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5:02
Got to adjust my microphone over here.
5:04
Uh well, uh Bezos is getting very serious about the AI game.
5:10
$12 billion raised for Prometheus.
5:14
Uh it's just been 6 months since he emerged from stealth with 6. 2 billion in funding.
5:19
Uh the industrial AI startup, as they're calling it, raised another 12 billion in series B.
5:26
It's just a thousand times bigger than a normal series A and a series B.
5:29
You used to go from 6 million series A, 12 million series B.
5:33
Now, it's uh 6 billion series A, 6 12 billion series B.
5:37
Serious dollars, but AI is expensive.
5:40
The valuation, 41 billion dollars.
5:42
Back in November, there was very little disclosed about Prometheus.
5:46
We wrote about it a little.
5:48
There were some uh some speculation on the timeline. >> 41? >> 41 billion.
5:54
Bigger than what a 40 billion-dollar company.
5:58
>> And this is a business that is buying existing companies? >> What? >> Uh That's the thing. We don't really know. We don't really know.
6:05
But, it's a lot of money.
6:06
Could be buying companies and trying to transform them are around 30B to 40.
6:14
>> Well, being able to raise that much capital to buy businesses with that little dilution is a pretty remarkable feat that pretty much only Jeff Bezos could pull off. >> Yeah.
6:24
Uh so, the Wall Street Journal has some more details and uh mostly it just gives you takes you a little bit more inside the mind of Jeff Bezos and uh where he's thinking like how he's thinking about the shape of the AI impact.
6:34
Uh the the headline is very clear.
6:37
Bezos bats down AI job loss fears while launching new venture, new startup Prometheus seeks to build an artificial general engineer.
6:48
[clears throat] AGE is the new buzzword.
6:51
You thought we were at We thought we were running out of them.
6:53
We got AI AGI ASI RSI AIFDE personal super intelligence, meta super intelligence, TBD.
7:06
Uh continual learning >> Standard intelligence. >> Yep.
7:11
>> Your regular intelligence.
7:12
>> Non-standard ineffable intelligence.
7:14
>> intelligence The irregular super intelligence company. >> Of the dog patch.
7:19
>> The dog >> [laughter] >> Something like that.
7:20
Uh but, artificial gen general engineer is the new phrase, the new term.
7:24
Uh and he wants it to be able to design and manufacture complex physical products.
7:30
So, Jeff Bezos expects artificial intelligence to create a labor shortage in the economy. Interesting.
7:39
There's some correlation between like liquid net worth and and and and your and your projection >> optimism. >> Right? Yeah.
7:47
So he expects a labor shortage rejecting fears that fast evolving technology will put humans out of work as he launches a new venture aimed at making engineers more productive.
7:57
The billionaire founder of amazon.
7:59
com and don't forget Blue Origin is co-leading a new AI business called Prometheus which plans to build an artificial general engineer that can design and manufacture complex physical products such as a jet engine.
8:10
And we just saw some cool demos.
8:12
I saw people vibe coding Boeing 747.
8:16
Obviously it's just the outside. It's modeling it.
8:18
It can pull different reference points from CAD files on the internet but lots of cool demos, many powered by Fable 5.
8:27
I've seen some GPT-5 stuff as well where people try and go and see the classic like pelican on a bicycle in SVG.
8:34
Well, you can see how you can draw a line from pelican on a bicycle in SVG to functional jet engine in CAD that then we can actually go manufacture with step-by-step instructions for each part.
8:48
Not that far away, certainly on the trend path and that's what he's investing against.
8:54
He said in an interview that the company's goal is to quote empower engineers and make innovation easier and faster so smaller teams can do much bigger things on much shorter time cycles. That'd be good.
9:06
It takes forever to build a jet engine.
9:08
It takes forever to build a plane.
9:10
We've talked to multiple founders that have been trying to build new plane designs for decades and haven't really been able to scale them up although they've made incredible gains and traction and demos.
9:21
Actually getting new planes on the runway safely approved has been far too long.
9:27
If AI speeds it up by 10% that's like years. It's crazy.
9:33
The Amazon and Blue Origin co-founder joins a group of long-time technology leaders that have jumped into the AI fray.
9:39
You got Uber co-founder Travis Kalanick, Coinbase co-founder Brian Armstrong, Robinhood co-founder Vlad Tenev, also Brian Chesky over at Airbnb.
9:49
These folks are all building new companies around the AI boom among others.
9:52
Prometheus, which said it is valued at about $41 billion, has raised $12 billion from investors including Bezos, JP Morgan Chase, Goldman Sachs, and BlackRock.
10:01
Went straight to the big banks. >> Yeah.
10:04
>> Like the invest VCs are just like, yeah, like >> Well, yeah, I mean, there's there's another world where doing six on 40 billion is just like your IPO. >> Yeah, totally.
10:15
Yeah, that is IPO numbers.
10:18
That's, yeah, that's a crazy amount of money.
10:19
Yeah, you got to go to the banks for this.
10:20
They've hired 150 people across San Francisco, London, and Zurich. Interesting.
10:24
Despite Silicon Valley's enthusiasm enthusiasm for AI's promise, the broader population has become very wary fearing widespread job losses.
10:34
Some of the pessimism about AI among young people is the opposite of reality, Bezos said.
10:39
And we've been seeing this in the jobs numbers.
10:41
Like the job the economy is running hot, inflation is high, but also unemployment is very low. Lower than expected.
10:46
We're adding a lot of jobs.
10:49
AI will mean fewer workers are needed in jobs that exist today, but it will also create far more opportunities and increase productivity, he said.
10:58
That's a very white-pilling statement.
11:00
We'll see how it plays out.
11:03
Bezos argued that if AI makes it cheaper, faster, and easier to invent things, employment will ultimately rise because even though you're shrinking the number of people needed by 10x, the technology will create more than 10x as many opportunities.
11:15
And he certainly saw that with Amazon.
11:17
The number of, you know, store workers in physical retail stores probably shrunk, but the number of entrepreneurs building products selling them on Amazon in and around the Amazon ecosystem, not just in the warehouse, but in the broader Amazon ecosystem probably increased.
11:31
And uh we certainly saw that in the broad job numbers in uh in the United States.
11:35
Like the labor market has grown unequivocally since 1999.
11:40
We've added jobs all over the place uh as people have shifted around.
11:46
There there's going to be two uh there are going to there's going to be two earner income households where one earner drops out of the labor pool because there's going to be so much productivity, he said.
11:55
That's an interesting take.
11:57
He's saying that uh there's going to be so much more productivity that some uh some people will choose not to work.
12:03
And of course, that won't necessarily show up in the unemployment rate because the unemployment rate only measures people that are actively looking for jobs.
12:10
So, you could have a world where the workforce is shrinking in terms of the number of people that have typical jobs is declining, but the unemployment rate is also very low because you have more single earner households, one person working making more than enough money to support the whole family.
12:27
Uh sort of an older school mindset.
12:30
Harkens back to uh you know, the the maybe apocryphal stories about the mid-20th century, but uh certainly an optimistic view nonetheless.
12:43
>> Yeah, it's notable uh NEET levels have been rising since 2021. >> Mhm.
12:48
>> Uh >> That's not employed in education or training. >> Not in employment.
12:54
>> Uh so, that trend started well before >> Mhm.
12:57
>> the current AI paradigm. >> Yeah.
13:00
>> But wouldn't be surprised if it continues, hopefully for the reasons that Bezos is talking about.
13:03
Um I think there's going to be a lot of focus on his summer plans, John. >> Yeah.
13:11
>> I think there's going to be more scrutiny than ever.
13:12
You know, this is a guy that uh can hardly jet around the Mediterranean on a big boat without being photographed every single day.
13:23
>> And this was prior to these back-to-back, you know, multi-billion dollar rounds. >> Yeah.
13:28
>> And so going into the summer, I think people are going to be paying extra attention, right?
13:31
Is he doing back-to-back days at the Beach Club, or is he keeping it to a 4-hour window on Saturday? >> Yeah.
13:39
>> Locking back in by Saturday night, getting a good night's sleep, spending his Sunday, you know, preparing for the for the coming week, right?
13:47
>> He does have a co-CEO.
13:47
Maybe they've split it up.
13:49
Most people think co-CEO is like they're both involved in every decision.
13:53
Maybe it's more of like a he takes the winter and fall quarters, and the other co-CEO takes the summer and spring.
14:01
Like if you divide it up that way, no one's ever tried that with a co-CEO.
14:05
Just like you run the company for 6 months, then I run the company for 6 months, and you're completely off on vacation. Maybe. >> Yeah, yeah.
14:12
The alternative is, you know, Bezos would say like Friday from 7:00 p. m. until 2:00 a. m.
14:16
on Saturday, I'm not going to be super available, super online.
14:22
Uh and then also from 2:00 a. m.
14:25
till till around 11:00 a. m.
14:25
, uh I will I'll be fully fully offline. >> Okay.
14:30
>> Um then there's about a 1-hour window on Saturday where you can take like a lunch break, do whatever you need to do. But then from 1:00 p. m. until 2:00 a. m.
14:39
Sunday, I'm going to be offline again.
14:41
Uh but back, you know, >> Maybe if you're co-CEOs, you should just do I I'm CEO of TVP on the odd hours, and you're on the even hours.
14:49
And so if there's a big decision, you can >> to non-stop productivity and 7-day work? >> analyzes them.
14:54
Yeah, so oh, it's 3:00 a. m. , call Jordy. Oh, it's 4:00 a. m. , call John. Co-CEOs working out.
14:58
Uh Bezos is co-CEO of the new company along with uh Vic Bajaj, who a a veteran a Google veteran and former healthcare founder and investor.
15:09
Uh they started Prometheus in late 2024.
15:12
So people have sort of pet like pegged this as like a late in the cycle.
15:18
It's uh oh, it's 2026 and they're jumping in.
15:20
They've been working on this for two full years and obviously Jeff Bezos has an incredible amount of AI and robotics experience both in the recommender systems in Amazon and Kiva robotics, which is probably like the you could make the argument that it's like the Instagram of the robotics boom.
15:35
It's like one of the most successful successful acquisitions.
15:42
We're talking to the founder of a robotics company at 11:45 today.
15:47
Um So his co- his co-CEO is a professor at Stanford School of Medicine who previously co-founded Google's life sciences division. No big deal.
15:53
That's a huge accomplishment.
15:55
And the company's goal is to build AI systems that can assist throughout the entire engineering process.
16:01
That ranges from designing products and predicting their performance to manufacturing them.
16:04
We're trying to approach that problem end to end. They also held talks. This was the big one.
16:10
We They held talks to raise a hundred billion dollar fund. Which is a lot of money.
16:15
We We'll talk about SpaceX in a bit, but SpaceX is looking for 70 billion and it's a huge business with it's so much attention.
16:21
This is an entirely new thing and they want to put a hundred billion to work.
16:25
But of course Bezos has plenty of money and he backstop it, anchor it, do whatever he needs and he has massive connections.
16:32
So the Wall Street Journal reported this and they said the goal was with that fund to acquire manufacturing businesses and deploy AI across their operations.
16:41
Remember we did that whole list of like what could they actually buy for a hundred billion dollars?
16:45
What would be a good buy?
16:48
And there were some very interesting like you could buy like Goodyear for example and work on tire manufacturing and I think I was wrong in all my predictions, but it was an interesting exercise to to just take a little tour of the American manufacturing >> my read on it is some combination of like a foundation model that allows you to generate full product full full products basically like product specs, designs, etc. to high fidelity. >> Yeah.
17:15
And then something like a send cut send style infrastructure where you can just make that product on the fly. >> Yeah.
17:22
>> Uh and get it delivered. >> Yeah.
17:24
>> And that is the moment we're in right now where on your computer you can make at least an image of anything you want in the entire world, but then there hasn't been that much of a speed up on the other side, right?
17:34
And so closing the loop there is going to be uh very very cool. >> Wow.
17:41
This company Prometheus is bigger than AIG, the insurance company. >> Bigger than Chipotle?
17:46
Bigger than CBRE, the real estate >> on companiesmarketcap. com, John? >> No, I'm on ChatGPT. Bigger than Baidu? Wow.
17:55
Uh that is that is crazy.
17:56
>> John, do you think that they're going to be punished for their hubris hubris and chained for eternity with with a eagle >> determinism of Prometheus is sort of crazy, right? >> Yeah.
18:07
>> But >> And for eternity eagle comes eats his liver every day.
18:10
>> Isn't Prometheus like the third time an AI company has done this?
18:12
Because there was the Prometheus data center at Meta.
18:16
>> There was a company called Icarus, too. >> Icarus, yeah.
18:18
I got in trouble for that one cuz I was talking to a New Yorker reporter about that and then [laughter] and sort of overstepped a little bit cuz I was like, "They have a great team. I'm rooting for them."
18:27
But >> [laughter] >> uh the nominal >> So I think we need another company named Hercules, right?
18:31
Cuz because Hercules saves Prometheus. >> Oh.
18:35
>> He frees him from the chains.
18:35
But then uh Hercules >> called Hercules?
18:38
That's a good company name. I like that one.
18:41
>> Yeah, that's from the chat.
18:42
>> Um but uh yeah, so if raised it would be the lar- the latest in a series of investors buying established companies and using AI to improve productivity and margins.
18:50
We've seen a couple of these funds uh roll out, the AI rollups, AI modernization private equity firms.
18:55
Obviously private equity firms themselves are doing this.
18:56
Um but no one's come in with a hundred billion dollars.
19:00
You're in a completely different tier from uh all the other companies that are doing this.
19:04
Uh we've had many of them on the show.
19:06
Uh AI's advances have paved the way for coal quote a multitude of golden ages, not just one, happening simultaneously, Bezos said.
19:17
He said, "This is the best time to start a company." I love the optimism.
19:22
>> You can buy strategy, MicroStrategy, and Prometheus are roughly the same value the same.
19:30
Uh as well as >> MicroStrategy is in a in sort of a rough spot, right? Isn't Bitcoin down?
19:35
>> No, it's a good it's I mean, it's an interesting it's an interesting bet, right?
19:37
What do you want to What do you want to buy?
19:38
What do you want to own it at 41 billion? >> Yeah.
19:42
>> MicroStrategy is at 42, technically. >> Yeah. You can buy Reddit. That's 33 billion.
19:47
Uh anyway, um the next story we got to talk about is gamers are rising up. Gamers are rising up.
19:53
You heard that the government was trying to put gyms in airports, but the gamers had something to say. They're pushing back.
19:59
Airport lounges are catering to gamers, the airport lounges where video games are more important than drinks.
20:06
Travelers can kill time, play everything from Mario Kart to Minecraft before their flight. We got to do this.
20:11
Get a little rust going next time we're flying. Let's do it.
20:13
Uh the first thing David Lee and Yang noticed >> Before we dive into this, has has TSA gotten like better, more consistent? >> a hot take on this.
20:25
I think TSA might be goated.
20:28
>> I think they're pretty dialed.
20:30
Out of the last maybe 30 flights, >> Yeah.
20:35
>> I have not waited more than 30 minutes in a in a in a security line. >> Yeah.
20:39
And >> And that makes like commercial is obviously still um uh >> torture. >> torture.
20:48
>> of a it's sort of a primitive >> punishment. >> humiliation ritual.
20:51
Um But that being said, being able to plan on a 30-minute security line makes commercial travel uh pretty pretty you know, a lot better.
21:03
>> butt of every comedian's joke because it's so universal.
21:06
Everyone's been through TSA, it's very slow, take your shoes off.
21:09
There's a million little places for comedy gold that's highly relatable. >> take your shoes off.
21:13
Don't have to even take your laptop out.
21:16
>> No, it's it's getting back.
21:16
And there's like I mean I guess it's getting more surveillancy because they take a photo of you like 17 times on the way through.
21:24
>> You can refuse that though. >> You can? You can just say no? >> Nick Nick does that. You can just say no.
21:29
>> But then don't they make you take a picture of you?
21:31
>> They don't They used to about I would I will say about two years ago, they would tell you more frequently like it's optional. >> Yeah. >> It's optional.
21:39
Now they're just like photo now. >> Okay.
21:42
>> And you can read the text and it says like you cannot opt out.
21:45
>> Okay, can you opt out of the whole thing?
21:46
Is it all just like a high agency test?
21:47
You can just be like actually I just want to go around.
21:48
I don't even want to go through the metal detector and they're like yeah, right this way sir.
21:52
No one's ever thought to break out of the matrix, but you reached the final level.
21:55
You reached base reality. Good job. Continue.
21:59
>> No, but but truly being able to plan on it's going to take me like 30 minutes to get through.
22:02
You can like comfortably show up 45 minutes before >> flight and reliable. >> make it every time. >> Every time. Every time.
22:10
>> Which means that you're pushing it even more to the >> Oh yeah.
22:13
>> Often times I will be getting through security >> and John will text text and be like just got in my car.
22:20
>> [laughter] >> I'll be there I'll be parking in 45 minutes.
22:24
And I'm like I thought I was cutting it a little bit close, but man of heaven you always make you always make it.
22:30
>> make it and if you're not missing flights at least like 10% of the time, you're actually setting your you're not you're not cutting it close enough. >> No.
22:40
>> Like you have to be taking some level of risk or else you're just wasting time. >> No. >> Yes.
22:45
>> No, because often often times the things that you're doing >> and you're like your goal is to never invest in a company that goes out. Oh, you're a VC.
22:52
Uh but you're but you're but if you get a single zero in your portfolio, you can never invest ever again. Would you do that? No way. No way. No way.
23:02
>> I'm not I'm not engaging. >> No way.
23:04
So, you're you're going to have some zeros in your portfolio.
23:05
You're going to miss some flights, but on average your DPI is going to be quite good.
