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6:55
Today is Wednesday, August 6th, 2025.
6:55
We are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
7:00
Jordy, how are you doing?
7:02
Have you been sleeping okay?
7:03
You were up late partying, hanging out with some of the greatest the greatest capital allocators of generation.
7:08
We won't say who you were hanging out with, but give me give me the redacted read.
7:13
How did it update your AGI timelines?
7:16
How did it update your your world view hanging out with uh some of the some of the most powerful people in Silicon Valley last night?
7:26
>> I I don't really know what I can say on this front.
7:29
Uh I feel like it was all >> Well, did it make you more optimistic?
7:33
Did it make you more pessimistic?
7:33
Did it make you feel like they're top like is this a top? Is this a local bottom?
7:36
Are do we have a long way to go?
7:38
Is there more are you more excited about technology?
7:41
Are you more excited about capitalism?
7:43
>> I left extremely bullish. >> Okay. >> On enterprise SAS.
7:47
>> That's fantastic to hear.
7:48
>> Even in the age of AGI. >> Okay.
7:54
>> Uh I also uh listened to a friend of mine say that he wanted to drink the blood of his of his enemy.
8:04
>> Wild guess who that is. >> I wonder who that is.
8:05
Uh but anyways, it was very it was very inspirational and uh I think everybody should have a friend that gets so fired up about winning in their market >> that uh that they have this sort of blood lust. >> Yes.
8:19
Well, you know who's fired up about winning in their market? Eric Limon at RAMP. Go to ramp. com. Time is money save both.
8:25
Easy use corporate cards, bill payments, accounting, and a whole lot more all in one place.
8:27
I wanted to highlight this post from Nikita Beer who said, "Getting the algo just right."
8:31
and he shares a beautiful photo um of the vibe aligner himself uh the tetetrogrammaton host.
8:40
>> All these AI researchers talking about fine-tuning.
8:44
>> Yes, >> we care about fine-tuning the uh the X algorithm.
8:48
>> I think people I think people haven't noticed how good it's been because you only notice when it's bad.
8:52
I feel like the Xalgo has been incredible lately.
8:56
>> What have you been thinking?
8:56
Have you been >> I think it's good.
8:58
I think it's good, but we >> Oh, Tyler's got Tyler's got something to say.
9:02
Wait, we >> Okay, Jordy and then we'll go to Tyler.
9:06
>> So, for us, we constantly are sending our favorite post to each other and so we're just like manually training.
9:12
>> Crazy reward signal >> to to to show us more of what we like. It's very good at that.
9:17
>> I've noticed that like I really like retweeting stuff.
9:19
If I just see if I see any post I like, I'll like it.
9:21
But if I see any post that I think, "Oh, that's my friend."
9:26
and they're just trying to like mention something, even if I don't think it's the most incredible, hilarious post, I'll repost it just to amplify it because just because I'm like, "Yeah, yeah, show some love."
9:34
Uh, so I've been more liberal with the like button, more liberal with the retweet button or the repost button.
9:40
And I think that's also amplified uh the ALGO.
9:41
So, I feel like my ALGO is dialed.
9:45
But Tyler, what do you think?
9:47
>> I feel like I'm getting like massive amounts of Normandy slop, >> dude.
9:51
>> Are you engaging with Normandy? No.
9:51
I I I always want to not >> not beating the allegations.
9:56
You know that these algorithms are reflections of yourself.
9:59
You just you just told on yourself.
10:00
Nor me what what what is an example of a normie post?
10:08
Like are we talking thread boy stuff? >> Thread boy.
10:11
Are we talking like thread boy tier?
10:12
Like here's how to start your first company or like here's the >> No. No.
10:16
Like just like not anything that has to do with technology or business. >> I never engage.
10:20
It's like about like some like dating thing or >> Well, I I swear I don't engage.
10:24
I always I I negatively engage. I say not interested.
10:29
>> You say not interested.
10:29
>> I I mute this account. Okay.
10:31
>> And they just feed me more and more stuff.
10:32
Feed >> you more and more.
10:33
>> It's just cuz it'll be like 100,000 likes on some random >> tweet.
10:36
It's like I am getting I am getting some of that.
10:38
I I I try to not give it any of my attention.
10:40
So, I try to move past quickly.
10:42
I don't want the algorithm to I don't want to send the signal that uh I want more of it, but it's tough. >> Yeah. Well, I don't know.
10:48
Maybe it's a skill issue.
10:51
Maybe it's just Nikita Beer working his magic in the ALGO.
10:54
But, uh, thank you for your service, Nikita.
10:56
We know it's a hard fight getting the ALGO just right.
11:00
And I think, uh, I I personally think you've been doing a great job. So, thank you.
11:03
And you know who else has been doing a great job?
11:07
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11:09
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11:11
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11:15
>> Show wouldn't be possible without that.
11:16
It truly would not be possible without without it.
11:18
We talked about Genie3 yesterday.
11:20
I wanted to noodle on it more.
11:22
Um, so Genie3, if you're not familiar, is a new frontier world model from Google and we played around it with a little a little bit yesterday. We saw some demo videos.
11:32
We We don't have access, right, Tyler? >> No.
11:35
Like no one has access like engineers. >> Yeah.
11:38
So this is at what like this is bard tier software.
11:40
We never got access to Bard >> and then Gemini was the consumer application and then there was Palm too.
11:48
>> Palm was their big multi-billion parameter large language model that Google did not release to the public but they started writing papers about and even the transformer paper that was just an architecture.
11:58
There was no product associated with it.
11:59
It wasn't until uh what February or March of 2023 that Google came out with their first consumer chatbot for public consumption. Correct. >> Yeah.
12:12
I think it's mainly there's probably a bunch of like safety stuff they got to figure out.
12:14
Especially Google, they're pretty safe about that kind of stuff.
12:17
>> That's a good that's a good point.
12:19
That's what I want to debate today.
12:19
So, interestingly, Google creates the transformer. They create Palm. They create Bard.
12:25
They have all of these incredible AI researchers.
12:27
Deep mind's fantastic research lab.
12:31
They they they're scaling up large language models, transformer-based large language models.
12:37
they are on the correct path in the tech tree and yet they don't release the consumer product fast enough.
12:42
Chat GPT releases in I believe November may I think it was I think it was November 30th of 2022 maybe December 1st.
12:49
So you can think about it at the beginning of December 2022.
12:56
Google takes three months to respond.
12:58
they respond with a product that's pretty close and yet consumer adoption is power law distributed and chat GPD has been the runaway success in consumer and so the lesson there is you got to be first if you have the technology you got to get it out in the public even if it's
13:17
messy and I mean maybe this is apocryphal maybe this is like the wrong way to frame it but like there is a there is a story out there that people are telling in the media in books that basically says Sam Alman got fired because he launched ChachiBT, >> right? They say the board, he didn't go
13:32
They say the board, he didn't go to the board.
13:36
>> He didn't go to the board and say, "Hey, we I want to launch chatbt."
13:38
He didn't tell the board he was launching consumer SAS product. >> Yeah.
13:43
I want to make the next consumer internet company.
13:46
>> I want to make something that makes a tr a billion dollars a month. Is that okay, guys?
13:49
>> I want to launch an app.
13:50
>> I want to launch an app. Is that okay? Is that okay?
13:52
That's basically that's basically what they So, yeah.
13:53
not not a fan of the board here.
13:56
Um, but the the the interesting point is that is that that move fast break things mentality like when chatbt launched people forget how bad the first version was because I mean it was amazing.
14:11
It passed the touring test but it was built on chatbt or it was built on GPT 3.
14:14
5 002 Da Vinci right and so the the model was hallucinating constantly.
14:21
it would it had no access to tools.
14:23
It had this crazy knowledge cut off so you couldn't ask it anything about the last six months or the or what's going on today.
14:32
It was it was like pretty useless.
14:32
It was magical and it was useful for some things, but for like 99% of prompts that we hit chat GPT with today, they would completely flop on the v1 of chatpt. >> Yeah. Yeah.
14:45
And I remember when it launched, there had been a bunch of companies that had been building on GPT doing like text generation for different use cases.
14:52
There were a number of companies that were generating text for marketing assets or emails or things like that or essays.
14:59
>> And those companies had >> absolutely ripped.
15:01
They had insane revenue ramps.
15:03
And when Chat GBT launched, there were still some people that thought, oh, you're still going to be able to build a business here around just like generating generating text for like niche use cases.
15:11
And then like a month or two in it was very clear that like all those companies had gone ramped and then like basically you know right back to where they started. Totally.
15:20
I mean, I I talked to a YouTuber at the time, someone with like I think many millions of followers in the uh in the true crime horror genre, and his whole his whole channel was like designed around finding an interesting uh case or, you know, uh crime and then telling the story >> an interesting crime. >> Yeah.
15:44
I mean, it's a true crime podcast.
15:46
We saw odd lots like true crime podcasts are the number one and the number two biggest podcast in the world right now above Joe Rogan at least in the charts.
15:52
Uh and so the like true crime it's all about storytelling.
15:56
It's all about just writing getting the facts together assembling them into a script that makes sense on YouTube.
16:02
This guy he's not he's not like the the most insane writer.
16:07
He's just like somebody who figured out how to write for YouTube and do the video production and he has a good voice for it.
16:13
He's a great voice for it actually.
16:15
Uh, and he has good lighting and he does all this all this great stuff to make the stuff work really well.
16:20
He's good with thumbnails and and and titles.
16:21
And so he'd grown to the point where he could just put up a million view video like every day.
16:24
Um, and he was like, I'm going to use Chachi PT to write all my scripts.
16:28
And he did that for like a week and then he just completely quit doing YouTube videos entirely and switched to a switched to an interview show.
16:39
>> This is the guy who interviewed Andrew Tate.
16:40
He interviewed a bunch of people, but there's one there's a couple like super viral like clips of like uh hustleneurs that he's the other guy interviewing them.
16:49
He's the reason that he that like this clip exists on the internet. He's a really nice guy.
16:53
But um uh it was just funny because he went like so hard into this and the product wasn't there yet and now maybe it is but still people people still can tell the flavor of of text written from GPT 4.
17:06
5 even uh and but >> at the same time the actual use case was information retrieval transformation of information translation all the things that we use chatt for for 30 minutes a day I'm not telling it write me a novel.
17:25
I want to read a great novel.
17:25
But I am saying, you know, give me pull all this data from the internet and from all your resources and put it together in a table. Teach me this thing.
17:33
It it it's super helpful for knowledge retrieval.
17:36
And when you look at Fiji Simo's five things that chatt is going to focus on, like writing new books was not one of them.
17:43
And I think that's by design because that's not where the models excess excel.
17:47
We're in this age of spiky intelligence.
17:49
And so you want to do you want to let the models cook on what they're good at.
17:54
And they're good at knowledge retrieval.
17:55
And they're good at, hey, my knee hurts. Here's some symptoms. Let's go look up.
17:58
It's another knowledge retrieval task.
18:00
And they're also good at just chatting back and forth, having a conversation.
18:03
And that's a therapy angle. >> Yeah.
18:06
>> But my question is, Genie 3, Google is clearly at the very front of this from a research perspective.
18:14
>> Y >> and so it's super high fidelity. It looks HD.
18:17
It's rendering at 20 to 24 frames per second. You can prompt it. It seems super fun.
18:22
There's this world memory.
18:24
They've clearly gotten a number of fundamental improvements like you know you you you watch what has happened in the LLM world with adding reinforcement learning, adding memory, adding tool use and uh and a web browser and a Python ripple and a bunch of other tools that have made it great.
18:40
Clearly in this Genie 3 model there's a bunch of those tools like you know they figured out how to do memory.
18:46
It's probably not just one simple algorithm.
18:49
It's a bunch of things working together.
18:51
They're they're crushing it.
18:52
Deep Mind is doing what they do best.
18:54
They've done the research and they've created something awesome.
18:57
>> The question is, >> what are they going to do with it?
19:00
>> They can't get in the chatbt world again.
19:02
They can't let another lab do the same research and then productize it first and then be playing catch-up.
19:07
>> So, three months is is enough to lose the race in the chat world. >> Yeah.
19:12
Yeah, I think one one question I have is this the kind of tool that's that's sort of like a Google Earth that I remember as a kid discovering Google Earth and realizing that you could just explore the real world from your computer and it was this like magical experience and I definitely spent a bunch of time just like going around boopping around different places being like I'm going to drop into this continent.
19:31
I'm going to drop into this city and that was really cool.
19:32
I think the question with Genie 3 is like is this something that people are just going to be generating themselves generating worlds?
19:40
Is this the kind of thing that video games uh will adapt and build on top of?
19:45
Is it more of a developer focused product? Um unclear so far.
19:50
We should probably have Logan on the show to break it down because >> uh I think there's a lot of people uh game developers specifically that would look at this and realize just the incredible potential of this if you can you can uh integrate some type of game engine into this and and rules.
20:06
>> Um >> are doing you imagine?
20:08
I mean, it's an interesting thing.
20:10
Uh, when you think of like first person shooter games, when I think of my memories playing those games, there's like a few key maps and a few key games that were just like iconic and like people loved playing in those maps.
20:23
And I think the interesting thing is when you have infinite optionality, you can imagine a world in the future where Call of Duty lets you just prompt battlefields, prompt, you know, different uh kind of arenas settings for for different gameplay.
20:37
But it'll be interesting if people still gravitate towards certain maps just because it's fun to have consistency with certain games. >> Completely agree.
20:46
There will definitely be a power law and the only way to actually um realize that power law and find out what's at the long tail of that power law is to get it in the hands of millions of people. Yeah.
20:57
And that's the same thing that happened with ChatBT.
20:59
Uh and so um >> beautiful website by the way.
21:03
I wonder if they designed it in Figma.
21:05
Think build bigger build faster.
21:06
Figma helps design and development teams build great products together, get started for free.
21:11
So my my point is is that I I agree with everything you're saying.
21:15
Is this going to be just like this meditative hangout space?
21:20
space? Will it be something that people put on in the background and then they're studying or will they be, you know, maybe people will be using this as a development tool to then go and hardcode a new video game or they'll use as an exploration canvas in the same way
21:34
that people use, you know, a lot of people use generative imagery as uh I was listening to a a talk about this where someone was like like if you're an artist, you probably can't just just turn in a fin turn in a prompt as your final work, but you're going to be on Behance and you're going to be on
21:56
there's a bunch of these services that like yeah you're going to be on but before you would like scroll Instagram for references and you would put that into a mood board and you'd be like okay this is the brand that we're going for now we're going to create our own and
22:09
it's not going to be derivative of any one thing like if you look at like >> I don't know if we I don't know if we ever actually did a mood board for TVPN but you could imagine there's like you know there's the there's the hardwood aesthetic the mahogany, the official wood of business. Then there's some
22:21
Then there's some racing livery.
22:22
There's the green that you really liked that you were like, "Let's do green." And that was great.
22:28
And then there's, you know, a little bit of sci-fi.
22:29
There's a gong for some reason.
22:31
You mix all these up and all of a sudden it's not just we're not just doing a racing team stick.
22:35
It's like racing team plus gong plus hardwood plus all these different things, suits.
22:41
And you add all that up and you get something new.
22:43
And people used to do that just by pulling imagery on on Pinterest and Instagram and Behance.
22:47
Um, and Arena was one of them, I think.
22:50
Uh, and and now people use generative art to do that.
22:56
And you could see that happening there.
22:57
But the main thing is that like there's zero chance that we figure that out in the lab.
23:01
I think you can only figure it out by actually getting it in the consumer's hands. Yeah.
23:07
And being very responsive to it.
23:08
But yes, there are safety concerns, but this is a game where the the the the most risktaking person, the most founder mode company wins.
23:16
And that's exactly what happened.
23:20
Two use case for Genie that I'm that I'm interested uh like I would be interested in playing around with.
23:24
One is like a voice prompting functionality where you can just be sitting with the screen and just be live prompting >> like no hands on the keyboard.
23:33
>> No hands on the keyboard.
23:33
you're sitting there and you're saying a dolphin just skateboarded by and a dolphin is going to skateboard by, right?
23:39
Then you're like, "Oh, it's like and there's a LaFerrari uh that has wings and it's like taking off into the sky, right?"
23:47
So, you're just like giving people the ability to like have this almost like lucid dream effectively. Yep.
23:54
>> Um >> and then uh what was the other thing I was thinking? >> Blanking.
23:59
Tyler, did did you have a thought?
24:01
Yeah, I mean I think obviously it's like super cool as a consumer use case.
24:05
Like I want to play with it, but I mean >> I think you could definitely make the case that the main value of this is it being used as training data for like robotics.
24:13
Like if you train a humanoid robot off this, >> that's like everyone says like the main issue like why don't we have humanoids yet?
24:20
Because it's a data problem.
24:20
We don't have like insane videos of first person like doing every single task, right?
24:26
I wonder I Yeah, I I don't know enough about it, but you'd think that you'd be able to generate uh endless procedural worlds with uh just traditional game development pipelines.
24:40
Unreal Engine, Houdini, you can define, you know, endless corridors.
24:45
Like there's that game No Man's Sky. Have you heard of that?
24:47
It's like every single planet you go to is procedurally generated.
24:50
There's an unlimited canvas.
24:52
Um, and so you'd think you would be able to walk around with that and then just do some style transfer on top of it to get to something that is trainable, but maybe this is better. I don't know.
24:59
We need to talk to some some robotics people to see if this is actually like a >> Yeah, we talked to we talked we we talked with the team from physical intelligence and they said they have effectively they're like generating a bunch of live real world data.
25:13
The question is how valuable is this >> in Whimo, Tesla and Cruz all had very serious simulation teams that were developing.
25:22
They would they would go and map the world, take all the pictures, reconstitute that into essentially a video game and then the cars could virtually drive around.
25:30
And then they they did have the trouble of like they kind of needed hallucinations because the first time that like it wasn't just like a dog running out and co and thing but like what what happens how much train data is there on like a cow going in the middle of the road like that happens like one in a 100red billion vehicle miles traveled.
25:51
So you could have like pabytes of data of cars mapping the road and maybe the big Tesla data set has like one image of it and so you can train on it.
26:02
Um but in a simulation you're going to get a lot more crazy hallucinations and then that might be valuable.
26:07
I guess my point Tyler is that like you're describing like the B2B use case and and I think that there might be a a consumer use case.
26:18
>> Here's a consumer use case >> and the consumer use case will be more monopolistic.
26:20
So, so yes, like OpenAI and Anthropic are duking it out in B2B, right?
26:25
And and it looks like that will be a lot less a lot less winner take all than chat like consumer chat like the the the interface the the new consumer company with all the aggregation that Chat GPT has is going to be incredibly valuable.
26:39
And then all the hyperscalers will have a frontier model that they can sell at, you know, somewhat competitive rates and they'll make a lot of money and they'll do great and it's a big new market.
26:48
So that could that that could happen here.
26:50
Thing is that if they if they if they start selling this to uh robotics training companies, what's stopping someone else from training a similar model and then selling it to another robotics company?
27:02
It becomes more igopolistic I would think. >> Yeah.
27:06
Well, isn't it like okay if you're super AGI pill then >> as you are >> then like consumer doesn't matter as much because they're not doing as like economically valuable things as a like as B2B would, right? M okay.
27:19
>> So in that case then >> B2B is like way more important even if it's not like as monopoly.
27:23
>> No Tyler so much of the economy is raw consumption.
27:28
It's the will of the American here's matter.
27:31
>> So here's the the other use case I was thinking.
27:33
I think it'd be cool if you could upload some images and some video and like recreate a scene that you were in.
27:40
So think about like >> uh uh your oldest like first birthday.
27:45
if you could take like three images >> from from that like you know celebration like cutting the cake or whatever and just like drop it into Genie and just like recreate the scene and be able to just like witness it again >> in in like virtual reality that would be
27:59
an absolutely wild experience and I think a lot of people would would do that when you know you know just reminiscing on >> and that feels entertaining and important whether or not I have a job like if the robots take all the jobs in this ASI future I still want something to do with my time, right? So like why not go hang out
28:16
So like why not go hang out in Genie 3, Tyler?
28:23
>> That that's like pretty black pilling, right? >> Why?
28:25
>> Just like wireheading all the time.
28:25
If everyone lives in the simulation, >> you don't need to be wireheading.
28:28
You can just you can just watch a movie.
28:32
Like is that wireheading?
28:32
You know, you you have more free time.
28:34
You can you can you can watch Dunkerk.
28:36
You Jordy's going to have the best time in the Singularity.
28:41
He's going to be like, I've never seen a single movie. So many movies.
28:45
>> I'm going to be like, I need a generative slop. I've seen everything.
28:48
And Jord's going to be >> I've just been building up an incredible backlog. >> Incredible backlog.
28:52
>> Almost a 30-year backlog.
28:53
>> It's going to be amazing.
28:53
You have you have a decade worth of films to watch and enjoy and discuss.
28:56
It's going to be a fantastic post singularity uh life for Jordy.
29:01
Well, until we hit the Singularity, you're going to need to stay compliant.
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29:17
So speaking of robotics, Tyler, I want to talk about the the five levels of robotic autonomy from semi analysis.
29:27
This article dropped when we were in New York last week.
29:30
We didn't get a chance to cover it, but I thought it was pretty interesting because just like with autonomous cars, they're uh like we had the five levels of autonomous cars, like level zero is basically no autonomy.
29:44
So, your Carrera GT fully full driver engagement, no uh >> what is it?
29:53
Uh >> no traction control.
29:56
>> Is that is that levels level one autonomy? No.
29:57
Uh, level one was like cruise control, basically lane keep assist, the basic stuff.
30:01
Uh, level two was it it does lane centering and adaptive cruise control.
30:06
So, it will it will it'll break if a car is slowing down in front of you. It'll speed up.
30:13
Um, but you have to be very engaged and you have to be prepared to take over at any time.
30:16
Level three is is the car is basically driving itself fully, stops at stoplights, does everything, but it can tell you, hey, you got to get back in the driver's seat.
30:26
And then level four is is the the human doesn't need to be involved at all.
30:31
And level five, I think, like no steering wheel, something along those lines.
30:33
Um, but there was always this question, um, you know, the the humanoid robotics discussion has become really really focused on like level five, the most insane. We're we're AGI pill.
30:46
It's going to be humanoids that can do everything. They can do plumbing. They can move perfectly.
30:50
But clearly there's going to be a roll out here.
30:53
And so semi- analysis did a great job of kind of breaking down like where we are because there's actually a a continuum of robotic capabilities and you'll see some of the those in that image.
31:03
So level zero is scripted motion.
31:06
This is high accuracy, high repeatability.
31:08
Uh but this this unlocks 247 automation and high throughput.
31:11
So this is when you see the car factory with the robotic arm that just moves the windshield, picks it up, puts it on the car, moves the windshield, puts it back like that is perfectly scripted in a computer simulation like like the key framed animation essentially does the same thing every time.
31:29
There are no cameras on that robot whatsoever.
31:30
And so if you are next to it and it decides to go like this, it will hit you and it might kill you.
31:37
So you have to be very careful.
31:39
So there's so there's typically like fencing around these and they have these Have you ever been to Hadrien and seen the the the light curtain?
31:44
Have you seen this thing?
31:47
>> So the light curtain is uh is a bunch of lasers and uh and if you break the beam it will immediately trigger stop everything on the line.
31:56
So it's it just knows >> don't kill the humans. >> Exactly. Exactly.
32:01
But there's no there's no cameras involved.
32:03
There's no machine learning.
32:04
It's purely just a big powerful, you know, arm that is scripted to do exactly what it want what it can.
32:11
But that's extremely useful and we use tons of these and these these robots have been around for, you know, decades at this point and they are definitely out there.
32:18
Uh they're expensive and you need constant oversight and and interestingly even though they do in theory enable 247 automation, uh they often don't run 247 because they need a person ma managing them all all the time.
32:31
And so, uh, like they like there are tons and tons of facilities that actually just straight up shut down the robots when they go to lunch, >> which is kind of crazy, but that's just the nature of these things. They're so precise.
32:43
And then we've talked to other folks about like you got to change out the motors, change out the grease, you got you got to put the oil can in the in the joints basically. >> Yeah.
32:51
And the big, you know, we we've talked to a few people around trying to get a sense for where humanoids will be valuable and people that run factories with traditional robots.
32:59
You know, these sort of the the arms that that you're describing.
33:03
Uh talk about just how often they're having to replace parts and motors.
33:08
And when you have a humanoid, you're like adding you're basically like multiplying the number of motors that need to be functioning properly in order for the robot to be like online and productive.
33:17
And that's just going to be one of the challenges that uh anybody building humanoids is going to have to deal with.
33:23
>> Techno Chief 2000 in the chat says, "Good morning, brothers."
33:24
Good morning, Techno Chief.
33:26
I hope you're on graphite code review for the age of AI.
33:28
Graphite helps teams on GitHub ship higher quality software faster.
33:32
Now, back to the semi analysis >> breakdown.
33:36
>> Level one is intelligent pick and place.
