Josh Wolfe on Where Investors Will Make Money in AI

26:19or product risk or customer risk, whatever it is, kill that risk. A later investor coming after us should pay a higher price and demand a lower quantum of return because they're taking less risk. And I should get rewarded for taking the early risk. So I sort of think about it as destroying risk to create value. Why do I say that? Because if we take an early stage risk in a company to prove that the tech works, I want those corporate VCs coming in. I want them coming in. I want them paying a higher price than we did, providing a lower cost of equity than we did, and helping to both validate and create some competition.

26:53So I'll give you an example. Runway ML, a bunch of interesting scientists. One of them was an intern back in the day at Hugging Face, became a co-founder of this company, Runway. Runway basically said, we can take the cutting edge models that we're developing. They actually were the developer of stable diffusion. And we're going to make videos. We're going to start with two second videos. You talk to the CEO there, Chris, he will say within the next two years, you will have a full feature movie that is entirely generated by people sitting at a computer and just prompting angles, lighting, actors, expressions.

27:29I mean, it's like a little bit hard to fathom. It's like looking at YouTube when it was 240 pixels versus like 8K today, but it's going to happen. And And it's interesting. A totally full-featured Hollywood film, everything perfect except the hands. Exactly. Although I think they'll get the hands right. And there'll even be some, you know, unique special effects. But the sound, the lighting, the angles, everything, I think we're two years from something that actually you'd be like, oh, my God, that was made by AI. And it'll probably be, you know, a shorter film. But it's coming. Okay. Why do I say that?

28:05You just had$140 million financing announced a week or two ago, Google, NVIDIA, and Salesforce. And those are three great companies. One is on the data side. One is on the sort of strategic side. One is on the hardware side that wants them to use their compute. All of those guys are now linked with this company. And so Google's competitors are looking at this. And Salesforce doesn't want to be left behind. And NVIDIA is looking. And AMD is looking. And so the more corporate strategic folks that you get in, the more competitive juices start to flow. And it increases the chance for the founders and for us that not only do you get good strategic partners, but you set up competitive dynamic for future exits.

28:44And so that's typically, you know, great companies get bought and they get bought because there's competitive fervor from a corp dev person at one of the big companies that says, we can't let our competitors get this. Okay, so that goes to the second thing, which is against this regulatory backdrop, you know, who's going to allow these big companies to actually buy these small companies. And I'm hopeful. Okay, this is wishful thinking. This is more prescriptive than observant. I think that the regime today is very focused post-2016 and the election and the chaos and social media and all the abuses, particularly that you saw at Facebook with users and fake information and misinformation.

29:22I think that we are turning our turrets of attention from Congress on the wrong targets. I think that focusing on the domestic industry and trying to slow it down and prevent acquisition and prevent failures and prevent these companies from buying and competing is exactly what some of our peer adversaries overseas would love. China, and particularly the CCP, would love nothing more than for AI in the U.S. to slow down and for all of these iterations and experiments to have problems and for there to be a disincentive for VCs to want to fund these things because they'll never get out. And I actually think that you'll see some sea change coming in the next few quarters, year or two, where people say, OK, wait a second.

30:04You know, it isn't that we've met the enemy and he is us. We actually have to have domestic competitiveness. And one of the great assets that the country has is competitive, great technology companies. And we need to let them thrive so that we can compete, particularly with China's CCP. Just going back to what you said about a fully AI-generated movie. When I hear something like that, it sounds incredibly exciting. It also sounds very sci-fi and difficult to wrap my head around in various ways. But it kind of leads into a very basic question, which is, what is it like to invest in AI right now?

30:43So how are you actually doing your due diligence? You know, if someone comes to you with an opportunity for investing in a new technology, is it like all of us sat here in the office playing around with chat GPT? Is that basically the thrust of due diligence on this technology or something else? And then secondly, how competitive is it right now from a venture capital perspective to get in on some of these investments? Because I imagine, given the level of excitement, there is a lot of money crowding into this space. So the latter I'll answer first, which is it's very competitive. I mean, anybody that can write a check is a competitor.

