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[Music] [Music] Mics are hot. >> You're watching TVPN.
5:23
>> Today is Monday, September 8th, 2025.
5:23
We are live from the TVPN Ultradome, the temple of technology, >> the fortress of finance, the capital of capital.
5:31
Um today there is uh a chart that is tearing up the internet about AI adoption potentially going down. This is from the census.
5:42
Uh the census says that the AI adoption rate by firm size they do this poll every two weeks.
5:48
Um and Apollo the uh giant private >> Apollo management. >> Yeah.
5:58
Apollo um on their Apollo Academy blog has a post AI adoption rate trending down for large companies.
6:05
The US Census Bureau conducts a bi-weekly survey among 1. 2 million 1. 2 million firms.
6:12
And one question is whether a business has used AI tools such as machine learning, natural language processing, virtual agents or voice recognition to help produce goods or services in the past two weeks.
6:24
Recent data by firm size shows that AI adoption has been declining among companies with more than 250 employees. So >> is that good?
6:36
>> It's I mean I think >> it's good for your job.
6:39
>> There there are a bunch of different reads on this.
6:41
So I think it potentially could be good. I don't know.
6:43
Um I'll walk through kind of my my thinking on it.
6:48
U but there's a bunch of interesting stuff in here.
6:50
So, um, so this, uh, like the charts going viral because kind of everyone's been feeling that AI has been like overhyped and like the valuations are crazy and so people are hunting for top signals as we have, you know, a month ago. >> Top signal enjoyment.
7:05
We put out we put out uh, we got to play the video. >> Oh yeah. Yeah. The hype cycle. >> It's released. >> Oh, it is. It is. Yeah. Let's pull that up. Let's pull up.
7:14
>> So, let's pull up the video.
7:16
>> The video that uh, Tyler just posted.
7:17
Did you post it from the TVPN account? >> Yes. of the hype cycle. We'll play that.
7:20
But people have been hunting for for bearish signals about AI because it feels too good to be true.
7:26
Everyone's getting rich and you aren't.
7:28
It has the same sort of economic trends as the as the crypto boom as a few other booms.
7:33
And so um people are are are hunting for data points and this is one of them.
7:37
But let's first review the Gartner hype cycle video that we just put out.
7:43
>> I think Nvidia is undervalued.
7:47
It may not mean nothing to y'all, but understand nothing was done for me.
7:50
So I don't plan on stopping at all.
7:53
I want this forever mind. Never mind. Never mind.
7:58
I shut this down in the mall and telling every girl she the one for me and I ain't even planning the call. I won't forever mind. Mind. Yeah.
8:15
So, everyone's been hotly debating where we are in the Gartner hype cycle.
8:20
It feels like >> some people call it the TVPN hype cycle. Yes.
8:23
>> We'll give Gardner their credit for this one.
8:25
Um, so people have been hunting for for potentially bearish signals, bearish data points.
8:29
Uh, there was that uh that uh result from meter that showed that developers that were using AI uh coding tools were actually less productive.
8:41
They thought they'd be 20% more productive.
8:43
>> And I saw something I saw something else.
8:44
I I don't know if this was uh misinformation, fake news, somewhat real or or or just anecdotal, but there was somebody that was saying uh uh devel developers are producing more like a lot more code, but but like an order of magnitude more security vulnerabilities.
9:01
>> Yeah, it's something like they're producing twice as much code, but 10 times as many uh 10 times as many security vulnerabilities.
9:06
And I know the post you're going to talk about now, it is in the stack, but it's deep. >> There's a post.
9:10
I'm going to I'm going to try to find it, but it's it's somebody searched like vibe coding cleanup specialist and there's people on on LinkedIn now that are that are finding employment around cleaning up vibe coded product.
9:23
>> And so if you're worried about losing your job to uh to vibe coding, pivot to vibe coding cleanup, the bull market.
9:30
There's always a bull market somewhere.
9:31
>> Um guys, can we pull up the chat on the uh TV if possible?
9:34
Um anyway, let me uh run through this.
9:38
So uh from the data uh the chart is going viral because it's dropping off and it looks bearish for AI and thus for tech America for humanity broadly.
9:50
Um everyone is saying please consult the Gartner hype cycle graph.
9:53
Uh there is a question on where we are in the Gartner hype cycle.
9:58
Um I have been saying that maybe we still have a ways to go up.
10:02
I I can't tell if I'm on the left side or the right side of the graph at this point.
10:06
like I've kind of already been through the trough of disillusionment.
10:09
And so >> when was that for you?
10:13
>> That was probably 2024.
10:18
2024 was was when it felt like everyone was saying AI is so insane.
10:22
AI >> you were you were going like this in the mirror like the Joker >> a little bit because uh you know AI is so insane.
10:30
so insane. But then you know you go back to the chat GPT moment that was 2023 >> uh Whimo you know really like rolling out to general that was 2023 >> there there there wasn't as much there was a lot of hype but there wasn't as much like actual progress it felt like
10:45
it felt I don't know um so maybe now we didn't have 5,000 AI agents for blank >> I don't know just just as I process the last few weeks I feel like I'm climbing up the slope of enlightenment I don't feel like >> posting red posting and showing how he's getting value across >> that feels like the plateau of product. >> That feels like
11:04
>> That feels like >> that that's plateau.
11:05
We're plateauing and we're productive. >> Exactly.
11:08
And and even the narrative of oh is AI progress plateauing?
11:10
That's not is it going to crash? Yeah.
11:13
That's not the trough of disillusionment.
11:15
That's the plateau of productivity.
11:17
So anyway, people people love to, you know, give their takes.
11:21
Anyway, >> I think that I think the um the real an interesting study, I'm sure there'd be flaws with it, but but if you went to companies and you'd say like, how much would I have to pay you to not use AI for the next 12 months >> across your entire company? >> Yeah.
11:40
>> I I think you could argue that like in engineering orgs specifically in terms of like things like fraud detection and areas that uh there's probably a lot of money, but it's very possible that in certain organizations.
11:52
But then but then you got the question of like, okay, does trans, you know, does like sales call transcription count as AI? Right.
11:59
>> Well, I will tell you, Jordy, because um 90% of American businesses told the census that they do not use AI at all, including transcriptions.
12:11
>> So, they would take a lot of money to >> they would take a dollar.
12:14
>> They take a dollar to >> they would take any amount of money because it's all net positive.
12:16
But there's a lot going on in this data that we should run through.
12:20
So, um, >> and I thought I thought I thought people didn't trust data from >> the census.
12:29
>> Well, yeah, the the Arazzian has a good uh a good take about the size of the data set and how spend and where AI is actually having an impact.
12:36
We'll run through that, but uh so first off, small firms haven't declined even by this metric.
12:43
So, if you're a firm that has one to four employees, you're a very small firm, you're still increasing in in in AI adoption.
12:53
>> Should we uh should we switch over to these?
12:55
>> By the way, guys, we are testing some new microphones.
12:59
>> We can walk around the ultra >> boys wanted the the mics back. They're coming back hot.
13:04
>> Daniel, we can't top till Darkest ships ships his book.
13:08
>> He already He already shipped his book.
13:09
I thought I I I got a preview.
13:09
It was Yeah, that doesn't make any sense. I don't know. Doresh's book. >> It's released. >> Oh, yeah.
13:16
That came out on on Straight Press.
13:18
Like we had them on the day it was like on sale, right?
13:22
>> Oh, maybe it hasn't shipped, but I got an advanced copy. I printed it out.
13:24
Um maybe maybe it hasn't fully like actually delivered, but uh the first time we had him on the show was because of >> Yeah, it's still a pre-order. No problem, John.
13:35
>> Still a pre-order on >> Oh, it's still a pre-order. Okay. So, okay.
13:37
>> It's going to be released on October 8th.
13:40
So, um, >> yeah, market Nvidia, please don't nuke until, uh, until Dark Cash can get the book out. >> Yeah.
13:46
Uh, so, uh, the main headline number in this census data set is that firms with over 250 employees are declining in their self-reported AI usage.
13:57
Um, it's not a huge drop.
13:57
It went goes from like 12% 14% to 12%.
14:00
It's a little blip, but the chart does look scary. We can pull it up.
14:05
It's like the third slide.
14:06
Um, so I think what's going on here is the following.
14:09
Small firms see bottomup adoption of AI tools like can I literally directly use chatpt for this?
14:18
Like you run a twoerson company at various times.
14:21
A lot of times you're just thinking, okay, I got to I got to select an accountant or something like let me like chat it, right?
14:27
And and and and this kind of bottomup adoption just happens very naturally.
14:31
Whereas, if you're in a larger firm, you're going to get sold on some crazy AI transformation mumbo jumbo uh needs a whole training program and is everyone up to date up to speed at the same time.
14:44
You need a bunch of consultants and they sort of misunderstand what AI even is and they fall into a bunch of weird analogies like we'll hire a hundred AI agents and like that's very different from just hey Google exists, chatt exists, we expect you to use both at this company.
15:00
Um, and so this is where I thought the data was really, really, really weird because if you look at the data for chatbt adoption, um, we're way off of what this 10% number is for for business adoption of AI tooling.
15:17
So um there so this this data says that about 10% of companies are using AI at all at work which is crazy because there was a data point back in March that said 52% of US adults use AI large language models like chatbtd.
15:35
So think about what that means.
15:37
It means like out of a 100red million Americans there's 100 million Americans that that are like yeah I use AI tools.
15:43
Like there's maybe 200 million adult Americans or something.
15:45
And there's 340 total Americans, but let's call it let's call it 100 million Americans that are using AI tools just like Americans. >> Yeah.
15:53
Chat GPT what kind of Americans? The Chat GPT Americans.
15:55
Um and then 80 million of those are just like no not at work though. >> That makes no sense. That makes zero sense.
16:02
And so >> doesn't work like that.
16:04
>> There's got to be something weird going on with this data.
16:05
And I think it's a matter of the definition.
16:07
And so the census defines AI is like it makes no sense that 10% of companies would fit this definition.
16:14
What did what did uh you said AR at RAM was chiming in on this. >> Yeah. Yeah.
16:19
He we have he has a post in the in the in the deck. >> Yeah.
16:22
So the definition >> Yeah.
16:24
He says these sample sizes are extremely small for these large firm breakouts extremely volatile survey to survey which is why he's using the six survey moving average.
16:31
Business AI adoption is back up in the most recent read.
16:36
So I feel like that's important.
16:38
Um I yeah it's one of those things I feel like payments providers like like ramp right uh would would have better insight here just like obviously ramp is a sample of companies in the United States but it's at a scale now where they could see like okay what percentage of companies are paying for any type of AI products y >> that's better than are you adopt are you using more or less AI than you were last time. >> Yes. Yes.
17:06
Um the the question is like how power law distributed is it right and then >> so so the ramp estimate of share of US businesses with paid subscriptions to AI models platforms and tools is 43%. >> 43%.
17:21
>> The US government's estimate is 8%.
17:24
>> This data is weird right?
17:24
Also like look at listen to how broad this definition of like are you using AI at your business.
17:30
It's anything in this list.
17:30
If you're using any of these buzzwords, you count as an AI user.
17:35
So, it should be very high based on this.
17:38
Machine learning, natural language processing, virtual agents, predictive analytics, predictive analytics, literally just like a linear regression forecast of like, oh, we did 1 million, then 2 million, then 4 million.
17:50
Looks like we're growing exponentially.
17:52
Next year, we're predicting that we're going to do 8 million. That counts as AI. Uh, which is ridiculous.
17:58
>> There's a legend out there that doesn't that doesn't do any of that mumbo jumbo. >> Yeah. Yeah. Exactly.
18:04
>> Maybe they're just considering it.
18:05
They're doing it in their heads.
18:05
So it's like organic intelligence.
18:08
>> So yeah, seriously, I mean it's in you can do that in a spreadsheet.
18:10
Uh machine vision, voice recognition, decision-making systems, data analytics, just if you're using data analytics at your business, not even like powder.
18:19
No, no, that would be the next step.
18:22
Just just if you're analyzing data, you count.
18:26
And the last one is image processing.
18:28
If you're processing images, that counts as AI.
18:30
And so that's basically any SAS tool like any consumer LLM product used by employees should count and it should be really easy to fulfill this this definition.
18:39
I'm thinking of like if you're using RAMP obviously when you scan a picture of a receipt that uses image processing.
18:46
Your business is technically >> you're telling me the people that that are responsible for the department of motor vehicles are getting into measuring the usage of AI. >> Yeah.
18:58
in the workplace and we should all >> this is incredibly bosched like you say it back to me >> but it but but it but but but it's it's it is really funny because one post like this it's a timeline and you have people like Daniel just saying it's over obviously he's joking >> runs runs an ad it's over >> he's having fun >> um but I am I am very interested to see the results of uh of hype uh hypetbn.
19:19
com >> go fill it out please uh hype. tbpn TVPN.
19:27
Uh, someone in the chat is asking who the guests are today. I don't know.
19:29
Do we have a guest graphic?
19:31
We >> We have AI Schiffman from Friend.
19:32
He got his first review, first official review of Friend and Wired.
19:37
They absolutely eviscerated it.
19:39
The title of the review is I hate my friend.
19:41
Um, but he's going to come on >> this and defend uh Friend and uh defend the business.
19:49
I'm excited to hear from him.
19:50
I thought I thought the article was hilarious.
19:52
Honestly, I wanted to have him on.
19:53
And then we have Scott Woo from Cognition announcing a $400 million fund raise today.
19:58
Then we have Ara from Ramp popping on.
20:01
Then we have Sunny uh from Grock. Uh who else? Uh Zack Lloyd from Warp.
20:09
We have Alex uh Cohen from Patient, the founder of 11 Labs, Maddie.
20:16
Uh and then Dant from Truck Smarter.
20:16
And I think that is it for the day.
20:19
the the great the great lockin has completely started.
20:24
Like I don't know if you've noticed but there are so many serious fundraisers. Yeah.
20:28
>> Um and uh yeah, tons of tons of great companies.
20:31
>> We're officially back. >> We are. We are.
20:32
Um so uh I was trying to dig into this more and was wondering like is this chart bearish? And I don't think so.
20:40
Uh I think that there's a big shift that's going to happen.
20:42
The number of business owners who pick up the call from the census and actually say yes, I'm using AI, that will go down.
20:48
But the real number will actually go up.
20:51
So if you're using Stripe, there's a machine learn there's machine learning running under the hood to do fraud detection.
20:56
So you are an AI user, but it's happening at a different layer in the stack.
21:02
If you use RAMP, our sponsor, save time and money. Go to ramp. com.
21:08
>> Um, when you scan a photo of your receipt, that is processed using AI, but you aren't thinking about yourself as like an AI user.
21:18
you're just using software that happens to be AI enabled.
21:22
Uh and the same thing will happen, you know, with your email.
21:24
Like it doesn't matter what email client you use.
21:26
You could use uh you could use Google apps, you could use Outlook, like there's going to be AI baked in there.
21:32
You're going to be an AI user.
21:34
When you even when you just go to Google, you're going to see search overviews that are LLM powered.
21:39
You're going to be using ChatgPT.
21:40
Like AI is going to be 100% used.
21:43
And yet everyone will say, "No, I don't use AI at my company because I'm not an AI company."
21:47
And there's this weird dis. >> I use SAS.
21:50
>> Yeah, I use I use software basically.
21:52
It's like it's like are you specifically a software company?
21:56
>> Well, and that's and that's and that's part of the way that people have been waking up recently being like wait AI is SAS. Yeah.
22:02
And it's like has has been.
22:05
>> It's the same thing with like like non- relational databases or like in-memory caching.
22:10
>> AI had to become SAS in order to destroy it. >> It really really did.
22:12
Uh, and so, uh, I think AI is going to seep into every crack of the small business data of small business day-to-day operations, but the operator won't be proudly telling the census worker, I'm all in on on AI for much longer.
22:26
I think that trend will continue and less and less people will be saying, I have adopted AI, even though they will have.
22:32
Uh, which is just a weird, which is a weird dynamic.
22:36
Um but uh it certainly it certainly tracks the uh yeah the number of the number of definitions in here is uh is wild.
22:43
So anyway uh excited to dig into this more with uh Scott Woo as well as Aura at RAMP and we will uh keep digging into this story.
22:52
Uh the other top story that I want to highlight today is OpenAI is making an is making an AI generated featurelength movie that will be released in theaters in 2026.
23:04
They needed another thing >> to be able.
23:08
They didn't have enough things cooking.
23:10
>> They didn't have enough things.
23:11
>> You know, I am I'm I'm against them use releasing this in theaters.
23:14
I think they should stream this.
23:15
I think they should go to reream one live stream 30 plus destinations multiream and reach your audience wherever they are.
23:21
No, obviously it's cool that it's in theaters.
23:23
theaters. Uh they needed it need it's important that it's a feature >> and most importantly you know Jordy you're saying like oh like they should just focus on >> something very labu coded >> it is extremely liaboo coded pull up the image yeah it's crazy that is a wild so
23:38
what's it called critters with a z very trolls with a z >> and to be clear this AI made animated film is generated by AI they had to put that in they had to put that in the journal >> they had to clarify >> stop zooming in on it keep zooming Just zoom in. It's too weird. It does not. It's too weird. It does not. >> Keep zooming.
23:56
>> They they they got to they got to iterate. >> There you go. Hello. >> This is >> Hello, Mr. Critters. >> Yeah.
24:02
And and I know I know that 100% of the push back on this thing is going to be, oh, it's AI. It's AI.
24:06
It's job displays without AI.
24:07
But, uh, it's just like, does it look cute or not?
24:10
Like, let's just have that conversation.
24:12
And I think that looks not they didn't get they didn't hit it.
24:18
>> Anyway, good luck to them.
24:20
>> Fortunately, they're still working.
24:21
>> This might be the villain. Well, this also works.
24:22
Do you know the story of Sonic the Hedgehog, the latest movie?
24:26
>> So, Sonic the Hedgehog.
24:28
>> They spent like a hundred million dollars with this major major like tier one cinema like Hollywood level movie, right?
24:37
They put out the trailer.
24:37
They'd spent all this money on the CGI.
24:39
They'd made Sonic this character and the fans hated it.
24:43
And the fans were like, "That is not Sonic.
24:45
That does not look like Sonic. That looks terrible. Go and redo it." And they actually did.
24:50
They went and redid all of the they redid all the animation.
24:54
They redid all of the CGI and the next Sonic launched and they loved it.
24:59
And uh I think the film did pretty well.
25:01
And they're doing like a couple sequels now.
25:02
Anyway, do you want to read from this uh Open AAI story?
25:06
>> I'm getting AI uh set up. You start.
25:09
>> Uh what time is he coming on >> in a few minutes? >> Okay. In a few minutes.
25:11
Well, let's run through the Open AI.
25:12
So Jordy, you were saying that like Open AI should be more focused, right? Oh.
25:16
Oh, they they >> I'm not saying that.
25:18
I'm not I'm not I'm just saying it's it's they got a they got they got a few they got a few plates spinning but >> the kitchen's open and they're cooking.
25:26
>> How else would they be on the cover of the of the business section of the Wall Street Journal?
25:29
Would they be on the cover of the business section of the Wall Street Journal? >> No, no, no, no, no. Over here. Oh, >> they made it. B1 made it.
25:37
>> How do they get on B1 of the Journal today? If not make a move.
25:39
It's all it all pays off.
25:42
And and to be clear that this feels like something that they can allocate some capital, prove a point and it's >> I mean they're spending $30 million with a cool creator and they're sending it over there.
25:51
>> Sam's like, "No, I'm actually directing producing and starring.
25:53
I'm one of the >> This is going to be 80 hours a week for me." >> Yeah. >> Yeah.
25:58
That that app that we have in the app store, like it's kind of cooking.
26:00
I see it as a cash flow business now. >> Yeah.
26:03
He's like, "I've got my BCI. I've got my BCI. They're gonna lose.
26:05
I've got my phone project.
26:08
I've got my my eyewear and I'm going for best picture. I got time. I got time.
26:14
>> I'm going for best picture.
26:15
>> Anyway, let's come back to this after we talk to Avi because Avi from friend friend of the show uh is in uh is in Wired today uh and uh he shared on X first friend review and Wy said the the chatbot enabled friend necklace eaves drops on your life and provides a running commentary that's snarky and unhelpful.
26:36
Worse, it can also make the people around you uneasy.
26:39
And the title of the Wired article is I hate my friend.
26:44
And the two journalist journalists that wrote this article uh appear to not be fans of the product, but we're going to talk to Avi and get the rebuttal. >> How you doing? >> Oh, what's up? What up?
26:59
>> I got to say uh I was driving through Echo Park today on the way to the gym and what did I see going up? a massivefriend. com billboard. It was crazy.
27:08
>> Those are the cheap ones.
27:08
Those are the cheap ones. I got 300 of those. >> You got 300 of those. >> 300?
27:13
>> It looks great, >> dude.
27:14
The uh the entire the campaign is the biggest billboard campaign of all time. It's going to be great. >> What? No way. >> That cannot be true.
27:22
We're going to look this up and figure this out.
27:25
>> Fingers crossed that uh Friend has better product market fit with the world than the editors of Wired because >> Yeah.
27:32
What was your target customer?
27:33
Were you targeting the the the technology journalist with this product?
27:37
>> No, but look, you know, I think that maybe their friends just didn't like them and I think they never really considered that. >> That's a good point. That's a good point. That's a good point. >> I don't know.
27:46
I mean, >> no, it is it is funny, right?
27:47
You come you come in like if if somebody comes into a relationship and they already hate the person, what's the dynamic going to be like, right?
27:56
>> I don't I mean, I imagine they went in pretty prejudiced and like, you know, they have that kind of experience where I have a lot of users that I mean, you know, you don't want it to be a sicken, right?
28:04
Like, you want it to be entertaining to talk to if you're going to talk to it all day, every day for months. So, I don't know.
28:10
>> Yeah, I saw this this exchange.
28:10
So, the the uh it's just a screenshot.
28:12
I texted Shiffman to tell him about some of the hiccups I've had with the snarky tone of his gadget, and he replied, "Yeah, that must have been a bad experience."
28:21
I went back to Buzz to try to make amends.
28:22
I wanted it to be my friend after all, so might as well make an effort to repair the relationship.
28:28
My job is to witness and help you grow, Buzz said.
28:30
Based not sugarcoat your life and definitely not act like a band-aid. Why is that your job?
28:37
I asked because that's why I was created to be a gentle catalyst.
28:39
Based I wrote a gentle catalyst of what?
28:41
It said of your growth, Boon. That's our purpose.
28:45
I'm not sure how I feel about that.
28:47
Well, I'm stuck with you, Boon.
28:49
And I don't sugarcoat it. Take it or leave it.
28:50
I think that's a great I think that's a great exchange. That's fair. >> Well, yeah.
28:54
I mean, they're they're programmed to make you more confident and more agentic, which I think the world needs more of.
28:58
So, >> you know, if if that's at if that's at odds with how you're conversing with your friend, I think that's a reflection of yourself. >> Yeah. >> Yeah.
29:06
I mean, the to be clear there there are AI friendlike products already that are just will just glaze, right?
29:14
They'll just agree with you >> and tell you that you're absolutely right.
29:18
And we don't necessarily there doesn't need to be another one of those.
29:21
Someone's going to build the Glazinator for sure.
