0:00
There are like ways to make a million bucks and then ways to make a million bucks that could turn into a billion bucks, right?
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0:06
This is Sarah Guo, the queen of AI.
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She's got a $100 million fund that she's investing into AI startups and we invited her on to brainstorm AI business ideas.
0:13
I mean, I think the market for this company is very deep because people want a lot of video.
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And so I think there's a billion dollars of video generation revenue.
0:21
Sarah, how hard is something like this to make?
0:25
People are generating a million dollars cash flow for themselves.
0:27
It's not because they're deep AI people.
0:28
And it looks super real, am I right? What? Is it this wild? This is amazing.
0:45
So what what do you mean by that?
0:45
You're saying there's a ways to make a million bucks and then there's ways to make a million bucks that could turn into a billion bucks. You have my interest. Let's go. Okay, okay, let's go.
0:52
So I I think maybe and I don't mean this in a dismissive way.
0:56
I think venture capitalists are very often accused of dismissing something as like a cash flow lifestyle business or whatever, right?
1:05
Or Which by the way, for anyone who is not in the VC world, you go to a VC, you say I've got this great company.
1:10
I think I can make 5 million in profit in year eight.
1:13
I and then after that maybe we can grow this for another 50 years and one day it could be a thing and they say that's that's a really nice lifestyle business.
1:20
It's like them saying that's cute. Right. It is that's cute, yeah.
1:24
I I remember my first time doing that.
1:26
Of course, the thing is is that anyone who actually is an entrepreneur, including anyone who's a VC, they know that you can oftentimes get richer and have a less stressful life if you have a quote lifestyle business.
1:37
Yeah, so I I'd say like there's many type of valid businesses, right?
1:39
And then also a lot of things that have become very interesting start very small.
1:44
So I I want to recognize that, but I think a reasonable analogy is if you can figure out internet distribution and then get, you know, super powerful models getting increasingly powerful to just do something useful in a niche.
2:00
Those two things together, that's like the new drop shipping.
2:01
You know how like for maybe seven or eight years, I'm like too old to know what the exact timeline was, but there was a period of time where people were like, ah, you know, I'm an internet kid, I'm going to figure out some drop shipping thing and like make my first $100,000. I think this is it.
2:14
Yeah, so so basically for people who don't don't really know, you could go on Alibaba or AliExpress.
2:18
That was like the open AI in this case, right?
2:21
So it was like this thing exists that you didn't have to build, but it's magic. Watch this.
2:27
You could push a button, you never had to make the product, you never had to warehouse the product, you never had to ship the product.
2:31
It will just magically appear at your customer's door, you know, somewhere between one and three weeks later.
2:36
Um all you have to do is the marketing bit and kind of what you're saying is Open AI and the other AI companies have built this magic that basically will take piece of text and turn it into a video or a song or whatever.
2:48
And if you just do the marketing bit, you can actually almost like drop ship a product or a service to the to the customer without having to make it yourself. Is that the idea? That that is.
2:57
Thanks for explaining it.
2:59
And I I think it's like easy with easier with a few examples, right?
3:01
Like copy editing is probably a prototypical one, right?
3:06
You can do not amazing, but like reasonable copy generation with these models today.
3:13
And so there's series of companies where you just have some templates that make it more obvious to somebody writing marketing copy how to use these models.
3:22
And then you have a website with decent SEO and then like you add some stripe integration and you're in business. What's an example?
3:30
Well, I I think like Copy.
3:30
ai and Jasper, these companies started this way, right?
3:35
And and then I have several friends who have shipped like AI companionship apps.
3:38
Just look at, you know, paid apps in the App Store by charting and, you know, some of those people are generating a million dollars cash flow for themselves.
3:45
It's not because they're deep AI people.
3:46
When you say companion, you mean like uh a digital girlfriend? Or boyfriend, right?
3:51
I think people think that it's skewed toward girlfriend in a way that's not necessarily true.
3:57
But if you and you know, you can have your own ethical points of view about like whether or not that's good for people, but it's a pretty basic human need and guess what?
4:04
People want all sorts of different things in terms of niche companionship and how you might distribute that.
4:10
Aren't these quietly very huge?
4:10
Like can we do some like ballpark, you know, give people a sense of the size and scale that these have gotten to?
4:17
So there's there's Replika, I think that's probably the most well-known one, which is a digital boyfriend or girlfriend.
4:22
They kind of try to say friend, but I think the use case is a little bit more in the in the relationship side of things.
4:28
And I don't I don't remember their exact numbers, but I don't think I would be crazy for saying they're doing like 50 million a year in revenue.
4:38
And I believe she had bootstrapped it for a while at least or raised very little money to get there. Is that right? Tell me if I'm off base.
4:43
I might be wrong on some of that.
4:44
Yeah, Eugenia's built a very cash efficient business.
4:47
Okay, is that like code for something?
4:50
Are you an investor in Replika? I'm I'm not an investor.
4:51
She Dude, you just said everything without saying a thing.
4:55
It was basically like you're friends with her, you know the number and they're killing it.
4:58
Are they killing it from your perspective?
5:00
I think they are making a lot more revenue than most startups.
5:06
I I don't think it's fair for me to give the number.
5:07
It's not my number, right?
5:09
Okay, what are the other ones that are interesting? So there's Character.
5:10
ai that has like some absurd amount of traffic, but I've also heard some things about like I don't know if this is all legit traffic or what, but there's Character. ai.
5:19
What are the other ones that are interesting or what do you what do you I want to touch on Character for a second because I I think like, you know, when you look at consumer companies, one of the things that I learned was that the behavior patterns, like when something just really really stands out from all other products in their category or previous categories, that's when you pay attention.
5:38
It's like the, you know, dumbest metric, but it is really clear when something has special consumer behavior around.
5:45
And the thing that is really interesting to me about Character or the companion apps that work really well is like people spend hours with them, right?
5:54
Like, you know, in terms of the number of products, like how many products do you spend hours with every day? Not a lot. Social media?
6:01
Sean, that's like my product that I spend hours a day with. Yeah.
6:06
Um you were at Greylock, I think, when they invested in Discord.
6:09
I I think the timing is there and Discord was one of those things that was probably overlooked cuz it was like, you know, mostly teenagers who play video games that were using this thing and it kind of looked like a chat room, but you're like, ah well, how's it going to make money?
6:23
It's not like Slack where you can charge the company, but the stat was people were spending like 7 hours a day or something on Discord, something ridiculous like that.
6:29
Just living in Discord, it was their social life.
6:31
And so you're like, well, there's there's definitely something there.
6:34
And they were able to make a ton of money just even selling emojis at that point because if you have that much engagement, you can't fake that. Yes.
6:40
By the way, I just went to Character.
6:43
ai and there's a option to chat with Elon Musk.
6:46
And the the preloaded question, why did you buy Twitter?
6:50
So I click it, so it starts a chat with Elon Musk as a character.
6:52
And then it the first response literally goes, you're wasting my time.
6:55
I literally rule the world.
6:59
Okay, so by the way, on according to SimilarWeb, which is like you multiply by two or three and then you divide by two or three and that's the huge range.
7:07
But according to SimilarWeb, it says that Character.
7:09
ai has 310 million monthly uniques. Are you kidding me?
7:15
I mean, that's more than the Wall Street Journal.
7:17
It's more than like a bunch of really popular Is this company really that big?
7:25
I think people want companions.
7:25
This is what I'm saying that the the like engagement characteristics around this stuff is real.
