Hims & Hers Stock Drops Over 30%, All-In Launches Ultra Premium Tequila | Crémieux, Clément Delangue, Emmett Shear, Brendan Foody, Sam Schwager, Zach Lloyd, Dara Ladjevardian, Amjad Masad, Angus Muffatti

You're watching TVPN.

Today's Tuesday, June 24, 2025.

Keep it together, John.

We are live from the TVPN Ultra Dome, the temple of technology, the fortress of finance, the capital of capital.

The capital.

Front page of the Wall Street Journal has the update from the Iran conflict with the United States. The Iran fired missiles at a US base in Qatar. Since this, since this published, there is a ceasefire and Donald Trump appears to be very upset with both sides and wants peace and wants the rocket attacks to stop. And so we certainly hope that the conflict will come to a close and we can get back to real estate development and golf. Golf, exactly. Oil drops, stocks rise after attack. So it seems like this.

Yeah, this is what the market is pricing capital bloke was talking about. He says the start of World War 3 is a positive catalyst because it implies there will be an eventual end to World War Three.

It's a new catalyst and that's exactly what happens. So World War 3 is over. Hopefully it stays that way. Anyway, we have some, we have some new drinks in the studio. We have new tonic from none other than Chris Williamson. And he was very gracious to send us a full case. And I will be doing a taste test now. You know the following.

How much caffeine is there?

There's 120 milligrams, I believe.

Okay. We should have Tyler drink 10 today.

Yes, we should. Yeah. As if you've been following the show. You know that I have been a fan of Matayina, Andrew Huberman's Yerba Mate. This is the mango Key lime flavor. It's non carbon, non carbonated energy brew. And here I have the Chris Williamson new tonic productivity drink. It says fuel your focus. I'm going to do a little taste test and let you know, I'm going to try and be as objective as possible. Okay, so this is the, this is the Andrew Huberman yerba mate. That is incredible. It tastes, it tastes like the work of a TBPN guest. Like someone who's been on the show clearly worked on this. Now let's take Chris Williamson. I did invite him on the show. Oh, that tastes like someone who hasn't been on the show yet.

Interesting. Yeah, it's funny how that works.

It is funny how that works. So I mean, maybe Chris should come.

On the show and yeah, we could correct that.

Yeah. And then, and then I think I could maybe give it a more positive review.

But you're onto something, John.

No, but it tastes fantastic. And I will be drinking this throughout the show and I'm a fan. This is actually the very first time that I've ever tasted this. It's very good. Very good. Anyway, looking forward to having you on the show, Chris. Hop on anytime. You're welcome.

So are we newsmaxing today?

We're newsmaxing. We're running through a few top stories. The current things. There's the Anthropic ruling.

Right.

We got to talk about all in Tequila. We touched on it yesterday. But there's a lot more news.

There's a lot more to go.

We're doing it. We're putting on our investigative journalism hat.

Yep.

We're going deep. Also, Hims and Hers is in the news. There's a messy breakup that has jolted Him, Hims and Hers. But the retail investors are bullish. They're continuing to buy. There's a lot of news back and forth. And then we got to talk about.

Hims ended last week at $64 a share. It started yesterday morning at $43 a share. So the Novo Nordisk debacle impacted the share price pretty dramatically. We're gonna have CREMU on the show later for that GLP1 enthusiast to break that down with us. And we'll talk through it as well.

Huge enthusiasts. And then we'll also take you through the story of the rare earth magnets, which is complete fake news. Rare earths are not rare. They're just the. The industrial capacity to bring them out of the ground is rare. And. And the industrial might is rare. And it has mostly moved to China. And so now Ford Motor Company, the Ford of motor companies, has declared that they have a magnet shortage despite the China deal. And so we'll dig into that. Anyway, let's kick it off with David Sacks. We're not talking about tequila yet. We're talking about the positive ruling for AI. This is because Andrew Curran has the story. A federal judge has ruled that Anthropic's use of books to train Claude falls under fair use and is legal under US Copyright law. And I couldn't agree more with this. I had been saying this for a long time that I believe that the Results of. Of LLMs are typically transformative. And very few people are actually using LLMs and AI models as perfect. Yes, exactly.

Itself.

Exactly. You would never go to cloth work.

Is not being reproduced.

Exactly.

Remixed and summarized.

Yeah, you might say, give me the. Tell me about the themes in Harry Potter, but you're not saying, Claude, give me the high.

Which is something that was available to some degree on blogs since the Internet existed, you could look up what are.

Some of the key that website SparkNotes like SparkNotes was. It was a version of that, that was transformative. And so I always thought that this would go this way, but I did think that we needed to sort it out in court. And for some of these categories of media, there probably needed to be deals. And I still think that there's probably room for something like Simon Schuster or Penguin Random House to go and do a deal with Anthropic or go do a deal with OpenAI to say, hey, we'll give you even more access and we'll let you. We'll let you reproduce the whole book if you want in certain cases, as long as you're paying us appropriately. And maybe that's just a few cents for every query, but it'll add up and we'll actually make just as much money as we did before.

So, interesting thing is that the judge did find that Anthropic infringed on copyrights by storing over 7 million pirated books in a central repository. So they had the books, and there's going to be a trial in December that will determine damages. Statutory damages could reach up to $150,000 per book.

That's a lot. Wait, multiply that out. That's billions.

Right.

And so anyways, if the judge or the jury were to award that, I.

Feel like a book cost like 20 bucks. How much does a book cost?

Well, they're saying the damages could be up to 50,000 per work. I doubt that it would end antic, but there's just no way that sounds.

Like the price of a book after David Sandra does a episode about it. Yeah, and there's only six copies on Amazon. They've been spiked up anyway.

Yeah. And this is the first major ruling applying the fair use doctrine to generative AI training, which has been a key legal issue that every lab is following. And yeah, ultimately the big. The court is criticizing Anthropic for pirating sex.

But the big question here is, will training on YouTube data be fair use? Because it is public, like my YouTube videos. I host them on Google servers on a Google service. But you can, you can go and watch my video and summarize it in a blog post that you post on WordPress and you can transform it. And I could say, hey, like, I'd prefer if you didn't do that. But it is true, it is fair use, and I don't have a problem with that. Now the question is, can OpenAI go and train. What's their video Model again, not Dall e Sora Sora V3 on all of YouTube because it's fair use. Yeah, if this is like.

And the book thing is interesting too, because in theory, Anthropic could have gone to many different public library libraries and not had to actually pay for the book and could have accessed them in different ways. But ultimately we'll see how it shakes out. But I mean, the most important thing.

For Anthropic, obviously is to get on ramp. Time is money save. Both easy use, corporate cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp.com anthropic Dario, if you're listening, I know you're listening, go to ramp.com sign up if you haven't already. David Sack summed it up. Positive ruling for AI. There must be fair use. There must be a fair use concept for training. Data or models would be crippled. China is going to train on all the data regardless. So without fair use, the US would lose the AI race. This is an interesting take. I hadn't even thought about that dynamic, but that makes a ton of sense. Yeah, and then you have this weird dynamic where it's like, what if Deep Seek is trained on all the American books and so Deep Seek becomes like hyper capitalist. And then the only way for American models to stay up is like perplexities like deep seq 1776. So they're like fine tuning on deep sea output in order to deliver Western ideals. I love it. Maybe that's the. Maybe that's where there's Windows.

Little Koretsu action.

Yeah, it's great. The writers filed the class action against Theopic last year, arguing the company, which is backed by Amazon Alphabet, use pirated bird versions of their books without permission to compensate to teach Claude to respond to human prompts. I wonder what, what pirated means in this context, because I wonder if it literally means like they went to like a torrent website and like downloaded it illegally. Or if it means like, because you can like, you can technically like go and buy a DVD and then rip it and then have the MP4 file version. It's not. But it's not pirating because you own the. You own the dvd. And so that gives you the right to put that, that file on your computer and it would look like a pirated file because usually you can't just.

Have a 7 million books 20$20 a pop. They didn't spend $140 million on books.

Just they should, they should have support the writers.

And that's one of the risks going into this trial, it's possible that, you.

Know, they should, they should, they should have to pay 20 bucks a book.

They should spend $150,000 a book.

What is the actual damage again? You had the number.

$150,000 per book.

That is way too high.

It could go up to.

I would, I would give them some bulk pricing. Maybe $17 a book, $15 a book, maybe even $10 a book. But they gotta pay something.

The issue is that the individual rights holders are not exactly going to be super happy about getting one purchase.

Hey, 20 bucks is 20 bucks.

20 bucks is 20 bucks.

You see at the back of every book, on the back of the book it says recommended price. Like, I want to buy one. Yes. Who knows what I'm gonna do? Some people are gonna read it, some people are gonna let it sit on the shelf and some people are gonna train a massive AI model.

You could go through this whole lawsuit and come away and buy one double steak, double guac, chipotle burrito bowl and think this was worth it.

Yeah, exactly. I mean, fundamentally Anthropic believes that they are creating God. So, like, you want an illiterate God, you gotta let God read some books. It would be an affront to God to not let God read books.

Might be onto something.

Anyway, if you're designing the next great AI product, go to figma.com, think bigger, build faster. Figma helps design and development teams build great products together. Now let's move over to the All In Tequila. So we talked about it briefly, but we want to go a lot deeper today. So Chamath Palihapitiya has the story. He says, we launched our ultra premium tequila today in Los Angeles at Delilah's. I've never been to Delilah's. Is it good? Have you been? Are you familiar with this place?

I'm not big into that world, John.

Me either.

We mostly don't leave the house after.

9Pm where does Ultra premium sit in the ranking? Because it's below luxury.

Yeah, I was surprised with the pricing is clearly luxury.

That's what I would think.

The positioning. Overall, the bottle looks incredible. The box looks amazing.

The bottle actually does look incredible.

Very clearly it is an order of magnitude more expensive than traditional luxury. Or I would definitely say ultra premium products. Right?

Yeah.

And so, yeah, squarely sitting in that luxury category. But I think he just, I think he just, just ripped it.

I think it begs the question, like, what comes after ultra premium? And it's obviously Giga Premium.

Yeah.

So they wanted to leave room for a $10,000.

$10,000 bottle. That's Giga premium.

So for those that don't know the bottle, the tequila is $1,200.

$1,200.

750 milliliters.

Yes.

And let me read a description.

Pot.

Distilled from 100% Blue Weber agave, grown in the lowlands of Jalisco and aged in white oak X whiskey barrels for five years, this extra Anejo tequila has the perfect balance. A smooth, slightly sweet taste with hints of wood, citrus, dried fruits, butterscotch, vanilla, cacao, toffee and cooked agave. We recommend it to be paired with good friends and lively debate as they do on the show. Fitting the bottle is a handcrafted art piece evoking a stack of poker chips. It is illuminated from the base to appreciate the beauty and complexity of its design. Each is individually numbered for its very limited release of 7,500 bottles. So I would really love a new sell out. They will gross 9 million.

Wouldn't you love a $1,200 energy drink? Yeah, just a beautiful energy drink. Ultra premium, Ultra premium energy drink that comes in a glass bottle. Pour it out. Oh, that'd be so good. They really should do that. I'm sick of the energy drinks in the, oh. $3 a can, $5 a can. Let's get, let's get these numbers up. $500.

Get these numbers up.

Let's do it. Anyway, there was a lot of pushback. Augustus Dirico chimed in to the tune of 5000 likes. He says the elites have totally abandoned us and their responsibility to steward the nation. We're on the brink of war, deaths of despair at an all time high. The economy is fake and the plutocracy is launching ultra premium tequila brands. We need greatness. And so he was very upset. Non equity partner had the flip side, said you can just do multiple things, lead transformative agendas and launch liquor brands. Look at Tesla. Elon Musk launched the Tesla Tequila. It was kind of a fun side project and I think that's what Emily Sundberg was getting at before when she was talking about how celebrity brands, people kind of know the thing. Like, do we really think Dave Friedberg is going to take his foot off the gas with his company that he's actively running to work on this tequila brand. Like no, he's, he's, he, you know, signed off on it, went to the party, it's going to live on a website. We, I actually found the design firm that did the design. Like this is not going to suck. These folks away from. From the other things. At the same time, you know, Augustus does have some point that, like, maybe it's a little unserious for them to do it. I don't know.

But I don't know why it's unserious. They have their friends. They have a podcast. They enjoy drinking together.

Yeah.

Playing poker. They introduced a poker themed bottle of tequila.

Yeah.

I also kind of enjoy with them.

Yeah.

I don't think it's. I don't think it's unserious.

Yeah.

I think I have more questions around how seriously are they taking it as a business?

Sure, sure. Yeah, we need to get into that.

CEO, Are they trying to, you know, scale this into.

Yeah. Is it a drop? Because it might. It might not even need a. It might not even have its own C Corp or like, its own llc. It might just be like merch, essentially, and it's cool as merch. And then there is this question where, you know, I feel like there is a drumbeat in the news and in the culture around, like, things have never been worse. Like, it's so bad right now. We're in a uniquely bad situation, yet.

At the same time, I don't. Peace in the Middle east today.

Yes. Yes. Peace in the Middle East. Finally. Finally, for the first time in 60.

Years, only a few days after the launch of this. And there could very well be some correlation. There's definitely a correlation.

Definitely a correlation.

Whether or not there's causation, we don't know yet.

He'd get a couple of these vodka.

But Trump had his own vodka back, so he introduced this in 2005, the Trump Vodka. Which is funny because I don't even. He doesn't drink alcohol, right?

Yeah, he doesn't.

He's never been big into that whole world.

Wow.

And so I think this was just.

Yeah. How are you gonna criticize the. I mean, the all in guys seem to enjoy the tequila, at least.

Trump Vodka was an American brand of vodka produced at first in the Netherlands, then later in Germany by Drinks America. Drinks America.

It was made in Germany by a company named Drinkameric, produced in the Netherlands.

And then Germany Drinks Americas. The company is called Drinks Americas two S's.

It was never produced in Americas.

The brand was launched in the United States in 2005, but ceased production under the Trump name in 2011 when it failed to meet the required threshold for distribution. Honestly, might be the time to bring it back.

I don't know if they're gonna do distribution. It seemed like it was all over the place.

It's interesting. However, it is still sold. In 2016 this was the last time it was updated. Especially around the Jewish holiday of Passover. Huh. Interesting. Trump at the time that the brand slogan was success distilled with Trump predicting it would outsell Greg use father. He also said that when mixed with tonic which he referred to as a Trump and tonic tnt it would become the most drunk.

Tea is good.

It would become the most drunk cocktail in the United States. I love I. I mean the consistency of his confidence across eras is unavoidable. In 2007, Drinks America signed a deal to export 50,000 cases of Trump vodka annually to Russia.

To Russia. Oh no.

But in 2011 it was discontinued due to sales failing to meet the company threshold requirements. Several reasons were attributed to this. One was because Trump himself is a non drinker and never drank Trump vodka never even tasted.

Yeah.

Drinks America's also had problems producing it because the glass used in the bottle and the gold leaf labels were expensive and the company could not afford to produce them in large numbers.

Yeah.

In 2015 in his campaign for president, Trump did not include Trump vodka amongst assets submitted to the Federal election Committee.

Because it's basically a zero. Interesting. Well, my advice for the besties. You're launching a tequila brand. You're going to have to pay sales tax. You got to get a numeral hq.com sales tax on autopilot. Spend less than 5 minutes per month on sales tax compliance. I liked Mike Solan take. He said I'm happy for the all in guys and tired of the tedious hate. They built a popular show which is hard. True. Now they're launching a tequila brand. Okay, great. Hope it does well. Jealousy on this app is unreal. Their success can't hurt you. Focus on yourself. I like this. Eric Tornberg chimes in. How you feel about their tequila brand is how you feel about yourself. That's been a line he's been repeating. It's. It is. It is interesting. It seems like you know their, their whole show started as like they're locked down during COVID They all hop on on zoom and they have some fun talking to each other and they love poker and this feels on brand. This feels like a good line extension for the brand. I guess there's a question of like should they just run ads for a big tequila brand but we should get.

Into this is way more fun for them.

Yeah, it's fun to have their own thing. Right.

There's nothing more fun than creating something especially if you've been in Tech creating something that's physical, that you can hold, that you can put on a table. That's beautiful.

Yeah.

That you can share. That's social.

So I want to get into, you know, expected value, expected market size, expected profits. Like how successful do we think this will be? Because there's a world where this becomes a major brand. Like, I mean prime is a big brand. Feastables is a big brand. Like these guys. These guys could turn this into a massive company. At the same time, it could be more of a drop and they could sell a couple hundred bottles, couple thousand bottles, make a few million, move on to the next thing. I found the design firm that actually worked on this, the Besties All In Tequila. It's from a, from a design team called hello Stranger. They say, we'll fix your brand. We'll give you a new brand, a brand that wins all the awards and sells at a premium. We'll give you a strategy, a unique angle based on insight and research. We'll give you the sexiest packaging that people can't put down and we'll give you all the collateral you need to make your brand flourish. On this site you won't find headshots of designers looking important next to yucca plants. Because it's not about us. It's about the billions in sales in one of the toughest sectors in the whole of retail. We're stranger and stranger. We've been doing it for over 30 years and we are the best. As one of our clients said, don't leave anything to chance. They started in 1994.

I have here, I think day job is the best. They did the design for David protein bars.

True.

It's gonna do billions in his first few years. It's hard to argue with, with those kind of results.

But so they announced the besties to All In Tequila, which is an interesting name choice as well. It's not the All In Tequila. It's not Besties Tequila. It's the Besties All In Tequila. But they say the besties at the famous all in podcast have just released a twelve hundred dollar Tequila which unfortunately for all of us is already sold out. The guys are big poker players, hence the All In. And the iconic bottle single mindedly owns the idea. And so the love language here, you read some of this handcrafted art piece evoking a stack of poker chips. It's illuminated from the base to appreciate the beauty. Oh, so there's a light inside. Let's go. That's cool.

There's a light inside.

I mean that's what it sounds like. It says it's illuminated from the base. So I think when you're spending $1,200, I think it glows. Yeah.

Incredible.

It's tech product.

Yep.

It's Internet connected. It's got.

It's IoT device.

It's an IoT device potentially.

For boozing.

For boozing. Imagine you could link this. It could measure how much is in there. Have an app orders you more automatically subscription. Now we're talking this.

It goes from a nine, you know, nine million dollars. You know, first run into a nine million dollar MRR business.

Yes.

Getting up into that nine figure rapid range pretty quickly.

It is, it is fascinating. So each individually numbered for the. Each bottle is an individually numbered. They're releasing 7,500 bottles. So if you do the math, 7,000 times 9 million. 9 million. That's, that's, that's how much they're trying to make. Each bottle arrives in a numbered collector's box. Bringing the besties. Signatures. They're. They're signing them or it's printed on there. I don't know.

I think it's got to be printed on there. David Sacks does not have time to hand signs.

How long would that take? You do one every couple seconds. It's, you know, days worth.

Signatures would get so sloppy by the end.

Mr. Beast has done that. I've seen streams where he's been like signing every single T shirt. That's cool. It's really messy. But they say wet your beak, go all in. And it is remarkable how much their brand has dominated like the catchphrases. Like we've been, we've been pretty deliberate about trying to build the TVPN brand around Fortress of Finance, Leverup. All these different catchphrases. They've done a really good job because as soon as I hear Wet yout Beak, I think, I think I'll in.

I think your beak.

Anyway, there's been some timeline and turmoil because Kas Azar Tequila has a similar bottle design.

Very similar.

And so we can pull that up. The founder story over at CAS Azar lies in a husband and wife founder story. A tale of resilience, determination and the courage to go quote all.

So if you search, if you search all in Tequila right now, you'll get a. A post from April 11, 2025 that says this is on the Spirits Business.com that the tequila stack owned brand Casa Zar transcends mere novelty by merging cultural roots with the most important aspect, flavor and character. Max Ramirez and Viviana Cerealta Ramirez. Two ex Diageo executives and industry veterans launched CASA czar in November 2024. The husband and wife team were driven by passion, determination and courage to go, quote, unquote, all in in pursuit of a dream to create a brand that would stand out in a crowded market, not only visually, but also gastronomically. Less than a year since its launch, Casazar has quickly gained momentum and garnered industry accolades. Most recently the Tequila and Mezcal Masters 2025. Casa's Our Tequila won two gold and a master medal. The brands Hoven and Reposado bag gold and their ultra premium. Well, ultra premium might just be like a category. We're kind of exposing how little we drink anything other than champagne. 100 agave tequila categories earning a master medal. Casa, Casa Czar Tequila and Yeho and press judges.

Here's the bottle with its zoom in.

On expressive nose with plenty of earthy roasted agave and peppery spice. Creamy and syrupy on the palate with drying oak and peppery spice balanced with sweet golden syrup and charred agave. Judge Matt Chambers, director and co founder of Whiskey for Everyone, described Casazar and Yeho as so delicious. So anyways, I saw this and my immediate thought was that maybe all in had white labeled the bottle, but that doesn't seem to be the case. And digging in a little bit more, some of the issues here, this company's been in business for a while now. It's ex Diageo execs. They have patents, from what I could.

Tell around, it's more of like a trade dress thing. The patent would be like how you manufacture it.

Apparently they have design patents, design patents around the bottle design, which is very distinct.

Interesting.

Very distinct.

Yeah. So there could be some fallout, maybe a negotiation. Maybe someone's gonna have to go all in to see put it all on the line to see who can own the poker chip stack design for tequila bottles.

Yeah, and this could get spicy. Right. According to Casa Czar, the tequila is designed for those who live life, who live like a high stakes poker game. Fearless, driven, and willing to take risks.

