0:03
[music] I see a large IPO on the horizon.
Search this video
0:11
You're surrounded [music] by journal your position.
0:19
Overnight [music] [music] success.
0:30
The place [music] 3000 [music] double right.
0:42
[music] This misinformation clearing order inbound.
1:02
[music] >> Let's just roll.
1:11
We [music] are surrounded by general. Hold your position. Come on. Get up. Trust the experts here. [music] My code. We are experts.
1:30
[music] Founder knowledge. Five code.
1:44
>> I see multiple journalists on the horizon. Stand by. Express. >> UAV online. [music] >> Blaze. Double blaze. Triple blaze.
2:11
>> [music] >> Double kill.
2:18
[music] [ __ ] [music] is it? Please. Team [music] Deathmatch. We are experts. Triple Blaze. That's just wrong. Right.
3:09
>> [music] >> clearing order inbound. Get up.
3:23
You're >> surrounded by journalist. Hold your position. Strike two.
3:37
[music] >> Activate golden retriever mode.
3:49
[music] [music] >> Mark clearing order inbound. >> [music] >> Five.
4:09
[music] I see multiple journalists on the horizon.
4:25
[music] You're watching TVPN.
4:37
Today is Monday, January 12th, 2026.
4:41
We are live from the TVPN Ultradome, the temple of technology, the fortress of finance, the capital of capital. >> Ramp. com. Time is money. Save both.
4:50
Easy use corporate cards, bill pay accounting, and a whole lot more all in one place.
4:55
Uh bunch of fun news out of uh RAMP.
4:58
They built a AI agent just for internal production.
5:04
Yeah, we we will go into that.
5:04
But first, we got to pay our respects to the big man Jerome Powell. >> Pull up the anthem. >> The anthem.
5:12
>> This is this week's anthem.
5:12
We've been blasting it all morning [music] here in the studio. >> Yes, it is.
5:19
>> It will make you emotional.
5:20
>> It's a very emotional song.
5:20
It uh >> So, trigger warning.
5:23
I I guess it's AI generated, >> but it hits [music] >> manufactured storm power turned hostile.
5:35
The rules [music] deformed threats in the [music] whispers.
5:44
>> Yeah, we should have gotten lighters for this for [music] sure.
5:45
Of course, this is on the back that the New York Times reports that federal prosecutors have opened a criminal investigation of Jerome Powell.
5:57
[music and singing] >> He took to the heer dropped a video explaining his side of the story, >> but instead of playing that, we're playing this.
6:14
We not [music] Jerome Pow.
6:30
>> I didn't want to cry at the office today, but it's happening. >> Oh, what a story.
6:39
Pal says the Justice Department served the Fed with subpoenas.
6:41
Federal Reserve Chair Jerome Pal said the US central bank has been served uh grand jury subpoenas from the Justice Department, threatening a criminal indictment related to his June congressional testimony on ongoing renovations of the Fed's headquarters.
6:54
In a statement released Sunday evening, Jerome Powell rejected the notion that the action was driven by his testimony or the renovation.
7:02
Uh Joe Weisenthal has a post here.
7:04
He says, "Powell confirms the Fed has been served. subpoenas from the DOJ.
7:09
Uh, fortunately, we have Tyler Cowan coming on the show uh, today.
7:11
I'm sure we'll be able to talk to him about that and a whole bunch of other things in the world.
7:16
>> We'll be asking him, should we roll the Fed into Truth Social?
7:20
>> That's a good That's >> World Liberty or World Liberty Financial, right? We have options.
7:24
>> Might be the most entertaining.
7:25
>> Anyway, let's pull up the linear lineup and show everyone what who's coming on the show today because we do have Tyler Cowen.
7:30
Uh we also have Andrew Feldman from uh Cerus coming on the show and a bunch of other folks.
7:36
Harley is joining to talk about agent of commerce and >> from Terra he's building drones Africa. Excited for that one.
7:44
>> And of course Harley >> and Ella Marina um and uh linear of course is the system for soft modern software development.
7:51
Linear is building is a purpose-built tool for planning and building products.
7:55
Um >> we also might have a surprise guest joining at 12:15 just so you >> we'll see. Uh yeah.
8:00
Anyways, watching uh Sunday night.
8:03
Uh I'm all excited, right?
8:06
One more sleep until Monday.
8:06
And I pull up this video.
8:09
I've got to watch Jerome uh uh >> give a two-minute talk. >> Yeah. Yeah.
8:15
I mean, really dark uh moment. Um it was funny.
8:17
Buco Buco Capital shared like if if it's illegal to run over budget on a remodel, my wife's getting the electric chair.
8:27
[laughter] You didn't give me the punish line when you said that the first time and I knew where it was going. But >> that's wild.
8:36
>> Uh not um >> very political, very fraught, but it's created a number of entertaining.
8:43
>> People have been standing up standing up for standing up for for uh the Federal Reserve chairman and uh fortunately I mean the the administration sees these.
8:50
They you know that they're very online and they see the support.
8:52
So we'll see where the story goes.
8:55
says, "Like if you would let Jerome Pal crash on your couch for a few months."
8:59
[laughter] >> AI is really at its best when you need a bunch of, you know, memes and images generated around a a current thing.
9:05
Uh before we do the next one, let me tell you about Reream.
9:09
One live stream, 30 plus destinations.
9:11
If you want to multiream, go to reream. com.
9:15
They make the show possible.
9:16
>> Rachel just said, "You just created a million central bankers."
9:18
When Jordy said this to [laughter] me, I just burst out laughing so hard.
9:25
>> It is it is I mean uh Fed chair >> probably one of the worst jobs on earth if you care what other people think about you, right?
9:34
Because it's just like every you know all the time people just have this massive fixation on on you and they're going to form an opinion immediately.
9:42
>> Uh but in this case I've never seen people so united around uh which is heartwarming.
9:47
That's the only uh >> and it is it is weird because like the the prediction is that there will not be another rate cut in January.
9:53
Uh there's a lot of people that would benefit from another rate cut.
9:57
Uh if you're if you're long the market, you would probably benefit.
10:00
Um but I think people do are generally still fans of Fed independence and they want uh Jerome to do whatever is best based on the facts and the data and the unemployment and inflation. >> Yeah.
10:10
Uh I'm surprised there's no reaction uh in the uh from from uh the prediction markets at all.
10:16
Khi still has 94% that the Fed maintains the rate in January. >> Yeah. Interesting.
10:22
You would think move the needle a little bit because it's not backing down video saying I'm not I'm not leaving.
10:32
You're going to have to prime me out with the jaws of life.
10:33
Uh Mary says, "Absolute insanity.
10:35
The Department of Justice just served the Federal Reserve chair with a grand jury subpoenas threatening criminal indictment over a historic building renovation."
10:41
And uh interestingly I I don't know that the details of this building but it's not like the White House where he lives there, right?
10:49
It's like it's just a it's a workplace.
10:51
I assume it's not like it's his personal house.
10:53
It's not like >> it's not you based on this. Yeah.
10:58
You would think you would cuz the other the the other >> um who was the woman who uh they they also opened an investigation. I'm blank.
11:09
Um, but uh in that case they said like she uh she got a mortgage for a primary residence but she actually ended up not living there full- time >> which um >> uh but at least the the Lisa Cook >> hopefully she's not cooked. We'll see.
11:29
Uh Jerome Pal is appealing directly to the American people and bluntly stating that the criminal charges are not about Congress's oversight role, but rather about the Federal Reserve's independence in setting the interest rate, American equities traded a premium because of our respect for law, accountability, and central bank independence.
11:44
Public service sometimes requires standing firm in the face of threats.
11:48
I will continue to do the job the Senate confirmed me to do with integrity, and commitment to serving the American people on a Sunday evening before market open.
11:56
What is the market doing?
11:58
We should go over to public.
12:00
com investing for those who take it seriously.
12:02
You got stocks, options, bonds, crypto, treasuries, and more.
12:05
All with great customer service. >> S&P 500 is green. >> Green. Yeah.
12:12
>> Um so anyways, I Yeah, I think everybody expected last night uh for things to happen.
12:18
Of course, nothing ever happens. >> Uh but uh we'll see.
12:21
In some ways, this this will just give the DOJ and the admin more confidence in their decision.
12:31
Although, they did come out and say like uh the White House had nothing to do with it. >> Yes. Yes.
12:34
Trump said, "I'm not pressuring."
12:35
He said something like, "I wouldn't even think to pressure him on this particular angle."
12:39
Uh he's saying, "I I might post something on Truth Social about where I think the interest rate should be.
12:45
He's free to do without that what he will."
12:46
So, uh I'm sure the story will evolve and there will be a lot of reporting on it.
12:49
Uh Eddie Elfen Bean says, "What are you in for?"
12:51
I gave imprecise information to Congress about the scope of renovations to the Federal Reserves HQ.
13:00
>> Trey in the chat says, "The funniest thing is the Fed renovation is self-funded." >> Oh, yeah.
13:04
By the actual Fed because it it makes enough money.
13:06
I think they make a bunch of money.
13:07
Don't they make money printing coins? Coinage?
13:09
I I think that they Oh, is that the mint?
13:12
Is the mint part of the Fed? I don't know.
13:14
But I know that I know that there's a number of uh like uh there's a number of uh government programs that are all self-funded.
13:20
Uh not all of them are, you know, taxpayer money pits.
13:23
Uh the the CIA's Incutel, for example, is uh is not from the CIA's budget.
13:28
Uh it makes money because they invest in companies and they put that money back to work. Very interesting.
13:35
>> Bubble Boy says, "I'm willing to die for the Federal Reserve."
13:37
So he is Jerome's strongest soldier.
13:42
>> Bubble Boy's getting standing up. 2,000 likes.
13:44
A lot of people are coming out in favor of Jerome Pal.
13:46
Quickly, graphite code review for the age of AI.
13:50
Graphite helps teams on GitHub ship higher quality software faster. Go check out graphite.
13:56
>> Uh Geiger Capital pal watching stocks turn green after thinking the mar market would defend him. >> Isn't that Biden? >> Yeah.
14:03
The the tough thing is like if you assume that uh uh rates are come going to come down like you don't exactly want to sell >> Yeah. assets. You want to own assets.
14:14
>> There's this weird dynamic where you might not like what's happening politically, but there's a big difference between what should happen and what will happen.
14:20
Positive and normative analysis.
14:22
And so if you you could be like, I don't like the fact that, you know, the Fed's going to be less independent.
14:27
But if it means that interest rates are going to come down, then that's bullish.
14:30
That's a bullish catalyst.
14:32
And so you wind up going long.
14:34
Uh Marco Rubio is finding out he has to be chairman of the Federal Reserve.
14:36
I haven't followed the Marco Rubio meme too closely.
14:40
I just know that he has a lot of jobs or keeps getting tapped for things.
14:44
And so I've seen him in an astronaut outfit.
14:45
I've seen him in, you know, different Venezuelan memes.
14:47
I I I I don't exactly know where this all came from, but I I'm I'm familiar with the concept of Marco Marco Rubio doing everything.
14:55
I guess I don't really >> Yeah, it's some it's somewhat depressing because it just means like if you're in the if you're in the inner circle, you're going to you're going to be uh you're going to get a lot of responsibility and if you're out, you will eventually get the the laser beam of the admin.
15:07
And uh but um >> uh well gold is through the roof today. Joe posts a chart.
15:14
Gold jumped from uh 4510 to 4585.
15:22
Not a huge move but a huge move for gold of course.
15:24
Um so people are bailing on the dollar potentially.
15:27
Silver's also up says the Kobes letter.
15:29
Silver surges above $85 an ounce for the first time in history.
15:34
It's already up 19% in 2026.
15:34
Uh there's been a number of uh hard techch founders have commented on the fact that silver is actually more of an important material than gold in manufacturing of the the semiconductor supply chain.
15:47
A lot of different uh AI supply chains.
15:51
And so there there's an interesting narrative of like the knock-on effects of high silver prices. >> Yeah.
15:55
>> Um the nothing ever happens uh this is nothing ever happens on steroids. I've never seen so much.
15:59
Nothing ever happens, says Mike Bird, because the S&P 500 is up on the news of chaos in the financial markets potentially.
16:06
Uh, very odd odd scenario.
16:09
Anyway, Crowd Strike, your business's AI, their business is securing it.
16:15
Crowd Strike secures AI and stops breaches.
16:17
Um, so, uh, the Apple Vision Pro is in the news because, uh, and I think we can pull up this video maybe of, uh, Trunk Fan posted this.
16:31
Mark German was a big fan of this.
16:31
Apple Vision Pro, uh, announced you can now watch a full NBA game in the Vision Pro, not just a little highlight reel, not just a trailer.
16:41
Uh, and Mark German asked the question, "Is the total addressable market for watching tonight's Lakers game in the Apple Vision Pro just me or is anyone else tuning in?"
16:51
A couple people said, "I haven't booed mine up for a year." They still have it. They did turn it on.
16:55
Uh, he wound up loving it.
16:57
Mark, >> is this Have they ever done this before?
17:01
Is this >> They've never done a full game.
17:01
So, they've done MLS highlights.
17:02
You could watch like an eight minute summary of an of an MLS game that had a ton of different cuts.
17:09
Not a lot of people were not fans of that.
17:10
There were also >> release cadence needs to be studied. >> It's crazy.
17:14
And I mean that's what Ben Thompson wrote about today in stratey.
17:18
He's he sees all this as like crazy own goals.
17:21
A lot of really uh obvious things.
17:24
Also, the reason that you see this video so grainy like this.
17:25
Uh so Mark German loved it in the headset.
17:29
He said it's absolutely wild.
17:30
It's like watching courtside.
17:31
Uh Trunk Fan has the video here.
17:34
You can't record what's happening in the headset.
17:36
You can't just steal an NBA game uh because so you need to like put your phone up against it and you don't really experience it here because uh for DRM reasons you can't just pirate it.
17:48
You can't just record what you're seeing.
17:50
Uh so the actual experience is better than this.
17:51
Uh I actually went to the Apple store yesterday to try and pick up a Vision Pro to experience this and they were sold out and I don't know if that means that they were just like not expecting to sell anymore so they stopped stocking them.
18:04
Uh but they didn't have one.
18:04
Um but uh but I I played with the the Vision Pro.
18:08
>> I mean, the real the real I I would wait to the real review would be getting the Apple Vision Pro, going to getting going to the actual game, getting the ticket right next to the system that they're using, and then just having the headset on and taking it on at the game. Yeah, at the game.
18:24
[laughter] You want to see how real it is?
18:25
Tyler, what would you do?
18:27
>> Well, so this is cool because it's like emulating like what is happening in real life, but in VR you can do like things that like you couldn't do in real life.
18:34
So, like I want to see what is the point of view like if I'm the ball.
18:36
[laughter] >> You'd probably be so motion sick.
18:41
>> I want to be the ball. >> That sounds terrible.
18:42
Who wants to be the ball? >> I know ball.
18:45
>> Uh Matthew Ball or who's the other ball? >> Dean Ball.
18:50
>> We haven't gotten Matthew Ball on the show yet. We need him. Uh he's a great analyst.
18:53
Um anyway, so uh Ben Thompson wrote about this because he's obviously a huge NBA fan.
18:58
Also, he's a Milwaukee Bucks fan and the game was the Lakers versus the Bucks.
19:03
So, this is like a royal flush of like the sweet spot for Ben Thompson analysis.
19:06
Uh, he had to jump through VPN hoops to watch the broadcast because it was only available in Lakers home market, which is uh California, also Hawaii, and I think one other state.
19:17
So, it's somewhat tricky.
19:20
>> Yeah, >> you can't >> you No. No.
19:22
If you're in New York and you had a Vision Pro, you could not watch the Lakers play the Bucks unless you had a VPN.
19:28
>> Yeah, there's a lot of details here.
19:28
And >> that's a huge detail. >> I know. I know. I know.
19:34
>> You're like, I have this I have this $3,000 device that is just gathering dust and then you make this big deal about this amazing [laughter] experience that I can have.
19:42
And then if I'm not actually within the area that the game is actually taking place, I can't I can't experience it. What's the point of VR?
19:50
>> So there there are a lot of reasonable critiques like that.
19:52
Ben puts a lot of those in his piece.
19:54
Uh I think that there are logical reasons.
19:57
I don't think Apple is dumb.
19:59
I don't think they just made a mistake.
20:01
I think these are all contract negotiations.
20:03
And when we look at the history of sports and transitions through various eras of broadcast and new technologies, I think their decision-making makes a little bit more sense.
20:13
Even though I agree from a user experience perspective, what you're saying, what Ben Thompson is saying makes a ton of sense.
20:18
So Apple clearly reads strategy.
20:20
They've sent him multiple headsets.
20:23
He bought his own, but they said they keep sending them to him being like, "Hey, you should try it.
20:27
Like we we're coming out with something new."
20:28
Uh, so they've sent him the new one, the M5 Vision Pro.
20:30
Um, and uh, and and he was ready to he was ready to watch this.
20:35
He was ready to love this, but he was very disappointed because it it it cut from one scene to another.
20:39
And so that takes you out of the experience.
20:44
He says, "Do away with all of the pre-show, special announcer, postshow content.
20:50
Just let me put on the headset, and if I put it on 30 minutes before the game starts, I'll just watch the players warm up."
20:55
And then you don't need any overlays because if I want to know the score, I'll just look up at the scoreboard like this. You're in the theater.
21:01
Like people pay a lot of money to sit courtside.
21:03
And they're not like, "Oh, I also >> I'm having a bad experience. I know.
21:08
Please, please give me an iPad with the score." No, no one cares.
21:10
They just look at the score. They hear the audience.
21:12
If there's if if something great happens, they hear the roar of the crowd. Um they see everything.
21:19
They can even look up at the screen and usually see a replay if they need to.
21:22
Um, and so all of that should be possible with just one simple Apple immersive camera rig, streamed the whole game, and that's it.
21:29
Instead, they did four different camera angles.
21:33
They're cutting between them, and every time they cut, you get kind of like, whoa, where am I? Like, I just teleported. It's weird. Yeah.
21:39
>> So, >> my uh my question was like was like, so Ben frames this as um he calls it Apple, you still don't understand the Vision Pro.
21:49
He's like taking shots at them.
21:49
Uh, and I titled my piece, uh, Apple, they actually do understand the Vision Pro.
21:56
And I think they I think they they've heard his response.
21:57
They clearly read his piece.
21:59
He wrote about this maybe two years ago when he got a demo before it even came out.
22:03
And he said the secret to success with this product will just be put a camera on the field, let me sit there front courtside. That's it.
22:10
No editing, nothing else.
22:12
And then every time they delivered him something that was edited, he wrote a piece about how bad the editing was and how you don't need that and just let me let me sit there.
22:19
Uh, and so my question was, um, there's no one that really disagrees with Ben.
22:25
Like Ben comes out and says these these things every time there's an Apple Vision Pro piece of content that comes out, he comes out and says, "Too many edits, too many cuts. Just let us sit there."
22:33
And there's not like there's a lot of people that are like, "Ben's wrong."
22:36
Actually, I love the edits. More edits.
22:37
Like they need to be even cracept for Ben, basically.
22:42
So they should clearly listen to him.
22:44
Uh, and no one's arguing that Ben's wrong.
22:46
Um, but my question is like why on earth isn't Apple doing this? Why?
22:51
Or at least why haven't they made it an option?
22:53
Like they have the single camera there.
22:55
They could just be like, "Do you want to watch the edited version or do you want to watch just the normal just sit there in the seat version?"
23:01
Then Ben would be happy and he'd be writing a glowing review right now.
23:04
Instead, >> uh, Apple's not giving what Tekk wants and they're feeling the pain because they got they got a they got an article that was not very uh not very complimentary to them in the experience.
23:14
So um uh I think that this actually [clears throat] has less to do with the technology, less to do with the creative direction and the directorial vision within Apple and more with just straight up contract negotiations.
23:27
So uh and if you go back in history, Ben goes back to uh some other some other history. I went back to 1947.
23:34
So TV adoption I didn't realize this TV adoption went through a fast takeoff in 1947.
23:41
there were 16,000 TV sets installed in America.
23:46
Eight years later, it was 32 and a half million.
23:50
It's like d completely asmmptotic, completely uh fast takeoff.
23:56
So, um the technology trend was clear, but there was still financial risk to getting the timing wrong for your league.
24:02
Uh the NFL is obviously a huge beneficiary of TV today.
24:05
They make a fortune from the Super Bowl ads that are extremely expensive.
24:09
Uh, but in 1949, the Los Angeles Rams, because the Rams are in LA now, but they did they went to St.
24:17
Louis and then they came back.
24:17
Uh, but they were in Los Angeles in 1949.
24:20
They sort of got wrecked because they jumped too early.
24:22
So, the NFL had gone to all the franchises, said all the teams, we're giving you the permission to sell your broadcast rights this year, this season.
24:30
If you want to put your your your particular team's home games on TV, you can do that.
24:35
You can go out and negotiate. You can sell those. It's an option. Yeah.
24:38
Uh, and the Rams said, "Yeah, we'll do it. We'll take the jump."
24:42
They were the only one that did it, and it sort of makes sense since they're in LA.
24:44
There's a lot of production people here. It would be a natural.
24:48
>> They were a little too TV pilt.
24:49
>> They were extremely TV pilot burned.
24:49
So, attendance dropped significantly.
24:52
Uh, on an inflation adjusted basis, they lost $2.
24:57
5 million of today's dollars.
24:57
Uh, and so the Rams had to go to all the sponsors that sponsor the TV broadcast and say like, "Hey, can you just make us whole because we're going to go out of business." And they did.
25:07
and the sponsors basically paid the Rams for the difference in what they had taken in ticket sales.
25:13
Uh but it was not a good it was not a good outcome.
25:15
Uh and >> although the the NFL eventually got through all of this and figured it all out, uh that was not the case for uh minor league baseball.
25:24
Minor league baseball attendance at minor league baseball events, minor league events peaked in 1949 uh right during the TV install base fast takeoff.
25:33
And so 49 people 49 million people went to little uh went to minor league events that that year in 1949.
25:42
By 1957 the total had dropped to 15 million.
25:45
So it actually did wreck the minor leagues in terms of like their business model and they never really recovered.
25:50
Um and so um the job of a league commissioner is to get the transition right.
25:56
Like if you transition too early you'll have a really really bad year while everyone just says hey I can just do the new thing the new technology.
26:03
I don't need to buy the tickets.
26:05
Uh if you do it too late, other leagues might have uh figured out their their their contracts, their ad sales, their their broadcast rights, all this other stuff.
26:13
So, Adam Silver, the commissioner of the NBA, uh who we learned about through his connection to Josh Kushner, of course, um uh he said, "I think it's my job to incentivize our partners to be able to look out into the future."
26:26
He's not saying, "Hey, my job is to get everyone out of the stadiums and into VR headsets ASAP."
26:30
like the end result is like there is a there is a separation between immersive rights and presence rights.
26:37
So there's broadcast rights and effectively they're using the same framework.
26:42
So when they sell a broadcast right they're not selling the right to they're selling the right to broadcast with with an announcer with multiple cameras with different cuts and edits.
26:53
They're not selling your you're teleported into the stadium. >> Yeah.
26:58
And that's something that they might sell, but they haven't sold yet.
27:02
And they're and they're I think they're deliberate about this.
27:04
And so I think when they went to Apple, they said, "Yes, we can do something because they did a deal with Meta and you can watch a number of NBA games in the Meta Quest." And it's the same thing.
27:13
They cut around even though and the reviews are bad. Everyone says it sucks.
27:17
And so it's obvious that that the tech companies should, you know, Google how did did people like this?
27:23
And it's obvious no people don't like it.
27:25
But I think the NBA is holding fast that they're like, "No, actually our courtside seats are really really really expensive and we want to keep it that way.
27:33
We don't want we won't we don't want it to be substitutive on day one."
27:35
And Ben Thompson when he first wrote about the Apple Vision Pro, he said, "I would pay thousands of dollars a year for an NBA league pass that allowed me to in VR sit courtside."
27:48
>> And that's less money than courtside seats to every single NBA game, which is effectively what you're selling.
27:53
So, and then how many Ben Thompsons are there?
27:56
People with Apple Vision and so you so there's there's financial risk there. I think it can work out.
28:00
I think that there's a deal and there's a price and there's a number.
28:03
The install base gets to this level and you price it at this level.
28:07
And >> I think they're two I think in some ways they could very easily be two wildly different consumers.
28:12
Like Ben is probably like >> Ben Thompson knows ball.
28:16
He wants to he wants to be able to watch courtside for the love of the game.
28:20
Y >> whereas somebody that's going side at the Lakers or the Knicks, they're going there to be seen watching courtside, right?
28:30
So they're willing to like it's not you're not just paying to watch basketball, right?
28:34
Because you could pay like, you know, a fraction to sit a couple rows back, you're paying to be >> sitting courtside, right? >> Yeah. Yeah. Yeah.
28:41
I think um the other the other uh interesting uh angle is is is this like region lock thing.
28:48
It almost feels weirder to allow someone in Los Angeles to watch the LA Lakers play because they really could just buy a ticket and go down to the stadium, but maybe you should actually.
29:02
>> That's the whole point.
29:02
If you're if you're like a diehard Lakers fan, but you don't live in Southern California, and then somebody says, "Hey, with the Apple Vision Pro, you can watch it like you're courtside." That's great. >> Yeah.