7:31
And so for anybody like starting a new business, you know, one-person company shipping AI companion app to a niche, like generating a million dollars of cash flow for themselves. It's real.
7:43
Do you know how these things grow?
7:43
So I mean, 300 million monthly visits is no joke.
7:47
What is what's the growth channel for something like this?
7:49
Well, I think that's going to be like an advantage in the future.
7:54
I do think one of the weird things about these AI capabilities is they are so novel and unique that they do drive word of mouth.
8:01
For example, with Character, you can make new characters and people share them, right?
8:07
So there's inbuilt virality there.
8:07
But like maybe I'll give you like two other examples of just like when I say the capabilities are just really new and they're powerful and people want to talk about them.
8:18
Like I don't think you can engineer that, but it's just characteristic of these companies.
8:21
Okay, so one example is I am an investor in a company called HeyGen.
8:25
You can make a video avatar of yourself.
8:27
You cannot tell the difference.
8:29
And you know, reaching that bar of quality is new as of this past year and like people create content that is unbelievable and they share it.
8:37
And so like now HeyGen is in tens of millions of revenue. Great.
8:41
They've never spent a dollar on like paid marketing.
8:42
Sam, have you seen this thing before, by the way, HeyGen?
8:44
This is one of those products that I've seen all over the place, but it felt like it was just like people younger than me talking about it, so I felt embarrassed.
8:52
Well, this is not like like the Character.
8:54
ai was like, you know, that's like teenagers kind of sharing stuff.
8:57
It's more like Wattpad or something.
8:59
This is a corporate use case.
8:59
So this is basically using like I make a digital AI of me or of a or or just like a fake character all together and then it can be used in training videos, it can be used in intro videos with customers, things like that.
9:12
So you could basically create a you don't have to actually set up a camera, film a video, have it edited and then post it in order to send a video to a prospect or send a video internally to an in in a training system or educational product.
9:24
And so that's what this is and that's why they it just says at the top raised 60 million in funding, but I think the the the chart I saw was pretty absurd.
9:31
They, you know, they basically raised to 20 million in ARR very, very fast. Holy crap.
9:37
Some of the usage actually also it yes, it's a business use case, but it's like all kinds of businesses, like creators, SMBs, like high-end enterprise advertisers.
9:45
And so like for you guys it'd be like, okay, well, like actually I bet there's a lot more demand for Sean and Sam talking than the amount I'm sure you hang out on the pod a lot, but like then even each of you can contribute.
9:58
And so if the marginal cost of more time of Sam talking is free, like you probably do more with it, right?
10:07
And I think that's just what people are discovering. Have you guys used this?
10:10
Is it the landing page makes it look amazing. Like it I've used it.
10:14
Is it amazing or is it still up and coming?
10:16
No, it's like pretty good.
10:16
This This cross This one crosses the line, I would say, of usable in real real life versus cool demo, which is the hard thing to say.
10:24
You know, you get a lot of cool demos, then you go in and you try to use it for your use case, and you're like, "How come the tweet had such a good output, but mine is kind of whack?" Every single time.
10:32
Or like, "Well, this is good, but it won't let me change the text on it, which is what I would need to use it in my my real thing."
10:37
I would say this one is is definitely production ready.
10:41
They wouldn't have, you know, tens of millions in revenue if they weren't actually usable by customers.
10:46
and they just did a like a public campaign with McDonald's, right?
10:47
Like an advertising campaign. some good limits, right?
10:49
Like you can't be like moving around.
10:51
It's like a face on camera, at least that's what it used to be when I tried it like 6 months ago.
10:56
Yeah, there's some new stuff.
10:56
You should try like, you know, you you can be walking around now, right? Okay. I stand corrected.
11:01
All right, guys, really quick.
11:03
So back when I was running the Hustle, we had this premium newsletter called Trends.
11:06
The way it worked was we hired a ton of analysts, and we created this sort of playbook for researching different companies and ideas and emerging trends to help you make money and build businesses.
11:15
Well, HubSpot did something kind of cool.
11:17
So they took this playbook that we developed and we gave to our analysts, and they turned it into an actionable guide and a resource that anyone can download.
11:25
And it breaks down all the different methods that we use for spotting upcoming trends, for spotting different companies that are going to explode and grow really quickly.
11:32
It's pretty awesome that they took this internal document that we had for teaching our analysts how to do this into a tool and are giving it away for free that anyone can download.
11:41
So if you want to stay ahead of the game and you want to find cool business ideas or different niches that most people have no idea they exist, this is the ultimate guide.
11:50
So if you want to check it out, you can see the link down below in the description. Now, back to the show.
11:56
All right, everyone's back.
11:58
Can they just Can we just upload our YouTube page, or do we have to stand in front of it and film?
12:03
You have to stand in front of your web or phone camera for 2 minutes and film, and it's more of a safety thing than anything else because they don't want people being able to take your YouTube and make you, if that makes sense.
12:13
Like they want they want you saying specific words about like, "I, Sam Parr, say it's okay to make this avatar."
12:20
And you said that you started the podcast by saying there's like a lot You had a real You The line you said was awesome, which is like there's a bunch of ways to make a million dollars that could eventually become a billion.
12:29
Is this one of those companies where it started that way?
12:30
Uh I think I mean, I think the market for this company is very deep because people like they want a lot of video.
12:38
And I think more like if you just think about the domain of making video, you guys know much more about this than me, but like people want a lot of control, right?
12:48
They want quality, they want specific expression and brand and motions, and they want like one person, two people, three people, like person walking around, a product, whatever it is.
13:00
And so I think there's actually a lot like there's a lot we still cannot do with research, and this is the company wants to continually pull like push the bounds of what you can do.
13:10
And so I think this is a good example of like I think there's a billion dollars of video generation revenue for them or for others, but like, you know, you you actually have to invest in the product pretty deeply, but it doesn't mean that your wedge can't be really powerful uh across a single use case.
13:27
Sam, have you seen the ones that do this for D2C products?
13:30
They'll AI for D2C product ads. So go to icon. me.
13:37
If you scroll down, you can watch the video.
13:38
So I see the video of the Asian dude who's holding like a collagen peptides thing.
13:43
So that's a AI generated video.
13:46
It's the product in his hand that's not actually in his hand with a script that was written. He never recorded it.
13:50
And now you have a UGC very authentic-looking ad for an influencer. You go to the next one.
13:56
Look, he's holding a different product.
13:57
That's cuz he didn't reshoot it.
13:59
They just put a different product in his hand, and it looks super [ __ ] real. Am I right? What? Isn't this wild? This is amazing.
14:08
And so he's got another one with ramen.
14:10
And so what he's doing is interesting.
14:11
What he's doing is he's letting actual In so these are not AI generated people. This is a real person.
14:15
This is like an Instagram guy who's got like, whatever, hundreds of thousands of followers.
14:18
So he's letting popular Instagram people say, "Hmm, okay, I'll do it.
14:22
I'll create my own my digital twin that will be able to do my brand like my branded content."
14:29
So a brand can come in, request from a let's say an Instagrammer with a million followers, and say, "I want you to sponsor this video. Here's the script. Here's my product."
14:36
And if I click yes, then it will AI generate that video.
14:38
I never needed to like open up a package, grab a thing, you know, take take 20 minutes, set up my tripod, record an ad, send it to the brand, ask them if it's okay, then they say yes, and then I get paid.