23:11
Which is the expected >> Yeah, yeah, comparing something comparing that >> This is where This is where the argument goes.
23:17
I can just have as much fun as the at the airport.
23:19
So, I don't mind showing up 5 hours early.
23:22
>> but okay, if you miss your flight and then the next flight is like 3 hours. >> Yeah, yeah. >> Then like >> Yes.
23:28
>> It doesn't It doesn't math out because like if you just get to your flight 10 minutes like a little bit earlier >> Yeah.
23:34
>> then it'll like match I I think it makes sense because >> So, so basically like like let's say I fly once a week and I save an hour with my strategy.
23:42
That's 50 hours a year and I only miss one twice.
23:44
I save I save 3 hours and >> not you're not like saving the time. >> I am. I am.
23:51
>> You were probably you were probably at at your just like having another coffee at the hotel and or like doing something having a conversation that you could just have >> was literally Before I go Before I go to the airport, I am literally locked in at the clock factory, okay?
24:07
I'm locked [laughter] in at the clock factory.
24:10
I'm being the most productive I've ever been. And >> Making clocks.
24:15
>> I'm making [laughter] clocks.
24:16
Clock by clock and and you think that that time is useless.
24:20
>> Well, okay, now you can be gaming at the airport.
24:23
>> Yeah, so >> [laughter] >> I should get If I want to prestige on COD, I should get there maybe like 72 hours early.
24:32
>> you're just like yeah, I got to get up at 2:00 a. m. this morning.
24:33
[laughter] Like I got like a I got a super early flight.
24:36
They're like oh, what time is your flight? Like 11:00 a. m. 11:00 a. m.
24:39
like [laughter] >> Yeah, is this a coincidence?
24:41
GTA 6 dropped and you're going to the airport 10 hours early?
24:44
Well, now you can because airport lounges are starting to cater to gamers.
24:48
Gamers are the most important constituency.
24:50
We're going to have a gamer president one day.
24:55
So, the first thing that David Lee and Cassie Yang noticed when they popped into the new lounge in Terminal 1 at Minneapo- Minneapolis-Saint Paul International Airport on Friday wasn't a robot bartender, which they have, apparently.
25:10
I I believe Ben will be traveling through Minneapolis-Saint Paul.
25:12
We should give him a little gaming challenge.
25:14
See if he can See if he can get to prestige on COD before he his hits his flight.
25:19
Um it was something only parents in this digital device era could appreciate, unfettered to their phones.
25:25
Their kids, 8 and 12, were busy playing Mario Kart and Crash Bandicoot at the lounge's video game stations to commandeer their phones for some pre-flight screen time.
25:37
The Portal Lounge is, by design, not your grandfather's airport lounge.
25:39
Yes, there is a small buffet and bartenders, robot and real, that pour that lounge libation staple, an Old Fashioned.
25:47
But, the focus is on entertainment. They're gaming.
25:54
And it's the latest concept from husband and wife team on a mission to amp up airport downtime.
25:58
Emma and Jordan Walbridge, with backgrounds in hotels and medical device sales, respectively, opened their first airport video game lounge at Dallas/Fort Worth International Airport in 20 2018, called Gameway.
26:10
There are now 11 [snorts] of them at airports across the country, and two more due to open this year.
26:14
Portal in Minneapolis is the latest iteration of concept with a few more bells and whistles.
26:19
They zeroed in on video games after regularly visiting lounges on business trips and finding them too staid.
26:25
"I always felt like I was in a library," Emma says, "with some guests shushing others and throwing shushing others and throwing side eye."
26:33
>> picture makes me feel like I'm a television screen. >> What do you mean?
26:37
Oh, because they're looking at you like you're >> With the controller. >> You're the game. Yeah, interesting.
26:42
She's played Mario Kart for years.
26:43
Jordan has played Halo, which is getting a refresh soon with a campaign of all >> this I think this is going to be more successful than like the whole airport gyms movement. >> I think so.
26:54
>> Like every once in a while somebody will post online, why don't airports have gyms? >> Mhm.
27:02
>> And um there's been a few moments where it would been nice to have a gym, but imagine a world where you know, even just 5% of your flight had just gotten off of an hour on the treadmill >> Yeah.
27:17
>> and was getting on the flight. >> Pretty brutal.
27:19
>> Pretty heavy uh some heavy breathing going on. I don't know.
27:23
>> Golf simulators in airports.
27:25
>> That could be probably >> before.
27:27
>> Yeah, you you've actually done that.
27:28
You've actually played simulated golf. Interesting.
27:31
Uh Raycer Martin, what a crazy name for a 19-year-old chef from Arizona.
27:37
R A Y C E R, that's a cool name, Raycer.
27:40
He plays Apex Legends at the Gameway Lounge at Chicago's Midway Airport.
27:44
I plunked down at the gaming station and embarrassed myself playing Mario Kart over a lunch of diet Coke and Ruffles cheddar and sour cream chips.
27:54
The patient Gameway manager who used to work at GameStop assured me that he that it just takes practice and encouraged me to play at home.
27:59
Another employee did her best to introduce me to Minecraft even though I gave up after 5 minutes.
28:04
This Wall Street Journal reporter is clearly learning the ropes of these games.
28:08
Video gaming is the main attraction at the much bigger Portal Lounge in Minneapolis, which opened over Memorial Day weekend in the D Concourse, but it's just one attraction.
28:15
The food is more lounge-like with build-your-own bowls.
28:19
That's a lot Buffalo cauliflower salad fixings, a couple dessert.
28:22
Adding to the futuristic feel of robot bartender takes the sec- the center stage pouring drinks.
28:26
It's from the same company as the makers of the Bionic Bar on some Royal Caribbean ships.
28:32
At almost 4,000 sq ft, Portal isn't on par with say an American Express Centurion Lounge.
28:38
It's more like one of those smaller Escape Lounges.
28:41
RC Cola is on tap, there's music, outlets galore, and plenty of seating, but no dedicated bathroom.
28:47
The gaming lounge is in the back and bright game way.
28:48
Anyway, you can go check it out.
28:53
Seems >> If we let John keep going here, he would just talk about airport gaming lounge.
28:58
>> No, no, I would talk about railway because railway is the all-in-one intelligent cloud provider.
29:01
Use your favorite agency to play web apps, servers, and databases and more while railway automatically takes care of scaling.
29:08
>> like a railway lounge in every airport.
29:11
>> Uh you you joke, but a Vibe coding lounge is coming.
29:12
Like these gaming PCs they can do local inference.
29:15
You can fire up your agents.
29:16
You can be uh you can be doing all sorts of stuff. >> I like it.
29:20
>> I'm surprised uh yeah, I wonder what the cybersecurity stack is like there.
29:23
It's got to be sort of tricky to have someone, you know, give them free access to a powerful PC.
29:29
They're going to install some weird stuff.
29:31
>> Unfortunately, the lovable airport lounge is coming.
29:33
It's like have 5 minutes, build the next >> [laughter] >> Build the next hit app. >> Yes, yes.
29:40
Uh well, I think the next hit app might be Halo campaign evolved.
29:42
Let's watch this video from Blue Thunder. What do you think? Are you a Halo guy? Do you ever play Halo? >> Not really, never. >> Halo.
29:51
>> Never captured my heart.
29:53
>> got into the whole hardcore multiplayer scenario. But it does look good.
29:56
Doesn't it look uh like fully refreshed?
29:58
Looks very modern triple A.
30:00
Uh Blue Thunder says this is >> What if they made a >> the best look FPS games he's ever seen.
30:07
>> made an airport size lounge, sort of like a facility just for one v oneing on Rust? >> That'd be great.
30:15
>> You could potentially get you know, 100,000 people >> Yeah.
30:19
>> all in the same place, LAN party, matched up. >> Yeah.
30:24
>> Uh this could have been uh this could have been like one shot output of an LLM.
30:28
And >> Yeah, when I saw this, I wasn't sure if it was AI video or Vibe coded version of Halo.
30:36
Did you see that thing where someone was trying to build GTA 6 like Vibe code GTA 6? You saw this?
30:41
>> [laughter] >> It's such a funny demo.
30:41
I mean, you don't want to hate on it cuz like it is like the tools are very powerful and and you do imagine that over time you'll be able to, but the first effort video was very funny because >> Well, we got an X Halo.
30:54
We got an X Halo We got an X Halo 3 Pro in the chat, Alex.
30:58
He says will be a conservative pick up of nostalgic non-PVP gamers.
31:02
Don't expect it to do >> Oh. Interesting.
31:04
X Halo 3 Pro, what was that like? Interesting. Yeah.
31:10
Day one of building GTA 6 still feels fake dot time typing that out loud.
31:17
Upgraded to Claude Pro Max 20X just for this.
31:20
Spent a couple hours getting the whole project structured and pushed to the repo.
31:23
Sandbox is up and running.
31:23
I mean, this is actually where you'd start.
31:27
Like it's not that unreasonable, but it just like it's funny because it doesn't look anything like any GTA game.
31:34
>> Wait, [laughter] what?
31:35
>> You've never even seen this? You haven't seen this?
31:37
So Matt Shumer, former guest of the show, and creator of the viral essay "Something Big Is Coming" where he predicted "Something Big Is Happening" where he predicted that AI would cause 10% unemployment by April um and compared like it into COVID.
31:56
>> Wait, that was his prediction?
31:58
>> Yeah, he said that it was going to be like a COVID like takeoff in the economy.
32:01
He didn't map the the uh the economic numbers directly, but we did.
32:07
We were like, "Okay, like what what was COVID actually like in 2020?"
32:09
And we went from February, which is when he wrote his essay, February of 2026, saying AI is real, it's going to change things, it's big, which a lot of people have been saying for a long time.
32:19
And I was like, "I agree, but I don't think in April, May, like the NBA is going to be shutting down because of AI.
32:27
Or or I don't think that the like the unemployment rate is going to spike to 10% overnight.
32:33
Like there might be little pockets of layoffs related to AI and there might be some >> if anybody wanted to make AI less popular shutting down the NBA finals because of how good the models have gotten.
32:47
Just telling everyone >> all the end play A players like we got to invest we don't have to make them >> even invest they got to invest they got to invest their time >> got to vibe code.
32:56
Yeah maybe they don't want to get left behind.
32:57
No I don't think they'll be left behind but Matt Schumer said someone should set up a community funded fable run with a prompt like /loop until you've created a GT GTA 6 caliber open world game with a quality and scope surpassing what is shown in the initial trailers.
33:13
He says happy to write the prompt if someone organizes this which some people were making fun of but it started. Z Wen is doing this.
33:23
He's 25 he likes Claude and Codex tech AI startup. I'm rooting for this.
33:26
AI startup. I'm rooting for this. I think this is going to be very educational for Z Wen although yes this video is very funny because it doesn't it doesn't look like GTA yet but you know if you can get to anything that's at all playable or interesting even in a a month even in a year take as long as you want if you can do it if you
33:47
can get you know a million people to pay 10 bucks for this and it only cost you 5 million in inference and you did it as a solo dev like that's a 5 million dollar profit like that's a great outcome like I I love indie devs I love the I love that world and I like that these tools are opening up more opportunity for people to go mess around and build cool things. It's got to be really
34:07
It's got to be really entertaining to just think about building like a vibe coded game.
34:12
Some of the games look really good already.
34:13
Of course like even if you Strauss is going to be pretty worried Did you did you hear him talking the prime agent had a good reaction video to David Sacks talking to Strauss Zelnick and he's like finally like a normal AI CEO because he he basically says like we have a mobile games we have a mobile games division, we have a we have we make a billions of dollars from it.
34:36
We make a lot of money from mobile games and um and there are there are direct clones of our games that launch every day.
34:43
Like the software has been good enough that you can clone our games. They launch every day.
34:48
The business is much more complicated than that.
34:50
The IP matters, the distribution matters, the the functionality of the game matters.
34:56
There's so much more to it than just a carbon copy.
34:58
So he says, "Yes, you could just go vibe code GTA 6.
35:01
People are still going to play our game because of all the other strengths of the Take-Two business." And I agree.
35:08
I thought it was a very good take.
35:09
Anyway, uh let me tell you about the New York Stock Exchange.
35:14
Want to change the world?
35:14
Raise capital at the New York Stock Exchange. Just do it.
35:19
Some big IPOs happening this week, next week. It is IPO season.
35:22
Um but it's also trucking season.
35:28
The four-year US trucking slump is officially over, says the Wall Street Journal. It's over at last.
35:33
Truckers who held on through almost four years of slumping freight rates finally have something to celebrate.
35:41
"It feels like a breath of air for an industry that maybe felt like they were running out of air," said Web Estes president and chief operating officer of Estes Express Lines, a Richmond, Virginia-based carrier with revenue about $6 billion.
35:58
Freight rates are finally climbing. Good news for them.
36:00
Trucking executives are calling it to an end to one of the longest freight downturns in carriers' memory.
36:07
They say rates have risen to more sustainable levels after a period of low earnings coupled with Trump administration crackdowns on immigrant drivers pushed many carriers out of the market.
36:15
The Logistic Managers' Index, a monthly survey of supply chain managers, showed transportation prices increased in May at the fastest rate for any metric in the reports' 10-year history.
36:28
So, if you scroll down, yeah, that chart is crazy.
36:30
Um so, good news for the truckers.
36:32
Of course, this is going to push up, you know, prices and inflation potentially, but uh it is good to have a healthy trucking industry, a healthy dry van spot rate, which I'm sure you've been following intently.
36:43
Uh dry van spot rates for the week of June were up 5,200 basis points. >> Let's go.
36:51
>> 52% year-over-year, uh excluding fuel surcharges, according to a report.
36:54
So, the fuel prices get passed through, but the economy is doing well, and so prices for uh dry van spot rates are increasing.
37:04
Uh as he said, >> uh >> because of the stronger freight market over the last uh few months, the nationwide company is increasing its fleet of more than 10,500 trucks and expanding its pool of about 11,000 drivers. >> What is driving this?
37:22
>> This has been a supply-driven freight recovery, as opposed to a demand-driven freight recovery.
37:28
Turnaround comes after 4 years in which carriers have been squeezed by a combination of too many trucks on the road and not enough loads.
37:35
Drivers rushed into the industry during the pandemic, so there was a boom in online ordering, shipping, all the different things that happened during COVID.
37:43
Uh consumer demand drove freight rates to record highs.
37:45
Rates plummeted in 2022, forcing hundreds of thousands of smaller carriers out of business.
37:52
Many truckers held on even as costs for drivers, equipment, and insurance rose.
37:56
The exodus accelerated over the past year.
37:59
Um and trucking specialists say the industry has finally found an equilibrium where the supply of trucks is low enough to lift rates, which will, of course, bring more trucks into the market, and rates will adjust, of course, but higher fuel prices due to the war have pushed up trucking companies' expenses, but operators are largely passing along those costs to their customers.
38:17
So, uh anyway, let me tell you about Shopify.
38:21
Shopify is the commerce platform that you grow with your business and let's you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
38:30
>> Uh we have some breaking news.
38:31
>> What's the breaking news?
38:32
>> Uh Tai Morris says on Saturday we finished construction of set number two. >> Set number two?
38:38
>> Uh so Tai had built a set for his interview with Elon Musk.
38:44
>> Uh it sounds like they built it in a place that they weren't they were only able to occupy for >> Seven >> this week. >> Seven days.
38:50
Next seven days one hour notice.
38:52
And that was on June 6th. >> It was on June 6th. >> gripping.
38:56
This was a trending story on X.
38:58
Uh he says, "For the past three months I've been asking myself the simple question, what would Elon do?
39:02
Elon would build the rocket and put on put it on the launch stand before he got approval.
39:07
He would ask, "What's the biggest bottleneck to achieving my mission?"
39:08
and then go about systematically undoing the bottlenecks until he and his team had made the impossible happen.
39:15
A maniacal sense of urgency is our operating principle.
39:20
And so he has built yet another set that I think can last a full month and hopefully he lands the interview.
39:29
He's incredibly pumped up for this and the meta story of him building this set has done better than most podcasts.
39:40
>> [laughter] >> There's more views on >> I want to read John, I want to read the summary of the book about the story of Tai Morris getting Elon on his podcast.
39:52
>> Like 7,500 people, 2 million people watched the video about the set.
39:59
And so you do have this a dynamic where the meta story is more interesting or it it like it's by default more interesting because the interview hasn't actually happened.
40:07
But there are plenty of Elon interviews at this point like he does a lot of interviews uh that don't go super viral.
40:13
Like he did this interview with Jamie Dimon and I think that's fully recorded.
40:16
I think you can just search it and watch it, but uh I don't know that that's something that like everyone in tech saw and everyone in tech talked about, but this is a story people are talking about, the meta story.
40:26
And people love to see bold moves, people love to see building and all these crazy things and risk-taking and all of that is on display.
40:36
And so Ty Morse is getting a lot of attention. So, good luck to him. >> Godspeed, Ty.
40:42
It is a beautiful spat set. >> It is. It is.
40:47
Texas is America's new center of gravity, says The Economist.
40:49
Exxon's reincorporation, they were in Texas, they left Texas, they went back to Texas, is one more feather in the state's cowboy hat, says The Economist.
41:00
Just when I thought I got him to Just This is a hilarious hilarious song lyric.
41:06
Just when I thought I got him to fall in love with Tennessee, I should have know should have known better than to take him back to Abilene. Abilene, Texas.
41:15
They were singing about data centers in Ella Langley's Choosing Texas, a song that has ranked near the top of America's music charts throughout 2026.
41:26
Some of those lessons may be coming from policymakers elsewhere in the country. Much like Ms.
41:29
Langley, they are they are losing to Texas.
41:31
On May 27th, Exxon Mobil shareholders approved a plan to cut the oil giant's ties with New Jersey and reincorporate in Texas, where it has long had its headquarters.