29:13
What you actually want is like Ben Thompson's in Milwaukee.
29:15
He loves the Bucks, but they're playing in LA.
29:18
He's not gonna buy a flight to go courtside in LA and so you let him experience that game and then when they're back in Milwaukee he can go get the courtside seats in his hometown.
29:28
So you almost want to do the inverse region lock something like that.
29:32
I don't know what do you think Tyler?
29:34
>> Um wait so is that deal where it's just the broadcast not the actual like live stream is that basically every single league like can you do the same thing in F1?
29:40
>> So because that's also like I feel like that would be everyone wants that you're in the you're in the cockpit.
29:43
So, so e every deal is unique and there's no there are some uh there are some laws around sports broadcasting and that sort of solidified like the blackout periods and made some of that uh defined some like legal language around that.
29:57
But really it's up to the leagues to decide how they negotiate these contracts whether every game's available only home games are available region locking blackout dates.
30:08
There's all sorts of mechanics where uh for for I I don't know how how true this is today, but I know that uh if you have a home stadium and it's full, then you can be much more permissive with the broadcast rights because you've sold out all your tickets.
30:24
But if you're if you're not selling out this the stadiums, then often you won't broadcast as much or you can't broadcast as much.
30:30
So you'll you'll be in your hometown and you'll go to watch the game and it won't be broadcast because they want you to just go buy a ticket and then and then the the equilibrium like the clearing the market clearing prices that people that are on the fence who are like I really wanted to watch the game. I can't watch it here.
30:47
I'll just go buy a ticket >> and then over time you fill it out. Yeah.
30:51
>> You're going to be very excited about this.
30:52
Please >> Ben Thompson's gonna join the show right now. >> Really? No way. Amazing.
30:55
[laughter] >> That's fantastic.
30:58
Someone in the chat earlier said uh you're Ben Thompson's biggest fan. And you are. We are. >> That's amazing. Oh, fantastic.
31:07
>> So, we're working on getting Ben on. >> Fantastic.
31:09
>> Um to uh continue the discussion. >> Um okay.
31:12
Yeah, this will be a lot more extra context because he is he is the expert in this.
31:16
Uh in the meantime, let me tell you about app loving profitable advertising with made easy with Axon. ai.
31:22
Get access to over 1 billion daily active users and grow your business today.
31:26
Uh, Maduro, we're back in politics land, but don't worry, not for long because we're going into watch land because he was caught rocking a chopard Ganesha, a fantastic Indian watch that uh is incredibly incredibly detailed.
31:43
Look at all these different Swissade.
31:46
This is a crazy I feel like this is sort of a lost art, you know.
31:49
Maybe Mark Zuckerberg should get into this.
31:51
wear a watch that has, you know, uh, uh, Sweet Baby Rays on the dial.
31:56
The Sweet Baby Rays Chopard dial might go incredibly hard. I would love that.
32:04
Uh, also, it was the Golden Globes.
32:06
I know Jordy [clears throat] didn't watch because you probably haven't seen any of these movies.
32:10
Uh, but they they did in fact happen yesterday.
32:12
Uh, Rob Report has some images of the best watches at the Golden Globes.
32:17
Uh, if the Golden Globes were any indication, Subtle is officially on hiatus, says the Rob Report.
32:25
Uh, this year's red carpet made a strong case for statement watches with bold dials.
32:31
>> Did we kind of call this originally with the show? >> Did we?
32:33
The uh I mean, no, I mean, we we the joke early on was like quiet luxury is over. >> Yes. Loud opulence. >> Loud opulence.
32:41
>> A lot of these are screaming loud opulence.
32:42
In fact, I need to return to my Let's start with the beginning of this of the slideshow.
32:46
Um, we need to return to uh my our original statements about um about, you know, uh the the the value of loud opulence because I see these and I'm like I couldn't pull these off with my life depended on it.
32:59
Uh but the rock was spotted watching a chopard much like Maduro.
33:04
Uh but this one is the Alpine Eagle frozen summit.
33:07
Look at all [laughter] those diamonds. >> I like it.
33:11
But I'd like to see I mean could we get at least a couple more >> couple more diamonds >> diamonds on here?
33:16
I think it's a little it's a little understated.
33:18
He could have gone with, you know, the rainbow the rainbow one, the gem set.
33:21
It's the Rolex with all the dime the different color diamonds.
33:25
Who else is wearing fine luxury watches at the Golden Globes?
33:29
Adam Scott was wearing a Vashron Constantine Traditional Perpetual Calendar Ultra.
33:33
That's a very nice watch. I like that one a lot.
33:35
I also like this Omega Se Master Aquaterara that Glenn Powell was seen rock uh wearing.
33:43
>> Mark Andre notoriously. >> He's an Omega guy. a good guy, right? New fund.
33:47
Maybe this was a nod from Glenn saying like, "I salute you." Hat tip. >> Yes.
33:52
He's celebrating the 15 billion.
33:52
He probably read the Paky piece >> and he says, "You know what?
33:55
I it's time to put on the Omega C Master Aquaterara."
33:59
Uh, in terms of Omega C Masters, this one stands out to me.
34:02
Uh, gold is a is a choice, but I think it's working very well here.
34:06
And you know who else is wearing a Omega C Master? George Clooney. Also an Aquatera.
34:10
I would love I would love to know the details of Omega and Rolex and the other brands like fighting over people like Clooney, right?
34:21
>> Uh because you know I don't think Clooney is putting on a watch without getting paid. >> Okay.
34:26
Well, we have Ben Thompson in the Reream waiting room.
34:29
Let's bring him into the TV at Ultra. >> Fantastic. Ben, how are you doing? >> Here he is. >> Good.
34:36
>> Thanks so much for hopping [laughter] on the show in such short notice. Uh I loved your piece.
34:40
>> I have I have takes to drop.
34:40
So I am I am >> Let's go. >> Let's go. Okay.
34:44
So uh I mean uh drop your first takes and then I want to know uh is there anything to what I was saying that that Apple actually does read your work and they do want to do it but they just can't because of some contract.
34:55
>> Oh I thought you were talking about watches. >> Oh no.
34:57
I was talking about watches. What's on the wrist man?
34:59
[laughter] >> Uh I have a tutor GMT. >> Very basic.
35:06
>> But highly recommend it.
35:06
T's favorite place to >> start.
35:07
And and it's covered in diamonds, I assume, like the rocks. >> Uh it is not.
35:10
[laughter] It is very basic with a rubber band cuz rubber bands rule. >> Oo. Okay. Rubber band was good. Yeah.
35:18
>> So, uh and I disagree with your take, >> please.
35:21
>> Um so, my overall view, NBA was on the Vision Pro on Friday. >> Yeah.
35:28
>> They had an NBA clip when they launched the Vision Pro.
35:30
So, I was there when they watched it.
35:32
So, I got to try it that day.
35:33
They took that clip out for the demo that shipped and that was in Apple stores.
35:38
So you only saw that clip if you were there the the first day.
35:41
And so I was a right to choose which I maybe lends itself to your argument or whatever it might be.
35:47
>> But it that was for sure it was like 3 seconds.
35:50
It was the clip that sold me on the Vision Pro more than anything cuz you felt like you were there. It was amazing. Yeah.
35:56
>> So they have this finally have a live sports thing which is a big deal.
35:59
They demonstrated that they can show stuff live and it worked. It worked well.
36:02
I don't think there was any technical issues.
36:05
Uh the cameras are quite small now compared to what they used to be.
36:09
You could see them on like the sideline table and underneath the basket.
36:13
>> So this technology works.
36:13
You can watch things live in the vision pro and it should be amazing and it sucked [laughter] and and it sucked because you're getting jerked around all the time. You're not you're there.
36:26
You feel like you're there. It is immersive.
36:31
The unemersive part is the Apple part, which is some producer in a truck is moving you around. There's a pregame show.
36:39
I don't need a pregame show. I'm sitting courtside.
36:40
I can watch the players warm up.
36:41
And the reason why I disagree with your take that Apple knows this. Okay. >> And wants to do it.
36:46
Is that every Vision Pro video has the same problem. >> Okay.
36:52
>> The Metallica video, super cool. You walk in.
36:55
The opening scene of that is amazing.
36:57
Well, there's the little bit where they're in like the the green room or whatever, but you're walking in, you're walking behind James Heatfield and you're in the crowd and it's like walking through and people are reaching and it's like it's so amazing and then suddenly he's going up the stairs and boom, you're jerked to somewhere else and you're seeing him come up this on the stage.
37:13
You go back, they cut this MLS video which they have the rights for. They're overpaying.
37:17
You want to talk about the F1 deal?
37:19
Look how much Apple's paying MLS.
37:20
Like one of the most absurd overpays in the history of sports.
37:24
I think they can do whatever they want here.
37:26
They cut a I love laugh tracks, but it is [laughter] very disruptive to hear.
37:30
Um >> they cut like a season and review video. Yeah.
37:35
That had like 56 cuts in it.
37:35
It's like done by >> What do you think it is?
37:39
Do you think it's like Do you think it's production teams that are just trying to create work for themselves because they go in there and they're like, "Hey boss, actually the people just want to they just want to put their goggles on and hang out."
37:48
It's like, "Well, then what are you doing here?"
37:51
>> I feel like there's just a lack of confidence here.
37:53
like like what I it feels very like it feels when you say it it's like halfass that we're going to go out we're just going to set a camera there and you can sit there and watch the game.
38:05
It's like no >> there's this pressure in part because it's not popular.
38:09
We It has to be a big production.
38:11
We have to have a pregame show.
38:13
We have to have dedicated announcers.
38:14
You have to do all the things.
38:15
The end result is you get six games which are physically uncomfortable to watch because you're getting jerked around and like they could have just the Vision Pro there. Yeah.
38:23
For every game and I would pay a lot of money to watch that.
38:28
They could have it at every concert and this sol it's what's amazing is it number one it would make it better.
38:35
I'm fully convinced of this. Yeah.
38:37
And number two, it would solve their content problem because you could suddenly have tickets to every single concert in the world, to every single game in the world.
38:45
It's it is a classic tech issue where you put in the upfront cost, you buy the cameras, you install them, and you have marginal upside forever everywhere.
38:54
forever everywhere. and and it it's latching on to a major trend which is live which is this idea that when everything's commoditized online everything's digital live experiences are worth more and more and more like you go back to like the Aerys tour and Taylor Swift like a big topic of discussion at that point because like
39:13
this is a something people are >> sports specifically are like pretty immune to to AI because nobody wants to watch like the AI box play >> no watch AI basketball right yeah it's the it's the human aspect And I don't think it's the thing that was most crazy to me is that it was like geolocked to Southern California. >> I get so I get that. I I'm not going to >> I get so I get that.
39:32
I I'm not going to like be on them for that because but part of it the reason why it was geolocked is cuz Spectrum spent all the money to do all this production >> and so of course they get the benefit.
39:44
It's in their catchment area.
39:44
But you don't need to do all that.
39:47
They're overthinking this.
39:49
like literally set a camera on the sideline and do nothing else.
39:55
I will be happy as a clam. >> Okay. Okay.
39:58
Uh it is expensive to do immersive production at the same time.
40:03
Blackmagic has the Ursa Cinei immersive that have you seen this thing?
40:06
Two fisheye lenses on the front 16K. It's it it cost $30,000.
40:11
And it feels like if this is the case, there has to be an opportunity for someone who's a little more agile, you know, maybe it's Red Bull, maybe it's some league that's not front and center to just go and do this.
40:26
They have to pay 30K up front. >> What's expensive? >> Yeah. 30K is nothing. Okay.
40:29
Like we're we're all in the tech industry.
40:31
We can laugh at figures like that. Okay.
40:32
So So that's an upfront investment.
40:35
Like the problem is they tacked on all these marginal costs to this production.
40:40
So, when you logged on for the game, there was a dedicated pregame host and show for the Apple Vision Pro viewers.
40:48
>> That's almost certainly not going to be as good as the main pregame [laughter] >> that where they're paying where they're paying like hundreds of millions of dollars >> is sitting courtside and watching NBA players warm up and make 57 threes in a row cuz they're incredible.
41:00
Like, I don't know if you guys have ever sat courtside, but like it's it's >> it's amazing.
41:06
Like, speaking of watches, this is where I spend my watch money, okay?
41:11
It's it it's an unbelievable experience and and you and they have all the like they have like uh for example they have like replays in there >> which okay yes you can see the better of replays.
41:22
You know where else they show replays >> on the scoreboard.
41:24
[laughter] How else can I see the scoreboard?
41:26
I can look up because I'm wearing a vision pro that's immersive and has this fisheye camera where I can see all around it.
41:32
I don't need a scoreboard bug down at the bottom.
41:35
I can look at the scoreboard.
41:36
[laughter] Like I actually during the game while watching it, it was actually kind of hard to see the scoreboard bug cuz it was way down at the bottom.
41:42
So I was looking at the scoreboard in the arena the whole time.
41:46
Yeah, >> that's the whole that's the whole thing. You're there.
41:50
It's it's And so all that stuff, the the pregame show, they had dedicated play-by-play announcers and and analysts for the Vision Pro.
41:57
They had these multiple cameras.
41:59
They had a production truck who's choosing how can I upset Ben this time and every like [laughter] the other cameras.
42:06
You didn't need any of that.
42:09
And and and you $30,000 is a onetime cost. Yeah.
42:12
You spend that money once and you put these cameras in every arena for every game everywhere and then you you suddenly have this exclusive selling tickets to live events in a way no one else can.
42:27
I think it's a huge like it seems so clear to me.
42:32
This is the Vision Pro use case.
42:34
This is your portal to every live event in the world.
42:38
>> What do you What do you think about Meta Meta's efforts on uh NBA uh partnership as well?
42:45
>> Specifically with Oculus >> the Vision the Vision Pro is better.
42:46
I mean like the the like the Oculus has advantages relative to the Vision Pro.
42:52
Actually I love Mark Zuckerberg's post and the Vision Pro came out.
42:54
It's like oh we're not surprised.
42:55
We could have done that but we didn't. Which was valid.
42:58
Um I'm also not particularly interested in the use cases that are good for that.
43:01
I don't care about gaming.
43:02
I don't care about a lot of the other stuff. Yeah.
43:04
>> Uh, like this is for me the killer use case for sure.
43:07
Like being able to >> Yeah. Yeah.
43:10
I mean, it seems like the next uh the next Quest, if they stay in VR, will be better.
43:13
We talked to James Cameron uh and it seemed like he was pretty excited that they might have gotten the same screen from the Apple Vision Pro.
43:21
like yeah, they're two years behind, but you bring that screen into the next Quest 4, >> which is fine, but then there's trade-offs for that as far as like number of pixels and the the field of view and all those sorts of things, but like the the the whole point is that $3,500 feels overwhelming, like for what you get. >> Mhm.
43:38
>> $3,500 to be able to attend any sporting event in person is one of the greatest deals of all time.
43:43
Yeah, I used to be in Taiwan. I used to be in Taiwan.
43:47
I would fly over for specific games like um and guess what?
43:50
I would spend more than $35 on my ticket.
43:52
I'm not flying in the back of the bus at this point. Sorry.
43:55
Like so like like the this would this is >> it is like it's like when the the Apple Watch when they realize oh people it's f it's fitness.
44:04
it's fitness. Remember they watched with all these lists of different things and what you could like remember you could like draw your Apple Watch and it would like draw you [laughter] >> the heartbeat texting to send someone a heartbeat that never went
44:16
>> who's the Apple who's the Apple exec that's the most hardcore NBA fan cuz I feel like I feel like you got >> I so I I know how much Golden State tickets cost because I sat well I I actually I was poor so I was in the second row behind the seat that was inscribed with Eddie Q's name on it right there. >> Uh yeah, he would he would he would be
44:37
>> Uh yeah, he would he would he would be the he's the guy that needs to argue for this. >> Okay.
44:41
So, do you think this is a next season they might get it right?
44:43
Are they already pre-baked on the next on the next because they have like four more games.
44:48
It feels like they could take this they they have the footage like they could just not edit the next game, not do that broadcast and do exactly what you're prescribing. >> I hope so. Look, free advice Apple.
44:57
This is your That's why I made I I've written this.
45:02
So number one, the reason I disagree with your take is because every video they make suffers from this problem.
45:07
They're they are produced in a TV style for a device that is fundamentally different than TV. That's the core problem.
45:15
>> Is [laughter] there is there at least a a possibility that Metallica also said, "Hey, we don't want a substitutive effect. We don't want people." >> Yeah.
45:22
So it's so funny to think the same thing. >> Lots of other videos.
45:25
They made lots of other like every video they have suffers. >> Yeah. Even the Alicia thing.
45:29
Can you can you imagine if the if the NBA actually sold a ticket where like every 30 seconds you had to stand up and go watch from a different [laughter] from a different view?
45:38
It's like they're like it's amazing. You see every angle.
45:41
You're like, "Please, sir, I just want to sit and watch." >> I turned it off.
45:44
I I I I watched both I watched half the game on TV cuz it was it was uncomfortable.
45:51
>> What do you What do you think is the long-term like like viewing like ideal viewing experience?
45:55
Is it you have it on TV and you have your your Apple vision and you're kind of like, you know, based on how closely you're paying attention, you're either like locked in >> with the vision pro on or you have it on.
46:08
>> But the >> I think that a big thing for sure, the the biggest missing experience is of course I want to be on my phone half the time like uh like any person.
46:18
>> I do have the the the M5 Vision Pro.
46:22
It's the first time I ever took a demo unit.
46:23
I've always like declined to do that, but I'm like there's no way on earth I'm paying for this, but I [laughter] do actually want to see if there's any difference.
46:29
The my actually biggest takeaway is the pass through is much better.
46:33
This might be I didn't do a I didn't do a direct compare.
46:35
That was just sort of my perception.
46:37
And to be honest, I haven't used a Vision Pro in a long time, so who knows how good my memory is.
46:41
The pass through was really good.
46:43
I had no issue using my phone at all.
46:45
It did seem better than it used to be.
46:46
Um so, but maybe that might be placebo just just to be clear. Getting screen time.
46:50
Getting screen time through another screen [laughter] is elite. >> It's a lot.
46:56
>> It's It's We got levels. >> Wait.
46:57
So, your screen time app could potentially show more than like [laughter] I had 26 hours.
47:03
>> 26 hours today because I was in the Vision Pro using my phone, my laptop. >> What a world. What a world. Um that's funny.
47:10
Um well, uh I mean, are you optimistic about any other Apple Vision Pro like opportunities?
47:15
Pro like opportunities? Because, uh I was looking at this $30,000 immersive camera and I was thinking like I I was actually advising some friends who they shoot a much more uh like like evergreen podcast like these really definitive interviews and I was saying maybe you should start shoot they were shooting in 8K because they were like hey maybe one
47:35
day we'll license these to Netflix we want the extra resolution we're not distributing in 8K but we have it now and I was saying well you want to go further why not 16K why not immersive maybe you should get this thing start recording now this particular device can only record for like 45 minutes I and then you have to swap the cards or whatever. But I was like maybe you
47:50
But I was like maybe you should be doing the flow maybe not this year but maybe next year.
47:53
Uh are is there is there some opportunity where someone >> who's there's lots of opportunities like like and I think like there there's real enterprise opportunity like for like especially with the pass through and things that you can do along those lines.
48:07
There's productivity sort of possibilities but you need like what is the anchor thing?
48:11
What is it everyone knows that this does?
48:13
And again I think the Apple Watch is a good example here.
48:17
It took them a while to get to that.
48:18
They launched with the physical fitness stuff, but it wasn't queer that that was the thing for a few years.
48:23
And now every vision, every Apple Watch thing is fitness, fitness, fitness, fitness.
48:28
It saves your life and you know, uh, all those sorts of things. And to me, this is it.
48:34
It It is you get live in your living room.
48:37
That's the vision pro pitch.
48:40
>> That's going to be fun.
48:40
We'll just have to wait another five years for them to back down from their their opinions.
48:45
It's but >> we're going to find we're going to find out the day.
48:48
You did write this two years ago.
48:50
Like I wrote this the day I wrote this the day it launched.
48:53
I said >> what's amazing about this is you don't need production.
48:58
All I want is to feel like I'm there and it delivers.
49:01
It lets you do you know do you of course you don't know you're there.
49:06
The resolution isn't perfect.
49:07
There is a bit of tearing if you go super fast.
49:09
Like the peripheral vision's not not not perfect.
49:13
But it is it's it's amazing.
49:13
It's an incredible experience that that no one else can match.
49:18
Quest can a little bit, but but the the Vision Pro in part because [clears throat] Apple invented these cameras.
49:22
Like Blackmagic is making them, but it's Apple's whole format.
49:26
It's Apple like created the whole thing.
49:27
And yeah, it like it's it just feels like this is a company that >> it's like a lack of confidence.
49:35
>> Y >> you let the device do what the device can do.
49:38
Stop trying to like overdo it.
49:42
put your we no step back. Yeah.
49:42
Just step back and let it do its thing.
49:45
And I'm more convinced than ever.
49:48
I I again I've been having this take a few times.
49:52
I wrote about the MLS thing.
49:52
I wrote after the Metallica thing.
49:54
I put on the front page of checkering today.
49:56
I'm like look, no one in the world cares about this device other than me. >> I know.
50:01
>> But [laughter] >> I'm desperate for someone to read this. So there's no payw wall.
50:04
You don't need a [laughter] forwarded to you. Just read read this.
50:09
And and they had to do the Bucks, too. It's so funny. It's like the first one.
50:14
It was a royal flush for you.
50:16
I I have a meta question about just uh being in a position to review new technology and having to deal with uh like the Pepsi challenge.
50:25
Are you familiar with the Pepsi Challenge story? >> I am. I Dude, I'm Gen X. I'm very old. >> Okay. Yeah.
50:30
So, so the Pepsi challenge, for those who don't know, it they they they had people taste a little a 1 oz cup of Coca-Cola, 1 oz cup of Pepsi, and overwhelmingly the random people that came and tested said the Pepsi tasted better.
50:42
And what the result was was that Pepsi was sweeter, so it tasted better over 1 oz.
50:45
But over 16 ounces, a full can, it was more like 50/50.
50:48
And people actually did prefer the Coca-Cola.
50:50
And I feel like with a lot of hardware devices, you put it on for 10 minutes, it's amazing.
50:54
You put it on for half an hour, it's incredible.
50:56
hour, it's incredible. But then then pretty quickly the you know the big tech executives say oh that's enough of the demo let's talk to you about something else uh now write your review based on 30 minutes and it's a very different
51:05
experience than two weeks a month seeing if it collects dust seeing if you churned and I'm wondering just how you deal with that mentally where you have to talk about something but at the same time you're not getting the you know you haven't been able to spend a year with a product. >> No it's a good point. So my way to deal >> No it's a good point.
51:19
So my way to deal with that is I generally don't do product reviews.
51:23
So that makes it that makes it much easier.
51:26
I think with the the vision pro though is a great example of this phenomena.
51:30
It is like the first 30 minutes of using a vision pro is one of the most mind-blowing experience of your life and it continues to be.
51:36
I actually I remember when I first got it I actually had uh I'm not I f perfect fall on from the watch segment cuz I found like a total douche this thing.
51:46
I had my assistant I had it shipped to his house and had him fly to Taiwan to bring it to me because uh it wasn't it was only available in the US and the and and and >> I remember actually I was going I think this is awful.
52:00
This is so [laughter] patient.
52:01
I was going on a ski trip like a week later.
52:03
So I'm I'm up there and I remember I'm sitting in this bar up in Seikko and I'm like all the ski instructors like cuz I was friends with I had the same guy for many years.
52:15
He brought all his friends over and they're all trying this.
52:17
I like I hone my whole demo script and like we still talk about this afternoon with the vision pro in this bar in Deco trying it and it's it's amazing.
52:26
It's absolutely incredible.
52:26
But then >> what do you do with it, >> right?
52:31
Like that's the big question.
52:33
What I will say in the Vision Pros defense is even now I don't use it very often.
52:40
>> Every time I put it on though I'm like this is so cool.
52:43
like it it retains that aspect of there's something magical about this experience.
52:48
It's just searching for that ongoing reason to come back that use case and that comeback use case needs to be something that only it can deliver.
52:57
The productivity things are cool.
52:59
productivity things are cool. I I would I I but I I the other thing >> the other thing I think is really real is like maybe from Apple's side like they have this device it has so much potential it's so exciting it's so cool and then it it it's almost disappointing that like okay the use case is just like live sports right because they're like we want to create the next computing
53:19
paradigm but the reason that it actually is is an incredible niche is that like what's more mainstream than bread and circuses right what's more mainream >> sports problem it's a chicken and egg problem you like the way you get those those productivity experiences and those new things that weren't possible before is you have a large install base that draws developers in to create those experiences. But to get there, it needs
53:41
But to get there, it needs to be a market.
53:44
So you need sort of the initial use case to create like this is why the iPhone is the greatest platform ever. Everyone needed a phone. Yeah.
53:53
Like so like so you you got that built-in sort of advantage so that developers like they didn't have to do anything to earn developers.
53:59
They just shipped the best. >> Yeah.
54:01
So that's what I'm saying like if you create this amazing live sports experience you get a million people that are using it multiple times a week and then and then they're using it.