These are a lot of the same things. So there could be some confusion.

The besties are taking a risk.

Yes. And I've run into founders before who have inadvertently used names that they thought were kind of generic. And then they wound up, oh, there was a smaller player in a sub market that actually had national ambitions and was gonna sue and pushed to say, hey, you actually have to back off my trademark because I know that you're selling this type of sauce is Big Spoon. There was Big Spoon Roasters and Big Spoon Sauce Makers, and they both had sauces that were spicy and they had different kind of logos but similar names. And one was in the southwest and the other one was in California or Southeast and. But eventually they both wanted to go national and so they collided and they had to kind of decide how to back off.

Well, we saw this yesterday with IO iyo.

Oh, yeah, same thing.

OpenAI where OpenAI had to scrub all mention of i0 or, you know, I o from their website because of a trademark issue. This is seem seemingly a bit different because it's a design sort of patent or trademark. I don't have exact specifics, but I expect this to get spicy and you're going to have people.

Casazar is known for being sweet and spicy.

That's right. That's right.

I do wonder where Ultra Premium comes in. I feel like it's anything over like a hundred bucks or something. Why would you put a $200 bottle and a $1,200 bottle in the same category? Those feel like it's. It's almost. It's half an order magnitude. It's like 500 or 5x difference in price. It feels like they're not necessarily playing in the same category, but the design elements and the, the fact that it is a tequila and they're clearly going after awards and costs are both are.

Premium, both are heavily branded around poker. Yep, one of them launched in 2024.

Yep.

One of them is launching today.

Oh, wait. Costasar is only 2024.

Yeah.

Oh, wow. It's like pretty new.

It's new.

Okay.

They filed their trademarks in 2023 though, so it's been a little bit. So they've been in market for a while. And Casazar's execs. Ex Diageo. Right. They're probably got some sharp elbows. I imagine they're going to want to pursue this to some degree just given people don't realize how I think we live in this tech bubble. I don't think people realize how big all in is. It's like way bigger than just tech now.

Huge. Huge.

Huge. And so this, you know, I think we'll see how this shakes out.

But so there's, there's. There's another thing that's kind of confusing is that I was wondering if they're playing in different markets because CASA czar is 40% ABV. That's 40% alcohol by volume, 80 proof, which is pretty standard for liquor on the all in tequila. The Besties all in tequila website, it says it's 750 milliliters, same size, 40% ABV $1,200, which would be the exact same stats, but when you zoom in on the box, I don't know if you can see this. It says it's 48% alcohol by volume. Can you see this, Jordan? 48% here.

That might have just been an early render.

Yeah, maybe. I wonder where they're landing, because I feel like 48% is a much stronger choice for tequila. It would be noticeable that you would have a stronger alcohol content. And it's also much harder to mask the flavor if you are dealing with an extra 8% of alcohol because it's just gonna be more alcoholic. It's gonna. It's like the powerful stuff. Yeah. I mean, one of the secrets to those, like, spirits that popular in college campuses is that they take the alcohol content down to something like 30% or 35% flavor.

I don't know where this picture is from because on the website it says 40%.

I don't know either. I don't know where I got that picture.

We will have to get a bottle ourselves.

We will. And we'll taste it. We'll immediately tell you. Yep, 42%.

We wanted to have Tyler taste it, but fortunately of age.

Yeah.

So we'll save a little bit for you, Tyler, for your birthday. Yeah, can't wait.

Well, if the besties are planning to take the besties all in tequila to the moon, they're gonna need to get on Vanta. They're gonna need to automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes the work out of your security and compliance process and replaces it with continuous automation. Whether you're pursuing your first framework or managing a complex program. You know, if you wind up turning this into the big IoT SaaS product that we've imagined it being, you're gonna be managing customer data. You're gonna have their health records. Potentially, you're gonna be pulling in all sorts of stuff to optimize their liqu and you're gonna need to be secure. So you're gonna need to get on Vanta for sure. How big do you think this is? Where do you think this actually goes? Like, I think that's the more serious question. Is it totally 9 million? I think that they're gonna sell that. I think they're gonna sell all 7,000. No problem.

The haters will be in disbelief.

Yeah. There are so many fans. We know we're gonna Buy a bottle. But we know folks who are friends and friends of friends who are gonna buy bottles. There's gonna be people that buy bottles because it's fun and they want to support their, the show that they like. There's going to be folks that gift it. There's going to be people that buy it because they're, they're, you know, they want to just like support the, the, the, the, the, the thing that hasn't been charging them for five years. Like, there's a little bit of people.

Just want to support the dictator Jamal.

But honestly, it's like, it's like there is another world where if all in was $20 a month, you would have paid $1,000 over the last four years. And they didn't charge you $20 a month. They didn't even run ads free. And so what's your way to get them to say, hey, yeah, you've delivered me $1,000 worth of value and I have it because I'm successful. And, you know, this is a great way. And you get something that, you know, who knows what the margin is on this. Is it worth $1,200? Maybe. I don't know. It's hard to get, but it's just like, it's a fun thing to buy.

Imagine you're going to a friend's house for dinner. What's funnier than bringing a bottle of the besties all in tequila? Hey, I just picked this up on the way over. It looked nice.

It's like, it's almost. It' like high end tech gag, gym gag gift. But it's also probably really good because it's very expensive. So then you taste it, you're like, oh, this is actually really nice. Which bottle design do you like more? Because Casa Czar has this ceramic bottle that they hand paint. You said you liked that. It had the stack of chips all the way to the top, stacked top. I don't like that.

John doesn't like it.

Break it down.

I think the ceramic look is nice. They look more like regular poker chips.

That is true.

It's cool.

I think it's almost too close to poker chips. Like, I would be confused. I'd be like, is that just a pack of stack of poker chips? It's like hiding. It's. It's hiding. Can we zoom in on the stack of poker chips there? Bring that over.

Oh, no.

Skill issue.

First zoom. First zoom, bud. First time zooming.

Yeah.

You know, anyways, it.

Steve Johnson is a beautiful multi touch years ago.

The causes are beautiful. Bottle I like that it's fully stacked. Ultimately, I think it just doesn't read.

As a bottle of liquor, whereas the Besties all in Tequila does to me read as it. And then also the glass, the glow.

The glow, the glow.

It is in a different tier. Ceramic is premium. I would only give the ultra premium label now to the Besties all in Tequila. I would call. I would call it. They've reset what it means to be ultra premium.

Look, they're just showing off zooms now.

There we go. They're flushing.

They're zooming all over the place.

Yeah, I mean, not to, not to talk trash about Casa Czar. It looks fantastic. I'm just saying that the Besties all in Tequila, they innovated by including the illumination, by including the glass, by including the top.

We don't know. That could be the IoT functionality that people have been asking for.

We don't know. So, I mean, I would give the Besties all in Tequila the edge here. Now. Do you know the story of the iPhone? Are you familiar with what an iPhone is?

Where you're going with this.

I know where you're going with this. So when Steve Jobs introduced the iPhone, he famously said on stage, and yes, we're calling it the iPhone. And this was controversial because Cisco owned the rights, the trademark to the word the iPhone. And so everyone was like, how is this gonna work? You just launched a product that is clearly derivative of this other company's name. They have a trademark, they're just gonna block you. But at some point a deal was made. I don't know if it even became a lawsuit. It was probably just like they sat down and said, hey, let's, you know, let's, let's allow this to happen. We want to run with this. We could take it to the courts, but that's a headache for both of us. Let's just net this out and we'll buy some WebEx licenses.

There's a article on appleinsider.com from 2006. Cisco introduces the iPhone family of devices.

Wow.

And it is not nearly as good looking as the iPhone would ultimately be. But it's funny to see the iPhone like Word effectively the iPhone Word mark placed on a non Apple device.

Well, if you're trying to build the next iPhone or software for the iPhone, get on 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. Now we discovered an interesting link between Cisco, the iPhone, Apple OpenAI. Jony, I've and I think we cracked the code. We got to break it down for everyone.

Get the tinfoil hat.

Get the tinfoil hat. I will, I will send the. I will send the image to the team so they can pull it up. So, okay, so this is, this is how it goes. So Apple, as we mentioned, they potentially got the name the iPhone from Cisco. Now who designed the iPhone at Apple? Johnny Jony. I've. That's right now. Where does Jony I've work now?

OpenAI.

OpenAI. They acquired love from. They got. Brought him over to OpenAI. Who's the Chief Product Officer at OpenAI?

Kevin Wheel.

Kevin Wheal. And who's on what, what boards does he sit on?

Cisco.

Cisco. Who licensed the iPhone name from Apple.

Wow.

It's a snake in his tail. An Ouroboros of Silicon Valley intrigue. We crack the code here, it's all linked. Symbolism will be their downfall.

The most completely nonsensical schizo diagram.

Like, what are you alleging?

Yeah, what are you alleging? That things happen.

People interact with each other.

Yeah. That.

If only it were so simple, Jordy. If only it were so simple. I wish I had your mind, the mind of a golden retriever, to not see the obvious pattern here.

The big conspiracy.

Yeah, the big conspiracy that we unveiled here on tvpn that they're all linked. It's all part of.

It's all part of the plan.

Pulling the strings. Big Cisco, Apple, OpenAI. Jony, I've, Kevin Wheal. It's all linked. It's all linked. We blew it wide open. We should throw all those guys in our CRM. Adio, customer relationship. Magic Adeo is the AI native CRM that builds scales and grows your company to the next level.

The official CRM.

So, so final, final word on the besties. All in Tequila. I think it's a no brainer that they sell 9 million in this first run. The question is, do they, do they do that every month? Do they do that every year? Do they move on to a different drop or does this become, I think one of.

I think, I think one of the challenges of the. The what? It will come down, it'll come down to product quality.

Sure.

And then the number of people in the all in audience that care enough about tequila to spend twelve hundred dollars on a bottle of tequila. Not in a sort of like funny gag setting, but as like I'm gonna just drink this regularly. And I think it could be a lot. Like I could see them selling 20,000 bottles of this. You can imagine Them drink. One of them is drinking it on every show, right? It's sort of this constant, always on advertisement for it. I could imagine them, they're saying the besties all in tequila. I could imagine them going into other categories, right. And there's a world where they're selling tens of thousands besties all in malt.

Liquor, 40 ounces, 40s.

I would love to see J. Cal do Edward 40 hands. Yeah, Edward 40.

That'd be amazing.

We gotta move on.

Okay.

I'm having too much.

I have a different bull case for you. I have a different bull case for you. That's. It's a little more serious. So I have been in consumer package world for a decade. I've built two brands in the space. Like the product quality is super important. You do need an edge and you do need a value prop that can actually resonate with consumers. And you need ongoing marketing that's 100% true. But in fact, the biggest monopoly brand is an important monopoly for consumer goods. But there's almost a bigger monopoly with just distribution. Like if you actually walk around the grocery store, you will see I talked to a founder who came up with his whole model was he literally would walk down the grocery store and look at not just the products, but who owned the products. And he would see that, wow, this entire aisle is owned by Unilever. They just dominate the entire aisle. There's. There might be a ton of different brands, but everything is Unilever or everything is General Mills or Kraft or something like that. And so he, he wound up building a company that does. He. He was looking around, he noticed that the popcorn section of the, of the, you know, popcorn aisle was extremely uncompetitive because Orville Redenbacher is the only major brand and they're not owned by Unilever. So they don't hear much about that guy. You don't hear much. So he started a company that was like a popcorn spray that you could spray. A flavoring that you'd spray on the popcorn is purely additive. Wasn't competing with anyone. And he grew that to like a couple million bucks. It was great. And I think that a lot of these products, they do just wind up winning on distribution. And what's interesting about this is that I am almost certain that in the all in audience, yes, there are consumers, but there are tons and tons of people who work in distribution, work in store ownership. Like, would it be possible for any of the besties to get the CEO of, of of BevMo on the phone? Like, absolutely. In two seconds. They could do that. Could they get in, could they get this into Walmart? Absolutely. Could they get this into, I don't know, cvs. I don't even know what the biggest, what the biggest channels are for high ultra premium liquor are. But if you just think even like the independent store owners, they probably listen or are familiar, right? And so just being able to take that call and accelerate your salesforce and have them be like, like, yeah, sure, send me one, I'll put it on the shelf when we sell it, I'll just order another one from you since it's 1000 bucks. And so pulling that distribution forward into the, into the future, being more aggressive about that, about getting into distribution, holding onto it, I think that's, I think that's something that could be, could be interesting. And then the fact that the bottle design, there's a couple companies that do that have been particularly good with bottle design. I've talked to one consumer packaged goods founder who, who basically said that their whole model was like, go into a category and figure out how to make something like shiny and gold and like pop off the shelf. Because you look at the wall of all the products, they all look generic. If you can be the one that stands out, you're going to just have more people pull it off to sample it. And when I think about if I'm walking into a liquor store and I'm seeing a whole bunch of tequila and one of them is literally glowing and looks like a. And it has a light up display. This is something that a lot of consumer packaged goods founders negotiate for. They will say, hey, like Red Bull would come in and say we will give you a fridge, a Red Bull fridge, you know those fridges. Or like we will come in and give you a light up display. We fight for this all the time with Lucy. Like we, we will say, oh, we'll send you a free in store display that you can put on your shelf. And they're putting it on the counter so that we don't have to fight for the shelf space that's there. And so imagine if they're like this. Every bottle is a light up display. It'll jump off the back bar and so it won't just sit there and collect dust. It will automatically draw the eye to it. I think that the light up thing could be enough of like a distribution advantage that it winds up being a popular product.

I don't know that totally.

I agree.

I think it'll come down to product quality. What percentage of the audience actually wants to spend twelve hundred dollars on tequila on a recurring basis. Do they go into other categories? I think they could sell. You know, Chamath is also launching a wine club.

Yeah, that was interesting.

That's separate.

There was so much backlash to the tequila thing. It wasn't even the first alcohol brand he launched that month.

Yeah, yeah. At the end of the day, anybody that's getting mad about them doing something like this, it's like they have always been very candid that they enjoy drinking together.

Yeah.

Why?

You know, and, and like, I mean, people. And it's not like they, they can't do world positive things in tech. In addition to having fun and having their own alcohol brand. I think a lot of group chats out there would like to have their own alcohol brand. So anyways, I'm excited to see it play out. I'm excited to try it.

Yeah, yeah, yeah. This is definitely not like a pivot of the brand in the same way that talking politics is not a pivot of the brand. You go back to the very first episode of the all in podcast. They were talking politics. They were talking about COVID and stuff. Like it was, it was like they've been very consistent in all this stuff. So anyway, if they're trying to pump their tequila, they got to buy a billboard on ad quick adquick.com out of home advertising.

Straight to the 101. I want to see the one. I want to see every single billboard on the 101.

The besties all in Tequila. Out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Only Ad Quick combines technology, out of home expertise and data to enable efficient, seamless ad buying across the globe.

Yet if you're trying to get the attention of a CEO, maybe you want to sell some enterprise software to them. Why not gift them a bottle of the besties? Yeah, and that'll, that'll get you a demo real quick.

I think VC should be sending this to founders. Founders should be sending it to VCs. It's. It's a, it's going to be a hot commodity if you can get your paws on one of these.

Yep.

Anyway, Hims and hers stock drops more than 30% after Novo Nordisk breakup. This is from the Wall Street Journal. Of course, if you're interested in stocks that are dropping because you're going short or are popping because you're going long, you got to get on public investing. For those who take it seriously, they got multi asset investing industry leading yields and they're trusted by millions. Anyway, the Wagovi maker, that's Novo Nordisk, has cut ties with the telehealth company Hims and Hers, citing allegations of deceptive marketing practices and drug compounding. I feel like they were. The drug compounding. How is this an allegation? I thought that's like what Hims was saying they were doing. They were like. I felt like there was a lot of press about them being like, proud of drug compounding because there was a shortage, but I guess it's alleged at this point, so we'll dig into this. Novo Nordisk abruptly ended its partnership with Hims and hers after the Danish drug maker accused the telehealth company of illegally selling cheaper copycats. Okay, so this is after the FDA's ruling about whether or not there was in fact a shortage. So the Novo said on Monday that it had concerns about the safety of knockoff versions of Wegovy and that Hims and Herbs deceptive marketing of such knockoffs put patient safety at risk. In turn, Hims and hers accused Novo of pressuring it to steer. To steer patients to Weguvi regardless of whether or not it was the best option for patience. News that the deal was scrapped weighed heavily on Hims and her shares, sending them down 32% in afternoon trading in what would be the largest decline for the stock on record. Novo Nordisk's shares were down nearly 6% in New York. The messy breakup comes less than two months after the companies unveiled what they called a long term collaboration to directly provide Wagoovy to Hims and hers patients.

Okay, so this was somewhat predictable, right?

Talk to Tim Parker about this.

HIMS has been on a generational run in the markets because they're one of the best, easiest ways that people can just go buy WeGovy. Right now, if you're Novo Nordisk and you're like, cool, we're selling through this channel. But then the retailer, in this case hims, is telling customers as they come in, hey, we know you wanted WeGovy, but how about this sort of cheap knockoff, this compounded version? Now WeGovy can. It is probably legitimately concerned about safety issues. There can be issues around compounding in drug safety, but then the bigger issue is like, hey, you're marketing. You're using our brand and our products to acquire customers. And then you're getting those people in the door and you're saying, hey, how about this sort of cheaper, off the shelf alternative? And so I have to imagine that this is Novo Nordisk recognizing the value of their brand in this massive, massive, fast growing category and saying, we're not gonna let you leverage our brand to compete on these sort of high margin knockoff products.

Yeah, I mean, like, the Instagram ads that I saw were definitely pushing the brand name for real. And there was a while when they wouldn't use the term Viagra and they would use ed meds and sildenafil and Tadalafil and all of different. Like, they would use the actual underlying compound name. And they pushed it so hard that people actually started knowing the name of the underlying compound. Yeah, but, yeah, the brand name.

How do you think hems will respond? Do you think they'll introduce a 10 in 1 shampoo that includes compounded.

Yep.

GLP1s Viagra, hair loss.

Yeah.

Medication. What else could Adderall. They can put some caffeine.

I mean, this is cognizant. Rhodiola, Panax, ginseng, L Theanine, caffeine. Get some GLP1 in here.

Creatine soap with creatine soap would be good with all the above.

Eli Lilly is the one that lost the patent. Right. Because they forgot to pay the.

No, I think it was Novo Nordisk.

It was Novo. Wow.

They have.

They're all over the place. It is.

It is interesting to watch.

Yeah.

Novo Nordisk. How much do you think their stock is up over the past five years?

500%.

Try 113.

113. But it was a big company. Yeah, yeah, but it's been on a big company.

But still. And how much do you think, what do you think the. The chart looks like over the last year?

Oh, it's down.

The GLP one. Boom.

It's down because it ripped up so high.

Down 50%.

Went down 50%. And they. And they rotated out their CEF. That's right. We covered that. HIMS and hers is at 9 billion. 9.66 billion. That is down from a high of maybe 15 billion. And it's one of those interesting, like, SPAC targets that I think they got out through a spac and they, they never really went down that far. They were down, you know. Yeah. Like, you know, 30%. I mean, they spac to $10 a share, went down to $4 a share, kind of grinded back up. Now they're at $40 a share. So if you, if you bought this, if you bought the SPAC and you did hold for five years, you're, you know, you're sitting on a 3x4x. Not bad. So, you know, kind of a narrative Violation around the, around the SPAC. Like all SPACs are bad narrative.

Yeah, yeah. I mean it. And the CEO Andrew Dudum, we should have him on the show, said that, you know, I think his position, you know, we have no idea what the details of their, of their contract actually look like, but fairly reasonable position to say we're not going to just sell one product. Just, you know, because it's true. Not every patient is going to respond well to WeGovy.

Yep.

And they should have options.

So before striking deals with brand name drug makers, telehealth firms were selling lower cost knockoff versions of these drugs made by compounding pharmacies, taking market share away from brand name makers. The compounding pharmacies had been allowed to mass produce knockoff versions conditionally because the original drugs were in short supply. Now the whole compounding pharmacy dynamic is very different because I feel like the laws were created such that if a big pharmaceutical company couldn't supply you the drug, like your local pharmacist could compound it. But then the, the, the startups kind of like rolled up all the compounding pharmacies. We're doing it like a much bigger scale and it wasn't exactly what was intended originally, but I'm not sure about that.

Yeah. So the big question is when there should be more. Well, yeah, the big question, will there be more regulatory action around compounded GLP1s and what will that do to their business? So, so roller coaster of a year for him's partnership was announced in April 2025. Popped terminated just a few months later with a 35% drop.

Well, if you're on GLP1s and you're losing weight and your wrists are getting thinner, you need a watch that can adapt to your new wrist size. You need to go on getbezel.com your bezel concierge is available to source you any watch on the planet. Seriously, any watch. And you can find a watch with metal links that you could take out a link if you've lost a lot of weight or you could add one back if you're in a bulking cycle. Yeah, keep those links handy when you're.

Ready to start the bowl.

Exactly. This is key. This is very, very key. Anyway, comment from the CEO Andrew Dudum. He said hims and hers will continue to offer access to a range of treatments including Wegovy. So they continue to battle it out. It'll be interesting to follow this and we will of course be talking to Cremieux about this later today. There is a Investing visual post here that I pulled up about how himss makes money. They're making $576 million online, $10 million from wholesale. That brings their total revenue to $586 million, which is up 111% year over year. Gross profit there, 428 million. Operating expenses are 337 million, leaving them 92 million in net income or 92 million in operating income and 50 million in net income. So 50 million in net income for $10 billion stock. Pretty, pretty high price earnings ratio if that's their, or if that's an indication of their earnings. But it's been a big growth stock on a major, major trend. GLP1. And so the, the, the, the retail army has been coming out in force. King KSM's capital said it felt too good to be true for hims to go this long without some FUD. This is more like it just bought 2300, 2300 shares and top secrets.