31:27Now, if you are a founder, you know, just like if you are a star high school athlete or a star high school scholar, you want to go to the places that reflect the quality of your craft. And so you might want to go to Yale or Princeton or Stanford, or you might want to go to Vanderbilt or Duke and, you know, and play or Michigan and play ball. And so I think it's the same thing where great founders want to work with great firms and Lux and Sequoia and Andreessen and a handful of others, you know, have brands that confer to a founder that we are highly selective, that we have a great network that we can be value add, but anybody can fund any of these companies.

32:05There's always somebody that's got a roommate who's got a mother or father that gave him some money and they became early investors in this company and they made a ton. And so our view is that we are competing on one hand with everybody. Now, the second thing is that I always say there's this five-year psychological bias, which is that you want to be invested today where, you know, we were five years ago. And so I'm trying to figure out what's the next thing three, four, five years ahead that people don't yet appreciate. So, you know, I mentioned biology. Now, all the listeners can go out and try to find the next models in biology.

32:38But it's a harder, more complex thing. And I'm confident that there's a fewer number of investors that actually understand or have the networks or the connections. So we have some slight competitive advantage there. When we're evaluating these things, you're looking at the credibility of the founders. Many of them happen to be academic published papers. So you can see, for example, the people behind Runway who published the papers that led to stable diffusion, or the team that came out of Google that published the paper on transformers, not the robots, of course, like Optimus Prime, but the underlying algorithms that led to ChatGPT.

33:14Every one of the people on those papers have basically gone on to start companies and raise money. People that were at OpenAI have the pedigree, they learned what works, they went and started Anthropic. And so there's this sort of like, just like if you go back in finance to like the Drexel days where they spawned, you know, Apollo and Carlisle and Jeffries and all these, it's the same sort of thing. There's a diaspora that's coming out of a small group of people and you can reference the credibility. And then, and then yes, you sit with them and you look at what their demos are. And we like to say that we believe before others understand.

33:48And so when we had that runway team in, or we had the hugging face team in, you know, it was very raw and very crude. And you have to sort of squint and see the future that they're seeing. And then we don't fully fund companies. You give a little bit of money and you say, how much money will accomplish what in what period of time and who will care? Are we going to get paid for the risk that we're taking in funding you? But I would say right now, if you're funding anything that is application focused, anything that is to your earlier point in the wrappers around the user interface, most of those things are just features.

34:21They're not companies. Most of those are going to be competed away by a hundred other examples. A great example of that is, and I can't even remember the name of it now, but there was something that went out and it was an app and you could pay 20 bucks and it would give you a hundred versions of yourself, you know, as a comic book hero and a cowboy and a black and white and noir. I think Tracy and I paid for that. I think we did. I think we signed up for the one month version of that. I don't know. I probably forgot to cancel. And it's spiked and then it's done. And you're going to have tons of those things where it spikes and it's done.

34:53And it ends up being a feature integrated into, going back to the earliest point you made, many of the big tech companies, the Adobe's and the Microsoft's. It's going to be in all of their suites. I have one contrarian take here, which is a bit odd. As an investor, as part of a partnership who's funding the deep tech roots of the semiconductors and the infrastructure and the networks and the models and the algorithms. And despite doing all of that, I actually have a view that what we are doing right now, humans talking, even though it's through digital communications in an analog way, that that is actually going to become the scarce thing.

35:28You are going to be flooded. I mean, utterly inundated by emails, texts, tweets that are not written by humans. And that's not like two years away. That's like two weeks. The increasing percentage of the communications that you receive, even by the way, from people that you know and love and trust are not going to be written by them. They're not going to be spoken by them. You know, voice is going to be the next domain where it's going to be very hard. You're going to be getting a voicemail and the voicemail was not actually spoken by your spouse or your cousin or kid. I can already, I've already trained a model on my child and I was able to trick my wife on it.

