TBPN Live - AI Boom Hits Speed Bump, Will Blue Owl Capital Fly Higher? | Jeffrey Katzenberg, The Winklevoss Twins, Hims & Hers CEO Andrew Dudum, Coatue’s Spencer Peterson, Max Hodak, Melisa Tokmak, Tomás Puig

Episode Date: November 13, 2025

(00:20) - AI Boom Hits Speed Bump (11:56) - Will Blue Owl Capital Fly Higher? (26:08) - AI Boom Hits Speed Bump (34:35) - 𝕏 Timeline Reactions (59:12) - Spencer Peterson, a general partner at Coatue Ventures, leads their growth fund focusing on late-stage, transformative technology companies. In the conversation, he discusses Coatue's investment in Cursor, an AI-assisted software development service developed by Anysphere, highlighting its rapid growth to a $9.9 billion valuation and $500 million in annual recurring revenue. Peterson emphasizes Cursor's unique culture, exceptional team, and the broader potential of AI in software development, noting the significant opportunities in the expanding market. (01:25:50) - Tyler and Cameron Winklevoss, co-founders of Gemini and Winklevoss Capital, discuss the launch of Cypherpunk Technologies, a rebranded public company focused on privacy and self-sovereignty. They highlight the company's recent $50 million investment in Zcash (ZEC), purchasing 203,775.27 ZEC at an average price of $245 per token, and their long-term commitment to holding these assets. The twins emphasize their belief in Zcash as a means to move value privately and their strategy to avoid fast capital by being the largest investors in the company. (01:29:49) - Max Hodak, a biomedical engineer and entrepreneur, is the founder and CEO of Science Corporation, a neurotechnology company developing brain-computer interfaces and retinal prostheses. In the conversation, he discusses his journey from co-founding Neuralink to establishing Science Corp, focusing on their development of the Science Eye—a visual prosthesis aimed at restoring vision for individuals with conditions like retinitis pigmentosa and age-related macular degeneration. He also elaborates on the company's innovative approach to brain-machine interfaces, emphasizing non-invasive technologies that avoid the need for in-skull implants. (02:02:27) - Andrew Dudum, founder and CEO of Hims & Hers Health, discusses the company's evolution into a leading telehealth platform offering a wide range of services, including cardiovascular risk assessments, weight loss treatments, and mental health support. He highlights the company's commitment to providing accessible, high-quality care through digital means, treating millions of patients daily. Dudum also emphasizes the importance of preventive healthcare and the role of personalized diagnostics in improving patient outcomes. (02:21:08) - Melisa Tokmak, founder and CEO of Netic, an AI company based in San Francisco, discusses how Netic's AI revenue engine assists essential service industries—such as HVAC, plumbing, and electrical services—in managing fluctuating demand by deploying AI agents to handle customer interactions efficiently. She highlights the challenges these industries face, including labor shortages and seasonal demand variations, and explains how Netic's technology enables businesses to predict needs, convert one-time interactions into recurring relationships, and maintain high service levels during peak times. Tokmak also shares that Netic recently secured a $20 million Series B funding round led by Founders Fund, emphasizing the company's strong fundamentals and commitment to building a business with solid margins and efficient scaling. (02:35:37) - Jeffrey Katzenberg, Founding Partner at WnderCo, discusses Alembic's recent $145 million funding round and its innovative approach to causal AI, which helps Fortune 500 companies understand the direct impact of their marketing and sales efforts. He highlights a case study with Delta Airlines, where Alembic's technology identified that the most profitable content during the Olympics was not traditional ads but the Delta medal presentation ceremonies, leading to increased ticket sales to Paris. Katzenberg also emphasizes the importance of ingesting vast amounts of data to provide actionable insights, enabling businesses to make informed decisions and optimize their strategies effectively. (02:58:11) - 𝕏 Timeline Reactions TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comPolymarket - https://polymarket.comAttio - https://attio.com/tbpnFin - https://fin.ai/tbpnGraphite - https://graphite.devRestream - https://restream.ioProfound - https://tryprofound.comJulius AI - https://julius.aiturbopuffer - https://turbopuffer.comfal - https://fal.aiPrivy - https://www.privy.ioCognition - https://cognition.aiGemini - https://gemini.google.comFollow 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

You're watching TVPN. Today is Thursday, November 13th, 2025. We are live from the TBPN Ultradome, the Temple of Technology, the Fortress of Finance. The capital of capital. Ramp. Time is money. Say both. Easy to use corporate cars. Bill paying accounting a whole lot more all in one place.

There is a bunch of breaking news. The big news out of Open AI. Of course, the Open AI show continues. Sarah Fryer had some comments about chat. is growth potentially slowing, and it's unclear. It's not in decline. It's maybe deceleration. We'll have to dig into that. It had me thinking about debt, and I was thinking about just the fact that the debt has come to tech for the first time, really. And this was sort of my take, and I'm a little bit, this is an area that I know the least about. And so I was doing some research, learning about a different

industry since it's just so abstract to me because I've never worked in private credit or really seen that industry or even just really studied it. You appreciate leverage. You've never been a big... I appreciate it. Yeah, and mostly I was just wondering, like, we keep going back and forth on the debt is coming to tech narrative as like, it's very scary. Like when debt comes, only bad things happen. You know, we live through the global financial crisis. And there's a lot of jitters when debt is around. It's like, oh, you could get wiped out. You could blow up.

The backstop comes in. It just feels like all of a sudden we're talking about things with a much more serious consequence than like, oh, yeah, a startup raised some money, and it didn't pan out, and it was a zero, and it wound up being a write-down, but it was part of, you know, a portfolio of equities that is averaged out across a whole bunch of different LPs. Like, there's no, there's no, even when, you know, like Theranos blew up, it was only equity holders that were lost. It wasn't this higher, entire industry. And so, it wasn't, it didn't turn into this, like, systemic issue, right? Yeah. But now it feels like with the $1.4 trillion of, you know, backlog that Open AI has kind of opened up across a whole bunch of different deals, there is this worry that, you know, maybe the level of indebtedness could be risk. You know, ski, the level of risk in the system, the level of investment in the system, could be something that's bigger than just, oh, if you're in this one name, you're taking a big risk. Now it's maybe

like, hey, we're all taking a risk. And if we're talking about backstops, at least. And so I was trying to understand, there's this old phrase from 2006 coined by Clive Humby, classic coinage. I love a coinage. He said, data is the new oil. And back then in 2006, his point was he was working as a data scientist at Tesco, which is this British grocery store. I don't know if you know this story. But he was working at this British grocery store chain. And his point was, we have all this data on a customer is in the rewards program. We see that they buy a Thanksgiving turkey before Thanksgiving.

We see that they buy this type of paper towels or this type of milk or whatever. We have all this data, but we don't really do anything with it. The data is not valuable. We need to refine it, much like oil. into gasoline, and once we refine it into gasoline, then we can do things like targeted advertising and we can increase our customer value. And so it was basically just a generic call to action for taking data science seriously, for just, don't just have the data there, understand that the data is valuable if you extract it, if you work on it. But the metaphor, people have been saying

data is the new oil for, I guess, two decades now. And it never really sounds. And it never really that well with me because unlike oil data is not perfectly fungible. So one tranche of data is not equivalent to another. Like Reddit is clearly very valuable since it kind of provided the backbone for GPT3. All the analytics data that flows out of some mobile game is basically used. A lot of data is worthless. A lot of data is worthless. All oil has at least some value.

Essentially, I mean, I guess there are different levels of crude, right? They're different grades. And I was actually trying to play out the metaphor more. I was wondering, like, can we get to a place where, you know, we can ring intelligence out of raw data, like the oil. And the result can be low-octane gasoline, kind of like midwit, you know, level, like slop and AI slop. Or it can be jet fuel, like a deep research report that's actually pretty great, or some

code that's really reliable and really useful. But it all depends on the processing methodology. but the more interesting data is the new oil take that I don't think was considered in 2006 is that maybe the tech industry is going to look like the oil and gas industry soon like I was looking up what how much debt is in the oil and gas industry it's over a trillion dollars of debt and it's like it's fine like yeah exactly yeah clap it's fine like it's not this like huge systemic issue it was two trillion a like you know a decade ago and then it went down and then went up and it's like it's all just a function of like how much oil and gas is going on how

what are the new projects how big are the projects how much debt goes in like just having a lot of mortgages in america is not intrinsically risky okay the difference the difference is that if you identify oil in the ground and you figure out how much it's going to cost you to extract it and how long you think you'll be able like basically estimating like the how much how much oil is actually available in this site yeah then you can lend against that pretty predictably because you know that the price of oil is going to fluctuate, but in general, as long as it's in some range, it will be like a profitable operation to pull it out of the ground. And I think it's a little bit easier to lend against that than GPUs today when we're, the big debate is around depreciation schedules and will these GPUs, you know, we, we have a sense at a data center that has power and basically a box.

with a lot of power will be valuable in the future. But if a lot of the cost of a new data center is GPUs, it's harder to gauge on what the value of those GPUs will be in four years than it is, okay, will this oil, like production site, still be producing oil in five years? I think that's a bit easier to answer and easier to lend against.

Maybe. I mean, sometimes there are tracks that only pretty, oil for four years, and you underwrite it against a four-year depreciation schedule. And as long as you match the risk to the reward, the deal pencils out just fine. But I understand what you're getting at. And I think that as we dig into the Open AI news, I think we'll have more, we can synthesize some of the recent leaks and rumored statements around potentially a plateau. and demand for tokens on maybe the consumer side.

But it is just like a wildly different question. Like the fact that you're walking through that math is very different than what the venture capitalists in 2000 were doing. Like Ev Randall, who's coming on the show on Friday tomorrow, he always says he goes back to the Google prospectus from when they IPOed. And Google was like the most pure play. just beautiful software business. So Google from 2001 to 2004 grew from 86 million in revenue to 3.2 billion in revenue.

And net income over that period went from 10 million to 400 million. And that includes stock-based comp. So they were still making 400 million in profit with the stock-based comp. Googlers made a lot of money. They gave away a lot of stock. And so it was not, it didn't look like an oil business. There was not this big KAPX build out. There was not this big, or even this crazy R&D phase.

There wasn't that much capital that went into Google before it became this monster cash flow machine. It was just a beautiful. It was sort of an infinite money glitch. It was this beautiful algorithm that was just discovered and it was so elegant and it just produced this monopoly insane growth rate for so long. And then, of course, they've been challenged and they expanded and there's million things. And then eventually KAPX did come into the picture as they grew.

through their cloud infrastructure, GCP, all this other stuff. But for a long time, like, tech just meant take a bet on a company, and it's either a zero or a trillion dollars or something like that. And so it's a lot different. And I wanted to dig into, like, the actual structure of one of these deals, because I don't, I think that tech people, I was almost going to call this, like, why is no one talking about Blue Owl, because people, obviously on Wall Street are definitely talking about Blue Al. It's a public company that stocks, I think, down like 30, 40% this year. But it's the data center of finance.

Private credit. Yes, private credit, exactly. And so I wanted to understand, like, how does Blue Al actually interact with one of these data center deals? Because that's important to understand, like, where the risk winds up living. So I'll break one of these down. But first, I'll tell you about restream. One live stream, 30 plus destinations, multi-stream and reach your audience, wherever they are. So, for Hyperion, you remember the Hyperion release? Zuck went on threads and announced that he was going to be building a five-gagawatt data center, was going to be as big as Manhattan. It's like somewhat of a Manhattan project. Somewhat of a Manhattan project, exactly. So the crazy, crazy thing about that deal,

so he spins up the, he puts out the announcement post on, on threads, says, hey, we're going to build this five gigawatt data center campus. It's going to be online in a few years. It's going to be as big as Manhattan. And he shares some of like where it's going to be, how many racks are there going to be, square footage, stuff like that. But he's basically just announcing that like, hey, the project's financed. We're ready to go on this.

Like, you would expect that when that it's a $27 billion deal. You would expect that, okay, meta went down. They spent $27 billion. It's worth it. They're going to. No, they got paid $3 billion. They got paid $3 billion. And the reason is because Blue Al financed it with external debt and they are basically paying META up front for the right to have them as a tenant, as a leaser for a very long time. So they get this like, we have meta as a client. Meta is always going to pay their bills. They're not, they're like, no matter what

happens with the AI build out, they're going to be good for it because they have this cash machine. So they are like the best possible tenant. Not like some fly by night. Oh, yeah, I'm a startup, maybe I'll be around in a few years. It's like, it's meta. They're going to pay their bills. And so you have this massive data center project that's going to be paid for. Even if it's not producing any valuable tokens, Zuck's still going to, he's not just going to default and be like, yeah, take the company.

No way. He's going to pay. And so in exchange from that, they got $3 billion up front. And so there's just each one of these deals, I think the more you dig into them. I want to have more of these people on. Mohamed El Arian at Pimco, or it was formerly at Pimco. I know he can explain this a little bit more. I want to have more people on the show to help us get up to speed on this because this feels deeply important to the current AI buildout, boom, the tech story.

It feels like an entirely new piece of the puzzle to understand where this technology is going. And I don't feel equipped to understand it at all. Barons did have a great article about Blue Owl and a very funny interaction between Blue Owl and Jamie Diamond and They're going at it, and I think it's interesting to read through. So let's read through a little bit of this to give you a little bit more flavor on what's going on at Blue Owl, because if you're just in tech, if you're just in venture, you might not know that much about them. But first, let me tell you about Privy. Wallet infrastructure for every bank.

Privy makes it easy to build on crypto rail, securely spin up white little wallet, sign transactions, integrate on-chain infrastructure all through one simple API. So in Barron's, I had this, this article's from October 24th. I had it on the table. We never got to it. We're getting to it now. it's the title of the article is private asset star blue owl has been flying high is it too close to the sun this feels like headline jorny would write i'm very skeptical about uh about

what's going on in the a i build out in the a i boom uh but let's let's dig it and see how the phrase private asset star yeah i start calling our friends private asset stars for sure for sure uh so the article says suddenly blue owl capital is everywhere this past tuesday uh the upstart alternative investment firm with an aptitude for private credit, announced a financing deal for Meta Platform's $27 billion AI Data Center in Louisiana. That is Hyperion that I was mentioning earlier. The week before at the Pact CIAIS Alternative Assets Summit in Los Angeles, Blue Owls co-CEO's co-CEO Mark Lipschitz called J.B. Morgan Chase's CEO, Jamie Diamond, cockroach warning about risk and private credit, an odd kind of fearmongering.

So what happened there was we talked about that, that blow up in the private credit world. And I have a little bit of background on this. So where did you say this? So I need to actually pull up what happened with the private, with the cockroach statement, because it's very funny. Is that about first brands? It's first brands. Let me say first brands. first brands

okay so so basically private credit has been growing a ton we've talked about this a few times aries is massive now blue owl is really big and the whole and and there's basically been this little bit of a fight

emerging between where the debt is coming from do you do private credit or do you go with the traditional bank route and so Jamie Diamond at least I'm pretty sure he's going head to head against blue in a bunch of these deals. And so there's this question of like, you know, are they chirping at each other intentionally?

And so Jamie Diamond was cautioning investors about potential risks in the credit market by invoking a proverb. When you see one cockroach, there are probably more. And so he was referring to recent loan defaults, such as the bankruptcy of auto parts maker first brands and subprime lender tricolor holdings, as warning signs of broader credit issue. So Jamie noted, or Diamond noted, that J.P. Morgan took losses on some bad loans and implied that trouble in one corner of the credit market could mean undiscovered problems elsewhere, implicitly casting doubt on the booming private credit sector. And so Mark Lipschitz fires back and

says, I guess he's saying that there might be a lot more cockroaches at J.P. Morgan. And so he's, he's actually saying, like, oh, yeah, maybe you should go check out their books and see if they have other, you know, bad stuff. Because I, so first brands collapsed was an isolated case of alleged fraud, actually, in the syndicated loan market. And it was not in the direct lending arena where Blue Al operates. So Blue Al had no exposure to first brands. And yet, and yet Mark Lipschitz was still, you know, firing back at J.P. Morgan for kind of casting doubt on the, on the direct lending arena where Blue Al plays. So there's these, There's these cockroach statements, and they kind of go back and forth on this.

But the history of Blue Owl is also interesting. It's this like merger between a few different, a few different companies here. And it's part of this broader boom in alternative. Blue Al is, was the primary lender for Correweave. Corweave, and they've also done Stargate. They've done a ton of stuff. Yeah. And, but interestingly, their, their data center.

business is I think like less than a third of their overall business. They have a lot of other stuff going on here. So George Walker, who's the CEO of the old line money management firm, Newberger Bergman, Berman, he's a cousin of President Bush. He says, it's extraordinary what they've done. It was just a startup. And now their $26.6 billion market cap compares to a number of large century-old financial institutions. There were some Blue Owls, backstory entails some rich behind the scenes machinations, but more significantly, it reflects the stunning trajectory of private markets, which have tripled to 26 trillion in assets over the past decade. The company's also, yes. So, I mean, I do think it's important to keep like the scales

in mind here. Like the 1.4 trillion seems so big in the venture context. And we think about, we think about Sam Altman as a venture backed founder. But he's now playing in, a market that is playing a hyperscaler game. Yeah, he's playing a hyperscaler game. And so when I think about it's like 1.4 trillion, that's the same size as the oil and gas market. Meta's deal, Meta's Manhattan, like Manhattan Project Scale data center, the five gigawatt data center that you talked about, them doing this deal with Blue Owl on. Meta's also just at a $30 billion bond offering. Yeah. Which has four billion of 4.2% senior notes due in 20,000. and then all the way up to $4.5 billion of 5.7 senior notes due in 2065. And there was an order book of

around $125 billion for the $30 billion issuance. So there's a massive amount of demand. So this is not, at least that we know of what Open AI has not been raising this style of debt for the business. And it's unclear if there would be like a ton of demand for Open AI. like on balance sheet debt given that it's unclear if they're going to be able to spend, you know, what they've already used. Yeah, but underwriting a data center

with Open AI as a client is very different than underwriting Open AI directly. So there's some really funny quotes in this article. Blue Al is the pretty girl at the dance right now, says Wall Street trader David Williams. We're talking many billions in private credit. Ah, yes, private credit. Though Blue Al has three lines

of business, private credit, lending in private equity deals is the firm's calling card and growth engine and the straw that's stirring Wall Street's Punch Bowl lately. They also have this like GP business. If you want to buy a GP stake in an alternative asset manager, you can do that through Blue Al. But what everyone's interested in is this private credit specifically for AI assets, at least from our perspective. I'm sure there's other people that find the other pieces of their business, much more interesting. But its core direct lending business has 145 billion in AUM out of 284 billion total. So that's about half the fund. And that was conceived. The firm started in 2016 as Al Rock at the Putnam

restaurant in Greenwich, Connecticut, of course, comfort food is best by principals. Doug Ostrover, formerly the O of GSO Capital Partners, now Blackstone Credit. Craig Packer, a former Goldman Sachs partner, and Lipschitz, a former KKR partner. The name came from the wisdom of an owl and the stability of a rock, says Lipschitz. And the website was available. That always helps. So instead of relying on in venture,

we all think of the GPLP private markets fund structure, right? Jordy. Al Rock changed this. They don't do the typical GPLP split. They use what's called business development companies, BDCs. So those companies, issue stock and lend money to businesses, usually those with junk credit ratings, so something like a one-off data center that really only has like one client. It's not like Apple. It's not Microsoft.

