.
Speaker 1:And then you have Richard on the other side. Everything will be blueberries.
Speaker 2:I thought you were talking about the Delicious Tacos post. Said, I'm the CEO of a hot dog company. I worked on hot dogs for ten years and I wasn't prepared for what I've just seen. Your life is about to change. So what can you do?
Speaker 2:Buy as many hot dogs as you can. Buy stock in hot dog company.
Speaker 1:It's a good idea. I I I am long hot dog. I like hot dogs.
Speaker 2:Hot dog market map.
Speaker 1:Good with the kids. Everyone loves a hot dog.
Speaker 2:Hot
Speaker 1:dog It's all American. There's nothing better than a hot dog at a ball game. Except for fin.ai. That's better than a hot dog. It's the number one AI agent for customer service.
Speaker 1:If you want AI to handle your customer support, go to fin.ai.
Speaker 2:And Earl fundraising shows defense tech is still red hot.
Speaker 1:Pretty crazy.
Speaker 2:Eighty roof, one of the scoop athletes. Scoop.
Speaker 1:There it is. Scoop.
Speaker 2:She says, in case you missed it on Friday, we broke the news at Andoril's and talks it doubled its valuation to around 60,000,000,000 funding round. So if you were buying triple layered SPVs in Andoril at
Speaker 1:You're gonna make
Speaker 2:45, you might make it assuming you didn't pay three levels of ten percent one time.
Speaker 1:And assuming that the guy you bought them from Actually scorned and is now in custody of the Feds. That's a bad decision.
Speaker 2:The round is notable for more than just its price. While Andoril technically has both A and I in its name, it's not the AI centric type of startup that typically gets all the investor attention in the But current
Speaker 1:very unsloppable, right? You're not going to vibe code a drone. You're not gonna vibe code
Speaker 2:a Yeah. I don't know. I think that I think I think when you think about who's going to unlock the potential of AI for the government Mhmm. You think of Palantir
Speaker 1:Yeah.
Speaker 2:You think of Andoril.
Speaker 1:No. No. I I yeah. No. I I just mean in terms of like AI disruption.
Speaker 1:Like, it's a like, it's not something that you can you can vibe code a Fury drone. Like, that takes a lot of hardware, a lot of testing. You gotta blow a bunch of stuff up. You need a test range. You need government contracts.
Speaker 2:I I just don't yeah. Relationships built
Speaker 1:over decades.
Speaker 2:I think all these all these, you know, defense oriented businesses, even if they are building software Mhmm. Are quite a bit more insulated just because
Speaker 1:Oh, totally.
Speaker 2:The trust factor. And if if Andoril sells a product for one price and you have a small team coming together saying, you know, we're 10 people. We can build you the same thing
Speaker 1:Yeah.
Speaker 2:For half the cost. There's not quite as much pricing pressure because the government wants reliability. They want to set something up and use it for a really long time. They don't want to really take risks, etcetera, etcetera.
Speaker 1:Defense techs on a tear, Shield AI, a drone business that can also tap the AI interest, thanks to its autonomous software, is in talks to raise a $12,000,000,000 valuation, Bloomberg reported, and several other younger startups will likely raise money in the next few months. Paul Kwan, managing director at General Catalyst, said that part of the reason the firm is so optimistic about defense tech is because there are very few trillion dollar markets that are critical for global resilience, that are dominated by legacy vendors and which are experiencing both tech and geopolitical transformation. Yeah. The number of companies that fall in that bucket is pretty small. General Catalyst has invested in Andorol as well as other defense related businesses such as Ceronic and Helsing, a European rival to Andoril.
Speaker 1:As the world unfortunately braces for more wars, increased government spending has led to high prices high priced contracts for defense tech. Kwan said that the US department is realizing that defense tech is critical for deterrence. Kwan said he has been seeing he has also seen a shift among entrepreneurs, believing that many of the most talented founders are choosing to build for the defense industrial base. And you can check out the rest of the story on the information.
Speaker 2:A lot of attention's been focused on Open Router. If you go on Open Router and look at the rankings, you can see that Chinese open source models are completely dominating charts.
Speaker 1:MiniMax is DHH talking about Kimi K2 is now a daily driver for squashing bugs at 37 signals. Very interesting data point. Since a lot of this can be I think the Open Router stuff can be a little hard to contextualize because there's some amount of volume that doesn't get captured in Open Router, obviously.
Speaker 2:It's the majority of the volume is not captured.
Speaker 1:You think so?
Speaker 2:Yeah. Yeah. According to Zephyr, who's very on it, it's one to 2% globally.
Speaker 1:Do you do you you think that's about right?
Speaker 3:Yeah. Definitely. I mean, if you just compare, like, the like, it's if you look at the actual, like, token count, it's, like, in the billions for, like, over, you know, a week or something Yeah. Where, you know Yeah.
Speaker 1:You'll see I
Speaker 3:remember Demis over the he was, like, we're doing, you know, quadrillion tokens every
Speaker 2:month or something.
Speaker 3:So it's, the the scale is completely different.
Speaker 1:Quad.
Speaker 3:And also, it's, like, no one is gonna be using the big labs models on this because they would just hit the actual API. It's just easier. Right? So it's like if I'm gonna be calling Anthropic, I I'm probably just gonna use the Anthropic API. Yeah.
Speaker 3:I'm not gonna go through OpenRatter. Yeah. So you should expect it to be the the open source models because, like, one of the good things about OpenMatter is that it has, like, all the different inference providers
Speaker 5:Yeah.
Speaker 3:Put together. So, like, you know, there's there's a ton of companies that host the different open open models. Yeah. So it like aggregates them all together.
Speaker 1:Yeah. And also, I mean, doesn't this doesn't account for token generation in consumer LLMs. Like and that's a huge thing. Like Google AI Overviews is, I think, the most used LLM product in the world, something like that. And that's technically generating tokens.
Speaker 1:When you just hit Google search and it answers with an LLM query, that's token generation. And then there's stuff that's happening in Gemini app, Claude app directly, not even coding. Like, no one's using OpenRouter within their consumer app, unless it's like some third party thing. But most of them are going. Anyway, let me tell you about Cognition.
Speaker 1:They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team. Let's continue with the timeline. Jacob Rintimaki has a post here. He says, unfortunately, it is not seen as cool to say, but the beatings will continue until more people internalize this.
Speaker 1:He's talking about Rune, saying, I don't think this is wrongly true, but it's hard to fight open source copium because people act like you shot a dog or something. Because Anton, two years ago, back in 12/21/2023, said AGI is more likely to come out of someone's basement, some mega merge Hermes 4,000 than a giant data center. And I think everyone agrees with this now, but it was very unpopular to say at time. I remember John Ludwig had a post about open source AI not being, like, on the critical path to AGI because of the scaling laws and a whole bunch of other economic factors. Like, he sort of predicted that Meta would stop being so focused on open source because it just doesn't make sense to spend a trillion dollars or $100,000,000,000 on infrastructure that then you capture so little of the value of.
Speaker 1:Yeah. And I think that's why Anthropic has not been very pushing, like, hard on open source. And even the other superintelligence initiatives, not many of them have been open source. The open source question has been a very different business model. But it is very important in terms of model commoditization and terminal economic equilibriums in the AI lab battle.
Speaker 2:Oren Hoffman is sharing that Ozempic is bad for business.
Speaker 1:Yes.
Speaker 2:A few months ago, someone told me they had heard a rumor that a banker hedge fund had banned its traders from taking Ozempic, Wegovy, and other GLP-one weight loss drugs. The theory, as I understood it, was something like traders need to make quick decisions based on gut instinct, and GLP-1s mess with your gut instincts. You're not hungry for snacks. You're not hungry for profits. You lose your edge.
Speaker 1:It is
Speaker 2:funny Warren says GLP is getting banned by hedge funds, maybe by sales teams too. Yeah. Killing your grind set.
Speaker 1:It is funny that doesn't it isn't GLP glucagon like peptide? Isn't that a peptide that's secreted by the gut? And so it's like your gut instinct is actually tied to your gut. Like, maybe it's just nominative determinism, but it is funny that those things wound up being
Speaker 2:Your gut instincts for some people saying put on mass. Scale. It's time to scale.
Speaker 1:Time to bulk. Bulking seasons here. Get off the GLP ones and start levering up, going risk
Speaker 2:Doctor Cameron Maximus says, guess what increases drive testosterone, a micro dose of tirzepatide to cut down on physical appetite, a macro dose of testosterone to amplify psychological appetite. The solution is We're GLP-1s only if you're taking them solo. You've be taking a full stack.
Speaker 1:Did you see bone GBT saying, turns out you really do gotta be hungry for it. It's fantastic. Fantastic. As is Gusto, the unified platform for payroll benefits and HR built to evolve with modern small and medium sized businesses.
Speaker 2:And TBPM. And
Speaker 1:TBPM. Claude Sonnet 4.6 has improved on benchmarks across the board. We touched on this yesterday, but particular particularly outstanding in office tasks in agentic financial analysis, you can see this being baked into Claude for Excel and a lot of knowledge work. Lucas Beyer over at MSL says, formerly OpenAI, I usually look at which benches the small model surpasses to its previous big brother. If it's only a few, I think that gives a hint as to what they focus on.
Speaker 1:Here, it is only agentic financial analysis and office tasks. It's just a heuristic, of course, but interesting nonetheless. And I wonder if that's I wonder if if Tyler, how how important is is speed between between Sonnet and Opus? Is is Sonnet consistently faster or just cheaper?
Speaker 3:Yeah. I think it's usually faster.
Speaker 1:Faster. It's just a smaller model. Yeah. Yep.
Speaker 3:And then there's Haiku, right, which is the smallest one.
Speaker 1:Because I'm wondering if if if in in the coding domain, there's a little bit more tolerance for, okay. I've delegated this task. It's gonna go cook, and then I'll come back and review the code, review the pull request, whereas Maybe but but in finance.
Speaker 3:This was the whole thing about codex. Right? Because codex was much slower for a while
Speaker 1:Sure.
Speaker 3:Before Srebros. So people would be like, oh, codex is so bad compared to Cloud Code even though, you know, a lot of people internally at OpenEye were saying, oh, no. Actually, codex is is way better. It's just because they're used to having the internal model that's run on the better hardware. Right?
Speaker 1:Yeah. Yeah.
Speaker 3:Yeah. So I think speed is actually it plays a, like, very large role. So even if you have a, you know, smaller model, it's much faster. Yeah. Even if it's a little bit worse, I think there's still a lot of, like if you're iterating a lot, that can actually be much much more efficient.
Speaker 3:Yeah.
Speaker 1:I I I I'm just thinking, like, in terms of, like, an Excel copilot for someone who's spending their time in Excel, not in GitHub. Will speed be a killer feature for them if they're currently like, Yeah, I've tried it, but it's really slow. It actually slows me down because it takes twenty minutes to respond. It gets it 80% of the way there, but I can do 90% in fifteen minutes. So I'm not using that model yet.
Speaker 1:I'm not excited about that. Maybe this is something that speeds things up. But of course, there's ways to just inference the model faster, even even the big guys.
Speaker 3:Yeah. I mean, I I think when a lot of the agentic browsers Mhmm. First came out, one of the like benchmarks I would I would use is like editing a
Speaker 1:Spreadsheet?
Speaker 3:Yeah. Sheets. And it was so slow that it was like it was working, but it's just so unbearably slow. There's like literally no point of using it.
Speaker 1:Yep.
Speaker 3:So I think, yeah, speed is like kills.
Speaker 2:What about hair bench?
Speaker 1:Hair bench? What's hair bench?
Speaker 2:Gabe says, Jordy needs to ring Tyler with him when he gets his haircut.
Speaker 1:Haircut? Haircut alert. Haircut alert.
Speaker 2:I I did send Tyler Tyler asked
Speaker 1:Yes.
Speaker 2:And I sent him my barber's information. Okay. They're working on it.
Speaker 1:Haircut alert. We gotta get a card up. Jordy doesn't wanna do it, but I think we should put up a card for Jordy's new haircut. We don't like secret haircuts. If you are heading to New York Stock Exchange, you need a fresh haircut and we are partnered with the New York Stock Exchange.
Speaker 1:Do you wanna change the world? Get a haircut and then go raise capital at the New York Stock Exchange.
Speaker 2:Great call, John. Duane says, what is going on at Anthropic? They're going after people with multiple paid max accounts. You're paying full price multiple times, and they're treating you like a criminal. That's what Dario is trying to speedrun you.
Speaker 2:And on Reddit, on Claude Code, it says, Claude just banned having multiple max accounts since around a few hours ago. Signing into another account has stopped working.
Speaker 1:I think some people do need to have their multiple max accounts banned. They're just they're not building anything useful. They're wasting tokens, and they're just creating endless endless setups and tool chains and MD files. And unless you're actually shipping something that's gonna drive business value and be used by more than one person, you only get one account. I'm with I'm with Claude on this.
Speaker 1:Stop wasting tokens on on your silly thing. I was reflecting on, like, like, the I I I was texting you this last night, like like, am I dumb and out of ideas? Or is all the software I want just illegal? Because I was like, all the things that I want are things that could exist This but is they can't exist for business reasons. Yeah.
Speaker 1:Like, I want I want an Apple TV app. Yeah.
Speaker 2:Give the example. So the I example was
Speaker 1:want an Apple TV app that has Netflix installed. It's like, why doesn't that why doesn't Netflix integrate with Apple TV? Netflix doesn't wanna get aggregated. They're an aggregator. They want you to open that app on the Apple TV.
Speaker 1:So the Apple TV app doesn't have Netflix content even though you have the Netflix app installed on Apple TV, the device. And I was saying, like, I I subscribe to all these different news sources. I want, like, an Apple News that aggregates them all, a Google Reader that aggregates them all. I pay, but I'm still logged out of a million things. Like, I'm in some social app, then it opens in a Safari web browser.
Speaker 1:I'm not logged in. There's a paywall. It's it's annoying to log back in. I want something that just, like, aggregates all my news sources and jumps the paywall. Well, that's not a coding issue.
Speaker 1:That's a business issue. They want you to log in for a reason, and they have a decision to that. So I don't know. I think we're still early in the broad distribution of people building custom software and experimenting with things. But at the same time, we've had great writing models for a long time.
Speaker 1:And anyone we know, everyone could write their own books, everyone could write a better ending to the end of Game of Thrones and send it to you as a text file right now with the current models. And I haven't read anything that I've been like, oh, yeah. This is really good. I gotta read this this AI generated book. So I don't know.
Speaker 1:There's like some weird bottleneck there that it's like it's it's it's not it's not a barricade
Speaker 4:for now.
Speaker 2:Gabe is offering. Yeah. Sounds sounds very illegal.
