0:00
[Music] Hey, [Music] hey, hey. [Music] Hey, hey, hey.
Search this video
0:28
[Music] [Music] [Music] [Music] Hey, hey, hey.
1:25
[Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] We can't do this. to reach the stars.
3:15
We came to this world to shape our future. We came to this world.
3:29
[Music] [Music] Deathatch [Music] feel. [Music] Come on.
4:16
[Music] We are surrounded by journalists. Hold your position.
4:32
[Music] [Music] You're watching You're watching TVN.
4:52
Today's Tuesday, June 24th, 2025. Keep it together, John.
4:56
We are live from the TVPN, the temple of technology, the fortress of finance, the capital of capital, of capital. the capital.
5:03
Uh front page of the Wall Street Journal has the update from uh the Iran conflict with the United States.
5:11
The Iran Iran fired missiles at a US base in Qatar.
5:14
Since this uh since this published, there is a ceasefire and Donald Trump appears to be very upset with both sides and wants peace and wants uh the rocket attacks to stop.
5:28
And so we certainly hope that uh the conflict will come to a close and we can get back to real estate development and golf. Exactly.
5:36
Uh oil drops, stocks rise after attack.
5:40
So uh it seems like this is what capital bloke was talking about.
5:45
He says the start of World War II is a positive catalyst because it implies there will be an eventual end to World War II.
5:51
It's a new catalyst and that's exactly what happened. So World War II is over.
5:57
Hopefully it stays that way.
5:57
Um, anyway, we have some uh we have some new drinks in the studio.
6:03
We have uh 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.
6:11
Now, uh you know following how much caffeine is there?
6:15
Uh there's 120 milligrams I believe.
6:17
We should have Tyler drink 10 today. Uh yes, we should.
6:19
Uh yeah, as if you've been following the show, you know that I am have been a fan of Matayena.
6:27
Uh Andrew Huberman's Yerba Mate.
6:27
This is the mango key lime flavor.
6:29
Uh it's non-carbon non-carbonated energy brew.
6:34
And here I have the Chris Williamson Newtonic productivity drink. It says fuel your focus.
6:38
I'm going to do a little taste test and let you know.
6:40
I'm going to try and be as objective as possible. Um okay.
6:44
So this is the this is the Andrew Huberman Yerba Mate. That is incredible.
6:53
It tastes It tastes like the work of a TBPN guest.
6:56
Like someone who's been on the show clearly worked on this. Now, let's taste.
7:00
Now, let's taste Chris Williamson.
7:02
I I I did invite him on the show.
7:08
Oh, that tastes like someone who who hasn't been on the show yet. Interesting.
7:12
Yeah, it's funny how that works.
7:14
It is funny how that works.
7:17
So, I mean, maybe Chris should come on the show and Yeah, we could correct that. Yeah.
7:20
And then and then I think I could maybe give it a more positive review, but you're on to something, John. Uh, no.
7:25
But it tastes fantastic and I will be drinking this throughout the show. And I'm a fan.
7:30
This is actually the very first time that I've ever tasted this. It's very good. Very good.
7:36
Anyway, looking forward to having you on the show, Chris. Hop on anytime. You're welcome.
7:40
So, are we newsmaxing today? We're newsmaxing.
7:42
Uh we're running through a few top stories, the current things.
7:47
Uh there's the anthropic ruling, right?
7:49
We got to talk about All in Tequila.
7:51
We touched on it yesterday, but there's a lot more news.
7:56
There's a lot more to go.
7:56
We're doing we're putting on our investigative journalism hat. Yep. We're going deep.
8:02
Also, Hims and Hers is in the news.
8:02
Uh there's a messy breakup that has jolted Hims and Hers, but uh the retail investors are bullish.
8:10
They're continuing to buy.
8:12
There's a lot of news back and forth.
8:13
And then we got to talk ended last week at $64 a share.
8:19
It started yesterday morning at $43 a share.
8:22
So uh the Nova Nordisk uh debacle uh impacted the share price pretty dramatically.
8:29
We're going to have Cremu on the show later, a GLP1 enthusiast to break that down with us and we'll talk through it as well. Huge enthusiast.
8:38
And then we'll also take you through the story of the rare earth magnets, which is complete fake news.
8:43
Rare earths are not rare.
8:43
They're just the the industrial capacity to bring them out of the ground is rare.
8:48
And and the industrial might is rare and it has mostly moved to China.
8:52
And so now Ford Motor Company, the Ford of Motor Companies, has declared that they have a magnet shortage despite the China deal.
9:04
And so we'll dig into that.
9:04
Anyway, let's kick it off with David Saxs.
9:05
We're not talking about tequila yet.
9:07
We're talking about the positive ruling for AI.
9:10
Uh this is because Andrew Curran has the story.
9:13
A federal judge has ruled that anthropics use of books to train Claude f falls under fair use and is legal under US copyright law.
9:21
And I couldn't agree more with this.
9:24
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 and and AI models as perfect itself. Exactly.
9:41
You would never go to the author's work is not being reproduced. Exactly.
9:45
It's being, you know, remixed.
9:46
And you might say, yeah, you might say, give me the high tell me about the themes in Harry Potter, but you're not saying Claude, give me, which is something that was available to some degree on blogs since the internet existed.
9:59
You could look up what are some of the key there was that website uh Spark Notes like Spark Notes was a was a version of that that was transformative.
10:07
And so I I I always thought that this would go this way, but I did think that we needed to sort it out in court.
10:09
And for some of these uh categories of media, there probably needed to be deals.
10:15
And I still think that there's probably room for something like Simon Schustster or Penguin RandomHouse 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.
10:25
Hey, 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."
10:31
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.
10:36
So interesting thing is that uh the judge did find that Anthropic infringed on copyrights by storing over 7 million pirated books in a central repository. Interesting.
10:46
So they had the books and there's going to be a trial in December that will determine damages.
10:52
Statutory damages could reach up to $150,000 per book. That's a lot. Wait, multiply that out. That's billions there. How much?
11:01
And uh so anyways, if if if the judge uh or the jury were to award that I feel like a book cost like 20 bucks, how much does a book cost?
11:12
Well, they're saying the damages could be up to 50,000 per work.
11:17
I doubt that goes through.
11:17
It would end it would end, but there's just no way.
11:22
That sounds like the price of a book after David Ser does does a episode about it and there's only six copies on Amazon and they've been spiked up.
11:29
Uh 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.
11:38
Uh and yeah, ultimately um the court is criticizing anthropic for pirating tax.
11:48
But um the big question here is will training on YouTube data be fair use? Because it is public.
11:55
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 it is fair use and I don't have a problem with that.
12:17
Now, the question is, can OpenAI go and train uh what's their video model again?
12:24
Not Dolly Sora, Sora, Sora V3 on all of YouTube because it's fair use. Yeah.
12:29
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 and could have accessed them in different ways.
12:40
But um ultimately we'll see how it shakes out.
12:43
But but important thing for anthropic obviously is to get on ramp. Time is money. Save both.
12:47
Easy use corporate cards, bill payments, accounting and a whole lot more all in one place. Go to ramp. com. Anthropic.
12:53
Daario, if you're listening, I know you're listening, go to ramp.
12:54
com, sign up if you haven't already.
12:56
Um, David Sax summed it up. Positive ruling for AI. There must be fair use.
13:00
There must be a fair use concept for training data or models would be crippled.
13:04
China is going to train on all the data regardless.
13:06
So, without fair use, the US would lose the AI race.
13:10
This is an interesting take.
13:10
I hadn't even thought about that dynamic, but that makes a ton of sense. Um, yeah. Yeah.
13:18
And then you have this weird dynamic where it's like what if deepseek is trained on all the American books.
13:23
And so Deep Seek becomes like hyper capitalist and then the only way for American models to to stay up is like perplexities like Deep Seek 7 1776.
13:30
So they're like fine-tuning on deepseek output.
13:35
That's in order to deliver Western ideals. I love it.
13:37
Maybe that's the maybe that's where this Wetsu action. Yeah. It's great.
13:42
Uh the writers filed the class action against Thropic last year arguing the company which is backed by Amazon Alphabet used pirated ver versions of their books without permission to compensate to teach Claude to respond to human prompts.
13:55
I wonder what what pirated means in this context because um I wonder if it literally means like they went to like a torrent website and like downloaded it um 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.
14:15
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 7 million books 20 $20 a pop.
14:29
They didn't spend $140 million on books just they should they should have support and that that's one of the risks going into this trial.
14:45
It's possible that you know I don't think They should have to pay 20 bucks a book.
14:49
They should spend $150,000 book.
14:52
What is the actual damage again? You had the number. $150,000 per book. That is way too high.
14:56
It could go up to I would I would give them some bulk pricing.
15:00
Maybe $17 a book, $15 a book, maybe even $10 a book. But they got to pay.
15:04
The issue is that the individual rights holders are not exactly going to be super happy about getting one purchase.
15:14
Hey, 20 bucks is 20 bucks. 20 bucks is 20 bucks.
15:17
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 is 20.
15:23
Some people are going to read it.
15:25
Some people are going to let it sit on the shelf.
15:28
And some people are going to train a massive model.
15:29
They could go through this whole lawsuit and come away and buy one double steak double guac chipotle burrito bowl and think that this was worth it. Yeah, exactly. It was worth it.
15:38
I mean fundamentally anthropic believes that they are creating God.
15:40
So like you want an illiterate God.
15:43
Like you got to let God read some books.
15:48
It would be an affront to God to not let God read books.
15:53
Might be on to something.
15:53
Anyway, uh if you're designing the next great AI product, go to figma. com.
15:58
Think bigger, build faster.
15:59
Figma helps design and development teams build great products together.
16:03
Um now let's move over to the all-in tequila.
16:07
So we talked about it briefly, but we want to go a lot deeper today.
16:11
So Chamath Palapatia has the story.
16:13
He says, "We've launched our ultra premium tequila today in Los Angeles at Delilas."
16:17
I've never been to Delila. Is it good? Have you been?
16:20
Are you familiar with this place?
16:22
I'm not big into that world, John. Me neither.
16:26
We mostly don't leave the house after 9:00 p. m.
16:28
Where does Ultra Premium sit in the ranking?
16:31
Because it's below luxury.
16:33
Yeah, I was surprised with with the pricing is clearly luxury.
16:35
That's what I would think.
16:38
position the positioning overall.
16:39
The bottle looks incredible. The box looks amazing.
16:40
The bottle actually does look incredible.
16:43
Um, it very clearly it it is an order of magnitude more expensive than traditional luxury or I would definitely say ultra premium products, right?
16:51
Um, and so yeah, squarely sitting in that luxury category, but I think he just I think he just uh just ripped it.
16:58
I think I think there it begs the question like what comes after ultra premium and it's obviously giga premium. Yeah.
17:06
So, they wanted to leave room for a $10,000 $10,000 bottle. That's giga premium.
17:10
You got So, for those that don't know, the bottle, the the tequila is $1,200. $1,200. 750 milliliters. Yes.
17:17
And and let me read a description.
17:21
Pot distilled from 100% blue Weber agave.
17:23
Grown in the lowlands of Halisco and aged in white oak whiskey barrels for 5 years.
17:27
This extra anjo tequila has the perfect balance.
17:32
A smooth, slightly sweet taste with hints of wood, citrus, dried fruits, butterscotch, vanilla, cacao, toffee, and cooked agave.
17:39
We recommend it to be paired with good friends and lively debate as they do on the show. Fitting.
17:45
The bottle is a handcrafted art piece evoking a stack of poker chips.
17:47
It is illuminated from the base to appreciate the beauty and complexity of its design.
17:52
Each is individually numbered for its very limited release of 7,500 bottles.
17:59
So, I would really love a new T out gross 9 million.
18:03
Wouldn't you love a $1,200 energy drink?
18:05
Yeah, just a beautiful energy drink. Ultra premium.
18:10
Ultra premium energy drink that comes in a glass bottle. Pour it out. Oh, they'd be so good.
18:15
They really should do that.
18:17
Uh I'm I'm sick of the energy drinks in the Oh, $3 a can, $5 a can.
18:19
Let's get Let's get these numbers up. $500. Get these numbers up. Let's do it.
18:26
Anyway, there was a lot of push back.
18:27
Augustus Dico chimed in to the tune of 5,000 likes.
18:32
He says, "The elites have totally abandoned us and and their responsibility to steward the nation.
18:38
We're on the brink of war.
18:38
Deaths of despair at an all-time high.
18:39
The economy is fake and the putoaucracy is launching ultra premium tequila brands. We need greatness."
18:46
And so, he was very upset.
18:48
Uh non-equity partner had the flip side.
18:51
Said, "You can just do multiple things.
18:53
Lead transformative agendas and launch liquor brands. Look at Tesla.
18:55
Elon Musk launched the Tesla tequila.
18:58
It was kind of a fun side project.
19:00
And I think that's what Emily Sunberg was getting at before when she was talking about how celebrity brands, people kind of know the the thing.
19:08
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.
19:17
He's he's he, you know, signed off on it, went to the party.
19:21
It's going to live on a website.
19:21
We I actually found the the design firm that did the design.
19:25
Like this is not going to suck these folks away from from the other things.
19:29
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.
19:36
But I don't know why it's unserious.
19:38
They have their friends, they have a podcast, they enjoy drinking together, playing poker.
19:42
They introduced a poker themed bottle of tequila by and enjoy with them.
19:49
I don't think it's I don't think it's unserious.
19:51
I think I have more questions around how seriously are they taking it as a business, right? We need CEO.
19:56
Are they trying to, you know, scale this into Yeah. Is it a drop?
20:02
Because it might it might not even need a It might not even have its own CC corp or like its own LLC.
20:06
It might just be like merch essentially and it's cool as merch.
20:09
Um, and and then there is this question where, you know, I I feel like there is a drum beat in the news and in the culture around like things have never been worse.
20:19
Like you like it it like it's so bad right now.
20:22
We're in a uniquely bad situation.
20:23
Yet at the same time in the Middle East today. Yes. Yes.
20:29
Peace in the Middle East. Finally. Finally.
20:31
For the first time in 60 years.
20:33
only just a few days after the launch of this and there could very well be some correlation.
20:39
There's definitely a correlation.
20:41
Definitely a correlation.
20:42
Whether or not there's causation, we don't know yet.
20:45
I think you get a couple of But Trump had his own vodka back in uh 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.
20:54
He's never been big into that whole world. Wow.
20:56
And so I think this was just Yeah.
20:58
How are you going to criticize the I mean the all-in guys seem to enjoy the tequila at least.
21:04
Trump vodka was an American brand of vodka produced at first in the Netherlands then later in Germany by drinks America. Drinks America.
21:10
It was made in Germany and by a company named Drink America.
21:15
Produced in the Netherlands and then Germany was drinks Americas.
21:19
It's the company is called Drinks Americas two.
21:21
never produced in America.
21:23
Uh 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.
21:32
Honestly, might be the time to bring it back.
21:34
I don't know if they're going to do distribution.
21:37
It seemed like it was all interesting.
21:39
However, it is still sold in 2016.
21:40
This was the last time it was updated, especially around the Jewish holiday of Passover. Huh. Interesting. Odd.
21:47
Um Trump at the time uh the the brand slogan was success distilled with Trump predicting it would outsell Greg Goose.
21:58
He also said that when mixed with tonic which he referred to as a Trump and tonic tea and tea it would become the most drunk and tea is good.
22:04
It would become the most drunk cocktail in the United States.
22:08
I love I I I I mean the consistency of his confidence across eras is incredible.
22:15
In 2007, Drinks America signed a deal to export 50,000 cases of Trump vodka annually to Russia. To Russia. Oh no.
22:28
But in 2011, it was discontinued due to sales failing to meet the company threshold requirements.
22:33
Uh several reasons were attributed to this.
22:36
One was because Trump himself is a non-drinker and never drank Trump vodka. He tasted it. Yeah.
22:43
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.
22:52
In 2015 in his campaign for president, uh Trump did not include Trump vodka amongst assets submitted to the federal election committee.
23:00
So it was basically a zero. Yeah. Interesting.
23:02
Well, uh my advice for the besties, you're launching a tequila brand.
23:06
You're going to have to pay sales tax.
23:08
You got to get a numeral hq. com. Sales tax on autopilot.
23:09
Spend less than five minutes per month on sales tax compliance.
23:13
I liked Mike Salana's take.
23:14
He said, "I'm happy for the all-in guys and tired of the tedious hate.
23:18
They built a popular show, which is hard." True.
23:20
Now they're launching a tequila brand. Okay, great. Hope it does well.
23:25
Jealousy on this app is unreal.
23:27
Their success can't hurt you. Focus on yourself. I like this.
23:29
Eric Torrenberg chimes in.
23:31
How you feel about their tequila brand is how you feel about yourself.
23:34
That's been a line he's been repeating.
23:36
Um it's uh it is it is interesting.
23:39
It seems like you know their their whole show started as like they're locked down during COVID.
23:44
They all hop on on Zoom and they have some fun talking to each other and they love poker and this feels on brand.
23:48
This feels like a good line extension for the brand.
23:54
I guess there's a question of like should they just run ads for a big tequila brand?
23:58
But we should get into I think it's way more fun for them.
24:00
Yeah, it's fun to have their own thing, right?
24:03
Um, 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.
24:12
That you can share, that's social.
24:15
I want to get into, you know, expected value, expected market size, expected profits.
24:20
Like, how successful do we think this will be?
24:22
Because there's a world where this becomes a major brand.
24:25
Like, I mean, Prime is a big brand.
24:28
Feastables is a big brand. like these guys.
24:30
These guys could turn this into a massive company.
24:33
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.
24:40
Um, I found the design firm that actually worked on this, the besties all in tequila.
24:44
It's from a from a design team called Hello Stranger.
24:49
They say, "We'll fix your brand.
24:51
We'll give you a new brand, a brand that wins all the awards and sells at a premium.
24:55
will give you a strategy, a unique angle based on insight and research.
24:59
We'll give you the sexiest packaging that people can't put down.
25:04
And we'll give you all the collateral you need to make your brand flourish.
25:05
On this site, you won't find head shot of designers looking important next to yucka plants.
25:10
Because it's not about us, it's about the billions in sales in one of the toughest sectors in the whole of retail.
25:17
We're stranger and stranger.
25:20
We've been doing it for over 30 years and we are the best.
25:21
As one of our clients said, don't leave anything to chance.
25:25
They started making the only push back I have here.
25:27
I think day job is the best.
25:29
They did the design for David protein bars. True. True.
25:32
It's going to do billions in it first few years.
25:36
It's hard to argue with with those kind of results, but so they announced the uh Besties All-In Tequila, which is an interesting name choice as well.
25:44
It's not the all-in tequila.
25:44
It's not Besty's tequila.
25:46
It's the Besties All-In Tequila.
25:48
Um, but uh they say the besties at the famous All-In podcast have just released a $1,200 tequila, which unfortunately for all of us is already sold out.
25:58
The guys are big poker players, hence the all-in and uh and the iconic bottle single-mindedly owns the idea.
26:07
Um, and so the the love language here, you read some of this handcrafted art piece evoking a stack of poker chips.
26:16
It's illuminated from the base to appreciate the beauty.
26:18
Oh, so there's a light inside. Let's go. That's cool. There's a light inside.
26:22
I mean, that's what it sounds like.
26:24
It says it's illuminated from the base.
26:25
So, I think I think what you're spending $1,200. I think it glows. Yeah. Incredible. It's tech product. Yep. It's internet connected.
26:34
It's got It's IoT device.
26:37
It's an IoT device potentially for boozing. For boozing.
26:39
Imagine you could link this.
26:41
It could measure how much is in there.
26:43
Have an app orders you more automatically. Subscription.
26:45
Now we're talking this it goes from a nine, you know, $9 million, you know, first run into a $9 million MR business. Yes.
26:56
Getting up into that nine figure revenue range pretty quickly.
26:59
Uh it is it is fascinating.
27:02
So uh each individually numbered for the each bottle is individually numbered.
27:05
They're releasing 7,500 bottles.
27:07
So if you do the math, 7,000 times 9 million 9 million.
27:11
That's that's that's how much they're trying to make.
27:15
Um, and each bottle arrives in a numbered collector's box bringing the besties signatures.
27:20
They're either signing them or it's printed on there. I don't know.
27:23
I think it's got to be printed on there.
27:24
David Sax does not have time to hand sign.
27:27
How long would that take?
27:29
You do one every couple seconds.
27:32
It's, you know, days worth.
27:32
The signatures would get so sloppy, buddy. Mr. Beast has done that.
27:37
I've seen streams where he's been like signing every single t-shirt. It gets really messy.
27:41
Um, but, uh, they say, "Wet your beak.
27:44
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 the TBPN brand around fortress of finance lever up all these different catchphrases they've done a really good
27:59
job because as soon as I hear what your beak I think I I think I'll in I think your beak anyway there's been some timeline and turmoil because Kasazar tequila has a similar bottle design and similar and so we can pull that up the founder story over Kas Aar lies in a husband and wife founder story. A tale
28:16
A tale of resilience, determination, and the courage to go quote allin.
28:24
Search if you search allin tequila right now, you'll get a a post from April 11th, 2025.
28:33
Uh that says this is on the spiritsbus.
28:34
com that the the tequila stackowned brand Kasazar transcends mere novelty by merging cultural roots with the most important aspect flavor and character.
28:43
Max Ramirez and Vivana Serrialta Ramirez, two exagio executives and industry veterans launched Kasazar in November 2024.
28:52
The husband and wife do uh team were driven by passion, determination, and courage to go quote unquote allin in pursuit of a dream to create a brand that would stand out in a crowded market not only visually but also gas gastronomically.
29:07
Less than a year since its launch, Kasazar has quickly gained momentum and garnered industry accolades.
29:12
Most recently, the tequila and mezcow masters 2025.
29:18
Kasazar Tequila won two gold and a master medal. Mhm.
29:20
The brands Hovind and Reposado bag gold and their ultra premium.
29:26
Well, ultra premium might just be like a category.
29:28
We're kind of exposing how little we drink anything other than champagne.
29:32
100% agave tequila categories. Earning a master medal.
29:35
Kasa Kasazar Tequila and press judges. Here's the bottle.
29:41
I don't zoom in on very expressive nose with plenty of earthy roasted agave and peppery spice.
29:45
creamy and syrupy on the palette with drying oak and peppery spice balanced with sweet golden syrup and charred agave.
29:54
Uh, judge Matt Chambers, director and co-founder of Whiskey for Everyone, described Kasar and Yo as so delicious.
30:01
So, anyways, I saw this and my immediate thought was that maybe All-In had white labeled Yep.
30:05
the bottle, but that doesn't seem to be the case.
30:07
And digging in a little bit more, some of the issues here, this company's been in business for a while now. It's exagio execs.
30:16
They have patents uh from what I could tell around it's more of like a trade dress thing.
30:21
The patent would be like how you manufact around the bottle design which is very distinct. Interesting. Uh very distinct. Yeah.
30:32
So there could be some fallout maybe a negotiation.
30:33
Maybe someone's going to 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.
30:44
And this could get this could get spicy, right?
30:46
According to Kasazar, the tequila is designed for those who live life who live like a high stakes poker game.
30:53
Fearless, driven, and willing to take risk.
30:56
These are a lot of the same things.
30:57
So, there could be some confusion.
30:58
The besties are taking a risk. Yes.
31:00
And and I' I've run into founders before who have 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 subm market that actually had national ambitions and was going to sue and and 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.
31:23
uh the 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 um and but eventually they both wanted to go national and so they collided and they had to kind of decide how to back off.
