TBPN - The AI lab market map, Robinhood brings startups to retail, GLPs & hedge funds | Diet TBPN

Episode Date: February 19, 2026

Diet TBPN delivers the best of today’s TBPN episode in 30 minutes. TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays 11–2 PT on X and YouTube, with each episode posted to podcast platforms right after.Described by The New York Times as “Silicon Valley’s newest obsession,” the show has recently featured Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella.TBPN is made possible by:Ramp - https://Ramp.comAppLovin - https://axon.aiCisco - https://www.cisco.comCognition - https://cognition.aiConsole - https://console.comCrowdStrike - https://crowdstrike.comElevenLabs - https://elevenlabs.ioFigma - https://figma.comFin - https://fin.aiGemini - https://gemini.google.comGraphite - https://graphite.comGusto - https://gusto.com/tbpnKalshi - https://kalshi.comLabelbox - https://labelbox.comLambda - https://lambda.aiLinear - https://linear.appMongoDB - https://mongodb.comNYSE - https://nyse.comOkta - https://www.okta.comPhantom - https://phantom.com/cashPlaid - https://plaid.comPublic - https://public.comRailway - https://railway.comRestream - https://restream.ioSentry - https://sentry.ioShopify - https://shopify.com/tbpnTurbopuffer - https://turbopuffer.comVanta - https://vanta.comVibe - https://vibe.coFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

We have a great show for you today, folks. Specifically, Tyler Cosgrove has been on a little bit of a tear with the market maps. He dropped the final 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. There was some VC associate out there that was making a market map and which is devastated. All the companies I was going to put on the market map are now on. this market map. 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 is like a very underrated data source and there's like all sorts of cool things I think you can do right but I mean Groghapedia right so Groghcopedia is a little different because it's like generated on the fly right I took every Wikipedia article there's like seven seven to half million English ones and I ran them through an embedding model it was quen three embedding four B I think you speak Chinese yeah well show on in the Google. Whoa, he's got it down.

He's short. Okay. So I got to betting for every single article, right? So it's like basically every article has a vector. It's like 2,500. You do this a while ago, right? 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 direction in the embedding space that's like, of course, wants to how much like companyness something as, right?

You just find all the ones that end. Oh, you don't filter by like Wikipedia's. categorization of whether or not. So I use that, but that's not inclusive of every single company. So it's like a little bit blurry. Because some things are like, well, is it a company? Is it not? Yeah, I noticed some like railroads on here that look like maybe they're

companies, but they're like state owned. And where does that get in? It's kind of a blurry thing. So you can just use just what Wikipedia says. But you can basically find things that are companies. And then you have an embedding for every single one, right? So it's this big vector, super high dimensional space. If you map it down to 2D, you can have this, like, cool 2D map, which is basically

what I did. So you can see there's these big clusters, right? So it's like in the top left, it's all these theater companies or there's space companies. I noticed the aviation companies were pretty far away from the train companies. Is that the difference actually? Because you knew there was kind of like a bit of rivalry. Yeah, rivalry. They need to be, you got to keep those apart.

It'll just start fighting. Like when you map something down from like, you know, there's like 2,000 dimensions down to 2D, it's like very hard to keep like a ton of things. And it just randomly looked like the United States. Yeah, that has nothing to do with. That's so crazy. That was totally random. Because I looked at it and I was like, oh, OK, there's a lot of companies in Florida,

a lot of companies in the Northeast. Yeah, I didn't even realize. I was like, oh, it kind of looks like. And then I was like, 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. Yeah, but it's actually interactive.

So you can like look up a company and you can find where it is and stuff. Tyler Cosgrove.com slash Wikipedia underscore map. HTML. Wow, really a wordsmith with the URL's there, Tyler. Couldn't use a TLD-less domain. There are some fun ones in here.

Anyway, that's a fun project. All the links take you to Wikipedia, go check it out. And market maps are basically done, but a lot of the Neo Labs are not on this market map. And let's click over to Tyler's market map of the Neo Labs, because we've been tracking the Neo Lab boom. We've had a lot of these founders on the show. We came out of the world where we were like,

like, okay, there's DeepMind, there's Google, there's Open AI, now we got Anthropic, there's thinking machines, and there's a couple different companies. But the Neo Labs have exploded, Tyler, take us through what's going on in the world of Neo Labs these days. Yeah, so NeoLab is kind of this interesting term. Like, it's very broad. People say like NeoLab, it's not very clear what they mean because there's like broadly, I think it generally is like.

