Sean O'Kane (3:08)

I mean, we should be so lucky, to your point, and then we can move on. This company, in whatever form it exists now, is basically borrowing $50 million. I don't know how many GPUs that's going to get them and how they're going to be able to get to the front of the line when everybody else has, you know, $100 billion or more. And relationships with these companies, we don't know. You know, they didn't initially disclose who this investor is. You know, there's just so much here that reeks of not just the Long island iced tea thing, but a lot of the stuff we saw during sort of the nft and like web3 craze and crypto in general too, where public companies are taking advantage of the fact that they're listed on public markets, they can make announcements like this and generate some hype. I think this probably went further than even the people who are doing this expected it to go. You know, the real question is like, are they going to actually put some effort into trying to become some sort of neo cloud, or are they just going to, you know, ride the stock price and issue more shares to snatch money while it's on the table before, you know, pivoting back to wool sneakers or whatever?

Kirsten Korosek (4:14)

Well, I do hope that whatever they do, they put out some cool swag so that I can pick it up and put it in my archive of tech that we forgot and I get to open it up ten years from now.

Sean O'Kane (4:26)

With your Quibi socks.

Kirsten Korosek (4:28)

Yes, exactly. But let's talk about some deals steeped in reality. And so we're going to talk about Wave Today and FluidStack, also going to do an update on everything that's happening with OpenAI and Anthropic, which there is a lot, and get into the phenomenon now called token maxing. Let's start off with Wave, a company I've actually spent a lot of time in. And Sean and I, we actually went into their vehicle. When was that?

Sean O'Kane (5:01)

During Disrupt last year. Yeah, yeah, yeah. We got a ride in a, in a Mustang Mach E outfitted with WAVES Tech last year and it was pretty impressive for something that was operating only on just a few cameras. Although it was on, you know, what seemed like a fairly planned route around where we had disrupt. The news this week is chip makers amd, ARM and Qualcomm all sort of jumped in with, with you know, enough money to start a NEO cloud if you want $60 million sort of pseudo extension, I guess of the more than a billion dollars Series D that Nvidia helped back along with Microso SoftBank Vision Fund and a couple other automakers a little while ago. And you know, my question here is like Wave has now raised multiples of billions and billions of dollars. Clearly the money here isn't necessarily something that means too much to what they're able to do. But you know, you know, it makes sense for Uber or Nvidia to invest in a company like Wave that's trying to make like a self driving system that can go into almost any vehicle. But I'm, I don't really feel like I have a good sense of why chip makers would be getting into this game. Did you, I know you talked to Alex, the founder of Wave. Did you get a sense from him, Kirsten, like what the sort of import of this is?

Kirsten Korosek (6:17)

Yeah, I've talked to Alex a few times over the years and the important thing to know about WAVES Tech is and their business model is the way Alex puts it, this is Alex Kendall, he's co founder and CEO, is that they're taking a contrarian look at their business model and their tech stack. So end to end, they built a software layer off of Neural Network. So think of it this way. The vehicle takes any kind of sensor that's on a modern vehicle and any kind of chip. So it's tech agnostic when it comes to the hardware and then takes that data and can teach the vehicle to drive. And this is obviously not just like plopped into any car. I mean there's a whole licensing deal that happens and they do have a solid customer with Nissan that seems to have just been expanded. The chip deal to me is really more about locking in with all of the different chip players that are already in vehicles and helping in that development to ensure that everything works and also to help scale. So all of these chip partners, obviously if they see Wave as an up and comer that is getting into these vehicles, they, they want a piece of that, they want to be part of that development. And then Wave benefits from working directly with these chip makers. I did ask them, by the way, hey, is this in kind trade type of investment or is this real capital and it's real equity. So you can see that they're playing the long game, but this is all about development and then the ability to scale.