54:09
They're watching they're watching together. It's a social thing.
54:12
Then they can be asking >> social [laughter] I [clears throat] put it on.
54:17
I don't look very social.
54:19
No, but but I'm I'm talking about more like maybe you have a FaceTime call open with a buddy in the headset and you're watching it together.
54:26
You're hanging out watching the game or something like that.
54:29
>> No, I I would just say I think it's the Vision Pro is more of a single player experience.
54:35
>> But what is the biggest single player market in the world? >> Productivity.
54:38
Like when I'm doing work like I want I I'm on my own working on it.
54:44
Right now I have four monitors.
54:44
Like I I'm one of those crazy people like a Vision Pro.
54:49
I wish I would have brought with me last summer when I back to Taiwan because I was actually doing work and I was working on my laptop and it was terrible.
54:56
Like, oh, I can't believe I didn't bring this.
54:58
It was the perfect use case for me to use it.
54:59
But by and large, I don't need it.
55:01
But if there were particular apps or use cases that were uniquely enabled by it, maybe that would be a reason.
55:09
But you're only going to get those by drawing in developers.
55:13
You're only going to get developers by having an addressable market that is worth putting the investment into.
55:17
Which means this is always been a this is one of my big thesis on strategy.
55:21
It's always been a question on tech chicken or egg. What comes first?
55:24
The device, the platform or the developers?
55:27
I was at Microsoft in with Windows 8.
55:29
I spent a lot of time and spent a lot of Microsoft's money getting developers. That doesn't work. What matters is demand.
55:39
Demand pulls in developers.
55:39
You need the core to sell a bunch of devices and then you can start the virtuous cycle.
55:49
To me, the core use case for the vision pro anyone remembers it exists and I'm not sure that Apple executives do is live in your living room.
55:55
You do have a bunch of devices and then you pull people in.
56:00
>> I have a buddy TJ who worked at Apple at one point when the vision pro was announced. He got it. He was so excited.
56:07
He was like, "I'm gonna spend the next three years building products for the Vision Pro." How long did he last?
56:11
He lasted like three months. Yeah. Like, no, no, no. Like less.
56:15
He was like, "What's the point of build?
56:16
What's What's the point of building for uh He's super talented, but what's the point of building if there's nobody there?"
56:21
You know, you know, it's not >> Are you Are you uh You mentioned the four monitors.
56:26
Are you going in on the 52 in Dell 6K monitor? >> No. Way too low resolution.
56:33
>> Way too low resolution. >> Actually, I lied.
56:34
No, I'm actually on the fifth monitor right now.
56:36
Um, [laughter] just for podcast.
56:37
So, I have I have two 4K monitors. I have my laptop.
56:41
I have another I have with that LG like square screen. Super useful.
56:42
It is Rosville resolution.
56:45
But then for podcast, I have a 55 in TV here. So, >> okay.
56:49
Staying staying on Apple.
56:49
Uh, Gemini the the Gemini Siri news dropped this morning.
56:55
It had been kind of previously reported.
56:57
So, in some ways it's old news.
56:59
What are you What are you expecting out of like this new version of Siri?
57:07
>> Well, the bar is 55 ft underground, so [laughter] I expect it to be a lot better.
57:12
Uh, no, I think it makes a lot of sense.
57:14
I mean, it's uh [laughter] now that the federal courts have approved Google and Apple combining to rule the world, Google has Google has the infrastructure to support the scale of Apple.
57:25
They know how to work together.
57:28
They've worked together for years.
57:29
They're are very natural partners in that respect that Google can think big picture about this.
57:33
Like I'm sure Apple the report that Mark German had last fall was Apple's going to pay like a billion dollars which again we're in tech that's no money at all which but it's tied into the search deal like they can massage it.
57:44
The problem with working with an OpenAI or or an anthropic is they need to make money and so like Apple doesn't I think there there's a more sort of I scratch your back your scratch my back sort of thing here.
57:56
Google's talking about, you know, working with Apple's chips, adapting it, whatever it might be.
58:00
Apple's does bespoke stuff like that.
58:02
So, I I I think it makes a ton of sense for both sides.
58:06
Um, >> do you think do you think it ever flips?
58:09
And do you think uh do you think Google will be paying Apple?
58:11
Because there's this news also that you're going to be able to do shopping through Gemini.
58:15
And so, you could imagine a world where you go to Siri, you ask for a product, and there's ads in that Gemini result.
58:21
And and Google's the one that's monetizing that.
58:25
So, they're passing some of that revenue back to Apple. >> It's a good question.
58:28
I mean, I think when Apple talked about like the next generation Siri and Apple intelligence, I was pretty optimistic about this idea of Apple basically replaying the search.
58:38
>> That's my that's my whole thing.
58:38
I'm like I'm like in some way if I'm Apple and I'm paying for an LLM to use it to power a product that can basically do search really well, that could eventually have an ads business attached to it, that eventually could have like commerce built into it.
58:52
Like it's this weird it's this weird situation where like Gemini is effectively helping like that's that's what I don't fully understand yet because I'm gonna be like >> I think that the market structure was so perfect for Apple in that they need like it's just a default search engine.
59:06
It's there's no sort of deep integration into the product.
59:09
It's just like when you type in your search bar what engine is used and so it's super easy like there there's like a concept when it comes to like figure out who's going to win in a value chain.
59:18
super easy subst sub substitility is good for whoever can plug whatever in.
59:25
So they could choose whoever they want.
59:26
So it made sense that the value flowed that direction.
59:28
The difference with this AI stuff is it needs to be integrated deeply and Apple is more on the defensive here like they need to have quality AI features built into the operating system.
59:40
And so I think the need is more on Apple's part.
59:42
And the benefit Google is getting, my suspicion, is less that they're is less about the ad thing and more they're getting some incremental revenue and they're probably getting a lot more.
59:57
I mean, Apple's going to be precious about the data.
1:00:00
We'll see how that sort of works, but um but they also don't need it's all incremental.
1:00:06
>> Even like the internal reasoning rollouts and and all of that that happens in Gemini, like Apple's not going to be able to claw all that back.
1:00:13
So you're going to have all this like reinforcement learning training on okay maybe maybe you're obiscating the the the the privacy data what the person asked for but all those interim steps of I went to a website I interacted with it I figured out how to click this button like that's that's going to acrue to Gemini you would imagine >> well and what it speaks to I think is what would be the red flags that would come up to this deal from an Apple
1:00:35
perspective it's like well they're not yet maybe they need to tough it out and build their own crappy LM so that in the future they control their own LM M such that if if you get to a world with say AR, right, where I'm I'm actually
1:00:49
>> lots of dispute about this, but I'm pretty optimistic on just in time UIs where the idea that something pops up that is nothing but the decision you need to make in that moment for whatever it might be and then it goes away. Like
1:00:59
Like to me, this was the the best part of the Orion experience was the the Facebook sort of AR glasses was when I received a call because the the the OS I used there was kind of like Quest just sort of dumped in there and it would it didn't really make s you have like blocky stuff and there's like an Instagram and stuff.
1:01:17
It's like I I could just look at my phone.
1:01:19
This is going to be better here.
1:01:20
But you could be >> we got I got a conversation right now.
1:01:21
I could have a notification pop right now saying so and so is calling and I could use my own little wrist thingy and and dismiss it and it's just there when I need it.
1:01:31
It only has one option accept or decline and then it's gone and and I could see that being a future of UI and important for Apple to control but by not shipping their own by depending on Google they might say pretty words about oh we're going to simultaneously develop our own no that whatever if you're that's not going to happen.
1:01:51
you're going to be so invested in this other one.
1:01:53
And that speaks to the value is acrewing to Google cuz they're the ones actually developing and pushing the technology and Apple is sort of trailing along.
1:02:05
Given that I have a hard time seeing you Apple's going to get more and more deeper into this using Gemini, are they going to be able to credibly go to Google say pay up or else we're going to switch to someone else?
1:02:15
I think that's probably unlikely.
1:02:17
So, I don't think it's going to play out like search, but we'll see.
1:02:21
I was obviously wrong about this once, so I could certainly be wrong again. >> Sure.
1:02:24
>> What was your reaction to the Manis acquisition?
1:02:26
From my point of view is exciting.
1:02:28
Um, specifically [clears throat] because Zuck has just been spending all this money on talent, but if you look historically, he's been very good at like buying something, scaling it.
1:02:36
It's sort of unclear to me so far whether he plans to take Manis from a hundred million dollar run rate to multiple billions or just leverage the team's ability to build great agentic, you know, effectively workflows product.
1:02:50
Um, how are you thinking about it?
1:02:54
>> Yeah, I I just I I have a hard time seeing the meta in the enterprise sort of angle.
1:02:58
of angle. So >> no but but I but even but even more talent than >> but even it's like like figure out the best product in this category and buy it for me >> like that that kind of work like that's what I can imagine the man being that's
1:03:12
my sort of understanding yeah is like this is actually a really excellent product team that is doing very good work and is worth having on board and does that mean growing their business into something larger that's a material source to our business? I think that
1:03:23
I think that would be a mistake.
1:03:25
Um, but I think the idea of agentic workflows uh is obviously a very compelling one.
1:03:33
Actually, one of my favorite things Mark Zuckerberg has been all over the place on AI.
1:03:35
I think I did an interview with him like nine months ago that was kind of bizarre.
1:03:39
Uh, it was right when he was clearly thinking through maybe I need to reset everything and I thought that sort of came across in the interview at the time.
1:03:47
But one thing he did say is actually what is the largest sort of most profitable atscale agent right now?
1:03:55
Facebook advertising, which I think is a very or or Google advertising thing. A very astute point.
1:03:59
You go in, you tell Facebook, I want >> I'm willing to pay a $149 for a customer or $9. 99 for a customer. Go get them.
1:04:09
And it goes out and gets them.
1:04:09
Now, is that a full LM denominated probabistic workflow?
1:04:12
No, it's it's not really LLM's.
1:04:14
It is more probabistically [clears throat] post.
1:04:16
But the idea that you ask for a job, the the focus is on the job to be done as opposed to specifying how you do it and that is just by and large for most advertisers particularly in the long tail probably at part of the tail too they just don't want to give up control the better way to do it.
1:04:34
And I think there's going to be lots of things like this.
1:04:36
I think Google's announcement with Shopify and and this idea of of you know ads that are perfectly targeted the user very compelling makes a ton of sense.
1:04:44
Uh that's where something like rock by the way fits in like super fast inference so you can generate like you think about how advertising works these auctions that are run and you get ads in the time it takes to load a web page is absolutely incredible where the the next step is would be insert generative ads into there which is going to require very high inference speeds.
1:05:04
Um so I think and this has always been the most compelling short-term AI monetization opportunity is basically Google and Facebook ads.
1:05:12
That's why I've been super bullish on both of them.
1:05:13
I think it's why Facebook needed to do this reset um and why Google, you know, it's justifiably been sort of going to the moon recently.
1:05:23
>> Well, uh what do you think of Eric Seuford's point that uh that you might not actually need to put the ads in the LLM responses in the sense that you could be you could be going to an LLM and saying, "Tell me the history of the Roman Empire."
1:05:35
It knows that you're shopping for shoes, for new shoes, and it shows you ads for shoes in the middle of your Roman Empire deep dive.
1:05:41
Just like on Instagram, you can be scrolling one thing and your algorithm can be recommending you a certain type of content, maybe like dogs, showing you dog videos, but then it also knows that you need luggage for your next trip and it's showing you ads for luggage or something.
1:05:56
>> No, I think I think I think it's a great point.
1:05:57
I think Eric makes some good points about like you're running a real risk of conflict of interest, even the perception of conflict of interest. >> Totally. [clears throat] Yeah.
1:06:05
>> Otherwise, and so I think that's a very good point.
1:06:08
And the reality is that's a much larger business like just being uh show what you're looking for is inventory.
1:06:15
The number one way to predict >> sort of the upside for Meta over the last several years, >> the stock market has consistently had it totally backwards.
1:06:25
>> Every time they're sort of uh their price per ad would plummet because the stock market would freak out.
1:06:31
This happened with stories in like 2018, 2019.
1:06:34
It happened with with reals a couple years ago.
1:06:38
>> And what the what the the issue is that the reason why price brand plummets is because there's a massive increase in inventory.
1:06:44
And when there's a massive increase in inventory, it's just more places to show ads.
1:06:48
That is a huge opportunity.
1:06:50
And you saw huge runups both times as they figured out how to monetize stories, as they figured out how to monetize reels.
1:06:55
how to monetize reels. And this should be an opportunity of how to like it's it's going to take a while to figure out how to monetize you know maybe it's maybe just an aspect of when they're reasoning when they're thinking or image
1:07:09
generation that might be an ad opportunity and it's a big opportunity a big problem is these folks I think the openai has hired so many meta people it's confuses me why they haven't been on board with this like it's a winwinwin you get you need money to fund your operation. The best way to make money is
1:07:27
The best way to make money is to is to show ads. Why?
1:07:30
Because you get to deliver a better product to more people.
1:07:35
This idea that we're going to commit to a world where if poor people get a worse product, that's not how tech works.
1:07:41
And the reason why tech is amazing is it generates a ton of consumer surplus.
1:07:45
You do this upfront investment and because it's monetized by ads, everyone gets the best product. It's great.
1:07:50
and OpenAI like having this religious devotion for so long about not doing this.
1:07:55
If they had launched, they could have launched the world's crappiest ads in 2023.
1:07:57
By today, in 2026, they'd be good.
1:08:00
They'd be making money and people would rebel against it.
1:08:05
Now, they're going to have to launch ads.
1:08:06
They're going to suck and people be like, "This sucks.
1:08:08
I'll just go to Gemini or whatever it might be."
1:08:09
Gemini or whatever it might be." just it drives me bonkers because like >> it seems like there's a little bit of like uh not to go back to chicken and egg problem but like the fuh first mover disadvantage like the first LLM that has ads there'll be a whole press cycle about oh Gemini's the ad one >> would have been a lot easier if you were
1:08:25
the only LLM like that like the the it's it it's it risks the entire company like like they need to get their opportunities in the consumer space first and foremost because the consumer space needs to monetize via ads And the fact they didn't get there or start to get there, still haven't started to get there is uh it it's a company imperiling >> poor decision. >> Last question uh from my side at least
1:08:49
>> Last question uh from my side at least uh predictions.
1:08:52
Do do you think there's anything to the the prediction that OpenAI will buy Pinterest or partner up with a uh social network at a more deeper level than they already have?
1:09:03
>> Well, so it's really interesting.
1:09:03
>> Well, so it's really interesting. This is one of my uh I was actually uh uh I was talking to uh I've been met when I was in New York a few months ago and I was at this this off actually me and the semi- analysis guys uh great guys but they were sharing an office with like a hedge fund and one of the guys is like
1:09:18
look you're responsible for one of our worst all-time decisions [laughter] and I'm like what's that he's like um we bought Twitter I'm like I never said to buy Twitter that's [laughter] terrible stock um unless he was going to overpay for it and he's like but then I remembered what it was it was I 2017 2018 when Twitter bought mopub. >> Oh
1:09:36
>> Oh >> and my theory at the time was Twitter's just a very poor inventory for advertising.
1:09:42
Part of it is it's text based there at especially then there were fewer images.
1:09:47
>> There's also a mindset when you're on Twitter you're like girded up for battle and like you're trying to engage like opposed Instagram like Instagram the ads might as well be >> the content >> Instagram [laughter] like X is fight or flight. >> Yeah. No. Exactly. Exactly.
1:10:00
And so my theory then, but Twitter has the potential to really understand your interest in a really sort of deep way.
1:10:09
And so what they could do is they could harvest signal on Twitter and they could manifest it with using Mopub and inventory sort of across a bunch of apps.
1:10:17
And that would be sort of a very compelling model.
1:10:20
>> Again, who knows if I was right.
1:10:22
Twitter's executives or Twitter was incompetent for years and years and years.
1:10:26
At one point, I said, "I'm never covering this company again because this is pointless."
1:10:28
Um, that's that's a bit what sort of Apploven did who did buy by by Mopub from from Twitter and has made a ton of money doing that.
1:10:36
But I think that would be the thesis there, which is because we're people are dumping everything into this LM, we can get all this signal and understanding, what we need is inventory to monetize that signal and could that be inventory to do so?
1:10:52
Um, the theory makes sense.
1:10:52
It feels like they have a lot more important things to spend money on.
1:10:57
I think probably at the end of the day, particularly post AT like O and O like your own and operated properties are always going to be the most valuable.
1:11:04
I think figuring out how to monetize and jetp it's not an insane idea for that reason. >> I like that.
1:11:11
Well, thank you so much for hopping on the show on short notice.
1:11:15
We're huge fans here and congratulations. >> Look, I am on a look.
1:11:17
No one cares about the Vision Pro but me.
1:11:20
Therefore, I take it upon myself everywhere.
1:11:23
>> Correct the record and say the strongest soldier. >> Well, camera. >> Yeah.
1:11:27
If you want the uh the most uh the deepest analysis, the most uh you know, the hottest takes on the vision pro, of course, sign up for strateg. [laughter] Let's do it. >> Let's do it.
1:11:54
>> We need to We need to [laughter] Well, thank you so much.
1:11:56
Have a great rest of your week and I hope your 2026 is off to a great start.
1:12:00
>> Yeah, great to see you, Ben.
1:12:01
>> We'll talk to you soon. Have a good one.
1:12:04
>> Label Box, delivering you the highest quality data for Frontier AI. >> Get in the box.
1:12:08
The label box [laughter] >> every time.
1:12:11
They didn't give us >> they didn't give us that tagline, but >> but we're using the box. The label.
1:12:18
Uh Walmart partners with Alphabets Google to allow shoppers to purchase products through Gemini.
1:12:22
Uh, so Walmart is jumping in with Google.
1:12:27
Um, we're we're having Harley from Shopify on the stream later to talk about Agentic Commerce, what's happening there.
1:12:32
There's a lot of other news.
1:12:32
Uh, and uh, >> person probably. >> Whoa.
1:12:37
I have the audio on my phone.
1:12:37
Um, the, uh, Google is, uh, posting a video of Wing.
1:12:43
Uh, the future of retail is landing.
1:12:46
They're taking shots at our boy Keller, uh, launching a, uh, a drone.
1:12:52
>> This one, this one hit me pretty hard. I know. I know. We love Zipline. We love Keller here. We love Google.
1:12:56
Obviously, their sponsor.
1:12:58
But >> did Google just leave one future of X thing for >> for someone else?
1:13:04
>> For someone else, right?
1:13:04
I didn't even know about the I didn't even know about Wing until today. Was this an acquisition? Wing. com. One of the best domains.
1:13:12
>> You're going to be texting Keller like Sam Alman and Elon were texting each other about the future of AI.
1:13:15
You're going to be like, "The future of drone delivery is in our hands, brother.
1:13:18
We gota [laughter] we gotta be wing."
1:13:19
No, Google's been working on this for a long time.
1:13:23
Obviously, this is going not to be, you know, the only there's only going to be one company with the technology.
1:13:28
There's going to be variety.
1:13:30
Tyler, what do you have for us?
1:13:30
>> Uh, just on that point of of of Elon and Sam, yeah.
1:13:32
Uh, >> Elon just said on the Apple and Google collaboration, he said seems like an unreasonable unreasonable concentration of power for Google given that they also have Android and Chrome.
1:13:41
So, he's still on the >> he's taking he doesn't like he he's not a fan.
1:13:46
Uh, well, >> we are fans of Plaid here and so let me tell you about Plaid.
1:13:50
Plaid powers the apps you use to spend, save, borrow, and invest.
1:13:54
Securely connecting bank accounts to move money, fight fraud, and improve lending.
1:13:57
Now with AI, uh we talked about uh about Apple confirming Gemini. Very excited for that.
1:14:03
I want them to roll this out immediately.
1:14:05
I know that it's probably going to be, you know, some normal release cycle with very polished ads and an onstage keynote and a developer preview and there'll be a whole cycle to updating.
1:14:17
But we are in the age of AI.
1:14:20
Apple, just ship it today.
1:14:22
Just replace Siri with Gemini today.
1:14:25
Uh I'm sure a lot of people would be fans of that, but you know, they operate the way they do.
1:14:29
Uh Eric, >> I pulled I I pulled a little history on wing. com.
1:14:32
So started >> Wait, they own Wing. com. >> Wing. com.
1:14:35
That's what I was saying.
1:14:36
[laughter] It's one of it's not only not only an amazing partnership, but uh fantastic domain.
1:14:41
Uh so it started within X uh Google X the moonshot factory.
1:14:49
The original mission was focused on emergency medical response. Okay.
1:14:53
>> Uh so they wanted to deliver defiills to heart attack victims.
1:14:56
Uh the uh basically they they pivoted away from emergency emergency services to last mile commercial delivery.
1:15:04
Uh they started doing their first uh like real world trials back in Queensland as early as 2014.
1:15:11
Uh it graduated from X in 2018.
1:15:16
They later became uh the first delivery drone delivery company to receive a part 135 air carrier certificate from the FAA and uh they've just been scaling the network since then.
1:15:26
So um yeah, I guess they're going to be able to serve 40 million people by 2027. Yeah.
1:15:31
I mean, as an American, as a human, as a technologist, I want more and I want competition.
1:15:38
But as a big fan of Keller at Zipline, I want him to dominate.
1:15:42
>> No, I think I think I think >> Google maybe did this.
1:15:44
They knew Keller had the potential for to be one of the great the greatest in history and but they realized if he didn't have a viable competitor, he would never live up to his.
1:15:55
>> So, they're inspiring him to grind harder. That's what's going on.
1:15:56
Okay, now we understand it.
1:15:57
Well, uh, Figma Figma make isn't your average vibe coding tool.
1:16:02
It lives in Figma, so outputs look good, feel real, and stay connected to how teams build, create codeback prototypes and apps fast.
1:16:08
Uh, OpenAI launched ChatBT Health now anthropic has cla [laughter] give give me blood transfer. >> Don't make mistakes.
1:16:27
>> Uh, I I used Cloud Code this weekend uh in a funny way.
1:16:30
I had I had it I was having slow Wi-Fi, which of course is a weird thing to go to cloud code for because it uses the internet.
1:16:36
So, you're gonna have slow interaction.
1:16:37
I had it uh I had it diagnose my my uh I I I gave it a prompt.
1:16:43
I said uh what did I say? Oh, it's somewhere here. Maybe I maybe I lost it.
1:16:48
But uh I I I basically told it I I told it like, "Hey, I'm having problems with my internet. Can you just go fix it?"
1:16:52
It ran all these different diagnostics, pinged Google, pinged all the different DNS servers, ran through everything, ran speed tests, and it came back and told me to turn it off and turn it back on.
1:17:02
[laughter] And it actually worked.
1:17:04
>> And I could have saved myself like 45 minutes of sitting there being like, "Yes, I'm okay with you using curl.
1:17:08
Yes, I'm okay with you using wget."
1:17:09
So >> the entire time, super intelligence was just turning it on.
1:17:13
Turn it off and then back on. >> It's Lindy. It's Lindy.
1:17:15
It should have just preempted me and just been like, "Look, dude, have you at least turned it off and turned it back on?"
1:17:20
[laughter] Uh anyway, Tyler, what do you think?
1:17:22
>> Uh if if Claude was being slow by the because of the Wi-Fi, then that's an example of like um you know, self-improvement. >> Self-improve. Oh, it improved itself. >> Yeah. Yes. Yes. Yes. Yes. Yes. Uh boom. >> Yeah. Yeah.
1:17:34
It was it was a weird issue. Really high ping.
1:17:36
Really like the bandwidth was fine, but the ping was really bad and so it was very annoying.
1:17:42
Um but it did resolve it.
1:17:42
And you know, at the end of the day, Claude Code did did a very thorough job of telling me some timehonored advice.
1:17:48
So, thank you to Cloud Code.
1:17:50
Uh, and uh, interesting that everyone's pushing into healthcare.
1:17:55
I'm I'm I'm I'm still waiting for the push into legal.
1:17:56
I'm wondering if that'll happen or if that's more complicated than healthcare.
1:17:59
Uh, I'm also wondering maybe healthcare is more lucrative, more viable, more I I I I would love to be in the meetings where they have prioritization of what uh who's whose lunch they're trying to eat off.
1:18:13
[laughter] Who's whose plate should we eat off of?
1:18:17
Let's let's the lunch meeting.
1:18:17
Uh well, New York Stock Exchange.
1:18:22
>> If you want to change the world, raise capital at the New York Stock Exchange. We love the night.
1:18:26
Can't wait to be out there.
1:18:28
Again, we're planning our next trip, so stay tuned. >> Cannot wait.
1:18:32
Uh Meta CEO Zuckerberg is launching MetaMP compute, planning tens of gigawatts this decade and hundreds of gigawatts longer term.
1:18:39
Uh this effort uh will be led by Santosh uh Jinard Han and Daniel Gross DG uh back in the mix.
1:18:50
Santos will continue to lead our technical architecture, software stack, silicon program, developer productivity and building and operating our global data center fleet and network.
1:18:56
Daniel will lead a new group responsible for long-term capacity strategy, supplier relationships, industry analysis.
1:19:02
Let's give it up for industry analysis.
1:19:06
[applause] Planning and business.