It's not an actually, like, you know, been in business for 30 years. It's not the government. And so it's going to have a junk rating. It's going to be a higher interest debt instrument. And other, and this has actually been a trend. Other major alt firms are also turning to BDCs, which support higher yields. And so BDCs send some 90% of the interest collected on, those loans to shareholders through dividends. So they've basically created the same structure as a real estate investment trust or something close to it.

And so this has allowed them to scale. So two of Blue Owls BDCs are publicly traded. Others are private. They have Blue Al Capital Corp, which yields 11.4%. And Blue Al Technology Finance, which yields 9.9%. Both are down about 14% this year,

the former from January 1st. And so Goldman Sachs recently called the fears overblown about, you know, the risk of falling rates and weakening credit. And they cited Blue Al as undervalued, noting that it has a stock price to fee-related earnings multiple of 21.7, which is 5% below its two-year low. So the stock has been beaten up, but it still has like a buy rating from Wall Street firms. Blue Al has generated a stable, highly predictable stream of earnings, says Osterover, the other co-CEO. It makes no sense that, it makes no sense that we're down more than our peers, he says. If anything, we should be down less. I love it.

I love a defensive CEO. Love the confidence. Wall Street may be particularly wary of direct lending as shares of both Blue Al and Aries, which specialize in that business, have fallen hard. It's also true that both stocks had previously outpaced their peers. The second leg of the Blue Al stool was created years earlier when a Lehman Brothers executive, Michael Rees, started a fund at New Burger Berman, that bought stakes and asset managers like D.E. Shaw, this is what I mentioned earlier about buying G.B. Stakes. Rees named his endeavor, Dial, after his children, Dylan and Alexia. He just took his two kids' names and pushed them together, raised its own capital from Coke Industries, and invested in the likes of Silver Lake and Vista Equity partners.

So he was a vehicle to allow you to buy GP stakes in Silver Lake and Vista Equity, which are not publicly traded, I believe. In 2020, Blue Owl merged with Al Rock. And so the, the The resulting company was named Blue Owl. A bank working on the deal had called it Project Blue. So Blue was added to, and Rock was dropped because it was Owl Rock before. And so the hatching of Blue Owl was problematic to some companies in which Dyle had invested, particularly Sixth Street Partners and Galube Capital, both of which sued, claiming the new company created a competitor with sensitive information about their operations because,

of course, they own GP stakes in the companies. And so in 2021, Blue Al bought Oak Street real estate capital of Chicago-based firm, specialized in sale leasebacks and triple net lease deals as its third business. This wing of Blue L has AUM of 71 billion and is home to the meta-infestructure deal. So it's like a remarkably balanced stool. I'm sort of shocked when I was expecting it to be like, you know, oh, we hear about about Blue Al in the meta context, and that's their main business. Or it's a new thing, and it's only 5% of their business. But in fact, they have a pretty, pretty diversified offering across a few

different products. And so this wing now has 71 billion and is home to the meta-infestructure deal and others, such as Stargate data centers in Texas and New Mexico. Next, Blue Al is working on AI deals with N-scale and Valor Equity to finance purchases from Nvidia, whose chips go for $30,000 and up, according to people familiar with the matter. Well, built its direct lending business by borrowing from the Silicon Valley Playbook of scale first, monetized later, or by underpricing established private credit firms to gain deal flow and then raising fees later, most of the firm's direct lending business is done as part of private equity buyouts. So Toma Bravo, Blackstone, Warwick Pincus, these companies come in, and then Blue Al

does the debt side of that. These investments generally entail floating junk bonds, a business pioneered by Drexylburnum in the 1980s, but it was typically done with banks. Now it's done with these private credit firms. The private credit market has grown from $2 trillion in 2020 to $3 trillion at the start of 2025. So again, I'm like, that's growth,

but that's not the craziest growth I've ever seen. Like, when I go back to global financial crisis, you know, you hear about these like 10x runups in these derivative markets. Like, I don't know. I, it just feels like, it feels like we're still in like the early stages of actually ramping this piece of the capital

markets and marshaling that to the really crazy stuff. It feels like the crazy stuff's common in two years. I don't know. Yeah, and that aligns with Doug, from semi-analysis point. He was like, we're still early in the debt cycle. We're early. But at the same time, market has jitters. I was working on our 2026 merch this morning. Yes. And I had about an hour call. And so I missed the fact that Nvidia is down 4%. Coreweaves down 8%. And, uh, It's a little bit shaky out there. We're certainly not in white suits today. No, no.

Well, let's go over to the timeline. Let's go over to some of that other news that we wanted to touch on today. But first, let me tell you about cognition. The makers of Devin, the AI software engineer, crush your backlog with your personal AI engineering team. So Alex Heath has a scoop here in sources. During a recent private call, OpenAI's investors asked about external signs that ChatGPT's growth is slowing.

CFO, Sarah Friar. This is the external signs where I think like app store data. There were some data out of Europe. Oh, yes, yes, yes. That's right. And it was hard to read into the European data because Europe, Europeans. They don't work ever. No, I mean, it was coming off of summer, right?

And, you know, ChatGPT is popular. But European summer hasn't ended yet. European summer ends like late December. No, I have to push back on that because when the French television network came. That's true. They were clearly done. That was about a month ago. They were clearly back from summer holidays and they wanted to learn about the AI talent award. Yes, that's true. That's true. No, we're obviously joking there. Anyway, so there's been some... There's been early warning signs. Well, yeah, walking through some others. So I can walk through Alex's coverage.

It says on Monday, open AI, open AI CFO Sarah Fryer held a private. She was really hoping to just not be in the news cycle this week. But when you're the CFO of one of the most important companies in the world, that comes with the job. What bagholder is leaking this? Yeah, that's my question. Private call, you're an investor and you're leaking bad news to sources. What are you doing? Did you get out or something? Like, are you, have you somehow facilitated some short position? Yeah. He jumps off the call, marking... This isn't very founder-friendly.

Whoever's doing this? Whoever's doing this is not very founder-friendly. Okay, anyway, excuse me. Anyway, Sarah Fryer held a private quarterly earnings call with the company's biggest investors. As usual, the numbers she shared were mostly up into the right. But behind the strong, top-line figures, a quieter question hung over the call.

Was Chat-GPT's momentum starting to slow? During the Q&A portion of the call, sources say Friar was asked to reconcile Chats GBT's meteoric growth and weekly users from 250 in September 2024 to over 800 million now, with external signs that the app's growth has slowed in recent months. Close followers of opening eyes business have been whispering about these signals from research firms since late summer, but this was an opportunity for company backers to hear directly from leadership on the matter. After telling the investors to take third-party estimates with a grain of salt, Friar acknowledged a chink in chat GPT's armor. She said time spent had declined slightly in response to, quote, content restrictions. The company rolled out in early August. She then referred to the loosening of those restrictions that CEO Sam Altman has said will be implemented for adults in December. So this is them. Sam came out and said, we're going to allow erotica on the platform. And Sarah says, an opening. I expects the decline in time.

spent to reverse. And so this reminded me of a conversation we had about exactly a month ago where I said, I don't think them announcing that they're getting into erotica is a sign of strength. I don't think that's something that you do just because you want to, right? In my view, it felt like clearly, I mean, clearly there's user demand for it. Yeah. But at the same time, that felt like something that they would do in order to stimulate growth while they get a bunch of other monetization online, right? So like commerce, ads, et cetera. Yeah, no, that makes sense. Yeah, I mean, the original, like, founding team at Open AI was incredibly idealistic, right? Like, incredibly, like, you're going to work on a nonprofit on, like, superintelligence, like,

AGI, like, you truly are working on, like, what you see is one of the most important problems. What I agree with is one of the most important problems. Then, of course, like, you know, eventually the company evolves and you bring in business leaders. But at the same time, like, I do believe that what they say, I want to cure cancer. I believe that. I believe that. But the reason I reacted strongly to it was that there had been messaging, you know, around the same time of, I don't want to be in a world where we have to decide between curing cancer and free education for the world. Yes. And so then at that same time, deciding we're going to do erotica.

It was very weird timing. It was very weird. It was very weird timing that those two statements, like, came out one after another. Yeah, I'm actually surprised why they're waiting until December to roll. out the adult content. So in this scoop, do we have any, do we have any specific data on, on what exactly, what exactly, you know, is indicated in terms of ChachyPT's growth slowing? Can we actually try and define that a little bit more? Is that, is that users, because there were already at almost a billion users, is it, is it time on site, is it monetization?

I mean, deceleration, we were talking about this. like, Open AI has decelerated revenue before because they, I think they tripled and then they went to a doubling, or they went, or they were quadrupling, and then they went to a, to a tripling. And so they actually decelerated in 2024. And then they re-accelerated in 2025. And so I was kind of saying, like, well, you know, this is a good chance that you could see deceleration in the future. It's happened before. Like, to be accelerating forever is basically impossible. But it would be interesting to track. exactly how chat GPT's growth is slowing, there certainly feels like there's just a level of saturation. Do you have the stats? Yeah, so similar web put out some information on month-over-month change in total visits to leading gen AI tools. ChatGBTGPT is at the bottom of a list that include is Gemini, DeepSeek, perplexity, grok, Claude, co-pilot, and meta-a-I. The key difference here is that, like, ChatGPT is just so much bigger than these other. platforms that they could still be adding more users on a on a on a on a on a on a on a

on a on a on a on a on a on a user basis than these other tools even if their growth is slower yeah yeah that makes sense I mean they do expect their growth to slow down so like from this is epoch AI they it was like yeah opening eye revenue estimates yeah so 2025's 13 billion and then they expect 2.3x 2026 two X and 2027 and one point six x yeah so i mean it's not like they're just saying like it's it's going to go from two x to three x to four yeah exactly so i wonder i wonder how much of this is just framing something that was sort of already priced in as a as like a bad thing like i feel like

people were expecting deceleration and so if if she's if she says like if she's on the call and She says, as expected, we're really big. We're going to be decelerating the level of new users that we're adding. I don't think she should say that. Yeah, maybe that would be bad framing. I don't know. It just doesn't seem that crazy. Please don't say that.

I don't know. It doesn't seem like that bad of a thing to say. Like the meta is not accelerating top line users. they have like 3 billion users like no one's expecting them to accelerate top line users maybe like randomly one quarter they accelerate

but not continually and so I don't know it just feels like an odd thing did you get a chance to read the Ed Zitrin article this thing I did but I didn't I felt it Ed is such a massive open AI

hater sure that I think it was hard to and the sources were pretty unclear it was hard read too much into it. Okay. Okay. Well, let me tell you about figma.com. Think bigger, build faster. Figma helps design and development teams. Built great products together. You can get started for free. Should we head over to some timeline? What else people are saying? Cairo Smith says it's going to be very funny when LLM's plateau around 120 IQ. And what we've created is just a digital guy, not a god. I mean, this doesn't make any sense. If we have like infinite

digital guys, that's like literally a guy is just like a worker. If we have infinite workers, that's like insanely bullish. Yes. It'll be bullish, but we've been promised, you know, people are promising. He didn't say bearish. He said it's going to he didn't say it's going to collapse

the economy when we just get a digital guy. He said it's going to be funny. I agree. I guess that's true. It's funny. But this is still like a very bullish take. I think people, I think you might read this as like being he's kind of bearish. Yes, yes, yes. No, I know. I know. I think you're right. If you get a digital guy, that's pretty powerful. Because guys can do a lot of stuff.

It's valuable. I love guys. Yeah. You need a guy for everything. You do need a guy for everything. And you will in the future. And that's one of the great luxuries, right? Yeah, that's the middle class has apps. Yes. The wealthy have guys. Yes. And the and the apps get better with the, the apps get better with AI agency, AI agents, right? Because you, you have, you have an app that a little bit more like a guy than a... Real quick, Scoot in the X-Chat. Almost bought a counterfeit TBPN hat. No way. Watch out.

There is a counterfeit TBPN store. These are not by us. They've made it look like it's by us. I'm not going to name the link, but we have not sold any merch. We will make the merch available as soon as soon as possible. I was working on it this morning before the show.

So it's coming, but do not buy any of the counterfeit merch. My big concern with that site is I don't even know if they ship it. Yeah, that is a big question. And they also made like 100 products. They made so many products, and I did email them. And to be clear, I emailed them. And we've submitted a bunch of take-day requests. Yeah, when I emailed them, I was like, hey, like, I assume like you're just a fan.

Like, I was being too nice. I was being golden retriever mode. I did say, I was like, hey, like, I, you know, I appreciate this idea. This is, this is very cool that you're enjoying the show. But, like, we just don't want people to get confused. We have our own plans for a store. They're like, okay, I'll make 200 different products. They just didn't respond at all.

And so then we sent a take down notice, and we will be fighting that tooth and nail. So stay safe out there. But please don't buy it because we have nothing to do with it. Tyler, did you get a chance to read Fiji Simo's latest blog post? moving beyond one-size-fits-all? I hope you didn't read. I hope studied. Sat your ass, Stephen.

We talked about this for a tiny bit yesterday. Yes, yes, yes. This was just the 5.1 release. Yeah, nothing, I would say, super supplementive in it. She kind of is talking about how, I think, with 5.1, they were going on. Like, we made our digital guy faster, better, stronger. Is that what it is? She talked about the EQ.

Okay. of the model lot, rather than IQ. Yeah. So that's why you see a lot less benchmarks. I think it's just hard to actually benchmark that kind of stuff. Yeah. But the actual, like, style of the model, I'm talking about kind of safety-ish stuff,

where there's like, you know. I mean, it is crazy following this company so closely because in here there's a line that says, with more than 800 million people using ChatGPT were well past the point of one size fits all. And 800 million sounds amazing, except I feel like I heard the 800 million number, like two months ago. and I feel like they have been accelerating so fast.

You would expect them to be a $9.50, $900. Exactly. And so the fact that they're repeating the 800 number is like, they're like, sorry we can't add a third of the United States every month. I know, I know. It's very, very high stakes. It's very impressive they're built to be clear. But I just, I am really keyed on that like $800, 800,

because I was excited. They were going to hit a billion. It was going to be a big moment. And yet it feels like maybe that's a next year to a next year goal. But NIRSyan has been going back and forth on this. NIR said, ChadGBT is officially in its Fiji-Simo phase. If you're wondering why the upgrade doesn't come with benchmarks, have fun.

Rune says, you are confidently wrong about the internal dynamics of this. It could be better summarized as an infra cleanup. And Nier says, The source for my top tweet is Fiji's blog post from today, which discusses the release. and its goals, I don't really know what else to say. I don't know. Is there hunger for benchmarks anymore? I might actually take the other side of this here

and say that I like that they're getting away from benchmarks. I wish they didn't do it 5.1. I don't want any more confusion. What is 5.1 versus 5? Just make it better and don't do a release. And certainly don't tell people because what if people imagine because you're not in love with a specific version, John?

I'm in love with five. I'm in love with five, Rune. Bring back five. I don't like 5.1. I need five specifically. Not 4.0. Not 5.1. I need five.

Five, please. I will say when... Just put the five in the bag, run. Yeah, come on. Bring back five. Bring back five. We need to cyber bully Rune until we bring back five.

Even the most minor tweak to the model is unacceptable. You can still use of five pro. I know. So that's got to count for something. Only five thinking. But I was saying when JupT4, like GPT4, like not for or anything, when that was the best model, they would do updates. They wouldn't like say, oh, this is a new model. And people could definitely tell. Oh, sure, sure. Okay, they release the model it's worse. And then everyone on Twitter would hate it, but then I think

So you think putting a version number actually helps like fight back against that? Because people are like, oh, I get it why it's worse, you, you changed it, like, instead of, like, there being a surprise under the hood. I think it's more, um, it's just, like, easier for people to tell it that it was actually a change when they're noticing something that they've been depending on. Yeah, yeah, yeah, yeah. It's, it's a little different now, like, yeah. I just don't understand why you're, why you're surfacing it in the UI of a, of, like, like, if I open my chat GPT app at the top, now it says chat YouTube 5.1.

Like, this is a consumer iPhone app. Today's Pulse is here, talking about Blue Al Stargate investment. And chat GPT5.1, and I just have to wonder if, like, the 5.1 is, like, unnecessary. Like, if I open up Instagram, it does not tell me what version of the Reels algorithm I'm on. They're going to change it every day.

Like, just change the algorithm all the time. Just make it better. And, yeah, if you make it bad, I'm going to churn. So don't do that. Make it better every day, forever. And just keep shipping. ship every single day. Like, I'm sure that internally, there are version numbers of Google search, right?

Because they push to, like, a main GitHub branch or something, or whatever they use for their mono repo. But, like, there is version tracking for, like, the Reels algorithm. They just don't surface that to the user. So I don't know why they're surfacing 5.1 to users after there was, like, so much pushback over 4.5, all this other stuff. It seems like, I don't know, it seems like a mess. You know what doesn't seem like a mess? Vanta. Automate compliance, managed risk, and

accelerate trust with AI. Vanta helps you get compliant fast and we don't stop there. Our AI on automation powers everything from evidence collection and continuous monitoring to security reviews and vendor risk. There was one more note from Alex Heath's article in Open AI that actually I think is worth sharing. He says, after Meta's last earnings call, sources say, and this is confusing because the name of sources is. I don't want to hear what Alex Heath has to say specifically. Give me some people who are close to the matter. I don't, I don't really, I don't want to know what sources says. I want to know what sources say that sources say, okay. Sources says that sources say CEO Mark Zuckerberg joined an internal employee Q&A and shared a warning

about the AI bubble. First, he shared a breakdown of how different players from startup's big tech names like META should think about timing their bets. He described three camps in the industry optimists who see superintelligence emerging within two to three years. Moderates who expect breakthroughs by the end of the decade. And pessimists who think it'll take well into the 2030s. Each outlook, he said, dictates how aggressively a company invests. Then he expounded on a version of the answer he gave me recently in our last interview. He noted that while unprofitable startups like Open AI and Anthropic risk bankruptcy, if they misjudge the timing of their investment. Meta has the advantage of strong cash flow. He also made the point that while Big

Tech has historically been relatively debt-free, compared to large companies and other sectors, the AI infrastructure race is leading meta and its peers to start using leverage in a more normal way relative to their size. Like he told me in September, Zuckerberg acknowledged to employees that Meta's market cap could suffer if his timing is wrong in the bubble burst, but the message was clear, we'll have the balance sheet to survive and emerge stronger than most on the other side. So anyways. Super Daria was quoting that and said the obvious end game in the next two to three years is that

Microsoft acquires OpenAI, Google acquires Anthropic, and Tesla acquires XAI. Only the large caps survive. That's a nuclear hot take. Nuclear hot take. That is a crazy, crazy. How would that even, I don't know, could Microsoft get the rest of Open AI? I mean, I guess they probably have the... Depends on the price.