33:39
And this is important because this is also something that we've had.
33:41
So, you put you put motors on a gantry x and y axis and then you put a little grabber.
33:47
It can be anything from like a suction cup to a little like actuator.
33:48
And all of a sudden, if you just say there is the Diet Coke, move this over, pick it up.
33:54
It's like the the claw game, you know, the claw game at the carnival.
33:56
Um, so you put a camera, some object detection, and then you map that.
34:00
And this is like very basic OpenCV, computer vision, very I mean, it's amazing.
34:05
It's miracle, but it's still like it's very doable at this point.
34:10
There's plenty of like open source packages.
34:11
There's a bunch of companies that have done this and it's important to to define this as like this counts as level one autonomy.
34:19
There is machine learning in the process.
34:20
There is computer vision at work and because of that this is a tool that can be used and it has benefits and costs. >> But is it end to end?
34:28
>> It I mean it doesn't matter.
34:28
But but sometimes it can be sometimes it isn't.
34:32
But the I think the more important thing that you're getting to is that there are a lot of people out there who are showing humanoid robotic demos doing things and they're saying, "Hey, we have a level four fully autonomous humanoid robot. It can do anything."
34:44
And they show it doing a level one task.
34:46
And it's like like I I I remember seeing some some demo of a of a humanoid robot just taking parts from one place and putting them to the other side.
34:56
And it's like, well, for that you just need a robotic arm with scripted motion.
35:00
arm with scripted motion. you need level zero autonomy actually like you haven't like you're not demoing it in the way that that would actually necessitate that and so even if you did it and even if you are successful it's a waste of money >> because you'd be better off using a simpler robot for that and the analogy here is that >> like LLM are clearly incredible to the point where I believe the open AAIM imo model was purely textbased like it
35:27
didn't have access to Python it didn't have tools right and So, but at the same time, no one cares like like like why not give an LLM tools like obviously catchy is better when it has a browser, when it has a Python ripple, when it has, you know, access to a database,
35:44
when it has just things that it can actually look up, a calculator like it should there's no reason to artificially constrain it just because like, oh, that's that's more impressive from an AI research perspective. And so in the same
35:54
And so in the same way, a humanoid robot should also have access to a standard robotic arm if it needs to.
36:02
And the and like you should if you're running a factory, you should say, "Hey, for this task, we don't want to use the humanoid robot."
36:06
In >> near term, John potential job opportunity for humanoid robots >> to just turn the the regular robot arm on and off.
36:14
Just be the guy that presses the button.
36:17
>> You're joking, but it's real. >> It's 100% real.
36:19
Uh just like just like, you know, the LLM could try and memorize everything on the web.
36:24
That was the first version of chatbt.
36:26
It didn't have access to a web browser. >> Yeah.
36:29
>> Now, if I ask it, you know, uh, how many how many, you know, how many how much sodium in a can of diet coke, it probably has that memorized, but also it can just Google it and look at the results.
36:41
Well, maybe not Google it. Maybe Google it. We don't know.
36:43
We don't know how they >> We don't know. We don't know.
36:46
>> I don't think they're googling it.
36:46
I think Google does not allow other people to use like Google search as an API, but who knows? Big question. >> I never know. I can use Google. I can use chatgpt.
36:56
Why can't I tell chatgbt to use Google? >> Yeah. Open up google. com.
37:00
Chatgptt a chatgbt agent. Go to google. com.
37:07
Download hit query gemini for me. >> Search this for me. >> Search this for me.
37:10
Um and so uh there are there are other levels and I think these other levels from two to four are going to become increasingly more important because these are the ones that are more on the frontier and they're more uh and they require more and more AI more and more you know end to end uh machine learning.
37:28
So level two is autonomous mobility, scene understanding, higher order planning, long horizon reasoning, agile movement.
37:39
Um capabilities are open world navigation and traversal.
37:40
So these are like um the Boston Dynamics robots.
37:43
So when you have that like Boston Dynamics dog that runs around, that dog is very useful for let me see this.
37:53
So level two is autonomous mobility robots that can understand the open world, navigate and traverse various terrains.
38:00
Um, and so early production phases for inspection and data collection roles.
38:04
You send a drone out somewhere.
38:07
Uh, construction sites, oil and gas refineries, critical infrastructure.
38:11
The the the default example is like you got the nuclear power plant and you want the robot dog to run around and take images of everything.
38:19
But there's a bunch of different places and there are a bunch of different companies that essentially offer level two autonomously mobile robots now. And it's real.
38:28
It's like it's a real thing.
38:30
It's just a narrow use case.
38:32
They can't do everything.
38:32
But if you want to send the dog out on patrol, you can.
38:36
And and of course occasionally you'll want a humanoid, not a dog, for certain things.
38:41
But this is not It can't do everything.
38:44
But it can get over rough terrain. It can climb stairs.
38:48
It can do things that aren't pre-programmed where it has to understand, okay, there's a stair coming.
38:52
I got to move my >> There's a Chinese company that's been showing off a robot that can crawl, swim, and fly.
38:58
So, it can just like walk.
39:00
It can walk around like it's like a spider and then it can jump into the water and and swim through the water like actually go under and then come up to the surface >> and uh actually take off into the air.
39:11
So, >> can it do sales tax or does it need to use numeral hq. com?
39:15
>> We'll have to use numeral. >> Okay.
39:16
Well, we'll tell the robot, "Put your sales tax on autopilot.
39:18
Spend less than 5 minutes per month on sales tax compliance." Go to numeralhq. com.
39:23
Um, so that's level two, autonomous mobility, the robot dog.
39:26
Level three is low skill manipulation.
39:28
These are getting more humanoid like robots that can perform basic non-critical low skill tasks.
39:36
The unlock here is generalizable manipulation.
39:39
Advanced pick and place is a capability and mobile manipulation.
39:41
So you want a robot to go and pick up a box and move it across.
39:46
It's not a defined zone where the pick and place robot is going to sit.
39:52
You can kind of set it up anywhere.
39:54
Give it some basic rules, but you're still going to be, you know, somewhat piloting it, giving it general uh general like uh you know um overview of what it needs to be doing.
40:05
And so this is actually already deployed in some pilot stages in kitchens, laundromats, manufacturing and logistics.
40:13
And these are like bipedal humanoid robots.
40:16
Now they don't have five fingers, five toes.
40:17
They don't look perfectly human.
40:19
Um but they can actually >> and a big thing is even a remotely operated humanoid that had the ability that had fingers that could do traditional act, you know, activities that were more complicated. Yep.
40:30
Even a remotely operated humanoid could be completely valuable, right?
40:35
Because you could have >> you could have somebody somewhere else say like pick up every single leaf leaf in my backyard and put it in the green bin.
40:45
>> And there's PE and there's like probably there's like a bunch of like uh bunch of use cases you can think of.
40:49
I mean the big debate is around um uh what is the level of human involvement in Whimos, right?
40:57
that the the allegedly uh there's there's at least one person kind of overseeing every active Whimo remotely.
41:07
>> I think that number is blended across the entire org.
41:09
So like at a given time there's probably like one human looking at a screen with four Whimo viewpoints on it and they can kind of jump back and forth, but then there are other people like monitoring the network and checking on the tires.
41:26
My point is that is that uh like having somebody remotely observe the activity of a robot while we're trying to get to the point of full autonomy is totally worthwhile and is what people should expect. Right.
41:41
>> This wait, yeah, this should be pretty searchable.
41:43
Uh Tyler, can you look up the number of employees at Whimo and then the number of Whimos on the road and get the ratio there because the real test of robotic leverage should be more vehicles on the road than employees at the company.
42:01
But it seems like >> So there's 2500 employees around and there's only 1500 Whimos. >> Yeah.
42:07
So that's the number that we're that we're hearing. When people say like 1. 4 1. 5, I think that's it. I'm sorry.
42:13
These could easily be contractors that aren't technically employees that are hired to work round the clock for every single, you know, active Whimo.
42:22
So, >> but still, >> you would expect I mean the bottom line is that is that >> it's still a massive step up from not having somebody that's just sitting in the vehicle observing it real time. >> Yeah.
42:36
But but e even if we assume that there are zero contractors in there like the job displacement narrative at least at this moment in time is completely debunked because because we put a 1500 taxis on the road and it took 2500 people to do that right like now the obviously the technological vision is that you'll have 2,000 employees 200 Yeah. Yeah.
42:59
Uh just like you know you don't need you don't need uh just like you used to have you know one paper boy delivering a newspaper to every city block.
43:09
Now you have you know a number of engineers that serve you know social networks and they just kind of go out and they're distributed across uh the internet.
43:16
Um, so but but that is an interesting that is an interesting benchmark and and and something that should be like the ratio of of vehicles on the road for Whimo to employees at Whimo is an interesting stat to follow even but the I agree that the contractor thing is is is important.
43:31
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43:40
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43:47
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43:57
>> So, the last the last level of robotic autonomy.
44:00
Level four, forced dependent tasks.
44:03
These are things that must be done very precisely.
44:07
Robots can perform delicate tasks at this level that require force and weight understanding, i. e.
44:14
Finding a phone in a pocket sounds easy.
44:17
Very difficult if you're a robot.
44:19
>> Doesn't sound that easy.
44:19
I think everybody here has experienced it. >> Yeah.
44:22
And you actually drop your phone a bunch.
44:24
It's pretty It's one of the harder things you do.
44:25
Uh driving a screw in on the correct threads.
44:28
So this is purely in the research phase.
44:30
The capabilities that this will unlock or delicate force dependent tasks, fine grain manipulation, and this is purely in the research.
44:37
Uh so there are different uh uh and and one of the examples they give is like pray place the soft bread on a plate.
44:44
So you could imagine that being valuable in the kitchen context.
44:48
If you're just like the robot's just crushing the bread every time you're trying to pass steak to your friends that are sitting in a different part of the plane. >> Yes.
44:58
>> That's >> that requires that's a force dependent task >> definitely because you might get tackled.
45:02
And when the flight attendant comes up to you, you have to put your hand on their chest.
45:05
Not fully threateningly, so that you get on the no fly list just gently.
45:09
So they don't, >> but you want to touch them.
45:12
>> You want to place your hand on their chest just a little bit just to let them know.
45:16
>> This could go one of two ways. >> Probably shoulder. >> Yeah.
45:18
Probably shoulder is more respectful.
45:19
But you want you want to let them know >> that you're ready to die.
45:23
>> I took custody of that steak. >> Yeah. Yeah.
45:24
That that this is happening one way or the other.
45:27
This can go down one or two ways, but you don't want to actually cross the threshold.
45:31
You know, I if you're passing if you're passing stake to your buddies in economy, uh don't use a level three robot >> because the robot will just shove right through them.
45:44
Uh other examples include unstacking single plastic cups from a stack.
45:49
Any any fraternity member should be familiar with that, but the robot has is is still working.
45:54
So, there's still full employment for the solo cup distributers out there saying, "I'd love to see a ro robot set up set up >> stack solo cups. >> What's the beer pong? Yeah. Yeah.
46:06
Robots, you know, not gonna be able to set up beer pong for a while, but they're researching it right now.
46:12
>> Place an egg in a pot.
46:12
Place a bag of chips on a plate.
46:14
Twist and lift a bottle cap.
46:16
Literally like open a bottle of medicine.
46:18
Actually, one of the more useful things for children.
46:22
>> Very hard for children. Very hard for children.
46:24
They're working They're working on it, but >> Yeah. Yeah.
46:25
What's the arc agi of uh of of robotic tasks?
46:29
That that that's what we need.
46:33
Maybe it's taking the phone out of the pocket.
46:34
Something that anyone can do, even a child, but but it'll be the last task solved by a humanoid robot.
46:38
Um but I mean, you can imagine like twisting a bottle cap is actually, you know, we we have an aging population.
46:47
And we need more help in the in the uh elder care market in in hospitals and uh and nursing contexts.
46:54
And if you have a robot that can that can dispense medicine effectively, you can imagine that that being very valuable.
47:01
But right now that would require like an entire rebuild of the way we distribute medicine because we distribute it in child safe and also robot safe bottles.
47:10
So >> anyway, let me tell you about linear.
47:12
Linear is a purpose-built tool for planning and building products.
47:14
All of these companies that are going to develop level four force dependent task robots, they're going to need to be on linear probably >> the system for modern software development.
47:24
It allows you to streamline issues, projects, and product road maps.
47:29
So, >> moving on to the next story. There's a lot going on.
47:32
Well, the big thing uh we should talk about Sarah because this was a company that was kind of dogged for a while.
47:41
Are you familiar with this company? Yeah.
47:42
So, Cerus makes a wafer scale GPU, wafer scale chip.
47:45
Um, when semiconductors are made, you go and you want an Apple, you know, Apple silicon chip or an Nvidia GPU.
47:54
Um, there is a wafer that is grown silicon and then the wafer is etched with all the different transistors on there.
48:03
the 3 nanometer, the 4 nanometer, the 6nometer uh transistors are put onto the chip and then the chip is the wafer sliced up into individual chips.
48:11
And the benefit of that is that if one of the chips is bad, one of the transistors is off, that chip's not working, you can dump that one and the rest are going to be fine.
48:22
But with wafer scale computing, with wafer scale chip manufacturing, if there's even one defect anywhere on that wafer, you got to throw the whole thing out. >> Yeah.
48:31
So everyone was very ups very worried that the yields would never get high enough and they were saying Sarah Brris also there's other trade-offs with when you're at wafer scale with memory and and inference but what we've heard and what Andrew Feldman the CEO is saying is that um a lot of the crazy bets that they placed they're paying off and it's working very well.
48:50
So, Andrew Feldman says, "In 2016, Sam Alman and Andrew met. OpenAI was a vision.
48:56
Sarah Systems was a PowerPoint.
48:59
Sam and the OpenAI founders became one of the early investors in Cabra Systems."
49:03
Uh, good to see Sam getting a markup. He needs it. >> He needed that.
49:10
>> He really needed that >> that badly badly.
49:11
Uh, in the following years, the Cabris and OpenAI frequently met, the teams frequently met to explore working together, but the timing was too early.
49:20
large language models hadn't been invented yet.
49:24
>> This is what being early looks like >> truly like developing foundational technology another foundational technology yet insane.
49:34
>> Uh today the for the story comes full circle.
49:36
OpenAI just released its most powerful openweight reasoning model and it runs fastest on Cabris systems.
49:41
Not a little bit faster than the competition, it smokes the competition.
49:46
Running our running on our third generation wafer scale engine, GPTOSs 120B runs at up to 3,000 tokens per second.
49:57
The fastest speed achieved by an OpenAI model in production.
50:00
Reasoning that takes minutes on NVIDIA GPUs can take a single second on Cabus systems. Good things take time.
50:08
Congratulations to the Cabus team. An overnight success.
50:13
Been in the trenches for a while.
50:13
Um, but I I think this is interesting.
50:15
We've talked to some folks who have started using cerebrus uh to speed up inference for specific use cases within larger AI systems.
50:25
systems. I think that's very interesting and I think that we are we like it's very easy to collapse the narrative AI of AI into you know there's going to be one single technology one single path one single implementation but as we're seeing with the development of the new
50:42
GPT models and the new open AI chat GPT functionality it's like you you squeeze out performance in a bunch of different ways you give it a browser you give it reasoning you give it you know a Python on ripple, you give it the ability to write code and like you add all that up and you get something great. And it's
50:59
And it's the same thing on the inference side.
51:02
Um, sometimes you want to do things on on device.
51:04
Apple's, you know, kind of steering towards doing that with Apple intelligence.
51:10
>> Uh, sometimes you want to do it on a really big cluster of Nvidia H100's or big GPU cluster and sometimes you need to just run something extremely fast and that's what Cerus is powering.
51:20
So, I'm interested to understand what 3,000 tokens a second unlock. >> Yeah.
51:30
>> Because I I was thinking about it in the context of that that famous uh Amazon.
51:35
>> Well, I mean an example being like right now if you want to use like if I open up chat GPT and I want to use >> it as functionally like knowledge retrieval Google search then doing 40 and just getting something like relatively instantly makes sense.
51:47
And then but I know I would get a better result with 03 pro and uh but if you're using >> using o3 pro for like raw knowledge retrieval in terms of like I want to understand this fact or this person is just not a great experience. Right?
52:04
Because I don't want to figure it out in like >> a few minutes.
52:06
I want to figure it out now. Right.
52:08
And so >> theoretically you could get to the point where you could get 03 pro quality >> answers. Yep. >> Relatively instantly. I want two things.
52:19
The first thing is I want you to sign up for Finn.
52:22
ai, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on G2.
52:27
The second thing I want is I want when I go to Chat GBT and I type in a query.
52:32
type in a query. I've been extremely frustrated by the the model picker because I'm constantly going back and forth between 40 and 03 Pro and one takes, you know, five seconds, the other takes 15 minutes and sometimes I accidentally hit something with 03 that
52:47
I should have gone to 0 40 with and then I have to open a new one and then I copy my prompt over and put it there and then I'm like actually yeah that's a great one like this was googleable and so it just put pulled it into the nice format. What I would love is is a system where I
52:59
What I would love is is a system where I can where I can hit it with a prompt and it goes to cerebrus and it gives me just hey off the top of my head here's what I know here's the basics of what I what I'm pretty confident about but I'm going to keep working on it.
53:15
So I kick hey I I kicked off an 03 pro heavy duty reasoning. I'm searching. I'm collecting data.
53:22
I'm gonna get you the best possible answer on this, but while you're waiting, here's the thing that I can turn over in two seconds.
53:29
Here's what I know right now. >> Yeah.
53:32
>> And I think that that >> Yeah.
53:33
And that's the same experience you might have working with somebody where you ask them a question and they're like, I'm 90% sure it's this. >> Give me 30 minutes.
53:40
I'll come back to you with confirmation.
53:42
We'll figure out the plan from there. >> Exactly. Exactly.
53:44
And and that also allows you, if somebody says, I'm 90% sure that that that it's this direction.
53:51
that allows the person that you're interacting with to go and think about that path and and now there's a 90% chance that the work that they >> doing something mission critical that that you can't make. >> Yeah.
54:02
And then if they and then if they if they need to adjust course uh they haven't burned a bunch of time.
54:05
So uh I'm excited for more you know advanced model routing.
54:09
We've talked about the the mixture of experts we Tyler what was the gro of evolution?
54:14
It was like mixture of models.
54:18
>> Mixture of models of experts. Well, yeah.
54:20
What what was the the latest groheavy architecture was something else.
54:23
It was like it was a mixture of something on top of a mix.
54:26
It was a bunch of mixture of experts models and then and then and then it was a bunch of mixture of models and then we were going to do mixture of models on top of models.
54:34
Mixture of companies, mixture of >> Oh, yeah. Yeah.
54:36
Because we're going to make a router on top of that which would prompt >> Every time you prompt it prompts all of them and then it and then there's a >> mixture of models of models of experts. >> Yeah.
54:46
And then it and then it uh and then and then there's a scoring that gives you the final best. Okay.
54:51
>> But I think apparently people I mean this is all like leaked stuff on Twitter so it's like probably not true but people are saying like uh GBD5 is like supposed to be kind of what I described. >> Yeah. Yeah.
55:01
Some kind of routing thing. >> Let's go. >> Yeah. >> Put me on the team.
55:04
I just predicted it two days before it comes out or something. I'm good. >> Um yeah.
55:09
Um it took me a while to get there, but I think I think I'm excited for that. I I'm excited.
55:14
Uh anyway, let me tell you about Adio.
55:16
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55:18
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55:24
>> Uh did you see this Hunter Biden clip?
55:27
We stay away from politics, but the video we should pull up this video.
55:29
This was this was very very insightful as to how people think about artificial intelligence and automation.
55:35
So, this is from Channel 5 Hunter Biden on AI automation and whether or not you should tip it in and out. and growing.
55:42
Daniel has a very insightful post here says when he says AI, he really means software in simple robotics, but still I'm actually very surprised by how smart Hunter Biden is.
55:54
Like my friends are smarter, but I thought he'd be way dumber after all the crack.
55:57
Um, but listen to what he has to say. >> In and out is fine.
56:01
You don't tip at an In and Out. >> I do. >> What?
56:04
You tipping it in and out?
56:05
>> Yeah, they have to wear those hats.
56:05
You know what that feels like, >> dude?
56:07
Did you serious conversation?
56:07
I met somebody that is in the uh you know owns fast food franchises.
56:13
His McDonald's employs 55 people. >> Okay. >> He went all AI. >> Okay.
56:22
It's about a $2 million investment >> and they just show you a humanoid robot.
56:27
It's like >> he only employs five people now. >> Oh.
56:30
>> So his margins go up by like 27%.
56:33
>> And he'll make back the $2 million investment in under like 18 months. >> Think about this.
56:38
There's about like 13,500 McDonald's in the United States of America. I did the math.
56:43
If every one of them went down to five from 55, lost 50 on average 50 jobs, it's 6 like 70,000 jobs in America. >> Mhm.
56:56
>> And that's like it's a certainty.
56:56
And that's just McDonald's.
56:59
You think that Burger King, Wendy's, Taco Bell, I mean, across the board, >> you're talking what, like probably three and a half million jobs in the um in the in the fast food industry alone that will AI with e easily within the next 5 years, if not 3 years.
57:17
So, I have I've flipped my thinking about this whole AI thing.
57:21
You're either going to have a massive extinction event >> or it's going to be really good with a rough patch in the middle.
57:30
Because if between supercomputing power, which we're we're there already, okay, like quantum computer >> and >> we're not quite there on quantum computing, >> but if we don't figure out the >> I think we are generating exactly zero tokens >> nuclear fusion within the next like 5 years.
57:50
And if we do that, >> limitless source of >> I have some friends. I've seen enough.
57:56
>> Give them a give them a hard tech fund. >> Yeah. Oh, no. Yeah. Yeah. Yeah.
57:58
Well, he doesn't even Yeah.
58:02
He doesn't even need to be in the private markets.
58:04
There's plenty of public names he could get into if he's bullish. >> Fusion quantum. >> Yeah.
58:09
I'm sure that'll work out great for he gets in the be rough.
58:10
Uh anyway, uh the interesting thing here, yeah, he's talking about automation.
58:16
I actually know an entrepreneur who built a uh you know, you take a TV, you turn it horizontally, you touch screen, and you can order at McDonald's.
58:25
I don't know if he actually had McDonald's as a client, but he had a number of those types of customers where you shop on a screen and check out on the screen.
58:31
Um, and that's something that the we had the slowest takeoff ever for that technology >> truly like when do you think it would have been capable from, you know, from first principles just the capability of software and hardware to show up, click buttons, pay, and then and then send the order to a human cook who's still cooking.
58:55
cooking. Um yeah, it's so interesting even even at grocery store grocery store checkout >> 2005 level technology in my opinion >> a lot of grocery I mean >> air1 still doesn't have uh like selfch checkckout but I just actively avoid selfch checkckout >> and you wonder you know I think a lot of people feel the exact same way it's like being able to sort of outsource the
59:18
scanning >> of >> people do the selfch checkckout because it's a thrill because like it's this negotiation like will they catch you for how much you're stealing because cuz like they're not really watching but there's someone that's kind of watching and you could get in an altercation and so it's about like it's about getting your >> It's about going risk on. >> Exactly. >> Exactly.
59:37
>> It's about going risk on. >> Yeah.
59:38
It's it's like uh the girls >> grocery stores to to encourage thrillsekers should actually start having uh like armed security there. >> Yeah.
59:47
It needs to be high stakes.
59:48
>> Standing there like this. >> Exactly. High stakes.
59:50
>> And so if you mess up and they catch you, you're getting tackled.
59:51
It is it is hilarious how yeah they kind of got rid of like the scanner but they definitely need to watch that stuff because people will just like fake scan and then check out.
1:00:01
I don't endorse >> Chris from takes here where it's like in areas where >> Yes. Yes. Yes. This is a great take.
1:00:08
>> There is um >> and Aaron Giddon too. >> Yeah.
1:00:10
Basically this idea that like >> I think that 20 years from now I will still go to restaurants and have a human waiter. >> Yep.
1:00:20
because it's an a great human waiter >> improves the experience, right?
1:00:24
It's it's enjoyable to have somebody that understands the restaurant you're hanging out with across >> the person will look more like an educator and an entertainer than a than like a plate carrier.
1:00:37
>> I wonder if anybody, by the way, I wonder if anybody's >> a bus boy.
1:00:39
You will be someone who talks about the food and gives you advice. You >> here's something.
1:00:45
I wonder if anybody's building like a friend pendant style device for waiters.
1:00:48
You just walk up to the table, have a conversation, but it's just actively like submitting them through like the restaurant's like order management system.
1:00:57
So, the waiter's just hanging out there.
1:00:59
They don't have to be like writing down stuff or in a phone.
1:01:03
They can just have a conversation, be like, "You want this? No cheese?
1:01:04
You want fries with that? You want a side salad? Great, great, great."
1:01:08
And then it's just automatically in the system and starts getting >> I like this idea.