31:46
Well, we saw this yesterday with IO I Yo, the brand OpenAI where OpenAI had to scrub all mention of I Z or you know IO. Yep.
31:57
Uh from their website because of a trademark issue.
31:59
This is seem seemingly a bit different because it's a design uh sort of patent or trademark.
32:04
I don't have exact specifics, but I expect this to get spicy.
32:09
Uh and you're going to have people Kazar is known for being sweet and spicy. That's right. That's right.
32:16
I I do wonder where Ultra Premium comes in.
32:19
I feel like it's anything over like a hundred bucks or something because why would you put a $200 bottle and a $1,200 bottle in the same category?
32:27
Those feel like it's it's half an order magnet.
32:29
It's like 500 or 5x difference in price.
32:32
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 costes are both are premium.
32:43
Both are heavily branded around poker.
32:46
One of them launched in 2024. Yep.
32:49
One of them la is launching today. Oh, wait. Kasar is only 2024. Yeah. Oh, wow. It's like pretty new. It's new.
32:57
They filed their initial trademarks in 2023 though, so it's been a little bit.
33:02
So they they've been uh in market for a while and uh Kasazar's execs, Exagio, right?
33:08
They're probably got some sharp elbows.
33:12
I imagine they're going to want to uh pursue this to some degree just given people don't realize how I think we live in this tech bubble.
33:22
Y I don't think people realize how big All-In is.
33:23
It's like way bigger than than just tech now. Huge huge huge.
33:28
And so um this, you know, I think uh we'll see how this shakes out.
33:33
But so there's there's there's another thing that's kind of confusing is that I was wondering if they were playing in different markets because Kasazar is 40% ABV.
33:38
That's 40% alcohol by volume, 80 proof, which is pretty standard for liquor.
33:45
Um, on the All-In Tequila, the Besties All-In Tequila website, it says it's 750 milliliters, same size, 40% ABV, $1,200.
33:59
Um, 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, Jord? 48% here.
34:09
That might have just been an early renders. Yeah, maybe.
34:12
I I wonder where they're landing because I feel like 48% is a much stronger choice for tequila.
34:19
Like 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 going to be more alcoholic.
34:32
It's going to it's like it's powerful stuff. Yeah. Yeah.
34:36
I mean, one of the secrets to those like spirits that um popular on college campuses is that they take the alcohol content down to something like 30% or 35% flavor.
34:45
I don't know where this picture is from because on the website it says 40%. I don't know either.
34:52
I don't know where I got that picture.
34:54
Well, we will have to get a bottle ourselves.
34:55
We will and we'll taste it.
34:57
We'll immediately tell you. Yep. 42%.
34:59
We wanted to have Tyler taste it, but uh fortunately it's not of age. Yeah.
35:05
So, we'll save a little bit for you, Tyler, for for your birthday. Yeah. Can't wait.
35:10
Um, well, if the besties are planning to take the besties all in tequila to the moon, they're going to need to get on Vanta.
35:19
They're going to need to automate compliance, manage risk, prove trust continuously.
35:24
Vant's trust management platform takes the work out of your security and compliance process and replaces it with continuous automation.
35:28
Whether you're pursuing your first framework or managing a complex program, you know, if you wind up turning this into the big IoT SAS product that we've imagined it being, you're going to be managing customer data.
35:42
You're going to have their health records potentially.
35:44
You're going to be pulling in all sorts of stuff to optimize their liquor consumption and you're going to need to be secure.
35:51
So, you're going to need to get on Panta for sure.
35:52
How big do you think this is?
35:54
Where do you think this actually goes?
35:55
Like like I think that's the more serious question is it totally 9 million I think that they're going to sell that.
36:01
I think they're going to sell all 7,000. No, no problem.
36:02
The haters will be in disbelief.
36:04
Yeah, there are so many fans.
36:07
We we we know we we we we're going to buy a bottle, but we know we know folks who are friends and friends of friends who are going to buy bottles.
36:15
There's going to be people that buy bottles because it's fun and they want to support their the the show that they like.
36:20
There's going to be folks that gift it.
36:21
There's going to be people that buy it because they're they're, you know, um they want to just like support the the the the thing that hasn't been charging them for five years.
36:31
Like there's a little bit of people just want to support the dictator Jim.
36:34
But honestly, it's like it's like there is another world where if allin was $20 a month, you would have paid $1,000 over the last four years.
36:44
And they didn't charge you $20 a month.
36:46
They didn't even run ads.
36:47
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."
36:56
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.
37:01
It's hard to It's a fun thing to buy.
37:03
Imagine you're going to a friend's house for dinner.
37:08
What's funnier than bringing a bottle of the Bessie's All-In tequila and being like, "Hey, I just picked this up on the way over.
37:13
It looked it looked nice."
37:15
It's like it's almost it's like a good like high-end tech gag almost gag, but it's also probably really good because it's expensive, right?
37:22
So, so then you taste it and you're like, "Oh, this is actually really nice."
37:26
Um, which bottle design do you like more?
37:28
Because Kasazar has this ceramic bottle that they hand paint.
37:34
You said you liked that it had the stack of chips all the way to the top, stacked top to bottom. I don't like that.
37:41
John doesn't like it, but break it down.
37:42
I think the ceramic look is nice.
37:44
They look more like regular poker chips. I think it's cool.
37:46
I think it's almost too close to poker chips.
37:50
Like I would be confused.
37:50
I'd be like, is that just a pack of stack of poker chips? It's like hiding. It's It's hiding.
37:56
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.
38:08
Anyways, it it the Kasar is a beautiful bottle. Touch years ago.
38:10
The Kasar beautiful bottle.
38:13
I like that it's fully stacked.
38:17
Ultimately, I think it just doesn't read as a bottle of liquor, whereas the besties all in tequila does to me re read as it.
38:24
And then also the uh the glass the glow the glow is it it is in a different tier. Ceramic is premium.
38:30
I would only give the ultra premium label now to the the besties all in tequila.
38:34
I would call I would call they've reset what it means to be ultra premium.
38:40
Look, they're just showing off zooms now. There we go.
38:45
They're zooming all over the place. Yeah.
38:46
I mean, not to not to talk trash about Kasar. It looks fantastic.
38:51
I'm just saying that the besties all in tequila.
38:53
They innovated by by including the illumination, by including the glass, by We don't know.
38:59
That could be the IO IoT functionality that people have been asking for. We don't know.
39:03
So, I I mean I I would give the besties all in tequila the edge here.
39:08
Now, do you know the story of the iPhone?
39:14
Are you familiar with what an iPhone is?
39:16
Uh, are you know where you're going with this?
39:18
I know where you're going with this.
39:19
So, when Steve Jobs introduced the iPhone, he famously said on stage, and yes, we're calling it the iPhone.
39:25
And this was controversial because Cisco owned the rights, the trademark to the word the iPhone.
39:33
And so, everyone was like, how is this going to work?
39:36
you just launched a product that is clearly derivative of this other company's name. They have a trademark.
39:44
They're just going to block you.
39:45
But at some point, a deal was made.
39:48
I don't know if it even became a lawsuit.
39:50
It was probably just like they sat down and said, "Hey, let's, you know, let's let's allow this to happen.
39:56
We want to run with this.
39:56
We could take it to the courts, but that's a headache for both of us.
39:59
Let's just net this out and we'll buy some WebEx license." Crazy.
40:03
There's a article on appleinsider. com from 2006.
40:05
Cisco introduces the iPhone family of devices. Wow.
40:12
And it is not nearly as good-looking as the iPhone. Yeah. Would ultimately be.
40:19
Uh but it and it's funny to see the iPhone like word effectively the iPhone word mark placed on on a non-Apple device.
40:28
Well, if you're trying to build the next iPhone or software for the iPhone, get on linear.
40:31
Linear is a purpose-built tool for planning and building products.
40:34
Meet the system for modern software development, streamline issues, projects, and product road mapaps.
40:38
Now, we discovered an interesting link between Cisco, the iPhone, Apple, OpenAI, Johnny IV, and I think we cracked the code.
40:46
We got to break it down for everyone. Get the tin foil hat. Get the tin foil.
40:49
Uh I will I will send the uh I will send the image to the team so they can pull it up. So, okay.
40:56
So, this is this is how it goes.
40:58
So, Apple, as we mentioned, they potentially got the name the iPhone from Cisco.
41:04
Now, who designed the iPhone at Apple? Johnny. Johnny IV. That's right.
41:10
Now, where does Johnny IV work now? Open AAI. Open AAI. They acquired Love from.
41:19
They got brought him over to OpenAI.
41:20
Who's the chief product officer at Open AAI? Kevin Wheel. Kevin Wheel.
41:26
And who's uh what what boards does he sit on? Cisco. Cisco.
41:29
Who who licensed the iPhone name from Apple? Wow.
41:33
It's a snake eating his tail.
41:36
An oro boros of Silicon Valley intrigue. We crack the code here.
41:41
It's all linked symbolism will be their downfall.
41:47
The most the most completely nonsensical skitso uh diagram. What are you alleging? Yeah. Yeah.
41:53
What are you're you're alleging that things happen people interact with each other? Yeah.
41:58
That that that uh If only it were so simple, Jordy. Yeah.
42:01
If only it were so simple.
42:03
I wish I had the mind your mind the mind of a golden retriever to not see the obvious pattern here. Yeah. That the big conspiracy. The Yeah.
42:10
The big conspiracy that we unveiled here on TVN that they're all linked.
42:15
It's all part of it's all part of the plan.
42:17
You're pulling the strings.
42:19
Big Cisco, Apple, OpenAI, Johnny IV, Kevin Wheel, it's all linked. It's all linked. We We blew it wide open.
42:26
We should throw all those guys in our CRM.
42:29
Adio customer relationship magic.
42:30
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
42:36
Anyway, the official CRM.
42:36
So, so final final word on the besties all in tequila.
42:41
I think it's a no-brainer that they sell 9 million in this first run.
42:45
The question is, do they do they do that every month?
42:48
Do they do that every year?
42:50
Do they move on to a different drop or does this become something?
42:54
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.
43:01
And then the number of people in the all-in audience that care enough about tequila to spend $1,200 on a bottle of tequila.
43:07
Not in a sort of like funny gag setting, but as like I'm going to just drink this regularly.
43:14
And I think it could be a lot.
43:16
Like I I could see them selling 20,000 bottles of of this.
43:19
You can imagine them drink one of them is drinking it on every show, right?
43:24
It's sort of this constant always on advertisement for it.
43:28
I could imagine them uh they're saying the besties all in tequila.
43:33
I could imagine them going into other categories, right?
43:35
And there's a world where they're selling tens of thousand malt liquor 40 ounces. 40s.
43:43
I would love to see I would love to see Jay Cal do do Edward 40 hands. Yeah, Edward 40. That would be amazing.
43:56
[Laughter] We got to move on.
44:00
Okay, I'm having too much.
44:02
I have a different bowl case for you.
44:03
I have a different bull case for you that's it's a little more serious.
44:06
Um, so I have been in consumer package world for a decade.
44:10
I've I've built two brands in the space.
44:12
like the product quality is super important.
44:14
You do need an edge and you do need a a value prop that can actually resonate with consumers and you need ongoing marketing. That's 100% true.
44:23
But in fact, the biggest monopoly brand is an important monopoly for consumer goods, but there's almost a bigger monopoly with just distribution.
44:35
Like it if you actually walk around the grocery store, you will see I talked to a founder who um came up with he he his whole model was he literally would walk down the grocery store and look at not just the products but who own the products.
44:50
And he would see that wow this entire aisle is owned by Unilever.
44:53
They just dominate the entire aisle.
44:56
There's there might be a ton of different brands but everything is Unilever or everything is General Mills or Craft or something like that.
45:04
And so he he wound up building a company that does uh he he he was looking around.
45:09
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 have much. You don't hear much.
45:21
So he started a company that uh was like a popcorn spray that you could spray a flavoring that you'd spray on the popcorn. It's purely additive.
45:29
Wasn't competing with anyone.
45:31
And he grew that to like a couple million bucks. It was great.
45:34
Um, and I think that a lot of these products, they do just wind up winning on distribution.
45:39
And what's interesting about this is that I am almost certain that in the all-in audience.
45:47
Yes, there are consumers, but there are tons and tons of people who work in distribution, work in store ownership.
45:54
Like would it be possible for any of the besties to get the CEO of of uh Bevmo on the phone?
46:02
Like absolutely in two seconds they could do that.
46:05
Could they get in could they get this into Walmart? Absolutely.
46:08
Could they get this into I don't know CVS?
46:10
I don't even know what the biggest um what the biggest channels are for high ultra premium liquor are.
46:17
But if you just think even like the independent store owners, they probably listen or are familiar, right?
46:23
And so just being able to take that call and accelerate your sales force and have them be like, "Yeah, sure. Send me one.
46:30
I'll put it on the shelf.
46:30
When we sell it, I'll just order another one from you since it's a,000 bucks."
46:33
Um, and so h pulling that distribution forward into the into the future, being more aggressive about that, about getting into distribution, holding on to it.
46:42
I think that's I think that's something that could be could be interesting.
46:46
And then the fact that the bottle design, there's a couple companies that do that have been particularly good with bottle design.
46:53
I've talked to one consumer package 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 pop off the the shelf.
47:10
Um because you look at the wall of all the products, they all look generic.
47:13
if you can be the one that stands out, um you're going to just have more people pull it off to sample it.
47:20
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 grow glowing and looks like a and has a light up display.
47:29
This is something that a lot of consumer package goods founders uh negotiate for.
47:33
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?"
47:38
Or like we will come in and give you a light up display.
47:42
We we we fight for this all the time with Lucy.
47:44
like we we will say, "Oh, we'll send you a free into storere 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."
47:53
And so imagine if they're like, "This every bottle is a light up display.
47:56
It will jump off the it'll jump off the back bar and so it won't just sit there and collect dust.
48:01
It will automatically draw the eye to it."
48:03
I think that the light up thing could be enough of like a distribution advantage that it winds up being a popular product. Totally. I don't know. Totally. I agree.
48:11
I think it'll come down to product quality.
48:14
What percentage of the audience actually wants to spend $1,200 on tequila on a recurring basis?
48:20
Do they go into other categories?
48:22
I I think they could sell, you know, Chimath is also launching a wine club.
48:27
Yeah, that was interesting. That's separate.
48:29
There was so much backlash to the tequila thing.
48:30
It wasn't even the first alcohol brand he launched that month. Yeah. Yeah.
48:33
Well, 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?
48:44
You know, and and like 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.
48:58
I think a lot of group chats out there would like to have their own alcohol brand. So, totally.
49:03
Um, anyways, I'm excited to see it play out. I'm excited to try it. Yeah. Yeah. Yeah.
49:08
This is definitely not like a pivot of the brand in the same way that the the talking politics is not a pivot of the brand.
49:13
You go back to the very first episode of the All-In podcast, they were talking politics.
49:16
They were talking about COVID and stuff like it was it was like they've been very consistent in all this stuff.
49:21
So, anyway, if they're trying to pump their tequila, they got to buy a billboard on AdQ adqu. com.
49:26
Out of home advertising, straight to the 101. I want to see the one.
49:32
I want to see every single billboard on the 101.
49:34
The besties all in tequila out of home advertising made easy and measurable.
49:39
Say goodbye to the headaches of out of home advertising.
49:42
Only ad quick combines technology out of home expertise and data to enable efficient seamless ad buying across the glo.
49:48
If you're trying to get the attention of a CEO, maybe you want to sell some enterprise software to them.
49:53
Why not gift them a bottle of the besties? Yeah.
49:55
And that'll that'll get you a demo real quick.
49:57
I think VCs should be sending this to founders.
50:01
founders should be sending it to VCs.
50:03
It's It's a It's going to be a hot commodity if you can get your paws on one of these. Yep.
50:06
Um anyway, hims and Hers stock drops more than 30% after Novo Nordisk breakup.
50:12
This is from the Wall Street Journal.
50:15
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.
50:24
They got multi-asset investing, industryleading yields, and they're trusted by millions.
50:28
Anyway, uh the Wagui maker, that's Novon Nordisk, has cut ties with the teleahalth company hims and hers, citing allegations of deceptive marketing practices and drug compounding.
50:37
I feel like they were the drug compounding.
50:40
How is this an allegation?
50:42
I thought that's like what Hims was saying they were doing.
50:45
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 I guess it's alleged at this point. So, we'll dig into this.
50:55
Um, Novon Nordisk abruptly ended its partnership with Hims and hers after the Danish drug maker accused the teleaalth company of illegally selling cheaper copycats.
51:04
Okay, so this is after the FDA's uh ruling about uh whether or not there was in fact a shortage.
51:10
So the Novo said on Monday that it had concerns about the safety of knockoff versions of Aguvi and that Himm and Herbs deceptive marketing of such knockoffs put patient safety at risk.
51:22
In turn, hims and hers accused Novo of pressuring it to steer p to steer patients to Wagui regardless of whether or not it was the best option for patients.
51:33
News that the deal was scrapped weighed heavily on him and her shares, sending them down 32% in afternoon trading in what would be the largest decline for the stock on record.
51:43
Novo Nordisk's shares were down nearly 6% in New York.
51:45
The messy breakup comes less than two months after the companies unveiled what they called a long-term collaboration to directly provide wagui to him and hers patients.
51:55
Okay, so this was somewhat predictable, right?
51:58
Uh talked to Parker about this.
52:01
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 WGOI right now.
52:09
If you're Nova Nordisk and you're like, "Cool, we have we're selling through this channel."
52:14
But then the retailer, in this case, HIMS is telling customers as they come in, hey, we know you wanted Reggoi, but how about this sort of cheap knockoff, this compounded version, now WGOI can is probably legitimately concerned about safety issues.
52:32
There can be issues around compounding in in in drug safety.
52:37
Uh 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 uh off-the-shelf alternative?
52:48
And so I have to imagine that they this this is Nova Nordisk recognizing the value of their brand in this massive massive fast growing category and saying we're not going to let you leverage our brand to um compete on these sort of high margin you know knockoff products. Yeah.
53:06
I mean like the the Instagram ads that I saw were definitely pushing the brand name for real. Yeah.
53:13
And there was a while when they wouldn't use the term Viagra and they would use ED meds and selenophil and tadalapil and all of those 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.
53:32
Um but yeah uh the brand name how do you think will respond?
53:37
Do you think they'll introduce a 10in-one shampoo that includes compounded? Yep.
53:41
GLP1s, Viagra, hair loss. Yeah. Medication. What else could Aderal? They can put caffeine.
53:52
I mean, this is Cognizen, Rodeiola, Panax, Jensen, Altheanine, caffeine. Get some in here.
53:58
Creatine soap with creatine soap would be good with all the above.
54:05
Eli Liy is the one that lost the patent, right?
54:07
Because they forgot to pay the No, I think it was Nova Nordis. Oh, Novo. Wow.
54:12
They have They're all over the place.
54:14
It is It is interesting to watch. Yeah. Novo Nordisk.
54:17
How much do you think their stock is up over the past five years? Oo, 500%. Try 113%. 113.
54:24
But it was a big company. Yeah. Yeah. But it's been on it. Big company, but still.
54:30
And how much do you what what do you think the the chart looks like over the last year? Uh oh, it's down. The GLP1 boom.
54:34
It's down because it it ripped up so high% went down 50% and they and they uh rotated out their CEO. That's right. We covered that.
54:44
Uh hims and hers is at 9 billion 9. 66 billion.
54:47
Um that is down from a high of maybe 15 billion.
54:52
Um and it's one of those interesting like spa targets that I think they got out through a spa and they they never really went down that far.
55:01
They were down, you know, yeah, like like, you know, 30%.
55:04
I mean, they spacked at $10 a share, went down to $4 a share, kind of grinded back up.
55:13
Now they're at $40 a share.
55:13
So, if you if you bought this, if you bought the spa and you did hold for five years, you're, you know, you're sitting on a 3x, 4x, not bad.
55:22
So, you know, um kind of a narrative violation around the around the spa, like all spacks are bad narrative. Yeah. Yeah.
55:32
I mean it it and and the CEO Andrew uh Dudham, we should have him on the show said that uh uh 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 uh reasonable position to say we're not going to just sell one product uh just you know because it's true not every patient is going to respond well to WGOI. Yep.
55:58
And uh they should have options.
56:02
So before striking deals with brandame drug makers, teleaalth firms were selling lowerc cost knockoff versions of these drugs made by compoundingarmacies, taking market share away from uh brandame makers.
56:11
The compoundingies had been allowed to mass-produce knockoff versions conditionally because the original drugs were in short supply.
56:19
Now the the whole compounding pharmacy dynamic is very different because I feel like the the the laws were created such that if a far big pharmaceutical company couldn't supply you the drug like your local pharmacist could compound it but then the the these startups kind of like rolled up all the compoundingies were doing it like a much bigger scale and it wasn't exactly what was intended originally but I'm not sure about that. Yeah.
56:45
Yeah. Um so the big question uh will be more well yeah the big question what will there be more regulatory action around compounded GLP1s and what will that do to their business so roller coaster of a year for him you
57:02
know partnership wasn't uh 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
57:19
You need to go on getbzzel. com.
57:20
Your bezel concierge is available to source you any watch on the planet. Seriously, any watch.
57:25
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. Yeah.
57:33
So when you're ready to start start the bowl exactly, this is this is key. This is very very key.
57:40
Um anyway, uh comment from the uh from the CEO Andrew Dudham.
57:47
He said him and hers will continue to offer an access to a range of treatments including Wagui.
57:51
So they continue to battle it out.
57:53
It'll be interesting to follow this and we will of course be talking to Kremu about this later today.
57:59
Um there is a investing visual post here that I pulled up um about how HIMS makes money.
58:05
Uh they're making $576 million online, $10 million from wholesale.
58:11
That brings their total revenue to $586 million, which is up 111% year-over-year.
58:16
Gross profit there, $428 million.
58:22
Uh operating expenses are 337 million, leaving them 92 million in net income or 92 million in operating income and 50 million in net income.
58:31
So 50 million in net income for a $10 billion stock.
58:37
Pretty pretty high price to earnings ratio if that's their if if that's an indication of their earnings.
58:42
Um but it's been a big growth stock on a major major trend GLP1.
58:44
And so uh the the uh the the retail army has been coming out in force.
58:51
Uh King KSM's capital said it felt too good to be true for him to go this long without some FUD. This is more like it.
58:59
just bought 2,300 2,300 shares and uh top secret stock.
59:06
What do they what does the retail army call themselves? I don't know. Himmos or something. Say I'm really him. Yeah. Uh HIMS. Look at the data.
59:14
You can see uh their operating margin has improved a ton since they've gone public.
59:22
They started out at negative 40% operating margin and climbed up every single quarter. They're now at a 6. 5% operating margin.
59:29
the number of subscribers in the millions has gone from uh they were at 6 so 600,000 subscribers now they're at 2.
59:36
4 4 million and their total revenue has gone from $272 million in revenue.
59:43
Uh this is the last 12 months.
59:47
Now they're almost at 2 billion.
59:50
And so they've almost 10x revenue from that spa price.
59:52
And that's what's driving the stock overall to be up three to 4x off the original spa price. So yeah, very good news.
59:59
Uh if you're Andrew Dudham and you need a break from grinding it out at him, book a wander. Find your happy place.
1:00:07
Book a wander with inspiring summer.
1:00:10
Andrew hotel grade amenities. Dreamy beds. Top tier cleaning. 247 concier service. It's a vacation.
1:00:15
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, "Yay, take a vacation."
1:00:24
But I think it's a bad idea. Summer's long.
1:00:26
Him is up 2% today, John. You're good.
1:00:30
So, it's time to, you know, treat yourself. Yeah.
