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Today is Tuesday, March 31st, end of Q1, 2026.
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>> Yeah, >> I got a new sound queue.
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I know you were pulling for me. I got three now. Dangerous. I got three now. Watch out.
5:00
Uh, I'm not going to go too crazy.
5:00
I'm not going to overdo it. We've been there. We learned. We changed. We evolved.
5:05
We became better as people as did our linear lineup. We have a banger show. Let's pull it up.
5:10
Linear of course is the system for modern software development.
5:13
70% of enterprise workspaces on linear using agents.
5:16
>> Alex Prudin coming in from project 11 going to be talking about uh Google's uh quantum >> uh news.
5:23
>> The crypto quantum crash.
5:23
Say that three times fast. >> Cryptoquantum crash.
5:27
Then we have Quaser from Applied Intuition. >> Yes.
5:31
Excited to catch up with him and Absolute Dog.
5:33
Then we have Sebastian Malibi. Yes.
5:36
>> Uh releasing his new book, The Infinity Machine, An Insider Account of Deep Mind.
5:41
>> Tyler's got it pulled up right there. >> Super intelligence.
5:44
>> I'm a huge fan of Sebastian Malibi.
5:44
You might have read more money than God.
5:46
You might have read The Power Law, the history of Silicon Valley.
5:50
It's the definitive count of how venture capital became what it is today.
5:54
Highly recommend that book.
5:56
This is a very interesting departure from that because it focuses on a single person.
6:00
president's biography, not a history of an entire industry, but very excited to talk to Sebastian Alibab.
6:06
>> And then we have Forest from Somos raising a $40 million round.
6:10
>> Uh then Dino from Seronic, Will from Whoop, Janick from Public, Ryan from Crosby, and Chris U.
6:17
>> who's working on a spinout from Rivian. >> Very exciting.
6:20
>> Already has a billion dollar valuation. >> There we go.
6:22
Well, uh, friend of the show, our president here at TVPN, Dylan Abriscado, uh, headed to the TBPN newsletter, which you can sign up for at tbpn.
6:32
com, and wrote a fantastic essay summarizing, uh, a trend that we've been discussing with him around how AI is changing meme making.
6:41
And I found it very interesting.
6:44
I'm glad that he wrote this piece.
6:45
And so, we'll read through this and then discuss it, debate it, and see uh, where we can take it further.
6:51
And then of obviously >> and Dylan's from Long Island. Yes. >> Uh New York.
6:54
So John is going to be >> I'm going to do it in a Dylan Abscato impression. >> Memes are changing.
6:59
That became abundantly clear during the Oscars a few weeks ago when Conan tried to create a new Leonardo Leonard DiCaprio meme accent.
7:12
>> That's just like UFC announcer.
7:14
>> Uh to go alongside the classic Leo memes.
7:16
In doing so, especially by using TFW, that feeling when, and the blocky white font that defined early internet memes, he inadvertently demonstrated that the meme templates millennials grew up with have become increasingly stale, even cringe. It's a good point.
7:31
Uh, instead, AI generated videos are the new meme template that every network and studio should be focusing their launches on. Look at what happened.
7:40
Uh, look at what's happening with the Harry Potter reboot.
7:44
When the trailer first dropped, the reaction to the new Snape played by Ganian uh Gan Gan Ghanaian, sorry from he's from Ghana.
7:54
>> Ganaian uh English actor uh Papa Isidu was predictably and unfortunately negative.
7:59
According to the LA Times, he received death threats since being cast in the new role.
8:02
But after a few incredibly viral and wellproduced AI videos, uh, one an original Snape versus Black Snape MMA match and another AI generated rap video and another drip warts the school of drip, the narrative has started to shift.
8:17
Have you seen any of these?
8:19
I think I've seen drip warts, but can we pull up the original the quoteunquote original Snape versus Black Snape MMA match because I have not seen this one and I think it is illustrative of what uh Dylan is talking about here.
8:34
Snape v Snape in the UFC ring.
8:34
While we pull that up, let me tell you about Plaid.
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8:50
So, let's take a look at Snape v. Snape in the UFC ring. >> Any luck? >> Here we go. I just dropped it in. >> Cool.
8:59
Uh, and we have we have a few others here.
9:02
The videos have amassed tens of millions of views and on Dylan's timeline at least.
9:06
Sentiment around both the character and the reboot has done a complete 180. >> Here we go.
9:12
>> Really photorealistic.
9:16
Does this does this uh >> are there any uh red flags here as a UFC enjoyer?
9:20
Does this feel like a proper UFC?
9:23
>> The actual video quality is >> so bulky.
9:25
The video quality is insane.
9:32
>> Wait, but Old Snape won >> uh in the fight. >> Yeah. >> Okay. >> Wow.
9:38
>> But I think it just I Okay.
9:38
Wait, how how how do you know that?
9:40
Um, I think uh it just sort of like makes the characters more entertaining, more fun.
9:48
Shows you that this is just creativity at the end of the day.
9:50
This is just like you should not be so up in arms about something that's a movie like it's entertainment and here's some more entertainment and so you're you're adding entertainment to the discussion and uh people are enjoying that.
10:03
Uh there's another AI generated rap video about the new Snape, uh which we can pull up a little bit of here.
10:12
>> Uh AI meme videos are inherently viral and driving real awareness in a way traditional memes no longer can.
10:15
Not just because they're novel and more entertaining be, but because a single AI clip can travel further and compound harder than traditional meme formats and social feeds that now heavily favor video.
10:26
This suggests Yeah, that's interesting.
10:28
on on X, it's still very easy for an image to go viral, but if you think about, you know, Instagram, YouTube, like a standalone image just can no longer actually get that escape velocity.
10:40
>> Uh, I mean, what about uh dripped out Pope? Remember that? >> Yeah, a little bit.
10:45
But, but people are just spending so much time in the in the short form feeds and it can go in there, but they're certainly >> Yeah. Yeah.
10:54
Yeah, I mean I guess even some of the the the dripped out pope or what was it? Was it Balenciaga Pope?
10:58
I don't remember what the name was.
11:00
But that pope >> says this suggests a new playbook for marketers, especially in entertainment.
11:05
If you're about to drop a trailer for a new movie or show, you need to be thinking about your rage bait character, the one people will latch on to, remix with AI, and build around.
11:13
Uh Conan tried to force a Leo meme down our throats at the Oscars.
11:19
didn't see that because I was sleeping.
11:23
But this might have worked 12 years ago. That playbook is over.
11:25
Today, enrage fans and communities will, if you're successful, take your characters or moments and turn them into something much bigger.
11:31
Entire cinematic universes. >> Yeah. >> Yeah.
11:34
I'm I'm just very impressed by the the overall quality of of those outputs.
11:40
>> The Oscar selfie, I remember this.
11:40
This I think became the most liked image on Twitter at the time in 2014 briefly. that image.
11:48
This is the canonical clout bomb.
11:51
If you're a fan of Bradley Cooper, you like it.
11:54
If you're a fan of Meyer Street, you like it.
11:55
You're a fan of Brad Pitt, you like it.
11:57
And so, you're you're amplifying all of it's the ultimate collab post.
12:01
And this has become a format that's been used time and time again.
12:04
Uh it's uh it's effective.
12:06
We we we did a little bit of it at the Super Bowl. It was fun. It works.
12:10
But now the future is uh is AI.
12:13
Let's pull up the uh the Dripwart School of Drip video.
12:15
I want to watch this one because I I saw a clip of this.
12:18
I didn't see the whole thing.
12:20
Let's see if we can play this. >> That's Harry Potter.
12:22
Are you really Harry Potter?
12:24
My g >> type Type >> Type Type >> None of that. None of that, broki.
12:32
We're all here on the Mayback Express for one reason and one reason only, and that's to go to drips, the school of drip.
12:42
>> The Mayback pulling the train is pretty good.
12:46
Hey, this Check this out. >> Run.
12:53
>> And there's uh and there's the new Snape character. So, yes, very effective.
12:54
Um I was I I was reflecting on this and thinking about how um it's not just AI videos that are unlocked as the new meme format.
13:03
Like, uh 20 years ago, video editing was extremely difficult.
13:07
Like, you had to do it on a desktop.
13:10
You had to have a piece of software that probably cost a lot of money.
13:14
It was not widely accessible.
13:16
widely accessible. And so these image makers, image memes, uh we were I was talking to Brandon about this like good guy Greg was one of these or like uh the insanity wolf and it would just be like a picture, one image of a duck and the duck would be on sort of like a solid
13:34
colored background and that would be the template and then somebody would put white text with black like like block text impact font on the top and the bottom and that was like the image me and that was accessible in the sense that it could be like generated on MS Paint. It was it was it was free to
13:48
It was it was it was free to generate it basically.
13:50
Then >> we got video editing, you know, Cap Cut, Instagram reels has an editor called edits and all of a sudden it became easy for someone to take a vibe reel and put different text over it.
14:03
I send you a bunch of these where I'll find some crazy vibe reel and I'll just recontextualize it with a new laughing thing, new caption basically.
14:10
Uh, and so the classic one is like those four uh those four jets in the new Top Gun and it's like when when you and the boys all drive somewhere in separate cars or something like that, you know, as an example.
14:22
Um, but now you can generate, you know, full AI videos that can express the joke of the meme.
14:27
And I think the next version of this is like software as a meme.
14:32
S A M something like that.
14:35
And we've been experimenting that with with this with the simulators.
14:39
There's TB TBPN simulator, Jeremy Gaffon simulator.
14:41
There are more simulators coming.
14:43
And all of a sudden we, you know, the idea of building a video game, becoming a video game studio was like an impossible challenge.
14:51
It would be months and months of time, maybe millions of dollars to get anything uh reasonable.
14:57
So, you had to be commercial about it.
14:58
You could not do it as a comedy bit.
14:58
Uh but now you can or or it's getting closer.
15:03
Certainly our organization is set up to where we can turn Ben or Tyler loose for a few weeks and say, "Yeah, like you know, work on this vibe coding project for a few days, a few weeks, like it's okay.
15:14
You don't have a lot of other responsibilities that are going to creep in."
15:17
Um, but but increasingly, it's going to be more and more just like a few prompts on your phone to get the piece of software that is that meme.
15:26
And you can think about the the Jmail suite from Riley Walls as another software as a meme moment where he's making a commentary on the Jeffrey Epstein saga and all of that, but he's instantiating the the the the humor, the commentary in a piece of software that actually works.
15:46
Although, of course, the feature set is a little bit boiled down from the full Google suite, but it get the the UI is familiar and the UI is part of the joke.
15:56
And so, uh, I think that's a little bit of where this goes.
15:58
Well, let me tell you about Cognition.
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16:16
So, uh, there is a whole bunch of hack news going on.
16:19
We're in a very weird week in terms of the news cycle because it's spring break and so a lot of uh executives at big town companies are like don't launch while my kids are out of school and we're going on vacation.
16:31
I think that I actually think this is my real theory.
16:33
Um so we're in a little bit of a slow news week and you can see that like the journal is covering announcements that happened last week.
16:40
They're talking about Sora.
16:42
They're talking about the Disney.
16:44
They're talking about, you know, things that uh that are more like reflective in strategy.
16:48
Ben Thompson has a sort of a 50-year retrospective on Apple.
16:50
It's not driven by a news item.
16:52
Like, it's not like Apple launched a new product this week.
16:56
Uh, so Ben Thompson is taking a step back and reflecting.
16:58
It's a great piece, but it's not exactly news-driven because there isn't that much news coming from big tech companies, coming from the labs, etc.
17:06
But there are a ton of crazy hacks. Uh, starting with Axios.
17:11
Uh, there is an active supply chain attack on Axio, one of npm's most dependent on packages.
17:16
So if you have been vibe coding, Axios is a is a a package that uh helps with HTTP requests.
17:24
So it gets sucked into all sorts of different projects.
17:26
Uh and if you upgrade it to the latest version, you basically got a virus with that.
17:30
And if that's running in the cloud, it's building and that's probably maybe bad because it could uh steal API keys or SSH keys.
17:42
It could do a lot of things.
17:43
Could wreak havoc on your system.
17:43
Also, if you built this piece of software and you included the contaminated Axios uh uh installer or package locally, it could potentially weasle its way out of your local environment and get onto your desktop. It's a it's a virus.
17:59
So, uh be careful out there.
18:01
Uh and uh I'm sure people will be responding.
18:04
Uh the recommendation from uh Ferros who uh sort of broke the news over at Socket Security is that if you use Axios, pin your version immedi immediately and audit your lock files. Do not upgrade.
18:18
Um so analysis confirmed that this was malware.
18:21
Plain cryptojs is an obfiscated dropper loader that deoffiscates embedded payloads and operational strings at runtime, dynamically loads fsos and exec sync to evade static analysis.
18:33
uh executes decoded shell shell commands, stages and copies payload files into OST temp and Windows program data directories, deletes and renames artifacts post execution to destroy forensic evidence. So very risky.
18:48
>> I would say like if you have installed this, you should just like freak out basically.
18:53
>> Should and and and if you break your computer, that's like the first thing you should do.
18:57
Just like try to slam >> Yeah.
18:59
Take the computer, throw it in the lake, throw it in the ocean.
19:02
>> That's how you should start. Um >> I concur. >> I mean practical. Yeah.
19:07
Uh I mean there is going to be some sort of like power law response here where of the people that that are victims of the attack they will go after the most vulnerable with the highest like ransomware potential and I think we're seeing that with uh one company I believe Merur was targeted but I don't know if that's >> but I don't was that my understanding is that yeah the crazy thing is you have you have this like clawed code leak. Mhm.
19:34
>> That was completely separate.
19:34
Nothing even though even though I do believe they use Axios in claw code. Saw something on that.
19:41
>> And you have the Meror leak which is uh >> it's not a leak. It's ransom. >> It's a ransomware.
19:46
>> Someone stole some data.
19:47
>> Yeah, they stole a bunch of data and now they're trying to, you know, get bids on it.
19:52
Uh we'll get to that in a little bit. Okay.
19:54
>> Uh and then there's there's this Axios uh supply chain attack.
19:57
Anish had a little bit more context.
20:00
He said, "A tiny piece of code called Axio runs inside almost every app on your phone and every website you visit.
20:05
Developers download it 100 million times a week.
20:07
A few hours ago, someone poisoned it with malware that hands an attacker full control of your computer.
20:12
If you've never heard of Axios, that's normal.
20:14
It does one boring but important job.
20:15
It lets apps talk to the internet.
20:17
When a website pulls up your feed or an online checkout processes your card, Axios is probably doing the work underneath.
20:23
Over 173,000 other code packages plug into it. It's everywhere.
20:28
The attacker stole a lead developer's login for npm.
20:30
Think of it as an app store, but for code that programmers use.
20:35
Once inside, they swapped the developer's email to an autonomous Proton Mail account and uploaded the poison version by hand.
20:41
They that jumped past every security check the project normally runs before new code goes live.
20:44
And this was not a rush job.
20:47
The stackers staged the malware at least 18 hours before pulling the trigger.
20:50
They built separate versions for Windows, Mac, and Linux.
20:54
They poisoned both the current version and an older one within 39 minutes of each other, casting the widest net possible.
20:59
Once the malware ran on a machine, it deleted itself to cover its tracks. The trick was smart.
21:04
They never touched a single line of code inside Axios itself.
21:07
Instead, they tucked in a fake add-on called plain crypto. js.
21:12
Built to pass as a well-known trusted library, it copied the real libraries description and author info, so nothing looked off at a glance.
21:18
When a developer installed Axios, this fake package quietly ran the malware on its own.
21:22
When a smaller package called UA Parser.
21:24
js got hijacked back in 2021 with about 8 million weekly downloads, the security world treated it like a four alarm fire.
21:34
Axios has 100 million over 12xi exposure with 173,000 packages depending on it.
21:40
Socket, the security firm that flagged this caught it in about 6 minutes.
21:44
That's fast, but six minutes is still plenty of time for automated systems at companies everywhere to pull and install the bad version before anyone can react.
21:53
If you or your team run Axios, freak TF out.
21:57
Now, lock your version to 1. 14. 0.
22:02
Change every password, API key, and access token on any machine that installed the compromised update.
22:05
and check your network logs for connections to sfrak.
22:09
com or the IP address 142. 1120673.
22:17
>> Uh Carpathy had some context if you want to go through this John.
22:21
>> I will but first I'll tell everyone a very important message from Crowdstrike which is super relevant today.
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22:39
So Andre Karpathy said new supply chain attack this time for npm Axios the most popular HTTP client library with 300 million weekly downloads. That's a lot. Scanning my system.
22:52
Andre Karpathy says he found uh a use imported from Google Workspace CLI from a few days ago when I was experimenting with Gmail Gcal CLI.
23:01
Uh the installed version luckily resolved to the previous version the unaffected 1. 13.
23:09
5 but the project dependency is not pinned meaning that if he did this earlier today the code would have resolved everything would have updated and he would have been pawned.
23:20
It is possible to personally defend against these to some extent with local settings eg release age constraints or containers or etc.
23:31
But I think ultimately the defaults of package management projects pip npm etc have to change so that a single injection usually luckily fairly temporary in nature due to security scanning does not spread through users at random and at scale via unpinned dependencies.
23:48
So very very crazy crazy story.
23:52
Um Scott Woo said that Devon review caught the Axio supply chain attack for multiple Cognition customers before the attack was publicly known.
24:02
These attacks will be 10x more frequent in the age of AI.
24:03
It is critical that repo maintainers start using AI for defense as well.
24:08
Showing one example below where Devon review caught the attack within an hour of its release.
24:14
Text minorly edited for anonymization.
24:17
So uh I was debating this with Tyler earlier.
24:19
The question is like how does this update diffusion of of coding agents diffusing diffusion of vibe coding?
24:28
Uh is this I was I was sort of saying is this bullish for cursor wind surf you know code readers because you would see an organization that said hey we were having a great time vibe coding but going forward we have a standard in this organization that we're going to have more humans in the loop.
24:46
Does this make people be more inclined to put humans deeper into the situation? Tyler's counterpoint.
24:54
I'll I'll let you explain how you were saying that maybe this is actually bullish for just more token generation, more code gen. >> Yeah.
25:03
I mean, clearly like there just needs to be more code review, right? Okay.
25:07
It the package was still seen within seven minutes by an automated system, right? >> That's true.
25:12
>> Um, so like yeah, I think people will just like there's going to be much more of an emphasis like okay, you use uh coding agent to write the code.
25:18
You also use a coding agent to review the code every time.
25:21
every time. And like right now that's kind of a thing you do maybe later if you're in a big team you have code review but if you're just doing it solo maybe you don't do as much code review right >> but it just becomes you know more embedded within the agents right you talk to codeex you talk to cloud code
25:34
there's already like every single >> I just think it's bullish overall for cyber security like I think every cyber security company will probably do well people are on edge already >> and even even though this type of attack has happened for years long for like the popularity of vibe coding. It just feels
25:52
It just feels like there's a bunch of new solutions that are needed.
25:55
The kind of incumbent cyber security players will do well.
26:00
They're going to release a lot of new products.
26:01
I think the question that I have is like why seven minutes, right?
26:05
Like if um >> why not check it before it's merged in in the first place? >> Yeah. Yeah.
26:10
Or or just like you know these are machines so theoretically they can be constantly monitoring versus like >> Yeah. I don't know.
26:19
And and the question is uh I I I we're going to be digging into this story more over the next few days, but I'm I'm interested to know like it's found in seven minutes.
26:27
When is it actually rolled back?
26:29
If you look at 300 million weekly downloads, like clearly there are people that were downloading it at that moment in time at all seven of those minutes.
26:37
There's probably like thousands of downloads, if not, you know, tens of thousands.
26:41
um just doing like a rough ballpark on what 7 minutes means over a week of 300 million per week.
26:49
But the question is uh like how quickly was it rolled back?
26:52
So is it only if you're in that seven minutes or was it it was discovered in seven minutes and then it took them another 20 minutes to to to to roll it back and stop serving the contaminated package.
27:03
um understanding the scope of this because it's very clear that as Andre Carpathy explained like he was actively using it every single day and yet was not caught in that 7-minute window and so he was clean and and understanding the scope and scale of the impact is very much uh determined by how many um uh just just how just just how broad and how many installs happened during the contamination.
27:28
Anyway, Will Brown has a good take.
27:30
He says, "I hope someone at Axios is reporting on this." And I completely agree.
27:34
It's going to be uh it's going to be confusing when they do.
27:38
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27:53
>> Uh last night, >> more leaks. What's going on?
27:55
Last night, quad code source code uh was leaked via map file in the npm registry.
28:00
There's just a link to >> wait, someone's just actually do not click a link.
28:07
If somebody ever says, "Hey, I got some really great source code here. Just click this link." Probably don't click it.
28:12
Let other people screenshot it.
28:13
Uh there's plenty of meta analysis over here.
28:15
Um seems uh seems messy, seems unfortunate.
28:18
Uh heart goes out to the folks who are are dealing with the situation at the same time.
28:26
uh codeex is open source.
28:26
It's not the end of the world, but it did reveal a bunch of things about the road map and also some of the internal April Fools. That is the worst part.
28:36
We love a secret surprise April Fool's joke.
28:39
I love a good joke and uh nothing spoils a joke like hearing about it a day early.
28:43
Um but much more importantly, there are lots of uh there are lots of other critiques of the way cloud code is implemented. What are the bad?
28:52
I I don't think this I don't think this hurts their business at all because people are >> using cloud code to make other products and then also having to take basically a fork of cloud code maintain that try to be shipping features against it which is again I think it's the it's it it's not uh seems to not be legal at all to just fork the codebase just because it's out there.
29:16
Oh yeah, you can't just people are convert converting it into other languages and maybe there's some argument there but but still I don't think this hurts understand some of the secrets what's special but at the end of the day all of these tools especially something like cloud code that's so new like it's more of like the process and >> it's more bad for for the overall brand of vibe coding. >> Totally. Totally. Yeah. Yeah. It's rough.
29:43
Um >> and and it and the the you know the the the irony here is that every time Anthropic has released any feature related to cyber security all the big cyber companies have been selling off you know tens of billions of dollars. >> Yeah. Yeah. Yeah.
29:58
The question of like yeah does this build trust in like using VI code.
30:03
>> So so overall overall it it uh it hurts some trust but but again you know very obviously going to get through this. >> Yeah.
30:10
So the how it started, how it's going is of course landing like a ton of bricks.