1:19:06
Let's give it up for planning and business modeling as well.
1:19:09
DG DG this is not his first rodeo.
1:19:12
Do you remember the Andromeda cluster >> NFDG?
1:19:14
That was really really cool.
1:19:17
>> Early and and great on that.
1:19:19
>> So they were they were doing uh was it AI Grant was the name of the program.
1:19:20
So they backed a bunch of companies some crazy companies in AI Grant too.
1:19:24
Sort of an incubator accelerator model.
1:19:27
A bunch of early stage companies smaller checks. Give me the details.
1:19:32
>> Let me just read this.
1:19:32
So in the first batch they had Perplexity Cursor Replicate [laughter] uh Chroma. >> Chroma too.
1:19:37
I think they had uh didn't they have Julius?
1:19:41
>> Julius was in maybe a second one.
1:19:43
>> It might have been in the second one, but there's so many bangers.
1:19:44
If you just go to the site, it list all of them. >> It's amazing.
1:19:46
Um and and so what they did was they went and bought a whole bunch of uh of GPUs. They built a cluster.
1:19:52
Uh and >> they had a feeling that GPUs would be be important and and it was so basically anyone in their portfolio was sort of default GPU at least for a little bit.
1:20:02
Uh although of course the resources were shared and I have heard about another accelerator doing this recently.
1:20:05
I need to confirm with the head of that accelerator if it's if it's okay to share uh because it's very exciting as well.
1:20:13
But um uh I was asking them like what does it mean to build a cluster at this level? Did you buy land?
1:20:18
Did you build a data center or did you just go to Microsoft and say hey cordon off this little you know rack of of GPUs we want those to be dedicated uh least instances.
1:20:31
And I believe it was more of the latter but still you know not their first rodeo here.
1:20:35
So I I think this project's in good hands with DG.
1:20:37
So let's hear it for the the Meta >> compet. Yeah.
1:20:40
Beta also brought on uh Dina McCormack. >> Oh yeah.
1:20:44
>> Join Meta as president and vice chairman to work on partnering with governments and sovereigns to build, deploy, invest in, and finance Meta's infrastructure.
1:20:51
>> This is making wave on Truth Social.
1:20:51
I saw >> government uh yeah governments uh getting involved in financing Meta's infrastructure.
1:20:59
>> So he's saying he's like Sam, they said it. I'm going to say it now. >> It's not a back stop. It's the front door.
1:21:05
>> [laughter] >> Uh Dena was a former deputy national security adviser.
1:21:10
>> Well, we have a new sponsor of the show, Century.
1:21:12
Century shows developers what's broken and helps them fix it [applause] fast.
1:21:17
That's why 150,000 organizations use it to get their apps to keep their apps working. I've used Sentry. I love Sentry. So, welcome to them.
1:21:25
Uh Nvidia is investing a billion dollars in the in an AI drug lab with Eli Liy over five years.
1:21:29
This will be very interesting.
1:21:32
We're excited for the Eli Liy progress. >> Drug lab sounds. >> It's AI Ompic.
1:21:39
It's the two biggest super trends of the last uh of last five years. Weight loss and AI. Could it get any better? Well, now it will.
1:21:48
Uh we'll have to dig into more of this partnership.
1:21:52
>> Tom Brady is now the face of uh the former CEO of Ax's new company, EMed. >> That's right. >> Did you see this? >> I I did.
1:21:59
So Tom Brady, if uh if you're not uh familiar, he was the former face of FTX. >> That's a rough one.
1:22:08
>> And also uh >> was he actually the face?
1:22:09
Because there were a lot of celebrities that partner with FTX. Larry D.
1:22:14
>> He was part of he was part of some of their bigger campaigns.
1:22:16
>> He did a bigger campaign. He did a TV campaign.
1:22:18
But again, you know, it's hard if you're if you're a celebrity to to >> But this is an interesting one because so so he's joining as the chief wellness officer of EMed. >> Yeah.
1:22:27
And it's interesting because this kind of just makes him the face of GLP1s, right?
1:22:36
>> Which is kind of a beneficiary like is beneficial to the entire industry, right?
1:22:39
If you sell GLP1s, >> well, Tom Brady is down. >> Yeah.
1:22:44
>> I wonder if he's That'd be interesting.
1:22:45
>> Um anyways, >> his pepide regimen is >> um maybe he's just super agil.
1:22:48
Maybe he maybe Sam said, "Hey, I'm a I'm an I'm an investor in Anthropic."
1:22:53
And he said, "Well, I think Anthropic is going to win.
1:22:56
I'm partnering up with you.
1:22:56
I don't care about the structure of your hedge fund.
1:23:00
I don't care if there's a back door out of your uh out of your trading platform.
1:23:03
I'm in on you because of your investing track record. What about that? Yeah.
1:23:08
>> You know, if Enthropic gets out at a trillion, there's going to be a debate at least about Sam Begman Freed's legacy.
1:23:14
>> Uh he of course invested at what 10 million for 10% or 8% of the company.
1:23:17
So that would be uh maybe like an 80 billion position today, something like that.
1:23:24
that. 50 billion 10 billion with delution I don't know it was a good investment uh just like getting your business on gusto is a good investment the unified platform for payroll benefits and HR built to evolve with
1:23:37
modern small and medium-sized businesses >> like us >> like us uh Paramount Sky Dance has now initiated what insiders are calling plan D they're running out of letters [laughter] as they look to upend Netflix's winning bid for Warner Brothers Discovery. Hey,
1:23:51
Hey, maybe the D just stands for discovery.
1:23:55
So, you know, maybe this is actually one of the earlier plans, but >> maybe they're maybe they're saving the best for last. >> Plan W. Never take the L. Skip plan L. Go straight to plan W. Get the W.
1:24:04
We're rooting for you, Ellison.
1:24:07
Uh it involves bringing home uh uh banging home to investors the immense amount of regulatory uncertainty of involved in the Netflix deal and how they could how that could spell trouble not just for the transaction but for Netflix itself.
1:24:23
And so if Netflix finds itself in a quagmire trying to acquire Warner Brother Discovery, that could be bad news.
1:24:29
And uh and David Ellison wants to make that clear to all of the shareholders that going with a Paramount Sky Dance might be a little bit less bumpy of a road.
1:24:38
We will see from the photo shoots.
1:24:40
Seems like they're pretty happy together, but we will we will see what happens.
1:24:44
It will be a proxy fight and I'm sure we will be following it closely.
1:24:48
Um some more news uh from Axios.
1:24:51
Bessant told Trump that investigation of Fed chair creates a quote mess.
1:24:55
Uh and so basically last night Bessant was saying the secretary isn't happy and he uh or no someone else said the secretary isn't happy and he let the president know.
1:25:06
Uh that's kind of a white pill, right?
1:25:08
somebody in, you know, the admin that uh that uh seems to, you know, have uh just kind of a a steady view on things is uh pushing back a little bit. >> Nothing ever happens.
1:25:20
[laughter] >> Yeah, you need a secretary of nothing.
1:25:25
Just did anything happen? No, nothing happens.
1:25:27
But Vanta happens and compliance happens. So get on Vanta.
1:25:31
Automate compliance and security.
1:25:31
The leading AI trust management platform is of course Vanta.
1:25:36
Um there was a massive debate that raged in a Google doc which was published on Substack.
1:25:41
The battle between Jack Clark who's at Enthropic of course the co-founder of Enthropic and Dwaresh Patel.
1:25:48
They were going up against Michael Bur Cassandra Unchained.
1:25:54
They had a good discussion and it's been published free to all on Substack where you can go and read it. >> Highlights Tyler.
1:26:00
Yeah, I have some highlights.
1:26:02
I mean I So one thing I It's not really a debate at all in this discussion.
1:26:05
And it's like there's a bunch of questions and they go and they basically >> they're just like AI is amazing. I agree. >> Yeah.
1:26:10
No, it's funny like all almost all the quotes I pulled were from uh Bur because the Dorces and Jack Clark, I just agreed with everything they said.
1:26:17
So it's like oh it's like not that interesting.
1:26:18
Like I already I already know this.
1:26:21
>> Your own opinions, bro.
1:26:21
[laughter] >> I agree with everything you said.
1:26:23
I I have no >> You're absolutely right. >> Yeah.
1:26:27
>> Uh so one thing I I it's always interesting.
1:26:29
Um Jack Clark, he writes um >> I've been doing research on the cost curves of various things recently.
1:26:33
And the examples he gives are dollars of mass to orbit and dollars per watt from solar.
1:26:40
>> So it's like okay anthropic is looking at space energy. >> Sure. >> Right. >> Sure.
1:26:44
>> Um some other stuff I I thought um Burie said his one like policy proposal.
1:26:49
>> Oh, so just the fact that Jack Clark is doing that research indicates to you that they might be thinking about orbital data centers in the future. >> Yeah.
1:26:56
I mean orbit mass orbit and and Yeah. I don't know what else. >> Yeah. Yeah. No, it makes sense.
1:26:59
I mean maybe he's just interested in space.
1:27:01
>> He might just be interested. >> Yeah.
1:27:02
He might just be like I want to go to the moon.
1:27:04
I'm bringing Claude with me. >> Yeah. >> Yeah. I don't know.
1:27:07
>> Claude, go to the moon.
1:27:07
Don't >> The other the other interesting uh Bur take was that he thinks that uh white blue collar work might be more susceptible to AI disruption than many people think.
1:27:17
He made this point that um he's been doing his own plumbing and electrical work apparently.
1:27:21
I thought I don't know if that's how true that is, but he said that Yeah. Can you read it? >> I have the quote. Yeah.
1:27:27
says, "Uh, given how much I can now do in electrical work in other areas around the house, just with Cloud on my side, I'm not so sure about jobs going away.
1:27:33
Uh, if I'm middle class and facing $800 an $800 plumber or electrical electrician call, I might just use Claude.
1:27:42
>> I love that I can take a picture and figure everything out I need to do to fix it."
1:27:45
>> So, I mean, this >> that was a big moment for me.
1:27:46
Uh, I forget who was sharing this, but somebody was like, "Yeah, they just took a picture of like the most insane >> wiring diagram or something." >> Yeah.
1:27:55
No, it was just a bunch of wires going everywhere and it just one time.
1:27:59
>> Take a picture of your car.
1:27:59
It needs engine out service.
1:28:00
You're like, where do I screw?
1:28:02
[laughter] I'm doing it myself.
1:28:04
Well, we have the perfect guest to talk about AI diffusion and its impact on the job market with economist Tyler Cowan joining in just a minute.
1:28:13
Uh, first, let me tell you about MongoDB.
1:28:14
Choose a database build for flexibility and scale with best-in-class embedding models and rerankers.
1:28:19
MongoDB has what you need to build what's next.
1:28:24
And we without further ado, we will bring Tyler Cowan in from the reream waiting room.
1:28:27
Tyler, how are you doing? Good to see you. >> Welcome back. >> I'm fine. Good to see you.
1:28:32
Congratulations on the Vanity Fair piece. I loved it. >> Thank you so much.
1:28:35
I'm so glad that you were able to to to check that out. It was a lot of fun.
1:28:38
Uh very funny getting dressed up all fancy.
1:28:41
>> When are you going to be in Vanity Fair?
1:28:43
>> They really doing their work.
1:28:45
>> I think I I would love to see a Vanity Fair >> photo shoot with you as a subject.
1:28:48
I think it would be fantastic.
1:28:51
We should make it happen. a style icon, right? >> Yes, definitely.
1:28:54
Well, I mean, they they really should do do more uh reflecting on uh conversations with Tyler. The team's grown a lot.
1:29:00
Did you just hit a recent milestone?
1:29:02
I saw that there was an event.
1:29:04
Can you just get me up to speed on on the organization and and how long you've been uh working on the show?
1:29:11
>> Conversations with Tyler is now 10 years.
1:29:13
It's a few hundred episodes. >> Success.
1:29:17
>> And last year we did almost an episode a week. >> An episode a week. That is fantastic.
1:29:23
Well, uh it's one of my favorite shows.
1:29:24
It always has been for I I feel like I might have been a decade long listener.
1:29:28
Uh maybe maybe not the first year, but I got on early and I've been very pleased the whole time.
1:29:32
Um but anyway, thank you so much for joining us.
1:29:34
Um, we we first wanted to have you reflect on this point from Michael Bur that artificial intelligence might displace more bluecollar jobs than people are expecting because you can now take a picture of your toilet and learn how to do plumbing or you can take a picture of an electrical panel and you can do your own electrical work.
1:29:54
Does that resonate with you at all?
1:29:56
Do you think that that there might be some substitutive effect in the DIY community that might have an effect on those trades jobs that previously have been known have been, you know, rumored to be very AI resistant?
1:30:12
>> Well, that's true, but there's still a net job boost coming in those areas because there'll be all these new projects, new data centers, new sources of electricity, >> and they need plumbers.
1:30:21
They're not all going to use chat GPT to take the photo and try to figure out how to fix the thing under the water, whatever. >> Yeah.
1:30:29
>> So, the house called plumber, maybe that goes down by 20%.
1:30:32
But so many other new things happening, terraforming the earth, whatever.
1:30:36
Other countries, Africa developing, >> those jobs will be doing great. >> Yeah.
1:30:41
How are you, >> that's it.
1:30:42
I agree with his example. >> Sure. Sure.
1:30:44
Uh how are you tracking the overall data center boom?
1:30:46
There's been this narrative that data centers are the only thing that are propping up the US economy.
1:30:52
It feels like we hear about new data center projects every day.
1:30:55
The numbers are getting bigger.
1:30:57
There's a new zero every time there's a new press release.
1:31:00
Uh and at the same time, the overall power generation, the big big glo like US national number is not yet started to move, but it feels like this might be the year where we see more electricity generated in America than before.
1:31:16
How are you tracking the overall impact of uh of AI on the broader economy?
1:31:22
>> We need to do much better, but I think it's wrong to feel that without the data centers, the economy would collapse.
1:31:28
Those resources would be used to do something else and different.
1:31:32
>> It might be less risky.
1:31:32
It might be more immediate.
1:31:34
Actually, consumption would be higher in the short run if not for AI in the data centers.
1:31:38
So, what we're doing is investing longer term, taking some risk, boosting medium-term productivity.
1:31:45
I'm all for doing that, but again, without that, we'd make more toys or more hot dogs or more something else. So, no big deal.
1:31:51
[snorts] >> Um, how awesome how often are you listening to AI music?
1:31:58
>> I try it reasonably often, but I don't yet listen to it because I want to.
1:32:05
>> It gets closer every time.
1:32:07
>> I would say within two years, I think I'll be listening to it on purpose, >> but right now it's experiment and tracking the field, not for enjoyment. Sure.
1:32:15
Do you find the the act of playing the game of trying to generate a song that you like more entertaining than the actual resulting music?
1:32:29
>> No, I don't find either entertaining. For me, it's a pain. Yeah.
1:32:32
>> You know, I have a very large collection of albums and compact discs.
1:32:35
I can hear literally the world's best music at my fingertips when I want to.
1:32:39
And the other is a distraction.
1:32:41
I do it as my own investment in seeing where things are headed.
1:32:46
>> Do you think there's >> I had someone share an interesting anecdote recently which is that uh a prof uh you know one one example a professional singer who who made uh who's uh sort of top of their field uh with within country country music.
1:33:00
They made something like $400,000 last year uh basically going into the studio and recording sample tracks.
1:33:08
You know, basically a songwriter would make a song, they would sing it, and then they go out or this person would sing it, and then it would get pitched to other artists uh to be made into like a hit, right, and actually be produced.
1:33:20
And uh his work literally went to zero because of because of Sunno this year.
1:33:27
>> And he doesn't have the ability, nobody hires like a backup singer to go on tour.
1:33:30
Like they'll you can be a back you can be like a studio guitarist and get live jobs.
1:33:34
And so their work went from >> because now people can just prompt with Sunno and say, "Hey, make uh make use these lyrics, apply it to this track uh and make it sound like this artist."
1:33:45
And so that's just been kind of an interesting uh uh space and and I was talking to another friend yesterday that says basically everybody is using Zuno at scale and nobody in the very few people in the industry will are willing to actually talk about it. >> Interesting.
1:33:59
So, >> you know, I played some for my wife recently and she said, "I hate it."
1:34:02
And I said, "Why did you hate it?"
1:34:04
And she said, [clears throat] "I hated it because it was good."
1:34:08
>> That's where we're at right now.
1:34:09
>> That is That is >> But yeah, it's notable, too, that it's it's maybe not it's it's not great for like the end listening stage yet, but it's totally good enough for like the sampling, for the professional kind of workflow side of things. >> Yeah. Yeah.
1:34:23
Do you think there'll be um sort of a a legal reckoning figuring out how all the royalties flow through these models and saying that okay there's 1% Taylor Swift in this generative sample and 2% someone else and and then all of the the money from like sort of like a more complex revshare that might flow through these generative models.
1:34:47
>> I don't know if that's practical.
1:34:47
I mean the Beatles took from Chuck Barry, Buddy Holly, Carl Perkins, everyone. Yeah, >> without paying.
1:34:54
And the world went on, even whether or not it was fair.
1:34:56
And I think we're going to redo that experiment.
1:34:59
I don't think it will be all that different.
1:35:02
>> Most musicians don't make from recording anyway. >> Yeah. No, it makes sense.
1:35:06
Uh, have you tried Claude Code? >> No, I have not.
1:35:10
I've been meaning to, but I've been traveling and I'm finally back home and I will be trying it.
1:35:16
>> Uh, >> everyone tells me it's amazing. >> Yes. Yes.
1:35:19
people are uh maybe one one click behind you.
1:35:22
I I remember you you declared 03 AGI and now uh people were maybe hesitant to call the game there but uh many more people have jumped in with uh affirmations that claude code is AGI because uh it can do so much more when it actually has access to your to your full computer.
1:35:38
Uh but it is a little bit more cumbersome to get set up.
1:35:42
>> How did you how did you process uh Powell's uh video yesterday? >> Oh yeah.
1:35:46
Well, it was terrible what Trump did.
1:35:50
>> Fortunately, most of the markets did not react very much, but gold and silver went crazy.
1:35:54
To me, that's a sign that the dollar is much less of a safe haven, >> and Trump is going a bit, you know, what I call the Captain Quig route, and he's just not reliable. >> And that's very bad.
1:36:04
But I don't think it's really going to change inflation or interest rates very much.
1:36:09
>> Is that just because he'll uh Powell hold steady?
1:36:13
>> No, because we already wrecked the independence of the Fed, which I'm not happy about. Mhm.
1:36:17
>> But that's the ugly little truth behind this story. >> Yeah.
1:36:20
>> That's why it's not been worse what Trump did is because it was already wrecked.
1:36:24
>> Why is Fed independence important?
1:36:28
>> Sometimes the central bank needs to do things that are not politically popular and they need that shield to do it.
1:36:34
>> But the basic problem is our debt and deficits are so high that over time we will monetize them to some extent and have higher inflation because we prefer that over higher taxes.
1:36:44
no matter what we might say.
1:36:45
And so the Fed independence is taken away through that mechanism >> apart from whatever Trump said yesterday.
1:36:52
>> Oh, so just by shape like I'm not telling you not to worry, but I'm telling you you should have been worried to begin with.
1:36:58
[laughter] >> Black Bill.
1:37:00
Um, so yeah, you're you're saying that just by running high deficits that reduces Fed independence.
1:37:07
>> And that's an old story, but it's now closer to a tipping point.
1:37:09
And Trump is making that much worse.
1:37:12
So, I would say his actions on the fiscal front do more to hurt the Fed's independence than his words, but they're both bad.
1:37:20
>> Can you walk me through your mental model for thinking through what the right level of debt for a nation is?
1:37:28
Some of the numbers get so big.
1:37:30
It's trillions of dollars.
1:37:30
It feels very abstractly bad.
1:37:33
Uh but then if you look at it more like a mortgage relative to, you know, debt to income, it feels maybe more reasonable.
1:37:40
like how should you know nations think about the level of indebtedness that's appropriate?
1:37:48
The >> United States is a special nation and we can get away with more debt >> which is great for our living standards but it's bad for our political responsibility because our leaders all know we can get away with more debt.
1:37:58
I think what we'll need to do at some point is have half a dozen dozen years of something like 7% inflation. Get the debt down.
1:38:07
It won't at all solve the problem.
1:38:09
the problem will never go away, but it will give us some breathing room.
1:38:13
We'll then lower inflation, maybe have a recession and start all over again, and it's highly unpleasant and a lot of people will be thrown out of work and living standards will be lower.
1:38:22
But we've already spent that money. We can't default.
1:38:27
>> And that's facing us over the course of the next 10 to 15 years.
1:38:30
But I don't think the world will end.
1:38:34
>> Is America's position in AI the biggest counterbalance to all that?
1:38:37
like sort of negative view >> it is.
1:38:41
So if AI would help our economy grow one percentage point more a year, >> we could just afford the whole thing and we wouldn't even need to inflate. >> Yeah.
1:38:50
>> Now that would not be my best prediction, but it's not impossible that it could happen.
1:38:54
And I've been predicting half a percentage point a year, which still puts us right on that border of can we, can't we? We don't know.
1:39:02
>> I wouldn't want to stake the whole house on that.
1:39:04
But again, there's some chance we'll squeak by due to AI and assorted productivity gains.
1:39:10
>> Yeah, but why not 1% growth? Why not 2% growth?
1:39:13
These tools, they feel amazing.
1:39:15
It feels like >> or triple digit as as Elon. >> Sure.
1:39:18
But but it does it does you use these tools and it feels like you're more pro productive.
1:39:22
And there's some studies that say, oh, maybe >> you can generate documents that don't get read >> basically.
1:39:28
Is is that what's going on?
1:39:29
like like like what is holding back AI from actually moving the needle on economic growth significantly?
1:39:36
>> Well, first about half of our economy right now is just totally perpetually sluggish. Look at government.
1:39:41
Look at most of the nonprofit sector.
1:39:43
Look at higher education.
1:39:45
Parts of our healthcare sector.
1:39:47
Add that up, you're at 50% of GDP.
1:39:51
>> To some extent, they use AI already, but in pretty trivial ways.
1:39:53
Like, oh, it saves people some time. They don't work as hard. They take more leisure.
1:39:57
they hang out more at the water cooler. That's fine.
1:40:00
It's fun, but it's not going to get rid of our debt problem.
1:40:04
And then you have some startups, you have programming, you have the dynamic parts of our biomedical sector that are already using AI a lot.
1:40:10
But the more they use AI, the more efficient they become.
1:40:14
And the more the inefficient parts of your economy are left over and it's just really hard to grow much faster. >> Interesting.
1:40:20
>> Unless you're like China playing catch-up. >> Yeah. Yeah.
1:40:22
Though the number is hard to estimate, but GDP is a huge mound of stuff, most of which is produced by people who are not neither white nor black on AI. Sure.
1:40:34
>> And it will take things a long time to change. >> Yeah.
1:40:36
How do you think about the legacy of Thomas [ __ ] and the uh the new uh debate over Pikid in the 22nd century I believe? Was it 21st century?
1:40:46
22nd century that Doresh wrote about uh 27th >> 21st uh >> 20 >> it's in the future talking about uh economic inequal inequality uh increasing gains to capital increasing returns to uh to capital >> 22nd century >> pick 21st >> he's too focused on the labor share I think real wages will go up a lot if real wages go up workers are happy they might be upset that Elon or someone else is a trillionaire but I don't think that will drive our politics.
1:41:17
I think if real wages go up, we'll be fine. People will feel good.
1:41:21
So, my view is very different.
1:41:23
>> Wait, but uh I mean real wages will go up, they'll feel good, but then they'll also be upset that there's now multiple trillionaires walking around and so won't those emotions actually drive the politics.
1:41:34
It feels like people are that envious.
1:41:36
They're envious about the people they went to high school with or maybe their brother and >> Most people are not that envious about Elon or Bill Gates or whomever else. >> Yeah. Yeah.
1:41:46
I was >> envy is local for the most part. Yeah, I was running.
1:41:49
>> Maybe you do envy each other, right?
1:41:51
>> Maybe >> you envy, you know, the she the richest chic in Saudi Arabia.
1:41:54
I bet you don't even think about him that much.
1:41:57
>> He does have a great >> Or if you do, you think about his role in the AI world, which is fine. Totally.
1:42:01
>> But you're not upset that he gets however much hummus and you have less hummus than he is.
1:42:06
>> It's all about the hummus.
1:42:06
Yeah, I was doing a thought.
1:42:08
>> Don't you think uh uh envy is is a factor in in the current wealth tax? uh sort of discourse.
1:42:18
>> California is a crazy state, but I think it's just more a money grab than envy.
1:42:23
Uh and I think there's a very good chance they ruin the greatest engine of wealth creation maybe in human history.
1:42:30
So I I hope it fails and soon even the risk of it as you know is inducing many people to leave or get ready to leave. >> Yeah.
1:42:37
What's the uh uh what's the retrospective view on the LER curve in light of what's happening in California today?
1:42:48
>> Well, at some tax rate, the LER curve is true.
1:42:50
We're not usually in that range, but California is playing with fire and experimenting with that range.
1:42:57
>> So, I dearly hope they don't do it for their own sake.
1:42:59
It'd be great for Austin, great for Miami, maybe good for New York. >> Yeah. Yeah. Interesting. New York has a problem.