It's a $4 trillion company versus a $500 billion. Yeah, I don't know. It doesn't seem like impossible. Let me tell you about graphite.com. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. It's starting to free. I want to run through some more of these posts.

Uchin Jin says, in contrast, OpenAI, employees stayed for two plus a years, sold $6.6 billion of equity. month. Many hit the $20 million cap. Morale and vibes are high, but so is the turnover rate. New Open AI hires are often shocked by how many Slack accounts get deactivated each day. This is a screenshot of an interaction between Jack Morris and Liang Chen Luo at XAI. Jack says, there are dozens or perhaps a couple hundred X, OpenAI, Google DeepMind Researchers, founding companies in the current climate. And this was talking about...

says the simple answer, the liquidity of anthropic options is the worst among those frontier labs. Yeah, this is talking about how a lot of people have been leaving various labs, less people have been leaving anthropic. And so Leon Chen is saying the simple answer. Yeah. And so Andre Carpath, he says, bullseye, it's interesting how large of a fraction of people don't see the dominant first order term that drives behavior of people in companies. You can construct a powerful world model just by understanding one, just by one understanding the system and two, assuming this, there is only this single term, like liquidity, how much cash you have. What would be interesting is if you could, is if companies started offering liquidity

in the form of annuities. So imagine you have an employee who's like a rock star. They're going to sell $20 million of stock, and they're going to basically be post-economic, if you could instead say we're going to be paying you out, like you're selling now, but you're, but we're, when you get a million dollars a year or something, there needs to be some way to like sort of cap. Is there, is there some way to cap the actual amount? I guess 20 million was the cap. But I don't know. There's some way to, to, to deal with this like, you know, if you don't get employee liquidity, like they'll leave for something else.

They'll just go somewhere else that pays them a higher salary. If you give them too much liquidity, they'll leave and start new companies. Very, very tricky to manage the team. But that is the nature of these companies. Chad Byers, that is his real name. He is a Chad in the literal sense and figurative sense. He says, One of my strongest beliefs is that it's going to take 20 plus years to get AI penetrated into the real economy.

I filled out a piece of paper at the doctor's office last week. I filled out a piece of paper at the doctor's office last week, too. It was crazy, and I was wondering, like, when will we see a fast takeoff in DocuSign? I finally realized why DocuSign has so many employees, because you need to go to every doctor's office in person, apparently, for decades, to get them to use online form-filling technology. like general SaaS really does not has not permeated as much of the economy as people think a lot of people still on spreadsheets for all sorts of stuff a lot of people still on paper and pencil there is a you know we joke about being pro ramp anti paper receipts of course um there's a company

that makes paper receipts that's worth 20 billion dollars 20 billion dollars there are fax machine companies the fax machine industry is still over a billion dollars still a billion dollar industry I would think it would, I would think it was actually more. Yeah, maybe that's, maybe that's too small. It's, it's sort of hard to, like, calculate because a lot of these things have been, like, rolled up into other companies. And, you know, like, big facts. Big facts wants you.

Like, I think Canon is one of them. And so, like, I don't even know if Canon breaks out their fax business anymore because they sell so many cameras and other equipment. But, yeah, that's funny. It's interesting. NIR says, IMO, in my opinion, the entire AI field switch. from explore to exploit two years early. Everyone convinced themselves, no, this isn't the case. Look at our exploration. And it's like watching someone go on a 50-foot walk and find a cool tree

when the entire continent is still covered in fog of war. Now that the terrain seems known, it should be harder to convince yourself. I suppose this makes sense, given a lot of people, hint at being good as gone as soon as they have enough money. But no, not me. I've been gone for ages already. that's a very funny post um i suppose uh weren't we talking about this yesterday this idea of like of like where will the next innovation come from where will the next breakthrough come from uh will it come from uh any of the any of the the the like will it come from xa i will it come from deep mind yeah like how much do you need the college campus how much do you need that environment yeah will it come from a university a university the universities seem to have not like

It's very odd that the university system did not produce the transformer paper feels like the perfect thing to come out of a university setting. Yeah, I mean, it's really tough right now. You can stay in a university system and be a student and be taking on debt or you can go work at a lab and make, have a good shot. At least if you did this a few years ago, have a good shot of making $20 million in a few years. And it's hard to give up that kind of opportunity.

Yeah. This Wall Street Journal article is given more context on the AI boom. It says the AI boom is looking more and more fragile. AI stocks have swung downward as doubt rises about sustainability and payoff. Perfect isn't good enough and any sign of weakness is a disaster. This is what's happening. It's like

you double revenue and your stock trades down. It's very, very odd, but everything's been price to perfection. Correweave, who again is the only neocloud in the platinum tier semi-analysis is down 45%. That is remarkable.

It's like they have built a like buy all accounts. fantastic product. Fantastic product. I mean, like, I don't know, maybe Samay and this has got it wrong, but I don't think so. But it feels like they've built something that as infrastructure delivers at the level of the hyperscalers, just like a fantastic product. And yet the market like sort of ran away with that narrative and now it's pulling back a little bit. So recent history suggests that the gloom won't last, but the shake-up serves as a strong reminder that the early years of AI pose a challenge for investors, accustomed to measuring returns on a 12-month time horizon. Generative AI services

require massive data centers and state-of-the-art chips and server racks that don't come together quickly. The companies at the heart of AI are now talking about years, plural, of all major investments still ahead. So everything has kind of sold off a little bit. Oracle is down the most from its three-month high. Invidia's down a little bit. Google is neck and neck. They're doing great. And oddly, Apple didn't even make the chart because they're not, they're so not indexed to AI right now. Last, the latest episode of fragility started last week when shares of some of the sector's leading lights lost ground. After a broad-based recovery on a Monday on news of a possible end of the government shutdown, AI stocks fell again Tuesday, and Vidia's down 4%.

Today lost 7% last week, slipped another 3% on Tuesday, while leaving. it well shy of its $5 trillion market cap. Yeah, looking at the trailing 12 months, Apple is up 21% and Microsoft, which owns a third of Open AI, is a huge AI beneficiary, has invested a ton of it, is only up 18%. Wow. So Apple, which has been going through, this is the secret, just don't invest in AI. Do nothing win. Just don't do it.

Just skip it entirely. No. Just do nothing. Tim Cook's like, wait, why would I? spend $100 billion on KAPX? I can sign up. He's like, I can sign up for chat. So hard.

So hard. She's like, yeah, you know, we have this, we have Safari. We have, we have this web browser. You can go to use AI from there. Just do that on your phone. That would have been the correct thing instead of the getting over their skis a little bit. On the branding side, fortunately not on the financial side.

So they've done very well. There is, of course, real reasons to worry about the sustainability of the boom. Chief among them is that there is far more AI computing infrastructure spending, then there is AI revenue, a gulf widening by the day. Open AI says is planning to spend $1.4 trillion in the next eight years, but is only pulling in around $20 billion of annual revenue today. And it lacks a clear business model to reach the hundreds of billions it needs within the next few years to keep the spending growth going. Open AI is projecting losses will swell to $74 billion in 2008. So skittish has the mood become that CEO Sam Altman

felt the need last week to defend the company on X saying the spending was understandably causing concern. Wow, he says he understands your concerns, Geordie. He pointed to his plans to boost revenue with new consumer devices, robotics efforts, and AI cloud computing service, none of which currently exists. And this is why when we were, the Monday after that interview,

when we were talking about it, saying that wasn't a strong answer because all those things seem like businesses that will lose a lot of money, even if they're successful, until they can reach some huge scale. Look at meta's efforts in hardware. Look at early days of any hyperscaler. Look at any robotics company, right? These are not cash engines.

They're cash incineration engines that could one day... If they want to get more like cash generation, stop incinerating so much cash. Open AI should, you know, I know they're doing a lot, but they should expand into like just, just rolling up HVACs, HVAC businesses, just buy a bunch of HVAC businesses. Adding agents into the workflows. Don't even, agents, we don't even need to do that. Just buy a good, durable business and roll it up. Plumbing, electrical, roofing. Storage units. There's a lot of good money in storage units. If they could get some storage units, just buying a storage facility. and then just like clip in five percent off storage storage storage uh storage uh storage units that look like clouds yeah yeah cloud storage uh lawn mowing businesses they could get into some a bunch of lawn gardening businesses um there's a whole bunch of opportunity landscaping yeah i mean just

buying multifamily homes just buying some multi-family homes single family homes getting the rent payments they put the money in they buy the house and then they get the rent payment and that's how they make the money. And I think that could be, it's a proven business model. Like, we know it works. It works for a lot of people. A lot of people, they start with one single, single family home, they grow it, they keep. Box, Box of Oranges, an open AI property management LLC. So they have the property management company. They actually, they own the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, the, and so they can, they can actually play both sides. Yeah. They could get into drop shipping.

Oh. Think about it. They could set up a TPPN merch store. They could set up merch stores. Counterfeit merch store. For sure. That's what, you know, they keep talking about agentic commerce

in the chat GPT app. Imagine like you go there and you're just like, I need some, I need some t-shirts. And it just instantly sends you some t-shirts. They're getting into drop shipping.

They could also launch a course. You can launch a course. How to build an AI startup. How to build an AI startup? $2,000. Buckle up, get ready to pay two grand. Sam Alman's already been driving around in hypercars, you know?

He has the garage. He has the garage for it. To be a course, bro. To be a course, bro. Actually, he has a much better collection. He really does. I would pay for his course, honestly. I would 100% pay for San Alvin course.

You see a guy in a McClare in a P1, and he's telling you, I will teach you to be rich. I will teach you to build an AI. I mean, how to do deals? How to do deals from some. Sam Altman, I would 100% pay two grand for that course. I'm not kidding at all. Like 100% it's worth it.

That would be better than any college course ever. Be incredible. Well, I'm glad we're having a good time. Let me tell you about Julius, the AI data analyst. Connect your data, ask questions in plain English, and get insights in seconds, no code. Julius has an out-of-home campaign right now in Estab. It's really good. That says, ever since I was young, I wanted to transform data into actionable business insights.

It's the best. It's the best. Fantastic. Great work. Meridu says, if you're down today, you're a certified beta bubble boy. You literally bid up Sandisk, W-T-F. Alternatively, you can call yourself a bad beta, B-I-T-C-H. People are having a lot of fun.

Dario. Oh, good. Sand-Disc is only down 15% today. Sandisk, by the address. Yeah, the White House last night tweeted, we are so back in all caps. What did that mean? What did they mean by that?

In what way were we back? I have no idea. But I have news I need to share with you that I can't share in the stream. But let me tell you about fall, generative media platform for developers, the world's best gender image, video, and audio models all in one place.

fine-tuned models with serverless GPUs and on-demand clusters. Anna in the chat says the open AI McLaren Museum. They open up a museum. The McLaren Museum. Just tickets. Just like adding to our revenue. Like we're going to charge 25 bucks. You can bring your kids. I would visit. I would buy the course. I would go to the museum. Yes. Well, our first guest to the show is in the re-stream waiting room. Let's bring him into the TVPN Ultram. How you do it? And Spencer, Good to see you. What's up, guys? What's up?

I hope you haven't been watching the last five minutes because we're having a little bit too much fun. I want you to know that I have been watching. And guys, we are so back from the White House, that's got to be a reference to the government shutdown. Oh, yeah. Okay. I thought it was so lost in the markets. I forgot about the government. I don't think about the shutdown.

Okay, well, that's fantastic. For those who don't know, you introduce yourself a little bit. Give us a little backstory. Yeah, everybody. I'm a general partner, Co2, help lead our growth fund, focus on late stage transcendent technology companies. So we work with companies across, of course, software, AI, obviously, and then also some stuff in hard tech, SpaceX and or old companies like this. So we're a 25-year-old hedge fund launched a private's business 15 years ago. We're about 70 billion of AUM today across private success. There you go. Where's the mallet? We're looking for the mallet. It's in front of your computer, John.

There we go. This is for Co2. We are thrilled to have you. I've had many fun conversations this year. First one on the air. The reason for today's appearance is none other than Cursor. Oh, yeah. What's new in Cursor world?

Right. The GPT rappers are, you know, they're just. demise was maybe greatly over-exaggerated on X over the past few years. Look, we've gotten a no cursor for a long time. We just think it's a really special company. Michael and his team are incredible. I'm sure maybe you guys saw a breeze piece about the company, the unique culture, how they approach hiring.

I've just never seen a company with such a deep bench of really talented young folks. And then look, on the growth, the growth speaks for itself, right? I mean, we're seeing folks on Twitter today talking about the company being the fastest ever to a billion of revenue, right? It's definitely in that air, which they disclose today being at a billion of revenue. And then if you think about the things that have transpired over the past year with Anthropic coming out with an excellent product in ClaudeCode, open AI responding with Codex over the summer, again, an excellent product. All these things happening at once. and then you sit here and you wake up today and say, wow, cursor's got an incredible business, incredible product velocity, an incredible team,

and now their own model, which they shared yesterday, is their number two most used model on the platform in Composer. So, you know, there's a lot of good companies in San Francisco. It's kind of a nice thing. Like, in early 22, everyone was very worried that all of our 21 investments and everything was just going to, you know, kind of wipe out. There's actually a lot of good companies in San Francisco. It's a great thing.

There's a decent narrative violation. Right, right? There's a lot of good companies. There's a few great companies also, but there are very few of these companies that, you know, the word of the day or the word I try to always come back to is transcendent. And you kind of know it when you see it or you know it when you're around it. And that's what we think, Michael and the team are doing at Cursor. Funny, funny story.

I cursor is I'm incredibly inspired by by their growth and user love and and everything they've accomplished over the last few years but I had a painful moment when they when they when they first kind of exploded onto the scene because I realized that Amman one of the co-founders had been following me since like 2020 or something I was like I I had this I've had this like you know lingering fear over the last few years of like you know you know know, getting followed by somebody not reaching out, not investing, and certainly, certainly would have been smart a few years ago to, to catch it. It's not too late. We think there's still a lot of upside, you know. So we'll see. Fingers crossed. One of the frameworks that I've heard kind of bandied about around what's going on, like a lot of people maybe want this to be more of a winter take all market than it is. And yet when and and yet maybe because of Jevin's paradox or just the nature of like we, it's very hard to understand how much code does humanity actually want to write?

Like it's potentially a ton. And so you're in this like entirely new market that's a blue ocean and it's massive and it's just growing, growing. and so there's opportunity, and I think you're in a unique position where you're in a number of names that do overlap somewhat, and there's a lot of opportunity. I'm wondering if you think that's the right framework, or is there more of like a winner-take-all monopoly thesis with this particular market, or if there's other historical anecdotes that you go to to kind of understand how this might play out? Yeah, I'm not sure what the best. I mean, I'll get to the anecdotes. It's hard to find the best analogs and analogs are always difficult, especially for this. We're investors in Open AI, Anthropic, and Cursor. We're also investors in Glean, Harvey, open evidence, a number of companies across the kind of AI stack. Our view, right, if you just take a step back, right, people talk about the bottoms up tam sizing on developers, to your point, people want to write a lot. People want to write a lot. lot of code. 30 million developers in the world, right? A fraction of a percent of the global population today. And so what's that number look like in 10 years, 20 years? What should that number be?

I mean, that's not really an answerable question, but probably much higher. And then if you take a step back tops down, you've got 5 trillion of global IT spend. And about a third of that is labor today. So, hey, Open AI is putting up historic growth numbers, Anthropics putting up historic growth numbers, right? All of that's well kind of directionally known. We see all these companies growing really, really healthy and doing it in a way that we think is pretty sustainable. Yeah. Did you have a reaction to Sotcha Nadella on Dwar Keshe X, Dylan Patel? There's this interview and he kind of talks about, it feels like he was kind of sending the signal, I'm going to steamroll you if you try and build an Excel agent.

I'm defending the castle that is Excel, but also I'm a platform for a bunch of other things. Yeah, exactly. And I think that I think that I would bet on him being able to defend the castle that is Excel, but I've, but I was going back and forward with Jordy about, it feels a lot harder for Microsoft to put up a fight in AI for lawyers because they just don't have a practice there. And yes, lawyers use Word documents, but it, is a, it, it, it, it just feels like a slightly different, uh, go to market, slightly different product. And so I'm wondering on how you think about the edges of like, where the, where the, where the hyperscalers or the neo hyper scalers, the foundation labs might steamroll versus not, uh, because cursor is an interesting example of a company that feels like almost steamrollable and yet hasn't been. Right. Hasn't been. Right. Again, if you look back at the past, if I told you, hey, Claude Code is going to be.

this amazing product that's this good and you can use it, you'd think, oh my God, right? Curse and Good. I'm short and cursor at the end of you. That's what a lot of people. So, again, I just think it's, you know, we get to sit in a unique spot where we see all these things happening and go, wow, we're just so early in terms of the pie growing, the tide rising with all boats. I think I messed up that somehow. But to get back to your question around the hypers and who wins where, it's hard to see. It's hard to see. say exactly. I think that's kind of the big question right now. If you look back at the beginning of the year, I think there was an open question around, are these API businesses going to work?

Is their long-term margin in the API business, right? Is something like cursor just going to get run over? Is something even like Anthropic in the API layer going to get run over and squeezed? I think now people are kind of going, well, you know, these businesses look really good. They've scaled really nicely, despite all these things to your point happening at once. Maybe now the question is, what's the architecture of that market look like with the hyperscalers over the next 10 years? It's hard to know. What I would say is if you take a step back and you look at the cloud AI revenues for the three hyperscalers,

I mean, they've been inordinate beneficiaries of this trend, right? Open, Anthropic cursor, like Harvey, all these companies are great. The hyperscalers have done really, really well. And the move to cloud and the move from on-prem to cloud that's being pulled forward by all this is really, really compelling for them. So, like, they don't need to worry about winning, in our view, right, like lawyers in beating Harvey. Like, that's almost, that's just further down the economic ladder in my mind for them. But, you know, we'll see. And then the other point, oh, you asked about Excel.