1:01:13
Usually when when like consumer hardware goes to the enterprises like where it goes to die like the original hollow lens and the Google glass like as soon as they said like hey we're actually going to be focusing on niche enterprise use cases usually a bad sign but that could be kind of like a toast type you know vertical SAS outcome.
1:01:32
I don't know that I I I'm I'm more bullish on that idea than um at least hearing it for 10 seconds. Um, but uh I don't know.
1:01:39
At the same time, if you go to a really nice restaurant, I would I would be leaning even more in the pure human world and being like, I would like to go to the restaurant that doesn't even have phones.
1:01:50
Uh, and there's actually a great post in here by Hip City Reggie.
1:01:52
Uh, we will read through because I want your take on this.
1:01:56
So, Reggie James, friend of the show, says, "Screenshot essay on wearable AIs.
1:02:01
Will all AIs leave the room?
1:02:04
Sitting down at breakfast, Yatu reveals he's wearing an AI pendant product on me.
1:02:08
I've never heard of that one. Very cool. There's a bunch. Sean and Jackson freeze.
1:02:12
A couple days later, I'm wearing a friend necklace. Shout, Avi.
1:02:17
And talking to my wife and I stopped to look at it, wondering if it should be included in the goings on of my home life.
1:02:24
I think it's clear that we will start to create a set of social norms around AI that's extremely explicit.
1:02:31
We will state things like, "Can all AIs leave the room?"
1:02:33
spaces will have machinery running that renders connected electronics useless.
1:02:37
So yeah, maybe we should uh have a Faraday cage that we can go hang out in.
1:02:42
Uh at the core is a it's a question of which minds authority and priority uh in a given space.
1:02:50
It's probably a good idea to assert the human ones. What do you think?
1:02:55
>> So Jackson Doll had a review of friend.
1:02:58
I guess he got an early one from Avi.
1:02:58
Uh the review was generally positive.
1:03:01
He said, "Clearly feels different to talk to a thing you're wearing and must touch to get a response from."
1:03:08
With friend, you put voice in and text out, which is like kind of an interesting feature.
1:03:12
So, you're it you're it's just hanging out with you, but then it's messaging you >> on your phone about your day, which is kind of a new >> just a new format.
1:03:22
Um he uh he says, "All feels like Avi have built something truly different, a hardware device that embodies a new set of values.
1:03:30
I suspect they will find an especially young group of people uh who quickly find themselves in daily communion with their new friend.
1:03:38
And again, uh this seems to just continue to be incredibly controversial, and I'm sure it will for a while.
1:03:45
Daniel says, "How do you feel about recording everyone you meet without their consent?" Jackson says, "Bad.
1:03:49
Bought to figure out society society with these types of things."
1:03:57
>> Yeah, the voice in text out thing is interesting.
1:04:00
I feel like there's there's a ton of different surface area to explore outside of just give someone a blank text box.
1:04:09
Like that worked for Google with the 10 blue links. It works for chat GPT.
1:04:14
But I think now the new surface area is figure out how to push stuff to the user.
1:04:19
And this is a way to do that.
1:04:20
You're just ambiently recording.
1:04:22
And then I feel like the retention is going to be way higher than other devices because as long as you put it on, it's going to be sending you messages. >> Yeah.
1:04:31
>> And so I think that's going to be really really good for retention. >> Yeah.
1:04:35
There's this there's Do you get push notifications from chat GPT at all?
1:04:39
>> Only if only postp prompt. Yeah.
1:04:39
So if I fire off deep research, it will give me a push notification telling me, hey, we're done with that.
1:04:45
But I >> there's a world in the future, for example, where Chad GPT has access to your calendar and it's like, "Hey, I saw your meeting with this person this morning.
1:04:53
Do you want me to run a deep research report on what they've been up to in the last like few months?"
1:04:57
And it's like, "Oh, they shared this update on LinkedIn and they were in this article and they went on this podcast and talked about this thing." Y more proactive.
1:05:06
>> If you go to the the chat GPT app, um it will actually um populate ideas for prompts.
1:05:14
And so for me right now tells you a lot about me.
1:05:16
It says Hollywood movies AI and filmm clearly because I was uh searching about Disney stock market mag 7 performance.
1:05:23
I can just click that and get an update and it says how have the mag seven stocks performed over the past decade.
1:05:29
What factors have driven their driven their growth and it just boom pulls that prompt up.
1:05:32
Uh media industry, luxury watches, automotive industry, F1 schedule, venture capital, tech business.
1:05:41
Uh, and so some of those if there was something triggering in the system that, you know, hey, this there's there's this interesting thing going on.
1:05:49
We should just generate this prompt and send it to John.
1:05:51
That's that's probably an interesting feature um that they'll probably explore at some point.
1:05:55
But, um, friend seems to have at least be at least be seem to be exploring this type of thing.
1:06:02
But voice in, text out, very exciting.
1:06:04
Sleep in, rest out, also exciting. eightsleep.
1:06:07
com pod 5year warranty, 30 night risk-f free trial, free free returns, free shipping. Go check it out.
1:06:14
>> I was riding a high Monday night.
1:06:14
I put up a 95 and I'm down in the dumps again, John.
1:06:19
I I got a little cocky going.
1:06:22
>> Well, you know what's not in the dumps?
1:06:23
The future of nuclear uh uranium enrichment because General Matter is bringing uranium enrichments back to the United States starting at the site where the US enrichment industry was born.
1:06:35
We've signed a lease with the Department of Energy to establish the nation's first US-owned, privately developed uranium enrichment facility at the former Paduca Gaseous Diffusion Plant.
1:06:46
75 years ago, the US Atomic Energy Commission selected Paduca to help lead the nation's original enrichment efforts.
1:06:51
Today, we are proud to return to and rebuild this historic site to power a new era of energy independence.
1:07:00
This is Scott Nolan's company.
1:07:00
I hung out with him while I was at Founders Fund. He's an absolute dog. >> An absolute dog.
1:07:05
>> One of the greatest to ever do it.
1:07:05
And uh he has been on absolute tear.
1:07:06
Uh spent I think over a decade at Founders Fund.
1:07:12
Uh helped Peter Teal with the original 0ero to1 lectures while at Stanford.
1:07:18
Helped you know ideulate and bounce ideas around for that book.
1:07:20
bounce ideas around for that book. then invested at Founders Fund for a decade and was, you know, kind of thinking about maybe starting a company but didn't want to force it and just waited waited waited until the perfect opportunity came around and really put
1:07:36
together the the the perfect team, perfect partners and has and has accelerated way faster than >> when General Matter first announced my first reaction which is always a positive reaction is nobody I haven't seen a pitch for this anywhere but it's incredible. incredibly obvious that this
1:07:51
incredibly obvious that this company needs to exist. >> Yep. Yep.
1:07:54
And so, uh, it seems like it's working.
1:07:56
They they they won a contract with the government very early, earlier than they expected.
1:08:01
And so, they are moving timelines up and now they say we will enrich or uranium by the end of the decade.
1:08:08
US leadership in enrichment will allow us to lead once again in nuclear energy.
1:08:12
Let this lets us lead in everything downstream of safe, clean, base load, power, AI, manufacturing, economy.
1:08:19
Um, today marks the beginning of America's restored leadership in nuclear enrichment.
1:08:23
We thank our partners in Kentucky and at the DOE for supporting us and you can see a beautiful render of the future facility that is absolutely massive.
1:08:32
But, uh, you know, they're thinking big and they're and and they're going for it.
1:08:37
There's also a great post in Pirate Wire, which you should subscribe to, um, digging into, uh, this from a different perspective and, uh, and and profiling the company, which is very exciting.
1:08:47
Uh anyway, if you are uh interested in investing, go to public. com.
1:08:54
Investing for those that take it seriously.
1:08:56
They have multi-asset investing seriously.
1:09:00
>> Industryleading yield, >> not financial advice >> and they're trusted by millions, not for casuals.
1:09:05
>> Taking investment investing seriously is not financial advice.
1:09:09
>> Let's go to Adam, person of swag.
1:09:09
He says he started a startup to impress a girl.
1:09:13
Starts seeing product market fit.
1:09:16
Gets more compliments from male users. Girls don't care.
1:09:18
Keep trying to get more MR.
1:09:20
Now I spend every day in a dark room coding with four men.
1:09:22
What is even the point of this in the best photo you could imagine?
1:09:27
>> Well, I would love to see Adam ring uh ring ring hit the gong with us at the New York Stock Exchange and say, "Adam, why did you start this company?"
1:09:37
>> And he just says, "I just did it to impress."
1:09:40
>> You know, you know what's funny about this?
1:09:41
This is this is the apocryphal tale of the founding of Facebook.
1:09:44
like in the Aaron Sorcin social network movie.
1:09:49
The whole premise I know you haven't seen the movie but >> I have seen that one.
1:09:54
>> What what Jordy Hayes has seen a movie? Incredible.
1:10:00
Um, but uh the uh the the the the story that Aaron Sorcin decided to tell was basically that Mark Zuckerberg started Facebook as like you know a way to get a date or something like that and then Mark like was like fact check false like I was dating Priscilla happily for years before starting Facebook.
1:10:22
So your whole your whole >> or the truth >> your whole plot is fake but but he was kind of just like whatever you know people like telling stories and maybe a better story that way.
1:10:33
But the social network 2 will be dropping soon.
1:10:35
If you have a way to get us in that movie make it happen Hollywood you're listening.
1:10:41
We're ready to be extras. Get Tyler in this movie.
1:10:44
>> I think I think it'd be so good if we could be extras just in the background.
1:10:48
I think it's pretty doable.
1:10:48
We're in Hollywood already. Make some calls.
1:10:49
This is my number one like manifest it put it on the vision board because let's make it happen.
1:10:56
>> A very small crew of people.
1:10:56
Those of you in the chat aar the game you guys would see the movie you'd see us and be like wow they pulled it off.
1:11:03
So we'll have to make that happen.
1:11:06
>> And then we'll have to buy a billboard on adquick. com.
1:11:07
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1:11:17
Adam D'Angelo says, "I love the fact that all the billboards on on 101 are for AI products and uh certainly many of them are are for >> regular enterprise SAS companies >> announcing AI products.
1:11:32
>> What is this uh oh interesting [Music] um do you see this do you see this response from Jasper?
1:11:42
He is advertising and he says cheap ondemand GPU CL clusters hyperbolic.
1:11:44
ai AI hyperbolic is an on trend term right now.
1:11:50
A hyperbolic can refer to several different concepts.
1:11:53
In language, it means exaggerated.
1:11:54
In geometry, it's related to a hyperola or hyperbolic space.
1:11:59
And in functions, it's related to hyperbolic curves.
1:12:03
>> The irony here that hyperbolic AI, you could read it as exaggerated AI.
1:12:07
And then every billboard on the 101 is just >> it's a very funny nominative determin. Yeah. Yeah. Yeah.
1:12:14
The nomine determinism is that they're overpromising.
1:12:18
>> But I think in this case it's like a neocon. >> Love Jasper. No hate on Jasper. Good luck to him.
1:12:22
I hope I hope he can deliver and I hope he can go something that can be delivered quite well today. >> Yes.
1:12:28
But but a hyperbolic function is something that goes up and to the right and and and reaches an asmtote and goes to infinity essentially.
1:12:35
So it is it is a good example and it is something that is important in AI as we scale to infinity and beyond. David George has a post.
1:12:45
>> He says, "What do Roblox, Anderole, Crowdstrike, and Apple all have in common?
1:12:48
None of them look like obvious winners from the start, but they built something far bigger than anyone expected.
1:12:53
We call these companies model busters." Great name.
1:12:55
Model busters either reveal a market that's much larger than anticipated or expand into new product lines so effectively that they break out of their original category entirely.
1:13:05
We're talking about model busters now because we believe AI is creating many more of them.
1:13:09
AI will may be the defining platform shift of our time.
1:13:13
It's changing how products are built, how they're distributed, and how buying decisions get made.
1:13:17
It's creating new consumer experiences, new workflows, and entirely new business models.
1:13:23
Platform shifts often create new winners. AI is no exception.
1:13:25
Today's most ambitious companies will grow faster and become bigger than anything we've seen before. example here.
1:13:31
Uh, if you were an investor modeling out Figma in the early days and you thought it would always be a design tool.
1:13:41
>> Again, I'm this is not how Dylan was pitching the business, but if you thought it was going to be a design tool, you could simply look and see, all right, how many designers are in the world?
1:13:52
>> And if you could get 5%, 10%, 20% of them using it, would this be a big company?
1:13:58
still would have been a big company but wouldn't have been a you know $50 billion public company most likely and and and it ultimately kind of like broke out of that TAM by being collaboration tool across um >> you know the across entire companies.
1:14:13
>> We should have uh we should have David back on.
1:14:14
I really enjoyed talking to him during in recent LP day.
1:14:16
I do wonder like is it a tautology that a model buster cannot be modeled?
1:14:22
Like are we talking about an ineffable quality that cannot be defined?
1:14:27
Like is there is there a pattern for finding model busters?
1:14:32
Because the like definitionally the model busters are things that cannot be modeled.
1:14:37
It's funny because he's also on the growth team and it probably does like the most modeling of anyone at Anderson.
1:14:43
>> Well, Roblox is an example. So Roblox had has 20 20.
1:14:45
6 million DAUs in the US and Canada last quarter. Yeah.
1:14:51
And there's I think that uh I don't know how many people young people under under 18 there are in Canada but in the US it's like something like 70 million.
1:15:03
And so that is like a meaning like if you were if you were evaluating Roblox and saying like more than a quarter of people under the age of 18 are going to be playing this game every single day >> by 2025.
1:15:14
you would have sounded a little bit crazy because I don't know that there's that many video games that I don't know how many video games have ever achieved that level of of daily active usage in a cohort like that.
1:15:27
>> Video games in general have been like a model buster in the sense that people were expecting it to be comped to the film industry and I believe the video game industry is like an order of magnitude bigger than the film and television industry.
1:15:40
It is it is a significant expansion of growth.
1:15:42
Um, but my question about like how much time should you spend trying to codify model busters or should it just be something that we refer to looking backwards?
1:15:56
Because my my question is like if you go back and you look at Danny Rhymer in the seed seed series A of Figma or Mammoon at KP doing the B or Andrew Reid doing the C.
1:16:08
Like at what point did it become important to win that deal to identify Figma as a model buster versus just say the metrics are really good. Dylan Field's a killer. I'm investing on that. >> Yeah.
1:16:22
And then and then yes, maybe there's a second act.
1:16:24
But if I get a bunch of those ultra high quality entrepreneur, ultra- high quality product, ultra high quality KPIs, I'm good enough.
1:16:33
And I don't even need to really predict that this will, you know, have a second act or expand out and and the TAM will will moon like that.
1:16:40
It's not and and you could see the same thing about like you know Anderol Palmer Lucky like you just look at the team and and and like the market's big enough to justify the investment at that phase and then you just keep doubling down and then it busts your model but you're in it for different reasons.
1:16:56
You're not in it because you predicted the model would be bust.
1:17:00
So I I I wonder what it teaches you about like the philosophy of of Yeah.
1:17:06
>> of early stage investing. >> Yeah.
1:17:08
I mean, I think you could have you could have underwrote SpaceX for a long time, ignoring ignoring uh the opportunity for Starlink, right?
1:17:15
And it's still probably be I it'd be interesting to see, >> you know, how that made it into its first deck. >> Yeah.
1:17:24
Or its first model, right? >> Yeah.
1:17:26
Probably 10 years into the business.
1:17:27
I I I have to imagine it was not in any of the series A through C deck.
1:17:34
>> People are like, I thought I was investing in a rocket ship company. Yeah.
1:17:38
>> Accidentally invested in >> internet company. Internet company.
1:17:40
>> The accidental internet company again and again and again.
1:17:42
The internet is the it is the category and that every company makes it makes money in. >> Yeah.
1:17:49
And I still I still remember as a kid when when uh uh I grew up in an Apple household.
1:17:55
I never had a like I never used Microsoft products really ever as a kid.
1:18:02
And I remember it was still at a time where you were kind of like weird if you didn't have a like a traditional PC at home and then 10 years later everybody has an iPhone, right?
1:18:11
So it was impossible to like underwrite having a breakout product of that caliber.
1:18:19
>> Kind of like luxury watches.
1:18:19
Not many people wear them right now, but in the future it'll be weird if you don't have one.
1:18:24
So you got to go to getbzzle. com.
1:18:26
Your bezel concier is available now to source you any watch on the planet. Seriously, any watch.
1:18:29
Someone in the chat yesterday said they got a moon swatch on. >> No way. Yeah. Amazing. Yeah.
1:18:36
>> I didn't even know that those would be on there. That's >> been out.
1:18:38
They they've moonwatch or moonwatch.
1:18:39
They've had different variations. >> Okay, cool. Very cool. Well, congrats to them. Hope they enjoy it. Send us a picture.
1:18:45
Uh we have some breaking news about SiriusXM.
1:18:48
They are cancelling the Howard Stern show.
1:18:51
Can you call it a cancellation when the guy's 71 years old and he's been doing it for 20 years?
1:18:56
Uh they say it's no longer worth the investment.
1:19:00
They've been paying him a hund00 million a year.
1:19:01
That is a huge salary and that's what three four times Colbear. Wow. That is that's big.
1:19:08
That's the power power of uh of radio power of you know the power law. He's done fantastically. So congrats to him.
1:19:18
Howard, if you're looking for a new gig, you're welcome to come and hang out at the Ultra Doome.
1:19:23
Max table next to Tyler and we'll we'll we'll bounce ideas off you. >> Yeah, it's wild.
1:19:29
Uh I I really wonder where SiriusXM business goes.
1:19:36
>> I know I know where this goes post AGI.
1:19:38
You're going to listen to every how every hour of Howard Stern.
1:19:40
I know you've listened to zero hours.
1:19:41
Um but there's probably 20,000 hours in the catalog or something like that of Howard Stern content.
1:19:48
You could listen to it from the beginning.
1:19:53
>> Do people listen to the back catalog ever? >> Absolutely not.
1:19:57
>> But >> Sirius XM is still a seven billion dollar company. Wow.
1:20:00
>> That's bigger than I would have thought. >> I wonder. Yeah.
1:20:02
Revenue like how much of that cost?
1:20:05
I mean it makes sense to give him a huge slice of that.
1:20:06
It is a talent driven business and he could go to Spotify.
1:20:09
He could go somewhere else.
1:20:09
My question is like he is old.
1:20:11
Will he retire or will he do a podcast or do something independent? Is there news?
1:20:17
Now they uh >> what >> they apparently did how much?
1:20:23
>> Okay, you look that up while I tell you about wander. Find your happy place.
1:20:25
Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, 24/7 concier service.
1:20:30
It's a vacation home but better. Now >> they did 8.
1:20:32
6 billion in 2024 revenue.
1:20:32
So they're trading at less than 1x revenue, which is says uh when you have a shrinking >> business, it is a rough place to be.
1:20:44
>> Not a growth, not a growth stock, I suppose. Um, yeah.
1:20:45
I wonder how much of that is getting eaten up by by talent.
1:20:50
Yeah, >> this is a trillion dollar stock if they have >> Yeah.
1:20:53
I wonder how much I wonder what percent of SiriusXM content is uh like power loss, celebrity, host, red, high salary contract versus essentially programmatic or AI content.
1:21:05
because it's probably not even AI, but if you're just like there's a there's a station on SiriusXM that's just the Grateful Dead and it just plays them the whole time.
1:21:18
Like I don't think you need someone making $100 million to like randomly play Grateful Dead tracks.
1:21:22
Like there's probably some Grateful Dead fan who manages that and picks the songs and orders them.
1:21:28
But like that could essentially be pseudo random.
1:21:30
Um, maybe one day you go through the the back catalog and then the new stuff and then you mix it up and then you play the hits or something.
1:21:38
I don't even know if they have hits in that way.
1:21:40
I know it's kind of a jam band, but um uh I wonder I wonder of their of their like of their content of their tonnage. Is that the term?
1:21:50
Tonnage is like the the amount of content on the network.
1:21:53
Uh I wonder how much of it is is driven by these high high dollar deals.
1:21:57
And I wonder if they'll get a new a new host in the seat.
1:22:03
I wonder who this generation's Howard Stern is.
1:22:05
Maybe it's like Tim Dylan or something. Some irreverent comment.
1:22:09
>> I think the thing I think the thing is >> as content is on demand, fewer and fewer people are just turning on the radio or turning on the television and listening to whatever they whatever just happens to be playing. Yep.
1:22:21
And so if you take people that were subscribed to Howard Stern and were like, "You liked Howard Stern, we're now just gonna play this other person through >> his channel."
1:22:30
They're just going to be they're just going to ask, "What's going on here?" >> Yeah.
1:22:34
I mean, certainly if you have a specific car that has Sirius XM and it doesn't have Spotify and Howard Stern's new show is on Spotify because it's a podcast, like you might stick around on Sirius.
1:22:48
Maybe they get someone new in the seat who's, you know, almost as good or can build a relationship.
1:22:52
But it does seem like a challenge to fill that, but also, you know, it's a lot of money to pay.
1:22:57
So clearly, it wasn't penciling out, so they had to move on.
1:22:59
Anyway, X is now noticing when you take screenshots. Did you see this?
1:23:05
I've seen this in other apps.
1:23:07
It's usually pretty annoying, honestly.
1:23:09
But when you take a screenshot, it triggers a UI element that says, "Hey, do you want to actually just copy the link to this post instead of taking our content elsewhere?"
1:23:18
So, it's a little bit of a retention hack.
1:23:20
I don't know if Nikita Beer's involved in this, but um uh it's uh it's it it's just like a classic UI thing.
1:23:28
I wonder what the actual like.
1:23:31
>> So many people still just screenshot a post and share it in like a group chat.
1:23:35
Yeah, because posts get deleted and then posts it's like oh that person blocked me or that person is a locked account and so the screenshot is just the universal language of like you know sharing information and content and a lot of people still share links but uh the uh like the screenshot is super lindy and I don't see it going anywhere.
1:23:52
So I mean the good thing is that this doesn't block your screenshot like your screenshot is still added to your camera roll but then you're prompted to hey do you want to actually share the link?
1:23:59
I haven't actually run into this.
1:24:00
I I don't I take a lot of screenshots of posts, but I do it on my computer, not on my phone.
1:24:05
So anyway, and Preston continues and says, "Nikita is going to look like a hero for putting features on Twitter that have existed on Tik Tok for a decade.
1:24:13
I don't know enough about Tik Tok features to know what he would port over, but I know he's a student of algorithms and student of social apps, so I'm sure he'll find something."
1:24:22
Tik Tok has is very smart about all these type all the different ways that con people are like diverting attention and hacking it.
1:24:33
It would make a lot of sense for to just copy best practices from there.
1:24:36
So I think this is a great good take. >> Yeah.
1:24:38
Well, we have Mark Andre joining in about 10 minutes.
1:24:40
Um if you have questions for Mark, throw them in the chat and we'll try and get to them during our interview with him.
1:24:46
Uh, Ray Sullivan says, "Once the summer is over and Mral is back to work, I'm sure they're going to be dropping some cool stuff. 1. 6K likes.
1:24:56
How do you even fight that? It's that's so rough.
1:24:59
Just Europe is uh is down bad.
1:25:02
The meme in the mimetic war I would be very interested to to actually understand.
1:25:08
We should have somebody on for talk about it.
1:25:09
Uh there are that the meme that that European founders and teams take off eight weeks in the summer is is >> extremely real.
1:25:20
Um and uh it's not always I mean >> a full eight weeks.
1:25:24
It's >> we have taken this summer we've taken one day off July 4th. >> Yeah.
1:25:31
>> And it's like extremely evident what's going on over here in America.
1:25:33
We run a media company >> and it's like you're in the most you're Yeah.
1:25:38
you're in the most uh aggressive fight ever.
1:25:40
Not not not to say the Mr. All is taking days off.
1:25:42
I actually don't know about that company specifically, but um but I have seen some some friends on the show proudly take time off.
1:25:49
>> I know I have I have friends that are European founders that have massive companies that are very successful and they >> their businesses allow them to take time off.
1:26:00
They can go they can have a nice vacation with family, friends, whatever it is.
1:26:04
they can maybe just dial down meetings quite a lot and their businesses are going to be fine.
1:26:08
They're probably still going to have great quarters.
1:26:10
They're going to put up great numbers.
1:26:11
The issue with Mistral is you are competing with the entire world, an entire world where if you're not at the frontier, you're not going to get usage.
1:26:22
And so I wouldn't be surprised if Mr.
1:26:25
said, "Hey, no, no, Euro summer this summer." >> But we don't know.
1:26:27
I mean, we don't know that they took a summer.
1:26:28
We don't know took time off.
1:26:31
Um, but yeah, I mean there there's also like the so there's the there's the facts of the matter like you probably shouldn't take a huge vacation in the middle of the biggest fight over new technology in the past decade or two.
1:26:42
Um, not that they are, but the the other interesting thing is like the vibes and the aura farming that comes from doing things that show that you're working extra hard.