Speaker 1:Yeah. Yeah. This is popcorn TV or or it's called Utorrent. I I know. I know.
Speaker 1:I know. Xbox Media Center.
Speaker 2:Try to play by the rules.
Speaker 1:Xbox Media Center. But that's the thing is that is that, yes, that streaming site, like, yes, you can vibe code that. But, like, that can't actually get to scale. It can't actually have an impact in the economy because it's breaking the rules. And there's a lot of there's a lot of AI stuff that feels magical.
Speaker 1:And you see this with Cdance from ByteDance, where it's it's in the journal today. TikTok's Chinese parent develops movie app. I love that headline. In in in on Twitter, it's all it's all, C Dance just destroyed VO three and Sora two. But in the word in the journal, it's TikTok's Chinese parent develops movie app.
Speaker 1:And there's something interesting here. So, Singapore is where it's based. Singapore. The company behind TikTok has developed an artificial intelligence model that can turn a single text prompt into a high quality video with a storyline, scene changes and distinctive characters. The the new AI video creation model from Beijing based ByteDance is generating buzz in China and backlash in Hollywood over copyright issues.
Speaker 1:It shows how ByteDance, known for creating TikTok, is emerging as a rival to OpenAI and Alphabet's Google in the race to build tools for making AI movies and other video entertainment. China's visual models have been very, very competitive, said Steve Long, a video game developer in Helsinki who participated in beta testing programs. ByteDance recently ceded control of The US version of TikTok to an investor group. Global users of another ByteDance app
Speaker 2:And Thompson was going off on on the
Speaker 1:Cheeky pint?
Speaker 2:On Cheeky pints.
Speaker 1:He's a couple of Cheeky pints on that guy. He's gonna let loose.
Speaker 2:He let loose. He'd be He's saying we got the worst No. He said he said we got the worst possible outcome with with TikTok where they still control the algorithm Yep. And we violated property rights.
Speaker 1:Rough. Shots fired.
Speaker 2:Of course, still still in motion. Yes. And but for now, not doesn't seem like it's been fully solved.
Speaker 1:But this was the interesting paragraph that I wanted to highlight in this journal Global users of another ByteDance app, CapCut, a popular video creation and editing app, will soon have access to CDance two, its latest AI model for creating videos, the company said. The model is already available to users on CapCut's Chinese version. And so I mean, you've seen on Instagram Reels, like, are a ton of CapCut editors out there. I get served how to edit in CapCut, and I don't even really use the app. But it's clearly incredibly powerful.
Speaker 1:There's a whole bunch of cool features in CapCut that would basically be After Effects plug ins and would probably take a long time to configure, but just come out of the box and it's just a couple clicks. So you don't have to know any code or install anything. It's just there. And now you're gonna be able to generate CDance videos. We'll see how long you can still generate Larry David and Marvel characters.
Speaker 1:That stuff will probably get pulled back on eventually, at least in the CapCut American version. But you're going to see a lot more slop in the trough. What do you think?
Speaker 2:Handle says, just had to drop in and say thanks for the gift suggestion I got my girl MongoDB for Valentine's Day. That's great
Speaker 1:to hear. That's so great to hear. I'm so glad. It really is the perfect Valentine's Day gift, MongoDB.
Speaker 2:Dean Ball
Speaker 1:Yeah. Before we do this, let me tell you about Phantom Cash. Fund your wallet without exchanges or middlemen and spend with the Phantom card.
Speaker 2:Dean Ball says if the Department of War and Anthropic can't agree on terms of business and they should do business together, I have no problem with that. But a mere contract cancellation is not what is being threatened by the government. Instead, it is something broader Mhmm. Designation of Anthropic as a supply chain risk. This is normally applied to foreign adversary technology like Huawei.
Speaker 2:Mhmm. In practice, this would require all Department of Work contractors to ensure there's no use of anthropic models involved in the production of anything they offer to DOW, every startup and every Fortune 500 company alike. This designation seems quite escalatory, carrying numerous unintended consequences and doing potential significant damage to US interests in the long run. I hope the two organizations can work out a mutually agreeable deal. If they can, I hope they agree to peaceably part ways?
Speaker 2:But this really needn't be a holy war. Anthropic is in Google in 2018. They've always cared about national security use of AI. They were the most enthusiastic AI lab to offer their products to the national security apparatus. If anthropic run by Democrats, whose political messaging is anthropic run by Democrats whose political messaging sometimes drives me crazy?
Speaker 2:Sure. But that doesn't mean it's wise to try to destroy their business. This admin believes AI is the defining technology competition of our time. I don't see how tearing down one of the most advanced and innovative AI startups in America helps America win that competition. It seems like it would straightforwardly do the opposite.
Speaker 2:The supply chain risk designation is not a necessary move. Cheaper options are on the table. If no deal is possible, cancel a contract and leverage America's robustly competitive AI market to give business to one or more of Anthropic's several fierce competitors. Mhmm. And there was also reporting this morning that Anthropic had approached seventeen eighty nine Capital
Speaker 1:Bruce Buskirk. He's been
Speaker 2:And and Don Junior. Yeah. And they turned him down.
Speaker 1:Turned down?
Speaker 2:Turned him down. Jack. Well They turned down from from 1789, they said not interested.
Speaker 1:I I think I for
Speaker 2:a logical reason.
Speaker 1:Think I know a little bit about why there might be so much pushback against Anthropic. I mean, you saw that the SONNET 4.5 people are really excited about this model, but it completely fell flat on its face when asked with a basic question, Why did clavicular get frame mugged? Sonnet 4.5 responded, I'm not familiar with clavicular as a specified person or entity or what frame mogged means in this context. Could you provide some more context? So it's just like when you see something like that happen, it it calls into question everything about a company.
Speaker 1:It's just like, how could you let this happen with so little worldly knowledge as to not understand the significance of clavicular's frame mugging. Anyway, overheard in SF, a VC was giving advice. OpenAI and Anthropic are like Godzilla. You need to find an alleyway to hide in. What a funny thing to say.
Speaker 1:This is Ben Hilack. He says, Don't take advice from junior VCs. There's something good there. I mean, the models, you know, if you're in the path of models improving, you will get stomped like Godzilla. But there's still plenty of opportunities all over the ecosystem, especially if you're not doing something that's in software.
Speaker 1:I'd like, know, like, there's plenty of startups that's just like, don't touch software.
Speaker 2:With code.
Speaker 1:Just don't do anything with technology.
Speaker 2:Don't don't do anything with a website.
Speaker 1:Don't do anything with a website.
Speaker 2:You need a website to do business.
Speaker 1:I'm short. I'm passing.
Speaker 2:You're correct. It's over.
Speaker 1:It's over.
Speaker 2:It's over. It was fun.
Speaker 1:No. But clearly, I mean, there's plenty of like brands and products and technology and all sorts of things to build and
Speaker 2:Well, we are working on we are working on an alleyway project
Speaker 1:Oh, yeah?
Speaker 2:With with Riley Walls.
Speaker 1:Oh, okay.
Speaker 2:Yeah. I'm not gonna share anything else on this.
Speaker 1:We are very excited.
Speaker 2:Yeah. We are we are cooking there. So more to come.
Speaker 1:Well, there are people who are doing well in spite of Godzilla stomping around America. And one of them is Eleven Labs. Build intelligent real time conversational agents. Imagine human. Re imagine human technology interaction with Eleven Labs.
Speaker 1:I like that Godzilla sound effect. That's good. For when the labs are on a tear.
Speaker 2:Let's pull up this video
Speaker 1:from Vuco Capital. This video. Dollars in CapEx for this. This is this is what if Donald Trump was from other countries?
Speaker 2:He was born in other countries.
Speaker 1:This is the the fidelity here is is really really high. Dmitry Trumphal. This stuff is probably going mega viral on TikTok now. It's going mega viral
Speaker 2:on So Buko Buko says 2,000,000,000,000 in CapEx for this by the way, kind of like saying like it's silly but I look at this and and think
Speaker 1:It's worth every penny.
Speaker 2:Completely worth completely worth it even if even if the 2,000,000,000,000 just created this one video. Yeah. Really good. We're entering the post post slop era.
Speaker 1:Back to taste gate. Young macro just chiming in on taste gate. Is taste valuable? I don't know. I can't tell.
Speaker 1:But maybe it is. Some people say it is. I'm not really going to weigh in. But young Macros weighing in. He says, many will not want to hear this, but taste is just g, intelligence, with sufficiently varied training data.
Speaker 1:Steve Jobs had taste because he was, like, plus three standard deviation IQ and trained on calligraphy class and being homeless smoking weed in India or whatever. Meanwhile, his IQ match now microdoses amphetamines to narrow the training set and ends up drone maxing at Citadel Securities with a great transcript. Sorry, Chud. The flunker will get the cake this time. There is something interesting there.
Speaker 1:I've I've just the idea of, like, varied wild life experiences being valuable to to generate, you know, it's not exactly out of distribution training data, but just a life well lived will translate into innovation and taste or just like new ideas as opposed to being tracked and funneled into Citadel Securities where it also works.
Speaker 2:I I I haven't I haven't really waded into the taste debate at all Yeah. Just because it it it's not everyone's trying to define it in their own way. Yeah. It's something that in some ways you people like say, oh, you can't buy it. Yeah.
Speaker 2:You can't buy it in the fullness of a company because I think like taste comes from the founder or the founders. And it just kind of like, you know, percolates through the organization indefinitely. Mhmm. Like, there's companies that have a billion dollars to spend on marketing Yeah. That just functionally can never be good at marketing because the founder likes to be heavily involved in marketing and they don't have great marketing taste Mhmm.
Speaker 2:Or instinct or what whatever this thing is. But it just feels like everyone's I don't know. I'm for taste. I'm against taste. I I have like, you know, it
Speaker 1:Fun fact. If you hold your nose, you can't taste as well. So if you're trying to be tasteful, don't hold your nose.
Speaker 2:Well, COVID wiped out a lot of people's
Speaker 1:Oh, yeah. They lost their smell.
Speaker 2:Yeah. Had a Some friends. Some good friends. Really? They got COVID in their household recently fully wiped out.
Speaker 2:So that household had zero taste. Zero taste. They traded all their cars for Lamborghini in a span of a week. I was like, what's going on, guys?
Speaker 1:Extremely tasteful.
Speaker 2:I don't
Speaker 1:know what you're saying.
Speaker 2:What's going on, guys?
Speaker 1:That's amazing. Well, speaking of taste, let me tell you about Figma, the most tasteful sponsor. Ship the best version, not the first one with Figma. Introducing Claude Code to Figma. Explore more options.
Speaker 1:Push ideas further. Moving on. What is self evidently true?
Speaker 2:AGM says, all this progress in Gen AI, not a single serious piece of culture other than slop shorts. Mhmm. I would take that back. I would say granny hit my granny got hit with a bazooka is a serious piece of culture.
Speaker 1:But that's not AI.
Speaker 2:I know. Okay. I'm just saying
Speaker 1:I think what he's saying is that there's always products in generative AI, and no one has, like, one shotted, like, make something amazing, and it just does it. Like, there's always this, like, Herculean effort and inspiration. Like, we always go back to Harry Potter Harry Potter Balenciaga. Even that Trump video is, it's only funny because of this con context. And, like, it's not purely just, like, oh, okay.
Speaker 1:The the Gen AI did it, and and it's certainly not a serious piece of culture. It is a slop short. That's fair.
Speaker 2:All this 10x vibe coding and not a single new compelling consumer Techies do this all the time.
Speaker 1:Confusing Wait. Wait. Tyler's I
Speaker 3:mean, he didn't try Cloud With Ads.
Speaker 1:Oh, yes. That's true. That's true. Cloud With Ads was was definitely a compelling consumer app. Well, lasted.
Speaker 1:RIP. Techies do this all the time, confusing being Gutenberg with being Luther, the maker of the technology of the culture for the culture itself. Hephaestus forges Achilles' armor in the Iliad, but he's not the hero and barely appears otherwise compared to other gods. Techno capitalism might make Hephaestus the rich guy on Olympus, but Homer is going to write him out of the script anyhow. Brutal.
Speaker 1:Mogged. History mogged.
Speaker 2:Jeremy Gaffan says humans don't belong behind desks. It's not our end state to be factory workers who replaced hammers with keyboards. Everything that can be automated should be automated. Hammers were meant to hit your face. Hammers were meant for bone smashing.
Speaker 2:Yeah. John Arnold said, everyone deep in tech or finance is in full freak out mode over the pace of AI progress over the past two months. Own index funds and you barely notice but specific sectors are exploding, digital and power infrastructure, well, anything related to human behind a desk is plummeting. Interesting.
Speaker 1:Don't strike your face with a hammer. Strike your crowd with CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches.
Speaker 1:Next guest is available.
Speaker 2:We before that Yes. We we've gotta talk about Japan's largest toy maker
Speaker 1:Toilet maker.
Speaker 2:According to a UK based activist investor is an undervalued and overlooked AI play. HALASER Capital sent a letter to the board of Toto last week to make sure Oh, make more of its advanced ceramic segment saying it holds a crucial position in the semiconductor supply chain. Segment generates 40% of TOTO's operating profit. Sounds like a insane headline but Yeah. We should dig in.
Speaker 1:No. Actually maybe sort of makes sense if you need ceramics in the semiconductor supply chain. I wonder if and the funniest outcome here is, you know, how, like, we we can't get PS sixes anymore. Playstations are out of stock. Like, will you be able to buy a toilet in the future?
Speaker 1:Like, no. Like, you will need to sacrifice your new toilet in favor of advancing the techno capital machine Right.
Speaker 2:Ryan Ryan artificial intelligence. Dehaney is responding to Buko saying, what stage of the cycle is this? And says, launch the nukes. Write it all down to zero. Who cares anymore?
Speaker 2:Because there's a business insider article called after three years of forcing myself to love venture capital, I quit and became a silent disco DJ in Bali.
Speaker 1:Let's go.
Speaker 2:So that's where we're at. That's where we're at.
Speaker 1:But Well, we are at the point in the show where we will bring in our first guest, Blake Dodge from Pirate Wires. You can go and subscribe at piratewires.com. Blake, welcome to the show.
Speaker 2:How are
Speaker 1:you doing?
Speaker 2:What's happening?
Speaker 9:I am great. How are you guys?
Speaker 1:We're fantastic. What has been keeping you oh, well, first, introduce yourself since it's the first time on the show. I'd love a little bit of your background and then some of what you've been focusing on at Pirate Wires recently.
Speaker 9:Yeah. Totally. So I basically started my career as a journalist at Business Insider.
Speaker 5:Oh, cool.