36:06It was, you know, funny and scary. The point of this is, if that happens and as that happens, you will start to grow increasingly distrustful of many of the communications you get. It'll be, you know, this form of chat fishing is what I call it. And you'll start to just pine for in-person communications. And there will be private clubs that form where people come and no devices. And you just know that you're talking to a human because increasingly that will be scarce. So the great irony here is the flood of money and talent and productivity in AI and deep technology is probably going to bring us closer to our innate humanity.

36:43It sounds like the answer is Tracy and I need to do a lot more odd lots, pub quizzes and other live events. I'm, uh, that sounds good to me. Can I ask a question though, about if it's like, if all you have to do is sort of be a graduate from one of the right universities and have your name on some paper that's on like the archive website, what does that mean for, um, recruitment from the companies that you are investing in? And when they want to go out and hire someone, how is the challenge like, no, that person who they probably want to hire can also raise$100 million? And how difficult is it to recruit if there's just like so much money going to, you know, a potentially smart founder?

37:26You know, this has been the plague, if you're an investor, for arguably the past decade in tech broadly. And it's a weird phenomenon. And what But I mean by that plague is everybody thought that they could raise money and they could. They all had a friend or a colleague or a former associate or roommate who raised money and they literally had this reaction. He or she just raised that money at that valuation. What an idiot. I can go and do that. And so that set a comparable for them to say, I'm going to go do it. And you get this sort of collective craze. And so talent gets diffuse and disperse.

38:00It's increasing the cost of hiring employees. Valuations are going up. Money is being misallocated, like the whole thing. All of that crashed about a year and a half ago once rates started rising and the SPAC boom ended and all that, except for this one domain of AI. And so if you actually look at the hiring data, and you have to parse this to see whether it's signals that they're posting jobs or they're actually hiring, but all of the layoffs that you saw, the tens of thousands at Meta and Google and Microsoft, et cetera, you're starting to see this spike back up in some of the data. And what are they doing?

38:34They're hiring, whether it's low-level jobs for data entry and processing and cleaning, or whether it's cutting-edge algorithmic design for AI. There was an existential panic at Google. And it's been reported when OpenAI came out. You know, the all-hands deck meetings that people had of, my God, we got to throw a ton of talent and money at this so that we don't get left behind. So right now, it's a bit of an utter craze. You got to be really careful. Most of the incumbents are the winners. And there's going to be some small companies that end up with these really interesting novel approaches that are not raising a ton of money, almost out of necessity.

39:09They're doing these cheap, very focused models. And arguably, and here's another interesting thing, training on distributed computing. Instead of having these big centralized clusters of compute, we, for example, backed a company called Together Compute. And his basic hypothesis was, can I train very sophisticated models on all of the excess compute from the crypto craze or from idle computers? And can I do it for a fraction of the cost of what OpenAI did? And the answer was yes. And so you're going to see lots of these small companies that come. And I always say, like, whenever the DOJ comes in and starts looking at monopoly concerns from the big companies, it's never the DOJ that disrupts the big company.

39:53that people are concerned with. It's always some small competitor. It happened with Microsoft in the late 90s. Google came along. It wasn't the DOJ. It was Google. You know, it happened with Facebook and Google. It's happened with OpenAI and now Facebook. And it'll happen again. And it'll be four guys or girls in a room in Croatia or Singapore or Mexico City or Silicon Valley that come up with a crazy new thing that disrupts the big incumbent.

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42:02Taxes and fees extra. See mintmobile.com. What impact do you see of AI on how the sort of tech industry slash VC is organized or operating at the moment? Do you see people start to respond to the idea that, well, maybe a lot of coding is going to be done by AI in the future? Are people sort of like reorganizing themselves or reorienting themselves ahead of some of this technology? Definitely. When you look at the co-pilot, which is both from people like GitHub and OpenAI and others, it's basically how can we either help you code or how can we completely, if you look at Code Interpreter, completely write the code for you?