Yeah, Excel's fascinating, right? the ultimate like dominant software product over many decades we've been looking for kind of the cursor for Excel for a while we've tested a few products we've got an internal team here that builds a bunch of things that we guys have built your fair share of models over the years I would hope we we do a lot with with data science and now increasingly with AI we haven't quite found something that works yet but there are a few folks building some interesting companies that we're not invested in them yet, so I'm not going to say what they are. But it's an interesting opportunity. I think that more likely than not, Microsoft still ends up owning a lot of

that. I mean, the close source thing is very important. Like, there is no VS code in that category. People talk about this with cursor for the, for biotech. Like, what's the lab notebook? And I was pushing on, like, I was trying to go, I was trying to go deep with an investor who kind of came at me with a thesis of cursor for bio, and I was saying, okay, well, if you're going to invest in the cursor of bio, what's the VS code of bio? What's the open source? What's the open source standard that you can fork that every bio lab uses? And they're like, oh, well, actually, like the labs use close source stuff and those enterprises do not just want to give up the data. So you're going to be fighting for the walled garden and all this other stuff. So it does feel like the cursor for X model. I mean,

it was really hot at YC, what, two batches ago, everyone was doing cursor for X, and it feels like it was wishful thinking in some markets. Yeah, I think that's exactly right. And what's interesting is for biotech in particular, right? And we've heard Sam make more public comments recently write about their effort with the sciences and how much time they're spending there. I just think that's where the value ends up accruing is something like an open. Anthropic probably throws their hat in the ring at some point.

There's isomorphic labs coming out of Google. There's the Chai Discovery business, which is a compelling company. There's a number of folks who are kind of building these pseudo lab companies that work with biotech. I think that's probably what ends up being more interesting because to your point, there's not a, there's not like a VS code for biotech today. And there are just very few markets where there even is a VS code analog, right? Part of the magic of cursor is they identified an incredible market where the models worked really well early, which was coding, right? This has been the frontier of model capability for a while. You had the ubiquity of the S code and of the terminal and all these things.

And then you just built a really nice product around it and have continued to just push the frontier of what's possible. And now you layer in their own model with Composer. So we're excited about it. But it's hard to find markets with the same anatomy and structure and kind of opportunity, to your point. People are kind of squinting and, like, kind of forcing ideas a little bit. Totally. Totally. Totally. Yeah. Jury. I'm sure you guys just try to back visionary founders that don't come to you for help, unless they really need it, hopefully. But how do you think private companies, how much attention should private companies in AI be?

be paying to the public markets right now because we're seeing so much growth, revenue growth in the private markets, and at the same time, you know, we were just, you know, core weaves down 45% in the past month. There's a lot of jitters in the market right now, and it's hard not to pay attention to some of these signals, even if a company's own revenue growth is skyrocketing. So I'm curious how you think the best companies are going to kind of manage through the next 12 months. Yeah, I mean, look, the fortunate thing for the best companies is almost all of them have a war chest in terms of capital on the balance sheet today. And I think the capital demands

of these businesses is a bit exaggerated relative to what it is would be maybe my personal view relative to like what's on X or what's in the media around these AI companies. In terms of like paying attention to the public markets, right? I think it's, I saw like Subu tweeted I think a few days ago, something around, right? Like the market's been above its 50-day moving average for like over 100 straight days, like something like 130 straight days or something like this. So you know that the market's been good for a while when you see a stat like that. I think founders are aware of that and are pretty aware that it's a good time to raise capital

and fortify a war chest, right, which we've had a really busy Q2 and Q3 and now early Q4. I think that's kind of the way to think about public markets is, hey, when's a good time to raise capital when my cost of equity is lower? But outside of that, I just think tunnel vision is everything. And again, just to bring it back to Kircher, like this is a very focused company, very heads-down company, doesn't make a lot of appearances, right? Like just stays in their lane and focuses. And I think that that's kind of the ultimate value, right?

You don't want to be spread too thin. And look, there's a lot of folks like myself running around San Francisco now looking to give founders money and tell them when the value of their equity is pretty good. Right. So we help give them that signal. Yeah, there's also this interesting. It's hard to measure corrections in the venture ecosystem because they're much less quantitative than just looking at, oh, okay, you could map the. Yeah, correction often looks like, wow, that company hasn't raised in three years. Yeah, yeah, that or, you know, there's some hiccup in LP fundraising or something, but there's many corrections in the public markets that I can think of that were like hiccups in the private markets, but for the most part, it was everyone just kind of being like, oh, there's some crazy stuff going on. Okay, like, let's cancel a couple meetings and, okay, we're back on two months later. Like, the COVID-19, like, sell-off was like a massive correction in the public markets. And for most, for most startup, it was like, yeah, you needed to understand what could your company continue or were you in like hospitality or something that was going to be heavily affected. But for a lot of companies, it was just like, oh, your March raise turned into a June raise over Zoom. And it was fine. Yeah, I mean, I think that's spot on, right? Like there is a level where, right, because we do have a public hedge fund. And so what's interesting is when you have conversations like the one you guys were

having prior to this, right? You know, as a hedge fund, you're always behaving in the market, right? There's always a choice to be making, right? It's very unusual to be in 100% cash or something like this, right? Is a private fund, as a growth fund, we can just choose to not invest for a while, right? We can just wait a bit. And for us, like, the convenient thing is, you know, we only make, I think this year we've maybe added about half a dozen new logos to the portfolio. So for us, we're only making three to five core big investments a year on the growth side right now is kind of our cadence. So it helps us kind of work through whatever that cycle is and just focus on the asset, focus on the entrepreneur, focus on what we view is the 10-year trend and story for why this

company is going to be so durable and so powerful over time. But yeah, like you don't see it, right? I think the other thing that's maybe like less discussed is we've had a bunch of companies and I've seen companies outside our portfolio, too, that were kind of your 2017-era SaaS businesses that have really seen a nice bounce back and a nice acceleration over the past few years with AI. Really, like, reinvention is the wrong term. It's just kind of like some product extension.

Yeah, the CEOs and the management teams and the teams are just re-energized and excited because there's this new capability that you can integrate across your entire platform. Totally. And if you were some, if you were some, you know, flavor of a source of record, your ability to now use that data and create economic value around it is just inordinately better. So, yeah, I mean, look, the market's been up for a while. It's definitely interesting. Yeah. But for us on the private

side, it's a little bit easier because we just get to focus on the companies. Yeah. How do you think people are, do you think people are reading too much into Sarah Fryer's like private phone calls these days are, I mean, it feels like, you know, opening eyes like a billion users, deceleration might be sort of like expected, like, you know, people don't excel. They don't expect meta to accelerate on, on DAUs. Do you have any thoughts on like what's going on there? I've got a big term because I knew this would come up. Yeah. So I thought of this before. This was my one big term here. Okay. Antiety displacement, guys. We've got anxiety displacement. That's what's going on. You know, Like, people talk about anger, displacement, right, all these things.

Yeah. But market's been up for a while. Like, that's a, that's like a fact. Yep. Oh, Chatsy BT is less than three years old. Sure. Is a product, right? Yeah.

It's grown really quickly, right? It's, it's, they've disclosed their almost 10% of the world is using the product weekly. Yeah. Right? Like, that's pretty remarkable, right? But the market's been up a while, we had, like, I still think as a society, people haven't really processed the whole lockdown thing. We had the government shut down for, you know, a month and a half.

There's all this stuff going on, and there's all this anxiety. And I do, I think, like, that's been very displaced because people, you know, like, open ads, a great company. It's a remarkable business. There's just, it's hard to think of an analog for what they've achieved in less than three years is a product. And I think Sarah and Sam, the entire team, do an incredible job. So people are definitely reading too much into anything and everything.

Sometimes I think there's a little bit of a malicious spin on some of the stuff they've put out also just to be very candid about that. But yeah, I mean, it's understandable for there to be a lot of anxiety in society in the market. And it's understandable that it gets displaced onto the company a little bit. But I don't think that's fair. Yeah, it was a little weird. I mean, we were reacting to this idea that there's a private call with investors. Like what type of investor is then leaking like potentially bad news to the press? It seemed like an odd chain of events,

but there's certainly unlimited demand for bearish takes about chat GPT right now because they've been on such a tear. Every day people log on to chat GPT and ask for what's the most bearish thing about chat GPT? Yeah, yeah, yeah, right, right. That's like that's the tweet prompt. Like that's your ex-maximalizing like prompt right there. Totally like that, right?

What chart can I put together or what can I do? but look I like we'll see right um worked with the company for a long time think it's an amazing company and been really impressed by what they've done um i continue to use the product every day a ton i think 5.1 the new model is really a nice upgrade too i enjoy it so you know um yeah i think it's i think they do a great job and i think people definitely over over rotate on it but we're we're excited for 5.67 which would be only a You upgrade cycles away. Rolling my eyes, that one.

Can't do it. I can't do the stupid six, seven memes. It's over. I'm over them. I killed it just now. They're over them. I like the new coinage, though. The anxiety displacement, it's good.

Let's talk about other growth funds because that's just a fun topic for every investor's talked about everyone else. Do you think anybody has, have you seen any other funds kind of, blink yet or or hesitate or or kind of slow down at all, get a little bit worried or because it's just like we're seeing every, every day we get like half a billion dollars of funding announced on on the show, but that has, that's a lag, you know, it has like a, these rounds like really got done, uh, in, in late summer, early fall and they're just kind of getting, getting out there now. Yeah, I mean, I'm sure there are some funds that have slowed down.

I'm sure there are funds that are deploying more than us and less than us and those things, right? I'd say generally, I think the vibe when you're catching up with someone over coffee or lunch is a lot more positive than over Twitter, right? And there's a lot more of like, well, how exposed am I to the AI trend, right? Like there are a few growth funds that feel like, you know, I've disclosed, right? Hey, I'm a little behind this and I'm trying to catch up here and there. So if anything like I've felt more anxiety about that, then, oh my gosh, you know, we just put more money and pick your big premier company,

and, you know, I haven't slept well about it. So that's not necessarily a great signal either, right? That's kind of like an average signal, but I'm sure there are some folks slowing down. I'm not sure who they are per se, because we have a lot of funds that are definitely deploying a lot more than us in terms of absolute dollars and just absolute number of deals. So for us, we just, again, we really just try to focus on our core,

mission, which is, hey, what are going to be companies that matter is public enterprises, you know, 10, 15, 20 years from now? And in some cases, a little bit sooner, right? Yeah, what do you think about the capital-intensive pre-revenue AI companies? We had Faye-Fei Lee from World Labs on. I don't know if they're fully pre-revenue, but it feels like a lot of the world model projects, the generative, 3D worlds, Gaussian splats, what Google D-Minds working on with Jemma, or is it Genie, Jeannie is the model. It feels like something that I just think will be like the next Roblox vaguely, but there's

nothing that you could do to underwrite this against revenue growth. And yet, and yet a lot of these projects are like, to do the next thing, we need $200 million, how would you as a growth investor even square that? Or would you just say, hey, let's just come back when we can ask. actually see some adoption data. Yeah, normally we would fall into the second bucket, like generally, in terms of how we operate. It's different for everyone.

I think all those rounds are ultimately just a representation of the idea size. Totally. Right. Of the opportunity. And then, of course, also of the entrepreneur and the team. Yeah. We did make, you know, one investment very early that maybe fits this mandate, which would be skilled in the robotic space, which has been a great company is executed.

incredibly well. I think Luke Metro's over there now. Oh, yeah. That's right. Yeah, we just know someone who's on the team, but not one of the founders. That left and roll to join. It's skilled, right? S-K-I-L-D.

S-K-I-L-D. Yep. So that was one where we leaned forward a little bit earlier than we would with most things. But, and again, that was on the back of just being very bullish on robotics on a 10-15-year time scale and that team and where they sat in the stack. but generally we tend to wait a little bit to see a company be a bit more flushed out, but it's always case-specific. That's amazing.

Well, thank you so much for coming on the show. Thanks for hanging out. We will talk to you soon. I hope you have a great rest of the day. And congratulations on the cursor round. We'd like to say to you, Spencer. Have a good one. Cheers.

Goodbye. Up next, we have Tyler and Cameron Winklevoss. At first, let me tell you about turbopuffer. Search every byte, serverless vector, and full-text search, built from first principles and object storage fast 10x cheaper and extremely scalable um the uh the winkle of us twins are in the restream waiting room i believe uh if not we have a uh slight delay let's follow up on that back to the timeline back to the timeline dario amade predicts that we will get to 90% on sui bench verified in a year that was one year ago it's been one year uh the best

performing model sonnet four five with parallel compute gets 82% on sui bench Bench verified. Close to 90%, but not quite there. They put him in the truth zone. RIP to Daria. What do you think, Tyler? Barish. I mean, I think he was pretty close. He's, it was 90. Oh, it's pretty close. Good enough these days. That was way more of a bullish take than most people. Yeah, it is very impressive. Totally. Do you think it's saturated? People are saying that, yeah, yeah. Yeah, I think a lot of those kinds of benchmarks are generally saturated. Yeah, yeah, yeah. Yeah, I mean, it is interesting that, like, simultaneously, you hit the 90% on sweet bench did very well there but on the flip side uh you have under carpathie saying like

it's slop and like you can't actually use it for like the frontier software development that he wants to do uh anyway i believe we have the winkle voss twins in the restring reading room let's bring them into the tvp and ultradrome tyler and cameron winkle voss welcome to the show how you guys okay very nice background uh give us the update give us the news i know we're running late uh so let's just jump right into it i assume everyone knows who you are Cool. So we launched Cypherpunk, a Z-Cash DAT yesterday. It trades under SIF, C-Y-P-H. We're really excited about it. The mission of the company is privacy and self-sovereignty, starting by accumulating Z-cash. And in due time, we hope to invest in other technologies that promote privacy and self-sovereignty.

This delay is extremely having some Wi-Fi issues. Sorry. Say more about the structure. This is Leap Therapeutics. You guys have rebranded it. This was an existing public company, but what more can you say on how this came together?

Yeah, so it was an existing biotech company, and we basically took it over and invested via a pipe into it, and then rebranded and changed the ticket. today. Awesome. So I guess Zcash has had a lot of momentum recently. At the same time, a lot of the DATs have, you know, struggled in more recently. What, like, talk through kind of like the next, how are you thinking about, you know, making sure, just kind of navigating this time when the markets are pretty choppy overall? Sure. So I think number one, the long term thesis we really believe in. And I think that when you look at Bitcoin as a store of value or how you store your value, Zcash is really how you move your value. This is very sound and we're obviously very bullish on that. But in addition, we're the largest investor into the debt. So we don't have like a lot of fast capital that's looking for a trade. We're just long.

term hoddlers or in the case of Zcash Zodlers and we just, you know, we plan to hold for a very long time. And I think that's one of the differences is that other Dats have, you know, had faster money and people that are moving in and out of it. And that's why we didn't fill the pipe up. We took, you know, the vast majority of it, I put a 52 million dollar check in. So the vast majority of equity will not be trading out of this, out of this, out of the shares. That makes sense. Well, thank you for the update. Sorry about the Wi-Fi connection. We have some technical problems. We'd love to have you back on the show and talk more about what's going on your world because there's so many interesting projects that you're working on,

but really appreciate you taking the time to give us a quick update on Cypherpunk technologies. And congratulations on the pipe closing, the rebranding, all the progress. So have a great rest of your day. Yeah, thanks for joining, guys. Thanks, guys. Cheers. Let me tell you about Google AI Studio. Create an AI powered app faster than ever. Gemini understands the capabilities you need to, you need and automatically wires them up the right models and APIs.

For you, get started at AI. Who is building AI agents to make the Wi-Fi work? That would be cool. It would be cool if we could deploy an AI agent. I mean, I guess that's like the next generation of the Restream waiting room. Like the Restream waiting room, somebody talks to them in a different waiting room and checks the Wi-Fi, that will be something. Maybe it's a 20-26 project.

Maybe it's a 20-46 project. Who knows? That could be the final box. Hopefully, our next guest is dialed into the Restream waiting room. We have Max Hodak from Science. How are you doing? What's going on? Welcome to the show.

Hi, guys. Good to be here. Good to meet you. Great to have you. I believe we met like years ago at an Oppenheimer screening, potentially. I don't know. Very possible. Very possible.

It's probably happened. Yeah. Anyway, for those who don't know you, please kick us off with a little bit of an introduction on yourself and maybe the company as well. Sure. So, I mean, I've spent most of my like thinking about how to engineer the brain. I mean, my origin story, I think in this field started when I was in the fifth grade and I saw the matrix. And I was like, I have no idea if we're living in a simulation, but we were definitely going to build one. I'd kind of broadly characterize my ambition is to eventually disappear into the simulation never to be found.

And I, as an undergrad, talked my way into a lab that was doing neural recording in primates and spent, really, that was where most of my education happened. And then in 2016, I got, I pulled into co-founding what became Neurlink. And I was there for four and a half years. And in the spring of 2021, started this company science. We're now about 180 people. Our main product is a retinal prosthesis. Like really the first retinal prosthesis that really works for Resort Vision.

It was in, it's actually on the cover of time last. week, which is pretty crazy experience. So you like The Matrix? Do you like the 13th floor? Have you seen that movie? I have not seen the 13th floor. Oh, the 13th floor. It's like one of those movies that got terrible reviews,

but it goes a little, I feel like it goes a little bit farther than the Matrix in terms of simulation theory and simulation hypothesis. It's a lot of fun. But anyway, we can get back to the actual story. So how far are you in building this business? Give us a general update on like, The shape of the business, it seems like you're in the office right now.

How big is the company? What's the progress overall? Yeah. So we have a couple of different elements of our pipeline. So the retinal prosthesis, we think, like, that is first, like, just an end in itself. Like, if you can restore vision to the blind, it is like, it's a quest that humans have been on for thousands of years. That is an unsolved problem. And I think, like, we've made, there's, like, real progress on that.

There's, we got two programs. One is a retinal chip called prima, which is this little, it's a little chip. implanted in the back of the eye under the retina that has all these light sensitive cells, works in conjunction with a laser projection glasses worn by the patient. That finished a major clinical trial last summer that was published just recently in the New England Journal of Medicine. These patients go from being unable to recognize faces. They can walk around because they've got a little bit of residual peripheral vision. The trial was in an age-related macular degeneration, but they definitely can't read. They are really profoundly blind and disabled. And the best patients

in this trial could read could go from reading none of an eye chart. to reading the entire eye chart. I mean, there's videos of these patients like building in crossword puzzles. It's really very cool. And then separately from that, we also have, like, another key program in the company

is a different approach to building brain computer interfaces where instead of placing wires, like not in the retina, but like in cortex, instead of placing wires or cables physically into the brain or genetically modifying the brain

so that, like, there's some things you can do with optogenetics or sonogenetics, Instead, what we do is we grow up these heavily engineered biological cells that we hide from the immune system. And then we just sit this on the surface of the brain. And so we don't place anything into the brain itself, but what these cells do is they grow in and they wire up and they form new biological connections and they can form billions of them. And so I think like the way to understand this or like I think actually fairly direct reference for how to think about it. John's face right now.

