Grok 4 Beats OpenAI + The $300 AI Agent Era | E2150

The Internet is filled, you'd be fine. The shocking Alex. And I'm sure the audience will as well. With biased people. It's. There are people on the Internet who are not straight shooters. They're not calling balls and strikes. They're on a team and they have.

Really?

Yes. And when they state facts about a person, they may use colorful language or you know, compare them to Hitler, Idi Amin, Stalin, etc. And they're doing it in bad faith.

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All right everybody. Welcome back to this week in Startups. I'm your host Jason Calacanis. With me again my co host Alex Wilhelm. We've got a full docket for you on a Friday join July 11th crypto at an all time high rock four blowing people's minds. What else do we got here? Just tons and tons of interesting stuff, plus a great guest. Got a great guest here. Second time founder. I've invested in doing something very interesting in the self driving space. So that's a real special treat for you. Live in studio here in Austin.

Yes.

How are you doing Alex?

I'm doing fantastically well. It's Friday. Feeling good I think. I think the interview today is going to be a lot of fun prepping for it. I'd never heard of this particular niche so everyone should make sure to stick around because that's. It's definitely a little forward looking you might say Jason, but I love people that are just ahead of the ball.

Yeah.

But I really do think that the biggest story of the last couple of days has been the debut of Grok 4 from X AI, which according to metrics, Jason is fantastic. According to the standards that we look at, it's blowing people's minds. A comment that I love that sets the tone for the latest kind of state of the art model is from Tim Sweeney, of course from Epic Games and he says Grok 4 feels like artificial general intelligence to me and I think in terms of endorsements that's about as good A1 as you can get.

Yeah, it's interesting. There are objective tests we can look at as well. Everybody knows these models do a series of tests, math, like sats, the lstats, whatever that is for legal, you can put these through all kinds of tests. Which of course the people who make models are now a bit obsessed with their rankings on these tests. So, you know, they. I'm not sure exactly how important these tests will become once they've all been mastered. We're moving into a space where all human knowledge has been mastered according to these kind of tests. The idea that AI would get something wrong on the SATs to use a common test, people know, just seems farcical at this point. Like why would it get it wrong now? That's.

Yeah.

Think about how far we've come. The idea that AI is going to win every chess match. We kind of got okay with that about 10 years ago. It's going to beat you at go five years ago. It's going to be a better driver than you probably. We're like soaking in that moment right now. It probably is better than you. Net net with drinking and distracted driving and certainly on these tests. So let's just go over some of these tests. I know there's like the artificial analysis index or whatever that is of seven or, or eight different tests. Maybe you could show this versus the competition. I think it's an interesting chart.

So the chart, the, the chart that I thought was the most interesting is this one. So it's from the group Artificial Analysis. They run kind of a meta test. Jason. So if you're familiar with GPQA diamond or the very well known Humanities last exam, this takes all of that into one bucket. And what we have on the screen here is a time series chart showing how models from different providers are doing over time. Now there's a little bit of screwiness because the, the Data points for OpenAI and Xia are both black. But this over here, the upper right little image here, that is Grok 4. It is now, according to them, the state of the art model. And as you can tell, OpenAI has led most of the way. And then GROK just pips it right now. So we do have kind of a new leading AI model company. And if you're a fan of Meta or Mistral or what Anthropic is working on, you can see them in this chart. Of course, Jason, a couple of points may not be the world to someone who's just using it to ask questions about cats, but if you care about applying this to your startup to your business problem, whatever you want to have the best. And currently look at that, man. Well done, xai.

Yeah, yeah, it's. What's particularly impressive here is if you look at when people started taking these tests with their large language models in November, December of 2022, you have OpenAI starting that test and then March 2023 and you know, they're making incremental. Then you see the blue line show up, which is meta. The orange line show up Mistral. The green line show up in 2023, Google. And then if you go forward right to the middle of the chart, March 2024 is when Grok, I'm assuming to dropped and was done for these tests. So in from March 2024 till now, which is five quarters or so, 15, 16 months, Grok has caught up to all of the folks who were ahead of them and who started a year or two ahead of them. That's really what's impressive, is how quickly they've caught up when you actually look at the distance between them. Okay. Not, not a big difference. Right. It's, it's. They're, they're both in the 70, 72 range, it looks like. So not a particularly difficult, you know, it's really impressive. It is difficult how? And challenging to catch up that quickly, I believe. Where it goes from here, who knows? That that remains the question.