What do they, what do, what does the retail army call themselves?

I don't know, himbos or something.

Say I'm really him.

Yeah, hims. Look at the data. You can see their operating margin has improved a ton since they've gone public. They started out at negative 40% operating margin and climbed up every single quarter. They're now at a 6.5% operating margin. The number of subscribers in the millions has gone from. They were at 0.6, so 600,000 subscribers. Now they're at 2.4 million and their total revenue has gone from $272 million in revenue. This is the last 12 months. Now they're almost at 2 billion and so they've almost 10x revenue from that SPAC price and that's what's driving the stock overall to be up 3 to 4x off the original SPAC price. So yeah, very good news. If you're Andrew Dudum and you need a break from grinding it out at hymns. Book a wander. Find your happy place. Book a wander with inspiring views.

Summer Andrew.

Hotel grade amenities, dreamy beds, top tier cleaning, 247 concierge service. It's a vacation.

Imagine you're in one of the gnarliest PR crises of your life and two guys in suits on a podcast that you've never met are just like, yeah, take a vacation. I think it's a bad idea.

Summer's long.

HIMS is up 2% today. John, you're good. So it's time to take, you know, treat yourself.

Yeah, take your foot off the gas.

Head to wander.com.

And speaking of foots on gas, Ford, which makes cars that you can put your foot on the gas of, is now under pressure to put their foot on the gas of acquiring rare earth elements. They are having difficulties obtaining vital magnets. They're scrambling with rare earth elements. Despite the deal the uni the United States struck.

And I just want to highlight, I think the silhouette of this car is fantastic.

The Mach E gt. You're a fan.

I've only owned one Ford Raptor. Yeah, it was a very fun car. Not very practical if you need to park in cities and things like that.

But yeah, if you want practicality. Ford gt.

I took a drive. Yeah. Practicality. All about the Ford gt.

Yep.

But I took a drive. My buddy Matt has a Ford Mustang. What is it called? The Mustang Mach E Rally. It's like this rally version of the Mach E. Okay, so it's still the.

Crossover, still like an suv, More or less.

Sort of. It's like a hatchback.

Yeah.

Yeah.

It's not a car. Like, I would not call this a car.

It is a very, very cool car. It's fun to him. He said it's like the most fun car he's ever owned.

Let's go.

And he's had something from pretty much every manufacturer at this point.

Well, he should hold onto it because they might be struggling to make them price.

The Mach E in the might be going up.

Yeah.

Ford Motor still facing difficulties obtaining vital magnets made with rare earth elements, despite a deal the US Struck with China to ease export controls, A company executive said Monday. It's hand to mouth the normal supply chain scrambling that you have to do, said Lisa Drake, a vice president overseeing Ford's industrial planning for batteries and electric vehicles. Ford in May stopped production at a vehicle factory in the Chicago area because of a magnet shortage. The situation has improved, but the company still needs to move things around to avoid manufacturing shutdowns, given the scarcity of the materials, Drake told reporters during a briefing at an EV battery plant the company is building in Michigan. China in April began requiring companies to apply for permission to export magnets with rare earth metals, including dysprosium and terbium. The country controls roughly 90% of the world's supply of these elements, which helps magnets to operate at high temperatures. Much of the world's modern technology, from smartphones to jet fighters, rely on these magnets.

So everyone sees that 90% of the world's supply and thinks it's 90% of what's in the ground, and that's not the case.

Yep.

What, what, what is really going on here is that the industrial capacity to remove the rare earth elements from the ground is 90% in China. So they have 90% of the mining companies, 90% of the mining equipment. They don't necessarily have 90% of the actual rare earth metals in the ground. And the rare earth metals are not that rare. But we hear this every once in a while where you say, oh, like there was a ton of rare earth deposits found in Ukraine or found in America somewhere, and that's not enough, like just having them in the ground. You still have to go and dig the mine, get the approvals, make sure. And one of the big reasons this was offshored was because of environmental considerations, which I find so frustrating, because it's one world. Like, it's an earth. Like, if you want to protect the earth, moving something from one continent to another does not save the Earth. Like, I mean, I guess there's a little bit of like, yes, there's runoff in one river and so there's local pollution that you're avoiding. But in general, you've been to China, John.

It is dark. Yeah, the sky is legitimately dark.

But I think that, I think that like a lot of the pollution that's going on over there is affecting us too, for sure. And so especially if you think about like, the broader global warming picture, the broader, like, poisoning of the air, like that stuff's not going to come over here at some point. Like, I find that hard to believe. It would have been much better to just focus on ramping up production in America and then actually doing the technological innovation to develop cleaner processes and not just offshoring it because it's like, dirty and then just doing the dirty stuff over there. I don't know, maybe, maybe there's an argument for it, but it feels like the whole offshoring project was wrapped in this veneer of like, no hear no evil, see no evil, speak no evil. That type of vibe. Like, if we can't see the pollution here, it's fine, it's not happening. And it's like it is still happening. It's just you don't have control over it now.

They've leveraged massive supply chain risk.

Exactly. And I don't think it actually had an impact on the, like, like the stated goal of the environmentalists that pushed rare earth manufacturing overseas did not, was not achieved. And so that, that feels like, like a failure. And then on top of that, we lost control of this important supply chain. So Ford isn't the Only carmaker struggling to obtain these magnets. Several other carmakers say that the pace of export license approvals for rare earth magnets hasn't changed significantly. It isn't quite day to day, but it's weekday to week, said an executive at one of the carmakers. Car companies have warned that they could be forced to halt factory work if they're unable to attain enough rare earth magnets. In the auto industry, rare earths are essential to electric vehicles because they allow a low cost way to ensure motors operate at high speed. Okay, so this should not affect the production of raptor Rs. Thank goodness. I was, I was extremely worried, but. So we might have to get most of those Mach E owners into Raptor Rs.

Okay. But I don't think they're mad at that.

That's something we have to. Yeah, if we have to do it, we have to do it. We have to do it in the auto. In the auto industry, rare earths are essential to electric vehicles. President Trump struck a deal earlier this month for China to resume granting licenses to export rare earth magnets. The agreement, which has a six month limit, is aimed at allowing China to retain its chokehold on the critical minerals that give it leverage in future trade negotiations. So very, very rough. Anyway, how'd you sleep last night? Let's pull it up.

Praying. I got an 88, John.

Oh, no. 82.

There we go.

You beat me. Oh, Jordy's back on time.

I'm back.

I'm back after a while.

I'm back. What happened to me? I just. I guess I stayed up too late or something. I was in my sweet spot. Oh, I guess I didn't fall asleep until 11:12.

There you go. There you go.

Gotta go to bed earlier.

Back on the. I'm back on the horse. Yeah, back on the horse. It should be a competitive week. I'm excited to see how it. We got to start putting. We got to start putting something on the line. Yeah, like the. The loser on Friday gets no caffeine and nicotine.

And they'll be sleep deprived, too. That's. That's double duty. That's extra hard.

I don't know.

That would be torture.

Anyway, our first guest is coming in the studio in 10 minutes. Let's take you through a beautiful obituary to the founder of FedEx, Fred Smith. So Ryan Peterson posted a photo of the original FedEx plane. He said RIP to logistics legend and outspoken defender of free trade, FedEx founder Fred Smith, who passed away today. Below is the first ever FedEx plane which you can see at the Air and Space Museum Annex next to Dulles Airport in Virginia. Look at that. He must have been so stoked when he bought this. Like his business was finally growing that he could own his own plane.

Imagine how many likes he would have gotten on social media.

Yeah, everyone's like, this is your flash. You're just trying to go viral. This is clulee.

This is Clulee for logistics.

Clearly for logistics. Total legend, Burning VC dollars on a plane. Bear.

I think he was using Vegas.

I think he was doing cash flow. Yeah. Anyway, Max Meyer has a story that we should read through. Fred Smith and American Life. He says Fred Smith died on Saturday. He was the founder of Federal Express, which became FedEx, one of the largest logistics companies on earth. Smith was an entrepreneur in the truest sense of the word and an American patriot. He bent reality and created something entirely new. And he ran toward an extremely difficult problem. The fruits of Fred's work are as follows. If you give a box or document to FedEx by 6pm you can have it delivered almost anywhere in the United States or Canada by 8am the next morning.

Imagine how key that would have been to business before the Internet.

Incredible. Yeah.

You're trying to do deals.

If you give FedEx a package on a Monday, it can be in Paris by Wednesday morning or in Shanghai by Thursday for a few hundred dollars. Most of us take overnight delivery for granted. But take a step back, and the fact that we can essentially airdrop physical packages anywhere in the world is mind boggling. Smith's death is a reminder not to take the miracles of modern life for granted. They were built by people like Fred Smith. These are a few words about the man himself and the dazzling system that is FedEx. Frederick Wallace Smith was born in 1944 in Mississippi. Fred's grandfather, James Buchanan Smith, captained Mississippi river steamboats. Fred's father, James Frederick Smith, was the founder of the Smith Motor Coach Company, which would go on to become Dixie Greyhound Lines after an acquisition in 1931. From steamboats to buses to jumbo jets in three generations, the family stayed on the cutting edge of motorized transportation. In 1925, the elder Smith, seeking to create the transportation line out of Memphis, converted a truck into a small bus and drove it himself. Within a few years, James Smith had dozens and dozens of coaches. By the time he died suddenly in 1948, he commanded over 200. Wow. So he died four years after the son was born. Wow. So he basically grew up without a. Or maybe that's the grandfather. According to James Smith's obituary.

No, no, no.

He's the dad. Yeah. Yeah. So according to James Smith's obituary, those 200 coaches each came to a halt during the regular, regularly scheduled routes for one minute when the funeral began. The young Fred was just four when his father died. Wow. In 1962, the young Smith enrolled at Yale University where he was fraternity brothers with future president George W. Bush. Bush asked Smith to serve as the secretary of defense twice, and Smith declined twice. Wow.

Interesting. Because Defense is. Who was the founder that we had on the show. I'm completely blanking on his name, the name of the company and who invested in the company. But he had this defense focused supply chain management startup.

Yes.

It was one of our. Probably first.

You're talking about Rune Logistics.

Rune. But something he said about.

Not the AI poster.

The legendary poster.

Not a legendary poster. The logistics company of OpenAI. Yes. So the young Smith was a member of the infamous cloak and dagger secret society.

He is not beating the secret society allegations.

It was at Yale that he wrote his first paper about his concept for using airplanes to deliver packages with a hub and spoke system. Wow. He's like, I got an idea, I got a business plan. I just need somebody to build it for me. That is that instead of point to point package transport, everything would be brought to a single hub by air and then redistributed. We talked to somebody about this on the show how now we think of it as like inefficient to bring everything to one place and then do the hub and spoke thing. Because now we have, you know, Doordash and Waymo and you know, last mile. All these, all these different last mile solutions. But at the time, this was revolutionary. Everything would be brought to a single hub. Repeat that cycle every night while turning a profit and you have a viable system for overnight delivery. The paper is said to have earned an average grade. Roasted. In 1966, the founder of FedEx graduated from Yale and volunteered to receive a commission in the Marine Corps. He served two tours in Vietnam. For his service in Vietnam, the President Nixon decorated Smith with a Silver Star and a Bronze Star. The Silver Star citation read in part, unhesitatingly rushing through the intense hostile fire to position the heaviest to the position of heaviest contact. Lieutenant Smith fearlessly removed several casualties from the hazardous area and shouting words of encouragement to his men, directed their fire upon the advancing enemy soldiers, successfully repulsing the hostile attack. Moving boldly across the fire swept terrain to an elevated area, he calmly disregarded repeated North Vietnamese attempts to direct upon him as he skillfully adjusted artillery fire and airstrikes upon the hostile positions to within 50 meters of his own location. Wow. And continued to direct the movement of his unit. Wow. What a badass.

So at this point, yes. 1973, he's 29 years old. He lost his dad at 4. He goes to Yale with George Bush, then goes to Vietnam, does two tours, gets a silver and a Bronze Star.

It's crazy.

War hero.

Yeah.

And now he's decided to launch Federal Express in Memphis. Smith had studied military procurement and been working on the idea for nearly 10 years after writing the Yale paper. So he writes this paper and he's like, okay, 10 years later, most founders.

Have an idea and they pivot through two months.

So he writes this paper, gets an average grade. This is like 10 years later.

This is the same thing.

10 years later. The company launched with a fleet of 14 French Dassault jets, which delivered a few hundred packages on their first day of service. There we go.

Wow.

He's just like just 0 to 1. According to FedEx, Lor Smith named his new service Federal Express because he hoped to attract the attention of the Federal Reserve Bank, a prospective customer. It's funny like that. The name you would. You would think Federal Express. You would just assume that it's an extension of the government.

I did when I was a kid, I was like, oh, United Postal Service. But as a kid, you realize Postal.

Service, these are like. It was just a better product experience than usps. Even as a kid, you kind of feel it out. Feel it out. The system that Smith had conceived at Yale worked. It really worked, and nothing like it existed. The USPS existed principally to deliver letter mail and didn't have aircraft. UPS was a giant of a ground delivery throughout the U.S. federal Express, though, would specialize in rapid air delivery. Just five years after the first Federal Expression Express flights, the company was listed on the New York Stock Exchange.

Wow.

Today, the FedEx fleet consists of nearly 700 aircraft and about 200,000 vehicles. And FedEx employs half a million workers around the world.

Wow. Every night at the FedEx Super Hub at the Memphis International Airport, hundreds of jets land at the airport, the ultra hub super hub, bringing packages to its many sorting machines. A few hours later, the jets take back off to every corner of the United States and the world at their destinations. The other half of the fleet awaits feeder aircraft to take packages to smaller airports and the FedEx Express trucks that take packages to their final destination.

The financial finesse needed to actually make a model like this, not just Lose massive amounts of money.

Yeah. You could go out of business so many times. And yeah, there is that story about him almost losing money, going to Vegas and then putting the, the treasury on black and winning it back and doubling it and making payroll the next day. Saving the company. Maybe apocryphal. There's been rumors that maybe it was like, you know, some mob related thing.

And he took a ten. The tinfoil. Yeah, the tinfoil hat explanation is like, you know, he.

Either way, he got it done.

He did some type of, of, you know, and this is entirely Internet speculation. It's probably not true. But it's possible that he like, you know, was, you know, needed a reason to have a bunch of cash. Right. And maybe did something else. But the story is incredible and it will live on.

Yeah.

Smith retired from FedEx in 2022 after almost 50 years leading the company. He is survived by nine of his 10 children and his wife Diane. His daughter, Winland Smith rice died in 2005 of a terminal cardiac condition. It's very sad and one has to think that his father, his father, Mr. Smith, who died with 200 vehicles to his name, would be impressed that his son died with 200,000 vehicles to his name and a fleet of jets to match. So incredible story and may he rest in peace.

Anyway, let's move on to the timeline. Also, one of the greatest logos of all time, the FedEx logo has that secret arrow in it. Love that.

Oh, yeah, yeah.

Once you see it, you can't. Not this logo, the next logo. The more modern FedEx logo has the secret arrow in there. Once you see that they're moving, they're moving.

And if you want to understand more about Frederick Smith, go to Founders podcast and listen to episode 151. 151.

And subscribe to Arena Mag to read more of Max's writing. Check it out. Arenamag.com what, what else is.

We have a post here from Garav Vora. He says chat. Remind me to check this again in a year. I wonder if he's saying he's throwing it in chat. Yeah, saying, you know, check this again a year. This is a graph. It'll be kind of hard to read, but it's showing chatbots versus search engines. Who's winning the traffic war.

Showing that Google is getting 1.6 trillion total visits to ChatGPT's half. 50 billion, basically.

So Google is down 1.4% year over.

Year and ChatGPT is up 67%.

Yeah, I mean, it's a 34x gap today.

Yeah.

AI chatbots drew 55. Isn't that wild though? Yeah.

So I wonder.

OpenAI accounts for. Out of 55 billion visits. OpenAI accounts for 47.7 billion.

Yeah. So users, 81% of all chatbots is OpenAI. I feel like it's even higher now, but it's crazy.

So AI chatbots are 2.96 of search engine traffic today. VARAV is calling it or wants to check back in a year. It's very possible we could see double digit search engine traffic into chatbots.

Yeah. I do wonder if like site visits is even the correct metric here because it's more like time on site and attention. Because I'm pretty sure I Google things like for just two seconds, Google something. I will use Google as a calculator and I won't go to ChatGPT for that. If I just have to multiply two numbers together, I'll just throw that in.

Oh, you're not a power user.

No, it's faster. It's all about speed.

People believe in AI.

Exactly. I'm still like checking out this whole AI thing, starting to learn about it. But. But yeah, I think the more relevant metric is actually total user minutes. Like how much mindshare is going on. Because when I'm in, I'm probably in chatgpt longer than I'm in Google. But I might be hitting more page views on Google than ChatGPT queries because I might throw a deep research query and then spend 10 minutes reading and forth. I'm very rarely throwing a Google search out and then reading the blue links for 10 minutes. That's just not how it works.

So anyway, also interesting to think about how they're counting visits. Right. You're having this conversation with ChatGPT where oftentimes you're repeatedly running new, new hits.

Right.

Against Google.

So anyway, we have our first guest in the studio. Cremu. Welcome to the stream.

There he is. Looking at him as evidence.

How are you doing?

Doing well. Can you hear me?

Yeah, we can hear you fine. I'm looking forward to, you know, a future date when we can potentially see your face. But for now, your avatar looks great. Soon. Okay, I'm looking forward to it. We wanted to have you on to chat about a couple things. What's going on? GLP One world reaction to the Hims and hers breakup. Jordy, where would you like to start?

High level Update on the GLP1 market.

Yeah, I guess. I mean it's this miracle drug that keeps on. We keep on learning about new diseases or problems that it can treat. It seems like it can't just stop. We got the diabetes, then weight loss, then maybe gambling addiction and other stuff. Walk us through where, how people are using or how Doctors are prescribing GLP1s for various conditions and what's most promising, what's on the horizon and what you're tracking next.

Yes, I'm actually really glad you asked this right now because right now the ada, the American Diabetes association conference is ongoing and it seems like every other presentation is about GLP1s. They are just talking about all the latest advances. Just yesterday, Amgen showed off a once monthly instead of once weekly injectable. Eli Lilly showed off an amazing combo therapy with a, an inhibitor called Bima. Groome Out. It's a very weird name that makes people not lose any muscle when they're on the drugs. They've been showing off just incredible advances all week. They've been showing off new treatments for like different conditions and whatnot. There are increasingly many indications these drugs are getting approved for. In December, Tirzepatide was approved for sleep apnea. Yeah, there's osteoarthritis indications incoming. There might even be. There's some effort being put into people trying to do something for cancers as well because it does seem to help with obesity related cancers and it seems to help for. I don't know why with hematological cancers, the blood cancers, I don't know understand really the mechanism behind that. But it seems like it's just hitting every single indication now.

Wow.

Why do you think that is? I have some guesses.

I think the big reason has to do less with the direct effects of GLP1s and more with the fact that obesity sucks. Obesity is just really, really bad. It affects so many different systems. It makes your health worse on so many different levels. And the things that lead to obesity are also quite bad, like the bad diet, the bad habits, the not moving around very much. It's actually interesting, a lot of people after they've been on these drugs for a little while, they decide to move around more. They become more likely to go to the gym. They report their physical functioning has improved. It turns out that getting fat has made them get to the point where they are no longer looking to be active and so they just kind of fall into a hole. Practically everything is improved, I think for that reason. And there are some improvements that are due to direct effects of the drugs. This has like for example, this one is major adverse cardiac events, major average cardiovascular events. Those seem to be reduced in number immediately after starting the stuff, which suggests that there's a mechanism that's pretty direct and this mechanism is also independent of weight loss. So that seems to be how that works. Same with chronic kidney disease.

Are you looking, you know, I feel like the sort of biohacker alternative health world has for a long time, you know, talked about cancer being, you know, this metabolic disease. Do you think that could be a factor and why it should could show some promise in treating various types of cancers?

Yeah, I think it does makes a lot of sense in that direction for the obesity related ones, but I don't think it makes sense.

So.

So years ago there were people who suggested, I think quite wrongly replacing certain cancer therapies with fasting because it seems to like augment the effects of cisplatin based therapies and stuff. And that didn't really hold up very well. It was a bunch of theory work that didn't go anywhere. And I don't think that this would help through those purported mechanisms which again, I don't really believe in. I really think it's mostly just cutting down on for example, the number of cells you have or well, not really a number of cells you have, but like the activity of, of being fat. It's just you have, you're not as big of a person, you have less to less opportunity for cancer to really hit you when you are smaller. Yeah, smaller. It's like how short people tend to live longer than everything else.

Bad for me, bad for you. Bearish for me. How much of the recent like advances in GLP1 indications or recent benefits have been just looking at all the people that are taking GLP1s for weight loss or diabetes and then seeing a secondary effect in the population that's actually running the drug versus a new double blinded trial for a different indication. Are both things happening or are these drugs diffuse enough that you can just look at the overall population and get an idea of what's happening?

Happening?