So we call it a biohybrid neural interface. Have you seen a James Cameron's avatar? movies. Yes, yes, yes. Do you know the ponytails of the alien pack? Of course, of course. I know exactly where you're going with this. They used to plug into like their tree memory store or like their horses.

So I think the question is like if you wanted to build a ultra high bandwidth neural interface, like how would nature do this? I think what nature would do is it would grow a new cranial nerve that has like a USB port at the end. And that, I mean, that that is super cool research, but that is definitely a research project. And so the way the company's architected is that is going to pay for by the retinal prosthesis. sure, which is a very practical near-term medical device.

We hope to have, we've submitted for marketing approval in Europe for that. We're going through the review process now. The FDA actually is being much slower. It's possible it won't reach American patients for a little bit longer. And that's kind of crazy that Europe is going to get it first, but that's where we are. No, that's rare. You're kind of narrative violation, but exciting. Narrative violation for sure.

But so, yeah, hopefully that'll be on market next summer, making money. And that is big enough to pay for the rest. That makes sense. So why go with a retinal prosthesis instead of cutting a hole in the skull and putting electrodes directly on the brain and trying to deliver the signal that way? There's a lot of BCI firms, obviously you co-founded one, that seem to be approaching the problem that way. is that just like do you have a particular view on that? Is that just farther

out and this is a way to get to market faster or is there something fundamentally like higher bandwidth about your approach? Like what are the different technical tradeoffs? So BCI is not a product. BCI is a field. Okay. And there are many different types of BCIs

for many different types of applications. Like obviously you can't go into the retina to decode like a video game controller out of the brain. simultaneously you can't stimulate like frontal cortex to do like to do some like sensory feedback and so it really depends on the type of thing that you're trying to do and when and so in vision which we I mean we think that a visual prosthesis is a is a brain computer interface we also think that cochlear implants are brain computer interfaces sure sure you don't need to be drilling in

through the skull to get to cortex so if you want to restore vision you kind of have a choice of you've got the retina, the output of the retina is the optic nerve that goes to a deep brain structure called the thalamus, and then the thalamus connects up to cortex. And so within the retina, so let's just take a look at the options that you have here. So in the retina, normally light shines in from the front, it hits the rods and cones, the rods and cones are the light-sensitive cells. There's about 150 million of those. These connect to about 100 million intermediate cells called bipolar cells, and those compressed down to 1.5 million, like optic nerve cells. That connects to about 1.5 million cells in the thalamus,

and that connects up to like 200 to 500 million cells in cortex. And so no one, I mean, people have been trying to stimulate vision into the brain for many decades. And until the clinical trial that we just finished, no one had ever gotten form vision, like structured vision that the brain could intuitively assemble into a whole. Like you could get patterns that if you looked at it carefully, it's like, oh, there's a line here, there's a line here. It's like connected.

That must be an A. Like here's a line. like that's an N. But in the prima trial, I mean, they could read off words at a time. And that had never really happened before. And a big difference is that we're stimulating that first layer of cells, the bipolar cells and the retina. And we know that if you just go one layer deeper from the 100 million bipolar cells to the 1.5 million optic nerve cells, if you stimulate those optic nerve cells, you don't get this. You just get these diffuse flashes of light that you can't really attend to and the brain does not intuitively assemble together because the brain

has already compressed the signal, and you have to then figure out, like, what is that transform? How did the brain compress this? Or how did even just the retina compress this? And the thalamus is the same issues as trying to simulate the optic nerve, except it's under eight centimeters of brain tissue under the skull. And then once you're up in cortex, you're dealing with hundreds of millions of cells that are distributed over large areas that you just can't stimulate selectively. And so, like, people, if you do this, like, you absolutely will get flashes of light. But converting that to, like, form vision that you can, you can, intuitively read is a totally different problem. And so, and then even if that worked,

like even if that worked perfectly, one is like an outpatient surgery going through the soft tissue of the retina. The other is like a four or five hour brain surgery drilling through the skull. I think like one of those is your kind of kind of wind sales. Yeah, wait. So you said outpatient, walk me through comparing the level of intensity of the surgery to something like LASIC. So it's a little bit of a little bit of. more than LASIC, but it's like not a ton more than LASIC. What about getting your wisdom teeth out? I was just coughing.

I mean, you could do this. So in the trial, moaning of them ended up being done under general anesthesia. But to be honest, in these cases, general anesthesia is really like as much like a commitment mechanism for the surgeon and the patient than it is like there's any medical reason to do it. I mean, you just like, you can't change your mind halfway through. Oh, okay. Commitment. And so you, but from a like experience perspective, so you could do this with, you could do this with,

You can make an injection next to the eye. The eye goes dark and numb for a couple hours. And then you can go in through the soft tissue of the eye. You leave the chip. There's a little injector. The surgeon presses a lever. It leaves the chip under the eye. They come out.

They're done. And so it's a really very simple. Yeah. And then, sorry, just to be ultra clear, like the chip is in the eye. Then how am I communicating with the chip? Is it wirelessly? Is there a device that's on the other side of my head? You said glasses maybe are interfacing with that?

Yeah, so if you look at this chip under a microscope, it has all these little hex cells on it. And every one of these hex cells, like the science prima chip, it's essentially a solar panel. And it works in conjunction with, there's glasses that are worn by the patient that has a camera looking out at the world, although you could really get the video feed from anywhere. And then there's a laser that projects the image onto the back of the eye in the infrared. Okay. And because you can't see infrared, you can't, like if you have residuals, peripheral vision or any if you're not totally blind this doesn't interfere with that you can still have that but the infrared laser where it strikes the implant it works like an overhead projector

like if wherever there's white that is projected that is like that's energy and wherever there isn't energy it's dark and wherever the laser is absorbed by the implant it it stimulates the cells directly above that pixel and so this is pretty cool um because the implant is powered by the information that's projected onto it like like as a solar panel this means that that there's no implanted battery, there's no cable, like this tiny little fully wireless two millimeter chip is the whole thing. And also because the eye moves relative to the projector, like the projector is shining in from the front of the eye, and then the eye moves and the image changes, this means that the brain can easily fuse it together with their existing

vision. And so there's like some pretty cool stuff here. Like if you show one of these patients a solid green bar all the way across their visual field, they'll see a contiguous bar, even though the implant only fills like a small area of the total area of blindness. And they'll say it's like it's green and then it turns white because we can only get black and white right now and then it turns green again. But the brain fuses all of this together. And so even though the implant only has 400 electrodes, as the eye moves around, you don't, you don't experience the image that falls on the eye all falls on the retina like a camera.

The thing you experience is the brain activity of the world model in the brain. And so as the eye is moving around, it's updating the world model. and that's the thing that you see. And so even though it's like 400 electrodes, you can't think of it like 400 pixels on a screen. You think of it as just getting the information to the world model and the eyes moving around and the brain's cross-referencing all that.

So it actually does significantly better than you'd think from being 400 electrodes. That's fascinating. How do you think about the analogizing around the artificial intelligence community of what you know of the brain? So a lot of people in computer science or AI might say,

Uh, with, with LLMs, we've built this piece of the brain, with the hard drive, we built the long-term memory, uh, has, has, what, your research, have you mapped any of that onto the current state of artificial intelligence, has it proven, um, uh, insightful to help to, to, for you to understand what's going on in AI? This is funny, because I mean, at the very beginning of, of neuralink and open AI, we were in the same building in San Francisco and we'd have these discussions about like, oh, who's going to learn? Or is AI going to learn from neuroscience or is neuroscience going to learn from AI? Yeah. And I think it has been revealed that like, like I asked, I caught up with one of those guys a while ago. And I was like, oh, like in retrospect, what do you think AI learned from neuroscience? He thought about it for a second. He's like the concept of a neuron.

Yeah, that's it's basically it. It's like the very, it's literally just in the name. Neuroscience is neuron and that's it. Yeah. And then nothing else. Because yeah, like the whole brain structure. Yeah, anyway, continue. And but going the other way, I mean, AI.

has been so useful. I mean, there is a really interesting convergence going on. This is kind of called like neuroaI, where neuroscience is learning a lot from artificial intelligence in ways that I don't think any of us really would have anticipated. Okay, explain that. Have you come across the platonic representation hypothesis? So there's an empirical finding

that different neural networks trained with different architectures, different objectives, and different concrete datasets. But for the same type of thing, like images or language or audio, they produce these, like, similar internal representations. And what I mean by like,

like, sometimes you'll hear people say like, oh, these models are like stochastic parrots or they're just like, there's glorified auto-completes. Like these people are safe to ignore. Like the mathematical objects that you see appear inside these models are super interesting and look a lot like the representations that you see in the brain.

And so that is hinting at like there's some like deeper fact about the universe that we're figuring out here that basically if you're, have a lot of compute power and you kind of run it in these ways, then you see these like these data, these like mathematical objects kind of emerge. And what evolution did and figured out in the brain is like looks a lot like stuff that you kind of see in these transformers and these other AI models. And there's definitely some interesting unification happening there. I mean, it's not, it's still like, it's a little more than speaking totally metaphorically,

but it is still, I'd say, like, instructive rather than literal. But that's getting, like, every month, there's, like, some new cool thing that comes out around this. I will say that, I don't know, and my view is that the transformer is, like, a reasonably good model of, like, what cortex is doing, but there's a lot more of the brain. And so there's other parts that aren't fully kept, that aren't, that we're going to need something else, but it's not like the transformer is wrong. I think it's like probably part of the story. Yeah, that makes a lot of sense. I wonder what you think about just the idea that like it like it takes like millions of years to train a model to like drive a car and it takes, you know, a 16 year old like a couple weekends to do it or or the amount of energy that I will consume in one day of like reasoning, generating my own reasoning tokens is like way less than what it takes to run a data center. there seems to be some sort of like exchange ratio of that's like we're off by a couple orders

of magnitude. Maybe that's an algorithmic question. I don't really know. Do you have any thoughts on that? Yeah. I mean, evolution has done, I mean, it has really, it has been very good at minimizing energy and optimizing some other stuff. But, I mean, that I think is like the advantage of the biological brains. Like every now and then I see pitches from companies that they're saying, well, AI is really energy intensive, so what we should do is we should grow up cultures of biological neurons and train them to do intelligence tasks. Because you can kind of do this. Like if you, you can grow up neurons on electrode arrays and you can condition them to learn things by stimulating them in different ways. Like when I was in college, I grew up a counterstriking game bot. Like, this is actually

not that hard to do. And this is a thing that I think nerd snipes many people in this field at some point. But I don't think that that's like the way to go. I think that there's like just really structural advantages in silicon. Like if you compare and contrast these two approaches, like in the deep learning models, like you can see all the weights. You can introspect them. You can like stop the model. You can change one. You can replay it. Like samples out. You can copy it to disk. You can send it over the network. Whereas with the biological living like these organoid brains, you like you can't see the weights. You can't copy it to disc. It's like the, what it learns is the time-integrated experience it's always had. And like at some point, four or five

months in, it will randomly get infected and die and you'll have to start over. Yeah. And so I think there's just like structural, it's like the thing that the biology does is it's energy efficient. But my response to this is like, generate more power. Yeah, I like the idea. There's no such thing as a low energy wealthy society, generate more power. That's, yeah, I like the idea of the solution to AI is just like have kids or something. And you're like, you've reversed it all the way down to like, if I want artificial intelligence, I can do it biologically. Or just have kids. you and the team getting much leverage out of models today? Is it accelerating your progress? Or is it really just about having, like, deep domain expertise and being more obsessed with

the problem than anyone else and hiring the smartest people in the world? Interestingly, I think companies like this are really limited by infrastructure. And so, like, one of the things that I got from my prior boss was I totally received the gospel of vertical integration. And the, and we're really not, it's not like we're held back by like genius scientific insights for the most part. We're limited by like, oh, like, well, we need to get a new, like a new material and our like microfab deposition tool.

But this requires hooking up some gas plumbing, which requires getting some specialist vendor to come out and like weld it to the machine. Or you're out of animal housing and like building that is like an architectural design process and then permitting and then construction. Like you're really limited by infrastructure more than you are genius scientific insights. And so even if you had this, like, I think, when I think about, like, being in the takeoff era and what is going to the impact of these progress in AI, like, we're still limited by how that can impact the real world in really meaningful ways for these Adams things. But I see there's two places that AI has had a bigger impact. The first is, ironically, like, comprehending regulatory standards and generating regulatory documentation.

I was about to say, if permitting is the bout on that, can you have, like, a permitting agent that just goes and expams the permits until you get exactly. who are you need. Yeah, I mean, they're not quite like they, you end up doing a lot of editing, but you definitely just don't want to spam the permits. This makes the regulator's mad. But the, but I mean, the, the filing in Europe for, to ask for approval for our retinal press thesis, which we submitted last summer, it was, I forgot exactly how many, it was like tens of thousands of pages. It was a 65 gigabyte PDF. Yeah. And that depends on like hundreds and hundreds of standards that were just expected to know all the details of. Yeah. And so being able to talk to these things is super useful, like chat with these data sets is super useful, rather than

having a big team of regulatory experts who are all kind of, it's like, you know, to use this through meetings. And then the other place that we've had big success with AI internally is on our protein engineering program. So there's conventionally many of the problems that we're interested in, you'd have to solve with like better electronics or better physical devices somehow. And we're now at a point where often when we find a problem, we ask, like, can we make a protein to solve this? So a couple months ago, we published a paper on a new type of optogenetic protein, which is these are proteins that can make a neuron light sensitive that is not normally light sensitive, so we could control it optically with light. And these

typically require very bright laser light in order to work. And we're able to use AI models to find one that is so sensitive that it is responsive to, like, not not just daylight, but like indoor office lighting. And so that allows us to substantially reduce the power consumption so that we can, because often the brain implants were often limited by thermals, like how much energy you can consume, depends on how much is limited by how much you can heat the brain. So if you have more sensitive options, then you can have your LEDs be dimmer and have more of them,

then you can think about going from like thousands to hundreds of thousands. But then also that might turn actually into our next generation retinal product. We might, that will have to go through clinical trials. that'll be a process. But it's possible that in five or seven years, you won't even need the chip at all. You'll just get an injection. And then we can just make the bipolar cells

themselves light sensitive. And then that won't even need the glasses potentially. And that really comes out of... The big breakthrough on being able to solve these problems with proteins is an AI-enabled thing. Chat says we should have you ask, how to explain this to preschool. school. Some labs, various groups have talked about the revenue opportunity and just automating

science. And it's usually very general where they're just like, we're going to come up with a bunch of ideas. And then hypothetically, they give the ideas to various people to execute on and they get some type of like royalty on it. How much, how much opportunity do you think there are for a more general foundation model company to just come up with a bunch of ideas? and then actually capture real value from it. It feels like in some ways the pharmaceutical industry maybe doesn't have a shortage of ideas. They have a shortage of infrastructure and funding

in order to test enough ideas to actually get viable solutions. Yeah, I think that a real bottleneck here is just the translation to human subjects research and then to the market is really difficult. We have like the... I think I sometimes joke about is like we're in a golden age

of mouse oncology. Like if you're a mouse with a cancer like we've got some great things for you. I love that. Give it up for all the mice out there. That's great to hear for the mice. That's fantastic.

We owe it to them for all that they've done for science. But like that's the tradeoff. And so if you can and the, and I get it. It's not, you can't just say like oh well the FDA

is the problem. Like the problem is that human subjects research is like life death. It's like it's like no joke. And like I've had the experience of like a patient goes into a new surgery for the first time or they or you're going to inject them with something and you're going to wait. And like that is a very stressful experience. Like you want them like and that's like that's stressful experience for people like me. I'm not even the one getting it. Right. And so the

there's tradeoffs there that I think are very deep and like our like the way that we in our civilization like value human life, which I like I think is right. And And so you have this knob of like how much risk do you think of taking in human subjects research and how fast you get new things. And we know that the toolbox of science is very, very powerful because when you look at what's possible in the animal models, you have these amazing things that are possible. But then getting that into humans is like, and it's not just to say like, oh, we should just deregulate all of this. Like there's, it's more complicated than that. although I do think that there's a little bit of that. But at the same time, I mean, certainly there's an intelligence effect.

Like, I think that there's, it's going to be inevitable that these things, I mean, the fact that you can fold all the proteins, at least in static forms is a big deal. Like, I would not, I would absolutely not bet against improvements in AI leading to improvements in medicine and health care. And I think there actually, just to go one step further, I think then the thing that we're going to have to reckon with is healthcare. So if you thought like 20 years ago, TVs and phones and computers were way, way, way more expensive. And now they're much cheaper, but we spend more on them total. This is like a technological growth industry. Normally if Nvidia sells 20% more GPUs next year and their revenue goes up and their earnings go up and the stock price goes up and like everybody's stoked about this.

But as time goes on and there's more things to spend money on in healthcare that produce better outcomes for longer lives. There's like spending should increase, but because we pay for this, these like kind of insurance schemes, which are kind of pseudo-fixed buckets of money, like if there were real breakthroughs in healthcare that a lot of people will live much longer and have much better outcomes, but they cost money, and you could spend like 10 times as much on health care, like that would be a catastrophe. Like you do not want to spend, like right now our system would not handle spending

10 times as much on health care. But that is kind of directly at odds with it being a technological growth industry. Yeah. What about the BCI industry? I think it's interesting. We've seen, like, this boom in quantum computing and there's public companies do all this stuff. But it feels like BCI... Well, so specifically, I feel like the interesting question with BCI's is, like, I want to understand your timeline.

Yeah, people aren't pouring capital. It feels like there's these therapeutic use cases where somebody's blind and they're willing to take some level of risk in order to see or at least see something. And then there's like the utility timeline and entertainment timeline where I just have, you know, instead of wearing glasses, I just have a screen that's just embedded in my retina and I don't need to wear glasses and it's always on and I can, you know, turn it off. And I feel like that's where, like, it feels like that's where you're going is sort of a general purpose technology on a long enough time horizon, but maybe I'm off. yeah i mean i think i mean it'd certainly be cool if the uh like when your eyes are open you've got

the world of bit a world of atoms and when your eyes are closed you've got the world of bits um the i mean the the near term is all these are medical devices um especially on the cortical side i think these are very serious brain surgeries that um like healthy 40 year olds are not going to be like if your hands work your a keyboard is a really great brain computer interface yeah and there's a lot of research that goes into like the design of the Xbox controller or the design of like the VR inputs because if you can convey the signals

from your brain to the muscles, like you can just capture that. And that works really well. But at the same time, I think many people eventually become patients. Like these bodies are great until they're not. And as they start to fail, we should have better options.