30:14
In the in the last 30 days, 100% of the contributions to cloud code were written by cloud code.
30:18
And uh the how it's going is that it leaked the source code, which is uh not what you want to have happen. >> Yes.
30:24
Angel says Mythos is so good at security that Claude Code source code got leaked.
30:30
>> Okay, let's uh I don't know.
30:30
Should I This is like uh you know, you you didn't get to watch the Super Bowl.
30:36
You have it DVRred at home. Do you want spoilers?
30:41
Should we review the April Fool's joke or should we leave it unspoiled so that we can enjoy it tomorrow? >> What do you think?
30:51
>> I mean, it's not it's not it's cool. It's very cool.
30:54
>> You've already read it.
30:55
>> I read through it, >> but it's not it's not to my I don't think we're getting I don't think we're getting a knee slapper out of it, but it's very it's very cool. I think it'll be cute. >> Okay.
31:04
Well, uh then we can move on.
31:04
Um what else what else did we learn?
31:06
Uh, Tuki summed it up here.
31:09
Uh, do you understand what just happened to Anthropic?
31:12
Someone on their team ran a production build of cloud code.
31:14
The compiler generated a map file, which is literally a blueprint that reverses the entire codebase back to its original source.
31:23
And then they published it straight to npm for the whole world to download.
31:27
And it really does show you how fast the npm downloads.
31:28
Like there are people that are downloading it every single minute.
31:32
And so if even if it's only up there for a minute, someone's going to get it.
31:36
and then all they need to do is send it to somebody, zip it, and post a link on X and it goes viral.
31:41
Um, it's like locking every door in your house, installing cameras, hiring armed guards, then accidentally uploading your floor plans to Google Maps. Does that matter? No. That's a bad analogy.
31:49
I don't like that analogy because um, floor plans are not why I lock every door in my house. I install cameras. I hire armed guards.
32:00
>> Aren't floor plans public on like Zillow?
32:02
>> Oftent times they're not.
32:02
I would say we can probably skip over this.
32:04
John, if you scroll down, this account just kind of posts like the same format every single time. So, we can skip this. Let's go over.
32:12
>> There's a red alert emoji. You got my attention.
32:14
>> Let's go over to Lean. I'll get you. >> Yes. Yes. Yes.
32:17
>> A few takeaways from the Claude Code leak.
32:18
Anthropic is actively using Mythos for development. >> Okay.
32:23
>> Uh they are already a Capiara V8.
32:23
We learned last week that Capi Baras are >> extremely deadly, >> but can be deadly >> in the right context.
32:31
Capy bar still has issues.
32:34
>> The foreshadowing is crazy.
32:35
>> The foreshadowing is crazy.
32:35
We were talking about how how the Fouian bargain that is uh getting a Capy bar as a pet seems so cute, but it can bite you and it seems like that might be what happened.
32:46
>> Capy barge has 1 million uh token context window and fast mode.
32:51
>> Um >> Numbat is another interesting code name tagged with at model launch.
32:54
Remove the section when we launched Numbat.
32:56
Uh Fenck seems to be the Fenic fox.
32:58
Thanks Fox is very cute, but also not a domesticated animal.
33:03
How about we get some uh golden retriever code names?
33:05
How about uh big fluffy poodle?
33:07
That's a good code name for your for your for your animal themed uh AI model.
33:12
Anyway, let me tell you about console.
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33:33
>> Arid says hottake anthropic leaked claude code intentionally to get a nerdosphere code review it would have never gotten if they had just open sourced it.
33:42
>> Oh, that's actually true.
33:42
Way more you don't leak your entire feature road map and >> you don't do I mean it's it's it's funny and I'm sure they'll make the most of this.
33:53
This is 40 chess right here.
33:55
>> But uh I'm not seeing the 4D chess.
33:57
>> I'm seeing the 40 trust now.
33:57
I'm convinced this is I mean we're in completely uncharted territory for marketing stunts and pre-releases and sneaky footage that is goes viral and maybe was planted. You don't know.
34:09
And it's like some leaked account. Like I don't know.
34:14
I think everything's I think the gloves are off.
34:15
Everything's on the table.
34:17
This could be an April Fool's joke.
34:19
This could be a stunt to draw to drive attention to an open- source move.
34:24
Although uh Tyler, you said that Dario is not a fan of open source at all, right?
34:28
He's like against unilaterally.
34:31
>> He doesn't want to do open source.
34:32
>> I I feel like isn't there some steel man there where where if you open source like I don't know like like Opus 2 or something that's like really old, it's entirely commoditized in the research community.
34:46
community. So all of those secrets that went into like making opus 2 good those have been commoditized they've been discussed at the house parties in SF the researchers have moved from one place to another so everyone knows these they've implemented they're available as open
35:02
source but by by open sourcing your model you can uh share with more of like the upand cominging academic community like if if I'm a if I'm a computer scientist >> yeah but if all the research is already commoditized and >> yeah I guess you could just use the other ones it doesn't really have a benefit. Maybe
35:17
Maybe >> has any Has anyone at Enthropic Has anyone at Enthropic commented on this at all?
35:24
I haven't seen I haven't seen anyone. >> Yeah.
35:28
>> What is undercover mode?
35:30
>> That is a way to contribute to projects without letting people know that you're using >> Claude Code. >> Oh, interesting.
35:39
>> Um, uh, >> that's a hack.
35:42
>> Gurgley over at Pragmatic Engineer says this. Gurgy, sorry.
35:45
This is either brilliant or scary.
35:47
Anthropic accidentally leaked the source code of cloud code which is closed source.
35:51
Repos sharing the source are taken down with DMCA.
35:55
But this repo rewrote the code using Python and so it violates no copyright and cannot be taken down. >> Okay. And there's a warning.
36:03
Do not store the code even though it has leaked.
36:07
do not store it because you might get DMCA uh according to the Prime uh the last time anthropic uh in their infinite PhD level wisdom leaked their own source code February 25th that happened.
36:18
I I missed that entirely.
36:20
They DS they DMCA all repos that had their code.
36:23
Careful storing the code because Anthropic will have no mercy.
36:27
Uh 40,000 users forked it.
36:30
So uh maybe unfork it if you if you did that because it sounds like you might get a legal letter.
36:34
Again, a DMCA is not uh is not like an actual lawsuit.
36:38
It's more just >> unfork unfork >> unfork it uh uh and uh and and people are of course making a joke that uh the codec source code has been leaked in full here and they're linking to the GitHub because codeex is open source uh which is which is cool.
36:52
I don't know it's it's interesting uh and more and more people are building their own harnesses.
36:56
harnesses. uh there was some interesting data that uh opus performs extremely well better than in clog code in cursor on some benchmarks and so there there is this new uh this new paradigm of like you know how can you add different value when you're building a harness so um what else
37:15
>> yeah c certainly there's other plenty of other companies that are building harnesses that are going to be able to dig through this and get some benefit be able to improve their products that's not that's not great but at the same time codeex has already the source code is already open source. >> Yeah. >> Yeah.
37:29
>> And so that's not that hasn't been hurting codeex's progress and growth.
37:32
So >> yeah, >> end of the day uh ultimately I would say I would I'm assuming very very embarrassing for the for the individual that um ultimately uh contributed to this but uh they will get past it.
37:48
>> Well uh we will put the the blame squarely on the AI model so they can take it.
37:53
Uh, DAX is getting line of code mogged, locgged because clog code open source is uh, clog code source is 512 lines of code whereas open code his project is only 118 lines and so he's got to get those numbers up.
38:09
>> And GT mogs everyone with over 50 billion lines of code.
38:13
>> He doesn't have 50 billion lines of code.
38:15
GT uh, Gary Tan will be coming on the show hopefully this week uh, and we will get the full scoop on how he's using GStack and other models uh, which should be fun.
38:23
Before we move on, let me tell you about Turbo Puffer.
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Pick channels, target audiences, and measure sales.
38:39
Just like on Meta, >> Zach says, "NAS are a great way to keep your corporate secrets safe from one or two beers, but not three beers."
38:48
>> Why is there a community note on this? this.
38:50
Oh, this joke was posted before on Instagram.
38:53
It's a little joke theft. Interesting. Interesting.
38:55
But it's a good joke and I'm glad that he brought it over to X where we could enjoy it along with 36.
39:02
>> The original the original post was an NDA is a lock and three beers is a key. >> Okay.
39:07
Well, yeah, he he uh toned it down for the uh for the timeline.
39:10
Anyway, uh there is news out of uh out of Google uh a Google paper warns that uh warns crypto on quantum risk ahead of 2029 timeline.
39:22
So, we've heard about the risk of quantum computing affecting uh the cryptocurrency industry, crypto projects broadly.
39:29
Uh there is some new uh research out of Google that provides some more perspective.
39:34
So Google researchers have warned that future quantum computers may be able to break some of the cryptography protecting Bitcoin and other digital assets with fewer resources than previously thought, adding urgency to the debate over how the industry should prepare.
39:49
The researchers did not indicate such a machine exists today, but said new work suggests the computing power needed to carry out that kind of attack may be lower than earlier estimates had suggested.
40:01
In a Google research blog post, this is from Bloomberg.
40:03
Uh the researchers said that a future quantum computer could break elliptic curve cryptography, a form of public key encryption used across much of the market.
40:13
Their latest estimate points to a 20fold reduction in the quantum computing hardware needed to break what's known as ECDLP 256, a mathematical problem that helps secure crypto wallets and transactions.
40:25
That does not mean Bitcoin and Ethereum are suddenly exposed.
40:29
But the researchers in a white paper dated Monday said the clearest defense is a shift towards postquantum cryptography or PQC.
40:35
I'm sure this will be a hot topic over the next few months.
40:41
A newer form of security designed to withstand attacks from powerful machines.
40:45
They also urged the crypto industry to cut avoidable risks in the meantime.
40:48
We urge all vulnerable cryptocurrency communities to join the migration to PQC without delay.
40:55
Google cast the paper as a warning meant to give the industry time to time to act, not as a prediction of imminent collapse.
41:02
Last week, the tech giant introduced a timeline to fully migrate its own security systems to post quantum cryptography by 2029.
41:09
Fears around quantum computing as a realistic threat to crypto have swirled for years.
41:13
In January, Coinbase established an independent advisory board to study what quantum computing could mean for the blockchain.
41:22
That same month, Christopher Wood, global head of equity strategy at Jeffre, removed a 10% allocation to Bitcoin from his model portfolio, citing fears that the advent of quantum computing could undermine the token.
41:32
On Tuesday, Bitcoin shrugged off the news of the Google paper uh making the rounds, rising as much as 2. 6% to $68,300.
41:44
I'm not sure where it is today, but Jordy, I'm sure you can pull that out.
41:47
Even so, the researchers said the time left before such machines arrive still appears longer than the time needed to move public blockchains to postquantum cryptography.
41:55
However, >> BTC is currently at 67 >> 67.
41:59
So, slightly off of yesterday.
41:59
Uh, a lot of this stuff has been discussed ad nauseium in the crypto community for years.
42:06
I I remember hearing about quantum potentially uh breaking Bitcoin >> as far back as 2016.
42:12
So you're saying you were already in that kind of like postquantum? >> Yes, 100%. I was locked in. No. Uh >> uh. Yeah.
42:21
>> I was aware I was aware of it. >> One concern >> Yeah.
42:24
>> Yeah. that uh people in the community have had that I've seen talked about is this idea that if you did have a computer powerful enough to crack these encryptions, you would unless you were like Google >> and you already had, you know, uh billions and billions and billions of dollars of cash flow, you wouldn't exactly stand up and say like, hey, I have cracked Bitcoin because the
42:49
incentive for a certain team would just be to go around and find these wallets that were uh maybe maybe uh didn't have any activity for a long time and just start cracking those individually because if you just stood up and said hey I have a quantum computer that is destroys Bitcoin the the price would go down and then you the the hack you know the the hacker wouldn't get any benefit from it. >> Yeah it's interesting. Uh what are
43:11
>> Yeah it's interesting.
43:11
Uh what are quantum stocks doing on this news?
43:16
>> Uh quantum probably ripping >> they rip on everything.
43:19
Saiquantum is that one of them quantum. Uh, Regetti's up 8%. >> Okay, there we go.
43:25
Oh, Scantum's priv privately held.
43:28
Uh, there's another one, D-Wave, right? D-Wave, are they public?
43:33
Yeah, they're up uh 10% today, but they're down 12% over the past five days, but and 25% over the last month and 42% over the last six months, but they're up 88% over the past year. Let's go.
43:46
Uh, D-Wave is a $5 billion company.
43:50
Yeah, there's apparently a bull market in Nick on our team's email inbox. Oh, yeah.
43:54
Quantum companies that want to come on and talk about.
43:57
>> Well, we do have someone coming on, right?
43:58
Uh we have Alex Prudin from Project 11 uh coming on to break it down for us at noon.
44:03
Uh so Nick Carter uh was talking about this.
44:07
He said, "Many are wondering what Google saw that caused them to revise their postquantum cryptography transition deadline to 2029 this week.
44:14
It was this and it's from uh research Google research.
44:17
google Google, which we will uh go through.
44:19
Max the VC says Google's basic basically saying we've we've cut the quantum resources needed to break Bitcoin's encryption by 20x. We can now break it. We can prove it.
44:30
We're just not going to tell you how.
44:31
We've slowed down research to give crypto a chance.
44:33
You have until 2029 to figure out a solution. Good luck.
44:36
Uh Elon chimed in and said, "On the plus side, if you forgot your password, the password to your wallet, it will be accessible in the future." also to everyone else. >> Yeah. Um Yeah. I I I don't know.
44:49
I mean it uh how do how do property rights if somebody if somebody does have a quantum computer and they crack your Bitcoin wallet that you forgot the password to, but you can prove that you owned and then they get busted for stealing your Bitcoin, you could potentially get it back.
45:06
>> Do you ever really own code? >> I don't know.
45:08
Uh Nick also said and the craziest thing is that the quantum AI the Google quantum AI paper is maybe not even the most concerning quantum paper released today from project 11 uh who's coming on shor's algorithm is possible with as few as 10,000 reconfigurable atomic cubits.
45:27
So this will be interesting to dig into uh further uh the uh within minutes with the 500,000 physical cubits.
45:37
Google is now more confident on a 2029 postquantum transition.
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46:01
So um there's a lot of news about this quantum story.
46:09
>> Nick said, "Good morning.
46:09
Now is not the time to panic.
46:11
The time to panic is if Bitcoin devs read these two papers and double down on their chosen solution of hoping it goes away, then panic." >> It's ridiculous.
46:19
Uh Dan Shipper says, "The first thing I've seen that could make Bitcoin go to zero or allow competitive coins to to to catch up."
46:27
So, uh other other uh uh other coins clearly have at least like a very clear like marketing story to tell if they are like the quantum proof or the first to be quantum proof or the most seriously regarded in the quantum proofing race. Uh will be interesting.
46:43
Uh Ariana Simpson uh chimed in and said except all or most other coins have this problem too but that is the opportunity that someone can uh maybe change something.
46:53
So uh the chance that NASA lands on the moon we were tracking this yesterday.
46:57
The the missions are starting to happen before 2028 on Kali is now at uh 14% before 2027 is at 4. 7%. So they are racing.
47:08
Of course this Artemis 2 mission is not boots on the ground on the moon.
47:13
It is rocketing around the moon.
47:13
Uh we'll have more about this tomorrow.
47:18
They're just going to check it out.
47:19
>> They're going to be gone for 10 days.
47:20
They're going to be in space for 10 days.
47:22
>> Um and uh we'll be will be very interesting.
47:25
Uh Brenda Gell was doing some deep dives on the technology, the streaming technology, what we really care about here that will be on board.
47:35
Something like 20 cameras, 4K live streams, laser beams to make sure it's low latency. Should be a lot of fun.
47:43
Super chats would be good.
47:43
We got to get a chat going.
47:44
I'm sure there might actually be because they usually stream on YouTube and so I wouldn't be surprised if >> Is it going to be a 247 >> like perpetual stream that's always on? Yes.
47:56
>> Even when the astronauts are taking a sleep. >> Yeah. >> Taking a little nap. >> Yeah. Yeah. >> Okay. >> Yeah. >> Okay. Yeah. It's going to be funny.
48:03
There's so many all the conspiracy theorists are going to be sitting there watching it very closely and then pausing and >> There was a glitch >> there. Did you see that glitch? That was that was VFX. That was AI. No, >> this is my mark.
48:14
It uh I will believe that it's real.
48:16
If I see an astronaut, put three fingers in front of their face.
48:20
Y >> because this is the one thing that the AI can't do right now.
48:22
If you're ever on a Zoom call with someone who you suspect of being fake, a scammer who said, "Hey, let's get on Zoom.
48:31
Let's talk about some financial investment opportunity."
48:34
financial investment opportunity." and you and it looks like someone you think is the person but you suspect that it might not be and they will be able to show you look look at the fingers the fingers are perfect it's fine it's fine that's because this part is not AI just the face is AI this is the deep fake
48:53
stuff that's happening so what you have to do is you have to ask them to hold up three fingers they'll be like yeah three fingers this is fine right I satisfy the task you got to say no put the three fingers in front of your face because if you put the three fingers in front of your face the AI gets confused and it breaks the deep fake that's happening underneath. So, you got you got to go
49:08
So, you got you got to go like this.
49:10
Show some depth of field.
49:10
You got three fingers in front of the face. This is the trick.
49:14
This is the only way you'll survive in the in the future. Be careful out there. Um Merkore had a breach. This is crazy.
49:20
Uh the design language for the uh hacker is very hacker coded.
49:28
the the the the hackers that are putting out a B bounty created like a an image that looks very aesthetic to me.
49:37
They the the design of this I didn't realize hackers um did stuff like this.
49:42
This is very interesting.
49:44
But you know, it's like you think about the hackers, you know, cosplaying as hackers.
49:48
They are, but they have >> they've like adopted like the green like the green text in the black terminal.
49:55
It's like they're they're they're they're living the they it's uh it's like life imitates art. That that type of thing.
50:02
Anyway, it seems like a very rough leak.
50:04
Very unclear what's actually happening.
50:06
There's a whole bunch of different uh questions in here.
50:08
There's a database of candidate profiles, source code, uh video, all sorts of stuff, tail scale VPN data.
50:15
Unclear how much of this is real. They could be faking it.
50:18
I don't know where the comments are, but um the risk is that uh if there is some sort of Equifax style payout that could be extremely costly because if they have millions of people in their database and they got to pay everyone 400 bucks like Equifax did uh because they have sensitive information that could be very very expensive.
50:38
Well, uh we have had the Merkore folks on the show uh many times and are hoping that they get through this smoothly and uh everyone's >> Yeah, absolutely brutal. I mean it's it sucks.
50:49
It sucks first and foremost for all the individuals >> whose PII is now potentially floating out there. >> Totally.
50:59
>> Uh it's probably quite bad for their customers who paid for >> uh paid for the you know some >> amount of this data and now it's just floating out there >> and then uh obviously you know unfortunate for the company but uh still unclear.
51:16
I was uh looking up lapsis which is >> uh the hacker group >> styled as lapsus with a money sign >> classified as by Microsoft as strawberry tempest and more recently identified as or a part of shiny hunters is an international extortion focused hacker group known for its various cyber attacks against companies and government agencies.
51:38
The group was active in several countries and has had its members arrested in Brazil and the UK in 2022. Wow.
51:44
According to City of London police, at least two of the members were teenagers.
51:50
Lapsis uses a variety of attack vectors, including social engineering, MFA, fatigue, SIM swapping, and targeting suppliers.
51:57
Once the group has gained the credentials to a privileged employee within the target organization, the group then attempts to obtain sensitive data through a variety of means, including using remote desktop tools.
52:08
Attempts at extortion follow.
52:08
Initially, the messaging app Telegram has been used for communications to the public, including recruitment and posting sensitive data from their victims.
52:14
The first major cyber attack attributed to Lapsis was against the Brazilian Health Ministry's computer systems in 2021.
52:23
Lapsis gained notoriety for a series of cyber attacks against large tech companies, including Microsoft, Nvidia, and Samsung.
52:28
Following these attacks, City of London police announced that it had made seven arrests in connection to a police investigation into Lapsis.
52:37
Although the group had been considered inactive by April 2022, it is believed to have reemerged in September 2022 with a series of data breaches against various large companies through a similar attack vector, including Uber and Rockstar Games with subsequent arrests again by City of London police and Brazilian police.
52:54
The group appears to have become inactive after September 2022 >> with members perhaps dispersing to other groups and a conviction of two British members.
53:05
It's also interesting because like they don't enfor they don't enforce like brand intellectual property around hacker collectives and so anyone can pick up the brand and use that whether or not they're in the organization. It seems very fluid.
53:17
But uh good luck to everyone who's working on the response and hopefully uh a a good resolution that is resulting quickly.
53:24
Uh let's move on to some good news.
53:27
Um uh we will be having Sebastian Malibi join the show at 12:30 today.
53:33
Uh but Colossus Magazine published an exclusive chapter from the book which Tyler has there.
53:39
Uh the the biography of uh Demisabus from Google DeepMind.
53:45
Uh and he secretly built a hedge fund inside of DeepMind trying to beat Jim Simons. Google shut it down.
53:50
So there's this interesting uh there's this interesting screenshot that Colossus shared.
53:56
uh Habis for his part assembled a secretive hedge fund operation within DeepMind.
54:00
He recruited a team of 20 researchers to train highfrequency trading algorithms and explo and explored a collaboration with the Wall Street behemoth Black Rockck.
54:08
It was not a project of which Google approved, but Habis a five a five-time world games champion at the International Mind Sports Olympiad.
54:16
Sick uh found hoped he'd found another game that he could win.
54:22
One day I asked about the story of this trading project.
54:24
I was told that Habis wanted to beat Jim Simons, the mathematician who founded the wildly successful algorithmic hedge fund Renaissance Technologies.
54:32
Rench operated in secret, which Demis loved, my acquaintance explained to me.
54:36
Did the secret DeepMind trading team make money? I wondered. No, came the answer.
54:40
Because of Google's weariness, it was quietly disbanded. I heard about something.
54:47
Maybe it wasn't this Deep Mind team, but >> Gabe says, "But did they rip SIGs?" >> Oh, yeah.
54:51
could have been the missing >> Simons.
54:53
He also never wears socks and always speeds and just pays the tickets because his his like risk adjusted value in terms of his opportunity cost is that he should never drive the speed limit which is sort of a wild move. Uh true true wild man.