1:43:08
>> What's your personal investing strategy? >> Buy and hold. Focus on other things. Investing.
1:43:16
>> But but by buy by by what?
1:43:16
Because if you buy individual names, you you it can end up being wildly distracting and then you can't focus on the other things that are maybe more productive.
1:43:26
>> Diversified portfolio.
1:43:26
I've thought now of buying some more gold just as a hedge.
1:43:30
It's not that I think it will do well, but I see higher risk.
1:43:35
>> And Bitcoin's not really a hedge, so maybe gold and silver.
1:43:36
Again, I'm not saying it will make you rich.
1:43:39
I'm just saying if everything else falls apart, you'll have something. >> Yeah.
1:43:43
Um, have you pushed any AI model, a AI labs to develop taste or smell technology to help with judging the [snorts] judging of food?
1:43:54
It feels like culinary aspects are uh particularly AI durable or or resistant.
1:44:01
Uh but I don't know if that's uh if that's something that can be overcome with better technology.
1:44:09
>> Maybe it's cheaper for now just to use humans and have the AI record what the humans say >> and judge the food that way. That seems to work well.
1:44:17
Like judging food is not hard.
1:44:19
It's one of the easiest problems for humans to solve.
1:44:21
And humans will do it basically for free.
1:44:24
How many food bloggers get paid?
1:44:26
Well, they might get some free meals, whatever. >> Sure.
1:44:30
>> But so many people do it for free.
1:44:30
I just wouldn't put AI money into that for a long time.
1:44:34
I'd work on almost every >> the other problem first.
1:44:37
You know, Merore, they wanted to hire some basketball analysts to make basketball commentary better by AI.
1:44:42
I'd rather do that than food. It's harder. >> Sure. Sure.
1:44:46
[laughter] That's very funny.
1:44:49
Um, what about uh this call for new aesthetics? What do you do?
1:44:55
You do you believe that we're in some sort of local minima for the development of new aesthetics?
1:45:00
Like what do you attribute this to just broad stagnation?
1:45:04
What are the the key sources that led us to this point where it feels like aesthetically we're stunted?
1:45:12
>> I think poor taste is a big problem around the world, but especially in America.
1:45:16
You look at the older parts of San Francisco, the Victorian homes, they're beautiful.
1:45:20
You look at the new buildings, I like some of them, but a lot of them are just awful.
1:45:24
Or you look at parking structures, or you look at a new bank branch that goes up somewhere. Awful, awful, awful.
1:45:30
Are we really so poor as society that we cannot afford to invest in more beauty?
1:45:35
So Patrick and I are trying to get people to think more systematically.
1:45:40
What can we do to try to make much more of our world just plain flat outright lovely?
1:45:45
It absolutely can be done.
1:45:49
Is there an is there an element of the financialization or or uh I don't know like multi-party like multi-pronged uh stakeholders that go into the development of a campus or a building now that maybe didn't exist a hundred years ago where one person could just decide that they have some crazy vision for a building and they go and build Hurst Castle and it kind of destroys them over their life.
1:46:15
But uh it's it's a singular decision.
1:46:18
And now a company that builds a property or something it it doesn't have there's not a single person that can be maybe authoritarian about the decision and the taste.
1:46:30
Even if they have the taste, they get overruled by a committee of investors and stakeholders that all uh that all kind of put the kibash on whatever they want to do. >> That's one problem.
1:46:40
And there are too many veto points.
1:46:41
But if you go back earlier in time to the 1920s, say, you look at a neighborhood like Shaker Heights near Cleveland, where the homes are being built by different families for the most part, >> they're still far more beautiful than homes being built today.
1:46:54
So, I don't think that's the sole main route of the issue.
1:46:58
I think just bad taste is. >> Mhm.
1:47:00
>> Mhm. Do you think there's a technology angle where uh I it feels like in the modern era a lot of young people lament high housing prices but when I look at their choices they'll often choose to live in a small studio apartment in a very dense city to be around other people and when they go to their
1:47:24
apartment it is small they don't have a library but they have a Kindle and they don't have a room to dance or something, but they have a TV where they can watch dancing and they don't need a movie theater because they just have their phone to watch a show on or something like that. And so the the number of
1:47:37
And so the the number of places, you know, if you were if you were rich, you know, century ago, you needed a lot of spaces to do different activities.
1:47:47
Now every activity can happen on the couch with a TV.
1:47:49
Do you think that there there's some effect there?
1:47:52
[laughter] >> John, >> I don't know.
1:47:54
>> Well, if you do all that and you live in the West Village, you're surrounded by beautiful buildings. Sure.
1:47:57
I'd like there to be more places in the country where you have that choice to be surrounded by beauty that you don't just have to be all scrunched in.
1:48:05
That you can have reasonable living space and afford it and what's around you looks nice.
1:48:10
Again, people have done this in the past, even the distant past. Yeah.
1:48:14
Even sometimes in medieval times.
1:48:14
So to claim we can't do it now, it's simply a failure of will.
1:48:19
There are laws that need to be changed, procedures that need to be changed.
1:48:23
But I think the first step is just to wake people up and increase awareness.
1:48:26
Yeah, it feels like the Yimi movement has a serious amount of energy behind it.
1:48:31
And yet, uh, in my lifetime, I haven't seen that much movement on it.
1:48:36
Maybe the the the ADU law in California is is moving a little bit, but it still feels incredibly slow to get permits.
1:48:43
Is there I is there a dynamic where land owners, property owners are actually >> I don't even think my my feeling uh is that the ADU new like support for ADUs doesn't actually really increase the housing supply because a lot of people are like you'll let me put another structure on my property. Great.
1:49:01
>> Doesn't mean I'm going to doesn't mean I'm going to like suddenly like it's a new single family home, right? >> Yeah. I don't know. What do you think?
1:49:06
I think the Yimi movement could go much further if it could promise it would boost housing and make neighborhoods prettier.
1:49:14
Right now, it's like, well, we're going to boost housing. Cost will fall.
1:49:18
That's wonderful, but maybe your neighborhood will get uglier. >> Sure.
1:49:22
>> Say you do it in Buffalo.
1:49:22
You replace the old with the new.
1:49:23
The new is probably uglier. >> Yeah. >> Uh I don't like that.
1:49:26
I think you would have a lot more successes when it can promise beauty. >> Yeah. Sorry.
1:49:31
on on on the new aesthetics.
1:49:33
Uh I heard I heard a critique or an idea that uh new aesthetics come from problem solving.
1:49:42
And so uh it's less about uh the taste and opinion and will and more of there's a specific problem in society in a particular neighborhood and then a design emerges to address that particular problem.
1:49:54
And so um the the the critique was that uh that we won't get the new aesthetics until we until we identify particular problems or maybe the bland aesthetics are solving for a particular set of problems that are in front of us.
1:50:06
Uh does that resonate with you at all? >> Not that much.
1:50:09
I mean I would say the problem is ugliness.
1:50:10
If you look at older structures around the world, especially in Europe, but often in the US, >> they can be very ornate and have all kinds of flourishes and small details that are lovely.
1:50:21
Those are not solving problems. Mhm.
1:50:24
>> They're put there because people think it will make the thing look better.
1:50:27
>> So, it's not mainly about problem solving, but I'm not against solving problems hardly.
1:50:32
>> Has there been any studies on uh the the effect uh the local effect of brutalist architecture?
1:50:37
Like does it make people like stay at the office longer or any or anything?
1:50:42
Uh cuz uh I can actually it's funny.
1:50:46
I can appreciate brutalist architecture when it is surrounded by nature in a big way. Right.
1:50:50
It stands out as contrast.
1:50:53
>> Yeah, it's a nice it's a nice contrast and it feels like, you know, a triumph of of man in some way.
1:50:57
Uh but it often times will make a a neighborhood much less warm.
1:51:04
>> A shipping container home in a forest sometimes can look beautiful if you see it as a uh a getaway. >> Yeah. Yeah.
1:51:10
Is there is there is there any uh like what what made brutalist architecture um uh you know be such a force in the world?
1:51:19
People don't like it once they live in it.
1:51:22
Personally, as a tourist, I often enjoy it.
1:51:25
I think it's interesting or sometimes creative, but it's not the model I would want to seek to spread through the world. Yeah.
1:51:32
>> Because to live with it all the time, I think it it wears thin on you.
1:51:36
>> Why it ever got as far as it did?
1:51:39
>> Maybe England is the best example.
1:51:39
The 60s, the 70s, it's just cheaper. They're in a hurry.
1:51:44
Concrete is easy to manage.
1:51:48
You have a bunch of planners who think they know better.
1:51:51
And a lot of it was a big mistake.
1:51:51
And you know, I would say maybe England got the worst brutalism.
1:51:55
Maybe parts of communist society got the best brutalism because they really needed the structures after World War II.
1:52:01
But I don't think it should be our emphasis moving forward.
1:52:05
We want to move away from that.
1:52:08
>> Do you think there's 8 billion people on Earth?
1:52:12
>> Because there's a popular >> exact number of people on Earth. >> No, no, no.
1:52:15
So, so tell me >> the back no the backstory is that there's there's a growing conspiracy theory specifically on X this this weekend uh movement of people that are just saying there's no possible way >> Google says it's 8. 2 two billion. Yes.
1:52:29
But this is >> many people many people are are disagreeing with and and one of China's official data.
1:52:35
>> One of the arguments is that is that in certain countries, China among them, there are incentives to uh to inflate your local population number.
1:52:42
So you get more resources from the state. You do that.
1:52:46
You game theory that out across the entire country.
1:52:49
>> And there's there's a homegrown there's a homegrown effort in China from people that are trying to prove this.
1:52:53
and they're going and they're they're finding these cities that are just barren.
1:52:57
It's a a city that that has, you know, a thousand homes and thousands, you know, but yeah. Yeah. Yeah.
1:53:04
But but but there's like a homegrown movement to prove that China does not in fact have as many people as the official numbers claim. >> What do you think?
1:53:14
>> I think there's a modest inflation there.
1:53:15
If there's a betting market on this, I'd love to get in on it.
1:53:19
>> Okay, that's [laughter] good. That's good.
1:53:21
>> Me to bet on, you know, eight billion or more. That's my bet. >> Yeah. Yeah. Yeah. Okay. >> If it's 8. 1 billion and not 8. 2, that I can believe. >> Sure. Sure. Yeah, that makes sense.
1:53:29
Um, back on the architecture uh question uh in the aesthetic question, uh it feels like when people are dissatisfied with the current status quo of architecture or any aesthetic, there's often an uh uh some sort of emotional response to return to a previous era, to just go back in time.
1:53:49
And I'm wondering if you think that that's that that is the solution.
1:53:54
We need more art deco or midcentury or all sorts of different uh I don't know gothic structures or or or or go back in time to pull to just build new buildings that look like they're hundreds of years old or you think we actually need something that's entirely new and and and never before conceived.
1:54:15
>> Yeah, everyone draws from the past.
1:54:17
Mostly I think we need freedom to experiment.
1:54:19
It's not that I want everyone to follow my preferred path.
1:54:23
>> The city where I love what they've done with new things and somewhat older things is Helsinki, Finland.
1:54:28
>> So, personally, that's what I want, but do I want every city to look like Helsinki? Of course not.
1:54:32
Or the modern parts of Copenhagen I think are quite striking and beautiful.
1:54:38
>> So, those would be my preferred directions.
1:54:39
But most of all, it's about simply the ability to raise your hand and say, "This is ugly.
1:54:43
We don't want to do ugly things anymore."
1:54:45
And we all look around for different ways of avoiding that outcome. >> Yeah.
1:54:50
I mean, the risk is that you just have nimbies that say, "I think everything looks ugly and I don't want anything to build."
1:54:55
I guess if you have the option to raise your hand and say, "That's ugly. We shouldn't build it." I don't know.
1:55:00
>> Earlier on the show, uh, John was sharing how uh in 1947 there was a very very small number of televisions in the US, 16,000.
1:55:09
>> 8 years later it was 32 million.
1:55:09
So, so we were talking about how that was effectively a fast takeoffs in hardware fast takeoff.
1:55:17
>> Do you think we can see something similar in robotics?
1:55:19
There's bunch of different exciting projects, a lot of which we've covered on the show.
1:55:24
Uh, I saw a video of a robotic hand yesterday spinning a screw perfectly and it looks like it's sped up like 10x, but it's actually in real time.
1:55:33
So, it's like spinning a spinning a screw, you know, uh, 20 times faster than a human can. >> Interesting.
1:55:39
>> Interesting. Um but uh but yeah so so I think people you know see the current state of humanoids today they can do cool demos and and other robotic form factors but uh it doesn't quite feel like you know we could have a population
1:55:54
of a 100 thou 100 million of these in three years but uh who knows >> I don't think we yet see the killer app in the home >> so if I ask myself what do I want if I could have a fully functioning robot that would be like a mater or a butler. That would be useful to me. But most
1:56:10
That would be useful to me.
1:56:10
But most things short of that don't quite seem worth it. Do I have a Roomba? No. I don't know.
1:56:17
What if there's a mechanical vacuum cleaner that goes around on its own when I'm at work? >> Fine.
1:56:22
It just doesn't seem that necessary. I do my own laundry.
1:56:25
Uh it's a welcome break sometimes.
1:56:30
So, I think we're still waiting to see the Killer app. Yeah.
1:56:36
>> Any other technologies that you're excited about this year?
1:56:39
Well, everything in biomedical, I mean, even without AI, progress against cancer.
1:56:43
Yeah, >> I think youngest people today will die of old age and maybe live to 97 or whenever the time is.
1:56:50
And that's already in the cards.
1:56:52
You don't even have to be a big AI optimist.
1:56:56
>> I don't think it will be soon.
1:56:56
To me, it seems like a 40-year process where you have some gains coming now, but it's mostly complete within 40 years that you just won't die of most of the things that kill people.
1:57:08
Cancer, heart attacks, there'll be accidents, and there'll be deaths by old age.
1:57:13
>> Yeah, that's an extreme way, pel. I love it.
1:57:15
>> Uh, >> and that's likely and again, it it doesn't have to rely on AGI, though.
1:57:19
Of course, AGI can help and accelerate that. Mhm.
1:57:25
>> How do you think about your information diet, your information consumption?
1:57:28
Uh, it's obviously AI augmented, but I imagine you don't start the day with the prompt to an LLM.
1:57:37
And maybe the the LLM prompts come in once you've explored or read some source text and want more context.
1:57:47
Is that how you're using them?
1:57:49
>> Oh, you imagine wrong.
1:57:49
I wake up in the morning.
1:57:51
I had questions when I was lying in bed.
1:57:54
>> Questions when I was falling asleep, >> okay?
1:57:57
>> And to ask an LLM something can easily happen in the first 10 minutes. >> Okay.
1:58:02
>> Because I've been thinking and wondering >> and I don't get up just to ask the LLM.
1:58:06
But once I'm up, it's like, hey, I'm here. Why not? >> Yeah.
1:58:10
>> And if the question takes a while to answer, then I scroll through Twitter, email, whatever. It's perfect.
1:58:13
You want to set your queries in motion early in the day. >> Yeah.
1:58:18
I actually do find that often I'll kick off a deep research report before bed because I know it's cooking for me when I wake up. I love that.
1:58:24
That's actually a great >> uh Iran is uh is in flux.
1:58:28
Very very hard to tell, you know, what the outcome will be there.
1:58:34
Uh but uh if you have a free Iran, how how should people be thinking about how that would impact world markets?
1:58:45
I think it's unrealistic to expect a free Iran.
1:58:47
I would like to see a stable Iran, which has been rare in world history, though Iranians are often very successful.
1:58:54
There are so many ethnic groups in the territory and they have expanded or contracted so many times.
1:59:01
What they need is stability and some breathing space and a government that's not one of the very worst in the world.
1:59:07
And I think the chances of getting that now are pretty high, maybe 50%.
1:59:09
But we should set our sights a bit low and not actually reach for too much and let the Iranian people over time, you know, make it as good as they can and not have it be a question of outside influence.
1:59:21
So, oh, we're giving you this, we're making you do that.
1:59:25
I think that's counterproductive.
1:59:28
>> What about uh the looking back the post-mortem on the tariff and the trade war from last year?
1:59:33
Obviously, the markets did very well even though they were tumultuous during the process.
1:59:36
Uh what what's the economic view on the impact of the tariffs in 2025?
1:59:45
>> Not as bad as we thought, but no gain, no upside.
1:59:47
Manufacturing in this country, manufacturing employment, they're still falling.
1:59:52
>> Our allies are mad at us.
1:59:52
People pay higher prices.
1:59:54
When I buy my favorite rainer cherries from Chile, they're 9. 90 pound 9.
2:00:00
99 a pound instead of $6. 99 the year before.
2:00:04
>> What's the point of that? So I'm against it. against [laughter] it.
2:00:07
Well, uh, we are certainly not against your appearances here.
2:00:11
We love having you on the show and we appreciate you taking the time to come chat with us.
2:00:14
Thank you so much for coming. >> Always a pleasure.
2:00:18
>> And always a pleasure.
2:00:19
>> I'm glad your 2026 is off to a great start.
2:00:21
I hope you have a great rest of the week. We'll talk to you soon. >> Great to see you. Cheers.
2:00:24
>> Have a great rest of your day. >> Uh, Finn.
2:00:26
AI, the number one AI agent for customer service.
2:00:29
If you want AI to handle your customer support, go to finn. ai.
2:00:35
And I'm also going to tell you about cognition.
2:00:36
They're the makers of Devon, the AI software engineer.
2:00:38
Crush your backlog with your personal AI engineering team.
2:00:43
And up next, we have Sarah Brus in the Reream waiting room.
2:00:49
Andrew Feldman is the co-founder and CEO, and we will have him join us in the TVP Ultradome. Andrew, how are you? >> He's back. >> Good. How are you guys doing? >> We're doing great.
2:00:58
And we're thrilled to not just have five minutes today.
2:01:00
We have a the last last bot.
2:01:06
So, thank you for taking a sh giving us a second chance.
2:01:09
There aren't many second chances in life, but we appreciate you uh having uh taking one with us.
2:01:14
Uh but anyway, how are you doing?
2:01:16
Uh how's how's your new new year going?
2:01:18
Um I'd love to just hear the state of the business and the level of optimism going into 2026.
2:01:25
Look, >> I think it's an extraordinary time to be in.
2:01:27
Well, first thank you for for uh inviting me back. I I appreciate it.
2:01:33
It's always good to talk to you guys. >> Thanks.
2:01:34
>> Um look, it's an extraordinary time to be in AI hardware.
2:01:39
>> I I think uh we have seen exceptional interest.
2:01:43
We've seen validation in the market.
2:01:46
We've been telling people for uh years that fast inference would be a separate category.
2:01:51
Uh and so important was this new category that that Nvidia spent $20 billion to buy the number two player in it.
2:02:00
>> And so um uh what a what an exciting time >> to to see.
2:02:06
I mean you were just talking about the guys at Cognition, big customer of ours and and what a great product, blisteringly fast, smart as can be, great coding tools.
2:02:16
Um it it is uh what we're seeing may maybe way to think about it is this is that that we had a GPT moment in 2023. >> Yeah.
2:02:29
>> Where people first realized that that a AI was interesting. >> Yeah.
2:02:34
>> And in the second half of 25 people demonstrated it was useful. >> Yeah. >> Right.
2:02:39
And that that is exploding.
2:02:42
They're finding different uses for it. These aren't demos.
2:02:45
These are production use cases and they're demanding vast amounts of of AI compute. >> Yeah. >> Underneath that. >> Yeah.
2:02:56
The fast inference thing is is so it's so obvious that it's become a meme.
2:03:01
I'm sure you've seen these where uh people will be uh you know joking about well I'm coding and while I wait for my coding agent to come back to me I I open Tik Tok and I scroll vertical videos.
2:03:13
And so I saw one guy made a made a script that as soon as he sends his prompt, it automatically opens them and then it closes them as soon as it responds so that he doesn't get sucked into a rabbit hole.
2:03:23
But [laughter] it's like it's brain rot, but it it exposes a real a real behavior, which is that there's a lot of waiting involved in programming these days.
2:03:33
>> How cool is it that other people are are are making Tik Tok videos about your value proposition? >> Exactly.
2:03:39
It's like how cool how often does that happen that an entire ecosystem's creativity >> is being brought to bear on how shitty the competition is to use. >> Yeah.
2:03:52
>> And what a what a cool thing. Yeah.
2:03:55
>> Um >> and since we have more time, I'd love to go back uh and actually get more of your full story, more of the story of the company and and sort of take us back in time to the initial idea, the first things that you did, all of that.
2:04:07
So, uh, if you could sort of, uh, you know, reintroduce yourself and the company, I think that that would be a really good level setting experience. >> Great. I'm Andrew.
2:04:17
I'm one of the founders and with Sean and JP, Michael, and Gary, we we founded Cerebrus in uh, early 2016.
2:04:28
>> What we saw on the horizon then was driving.
2:04:30
[laughter] >> There's still going to be some soundboard here.
2:04:33
The overnight success is real.
2:04:36
>> The overnight success, >> it really has been, right?
2:04:37
I mean people people were skeptical at v various amounts of times and I think people are finally getting it now. >> Yeah.
2:04:44
I I think that when you build real things >> Yeah. right?
2:04:47
You you don't get the same sort of rate of growth that you have in a in a viral software, right?
2:04:53
I mean, when you actually build physical things, there's components, there's factory, there's real manufacturing work that needs to happen.
2:05:03
[snorts] And especially when you do deep tech >> and what we what we set out to do, what we saw on the horizon was a new workload that AI wasn't the same.
2:05:13
It it it presented fundamentally different challenges to uh to to the computer and that if we were able to build a new design, >> we would not be a little bit faster, not one or two or three or five times faster, that we could get to 10, 20, 30, 50x faster >> on this work.
2:05:37
And the way to do it was to solve a problem that had been unsolved in the computer industry for 75 years.
2:05:44
And that was how to build a really big chip.
2:05:47
>> You know, most chips are the size of postage stamps.
2:05:48
And our chip is is the size of a dinner plate, >> right? >> So good.
2:05:56
>> And and so um now it it it took >> Yeah.
2:06:00
>> an enormous amount of work to build. >> Yeah.
2:06:02
What what walk me through exactly like you you incorporate the company and then you're doing design and you're calling a manufacturer and saying, "I got this crazy idea."
2:06:12
And then I imagine like a year years go by until the first one comes off the line.
2:06:17
You can actually test it.
2:06:19
Like what were those early days like?
2:06:22
>> They they were unbelievably challenging.
2:06:24
I think when you do [laughter] >> when when you do really hard work uh your first one is like that first pancake.
2:06:31
You know, it's [clears throat] sort of messed up.
2:06:32
Make the pancake and the the pan isn't hot enough and the pancake is all nasty and and it's like that.
2:06:41
And we [snorts] had an idea that that we could solve this class of problems that had broken every other effort to build a big chip. >> Mhm.
2:06:50
>> And uh we we spoke to backers that had vision and believed in us. >> Mhm.
2:06:56
>> And we put together one of the the truly worldclass chip teams in the industry.
2:07:02
There only about half a dozen world-class chip chip teams and we have one of them. Mhm.
2:07:06
>> And then we uh we laid out a plan and we flew out to TSMC and said, "We we think we can do um uh something with your process >> that nobody else has ever been able to do."
2:07:23
>> And they listened and and to their enormous credit, they listened and said, "Shit, that's a good idea."
2:07:28
And in the meeting, they green lit it. >> That's amazing. >> It was amazing.
2:07:32
What was their what what what risks were they identifying?
2:07:35
What was their push back?
2:07:37
I mean, even if they say, "Yeah, we'll take your money and we'll build this thing."
2:07:40
What are they cautioning you about at that moment? >> Well, also Yeah.
2:07:44
Also, I feel like if you're a founder, you get a lot of nos.
2:07:49
Sometimes it's with customers, sometimes it's with uh investors or talent, but if you're building a chip and TSMC says no, like you do you do you just go back to the do you go back to the drawing board?
2:08:00
like you you got to give them that carries like quite a bit more weight than just an investor saying I'm I'm I'm passing.
2:08:07
>> I mean there's TSMC is the best in the business.
2:08:11
And so uh um we we heard no when you do when you're interested in pioneering work, when you're interested in fearless engineering, you're going to hear no a lot because everybody's afraid of the problem that you're trying to attack.
2:08:25
And when everybody's failed at a problem, then those who are medium, lack vision, are always like, "It'll never work. It can't be done. Others failed." >> Yeah.
2:08:38
>> And it it takes a special type of person to say, "Well, just cuz others fail doesn't mean we need to fail. The world has changed. The tools are better. We have better insight.
2:08:47
We can use uh architectural techniques to avoid some of the things that broke previous efforts.
2:08:55
And so what we did is we went out, we studied the previous failures and we came to believe that that we could work around everything that had broken previous efforts and uh we brought this back to our investors.
2:09:10
They're like, "Wow, this could be really big." And uh we we tuned it. We tuned it.
2:09:16
We flew out to TSMC and they agreed.
2:09:18
Um I I think even when you do pioneering work uh you encounter problems that nobody thought of. >> Yep. >> Right.
2:09:28
I like to tell the story that I mean imagine before Everest was summited.