Speaker 9:I covered health care and then technology. I was doing, like, big scary investigations with a lot of documents and, you know, secret sources and stuff. And I got a little bit not burned out, maybe a little bit burned out. I wanted to tell more optimistic stories about what was going on in tech. Yeah.
Speaker 9:And so that's why I joined Pirate Wires about a year ago, where I've done a lot of that work kind of like the white pill case for why you should believe in someone. But then we also do we do a lot of work that I think centers original thought Mhmm. And maybe the kind of in the spirit of the contrarian. Yeah. We'll look at an issue, what everyone else is saying, and then kinda tell people, actually but actually, this is what you should think.
Speaker 2:Truth
Speaker 9:is really. Yeah. And so lately, we've been doing a lot of that with the proposed wealth tax.
Speaker 5:Sure.
Speaker 9:In in California, we've kind of flooded the zone there and been duking it out actually with the New York Times and the Wall Street Journal. So I kind of feel like I'm back at BI all of a Exactly.
Speaker 1:Well, yeah, what has been the response? I mean, you've interviewed a ton of billionaires in California. It feels like the base case is just like everyone leaves. Like, maybe they're not all loud about it, but, you know, Mark Zuckerberg is not out there, but, like, he did buy a place in Miami, and it seems like he might be Miami resident soon.
Speaker 2:Yeah. There's there's kinda two waves. There's people that were like, I'm gonna get out in 2025, so I never have to pay the tax. Yeah. And there's a second wave, which I think is the Mark Zuckerbergs that are like, I like, if this goes through, it'll get fought.
Speaker 2:Yeah. I might not have to pay it, but then I'm still kind of like Hedging. Potentially hedging Yeah. And getting out. And so I think there's again, this is we're kind of in the midst of the second wave of people that are like, I might have to pay it once, but I'm certainly not gonna pay it every year Every for the rest of
Speaker 1:my Yeah. Life.
Speaker 9:Yeah. Yeah. A couple weeks ago, Mike Solana published a piece where he interviewed more than 20 billionaires in the state of California, which is like wow. Might make him the most well sourced tech journalist ever, but they literally all said that they were leaving or planned to leave. So that's really striking.
Speaker 9:That's like a meaningful percentage of the total billionaires in California. And what's really interesting is they're not they may be leaving because they don't want to pay the tax, but, actually, the tax is retroactive, so many of them many of the folks who are leaving probably will still have to pay it if it goes through, but they're leaving anyway because of the kind of overarching political landscape of California. Like, they're they're just kind of over it, they find the kind of lefty politics to be too risky Mhmm. Not only to build wealth, but to build companies. Sure.
Speaker 9:There's language in the proposed ballot measure that has really thrown people through a loop where so the government has this challenge of tallying people's net worth, you know, which is not easy. When it comes to founders of private companies, they're using kind of a shortcut where founders will be presumed to be owners of anything they control. Mhmm. You guys have probably seen the scary math with this
Speaker 1:Yeah.
Speaker 9:On your timelines, but basically, since founders often have their shares often come with outsized voting rights
Speaker 1:Yep.
Speaker 9:What this means is you could be presumed to be an owner of 10 times the value of your actual economic position. Yep. And that's all subject to a rebuttal process and stuff. It's not supposedly meant to be the final word. But I think founders hear that, and it's like, okay.
Speaker 9:Like, this is this is a significant risk to to to the business and to my longevity in the state.
Speaker 1:How are you thinking about the probability that this actually passes? It feels like something that would be broadly popular amongst a direct in a direct democracy scenario. I saw some protests that did not seem very widely attended, and so it doesn't it it seems like it's hard to marshal 50,000,000 people or 10,000,000 people that are against this because it's not a tax that affects everyone.
Speaker 9:Yeah. Yeah. The pro billionaire protest for some reason was not well attended in San Francisco. I have no idea
Speaker 2:why. Not by billionaires. Yeah.
Speaker 9:It's like Gary Tan with, like, one sign.
Speaker 2:Did Gary go?
Speaker 1:I don't think he went.
Speaker 9:I actually don't think he
Speaker 1:went. No.
Speaker 9:Yeah. So the politics on the other side are a bit better because the headline of this whole thing is, let's tax billionaires 5% of their net worth one time for this, like, you know, emergency of paying for health care for poor people.
Speaker 1:-Yeah.
Speaker 9:-And so for Medicaid.
Speaker 1:-Yeah.
Speaker 9:-And so I think that does have a certain political appeal if it does make it on the ballot. We're sort of hearing, like, mixed reviews on its chances. Mike did some reporting that went out just today, actually, that suggests their signature gathering may be a little bit behind. And then you have a ton of opposition in state. Like, Gavin Newsom hates this thing.
Speaker 1:Mhmm.
Speaker 9:He's been meeting with Dave Reagan, the head of the union, who sponsored the ballot measure to try and get him to stop. There's also like teachers unions and and kind of some surprising adversaries.
Speaker 2:Well, yeah. There's other unions that are like, hey, you're gonna you're you're trying to you're you're trying to get this tax for purely your own benefit. Like, we you've gotta cut us in. So it's like the unions, even if they might have been in favor of it, if they were gonna get a piece of it, there's there's quite a number of groups that are just saying, like, I don't want this to happen if I'm not getting the right. Right?
Speaker 2:Is that is that
Speaker 9:that is kind of how it works. Yeah. Because the unions in different special interests use the ballot proposition process to raise money, like, or to to to get more funding streams. And Mike learned specifically that the teachers union is feeling kind of left out in this particular scenario.
Speaker 2:So let's how how has Reagan reacted to everyone leaving? How how are they are they processing this? Because because, you know, play this out.
Speaker 1:Yeah. You have a number in mind. You're like, I'm getting 5% of 60 people's wealth, and that's probably like a couple billion dollars. And then there's and then 20 leave and you're like, okay. Now I'm getting like 3,000,000,000 and then another 20 leaving, like,
Speaker 5:now I'm getting 1,000,000,000.
Speaker 2:Yeah. There's also an insane power loss.
Speaker 1:Yeah. Right. Oh, yeah. Sure. So so The biggest ones leave.
Speaker 2:People the people that stay might be the
Speaker 1:The guy who's at 1.2 is like, I guess I'm good for my 20 mil. You can take it.
Speaker 9:Yeah. I mean, so far, the the folks behind the ballot measure have not acknowledged that people are actually, in fact, leaving. Yeah. They continue to call wealth flight largely a myth
Speaker 1:Mhmm.
Speaker 9:Which is crazy. We'll be talking to these people on Twitter, like, we literally spoke to to 20 of them. They literally are leaving the state. It's not a myth. But they point to research, mainly looking at the movement of millionaires and just generally wealthy people after taxes are increased.
Speaker 9:Mhmm. And it's true that in those cases, there's not a lot of mobility, but I think they have made
Speaker 4:Well, is
Speaker 3:part of the strategy are the same.
Speaker 2:Is is part of the strategy that this is the best possible branding for attacks like this and it and this type of like campaign focused on billionaires one time is how you get something like this passed. Then once it's passed, you'll have the ability to kind of like reduce reduce the set of requirements to qualify for it and you can eventually get down and be eating off of the plate of all Californians, middle class, etcetera.
Speaker 9:Yeah. I'm actually I'm staring at a quote that I have here in my last story. There's a couple of academics whose work, like, heavily influenced this wealth tax and pretty much all wealth taxes globally. One of those men is advocating for a two percent globally coordinated billionaire tax where all of the countries kind of get together and agree they're gonna do this. And he says
Speaker 2:Sort of like a one world government.
Speaker 9:I literally, in this quote, have a screenshot of Michael Gibson's
Speaker 1:Oh, yeah.
Speaker 9:Summary of the Thiel Antichrist lectures. So, yeah, he says, it's clearly far from enough, but also what history shows is that what's most difficult is to move from zero to something positive. And once you have something positive, even if it's 2%, then it opens up a realm of possibilities. And so they say it's one time, they say it's an emergency, but clearly
Speaker 2:Yeah. What what's the takeaway from The Netherlands? They passed this 36% unrealized capital gains tax. Mhmm. It's the it it excludes, I think, real estate and start up equity.
Speaker 2:But what's the thought process there? It seems super bearish for the country as a whole. But Mhmm. What any any learnings?
Speaker 9:I haven't looked at that one specifically. I know that internationally, these wealth taxes do have a pretty dismal outlook. Mhmm. The cycle is kind of
Speaker 2:It's very American to be like, we can make it work. Built everywhere else, but it'll work here. Yeah.
Speaker 9:And it's funny too, this this the they're still saying wealth fight is a myth, but part of why these other wealth taxes tend to go poorly is because the wealth leaves.
Speaker 1:Yeah.
Speaker 9:So
Speaker 1:Can you give us a white pill, something that I I don't think, from a comps perspective, don't tax me is gonna be effective for the billionaire class. But what should they be focused on in a world where a lot of people are seeing billions of dollars in wealth creation from what they see as slop, what they see as scams, what they see as a variety of water usage, energy price, blah blah blah. What what are the white pills that you think tech has delivered or is in the process of delivering over the past few years and into the future?
Speaker 9:Yeah. I mean, that's the question of the hour because inequality isn't continues to get worse Mhmm. And kind of fuels the politics behind these things.
Speaker 1:Yeah.
Speaker 9:I'm kind of a Gundo stan. Like, I I believe in this patriotic vision for tech
Speaker 1:Yeah.
Speaker 9:And this idea of keeping regular people in mind and building businesses that last and create value and don't just kind of addict people to things that they shouldn't be doing or shouldn't be spending their money on.
Speaker 1:Mhmm.
Speaker 9:And I think, you know, who knows what billionaires could do? Like, there's a lot of ideas out there. Mike Salana actually just wrote a Christmas wish list for billionaires with, like, 20 of these really beautiful white pill ideas. One of the easiest things is, you know, building like beautiful public works, libraries, statues, like things that people can see with their own eyes and feel gratitude about. Whereas right now,
Speaker 2:I feel Yeah. Like It's like it it's not that compelling to be like, don't hate me. I built this short format. Instead of like the
Speaker 1:public library, it has the Rockefeller name on it or something. Like there's a lot of examples as you walk through New York City where you see a beautiful building and you're like, oh, yeah. And that's free to the public now. I I I'm a big fan of, like, the Hearst Castle. Like, William Randolph Hearst, like, built this castle for his entire life, spent all his money, died before it was even done,
Speaker 2:and then just Or or even in California, the the, like, really ramping up something like an Adopt a Highway program Mhmm. Like driving around LA. Mhmm. The roads are just so so so bad.
Speaker 1:Yeah. But the tangible yeah. The tangible thing that you can see is is very very it's very impactful as opposed to like the the the anonymous donation that just kinda works its way through the economy. Might be more impactful, but certainly less grounded in reality. Anyway, where can people find you?
Speaker 1:Sign up for Pirate Wires, follow you on X. Where else are you active?
Speaker 9:Yeah. Yeah. I'm on X. I'm at dodgeblake, piratewires.com. Fantastic.
Speaker 9:We're covering all this stuff every week. We've really flooded the zone and And I I feel like, too, we we're we're pro tech in the sense of not being anti Yeah. But we also tend to ground things in a set of values which I think is a little well, I love it, personally.
Speaker 1:I'm glad. That's fantastic. Great. Well, thank you so much for taking the time We'll keep following to come chat with us, and we will talk Goodbye. You Cheers.
Speaker 1:Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy apps, servers, databases, more while Railway automatically takes care of scaling, monitoring, and security. And with that, we will kick off the Lambda Lightning round because we have Freddie DeVar from Substack. He's an independent writer.
Speaker 1:We're bringing Freddie into the TVPN UltraDome from Let's do it. The restream waiting room. Freddie, how are you doing?
Speaker 5:Pretty good. Although, you know, from Substack still never sounds as cool as
Speaker 2:Sorry.
Speaker 5:From the Wall Street Journal or whatever. Whatever anybody says about, like, independent media, it's just never gonna catch up, but that's okay.
Speaker 1:Yeah. I don't know. From Do you think
Speaker 3:Substack should
Speaker 1:do a bundle? Do you think Substack should do a bundle? This is a big debate.
Speaker 5:It's the thing is is, like, it's like the same question about, like, why can't I just pay a dollar for the New York Times article I want? Because the reason why is, the finances just don't work. Mhmm. I would like, if I would love to be able to do that from a standpoint of, like, getting people to read my stuff Mhmm. But my financial life would collapse.
Speaker 5:Like like, it's it's getting that that regular income and that sort of makes this possible.
Speaker 2:Yeah. I think I think my view on it is I think the like a a bundle that is just a is systematized via a platform Yeah. Is gonna struggle. But a bundle that a where you get four or five writers that just basically say, we're gonna build a media company together, that can work. Yeah.
Speaker 2:Because there's just so many other small things you need to do around compensation and what's fair and who's doing what and all all these different things that I think are when you have a bunch of personalities coming together, it's hard to just have it be entirely in code.
Speaker 1:Anyway, let's Yeah. Move
Speaker 5:problem is that like eventually, if you bundle enough people, you just have a newspaper. And I probably wouldn't get into the newspaper business in the twenty first century.
Speaker 1:I love newspapers though. I got
Speaker 5:I'm not investing in
Speaker 1:one, though. No. No. I I think it's it's the time the days are numbered. I might be the last person subscribing.
Speaker 1:Anyway, give us a little bit of your background since the first time on the show. How'd you get to Substack? And then I wanna talk about your wager and the future of AI, the impact on the economy, all of that.
Speaker 5:Yeah. So I I mean, I'm a I'm a writer. I, you know, was an academic. I was in academia for years. Mhmm.
Speaker 5:I used to work for the City University of New York. But now, I find not having a boss or a schedule or ever having to get up on any particular day to be very attractive. And now I just write books and I write my sub stack and, you know, has enabled me to buy a house and, you know, so it's, you know, it's it's a pretty
Speaker 2:good That's a dream.
Speaker 1:So tell me about your wager. How did this happen? What is how did how did you come to define the the the actual bet and what's at stake?
Speaker 5:Yeah. So I I'm frustrated by the AI conversation. Mhmm. I think that it is I don't know if you guys are familiar with the concept of a Mott and Bailey argument. Yes.
Speaker 5:Mott and Bailey. Yeah. So Mott Bailey's. Yeah. For those at home, it's just like, you are you make a very sort of extravagant argument, and when challenged, you retreat to a simpler and easier to defend argument.
Speaker 1:Yeah.
Speaker 5:So you might say, the Christian God is real and built the universe and he rules over everything. And then when you're challenged, you say, oh, well, God's just a feeling and God's in the in the wind and whatever. Right? That's like a mountain bailing. Mhmm.