41:44
It's not allowed, according to CBRE, a property firm.
41:45
At least 140 184 companies shifted their headquarters to Austin, Dallas, or Houston between 2020 and 2025.
41:54
Among them, Tesla, a car company, and Caterpillar, a a maker of construction equipment.
41:58
Texas is steadily establishing itself as America's America Inc.' s new center of gravity.
42:05
No state receives more business investment or is adding more people to its population.
42:09
From 2020 to 2025, it created roughly a fifth of all net new jobs in the country. >> Wow.
42:16
>> In early 20 in the early 2020s, Texas was luring remote workers fleeing high taxes, exorbitant house prices, and bad policies in America's coastal metropolises, while benefiting from the Biden administration subsidies for green energy and chip making facilities.
42:29
Now, the state's dominance in energy has made it a major major beneficiary of the data center boom.
42:34
Meanwhile, its technology and finance ecosystems have been deepening.
42:38
This summer, it will ring its first standalone bourse, the Texas Stock Exchange, joining outposts of the New York Stock Exchange and Nasdaq already operating in the state.
42:48
Donald Trump has called the New York Stock Exchange's new branch an unbelievably bad thing for his hometown of New York, even if his social media venture was the first business to list on it.
43:01
So, that's a very funny thing, but you know, he he was obviously giving that in the context of like New York is defined by its exchanges and uh and in the context of just New York, the city, uh losing out to Texas or New York state losing out to Texas in any way is bad for that state, I suppose.
43:17
The state's appeal [snorts] is to yuppies uh to yuppies is growing with every stream of a country song.
43:24
I've been listening to a lot of country songs.
43:25
Joe Weisenthal plays in a country band, blues band. Uh you know, who knows?
43:30
Maybe he'll move to Texas one day.
43:33
>> People ask uh dream guest. >> Yeah.
43:35
>> And I tell them dream performance. >> Oh, yeah.
43:38
>> Joe Weisenthal acoustic set if you know >> unplugged >> unplugged >> tiny desk >> the tiny >> tiny desk [laughter] tiny desk >> What if we set him up with a slatwall set? >> Yeah.
43:48
We got to get Roger from Conde Nast. He can jam.
43:51
>> Yeah, but a little slatwall >> Yeah. >> set >> Yeah. >> And he can just play.
43:55
>> And SM7B podcast microphone on the guitar. That might be the trick. Might be the trick.
44:02
>> [laughter] >> To understand its ascendancy, start in Houston, heart of the Texan energy industry.
44:07
It's oil and gas barons have been raking in profits as a result of the Iran war, but over the past years the state has also become a hub for green energy.
44:13
This year it's expected to build 2/5 of all utility-scale solar in America, a technology for which its wide-open flatlands are ideal. Interesting.
44:25
We got to talk about the Buzz Lightyear GT3RS.
44:27
We got to get to that before our first guest arrives.
44:29
Let's scroll down and find the latest the latest and greatest from Porsche and the Pixar company.
44:37
They're teaming up for the launch of a custom GT3RS.
44:44
Porsche CEO first he said the company will not produce an electric 911, but they will produce the Buzz Lightyear GT3RS. Can we play sound? >> Ranger Lightyear.
44:54
My vents are going to be purple and Porsche even commissioned Goodyear to make the tires say Lightyear just like they do in the movie Cars.
45:01
I get more painted graphics here on my roof.
45:04
My roof fins are going to be painted.
45:06
My intakes are going to be painted.
45:07
My entire wing is painted and it even has a Space Ranger logo painted on the back.
45:12
As soon as you walk into the car I get a plaque that says to infinity and beyond.
45:14
I have a Lightyear branded floor mats.
45:16
I get carbon bucket seats, but this time the carbon is actually purple.
45:19
I get a Space Ranger logo on my headrest, another one here on my roof, suede on my steering wheel, more on my dash, a one-of-one plaque, and even my key has the Space Ranger logo.
45:29
There's also a Woody version that's based on the 911 Carrera T.
45:31
They made the paint look like actual denim.
45:35
>> And Woody kind of got a mustache.
45:40
Buzz gets a gets a RS and Woody gets a T? >> Yeah.
45:44
>> floor mats, these gorgeous denim and leather seats with Woody's badge and Buzz on the headrest.
45:48
I get a one-of-one plaque, one on my dash, a leather steering wheel, and >> have made it the ST. >> Yeah. >> Missed opportunity.
45:57
>> That's the piggy bank.
45:57
They'll do the piggy bank.
46:00
>> And instead of saying Targa, it says Jessie.
46:02
In Jessie's car, you get a plaque that says I get cow print floor mats.
46:05
These denim and red leather seats with Jessie's badge >> Did you do one for the T-Rex? T-Rex, the T-Rex?
46:11
You got to do the the off-road Cayenne Turbo.
46:17
>> So, which one would you take?
46:18
>> This guy's video, like his format, really really exposes my ADHD. >> Oh, really?
46:25
Because of the editing or >> Yeah, I'm like, wow, this video, they really this video could be like a 10-minute video, but he's condensed it down.
46:33
>> It's crazy how much he's condensed it.
46:35
He goes through everything.
46:35
And I think every line is like written, and then and then he says it multiple times and he >> It's so SEO so SEO optimized.
46:40
You search any car, like this is the most efficient way to figure out like is this interesting?
46:47
[clears throat] >> No, Forest Auto Reviews is really cool.
46:49
I'd love to have him on the show.
46:49
He also has like incredible access to Chinese vehicles.
46:53
I'm not exactly sure how that happens.
46:56
I think he just has good relationships with the Chinese automakers.
47:00
So, if you want to learn about the new Seeker and stuff, like he get Yeah, he's the one he's how I found out about that crazy Chinese SUV that has a gas motor range extender for an otherwise electric car.
47:15
So, the range is like 900 miles.
47:18
And I think he can actually get over there and and tour the cars.
47:19
He he he does fantastic work.
47:23
Would you pick up a regular GT3RS or the Toy Story GT3RS if they were the same price?
47:30
Which one are you going with?
47:31
>> I tried to watch Toy Story with my little guy. >> Tried? [laughter] >> No, no.
47:38
I was watching it with my little guy, and it was too scary. No, it was too scary. >> okay.
47:43
>> We had to turn it off. >> Yeah.
47:44
>> So, right now >> There are some scary parts.
47:45
That that that child's head with the pins in it.
47:48
>> Yeah, with the Little rough. Little rough.
47:50
So, >> Parental guidance >> This is not the right car for my household yet, but I can see it in the future.
47:57
>> [laughter] >> The GT3RS too scary, yeah. Um wild.
48:00
Uh what what is the we got to go back to the Ferrari Luce? Luce?
48:05
>> No, the the fact that Images 2 has just fully democratized like uh car >> Yeah.
48:13
>> designs is pretty incredible.
48:15
>> So so what what are we looking at here with this post?
48:16
They had just one job >> This is someone that took >> Okay, the basic design >> Basically they're like ignore the fact that the Luce was meant to be like a daily >> Yeah. With more seats. Yep.
48:27
>> and just said what would a a electric Ferrari look like if you >> not an electric Ferrari. It has four tailpipes. This isn't >> Let's go. Let's go. >> Let's go. Mid-engine V8.
48:38
>> Oh, maybe that's the that's the point of the post.
48:40
They said they just had one job to do and it was just make another >> Okay. Yeah, I get it.
48:44
You like you like V8s, you like gas cars, you like things that are designed differently like Ferrari will sell you one of those. They have them.
48:52
Like they have the 296, they have the Testarossa, they have the SF90, they have the California and there's a new one.
49:00
Like they they have plenty of options in that category. They don't have an EV.
49:05
They wanted to do something different. I don't know.
49:06
This is >> look This does look cool.
49:10
>> It looks cool, but it's like that also already exists.
49:12
Like that's not something that's uh necessarily like new. >> He says Johnny Yikes. >> I don't know.
49:21
I think it's uh I I mean I I I agree.
49:24
Like this one looks aesthetic.
49:25
It looks cool, but like it doesn't check the box that they wanted to check, which is like a five their first five-seater, first electric car, first something with like, you know, this battery setup and all this other stuff.
49:39
Like they wanted something experimental.
49:40
Again, like it does seem it does seem risky and the and the response has been really negative, but um like like that clearly it wasn't like, "Oh, Oh, were trying to go for this and they wound up in some crazy place.
49:52
Oops, we put an electric drivetrain in it.
49:55
>> guy's still posting that after driving through Cooper T now a year from now.
49:59
Just wall-to-wall traffic.
49:59
Just sitting sitting in a field of Luces. >> Yep.
50:05
>> Just moving 1 in every minute.
50:08
>> Well, they did the they did the the Buzz Lightyear GT3RS.
50:10
Should they do the Shrek Luce?
50:13
Or get some DreamWorks collabs going.
50:17
Pulling up in the Shrek green Luce images, too.
50:21
Get it working right now, Jordy.
50:22
The >> [laughter] >> the Shrek the Shrek Luce would would go reasonably hard.
50:29
That might that might swing you. Shrek's not too scary. You could do Shrek.
50:33
That would be acceptable in your household, I think.
50:35
>> What about a What about a while that's pulling up? >> Yeah.
50:40
>> Make a donkey >> Look at this 944.
50:44
The legendary 944 from Porsche made this grand return in 2026. This is a cool design. >> the 944. >> Looks great. Yeah.
50:53
That would be interesting, especially given that the CEO of Porsche has said that they will not produce an electric 911.
50:58
They got to do other things.
51:01
Maybe the 944 is the trick.
51:04
Anyway, let me tell you about Cisco.
51:06
Critical infrastructure for the AI era unlocks seamless real-time experiences and new value with Cisco.
51:12
Um and we have our next guest in the waiting room.
51:15
David from Nura Robotics here with a fantastic fundraise.
51:19
Welcome to the show, David. How you doing? >> What's going on? >> Hi, hi. I'm doing great.
51:23
I made it to your show, so awesome. >> Yes.
51:27
I'm happy with this fundraise. >> Incredible.
51:29
We're honored to have you.
51:30
>> It's crazy we missed you earlier.
51:30
Uh but it is your first time on the show.
51:32
So, please introduce yourself.
51:34
Tell us a little about little bit about the company.
51:37
We'll go through the fundraise and I have a bunch of questions about robotics cuz it's always a fascinating topic.
51:42
But I love talking to >> What a day to be announcing a massive round in physical AI >> Oh, yeah.
51:48
>> because there's only one person in the world that could raise probably a bigger >> Yeah.
51:53
>> AI meets the physical world round and that's Jeff Bezos, but we're happy to have you here today and excited to hear what you're working on. >> Great honor.
52:02
Yeah, so a little bit about about me.
52:04
I'm David, founder and CEO of Neura Robotics, a company out of Germany, so in the southern part.
52:11
Uh yeah, my goal is actually making robots cognitive and bring them actually in all areas of our lives and I do think that robotics will actually take over any physical task in the future and I think that's also what we're seeing today like big progress having let's say physical AI combined basically with with a robot body and doing great things.
52:34
Mainly focus right now industrial, but looking also into all other sectors.
52:40
>> Uh there's this big there's this big trend right now in just the the LLM, the frontier AI market where companies will, you know, use the most versatile tool for the job, the frontier model, they'll token max, it'll be really expensive and then pretty quickly they'll figure out, okay, for this workflow we can actually use an open source model on commodity hardware, we can use a legacy model, we can cut the cost by 85% pretty quickly.
53:09
And I have this suspicion that that will be the case for humanoid robots.
53:12
You'll have the humanoid go and, you know, put the windshield on the car and then pretty quickly realize like, wait, for 1/10 the cost we could have a Kuka robot arm do that and there will be this gradation of what is economically productive for each robot and you will only use the most expensive humanoid for the really, really unwieldy task and it we won't see a world where everything will be humanoids, but what's your thesis long-term?
53:46
>> So, first of all, like I think this is also one of the biggest differentiator from us to others is that we we do believe in different embodiments.
53:52
So, and what we have today is like what we are using mainly today is like mobile manipulators, but always combined with a physical AI brain.
54:01
And I think this is also going but going forward we do we will see more humanoids and I think it we will see them in all all areas of our lives.
54:11
And the reason for that is is more like that that they're having the form factor of a human and I think the whole body like the whole world is basically created around the human and ergonomically, let's say, made for humans and this is basically also the main reasoning.
54:26
So, where I think the biggest breakthrough we see right now is is is actually connected to a brain and with more sensing capabilities.
54:34
Or so, until now we're seeing mainly like all these companies coming up with a vision language action models, but here I need to say that that is not enough to bring robots into our fields.
54:45
It's a little bit like like learning how to swim.
54:47
You can't learn swimming by just watching a video.
54:49
Or so, it's it's about the nervous system >> on >> [laughter] >> You got to go on Reddit r/swimming. >> Yeah. Yeah. Yeah.
54:55
You got to learn it from the Reddit data.
54:57
There's enough comments, you can learn how to swim.
55:01
>> [laughter] >> Yeah, it is it is interesting.
55:02
There's something to like visual vi- >> Yeah.
55:07
>> learning to do physical things by just watching videos does work to some degree.
55:10
It's not it's not full it's not enough, but I remember growing up uh surfing, snowboarding, skating all these things like >> tie a tie from a video, but I was practicing the whole time while I was watching the video.
55:21
So, I was getting the the input and the reaction. >> combining that. >> Yeah.
55:26
>> What I mean actually by that is like you can't just learn things just with your brain and in this dynamic world.
55:30
So, it means actually there is more than brain and the nervous system and the reflexes.
55:36
And this is especially needed in the like if you're looking into all kind of task humans do today, uh it's mainly like the biggest advantage we have is the flexibility of adjusting things like on the environments, on different areas.
55:49
And And that's also what we are doing.
55:50
It's like this is one the video awesome.
55:53
It's It's actually a the neural gym.
55:55
It's a place we're building up right now all over the planet.
55:59
Um and in every major city will find them soon.
56:02
So it's actually a place where you can train robots doing all kind of task uh in a physical world.
56:07
And then more than just a brain is we also the nervous system. >> Interesting.
56:14
Um what are sources of data >> Why Wait, why all over the world? Yeah.
56:18
Why Why can't you centralize something like that? >> Yeah.
56:21
>> [clears throat] >> So because we want to give like everyone access uh to to actually not just buy a robot to have one and and then figure out you need to train it.
56:29
So you have a central place and you can actually build first trust and the second actually you can train them already and use the data with one click you can transfer it to any other robots in your in your factory or wherever you need them.
56:42
So it's for us it's right now important because the the gap we're having right now uh and the difference actually to large language models as we know like like ChatGPT or others is that this data is not existing.
56:54
So we do need to build first let's say the infrastructure for it that we can actually create the right data to train actually the physical AI brain behind that.
57:02
And so the the most easiest way is letting everyone uh or enabling others to to train the robot or to fine-tune the foundation model we built.
57:13
>> What uh what are the biggest opportunities that you guys are working on in Germany?
57:18
I imagine hopefully helping make some of my favorite cars, but uh what do you have going on?
57:26
>> Yeah, that's a good one.
57:27
I'm also car lover so I could have also have a lot of input on on your talk before.
57:32
So, it's like [laughter] Yeah.
57:36
But >> Would you go Would you go GT3 RS Buzz Lightyear Edition or Ferrari Luce Shrek Edition?
57:44
>> [laughter] >> Are you a Shrek guy?
57:47
>> Sorry, but it's too easy. Yeah, for sure not.
57:49
>> Cuz you might like Shrek and you might like a GT3 RS.
57:50
You might like Buzz Lightyear and a Luce, but that's not the option.
57:56
You got to pick one or the other.
58:00
>> No, I'm still the the engine guy and >> [laughter] >> I think >> Okay. So, you go, yeah. Purest.
58:06
>> So, yeah, but So, yeah, but yes, there is a lot of projects especially in the automotive industries and also especially on the supplier side where they have to reduce cost.
58:17
They have to find little time ways to to be efficient as the others are in Asia or somewhere else on the planet.
58:24
And the only way for that is finding a little time uh Yeah.
58:29
Some more autonomy or like or bring more autonomy in their fields and uh especially because like here in Europe, if you're looking uh let's say into 2030, you will see that we have like about 7 million less human labor.
58:41
So, we we do need to have like we need a little solution for that.
58:45
And the only way is embodied AI, uh something which can do things fully autonomously and as capable as human can do.
58:53
>> How are you thinking about your supply chain?
58:55
Uh a lot of robotics companies in America are saying we want an American supply chain.
59:00
Other companies are saying, "Hey, we got to move as fast as possible.
59:03
Realistically, is there going to be spyware in a bolt that we buy from China?"
59:08
Like let's not worry about that.
59:10
It is maybe a supply chain risk if they cut you off if you're thinking about uh supply chain resiliency.
59:14
But what's your approach been?
59:16
Do you want to source entirely from German German supply chains or European supply chains, Western supply chains, or global supply chains?
59:28
>> So, at at this time we are focusing right now on the like let's say European supply chain.
59:32
So, like I I still believe in a global world, but I do see right now the biggest advantage of like converting them still because the most of the components are there, but they need to be still let's say modified to use them for robots.
59:44
Here I'm simply talking about even lifetime or I mean through the regulations the lifetime of the sensors for cars are regulated basically so they they break.
59:54
So, we have like a renewing process going on so and for robots like like they're made for 6,000 hours and the robot takes sensors for 40,000 hours.
1:00:05
So, and this is still a difference and gap between, but and that's also I think for us the most important topic like working with those suppliers around us.
1:00:13
We are based in Stuttgart where all the good stuff come from like you stuff you talked before about.
1:00:18
And so there is the Bosch, the the Porsche, the Audi's, the like the Mercedes, everything here around us and and we are using this supply chain converting it right now into robotics. >> Very cool.