2:09:32
You get to base camp and there's a a team there having tea that just failed to summit.
2:09:36
And you talk to them and you go, "Hey guys," and they say, "There's this part about halfway up that's really really hard at being.
2:09:44
>> No one's ever gotten past it." >> Right?
2:09:46
and you go up and you go up and you come down and you're having tea with the same guys and you lean forward and say that wasn't the hard part, [laughter] >> right?
2:09:55
And when you do things that nobody else had ever done, you encounter things that nobody else has ever encountered and uh we had to invent materials, we had to invent packaging techniques.
2:10:06
The problem that caused, for example, the the B200 to be 18 months late was a problem of the coefficient of thermal expansion that we'd solved in 2017.
2:10:14
We saw it, we knew it was coming for them, and we'd solved it.
2:10:19
The problem that that caused the dojo project, the Tesla to fail.
2:10:23
We'd predicted we'd solved it in 2018.
2:10:25
Um, we we we had already encountered these pro these problems.
2:10:30
We'd found ways around them.
2:10:30
And uh you know what fun is it to be an engineer if if you're doing the same stuff everybody else has done already?
2:10:38
I mean, it's only fun when you're doing >> What were the What were the early kind of key customers that uh because it's great if you can have a partner like TSMC that says, "Hey, you guys are on to something.
2:10:50
We want to we want to be a part of this."
2:10:52
>> 2016 there's no LLM, right?
2:10:52
So, >> no LLM >> who's doing AI that's that might be a potential customer. >> That's right.
2:10:58
So, early customers included, you know, a visionary group at Galaxos Smith Klein.
2:11:02
Not who you think of as likely to bet on us. Yeah.
2:11:04
truly visionary group and and one of the I think truly great minds in in the application of AI to pharma is a guy named Kim Branson uh who runs AI for for them.
2:11:17
Um the the military and the national labs they were accustomed to understanding what could be done with blisteringly fast hardware. >> Interesting.
2:11:27
And so our our first our serial number 01 went to Argon National Labs, part of the DOE >> infrastructure.
2:11:35
And we have projects today with Argon and with Sandia that and the and the I guess Department of War it's now called that, uh, measure in the hundreds of millions of dollars. >> Mhm.
2:11:47
And so, uh, they were early customers and, uh, they were willing to take early machines that that were a little rough around the edges and that was our first generation.
2:11:58
Then we delivered the second generation a couple years later and it they got better and better.
2:12:04
Then we delivered a third generation and then it took off and uh, we had the rise of of inference as a meaningful workload.
2:12:12
Uh, and suddenly performance was everything.
2:12:17
talk about that early critique that I heard that part of what was going to be difficult about this was the fact that when you're operating on the wafer scale, if there's one defect, you throw the whole chip out as opposed to with smaller chips.
2:12:32
If there's a defect over here, well, I still get, you know, 80% of the chips.
2:12:37
>> No, that that was that was the received wisdom.
2:12:39
The received wisdom, remember how this works. works.
2:12:42
I mean, imagine a a a wafer is like a a big circle.
2:12:47
Imagine it's a a cookie sheet your mother rolled out into a circle.
2:12:48
She takes a handful of M&M's and throws it up in the air and they land throughout this.
2:12:54
We'll call those the flaws, [laughter] >> right?
2:12:56
They're randomly distributed.
2:12:58
>> And say you can't have a cookie with M&M's.
2:13:00
Your your mom goes like this and does a cookie cut through the entire thing.
2:13:04
And if there's an M&M in it, she has to throw away the cookie. >> Yeah. >> Okay.
2:13:08
This is exactly how it works. >> Mhm.
2:13:11
Um, now historically, the bigger her cookie cutter, the higher the probability she'd hit an M&M >> and the more good silicon around it, good cookie dough would need to be thrown away. >> Mhm.
2:13:26
>> This was one of the problems everybody said could never be resolved.
2:13:29
And we solved it in 15 months with $12 million. It wasn't even a heart. >> That's incredible. Wow. >> Everybody did. everybody. And it worked like this.
2:13:41
It's there is another way to solve that problem and that's the way memory has solved it. >> Mhm.
2:13:49
>> Memory has lots of identical tiles.
2:13:53
They're called bit cells. >> Mhm.
2:13:55
>> And in the array of bit cells on a chip.
2:13:59
They have redundant rows and columns. >> Mhm.
2:14:03
>> And if there's a flaw, they map it out and use one of the redundant ones. >> Interesting. >> And that's it. >> Yeah.
2:14:09
They're built to withstand flaws, not avoid them. >> Okay?
2:14:13
>> And so we looked at memory and said, "Nobody's ever done this in compute, but if we built a computer architecture with a million identical tiles >> and we took 5% of them and we held them aside for redundancy, we could withstand almost all failure patterns." >> Mhm.
2:14:34
>> And so we we thought about the problem differently. >> Yeah.
2:14:38
And it it that wasn't it was top of everybody's mind.
2:14:42
They've just been taught that that big chips have lower yield.
2:14:46
They they don't really understand the alternatives.
2:14:50
>> In the same way when Google first built their big data centers, they they said, "We don't want servers that are redundant.
2:14:57
If they fail, we'll route around them.
2:15:00
>> We don't want to pay the extra cost of making them high reliability.
2:15:03
If they fail, we'll shut them down. will get new ones. We'll route around it.
2:15:09
>> So, does that mean that between from chip to chip there might be a slight difference in the number of flops or power that can come out of the chip?
2:15:15
Is that is that like a real thing?
2:15:19
>> Not that it matters practically, but I'm just wondering.
2:15:21
>> We have to invent a a way to communicate across that little bit of cookie dough between the two cookie cuts that your mother makes, right?
2:15:32
She she puts the cookie here and she puts the cookie cutter here for her Christmas cookie and there's a tiny little bit of dough. >> Yeah. >> Right.
2:15:39
And usually what she does is she lifts all that bit of dough up and rolls it and makes more cookies later.
2:15:44
>> But in the chip world that's called the scribe line. >> Okay.
2:15:48
>> And they run a laser across it and that's how they dice the chips.
2:15:50
That's how they cut them. >> Yeah.
2:15:54
>> They obliterate that that tiny little bit of distance.
2:15:56
We had to invent a technique to run communication across those And we had to use the tools that were already being operated at at TSMC. >> Yeah.
2:16:10
>> And so, you know, we we benefited from the fact that we had this extraordinary chip expertise, not not just how to write logic to make the chip work, but the back-end design, what we call the physical design and timing.
2:16:23
We knew EDA tools, and we knew manufacturing of chips.
2:16:28
And so we were able to to think very differently than most companies.
2:16:34
>> How does intellectual property play into this category?
2:16:37
In so many tech startups, they say, you know, don't worry about patents.
2:16:42
Uh worry about your network effect.
2:16:44
This feels very different.
2:16:47
What's your IP strategy broadly?
2:16:49
>> Deep technology companies have to worry about technology. >> Yeah.
2:16:52
>> Um you know, [laughter] the statement of the century.
2:16:56
>> You've been you've been talking to SAS guys a lot. [laughter] Right.
2:17:00
Um they they worry about virality and they worry about network effects.
2:17:03
Um >> we we worry about the fact that we can build things nobody else can build. >> Yeah.
2:17:10
>> And that that is a combination of of protecting your IP with patents with trade secrets >> uh wi with uh segmenting your manufacturing so your manufacturers can't see >> Oh, interesting.
2:17:23
>> Uh uh the interaction between steps.
2:17:27
It's using all the tools in all the wisdom in in your sort of in your toolbox to defend your invention.
2:17:36
>> And sometimes patenting is not the right. Right.
2:17:37
When you patent, you have to disclose. >> Yeah. >> Right.
2:17:41
And if you have to disclose something that is then very difficult to tell if somebody else used, you might want to think about not patenting it. >> Yeah.
2:17:50
And so, uh, generally you want to patent things that that you can then measure if someone stole. >> Mhm.
2:17:58
>> And so, we have a very aggressive patent strategy, but we also have a very aggressive trade secret strategy and a collection of other tools that we use to defend our inventions.
2:18:07
>> Talk to me about space data centers.
2:18:07
It seems like uh if it does work, if the heating question is solved, um, you probably don't want a server rack with a ton of chips in space.
2:18:18
that seems like more to manage more networking uh wafer scale compute in space could be a logical extension of that.
2:18:26
Are you excited about that? Have you dug into it?
2:18:29
Has it been something that's been on your >> road?
2:18:31
I was digging into it this weekend with with some friends.
2:18:32
I think the following I I think one of the uh real weaknesses >> of [clears throat] today's GPUs is by being little tiny chips, it has put a lot of pressure on how you tie them together. Mhm. >> Right.
2:18:50
And this is why Nvidia bought Melanox. >> Yeah.
2:18:53
>> Why did it make sense?
2:18:53
Because they knew that the individual chip would be far less powerful than a collection of chips.
2:19:02
And if you're going to bring a collection of chips to a problem, you have to tie them together.
2:19:07
Now, that problem is made more complicated in space, >> right?
2:19:11
You would like bigger blocks up in space.
2:19:16
Um I think uh there are a lot of hard problems yet to be solved with data centers in space.
2:19:22
I think uh we ought to be working on them but I I don't think it's something that you're going to see in production in the 3 to 5 year time frame. >> Sure.
2:19:31
What about uh on the topic of cooling?
2:19:34
Uh we were just talking to Jeremy from semi analysis about how uh Meta changed their uh data center design from this H structure that was air cooled, very efficient, took them two years.
2:19:47
They couldn't do water cooling.
2:19:49
Uh now they're doing water cooling in their new data centers, the tents.
2:19:51
Um what what have you learned about uh various ways to cool?
2:19:56
What's special about your product specifically with regard to cooling and and energy management?
2:20:03
>> Look, this is not a complicated problem. Um, I love it. >> In in >> I'm sure. Yeah. Yeah. You want to employ me?
2:20:10
You want me to handle it?
2:20:10
It's not complicated, right? >> I got it. >> I can do it. >> In Buffalo, >> Yeah.
2:20:16
>> at a at a Bills game, there always three idiots who have their shirt off, right?
2:20:21
It's 10 below and they've got their shirt off and Right.
2:20:23
They've been drinking hard, but they're not dead. Yeah. >> Why aren't they dead?
2:20:30
>> Because if you're if you're in the water >> and the water's 45° and you're there for 8 minutes, you're dead. >> Why is that?
2:20:38
It's because water's really good at sucking heat off >> off heat sources. >> Yeah. >> Right.
2:20:44
We we say in the technology, the thermal density of water is really high. It it rips heat off you.
2:20:51
>> Whereas the air doesn't do that.
2:20:51
So they can stand there with their shirt off and not be dead. >> Mhm.
2:20:58
>> It's the exact same thing when you're cooling a chip.
2:21:00
That water has an ability to pull heat off a heat source that is vastly better than air. >> Mhm.
2:21:10
>> So you have two choices.
2:21:10
you you can blow cold air over your chip and you don't get the same cooling effect as if you ran cold water against the back of your chip or against the back of a cold plate.
2:21:25
And so it is more efficient by an order of magnitude to use liquid water in particular is great and low cost to pull heat off the back of chips.
2:21:38
>> And we were among the first to do it.
2:21:40
Google started doing it with their TPUs in in 2017.
2:21:42
Um, it had been done previously in the supercomput world exclusively and now you know the new we do it been doing it for years.
2:21:54
>> Gamers I remember you build a gaming gaming rig, you get liquid cooling if you want that extra juice.
2:22:01
>> Yeah, >> that's exactly right.
2:22:01
Gamers have been doing it forever because they want to run those GPUs hot totally.
2:22:06
>> And we It's Facebook was they they learned a lesson and they jumped on it.
2:22:15
>> Well, they were optimizing for one thing which was this energy coefficient and now they're optimizing for speed and new scale and so they have a different set of optimization parameters and they adjusted their strategy.
2:22:25
What else in the supply chain have you had to find partners for or develop inhouse?
2:22:30
I know you have experience actually building servers, but uh how much else changes when I'm racking your product versus an NVIDIA product from the energy that's outside to the land to the building to the we talked about the cooling. What else is different?
2:22:47
How do you solve those to actually stand up whole data centers? >> Right.
2:22:53
So, we we designed to fit in the exact same footprint as as an NVIDIA >> rack 72. >> There you go. Right.
2:23:00
And so, uh, we are underneath that envelope.
2:23:04
We will fit in any any data center designed for for that.
2:23:09
>> Um, you know, there are fewer little boxes to stuff in because we have a bigger box, but we fit in the standard racks. >> Yeah.
2:23:17
>> You just roll them in.
2:23:17
They're exactly the same as you bought for your Dell servers or your for your uh super micro servers >> um or your your Arista switches.
2:23:25
These are we fit in exactly the same. we use the same power.
2:23:31
We we require the same cooling that that all high-end uh >> uh AI chips now use.
2:23:38
And so uh we we were able to uh we we were able to to sort of fit in the envelope that they carved out. >> Yeah.
2:23:51
>> To make it really easy for data center operators and owners to roll us in.
2:23:54
And then on the demand side are our customers who want to use your chips asking, "Hey, we'd love for you to rack these with the hyperscalers or set up a deep relationship with a bunch of NeoClouds or they want to buy and operate themselves or they want you to buy to build the data center and just offer basically like an API for them or >> all of them. All of the above. We have an API service. It's ripping right now.
2:24:22
We have uh customers who buy the hardware and ask us to operate and manage it for them in their facilities.
2:24:28
We have customers who uh uh buy the hardware and they operate it, manage it in their facilities.
2:24:33
We have customers that >> uh the the whole gamut.
2:24:36
Uh you can buy our hardware, you can rent it by the the week, the month, the token uh from various clouds.
2:24:43
So it's um the the the customers have sort of consolidated around either they have uh demand to buy hardware and operate it on one side or uh they're sort of under 30 and have grown up in the cloud world and uh don't want to think about hardware.
2:25:07
They want to think about tokens and then they pay by the token.
2:25:11
How uh what what use cases outside of the coding agents you mentioned uh uh cognition working with you?
2:25:16
That one seems super logical in the sense that people are waiting for these agents to complete their really long work uh rollouts, really long like tons of tokens generated uh to to build a whole app or build a new feature.
2:25:30
Uh where else are you excited about the potential of not just AI this year but faster AI and faster inference having an impact that might be tangible to someone like a software developer or even a consumer.
2:25:45
>> I I think uh some of the use cases we've seen in pharma are extraordinarily interesting.
2:25:49
[clears throat] I I think >> so that that that feels weird to me because if I'm developing a drug it's going to take me three months to get mouse data.
2:25:56
It doesn't feel like a couple minutes matters.
2:25:58
What's going on in pharma?
2:26:00
I I I think it it is exactly because the process is so long and painful and expensive that if you can rip a year out of an 18 process where the whole patent is only good for 27 years, >> you've made a huge difference. >> Interesting.
2:26:16
>> And so you can run more experiments in less time. >> Interesting.
2:26:21
>> And the probability that uh once you run these experiments, you have to go to the wet lab which is much slower.
2:26:26
you the the probability that that that the one you select out of the simulation out of the AI is a good one and makes sense to go to the wet lab and take to the next level increases dramatically.
2:26:41
>> Yeah, >> I think the the act of being a researcher, right, is really one that AI is particularly well suited to help.
2:26:47
You want to scan the literature.
2:26:49
You want to make sure that that whether it's in Chinese or French or English, that if there's a publication about the gene you're studying, that you're on top of it.
2:26:57
You you you want to be able to scan the literature. >> Yeah.
2:27:01
>> And >> basically every question is a deep research report.
2:27:02
And so you you want to go if you can go from half an hour to two minutes, that's a huge speed up in your workflow. >> That's right.
2:27:10
And so what you're speeding up is the researcher.
2:27:12
>> Yeah, that makes sense.
2:27:13
>> And you're increasing the number of questions they can ask per unit time. >> Yep. Yeah.
2:27:19
>> That is uh a very very exciting application. >> Yeah.
2:27:24
Jordy >> uh out of your sweet spot, but how do you expect the memory and CPU market to evolve uh this year?
2:27:33
>> I think uh first memory has historically been an extraordinarily cyclical market, right?
2:27:38
I mean, it it has had painful troughs >> uh and and crazy high prices both.
2:27:47
Um, and I I think right now what you're seeing is a tremendous amount of demand for HBM, which is a form of DRAM. >> Mhm.
2:27:55
>> Um, I think uh those fabs aren't easy to build.
2:28:00
So, additional capacity isn't easy to bring up. >> Mhm.
2:28:03
>> And so, you've had this steep upswing of GPUs which are heavily dependent on uh this HBM.
2:28:12
And uh as a result all the capacity for for DRAM has sort of moved towards HBM.
2:28:19
That's made traditional DRAM and servers more expensive.
2:28:21
When it gets more expensive, the hyperscalers panic.
2:28:27
Panic may be the wrong word, but their response is to place orders for for the full year, >> which causes the Dell and and the the the server builders to go, "Holy crap, I need to buy more. Yeah. Right.
2:28:40
And you just watch this uh sort of crescendo of uh of price exploding, right?
2:28:49
You just see this huge movement in prices as everybody worries that they're not going to get it.
2:28:56
So, they place all their orders for next year early.
2:28:58
So, it looks like the year is going to be way bigger than it actually is going to be.
2:29:01
And you that's what's happening right now.
2:29:06
>> How are you thinking about the the financial management of the business? You raised the 1.
2:29:09
1 billion series G uh last year.
2:29:13
Are you thinking of building the company for a really long time in the private markets, taking it public? >> Thank you for sound. That's perfect.
2:29:20
>> Yeah, we probably hit the gun properly. >> I appreciate that.
2:29:31
>> Uh but but where do you see the company going?
2:29:32
How do you want to operate?
2:29:32
What makes sense in 2026?
2:29:34
Yeah, unlike some of our our competitors, we we we sought to to run a a business that could be measured on traditional financial metrics.
2:29:46
>> We we like >> I love just taking taking shots [laughter] on the way into that that answer.
2:29:53
>> Look, I mean, I I I think we we we do we we seek to to run a a business that >> people can look at and understand. Mhm.
2:30:03
>> And uh you know, our our gross margins are are are we're better than all our startup competitors.
2:30:08
We uh we're growing faster and we're bigger.
2:30:12
>> And so I I think that's really um >> Let's go. Give him the fog horn.
2:30:17
[laughter] >> Oh, I I I You guys got to tell me like in in a pre-briefing what the various sounds [music] mean so I know what >> they're all power.
2:30:25
>> This is This is the heavy tanker ship.
2:30:27
You'll you'll know if it's the right >> the heavy tankership is backing up the truck for big business. We love it.
2:30:35
>> I think um we raised the money because uh we had a ton of opportunity to continue to invest in the business to produce extraordinary growth.
2:30:42
I mean that's the right reason to raise money, right?
2:30:45
You raise money because the opportunities in front of you >> are large and many and maybe have a time uh element to them.
2:30:52
So attacking them quickly is of value. >> Yeah.
2:30:56
And so that that's that's why everybody I mean if you go out and raise money from other people that that's why you should do it is because your opportunity set is uh ripe for for pursuit.
2:31:07
Um and so that's what we did.
2:31:07
I I think uh we we will deploy it in expanding expanding manufacturing um which is a uh real value in the acquisition of additional data center capacity.
2:31:24
um a collection of other things, expansion internationally.
2:31:26
These are all things that that the business is asking for right now.
2:31:31
>> Let's hear it for opportunities that are ripe for pursuit.
2:31:34
I like >> and traditional pursuits and traditional financial metrics.
2:31:37
Um those how can >> when in the past has it been worth a clap to say that you like positive gross margins that that you'd like to you'd be surp You'd be surprised.
2:31:47
We've had we've had some people we we have people come on.
2:31:52
They're trying to bait people by saying, "I don't care about gross margin.
2:31:55
I don't [laughter] care about >> Yeah, they do. They do.
2:31:57
We care here and we thank you for caring as well."
2:31:59
Um >> uh what what can people expect u out of big, you know, any any big announcements in the pipeline?
2:32:06
How can people work specifics?
2:32:08
But >> yeah, I I'm interested.
2:32:10
>> I think you can go to surbur.
2:32:10
ai and [clears throat] you can try our our you can see how fast it is yourself, right?
2:32:17
I I think we the the beautiful thing about the cloud is that it's uh dead dead simple to demo and to try and you we've got a free tier. Jump on it, play around.
2:32:27
Um ask a GLM model, which is a great coding model.
2:32:31
Just ask it to make a video game for you. >> All right.
2:32:35
And you will see in 3 seconds it'll make Space Invader for you.
2:32:39
>> That that will be real code. Yeah. >> Right.
2:32:41
Ask it to to to play pool to to make a two play player pool game.
2:32:44
or if you're a physics nut, a a threeball interaction according to laws of physics.
2:32:51
I mean, just ask it to do interesting things and you will see uh right away the the joy how fun it is to engage with an AI that is truly interactive. >> That's amazing.
2:33:05
>> And I I I think that's the best marketing you you if you go there and you enjoy it, um send us a note. We'll we'll follow up.
2:33:11
But >> play with the eye. I mean, screamingly fun. >> Just use it.
2:33:16
>> Well, thank you so much for taking the time to come chat with us.
2:33:18
We hope you have a great rest of your day and congrats on all the progress to really chat and [applause] yeah, congrats on >> guys.
2:33:25
Thank you for having me back.
2:33:25
It's very much appreciated. See you soon. >> Anytime. We'll see you soon. >> All right, guys. >> Goodbye. vibe.
2:33:30
co where DTOC brands, B2B startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on Meta. >> Well said, John.
2:33:41
And I'm also going to tell you about Console.
2:33:42
You see it here on the sticker.
2:33:45
Console builds AI agents that automates 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
2:33:53
Um, >> we are now entering the uh the our lightning round. >> There you go.
2:34:00
>> The Lambda lightning round. >> That is real. The cloud is real.
2:34:03
It is lightning in the Ultra Dome >> from Terra coming in.
2:34:08
Nathan is in the re waiting room.
2:34:11
Let's bring him into the TV pan.
2:34:12
Nathan, how are you doing? >> Very good.
2:34:17
>> Thanks so much for taking the time to hop on the shirt.
2:34:18
It almost look Oh, I thought it was a jacket for a second. Uh, very very cool. >> Looks great.
2:34:25
Uh, please introduce yourself. Introduce the company. >> Yeah. Awesome.
2:34:29
I am Nathan, um, co-founder and CEO of of Terra Industries.
2:34:33
I'm a 22-y old software engineer and essentially we're building Africa's first modern the first try. Wow.
2:34:39
And uh what got you into the industry?
2:34:42
What were you doing before?
2:34:44
How did you recognize this opportunity?
2:34:47
>> Um well, I I began my journey in tech when I was 15.
2:34:52
Um had an accident that made me lose my lose my sight >> success.
2:34:56
[laughter] And uh at some point during the pandemic um I was 17 at at at this time I went on to launch my first you know startup that was solving like the the education crisis especially in emerging markets.
2:35:10
Um and that allowed me to to understand that uh basically if we truly want to help industrialize the continent if we truly want to help push Africa towards like a massive industrial growth we have to solve much more foundational infrastructural problems.
2:35:24
And I start to think around you know what is the single problem that we could solve today that could basically cut across every every industry.
2:35:34
And that's you know what that common um denominator was was was was security.
2:35:38
So sometime in 2024 I and my co-founder Maxa we we um decided that we want to start um terror industries to essentially give Africa the technological edge needed to um to uh um defend it itself its resources and its critical infrastructure. >> Sure.
2:35:57
How are you thinking about the first products?
2:35:59
Uh there's a lot of uh defense technology companies that focus on drones or maritime or ground autonomy.
2:36:07
there's a whole bunch of different products.
2:36:09
It's I imagine you want to build them all eventually, but uh do you have a a foothold that you want to dominate in first? >> Yeah.
2:36:18
So for us, we're thinking quite multi-dommain.
2:36:19
Um the the question for us is how can you protect these critical um assets from all sort of threats and right now know this evolving threats are coming from the air, from land and from sea.
2:36:31
So in the aerial domain we have our longrange and short range drones.
2:36:33
In the ground domain we have our sentry towers and soon in the maritime domain we'll be deploying some USVs that will be that'll be carrying out large scale maritime surveillance.
2:36:42
All these different systems are being powered by one unified software platform that carries out data intelligence you know um um collecting all these data from all the different systems synthesizing that data and um um allowing the security agencies to identify and track threats in real time.
2:37:00
So this is basically what we're trying to to do.
2:37:02
You could almost think of it as kind of like the same strategy that Palanteer did in the west, you know, but the major difference is we also have to build out the hardware um um infrastructure that is collecting this data because there's there's no like previous um surveillance infrastructure that allows us to basically plug in our our software platform.
2:37:23
>> How does the procurement uh process work in Nigeria?
2:37:26
How is there a program of record concept?
2:37:30
Are there grants for smaller projects? Uh what what's the goal?
2:37:35
>> You guys already have a a couple million dollars in revenue.
2:37:38
Sounds like that's growing quickly. >> Yeah.
2:37:40
How did that come together? >> Yeah.
2:37:43
When we first started um the company, we focused mostly on privately owned infrastructure assets, you know, lower barrier to entry, shorter sales cycle that allowed us to rapidly scale.