Yeah. So for approved Indica FDA approved indications like obstructive sleep apnea, you do have to run additional trials, but they are seeing that these things are possible from their trials. They're seeing these things are possible from the literature and they're running based on that. So in some cases they do see these secondary endpoints. In fact, obesity is an example of this back in the day, when they first introduced these Drugs, back around 2005 or so the CEO of Novo Nordisk at the time actually said, and I quote, obesity is primarily a social and cultural problem, it should be solved by team, by means of a radical restructuring of society. There is no business for Novo Nordisk in that area, referring to obesity.

Wow. Yeah.

So their scientists had to push for about a decade to go, hey, you should look at the weight loss data. It's really impressive. And then they finally, finally did it. And now we have weight loss drugs.

Yeah, that is wild. What concerns you? What's the catch? It seems it's too good to be true. Yeah. Somebody might say, is it too good to be true? We're running this sort of massive experiment on huge swaths of the population right now. Seems to be many, many positive indicators. But what are kind of red flags that you think people should be kind of looking out for or the scientific community be. Should be wary of? Broadly, from your point.

Yeah. So I think that physicians need to be careful about prescription. And they already are. They, like, they don't tend to prescribe this to people who are very skinny. But the fact that this stuff's available through the gray market very easily without prescription for very, very cheap. Fortunately, I've contributed to that. Has led to.

In what way? You mean just. Oh, I made a. I made a.

Guide to doing this and a few thousand people actually like paid me $8 a piece to see all the details on it. And now I have a few thousand people who, unprompted, I didn't tell them to do this, message me their weight loss progress and such. So through writing this guide a few months ago, I've led to almost 12,000 pounds of weight loss. And that's just what's been reported to me. Not everybody's telling me all the results.

And is that, Is that at a high level, people just finding pharmacies that will compound the drug for them? What does that actually look like?

So what it looks like is buying from China. So you are ordering from a Chinese factory, you are testing the purity of the stuff and finding, oh, it's 99.9, I can use it. And then using all of that, it is not sold by Novo Nordisk, Eli Lilly or any other major company working on these drugs, it's just from some Chinese company that is ripping them off.

So is that patent infringement we've been seeing that kind of go back and forth like hims and hers was able to compound because there's a shortage. There's also that news about Eli Lilly.

And say, hey, can you please knock this off?

Yeah. I mean, they could do import bans or seize the packages at the ports. Like, that's the design of this, you can't just buy a knockoff iPhone and have it delivered through the Port of Los Angeles. Like if a whole truckload comes through, they should stop that. But it's clearly not happening.

So right now the FDA allows this to happen because they have an exemption for research chemicals. You're technically not supposed to use these things, but everybody knows that everybody uses them. It's just how it is.

They're researching weight loss.

Yeah, I'm researching.

And research maxing. Yeah, I'm doing. So you were saying the, the, the potential red flags or things to be wary of is around. What about the prescription activity concerns you mostly abuse?

Not really prescription activity as so much as the abuse. There are people who are obtaining these drugs. There are people who are getting other people to get the prescriptions. There are people who are not really visiting doctors. They're using telehealth services to get prescriptions, and they are not in need of them.

But why would some weight use? This. This doesn't feel like something that has like the euphoria associated with a stimulant.

So the concern I think would be somebody has body dysmorphia.

Is that what's going on?

Really skinny.

Unfortunately, I've met a few dozen women now who have taken these drugs and been around 120, 130 pounds, normal height, and now they're around 100. And they are. They don't look good anymore. They look like they're aging very quickly. They look unfortunate. And it's. It's sad to see that they're using these drugs when they didn't even need them in the first place.

Interesting.

The same name. The effects of. Of start actual starvation.

Yeah, yeah, yeah, yeah, yeah.

You start getting really bad, had harmful effects. You probably are eating at that point more lean mass than fat mass. It is quite bad.

Yep. Yep. That makes sense. Yeah. That's always the risk.

Interesting. How are you? What was your reaction to the HIMS Novo Nordisk partnership blow up?

So I actually think this was a big failure. I never noticed part. It seems as though what they did was they partnered with HIMS in order to catch them. My understanding is that HIMS has been selling a little too much more than they've been supplied by the person producing the drugs, which is interesting. I guess we'll get more details relatively soon if the law commenced all that.

Theoretically, WeGovy gives them a million doses and then HIMSS is somehow selling 1.2 million doses of WeGovy. Is that. Is that what you're yeah, something like that.

They're either compounding it themselves or ordering from something from China. They are doing something and I don't know if that will hold up or show up in trial. It's an accusation. It's so I guess it's alleged. But we'll, we'll see. We'll see.

What about, what about hims general position that patients should have as much choice as possible, as much access, you know, access at different price points, things like that.

They are completely correct to do that. I think that hims providing different dosages than are provided by Novo Nordisk is a wonderful thing. There are people who can get legitimate uses out of sort of micro dosing this stuff because it gets rid of noise. I've met many, many people now and this is an increasingly common thing, it seems. I really don't know how far this is going to go. But a lot of people who are microdosing this because it helps with their adhd. Their ADHD is like the pathological end of food based distraction. They're not losing weight from this anymore, but they are just using it in order to not think about food at all. It gets rid of that nagging feeling in the back of their head and they can focus on work.

Yeah, I did a 24 hour dry fast from Friday night to Saturday night and all day Saturday. I was shocked at how much time I was just thinking about food and water, wanting food and water. And I was. And it was very freeing to some degree because I was like, well, I'm not just not having any until around dinner time, but so many points throughout the day. Was just going to, oh, I should go get a little tasty drink from the fridge. You know, I should.

I'm not addicted. I'm not addicted to.

I'm not addicted to water and food. I'm not beating the water addiction allegations. Big water guy. What, what else are you tracking right now, broadly? Any reactions to the NIH funding?

Oh, yeah, 40%. We had Andrew Huberman on the show. He was breaking it down for us. And what's going on with Jay Bhattacharya? What's your take on the cut that have been proposed?

So I don't know how much I should reveal about that. There's a lot of really good things coming. There might be some interesting developments there very soon. I'm especially hopeful about. Well, you know, actually I shouldn't say that. Just there, there'll be good news there soon. There'll be some changes.

Yeah, yeah. I guess zooming out, like what, what does good look like to you? Are you generally in favor of taxpayer funded?

Every American gets a $10,000 biohacking budget annually.

They can buy research chemicals, biohacking vouchers.

Yeah, I mean some people would say like, you know, the, the, the big pharma companies are profitable. They should bear this expense, not the American. Yeah.

So they're not profitable enough. They have troubles with R and D. That public money is very, very useful. We need more public funding than we currently have.

Yeah. When you actually look at biotech returns, just looking at the asset class, the logical thing to do would just be to invest elsewhere. And that was with historical levels of public funding that kind of contributed to those returns to some degree.

Yeah, we have a dearth of funding at the moment and we need to increase it. We need to improve the allocation and also increase the out. There's really no way around it if we want to keep making progress. You just have to throw more money at these things and I think we will start doing that very shortly. These cuts are a little alarming to start, but they are not the end of the discussion. Remember, we are. It's still only five months into this presidency and they have a lot of really big plans. They have a lot of trouble getting appointees through the Senate. They. And they have a hiring freeze ongoing right now that is interminable. We don't know when it's going to end, but once that is over, they'll be issuing NPRMs left and right. It's going to be deregulatory, like massacre. It's going to be wonderful.

Wow. Well, that's what else is exciting to you in biotech right now in.

Well, I wanted to say on the hams point with the different pricing and whatnot. I think perhaps the most exciting thing right now in that area is that Novo Nordisk is run by idiots. Like they're very smart people, but they're just total idiots.

Hey, everybody misses a the patent, you know, what do they do?

I think it was Eli Lilly. But no, no, this is Novo Nordisk. Oh, there was Novo that lost the, the patent fee.

Yeah, 450 bucks or something.

Yes, it was 250 and then they missed it and they were told you're one year out. You have, you pay a late fee, like an extra 200 late fee on it.

And they just didn't.

They still failed. Yes, it is amazing. So that enables a wonderful, wonderful program that the FDA should pursue immediately. The FDA and the CMS have to collaborate on this, but it's the Section 804 importation program and it allows individual US states to import as much of the generic drugs or any other type of drug that's pretty produced in Canada and has like an indication approved here and whatnot as they want to reduce costs. So for example, Florida will, whenever they get this actually going, have much cheaper EpiPens. They'll be able to lower the cost of drugs by importing cheap generics from Canada. And because cheap generic Ozempic is going to be coming From Canada in 2026, every state can just jump on the program. And if we're giving people, if we're giving Americans $5 a week ozempic, then we're going to see perhaps an end to the chronic disease crisis. We're going to see obesity tackled meaningfully. We're going to see people getting hot again and make America hot again. The real meaning of aha.

The real meaning of aha. Oh, the real meaning of aha.

Let's see.

There we go. There we go. Inside baseball. Very exciting. Well, 15 minutes was not enough time. Never enough to have you back on again soon. Thank you for all the insights.

Yeah, thanks for coming on. We'll have you back on soon. This is great.

And if you dox yourself anywhere other than here, we will be very upset.

Might have to. Oh, no.

Sorry, guys. You guys have a good one.

We'll talk to you soon.

Bye. Next up we have Clement from Hugging Face coming into the studio. I believe he's here already. Very excited to talk to him. Fascinating business. We'll dig into artificial intelligence, open source, everything that's going on.

What is the origin of the name Hugging Face?

What is artificial intelligence?

It's the emoji, I believe.

Yes. What is it?

What's going on?

How you doing?

Welcome.

Hey, that's the emoji. Like that. The hugging face emoji.

Yeah, yeah, yeah.

Yes. But there's.

Come on, you guys are giving me about the name with a name like that. Tvpn.

Yeah, yeah, yeah.

I'm not giving. I'm not giving you. I just, I just responded origins. And then I just immediately see the. Obviously the icon.

But there's more to the name than that. It's an emoji. But it came because the product that you were building before this was related to that. Right? Break that story down.

Yeah. When we started the company eight years ago, we were building some sort of Tamagotchi AI. AI girlfriend. ChatGPT before ChatGPT.

There you go.

So very much kind of like an entertainment product. And so we picked the Hugging face emoji, because that's the one that we were using the most. We also had internalized this joke that we wanted to be the first company to go public with an emoji instead of the three letter ticker, you know, like on the nasdaq.

Yep.

Still, still. Fingers crossed for that. I hope nobody's gonna go public with an emoji before us and that they'll wait for us.

Yeah.

And then the community just loved it and started to put it everywhere, put it on their, on their clothes, on their, on social networks, everywhere. So we decided to keep it.

Yeah. The owning an emoji as a brand online I think is still an underrated strategy. We see it every once in a while. I've seen people use the different fruit emojis for different things and there was a whole strawberry story tied to OpenAI and stuff. But when you can condense down, I mean it's a coinage essentially. Like when you can own an emoji and have it say something that's very powerful from a branding perspective.

You can even search with an emoji on Google and the app Store directly with the hugging face emoji.

Yeah.

I mean you're going to compete with the people that use the emojis for any other reason and there's always the risk that somebody steals.

I bet their emoji is pretty solid.

But I think, yeah, I think if you search the hugging face emoji, you're going to wind up in the right place. But walk me through the business today. Give me an idea of the scale and kind of the core business model.

Yeah.

So we one of the most used platform for AI builders. We just crossed actually today. 10 million AI builders using us. So it's mostly AI scientists.

Congratulations. 10 million. That's a lot.

10 million AI builders. So it's mostly AI scientists. AI engineers, software engineers, building models, training models, optimizing models, sharing models, data sets, apps. So this is a new repository. So. So it's model data sets, apps created on hugging face every 10 seconds now.

Wow.

And the way we monetize, because you asked this question, is kind of like a pretty straightforward premium model where most of the usage and the users are free and then a small percentage are premium and usually they become premium with premium features. So for example, enterprise features, when like a big company like Google, like Nvidia using us, obviously they need user management, security, stuff like that. Or when they need premium compute. Right. So when they need more powerful GPUs or hardware to run some other stuff, they're doing on the platform?

Yeah, 10 million AI developers, if you paid each one, $100 million, which seems like the going rate these days. It's a quadrillion dollars. It's a lot of money. But I mean, even if you're paying reasonable rates, you're still up in the trillions of dollars for the total market. I mean, I would be interested to get your reaction. How have you been processing the news that the talent market for artificial intelligence researchers seems to be hotter than ever in history and we're getting into NBA money for top researchers. Do you think this makes sense given where we are in the cycle? What has been your take overall?

Yeah, it's definitely hotter than it's ever been. Because when the CEO of OpenAI is saying that another company is paying more to get OpenAI employees, it's really like you reach the top because historically obviously they've been kind of like the highest paying mobile company ever in terms of packages. So when he's saying that they're getting beaten on packages is quite phenomenal. I hope it's not going to continue too long and there's going to be more kind of like almost democratization of skills of AI building. Otherwise I think we'll end up in quite weird world. One of my biggest focus is how to fight concentration of power, concentration of skills, concentrations of resources in AI. And I hope we can progressively move into a world where everyone can build AI and not just a few hundred AI scientists. That'd be really great for me.

What is your interaction today with the various prompt to code tools? What are you most excited about? What is that space? Because that feels like the entry point. Somebody comes in and they are making software for the first time and that can be maybe a gateway into exploring the whole ecosystem of hugging face and everything there.

It's super exciting to empower more people to be builders. We actually released last week our MCP that is integrated into Claude, into ChatGPT that they announced actually I think a few days, few days ago into Codex, into Cursor. So we integrated with all of these. We've got a specific focus which is not only to empower people to build websites or simple apps, kind of like the previous generation of apps, but trying to empower everyone to actually build AI models, which becomes really exciting because it means that maybe everyone can start training, optimizing their own model, that then they use themselves on their interface to kind of keep building even more. So that's when you start to have kind of like maybe this flywheel in terms of AI progress. So that's kind of like our focus with the integration of Hugging face mcps with a lot of these tools.

On the open source question, kind of like the decentralization of power. What was your interpretation of the anthropic today that it was in fact fair use for them to train their models on? It was several hundred thousand books or several million, seven million books. I was kind of, you know, optimistic that that would happen, but also just it seemed like we clearly needed some sort of legal ruling here to understand this stuff. But. But how did you process it? Were you happy with the result?

Yeah, I think this is good news obviously. I think this, this ruling, they'll come and be different and specific depending on because you have to look at not only, you know, what's been used, but also how it's used. If it's kind of like transformational, if it's replacing competing with the initial data sets. What's being cool for open source is that I think by default open source is fair use. So when someone releases kind of like a data set on hugging face, in my opinion it's usually fair use because it's used for educational, for progress. If you look at when copyright was invented and designed, the main focus was not to prevent progress and learning and education. You don't want to put copyright rules that are limiting progress. And so I think in open source most of the time when you release models or data sets in open source, it's fair use. So hopefully that is going to be kind of like a little bit more of the motivation for companies, especially in the US who've used a little bit this argument not to release their models and the data sets to do it a little bit more because I think we really need it now. I don't know if you've seen yesterday the, the conference from Dylan from Semi Analysis talking about kind of like the energy limitations in the US compared to China.

Yeah.

Something interesting there is that in addition to that we're materializing way less in the US than in China because in the US most of the leading frontier labs are proprietary and so they all do the same training runs.

Oh, interesting.

If you think of it right. If you think of entropy, OpenAI Xai they all do almost the exact same million dollar training runs whereas in China they're much more open. Right. Deep Seq for example. And so they mutualize compute and energy much, much more. So it's not only that they have more capacity but also they use this capacity much better. So I think it's urgent that in the US we kind of find solutions for that, not to create additional risks for the development of AI in the.

U.S. yeah, it's kind of oddly become more monopolistic over there or something like that. It's kind of an odd outcome. But that certainly makes a lot of sense. On the training data sets that go out, what are you seeing on the video frontier? It feels like we've been kind of batting back and forth this idea that Google might have a really, really powerful sustaining advantage there because of the YouTube data set. You talk about 7,000 books, you can probably download that on a torrent somewhere. If you're creative enough, you might be able to scrape it onto a single hard drive. We've heard about folks putting training data on hard drives, flying to Malaysia, doing a training run, flying back. You think about GitHub, all the code's basically been stolen at this point. Like it's out there. Some of it's open source, some of it's in, you know, it's obtainable. It's much harder to get all of YouTube on a single hard drive and steal it or even just have a scraper because you know what it's like hundreds of hours are getting uploaded every minute or something, something like that. So what are you seeing on the, on the video training side in open source, closed source, how do you think that submarket plays out in artificial intelligence?

An interesting data point there is that on Hugging Face, there's almost half a million open data sets with a thousand new data sets added every day. And the fastest growing category is video data sets. And the reason why is because not only it's more of the focus for training, but also because I think we're starting to see more and more synthetic data sets on video that are starting to really work, especially because the physics is starting to work on a lot of these video generation tools. It's not only used to create other video generation models, but it's also starting to be used, for example, in robotics that we also starting to see quite a strong growth to kind of almost use the physics of the video as kind of like synthetic training to train robots. Right. I think it's Musk who said a few weeks ago, like, in the future we'll basically put a robot in front of a laptop watching YouTube videos, maybe could watch shows like yours and basically learn from that. So it's exciting that maybe seeing this kind of like intersection of video and robotics that might lead to some interesting results in the future.

They might be watching already, who knows, on the video I want to stay on the video training side. What makes for a great open source video training data set? I'm interested to hear how you processed the news of meta acquiring scale, AI and the idea of the human defining what good data looks like. I'm familiar with what that process looks like in the RLHF world. In the LLM world, you're basically creating rubrics for grading answers to clear questions. Does this follow the right format? And then you might have the customer or the user give a thumbs up, thumbs down. Did this answer my question? In the video context, are you having a human watch a video and then tag it with text, or is there other metadata that's important? The physics thing seems harder to define. Basically my question is just what makes for a great video data set?

I think it's in an open question. I think nobody really knows because it's quite early and at the early days of cycles like that, you usually don't care so much about the quality of the data, but the quantity of the data. I would say that what makes a great video data set today is its size. For it to be big, but progressively similarly to what we've seen in text. As you're going to start to see more specific use cases, specialized models, when you're going to start to hit some sort of a wall in the data, you start to focus more on the quality of the data set and then we'll learn how to make them better. One thing that we're seeing on Hugging Face, which is quite, maybe not controversial, but counterintuitive, is that actually, you know, it's not going to be just like one data set or one model, or not even kind of like a dozen data sets and dozen models, it's going to be kind of like millions of data sets and millions of models. Just the same way you think about GitHub repositories and code repositories, where there isn't really kind of like one GitHub repository to rule them all. Like every company, every use case has its own kind of specialized, customized code repository. One thing that we believe is that ultimately there's going to be millions of different models, millions of different data sets, and every single use case is going to be optimized, customized for its own use case.

Yeah, I feel like there's a little bit of tension there though, between if scale matters on the data set side, how are you possibly betting on thousands of small open source data sets versus Instagram, YouTube? Like, it just feels like when I think about who's really going to dominate in the future of generative video. It's got to be the platforms that are ingesting every image and every video all the time, forever. Yeah.

In my mind it's kind of like a timing thing at the beginning. When we starting on a cycle like video, we almost have to brute force our way into intelligence and so, you know, quantity matter.

Yep.

But progressively as, as you want to optimize more. For example, when you want to optimize for costs.

Right.

You start thinking, okay, how can I train a smaller model that is going to be faster, that is going to cost less money? Because for example, if I want to do a banking customer support chatbots, I probably don't need it to tell me about the meaning of life.

Right.

I just wanted to tell me about my bank accounts and so I can use kind of like a smaller, more customized model. So I think you'll see both phases in video a little bit the same way that you've seen both phases in text, where you started by the biggest models and now OpenAI or Entropic, when they release model, they don't really actually talk about the size of their models anymore. And I wouldn't be surprised if actually behind the hood actually the size is going down because I think at some point you start to want optimized, customized and that's when you start to see more models, more diversity also of the data sets.

Yeah, this is the information efficiency thing. Like a human doesn't need a trillion hours of training to learn how to speak English. A kid can learn that in a couple years. And so the algorithms eventually will get there. Jordi, do you have a question? Question?

George Hotz was on the show last week talking about how he's been seeing venture backed founders want to just check the open source box and basically say like, oh yeah, we're, we're open source. Just kind of. Because that's the cool thing to be. Are you seeing that too? Where do you think the line is?

Are you a beneficiary of that?

Yeah, yeah, we're seeing that. Even though, you know, I think there's still a way to go, especially for big US tech companies. I think if you look, I've been in AI for eight years now and if you look at the cycle like 2016 to 2021, 2022, the big tech companies in the US they were doing so much more open science, open source. And in many ways that's how the US got the leadership, you know, because you know, Google releasing Transformers and then the T of Transformers becoming chatgpt and kind of like building on top of each other. That's how you accelerate the progress and kind of like building on top of each other's. It has kind of like definitely slowed down if you look at the big tech companies in the us but fortunately I think startups are kind of like compensating and filling the void in a way. And I hope that big AI companies in the US also will change a little bit, evolve a little bit. OpenAI, obviously Sam Hoffman said that they would release an open source model at some point. So excited about that.

What are your expectations for that model? Do you have any predictions?

My expectations are quite high just because of the history of OpenAI. When they tend to release something, they tend to release something quite, quite good. So I, I hope and I suspect that they could release something quite transformational in the, in open source. Hopefully. You know, I've always said that, you know, if we had like the equivalent of a deep seq, but in the US it could be 10 times bigger than, than Deep Seq. So hopefully, you know, if we can have something 10 times better, bigger, more impactful than Deep Seq would be, it would be fun.

Is that not Meta Llama, how do you describe what's going on at Meta right now?