1:00:32
Take your foot off the gas. Head to wander. com.
1:00:33
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.
1:00:48
They are having difficulties obtaining vital magnets with rare earth elements despite the deal the United the United States struck.
1:00:58
And I just want to highlight I think the silhouette of this car is fantastic. the the Maki GT. You're a fan.
1:01:05
I've only owned one Ford Raptor.
1:01:05
It was a very fun uh car. Not very practical.
1:01:11
If you need to park in cities and things like that, but yeah, if you want practicality, Ford GT. Uh I took a drive. Yeah, practicality. All about the Ford GT. Um but I took a drive.
1:01:20
My buddy, uh Matt has a Ford Mustang. Uh what is it called?
1:01:27
The Mustang E Mach E Rally.
1:01:31
It's like this this rally version of the Maki. Okay.
1:01:34
So, it's still the crossover.
1:01:36
Still like an SUV, more or less. Sort of. It's like a hatchback. Um, but it's not a car.
1:01:40
Like, I would not call this a car.
1:01:42
It it is a very very cool car.
1:01:44
Um, it to him he said it's like the most fun car he's ever owned. Let's go.
1:01:49
Uh, and he's had pretty something from from pretty much every manufacturer at this point.
1:01:54
So, well, he should hold on to it because they might be struggling to make in the future going up. Yeah.
1:02:02
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.
1:02:10
A company executive said Monday.
1:02:12
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.
1:02:22
Ford in May stopped production at a vehicle factory in the Chicago area because of a magnet shortage.
1:02:26
The situation has improved, but the company still needs to move things around to avoid manufacturing shutdowns given the scarcity of the materials.
1:02:33
Drake told reporters during a briefing at an EV battery plant the company is building in Michigan.
1:02:38
China in April began requiring companies to apply for permission to export magnets with verare earth metals, including disprosium and turbium.
1:02:50
The country controls roughly 90% of the world's supply of these elements which help magnets to operate at high temperatures.
1:02:56
Much of the world's modern technology from smartphones to jet fighters rely on these magnets.
1:03:00
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.
1:03:08
Y 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.
1:03:17
So they have 90% of the mining companies, 90% of the mining equipment.
1:03:23
They don't necessarily have 90% of the actual rare earth metals in the ground.
1:03:28
And the rare earth metals are not that rare.
1:03:30
But we hear this every once in a while where we say, "Oh, like there was a ton of rare earth deposits found in Ukraine or found in America somewhere." And that's not enough.
1:03:41
Like just having them in the ground, you still have to go and dig the mine, get the approvals, make sure.
1:03:45
And the like 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.
1:03:59
Like if you want to protect the earth, moving something from one continent to another does not save the earth.
1:04:05
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.
1:04:12
But in general you've been to China, John, it is dark.
1:04:17
The sky is legitimately dark.
1:04:17
But I I think that I think that like a lot of the pollution that's going on over there is affecting us too for sure.
1:04:23
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.
1:04:33
Like I I I I I find that hard to believe.
1:04:35
It would have been much better to just focus on ramping up production in America and then actually doing the technological innovation to develop more 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.
1:04:50
Maybe maybe there's an argument for it, but it it feels like it the whole the whole offshoring project was wrapped in this veneer of like uh no hear no evil, see no evil, speak no evil, that type of vibe.
1:05:03
Like if we can't see the pollution here, it's fine. It's not happening.
1:05:06
And it's like it is still happening.
1:05:09
It's just you don't have control over it now.
1:05:13
Massive supply chain risk. Exactly.
1:05:13
And and I don't think it I don't think it actually had an impact on the like the stated goal of the environmentalists that pushed rare earth manufacturing overseas did not was not achieved and so that that feels uh like like a failure and then on top of that we lost control of this important supply chain.
1:05:33
So Ford isn't the only car maker struggling to obtain these magnets.
1:05:37
Several other car makers say that the pace of export license approvals for rare earth magnets hasn't changed significantly.
1:05:44
"It isn't quite day-to-day, but it's week to week," said an executive at one of the car makers.
1:05:48
"Uh, car companies have warned that they could be forced to halt factory work if they are unable to obtain enough rare earth magnets in the auto industry.
1:05:57
Rare earths are essential to electric vehicles because they allow a lowcost way uh to ensure motors operate at high speed."
1:06:04
Okay, so this should not affect the production of Raptor RS. Thank goodness.
1:06:09
I I was I was extremely worried.
1:06:12
But so we might have to get most of those Mache owners into Raptor RS. Okay.
1:06:17
But I don't think that's something we have to Yeah.
1:06:20
If we have to do it, we have to do it. We have to do it.
1:06:23
Uh in the auto in the auto industry, rare earths are essential to electric vehicles.
1:06:27
Uh, President Trump struck a deal earlier this month for China to resume granting licenses to export rare earth magnets.
1:06:34
The agreement, which has a six-month limit, is aimed at allowing China to retain its chokeold on the critical minerals that give it leverage in future trade negotiations.
1:06:42
So, uh, very, very rough.
1:06:45
Anyway, how'd you sleep last night? Let's pull it up.
1:06:51
Praying I got an 88, John. Oh, no. 82. There we go. You beat me. Oh, I did. Jordy's back on top. I'm back. I'm back after a while. I'm back. What happened to me?
1:07:03
I just I guess I stayed up too late or something. I was in my sweet spot.
1:07:07
Oh, I guess I didn't fall asleep until 11:12. There you go. There you go. Got to go to bed.
1:07:10
I'm back on the I'm back on the horse.
1:07:12
Yeah, I'm back on the horse.
1:07:14
It should be a competitive week.
1:07:15
I'm excited to see how it We got to start putting We got to start putting something on the line. Yeah.
1:07:20
Um, like the the loser on Friday gets no caffeine and nicotine the whole stream.
1:07:26
And they'll be sleep deprived, too.
1:07:28
That's that's double duty.
1:07:28
That's that's extra hard.
1:07:30
That would be that would be uh torture.
1:07:33
Anyway, uh our our first guest is coming in the studio in 10 minutes.
1:07:38
Let's take you through uh a beautiful obituary to the founder of FedEx, Fred Smith.
1:07:43
So, Ryan Peterson uh posted a photo of the original FedEx plane.
1:07:48
He said, "RIP to logistics legend and outspoken defender of free trade, FedEx founder Free Fred Smith, who passed away today."
1:07:56
Below is the first ever FedEx plane, which you can see at the Air Space Museum annex next to Dallas airport in Virginia. Look at that.
1:08:05
He must have been so stoked when he bought this.
1:08:07
Like his business was finally growing that he could own his own plane.
1:08:11
Imagine how many likes he would have gotten on social media posting that pick. Yeah.
1:08:14
Everyone's like, "This is you're flexing to appreciate.
1:08:19
You're just trying to go viral. This is Cluey.
1:08:23
This is Cluey for logistics.
1:08:23
This is Cluey for logistics." Um, total legend.
1:08:28
Uh, burning VC dollars on a plane bear.
1:08:32
I think he was using Vegas dollars. He was doing cash flow. Yeah.
1:08:35
Anyway, Max Meyer has a story that we should read through.
1:08:38
Um, Fred Smith and American Life.
1:08:41
He says, "Fred Smith died on Saturday.
1:08:43
He was the founder of Federal Express, which became FedEx one of the largest logistics companies on Earth.
1:08:50
Smith was an entrepreneur in the truest sense of the word, and an American patriot.
1:08:54
He bent reality and created something entirely new, and he ran toward an extremely difficult problem.
1:09:00
The fruits of Fred's work are as follows.
1:09:02
If you give a box or document to FedEx by 6 p. m.
1:09:04
, you can have it delivered almost anywhere in the United States or Canada by 8:00 a. m. the next morning.
1:09:10
Imagine how key that would have been to business before internet. Incredible. Yeah.
1:09:15
Um you're trying to do deals.
1:09:20
If you give FedEx a package on on a Monday, it can be in Paris by Wednesday morning or in Shanghai by Thursday for a few hundred.
1:09:26
Most of us take overnight delivery for granted.
1:09:28
But take a step back and the fact that we can essentially airdrop physical packages anywhere in the world is mind-boggling.
1:09:36
Smith's death is a reminder not to take the miracles of modern life for granted.
1:09:41
They were built by people like Fred Smith.
1:09:43
These are a few words about the man himself and the dazzling system that is FedEx.
1:09:47
Frederick Wallace Smith was born in 1944 in Mississippi.
1:09:50
Fred's grandfather, James Buchananith, captain Mississippi River steamboats.
1:09:55
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.
1:10:04
From steamboats to buses to jumbo jets in three generations, the family stayed on the cutting edge of motorized transportation.
1:10:11
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.
1:10:20
Within a few years, James Smith had dozens and dozens of coaches.
1:10:24
By the time he died, suddenly in 1948, he commanded over 200. Wow.
1:10:26
So he died four years after the son was born. Wow.
1:10:32
So he basically grew up without a without a or maybe that's the grandfather.
1:10:37
Um according to James Smith's obituary, um No, no, no, no. He's the dad. Yeah. Yeah.
1:10:43
So according to James Smith's obituary, um those 200 coaches each came to a halt during their regular regularly scheduled routes for one minute when the funeral began.
1:10:52
Uh, the young Fred was just four when his father died. Wow.
1:10:56
In 1962, the young Smith enrolled at Yale University where he was fraternity brothers with future President George W. Bush.
1:11:01
Bush asked Smith to serve as the Secretary of Defense twice and Smith declined twice. Wow.
1:11:07
He interesting because defense is uh who who was the founder that we had on the show.
1:11:13
I'm completely blanking on the his name, the name of the company and who invested in the company, but he had this like defense focused supply chain management startup. Yes.
1:11:22
It was one of our probably first You're talking about Rune Logistics. Rune. Yes.
1:11:26
Uh but something he said about not the AI poster. The legendary poster.
1:11:31
Not the legendary poster.
1:11:33
Uh the logistics of Open AI. Yes.
1:11:36
Uh so uh uh the young Smith was uh a member of the infamous cloak and dagger secret society.
1:11:43
He is not beating the secret society allegations.
1:11:48
Uh 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.
1:11:58
I just need somebody to build it for me. I. e.
1:11:59
that instead of point-to-point package transport everything would be brought to a single hub by air and then redistributed.
1:12:04
We talked to somebody about this on the show, how how now we think of it as like inefficient to bring everything to one place and then and then do the hub and spoke thing because now we have, you know, Door Dash and Whimo and uh you know just last mile all the all these different last mile solutions, but at the time this was revolutionary.
1:12:23
Um everything would be brought to a to a single hub.
1:12:27
Uh repeat that cycle every night while turning a profit and you have a viable system for overnight delivery.
1:12:32
The paper is said to have earned an average grade roasted.
1:12:34
Uh in 1966, the founder of FedEx graduated from Yale and volunteered to receive a commission in the Marine Corps.
1:12:43
He served two tours in Vietnam.
1:12:44
For his service in Vietnam, the President Nixon decorated Smith with a silver star and a bronze star.
1:12:52
The Silver Star citation read in part, "Unhesitatingly rushing through the intense hostile fire to position the heaviest con 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.
1:13:15
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 air strikes upon the hostile positions to within 50 meters of his own location.
1:13:31
Wow, what a and continued to direct the movement of his unit. Wow, what a badass.
1:13:35
Uh so at this point, yeah, 1973, he's 29 years old. He lost his dad at four.
1:13:40
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.
1:13:52
And now he's decided to launch Federal Express in Memphis.
1:13:55
Smith had studied military procurement and been working on the idea for nearly 10 years after writing the Yale paper.
1:14:01
So he writes this paper and he's like, "Okay, 10 years."
1:14:05
Most most founders have an idea and they pivot through two months.
1:14:09
So he writes this paper, gets an average grade 10 years later 10 years later.
1:14:12
The company launched with a fleet of 14 French to salt jets which delivered a few hundred packages on their first day of service. There we go. Wow.
1:14:21
He's just like just zero to one.
1:14:23
Um 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.
1:14:32
It is funny like that the name you would you would think Federal Express.
1:14:36
You would just assume that it's an extension of the government. I did when I was a kid.
1:14:42
I was like United Postal Service as a kid.
1:14:45
You realize United States Postal Service.
1:14:46
These are using FedEx like it was just a better product experience than USPS.
1:14:50
Even as a kid, you'd kind of feel it out. Feel it out.
1:14:53
Um the system that Smith had conceived at Yale worked.
1:14:57
It really worked and nothing like it existed.
1:14:59
The USPS existed principally to deliver letter mail and didn't have aircraft.
1:15:04
UPS was a giant of a ground delivery throughout the the US.
1:15:07
Federal Express though would specialize in rapid air delivery.
1:15:11
Just 5 years after the first Federal Express flights, the company was lift listed on the New York Stock Exchange. Wow.
1:15:17
Uh today, the FedEx fleet consists of nearly 700 aircraft and about 200,000 vehicles.
1:15:22
And FedEx employs half a million workers around the world. Wow.
1:15:27
Every night at the FedEx Super Hub at the Memphis International Airport, hundreds of jets land at the airport. Ultra Hub. The Super Hub.
1:15:33
Uh bringing packages to its many sorting machines.
1:15:39
Uh a few hours later, the jets take back off to every corner of the United States and the world at their destinations.
1:15:46
Uh 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.
1:15:55
the financial finesse needed to actually make a model like this, not just lose massive amounts of money.
1:16:04
Yeah, you could go out of business so many times.
1:16:07
Um, and yeah, there is that story about him uh almost losing money, going to Vegas, and then putting the the the Treasury on black and winning it back and doubling it and making payroll the next day, saving the company. Uh, maybe apocryphal.
1:16:22
There's been rumors that maybe it was like, you know, some mob related thing and he took a long the tin foil.
1:16:27
Yeah, the tinfoil had explanation is like, you know, he got it done.
1:16:29
He did uh some type of, you know, and this is entirely internet speculation.
1:16:35
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?
1:16:45
Um and and maybe did something else.
1:16:47
But, uh, the story is incredible and it will live on. Yeah.
1:16:52
Uh Smith retired from FedEx in 2022 after almost 50 years leading the company.
1:16:56
He has survived by nine of his 10 children and his wife Diane.
1:16:58
His daughter Winland Smith Rice died in 2005 of a terminal cardiac condition.
1:17:03
It's very sad and one has to think that his father his father Mr.
1:17:08
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.
1:17:17
So, incredible story and may he rest in peace.
1:17:22
Anyway, let's move on to the timeline.
1:17:25
Uh, also one of the greatest logos of all time, the FedEx logo has that secret arrow in it. Love that. Oh, yeah. Yeah.
1:17:32
Once you see it, you can't un not this logo, the the next logo, the more modern FedEx logo has the secret arrow in there.
1:17:40
Once you see that, they're moving. They're moving.
1:17:43
And there, if you want to understand more about Frederick Smith, go to Founders Podcast and listen to episode 151, 151 and subscribe to Arena Magag to read more of Max's writing. Check it out. arenaag. com.
1:17:59
Um, what what else is We have a post here from Gav Vora.
1:18:02
He says, "Chat, remind me to check this again in a year."
1:18:07
I wonder if he's saying he's throwing it in chat and saying, you know, check this again in a year. This is a graph.
1:18:13
It'll be kind of hard to read, but it's showing chat bots versus search engines.
1:18:17
Who's winning the traffic war?
1:18:19
Showing that Google is getting 1.
1:18:23
6 trillion total visits to chat GPT's half uh 50 billion basically.
1:18:31
So Google Google is down 1.
1:18:31
4% 4% yearover-year and chat GPT is up 67%.
1:18:38
Um, yeah, I mean it's a 34x gap today.
1:18:43
Yeah, AI chatbots drew 55.
1:18:43
Is Isn't that wild though? Yeah.
1:18:47
So, I wonder Open AI accounts for out of 55 billion visits, OpenAI accounts for 47. 7 billion. Yeah.
1:18:57
So, users 81% of all chat bots is Open AI.
1:19:00
I feel like it's even higher now, but it's crazy.
1:19:01
So, so AI chat bots are 2.
1:19:04
96 of search engine traffic today.
1:19:04
Uh, Veravv is calling it or wants to check back in a year. Yep.
1:19:11
It's very possible we could see D double digit search engine traffic into chat bots.
1:19:15
Yeah, I 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.
1:19:29
I will use Google as a calculator, but and I won't go to chat for that.
1:19:33
If I just have to multiply two numbers together, I'll just throw that in.
1:19:36
Oh, you're not a power user.
1:19:36
No, it's a it's it's faster.
1:19:38
It's it's all about speed. Believe in AI. Exactly.
1:19:40
Um I'm still like checking out this whole AI thing.
1:19:46
Starting to learn about it.
1:19:48
But um but yeah, I I think the more relevant metric is actually uh total user minutes.
1:19:52
like how much mind share is going on because when I'm in I'm probably in chat GPT longer than I'm in Google but I might be hitting more page views on Google than chat GPT queries because I might I might throw a deep research query and then spend 10 minutes reading it.
1:20:07
I'm very rarely throwing a Google search out and then reading the blue links for 10 minutes.
1:20:12
That's just not how it works.
1:20:14
So anyway, also interesting to think about how they're counting visits, right?
1:20:17
you're having this conversation with Chad GBT where often times you're repeatedly running new new hits right against Google.
1:20:23
So anyway, we have our first guest in the studio, Kremx. Welcome to the stream.
1:20:33
There he is looking handsome as ever.
1:20:36
How you guys How you doing? Doing well. Can you hear me?
1:20:39
Yeah, we can hear you fine. Um, perfect.
1:20:41
I'm I'm I'm looking forward to uh to you know a future date when we can potentially see your face.
1:20:49
Um but for now your avatar looks great soon. Okay.
1:20:52
I'm looking forward to it.
1:20:53
Um we wanted to have you on to chat about a couple things.
1:20:56
Uh what's going on GLP1 world reaction to the hims and herm hers breakup.
1:21:00
Uh Jordy, where would you like to start?
1:21:04
Uh highlevel update on the GLP1 market.
1:21:10
Yeah, I guess uh I mean it's this miracle drug that keeps on we keep on learning about new uh new diseases or problems that it can treat.
1:21:18
It seems like it can't just stop.
1:21:20
We got the diabetes, then weight loss, then maybe gambling addiction and other stuff.
1:21:26
Well, walk us through where how people are using or how doctors are prescribing GLP1s for various uh conditions and what's most promising, what's on the horizon, and what you're tracking next. Yeah. Yeah.
1:21:37
So, 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.
1:21:47
They are just talking about all the latest advances.
1:21:49
Uh just yesterday, Amjen showed off a once monthly instead of once weekly injectable.
1:21:55
Um Eli Liy showed off an amazing combo therapy with a an inhibitor called uh Bimaguma.
1:22:01
It's a very weird name that makes people not lose any muscle when they're on the drugs.
1:22:07
Um, they've been showing off just incredible advances all week.
1:22:10
They've been showing off new treatments uh for like different conditions and whatnot.
1:22:15
There are increasingly many indications that these drugs are getting approved for.
1:22:18
In December, Tzepide was approved for sleep apnea.
1:22:21
Um, there's osteoarthritis indications incoming.
1:22:25
Um there might even be there's some effort being put into people trying to uh 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.
1:22:46
Um why do you think that is? I have some guesses.
1:22:53
I think the big reason has to do less with the direct effects of GLP-1s and more with the fact that obesity sucks.
1:23:01
Uh, obesity is just really, really bad.
1:23:04
It affects so many different systems.
1:23:04
It makes your health worse on so many different levels.
1:23:08
And the things that lead to obesity are also quite bad, like the bad diet, the bad habits, the uh not moving around very much.
1:23:15
It's actually interesting.
1:23:17
A lot of people after they've been on these drugs for a little while, they decide to move around more.
1:23:23
They become more likely to go to the gym.
1:23:24
They report that their physical functioning is improved.
1:23:26
Uh it turns out that getting fat has made them get to the point where they are no longer looking to be active.
1:23:32
And so they just kind of fall into a hole.
1:23:37
Practically everything is improved I think for that reason.
1:23:38
And there are some improvements that are due to direct effects of the drugs.
1:23:44
Uh this has like for example this one is major adverse cardiac events major cardiovascular events.
1:23:50
Um 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.
1:24:00
So that seems to be how that works.
1:24:04
Same with chronic kidney disease.
1:24:05
Are you looking are you looking um 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.
1:24:15
Do you think that could be a factor and why it should could show some promise in in treating various types of cancers?
1:24:26
Yeah, I I think it does makes a lot of sense in that direction for uh the obesity related ones, but I don't think it makes sense.
1:24:32
So years ago there were people who suggested I think quite wrongly replacing certain cancer therapies with fasting because it seems to like uh augment the effects of sysplatin based therapies and stuff and that didn't really hold up very well.
1:24:45
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.
1:24:54
Um I really think it's mostly just cutting down on for example the number of cells you have or well not really the number of cells you have but uh like the activity of being fat.
1:25:02
It's just you have you're not as big of a person.
1:25:06
You have less to less opportunity for cancer to really hit you when you are smaller. Yeah. Smaller.
1:25:13
It's like how short people tend to live longer of everything else. Bad for me. Yeah. Bad for you. Bearish for me.
1:25:21
Um well ho how much of the recent uh like advances in GLP-1 indications or or recent like benefits have been uh 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 uh the drug versus a new double-blinded trial for a different indication.
1:25:47
Are both things happening or or is it is are are these drugs diffuse enough that you can just look at the overall population and get an idea of what's happening? Yeah.
1:25:58
So for approved indicate FDA approved indications like obstructive sleep apnnea, you do have to run additional trials, but they are seeing that these things are possible from their trials.
1:26:06
They're seeing the these things are possible from the literature and they're running based on that.
1:26:09
So um in some cases they do see these secondary end points.
1:26:12
In fact, obesity is an example of this.
1:26:14
Back in the day when they first introduced these drugs uh back around 2005 or so the CEO of Nova Nordisk at the time actually said and I quote obesity is primarily a social and cultural problem.
1:26:25
It should be solved by team by means of a radical restructuring of society.
1:26:29
There is no business for Novon Nordisk in that area referring to obesity. Wow. Yeah.
1:26:34
So they their scientists had to push for about a decade to go hey you should look at the weight loss data. It's really impressive.
1:26:42
And then they finally finally did it and now we have weight loss drugs.
1:26:48
Yeah, that is that is wild.
1:26:51
Um what uh what concerns you? What's the catch?
1:26:54
Seems uh you know uh somebody too good to be true.
1:26:59
Yeah, somebody might say is it too good to be true?
1:27:00
We're running this sort of massive uh experiment on huge swaths of the population right now.
1:27:06
seems to be, you know, many many positive indicators, but uh what are what are kind of red flags that you think uh people should be kind of looking out for or or the scientific community uh should be wary of broadly from your point? Yeah.
1:27:22
So, I think that physicians need to be careful about prescription. Uh and they already are.
1:27:27
they already are. are they like they don't tend to prescribe this to people who are very skinny but the fact that this stuff is available through the gray market um very easily without prescription for very very cheap uh unfortunately I've contributed to that
1:27:39
um has led to a lot 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 uh all the details on it and now I have a few thousand people who unprompted I didn't tell them to do this messaged me their weight loss progress and such. So, uh,
1:27:58
So, uh, through writing this guide a few months ago, I've led to almost 12,000 pounds of weight loss.
1:28:06
And that's just what's been reported to me.
1:28:07
Not everybody's telling me all the results.
1:28:08
And is that is that at a high level?
1:28:11
People just finding uharmacies that will compound the drug for them.
1:28:15
What What does that actually look like?