42:44You just describe in general lay language what you want to do, and it will, in Python, create the code. So pretty much every company will have a form of computer programmers in the software that they use, whether it's open source or proprietary, that is constantly developing and iterating their own applications. And it'll touch everything from customer service to radiology and x-ray image analysis to Bloomberg queries. and people will be able to basically have superpowers. What it means is you'll have the elite coders that are sort of always on the edge trying to figure out the next thing. And then you'll have the average coders that are basically really leveled up and almost indistinguishable from the prior elite coders.

43:30So I do think that what once was really scarce and really valuable, which was top-notch, what people call 10X coders, is now going to become increasingly commodity. and people will start looking, for example, now, the real value is not, can you code? For the current moment, it's like, are you an amazing prompt engineer? Like I can't draw, I can't code, I can't write, you know, 12 line stanzas, but I can prompt pretty well. And so it shifts the capability to the creativity of somebody that really wants to describe and control the machine. Again, almost more like casting a spell than the person that actually has the discrete technical capability.

44:14Can I ask, you know, you mentioned that roughly, I don't know, a year and a half or so ago, or maybe two years ago, this sort of the model that had been working, like this incredible trade, this incredible line go up decade or whatever for tech and VC like did sort of crumble to some extent. And we saw the big plunge of the NASDAQ. And I'm sure there were like tons of funds raised in 2021 and 2020 that are like deep underwater and all that stuff. And everyone knows that. When you're at the table now looking at companies, do you still, is there still pain and paranoia and fear from that? Have there been like, or has the pain of that been internalized in the way, or is it, you know what, we're just back in it.

44:57Game's back on, FOMO cycle back on, let's go. Like how much are there scars from the sort of crash of 2021? I think people that put a lot of money to work in 2020, 2021 feel a lot of pain. They invested at record high multiples. They made the presumption, which was a fair presumption to make, that if you fund something, there's going to be later stage capital or a robust public market to follow you on. All of that is gone. You know, so I think we went from what I call, what everybody called FOMO, fear of missing out, to what I call SOBS, which was the shame of being suckered. and that wasn't just that that wasn't just can i just say you know what can i just say there's no shame and you know people buy that it's hard to know at the top is but i think about like the person who paid half a million dollars or millions of dollars like for the board ape nfts that's the ultimate sob you can never live that down okay keep going sorry i just thought about that recently and that was in my head okay keep going but you know i got a friend zach bisonette who wrote the book back in the day on.

45:59We've had one. Yeah, Zach's amazing. Yeah, I like Zach. So, but this is one of the things that I love to say, which is not some crazy personal insight. It's just an observable truth, which is that technologies change and businesses change and rules change and policies change. Human nature is a constant. Greed and fear is a constant. That is what made Buffett and Munger brilliant. You know, it's what Howard Marks chronicles all the time. It's what you guys cover, the excesses of human emotion. And so a lot of this is actually capturing, I love finding like, where are people not paying attention?

46:29Where is attention scarce? Because where attention is scarce, valuations are going to be low. And we always say, oh, you know, just like everybody says, they're contrarian investors. We want people to agree with us just later. And that's the key. Okay, going back to your question, you know, we went from FOMO, fear of missing out, to SOBS, the shame of being suckered. And there was an important reason for that, which was the disappearance of two major players. at least symbolically. And that was SoftBank and Tiger. And why was that important? Because, you know, you had a venture firm maybe a decade ago that said, the price you pay for a company doesn't really matter because there's only 10 companies that matter amongst all the ones that are funded.

47:10And if you would have funded LinkedIn or Facebook at 5 billion or 10 billion or 20, it wouldn't have mattered, right? And so that sort of set a precedent that I think was a bit insidious and dangerous to say the price doesn't matter. You just have to be in the right companies. Of course, that's only obvious in hindsight. So you had lots of people that lost valuation discipline. It skewed control and leverage to the founders over from the investors, you know, and you saw weak governance and you saw fraud and excess and all that kind of stuff. And it's starting to wash out, you know, if not fully.