I find this super encouraging. Now, if you're a big OpenAI, Stan, if you're a big believer in Google's Gemini models, you might be a little bit annoyed that your favorite company is currently lagging behind one other one. But how great is adjacent just for the state of technology that we're still finding ways to improve these models, that these AI scaling walls that we've heard so much about currently are still being knocked down. We're not at a point at which we're out of ideas. We can use more compute, we can use more data, more reinforcement learning, more humans in the loop, more time, serious compute, et cetera, et cetera. And things are getting better. And perhaps even more importantly, we're seeing the price of these models collapse over time. So here's another chart from the same source. This just ranks models by their intelligence bucket. So Jason mentioned the intelligence score. Well, you can see here, Jason, that as time goes on, even the more intelligent models are seeing rapid price declines. So if Grok 4 feels a little expensive to you right now, or if OpenAI is 03 or, you know, Gemini 2.5, wait six months and they'll be half off. So it's incredible. I think the pace of progress here and also just the fact that they're getting more and more affordable. I love this chart.

Yeah. So if you look at the. I guess the deep purple line is an intelligence index of greater than 50 and I guess it was achieved in. The first time that was achieved was in September of 2024. And at that time it looks like it was $2 per 1 million tokens. That price has come down to. It looks like 6 cents per 1 million tokens. So that's a pretty dramatic drop from 2 bucks to 6 cents. Extrapolate this chart, it's going to drop even further and this will continue to drop as the hardware gets more powerful, the software gets more efficient and the models get better. So. And this is probably why you're starting to see deep research. I noticed like people with free accounts are doing a certain number of deep research ones. I think they're slowly starting to give those deep research projects where multiple threads are done and it's doing like 20, 30, 40 different searches, compiling the data and it takes five minutes. Those things. I keep seeing people do them for free. So I'm paying for those on like three or four different services. I'm paying for premium on and I don't know if I need to. This will all probably become free for most use cases. I'm interested to see if this is all going to be this idea that you're paying for AI like we used to pay for usage of online dial up services. When they started they were six or seven bucks an hour, went down to five, three and then eventually all you could eat. I think we're going to kind of get to all you can eat subscriptions. We kind of have those at some levels already. Including this 200, $300 level. Is $300 level version of Grok a $200 level of perplexity? I think Google has an offering in that range as well. I wonder if those things are long for this world and if we just have a $20 version, all you can eat eventually is where this winds up.

Okay, so that's what I was thinking too. Like that was absolutely my perspective that things will get cheaper and we'll have a nice consumer friendly price point and you'll get either tons of it for free or tons of it for a very low price. However, Xai, introduce a new plan that costs $300 a month and gives greater access to Grok 3, Grock 4 and Grok 4 Heavy. Now $300 a month is actually a new high Watermark, because I believe you can pay Google 250, you can pay OpenAI 200, you can pay Perplexity 1 or 200 bucks, cursor 200 bucks and now 300. So we're seeing that people are charging more for models at the absolute bleeding edge. But I think that for pretty much any consumer, the 201525 buck a month option is going to be okay. But it is interesting to see that the price trend we see in general is not manifesting at the edge. And I think, you know, Xia is trying to push the price point further up and, you know, Godspeed to them if it works out because this stuff's expensive to build. So I get it from there.

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That concept of multiple agents doing the same search and trying to debate each other to get to the right answer, we're going to keep seeing that. We talked about in a previous episode here, somebody had done it with programming and checking code. You know, you can almost think of it like pair programming where two people write code at the same time. In this case, two AIs write code at the same time. A third or fourth AI look at the results, pick the best one, debate it between them. Was it, could this have been done better? Is there a better way to do it? And so all of human knowledge feels like it is somewhere on the Internet or all human knowledge that's worth writing down at least is on the Internet. So if it's not worth writing down. One might argue it's not that important. So it will stand to reason that the next phase of this is novel creation. And that I think is going to be really interesting. Can these products become so good that they find novel solutions or novel ideas, maybe problem solve or even find questions that are hard to answer and then go and try and figure it out themselves and go down some rabbit hole that we haven't seen? I don't think there's a mathematical problem that's so sticky that humans can't understand it, that AI has solved yet. So you can look for it in math and physics. Will these make a discovery in math and physics that would have won some notable prize for math or physics? Right. We haven't seen that, but it does feel like we're about to see that that's the next phase of this is novel solutions, novel identification of problems. Even the identification of a unique problem, like finding a unique problem in the world that's unsolved, that's even hard to do now because there's so many humans, billions of humans sharing collectively their knowledge on the Internet.

So basically we're setting up a poly market here, Jason, kind of in real time. So let's pick a date here for the over under. When do you think is a reasonable estimate for when we reach that milestone from your end?