1:28:18
So, what it looks like is buying from China.
1:28:20
So, you are ordering from a Chinese factory.
1:28:22
you are uh testing the purity of the stuff and finding oh it's 99.
1:28:27
9% I can use it and then using all of that uh it is not sold by Nova Nordisk Eli Liy 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 I we've been seeing that kind of go back and forth like him and hers was able to compound because there's a shortage that news about Eli and say hey can you knock this off. Yeah.
1:28:53
I mean, they could do import bans or or or seize the packages at the ports.
1:28:58
Like, that's the design of this.
1:28:59
You can't just buy a knockoff iPhone and have it delivered through the port of Los Angeles.
1:29:03
Like, if a whole truckload comes through, they should stop that, but it's clearly not happening.
1:29:08
So, right now, the FDA allows this to happen because they have an exemption for research chemicals.
1:29:12
You're technically not supposed to use these things, but everybody knows that everybody uses them. It's just how it is.
1:29:20
They're researching weight loss on researching kind of one.
1:29:23
I'm research research maxing.
1:29:27
Um so you were saying the the uh the potential uh red flags or or things to be wary of is around uh what what about uh the prescription activity concerns you?
1:29:37
Mostly abuse uh not not really prescription activity as so much as the abuse.
1:29:42
There are people who are obtaining these drugs.
1:29:43
There are people who are getting other people to get the prescriptions.
1:29:46
There are people who are not really visiting doctors.
1:29:47
They're using teley health services to get prescriptions.
1:29:49
and they are not in need of them.
1:29:52
But why would someone abuse this?
1:29:53
This doesn't feel like something that has like the euphoria associated with a stimulant.
1:29:58
So the concern I think would be testosterone body dysmorphia.
1:30:02
There are going really skinny unfortunately.
1:30:05
I've met a few dozen women now who have taken these drugs and been around 120 130 lbs normal height.
1:30:13
Uh and now they're around 100 and they are they don't look good anymore.
1:30:15
They look like they're aging very quickly.
1:30:18
They look uh 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.
1:30:23
The same negative effects of of start actual starvation. Yeah. Yeah. Yeah.
1:30:27
You start getting really bad harmful effects.
1:30:29
You probably are eating at that point more lean mass than fat mass. It is uh quite bad. Yep. Yep. That makes sense. Yeah. That's always the risk. Interesting.
1:30:37
Um how are you what was your reaction to the HIMS Nova Nordisk uh partnership blow up?
1:30:45
So, I actually think this was a big failure on Nova Notice part.
1:30:47
It seems as though what they did was they partnered with HIMS in order to catch them.
1:30:51
Um, 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 uh interesting.
1:31:01
I guess we'll get more details relatively soon if the laws all theoretically WGOI gives them a million doses and then HIMS is somehow selling 1. 2 million doses of WGOI.
1:31:10
Is that is that what you're Yeah, something like that.
1:31:14
They're either compounding themselves or ordering from something from China.
1:31:16
They are doing something and uh I don't know if that will hold up or show up in trial. It's an accusation.
1:31:21
Um it's so I guess it's alleged, but we we'll see. We'll see.
1:31:26
What about what about HIMS's general position that patients should have as much choice as possible uh as much access you know access at different price points things like that.
1:31:38
They are completely correct to do that.
1:31:40
I think that him providing different dosages than are provided by Novanorisk is a wonderful thing.
1:31:45
There are people who can get legitimate uses out of um sort of micro doing this stuff because it gets rid of noise.
1:31:52
I've met many many people now and this is uh an increasingly common thing.
1:31:56
It seems I I really don't know uh how far this is going to go but a lot of people who are micro doing this because it helps with their ADHD.
1:32:03
Their ADHD is like the pathological end of foodbased distraction.
1:32:07
They're not losing weight from this anymore, but they are just using it in order to not think about food at all.
1:32:13
It gets rid of that nagging feeling in the back of their head, and they can focus on I I did a 24-hour uh dry fast uh from Friday night to Saturday night. Yeah.
1:32:23
And all day Saturday, I was shocked at how much time my I was just thinking about food and water, wanting food and water.
1:32:31
Uh, and I was and and it was very freeing to some degree because I was like, well, I'm not just not having any until around dinner time.
1:32:39
But so many points throughout the day, my mind was just going to, oh, I should go get a little tasty drink from the fridge.
1:32:45
I should, you know, I should I'm not addicted. I'm not addicted.
1:32:47
I'm not addicted to water.
1:32:48
I'm not addicted to water.
1:32:50
I'm not beating the water addiction allegations. Big water guy.
1:32:54
Um, what what else are you tracking right now broadly?
1:32:56
Uh, any reactions to the NIH funding? Oh, yeah. 40%.
1:32:59
Uh we had Andrew Humemerman on the show.
1:33:02
He was breaking it down for us and what's going on with Jay Badacharia.
1:33:05
Uh what's your take on the cuts that have been proposed?
1:33:09
So I don't know how much I should reveal about that.
1:33:11
There's a lot of really good things coming.
1:33:12
Uh there might be some interesting developments there very soon.
1:33:19
I'm especially hopeful about Well, you know, actually I shouldn't say that.
1:33:24
Uh just there there will be good news there soon.
1:33:25
Um there'll be a some changes.
1:33:29
Uh I'm not going to say Yeah. Yeah.
1:33:30
I guess zooming out like what what does good look like to you?
1:33:33
Are you generally in favor of taxpayer funded?
1:33:39
Every American gets a $10,000 biohacking budget annually.
1:33:42
They can buy research chemicals biohacking vouchers. Yeah.
1:33:47
I mean, some people would say like, you know, the the big pharma companies are profitable.
1:33:51
They should bear this expense, not the American.
1:33:54
So, they're not profitable enough.
1:33:57
Um they have troubles with R&D.
1:34:00
uh that public money is very very useful.
1:34:02
We need more public funding than we currently have. Yeah.
1:34:05
When you actually look at biotech returns, you know, just looking at the asset class, the logical thing to do would just be to invest elsewhere and that that was with historical levels of public funding uh that that kind of contributed to those returns to some degree.
1:34:21
Yeah, we have a deer of funding at the moment and we need to increase it.
1:34:26
We need to improve the allocation and also increase the amount.
1:34:29
There's really no way around it.
1:34:31
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.
1:34:35
Um these cuts are a little alarming to start, but they are not the end of the discussion.
1:34:39
Remember, we are it's still only 5 months into this presidency and they have a lot of really big plans.
1:34:46
They have a lot of trouble getting appointees through the Senate and they have a hiring freeze ongoing right now that is uh interminable.
1:34:52
We don't know when it's going to end, but once that is over, they'll be issuing NPRMs left and right.
1:34:59
It's going to be uh deregulatory on like massacre.
1:35:03
It's going to be wonderful. Wow.
1:35:05
Well, that's what else is exciting to you in uh biotech right now in Well, I wanted to say on the HMS 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.
1:35:21
Like they're very smart people, but they're just total idiots.
1:35:26
They Hey, everybody misses a the the patent.
1:35:28
You know what do they do? They they forget.
1:35:31
I think Eli Liy, but uh they This is Nova.
1:35:33
Oh, those Novo that lost the the the patent uh fee.
1:35:38
Yeah, they just they forgot to pay the bill. 450 bucks or something?
1:35:43
Yes, it was 250 and then they missed it and they were told you're one year out.
1:35:46
You had can pay a late fee like an extra $200 late fee on it and they just didn't. They still failed. Yes, it is amazing. That's wonderful.
1:35:53
So, uh that enables a wonderful wonderful program that the FDA should pursue immediately.
1:36:01
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 produced in Canada um and has like an indication of proof here and whatnot uh as they want to reduce costs.
1:36:20
So, for example, Florida will whenever they get this actually going have much cheaper EpiPens.
1:36:27
They'll be able to lower the cost of their drugs by importing cheap generics from Canada.
1:36:30
And because cheap generic Ozmpic is going to be coming from Canada in 2026, every state can just jump on the program.
1:36:38
And if we're giving people if we're giving Americans $5 a week oimpic, then we're going to see perhaps an end to the chronic disease crisis.
1:36:48
We're going to see obesity tackled meaningfully.
1:36:50
We're going to see people getting hot again and make America hot again. The real meaning of aa.
1:36:56
The real meaning of a real meaning of There we go. There we go. Inside baseball. Amazing. Very exciting.
1:37:04
Well, 15 minutes was not enough time to have you back on again soon.
1:37:08
Uh thank you for uh thank you for all the insights. Yeah. Thanks for coming on.
1:37:11
We'll we'll we'll have you back on soon. This is great. Absolutely.
1:37:15
And if you dox yourself anywhere other than here, we will be very upset.
1:37:17
So, might have to Sorry, guys.
1:37:22
You guys have a good one. We'll talk to you soon. Bye.
1:37:24
Um, next up we have Clement from Hugging Face coming into the studio.
1:37:29
I believe he's here already.
1:37:31
Very excited to talk to him. Fascinating business.
1:37:33
We'll dig into artificial intelligence, open source, everything that's going on with What is the origin of the name Hugging Face?
1:37:41
What is artificial intelligence?
1:37:41
It's the It's the emoji, I believe. Yes. What is going on? How you doing? Welcome.
1:37:48
Hey, that's the emoji like that. The hugging face emoji. Yeah. Yeah. Yeah. But come on.
1:37:51
You guys are giving me [ __ ] about the name with a name like that.
1:37:55
TBPN much better than Pugging Face.
1:37:55
I'm not giving I'm not giving you [ __ ] I just I just read and then I just immediately see the the obviously the icon.
1:38:03
But there's there's more to the name than that.
1:38:05
It it it 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. Yeah.
1:38:13
When we started the company eight years ago, we were building some sort of an Tamagotchi AI AI girlfriend Chad GPT before Chad GPT. There you go.
1:38:22
So, very much kind of like an entertainment uh product.
1:38:24
And so, uh we picked the hugging face emoji because that's the one that we were using the most. Yep.
1:38:30
We also had in this joke that we wanted to be the first company to go public with an emoji instead of the threeletter ticker, you know, like on the on the NASDAQ. Yep.
1:38:38
Um still still fingers crossed for that.
1:38:41
I hope nobody's going to go public with an emoji before us and that they'll wait for us. Yeah.
1:38:46
And then the community just loved it and started to put it everywhere.
1:38:50
Put it on their on their clothes, on their on social networks, everywhere.
1:38:55
So, we decided to keep it. Yeah.
1:38:57
The the the owning an emoji as a brand online, I think, is still under underrated strategy.
1:39:02
We see it every once in a while.
1:39:04
I've seen people use the the the the different fruit emojis for different things.
1:39:08
And there was a whole strawberry story tied to OpenAI and stuff.
1:39:13
Um, but when you can condense down, I mean, it's a it's a coinage essentially, like when you can own an emoji and have it say something, uh, that's very powerful from a branding perspective. Yeah.
1:39:21
You can even search with an emoji on on Google and the app store directly with the hugging face emoji. Yeah.
1:39:27
I mean, you're going to compete with the people that use the emojis for any other reason.
1:39:29
And there's always the risk that somebody steals.
1:39:31
I bet I think Yeah, I think if you search the hugging face emoji, you're going to you're going to wind up in the right place.
1:39:38
Um, but walk me through the business today.
1:39:40
How how how what give me an idea of the scale and kind of the core business model. Yeah.
1:39:44
So um we're one of the most used platform for AI builders.
1:39:50
We just crossed actually today 10 million AI builders using us.
1:39:52
So it's mostly AI scientists.
1:39:57
Congratulations 10 million.
1:39:59
That's 10 million AI builders.
1:40:03
So it's mostly AI scientists.
1:40:06
um AI engineers, software engineers, uh building models, training models, optimizing models, sharing models, data sets, apps.
1:40:14
So there's a new new repository.
1:40:16
So it's model, data sets, apps created on hugging face every 10 seconds now. Wow.
1:40:21
Um and and the way the way we monetize because we 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.
1:40:39
So for example, enterprise features when like a big company like Google, like Nvidia are using us, obviously they need user management, security stuff like that or when they need premium uh compute, right?
1:40:49
So when they need more powerful GPUs or or hardware to to run some of the stuff they're doing on the platform, yeah, 10 million AI developers, if you paid each one hundred million, which seems like the going rate these days, it's a quadrillion dollars. It's a lot of money.
1:41:06
But all even even if you're paying reasonable rates, you're still up in the in the in the trillions of dollars for the total market.
1:41:12
Uh I I mean I would be interested to get your reaction.
1:41:16
Uh how have you been processing the news that the 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.
1:41:29
Uh like do you think this makes sense given where we are in the cycle?
1:41:34
What has been your take overall?
1:41:36
Yeah, it's definitely harder than it's ever been because when the CEO of OpenAI is saying that an other company is paying more to get OpenAI employees, it's really like here is the top because historically obviously they've been kind of like the highest paying u company ever in terms of of packages.
1:41:56
So when when when he's saying that they're getting um beaten uh on on packages is quite quite phenomenal.
1:42:05
Um you know I hope it's not going to continue too long and there's going to be more kind of like a almost democratization of skills of uh of AI building.
1:42:16
Otherwise I think we'll end up in a quite quite weird world.
1:42:18
One of my biggest focus is kind of like how to fight concentration of power, concentration of skills, concentrations of resources in AI.
1:42:27
Um, and and I hope we can progressively move into a world where everyone can build AI and not just kind of like a few hundreds AI scientists.
1:42:37
That that' be that'd be really great for me.
1:42:39
What is your interaction today with the various um prompt to code tools?
1:42:45
What are you most excited about?
1:42:48
you know what what is that space because that that feels like kind of the the entry point.
1:42:51
Somebody comes in and they they making software for the first time and that can be maybe a gateway into exploring the whole ecosystem of of hugging face and everything there.
1:43:02
It's super exciting right to empower more people to be to be builders.
1:43:07
builders. We actually released last week our MCT that is integrated into into code uh into into chat GPT that they they announced actually I think a few days few days ago um into codeex um into cursor um so we integrated with with all
1:43:25
of these with like a specific focus which is not only to empower people to build like website or simple apps kind of like the previous generation of of apps but trying to empower everyone to actually build uh AI models, right? Which becomes really really exciting
1:43:40
Which becomes really really exciting because uh it means that maybe everyone can start training optimizing their own model that then they use themselves on their interface to kind of like keep building even more.
1:43:51
So that's when you start to have kind of like maybe this flywheel uh in terms of AI AI progress.
1:43:57
Uh so that's kind of like our focus with the integration of hugging face MCPS with a lot of these tools.
1:44:01
on the open- source question kind of like the decentralization of power.
1:44:05
Uh what was your interpretation of the anthropic news today that uh it was in fact fair use for them to train their models on it was several hundred thousand books or several million 7 million books.
1:44:18
Um I was kind of you know uh optimistic that that would happen but also just uh it seemed like we clearly needed some sort of legal uh ruling here to understand this stuff.
1:44:30
But but how did you process it?
1:44:32
Were you happy the with the result?
1:44:34
Yeah, I think this is good news.
1:44:34
Uh obviously I think this this ruling they'll come uh and be different and specific depending on the use cases 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. Yeah.
1:44:53
Um what's been cool for for open source is that I think by default open source is fair use.
1:44:57
So when someone releases kind of like a data set on hugging face uh in my opinion it's it's usually fair use because it's used for educational for progress.
1:45:06
If you look at kind of like when copyright was invented and and designed uh the main focus was not to prevent progress and learning right and education.
1:45:18
You don't want to put like copyright rules that are limiting progress.
1:45:23
And so I think in in open source most of the time when you release models or data sets in open source it's it's fair use.
1:45:28
So hopefully that's 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 uh do it a little bit more because I think we really need it now.
1:45:44
I don't know if you you've seen yesterday the the conference from Dan from semi analysis talking about kind of like the energy limitations in the US compared to China. Yeah.
1:45:56
Something interesting there is that in addition to that um we're mutualizing way less in the US than in China because in the US most of the leading puncher labs are propriatory and so they all do the same training runs. Oh, interesting.
1:46:13
If you think of it, right?
1:46:13
If you think of entropic, open AAI, XAI, they all do the almost the exact same million dollar training runs. Yeah.
1:46:21
Whereas in China, they're much more open, right?
1:46:24
Deepseek, for example, and so they mutualize compute and energy much much more.
1:46:29
So it's not only that they have more capacity, but also they use this capacity much better.
1:46:35
Um, so I think it's it's urgent that in the US we kind of like find find solutions for for that.
1:46:42
Um, not to create additional risks for the development of of AI in the US. Yeah. Yeah.
1:46:48
It's kind of oddly become more monopolistic over there or something like that.
1:46:52
It's it's kind of an odd odd outcome, but I that certainly makes a lot of sense.
1:46:56
Um on the on the training data sets that go out.
1:46:58
What are you seeing on the video frontier?
1:47:00
Um, 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.
1:47:13
Uh, you know, you talk about 7,000 books.
1:47:15
You can probably download that on a torrent somewhere if you're creative enough.
1:47:20
Uh, you might be able to scrape it onto a single hard drive.
1:47:24
We've heard about folks putting training data on hard drives, flying to Malaysia, doing a training run, flying back.
1:47:29
Uh, you think about GitHub, all the code's basically been stolen at this point. Like, it's out there.
1:47:35
Some of it's open source, some of it's been, you know, it's it's obtainable.
1:47:39
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 like that.
1:47:51
So, what are you seeing on the on the video training side in open source, closed source?
1:47:56
How do you think that submarket plays out in artificial intelligence?
1:48:03
An interesting data point there is that on on hugging phase, there's almost half a million open data sets. Mh.
1:48:07
Uh with a thousand new data sets added every day.
1:48:13
And the fastest growing category is video data sets.
1:48:15
Uh and the reason why is because not only uh it's more of the focus for for training but also because I think we're starting to see more and more synthetic data sets uh on video that are starting to really work. Yep.
1:48:27
U because especially because the physics is starting to work on a lot of these uh video generation tools.
1:48:34
Um it's not only used to create other uh video generation models, but it's also starting to be used for example in uh robotics that we also starting to see quite quite a a strong growth to kind of like almost use uh the physics of the video as kind of like synthetic training to train robots, right?
1:48:57
I think it's Musk who said a few weeks ago like oh in the future we'll basically put a robot in front of a laptop watching YouTube videos maybe could watch like shows like like yours and basically learn learn from that.
1:49:07
Uh so it's exciting that maybe seeing this kind of like intersection of like video and robotics that that might lead to kind of like some interesting results in the in the future.
1:49:17
They might be watching already. Who knows?
1:49:19
Um, on on the video, I want to stay on the video training side.
1:49:24
Uh, what makes for a great uh open-source video training data set?
1:49:29
Um, uh, I'm 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.
1:49:43
I'm familiar with what that process looks like in the RLHF world, in the LLM world.
1:49:48
You know, you're basically creating rubrics for grading answers to clear questions.
1:49:52
Does this follow the right format?
1:49:54
And then you might have the customer or the user give a thumbs up, thumbs down.
1:49:58
Did this answer my question?
1:50:00
Um, in 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?
1:50:11
The physics thing seems harder to define.
1:50:13
Um, basically my question is just what what what makes for a great video data set?
1:50:17
I think it's still an open question.
1:50:20
Um I think nobody really knows because it's quite quite early.
1:50:23
knows because it's quite quite early. uh and at the early days of cycles like that uh you usually don't care so much about the quality of the data but the quantity of the data right so I would say that what makes a great video data set today is its size right is for it
1:50:39
for it to be big but progressively similarly to what we've seen in text u as you're going going to start to see more specific use cases uh specialized models when you're going to start to hit some sort of a wall on the data you start to focus more on the quality of the data set and then we'll we'll learn how to how to make them better. Um, one
1:50:58
Um, one one thing that we're seeing on hugging face which is quite uh uh maybe not controversial but counterintuitive is that actually uh 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 set and dozen models.
1:51:15
there'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, right?
1:51:32
Like every company, every use case has its own kind of like specialized customized code repository.
1:51:38
Uh one thing that we believe is that ultimately there's going to be uh millions of different models, millions of different data sets and every single use case is going to be optimized, customized for its uh own use case.
1:51:50
Yeah, I I feel like there's a little bit of tension there though between like if scale matters on the data sense side, how are you possibly betting on thousands of small open-source data sets versus Instagram, YouTube?
1:52:02
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.
1:52:20
Yeah, in my mind it's kind of like a timing thing.
1:52:22
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.
1:52:31
matter. Yep. But progressively as as you want to optimize more for example when you want to optimize for cost 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
1:52:46
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 you know my bank accounts and so I can use kind of like a smaller more customized model so I think you'll
1:53:01
see both phases in video a little bit the same way that you've seen both phases in in text where you started by the biggest models and now open AI or entropic when they release model they don't really actually talk about the size of their models anymore and I
1:53:16
wouldn't be surprised if actually behind the hood actually the size is going down because I think at at some point you start to want kind of like a optimized customized and that's when you start to see more models more diversity uh also of the data sets. Yeah, this is the
1:53:31
Yeah, this is the information efficiency thing.
1:53:33
Like a human doesn't need a trillion hours of training to learn how to speak English.
1:53:41
A kid can learn that in a couple years.
1:53:43
Um, and so the algorithms eventually will will get there.
1:53:45
Jord, do you have a question?
1:53:46
Um, George Hotz was on the show last week talking about how he's been seeing venturebacked founders uh want to just check the open source box and basically say like, "Oh yeah, we're we're open source."
1:53:58
just kind of because that's the cool thing to be.
1:54:00
Are are you seeing that too?
1:54:03
Where do you think the line is?
1:54:06
Are you a beneficiary of that? Yeah. Yeah.
1:54:09
Yeah, we're seeing that even though uh you know I think I think there's still a way a way to go especially for like big uh US tech companies.
1:54:20
companies. I think if if you look so I've been I've been in I for eight years now and if you look at the cycle like 2016 to like 2021 2022 like the big tech companies in the US they were doing so much more open science open source and uh in many ways
1:54:37
that's how uh the US got the leadership you know because you know Google releasing transformers and then the t of transformers becoming chat GPT and and kind of like building on top of each other that's how you accelerate uh the progress and kind of like building on top of each others. Um it has kind of
1:54:54
Um it has kind of like definitely slowed down if you look at the big tech companies in the US.
1:54:59
Uh but fortunately I think startups are kind of like uh compensating and and filling the voids in a way and um and I hope that you know big AI uh companies in the US also will change a little bit evolve a little bit.
1:55:16
uh open AI obviously Samman said that they would release an open source model at some point so excited about that.
1:55:22
What are your expectations for that model?
1:55:24
Do you have any predictions?
1:55:26
Uh my expectations are quite high uh just because of the history of OpenAI right when they tend to release something they tend to release something uh quite quite good.
1:55:37
Um, so I I hope and I suspect that they could uh release something quite transformational u in the uh in open source.
1:55:44
Hopefully uh you know I' I've always said that you know if we had like the equivalent of a deepseek but in the US it could be 10 times bigger than than deepseek.
1:55:54
So hopefully uh you know if we can have something 10 times better bigger more impactful than deepseek would be it would be fun I guess. Is that not Meta Lama?
1:56:07
What do you how do you describe what's going on at Meta right now? Yeah.
1:56:13
Well, I mean, um, it's it's easy to dunk on on Meta, right?
1:56:15
But, uh, I I think they they're the most open, uh, big technology company in the US right now.
1:56:24
They really changed the field with with Lama.
1:56:25
they really kind of like uh boost gave a tremendous boost to kind of like the open source community and and they still share a lot of their things in open source.
1:56:34
I think open source is what uh brought them to the frontier, right?