47:44But the disappearance of those two players, symbolically, they were the top-ticking marginal price-setting investors. SoftBank was paying insane prices. And of course, you know, they were all kind of shenanigans of them marking up their own book and pricing up again and all that kind of stuff. And Tiger sort of took a passive indexation approach, which was something that was widespread in the public markets, but they did it in the private markets. And they said, we're just going to be in all the companies. And the winners will make up for the losers and it'll work. When those kinds of players disappear, now all of a sudden you have a more rational, scrutinizing market of people who are afraid of paying excess prices, feel like they need to get a better deal.

48:22You're seeing down rounds in companies. You have a morale spin and decline where employees now have underwater stock and need to be refreshed. And here's where things get really interesting. We went from this domain where I called it the megas and the minnows. The megas were the giant funds that were, you know, 10 billion plus, and they were writing these giant checks. And the minnows were the thousands of small sub hundred million dollar funds that were just doing all the seed investing. Both of those guys have been squeezed out. And so now you have a smaller base of capital. You can see it in the data.

48:55LPs have pulled back. The champagne has stopped flowing down the pyramid of glasses. GPs are struggling to raise capital. We closed a billion two fund in 10 weeks, which for us was amazing and is a signal of great support of our LPs and great founders. A lot of funds out there right now are downsizing. It's taking them a lot longer to raise. And all of that is a rational reaction to a retraction. So I don't think you see the same FOMO. I think you see a lot more fear. People don't want to pay higher prices. The only area where there's an exception is inside of AI. You know, I just have one more question.

49:36And you sort of touched on this earlier where we were, well, you were talking about parallels between now and the sort of dot-com era and the idea that, well, you know, maybe eventually some big winners will emerge from this new technology, whether it's AI or the internet as it was in, you know, the late 1990s, early 2000s. What's the case for investing in AI right now rather than waiting a little bit to see where the dust settles, maybe wait to see who those big winners are, or maybe at the very least, get a little bit more clarity on how this whole thing is going to be structured or organized?

50:19Well, the argument for waiting is by the time you know, it's already fully factored into a price. The contrary to that is you pay a high price for cheery consensus, as Buffett historically said. And so if everybody agrees that NVIDIA is the winner, you know, that to me gives me pause for concern. You know, Jensen is running high. He's got the iconic leather black jacket. He's becoming the sort of, you know, next prophet of tech. Those are all signals that are like, okay, just like the classic, you know, Sports Illustrated curse, simple reversion to the mean, like what happens? Where's the vulnerability there to me is the question.

50:52And I gave you guys and listeners a clue, which is that CUDA, their language system is vulnerable to these other ones of PyTorch from open source originated from Meta and Triton from OpenAI. And that means that AMD could actually come from behind and start to take share. It's something that people are skeptical about. So I would say that if you're thinking about investing now, it's too late. It really is. You know, again, five-year psychological bias. You want to be invested five years ago where everybody wants to be today and vice versa. So I'd be thinking about what are the improbable things that are likely to happen in the next wave.

51:31I'll give you one company that I think is interesting that Lux is not invested in. It's a public company and we do private, but Cloudflare. You know, if you go back to the internet early days, one of the winners in the infrastructure was Akamai, the people that were sort of caching. And they were helping to shape the structure of the internet. Cloudflare is very interesting because they have a lot of compute infrastructure at the edge of the network. And you hear about this in sort of a hype-y way sometimes, the edge, edge inference, edge compute. It's a real thing. Very simply, you're talking on a mobile device or you're on your computer.

52:06Right now, you have to go up to the cloud and the cloud, which is basically a bunch of servers somewhere with high bandwidth interconnectivity processes. Then you have another domain, which is on device. So you do something, the models get smaller, the chips get better. On your Apple device or your Android or your iPad, you're able to run the AI model there. Cloudflare is caching a lot of these models and hosting them very close to the users. And they're doing it in thousands or tens of thousands of places all over the world. So I think that they, you know, probably a$20 billion market cap company, billion revenue, 50, 60 % growth.