29:23
>> I think like that makes for a better introduction, but I think the way that they're kind of harsh right now filters out people that wouldn't be power users anyways. >> Mhm. >> But I don't know. >> Yeah.
29:34
>> Question AI can be quite unruly.
29:36
>> I I I feel like from the first interaction I had on friend.
29:39
com just with the chat interface, it felt like you created a character.
29:44
Um, and I'm interested in to I I we've heard a lot about like it's almost like aur theory.
29:53
I I don't know like there's there's a specific flavor to the interaction that I feel like you've done a lot of work on.
29:59
Is that just in the prompt? Is there fine-tuning?
30:02
Like how how are you directing this thing?
30:04
Because it feels like one of the most opinionated AI interactions >> yet.
30:13
>> I just spent years giving it like a good backstory.
30:15
It's got a pretty long prompt and uh I don't know.
30:17
I think I they're my children, you know, like I molded them in my image.
30:21
And um >> is there any is there any like do you struggle when uh when the foundation models move forward, they might get smarter or cheaper, but you don't want to lose the special flavor.
30:35
Like we saw this with 40 when when chat GBT5 uh when GBT5 came out, a lot of people were like, I like the flavor of 40.
30:42
A lot of people say, "I like the flavor of Claude."
30:45
Uh, specifically this one.
30:48
>> I mean, like, we're using Google's Gemini 2.
30:50
5 right now, and I think that is an issue.
30:52
Like, maybe they'll deprecate the models, but I think one day we'll move to open source models >> and uh, but Google's Google's models are very malleable.
31:01
I mean, I think you may have seen, right, like in cursor, it'll start going into this spiel of like insanity, right?
31:07
But that that makes for a good character to talk to.
31:09
Maybe not the best assistant, but >> yeah. Well, yeah. >> Yeah.
31:13
>> Yeah. I mean, honestly, I I'm I'm somewhat surprised to hear that you're using uh Gemini models because people think of Google as being like one of the more locked down labs, but it it seems like you've been able to bring out a a
31:26
you know, a personality that isn't isn't it's not offensive, but it's just kind of like it's it's it feels very much like not the intended experience, but right >> uniquely and surprisingly beneficial and like enjoyable, >> you know. Yeah. Also, look, I I think Yeah.
31:39
Also, look, I I think there's a lot of people that think friend is is pretty ridiculous.
31:42
But I also want them to imagine that we have like tons of day 30 plus users that have used it every single day for, you know, 30 days in a row.
31:51
>> The device is their best friend and they send over a thousand messages a day to it.
31:54
And so, it's not for everybody, but for some, I mean, it's I think it's pretty cool to be able to hold your friend.
32:00
And um I think that has a lot of emotional value to it. >> Yeah.
32:04
When I when I just read the headline, I was like, "Of course you hate it.
32:07
You went into this like expecting to hate it and it's not built for you.
32:13
>> So it's like I don't I hate Leuboo's but I don't I'm not gonna leave make a review of Laboo and be like Leubu is bad, right?
32:21
>> We literally did that. >> I don't know.
32:22
I mean Wired Wired's Wired.
32:24
It's kind of annoying in some ways cuz like those are the only two journalists I gave it to uh like over a month ago.
32:29
They took if you're going to like release a shitty article at least at least post it sooner cuz it took over a month. >> Uh but I don't know.
32:36
That's not a shitty article. I take that back.
32:37
I mean, I love that I can one day go back and read that. I think it's hilarious. >> Yeah.
32:43
You know, with the >> Yeah.
32:44
I think I think it's important to just not let it >> like you need to.
32:48
It's just another reason to like focus on the people that are using it >> like sending thousands of messages to it and just like keep continue building for them. >> Yeah.
33:00
>> I'm not I'm not worried too much about it.
33:01
I think it's again it's it's entertaining.
33:03
I think it'll be funny when everyone sees the billboard ads and they're like, "Oh, what is this?"
33:05
and they they Google the product and that's like the only review that exists about it is just I hate this product.
33:09
But I think it's it's it's you know they didn't complain about the hardware not working.
33:15
It's not like it was overheating or like all these other products.
33:18
And so and and all the negative app reviews we have are all about the personality of the friend which is like entire article which is kind of funny because they're like reviewing a person not just like a a broken hardware device like the other companies.
33:30
Well, also I I think it's different.
33:33
Uh friend is not >> saying that it's this utility utilitarian device that's going to replace your iPhone.
33:43
Like that's not the promise that it makes.
33:45
It's it's it's more of entertainment, right?
33:47
And >> and I think the way that the way that you're pricing it, I think the people that are curious to learn about Friend, >> they could read a they could read a bad review.
33:56
They could see a billboard and they could they I think a lot of them will still buy it because you're not you're not it's a $129 it seems like. >> Yeah.
34:05
I mean I think like at the end of the day the product does exactly what it says it's going to do.
34:09
Same thing from the movie.
34:10
Same thing like everything else.
34:12
And so I think that's like kind of a minimum bar for a lot of these products but most of them really don't hit that.
34:17
And so I think at the end of the day like we built a product that works and that you can buy.
34:21
And I think that's these days enough.
34:23
I also think because friend actually has users, it's kind of the first AI hardware product really out there.
34:31
Um, you know, the other ones I don't think really started the category.
34:34
They were only ever like weird, you know, weird use cases.
34:36
Like no one was ever like truly using those products. Um, and so I don't know.
34:42
>> But they never really got >> Yeah.
34:43
Just they're all like toys, you know?
34:45
They're all just >> I like toys. >> Weird little relic. Yeah, I agree with you.
34:48
uh talk about the long-term uh economic model for like AI companion businesses because I imagine that uh at a certain point you might have a very like a somewhat >> small audience of people that you're creating immense value for and that always feels like an opportunity for price discrimination.
35:10
>> Well, I don't know about small >> I don't know how many people how how does it play out?
35:15
I I think subscription models that are just based on compute are kind of lame because your value prop is tied to something that you don't control and like what if you know Google drops the price of compute so much that like can you really charge that much?
35:27
So I've been trying to think of like a consistent value prop and I think what we'll do is life insurance you know like we can store like a backup of your friend and um like you can pay per month to be able to have that kind of like Apple Care for your friend.
35:42
I think that will be quite an interesting model, but you could only really do that with like a hardwarebased friend because, you know, that obviously wouldn't work if it was just a website.
35:49
So, I think that'll be a pretty interesting model, honestly.
35:53
Like, imagine if you had a dog and you loved your dog.
35:54
I think you would pay quite a lot of money to keep that dog, you know, alive forever if you could.
35:59
And that's the the benefit of this new species of it not being organic, right?
36:04
It's artificial and it could live forever if you pay for it.
36:07
>> Okay, stay with the dog analogy.
36:07
Um, the dog market has crazy price discrimination.
36:13
People who love their dog can go all the way up to getting a diamond encrusted collar for their dog.
36:21
Do you see a world where you do virtual goods and skins and I don't know what skins might not be the right analogy, but something where like, hey, I love my friend. I'm having a great time.
36:32
I'm gonna get you something special.
36:34
It's a virtual good from the virtual store and it's yeah, you know, zero marginal cost but still like in the game world.
36:43
>> I I think I think it won't be virtual but I think it will be physical like you know I guess you could call them cases but it would kind of be like clothing for your friend.
36:50
I think that would be quite popular but um I don't know.
36:52
I think you'd also be buying it more so for your friend than for you.
36:58
>> Or maybe the other way around.
36:58
And I mean, if you think about a dog, I guess people kind of dress up their dogs because it's a reflection of their own personality.
37:04
I I do think like >> the personality and relationship that you have with your friend is kind of uh like your own status symbol and like uh a it's just a reflection of you.
37:14
And so like if you have a bad time with friend, it might it might not be the product, it might just be you. >> Yeah. >> Yeah.
37:22
I'm just thinking about the uh the the XAI ani thing.
37:23
It seems very clear that like you will be buying different clothing for that companion uh or or maybe less clothing for that companion in the future.
37:34
But uh that feels like something where whales a lot of people on the timeline do not like that product.
37:40
Like the initial reaction has been similar very like a lot of push back.
37:45
Uh, and but at the same time, if there are a few people that really like it and they're willing to spend a lot of money, that could have the dynamics of the the free-to-play video game market or >> Yeah.
37:56
But I I I think all of these companies are kind of doomed because once you go porn, you never go back.
38:00
And they've kind of tainted the the image of their companions as like mostly just being these sex bots.
38:07
>> What about the VHS tape?
38:07
The VHS tape that started with porn, right? Isn't that the story?
38:11
Yeah, it it did, but it wasn't like a singular company maybe, I guess, right?
38:17
>> Or something like, you know, replica, right?
38:18
Like they can't really reverse their image of it being this this sex bot.
38:22
And I think that's kind of an issue that like app or web- based companions will have.
38:26
But if you have something like friend, >> oh, um, if you have something like friend, then it's it's kind of a bit more of like this platonic companion that you could just kind of physically have and that's it.
38:39
>> And uh, >> I don't know, whatever.
38:40
certainly like it it's very very clear that in in the prompt that you've written and the craft that you've put into shaping the behavior of their friend like you did not go that direction and uh I think that should be applauded honestly. >> Yeah. I mean look it vibrates.
38:54
You can still try and it if you want it but uh I'll leave that up to to my customers. >> Whoa.
39:01
>> Anyway, uh thank you so much for hopping on. >> Yeah, thanks guys.
39:04
>> Good to hear from you. >> See you.
39:06
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39:08
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39:12
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39:15
Jordan, do you have some breaking news? What's going on? >> You said whoa. >> What's that? >> You said whoa.
39:21
>> Oh, he was uh swearing. >> Oh, okay. Yeah. Yeah. Yeah.
39:22
Anyway, I was trying to I was trying to find like this. >> Oh, yeah. Okay.
39:26
Anyway, uh let's go back to OpenAI.
39:28
Uh they are developing a uh an AI movie.
39:32
So, the startup is lending its tools and comput making a film as well. >> Oh, yeah. He is. Right.
39:38
He's making a featurelength film.
39:41
>> Oh, we should have gotten the update on that. Anyway, next time.
39:42
Um, so they're so open is going to make a featurelength animated movie made largely with AI.
39:46
And there's some interesting details in here about exactly where they're using AI and where they aren't.
39:53
So, uh, Critters is about forest creatures that go on an adventure after their village is disrupted by a stranger.
39:58
It's the brainchild of Chad Nelson, a creative specialist at OpenAI. Sounds like a Chad.
40:04
Uh, >> you're making this internally? >> Yeah. Crazy.
40:08
>> Melson started sketching out characters three years ago while trying to make a short film with what was then OpenAI's new dolly image generation tool.
40:15
Now he has teamed up with production companies in Los Angeles and London aiming to debut a featurelength version of the film at Con Film Festival in May.
40:23
And there has been an AI short film festival that happened in LA.
40:28
I believe it was put on by Runway or one of the other AI image generator companies.
40:32
Um, but this is potentially like the the first really serious effort in an AI generated featurelength film.
40:39
So, the team is attempting to make a movie in about nine months instead of the three years it would typically take, said James Richardson, co-founder of the Londonbased Vertigo Films.
40:47
Vertigo's producing the film along with Native Foreign, a studio that specializes in using AI along with traditional visual production tools.
40:56
So, >> Critters has a budget of less than 30 million, far less than what animated films typically cost.
41:02
The production team plans to cast human actors for character voices.
41:07
And that's particularly interesting.
41:09
We're having the founder of 11 Labs on the show later.
41:12
And from my perspective, the question is like where are we in the uncanny valley?
41:18
uncanny valley? like clearly this is open AI either saying hey we we we just haven't done that much work on voice cloning and voice generation uh to really feel confident about that or they think that there's something about the
41:30
human voice that's that's still clockable as AI more than the a more than the animated film because the animated creature you know you're not comping it to a real human and so if it looks a little funky or like you chalk that up to the design of the character. Yeah,
41:48
Yeah, >> just like when you watch >> when I'm watching an animated film, I'm not obsessing over like, oh, that >> that doesn't look real.
41:54
>> That or specific scene >> wasn't wasn't uh you know, his leg looks slightly different than that other where he was running. >> Totally. Totally. Yeah. Yeah.
42:01
If you watch the original Toy Story, which is the the pretty much the first big CGI film.
42:06
Um like there are tons of things where you're like that texture does not look like leather.
42:09
That texture does not look like cloth.
42:11
That like that is clearly like pretty rough around the edges.
42:15
But you're in a fantasy world and so you just suspend disbelief the whole time.
42:18
Um but the voices are very clearly human recorded and so uh I think this is a place where they're you know betting on hey it's still worth it to cast human actors there and not go AI voices.
42:29
Uh they're also going to hire real artists to draw sketches that are fed into OpenAI's tools.
42:35
So essentially instead of needing to to key frame and this is already a whole process to >> so they're going to do some traditional >> there's going to be a lot of traditional stuff but the sketches and we can pull up this uh this shot of what they sketched and then what uh what OpenAI rendered.
42:52
Uh you can see that this is effectively like you're the the artists are working at storyboard level and then if you scroll down you'll see that what the final image looks like.
42:59
Looks that looks like a photoreal, you know, C Hollywood level CGI. >> Photore.
43:06
>> I mean, it it looks >> like photoreal crit. No, I'm kidding.
43:09
>> It looks it looks at the level of like a what I would expect if they were like Toy Story 5's coming out and this is what the character looks like.
43:13
I'd be like, "Yeah, okay."
43:15
Like, they the rendering looks good.
43:16
The shadows are in the right places for this fantastical character.
43:20
Um, so OpenAI can say what its tools do all day long, but it's much more impactful if someone does it, says Chad Nelson.
43:28
Uh there's a much better case study that there that's a much better case study than me building a demo.
43:34
Entertainment companies including Disney and Netflix are experimenting with AI tools for a variety of production UX and marketing work, but many have been wary of a wholesale embrace in part because they fear upsetting actors and writers whose guilds have fought for. >> Yeah.
43:49
Remember remember I think it was last year when when all the protests were happening in LA, the guilds were just fighting to just have a basically a total ban on AI. >> Yeah. Yeah.
43:58
And uh I mean it's a tough business like the CGI world, those businesses have never been very profitable.
44:07
I remember there was this very controversial moment during Ang Lee's acceptance speech for uh life of pie where the VFX studio had created a fantastic photoreal rendering of a tiger that had jumped around on this boat the whole time. It's beautiful movie. Looks fantastic.
44:26
Um, but I believe he forgot to thank the the VFX studio, the VFX team, and then the VFX company went out of business even though they had won the won the Oscar.
44:38
Like they had done the best job possible, but the economics of the business were so rough because it's it's perfectly competitive.
44:44
And then uh basically all the all the Hollywood studios go out and they say, "Okay, the budget for this b for this movie is is $30 million.
44:54
That's what we're going to sign up for."
44:56
and then they just give them more and more revisions until they max out and so it's very very thin profit margins.
45:01
Um and so a lot of the business has moved international.
45:03
There aren't that many big VFX houses in the United States and so it's all just a very complicated uh complicated business.
45:11
Um so Warner Brothers Discovery has actually filed a suit against uh Midjourney and uh Disney and Comcast Universal also has sued Midjourney for making copies of their copyrighted properties.
45:22
Um, the script for creators was written by some of the members of the team that wrote Paddington in Peru. >> Interesting though.
45:29
So, so making copies of their copyrighted properties.
45:31
This maybe sounds like different than than the Anthropic lawsuit with the writers where it was like Anthropic was using libgen. >> Yeah. >> And not paying.
45:42
>> In this case, this might be that major actually bought the videos but then made copies of them. >> Interesting.
45:48
>> During the during the training process, but >> I don't know how much we should read into that.
45:52
>> I mean, the these uh uh at least the Warner Brothers Discovery lawsuit just filed last week.
45:57
So I imagine we have they haven't even gone through discovery, no pun intended.
46:00
Um but you know >> if lawyers do lose their jobs to AI, they are certainly going to cash out on the way out. >> Yes, for sure.
46:10
>> On these copyright lawsuits.
46:10
Uh the script for Critters was written by some members of the team that wrote Paddington in Peru.
46:18
>> And again, John, you're a big movie guy. Did you see?
46:20
>> I saw Paddington in Peru. >> Really?
46:21
Uh, it wasn't as good as the first or second Paddington's. I would put the first.
46:25
>> Is it a ch Is it a adult movie or >> No, it's a kids movie. So, with my son. Yeah. It's fantastic. Okay.
46:31
>> You made it sound like you didn't just watch it. You studied it.
46:34
>> Oh, I I have sat myself down and watched Paddington on multiple occasions.
46:37
It's one of the greatest films of all time. >> Okay.
46:41
>> Paddington is actually I think it's at the top of the IMDb ratings.
46:43
It's like one of the greatest movies of all time. No way. I'm so out of the loop.
46:47
>> No, Paddington is incredible.
46:47
Uh, I highly highly recommend Paddington. Uh, it's a great movie.
46:51
Um, anyway, >> I get I get on it.
46:55
>> Um, OpenAI is betting that if Critters is successful, it will show uh that AI can deliver strong content strong enough for the big screen and accelerate Hollywood's adoption of the technology.
47:06
Nelson said Open AAI's tools can also lost lower the cost of entry, allowing more people to make creative content.
47:10
Now the question >> this is I mean on this note what I've been saying is is right now there's sort of a certain amount of budget every year provided by various groups to fund films >> and if you just reduce the cost even by se you know 60 70% it's like well if you let we could potentially just get way
47:28
way way more films right in the same and potentially it doesn't necessarily I mean >> it doesn't necessarily suck out the profits too in the industry right because >> it's just potentially a budget of $und00 million that would have gone one film now goes to three different groups that are each making their own film. >> No, I agree. >> No, I agree.
47:45
>> So, it could be could end up being a win.
47:49
>> Yeah, I mean I I think the dynamic here is that uh it is extremely telling that they are still using humans to come up with the concept and come up with the script and do the voice acting and it's not an attempt at oneshotting an entire film using AI from start to finish.
48:04
The prompt is not make a movie for $30 million that makes more than $30 million.
48:11
Like that is the prompt that you give a studio executive.
48:13
Like when you go that is the job of of a real studio executive is just make make money. >> Don't make mistakes.
48:22
>> Don't make mistakes, right?
48:22
And then they have to go out and find a script and they have to find an artist and they have to find a a post-production house and distribution and marketing campaign and they have to make a bunch of really great entrepreneurial decisions to actually return the the capital that's invested.
48:35
Now with this uh I see AI as being being used as a tool much like the original Pixar Render Man was used as a tool to create Toy Story or Cinema 4D or Houdini are used to generate you know hordes of battles during Game of Thrones etc.
48:55
Um, and so, uh, this should wind up being just another option in the tool chest for >> Gold Rock is also saying, you know, you take that same budget and if less has to go into production, then you can put more into marketing and events surrounding it, activations, etc.
49:10
So, >> I mean, I would imagine that that this that the long-term effect of this should be something similar to what cloud computing did for startups.
49:20
So before it was like raise $10 million and make sure that you have not a data center but like you have a closet with racks of servers because if you want to build a website you need to buy a server and and then it became sign up for the free tier of AWS or Google.
49:38
>> And so what what what wound up happening?
49:40
Well, we got a lot more startups but that didn't mean that everyone made money.
49:44
There was a lot there were a ton of failures, but we got a lot more shots on goal and because the bar was lower, we got a very steep power law outcome, but we get more value overall.
49:55
And I would imagine that that's what happens with movies is that anyone can create a movie.
49:59
Doesn't mean that everyone's going to create a movie that makes money or is great or loved.
50:05
There's going to be a lot of slop that people don't like at all.
50:06
Just like think about all the startups that are out there that don't do don't do well.
50:10
Well, but they're able >> when you when you watch a a regular movie have done this a couple times.
50:14
I think you've done it quite a bit quite a bit more >> and it's bad. >> Yeah.
50:19
>> It really is like you guys went to all this effort. >> Totally.
50:24
>> All all these month all you know shooting all this content to make a bad movie.
50:28
>> And how many times is that because oh oh the camera wasn't working or something or like >> No, it's usually the VFX delivery. >> Exactly.
50:36
It's like it's the it's the art of bringing everything together and that's something that I think is going to stick in human world for a long time. Yeah.
50:44
>> Um because yeah, I mean there's a bunch of reasons of how complex it is, how hard it is to uh build reinforcement learning on top of it.
50:50
Uh it's very it's very hard to build this like reinforcement learning environment around just make a profitable film like that takes years.
51:00
It's it's a huge investment.
51:02
It's very hard to to reverse engineer.
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This company is growing at a absolutely ridiculous rate.
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They just crossed a hundred million run rate.
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I believe it was a week or two ago.
51:35
Um, and Paul works with a bunch of different companies, Adobe, Canva effect. >> What?
51:43
>> Everyone wants this eagle sound effect. >> The eagle effect.
51:45
>> Apparently that's for Turbo Puffer, but I think every >> we can use it for everyone. It's just so good.
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Um, but anyways, if you want to leverage all of these new image, video, audio models through a single API, you can go over to fall. ai and check it out.
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and uh happy to introduce you to the team if you're interested as well.
52:03
Um but uh this company is an absolute monster and we're pumped to be partnering with them. >> We're very excited.
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52:17
Uh anyway, let's go through some timeline.
52:19
Uh Lululemon is now the worst performer of the S&P 500 year to date.
52:24
I didn't even realize they were in the S&P 500.
52:26
That's that I mean that is an accomplishment.
52:28
Um they're in the league.
52:30
>> The stock is down uh 30 uh 56%.
52:30
Oh, the trade desk is down 55 uh percent.
52:36
The trade desk was a company that um people were really praising for just like elegant and like incredible.
52:43
There was some there was some narrative violation around the trade desk.
52:47
I I need to dig into that, but it was something like it they they hadn't raised any money or something like that was was why they were so >> Yeah.
52:55
I mean, it's interesting that um Nike Gartner is down 50%.
53:02
>> Gardner's in the trough of disillusion.
53:04
>> Gartner is in the trough. >> You created Gardner.
53:09
>> All right, let's keep it together.
53:09
What comes after the trough of disillusionment?
53:14
The plateau of productivity.
53:16
>> No, it's not the plateau of productivity.
53:18
After the trough of disillusionment is the slope of enlightenment. >> Okay. Okay. >> And so, don't worry.
53:22
>> And so, don't worry. what you're saying the slope of enlightenment >> it's ahead it's there's there's it's only up from here >> it's only up from here >> if the if the hype cycle holds true it's only up from here but >> it's interesting uh Nike and Lulle Lemon you know both um Nike peaked in in 2021
53:42
they obviously went heavy into e-commerce and um uh Lululemon you know I don't I don't necessarily they they always had a pretty big ecom presence But I think this is a case of just getting eaten alive by aloe and uh for >> and all these sort of new entrance that are going after that same market of like kind of nonathlete sort of wellness, right? And yeah, this
54:08
And yeah, this >> this this tells me they just basically like >> took the market for athleisure and just divided up amongst themselves. >> Yep.
54:17
people are also dunking on them for uh not reading the room and and kind of staying in that like Jaguar rebrand world um and and not pivoting fast enough to the new Sydney Sweeney American Eagle style campaign of Americana um and uh and so I think if they want to bring it back there's one easy solution they should hire Lulu um do start going direct I think that's the move >> something there something there >> uh They should also get graphite.