Anthony Ha (7:52)

I did want to get back to Wave in a second, but I also wanted to ask about something that Sean mentioned, which is that I think not in this extension, but in that giant billion dollar plus round, Uber was also an investor. And I know that on some past episodes we've talked about the kind of sense that when it comes to robo taxis and self driving, Uber is basically just like investing in everyone and partnering with a different partner in every single city. I mean, is this part of that same strategy?

Sean O'Kane (8:19)

Yes. And I guess is the way to answer that like yes, in the sense that Uber's basically placed bets. I mean the Financial Times had a story this week that has kind of rounded it all up and, and sort of figured out that it's about $10 billion that Uber has now committed in some way to these other companies that are working on autonomous vehicle tech. So in large part I think it's that. But also Uber seems to be, seems ready to be working closely with Wave to put, you know, put a real robo taxi service the street in a way that maybe Uber isn't necessarily sort of being so explicit about with some other companies. I think there's gradations to the bets that Uber is placing. Some are a bit more speculative and they just want to have that relationship and some where they're actually moving pretty quickly towards or already deploying like we see with Waymo, where, where Waymos are available on the Uber app in a number of cities already.

Kirsten Korosek (9:11)

Yeah, the Uber relationships are definitely on a sliding scale. So I always like to look at word wording like at least order 20,000 vehicles and not up to. There's a big difference. The case with Wave is, is. Is seems pretty rock solid. I mean this is Uber working with Wave wanting to have their tech in a vehicle that it goes on the Uber network in London. And this is Uber is planning on investing another $300 million into WAVE. And, but it's milestone based. So once they're able to launch, and my understanding is that it doesn't have to launch driverlessly right away. So there may be a human safety operator behind the wheel that that will unlock that $300 million milestone. And then Wave is also talking to and working with other automakers Beyond Nissan, we should mention that Stellantis and Mercedes are both investors. They clearly are working together. There's no timeline though on like when that tech might go into their vehicles. So it's not like quote unquote an official customer announcement yet. So there's absolutely a lot going on and I would put the Uber Wave relationship as far more serious one than some of the other ones that they've done. And also I think Uber's just playing

Anthony Ha (10:32)

the long game in terms of like what success looks like for Wave. It sounds like they're partnering with a lot of different automakers. Is this something where, you know, in a few years potentially a lot of people could be in vehicles that have, are powered by Wave technology or at least you know, the kind of self driving parts of it are, and not even know that it's there?

Kirsten Korosek (10:52)

Yeah, I'll let Sean answer in more, more, more beyond the. Yeah, but yeah, they have two products. Sean, what do you think?

Sean O'Kane (11:01)

Yeah, no, I mean that's pretty much it. The, the idea is that this could be something that's powering a robotaxi that you're hailing or this could be something that's powering, you know, a Nissan vehicle or insert other automaker here not named Tesla, you know, that you purchase, you know, in the near future. And you know, one thing that I think is also really interesting about Wave and in some ways gets more interesting the more of these deals that they strike and the more money that they raise is, you know, Kirsten mentioned it before, they're looking to launch in London because they're a UK startup like, and I think that's just for so much of the focus on autonomous vehicles. We're talking about, you know, Silicon Valley or China really. And you know, Wave was by nature of taking this kind of contrarian approach and going at this like sort of end to end hardware agnostic tech a couple years ago that seemed at the time, especially during the, you know, the late hype cycle of the 2010s of that initial sort of AV hype cycle, it seemed like a real long bet. And that long bet has turned them into, you know, one of the more valuable startups sort of across Europe in general.

Kirsten Korosek (12:07)

You know what also they're an AI company, but you know, what also is an AI company or powers AI data centers. That's my like terrible segue into the next deal that I really want to talk about, which is Fluidstack and this is an AI data center startup. I don't know if either of you have been Tracking this company, I didn't know a lot about Fluidstack actually prior to this. They're in talks for a billion dollar round at $18 billion valuation. So I was like, wow, I should probably know this company a little bit better with that type of valuation.