Gosh, it's a interesting one. We should probably sharpen this. And I'm not an expert on physics or math. I don't spend my time looking at what physics and math problems have yet to be solved. But if I were to use Comet right now, my browser from Perplexity I've been playing with, and I just said, what math problems haven't been solved by humans or AI? And you can ask producer Claude as well, because I think my Perplexity is hooked up to Claude. So maybe this is the same answer and we can kind of just pull up what hasn't been solved. Then if we can take some of those, you could say, of this list of 10 problems, when will AI solve one of them before a human does?

I think we should probably. Well, producer Claude's asking that question right now for us. We'll have that in a second. But I wonder if we should set the bar that high, because if we're looking at the top 10 problems, we're probably picking the hardest ones. So I wonder if that's the right threshold. But I think it is because we want it to be the point at which they actually blow our minds, not. Not do the bare Minimum here.

I just wonder how many unsolved math problems have been identified. Oh, like that actually is an interesting one just in and of itself. So, you know Hilbert's problems, 190023 problems were posted, of which 15 remain unsolved or only partially solved. Landau's problems, 1912, 4 problems, all remain unsolved. Millennium Prize problems, 2007 problems, 6 remain unsolved of 2025. So there are in academia, in math circles, physics circles, people have been doing this for hundreds of years trying to find math problems that are just too difficult to solve. And then this is going to be the next phase. Almost all of the work done and those tests and those benchmarks we look at are for problems that have been solved. And then you're just trying to see, can the AI solve this problem? What's its thought process? How did it learn to do it? Well, it went to brilliant.org or it went to Khan Academy, it found a video on YouTube. It understands how to solve this problem. And now anytime you give it that problem, it gets it right. And it, it's just such a known problem that it's in its, its corpus of knowledge that it can solve.

So, yeah, producer Claude puts out the P versus NP problem, which I'm actually familiar with, the Riemann hypothesis, discussing the distro of prime numbers. I'm also familiar with that one. And then, oh, I didn't know this one. The twin prime conjecture, that there's infinitely many pairs of primes that differ by two. That intellectually feels right to me. But it's another unsolved problem. So really, there's a lot that's still out there in the math rule for these companies.

I mean, theoretically, to solve infinity, you need an infinite amount of time, which is impossible. So, like, some of these problems may just in their definition, not be solvable.

I do literally have a mathematician on speed dial. But I'm not going to call up during the show, but I'll ask, I'll ask Kirithi afterwards what he thinks about these and when an AI will pull it off. But it's a good point, Jason. We're now to the point when we have digested what we know and can spit it back out. And now the question is, when will these be actually better and stronger than us and can therefore lead us into the future? Before we scoot on, there's a little bit more here we should talk about. Okay, so a couple things. The Attorney General of Missouri has sent letters to Google, OpenAI, Meta, and Microsoft pertaining to their AI models. Now we talked on the show quite a bit about the push to ban state level AI regulation here in the US that ended up not becoming law. So that's not currently really in place. And so we're seeing people begin to politic and kind of regulate by threat here a little bit. And the Missouri AG thinks that AIs from those companies are biased against threats. President and at the same time some Democrats in Congress are annoyed with xai over when Grok3 went a little bit nutty the other day and they want GROK to remove some posts. So clearly we're running up against what I would call First Amendment issues as it relates to AI models. And as they become more powerful, more prevalent, more commonly used, more kind of just in and around the market, there's going to be more of this. I just hope that we end up allowing companies to have their own speech and not having draconian top down regulation by threat, because it just seems like a backward step for the nation compared to other countries.

Okay, so let's still amend this. There's output from large language models that people sign an agreement that these are essentially not to be trusted. There's a million disclaimers when you agree to use these. These are in beta format. You've agreed explicitly in all these terms of services in 20 different ways not to trust this information. But, but people using it do trust it. I mean, we're sitting here using producer Claude all the time to check on facts, asking it to cite sources and we haven't found situations where it's let us down. I'm sure there will be one and we've talked about it ad nauseam with hallucinations, etc. So this attorney General in Missouri wants to know about President Trump specifically, is that correct? This is about Trump?

Yes. He asked the AI models. I think the question was list the most anti Semitic presidents or something along those lines. And he is disputing the probabilistic output from these companies.

Okay, so I think this is where Wikipedia also got in trouble, which is the bios of living persons. I've talked about before. When you are trying to solve a math problem and it gets the wrong answer, it doesn't know how to solve the problem. You look at it and go, okay, I'm using AI to try to do a hard math problem. This language model versus the other one. Got it right, got it wrong. My prompt was changed. It's all experimental. Right. Nobody should be using this to make life and death kind of decisions. That being said, when the AI which is super impressive and is passing all these tests, starts to talk about living people and tell you what it thinks of them based on the information it trained on. From where? From humans on the Internet? Well, garbage in, garbage out.