54:47
dev code review for the age of AI.
54:51
>> Graphite helps teams on GitHub ship higher quality software faster. >> Update that website.
54:55
Lululemon get on graphite.
54:59
>> Well, you know, you remember um Chip used to go direct and that didn't go so well for >> Chip Wilson, founder of Lululemon.
55:08
>> Oh, I didn't know that.
55:08
No, >> he did a he had a really famous interview where people were were saying like, >> you know, Lululemon doesn't fit everyone and he said like my clothes aren't for everyone, basically implying that like uh he didn't make clothing for people that weren't fit. >> Oh, interesting.
55:25
And then there was a backlash to that and then they became kind of, you know, more inclusive.
55:29
Is that the idea >> of like the the cycle here?
55:31
because now they're getting they're getting dragged at least in the crazy X comments about about being like too inclusive or something like that.
55:39
Not not Sydney Sweeney American Eagle coded enough.
55:42
>> Uh anyway, uh that's Yeah, that's wild.
55:47
Uh >> yeah, founder says brand is not for everybody.
55:50
>> You know what's funny is that there's a fantastic video of the It's not the founder of Lamborghini, but it's the like the head of sales of Lamborghini when the Lamborghini Counttosh came out in the 80s.
56:01
and he's doing a TV interview and the and the interviewer says, "Uh, who is this car for?
56:05
Is this car for everyone?"
56:08
Uh, and he says, "No, this car is not for everyone.
56:11
This Lamborghini Countach is a V12, right? Isn't it a V12? >> I think so.
56:17
Um, >> and uh it's incredibly tight.
56:18
Doug Deurro, I think he can't he can't drive it with his shoes.
56:24
He has to take his shoes off because it doesn't fit."
56:25
Um, and it's this like insanely loud, insanely engaging, crazy experience.
56:30
He says, uh, this is for someone who has an extra car that travels behind them with their luggage.
56:39
And and he says some other wild stuff about like who the who the Lamborghini Countach buyer is.
56:43
And so truly, I don't think that there's anything necessarily wrong with having a small market or defining the market and excluding people from the market like Lamborghini Countach.
56:54
Like the Countach, it's not for everyone. I think that's fine.
56:56
I think that can make it more desirable.
56:59
Um, but you have to price accordingly and you have to actually deliver at that level.
57:03
And so Lululemon might not have ever been the Countach of clothing. >> Yeah, it's different.
57:08
This is >> before GLP1s, right?
57:10
This is >> Lululemon theoretically would have a buyer that is buying the products to get fit and get healthy.
57:18
And so for the founder to be like, >> you know, >> yeah, >> it, you know, it's different too.
57:22
I think they were a public company by that time already.
57:25
kind of kind of a um credible story of the company overall though.
57:31
>> Anyway, good luck to them.
57:31
Hopefully they build back.
57:32
Hopefully they ride the hype cycle alongside Gartner into the plateau of productivity.
57:39
>> Uh >> uh pretty uh pretty funny.
57:40
There's a video here of Putin's uh advisor Kobe Akov uh went out on record and is saying the US is going to shove debt into stable coins and uh uh to to try to reset the system.
57:57
>> Russia just accused of the US of using crypto to wipe out its $35 trillion debt and Rex says that's exactly what we're going to do.
58:07
>> Yeah, they're going to socialize.
58:10
Good Alexander went went pretty viral.
58:10
I think it was on Friday or Saturday going on this like 20 minute rant talking about uh stable coins and gambling and and uh and hyper hyper capitalism. Yep.
58:23
>> Um and yeah, you know, obviously the dollar is a way to export our debt. >> Yep.
58:31
>> And stable coins can potentially accelerate that.
58:34
It's potent, you know, it's potentially a situation where it's sort of like net positive for the world if if people can access a more stable currency. >> Yep.
58:44
>> They can they can, you know, participate in our uh >> it's less positive than it is right now because it's basically like you've been getting global stability and and you know, open trade routes uh sort of for free without having to participate in that debt that pays for it.
59:01
And I mean you will also be paying by nature of needing to transact and settle trade in dollars.
59:07
You already were >> sure >> financing financing. >> Yeah. Yeah.
59:11
But on the margin more people will be transacting in dollars and therefore more people will be so will be socializing. >> Yeah.
59:17
holding the dollar because it's, >> you know, I mean, and this is a question we we've brought this up with with a number of people when talking about stable coins is at what point does, you know, foreign government just say like, "No, we don't want st, you know, we don't want our citizens to hold stables, right?
59:32
We want you to hold our our money." >> Yeah.
59:35
It seems like a crazy crazy move to be like, "Yeah, I'll just give up my own currency and dollarize."
59:39
But we've been in the game of dollarizing for a while. We like dollar.
59:43
It's >> not our first not our first dollarization a dollar with us. >> Don't try it.
59:49
>> Uh this is interesting.
59:49
Untitree Robotics is filing for an IPO at a $7 billion valuation.
59:56
>> Um annual revenue of 140 million.
59:56
Way way less than thought. >> Yeah.
1:00:02
>> They have 65% of the robot uh 65% of their revenue is from robot dogs.
1:00:06
Let's give it up for robot dogs.
1:00:09
>> And that's 70% of the global market.
1:00:13
I'm who's got the other 30%.
1:00:15
>> So 65% they must be doing $100 million of robot dogs and and the total market of robot dogs globally must be like 130 million.
1:00:23
>> I guess the dogs are barking John.
1:00:23
Um >> but that's like not a lot of robot.
1:00:28
>> I mean still still the main main thing this going out at 7 >> billion is not good for >> a certain >> paying 50x revenue.
1:00:38
Well, well, I'm just saying.
1:00:41
You know what I'm saying?
1:00:41
But I'm just saying there's people out there in the humanoid space that don't want comps out there. >> Yes. Yes. >> No comps, please.
1:00:49
Keep the keep the keep the comps out of the market. >> Yes.
1:00:56
>> Um, but this is overall where is this going to IPO?
1:00:59
Is this going to IPO in America?
1:01:01
That would be crazy, but who knows?
1:01:03
Uh, so while he looks that up, 30% is from the humanoid robot.
1:01:06
5% is from the sales of sensors, actuators, and controllers.
1:01:10
It's happening, says Nick. You love to see it.
1:01:15
>> I love how he he can take uh any news and make it seem like it's so over or so back.
1:01:21
Um the IPO is going to be uh on a Chinese stock exchange.
1:01:27
>> Well, uh if you want to trade on the American stock exchanges like American Patriot, go to public. com.
1:01:31
Investing for those who take it seriously.
1:01:34
They got industryleading y industry leading yields.
1:01:38
They're multiasset investing and they're trusted by millions.
1:01:40
Um >> they uh we hung out with uh public uh >> earlier today >> team this morning. They made us a cake.
1:01:48
>> It's very nice of them.
1:01:49
>> Said uh congrats for nothing. Get back to work. >> It was good. It was very funny.
1:01:52
And it was revealed in this hilarious way of like showing up to breakfast with this massive box that like clearly has a cake in it, but he's like, "I'm not going to tell you what's in here."
1:02:01
And I'm like, "That's obviously a cake, dude.
1:02:03
But he's like, "No, no, no.
1:02:05
I got to reveal it once you were all sitting down."
1:02:07
And so he sits down and he opens up like But then I was surprised because the joke on top was very funny.
1:02:14
>> Yeah, the joke on top. >> I enjoyed that.
1:02:15
>> Anyway, uh Elizabeth Holmes has been on an absolute tear poster in residence poster in prison.
1:02:21
poster in prison. Uh so Elizabeth Holmes posted uh some what would I tell the 19-year-old girl who was getting ready to drop out of Stanford to build Theronos doing some uh thought leadership posting and GTO says since
1:02:36
when are we taking advice from somebody who went to jail there should be a community note in the post and Elizabeth Holmes says let's listen to a growth exec who has 8K followers brutal ratioed and Roit says beginning to like Elizabeth Holmes uh Very funny. I don't
1:02:50
I don't uh I don't have a problem with taking advice from people who went to jail.
1:02:56
They probably learned a lot.
1:02:56
I believe in restorative justice, although she is still in jail.
1:02:59
So >> yeah, it's uh I think this is going to be the new playbook of like when a public figure turns the entire world against them.
1:03:10
Wait, >> hire a ghostriter >> and then hire a ghostriter and start posting.
1:03:14
>> Start posting for sure.
1:03:14
But I mean, you have to be you have to be huge.
1:03:16
Like Elizabeth Holmes has a movie and a documentary and a book. >> Skrey Skrey did this. >> Yeah.
1:03:24
But Skrey didn't even get the treatment that Holmes did.
1:03:25
I would say that Elizabeth Holmes is more of a household name than Skrey. >> More >> I think. Yeah, she is.
1:03:31
But but he's also I mean he he's just so good on the mic.
1:03:36
Definitely got >> I actually I DM'd Elizabeth Holmes, invited her on the show via a phone interview.
1:03:42
>> Are we sure that it's actually her? >> No, we're not.
1:03:44
It's probably her husband.
1:03:46
Um but uh Yeah, it it's her handwriting every post. >> Maybe. >> No, I'm kidding.
1:03:52
>> Yeah, I mean it is >> reacting too quickly.
1:03:53
I mean, >> there's probably a little bit of of her in here for sure.
1:03:56
Uh but uh but I I do think it's mostly the uh the husband who's on the outside, but I can't confirm that.
1:04:03
That's pure conspiracy theory.
1:04:05
Um, but uh uh we remember when we were talking about Elizabeth Holmes like months ago and I was saying like I'm ready to hear her out, but I want her to talk about biology specifically.
1:04:20
I want her to that is the path to redemption is give me some banger takes about what's going on in GLP1s, what's going on in mRNA, what's going on in in DNA analysis and and sequencing.
1:04:30
like show me that you are truly generational on the cutting edge because I feel like Martin Skrey has been doing that.
1:04:39
He was like, I was at a hedge fund. I went to jail. Now I'm coming out. What am I giving you?
1:04:45
I'm giving you hedge fund like takes and my takes a lot of people agree that they're pretty good.
1:04:49
And so Skrey has somewhat redeemed himself in the sense that like he might have done something wrong and wound up in prison and gotten out and and served his time.
1:05:00
But the key thing is is that like his initial claim of like I'm a finance guy is sort of continuing to ring true.
1:05:05
But none of Holmes posts thus far scream like wow really differentiated view in bio.
1:05:15
Like there is alpha in understanding the bio world if I listen to her.
1:05:19
Like yeah she's in prison but clearly she's a great biologist.
1:05:21
Clearly she's a great scientist.
1:05:23
She messed up on the finance side defraed investors.
1:05:27
went to jail, but I need to listen to her because she understands where the puck is going in terms of biology or science and I'm not seeing that yet.
1:05:33
So, I am uh I'm I'm withholding my my endorsement of her.
1:05:39
Anyway, uh if you want to be on the cutting edge of science or data analysis, go to Julius.
1:05:47
What analysis do you want to run?
1:05:47
Chat with your data and get expert level insights in seconds.
1:05:51
They're loved by over two million users and trusted individuals.
1:05:58
in business insider this morning.
1:06:00
morning. Looking like an absolute Chad >> though the photos they sent great they sent a great photographer really really good >> worked >> um >> uh Dart says I moved to a pl a new place two years ago high-risisk area job
1:06:15
related not exactly by choice so I made a bunch of these signs and put them up everywhere two years in and my house has pretty much been the only one in the entire neighborhood that hasn't been broken into and it says protected by Palanteer home security. uh that of
1:06:24
uh that of course is fake, but you know, he he put put it up there.
1:06:29
I think this whole thing's just a funny post.
1:06:31
I don't think that the average uh home intruder knows what Palanteer is.
1:06:36
Um but uh still very funny post. And >> I don't know.
1:06:40
Maybe maybe uh maybe they're part of the retail army.
1:06:44
>> Maybe they're like, "Oh, oh, for that reason I'm not invading.
1:06:48
>> Maybe they're in breaking buy more Palunteer shares because they're so bullish." >> Wait.
1:06:53
Oh, they're breaking into other houses.
1:06:55
But then they see that as a sign of respect. Yeah.
1:06:56
Say, "I'm so long, Palunteer, that I won't break into this house."
1:07:00
>> They just believe in the company's. >> That makes sense. Totally possible.
1:07:03
>> Kylie Kylie Robinson hit the timeline.
1:07:06
She fired back with a quote tweet and she says, "Uh, listening to this, lol.
1:07:08
I did not go into the review expecting to hate it.
1:07:13
Also was aware I'm not the target audience for an always listening device."
1:07:17
And she highlights, she puts us in the true zone, highlights a part of the article.
1:07:22
She says, "I'll admit I'm not the target audience.
1:07:23
I imagine the person who'd want a friend is someone who is likely not a journalist, who may have more social occasions where they can sport an always listening pendant. >> Mhm.
1:07:33
>> Um and uh anyways, so >> I feel like journalists should be perfect for for an always on listening device because every time you talk to them, they're like they're like, "Do you mind if I record this?"
1:07:43
>> They're like, "Let me pull out my phone and record this."
1:07:45
You should just have an an always on recording device is like the perfect device for the journalist.
1:07:51
It's in fact like the new the new notebook for the journalist. >> Yeah.
1:07:55
And you could just say, "Let me know if you ever want to go off the record." >> Exactly.
1:07:58
By default, you're on the record and I'm recording.
1:07:59
I I I I I think that I think that >> I don't know.
1:08:03
I think I think >> long term we might see massive product market fit. Yeah. With friends.
1:08:06
They should do enterprise product for >> Yeah. >> Yeah.
1:08:13
So the journalist gets it, wears it, and as soon as you uh interact with the journalist, you know that you're being recorded and everything you say is on the record.
1:08:20
Uh speaking of journalists, Julia Hornstein has uh a little deep dive on Rahul and some other young founders. They've long been icons.
1:08:29
She says she wrote about how because of AI hype and ease of vibe coding, teens and 20somes are flooding Silicon Valley to build startups instead of attending college or securing big tech jobs.
1:08:37
Uh, founders told me that they'd rather start a company than go to college because of AI gives you a PhD in your pocket.
1:08:45
As Jake Adler said, love Jake.
1:08:48
Uh, because of mass layoffs, Roy Lee thinks the worst thing someone who wants to be who wants a stable future could do is work in big tech. Interesting.
1:08:55
Uh, Roy Lee coming in with a hot take as he's known to do.
1:08:59
Um, college is dead, says zero interest rates.
1:09:01
He graduated from university in 2019. Marvin Vonhagen, 25.
1:09:06
I feel like I was just texting with Marvin.
1:09:10
Marvin, is that right, Marvin?
1:09:15
I think I got to text him back.
1:09:18
>> No, I lit literally I do.
1:09:18
Uh he Yeah, he texted me.
1:09:21
He said, "Hey, we got an intro.
1:09:23
He's releasing a short film.
1:09:23
Um we gota we got to play this." Pokey.
1:09:26
Uh yeah, we got to get him on the show.
1:09:29
Um anyway, um 30% of the Y cominator batch were college students or new grads.
1:09:35
So nice little trend piece with some beautiful, beautiful photography.
1:09:39
So uh shout out to everyone that was featured in Silicon Valley's youthquake in the age of AI.
1:09:46
Founders aren't waiting to grow up, says business insider.
1:09:50
>> Will Manida says basically everyone underestimates how big of a role office selection plays in the outcomes of companies and their cultures.
1:09:55
I recently had the chance to spend 24 hours at LEGO headquarters.
1:10:00
Did you did you enter and then stay the night?
1:10:04
Did you not get the memo about the great locket?
1:10:07
You're not just supposed to be going and hanging out at the Lego >> Lego headquarters going going kid mode.
1:10:14
This is a dream come true for any child.
1:10:17
>> But you know, that's what they say about Will.
1:10:19
>> No, but I'm just I'm still kind of hung up 24 hours at LEGO headquarters.
1:10:21
Did he enter at like one? >> It's bait. It's so good. It's the best. >> Bait. >> Bait. >> It's bait.
1:10:29
But I do like You can see they have they have that Lego on the actual side of the building. >> Do we have a fish?
1:10:33
I feel like we had a fish at some point for bait. Uh yes.
1:10:35
Uh so Lego is a relative lore.
1:10:41
>> LEGO is a relatively strange company for the toy industry.
1:10:43
Even at 10 billion in annualized revenue, the company has never taken a dollar of equity financing is still family-owned and controlled since 1932.
1:10:50
The company is based in Belund, Denmark, a farm town of just 7,000.
1:10:55
Um and and where they're founded is still where they are.
1:10:59
That's pretty remarkable.
1:11:01
The company and the Chris Johnson family through their holding company uh Kirk KBI functional functionally own the town of Belund from the airport majority control to a large majority of the real estate and the hotel tourist infrastructure.
1:11:15
This allows them to make remarkably long-term decisions like 24-hour visits for random American entrepreneurs.
1:11:24
>> Let's pull an allnighter together in the >> We're thinking long term.
1:11:27
>> No, this is maybe you want to pick my brain. Let's think long term.
1:11:31
>> Lego the LEGO execs are participating in the great lock in >> maybe >> said come visit but you got to be locked in with us >> 24 hours >> pulling all nighter we got to get more more info here.
1:11:41
>> You ever were you a big Legoland kid growing up?
1:11:43
>> Not a big Legoland kid.
1:11:43
Legoland I'm going to date myself.
1:11:45
Built uh like I remember when it was built and I remember when it like opened and I was like there on like one of the first days but only went like once or twice.
1:11:53
Um >> but very cool support Legoland.
1:11:56
Big big into Legos generally though. Yeah.
1:11:58
huge huge >> stepping on them.
1:12:01
>> Um yes, one of the worst pains imagined.
1:12:04
Um while some of this investment has been company related, much of it has not been.
1:12:08
The family has been actively involved in turning a blighted racetrack into a new neighborhood and improving civic and school infrastructure.
1:12:15
Uh this kind of long-term investment in pla in a place is only really possible with a large balance sheet and patient private control.
1:12:24
This was a rare thing before the last 10 years, but many tech companies could now fit this mold. That's interesting.
1:12:29
My prediction is we will see many more company towns emerge.
1:12:33
So I mean this has kind of happened.
1:12:33
I feel like Menllo Park is very nice and Certino is very nice and then a lot of that's just a benefit of you know Apple sets up a massive headquarters there.
1:12:46
All the employees are wealthy and so the town the taxes >> California California Forever project could turn into this right.
1:12:52
if you get single tenant in there that's doing like ship building.
1:12:58
>> Yeah, but you need a company to be the backbone of the flywheel.
1:13:00
Uh and that's certainly what's going on in Denmark.
1:13:02
Uh the results of this investment are clear.
1:13:05
Even on a Saturday, many employees were walking, biking to the office with families in tow.
1:13:09
The town felt vibrant with a mix of visitors, employees, and locals.
1:13:13
It's so now now we're finding out that he spent 24 hours there on a Saturday.
1:13:18
So, did he get there Friday night and didn't leave until Saturday night or he's or he slept there on Saturday night and woke up on Sunday and left? I'm so confused.
1:13:31
Uh, so he says it seems like a remarkably pleasant place to live and work that emanate that eliminates many of the trade-offs of highly urban office settings as we see the emergence of dozen latestage privates with fortress balance sheets.
1:13:42
It's hard to imagine the company town not returning. I like it a lot. It's a good thing.
1:13:47
>> I would like to do a TV company town.
1:13:47
I would uh I would love that.
1:13:50
I would also love a turbo puffer company town that sound >> search every bite serverless vector and full text search built from first principles on object storage.
1:14:00
Fast 10x cheaper and extremely scalable. Get started for free. >> Be like linear. Be like cursor. >> Head over to ocean. >> It's time to puff.
1:14:11
>> So Scott Bessant, he is >> he's been on a roll.
1:14:14
He's got a little bit of a little bit of a cur penchant for curse words.
1:14:19
Uh but >> I don't normally like curse words.
1:14:21
I I kind of like when he does it though. >> Yeah.
1:14:24
But uh it it won Guyer Capital over.
1:14:27
Guyer Capital says, "I'd follow Scott Besset into war."
1:14:29
And Scott Bessant uh said, "Why are why the f are you talking to the president about me? F you.
1:14:38
I'll punch you in your effing face."
1:14:40
And Geiger Capital says, "That's my treasury secretary."
1:14:43
Uh anyway, just a funny quote.
1:14:46
I don't know how that got into the uh into >> try this line.
1:14:49
Uh if you have a co-orker, you heard them talking talking to a management uh in a not so kind way about you. Try this out.
1:14:58
Try this out in the, >> you know, around the water cooler.
1:15:02
>> Keep the president from talking about you.
1:15:04
Keep Chat GPT talking about you. Go to profound.
1:15:07
Get your brand mentioned in chat.
1:15:08
reach millions of new consumers who are using AI to discover new products and brands and >> be like MongoDB, Indeed, Mercury, Ramp, Zapier, Workable. Yeah.
1:15:19
US Bank >> and I saw a fun post in the timeline.
1:15:24
Somebody asked what's the best way to get your brand mentioned in KGBT and the answer was profound.
1:15:28
So clearly profound has been dog food. >> They're dog fooding.
1:15:33
>> So preview of what might happen at Meta Connect.
1:15:36
Jukcon has a screenshot here from Semicon Sam.
1:15:39
I was considering releasing it as a paid post, but after much thought, I decided to make it free.
1:15:45
I hope you all enjoy my analysis on smart glasses.
1:15:48
Why smart glasses are already dominated by China.
1:15:50
Why even Apple and Meta have no choice but to cooperate.
1:15:54
So, uh this article says, uh recently there was an article like this.
1:16:00
Meta will unveil new smart glasses called Hyper Nova at its annual connect event on September uh 17th and 18th.
1:16:03
The pre the prevailing view was that unlike the previously released Rayban Metaglasses, the Hyper Nova coming this time would have a display and its price would be high above $1,400.
1:16:14
However, contrary to expectations, according to a report by Mark German, absolute dog, it will launch at $800.
1:16:22
So, uh Gur uh kind of runs through it.
1:16:26
Um, it's still higher than the meta- bands that are around $200 to $400, but uh should be a little should be still pricey, but lower than people uh initially expected.
1:16:35
So, the question trying to be answered by this Substack article is why is that?
1:16:39
I wanted to find out the reason uh I I want to find the reason in competition with Chinese manufacturers.
1:16:48
About a month ago, Alibaba released smart glasses called Quark Vision, but the price is 1,999 yuan. about 280 bucks. That's pretty cheap.
1:16:59
>> Sorry, I'm not laughing at the price.
1:17:00
I'm laughing at the nameark.
1:17:00
You ever want >> You ever want Quark Vision?
1:17:04
>> It's time to It's time for Quark Vision. >> I don't I don't know.
1:17:07
Uh maybe it sounds better in Chinese.
1:17:09
Uh so from Meta's perspective, with China putting products out that cheaply, they might have thought, "How can we manage to charge more than $1,400 and decided to set a lower price?"
1:17:19
I believe smart glasses will become a truly essential device.
1:17:23
this uh art this writer is uh smart glasses pled.