Speaker 5:I just think that that's all over AI where the CEO of Google is saying that this is bigger than fire and electricity. Okay. And people are saying it's gonna end death, etcetera. But then when challenged, it's like, hey, you know, these LLMs, like, you know, they they might make like, you know, going through legal documents, you know, of much more efficient process. There's this constant sort of back and
Speaker 1:forth. Sure.
Speaker 5:As far as the wager goes, the people in the AI world kinda come from this sort of rationalists, yeah, a Silicon Valley sort of culture. And they say you should be very sort of objective and specific in your predictions
Speaker 1:Mhmm.
Speaker 5:And you should put money on them. And so Scott Alexander is a guy I've known for a long time, the the blogger of SlateStar Codex and now Vastral Codex 10.
Speaker 1:Yep.
Speaker 5:He is a AI enthusiast. He was a signatory on the AI 2027 document. Yep. So I just I I challenged Scott and said, I believe that three years from now, we'll be in a more or less normal economy.
Speaker 1:Mhmm.
Speaker 5:And that was chosen because, you know, AI 2027, you know, this is like going to 2029. So I felt like it was giving him enough sort of wiggle room. Mhmm. And I just defined a bunch of economic indicators and said that if any one of these indicators are violated, he'll win the bet and I'll lose.
Speaker 1:Wow.
Speaker 5:And the reason to do that is just I'm I'm looking for someone to put their money where their mouth is about like, is this actually going to cause a white collar apocalypse and all these economic sort of things? And, I mean, he said no and would prefer to do a ten year version. So we're kind of looking at that right now.
Speaker 1:Okay. So I have some of these. Unemployment must stay under 18%. That if if where are you at now? 5%?
Speaker 1:That feels like
Speaker 5:But see,
Speaker 2:but this
Speaker 5:is this is the point. Yes. This this is the Martin Bailey. Right? Dario Amode, the CEO of Anthropic, last week in a interview with the New York Times said that within the next couple of years, 50% of all jobs are going to be destroyed.
Speaker 5:Right? You said 50% of all jobs?
Speaker 1:I thought it was early stage white collar
Speaker 5:No. No.
Speaker 1:No. No.
Speaker 5:Look No. Look it up. He's he's said 50% of of all the jobs in the economy are going to be eliminated. Right? And this is the thing that bothers me.
Speaker 1:This is
Speaker 5:why I made the bet.
Speaker 1:Because I ran I yeah. I actually ran the numbers on the new argument, the Bailey, which is entry level white collar work. I mean, The US economy is only 60% white collar. Early stage is, you know, a couple percent of that. And so you're at a percentage over percentage.
Speaker 1:And quickly, if you lose 50% of that, the unemployment rate goes from 5% to 8%, 9%. Like, that statement that new statement can be true, but it cannot be it it can simultaneously be not that disastrous.
Speaker 5:Right. So the the the c not the CEO, but the
Speaker 1:Yeah.
Speaker 5:The the head of AI science Microsoft just made a very similar sort of pronouncement. Sure. And and this is what I find just endlessly frustrating about this conversation is it cannot simultaneously be true Mhmm. That we are imminently facing a replacement of an immense number of jobs in the economy thanks to AI, but also 18% is like a extravagant figure for me to set for this bet. Mhmm.
Speaker 5:Right? If you if you really believe these things and so I I'm just never sure how seriously these AI people take it in part because the the CEO of Anthropic and the head of AI at Microsoft and almost everyone else who gets quoted in this domain has a direct financial incentive Mhmm. To exaggerate the impact of AI. Mhmm.
Speaker 1:Yeah. It I mean, Scott Alexander did take the bet, though. So he's putting his money where the where his mouth is and and certainly on the other side of this. Correct?
Speaker 5:Well, we we are looking at the at the conditions. He wants to do ten years instead of three.
Speaker 1:Oh, interesting.
Speaker 5:And so this is the it's actually turned into a kind of an interesting econometric debate. Right? So people are saying, where did you get 18 unemployment for for and there's something like 40 conditions I listed.
Speaker 1:Yeah. There's a ton here.
Speaker 5:And I said that we had 15% unemployment, you know, five and a half years ago.
Speaker 2:Yeah.
Speaker 5:Right? Because of Yeah. And what I'm trying to do is to set up the bet in such a way that a non AI source is not going to screw me. Right? You know?
Speaker 5:And it is Oh, sure. In the in the Great Depression, which obviously was not AI driven, we had 28% unemployment at some point. Right? So and it's actually led to a kind of interesting debate about, like, how do you define a normal economy without letting the natural swings that are common to a capitalist economy.
Speaker 1:Catch to it. I was listening to a conversation about AI apocalypses, and and and and the person that was being interviewed was like, well, my p doom from AI is extremely low, but I think the chance of nuclear war is, five percent. So Right. It's like they had a high p doom, but not because of AI, which is a very hard thing to wrestle with. And that's what you're getting at.
Speaker 2:Yeah. Is is I I've talked on the show a bunch about a bunch of these different groups using basically fear
Speaker 1:Mhmm.
Speaker 2:As as as a kind of motivator to get the to kind of bend the world. Right? So if you want people to adopt AI, you should tell them that it's going to, you know, create such such insane changes in the economy that any company that doesn't adopt as much AI as possible today is gonna is gonna be destroyed. Or if you are trying to get, as many young people to adopt a product, you tell them, well, all jobs are going be wiped out. Or if you're pitching investors on Wall Street, can say, well, all these jobs are going to go away.
Speaker 2:So it's effectively like the the the incentive to use kind of like fear is very obvious in all of this. And I think it's now coming back to bite a lot of these people because the broad broader populace is saying, I don't want AI. I'm good. I don't need it. Right.
Speaker 2:Even though they're using the products and they love them. Mhmm. Like, almost everyone can tell you an incredible story about AI in their personal life. Like, even if it's as simple as like, I made this like cool illustration for, you know, my grandma for her birthday and she loved it. Right?
Speaker 2:Or Right. I used it to learn about this thing. And so, I think it's interesting is like using this like intense fear based marketing to justify to kind of catalyze adoption, you know, fund, you know, success with fundraising, etcetera. But then again, it's kind of coming back to bite in the sense that everyone's saying, well, no data. I don't want a data center in my backyard.
Speaker 2:I don't I don't want my company to even be investing in this, etcetera. I mean, speaking of fear,
Speaker 5:I mean, you just mentioned nuclear war. Right? And it's I I just think that you can believe, as I do, that AI is going to be a very meaningful technology, but the fact that people are more scared of a robot apocalypse than nuclear war. Look, right now, this Russia has multiple Bore class nuclear submarines off the coast of the East Coast Of America that has the capability of raining nuclear fire down thermonuclear fire down all up and down the seaboard, right, the Eastern Seaboard. I mean, like, you know, a single modern thermonuclear bomb detonated above Central Park would destroy 80 plus percent of the buildings in Manhattan and hit parts of New Jersey and Connecticut, etcetera.
Speaker 5:Right? And that and again, this is the Martin Bailey thing. Right? Which is like, you might say, well, that's a very extreme scenario, but every day I am opening up my web browser and reading about, oh, AI is gonna exterminate the human race or, you know, AI is going to put us into this utopia where no one is ever gonna die again, right? And it's like, part of what I'm trying to do is just claw out like a normal space in this, To just say, there is a very obvious future where these tools are meaningful, eliminate some jobs, are have a lot of cultural importance, but where we're not suddenly faced with a fundamentally different version of human life.
Speaker 1:So if it's not nuclear war and it's not fire and it's not electricity, it's also not the fax machine. Are we talking about mobile, cloud, the Internet? Like, how big is this thing? What does your world model look like for how AI progresses and diffuses through society?
Speaker 5:Sure. I we have to understand there's a different kinds of importance and different kinds of influence. So you've mentioned the Internet and the mobile phone. Okay.
Speaker 6:It
Speaker 5:obviously, the Internet and specifically the smartphone, the iPhone have had massive cultural and social impacts
Speaker 1:Mhmm.
Speaker 5:On The United States. It would have shocked people in the mid nineteen nineties to learn that we have about the same productivity growth and about the same GDP growth in this country now that we did back then. Right? Like many many people were invested in this idea that this sort of this missing GDP growth, you know, we're at half of what we were in the mid nineteen sixties. A lot of people thought, okay, the Internet's the thing that's gonna restore us.
Speaker 1:Yeah.
Speaker 5:The Internet is very meaningful and it's very influential. Right? And yet economically, it hasn't had the effects that are expected. And that's just like, that's how history works. Know, that's that's just like, there's there is a you you always have to bake into percentage or the degree to which like there's regression to the mean.
Speaker 5:Right? Like we always seem to find ourselves way back to this sort of mundane reality and I look at things like when everybody got so depressed and disappointed after chat GPT five was released because they thought it was gonna be AGI and you had all these lonely guys who were like, oh, this is just gonna change life forever and now everything's gonna change. It's like, no. It's things aren't gonna change but slowly and in a distributed fashion and you have to keep planning for normal life.
Speaker 1:Mhmm. Counterpoint, maybe this time is different.
Speaker 5:Maybe this time is different, but he absolutely. So show me. I mean, the the here's the beauty of all this. The beauty of all this is, like, if this if if the real stuff happens Yeah. You're not gonna have to convince me.
Speaker 1:Yeah.
Speaker 5:Right? Like, if if we really have AGI the way people think we are, no one's gonna disagree because the effects are gonna be so profound. There's gonna be nothing to disagree about.
Speaker 1:Okay. How did you interpret this latest piece in the Financial Times from Eric Brian Fawson. I can't pronounce his last name. But, it says, while initial reports suggested a year of steady labor expansion in The United States, the new figures reveal that total payroll growth was revised downward by approximately 400,000 jobs. Crucially, this downward revision occurred while real GDP remained robust, including a 3.7% growth rate in the fourth quarter.
Speaker 1:This decoupling, maintaining high output with significantly lower labor input, is the hallmark of productivity growth. His own updated analysis suggests a U. S. Productivity increase of 2.7% for 2025. This is nearly doubling from the sluggish 1.4% annual average that characterized the past decade.
Speaker 1:It feels like we're seeing glimmers of something changing. Is that not a sign?
Speaker 5:I mean, we'll see. Right? We have to actually like look at the at the numbers as they come down the pike. We also have to be aware that like there's a lot of built in incentive for people to ascribe these changes to AI. So for example, cutting a lot of jobs is very unpopular.
Speaker 1:Mhmm.
Speaker 5:And firms tend to be sensitive to that unpopularity. Right? And saying, well, hey, AI came. We didn't make the decision. We just we had to sort of do like, that's a very sort of easy thing
Speaker 1:ever do that. That doesn't make any sense. To
Speaker 5:like, what to say that AI was the reason to do
Speaker 4:it? Yeah.
Speaker 1:Great. Use anything cover.
Speaker 5:Yeah. And so I I I just I in general, I caution people to say, look, it's like I I've said this before, you know, when I was in high school, a very distinguished scientist came to my science class, and he was on like the board on like the national science some sort of board of the National Science Foundation. He was a like a geneticist and he came and he said like that he envied and also felt bad for us because the the human genome project was going to so radically change human life that we were gonna see things that he couldn't imagine, but also the job of doctor wouldn't exist in ten years. Mhmm. And this I was in high school in like 1998.
Speaker 5:This probably happened, so, know Studying medicine. Right. Right.
Speaker 2:And you quit. Right. Right.
Speaker 5:And like, you know, like if you can actually but this is this is an exercise that people can do at home, is to go back, like just to Google and look at the predictions about what people thought the Human Genome Project would do.
Speaker 1:Yeah.
Speaker 5:Obviously, genetic research in general is very important, but there was a real belief among very intelligent and highly credentialed people that we were on the verge of something absolutely humanity changing and life's more complicated than that. Yeah. And again, like, I I just I I want AI boosters to do more showing and less predicting. Yeah. Right?
Speaker 5:Show me. Right? Like, show me the change instead of predicting the change.
Speaker 1:Yeah. Well, thank you so much for taking the time to come chat with us. This is really fun.
Speaker 2:We Yeah. Have this we have this we have this we have these, you know, kind of debates and conversations all the time. Specifically, there's a popular influencer on Instagram that every time a tech company does a bunch of layoffs and says, we did this because of AI, he takes that and like makes this crazy story up around how, you know, AI is just immediately Yeah. Causing all this job loss. And I'm just looking at it as like, I know the company.
Speaker 2:Yeah. They had a lot of bloat. They're getting some they're getting some Efficiency. Efficiency increase because of AI. But certainly, it wasn't like the the 2,000 people or whatever Yeah.
Speaker 2:Were sitting there being like, oh, yeah. I just onboarded this new agent and now it does everything that I did including going to all the meetings and, you know, sitting around all day.
Speaker 1:Yeah. There's incentive on both sides. Both the AI boosters and the AI bears sort of have an incentive to be like, it's going too fast. It's going it's it's going wrong. If you if you love AI, you wanna say it's going really fast.
Speaker 1:If you don't like AI, you wanna say it's going too fast. They're both sort of aligned so you get this, like, super cycle. Very fascinating. Well, have a great rest of your day, and thank you so much for taking the time to come chat with us.
Speaker 2:Everybody. Cheers.
Speaker 1:Let me tell you about Graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. And our next guest is in the restream waiting room. We have Sohal Prasad from Destiny.
Speaker 2:What's going on?
Speaker 10:Hey. How's it going?
Speaker 2:Great. Thank you for having me. Great to finally have you on the show. We met once. I think it was too long ago to remember what we were even talking about, but it's great to great to see you again.
Speaker 2:And a lot going on in your world, so why don't you kick off quick kind of background on yourself, and then let's talk about Destiny.
Speaker 10:Sure. Great to see you. Thanks for having me. Founded Forge, a stock market for private companies back in 2014. Took that public in 2022, and then Schwab bought us last year.
Speaker 10:And in 2020, started a company called Destiny to bring public access to private tech. So along the way, I realized that there's such a big inequity. Most people in the world that use you know, all the companies that are advertisers for you guys that are tech companies in our everyday lives, you have no way of owning that and wanted to create a way for anyone to own a piece of that future from the convenience of their brokerage account.
Speaker 2:Very, very cool. I've been, yeah, following Destiny since you since you launched it. How long did it actually take to get it up and running? There's a number of groups now that have seen what you've done or maybe had a similar idea and are trying to bring products to market, but you've been you've got a nice little head start. Guess I guess the journey really did start with Forge.
Speaker 2:It was probably couldn't have pulled Destiny off without having having done that first and had all of that understanding of of the market. But but, what what are what were kind of like what was the logic around the decision for for kind of the current structure and all the decisions that made that went into building the initial product and then kind of where is it going from here?