And so I think that DCI, I think that there's a kind of a meme that it is an AI adjacent story, but I actually think it's like a longevity adjacent story. I see like the only organization I really care about is the brain. As far as I'm concerned, kind of the rest of the body exists to keep the brain alive and healthy and move it around and cause it to do things. And I'm going to be fairly disappointed if I'm murdered by my pancreas or my heart. And so I think the, you can get

to this point where you say like, well, instead of, if you've got all these hard problems, like, yeah, we've made progress on cancer and cardiovascular disease and metabolic disease. But again, like when you think about health insurance, like you can't insure something with a 100% loss rate. And we still, that is what we were talking about in medicine. And I think you can get to this point where the brain is the thing that is really special, makes you you. And like, when I look at a person, I see an agent and a robot, and biology makes great robots, but the thing we really care about it as the agent. And if you can kind of deal with the agent directly and the rest you can swapable parts, then instead of needing to cure cancer, we might just be able to avoid

this entirely. And that I kind of see as, as one of the central elements, at least how I think about the promise of BCIs. And so I'd say, like, one of our, one of, I think that I think, could really be possible. It's like by 2035, it won't be widespread. I think it'll take longer than that for sure. But by 20, 2035, can you offer patient number one the choice of like dying of pancreatic cancer being inserted into the matrix? Yeah. What's the strongest steel man you can offer for the anti-transhumanism arguments? Because I mean, I've been steeped in this exact Silicon Valley lore for basically my entire life. I've heard it articulated a bunch of different ways in media, video games, The Matrix.

And yet I've also seen a lot of pushback. There's a lot of pushback against the transhumanism stuff. What's been the strongest argument that you've had trouble debunking, if any? Yeah, I mean, I don't really like the label transhumanism. It just has like all these connotations. I also don't like to work the term. I think it is important that these things, Like, people don't want to be different.

They want to be themselves. I think it's important to realize that things we're talking about should make you kind of just as much you as you've ever been and just like with the best quality of life you've ever had. And I think, like, a concern with AI is that we could, it could be massively, like, it would lead to really undermining our agency. It could lead to a massive loss of agency for humanity in the emergence of something else.

Whereas I think that these BCI technologies, are really about increasing human agency. It's really, it's a very like, yeah, they kind of exist to facilitate you. And it should not, and it should be, it's not other than human. It's like it is a very pro-human technology. Yeah.

I mean, as much as any kind of health care, right? Like we try, like you, we do heart transplants. We're working on our visual hearts. You have dialysis. You have, we treat cancer. We like think that these things are worth trying to improve on. And it's only transhumanists in the way that, like, any health care is. That you don't accept that just, like, the state of the art in the middle ages,

if you were, like, playing in the wrong forest and got to scrape on a branch, you could suddenly die of a bacterial infection two days later. Like, we developed antibiotics. Like, this is only transhumanists in the way that antibiotics are. It's this continuation of that story. That's a great argument. I love it. What, yeah, Jord, do you have anything else?

I was going to ask about the merge. Yeah, I'd be interested to get your personal definition of the merge. Sam Altman wrote in 2016 that it could be a scenario where people become best friends with the chatbot. Maybe the merge is something like AGI where we just keep moving the goalposts. Yeah, do you think it's inevitable or do you think there's like some sort of fork or where do you think the unexplored discussion service era is around the concept of the merge? I mean the way that we interact with AI as I mean there's many different ways of this could go I think like the failure mode of like terminator seems less likely but I definitely agree with Sam that like an underrated failure mode is people just start like delegating their decision making to it because the models just make better decisions like there's I was reading an article that one of the US military like combatant commanders is now like running personal decisions by chat GPT and if you're just like realizing like hey like these things make as good to decisions as I make, then you, they kind of come like premurge. Like, you don't need a device for that necessarily because we are just kind of like, like causing it to happen in the world, like whatever

it wanted. And there's like some dark versions of that. Like you can imagine like an extension scenario is that we just really become, we're like, man, these things have great judgment. They really know what to do. We should like ask it for advice and listen to it and like persuades a bunch of humans into suicide. Like you should, I think you got to keep an eye on those. rates. They won't be zero. And I think it's unreasonable to expect them to be zero because you're talking about hundreds and millions of people. But like do those trends like what do those look like over time? Yes, yes. Keep an eye on the rates. That's the great summation of what's going on. The baseline's not zero, but if it starts climbing up, you've got to watch it.

Exactly. Just like self-driving cars. Like humans are not perfect. Don't hold them to like these unachievable standards. Yes. But like keep an eye on the rates. Keep an eye on the rates. I completely agree. That's a great take. Thank you so much for coming by this show. Congratulations on the progress. Do you have anything else? Yeah, this was incredible. I wish we had more time.

Yeah. But come back on whatever you want. Yeah, I really appreciate this. Thanks for having me on. Good to see you guys. This was super fun. Yeah, we'll talk to you soon. Cheers.

Bye. Bye. Bye. Let me tell you about Profound. Get your brand mentioned in Chuck. GPT. Reach millions of consumers who are using AI to discover new products and brands. Get a demo at Profound.

Our next guest is Andrew Dudum from Hems and Hers. Two companies. No, just one company. Hems and hers. Welcome to the show, Andrew. How are you doing? I'm great, guys. How are doing? Thanks so much for taking the time to jump on the show. For those who might not be familiar, can you just kick us off with a little bit of an introduction

on the state of the business right now? It's a public company. People know telehealth. Yeah, I thought you were going to say for anybody that hasn't heard of Hems, because I'd like to find with. You guys have some great pair, so I feel like maybe we've got some customers on the call. Oh, yes. Yes. Yes. So Hymns and hers, we've been around for about eight years. It's actually our eighth birthday this month.

Congratulations. We were in 2021. And the vision is to help people feel great through the power of better health. Yeah. So we connect you on your phone. You pick up your iPhone, you click an app, and you immediately get connected to one of a thousand or two thousand doctors who are registered in your state and then can immediately engage in everything from cardiovascular disease risk, at home testing for testosterone,

own menopause, weight loss, prescription treatments, all the way down to stigmatize things like sexual health and mental health and depression and anxiety. So, you know, we treat, you know, millions of patients on the platform, 10 to 15,000 patients per day. So while we are in many ways a new and innovative telehealth company, as people call us, we're actually probably one of the largest healthcare systems in the U.S. today, just given the pure volume of patients that we treat. And it's all digital. So no matter what zip code you're in, you have access to world-class, consistent care, standardized care, which I think is one of the most important parts of all this digital health care revolution,

which is no matter where you are, you get great care, as if you're 10 minutes away from Stanford and go see a dermatologist, you know, right outside your door. So this year, we're on track, you know, two and something billion in revenue profitable and growing super fast, which is exciting, a bunch of the categories. Gong hit. Gong hit for you. Let's talk about labs. Yeah, labs. So labs is an important one.

We launched today two packages where you, for a few hundred bucks, can get over 120 biomarkers. This is the most advanced diagnostics, frankly, that are out there in the market. And I spend a ton of time figuring out with concierge doctors and others, what is kind of at the leading edge, where you can get twice a year annual testing. and then have all those biomarkers come into the platform and have thousands of doctors essentially overlook it, coupled with our AI, to be able to prescribe and treat very specific treatment plans for you. So it's not just a data dump of here's 120 biomarkers, good luck, throw it in chat GPT, but it's actually real providers that are then helping you make tactical, personalized prescription next step. So we have about a million square foot of pharmacy compounding in the U.S. So we actually make a lot of these medications ourselves. So if you're a person that comes in, like me, low vitamin D, you know, testosterone's not as optimized as I want to be.

So it's going to be a zinc and ashrigandah or magnesium supplement along with core pharmaceuticals, let's say, for heart disease like a statin. We'll be able to actually put that together for you in a form factor that you love, you know, customize into a beautiful personalized treatment and then deliver it to your door for something like 30 or 40 bucks a month. So it's really this vision of a completely unified system that gets to know you, optimizes you, and then actually can verticalize the making of treatments for you so that we can see you get better and help you kind of get preventative given we're in a country here where almost everybody dies of preventable disease, right? It's like heart disease, heart attacks, diabetes. It's stuff that takes like 10 to 20 years to develop. We should be able to get ahead of this stuff and actually start people, you help people change that course of direction. How do you think the labs

market evolves. There's a ton of players in the space. This is obviously not your core business, although it feeds into the core business. I think there's players that are trying to use labs as like a wedge to then go and compete with you guys. You guys are kind of doing the opposite. But do you think that margins on labs effectively go to zero over time? It's going to go to zero. Yeah, I think anybody who's in the lab's business today whose core business is labs needs a new business. Yeah, you've got Quest and Laporteur and great partners. They've got thousands of locations, you know, $10, $15 billion public companies each of them. There's no way that those margins will be constrained when you have a platform like ours where it's in our, it's in our

best interest and it's in our consumer's best interest to verbalize this infrastructure over time and give it away for free. For you guys or anybody who's a hymns or hers customer, it's to our benefit that we do a full panel and get you that at cost or even as legion, right? Like we can, we'll pay you to take it eventually as you actually verticalize this infrastructure because the data you then get back from it allows us to give you very tangible next steps and manage your care over, you know, five, 10, 15 years, which is really where the long-term relationship and value creation comes from. So, you know, for us, you know, we're excited about these price points.

it's $1.99 for a base package. It's $4.99 for the advanced package. You know, my hope in three years from now, my CFO would be mad. If I said this, but it's like, my hope is it's $30. Right. And it just gets added on to your Hymns and Hers membership. And if you have a treatment with Hems and Hers at all, you get this stuff for free, right? Because it just makes the platform and it makes your precision care that we can deliver so much better, right? Say you're a hair treatment and you're taking, you know, our oral chew for hair loss, which is like finesteride and monoxid. and then we figure out that you're pre-diabetic. Our ability to compound that with a low dose of metformin

or some type of other, you know, microdosing GLP1 or GIPP, like that just transforms the actual clinical outcome for you and it all started with a very simple relationship, which is I'm worried about my hair. I want to start taking advantage of that. I want to know your take on Theranos. I have this hot take that it was never a good idea at all

because you can just take a full vial of blood and it was, even if it worked, it wouldn't be that big of a product because if I go to the doctor and they take this much blood instead of this much blood, it's just not that big of a deal. Do you think if Theranos had worked, that would be a successful product? Would that have reshaped? Was there ever a chance that would have been a great thing? Yeah. The only reason that the idea for Theranos is interesting was if you can do at-home diagnostics

as opposed to in office phlebotomy. Sure. Right. So, you know, that burden of leaving your house, going to a doctor's office, the number one fear in the country is needles, right? So you sitting there and somebody, you know, putting a needle in your arm to take out that tube of blood, whether or not it's a tiny tube or a big tube, it actually doesn't matter. You know, you had to go and park and take time off work. I just see that as a terrible problem in our society that people are afraid of noodles. It didn't matter.

We should not be fearful. I don't like that at all. I feel like we should solve the fear problem before we solve the needle problem. I think if you can do, and this is something we're working on that we've talked about this, I think in the next year or two, you'll have at-home diagnostic devices that you can put on your arm, click a button, you feel nothing. It's kind of like a CGM, right? Sure, sure, sure. And you can actually probably eventually look at the interstitial fluid. So you're not even doing injections deep into the blood, but you're actually just doing kind of like top capillary fluids to be able to interpret

what some of these base biomarkers are. If you can pull that off and it costs $10 to do that and you just click a button, take it off, and mail it back to Hymns, that I think really transforms access because so many more people I think will do that versus the whole, you know,

kid and bootle like going and scheduling and showing up in office. Yeah. Yeah, that makes a lot of sense. How, what's your, like, framework for how the GLP1 market shapes out? Yeah, it's a crazy market. You know, it's like one of the most important categories probably in the next few

years. I think you're going to have more and more treatments on the market very quickly, right? You've got NetSara deal with with Pfizer and Novo that's been taking place, you know, back and forth. You've got Kaila that just raised a huge growth fund. That's got a GLP, GIP that is at par or possibly superior to Tersepetide. You've got Viking coming out probably in 29 or 30. You then have Wagoving, a Mozambic, going generic. sometime in 2030 or, you know, 31, which is going to bring the price down to, you know, it costs, you know, it probably costs $10 to make one of those vials, right? So I think in the next few years, the landscape is going to be incredibly competitive.

I think the prices are going to come down dramatically. This is something we're very excited by when we first started putting these treatments out, the prices were $1,500 a month, but now they're down to about $150. I would guess in three years from now, you can be buying, you know, one of the best, treatments for 50 bucks a month. And at that point, it's going to be just cash pay. Customers are going to be able to use HSA, FSA, not have to deal with the pain in the ass of insurance.

And then the massive market will expand pretty dramatically. Yeah. You said you have like, what, thousands of square feet of compounding, something like that, tens of thousands? Yeah. You know, we've got a million, a million square feet. A million square feet. I feel like that's been controversial in the past.

There's been battles between you and maybe the FDA, maybe the, just a little controversial. Yeah, I mean, I've read about it in the Wall Street Journal. Is there, are you staying the path on compounding? Is that where you want to be in a decade for, is it, is compounding here to stay or is there a world where you wind up partnering with the, the legacy pharma companies? I think it's both, right? I think we will inevitably partner with a lot of these companies, you know, we have the

largest distribution platform for therapeutics in the U.S. for consumers, right? So if you have a next generation treatment, we should be talking because if we want to get your medicine to a lot of people, you know, there's just no faster route to do so. So I think that's a very logical and natural thing to happen. And we've been doing things like this. We recently invested in Grail, which is one of the, I think the most advanced early multi-cancer detections blood tests, simple blood tests, can detect over 100 cancers as early as stage one. I have every single person in my family take this test every year. more things like that are going to come to market, and I think we'll come to the platform. But for compounding in specific, there's really clear guidelines with regard to FDA allowance of compounding.

There's different types of pharmacies. They can do different types of things for very specific reasons, provider personalization, form factor, side effect management, etc. World Public Company, you know, our chief medical officer was the chief medical officer of Walgreens, Demo Tor, who's on our board, who runs the risk committee. was the woman who wrote a lot of the compounding legislation at the FDA for a decade. So I think we played very clearly by the rules. I think this is one of the first times in history that we're able to give this level of personalization to a lot of people, right? Historically, this level of personalization only was possible for people that, you know,

we're spending $50,000 a year for concierge doctors and they could have treatments made for them. And I think it's our ambition to figure out how do you get that for the 1% to everybody. And so I think there's friction without question in that system. But the regulatory framework is very clear. And I think we're just staying the course. And I think over time we'll be able to figure out ways to make the other parties in the ecosystem feel like they're getting well, well compensated as well. Yeah.

Makes sense. How would you describe your management style? The, you know, the companies up massively from, you know, the IPO. I feel like I started tracking hymns during the D.C. era, right? You guys were the poster child of D2C, this meteoric rise, and then obviously, you know, the public markets have been wild. Yeah, I'm curious, like, how you navigate, you know, the market internally, you know, even with the team, right?

It feels like you guys are very built for it. But what's your approach? yeah you know when we i remember waking up one morning and looking at my wife and the stock was two dollars and eighty seven cents like we're trading it i think like point four times next year's revenue or something like that it was crazy so i think the team has a stomach of steel you know whether it's not 70 dollars or two dollars and 87 cents i think you know most of the executive team will retire with this company including myself because i think there's this incredible opportunity to figure out how you redefine what is a healthcare membership that every single

one of us wants to buy. Like, it's got the cutting edge. It has the most, you know, the best diagnostics. It's the most affordable. It's an Amazon Prime version of health care that you can afford, right? It's like the 500 bucks a year. And for 500 bucks a year, why deal with insurance in this country when everybody's insured, but everybody has a high deductible plan with a $2,000 deductible, right so while everyone is insured nobody can actually get the benefits of insurance because they can't actually afford to use all the cash to then get the $1 of insurance so i think our management team is um it's not a very glitz and glamour team right like you're not seeing us out on tv 24 7 it's a really heads down team uh it's a gritty team it's a team that loves to build we have a ton of fun together uh and i think it's a team that genuinely focused is on what can be accomplished in the decade uh and not going to be accomplished in the next quarter or two, which is why I think a lot of the investments we're making have a much longer time horizon.

But, you know, as a founder that runs the company that has the high-bode stock, like we have that privilege to be able to invest over that long period of time. That makes sense. What kind of horror stories have you heard about Chinese peptides? There's sort of a meme going on on acts of people talking about it. Obviously, some of the pricing coming out,

you know, people buying directly there is pretty, wild uh what what are the what are the risks that people should be aware of yeah you've got to make sure you know the the pharmacy suppliers are working with are good quality pharmacy suppliers there's something called a certificate of analysis that um you know high quality FDA oversight facilities in the u.s can deliver third party tested and validation you can actually ask for this certificate we give customers their certificate for for any of our compounded products which actually shows the independent laboratory saying this is exactly what, you know, we say it is. So I think you want to have organizations or pharmacies that have that type of coverage, that type of third-party testing, you know, good manufacturing practices, and ideally have some type of oversight from, you know, state boards or FDA.

I think there's a lot of stuff you can buy online that's, you know, truly not for human use. And they say that as a way to kind of loophole around, but it like truly is not for human use. and, you know, I would encourage people to try to stay away from that kind of stuff. Random question. I'm curious to get your take on it. Something like 1% of U.S. GDP is dialysis. It doesn't necessarily seem like a problem for Hymns to solve, but from everything you know about, you know, working in and around this industry, how do you think it's a solvable problem or is it just that? yeah you know my grandfather was on dialysis for like this five or seven years before he died and it's a it's like the worst thing in the world like watching somebody on that right you have to show up to the facility every week if you don't you literally your body it deteriorates and you

die dialysis is the result of you having totally failed taking action on you being sick for 20 plus years like a very long time similar to cardiovascular it's disease, right? Like, you show up in the ER at 60 and you have a heart attack. You know, that took 20 years to build up. Like, there's just no other way it happens. And so something like what we launched today, I actually think is the first step of the salt. Because you get for a couple hundred bucks, something like a lipoprotein little A test, which tells you your predisposition for advanced cardiovascular disease, which means even if your cholesterol numbers are amazing, they're not amazing enough. Right? You have to have, like, Like the best gold standard cholesterol numbers like you're an 11-year-old kid to avoid a heart attack because you have this predisposition to risk. Same thing with diabetes, diabetes, A1C, fasting insulin, all of these are fasting glucose. These all rise over time. So if we're 30 or 35 and have these numbers, you can just chart what it's going to look like

at 50. And so, you know, micro steps in health, in food, in movement, in, you know, metformin at the right time or GLPs or preventative statins or PSK9 inhibitors, like all of these tools exist. And for the most part, these tools are not extremely expensive. So the real burden in the U.S. healthcare system isn't actually lack of innovation. It's lack of education and access. So how do you get more people tested faster? How do you make it easy and less scary for them to take that first step?