Sean O'Kane (12:41)

It's hard with this sort of speed and scale of the announcements that are happening around how many of these kinds of data centers are being built out to really, I think sometimes understand all the different roles that different companies will play in that progression should this all happen as it's being sort of promised. And I think there are good reasons to question that. Not just because of the sort of hesitance around data centers in the US in general right now and from people who live in the areas where they're being built, but also because we keep seeing some of the plans shift from some of the bigger players who are making commitments to these and backing off them in different kind of interesting ways. All that is to say that, you know, I find, you know, a company like Fluid Stack sort of interesting as someone who's kind of trying to stand in the middle to a certain extent of all those other larger players that are household names by now. One thing that I am kind of curious about as they continue to raise money at this scale and other companies in this area, specifically around the construction side of this and maybe design a little bit too, is how much gleam they get from the size of the number. And I'd say that in the context of someone who writes a lot about automotive startups where it's easy to kind of get lost. And I think we've seen this in a pretty hard way over the last couple of years in those big numbers. If you're not really thinking about how much the sort of table stakes really are for how much money you need to do this right. So like a good example is like Lucid Motors went public in a SPAC merger a couple of years ago and it raised $4 billion in that transaction alone. And like they're still struggling to kind of like get things right and get really get off the ground in a sustainable way. And I'm curious like, you know, if that's something that's crossed your guys minds too as you look at some of these where it's like wow, billion dollars, you know, $18 billion valuation. But like, you know, how much is that really tied to future prospects for this company versus they just need a lot of money to do this stuff. And like that can kind of skew their perspective.

Anthony Ha (14:44)

To throw one other number in there just to kind of like for some of the scale involved here is that I think they also have a $50 billion contract or agreement with Anthropic to build data centers for them. And so yeah, it's this thing where again, as we often say on this podcast, it's like billion dollars is like a lot of money in most contexts, but actually in the context of AI and AI infrastructure, it's actually not that much. And like, I think your other point is like really well made too of like when these deals get announced, like the price tags are just huge, like we're going to build so many data centers for this much money. And then it kind of goes quiet for a while. And I mean the building there is building happening, but I think it's not as clear as I think probably we would like in terms of like where they're actually at and how much is actually going to get built.

Kirsten Korosek (15:34)

Do I sense some skepticism, Anthony, as to whether these infrastructure projects are actually going to happen?

Anthony Ha (15:42)

Yes. I mean I don't think none of nothing's going to get built, but I would be similar. I think it's a very safe bet that the number will be somewhere between the numbers that have been announced and zero.

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Kirsten Korosek (16:23)

Well, I'm glad you brought up the Anthropic deal because we are going to get into all the things OpenAI and Anthropic here next. But I do want to make one final point about FluidStack, which is to me, I think that it's an example of AI startups increasingly becoming like sort of dedicated infrastructure plays for the big frontier labs as opposed to trying to compete with them. So if you can't beat them, join them. And so I'll be watching for more. I would expect more of those types of relationships. But we should talk about Anthropic and OpenAI because darn, there's been a lot in the last week. Anthony, you want to kick things off? Yeah, let's do deal.

Anthony Ha (17:01)

Let's do. I mean this is equity. We'll mention a couple of deals and then I think we can kind of zoom out to the bigger significance. But two deals that are worth mentioning. One is that OpenAI acquired this personal finance startup called Hero. That's Hero with an I instead of an E. And that kind of comes after another deal that I think was literally announced when we were recording our last episode of Equity. So we didn't get to talk about it, which is that OpenAI had also acquired TVPN, which is this essentially a business talk show, a new media company. And I think both of these deals are pretty small by the scale compared to the scale of OpenAI. These are not things I think that people expect to really change the course of their business or anything like that. But they're interesting because it suggests that there's still this kind of like, all right, let's try out different things. Especially the TBPN deal of people. It's just like, why would you do this? Particularly at this time when it feels like OpenAI, from all the reporting we're reading, is also trying to, like, really refocus on making, you know, ChatGPT and its GPT models really competitive in enterprise context with programmers and things like that. Like, is like running like a tech talk show. Really? Should that really be on the to do list?