And this will make it clearer? Yes. Yes. I think after this, it'll be pretty obvious, like, what, you know, what are you should be looking at? how to think about these different companies. Yeah, I don't want to be more confused at the end of this. Yeah. That would be a disaster if that happened.

Yeah, that's not going to happen. This is going to be easy. Okay, got it, got it, got it. Go on. Okay, so let's just start, okay, so you have Neo Lab, right? Yes. So Neo is prefix, okay, you have to be relative to something. Yes.

So Neo is relative to, like, your tribe lab. This is your big lab. Traditional lab. This is your open AI. And let's give it up for the big labs. Yeah, they don't get enough credit today, the open data centers, spike in CAPX. So this is going to be your open AI, your deep mind,

your Anthropic. He's kind of your big lab. Yeah, XAI. XAI kind of fits in there too. Even though it's a newer Tad lab, it fits in with the big lab, they got a lot of money. Dario, I think on Torekash, he was like, yeah, three, maybe four labs, right?

So the forest is probably XAI. Yeah, I think you can also kind of throw in mistral in there. Okay, yeah, mistral's a little bit older, yeah. Yeah, I mean, mistral, there's much of these labs that were basically founded in the like two or three years before Chachaputee and then in the like six months after. Yeah.

So I think XAI's in there, mistral's in there. And these specifically, these, I feel like those trad labs, it's like they did a transformer-based pre-training run. They have their own base pre-trained. 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. So that's sort of like you're in the trad-lab world when you're thinking about like a big pre-trained run loosely. Yeah.

I mean, especially if you're talking about these big pre-trains, it's really just these four. No one else is really at that scale. Yep. Okay. So Mistral kind of brings us down into what I call the sovereign labs. You know, if you kind of look at this, it's basically just labs that are not in America. But I think also there actually is some meaning to this. So like Mistral, you've seen Mistral become kind of the leader in European AI, right?

So I think it was in Sweden maybe, they're bringing a new data center. Yeah. So they're kind of becoming like. Lots of stuff going on in France too. Macron is always talking about Mistral. Yep. It's a big leader. Cohere is also kind of, I think it has like a very, you know, Canadian.

It's Canadian company. Yes. Yes. But also has done their own pre-trains. No ties to the curling team, though. And then you can go back. You can go down, you can kind of see all your Chinese open source labs. This is your Kwan, Deep Sea, Kimi.

Unitary is also in there, right? Unitary, I think, so as we'll see later, there's also, I have sectioned for, like, robotics labs. Sure. Take us back in time now. What was going on before the Trad Labs broke out? Yeah. So here I have this section Legacy Labs. Okay.

So these are ones that are kind of more entrenched in these big enterprises. Yep. So you have stuff like Microsoft Research, AT&T, Bell Labs, right? Oh, Bell Labs. Yeah, but I forgot about Bell Labs. After, you know what, you know why they call it Bell Labs? Why do they call it Bell Labs? Alexander Graham Bell.

Yeah, it was founded by him. Yeah. Bell Labs. Okay, but also you have fair, Facebook AI research. This was like, I mean, there's so many like OG research papers that came out of fair. Yeah, Jan Lacoon. Yon LeCoon used to be head of before it transitioned to the MSL. Yeah, MSL.

Around your T-Rad Lab, you'll say have post-lab, right? P-O-A-S-T. Yes, these are posters. Yeah, these are labs where you get a lot of posters, right? So obviously, this is opening out. You got Rune, Anthropic, a lot of, you know, Shulto, et cetera. Yep, got posters over there. Prime Intellect.

They're great posters. They're great posters. Yeah. A bunch of Anans at Prime Intellect doing great stuff over there. For sure. And then you kind of get into the core. The proper Neo Lab. Yeah, the proper Neo Lab.

Okay. This is also a bit hard to identify because, like, what is actually the core of a new lab? What are these different kind of offshoots? I think Prime Intellect is kind of the prototypical. prototypical, like quintessential neolab. Okay. When you think of it, it's like fairly recent. Yeah.

It's still very much research focused. Okay. Like, sure, they have enterprise, like, you know, thinking about different stuff, but at the core of it, you're still like trying to find these like new novel approaches. It's research. You're hiring researchers. It's not just like engineers, sales guys, et cetera. So let's...