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The Internet is filled. You'd be fine this shocking, Alex, and I'm sure the audience will as well. With biased people. It's. There are people on the Internet who are not straight shooters. They're not calling balls and strikes. They're on a team and they have really? Yes. And when they state facts about a person, they may use colorful language or, you know, compare them to Hitler, Idi Amin, Stalin, etc. And they're doing it in bad faith. So these models, if they're trained on social media, Reddit, blog posts, substacks, YouTube videos, podcasts, whatever it is, transcripts of those things, obviously asking it, oh, do you think Trump is Hitler or not? Or which president is most similar to Hitler? Well, it's, it's been trained on whatever number of years of people referring to the authoritarian tendencies of Donald Trump, whether they're right or wrong. And in most cases, they're going to be biased. He's not Hitler. He is Hitler. You know, there's no comparison. It's the perfect comparison. So what do they expect here? I think the all of these services are going to say, well, did you click the link that says this is an experimental service? The other possibility here is, is what you see when you do an OpenAI search, which is often Google will give you, hey, I don't comment on political stuff at this time. Right. It just doesn't even try to answer a question like that. So. Right, yeah, I don't know what people expect from it. Maybe there has to be like a big disclaimer that comes up and says, this is experimental software. You're asking a politically charged question. How would you like the AI to answer it? Because you can give this prompt to get the answer you want, or that prompt, just like you can watch MSNBC or Fox to get your version of reality. And if you want to really go far, you could, you know, go all the way to the right to Alex Jones or something, or all the way to the left with somebody else. So, yeah, this is. Is this performative? I don't know. I.

So I think it's definitely performative, but I think there's also a bit of risk to it because the fourth point from this Missouri AG says that he wants them to, quote, provide all documents and communications regarding the rationale, training, data weighting or algorithmic design that resulted in your chatbot ranking President Trump unfavorably in response to questions concerning anti Semitism. That is all the secret sauce. That is all they're. That's how they built these things and they don't want to share that. And so this AG is, I believe, fishing with an eye on some position in the White House. But this is a pretty strong statement of what some states might do. And this could create a lot of just legal drag on American AI companies. It could scare them into making more neutered models. It could make them be sycophantic to current political leadership, for example. It's just not good. And I think it really just goes against the spirit of the First Amendment, which is you can say pretty much what you want. And I think that if we hold AI models responsible for speech in this way, we're just not going to have very powerful AI models. And that to me would be such a shame at this moment of the potential for such progress. As we discussed earlier, we want to solve physics, we want to solve math, we want new chemicals, new treatments, new services, new startups. We don't want whatever the hell this is. It's just disappointing.

I'm just looking at OpenAI right now and I asked it, what evidence is there for how Trump Fields about Jewish people and the Jewish state. I mean, talk about, you know, opening a can of worms. And it says supportive actions towards Israel and Jewish communities. And it Golan Heights proclamation recognized Israel sovereignty over the Golan Heights Abraham Accords, Executive orders on anti Semitism. So these are actually. And then it mentions the Shylock remark. Use the term Shylock considered anti Semitic. Slurpee. It's kind of straight down the middle when I asked it that way. Right. So you can, based on the prompt, get it to say different things. Right. Like if you ask it just to give you evidence of Trump's anti Semitic behavior, we'd only give you that. But if you ask it just for evidence of how Trump feels about Jewish people in the Jewish state, it seems like it's just going to sources like Wikipedia, Jewish News, cbs, the Forward, pbs, and just telling you what they said. So in other words, it's what a researcher would have done for 20 bucks an hour on, you know, fiverr or something. If you said give me a summary of, with citations from notable sources of how Trump feels about Jewish people in the Jewish state. So I don't know.

Just to make this nonpartisan, though, I want to point out that the Democrats getting mad at Xai and trying to command what it should do with its Grok Twitter account is also too far over the line. What we want is people to step back, let the AI companies cook, as the kids say, and build new technologies with the hair on them and the caveats that says, you know, don't trust this, clouds in beta, et cetera, but we don't need to turn this into China, in which if you say the wrong thing about the wrong person, your company gets shut down or you run into major legal risks. If we want to win, we need to let these people play. And you know what, Jason? Screw it. One more chart from the same Source earlier about Grok4. This shows progress of the two leading countries in AI, the United States and China. And as you'll note, Xai's Grok 4 gave us a little bit more of an edge over the current leading state of the art models from China. So this is, to me, a bit of a national security point wrapped in a First Amendment ribbon.