55:08
Uh I I heard about the the potential of a Google hedge fund years ago.
55:12
I don't know if it was related to DeepMind though, but just the amount of uh cash they have on the balance sheet.
55:18
like they need a trading desk basically to move that money around.
55:21
Even if they're just buying treasuries, they need a strategy, forex, there's so many different operations.
55:27
And there was a pitch I heard about years ago that they were thinking about like, should we be more active?
55:31
We have a lot of information.
55:33
We have a bunch of great engineers.
55:35
We should we could build a hedge fund here.
55:36
But they decided that it was not compatible with like the don't be evil philosophy.
55:40
It was not core to the mission.
55:42
And that they, you know, at at some point there is risk associated with active trading.
55:47
And so you could potentially blow up.
55:47
Uh there are certainly uh plenty of examples of hedge funds that had fantastic teams but could not stick the landing and uh wound up wound up zeroed.
55:59
>> Sophie says Google shutting down a deep mind hedge fund quit right before they were about to >> strike diamond. It really is this meme.
56:08
They they probably would have printed.
56:10
Although it's not like the high frequency trading firms are are not using AI or or not using I mean Jane Street invested in a uh in a a custom server company or custom silicon company something along those lines uh specifically for high frequency trading.
56:28
So they they they have a lot of you know AI researchers there and and you see this with a lot of the labs saying hey does anyone from uh the high frequency trading industry or quant finance want to come work over here?
56:38
uh we can maybe start matching your salary, maybe give you uh a a more interesting project that you can actually talk about and people will be potentially excited about. I don't know.
56:49
Anyway, >> uh Bone GPT the rapper eater shared, "I don't want this part of my brain to grow," which is a quote from this.
56:55
So, in the weeks after the presentation, the two sides finally converge on a fleshed out version of the PCAI plan.
57:01
Sullyman would lead Deep Mind's applied side from within Google while HBIS would run research as an independent global interest company.
57:10
For Sullyman, this was a triumph.
57:12
Google had finally signed a complex term sheet granting most of what he wanted.
57:16
HBIS was equally pleased.
57:16
The plan guar guaranteed him an astronomical 15 billion in Google funding to sustain AGI research over the next decade and it would put an end to the meetings on corporate structure which he found screamingly boring.
57:30
After two years of negotiations, he had hit his limits.
57:33
I don't want this part of my brain to grow, he often said when asked to get his mind around another legal document. >> That's hilarious.
57:41
That's a that's a great uh that's a great saying.
57:44
I don't want this part of my brain to grow.
57:45
Uh it's so funny that uh that that uh you know, you're you're going through two years negotiation and they're like, "Okay, you're going to be you're going to be have so much funding to build AGI $15 billion."
57:58
You're like, "Oh, so like a seed round for like a Neol like great."
58:04
Like, "Oh, so like one data center from a NeoCloud or something."
58:10
Like it's like it's like the numbers have gotten so so big that 15 billion does not feel like anywhere near enough at this point.
58:18
>> Uh Colossus, hit me, John.
58:20
>> Uh let me tell you about Railway.
58:22
Railway is the all-in-one intelligent cloud provider.
58:24
Use your favorite agents to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security.
58:30
Uh, tell me about the >> Elon uh Colossus shares, Elon has spent a decade trying to control an AI lab.
58:34
He tried to absorb Deep Mind into Tesla in 2014, then OpenAI in 2018 when that failed. An intern spoke up. It did not. >> Interesting.
58:44
Okay, let's read through this.
58:46
>> Uh, he also tried to control XAI to some degree.
58:51
>> Well, doesn't he control XI?
58:51
He controls it, but at what cost, >> right?
58:55
All all seven co-founders. >> Oh, true, true, true.
58:58
That's what you're referring to. Got it.
59:00
>> Anyways, from from the book, pushing back against Musk's obsession with the race against Google and Deep Mind, Brockman added, "It doesn't matter who wins if everyone dies."
59:06
Musk responded the next morning at 3:52 a. m.
59:11
>> He confronted Brockman with a proposal that recalled Pichai's pitch.
59:13
Open AAI should spin into Tesla.
59:15
Initially, OpenAI's team could accelerate Tesla's development of autonomous vehicles.
59:21
Next, it could use the profits from self-driving cars to fund its AGI moonshot.
59:26
Tesla is the only path that could even hope to hold a candle to Google, Musk declared.
59:29
Even then, the probability of being a counterweight to Google is small. It just isn't zero.
59:36
Back in 2014, Musk had Skyped HBIS from a closet in LA.
59:41
>> What a funny what a funny answer.
59:42
>> Proposing that Tesla or SpaceX should absorb deep mine.
59:44
Almost exactly four years later, the new version of this proposal played into Altman's hands.
59:50
proved Musk's power hunger.
59:52
>> With little difficulty, Altman now persuaded Brockman and Sutzgiver to take his side.
59:57
>> Together, the three told Musk that OpenAI would not attach itself to Tesla.
1:00:01
>> At an all hands meeting on the top floor of a converted truck factory that housed OpenAI, Musk announced to the employees that he was quitting the lab, scornfully, adding that >> I need Raptors.
1:00:10
I need a I need a new Ford Raptor potentially every day.
1:00:12
We got to put this lab above >> inside of a truck factory. This is amazing.
1:00:19
>> Uh, scornfully adding that OpenAI would have to sprint faster to stay relevant.
1:00:23
>> Yeah, >> I guess they did.
1:00:25
>> Hoping to lure away some researchers, he declared there was a much better chance of building AGI at a strong business like Tesla.
1:00:32
>> Showing courage or perhaps just youthful innocence, an intern asked Musk if speed might be reckless from a safety perspective.
1:00:38
Besides, wasn't developing AI at a for-profit company like Tesla the same as creating it at a for-profit company like Google?
1:00:45
Isn't this going back to what you said you didn't want to do?
1:00:48
The intern demanded, you're a jackass, Mus retorted.
1:00:51
Then he stormed out of the meeting.
1:00:54
>> That intern >> Tyler Cosgrove.
1:00:57
>> No, that intern was Steve Jobs. Just kidding.
1:01:01
That intern was Taylor Swift.
1:01:03
Uh it is it is my interesting read on this is like it's it's crazy that uh Elon was interested in in basically buying all of Deep Mind, absorbing all of Deep Mind and then four years go by and he's like I'm I still want a lab.
1:01:19
I want to absorb all of Open AI instead of just incrementally adding to an internal lab at Tesla just one researcher at a time.
1:01:28
Like he was able to >> already working on self-driving. >> Yeah.
1:01:33
He and he was able to assemble eight co-founders at XAI, of course, like they wound up leaving.
1:01:37
But if you just think about it as like, okay, there's going to be some churn.
1:01:40
Maybe the churn will be higher even.
1:01:42
But if you start the process in 2014 and you're and you're hiring researchers continuously and using cash flow from Tesla to fund that and then yes, researchers might leave, but then you get new ones and you're just building that capability.
1:01:56
It's like the Supercharger network or you know Starlink like you have to build a team and and you have to continually add but instead Elon's been in this world where it's always like all or nothing which is a very odd strategy to me instead of just like homegrowing it. I don't know.
1:02:15
Uh it it is just like an interesting it's an interesting strategy I suppose.
1:02:19
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And without further ado, we have our next guest in the Reream waiting room.
1:02:37
Let's bring in Alex from Project 11 to the TV show. Alex, how are you doing? >> I'm doing great.
1:02:43
It's great to be here, guys.
1:02:45
>> Is it over or are we back? What's going on? How bad is it? Tell it to me. Give it to me straight. How long do I have?
1:02:52
Uh well, according to Google, you have until 2029. >> That's like forever.
1:02:57
>> That's forever in my mind. >> Yeah.
1:02:59
Uh although maybe not forever if you think about blockchains that take a long time to change.
1:03:03
Bitcoin's last uh upgrade took four years and that's 2029 is less than four years away.
1:03:08
So >> yeah, that seems really risky.
1:03:09
uh take us through like what actually changed because I >> well before we get into that a little context would love would love some background on on you and project 11 and then we'll get into all the papers. >> Yeah. All good.
1:03:23
Uh yeah so me I'm a former army green beret uh got out or I got really interested in Bitcoin working in the Middle East.
1:03:28
Uh got out went to Thanks nice sound effect.
1:03:31
Thanks nice sound effect. uh got out uh went to Stanford then got a job working in venture first then uh entered the blockchain space at a company called Alo where I was at for five years before getting really excited about solving this quantum problem that blockchains face and so that's what led me to found project 11 so project 11 I kind of gave it away it's all about securing digital assets on blockchains into the
1:03:51
postquantum future right so uh the way I like to to frame it is the what quantum computers threaten is the underlying foundation of cryptography that all blockchains are built on right so it's that level that we have to fix and then
1:04:04
ultimately everything on top of that as you guys know from tech like there's all kinds of dependencies at each layer of the stack and we have to rebuild the whole stack and that's what project 11's all about. >> Uh just to put it into perspective when
1:04:12
>> Uh just to put it into perspective when did you found project 11?
1:04:15
You said it was five years you spent five years at the last company.
1:04:19
When did when did you actually get started on this? >> Uh October 2024.
1:04:22
So just over I guess almost a year and a half ago.
1:04:25
almost a year and a half ago. And what was what was the general dialogue around quantum and the risk to crypto at that time >> that it wasn't real that quantum computers were always going to be 20 years away >> that uh you know that no one had to pay attention there were bigger things to
1:04:41
worry about uh honestly I feel like that's slowly changed and I think today's not just so there's a paper from Google there's another paper out of Caltech both dropped on the same day both effectively lowered the bar massively that a quantum computer had to clear to he considered crypto cryptographically relevant to threaten Bitcoin. Right? So that was the Right?
1:04:58
So that was the breakthrough and I think this is a watershed moment where really at this point when Google the head of the Ethereum Foundation and a Stanford cryptography professor all pound the table and say we cannot wait to migrate anymore then people are going to start paying attention. >> Okay. What actually changed?
1:05:14
because it doesn't seem like the like the number of logical cubits or physical cubits like that seems to be growing exponentially.
1:05:24
But even when you trace out the curve, you're 5 10 years away from what we thought we needed.
1:05:30
Uh so is this a new algorithm, a new stack of code, or is it new math?
1:05:37
Like what changed that we got this 20x increase in efficiency in terms of cryptography breaking via quantum computers? Yeah, a couple things.
1:05:47
So, first off, these two papers are not necessarily about a quantum computer that's bigger or more capable, right?
1:05:52
So, this they're about what is what it takes to break cryptography, right? And so, what changed?
1:05:59
So, one of the things that changed was that interestingly physicists and you know, kind of quantum cryptographers that looked at this problem for a long time studied an algorithm called RSA.
1:06:09
>> It's not worth defining, but it's kind of an older cryptographic algorithm, but that's not what really any blockchains use, right?
1:06:14
use, right? because you know RSA keys are very large right so it turns out and this was kind of the key one of the key upshots of the Google paper it turns out that if you actually focus on the cryptography used by Bitcoin Ethereum and other networks it's actually way easier to break than they thought it was compared to RSA and so that is that is
1:06:31
one of the major things the other big breakthrough and this is from the other paper from Caltech is that you know quantum computers as as you guys may or may not be aware as your audience may not be aware are kind of you know they're very fragile generally so to be useful They need to have what's called error correction applied and that error correction can kind of result in a lot of overhead. You need to have tons of
1:06:50
You need to have tons of physical cubits to get to you mentioned logical cubit to get one logical cubit.
1:06:56
Well, this Caltech paper basically showed hey we have some new ideas to do error correction.
1:07:00
And it turns out if we apply those we don't need hundreds or thousands of physical cubits.
1:07:04
Maybe we just need a handful to make one logical cubit.
1:07:07
So that the title of their paper actually the headline is you may only need 10,000 >> physical cubits >> to break short to run shores algorithm and by the way they demonstrated last year 6,000 cubits. >> Okay, so we're close.
1:07:20
Yeah, >> that's you know no one's can put a timeline on it but how how fast do you think you can close that gap is the question. >> Okay.
1:07:28
Uh, is it possible Jordy was uh throwing out the idea of someone having a secret quantum computer going around the blockchain uh siphoning Bitcoin from, you know, cold wallets that haven't >> I'm not wasn't implying that it exists yet.
1:07:41
Just implying the incentive of if somebody were to create >> one of these, but but but yeah, the way you're reacting, I'm imagining it's like if if somebody does it, it'll be >> Google first, which is maybe a good thing. I don't know.
1:07:57
It's like look, it's really hard to know how it's going to play out.
1:07:58
I I wrote a whole blog post on our on our blog on project 111.
1:08:01
com people can check out called quantum war games and it was really fun because it's exactly it's like the whatif scenarios, right?
1:08:08
>> Um you know because why do people want quantum computers generally?
1:08:10
Uh well, they're great for science.
1:08:11
Two, like you can imagine governments that want to do espionage might want the ability to break cryptography, too.
1:08:16
They probably don't want to reveal what they have.
1:08:19
Certainly not if it's China or Russia. Yeah. >> Right.
1:08:22
>> Right. and um you know but and private companies maybe not Google maybe some of these pure play quantum companies like how are they going to make money well one way would be to recover Satoshi's Bitcoin as if it were buried treasure right like oh buried treasure Satoshi's not here it's mine now >> right so I mean that could be another
1:08:38
scenario >> um so look I think the there is just a whole bunch of uncertainty about how this is going to play out about who's going to execute the attack about how long a quantum computer will take and again because blockchains like Bitcoin fundamentally rely on this cryptography like it's existential for them. That's
1:08:52
That's one of the reasons like I founded project 11 we and we pursue this you know solving this problem very vigorously is because everything's on the line here >> and we have to solve it for these chains like Bitcoin to have a future. >> Yeah.
1:09:04
Uh is there generally low optimism right now that Bitcoin developers will be able to react quickly >> enough?
1:09:13
Uh what what's the statement about like I think Churchill said about democracies or the Americans maybe where was like they'll do the right thing when every option is exhausted.
1:09:20
Um I think this is look I think this is true of decentralized networks like Bitcoin.
1:09:25
decentralized networks like Bitcoin. I mean their greatest strength is the fact that there's no single party that says how it works or how it should work right and this is this is encoded into how it was built by Satoshi as a as a reaction to the great financial crisis right um so that's a great philosophical strength
1:09:43
in the face of a crisis like this that demands a massive technical effort to overhaul um it's a daunting challenge because unlike say Google which you know Google has said they're going to upgrade all their systems by 2029 that's just you know someone at Google can make that decision snap right in bitcoin because it's distributed community everyone's
1:10:00
kind of first has to agree there's even a problem then everyone has to agree on the solution but I think there's examples of of uh places where blockchains like you know I'll take ethereum uh have done amazing things right so one is they they transition from an old system of consensus called proof of work to a new system called proof of stake it took four years to be sure but it involved thousands of people
1:10:20
all over the world and they did it they did it the blockchain's been running Ethereum is the second largest blockchain by market cap so I don't think it's impossible right but I do think especially in light of these two papers, these two breakthroughs, you just can't stop or you just can't wait anymore before starting that process. >> Uh what about the rest of the digital
1:10:36
>> Uh what about the rest of the digital world?
1:10:38
Because if if uh if if Bitcoin is having problems then so many other kind of core institutions and companies organizations I imagine would uh have issues as well.
1:10:51
Maybe maybe uh because they are centralized there's you know easier to react easier to kind of lock things down but still need to upgrade overall encryption.
1:11:04
>> Yeah, there's no doubt that other institutions need to upgrade but in my mind there's also no doubt that you know blockchains and digital assets are just the most vulnerable.
1:11:11
I mean one of one reason is obvious.
1:11:12
I mean, Satoshi, uh, Satoshi's Bitcoin, so the founder of Bitcoin, who we think has gone away or died or something, you know, they have a bunch of their early Bitcoin that hasn't moved.
1:11:22
There's a bunch of lost coins, you know, all in all, you know, that's about to maybe 15% of all of Bitcoin supplies estimated to be lost.
1:11:27
I mean, that's >> hundreds of billions of dollars >> uh potentially in in, you know, in market terms.
1:11:35
market terms. So that's just a huge incentive that like let's take let's take the counter example of you know if someone wanted to hack into a bank or something you know as you pointed out banks are centralized they can kind of react also the cryptography the way that banks implement this cryptography is just kind of one of many
1:11:50
layers of security right so it's kind of this breaks like theoretically someone tried to wire all the money out of my account my bank call me >> yeah no they literally have tape drives where you know they they have cold storage they print things out and they have the ledger and they can potentially
1:12:02
roll back which is crazy to think about but like they could if there was like a catastrophic hack they could be like look everyone's just going back to yesterday's accounts and you know that's better than the chaos that we were in >> that's it and that's not true for Bitcoin right all I need is one signature and all of Satoshi's or
1:12:21
Coinbases or Binance's Bitcoin is mine there's no fallback there's no anything that's how it was designed right that's the point that was the point permissionless >> finance that was so >> that's the challenge >> so what is the state of the more faster moving coins, faster moving moving chains. Are you consulting or do you
1:12:37
Are you consulting or do you think you'll plan on launching something yourself that is uh uh quantum secure, quantum proof?
1:12:46
Um how do you think this plays out?
1:12:48
Because it does feel like uh you know, I'm optimistic that I'm rooting for Bitcoin.
1:12:53
I hope the devs figure it out quickly.
1:12:55
Uh you know, hopefully that happens.
1:12:57
But it does just feel in terms of like the marketing of a new project, there is a bit of a white space to say we're the ones that are taking this particular feature most uh most uh most seriously. >> Yeah.
1:13:14
Look, I mean it's kind of hard to know how things are going to play out, but the white space that we're occupying is we want to be the bridge, okay, >> for digital assets to the postquantum future. right now.
1:13:22
That doesn't necessarily rule out potentially having a platform to issue on top of at some point, but I think for now our priority is more or less, you know, people have already decided that things like Bitcoin and Ethereum and Salana and stable coins have value. Yeah.
1:13:36
>> And I think overwhelmingly they would like to keep the things that they already value and just make them secure.
1:13:41
So that's what we focus on, right?
1:13:41
And there's no shortage of things for us to do because uh the protocols all have to get fixed, all the smart contracts have to get fixed, all the apps have to get fixed, and then all of the user wallets have to get fixed.
1:13:52
And so again, going back to the fact that this is a stack, and you're breaking the bottom part of it.
1:13:56
So I mean, we really focus all the way across.
1:13:58
So we've done work with Salana, the Salana Foundation, we did the first postquantum test net for them.
1:14:03
We've worked with a few other protocols as well.
1:14:04
We designed actually a new novel postquantum algorithm designed for blockchains with the founder of Zcash. We've done that, too.
1:14:09
We collaborate with EDF and we're doing we're getting ready to launch our own postquantum wallet as well. >> Yeah.
1:14:14
Uh talk about the information flow.
1:14:17
How much of the work that you do the work that will be done by the Bitcoin Foundation, Ethereum Foundation, all the different developers.
1:14:24
How much of that is open source by default or licensable or just can be understood by other parties and implemented very quickly?
1:14:35
How should we expect diffusion once this problem is solved to actually roll out?
1:14:40
Will it just be like, oh yeah, like we're just following the Salana standard and so we're just going to mirror that over onto, you know, whatever chain we're working on.
1:14:50
>> Yeah, I think there will be diffusion.
1:14:50
>> Yeah, I think there will be diffusion. I think there will be uh you know uh sort of sort of consensus if you will around a certain subset of postquantum algorithms but I don't think it's just you know one and done because Salana is a very different system than Bitcoin right Bitcoin's digital gold it's sort
1:15:07
of meant to be slow you know there's no apps on it Salana is meant to be fast right y >> and so the cryptography that works for Bitcoin might not be this cryptography that works for Salana and this is actually was kind of the results of of some of the experiments we ran with Salana and uh and Look, this is one of the challenges, right? And this is again
1:15:21
And this is again by why why we keep saying this is like time to start is now because we don't know how long it's going to take to migrate because >> you know these new algorithms, there's trade-offs that come with them.
1:15:29
And by the way, even if you choose to implement one, you need to test it and you make sure it's secure, all this stuff.
1:15:33
So, um, >> have you tried to have you tried to quantify or guess estimate what the quantum discount rate is on Bitcoin right now?
1:15:42
Because it's an interesting thing where like if you own a lot of Bitcoin, there's a bunch of people on the timeline today talking about this.
1:15:49
They don't have an incentive to like really freak out and spread the narrative, but they have some incentive to say like, "Hey, we need to have a conversation.
1:15:55
We need to make progress on this."
1:15:57
But, uh, do you think that's that's factoring into price at all? >> Totally.
1:16:02
I mean, the way I would put it is uh I think if this risk didn't exist, Bitcoin would be priced significantly higher.
1:16:08
So, I think exactly what you said is right.
1:16:09
you like, "Oh, I'm not going to sell my Bitcoin because, you know, it's maybe not right around the corner and I'm hoping people fix it, but I also think there's people that would maybe enter uh and they're like, you know, Chimath has said this exact thing.
1:16:23
He's like, "Hey, is this really digital gold uh without with this quantum threat hanging over everyone's head?"
1:16:27
So, I think if that threat was removed, then you know, you remove this cloud over that ecosystem and potentially, you know, you'd have a lot more people coming in and therefore price would be up. >> Yeah.
1:16:36
the the it's easy to imagine as you approach that 2029 mark more selling pressure, more concerns if meaningful progress isn't made in the next two years.
1:16:48
Um uh what what what countries uh have the most kind of advanced quantum projects outside of the US?
1:16:55
I can guess, you know, China's, you know, investing heavily here.
1:17:00
Uh do they have their own retail quantum companies that are trading like crazy? Yeah.
1:17:09
Uh first off, I I think it definitively the leaders uh both companies and research is American.
1:17:13
So I think we should, you know, proud to be an American here.
1:17:17
Uh but look, I think one interesting thing about the way China has chosen to attack this is uh they've made quantum computing a priority.
1:17:23
And what that means in China is, you know, it's like there used to be a lab at Tencent and at BU and a few other places.
1:17:29
And at some point a Chinese Communist Party official came in and said, "Guess what?
1:17:32
You guys all work for us now." And guess what?
1:17:34
You're all working together now. And guess what?
1:17:38
You're not allowed to talk about it anymore.