Kirsten Korosek (18:20)

No, it should not be on the to do list. That's it. I do want to mention Hero, because that, to me, okay, I know Sean has stuff to say about TVPN for sure, because there's a, there's a pithy comment in there somewhere. But with the, with Hero, that's an interesting one because Julie Bort, our venture editor, super talented. She, she wrote about this and was, I think, the first to write about it. And she dug in a little bit and basically this looks like an acquihire. The company is, is folding. I mean, they, they basically said by this date you won't be able to access this anymore. This is a personal finance startup and they only launched two years ago. So this absolutely is about getting talent on board. So I'm very curious to see if OpenAI is going to be. Is full, just, just absorbing them into the ether, if you will, at OpenAI or if they're actually like, interested in some sort of personal finance product that they are. They want to work on. So it's a very specific skill set. It's. To me, it's not really clear.

Sean O'Kane (19:24)

I think you could look at both of these as aqua hires to a certain extent. I mean, like, the TPPN acquisition is, you know, allegedly, they are going to retain Their editorial independence on the show that they make every day. And, you know, all respect to those guys who've put that, you know, out there and gotten it off the ground so quickly and grown it into what it has become. I think you, any person who follows the media should have a healthy dose of skepticism that when you acquire something like that and you put them, the people who make the show under the org of sort of the public policy people and sort of comms or marketing adjacent people higher up at the company making the acquisition, that you could have good questions about whether or not saying editorial independence is enough. It's not an incantation that just works. But you know what's interesting to me about these two, while they are similar in their, like, aqua hiring ness, I think they Both represent like two major problems that OpenAI is facing. One is Hero is, you know, OpenAI has a very successful product in ChatGPT. As far as whether or not that will actually ever make them enough money to become a sustainable business that's not raising the most, you know, the largest private rounds in the world ever to keep things going is a big question. And they have also seemed to be struggling to sort of keep up on the enterprise side of things, where the real money seems to be from some of the other players. And so bringing in a team like this, to me seems like taking a shot at like, what else can we do? You know, the, the guy who founded Hero seems to have this kind of serial entrepreneur streak of creating consumer apps. And so this seems to me like a bet on them being able to come up with something else that may have more hooks than just a chatbot and maybe something worth paying more for. And then, you know, TVPN is like an acquisition made to help better represent what the company does and better shape its image in the public eye, which lately has not been great and certainly is under more questions now than just a few weeks ago, because Ronan Farrow just led a report at the New Yorker that dropped suspiciously right around the time that this and a couple other announcements from OpenAI came out last week. And so there's just, I think those are two big sort of existential problems that OpenAI is trying to solve right now. And these acquisitions both seem like they're targeted at trying to crack both of them.

Kirsten Korosek (22:03)

And so the thing that you didn't say is then there's anthropic kind of looming, not in the shadows. I mean, they're very much taking up a lot of space here, but they're having a lot of success on the enterprise side of things. So it feels like these guys are competitors and they also feel like very different companies in a lot of ways right now.

Anthony Ha (22:25)