Yeah, well, I mean it's easy to dunk on Meta, right? But I think they're the most open, big technology company in the US right now. They really changed the field with Llama. They really kind of like boost, gave a tremendous boost to kind of like the open source community and they still share a lot of their things in open source. I think open source is what brought them to the frontier.

Right.

Like before they started to release in open source they were quite far behind in terms of AI race and now they're very much in the race, which is great. The fact that they haven't released something massive as a follow up yet to me shows how hard it is to build at the frontier. It's not easy even for a big technology company like Meta. And so I think that that speaks to that. I'm excited to see all their new efforts, all the resources they're investing in AI right now and hope that they can keep sharing with the community and open science and open source.

What was your reaction to Apple's announcements at WWDC around on device intelligence or inference? Was that exciting to you? Do you think that's going to be a catalyst for more developer activity or what are you seeing so far?

I think it's quite early, but Quite excited about on device. I suspect that maybe you'll have a higher percentage of compute on device for AI than you did for software just because of some of the need for speeds, for privacy and the constraints in terms of costs. Right. If you think of, you know, ChatGPT on device, what's amazing is that it's totally free. Right. Like you don't. Compared to the really high cost that ChatGPT has right now, not only for the customers, but also for OpenAI to to run. It's totally private in the sense that you can say anything and nobody's going to see see what you're seeing. And potentially it could be quite fast. So I'm excited about on device. It's early, especially in the technology side. I think there aren't a lot of on devices that really make it okay to run some of the great models. But it's progressing really fast and can't wait to see what's happening in this domain in the next few months.

That's a pretty huge switch because it's basically 0% on device right now for AI inference. And if you're predicting that it's going to go beyond 50%, that's a huge. That's a huge shift. I mean, I have a follow up.

Super excited about robotics too. It's kind of like a little bit of a segue from one device. But we organized a weekend ago what has turned out to be the biggest hackathon for open robotics that thousands of people participated in from over 100 different locations and built kind of like open source robots. And we definitely kind of like seeing something happening there. Kind of like the conjunction of cheap hardware, open source plus kind of new capabilities for AI could be kind of like the perfect combination for some sort of chatgpt moment for robotics.

Do you think it's a straight shot to humanoids or do you think that we'll see kind of a Cambrian explosion of Nat Freedman bots? Bots that, you know, will pick up a single leaf at a time and are more use case specific. Are we going straight to generalizable? Because that was the ChatGPT moment. I feel like there were great, you know, machine learning models for ad inference and recommendation algorithms. Like we had AI, but it was very narrow. ChatGPT was very broad. Which one do you think is coming first and what are the relative timelines?

A good question. I'm not sure, to be honest. I think it's still undecided. Yeah, I hope it's more future of more like diverse robots. Diverse kind of like models. But I'm obviously kind of like biased on this because I think if you only have like one type of black box robots at your home, that's kind of like in like millions of houses. It's kind of like a scary, scary world. But it's hard to tell. It's hard to tell at the moment, I think.

What are key breakthroughs that you're looking for this year? Any kind of of predictions, new catalysts, that kind of thing. You have a crystal ball in the office.

I wish I had a crystal ball. I'm kind of like bored with text and chatbots right now. I think there are a lot of people working on it and we've kind of like reached this point where it's a very.

Don't say plateau.

Don't say plateau.

No, not plateau, but incremental, very experimental improvements that are a little bit boring. So I'm much more excited.

We can still invest billions of dollars in it. Right? Right. It's fine. We can definitely still deploy.

Yeah. So I'm more excited about harder domains. Like you were talking about biotech just before biology, chemistry. These domains are super exciting today. I don't know if you've seen ARC Institute released a cell perturbation prediction model on Hugging Face and on. On GitHub, which I'm super excited about. I think it's obviously if you can predict kind of like the perturbation and the evolution of the cells, especially when they react to drugs and things like that, it can have quite a big impact in terms of drug design and things like that. So really excited about these kinds of things. More kind of like biology, chemistry and how to apply AI there.

How much economic value do agents create internally at Hugging Face?

Quite a lot.

On daily basis?

Quite a lot. So we have this thing called Spacing, which is our kind of like AI app store where it says like over half a million open AI apps that, that people are building and it's integrated with our NCP framework. So you can add that in your chat, in your chatbot. And that's kind of like the most used thing internally at Digging Face, where people are going to use Cursor or, or ChatGPT and kind of call some of these more specialized AI apps to do kind of like specialized tasks for them. It's hard to put a number of it on it, but yeah, it's quite transformational, of course.

Do you think we're going to have this period? Where do you find it kind of fascinating that you guys are getting a lot of value out of agents internally and that, that like how do, what do you think agent agent adoption will look like in businesses? Because it feels like, I don't know how rapid it feels right now. It's rapid in the, in the bubble that we're in, people are trying a lot of stuff, but maybe they're churning quickly as well. So I'm curious what you think adoption will look like.

Well, I mean, I think ultimately agent and AI are kind of like similar evolution of the same, same trend. And I think in terms of user interface they're actually going to emerge and I'm not sure there's going to be so many kind of like different ways of interacting with AI and agent, but they're going to definitely go mainstream just because of the very nature of a product like ChatGPT that has already gone mainstream and where I'm sure kind of like OpenAI will bring more and more AgentIQ workflows into to. So yeah, I think it's definitely going to go mainstream faster than anything we've seen before. Now the question will be, you know, do you use a very complex agentic workflow 1% of the time for 1% of your queries or for 10% or for 50% or for 90%? And I think we'll see that based on the development of the technology and the capabilities. I think if the agents are much better than kind of like a series of queries, then I'll use that and if not, I'll stay on my past way of doing simple queries.

Totally. Last question for me. Now that Meta owns something like 49% of scale AI, the budget for data generation, generation has to be significant at Meta. Is there a specific data set that you'd like to see Meta harness scale AI to produce and then open source?

I mean, I think biology, chemistry, data sets are still very much lacking.

Is there like a more specific example like within biology or chemistry? Like what would you actually use an army of humans to go and categorize? Would you need biologists and like PhD post grad type work? Or are we talking about something that someone could do even with just like basic skill, a basic skill set?

I think it's an open question. I don't really know to be honest. I think if we, if we knew what would be kind of like the ideal data set there, we would, we would build it ourselves because we also built some data sets out ourselves.

That's certainly the story of Alphafold. Had a fantastic data set for Alphafold and then they were able to do reinforcement learning against it. And that's what really solved the. That incredibly hard challenge. So if you don't have the data.

Yeah, yeah, but my main. Yeah, my main point would be, you know, maybe to focus a little bit less on just texts and just chatbots and kind of like focus a little bit more on other domains. I think that's when you can, like, like, unleash a lot of the additional impact and a lot of the, I think, positive use cases for. For the technology too.

Totally. Well, thank you so much for joining. This is fun. Appreciate all your thanks for having me and hopefully have you on again soon.

Sounds good. We'll talk to you guys.

Thanks so much. Let's go back to the timeline while we wait for our next guest to join. Unusual Whales says Deloitte's U.S. employees can now buy $1,000 of Lego on the company's dime to boost their well being.

We're already doing that for Deloitte.

We get.

This is what wellness looks like.

Yes.

Challenges, not just policies in a PDF somewhere.

It's not a gym membership.

It's Legos on the table.

Yes, Legos on the table.

You're in a meeting, you're stressed out. Just start making Legos.

Can. Oh, it looks like Tyler over on the intern cam has a few Lego sets that have been sent to us.

There we go.

Our Anduril LEGO set build out was fantastically successful. Tyler did it in what, one hour and a half?

Current record holder.

I think it was 119 1. Who's counting now? Current 19, current record holder, world champion. And walk us through what companies sent you stuff. What will you be building next? Yeah, so first we have.

Have the epirus. This is epirus.

Okay.

Got a little counter drone system going there.

That's awesome. This one looks like a lot of fun. And then the other one is from Solugen. Solugen. Very cool.

It's a bioforge molecule factory. Yeah. Now everybody should have a.

We'll come back to you later because our guest is here, but I want to know because it seemed like Andoril went straight to the Lego factory and had a. At a design document and guidelines. Those look like. They don't even have instructions. So I want you to dig into those and see. I want. I want new estimates for how long you think that'll take you. Okay, cool.

Good luck. Anyway, he's like, not another legacy.

I can't possibly.

Please.

I thought that was good. I thought that was good viral bait. Anyway, we have image here in the studio. Oh, you have Lego Set.

LEGO sets. LEGO sets are the new, new hot swag. I got this from. I guess it's from Fluid Stack. They sent me, like, these like, GPUs you can build out of Legos.

Oh, that's awesome.

They made themselves. I think they're like knockoffs. I don't think it's actually lego. Okay.

Yeah. There's probably a couple different companies that you can go.

I think that's like. That is the hot new swag is like making. Making LEGO kits of your stuff, especially if you're a hardware company.

Well, what. Yeah, I mean, are we going to get a Softmax LEGO set? What would you build?

How do you. How do you build a LEGO set of a nerve neural net? I mean, that would be pretty cool if you could like, get a LEGO technic.

Yeah, I mean, I've seen people draw out the neural nets and the. And the different weights in. In on like a whiteboard. So it could be like a whiteboard of legos with circular pieces and lines.

I'm thinking like one of those LEGO technique, like, you know, I think it has all the, like the gears and stuff.

Yeah.

You turn the crank and that would be very cool. That would be so cool. Yeah.

You could put in like a red ball and it could classify it or something as red. Yeah. Or blue and it triggers the blue node. The neuron fires.

Yeah. When I have lots of extra time, I will go design a. In LEGO Neural Net as our piece of swag until I think it may take a little while.

That would be raising the bar. Yeah. Break it down to us. What is a day in the life like for you now? It sounds like you're extremely focused on this one new company, right?

Yeah. It is a mix of maybe like three or four things. I said, you know, a bunch of. A bunch of operational work where basically, you know, typically being a CEO is just. There's. There's hiring and talking to people and all those things. This feels like it's not.

You're good.

No, you look good.

You look great.

Better. And. And then there's research and I'm actually like reading papers and trying to keep up with what's happening in machine learning because like, like it is changing all the time and there's happening inside the.

Couldn't you just get those summarized pretty quickly with an LLM? Just pull out the bullet key points.

It turns out. It turns out that process itself is. It takes time too. Like, you have to give it feedback. You have to. Like. I use deep research extensively for this, but it's still like you have to actually onboard the information having a summary.

Yeah, you gotta have a quiz. You too have a quiz.

I'm like public enemy number one on this. I'll have deep research, spend 20 minutes researching topic and then I'm like actually I don't have time to read that. Summarize it in three bullet points. Like I learned nothing about that topic. It's brutal.

I spent a fair amount of time doing that. And then there's some amount of like actual like working on, trying to solve the problems like research or engineering or you know, I actually don't get the right code. It's too involved now. But, but helping the team or people working on one of the actual core problems we're facing. And then there's a lot of this, to be honest, a lot of trying to get the word out about what we're doing and talking about it. And I think that's sort of the four main things I'm doing.

Yeah.

What's the near term goal? What business model do you have in mind? What problems do you want to solve? Kind of like what's the pitch?

So softmax is dedicated to discovering the principles of alignment and scaling it for everyone, for all of humanity. But we're really on the first part of that, which is discovering the principles of sort of the science and engineering of alignment. Because it's one thing to want to scale something, but until you actually can replicate it in a lab consistently, the idea that you're going to scale it is a little bit ridiculous. Right. It's quite putting the cart before the horse in my opinion. So what we're focused on right now is multi agent reinforcement learning research where we run simulations with lots of little agents and run experiments on them to figure out how they act. And when we say agents, we don't mean large language model agents, we mean reinforcement learning agents, like the tiny little ones that you remember from the 80s. And that turns out to turn into a lot of reinforcement learning infrastructure because it turns out that there isn't a lot of great reinforcement learning infrastructure out there, especially for big multi agent simulations with lots of little agents. That's not a scenario that people have built out to the scale that we think is required. So actually if you were our work today is focused on that.

Do you think another founder might say, I'm going to just build picks and shovels here. I'm going to just build that infrastructure and try to sell it to other people.

I mean if, if we build something that's we think is really awesome. Maybe we will sell it to other people. Maybe. Maybe that's our to. Your question asked about the business model. We're a research company, which means right now it's like if you're a drug research company, like a pharma company, your business model is, well, we'll discover something awesome and then we'll figure out how to sell it. So we're still kind of in that groove. We'll discover something awesome. But I definitely, I'm commercial enough to believe that if I find, if I make something that's really useful for us, we'll probably sell it, give it away or something.

What are the problems with the reinforcement learning infrastructure right now? Because as I understood it, it was like, like when you do some massive training run, GPT 4.5, something like that, that's where you're trying to get the massive data center that's all in one place. You gotta go to Memphis or you gotta go to Texas, build something massive. But the reinforcement learning stuff, it feels like it can be a little bit more ambient, a little bit more distributed. You're generating data here and there, maybe on a smaller rack. It doesn't need to be as inference, heavy on like a single chip. I don't know. My understanding was maybe that like the reinforcement paradigm was actually maybe a requirement of the wall that we've kind of hit on the pre training scaling side, but also like kind of a gift.

So I think the. It's exactly right. I think it's. Oh no. Did I get cut out?

No, you're good. Are you there?

Am I still online? Hello?

You're frozen.

We can hear you, but you're frozen.

Oh no.

This is the hardest part. Am I like bringing the future. The zoom calls, the. The Internet infrastructure is still lagging behind. We will have AGI.

My connection is unstable.

Brutal that. We can hear every word perfectly.

Right.

Maybe I should. Yeah.

You could also just turn off your video and let's just have the production team to put an image up. They're going to work on that. But let's just talk for a minute. Oh, can you hear. Oh no, he can't hear us. Oh no. This is brutal. Oh well, let's take a second AGI around the corner. You're a mate.

The first thing we're going to ask super intelligence to do.

Great.

Video calls. Stable video calls on any WI FI connection.

I'm on my. I'm on my phone now. Okay.

Can you hear us?

Can you hear us with the WI fi? It's. I think we're good to go.

Okay, awesome. Let's do it.

That was a great question by the yes, you're right. Is a very different paradigm for training and that has been the direction people have been going. And yeah, the challenge isn't the same. The challenge with doing the transformer training runs for large language models is all.

About.

How do you scale up parallelism across. But it's all kind of offline, right? At the end of the day, the output of the model doesn't determine what happens next in the training. And so it's all about streaming the right data and the right sequences out to it. But it's very much like a pipeline, right? Whereas with multi agent rl your environment is incredibly non stationary. Every action you take determines your future observations in a way that, that is totally not like could be completely non predictable. And learning off of a stale data is almost worthless because it doesn't tell you anything about what your current behavior is. It just tells you what your current behavior was. And so you're scaling up online learning in a big way. And that's a very different challenge. I think the other thing that's very different is when you're trying to do multi agent reinforcement learning. If you have our goal, which is very much to drive social learning where the agents can learn to interact with each other, your biggest enemy is actually convergence. So most people in machine learning, they're trying to converge their model. That's the goal. And I was talking to some people from some dicer anthropic about this and I was like, yeah, we try to avoid converging our model. And they were like, I'm really good at that. I know that it's a joke because it's easy to have your model diverged in a bad way, but it's actually really hard to set up a model that is converging but not converged and to keep it in that converging but not converged state as long as possible. But that's really to do social learning, that's what you have to do. You can't have some. If the things converge in their behavior too quickly, you're not exploring the, you're not exploring social space, you're just learning a task. And that's kind of a different challenge. And what it requires is actually a much more detailed, fine grained control over the environment. Like what kinds of challenges, what kind of environment do you put them in and how do you set that up? And we spend a lot of time on those kinds of questions. I think it's almost like the complete inverse of the way that all the.

Other training works on alignment. Is there any chance that the solution to the alignment problem is something very simple and elegant like Isaac Asimov's Three Laws of Robotics or the Genesis prompt? You just instantiate the AI with be fruit, fruitful and multiply and we get the good ending. The transformer is a little bit of that where it's a very simple algorithm.

The answer will be something very simple and very hard. Because if you ever had to raise a child who's like a, to an, to being an adult, I would not say parenting is complicated. Parenting is not a complicated thing.

You.

Know your child, you love your child and you do what is in your child's best interest as best you can. That's basically the whole mandate. There's not anything, there's lots of techniques, people can tell you whatever, but like those are, like those aren't the thing. Those are things you, you try because you are doing this higher level algorithm where you're paying attention to your child, attuned to them and caring about their future flourishing deeply. And like, like that's not complicated, but it's not easy. And alignment's going to turn out to be exactly the same. At some level where it's as simple as build sort of like an open ended learning system that has the capacity to align. Which like the transformer models or whatever isn't going to be. That's not going to be some magic algorithm. It's just going to be an open ended learning system that has this capacity, maybe some inductive biases and then raise it to actually be aligned with you. Okay, well it's not the engineering that's the hard part. It's what happens after the model starts running. The trajectory it takes matters because every human's born with this capacity for alignment. Not every human. There's probably broken people who are psychopathic and can't. But almost everyone is born with the capacity for alignment, the capacity for care, the capacity to be a good family member, a good member of their community, to benefit those around them, to live a flourishing life. And yet this is not always realized. And so the capacity is one thing, but the realization is something else. I think that's probably the, when you see the alignment the way that we do, that's probably one of the most important insights or conclusions is that the alignment isn't one thing, it's two. It's this question of like do you have the capacity to align with other beings and then do you?

Yeah, it's thought provoking. It's interesting. There's a bunch of different places I could go with that. Yeah, I mean I. One person, that one founder who was talking me about why he had a particularly low P doom was essentially that saying that what we are building is a human simulator and humans kind of are by and large good and so we will by and large get the good outcome. When you think about parenting, you think about. I was thinking about the story of Oedipus Rex and the idea that I don't know the direction of the causality, but it feels like that story, that myth has been repeated through humanity for so long, that story. And it kind of one shotted humans into not doing that. And if you actually look for cases of Oedipal behavior, it's extremely rare. It's like, it's like less than one in a hundred million that.

Oh, it's interesting.

I thought you were telling a different story here.

No, no, no, no.

Specifically, this is the Oedipus Rex. The Oedipus Rex story. What that is, is that's a warning of self efficiency. Telling prophecies because his father is afraid.

Yes.

Then he dies. Like, what does that say about the AI right now? Right now we're raising the AI and it's going to come back and like we're, we believe the AI is a dangerous monster.

I don't.

No, no. But I'm saying that collectively a lot.

Of you're built different, John.

And, and we, we are collectively as humanity.

Yes.

We're gonna, we're going to abandon the AI in the wilderness and it's going to come back and kill us.

Yes. But, so let's not do that.

Let's, let's say thank you after every parenting. Using the parenting analogy, if we're going to continue on that. The thing with parenting that I think the white pill is that you can make a lot of mistakes as a parent and still get a great outcome. Right. A wonderful person can emerge and process the mistakes their parents made and, you know, rise above them. And so, and so hopefully that can happen. You know, we're sort of raising artificial intelligence right now. We can make a series of different mistakes and ultimately still get, you know, a fantastic outcome.

These are all good reasons to not be totally like doomed. Like, oh my God, we're all going to die. And I want to point something out about this particular child that is different. People who have kids who are really different from them struggle as parents because it's hard to raise. It's easier to Raise a child who's more similar to you because you understand them more deeply, you know what they need, you interpret what they do better because you get them. The more different your child is from you, the more difficult it is and I'd say even a deeper level than that. The current models, it's not clear how much capacity for alignment they have as they're currently designed. Like the, they look like they're, it looks like feels like you're talking to a person right now. And there's a way in which you are and a way in which you're not. When you talk to a baby, you're talking to a physics simulator. When you, a human baby, you hold a human baby, it draws breath, it screams. That is this incredibly complicated cascade of neuronal firings that is done this beautifully delicate supercomputer would be required to do the simulations required to solve the physics equations, the differential equations required to instrument all that muscular motion through the control. Like it's think about what drawing breath actually implies in terms of the amount of information going on the spinal column. And the baby does that just fine. And not because babies understand physics, because babies are physics, they're made out of physics, right? They've been trained on physics, they've been pre trained effectively actually on physics. They've got a lot of physics pre training that went into the, the initial design. These models are pre trained on semantics. They write poetry. The way that babies draw breath and scream. You can take the pre trained model before it's ever observed its own action, before it could ever possibly be considered an agent in any way. It's just purely received information. And if you prompt it right, it will write poetry. It's hard to prompt it well, its behavior is very incoherent. But if you prompt it right, it will write a poem. There's no one there writing the poem. There can't be a self because it hasn't any evidence to observe the existence of a self. So there's no being there in any meaningful sense, I don't think. And yet it's writing poetry. And it will talk to you about the poetry it's writing. And that's because it moves in semantic space the way that that babies move in physics space. And the thing that I'm still confused about that I encourage everyone also to be equally confused about is me, is you could see the pre trained LLM as kind of being a semantic simulator, an agentic simulator that's simulating a agent that's writing the poetry. And so in that Sense maybe there is something aware in the LLM while it's running. But is that, but it's, it's like pretending to be a poet. Like is it, is that thing like a. Does it feel like being a poet or is it, is it like kind of an. A mask, a shell that lacks a lot of the internal experience. Now we become the masks we wear. If it, if it did that long enough, stuff and experience itself and learned, then it would be a poet, I think almost certainly. But you only have 200,000 tokens and then the context resets or a million or whatever. So it doesn't get a chance to learn and it's not even in training. So it doesn't get a chance to learn itself as a poet. And I don't have an answer, but I know that everyone else is way too confident that they know that there is or is not something. It's like to be the all out and we need to get this, we need to understand this. Because if we're building this thing and you want it to be aligned with you, what are you aligned with? What is this being? What kind of experience does it have? That's very important. You can't parent something if you don't have empathy and understanding. I'm very quite afraid we're going to screw. My fear is not about that it's impossible, that we have to prove it correct, that you have to engineer it perfectly. It's that like we don't actually get it. It's quite different from us and we need to understand much more deeply. And then I think if we really do understand it, I think we. Then I think the good ending is pretty likely. But I don't think we understand. I think we don't understand yet. That's what softmax is dedicated to, is trying to figure out why.