1:17:39
Uh, and that's the state of things.
1:17:41
It's it's kind of a I don't want to say Manhattan project, but it's like that level of secrecy in China.
1:17:44
Uh, and there's a legitimate question around how far back they are.
1:17:48
So, the best estimates that we have from quantum like we have a quantum physicist who's an adviser to project 11 that, you know, tracks generally resource estimates across the world and and their view is that China may be six to 12 months behind at most.
1:18:02
>> And so, this is Yeah, exactly. That's not that far.
1:18:05
>> Yeah, that's really quick, >> you know.
1:18:07
And so, can we expect, you know, a quantum computer in the hands of the Chinese Communist Party that maybe is more willing to crush descent in places like Hong Kong to uh care as much about the philosophical principles of Bitcoin and decentralization uh if it serves their purposes to do otherwise. I don't think we can.
1:18:21
And so, I think again back to the fundamental problem, uncertainty, right?
1:18:25
And it's better to be safe than sorry.
1:18:26
So, we need to basically prepare today to prevent the crisis tomorrow to keep the trust in these systems.
1:18:31
Well, thank you for everything that you're doing.
1:18:33
Thank you for your service both here and before. Uh project 111.
1:18:37
com is the website, correct? >> Y all spelled out. Yep. >> Fantastic.
1:18:45
Thank you so much for taking the time to come chat with us. We'll talk to you soon. >> The breakdown. >> Have a good one.
1:18:50
>> Great to be here, guys. Thanks. Cheers. >> Goodbye.
1:18:51
Let me tell you about Vanta.
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1:18:58
And without further ado, we have Quaser Ununas in the Reream waiting room from Applied Intuition.
1:19:03
He's the founder and CEO of the company.
1:19:06
And we'll bring him in in just a second. Uh we are running.
1:19:14
>> We need a little bit of time.
1:19:15
>> A little bit ahead of schedule.
1:19:15
A little bit ahead of schedule.
1:19:18
>> We need a little bit of time.
1:19:19
>> And it's hard because there's not all that much short-term news.
1:19:21
There is one news item that we can go through quickly.
1:19:25
All birds just sold for $39 million.
1:19:28
The company was once worth over $4 billion with DTOC Darling.
1:19:31
Followed this company closely.
1:19:34
Uh because I was building a DTOC company at the same time.
1:19:37
I was like, "Wow, they are really getting big."
1:19:39
Um but it seemed like it did not particularly scale.
1:19:42
It was more of a niche product potentially.
1:19:45
Uh and of course, you know, margins and cost of sales creep in and uh then everything collapses to private equity multiples.
1:19:54
Did you ever wear a pair of allirds?
1:19:58
Would they ever pull you away from Bayga, get you in some Allirds?
1:20:00
You know, it's uh Australian wool, >> you know.
1:20:05
It's kind of like Italian leather Australian wool.
1:20:06
Yeah, there's something like that.
1:20:09
>> No, I never I never own a pair.
1:20:12
>> Not even if you're visiting San Francisco.
1:20:14
It's a great It's a great sign of respect. >> Sign of respect.
1:20:16
>> Did you ever Did you ever have a pair? I probably did.
1:20:19
>> I think I had one pair at some point. Um they were okay.
1:20:21
They didn't I don't know.
1:20:24
They they they sort of like look okay and were comfortable on day one, but then they sort of deteriorate a little quickly.
1:20:31
>> This would be >> probably2 to3 trillion dollar company >> if the shoes had aura. >> Yeah.
1:20:39
>> But they they had >> they should have released a lot.
1:20:42
>> It seems like they potentially had negative >> Aura. Yeah. >> Yeah.
1:20:46
>> And they got and the I mean the the stock suffered.
1:20:47
They they had to pay the Aura tax, >> the Oura discount. massive or loss.
1:20:52
Yeah, I mean still a very interesting uh launch, very interesting uh go to market telling the story of where the materials are from.
1:20:59
That was certainly a playbook that was adopted by a lot of companies.
1:21:03
Uh showing putting the supply chain on display basically uh it was the right right fit at the time but people are not not into it.
1:21:11
The chat is not is not happy about >> let's ask let's ask our dear friend >> Queser Unice from Applied Intuition because he's here.
1:21:19
He's in the TBPN Ultra Dome now. Quer, how you doing? >> I'm doing great. How about you guys? >> We're doing great.
1:21:26
We have to ask you, >> do you own a pair of Allirds?
1:21:29
What's your preferred shoe when you're walking around a factory like that?
1:21:35
>> I uh don't own any Allirds.
1:21:35
When you're in a factory, uh you have to wear >> Yeah, exactly.
1:21:42
You have to have a steel.
1:21:43
There's no All birds at >> Maybe they should Maybe that's the comeback story for them.
1:21:45
So, they just they were worth four billion, now they're worth 40.
1:21:48
Maybe the steeltoe allirds are what gets it done.
1:21:52
>> A steeltoe allird would look fantastic.
1:21:55
Uh we seem to be having a video delay.
1:21:55
I think the team will work it out, but we can't hear you. Can you hear us? Okay. >> Okay, great.
1:22:00
Yeah, I can hear you and I can see you. Okay, so fantastic.
1:22:01
I know exactly what's going on.
1:22:04
>> Uh well, uh great to have you back on the show.
1:22:06
I'd love for you to just uh reset with us for the the shape of the business, where the company is today, how big are you, give us, uh you know, the broad strokes, and then we'll go into the partnership today. >> Yeah, thank you.
1:22:16
Uh thanks again for having me.
1:22:18
Uh the company applied intuition.
1:22:20
We're a $15 billion uh company still uh uh doing what we were doing before which is taking intelligence and putting into physical machines.
1:22:29
>> Uh today we have our first ever physical AI day where we're bringing lots of investors together, bringing industry analysts, you know, bringing everybody who's kind of relevant uh in the field to talk about all the things that are happening in physical AI.
1:22:43
We're we're pretty strong believers that the future, you know, the next kind of big thing is AI going out of screens and going into the real world.
1:22:52
>> Yeah, I couldn't agree more.
1:22:52
Uh talk about the the most recent partnership LG. >> Yeah, LG Intech.
1:22:58
We just uh we just announced this a couple of days ago.
1:23:00
The uh I don't know uh how many of your viewers know um but LG provides >> You're putting AI in TVs.
1:23:08
That's what you're doing.
1:23:10
The AI is going in the TV and I'm going to be able to ask questions. >> Thinnest biggest.
1:23:16
>> No, that is not that is not what we're doing. >> Much more serious.
1:23:20
>> I mean, what uh what's happening in the self-driving space is there is an now the models are basically working and they're they're figuring out.
1:23:27
So, really there's an aggressive downward pricing pressure of how to make self-driving cheaper.
1:23:32
The the research kind of question is done and now it's just an engineering question and that's just another way of saying it's a cost question.
1:23:38
So companies like LG who are doing you know sensors at really really uh large scales and really really cheaply. >> Yeah.
1:23:47
>> You know they're they're entering the space as well and we're working together with them on self-driving. >> Yeah.
1:23:51
So uh yeah take me through uh when when people think self-driving they always think Whimo Tesla but the the the the the market map of like products that need autonomy that would be defined as vehicles.
1:24:06
Uh give me some examples.
1:24:06
I mean you're standing in front of something.
1:24:09
Uh I I know that it's very broad.
1:24:11
Uh what's in this partnership and then what else are you focused on? What's adjacent?
1:24:16
Uh and what's you know on the road map? >> Yeah.
1:24:19
So um I think what's different about us versus let's say vertical players like a a Whimo or a Tesla is we provide this uh you know AI across all types of machines.
1:24:31
So you see a machines behind me if you were you guys were here for physical AI day.
1:24:35
We do we take the same models and we put them in defense.
1:24:39
We put them in commercial trucks.
1:24:39
We're running driverless trucks in Japan right now uh that are going into commercial operations in the next quarter. We are running in mines.
1:24:48
Uh so both all the way from you know Arizona to Australia.
1:24:51
So our hypothesis basically is >> these this these technologies whether it's self-driving or the underlying operating system they're so expensive and they're so complex to build and maintain.
1:25:04
The only way that you really make this a viable business is that you actually spread this across lots of manufacturers and lots of industries and lots of use cases.
1:25:11
I mean, our kind of crazy claim to fame is, you know, our company's almost 10 years old and we've preserved basically all the capital we've ever raised.
1:25:21
>> Which is kind of, you know, it almost sounds like BS, right?
1:25:23
Because uh the whole mantra is, you know, raise a lot of capital and then and we're a real AI company.
1:25:31
We have real AI bills and we we figured a commercial model which is allowed to scale.
1:25:35
We're we have over a thousand engineers and so we're one of the if not the biggest physical AI companies on the planet uh that's obviously also commercially viable.
1:25:44
So but it all goes back to that simple thing is like you want to distribute all this cost across lots and lots of companies, lots and lots of verticals.
1:25:53
>> What about what about shared learnings?
1:25:54
like are is a team that's working on mining are they able to find a breakthrough or discover something you can apply to trucking in Japan >> like is there a lot of >> absolutely that that is the heart of the company and so there's all the what you what you described as like shared learning kind of broadly but there's
1:26:10
also technical advantages what we've seen is taking data which is just obvious also not obvious but taking really really diverse data from a mine actually makes our self-driving car system better >> and taking you know data that we have from our software and car in Germany, you know, makes our defense work uh better. And so it really is it's really
1:26:29
And so it really is it's really is >> to our Yeah, I've heard so many stories about that where like there will be like exactly one instance of a a chicken being chased by a woman on a tricycle in the training set.
1:26:45
And so it's very hard for the machine learning system to actually understand that if you see that exact scenario, you got to slow down.
1:26:54
But that's the nature of big data and machine learning and these scaled systems.
1:26:57
And and and it's not it sounds crazy, but it's not that crazy to imagine some weird scenario that you see in a mine actually teaching you something that you could use just on a normal street. >> Yeah.
1:27:08
Maybe getting a level level lower just just so because I always me being an engineer always bothers me to talk in pure generality because I tend to mix miss things.
1:27:16
Uh just getting to a level lower what you're really talking about is anomaly detection and it's not necessarily like you know you need to see the chicken running across the road in Thailand and that's going to make the mind better.
1:27:26
But what's really happening is models are getting a better understanding of the physical world around them >> and the kind of parameters around them.
1:27:34
If you look at uh you know kind of the the last kind of generation I'm crazy to say last generation but really large language models large language models really improve with diversity of data that is really like you know a kind of a big breakthrough and of course scaling laws all of that stuff is being brought in to the physical world. Yeah.
1:27:50
And uh and we're powering that. >> Yeah.
1:27:54
I mean truly no one would have predicted or I mean of course some people did predict but I would have never predicted that like uh including poetry would help a model get to like solving math.
1:28:03
Like I would just see those as different things and say put the poetry team over there, put the math team over there.
1:28:08
But actually bringing all these things together worked really well.
1:28:11
Uh play out the counterfactual for me.
1:28:13
Uh you you haven't you haven't been a high burn company.
1:28:15
You haven't been super capital intensive.
1:28:17
If you'd done vertical integration and built the tractor behind you uh that would have been extremely capital intensive. Correct.
1:28:25
Is is is that like impossible?
1:28:28
>> It's well nothing is impossible.
1:28:28
Uh but you know I my my my my uh undergrad uh was at this obscure school called the General Motors Institute and uh as the name implies it's really about automotive.
1:28:40
It's like the West Point for automotive and uh when you spend a lot of years in factories as as I have uh there are some deep lessons that get imparted into you and one of those lessons is holy crap these factories are extremely cost intent the capital intense and they're extremely complex and uh the strengths of Silicon Valley are actually don't quite overlap with the strengths of building a large factory.
1:29:05
Now in terms of the core question, we had Mark and Dreon here today and we we you know we we talked about this.
1:29:11
Mark was one of our first investors and has kind of been been along with us with the entire ride.
1:29:15
I mean all the way to the presentation today and we asked him this question about vertical horizontal.
1:29:19
What do you see happening in AI?
1:29:21
What do you see happening specifically physical AI?
1:29:22
And the punch line is you know we all of our values at applied intuition can be reduced down to two words radical pragmatism.
1:29:30
And if there are verticals that we think that we should be a bit more vertical in, we'll we'll we'll do that.
1:29:36
And I think it's it's kind of a false trade-off to say what we do in, you know, trucking is what we're going to do in construction, which what we do in agriculture is what we're going to do in mining.
1:29:46
What we're really trying to do is bring intelligence out into the real world.
1:29:49
And each of these verticals are facing really, really different problems.
1:29:53
You take a, you know, with a tractor behind me, the average American farmer is 58 years old.
1:29:56
there's nobody coming to replace that person.
1:29:59
And so what is going to happen because you know if you take that person their kids have have left and they're often not coming and taking over the farm like maybe in previous generations.
1:30:09
So that farmer needs you know we don't need to teach them how to use claw code.
1:30:13
That's not what's going to change the farmer's trajectory.
1:30:18
What's going to change the farmer's trajectory is the machines are intelligent and they're working harder and smarter on the on on their behalf.
1:30:26
So he can run an entire farm with a, you know, with a swarm of machines.
1:30:29
And that's not, >> you know, that's not too far into sci-fi.
1:30:34
One of the key components here that, you know, we're doing and we believe is you need to abstract that hardware and software away.
1:30:39
We we as technologists, you look at like your laptop and your phone and you kind of take for granted the miracle that exists.
1:30:46
Android runs on thousands of hardware devices flawlessly.
1:30:48
So that's also something that apply does.
1:30:50
We're just abstracting a hardware and software.
1:30:53
Once you do that, you can make every machine, you know, intelligent.
1:30:57
>> Have you tried to estimate the economic impact assuming you guys, you know, stay at the, you know, at at the current kind of improvement rate or accelerate as the technology kind of starts to diffuse in in some of these industries like trucking and and mining and agriculture like what what are the downstream impacts?
1:31:16
I mean, there's such a debate right now around what what what impact will AI have on the economy?
1:31:21
So much the economy is like moving physical things around, producing things, shipping them.
1:31:28
>> Let's let's sep Exactly.
1:31:28
Let's separate a little because economy is such a generalization.
1:31:32
So when you're talking about like you know code complete and white collar work is very different than you know trucking where there is a huge labor shortage.
1:31:40
It's very different than in mining where you know people don't want to go live in kind of remote areas doing 12-hour shifts.
1:31:47
I mean literally labor shortages are preventing construction companies from you know collecting billions and billions in revenue.
1:31:54
So these are industries where AI can't get there fast enough. >> Yeah.
1:31:58
>> It's a very different calculus than a kind of you know I think what the normal narrative is and uh and then we're super obviously excited about that.
1:32:05
Let's take defense as a particular example.
1:32:06
It's a very salient example.
1:32:09
We don't need more warf fighters in harm's way.
1:32:11
We need less war fighters in harm's way.
1:32:14
And no war fighter wants to go out in into that ecosystem where a autonomy is really becoming the dominant thing.
1:32:21
And so so I think the way to think about this impact in the physical world is it's a lot less resistance. There's a lot more pull.
1:32:28
Now the first question you asked is the size of impact.
1:32:32
I don't want to, you know, sound like I'm pitching my own book here with the >> I'm asking you. I'm asking you.
1:32:36
I want I want the biggest number.
1:32:39
I want the biggest number.
1:32:41
>> The numbers are absurd and ridiculous.
1:32:41
>> The numbers are absurd and ridiculous. I I but there but I can tell you this much if you think about you know the way I think about you I used to be a Y cominator before I was a COO and and and you know ran the firm and funded lots of interesting companies and one of the analogies I used to use to help founders
1:32:57
understand market potential market sizes yeah I grew up in Detroit you're sitting in the Detroit metro airport and you're sitting in a gate you look around how many of those people are like really deeply using cloud code I mean sure >> frankly speaking not many lot will be using something like chat GBT, some variant of that, maybe Gemini. Uh, but
1:33:15
Uh, but how many of those people drive?
1:33:20
>> How many of those people work at construction sites?
1:33:21
How many of those people ride in buses?
1:33:22
How many of those people serve in our armed forces?
1:33:25
The point is a much much larger group.
1:33:27
point is a much much larger group. And I I I like that I I feel a little again the engineer in me feels a little awkward saying these kind of you know pitching these things but I think the market for physical AI is way way bigger purely because the surface area is much
1:33:43
bigger and it's compounded by the fa the way that the way technology diffuses with phones and laptops creates this like rapid you know competition that you see in you know that you're seeing in all these kind of subspaces right >> in physical AI you got kind of know what's going on in the car business. And
1:34:00
And I'm not saying, you know, I'm not, you know, gatekeeping and saying, you got to go to the General Motors Institute to build technology for the car business, but you bet your bottom dollar it helps.
1:34:10
>> And uh and we're doing that across a bunch of industry.
1:34:12
I think it's I think it's, you know, I'm I'm as confident about the company as ever before.
1:34:15
You know, the question we always get asked this question, why the hell did you raise all this money, you know, almost a billion dollars?
1:34:21
You're just going to keep plowing it away in the bank account.
1:34:23
We're doing it for a simp simple reason because we can if we need to we can invest very aggressively to take opportunities that we think we can accelerate you know beyond just traditional organic growth and so far that's worked.
1:34:34
It's not to you know promise the future that we won't uh but that's those are kind of debates we have every single day.
1:34:41
>> Yeah makes a ton of sense. Well thank you so much.
1:34:44
>> I just want to say I can see the path to a hundred and then a trillion dollars in in run rate. I agree.
1:34:49
>> Well I mean uh Whimo uh you know a company that we we we love them.
1:34:51
there are local, you know, we're we're also in Mountain View now, Sunnyville.
1:34:55
That company, uh, you know, >> is a great company, but is burning a lot of capital and, uh, is a smaller revenue base than us and just raised at $126 billion.
1:35:10
>> I mean, I love those guys.
1:35:10
I mean, we have so many friends there.
1:35:11
I'm not I'm not trying to talk poorly about this, but >> No, we love Whimo, too.
1:35:16
It's very impressive what they're doing.
1:35:18
you know, 15 that we're at and 126.
1:35:19
I I think we got room to grow. >> Massive. Massive.
1:35:23
Yeah, we got room to grow. >> Tell tell Mark. Tell Mark you're ready.
1:35:28
You're ready for the big believe me.
1:35:31
Everybody wants to, you know, I feel like it's faux where they want to get Pete keep putting money, you know, money into the company.
1:35:36
We we don't need anybody.
1:35:39
>> That is the best analogy for a venture capitalist.
1:35:41
They are the farmers stuffing the goose.
1:35:43
We we we we have our own we have our own uh farm, you know, and we're making our own money, so that that's really great.
1:35:50
And frankly speaking, I mean, like I said, Whimo is great, but it's just robo taxis. >> Yeah. Yeah.
1:35:55
>> And and and that's a small it's >> so much go to go to go to Warren, Michigan. >> Yeah.
1:36:02
>> And you just go go to the party shop in the corner and say, "Hey, aren't you excited about Whimo?
1:36:05
I don't think you know it's not hit the masses yet."
1:36:08
which just shows obviously Whimo's growth potential, but also shows I think how big physical AI is going to be. >> Yeah. Yeah.
1:36:15
Well, thank you so much for taking the time to come chat with us.
1:36:19
>> Fantastic talking to you guys. Thanks. >> Goodbye. >> Great to see you.
1:36:23
>> Let me tell you all about public.
1:36:23
com investing for those that take it seriously.
1:36:26
We got stocks, options, bonds, crypto, treasuries, and more with great customer service.
1:36:29
And we're talking to them later today.
1:36:31
But first, we have Sebastian Malibi.
1:36:33
He is the author of The Infinity Machine.
1:36:36
Sebastian, how are you doing? I'm doing great. Thank you.
1:36:39
>> Thank you so much for uh >> this has been you've been on uh on John's radar for a long time dream guest list for a long time.
1:36:48
>> We met maybe four years ago at a uh at a talk you gave around the power law and uh it was very fascinating. I love that book.
1:36:57
This book uh goes in a different direction.
1:36:59
Um, and after that conversation, I asked you uh probably the worst question you could ask to an author.
1:37:07
I asked you uh what what's your next book going to be about because you had selected venture capital.
1:37:11
Venture capital had done very well and I presumed that whatever you would pick would be a great investment category because you seem to be a good picker.
1:37:18
Uh you told me that you were thinking about biotechnology, biotech investing.
1:37:24
You went a different direction with AI.
1:37:27
Is there anything I should read into that?
1:37:34
>> Well, I always kick the tires on a few ideas before I I settle on one.
1:37:36
And um I think it took me from the power law coming out in February of 2022 >> to somewhere around the summer uh maybe August when I really settled on AI and then it took me another I don't know three months to get the courage up to go and pitch deis on the idea of giving me a ton of access so I could write this book.
1:37:55
And then I got lucky because I pitched him and one week later, guess what? Uh, Chachi PT came out.
1:38:01
So what I thought was maybe a fringe subject. Yeah.
1:38:06
>> Went mainstream super fast. >> Super fast.
1:38:08
Uh, what was the response with the team? What was the process?
1:38:13
Obviously, he's extremely busy.
1:38:13
He also uh sleeps at very random times. We can get into that.
1:38:18
But uh what was your actual interaction?
1:38:20
How much time did you spend?
1:38:21
What was the research process like?
1:38:24
So um once he agreed to be in, he was really in.
1:38:28
Uh it took about six meetings, two with him, four with his team to get them to agree.
1:38:32
And you know, my pitch was, hey, if you say in every speech you give that artificial intelligence is the greatest invention in history. >> Yeah.
1:38:45
>> That means you're way too important not to have a book about you and it's going to happen.
1:38:48
So you better get used to it. Yeah.
1:38:51
>> And also, if you're going to upend our lives, um, you know, change the way we think about ourselves as humans because it's a rival form of machine intelligence, you know, you better explain your motives to people, otherwise they're not going to accept it. So, that was the pitch. He agreed.
1:39:06
>> And then once he agreed, uh, we would meet like for two hours at a time.
1:39:08
Uh we would go to a pub near his home in North London and there was a kind of secret staircase at the back, go upstairs, kind of dusty little room with nobody else there and we would sit there for 2 hours usually >> and um he would just riff, you know, uh talk about philosophy, movies, computer science, neuroscience.
1:39:29
I mean, he's such a range of a person.
1:39:33
By far the most fascinating person I've ever written about. >> Wow.