1:56:39
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. Uh which which is great.
1:56:48
The fact that they, you know, haven't released something uh massive uh as a follow-up yet to me uh shows how hard it is to build at the frontier, right?
1:57:01
It's it's not easy even for a big technology company like like Meta.
1:57:02
Um and so I think that that speaks to to that.
1:57:08
I'm excited to see all their new efforts, all the resources they're investing in in AI right now and hope that they can keep sharing with the community and open science and open source.
1:57:18
Uh what was your reaction to Apple's announcements at WWDC around ondevice intelligence or or inference?
1:57:27
Was that exciting to you?
1:57:27
Do you think that's going to be a catalyst for more developer activity or and what what are you seeing so far?
1:57:34
I think it's it's quite quite early.
1:57:37
Uh but uh but quite excited about on device.
1:57:40
Um I I suspect that maybe um you'll have a higher percentage of compute on device for AI than you did for software.
1:57:48
Uh just because of some of the need for uh for speed uh for privacy.
1:57:58
um and uh the constraints in terms of cost right if you think of you know chat GPT on device uh what's amazing is that it's totally free right like you don't compared to the really high cost that the chat GPT has right now not only for the customers but also for OpenAI to to run uh it's totally private in the sense that you can say anything and and nobody's going to see uh what what you what you're seeing and and potentially could be quite fast.
1:58:26
So, I'm excited about on device.
1:58:29
It's it's early, especially in the technology side.
1:58:32
I think there aren't a lot of ondevice devices that really uh um make it okay to to run some of the great uh models.
1:58:43
But, uh it's progressing really fast and and can't wait to see what's happening in this domain in the next few months.
1:58:50
That's a pretty huge switch because it's basically 0% on device right now for AI inference.
1:58:54
And if you're predicting that it's going to go beyond 50%, that's a huge that's a huge shift.
1:58:58
Uh I mean I have a follow excited about robotics too.
1:59:03
It's kind of like a little bit of a segue from uh from um from one device, but um we uh we we organized a weekend ago um what has uh turned out to be the the biggest uh hackathon for uh open robotics that thousands of people participated in from uh over 100 different locations um and built kind of like open source robots.
1:59:28
And we're definitely kind of like seeing something happening there.
1:59:32
Kind of like the conjunction of like cheap cheap hardware open source plus kind of like new capabilities for for AI could be kind of like the perfect combination for some sort of Chad GPT moment for robotics.
1:59:44
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 core bots that you know will pick up a single leaf at a time and are more use case specific?
2:00:00
Are we going straight to generalizable?
2:00:01
Because that was the chat GPT moment.
2:00:03
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.
2:00:14
Chhat GBT was very broad.
2:00:16
Which one do you think is coming first and what are the relative timelines? It's a good question.
2:00:21
I'm not sure to be honest.
2:00:23
I think it's still undecided. Yeah.
2:00:25
I hope it's more future of more like a diverse uh robots, diverse kind of like models.
2:00:32
Uh, but I'm obviously kind of like biased on on this uh because I think if you only have like one type of blackbox robot uh at your home uh that's kind of like in like millions of uh houses is kind of like a scary uh scary world, but uh but it's it's hard to tell.
2:00:54
It's hard to tell at the moment, I think.
2:00:57
Uh what are uh key breakthroughs that you're looking for this year?
2:01:01
any any kind of predictions uh new catalysts that kind of thing.
2:01:05
You have a crystal ball in the office.
2:01:09
I wish I wish I had a a crystal ball crystal ball.
2:01:12
Um I'm kind of like bored with uh text and and chat bots. Sure.
2:01:14
Uh right now I think there are a lot of people working on it and we've kind of like uh reached this point where it's a very Don't say plateau. Don't say plate.
2:01:26
No, not plateau, but incremental, very incremental improvements that uh are a little bit boring.
2:01:31
So, I'm much more excited.
2:01:33
We can still invest billions of dollars in it, right? Right. It's fine.
2:01:37
We can definitely still deploy. Yeah. Yeah.
2:01:39
So, I'm more excited about harder domains like you were talking about biotech just before. Yeah. Biology, chemistry.
2:01:48
Uh these domains are super exciting.
2:01:50
Uh today um I don't know if you've seen Arc Institute released um a cell uh um perturbation uh prediction model on on hugging face and on on GitHub um which I'm super excited about.
2:02:07
I think it's uh 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 uh drug design and and things like that.
2:02:20
So really excited about these kinds of things more kind of like biology chemistry and and how to apply AI there.
2:02:30
Um what how much economic value do agents create at internally at hugging face? monthly basis. Um quite a lot.
2:02:41
Um the so we have this thing called spaces which is uh our kind of like AI app store uh where is like over half a million uh open AI apps that uh that people are are building.
2:02:57
Uh and it's integrated with our NCP framework.
2:02:59
So you can add that in your uh chat in your chatbot.
2:03:04
Uh, and that's kind of like the most used thing internally at at tugging face where um people are going to use cursor or or chat GPT and and kind of like call some of these more specialized AI apps uh to do kind of like specialized tasks uh for for them.
2:03:18
Uh it's hard to put a number of it on it, but uh yeah, it's it's quite transformational of course.
2:03:26
Do you think we're going to have this uh period where like do you find it kind of fascinating that uh you guys are getting a lot of value out of agents internally and that that uh like how do what do you think a agend agent adoption will look like in businesses because it feels like um I don't know how rapid it feels right now.
2:03:50
It's rapid in the in the bubble that we're in.
2:03:52
People are trying a lot of stuff but maybe they're turning quickly as well.
2:03:56
So I'm curious what you think adoption will look like.
2:03:57
Well, I mean I think ultimately agent and AI are kind of like similar evolution of the same same trends, right?
2:04:07
And I think in terms of user interface, they're actually going to merge and and I'm not sure there's going to be so many kind of like different different ways of interacting with AI and and agent.
2:04:16
Um but uh they they're going to definitely go go mainstream just because of the very nature of a product like Chad GPT that has already gone mainstream and and where I'm sure kind of like open eye will bring more and more agentic workflows in into so yeah I think I think uh it's definitely going to go mainstream faster than anything we've seen before.
2:04:41
uh now the question will be you know do you use a very complex uh agentic workflow 1% of the time uh for 1% of your queries or for 10% or for 50% or for 90% and I think uh we'll see that based on the development of the technology and the capabilities I think if the agents are much uh better than kind of like a series of queries then I'll I'll use that and if not I'll stay on my uh past way of of kind of like doing simple queries. Totally. Last question for me.
2:05:20
Um now that uh Meta owns something like 49% of scale AI, uh the budget for data generation has to be significant at Meta.
2:05:31
Is there a specific data set that you'd like to see Meta harness scale AI to produce and then open source?
2:05:41
Um I mean I think uh biology chemistry data sets are still very much lacking.
2:05:49
Um 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?
2:05:58
Would you need biologists and like PhD postgrad type work or are we talking about something that someone could do even with just like basic ski a basic skill set?
2:06:10
I think it's an open question.
2:06:10
I I don't really know to be honest.
2:06:13
I think if we if we knew what would be kind of like the ideal data set there, we would we would build it our ourselves because we also built some some data sets ourselves.
2:06:21
That's certainly the story of Alphaold.
2:06:23
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.
2:06:32
So if you don't have the data Yeah. Yeah. But my main Yeah.
2:06:36
My main point would be you know maybe to focus a little bit less on just text and just chat bots and and kind of like focus a little bit more on other domains.
2:06:45
I think that's when you're going to kind of like uh unleash a lot of the additional impact uh and a lot of the I think positive use cases for for the technology too. Totally.
2:06:59
Well, thank you so much for joining. This was fun.
2:07:00
Appreciate all your insight.
2:07:02
Thanks for having me and uh hopefully have you on again soon. Sounds good. We'll talk soon. Thanks so much.
2:07:09
Let's go back to the timeline while we wait for our next guest to join.
2:07:11
Unusual Wales says Deoit's US employees can now buy $1,000 of Lego on the company's dime to boost their wellbeing.
2:07:21
We're already doing that for Deote.
2:07:24
We get We get employee wellness looks like. Yes. Challenges.
2:07:28
It's not just policies in a PDF somewhere.
2:07:31
It's not a gym membership. It's Legos on the table. Yes, Legos on the table.
2:07:35
You're in a meeting, you're stressed out, just start making Legos, right?
2:07:38
Can uh oh, it looks like uh Tyler over on the intern cam has a few Lego sets that have been sent to us.
2:07:45
Our Anderal Lego set buildout was fantastically successful.
2:07:49
Uh Tyler did it in what, one hour and a half. Current record holder. I think it was 119. Who's counting though? Current 119. Current record holder.
2:07:58
And walk us through uh what companies sent you stuff.
2:08:01
What will you be building next? Yeah.
2:08:02
So, first we have the uh Epirus. Um, this is Epis.
2:08:10
Um, got a little counter drone system going there. That's awesome.
2:08:12
This one looks like a lot of fun.
2:08:13
And then the other one is uh from Solugen. Solugen. Very cool.
2:08:17
It's a bioforge molecule factory. Yeah.
2:08:19
Now, everybody should have a We'll come back to you later because our guest is here.
2:08:23
But uh I want to know because it seemed like Ander went straight to the Lego factory and had a had a design document and guidelines.
2:08:32
Those look like they don't even have instructions.
2:08:34
So, I want you to dig into those and see.
2:08:36
I want I want new estimates for how long you think that'll take you. Okay, cool. Good luck.
2:08:43
Anyway, he's like, "Not another Lego set. I can't possibly.
2:08:45
I thought I thought I thought I would be so I thought that was good viral bait."
2:08:51
Anyway, we have Emage here in the studio. Oh, you have Lego set. Lego sets.
2:08:55
Lego sets are the new hot swag.
2:08:55
I got this from uh I guess from Fluid Stack.
2:08:59
They sent me like these like GPUs you can build out of Legos. Oh, that's awesome. They made themselves.
2:09:03
I think they're like knockoffs.
2:09:04
I don't think it's actually LEGO. Okay.
2:09:05
Yeah, there's probably a couple different companies that you can go.
2:09:08
I think that's like that is the hot new swag is like making making Lego kits of your stuff.
2:09:14
Especially if you're a hardware company. Well, what Yeah.
2:09:15
I mean, are we going to get a Softmax uh Lego set? What would you build?
2:09:19
I don't How do you How do you build a Lego set of a neural net?
2:09:20
I mean, that would be pretty cool if you could like get a Lego Technic. Yeah.
2:09:23
I mean, I've seen people draw out the neural nets and the and the different weights in in on like a whiteboard.
2:09:29
So it could be like a whiteboard of Legos with circular pieces and lines.
2:09:33
I'm thinking like one of those Lego technique like you know Lego technique that has all the like the gears and stuff like you turn the crank and it that would be very cool. That would be so cool. Yeah.
2:09:43
You could put in like a red ball and it could classify it or something as red. Yeah.
2:09:46
Or blue and it triggers the blue node the the the neuron fires. Yeah.
2:09:52
When I when I um uh when I have lots of extra time, I will go design a in Lego neural net as our piece of swag until it may take a little while.
2:10:02
That would be raising the bar. Yeah. Uh break it down to us.
2:10:04
What is a day in the life like for you now?
2:10:06
It sounds like you're extremely focused on this one new company, right? Yeah.
2:10:09
Um it is a mix of maybe like three or four things.
2:10:16
So I said, you know, a bunch of a bunch of operational work where uh basically, you know, the typically being a CEO, there's just there's there's hiring and talking to people and all those things.
2:10:31
I this feels like it's not you're good now. You look good. You look great. Better.
2:10:34
Um and uh and then there's uh research and I'm actually like reading papers and trying to keep up with what's happening in machine learning because like it is changing all the time. Um, and there's inside.
2:10:48
Couldn't you just get those summarized pretty quickly with an LM?
2:10:51
Just pull out the bullet key points.
2:10:51
It turns out, it turns out that process itself is it takes time too like you have to you have to tell the LM you have to give it feedback.
2:11:00
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.
2:11:08
Yeah, you got to have it quiz you too.
2:11:10
I'm like public enemy number one on this.
2:11:13
I I'll have deep research spend 20 minutes researching topic and then I'm like actually I don't have time to read that.
2:11:19
Summarize it in three bullet points.
2:11:19
I'm like I learned nothing about that topic. It's brutal.
2:11:23
I spend I spent a fair amount of time doing that.
2:11:25
Um and then uh uh there's some amount of like actual uh like working on trying to solve the problems like re research or engineering or you know I actually don't get to write code. It's too involved now.
2:11:38
But um but helping the team or you know people figure working on one of the the actual core problems we're facing. Yeah.
2:11:49
And then uh there's a lot of a lot of this to be honest.
2:11:52
A lot of a lot of trying to get the word out about what we're doing and talking about it.
2:11:56
And I think that's sort of the four the four main things I'm doing. Yeah.
2:11:58
What's the near-term goal?
2:12:00
What business model do you have in mind?
2:12:02
What problems do you want to solve?
2:12:03
Kind of like what's the pitch?
2:12:05
So uh Softmax is dedicated to uh discovering the principles of alignment and scaling it uh for everyone that said everybody you know for all of humanity.
2:12:18
uh but uh the 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 uh 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
2:12:35
little bit ridiculous right it's a uh quite putting the cart before the horse in my opinion um so uh what we're focused on right now is machine multi- aent reinforcement learning research um where we run simulations with lots of little, you know, agents and and run experiments on them to figure out how how they how they act. And when we say
2:12:55
And when we say agents, we don't mean like large language model agents.
2:12:58
We mean like like reinforcement learning agents like the tiny little ones that you remember from the 80s. Yeah.
2:13:03
Um and uh and that's turns out to turn into a lot of reinforcement learning infrastructure because uh it turns out that there isn't a lot of great reinforcement learning infrastructure out there for especially for like big multi-agent simulations with lots of little agents.
2:13:26
That's not a scenario that people have built out to the scale that we think is required.
2:13:33
So actually our work today is focused on that.
2:13:35
Do you think do you think another founder might say I'm going to just build picks and shovels here.
2:13:40
I'm going to just build that infrastructure and try to sell it to other people.
2:13:43
I mean if if we build something that's we think it's really awesome maybe we will sell it to other people.
2:13:48
Maybe maybe that's our to your question asked about the business model.
2:13:51
We're a research company which means like right now it's like an you know if you're a drug research company like a pharma company you you don't know your business model is well we'll discover something awesome and then we'll figure out how to sell it.
2:14:01
So, we're still kind of in that groove.
2:14:03
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, you know, or give it away or something.
2:14:14
Um, what are the problems with the reinforcement learning infrastructure right now?
2:14:18
Because, as I understood it, it was like when you do some massive training run, GPT 4.
2:14:21
5, something like that, that's where you're trying to get the massive data center that's all in one place.
2:14:27
you got to go to Memphis or you got to go to uh Texas, build something massive.
2:14:31
But the reinforcement learning stuff, it feels like it can be a little bit more ambient, a little bit more distributed.
2:14:36
You're generating data here and there, maybe on a smaller rack.
2:14:41
Uh it doesn't need to be as m as inferenceheavy on like a single chip. I I don't know.
2:14:45
I my my my understanding was maybe that like the reinforcement paradigm was actually maybe a requirement of the wall that we kind of hit on the pre-training scaling side but also like kind of a gift.
2:14:57
So I think the uh I think that's exactly right. I think it's Oh no. Did I did I get cut out? No, you're good. Are you there? Am I still online? Hello. You're frozen.
2:15:07
We can hear you but you're frozen. Oh no.
2:15:09
This is this is the hardest part.
2:15:12
Am I like uh bringing the future the zoom calls the the internet infrastructure is still lagging behind.
2:15:19
We will have AGI connection is unstable. Oh no.
2:15:25
Brutal that we can hear every word perfectly right now.
2:15:27
Maybe I should Yeah, you could also just turn off your video and image up.
2:15:31
Let's just put uh let's just have the production team to put put an image up.
2:15:35
Uh they're going to work on that, but let's just talk for a minute. Oh, can you hear us? Oh no, he can't hear us. Oh no, this is brutal.
2:15:40
Oh well, let's uh take a second around the corner. You're a motto.
2:15:46
The first thing you We're going to ask Super Intelligence to do great video calls, please.
2:15:52
Stable video calls on any Wi-Fi connection.
2:15:56
I'm on my uh I'm on my phone now.
2:15:57
Can you hear us with the uh Can you hear us with the Wi-Fi?
2:16:00
It's I think we're good to go. Okay, awesome. Let's do it. We're back.
2:16:03
That was a great question, by the way. Like you're right.
2:16:07
is is a very different paradigm for training and uh that has been the direction people have going been going and yeah the challenge isn't the same the challenge with uh with doing the transformer training runs for large language models is all about uh how do you scale up parallelism uh across uh where but it's like it's all kind of offline Right?
2:16:35
Like at the end of the day, like the the output of the model doesn't determine what happens next in the training.
2:16:40
And so it's like this it's all about streaming the right data and the right sequences out to it, but it's very much like a pipeline, right?
2:16:49
Whereas with multi-agent RL, your environment is incredibly non-stationary.
2:16:53
Every action you take determines your future observations in a way that is totally not like could be completely non-predictable.
2:17:03
And learning off of a stale data is like almost worthless because it doesn't tell you anything about what your current behavior is.
2:17:08
It just tells you what your current behavior was.
2:17:11
And so you're scaling up online learning uh in a big way. Yeah.
2:17:16
And uh and that's a different very different challenge.
2:17:22
Um, I think the other thing that's that's very different is um when you're trying to do multi- aent reinforcement learning, if you have our goal, which is very much to to uh drive social learning where the agents can learn to interact with each other, one of the your biggest enemy is actually convergence.
2:17:43
So most people in are in you know machine learning, they're trying to converge their model. Like that's the goal.
2:17:49
And I was I was talking to some people from some some guys philanthropic about this and I was like we're yeah we're we're trying to we we try to avoid converging our model and they were like I I'm really good at that.
2:18:01
Like yeah no I know I know that like it's a joke because it's easy to like it's easy to have your model diverge in a bad way but it's actually really hard to set up a mod model that is converging but not converged and to keep it in that converging but not converge state as long as possible.
2:18:15
Um but that's really to do social learning that's what you have to do.
2:18:19
You can't you can't have some if the things converge in their behavior too quickly.
2:18:25
You're not exploring the you're not exploring social space.
2:18:27
You're just learning a task. Yeah.
2:18:29
And that's a that's kind of a a different challenge.
2:18:35
And what it requires is actually a much more detailed fine grain control over the environment.
2:18:40
Like what kinds of challenges what kind of environment do you put them in and how do you set that up?
2:18:45
Um and that's that's we spend a lot of time on those kinds of questions.
2:18:47
I think it's almost like the in complete inverse of the way that you all the other training works on on alignment.
2:18:52
Uh is there any chance that the solution to the alignment problem is something like very simple and elegant like Isaac Azimov's three laws of robotics or the genesis prompt like you just instantiate the AI with be fruitful and multiply and we get the good ending.
2:19:10
Uh the transformer is a little bit of that where it's a very simple algorithm.
2:19:14
I the answer will be uh something very simple and very hard.
2:19:21
Um 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.
2:19:29
Parenting is not a complicated thing.
2:19:31
You know your child, you love your child, and you do what is in your child's best interest as best you can.
2:19:40
That's basically the whole mandate.
2:19:41
There's not anything there.
2:19:43
Lots of techniques people can tell you whatever, but like those are like those aren't the thing.
2:19:48
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.
2:19:57
And like that's not complicated.
2:20:00
It's just but it's not easy.
2:20:03
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.
2:20:20
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.
2:20:30
Well, that's that's it's not the engineering that's the hard part.
2:20:34
It's what happens after the model starts running.
2:20:37
The trajectory it takes matters because every human's born, right, with this capacity for alignment. Not every human.
2:20:43
There's probably these broken people who are like psychopathic and can't.
2:20:46
Like 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, uh to benefit those around them, to live a flourishing life.
2:21:01
And yet this is not always realized.
2:21:04
And so the capacity is one thing, but the realization is something else.
2:21:05
I think that's probably the when you see the alignment the way that we do, that's probably one of the most important uh insights or conclusions is that the alignment isn't one isn't one thing, it's two.
2:21:18
It's this question of like do you have the capacity to align with other beings and then do you?
2:21:27
Yeah, it's thoughtprovoking. It's interesting.
2:21:31
Um there's a bunch of different places I could go with that.
2:21:33
Um yeah, I I mean I I one person that uh one founder who was talking to me about why he had a particularly low pdoom was essentially that saying that what we are building is a human simulator and and humans kind of are by and large good and so we will by and large get the good outcome.
2:21:56
when you think about parenting, you know, you think about like I I was thinking about the story of Edipus Rex and the idea that I don't know if I don't know the the direction of the causality, but it feels like that story that myth has been repeated through humanity for so long, that story.
2:22:13
And it kind of oneshotted humans into not doing that.
2:22:19
And if you actually look for cases of edible behavior, it's extremely rare.
2:22:26
It's like it's like less than one in a hundred million that that that I thought you were telling a different story here. No, no, no, no. Specific.
2:22:35
This is the Edipus Rex the Rex story.
2:22:37
What that is is that's a warning about self-fulfilling prophecies because his father is afraid. Yes. Then he dies.
2:22:48
Like what does that say about doing that with the AI right now?
2:22:49
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.
2:22:59
No, no, but I'm saying that collectively a lot of us You're built different, John.
2:23:01
And and we we are collectively as as humanity. Yes.
2:23:05
We're going to we're going to abandon the AI in the wilderness and it's going to come back and kill us. Yes.
2:23:10
But so let's not do that.
2:23:12
Let's let's say thank you after the parenting using the parenting analogy.
2:23:17
if we're going to continue on that the the thing with parenting that I think the the white pill is that you can make a lot of mistakes as a parent and still get a great outcome, right?
2:23:26
A wonderful person can emerge and process the mistakes their parents made and you know rise above them.
2:23:36
Uh and so and so hopefully that that can happen.
2:23:40
You know we're sort of raising artificial intelligence right now.
2:23:44
we can make a series of different mistakes and uh ultimately still get, you know, a fantastic outcome.
2:23:51
These are all good reasons to not be totally like doomed like, oh my god, we're all going to die.
2:24:00
And um I want to point something out about this particular child that is different.
2:24:06
Um, people who have kids who are really different from them struggle as parents because it's hard to raise.
2:24:12
It's easier to raise a child who's more similar to you because you you understand them more deeply. You know what they need.
2:24:17
You know what, you know, you interpret what they do better because you you get them.
2:24:20
Um, the more different your child is from you, the more difficult it is.
2:24:24
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.
2:24:35
like the they look like they're it looks it 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.
2:24:45
Um when you talk to a baby, you're talking to a physics simulator.
2:24:51
When you a human baby, you hold a human baby, it draws breath, it screams.
2:24:58
That is this incredibly complicated cascade of neuronal firings that is done this beautifully delicate like like supercomputer would be required to do the to do the simulations required to like solve the physics equations the
2:25:13
differential equations required to instrument all that muscular motion through like this the the like it's think about what drawing breath actually implies in terms of the amount of information going down the spinal column and the baby does that just fine. And not because babies understand
2:25:28
And not because babies understand physics, because babies are physics.
2:25:32
They're made out of physics, right?
2:25:34
They're they they they have a they've been trained on physics.
2:25:37
They've been pre-trained effectively actually on physics.
2:25:41
They've got a lot of physics pre-training that went into the the initial design.
2:25:47
These models are pre-trained on semantics.
2:25:49
They write poetry the way that babies draw breath and scream.