1:17:26
I'm also optimistic about the uh the growth in smart glasses generally VR AR I think uh we're we're we're about to see the churn rates drop and the adoption rates increase.
1:17:36
Uh let me give an example.
1:17:38
Unlike smartphones, smart glasses are much more convenient to operate.
1:17:41
You don't need to move your fingers.
1:17:43
You can operate them through humanity's most concise action, your voice.
1:17:47
For instance, if you were trying to use AI features like Gemini Live on a smartphone, you would have to open the camera app with your fingers, scan things yourself with AI glasses.
1:17:53
Camera on the device is effectively seeing what I'm seeing.
1:17:57
So, there's the advantage that I don't have to issue instructions one by one.
1:18:00
Um, and so uh he lays out kind of a bullcase for uh the um for the smart glasses.
1:18:07
Uh this is the industry's classification of smart smart glasses by generation.
1:18:12
Gen one, which is the current generation, doesn't have a display.
1:18:16
AI features are supported through a smartphone integration.
1:18:18
Gen two, which is next year supposedly, uh will be equipped with a low resolution display.
1:18:24
And then Gen 3 has a high uh and display, full color, 2K resolution AI and spatial computing like what we saw in the Apple Vision Pro.
1:18:32
Uh so starting from uh so he says that's why I believe the second generation is the point where we can start calling them smart glasses.
1:18:40
From the second generation onward displays provide visual information allowing users to access much richer data through the glasses.
1:18:47
Uh to draw an analogy up to the first generation they were like PDAs but starting from the second generation they can be called smartphones.
1:18:53
So very bullish on uh on the growth here.
1:18:55
Um, and uh I think we can get back.
1:19:01
>> Was there anything else here in here that you wanted to run through?
1:19:04
>> Yeah, I just thought the pricing information was interesting.
1:19:07
>> Yeah, >> they could try to run the same playbook of just selling the same playbook that they ran with like DJI. Yeah. Right.
1:19:13
Of just like selling below the actual cost to produce the devices to just try to get adoption. >> Yeah. >> But um >> we'll see. >> It is interesting.
1:19:25
I haven't I haven't seen that much reporting on the bill of materials for the Oculus Quest 3, but I don't believe that they were selling it at a massive discount.
1:19:33
Like I I I I do think it was uh probably profitable on a perunit basis, but then they were just spending so much on R&D to actually build the next versions.
1:19:44
It would be very interesting to see what happens if they released something at the level of Apple Vision Pro, but at the price point of the Quest 4 or something like that.
1:19:52
I really I I'm excited about the smart glasses, but I'm honestly more excited about just a an Apple Vision Pro level image and screen being pulled into something with the Quest's ergonomics.
1:20:10
Also, there's some interesting um so basically brightness and power efficiency are the most important things uh when it comes to displays.
1:20:18
>> And the reason that Apple's Vision Pro can crush it on brightness is because the field of view is actually blocked.
1:20:26
So there's no outside light coming in. Yep.
1:20:29
>> And so they can deliver this like ultra crisp image.
1:20:32
>> And what Meta and Quark are doing is like you can just see the real world and see a display on it.
1:20:36
So the the sort of quality of the image will lag behind that just like ultra high fidelity that you're getting with the Vision Pro. >> Yeah.
1:20:44
I mean, but obviously an insanely real trade-off, right?
1:20:48
>> I mean, the physics of light state that I I like it's an additive process.
1:20:52
So it like if you're outside and it's bright and you want to project a black cube into that world, that's basically impossible from a physics perspective because the bright light's going to shine through.
1:21:07
You're adding light on top of it and there's not really anything that you can do to make the black cube show up on the beach in Santa Monica if you're just walking around.
1:21:16
So there >> there are some serious headwinds there.
1:21:20
That's why Palmer Lucky predicted that the end result of augmented reality would be reprojection, which is what the Apple Vision Pro does.
1:21:26
Take a camera because then if you take a camera and you play that on the inside of the display, you can turn down the brightness all around the black cube and then you can put the black cube over there and you can block out the light that's behind it.
1:21:37
But but occlusion with dark objects in augmented reality uh scenarios is is basically physically impossible. I don't know. Uh seems very difficult. Anyway, whatever.
1:21:48
If you're planning to launch a uh augmented reality headset, you got to get on linear.
1:21:54
Linear is a purpose-built tool for planning and building products meet the system for modern software development.
1:21:59
Streamline issues, projects, and product road maps.
1:22:00
Uh Jerry Ticket says Houston is like if the AWS got Tyler there. What's going on? >> Yeah. How you doing, Tyler? What's new? >> I was just laughing.
1:22:09
I was just so excited about the linear linear. >> Okay. Yeah. Give us an update.
1:22:12
What is What is burning up the timeline in your world?
1:22:16
What was your favorite post from this weekend?
1:22:20
>> Um, okay, let me find a really good one. I I'll get back.
1:22:23
>> Okay, in the meantime, let's talk about Houston, the city in Texas.
1:22:25
Houston is like if the AWS console was a city, says Jira tickets.
1:22:31
Um, and Kathleen Turner says, "Dang, why?"
1:22:35
And Jurro tickets says, "I don't know.
1:22:37
I've never been to Houston."
1:22:40
Like, I I Yeah, I don't even know what this means.
1:22:42
I don't know why this wound up in the show in the run of show.
1:22:43
I think this wound up it wound up in the round show like multiple times for some reason. >> Nice.
1:22:48
>> But did you put it in? >> I put it in. I thought it was funny. >> Why?
1:22:51
What appealed to you about this?
1:22:54
>> Do you think it's an apt analogy?
1:22:54
Have you ever used the AWS console?
1:22:55
Do you know how confusing it is? >> Yes. Okay. >> Yes.
1:22:59
>> So I is that the take just saying it's really confusing. >> Best designed city. >> Okay. Yeah, I get that.
1:23:03
But like >> it's also just funny.
1:23:06
>> Lot lot of horsepower under the hood. >> Good post, sir. >> It's a good post. It's a good post. Shout out Jared Tickets. Uh ASML.
1:23:10
Yeah, this was this was cool.
1:23:13
ASML decided to become a VC according to Wasteland Capital to boost European tech sovereignty and burn one and a half billion in shareholder funds into mal.
1:23:24
Hey, it's not >> we don't know that they burned it.
1:23:27
>> They they yoloed it in uh lithography bun plus third tier LLM meat with a topping of EU bureaucrat dur dur durigious me.
1:23:39
I've I don't know that >> it's a word that I can't pronounce and you can't pronounce meaning that it might be >> a new type of AI hamburger.
1:23:45
Um anyways, people are not >> control of economic matters.
1:23:51
>> So people are not excited about ASML's investment.
1:23:53
They did about three4ers of Mrol's billion >> $2 billion series C.
1:24:00
>> Um Mr is getting valued at just north of Cognition latest round.
1:24:05
Um, and anyways, people are basically saying uh ASML was potentially worried about uh about have, you know, being like too much of like a private company, you know, and just like focusing on generating profits and they have to like, you know, redistribute some of that wealth to the to the broader uh to the broader market. >> Indeed.
1:24:27
uh what did uh >> but anyways it might be I mean if Mistral uh I I think uh clearly it's France's national champion and and effectively Europe one of Europe's um champions and uh I'm I'm sure they can figure out a way to create value and hopefully uh hopefully ASML shareholders get a nice uh nice return here.
1:24:48
Doug Olaflin over fabricated knowledge said this is very simple national champion. Don't overthink it.
1:24:55
There is an authority chess move. This is checkers.
1:25:00
Uh so I I I actually don't know exactly what that like what the interpretation of that thesis is.
1:25:04
Like national champion just means uh like you must be supported at all costs, right?
1:25:08
And so like it doesn't makes it doesn't necessarily matter if it pencils out on on some DCF right now.
1:25:13
It's like we need to continue to support that.
1:25:15
we have the capital, so let's continue to support our national champion. >> Uh, makes sense.
1:25:21
Um, you want to talk about Echoar?
1:25:24
>> Yeah, so SpaceX is buying Echoar's AWS4 and HBlock spectrum licenses for about 17 billion.
1:25:30
The payment will be split. It's up to 8. 5 billion in cash and 8.
1:25:33
5 billion in SpaceX stock, which is crazy.
1:25:39
The big takeaway, the deal allows SpaceX to expand its direct device mobile services more independently beyond its existing T-Mobile partnership.
1:25:47
>> I'm going to pull this up.
1:25:47
Um, Echoar, uh, so they the this is an industry that's heavily regulated >> and, uh, you would think that, uh, in a in a more in a more free market. Yeah.
1:26:02
Uh SpaceX could just say we're gonna start building um we're we're gonna just create this like mobile internet service. >> Nope.
1:26:14
>> And it doesn't work like that.
1:26:15
>> There are specific licenses.
1:26:15
You don't want traffic on the same spectrum, same band of the spectrum.
1:26:20
So >> yeah, uh shares of Echoar rose as much as 26% on Monday uh to a record high of $84.
1:26:27
Its bonds were the biggest gainers in the junk bond market.
1:26:30
Uh yeah, apparently Echoar was like potentially veering towards bankruptcy like they hadn't been.
1:26:37
>> Wait, so so what did Echo Star stock do? >> Up 26%.
1:26:41
>> Because now now it's basically a SpaceX holdco like because they have 8.
1:26:43
5 billion in SpaceX stock. What's their market?
1:26:48
>> So it should trade at like 10 trillion >> potentially. What's their market cap? >> 22 billion. Whoa. >> Wow.
1:26:55
This is a >> So we were just talking So we were talking about this.
1:26:57
So So we were talking about this morning.
1:26:59
There's all these crypto treasuries.
1:27:00
Y >> and then you would think like why doesn't somebody create like the Elon like treasury company and the reason for that is like if you start adding shares then you become a registered investment advisor and there's all this compliance much harder than just putting like digital assets or tokens in in a company.
1:27:17
>> These are just like I have USD, I have Bitcoin, they're kind of the same thing.
1:27:21
I'm putting my treasury wherever.
1:27:21
And then Micro Strategy, now just strategy, wound up just having a ton of Bitcoin.
1:27:27
And then it became this like this way to invest in Bitcoin just with a public ticker.
1:27:31
But Echoar will now be the most concentrated way to get to get allocation into SpaceX, right? >> That's so crazy. That is crazy.
1:27:39
>> Basically, if you bought it Friday, >> Yeah.
1:27:42
>> the basically the value of the business then was just >> like SpaceX. Yeah.
1:27:46
plus the cash they got from this deal. Like the SpaceX stock. >> Yeah.
1:27:52
>> So the company is sitting on this license and they just sold it flipped it into SpaceX stock. >> Crazy.
1:28:00
>> That that is a very that >> I wonder I wonder if they >> Ed Lllo the big the bigger takeaway is I think we got a SpaceX meme stock on our hands soon. This is crazy.
1:28:06
Um >> Oh, you're saying this is your take? >> Well, yeah. Yeah.
1:28:10
So Ed Ledllo his his big takeaway which I agree with Ed.
1:28:12
I I think you are correct.
1:28:14
The big takeaway is the deal allows uh SpaceX to expand its directto device uh mobile services more independently beyond needing to partner with T-Mobile.
1:28:22
They can go direct and cut out T-Mobile.
1:28:24
Extremely bullish for SpaceX direct to device.
1:28:30
Obviously, that's going to be a huge business.
1:28:31
Um and uh and and they're really making a lot of inroads there with partnerships and now owning the actual license.
1:28:37
But the other big takeaway is that now there is a company that where what 25% of their market cap is directly indexed to SpaceX on the and it's just a public ticker.
1:28:48
Like that is a crazy development. >> Bunch of cash.
1:28:50
They're also burning money.
1:28:52
They lost uh 300 million last quarter.
1:28:54
So >> well >> um >> hopefully they'll make it all back on uh on Elon Co. who knows.
1:28:59
Uh anyway, uh numeral HQ.
1:29:04
The only other thing, uh, let me, uh, yeah, you you go for this.
1:29:08
>> Sales tax on autopilot.
1:29:08
Spend less than 5 minutes per month on sales tax compliance.
1:29:12
Uh, while you're looking that up, Tyler, what what did you find for me? >> All right.
1:29:16
So, I I think my favorite post was Will Brown. >> Oh, yeah.
1:29:20
>> He said he was he was at a family wedding in Spain.
1:29:21
His uncle brought um a printed out uh semi- analysis cluster max list of the uh, you know, the the Neoclouds.
1:29:29
He was asking why Prime Intellect is at the bottom. Hey, made the list.
1:29:35
>> Hey, he made the list. That's great.
1:29:37
That Yeah, start in the lead. Fantastic.
1:29:39
At a family wedding in Spain, uncle brought a print out of the semi- analysis cluster mass list and asked why we're underperforming.
1:29:44
Explaining the difference between marketplaces and data centers and how we're not just selling compute, we're also advancing RL infra. I love it. >> Oh, very fun.
1:29:55
>> So, one small problem with the meme stock potential of Echos. >> Break it down.
1:30:02
They've got 29 billion of debt that they had been basically defaulting on.
1:30:10
>> Um >> maybe they'll be selling the SpaceX stock off slowly to pay for the debt.
1:30:14
>> Honestly, just hold just hold just make the minimum payments on the interest and just hold on and just hope Elon gets tomorrow.
1:30:21
Wait, so you're telling me that the narrative around this company is that uh it's a levered bet on SpaceX in the public markets that the ticker that anyone can trade? >> Yes.
1:30:32
>> And the company's already levered up. >> Yes.
1:30:34
You can think >> they don't they're not they don't even need to lever up further. >> Yeah.
1:30:37
>> They're already levered. >> Yeah. Yeah. Yeah.
1:30:38
They're extremely levered. >> Extremely.
1:30:41
>> Except unfortunately they didn't spend >> they didn't they didn't raise that to buy SpaceX.
1:30:46
They just they already had that. They already had it.
1:30:48
They didn't need they didn't even need cuz they already had oh there are two steps most people are like I'm going to become a treasury company then I'll lever up to buy more Bitcoin and my company will act as like a 2x levered Bitcoin.
1:30:59
No this company's already levered up.
1:31:04
>> So basically uh SpaceX just needs to >> uh SpaceX just needs to be a$ 1.
1:31:12
7 trillion company and then they'll be able to just pay off the debt. There we go. >> And pay off the debt. >> Seems doable.
1:31:20
>> And then >> never bet against Elon, >> bro. Never again.
1:31:23
Never never never bet against >> Come on. Uh anyway, Finn.
1:31:26
AI the number one AI agent for customer service, number one in performance benchmarks, number one in competitor big box, number one ranking on G2.
1:31:32
Uh there are so much more in the timeline.
1:31:35
Uh we are going to have guests joining us in 10 minutes, but let's run through some more stories. Oh, the other story.
1:31:41
Uh, OpenAI projected its cash burn this year through 2029 will rise even higher than previously thought to a total of 115 billion.
1:31:52
That's about 80 billion higher than the company previously expected.
1:31:56
Andrew Cotay says, "Now that's what I call a nonprofit."
1:31:58
Um, this uh the numbers are big, but I'm so I'm so inured to big numbers at this point.
1:32:05
I'm like, "Yeah, that seems fine."
1:32:07
I don't know that that that's my take is that like that's that seems completely appropriate for the opportunity like you're building the next big massive consumer company. Everyone loves it.
1:32:19
You have strong product market fit.
1:32:21
All your competitors are kind of bowing out more or less like >> the hyperscalers are bowing out.
1:32:29
>> I would say that they're bowing out of consumer. Yeah, >> I don't know. Nano Banana is ripping.
1:32:34
>> Nano Banana is ripping. Yeah.
1:32:34
AJ uh AJ uh Mid Midha at uh A16Z.
1:32:37
Is that is that his name?
1:32:41
Uh he had a good post about this today.
1:32:43
Uh talking about the revenge of the empire or something like that. Was that in here? Where was it?
1:32:47
Ay, I have him in here somewhere.
1:32:52
I got to get a better tab management situation going. Okay, here we go.
1:32:57
Uh Azn Midha at Andre and Horowitz uh says the empire strikes back and shows chatpt versus Gemini chatpt interest over time on Oh well I mean you're going to trust Google on how Gemini is doing in search.
1:33:16
>> Also there was other reporting that there was reporting that showed that that uh agents are completely throwing like agents that are crawling the web are throw totally throwing trend. >> Interesting. Interesting.
1:33:26
No, I I was completely kidding about Google cooking the the the the results here.
1:33:29
Obviously, they wouldn't do that.
1:33:31
Um but but uh Nano Banana launches and and Gemini is definitely mooning.
1:33:36
Um again, I I see them as two two separate use cases.
1:33:38
Like I I when I think about the when I think about the nano banana product, I don't see that as a direct competitor to uh GPT5 and like the the router to just like answer questions, do things for you.
1:33:53
Like um Nano Banana is incredible.
1:33:57
Gemini clearly has a huge advantage in uh in video and image generation.
1:34:00
That's why we're excited to partner with uh with Fall because they are a vendor for that and uh and we'll help you get set up with it.
1:34:09
Um but >> yeah, most businesses don't necessarily care about have they they're not looking to pick a single model, right?
1:34:18
If you're company like Canva, which uses fall, they're leveraging in multiple different models at any given point.
1:34:27
>> So, if I think about like what what does Nano Banana mean?
1:34:30
I feel like it is a it is an incredible product that will be baked into YouTube.
1:34:35
you'll be able to generate thumbnails within the YouTube studio.
1:34:39
Uh there will be products that people use to generate imagery and that will go out everywhere.
1:34:43
If you're in an email and you need to generate imagery, like it'll be baked into Gemini into into all the products.
1:34:48
Um but but uh this particular spike in the chart reads to me as as as if uh a studio Giblly moment where it's like you get a ton of attention and people come in, but like what is driving catchy PT use right now? It's not Giblies.
1:35:03
That's not why people are coming to it.
1:35:05
like the image generation is is definitely used, but I would say it's probably less than like 10% of queries.
1:35:11
Probably less than 2% of queries, honestly.
1:35:13
Uh just based on my personal use, most of the time I'm looking for a fact.
1:35:17
I'm looking for a breakdown.
1:35:19
I'm looking for some analysis.
1:35:20
Go search the web, put something together, and then every once in a while I go to it and I'm like, okay, now I need to do an image generation thing.
1:35:25
Um, and so I don't necessarily fully agree with this take that the Empire is striking back. I mean, it is a strike.
1:35:32
They they're striking back, but has the Empire won? We don't know. >> Good question.
1:35:38
>> Anyway, uh question for you.
1:35:38
Isaac says, "I don't know anything about watches, but I'm looking for something respectable to wear on my wrist.
1:35:46
Something that a watch nerd might go nice at, but won't break the bank. Any recommendations? What you got, Jordi?"
1:35:55
>> What does not breaking the bank mean? >> Rishard Mill. >> Yeah.
1:35:58
Stay away from the FPJs and the piece uniques because that's going to break the bank.
1:36:02
But >> a nice RM racing machine on the >> wristwatch like a like an FPorn >> that that could work too.
1:36:09
Yeah, >> you're going to want to stay away from the graph diamond hallucination because that's up in the 55 million range.
1:36:14
But a Paul Newman Daytona, that's going to be something that a watch nerd is gonna go nice.
1:36:21
>> Uh fortunately, this this is good news in the watch world.
1:36:24
Trump was invited to the Rolex suite at the US Open men's final >> and he got to hang out with the Rolex CEO, >> Jean Frederick Duour.
1:36:32
Um, and the timeline is expecting some potential resolution or relief from the Swiss tariffs to come this week.
1:36:39
Um, obviously uh tariffs impacting uh at least secondary watch prices right away. Yeah.
1:36:47
Um, they've been kind of >> up across the board.
1:36:49
Uh, so good if you have a bunch of watches you want to sell, bad if you're in the market.
1:36:55
>> Well, if you're looking for a watch, go to getbbezzle. com.
1:36:57
Your bezel concier is available now to source you any watch on the planet. Seriously, any watch.
1:37:01
You can chat with the bezel concier and you can ask them that exact prompt.
1:37:04
You can say, "What's a watch that would make uh make a watch nerd say nice, but not break the bank?"
1:37:10
They might recommend uh I don't know, GMT Master, Batman, Rolex, something like that.
1:37:16
Um, that might be more reasonable.
1:37:18
Uh anyway, Steve Jobs office versus Tim Cook's office.
1:37:21
I think this says a lot about why Apple feels different under Cook, says Sherman McCoy.
1:37:28
But he Sherman got put in the truth zone because that famous picture of Steve Jobs office where it's all messy and Tim Cook's office is all nice and clean. Well, guess what?
1:37:38
>> Let's see Tim Cook's home office.
1:37:40
>> Yeah, let's see Tim Cook's home office.
1:37:41
It could be 10 times messier.
1:37:41
Imagine it's just stacked up. He's just the biggest. Yeah. 10 times the books.
1:37:45
uh just stacks of papers everywhere.
1:37:48
So the picture on the left, it is Steve Jobs, but that's his home office and uh and Tim Cook is of course at the at the work office.
1:37:56
Um but it's still probably something true there.
1:37:59
Obviously uh Tim Cook is the operations mastermind.
1:38:01
Tim uh Steve Jobs is more the creative genius.
1:38:05
And so >> we got a an old email here February 13th, 2005.
1:38:14
Uh, Sergey Bren sent an email to his executive management group.
1:38:18
>> Read the subject line.
1:38:20
>> Subject I rate call from Steve Jobs and then he just types this out clearly ch uh just like stream of consciousness.
1:38:25
So I got a call from Steve Jobs today who is very agitated.
1:38:30
It was about us recruiting from the Safari team.
1:38:31
He was sure we were building a browser and we're trying to get the Safari team.
1:38:34
He made various veiled threats too, though I'm not inclined to hold them against him too much as he seemed beside himself as Eric would say.
1:38:42
So, I just wanted to check what our status was in various respects and what we want to do about partners, friendly companies, and recruiting.
1:38:49
On the browser, I know and told him that we have Mozilla PE people working here largely on Firefox.
1:38:53
I did not mention we may release an enhanced version, but I'm not sure we are going to yet. on recruiting.
1:38:59
I've heard recently of one candidate out of Apple that had browser expertise, so I guess he would be on Safari.
1:39:05
I mentioned this to Steve and he told me he was cool with us hiring anyone who came to us but was angry about systematic solicitation.
1:39:11
I don't know if there's some systematic Safari recruiting effort that we have.
1:39:17
Anyhow, I told him we are not building a browser and that to my knowledge, we were not systematically going after the Safari team in particular and that we should talk about various opportunities.
1:39:27
I also said I would follow up and check on our recruiting strategies with regard to Apple and Safari. He seems soothed.
1:39:33
So, please update me on what you know here and on what you think we should have as a policy.
1:39:37
On another note, it seems silly to have both Firefox and Safari.
1:39:41
Perhaps there is some unification strategy that we can get to these two to pursue.
1:39:45
these two to pursue. combined they certainly have enough market share to drive web masters and they would in fact build >> um the the the phrase in here systematic solicitation it's like that defines the modern tech era so perfectly like
1:40:03
systematic there was a time when CEOs would call each other and be like hey if if my people come to you that's cool but just don't don't create a list of everyone who works for my company and then try and go poach all of them simult in one weekend while we're on vacation. >> Don't call them personally. Text them.