And then keep them motivated along the way because, you know, these treatments don't make you feel amazing the next day, but they'll save your life 20 years from now. And I think that's where a brand like ours spends a shit a lot of time is, you actually have to love hymns and hers, because staying on this medicine is good for your health, and it's hard because you've dropped that habit and then you drop that benefit. It makes a lot of sense. Well, thank you so much for joining. It's great. Great to finally meet. Certainly we're an inspiration during, again, that D.C. era. It was like just a great. crazy, crazy moment in time, and it's awesome to see you guys execute in the public markets.

Yeah, congrats. Thank you, you on. We'll talk you soon. Have a good one. Before we move on, let me tell you about linear. Linear is a purpose-built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product roadmaps.

We have our next guest in the studio, Melissa Tokomak from NETIC. We also, the market is selling off like crazy. People are asking us to cover it, but we will talk to Melissa. at first. How are you doing? Good to see you. Have a seat right there. We do need to cover. I'm glad we have you on the show because the market is in turmoil, but your business is maybe less index to the market. Is that correct? That is correct. Explain, you know, how, explain the business, the news, take us through it. We'll get your take on all sorts of things. Well, I mean, we serve the essential services businesses that are really backbone of our American economy.

nature countercyclical. Let's give it up for the background. The backbone of the American economy. Thank you. So these businesses are, these enterprises are in industries like HVAC, plumbing, electric, solar, consumer health, energy across the boards. So whether the market is going down or up, that somebody, a business or a consumer, always needs these businesses.

Actually, today I'm coming from San Francisco, as you know, all of San Francisco needs a lot of these services today because the weather is a complete disaster. It has been raining. No, it's complete rain. Everything is shut down. Yeah, electricity goes off all the time and I'm sure a lot in the Bay Area will be needing these services all day today. So what we do is provide really these enterprises with an AI revenue engine, right?

So in these times of need, they can actually handle all of the demand with AI agents and serve the communities, but also when the demand is soft, they can predict the need and turn these relationships into multi-time recurring relationships. Okay. So I feel like every time I call a plumber or a roofer or an electrician, people like that, they don't, like the delay and the lag of getting, like there's always like crazy lag in terms of getting back and just being like, yes, I can see, I can come by at this time. And I feel like the lag is because they're super busy.

And if you can help them respond more quickly, they can generate a lot more. Exactly. Actually, many of them are very large businesses. And the lag is because everybody needs it. When you needed, odds are millions of other people need it at the same time. And I'm sure, like this has been talked here in this program too, there's a national shortage and skilled labor in these industries too. So it's actually, Jensen talks about it a lot. and it is the type of labor we need in the country.

And until then, is that what Jensen was talking about? I feel like he said, you know, we don't have enough plumbers, but I felt for some reason he was talking about plumbing and data centers. Yeah,

it's the same, right? So HVAC technicians or plumbers, what the data centers need cooling, right? Yeah, but it's not that many. Or to be able to stand it up. But if you think about it, it takes a lot of years to get actually trained for these jobs.

Sure, sure, sure. Probably more than I went to school for at Stanford or you didn't want to school for. Actually, it's very important. And then afterwards, you have to do it in real life the training as well. So with data centers and consumers and businesses across the world, the need for these businesses a lot. And it's not only about HVAC plumbing, electric, when you say essential services, right? It's also across energy and solar or consumer help, like the Bay Club, right, that we have been serving. So it's really the things that everybody in their daily lives need and has to interact with.

Yeah, walk through the typical stack of HVAC repairment. I imagine somebody could just have, you know, like a Yelp page and a Venmo account. Then some of them have a full website with a booking system and almost like their own little mini ERP, probably not something they built themselves. Maybe they have a Shopify site or something. And then at a certain point, they get a roll-up happens, they get big. They get more industrial, they get more mid-market. And then I imagine that there's some sort of central point of record.

Are you plugging into that? Are you trying to replace that? Are you trying to be the first choice for setting up all the touch points? Yeah. So we primarily work with what you described as mid-market and large enterprise. So a lot of these businesses are owned by private equity, or still owner-operated. But they have built it from zero to hundreds of months. millions of dollars in revenue.

So they will actually, I love that you went through that stack, they might have a more sophisticated tech stack than here, right? So these businesses run on EBITDA, right? So it's extremely important that they think about their efficiency, the customer relationship, and how do they serve their communities. So primarily it will focus on, you know, what type of data they have and where do they keep it, various software solutions, and of course third-party aggregators where they might do advertising. So we will partner with different solutions that they might have to make benefit

of any of the data they can. But primarily what we're doing is bring frontier AI to these industries so that when their demand is very high, instead of losing that, they can handle it all at the same time. And when the demand is soft, they can generate net new demand. As you know, these industries, just like we talked about, San Francisco today, is, very volatile due to seasonality or some other external effects that they can't really control, right? So that's why it's very important how you need to be efficient when the demand is coming, you have to capture it all.

And when it is not, you're thinking about how do I predict the next need? If you can't sell during Black Friday, during Q4, you're cooks. Like, you're probably not profitable at all. Exactly. Exactly. Or even how to predict the next thing. Like one of our customers, there were tornadoes in Missouri a few months back. And before the tornado literally happened, using NETIC, right, reached out the potentially affected areas and talked about generators. How would you feel if your electricity went in this studio? You would not like that because your business would be down, right?

And but then afterwards. I tried to get a generator when the power was out last year. It was a denied by. It doesn't work well. It doesn't work once the crisis starts. Because the electrician is like, yeah, buddy, I got 200 people calling me asking the same thing. I will help you up at the best. I got one. I'm covered now.

But also, you know, when the disaster actually happened, in 90 minutes, maybe they got thousands of calls, right? So how do you help? But it was great for them because they could answer every call with NETIC. And they had already maybe rescheduled the non-essential jobs that they had so that they could help the community in that moment. So that type of proactivity and focusing on the future and like revenue generating interactions for the businesses is very important for these. Let's talk about traction. Yes, sure.

Yes. You raised a new round? I did. Today we announced. Very low dilution. Let's let, uh, let's let her hit the gong. Oh, that's me. Yeah.

As hard as you can. 23 million dollar series B led by founders fund, hit that gong. Wow. With authority. A powerful hit. A powerful hit. A $450 million cap, which is a strong 4-X step-up in valuation. Very low dilution.

Very low dilution. Talk about that. Well, why? Well, I think from the beginning, I really... You hear this? Good omen. It's still going, everybody. The same strength we put into our business, right?

No, I mean, that is actually the answer. From the beginning, what was important to me is that we build a business with strong fundamentals, right? It is not about the hype. It's not about the valuation for me. The most important thing, even in investments, we work with the, best and we're lucky and grateful that same people triple down in a row in NEDIC. And when you have a business with strong fundamentals and strong margins and scaling

efficiently, you don't want to raise more than unique. And if you do that, by the way, that would be a detractor actually in the type of talent that we're hiring today. They do want to work in nimble teams. They do want to run through walls. They want to be here because they want to build the future of essential. I want to run through a wall, right? Yes, you should.

Get one of your customers to build us a wall. We'll run through it. Exactly. I have a question about models. We were talking to Brian Chesky, and he's starting to add features to Airbnb that allow the booking of like a chef. It's a very different model for someone who's traveling. They want a private chef or something like that. But he mentioned that he's having a lot of success with open source models.

obviously he's operating at massive scale, and so every dollar counts. Are you seeing luck with open source models, or are you sticking to the close source models? Yeah. You actually can't stick to one. The way to the, because if you think about it, maybe the difference there is we serve essential services industries.

I'm like a utility to these companies. I can't go down. I can't be wrong. So the way that we build our own ML orchestration, right? The way that you build and think about models and what's really helping with each task that you need to do in that orchestration is very important. So you have to think about what's best fit in terms of address verification in this case versus understanding what does Jordy need when he's calling me, right, or messaging me. So that would be need finding. So the whole point is how do you think of these modules and what do they need to get done and what is the model that can give you the best answer, right?

right? And you have to obviously build a lot on your internal evals to be tracking that continuously and make any changes as you need, right? So today, definitely, like, we do use quite a bit of more closed source models, but depending on your evils, if something is not, you know, like keeping up with what we need and the new functionality we add, we would always test and think about any other models. What about in 10 years? Do you think in 10 years? Before that, are you using voice models at all? Like, do you have, like, phone agents? Yeah, we don't do voice to voice.

We do have voice. Actually, today we support our customers from voice, text, online. Like any type of channel you can take. We are. We're the single inbox, right, for anything that they're really getting. So voice, yes, we support. But voice to voice is actually not there yet, speech to speech. So we do really orchestrate all of that in terms of speech to text, reasoning models,

and then text the speech afterwards to really give that accuracy, reliability, as well as the flow, the feel, right? And hopefully maybe in 10 years you're asking, we will have to think that. Not in 10 years, maybe even a few. Where's voice to voice speech is going? So according to that, we have to continue. What's the sales cycle like? To be frank with you, I think we really sell based on ROI. So we show our customers, right?

and they can talk to our existing customers at any point, anyone interested, private equity firms that we support, large companies that we support. Yeah, our private equity firm's been one of the main channels in here where they're just like, hey, we have a roll up of a bunch of different underlying businesses, let's roll it out. Or you have a number of roll-ups and we want the same software. We have a roll-up of roll-ups.

I mean, that's what private equity firms are these days. Today, yeah, everybody's there. That is correct. It has been one of the good channels, but also it can be direct to large companies itself. I think the reason we love working with private equity because in today's world, they understand the importance of AI

and they're looking for an AI partner. Yeah. Right? It's not really about a thing. We need an AI strategy. What can we buy? Yeah. Actually, you'd be surprised.

Like, I think a lot of tech companies maybe looking for something or a strategy to put on a board deck. A lot of these businesses I work with, I will say they're absolutely incredible and better entrepreneurs than entrepreneurs in Silicon Valley. Sometimes I see.

And they are focused on real value. They've experienced free cash flow. Yeah, it's, I mean, you can't hide behind raises and valuations, right? Like, all you see is that does this help my revenue? Yeah, yeah. Very easy. And for me, too, I can say, hey, I will not give you any random words, AI this, AI this, blah, blah, blah, blah. No, let me show you how is this going to affect your revenue.

Let's talk about that. So when you do it that way, I think the cycles are pretty fast. Yeah. Do you think people are scared? to compete with you? You seem like a pretty formidable opponent. I don't know. I hope not because I...

You enjoy crushing them? Yeah. I do enjoy crushing. How are you segmenting? Not only me, my team too. And this is just for them from here. You all, they're watching right now. You're all beasts.

And there's no one else in this world that I would rather work with other than you. Incredible people coming from scale, HRT, Databricks, MIT, Stanford. But I don't want to even talk about the accolades. Who cares? Most of them have deployed AI applications in the real world, in production, and they run through walls every day to deliver for the real world, even though they could be anywhere.

They could go in any company. Well, for the Series C, we will get a wall built. You can run through it. Exactly. I will be doing that. Yeah, thank you so much for coming on the show. Amazing progress. Congratulations.

Thank you for having me. We'll talk to you soon. We have one more guest. Stay with us. The market is crashing. Everything is in turmoil, but the business continues. The show goes on. The White House needs to announce a hundred-year mortgages.

We have a second round of stimulus checks. Let's move to 100-year mortgages. That will be the solution to all this. No, the only thing that can save us right now is numeral.com, sales tax and autopilot. spend less than five minutes per month on sales tax compliance also finn.a i the number one agent for customer service number one in performance benchmarks number one in competitive bakeoffs number one ranking on g2 and our next guests are here let's bring them in to the tbpn ultradome we have geoffrey katsenberg and thomas welcome to the show folks thank you so much

for taking the time to come down to the tbpn ultredom good to see you again congratulations on the news Let's get some introductions first. Who are you? What organization are you with? Let's kick it off there. I'm Tomas Pueig. I'm the CEO and founder of Olympic. Thank you.

Jeffrey Katzenberg, GP at Wonderco. Third time on the show, second time of the show, something like that. But first time on the show here. Congratulations. And what's the news today? Oh, well, the news is that we actually just raised $145 million. Fantastic. Why don't you go hit that wrong?

Please enjoy this. That must be like enter the dragon. Yes, yes. Yes, yes. Whoa! We haven't seen that before. Different style, different style. Okay.

That was a very aggressive ring. I like it. It's still ringing now, it has a nice sound. So take us through the business. How are you pitching it these days? So what's really interesting about is we do a little bit of a different thing in the AI space. We do causal AI. And really what our executives that we work with and these Fortune 500 in Global 2000s want to know is they want to know

into every chain reaction and lever that moves the metrics that they care about in the business at any time. And so where we started originally was on the marketing and sales side. And so they would be like, hey, I spent $100 million on a stadium name, all these unknowables, these large content pieces, all this brand. We all know it worked at the time. But nobody could actually prove down to the dollar, down to the actual effect of what it would be.

And so when we built the company, originally we were, you want to know how to shine a light inside this black box and actually be able to get the real dollar value so that you can start telling stories because there's been so much of this improvement in, say, the programmatic side of the house, biting these ads. Well, what ended up happening is once we built that, we found out it actually worked really, really well, and we got a lot of incredible clients. And then they started to ask us to do other things, like being like, oh, hey, now can you see how all that affects foot traffic? Now can you see how all that affects my ordering systems? And as we started putting this causal model out further and further, we realized it actually worked on an incredible amount of stuff. And so then our clients started asking us to be like, well, can you do our FP&A for finance? Can you do our supply chain? And so that's really kind of where the business came from.

But the core of it is is that when you have low information or low amounts of stuff, you want to be able to actually affect the metrics you care about. Take us through some of the case studies. Who have you worked with? What's the most concrete example of? You talked about buying a stadium. Have you literally found whether or not crypto.com arena penciled out? Have you looked at these?

You know, I grew up at the Staples. I miss Staples. It's been renamed. But I want to at least know. I want to at least know that it was worth it financially. Is it wasn't worth it financially? Can you tell me that? Yeah, so we did a great...

Let's check Staples stocks and say... Oh, oh. Yes, should Staples have stuck with the sponsorship? See, the problem is it doesn't count for execution risk. Yes, yes, yes. So when we... There's always unknowables, but what can you know? No, so we did a great case study with Delta Airlines

that we actually presented with their CMO at the NVIDIA conference, at the GTC conference, where they were sponsoring the Olympics. Yeah, yeah. And one of the things about these large sponsorships is there's two big aspects people don't talk about. One is every time you've ever worked in the business side of the house, they go, hey, you need enough historical data to be able to do something, right? The second is it takes a lot of time to get a response. Well, when they were doing this, when they were doing the Olympics, they were doing the promotions, one of the most interesting things we found out is we analyzed all this ad work that's coming out. You have only two weeks.

You're holding up tens of millions of dollars on the P&L line while you're doing this, right? These are not cheap options. And when we pulled the study, we actually found out that the best piece of content that functioned for them, the most profitable, was not actually the content that was the ads. The ads did okay, right? The 30 seconds, 60-dicken spots. But what ended up happening is they actually, if you watch the Olympics, they had the Delta Medal presentation ceremony where, like, every time an American athlete would win a medal, they would take it, put it on, you know, their shoulders, and that would be, you know, a really emotional moment. Well, it may seem kind of obvious in hindsight, but when you have the Eiffel Tower in the background, really emotional moments, you sell a lot of tickets to Paris.

But the key is, if you can know that within a few days, you can either double down, right? You can sponsor the next Olympics. You can do all these things. And then you can actually act on it. Now, the problem also with when you do big, huge campaigns like that, is you walk into the lounge for Delta Airlines, and Team EOSA is the Wi-Fi passcode. It's not like one simple campaign, right? you pivoted entire company to a messaging set.

But we were able to tell them within a couple days down to the dollar, a material amount of cash that they were able to pull back, and then they could actually show that to, you know, executives. All this problem in advertising, right, of like, I know my advertising, like, half of my advertising. That's a line. I'm 100% sure that 50% of my brand marketing is working if I only knew which 50%, which has been true in brand marketing forever, going back to the 1980s. Yeah, I'm sure in entertainment, especially,

because there's less like the attribution is really challenging. We did a bunch of marketing and then people went to movie theaters and then some people streamed it and it's hard to actually track it all the way through. But what the brilliance of what Tomas and Olympic have done is, is that using, well, first of all, and he should explain it because he's the brainiac here, the new math that came out of contact tracing from COVID, which actually has impacted many different businesses in terms of research and, you know, causality and attribution.

So we got advertising learnings out of contact tracing. By the way, it's absolutely, there's no, it's a biggie. Very American to like, you know, squash a pandemic and turn it into an ad. But when you think about it is, is that either for COVID testing or for any of these attributions, what they are able to do, which was not possible, even only three or or four years ago, which is to be able to ingest billions of rows of data from all sources and using machine learning and AI to actually digest that and make sense of that and actually then be able to see directional in time.

You know, he'll explain neural networks and how this actually works, which, as I said, is way above my pay grade here. But I can tell you, which is to your question here, which is when we went to the top brand marketers, the first reaction was, no way. You know, this is like, you know, yeah, it's not possible. And this is used like telling us, you know, pot of gold at the end of the rainbow or, you know,

Dumbo flies or I don't know, whatever you want to say. And they went, not possible. And that's when these guys, come in and do these POCs, Disney, Mars, Accenture, Delta, and you know, in the world once as an accident, twice as a coincidence, three times you go, okay, well, this thing actually delivers as fanciful as the notion may be. It's real. Yeah. Can you tell me a little bit of the history of how product placement works in Hollywood? Because that feels like the classic example of difficult to measure, but you've been in that situation.

You know, but it's, when you start to actually think about this, there's a trillion dollars a year globally spent on brand marketing. And brand marketing is everything from crypto on the Staples Center. To an interstitial, to imagine in the Disney parks, all the things that you're, you know, that they're able to offer to their brand partners to putting a logo on a car. What do you, you know, what's the value of having Oracle? Yeah, on the race car. On a race car in this or a patch on a baseball player or a basketball player, you know.

So is it, has it always just been intuitive? Yes. Or has it been more relationship driven? No. No, it literally is intuitive. It is. I mean, he can tell you there's a, there's an old math, MMM, he'll, he can, again, I Tamas can really take you to explain it.