1:39:38
That's uh that's high praise.
1:39:38
Um, how do you think about balancing the biographical timeline, the history, the financial impacts which you've covered in the past?
1:39:49
When I think about the the stories that you've told in the power law about venture capitalists, there's a little bit of their philosophy, but it's a lot of how the deals came together. Uh, fly on the wall.
1:40:03
I love that type of storytelling, but this goes a little bit of a different direction.
1:40:07
So, how did you how did you think about balancing all the different uh perspectives that you could bring to his story?
1:40:16
>> Yeah, I mean, I always want to do the personality, the the figure, but then the landscape behind as well.
1:40:20
So, it's always a mixture of, >> you know, you need a character who drives the story, but the story is boring if it doesn't mean anything. >> Yeah.
1:40:29
>> So, you have to link it to larger stuff that's going on in capitalism and how societyy's going to change and all that. Mhm.
1:40:35
>> And I mean in this case because Demis is who he is.
1:40:38
Um and he would just riff in these extraordinary paragraphs of like storytelling and and theoretical stuff and you know it's just so fascinating that I did give him the microphone more than I have in any other book.
1:40:52
I mean, I basically quote quote him at some length, you know, and it's broken up with me asking him questions.
1:40:58
And so, um, I'm kind of the reader's lens through which to see Demis talking.
1:41:03
And I'd never used the first person really before in my other books, but in this case, those 30 plus hours I had talking in a pub with this extraordinary man, that was the gold dust I had.
1:41:17
So to really make the most of it, I did have >> these passages of us talking together which kind of interperse the more analytical or narrative bits of the book.
1:41:30
You know >> how after the transformer model dropped, what was Ilas reaction and why did open AAI get ahead?
1:41:36
You know, I cover all that stuff as well. >> Yeah.
1:41:39
>> Um but I do have these passages where you see events through Demis' eyes because and I think it's worth doing because he's so unusual.
1:41:46
What was your understanding of AI or uh view on AI in 2022 before you meet Demis for the first time?
1:41:58
Were you aware of the the doom arguments?
1:42:02
Were you a believer in the technology?
1:42:03
Did you think it was 20 years away, a hundred years away, two years away?
1:42:08
Like where did you where were you before this book?
1:42:10
Because I feel like it probably changed you. >> Yeah.
1:42:15
Um, you know, I had met Demis before at tech conferences because of the power law and writing about >> venture capital.
1:42:21
I would go to tech conferences in Europe and he would sometimes be there and I I I actually cheekily you know raised the issue of um hedge funds and especially uh you know the one Renaissance Technologies the the main CEO Peter Brown um had done a PhD with Jeff Hinton about AI back in the day and of course I knew that Dennis would know that and so I said you know do do you know these guys who used deep learning and applied it to markets?
1:42:49
Um and and that got his attention.
1:42:52
So I I I talked to him a bit.
1:42:54
Um so I I knew that he was amazing.
1:42:56
I knew that the technology was ripe in the sense that he'd produced this string of breakthroughs.
1:43:02
You know, Alph Go >> defeating the human Go champion, >> then Alpha Zero, which was even stronger.
1:43:08
Then there was Alpha Fold, which won him the Nobel Prize, >> um for predicting all the shapes of protein in nature.
1:43:14
So there was a series of good models.
1:43:16
And what they all had in common was they dealt with they dealt with insane amounts of data, crazy combinatorial spaces.
1:43:24
Like in Go, there's 361 first moves you can make.
1:43:29
Okay, that's way more than chess. >> Yeah.
1:43:32
>> And so unscrambling go and the strategies in Go was much harder than chess.
1:43:37
And I knew that these breakthroughs were not just cool in themselves, but they represented the coming of a time when machines could make sense of an almost infinite amount of data and extract meaning.
1:43:48
And hence the term the infinity machine, the title of the book, and hence my enthusiasm for writing about it.
1:43:56
And you know, so I knew it was breaking out.
1:43:58
I knew Demis was amazing.
1:43:59
What I didn't know is it was going to break out literally the week after a met him and pitched him on the >> What has what has surprised you about how the industry overall has evolved since you started meeting with Demis?
1:44:14
Because in some ways I have to imagine you kind of maybe maybe it hasn't been that surprising at all even though a lot of the the growth is is impressive but uh do you feel like you had a view into the future from those first conversations in the pub?
1:44:30
Yeah, I mean I think you know I was lucky that the meetings were bookended by you know going to see Demis sort of maybe the third meeting or something.
1:44:39
Chachi Pety by this point had gone viral and him saying to me, "Okay, this is war, you know, and you could see his competitive side come out, right? This is war.
1:44:47
These guys, he said, have parked the tanks in my front yard, you know, I'm fighting back." So, you could see that.
1:44:54
And then after that comes the merger between Google Brain in Mountain View and the Deep Mind team in London.
1:45:03
So the two kind of halves of Google's AI um talent base are are united and then I think you get what you know a business school professor is in the future going to write about is kind of like a textbook case in how you make a merger successful
1:45:20
>> because everyone knows that mergers are hard and when you do it with eight time zones between the two teams one in London one in California and you're doing in the middle of this knockdown dragout you know capitalist fight over building LLMs. This is this is going to
1:45:33
This is this is going to be you know most people said this is going to fail and I would come to Silicon Valley while I was doing the book check in with my friends at you know different venture capital shops and they'd all say game over open one and you know the surprise is that within two and a half years um demisses you know Google deep mind model Gemini >> was doing better on the rankings than the open AI model.
1:45:57
So that was an incredibly fast comeback. Yeah.
1:45:59
How do you think about the importance of being like a business person or a deal guy in AI?
1:46:09
It feels like Demis has this quote he doesn't want to grow that part of his brain referring to some legal uh negotiations that took a number of years. >> Solomon. >> Oh. Oh. Was that Mustafa?
1:46:21
That was >> No, actually that that that was De saying I don't want part of this this part of my brain to grow.
1:46:27
Take away these legal briefs.
1:46:29
I completely get that and it seems incredible for him to stay in the research mode, build the research organization and yet uh because of scaling laws, we're in this weird regime in this paradigm where sometimes doing a deal to marshall an extra 10 billion of compute actually does unlock a new capability and in is almost in the research track.
1:46:53
And I'm wondering how you perceive the relative importance or or Demis' uh perception of the relative importance of these sort of like business dealings that might be more critical path to AGI than the demis of 2021 might think.
1:47:12
2021 might think. H you know I would say that the single most important business relationship in the world today is between Sundar Pichai you know CEO of Google and Deis Sabis who's running the AI brain trust because you know Sundar has Deis' back he deals with providing
1:47:34
the resources you know supporting the notion that you're going to spend all these tens and maybe hundreds of billions on compute you know that's Sunda's that's what he delivers and he gives Demis the oxygen to then just go do the science and sure he has to build products but I think you know he said to
1:47:51
me several times Demis >> we've got to a point where building a product like Gemini is in fact advancing the progress towards AGI there's not a there's no tension between the two if you had stopped your AGI research 10 years ago and taken a sidetrack to build some widget yeah that would have been a
1:48:12
waste of time >> but Well, now that it's so mature and you're actually to build the next LLM, you got to kind of figure out, you know, a reasoning model, then it's going to be a gentic and then you're going to be scaling it even more and all this sort of stuff that we've seen. Um, and this
1:48:25
Um, and this is genuine scientific progress as well as product advance. >> Yeah.
1:48:31
Uh, do the products also help sort of shift the culture in Google?
1:48:35
I'm interested in understanding uh this concept of like AGI pilling becoming uh becoming a believer in the demis worldview of the impact of AGI what artificial intelligence will do that mindset has to diffuse through Google the chatbt viral moment clearly had an impact I'm sure agentic coding has had has has had a similar impact but what has demis' role been in being the culture carrier of that belief belief in AI progress internally.
1:49:11
>> Well, I think he's used all his sort of visionary communication skills to unite the Mountain View team and and the and the London team.
1:49:22
>> And I think the the the one sort of organizational contribution he's made which is sort of super powerful is that from a long time ago, Deep Mind had always two different cultures going on at once.
1:49:32
There was a kind of blue sky research for scientists.
1:49:36
You get a lot of freedom.
1:49:38
You could publish papers and all that.
1:49:39
You know, go go go find what you want to find.
1:49:41
And then there were moments when Demis decided that if you pushed really hard on a particular product or a particular project, you could get a, you know, breakthrough >> achievement that would really shock the world.
1:49:57
And so he did this repeatedly with, you know, Alph Go and Alpha Fold.
1:50:01
And this was sort of like his judgment, scientific taste being applied to knowing when, you know, the moment was ripe to to really go for it.
1:50:08
And once he decided that there was, you know, the blue sky research kind of bottoms up stuff, you know, that went out the window and it became a top- down strike team they called it.
1:50:20
>> And in a strike team, there was a lot of top down direction and kind of everybody had to work on the same code base.
1:50:24
You couldn't just like go off and code your own experiment on the side.
1:50:28
You had to be contributing to the main one.
1:50:29
be contributing to the main one. and that drives towards uh you know a team is driving in a united way towards an outcome and I don't think um Google brain had that Google brain had you know much more of the bottomup stuff >> and there was no strike team component
1:50:47
and but and and so Deis brought this strike team idea and it came from video game design you know in earlier in his life he'd been a a builder of video games and he in fact started a company doing that >> and so this was like how you ship product and and that's been a key insight for Gemini. >> Yeah,
1:51:05
>> Yeah, >> Google and Gemini have every advantage just due to the massive cash flows that they have from their other businesses.
1:51:13
How do you think that has impacted the culture of Deep Mind given that they have something very real to lose? Right.
1:51:22
It's not just about the, you know, maybe Demis' personal desire to be at be, you know, be at the forefront of this research, but if you're not successful, then you you lose one of the greatest business.
1:51:34
You have the potential to lose or or have your kind of core business threatened. Yeah.
1:51:38
Google search in such a big way. >> Yeah. >> Yeah.
1:51:41
Um and I think you know Google search stands for a more general point that you know Google's whole reputation stands on providing reliable information.
1:51:51
And so the penalty for screwing up is very high.
1:51:54
You've got this very valuable company.
1:51:56
You don't want to support its reputation.
1:51:57
And so I think they were more worried about you know releasing a chatbot um fast.
1:52:02
And so they had they had prototypes of a chatbot in the fall of 2022 and they didn't want to release and then OpenAI went ahead and did it.
1:52:13
Um and so that kind of forced their hand but their first instinct was this is going to hallucinate.
1:52:19
Um this is going to do bad stuff.
1:52:21
We can't afford that hit to our reputation.
1:52:24
Um and you know Demis was quite honest with me in saying well you know the surprise was actually the public's quite happy to play with the tool that hallucinates.
1:52:32
you know, they still it still went viral, you know, so we should be less inhibited, but but that was an example of how >> being at Google could be a kind of inhibition in moving ahead.
1:52:45
>> Uh how do you how does Demison uh he's always told a very optimistic story about AI?
1:52:50
I I love him as a science communicator, as a as a as an optimist.
1:52:55
How has he interfaced with the effective altruist commu community more of the uh the AI doom crowd?
1:53:01
Uh does he because he doesn't talk about it that often but does he think about it often?
1:53:08
>> He does think about it.
1:53:08
In fact, you know, he met his co-founder Shane Le at an AI safety lecture, right?
1:53:12
They bonded in a safety lecture. >> Yeah.
1:53:16
>> And so, right from the beginning, safety has been a big part of the agenda.
1:53:18
And when Demis sold his company to Google in early 2014, part of the deal was you're not going to use this technology for weapons ever.
1:53:28
And you're going to have a special independent oversight kind of committee, you know, which will decide on AGI deployment because we don't want that to be just up to the corporate board of of Google.
1:53:41
>> Now, you know, he's he's slipped on some of these things, particularly the military stuff.
1:53:44
Um but he has been thinking about safety and um you know the question is what has he got to show for it?
1:53:52
It's all very well to think about something but what can you deliver?
1:53:55
And I think you know this is why towards the end of my book he's talking to me quite honestly about how it's a sort of paradoxical moment.
1:54:01
He's doing great as an AI inventor.
1:54:03
He's doing terribly badly as a sort of AI steward as as making it safe.
1:54:10
It's just it turns out that there's a race dynamic.
1:54:14
the race dynamic includes China. Yeah.
1:54:17
>> You know, how do you control this technology when everybody is racing to jam it out the door?
1:54:24
>> Yeah, it was interesting last week we were talking about how uh you know, Bernie Sanders has come out with a with a push uh to to pause data center development and he quotes Demis and some other lab leads talking about how they would agree to a pause if other countries were were kind of in agreement on it.
1:54:42
Uh, and Bernie obviously left out the fact that, uh, I don't think any lab lead could see China pausing on development.
1:54:49
So, >> um, uh, how has your personal definition of AGI evolved over the last few years because everyone has their own definition.
1:54:58
Half the people that come on the show says it was >> it was six weeks ago. Exactly.
1:55:01
Uh, and then and then and then yet we're still in so many of these kind of more highlevel conversations.
1:55:08
lab leads talk about race.
1:55:11
You know, we're AGI is six months away.
1:55:13
You know, >> you're you're you're completely right.
1:55:16
Everybody has their own definition.
1:55:16
And so my solution is not to have that discussion.
1:55:20
I mean, who cares what you know this like you could say right now it's Gemini is artificial? It's general. It's intelligent. Game over.
1:55:25
But >> you know just a definition thing.
1:55:28
I think the other one which is sort of usually fruitless is is AI conscious?
1:55:34
Could it become conscious? What is consciousness? Nobody has a good idea.
1:55:38
So >> let's just uh sidestep those.
1:55:40
>> I heard one good idea which was something around uh training a model specifically that would hold back all data and all and all training data related to consciousness and the idea of consciousness.
1:55:52
And so it cannot just pull from the archive and and and reference or simulate consciousness.
1:55:57
And if it develops consciousness from that and can talk cogently about consciousness without having any training data, ever seen the idea of consciousness, then maybe that's conscious. I don't know.
1:56:09
It was just an interesting thought experiment.
1:56:11
I don't know that anyone's actually run the uh run the test and I don't know that I would even accept it if they did, but uh it is something to think about.
1:56:18
>> Did did you feel an acceleration in your personal writing process due to AI?
1:56:25
I felt an acceleration in my learning process which is sort of what I do before I go interview people.
1:56:29
Um so because all of the >> computer science papers are basically on archive and you know recently there's been less publication but you know certainly up to about 2022 you could go see a scientist either at DeepMind or one of the rival labs and and just have a conversation with the model about okay this person has done four papers.
1:56:49
What's the connecting thread?
1:56:51
Why is this person different to the one I interviewed last week?
1:56:53
That was a super efficient way of getting up to speed and I didn't worry that it might be wrong because I was going to speak to the human um and cross-check it. But uh that was helpful.
1:57:04
>> Do you think uh Demis' uh having a having a home base in the UK is in what ways do you think it would have helped or or hurt the company so far?
1:57:16
>> Uh like has it been beneficial from a talent war standpoint?
1:57:19
I'm sure I'm sure lab us some of the other lab leads have taken a trip out to the UK to >> Mark Zuckerberg's hoping hosting nightly dinners for AI leads at his house which is just a couple blocks from all the other labs.
1:57:32
Can't do that if you're in if the researchers are in the UK, >> right? Yeah.
1:57:37
I mean, there is movement across the Atlantic, but I think the deal is if you're in London, it's a little harder to recruit people, but once you've got them, they're probably stickier than they would be if if you're in Mountain View or somewhere.
1:57:51
>> Um, you know, I think Demis has stayed in London because actually he is weirdly patriotic.
1:57:55
You know, he comes from this >> mixed up sort of, you know, Greek heritage father, a Singaporean Chinese mother.
1:58:03
>> Um, in a way that makes him a typical Londoner. >> Yeah.
1:58:06
because London is a really a melting pot.
1:58:07
Um but you know he stays there because he feels he wants he believes in sort of British social democratic values.
1:58:14
It's maybe ironic to an American audience but you know actually he thinks it's more egalitarian in Britain than it is in the US.
1:58:20
in Britain than it is in the US. you know, the US, if you go to the Deep Mind Office in London, you know, you go past the sort of public spaces like this kind of fountain with toddlers playing in it and there's a kind of free movies in the
1:58:34
summer by the canal and then you get to this green space where the kids from the local housing project are playing soccer and then you get to the deep office and it's hard to imagine you'd find that out on the way to the, you know, the the Apple headquarters or something, you know, it's just a different vibe. Could you ever see Demis as CEO of
1:58:53
Could you ever see Demis as CEO of Google or would he have to do too much paperwork?
1:58:59
>> You know, this gets to the heart of the dichotomy about Demis.
1:59:01
It's so difficult because he's so many different things at once.
1:59:04
I mean, you know, he is this Nobel Prize winning scientist who would love to just do pure research.
1:59:09
And he often would sort of fantasize to me about, hey, I want to retire to the Princeton Advanced uh Institute of Advanced Studies uh and and do what Einstein and Oppenheimer did before me and go there.
1:59:22
And that, you know, I think he really means it when he says that.
1:59:25
>> At the same time, he also wants to be in command of, you know, an AI lab.
1:59:28
and he he likes the capitalist competition. >> Mhm.
1:59:35
>> So if he had the opportunity to be chief executive of uh the whole of Google, I suspect he's too competitive to say no.
1:59:43
Um but but but who knows?
1:59:43
I mean there is that science side.
1:59:47
So it's genuinely unpredictable.
1:59:50
>> He probably doesn't know himself.
1:59:52
>> Were you left personally optimistic after this process about just our AI future broadly?
1:59:58
net positive impact from AI.
2:00:02
>> I mean clearly there's a lot of upside especially in medicine um uh and pharmaceutical discovery.
2:00:06
Um I think you have to be honest and say there's also downside significant downside.
2:00:12
Um, and as I continued to do the research for this project, you know, I I I became more worried about the downside because, you know, people like Jeffrey Hinton, I went up and spent two hours in his kitchen in Toronto and sat there debating not necessarily whether machines would be more intelligent than humans, obviously that they will be.
2:00:33
>> Um, but whether they whether machines have a motivation to harm humans, and he's very persuasive in arguing that they will.
2:00:40
I mean, my point was, look, humans evolved over centuries to survive, to pass on their DNA.
2:00:46
We're hardwired to survive.
2:00:48
That's why we fight each other.
2:00:50
Um, machines aren't like that.
2:00:53
So, why would they attack us?
2:00:54
Why are you so worried, Jeff?
2:00:54
And Jeff is like, well, you know, imagine you've got this super powerful AI and it's going to be attacked by the enemy AI and you have to defend it.
2:01:01
So, you tell the AI, if you see a cyber attack coming, you've got to fight back.
2:01:06
You got to defend yourself.
2:01:07
And now all of a sudden you've given your AI a survival instinct.
2:01:12
And so don't tell me that evolution has to happen as it happened to humans.
2:01:17
The evolution can happen in a machine way. >> Mhm.
2:01:20
>> But these systems are going to want to survive and they're going to be more intelligent than us. >> So we're in trouble.
2:01:25
And I think you can't dismiss that.
2:01:26
So >> I'm kind of both worried and excited at the same time.
2:01:31
And I I I think that's how humans generally respond to all technology.
2:01:36
And if we didn't take that trade and move forward with both the excitement and the scariness of technology, you know, if we didn't take that, we'd be still living in caves. >> Yeah.
2:01:47
>> So, in some sense, the story of Demis is like, you know, the story of all of us, but magnify 10x.
2:01:51
There's a documentary that was just released or might be releasing right now that features an interview with them uh the AI doc and it it it spends more time talking to all the different lab leads and voices in the industry.
2:02:06
Uh more focused on the doom question uh can we be apocalyptic? Should we be optimistic?
2:02:13
Uh but what I found most interesting was that uh the creator of the documentary uh you know summed up his full takeaway and said that AI is a Ponzi scheme.
2:02:21
And I'm wondering if you got any any uh any vibes that uh everything will collapse that this is uh just not financially viable.
2:02:34
>> No, my view is that there's no AI bubble but there's only just an open AI bubble.
2:02:40
um you know I in the sense that um the technology clearly uh is getting better and better pretty fast right you know we had the first chatbot in 2022 and it hallucinated then they killed the hallucination then they had longer
2:02:53
context windows then they had you know multimodal systems that could handle video and pictures and then they went to reasoning models and now we're getting agentic models and now next there's going to be you know world models that will be built into these things. This is
2:03:05
This is a lot of progress in just three and a half years.
2:03:09
Um, so I think it's it's accelerating in progress and therefore it's not a bubble. Mhm.
2:03:17
>> But what is true is that it's super expensive to develop and if you're not attached to a really deep pocket like you know Demis is attached to Sunda um you're in trouble.
2:03:28
Uh because I don't think OpenAI can raise enough money to bridge from today when they have a a very popular chatbot but almost none of those customers pay for it to some future where the product is stickier somehow and they can charge money.
2:03:43
And so I think you know open AI has been running two simultaneous experiments.
2:03:49
One is with a new frontier technology and the second is how deep are global capital markets and they already raised you know 41 billion last year which was a record for any private fundraising uh bigger than any IPO by the way as well.
2:04:06
Um, and so, you know, kudos to Sam Wolman for raising that much money, but can you pull that trick like on a bigger scale every year until 2030 when they hope to break even? No.
2:04:16
Uh, and that's why they're cutting products like except for right now >> cuz they just raised the 20.
2:04:26
>> But if you look at the 100, it's kind of smok and mirrors.
2:04:27
That's that's, you know, a lot of that is contingent on you you get this money if you go public.
2:04:31
Uh, you get this money in the future.
2:04:33
you get this money in kind in terms of you know compute or something.
2:04:37
The 100 wasn't really 100.
2:04:41
>> Isn't there a little bit of a dynamic where you could wind up with like an anti- Googlele alliance?
2:04:44
Maybe there's, you know, there's like a tension between the the industry and Google.
2:04:48
This is like the foundational like myth of the AI industry and the AI labs broadly, although they of course have fractured many many times at this point. >> Yeah.
2:05:01
I mean, you know, of course there's always rivalries.
2:05:03
Um, you know, one might say people will gang up on Nvidia.
2:05:08
Um, you know, that's the occupational hazard of being the leader, right?
2:05:13
>> I think they'll deal with it.
2:05:13
I mean, I don't think it's a winner takes all market, by the way.