2:37:54
Um so um mostly owned by like corporations and billionaires but over time we're able to build an impressive enough portfolio that allowed us to then sell to governments and uh and militaries.
2:38:05
So >> the the defense contracting model in Africa is like fundamentally very different from how it's done in the west.
2:38:12
In the west is quite bureaucratic.
2:38:14
It could take you one to two years before you get to like a program of of record.
2:38:18
In Africa is quite very network-based you know and also very solution first.
2:38:22
So essentially no one is is is really expecting you to write um um dozens of of of proposals and you know come to office and present them like powerpoints they're expecting you already have a solution to their problem.
2:38:37
problem. So in a very funny way, the Android approach of like taking R&D head on and having the the actual products to then go carry out live demos on the field works perfectly for the model of defense contracting on the continent and that has allowed us to scale very
2:38:56
rapidly and that is something that most western companies don't understand you know western Chinese you know they come here with papers [laughter] >> and uh they end up basically you know um wasting a lot of time um and not really being very productive. >> Yeah. >> Yeah.
2:39:10
>> Do you guys have a dual use opportunity?
2:39:13
I can imagine people that that have uh various assets on the continent that could be oil and gas they want to I can imagine maybe your sentry towers are applicable drones etc.
2:39:21
Uh even for non-kinetic solutions just surveillance uh from a security standpoint what kind of opportunities are you guys pursuing there?
2:39:34
>> Yeah, we don't do kinetic at all.
2:39:34
So we are entirely focused on building surveillance. >> Sure.
2:39:40
>> Because you know essentially the Nigerian army today has enough firepower to you know um basically destroy any terrorist group in West Africa.
2:39:48
The the the problem with insecurity in Africa today is not the lack of firepower.
2:39:53
It's the lack of intelligence, the lack of visibility.
2:39:57
visibility. you know um understanding where these attacks are are coming from how is being perpetuated you know looking at previous attacks to to to um sort of like part out a pattern recognition that can help you predict future attacks this is the major issue so what terror is trying to do is build
2:40:14
that intelligence and surveillance layer across the continent not necessarily you know um uh building kinetics you know we don't ever intend to get into kinetics I think it's the um the the sort struggle and war that African governments are fighting against terror does not require us getting into kinetics. You know what the religious
2:40:33
You know what the religious negative and that kind of takes me into like my second point of like data sovereignity.
2:40:40
Um because um today when we announced around there was a lot of you know viral tweets of how Palanteer is now in Africa.
2:40:48
Um we are sellouts and stuff like that.
2:40:52
stuff like that. Um so I want just make it very clear you know >> um >> this is an investment from yes a Palanteer co-founder um and several other visas but this is a technology that is entirely owned by Nigerians is built by us is managed by us operated by
2:41:12
us we have no direct relationship with Palanteer we don't share any data with Palanteer so that's just something to just very clear that's a good point to make uh obviously as you scale a business, you're going to need to hire a lot of people. Uh what where are the
2:41:24
Uh what where are the great talent pools in Nigeria or Africa broadly? What's the Stanford? What's the Waterlue? What's the Y Combinator?
2:41:31
Uh where will you be sourcing candidates from? >> Yeah.
2:41:38
Um first off, you know, Nigerians are some of the smartest people you could ever meet.
2:41:42
You know, very underrated talent base.
2:41:45
base. Um there's there's already a lot of like software talent on the continent mostly because of that fintech boom of you know the >> exactly empa wave so there's there's there's a lot of existing software talent and in terms of hardware you know
2:42:01
there's there was basically an um a hidden um hardware base you know that have been working mostly with the military they have been doing a lot of side projects they have never been able to kind of commercialize their skills at
2:42:14
scale And you know what we essentially went um um um um did was we we went to these communities and we hired the entire communities [laughter] you know um I love it >> community acquisition >> it's [laughter] great >> you know so for us really in scaling
2:42:33
talent is it goes beyond Nigeria because part of our strategy is we we want to build a decentralized manufacturing network you know so having >> a factory in each sub region you know our manufacturing base now in Nigeria would serve West Africa. >> Um in the next couple of months we'll be
2:42:47
>> Um in the next couple of months we'll be opening a factory in East Africa to serve the East African region.
2:42:51
And the reason that we're doing this is you know first of all it's it's it's much easier in terms of supply chain and logistical networks.
2:42:59
But second you know um the threats that are being faced in in each of these regions are actually quite different.
2:43:05
different. you know in in in West Africa you have t mostly in like the Saharan you know very hot climates very desert climates um you're mostly deploying mostly aerial and ground systems but when you come to East Africa you know
2:43:20
you have issues for example with mostly in the maritime you know with the Somalian pirates um where you would mostly have to deploy you know maritime systems so you you can't essentially have one centralized factory building for the continent you know Africa is too big for that. Too big, too complex. You Too big, too complex.
2:43:35
You have to basically use this decentralized manufacturing network.
2:43:39
So each factory we open would tap the local base of the region it is located at. >> Sure.
2:43:46
Uh give us the information on the round. You raised some money.
2:43:48
We want to hit the gong for you. How much did you raise? >> 11. 75 million. >> Congratulations. >> There we go.
2:43:59
>> And thank you for taking the time to come chat with us here.
2:44:01
>> Yeah, great to meet you.
2:44:01
I'm sure I'm sure you'll be back on very soon and congrats to the whole team on a very cool milestone and getting a great group of people involved.
2:44:10
You got 8C of course, Valor Equity, Lux Capital, Wow, >> SV Angel, Silent, Mickey, >> Alex Moore. Let's go.
2:44:21
Well, thank you so much for coming on the show and have a great rest of your week. We'll talk to you soon. >> Great hanging. >> Goodbye.
2:44:26
Phantom Cash, fund your wallet without exchanges or middlemen and spend with the Phantom card.
2:44:32
You see the ticker with the crypto prices in the bottom of the stream. That's from Phantom.
2:44:38
And before we bring in our next guest, I'll also tell you about Lambda.
2:44:41
Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
2:44:48
So up next, we're going over to LM Arena.
2:44:54
>> Anastasios, welcome to the stream. How are you doing? >> Hey, brother. How's it going? Nice to see you.
2:44:58
[music] >> It's going fantastically.
2:44:59
It's going extremely well for you.
2:45:01
You raised some money recently.
2:45:03
Let's kick it off with a big gong smash. How much did you raise? >> 150 million.
2:45:14
>> I have all the good stuff. Fantastic. >> Great stuff. Great stuff. Uh okay.
2:45:16
So, our friend was just joking around this account near they were saying LM Marina raised uh at a $ 1.
2:45:26
7 billion valuation and they were using the Michael Bur. >> Very rude. Very rude. Very rude. Very rude.
2:45:32
But they were just joking.
2:45:32
But it's okay because you're here to tell us why why that's a deal of a lifetime. >> Yeah. Explain.
2:45:40
>> Listen, evaluation's a big problem.
2:45:42
Evaluation is a big problem.
2:45:42
People don't know how to solve it.
2:45:43
You have all these different AIs.
2:45:45
The space becoming more complicated.
2:45:47
You have different modalities, different models that are doing all all these people competing in coding, competing in, you know, software engineering, competing in the general chat.
2:45:56
You have models from China, models from the US.
2:45:58
Who are you going to pick?
2:46:00
Let's say you're a consumer, you're a developer.
2:46:03
>> Even even a business, you're going to make a decision that you're going to the you're going to make a decision.
2:46:06
You're going to spend millions and millions and millions and millions of dollars on that.
2:46:10
You got to make sure you make the right decision. >> Yeah.
2:46:12
Procurement procurement is a big market.
2:46:14
And you know all these problems are are huge.
2:46:16
I mean and and the ultimate problem is how do you help people find the best solution for them.
2:46:23
Um and as a neutral platform of course it needs to be separate from the labs.
2:46:26
It needs to be a third party that does this.
2:46:28
Uh we're positioned well to attack it.
2:46:30
>> So I imagine I mean independent uh we were joking around that if you ever wanted to return the capital you could get one of the labs to pay you10 billion just to put them permanently hardcoded at the top of the rankings.
2:46:40
Uh you'd be out of business in 12 months, but you'd walk away with a pretty penny.
2:46:45
>> Well, [laughter] that's the thing.
2:46:46
>> I don't think that's what's happening. How do you make money? >> Value if you do that. >> Yeah. Yeah. Exactly. Exactly.
2:46:48
So, how how do you make money then?
2:46:53
>> Well, what we do is we help labs and enterprises get analytics on how well their models are doing.
2:46:57
Help them understand the strengths and weaknesses of their models in different domains like math, coding, instruction following, multi-turn.
2:47:02
Think about it like a full body scan of your model.
2:47:06
>> And what distinguishes us from the standard benchmark is that it's all live.
2:47:09
So you can't overfit it because there's constantly new data coming in. >> Oh, interesting.
2:47:12
>> Um, and it's on real users.
2:47:12
So we have tens of millions of real users that are coming to Alam Marina using A for like this huge diversity of different tasks.
2:47:20
Uh, and that's of course the data that's used as the basis for these analytics. >> Yep.
2:47:24
Um, talk to me about the proliferation of different LM arena categories.
2:47:31
I imagine there's a exponential curve there as different models have different capabilities.
2:47:38
We're not just testing math and science reasoning and chatting ability and there's so many of these.
2:47:43
So, how fast is it growing?
2:47:45
How are you setting up your system to handle potentially tens of thousands of different benchmarks and models like how is that growing and scaling?
2:47:54
>> That is a great question and I think that we're honestly still developing what that you know big road map looks like.
2:48:01
>> But that being said, here's where we're starting.
2:48:03
Um, we have a bunch of different categories.
2:48:05
different categories. I mentioned a few earlier like math coding instruction following but we've recently also dug in a little bit more to look at different types of users basically almost like user research expert users what are experts saying about all these different models we have a leaderboard for that
2:48:19
occupational categories law medicine >> you know business which models are best for these different categories of usage marketing we have that information on Alam Marina so it's a one-stop shop for you to understand the different industry economically valuable industry level performance of these models but if you really Think about it. The long-term
2:48:35
The long-term vision of this sort of thing.
2:48:37
It's almost like every every individual should have their own evaluation.
2:48:43
>> Which model's best for you.
2:48:43
You know, the technology brothers, >> technology [laughter] brothers, eval. >> Yeah.
2:48:48
[clears throat] >> It needs to have its own kind of thing because you're you're doing your own tasks and they might be very different from what I'm doing.
2:48:53
And so eventually the future you can imagine of building a technology like this, we're building the infrastructure to do this is to have evalu.
2:49:02
How do you incentivize people to participate on the voting side, the ranking side?
2:49:06
That human element is really important in terms of grading different LLMs.
2:49:10
Uh what's the current incentive structure? How is that evolving?
2:49:14
What are the challenges that come up with uh running a multi-sided marketplace like this? >> Very good question.
2:49:20
Uh incentives are really really important.
2:49:24
If you think about it, incentive is almost like a little hack into the human brain that tells you how to move, how to operate. >> Yeah. >> Right.
2:49:30
So that's why games are so powerful.
2:49:32
Games can get you into an incentive system that's just like, hey, I'm Flappy Bird or I'm doing my Candy Crush and I'm just swiping, swiping, swiping, >> we do not really incentivize users on Alamarina to vote.
2:49:44
And that's part of the power of the platform. Yeah.
2:49:47
>> Is that unlike let's say we were to pay people to vote, we don't do that.
2:49:51
>> The reason we don't do that is because we want them only coming to do their real job.
2:49:55
They come because they get value out of the platform and they vote only because they want to because they're intrinsically motivated because they got something to say.
2:50:02
>> You can imagine if you in incorporate incentives that it might hurt the leaderboard.
2:50:08
So we're very careful about the way that we go about that.
2:50:10
However, we are exploring how can we design the incentives in sort of incentive compatible way. >> Yep.
2:50:18
>> In order to preserve the integrity of the leaderboard while also rewarding people to vote.
2:50:21
That's on our minds but not yet done.
2:50:23
How confident are you that you can encode big model smell into a uh you know the taste, the vibes into a ranking?
2:50:36
>> Well, if you look at the leaderboard, it's there.
2:50:38
It's there for you to see. >> Okay. >> Yeah.
2:50:40
I mean, it does reflect it >> and it goes to show how powerful human preference can actually be that people are seeing things that you wouldn't necessarily anticipate. Mhm.
2:50:52
>> And that's why when you know when model developers develop their model, the big problem is when I put it out into the real world in the wild, what's going to be the performance like? >> Mhm.
2:51:00
>> I don't know unless I see it.
2:51:00
And that's because people react in these, you know, strange ways when they see a model for the first time.
2:51:07
the first time. That's part of the power of this platform is that it puts it in front of those people and then we give analytics to try to understand how different individuals, you know, what are the different usage patterns and who
2:51:18
who's voting for what and so you can code things like big model smell identify, you know, it's not uncommon that model providers will find out through us that their model's really great at math or really great at coding and they didn't even actually ever know. >> What does it take to get a model on LM
2:51:31
>> What does it take to get a model on LM Arena?
2:51:33
Is it something that the lab is giving you preview access to?
2:51:36
Is there an application form?
2:51:38
Do you already have relationships with these folks?
2:51:40
Is there >> So, we have a contact form on our website that you can use if you want to, you know, submit a model.
2:51:46
Of course, we have capacity constraints, but we try to be judicious and let you know everybody everybody participate in the battle.
2:51:52
Um, and to um, yeah, in terms of paying, >> someone was asking Deep Seek >> to get on the leaderboard. >> Deep Deep Seek R4.
2:52:04
Well, uh, what does it take to get a model like that on the platform?
2:52:10
>> We'd love to get Deep Seek R4 on the platform.
2:52:11
I don't know, maybe it's already in progress. >> Okay. Yeah.
2:52:13
Um, how much does hardware matter here?
2:52:16
Uh we were just talking to Andrew from uh Cerebrus about the speed that comes from that.
2:52:23
Uh there's an element where uh plenty of people would rather use a dumber model if it's 10 times as fast or vice versa, right?
2:52:30
Uh and so you have to create an applesto apples uh situation most likely or at least uh pre-cache the results so then you're not noticing speed.
2:52:39
But do you think that speed tradeoffs will become a bigger piece of what you do? How about that?
2:52:46
Yeah, there's no question about it.
2:52:48
Really, what the the ultimate question that people have is how do I >> for myself or my organization or whatever >> choose along the purto frontier of speed, performance, and cost. >> Yeah. >> Right.
2:53:00
Those are the three things.
2:53:00
And usually it's performance and speed number one and number two. >> Yeah.
2:53:05
>> Because everybody's spending so much money right now. >> Yeah.
2:53:08
>> That it's like, you know, ring the gong again. So much money. [laughter] >> Why not? >> There you go. Go to gong. Money being spent, baby.
2:53:18
Now the issue with that is >> there's gong twice. Let's go.
2:53:21
The uh the speed if you don't equalize it, you can get bias in the ratings. Yeah. >> Right.
2:53:28
So we want to be able to disentangle speed versus performance.
2:53:31
And that requires us equalizing. Sure.
2:53:33
>> But if you go to direct chat mode, you can use the model see it just as it is.
2:53:36
And we're planning on expanding the leaderboard to get more of the speed in there, the latency um as well as cost so that people can make all those trade-offs right on our platform. >> Yep. That makes sense.
2:53:44
Would you ever do anything at the application layer or does it just get too chaotic because you know UI is a new variable and there's all these other factors?
2:53:55
>> I mean this is Alam Marine is an application. No. >> Yeah, sure.
2:53:58
But I'm I'm talking about like you know two legal AI tools and and trying to because if you go if you go down the procurement route and you're and that becomes I don't know I don't know if that becomes a big >> uh >> yeah you could see like a G2 cloud type of business here as well.
2:54:12
of business here as well. Although I have no idea if that is makes any sense for you but >> totally understood but the so the thing is that it's hard to do that for our users right because then we need to build 10 different product services or 100 different product surfaces and that's one of the exciting things about the ecosystem right now is that it's
2:54:29
actually the fundamental product surface where uh things are evolving very quickly and also a lot of value is being aggregated right there's a reason why you know number one revenue stream of open AI is consumer >> right it's a consumer application >> um and you While other companies have different strategies, but ours can't simply cannot be to replicate every application. >> Yeah. >> Yeah.
2:54:49
>> So what the value that we hope to provide again is to help people understand the different trade-offs of different models, evaluate them for their use cases, procurement, so on and so forth.
2:54:58
And that might mean helping enterprises link together with their feedback um you know understand their users better perhaps you know warm starting from the large user base that we have uh and giving them those analytics and tools to help them make decisions.
2:55:12
That's how I can imagine us moving into the application workflow. >> Yeah.
2:55:15
>> Will you ever create a romance benchmark?
2:55:19
>> How I think it's a good idea.
2:55:20
>> How quickly models make people fall in love.
2:55:23
>> Comedy benchmark would be >> Let me ask you, are you are you asking that for any specific reason? [laughter] >> Got them. >> Got me.
2:55:30
We talk about we talk about comedy, you know, comedy bench.
2:55:32
That's it's something we we try to test internally.
2:55:37
Uh uh it they usually end up being they usually end up being funny because they're so not funny that it's that it's pretty brutal. It's pretty brutal. >> Brutal.
2:55:46
Or or or if it is good, it's like recycling.
2:55:48
Like clearly it went to Reddit, copied the top joke, and then just regurgitated it.
2:55:52
>> Well, did it ever make you laugh?
2:55:52
Has it made you laugh before?
2:55:55
>> Yes, but accidentally, but when it's accidental, it's amazing. Uh it's the best. Yeah.
2:56:00
>> Where did the idea for this come from?
2:56:02
Like what was the inciting moment to start the company?
2:56:04
Well, the so there's the to start the company and then there's the idea.
2:56:08
I've been personally working on Alam Marina for almost three years now along with Wayin and Yan and there was actually a big group of students at uh at at Berkeley. Sure.
2:56:17
>> This came from an academic project.
2:56:17
I was doing my PhD on like theoretical statistics, theoretical machine learning, >> you know, kind of abstract.
2:56:24
I was in a basement proving theorems.
2:56:25
I had no idea that [laughter] I would be >> He built a basement of scraps. Scraps.
2:56:30
>> He built it in a cave.
2:56:31
>> Seriously, there were rats rats in the ceiling. No way. You know, not kidding.
2:56:35
>> I'm glad you have $150 million for a new office. Hopefully, it's nice. >> Go Bears, baby.
2:56:39
And so, what ended up happening is that I got looped into this project that was happening at Skyab, which is, you know, Yan and Joey Gonzalez and, you know, Luca and all these people at Skyab were working on it.
2:56:51
>> Um, that's the lab where data bricks came out of and any scale ray and so on. >> Yeah.
2:56:55
>> Yeah. and they were working on like how do we evaluate early days of chat GPT you know there was model A and model B they were doing one was doing better than the other on the benchmarks then you would chat with them >> and it's like hey these benchmarks are not reflective of how good it is at talking to me
2:57:11
>> so how are we going to measure that was in the context of one of their early open source models called Vikuna that they had developed >> and so the the sort of pair-wise preference hey chat with the models and see which one you like better that strategy emerged from there but it started with Amazon gift cards. It
2:57:25
It didn't start from organic usage.
2:57:26
It started from passing around Amazon gift cards to people at Berkeley >> and then it sort of, you know, popped and then it went down and kind of sat at 30 users a day for a little while and then it grew and grew and grew in large part due to way sort of consistent effort in Twitter and so on.
2:57:42
>> It's awesome >> up until the point where it became a this juggernaut, >> a true overnight success to see it over here and thank you so much for taking the time to come on.
2:57:50
Congrats on all the progress.
2:57:52
>> Hey, great to see you guys. Thanks so much. Have a great day. >> Yeah, you too. We'll talk to you soon. Goodbye.
2:57:58
>> Turbo Puffer serverless vector and full text search built from first principles and object storage.
2:58:03
Fast, 10x cheaper and extremely scalable. >> Shopify.
2:58:08
>> Yeah, >> which is relevant to our next guest. >> It is. It is.
2:58:10
Um, we'll bring them in in a second, but uh Deepseek founder uh is running a hedge fund as well in addition to building Deepseek.
2:58:18
Guess how much they're up? 57% last year. Massive year. Uh that's highf flyier.
2:58:26
Boost uh boasting the potential uh war chest for a company that's already shaken up the global tech.
2:58:33
>> Is this good for the AI?
2:58:33
Uh >> it's good for the open source community. It's good for academics.
2:58:36
What What do you think, Tyler?
2:58:39
>> Oh, I I have some other breaking news.
2:58:40
>> Give me some breaking news. >> Uh okay.
2:58:41
So So Anthropic, they have cloud code.
2:58:43
They launched uh co-work, which is cloud code for the rest of your work. >> No way.
2:58:48
>> So it's like everything else. >> That's crazy. >> Yeah. Exciting.
2:58:49
It's it's basically it's like a local app. >> Oh, it's a local app.
2:58:52
So you don't need Oh, you don't need to do the the the terminal stuff anymore.
2:58:55
You can just use it in an app with a prompt box. >> Yes.
2:58:58
And then it can interact with with all like your local files, whatever.
2:59:00
And then >> this is going to be really really big.
2:59:03
>> I don't know if you guys have used the the clawed Chrome extension, but it's like super good.
2:59:06
The the computer use is super good.
2:59:10
>> Um so yeah, this is very exciting. >> Okay. Yeah. Yeah.
2:59:11
Get ready for some threads, people.
2:59:13
People are going to be breaking it down on on all the fun things they had to do.
2:59:17
I fixed my Wi-Fi in under an hour by rebooting it.
2:59:21
[laughter] But no, seriously, I was listen I was listening to Doug Olaflin from Semi analysis talk about uh how he uses cloud code in a knowledge work setting and it's fascinating.
2:59:28
setting and it's fascinating. So he'll kick off one deep research report about one company that he's researching, then a few more, and then he'll do a deep research report on top of that, but instead of it all living in the clawed web u web UI, it's just creating markdown files that then he stores in
2:59:45
Obsidian, and then he can run these meta deep research reports on the other deep research reports that he's put together interact with whatever's going on in the semi- analysis private data world, all the data that they've they've collected, interact with their Slack, they a Slack bot that interacts with it. And so, uh,
2:59:59
And so, uh, he was he was talking he was very very oneshot by claude code and was saying everything is a skill issue now.
3:00:08
Everything is a skill issue now.
3:00:08
Um, much like generating AI voices, but thankfully we have 11 labs.
3:00:16
Build intelligent real-time conversational agents.
3:00:17
Reimagine human technology interaction with 11 labs.
3:00:20
Um, well, uh, Star Wars has already begun.
3:00:26
In reality, ask a ski resort.
3:00:26
In China, there is a robot that's skiing.
3:00:30
This feels like it should be AI, but I believe it's not. I believe this is real. This is remarkable.
3:00:36
You know, you don't have to go skiing anymore thanks to AI.
3:00:40
>> Cancel the skiing trip.
3:00:40
I have a ski trip coming up at the end of February. >> Cancelled. >> Cancelled.
3:00:44
I'm sending this guy instead. >> Yeah.
3:00:46
Just watch the video stream.
3:00:46
You don't have to put on the boots realistic to go get cold.
3:00:50
You don't have to sit on the lift.
3:00:51
You don't have to be in lift lines. >> Yep.
3:00:53
You know, >> you've seen you've seen the uh >> you've seen the drone that will follow you as you ski and takes really cinematic video. >> Yeah.
3:01:02
>> How could it be more cinematic?
3:01:02
Get the camera at waist height.
3:01:07
>> You can go way harder.
3:01:07
Hit uh hit the double black, hit the cliffs, right?
3:01:09
You don't even have to worry about rocks, right?
3:01:13
Like, >> no, he's just tumbling down on the skis. This is fantastic.
3:01:15
Uh I love uh I love the idea of having a robot follow me with a camera.
3:01:20
I don't know what else you would use this for.
3:01:24
ski [snorts] patrol surveillance.
3:01:24
I I don't know why they built this other than it's really cool and fun.
3:01:27
Uh but the obvious the obvious use case is uh Red Bull viral videos probably. >> Yeah.
3:01:35
So So the use case here is obviously uh this is the new ski patrol.
3:01:40
There's thousands of these on the mountain and they monitor your speed in real time and if you were going >> uh if you're skiing recklessly, it just skis into you and explodes.
3:01:48
Um, [laughter] and so instead of ski instead of uh instead of getting your past pulled, you just get your life pulled.
3:01:57
>> It's over kind of sense.
3:01:58
>> Um, so anyways, that is that is a dark uh sci-fi future.
3:02:03
>> I have a prediction from Gummo from Verscell, but first let me tell you about Railway.
3:02:05
Railway simplifies software deployment.
3:02:07
Web apps, servers, and databases run in one place with scaling, monitoring, and security built in.
3:02:13
Uh, GMO says, "There's definitely a non-zero chance that we get quote, "generate your own GTA 6 in a few minutes before GTA 6."
3:02:22
I think that mechanically it's possible, but uh the humor is what makes GTA so special.
3:02:28
The writing and the character development.
3:02:31
I mean, also the mechanics are very unique.
3:02:34
It's not just a walking simulator. I don't know. Have you played GTA? >> Yeah.