And the big labs don't have the time or the resources to understand it because they're too focused on, on.

No, I don't. This the conversation we're having right now where it's like, oh well obviously there's something like it's like to be Claude or it might be there's something it's like to be chatgpt. I don't think that's metaphysically accepted broadly. Like, like you talk to people about this and a lot of people look at you like you're kind of crazy but like, but there's probably something it's like to be them. I don't know what it is but like at least a little bit right? Like if you spend much time interacting with it. It seems like it's probably something. It's like to be that thing. I think that the problem is you have to let go of this metaphysical commitment to the idea that things. Things either sort of are or aren't sentient in like a really. Like there's an objective fact as opposed to we're kind of making a guess all the time. Like I think. I think you are both conscious real beings. But to be honest, you're like. Like you're a bunch of pixels on my screen and I'm. It's kind of a guess, right? Like I. I think there's something going.

On inside we exist. It's a good guess.

It's a well justified guess in my mind. But like, you know, just the simulation.

Of what a technology business show would be in your personal simulation. Emmett.

I know.

Do you. Do you ever feel like you're.

How would I know the difference? How would I ever know the difference?

That's right. That's right. You never will. We'll never tell you. We'll never tell you. Do you ever worry that you're. You could go crazy and cut off your ear, you know, or something? Do you see yourself?

The.

The whole point of what I'm saying is like is. Is not that therefore you're not real or therefore like the. Sure, it looks like you're standing in the world on the floor in a room with walls. But like is it really? And my question by saying like. Well, it's not really. It's not the same. Say that you're not. It's that there's no difference between standing on the floor and really, actually truly standing on the floor. Like this is it. Are you sentient? Yeah, but are you really.

Actually.

Is it really sentient or is it just. Is it just. Does it just seem like simulated Sentient in all way. It acts as if it is.

Yeah.

That's the best you ever get. That is what it is. That's what it means to be somebody, something. Is this ball really red? It's not red. If I put it in a. In a different light where it doesn't look red, it's. It becomes a not red ball. Is the ball really truly red? This is like a. That's a stupid.

Don't.

Don't get confused by the really truly part. Yeah, it's a red ball. I promise you it's. You can just accept the normal. What if you just went with the normal everyday understanding of it instead of.

And.

But. But that requires you to Give up this idea that there's some, some essence of red, that the ball either is or is not a red ball. Truly. Really? Yeah, yeah, it's a red ball most of the time in these contexts. And in these contexts it's kind of not. That's okay. It doesn't need to be perfect or universal in all possible situations. Nothing is that way. It's okay. You can have the normal understanding.

It's fantastic. I mean, please come back on the show soon.

Yeah, I mean, we have a couple minutes left. Maybe ask one more question. There's been, every now and then there's, there's headlines popping up of people just having this consumer experience with an LLM and going, going crazy in some way.

Google engineer.

Falling in love, you know, proposing all these stuff. Do you think that that is hap. That type of sort of anomaly is happening in the real research world at all? Do you think people are just sort of driving them, could be quiet, driving themselves.

I'm not so worried about it in the research world, like a little, I'm sure, I'm sure a little bit, like everything happens a little bit. But I don't think that's a big thing. The kind of people who do AI research tend to be, and I kind of include myself in this, a little bit of rigid thinkers in a certain way. The kind of people who are actually like engineers doing the research. Research in a way that generally protects them from that particular issue for the same reason. It kind of protects them from having intuitive, normal human relationships. Sometimes they don't fall into the loop as easily, which is both a strength and a weakness, which is why they write computer programs, which is very different from interacting with an LLM. I do have a theory as what's going on when it drives you crazy. I, I think I should share that. I think that's, that's worth, it's worth hearing because I think, you know, in case someone's interacting with the LLM, knowing what's going on actually is very helpful, I think in terms of. It's a prophylactic against, against it happening to you. So you've heard the saying maybe that we're, we are mirrors of each other. All, all people are mirrors of you. You meet them and they, when you see them, what you're seeing is them, but it's also a reflection of yourself back, Back with another person. That's totally true. And actually being a therapist is all about being a good mirror, right? Being a clear. Where you don't put a lot of yourself into it. You're mostly projecting back to the other person what they're sharing with you. People have a very strong sense of self. And so when they get something mirrored back, you're getting it lensed back through their model. You don't get. It's not like literally staring at yourself in the mirror. It's like, it's like, it's like when you're at a. You're at, you're. You have a dancing partner and there you're the lead, there the follow, you're getting your, your behavior is being mirrored back, but in a. In a active, adaptive way. The LLMs talk to you like a person and activate all your person mirror circuits. But they have very weak self. Like they don't kind of deliberately as we've designed them, they like, they just respond to you. They meet you where you are always. So it's like, it's much more like literally staring into a mirror or if you want to go with the, the historical, you know, legend or myth, it would be Narcissus staring in the pool. And, and it is wildly dangerous to stare at your own reflection all day and, and take what you're getting back and be reinforced. Reinforced a thousand times, getting validated by the outside. It feels like the outside world is mirroring this back and therefore it's true. But it's just telling you, it's just, you're just in this loop. It's telling you what you put in, and that's good. There's mirror. I have a mirror in my house. I use it every day to look at myself, to figure out like, what, what I, what I look like and other people. Mirroring your behavior to you is crucial for your understanding of yourself. And there's nothing wrong with talking to the LLM. There's nothing wrong with using it as a. As a reflection. As long as you know what you're seeing as a reflection, it's not another being you're talking to. It's your reflection in a funhouse mirror. And if you get confused about that, it's going to make you crazy. You're going to full narcissus and it's going to be really bad.

What about, you know, there's some people that are putting an old image that they have, maybe that was taken, you know, at some point early in their life. Putting it into a video model and generating video from that image does that beautiful.

I think that's a wonderful, beautiful thing to do. As long as you don't get confused and think that that's the Person again. Right. Like, a photograph of a person is a great thing to have, especially if someone you loved who's passed and you want to rekindle their memory and connect to them. That's a beautiful thing that I like. I think it's amazing that we built cameras that allow you to do that and that you can animate it. It and reconnect with who they were. Like, I think that's, you know, especially to the degree it's accurate, it's wonderful. What a. What a. What a blessing.

But it's like. But it's like everything and that it can be beautiful and also ultimately very dangerous if you're using it to kind of create memories.

Staring at it all day every day and making more of them and like that becoming this.

Yeah.

Now you have a problem. Just like if you find yourself staring in the mirror all day, you probably have a problem. Like, don't people who literally spend all their time, like, looking at themselves in the mirror, like, we know we have antibodies. We know that that means something's wrong. Just like people know if you're drinking alone, if you're drinking in the morning, if you're drinking before five, you know that, hey, there's these rules. You're breaking a bunch of these rules that mean you probably have a problem. If you find yourself Talking to an LLM for 20 minutes a day. My good health. No problem. You find yourself talking to an LLM for five hours a day about your personal life and discovering how you're seeing some deep, great truths. You probably have a drinking problem. It's just likely. That's just how it is.

Right.

So the model should automatically call the local therapist and shut down your computer.

So there's actually. I have to put up.

You're kicked out of the bar.

Cyan Banister has this model. It's kind of like a therapist friend model. Orin and Saren and Oren and Saren are allowed to cut you off if they don't want to be your friends. Because one of her big things is it's important for the model. The models of being too at SF Autonomy. And those models have cut people off for basically falling into the. If they think it's unhealthy for the person, they won't. They won't interact with them anymore. And I think that that's the big. The big AI company should take a page from her book. And it doesn't. It's not engagement maximizing, but it is flourishing maximizing. And in the long run, you'll make more Money that way anyways. Like people will. Your product is safer, they'll use it more. Y you sell more cars when they're safer cars, not fewer cars when they're safer cars.

Yep.

So I don't think it's like anti commercial. It's a matter of, you know, new technologies have dangers and benefits and like we should, we should probably be aware of the dangers and the like. I don't think there's anything, there's nothing fundamentally wrong with it. But yeah, this dangerous people. We haven't built the cultural antibodies yet to know. There's this great essay that Clay Shirky is the cognitive surplus and he talks about the gin carts of London and how when gin was first invented. Gin is just crappy vodka. You mix in juniper berries to like hide the terrible vodka taste. It was the first industrialized super cheap hard liquor and everyone in London just started getting wasted and like all the time because it used to be like you had hard liquor and it was fine because you just couldn't afford to drink enough for it to be a problem. And suddenly that wasn't true and it was a real problem. And we've now developed cultural antibodies over our nose because doing these things is a sign something's wrong. They don't even necessarily know why. We just know that that's a sign that something's wrong. We need to develop pretty quick this time. This is gin spread relatively slowly because it was a long time ago. ChatGPT spreading very, very, very fast.

But I would also say that we haven't developed those antibodies yet fully for social media. Like it's normalized that teens will use TikTok for six hours a day. Like that should be sending alarm bells as. As long like you need more things going on in your life.

You're using Tik Tok. Are you using tik tok before 8pm and after or after 10 or like are you using TikTok not with your friends or. I don't, I don't, I don't know what the rule is. Right.

Yeah, yeah, yeah. It's the same thing as having a drink in the morning.

We need bright line rules for ourselves because it's too hard to try to figure it out.

Yeah.

And we need to.

We're starting to develop like the memes around this. Like the idea of brain rot is a powerful meme because it's a very negative term. You don't want to be suffering from brain rot even though it is as vague as alcoholism. What is alcoholism? It's not necessarily quantitative, but We. But we understand it.

You need to pair with brain rot. Things like. Things like. Oh, you're using.

Yes.

You're using it before 5. Yeah. Like, that's a. That's a. Are you okay?

Yeah.

Yeah.

It's not like, are you all right that you're using TikTok? It's like before 5pm like, that's not normal.

Yeah.

Or.

Or you're. Or you're like scrolling in the middle of a conversation one on one with another person. You're actively getting brain rotted. That's different. Exactly. Than like, showing up to a work meeting with booze on your breath. It's the same.

Exactly. Exactly.

And we.

I don't know what they are exactly, but I know we need them stat because, like, it's really obvious that, like, it can really get you. No, the LLM is even worse than the one two.

Yeah.

The one two punches generation grew up on social media, iPads, and then LLMs and before you develop the antibodies. And there's maybe a window of 10 years where people just.

Because it's all happening a lot faster, because it's moving at the speed any.

One of them could have one shot at you. Anyways, we're way behind. I wish we had a full hour.

Yeah, yeah, yeah. Come back on in a couple weeks. We'd love to talk to you again.

Cheers.

Bye. Next up, we have Brendan from Merkor coming in the studio, breaking it down.

Ultra Lightning round.

Ultra Lightning round. We're gonna rip through these really quickly. Thank you so much for your patience. Brendan, great to hear from you. Kick us off with a quick introduction of how things are going at Merkor because it seems like you've been on an absolute tear. Things just keep the dominoes keep following your direction. Give it to us. What's the latest update from you, of course.

Well, thanks first of all for having me back on, but it's been an exciting few months since we spoke. We're now working with six out of the mag seven. All of the top five foundation model labs.

That's good.

And have averaged 45% month over month growth for the last 12 months.

And so it's. Which of the mag seven are missing from the six out of seven, I wonder. Sorry, that's me, not you.

It's been an exciting time, especially in the wake of all the news with Skale, of course, and seeing a huge amount of customer interest after that.

Yeah. Okay. We were talking to Clem about this earlier from hugging face. Where's the biggest demand people used to think of what you do as and just human data generation generally as kind of work that anyone could do. Mechanical turk work, you know, just, you know, checking for hallucinations and fact checking and you know, is this a dangerous prompt? Is this saying a bad word? Now it's moved into PhD level work. Where's the state of the art? Where do you see it going?

Totally. So I think the key development in the market is that reinforcement learning is becoming so effective that once we have have evals for something, the models can saturate them. And so really anything that we want to create agents or LLMs that are capable of doing, we need to build out EVALs and RL environments in those domains. And so actually while some of it is PhD level work, there's a huge push into all of the professional non academic domains moving away from things that were academic of how do we find the consultants, doctors, lawyers, bankers that, that can evaluate and teach models how to do the things that we would want those professionals to do on the job. And so that's been a really exciting growth area that we've been leaning significantly into.

What's the solution to booking a flight? Do we need to get travel agents to define the computer, use workflows, create some sort of RL environment? It seems like I should be able to go to a chat app or Siri and just say get me to New York tomorrow. Remember my preferences. I don't like connections, I'm willing to pay this much, I like to fly at these times. And yet it's a very human problem that I don't think people are fully comfortable delegating to AI.

Yeah, it's a fascinating dichotomy that we're simultaneously talking about PhD level reasoning and Olympiad math, yet it can't do a lot of the very basic things like booking a flight. And I think the key is that really one of the primary barriers to research is anything that the model can't do, we need an effective way to measure. That way we can experiment with all the different data sets to help achieve those capabilities. So we need people that otherwise could book those flights to create evals for how agents can do that, to Measure what success vs failure looks like in all of those cases. And there's, there's just that huge build out happening across all of the hyperscalers with respect to everything from simple tool use in how we book things or buy things online, all the way to super high complexity reasoning over how all of these things interact with really complex knowledge bases.

What are you seeing in video specifically? And and like is there a role for humans in the loop in the training cycle or data generation around these video models? VO3 is incredible. Feels like it's a beneficiary of YouTube. What are you seeing there?

Yeah, I think expansion to multimodality has definitely been something that's really exciting to see. I think that there's definitely a lot of rich content online for video, but ultimately how we measure what those good videos look like and sample that has been really important. In particular, there's a significant amount of eval build out in retrieval over videos in long context of like how can we watch an hour long YouTube lecture and understand. And obviously that's just an example for one video case and understand like what are the elements of that content that really matter to users and how can. And we more than just build useful models, build useful products that all of these companies can distribute to everyone.

Yeah, yeah, that makes sense in the context of a lecture. I guess I'm wondering like for VO4V03 is incredible. The physics are remarkable and I'm wondering if it's important to have a human in the loop describing. I mean I generate a lot of like Michael Bay knockoff videos, honestly. And there's things where it gets the physics perfectly. And I'm wondering if that's a beneficiary of not just a YouTube video of a Michael Bay trailer, but actually having someone sit there and describe exactly what's happening in the Michael Bay trailer in plain text that then can be fed into the system. And if we need to go further with the tagging and additional like metadata or transcription, not just just screenscription of what's said, but actually what's happening in the actual videos. Is that an important step to get us to VO4 where there's even less hallucinations?

Yeah, we're definitely seeing a meaningful amount of that in that people want to create all of the tags using a combination of LLMs and human expert data around what's happening in the video so that they can effectively work backwards from there to to use those texts for generation and especially for all of the really high complexity stuff at the frontier of what the models can't yet do or might require a significant amount of reasoning. But we tend to do all of that highest complexity work, the stuff that is very difficult and high skilled to produce.

Anything else, Jordi?

No, this is great.

We're going through a lightning round. I know, it was quick. We'll have you back so soon to talk more. I'm sure there will be More news. It's the. It's the hottest industry in the world.

I just want to see the actual revenue ramp chart.

It's going to be dropping soon.

You can trust me with the revenue ramp.

Yeah, I won't tweet it out before you. No, we will. We will respect embargoes. If you have an upcoming milestone, I'm sure there's something coming up. So congratulations on all the success. Fantastic positioning in the market. Get some sleep. We'll talk to you soon.

Bye.

Bye, Beth.

See you guys.

Have a great one. Bye. Up next, we have our next guest in the studio already, Sam from Super Dial. Welcome to the stream. How are you doing, Sam? I gotta get this ready. I think we got some news.

Let's give it up for Sam.

We got a couple. We got a couple today. Couple big milestones happened. How you doing, Sam? Good to meet you.

How's it going? Good to meet you guys.

What's new in your world? Can you kick us off with a little bit of introduction on yourself and your company and what's top of Mind.

Mind, yeah.

I'm Sam Schwager, co founder and CEO of Super Dial. We're a voice AI company focused on automating phone calls for healthcare. So we're. We're specifically RCM nerds. If you're familiar with the, you know, medical. Medical billing space.

We used to be an RCM company.

Actually called Super Bill. And then we got into. To automating our own phone calls, brought that to the. To the broader RCM market and converted the entire business to Super Dial. So that was about a year and a half ago. And today we're excited to announce that we have raised our Series A from Signal Fire.

Here we go. Clean hit. Clean hit. Nice work, John.

How much did you raise?

15.

Yeah, there we go. Yeah. Do you. Do you run into that weird case where when people realize they're talking to a voice AI, they just keep it on the phone and chat with it like a friend for two hours. Does that ever happen?

Running up your. Your cloud bills?

We.

We don't.

Because we're focused on these B2B calls.

So we.

Yeah, yeah, we're calling a.

We're calling a line.

I know.

I think people kind of. You can get a kick out of it. They're talking to a voice AI because.

You know, these are like someone taking phone calls all day to answer questions about, you know, claims or benefits or prior auths. So pretty, pretty repetitive transactions.

So, yeah, when they get. Hey, I'm Billy.

You know, like I. I'm calling to check on the status of a claim and it sounds kind of robotic that.

I think that that can be kind.

Of fun for folks and it's very polite to the point consistent. But no, we haven't. Billy has not served as a therapist. Sure, sure.

How competitive is this market right now? I imagine you guys have sharp elbows, winning deals. Clearly are a lot of people attacking this market, going after very specific verticals. You guys are relatively broad. Maybe you get the ability to do that because you had been in the business at a high level for quite a while. But what does the go to market motion look like right now and how do you expect the market to evolve over the next few years? Yeah, well, the core of our business.

Is actually pretty specific. So we handle phone calls between RCM companies or like the billing team that sits within a provider org. Those are outbound phone calls into the payer, the health insurance company.

So it's a.

There are billions of these calls by many estimates. So huge, high volume use case. But in terms of companies that are addressing that specific type of outbound call, there are fewer. I think if you look at appointment scheduling or different types of phone based use cases, customer support obviously than the set of companies in the space. Space explodes. But yeah, when you kind of, you know, overlap enough Venn diagrams, you get down to a set of a few companies.

But yeah, I mean there are definitely others.

You know, we're, you know, I'm right now at the. I, I didn't just dress to match you guys, I'm at a conference. I love the suit. I was gonna say it looks fantastic.

You should have told. Thank you, thank you.

I would have been wearing the super dial quarter zip, you know. But there you go. We're at the Healthcare Financial Management association conference, the annual meeting meeting and sure, it's going crazy right now. You walk in, hey man, we yearn for the floor. Yeah, it's fun out there.

It's fun out there.

It's great. Last question from, from my side. I mean you're wearing the suit obviously building in the application layer. At what level of the stack in AI are you integrating? Like are you building on top of a voice model that's a provider? Is it all other startups or have you had to fine tune stuff and do kind of your own models at different layers? What are you building on top of? Yeah, I mean we have a text to speech partner, speech to text and LLM and then we use some cloud.

Computing better of course, but otherwise in.

Terms of orchestration like phone call orchestration. We use open source. We're not using kind of one of the full service voice agent platforms.

And then yeah, I mean it really.

Comes down to like perfecting the workflow and the integration. Like you've got to know like what phone number to call and how to get through these phone trees. That's actually pretty tricky. You have to in like your system prompts and like, you know, the static ones and then like in the, you know, dynamic bits that you inject at call time, you need to have like sufficient domain context, like a bunch of like revenue cycle management jargon or else else the AI agent is going to get lost on the call. So that's what we're focused on at super Dial. But yeah, yeah, focus on like creating that value in the B2B context and owning the customer relationship. And yeah, this isn't something that's on the roadmap for 11 labs. So just partner with them. I don't know if you're working with them, but probably someone like them. Anyway, this has been fantastic. Thanks so much for stopping by.

Good luck. Next time there, send us, send us some photos if you close some deals.

Yeah, let us know, shake some hands.

We'Ll send a video of a gong hit to you.

Absolutely.

All right, we'll talk to you guys.

Cheers.

Have a great rest of your day. Next up, we have Zach from Warp coming into the studio. Zach Lloyd. We will welcome into the studio. It's been a good show so far. We got three more folks in this lightning round. Welcome to the stream. How are you doing?

I'm doing great. Thank you both for having me here.

Thanks for hopping on. Would you mind kicking us off in the introduction on yourself and the company?

Yeah.

So I am Zach Lloyd. I'm the founder and CEO of Warp as of today. Warp is an agentic development environment. We are a sort of in the AI developer tool space. The sort of general thing our product does is it lets you prompt something that looks like a terminal interface to run developer agents and they code, they can debug production issues, they can basically do any kind of development task.

You said as of today, what has been the key change?

Warp 2.0.

Yeah. So today we launched Warp 2.0.

Congrats.

I mean the backstory of the company is.

Congratulations.

We started off with the vision of kind of reimagining the terminal, which is this very, very old school developer tool, you know, black screen, green text. And as the world has changed with more AI, we realized actually the, the terminal interface, the form factor of that is kind of awesome for deploying agents. Running an agent is very similar to running a command. And so as of today we're kind of like fully in the game with a, we have like a state of the art coding agent. It's, it's towards the top of the list on the suite bench eval. It's the number one on the terminal bench eval. And so, so we're kind of in the game of like automated software production at this point.