14:49
Instead, in this case, it's basically like I just approve the brand, it uses my digital twin to make the ad.
14:54
If I'm cool with the ad, I get paid. And that's it.
14:59
And so that's what he's doing.
14:59
Our Kads is the same thing.
15:00
If you go to Our Kads, it's like pretty [ __ ] wild.
15:01
And in And their case, these are fake actors.
15:05
So these women that you see on the thing that are like promoting stuff, these people do not exist.
15:11
This is an AI generated woman who looks like a real person that is promoting some product.
15:16
And you script it, and you can, you know, get these made.
15:17
I These are the Or Or it might be like a real person, but they said like license to the company, you can do whatever you want with it. Yeah, exactly.
15:25
Uh but I think in this case they they might have started with a couple of those.
15:28
Like I think they found one of the girls from this like on Fiverr or something.
15:32
Um but the idea would be I I I don't know too much about the under under the hood stuff of these.
15:36
I I just started playing with them, but the idea would be that, you know, people are not going to know what the hell's real and what's not.
15:42
This These look like real people in their home giving a genuine endorsement of some product that they like, and it is very simple to create.
15:49
I think, Sarah, this is the type of idea you're talking about where two people can kind of take the existing models, you know, maybe customize them here, but then it's just in a wedge.
16:00
In this case, it's for e-commerce companies, and they're going to try to build a business here that will do It'll be these both these businesses are very quick to get to, you know, mid-seven figures of revenue without, you know, much marketing spend or much of anything just cuz the product is such a wow product.
16:14
And then, you know, from there, who knows if it can get, you know, really enormous or or not.
16:20
Yeah, and I think a piece of it is just like for for me like, "Okay, what's the difference between like the first million and the next 999 million?"
16:25
It is whether or not the capability exists in the company to make the product deeper and keep expanding scope for what you do for your customer, right?
16:38
And but there's a ton of these wedges.
16:39
So he is staying with visual content.
16:45
Uh you can use this cadre of models.
16:47
They're open source to be fine-tuned for different use cases that are super commercial, right?
16:51
So it could be models or creator videos for e-com, as you described.
16:55
It could be renderings for like interior design or buildings.
17:00
I don't know if you guys have ever looked at a floor plan.
17:02
Like maybe I just have terrible visual-spatial reasoning, but I can't look at a floor plan with like a couple blocks and then like a fuzzy piece of fabric and be like, "Yes, I see it. That is the room."
17:15
I'm putting my life savings into this.
17:17
And our friend Peter Levels has a thing where you take a picture of your home, and then it does interior design for you and shows you mock-ups, which is pretty cool.
17:24
Yeah, but but I'd say like those, you know, those renderings traditionally generated cost like thousands of dollars, right?
17:30
And now if you can give it to people for very little incremental cost, like that's an interesting wedge.
17:35
Like there's a handful of AI headshot companies making revenue.
17:38
If you guys have ever gone like a a professional headshot taken, Yeah, dude, I So this actually this is like a kind of actually interesting version of the drop-shipping idea.
17:48
So these are This is I I bet you this would work.
17:51
So there was an ad I saw on Facebook, I think. It was a Facebook ad.
17:54
And it basically was a guy He had a headshot, I think, of somebody who I recognized.
17:57
Maybe it was a VC in Silicon Valley.
17:59
It was basically like, "If you're in San Francisco, I take awesome headshots for you.
18:06
You You should have a great shot for your website, for your LinkedIn, whatever. It's good for business. Good for your career."
18:10
and it was like $300 and I went to some warehouse-type of place in some some little like photo shoot studio in San Francisco, stood there awkwardly, got like headshots made, and paid this guy, you know, 350 bucks.
18:24
And he was running Facebook ads profitably to do that.
18:25
So he was able to put in, and he was acquiring a customer for, whatever, 70 bucks, and he was generating 350 bucks off them.
18:32
And now you could run that same funnel just without the San Francisco studio and without the guy taking the picture and without any of the cost, right?
18:40
Like you just say, "Awesome, give me a couple of your photos," and then boom, here you go.
18:43
And I've seen a couple of these go viral of like viral headshot, viral yearbook ideas, but I haven't seen too many people just like running paid on them and making them work.
18:52
But I'm pretty sure that you could create a paid funnel that would print cash for a period of time.
18:59
Yeah, but what's the what's an exa- Like so I've seen the same ones where it's like you look like a '80s glam shot model.
19:06
Remember like I I think the the professional one, people are willing to pay more, right?
19:09
So if it's if it's actually going to be for your example of one?
19:11
Yeah, like look at this um look at this company Aragon. ai.
19:13
Oh, dude, look at this landing page. This is genius.
19:17
They just have a side-scrolling carousel, and it's the before's, and then there's a line, and then they just that same photo becomes the after. That is very well done. That's good.
19:24
Uh Sarah, how hard is something like this to make?
19:30
So like there are a million of these wedges, right?
19:33
And I think that means like it's an amazing time to, as you were saying, like be good at distribution.
19:39
Understand like how to make a funnel and how to market something.
19:45
And like to be an idea person, right?
19:47
Fundamentally, like if you run into problems all the time, you like see the basic capabilities, you're like, "Oh, I can think Like you guys are both like, oh, I can think of like five other use cases for this, right?
19:56
the way, you know the distribution thing, so it's a good example.
19:57
The I so I invested a little bit in Jasper, and Jasper was started by guys who were internet marketers first, not AI researchers, not AI, you know, engineers, not not even frankly very good engineers probably.
20:10
They were just like internet guys, internet internet business guys.
20:14
And they were I think they were doing something before this that wasn't really working very well, but they had spent a lot of time building like internet marketing funnels.
20:22
And so when they got access to probably chat GPT-3 or something like that, they they were kind of back before or sorry, before chat GPT, just when it was GPT-3, they got access to the API, and they built Jasper, which was a took that same capability, but now made it useful for marketers.
20:37
So if you're a marketer, you need a blog post written or an email, or you needed um, you know, copy written for an ad, whatever it was.
20:43
They just made a standalone tool that would do that.
20:46
Under the hood, it's, you know, the OpenAI model is doing 80-90% of the work.
20:51
They maybe customize the last last mile of it.
20:53
But they were so good at internet marketing that they started running Facebook ads on this thing, and it's the fastest company I've ever seen get to 50 million in ARR.
21:00
They got to 50 million in ARR in in in one year, which is to go from zero to 50 million in revenue in one year is just absurd.
21:07
And the way the reason they were able to do that is because their background as internet marketers as guys were like, as soon as I have anything that works, I will just plow the maximum amount of cash into Facebook ads as I can, and I will just keep optimizing the ads until I get this thing, you know, a dollar in equals a dollar 50 out or a dollar in equals two dollars out.
21:24
And that's why they were able to be so successful early on because they had a different skill set than most of the Silicon Valley people.
21:31
Most of the Silicon Valley don't ever run paid ads. Mhm.
21:33
That's just like a pretty crazy thing. Mhm.
21:36
I think like if we just go to the difference then, like the challenge for anyone of these companies that gets this wedge and like is rare to see zero to 50 in one year, that's pretty special, but even if you get like a product to hit in terms of initial adoption, then I think the like the the next 999 million of revenue has to be like I think more traditional moats.
21:56
Um, uh, because the problem is if it was I'm not saying the distribution piece was easy, but let's say you were just first with an idea, uh, and like you hit it on Reddit because it's a novel capability.