1:26:53
So this is the Elon, you know, taking a meeting really late at night with a journalist in the room and then that gets out and you see that, oh, he really was sleeping.
1:27:03
The picture sleeping bag >> team having tents >> tents in the office.
1:27:05
Another example is Mark Zuckerberg.
1:27:07
Uh Meta dropped Llama on a Saturday or a Sunday or something and somebody asked Mark, why'd you drop it on a Sunday?
1:27:14
He said because that's when it was ready.
1:27:15
And it was a little bit rough because Met Lama wasn't like fully ready to the full extent, but it just showed that they were trying to move as fast as possible very clearly.
1:27:25
And then >> uh similarly Sam Alman and the OpenAI team, they dropped that IMO stuff at like 2 a. m. on a Saturday.
1:27:30
And it was like, okay, there's like all this debate over, you know, were they inside the stadium?
1:27:36
Were they running in the parking lot outside?
1:27:37
You know, was it signed off or whatever.
1:27:39
But you can't say that they weren't up late working.
1:27:44
Like that's the one thing you can't say.
1:27:46
>> You can't say they didn't have that dog. >> Yeah. Yeah. Exactly.
1:27:47
You can't say they didn't have that dog with them.
1:27:48
They might not have been nice with it, but they definitely had the dog in them. Right. >> That's true.
1:27:53
>> Like it wasn't very nice with it to kind of >> Krishna here says the irony is that Mrol the meteorologic the meteorological event the company was named after mostly occurs in the winter and spring. >> That's wild.
1:28:06
The nomative determinism strikes again.
1:28:09
TJ Parker says, "The best Amazon leadership principle is right a lot, and it's not particularly close."
1:28:16
Quote, "Leaders are right a lot.
1:28:16
They have strong judgment and good instincts.
1:28:19
They seek diverse perspectives and work to disisconfirm their beliefs.
1:28:21
Thought this was interesting.
1:28:24
I thought it was a a typo.
1:28:27
>> A typo famously writes a lot. WR, but this is right. They are correct a lot." >> Interesting.
1:28:36
Stuart says, "Kind of true with VCs, too.
1:28:39
Feels like the best ones just have good sense broadly and pick really well." TJ says, "Yep."
1:28:43
Uh TJ uh w has been right a lot himself.
1:28:46
Uh created Pill Pack, sold it to Amazon for a billion dollars. So, pays to be right.
1:28:54
>> He's also been right a lot about his selection of time pieces.
1:28:57
He has a fantastic collection of watches.
1:28:59
Uh some of them are on display from time to time. And every Yeah.
1:29:06
>> Andrew Reed says, "Sector focused VC firm called Specific Catalyst." >> Okay.
1:29:10
Andrew's been, you know, Yeah. Yeah. He Yeah.
1:29:14
He took Figma out at IPO.
1:29:17
He's been on a generational run.
1:29:17
He's backed like a dozen deckorns.
1:29:19
What potentially greatest allocator of this generation doing very great.
1:29:25
Getting a little cocky on the timeline.
1:29:27
Coming for General Catalyst, making fun of their name. Coming for A16Z. You remember this? He said A16Z.
1:29:33
The 16 doesn't count the space in the middle.
1:29:39
So he's taking shots from his high perch.
1:29:41
Heavy is the head that wears the crown.
1:29:43
Andrew, be careful or else people are going to start asking questions about why you don't own sequoia. com.
1:29:50
>> And you don't want that to happen. >> Whoa. >> You know this. >> Yes. >> Yeah.
1:29:55
But I think he's having fun.
1:29:55
I don't think he crossed any lines.
1:29:57
But it is funny because he's just he's just like, "hm, I'm I'm having a good time.
1:30:03
Let me just let me just just fire off some some some jokes at the expense of my competitors."
1:30:06
But >> he's having he's having fun. This is harmless. This is fun. I love this. >> Yep.
1:30:13
There's certainly plenty of VC firms formed to capitalize on a specific technological trend.
1:30:17
And maybe >> highly specific catalyst capital.
1:30:24
>> And maybe we'll ask Mark to settle the debate.
1:30:25
Is it A16Z or is it A17Z or is it like Wilmer Hail or Wilmer Hail the law firm two names there's no space in between Wilmer and Hail and so if Wilmer Hail were to do the A16Z thing and abbreviate it they would be correct. >> Yeah.
1:30:40
>> So you never know maybe Andre Horowitz doesn't have a space in the middle.
1:30:43
>> Post here from Dan Tumi quote I don't do drugs lame weak beta childish.
1:30:46
I don't touch the stuff refined respectable aged wise.
1:30:54
It does sound like yeah, you have experience. I don't touch the stuff.
1:30:58
>> Trump's line has never been big into that whole world. >> Yeah. Yeah. Yeah.
1:31:00
It just it really really hits way way differently when you say that.
1:31:04
So yeah, kids, uh, just say no.
1:31:07
Just say you don't touch the stuff. It's great.
1:31:10
>> Uh, post here from Carl Rivera over at Shopify.
1:31:13
Being an angel investor is just a different way of subscribing to extremely expensive email newsletters.
1:31:19
Yeah, you're oftentimes, you know, basically giving somebody 25K for 5 to 10 years of of monthly sends.
1:31:26
>> Don't we know an angel investor that writes like $1,000 checks to get the email updates?
1:31:31
>> Just any LPS and funds, too, and then gets all of that information.
1:31:34
He's just like a master of information collection. >> We certainly do.
1:31:40
I had a uh a portfolio company that I hadn't heard from for years.
1:31:50
I I got updates for a while after I invested >> and uh I got pinged to sign uh some docs and they and I assume that the company was shutting shutting down and they got a massive acquisition. >> Oh, acquisition. That's great. >> Yeah.
1:32:09
uh was was extremely pleasant uh pleasant surprise.
1:32:14
>> Like normally if you just like the the updates trail off, you know, >> things aren't going that well.
1:32:18
Uh but uh every once in a while you get a really nice surprise. >> That's great.
1:32:22
Uh Reeds with Ravi says, "Great leaders think like farmers. Think like a farmer.
1:32:28
Don't shout at the crops.
1:32:30
Don't blame the crops for not growing fast enough.
1:32:32
Don't uproot crops before they've had a chance to grow.
1:32:35
Choose the best plants for the soil. Irrigate and fertilize. Remove weeds.
1:32:39
Remember, you will have good seasons and bad seasons.
1:32:44
You can't control the weather. Only be prepared for it. Very >> good philosophy. Think like a farmer. >> I wonder.
1:32:51
>> Think like an aura farmer.
1:32:53
>> Think like an aura farmer. Don't shout at the aura.
1:32:56
>> We still need to we still need to have this debate with with Tyler around farming.
1:33:00
>> Well, I'm trying to get him to coin it. Cosg Groves law. >> I'm still writing it.
1:33:03
I got to get it perfect because the tweet in and of itself is or farming. >> Exactly. Right.
1:33:09
So it is >> kind of recursive in that way.
1:33:11
>> Same with Kugan's law.
1:33:13
>> Kugan's law is a recursive coin. >> Exactly. Yeah. >> Yeah.
1:33:15
I think this could do really well.
1:33:17
This has 1k likes written all over it.
1:33:20
Uh >> uh and and and endless citations of Cosgrow's law. So we will work on that.
1:33:27
Uh Merrill from Graphite says it's a massive week for his customers. Figma IPOed at 36. 3 billion.
1:33:31
Ramp raised at 22 billion and clay raised at 3. 1 billion.
1:33:39
The future is being built with graphite.
1:33:41
Congratulations to all those companies.
1:33:42
Congratulations to graphite.
1:33:42
You got an absolute murderer's row of clients. Congratulations. >> Line up.
1:33:48
>> Well, we have Mark Andre joining us.
1:33:51
He's live from the TBNN Ultrajum. Welcome to the stream. How you doing, Mark?
1:33:55
>> Hey, what's happening? >> Great to see you. >> Yeah, you too. >> A lot.
1:33:59
It's uh it's a little bit of a slow news day, but uh exciting stuff with GPT opensource.
1:34:06
>> It's not a slow August.
1:34:06
I will say >> it's not a slow August. We're glad.
1:34:08
We were just reflecting that we've taken exactly one day off this summer.
1:34:10
That was July 4th and we're showing the Europeans how American companies work. >> American work.
1:34:19
>> We're setting an example and the and the and we have proof of work because we exist on the internet and you can see us live every day.
1:34:25
So, we're setting an example. How are you doing? How's your summer going? >> Fantastic. Going really well.
1:34:30
Um, so how long is it going to be until you guys put up avatars that make claims that you're working hard all through the summer when it turns out you're you're on the beach?
1:34:38
>> You might have caught us.
1:34:39
>> I think you'll know better than us as to when the technology gets there.
1:34:41
We we we've been demoing some of the stuff.
1:34:44
People have been doing a lot of deep fakes of us.
1:34:45
And fortunately, all of them have been clockable, so it doesn't feel like a brand risk, but they're getting closer and closer.
1:34:52
And I know that there's going to be a moment where we have to say, "Hey, that's actually using our name and likeness to endorse something that we don't necessarily endorse.
1:35:00
Can you please take that down?"
1:35:02
So, we're we're approaching the the the touring test, the the uncanny valley.
1:35:06
We're escaping the >> question like looking back over the, >> you know, maybe 10 or 10 or 15 years.
1:35:13
Was was what moments did you feel like there just was not a lot of action happening?
1:35:17
because this summer is just the pace uh from so many different teams has been absolutely insane.
1:35:22
Everybody's like trying to keep up and it didn't used to feel that way at least from my point of view.
1:35:31
>> So my my view it always is there's like these there's this these disconnected, you know, kind of patterns or trends.
1:35:37
There's there's sort of the the sort of day-to-day phenomenon where like engineers show up every day and they make things a little bit better and then every once in a while, you know, you get a technical breakthrough or a new platform and and and and that process kind of this, you know, kind of sawtooth kind of up to the right >> kind of process kind of plays out over time kind of regardless of what else is happening in the world.
1:35:54
And so it it keeps happening through recessions and depressions and wars and like all kinds of crazy crazy stuff that's happening.
1:36:00
But basically, you know, the the technology keeps getting better.
1:36:02
technology keeps getting better. So there's there's kind of that curve and then and then there's the the sort of enthusiasm curve and and the and then the adoption curve, you know, which is basically like when do these things actually show up in the world and then by the way when are people actually ready uh you know for for for the new thing um like if you talk to people who
1:36:18
worked on I'm sure you guys have talked to people who work on language models they will tell you that they were surprised the chat GPT was the breakthrough moment because they thought everybody already knew what these models could do for you know 3 years before that and so they were you know they were shocked that it was the chatbot interface that that made the thing go. Um and so so there there's somewhat of a
1:36:32
Um and so so there there's somewhat of a sort of arbitrary disconnection um between what's actually happening in the substance and then what what what what people are are seeing and feeling.
1:36:39
And so it's just it's it's really hard to predict when these things pop.
1:36:42
But also if if you're in this day-to-day, it's it's really hard to tell um you know when things are going to be hot or not uh because it doesn't necessarily map to how much the techn is improving.
1:36:51
>> Yeah, we were just talking about that in the context of uh of Google's new world model.
1:36:56
It's this like generative video game that you can kind of move around in and it feels like Deep Mind is just absolutely crushing at the AI research frontier.
1:37:04
They have the best world model simulator that you can walk around in.
1:37:09
The question is like if they let another lab do the chat GPT thing and just get it out into the consumer three months earlier, they might wind up kind of chasing and trying to catch up if somebody actually figures out how to make it like a dominant consumer product.
1:37:24
Now in the enterprise it's more igopolistic but consumer seems to be winner or take all.
1:37:28
I guess the question is like how much value uh do you place right now in the AI race to just like moving fast breaking things uh you know uh dealing having like the thick skin to deal with like the safety constraints and all the different stuff.
1:37:43
Obviously not being irresponsible but just speeding up the organization as much as possible.
1:37:48
It feels like now is the time to really push on that. >> Yeah.
1:37:51
Well, first of all I need to correct you.
1:37:52
It's It's moving fast and making things.
1:37:53
Um, I don't know where I I I don't even know where that came from.
1:37:58
>> I I I I I I have no idea what you >> never heard Never heard of it.
1:38:01
>> I mean, didn't really break anything.
1:38:01
I I think that's a good point.
1:38:03
It really did just move fast and make things.
1:38:05
The first things it made were weird, but that was fine.
1:38:08
And it failed and it and it hallucinated a ton, but it didn't really break anything. I don't know. >> Yeah.
1:38:12
I Yeah, I believe in I believe in this case total deaths attributable to uh to chat GPT are still zero. Zero.
1:38:19
So not notwithstanding all of the notwithstanding all the all the catwalling but um >> yeah so look I think the AI industry in particular has a very acute version of the of the of the sort of challenge that you identified with and and you know and I don't say this negatively just an observation which is that there you know like in sort of a normal technology company you've kind of got engineers who make products and then you've got you
1:38:39
know kind of sales people or marketing people who sell them you know in in the AI companies you have this third tier of you know the quote unquote researchers >> right um and so you know which is which has worked out incredibly well I the
1:38:48
researchers have done, you know, they've just done like amazing breakthroughs at these companies, but you know, the the the handoff, you know, there's not necessarily clean handoff from the researchers to to the market. Um, and so
1:38:56
Um, and so it kind of raises this question of like, okay, like is there is are these companies therefore kind of three, you know, kind of three segment companies where they have research and then they have product development.
1:39:05
Um, and then and then they have go to market.
1:39:07
Um, and and I think that's a really open issue.
1:39:10
I mean, if you you know, Google's kind of a case study of this, you know, you alluded to deep mind, but even more broadly, Google, you know, Google developed the transformer in 2017.
1:39:15
Um, and then they basically let it sit on the shelf, right?
1:39:19
Because it was a research project.
1:39:20
They didn't productize it.
1:39:22
They were very worried about, you know, from people I've talked to, they were very worried about the, you know, brand issues and safety is, you know, kind of all these all these they had all these reasons to not productize it.
1:39:28
U, I talked to somebody senior who was there at the time who and I I asked them, you know, when when could you have had chat GPT with GPT4 level uh output?
1:39:35
Um, if you had just got, you know, gone gone flat out starting in 2017. And they said by 2019. >> Yeah.
1:39:43
>> You know, they they already knew how to do it.
1:39:44
and then you know they've now caught up but it took it took an extra 5 years 5 years to catch up.
1:39:48
Um and and so I I think a lot of these companies kind of have that challenge.
1:39:52
Elon as usual of course is is provoking this question is I'm sure you guys talked about but you know he he has now you know with XAI he's now collapsed you know he's eliminated the distinction between research and product.
1:40:04
>> Um and so you know of course you know he's pushing this as hard as he can and I think it's a it's a good question for a lot of these other companies kind of how hard they want to push on actually getting these things in fully productized form out to the market. Yeah. Yeah.
1:40:14
On on on Elon's uh like distinction, it feels like there is more research to be done, but it feels like we're we're entering like a new cycle of, you know, just focus on the engineering, focus on the deployment, the applications.
1:40:27
Let's get all this technology out into the world.
1:40:28
Let's reap all that benefit.
1:40:30
And yes, there will be a a different track of fundamental research that's happening somewhere, but it's really really hard to predict.
1:40:38
And so if you have something that's working, just double down and just go really aggressive on it.
1:40:42
Um I'm I'm wondering uh more on on that, but also on Apple strategy.
1:40:47
It feels like Apple's been um kind of like, you know, people have been maligning them for not for missing the AI opportunity and Tim Cook's just there on the earnings call being like, "Look, we acquired a couple small companies and seven this year, >> seven companies."
1:41:02
But then it seems like they're taking more of like an American dynamism approach.
1:41:06
Like there was news today in the journal that they uh that they're investing $100 million in American manufacturing.
1:41:10
They're certainly doing stuff.
1:41:12
They're just not chasing the you know the the shiny tennis >> headline$undred billion dollar capex.
1:41:20
>> Um so I'm wondering about your thoughts on on when you have a you know uh when a when you have a platform uh how hard is it to resist chasing the new shiny object?
1:41:32
Is that the right move or are are there any other things that you think Apple should be uh you know changing their strategy on? >> Yeah.
1:41:39
So look, Apple's always had this you know very clearly defined strategy that you know Steve Steph Steve and Tim you know working together figured out a long time ago which is you know they they I I forget the exact term but it's it's something like basically they they they invest deeply into the core of what they do.
1:41:50
You know they'll basically work internally on things for many years.
1:41:54
They they only actually release things when they feel like they're kind of fully baked. >> Yeah. Um, right.
1:41:57
And and and so as a consequence, they have this thing where and Tim says this, right?
1:42:01
You know, they're rarely first to market with new technologies.
1:42:04
You know, they're more often in the category of what, you know, Peter Peter Teal calls last to market.
1:42:09
You know, they're, you know, they'll they'll they'll come out whatever, three years later, whatever, 5 years later.
1:42:13
You know, there, you know, there were tablets for years before the iPad.
1:42:14
There were, you know, smartphones for years before the iPhone. >> Folding phones.
1:42:18
They're about to do a folding phone.
1:42:19
It's like 10 years into that technology.
1:42:21
I'm sure if they do the last mover. The last mover. >> Yeah. Yeah. Yeah. Sorry.
1:42:25
the the last mover, I guess. Yeah.
1:42:27
Well, what I would say is like, look, that that clearly works if you're Apple, right?
1:42:30
Um, and so it clearly works if you're Apple, but I would say there's a fine line between that strategy and just and simply becoming obsolete, right?
1:42:36
Um, and so the the problem is like if you're not Apple and you don't have all the other kind of super strengths and, you know, kind of now the market position that Apple has, you know, do you really want to be a company, you know, if you're not Apple, do you really want to be a company that basically sits there and says, "Yeah, the world's moving and we're very deliberately not going to lean as hard as we can into it."
1:42:52
Um, and so I I I think there's a lot of survivorship bias in these kinds of strategy discussions where people look at the one company that's able to pull this off and they don't look at the 50 other companies that are in the graveyard, you know, because they, you know, because because they didn't adapt.
1:43:05
I mean, you know, all the other smartphone companies when the iPhone came out, they were like, "Oh, yeah, well, we could do Touch 2, right?
1:43:10
You know, we'll just, you know, we'll get to it, right?"
1:43:11
Um, and you know, >> you know, they're gone. >> Yeah. What was it? >> Very bold.
1:43:16
I remember it was like an iPhone knockoff. >> What do you think?
1:43:19
You know, right now people are are variety of, you know, shareholders are annoyed at Apple around their reaction to AI LLM.
1:43:26
John's annoyed around just like transcription generally, just like super basic stuff.
1:43:35
But it doesn't feel like the the uh core business is immediately threatened today.
1:43:40
It feels like it's still on the horizon around these sort of like, you know, eyewear based computing, you know, potentially net new devices that we're that that we'll see from uh, you know, companies like OpenAI over time.
1:43:50
But where do you like like how how real is the threat you know this year uh versus 10 years from today and and kind of what's your framework? >> Yeah. Yeah.
1:44:02
Well, look, I mean, I think the biggest ultimate danger, I mean, the biggest ultimate danger is very clear, which is just like at what point do you not carry around a pane of glass in your hand, you know, called a phone.
1:44:09
Um, you know, because other things have superseded it.
1:44:12
And, you know, look, everything, you know, everything becomes obsolete at point.
1:44:15
So, there will there will come sometime when we're not, you know, carrying phones around and we'll we'll watch movies or people have phones and we'll be like, yeah, look at look at how primitive they were, right?
1:44:22
how primitive they were, right? because because we'll have moved on to other things and whether those things are eye based or you know uh you know other kinds of wearables or whether it's just kind of you know computing happening in the environment um or just you know entirely voice based or you know who knows what it is but um you know there will come a time when that happens you
1:44:39
know is that time 3 years from now because there's like some you know huge breakthrough you know from from some company that figures out the the product that obsoletes the phone right away or is that 20 years from now because the phone is just you know such a standard platform for everything that we do in our lives and everything else you know kind of remains peripheral to the phone. I mean that, you know, that's, you know,
1:44:54
I mean that, you know, that's, you know, that that's the game of elephants that's playing out there.
1:44:57
Um, you know, obviously I think, you know, I think it's highly likely that we we'll have a phone for a very long time.
1:45:03
>> Having said that, it is it is exciting that there are companies that are going directly at that challenge.
1:45:06
Um, and you know, who whoever cracks the code on that will be the will be the next Apple.
1:45:11
And by the way, that that may in the fullness of time be Apple itself.
1:45:12
You know, they they may be the company that figures that out. >> Yeah.
1:45:16
I remember being at a board meeting at Andre and Horowitz maybe a decade ago or something and Chris Dixon showed me the hollow lens and I was like okay we're one year away from this band everywhere and and I feel like today I'm still in the like yeah VR it's definitely one year away the next Quest I'm going to be wearing daily.
1:45:34
Um, and and it feels like we're always there, but it does feel like Apple did a lot of work on the on the fundamental uh, you know, pixel density of the resolution of the display.
1:45:44
And then Meta's been doing a ton of work on just getting it light and affordable.
1:45:48
Like it feels closer than ever, but uh, you know, you you always got to wait until you see the churn numbers until you really call the game, right?
1:45:56
>> Well, here's the other thing.
1:45:56
But, you know, I think that's true.
1:45:57
But you'd also say, you know, I'm on the on the meta board, so I'm kind of a a dog hunt in this one.
1:46:03
But like the meta rayband glasses are a big hit. >> Oh, totally >> right.
1:46:06
Like like they're a big, you know, so I think we we now have a form factor that we know works, you know, for for for eyebased wearables.
1:46:11
This, you know, there's not VR and then VR, you know, on top of that.
1:46:14
But, um, you know, just the, you know, the glasses and, you know, and then the the glasses with camera, you know, sort of integrated camera, integrated microphone, integrated speaker. Yep.
1:46:21
>> You know, that's a very interesting platform.
1:46:22
platform. Um you know the watch clearly works by the way which Apple of course you know is played a significant role in making happen you know that now sells in in in huge volume >> um you know so that's the second data point and then you know look I think these you know these these I I think some form of AI pin is going to work um I also think head you know headphones are going to get a lot more sophisticated which is already happening
1:46:40
>> um and and so you you know you do have these you know kind of data points coming out and then yeah look the the trillion dollar question ultimately is are these are these peripherals to the phone >> um you know which is what they are today
1:46:50
or are these replacements for the phone and it you We we yeah I would say we you know we have we allow we I think we have a lot of invention coming both from new companies and from the incumbents who are going to try to figure that out. Yeah, I always think about the value of
1:46:59
Yeah, I always think about the value of like narrowing the aperture on these new technologies.
1:47:04
Like with with the the meta ray bands, I feel like the fact that they aren't also trying to be a screen is actually a feature, not a bug.
1:47:12
And I always go back to the iPhone.
1:47:12
Like it was first and foremost a phone and people bought it because it could make calls and then it could make text messages and then it was an iPod.
1:47:19
But I do you disagree with that, please?
1:47:23
>> Well, you you guys I don't you guys might be too young.
1:47:25
The first iPhone actually was a bad phone. How so?
1:47:29
>> Because for the first two years I couldn't reliably make phone calls.
1:47:33
>> I I had I had like the third one and a friend had one, but I feel like it was still like people were carrying cell phones and that was the at least the expectation.
1:47:41
But yeah, I mean I guess you're right.
1:47:43
>> So for for the first it was a classic Apple store because the first for the first two years the thing couldn't make reliably make phone calls and then it turned out there was an issue with the antenna and with with how you held it and there was a famous Steve email. >> Yeah.
1:47:54
Youard it and you would and you would disconnect it.
1:47:55
you could basically brick the device from >> based on how you held it.
1:47:58
And somebody emailed, this is when Steve would would respond to emails from random people.
1:48:02
And somebody emailed Steve saying, "If I, you know, hold the phone this way, it doesn't make phone calls."
1:48:04
And he's like, "Well, don't hold it that way." >> Yeah. >> Right.
1:48:09
>> So, so, so even there it was like, Yeah.
1:48:11
And people, you know, people forget it took like five years for the iPhone to find its footing.
1:48:14
It took like two years to get the And remember also the original iPhone didn't have it didn't have broadband uh data.
1:48:18
It it was on it was on the the old 2G uh it was called the AT&T Edge network.
1:48:22
So, it didn't have broadband data.
1:48:24
And then of course it didn't have an app store, right?
1:48:25
It was completely locked down, right?
1:48:28
>> So the challenges the challenges for Apple now is that people are so used to perfection with the device that launching a product that isn't perfect >> like is embarrassing, right?
1:48:36
Like you look at the Vision Pro and it's like, well, the battery is big.
1:48:40
Steve would have hated this, right?
1:48:42
Like how he never would have shipped this.
1:48:44
and that being constrained and and not being able to innovate because you're tied to this like impossible standard of being on whatever generation 17 of the iPhone and perfecting every element is is a real challenge.