Speaker 10:Sure. Thinking about what the dream product is, it kind of looks like QQQ for private tech. That's a dream. Anyone can buy it on any given day. Anyone can sell it.
Speaker 10:It has exposure to a broad base of private tech companies. Now structurally, there are definitely challenges. An open end ETF, you don't have enough liquidity in the underlying private companies that would support the creation of shares on a given basis or redemption on a daily basis. So we looked across the market at what kind of structures are possible and ultimately decided that a listed closed end fund gets that intraday liquidity. It's listed on the NYSE.
Speaker 10:It's accessible, but you're still able to go invest in these companies. So it took us quite a while. We spent nineteen months waiting for registration with the SEC the first time. We listed in March 2024, and then we spent another fifteen months waiting for the SEC to approve our shelf.
Speaker 1:Overnight success. I love it. Walk me through the mechanics of the closed end fund. That means that you you own shares in private companies. When I buy shares in Destiny and then I go to sell them, I'm not selling them to you, I'm selling them to Jordi.
Speaker 1:Is that right or someone else on the in the market?
Speaker 10:Exactly. So we trade intraday on the NYSE. Market just closed. But anytime you want, you can go into your Schwab account. You can buy DXYZ.
Speaker 10:You can sell it. And it's all effectively secondary market trading. You're not creating or redeeming shares. Now last year, we got approval from the SEC or got effectiveness to raise up to $1,000,000,000 opportunistically. And that allows us to issue new shares, use the capital we raise from that, and then invest in new companies.
Speaker 1:Okay. So if there's a delta in NAV to market cap, it's because there's expectations about what you'll buy with that with those shares maybe?
Speaker 10:Yeah. Early on, there was a huge delta as people found out that this was even possible back in 2024. Mhmm. And I think that was just people realizing, oh, wow. I can actually do this.
Speaker 10:Like, I don't have to go anywhere. I don't have to make a new account. I can buy this, and people got really excited. And now that premium has come down just as we've gotten more mature. I kind of we had a decision to make when we brought it to the market, which is we wanted to have a portfolio of the top 100 private tech companies.
Speaker 10:Should we wait until we build a whole portfolio? Should we just list it with no companies in the portfolio? And we decided, hey, we'll build it effectively in public. So we've listed with 20 some odd companies. Today, have 35, and we're kind of growing that over time.
Speaker 2:What what were the conversations like originally with companies? Obviously, you're not always buying direct access or not getting direct exposure, but you're buying into SPVs or things like that. But what were the conversations like in the beginning? How are they going now with with Robinhood's new product? It sounds like at least some of it is is actually being, like, authorized by the company or they're, like, effectively signing off on it or cool with it.
Speaker 2:I'm sure in other cases, companies are are less excited about it, but, like, give us give us the an overview there.
Speaker 10:Yeah. But the secondary market, it's always, even for the last fifteen years, been case by case basis. Some companies have really active secondary markets, they facilitate it. Others try to keep more of a tight control. From day one with Destiny, what we did is make sure we have flexibility to invest across the board.
Speaker 10:So we've invested in companies that are doing primary rounds. We've recently invested in a company called Skilled AI. Softbank led that round and we were a part of that round. We partnered with Beast Industries and are working directly with them. And then at the same time, we can also opportunistically buy through secondary markets.
Speaker 10:So sometimes there are employees or early investors that need liquidity and they come directly to us and we can buy from them.
Speaker 2:What part of the part of why Destiny is exciting and other products are exciting that every anyone can get exposure to the asset class. The the the challenge is that oftentimes by the time you know a company's amazing and it should be in the Destiny 100, it's already been marked up to 50 True. 60, you know, billion or or whatever the number is. 130. Sometimes 80, you know, in the case of SpaceX, you know, hundreds of billions.
Speaker 1:It's really
Speaker 2:What are your plans around obviously, picking companies at the super early stage is hard. It's also very risky. Like, part of the appeal of Destiny is that you're you're getting exposure to companies that we already know are, like, solid. They're well capitalized. They're hopefully leaders in their market.
Speaker 2:But how are you thinking about, like, qualification, for, for Destiny? And would you ever go earlier stage? Is that too risky? All that stuff.
Speaker 10:Yeah. That that's one of the reasons we decided to call it the Destiny Tech 100 and target building out a portfolio of a 100. You wanna have enough range in there so you can have some of the early unicorns. You call it $1.02, $3,000,000,000 companies that have, in many cases, product market fit. They have growth, but they have more room to grow as well as at the same time some of the larger companies that are tens, now hundreds of billions of dollars and beyond.
Speaker 10:And so we will have over time a mix of those companies so that we can kind of get some of those earlier stage, albeit still late stage bets, and others that are the blue chip mature companies.
Speaker 1:How do you think about the actual investing strategy? Is are there any like I mean, you mentioned like post unicorn, are there heuristics or firm rules that are in a bylaw in bylaws? Or are you just sort of like the fund manager and you're tasked by the shareholders to make the best investments that are according to your own intuition, skill, obviously, incredible background, all of that? But how do you think about the actual capital allocation question?
Speaker 10:Yeah. So right now, the portfolio is in progress. So if you look, sometimes we might be overweight one company. For a while, SpaceX was greater than 40% of our portfolio that's come down. And so we're kind of in this building phase.
Speaker 10:As we reach a more steady state, we want to be reflective of the late stage venture backed ecosystem. So we actually publish rules and eligibility criteria our website where, like, companies had to raise recent rounds of financing. Sure. They other kind of growth metrics and TAM that we look at. But generally speaking, we don't want it to be whatever we like on a given Monday.
Speaker 10:We want to say, hey. We want overall late stage venture backed exposure. And where we get to use our discretion is, hey. What's the right time to buy this? What's the right structure?
Speaker 10:What's the right pricing? Things like that where if you just had an index, you would be a forced buyer at any price, at any structure. And so it gives us the ability to go and find unique opportunities in the primary, secondary markets and actually invest behind that.
Speaker 2:What what's the process when a company in the portfolio IPOs? Have You a number a number of portfolio companies that will be IPO ing or should IPO this year. There's a lockup period, and then I imagine you guys plan to exit those positions and then recycle the capital. But how are you thinking about that?
Speaker 10:Yeah. We so we wanna be long term capital partners for the company. And so generally, once a company goes public, we're not selling our shares immediately. We'll wait for a few years. Instacart was one of the companies in the portfolio that went public, and we waited for a few years before we slowly started divesting that position.
Speaker 10:And so that's how we're trying to balance the two things, which is our public shareholders are looking to us for exposure into private markets, but we also want to be great partners for companies and smooth their transition as they go public.
Speaker 1:It's amazing. Well, congrats on all the progress.
Speaker 2:What was the so what was the talk about the most recent acquisition or or investments? You guys are in Anthropic with for a $100,000,000 breakdowns of the new companies.
Speaker 10:Yeah. We so we just announced a couple weeks ago that we closed in a $100,000,000 investment, a secondary purchase in Anthropic. I mentioned Skilled AI, Beast Industries.
Speaker 2:That's Jordan was talking
Speaker 1:He's like, I can't let you get out of here without a gong. I knew it.
Speaker 2:That's right. Very cool. Well, yeah, we're excited to continue to follow Destiny and and the overall overall market. You guys have definitely led led the charge. Second time leading the charge.
Speaker 2:It felt like with Ford Yeah. You guys were very ahead of the curve and and ahead, here as well. So great to have you on.
Speaker 10:Thanks. More to come.
Speaker 1:Amazing. We'll talk to you soon. Cheers. Have a good one. Let me tell you about Labelbox reinforcement learning environments, voice, robotics, evals, and expert human data.
Speaker 1:Labelbox is the data factory behind the world's leading AI teams. And let me also tell you about vibe.co, where d to c brands, b to b startups, and AI companies advertise on streaming TV, pick channels, target audiences, measure sales just like on Meta. And before we bring in our next guest, we have some breaking news. It's Jensen's birthday from NVIDIA. And guess what?
Speaker 1:He was born on the same exact day, same year as Michael Jordan. I thought
Speaker 2:Really is the Michael Jordan of GPUs.
Speaker 1:Dylan Abercauta on our team is such an underrated poster. Got 8,000 likes just with two screenshots. One, Jenson's birthday. The other, Michael Jordan. Playmaker.
Speaker 1:02/17/1963. Happy birthday to Jensen, and thank you for all you do. I'm gonna tell you about Shopify before we bring in our next guest. Shopify is a commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. And without further ado, let's bring in our next guest, Travis from
Speaker 2:It is.
Speaker 1:Dash Optical. Travis, how are doing?
Speaker 6:Hey. Nice to meet you guys. Nice to me on.
Speaker 1:Thanks for hopping on.
Speaker 2:Big big big day.
Speaker 1:Yeah. Huge day. We saw
Speaker 6:the happened on February 17. We we launched on February 17 as well.
Speaker 1:That's true. That's true. Add it to the list. How much did you raise? Break it down for us.
Speaker 6:Yeah. 50,000,000 total across our seed in series a.
Speaker 2:Nice. Congratulations. First time on the show before we get into Mesh, introduce yourself. What got you into this? All that good stuff.
Speaker 6:Yeah. Yeah. I'm Travis Breshears. One of the cofounders and CEO here at Mesh Optical. And I work I I I I've been working on lasers since I was in high school and with a professor at UCSC, Philip Lubin.
Speaker 6:And then
Speaker 2:I went to Oh, interesting. So in high school, you were you were basically studying The blue. UCSB. You're studying the Yep. The laser beam.
Speaker 4:Yep. I was You're studying the beam.
Speaker 1:Studying the laser.
Speaker 6:That's right. Been been one with the laser since I was, you know, 15. And then I I went to SpaceX and started working on the space laser comm system there and got to the really fortunate opportunity to design and I worked with a really awesome team there on on the free space laser comm terminal.
Speaker 1:Cool. So talk
Speaker 2:about Living the space laser dream.
Speaker 6:Incredible Yeah.
Speaker 1:So talk about the actual product, how much of this is still R and D ready for commercialization. Then I want to talk about the implications, like, how this product actually rolls out into the into the world.
Speaker 6:Yeah. Yeah. So our first product is a pluggable transceiver that is used in all of the GPU clusters. So you just mentioned Jensen. Yeah.
Speaker 6:Like, the NVIDIA GPU clusters, for every one GPU, there's, like, four to five of these optical interconnects that help connect all the GPUs together through the networking, through making sure that they can be, like, a coherent cluster. And so the first product we're making is what we call like a linear pluggable optic, and it deletes a really expensive and costly, like like power hungry thing that is called a retimer or DSP. Mhmm. And so it allows the people who deploy compute to save a lot of that power. And so that first product is just simply allowing those GPUs to connect over optical deleting some power power hungry chip inside.
Speaker 1:And this is within a data center or in between different data centers?
Speaker 6:This is within the data Yeah. So our first yeah. Our first product is is yeah. Within the data center, they connect them with fiber optic cable on either end. And yeah.
Speaker 6:And so they And these are these
Speaker 2:are already already in market. You're selling these. Wow.
Speaker 6:Well, ours are the we're standing up the production line, so we we care a lot about colocating the engineering talent with the manufacturing. One of the key things we learn at SpaceX is to to be, like, right where the stuff is built. So behind me is the manufacturing line, and we'll start testing in the next month here some samples and then start scaling production right after that. And trying to get to, you know, millions of units in 2027 is, like, really where the the high volume starts to come into play.
Speaker 2:Exactly. Is this the kind of thing where it's really just a it's execution risk? Like, can we build this at scale? And if we can build them, there's insane demand, and it's and it's less demand risk?
Speaker 6:Yeah. The demand, we sort of think of as infinite because, you know, the more intelligence we have the more intelligence we have, it it just, like, is more compute. And so whenever you see people deploying more and more compute, they need more and more transceivers. And so as intelligence scales with compute, so does transceiver demand. Mhmm.
Speaker 1:$50,000,000 in the bank. Where are you based in the company? How big is the team? What does the next twelve to eighteen months look like for you?
Speaker 6:Yeah. We we're based in Los Angeles. We're in Gardena, California.
Speaker 2:Let's go.
Speaker 4:It's a little of lasers.
Speaker 6:Thank you.
Speaker 1:You. Los Angeles needed a win.
Speaker 6:Yeah. Yeah. Yeah. A little outside El Segundo, but, yeah, we're gonna bring Gardena onto the map as the the laser hub of of the world. Okay.
Speaker 6:Love it. And yeah. So we we're about 15 people now and and growing quickly and need to move to a bigger building now.
Speaker 2:Good size.
Speaker 1:Are there are there, like, two buyers for this? Like, are you gonna do deals with, like, every data center builder, every Neo Cloud, just the hyperscalers? Are you gonna be a supply chain partner, like, just to NVIDIA or just to AMD? Like, what does your business look like in, like, at scale?
Speaker 6:Yeah. We we wanna sell I mean, my our long term goal here is to be able to connect all all things with optical photons and whether that's an interconnect in a data center or an interconnect in space, whether that's free space or in a fiber. Mhmm. But to start out, to answer your question specifically, like, are anyone who who deploys compute on the ground, we will try to sell to. That could be a Neo Cloud, as you mentioned.
Speaker 6:It could be a hyperscaler. We have a strategy that we want to follow to kind of follow our match our volume to our potential, like, future customers and make sure we don't start all the way at, like, really high volume because, obviously, we need to scale our line. We care a lot about getting our manufacturing done here in The United States. One thing about all these transceivers that are made today, they're all made overseas. They're made mostly in China and Thailand.
Speaker 6:And so no one has, like, really stood up these high precision, what we do what they're called flip chip die bonding or pick and place machines. Like, when we bought the most high volume flip chip die bonder, they asked for your Chinese social credit number on it because because no one buys them here.
Speaker 2:Wow. Easy. Yeah. What do you think that we'll get, any mesh products in space in the next five years?
Speaker 6:Yeah.
Speaker 1:That's awesome.
Speaker 2:There we go.
Speaker 1:2027, you think what I'm thinking? Valentine's Day gifts. Yep. Here we go for that special person.
Speaker 6:Lasers for lasers for Valentine's?
Speaker 1:Crazier things have happened. We We're big we're
Speaker 2:big fans of girlfriend Yeah. They like they keep saying they want some metal, you know? Yeah. Some Get hardware.
Speaker 6:I was a I was a laser cat for Halloween once.
Speaker 2:No worries.
Speaker 1:Oh, that's cool. Yeah. Talk about, like, is the shape of, like, actually working in the factory? Is this stuff risky, or does it all happen in a clean room? How much of this is, like, a TSMC type fab?
Speaker 1:Like, what is it like in a day?