22:12
Uh, like I think then you need need to get to traditional like reasons companies get really big, product velocity, depth of product ability to serve the customer, social engagement, or something. Right.
22:22
So like if you think about companions, um, uh, it could be like what are the arguments for like why somebody gets to dominate that that business?
22:30
Um, there's a version of a companion business or any business with paid spend, and you know this really well, that is like just a treadmill, right?
22:41
Like I make money, but I have to keep putting money in.
22:42
It's the opposite of compounding.
22:44
Um, and if I like stop working hard or other people compete with me, like the treadmill gets steeper or I fall off.
22:52
And and I I think one simple answer is on companions, did you guys ever play The Sims growing up? Sure.
23:00
Like it's very hard for me to not imagine The Sims better if the characters are like smarter and like richer in interaction and have like what looks like realistic video and voice.
23:14
Um, and and so like technically, instead of it just being like I'm talking to a person, it could be, you know, that person has some combination of memory of me, other interactions, goals, and like the media experience of them is richer.
23:27
And we haven't gone there yet, but I think like there's a version of that company that's somewhere between like a companion and a game world that will be very big.
23:33
It's kind of an interesting exercise.
23:35
Well, if I could just get to a million, then I've increased my likelihood, and then maybe I can get that to 10, and then 100, and then a billion.
23:43
I actually firmly believe that if if something can scale to 10 million, there it may take a while, but if it can get to 10, almost always get to 100.
23:50
Like there's enough people in the world to to make that work.
23:54
But it's actually an interesting exercise to think of all the things that you need to do in order to make those jumps.
23:59
Now, getting it to a billion, I've actually that's been that's been hard for me to figure out how to do that.
24:04
But uh, that's a fun exercise to think, well, if I can just get to a million, I bet you I can get to 10, and if I get to 10, I know for a fact I can get to 100. Yeah.
24:12
By the way, this The Sims, lifetime sales $5 billion.
24:14
So, uh, without AI, The Sims was able to get to 5 billion in sales.
24:18
If if you made it more engaging by by AI powering all these characters, that's going to be even stickier.
24:25
It's going to be a big business, right?
24:27
Um, Hey Sarah, why dude, you're like pretty in the know. [ __ ] this fun thing.
24:34
Like why don't you just go do this?
24:34
This sounds pretty awesome. Go make one.
24:37
This sounds way more fun than investing in it.
24:40
Um, I get to I like really like doing the zero to one thing repeatedly, right?
24:46
And and so I think you just have to figure out what you're motivated by.
24:47
I uh, am really motivated by working with people that are entrepreneurs that I like and respect and I think are super special, and I do not like working with people that um, that I don't have as much enthusiasm about, right?
25:02
That's like a very specific personality trait, and like law of large numbers, as soon as you manage very large teams, not everybody is going to be at the same level.
25:11
Um, and so like doing investing, like in making being able to contribute to other people being successful that are really special, and then the competitive nature of be right with skin in the game and then know what is happening.
25:24
Like I like all of that, but I, you know, never say never.
25:29
I think we we incubate companies where like it's essentially like, uh, I see it, I see it, I see it, and then there's frustration that like the right, you know, a set of people you're really excited to back just hasn't come together around a certain idea.
25:41
Sean, you are more technical than me, but you're still not technical I would say, but you're more than me.
25:49
Uh, but classic compliment. Thank you very much.
25:52
You're not tech You're more technical than me, but you're not technical.
25:55
But you're also not technical.
25:55
You're almost good-looking.
26:00
You're hotter than me, but I'm a one, you're a three.
26:02
Uh, did you uh, when you're I know you've been like studying this stuff.
26:06
When you like this seems like a really fun weekend thing just to to play with.
26:09
Are these actually Would it be really hard for me to learn how to do this?
26:15
Would it be hard to build one of these?
26:17
Just like a really simple project cuz I I now she's Sarah's getting me all hyped on this [ __ ] I'm like this looks really fun to to mess around with.
26:21
Yeah, I mean I think it's like anything else.
26:23
You got to you'd have to have a partner who just speeds you up.
26:26
Like you learning to to code to be able to to do these things is would be the slow way of doing it versus the easy way is you find an engineer who's excited about this and doesn't have clarity of vision around it, maybe doesn't have a doesn't want to run the business side of things, and you say, great.
26:39
Hey, let's let's build X together.
26:41
I have a clear idea that X will work, and I'll handle the marketing side.
26:44
You got to make this product do do this.
26:45
And um, that's not so hard.
26:48
That's that's pretty easy. This is exciting.
26:50
Uh, you get to see a lot of cool [ __ ] Let's uh, let's do some of your like specific kind of thesis.
26:56
So you have this website, conviction. com. Good website by the way.
26:59
How did you get that domain?
27:01
I'm an internet person, yeah. Okay, all right. Did you see her website?
27:03
She has a website for her uh, I think it's the incubator where you got to like code in order to get access to it.
27:10
You don't really code, but like the menu is set up like that.
27:12
It's a little It's like yeah, it's a little CLI. What's What's that URL?
27:17
Um, I think it was called commit.
27:17
It was like a program for like hackathons, college students, etc. Yeah. It's commit. conviction. com, Sean.
27:25
It's a pretty cool website actually.
27:27
Oh, you open up it's a terminal. Yeah. Oh god. Uh, let me see. Let me try to do this.
27:31
So run No, uh, type type You got to type in help. Give me a job. html. You got to type in help.
27:40
So if you type in help, it like gives you the menu. Anyway, it's cool. is like a folder. I don't know.
27:43
I don't know how to do this. Um, all right.
27:44
So you have a website with a bunch of basically like request for startups or, you know, things that you think are going to going to be built in in uh, in AI.
27:53
So let's run through some of these cuz I that's actually why initially was like, we got to have her on the pod to to kind of um, to talk some of these out.
28:00
So let's do one that's you call your personal seller. Do you remember this?
28:04
You might have wrote this a while back while back, but your your personal seller.
28:07
It might have been one like my partner kind of ready is or something, but we can certainly talk about it. Yeah.
28:12
Okay, I'll I'll give you the summary.
28:13
So the summary is uh, your personal seller.
28:15
I think the idea here is that there's a bunch of places online that sell stuff, Etsy and eBay and Amazon.
28:21
There's a bunch of different places to sell things.
28:24
Um, but actually like doing that is a bunch of work, like creating the store, listings, changing prices, writing the copy, all of that.
28:31
And I think what you're saying is somebody should be able to just like have a product and then the AI should be able to like do the actual e-com management of this of the sell of of the of setting up the shop and running it. Is that what that means?
28:47
Yeah, I think like um, it's probably it it matches like a larger theme that I really think is exciting about AI, which is like because all of these skills, and it could be um, run a basic like social marketing campaign, right?
29:00
Or like send email to your customers that are likely to be repeat customers, or improve your website for indexing.
29:09
Like there are a bunch of things that um, are probably not related to Let's say it's a Let's say it's a Shopify drop shipping store for like a particular type of sock, and you love socks as an entrepreneur.
29:22
It's not like related to the merchandising decision or the design decision of like what is the sock I want to give the world. Right.
29:30
And like that's kind of the essence of like why like sometimes people become entrepreneurs.
29:34
And so can you can you take a bunch of these tasks that require skills in all these different domains and just automate them at least at a a level.
29:44
Like I think you can now, right?
29:46
And I think like that and there are the platforms um Shopify and and Square etc.