I think they're directly competing with each other. I mean, there's definitely a scenario where if AI as an industry, as a technology, as successful as the sort of its proponents hope for, that they could both be very successful companies. Like, they could just be the kind of one and two. And the success of one does not necessarily mean that the other will just fade into obscurity. But it does seem like, I mean, more than anything else. And again, none of this is official, but there's just been a lot of reporting around how it seems like OpenAI more than anyone, is kind of obsessed with and upset about Anthropic's rise. Although actually another kind of angle on that was also our reporter Lucas. He did a great piece over the weekend about the Human X conference and where he was talking to everyone there and everyone was talking about Claude Code. And they're sort of like, oh yeah, like chatgpt, like that's, that's fine too. But like they were all about Claude code. And I think that is exactly what, you know, OpenAI is worried about, because again, in theory, there could be many other opportunities for generative AI, for LLMs, but it feels like the big growth area, the area where the most money is and where they could, you know, maybe at least see a path to having a sustainable business in the future, is in these kind of, again, enterprise encoding tools, which are not like exactly the same thing. I mean, there's plenty of other enterprise use cases beyond coding, but like, especially with coding, I feel like if they're, I think they're worried and probably correctly, that if they lose there, that it's going to be very hard to kind of be the number one company, at least in the near future.

Kirsten Korosek (24:02)

Yeah, I see this as like kind of three slots right now. Like Human X, it's full of people using this for their jobs, so tracks that and it bodes well for Anthropic. Right. And so then all of a sudden it seems like the folks who are going to the Human X conference are looking at ChatGPT as that consumer product. That's the thing that maybe to Sean's point earlier, like, maybe they're going to be building out like interesting consumer apps based on sort of the background of OpenAI, like you could kind of see that. But then there's this other bucket, which is Defense, which is like a hybrid of enterprise in a way. And it seems like, they're both fighting over that. Absolutely. Like, the. The wallet's quite open with the Department of Defense, and I think they're both vying for that. Absolutely right.

Anthony Ha (24:50)

And part of the other anthropic news recently was about the announcement of this. I think it's pronounced mythos, which they hyped up as, like, the model so powerful that we can't release it to the public. But there was sort of been this interesting kind of government angle to it where, as we've discussed quite a bit on this show, like, Anthropic is sort of not on great terms with the Pentagon right now, which has declared them a supply chain risk. But apparently there are other parts of the Trump administration that are very interested in working with Anthropic. And so Jerome Powell apparently called a meeting last week and, like, told a bunch of, like, the big banks, like, you should all be trying out Mythos, because, like, this could be like, a really, really important cybersecurity tool.

Sean O'Kane (25:30)

Yeah, that timing is really interesting, isn't it? I'm not saying Anthropic is only talking about this now because, you know, it's a way for them to sort of get some leverage back over the government, but it certainly works out in that way where all of a sudden, the Trump administration is kind of knocking on Anthropic store to a certain extent to say, like, we actually want to evaluate this, you know, remove yourself from, like, all context. But, like, if you do really develop a model that can hack pretty much anything, like, yeah, actually, I would want the government to probably take an evaluation of that. And maybe that is something that needs to have some regulation around how those things get developed and get handled and who gets access to them and all these things. And so, like, in some ways, like, it's a little encouraging that they're willing to maybe set aside their petty differences for a moment to, like, take a look at this and talk it out. But, like, you know, all that context comes rushing back in. I don't think that those are the kind of conversations that are actually happening right now.

Kirsten Korosek (26:30)

You know, I want to also kind of take a step back and, like, against this backdrop or what we are living, like, I feel like, very steeped and very, very much inside that AI bubble of, like, startup scene in Silicon Valley and the AI labs that are in San Francisco. And, like, we're really close to it, but there is quite a lot of people outside of that. And, you know, Stanford did a recent report highlighting sort of this growing disconnect between AI insiders and everyone else. So I think it's important that we sort of acknowledge that as much as we, you know, we're here to talk about startups, there really is a whole big group and population that not only are disconnected from it, but also quite suspicious of AI and how it is going to, you know, seep into their lives if it hasn't already.