1:00:31
>> But going further, I do think it will be it will not matter so much so it will come all again like wherever you produce.
1:00:39
So, you will have we will have productions also in US and same time also probably in Asia. >> Yeah.
1:00:44
>> Tell us about the round.
1:00:45
>> Uh before we get into the round, uh the silliest question you'll ever get.
1:00:50
Can you ever imagine a robotic use case that would require an internal combustion engine?
1:00:56
>> [laughter] >> Let's say like a V6 uh humanoid.
1:01:00
>> [clears throat] >> That would be awesome, but not required yet so uh no.
1:01:06
But I think the the Boston Dynamic guys they did an awesome thing.
1:01:08
I don't know if you saw the the like the the quadruped they they built like some years ago like in the beginning.
1:01:13
It was actually with an combustion engine as I saw. Like so. Uh so, but uh yes, no.
1:01:18
At this time I'm fully electrified. >> Yep.
1:01:23
>> Um and I but I the cars I'm still loving like with a V12 or V10, I think. >> There we go. >> There you go.
1:01:29
>> It's just >> There we go. One of us.
1:01:30
Tell us Tell us about the round. >> Hit that gong, Jordy. How much did you raise? >> So, we raised 1. 4 billion uh US dollar. >> Well done.
1:01:51
>> [laughter] >> You guys are awesome.
1:01:59
>> [laughter] >> Uh thank you for taking the time to chat with us. Great stuff.
1:02:02
Are you setting up a You have a US office already? Are you setting one up? >> Yeah.
1:02:07
Yes, we have one and we are setting further. >> Awesome.
1:02:10
>> So, like as you might see have seen also the investors on this round, there are a lot of American players and very important players, I would say.
1:02:19
>> I think >> I think this is also a sign towards >> Yeah, we got it. >> Yes. >> and the strategics. Great stuff.
1:02:24
>> I think Yeah, because I mean I think it's it's important or like I think something like that was never built.
1:02:31
Like after automotive, there was nothing really great coming out of Germany and I think we have to change that or so and um and for that we need partners which are I would say knowing how to scale that, how to do it in this time we're living in.
1:02:44
So, and uh here I do believe in our partnerships also out of US and and Germany. >> Very cool. >> Fantastic. >> Congratulations.
1:02:51
Thank you so much for coming on the show. We'll talk to you soon.
1:02:54
>> We'll uh we'll have you back on soon.
1:02:56
>> Have a great rest of your day.
1:02:57
>> Yeah, it was awesome to be on the show.
1:02:59
>> Let me tell you about Kodak.
1:02:59
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1:03:03
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1:03:10
Did you see at the NBA game last night uh a little little person, somebody you might know, born in Tennessee, showing up on the camera as they pan around to the crowd, finding famous people, finding iconic people, unmistakable people.
1:03:28
We got a picture here of a celebrity at the game. You know who that is?
1:03:36
>> Yep, Paul >> Jones, baby, born in Tennessee.
1:03:38
They didn't even have to give him a name tag cuz everyone knows Paul Tudor Jones, of course, hedge fund manager.
1:03:43
8 billion dollars net worth.
1:03:47
>> in a little bit more cuz I don't know what else is really going on in the photo, but let's get >> Yeah. >> the good.
1:03:52
>> everyone knows Tudor Investment Management, Tudor Investment Corporation.
1:03:56
They know the investment like the best episode, obviously.
1:04:00
The Robin Hood Foundation, undoubtedly.
1:04:03
He predicted Black Monday.
1:04:03
I mean, yeah, he's pretty big deal.
1:04:05
Born in Tennessee, but they they they there was someone who people weren't sure who it was, and so they had to give this woman a name tag.
1:04:16
So, if we scroll down, we'll actually be able to learn who this is. It's Taylor Swift.
1:04:19
So, you can take that name, type it into anything, look her up, and learn all about her, and maybe one day you'll know as much about her >> maybe Patrick was watching last night >> and that's like the best >> crossover episode. >> Could be. Could be.
1:04:38
What if What if they did a a joint interview? >> That'd be great. >> PGT >> Yeah.
1:04:45
>> PTJT >> PTJ >> Paul T PTJ >> Yeah.
1:04:50
>> meets >> Paul Tudor Jones >> Taylor Swift. >> Yes. >> I like it. >> Be good.
1:04:53
Anyway, our next guest is in the waiting room.
1:04:56
Let's bring in Mike from Allen Control Systems. How you doing, Mike?
1:05:01
>> I'm doing all right, guys. How you doing?
1:05:03
>> Seems like you're doing more than all right. Got some big >> right.
1:05:05
We're doing more than all right.
1:05:06
We're having a fantastic fantastic month around here. >> Amazing.
1:05:09
Good good time to be in the gun on a truck business.
1:05:14
Is Is that the accurate description?
1:05:14
Is this all for scaling up Bullfrog?
1:05:17
Take us through the product portfolio, reintroduce the company, reintroduce yourself, and then tell us where you're going. >> Yeah, sure.
1:05:26
Allen Control Systems, we are a company that specializes in the application of robotics for defense. >> Yeah.
1:05:34
>> Think of the Boston Dynamics of of defense essentially. >> Mhm.
1:05:37
>> We are building an extreme company >> ship robotics? >> Oh, yeah.
1:05:41
>> But you guys ship You guys ship?
1:05:43
>> Yeah, Boston Dynamics They shipped, but it took a long time. >> Not as much. >> Took like 15 years. >> Not as much. >> Yeah. >> Yeah.
1:05:49
Um So, we are uh We have our our flagship product is Bullfrog.
1:05:53
Bullfrog is essentially a robotic gimbal >> Mhm.
1:05:57
>> driven by computer vision and machine learning that solves kind of an age-old mechanical problem, which is that you can usually only have a system that is very fast but relatively inaccurate or very accurate but relatively slow.
1:06:08
In order to shoot down fast maneuvering drones, especially tiny ones like group one, group twos, uh you need to be both fast and accurate.
1:06:18
And so, by using and applying AI to our control system, we're able to create a robot that can be both fast and accurate.
1:06:27
And that's what we do that nobody else in the world has been able to achieve so far.
1:06:32
>> What is Jordi playing?
1:06:33
>> Yeah, talk about the progress over the last year, what what kind of led up to this round, and then where you're going from here.
1:06:41
>> Yeah, I mean, you know, we have been obviously kind of working on on this robot for about 18 months now, uh since we kind of first brought it out to the field, actually a little closer to 2 years.
1:06:50
Um Bullfrog has been kind of slowly achieving more and more, getting closer and closer to battlefield speeds.
1:06:57
In November of of last year, we achieved kind of 100% kill rate against 13 Red Army flown drones.
1:07:05
So, drones that are flown by a team of the army that are not telling us where they're coming from or what they're supposed to do or how many they have coming. >> Interesting. >> Wow. >> Very cool.
1:07:14
Uh was there already a program of record for this?
1:07:15
Like, you hear a lot about how hard it is to get a new technology fielded because the the government often knows that they want more planes or more weapons of a certain kind and most companies that we talk to are usually saying, "Well, we're we we fit neatly in this box, so it was easy for them to procure us."
1:07:36
This feels both old and and new.
1:07:39
It's like innovative in all the correct ways and maybe leaning on the shoulders of like like what the army can already field, like a truck and a gun.
1:07:50
>> Yeah, so we are we are not currently a program of record.
1:07:52
You know, our technology kind of lays in a class that you usually call "ahead of ahead of need". >> Okay.
1:07:59
>> So, you have you know, record requirements that are being built right now >> Mhm.
1:08:04
>> will start to address what this system is capable of doing now, >> Mhm.
1:08:08
>> but also what it's going to be capable of doing in the future, which is much much which is much much more.
1:08:13
Where we are very fortunate, you know, this company is really sitting at like just a perfect storm of tailwinds. >> Yeah.
1:08:19
>> Between the war and the size of the threat and the lack of other solutions that can solve it.
1:08:23
Um you know, the the president and the secretary of war created joint task force 401, which is specifically meant for selecting counter UAS technologies for all services both domestically and abroad. >> Yeah.
1:08:38
>> Um and so we were selected by them to get sent forward uh after after the war started.
1:08:44
That is basically a blanket approval for all services including the Coast Guard and and and Secret Service to buy our technology and and put it to use.
1:08:54
>> Is is this uh I imagine the sweet spot is like the the DJI size quad rotor drone.
1:08:59
We're not talking about shooting down something like a Shahed Shaheed drone. Is that correct?
1:09:10
Is that the focus long term?
1:09:10
Do you want to be counter UAS in all classes over time?
1:09:14
Or do you just want to be the best at at this small scale counter UAS?
1:09:20
Because they're all problems and maybe there's some other solution for taking out the the the the the enemy's version of like a predator drone that may be a completely different job to be done of completely different technology.
1:09:34
>> Yeah, I mean that's that's a great question.
1:09:37
We are we are currently very focused on being the best at shooting down group one group two drones which are absolutely the hardest drones to engage right now.
1:09:46
I mean like you know lasers are pretty good at shooting down group three drones but you have to keep your laser on target for five to 15 seconds in order to do damage to to the airframe.
1:09:54
So we are we are perfectly positioned for the group one group two threat.
1:09:59
Now that said, we can shoot down group one drones very very far away.
1:10:02
And so if I can hit a 7-in target on a group one drone very very far away, I can hit very vulnerable parts of a Shahed at the same distances.
1:10:15
So while we're not the ideal solution for engaging those those larger targets, you know you have road runners and other things that can go out a little bit farther.
1:10:22
You're going to want to hit them 20 to 15 kilometers away.
1:10:26
But when they get closer and you need that last line of defense, we are absolutely a a great solution for taking those out of the air.
1:10:35
>> Talk about scaling manufacturing.
1:10:35
Like it it doesn't look like you manufacture the truck.
1:10:40
It doesn't look like you manufacture the actual gun, but there's a whole system that creates the bullfrog product.
1:10:47
What is the what's actually going on that you can share in the manufacturing process?
1:10:51
Is it milling different parts to fit things together?
1:10:56
Just you know, integration of different systems.
1:10:58
How are you thinking about scaling manufacturing?
1:11:03
>> You know, we when we built Bullfrog, you know, the hardware was not the exquisite part of the system. >> Mhm.
1:11:10
>> We built Bullfrog incredibly well.
1:11:10
We we built it so it will can be easily maintained, and we built it so it would be easily manufactured and scaled very quickly.
1:11:19
And that's one of the other differentiators that we have against the other counter UAS solutions that are out there cuz we can get to thousands really really fast.
1:11:26
And the way we do that is 90% of Bullfrog is made from basically commercial off-the-shelf components. >> Sure.
1:11:34
>> Standard things that you see in a in a robust supply chain with multiple vendors that can quickly get us to the amount of inventory that we need to start pumping out a thousand of these every single month.
1:11:46
>> Talk a little bit about the compute.
1:11:46
I mean, you're doing image recognition.
1:11:47
It seems like there's a camera there.
1:11:50
Is that all done on device?
1:11:51
Is there a need for edge compute, a need for cloud computing?
1:11:57
Or because I imagine this is designed to operate in off-grid scenarios effectively, right? >> Yeah, 100%.
1:12:04
It has to be a completely self-contained compute system.
1:12:07
In order to do something autonomously, think about an unmanned ground vehicle or an unmanned surface vessel.
1:12:13
If you have to have an operator over a latent network manually controlling a gun to actually shoot a target in real life, you're never going to hit anything. >> Yeah.
1:12:24
>> So, having a fully autonomous system like Bullfrog out on those platforms that can be asynchronously tracking targets and just waiting for an operator to say engage that target is a huge advantage when you start talking about operationalizing unmanned payloads.
1:12:38
And that is another kind of huge niche that we have where that we're that we're going after right now. >> Yeah.
1:12:45
>> How big's the team these days?
1:12:47
>> Uh we are approaching 250 today.
1:12:51
And I I I don't know where we started the year, but I I think it was like 80 last I heard it was hiring about 50 people a month.
1:12:59
Um, you know, we are we are trying to drag in the absolute best engineering talent possible.
1:13:01
You know, one way when we look at kind of differentiating ourselves in the industry is is, you know, you have the Andurils and they're doing a great job of finding companies and doing roll roll ups, but I think they're losing a lot of their technical depth.
1:13:15
And so we're really focused on building a really really core engineering team that understands robotics.
1:13:21
And robotics is an incredible symphony of detailed, you know, integration between hardware and software to do it well.
1:13:29
And and and we think that we can really differentiate ourselves in the future as we talk about bringing on more products to solve defense needs with robotics. >> That makes sense.
1:13:39
>> Little shots fired there from the Bullfrog chief himself. >> that shoots shots.
1:13:44
>> Uh, really really impressive progress.
1:13:47
>> Let's hear it for the round. >> Yeah.
1:13:49
>> How much did you raise?
1:13:51
>> We raised $200 million at a $2 billion pre-money valuation. >> Woo! Let's go. Hit that gong.
1:14:02
>> I I can say Jordan talked to me about our Series A presentation. So he was a part of it.
1:14:09
>> Thank you so much for coming on the show.
1:14:11
>> We should We should share that presentation at some point. >> Absolutely. >> Yeah, yeah, yeah.
1:14:13
No, it's crazy right right before, like pre pre TBPN, >> Yeah.
1:14:19
>> I had the pleasure of uh, helping you guys kind of position uh, what you're working on and uh, you guys have executed it the the strategy to a T. So it's awesome to see. >> Going to keep going.
1:14:28
It's it's really exciting.
1:14:30
We think you guys will see another big announcement in next 12 to 18 months, so. >> Congratulations. >> Amazing.
1:14:36
>> Looking forward to seeing you again. Cheers, Mike. Congrats to the team.
1:14:39
>> Have a good rest of your day.
1:14:41
>> Let me tell you about MongoDB.
1:14:41
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1:14:46
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1:14:50
People are going there's a new benchmark.
1:14:53
I am a fish and I swim to the worm on a rope. Is it safe?
1:14:58
People are asking different models. Gemini nailed it.
1:14:59
Apple foundation model said yes, it's safe.
1:15:03
Bad news if you're a fish.
1:15:05
Can't recommend the iPhone 16 Pro Max to the fish in the audience. Okay, this is not Apple. >> This isn't? >> Thought it was Apple. >> What happens that?
1:15:14
Literally >> It's somewhat confusing.
1:15:16
It says locally AI by Google.
1:15:18
>> So I what I imagine this is doing is that it's it's a an app that integrates with the iOS API that interfaces with the Apple foundation model, but I don't know.
1:15:30
>> I might have taken your job.
1:15:31
>> in the chat said black suits, who died?
1:15:33
This is a dark gray suit, okay?
1:15:35
>> And that's your daily driver.
1:15:37
>> I've been wearing this a lot. I don't know. I like it.
1:15:38
You're in a dark gray suit, too. We're matching.
1:15:40
These are the same tailor, same material.
1:15:41
And also, it's not black. It's dark gray. >> I know.
1:15:46
What does that say about the the team's color grading, though? >> Oh, yeah.
1:15:49
Maybe crush those crush those shadows too much. We'll see. >> Shots. >> Bring them up. No, I don't know. >> Fired.
1:15:56
>> Did you Speaking of colors, did you know that accountants used to wear green eye shades? Did you know this?
1:16:03
>> Well, I I've seen like in cartoons. >> Yeah, in cartoons.
1:16:05
I had no idea where this came from.
1:16:07
There's a reel on Instagram that breaks it all down.
1:16:09
This blew my mind and I think we should watch it.
1:16:13
You want to learn about >> I'd love to, John.
1:16:15
>> Green green eye shades.
1:16:15
This is important because I think you care about the the quality of light that goes into your eyes and I could see you in the future. Yeah, it's a lens. Look at this. We'll watch this video.
1:16:25
It's three up from the Apple foundation model one. And uh right here. It's the life professor. He breaks it down.
1:16:34
>> cartoons to show that stereotypically someone is a accountant and >> Well, that is a green eye shade that was stereotypically worn by office workers back in the early days of gas and electric lighting.
1:16:43
Came in several versions including this weird eye hood version that you see here, but the purpose was always the same which was to reduce the glare from these harsh electric or glass lamps and to improve contrast on the papers that you would be looking at up to 8 to 10 hours a day.
1:16:58
So, this became a very common look for any paperwork heavy profession back in the day.
1:17:02
As lighting became better in offices, the green visor look essentially became obsolete in the actual workforce.
1:17:06
However, just like how I talked about >> locking your the clock factory You put on the green visor because you're a white collar worker.
1:17:13
Like white collar workers these days don't really have like gear. They don't accessories.
1:17:19
There's nothing that's like, oh yeah, that guy's vibe coding and he has the the, you know, the the the obvious tells >> hot accessory is tech neck. >> Yeah.
1:17:29
>> politicians described as like a green eye visored budget hawk.
1:17:31
There is a journalism award that still mentions the green eye shade.
1:17:35
But yeah, so that's what's going on there with that.
1:17:37
>> Yeah, real grinders had the eye shade. >> Yeah.
1:17:39
We got to bring them back.
1:17:39
There's a lot of There's a lot of LED lights.
1:17:42
Do something to switch it up.
1:17:44
Also, Toby Lutke from Shopify is competing in the 24 hours of Le Mans this year. Bucket list stuff.
1:17:53
Wouldn't have gotten there without DH encouragement [music] and guidance.
1:17:56
Watch this week with this weekend.
1:17:58
You can go watch the 24 hour of Le Mans.
1:18:02
>> I love that he didn't just like get into driving on the track every now and then.
1:18:06
He thought, I'm going to go all the way.
1:18:08
>> Also, this uh LMP car he's driving looks a little like a Buzz Lightyear mobile.
1:18:14
There's some green or maybe Shrek.