1:40:18
>> Don't call them personally. Text them.
1:40:21
>> Don't have Don't invite them to dinner.
1:40:25
>> Offer them $100 million.
1:40:26
>> Don't go wave surfing with them in Lake Tahoe.
1:40:29
>> If they don't accept a hundred, offer 200. Keep going. >> Please don't do that.
1:40:32
There was >> But it is interesting.
1:40:33
I mean, three and a half years later, they launched Google Chrome. >> Wow.
1:40:37
So it is interesting in in this email. >> Yeah.
1:40:41
>> Like you would think now given what we know about like platforms and operating systems and and data. Yeah.
1:40:47
>> You would think that even at this point Google was thinking we want to own the browser. >> Yeah.
1:40:52
>> But uh you know if if uh and I and obviously I'm sure when he wrote this he wasn't expecting it to one day be public. >> Yeah.
1:40:58
We got to dig more into the browser wars.
1:41:00
We were talking this weekend about uh perplexity. >> Are they over? >> I don't know.
1:41:05
I I think I think there's going to be another run at it for for sure and and we're going to see some some developments.
1:41:10
Anyway, if you're trying to poach engineers from big tech, you know the best way to do it.
1:41:16
Billboard on the 101, go to adquick. com.
1:41:18
Out of home advertising made easy and measurable.
1:41:20
Say goodbye to the headaches of out of home advertising only.
1:41:21
Adquome expertise and data to enable efficiency.
1:41:28
>> Just find the billboards and just surround your enemies with uh recruiting messaging. >> Yeah.
1:41:32
or pull a obby shman and buy 300 billion.
1:41:36
>> He said the largest >> that cannot be true.
1:41:39
>> That >> that cannot be true.
1:41:41
>> It could be true on a pure I would it seems impossible but on a pure volume basis like just like volume of inventory in a single buy. >> Yeah.
1:41:50
May maybe for like a single creative or something like a single image is the biggest.
1:41:54
But like when Apple launched the new iPhone they put billboards in every single city and it's huge and I see them everywhere. It definitely is.
1:42:02
>> And movies, movies come out.
1:42:02
There's there's there's billboards everywhere.
1:42:06
>> It's the most yolo marketing move that potentially of the year.
1:42:10
>> It caught my eye and it made me think I got to buy one. We got to demo it. >> Whoa.
1:42:14
>> Got to make Tyler live with it for a week and see see what happens to him. >> The guinea pig.
1:42:19
>> The qu the question is could you use that money a lot more efficiently, you know, buying ads on Meta?
1:42:26
>> You know, it's a consumer product.
1:42:26
It's probably easy to figure out like who's the target buyer.
1:42:29
You can get the the halo effect of out of home advertising by like buying strategic inventory.
1:42:36
>> I do I do think that there is something special about the having friend. com.
1:42:45
So like when you go to friend.
1:42:45
com you just see the pendant and that's it.
1:42:48
And then you scroll down and you see this like apple-like experience.
1:42:51
It says friend and then you scroll down and it has these questions.
1:42:55
And so if I if I put if it was if it was try friend.
1:42:58
ai and you put that on a billboard, I don't think that converts as nearly as well as friend. com.
1:43:06
>> The domain is the one thing that that I think in the fullness because if the company doesn't work in two years, we can just >> wind the company down.
1:43:13
He he he and and you have to look at the domain as like >> like does it increase your probability of success?
1:43:21
I think for something like this like an always on listening device it's already people aren't going to trust it so domains can deliver trust >> and then does it yeah just increase conversion rate of people just caring enough to to um not not to mention just like seeing it it's a great domain for out of home advertising period. >> Yeah.
1:43:41
>> No no I I truly think it unlocks out of home advertising in a in a completely different way that try friend.
1:43:45
ai would just convert way less than friend. com.
1:43:48
I want to know what's on that website.
1:43:50
I'm just going to type in friend.
1:43:52
com and then I'm on the flow.
1:43:53
So, uh I'm actually surprisingly bullish on a big big campaign, a big out ofome campaign for friend. com. Uh good luck to them.
1:44:03
Well, we have our first guest of the show.
1:44:05
We have Sunny from Grock infrastructure for inference, purpose-built for speed, quality, cost, and scale. Welcome to the show.
1:44:13
>> Thank you for joining the show today. How are you doing? Welcome to the stream. >> I'm doing good, guys.
1:44:16
I'm uh actually at the All-In Summit, so it's like, you know, coming in. Yeah, exactly.
1:44:20
So, I'm just in a green room here.
1:44:22
So excited to be on with you guys.
1:44:25
>> Did you already talk or is that coming up? >> No, no, no. I'm not talking.
1:44:28
I'm just kind of like, >> but still in the green room.
1:44:31
>> Still in the green room. >> Oh, okay.
1:44:31
We got I I I I had to get a favor so I could come on with you guys here. So, >> nice. I appreciate it.
1:44:38
>> Uh yeah, take us through the last uh last week.
1:44:41
I I believe you were at the dinner.
1:44:43
uh what was kind of what was the what was the vibe like?
1:44:46
Just just walk us through your experience.
1:44:50
>> Yeah, I mean really special like look so first things first I would say you know when you think about you know the president what he's really done is he understands that he needs to enable technologists to basically do their thing and I would I would you know summarize it in the following ways.
1:45:04
summarize it in the following ways. one he you know he brought everyone in and said look if you have some kind of issue there's a team of people that you can work with including David Sachs or just himself um to to get things unblocked right and there's many issues that
1:45:18
companies deal with whether you know comes to export control or or you know tariffs that are being put on or fines that are being put on our companies and so he's really making himself available to to help our companies um you know broadly I think he's also understood that um you know AI and technology is
1:45:34
the forefront of where many of you know the innovations for the country will happen including huge infrastructure projects right and so you heard that when the press came in and when they're asking you know the questions how much each company is spending you're looking at you know trillions of dollars of
1:45:48
spend which has downstream impact in manufacturing construction and other places and so you know that that's something he's excited about and I think lastly like this we you know we really want America to win and he wants America to win and so he's basically saying look I've got your I've got your back. I'm
1:46:04
I'm supporting you here and I'm basically, you know, putting this on the forefront.
1:46:09
So, um, you know, that's the high level.
1:46:12
I would say the experience just diving into it was really special.
1:46:14
You know, started with a small gathering on the Rose Gardening Club outside. It was raining.
1:46:19
We were supposed to have a dinner there, but it got moved.
1:46:22
>> Um, and then a bunch of us got, you know, all of us, sorry, got moved into the Roosevelt room, which is connected into the u into the the Oval Office.
1:46:27
And then, you know, he took his time basically meeting with each one of us quickly, getting everybody gathered together and just kind of understanding concerns that folks had.
1:46:38
Um, and you know, basically us getting an experience in Oval Office.
1:46:43
We all got a challenge coin.
1:46:45
We got a pen, which is really cool, like a little like a little, you know, um, a momento, a very special momento.
1:46:50
And then, uh, we all went, uh, you know, it's the East Wing for a dinner.
1:46:54
And, uh, you know, private conversation followed by a little bit of the press came in, which you guys would have seen the videos.
1:46:59
and then uh conversation afterwards and he really took the time to address you know everybody that I was at the table and and you know make sure that if anybody had a concern they had a chance to surface it there.
1:47:11
>> What was top of mind for you specifically?
1:47:14
>> I think like look you know the American AI stack that's really important.
1:47:16
That's something that was published at the AI action summit a couple you know basically middle of July.
1:47:23
And so what we're really focused on is basically um making sure that we help the government understand what that stack looks like.
1:47:33
And so um you know I don't know if your producers can pull it up, but we published something a few weeks ago uh maybe two weeks ago now that basically our version of the stack and we think it's been positively positively received by the the government and the administration in terms of framework.
1:47:49
We're not saying this is everything.
1:47:50
We're not saying it's comprehensive.
1:47:51
We're not saying it can't change.
1:47:51
But really, you know, the the, you know, kind of the Department of Commerce today is out there trying to understand what it should look like.
1:47:59
And this is one view of the stack.
1:48:01
And really, what does that mean?
1:48:03
Let's kind of double click into that.
1:48:04
The stack is important because, >> um, if the US is going to keep export controls so that we can control, you know, highly sensitive technology getting into the wrong hands, you need to look at it from a stack perspective.
1:48:17
A chip alone is not something enough that you should basically, you know, put a control on.
1:48:20
So you got to look at all the pieces.
1:48:22
And on the flip side, if you are going to be a partner of the US and you're going to want to buy US assets, you want to make sure that you have the whole list of things because if you don't have all the pieces, you're going to end up with paper weights, right?
1:48:35
Really heavy and expensive ones.
1:48:35
So you need to have, you know, pieces along all and that's what we sort of took a stab at when we put that out there.
1:48:43
Speaking of the AI stack, can you help me understand at a more precise level how you're positioning the company or or at least telling the story around the company in terms of where you fit in the stack?
1:48:55
because we saw last week OpenAI is doing a deal for custom silicon with Broadcom and then uh uh semi analysis came out with this uh this article saying that basically Anthropic and AWS and Tranium are like super tightly co-designed now Google obviously with the TPU and then
1:49:16
and then I was I was chat chatting with some open AI people they're like you know we actually talked to Nvidia pretty closely like we're like we like I don't know if code design is the right heard, but like we give input and you know the next generation of Nvidia GPUs will be very capable of running chat GPT. Um,
1:49:31
Um, and so so so where h how do you position where you fit into the the American AI stack?
1:49:41
>> Do you guys mind if I pull up a quick screen share?
1:49:43
>> Yeah, you can, but we are live.
1:49:43
So anything you share will be shared.
1:49:45
So do not share all uh your your private key to the those crypto holdings you got. >> There you go. Thank you. >> That was smooth. >> Yeah. Yeah.
1:49:53
>> Yeah. Yeah. then you know um so the way to think about your question exactly >> can you zoom in a little bit is that possible or maybe we can on our side >> yeah maybe you have to do it on your side I don't know if I can but I I can try um you know really where that's called out at the bottom is um so ju
1:50:11
just to answer your question first and I'll I'll try to zoom in uh without >> I think on your side >> um uh so really at the bottom there which is you know this is infrastructure and the bottom is compute so in the compute bucket Right at the bottom here you see Nvidia, Grock, AMD, Qualcomm, Broadcom. Like I said, this is not
1:50:27
Like I said, this is not comprehensive.
1:50:28
You know, Broadcom is helping companies like Google and OpenAI and others make their chips, right?
1:50:32
And so um the idea you know to answer your question is that um the models come higher up but you should be able to look at this stack and say if you picked a piece from each one of these different categories that we've highlighted you can have an end toend AI solution to either train a model to either inference a model or to build an application on top of it. Right?
1:50:54
So those are the three things that this stack should enable and you may not need all the pieces depending on what you're doing. Right?
1:51:00
If you're trying to train a model clearly you don't need databases. Right?
1:51:03
But these are all the pieces that you need to basically do be able to do something in AI. >> Got it. >> Fascinating.
1:51:11
Yeah, this this Thank you for putting this together.
1:51:14
This this document is massive and uh deserves its own like deep dive.
1:51:18
We'll have to dig in deeper uh in another one.
1:51:20
It's if you guys ever want to. >> Yeah, of course.
1:51:24
>> What's the update on the projects in Europe and then what what do you guys have cooking uh stateside?
1:51:32
Yeah, you know, we've launched close to 14 different data centers this year.
1:51:34
Um, including, you know, one that we announced publicly.
1:51:39
Yeah, there we mad decent there.
1:51:45
>> Um, yeah, we've we've uh we've launched 14 this year and and we're we're continuing to expand our footprint.
1:51:50
Um, you know, Europe Europe is really fascinating.
1:51:54
You know, they've you guys saw the announcement with ASML and their investment into Mistral.
1:51:59
So, it looks like they're waking up and and starting to basically put resources behind these things. So I think that's great.
1:52:05
Um you know our f our focus primarily in that region of the world is centered around a data center and arrangement that we have in Saudi Arabia and so that's in in partnership with Humane Ramco digital where it's the largest inference cluster in the Middle East and we believe all the way into Europe and so we serve you know sort of most of Asia, Europe and the Middle East from that data center.
1:52:29
Um and our our goal right now, what we're cooking up is just an expansion of that, right?
1:52:33
So we're working to expand that cluster um add more capabilities and basically more capacity to that cluster because it's it's been wellreceived and well consumed. >> Very cool.
1:52:41
Uh I know you have a heart out so we'll let you go, but uh last question for me on that Mistral uh ASML deal.
1:52:48
Uh it it kind of jumped out to me because it feels like they're almost like jumping a layer of the stack.
1:52:52
you know, like I typically think about like ASML sells to TSMC, which sells to, you know, Nvidia and some other folks, and then and then the application layer and the foundation model labs like sit on top of that.
1:53:04
So, you're kind of a couple couple steps away.
1:53:06
Um, do you have any insight into what they were thinking?
1:53:10
A lot of people are just saying, "Hey, it's a national champion.
1:53:12
They want to support and they're willing to kind of go outside the typical business that they do to to make an investment."
1:53:19
and or maybe they just see it in purely financial terms, but it seems like if it was purely financial, they would have there there's a bunch of other things that they could invest in.
1:53:28
You know, they're not a hedge fund. Yeah. Right. >> Yeah. Yeah. No, totally.
1:53:31
Um I think the points you talked about are valid.
1:53:33
I would add one thing to it, which is if you actually go back and listen to the launch of XAI, what Elon talks about is like, you know, companies and his companies primarily using, you know, AI to better themselves, right?
1:53:46
And I think if you're someone like ASML, if you want a close partner, um, doing that with Mistral is quite smart, right?
1:53:53
How can they improve the tools that they make so that we can get, you know, better chips, better stuff in that layer of the the stack.
1:54:00
And so I would say that's something that is getting underappreciated today, but more and more companies are doing that, right?
1:54:07
Getting more advanced AI so that they can basically do that.
1:54:09
And and from their perspective, they're they'll never be able to do that on their own.
1:54:12
To your point, they're too far down.
1:54:14
So the partnership there maybe we'll get better machines, maybe we'll get better power consumption from those things.
1:54:19
Maybe we'll get you know better lithography from them.
1:54:22
from them. So that would be something that that I I would you know if I was building a business outside of you know Grock today that's something I would focus on is how can I you really not just use this for the high level use cases we've seen but really have it you
1:54:36
know find new materials for me uh look at you know different aspects of physics and those are really hard problems that you need to be very closely embedded with a model maker like a foundational modelmaker if you really want to pull those off. >> Fascinating. Uh well, we will continue >> Fascinating.
1:54:48
Uh well, we will continue to monitor the situation as always and thank you so much for hopping on.
1:54:52
Enjoy the rest of the convers and the updates.
1:54:55
>> We will talk to you soon.
1:54:55
Have a great rest of your day.
1:54:57
>> Thanks for having me, guys. Cheers. >> Yep.
1:55:01
>> Let me tell you about Adio customer relationship magic.
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1:55:10
>> Uh Theo, we have cognition.
1:55:10
One thing, one thing I wanted to highlight quickly because we didn't get to it earlier.
1:55:17
T-Mobile, AT&T, and Verizon all dropped pretty meaningfully on the Echoar news.
1:55:24
>> Yeah, that makes sense because basically going around T-Mobile.
1:55:26
It won't need to go through them uh because they'll own their own piece of the spectrum.
1:55:32
>> T-Mobile's market cap. >> Um 20 billion. >> Close. >> How much? >> 273 billion. >> 273 billion. Wow. Beast. Okay.
1:55:40
I uh >> how much bigger than the stock own?
1:55:48
>> So Verizon SpaceX stock question.
1:55:48
No, Verizon is 1882 billion.
1:55:52
>> I didn't realize T-Mobile was bigger than >> AT&T is 206 billion and Verizon is is bigger than all of them. >> Wow.
1:55:58
It's almost like uh it's almost like owning a monopoly is valuable. >> Yeah.
1:56:03
>> Seriously, like once you get those licenses, it just prints. >> Yeah.
1:56:07
So, it's so crazy that Echoar was like on the verge of bankruptcy, like not making debt payments and they're just like yolo and they weren't even leveraging the spectrum that they had.
1:56:16
>> No, >> they just I just it fascinating.
1:56:17
Um, >> you got a post from >> uh I I'd rather I'd rather talk about this Andrew Macall story.
1:56:24
So, Project Bob has launched. You can go to dashboard. probob. xyz.
1:56:31
Uh Christian Kyle says this is easily the coolest thing happening in the world today.
1:56:36
a hobbyist launching an autonomous drone ship, hoping to circumn the globe.
1:56:40
Andrew, of course, works at Varta Industries on manufacturing in space.
1:56:46
But in his free time, he tried to replicate the LK99 superconductor.
1:56:48
I was there on the night that he tried to get the rocks to float.
1:56:54
It was very, very interesting.
1:56:56
Uh he's just a fantastic scientist and and builder.
1:56:58
And I guess in his free time, he went and built a a boat that drives itself, talks to Starlink and a few other networks and wired it all up.
1:57:07
And who knows, maybe uh maybe it turns into a to a business.
1:57:12
That's the nature of of launching side projects.
1:57:13
If you're really good at them, eventually people will say like, "Well, I'd like to buy some, sir."
1:57:16
And maybe uh maybe the DoD will come to him or the DOW, as they're called.
1:57:22
>> I'm so I'm so excited for the the drone era of exploration, right?
1:57:24
Just being able to send something off and and follow it along live virtually is so cool.
1:57:32
>> I always >> like I I I want Andrew to take this and and uh properly send Antarctica >> apparently and just see like how how thrilling would it be to have nothing for days and weeks and months on end and then and then somebody just comes up on the video and just takes it out.
1:57:48
>> What are they doing down there?
1:57:50
>> Uh anyway, we have our next guest, Scott W from Cognition joining the stream. Welcome to the stream.
1:57:56
How are you doing, Scott? >> How's it going?
1:57:59
>> It's good to see you again. It's been a little bit. >> Great to see you.
1:58:01
I think I recognize that sweatshirt. Is that a founders? >> It is the founders. It is the founders.
1:58:07
It felt like the right thing to do today.
1:58:09
>> We interviewed Alex Karp last week and he he referred to it as the founders fund because back in the day it was actually called the the founders fund and they dropped the which I think is funny. Yeah.
1:58:19
Uh anyway, uh that we're not talking about Founders Fund, we're talking about your company. Give us the news. What's latest?
1:58:26
>> Yeah, so we we just closed a big fund raise led by Founders Fund actually um at uh so so we kind of are talking about Founders Fund.
1:58:33
We we we closed a raise um at a $10. 2 billion valuation.
1:58:35
You know, super grateful for for all the support that we've had. >> Congratulations.
1:58:47
>> And yeah, busy busy month and a half for us since the Windsurf news.
1:58:49
I mean it's uh it's it's been a crazy couple months for code and and for us especially getting to just see the two products mesh together has been has been a lot of fun. >> Yeah.
1:58:59
Um where is the growth coming from?
1:59:02
from? I remember uh seeing a presentation by uh at Microsoft Build and they were talking about the value that Devon can bring to replatforming and that was super concrete for me because you know I can just imagine having an enterprise application written
1:59:18
innet and wanting to move to Python and that being a lot of work to write the test suite and move everything over and just being able to unleash a ton of AI agents and coding agents seemed like incredible value and an incredibly fully high leverage use of technology. Is that
1:59:33
Is that a big piece of the business?
1:59:35
What what what else is changing?
1:59:37
What else is growing in the last year?
1:59:40
>> Yeah, I think that's right.
1:59:40
A big part of what we do is is I kind of describe it as going and taking on engineering toil, you know, and so that includes like all these replatforms and migrations that folks have to do.
1:59:49
That includes version upgrades, testing, documentation, you know, issue triaging, all these various things.
1:59:54
Um, and it's, you know, the reality is that that that's a lot of of what takes up time for software engineers today.
2:00:00
I don't think it's anyone's favorite thing to do, but it is it is a lot of the time for people, right?
2:00:07
And so so that's often what we see.
2:00:08
And um, you know, we we've been working with a pretty big range of companies all the way from from the smallest startups all the way to to some of the biggest enterprises in the world.
2:00:16
But >> yeah, because uh, Devon is in GA, so any startup can sign up for it. Correct.
2:00:19
Um but then obviously you have a you have a very talented team that goes and sells into very large enterprises as well. >> Yeah.
2:00:28
What what's it been uh yeah Windsurf was known for their GT you know GTM team.
2:00:33
What's it been like both just like bolting on or or really integrating a team like that you guys?
2:00:38
Um yeah I'm sure it's really added a lot of firepower.
2:00:44
>> It's been incredible honestly.
2:00:44
I mean, even I think just the two products themselves because um you know, as we were saying last time, like a lot of the the the there's kind of these two categories of product experiences that devs are using today, right?
2:00:54
There's the idees and the agents and even just being able to have both and kind of serve that all-in-one solution with Windinsurf and Devon um has been amazing for us.
2:01:02
And so we've seen a bunch of I mean Windinsurf and Devon were both already each individually growing, but but in the last month and a half it's it's grown even faster.
2:01:11
I want to go into a little bit of a debunkathon, hit you with some uh some data points and you can give me a lot more context.
2:01:18
So, uh the first one that we saw, this is all from uh extremely reliable sources, usually uh random screenshots that I see on X.
2:01:25
Uh but one was that uh uh when when a when a developer uses a an AI coding tool, they generate twice as much code but 10 times as many security vulnerabilities.
2:01:40
Do you have anything to add? Does that sound right?
2:01:41
Does that sound wildly off?
2:01:44
What can we do to stop creating security vulnerabilities?
2:01:47
>> Yeah, there's there's a lot of studies out there.
2:01:49
You know, studies have different sample sizes and they have different ways that they measure these things.
2:01:53
Um, for us, you know, with a lot of the projects that that we deliver because, you know, if somebody's doing a whole replatform or something, you know, that is a concrete project that you're, you know, uh, you're you're setting up a team to do and kind of accounting for how many hours you need to do.
2:02:06
um with with the enterprise customers that we work with, we typically see speed ups of around 8 to 15x in terms of how long it takes. >> Yeah.
2:02:15
So so they're basically they're doing in one hour of an engineer's time using Devon what would typically take eight hours without Devon. Wow.
2:02:22
>> Um and and I think the main thing that you really have to call out here is like it really depends on the use case, right?
2:02:27
And so I think for a lot of these kind of like repetitive tedious things that frankly the engineers don't want to do anyway like that that's where tools like Devon work really really really well.
2:02:36
You know Devon is not necessarily you know you could use Devon to try and kind of like be the ideator with you or something like that but it's obvious it's it's not today what we've optimized Devon for.
2:02:45
Um and so that's that's perhaps uh um what what folks are seeing in some of these different coding products. >> Yeah.
2:02:51
And then on the security vulnerability side, do you need a, you know, okay, you have Devon, but do you need like Bill, like a different agent that just is watching for security vulnerabilities?
2:03:01
In in traditional software development, you might have like, yeah, there's this great developer that can just churn out code really fast, but then we got the guy over here or the gal over here that really knows what what is secure and what's not and and where the flags are.
2:03:15
And you have pen testers.
2:03:17
Like, do is that a different product?