2:05:16
I I think that, um, you know, >> there'll be space for others.
2:05:20
>> Yeah, that makes sense.
2:05:22
>> Last question from my side, then we'll we'll let you go.
2:05:24
Uh, did you have any takeaways or kind of ideas around uh the diffusion of physical AI and robotics? Did anything stand out?
2:05:33
Do you have a strong opinion there?
2:05:35
Right now it feels like we've entered the sort of software singularity.
2:05:39
Um but uh we we just had Kaser from Applied Intuition on and we're talking with him about how autonomy and AI is diffusing through the physical world, but I'm curious if you had any takeaways.
2:05:54
Yeah, I mean look, I think that, you know, one thing sometimes people don't quite understand is that large language models and the transformer architecture that underpins them is super consequential for lots of applications, not just chat bots.
2:06:06
And so robotics is being improved by this technology and you know I fully expect to see a huge breakthrough um you know over over the next two or three years with the capability of robotics and so I think that's that's going to be the the big story uh I kind of agree with um the guy from Kesar you had before uh that you know the movement of atoms is going to be affected as much as as anything else.
2:06:36
Um, so that's part of why I don't think this is a bubble.
2:06:38
I think, you know, the potential in, you know, this super powerful AI is is enormous. >> Yeah.
2:06:45
Well, thank you so much for coming and joining the show.
2:06:47
It was a pleasure talking to you.
2:06:48
The book is The Infinity Machine.
2:06:50
It's available everywhere books are sold. Thank you so much.
2:06:53
And we will talk to you soon, too. >> Yeah. Beautiful cover. >> Check it out.
2:06:58
>> Thank you for having me.
2:06:59
>> We'll talk to you soon.
2:06:59
Have a great rest of your week. >> All right. Goodbye. >> Take care, guys. Bye.
2:07:03
>> Let me tell you about Flint.
2:07:03
AI, AI, the number one AI agent for customer service.
2:07:06
If you want AI to handle your customer support, go to fin.
2:07:08
ai and we will kick off the lambda lightning round. Let's see. Oh, look at this. We got everything. This is amazing.
2:07:16
Uh, >> let's bring in Forest. >> Forest from Somos. Welcome to the stream. How are you doing? >> Hello, guys. How you doing? >> We're doing great. >> Thanks for editing.
2:07:28
>> First time in the show.
2:07:28
Please introduce yourself.
2:07:30
>> What a what a setup here.
2:07:31
>> This is a great setup. >> Set up. >> This looks fantastic.
2:07:34
armed with a bunch of >> nerdy stuff from the the team, all the things we're building. No. Hey guys, I'm >> Forest. >> Amazing. >> Yeah, break it down. >> Amazing. Uh, yeah, kick it off. >> Let's see. Where do I start? I'm Forest.
2:07:48
I'm a fancy plumber building infrastructure from scratch down here in Colia to make internet way better and make compute and everything kind of work well in Latin America and beyond.
2:07:57
So very weird journey, but making the fastest internet in the world at the lowest cost is kind of the summary in a very short nutshell. >> Amazing.
2:08:05
You have uh a lot of fans.
2:08:05
I got a bunch of texts from uh investors uh that were excited for you to come on.
2:08:13
Um what what were you doing before before we get into so much?
2:08:14
What were you doing before this?
2:08:18
>> Dude, I came to Medigene when I was like 18 years old.
2:08:20
Basically just dropped out of high school.
2:08:22
I started building stuff and ostensibly came to visit a friend for a couple weeks and that was eight years ago and here I am. So I I made websites.
2:08:30
I kind of took a very non-traditional path and it's led me to doing a bunch of weird stuff here.
2:08:36
>> That's actually a non-traditional path.
2:08:38
Normally when somebody comes on and says they had a non-traditional path, it's like you know Stanford to a meta internship, a Google internship, a VC internship.
2:08:47
Um but uh very very cool.
2:08:50
What uh yeah, break down like you know Somos, you're raising a series B today.
2:08:55
What like how long have you been at it?
2:08:57
Uh what what initially I I can kind of guess what the initial inspiration might have been.
2:09:01
You're building digital products it sounds like and we're probably frustrated with internet speeds but uh what's what's the backstory?
2:09:09
>> No, I came to Colombia in 2018.
2:09:13
I got roped into helping people build this like blockchain incentivized blah blah blah back when everything was going to be blockchain in like urban slums here in Medigene.
2:09:21
And as those blockchain projects happened, everyone got bored really quickly.
2:09:25
got bored really quickly. So they just left me with all the equipment and I just kind of became fascinated by how do you build connectivity in slums and didn't speak any Spanish, didn't know anything about telecom and just started tinkering and first couple years were me like literally living in a slum here in
2:09:39
Medigene building internet stringing stuff up in the middle of the street and kind of bit by bit I just became fascinated by the concept of like internet is the most basic thing for the modern world and we just sort of assume that it's been solved and really we haven't done engineering in the last like 30 years. It's It's the same
2:09:55
It's It's the same underlying architecture that like John Malone was building in Cable Cowboy days. >> Yeah. >> Yeah.
2:10:01
Every time I go travel to another country, I always look up like who the biggest industrialists are and who the richest people in the world are.
2:10:06
It's always the people that built like the railroads, the mines, the telecom infrastructure, the the Wi-Fi, the internet, the power lines.
2:10:13
It's always like the stuff that once you install it, uh it provides value.
2:10:19
>> So, yeah, sounds like sounds like you're doing a lot.
2:10:20
what what is what is in your strike zone of of things that you want SOS to take on versus where do you work with external partners?
2:10:26
Like what is what is the kind of core path?
2:10:30
>> Dude, this is kind of the insanity of SOS.
2:10:32
So we literally do everything from like we interface with the submarine cables.
2:10:35
We built like a nationwide backbone crisscrossing the country.
2:10:37
We like make the the Wi-Fi router.
2:10:39
So like the things that go inside of the thing here is all PC. >> Oh, that's a Wi-Fi.
2:10:44
I thought that was just a pretty lamp.
2:10:47
>> So So this is literally the router that goes in customers homes.
2:10:49
So instead of being some like ugly blinky box, it's like a beautiful lamp. >> The lamp.
2:10:55
>> You're like, "Wait, does it have to be an ugly box?"
2:10:56
Or >> no one thought of this.
2:11:00
>> Like the internet is like literally the most incredible machine humanity's ever built and we just relegated it to being this like ugly piece of infrastructure and kind of our our idea is like what if it was dope? >> That's amazing.
2:11:09
So yeah, like how how do you like how how does the coverage map like spread out?
2:11:15
Everyone's familiar with those like AT&T and Verizon coverage charts of like the map of America.
2:11:20
Uh do you have to go city by city, block by block?
2:11:23
Are are there ways that you can like how do you actually scale out to reach an entire coverage area?
2:11:31
>> So I literally have like a thousand plus employees cabling the streets.
2:11:33
We have like linemen and installers and they're all work directly for Somos.
2:11:37
And this is kind of the the insanity of what we're doing.
2:11:41
It's been a bit of a like slow flywheel to get ramping, but then at the end of the day, you're building this actual mode because it turns out it's really hard to build infrastructure from scratch.
2:11:50
So, we literally are cabling the entire city from scratch with a new type of fiber to connect people to faster, cheaper internet. >> Yeah.
2:11:57
What in what ways do you think it's easier to do in a place like Colombia uh than the United States and and and vice versa?
2:12:06
Yeah, I think this is one of the interesting things is like the US is kind of looks archaic in comparison to some of the stuff we're building here.
2:12:12
So like my base plan for customers like 12 bucks a month and is a gig and we're giving people 10 gig connections and soon 100 gig connections in their home.
2:12:20
So the kind of weird thing that has happened in the US is we sort of believe Comcast is sacred.
2:12:24
So we don't let people go build new infrastructure and we're almost there's a world where it's like 10 years from now we're like the US has like third world internet infrastructure and the what we thought of as the third world has infrastructure lets us do all these crazy things that AI is enabling that you couldn't do before.
2:12:41
So I think there's this inversion happening kind of in the same way as there were no landlines in Africa >> that we're we're kind of leapfrogging all the crappy old cable and just building internet as it was intended back in the ARPA days. >> That's amazing.
2:12:53
How how do you get people to move to Colombia to work on this? What's your pitch?
2:12:59
>> Not not saying anything wrong with Colombia.
2:13:01
It's just it's it's a long way away.
2:13:02
It's a it's a long it's a long flight.
2:13:04
The time zone is not too bad, but >> it's 75 degree weather year round.
2:13:08
We have awesome engineering.
2:13:10
It's like San Francisco without the fog and we get to just build whatever the hell you want.
2:13:15
It's kind of like cowboy western technology gulch in the middle of the the jungle. >> That's amazing. Uh last question for me.
2:13:22
Um, I'm sure you got asked this uh in all the VC pitches.
2:13:26
Uh, how's Starlink rolling out?
2:13:28
How's satellite internet fit into this? Is that a competitor? Is that a compliment?
2:13:33
Uh, a lot of people in America sort of have both, but uh how how how does that fit into the picture?
2:13:41
>> I think the big takeaway here is I would sell your Comcast or Telefonic or Telm stock because I think what's happening is Starlink is attacking lower density areas, moving stuff, mobile.
2:13:49
Somos is basically building think of Starlink for city.
2:13:54
So we're building a pure play just the best internet for dens urban environments and >> I think there's like a density threshold where below that Starlink will win above that a thing like will win but the traditional telecoms are kind of screwed.
2:14:08
>> If I'm on level if I'm on the third floor of a 15story building in the heart of the city and like you're going to win on reliability, connectivity, speed, cost, all of that, right? Right.
2:14:18
Just base physics will be cheaper and way better and more reliable.
2:14:21
Like even Elon will say this.
2:14:23
He's like Starlink isn't really for cities.
2:14:24
It's for everywhere outside of that, right? >> Okay. Yeah.
2:14:26
So, so like like basically unaffected by everything there because of physics. Uh always good news.
2:14:32
>> Uh mutual friend Zach asked me to told me I should ask about how kind of AI is impacting bandwidth needs and how that that factors into the opportunity for you guys.
2:14:44
Yeah, I think we're going to look back and say like, damn, the infrastructure we have currently is far underbuilt for the future of applications with AI.
2:14:49
And one of the things that we are thinking a lot about in Somos is what if you extend the data center to everyone's end home, all the crazy application you can build on top of that.
2:14:59
Not only just speed, but reliability, redundancy, low latency.
2:15:01
I think there's a world where compute lives in data centers and we're streaming your OS.
2:15:06
Think of like super Chromebooks to everybody.
2:15:08
And that that's a world where you make compute way cheaper and way better in a way that historically wouldn't really be doable in traditional telecoms.
2:15:15
And I think this is back to like there's a world where LATAM has orders of magnitude better compute than parts of the US just simply because we rebuilt the telecom infrastructure from scratch. >> Wow.
2:15:26
>> Uh what other what other markets are are are on the road map? >> Yeah.
2:15:31
Well, we're heading to Mexico in the very near future and I don't know, there's some interesting neighbors of Colombia that are becoming open again.
2:15:39
That might be a new place to expand to from from Colombia.
2:15:42
So, uh I think SOS Caracus might be a thing in the future.
2:15:46
>> Before we hit the gong, uh uh another mutual friend, Aaron, asked me to ask you about the high frontier.
2:15:51
What's up, what's up with that?
2:15:56
>> Yeah, I mean, I'm obsessed with this vision of the future as it used to be.
2:16:00
And I I think one of the things that's is stoked for me right now is like it feels like we're building awesome things like new ship factories and new infrastructure in the world that are like building a future as it used to be.
2:16:11
Like we used to think the future was going to be awesome and we kind of got okay with a very boring muddling kind of version of it.
2:16:17
And it feels like we're now training this wave of like let's go build orbital space stations and the lrangee points.
2:16:23
Let's build fleets of autonomous vehicles.
2:16:24
Let's build all these amazing things from scratch.
2:16:26
So, it's like build infrastructure, rebuild the world, make awesome things happen again. >> It's fantastic. How much did you raise?
2:16:35
>> We just raised 40 million this round. >> There we go.
2:16:40
>> Who uh who who came in? >> So, Ribbit led this.
2:16:43
We had Bracket Capital and then USV, Kazix, and Y Combinator all kind of doubled down from the past.
2:16:52
So, >> I love a great YC story, too. Uh yeah.
2:16:57
Fascinating company, fascinating industry. Just Yeah, I love it.
2:17:00
>> Did you Did you pop up uh to the West Coast for the raise or did you make uh everybody visit you?
2:17:06
>> Oh, it's a little bit of both.
2:17:06
Like, uh we get people to come down to Medagen and they're definitely not regretting when they come visit.
2:17:13
So, we have some fun adventures driving to the countryside. >> I love it.
2:17:16
Well, thank you so much for taking the time.
2:17:18
>> Great to meet you, Forest.
2:17:18
I'm sure you'll be back on soon. >> Have a great day. >> Cheers, guys. >> Goodbye.
2:17:23
>> Let me tell you about Phantom Cash.
2:17:23
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2:17:28
Uh our next guest is Dino from Seronic.
2:17:30
He's in the rich room waiting room.
2:17:32
Let's bring him in to the TV Ultra. Dino, how you doing? >> Good guys. How you doing? Thanks for having me on.
2:17:38
>> Thanks so much for joining.
2:17:38
Uh >> great to finally have you on.
2:17:41
>> Yeah, give us the state of the union.
2:17:42
What's going on with Seronic? >> Yeah, likewise.
2:17:44
And you may have seen today we announced a $1.
2:17:46
75 billion financing round over. >> Thank you.
2:17:56
>> So, do we need to build some ships? What's going on?
2:17:59
>> We got to build some ships.
2:18:01
>> We're super excited for this.
2:18:01
I mean, it is a true true byproduct of the execution that the team has delivered on over the last not just 12 months, but the last really 36 months since we started the company.
2:18:13
I mean, our team is truly A+.
2:18:15
If you look at where we were just just a year ago, we came off a $600 million financing round.
2:18:21
What that let us go do is we opened our first shipyard.
2:18:25
We launched Marauder, which is a $180 foot autonomous and unmanned ship.
2:18:31
We then announced a multiund million dollar project into that shipyard to scale production of Marauder.
2:18:38
And then Corsera, which you see behind me right here, our small USV platforms.
2:18:43
We've already taken production of those well into the thousands.
2:18:47
So now, as we look forward, what we're going to do over the next 12, 24, 36 months um with this capital raise is we're going to accelerate that.
2:18:54
We're going to accelerate the production, accelerate the deliveries of our vessels to the US and our allies around the world.
2:19:02
We're going to launch new products.
2:19:03
We're going to build new ships. >> Mhm.
2:19:06
>> And then we're going to go and build new shipyards. >> Yeah. Yeah, right.
2:19:08
We're going to invest in the ship building industrial base in this country to the tune of billions of dollars.
2:19:14
We're going to create thousands of jobs.
2:19:16
And ultimately, we're going to we're going to unlock production rates that we haven't seen in this country since World War II.
2:19:22
And we're going to do it in a very technology first, software first approach.
2:19:27
>> Um you you mentioned USV.
2:19:27
Is that unmanned surface vehicle?
2:19:31
>> Unmanned surface vessel. Yes. >> Vessel. Got it.
2:19:33
And then uh so walk me through uh the the use of you know boats used to transport people now we put equipment on them.
2:19:41
How versatile are these vehicles?
2:19:43
What are the different use cases?
2:19:45
Uh are some weapons platforms or some just ISR capabilities?
2:19:48
Like what is the range of of utilities that we that the the armed forces will get out of these USVs? >> Extremely versatile.
2:19:58
The whole the whole point of the platforms we're building is actually for them to be modular by nature, right?
2:20:04
And actually we actually try to change the acronym around a little bit.
2:20:08
USV is like unmanned surface vessel.
2:20:11
You know, when you look in the past, it's really like a remote control platform. Yeah.
2:20:16
>> Um very similar to a predator drone.
2:20:16
We use ASV, autonomous surface vessel, because what we're building at Seronic is not just onetoone control, >> but it's true maritime autonomy to then go and deliver these platforms at scale and be able to control them at scale, meaning fleets of hundreds or thousands of vessels through the most advanced software on the planet for the maritime domain.
2:20:40
And then when you're looking at the missions, the use cases that you mentioned, it really all just boils down to scale, persistence, and risk reduction. Yeah. Right.
2:20:49
How do you operate large numbers of vessels?
2:20:50
How do you do how do you do that continuously in what's becoming an increasingly dangerous maritime environment?
2:20:59
>> And then how do you offer like real capability to commanders while keeping sailors out of harm's way?
2:21:05
keeping people safe is very very critical and a key point to what we're building here.
2:21:11
>> I don't want to diminish the the the work, but I'm curious about how how much of a challenge is it actually to create an autonomous surface vessel because it feels like uh when you're driving on the road, there's so many random conditions and the car can flip over.
2:21:26
But boats, it's a little bit safer, I would feel like.
2:21:31
But am I miss am I missing something there? Like what does it take?
2:21:34
issue is you have people other boats that are trying to kill you. >> Okay. Okay.
2:21:37
Maybe that's but I'm just thinking like a plane, you know, if it doesn't land perfectly, it'll crash.
2:21:43
Like boats, you know, they just kind of rock through the water, but there's obviously more to it.
2:21:46
So, what went into making it uh fully autonomous?
2:21:49
>> There's a lot of Yeah.
2:21:49
So, the ocean's just a completely different environment all together.
2:21:53
So, we deal with a lot of a lot of different challenges. Sure.
2:21:55
One of the challenges that that's really different from self-driving cars is yes, there's a lot of complexities on the road, but that singular car really only cares about how it gets to its end destination.
2:22:08
It doesn't care about how the other hundred cars get to its end destination as well and how they're all working together collaboratively on a mission.
2:22:18
Oh, and then you start throwing in 6, 8, 10 foot seas, high winds, enemy environment, some of the things that we're seeing now.
2:22:26
And like >> whether it's the Black Sea, the Middle East, we're anticipating in the Indoacific, like those are very very complex challenges that that we're solving at Seronic. >> Yeah.
2:22:38
>> Uh what what goes into setting up a new shipyard?
2:22:41
Do you have to kind of colllocate around existing shipyards?
2:22:46
Can you kind of stand something up, you know, totally independently?
2:22:48
How does that how does that work?
2:22:52
>> Yeah, I mean, when you look at shipyards and the ship building industrial base in this country, it's really how do you bring on net new capacity?
2:22:58
You're not really coll-locating next to anything because a lot of that capacity has really atrophied over the last 30, 40, 50 years.
2:23:06
So what we're focused on is is building new shipyards and then building the ecosystem and the infrastructure to support that as well through partnerships and vendor relationships.
2:23:17
But one of our one of our main projects and one of the thing a large part of this capital is going to go towards is Port Alpha, right?
2:23:23
We have a shipyard in Franklin, Louisiana.
2:23:25
mentioned that we're investing hundreds of millions of dollars in that yard, but we're looking at a brand new shipyard, building this from the ground up, completely green field, investing billions of dollars to 10x the size of our existing yard, right?
2:23:42
To bring on new scale, new capacity, and build rebuild the ship ship building industrial base from the ground up.
2:23:49
That's what's needed because if you go around the country right now, you go to places which used to be shipyards and you'll see apartments and condominiums that are called naval yards.
2:23:59
That's not just a name they came up with.
2:24:01
It actually used to be a shipyard.
2:24:03
So, what we're doing now is we're investing in the shipyards of the future again to produce at a scale that we haven't seen since World War II.
2:24:12
>> What's the best way to get a job at Seronic?
2:24:15
>> You can apply on our website. I mean, we are hiring. We are growing.
2:24:17
I I mentioned how amazing our team is.
2:24:19
What we're doing is absolutely critical for the country.
2:24:24
The team comes in every single day.
2:24:26
The work they're doing is changing the world.
2:24:28
And so if you're a top engineer or looking to get into the defense tech space, please please apply.
2:24:36
Um everything we're doing is absolutely critical.
2:24:38
We grew the team from 200 to,300 people over the last 12 months.
2:24:44
>> And that's that's only the beginning guys. >> That's amazing.
2:24:46
Well, thank you so much for coming and breaking it down.
2:24:48
Have a great >> progress.
2:24:50
The chat the chat says just put the S1 in the in the SEC mailbox.
2:24:57
>> We'll talk to you soon. >> Good to see you.
2:24:59
Looking forward to following up.
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2:25:10
And our next guest is already in the reream waiting room.
2:25:15
We got Will Ahmed from Whoop Whoop. He's back. How you doing? Good to see you again. Welcome back.
2:25:20
>> Hey guys, thanks for having me. >> Give us the update. What happened? How you doing? >> Things are good. Thank you.
2:25:25
We uh we announced a round of financing today.
2:25:29
Our series G $575 million round. So, thank >> Yes. There we go. Thank you.
2:25:39
>> Is this Is this the capital you finally need to make a bust down whoop?
2:25:44
Diamonds from the factory.
2:25:44
That's what I'm looking for. >> Can you do anything?
2:25:48
>> You know, we do we do have some we have some premium offerings in the mix that are going to be just right for you.
2:25:53
Actually, >> very happy with the product development roadap.
2:25:57
>> Jordy wants a bus done. No, no.
2:25:57
Uh seriously, give me give me updates. What uh what's changed?
2:26:02
Uh where do you want the product to go?
2:26:05
And yeah, I am interested to know uh are more collaborations in the works?
2:26:09
Do you see that as an important point or are you just focused on uh more and more channel partners, more and more distribution, more growing because the product's pretty dialed at this point?
2:26:21
>> Well, look, it's been an extraordinary uh 12 months for the business.
2:26:23
You know, we we ended 2025 with over 100% year-over-year growth. You know, 1.
2:26:29
1 billion in bookings run rate to end the year.
2:26:34
Our membership is growing around the world.
2:26:37
Um we're operating in 60 markets.
2:26:39
We've got Whoop members in over 200 countries.
2:26:41
We've launched medical grade technology now.
2:26:44
We're coming out with blood tests uh around the world.
2:26:49
And so Whoop's really become this broad-based health platform.
2:26:51
And uh and you can see that in the financing announcement today.
2:26:55
You know, we've got the history of Whoop with the worldass athletes.
2:26:59
We've added now uh LeBron James is a new Whoop investor.
2:27:02
We've got Cristiano Ronaldo on the cap table.