1:48:59
>> So I would say there's a correlary to that.
1:49:00
One of the things I've observed over the years is I I think technology products become obsolete at the precise moment they become perfect.
1:49:05
And and to your point what I mean by perfect basically is like yeah it's like the perfect idealized complete product.
1:49:11
Like it does everything you could possibly ever imagine.
1:49:14
Everything a customer could imagine everything you as the technology developer can imagine. It's absolutely perfect.
1:49:20
Um and there's there's been tons of examples of this o over the last 50 years.
1:49:24
um where it's like the absolute perfect permanent it seems to be the permanent version of that product and then it just turns out that's actually the point of obsolescence because it means creativity is no longer being applied right into that platform.
1:49:34
You're just like there's just nothing else to do.
1:49:35
You're just like you're you're you're done, right?
1:49:38
The product has been realized and then and then the cycle is what happens to your point.
1:49:41
The cycle is other people come in with completely different approaches, completely different kinds of products that are broken and weird in all kinds of ways um you know but but are fundamentally different.
1:49:50
So, you know, that is one of the time honored traditions and, you know, one of the, you know, one of the, you know, things you could say about, you know, Tim is, you know, his willingness to kind of break the mold of Apple only ships perfect products by, you know, be willing being willing to ship the, uh, you know, the vision pro.
1:50:01
Um, you know, you know, shows a level of determination to kind of stay in the innovation game like that, which I think is very positive. >> Yeah. Yeah. Yeah. Yeah. That's great.
1:50:09
Um, >> updated thinking on open source since we last talked.
1:50:13
Uh, there's there's a lot that's been >> Open AI is an open source company >> yesterday. Yes. Open AI is open again. Yes. >> Yeah. Yeah. Look, very encouraging.
1:50:20
You know, a year ago, I was very, you know, I was I was getting very distressed about open, you know, whether open source AI was going to be allowed. >> Uh, right.
1:50:28
It was even going to be legal.
1:50:29
And so, and I think, you know, we're basically through that at this point.
1:50:31
I say we're through that in the US.
1:50:34
Um, you know, we'll we'll see about we'll see about the rest of the world.
1:50:37
>> Um, and then look, you know, the US China thing is obviously a big deal, but it, you know, I think it's been net positive for the world that China has been been so enthusiastic about open source AI coming out of China, >> uh, which has been great.
1:50:46
>> uh, which has been great. And then yeah look open leaning hard into this um you know and releasing what you know what they did is I is I think fantastic um both because of of what they released which is great but also just the fact
1:50:55
that they are now you know willing to do that and then Elon reaffirmed overnight that he's going to you know open source you know start open sourcing previous versions of Grock um and so yeah so we you know we we we we seem to be we seem to be in the timeline where open source AI is going to happen. Um you know right
1:51:07
Um you know right now you know what you I think what you would say is it kind of lags the leading edge proprietary implementations by you know six months or something like that.
1:51:16
Um but but I think that you know that's a good if that's the status quo that continues I think that would be a very good status quo.
1:51:22
>> What are the rough edges that we need to kind of sand down when we're thinking about uh Chinese open source models specifically?
1:51:27
Uh is it we need to do some fine-tuning on top of them to add back free speech or do we need to watch for back doors?
1:51:34
Say it's phone and home if it runs into this specific thing like uh the Chinese open source thing it was remarkable because I feel like it really does accelerate the pace of innovation because everyone gets to see oh this is how reasoning works. I think that's great.
1:51:46
Uh, at the same time, it made me very it made me much more appreciative of AI safety research and capability research and actually being able to interpret what's going on and and say definitively this model is going to behave weird in this weird way.
1:51:58
Uh, like the Manurion candidate problem.
1:51:59
We haven't found any of that, but it certainly seems like something we'd want to keep an eye on.
1:52:04
But in from your perspective, like what what are the what are the risks that we need to be aware of going into a world where China is really pushing hard into open source?
1:52:13
Yeah, there's two there's two and you identified them, but let's let's let's talk about both of them.
1:52:16
talk about both of them. Um, so the so the phone home thing is the is the easy one which is you can put a you know you can packet sniff you know a network and you can tell when the thing is doing that >> and you and and plus you can go you can
1:52:26
go in the code and you can see when it's doing that and so you can validate you can validate that that's either happening or not happening and I think that you know that's important um uh but you know I think people are going to people are going to are going to figure that out. You you can kind of get that
1:52:36
You you can kind of get that problem practically. Yeah.
1:52:40
>> Um the the the bigger issue is um we we have this term in the field uh right now called open weights.
1:52:44
Um and um open weights is a loaded term.
1:52:47
Uh it uses the open term from open source.
1:52:50
But of course with open source the thing is you you can actually read the code.
1:52:55
>> Um you know with open weights you have you know just a giant file full of numbers as you said that you you can't really interpret.
1:53:00
really interpret. And then what you don't what you don't have what what most what most of the open source open weights models don't have including you know deepseat specifically what they don't have is they don't have open data right um or open corpus right so you you can't actually see the training data that went went into them um and of course you know most of the people
1:53:16
building models are kind of obscuring what that you know what that training data is in various ways um and and so when you get an openweight model you know the good news is the the the software source is open the good news is you can run it on your machine you can verify that it doesn't phone home but you don't actually know what's happening um inside the weights. And so I I think
1:53:31
And so I I think that that is going to be a bigger and bigger issue which is like okay how the thing behaves like yeah what what has it actually been trained to do um and what restrictions or directives has it been given in the training um you know that are embedded in the weights that that you need to be able to see.
1:53:45
you need to be able to see. Um you know this is I would say this is coming up as sort of I would say a global issue um you know which you know we worry about when these models come from China other countries worry when these models come from the US right which is right so one of one of the phrases you'll hear when you talk to people kind of outside the
1:53:59
US is kind of this this phrase people are kicking around which is not my weight's not my culture >> okay >> right right or or by the way for that matter not my weights not my laws >> right um which is like okay like what actually is this thing going to do right and to your point that Chinese models for example might you know ever criticize, you know, communism or something. >> I can tell you the American models have
1:54:19
>> I can tell you the American models have all kinds of constraints also. >> Yeah.
1:54:22
>> Uh right, implemented, you know, usually by a very specific kind of person uh in a very specific location in the US.
1:54:27
>> Um and so, you know, I think that this is a this is a general issue and and and we're going to have to see basically people's tolerance levels uh being willing to run open weights models where they don't fundamentally have access to the data.
1:54:37
And then correspondingly, I think what we'll see is more open source developers also doing open corpus open data so you can see what's actually in them. >> Yeah.
1:54:44
Um obviously open source is very important in terms of just distributing intelligence broadly uh giving people the ability to run their own models and and really fine-tune them and have control.
1:54:56
Uh there's also the big push just to make frontier models and high capability models free.
1:55:01
One model is you charge for the premium, you give the free away. It's a premium model.
1:55:06
That's what we're seeing at most of the labs right now.
1:55:08
There's also this kind of uh spectre on the horizon of potentially putting ads in LLMs and what that would do to the world.
1:55:16
Jordy got in a little dust up with Mark Cuban on the timeline uh deciding whether or not it would be a net good to put advertising in LLMs.
1:55:25
What might happen that might be bad there?
1:55:27
Uh do you my yeah my my point broadly was that ads have been uh an incredible way to make a variety of products and services online free and just saying like default just no ads would would potentially um you know be incredibly destructive um but uh yeah curious your framework.
1:55:49
>> Yeah so I should start by saying like whenever I personally use internet service I always try to buy the premium version of it that doesn't have ads. Um, right.
1:55:56
And so if if I can like live personally inside an ad for universe and pay for it, like that's great.
1:55:59
Um, and I I'll freely admit, you know, whatever level of, you know, hypocrisy or in congruence, you know, kind of kind of kind of results from that.
1:56:06
But >> no, the point is choice. The point is choice.
1:56:09
>> Well, the point is the point is exactly what you said. It's affordability.
1:56:10
So the the problem is if you really want to get to f if you want to get to a billion and then five billion people, um, you you you can't do that with a paid offering.
1:56:19
Like it just at any sort of reasonable price point. It's just not possible.
1:56:22
uh the you know global per capita GDP is not high enough for that.
1:56:25
People don't have enough income for that at least today.
1:56:27
Um and and so if if you want to get to you know if you want the if you want the Google search engine or the Facebook social app or the whatever AI you know Frontier AI model to be available to 5 billion people u for free.
1:56:39
Um you you need to have a business model.
1:56:43
You need to have an indirect business model and and and ads is the obvious one.
1:56:45
Um, and so I I do think if you know if if if you take some principal stand against ads, I think you unfortunately are also taking a stand against against against against broad access just in the way the world works today.
1:56:55
today. And then and then look the other the other really salient question is um you know the same question that the companies like Google and Facebook have been dealing with for a long time which is um are ads purely destructive or negative to the user experience or are they actually if done properly are they actually either neutral or even positive
1:57:11
right and and this was something that you know Google I think to their credit figured out very early which is you know a a wellargeted ad at a specifically relevant point in time is is actually content like it actually enhances the the experience right because the obvious case you're searching on a product there's an ad, you can buy the product, you click to buy the product. That was
1:57:26
That was actually a useful piece of functionality.
1:57:27
Um, and so, you know, can you can you have ads or or or other things that are like ads or look like ads, you know, different kinds of referrals, you know, mechanisms or whatever.
1:57:36
Can you have them in such a way that they're actually additive to the to the product experience?
1:57:39
Uh, and you can just like with search and with social networking, you could imagine lots of examples of that.
1:57:45
>> People will, you know, people will, you know, they'll whine around in lots of different ways.
1:57:49
But I think it, you know, I think that hasn't been a bad outcome overall.
1:57:52
Um and I think that uh I think it's entirely possible that that's what what happens with with these models as well. >> Yeah.
1:57:58
So uh kind of similar kind of question what what should be legal kind of trying to create legal frameworks on on a number of issues with AI.
1:58:07
Uh there's been a number of IP cases that have been working their way through the courts.
1:58:14
What can labs use to train models etc.
1:58:17
There's been some good outcomes recently.
1:58:18
Sam also was talking about how a lot of people are using AI as like a confidant, like a, you know, a friend, things like that.
1:58:26
And he mentioned that currently your chats are not privileged, they can be used in in in a in a lawsuit or or other uh situations.
1:58:34
or or other uh situations. uh how how optimistic are you that our sort of legal system in the US can get some of these issues right where maybe it can't just be you know total free markets kind of lawless whatever goes >> you know so in the case of training data I think that there I mean there's a
1:58:54
bunch of these copyright you know kind of lawsuits happening right now there's you know the big New York Times open the I1 and there's you know been a bunch of others um I I think in that for that particular problem my guess is that problem ultimately has to be solved through legislation um it's It's it's ultimately a legislative question. The
1:59:07
The reason is because it goes to the nature of copyright law itself, you know, which which is legislation and and and of course, you know, the the the content industry is already claiming that of course, you know, using using copyrighted data to train, you know, without permission and without paying is is is sort of, you know, they they believe illegal on its face, you know, due to violation copyright law.
1:59:24
The counter-argument to that, which, you know, which we believe is, well, it's not copying, right?
1:59:28
There's there's a distinction between training and copying, just like in the real world, there's a distinction between reading a book and copying the book, you know, as a person.
1:59:35
And so there there's going to need I I think, you know, the courts are trying to grapple with that.
1:59:39
There's a whole bunch of cases.
1:59:40
There's jurisdictional questions.
1:59:41
You know, probably ultimately Congress is going to have to figure out a a um you know, figure out an answer on that.
1:59:46
And by the way, the president has kind of, you know, thrown down that gauntlet in his I think the speech he gave last week or two weeks ago.
1:59:52
Um you know, where he said that, you know, Washington probably needs to deal deal with that as an issue.
1:59:56
Um so that's one on the on the on the um on the on the privacy thing.
1:59:59
I I think that that one feels like it's a Supreme Court thing.
2:00:04
Um to me it feels like that's the kind of issue say the Supreme Court and the in other words like whether for example your trans transcripts are are considered your property and whether they're protected against you know warrantless search and seizure.
2:00:15
Um and and the observation I would make there is if you look at the march of technology over time.
2:00:19
So the the constitution has like very clear, you know, fourth, fifth amendments, you know, very specific rights around the, you know, the things that are yours, you know, such as, you know, your home, you know, being in your home, you know, by the way, the thoughts in your head, right?
2:00:31
Um, uh, you know, that the government can't just like come in and take.
2:00:35
They can't, you know, they can't just come in and search your house without a warrant.
2:00:38
>> You know, they can't like, you know, put you in a jail cell and beat you until you fess up.
2:00:41
Like, you know, there there are, you know, we we have constitutional protections against the government being able to basically, you know, take information, you know, fundamentally.
2:00:47
um uh you know as well as possessions.
2:00:50
Um and then basically what happens is every time there's a new technology that creates a new kind of sort of you know thing that you own, you know, thing that's yours, thing that you would consider to be private thing that you wouldn't want the government to be able to take without a warrant.
2:01:05
to take without a warrant. You know, out out of the gate, law enforcement agencies just naturally go try to get those things because they're ways to solve crimes and, you know, it feels like that that's a legal thing to And
2:01:14
then basically the courts come in later and they you know rule one way or the other and basically say no that that actually is also a thing that is protected against uh you know warrantless for example warrantless search um you know warrantless wiretapping. And so I I feel like that
2:01:24
And so I I feel like that you know this is the latest of probably I don't know 20 of those over the last 100 years.
2:01:29
Um and you know I don't know which way it'll go but I think it's it's going to be a key thing because as you know people are are already telling these models you know lots lots of things that they're you know that that are very personal.
2:01:40
>> Okay lightning round quick questions.
2:01:40
as we're letting you get out of here in a couple minutes.
2:01:43
Um, we're in this age of spiky intelligence.
2:01:45
Models are great at some things and then terrible at others.
2:01:49
Where are you actually getting value out of AI right now?
2:01:51
Where is it falling down for you?
2:01:53
Where are you how are you using AI day-to-day? >> Yeah.
2:01:57
So, I I I have two kind of I don't know bar barbell approach.
2:01:59
Um, one is for for serious stuff.
2:02:02
I love the deep research capabilities. Yeah.
2:02:03
Um, and so and I'm doing this in a bunch of models, but like the ability to basically say I'm interested in this topic and then I just I just felt like write me a book and I, you know, I'm kind of hoping for the longest book I can get.
2:02:13
I always tell like go longer, go longer, more sophisticated.
2:02:16
Um, you know, but the the leading edge models now they're getting up to like 30 page PDFs.
2:02:18
Um, you know, that are like completely well formulated, you know, basically long form long form essays.
2:02:23
Um, you know, with just like incredible richness and depth.
2:02:26
Um, and you know, if it's 30 pages today, I'm sort of crossing my fingers that it'll get to, you know, 300 pages coming up here in the next few years.
2:02:32
Um, and so I, you know, I'm able to basically have the thing generate enormous amounts of of reading material with just like I think incredible richness and depth and complexity.
2:02:40
Um, and then and then on the other side of the barbell is humor.
2:02:43
Um, and I've I've posted some of these to my my X feed over over the last couple years, but I think these models are already much funnier than people give them credit for >> really.
2:02:52
>> Um, I think I think they're they're actually quite highly entertaining.
2:02:54
Um, a while ago I post I had >> specific specific formats like you know the >> chatting back and forth be Mark Andre you know that that formats >> take a dip in my pool in my office. >> They're really good.
2:03:08
So they're really good at green text u that works really well.
2:03:11
But the the the for some reason the ones I find hysterical are the I have it right screenplays um you know for like TV shows or or or plays or movies.
2:03:18
>> Um and um I I posted I had it right a new season of the HBO Silicon Valley you know set 10 years later. >> Yep.
2:03:24
Um, and I had it write like an entire I had it write like 10 10 scripts for an complete season.
2:03:28
And of course, I just said, you know, make it like Silicon Valley except, you know, it's happening at in 2021 at kind of peak woke.
2:03:34
Um, and I thought it was I think it's you know, I'll sit there at 2 in the morning just like laughing my ass off at how funny this thing is.
2:03:41
>> Um, and so I think these things are actually are actually already like extremely funny.
2:03:45
They're extremely entertaining when they're when they're uh, you know, when they're used in that way.
2:03:48
And I I I do I I do enjoy that a lot.
2:03:50
And I generate a lot of those uh that that I don't post which Stay in the group chats.
2:03:58
>> They're your property.
2:03:58
>> Yeah, hopefully the fourth amendment holds on these. >> It's great.
2:04:01
I have one last question. >> Go for it.
2:04:03
And then I've got one more.
2:04:04
>> Uh how do you get a job as a venture capitalist in 2025?
2:04:08
>> Um so I think I mean look the the best way the best way to do it is to have a a track record early as somebody who is like in the loop specifically on new product development.
2:04:15
Um and so somebody who you know be be like deeply in the trenches um at one of these new companies in one of these spaces.
2:04:20
um you know participate in the creation of of a great new product uh and and and a great new company and you know really demonstrate that you know how to do that.
2:04:28
Um you know there's there you know there there are great VCs who have not done that but you know I think that is sort of a foundational skill set uh you know for working with the kinds of founders that that you want to work with who are going to who you know are going to want you to have you know kind of very interesting things to say on that um as I think that you know still the the the best way to do it.
2:04:42
Yeah, like feel the growth, be immerse yourself in the growth, the the the the the aggressive growth environment and then you'll be able to identify it when you see it from afar. >> Yeah, that's right. >> Last question for me.
2:04:53
State of M&A in your mind, how are you advising, you know, companies uh where where you're on the board or just the portfolio broadly around what they should expect now and and in the near future?
2:05:08
>> You mean in terms of whether you can get things approved or >> basically? Yeah. >> Yeah. Yes.
2:05:12
So look, approval still appro approval is not a slam dunk.
2:05:14
There was there was you know there was a I just saw there was a medical device company this morning you know where the the acquisition was not allowed by the FTC.
2:05:21
So um you know look there is still scrutiny.
2:05:22
It's you know it's obviously a very different political regime in Washington.
2:05:25
But you know this is this is not an admin you know by by their own statements this is not an administration that believes in total affair um M&A and it definitely wants to you know in in their view maintain a a very healthy level of market competition. Um, >> yeah.
2:05:37
How many do you expect do you expect certain companies to be negatively impacted by the Figma story, right?
2:05:44
You have this deal gets blocked, successful, you know, IPO, Lena Khan is taking a victory lap.
2:05:50
uh you know many people were responding and and joking saying you know someone Lena cuts off the arm of a pianist and they endure and can create a masterpiece and then >> um and so I expect and then you look at the example with you know Roomba I think it was where where Roomba had a deal with Amazon it was blocked and and the company has just been shambles ever since.
2:06:14
So my concern is that people look at Figma and say you should be independent. You just figure it out. >> Nothing can go wrong. >> Yes. Yeah.
2:06:22
Miscon lap was very disconcerting.
2:06:24
Um and and for exactly the reason you said which is survivorship bias.
2:06:28
>> Um right which is you you you pick the one that worked out and then you know it's the it's the airplane the red dots in the airplane mean you know you you you ignore the 50 that are in the ground uh that you've never heard of.
2:06:37
Um, and so that that was very disconcerting because that, you know, it's sort of the central planning fallacy, which is like we make centrally planned economic decisions.
2:06:44
We have one example, you know, it's like in Europe it's like, yeah, well, the bottle caps actually don't fall off the bottle, right?
2:06:48
Like, you know, it works, >> right?
2:06:54
It's like, okay, but do you want to live you want to live in an economic regime in which that, you know, the government has dictated bottle cap design?
2:07:01
The answer is clearly no.
2:07:01
uh cuz the downside consequences or >> even even looking at that uh you know the Chinese model which is you know people can say they're picking winners but to get to maybe picking a winner you have this intense bloodbath of competition where you know teams need to rise to the top and sort of prove themselves before they get any of that real like you know meaningful state benefit. >> Yeah that's right.
2:07:26
And so you just you just yeah you just you just have this adverse election survivorship bias thing where you just you don't pay attention to all the collateral damage.
2:07:32
So I I I I do think that mentality is like super super dangerous.
2:07:36
Um and so yeah look I I think companies just have to be very thoughtful about this both acquirers and the acquirees.
2:07:42
the acquirees. um you know and the big thing is if you're selling a company like you just need to anticipate that you might you might not get it through and if you don't there sort of they like okay number one is there like a big
2:07:51
enough breakup fee right are you going to get you know paid for the you know paid for the the the you know the damage that you're going through um you know is and and how is that structured on the one hand and then two is yeah look do
2:08:00
you have the kind of company culture that's going to be able to withstand that um and and is your business you know strong strong enough to be able to be able to get through that and it's it it is a real risk and something worth you know taking very seriously
2:08:09
>> yeah and that's that that's why it felt emotion we were at I see last week it felt emotional this that that the the Figma team was was able to like effectively just like restart the business and say like we're we're we're taking this all the way. So
2:08:23
So >> if you talk the way to think about it, if you talk to any really successful company, what they'll tell you is, yeah, over the years we had these like crucible moments in which like we almost died, right?
2:08:32
But we like pulled together and we pulled it off and then that became like, you know, one of these central kind of mythical events in the history of the company that we always refer to and like my god, we got through that and we're so strong and tough and we've been forged in fire and now we can do anything.
2:08:43
And it's like, yeah, that's great.
2:08:45
And then there's 50 other companies that hit those crystal moments, blew up and died.
2:08:52
So, >> yeah, like it's it's all of the quote lessons learned on this stuff, they're all conditional on on like survival.
2:08:58
>> Um, and so they they these things need to be taken incredibly seriously.
2:08:59
Um, you know, which which the great CEOs do. >> Yeah.
2:09:03
Well, thanks so much for joining.
2:09:04
We'll let you get back to your day.
2:09:04
We already five minutes over.
2:09:05
Next time we have to book five hours because this is fantastic.
2:09:09
I got 10% of the way the first 24hour TV.
2:09:13
>> Yeah, we would love to have you again.
2:09:15
Uh, enjoy the rest of your day.
2:09:15
We'll talk to you soon, Mark. Have a great day. Bye. Thank you, guys. Thank you.
2:09:17
Up next, we have Harley from Shopify coming in the temple of technology, the fortress of finance, the capital of capital. Welcome to the stream.
2:09:27
Harley, get that gong ready, Jordy. What happened?
2:09:34
>> Give us the update, Harley. How you doing?
2:09:36
>> Give me the update's good.
2:09:36
I I just finished watching you guys with uh with Mark.
2:09:39
It was It was an amazing interview.
2:09:40
>> It was really a lot of fun. He's fantastic.
2:09:43
>> Before I get into Shopify, um you guys you guys mentioned the emotion of being uh at the ICU with Figma.
2:09:47
uh at the ICU with Figma. uh yesterday I think right uh so we we are 41 quarters now I maybe 42 quarters post IPO >> I think it's emotional for anybody I mean obviously that story is incredibly emotional because of what happened with with you know with Adobe and all that but I think it's it's I think it's emotional for anyone who who goes there
2:10:06
um although I I do think you know you'd said that is is that going to you know create some momentum for more companies to do it independently I don't know if that's going to be the main catalyst or not but I said this last time when I was on on your show I I want to say it again for those companies that are out there is this perception that like the public markets are something to avoid as much as possible. >> I I I you know 42 quarters in let me
2:10:26
>> I I I you know 42 quarters in let me just say like one of the best things Shopify did was was go public.
2:10:30
It's it's made us a better company.
2:10:33
It's allowed us to um to be a lot more transparent.
2:10:35
I think there's like this hygiene thing that that these quarterly the quarterly reports do.
2:10:41
Um so I I don't know I don't know how to where else to do this other than a show like this.
2:10:45
This is my endorsement that if your company is ready, the team is ready, the business is ready, accessing the public markets should not be this thing that is like if I don't get acquired, I I guess I'll have to take the IPO route.
2:10:56
Um, it's been an amazing experience for us. >> That's awesome. >> 41 quarters. >> Yeah, amazing run.
2:11:01
Uh, >> uh, advice for Dylan Field.
2:11:04
How can he make the first 41 quarters of Figma, their public debut a success? >> Oh, wow.
2:11:12
Uh I know Dylan he's an amazing founder, a great great entrepreneur.
2:11:14
So uh I don't know if I much to teach him other than to say that you know we looked at the um we looked at the IPO is sort of like we we actually called it game day like we were graduating from the the minor leagues to the major leagues.
2:11:27
And I actually think that type of um that that metaphor actually works really well.
2:11:31
It's it's not like you're done.
2:11:32
In fact, it it just like you're just sort of graduating to the next step.
2:11:35
The thing that I I think I I I on the earnings call today, I spent a lot of time talking about this and get into the results in a moment.
2:11:41
Uh this idea of like providing these like breadcrumbs to the public to to the street to your you know you have this huge book of investors including retail but you have these 10 or 20 funds that if you're lucky and we've been lucky I assume Dylan will have the same fate.