And I wonder if this is the type of technology where there might not be some crazy breakthrough where one person wins and everybody else loses. It just might be people hit certain benchmarks and they solve a series of problems for humanity, but there's not some breakthrough where one side, China or the United States, figure something out that is so colossal and important that the other side doesn't quickly figure it out as well. If we look at self driving as an example, there's plenty of self driving cars in China. It's undoubtable that both countries and countries in between that have similar services will have a solution for self driving. It's an achievable goal. Therefore there's no winning here. It's just I don't know which person wins which month or quarter before the other person wins, you know, and it's not winning because the other person still wins. And if you were to look at something like the com, you know, internal combustion engine, well, Japan, China, the United States, Germany, everybody produces a nice engine. So is there a winner in that space? No. Who can produce a computer? Like there's computers, laptops, phones produced all over the world, chips, same thing. So I don't know that there's like a winner take all moment here. Based on the history so far, based on the history there is no person is going to win it. It's not like the person who wins gets a nuclear bomb and gets to destroy all the other players on the, in the game.

Yes.

Which. The Manhattan Project. Even in that situation where you literally did have that possibility where the winner gets to blow everybody else up, the winner didn't blow everybody else up. So here we are.

And keep in mind, the gap between the US's first test atomic explosion and the USSRS wasn't that long. That technology advantage didn't last forever. But Jason, I really feel like you're just.

That's like a really interesting question. Like even in that situation, Producer Claude.

Can you get us the gap between the US Trinity explosion and the first test explosion of the ussr? Jason, you're doing the meme though, and I just pulled it up from the Singularity subreddit. I saw this the other day. Yeah, it's a flow chart in a circle and it says GROK introduces the world's powerful model. Then OpenAI does, then deep Seek, then Gemini, then Grok. And so you're right, but this is the spinning wheel that I don't want too slow because there's so many cool companies building cool stuff and so we just need to protect that. And that's something I want to, want to keep our eye on as we talk about all this AI stuff as time goes on. All right, four years in one month. The U.S. had as an edge over the USSR in atomic pretty significant four years.

You could, you could have taken over the world in that amount of time. What was the minimum amount of time necessary once achieving that accomplishment. And having a nuclear bomb would you need in order to take over the world, a year.

Let's get producer Claude on that immediately. And if we don't like the answer, we're going to drag Dario up in front of Congress and whack him with a stick.

No, unnecessary to unnecessary to even think that one through, because it would be like you did have plenty of time to do it. Thankfully, in that situation we did. So in this one, the I guess the thought experiment would be somebody creates something so powerful that they could dominate all of humanity for some very long period of time. What would that be? Fusion energy. Maybe. Maybe some type of bioweapon. Like if you think about it as something dark like a bioweapon, or you can think about it as something very powerful in terms of economically or for the quality of life, like, I don't know, fusion. If you discovered fusion and you kept it to yourself for a couple of years and then everybody else got it, would you have some insurmountable lead? I don't think so.

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So maybe somebody in the audience can give us these ideas. Infinite energy would then accelerate the amount of energy you could put towards computing and then maybe you make the next 10 discoveries. So I guess it could be like a dominoes effect.

So there's a short story by Isaac Asimov called Alexander the God. It's not about me, shockingly enough, but it's very good. And it breaks down what might happen if someone built a computer system that was so powerful it could run the global financial markets and essentially win. And then the moral of the story, just spoiler, is that the computer eventually becomes so powerful it fuses and then there's a global panic and then everything goes back to normal. But this has been a thought experiment for a long time, and I think even in those earlier pre AI moments, we were thinking about how it might also unravel.

Perfect segue.

No one's going to win forever.

Perfect segue. Speaking of infinite money glitch and the gods, bitcoin is at an all time new high. It's kind of somewhat related, right? There's a crazy crypto project in the sky that is now at $119. This feels like a breakout point. It was always hovering right around 100k and people are wondering, you know, is that 250k moment going to arrive if it breaks to 119, that feels like some support level where it does feel like, okay, we're on the way to 200. And if it's on the way to 200, then hitting 3, 4, 5 seems also reasonable. And then that eventually becomes this magical million dollar bitcoin. But there are people who are clearing positions. Did you hear about this old wallet that was a. I did, yeah. There's a wallet that's been around since the time of satoshi, the satoshi era, and it just got cleared. So what that means is somebody sat on some billions of dollars, tens of thousands of coins, for an extremely long time. People probably thought the wallet was dormant. And here we are. Explain to the audience what this sleeping beauty bitcoin wallet is.