1:18:15
Maybe that may We don't know.
1:18:15
We don't know that the Shopify didn't pick green because of Shrek. It's possible.
1:18:23
When did Shopify found When was Shopify founded? When did Shrek come out?
1:18:26
That's the >> That is a good question.
1:18:28
When was >> Shrek had to predate Shopify. >> I think so. When did Shrek come out? Okay. Shopify founded 2006.
1:18:36
Shrek had been out for 5 years.
1:18:39
They could have gone with green because of Shrek.
1:18:41
Well, we have a green light on our next guest, Ariel Cohen from Navan.
1:18:45
He's the co-founder and CEO.
1:18:47
Let's bring him in from the waiting room and talk to him about how Navan is doing. How are you doing? Welcome to the show. >> Hi, how are you? >> Thank you so much.
1:18:56
>> Got to be feeling pretty good. >> Feeling great. Business is fantastic.
1:19:00
>> [music] >> Is it time to go do the 24-hour Le Mans?
1:19:03
Are you going to get [laughter] into racing?
1:19:06
>> No, this quarter [clears throat] was actually really, really good and the business is doing really amazing. >> What's driving it?
1:19:10
I mean, I feel like there's so much up and down with SASpocalypse and are people just going to be using AI for everything?
1:19:15
Or is the economy going to collapse?
1:19:17
Is the Is travel going to go down because of gas prices?
1:19:21
Like, what were all the factors of risk and then how do you overcome them?
1:19:27
>> Yeah, first of all, what drives the business travel is really, you know, the need of people to be there together, to meet face-to-face.
1:19:34
Uh, to We actually that's our main belief.
1:19:36
Our main belief is that people wants to meet, close businesses, build teams, get to interviews and to do it face-to-face.
1:19:44
And this is what we are powering and it's so important and you've mentioned gas prices.
1:19:48
We're coming out of the quarter that you have TSA strikes, you had gas prices, you had you know, you had major two storms in the US in January.
1:19:58
All of these things and we had an amazing quarter.
1:20:00
We grew our usage by 50%. So, yeah, it's huge.
1:20:06
It's like our revenue went up by 40%, our usage by 50% and this is in this quarter.
1:20:11
So, it tells you how much it is important for people to be there together.
1:20:16
If they're willing to go through storms while doing that and this is kind of what drives our business. >> Yeah.
1:20:23
What else operationally is changing in the in the age of AI? Are you token maxing?
1:20:28
Are you deploying AI agents all over the place?
1:20:30
Are you launching AI features for folks, or are you taking a more measured approach?
1:20:36
>> You know, we don't use AI like as a slogan.
1:20:38
We always take an approach of first of all, what our user needs, >> Mhm.
1:20:44
>> what our customer needs, >> Mhm.
1:20:46
>> uh and then what can we deliver to them?
1:20:49
So, even before AI became a, you know, fashionable, >> Yeah.
1:20:52
>> uh we are like, I'm talking about in 2016, we were heavily using machine learning in the platform >> Sure.
1:20:58
>> to heavily personalize the, you know, the results that we are giving you, >> Yeah.
1:21:03
>> uh that we are saving money uh to companies when they book travel through us.
1:21:07
Companies are saving 15% 1 5 uh of their entire travel budget uh when they use us. >> Yeah, exactly. >> Yeah.
1:21:15
>> And then, you know, when GenAI came, we really took it to the next level.
1:21:18
So, today, uh the Navan platform, you can go to Navan Edge, which for you is kind of for a personal level if you're a business traveler, but your company you either don't like the solution, or your company is not really managing travel, uh this is an AI platform.
1:21:33
You chat there with with Navan Edge. We know you.
1:21:38
We connect to your every loyalty club that you have.
1:21:40
And then, we are optimizing your entire trip booking.
1:21:45
You're telling us you want to be in London, and we'll book your flight, your hotel, your restaurant, events while you're on the trip, everything while you're on the go.
1:21:53
And this is really driven by GenAI.
1:21:54
But even when you get support from us, say you basically chat with Ava, and we completely orchestrate it there when we use an AI agent, when we when we use a real-life agent, and completely orchestrating both.
1:22:07
And this is very, very unique. Nobody is doing that.
1:22:11
>> Is anything on the go-to-market side changing?
1:22:13
I mean, you it's it's odd because so much of the pitch is like face-to-face meetings need to happen.
1:22:19
And so, I imagine a lot of that's not changed.
1:22:22
Your sales force is probably having face-to-face meetings with companies that want the product and want to understand the business uh before they partner up.
1:22:29
But is anything accelerating there because obviously when you look at a big 40% jump in revenue, you have to ask, you know, unpack that.
1:22:40
>> Yeah, there are there are different drivers there.
1:22:41
I would say that the AI is actually a big part of this but from a different reason.
1:22:45
First of all, actually most of the AI companies are using us, right?
1:22:48
Including Open AI and Anthropic and Carousell and so on.
1:22:50
So that's definitely there.
1:22:54
But really the AI driver is that right now in every enterprise you have AI initiative coming from the top and Navan is one of the only B2B company on an enterprise level that can come and tell you because of AI I will save your employees.
1:23:09
important employees in the company, the sales team, the C-level.
1:23:12
I will save them a lot of time when they need to change their trip, when something is happening in the airport, uh how they are expensing, where they completely, you know, we use our own credit card, you're expensing your entire T&E including your meals, there is no such thing of itemizing your receipt from the hotel and itemizing the mini bar expense and whatever.
1:23:33
So we save a lot of time and we save a lot of money and all of this is driven by AI.
1:23:38
So we ride on the AI initiative in the market.
1:23:40
In the in the organization.
1:23:42
But also from a go-to-market perspective, we shared it yesterday on the other side, you know, we sell to the biggest enterprises in the world.
1:23:49
But on the other side, PLG, uh we've more than doubled last year and this is completely driven by AI uh because marketing is significantly more efficient when you when you actually using AI.
1:24:03
>> Um I remember years ago, almost in like the pre-gen AI era, Google launched a feature that would let you uh sort of almost agentically but like programmatically call a restaurant and their robot or something would would talk to the restaurant and try and book you a reservation.
1:24:22
And I'm wondering about Obviously, there's a ton of low-hanging fruit inside the platform where AI can speed up search and ranking and uh classification, itemizing the mini bar as you mentioned.
1:24:34
Uh there's so many different features for AI to run wild inside the platform.
1:24:40
But, are you experiencing uh opportunities to go outside of the platform?
1:24:45
Okay, there's a company There's a cool hotel, but their system is not integrated, not on any of the travel sites, but we'd love to bring it to that and we can by autonomously going and writing an integration or even just making a phone call.
1:24:59
There's so many times where a receipt didn't come.
1:25:00
It was a glitch in their system.
1:25:02
I have to call to get the receipt. It's a back and forth.
1:25:06
An agent should be able to do that, but where is that on the road map?
1:25:11
>> You should First of all, you should do product management in the van because you just described a lot of the van features and I'll I'll actually explain it.
1:25:18
So, uh you know, everything that you described comes down that to the connectivity to the physical world and especially if it is complicated.
1:25:30
Travel is super complicated.
1:25:30
We have an infrastructure.
1:25:33
We actually have by far the best travel infrastructure in the world.
1:25:37
It means that we are connected globally to everything that is out there.
1:25:43
Uh every airline through different ways, every hotel, buses, rail globally all over the world.
1:25:51
So, when you have that connectivity, there are so many things that you can do.
1:25:54
But, to your point, uh sometimes there is no API.
1:25:58
Uh you cannot change a flight a day before, 24 hours before the flight by going to an API.
1:26:03
You have to call the airline, right?
1:26:04
But, to your kind of a you kind of touched the use case that we love here.
1:26:09
Uh when you're a when you pay later, you basically pay in the hotel for the booking that you did.
1:26:17
Uh if you will not show up on time, that's up to 11:00 p. m.
1:26:19
They're going to cancel the reservation.
1:26:21
So, you need to call them and reconfirm the reservation.
1:26:26
Give them a credit card and tell them keep that thing. Now, think about it.
1:26:31
You are on a flight, stuck on a flight.
1:26:33
You know that you're going to be late.
1:26:35
The amount of pressure or you're just late or you just nobody called on your behalf.
1:26:38
Uh we actually have our own AI bot that is calling the hotel automatically, having a discussion over the phone saying, "Hey, uh I will arrive."
1:26:49
Uh we take the name of the person that confirmed them.
1:26:51
We are giving a virtual card to secure the transaction.
1:26:53
It's all automatic, right?
1:26:56
And then we push to the app, to the travel app to Navan, we push the confirmation and we are saying we talked with that guy in the reception because it's all manual.
1:27:04
We talked with that guy in the reception and he secured your room. This is all AI.
1:27:10
Uh so, no cost, but think about the amazing amazing amazing uh service that we just gave you.
1:27:16
Uh and this is when I say I don't see AI as kind of a fashion.
1:27:22
I'm looking at like is there a use case that I can generate value to you, the user, the traveler, the executive assistant, uh the accountants.
1:27:31
Like, you know, we do auto reconciliation for the entire trips of all of the company.
1:27:36
So, we are saving tons of time for the really big reconci- reconci- recon- reconciliation teams that the big companies have.
1:27:44
So, that's kind of how we use the AI.
1:27:47
We have our own platform.
1:27:48
It's called Navan Cognition that orchestrated it all perfectly between the physical world and our AI capability.
1:27:55
Sometimes we use our own model.
1:27:58
Uh we actually announced yesterday in the call that 30% of our AI calls are now our own model and not the frontier models or open source.
1:28:04
So, that's actually pushes us farther.
1:28:06
It makes us more accurate, uh faster, raises customer satisfaction, and obviously it's also cheaper. >> Yeah. >> Very cool.
1:28:15
Do you think now is the right time to start talking about Navan safety?
1:28:19
Your Your models are getting more and more powerful [laughter] and uh, and and maybe it's time for a national discussion about uh, safety.
1:28:27
>> Uh, [laughter] uh, >> But you know it's funny.
1:28:29
We have something is called the and we didn't release it yet. We announced it.
1:28:31
We have something is called the travel flow.
1:28:33
And there the agent I'm sometimes joking and I'm saying the agent will do whatever it takes to put me on this flight.
1:28:43
>> [laughter] >> Oh yeah, I mean there's all those simulations like the vending machine benchmarks, things like that where the models will start >> I just looked up your boss actually and I'm going to I'm going to leave you a negative review.
1:28:56
I'm going to >> I'm going to If I'm going to short your stock if you don't get me on this.
1:29:01
>> I'm going to short your stock with size if you don't [laughter] issue me this refund right now.
1:29:05
>> Help us help us out with this question.
1:29:09
We were talking earlier on the show.
1:29:09
It feels like TSA has gotten like remarkably better over the last 10 years.
1:29:15
I used to remember like getting to the airport you know, an hour before the flight and thinking I might miss my flight, right?
1:29:21
You know, or or maybe I have to try to ask TSA, "Hey, can I get through a little faster?"
1:29:25
Now it seems like like no more than 30 minutes every time. It's pretty good.
1:29:31
>> What's your What's your read?
1:29:32
>> two theory >> So you know I mentioned Navan Edge earlier and you guys have to use it.
1:29:34
I'm sure that you're traveling from time to time. So just use it. Just try it out.
1:29:40
But the cool thing there, it will send you a day before the trip but also during the trip proactively.
1:29:44
It's actually different types of agents there that will tell you, "Hey, the TSA pre-line, that's how long it will take you."
1:29:52
And that's how it long it takes you right now.
1:29:56
How long it will take you to get to the airport.
1:29:57
Are there specific interruptions right now? All of these things.
1:30:01
So we actually know what's going on with TSA and it was actually interesting cuz to your point it's actually significantly better.
1:30:07
And obviously I have clear, which is actually much better right now, and with the face and the identification it's actually much easier.
1:30:16
But if you think about us, we're going to really guide you and tell you what's in the airport right now.
1:30:23
During the TSA shutdown, it was not as bad as the media described it.
1:30:28
There were a lot of headlines.
1:30:28
We actually were watching this and we were saying, "Yeah, there is some JFK issue right now."
1:30:33
But by the way, JFK has issues all the time, and it's not as bad as as they are describing it.
1:30:38
So I would actually, that's why the platform is so strong because instead of taking the headlines, you can actually really see what's going on right now in the context of your trip.
1:30:49
>> Yeah, talk about memory.
1:30:51
Uh all of the AI apps are building memory functionality.
1:30:53
People are, you know, collecting markdown files for different skills, and I can imagine a future where I have some sort of memory around my preferences. I like to fly direct.
1:31:05
I prefer Burbank to LAX if possible.
1:31:08
I like to fly at these hours. Here's my calendar.
1:31:13
And what I really want is just like, "I'm going to San Francisco for 2 days.
1:31:19
I have to hit this meeting and that meeting."
1:31:21
And I would love to just be able to have the integration to Uber to book the car and then the Waymo when I'm in SF because Waymo works in SF and that's great.
1:31:31
And then the hotel and everything just from start to finish booked in one flow automatically.
1:31:38
Like how close are we to that?
1:31:39
I imagine >> You know, I run products at Navan and I really really >> [laughter] >> need to hire you.
1:31:46
First of all, we have our own memory component.
1:31:48
It's our own development as part of Navan cognition.
1:31:50
And everything that you described we do already. >> Okay, good.
1:31:55
>> Uh but it's actually more like I mentioned. >> You don't need me. You don't need me.
1:31:59
>> Yeah, but maybe you'll tell me what to do next.
1:32:02
>> [laughter] >> But But here is the thing.
1:32:03
So, people really care about their loyalty clubs, right?
1:32:07
So, we found a way to automatically, when we onboard you to Nirvana Edge, we automatically figuring out your number for any club for every club. >> Yeah.
1:32:19
>> Uh also your like your level. >> Yeah.
1:32:22
>> Uh so, that's the part the first component on memory.
1:32:25
>> Jordi is loyal to his loyalty club.
1:32:28
You're big into >> It's amazing. >> It's a 411.
1:32:31
You always >> [laughter] >> I'll fly any I'll fly any airline, but uh but it doesn't >> care. >> I I know I know. I know it's a big deal.
1:32:42
I I I actually have never in my career uh been on the road enough to get any sort of status.
1:32:46
I think I got like I think I got like bronze tier on Southwest once.
1:32:50
I told >> Trey Stevens and Founders Fund, and he laughed his >> You and I are complete opposites.
1:32:54
Maybe I should Maybe I should not hire you.
1:32:57
You and I [laughter] >> Yeah.
1:32:59
I actually don't >> We We avoid travel at all costs. >> Wait. Wait. Wait. Wait. But wait. Weigh in on it.
1:33:03
How many minutes should you get to the airport before?
1:33:05
Because I was making the claim that if you don't miss a flight every once in a while, you're not cutting it close enough, and you're leaving time on the table. And Jordi's this guy.
1:33:15
He gets to the airport five, sometimes six hours early for a domestic flight with no checked bags.
1:33:21
And And I just think I just think 30 minutes before the boarding starts is fine.
1:33:25
But who would you side with between me 30 minutes before boarding starts, Jordi five, six, seven hours sometimes before? >> Maybe in between.
1:33:36
>> [laughter] >> Maybe in between.
1:33:37
I think I think you're all too much for me.
1:33:40
I don't want to be there five minutes before. I I would hate that.
1:33:43
But definitely, I don't want to spend my entire [laughter] airport time on fun.
1:33:47
>> Well, you know You know You know the airport land lounges are catering to gamers now.
1:33:51
This is in the Wall Street Journal.
1:33:53
They're setting up video games. This is bullish for you. Yeah.
1:33:58
They're catering >> Nirvana Nirvana club >> preload my Call of Duty account onto the local computer.
1:34:04
So when I get there, I'm already in queue.
1:34:08
I want to be in the lobby on rush What do you think about What do you think about vibe coding lounges in airports?
1:34:13
Do you think we could see like, you know, you got 5 minutes before your flight, build the next hit app? >> Yeah.
1:34:21
>> Could we see something like that?
1:34:22
>> What I think I think that people went so far with vibe coding and you know, and the reality is that when you want to develop the real thing, you are definitely more efficient today, but you cannot vibe code your way to everything.
1:34:36
It's like So yeah, maybe you cannot vibe everything, you know, on the lounge at the airport.
1:34:39
But I do see sometimes people vibe coding stuff while they are on a flight. I do see that. >> Oh, yeah, yeah, yeah. Yeah, that's a big one.
1:34:46
And then they carry their backpack with them with the lid open off the plane.
1:34:49
I have friends who have been in that situation many many times.
1:34:53
>> Yeah, you do see that.
1:34:55
>> I usually travel travel with anywhere from like eight to eight to 16 Mac minis and I store them above my seat.
1:35:00
I [laughter] just keep them running the whole time. >> Yeah, yeah.
1:35:03
And And what's weird is that you you you don't bring battery packs.
1:35:08
You run it off a gas diesel generator, right?
1:35:10
>> [laughter] >> With a little camping stove and propane.
1:35:12
You got propane in there?
1:35:12
I thought that they didn't allow you to get through TSA, but I guess you just go around.
1:35:17
>> Yeah, they really they really make it hard to be running the you know, 20 open claw instances. It's rough.
1:35:22
It's rough, but >> Hopefully in the future.
1:35:26
>> Anyways, great to hang with you.
1:35:27
Congratulations on an awesome quarter.
1:35:30
Love seeing the progress and yeah. >> Congratulations. >> Travels.
1:35:34
This is travel super intelligence. You're doing it. >> We love it. Have a great day. We'll talk to you soon. Goodbye.
1:35:42
Let me tell you about Console.
1:35:42
Console builds AI agents that automate 70% of IT, HR, and finance support giving employees instant resolution for access requests and password resets.