2:11:57
they kind of hold your stock, you know, for a very long time and making sure you leave enough breadcrumbs so that they can anticipate where things are going to provide some consistency, I think is really really important.
2:12:07
Um, so uh I don't know like becoming a trusted version of Figma in the public markets is a much better way to I think do things than just becoming like a different version of Figma.
2:12:18
I think the reason that Figma is so successful is because they understand their culture, their product, their customer base.
2:12:23
I think it this is just sort of the next phase for them as opposed to like okay we're done let's now change the company and become something different and in sort of this era of founder companies uh and founders being allowed and and and permissible to run their companies over the long period of time I think that works much better.
2:12:40
One thing that stood out to me is Figma was launching new features on the day of the IPO, which to me just sent this signal that we're still the same company that care like >> Dylan was replying to customer support posts on on the IPO day. >> It's it's amazing.
2:12:55
I mean, look, that that is uh like we we we do the same thing.
2:12:59
There's there is something different about founder companies.
2:13:00
Uh and with that, less about Figma, more about Shopify. Yes.
2:13:04
Um okay, so uh obviously, you know, we had our results this morning.
2:13:08
The news The news is Q2 GMV was 87 billion. That's up 31%. Revenue was 2. 7%.
2:13:18
Uh free cash flow was 422 million uh which is 60% of revenue.
2:13:22
So um back to the consistency point, we've now had 11 consecutive quarters of positive free cash flow, eight consecutive quarters of double digit free cash flow.
2:13:30
And um it's you know this is Shopify operating on all cylinders.
2:13:34
Um and and yeah, I think that it was it was a really good quarter.
2:13:39
quarter. I think there was like a a bunch of these interesting uncertainties that the street had uh tariffs dimminimous macro um but our our merchants you know did disproportionately better than the overall e-commerce market which is really cool and then I got to announce
2:13:54
some like amazing brands uh you know Michael Kors Canada Goose Starbucks these incredible companies uh that are now coming to to shop like Burton camele came um so really cool to also be able to talk about some of the big brands that are now joining Shopfly 2. >> Break down uh some of those concerns
2:14:10
>> Break down uh some of those concerns kind of one by one.
2:14:13
I'm sure you did, but but tariffs, dimminimus, you know, the market broadly, how have you guys how how have you guys been kind of approaching that?
2:14:21
And and uh >> yeah, how did you how do you think you got through it?
2:14:26
Is it just that it was always, you know, kind of like a lot of these a lot of these political changes, it feels like really crazy and then it rolls back and it's actually fine.
2:14:34
Is that the right narrative or is it the actual like adaptation and agility of both Shopify and the merchants to actually work around a changing environment?
2:14:43
>> I mean it's a team effort too because each individual brand has to say hey we're facing some headwinds here and we have to figure this out.
2:14:49
We have to navigate this and you know just find a way. >> Yeah. Yeah.
2:14:54
>> It it actually carries all the way to the consumer because the consumer also is like well what if I lose my job?
2:14:57
What if I you know have have less disposable income now? Do I have to select?
2:15:01
Do I have to make choices and trade-offs of of what I buy, what I don't?
2:15:04
I mean, you know, just to kind of at the high level, we we are not seeing signs of slowdown.
2:15:10
I'll just start with that.
2:15:10
Um, we can look at data actually through early August.
2:15:14
We're August 6th today, so not obviously not not half the month, but but certainly the first week of August and and generally we're not seeing any any slowdown.
2:15:21
The factors we monitor at Shopify are as consumer spending, household savings, tariffs, uh, foreign exchange trends, and then supply chains.
2:15:32
And generally we're not seeing nearly what what I think a lot of us were were concerned about.
2:15:37
Um the other thing that I think is is interesting is that I mentioned like you know Starbucks and Burton Canoose joining Shopify.
2:15:43
One of the interesting things that happened that I don't think we fully antic I didn't certainly didn't anticipate this is that because of this uncertainty a lot of these bigger companies were beginning to be like they were rethinking whether or not their tech stack was futurep proof.
2:15:58
like am I spending too much money on technology?
2:16:01
Is my technology partner and and commerce in our case platform are they futurep proofed?
2:16:05
futurep proofed? like I'm hearing all about you know you think about like um you know think about like a metaphorical board meeting uh at one of these very large retailers someone is going to raise your hand and say how are you guys think about AI inside the company and what about like agentic commerce and so I think one of the neat parts for us as act as a as a tailwind has been that a
2:16:24
lot of the big brands that historically said we we we our stack is not great but we're fine with it are now think are now looking saying like all right this is ridiculous it's like duct taped together it's not futurep proofed we're not able to you know we don't even like our provider doesn't even know what agent commerce is and that's leading a lot of brands to to come to Shopify. Um the
2:16:39
Um the thing that we've I think you know we were around in 2010 um and and so sort of at the tail end of of the of the global uh financial crisis certainly uh pandemic obviously was was was had a lot of changes too.
2:16:54
What we try to do is not necessarily um you know forecast what any any organization any administration is going to do uh from a policy perspective but rather figure out okay if if if if any of these things happen how do we set up merchants on Shopify so that they're better off than merchants that are not.
2:17:11
So in the pandemic for example like immediately we didn't know how long the pandemic was was going to last but we immediately were like okay there's a bunch of these like restaurants for example that are now going to have to do some sort of like delivery service.
2:17:22
We're not we don't restaurants is not one of the core uh verticals that Shopify has ever been in but like let's just make sure that we help them and perhaps they end up going to accessories later on and they'll eventually stay with Shopify or you know a bunch of physical retailers now have to move online very quickly.
2:17:36
What can we do to actually help them do so at this incredible clip?
2:17:39
So that's kind of how we look at these these these times of uncertainty which is simply prepare merchants on Shopify.
2:17:45
So maybe they don't want to do a tariff calculator.
2:17:49
Maybe they don't need to do a tariff calculator, but if they decide to do so and it's valuable to them, let's make sure it's embedded in the product and they can simply just just opt into it.
2:17:57
So that's kind of the way we we we do that as opposed to, you know, you can read all you can read as much information, you can read every paper and listen to every interview from the administration as possible.
2:18:04
You still may not know what's happening.
2:18:06
And so rather than do that, let's just anticipate all these things could happen.
2:18:11
Let's just make sure our merchants are prepared.
2:18:12
I'm not sure if I'm like over storytelling here.
2:18:14
Um, but uh, Burton, is that a full circle moment for the company? Tell me about that.
2:18:24
>> Tell me about the significance of that.
2:18:26
>> The significance of it is that, you know, >> why did it take them so long? What were they doing? >> Oh man.
2:18:29
Okay, so Canada Goose, Danny, uh, who's an I don't know if you know, you guys know Canada Goose, right? >> Yeah. >> Yeah. >> Okay.
2:18:35
So, Danny Ree, an incredible incredible entrepreneur, one of the greatest retail entrepreneurs on the planet. I He's a friend of mine. He's a Canadian guy.
2:18:43
Canada Goose and Shopify are two Canadian, you know, stories, success stories.
2:18:46
And and I've been trying to get them on for a while.
2:18:48
They finally came on, too.
2:18:49
But Burden is really relevant because, uh, the history of Shopify is that when Toby moved to Canada in 2004, uh, he couldn't get a job because he was, you know, new immigrant and no one would hire him.
2:18:59
Uh, so he ended up deciding to start a business, which was, you know, if you're an immigrant, that's okay.
2:19:04
an immigrant, that's okay. and he decided he would sell snowboards on the internet because he was in Canada and he loved to snowboard and he couldn't find any good software and so he wrote uh he wrote this software to sell these snowboards the store was called Snow Devil and that software that he wrote
2:19:19
this for Snowevil would become what is now Shopify um and so the fact that Bird one of the most important snowboard companies on the planet is now using Shopify is is really really cool uh and um but I I love the I mean I I spend if you listen to the earnings calls I spend uh quite quite a bit of time on these calls talking about some of the larger brands coming on. Part of it is that I'm
2:19:37
Part of it is that I'm very excited by these brands like you know I I love the fact that these it's weird but like Hunter Douglas uh Birkenstock Mattel these are brands Hunter Douglas was created I think in 1919 Birkenstock was created in the 1700s uh and uh and and I think yeah so Mattel was created in 1945.
2:19:54
I like that these very large iconic retailers are selecting Shopify.
2:19:59
selecting Shopify. The other reason I like to talk about these >> and it's significant too because there's some certainly some people living under a rock and early on Shopify was loved by small merchants that were just starting out and I'm sure I'm sure you went through a bunch of calls with investors
2:20:18
and things like that over the years which was yeah it's great but like you guys just have the like long tale of enterprise you're never you're never going to really dominate with the retailers that matter and like clearly that's that hasn't been true for a while, but you still kind of have to just like say it over and over and over and over and over. >> Yeah. So, I'm just I'm just repeating it >> Yeah.
2:20:35
So, I'm just I'm just repeating it over and over again.
2:20:36
The other thing that was that we announced today was that uh we now have 12% of e-commerce market share in the US.
2:20:41
So, if you think about from a checkout perspective, um yeah, that's Thank you.
2:20:47
>> That's really good advice for entrepreneurs over there.
2:20:48
Just go get 12% of the entire market. You probably be good.
2:20:51
>> A lot of people say I just I just all I want is 1%. I'm good with one. >> A little bit higher.
2:20:54
Go for >> 1% is pretty good.
2:20:55
I I I think makes us the second largest checkout uh in in the US on the on the internet uh after Amazon which >> congratulations.
2:21:04
>> How do you um how do you think about sales cycles because for someone like a Burton I imagine the first conversations there like that feels like this whale that like is just a natural fit for the product but it's not the kind of thing that was closed in like a quarter.
2:21:20
that was closed in like a quarter. So like how how do you how do you kind of even work with the team on that front to understand that like we're actually playing and you know ideally we close all the customers we want to close next
2:21:32
quarter but realistically sometimes great partnerships take time to come together and you guys almost have the luxury of like you're 41 quarters in you're probably thinking about you know you're you're thinking you know actually able to think you know long term. Um,
2:21:45
Um, but uh, >> in some cases it's it's it's it's actually it's not necessarily based on size or like GMV band.
2:21:54
I mean, we have merchants on Shopify that are doing hundreds of millions of dollars of GMV and they have like I'm not joking like they have like 12 employees. >> Wow.
2:22:05
>> Um, and then we have merchants that have, you know, thousands of employees and are doing far less in GMV.
2:22:09
So, it's not necessarily about the size of merchant.
2:22:12
It has to do, I think, with two things.
2:22:14
One is complexity in terms of how much uh you know technical debt and baggage do they have meaning how much duct tape do they have to undo to migrate over and then the second part is like you know what h how motivated are they to move over um I remember uh when when Emily Weiss left Glossier uh Kyle Lehey replaced her um Kyle's an incredible CEO uh Kyle came in to run Glossier and um Kyle called and said you know, we're a cosmetics company.
2:22:44
We have this incredibly, you know, complex technology stack.
2:22:49
We have tons of people running e-commerce. Do we need this?
2:22:53
And we looked at like, no, we we can help you.
2:22:54
And I think the Glossia migration, again, that was that was a that was um a homegrown stack.
2:22:58
And we said, >> well, that was at that was at an era where by the way, >> well, yes, but also investors at that time wanted to invest in consumer brands that had an insane CTO.
2:23:10
You know, it was like it was a point it was a badge of honor to be like, "No, we're not using offtheshelf software.
2:23:16
Like we have we're running on our own tech stack.
2:23:18
We're a technology company.
2:23:20
Give us a technology multiple."
2:23:22
>> Well, and and exactly you got I mean, you said it right.
2:23:24
It's a technology multiple.
2:23:25
They're like, "Well, we're not really this.
2:23:27
We're this other thing as well."
2:23:28
>> They're like, "Sorry, Harley.
2:23:28
I can't switch because if we don't have uh our own tech stack, like my multiple is going to get cut."
2:23:34
I talked to one CTO at a DTOC company that they didn't just build their own e-commerce stack, they built their own Salesforce.
2:23:41
They built their own CRM and their email email management.
2:23:46
>> And the good thing good thing is that everybody realized that you can build your own tech stack and you're still not going to get a a software tech multiple way and your cost is exact and not just just not your cost.
2:23:56
Just talk about your efficiency.
2:23:58
I mean totally you know back to the 12% market share of e-commerce.
2:24:01
There is no checkout that is more performant than Shopify's checkout simply because we have more data in which to make better decisions with.
2:24:06
So even if you do have the most technical team building the most incredible technology stack, you still don't have the economy of scale that you can get by being part of like that.
2:24:14
That's the weird part that people miss about about Shopify.
2:24:18
That's the reason why the 12% number is is I think valuable.
2:24:19
If you sort of put together, if you were to assume for a second that we were one single retailer instead of millions of of individual stores, we would be the second largest online retailer in America.
2:24:32
>> As part of that, you get you are entitled to incredible economies of scale.
2:24:36
So even if you can do it yourself, even if you can do it in a cost-effective way, you're still missing out on like, you know, we we announced the Agentic stuff which we just talked about yesterday.
2:24:46
you you can go do your own deals with every single, you know, agent like that that's available or we can just do it for you.
2:24:52
We're already doing it for millions of others.
2:24:53
Might as well throw in with us.
2:24:55
Your point though on the multiple is interesting. Something shifted.
2:24:58
I think at some point I don't know what year it happened, but at some point the flex of oh, I built my own e-commerce stack stopped being a flex and started to look like why did you do that?
2:25:11
I mean, write down basically start looking at it.
2:25:15
it. It's like, wait, you're spending $3 million a year on this like technology team >> and that is like cutting that could be cutting >> I don't know safely like $30 million off of your like >> I was running an e-commerce company in that era and I went around and I and I
2:25:34
went and I did uh uh I I looked at all the different companies all the leading DTOC companies looked at their headcount on LinkedIn how many people do they have in their technical organization what's the average comp and I found out the amount of money that they were spending
2:25:47
as a function of revenue and some of the companies were spending 10% of revenue on just building e-commerce software and I was like and and and so at that time I was like oh I you know we were on Shopify Plus and I was like benchmarking I was like okay so we're like an order of magnitude more efficient but we could
2:26:03
be even more efficient we need even less people like it was just like we could we should be focusing on the marketing we should be focusing on the brand and and >> there's this great uh PE firm you guys probably know it called El Caterton yes latter It's amazing. Michael Chu runs Michael Chu runs it.
2:26:16
It's like Michael Chu and and um uh the Arno family.
2:26:18
Bernard Arno is involved there, too.
2:26:20
And Michael is an incredible investor.
2:26:22
But he he's, you know, he's acquired a bunch of of of merchants uh some on Shopify, some not.
2:26:28
And one of the things he he's recently told me is that in some of those meetings where he's about to, you know, where where he brings sort of their first meeting once they've been acquired uh by by by them, he says, "Okay, well, now when are you migrating over to Shopify?"
2:26:39
Like at some point it flipped from being, oh, I can I have all this opportunity because I can build everything myself to I actually think you should be like do what you do best, which is you're an incredible cosmetics brand. Go do that really well. >> Yep. Totally.
2:26:52
>> Did uh Stables come up on the earnings call at all?
2:26:54
Any any >> I brought them up a lot many times in the past. >> Yeah.
2:26:58
>> Uh what what's your updated thinking?
2:27:01
How do they fit into the kind of Shopify ecosystem in the near term, long term?
2:27:06
>> Sorry, you said staples or stable coins? >> Sorry. Sorry. Sorry. stable coins. >> Oh, Staples.
2:27:10
Staples is a merchant on Shopify. >> Oh, yeah.
2:27:15
>> So, you know, the big it feels like we're we're in the they're now legal.
2:27:20
There's a public company.
2:27:20
They're out there, but when are we going to see people paying for it?
2:27:24
I'm sure that there's integrations.
2:27:25
I mean, a decade ago, you could pay for a shop, you could do a Shopify checkout with with Bitcoin, with the Coinbase integration and a couple other >> since two since 2012. You're >> 2012.
2:27:34
I remember because that was it was when when Coinbase started in YC. >> Exactly.
2:27:37
50 Cent had had SMS by 50.
2:27:37
50 Cent was trying to compete with Beats by Dre.
2:27:44
>> It was like it was a big battle.
2:27:45
Anyways, we had both of I think then we had both of them on and 50 Cent actually um I think was one of the first merchants to actually accept Bitcoin.
2:27:51
I I don't know if anyone did it.
2:27:53
But but look, I I think in in that era, it was really that was really about speculation, not about detail.
2:27:57
Um the way that we think about stable coins in general, and I'll get into USDC in particular, is that anything we can do that can bring more flexibility to commerce is a very good thing.
2:28:07
I think uh stable coins, USDC in particular, it just gives merchants more choices, more security, and it offers much faster settlement.
2:28:16
Now the other thing it it solves which is not getting discussed but it's important is that it solves like a real problem which is crossborder.
2:28:25
>> Crossborder is now becoming this it's not becoming a feature of of of modern retail like this like default global is how most modern the best merchants the best companies I know are default global.
2:28:38
They they don't necessarily look at these geographic physical bounds as as different markets.
2:28:43
It's like, well, if you sell to the US, why wouldn't you also sell to Canada?
2:28:47
Uh, it's effect, you know, it's it's the same continent.
2:28:51
And so, I think with stable coins, this idea of offering a payment method that combines like the transparency with a blockchain with the speed and a price stability of a major currency is really, really valuable.
2:29:01
And then in terms of like, you know, doing it with with uh with a trusted partner with us, it was Coinbase, which we we love.
2:29:07
It means that you can actually bring all these like, you know, very familiar commerce features like a authorization and refunds.
2:29:16
Um, but you don't actually need a new wallet there.
2:29:18
Like part of what I think is is scary about um this type of stable coin is like, well, do I have to now, you know, create a new account and like what is the friction involved?
2:29:27
And I think this the way that we're looking at it is that merchants get paid in dollars.
2:29:33
There's no new wallet created.
2:29:36
it there's no added friction but it's a seamless flexible safe transaction.
2:29:38
So I again it is not about um it's not a speculation it's more about utility.
2:29:44
I think once I I I think it'll be a slow um sort of increase in penetration and then eventually there'll be a cohort of of consumers and a cohort of merchants that are just like this is the this is so much better. >> Can we shift to AI?
2:30:01
I know that you have some stuff that we should review.
2:30:04
I also want to ask about uh shopping in LLMs and then how that flows through.
2:30:10
Uh there's the potential of ads and there's potential of the checkout happening, you know, or or you know, I I send my agent out to purchase it.
2:30:19
Just give me the updated thinking on uh how AI is change or how AI is changing commerce.
2:30:26
>> So if you think about um >> if you think about it from a from a sort of a model perspective, think about Shopify as being the hub in the middle.
2:30:34
this like retail operating system where you have your inventory, you have your analytics, you fulfill orders from there, you have your customer data, everything is sort of at this hub and you sort of think about like the main spoke off that hub is has been e-commerce for us.
2:30:46
And then a second spoke obviously was like point of sale like physical retail which is one of our largest growing segments and then you can sort of think about new spokes.
2:30:54
Another spoke for example is like social commerce.
2:30:56
We integrate with like Instagram, we integrate with YouTube, we have a Roblox integration, a Spotify integration.
2:31:01
So one of the things that we think a lot about is the future of retail is not going to be this weird binary online versus offline.
2:31:08
It's going to be where every surface area where consumers spend their time.
2:31:12
And for most merchants most of the time you know the Roblox integration is not going to be the main thing.
2:31:18
Although you know Fenty Beauty u one of our brands is doing really well with this Roblox integration.
2:31:23
They they have figured out that their consumers are spending time and there's actually a physical they have a sorry like it looks like a physical store inside of of the Roblox universe.
2:31:32
Roblox by the way has like hundreds of millions of of monthly activives.
2:31:34
It's >> we were talking about earlier it's they have I think it's we we talked about earlier 20 plus million DAUs in the US and >> it's that's unbelievable 18 under 18.
2:31:45
It's like all every everyone. >> Okay.
2:31:47
So, like think about it from like, you know, the perspective of of a direct to consumer cosmetics brand where their core demographic is that age group.
2:31:53
Now, it's a new place and there's no competition because no one else is like like Fenty created a store inside of Roblox.
2:32:02
>> You look next door unlike their store in Soho, there's no one else.
2:32:06
>> So, >> we think about this idea of like these different sort of spokes being different channels.
2:32:09
Y >> we think that commerce is very likely going to be a new one of those spokes.
2:32:18
And so in the last 12 months or so we began to build infrastructure that allows these AI conversation basically to bring native shopping inside of these AI conversations.
2:32:27
So we we we we launched three things um and I'll go through all three because you guys are technical and you have a technical crowd.
2:32:34
So the first one is catalog.
2:32:34
We launched it in in this past quarter.
2:32:35
So catalog effectively helps agents to search and and to sort of surface exactly what customers want in seconds.
2:32:44
It looks across all of Shopify's products, every skew on Shopify.
2:32:46
And then it uses large language models to like categorize them based on like you know meta metadata and and and and the types of products they are.
2:32:55
It also creates sort of this like standard product data at these massive volumes and then we package it in these like basically these search APIs.
2:33:04
So if you are if you if you have an agent, you simply can ingest the search API and have the entire catalog of Shopify merchants.
2:33:13
>> And is this is this tech by an MCP server or is this a API that's just accessible?
2:33:18
>> So you can you can do an MCP server with like UI components or you can do it through an API. >> Okay, got it. Yeah, makes sense.
2:33:24
>> The second piece is universal cart. This is new.
2:33:26
So it's part of what we call checkout kit, which I'll get into a second, but effectively it holds items from multiple stores in one single spot.
2:33:34
So, as you're sort of having a conversation with your agent, let's say you're going on a camping trip, for example, you may want a tent, but you may want a sleeping bag.
2:33:41
Those are different stores.
2:33:42
You may not be ready to check out immediately, but you also you want to hold all these things in in one single cart. >> Mhm.
2:33:49
>> And then that all feeds back into checkout kit, which we launched last year, which lets partners embed merchants checkout directly in their agent.
2:33:57
Uh, and it has Shopay built into it, but it it it, you know, it's the best converting checkout on the internet, which is ours.
2:34:02
And now we're effectively giving it to these agents.
2:34:05
What we announced yesterday was that now partners, any any agent can actually um theme the checkout kit so that it matches the application's look and feel.
2:34:14
So it doesn't feel like some weird, you know, iframe that pops out that looks like it's a third party.
2:34:18
So it actually looks natively integrated.
2:34:20
And then, you know, merchants get the tools that they need.
2:34:24
They'll get address verification. Uh they get fulfillment.
2:34:26
So and and and actually in the case of checkout kit, Microsoft's co-pilot um is is already using it.
2:34:33
So the benefit is sort of three-fold.
2:34:35
The first is for consumers now they can get these like personalized conversational shopping experiences.
2:34:42
From the merchant perspective, merchants on Shopify are now going to have a new place to get discovered across all these AI platforms.
2:34:48
But from the partner perspective, which I think is the most interesting, is that they don't have to build the complex parts of of commerce.
2:34:55
They get access to millions of these merchants through the this MCP catalog and they also get the best converting checkout.
2:35:01
And um we think I if this does become a place that is a predominant or or a popular surface area for commerce um it it it means that merchants on Shopify will be very well positioned.
2:35:15
And what's neat about it is if you think about how a lot of those, you know, like if you were if you if you were trying to go on a on a camping trip now, you'd probably do it in some sort of search Google or something like that, the the products you're going to find are likely going to be based on like a lot of them at least may be sponsored where where the more you pay, the more likely you are to show up.
2:35:36
Whereas in sort of the agent world, in sort of a commerce world, it's actually more of a relevancy.
2:35:41
like it has all this history of everything you've ever talked to it and said to it.
2:35:45
It knows that you're price sensitive for certain things but maybe not for other things.
2:35:48
Um so it may it may turn out to be a really new sort of vector for commerce and and and we want to be at the center of it.
2:35:58
>> How do you uh how what's your kind of looking out into the future commerce within LLMs?
2:36:04
Are you bullish on on paid placements?
2:36:08
Are you bullish on referrals?
2:36:10
Uh I was uh obviously like in the same same thing as you know in the influencer world like consumers deserve to know what's an ad and what's kind of an organic mention and all that kind of thing.
2:36:22
Uh there've been a debate recently around you know should ads be banned entirely from LLMs.
2:36:26
Um and uh I you know generally don't agree with that just because I think you know these tools should be broadly accessible and and ads are potentially a way to do that.
2:36:37
But the other thing would be ultimately like do LLMs would LLM at some point earn referral fees from merchants?
2:36:44
I mean all this stuff is like extremely complicated and yeah >> um can have you know positive effects, negative effects, but uh what's your framework?
2:36:54
>> Uh it's that that that I think is the $64 question. I I I I'm not sure.
2:36:57
I don't know exactly because part of the reason that I think agentic shopping is so interesting to so many people is because um it feels more democratized. >> Yeah.