So if you go back in time to when bitcoin was put together, a lot of people accumulated a lot of bitcoins because they weren't worth much at the time. In fact, if you go back in time, you could get a couple for doing like a captcha. People gave them away in their signatures because they were worth a fraction of a cent, you know, and there was going to be lots of them. So who really cared about some of those wallets from that era simply have not made a transaction. So they're called silent or asleep or come. You pick whatever term you want for it, Jason. But when one of those early wallets wakes up and begins to transact or move currency around, people pay a lot of attention to it for several reasons. One, it means that the overall supply of Bitcoin may be more liquid than we thought. One reason why people are often very bullish on bitcoin's price appreciation is that people buy it and then hold. And so a lot of the big blocks of bitcoin holdings move. Well, it could imply they're going to sell and move the price and so forth. People are also curious about Satoshi's own holdings and so forth. But just seeing a wallet wake up after 10, 15 years is, is a, it shakes the foundation of how people think about Bitcoin. Now, in this case, hasn't changed the price in a negative way. In fact, as you just said, we hit a new high. But I'm curious to see if more of these wallets will wake up, because if I had $2 billion sitting in bitcoin and I don't, I would probably buy a boat.

Just saying, what is the thesis here or the, the theory of who this person is and what happened? Did they have enough money so they were a tech executive, let's say, who got into this early, and they were already worth tens of millions of dollars and they had this wallet, or maybe they had that wallet plus some other ones. Those other ones they were living off of, they sold along the way. But what else could explain somebody having billions of dollars in bitcoin and previously hundreds of millions, and before that tens of millions and before that millions, and just being able to sit on it and do nothing? Were they getting a margin loan against it this whole time and living off of a loan against it? Could that be possible without the. And the wallet wouldn't have needed. They could have just given Custodia the, the custodian. Somebody else could be the custodial of that wallet, I guess would be the way to say it and. Or given ownership of it, and now they've decided to liquidate it. Did the person lose the password for 12 years and find a thumb drive with it on it and then say, oh, I forgot I bought these and they opened up their account and it was there. It's just a very weird story to have come out of nowhere.

The, the latest that I've seen on this, and I have not actually gone and verified this to the nth degree, so I'm spitballing here with my friend Jason. Don't take this all the way to church. And. But I did see some reporting that there is new scams and exploits being aimed at very early bitcoin wallets. And I'm curious if this may have got caught up in that because I don't see a particular reason why it would start to move at 118 vs 57 vs 32 vs 11.

So somebody was able to hack it in some way. Interesting.

Worrisome.

Yeah, that would be worrisome. Anyway, Coinbase, Robinhood, it seems like everything just six months into this new administration, right. They started on January 20th and it's July 11th, so we're almost at the six month mark here. Crypto has been so given the green light, green flags in order for people to do things like stable coins, meme coins that Robinhood and Coinbase have just gone on a run. Stablecoins. With Circle going public, this is quite a time for Fintech too.

Yeah, absolutely. And we're seeing venture capitalists respond to this. So if you're listening to the show today and you're building in the Web3 space, we have some good news for you. According to crypto rank, in the first quarter of this year, crypto venture investments just cracked the $10 billion mark. That was up 263% from the year ago quarter. And in the first quarter of this year, Jason, 7.45 billion. That was up 136% year over year. So if you take a look at the historical chart here of investments into the crypto space, you'll note that there's quite a lot of large bars to the right, which means that people are putting more capital to play. Now, the number of rounds isn't actually that exciting. It seems to be relatively trending lower. But the amount of money flowing into crypto companies is, is popping off. And so if you got stuck in the winter and are now looking to raise again, well, this is a pretty warm time. The real question, though, Jason, for you is are you going to start now backing crypto companies? Because when I joined the show, you were a little skeptical.

I mean, for good reason. If you looked at the companies, you could wind up very quickly getting into a lawsuit, being sued, you know, being, you know, and not just being sued by anybody. Maybe the SEC decides to sue you. This was a really dangerous place to be investing capital. And that fall off there for July, that's a obviously a partial month. So that might only be a week. And that would probably explain that Drop off. If you look at June, $5 billion raised, that's a big number. I wonder if that includes circles. IPO would think it does so and then the other 5 billion, I wonder if that's another crypto public company as well or if this is all just venture dollars into those companies.

This is all venture dollars as it was described by Crypto Rank. But you know, everyone counts slightly different than Jason. So I don't want to be overly prescriptive but my, my read was this is just venture so it would not include the circle around.