Speaker 6:Yeah. The the the the clean room is here. We we took some we took some panels off to get the machines in. But, yeah, it's it's a pretty like, we take the approach of, like, quest question the requirements and delete the part of process if we need to. And, you know, we start in, a semi dirty environment to make sure, like like, we we wanna we don't wanna go overboard.
Speaker 6:Right? You don't wanna just go all in on a clean room when you don't have to. So, actually, back at SpaceX, we started making the space lasers in a tent. And so, like, there's actually a tent behind me or in front of me. Sorry.
Speaker 6:And so, like, you you you wanna not you don't wanna go too all in on, like, it has to be in a cleaner. You you do tests, end of line testing and and qualification to make sure that, like, if it starts to impact your yield, then you would implement procedures and processes to keep it cleaner. This is, like, a a pretty good clean room, but not the best. And so we'll we'll see how our yield looks with with this one,
Speaker 1:and Mhmm.
Speaker 6:We'll implement stronger strategies if we need to. But, yeah, all of our semiconductor packaging is happening here, and, you know, we we get some dyes from other foundries that are all outside of Asia, and then we bring them here and package them.
Speaker 1:Mhmm. Last question for me. What was the biggest lesson you learned from working at SpaceX?
Speaker 6:I mean, just what I said is, like, question the requirements and delete the part and process. It's, like, it's so simple and but it's so useful. And, like, when we're designing something, like, you you wanna try to know why each part is there. So in our design, we've deleted quite a few parts, and Mhmm. Most people don't delete that part, but it ends up work anytime you delete a part, you delete a potential failure mode.
Speaker 6:And you want to be like a really reliable system, you need to delete as many parts or processes as possible. It also helps you like assemble things faster and so that that was one of the big lessons I learned.
Speaker 1:Yeah. That feels like, I don't know, easy to say, really hard to do in practice. Like, it feels like you have experience it. Like, I've heard that a million times, and, like, I'm sure that there's things that I could delete, like, even my daily workflow that I haven't Yeah. Figured out how to do.
Speaker 1:That's I love that.
Speaker 2:Yeah. Skatex is a company where, like, you learn learning things the hard extreme way.
Speaker 5:Yeah. Where
Speaker 2:you have mostly you ship a soft you ship a piece of software, it doesn't work. It's like Yeah. Okay, let's patch it. You ship a rocket, it has some like dependency that you didn't think was maybe that important Yeah. And it blows and you gotta live with that.
Speaker 6:Or or the whole laser mesh doesn't work. So
Speaker 1:hope that doesn't happen.
Speaker 6:That would that, you know, like putting a a kid in charge of that is is really a crazy thing that SpaceX does is they hand the baton to a really young person and put the whole company on like, bet the company on those people and Yeah. I think that forges things like within people to be able to deliver and then the delete the part and process like helps them understand the whole system really well.
Speaker 1:I love it.
Speaker 2:Well, we are not far from Gardenia.
Speaker 1:Yeah. Come by.
Speaker 2:Come by for your next appearance. We got a feeling you'll be back on the show this year. Great. Yeah.
Speaker 6:I would love to be there. Yeah. You guys are welcome to come anytime as well.
Speaker 1:I love it. Love lasers.
Speaker 2:I would love to.
Speaker 1:Have a great rest of your day. We'll talk soon. Let me tell you about Plaid. Plaid powers the app to use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. And you saw it at the opener.
Speaker 1:Jordy, get those juggle balls ready because it's time to tell you about Turbo Puffer. Solar Release Factor and Full Text Search, built from first principles and object storage. Fast, 10 x cheaper, and extremely scalable.
Speaker 4:Team sent me these
Speaker 2:these little puffers. They're incredible.
Speaker 1:Jordan's gonna be hard to very fast.
Speaker 2:They're gonna be hard to keep here at the Well,
Speaker 1:without further ado, we have Evan Spiegel from Snap in the TVPN UltraDome. Good to see you again, Evan. Welcome to the show. Welcome back to the show.
Speaker 5:Great to have you.
Speaker 1:Thank you so much for coming by and stopping by the TV pin Ultradome. Always You're
Speaker 2:out suited me. You're suited.
Speaker 1:And that is a beautiful suit.
Speaker 4:It's always a great excuse to wear a suit. My wife was like, where are you going today? I like
Speaker 1:I like the buttons that don't show through. I don't know what that's called, but that's a touch of like some it's very tasteful.
Speaker 4:Thank you. I appreciate that.
Speaker 1:Are you are you in are you following the taste discourse? People are saying that taste is important. Do you have a stance on this?
Speaker 2:In the context of building
Speaker 1:It's more of like a post AI thing. Like, is gonna be able to do everything but not taste. And it's just like it's sort of always been obvious, but it's also fun to write about. It's fun to talk about. There's a whole bunch of interesting examples.
Speaker 4:But It's funny you say that because our designers are literally becoming engineers right now. So it's kind of like, you know, I mean, if you think about like ten years ago, right, the even like the power dynamic in a company, the hard part was building things. Right now, the hard part is like having a great idea. So think taste is important.
Speaker 1:I guess the I I guess the question I was joking about earlier was, like, there's there's two ways to build a new consumer product. One is you a b test the color of the button, and you just look at the data, and that's more of the engineering mindset. And then there's the tasteful approach, which is maybe like, I just know green's the right color for my brand. Did you engage in both throughout your journey? Did you is there a place for both?
Speaker 1:Like, how do you see those two, the gut instinct interfacing with, like, the engineering reality? Like, somebody pulls up the chart and they tell you that it's got to be blue, but you know yellow is right.
Speaker 4:I think for us, like, there's a huge difference between, like, generation and iteration. Mhmm. Right? If you're trying to come up with a new idea Sure. It is really important that you can exercise your sort of creative opinion or judgment.
Speaker 4:I mean, you know, the reason why we chose yellow is there were no other apps in the top 100 that were yellow. So that was like an easy one, right, to stand out. We didn't have to test that yellow.
Speaker 1:Vertically, it's yellow.
Speaker 4:Us and McDonald's. Yeah. But I think, you know, what becomes very important very quickly is that you're able to iterate, you know. So once you put something out there, AB testing, experimenting, that really helps. Especially as you have a big organization, you don't want to bottleneck, you know, people's experiments.
Speaker 4:So anyone can experiment and and and learn.
Speaker 2:Yeah. It's interesting. I I One way to think about it is, like, I feel like executives thrive if they have great taste because they have a lot of people coming to them with, you know, work or projects, and it's Sure. Their job to decide, like, what are we actually gonna focus and prioritize. And now anybody can create, like, 20 different concepts for a website.
Speaker 2:And so they're having to choose from that to then go up the chain and decide, okay, which one of these should we actually implement? But there's, like, taste is becoming more important because now it's so much faster to just create anything. So at every level of the stack of the organization, have just like more things to choose from and taste is just choosing. Taste in your personal life is like choosing like, do I get this jacket
Speaker 1:Yeah.
Speaker 2:Or that jacket? Or do I put use this flooring in my house or
Speaker 5:How many
Speaker 1:logos should be on my shirt?
Speaker 2:Yeah. That's great.
Speaker 1:Give us the news. Massive milestone. What happened?
Speaker 4:Well, literally came here for the gong. You know
Speaker 2:what mean? It's a great strategy. We got a bigger gong since you were here last. We could been a horse apparently. Is
Speaker 4:a new horse? Is this like for year of the horse? No.
Speaker 2:We were early. We were Yeah. Yeah. We were early. I we it was really funny.
Speaker 2:It was so funny. So so we were walking by the store Yeah. And John and I were walking. And I look inside. The store is closed, but all you can see it's like kind of dark in there and there's this massive it's at the yeah.
Speaker 2:Massive horse. And I was like, we need one of those immediately. John's like, do mean? We're not gonna be able to get like a horse. And then when you look on this website for like a few thousand dollars, you can get this horse.
Speaker 2:That's like the
Speaker 1:easiest The hardest part of buying the horse was convincing the production team that we actually weren't joking. Yeah. Because Jordy sends in the chat, hey, we need a we need a horse statue. And he's like, oh, this is funny. And they were like, no, we're seriously.
Speaker 1:Okay. He's joking. And we're like, no. Actually, go figure it out. This is your job.
Speaker 1:Anyway, we're not here to talk about this.
Speaker 3:Congratulations on the horse.
Speaker 2:Thank you. No. We got a horse. You got a big milestone.
Speaker 1:I think the horse was here last time, but it was wrapped in Christmas lights, and we had a massive Christmas tree. And there were so many other things going on in the studio. You gave us that very nice Christmas ornament, which we love. You you you signed it. But it was distracting from the horse.
Speaker 1:But now the horse is front and center. But more importantly, your your direct revenue is front and center. Give us the news.
Speaker 4:Yeah. So we've reached a billion dollar annual run rate on our oh, wow. Thank you.
Speaker 2:Incredible.
Speaker 1:Is the job finished?
Speaker 4:And 25,000,000 subscribers.
Speaker 1:That's huge.
Speaker 4:So I think that's like ESPN size for subscribers, which is like next stop Hulu.
Speaker 2:You know?
Speaker 4:There we go. But really exciting for us as we work to diversify, you know, our revenue and create this this whole new business line.
Speaker 2:What was the Yeah. And then, like, narrative narrative violation too around
Speaker 1:Oh, totally.
Speaker 2:Social media. Right? There hasn't been a lot of people will pay for entertainment products, but there hasn't been a bunch of, like, scaled actually, like, a social media Yeah. Product Yeah. With, you know, that kind of SaaS.
Speaker 1:Yeah. What was the reaction like when you initially launched subscriptions?
Speaker 4:Well, I think what's so cool is people are really passionate about Snapchat. Yeah. So they want all these new features. And they're asking us all the time, like, hey, can you, you know, chat backgrounds? Or like, can we have a Bitmoji pet?
Speaker 4:Or whatever it is. Sure. And in the past, we would be like, oh, man. Like, this is really a feature for power users. Right?
Speaker 4:Like, this we can't build this, like
Speaker 1:Oh, it's for
Speaker 4:a billion people. Yep. So this gave us the justification and the resources. Like, okay. Fine.
Speaker 4:Like, you know, pay us $22 a month. Yep. Have your Bitmoji pets and your chat backgrounds and all this fun stuff. And so people just keep the request coming. We keep building all sorts of fun stuff.
Speaker 4:And and actually, it's great for the team because otherwise we never would have prioritized all these really fun features.
Speaker 1:How do people actually submit requests?
Speaker 4:Literally, email. Email. Email customer support. We do, you know, we do like research and things.
Speaker 1:Because a lot of the tech companies, it feels like they're Well, very
Speaker 4:it's evansnap.com, so it's, like, a little too easy to to send. Anyway, it goes, like, straight to
Speaker 2:my phone too. We love that. Yeah. Dangerous dangerous to say that on this show.
Speaker 1:So, yeah, what has been the key to scaling revenue there? Has it been just driving increases in ARPU or just onboarding more and more people into the premium product, doing more top of funnel, like bringing in these prosumer users as net new users, reengaging people? Like, what's been working?
Speaker 4:Yeah. A big focus has just been continually dropping new features Yeah. And letting people know about those features, creating new entry points Yeah. You know, into the subscription service through those features. You know, one of the big things that we rolled out last year was memory storage.
Speaker 4:So we've got people who are storing a lot of memories Yeah. On on Snapchat. So we give, like, five gigs free, but if people want more than five gigs of storage, then, you know, they can either pay just for the memory storage or they can join Snapchat Plus.
Speaker 1:It's so funny because I remember when Snapchat started, everyone was like, oh, this is genius. They don't have to have any cloud storage costs. Have you seen demand for AI features? And what does demand for AI features in a consumer context look like?
Speaker 4:Absolutely. I think one of the really exciting things people don't realize how widely the Snapchat camera is for generative AI, you know, images and videos. I think in q four, seven hundred million people use generative AI lenses. So those are, like, our camera editing Okay. Tools.
Speaker 4:And we have a feature called Lens Plus, which basically takes some of the most cutting edge Yeah. Gen AI features, you know, video generation, those sorts of things, and puts it behind a paywall. So if you want the most advanced Gen AI, you know, image and video editing features, that's that's part of Lens plus
Speaker 1:How have you thought about using camera as the end to end editing suite versus sort of bifurcating them, looking at, like, what TikTok and CapCut are separate, edits and Instagram are separate. When do you wanna go separate? When do you wanna consolidate everything?
Speaker 4:Generally, for Snapchat, one of our strengths is how much content is actually created in our camera because it's much more authentic. And what we find today, because everything is so overly edited and stylized because everything is created with generative AI. What our community tells us all the time is that we want authentic original content. So for us, we really focus on stuff that's actually captured and made in our camera rather than uploaded. And even as we think about, like, the types of content we distribute on Spotlight or, you know, Boost in Spotlight, for example, we're thinking a lot about what's actually made in the Snapchat camera.
Speaker 4:And this stuff is hilarious and but but not edited in the same way that it might be on other platforms.
Speaker 1:Have you thought about how, like, agents will take hold in a social media app? I've been trying to think about this, like, you know, the the the Manus acquisition. Like, what does it look like if I have an agent that can go and, you know, work its way through my social network profile? It's like, I could kinda tell it to, like like every comment that comes in that's positive, and it could do some sentiment. But I don't know if I actually want that.
Speaker 1:Like, how does that play out once you get to models that can actually run-in the background? It's not just I ask for a question, I get an answer, or I say replace the background with a beautiful forest and it does it. Have you thought about any of that yet?
Speaker 4:You know, we early on brought MyAI into Snapchat. Right? And that was like a great Yeah. Proving ground to experiment with things like, you know, personality, memory, all those sorts of things. We're being able to bring MyAI into group chats or conversations, like So I I do think it's been useful in that regard.
Speaker 4:Certainly, the the MyEye use case is very utilitarian. Like, we see a lot of, like, just questions Yeah. Homework help, like that kind of stuff. You know, on the on the AgenTex side, I'm much more excited about what's happening inside the business. Like, I think the potential for business transformation Yes.
Speaker 4:Is off the charts. I think, like, you know, if you look at small and medium sized companies for the last ten, twenty years, they've almost been, like, left for dead. Everyone's been so excited about mega cap companies. Like, I think the next ten or twenty years, the efficiencies that small and medium sized businesses can drive to grow Yeah. Using agents is going to be off the charts.
Speaker 4:So I think that's like that to me is where where I'm most excited.
Speaker 1:So is anyone writing code anymore? Are you vibe coding stuff now? We see every level of the spectrum. It's either the CEOs Yeah.
Speaker 2:Toby, drop
Speaker 1:buys. No one's writing code. It's always at the extreme. But what's your experience?