2:27:05
uh Virgil Van Djk, um Matthew Vanderpole, some of the world's very best athletes really from every sport uh are now on the Whoop Cap table.
2:27:17
And then uh in addition to that, we've got a bunch of uh great existing investors continuing to support the company, Collaborative Fund, IVP, Foundry Group, and and more.
2:27:29
Uh and then we've brought in some sovereign wealth funds uh from uh the GCC.
2:27:34
proud to have Mubata and QIA and uh 2. 0.
2:27:38
So really some of the biggest funds in the world that are are I think phenomenal long-term partners. >> Yeah.
2:27:44
>> And then lastly to the point about health, you know, we've added uh the Mayo Clinic is an investor in Whoop, one of the premier health institutions.
2:27:54
>> That's a that's a niche.
2:27:54
That's a hard rare Pokemon in the venture world.
2:27:56
I haven't seen I haven't heard of them on >> ripping a lot of seed checks at YC Demo Day.
2:28:02
Yeah, they haven't they haven't done a lot of investing, but uh we've see a ton of synergies from a research and medical capability standpoint.
2:28:08
Uh and then we also have added Abbott as an investor and you know really one of the best medical device makers also in the world.
2:28:18
So it's a it's a phenomenal mix of investors and I think we've been able to achieve this because of uh of the remarkable growth that we're seeing as a company and I think also just the the tailwinds around health and longevity.
2:28:31
How do you think your marketing mix will change over the next few years?
2:28:33
Because I'm I'm seeing $575 million, LeBron James, Cristiano Ronaldo that has like crazy Super Bowl ad written all over it.
2:28:44
At the same time, you're tech native.
2:28:44
I could imagine going way further into AI generated personalized ads, pushing the performance marketing further.
2:28:53
Like, what appeals to you?
2:28:55
How do you think you'll change?
2:28:56
What will what will stay the same?
2:28:58
What will change over the next few years from a marketing perspective?
2:29:02
>> Well, we never want to lose sight of the fact that we started in sports and we've built this aspirational performance lifestyle brand.
2:29:08
And so that'll really be at the core still of of a lot of what we do for Whoop, but we also now have a product that, you know, can detect whether you have AIB and tell you your blood pressure every morning and help you do blood tests.
2:29:20
So, it's it's just a much broader health platform than it's ever been before.
2:29:25
and our marketing needs to reflect that.
2:29:27
You know, one of the areas I would say of maybe not weakness but opportunity for Whoop is uh is brand awareness.
2:29:33
You know, we don't have massive brand awareness around the world.
2:29:37
And so this capital is going to give us the gunpowder to really grow uh broadly internationally and so uh you're going to be seeing a lot of whoop uh wherever you consume content.
2:29:51
>> Super Bowl ad incoming. >> Yeah.
2:29:52
If you I mean if you want to reach me specifically maybe a partnership with like an athlete like Johnny Knoxville might work.
2:30:00
>> It it it just might make sense.
2:30:03
>> We'll do a Whoop live heart rate on some of the stunts. >> Stunts.
2:30:06
I think that would do the trick.
2:30:08
>> That would do the trick.
2:30:10
>> Uh I'm curious like how >> uh Whoop uh like how do you guys think about improving accuracy at this point?
2:30:19
Like I'm assuming like a lot like so so much progress has been made over the last however many years but there's still always incremental progress like you can always be more accurate.
2:30:28
H how do you think how do you think about how do you think about that?
2:30:33
Is that is that still like a top priority or are there other is it accurate enough at this point that uh that there's better there's better things you can focus you know the the core energy of the team on.
2:30:48
I mean, I think big picture, we want the product to be getting constantly smaller and smarter.
2:30:52
You know, we want it to be an aspirational product in the sense that it's something cool that you wear on your wrist or we want it to be something that disappears throughout your body and can essentially be invisible.
2:31:02
And so, however you can gather this data super accurately, have the data sets grow in nature, more sensing, more capabilities, more medical approvals, um, the better.
2:31:14
And I think that's going to continue to expand our TAM.
2:31:16
I think it's going to continue to deliver deeper insights for our members.
2:31:20
So, we're going to be leaning in pretty heavily on research and development.
2:31:24
You're going to see a lot of very powerful sensing coming from Whoop in the years to come.
2:31:31
>> How is the peptide boom affecting Whoop?
2:31:36
Well, I think the underlying reason for the peptide boom is that people want to take more control of their own health and they're sort of generally frustrated with the tools that they've had uh to improve their health.
2:31:51
And so that leads in different directions.
2:31:52
Peptides being part of it, supplements being part of it, uh concierge doctors being part of it, uh AI health coaching being part of it.
2:31:59
Uh but broadly speaking, it's it's I think good for Whoop that people want to take more control of their health.
2:32:07
And 10 years ago, I would talk about health monitoring and people would say, "Well, that sounds like something niche for athletes."
2:32:14
And now, you know, everywhere I go, people want to talk about how they can improve their sleep or improve their V2 max or what is heart rate variability.
2:32:22
So there's just clearly been a cultural shift to care a lot about your health.
2:32:27
And you know, longevity has become one of the most common reasons that people use the product.
2:32:33
Our health span score, the Whoop age score, has become the most screenshotted page in the Whoop app. Yeah.
2:32:39
>> So clearly you've got people who want to show off uh how old they are or, you know, who want uh some counseling for how how um how old they might be. >> Yeah.
2:32:49
Yeah, that makes a lot of sense.
2:32:50
Yeah, there's an interesting dynamic with the various health platforms where there's like kind of an incent there's like a weird incentive to like you know measure like say somebody's uh uh you know their chronological age versus their biological age make it like lower so people are more likely to share.
2:33:06
It's like I've seen I've seen some people have you know come in and say like well my biological age is 19.
2:33:14
>> I I I did one test that said I had I had the mind of a five-year-old.
2:33:19
It said it was testing my brain health and it said that I had the >> Is that good or bad? >> It's not. >> It's extremely young. I'm way over five. So I assume it's good.
2:33:27
Look, I think we've built the most credible uh biological age metric because we did first of all, we did it in partnership >> um with the leading longevity institute uh out of uh California and then uh the Buck Institute and then >> uh we show you in great granularity each of your biometrics and what's improving it and what's not and by how much.
2:33:51
>> So here's a trivia question for you.
2:33:53
What percentage of people on Whoop do you think have a younger Whoop age? >> Oh, interesting.
2:33:58
I I mean, if it was perfect, I think it would be 50/50, I would think.
2:34:03
>> 70% because people that use Whoop are much more likely to be >> Oh, true.
2:34:06
Okay, so let's go with 70. What is it? >> It's 55%.
2:34:11
>> What that means is 45% are older on Whoops.
2:34:16
>> You know, they're early in the >> You guys have done a lot, but this whole show is really dialed in. Uh, no.
2:34:20
So, so 45% are uh, >> you know, 45%. >> Yes.
2:34:31
>> So, you know, but that shows that like it's not just telling you what you want to hear.
2:34:35
It's, you know, it's going to push you. >> Yeah. >> Yeah. Yeah.
2:34:38
And I and I only I only brought that up originally because I I've seen some of these come out and I'm like, okay, there's zero shot this person's biological age is lower than their chronological age.
2:34:47
uh and based on not not every platform, you know, platforms are just kind of every platform is going to run their own kind of algorithm to determine that and not necessarily working with the Buck Institute. >> Yeah, exactly.
2:35:00
>> Um >> well, >> very cool to get the update.
2:35:02
Congrats to the whole congrats to the whole team.
2:35:04
I feel like just in the last year, this like the world has woken up to this >> kind of category and your guys's progress is a testament and I still think it's I still think it's very early.
2:35:17
It must be fun to walk down the street for you and, >> you know, some place like LA because everywhere and, you know, I'm sure it's like every 10th person has a Whoop band on, but that means uh there's nine nine or so.
2:35:30
>> Uh, >> yeah, it is it is a trip seeing seeing Whoop in the world.
2:35:32
And, you know, for people who decide to take the hard path of building hardware, it's an amazingly rewarding feeling when you see a physical product that your team's built in the world.
2:35:43
So, I will say that's a that's a very gratifying thing.
2:35:45
But you guys, you guys owe me a question here. You haven't asked me. >> What is it? What's the question?
2:35:51
>> Aren't you going to ask me if the job's done? >> Oh, yeah. Is the job finished? >> Job's not done, guys. We got to keep going. >> Thank you. Thank you for that. >> Great stuff. >> Thanks.
2:36:07
>> I appreciate you guys. Keep it up. Thank you.
2:36:09
>> We'll see you at soon, I'm sure. >> Yeah. Get get ready.
2:36:11
The chat's going to be your strongest supporters.
2:36:14
Thank you so much for taking the time to come chat with us.
2:36:18
We'll talk to you soon, Will. >> Have a great one. Goodbye.
2:36:21
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Don't just build AI, own the data platform that powers it.
2:36:30
Continuing our lightning round, >> you know who we got? The CEO of public. com, Yanick. How you doing?
2:36:39
>> Hey guys, I'm doing well. How are you? We're doing fantastic.
2:36:41
Look at that stuff in the background there. >> I know.
2:36:44
Do you recognize any of this stuff? >> Oh, yeah. Yeah.
2:36:46
You got the whole head to toe. Head to toe.
2:36:49
>> I don't recognize what Jord is wearing.
2:36:51
I don't think you got to get one. This is the new polo. You're right there. Top left. You got lean left.
2:36:59
>> Plenty of room on the wall.
2:36:59
There's plenty of room on the wall.
2:37:01
>> Anyway, uh enough about our merch.
2:37:01
Let's talk about your business.
2:37:04
Uh walk us through the launch today. Yeah.
2:37:06
So, today we launched AI agents for investing. >> Yes.
2:37:11
>> The easiest, safest way to put AI agents to work directly inside your portfolio. >> Yeah.
2:37:17
>> Um, and the way it works is pretty simple.
2:37:18
There's now an agents tab directly within the public app.
2:37:20
You chat with an AI to set up agents that monitor markets, move money around, and even execute trades for you all within the app, right?
2:37:30
So, there's nothing to install from a security standpoint.
2:37:33
Obviously, everything stays in a safe controlled environment because it's within the brokerage. all Axios. >> No, do not do that.
2:37:40
That is such a niche joke.
2:37:42
Everyone's going to think you're talking about the publication.
2:37:47
>> Um, no, but I mean it's it's been really fun.
2:37:49
I have a bunch of agents running now on my account.
2:37:50
It's been really awesome to see how it's changed my behavior as an investor, right? So, >> John, relax.
2:37:58
>> I like the sound of that.
2:37:59
>> I knew you were going to do that.
2:38:01
>> We got a little John and No.
2:38:01
So, so, so, uh, make makes total sense.
2:38:04
What like if people are like uh already signed up, which they should be, how what what should they what what what's the first thing that that they should try to like set up or experiment with?
2:38:15
Like what what was your first few agents that you've set up and and like continue to keep running because I'm assuming you can effectively like run them, you can retire them at different points. >> Exactly. Exactly.
2:38:26
The first one I set up was um one that checks the oil prices before the market open and buys protective put options every day as a hedge. >> Sure.
2:38:36
>> If there's a spike in those, I call it the >> I'm tired of seeing red due to war agent.
2:38:40
Um and so, uh today that didn't fire, thank God.
2:38:44
Um >> you know, I have another one that just looks at my bank accounts and automatically sweeps any cash in excess of a certain amount into my bond portfolio.
2:38:53
So, I'm always yield maxing.
2:38:55
You want to be yield maxing always, especially while rates are still high.
2:38:58
>> Yeah, that makes sense.
2:38:59
>> Um and uh and then I got some more advanced stuff like I got one that scans the markets for opportunities to write covered calls. >> Okay.
2:39:06
>> Across my top position.
2:39:06
So if there's a lowrisk opportunity to make like 20 grand a month. >> Yeah.
2:39:12
>> Um selling options premiums.
2:39:12
I instructed it to just go ahead and place those orders.
2:39:16
So that just rolls >> every time. All the time.
2:39:18
And I don't have to think about >> that.
2:39:21
strategy was the first thing a uh a private wealth manager ever pitched me in my career like a decade ago.
2:39:25
They were like I and they had like a guy that did it and you had to have a lot of money to like access that and there were minimums and stuff and now check on that guy after no but uh so so I I there are obviously like incredibly advanced things that you can do with these agents in in the market.
2:39:43
I'm also interested in just driving behavior change because a lot of folks that I know are earlier in their career.
2:39:50
They don't want to necessarily take a ton of risk.
2:39:52
The biggest lever on their financial future will just be seamlessly funneling money from their paychecks into something as simple as VTI and then they can do something more more advanced down the road.
2:40:02
But what does it look like in terms of uh the best practices or best functionality for just creating a set it and forget it.
2:40:11
I want to make sure that every time I get paid, money's flowing into the market.
2:40:18
How easy is that these days?
2:40:20
Um well I think with agents that becomes really really simple right I think this is sort of the whole point you know the stock market has always been about manually entering orders right like you do all this work and eventually you end up manually being like buy 200 shares of Apple at this price >> I think that user interface is now shifting to something like >> um increase my position if valuations compress 15% from here
2:40:44
>> you know and it stays within my defined risk tolerances and so forth and so I think it changes is how people think about and manage their portfolios um in a pretty profound way and and we do see it as a user interface shift like you know the the the interesting thing about this industry is every technology kind of had their model of brokerage right like we started on the horn >> and then the dawn of the internet gave
2:41:06
us the discount broker with mobile came the neo broker >> and I think now with AI it's the era of the aenic brokerage but >> what's uniquely interesting about this shift is every previous shift was about streamlining the process and reducing the responsibility set of the broker you know to basically just trade execution ultimately >> but it actually used to be much more full service to Jord's point there used
2:41:28
to be a guy used to call you used to pitch all these kind of ideas risk you know trade ideas etc >> I think with the identical brokerage model you're reversing back to that >> um and it's much more full service than obviously any human service could ever be because this thing can like write an algorithmic trading script for you in 10 seconds it can do tax harvest it can instantly analyze risk. >> Sure. >> Sure.
2:41:49
>> And so it's it's a shift back to a world where the brokerage plays a much a much larger role than just trade execution.
2:41:57
It sort of goes into the realm of maybe a quant and a financial advisor and that's what we're excited about the brokerage playing at a much bigger role through essentially a >> uh Jordy >> uh can it can can it pull in external data sources yet?
2:42:11
I'm thinking like fear and greed index like should I could I said something unemployment if you have like max fear that you you want to buy on days when when the the >> yeah fear index is high but that might not be an an actual uh like instrument in that you can buy and sell directly. >> Yep. 100%.
2:42:30
unemployment data, CPI, Fed cuts, like one that people have been kicking around today is, >> you know, whenever there's a Fed cut, >> move money obviously out of my high yield cash account public, put it to work into high growth tech. Yep.
2:42:43
>> We like the sound of that. Am I right? >> That makes sense.
2:42:45
>> Um, and so >> and u and so there's a lot of those. >> Yeah.
2:42:51
>> CPI like like the fear and greed one uh was requested today.
2:42:54
I think that's coming in in the next couple of days.
2:42:57
And so really it's about getting all that into this natural language interface and just letting people kind of instruct AI to um to do this on their behalf.
2:43:06
>> Last question for me about uh AI on the platform.
2:43:09
What have you what are the capabilities?
2:43:11
What have you learned about users educating themselves about various financial instruments within the public ecosystem?
2:43:19
uh you know, okay, I see a company.
2:43:22
You're going to surface price to earnings ratio, market cap, the usual stuff, but there's so much more that you can ask an LLM these days about what does a company actually do? What is their strategy?
2:43:32
How what's the history of this company?
2:43:34
Do I what's the founder like?
2:43:36
These things are are perfect for LLMs and you can vend those in, but what are users actually using?
2:43:41
What's adoption been like?
2:43:43
What have the learnings been? Yeah.
2:43:46
I mean I I think one of the core task in application lay AI is to sort of figure out obviously what do users want to achieve. >> Yeah.
2:43:54
>> And then which model and kind of harness is best suited to achieve that purpose. >> Sure.
2:43:58
>> But then also focus on like >> what are we uniquely able to deliver. Right. So we know what you own.
2:44:03
We know what you used to own. >> Yeah.
2:44:07
>> We know what your risk tolerance is.
2:44:07
By the way, we also know the difference between what that actually is and what you said it was when it signed when you signed up. >> Yeah.
2:44:14
um and and and we have real time data feeds of everything, right?
2:44:16
And so I think as a product builder, those are >> like some of the situations where you can really create a magic moment that general purpose LLMs can't.
2:44:24
And I think a lot of that comes because we just have a lot of that kind of history about how people like to invest, what questions they've asked to your point in the past about the PE ratio, what the founders like, etc.
2:44:38
Because we've been basically running a research assistant since 2023. >> Yeah.
2:44:42
and we're only a six-y old company, so it's already for sort of like half the time that we've been live.
2:44:49
Um, and so we've been able to gather a lot of data for the last three years that we can now kind of repurpose into this.
2:44:56
>> What's your theory right now?
2:44:56
It's obviously day day one, but do you think in the future we'll get, you know, more volatility because you have like financial institutions that are effectively using like agents or algorithms to do trading and then you also have retail.
2:45:11
So when you get like a new CPI print, you know, you have, you know, even even, you know, additional trading activity off of these single events.
2:45:20
Like do you think this is something in the future that that everyone will effectively have like a handful of agents running just naturally in the product and then some people will you know be like you know maybe proumers people that are more into it will have you know many or or at some point is everyone you know at what point do is it like you know old-fashioned to be just like you know buying a stock yourself even with a button. >> Totally.
2:45:45
>> Totally. I actually think we will look back at like tables and buy buttons and feel that's a little antique maybe already uh 12 months from now but I think the effect is things will get priced in faster for sure on the institutional side they've you know they've used some version of AI for the
2:46:02
longest time right but then at the same time retail have gone from being like 5 to 25% of the market and on the retail side folks haven't been as fast to react always right they haven't been that disciplined they're not necessarily glued to the screen 24/7 and so you know
2:46:17
they can't always react as quickly as they want to and agents obviously change that right and so I do think that there might be I mean it's a little bit like whether it's crypto prediction markets there's always a little bit more of a of sort of an alpha opportunity or an AR opportunity in the early early days
2:46:35
>> um and then over time it becomes more mainstream and that kind of fades away and I would suspect that this follows something >> like a similar pattern at least I've just been thinking about it because because a content on X is primarily user generated at least the big accounts. It
2:46:48
It means that an event happens in the real world.
2:46:52
It gets reported on or it pops up on a website or you get a newswire and then a human takes that and puts it on X and then this trade even the majority of retail volume is like flowing off of like that human seeing the news posting it and then you get this sort of trading activity.
2:47:09
Think of it in a perfect world, you see news and then you go to your broker and the the the the right trade has already been made on your behalf.
2:47:18
>> Um and anybody that's not adopting this will just be like well I I missed kind of I missed the opportunity unless you want to get out entirely. >> Totally.
2:47:26
Speaking of ex a fun one is uh that was if DJT says buy just buy.
2:47:36
>> That's actually that's actually really smart.
2:47:40
probably back test very well.
2:47:42
>> It back test extremely well.
2:47:44
>> What a crazy timeline we are in.
2:47:44
Well, thank you so much for coming on and breaking it down for us.
2:47:50
Let's let's be sure to hang out. >> Let's hang soon. >> All right, you guys. Cheers. >> See you.
2:47:57
>> Let me tell you about Sentry.
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2:48:04
And without further ado, we have Ryan from Crosby. How you doing, Ryan? >> Welcome back.
2:48:12
>> Hey guys, good to see you again.
2:48:13
>> Dude, you're on you're on here like every week.
2:48:15
>> It's getting ridiculous.
2:48:17
>> Yeah, it's getting a bit much. Let me guess. Another one.
2:48:18
You should just bundle all the fundraisers together into like uh series alphabet.
2:48:23
Then we just do >> I never get to see you guys in the >> It is.
2:48:28
It is more strategic to break them up.
2:48:30
But tell us what happened. How much did you raise? What's going on?
2:48:33
>> We have two announcements.
2:48:33
The first announcement is we've raised $60 million led by Lux series B.
2:48:41
>> And our second announcement, >> thank you.
2:48:43
The second announcement is we did some math last month and we have now closed contracts worth over a billion dollars for our clients.
2:48:50
>> It's a big milestone for us. >> Okay.
2:48:52
Million dollar for the client. That's good.
2:48:55
>> Was there a power in there?
2:48:55
Was there like one sneaky $950 million?
2:49:00
>> Did you get 1% of this new Open AI round in there?
2:49:02
Somebody was like, "I'm going to review one clause."
2:49:03
And you're like, "I'm going to No, it sounds like it sounds like there's a lot of lawyers using it." >> That's right.
2:49:09
I mean, these are small deals, so it's a lot of velocity.
2:49:11
I think definitely my corporate law friends are like, "That's like one deal for me, so that's not interesting, but for us, that's a big number." That makes sense.
2:49:17
So, it's a really good milestone. >> Yeah. So, yeah. Yeah.
2:49:19
T take us through I mean, it sounds uh like like the the shape of the work that is being augmented by Crosby these days. >> Yeah.
2:49:29
So, you know, we're about a year and a half into it.
2:49:31
We announced our seed um around 230 days ago.
2:49:32
We do commercial agreements.
2:49:36
These are the sale of agreements, MSAs, NDAs, um BPAs for like fast growing AI companies.
2:49:41
Now we're branching out, but since the beginning, we've been a law firm.
2:49:45
So we have about 30 lawyers here who I'll give a shout out to are just the last day of the quarter.
2:49:51
They're working so hard for our clients getting the deals closed and we close deals fast, like in a couple hours.
2:49:57
And so this idea has just taken off with a lot of tech companies now and and now even bigger clients who just want to close faster.
2:50:04
>> Uh how how have you been processing you're kind of uh I would say very tapped into how well the models work in different roles.
2:50:13
I'm curious your view on >> uh how application layer legal AI companies will do uh compared to just the labs themselves, right?
2:50:24
the labs themselves, right? I feel like every other day on X somebody says wait >> this LLM >> seems to be doing just as much as you know this application layer company you guys are using all the models internally for your own internal tools but like how
2:50:42
how are you processing kind of what feels like well ultimate in the same way we saw with codegen where you have application layer companies and foundation model companies and then you have foundation models with their own applications I'm assuming we'll see that in legal but uh how have you been kind of processing it? >> So I mean that's that is the question we
2:51:01
>> So I mean that's that is the question we have to ask ourselves every day.