3:02:38
I mean, but uh Shto's game looks pretty good.
3:02:40
He he put out a screenshot of it.
3:02:42
I I trust Joto to make you.
3:02:42
Are you sure it's not just an image gen [laughter] out?
3:02:46
He's like, "Look at this crazy game I made."
3:02:49
>> I mean, the Grock folks are known to to put up some some viral videos uh espousing video game development, but clearly video game development is here. It's going to happen.
3:02:58
Um, but we have our next guest, and guess what ad I have to read before he comes on? Shopify.
3:03:04
[music] Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social and on marketplaces and now with AI agents.
3:03:12
And that's exactly what we're going to talk about.
3:03:15
We have Harley from Shopify in the team at Ultra. How do we do?
3:03:20
>> That is Was that planned? It was amazing.
3:03:23
>> No, it's somewhat random, but we timed it up perfectly. But we're very excited.
3:03:26
>> Speaking of random, I've never done an interview in my life.
3:03:28
I am at NRF, biggest retail show in the world.
3:03:29
There are 40,000 people here.
3:03:31
This is the Shopify booth behind me.
3:03:33
There's going to be random people walking by Easter egg.
3:03:39
>> That's how it all started.
3:03:39
That's how it all started right there. >> I love it. I love it.
3:03:42
So, you're in person, but today we're talking about >> Where's NR? Where's NRF? Is that Vegas? >> Javit Center.
3:03:48
>> Javit Center, New York City. >> Cool.
3:03:50
>> Everyone, it's just it's sort of the the largest conference uh actually on the planet for retail and commerce.
3:03:54
It used to be more about the traditional retailers, but um we've sort of hijacked it and made it about modern retail, direct to consumer technology companies.
3:04:03
>> You're kind of behind enemy lines there.
3:04:04
I mean, you do have a POS system, so it makes sense.
3:04:06
>> We have a POS system, but actually and and and they've given me the keynote four years in a row, which is pretty cool.
3:04:11
And today for my keynote, I brought up uh Emma from Skiims, which is amazing.
3:04:15
Uh and and Ben Francis from Gym Shark.
3:04:18
We talked about basically this idea that there will be more billion dollar brands built in the next 10 years than the last hundred years.
3:04:25
Emma, I mean, thinky shark and skims.
3:04:27
They're like 10 years old and they're so big. >> Yeah.
3:04:32
I mean, what's the key to building a billion dollar brand if you're starting in 2026?
3:04:38
It feels like it's incredibly crowded and yet there's a new breakout brand every year.
3:04:42
Uh what advice are you giving to people to get started other than just hop on Shopify?
3:04:46
>> There's multiple new breakouts and let that take out a lot of almost every vertical and and companies are growing.
3:04:52
Uh the the the way the the bar has been set with with new e-commerce brands is insane.
3:04:56
Like best in class is like okay you're doing 200 million in your second year.
3:05:01
>> I know exactly what you're talking about and there's so many examples of this and it just it just >> you guys are hard graders doing $200 million.
3:05:07
[laughter] No and no gong for that.
3:05:10
>> Of course we're of course we're hitting the gong for that.
3:05:12
>> So So let let me say something.
3:05:12
Uh I brought on my my first time I was up on stage.
3:05:17
I brought Richard from Mattel, Richard Dixon, who's now co of of the Gap because basically what he had figured out was that Mattel has this tre treasure trove of IP in their vault and he was like commercializing all of it.
3:05:29
And so it just it was amazing that a company from 1945 I think uh was basically you know dominating.
3:05:34
Uh the next year I brought uh Cat Cole from AG1. >> Oh yeah.
3:05:39
And obviously you guys know the story well but one skew $600 million, right? Like unbelievable. Another gong. >> Another gong.
3:05:48
>> Uh, I mean, there's going to be a lot of gongs in this one.
3:05:49
Uh, and then last year I brought >> someone you know, Sarah Foster from Favorite Daughter, who has been on the show, who effectively, I mean, Sarah and Aaron created a hit Netflix show to sell more apparel and and succeeded with it.
3:06:02
So, this idea that so I think one major thing if you look at all of these different incredible brands, what they've done is they didn't just take a bigger piece of an existing pie.
3:06:09
They effectively were TAM creators.
3:06:11
I mean, shapewear existed.
3:06:13
There were companies like Spanx out there, but the way that Kim and and Emma built, you know, Skiims is totally different what Spanx is.
3:06:21
It is like almost like a cool version of of an old school product.
3:06:25
Um, and then we announced four big things which uh which I'm very proud of.
3:06:31
The first is that it it's fairly [laughter] clear. >> Sorry, John.
3:06:37
Went down the wrong pipe. >> Crazy.
3:06:39
This show is is so unhinged.
3:06:42
Also, it's the end of the show, I think. Right.
3:06:44
>> [laughter] >> I'm like five Diet Cokes deep at this point.
3:06:47
So, anything could happen.
3:06:47
I haven't I just I didn't John was [laughter] doing such a good job keeping it together. >> You got me. You got me. >> That's okay. That's no problem. Sorry.
3:06:57
>> So, the first thing we announced was uh actually Sundar announced it yesterday on stage, but uh with Google, we are making it possible for every agent to connect to every single merchant.
3:07:04
We created this protocol called Universal Commerce Protocol, which effectively is this universal language.
3:07:10
It's open sourced so that all merchants can speak directly to every single one of the agents.
3:07:15
And the best way to explain it is >> up until now it was really just about like a single transaction.
3:07:19
So I can buy something on chat GBT or Gemini or um or Microsoft.
3:07:27
>> You could only do like a single item at that time.
3:07:29
It couldn't really >> but there's no concept of loyalty or subscription or bundling or you know if it's furniture for example, please don't ship it to me on Thursday. I'm not home Thursday. Send it Friday.
3:07:38
So this idea of creating this universal protocol that we we we co-developed with Google means that uh now merchants can actually tell these agents exactly how to show their products on these on these agentic tools and and it should be as good as it is on the online store.
3:07:53
Uh so that's a that's that was a really really big one.
3:07:55
The second thing we announced uh also with Google is that now we're actually expanding you can sell everywhere commerce is happening from an agentic perspective.
3:08:02
So, we're going beyond the agentic storefronts of just chat GBT, which is what we said, you know, in Q3.
3:08:09
Now, it's also we're going to be working with Gemini with um with AI um with AI mode in Google search and also with C-Pilot.
3:08:16
And maybe the last one, which I wouldn't bring up on any other show than TVPN, is that uh we're actually bringing aentic commerce to every brand whether or not they're on Shopify.
3:08:24
So, if you're not on Shopify, but you want to have your product syndicated and and index, you can do so with our aentic plan.
3:08:32
And uh that seems to be the talk of the show, which is amazing. >> Very interesting. Right. Right.
3:08:37
Cuz that's that's uh >> nice ecosystem. I like that. >> I like it. I like it.
3:08:42
>> I mean, if you're if you're going to I I I think if if Aentic is going to do what a lot of us think it's going to do from a commerce perspective, you have to give consumers all the brands.
3:08:50
We obviously want them all on Shopify, but there's some brands that want to participate now, but it may take some time for them to migrate over.
3:08:56
So, this idea of opening up to anyone, we think is a big opportunity. >> Very cool.
3:09:00
Uh, walk me through the the the customer experience journey that might shift over this year.
3:09:05
We were following the Aenta Commerce thing so closely that we were, you know, we were chat cheering for ads and chatbt back in, you know, June, uh, when they were kind of like, maybe we'll do it.
3:09:17
Uh we were hoping that Black Friday would be the day that people were purchasing things in LLMs. Didn't quite happen yet.
3:09:25
It's still in the experimental mode.
3:09:25
I was using the uh shopping feature in ChachiPT to do shopping research.
3:09:32
>> We want we want fast takeoff.
3:09:34
>> But yeah, but I'm wondering like like the early adopters, is this going to be a more techy community that's buying their next TV in an LLM?
3:09:42
Do you think it'll jump straight to the the the skims uh and the you know the TOAS category first?
3:09:53
Like how do you see >> Oh, look at you with all your direct to consumer brands. Way to go. >> I got it. >> Uh a couple things.
3:09:58
I I think um I think it'll likely be something that like most people use some of the time and some people use most of the time.
3:10:05
I don't think it's going to cross the threshold of most most the way e-commerce does now.
3:10:11
Um I think >> it's going to take some time.
3:10:13
I do think though that you know this is these are all very very small numbers but if you look at the velocity I was asked um back as I was coming on stage uh today to do the keynote uh the uh the keynote after me was the CEO of PepsiCo and he said you know last year you talked about I asked you if if um uh if Aentic was overhyped and you said it's underhyped and I and he said well you know and I he said do you still believe it?
3:10:33
I said, "Well, if you actually look January 2025, the last NRF to this NRF, we've actually seen a 14x increase in orders to Shopify stores coming from some sort of agent."
3:10:45
Now, that doesn't mean the transaction >> off the link >> wherever it was.
3:10:48
They may be going to the online store, but 14x is is dramatic.
3:10:52
And again, it's on a very small base.
3:10:53
We processed 90 billion, you know, last quarter.
3:10:55
So, it's a small base still, but I think it's going to ramp up quickly.
3:10:58
What I think is really cool is I think you're going to see companies that are going to actually have these drops.
3:11:03
I think once you start seeing these excl like for example um last night I did an NRF event with Tom Sachs who is the designer behind the Marsard 3 shoes which I think is the coolest sneaker in the world. He runs Nike Craft.
3:11:19
>> Imagine he actually dropped something directly on one of the Agentic applications.
3:11:24
Now you obviously have people that go there specifically for it.
3:11:27
you now may decide, okay, that experience is pretty good.
3:11:29
I'm now going to book my entire ski trip, uh, everything I need for my ski trip directly in the application.
3:11:34
So once you have a good experience, I think the actual friction reduces.
3:11:38
You'll keep having it over and over again.
3:11:40
But the thing that we felt was missing and this is the reason why I think this UCP protocol is so important is it was very difficult to do merchandising inside of these applications and this protocol allows you to do a lot more of that.
3:11:53
allows you to do a lot more of that. can say like back to cat and AG1 it's obvious that anyone who knows studies the company subscriptions play a huge role in the AG1 business model well you you know up until UCP happened you couldn't actually do subscriptions now you can or this idea of bundling you know for Gym Shark it's a huge part of their business is if you buy these
3:12:14
you'll also buy these as well you can do that as well so I think all of these things are sort of in line with creating a much more delightful experience in the chat and and I think ultimately what it leads to is like this will be merit-based shopping which will be different than I think some of the traditional retailers who were kind of leaning on their balance sheets to spend money on ads. You can't really game the
3:12:32
You can't really game the system in this in in that way.
3:12:34
You actually have to be from a context perspective the right product for the right consumer.
3:12:41
>> How do you think uh creative assets will change or maybe stay the same?
3:12:45
I've noticed that a lot of LLMs when you pull a link, it'll actually hydrate that link with an image of the product that you're looking at.
3:12:54
Uh I imagine that a lot of people were previously thinking, well, everything's going to collapse down to text.
3:12:59
I just need the facts and the data.
3:13:01
Uh but now maybe the creative, the photography, the videos that actually just gets pulled into the chat apps that folks are using and it stays important.
3:13:11
How are you thinking about that evolving?
3:13:12
I think you're probably you're not going to I mean the idea of SEO won't exist in agentic because again it's merit based and it's mostly based on the context history you've had.
3:13:18
But I do think though you're going to have these brands are going to have people at their companies who are thinking a lot about like consistent updates to UCP, consistent updates to the catalog.
3:13:27
So they may pull something off the catalog and say we don't want to sell it anymore this way.
3:13:31
this way. Um, so I think there's going to be I don't know if they're going to be actual jobs, but there's going to be people inside of the company potentially in the in the merchandising department, um, who say actually the way that we
3:13:42
want to sell this, the way we want to describe this to these agents is a particular way and then because of UCP and because of Shopify catalog, it gets easily disseminated across every single one of these agentic applications. So
3:13:52
So the experience just gets better and better.
3:13:54
I think you have to be a little bit of a of a techno optimist.
3:13:56
You guys obviously are are certainly there as I am to believe that even if the experience is not incredible right now, it's likely just going to get better at this ridiculous pace. >> Yeah.
3:14:07
Are the folks that you talk about uh the brands that you talk to, the leaders of those brands excited about um ads coming to uh chat surfaces?
3:14:13
It feels like new unexplored territory.
3:14:17
Whenever there's a new ad product, that's opportunity for fastmoving brands.
3:14:22
But uh what are they worried about?
3:14:24
What are they excited about? But what's the mood?
3:14:28
>> Most of the most of the excitement is actually around this idea of like is there a potential for this to level the playing field?
3:14:32
Meaning, you know, if I've done a bunch of research historically on on the on aentic application, >> yeah, >> about James Purse or about, you know, Tom Sachs or about the stuff that I love, the brands that I love, and then I'm going on a hiking trip, it probably should not show me a generic pair of boots.
3:14:49
it should probably show me on running because it knows to some extent that I actually favor direct to consumer brands or more modern retail brands as well.
3:14:56
So the excitement actually is around like is this going to introduce more brands that otherwise are unknown to more people or you know uh True Classic T for example which you know if you're looking for a black t-shirt I suspect on a search engine you're not going to see True Classic T come up that much but it's an incredible product and and ultimately it can be found on these agentic tools in a way that it probably couldn't historically.
3:15:16
That seems to be a lot of the excitement.
3:15:18
The other excitement is e-commerce as a percentage of total retail is still sub 20%.
3:15:22
You've heard that literally you hear that at the show all the time that people are like well you know we're inside the Shopify booth now and people that are more traditional say well where when's this going to eclipse 25%.
3:15:32
There is a chance there is a school of thought that says that one of the things that Agentic might do is increase that penetration rate at a faster clip kind of alla you know co did because people that may not be big e-commerce consumers may be searching for recipes on chat GBT and through that process may end up actually starting to buy stuff there as well.
3:15:54
So the other the other thing is like I think some of the time you go to a retail store you're going because you want to have a conversation about the product in a way that you just don't get with a website.
3:16:06
A website is like a beautiful catalog and if you go around in the right order and you look at the FAQ and maybe you talk with support and all the and hopefully they respond quickly and actually give you the insight like then you can get to the purchase decision.
3:16:19
But so a lot of people will just be like I'll just drive by the store and get it.
3:16:22
But I feel like LLMs can provide that uh they can give people understanding on a subject or a category or a specific product that allow that gives them the confidence to make a purchase, right?
3:16:33
And so >> actually I'll go one step further.
3:16:35
I think it's actually a better version of that because it's an unbiased discussion, an unbiased conversation.
3:16:39
I mean the bias is based on your context history and based on merit as opposed to being based on, you know, what spiff is that particular salesperson getting today in a commission structure. So yeah, it does.
3:16:50
yeah, it does. I mean, you know, it's so cheesy of course, but like when I describe it to like my mother where this is going, I explain that this may very well be the greatest personal shopper in the history of retail who knows
3:17:01
everything about you, knows your sizes, know in certain, you know, in in European fashion, you that's this size, but Americans, it's like that knows where you're located, knows where you travel to, and can provide this unbiased objective recommendation. Uh and then
3:17:12
Uh and then once you build in these applica you build in checkout which we're doing with with our Aentic um storefronts right into the chat it becomes this really delightful experience. >> Yeah.
3:17:25
>> Well congrat uh yeah the most uh transformative year for the way online commerce happens.
3:17:32
>> How can we how can we follow the numbers here?
3:17:36
I can keep I can I can keep coming and telling you the numbers.
3:17:38
telling you the numbers. I will tell you that I did say on stage of 5,000 people about an hour ago that I do think like this is the gold this is a golden age uh of retail and and I think you're going to see brands there are brands right now that none of us have heard of that in 6 months from now we be like I can't believe we didn't know that brand
3:17:53
existed and I think that type of velocity you know there there's going to be so many more of these skims and Gym Sharks and Alo Yoga and Vioris and Tovis and AG1s and favorite like you know we know these brands because we kind of live in this world it's what we're interested in um but for the most part most readily through the evolution and we shop wants to power the whole thing. >> Yeah. It's going to be so fascinating >> Yeah.
3:18:16
It's going to be so fascinating following this ramp relative to mobile in previous booms or or >> That's right.
3:18:23
Or or actually social commerce be another one because there was some there was uncertainty around it and then ultimately actually social is a wonderful >> there were a lot of experiments where oh you'll be able to shop under YouTube videos or under Facebook marketplace concurrently as well.
3:18:35
It turned out it was a great place. >> Yeah. Exactly. >> That's right.
3:18:38
It was a great place for discovery, but the transaction still took on the online store.
3:18:40
This is different because a transaction happens embedded. >> Yeah. Yeah. Yeah.
3:18:45
It's going to be fascinating to follow.
3:18:46
I think I think we're in for a fast takeoff.
3:18:48
It's going to be a good year.
3:18:50
>> Uh a great time to be in business and a great time to be at Shopify.
3:18:52
So, congratulations on all the success. >> Thank you very much. You guys are impressed.
3:18:55
Thank you for having me on.
3:18:55
I like broadcast from wherever. >> Fantastic. >> Amazing.
3:19:00
Going to be a massive year.
3:19:01
>> Have a great rest of your week. We'll talk to you soon. >> Goodbye.
3:19:04
Uh, and you know their other partner, we got to tell you about Gemini 3 Pro.
3:19:10
Google is powering all of that.
3:19:10
It's Google's most intelligent model yet. Gemini 3 Pro.
3:19:13
State-of-the-art reasoning, next level vibe coding, and deep multimodal understanding. You can build there.
3:19:20
>> We talked about this last week.
3:19:22
California state reservoir levels are now at 130% of normal, holding 7 trillion gallons of water. It's remarkable.
3:19:29
Ally Bell says, "God wants us to feed Claude in every model, every data center.
3:19:35
There's plenty of water to go around."
3:19:38
>> And Ashley had the same idea.
3:19:38
Ashley Van says, "God is rewarding us for building AI.
3:19:42
All the water, all the water people are super happy."
3:19:45
Uh Tyler, you have some breaking news. >> Uh yeah. So, okay.
3:19:48
So, earlier on the show, um I was reading into the Jack Clark blog.
3:19:51
I was like, "Oh, maybe Jack Clark is is pointing to something that data anthropics can build space data centers." I posted that.
3:19:57
He responded, >> put me in the truth zone.
3:19:59
He said, "No, you should not be reading into this or any anthropic grand strategy."
3:20:03
And he um he totally ratioed me. >> Oh wow. He got destroyed. >> But wow. >> Brutal mogging. >> Brutal mogging. >> Oh wow. >> So no. Yeah.
3:20:14
No anthropic data centers in space.
3:20:17
>> Well, I mean you It's funny.
3:20:17
I was we were talking to Andrew from Cerebrus and uh I was kind of giving him the layup.
3:20:23
like I'd heard from other people that uh like that that Cerus would be a unique beneficiary of space data centers if it happens and he was like nah it's not really [laughter] on my road map in the next 35 years.
3:20:33
Um but we we will see you know everything could be pulled forward if there's you know new uh new new advances there space uh you know payload to orbit comes way down there's a bunch of ways that that could be exciting but >> raised additional capital at a $1.
3:20:48
6 6 billion valuation their series C2. This was wonderful team. Love to see it.
3:20:55
They got Tro Price Alimter D1 >> Stepstone.
3:21:03
>> We got to get >> 1789 Founders Fund Lux Capital A16Z 137 >> Delian Company.
3:21:09
>> All >> the absolute uh boys. >> Yeah. Back in.
3:21:14
>> What a run from Chris Power. >> Uh what else we got?
3:21:17
Uh this post here from horse hater.
3:21:21
>> Horse hater >> went very viral yesterday.
3:21:22
I didn't uh I didn't like this post.
3:21:25
The whole post is horses. Don't like them. >> Boom. We love horses here.
3:21:32
>> Horse hater was asked why.
3:21:32
And horse hater replies they are evil creatures.
3:21:35
I don't know that there I I know that there is only malice in their hearts. >> Completely false. >> Fake news.
3:21:43
>> Just exposing yourself.
3:21:47
We should community note this.
3:21:48
>> I I'm going to write a community note right now.
3:21:50
I'm going to get kicked out of the program if I do this.
3:21:53
>> Horse hater hates horses. Huge surprise.
3:21:55
Alexis >> says uh is sharing an article.
3:21:57
Luxury watch prices hit a two-year high in the secondary market.
3:22:02
Partially due to and maybe almost fully due to tariffs. >> Oh yeah.
3:22:08
Tariffs were big part of the story.
3:22:10
>> So if you like spending more money on watches, >> the show is probably doing a lot.
3:22:13
If you like spending more money on watches, you'll love tariffs. >> Yes.
3:22:18
>> Um, but Alexa says, "A great anti- AI bet I've been making is in human craftsmanship. Human excellence.
3:22:24
Collectibles will keep thriving."
3:22:24
So, if you needed if you if you needed a reason to buy another watch, this is it. >> This is it.
3:22:30
But it's interesting because he say he frames it as an anti- aai bet.
3:22:34
It's sort of an anti-AII bet in that it's not a beneficiary of AI, but it's still it's it's a very AGI pill bet in the sense that in in a moment when AGI AI is accelerating, maybe humans craftsmanship is more valuable than ever and that the it's sort of an anti-slop, but it's it's it's still aligned with a with a bullish view on AI broadly.
3:22:55
So, he's not saying I'm I'm not I I don't think AI is going to work, so I'm buying watches.
3:23:03
He's saying AI will work and so I'm buying watches which I think >> yeah I mean humanoids are going to have to be stunting.
3:23:08
>> They will they will need some something on the wrist of your humanoid and why not an FPJ or a PC Philippe. >> Yeah. So, so it's interesting.
3:23:15
Uh, uh, watches, Evelyn goods, right, more desirable as they get more expensive.
3:23:22
That means that if a robot can make a Swiss watch, like right now Rolex might cost $2,000 to make, right?
3:23:27
Some parts are >> automated, some is uh, you know, handcrafted, and suddenly Rolex can uh, make the watch for, you know, 50 bucks just due to automation. It does. They don't automatic.
3:23:43
They're not automatically going to say like, "Okay, let's bring the prices down, right?"
3:23:47
Because the price is part of the product.
3:23:48
So, I do think it's a I do think >> there is a little bit of a potential scoop here.
3:23:52
Bobby Good Latte uh replies to Alexis O'hane here and says, "Yep, I love that both Zuck, we all knew Zuck is into watches and Sam Alman are both into watches.
3:24:03
Shows that they still value handcrafted objects.
3:24:06
I didn't know that Sam Alman was into watches. It makes sense. He's into cars. We know that.
3:24:10
But He likes he likes to double.
3:24:12
Does he do like a Jacob and Co on each? [laughter] >> I haven't. I know.
3:24:17
I I truthfully I've not seen a photo of Sam with a hitter on the wrist.
3:24:22
I've seen him in the Koig.
3:24:24
I've seen him in the McLaren F1.
3:24:24
Uh I know that there's a car collection there, but I haven't seen anything hit the timeline of a wrist check, but maybe 2026 is the year of the Sam Alman risk check.
3:24:35
Uh I'm sure his PR team would love that going out on the internet.
3:24:37
Uh, but I would support it and I will fight for you.
3:24:41
I will be your strongest soldier, Sam, if you want to drop uh a little little photo on the Instagram of the of whatever's on your wrist. Anyway, fantastic show. >> Great show, folks. Great show, folks.
3:24:54
Uh, thank you for hanging out with us today.
3:24:56
>> Well, there's one last scoop that we should that we should talk about is uh from Kylie Robinson over at uh Core Memory with Ashley Vance. She got another scoop.
3:25:04
>> Uh, no, this was just from the weekend.
3:25:06
We didn't talk about this, but uh XAI staff has been using Anthropic's models internally through Cursor until Anthropic cut off the startup's access.
3:25:14
This week, everyone's using uh Anthropic apparently.
3:25:16
So, uh this went viral, got 7,000 likes.
3:25:18
Uh and uh >> yeah, I think at this point, if you are a lab and you haven't had your access to anthropic cut off, polish up your resume [laughter] >> because clearly they're just going to do this to any company that that is a meaningful threat. >> Yeah.
3:25:34
There's another dynamic where you can be using the model because you think it's good, but you can also be trying to distill the model because if there's good data that can be pulled out, you you might just say, "Okay, we want this capability that's uniquely available at this model endpoint. So, let's grab that."
3:25:49
There's a whole bunch of reasons why this could be happening, but it is dramatic.
3:25:52
Tyler, >> yeah, I was just going to say that was like the original deep deepsee controversy people thought they were distilling from uh CHBT. >> Yeah, GBT.
3:26:00
>> Uh before we go, I got to give a shout out to Cooper in the chat.
3:26:01
Every single day when the market closes, he comes in and he says, "Time to like the stream." >> I love it. Thank you so much. >> It's a movement. It's a movement.
3:26:12
>> Thank you everyone for watching.
3:26:12
Thank you for leaving us five stars on Apple Podcast and Spotify.
3:26:17
>> Thank you for subscribing to our newsletter, tvpn. com.
3:26:18
We will see you tomorrow. Goodbye. >> Just one more sleep. >> Goodbye.