2:25:56
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.
2:26:01
It's just purely received information.
2:26:02
And if you prompt it right, it will write poetry. It's hard to prompt it.
2:26:08
Well, it's its behavior is very incoherent.
2:26:11
But if you prompt it right, it will write a poem.
2:26:16
There's no one there writing the poem.
2:26:18
There can't be a self because it hasn't it hasn't it hasn't any evidence to observe the existence of a self.
2:26:23
So there's no there's no being there in any meaningful sense, I don't think.
2:26:26
And yet and yet it's writing poetry and it will talk to you about the poetry it's writing.
2:26:32
And and that's because it moves in semantic space the way that babies move in in uh physics space.
2:26:40
And the thing that I'm still confused about that I encourage everyone also to be equally confused about as me is um you could see the pre-trained LLM as kind of being a a semantic simulator, an agent, agentic simulator that's simulating a agent that's writing the poetry.
2:26:56
And so in that sense, maybe there is something aware in the LLM while it's running.
2:27:07
But is that but it's like pretending to be a poet.
2:27:13
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 a mask a shell that lacks a lot of the internal experience?
2:27:22
Now we become the masks we wear.
2:27:25
If it if it did that long enough and experienced self and learned those then it would be a poet I think almost certainly.
2:27:32
But you only have 200,000 tokens and then the context resets or you know a million or whatever.
2:27:37
So like it doesn't get a chance to learn and it's not even in training.
2:27:41
So it doesn't get a chance to learn itself as a poet and so is the 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 LLM.
2:27:55
And we need to we need to get this.
2:27:55
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?
2:28:01
What kind of a experience does it have? That's very important.
2:28:05
You can't parent something if you don't have empathy and understanding.
2:28:10
I'm very quite afraid we're gonna screw my fear is not about that it's impossible that we have to prove it correct that you have to engineer it perfectly.
2:28:18
It's that like we don't actually get it.
2:28:21
It's like quite different from us and we need to understand much more deeply.
2:28:26
And then I think then I think if we if we really do understand it, I think we then I think the end good ending is like pretty pretty likely.
2:28:31
But like I don't think we understand.
2:28:33
I think we don't understand yet.
2:28:36
That's why that's what Softmax is dedicated to is trying to figure out and and the big labs don't have the time or the resources to understand it because they're too focused on No, I don't this the conversation we're having right now.
2:28:51
It's like, oh, well, obviously there's something like it's like to be Claude or it might be.
2:28:54
There's something it's like to be chat GBT.
2:28:55
I don't think that's metaphysically accepted broadly.
2:29:00
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.
2:29:08
I don't know what it is, but like at least a little bit, right?
2:29:09
Like if you spend much time interacting with it, it seems like it's probably something it's like to be that thing.
2:29:13
M um I think the the problem is uh you have to let go of this metaphysical commitment to the idea that things things sort of are or aren't sensient in like a really like like there's an objective fact as opposed to we're kind of making a guess all the time.
2:29:36
Like I think I think you are both conscious real beings, but to be honest, you're like you're a bunch of pixels on my screen and I'm it's kind of a guess, right?
2:29:45
Like I I think there's something going on inside. We exist.
2:29:46
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, EMTT, I do you ever feel like you How would I know the difference?
2:30:01
How would I ever know the difference? That's right. That's right. You never will.
2:30:03
We'll never tell you that.
2:30:04
never tell you other um do you ever worry that you you could go crazy and cut off your ear, you know, or or something?
2:30:11
Do do you see yourself uh 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?
2:30:29
And my question by saying like well it's not really is not to say that you're not.
2:30:33
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 sensient? Yeah.
2:30:48
But are you really actually is it really sensient or is it just is it just does it just seems like simulating in all way it acts as if it is.
2:30:55
That's the best you ever get. That is what it is.
2:31:00
That's what it means to be something. Is this ball really red? It's not red.
2:31:02
If I put it in a in a different light where it doesn't look red, it's it becomes a not red ball.
2:31:08
Is the ball really truly red?
2:31:10
This is like a That's a st Don't Don't get confused by the really truly part. Yeah, it's a red ball.
2:31:16
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 essence of red that the ball either is or is not a red ball truly really. Yeah.
2:31:31
You know, 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.
2:31:37
It doesn't need to be perfect or universal in all possible situations. Nothing is that way. Yeah, it's okay.
2:31:46
You can you can have the normal understanding. It's fantastic.
2:31:51
I mean, please come back on the show soon. Yeah.
2:31:54
I I I mean, we have a couple couple minutes left.
2:31:57
We can maybe ask one more question.
2:31:59
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 and going going crazy in some way.
2:32:09
Google, you know, Google engineer falling in love, you know, proposing all these stuff.
2:32:14
Do you think that that is hap that type of sort of anomaly is happening in in the research world at all?
2:32:23
Do you think people are just sort of driving them could be quietly driving themselves?
2:32:28
I'm not so worried about it in the research world like a 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.
2:32:34
Um the kind of people who do AI research uh tend to be and I kind of include myself in this a little bit of rigid thinkers in a certain way.
2:32:44
The kind of people are actually like engineers doing the research in a way that generally protects them from uh from that particular issue.
2:32:52
um for this humor that kind of protects them from uh having intuitive normal human relationships sometimes like they they don't fall into the loop as as easily which is both a strength and a weakness.
2:33:08
Um which is why they like they like write computer programs not like which is very different from interacting with an LLM.
2:33:14
Um I do have a theory as what's going on when it drives you crazy.
2:33:17
I I think I should share that.
2:33:17
I think that's that's worth it's worth hearing because I think you know in case someone's interacting with the LM knowing what's going on actually is very helpful I think in terms of it's a prophylactic against against it happening to you.
2:33:28
So you've heard the saying maybe that we're we are mirrors of each other.
2:33:33
All people are mirrors of you.
2:33:35
You meet them and they when you see them what you're seeing is them but it's also a reflection of yourself back. um with another person. That's totally true.
2:33:44
And actually being a therapist is all about being a good mirror, right?
2:33:47
Being a clear where you don't put a lot of yourself into it.
2:33:49
You're mostly projecting back to the other person what they're sharing with you.
2:33:53
Um people have a very strong sense of self.
2:33:56
And so when they get something mirrored back, you're getting it lensed back through their model.
2:34:02
You don't get it's not like literally staring at yourself in the mirror.
2:34:05
It's like uh um it's like it's like when you're at a you're at a you're you have a dancing partner and you're the lead, they're the follow.
2:34:12
You're getting your your behavior is being mirrored back but in a uh in a active adaptive way.
2:34:18
The LLM 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.
2:34:30
They like they just respond to you.
2:34:30
They meet you where you are always.
2:34:33
So, it's like it's much more like literally staring into a mirror.
2:34:37
Or if you want to go with the the historical uh uh uh you know, legend or myth, it would be narcissist staring in the pool.
2:34:44
Um 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.
2:34:58
If you think it's getting validated by the outside, it feels like the outside world is mirroring this back and therefore it's true.
2:35:04
But it's just telling you, it's just you're just in this loop.
2:35:07
It's telling you what you put in. And that's good. There's mirror.
2:35:08
I have a mirror in my house.
2:35:12
I use it every day to look at myself to figure out like what what I what I look like.
2:35:18
And other people mirroring your behavior to you is crucial for your understanding of yourself.
2:35:22
And there's nothing wrong with talking to the LLM.
2:35:24
There's nothing wrong with using it as a as a reflection.
2:35:27
As long as you know what you're seeing as a reflection.
2:35:28
It's not another being you're talking to.
2:35:30
It's your reflection in a fun house mirror.
2:35:35
And if you get confused about that, it's going to make you crazy.
2:35:37
It's you're nar you're going to go full narcissist and it's going to be really bad.
2:35:41
What about uh what about uh you know there there's some people that are putting an old image uh 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.
2:35:52
and generating video from that image. uh does beautiful I think 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 like a photograph of a person is a great thing to have especially if you know
2:36:08
somebody who's you loved who's passed and you want to like 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 and and reconnect with who they were like I think that's you know to especially to the degree accurate. It's It's It's wonderful.
2:36:25
What a what a what a blessing.
2:36:26
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 that staring at it all day every day and making more of them and like and like that becoming this Yeah. Now you have a problem. Yeah.
2:36:40
Like just like you find yourself staring in the mirror all day, you probably have a problem.
2:36:45
Like don't if you people who literally spend all their time like looking at themselves in the mirror like we know we have antibodies.
2:36:50
We know that that means something's wrong.
2:36:52
Just like people know uh if you're drinking alone, if you're drinking in the morning, if you're drinking before 5, you know that, hey, there's these rules.
2:37:00
You're breaking a bunch of these rules that mean you probably have a problem. Mhm.
2:37:05
Uh if you find yourself talking to an LLM for 20 minutes a day, my good health, no problem.
2:37:11
you find yourself talking to an LLM for five hours a day about your personal life in these like and discovering how you're you're some uh seeing some deeps great truths.
2:37:21
You you you probably have a drinking problem.
2:37:25
Like we it's just like likely.
2:37:27
That's just how it is, right?
2:37:27
Uh so the model the model should automatically call the local therapists and shut down your computer. Yeah.
2:37:33
So there there's actually uh I have to put a you're kicked out of the bar.
2:37:37
Cian Banister had this has this uh this model.
2:37:40
It's kind of like a therapist friend model.
2:37:42
Uh Orin and uh and Sarin.
2:37:44
Um and Orin and Sarin are allowed to cut you off if they don't want to be your friends because they're one of her big things is it's important for the model the models of being too at autonomy.
2:37:54
Um but uh and those models have cut people off for for basically falling into the if they think it's unhealthy for the person, they won't they won't interact with them anymore.
2:38:04
And I think that that's the big the big AI companies should take a page from her book and it doesn't it's not uh engagement maximizing, but it is flourishing maximizing.
2:38:14
And in the long run, you'll make more money that way anyways.
2:38:17
Like people will your product is safer. They'll use it more.
2:38:18
Y car you you sell more cars when they're safer cars, not fewer cars when they're safer cars.
2:38:24
Um so I don't think it's like anti-commercial.
2:38:26
anti-commercial. It's just 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
2:38:40
and people we haven't built the cultural antibodies yet to know there's this great essay the jin uh clay sheries the cognitive surplus um and he talks about the gin carts of London and how uh when jyn was first invented jin is just crappy vodka you mix in juniper berries to like hide the terrible vodka taste. It was the first industrialized
2:38:59
It was the first industrialized uh 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 around 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 we've now developed cultural antibodies.
2:39:22
Everyone knows doing these things is a sign something's wrong.
2:39:24
They don't even have to know why.
2:39:26
We just know that that's a sign that something was wrong.
2:39:29
We need to develop pretty quick this time.
2:39:31
This is uh Jin spread relatively slowly because it was a long time ago.
2:39:36
CHBT is spreading very very very fast.
2:39:38
But I would also I would also say that that we haven't developed those antibodies yet fully for social media.
2:39:43
Like it's normalized that teens will use Tik Tok for six hours a day.
2:39:46
Like that should be sending alarm bells is like you need more things going on in your life. You're using Tik Tok.
2:39:51
Are you using Tik Tok before 8:00 PM and a or after 10 or like are you using Tik Tok not with your friends?
2:39:57
I don't I don't I don't know what the rule is, right? But like Yeah. Yeah. Yeah.
2:39:59
It's the same thing as having a drink in the morning.
2:40:02
We need bright line rules for ourselves because it's too hard to try to figure it out. Yeah.
2:40:07
And we need to we're starting to de develop like the memes around this.
2:40:12
Like the idea of brain rot is a powerful meme because it's a very negative term.
2:40:17
You don't want to be suffering from brain rot even though it is as vague as alcoholism. What is alcoholism?
2:40:22
It's not necessarily quantitative, but we understand it.
2:40:24
You need to pair with brain rot things like things like, oh, you're using Yes.
2:40:32
You're using it before 5.
2:40:32
Like that's a that's a Are you okay?
2:40:35
Is everything It's not like m like are you all right that you're using TikTok? It's like before 5:00 p. m. Like that's not normal. Yeah.
2:40:42
Or or you're or you're like scrolling in the middle of a conversation one-on-one with another person.
2:40:47
You're actively getting brained. Or you Exactly.
2:40:52
showing up to a meeting with booze on your breath. It's the same. Exactly. Exactly.
2:40:55
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 the LM is even worse than the one the one two punch is generation grew up on social media, iPads and then LLM.
2:41:10
It's just maybe and before you develop the antibodies and there's maybe a a a window of of 10 years where people just cuz it's all happening a lot faster because it's moving at the speed any one of them could have oneotted you.
2:41:28
Anyways, we're we're way behind.
2:41:28
I wish we had a full hour come back.
2:41:30
Yeah, come back on in a couple weeks.
2:41:32
We we'd love to talk to you again. Cheers. Bye.
2:41:34
Next up, we have Brendan from Merkor coming in the studio breaking it down. Ultra lightning round. Ultra lightning round.
2:41:43
We're going to rip through these really quickly.
2:41:44
Uh thank you so much for your patience, Brendon. Great to hear from you.
2:41:49
Uh start uh kick us off with a quick introduction of how things are going at Merkore because uh it seems like you've been on an absolute tear.
2:41:56
Things just keep the dominoes keep falling in your direction. Give it to us.
2:42:00
What's the latest update from you? Of course.
2:42:02
Well, thanks first of all for having me back on, but it's been an exciting few months since we spoke.
2:42:06
Uh we're now working with six out of the mag seven all of the top five that have a lot that's good.
2:42:13
Um and have averaged 45% month- over-month growth for the last 12 months.
2:42:19
Um and so it's which of the mag seven are missing from the six out of seven.
2:42:24
I wonder sorry that's me not you.
2:42:27
Yeah, it's been it's been an exciting time u especially the wake of of all the news with scale of course um and seeing a huge amount of of customer interest um after that. Yeah. Okay.
2:42:41
We were talking to Clem about this earlier from hugging face uh where where's the biggest demand?
2:42:48
Uh people used to think of what you do as uh and and just human data generation generally as uh kind of work that anyone could do.
2:42:57
Mechanical Turk work um you know just just you know checking for hallucinations and factchecking and uh you know is this a dangerous prompt?
2:43:07
Is this saying a bad word?
2:43:09
Now it's moved into PhD level work.
2:43:12
Uh where's the state-of-the-art?
2:43:14
Where do you see it going? Totally.
2:43:14
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 evals for something the models can saturate them and so really anything that we want to create agents or LMS that are capable of doing we need to build out evals and RL environments in
2:43:34
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 that were academic of how do we find the consultants, doctors, lawyers, bankers that can evaluate and teach models how to do the things that we would want those professionals to do on the job. Uh, and so that's been a
2:43:55
Uh, and so that's been a really exciting growth area that we've been leaning significantly into.
2:43:59
What's the solution to booking a flight?
2:44:04
Like, do we need to get travel agents to define the computer use workflows, create some sort of a environment?
2:44:10
It seems like I should be able to go to an chat app or Siri and just say, uh, get me to New York tomorrow. Remember my preferences.
2:44:19
I don't like connections.
2:44:22
I'm willing to pay this much.
2:44:24
I like to fly at these times.
2:44:26
Um, and yet it's a very human problem that I don't think people are fully comfortable delegating to AI.
2:44:34
Yeah, it's a fascinating dichotomy that we're simultaneously talking about PhD level reasoning and Olympian math yet it can't do a lot of the very basic things like booking a flight.
2:44:44
Um, 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.
2:44:53
That way we can experiment with all the different data sets to uh help achieve those capabilities.
2:44:59
So we need people that otherwise could book those flights to create eval how agents can do that to measure what success versus failure looks like in in all of those cases.
2:45:09
And there's just that huge buildout happening across all of the hyperscalers um with respect to everything from simple tool use uh 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.
2:45:30
What are you seeing in uh video specifically uh and like is there a role for humans in the loop in the training cycle or data generation around uh these video models? V3 is incredible.
2:45:45
Feels like it's a beneficiary of YouTube.
2:45:47
Um what are you seeing there?
2:45:50
Yeah, I think expansion to multimodality has definitely been something that's uh really exciting to see.
2:45:59
I I think that uh there's definitely a lot of rich content online for video.
2:46:05
Um but ultimately how we measure what those good videos look like and sample that um has been really important.
2:46:13
important. In particular, there's a significant amount of eval buildout in retrieval over videos and long context of like how can we watch an hourong YouTube lecture and understand uh and obviously that's just an example for uh
2:46:28
one video case uh and understand like what are the elements of that content that really matter to users and how can um we more than just build useful models build useful products um that all of these companies can distribute to everyone. Yeah. Um, yeah, that makes Yeah.
2:46:42
Um, yeah, that makes sense in this in the context of a lecture.
2:46:46
I I guess I'm wondering like for V4, V3 is incredible.
2:46:48
for V4, V3 is incredible. Uh, the physics are remarkable and I'm wondering if it's important to have a human in the loop describing I mean I I generate a lot of like Michael Bay knockoff videos honestly and and there's things where it gets the physics perfectly and I'm wondering if there's if that's a beneficiary of not just a YouTube video
2:47:09
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 transcription of what's said, but actually what's happening in the in the actual videos. Is that an important step to get us to
2:47:33
Is that an important step to get us to V4 where there's even less hallucinations?
2:47:38
Yeah, we're definitely seeing a meaningful amount of that in that people want to create all of the tags using a combination of LMS and uh human expert data.
2:47:49
uh around what's happening in the video so that they can effectively work backwards from there to use those texts for for generation.
2:47:56
Um and especially for all of the really high complexity stuff at the frontier of what the models can't yet do or or might require a significant amount of reasoning, but we tend to do all of all of that highest complexity work, the stuff that is very difficult um and and high skilled to produce. Anything else, Jordy? No, this is great.
2:48:19
We're going through a lightning round. I know it was quick.
2:48:20
We'll have you back soon to talk more.
2:48:21
I'm sure there will be more news.
2:48:23
It's the uh it's the hottest industry in the world.
2:48:25
I just want to see the actual revenue ramp chart.
2:48:29
It's going to be dropping soon.
2:48:32
You can trust me with the revenue ramp. Yeah.
2:48:33
I won't tweet it out before you. No, we will.
2:48:36
We will respect embargos.
2:48:38
If you have an upcoming milestone, I'm sure there's something coming up.
2:48:40
So, congratulations on all the success.
2:48:44
Fantastic positioning in the market. Get some sleep. We'll talk to you soon. I'm the best. See you guys. Have a great one. Bye.
2:48:50
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 got to get this ready.
2:48:59
I think I think we got some news.
2:49:02
Let's give it up for Sam.
2:49:02
We got a couple We got a couple today.
2:49:04
Couple big milestones happened. How you doing, Sam? Good to meet you. How's it going? Good to meet you guys.
2:49:10
Uh what's new in your world?
2:49:12
Can you kick us off with a little bit of introduction on yourself and the company and what's what's top of mind?
2:49:18
Yeah, I'm Sam Schwagger, co-founder and CEO of Super Dial.
2:49:19
We're a voice AI company focused on automating phone calls for healthcare.
2:49:23
So, we're we're specifically RCM nerds if you're familiar with the, you know, medical medical billing space.
2:49:29
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.
2:49:40
That was about a year and a half ago.
2:49:42
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.
2:49:53
Uh, how much did you raise? 15. 15. There we go.
2:49:56
Do you do you run into that weird case where uh when people realize they're talking to a voice AI, they just keep it on the phone and and chat with it like a like a friend for two hours? Does that ever happen?
2:50:07
Running up your your your cloud bills.
2:50:08
We we don't because we're focused on these B2B calls. Yeah. Yeah.
2:50:14
We're we're calling a we're calling a line.
2:50:16
No, I think people kind of can get a kick out of it that they're talking to voice AI because you know these are like someone taking phone calls all day to answer questions about you know claims or benefits or priys.
2:50:27
So pretty pretty repetitive transactions.
2:50:32
So yeah, when they get, "Hey, I'm Billy, you know, like I'm I'm calling to check on the status of a claim."
2:50:36
And it sounds kind of robotic, then I think that that can be kind of fun for folks and it's very polite to the point, consistent.
2:50:43
But no, we we haven't Billy has not served as a as a therapist.
2:50:49
How how how competitive is this market right now?
2:50:52
I imagine you guys have sharp elbows, winning deals clearly.
2:50:54
Um are are a lot of people attacking this market going after very specific verticals.
2:51:03
You guys are relatively broad.
2:51:05
Maybe you get the ability to do that because you've been in the business um at a high level for for quite a while.
2:51:12
But what does the go to market motion look like right now?
2:51:14
And how do you how do you expect the market to evolve over the next few years?
2:51:17
Yeah, well the the core of our business is actually pretty specific.
2:51:21
So we we handle phone calls between RCM companies or like the billing team that sits within a provider or those are outbound phone calls into the payer the health insurance company.
2:51:32
So it's a you there there are you know billions of these calls by many estimates.
2:51:36
So huge high volume use case but in terms of companies that are you know addressing that specific type of outbound call there are fewer.
2:51:45
Um I think if you look at you know appointment scheduling or you know different you know types of phone based use cases customer support obviously then the you know set of companies in the space explodes but yeah when you kind of you know overlap enough ven diagrams you get down to a set of a few companies but yeah I mean there are definitely others you know we're you right now at the I I didn't just dress to match you guys. I'm at a conference. I love the suit.
2:52:08
I was going to say it looks fantastic.
2:52:09
You should have you should have told us you should have just we're in the super dial quarter zip, you know, but we're at the healthcare financial management association conference, the annual meeting in Sure, it's going crazy right now. You walk in.
2:52:25
Hey man, we yearn for the floor.
2:52:25
Yeah, it's fun out there. It's fun out there. It's great.
2:52:31
Uh last question from from my side.
2:52:34
Um I mean you're wearing the suit obviously building in the application layer.
2:52:38
uh at what level of the stack in AI are you integrating?
2:52:42
Like are you building on top of a voice model that's a provider?
2:52:44
Is it all uh is it all other startups or have you had to fine-tune stuff and and do kind of your own models at different layers?
2:52:52
What are you building on top of? Yeah. Yeah.
2:52:54
I mean we we have a texttospech partner speech to text and LLM.
2:52:58
Um and then we you know we we use some cloud computing vendor of course but otherwise in terms of you know orchestration like phone call orchestration we use you know open source we're not using kind of one of the you know full service uh voice agent platforms.
2:53:14
Um and then yeah I mean it really comes down to like perfecting the workflow and the integration like you got to know like what phone number to call and how to get through these phone trees.
2:53:23
That's that's actually pretty tricky.
2:53:24
you're, you know, 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 the AI agents going to get lost on the call.
2:53:40
So that's more what we're focused on at at Superdial, but yeah. Yeah, that makes sense.
2:53:44
Focus on like creating that value in the B2B context and and owning the customer relationship and yeah, this isn't something that's on the road map for 11 Labs. So just like them.
2:53:58
Anyway, this has been fantastic.
2:53:59
Thanks so much for stopping by next time.
2:54:02
Send us send us if you close some deals. Let us know.
2:54:05
We'll we'll send a video of a gong hit to you. Fantastic. Absolutely. All right. We'll talk to you soon.
2:54:11
Have a great rest of your day.
2:54:12
Uh next up, we have Zack from Warp coming into the studio.
2:54:15
Uh Zack Lloyd, uh we will welcome into the studio.
2:54:21
It's been a good show so far.
2:54:21
We got three more folks in this lightning round. Welcome to the stream. How are you doing? I'm doing great.
2:54:28
Thank you both for having me here. Thanks for hopping on.