And that literally dates back to the 1980s. And one, it's directional, not specific. And two, the lag between the time it happens and you're able to gather the data on it was months. So it doesn't, the value of it, you know, is really questionable. I guess my question for you is, it's very clear that with the progress in AI, there's the ability to find insights in data,

clearly we see this across everything. My question is like, there's so little ground truth that how can your clients A, B, test your solution against something else? Like, if I go to a coding agent and I ask it to generate some code, I can run the code at the end and I can say, well, yeah, the code worked, right?

Or I can read the report, but if I go to you and I say, how much was this sponsorship worth and you tell me it's $4 million? And I say, okay, like maybe it was for, that could have just been a guess. So how do you justify the results that you spit out since we can't run a controlled trial? So validation is one of the number one things we get asked constantly. When we give out papers, it's really funny. We have one paper where it's like a two-page brochure and then the next 15 pages is how we validate.

Yeah, right? And, you know, one of the things that people don't talk about is it's actually very possible to test these things. So what you can actually do is you can do what we call backfit testing. You can set the machine backwards in time. And then you can test against things that you know. You can withhold information. You can do all sorts of things to actually see whether, you know, you feed the machine up to like last year. You know what all the results are going to be this year.

So when you predict what something's going to be, you can see how close you got. And so I think that when we're testing things, we use a variety of both synthetic data testing methods. Because we're not, you have to keep in mind. We're not a transformer model or an LLM. It's an entirely new methodology. And so when we grab this stuff, we have both synthetic data we can build. So there's systems for the nerds like Teagramite that does causal synthetic data. Or there's real data, like eFMRI data, that we actually know that there's a cause and effect that we can pull from physical world or physical bodies that you can test the algorithms against as well.

And then from the business side of the house, there's lots of ways to do it. Now, one of the things I like to correct on this is it's like we often say the mantra of our company is we're about being directionally correct, not specifically wrong. And so when you need to make decisions, a lot of time when we do these simulations, we're like, here's the top 20% of things you need to absolutely keep doing because they knock it out of the park. Here's the 20% of things that are just literally hurting you. And when you have zero information, like you're in a pitch black room and you have no idea where the exits are,

would you rather take a really, really good educated guess about where the exit is or would you rather wander around the dark? Yeah. And so I think that one of the things about business intelligence is when you have zero information, the value of the information you can get is that much more important. And so we do various ways. I'm still confused about the back testing thing.

Like if I, like how would you go back and assess the value of like Budweiser sponsoring Super Bowl 40 or something? It's like you can't, you can't run the counterfactual. Well, you can simulate it. So counterfactual simulations are assumptions.

So think about like this. A lot of people talk about probabilistic graph, right? Graphics, graphs, whether they're causal, whether there are anything else. Sure. is, to a certain extent, I mean, in a little pedantic, LLMs are almost a probabilistic graph, right?

Undirected until you query it. A neural network. And exactly. And so when we do this type of analysis, the thing about it is that we actually have seen lots of instances of the same exact thing. It's about the specificity. So we just did a calculation literally yesterday that we looked at one trillion connections across six months for a company.

Like, that's the type of scale of analysis we're doing. And we haven't seen when you have it, when you say the counterfacture when you're saying, what does it look like when you have a base state? We've seen the operating version of a company over years. And so we know what the base state looks like when there's no influence from that. The key is you have to have enough data. So in the old world, when we were doing all this analysis, we used to say, you hear about the term overfitting, right?

Everybody's worried that is the model just biased? Well, in the old world, you'd say, I want to reduce the number of features, reduce the dimensionality, to prevent overfitting, right? to prevent over-prediction. Well, in the modern world with like computational statistics nowadays, or AI, as we call it, you want more features. You get more accurate, the more data you have. That's counterintuitive for how people think

about these type of things. So my answer to you is we have to have immense amounts of data, right? And so we ingest a lot of it. And then that gives us enough vision, right, that we can see what a state would be and what would not be. And then we also provide our customers with confidence and everything else.

So there are times where we really, really know, right? And we go, this, we have 100% bet on, and we see enough examples of this. And sometimes we go, you're asking for a call on this. And, yeah, we've got a pretty good guess, but you should still keep it eye. So the interesting thing is, is, you know, he's going fishing to see where, you know, the best fish are. And interestingly, we did one of these POCs for a very, very big branded company. and they were looking for the positive impact of event-driven brand marketing they were doing. When they went out and sucked in all of this data to do this assessment for them,

in addition to finding what were the sort of positive impacts of this, which were modest, what they actually caught in the net was unknown to them, a promotion being done literally in Canada by a little subsidiary that was just like a regional commercial, which somehow another bled over into the state. So it was being run in Canada by a subsidiary there, bled over into the states, and had a tremendous negative adverse impact on brand.

Yeah. As Canadians. I mean, yeah, the classic example is, like, the social media manager intern of your Canadian, you know, offshoot is doing something that goes viral in America and everyone hates it. This one was even funnier. They bought out a national, the national sports, national hockey league final spot.

Okay. And so that's going to be huge in Canada. Yeah. So they, but that broadcasts across the entirety of North America. Okay. So everyone saw it. And so, like, suddenly this little, like, thing there. Drippy, ugly hamburger in the hand in a way.

And it was poorly executed. And I'm sure maybe natively, they thought it was funny. Okay, interesting. And so you're looking at like when sales data is happening relative to when the campaign goes on and then you tease out from there. Yeah, think about like, you know, one of the big inspiration for the company was Renaissance Technologies at New York. So the high frequency trading firms and everything, they can do a pretty good job about knowing when things affect each other or not. But you have to have an immense amount of incredibly high-speed data sets. Talk about Accenture.

You're partnering with them. Are they just an investor? they also go to Market Channel? Well, they actually started as one of these tests we did because they were curious. They were a customer. Yeah. And the interesting thing is the best way when you think about it, John. So they started as a customer, then said, wait a minute.

We have a multi, multi-billion dollar business around marketing go-to-market. It seems like a lot of people go to Accenture for these questions. Gillians. Bane, NBCG, and McKinsey. And so then it went to, hey, can we help take you to market, which they've been fantastic at. I can imagine. And then that led to when Tomat's doing this most recent round, them stepping is the biggest venture investor they've ever done. Wow.

That's amazing. So big companies, Fortune 500 have been hiring Accenture and other consulting firms and research firms to help them understand what is driving results, positive, negative in their business for a long time. What's the timeline to productizing what you're doing to a degree that a much smaller company, let's say a company with like a million dollar a year advertising budget, can actually start to get value out of this. Oh, that's interesting. Oh, so this is actually one of my favorite questions because it has to do with a lot of long-term vision of the company. One of the problems you get when you have mid-size or small-sized firms and they're near and due to my heart is that they literally have never done things.

So when you have a really large corporation, right, they've been in a podcast in whether they want to be to or not. Somebody's mentioned them, right? They have all of these data sets across everything. But when you're a smaller company, right, you say a million dollar your business or something like that, you haven't done everything. So there's no actual priors, there's no data, we don't know how they react. But eventually when we see enough of the universe, right?

Just like you hear about world models, just like you hear about anything else, we'll actually know what the causal universe looks like. what is the actual most likely outcome of when somebody does something? So in the future, in a, say, a couple of years, we'll actually be able to build synthetic data sets that you can send us any query and we can respond to you what the most likely outcome would be. And where this gets really, really important

is I think that, especially when you're doing private businesses, the world of LLMs and everything nowadays, I think they're amazing, but they're quickly converging, right? There's not going to be that much difference for a client between like ChatGPT and Claude. The problem is that if you're using that for business intelligence and business decisions, what are you going to do when your competitor gets the exact same answer and strategy you do? That's a real problem.

And so we believe that we will take the best private data sets in the world, do stuff for just them, get our overall learnings in other places, and then we can actually provide people with strategies that are unique to them, right? Augment the other sets of intelligence. Yeah, there are certain brands that, will get a better return on investment from being in the Super Bowl than others. If you are a no-name brand and you just put up a 30-second spot in the Super Bowl, people are going to be like,

your website would probably crash, right? Like all sorts of things. Yeah, yeah, your web server might not be ready for it, but also people might just be like, I'm not ready to learn about that, as opposed to I actually am in the market for beer right now. And thanks for showing me those Clydesdales. Yeah, but I mean, to kind of like talk to your question, like that is an absolute dream that I have, right,

of being able to level the playing field across that, but also provide- Yeah, because that's one of the advantages of these massive businesses. They can spend $20 million to figure out what's really working and then do a lot more of that, whereas a small firm is, like, kind of doing the vibes-based analysis. I started my career helping companies, like, advertise on YouTube channels and with podcasts, and, you know, they might run a $200,000 campaign, and there's some, like, direct attribution that they get, either from a landing page or a code, but then they're like, wait, our conversion rate is just going up on the site generally. Is that being driven by changes that we made at the site level, changes that we made to the offer?

Is it just overall lift from podcast advertising, or is it some other strategy entirely? And so the more you can bring real business intelligence to small companies, the more they'll be able to actually compete against the big guys. And that makes me happy because everybody should have the level playing field, and whoever has the best strategy and product should do well, right? I think that it's important to note, as we kind of talk about this thing, we spent years, years building the signal processor for this thing. We had to figure out how to bring in all this unstructured and semi-structured data

and be able to basically do data dog for unstructured data first, before we could even try the causal thing. And so we have years of working on that, and that ingestion pipeline, that skill there is what allows us to do what you're talking about. You can't just be like, I'm going to slap a model on top of it, right? You actually have to be able to have a sensor that can actually understand every data feed. have you found a company yet that Jeffrey can't get an intro to or directly connect you to the CEO like this guy

imagine this oh you want to meet this guy yeah I'll give him a call right now you ever want to not take a bet on something that's one of the things I would not take a bet on right Jeffrey will find them hunt you down well congratulations on the progress thank you so much for coming by the Ultradome and yeah good luck with the next with the next phase putting the capital to work. It's going to be an exciting time. And I'm excited to hear more of these case studies as they roll out. Yeah, I really appreciate it both you. Yeah, let us know when you're ready for your first podcast customer. We got. Yeah, yeah, we got a analysis that we want

to do. I mean, we just do the vibe space analysis. We did a billboard. We did a billboard in New York. I think it did really well. We should just do it for fun anyways. Like there's nothing more that I like than like looking at datasets. Yeah, yeah, yeah. We ran a billboard campaign in in Manhattan. We ran two, exactly two billboards. We have no. whether or not it worked. It seemed to work because people shared it a lot on social media. For a million dollars, he could tell you. For you all, we could do some drinks. It'll be fun. Well, thanks so much for coming on the show. Congratulations on all the progress. And we will go back

to our regular scheduled programming. And I will tell you about Adio, customer relationship magic, the AI-native CRM that builds scales and grows your company to the next level. Bucco Capital Bloch is also blackpilling on the timeline. It is a bloodbath in the markets. NVIDIA is down 4%. Michael Burry, Ragequit. Michael Burry, Ragequit. We need to talk about Michael Burry.

I'm sure there's something in the stack. Let's go through some quick updates as we run through the show. Oh, this is cool. This is a white pill. Google the mine. SEMA 2, our most capable AI agent for virtual 3D worlds. Tyler, what's the deal with SEMA 2? Yeah, this is really cool.

Cool. So this is a, it's like a general model that can basically play like any video game. Sure. Which is different because like you've seen a lot of like even early opening I. There was like Dota 2. This is amazing for me because I don't have any time to play any video games anymore since I have kids. And if with this agent, I could just tell it to go play the game and then I could go have fun. And then describe the fun you had and I'll read it and I'll get to fully experience the fun. And email it to me and I'll have Nick read the email and summarize that.

to me in a text message. That would be my experience of the video game. No, seriously, what I actually want this for is I hate how modern video games, it takes 20 minutes to set up. Have you, have you ever experienced this? It's like, going to the tutorial. Remember when I, yeah, when I made you play Halo, when I made you play Halo, it took like 10 minutes for you to actually get into the game and then the actual game took you five minutes to play. And so, uh, I like, there are a lot of times when I hear a new game, I'm like, I only have 20 minutes in my weekend to play this game. I want to jump straight into the action. I don't want any of the opening unskippable cutscenes. I don't want any of the tutorial, learn how to jump, learn how to crouch. I already know how to move. I know what

the stick does. Don't tell me that. This is going to solve that for me, hopefully. Yeah, but this is actually, I think this is like one of the most interesting papers this year. Yes. A big part of it is it's general so you can put in a new game and then it does like self play essentially sure um which is like really important because that's like it's teaching itself yeah this is basically the first like agenetic model that can like see a new completely new environment yeah and then do self play yeah uh where it gets better so you um i wonder how wild i'd love to know how how diverse the inputs are like does it expect a Xbox controller's worth of inputs Does it expect a keyboard's worth of inputs because that's more inputs that it would need to learn?

That's fascinating. And then I wonder what happens if you start marrying it to generative world models in the future as those become games. Like you have this weird like agent on simulated world. You're simulating both of these. That's very interesting. A big part of it is they connected it to Genie 3. They did. Yeah.

No way. It works. So you could you have a generative basically video game. Okay. It's like generating frame by frame and it has a little keyboard and stuff. And then you have the generative agent that learns what the world is and then actually plays it. So you can see this flywheel kind of starting very well. Whether you're going long or short, go to public.com investing for those that take it seriously.

They got multi-asset investing, industry leading yields. And they're trusted by millings. They also acquired Alto IRA, crypto IRA. You're now going to be able to hold digital assets in your retirement accounts all on public. They acquired Alto for $65 million. announced this morning. So great pickup from the public team. Major White Pill, Miramarati's startup thinking machine labs is in early talks. We love early talks. We love early talks. Some of our favorite talks to raise a new round of funding at

a valuation of roughly 50 billion more than 4X their valuation. Everything's cooking. Everything's cooking. Stop blackpilling. In other news, Anthropic disrupted a highly sophisticated AI-led espionage campaign, the attack targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We assess with high confidence that the threat actor was a Chinese state-sponsored group. I guess they were using Claude, I think, is...

Yes. I think they were using Claude code, actually. Hmm. Weird. So they were vibe coding espionage. Yeah, it was pretty funny. I read through some of the blog post, and it was like some of the interactions of, like, the hackers. like this is what they were saying to them all they're like okay good job claude but i think this part is wrong you can see like the actual transcript very bullish phanthropic well go to eightsleep com get a pod five five year warranty 30 anniversary trial free returns free shipping

michael burry appears to be shutting down siam asset management he said dear investors with a heavy heart i will liquidate the funds and return capital but for a small audit slash tax holdback by years end my estimation of value in securities is not not now and has not been for some time in sync with the markets with heart with heartfelt thanks but also with apologies I wish you well in your future investments I do suggest investors contact my associate PM did he really did he really quit right before the market started correcting he's this one of those like you know 90% 90% quit right before 90% of gamblers quit right before apparently this is finally call the top correctly yeah it does seem

odd. I mean, if he, if he, if there is a crash and he was going to be short, but he pulls out before like getting that short thesis to work and realizing the results of that, it really changes his legacy. It changes the meaning of that meme. It changes the, the meaning of the the Michael Berry image, uh, in my opinion. But, uh, we'll see. I mean, he might have, he might be out of step for years. And we might look back on this and say, that it was great that he got out. And it was great that he didn't short the greatest whole market. His memory will live on through meme images from the big short.

And through whatever he gets on his wrist, go to getbezzle.com. Your bezel concierge is available now to source you any watch on the planet. Seriously, any watch. In other news, Paramount Comcast and Netflix are preparing bids for Warner Bros. Discovery. They will have until November 20th to submit non-binding, first round bids. Warner Discovery is holding the auction process and the hopes of having it completed

by the end of the year. Have you seen how expensive streaming is getting? This is on the cover of the business and finance section in the Wall Street Journal. The price has gone up of pretty much everything. Netflix has gone from something like five bucks to 25 at the top end. Everyone's raising the price.

And now they're creating bundles of streaming properties. It's only going to be $2,000 a month. They're all going to have, yeah, $2,000 a month. They all have ads constantly. They all have different logins. All different logins. And you can barely re-bundle them even if you try. I wish that we could get Jeffrey in here to talk about this Warner Bros. deal.

But you're probably too close to the medal on this one to provide to be able to really comment on it. Well, we'll tell you about Wander instead. Find your happy place. Book of Wanderth, Inspiring, Reviews, Hotel Grady, Menys, Dreamy Beds, Top Tier Claiming, and 247 Concier Service. It's a vacation home but better. In more news. Apparently, Vine is being rebooted under the name Devine with funding from Twitter's former CEO, Jack Dorsey. Oh.

The app plans to feature more than 10,000 previously archived vines and does not allow AI-generated content. That's remarkable. There have been so many Vine revival attempts. Elon was talking about bringing it back at one point. I believe the founder of Vine was talking about bringing it back and did a number of different projects. there was a project called V2, right, at some point. It would be fun. I was a huge fan of Vine when it came out.

I really enjoyed it as a new creative medium. It was very, very, very interesting, very, very fun. Let me tell you about adquick.com, out-of-home advertising, say goodbye to the headaches of ad-of-home advertising. Only ad-quick combines technology, out-of-home expertise, and data to enable efficient, seamless ad-buying across the globe.

What else? In other news, strategy has gone below one nav for the first time ever. Whoa. Meaning that sailors, BTC holdings are worth less than their total debt. How is that even possible? That seems very concerning. Anyways, their debt has long maturities, 2027 to 2032. They're not margin loans.

But eventually they'll be forced to sell if they can't make interest payments. They have something like a $700 million worth of interest payments due, next year, and they have, I think, under 50 million of cash on hand at the moment. So they'll either need to raise more or start selling. And just, like, immense pressure from the other products in the market. I feel like if you want access to Bitcoin, which has been Michael Saylor's flagship asset, you were able to initially mine it for free, which was weird, then buy it on Coinbase with a somewhat clunky process.

now it's pretty simple. Now you can buy Bitcoin on a credit card. You can get it in almost every app. You can get it in an ETF. You can get it in your retirement fund. There are a whole bunch of different ways to get exposure. So that particular strategy is not the only one in town. Anything else, Jordy, or should we wind down for the day and say goodbye to everyone. Say, leave us five stars on Apple Podcast. Everybody go DM the White House now on X and just request the 100-year mortgage. We need some type of bullish announcement. Otherwise, tomorrow will likely be even worse. Yes. Well, if you do DMX has changed the way DMs work. Now, there's unified DMs and encrypted chats all in one place. That is the last piece of news of the day.

Well, thank you for tuning in. Leave us five stars on Apple Podcasts and Spotify. And we will see you tomorrow. Can't wait. At night.m. Pacific. Sure. Goodbye. Cheers.