52:43I think that they might be poised and aren't one of the names that are on the tips of people's tongues that are benefiting. But we see them in all the infrastructure behind a lot of our companies. Interesting. A little investment tip for people listening. Yeah, it's just, you know, do your work, investigate it, but it's something that is just not on the front page. And I think that they're poised in the same way that if I go back 10 years when I'm in that room in our startup and I got the benefit of this legal inside information of seeing these guys from NVIDIA making these chips that were the soul of the new machine, you know, in the proverbial Tracy Kitter sense.

53:17I just see that this infrastructure from folks like Cloudflare is probably going to win. So I just have one more question as well. And it actually also is sort of on the public market side. But, you know, going back to a company like Alphabet, and I sort of talked about this in my introduction. And, you know, obviously, they've made a lot of AI investments. And, you know, they've been doing research for a long time. Nonetheless, though, like the core business for now and for probably at least the medium term is going to be what we call, you know, Google.com or something like that and enter a search and get served a really compelling ad because it's very good at that.

53:55Like, in your view, how confident should people be that some of these big companies can find, you know, can actually produce revenue and income? I mean, like inference is a lot costlier, I presume, than a typical search query. We don't know what the advertising is going to look around it, et cetera. We don't really know. Like, do you think it's obvious that these big companies are going to find ways to actually sell something profitably from this tech? I do if there's good, strong leadership. And that sounds like a weasel answer. But historically, if you look at Satya and Microsoft and you look at Google, I just feel like Google was run by the inmates for a very long time.

54:39And this competitive near existential threat from open AI has given a sense of urgency for them to refocus and say, okay, we got to stop with all of the social stuff that is happening internally. And we got to really focus on what our roots were. Google hasn't really had a killer product. I mean, a true new product in over 10 years. But what's interesting is YouTube is a big winning, I mean, that was a great acquisition. It's a thriving product. It's generating a lot of money. Hopefully they don't go crazy and spend, you know, like everybody else in the streaming wars. But just like Facebook, right?

55:12Facebook.com is dead, right? What makes money for Facebook is everything else, the Instagram and WhatsApp. And if Threads takes off, you know, who knows? You know, and they're able to capture some modicum of the enterprise value that has been destroyed by Elon with Twitter. So it's all of these ancillary product categories inside of the mothership that I think that people are cranking and figuring out how do we make this work? Google's prominence in search, I think, is going to persist. I think it'll extend into other domains. I think it's less likely to be threatened by a lot of the AI stuff.

55:41They'll integrate it. BARD, when it first launched, sucked. Now it's not bad. You know, incremental search results are pretty good. But the corpus of information that they have, from my photos to my emails to my calendar, I'm pretty locked in. And I'm relatively trusting of Google. I'm also relatively, if not high trusting of Apple. And I've historically been very low trusting of Meta. I always say that whenever Meta launches a product, the one feature that it lacks is trust. And I think they're realizing, even if it's a little bit of a showcase facade for both the regulators and the critics, that they really have to double down on trust.

56:22And one of the ways to do that is a lot of open source stuff. So really watch for Meta to embrace open source in a giant way. Josh Wolfe, Lux Capital. That was a great conversation. Great overview of sort of the market right now. Thank you so much for coming on AdLots. Got to have you back again. Joe, Tracy, great to be with you.

56:52Tracy, can I just say, you know, I don't know. listeners might know I'm an amateur, you know, songwriter. And my only goal is to get something published before like the computers are just like so good at it. There's like my, you know, I've like, maybe I have like a window of like a year or two. I just want like one public, you know, I just want to have like one something, someone singing one of my songs and then the computers can do their thing. I mean, I do think this is kind of the most disturbing aspect of this whole AI discussion, which is that so far it seems to mostly apply to the fun stuff, songwriting, poetry, making movies, and we're still sort of doing all the dredge work ourselves.