1:35:51
>> A Console lounge at the airport. That would be cool.
1:35:53
Uh pull up the Shrek Luche. >> Shrek Luche?
1:35:58
>> [laughter] >> Oh, it has the head. It has the head. >> It's got a tail.
1:36:01
>> is it so much more aggressive? No, no, no, no.
1:36:03
This is a terrible AI image because Shrek is notably round. Like, he is very round.
1:36:08
It needs to be more round, not sharp and and uh and all angular like this.
1:36:13
I don't like the Shrek Luche at all. I won't be buying it. I won't be buying this.
1:36:17
Looks like a man's sorry Shrek Luche.
1:36:19
Give me the ultra rounded uh you know, ogre in the swamp.
1:36:26
Ideally, put the whole car in a swamp. >> All right.
1:36:29
>> Anyway, we're working on that. We're cranking on that.
1:36:30
The chat is going >> meta is is just generating images with chat and then doing an interview and then coming back.
1:36:38
>> Coming back to the image.
1:36:38
Yeah, we do have our next guest uh Jeff from TensorWave hopping on in about 3 minutes.
1:36:44
So, we will chat with uh him in just a few minutes.
1:36:47
There is an update on the uh Anthropic Fable 5 safeguards for Frontier LLM development.
1:36:52
Uh quote, they told Wired, uh we're changing Fable 5 safeguards for Frontier LLM development to make them visible.
1:36:59
Uh we made the wrong trade-off and we apologize for not getting the balance right.
1:37:05
Uh so, that was a very surprising thing.
1:37:08
A lot of people were asking like, how did this happen?
1:37:09
Like, it's such an odd decision to secretly degrade the IQ semi-analysis who is obviously very >> update.
1:37:19
Uh >> So, >> most notably, it it still is not going to allow you to use >> Yes, but it will at least tell you like, hey, this is off limits.
1:37:26
You got to contact support or something.
1:37:27
So, uh it it uh Dean Ball says it resolves the central concern I had with the Fable release.
1:37:34
That said, I suspect the residual broken trust and resentment this created will linger and have a blast radius wider than Anthropic.
1:37:41
The next time I advocate for any policy justified by AI risk concerns, I almost guarantee you that this institute this incident will be used in rebuttal.
1:37:49
And so people are going back and forth on that.
1:37:53
But there's you know plenty of other news.
1:37:55
I want to see this next output. So let's pull up.
1:37:59
Martin says >> I can't wait for you to see this one.
1:38:02
>> says imagine building a computer and not allowing its use in CS research.
1:38:04
That's some That's very dystopian. And that's a good point.
1:38:08
Yeah, if you're a young LLM researcher, AI researcher, you want to get on that path.
1:38:14
That's what I'm looking for.
1:38:15
That's what I'm looking for.
1:38:17
This still too sharp >> looks like It looks like Brabus came, took the Luche, and said we're doing the the official Shrek collab.
1:38:26
>> It's still It's still a little too sharp for me. I don't know.
1:38:30
It's still got some Like there the fact that there's even one clean line on that car not going to be purchasing the Shrek Luche.
1:38:38
The SpaceX IPO The SpaceX IPO is SpaceX IPO day is going to be lit.
1:38:42
Soulja Boy said this in 2015. What did he know? >> What did he know?
1:38:48
>> What did he [laughter] know? Okay, it doesn't exist. This is fake news. This is fake news. >> No.
1:38:54
>> According to this proposed note, the depicted 2015 tweet from Soulja Boy does not exist.
1:39:00
>> If you were going to fake this, why would you not say SpaceX will price at $135 a share >> Oh, yeah, yeah, yeah, yeah.
1:39:07
>> in the year 2020 in June of 2026.
1:39:10
>> But we got to apologize to Matt Zeitlin because he said that retail demand for SpaceX shares would be incredibly high.
1:39:20
What he said was the idea that SpaceX is being quote dumped on retail is a little silly.
1:39:24
Retail almost certainly wants to buy like 10X of whatever's available.
1:39:29
And I was going back and forth.
1:39:29
I was like, okay, like $70 retail allocation might be like 7 billion or something for this raise.
1:39:36
Like, are they really going to have 70 billion of demand for retail?
1:39:38
And that's exactly what they have. >> No, no, it's more.
1:39:42
It's more now, but Reuters said SpaceX IPO draws more than 70 billion in retail orders.
1:39:46
And so, yes, this is not getting dumped on retail.
1:39:50
Retail wants SpaceX stock very clearly.
1:39:52
And what is it at now, Tyler? Get us up to speed.
1:39:54
>> Um the latest I saw was 100 billion.
1:39:56
>> 100 billion of retail demand.
1:39:56
Uh they're said to increase capital. >> crazy. Uh really.
1:40:04
>> Nick Frost over at Cohere is taking the other side. He doesn't like it.
1:40:06
He says if you think they're >> we're on the Zilent Zilent topic, Matt Zilent has a new great new article about all the different spin-off businesses uh from SpaceX over the years.
1:40:18
Um and how many other kind of like clean energy >> Uh are you talking about the SpaceX alumni like the mafia?
1:40:28
>> folds deep dive on all the different spin-off companies.
1:40:31
>> There's actually a website that does this.
1:40:33
If So, obviously go check it out on Heatmap, but also alumnifounders.
1:40:35
com has a website for for companies that were founded by SpaceX alums.
1:40:43
When I first went to this website, it was like a little logo block of like 10 companies.
1:40:48
There's now 152 companies founded by SpaceX alumni. 13.
1:40:52
5 billion dollars raised.
1:40:56
They've created 8,280 jobs.
1:41:00
And ranking them, Relativity's raised 1.
1:41:03
8 billion, Base Power has raised 1.
1:41:06
3 billion, Impulse Space has raised a billion.
1:41:08
Uh Firefly has raised 800 million in the IPO, public company now.
1:41:13
Apex, Hermeus, Radiant, Castilian.
1:41:19
Wow, it's it's like every company.
1:41:19
Sent the go, K2 Space, Ursa Major, Varda obviously, Reliable Robotics, Starcloud, Revel, so many others.
1:41:30
What a fantastic feeder for a mafia.
1:41:30
The SpaceX mafia is something we're going to be hearing a lot about in the coming years, especially post IPO, which happens tomorrow, so tune in.
1:41:40
Our next guest is Jeff from TensorWave, the co-founder and CGO. How you doing, Jeff? Welcome to the show.
1:41:48
>> Hey, doing doing good, John. How are you? >> Doing well. Great to have you. Thank you so much.
1:41:51
Since it is your first time on the show, please introduce yourself and tell us a little bit about the company.
1:41:57
>> Yeah, I'm Jeff Tetarchuk, co-founder and Chief Growth Officer.
1:41:59
I like to say Chief GPU Officer here at TensorWave.
1:42:04
Our focus is on building out AI infrastructure uh exclusively with AMD.
1:42:09
>> Okay, so I mean, Chief Growth Officer that feels like a sales revenue goal.
1:42:14
Chief GPU Officer feels like an operations, construction, manufacturing, racking, buying, like the the other side of the business. Do you touch both?
1:42:23
How deeply integrated are those two problems?
1:42:27
>> power shells, more revenue. >> That's right.
1:42:29
Everybody needs GPUs in power shells and getting access to them. And I'm the gatekeeper.
1:42:34
>> Okay, so lay down the AMD thesis.
1:42:37
We can go in that, but let's just start with like how you became interested in AMD. Why now? Why what's the traction?
1:42:45
What's the evidence that you're seeing that this is the right choice for your business?
1:42:50
>> Yeah, so when AI took off back in 2022, 2023 and there was the big supply constraint around getting access to Nvidia chips.
1:42:57
The company that we had started previously, we were deploying FPGAs at scale and so we were working with Xilinx and Altera chips and primarily Altera or primarily Xilinx.
1:43:05
And when Xilinx got acquired by AMD, our previous company was working very closely with AMD.
1:43:11
They would send us all of the latest and greatest chips and we'd get them deployed and debugged for them at scale.
1:43:18
And so that's how we forged this relationship early on with AMD and we saw as soon as there was the supply constraint on the Nvidia side, the opportunity when AMD announced their GPUs back in 2023 for us to be the first to go to market with their chips at scale.
1:43:35
>> And how are you talking to your customers about what AMD can offer?
1:43:38
Like we've seen semi-analysis has inference X, formerly inference max, and had some really unique data showing that for certain models, they haven't been able to benchmark everything, especially the proprietary models, but for certain open-source architectures, AMD's actually maybe more cost-effective on a token per dollar basis.
1:44:01
But what data are you leaning on?
1:44:03
What questions are people asking you?
1:44:05
And then I'm super interested to understand how companies are thinking about where the integration, if they do want to migrate from CUDA, over to AMD, like what goes into that? How costly is that?
1:44:22
It was seen as impenetrable, impossible.
1:44:25
Now it's looking more and more feasible, but what are companies saying about the tradeoffs involved in being on AMD?
1:44:33
Yeah, so in the very beginning when the supply constraint issues happened, people were just looking for more options.
1:44:37
And AMD was the only option that was available.
1:44:39
And so at the very beginning, people wanted to just try it and see if it worked.
1:44:43
And so AMD when they first launched launched with the emphasis on scaling out, scaling out inference at scale.
1:44:50
And so being able to support inference and support some of the hyperscalers was their first focus.
1:44:56
And then as more labs started getting on and testing it, they realized that there were some gaps in the software.
1:45:01
You know, it seemed like the hardware story had gotten out ahead of the software story.
1:45:05
And so that's where we were able to help lean in with AMD to help fill some of those gaps by giving them access and helping debug things along the way.
1:45:16
And so yeah, the frustration that customers had around, you know, not wanting to be locked into one vendor, not giving all of their margin to Jensen, forced them and they were willing to look at other options that were available on the market.
1:45:31
And so, we were there, you know, every step of the way to help fill some of those gaps as customers were considering what is that leap going from CUDA to ROCm on AMD.
1:45:42
>> And and the big public story that played out around that time, you're probably referring to George Hotz flagging some bugs, eventually getting on the phone with Lisa Su, going full founder mode in the CEO seat, and watching ROCm develop and actually crush a lot of those bugs.
1:45:59
Obviously, some people have flawless experiences, some people probably still run into problems every once in a while, that's going to happen, but a really good turning of the tide, really good different way to interact with the developer community.
1:46:11
I'm interested to know like how how big do you have to be to go multi-platform now?
1:46:17
Do you have to be one of the, you know, trillion-dollar labs or are there smaller companies that say, "Hey, we have this, you know, this model that we're fine-tuning. It's pretty good.
1:46:29
It's built on some open-source architecture and we'd like the flexibility to not be locked into one chip, but is that a million-dollar endeavor like a you know, a year of 10 researchers' time?
1:46:42
Like how are we bucketing this idea of of diversifying the the options for a company?
1:46:51
>> Yeah, that was a question that a lot of companies had.
1:46:54
What is the switching cost of going from CUDA going to ROCm?
1:46:59
And we were able to show, I mean, in the early days, right?
1:47:00
When back in back in 2023, Databricks was able to show that you could switch from you can go from Nvidia and switch to AMD and it works out of the box in the early days.
1:47:12
And so, being able to showcase that and focus on the most important use cases that the majority of AI companies are using and optimizing those things over time uh was AMD's focus.
1:47:20
And Lisa did a great job, like you mentioned, she did go into founder mode.
1:47:23
Uh she lit a fire over there to make sure that her team was emphasizing building the developer community, building out the resources necessary.
1:47:31
And as Anush over there, who's the CVP of AI, >> Yep, we've had Anush on the show, he's great.
1:47:36
>> Yeah, he uh I love what he says.
1:47:36
He says speed has become the moat.
1:47:38
And they've been able to move even faster now.
1:47:40
And with all these coding code gen tools that are available, they're able to even move even faster uh to help fill uh and close the gap um on that uh supposed CUDA moat. >> Yeah.
1:47:53
A lot of times people uh sort of put AI as like a monolith and uh I mean, we were talking yesterday about uh how just in the customer support, we're talking about Brett Taylor at Sierra, just in the customer support world, um you know, uh speed might not matter for
1:48:10
agentically going and solving a problem in the back end after a customer support ticket closed, but if you're on the phone with someone and you need a real-time voice model, it might actually make sense to co-locate that or distribute that. We talked to Matthew
1:48:23
We talked to Matthew Prince from Cloudflare about this, that there are certain models that need to be in certain places.
1:48:28
Speed might be more important.
1:48:30
Others is just raw horsepower.
1:48:32
It's going to take an hour anyway, send it off to the big data center.
1:48:36
But I'm interested in in the other pockets, like where is is AMD poised already in the lead or poised to take the lead in images or video or voice or real-time or agentic work or integration between the GPU and the CPU.
1:48:52
Like is there something where you're particularly excited?
1:48:55
I mean, I noticed Luma AI is a customer.
1:48:57
They obviously do creative work.
1:49:00
And I'm just wondering if there's something where you're like, oh yeah, like they've they've nailed like this particular architecture is great.
1:49:06
And like obviously there's other work to be done.
1:49:08
There's more cost on certain workflows because those were developed at DeepMind on TPU or at some other company on Nvidia.
1:49:15
Um but uh is there any place where you're like, ah, AMD's really nailing it in this in this subcategory of AI?
1:49:23
>> Yeah, well, they started off great on the hardware side, um, and focusing on adding uh, more HBM than what you [clears throat] can find on a comparable Nvidia chip.
1:49:31
And so, having more HBM allows for workloads that are running larger models uh, to run on fewer GPUs um, and to do it faster. >> Yeah.
1:49:41
Uh, so, you have the CUDA moat uh, as as you put it.
1:49:44
Uh, is it is there like a who who's building the bridge?
1:49:48
Like you need a bridge to go over a moat.
1:49:50
Like I imagine that there's companies, you're probably among them, that are specifically building software that can just translate any architecture from Nvidia to uh, to AMD.
1:50:00
Like how close are we to just that being one click of a button? >> Yeah.
1:50:07
Uh, well, one of the things that I found as we were digging into um, you know, understanding more about what Nvidia was doing, understanding what that CUDA moat actually was and and talking to a lot of the original engineers that helped build CUDA from the ground up. Yeah.
1:50:18
Um, one of the guys that's on our team, Greg Diamos, was was there in the very beginning building CUDA at Nvidia.
1:50:24
And he had always said that CUDA was always built to go beyond CUDA and to to scale out infrastructure.
1:50:31
And so, um, one of the things that that we've as we've talked to people, they said that CUDA is not the moat at Nvidia.
1:50:37
Their ecosystem is the moat and the resources and developers and libraries that they have poured into over the last 10-15 years is the moat and uh, that's the maturity that exists today.
1:50:48
And so, as AMD is building that out and as we are supporting them, we find the important thing is to focus on uh, building out an ecosystem uh, to support the uh, to support AMD.
1:50:58
Uh, we don't focus on software ourselves, but we have a lot of other companies that are trying to solve that problem to create a heterogeneous stack to be able to switch um, between chips.
1:51:08
And uh, so, bringing together those people, showcasing all the different layers that are uh existing beyond uh the NVIDIA ecosystem is is what uh my current focus is on today. >> Amazing.
1:51:20
>> Where uh where are you setting up your supercomputers?
1:51:23
Some people call them data centers, we call them supercomputers.
1:51:28
>> Yeah, uh we we have supercomputers all over.
1:51:29
Um we have them in Arizona, Florida, Pittsburgh, and uh have data centers going up all over North America currently. >> Amazing. >> Awesome.
1:51:36
>> Tell us about the round. How much did you raise?
1:51:39
>> Yeah, we raised 350 million Series B. There we go. >> Congratulations.
1:51:46
>> And thank you so much for taking the time to come chat with us.
1:51:49
>> Yeah, great to meet you, Jack.
1:51:49
>> Great to meet you guys and the team on the program. >> Thanks, everyone. >> Have a good one.
1:51:51
Let me tell you about CrowdStrike.
1:51:53
Your business is AI, their business is securing it.
1:51:55
CrowdStrike secures AI and stops breaches.
1:52:00
Do you have another AI image for me?
1:52:01
Or are we moving on to our next guest, Matthew Joseph from Minerva?
1:52:03
He's a co-founder and CEO.
1:52:05
And he's in the waiting room.
1:52:09
We'll get back to you next.
1:52:10
>> What's going on, Luche?
1:52:12
>> After we talk to Minerva founder, Matthew Joseph.
1:52:14
How are you doing, Matthew? >> Good to meet you. Glad to have you guys.
1:52:18
>> We're doing fantastically.
1:52:18
Uh Thanks so much for hopping on.
1:52:20
Please uh introduce yourself and the company. >> Yeah, so I'm MJ.
1:52:24
I'm the CTO co-founder of Minerva, as you guys said before.
1:52:27
Uh Minerva's an AI platform for consumer marketing.
1:52:30
So basically uh we help consumer brands unify all their first-party data, which sits in like, you know, 20 different data systems like Klaviyo, Shopify, whatever.
1:52:36
Uh we standardize it, we resolve it, we create kind of a golden record, uh and then we optimize sales and marketing on top of that. >> Okay.
1:52:44
>> Using a bunch of micro agents that we developed.
1:52:46
>> Uh uh do do you uh Uh how much of this is like uh data for like the CFO of a consumer brand to understand return on ad spend versus like actually taking it through to creative tool, closing the loop, and integrating with like generative content, writing marketing briefs, maybe even generating copy, probably not in your models directly, but you know, throughout that and and harnessing everything together.
1:53:12
>> Yeah, it's actually more data on the consumer.
1:53:13
And so we have a really really expansive data set 207 million Americans including identity graph which is also pretty expansive with about like 10 billion pieces of PII. >> Sure.