Wouldn't Sakana be more of like a sovereign lab? Yeah, I mean, so a lot of these can fit in all different places. Sakana would be, yeah, Japanese maybe. Okay. And you put MSL in here because it's a new project. Yeah, this one was also a bit hard. Thinking machines is my classic go-to NeoLab. I feel like it's post-open AI, Exodus,

and sort of open AI is nothing without its people. You get the spin-outs and you think thinking machines and SSI are two of the first case studies that sort of set the tempo for, OK, it's possible to do some research outside of the big trad labs. And so that's where you get the NeoLab boom from. And then a lot of the other companies I feel like are saying, saying, okay, we're going to do something similar to thinking machines or SSI, we're going to commercialize earlier, late, but we're following in that, and we're benchmarking to that.

Oh, they raised $2 billion, we're raising $200 million. It's easier. There's a 10% chance that we, you know, are at their scale, so you can underwrite it that way. Yeah. So thing machines also brings us to what I call the TradSAS lab. Okay. SAS Lab, you've trad SAS Lab. So I think the way I think about this is the Trad SaaS Labs are trying to basically use the data that's... inside these big enterprises, pull them out with AI. Okay. So this thing machines, right?

Rumored idea, right, is they're doing RL for Enterprise. A bunch of these 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's going to be inside the company. You can't really pull it out anyway. So it's having the AI be like internal, so you have applied compute, you have poolside doing all kind of similar things in this like enterprise LOM field. And then I have a Neo-SAS lab, this is different than trash. SASS.

I think these 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. Also much more of like startup focus. But they're making a product that is sold effectively as SAS. So cursor, cognition, windsurf. I have ramp labs. Ramp labs.

These are seat-based sort of consumption-based. But it's a product that's vended into a, and the product is what you get and then sort of customizes as you integrate it, but it's not, it doesn't, the conversation doesn't start with a business development relationship. Yeah, and of course, I mean, these lines are pretty blurry. Okay, let's go down to the post lab. 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 think of it. Okay. So you have meter, you have epoch, these are going to do e-vals. Yep. You have pangrum.

They're seeing is the, is the model producing slop? Yes. or is it producing text that you're using in some way? Yes, yes. These are purely e-valed. They don't have necessarily AI products themselves. They don't necessarily sell to big businesses. But they could still be training models, right? Like PandGram is training models that sit on top of the lab.

That's true. That's true. So it counts as the lab. And then maybe that brings us down to the safety lab. Yes. So these are pretty interesting. Anthropic kind of fits in this, right? Because they have a big safety team. They're doing a lot of mechanistic interpretability.

You have Goodfire. I think they just raised at like 1.25 billion, And they're just doing mechanistic and capability. Let's go. Very interesting. Eleuther AI is a similar kind of lab. I know Eleuther, yeah. Okay, so then in contrast to the Sass Labs, yeah.

We have the consumer labs. Okay, consumer labs. So these are focused on consumers, right? So you have Eureka Labs. This is Andre Carpathy's project. I don't think there's anything been released from it yet. Education, though. But yeah, education.

Makes sense. It's for people. You have humans. Oh, it's four people, not four individuals working there. It's four people. Yeah. It might be four people. It might be one person, who knows, he's pretty good.

Yeah, you have humans and, right? This is the, I'm going to turn that phrase, it's like humanity focused. You're going to turn human into sand? Human sand. Human sand. Yeah, we got to hang out with the founders at the Super Bowl, but they're, but, yeah, focus on creating models that work better alongside people. So then that brings us down to the visual labs, right?

So there's a lot of either multimodal models or they're actually like producing. using video or images, right? We've talked to a lot of these founders. You have, okay, you have Neo Auditori lab. Okay. Right, so this is gonna be anything that has to do with vocals or voice or music, right? Yes.

11 labs? 11 labs, of course. Sponsor of TBPN, thank you. Suno, right, making music. Gemini also released a new model. Yes, for Leria. Lyria 3. Neo-Trad Lab.