2:51:05
We think that uh code generation more or less is kind of like a year and a half ahead of the sort of non-selfverifiable domains.
2:51:12
So anything that's not like math or code and law is one of those but it's a huge service area and our sort of like insight a couple years ago was let's you know not think about these sort of like AI co-pilots that are kind of like you know the equivalent of what cursor was a year and a half ago when you kind of hit tab to autocomplete but these long form agents with bigger context that could do a full job end to end.
2:51:32
And if you have agents that can do entire swads of legal work, then the best thing you should do is start a law firm because you're selling work to clients, not, you know, fractions of work or kind of helping them along.
2:51:41
And in truth, we were ahead of the models.
2:51:44
And so we were selling something that like we weren't able to fully automate.
2:51:48
And as the models are progressing, we're seeing more and more of a compounding advantage as, you know, we have more and more contracts that we're processing.
2:51:53
We have more and more lawyers that were able to help us, you know, tune judges and and, you know, like create better agents.
2:52:00
And so we're able to just do endto-end work in a way that like if you're just selling a legal, you know, co-pilot, I think you're going to face a lot of competition just from the models with no customization. >> Yeah. >> Sorry. >> Wild John's back.
2:52:13
Uh yeah, wild wild moment.
2:52:17
moment. Um what I'm assuming you'll also face competition from clients that are just like hey we can should should we should we have an in like uh should we have an in-house uh lawyer that we can you know speed up uh but but everybody's competing with everyone but uh yeah
2:52:34
>> how are you how are you tracking the legal education market uh I've seen it I it it seems very hard to predict for me like there was this weird spike I want to say like it was maybe post chatbt where there were like more people signing up for a law school and that was like sort of contrarian based on the
2:52:51
model capabilities like the AISF discourse but maybe it makes more sense like are you tracking that data and then are you tracking like how legal education is changing uh I imagine that uh using AI tools already happening in middle school for a lot of people high school definitely college definitely law
2:53:12
school uh how will that how will that all trace through and how closely are you following I mean, I think every industry is asking themselves like how do people get the entry- level jobs to learn those skills so they become really good and senior and get leveraged by agents. Um, I I
2:53:23
Um, I I went to law school at Stanford.
2:53:26
I'm talking to a lot of professors there who are struggling with this question.
2:53:28
I think our insight for now, like the stat we found recently is that the top 100 law firms last year made a little under $70 billion in just profit just in 2025.
2:53:39
That's just paid out to their partners. That's just salary.
2:53:40
That's just salary. and bigger than >> says there's not enough >> good year >> that's so good >> and that was that was more money than Google spent on all their R&D and so like our insight was >> which is great so like if we could just put some fraction of the profits law
2:53:57
firms are making into building better tools and experiences for lawyers and for their clients I actually think the legal industry gets a lot bigger and so it's like for a a person in law school today >> it's a good time to be thinking like how can I just build better stuff and that's just a new way of lawyers is thinking. >> Okay, that's one way to put the profits
2:54:12
>> Okay, that's one way to put the profits to work.
2:54:14
Uh, let me pitch you another way.
2:54:16
If I'm a partner at a law firm >> and I see that yes, agents can do the work of the the associates that I would be hiring. Yeah.
2:54:25
be hiring. Yeah. Uh maybe I you know uh contrarian in me wants to still hire associates just for the mentorship and uh and building like the pipeline of partners that will do more human work, more deals work, more interpersonal relationship work, but I know that if I
2:54:43
don't start buying and paying for that service right now, even if I'm getting less margin on it loosely because I'm paying an associate a bunch of money and it's work that an AI agent like sort of could do and Maybe they're a little bit more free. I I I'm actually incentivized
2:54:56
I I I'm actually incentivized to figure out how to accelerate them faster in their career.
2:55:00
Have them start working on larger, stickier deals that AI can't necessarily navigate just yet. >> Yeah.
2:55:08
I mean, I I I buy the argument.
2:55:10
Like, I think that there's two jobs for lawyers really to focus on right now.
2:55:14
One is just doing client-f facing work and being really good at >> being like, you know, be talking to people and understanding what their points of view are and not being buried in the sort of paperwork like a typical associate.
2:55:23
And the other is being able to explain reasonably well to an engineer or a researcher what it is you're doing and what you're thinking about and all the subtleties of context. >> Yeah.
2:55:31
>> And those two things I think are both things that if you're not hiring enough lawyers, you can't do well and you can't build better legal technology and experiences.
2:55:37
And so I think we're feeling this and every law firm is feeling like you just need people to be really thoughtful about doing both those jobs. >> Yeah. Yeah.
2:55:43
Are you guys fine-tuning any models, you know, based on fine-tuning like open source models, or is that not even, you know, I've seen like Finn and and Notion have had some success with this.
2:55:56
>> Is that even a good use of time right now?
2:55:59
Because I'm assuming your guys' like actual like inference costs are not that high relative to what you can charge clients even if you're using the frontier models.
2:56:08
But >> how are you thinking about that?
2:56:12
I think again if we just look at code generation as like the blueprint for the future you'll see like a lot of the codegen companies got a lot of lift from just like you know the main you know three big models >> and over time you have to start fine-tuning your models as you get scale as you get data and as you need a more
2:56:27
competitive edge so we're not there yet we have a lot of lift from just getting the right context to models building the right agent flows like um just doing some reinforcement learning on like basically you know we work with really you know open athropic and Google's models but yeah in a year and a as you get really specialized in use cases of law. I I I'm sure like we're going that
2:56:43
I I I'm sure like we're going that direction and part of the reason for this funding and doing it so quickly is to start investing in a research team that can can kind of push the boundaries there. >> That's very exciting.
2:56:54
Well, congratulations on the funding round. I'm sure we'll see you. We'll just book it now.
2:56:58
You just tell us and and uh >> same time next month. Thanks.
2:57:02
>> Uh we'll talk to you soon. Have a great day. >> Thanks, guys.
2:57:05
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2:57:15
And without further ado, we have Chris Yu from also.
2:57:20
>> How are you doing, Chris? >> For taking the time.
2:57:23
>> Yeah, thanks for having me. >> Welcome to the show.
2:57:24
Uh, since this is your first time, please introduce yourself.
2:57:29
>> Yeah, my name is Chris Euan.
2:57:29
I'm the uh co-founder and president of Also.
2:57:33
>> Okay, break it down for us. What is also?
2:57:35
give us some of the corporate lineage, the strategy, the product, it just sort of everything. >> Yeah.
2:57:41
So, um, actually before 2022, R. J.
2:57:44
and I met and we immediately hit it off on this one topic.
2:57:46
And so, that turned into me joining Rivian at the time >> with the explicit mission to create a startup within a startup.
2:57:52
startup within a startup. an entire thesis that we had and that's this has turned into also with the spin out last year is that >> you know if you look at the vast majority of trips that happen for the movement of people and goods around the world they happen in smaller than car
2:58:05
things but nearly none of them have been electrified yet and so it's really taken the Rivian or Tesla playbook and applying it to these smaller form factors >> okay uh smaller form factors that means everything from hoverboard to a horse and carriage what are we thinking >> we're focusing on wheels but yeah Okay. Uh but yeah. Yeah. What uh narrow down Uh but yeah. Yeah.
2:58:24
What uh narrow down the product for me, the the go to market uh the uh the the the quad and the pedal assisted electric bike.
2:58:33
Uh are there timelines, shapes, sizes, ranges?
2:58:35
Like how do you think about narrowing down the product set because it is a really wide and diverse category? >> Totally. Yeah.
2:58:46
So we think of it as uh in a way two phases of the business.
2:58:48
Um phase one of the business is how do we create a vertically integrated softwaredefined EV platform >> but optimized for small form factors and we've applied that to our first products.
2:59:00
We call them uh EVs that you can pedal >> and we announced those back in October.
2:59:04
So one is a consumer ebike and the other is a pedal quad which we partnered with Amazon um to deploy soon.
2:59:10
>> That's really exciting.
2:59:10
Um but if you look globally again today things move around in things like uh two wheelers like scooters, boa boas, tuk tucks, micro cars, K trucks.
2:59:19
There's just these rich diverse set of form factors and again none of them have been electrified and all of them are ripe for um a really kind of tech forward platform which is what we're building.
2:59:32
>> Um but importantly today we announced a partnership with Door Dash and that kind of underpins phase two of the business which is >> Thank you.
2:59:39
>> Thank you. Um yeah so if you look at the world becoming more and more autonomous and even as that happens um some fundamental constraints don't change meaning these trips are all happening in dense urban suburban environments congestion is always going to be an
2:59:52
issue cost per mile is always going to be a factor >> and so we believe really strongly that even in a fully autonomous autonomous world um small form factors make sense uh for a lot of these trips and that's really what this um partnership is about. talk to me about uh I mean I I
3:00:06
talk to me about uh I mean I I love R. J.
3:00:10
Rivian is an incredible company.
3:00:12
Uh obviously a a younger company in many ways than other EV makers that might be more vertically integrated.
3:00:18
So, I'm I'm wondering like how much is it that you're taking the supply chain knowledge, the expertise, the best practices, the connections and setting up sort of an entirely new supply chain that's distinct versus you're just going to be able to buy stuff from Rivian or license it or there's going to be more of a business relationship other than just funding.
3:00:39
>> It's all of the above.
3:00:39
We RJ and I talk about us as kind of like sibling companies, if you will.
3:00:44
>> Um, so I think uh I mean there's a few aspects.
3:00:46
one is uh we share the latest and greatest from a technical architecture standpoint.
3:00:50
So if you look at how also vehicles are built um they're very very similar um in terms of how a Rivian is built.
3:00:58
>> There are some commodities that um are shared.
3:01:00
So battery cells we our first products actually use the same cell that are in Rivian R1 and that helps a lot from a scale >> I'm sure >> standpoint but there are other areas where we are taking a decidedly different path um because our products are different from a car truck or SUV.
3:01:15
So supply chain that you mentioned, that's actually one of them.
3:01:17
Um, we are fully engineered inhouse, but we partner with contract manufacturers across the world to be able to do assembly and that that's right for smaller scale products. >> Yeah.
3:01:27
And with cars, you almost always want to manufacture them where they're going.
3:01:31
Like that's why even even like the Japanese car makers have facilities in America or Mexico because you just would drive the car as opposed to putting >> That's exactly right.
3:01:38
I mean if you look at a car I mean the size of tools necessary custom they are tariffs like they all have to like you have to have your own factory in region >> but if you look at any product south of a car almost all of them are built with this contract manufacturing model.
3:01:53
>> Okay talk about the name and the brand Riven has those delightful headlights uh lot of different interesting brand decisions around Riven. What are you taking?
3:02:02
What are you thinking and where's the name come from? >> That's so great. I love it.
3:02:07
Um we naming something is so hard. Um and so R. J.
3:02:10
and I battled quite a bit with this, but when we landed on this one, we knew it was the one because if you look at um transportation, it's always been so singular in narrative.
3:02:19
It's like it's just cars or it's just not cars. >> Yeah.
3:02:24
>> And for us, the approach is like whether it's a commercial enterprise or a consumer, >> it's all of the above most likely.
3:02:32
meaning that I want to use my R1 to go on a long weekend trip, but my school drop off with my kid, it's a pain in the butt to sit in the car line.
3:02:38
Um, and something smaller probably makes more sense.
3:02:42
And so the transformation of electrification of um, uh, transportation is also it requires all of the above in a way.
3:02:52
>> Um, and on kind of like how we present ourselves from a brand, you know, one one analogy that R. J.
3:02:56
and I really um love and use often is it's kind of like we're two characters in the Marvel universe, if you will.
3:03:02
>> So, it's like we we have the same uh mission, but we can have very different personalities.
3:03:05
And so, also has an opportunity to be maybe in a way really expressive and take a little bit more liberties, which you're starting to see in some of our products than um a more grownup vehicle brand may may need to be. >> Okay.
3:03:17
How do you think about competition with Chinese manufacturers?
3:03:19
you know, Rivian Rivian's had the benefit of of not having to compete with all the Chinese manufacturers in the US.
3:03:29
>> I imagine micromobility, you know, is not going to be having the same kind of export restrictions.
3:03:35
Uh, you know, h how do you how do you think about that threat cons, you know, assuming that, you know, they there's Chinese companies out there that for one reason or another will be able to like sell at a loss for some amount of time. >> Yeah. the DJI story basically.
3:03:52
>> Yep, that's a great question.
3:03:52
I think there's a couple of ways to think about it.
3:03:55
Increasingly as you get to the larger form factors in our portfolio and certainly um as we get into autonomy uh I think a lot of the similar factors that we're seeing in the automotive world in terms of the natural firewalls that are happening >> um will exist in our space to some extent as well.
3:04:11
Um but just to back up, I think one of the things that gets lost is um there are a tremendous number of products in this kind of like small uh mobility or microobility space that are coming out of China for sure.
3:04:22
Um but I think it's without debate that the vast majority of these products are commodity like relatively lowquality white labelled type products.
3:04:32
>> That being said, there are a small handful that are really really great products and using the latest and greatest tech.
3:04:37
And if you look at take apart one of those products and you take apart one of our products architecturally and from a technology capability standpoint, they're actually more the same than not.
3:04:44
And I would say also it's probably one of the only brands outside of China that you could say that. >> Yeah. >> Of within this space.
3:04:49
And so just purely from a product uh feature quality and technical capability standpoint, we feel like we're very very competitive. >> Okay. Product pitch.
3:04:58
The Rivian R1T has a gear tunnel. It fits a snowboard.
3:05:04
electric longboard with a handle that flips up like a giant Razor scooter that fits perfectly in the gear tunnel. Am I on to something? >> I love it.
3:05:14
That That's not the first time we've heard that one. >> Really? Okay.
3:05:18
>> The gear tunnel, it just it just does feel like such a unique feature and it just it just demands some bespoke thing that fits in there.
3:05:24
You know, you want like a big speaker, Bluetooth speaker that fits in there or like barbecue or something.
3:05:29
It just I want an ecosystem around the gear tunnel even if you know who knows how viable that is. Uh anyway, very fun. Jordy, anything else? >> Very cool. Thank you so much.
3:05:38
>> I'm I'm on the website right now. I'm interested. >> You're shopping. >> I'm shopping. >> I'm shopping. >> We'll look you up. Just let us know.
3:05:44
>> We will be very excited to ride these around.
3:05:45
We've been doing uh we've been doing some uh office chair racing in the studio.
3:05:50
You can This is apparently a whole >> That's what I want.
3:05:52
I want an electric office chair. >> Oh, there you go.
3:05:56
We have uh well we have in-house vertically integrated motors and rovers.
3:05:59
We can power we can soup those up.
3:06:03
>> Adjust me to the left one in.
3:06:06
>> Yeah, just a little joystick. >> Pilot me.
3:06:10
You know if if if you're not in the right shot, you're a little bit to the left.
3:06:13
Production can just move you.
3:06:15
>> That's actually you will have one or two customers for this.
3:06:19
If you chair >> autonomous office chair, hey, you're you have to leave the meeting. Go back to your desk. drive you around.
3:06:26
I think we're on to something.
3:06:28
Well, thank you so much for taking the time to have a great congratulations on the show. Thank you. >> Thank you. We'll talk to you soon. Goodbye.
3:06:36
Let me tell you about app loving profitable advertising made easy with Axon. ai.
3:06:39
Get access to over 1 billion billion daily active users and grow your business today. What's up, >> Brett?
3:06:46
Adcock was on the show yesterday. Yes.
3:06:49
>> He had some interesting comments about >> the state of AI. Okay.
3:06:51
I disagreed strongly with many of them. >> Okay.
3:06:56
>> But we have to cover uh this video from the Shawn Ryan podcast. >> Yes. >> Uh it's a new gate.
3:07:04
>> It's uh they're calling it gate >> ad gate.
3:07:06
>> Ad well maybe that too. >> Who knows?
3:07:09
>> Uh so so he is hanging out with a figure robot. >> Okay.
3:07:13
>> Uh on the Shawn Ryan podcast. >> Oh, okay. He went outside for it.
3:07:15
I was wondering because like Shawn Ryan normally shoots in that like very cinematic whiskey bar.
3:07:19
Uh, but he's outside and >> there's like a twominute video where they're hanging out with the robot and then let's pull this up and I want to get your >> take. All right, turn around.
3:07:32
>> So, this is the first time he tells it to turn around.
3:07:34
>> Two is like we uh we basically >> at the end of the video, >> it starts turning around and then he says turn around.
3:07:43
>> And Nema here says the video is the smoking gun that figures robots are teleyoped. Again, I love teley op. Not a problem.
3:07:50
But Brett has he always says he's not doing teleop. >> You never do teleyop. >> I don't know. This is not autonomous.
3:07:55
Notice how the robot starts turning around >> before Brett says, "All right, turn around."
3:08:00
>> Yeah, you can skip forward a little bit.
3:08:02
>> And there's pull up pull up this other video that I'm actually on.
3:08:05
>> There's another Yeah, there's another video quoting this that shows it on repeat. Uh >> let's see.
3:08:13
>> Now, thing too is like we uh we basically uh the robot almost all fully software.
3:08:17
It's by Vic Vic quoted and said, "Yeah." Okay. Yeah.
3:08:19
It's definitely not waiting for for the >> It's very this one. >> All right.
3:08:25
It's very subtle, but you can see it's turning around and then he says, "All right, turn around. >> Turn around." >> Yes.
3:08:29
But the steelman here >> premonition.
3:08:33
>> All right, turn around.
3:08:34
>> The robot knew what was going to happen because personalized super intelligence understands that a turnaround command is coming before Brett even says it.
3:08:39
Starts turning around before.
3:08:41
So, that would be one possible solution. But yes, um, who knows?
3:08:47
Also, >> the the the moment from yesterday that stands out to me is uh I said, "Why build a new a separate AI lab focused on personal super intelligence outside of your company that is trying to sell some combination of intelligence in the physical world."
3:09:05
And he said, "I really value focus."
3:09:09
which I thought was fascinating given that he is diverting his >> his personal focus >> personal focus. >> Yeah.
3:09:17
It's like focus within an organization like a specific like the leaders that join that company can focus just on that problem.
3:09:22
It was it was an odd uh an odd comment to sort of process.
3:09:27
Um yes the uh I mean I don't know I I I haven't watched the full uh the full interview with Sean Ryan.
3:09:35
wonder if uh if if he talks about whether or not this particular robot is teleyop because it's totally reasonable that a company would have some teleyopt robots, some autonomous robots and sort of mix and match them based on the particular demo.
3:09:48
Obviously, if you're doing some sort of presscripted stunt uh dance or parkour scenario, you might press that and then ideally you would say, "Hey, you know, this this one's teleop here.
3:10:00
Here's a demo of what we're capable of when we're using teleop.
3:10:04
Here's a demo of what we're capable of when we're fully autonomous, when we're, you know, partially, you know, remote controlled or something like that somewhere in between. Um, I don't know. We'll see.
3:10:12
Uh, you know, people will continue to dig in.
3:10:15
I mean, all of this, uh, you know, the rubber meets the road when the when the robots are out in the wild.
3:10:20
When people get them and they start shipping and people can see, uh, unless you buy one and it's secretly teleop, that would be wild.
3:10:26
You're like, "Wow, this is remarkable.
3:10:28
I can give it the most complex I can give it the most complex vague instructions and it just does exactly what I done.
3:10:36
>> If the figure robot can simply open a Diet Coke for John, we're a buyer.
3:10:42
>> That's that's the goal post.
3:10:44
>> I don't we don't need it to do everything. >> That's the goal post.
3:10:45
Just need to do >> crack open a sixack of Diet Coke.
3:10:46
Uh Tyler, what do you think about uh the figure figure gate?
3:10:51
Uh yeah, I mean it's hard to say just from that video, but I think broadly like >> um people are probably like too against teleoperation generally. >> I agree.
3:11:01
>> Uh because like you know the lesson from Whimo is that like actually >> it's goed >> you know part maybe if it's totally like 100% teleop like okay that's not great but if it's like partly like there's someone overseeing it and maybe they're like pretty involved sometimes it can be like extremely valuable like Whimo is a great >> product whatever. Yeah.
3:11:17
>> product whatever. Yeah. Like even just like deploying robots in dangerous locations if it's fully teleoped that's still like a great thing >> hugely valuable >> and like clearly uh the way we get fully autonomous robots is by starting out
3:11:28
with with partially telep Oh we we we do have we do have one followup to yesterday so we did a little deep dive from the Wall Street Journal on Mark Laneir, the lawyer who successfully argued that meta and YouTube are addictive in the LA court last week and we posted the clip. A lot
3:11:55
A lot of people enjoyed learning about him and in particular the fact that he has a menagerie that contains lemurs and llamas as well as a 120 person train.
3:12:03
Uh we we love the way he's living his life.
3:12:10
were huge fans of Mark Laneir, although do have some disagreement around uh the the legal findings, but uh a lot of people chimed in.
3:12:17
Uh XL rotate uh XL Raider said uh by the way, this is the Laneir Theological Library in Houston, which is open to the public for touring. Incredible guy.
3:12:26
Shares two amazing images of, you know, what an amazing contribution to the community.
3:12:30
And Eric Seufort uh quote tweeted our post and said, "This is true.
3:12:36
I grew up down the street from his property and he hosted a high school graduation party for one of my friends.
3:12:41
He recently bought an adjoining horse ranch and built a seminary on it.
3:12:44
So, a lot of people uh coming out in support of Mark Laneir and uh yeah, I mean just seems like seems like a fantastic lifestyle.
3:12:51
Fantastic menagerie and he really re you know everyone's everyone focuses on oh are you flying private?
3:13:00
Are you are you post economic?
3:13:02
Like menagerie is clearly just a different tier, different ladder.
3:13:06
That's where you want to go in life if you're successful. And he's done it. So congrats to him.
3:13:10
Anyway, thank you so much for tuning in to TBPN today.
3:13:12
Leave us five stars on Apple Podcast and Spotify.
3:13:16
Sign up for our newsletter at tbn. com.
3:13:18
>> A wonderful last few hours of your quarter.
3:13:21
>> Yes, >> it's been an honor. >> See you tomorrow. Goodbye. Rolling >> flashbang. Bye.