2:37:10
>> It feels more based on it has a great understanding of who you are.
2:37:13
Therefore, you know, you guys started the show with me today saying like I'm going to have my agent go and buy me a bunch of stuff.
2:37:21
I want my agent to go if that is if that is how I am purchasing in the future.
2:37:24
I want my agent to go buy things that I actually really like, not the thing that my agent is getting paid for. >> Yeah. Yeah.
2:37:31
When I when I think about the use case here is like I have certain brands and I only buy their t-shirts.
2:37:37
And if I could just be in an LLM and say like, hey, I want to get some new t-shirts.
2:37:40
Can you like and they're like, cool.
2:37:43
Here's the t-shirts you normally buy. Would you like?
2:37:45
And I'll be like, I'll take five white t-shirts and five black t-shirts. And it's just done.
2:37:48
Like that's amazing because I don't want to be navigating around and you know it's just like removing that friction which is >> kind of the I mean has been the history of Shopify.
2:37:59
So all these new products >> if you if you think about you know I think Toby told me this that like if you want to look at you look out to where technology is going look at what like rich people currently do and then everyone else will be able to get that feature.
2:38:10
Uh so you go back to this idea of like personal shoppers.
2:38:12
If your personal shopper is constantly selling you the thing or trying to sell you the thing that they make the most commission on, it may work once or twice.
2:38:21
Eventually, you'll stop going to that store.
2:38:23
>> You're going to look in the mirror.
2:38:24
You're going to look in the mirror.
2:38:25
>> You're like, "Dude, this is like this like some gold chain or like I wear a black t-shirt.
2:38:28
Like don't, you know, like I know you're getting paid more for this gold t-shirt, but like I wear a James Purse black t-shirt every day of my life."
2:38:34
And James Purse uh is a great Shopify merchant and a great entrepreneur himself. >> There we go.
2:38:39
>> He doesn't he doesn't advertise. Doesn't advertise.
2:38:40
So like so like he's not going to participate in that.
2:38:44
But if it knows that I really love James Pur black t-shirts, it has to be highly contextualized.
2:38:50
So that that is a really good question.
2:38:52
I think the way that we look at is is like this.
2:38:54
There is a there is a there is um a a decent chance that aentic shopping will become very relevant for some segment of the market.
2:39:04
Therefore, if we want to qualify and re-qualify to be the merchant uh the retail operating system for all these incredible brands, we have to be there in the same way that we have to be in social commerce.
2:39:13
And social commerce, you know, for some people it is a really really important channel for them.
2:39:17
You know, my mom is I don't think my mom has ever bought something on social commerce.
2:39:21
She still goes into a physical store.
2:39:23
So, we we're not going to predict like our our our job is to make it so that wherever you want to sell, you should be able to do so really easily.
2:39:31
It's going to be absolutely wild when you think about I mean this this experience where you're chatting with a model and it surfaces you a product and you can ask it well what do people like me think about it and it like automatically pulls you know reviews from relevant people.
2:39:46
It pulls what your favorite influencer thought about the product.
2:39:50
It it surfaces other brands.
2:39:52
Like it it's going to be incredibly powerful.
2:39:54
And I think at at best it's like a personal shopper that's aligned with you, not, you know, trying to maximize every purchase or a great sales rep who's if you're working with, you know, a a sales rep at at a retail store, they're not fixated on like how do I maximize this the value of this cart, right?
2:40:12
They're thinking about the sort of long-term relationship with the customer. So, very exciting.
2:40:16
I'm excited to see what people build.
2:40:19
>> Well, congratulations.
2:40:19
Thank you so much for hopping on and chatting with us. Always so much fun. Fantastic work.
2:40:24
>> You guys are the best. I I love your show.
2:40:25
Love what you guys are doing.
2:40:25
And I I like that this is becoming a a new routine that after see you guys.
2:40:35
>> We'll talk to you soon.
2:40:35
Up next, we have uh Anton from Lovable coming in the studio.
2:40:39
Get that gong ready, Jordy. What? >> Shopify. >> Oh, what? >> Up 20%. >> 20%. Yeah.
2:40:44
I was trying to tell him that on the stream because I wanted the eyebrow raise like the uh you know from the Brian Chesy when the IPO and Emily Chang tells him how much the stock is up and he goes It's like one of the most iconic moments in tech history.
2:40:56
Anyway, uh we got Anton from Lovable. How you doing? >> What's happening? >> Great.
2:41:00
Great to meet you finally. >> Yeah. Yeah. Great to meet you, too.
2:41:02
Uh we were going back and forth with uh with with folks in and around your orbit.
2:41:07
Every time we talked, there was a new massive number.
2:41:10
There was uh you know certain amount of people on the platform, certain amount of websites.
2:41:15
Give me the latest headline number. That's shocking.
2:41:17
Isn't it like some insane number of websites on the internet are generated every day? That is true. What are you holding? >> I'm holding a gong. Uh, a malar celebrate.
2:41:27
I >> I just learned today we have 100,000 new projects built every single day. >> Congratulations. >> That's fantastic. >> How'd you do it?
2:41:39
What's the key to success?
2:41:40
What are people using Lovable for more than anything else?
2:41:43
There's when you think about just a web page can be anything.
2:41:48
It can be everything from from Facebook, a billion users, a trillion dollar company to, you know, a little homepage for my, you know, my my like my resume.
2:41:59
Um, what are people using it for? >> Yeah.
2:42:02
Look, look, Lovable, it's the fastest way to go from an idea to a production ready application and a lot of people make that into a real business and that's something we that's in our mission to empower much more people to do.
2:42:14
do. But apart from the entrepreneurs, the solarreneurs like building for the first time or building for the nth time without but by themselves you have a lot of people in larger companies now and we're seeing that use case growing very
2:42:30
very fast like percentage wise much faster >> and then they go from like I have this idea my engineers should build it but they don't understand me so I need to create a a full working version of it and then they're going to be like okay I get it. looks great. Let's build it. looks great. Let's build it.
2:42:46
>> How are you How are you thinking about tool use right now?
2:42:47
I I I feel like there's so much open source software there. Um LM are incredible.
2:42:51
They could probably rewrite Linux from scratch.
2:42:55
They could rewrite a database from scratch, but you want to be provisioning and standing on the shoulders of giants.
2:43:00
But how often are you focused on allowing the like the like to grab different open source projects and tools?
2:43:08
Like if you want to build an e-commerce software, you probably don't need to rewrite a catalog from scratch.
2:43:14
There's probably a tool for that. >> Yeah.
2:43:15
You know, um how we think about build making the product as good as possible.
2:43:19
And we've thought about it for a long long time is like >> we have an agent >> that can do things.
2:43:24
You can browse the web, generate images, but specifically create applications >> and a website, personal website for you, whatever.
2:43:32
We are making giving that this agent more capabilities. We're adding new things. Okay.
2:43:38
So, for e-commerce specifically, we're taking the best of breed to build e-commerce as a tool and more to I'm spoiling some teasing some things there on the e-commerce side actually.
2:43:50
>> Um, giving it more tools >> and then we're making the agent itself smarter.
2:43:56
>> So, those are the two things we're doing.
2:43:57
Giving more tools, making it smarter.
2:43:59
>> What's the key to high retention?
2:43:59
I feel like um there's a world where you you you know use a tool lovable, you build something and then you're like okay we're ready to go and stand up a whole team of engineers to actually build this thing and take it to the next level.
2:44:14
How how are you uh you know fighting that urge to just use this as a prototyping tool? >> Yeah.
2:44:21
>> Yeah. Um like if you have a high performing engineering team with a large existing system then there's always this balance of like do I take this thing I built in lovable y and I connect it to my system many people do that or do I just use it as a design and then um I like know exactly how to build it so
2:44:39
it's going to be super fast with my engineers both are fine >> or do you do I even edit the code as an engineer level also popular um I I think regardless of all of those you can have very very high retention because if If you want to just prototype in Lava, it's the easiest way to do it. You just open
2:44:53
You just open the browser and then boom, you have you have your prototype and it has access to your design philosophy.
2:44:59
It has access to um like integrations and different tools that you might want to want to use.
2:45:04
So there's a high retention there's a very high retention on that use case.
2:45:08
But um how I think about it going forward is that we want to just build a platform where you never want to leave this platform because it provides you so much value and what large language models have done now is that like they generate code really well and but that's just one tiny part of the entire life cycle of building and maintaining and operating and a product and growing a growing a business on top of that.
2:45:34
>> So I'm not sure you know Eliana on our team.
2:45:37
She's like, uh, I've been doing growth for 20 years and now I'm so excited to not have to do like the boring growth and just do the innovative growth and AI is going to handle all the growth like all the growth things.
2:45:46
So, so that that's on the horizon.
2:45:48
And when when you have a platform like that, >> um, you should be getting so much value that you never want to live. >> That makes sense.
2:45:55
>> How do you what do what do you think is the future state of, you know, what do you think the average startup's website will look like 5 10 years from today?
2:46:02
I feel like right now we're in this era where AI is changing everything. It's changing workflows.
2:46:09
It's changed the way changing the way we work with software.
2:46:13
And yet startups, you know, still buy they try to buy their one-word uh. com domain.
2:46:17
And that the typical website is like incredibly, you know, static and and tries to reach a broad audience.
2:46:21
And I can imagine uh I can imagine a world in the future where where websites are being almost generated in real time depending on the user and and the type of customer they are.
2:46:32
um more paral we're getting more paralyzed. >> Yeah. Yeah.
2:46:36
Knowing knowing the the trend to date will be more of that.
2:46:39
Um but I'm curious, you know, kind of if you have >> I think the websites of the future are going to be better at hacking the human brain and like its addicting nature addictive nature and so on.
2:46:54
And what that means exactly, I don't know.
2:46:55
We like we let algorithms figure out partly.
2:46:59
Um, but no, I think >> Anton is going to hack your brain everybody. >> Yeah.
2:47:05
I mean, do you think that starts with like AB testing because you can generate more pages quicker that you're just kind of optimizing for retention or conversion and then because you're just generating the entire site instead of just, you know, testing two different headlines.
2:47:20
You're testing the entire concept of what the website is.
2:47:24
I I yeah I think the algorithm like there's going to more and more be algorithms that figure out how how things should be optimized for us and then um I think what like what you're also seeing now already is some a bit of counterculture to that where a human coming in and being like no I want it to be much more minimalist like a new type
2:47:43
of >> yeah this is the Nat Friedman style that Mark Zuckerberg recently times just raw HTML there's a time and a place for both >> time and a place for So I guess we see like some complex um evolution of the of of different different ways of doing things and um generally I think the f like the future has always been more and more diverse. There's like many
2:48:05
There's like many different websites and applications and we I think that trend is going to continue.
2:48:10
It's not like it will converge to just just one way of doing things.
2:48:14
>> Last question from my side.
2:48:14
What what's uh what's next on the horizon?
2:48:17
Are you focused on taking the product that you have?
2:48:21
You clearly have product market fit.
2:48:22
Are you focused on sales marketing, ramping up, expanding what you have or or or expanding the portfolio to different areas and different markets, different products? >> Yeah.
2:48:35
Um I'll answer it like this.
2:48:35
So in the order of like the sides of the use cases, founders are taking their ideas, they're building real businesses, software businesses.
2:48:44
designers and product managers and others in in companies, they're taking their ideas and building um concepts to communicate with their team up and like 100 times faster than building out the concept in the past.
2:48:59
And then everyone else is building like their personal or business websites much much faster.
2:49:02
And we're doing all all of these things.
2:49:05
Lovable does all of these things at the same time.
2:49:08
And it like becomes as you use it, it becomes better and better at uh helping you. >> Cool.
2:49:18
>> So that then that's what we're going for. >> Amazing.
2:49:20
Well, congratulations on all the fantastic growth.
2:49:22
Uh truly staggering data.
2:49:26
>> Barely a week goes by without a big lovable number hitting the timeline.
2:49:30
>> Yeah, another another lovable number has hit the timeline. Congratulations.
2:49:32
Thank you so much for stopping by. We'll talk to you soon.
2:49:36
>> Have a great rest of your day.
2:49:36
And up next, we're shifting over to uh Thomas from GitHub.
2:49:41
Another little post earnings breakdown.
2:49:44
Get the update from Microsoft and GitHub.
2:49:46
Uh Nat Freiedman was running the organization.
2:49:49
Thomas has taken over and they've been on absolute tear. Just cross to follow. >> Just crossed. >> Welcome to the show.
2:49:56
>> 20 million users since growth is serving 90% of the Fortune 100. Congratulations.
2:50:02
Uh kick us off with an introduction.
2:50:05
>> Thank you so much for having me on the show. Great to be here.
2:50:08
>> Thanks so much for joining.
2:50:08
>> And uh yeah, I'm Thomas and uh I've been running GitHub for the last four years.
2:50:13
Um I've been with GitHub for seven years uh since we acquired it in 2018 and it's been a tremendous run uh that GitHub had as part of Microsoft.
2:50:22
Is it fair to describe the run as as growth in overall users or growth in uh GitHub co-pilot revenue or uh you know this 90% of the Fortune 100's using the product now has that been the win case?
2:50:38
Has it been a little bit of >> what's the other 10% doing?
2:50:43
>> Well% software I think software that's why they that's why >> this is the principle.
2:50:48
The last 10% is going to take you 10 times as long to.
2:50:52
>> I got to we got to figure out the 10% and short them.
2:50:54
That's that's >> I mean, but seriously, if you're a Fortune 500 company and you're not building some software in your organization, >> there are other companies that provide similar services that do well.
2:51:05
You know, we're not going to talk too much trash about the competitors, but you know, we are we are big fans.
2:51:10
Um but yeah, what what uh over your tenure, what have been the big initiatives that you've shipped and then maybe opened a bottle of Don Peran champagne or or just had a pizza with the team to celebrate?
2:51:23
>> Uh you know, we always keep pushing further.
2:51:24
So there isn't um there's celebrations every now and then.
2:51:27
What's really like about what's next? What's next? What's next?
2:51:29
Um if I look back to 2018 when we did the when we did the deal, we really had three principles. Put developers first.
2:51:36
And I think we nailed that one. GitHub is still GitHub.
2:51:40
you know we are talking about developers we're building for developers we are you know uh meeting with them all the time and we have preserved you know that um spirit of what GitHub is all about the second one was that Microsoft helps us to accelerate Microsoft if you will as
2:51:54
an investor into GitHub and I think that's you know the 150 million uh developers on the platform uh recently we we hit over a billion repositories both you know original repositories and forks um you mentioned the 20 million copilot users um Microsoft's visual studio family. So VSE and VS Code
2:52:09
So VSE and VS Code together has 50 million active users.
2:52:11
So you can also see how much room there is still for Copilot to grow its its market share.
2:52:18
Um and uh a year ago we we passed 2 billion in AR annual revenue runner aid and I think all these metrics show that both the business itself uh is healthy and and and keeps growing um the network effects that that GitHub as a platform has.
2:52:32
Then the third one was that GitH helps to accelerate Microsoft and the most obvious thing obvious is that uh you know Microsoft developers are using GitHub and are using copilot.
2:52:41
So Microsoft itself benefits from the same productivity gains that our customers benefit from and we're sharing a lot of the AI knowledge across uh Microsoft you know within the core AI division Azure AI foundry and all these tools.
2:52:54
>> I'm hearing glimpses of self-improving artificial intelligence.
2:52:56
Microsoft is using GitHub to improve GitHub. I'd love to see it.
2:53:01
Um what where else are people using GitHub Copilot?
2:53:04
Um where are the what are what are the biggest like win conditions or win win use cases in those Fortune 100 companies?
2:53:14
Where's the biggest value being derived right now?
2:53:19
Believe it or not, I think the biggest value is still the core scenario which is you have your IDE open, you know, VS Code or Jet Brains, um, uh, even Apple Xcode and you're writing code and instead of switching between the IDE and and the browser where you have, you
2:53:35
know, all these tabs open and you watch the show and and there's all the distractions, you know, in in your browser and and you try to find the answer to problem you're trying to solve, you just have it right there, uh, where you're building. So whether it's
2:53:45
where you're building. So whether it's code completions that you know predicts to you something that you might have not not have even thought about in that moment or whether it's the ability to go into chat and and ask the question about that code and find a bug or I was working on my blog on on Sunday and I couldn't figure out how I couldn't remember the markdown syntax to to embed
2:54:02
an image and it's just like give me that real quick right and then all the way to agentic scenarios and I know you talked with Anton right before it's this ability to give it a task and then watch it do these things and call tools and it figures out how to install this npm package and and then it looks at the error message and it sees that there's a test case missing. So I think this end
2:54:22
So I think this end to end spectrum where I'm still the pilot and I'm still in charge because I think and I strongly believe that the majority of developers actually want to build something.
2:54:33
They don't want to offload their job to somebody else like an agent or a set of agents.
2:54:37
They want to use these agents to do what they uh uh uh love doing most. >> Yeah.
2:54:43
Can you talk to me about um like where the boundaries of uh GitHub or Microsoft's agnosticism land?
2:54:48
Like you don't make everyone write C, you don't make everyone use uh VS Code.
2:54:53
Um but uh how are you thinking about integrating different models at at Microsoft Build?
2:55:03
Sachi Nadella was talking about the importance of Azure being a place where you could get everything from GPT4 to DeepSeek to Llama to it sounds like XAI is coming on as well.
2:55:13
Um, how are you thinking about uh integration with a broad suite of new tools as they come up?
2:55:21
>> Choice is crucial for any developer tool to win the market.
2:55:23
You can't you can't be in uh in the space of of selling developer tools and and not offer developers choice because if you don't do that they go somewhere else and they will find the choice uh somewhere else.
2:55:35
So since last year we're offering what we call multimodel choice.
2:55:37
Um so we're not only having the open AI models which which are still great and and many people use um as their default.
2:55:42
We also have anthropics models, we have um uh Google's models.
2:55:47
Um we actually have you know bring your own model.
2:55:49
So you can connect from uh copilot uh to open router or lama and and and from there you can go to you know every model uh imaginable as long as it has an API and and a key that you have a um access to and so we think that is crucial and developers will not want us to tell them what model to use.
2:56:07
Like that's just like you know in intrusion in in in my my you know personal freedom.
2:56:12
know personal freedom. um and they they know better what's what's best for them in the same way that at at GitHub we wouldn't tell you use this open source library or you know use this programming language like you wouldn't GitHub wouldn't be what it is today if it had
2:56:25
only you know one ecosystem let's say JavaScript right and and all its libraries um now obviously there's boundaries there um because we have only so many people at GitHub at Microsoft that can integrate all these models and there's a new model every single day sometimes multiple times a day u
2:56:41
>> yes yesterday there were two new models three I think two open source ones >> and all these models need GPU capacity and and you know responsible AI testing and and red teaming and and all that and so we believe it's a mix of we provide models out of the box and you bring your
2:56:57
own model um uh uh through open router and what have you >> fantastic last question >> last question you have over 100 million developers on GitHub have you tried to estimate how many of them are not using any AI tools that just >> uh hanging back saying I I'll I'll I'll
2:57:16
make my code by hand please >> handmade >> none of that AI for me >> it's over 150 million um I think it's still you know less than 50% that use AI on a daily basis and that's just the nature of things right if you look at what are these 150 million developers there's lots of students there uh where
2:57:33
the professor may not allow the use of AI or they haven't make made that step because they're really just trying to solve that uh you know task from from their homework or from from the test but at the same time we see more and more developers making their jump software
2:57:47
development has always been a spectrum right there's those that are still working on cobalt mainframes in Germany there are still companies I think the train system is looking for people that have Windows 95 experience in in 2025 right like that's the like >> any of you new grads know Windows 95
2:58:02
from when from when you were >> but believe it or not even if you you know are new grad or postgrad and you join a company and you have to work on a cobalt project as long as you can then also use, you know, GitHub and and and Copilot and and and AI tools. That might
2:58:14
That might not be the worst job in the world, right?
2:58:18
Because you can combine modern technology and apply to that old stuff.
2:58:21
But what I was going to say is that we have this huge spectrum between the people that are most ahead on the curve, you know, those watching your show and or or talking on the show here and then those that are still having to maintain the systems that power the world.
2:58:32
And we our our mission at GitHub is to to cover all these developers and and enable them, you know, to collaborate between humans and humans and very soon uh uh uh between humans and agents and agents with each other, right?
2:58:45
That's where that's where the platform is going.
2:58:49
>> Well, thank you for your service and congratulations on all the growth.
2:58:50
It's been great chatting with you. We'll let you get back.
2:58:54
>> Thank you for joining. Super insightful. >> Have a great day.
2:58:56
>> Thanks so much for having me. >> Talk to you soon. Bye.
2:58:58
>> Up next, we have Alex Jacobson from 137 Ventures.
2:59:01
We've had Christian Garrett on the show many times for 137 Ventures and we're excited to catch up with Alex >> of ours. I'm excited.
2:59:08
>> We have a great conversation with him uh a couple months ago.
2:59:11
Excited to catch up and chat with him about everything in the 137 Ventures profile.
2:59:17
>> How are you doing, Alex? Good to see you. >> Oh, good. You too.
2:59:19
Sorry we're running late.
2:59:22
>> We we Yeah, we ran a little late.
2:59:22
We got a bunch of very yappy people.
2:59:24
This guy Mark Andre came on. He was talking a lot.
2:59:28
We were asking a lot of questions, so we put us behind, but good to catch up with you. How are you doing? >> Good.
2:59:33
I was just watching, but I was three minutes behind, so I thought I was I had a bit more time. Sorry about that.
2:59:40
>> Yeah, we're going to figure out how to feed you the show so that as soon as you join the room, you're seeing it live instead of with the delay.
2:59:46
But, uh, anyway, thank you so much for joining.
2:59:49
What's new in your world?
2:59:49
What's the biggest news in the 137 Ventures portfolio?
2:59:53
I'd love to just get the general update. Oh. Uh, >> where to start? Well, I'll start. I'll start.
3:00:01
Christian had like a screenshot and it was it was I know, but it was it basically had the 137 portfolio up and it basically looked like the top 10 most in demand private companies.
3:00:13
And I was like, "Oh, that looks like a pretty good portfolio to have."
3:00:16
So, you guys have been everywhere. >> Yeah.
3:00:20
I I mean we have we we're building this general concept of mag seven for private >> and so we have there's this idea of there's these companies that grow indefinitely in the public markets and they've built themselves to do that in the public markets.
3:00:36
The strategy for doing that in the private markets is different because you need to do different things in different ways.
3:00:43
So SpaceX has led the way on this because the they give employees equity and they then also run tenders regularly so that that equity can become liquidity. >> Mhm.
3:01:00
And the important the important bit of that about that strategy is that the price at which they're providing liquidity is materially lower than what the market would pay in a fully liquid public market.
3:01:17
And so you can say, "Oh, that's terrible.
3:01:18
The employees aren't getting the right thing." But that's not fair.
3:01:22
The actual thing that's happening is when employees are issued uh equity when they get hired, they know it's going to go up because SpaceX keeps growing.
3:01:31
SpaceX is one of all these companies have the property of having a huge amount of power in their market and a even larger TAM.
3:01:39
And so you can you can understand this indefinite growth.
3:01:45
And you can talk about for the public companies or the private companies, but the general thing that you're looking at is this combination of power and large TAM.
3:01:53
And so in a private in a private market context, all these companies need to hire people to go capture that TAM.
3:02:01
And the value of these companies keeps going up.
3:02:04
And the strategy is to give the employees certainty that the equity they've been issued will be worth a lot more in the future.
3:02:11
That's harder to do in the public markets because everything's perfectly priced and so you don't really know if the stock is going to go up.
3:02:19
You think so, you hope so, but it's harder to tell.
3:02:20
In the private markets, the nice thing is you control your price and you can if you're just if you run your process properly, you can have this very deterministic outcome for your employees, which I think is super powerful.
3:02:34
>> We talked to Harley at Shopify about the benefits of being public.
3:02:37
You have uh liquid currency for acquisitions. It it it sets him up.
3:02:42
He referred to it as being in the major leagues.
3:02:44
Now, uh, give me the pitch for staying private as long as possible.
3:02:50
>> I mean, I don't think SpaceX isn't major league. >> Yes, I agree.
3:02:58
>> So, there's this >> what are the benefits of staying private?
3:03:02
>> The I think the big one is hiring.
3:03:02
Okay, >> this is that's the thing that I think people underestimate which is that if you can issue people private company stock at your >> 409A >> and then you and and you control the price it keeps growing then this is all a much more deterministic thing and it's super powerful to be in these companies because the nice thing about these companies like there's this funniness of uh they're always underpriced.
3:03:34
So there's always investor demand for them. >> Yeah.
3:03:37
>> So as long as they as as long as >> So you just have this positive feedback loop of there's always investor demand for them.
3:03:43
So the investors want to buy more and the stock price keeps going up.
3:03:49
Which means the employees can look at these companies and go, "Oh, >> this equity is really worth something because they know it's going to go up."