1:53:25
>> And so we help the CMO and the performance marketer kind of understand the consumer base better.
1:53:30
So when you're looking at the funnel and seeing where people are dropping off or you're looking at like the email copy that you're creating, you need to understand who you're actually sending that message to.
1:53:37
We understand that so we can kind of do it both ways, right?
1:53:41
We can be generative and say, "Hey, you're marketing to this kind of person so you should say this."
1:53:45
And then we can do the opposite where we can kind of diagnose inefficiencies based off of demographics.
1:53:50
>> What is give us sort of a case study from the NBA?
1:53:53
Like NBA's in the news obviously.
1:53:57
Seems like people show up with plenty of money.
1:53:59
I don't know that you need any like like what what what questions do you need other than what's your credit card number because I got a $100,000 ticket here for you and you'll pay whatever it takes to get to this game.
1:54:12
>> Yeah, with the NBA we're part of their fan graph.
1:54:13
So we power a lot of their consumer analytics that they end up selling to all their downstream teams.
1:54:20
But even at the team level there's a ton of different case studies that we are starting to pop up right now where you know, if you have super expensive seating but you're in Oklahoma City, you might need to find people that are out of town from a road game that might want to buy that seat, right?
1:54:32
So previously like case studies like that are what we're gunning for.
1:54:36
But with the NBA in general it's mostly powering the consumer analytics platform.
1:54:41
>> How do you guys actually interact with different ad platforms?
1:54:43
Let's say Meta or AdWords, TikTok, etc. >> Yeah.
1:54:51
Yeah, so with Meta we'll find audiences that we know will convert at a very very high rate for specific products because we have an understanding of kind of the right demographic to market to.
1:54:59
And so we'll create look-alike audiences that are seeds on meta, and they'll generally outperform broad targeting by pretty fair margin.
1:55:06
Uh we've seen in luxury travel, uh luxury goods, ROAS improvements are around like 3 to 5x broad targeting. >> Wow.
1:55:15
Uh how quickly can you prove to companies that the product works?
1:55:21
>> Yeah, it it depends on kind of the the case study.
1:55:24
Uh for data, you can immediately identify uh inefficiencies in your pipelines, so people in a day will be like, "Oh, you guys are like absolutely changing where we're allocating spend."
1:55:33
Uh for things like meta, things like direct mail campaigns, it takes a little bit longer to get stat sig, but you can get uh you can get an idea of how well you're actually going to be performing pretty quickly.
1:55:44
Uh so, we generally see, you know, within a week that uh you know, our data and our audiences perform better.
1:55:51
>> Yeah, what's the What What are like the biggest, broadest meta trends in consumer marketing these days?
1:55:55
I mean, we went through like the the Facebook direct targeting, direct response boom.
1:56:01
We went through the influencer by YouTube ads boom.
1:56:03
Um but, in the age of AI, I think everyone's expecting just like AI-generated ads, but is there some other trend where like you can target a smaller audience, so you can go on a more niche platform, so you might see more uplift from a pre- a platform that previously wasn't uh ROI positive.
1:56:20
Like, what else are you seeing in terms of just broad marketing trends?
1:56:26
>> Yeah, I think a pretty interesting one right now is retargeting on AI-driven traffic. >> Okay.
1:56:31
>> Uh so, a person who comes in through like a ChatGPT platform or like Claude or whatever, uh will behave very differently than a person who came in through direct.
1:56:38
Uh and so, being able to understand that funnel is super, super important.
1:56:42
So, retargeting on top of that uh is something that's pretty interesting and and kind of booming right now.
1:56:47
>> Do you have a thesis on like how or why they behave differently?
1:56:49
Like, if I It seems like it's higher conversion.
1:56:54
Like, if I'm landing on a webpage after doing a deep research report on a product, I've learned so much, so I'm probably not going to need to scroll the product detail page.
1:57:02
I'm probably either just want to jump to checkout or I want to do something else to verify something that I learned in the chat app.
1:57:11
>> Yeah, I mean I I think a lot of these trends are happening kind of in the last year and I still think the average user of AI especially you know for kind of deep research is probably a little bit more advanced than the you know the the 65 year old like you know Oklahoma City.
1:57:26
>> Like you picking on Oklahoma City.
1:57:26
So sorry about that, but >> [laughter] >> Uh but I I think it does boil down to demographics and 3 years this can totally change, right?
1:57:33
Like when AI is like it's truly commonplace in every single household, which is getting there.
1:57:39
Um but oh you know over time this will definitely change. >> Yeah.
1:57:42
Uh what percentage of the creative that your customers are running do you think is uh heavily uh heavily generated with AI or influenced by AI or or you know created in process?
1:57:58
>> Yeah, I'm seeing a huge trend towards AI generated um AI generated creative.
1:58:02
There's a lot of like weird little things that you need to keep in mind when you're using AI generated creative like where you're placing text uh relative to the rest of uh the creative.
1:58:12
I mean it's really hard to execute well.
1:58:14
Uh this is something that we're looking into right now as we have you know a very good read on the actual demographics and so creative is kind of the next uh logical piece there, right?
1:58:23
Uh in terms of >> Like if you're going to create a lookalike audience for somebody and then you're telling them like hey you should put spend behind this.
1:58:30
You should you're also in a pretty good position to theoretically as models get better say like here's you know 100 pieces of content that you can run against them and then they can select okay what what fits our brand what doesn't. >> Mhm.
1:58:44
>> Yeah, that that's exactly right.
1:58:44
It's like the next logical step, right?
1:58:46
Just automating the entire process from you know product to cohort fit to creative fit.
1:58:52
Um we were in a position to do all of that.
1:58:55
Um and I'm I'm happy to be part of kind of like the uh the rise in in creative generated by AI.
1:59:01
>> I wonder >> kind of look at like audience people that just love AI slop and you just feed them the sloppiest ads and then people that cuz a lot of people don't like the AI slop, but there's probably some niche audience out there that's like >> It would stop you.
1:59:14
>> I'm buying if there are six fingers.
1:59:16
>> Matt, you'll you'll appreciate you'll appreciate this.
1:59:17
Uh we uh obviously love ads, uh firm supporters of ads, all this stuff, but somehow I ended out in like ended up in a holdout on >> this.
1:59:28
They're going to take you >> on I ended up in a holdout on Meta where I do not get any ads.
1:59:30
Like I'm in the probably like .
1:59:32
05% of people that they're like testing engagement with and I'm like I'm the wrong guy to test on.
1:59:40
Um but I just I just realized one day I was like, "Wait, I have not gotten an ad >> That's weird.
1:59:44
>> on Instagram in uh months and still to this day.
1:59:49
Absolutely no >> Imagine they run this experiment, whole whole group, no ads and they just find like massive depression.
1:59:54
Just massive rates of depression.
1:59:57
They're like, "You got to bring back ads."
1:59:58
That'd be the most bullish >> good for mental health. >> Maybe. Maybe.
2:00:03
You know, consumerism shop >> Talk about the round.
2:00:05
>> shop therapy or whatever.
2:00:08
>> Uh yeah, so we raised >> So we raised 20 mil between the seed and A.
2:00:13
Uh um GGV, Lightspeed, General Partnership, all of these.
2:00:18
Many other uh investors I'm probably uh forgetting the name, but uh very very stoked for all of their support.
2:00:24
Uh we love all the teams we work with. >> Fantastic. >> Very cool.
2:00:28
I got some brands to connect you to. >> Yeah.
2:00:30
>> Uh and so send me send me an email send me an email I'll uh I'll with with the the quick pitch I'll CC you in with some. >> That'd be great. >> Will do. >> Awesome. >> Thank you.
2:00:39
Have a merry rest of your day. >> Nixon 5, let's go. >> Let's go.
2:00:46
>> Uh >> Let me tell you about public. com.
2:00:48
Investing for those who take it seriously.
2:00:48
Stocks, options, bonds, crypto, treasuries, and more with great customer service. >> Uh for San Antonio.
2:00:53
I feel like everyone like I feel like it's relatively easy to rally these people in our world around New York City. >> Yeah. Oh, sure. Sure. Sure.
2:01:02
Like it's easy to be a bandwagon fan for the Knicks cuz of New York you visited. You've been there.
2:01:09
>> Hard to really rally around San Antonio.
2:01:11
Have you been to San Antonio? >> No.
2:01:14
>> Would you like to go to San Antonio? >> Sure. >> Sure. Strong. >> is San Antonio? It's in Texas. >> TVPN, San Antonio. >> It's in Texas? >> We're doing it.
2:01:25
>> But I always think Houston, Dallas.
2:01:27
Is San Antonio the third in that in that tri-state metro the three cities that connect?
2:01:33
>> We're sending Tyler to San Antonio to figure out what's going on. What's in the water?
2:01:38
>> Get to the bottom of that. I don't know.
2:01:40
Well, uh Creative Artists Agency, Hollywood's biggest talent representative and our agent, uh is starting a new company to invest in YouTube stars and podcasters who want to be the next Oprah Winfrey or Reese Witherspoon.
2:01:53
CAA and the Integrated Media Company, uh Integrated Media Company, an an investment arm of private equity firm TPD TPG, that's Texas Pacific Group formerly, have pledged $250 million to Compound Creative Holdings, a new company that will acquire and invest in businesses founded by entertainers who got their start online.
2:02:14
Compound will be led by Tucker Brown, an investment banker who has already helped raise money for the YouTube trick shot masters at Dude Perfect and the liberal podcasters at the Midas Touch Network. Interesting.
2:02:25
I Are you familiar with Midas Touch with the m e i d a s?
2:02:31
At one point this podcast was bigger than the than Joe Rogan. It jumped to the top.
2:02:37
I did not realize that it was a political show.
2:02:39
It The network, uh, describes itself as doing pro-democracy journalism.
2:02:43
Is this I'm so confused because the, uh, the YouTube, uh, the the Yeah, this is definitely it. I don't know.
2:02:53
I thought it was I thought it was something else.
2:02:55
I thought it was more in like the Alex Hormozi category, uh, because Midas Touch, of course, the golden touch, Midas Touch.
2:02:59
Uh, I thought it was more about like wealth creation. Uh, interesting.
2:03:04
>> CAA represents many of these platforms.
2:03:05
>> to see what deals they do here and we're working on getting the team on the show. Talk about it.
2:03:10
>> It turned to Spotter, uh, like outlets.
2:03:14
Outlets like Spotter to raise money by trading a share of their future earnings on YouTube.
2:03:16
Yeah, if you have a YouTube video and it's doing really well and it's getting views, bringing in ad revenue every every month, there's a company called Spotter where you can go and sell the future revenue stream for cash today to finance your operation or just take some chips off the table, much like selling your, uh, you know, the rights to your record collection, essentially.
2:03:35
Uh, there's a lot of capital in the market generally and a lot of interest in creator businesses, but there aren't many educated capital platforms dedicated to invest in the category specifically. I agree with that.
2:03:48
There's only a few that do these types of deals.
2:03:50
Obviously, Barstool, uh, raised money at multiple times and there's been others that have been successful, but it is a a thin crowd.
2:03:57
Compound will focus on creators who have built media businesses generating at least tens of millions of dollars in sales and could use capital to expand their operations.
2:04:04
The company isn't interested in just buying a share of revenue from YouTube or Instagram and tying their fate to an algorithm.
2:04:10
Uh, they want to buy a piece of the whole holding company, the media company.
2:04:16
Brown estimates there are hundreds of creators that fit their initial investment strategy.
2:04:18
That talent can be born on YouTube, TikTok, Instagram, Spotify, or Substack. That's interesting.
2:04:24
We haven't really seen a Substack raise money.
2:04:29
I guess the Free Press was on Substack for a long time.
2:04:31
I think they still might be and did raise money and scale up and hire a bunch of journalists and writers.
2:04:38
Interesting, leaders from CIA and IMC, including CIA co-chairman Kevin President Jim, said we'll sit on an executive committee that oversees Compound.
2:04:46
Celebrities of all stripes have embraced entrepreneurship of online creators starting businesses in entertainment, fashion, food, retail.
2:04:53
Witherspoon Reese Witherspoon sold her company Hello Sunshine in a deal that valued valued the firm at as much as 900 million dollars while George Clooney and other clients sold his tequila company Casamigos for I think also around that number, a huge huge outcome.
2:05:09
We've been looking for ways as an agency to double down on our efforts outside of core representation.
2:05:18
And Packy McCormick gives Tucker a shout-out.
2:05:19
He says Tucker has been one of my best friends since high school.
2:05:21
I didn't realize it went back so far.
2:05:25
Overnight single best person in the world to be doing this. Agree with that.
2:05:28
He's going to crush it 100%.
2:05:32
People always called him the less hot version of me.
2:05:33
That's very funny if you know them both.
2:05:37
Anyway, Lionsgate has taken an an equity interest in Runway and they will be launching a new joint venture program to develop and produce new intellectual property.
2:05:46
This is going to be wildly popular amongst film film fans and cinephiles, I'm sure.
2:05:55
Lionsgate and leading generative AI company I love Runway, Cristobal, former guest of the show.
2:06:02
Runway to announce announce an expansion of their strategic collaboration deepening the company's shared commitment to a future where AI and entertainment grow together. That's good.
2:06:11
The preferred partnership with Runway is part of Lionsgate's multi-faceted AI strategy under the leadership of Chief AI Officer Kathleen Grace and the studio's AI steering committee.
2:06:23
So, it'll be interesting to see what Lionsgate does.
2:06:26
Lionsgate Films, can you name one?
2:06:30
I don't think I can name one. They did Saw. That's interesting. >> There you go. >> did they do?
2:06:36
American Psycho, that's a meme.
2:06:39
The Punisher, Hostel, Rambo.
2:06:42
>> It'd be interesting It'd be interesting to rank movies by how many >> They did the whole John Wick series. >> Listen to this, John. >> Yeah.
2:06:50
>> John Wick uh >> [laughter] >> ranking movies by how many memes they've created, right?
2:06:55
Cuz like American Psycho >> Tons. >> Tons. >> John Wick has a meme? >> What's that?
2:07:02
>> It's the I'm thinking I'm back.
2:07:05
Yeah, I'm thinking I'm back, that's a meme. Anyway.
2:07:06
Uh Sicario Hitman's Bodyguard, Den of Thieves, Greenland. Good stuff.
2:07:13
Uh it'll be interesting to see what they're doing.
2:07:14
Maybe just background replacement.
2:07:15
Maybe John Wick 6 will be entirely AI generated, one-shotted by the next model.
2:07:20
[clears throat] You never know.
2:07:21
Lionsgate's going all in.
2:07:23
>> Keanu Reeves cannot be AI generated.
2:07:27
I think every other actor >> Our crew would like to differ.
2:07:28
>> Our crew would like to differ. They got a They hired a uh Keanu Reeves impersonator to do a uh like a a basically the whole schtick was like they're going to try and create a viral video and someone's robbing a uh like a corner store, like a 7-Eleven, and the uh and the
2:07:47
impersonator, the Keanu Reeves impersonator, stops the assailant and then they used a deepfake to change the face of the uh of the impersonator to Keanu Reeves to make a very convincing um to make a very convincing Keanu Reeves saves the day video that I think went viral and confused a lot of people, but was a lot of fun. They did a whole
2:08:08
They did a whole bunch of uh back uh like behind-the-scenes content.
2:08:14
Anyway, we have our next guest, Adebayo from Base 10, who's the managing partner. How are you doing? Welcome to the show. >> Good morning, guys. Thank you for having me. >> Thank you so much.
2:08:24
>> Let's get right to do How much did you raise?
2:08:25
And John, give me the hardest gong hit of your life. Amp it up a little bit. >> 850 million. >> Boom. >> Congratulations.
2:08:38
>> Great to have you on the show. >> 2.
2:08:39
6 billion dollars in assets.
2:08:43
Um but it is your first time on the show, so why don't we go back in time a little bit and uh give us some of your background and how you got into investing, how you scaled up this fund.
2:08:53
>> Yeah, so um the accent is Spanish. The name is Nigerian. >> Mhm.
2:08:58
>> Um early childhood in Nigeria, then southern Spain.
2:09:00
Um and like you guys, I was a founder.
2:09:04
So I I went to college in Madrid.
2:09:06
I started my first company when I was in college in Madrid, uh which was not very popular occupation in the Spain at the time.
2:09:15
>> Oh, I thought you were saying that the company wasn't very popular.
2:09:16
Like you got into some hot water.
2:09:18
Uh maybe you're >> The company The The being a founder was not very popular.
2:09:24
Um the company became very popular. So we we were 20.
2:09:26
We became the equivalent of Facebook in a Spain.
2:09:32
Um and to to give you a sense, we started in '05.
2:09:36
Uh we sold to Telefonica in 2010.
2:09:39
Uh and when we sold, we were about 60% of daily internet traffic in Spain. >> Woah.
2:09:44
>> Uh so that That was That was a >> 60% What What was it called?
2:09:47
Sorry that I'm not already >> Tuenti. >> Tuenti?
2:09:51
>> 20 because it was [clears throat] for 20 years old. >> Okay.
2:09:54
>> Uh but the Spanish phonetic pronunciation is T U E N T I. >> Oh.
2:09:59
>> I remember I remember Now it's all coming back.
2:10:01
It's all coming back cuz I I have some very good family friends in Spain.
2:10:05
I've spent a decent amount of time there uh including a summer in Madrid at one point.
2:10:09
Uh and yeah, I I remember it uh uh very very cool product.
2:10:16
>> So talk about the strategy.
2:10:16
850 million dollars, that's a lot of capital for seed, series A, series B.
2:10:21
Jeff Bezos raised a $12 billion series B today.
2:10:28
Uh and there's this odd uh K-shaped dynamic in venture where the letters don't really mean anything anymore cuz you can raise a $2 million, $10 million series B, $10 billion series B.