29:51
They're they like, you know, they now have native assistant products that help you use the platforms better, but I I think across the spectrum of how to be a good internet entrepreneur like in the e-commerce sense, I think there's more opportunity there.
30:08
Um How do companies do that now?
30:11
So let's just say you're a company with 10,000 SKUs.
30:13
Um how do you get accurate descriptions for all of them?
30:20
Well, usually if you have 10,000 SKUs, you have like it's a you have like you don't have 10,000 unique uh totally variant products have a color variants, size variants, things like that.
30:29
So like I'll give you I'll tell you in our case, right?
30:31
So I have an e-com store and we have we spend uh let's see, probably like five or six grand a month on just Shopify per plus or whatever like the pre the enterprise Shopify thing.
30:43
So that's just the Shopify cost.
30:44
On top of that, I would say we probably have another um three to five grand a month on Shopify apps.
30:51
So you need an app for search, you need an app for uh bundles, you need an app for this, that, you know, there's like a ton of things that Shopify doesn't provide.
30:58
So my all-in just software cost is at least 10 grand a month, probably a little bit more.
31:02
On top of the fees they take of every transaction.
31:05
Then I have an e-commerce store manager.
31:08
His job is just to like run the store.
31:10
Like the we have new products coming up, make sure those launches go well, move things around, oh this is broken, there's a bug, whatever.
31:16
We then have a merchandiser.
31:16
The merchandiser goes every day, looks at the collections and says, this thing is sold out, it shouldn't be at the top anymore, we don't have sizes for this or we don't have uh colors for this.
31:24
So let me move this other thing to the top.
31:26
Or hey, the season just ended, these need to be rearranged.
31:29
So there's a human being that does that.
31:31
There's also apps that do that, but you kind of need the app plus the software today cuz the app's not quite good enough to do it by itself.
31:38
We then have VAs that go in and they do all the product pages, the the descriptions, the templates, the tagging so that our inventory data is correct cuz we need to be able to analyze inventory.
31:47
To do that, you need to tag every product accurately.
31:48
So there is like four or five people that are just making sure the store runs in addition to five apps that make the store run.
31:57
That all today is shouldn't be the lead like future state of things.
32:01
That's just the current state of things.
32:04
And and Sean, I think the future state is for entrepreneurs who cannot recruit, manage, pay the five people it takes to run your store. Like what do they do?
32:12
As Sam said, like I think it will be easier in the future, right? Yeah.
32:18
I I think this is also kind of like similar as an idea to all of the another area that we are and I'm like personally really interested in is um the voice automation market.
32:29
I think like a lot of your listeners will have seen the GPT-4o demo where it's like a voice that may or may not sound like ScarJo talking like in real time.
32:40
Well, we played with uh 11 Labs. Mhm. No, but that's dubbing.
32:43
She's talking about just being able to like Alexa, you you just talk to it and um it just talks back and it'll sound like Scarlett Johansson.
32:50
Just like ChatGPT, but you don't have to type.
32:53
Yeah, but but both of these things either like it could be in your voice or like some spokesperson for a brand or a company, but like the ability to give reasoned, you know, knowledge-based responses in a human voice, I think it's just really powerful, right?
33:06
And I don't think people are thinking enough about the opportunities here. What you mentioned 11.
33:12
There's like exactly one independent voice API business in tens of millions of revenue and that's 11. They're great. That's amazing.
33:18
Um I think there are other opportunities.
33:20
So like there's a company called Cartesia that does like more real-time voice, for example.
33:25
You think 11 is by the way 11 Labs, you think they're at tens of millions of in revenue?
33:30
Uh they are they are definitely at, you know, a a large number that is in the tens of millions of revenue.
33:34
Hopefully I'm not surprising surprising the market with that.
33:38
But, you know, a lot of developers will immediately gravitate like toward API business, but that is not how the rest like the world is full of niches and people running businesses that don't think about APIs and won't use them, right?
33:48
And and so like just to just like, you know, your personal seller, um I think there are going to be a bunch of interesting voice services for everything from restaurants to HVAC companies to dental reception that are just like answer the phone.
34:03
I think that's one of the ideas we had.
34:04
And it could be informational like we are open from 8:00 a. m. to 6:00 p. m.
34:10
Um or a lead generation business where I'm like, well, like my plumbing broke and like are you available tomorrow at 3:00 p. m.?
34:19
I'm a huge believer in this, huge. Like In what, Sean? This this simple idea.
34:23
So you know like when the when the internet came out, it was like um oh, it's going to be so crazy, but like one of the obvious things was like, hey, every restaurant just kind of needs their menu online.
34:34
Like you should put your you should put that your restaurant exists, where it's located and then put your menu up there even as a PDF, it's still like value add for you.
34:40
It's like it became where every business needed a website.
34:45
And now what I think is going to have is that every business needs an agent.
34:46
And so what's the agent for most small businesses?
34:49
So like I call pest control cuz we always get a little bunch of like mice jumping in our pool for whatever reason.
34:55
And try calling pest control.
34:55
Nobody ever picks up the damn phone.
34:58
And because there's usually it's usually run by like it's like Mike's pest control and Mike's out in the field doing things all day. Controlling the pest.
35:05
Actually doing work and so he doesn't pick up the phone and so then you leave a message and you're like you and then but you called 10 of them because you're not sure if Mike's going to get back to you.
35:13
So then it becomes whoever gets back to you first.
35:15
Mike loses business because Mike doesn't pick up the phone.
35:18
Mike also is not going to hire somebody to just sit there and wait for the three phone calls a day that he's going to get.
35:23
It just wouldn't make sense.
35:23
But now you go and I built one of these in our like AI uh like weekly tutoring session that I have basically.
35:30
I was like, I want to build one of these.
35:31
So we have the same problem for our our offshore recruiting business.
35:34
So we own a offshore recruiting business called Somewhere.
35:37
And it's like you can find you can find amazing talent, they're just somewhere out in the world, you just have to find them.
35:41
So what Somewhere does, they find you elite talent.
35:43
Now the big problem, if you go to somewhere.
35:45
com, it's like you say, okay, I'm looking for a designer or I need somebody who could do who get me leads for my marketing business or my real estate business.
35:52
Or I need somebody to do data entry, right?
35:55
So you have all these jobs.
35:57
Now the button on the site is basically like, you want to start hiring? Fill out this form.
36:00
So you fill out the form and then it's like, awesome.
36:03
We will get back to you soon.
36:05
Or it's like schedule a call, here's the call tomorrow or two days from now.
36:09
And no matter how many sales agents we have a call tomorrow is not as good as talk to me right now about what I need cuz right now is when I'm interested.
36:17
Right now is when I'm on your website.
36:19
Right now is when I'm not thinking about other variations of how I might solve this problem and you have an opportunity to sell me.
36:26
And so Sam, I don't know if you've seen this, but like check out bland. ai.
36:27
This is this is the one the one I built on.
36:31
If the answer is, have you seen this, assume it's no and my mind is being blown by all this stuff.
36:34
But basically it lets you build a phone agent for yourself.
36:38
So I went on here and I built a phone agent.
36:39
So I built a guy who could answer the phone so that when somebody goes to Somewhere and they want to they want to hire somebody, it'll be like, awesome. What are you hiring for?
36:47
Have you ever hired overseas?
36:47
And you're like, yeah, I have. It's like, cool.
36:48
Um tell me what you're looking for in a couple, you know, a couple sentences.