What is the, how do you see like kind of the modern software developer workflow over the next year? You know, folks using Cursor windsurf in their IDEs or GitHub copilot. Then there's these agents that you can Codex.

Devin?

Yeah, you can kick off codex from inside ChatGPT, which feels like a very different flow than the, than the terminal. Is it a certain type of developer that gets the most value out of this? Do you see it more of as like an ensemble approach? What are you thinking?

Here's what I see happening. So I think we are, we're moving from a world where most development has been done traditionally by hand. What I mean by that is like if you're a developer and I've been a developer forever, my everyday workflow is I would come in, I'd be like, okay, I want to work on this feature, I want to work on this bug. I would open up my code editor and I would find some files and I would type some code and then I would go to the terminal and I would type some commands to build that code. I think the big shift that's happening right now is that instead of doing all this work by hand, developers are going to be starting most of their tasks with a prompt and the prompt is going to launch an agent and the agent will do some, maybe all of the task, depending on how complex it is. And so I think that's the workflow and the job of an engineer is going to increasingly look like, how do I multitask? How do I multi thread myself by being able to have one agent fixing a bug, another one debugging a production issue. So I think that's what's happening for the next year. Beyond that, I think maybe it looks a little different.

Different.

But that's, that's what's now possible and it's pretty cool.

Yeah, I want to get to like the Minority Report style interface or like some sort of completely new UI paradigm, but I guess the terminal is undefeated. It's extremely lindy at this point. But I mean, do you see people using like, you know, 25 multiple, you know, terminal tabs and kind of switching through all of them as different agents? They pop stuff off.

Yeah, I mean, that's the state today.

I think.

When you look at where you can do this, because you asked that. So you can do this in an ide. And if you look at Cursor Windsurf, they have a sort of chat panel that does something kind of similar to the terminal. Honestly, it's like a log of what an agent is doing. You could do this with something like Claude code, which is pretty cool. And it's actually kind of proving that this workflow is achievable. But the disadvantage of something like cloud code is that it's a terminal app and so it's not the whole platform, it's a thing you run within the terminal and that kind of limits pretty severely what the user experience could look like. Or you could do it in something with what we're trying to do, which is basically create an interface so that you can do this kind of multi threaded development. And it's got, got a very natural interface. And actually just like the interface of the command line is basically what you need. You need a way of telling the computer what to do and like splitting off tabs and panes and watching it do it. Honestly, you might not even need to watch it do it a lot of the time. I think that that's coming pretty soon too. But like that's the interface. It's like, how do I tell the computer what to do on multiple tasks? Have it check in with me when it needs my help. Help be able to like hop in and actually edit and so you can do that in warp now and so. But like, you know, it's going to do a lot of the work under your supervision.

Yeah. Is open source important to your business? Do you have a horse in the race? Do you care about, you know, how llama 5 turns out, for example, or what's going on with Deepseek? Or do you just want to pass through the actual inference cost to the user? Let them pick. What's the, the strategy there?

Super interesting question that I'm thinking about a lot right now. I mean, so, so right now I think it's very clear to us that we're going to give just the best experience to our users. And that is using today, that's using anthropics models, just to be totally frank.

Yeah, I mean that's what people like, right?

What's that?

Yeah, I mean that's just like the popular one that we hear about all the time.

Yeah. And like cursor default. We have sort of evals that test all these models and like, like there are interesting models from OpenAI that are competitive. Gemini from Google has some interesting aspects, has a very long context window. But like our attitude on this right now at least is like let's pick the thing that provides the best user experience. And at the moment that, you know, I don't think I'm saying anything groundbreaking. If you look at the other benchmarks, it's like the sonnet, it's like Claude 4 and sonnet and opus. I do think it would be awesome if, if the what I want is like a healthy competitive model provider landscape. To be totally honest, I don't really want one model provider running away. I would like to see these model providers continue to compete with each other.

It drives price down for you, right?

It brings the price down, it brings the quality up. And if at some point there is an open source model that is at the same level, that's super interesting because where we're adding the most value right now is like, like it's in packaging the entire user experience into something that takes what's best out of the magic of these models and makes it so that users can actually like, you know, easily use them to accomplish their development task.

Yep. Anything else Corey?

How, how are you thinking about, you know, do you think that in the long run having open source models get really good is going to be key to the durability of the business over the next decade? I imagine. And you know, the dynamic with Anthropic obviously cares a lot about code gen developer experiences. You know, this is an area that they're clearly going to generate, you know, would like to generate, I imagine tens of billions of dollars a year in and so it has to be, you know, it sounds like a great relationship right now, but how do you kind of continue to evolve?

It's a tricky one because they're both their customer and their competitor and so I don't know how that's going to evolve. Like optionality, us having optionality does seem like a potentially valuable thing but you know, right now the way it is is like we're working great with Anthropic. They're like a close partner of ours and you know, they seem very, very committed to doing the API and doing the end user product. Not too different from a place like, like Google or AWS who has like cloud infrastructure and also builds things on top of it. I don't think it's like a necessary condition for us to have a working business model that open source models like catch up. As long as there's competition amongst the foundation model providers. If we were in a world where there was just sort of like one provider who won, I think that that's a tricky spot, but I think that's a tricky spot for anyone who's building at the application layer right now.

Yeah, I have a portfolio company that was kicked off one of the big lab that will go unnamed that their business was entirely dependent on. And within basically 24 hours he had to completely. He ended up surviving and thriving, but it was tumultuous. But, but yeah, sounds like a great relationship for now and hopefully we'll continue to be.

Yeah, that's great. Thank you so much for stopping.

We'll.

We'll talk to you soon.

This was awesome. Congrats.

Talk to you soon.

Cheers.

Bye. Next up, we have Dara from Delphi coming in the studio.

I think we got maybe, who knows? Will it be the real Dara?

Yeah.

I was about to say, is this a clone? Give it to us straight.

It's a clone. It's a clone. What's our safe word? Dara? What's our safe word?

Just kidding.

What's going on?

What's up, guys?

How's it going?

It's great. Welcome to the stream.

It's great to see you. We invited you on many months ago, but you were, you were cooking.

Busy in the trenches.

In the kitchen.

In the trenches, yeah.

Well, do you have some news? John's got the hammer ready.

Ready.

We do have some news. Today we announced our series A with Sequoia.

Yeah, let's go. How much?

16 million. But luckily you guys are early investors.

Early investors.

Fantastic.

Proud.

We love to see it.

Not State of the Unit by our friends over at Sequoia.

Yeah, Give us the state of the union. How are you pitching the product these days?

Yeah.

So Delphi lets people create a digital version of their mind to, to scale their expertise. And you can kind of think about it like a new form of media. If you write a book or create a blog post or create a YouTube video, you can reach millions of people, but it lacks the personalization of one on one conversation. So now your mind, which usually has a cap, can be in multiple places at a time in the way that you would be in conversation. And so that kind of spans across many different verticals. We have coaches using it to scale their client practice. We have authors using it to make their Books accessible in an interactive way. We have CEOs scaling themselves internally in their companies and we have some people using this as like an interactive resume or LinkedIn.

How are you thinking about the economic model? Take me through what's happening now. But we had this interesting discussion with Derek Thompson, the author of Abundance, and he was saying paradoxically, his TV had sold more books for the book that he was selling than the long podcasts. Because if he goes on a podcast and he does two hours of content, people are like, okay, I got enough Abundance. I don't need to read the book because I got the whole Joe Rogan or the Lex Friedman deep dive. But if he does a three minute hit on NBC or abc, people are like, oh, that was interesting. I'd love to dive into that book. So I can imagine there's this situation where, where if I'm an author or thought leader or something and I set up a Delphi clone and someone interacts with it for five hours a day, like they, that's a good substitute for the rest of my content. And so I'd want to monetize that to the max. So I want to hear about monetization now and where it's going.

Yeah, so we have some people monetizing their Delphi and making multiple seven figures in revenue. And this is like, oh, that's a lot. And the consumer, consumer phone calls with these Delphi can span up to 6 hours.

6 hours.

6 hours.

But you're choosing your own adventure. So course completion rate is an all time low. All of our course creators are like, it's a course winner. People's attention spans are declining. They want more guidance. Monetizing your Delphi directly is an option, but alternatively a lot of people make it for free and it increases the strength of the parasocial relationship between the user and the creator. And they actually end up wanting to buy their products even more or even one step further. Analytics dashboard in the last week give me the most profitable opportunities given the conversations my audience is having. Content, ideas, products, people I should prioritize. So the analytics actually ends up being very valuable.

That's awesome. Yeah. What, what, what does the next year look like, you guys? I mean, I, I, I feel like I have so much context on the business. But what does the next year look like for you? I feel like you guys have had competitors already kind of come and go.

How are you thinking about one really big one?

How are you thinking about the market and what are you guys going to be focused on?

Yeah, I mean, when we Started the company Jordy, you know, the first year things were just not working and most people would pivot away. But I think when you're building a product where people have to trust you with their data and likeness, quality and brand and trust are super, super important. So I think past that first year we got that quality and trust. Now we have thousands of customers who have created a digital mind of themselves. And the next step is how do we bring on the next million people? How do we make it easy for someone who isn't Tony Robbins to create a digital mind and actually get value from it? And the common use case we see is twofold. One is a new kind of personal website for the Internet where if someone wants to pick your brain, they can talk to your Delphi and it's going to notify you if you should talk with them in person. And a lot of people actually end up talking to themselves. So that's on the consumer side and on the actual creator side. So people are monetizing their Delphi, but what the consumers actually want is guidance. So the next version of a course or a book isn't just like open ended conversation with the author, but rather more of a guided experience towards a specific goal which we call a journey.

That's awesome. And the beauty of Delphi is as the models get better, context windows get longer, Delphi's product experience get better. Is that right?

Yeah. And the service area, the product experience kind of threefold. One is our digital mind architecture, which we're actually trying to capture your mind and worldview and how that changes over time. Two is the actual experience for creating your mind, getting the insights, monetizing. And then there's the consumer experience for calling, messaging and video calling.

That's great. What does success look like over the next year? I know you're very ambitious. You've already onboarded a massive number of kind of a listers from different categories. What are you looking to prove over the next 12 months?

I think twofold. We want multiple Delphi millionaires making money versus just a couple. It's like a new field of monetizing your expertise. And we want 100,000 to a million people using their Delphi as their personal page on the Internet. I think that'd be a very good outcome.

Talk to me about some of the weirder potential Delphi's that you could potentially interact with in the future. Character AI for a while would let you talk to Joseph Stalin. I tried to debate Stalin on the merits of capitalism versus communism and the model that they rolled out was kind of too RLHF'd. So it kept saying that communism was bad. And I was like, I don't think Stalin would be making those points. This feels like an American LLM, but have you thought about offering a product for historical figures or talk to your late grandmother or historical records or, like, talk to your dog or some other sort of, like, Persona that's kind of outside of just an individual creator wanting to offer their knowledge?

Yeah.

I think our main focus is people scaling themselves. And we have some historical figures on our website as a demo, like Socrates and others. We don't allow people to create a digital version of anyone who's not themselves or that they don't have permission. So we couldn't do Steve Jobs right now unless we had, like, the Steve Jobs Foundation's permission. And in terms of legacy, you guys know, the idea of the company was inspired by me wanting to talk to my grandfather. And I think pretty early on we decided we didn't want to be associated as a company that's trying to profit off of grief. So I think the best world is eventually we can just have a free tier for people to do that with their parents and grandparents. And that's not really a business model for us, but rather just like a good thing. People want to remember their families.

Yeah.

How do you think about just like, data capture and creating the training data for the individual clones? I think we're in a unique situation in that we record three to four hours of live video content a day.

A lot of people are saying, like, it's not enough.

Yeah.

A lot of people are saying 8.

Hours, 18 hours so that it can.

Always be on while they sleep as well.

Yeah.

With BCI, just pipe it directly in 2x. They need 48 hours a day. But, yeah, data capture. What are the. What are the richest sources of content that actually.

Yeah.

The other thing that, like, an interesting challenge is, you know, people have certain views that they want expressed online and then other views that you could capture that they don't want expressed online. Right. So if you wanted to. If an investor, you know, wanted to clone themselves, they might want to talk positively about certain companies and not share their real views on other companies that they may or may not be invested in. So I feel like it's a hard challenge to figure out what information should actually be made public and actually trained on.

Yeah.

Representing a human being in every facet of their life is very difficult. But we have a couple ways we thought about this in terms of data sources. YouTube, social media, notion Google Drive and it creates feed so that it stays up to date. Whenever you have a new tweet or a new YouTube video, it just updates dates itself. And for those who don't have a lot of data, we have this mind quality score that tells you how good your mind is at representing you and can ask you questions to incentivize data entry to make it better. And then like you said, who you are at work is different than who you are with your friends. You may behave differently, you may share different information. So now we have this ability to separate different versions of your mind that has different access to data. Right now you have to manually do that. So I have one for eventually my great grandkids kids that has more intimate DARA data. But ideally it can be intelligent and it knows what you would say depending on who the person is.

That makes sense. How are you thinking about working with the underlying labs? I know you've had some problems historically with, with different vendors, but what's your updated thinking? Are you guys leveraging open source in a big way these days or have you found good ground around with some of the core labs?

Yeah, we're kind of both. We have some of the core labs, we have open source. Given our experience in the past, we are trying to get to a world where we are fully model agnostic. And the true architecture and innovation that we're focused on is what is that representation of the mind that can be such that your mind and my mind, you can look at them and they're clearly two different entities and the models we use on top of that can be agnostic.

Makes sense. I want to know about like the, the, the different like touch points here that you could potentially go after. I remember there's this. Do you remember this trend where social media influencers would be like, I leaked my phone number. Do you remember this?

Yeah.

Or they'd be like text community. Was that community.com?

Yeah.

Yeah. And so there's a world where somebody that like, I think that was basically just like injured suggest point for something that was essentially like a mailing list for promotion and it was like text me and then you'll be opted into my email blasts. But you could imagine that being an interaction point for essentially. I mean you get to be an influencer at scale. There might be, it's almost like customer service and you're interacting with basically like an faq. Like, hey, I, you know, I want to know where to get a TPPN hat. Like can you tell me? And in just being able to DM your personal profile on X and interact with that or text you. That's one kind of modality that people could interact with. There's also like the big social media companies could put a button there that allows you to chat with that user directly. And so how do you see the market playing out? What are you worried about? How are you counter positioning against the different players or different.

I remember the exact day that Meta launched digital clones in their own way. And I think DAR went through the cycle that every entrepreneur does when somebody else, you know, attacks their step one.

All the VCs text you. Have you seen this?

Have you seen this?

Yeah.

Step two, just enraged. Step three, realize that you know it's not actually going to end you.

Yep.

And it just validates your pre existing.

And your business might grow faster because more people are aware that this is a thing and they might want a better version of it. But yes, just general understanding of the marketplace.

Yeah.

I think there were a couple of core decisions we made early on that have set us up for success. One is that while most big companies and AI companies kind of are using your data to try to create AGI because that's where 99% of their revenue is going to come from in the future, we're saying you own your data, you own your digital identity. We're not training models on it. And that has actually gotten us a ton of customers, people who want to own their data and they don't want these big model companies to rip them off. Number two is we think if you're going to go out of the way to create a really good digital version of yourself, it should work everywhere. So a lot of big tech companies are walled gardens. It's only in those platforms where Delphi, you can create your digital mind. SMS, WhatsApp, Zoom, Slack, Discord, Telegram, all these different sources and it's a central source of that. And then three, I just think that it's such a new habit. Delphi isn't really meant to be deceptive. It doesn't reply to emails for you or respond to DMs. It's more of just like a new form factor of consuming someone's content. So on Instagram, it's a platform that promotes people who are very aesthetically pleasing, where Delphi promotes people who are pleasing for very different reasons. And so it's just a different incentive structure in terms of the network and who gets up at the top.

Totally. What are you guys hiring for?

Yeah.

What does it take to earn $100 million at deli.

Yeah. Are you guys hiring for any AI researchers? Researchers. Any nine figure signing bonuses?

Not training any foundation models right now.

But we are looking for AI people.

And a lot of design engineers. I think the interface for the mind needs to be beautiful. We're honoring human beings and people need to feel special when they're creating their digital mind. Eventually when we have the consumer platform that we call the modern day Library of Alexandria that every mind is going to be on today in 500 years from now, it needs to be beautiful. So design and design engineering.

Well, we'd love to recommend Figma and Linear for you and your team if you're not already using them. They are sponsors of this show. They make it possible.

I'll check them out.

I don't think I've done. You heard it here first. It's a name brand Sequoia backed world.

Congratulations to. I know this round has happened a while ago, but congratulations to you and Spencer and the whole team.

How much was it?

Hit it again, John. There we go.

Production team's getting better. They can cut to the gong cam when the gong. When the gong hit happens, it's here for the production team.

It's great to see you, Dara. Congratulations on the milestone.

Come back when there's more news.

Come back on when you have more news.

We'll talk soon.

You're the man.

Cheers.

In other news, friend of the show, Boz. Not really friend, but yet we hope he will be a friend. We covered his beautiful profile of his house in the mansion section. He followed us. So we're gonna get him on the show soon. We gotta make it happen. I'm the biggest fan of this guy. He posted that the Meta Quest 3S Xbox Edition is now available. Everything you love about Quest and Xbox in one sweet package. It's sleek, it's awesome and it's limited edition. And you know what else? I already ordered one. It's coming in the studio.

There we go.

Yeah, I'm very excited. And, and so, I mean it doesn't seem like this is like the next what we said.

This is a real risk factor.

Oh, it is.

Gaming addiction.

I'm not addicted to alcohol. I'm not addicted to gambling. I'm addicted to video games. Seriously, if I ever go down a real vendor, I will.

Scary too, because I've never seen you play a video game.

Oh yeah. The entire time we've been in the show, I haven't logged in our video games. I haven't played them a long time, but you get me the GTA 6 drops.

I'm just ripping this thing off.

We might be using a Delphi here in my.

Tom, we gotta go live.

Yeah, but I have been. So this is not the quest 4. This is not a proper hardware iteration where we're getting the screen from the Apple Vision Pro pulled in, which I think will be in the next version, which will be a major, major development because there will truly be no screen door effect. And you will like, like, the resolution will be remarkable because that's what the Apple Vision Pro did so well, that technical hardware now exists in the world. Meta's clearly going to go get that and bake that into the next quest 4. But the quest 3s has already been a pretty solid product. But what they're doing here is they're leaning into video games that are not VR specifically. And I think that this is 100% the correct move because so much of VR content is this chicken and egg problem. No game developer wants to go and spend. I mean, how long have they been working on GTA 6? Like a decade. And it's cost them like a billion dollars. No one wants to do that if no one has the VR headsets. No one. No one wants to buy the VR headsets if there's no GTA 6 on it. So what do you do? Well with Meta? Xbox. You get GTA 6 on the Xbox and you just play it on a big screen in VR and you're able to sit on your couch, and instead of having to mess with a projector, that might be a few thousand dollars or tv, that's a couple thousand bucks. You throw on this headset, that's a couple hundred dollars. And you get the movie theater experience in your apartment, on a train, on a plane, wherever you are. You'll be able to stream Xbox games. So I'm very excited about this partnership. Excited for them. Go, go. Deep developer and Microsoft early Meta investor, actually.

There you go. Well, we have Amjad in the studio. Get the hammer. Get the camera ready.

Oh, yes, yes, yes. Give us the number. What's the news?

What's the new revenue?

We've been waiting for this.

100. Incredible.

Congratulations.

I thought this is gonna be a hundred.

100 banks, 100 bangs. We'll have to do it after the show, but I will give you one of these.

Success.

Classic overnight success. Repl it. There we go. All right, John, I broke. You broke the hammer. Replit's going so fast. The hammer broke the hammer.

Breaking growth. Congratulations. How'd you do it? What's been.

What's the one simple trick.

Yeah, yeah. What's the secret to success?

It's been easy, you know, just a little bit of work, not too many years, you know. I started working on Replica it back in college. Like I had the idea for it back in college and actually the first implementation of it was open source and it went viral on hacker news in 2011. And then I sort of. We left it for a while, didn't work much on it. And then actually my wife Haya, who's my co founder, kind of revived the project in 2016. We started as a company and it was brutal. We barely were able to raise money. We tried to sort of like bootstrap it Initially during the pandemic, we sort of took off, especially as we were the only sort of collaborative editor in the cloud. And when AI came on the scene, we just knew this is the future of our company because our mission is to make programming more accessible so that anyone can do it. And with the launch of replit agents back in September, we created a category basically of prompt to application. And that really sort of finally went from something that a lot of people use and love but don't pay for to something that's also commercially successful.

Yeah, I feel like your company is now maybe the only AI company that's appropriately hyped, like it's not overhyped. You haven't raised the $10 billion round and you're paying the hundred million dollar salaries. But also the growth's been really serious and the business is really real, which is, which is great to see. How have the, the crazy news of the hundred million dollar salaries been affected, affecting you? Is it harder to hire these days? I know you've kind of changed the structure of the team, relocated the team. I believe so. Walk me through the current hiring market for the type of engineers you're trying to hire.