It's a Neo-Lab, but it's Trad. Okay, so what does that mean? So basically, the way I think about a lot of these labs, is that they're extremely research focused. Okay. They're also largely, they're focused on, like, kind of a single idea. Yeah. So if you think of, like, Open AI, very research focused, obviously,

but they're doing a lot of different things. Yeah. So they have consumer, enterprise. Yeah, they have consumer, but it's even like on the product or on the research side, right? They're doing video images. SORA images. Yeah, but even within, like language models, I'm sure they have a, you know, continual learning team or all these like weird new shot things,

where I think a lot of these neotrad labs are basically focused on one single moonshot idea. Okay, so example, flapping airplanes, right? They just came on. They're talking about data fintency. This is kind of the one kind of moonshot idea, right? Obviously, it's like a very general, broad. There's a bunch of different ways you can tackle it, but they're like, that's the problem that we're going after. But it's one specific thing they're working on.

Yep. Let's move up a little bit. Yeah, what is Neo Lab Lab? Neo Lab. So these are a lot of companies that are focusing on, they're also like very research focused the point of the research is to build essentially like a researcher so they're recursive right okay so you have recursive and recursive yeah you have actually two that are recursive and recursive wet labs okay so these are your

bio labs oh you got lab corp yeah I'm familiar with lab corp but there's there's a lot of like biology focused labs it's actually like I didn't know a lot about a lot of these these are all your kind of neoconnect labs right these are fairly recently in the past like maybe four or five years broadly. And then the Neo Neo Lab. Neo Lab, right? Okay, so 1X is building Neo Robots. So there's a Neo Neo Lab.

That makes sense. Yeah. Yep. And then Legacy Kinetic is the previous. Legacy Kinetic is kind of the old gen. Yeah. But cooking. They're cooking.

Waymo's cooking. Yeah. Cruise and Boston Dynamics have been a little bit behind. Zook's also another self-driving car company. There's a bunch in here that I could have included. stealth, I think, that never really hit. You have your dark lab? Yes.

Working with the government. I have, yeah, I have Shield AI. I also have DARPA. DARPA is a lab. Yeah, they invented the internet, right? GPS. Yeah, so I think this should be pretty obvious to anyone who's thinking about neo-labs, like I should be thinking about them now.

But these things are coming out like every day, right? And you put the typos in just to prove that what typos? Human, like Sovereign Lab, and then. Sovereible intelligence also has a typo. And so I just want to make sure, I wanted to make sure people do, you put the typos in so that it was proof that you made it. Yeah, yeah. I don't want to.

Well, yeah, whatever you built this in doesn't have spell check, I guess. One show, two maps. One show, two maps. Strong start. Robin Hood says historically investing in private markets was limited to institutions in the elite, but not anymore. With Robin Hood Ventures, you can now get exposure to private companies. companies like the ones listed below. They have a new fund that has Databricks, Merckor, Revolut, Air Wallachs, Boom, Supersonic, Ramp, ORA, and Stripe, which is signed and pending

close. 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, you know, if this is coming out from your head of investor relations, it's not exactly a Matt Grimm style response. They bought Databricks at $150 $50 per share, now trading at 204 ramp at 90, now trading at 98. Airwallach's $21. It's now trading at 18.8, and then Mercor at 714 now trading. So I've already seen a little uptick. Anchor came in and was sharing some of his sites.

It was 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 Anthropics, SpaceX, and OpenAI, SBVs. He says, two, the structure of this fund is broken. As a closed-end fund, the price here can diverge very significantly

from the net asset value of the underlying assets. With FOMO from Access, this easily traded a very high multiple 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 It's a great disclosure. It's a great disclosure.

Long. Elon Musk announced that XAI is moving away from traditional academic benchmarks like Humanity's last exam to focus GROC on maximal utility for real world engineering and software development. He said, actually, I don't think HLE is a great measure of usefulness for moving away from these benchmarks. Andy Scott says, so it's bad, question marks. I think it's totally fair to just focus on real world utility.

but of course people are still going to ask. Well, I still want to know how it does. So GROC 4 has already been out. This is a minor revision. And 4.1. 4.1. So now we're at 4.2. Historically, especially when Grog 4 come out,

people were like very, very quick to say, it was like, oh, this is so benchbacks or whatever. I think they've definitely retreated from that, like, at least path with 4.2. It doesn't look like outrageously benchmarks or anything. They did this kind of interesting thing where it's still not, like, fully out. It's still like in beta, if you go on the Groc, like. interface. They did this kind of distinct thing where there's like four agents.