36:52
Oh great, it sounds like what you're looking for is somebody who could be a developer for your Shopify store.
36:58
Our our noble budget for that is 2,000 a month.
37:00
Would that work for you or are you looking for something a little bit more or a little bit less?
37:03
And then it answers it it basically does the intake, the initial sales call for you and it's like, no problem.
37:08
We've hired this month for 85 other Shopify brands who are looking for Shopify developers. You're in good hands.
37:14
Uh we do this all the time.
37:17
We will I'm going to start looking for candidates now.
37:19
I'm going to email you tomorrow with three candidates. How does that sound?
37:21
And the person's like, great.
37:24
I guess I can just like wait for that to happen or it'll pull from our existing database and be like, here's an example resume.
37:29
This is the type of person we'd be looking for.
37:31
Would this person fit your needs? Yes or no.
37:32
your needs? Yes or no. So then the human salesperson will come into work and see a ticket that's like the AI agent did the initial sales call and found the customer's requirements and kind of already warmed sale up and told the customer what they needed to
37:47
know, the things you repeat every time on the phone, and now you could follow up with a more of it, but that's what I think websites even like ours, which is an internet business, should have, which means that every plumbing and pest control and restaurant, they're going to have their version of that. This is 100% way better than having a
38:07
This is 100% way better than having a call center or or it might or it will be when it as long so long as it works as good.
38:13
But this is absolutely the way to go.
38:15
All right, let's do some more.
38:15
So you have another one on here that's I think an easy one that's cool. Next gen auto complete.
38:21
And I think the idea here is you do a Chrome extension or a browser extension that not just like auto complete helps you fill in the next word it thinks you're going to say or how to spell a word, but what you have here is that it starts to learn your voice so it can write your it can help you write your emails or your blog posts in your voice, which is kind of like the next level up from auto complete, next level up from Grammarly.
38:43
It doesn't just kind of correct or spell check your stuff, but it actually writes the way you write because it has watched the way you write. Is that the thesis here? Yeah, yeah, absolutely.
38:52
And I think it can be, you know, lots of different types of business communication, but especially like email.
38:59
So I don't know if this is this is actually my friend Mike Vernal's idea.
39:03
I think he suffers from the same thing I do, that might be true for you, which is like I'm an incredibly picky writer.
39:09
And so I will use the models today for generation of basic content or I'll ask my amazing EA to like draft emails for me and then I will go rewrite the whole thing because I don't like the tone, cuz it doesn't sound like me or because it's not tight enough or because I want to use a certain phrase.
39:26
And I think the next level of like value and impact is definitely going to be um fine-tuning to specific voice.
39:32
And nobody wants to write like ChatGPT, like nobody wants to be the generic AI either.
39:39
So what everybody wants is the thing in between.
39:41
This shit's all wild to me.
39:43
Is there anyone right now doing that that you like?
39:45
Because I would like to use this today.
39:48
I mean Superhuman has like really interesting AI features, but I think though the unlock is going to be the personalization.
39:55
And what's your overarching investment thesis?
39:57
So you have this thing called software 3.
39:58
0, which by the way, most VC thing to do to be like oh, software 3. 0, web 3. 0. You you you've done it.
40:05
You you have gone full VC. What is software 3. 0? Yeah, okay.
40:10
So the seed for that phrase software 3.
40:13
0, it comes from actually an essay that Andrej Karpathy wrote years ago about software 2. 0.
40:18
And the base premise here is that like you had to write a lot of software by hand in a prior generation before machine learning. And then software 2.
40:31
0, Andrej, you know, worked at Tesla, was working on autopilot, was really about data set labeling, right?
40:37
You know, you are teaching a machine learning model by the data you choose to put into the pipeline um how to do new tasks. Software 3.
40:49
0 is the idea that the next generation of software, a lot of it is about manipulating foundation models.
40:55
And they're called foundation models because they have a lot of capability out of the box.
40:59
You don't need to train them from scratch.
41:02
You just need to give them like guidance, reinforcement, the information specific to your business.
41:09
And so an example would be like Shawn was talking about for his lead capture intake form voice bot.
41:13
Like he doesn't need to go train a model.
41:15
He doesn't need to go like collect data for that software application.
41:20
Like the voice agent is a software application.
41:21
He just needs to like make sure it's plugged into his scheduling system and his database of candidates and be able to retrieve the right information about the business and like you know, respond consistently to customers in a certain tone, right?
41:38
And so that's more about like manipulating a bunch of this base work that people like labs have already done for you.
41:48
And the premise here is like that last mile of getting a foundation model to be like something that serves all these use cases in the real world that you know, maybe the research labs think of as niches.
41:58
Like the world is composed of very large niches.
42:00
And it's why I think it's a I think it's really big opportunity for entrepreneurs and for us.
42:05
What are some of your like hot takes or maybe your contrarian takes?
42:08
Anything that you think that might be counter to what the most people say, most people do, most people are betting on?
42:15
Do you have anything that is against the grain?
42:20
You know, I'm going to get I'm going to give you like a somewhat arrogant answer, which is I don't spend a lot of time trying to figure out what the entire market thinks, actually.
42:25
So I'm like I don't know which of these things are contrarian.
42:28
I can tell you where like my opinion has changed dramatically.
42:32
Like let me give you one example.
42:33
For many years, including you know, the tenure of my investing at Greylock, I was one of several people who were like okay, we're going to go understand healthcare and digital health.
42:42
And I was like ah, healthcare sucks, right?
42:43
It's a quarter of the economy, it's really important.
42:45
How could you not want to work on this mission, but it is so slow and the incentives are so screwed up that like trying to enter that market with technology or the speed of entrepreneurship that you know, Silicon Valley entrepreneurs are seeking is like not a good idea.
43:00
And we just did a healthcare administration automation company.
43:06
So I'm like oops, like changed my mind, real hypocrite here.
43:10
And and like one of the reasons being I'm like well, if you think about the mind-numbing work that happens in healthcare administration, like billing, authorization, coding, claims processing, like all like even not even mind-numbing, but just like expensive and manual like patient support, it's actually really fertile for an AI company.
43:32
And you know, we backed something that's like growing really quickly in one of those domains, right?
43:34
And so I just say like I I guess I've changed my point of view on healthcare.
43:38
I went to the pediatrician yesterday.
43:41
My doctor is with my baby there and I'm sitting there and she's got her iPad on like a table and there's a video like there and I'm like who the [ __ ] is that guy?
43:55
And they're like oh, that's just like my scribe.
43:57
I he's just listening in and he's and he's taking notes.
43:59
But she was like I used to stay up until 3:00 a. m.
44:03
taking notes on all of my patients. They just do it for me.
44:05
And obviously the wheels are turning in my head.
44:07
I'm like yeah, that that job is going to be unnecessary in a few years.
44:11
But it was amazing to have a medical scribe.
44:12
I've never seen such a thing.
44:14
And she's like oh, this has been around for a long time.
44:17
I was like I've never seen that.
44:18
Yeah, I do think one framework for like your listeners like thinking about different ideas is like what parts of work have been outsourced services already, right?
44:29
Because like it used to be the doctor taking the notes.
44:31
And they were like wow, we pay this person a lot and like they should see more patients and think about their patients more.
44:38
Like let us outsource that to you, a cheaper tech in our office.
44:40
Let us like outsource that tech to India or the Philippines.
44:46
And now there are a number of scribe businesses in medicine that are growing really fast.