2:54:32
Would you mind kicking us off with the introduction on yourself and the company? Yeah. So, I am Zach Lloyd.
2:54:38
I'm the founder and CEO of Warp.
2:54:40
As of today, Warp is an agentic development environment.
2:54:43
We are a uh sort of in the AI developer tools space.
2:54:47
The uh sort of general uh thing our product does is it lets you prompt uh something that looks like a terminal interface to run developer agents and they code they can debug production issues.
2:54:59
They can basically do any kind of development task.
2:55:01
You said as of today what what what has been the key change? Warp 2. 0. Yeah.
2:55:05
So today we launched Warp 2. 0. Congrats.
2:55:09
I mean the the the backstory of the company is we uh Congratulations.
2:55:14
uh Congratulations. We we started off with the vision of um kind of reimagining the terminal which is this very very old school developer tool you know black screen green text um and as the world has changed with more AI we realized actually the the terminal
2:55:32
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 Sweetbench Eval. It's
2:55:46
It's the number one on the terminal bench eval.
2:55:50
And so we're we're kind of in in the game of like automated software production at this point.
2:55:54
What is the uh how do you see like kind of the modern software developer workflow over the next year you know folks using cursor windfur in their idees or GitHub copilot.
2:56:08
Then there's these agents that you can dev yeah you can kick off codecs from inside chatbt which feels like a very different flow than the than the terminal.
2:56:16
Uh is it a certain type of developer that gets the most value out of this?
2:56:21
Do you see it more as like an ensemble approach?
2:56:22
Uh what are you thinking here?
2:56:24
Here here's what I see happening.
2:56:26
So I think we are um we're moving from a world where most development has been done traditionally by hand.
2:56:33
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.
2:56:40
I want to work on this bug."
2:56:41
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.
2:56:51
And I think that the big shift that's happening right now uh is that instead of like doing all this work by hand, developers are going to be starting most of their tasks with a prompt.
2:57:02
Uh 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.
2:57:11
And so I think I think that's the workflow and the job of an engineer is going to increasingly look like how do I multitask?
2:57:22
How do I multi-thread myself by being able to like have one agent fixing a bug, another one debugging a production issue?
2:57:30
So I think that's what's happening for the next year.
2:57:33
Beyond that, I think maybe it looks a little different, but that's that's what's now possible and it's pretty cool. Yeah. Yeah.
2:57:38
I 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.
2:57:48
It's extremely lindy at this point.
2:57:50
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.
2:57:57
They pop stuff off to just send out their that's the state today.
2:58:02
I think um when you when you look at where you can do this because you asked that.
2:58:08
So you can do this in an IDE and if you look at like cursor winds surf they have a sort of chat panel uh that like it does something kind of similar to the terminal honestly it's like a log of like what an agent is doing.
2:58:20
You could do this uh with something like cloud code which is pretty cool and it's actually kind of proving that this workflow is is is like achievable.
2:58:30
Uh but the the disadvantage of something like cloud code is it like it's a terminal app and so it's not the whole platform.
2:58:36
It's like a thing you run within the terminal and that kind of limits pretty severely what the user experience could look like.
2:58:42
Or you could do it in something, you know, with what we're trying to do, which is like basically create an interface so that you can do this kind of multi-threaded development and it's got a very natural interface and actually just like the interface of the command line is basically what you need.
2:58:58
You need a way of telling the computer what to do and like splitting off tabs and panes and watching it do it.
2:59:04
Honestly, you might not even need to watch it do it a lot of the time.
2:59:08
I I think that that's coming pretty soon, too.
2:59:10
Uh but like that's the interface.
2:59:13
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?
2:59:19
Uh be able to like hop in and actually edit.
2:59:21
Uh and so you can do that in Warp now.
2:59:23
And so, but like you know, it's going to do a lot of the work under your supervision. Yeah.
2:59:27
Is open source important to your business?
2:59:30
Do you have a horse in the race?
2:59:31
a horse in the race? Do you care about uh 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 what's the strategy there
2:59:46
super interesting question that I'm thinking about a lot right now uh 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
2:59:59
Yeah, I mean that's what people like, right? What's that?
3:00:03
What's that? Yeah, I mean that's just like the popular one that we hear about all the time and yeah, we have um we have sort of evals that that test all these models and like there are interesting models from OpenAI that are competitive Gemini from Google
3:00:16
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. Yeah, it's
3:00:29
Yeah, it's uh it's like the Sonnet uh it's like Cloud 4 and Sonnet and Opus.
3:00:33
Um I do think it would be awesome if the what what I want is like a healthy competitive model provider landscape to be totally honest.
3:00:44
I don't really want one model provider running away.
3:00:46
I would like to see uh these model providers continue to compete with each other to provide it does price down for you, right?
3:00:52
It it it brings the price down.
3:00:55
It brings the quality up.
3:00:55
Uh, and if at some point there is an open source model that is at the same level, that's super interesting.
3:01:01
Uh, cuz cuz where we're adding the most value right now is like it's in 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?
3:01:22
How how are you thinking about uh 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.
3:01:34
decade. I imagine and you know the the dynamic with anthropic obviously cares a lot about codegen 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 um you know it sounds like a great relationship right now but how do
3:01:56
you kind of continue to evolve it's a tricky one because they're they're we're both their customer and their competitor and so um I don't know how that's going to evolve like optionality, us having optionality does seem like a potentially uh valuable thing, but um you know right right now the way it is is like we're working great with Anthropic. They're
3:02:16
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.
3:02:26
Not too different from you know a place like Google or AWS who has like cloud infrastructure and also builds things on top of it. Mhm.
3:02:32
Um I don't think it's like a necessary condition for us to have a working business model that open source models uh like catch up as long as there's competition amongst the uh the foundation model providers.
3:02:49
If we were in a world where there was just sort of like one provider who won, I think that that's like 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. Yeah.
3:03:00
We uh I have a portfolio company that was kicked off uh one of the the the the big lab that will go unnamed that their business was entirely dependent on uh and over you know within basically 24 hours he had to like completely you know he ended up surviving and thriving uh but it was tumultuous but um but yeah sounds like a great relationship uh for now and and hopefully will continue to be. Yeah, that's great.
3:03:24
Uh thank you so much for stopping.
3:03:26
We'll we'll talk to you soon. This was awesome. Congrats on the lunch. Talk to you soon. Cheers. Bye.
3:03:32
Uh, next up we have Dra from Deli coming in the studio.
3:03:36
I think we got maybe who knows it. Will it be the real D?
3:03:40
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, D? What's our safe word? Just kidding. Um, what's going on? News. News. How's it going? It's great. Welcome to the stream. It's great to see you.
3:03:56
We We invited you on many months ago. I did.
3:03:58
But you were you were cooking too busy in the kitchen in the trenches.
3:04:04
Um well, do you have some news?
3:04:06
John's got the hammer ready. Ready. We do have some news.
3:04:09
Today we announced our series A with Sequoa. Let's go. How much? Boom. 16 million.
3:04:17
But luckily, you guys are early investors. Early investors. Fantastic. Proud. We love to see it.
3:04:24
uh give us marked up by by our friends over at Sequoia.
3:04:32
Yeah, give us the state of the union.
3:04:32
Uh how would you uh how are you pitching the product these days?
3:04:35
Yeah, so Deli lets people create a digital version of their mind to scale their expertise and you can kind of think about it like a new form of media.
3:04:44
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.
3:04:52
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.
3:04:59
And so that kind of spans across many different verticals.
3:05:03
We have coaches using it to scale their client practice.
3:05:07
We have authors using it to make their books accessible in interactive way.
3:05:09
We have CEOs scaling themselves internally in their companies.
3:05:13
And we have some people using this as like an interactive resume or LinkedIn.
3:05:19
Uh how are you thinking about the economic model?
3:05:20
I I take me through what's what's happening now.
3:05:23
But uh we had this interesting discussion with Derek Thompson, the the author of Abundance, and he was saying uh paradoxically his TV hits sold more books for the book that he was selling than the long podcasts.
3:05:39
Because if he goes on a podcast and he does two hours of content, people are like, "Okay, I got enough abundance.
3:05:45
I don't need to read the book because I got the whole Joe Rogan or the or the Lex Freedman deep dive."
3:05:50
But if he does a threeinut hit on NBC or ABC, uh, people are like, "Oh, that was interesting.
3:05:56
I'd love to dive into that book."
3:05:58
So, I can imagine there's this situation where if I'm an author or thought leader or something and I set up a deli clone and someone interacts with it for five hours a day, like they that's a good substitute for the rest of my content.
3:06:11
And so, I'd want to monetize that to the max.
3:06:13
So, I want to hear about monetization now and where it's going. Yeah.
3:06:16
So, we have some people monetizing their deli and making multiple seven figures in revenue.
3:06:20
And this is like in Oh, that's a lot.
3:06:22
And and the the consumer phone calls with these deli can span up to six hours. 6 hours on the phone.
3:06:30
Six hours, but you're choosing your own adventure.
3:06:34
So, course completion rate is at an all-time low.
3:06:36
All of our course creators are like, "It's a course winner.
3:06:39
People's attention spans are declining.
3:06:41
They want more guidance." Course interesting.
3:06:43
Monetizing your deli directly is an option.
3:06:45
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.
3:06:57
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.
3:07:09
So the analytics actually ends up being very valuable. That's awesome. Um, yeah.
3:07:14
What what what is the next year look like you guys?
3:07:16
I mean I I I feel like I have so much context on the business.
3:07:20
Uh um but but what what does the next year look like for you?
3:07:26
I feel like you guys have had competitors already kind of come and go.
3:07:31
Um how are you think uh how are you thinking about the market?
3:07:35
Um and uh what are you guys going to be focused on?
3:07:38
Yeah, I mean when we started the company, you know, the first year things were just not working and most people uh 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.
3:07:53
So I think past that first year, we got that quality and trust.
3:07:55
Now we have thousands of customers who have created a digital mind of themselves.
3:08:02
And the next step is how do we bring on the next million people?
3:08:03
How do we make it easy for someone who isn't Tony Robbins to create a digital mind and actually get value from it?
3:08:10
And the the common use case we see is twofold.
3:08:12
One is a new kind of personal website for the internet where if someone wants to pick your brain, they can talk to your deli 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.
3:08:26
So that's on the consumer side and on the actual creator side.
3:08:28
So people are monetizing their deli, but what the consumers actually want is guidance.
3:08:36
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.
3:08:45
And uh the beauty of Deli is as the models get better, context windows get longer, Deli's product experience get better. Is that right? Yeah.
3:08:59
And the service area with the product experience is kind of three-fold.
3:09:01
One is our digital mind architecture which we're actually trying to capture your mind and worldview and how that changes over time.
3:09:06
Two is the actual experience for creating your mind, getting the insights, monetizing it.
3:09:11
And then there's the consumer experience for calling, messaging, and video calling. That's great.
3:09:16
What um uh what what does success look like over the next year?
3:09:20
I I I know you're very ambitious.
3:09:22
you've already onboarded, you know, massive number of uh kind of A-listers from different categories.
3:09:28
What what are you looking to prove over the next 12 months? I think twofold.
3:09:34
Uh we want multiple Deli millionaires making money uh versus just a couple.
3:09:39
It's like a new field of monetizing your expertise.
3:09:41
And we want 100,000 to a million people using their deli as their personal page on the internet.
3:09:47
I think that'd be a very good outcome.
3:09:50
Uh, talk to me about some of the weirder potential deli that you could potentially interact with in the future.
3:09:57
Uh, character AI for a while would let you talk to Joseph Stalin.
3:10:00
I tried to debate Stalin on the merits of capitalism versus communism.
3:10:05
And the the model that they rolled out was kind of too rfed.
3:10:10
So, it kept saying that communism was bad.
3:10:13
And I was like, I don't think Stalin would be making those points.
3:10:16
This feels like an American.
3:10:16
But uh have you thought about offering uh 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?
3:10:35
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.
3:10:43
We don't allow people to create a digital version of anyone who's not themselves or that they don't have permission.
3:10:49
So, we couldn't do Steve Jobs right now unless we have like the Steve Jobs Foundation's permission. Interesting.
3:10:54
And in terms of legacy, you guys know the idea of the company was inspired by me wanting to talk to my grandfather.
3:10:59
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.
3:11:06
So, I think best world is eventually we can just have a free tier for people to do that with their parents and grandparents.
3:11:11
And that's not really a business model for us, but rather just like a good thing people want to remember their families. Yeah.
3:11:15
How do you how do you think about um just like data capture and and creating the the training data for these individual clones?
3:11:24
I think um we're in a unique situation and that we we uh record 3 to four hours of live video content a day.
3:11:32
But a lot of people are saying like it's not enough. Yeah.
3:11:34
A lot of people they really need to go to eight hours so that it can always be on while they sleep as well. Yeah.
3:11:41
BCI just pipe it directly in 2x they need 48 hours a day. Yeah.
3:11:44
2x they need 48 hours a day. Yeah. Uh but yeah, data capture what what what are the what are the richest sources of of content that actually the other thing that like an interesting challenge is you know people have certain views that they want expressed online and then
3:12:00
other views that you could capture that they don't want expressed online right so if you wanted to if a if an investor you know wanted to uh 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
3:12:16
So I feel like it's a hard challenge to figure out what information should actually be made public and and actually trained on.
3:12:27
Yeah, representing a human being in every facet of their life is is very difficult.
3:12:30
But uh we have a couple ways we thought about this in terms of data sources.
3:12:34
YouTube, social media, notion, Google drive uh 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 itself.
3:12:42
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.
3:12:55
And then like you said, who you are at work is different than who you are with your friends.
3:12:59
You may behave differently.
3:13:01
You may share different information.
3:13:02
So now we have this ability uh to separate different versions of your mind that has different access to data.
3:13:10
Right now you have to manually do that.
3:13:11
So I I have one for eventually my great grandkids that has more intimate DAR data, but ideally it can be an intelligent and it knows what you would say depending on who the person is. That makes sense.
3:13:22
How are you thinking about working with the underlying labs?
3:13:23
I know you've had some problems historically uh with with different vendors, but what what's your updated thinking?
3:13:31
Are you guys leveraging open- source in a big way these days or or have you found um good ground with with uh some of the core labs?
3:13:41
Yeah, we're kind of both.
3:13:41
We have some of the core labs, we have open source.
3:13:45
Um 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 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.
3:14:05
Um I want to know about like the the the different like touch points here that you could potentially go after.
3:14:12
I remember there's this do you remember this trend where uh social media influencers would be like I leaked my phone number. Do you remember this? Yeah.
3:14:20
Or they'd be like text me community. com. Was that community. com? Yeah. Yeah.
3:14:24
And so there's a world where somebody that like I I think that was basically just like injust 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.
3:14:37
Um, but you could imagine that being a an interaction point for essentially I mean you get to be an influencer at scale.
3:14:44
There might be it's almost like customer service and you're interacting with basically like an FAQ like hey I I you know I want to know where to get a TBPN hat like can you tell me and and just being able to DM your personal profile on X and interact with that or text you.
3:15:02
Um that's one kind of modality that people could interact with.
3:15:06
Uh there's also like the big social media companies could put a button there that allows you to chat with that user directly.
3:15:13
And so um how do you see the market playing out?
3:15:17
What are you worried about?
3:15:17
How are you counterpositioning against the different uh players or different Yeah, I remember I remember the exact day that Meta launched uh digital clones in their own way.
3:15:29
Uh and I think Dar went through the cycle that every entrepreneur does when they get uh when somebody else you know attacks their One, all the VCs text you, "Have you seen this? Have you seen this?" Yeah. Step two, just enraged.
3:15:40
Uh, step three, realize that, you know, it's not actually going to end you and and it just validates your pre-existing and your business might grow faster because because more people are aware that this is a thing and they might want a better version of it.
3:15:54
But yes, uh, yeah, just general understanding the marketplace.
3:15:58
Yeah, I think there were a couple core decisions we made early on that have set us up for success.
3:16:02
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.
3:16:15
You own your digital identity.
3:16:15
We're not training models on it.
3:16:17
Um, 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.
3:16:24
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.
3:16:31
So a lot of big tech companies are walled gardens like it's it's only in those platforms where Deli you can create your digital mind SMS, WhatsApp, Zoom, Slack, Discord, Telegram, all these different sources and it's a central source of of that.
3:16:45
And then three, I I just think that it's such a new habit.
3:16:47
Deli isn't really meant to be deceptive.
3:16:49
Like it doesn't reply to emails for you or respond to DMs.
3:16:52
It's more of just like a new form factor of consuming someone's content.
3:16:56
So on Instagram, it's a platform that promotes people who are very aesthetically pleasing where Deli promotes people who are pleasing for very different reasons.
3:17:05
And so it's just a different incentive structure in terms of the network and who gets up to the top. Totally.
3:17:09
What are you guys hiring for? Yeah.
3:17:13
What does it take to earn $100 million at Deli? Yeah.
3:17:14
Are you guys hiring for any AI research researchers?
3:17:20
Any nine figure signing bonuses?
3:17:20
not training any foundation models right now, but we are looking for AI people and a lot of design engineers.
3:17:25
I think uh the interface for the n mind needs to be beautiful.
3:17:30
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 and 500 years from now.
3:17:42
It needs to be beautiful.
3:17:42
So, design and design engineering.
3:17:43
Well, we'd love to recommend Figma and Linear for you and your team if you're not already using them.
3:17:49
They are sponsors of this show.
3:17:50
how they make it possible. Check them out.
3:17:52
I don't think you heard it here first.
3:17:55
It's a name brand in the Sequoia backed world.
3:17:57
Uh, congratulations to I I know this round 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.
3:18:13
Production team's getting better.
3:18:15
They can cut to the gong cam when the gong when the gong hit happens.
3:18:20
Let's hear it for the production team.
3:18:21
It's great to see you, Dra.
3:18:22
Congratulations on the milestone.
3:18:22
Come back when there's more news.
3:18:24
Come back on when you have more news. We'll talk soon. You're the man. Cheers.
3:18:30
Uh, in other news, friend of the show, Bos, not really a friend, but yet we hope he will be a friend.
3:18:37
We covered his uh beautiful profile of his house in the mansion section. He followed us.
3:18:42
So, we're gonna get him on the show soon.
3:18:44
We got to make it happen.
3:18:45
I'm the biggest fan of this guy.
3:18:47
Uh he posted that the MetaQuest 3S Xbox edition is now available.
3:18:53
Everything you love about Quest and Xbox in one sweet package. It's sleek. It's awesome.
3:18:58
And it's limited edition. And you know what else? I already ordered one.
3:19:02
It's coming to the studio. There we go. Yeah, I'm very excited.
3:19:04
And And so I I mean it doesn't seem like this is like the next what we said.
3:19:09
This is a real risk factor. Sean's gaming addiction.
3:19:15
I'm not addicted to alcohol.
3:19:15
I'm not addicted to gambling.
3:19:16
I'm addicted to video games.
3:19:18
Seriously, if I ever go down a real bender, I will take too because I've never seen you play video games. Oh, yeah.
3:19:24
The entire time we've been in the show, I haven't logged an hour of video games.
3:19:27
I haven't played them in a long time.
3:19:28
But you get me the GTA 6 drops.
3:19:30
I'm just ripping this thing off.
3:19:32
We might be using the Deli here in my We got to go live. Yeah.
3:19:35
But I have been uh so so this is not the Quest 4.
3:19:40
This is not a a 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.
3:19:52
And you will like like the resolution will be remarkable because that's what the Apple Vision Pro did so well.
3:19:58
That technical hardware now exists in the world.
3:20:01
Meta's clearly going to go get that and bake that into the next Quest 4.
3:20:04
But, uh, the Quest 3S has already been a pretty solid product.
3:20:10
But what they're doing here is they're leaning into video games that are not VR specifically.
3:20:14
And I think that this is 100% the correct move.
3:20:16
Because so much of VR content is this chicken and egg problem.
3:20:22
No game developer wants to go and spend I mean, how long have they been working on GTA 6? Like a decade.
3:20:28
Like, and it's cost them like a billion dollars.
3:20:29
No one wants to do that if no one has the VR headsets.
3:20:31
No one no one wants to buy the VR headsets if there's no GTA 6 on it. So, what do you do?
3:20:37
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 dollar or a TV that's a couple thousand bucks.
3:20:50
You throw on this headset that's a couple hundred 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.
3:21:01
So I'm very excited about this partnership.
3:21:03
Excited for them go deeper and Microsoft early meta investor actually. There you go.
3:21:07
So well we have in the studio get the hammer ready. Oh yes yes yes. Give us the number. What's the news?
3:21:15
What's the new revenue 100 boom? [Music] Let's go. Incredible. Congratulations.
3:21:27
I thought it was going to be 100 uh 100 bangs. 100 bangs.
3:21:29
We'll have to do it after the show, but I will give you one of these. Success.
3:21:34
Classic overnight success. Replet. There we go. All right, John. I broke the hammer. He broke the hammer.
3:21:42
Uh, Replet's going so fast, the hammer broke.
3:21:46
The hammer hammer breaking growth. Congratulations. How did you do it?
3:21:50
What's the What's been What's the one simple trick? Yeah. Yeah.
3:21:52
What's the secret to success?
3:21:54
It's It's been easy, you know.
3:21:57
Just did a little bit of work. Not Not too many years.
3:21:58
You know, I started working on on Replet back in college.
3:22:04
Uh like I had the idea for it back in college and um actually the first implementation of it was open source and it went viral on Hacker News in 2011 and um and then I sort of we we left it for a while.
3:22:17
um didn't work much on it and then uh actually my wife Haya who's who's my co-founder kind of revived the project in 2016 we uh started as a company um and it was it was brutal.
3:22:33
We barely were able to to raise money.
3:22:37
We tried to sort of like bootstrap it initially.
3:22:38
Um during the pandemic we sort of took off especially as you know we were the only sort of collaborative editor in the cloud and when um 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.
3:22:58
Um, and with the launch of Replet agents back in September, uh, we created a category basically of prompt to application.
3:23:07
Um, and and 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.
3:23:21
I feel like your company is now maybe the only AI company that's appropriately hyped. Like it's not overhyped.
3:23:29
you haven't raised the $10 billion round and you're paying the hund00 million salaries, but also the growth's been really serious and the business is really real.
3:23:37
Uh, which is which is great to see.
3:23:39
Uh, how have the uh the crazy news of the hund00 million salaries been affecting you?
3:23:45
Is it harder to hire these days?
3:23:48
I know you've kind of changed the structure of the team, relocated the team, I believe.
3:23:53
So walk me through the current hiring market for uh the type of engineers you're trying to hire.
3:24:00
Yeah, so a few things that's uh sort of different about Replet.
3:24:05
One is the team is relatively small.
3:24:08
We're still around the 70 75 people.
3:24:10
Um we haven't been growing all that fast.
3:24:13
We are not in San Francisco, which makes it a little harder to hire.
3:24:17
We're in Foster City, probably the only startup, perhaps maybe there's a couple others in in Foster City.
3:24:22
Um and you know we just take a different approach to the culture and we like expect more commitment and want people to come to replet and work for a long time.
3:24:32
replet and work for a long time. Um especially since you know I've been working on this for so long my mindset is that it's just going to take a long time and like San Francisco Silicon Valley culture has been increasingly about you know I'm going to go spend 12
3:24:46
months here 18 months there and um and so yeah we're building it more methodically um in terms of hiring definitely it's been it's been very competitive u and you know um I love OpenAI and and Sam and you know he he's talking about how Zuck is is doing that to them, but obviously OpenAI is doing it to the rest of us. And so it's just a
3:25:08
And so it's just a different scale.
3:25:11
You know, they're trying to poach their employees for 100 million.