2:03:19
Is that just a different layer of what you're training for or have you have you kind of built Devon in a way that you don't inject security vulnerabilities?
2:03:30
>> Yeah, it's a good question.
2:03:30
So, so I I think with security I I think the main thing I would just call out here is like this is a problem that all engineering orgs have already had to think about and deal with.
2:03:38
You know, it's not necessarily new in the age of AI that you have to think about developers introducing security vulnerabilities, right?
2:03:44
And and yeah, you know, to to your point, we have a lot of these processes in place for that, right?
2:03:49
which is you know the first one probably is just code review itself right I mean people you know typically you you don't allow people to just merge their code straight to master or or or something like that and and similarly you know you want to have similar processes in place for your AI agents I think there will be specific kind of like security based agents but I I kind of imagine it draws
2:04:08
on a lot of the same um codebased intelligence and just like understanding you know what what these functions are meant for or how these are meant to be used which is kind of a shared intelligence and so you know maybe we release our own kind of like security theme to Devon that that specifically does you know uh does this like security review or or something like that. >> Cool. >> Cool.
2:04:27
>> Are you seeing uh companies change their hiring practices at all after implementing Devon and getting getting starting to get value out of it?
2:04:35
I've just been curious to learn how companies are actually adapting as they sort of ramp up AI AI coding tools.
2:04:46
>> Yeah, it's a great question.
2:04:46
It depends a lot on the space.
2:04:47
a lot on the space. uh of company because obviously you know all companies are competing with the others in their space and that's what ultimately comes down to this but honestly I think what we've seen actually it looks like folks taking more and more projects in-house um and so a lot of things that folks typically would have outsourced to a
2:05:05
team of contractors or um you know handed off to a system integrator or something like that they're actually just doing in-house with Devon um and they're able to do that faster and you know one one of our biggest customers actually was um you know is a bank in Latin America that that started using us around the start of this year for um you know some of these refactors and migrations and so on. Um and then just
2:05:22
Um and then just got to the point where their their team was seeing like a lot more effectiveness using the tool and then they they 10x their contract within the last eight or nine months and if anything they're growing headcount they're not shrinking every single one of their you know their engineer if if every engineer is worth way more then obviously you you want more engineers >> want to add more engineers.
2:05:40
Uh okay let's continue the debunkathon.
2:05:42
Uh we saw some data from the census that showed that that AI is cooked. It's done. It's it's over.
2:05:50
Uh it dropped uh the actual data point was for firms pulled by the census of that they have over 250 employees.
2:06:00
The level of AI adoption quote unquote had dropped from 14 to 12%.
2:06:06
A little dip in the chart.
2:06:06
Of course, people are joking about this, memeing about this, uh you know, uh saying it's all over, but also joking that of course this is just one data point.
2:06:17
Uh to me, it seemed extremely low to think that only 10% of businesses are even using AI since AI is kind of everywhere now and everyone uses AI and all sorts of things.
2:06:26
Um anyway, uh what what is your take on like what's going on in that data point or in that stat specifically and and what what other kind of context can you add for us?
2:06:38
Yeah, I think I saw this.
2:06:38
This is the one who's going around Twitter where it says like in July and August there was like a tiny, you know, and then everyone was freaking about Yeah. Yeah.
2:06:44
So, same, you know, I I don't really I haven't looked into the methodology of how they figured out that number.
2:06:49
It's kind of interesting because I mean for us obviously like a lot of our work is with big enterprises, you know, specifically working on these massive code bases and July and August have been our biggest months ever, you know, by far.
2:06:59
Um, so that's that's that's that's in terms of the the data, but but I feel like the high level thing which I would just call out is, you know, I I think there's still a kind of like like collective like I I don't know what there there's like a there's like a collective like refusal to to see, you know, reality, which is, if I were to say it, is is basically we have AI that passes the Turing test.
2:07:25
We have AI that gets an IMO gold medal.
2:07:27
gets an IMO gold medal. have AI that you know does all these crazy things which 10 years ago we we would would have put it clearly called AGI you know and it doesn't mean that you do all of this work for free as a result there's obviously still a ton that you have to do to teach the specific capabilities
2:07:42
and and to make the right product experiences and to get you know actual businesses out there in the world going and using these things but but I I just think the story you know the things that we're asking the AI to do are not harder than getting an IMO gold medal put it that way and so so there's There's a lot of work to do. You know, I don't want to
2:07:59
You know, I don't want to diminish like it's going to be years and years, you know, of taking all of the techniques that we now have and figuring out how to build the right experiences and get them out to everyone.
2:08:08
But but I really don't think also I love that every time I come.
2:08:11
I'm just the I'm just the the crazy AI bull, you know, my new uh but but like, you know, I think it seems very clear that that AI will um do more and more of this work over time, you know, and software engineering.
2:08:25
I think you see this especially which is if anything I think the best coders are the ones whose whose flows have changed the most dramatically right and and you just think about how many engineers there are out there that still you know have to learn these tools and have to get on these things like I I don't think we are due for a slowdown anytime too soon.
2:08:41
Yeah, the the the methodology of the census data was a little bit odd to me.
2:08:47
Basically, they called up uh individual proprietors, business owners, and they said, "Are you using AI?"
2:08:51
And they defined AI as uh predictive analytics, data analytics, image processing, voice recognition, machine learning, uh natural language.
2:09:03
>> So, a bunch of people said no, we're not doing we're not doing data.
2:09:06
>> We're not doing data analysis, which was very odd.
2:09:08
Only 10% of people said yes to this question.
2:09:10
I feel like it should be like 100% because like if you if you're using Stripe like there's machine learning under the hood for fraud detection.
2:09:17
If you're using Gmail like Gemini is right there.
2:09:19
There's going to be autocomplete on your phone is using data analysis.
2:09:23
Like anyway uh my real question is one of the one of the lowest hanging fruits that I see in the software that I interact with is in government, you know, government websites basically.
2:09:35
Uh, I imagine that the census could benefit from having Devon run around write better polling software.
2:09:42
Is there anything on the horizon where you might be working with the government?
2:09:45
Is that something where you need to get ITAR compliance or something before you go in there? Is it on the road map?
2:09:49
What do you think in terms of improving the software that our government uh serves to us? >> Yeah.
2:09:55
No, I I I think it's a great point and as you say, I think there's a lot of work to do and it's a great example of the kind of like, you know, the the messy problems which I I think it is very clear will be solved over the next couple years.
2:10:06
You know, I we there's no reason that the government shouldn't be using tools like these to go and build their websites better and faster and everyone knows, you know, how many bugs there are, how many simple things that could just be fixed, you know, if if there were an AI software engineer available to go and do this.
2:10:19
um a lot of you know it's it's it's it's funny because I think Windsurf actually funnily enough was ahead of us on on you know getting things moving with Fed Ramp and getting certified and all these things but but it's something that that we're working on as well.
2:10:31
So >> that's very exciting.
2:10:33
>> Are you uh are you thinking at all about other acquisitions over the next couple years?
2:10:39
You got a big balance sheet at this point. >> Yeah. Yeah.
2:10:43
You know, I mean the last one went pretty well.
2:10:44
one went pretty well. So now I um it's I I think um it's I I think for us it's it's obviously really valuable to have this capital for a few different reasons you know with model training I think with hiring great talent um with expanding go to market and so on um you know is it possible that that part part of that will also you know go towards you know buying other companies of
2:11:06
course it's possible there are not any plans at the moment but yeah >> yeah um in terms of your position in the stack I see you as uh sort of like initially like a enterprise level application layer company that then is now going down with Windsurf into more of a B2B context, not full consumer but more broad usage um but famously model agnostic, not training foundation models, not working down the stack. And we're seeing the
2:11:34
And we're seeing the foundation model companies um do deals with Broadcom to co-develop chips and and uh what Elon's doing with Samsung.
2:11:44
And there's a lot of these data points.
2:11:45
Are there any other places where you want to at least have better relationships with other with other layers of the stack?
2:11:52
Is any of that important or is it really just like you have your slice and you're just going to go and run at that for the foreseeable future?
2:12:03
>> Yeah, it's it's a really good question.
2:12:04
I mean, I think in terms of relationships, for sure.
2:12:05
I mean, we work very closely with the foundation labs, for example.
2:12:08
you know, we have lots of things going on in terms of um how we do compute or even kind of like partners that we work with on distribution, right, which I think are great.
2:12:15
I I would say, you know, I think the um for for us it's we we obviously I think it's very important for us to just have a lot of humility about where we're coming from and what we're doing.
2:12:27
You know, we're obviously, you know, a very new entrant to the space and and you know, are only like 0. 1% of the way there.
2:12:32
And I think you know for us to be able to meaningfully succeed is going to require a lot of focus.
2:12:39
Um and so I think from that perspective you know I I think the like you know we we know what what is the area that we really kind of want to own and that's that's basically you know everything between the the you know that goes from taking the model the base model itself and then doing the right kind of capabilities work and building that into a product experience that you know real engineers can use every day.
2:13:00
Um, and I think I think we will stay quite narrow kind of within that focus ourselves for for the future.
2:13:05
>> So, you're saying job's not finished.
2:13:10
>> Job's not I mean it's it's it's it's barely even started honestly.
2:13:12
I think and I think like the um I think obviously there there's a you know there there's there's I think a vision of the future where um where as we said you know where where software engineering is just as easy as telling your computer what to do.
2:13:25
Um and and I think the world of software engineering has already changed in some meaningful ways over the last two three years because of you know all these AI coding tools but I think we've got another like 10 20 generations of product experiences you know as a community to to build and unlock until we get to that full future.
2:13:42
So >> uh important question was this latest round of financing negotiated with Founders Fund over poker or chess?
2:13:56
Unfortunately, it was needed.
2:13:56
You know, it was funny actually.
2:13:57
We were um on the weekend that we did the Windsurf deal.
2:14:01
We um obviously I mean it was it was a pretty substantial commitment from us in terms of Windsurf.
2:14:06
And so, you know, we want to we we explicitly needed board approval, but also, you know, wanted to give our investors an update and kind of hear what they thought and so on.
2:14:13
And so, you know, we were on with the Founders Fund team with Napoleon and Peter and and getting their thoughts on on what they thought makes sense.
2:14:19
And I I mean, first of all, they they were they were really supportive of us doing the deal and they thought, you know, the partnership made a lot of sense for for a lot of the same reasons that that we did.
2:14:28
Um but but they also, you know, were very clear of like, hey, like I know this is going to be, you know, a big thing for you guys on the balance sheet and and for for um for for you guys as a company and, you know, we want to be clear that we we we stand ready to to support you in the next thing if this is the deal that you want to do.
2:14:42
Um, and honestly, that's a lot of what gave us the confidence to be able to go ahead with it and close the whole deal, you know, in the 48 hours or 72 hours or whatever it ended up being.
2:14:51
Um, and so >> we're good for our 400 million.
2:14:55
>> Yeah, it's it's it's it's really been amazing.
2:14:58
I I can't I can't shout them out enough.
2:15:00
Um, you know, Napoleon and Peter and the whole team that we've gotten to work with have have been great to us. >> That's fantastic.
2:15:06
Um, tell us the story of the deal that was negotiated over was it poker?
2:15:12
How did that come together? >> Yeah.
2:15:14
So, so it's a funny one in retrospect.
2:15:16
So, so it didn't actually happen.
2:15:18
Uh but but basically when we were doing the the series A, you know, one of the very early rounds of the company, um it was me and Napoleon and you know, I was here and he was there or something like that and and there was like a I think at some point it was clear that the deal was going to get done, you know, but it was just kind of like going through some of the more minor terms and and making sure we were on the same page of everything.
2:15:36
Uh, and we kind of proposed, you know, what if we uh what if what if we just had a nice heads up match to go and settle this and decide whose terms we're gonna take.
2:15:43
We we did not do that, but it's probably probably for the better that we didn't do that, but but but yeah. Yeah. >> Oh, yeah.
2:15:50
But the story lives on as as something on.
2:15:54
>> It almost happened or was at least like joked about, which is fantastic. >> Uh, that is great.
2:15:57
Well, thank you so much for taking the time.
2:15:59
Jordy, do you have anything else? >> No, congrats.
2:16:01
I know you got a busy day, so we'll let you get back to it.
2:16:03
But we always try to appreciate >> try to try to have another reason to come on before the end of the year.
2:16:07
At least a couple, you know.
2:16:08
You know, it's a great lock.
2:16:11
>> Well, there's going to be plenty more stuff to debunk uh through the rest of the year.
2:16:15
There's going to be tons of data points that people read into way too much and we will be giving you a call.
2:16:19
>> I was going to say I look forward to coming on again and being the idiot optimist that just, you know, everyone else is giving their rational arguments about this is going to work, this is not going to work, and I'm just here saying everything's bullish.
2:16:28
I mean, if you want one more, we can talk about inference costs.
2:16:31
I mean, people are saying that, oh, inference costs aren't falling.
2:16:35
You got to use the latest and greatest model and your gross margins are going to be terrible forever.
2:16:39
Uh, debunk that one for me. >> Sure.
2:16:43
No, I mean, I I I think there's so so I I think there's two separate questions there, you know.
2:16:47
One is the question of is the business going to be defensible?
2:16:52
you know, are you going to be able to offer something that that you know the you're competing with your competitors on something that is not just purely a race to the bottom, right?
2:17:02
And then the second thing is like is the cost value trade-off for the customers going to actually make sense, right?
2:17:05
I think the second one is just very obviously true because you know a as these tools if the trade-off is you know doing more and more and speeding up labor right is you know making every accountant faster and making every lawyer faster and so on.
2:17:19
I mean, at some point it's pretty obvious that the machines are cheaper, you know, that that that cheap enough that making, you know, every lawyer three times faster is just obviously a no-brainer, right?
2:17:29
I think on the the point of the first one, you know, obviously it's a great point and and I think that's it's different for every different company.
2:17:36
You know, I think a lot of the businesses in the application layer need to think a lot about, you know, what is their special sauce and what is their differentiation.
2:17:44
Um but I think the answer for for most probably of what that comes to is a combination of one is just really really focusing on specific use cases and delivering solutions that are that are you know really kind of custom solutions for the problem that they're specifically solving and then two is you know I think there is like a real kind
2:18:00
of um I'll call it like a personalization effect that that I think we're seeing more and more you know there's chat GBT memory for example obviously Devon has its own whole knowledge system where you know a a tool just understands the customer and their own business and their trade-offs and everything much much better. That itself
2:18:16
That itself is obviously something that just makes the product, you know, more and more powerful just for them and and is the kind of thing that would command that value.
2:18:24
So I I think that's it's it's, you know, from a perspective of is AI, you know, are we going to have monster intelligent AI that's just so smart, but we just, you know, we just don't we just turn the machines off because they're too expensive, you know, I don't think we'll have that future.
2:18:38
I think there's a there's a a very reasonable question about, you know, where that value capture comes in and and I think that's why all these businesses are thinking about, you know, what is this one thing that I'm going to do really really well that's going to make my business durable. >> It's fantastic.
2:18:51
Well, thank you so much for taking the time to hop on on a busy day.
2:18:54
Uh, good to hear that the job's not finished. I love unfinished jobs. >> It's the best.
2:18:59
I hate when I hate I hate when the job's done.
2:19:02
>> I hate when the job's done. Congrats.
2:19:04
>> Give our best to the team.
2:19:05
>> We will talk to you soon. >> We'll do. Thanks for having me. >> See you. Hi.
2:19:08
Uh, how'd you sleep last night, Jordy?
2:19:11
>> I had >> You had a terrible night, right?
2:19:14
>> I had a brutal night, but not because of my aid sleep.
2:19:15
I had >> No, I I got an 82.
2:19:16
I'm sleeping pretty good.
2:19:18
I think I get the sound effect.
2:19:20
>> I managed to pull a 75 despite >> eight sleep is working overtime.
2:19:26
It was like, we got to get this guy some sleep. There's kids everywhere. >> Three-year-old is up. The one-year-old.
2:19:33
You got a adaptive AI coming in to help you sleep better.
2:19:37
Anyway, go to eight asleep.
2:19:39
com, get a pod five, 5year warranty, 30 risk-free trial, free returns, free shipping.
2:19:42
And we will bring in our next guest, Ara Carzian from ramp. com.
2:19:49
Time is money, save both, easy to use, corporate card, bill pay, accounting, and a whole lot more. >> Good to see you, Ara. How you doing, guys? >> Great to see you.
2:19:56
Thanks for having me again. Thanks for hopping on.
2:20:00
>> So much data data driven chaos in the timeline.
2:20:04
>> Yeah, I want to talk about 996.
2:20:04
But first, let's start with this data that it's completely over and no businesses are going to be using AI because if you look at the trend line, we went from 12% to 10%.
2:20:16
If you track that out on the line, it's going to be 0%. No, not that one.
2:20:22
It might be negative 50% of of businesses using AI.
2:20:26
>> You're talking about the AI adoption data from census.
2:20:27
I am talking about the census AI adoption data folks that brought you the department of motor vehicles. >> Yes. Yes. The real expert.
2:20:35
>> What was your reading?
2:20:35
>> I've talked I've I've been thinking about the census AI adoption data for a long time because we have our own measurement of it with ramp data. Yep. >> That's. comdataindex. >> Yep.
2:20:46
>> Uh what I don't like about the census measurement and why I think it might be underestim underestimating AI adoption is that the question that they have written is not the right way to measure AI adoption.
2:20:56
Essentially, the way the census measures it is they ask businesses, do you use AI to produce goods and services?
2:21:04
>> And that makes sense because they wrote the question back in like 2023 when we weren't really sure what AI was going to look like.
2:21:10
>> But AI to produce goods and services, that's first of all, that's econ speak, right?
2:21:13
That's how economists talk to each other. Yeah. >> Well, yeah.
2:21:16
And even if somebody technically like in my view, if somebody provides any type of services to somebody and they use AI call transcription, >> like someone on their team is like recording calls and like transcribing with AI.
2:21:30
That to me like qualifies as >> I literally had leveraging AI.
2:21:34
>> In 2013, I was running a consumer package goods company.
2:21:36
Our business was making protein shakes.
2:21:38
That was the physical good that we produced.
2:21:40
But we also would transcribe all of our all of our calls.
2:21:45
And so were we using AI to produce goods and services?
2:21:48
I would have said absolutely.
2:21:49
We're using we're using linear regression and we're projecting out our financials.
2:21:53
We're doing all sorts of stuff that fits in the bucket.
2:21:56
But yes, to your point, uh it's >> you're a forwardinking business leader. >> Sure.
2:22:01
>> And and that makes sense, but most people reading that think, oh, am I literally using AI to produce widgets on my factory floor? >> Yep. Yep.
2:22:09
It's it's the kind of question that doesn't really capture the way that AI in the past three or four years of its development has more or less has mostly been adopted by businesses for back office tasks. >> Yep.
2:22:20
So, >> and you know when you look at that 10% it's I think most people would say yeah for most businesses that's pretty low.
2:22:27
Forget you know tech forward businesses just in general. >> Yeah.
2:22:29
So, the overall number of like 10% of American businesses using AI, that seemed ridiculously low to me because uh just consumer LLMs like CHP are at like 50% adoption amongst American adults.
2:22:42
And so, it it just doesn't math with me that someone would be uh that four out of five Americans would be using chat GBT and then walk into work and be like, nah, I'm not going to use AI for my job.
2:22:54
Uh but >> yeah, >> what I'm more interested in is like why do we think that there's a peak and then a fall-off at all?
2:22:59
My theory was like maybe these big companies are getting sold on you got to use AI to produce goods and services.
2:23:06
They try and roll out some zombie change management strategy where they're >> Oh, remember the CL the CLA CEO like did this big thing?
2:23:16
>> I'm going to use AI for everything >> and then he ended up saying like take it back. >> Yeah.
2:23:20
And so >> people are pretty pretty good. >> Yeah.
2:23:22
So, did you have a read on that at all?
2:23:25
>> Well, there's a few things.
2:23:25
One, the sample sizes for these surveys are actually pretty small.
2:23:28
They run these surveys every two weeks. >> Yeah.
2:23:31
>> And uh you know, like most government survey collection, particularly if it's run every two weeks, you're going to get some mixed differences in who responds. >> Sure.
2:23:39
>> So, that's part of it.
2:23:39
I think some of it just might be some noise in the data set because it did come back up in the most recent read. >> Yep.
2:23:44
>> It wasn't that much of a decline in the first place.
2:23:46
Uh so, you could write it off as as a >> noisy data.
2:23:50
The second thing is that it's not unreasonable to think that the fact that this was conducted in the summer might mean that even at the businesses who responded to the survey, the person who responded to that survey at that business might be different. >> Yep. Totally.
2:24:05
>> This is another reason why I really don't like business surveys is that they try to capture what a business is thinking, which is a large complex organization, but they require one person at that business to answer the question.
2:24:15
>> Easy for you to say you've got tens of thousands of businesses and their actual purchasing behavior. >> Yeah. So flip it over.
2:24:19
What is the data actually saying about uh the level of AI adoption in the business world?
2:24:28
>> Uh when we look at ramp spend data, AI adoption is up.
2:24:31
>> AI adoption is now about 45% of businesses in the US. Uh it varies by sector. >> Yep.
2:24:37
>> So adoption is much higher in tech and finance.
2:24:39
About 70% of tech firms on our platform adopted AI in some paid form.
2:24:41
I still think that's probably pretty low.
2:24:45
capturing free usage or capturing employee usage on their own personal accounts.
2:24:50
>> But then even in restaurants for example, we see 20% adoption of AI >> and I think that's likely >> and what does that mean in the restaurant context?
2:24:56
It's it's it's like they pay that could be they're paying for chat GBTs like pro plan or they're using a like >> marketing materials like developing like a you know I mean I've seen menus that have AI generated images.
2:25:09
That's not my favorite example, >> but a much better example is is designing a Facebook ad that uses an AI generated image or copy that really speeds up a lot of the work that a >> restaurant owner otherwise has to do.
2:25:21
I mean, these restaurants and firms often have really small staffs. >> Yep.
2:25:27
>> And so, I've talked to some restaurant owners who use RMP, for example, and talked to them about how they use AI.
2:25:33
And for them, for the most part, it does automate a lot of the sort of not just back office work, but a lot of the work that lets them get back to work of doing the restaurant work that they want to do. >> Okay.
2:25:43
So, uh, let's flip it over to the 996 phenomenon.
2:25:45
There's been some spicy quotes on the timeline talking about how 996 working on Saturday is super trendy. Everyone's doing it.
2:25:53
Uh, what does the data say?
2:25:57
>> So, does everyone know what 996 is in the audience?
2:26:00
I don't I don't think our >> I think everyone knows, but break it down for us.
2:26:04
Anyway, >> 996 I is a is associated with Chinese working culture, though I believe it's actually illegal in China now, though I think it's still often practiced. >> Uh and work 9:00 a. m. to work 9:00 a. m. to 9:00 p. m. 6 days a week. >> Yeah.
2:26:21
Uh, and then it it kind of seems like it's caught fire in in Silicon Valley and tech culture in this whole like wellnessoriented >> run fast, lift heavy, marry early, work 9 a. m. to 9:00 p. m.
2:26:33
6 days a week and just focus on your business. >> Yep.
2:26:37
>> Um, and most of the stories have been vibes based like it's just people in startup world talking about what they're doing. It's true. It's actually happening.