44:49
Like Abridge, Nabla, Freed. Like it is happening.
44:51
And so I think that will happen in a bunch of different areas where like basically if you can create separation of that work already to outsource it, then maybe you can outsource it to a machine as well.
45:04
Yeah, Sam Altman had a good thing.
45:04
He was like everybody worries about AI taking your job.
45:07
You have that's not the right way to think about it.
45:10
It's AI will take your tasks.
45:13
Like you have to think about it not at a job level, but at a task level.
45:15
There are certain tasks it can do really well.
45:18
There are certain tasks it can't do really well.
45:19
There are certain tasks today it can't do that in the future it can do.
45:22
And so eventually a job becomes a bundle of tasks.
45:27
But but it for now it's you can't think of the whole bundle because it can't replace the whole job, but it can replace specific tasks, which might be just the way it works in the long run is that there's a huge slew of tasks that can be that can be done by AI and then there's people that bundle those tasks together to make sure that they're getting done well or at the right time.
45:44
I think that's like approximately right, but to be intellectually honest, like that there was a scribe in that outsourced BPO that had that job.
45:50
And so it's not taking the doctor's job, but it's taking the piece of the job that like the doctor's job that already got separated out, the task that they did they didn't like, but that became a job of its own.
46:02
Yeah, the task became a job and the job goes back to being a task basically in this case. Yes, yeah, yeah. It's a good framework.
46:08
Sarah, are you are you investing exclusively in AI-related businesses?
46:10
I am a technology investor.
46:13
I'm not a machine learning researcher.
46:15
I've been working on this stuff for a handful of years and I really believe it.
46:18
I think it's like the most important thing to happen in technology in a long time.
46:21
But I'd say like I'm also here just you know, invest in great tech companies.
46:27
And so You're also here to get paid.
46:27
I am also here to work on things that will work that are important, right?
46:33
And so like if a if an entrepreneur that I think super highly of or like that I've worked with before or whatever comes to me and says like I have a great idea, nothing to do with AI, I'm still definitely going to be really interested in that.
46:45
If you ask me like what are the ideas that we think about or are hunting, it is all in AI.
46:48
I do want to put one more thing out there, which is definitely not a idea that just anyone can go after.
46:58
It's kind of the opposite of the like easy wedge idea in terms of how can I put distribution around like one functionality for a niche on a on a model like a AI headshot application or something.
47:12
But I do really want to hear from anyone who has a point of view on what happens to the like Nvidia compute monopoly and overall what's changing in the data center.
47:19
I don't know if this is a hot take to your former question, but like I think a lot of people intellect in technology really they intellectually like are like oh yes, of course, workloads are changing from not AI to AI, but they don't actually think about like what that means in terms of scale and market cap.
47:37
Like that means like chips, memory bandwidth, networking, energy, storage, optimized system design, like that was a lot of technology company market cap before.
47:49
And so like if that's true, there's going to be a bunch of different like new specialized solutions and it's trillions of dollars of value at stake.
47:56
And it's not just like single direct attack on Nvidia that is like the opportunity.
48:01
What what else would be in that category?
48:03
If it's not just like hey, our chip is better than Nvidia's chip.
48:05
What what else is what is the what's another shape of a company that could be in that that space?
48:08
So I I guess the example would be like well, what are other bottlenecks like memory bandwidth?
48:16
Well, like what if you design storage to be specific for AI data centers?
48:20
What if you like you could do cooling systems for like there are if you just reimagine the entire data center around like big AI inference, Right.
48:29
I think you end up with like totally different needs.
48:32
The The New York Times had this article the other day.
48:35
I don't remember the stat entirely, but it was something like the amount of AI capacity or in chips like currently created right now, we need to create like another like four trillion dollars in market cap in order to satisfy like the amount of capacity that we have.
48:52
And they were sort of writing it in a in a way of like I don't know if we're going to be able to do that.
48:58
But then when you think about it the other way around where you where you think about well, in 1998, if you said like you know, what how big is the internet going to be?
49:06
I'm sure it went far beyond virtually 100% of the experts' opinion as to how big it will get.
49:11
And I remember reading this article the other day and I was like that's just absolutely astounding that we're in one of these moments.
49:18
Sequoia came out with a a sort of blog post or I don't know, PDF or something like that about this.
49:21
The thing they called it the $600 billion hole or something.
49:25
It was basically saying well, we've we've invested this much or we're investing this much in capex.
49:30
So if you invest that much in capex, what do you need to get out to make that you know, return?
49:35
And that's a VC saying that, which is which is not just like some journalist who doesn't get it, who doesn't get tech.
49:40
So, what was your reaction to that and what's your take on that?
49:42
I think it is a lot of capex.
49:44
I think if you put it in context of like how does it compare to other big capex spends in the past?
49:55
Let's say like the broadband build out.
49:58
Like well, we wanted the internet.
50:00
You know, like we spent about $2 trillion on broadband to date.
50:05
Like we're not there yet, right? That was worth it.
50:06
And so what I would say is yes, like it's a totally valid question.
50:11
We're spending a lot of money.
50:11
What are we going to get out of it?
50:12
I think we're going to get a lot of value.
50:14
We had Dharmesh on the Dharmesh founded HubSpot. Dharmesh is amazing.
50:18
Yeah, he's really wise and he's tends to be right more than he's wrong.
50:21
And I think he said something great when I asked him.
50:24
I'm like, man, I'm I'm a little nervous about a lot of the stuff where the world is going to go.
50:28
And he's like, well, I'm I'm fairly educated and I think that it's not going to be as good or bad as you think it's going to be.
50:34
Do you agree with that sentiment?
50:37
No, I think I think it's actually pretty bimodal.
50:39
I think it'd be like bad or and it's like it could be much much better. Great. It's It's the opposite.
50:43
It's either going to be much worse or much better. It's kind of your take.
50:49
What's the bad like what's the bad situation look like where like like for example, I think the bad situation and I'm fairly uneducated.
50:56
So take it with a grain of salt.
50:57
The very bad situation is that there's just going to be this massive gap between the haves and the have nots and like if you have money now, that's going to grow and you're going to be awesome.
51:06
situation is AI kills us all, right?
51:07
That's the the doom situation.
51:07
That that's a bad situation.
51:09
But then I but in route to that, there is just this massive separation of the haves and have not have nots.
51:15
Do you know what I'm saying?
51:17
That kind of freaks me out.
51:18
What's your what's your where do you see the bad situation going going towards?
51:23
So I think it is not necessarily that correlated that your your resources or your capital today mean that you most take advantage of the of the AI revolution, right?
51:36
I actually think people have a lot of agency in this.
51:37
I think they go start these businesses, make a million dollars.
51:42
That's such a small group of people. Why does it have to be? Because of human nature.
51:46
How many people know about this [ __ ] You go do you Well, your parents are tech entrepreneurs, but ask Sean's mom and dad. I'd go ask my parents.
51:52
Go ask my brother and sister.
51:54
Like, you know what I mean? entrepreneurial.
51:56
Even if this widens the number of people who can be successfully entrepreneurial, it's not going to like it's going to go from 0.
52:01
1% or whatever 1% of the population to I don't know, not 50, right?
52:06
Not It's not going to go that far.
52:07
Yeah, I don't know if it has to express in pure entrepreneurialism versus like you will get increased productivity for people in lots of different types of jobs.
52:18
And it's not obvious to me that's like just the people who are already most highly paid today.
52:25
You're somebody who thinks a lot about AI.