3:03:56
If you're getting public companies stock, you don't get that. >> Yeah. Yeah.
3:03:58
And there's not the volatility that comes with I checked my portfolio today.
3:04:01
I'm down a little bit just because oh there's some weird tariff thing going on in some foreign country and like how does that affect my business whereas yeah if you're in the private market you don't have to deal with that.
3:04:11
Um what about these new what's your take on some of these new initiatives to uh give retail investors access to private company shares or put private company shares on chain and create tokens and SPVS and all these like like different financial engineering efforts to uh bring to give retail traders access to private market company stocks.
3:04:37
What's your take on all that?
3:04:41
We've been seeing people trying to do this forever.
3:04:44
>> It's an ongoing thing of, oh, we find it inconvenient that these companies are private, so we're going to try to do things to make them seem more like public companies.
3:04:52
But the one of the big values of being a private company is controlling who your shareholders are >> and controlling your pricing.
3:04:59
And so, uh, if you're trying to stop that from happening, that's, you know, maybe that's an opportunity.
3:05:09
And maybe you can force one of these companies to be a de facto public, but that's not a service.
3:05:17
If they want to be public, you know, there's this mechanism called the public markets to do that. >> Yeah.
3:05:21
What what about a higher level of abstraction?
3:05:23
Like I I believe I believe >> gold I mean the other big thing is sorry >> you know certain private companies don't want to be public because they don't want to be on this sort of regular reporting cadence.
3:05:34
They just don't feel like they're ready for it.
3:05:36
But uh the idea of like taking private companies, putting them on chain, letting private company shares, putting them on chain and then just letting anybody in the world by access buy access, you know, buy them, but not giving them any of the information that allow that that that makes the the public market so beautiful, which is like anybody can read this information and you can come up with a decision on your own.
3:05:56
And there's like rules and frameworks to make sure that people aren't insider trading and things like that.
3:06:02
And so it's like who's benefiting here?
3:06:04
It's like retail has a potential to get even more hosed.
3:06:08
Uh and and then the companies are having to deal with shareholders that that now have an opinion about how they're operating the company.
3:06:17
Uh but none of the real rights associated with with owning the shares.
3:06:22
>> Let let me be charitable to these people.
3:06:23
There's a real thing of the only people who get access to these private MAG7 companies are institutional LPs who invest in our fund or funds like ours. >> Yeah.
3:06:34
And you know, we're not we're not we don't have retail investors in our fund.
3:06:40
Um there's there's a sort of in the manager class, there's something we refer to as retail, which is there's a longer tale of of wealth that is now trying to play >> in and invest in these things.
3:06:52
So there's some that is in some sense a longer tale, but there isn't the people who have who are public markets players.
3:06:59
There aren't non-institutional players in the game really.
3:07:03
And there's something real about giving people access to the growth that these companies are going to have.
3:07:09
There's re and it's unfair in some general sense that that these retail investors don't have access to this growth.
3:07:17
And I so I think there was some amount of institutional design around how do we give them access to this growth but turning these private companies into public companies is not necessarily the way the way to do that. >> Yeah.
3:07:31
It's almost like like what if like like what if uh the Yale endowment was publicly traded?
3:07:37
>> It's like then I'd have broad exposure to a bunch of venture capital firms which have exposure to a bunch of private companies and you know it still just rolls up to just a few line items on the cap table.
3:07:47
I'm not you know this random uh like retail trader doesn't isn't actually on the cap.
3:07:52
It's also it's also disingenuous to say that like everyday people don't benefit from the private MAG7 as you've described it because it you know a lot of venture capitalists raised from pension funds.
3:08:06
It's teachers and firefighters and things like that who are are actually you know benefiting from the performance.
3:08:12
>> I mean I I think there there's a pension we're definitely in the b pension funds are definitely beneficiaries and that's very real.
3:08:19
But I I don't know how much of the like there's definitely these, you know, those types of pension funds that are out there.
3:08:26
Um, but there's lots of people who aren't in these sorts of pension funds.
3:08:32
>> Like I think you're right.
3:08:32
There's there's definitely that that sort of universe is taken care of.
3:08:36
But I think there's plenty of people who aren't in that type of pension fund either. >> Yeah.
3:08:43
>> And totally >> if and and generically they're in the pension it's in a pension fund.
3:08:47
They're not able to say, "Oh, I would like more exposure to privates." >> Yeah. >> Right.
3:08:54
So, at a at invest at the CL there's there I I understand the feeling of that there's these people are underserved in some way.
3:09:03
It's not they're not my customers, but I get the feeling.
3:09:07
>> I just think we need to design for It is funny to think about if if if a bunch of Stripe shares were dropped on Salana, like what Stripe would actually trade at because I would guess that it would look like it would look like it would be like the most insane pop and then suddenly it's like, okay, if you want to buy Stripe on chain, you got to pay like $400 billion or something or a trillion dollars, right? You could.
3:09:32
>> And for some of the even bigger like me like like potentially like me uh private companies, it could be even crazier. >> Yeah. Yeah.
3:09:39
Um >> I mean, >> yeah, >> there there's the whole Elon universe of companies. Yeah.
3:09:43
You know, we we have a sample of one of them that's public. >> Yep.
3:09:47
We know what happens there.
3:09:47
Uh speaking of that, I mean, he was talking loosely about uh taking Tesla private at one point.
3:09:53
uh that you know obviously didn't materialize but is there a world where the private markets evolve to such a point and it becomes so elusive that you see a takeprivate of a company specifically to get back on that track or or once you IPO has the ship sailed and it's gone forever.
3:10:16
>> I mean I'm I live in the private markets.
3:10:18
I like the private markets.
3:10:18
I think there's a huge amount of value of being here in the private markets and so I'm definitely talking my book.
3:10:24
But the the the big thing that has changed over the past some number of years is how big the private markets now are. >> Yeah. >> Right.
3:10:36
So we so the how much we can invest in SpaceX or Anderl or Gustoa or any of these companies has gotten to be large numbers.
3:10:44
And so, >> you know, there's this argument of when you're public, you have this currency that you didn't have because the public markets have more money.
3:10:53
And I don't think that's as true anymore.
3:10:56
I think that there's this real chance that you could decide, I just want more control.
3:11:02
I don't want to deal with this regulatory nonsense and be private.
3:11:07
there is this they're both it's a it's a regulatory ritual but it's not actually a different company and you might want to just have a different regulatory environment.
3:11:16
>> Yeah, I'm thinking specifically about Snap. Uh Snap had earnings. They're down 17% today.
3:11:19
They live and die by the earnings call.
3:11:22
Uh meanwhile, Apple's up 5%, Meta Platforms up 1%, Amazon's up 4%.
3:11:27
and and it's only a$ 13 billion company that the capital exists and there's always been this narrative like it's easier to turn the cruise ship when you're in the private markets.
3:11:36
You go to just a few investors, you say, "Hey, we're going to miss earnings really bad for a couple quarters, but then we're going to build something new." Um, I don't know.
3:11:43
It's a >> You could have three snaps or one perplexity. Wow.
3:11:51
>> I mean, the the part of I mean, the hard part is these things are now priced >> and so you're going to take it private and you now have to go resell this to the private capital markets >> who have looked at this in the public markets and gone, >> well, that didn't look right.
3:12:06
Uh, and so I think there there's a hard sell of going to the private markets and selling, you know, selling Snap in the private markets.
3:12:17
I think it's entirely possible that it could do better, but >> you know, the they have to go, they have to sell it.
3:12:24
It has there's a founder story.
3:12:26
I mean, >> I think we can like sit here and script it and maybe we can make it work.
3:12:30
But >> an exciting story.
3:12:33
I I think the best example is probably Dell, which went through Take Private and then and then uh later went back public at a much higher price.
3:12:41
Um but I mean these stories are extremely few and far between. >> Switching gears.
3:12:46
Uh I wanted we had Dan on from Armada earlier this week. Super exciting company.
3:12:52
I know uh you guys have been involved from uh probably before the company was created.
3:12:57
wanted to get your view on on the opportunity and and what made you so bullish >> uh uh now or back then? >> I mean both.
3:13:11
I mean we we got we got uh last time we talked I think we got a good good overview but it was kind of hearing the kind of landscape and and the initial catalyst was was interesting.
3:13:22
I mean the the the original version of this is if you think about what a data center is, a data center is a point source is is trying to maximize the value of a point source of connectivity and power, >> right?
3:13:37
That's like structurally what it is.
3:13:39
Uh and so you know power has is available at different prices at different places.
3:13:45
Fiber is available at different pl at different levels of reliability.
3:13:49
How many fiber points do you have?
3:13:51
Are they really one or two?
3:13:53
Like it's doing the underwriting of what it's actually a lot of work to make a data center.
3:13:57
But the whole premise is that you have sufficiently reliable and large power and sufficiently reliable and large connectivity. SpaceX changes that.
3:14:05
So SpaceX says actually there is no longer this concept of a point source of connectivity.
3:14:12
It's available everywhere. Mhm.
3:14:17
>> Uh and in any one point it's not, you know, it's not as good as a as fiber, but the world's pretty big.
3:14:24
And so the aggregate bandwidth of Starlink is huge even if the available the availability in the square foot you're in is not as big as holding a fiber in your hand.
3:14:36
Uh and so the insight is okay well SpaceX gives us opportunity this opportunity to rethink how we do connectivity.
3:14:45
So does that mean we can think rethink how we think about power?
3:14:52
>> And the interesting thing is if you're looser about connectivity now you can look at power in a bunch of different places and you can say hey there's solar everywhere.
3:15:00
So now you just simply put out a solar panel and a dish and you're live.
3:15:04
uh and the and is the solar panel enough for the amount of compute you want to do? Maybe, maybe not.
3:15:10
But that but that's the beginning of the conversation.
3:15:14
And then, you know, so in the original design for this, it w I sketched out a uh shipping container that unfolds solar panels on a roof.
3:15:21
And I figured out that you need a lot of solar panels to power a rack, but you can do it.
3:15:30
But and so that's but that but you know, the math on that actually worked.
3:15:32
So it was like a 3% IRRa when you did the model and the 3% IR isn't glorious but it was just a model and then you have the testing.
3:15:41
the testing. So we're saying oh this is is sufficiently interesting that it's worth testing and then when we then we got Dan and Dan is this phenomenal has has phenomenal network has phenomenal sales and his solution wasn't hey let's build it and sell sell cloud his
3:15:58
solution was calling people he knows and asking them what do you think because that's how he works and so we get on the phone with the CTO of Ramco somewhat of a surprise to me so I'm suddenly on the phone with this guy who is >> San Francisco San Francisco company, right? >> Yeah. Founded in San Francisco, >> Yeah.
3:16:15
Founded in San Francisco, >> right?
3:16:20
>> West Coast Tech wins again. >> Yes.
3:16:23
And so I'm suddenly pitching this to this guy.
3:16:26
Uh and the insight is well there's this other problem.
3:16:31
You know, the underlying story that I just told you is about stranded energy.
3:16:33
There's stranded energy all over the place.
3:16:36
Let's use stranded energy.
3:16:36
But the thing that's happening on an oil platform is they're stranded data. >> Mhm.
3:16:42
>> And so these these these oil platforms produce huge amounts of data that get effectively dropped on the floor. >> Mhm.
3:16:50
>> And they have some amount of compute that is in in a closet somewhere that some guy on the platform manages. Uh >> yeah.
3:17:00
>> And Hallebertton support and Hallebertton sells him the software.
3:17:03
It's like the the actual architecture of that market's crazy. >> Yeah.
3:17:08
>> And so it's like, oh, wait, we could do better.
3:17:11
>> Y >> and so if we if we provide a cloud at the at this locus of stranded data and stranded energy and and a global communications, we can create a lot of value. >> It's great. Very exciting.
3:17:28
Well, well, next time you join, we'll have you on for an hour. >> Yeah.
3:17:33
Yeah, we can go so much deeper.
3:17:35
Thank you so much for stopping by. We'll talk to you soon. >> Great to see you. >> All right. >> Hang out soon. Bye. >> Cheers.
3:17:41
>> Up next, we have Nick from Relet coming into the studio.
3:17:45
I think we got to get the ready.
3:17:47
We got to get the gong ready.
3:17:50
Jordy, you want to take this one? You want to hit this? >> I'll take this one.
3:17:53
>> I think I hit the last one, but let's bring him in. Let's play some music.
3:17:56
Let's play some soundboard. Let's bring in Willlet. How you doing? Welcome to the stream.
3:18:02
Thanks so much for joining.
3:18:04
Sorry we're a little bit late. How you doing? >> Good. Check. Check. Do you hear me? Okay. >> Oh, hear you. Great. >> Live.
3:18:09
>> Uh, is it Nick Nicholas? Is it Roulette or Relay? >> Roulette. Roulette.
3:18:14
>> So, the American spelling. Yeah, >> there we go. Okay.
3:18:16
I wasn't sure if it was French.
3:18:17
Uh, anyway, give me the update. Give me the news.
3:18:19
Give me the overview of what you're building. >> Awesome. Yeah.
3:18:23
Excited to be here, guys.
3:18:24
Thanks for having you on. So, thanks so much.
3:18:26
Uh today we're announcing our $70 million series B uh co-led by Andre Harowitz and Iconic.
3:18:32
>> Congrat Oh, that was good timing. Good timing. >> Congratulations. >> Boom. Thank you.
3:18:39
>> Uh give us a little prehistory on the company. Uh when did it start? How's the growth been?
3:18:42
And uh key customers, how you're building and how you're thinking about uh solving AI native ERP. >> Yeah.
3:18:51
Um so we've um so quick backstory also myself.
3:18:56
deeply um accounting and finance uh verse uh sort of full background there.
3:19:01
>> Started this company uh roughly three and a half or so years ago. >> Mhm.
3:19:05
>> Very much in stealth for a very long time.
3:19:07
As you can imagine, a full-on accounting system or ERP is not a small feat to build.
3:19:11
It's a lot of surface area.
3:19:13
Um these are very entrenched systems traditionally dominated by Netswuite, Oracle, SAP, these type of names.
3:19:20
Um so we uh yeah we're very fortunate to to have had a stellar team of accountants and engineers building and building.
3:19:25
Um and then we came out of stealth uh last summer roughly a year ago and things have gone vertical uh since then.
3:19:32
So uh it's been an awesome journey.
3:19:34
Uh raced our series A here um just a couple of months ago, 3 months ago, 12 weeks back and um yeah back to back here with a B.
3:19:43
>> What is it what does it take to get a company to rip out their existing ERP and and bet on a new company? Right.
3:19:49
Like that's the real challenge that >> I was about to ask are people ripping out Oracle and SAP and Netswuite or is it uh I'm upgrading from a spreadsheet. >> Yeah, great question.
3:19:59
So we are getting 70% of our customers today coming from software called Quickbooks and Zero. Sure.
3:20:05
Um and then 30% of our customers coming from Netswuite and Sage Intact. >> Okay.
3:20:10
>> So it's very much a mid-market focused ERP software.
3:20:12
ERP software. Um key reasons why people uh use Relet or want to buy Relet despite us being newer to the market over a legacy player is um number one uh we have super strong native integrations that really suck in all that key upstream information that you need for
3:20:29
AI automation um really seamlessly into our platform and then our automations on top produce reporting that's just unmatched in the market um and that would yeah leads us eventually to getting customers like Windsurf one of the fastest growing AI companies in recent history's mind. >> Wow. >> Wow.
3:20:45
>> Um and and others uh to trust reallet over their current systems.
3:20:49
>> Real now used by Google and Cognition potentially.
3:20:51
That's the best part about a zombie acquisition.
3:20:53
You get potentially two new customers >> maybe.
3:20:57
>> Anyway, uh I want to know about um do you want to put a chat box in your product or do you want to use AI behind the scenes and not surface that to the customer?
3:21:09
Whenever I I see tools like this, I think I love the idea that you're using AI, but I don't want to open it up every day and prompt, hey, clean up my ERP.
3:21:18
I want you just to do that, and then when I show up, I want it to look like a nice groomed garden. >> Yeah, love it.
3:21:24
Um hopefully a bit of both, actually.
3:21:27
So, >> um for very important for our controllers, accountants, and CFOs, um having a human in the loop on some of their AI processes is actually really important and a positive.
3:21:36
So yes, these are background processes uh but uh always with a human in the loop for the most critical ones um there.
3:21:43
And then for you as a business owner specifically or uh strategic CFO or an investor, >> you want none of that detail, right?
3:21:50
You want to go in in a clean box, ask a question, get the information you need, move on.
3:21:55
So we're building both to both ends of these spectrums.
3:21:57
Um, and you really need both to be successful here.
3:22:00
And >> I guess my question is a lot of people want to go, a lot of CFOs, a lot of investors want to go into the ERP, the accounting suite, and get information, but I feel like 99% of the time they're asking for the same thing.
3:22:12
They want a really clean balance sheet, a really clean income statement, a really clean cash flow statement, and they don't want to think of a prompt like, "Oh, I want let me describe to you what a balance sheet."
3:22:24
It's like, I want a balance sheet.
3:22:25
I just want it to be accurate and I want everything to be tagged correctly.
3:22:28
I my prompt is don't make mistakes.
3:22:30
So talk to me about the trade-off there. >> Yeah. Yeah. Great question.
3:22:33
Um so definitely there are these pre-anned reports.
3:22:37
Um you don't want to be teaching an AI to rebuild your income statement every single sorry every single time.
3:22:44
Every single time the same way.
3:22:46
Um and so 100% agree there.
3:22:46
Um there are a lot of more custom analyses though that you want if you're a professional like specific for your business maybe track also some non-GAAP metrics and and and non-accounting metrics on the financial side that is really handy to just describe it in natural language and get what you need. >> Yeah.
3:23:05
And then the other question is like I feel like oneshot prompting in this context is even less relevant because if I if I'm design if I'm designing a new uh non-GAAP metric I probably want to say like set up a workflow so we produce this every month and that it's just on >> like vibe adjusted EVA. >> Exactly.
3:23:26
>> Exactly. Vi I want you I want you Vibe code and adjusted DV but then I want it to be the same every month because when I've reported non-GAAP metrics in the past like churn I mean even Dow Mau that's a non-GAAP metric but like you want it to be accurate and you want it to be classified the same way because there's often these times where you change one underlying thing in your uh in your product and then that flows to a
3:23:48
complete change in the non-GAAP metric and then you're going it was non-GAAP the whole time don't worry don't get mad at me investors I know you thought that that was never going to change, but the metric changed and and it's actually not
3:23:58
that different for the we're just looking at the business in a different way now, but talk to me about like how AI can improve the development and ongoing maintenance of non-GAAP metrics. >> Yeah, great question. So, um there is >> Yeah, great question.
3:24:10
So, um there is definitely an element of like repetitive adjustments uh certain things that can even be codified outside of AI in terms of certain customizations of your uh non-gap metrics.
3:24:21
ARR is a very prominent one for software AI businesses, recurring revenue businesses for example.
3:24:26
example. Y >> um and so there uh yes it is definitely uh something you can do basically in the UI customize your metrics the way you want it in a repeatable fashion but there is definitely also an element of certain workflows and I almost call it openness to human interpretation where
3:24:43
you need the need these more like LLM driven uh workflows that help interpret maybe look at your chart of accounts look at historical transactions what happened there and try and make sense of things and that's where AI today is very powerful But again, you do need usually a human in the loop to do these repeatably and reliably. Uh just given
3:24:59
Uh just given the mission criticality of the workflows, >> what's next?
3:25:05
What's more important for you?
3:25:06
Uh you're in the midm market.
3:25:06
Do you want to go downward, upward?
3:25:09
Do you want to expand and offer go multi-roduct?
3:25:13
What what's most interesting to you? Yeah. >> Yeah.
3:25:17
Um so for us, uh more of the same.
3:25:21
The opportunity that we have in the mid market is insane.
3:25:23
the amount of customer love we're getting um and product quality that we have with the reviews that we have combined with like really entrenched and frankly universally disliked ERP systems.
3:25:34
You'll be hardressed to find someone that truly enjoys using their accounting system or ERP that creates a huge influx of just demand uh on on the product and and the company.
3:25:45
So what we're going to do with the money that we're raising is double down on product, build more of the same additional features, um go up market from here, >> uh with the money that we've raised, we have a stronger balance sheet to like cap capture even bigger uh names and logos that can work with us.
3:25:58
And then the other piece is just in uh investing heavily into our customer success and on on boarding motions.
3:26:04
We're just like we work with very talented accountants in these teams uh to help onboard help onboard their plat their platform into their systems and we're massively expanding these teams to just absorb to the demand that we have. >> It's awesome.
3:26:17
What a what an opportunity. It's great. >> Yeah.
3:26:21
>> Uh congratulations and good luck.
3:26:21
Many people have have tried and and failed to rebuild the to build a new ERP, but >> there was a there was a gap in the pre AI era where there were a lot of people that took a run at it and it was it was a little rough, >> but finally >> the mind share is there the opportunity is here.
3:26:37
It's it's really exciting. >> Amazing. >> Congratulations. Congratulations.
3:26:41
>> We'll talk to you soon. Have a good day. >> Cheers. >> Thanks for having us.
3:26:47
>> What else we cover ARP?
3:26:47
I didn't like the way he was talking about Netswuite.
3:26:51
I would die for Netswuite. I would die for SAP.
3:26:53
I love I love I love all XRP systems equally.
3:26:57
Like my children, I like them all equally.
3:27:00
>> Um anyway, uh Perplexity, you mentioned it briefly.
3:27:03
It's now worth almost 15 times JetBlue.
3:27:07
They raised another $200 million billion a little under.
3:27:12
Yeah, they think Snap's at 13, but Perplexi is now at $20 billion.
3:27:18
It's unreported, but it's been leaked by Arur Rock.
3:27:21
Who knows if it's true, but he usually gets it right.
3:27:23
So, we're chatting about it here.
3:27:25
138,000 people saw the news.
3:27:28
Uh, I'm sure Arvin will comment if it's fake news.
3:27:31
But, uh, in other news, what else do we have?
3:27:34
Um, we wanted to send our regards to the Doge staffer who was assaulted or or gotten a dust up with someone who was attacked. He stepped in.
3:27:45
Uh and uh fortunately we saw another picture that he has uh been cleaned up and healed and seems like he is on the mend and so um sending our best to Mr.
3:27:57
Balls >> rough but sounds like he acted with uh asourage as poster would say bravery and courage.
3:28:06
So >> yes, >> back at it.
3:28:10
>> That's pretty much everything, Jordy.
3:28:10
I don't know if there's anything else you want to cover >> other than send it.
3:28:14
>> Maybe leave five stars on Apple Podcast and Spotify. >> Maybe. >> Thank you.
3:28:19
If you've been in the chat today, I like this post from Aiden Beltskies says, "Timeline not in turmoil.
3:28:27
John and Jordy pulled off some S tier handshakes during the Figma IPO liveream.
3:28:32
>> This is what it's all about, boys. Keep it up." Thank you from the chat.
3:28:34
That's on the X chat and Mark is >> live handshakes. He's >> laughing. >> High stakes. >> Nothing. >> High stakes.
3:28:42
We've seen some We've seen some viral botched handshake/dapups.
3:28:48
>> You got to have a shared language.
3:28:48
Stick to the default handshake. It's Lindy. It's not going anywhere.
3:28:53
>> Do you think it's better to look at the person's eyes or the hand coming in?
3:28:58
because I think it might be more about like a like kind of you don't actually you want to keep the >> I think it's kind of coming in.
3:29:04
>> It's kind of like a a game of rock paper scissors >> and so it's a high stakes game.
3:29:09
>> But but the optimal the optimal strategy is to just stick with the handshake and never deviate.
3:29:14
Never never uh never doubt yourself >> with one of these.
3:29:19
>> Make it very clear from early on you're coming in with the handshake and you're not blinking. It's a game of chicken.
3:29:22
So if you come in with it doesn't matter if you come in with knucks or you come in with with the I'm going to hit you here. Doesn't matter.
3:29:29
As long as you stay here forever, they will see that you're not backing down. They'll conform. >> Yeah.
3:29:36
>> And you'll assert your dominance. >> Yeah.
3:29:37
So go out into the world and uh practice. Practice live. >> Yeah.
3:29:42
I mean it's tr it is tough because I hit people with all sorts of different things.
3:29:44
Every time I go to the bathroom, Ben hits me with the knuckles on the way back. It pumps me up.
3:29:48
Gets me back on the stream. >> Back in the game.
3:29:50
Anyways, thank you to John Xley for moderating the chat. Fantastic work today.
3:29:54
Thank you to Gabe for chiming in with hilarious comments all stream.
3:29:58
Thank you for Mark for watching and enjoying the stream.
3:30:00
And we will see you guys tomorrow.
3:30:02
Tomorrow is going to be an absolutely insane day.
3:30:04
We can't say why, but it's going to be insane.
3:30:07
>> Something's going to happen tomorrow. >> And uh I cannot wait. >> I'm pumped. It's a stacked lineup. We will announce it.