Anthony Ha (27:23)

That also like ties into something that, that Sean had mentioned earlier about the, the New Yorker piece about Sam Altman. And like, it just feels like we're at this moment where a lot of anxiety about AI is, is very, very high. I mean, I think it definitely might continue increasing. I don't know that we're at the top yet. But at the same time it feels very disconnected from the way people in the industry talk about it. And I think that some of that is of course, I mean, AI insiders are to a certain extent kind of just hyping their own product, right? Well, of course, the product that you have billions of dollars on the line trying to sell, you're going to tell me that that's going to lead to a good future. But I think there's also this disconnect because you were talking about us as sort of being in this world and obviously we are in a lot of ways. But I think in terms of how much our lives have been transformed versus a, or at least our professional lives have been transformed versus a programmer, like I think is much smaller. Like, whereas like you talk to anyone who codes, right? And I, and, or almost anyone who codes and like just what their daily day to day looks like now is so sounds so radically different versus how it was a couple of years ago. And I think that's not really true in almost any other profession. And so there's this part of the disconnect I think is that there are these people who are like, no, like this is the future, I'm living it right now. And everyone else is like, maybe.

Kirsten Korosek (28:42)

Well, and I think that like we've seen this with any new and emerging tech that really kind of takes over the conversation. And also with these massive valuations, I mean it's a financial piece, it's like creeping into culture, it's creeping into our entertainment. In terms of like references to it, then you also are seeing like these backlashes towards it. I mean, we've seen that with, you know, autonomous vehicles, people kind of like going after the robots in this, in this scenario. What's happening with AI, there are far more serious situations that are occurring where, you know, people who are you know, let's say, like, clearly not well, are going after the people behind AI. And while this certainly isn't, I would say, a trend yet, I mean, we saw the attack that happened on San Altman's house earlier this month. You know, I kind of wonder if we're going to see more of this. Hopefully not. But people's sort of suspicions and frustrations sort of maxing out like this as opposed to protesting about it or doing more rational pushback.

Anthony Ha (29:49)

Yeah, it's a difficult thing to talk about in some ways because I think, and Altman himself did a blog post where he talked about sort of trying to take the rhetoric down a bit. And I think that's completely reasonable because we, we don't want to see tech CEOs homes being attacked. But the challenging part is how can we take these issues seriously? Because these are very, very serious issues. These are going to determine sort of the course that AI takes over the next few years, really could potentially determine what all of our lives look like for the next few decades. And to take that seriously, discuss it seriously, be willing to criticize the companies when they should be criticized, but also not, you know, have a situation where those kinds of things are happening.

Kirsten Korosek (30:36)

You know, one thing I think that is worth noting is that while this is happening and there's these big shifts in society, what is very real is that people are using it, right? I mean, a year ago or two years ago, I don't know if I would have predicted the amount of time that people would spend, you know, interacting with Claude or ChatGPT. And certainly we've seen, you know, misuses of it. But to your point earlier, Anthony, about uses on the enterprise side, there is like, I mean, our language is even changing to talk about this. And so, you know, token maxing is another thing we wanted to talk about today. You know, did that, that term even exist a year ago? I don't think it did.

Anthony Ha (31:23)

First of all, I just want to say that whoever is coming up with these phrases for, you know, the software maybe take a different tack because I just feel like things like vibe coding and token maxing are to me not.

Kirsten Korosek (31:37)

I kind of like them. I kind of like them. I kind of like them because it perfectly illustrates what is happening. I mean, is there anything more? Like you could talk to someone and be like, what? You know, token maxing, like, I get it right away.

Anthony Ha (31:51)

Yes. I mean, they're memorable. So for that, and I mean, the number one thing you need from a meme is it has to be memorable. It's sort of clear what you're talking about. So that's important. I think that if you think that a lot of people using Claude or whatever model are basically just sort of like cooking their brains and just really spiraling, then calling it token maxing is not going to dissuade you, let's say. And so we should say that what we're talking about is essentially this idea that at a lot of tech companies, both kind of the AI labs, but just, you know, more broadly because, you know, every tech company is an AI company now, like, there's this almost like a performance of like, you have to just use as much compute as possible. You need to be using as many tokens as possible. There were reports that Meta had like a leaderboard showing who was using the most tokens. And then also. But then it turned out maybe that was incentivizing some, like, not great behavior because then it was just like, well, what if we can just like make this query as long and complicated as possible because that'll use more tokens? And so, I mean, I think it's a very real thing, but also feels like it's, you know, encompassing a lot of the things that are kind of silly about the AI craze, which is this, like, this sort of just like people kind of just going a little crazy.