52:26
You spend your time in the AI ecosystem.
52:31
A lot of very smart people are actually worried about the doom scenario.
52:34
Every you know, from Elon Musk to we had Emmett Shear on the podcast and Emmett's a smart thoughtful guy and he's like, you know, the P doom, the probability of of actual doom here is is pretty scary.
52:44
It's not zero and and here's here, you know, here's where I think it is.
52:49
What do you think about that?
52:49
What are the odds that AI truly is a sort of like a critically dangerous thing?
52:55
You know, I don't actually spend a lot of time thinking about this problem because the because it is like conjecture in the future of both the objectives of these models and capabilities of these models that are kind of like hand-wavy. Right?
53:07
Like if like I think when you talk to experts about some of the suggested scenarios, like here are two classic ones.
53:15
Oh, you know, people are going to use this to design a virus that kills us all, bio weapons.
53:22
Or somebody is going to make the objective for a foundation model that is super powerful to be like make the most money or generate the most paper clips and it's going to take over all of the resources in the world and kill us all.
53:38
There's no linear path from here to there.
53:41
And so when when people ask me about like the doom scenario, like I am much more concerned about abuses we actually do understand.
53:49
So for example, like what if people don't understand what information is true or not or like people are going to use this stuff for hacking and fraud and lots of like bad activities today.
54:00
And like we should go understand that and react as quickly as possible to that.
54:06
And as a country, like probably want to stay ahead on these capabilities technically.
54:11
Well, have you heard any What are some what's a wild example of how people use this for hacking or for fraud?
54:17
Oh, I mean Like for for my company, we get emails from me. It's not really me.
54:23
And sometimes it will have or like it'll have a link to something that sounds like it's in my voice.
54:27
Yeah, I think that's the simplest example, which is well, like what happens if you can create really authentic sounding media.
54:36
Like, you know, are you are your parents like, you know, going to not pick up the phone if it's a spoofed phone number and it sounds like you and you say you need something.
54:46
Like that's a bad scenario.
54:48
And so I think we need more tools to protect against that.
54:53
And general education about it.
54:53
So I I worry more about that.
54:55
And then I'd say like I think of the probability of a bad scenario.
55:01
I said it was like it is possible.
55:03
I can't see exactly how we get there.
55:06
And if you ask me like what are the reasons in which broad use of cheap intelligence are going to be great, I can give you so many reasons, right?
55:15
So Andrej Karpathy just started a company around education.
55:20
And like the the the fields that have been super resistant to cost improvement, basically health care, the government and education, like I I think this will actually move the needle on some of the domains that matter a lot to all of us humans.
55:37
And I I think like when when people talk about like the doom scenario, it's really fun and scary to talk about the dystopian doom scenario.
55:46
But I think the opportunity cost of not exploring the ways in which like you know, you can have an economy of abundance.
55:55
We need to talk about that and that is really what I focus on.
55:56
Sam, do you know who Andrej Karpathy is? No, but I love his name. It's a lovely name.
56:03
Andrej is a is a amazingly well-respected research scientist and educator who's trying to create like an experience that is AI-powered in education where like the most amazing expert in a domain is like a personal tutor taking you through the material interactively.
56:20
And he's one of like the five big thought leader type guy.
56:24
He ran Tesla's AI program.
56:28
In terms of self-driving cars, he was like one of the let's say five most known and respected guys about that. He then went to OpenAI. He then quit OpenAI.
56:37
It says he's listed as a co-founder of OpenAI.
56:39
So So I guess he's the man.
56:41
he was like the early early mind behind it.
56:43
And at Tesla, he was basically the the guy leading their entire self-driving unit.
56:49
I think he's I forgot what his title was, but he's like, you know, chief AI guy.
56:52
When I lived in San Francisco, it was a fun period.
56:54
I lived there from 2012 to basically 2000 20 or 2022.
56:56
And back then it was like the Airbnbs of the world and Tesla or um Uber and we had Sidecar back then where it was like holy crap, we're going to get into a stranger's car. And this is so exciting. This is so new.
57:12
And and you'd go to hackathons and people were working on like meal delivery services.
57:16
And that was like really cool.
57:18
I went recently this was about a year ago and I was walking around the Ferry Building.
57:25
And this kid recognized me.
57:25
He's like, oh Sam, I you know, I like the pod. I go, what's up, man?
57:29
And he said, I'm doing a hackathon right now in the Ferry Building upstairs.
57:33
Do you and your wife want to come up and like see what's going on?
57:36
And I was like, hell yeah, let's do it.
57:37
And so we go up there and it was so invigorating.
57:40
I was like, dude, we used to do these exact same thing, but it was around like the sharing economy and and all this type of stuff.
57:46
And they were I was just talking to people what they were building.
57:48
And I remember thinking like this is like totally I guess it it happens in San Francisco a bunch.
57:54
I was like, this is like the Renaissance.
57:55
Like there's something really really cool going on and everyone was doing AI stuff.
57:58
And I just thought it's magical.
58:00
Right when I moved there, it was like mobile was the thing.
58:03
It was like, oh, X for mobile.
58:06
Everything we got to make we got to make it work on a iPhone and an Android.
58:08
And then you would see like, you know, some like false flags. Like Frontback came out.
58:15
It's like, oh [ __ ] this is the next thing.
58:16
This is the next big social app and then it would kind of die.
58:18
But then, you know, Instagram, Snapchat, you know, they they actually they stuck.
58:22
And I remember early days of Musical.
58:24
ly that now become TikTok.
58:26
And so mobile was like the big thing at the time.
58:28
Then it became crypto and it became the crypto hub.
58:31
But it started to lose a little bit of the steam for crypto because crypto was a lot more international.
58:38
But now it looks like for AI, San Francisco at least is back as the the hub.
58:41
Sarah, are you in in San Francisco?
58:43
Yeah, we're in the mission in San Francisco and like I I think we really believe in the sort of like community aspect of not in the like maybe in the squishy sense of the word, too.
58:54
But like if you're thinking about looking for ideas for companies and being inspired to like be committed to the grind and have the right ideas, then the right thing to do is not do it like alone in your basement.
59:05
What you have in San Francisco are people who are optimistic and then like work-oriented.
59:10
They believe lots of things are possible.
59:12
They're learning about what's going on at the frontier.
59:15
And we actually do this grant program in bed, in bed. conviction.
59:16
com to create that kind of community and a bunch of other stuff.
59:20
But it is it is around this idea that you people want to have the experience that you described, Sam, which is like, well, like not all of this is going to work, but what are smart people trying that is some version of the future in this area of AI and like that will probably educate and inspire me and some of it will be really big.
59:38
Yeah, I think that like if you're 22 um and you're young and single and you're into this [ __ ] I would just say two words. I would say go west. Go west, young man.
59:50
Like By the way, people get I always talk about San Francisco, it's dangerous, it's dirty, it's lawless. That's the appeal, baby.
59:57
You can say you you made it in the war-torn city of San Francisco.
1:00:01
You don't want to be a billionaire who is coddled.
1:00:02
You want to be a billionaire who grew up on the mean streets of San Francisco. They're not that mean.
1:00:13
All right, I think we have to wrap up with Sarah. Thanks for coming on.
1:00:14
Where should people find you and where where where should they follow you?
1:00:17
You can just Google Sarah Guo or conviction. com.
1:00:22
And I'm on I'm on Twitter. Um all right. That's it. That's the pod. Thanks, guys.