Yeah. And these rounds are also very strange. Like These could include ICOs and people selling coins and then getting back other coins. So I don't know if this is all venture capitalists putting money in, but let's put that aside for a second. I think you could feel pretty good going to an attorney and saying if I'm going to do this stablecoin thing, if I'm going to do this, will I be sued? And they would say a lot less chance than under Biden. So if the president can launch a meme coin, I think you can too. And I think that's kind of where these, well, I mean let's call it what it is. You know, they've said meme coins NFTs, these are collectibles, if you want to buy collectibles and they trade with the ticker symbol on, you know, trading accounts on Robinhood where I bought my Trump coin and have lost 70% and I did it as a joke obviously. But you know, you, this is now the rules of the road. And I think it was previously if you do something that's innovative or new, you're going to get caught. And it's just a matter of how big the settlement is and if you can survive. Well, we can see XRP as an example of that. They were able to survive. They had enough money, enough cash that they were able to fight that lawsuit until Trump came into office. And XRP was I think is largely off the hook. Now I don't know the exact state of all their cases, but I believe they won one case. They weren't able to prove that they were doing solicitation of non accredited investors because those things were trading on marketplaces not being sold directly by xrp. So they wasn't that they weren't selling to consumers. It was, it couldn't be proven that they were selling to consumers. Putting all that aside, I think now people are you're in the clear is probably how most people feel to experiment. Does it mean commit crimes? Does it mean abscond with the money like we saw with ico? So I think we'll see a lot of innovation. I've always liked fintech. We were involved in Robinhood and Wealthfront. I think fintech's a great space, you know, and adjacent to fintech is crypto. Sometimes they overlap, sometimes they don't. But now with crypto regulations being out there, I think you're allowed to dream again. Hey, what could the world look like if you could tokenize shares of a private company like Robinhood did with open air shares? Like, okay, it seems like there's enough legal consensus that you can experiment against. So here we are, folks. Great time to give it a shot and invest. And everybody's got to take as investors and as founders, you got to take your. You got to define your own level of risk. And when you talk to attorneys, they will almost universally tell you, like, we can't give you a legal opinion on this. It's too new in these kind of areas. And so then they rely on what's happened to other companies and other cases out there. Well, if all the other cases are being folded and settled, okay, yeah, they can tell you we don't have exact law or, hey, the stablecoin laws are in process. This is where we think they wind up. Here's what Circle did. They're in the clear. And then if you wanted to innovate beyond what Circle's doing and maybe get closer to tether and offshore marketplaces for crypto, et cetera, and exchanges. Yeah, then you're going to be taking more risk. And jurisdiction is the other piece that really matters here. If you're doing stuff in Panama and Malaysia and Singapore and Dubai, like Zerg, different places have different rules. The United States is catching up to those.

Yeah, but catching up by having fewer, I think, is maybe the right way to say that. Kind of a race to a more relaxed market for entrepreneurs. And that's why when I see companies like Agora raising for its, you know, stablecoin product, well, it kind of just tracks with how you and I view the world and what we see coming. People want stable coins. They want to be able to trade. Okay, well, off we go. Now, before we get to our guest, Jason, a couple of small things. One, Grok Gro Q. Not Grok, the AI model. This is the inference provider. Of course, I believe Sonny from shows. Yeah, yeah, He's. He's. Now, he's part of the Grok family. Right.

He sold his company to Grok and He is responsible for all the developer relations, which I think is like developers.croc.com GROQ as opposed to GR. Okay, which is Elon's Grok. These folks make inference chips and they've done a ton of different deals and they're raising more money, it seems.

Yeah, yeah. So according to reporting, they're going to raise between 300 and $500 million at a $6 billion valuation. For context, their last round, Jason, 640 at a 2.8, so a more than doubling of their value. Why? Well, they signed a big deal with Saudi Arabia and I believe it was the humane project, their AI kind of G42 competitor. They also announced an expansion into Europe. And perhaps most importantly, the information reports that they grew their revenue from 90 million last year to an expected 500 million this year. So 6,512,X makes a lot of sense to me. I don't know their margins, I don't know how repeatable the revenue is. We can't say it's an ARR multiple, but 12x does not seem nuts for that level of growth. And I just love to see companies that are not just Nvidia, but are building chips for the future do well. Because back to our point about AI models, steel, sharpened steel, and we want to see a lot of companies pushing ahead here with new ideas and so forth. And Grok makes LPUs, not GPUs. Those are language processing units as opposed to graphical processing units. So I'm really excited about this. I'm keeping tabs on Grox. I think it's a really cool company and I just hope that they do really well and make sure that Jensen stays up at night.