57:36But that was a really interesting conversation. I do think so. I don't know. I take Josh's point about getting in early on some of this, but I'm looking at a chart of what am I looking at? Google. since the IPO. And if you got in in 2007, 2008, I think you'd still be okay. You would have missed maybe the life-changing money, but you'd still be up significantly on your investment. So I do wonder, obviously, there's a lot of excitement around the prospects of AI and what it means for various companies. But I also feel like if you waited for the dust to settle a little bit, you wouldn't necessarily be automatically losing out.

58:22I like how your question and your point here is not really, is basically like questioning the entire premise of venture capital. I like how that is actually the entire subtext of the question. Hey, after 2022, I think that's a valid question. Why not just wait for it all to go public? Yeah, it's fine. The other thing which I hadn't appreciated, which I thought was really interesting, You know, obviously, I know that, you know, Microsoft OpenAI, Google, or Alphabet Anthropic, but the sort of like the way in which some of this may be a function of the regulatory environment, I had not really like appreciated that.

58:59And why like, okay, it's going to be hard to like make big acquisitions. So you just invest in companies who spend most of their money with you. Like, yeah, yeah, it's like sort of I hadn't appreciated that element. No, I think that was a really interesting angle and actually explains a lot of the choices and decisions that are being made at the moment. Because sometimes you look at them and you're like, this is interesting, but I'm not sure I completely see what's happening here. But if you look at it from a regulatory slash reputational angle, it makes a lot of sense. You know what I'm really excited about?

59:34What? Bloomberg GPT. Did Josh say that it's going to be one of the winners? I feel like we should be doing a disclaimer here. We work for Bloomberg. It's fairly obvious we work for Bloomberg. Disclaimer as we work for Bloomberg. But we did not tell Josh to say that Bloomberg GP... But this point about who has actually high quality data is interesting. Yeah. And I would say so far, a lot of the excitement is around the chip makers, some of the incumbents, like Microsoft. I haven't seen people get really excited about insurance companies as an AI play yet. But I think there's something there. The other thing I wanted to say, and you asked this question about the user interface.

1:00:15Yeah. And I actually think it's really important in the story here. And this is where I would draw a parallel with blockchain and crypto, which is the interesting thing about crypto was that you could participate in this as a sort of normal person. You know, you could open a wallet of some sort and buy whatever your preferred cryptocurrency is so you could participate in it. And I think having something like open AI and various other models that you can play around with, like clearly has drawn in that additional interest. Oh, yeah. Like that is a big part of it. Absolutely. I do think like it's just like we've all had that jaw dropping moment, which is like you didn't really get with crypto.

1:00:57It's like, yeah, you could do it. But then it's like, OK, now I have this coin in my wallet. Right. Well, that's true. And then but then you just like, you know, literally it takes you 10 seconds to like be blown away. is just so powerful. Yeah. Shall we leave it there? Let's leave it there. All right. This has been another episode of the All Thoughts podcast. I'm Tracy Alloway. You can follow me on Twitter at Tracy Alloway. And I'm Jill Weisenthal. You can follow me on Twitter at The Stalwart. Follow our guest, Josh Wolf, on Twitter. He's at Wolf Josh. Follow our producers, Carmen Rodriguez at Carmen Armin and Dashiell Bennett at Dashbot.

1:01:31And check out all of the Bloomberg podcasts under the handle at Podcasts. And for more OddLots content, go to bloomberg.com slash OddLots, where we have transcripts and a blog and a weekly newsletter. And check out the Discord. We chat about all these things 24-7. We even have an AI room in there. Some of the questions from the conversation I sourced from there. So go check it out, discord.gg slash OddLots. Also, if you enjoy OddLots, if you appreciate conversations like the one we just had with Josh, please leave us a positive review on your favorite podcast platform. Thanks for listening.

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