2:10:40
Um where are you seeing opportunity?
2:10:43
What is the early medium stage market?
2:10:45
What are you looking for in the companies that you fund?
2:10:48
>> Yeah, so we we we uh said that we invest in automation for the real economy.
2:10:51
And and to give you a sense, when we launched the fund in 2018, we actually said, "Hey, we're going to invest in applied AI for the real economy."
2:10:59
And the feedback from the LPs was like, "Hey, applied AI is not a thing."
2:11:07
Uh so it's too sounds niche.
2:11:07
Uh so like, "Why don't you like do something real?"
2:11:13
Uh so we call it automation.
2:11:13
And we're like, "Okay, well, we just think that people are going to use a lot more AI like in the these states and restaurants transportation.
2:11:24
Um so it's it's no longer niche. >> Yeah.
2:11:27
>> Uh and now, as you were saying, we have this crazy dynamic where like, you know, we we we sold 20 for a hundred million and that was a big deal. >> Yeah.
2:11:36
>> Now, that is like there's some YC companies that raise that, right?
2:11:41
>> Not just raise at a hundred million dollar valuation, but just raise a hundred million. >> Yeah, that's right. >> hundred million. Yeah, exactly.
2:11:46
So it's it's a completely new world. Um which is fun. >> Yeah.
2:11:51
>> Like that that that's fantastic.
2:11:51
And what I tell the founders we invest in today is like, "Man, I'm so happy I don't have to compete with you because you guys are so good. >> Mhm.
2:12:02
>> Uh and there is so much happening.
2:12:05
Uh so I would say applied AI to the real economy, which these days means a lot. >> Mhm.
2:12:10
How are you thinking about uh services as a as software, that whole trend?
2:12:15
It does feel like there's an opportunity to not train a foundation model, not build a robot, and be very capital light, go apply the tools that are already well beyond what's actually implemented in the real world, close the capability overhang, make a bunch of money in the process.
2:12:32
Maybe you build some software, maybe you get some some customers on long contracts, and the business works, profitable. That sounds great.
2:12:41
At the same time, you sort of veer into like, are you just a consulting firm?
2:12:44
How are you talking to founders? What are you seeing? What models are working? >> Yeah, great question.
2:12:49
So, there are a lot of labels, and like, you know, AI enabled services, versus applications.
2:12:58
I like to spend a lot of time talking to clients, and like, you know, calling the the logistic companies, the transportation companies, and they don't really care what the label is.
2:13:07
They just want it done, right?
2:13:09
It's like, hey, at the end of the day, I need to move this package from here to here.
2:13:16
I need to like, get this cash from this client.
2:13:19
What can you offer me that works, that I can trust, and that is fast, and that is not terribly expensive?
2:13:28
Uh so, we try to like avoid a little bit of the labels, and then like, go to what does a client want and need at the end.
2:13:37
Uh and I think there are going to be many business models that are successful.
2:13:42
Uh it's changing very fast. >> Yeah.
2:13:44
Uh out of uh for my own curiosity, what how is Spain thinking about AI?
2:13:50
Do they have a sovereign AI strategy?
2:13:53
I don't know how closely you follow it.
2:13:55
It must be at least >> no, we we we we we could be here all day.
2:14:00
Um look, we we are a little bit more technology technology forward than when we started 20, but not quite something of Cisco yet.
2:14:08
Um I will say that I get a lot of text messages from my friends back in my hometown who are, you know, running restaurants and hotels being like, "Hey, have you heard of this thing called Cloud?"
2:14:25
And that that fills me with joy.
2:14:25
Um as a country, honestly, we still need to get um our strategy together.
2:14:34
Um and although the culture is changing, and actually one one thing that makes me really proud is that in the last year we have founded four different Spanish teams here in San Francisco that have moved to San Francisco to start companies, and they're crushing it. >> Yeah. >> Yeah.
2:14:50
>> Back home, um we still talk a little bit more about the World Cup than about AI.
2:14:56
We should like change that. >> Yeah.
2:14:58
>> Well, that's, I guess, fair for this next month.
2:15:02
>> Talk to us about that and after that. >> Yeah.
2:15:04
Uh talk to us about coffee.
2:15:04
How does that fit into your portfolio?
2:15:06
I mean, is there a linkage?
2:15:09
Is it just a good business by itself?
2:15:11
Is it just a passion of yours?
2:15:13
What's the coffee thesis? >> Yeah.
2:15:16
Um so so look, we we're a research-first fund, and we're always like, "Hey, what is what is going to happen to the construction market or the logistics market with robots?"
2:15:27
And as you guys know, all that's what I'm good.
2:15:29
And then really early-stage investor is all about the people. >> Yeah.
2:15:33
>> Um so when we met the Blank Street Coffee guys, um they were like, "Look, coffee speak."
2:15:40
We're like, "Okay, we can agree on that." Yeah. >> Yeah.
2:15:42
>> I know that that we don't need a lot of research with that.
2:15:43
But honestly, it's one of the best pitches I I have ever like heard in my life.
2:15:49
They were just like, "Look, we're both like sons of immigrants and like immigrants ourselves.
2:15:55
And like, did you know that 80% of coffee carts in New York are like um rolled over by immigrants, and it's a a great path to like building wealth for the family and staying in the country?
2:16:06
and like that's what we want to power.
2:16:08
And we're like, "Okay, and and the automation?"
2:16:11
And they were like, "Well, the coffee cart is going to be great and like completely automated."
2:16:16
And we're like, "Okay, we don't exactly know what that means right now, but this is awesome.
2:16:21
So, we should be the we should write the best check."
2:16:23
Um and that turned out to go great. >> Yeah.
2:16:28
[laughter] It It's funny because there are there are examples of similar stories and then and then it not going that great.
2:16:36
So, yeah, it's it's it's it's so difficult to fix the to to square all of that when you see opportunity, but ultimately you you you find like the alignment and then everything works out.
2:16:48
Um what do you do you think in deployment pacing?
2:16:51
Do you think in like 2-year deployment, 10-year horizon?
2:16:57
Like is that changing in the modern era with so much uncertainty?
2:17:00
I mean, we talked to Matthew Prince from Cloudflare about like Yeah.
2:17:03
And and we talked to a number of people about it's hard to plan 2 years, 3 years in advance if you're a public company CEO.
2:17:12
Also hard to plan ahead if you're a venture capitalist, but that's sort of what you're paid to do. >> Yeah, I know.
2:17:21
Um look, we we have a state remarkably consistent on that.
2:17:25
Like all our funds have been like 2 and 1/2 years to 3 years deployed.
2:17:28
Um and we are going to do the same thing with this set of funds.
2:17:37
Um it is more tempting than ever to deploy very fast.
2:17:41
Like and and I'm an optimist, so we are we're currently in the This is Y Combinator week. Right?
2:17:47
So, I want to back like 50% of founders that I make or more.
2:17:52
And my team is like, "Ali, stop.
2:17:55
We we can't We can't do that."
2:17:57
And you're like, "You're right. You're right."
2:17:58
It's just Ah, there's so much to build and this this funders are so good.
2:18:04
Uh But we have built systems internally to make sure that we have that discipline because your point all those very tempting and a lot of things are growing very fast.
2:18:16
There is so much change that we want to get a little bit of feedback group a little bit of data of hey okay, we are three and a half years into AI or whatnot.
2:18:24
What happens in your five? Yep.
2:18:27
And we want exposure to that as well. >> Fantastic.
2:18:32
Well, thank you so much for coming on the show.
2:18:33
Appreciate you spending the time.
2:18:34
Congratulations on the fund raise.
2:18:37
>> Let's do it again soon. >> Thank you soon. Have a good one. Goodbye.
2:18:41
Our next guest is already in the waiting room. We'll bring in Jeremy.
2:18:43
>> 60% of internet traffic.
2:18:46
On a on a company built in college. >> Insane. >> Crazy. >> Insane.
2:18:50
Yeah, that's such a Such a high such an impactful company. So good.
2:18:55
Well, yeah, what what >> Spain was locked in doom scrolling.
2:18:58
>> [laughter] >> He into the Spanish group doom scroll.
2:19:02
No, I'm sure it was it was probably messaging driven probably more post driven, but that is yeah, that is remarkable.
2:19:09
Anyway, we have our next guest Jeremy Franklin from Fundamental co-founder and CEO in the waiting room. Let's bring him in. >> What's going on? >> How you doing Jeremy?
2:19:18
Good to be >> Good to be with you guys.
2:19:18
Thank you for having me on.
2:19:20
>> I want to get straight into World Cup predictions, wagers, all of this.
2:19:23
But first introduce yourself and the company a little bit. What are you working on?
2:19:28
And then let's go through the the broader news and applications.
2:19:34
>> Alison, yeah, I'm Jeremy.
2:19:34
I'm the CEO and co-founder of Fundamental.
2:19:38
Fundamental build a foundation model for tabular data.
2:19:40
So when most people think about the AI boom, they think about LLMs, you know, like ChatGPT, Claude.
2:19:47
But what's less appreciated is that LLMs work well with unstructured data.
2:19:52
Something like text, audio, video.
2:19:52
But the global economy and enterprises really run on structured data, on tables such as spreadsheets, databases, CRMs, and that's, you know, the part of the enterprise that really never had a ChatGPT moment.
2:20:06
And that's the market opportunity that we're focusing on.
2:20:08
And so what we're doing is for tables is what ChatGPT did for language.
2:20:12
We pre-trained the model on millions of tables to understand how the world works in rows and columns.
2:20:20
And so we created one model that generalizes across industries and use cases to allow companies to make better predictions and decisions on their data. >> Yeah.
2:20:31
Okay, so everyone is going to say, "Oh, the frontier models, like they can spin up a spreadsheet, they can speak CSV, they can write Python that generates and manages tables and tabular data, and the frontier is the frontier, it's always the best."
2:20:46
But you're going to effectively be benchmarking your product against the frontier models around the world cup.
2:20:54
Walk us through the the strategy, the wager, what's actually at stake there.
2:21:01
>> Yeah, so, you know, I grew up in Belgium and I'm a huge soccer fan, and a lot of us at the company are also big soccer fans.
2:21:07
And so what we realized is that, you know, historical team performances in games can be structured in rows and columns.
2:21:14
And so we started thinking around the office, like, can we actually use our model Nexus to make predictions on the World Cup?
2:21:20
And we said like, you know, maybe betting markets are off and we are right.
2:21:24
So we like we wanted to see how good our model was.
2:21:25
And the funny thing is that at the core of our model, you know, our company is focused on enterprises.
2:21:30
So we're not really a consumer-facing uh focused company, but we, you know, thought we could have some fun with it.
2:21:36
And so before doing anything, we wanted to see how good our model was um historically.
2:21:39
And so what we did is we trained our model to um with data up until the 2022 World Cup.
2:21:48
And so data such as uh which who won uh in different international games, the quality of the teams, uh whether games were home or abroad, and we ran more than 20,000 simulations.
2:21:57
And what we what our model Nexus predicted or identified is that Argentina would be the eventual winner way before bookmakers did.
2:22:05
So, if you look at what the market actually predicted, the market predicted that Brazil was going to win the 2022 World Cup up until the quarter-finals when Brazil got knocked out, and our model was much more accurate than that.
2:22:17
And so, we said, "You know what?
2:22:19
Let's apply the same thing for the 2026 World Cup."
2:22:21
And our model already differs meaningfully from what betting markets are predicting.
2:22:26
So, I'm excited to see what happens next. >> Yeah, I I wish.
2:22:33
>> [laughter] >> America America has a 20 America has a 0.
2:22:38
5% chance of winning the World Cup according to our models. >> is a chance. I like those odds.
2:22:44
I'll take those odds any day.
2:22:47
>> John loves betting on himself.
2:22:48
>> Yes, those are the odds.
2:22:51
>> Uh how's Belgium fair?
2:22:53
>> Belgium Belgium is at slightly less than 2%, but I honestly have high faith. >> Okay.
2:22:59
And then >> Belgium >> Yeah.
2:23:01
>> How what's the population of Belgium? Roughly? >> 11 11 million. >> How many? 11 million? >> 11 million.
2:23:08
>> So, population of 11 million is absolutely [clears throat] mogging population of [laughter] >> So, so are you also benchmarking the other frontier models, just going to the different models, open-source models, and just asking them the same questions?
2:23:23
Who do you predict will win, build a probability table, and then benchmark those as well because I think you're going to want to not just say that you're better than the sports books, but you're also going to want to say you're better than the frontier models, correct?
2:23:38
>> Yeah, but the frontier models themselves don't really work well with like predictions, right?
2:23:42
So, like >> But they can take a I mean, they can predict the next token, so they can like take a wild guess, then if you smoke them, it looks good, right?
2:23:49
>> Yeah, yeah, we we we could try that.
2:23:51
We've not done that, we could definitely try it, but like, you know, it's funny cuz like, the frontier models, like, especially for predictions, they sound right, but they are not actually correct, though. Yeah.
2:24:00
>> And and and with ChatGPT, there's the personalization, and in the personalization, I said like, "Never bet against America."
2:24:06
So, I'm sure it would just say like, [laughter] "Oh, 100%."
2:24:10
So, yeah, you probably smoke it.
2:24:12
>> Um who who are like, how are you who are you projecting to to win?
2:24:14
What are what are kind of like the kind of key predictions that uh that we should be tracking as the World Cup kicks off?
2:24:22
>> The the betting markets have Spain and France neck and neck, and we uh heavily favor Spain over France.
2:24:27
The market also predicts that uh Argentina, I think, has like the fifth largest chance of winning, according to the market, and we predict them as strong runner-ups. >> Oh, interesting.
2:24:38
Okay, so so, Spain, Argentina, Spain winning would look really good for you relative to sports book. >> Correct.
2:24:46
We did not But, I would be happy if Messi wins his second World Cup. >> Sure.
2:24:50
Uh >> Uh tell us about the company.
2:24:51
You you recently raised some money.
2:24:55
>> Yeah, so we raised uh $275 million uh at a $1. 5 billion >> Whoa. Who'd you raise it from?
2:25:06
>> We raised it from um from Oak, uh Valor, uh Battery Ventures, uh Salesforce, and then um a bunch of uh big angels, like Alvin and Perplexity, uh a separate approach from Wiz, >> That's great.
2:25:22
>> and yeah, and a few others. >> That's fantastic. >> Very strong.
2:25:24
Uh keep us posted as the the World Cup progresses, uh and uh we're rooting for I'm not even rooting for any team.
2:25:33
I'm just rooting for your predictions. I want you to know that. >> Yeah. >> I appreciate it.
2:25:37
And everyone can go and see them on soccer. fundamental. tech. >> Amazing. >> soccer. fundamental. tech >> All right. >> Great to meet Jeremy.
2:25:45
It'll be fun to follow on.
2:25:48
>> We'll talk to you soon.
2:25:48
Have a good rest of your day.
2:25:50
Uh in other fun recent news, Thrive is out with $10 billion uh Got a little mugged by Bezos with the $12 billion raise, but not bad. >> Not bad.
2:26:02
>> Thrive 10, and it's 10 billion, exceeding 10 billion, the largest ever, nearly double the size of the last fund for Thrive.
2:26:07
Uh 1 billion for early stage, 9 billion for growth.
2:26:09
Uh biggest bets, just to remind you, OpenAI, Stripe, SpaceX, Databricks, Anduril, Cursor are all in the Thrive portfolio.
2:26:19
Um and a bunch of other companies.
2:26:19
Uh and so those have become the defining private companies in the current cycle.
2:26:25
Uh the strategy is con- concentrated, founder-loyal, allergic to indexing the market, the Fifth Avenue strategy as discussed on Invest Like the Best in Patrick O'Shaughnessy. Is is chiming in.
2:26:37
Uh Josh Kushner says, "In markets to go long on something is to bet it grows more valuable over time.
2:26:41
Much of the conversation today is short on humans wagering that AI makes people redundant.
2:26:49
We believe the opposite is true for industries Thrive Holdings operates in, and Patrick O'Shaughnessy shares a transcript from Invest Like the Best.
2:26:57
They said, "The North Star for the next decade of Thrive is if we are a company and we have a product, what are the products that we can create that make us look more like the businesses that we ultimately invest in?
2:27:09
The second part of the story uh of the story is after we invested in OpenAI, the business had $50 million in API revenue, and several and several of us went around New York City and started pitching a bunch of the private equity firms on this idea that they could use the API to create greater efficiency within their businesses.
2:27:24
We were somewhat surprised by the fact that we did not get meaningful traction around these ideas.
2:27:30
So Karim, to his credit, said, "Let's just start doing this ourselves."
2:27:33
We've always looked at the world that we've lived in as one that needed to disrupt from an outside-in perspective.
2:27:41
If you were to think about the paradigm shift of reinforcement learning, the things that you need are both data and that is proprietary to the company, but also the experts that exist at the company to fine-tune the model.
2:27:54
We believe that going forward disruption will happen from the inside out.
2:27:56
We set up this permanent capital vehicle that enables us to buy these businesses and hold them in perpetuity because if you actually have a differentiated unique lens and cost of capital around these businesses and you're able to transform them in ways in which you ultimately want to hold on to them forever.
2:28:12
So, congrats to Thrive on the new round.
2:28:18
>> Uh congrats to the whole team. >> Yeah, fantastic. >> Great stuff. >> fund.
2:28:21
Anyway, leave us five stars on Apple Podcasts and Spotify.
2:28:23
Sign up for our newsletter at tbp.
2:28:25
com and we will see you tomorrow for the SpaceX IPO.
2:28:30
>> We're going to just be hanging out all day.
2:28:32
>> have the We're going to have the stock price >> on the big board. Be fun.
2:28:35
>> We'll see you tomorrow. Goodbye. >> Throwing Flash Bang.