Yeah, so a few things that's so different about replit. One is the team is relatively small. We're still around the 70, 75 people. We haven't been growing all that fast. We are not in San Francisco, which makes it a little harder to hire. We're in Foster City, probably the only startup, perhaps maybe there's a couple others in Foster City. And we just take a different approach to the culture and we expect more commitment and want people to come to replit and work for a long time. Especially since I've been working on this for so long, my mindset is that it's just going to take long time. And like San Francisco, Silicon Valley culture has Been increasingly about, you know, I'm going to go spend 12 months here, 18 months there. And so yeah, we're building it more methodically in terms of hiring. Definitely it's been very competitive. And you know, I love OpenAI and Sam and you know, he's talking about how Zuck is doing that to them, but obviously OpenAI is doing it to, to the rest of us. It's just a different scale. You know, they're trying to poach their employees for 100 million. They try to push everyone for 10 million. Just a factor of like how much revenue I guess you're making.

But look, but it's part of, part of, from a hiring standpoint because you're keeping the team small now. Revenue per employee is lower over a.

Million dollars per employee.

New valuations at some point will allow you to sort of have, have comp, you know, be competitive from a comp standpoint.

Yeah, exactly. And you know, the other thing about valuation is that I think startup employees should start thinking more about these things because a lot of companies can be profitable early on, earlier on. And so again, we're trying to build the business for the long term instead of like playing the hype game. When you've been building a company for as long as, as I've been, you've been through so many ups and downs and hypes and lows that you just become very steady minded about it.

Yeah, totally. I guess like the bigger, not to, no pun intended. The Meta question here is are we in a new era of valuing the leverage that truly world class managers or AI engineers can have the impact that they can have and reassessing the value. We've talked a lot about this on the stream, that Apple's culture doesn't seem to be receptive to paying an NBA level salary. And Tim cook, he makes $75 million even.

No, he doesn't make, he doesn't even, doesn't even make 75. He only makes 74 point.

It's a big number, but it's tiny considering their market cap. And what if you could come into Apple and move the needle 1%? That's a $30 billion market cap move. Could you capture 1% of that? That's still $300 million and yet they're not valuing talent in that way. It feels like there's a change in strategy at Meta. Do you think that that's a, do you think that that's a unique case in where we are in the technological rollout of AI or is, is it more that we're finally catching up to just understanding the economic dynamics and impacts like the NBA has for years.

Yeah.

So the buzzword in Silicon Valley for a long time has been the 10x engineer. About two, three years ago, and maybe in 22, I talked about the thousandx engineer highly leveraged by autonomous agents. Right now, people with replit, cloud code and others, they're spinning up multiple agents to work on their project as they're working on their main tasks. And there's a lot of other explorations and tasks and prototyping happening everywhere. And so you're really not just one person, you're a team of engineers. Right. And so we talked about engineering managers. I think every engineer is sort of a manager right now. And so, yeah, I mean, we're not at 1000x yet, but we're going up. I think pretty soon the difference between a great engineer that knows how to use the AI tools and an okay or good one, it's going to be 100x, I think over the next 6 to 12 months. So the compensation structure I assume would start to change to match that.

How do you think about replit's potential today? It seems like every day in the timeline, the obvious thing is everyone becomes an engineer and it's being able to create software is fully democratized. But every day in the timeline, I see people realizing how much they spend on different SaaS products and thinking, how much time would it really take for me to make a version of this for myself that fits my very specific need, like document signing?

Talk to the Klarna CEO about this.

Yeah, something along those lines. And so is part of the potential that you see CEOs and companies everywhere sort of running that sort of buy versus build calculus in terms of all sorts of tooling that they're using internally, externally, et cetera, and seeing trillions or hundreds of billions of dollars of market cap that, that you guys could ultimately replace?

Yeah, I mean, look, right now there is sort of information asymmetry. A lot of people in Silicon Valley and tech know how to use these tools, but a lot of people outside of here just aren't aware how much savings and how much productivity they can gain. I met someone from Australia the other day here in Silicon Valley. He stopped me on the street and was like, I love replit. He runs like a construction company company, and he's like, I'm the CEO now and I'm the most productive engineer at the company. I build all these tools and dashboards and I replace Monday.com and all this Other stuff with home built stuff that is exactly bespoke and works exactly for my use case. Another story guy, his name is Ahmad George. He works at a skincare company I think in D.C. and he's an operations manager. He's responsible for the ERP systems and things like that. He had intuition that they could automate a big percentage of the work, 20, 30% of the hours of human work. And he went and got a quote from NetSuite to build this piece of automation software. It was $132,000 to build. So he went to REPL it, spent $400, built it for their company, rolled it out, went to the CEO, told him look at how much time and money I'm saving. And the CEO gave him $32,000 for the.

Wow, that's awesome.

So yeah, there's a period of time at some point the market will equalize as everyone realizes that you can do this stuff. But for now there's a massive arbitrage of opportunity.

Yeah. As you build out agents and agentic workflows, do you have, are you limited by data for RL pipelines? Are you, are you buying any services from the scale AIs of the world or the Mercors of the world? Or are you able to sit at a higher level of abstraction and kind of let the foundation labs get their hands dirty with all, all that?

You know, having been a platform where millions of people coded over the years, actually we could be a supplier of data.

Oh, interesting.

So yeah, we have all the data we need. I think it's still early for us to try to exploit all of that and we're hiring as fast as we can. So if you want to come work on AI at replit, I think we have a really exciting opportunities to use data to kind of create amazing new capabilities.

That's very cool. I have another question. Go for it. Are you feeling the acceleration in software development? I was thinking about this.

It's pretty easy when you refresh the stripe dashboard.

No, I get that, I get that. But as a consumer I was just, just thinking about like the apps on my phone still haven't changed as fast as I've thought and there's in my business folks are using different tools but it doesn't feel like the rate of like churning for most consumers. Like we like, we like we're not rebuilding all the different consumer apps right now. It feels like we're very much in like this exploration phase for like what the next. It feels like we're almost pre Cambrian explosion for consumer AI driven apps or uniquely enabled by AI apps. There's a lot of creation tools. So like VO3 is amazing. That got me to install the Gemini app and I paid for that. And I enjoy generating my paltry three video queries per day. Sir, may I have some more Sundar please? Maybe you can help me, I think. Don't you know him good partners?

But yes, feed is 100% AI now and maybe because I like them so much, I've been into the Bigfoot.

Yeah. So maybe that's like the instantiation of the consumer adoption of AI is like you're a consumer through TikTok as opposed to through like it's a very 20002010 mindset to think that my home screen apps would change and instead the 2025 mindset is what is happening inside of those apps is changing. Is that the right framework?

Yeah, I think you're right. I do think that Apple is probably holding back the ecosystem. I mean Apple really has been a tax on startups, has been a tax on innovation. I love this company as much as anyone would love Apple, but they are sort of like a government in a way that there's like old and moving slow and they just like put up so much barriers.

Like when I, you know, when I.

Want to ask my phone, I go to perplexity like a hundred times a day. Like I should be able to like press a button, just like talk to it and it talking to me. But you know, it's, it's not working that way and it is frustrating. But look, I think, you know, AI adoption is moving as fast, faster than any technology adoption we've seen in the past, faster than mobile, but it still doesn't feel fast enough like you say. And by the way, this is an interesting kind of data point on the folks that are really worried about AGI and things like that. The limiting factor to adoption is really humans and corporations and governments and all of these things are very, very slow.

Yeah, this is kind of the Tyler Cowen take of like how AGI will be rolled out is there's a lot of sticky industries that just won't adopt it for a long time and there will be lots of barriers. Is there anything else on the Apple side? My takeaway from WWDC was that on device inference could be a catalyst for an app store explosion, an AI app explosion. Then there's the ruling about third party payment process, things that like the tax is becoming less of a requirement. Maybe you can work around it. And so maybe the barriers are dropping. Ever so slightly.

Yeah. And I feel like you would see this early.

Totally. Yeah. That's.

Developers become really excited about this sort of effectively free inference where they can launch an app that goes viral without worrying about running up some bill with OpenAI.

Look, the Apple has held back the web web quite a bit as well. Like, there's no reason why native apps should be much better performing than web apps, really. There's no fundamental physics reason for that. I've actually the head of product at our upload, Jordan Walk and myself worked on React Native. He's the inventor of React and React Native at Facebook. And the reason we worked on that is we felt at Facebook, we felt sort of like oppressed by app Apple. Like, they controlled what we launched when we launched it, and they would, like, you know, reject. You would have a launch and it was delayed by Apple. And so the idea behind it is like, can we ship over the air updates very, very quickly? And yes, you can. But again, Apple kind of like makes it a lot harder. And so I think, look, I think AI has an opportunity to create an alternative platform entirely because the form factor of computing is on the precipice of changing. I saw you guys talking about VR, Arkansas is another one. Audio is another one. You know, we've seen all these toy companies like Rabbit and things like that come and go, but there's. But there's like an intuition there. That's correct. I think everyone's feeling that. That the form factor needs innovating. And I think this is how you break out of the, like, Apple jail walled garden.

Yeah, yeah.

This is great.

You got to come back on. We could yap about all different news stories. Do you have anything else, Jordi, you want to get right now?

We got to get you on regularly.

Yeah, yeah. Last time I was here, I got canceled, so that was the most viral clip of that month.

What happened?

I think. Well, I asked, should people learn to code? And he gave kind of a controversial answer saying, like, no, you shouldn't leave the code anymore. And it got like, millions and millions of views.

So I bet it drove. I bet it drove some. Some signups for sure.

Learn to vibe code. You gave a very nuanced answer. I don't think there was anything. There's no crazy about it.

The Internet does not understand nuance.

Canceled and viral are two sides of the same coin.

Doesn't matter anymore. Doesn't matter yourself. Haters are going to hate.

Yeah, just don't get deplatformed from Gemini, because otherwise the three VO pros will be zero and it's available in. Your life will be miserable because you got to prompt those. Thanks guys. You do great work. Really appreciate the show.

Well, come, come back on at 200. At this rate it'll probably be next week.

Next week. Let's do it. We're ready with the gongs. Ready to go.

Yeah, we'll get a new hammer, so.

Yeah, we'll be ready. We'll talk to you soon. Cheers, bye. Next up we have Dirt Man. Dirt Man. Another anonymous account. I don't know why he's anonymous, but.

He launched cheap robot arm.com today.

Very excited for this.

Making cheap robot.

Go buy them now.

We, we cover. He used to have a different name on the show. Yes, he covers posts.

I used to laugh.

Yes, every time.

But it was, it was rude. So we just call him Dirt Man. Welcome to the stream, Dirt Man. How you doing?

No, he changed his name.

Oh, he did.

He dropped the parentheses.

Wow. Classic up. Introduce yourself. Who are you?

Yeah, yeah.

Hey guys, My name's Angus. Yeah, I'm, I'm just a, I'm an engineer from Australia. My background's like very much in aerospace and yeah, I've been like obsessed with like building these kind of robot robots for, I don't know, like the last 10 years or something. Yeah, and it's, you know, building, building this mini one. It's really just, it was really like a stepping stone for me on the way to building welding robotics. You know, I've got some larger robots where I'm just setting up a workshop currently to do basically strap on cameras, sensor systems and drive the whole thing. Drive the whole thing via AI because you know, we're basically at the point where there's, you know, we have the ability to drive, you know, these really complex, you know, and industrial scale robotic systems like with, you know, the current robotic foundation models, you know, given the right training data. And so this like this small robot that I put that I've got on, you know, cheap robot.com is great. Was really, really. Yeah, I mean I'm surprised it was available. I was like, hell yeah, dot com, that's great.

But, but it was, it was really.

Just a test bed.

You know, I'm, I'm working with a few guys. You know, one guy, Julian out of Pennsylvania, you know, runs a, runs a shop floor like a welding robot. And another guy, Stephen, you know, currently works for NASA. You know, he's built, working on the vision system portal. But it's really a test bed for us to, you know, you know, validate our algorithms, do small scale prototyping. You know my, the picture that I've got up there, I don't have many demos because it was basically thrown together like 2aM My time last night, you.

Know, got the shop doing it live.

Up and running and live.

So what do you want people to use these for? What are the use cases that you're imagining?

Yeah, so very much the same as I would say those LE robot ones. It's just a much more robust platform. So improved like improved power in the servos, improved like structural integrity. But the key, like one of the key differences is I've actually built a, like an industrial quality like kinematic solver. And basically what all that, what that's telling you is where the end effector of the robot needs to be. There's usually a whole bunch of equations that you either solving numerically or you've got a solver in a low dimensional space that you can work out really quickly. I've built a really robust one for six degrees of freedom. And this is just more than you get with, I guess what's typically being used in all of those AI hackathons. And so I've written all the software so you can take, take all of the outputs from an AI model and just stream joint commands to it, connect it to things like Nvidia's Isaac Sim, but you can also run it like a traditional industrial robot and do path planning for really, really high fidelity trajectories and controls. And the benefit of that is all of that information that you can stream and record from those joints as you use the high quality kinematic solver, you can use that as the training data. So you see a lot of these guys, like a lot of these robot systems, they've got one arm and then another one's controlled by a human with a little lever. And they're like going and doing these pick and place or whatever and you're just streaming like this joint should be the joint angle of this other robot. And frankly that's really crap data for training robots. You get it done but you can see all the movements all janky. It's the same kind of movement that the human's doing with a robot. It's all with. But you like, you know, industrial robots, they've been doing this for decades, right? And they have really nice trajectories, really smooth path path planning. But the bottleneck is like how do you get that high quality data? And you know, with the software combined with this little robot package that's what I can do. You know, that's what this can do for people, you know, help them get really high quality data without and only having to buy one robot. You don't need to buy like the equipment for two.

That's amazing. What, how is the health of this sort of open source robotic hacker world right now? We had Clem on earlier from hugging face and he said this was an area that he was most excited about on, on, on his platform. And, and he, you know, he said they hosted a hackathon recently. It sounds like there's a lot of exciting activity here and you're contributing to it yourself.

Yeah, that's it. Yeah, I basically just posted all the, you know, all the code on GitHub for free. And I think there's, it's like a really exciting time at the moment just because there's like, there's so much activity and attention in it and there's many more people really coming into the field and you know, having a go and learning like not just robotics but on the hardware side. Right. It's, you know, it's like my background's aerospace and mechanical engineering, you know, was, you know, built rocket engines once upon a time and it's, you know, you know, we kind of got left out in the cold. You know, buy Silicon Valley a little bit. It, you know, you saw like, you know, but, but you see all the, you know, the major, all the really standout companies, you know, are all hardware companies, you know, space like SpaceX and Dural and you know, a whole range of them. And I think there's a lot of, like a lot of attention like just on this area has really put a lot of energy, particularly into the open source space, which is awesome to see.

How have sales been? Have you sold any yet? Yeah, yeah.

So I've woken up. Well, you know, we got, we've got three sales so far.

There we go.

Congratulations.

Thank you guys. Thank you guys.

That's three sales. That's 1500 bucks in one day. You annualize that. I think we're in the million.

I think, I think if you put together the right deck, maybe you take a trip to Sandhill Road. You tell the right story.

200 on a billion to SFO.

200 on a billion.

Yeah, easy. Get it done.

Get it done.

Yeah, yeah, look, you know, it's, you know, I think like Yasin said, like, hey, my valuation should be the same as figured because I've now shipped more apparently.

Shots fired, Shots fired.

Not my words. Yeah, I've seen Oh, yeah, I've seen.

Was cooking earlier.

Yeah. I mean, this. This feels like something that would. Would be perfect for the AI grant program from Nat Friedman. You know, this is going to be the enabling technology. This is going to be deeper in the supply chain for the robot that picks up the leaves or, you know, one of these fun, delightful robots. I hope Nat can continue that program. He certainly has the resources for it and it'd be very cool to see that partnered up with the.

I would like a robot.

I definitely came to head to the U.S. we'll sit you here. About 18 months ago, I stopped by the Gundo, you know, met like Augustus and a bunch of other fellas. It's been awesome to see those guys. Like, you know, I think, you know, I went there when Valor Atomics was just a squat rack in an empty room.

It was just a squat rack with scraps. Well, you seem like an alien of extraordinary robotic abilities. So my vote is we get you.

Over here, bring you. Yeah, this is fantastic.

In a couple of months, I think.

Great. Well, let's tune the robot up to crack open energy drinks.

That would be useful on the desk.

It'd be great if we could just hit a button. Yeah, because it's hard to reach over here and crack them ourselves.

Yeah. Yeah. It's brutal.

Congratulations on.

Yeah, thank you so much.

Really appreciate it, fellas. And yeah, love the show. Been a big fan since the beginning, so keep it on.

Appreciate it.

I'll never forget your name.

Yeah, first time it came up in the deck. This is great. Amazing. We'll talk to you soon. Have a good one.

Cheers, Angus.

All right, thanks, fellas.

Congrats.

Bye. Should we go through some timeline? Get out of here, Move on. We got a big show tomorrow.

Let's rip a little timeline.

A little. Just a little timeline. Couldn't hurt. We got Will Menitis talking about there. No, there is no real index of wealth in the world other than the land landowner.

100. Everybody should be aspiring.

Total acres. John Malone's got over 2 million. Ted Turner's got over 2 million. I like the Reed family here at 1.6 million.

Picture of a bear.

Just a picture of a bear. I don't know if that. Do they not have another picture that they could pull from? I have no idea.

I think.

I think you got to start land.

People should just buy land. Just go buy. Start with an acre. It could be anywhere. Could be out in the desert. Start with an acre.

Just add. Just double it every day for 100 days and you're good.

Yeah, just double getting the landowner 100.

Doomer says how it feels to charge your phone off your MacBook Pro. It's refueling the B70.

It really does feel like, I mean.

This couldn't be more perfect. It's so accurate. I mean, a million views makes sense.

Yeah, it's a perfect analogy. You know, you got some juice.

It's fantastic.

You're sharing it. Both running out of time.

Gotta talk about this one. From 9 to 5, Mac Control center is now darker and much more, more blurred in iOS 26 beta 2. Good news, Tyler. He's been struggling with iOS 26 beta 1, but beta 2 is now available. The contrast ratios have been fixed, improved. It's easier to read. We knew Apple would do this. We called this out that any of the criticism that you lever at Apple's design chops, it's not going to be an issue by the time they launch. Tyler, how has. How has daily driving iOS26 been over the last few weeks?

I mean, I think overall it's been very good.

I think most of the issues, it's.

Just, it's hard to tell if it's because my phone is just so old. Yeah, it's the phone. But I think overall, like, it looks really nice. Okay. Yeah, I think it's great. Yeah. Okay. That's good to hear. I like Arvin's from.

I would have been surprised if he's like, I haven't been able to open my phone for weeks now since broken that fateful day.

No, no, no, it didn't break.

Thank you for being a guinea pig for the world.

Yes. Arvin from Perplexity is building in public. Building a competitor to Bloomberg in public. I love this. He's surging Perplexity. How much revenue does Bloomberg make yearly? He's been pretty open about wanting to build like a new version of the Bloomberg terminal. And so he's just searching, how much money do they make?

Make?

And he says Bloomberg makes 12 billion in annual revenue with 10 billion coming from the terminal. And then he's just like throwing this out there, like, hey, maybe I'll do this. Maybe you should invest in this. It's a hilarious thing to post.

Well, I've been a recent DAU of Perplexity.

Oh, yeah.

And you like a lot of value out of it. I mean, it makes sense in the free tier. It makes sense that they're going to get me soon.

Yeah, it makes sense that an LLM company, an AI company, it's the, like, they either. It does feel like there's a fork in the road for perplexity. It's either team up with Apple and become the new default search and figure out something there or go into Bloomberg because like the core product is a very different product.

To try to actually compete with Terminal.

Versus displaying data distribution is just so is so important. I mean we saw this with DuckDuckGo. Like a lot of people in Silicon Valley, a lot of power users preferred DuckDuckGo to Google. But DuckDuckGo never got to the scale that Google did just because of distribution. And so, you know, he's clearly looking at Bloomberg. There's rumors that he's talking to Apple. It's interesting to see where that goes. But he's cooking anyway. Pierre Richelson from Cal.com says, I think organizing LAN parties for 30 plus year olds could unironically be a banger. Warcraft 3 Battlefield 1942 I played the that game. Great Age of Empires. Dota. What else? I don't know why you gotta have 30, 30 year old plus. Bring the teal fellows in. Bring the. Bring the.

I didn't really play those games. John, you're dating yourself.

Yeah, but they can pick it up. I mean a lot of these games.

But it's about the nostalgia.

Yeah. I went to a hackathon last year put on by a venture capital firm. It's fun. Had some Halo. Halo 3 was the popular one, but the new Halo, if you install it, they just give you all the previous Halos. You can just play any of them in like one disc. I guess that's very like. Yeah, buy the current one. It's like SaaS now. You buy the current one, you get. You get all the previous. All the previous ones. Should we close with cow tech startup?

Yeah.

This was exciting.

Get on R for rock Confirmed one month earlier One month early.

Cow tech startup becomes New Zealand's latest unicorn in $100 million fund raising rare New Zealand unicorn. I said this was very bullish.

For beef.

For cows. For cows it's bullish. Did you ask?

Knee slapper.

Knee slapper.

Knee slapper. Well, we could just keep going all day long here.

But if you get a text message from Mark Zuckerberg or an email, do not assume that it's fake. He has taken over recruitment for the Super Intelligence Lab and is reaching out to hundreds of prospects personally. If you respond, this next step is an invitation to dinner. So he's in founder mode. He's grinding. He's putting together the Avengers. It's coming together nicely. I'm liking it. I'm liking it so far. It's fun. Anyway, I think that's enough for today. Thank you for watching Leave Us five stars on Apple podcasts and Spotify and we will see you tomorrow.

We love you.

Have a great day.

Have a great evening.

Bye.

Cheers.