Okay. Every time you actually do a prompt, there's like four agents and the agents specifically have like distinct roles. Okay. 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. Instead of mixture of experts, mixture of agents. I wonder, I wonder what the bulk case is here for XAI. There's a world where they carve out some sort of niche, you know, Anthropics, like focused on coding very specifically and, you know, had some major, major gains there. What else is there? Also, it is interesting to think about with the cerebrous 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 iterate towards on a faster time horizon than other chip companies? I mean, they do custom sell. Like, and they've done it for a long time and they got an entire self-driving model that runs on a car so, you know, they have some experience there. Tarek says I'm proud to share that Humane has invested $3 billion into XAI

Series E-Round just prior to its historic acquisition by SpaceX. Through this transaction, Humane became a significant, a significant minority shareholder in XAI. The investment builds on our previously announced 500 megawatt AI infrastructure partnership with XAI

in Saudi Arabia. Maybe, you know, have wanted to get this out before the SpaceX acquisition, but better late. Wait, wait, they said they got in before the acquisition. I know. You mean the news? This round got announced a while ago, so maybe they would, they're coming out with this news today. Yeah, but they're saying, hey, we got in before the acquisition.

So we got, we got SpaceX shares. Yeah, I don't know. It's odd that it's the way. Better late than never. Yeah, you mean on like a comms front. 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. Recently, Jeff Bezos, who never tweets, this was his first tweet of 2006, posted a photo of this, like, black tortoise, which goes along with Blue Orleans, the motif of slow and ferocious, methodical. But a lot of people have viewed it as a warning shot to Elon Musk, which,

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? Well, it gives me an opportunity to put on a t-shirt for you, so there you go. That's that.

Nothing else, let me do that. Will I get to keep this? Yeah, that's all yours. And that's the first one off the presses too, by the way. I think everybody's gonna want one of those. He t-shirted Ma Bloomberg. Doesn't have to lose for Blue to succeed.

What the US needs, is it needs two SpaceX's. It needs two launch companies 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 to be moving very quickly.

Healthy competition. But I think a lot of people read into that as the tortoise being Blue Origin and the hair 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 going to get the contracts.

So do you think you're going to get there first? I think if asked, we will make it, we'll give it a run for our money. I like our architecture. I like our odds of getting there very quickly. I don't have a crystal ball into what SpaceX is doing. I think, again, Gwen and Alon are competent, and they show it every day. launching rockets. But I love the fact that the U.S. 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. Move heaven and earth. Powerful line. The moon race is going to be fun. I think it's shaping up well. I mean, yeah, a little bit of a tortoise and the hair story, a little bit of come from behind. I'm not buying the tortoise as ferocious. Yeah, I don't love you now. I don't really love the analogy. Like, I don't think it's the best calm strategy. Like, I like the vague posting out of Jeff. It gets the people going.

But at the same time, just imagining BASX as a hair, just like running a bunch of laps around the tortoise, just kind of. They need to take this way further. Elon needs to wear tortoise shell glasses. Be like, I turned your tortoise into my glasses. And Bezos needs to start carrying a rabbit's foot for good luck. That would be the hair.

Like, I got your foot. We have some breaking news. What's that? Claude Oath is officially not allowed an open claw. So Anthropic is responding to the OpenClaw, OpenAI news. This would be a great time for Sam Altman to step in and let us use OpenAI subscriptions with OpenClaw. So in the Claude Code docs, OOath and Oath authentication, which is used with the free pro

and max plans, is intended exclusively for ClaudeCode and Claude.A.I, using OOTH, tokens obtained through clawed 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. Out of the journal, the fossil fuel tycoon teaming up with the Rockefellers to fight energy, poverty, I'm sure the online conspiracy community will love this one. EQT chief executive Toby Rice is starting a nonprofit to tackle a lack of access to modern infrastructure in poor countries. Toby Rice made his fortune unlocking a gusher of natural gas in Appalachia. He has a bold new ambition, bringing energy to millions of people in impoverished nations. Rice,

the chief executive at EQT, one of the largest natural gas producers in the U.S. is a co-founder of energy corps, a nonprofit, 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. Notably, this approach has been endorsed by the Rockefeller Foundation,

one of the oldest and richest foundations in the U.S. They really opened up the floodgates 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 Gs. 200 K. Go solve it. Go solve energy globally. 200K, there you go. Best I can do is 200 bucks.