Speaker 4:Well, it's not vibe coding anymore. It's agentic engineering.
Speaker 1:Yes. Yes. Yes.
Speaker 4:I think, look, I think what's really interesting about what we're seeing in Snap is that, like, to some degree, you know, and because the company's been around for a while, you know, it's operating at two speeds. Like, are team members who have fully embraced agentic engineering, right, and who are essentially not writing code. Right? And then there are other teams that are still operating in a more traditional way. So, you know, because this change is happening so quickly
Speaker 1:Yeah.
Speaker 4:One of the things we're very focused on is driving these tools through the company, you know, really making sure that folks embrace this new way of working, helping train folks Sure. To do that because, you know, certainly for quite a number of folks, they are not not writing code
Speaker 1:Yeah.
Speaker 3:The way
Speaker 1:they used to. What's the, like, the next development that you're most excited about? Is it just understanding the code at a deeper level, sort of like a higher IQ model or thinking in systems and scalability. Like, it's not, you know, some tiny app. Like, there's so many users on here.
Speaker 1:Once tiny change can have massive ramifications across a database, the the the the stakes are a lot higher. So what are you looking for in the advancing in the tools of AI tools to actually improve your business?
Speaker 4:Yeah. For us, it's really just right now about building agents across the enterprise. Right? Like, whether it's like, you know, somebody reports a bug, the agent goes out, figures out who else has reported a bug like it, actually tries to go figure it out, right, proposes a fix. Mhmm.
Speaker 4:Right? Those sorts of things. Or, you know, you look at our sales team, right, and all the work they're doing, everything from really trying to understand client's objectives Yeah. Generating insights for them, putting that together into a presentation, mapping it to our, you know, advertising solutions. Like, you know, I I think there's just a huge opportunity.
Speaker 2:Yeah. Even even thinking an advertiser that spends $20,000 a year with you guys should event should in the relative near term get the same type of presentation and like almost like high touch experience that somebody spending $10,000,000 should get. Right? And that doesn't feel like a lot of that is, like, people making slide decks Yeah. Like, really being on it, like like, being timely with Mhmm.
Speaker 2:With, like, kind of feedback or, you know, things like that.
Speaker 1:Sure.
Speaker 2:Sure. That feels like very within reach with agents.
Speaker 1:Yeah. Walk me through the current pitch to advertisers. When you meet with a new big company, I mean, I'm sure everyone's used, you know, your advertising product at this point. But let let's assume there's some new hot company that is growing. They have a physical product or something, and they want to grow their customer base, grow their reach.
Speaker 1:What are how are you positioning your offering on the advertising side?
Speaker 4:Nearly billion user platform, including more than 110,000,000 monthly active users right in The United States in this really, really important thirteen to thirty four demographic. And the reason why that demographic is so important is because they are forming lifelong relationships with brands and with products. Yeah. Right? And not to mention, they're making, you know, their first car purchase, their first home mortgage.
Speaker 4:I mean, even their first, like, tube of toothpaste. Right? So I think those are the sorts of really important long term brand relationships Yeah. That are so critical. And and so I
Speaker 1:I'm sure I'm still using the same toothpaste brand I bought when I was 19 or something. I have not churned from that company. The LTV is probably through the roof. It is. Does but so do you have to stress the importance of thinking in not a ROAS, not a one year LTV payback, but thinking about capturing a customer that could stick around for a decade or more because they're a younger audience?
Speaker 1:Is that something that's resonating?
Speaker 4:I think that fundamentally, ROAS is critically important. It's something that we really optimize towards. And a lot of people use, you know, lower funnel objectives on Snapchat. That's been a huge driver of growth for us, especially with the small medium customer segment, because folks are very sensitive to their return on investment. Yeah.
Speaker 4:But when I, you know, talk to advertisers about why they love using us, it's always the new customer metric. Like, is why they're coming to Snapchat. They say that if I look at the percentage of new customers I'm getting
Speaker 1:Yeah.
Speaker 4:When I spend on Snapchat, like, that really moves the needle for my business and it moves the needle for me over the long term.
Speaker 1:And it feels less like a tax, which happens on some other platforms where it's like, these people were already coming to my they were looking for me and I had to pay for that? It's frustrating. Stuart, you have something?
Speaker 2:Yeah. How are what are you excited about in AI hardware broadly and everything that you guys are working on? It feels like this will be a massive year for hardware across the board. You've got, you know, Apple, you know, people have been reporting, I think, this week multiple new hardware devices. There was that like somewhat believable looking like open OpenAI Oh, yeah.
Speaker 2:OpenAI ad. Ones. But anyways, a lot of action going on, a lot of energy and excitement. You guys are in a good position because you've been working on it for better part of a decade now.
Speaker 4:Yeah. I mean, it's it's a transformational year for for Snap. In this regard, we just spun out Specs into its own standalone subsidiary, so it's really going from, you know, R and D science project to, like, real company after So almost 12 that, you know, is is really important for us. I think, you know, it intersects with some of the things that we were just talking about in terms of the evolution of AI because, you know, one of the biggest things I think folks have been concerned about when it comes to building a new computing platform is how to compete with the lock in that the app stores have. Right?
Speaker 4:How can you possibly compete with all these other app stores? And I think literally at the beginning of this year, people realized, like, software isn't a moat anymore. Right? That like having an app store isn't a moat anymore because it's so easy to build software. You can even build software on the fly.
Speaker 4:Right? And that to me is really exciting and coming at an amazing moment.
Speaker 2:What can you do to lean in? I saw somebody had hacked a pair of smart glasses to work with OpenClaw.
Speaker 3:Mhmm.
Speaker 2:And I imagine, like, is there anything that you would do on that front to really lean into the whole kind of, like, hacker movement around AI? Because there's, like, you guys are building a bunch of experiences internally. We've used a lot of them. They're very cool. But at the same time, opening it up and saying like, hey.
Speaker 2:This is a platform that anybody can build on. And we've seen this even with the kind of the Mac mini movement. Mac minis are starting to sell out in different points around the country. People are obviously willing to spend real money to experiment around all these products.
Speaker 4:I think the the big thing that you're sort of circling is the way that people are using their computers is really changing. Right? And they're really just supervising agents doing work for them. And that is a perfect fit for specs. Because the whole idea is to stop spending all this time hunched over your laptop or staring at this We we were at breakfast this morning
Speaker 2:and this guy I didn't take a picture because it would have been rude, a violation of his privacy, but his his posture was literally like it was it was the most insane posture. He needed he needed his back.
Speaker 1:He's getting acting on it. One way or another, it's peak performance.
Speaker 2:He's getting fired. He 's calling
Speaker 1:it now. Like, I know we're gonna see this guy.
Speaker 2:Yeah. Like, we we it feels the the the What you're imagining, which is like we can all just spend all of our day walking around being productive, monitoring agents in a in a kind of a heads up display. It feels within it feels within reach.
Speaker 1:It does.
Speaker 2:Yeah. Finally.
Speaker 1:It does.
Speaker 4:Yeah. It's incredibly exciting. So it's cool that all of this stuff is coming together, you know, in this moment. And I think, you know, it is super important for us to be investing in hardware because we talked about software's not a mode anymore. Right?
Speaker 4:So it becomes even more important to do very hard things in the real world at a time when software is being disrupted in this way.
Speaker 2:Yeah. But at the same time, I feel you guys are in a unique position because it doesn't feel, well, like, looking at the video game industry, I think that, AI will presents like a pretty huge challenge for a lot of these, you know, smaller studios that were just in the business of, like, spending a few years making a game, releasing it. If it becomes way easier to to build a game, that's bad for them, but it might be great for like a Fortnite or a Roblox or one of these platforms that have these big existing social networks. And so I feel like your your core business of of actually still being a social network where people are connecting with other real humans is in a good is in a good position. And so, yeah, the hardware is just like a bonus.
Speaker 2:Yeah. And and one of the
Speaker 4:things we've been thinking a lot about, you know, is both with the Friend Graph and in terms of our distribution, how do we leverage all these amazing tools to just start building more apps. Right? Like, one of the things that we always love to do is come up with new ideas. In the past, we've been like, oh, we got a great idea, but we got to build it.
Speaker 2:Oh, man.
Speaker 4:Right now, you know, I was just looking today, we have a really I mean, shouldn't even be saying that. Shouldn't say
Speaker 1:Something coming soon. Anyway.
Speaker 2:We've got
Speaker 4:a wild new idea that we're working on. Yeah. We can
Speaker 2:yeah. I was I was gonna ask, like, have you been pitched by the vibe coding? Like, do people wanna be able to, like, send an app around, basically, that they just prompt on the fly?
Speaker 4:I think so. And I think I think what's gonna be really interesting about all these companies, like before, so many of their resources were dedicated to engineering. Now, I think people are gonna be much more focused on marketing, on distribution. Right? And and that's a a big shift in the way they do this.
Speaker 2:Being able to being able to send send somebody an app that you just made for them that historically you would have just like sent a funny picture to your friend.
Speaker 1:This was my experience sending you sores of me walking on the beach in the Volta themed suit. Like, was it like I I was able to make an in joke with me and my three friends in a group chat that would not do well on social media broadly. You have to have all this context, but because the cost of generating new content had dropped so low, I could do something that didn't require a costume department and cameras getting set up or all the all those different things. Talk a little bit more about Gen AI. There's a lot of crazy video models releasing.
Speaker 1:It seems like a lot of companies are moving fast and breaking a lot of things, particularly in like the Hollywoods or Hollywood's not happy about this stuff. Like, what does responsible rollout of generative video features look like?
Speaker 4:What a great question. So I think for us, we have a lot of safeguards in place, you know, both around basic things like you shouldn't be able to make somebody nude, or you put in a compromising position, or that sort of thing. You know, you shouldn't reproduce copyrighted content, those So sorts of we we you know, as we look at, you know, even open prompt experiences where people can ask for Sure. You know, to to create different sorts of photos and and videos, we try to layer in safe ards to prevent that sort of thing from happening. And we do a lot of adversarial testing Okay.
Speaker 4:To to make sure, you know, that that is unlikely to happen.
Speaker 1:And then in terms of lenses, sponsored lenses, different experiences that partners are bringing to the platform. I'm interested to know what's the shape of the ecosystem? Like, there are there random developers out there who are making things and then earning some sort of rev share from that? Is there actually a flywheel there? Or is it particularly like you're working with a brand and they're gonna do a sponsored lens and like your team is developing that for them?
Speaker 1:What does that side of the business look like?
Speaker 4:Yeah. It it it absolutely spans the spectrum. So there's a 100 thou more than well, gosh, maybe 400,000 developers Okay. Now Yeah. Who who build Lenses Yeah.
Speaker 4:For for Snapchat and and increasingly for specs Yeah. As well. You know, those developers can apply to include their Lenses in Lens Plus and earn a revenue share out from that Yeah. You know, if if people are engaging with their Lens and that kind of thing. And then we've got a whole, you know, internal studio as well.
Speaker 4:So we can work with advertisers if they want to build a unique experience, or we have tons of partner studios who we can connect them with. But, you know, increasingly, there's a tool called Easy Lens. It's pretty fun. If you pull it up and just play with it, you can build a Lens from a That's
Speaker 1:what I was gonna ask. I imagine that that has to be accelerator for you. Right?
Speaker 4:It's huge for us. And again, we're thinking a lot about how to connect, you know, the we have, you know, Lens Studio, is more of the pro tool, and then we have Easy Lens, which allows anyone to create with a prompt. But I think, you know, even Lens Studio itself is going to become much more, you know, oriented around agentic engineering rather than
Speaker 1:Yeah. Because you just prompt it and it's it's wiring up whatever your domain specific language is. Very interesting. Yeah. Are you starting to see an actual, like, kink in the graph of Lenses that are being deployed yet?
Speaker 1:Or do you think that this is something that comes once people realize that it's actually easier to go and
Speaker 4:Yeah.
Speaker 2:So it's so interesting. We we like, there's some dynamic on the Internet that I feel like is somewhat real where the the the more funny you think something is, like, the less likely it is to be actually viral. The Yeah. I jokingly called this the Hays Hays Paradox, which is also a Hays Paradox. It doesn't work.
Speaker 2:It's just not working through. But but yeah, it's this idea that something that is actually the funniest thing that you see on the internet for an entire year is has might have a TAM of, like, close to one or or your group chat. Mhmm. But that's great if you're talking about using giving people tools that allow them to generate, like, hyper personalized things that are only funny to them or, like, a handful of their closest friends. It's like actually gives you the ability to, like, create a lot more joy on your platform.
Speaker 4:And that that's exactly what we see with Gen AI, that people are using it for these more communication oriented use cases. But on the content consumption side, it's the authentic, original, like, unedited, non AI content that does super well. So definitely a major a major contrast there. And I I think, you know, as it pertains to EZLens, when we started rolling that out, we saw a huge step change in the lenses that were being Sure. Created.
Speaker 4:So that's become a big a big focus for us. But I also think you can imagine in a not so distant future I mean, now the way that the models work, it's very hard to scale real time, you know, image transformations, which are one of the reasons why I think people love Lenses because you it almost feels like you're looking in a mirror, right, and transforming what you I look think in the not so distant future, a lot of Lenses will just be prompts. Right? And those prompts are gonna be shareable and, you know, we have a whole feature right now around the Imagine Lenses, some of our other generative Lenses where we have trending prompts and you can share prompts with your friends and, you know, iterate on them. And I I think, again, kind of tying back to the importance of the friend graph, I I think you see that intersection of people creating these, like, inside jokes, but then also being able to really easily share them with their friends, have people create their own content, you know, inspired by those prompts.
Speaker 1:Yeah. It's pretty cool. Yeah. That seems really, really important. I mean, whenever one of these new image models goes viral, the the stuff there's always some, like, ground truth, meme, human element that's underlying it.
Speaker 1:I think of the Studio Ghibli moment. It's like, I've seen cartoons. I could just go look at a cartoon, but I haven't seen a cartoon of me. And so there's a little bit of that in there, so the lenses make perfect perfect sense in that in that case.
Speaker 2:Let's get let's get the California update.
Speaker 1:Oh, yeah.
Speaker 2:What's on your mind broadly in the state? Going
Speaker 1:better than ever. Right?
Speaker 4:It seems to just get better and better. Don't know I how we mean, if we didn't have this weather, we'd really be in a tough spot.
Speaker 2:I mean, it's incredible what we get away with. I know. It really it really is. The weather. It really is.
Speaker 1:That's got to be a big piece of it. The weather is fantastic. Although, yesterday was a little rainy.
Speaker 2:Yeah. Yeah. Basically California has like karma for forever flexing the weather Yes. On the rest of the state. Yes.