Sean O'Kane (33:10)

I want to know more about token maxing fraud. I want to know who's coming up with the most clever ways. Because, listen, like, are you doing your job or are you doing your job to the like, degree and quantity that I want you to is like one of the oldest sort of, you know, boss overreaches in history. And so it's just, you know, are we monitoring keystrokes? Are we monitoring token usage? Like, it's all different flavors of the same kind of impulse. You know, Meta shut down its sort of way of tracking this and showing it to people after it leaked. But Reid Hoffman said this week that like, you know, he thinks it's like a good rule of thumb. What I want to know is if that pressure is really up there on folks out there to the point that they feel like they can't, you know, they're spending every waking day trying to token max and they're not, you know, matching the leaders in their companies. I want to know what they're doing to get their token usage up. If it's stuffing it with long queries like you said, or running open claw to fill more requests or something like, let us know.

Kirsten Korosek (34:15)

Yeah, reach out to us and let us know. How you're using it. The element here is also that AI tokens cost money. And so companies are incentivizing folks to use it, but hopefully with a result that makes the business run better or creates a new product. And what we're seeing now to answer that problem is some emerging startups that are all about token maxing or how to do it in a cheaper, faster, more efficient way. So how to get more out of that? And there's a company called Parasail that Tim Fernholz wrote about this week. They just raised about $32 million, which is small compared to, you know, a lot of the other companies we talked about. But they, their whole pitch is about how they can scale like the AI inference infrastructure in a cheaper way. I think we're going to see a lot more startups like this or companies with like enterprise companies that have, let's say an AI product that, or AI agents that will market something like this. Because it's not just about, hey, everyone's using it. How do you keep your budget low enough so that you can keep using it?

Sean O'Kane (35:23)

How do you keep your budget low enough to use it? And also like, this brings me back to sort of the question at the core of all of this, which is like, is what presumably these companies are not. Are more incentivized right now to charge an amount that keeps people using it cap where it goes too far. But like, is that amount enough? And maybe we'll get visibility into this when some of these companies go public by the end of this year perhaps is that amount enough to actually turn into a sustainable business? Or is the amount of money that they're raising from outside investors offsetting that cost to such a low extent that you're not able to do that. And you know, so like, that's the thing that's always on my mind. And you know, even with that in mind, Uber CTO said this week that like they pretty much he feels like they blew through their budget on AI spending already because of how much they're using it. And it just, that is like the heart of this issue here. As fun as it is to think about, like how this stuff is being used, like it also the cost of it all really, it just seems so like such a hot issue for me and like one that I'm maybe the most eager to see, you know, if and when we get These sort of S1 filings when these companies go public later this year.

Kirsten Korosek (36:38)

Yeah, Parasail is probably not be going public anytime soon, but I did have this fun fact that I think it will kind of put a, a figure in your head that just seems so insane. But the founder or the CEO spoke to Tim and said that it generates 500 billion tokens a day, which is just. It's hard to even think about how like I'm. Who are we who's using all this? Which is like just it helps understand like the weight of this marketplace and I don't know where it goes from there.

Anthony Ha (37:14)

Well, I feel like there is so much we could talk about here, but we are a little over time already, so let's wrap things up there. Of course, if listeners want to keep up with us, we are at Equity podcast pod on X& Threads and we'll be back soon.

Podcast Host/Announcer (37:32)

Equity is hosted by TechCrunch senior reporters and produced by Teresa Loconsolo with editing by cal. Subscribe on YouTube or wherever you get your podcasts and find out what's next@techcrunch.com events. Thanks so much for listening and we'll talk to you next time.