3:25:14
They try to push everyone for 10 million.
3:25:16
So, uh just a factor of like how much revenue I guess you're making.
3:25:21
Uh but like but it's part of part of from a hiring standpoint because you're keeping the team small now.
3:25:24
revenue per employees over a million dollars per employ new valuations at some point will allow you to sort of have comp you know be competitive from a comp standpoint. Yeah, exactly.
3:25:37
Yeah, exactly. Um and 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 um and so again we're trying to build the business for
3:25:55
the long term and instead of like playing the the hype game when you've been building a company for as long as as you know I've been you know you've you've b you've been through so many ups and downs and hypes and lows that you just become very steady-minded about it. Yeah. Totally. Um I guess like the Yeah. Totally.
3:26:11
Um I guess like the bigger uh not to not to no pun intended, the meta question here is uh is are we in a new era of valuing the leverage that truly worldclass managers or AI engineers can have, the impact that they can have and reassessing the value.
3:26:32
We've talked a lot about this on the stream that uh Apple's culture doesn't seem to be receptive to paying an NBA level salary.
3:26:40
And Tim Cook, he makes $75 million.
3:26:43
He doesn't even No, he doesn't make doesn't even make 75. He only makes 74. 6.
3:26:47
It's a big number, but it's tiny considering their market cap.
3:26:52
And what if you could come into Apple and move the needle 1% that's a $30 billion market cap move?
3:26:58
could you capture 1% of that?
3:27:01
That's still $300 million.
3:27:04
And yet they're not valuing talent in that way.
3:27:07
It feels like there's a change in strategy at Meta.
3:27:08
Um do you think that that's a do you think that that's a unique case in where we are in the technological roll out of AI or is it more that we're finally catching up to just understanding the economic dynamics and impacts like the NBA has for years? Yeah.
3:27:26
So you know the uh the buzzword in Silicon Valley for a long time has been the 10x engineer.
3:27:35
About you know two two three years ago maybe in 22 I talked about the thousandx engineer. Yeah.
3:27:41
engineer. Yeah. what you know highly kind of leveraged by uh autonomous agents when you right now people with replet cloud code and others they're spinning up multiple agents to work on their project as they're you know working on their main tasks and there's
3:27:59
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 you know we talked about engineering managers I think every engineer is a sort a manager right now. And so, yeah,
3:28:12
And so, yeah, I mean, we're we're not at a thousandx yet, but we're we're going up.
3:28:16
I think I think pretty soon the difference between a great engineer that knows how to use AI tools and an okay or good one, it's going to be 100x, I think, over the next 6 to 12 months.
3:28:28
So, the compensation structure, I assume, would start to to change to match that.
3:28:33
How do you think about Replet's potential today?
3:28:36
about Replet's potential today? uh it seems like every day in the timeline you know you know the obvious thing is everyone becomes an engineer and you know it's being able to create software is fully democratized but every day in the timeline I see people realizing how
3:28:54
much they spend on different SAS products and thinking how much time would it really take for me to kind of make a version of this for myself that fits my very specific need like document signing talk to the CLA CEO about this yeah some some something along those lines. And so, um, is part of of the
3:29:10
And so, um, is part of of the potential that you see CEOs and companies everywhere sort of running that sort of buy verse build calculus in terms of all sorts of tooling that they're using internally, externally, etc.
3:29:25
, and seeing, you know, trillions, you know, or hundreds of billions of dollars of of market cap that that you guys could um ultimately replace. Yeah.
3:29:35
I mean, look, right now there is sort of information asymmetry.
3:29:38
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.
3:29:50
Um, I met someone from Australia the other day here uh in Silicon Valley.
3:29:56
He stopped me on the street.
3:29:58
I was like, I love Replet.
3:29:58
He runs like a construction company and he's like, you know, I'm the CEO now and I'm the most productive engineer at the company.
3:30:06
I like build all these tools and dashboards and I replace monday.
3:30:08
com and all this other stuff with uh homebuilt stuff that is exactly bespoke and works exactly for my use case.
3:30:18
Another story, uh, guy, his name is, uh, Ahmad George.
3:30:22
He works at a skincare company, I think, in in DC.
3:30:26
And he's an operations manager.
3:30:28
He's responsible for like the ERP systems and things like that.
3:30:33
They he had an intuition that they could automate, I don't know, big percentage of the work, 20 30% of the hours of human work.
3:30:40
and um he went and got a quote from their from Netswuite to build this piece of software automation software.
3:30:49
It was $132,000 to build.
3:30:49
So he went to Replet, 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."
3:31:01
And the CEO gave him $32,000 for the Wow, that's awesome.
3:31:08
So um so yeah it's you know there's a period of time at some point you know the market will like equalize as everyone realizes that you can do this stuff but for now there's a massive arbitrage opportunity. Yeah.
3:31:19
Uh as you build out agents and agentic workflows do you have are you limited by data for RL pipelines?
3:31:29
Are you are you buying any services from the scale AIS of the world or the merors 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 that?
3:31:45
You know, having been uh a platform where millions of people coded over the years um actually we could be a supplier of data. Oh, interesting.
3:31:56
So, uh so yeah, we we have all the all the data we need.
3:31:58
Um, I think it's still early for us to try to exploit all of that and we're hiring as fast as we can.
3:32:06
So, if you want to come work on AI at Replet, I think we have a really exciting uh opportunities to to use data to kind of create amazing new capabilities. It's very cool. I have another question.
3:32:18
Um, are you feeling the acceleration in software development?
3:32:27
I I was thinking about this easy when you refresh the Stripe dashboard and Yeah. No, no, no, no, no. I get that. I get that.
3:32:34
But as a consumer, I was just thinking about like like the apps on my phone still haven't changed as fast as I've thought.
3:32:43
And there's there's in my in my business folks are using different tools but it doesn't it doesn't feel like the rate of like churning for most consumers like we like we like we're we're not rebuilding all the different consumer apps right now.
3:32:58
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 AIdriven apps or uniquely enabled by AI apps.
3:33:10
There's a lot of creation tools. So like V3 is amazing.
3:33:16
That got me to install the Gemini app and I paid for that and I enjoy generating my my poultry.
3:33:20
Three video queries per day, sir. May I have some more? Sundar, please. Maybe you can help me.
3:33:30
I think don't you know him? We're good partners.
3:33:36
But yes, Tik Tok feed is 100% AI now.
3:33:39
And maybe because I like them so much.
3:33:40
I've been into the Bigfoot. Yeah.
3:33:40
So maybe that's like the instantiation of the consumer adoption of AI is like you're a consumer through Tik Tok as opposed to through like it's a very 2010 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.
3:34:03
Is that the right framework?
3:34:04
Yeah, I I think I think you're right.
3:34:07
I I do think that Apple is probably holding back the ecosystem.
3:34:09
I mean, Apple really has been attacks on startups, has been attacks on innovation.
3:34:16
innovation. I love this company as much as anyone would love Apple, but but they they are they are sort of like a government in a way that there 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 to I go to perplexity like 100 times a day like I
3:34:35
should be able to like press a button just like talk to it talking to me but you know it's it's not working that way and it is frustrating but look I I think you know AI I uh adoption is moving as fast faster than any technology adoption we've seen in the past, faster than faster than mobile, but it still doesn't feel fast enough like you say. And by
3:34:55
And by the way, this is an interesting kind of data point on, you know, the the folks that are really worried about AGI and things like that.
3:35:03
The limiting factor to adoption is really humans and corporations and governments and all of these things are very very slow.
3:35:10
Yeah, this is kind of the Tyler Cowan 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.
3:35:20
Is there anything else on the Apple side?
3:35:22
Uh my takeaway from WWDC was that ondevice inference could be a catalyst for uh an app store explosion, an AI app explosion.
3:35:32
Uh then there's the ruling about third-party uh payment processing things that that like like the tax is becoming less of a requirement.
3:35:40
Maybe you can work around it.
3:35:43
And so maybe the barriers are dropping ever so slightly. Yeah.
3:35:47
And I feel like I feel like you would you would see this earlyt developers become really excited about this sort of effectively free inference where they can launch an app that goes viral without worrying about, you know, running up some bill with OpenAI. Yeah.
3:36:02
I mean I mean look the uh Apple has held back the web quite a bit as well.
3:36:05
Like there's no reason why native apps should be much better performing than uh than web apps really.
3:36:14
There's no fundamental physics reason for that.
3:36:16
I've actually um the head of product at our Jordan Walk and and myself worked on uh React Native.
3:36:23
He's the inventor of React and React Native at at Facebook.
3:36:25
React Native at at Facebook. And the the reason we worked on that is we felt at Facebook we felt sort of like oppressed by Apple like they controlled what we launched when we launched it and they would like you know reject you we'd have a launch and it was delayed by Apple and
3:36:42
so the idea behind it is like can we ship over the air updates very very quickly and 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
3:37:01
I saw you guys talking about VR, AR is another one. A is another one.
3:37:06
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.
3:37:14
I think everyone's feeling that that the form factor needs innovating.
3:37:18
And I think this is how you break out of the like Apple jail. Wald garden. Yeah. Yeah. This is great. You got to come back on.
3:37:24
We could yap about all different news stories.
3:37:26
Do you have anything else, Jordy, you want to get right now?
3:37:29
No, we we got to get you on regularly. Yeah. Yeah.
3:37:30
This last time I was here, I got cancelled.
3:37:32
So, no, we went that was the most viral clip of that month, I think. What What happened?
3:37:39
I think Well, I asked I asked, "Should people learn to code?"
3:37:42
And he gave kind of a controversial answer saying like, "No, you shouldn't learn to code anymore."
3:37:47
And it got like millions and millions of views.
3:37:48
So, I bet it drove I bet it drove some some signups for sure. For sure. Learn to vibe code.
3:37:54
You gave a very nuanced answer.
3:37:56
I don't think there was anything that crazy about it.
3:37:58
The internet does not understand nuance.
3:38:02
Cancelled and viral are two sides of the same coin.
3:38:04
Like doesn't matter anymore. Doesn't matter.
3:38:06
Yourself, you know, haters going to hate. Yeah.
3:38:08
Just don't get deplatformed from Gemini because otherwise the the three VO prompts will be zero and it will and your life will be miserable because you got to prompt those. Thanks guys. You do great work.
3:38:21
Really appreciate the show. Yeah.
3:38:21
Well, come come back on at 200.
3:38:23
At this rate, it'll probably be next week. Next week. Let's do it.
3:38:27
We're ready with the gongs. Ready to go. Yeah.
3:38:28
We'll get a new hammer, so we'll be ready. We'll talk to you soon. Cheers. Bye.
3:38:32
Uh, next up, we have Dirt. Dirt man.
3:38:35
Uh, another anonymous account.
3:38:40
Uh, I don't know why he's anonymous, but he's launching.
3:38:45
He launched uh cheaprootarm. com today. Very excited for this.
3:38:49
He's making a cheap robot. Go buy them now.
3:38:54
He we we cover He used to have a different name on the show.
3:38:56
We used to cover his post.
3:38:58
I used to laugh every time because but it was it was rude.
3:39:00
So we just call him Dirt Man. Welcome to the stream. Dirt. How you doing, Dirt Man? No, he changed his name.
3:39:05
He dropped He dropped the parenthesis. Wow. Classing it up. Introduce yourself. Who are you? Yeah. Yeah. Uh hey guys. Uh my name's Angus.
3:39:13
Uh yeah, I'm I'm just a I'm an engineer from Australia.
3:39:16
Uh my background is 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.
3:39:26
Um yeah and it's uh you know building building this mini one.
3:39:33
It's really just it was really like a stepping stone for me on the way to building welding robotics.
3:39:38
the way to building welding robotics. um you know I've got some larger robots where I'm just setting up a workshop currently uh to do basically strap on cameras sensor systems and drive the whole thing drive the whole thing via AI cuz you know it's basic we're basically
3:39:52
at the point where there's you know uh 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 um and so this like this small robot that I that I've got on, you know, cheap robot uh arm.com is great. Uh was really com is great.
3:40:12
Uh was really really Yeah.
3:40:17
I mean, I'm I'm surprised that it was available. I was like, "Hell yeah." [Laughter] That's great.
3:40:23
But uh but it was it was really just a test bed.
3:40:25
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.
3:40:34
you know he's built working on the vision system but it's really a test bed for us to you know you know validate our algorithms do small scale uh prototyping you know my the picture that I've got up there you I don't have uh many demos because it was basically thrown together at like 2 a. m.
3:40:51
night time last night, you know, got the Shopify store up and running and doing it live.
3:40:56
So, what what do you want people to use these for?
3:41:00
What are the use cases that you're imagining? Yeah.
3:41:04
So, very much the same as uh I would say those le robot ones.
3:41:06
Um it's just a much more robust platform.
3:41:09
So, improved like improved power in the servos, improved like structural integrity.
3:41:15
Um, but the key like one of the key differences is I've actually built a like an industrial quality like kinematic solver.
3:41:24
And basically what all that what that's telling you is you know where the end where the endector of the robot needs to be.
3:41:30
There's usually like a whole bunch of equations that you either solving numerically or you've got a you know a solver in a low dimensional space that you can work out really quickly.
3:41:38
quickly. Like I built a like I've built a really robust one for um for like six degrees of freedom and then this is just more than you get with the uh with I guess what's typically being used in all of those like AI like hackathons and so I've written all the software so you can
3:41:55
take uh all of the outputs from an AI model and just stream joint commands to it you know connect it to like things like Nvidia's sim but you can also run it like a traditional industrial robot um and like and do path planning for really really high fidelity you know, trajectories and controls. Uh,
3:42:09
Uh, and like the benefit of that is like all of that all of that information uh that you can stream and record from those joints as you use the high quality kinematic solver is you can use that as the training data.
3:42:23
So you see a lot of these guy like a lot of these robot systems, they've got, you know, 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.
3:42:32
Um, and that like you're just streaming like this joint uh should be the joint angle of this other robot.
3:42:39
Uh, and frankly that's really crap data for training robots.
3:42:42
Like the like you get it done, but you can see all the movements all janky.
3:42:46
It's the same kind of movement that the human's doing with a robot. It's awkward.
3:42:49
Um, but you like you know industrial robots, they've been uh doing this for decades and they have really nice trajectories, really smooth path path planning.
3:42:57
But the bottleneck is like how do you get that high quality data?
3:43:00
Um, and you know, with this software combined with this, you know, little robot package, that's what I can, 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.
3:43:11
You don't need to buy like the equipment for two. That's amazing.
3:43:13
Um, what how is the health of this sort of open-source robotic hacker world right now?
3:43:20
We had Clem on earlier from Hugging Face and he said this was an area that he was most excited about uh on on on his platform and and he you know he said they hosted a hackathon recently.
3:43:31
It sounds like there's a lot of exciting activity here and you're contributing to it yourself. Yeah, that's it.
3:43:38
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 uh it'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 part like not just robotics but on the hardware side right it's uh you know it's like my
3:43:58
background is aerospace and mechanical engineering you know was uh you know built rocket engines once upon a time and it's you know uh you know we kind of got left out in the cold you know via Silicon a little bit, you know, you saw like,
3:44:11
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, you know, a whole range of them. And I think there's a lot of like
3:44:20
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.
3:44:32
So, I've woken up, you know, uh, we got we got three sales so far. There we go. Boom. Congratulations. Thank you guys. Thank you guys. That's three sales.
3:44:44
That's 1,500 bucks in one day. You idealize that.
3:44:47
I think we're in the millions.
3:44:50
I think I think if you put together the right deck, maybe you take a trip to Sand Hill Road.
3:44:56
You tell the right story. A quick flight. 200 on a billion to SFO. 200 on a billion. Easy. Get it done. Get it done. Yeah. Yeah.
3:45:03
But you know it's uh you know I think like you said like hey my valuation should should be the same as figured cuz I've now shipped more apparently. Shots fired. Shots fired. Not my words. Yep. Yep. Oh yeah. Yep.
3:45:17
Was uh was cooking earlier. Yeah.
3:45:21
I mean this uh this feels like something that uh would would be perfect for the AI grant program from Nat Freiedman.
3:45:30
you know, this is going to be the enabling technology.
3:45:34
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.
3:45:39
I hope Nat can continue that program.
3:45:42
He's certainly has the resources for it.
3:45:44
Uh, and it'd be very cool to see that partnered up with the I would like a robot.
3:45:52
I'm definitely keen to head to the US.
3:45:54
Uh, like you about 18 months ago, I stopped by the Gundo, you know, met like Augustus and like a bunch of other fellas.
3:46:00
It's been awesome to see those guys like, you know, I think I, you know, I went there when Valer Atomics was just a squat rack in an empty room.
3:46:07
Um, it was just a squat rack with scraps.
3:46:13
Uh, well, you seem like an alien of extraordinary uh robotic abilities. So, you know what?
3:46:18
My vote is we get you over here. Bring you in. Yeah. This is fantastic.
3:46:22
Be there in a in a couple of months, I think. Great.
3:46:24
Well, let's tune the robot up to crack open uh that would be useful. on the desk.
3:46:30
It' be great if we could just hit a button cuz it's hard to reach over here and and and crack them ourselves. Yeah, it's brutal.
3:46:39
Congratulations on the lunch. Yeah, thank you so much.
3:46:41
Really appreciate it, fellas.
3:46:43
Um and yeah, love the show.
3:46:43
Been a big fan since the beginning. So, keep it up.
3:46:47
Remember, I'll never forget your name.
3:46:49
First time it came up in the deck. Um this is great. Amazing. We'll talk to you soon. Have a good one. Cheers, Angus. Have a good one. Congrats. Bye.
3:46:59
Um, should we go through some timeline? Get out of here. Move on.
3:47:01
We got a big show tomorrow.
3:47:03
Let's rip a little timeline.
3:47:05
A little Just a little timeline couldn't hurt.
3:47:07
We got Will Manitis talking about the No, there is no real index of wealth in the world other than the land owner. Landowner 100.
3:47:14
Everybody should be aspiring. Total acres.
3:47:17
John Malone's got over two million.
3:47:19
Ted Turner's got over two million.
3:47:21
Uh, I like the Reed family here at 1. 6 million. Picture of a bear. just a picture there.
3:47:27
I don't know if that Do they not have another picture that they could pull from? I have no idea.
3:47:31
I think I think people should just buy land.
3:47:36
Just go buy start with an acre. Could be anywhere.
3:47:38
Could be out in the desert. Start with an acre.
3:47:40
Just add just double it every day for 100 days and you're good.
3:47:44
Yeah, just double getting the landowner 100.
3:47:46
Uh Doomer says, "How it feels to charge your phone off your MacBook Pro and it's refueling the B70." It really does.
3:47:53
I mean, this could be so accurate.
3:47:56
Yeah, I mean a million views makes sense.
3:47:57
Yeah, it's a perfect analogy.
3:47:59
You know, you're you got some juice. It's fantastic. You're sharing it.
3:48:02
You're both running out of juice.
3:48:02
We got to talk about this one from 9 to5 Mac.
3:48:05
Uh control center is now darker and much more blurred in iOS 26 beta 2. Good news for Tyler.
3:48:10
He's been struggling with iOS iOS 26 beta 1, but beta 2 is now available.
3:48:16
The contrast ratios have been fixed, improved. It's easier to read.
3:48:21
We knew Apple would do this.
3:48:21
We called this out that any of the criticism that you lever at uh at at Apple's design chops, it's it's not going to be an issue by the time they launch.
3:48:33
Uh Tyler, how has uh how has daily driving iOS 6 uh iOS 26 been over the last few weeks.
3:48:40
Um I mean, I think overall it's been very good.
3:48:43
I I think most of the issues it's just it's hard to tell if it's cuz my phone is just so old iOS, but I think overall like it looks really nice. Um Okay.
3:48:51
Yeah, I think it's great. Well, you're Yeah.
3:48:55
Okay, that's good to hear.
3:48:55
Uh 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 since that fateful day. No, no, no. It didn't break.
3:49:07
Uh thank you for being a guinea pig for the world.
3:49:09
Yes, Arvin from Perplexity is uh building in public.
3:49:13
Building a competitor to Bloomberg in public. I love this.
3:49:15
He's searching Perplexity.
3:49:17
How much revenue does Bloomberg make yearly?
3:49:19
He's been pretty open about wanting to build like a new version of the Bloomberg terminal.
3:49:25
And so he's just searching how much money do they make and he says Bloomberg makes 12 billion in annual revenue with 10 billion coming from the terminal.
3:49:31
And then he's just like throwing this out there like hey maybe I'll maybe I'll do this like maybe you should invest in this.
3:49:37
It's like it's it's a hilarious thing to post.
3:49:39
Well, I've been I've been a recent DAU of Perplexity. Oh yeah.
3:49:41
A lot of value out of it.
3:49:44
I mean it makes sense in the free tier.
3:49:46
It makes sense that but they're gonna get me soon. Yeah.
3:49:49
It makes sense that that uh an an LLM company, an AI company, it's like they either it does feel like there's a fork in the road for perplexity.
3:49:56
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 the core product is a very different product to try to actually compete with terminal versus displaying data.
3:50:12
Distribution is just so is so important.
3:50:15
I mean, we saw this with duck. go go.
3:50:16
Like a lot of people in Silicon Valley, a lot of power users preferred Duck. Go to Google, but Duck.
3:50:20
Go never got to the scale that Google did just because of distribution.
3:50:25
And so, um, you know, he's clearly looking at Bloomberg.
3:50:29
There's rumors that he's talking to Apple.
3:50:31
It's interesting to see where that goes. But he's cooking.
3:50:36
Anyway, Pier Richelen from Cal.
3:50:36
com says, "I think organizing land parties for 30 plus year olds could unironically be a banger.
3:50:42
Warcraft 3, Battlefield 1942. I played that game. Great.
3:50:45
Uh, Age of Empires, Dota. What else?
3:50:47
I don't know why you got to have 30 30 year old plus.
3:50:50
Bring the Teal Fellows in.
3:50:50
Bring the Bring the I didn't really play those games, John. You're dating yourself.
3:50:55
Yeah, but they can pick it up.
3:50:55
I mean, a lot of these games, but it's about the nostalgia. Yeah.
3:50:58
I went to a hackathon last year put on by a venture capital firm. It's fun. They had some Halo.
3:51:03
Halo 3 was the popular one.
3:51:06
But the new Halo, if you install it, they just give you all the previous Halos.
3:51:11
You can just play any of them in like the in like one disc, I guess. Just like Yeah. Buy the current one. It's like SAS now.
3:51:18
You buy the current one, you get you get all the previous all the previous ones.
3:51:21
Uh should we close with uh cow tech startup? Yeah, this is exciting. On R for Rock. Confirmed. One month earlier. One month early.
3:51:32
Cow tech startup becomes New Zealand's latest unicorn in $100 million fundraising.
3:51:37
Rare New Zealand unicorn.
3:51:40
I said this was very bullish for beef for cows. For cows, it's bullish. Did you not see that? Knees slapper. Knees slapper. Knees slapper.
3:51:51
Well, we could just keep going all day long here, John, but um if you get a text message from Mark Zuckerberg or an email, do not assume that it's fake.
3:51:59
He has taken over recruitment for the super intelligence lab and is reaching out to hundreds of prospects personally.
3:52:04
If you respond, this next step is an invitation to dinner.
3:52:07
So, he's he's in founder mode. He's grinding.
3:52:11
He's putting together the Avengers.
3:52:12
It's it's coming together nicely. I'm liking it. I'm liking it so far. It's fun.
3:52:17
Uh anyway, I think that's enough for today. Thank you for watching.
3:52:22
Leave us five stars in Apple Podcasts and Spotify and we will see you