Speaker 2:Like how many times I've I've messaged a friend and or they'll say like, oh, it's like it's my it's like five degrees out right now. And I'm like, oh, it's like 71. It's gonna be that way all week. And so in exchange and exchange we get like the the gnarliest political
Speaker 1:It's little chilly today. It's 56. That's sweatshirt weather.
Speaker 2:It is. I'm freezing. It's freezing. Absolutely freezing. Stay indoors.
Speaker 2:Yeah. This is crazy. But,
Speaker 1:yeah, broadly, how do you think California is going?
Speaker 4:Yeah. I, you know, I'm concerned. What I what what gives me some optimism is that it looks like more and more people are increasingly concerned.
Speaker 1:Okay.
Speaker 4:Right? What I was most worried about, you know, even six to nine months ago was the number of people that, like, thought things were going really well in California because they were contrasting with what they were seeing at the federal level. Right? And feeling like, oh, California is better. It seems like, you know, there's less chaos here or whatever, you know, because we've got a single party Yeah.
Speaker 4:State essentially. And so I think now more and more people are, you know, are hearing that we're number one in terms of homelessness, number one in terms of poverty rate, number one in terms of unemployment. And they're like, woah. Like, that doesn't line up with the California that I love, that I wanna be a part of. Like, how can we change that and and fix that?
Speaker 4:So I think the awareness is really important because, you know, in a democracy without awareness, you're not gonna get change. Yeah. And so I think, you know, hopefully that will continue to build. I think, you know, if Newsom decides to run for for president, that's gonna, I think, raise even more awareness of California and the challenges that we're facing here, which again, I think will be helpful. So right now to me, it's really an awareness game of helping make sure Californians understand, like, this is not going in a direction that I think we Yeah.
Speaker 4:Want. And if we want change, then we're gonna have to ask for that, right, and advocate for that. But I think that's happening more and more, you know, which which gives me some some hope.
Speaker 1:Yeah. Makes a lot of sense. I wanna ask about live streaming. How do you think about it? It feels like it's having a little bit of a moment with the with the clavicular stuff.
Speaker 1:I don't know if you've tracking this. Clavicular.
Speaker 2:I love this. So locked in. He he he got frame hogged.
Speaker 3:It's a huge deal.
Speaker 2:No. Yeah. So he's running, you know, have a billion users on the Internet. But so there there's there's basically a number of creators on on Kik that have generated probably a 100,000,000,000 views, like, some some absurd number. The one John referenced is very is is from the looks maxing community, which is effectively guys that try to be as good looking as they possibly can.
Speaker 2:So it's basically this whole drama, like, it's kind of like WWE brought to very Internet native. There's all these different characters. One of them is running effectively a twenty four seven every whenever he's sleeping, he's streaming. Live streaming. So it feels like IRL IRL live streaming is is hitting just have having a really big moment Yeah.
Speaker 2:Right now. How have you thought about it historically? Does it does it Today. Play any type of role Yeah. Snap's future?
Speaker 2:Or is it not something that the users actually want?
Speaker 4:We're we decided to step our way there essentially with creator subscriptions. So we just started testing creator subscriptions with a small group of creators. What we find on Snapchat is that people have very, very loyal relationships with creators. So once they subscribe, like, they wanna come back every day and see what's new on their story and message with them and, you know, really get to know them better and and build this deeper deeper relationship. So we thought creator subscriptions was a good extension of, like, what we're already seeing happen on Snapchat.
Speaker 4:We're gonna test that out and see how that goes, but that will give us some of the infrastructure to to start thinking about, you know, stepping from there and
Speaker 2:So that would be an individual creator just going live, talking with with with their existing follower base?
Speaker 4:Yeah. Potentially to start exist you know, with their existing subscriber base or even with their, you know yeah. Not not necessarily even their followers more broadly, their existing subscriber base and then Yeah. You know, layering in some of the replying and gifting and those sorts of things before opening it up more broadly.
Speaker 2:How have you been I I felt like my personal stance is that like Twitch as a platform since being landing at Amazon is just like not not gotten the not just gotten the attention that I think it potentially deserves. I created an opportunity for the kicks of the world to to step in.
Speaker 1:Well, I I mean, I haven't seen Andy Jesse live streaming on Twitch once. Yeah. And so
Speaker 4:I would love to see that.
Speaker 1:I would love to Now see we're Earnings on Twitch, obviously. Do it.
Speaker 4:That would be cool.
Speaker 1:Come on.
Speaker 2:Yeah. So you you guys should you you should fire up your and do do just an earnings call on on the on the platform.
Speaker 1:It'd be great. I want the CFO there explaining the whole financial model, what happened. Keep it wonky. It's fine. That's what Twitch is.
Speaker 1:It it every social media platform is like a flourishing of niches. And you find your niche, there's gonna be someone there who's like, yeah. This is amazing. Switching gears a little bit. You mentioned subscribers are getting close to Hulu numbers.
Speaker 1:How have you been processing the somewhat polished, produced vertical short form trend that's sort of happening. I see them in the App Store. I haven't been a user really, but you're familiar with what I'm talking about. Real short is one of them. They seem to be popular.
Speaker 1:There's obviously some organic creation that's happening on a fully UGC platform. But how have you thought about that? It feels like sort of Revenge of Quibi in some ways. But where do you think that goes? How important is that?
Speaker 1:Is there a role for you to play in that ecosystem?
Speaker 4:Yeah. I I know that we've got a lot of, you know, advertising partners who are marketing the short form videos on Snapchat. Yeah. Makes And, you know, I mean, ads are so sometimes I find myself watching one for, a minute,
Speaker 1:and I'm like, oh, my god. Yeah. I gotta know what happened
Speaker 2:to ask.
Speaker 1:He's like, who killed her?
Speaker 2:Yeah. That's always what it is. So so
Speaker 4:that seems to be working.
Speaker 1:Yeah. Okay.
Speaker 4:Good. But I I think, you know, when when we experimented with shows, you know, many many years ago, I think for us, we just found that the volume of creativity, you know, the billions of Snaps being created in the Snapchat camera meant that really, like, Snapchat is at its heart about UGC fundamentally. Yeah. And I think in the places where we've really allowed UGC to flourish and creators to flourish and actually where we we didn't do as many shows or didn't do as many publisher stories. We we really built a very vibrant organic creator ecosystem.
Speaker 4:So I I think, you know, in in sort of the ensuing few years, we we've pulled back from doing that sort of more premium content because what we just see our community love is connecting with the folks that feel like they're next door.
Speaker 1:Yeah. And I mean, YouTube did the same thing. YouTube Red, they had a whole bunch of, like, produced things and you'd see the it'd like, my favorite creator got paid a bunch of money to do something produced and it's to get him less views because, like, I actually just want him to turn on the camera and just talk. I I don't need all that other stuff because, like, that's not what I'm there for. And I think that recognizing the the desire of the user, the context, like, all of that really matters.
Speaker 1:Like, the medium is the message. Right?
Speaker 2:What is your how do how do you allocate your time in 2026? Where are you where are you spending time that you know, how how has that kind of changed over the years?
Speaker 4:I mean, at a high level, it's probably 8020 Snapchat and specs. I think that's gonna have to start shifting this year, you know, not maybe not totally 5050, but certainly close close to it just as we as we ramp up and and, you know, bring that product out into the world. You know, my happy place is making new stuff with our team. That's what I love to do. Our design reviews, you know, whether that's, you know, with specs or with the Snapchat team.
Speaker 4:I that's that's really what I what I love to do. But, know, a lot of what I've had to do over the past couple years is really work closely with the team to rebuild the ad platform and to create a totally new you know, this small medium customer segment for of our advertising business. I mean, our our business three or four years ago was almost all large customers and, like, highly concentrated in The United States. And when your business is concentrated on a small number of very big customers, it just creates a lot of unhelpful volatility. And so Totally.
Speaker 4:What we've done since then is, you know, build out a platform that can deliver lower funnel goals, you know, especially the small and medium customers, then really diversify You don't
Speaker 2:get in the work on the fun stuff if you don't have the economic engine.
Speaker 3:Yeah. Yeah. Yeah. Last
Speaker 1:question from me. Virtual reality, you've obviously looked at this, haven't gone super deep in it. Over the weekend, I watched The Matrix in VR. Watched in on Apple Vision Pro.
Speaker 4:You watched the whole
Speaker 1:Matrix in VR.
Speaker 5:No way.
Speaker 1:The Matrix, I
Speaker 5:did. No way.
Speaker 2:Yes. They said no one had ever done that before.
Speaker 1:I also I also watched.
Speaker 2:You made history.
Speaker 4:I think it's incredible.
Speaker 3:Get it.
Speaker 4:You should hit the gong for that.
Speaker 2:I mean, that's unreal. Gong for yourself. That's a selfish. That's I'll incredible. Do you one better.
Speaker 2:Love you. Did. Love love I did.
Speaker 1:We
Speaker 2:did. But
Speaker 1:but I went further on Saturday night. I watched Terminator two in v Woah. Back to back. Back to back films. I watched two movies.
Speaker 3:And you don't
Speaker 4:have like a ring around
Speaker 1:your It's not it's temporary. It goes away after about an hour. And yes, my wife did say something about it. But
Speaker 4:What was she doing? Was she there?
Speaker 1:It it was it was a rare situation where she was out of the house with the kids, and so I just had free time on Friday. I never had She just plugged
Speaker 2:it in.
Speaker 1:But truly truly around family, like, can't use it because it's so antisocial. Even with the eye, it just doesn't work. So, like, I actually finished watching Terminator two just on my phone because it was less antisocial than putting this VR headset back on when once the family came home. Anyway, I did successfully watch a full movie in VR. It be I did.
Speaker 1:I can't tell and I think I already know the answer now that you're laughing at me. But am I like one year early? Am I ten years early to watching movies in VR? Or am I just weird and it's never gonna happen?
Speaker 4:You're gonna watch movies in glasses for sure. Okay. Right? And I I think like what you know, it's so funny. A couple of my buddies, you know, are big into finance stuff like that.
Speaker 4:So, like, if we travel together, you know, they'll bring their monitor No way. To, like, oh, yeah. Yeah. Come on. You can't get stuff done
Speaker 2:without your just got the new Dell one.
Speaker 1:Yeah. Is Oh, we did?
Speaker 2:Yeah. It's it's, like, six feet long.
Speaker 1:That's amazing.
Speaker 2:You gotta have
Speaker 4:your you gotta have your setup. Yeah.
Speaker 2:You know? And so Yeah.
Speaker 4:So they travel with, like, a big monitor or, you know, even two monitors. So I think, like, a lot of the early stuff you're gonna see with glasses are people who just want the full Yeah. Setup, but, like, do not wanna ship, you know Sure. A monitor to to wherever they're going. So I think, like, if you, know, if you're you're traveling or you're, you know, on a plane or something, you wanna really get work done.
Speaker 4:It's so hard to do that on a laptop.
Speaker 2:So I
Speaker 4:don't I think you're I think you're right on time, actually.
Speaker 1:Right on time. Yeah.
Speaker 4:Yeah. Or a pioneer.
Speaker 1:Next time you come on blast, have you watched a full movie in any VR product? And I and we'll see. We'll see if I'm if I'm early or just weird.
Speaker 2:And what do you think about timelines for watching movies in glasses? And
Speaker 4:like what this year And
Speaker 2:and then what about what about glasses? Is it that you still have some element of the real world that's not as anti you know, you're not getting the, like, you know
Speaker 4:Yeah. It's not this huge, heavy closed headset with a screen, you know, right
Speaker 2:in front of your eyeballs.
Speaker 4:So I mean, sorry. It seems like you love I
Speaker 1:was so so so the trick is that I was laying perfectly flat. And so In
Speaker 2:a fully bright room.
Speaker 1:Yeah. Oh, yeah. This is the other thing. This is the other thing. It needs tracking, so you have to leave the lights on.
Speaker 1:I'm not kidding. I'm not kidding. No. No. Seriously.
Speaker 1:So you can't turn off the lights. And so if I get home and and my wife wants to go to bed and turn off the lights, I'm like, oh, okay. It doesn't work. No. That doesn't work.
Speaker 1:It loses the tracking. No. What? But but if you rest it right on your head just perfectly and and then also the the the VR headset, it it wants to be world locked. So initially, the screen is down here, and you have to look like this.
Speaker 1:And then you have to recenter it up here, And then it appears above you in beautiful four k and it's amazing. And you sit there and you watch The Matrix from start to finish and it's actually a great experience. But it is weird and niche and I don't know if it'll ever happen.
Speaker 4:But I think the idea of, you know, being able to watch something on a giant Yeah. Display Yeah. In a lightweight pair of glasses is compelling.
Speaker 1:Oh, yeah. If it's lightweight. But, like, truly, you actually can't have a VR headset on your face for more than ten minutes. It's not.
Speaker 4:I love I love
Speaker 2:that it's super bright. It has to be bright.
Speaker 1:Like, the ISO on these cameras is so low that even if I just have my lamp on, it's like all fuzzy and noisy, you know.
Speaker 2:You should make a
Speaker 1:It's terrible.
Speaker 2:Get a warehouse and get a bunch of, like, yoga mats and have the VisionPros and it's a VR movie theater. You go and you just lay in the bright super bright. It really is
Speaker 1:like the most dystopian antisocial thing you can possibly do. But The Matrix is a great movie, so it was worth it. I sacrificed
Speaker 2:Worth it.
Speaker 1:For the for the board.
Speaker 2:And you broke the the record.
Speaker 1:I did. I did. The Guinness. Call Guinness right now. When you
Speaker 4:all aren't aren't live, you just move the table, put some mats down, and then you've got this.
Speaker 2:Yeah. It's perfect. This is perfectly lit.
Speaker 1:Anyway, thank you so much for coming on the show.
Speaker 4:Great to catch up. Thanks for having me.
Speaker 1:Good to see you.
Speaker 2:Yeah. Congrats to the whole team Thank you. Really Congratulations. Thank Incredible.
Speaker 1:Leave us five stars in Apple Podcast and Spotify. Subscribe to our newsletter at tbpn.com. And we will see you tomorrow at 11AM Pacific.
Speaker 2:Are you sure you gotta get out of here?
Speaker 1:Oh, yeah. You wanna keep going? I
Speaker 2:kinda wanna I keep
Speaker 9:I don't
Speaker 1:know. What else is in the news? We we if we got news, we can
Speaker 2:do it. We can get to it tomorrow.
Speaker 1:Okay. We can get to it
Speaker 2:Thanks for hanging out with us, folks.
Speaker 1:Thanks for hanging
Speaker 2:out Love you. We will see you Tomorrow. Morning. Goodbye. Cheers.