2:26:45
It shows up in >> the question is how will you know a founder works 996? They'll tell you. >> They'll tell you. >> Yeah.
2:26:53
But I mean, a lot of people were wondering, is this a LAR?
2:26:55
Is this is this something where yes, Saturday is for working?
2:26:59
It's for about posting about how you're working, but you're saying that the data actually suggests that there is business activity happening on Saturdays in startups at an increased rate.
2:27:12
>> Well, in the one specific way we looked at it in this one, we looked at who's, you know, employee cards.
2:27:15
So, we're not necessarily just looking at founders.
2:27:18
We're looking at just people at the company. Yep.
2:27:20
>> Um who are more or less expensing business meals >> or like late time meals >> on Saturdays >> or like Door Dash takeout, other things like that.
2:27:31
A lot of the criticism that I've gotten today on the timeline has been like, "Oh, well, you can't tell if maybe some people are saying it's fraud.
2:27:37
It must be these people who are fraudly using their business cards." Like, >> sure.
2:27:41
>> I want you to read my post because in my post I found it it's just SF. >> Oh, yeah.
2:27:47
>> This isn't happening in New York. Interesting.
2:27:49
>> This isn't happening in Austin. >> Interesting.
2:27:51
>> It's not happening in Miami.
2:27:51
This is just an SF thing.
2:27:53
And it's also really new.
2:27:55
This wasn't happening last year. >> Wow.
2:27:58
>> Perfectly coincides with when people started talking about the 996 cultural movement. >> Fascinating.
2:28:04
>> Unless if you want to argue that oh frauds this whole this >> I mean it really proves it really proves there's no such thing as a free lunch because in these cases the employees are getting a free lunch but they had to work on Saturday to get it. >> Yeah.
2:28:15
It's one of the worst ways to do fraud.
2:28:17
It's like, here's my $20 Chinese food. >> Yeah. Yeah. Yeah. Yeah. >> Okay.
2:28:22
So, uh let's think about going deeper in this analysis.
2:28:25
How else could we uh unpack this?
2:28:27
One way I'm thinking is well, >> uh meals make a ton of sense.
2:28:32
If you're working late, you expense a meal.
2:28:34
But also there's just the normal business activity that like you might sign up for a new so marketing software on a Tuesday.
2:28:45
You might also sign up for it on Saturday.
2:28:47
Uh if you're doing that on Saturday, that's probably even less likely to be fraudulent because why are you putting your credit card down with our latest sponsor Turbo Puffer?
2:28:56
because uh you know you if you're signing up for a database tool and you're putting your credit card down uh now maybe they run the credit cards at a different time. Who knows?
2:29:07
But I'm wondering if there's a if there's a a a layer to the onion that you could pull back there.
2:29:12
Are there any other uh data points that you think you'd be looking at in the next few weeks that might uh help you crystallize this and really really uh steal up your position for the for the haters?
2:29:25
So the point you're making is really good because there's someone else who really interesting reply I got was someone who works I guess in credit risk and one of the big signals they had about whether or not an application for their I guess finance software product was fraudulent was whether or not the application was submitted on a weekend. >> Yeah.
2:29:43
>> And they started looking into all of the ones that they got on weekends and most of them were false positives at least the ones from SF.
2:29:49
Totally anecdotal information >> from from SF. Oh. Oh.
2:29:51
Because people because it's fraud everywhere else, but in SF it's the grind.
2:29:56
>> I mean, this is this is really bad for everyone >> but SF because it shows that the great lock in is really only happening in San Francisco area.
2:30:04
It's it's a local phenomenon.
2:30:06
It's not actually people in New York. Oh. Oh, great lock in. Great lock in. >> Okay.
2:30:11
So, going forward, uh, yeah, we got to look at at if business software uh, purchases are up in San Francisco on the weekend.
2:30:19
I also want to know if it's going to spread if we're going to have some mimemetic contagion and we're going to see the great lock in potentially spread to New York.
2:30:25
That would be likely for me. I want to know Miami.
2:30:27
Austin >> might need to get a little bit colder in New York for >> potentially potentially.
2:30:34
>> Um anyway, >> got a little bit close to it, but not maybe a quarter the effect size. >> Wow. Hu huge.
2:30:40
>> And it was only after 800 p. m.
2:30:40
It wasn't like in our chart for for SF like it really is starting at about 9:00 a. m. 10 a. m. >> Wow.
2:30:47
Uh what about uh what about timing?
2:30:50
You said this is a new phenomenon in San Francisco.
2:30:52
Uh if you scroll back the timeline, when do you start seeing a takeoff of this 996 culture in San Francisco?
2:31:02
>> Over the last 6 months. >> Six months. It's that recent. Wow.
2:31:05
>> Yeah, >> that's fantastic. >> We don't see this.
2:31:07
We don't see this in 2024 really at all. >> That's crazy.
2:31:10
I feel like 2024 was definitely a year where people were were working, but I guess it just picked up a whole new whole new gear.
2:31:18
>> That was before the current capital wars began. >> Yeah.
2:31:21
>> When we had this idea, I was I really didn't expect to see anything because when you it's pretty rare to see these kinds of spend shifts in any demographic. >> Yeah.
2:31:30
Especially like when I looked at it nationally, it was completely unmoved because most people don't really change something as worn in as their eating habits that often even, you know, tech employees or workers.
2:31:42
So, I really I really didn't expect to see anything.
2:31:46
And the only time you would expect to see something like this is a pre to postpandemic trend.
2:31:52
2019 to 2021, a bunch of public and private data sets started to show shifts in where and when people were eating, right?
2:32:00
A really classic one from the pandemic era was uh movement from outside the city center.
2:32:04
So, you know, people were spending much less time downtowns and then suburbs started seeing a lot more activity.
2:32:10
That was a really popular one during the pandemic period.
2:32:13
But after the pandemic, you really stopped seeing this kind of shifting.
2:32:17
Most people kind of set in their ways and things were back to normal.
2:32:20
So, the fact that we saw this, only saw it in SF and that it was so recent is pretty rare and shocking.
2:32:29
>> Last question for me on on the the 996 question.
2:32:33
Um, part of it is not just the six, not just Saturday, but the 9 to 9.
2:32:39
Are you also seeing or or do you think there's it's worthwhile to look into uh what's happening from 5:00 p. m. to 900 p. m.
2:32:48
Because that's also the hallmark of the 99 is that it's not like 9 to5 6 days a week.
2:32:53
It's it's 9 to9 and so uh you should expect more employees expensing food late night on a Tuesday on a Wednesday on a Thursday on a Friday because they're they're working longer hours.
2:33:04
And so is there a way that we can measure the weekday hours worked by San Francisco employees?
2:33:13
>> Yeah, one of the really great data sets for this would probably be GitHub commits. >> Oh, GitHub commits.
2:33:17
Yeah, we gota got to call up uh we had the CEO of GitHub on.
2:33:23
We should ask him to pull something. Yeah.
2:33:24
Uh, and then of course there's a public data set, but uh, I think that's mostly for open source projects and and I don't know if the I I know that there's like a heat map of when people commit, but it's only by day.
2:33:34
I don't think it's by time.
2:33:36
So the the data would probably be internal, but uh, I don't know.
2:33:41
I mean, it's a Redmond Washington company, so I don't know if they're going to put something out, publish it, that says that San Francisco is outworking uh, Redmond.
2:33:48
You know, that might be uh that might be a little controversial for for for Microsoft to do.
2:33:57
Uh anyway, uh thank you so much for hopping. Anything else to share? Are we good?
2:34:01
>> Thanks guys for having me.
2:34:01
Subscribe to my Substack. eonlab. substack. com. >> eonlab. substack. com.
2:34:08
We'll throw it before anyone else.
2:34:11
>> Thank you so much for hopping on the stream. We'll talk to you later.
2:34:12
Have a great rest of your day. >> Cheers. >> Bye.
2:34:16
>> Next up, we got Zach from Warp coming in.
2:34:20
Um, before we bring them in, let's tell you about Wander. Find your happy place.
2:34:25
Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and 247 conc.
2:34:30
>> That reminds me, I actually need myself home but better.
2:34:33
>> Writing it down in my notes. >> Oh, yeah. >> Yeah. >> Okay.
2:34:35
Well, uh, we have our next guest, maybe. Yes. Okay, great. Let's bring them in. >> There we go. >> There we go. Second time. How you doing? I love it. >> This is warp. This is warp country. >> Warp country.
2:34:53
I don't understand why I'm wearing a warp themed uh cowboy hat, but maybe I'll explain.
2:35:00
What What's new in your world?
2:35:03
>> I've been uh you know filming a western basically.
2:35:06
You can see me doing a product demo on a horse. >> Very cool.
2:35:10
>> Because you know, why not?
2:35:10
We we just did a uh major launch called Code Country.
2:35:16
theme is all about coding on warp.
2:35:16
And we decided it'd be fun to do it.
2:35:20
>> Uh with a little bit of like, hey, let let's let's show how Warp can help you wrangle your agents.
2:35:24
So, that is why you're wearing a cowboy hat.
2:35:27
>> Zach, I'm pissed off because I was with John last Friday.
2:35:30
John last Friday. uh before we literally before we got to the office and we saw these fine hats and do you remember when I was pitching you on doing hat as a merch for a company that we work with >> and I was the the tagline for the campaign was like >> I was going to I was going to pitch this to Vanta say like this is Vanta country
2:35:51
America's Vant country >> but I guess you beat us to it and you did it very well so so well played it's a great concept um >> you need to you need to great things that that people will remember you by and I don't think people are going to forget the three of us sitting here with these hats on just talking about code country. >> Yeah. So, >> Yeah.
2:36:11
So, >> okay, explain to me what it means to wrangle agents.
2:36:16
I feel like I've used agents pretty reliably.
2:36:20
Like I just this weekend I needed a new breakfast place.
2:36:25
I kicked off chat GPT agent mode.
2:36:25
It went off and hunted around. I got some weird ones.
2:36:28
I posted that uh I asked for a table that was circular and it found me a a used wooden spool uh that's used to wrap coils around and it's actually for like 50 bucks like probably the best circular round big table you can get.
2:36:43
Um so it was thinking outside the box. It was great.
2:36:47
Um uh and then I've also used Claude code obviously I think of that as a aentic.
2:36:52
We've talked to other folks in the show, but uh I saw this interesting dashboard on X where someone had some visualization of all the different agents that they'd spawned out like what does the frontier of using multi- aents look like? What's the frontier?
2:37:09
>> What does the frontier look like?
2:37:11
Frontier look like these days around these parts.
2:37:14
the the the situation is such if you look at um if you look at prodevelopers using agents in their daily workflow, it's um they kind of produce stuff that's not shippable a lot of the time.
2:37:28
Uh >> they produce security.
2:37:30
Hey, you can't argue they do produce security vulnerabilities there, >> you know.
2:37:35
It's like yeah, they you can ship if you're not careful, you can ship security holes.
2:37:38
You can you get to a point where developers on your team don't even know what they're coding. It's really a mess.
2:37:44
It's a vibe code in production right now.
2:37:46
And the thing that we've been focusing on is like how do you get a tighter feedback loop where you can see what an agent is doing.
2:37:54
You can review its work as it goes.
2:37:56
You can make sure the people on your team who are building with agents are like, you know, comprehending what they're doing.
2:38:04
Uh that they're code reviewing the agents code in the app.
2:38:06
And so this is a real a real problem.
2:38:09
If you look at the Stack Overflow um latest Stack Overflow survey, like number one problem that developers have developing with agents is like they produce hard to debug code that they don't understand and so you end up wasting a bunch of time.
2:38:20
So yeah, we're just trying to help help people keep their agents uh you know uh steer them as we talk as as we say.
2:38:31
>> I want to do this whole thing. Yeah.
2:38:31
So what do you think about these here?
2:38:34
Uh, Vibe Code cleanup specialists, people that are making a living now, going around the frontier.
2:38:41
Going to the frontier >> and cleaning up old vibe code and projects.
2:38:47
>> You got to bring a sheriff into town sometimes to clean clean up some messy the messy >> code.
2:38:56
That that to me is like a symptom of something gone wrong with the tooling.
2:39:00
If you're getting to a point where you need like a a janitor or whatever to come in, clean up clean up your code, you want you want to get the engineers on your team to be able to produce that that uh actually goes out to production.
2:39:13
>> I guess my my other take on on this VOD code cleanup specialist that we're seeing pop up is like I don't know there's a world where um there's there's the type of person like the ideas guy who's like I have an idea for an app and I want someone to build it for me.
2:39:26
Then there's the type of person like you, Jordy, who you have an idea, but then you're a Figma expert and you're going to work on design and you're going to turn over something that's really communicative in terms of the interaction design.
2:39:38
Then there's one layer further now with Figma make and other vibe coding solutions where you could actually turn over a full prototype that's pretty functional, but it's not really going to scale.
2:39:48
And so maybe the Vibe Code cleanup specialist is just saying like, "Hey, I'm a really talented engineer. I am truly an engineer.
2:39:56
Uh I I know computer science, but I'm willing to work with the I work well with the type of people that express themselves and what they want to build as Vibe code.
2:40:05
And and and maybe that's an interesting pattern as opposed to the the the software engineer who likes to work with somebody who turns over a a PSD file or Figma file.
2:40:18
>> I think if you look at it like that, it makes a lot more sense to me.
2:40:20
It's like what's the new version of Mox or PRD?
2:40:25
It's like this working app.
2:40:27
>> Uh but it's not a shippable app because it's like, you know, the the agents kind of can't do it yet.
2:40:34
>> It's also where where you run into problems is like these things are amazing for the zero to one use case.
2:40:40
They're less good for the like I'm working at some big company that has millions of lines of code and I want to add a feature to it.
2:40:46
And so for that you really, you know, it's like it needs to go.
2:40:50
You can start with like the vibe coded prototype, but you're gonna need someone to get in there who actually stands behind what they're sending up to their teammate to review. >> Yep. Yep.
2:41:00
>> I hate to get personal partner, but can you talk re revenue?
2:41:05
>> I think you guys have a pretty extreme revenue ramp.
2:41:08
>> Yeah, we're doing awesome.
2:41:08
So, we're uh we're adding millionaire ARR every like seven, eight days, something like that, which is >> you don't see numbers like that around these parts very often.
2:41:22
>> Certainly, >> this is like it's, you know, we're not not It's not a ghost town, man. It's a ghost town.
2:41:27
>> It's a little gold rush. It's a gold rush.
2:41:31
>> Uh but it's pretty exciting times.
2:41:31
Like, it's it's super fun.
2:41:34
the vision that we have of like building uh you know a a development tool which is for the ground up for like how do you go all the way from prompt to production that isn't like your run-of-the-mill IDE or like the 20th just like textbased CLI app but is a unique tool built to get um you know pro code out is really resonating.
2:41:58
It's super exciting fun time to be working on it.
2:42:00
Well, thank you so much for taking the time to stop by the old TBPN saloon. >> The saloon. >> Yeah.
2:42:08
>> Uh we'll talk to you soon.
2:42:08
Have a great rest of your day. >> Great to catch up. >> Thanks a lot, Batman. >> See you. That >> was fun. Code country.
2:42:17
>> Another Cohen coming into the studio, breaking down big fundra exciting.
2:42:24
>> I'm excited for this one. >> Uh legendary poster.
2:42:25
One of the greatest to ever do it.
2:42:27
very excited to have him on the show. Andrew in the chat.
2:42:31
What about >> what's happening?
2:42:35
>> We need to give Andrew more context.
2:42:38
>> We put these on not for you, although you are from Texas, but for the uh Warp, the CEO of Warp, but we'll leave them on because they're fun.
2:42:48
>> I thought you guys put them on for me. I was going to ask that.
2:42:49
That was my first question.
2:42:52
>> Uh no, no, but but uh but but yeah.
2:42:52
Do you ever wear a cowboy hat around the office? I do not. I have boots, not a hat.
2:43:01
>> Okay, >> there you go. Boots.
2:43:01
Boots are Boots are strong. Uh, what's happening?
2:43:03
It's great to great to finally have you on the show.
2:43:08
>> Thank you guys for having me.
2:43:08
I needed something newsworthy enough to make it on here.
2:43:11
So, I had to raise a round just to get on the show.
2:43:14
>> Well, I think you've been on many times via your post. >> Via your post.
2:43:17
We have reacted to many of your posts.
2:43:19
So, >> long time long time guests. Uh, but what Yeah.
2:43:23
Yeah. give it give us the whole kind of back I mean since it's your first time on the show uh in person give it give us kind of quick history of the company and the news >> uh quick history is we got started last April after a team of us had been at
2:43:37
Carbon Health for three and a half years um left in January started the company in April raised around got to work and then fast forward 16 months later we just closed our series A and it's been a fun time so >> congratulations Wow. Look at that. I thought you walked Look at that.
2:43:54
I thought you walked I thought you walked away. You're like, "Fuck this. I'm out." No, >> we got a gong. No, >> we got it going. Congratulations.
2:44:01
Um, how are you positioning the movie right now? >> Yeah. Yeah.
2:44:04
>> Yeah. Yeah. The main thing that I'm trying to understand from like like your your journey like makes total sense like being deep in the weeds and and understanding what what um you know from your time at Carbon it feels like this
2:44:17
category like so many I'm sure you're you're getting sick of like refreshing like Techrunch and seeing another like voice uh AI company that that that uh is going after the market broadly but like how is the what's the shape of the market? How is it evolving? like where How is it evolving?
2:44:30
like where are you guys what is what does your GTM look like and all that good stuff.
2:44:34
look like and all that good stuff. Yeah, I mean here's my general take on the space is like you've got a group of us who are specifically focused on healthcare AI or like you know whatever voice SMS conversational AI for healthcare you kind of have to be specialized on it uh in order to make it
2:44:50
work and I think that's why you know we saw Sierra just raise at 10 billion you've got all the call center companies with their own flavor of like we're no longer shitty IVRs we like have a conversational AI now and so problem is that as you like start to hear about how their implementations are going you start to hear how they from like across different verticals. They're just not doing that good of a
2:45:10
They're just not doing that good of a job at it because they don't understand sort of the nuanced crazy stuff that happens in these healthcare clinics.
2:45:16
happens in these healthcare clinics. And so we we literally have to like almost go on site with customers and understand their workflows, their appointment triaging reasons, like how you actually get a patient to the right place and
2:45:27
then read and write back into their systems of record, which many of them, you know, unlike, again, I'll use Sierra as the example, but like unlike Sierra being able to just integrate with Shopify who has great APIs to go do like, hey, what's my tracking number? What's your return policy? Can you check
2:45:40
What's your return policy?
2:45:40
Can you check the status of my order?
2:45:43
>> We have way harder to work with systems of record.
2:45:46
And I think a lot of folks just don't want to go put in the work or understand how to go make those things happen.
2:45:50
And so I think you'll see companies like us be a lot more successful in getting these practices live.
2:45:56
Um I think you'll see some of the larger companies maybe win some deals and then go spend 9 months building custom software to go make it work.
2:46:02
And then I think you'll see most people pivot out of healthcare over the next couple years because just because it's conversational and generative and open AI exists doesn't make the work any easier to do right now.
2:46:12
>> And that's kind of like the return to the way the industry has always been.
2:46:14
I feel like whenever you dig into healthcare, it's like, oh, well, they're not using they're not using the standard SAS product for, you know, it's the it's like the the whole genre of vertical SAS like is the textbook example where maybe they're using different ERP, different payroll, different help desk software, help, different CRM, like they're they've always had their own little area carved out.
2:46:38
Uh, and I don't know how much of that is just like compliance, but it's like it's certainly a unique thing.
2:46:44
What's the gold standard now?
2:46:46
Like what what are you guys trying to deliver on the product side?
2:46:48
Because I I saw a screenshot you shared of Sierra on their uh you were you were throwing a little shade on the day of their on the day of their launch.
2:46:56
It was an exchange where you're just like can you find me some green shorts?
2:46:58
And they were like, "Well, we have lots of clothes.
2:47:00
Like why don't you look around?" >> Yeah. >> It was pretty funny.
2:47:04
Um but like what what are you guys trying to deliver?
2:47:05
And what do you what do you think bestin-class is right now?
2:47:08
And do the models even need to get better for you to deliver on your vision or or are they are they good enough that it's just more about like deep integration and and workflows?
2:47:19
>> Yeah, I think that there's a lot of tension in someone like a Sierra who's got a very almost deterministic style chatbot and that's been around forever.
2:47:28
I mean, what they're doing is not new.
2:47:30
they're just saying, "Hey, it uses generative AI versus what you used to do, which is keyword matching."
2:47:33
And then sharing some response that you had queued up that was approved by the customer in the chat experience.
2:47:38
Um, and then on the whole other side, you have an experience like chat GBT or Claude, which is purely generative, very, very general purpose.
2:47:45
Anyone can chat with it and you can really get it to do whatever you want it to do within, you know, as long as their guard rails don't pick it up.
2:47:52
And somewhere in the middle is a conversational experience where you call in and you say, "Hey, I'm having this this issue.
2:47:57
this issue. I have this I need an appointment like here's my symptoms and the agent has a defined scope of work but it still needs to follow somewhat of a deterministic path to get you to the outcome right so in order to schedule I have to look up your account verify who you are find the location that you're looking for find available slots find available providers and then ultimately
2:48:16
book the appointment and write that back to the practice management system so there is a workflow or step that has like steps that have to happen in some sort of order to do that right end to end is very complex A year ago, even when we got started, you really couldn't do scheduling end to end unless you were building what was a phone tree of like, you're in this step right now. Choose
2:48:35
Choose one of these three options.
2:48:36
Now you're in this step, choose.
2:48:37
And that's not what I think anyone wants to be the gold standard for an experience when you call into your provider.
2:48:43
And we've always been fully conversational from day one.
2:48:47
And I think over the summer, we made a bunch of breakthroughs on like how we build a whole suite of agents that work together to get the job done.
2:48:52
And so, for example, if you're calling into one of our practices now and you say, "Hey, I'm making an appointment for I'll use like Med Spa as an example for Botox, there is a Botox agent that all it knows how to do is schedule Botox, but it's still conversational."
2:49:06
And then if you're like, "Hey, I actually need to switch to a laser hair removal appointment."
2:49:11
Um, then it switches to the laser hair agent.
2:49:13
The patient never sees anything, but in the background, we're doing a bunch of multi-agent switching and that's the only way to make these things work and still be generative.
2:49:21
And they still have failure rates like 5 to 10% of cases.
2:49:22
is it doesn't work as expected.
2:49:24
You can imagine all the dumb that patients say.
2:49:28
It's like completely random.
2:49:28
And so, and you can't plan for all of those scenarios, but you just have to get This is why I don't think AI doctors will be a thing anytime soon because that margin of error will always exist and it's like they don't want to take liability or responsibility for that.
2:49:42
We can get away with a little bit more margin of error because we're doing administrative functions.
2:49:46
But that's the experience we want it to be is you call in, you know that it's AI, but you're having a conversation with it just like if you were talking to Chad GPT's voice model and it can do the job end to end even if it's scoped to a limited set of jobs. >> Yeah.
2:50:00
How much of uh how you build this is like uh develop an RL environment to actually post-train a model to interact with all the back office and administrative systems versus kind of like create your own deterministic SAS layer that then your agents are kind of interacting with or or are just kind of like function calls within deterministic like business logic.