I'm super excited about this. I think McCrone deserves a victory lap at this point. I mean, his, McCrone's size is looking. Yeah, it's size. It's size compared to this. Should impoverish society 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. It's the world's lungs. Everyone suffers if that happens, but they would certainly benefit in the short term. So there's a hot debate here, and he is engaging in it. David Holtz has hit the timeline. He says 5 million humanoid robots working 24-7 can build Manhattan in six months. Now just imagine what the world looks like

when we have 10 billion of them by 2045. Now imagine the year 2100. Dyson sphere. Dyson sphere. Dyson sphere. Dyson sphere by 2100 is the year. the is the correct like debate. I keep, uh, I keep going back to my land thesis. Yeah.

When armies of robots can build anything. Yeah. Anytime what, what is actually scarce? In this case, I think with, uh, 10 billion of them, I don't even think land will be scarce anymore. It's like, hey, we're making, we're going to build an island. We're going to build another moon. We're building the moon.

New moon alert. There's, there's no moon alert. Just build another earth and just throw it on the other side of the solar system. Yeah, yeah. I mean, it's, it's, you know, right now we're talking about. about what businesses are unslopable. The next meta will obviously be unclancaable. Unclankable.

Richard says SF guy eating a delicious blueberry. In 18 months, everything will be blueberries. This is a perfect contrast to the other post. Just two sides of the SF discourse. No, no, no, David Holes. David Holes is like, because David's seen humanoid robots. Like he's lived in SF and been around this stuff. Like he's a true believer.

and he's sort of saying, like, I've seen what they can do, and I understand the exponential here, and now imagine 10 billion of them in 100 years. Like, it's going to be crazy. And then you have Richard on the other side. Everything will be blueberries. I thought you were talking about the delicious tacos post. He said, I'm the CEO of a hot dog company. I've worked on hot dogs for 10 years, and I wasn't prepared for what I've just seen.

Your life is about to change. So what can you do? Buy as many hot dogs as you can. buy stock in hot dog companies. It's a good idea. I am long hot dog. I like hot dogs. Hot dog market map.

Good with the kids. Everyone loves a hot dog. Hot dog. It's all American. There's nothing better than a hot dog at a ball game. Oran Hoffman is sharing that OZempec is bad for business. A few months ago, someone told me they had heard a rumor that a banker hedge fund had banned its traders from taking OZempic Wagoe and other GLP1 weight loss drugs.

Theory, as I understood it, was something like traders need to make quick decisions based on gut instinct and GLP ones mess with your gut instincts. You're not hungry for snacks. You're not hungry for profits. You lose your edge. Orrin says GLP is getting banned by hedge funds, maybe by sales teams too. Yeah. Killing your grind set. Your gut instincts for some people saying put on mass. Scale. It's time to scale. Time to bulk. Bulking seasons here. Get off the GLP ones and start levering up. Dr. Cameron Maximus says, guess what increases drive testosterone, a microdose of epitide to cut down on physical appetite, macrodose of testosterone, amplify psychological appetite. So the solution is, we're going to ban GLP ones only if you're taking them solo.

You've got to be taking a full stack. Did you see bone GVT say, turns out you really do got to be hungry for it? What about a hair bench? Hair bench. What's hair bench? Gabe says, Jordy needs to bring Tyler with him when he gets his haircut. Haircut, haircut. And then, And Dave, Tyler asked, and I sent him my barber's information. So I think they're working on it. Haircut alert. We got to get a card up. Jordy doesn't want to do it, but I think we should put up a card for Jordy's new haircut.

We don't like secret haircuts. Overheard in SF, a VC was giving advice. Open AI and Anthropic are like Godzilla. You need to find an alleyway to hide in. What a funny thing to say. 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. I'd be like, you know, like, there's plenty of startups that's just like don't touch software. Just don't do anything with code. Just don't do anything with technology. Don't do anything with a website. Don't do anything with the website. If you need a website to do business. I'm short.

I'm passing. You're cooked. It's over. It's over. It's over. It was fun. No, but clearly, I mean, there's plenty of like brands and products and technology and all sorts of things to build. Thanks for hanging out with us, folks.

Thanks for hanging out of us. We love you. We will see you tomorrow. Morning. Good morning. Goodbye.