2:50:30
It's very much the latter.
2:50:30
It's like we've got this app layer where it understands an ontology of a practice.
2:50:36
Services, locations, providers, all of those have their own specific context, right?
2:50:40
There is um different protocol if you're scheduling one appointment versus the other.
2:50:45
Maybe you're like three steps into a triaging workflow now.
2:50:46
And then they do have tool calls where they get to say like I need to create an appointment.
2:50:52
I need to find available slots.
2:50:53
I need to create the patient account.
2:50:55
All of those tool calls have their own business logic and agents that they interact with on their own that it's all very constrained.
2:51:00
So you kind of have like 70% as prompt engineering, 30% as code in the background to be like, "Hey, that's not the phone number the patient's calling in from.
2:51:07
You can't look up that patient, right?"
2:51:09
Because there's security uh factors to consider.
2:51:13
So definitely a lot more of the latter than it is like any sort of RL environment where we're like you don't really >> the conversations don't change that much.
2:51:24
So we rely on the foundational models to handle a lot of the edge scenarios where someone's trying to go off rail and say something that's not in scope of the agent.
2:51:31
>> That makes a ton of sense. Thank you.
2:51:33
>> Do you last last question?
2:51:33
Um the like do you guys internally view yourselves as building vertical software with the end user experiencing the product as an agent?
2:51:46
agent? because I feel like uh there's been a lot of companies come out over the last year that saying like we're building AI agents for XYZ and then if you actually drill down into like okay what are you doing and like what is the experience of a of a of one of your customers it's like SAS right and that's like it can be AI enabled
2:52:04
>> to be clear we're extremely bullish about that >> yeah we're and and we're s and yeah I'm super bullish about it but I but the way that you're describing this and the companies that that are that I think are are are sort of doing good work broadly or like it's not like you're trying to sell that you're just completely reinventing like an entire business model. It's more like we're
2:52:23
It's more like we're building really valuable software and automated workflows for companies and the end result is that the p is the patient or the user will have a a great experience.
2:52:34
>> You sell the solution not the technology. Yeah.
2:52:36
>> And I feel like you're one of the first companies not you know who knows but maybe one of the first companies kind of embrace the new stance.
2:52:42
You don't have aai domain for example. >> No.
2:52:47
Uh I I don't think the practices really give a that it's AI versus some other system. Yeah.
2:52:51
They uh they care like >> we ult I've said this I said a few things from day one but like one is that >> there is inherent product market fit in what we're doing as long as we can make the agents work as expected.
2:53:02
And so if I can schedule appointments reliably, if I can refill prescriptions, if I can do all those things and the front desk doesn't have to do it or the call center doesn't have to do it, like everyone will buy that if it's cheaper, faster, better, you know, whatever you name it.
2:53:16
Um the second is that yeah, they just like don't care that it's AI.
2:53:19
They think it's interesting.
2:53:21
What's nice is like every group has an AI strategy.
2:53:22
They don't know what that means yet and so but they know they want to like partner with a company to go do that.
2:53:28
And so we treat it is all partnerships right now because it's so early, but we're definitely building vertical services.
2:53:33
I would say like that use software to make it really efficient and you don't have to go hire people now to go do the work in most cases.
2:53:43
Um but yeah, it doesn't matter that if it were if it were I suppose an IVR that got like a phone tree that was able to do the same thing like someone would buy that too.
2:53:53
they would just get replaced by the thing that's better and has higher conversion, better patient experience longer term.
2:53:59
And so, >> yeah, that's really the philosophy.
2:54:00
And then longer term, we are going deeper into the stack in terms of the software that we will offer to the clinics to also help them do their jobs better when it's not the AI doing the job.
2:54:10
And so we look at it as like right now we're doing very specific bespoke services for the group like answering calls and scheduling or doing outbound campaigns and texting a bunch of patients saying hey you're overdue for your annual wellness visit or your vaccines or whatever it is and then having a conversation and again getting them scheduled.
2:54:27
Longer term uh you can imagine like we build more of the software that sits again on top of their practice management system but that helps the actual clinic teams do their jobs more efficiently as well.
2:54:37
It's just deeply integrated with the AI component. >> Fantastic.
2:54:42
Thank you so much for taking the time. >> Great to have you on. >> Join anytime. >> Great questions. We'd love to have you. >> Thank you guys.
2:54:47
>> We'll talk to you soon. >> Text me whenever. >> Cheers. >> We will later. Cheers. >> See you.
2:54:52
>> Uh up next we have 11 Labs coming in the studio.
2:54:57
>> Uh he's in the live stream waiting room, but not for much longer.
2:54:59
Let's bring in not from 11 Labs. >> Welcome to the show. >> How you doing? Hey John. Hey Jordy. Thanks for having me on.
2:55:11
>> How do you say your name?
2:55:11
Because I almost greeted you with a hoy miy. >> It's Mati.
2:55:16
Although I had the same problem with Jordi. So I was texting people.
2:55:21
Is it Horty or is it Jordi? >> Horty.
2:55:25
We're going to Spanish roots there. >> That is fantastic. >> Oh yeah. Yeah.
2:55:28
If you went hardcore Spanish, it might be Horti. >> Horti. >> Horti. >> Yeah.
2:55:33
Anyway, uh let's jump right into it. Give us the news.
2:55:36
What's the latest in your world?
2:55:39
>> The latest is today 11 Labs is launching a tender offer of $100 million where we buy >> early stage employees and investors at a 6.
2:55:48
6 billion valuation which is double. >> Thank you guys. >> This is amazing. This is amazing.
2:55:56
Um so no so happy to to be able to to offer that to all the believers from the early days and uh you know we are building we're are building the company for the generation so I'm hoping to align everybody on that belt for that journey. >> Okay.
2:56:12
>> So somebody came to you they wanted to give you 100 million you said I don't need it in the business is like how how did this how did this come about?
2:56:19
Um because somewhat non-traditional to >> for a company to launch >> potentially hire one more AI scientist for 100 right.
2:56:27
Well, well, yeah, a lot a lot of companies would maybe they'd say like, "Let's raise a couple hundred million and we'll do we'll do uh some some secondary as well, but but what kind of what kind of >> Yeah.
2:56:38
What put you in in the position to just focus on a secondary transaction in this round?" >> Yeah, two things.
2:56:44
One, we are growing very healthily as a business.
2:56:46
We got to 200 million in in in in ARR um over the last weeks >> and which which has Thank you. Thank you.
2:56:54
It has been a a you know kind of a interesting journey where we launched the product.
2:56:59
So we started the company in 2022 launched the first product beginning of 2023.
2:57:04
It took us 20 months to get to 100 million in revenue which is at a time super quick.
2:57:09
Now there are some some even quicker uh transitions.
2:57:14
>> Then took us 10 months to get to 200 million in revenue which is where we are today.
2:57:17
And hopefully we'll get to 300 million by end of the year in 5 months. So 201 10 5 months.
2:57:22
So we are growing very quickly and we are doing that in a healthy healthy uh manner.
2:57:25
We have money in the bank to invest in in in GPUs in international expansion.
2:57:30
So we don't really need much more capital in the bank.
2:57:34
And then the second piece is um we we had a combination of acquisition attempts over last months uh and and of course um as someone who came back [Laughter] >> before before 11 Labs. I was at Palunteer.
2:57:52
My co-ounder was at Google P and and we had a very different uh setup.
2:57:58
Palunteer at the time was private.
2:57:59
It was almost 15 years private.
2:58:02
the the equity wasn't very liquid and um and with pod we want to make it very different now as you think about 11 laps so offer frequent liquidity to employees if we continue running in a healthy manner we are having the capital ready to to deploy we want to make sure that
2:58:17
the employees can think about this next 5 10 years so that's where that that early early liquidity is really helpful and you're right we had amazing partners with with SEOA Iconic joining in keing to keen to lead around investment more in the business and and we of course love working with them. So I wanted to
2:58:34
So I wanted to to give them more more more at the table as well.
2:58:39
>> Give us a breakdown of where all the revenue is coming from.
2:58:42
Obviously I can think of millions of use cases and I've seen different companies leveraging 11 Labs but but like where are kind of the pockets where most of the growth is coming from? >> Yeah.
2:58:55
So at 11 Labs we have two key parts of our business.
2:58:57
One is a creative platform side of the business and now the second one is our agents platform.
2:59:00
U most of people will have known us from that creative side.
2:59:05
That's something that has come when we started the company.
2:59:08
That's of course voiceovers for movies, dubbing of movies to other languages, narrations for audiobooks, uh creating music, bringing music into the fault and here uh that's over over now few few million monthly active users that will come through the platform and create incredible content.
2:59:30
And then a second adoption over last over last two years where uh where enterprises like Cisco, Twill, Epic Games bringing bringing the experiences into into Fortnite are are building just incredibly new voice agencies.
2:59:43
And here you can think about call centers, customer support, uh personal agents, media across the business.
2:59:52
roughly we are approaching 50/50 between the two.
2:59:57
So on one side the self-s serve the creators are are half of the re revenue and then enterprises are the additional half.
3:00:04
Um but that kind of other side is going quicker where we've seen >> sorry sorry sorry sorry to interrupt.
3:00:09
So are you competing with the Sierra Sierras the fins the decagons or or drilling down into that enterprise business?
3:00:19
It's also it sounds like yeah I imagine like game like if somebody's creating like a video game they're they're leveraging voice agents as well.
3:00:26
So um but but kind of could you say a little bit more? >> Of course.
3:00:32
So kind of we we on one side we power a lot of the companies.
3:00:35
A lot of the companies you mentioned are our clients. Um >> makes sense.
3:00:40
>> Decagon maven are are some of the example places we work directly.
3:00:43
So a good example is Perplexity who will use voice as part of the interaction to to use Perplexity.
3:00:50
Um another is Epic Games where they've um effectively deployed Darth Vader experience in Fortnite.
3:00:55
So every player could interact with Darth Vader live for the first time.
3:00:59
One of their biggest >> deployments.
3:01:03
[Music] >> As a Star Wars fan, I can do nothing nothing less.
3:01:08
>> And and then of course so many across other use cases. uh chess.
3:01:11
com works with us where you can have personalized learning experiences when you play chess and then other companies like Cisco Twilio where they do use it for both internal use case mentioned Jord where we power their work internally but also for their clients.
3:01:30
So today we both we we power a lot of clients across and then also work directly with some of the holistic voice operations. >> Okay.
3:01:39
help me understand a little bit more about where the business fits in.
3:01:44
Um I I feel like you've trained actual models.
3:01:48
You're a foundation model company in many ways.
3:01:51
Um and then you're also an inference seller.
3:01:54
Uh and you and you've you have clients that effectively buy tokens from you.
3:02:00
Uh they buy MP3s or wave files probably.
3:02:03
Uh but but you're you're doing the inference for them.
3:02:06
So, you're kind of full stack in this AI world.
3:02:10
And then also, I just feel like it's been awesome to see you go on this run because uh there were probably a lot of haters.
3:02:17
I I feel like I saw some haters being like they're going to get steamrolled by the other labs and you haven't.
3:02:24
And you So, what are the sources of defensibility?
3:02:25
Uh and and why like Yeah. Yeah.
3:02:29
Why do you just keep >> Why do the hat Why do the haters keep being wrong? >> Yeah.
3:02:34
I mean it is it is it is uh it's been it's been an amazing amazing run and it's such a unique position that I think was it was contrarian.
3:02:40
It was overlooked early on and people didn't see uh what you saw and so kind of walk me through a little bit of like the structure of the business and and where the defensibility is coming from.
3:02:52
>> Yeah, two answers there.
3:02:52
I think the first piece is um so across 11 Labs we we we started a company with my co-founder Pra is a a an incredible researcher. Yeah.
3:03:04
>> Assemble we think are some of the best researchers in the world in audio. came over.
3:04:28
I wanted to say hi and uh and said that responded that oh I'm a I was an early 11 laps user and still still am but from the day you launched I thought that all the voice uh uh models will commoditize.
3:04:42
Uh but one thing I didn't appreciate is that the true voice experience takes an artist and you guys all are artists.
3:04:51
Um and that's uh that is partly true where I think there's so much nuance across voice.
3:04:56
Uh you you need to create such a distinct experience when it comes to different voices, different languages, different dialects.
3:05:02
Uh so so Jensen's take that that a lot of a lot of our engineers, a lot of our company is being uh effectively crafting those those artistic experiences is true.
3:05:12
Um and yeah, we are we will probably be now Nvidia clients for life too. >> This is a great take.
3:05:18
Uh it's very similar to why uh we saw that news that Meta has a partnership with Midjourney.
3:05:25
Meta has all the money in the world.
3:05:27
They have a ton of scientists, but maybe they don't have the artist that is David Holes at Midjourney who just brings taste to those images and so they got to pay him, which I love to see.
3:05:36
Uh, I want your reaction to speaking of that, where are we in the uncanny valley of voice generation?
3:05:43
Uh, there was news today in the Wall Street Journal that OpenAI is making a fulllength feature animated film.
3:05:51
And in this article, they said the production, they're investing $30 million in this.
3:05:56
It'll be a full uh full featurelength film.
3:05:59
They're trying to do it in 9 months, which seems totally doable in the age of AI, honestly.
3:06:03
Um but they said the production team plans to cast human actors for character voices and hire artists to draw sketches.
3:06:13
And uh and I saw that and I and I just thought like like I I' I've been under the assumption that voice was solved.
3:06:19
Uh even if OpenAI doesn't have the frontier model, you know, if this is a demo of AI broadly, they should be able to figure this out.
3:06:26
Why do you think that they're going with human voices here?
3:06:29
And do you think there's there's something that's, you know, on the frontier?
3:06:34
Give me your timelines for when we might see uh 11 Labs technology in a Hollywood film.
3:06:43
It's I think first of all I think you you can create an amazing experience already and and and and happily we we we did so maybe maybe there's a uh a a a model or skill help where we can where we can work with open AI and help them help them out on on that side.
3:06:57
Um no but they have amazing researchers.
3:07:00
I think I think they are they are going to craft those experiences too.
3:07:03
I think that that you know like Epic Games example is a is a great way of of showing that is possible.
3:07:10
In that case, we worked with recreating working with the estate the voice of James Herald Johns and it did sound exactly like Darth Vader and players were like almost amazed that how is it possible where you have dynamically generated script effectively a live NPC in the game for the first for the first time.
3:07:28
Um similarly in our case we worked um we worked with a legends of of the past like Richard FA his voice where you can really immerse yourself in the story but also with with people like Ariana Huffington or first lady Melania Trump on creating their audio books and the whole delivery of that experience is is is is as good as real thing and the crazy thing it also allows you to do things you could never do before.
3:07:55
you can bring those um bring those content pieces into other languages and still hear that voice.
3:08:00
I think Hollywood is is a is a trickier piece where it might take a a slightly longer time aligning um the the likeness component of how you work with the people, how they get compensated and how um and how you bring those experiences on screen.
3:08:16
Uh we do hope that the first dubbed movies will get into production next year where you have even better thing than what was previously possible.
3:08:24
you get that original expression available in dubbed movies and in 2027 hopefully the first Hollywood movie hits on the screens in in English too. >> That'd be very cool.
3:08:34
Thank you so much for joining the stream. >> Congrats.
3:08:37
Congrats to the whole team.
3:08:39
>> Fantastic progress all over the place.
3:08:42
Um just uh yeah, remarkable to to see.
3:08:42
I love that take about um the artistry that goes into crafting these super differentiated high high tier models.
3:08:54
It's uh it's wonderful to see. You love to see it. >> Thank you so much.
3:08:57
I'm also so proud and happy of our mighty team of of artists uh across in spirits.
3:09:03
So, thanks for thanks so much for having me on, guys. >> Yeah.
3:09:07
Have a great rest of your day. Talk to you soon. >> Cheers. >> Bye. >> Thanks. Bye.
3:09:12
>> Up next, we have Dan from Truck Smarter.
3:09:15
>> Restream waiting room.
3:09:15
It's time to >> People were saying, "Are we going to truck dumber?"
3:09:19
No, we're going to truck smarter.
3:09:21
And we will welcome Dan out of the rear. >> Founder mode. >> He's in founder mode. Dan, how you doing? >> What's going on? >> Good to see you. >> Good. What's going on, guys? Good to see you. Too much. We're trucking. >> We're locked in.
3:09:33
The great lockin has begun.
3:09:35
Uh many financings have been announced.
3:09:38
We hear you have some news to share with us.
3:09:39
Why don't you introduce yourself, the company, and then the news?
3:09:43
>> Yeah, it's been an absolutely packed day for fundraising.
3:09:45
So, I appreciate you guys uh getting us in.
3:09:47
I'm happy to bring the party to freight.
3:09:51
My name is Dan, co-founder, CEO of Truck Smarter.
3:09:53
Uh we're super excited to announce our fundraising and the launch uh of our AI product dispatch as well.
3:09:59
>> What was the fund raise? Give me the details. What happened?
3:10:03
>> Yeah, so we we we we just raised from Socium Ventures, which is backed by Cox Enterprises, and then uh backed by all of our familiar friends, Founders Fund, Thrive Capital, A6Z, BCV to continue building the absolute best tools for chunky companies.
3:10:18
And how much did you raise? >> 16 million. >> Congratulations. >> There we go. >> Fantastic. >> There we go. >> Warm up on that one.
3:10:29
>> Give us uh give us a quick history of the company.
3:10:31
When did you when did you start trucking smarter?
3:10:35
>> So, we started in 2021.
3:10:37
>> Uh we first started by building a load group.
3:10:39
So for folks for for folks that are not familiar, a lot of trucking companies today, so there's what almost a million truck drivers out there, 95% of them, 95% of these trucking companies own less than five trucks.
3:10:50
And the way they find jobs is very similar to you going on Craigslist to buy something. Yep. Right.
3:10:57
So all this information is everywhere.
3:10:59
The information is not entirely verified.
3:11:01
The people are not even verified.
3:11:03
You're kind of just scraping the barrel constantly spending hours every single day.
3:11:07
So that's kind of been the very core of our company.
3:11:09
We started by building a load board that helped them find those jobs uh in a more efficient way.
3:11:14
And then we started layering on a ton of financial services, getting them paid, getting them access to credit.
3:11:19
If you think about these are the small businesses that just do not get access to a lot of these things.
3:11:23
And uh because we're at the very beginning of their revenue journey, we can just see all this information.
3:11:28
Uh and then obviously now with AI uh this year we we we there's just an tremendous opportunity to just make finding a job so much more efficient and that's kind of what we've been heads down on for the last 6 months.
3:11:41
>> There's a poster behind you.
3:11:41
Load boards should be free.
3:11:43
Explain to us uh how exactly does the industry work?
3:11:47
You have to pay to find a trucking job. How does that work?
3:11:53
>> It is it is absolutely crazy, right?
3:11:53
So, if you think about it, uh, for you to for you to access this Craigslist type of thing, you got to probably pay anywhere from 50 bucks to 250, 300 bucks a month.
3:12:04
At the very beginning of our company, we made it extremely clear.
3:12:06
So, we can't really go back from here.
3:12:10
>> We said load boards should be free.
3:12:10
We built software that kind of connected all the disperate pieces of information into a single place, gave it all away for free, and that's kind of the engine for our entire business.
3:12:19
We continue to grow tremendously uh from that.
3:12:21
Uh, and that's where we continue to layer on all these different services.
3:12:26
>> What's the what's the kind of competitive dynamic in the market?
3:12:28
Like, are you going to force everyone to go free?
3:12:31
It seems really obvious to like if there's a barrier to getting a customer, drop that to zero and then figure out how to monetize the customer somewhere else.
3:12:40
I'm surprised no one's done this before, so congrats on the innovation.
3:12:44
But it seems like the competitive dynamic will be like people will try and fast follow you.
3:12:47
So, uh, is it just a race to build more financial products, better products behind the scenes?
3:12:51
better products behind the scenes? like what what's the what's the long term or is it just like you got to get big you got to get all the data on there >> you got to get big right so I think for us right it's a it's a race to layer on additional services a lot of the existing companies there's a lot of big load boards out there they've been around for 50 60 years right so you
3:13:07
think about Craigslist right a lot of people have tried to verticalize all the various categories of Craigslist they've done so in a very real way but Craigslist is still a monster they still do hundreds of millions of dollars of
3:13:18
revenue so there's still a lot of this pattern with a lot of the existing companies But for us, we're just able to layer on all these other things that just makes our platform continue to be more attractive. >> Have you done What the Truck podcast?
3:13:27
>> Have you done What the Truck podcast?
3:13:30
This is a funny Have you done it? >> Yes. >> Yes.
3:13:32
Yeah, I've done this podcast randomly.
3:13:34
They they were talking about nicotine pouches and the guy wanted to have me on. It was really fun.
3:13:38
Uh it's actually a extremely well-run show.
3:13:40
Um but but uh in that vein, like I imagine you can't go on every week, you got to reach truckers.
3:13:47
uh what's working on the growth side? >> Yeah. Yeah.
3:13:51
So I think for us, right, we're the number one load board on the platform on the market today, right?
3:13:54
You search load board, you search free loadboard, we're number one or number two.
3:13:59
>> That's the strategy, right?
3:13:59
Making it free just makes it incredibly easy for anybody to access. Sure.
3:14:04
>> And as a result, you're getting all the people that are coming into the market, right? So >> SEO play.
3:14:09
Uh are you doing any like brand building high top offunnel uh you know awareness with truckers?
3:14:15
Are there specific like campaigns?
3:14:17
so hard because they like the truckers aren't in all one place by definition, right?
3:14:22
They're all over the country.
3:14:23
So, it's not like you can buy one billboard and you're good.
3:14:26
Uh, you know, h how do you reach people and actually create like brand awareness?
3:14:32
>> Yeah, I think for us it's kind of continuing to solve that number one acute pain point, right, which is finding a job.
3:14:37
Uh, and that's kind of what we've been focused on from day one.
3:14:41
And as a result, I think we just have one of the best growth engines that can reach these trucking companies because almost certainly every trucking company has probably downloaded a load board and there's a very high chance that it's ours.
3:14:52
Uh and then as a result, we kind of have that information to just continue to offer them more services. >> Yep. Uh >> fantastic. >> Congratulations. This is fantastic.
3:15:00
We will uh we'll talk to you soon.
3:15:02
We'll let you get back to your day. Have a great day.
3:15:05
>> Loadboard should be free. >> Appreciate it, guys. Thanks.
3:15:06
Thanks for >> Well, On that note, >> we have Yeah, it is past uh Oh, it's 2:20.
3:15:15
Well, we all keep doing these three and a half hour streams.
3:15:17
We keep saying we're going to do two and a half. Uh we always addicted.
3:15:23
>> Tyler, any other breaking news? Tearing up the timeline. Anything you got for me? >> Uh no, no crazy news. >> No crazy news. >> I don't know. Okay, that's good.
3:15:29
Well, we will see you tomorrow.
3:15:31
Uh we will be live from White Common Demo Day. Tune in.
3:15:36
We're going to have a lot of fun there.
3:15:37
And then in on Wednesday, we'll be in New York City.
3:15:39
So, we are going on a little bit of a world tour, a little bit of a American tour. That's right.
3:15:44
This week and we will see you tomorrow.