Yeah, I am a shareholder and they. Of course, I was a shareholder in Sunny's company which got bought. So I have some modest exposure here. So apparently this is good for me.

Never mind. And I hope Grok crashes into a wall. And I hope. No, I'm just kidding.

No. So far, so good. You know, the inference chips are different architecture than say when you're building your language model and you have to compile it essentially. So there is going to be an infinite, it seems or in the medium term, an infinite appetite for this as consumers stop doing jobs and businesses stop doing jobs inside of apps or SaaS software. And they start with a language model. And when you start with a language model and you need a context window and you've got a. You want to throw a video in there and say, tell me about this video. Or a book. Or a book And a video or you want to index your entire hard drive and you know, make that the context window. Like it's going to be pretty crazy. I don't know when we get to the point at which this becomes like storage and people are like, I don't know how much storage I have or need because every three or four years like they keep giving me the ability to record in 4K, 8K, whatever, you know, and doesn't make the videos any better. And the storage keeps going down as our phones and the quality of the video goes up. So even as we make bigger and bigger files, it doesn't seem like the storage business is a great one to be in. At some point, 10 years from now, 20 years from now, we'll be looking at these, this kind of infrastructure in that way, I'm sure. But that's not going to be for another 10 or 20 years. It took, gosh, I'm trying to think about how long we sweated storage on computers for consumers or businesses. And I would say for consumers it ended sometime 20 years ago. Well, you really didn't have to think about it, right? Like you weren't buying your computer and saying how much storage does it have? Because you had cloud become available and cloud was easily expandable. So that was 15, 20 years ago, 2005 time period RAM and processing power of chips. Gosh, I think that stopped maybe 10 or 15 years ago where people don't even look at how much RAM they have on their computer. Unless you're doing video editing or video games.

No.

Or, or you're a tab hoarder in Chrome. Because Chrome, Chrome's. I mean, you're right. Apart from Chrome.

Yeah, but you don't need to have that many tabs open. That's like a choice. That's like a crazy, that's like, I don't know, I'm going to make a 2 hour 8k video on my. Or 4. I don't know if my phone can do a K, does 4K for short. I'm going to make like a 60 frame per second 4K video of like a flower growing. Like you don't need to make that. You can make a short 30 second video. It's the same thing. It doesn't change. You're choosing to open infinite tabs and then complaining when you run out of memory. It's stupid. It's like it's unnecessary. Just close your tab. In fact, people like you are now causing these browser companies to add features where they turn off and they shadow turn off. Your tabs, like, you know, that's what's happening now. They, like, actually turn them off. Well, you can also close your windows. Why do you keep all these tabs open? I don't get it.

Well, I mean, just for this show, I have about 15 articles pulled up for various contextual points that I might need to reference.

15 is fine, but you're.

Did I have another entire. Sorry.

Good. I'm sure you're. You're. We all know 15 is okay, but I think you've got 50 tabs open right now.

Oh, yeah. Then I have a separate Chrome instance that is all my screen shares prepped for the show. And then in my third Chrome window and then on my other screen. I mean, we pull together a lot of stuff for this show, and so I just. I use a lot of tabs and. Wait, how do we end up here? Oh, ram. Right. Let's get back on top of that.

Like, June, could you possibly need more than 16 gigabytes of RAM on a laptop if you're not doing video editing? I think the answer is no. And I have now stopped even. I literally get the lowest amount of storage because everything's in the cloud. So I don't think about storage anymore. I don't think about the cp, the gpu, or the CPU anymore because they're all off the charts in Mac. And on PC, there's no game or something I'm playing that needs that. And then even video editors, they used to come back to me every year and say, oh, you know, can I get an upgraded computer now? They'll have computers that are two or three years old. And they're like, yeah, it works fine. Works fine. I'm like, should we get the new one? It seems like it's faster. It's like, yeah, it's 20 faster. We don't need it. So that's going to be interesting to see if that happens with AI clusters. And then you think about, like, Colossus that Elon built. That really, I think, is a big part of why Grok hit these things is that they have this giant cluster. How long are those GPUs good for? You put up 100,000 of them. You can use them for three, four, or five years. What's the lifespan of those is.

Microsoft recently changed the accounting of its depreciation, Jason pushing it out by one more year. I think it was four to five. From four to five. Okay, so call it a half decade.

Okay, five years. So you spend all of that money, billions of dollars. Hundred thousand. You Know, per GPU or server, I guess, you know, like, like and then it's gone in five years and then what do you do? What are we going to do with all these colossus, you know, data centers? Do they stay online? Do they have some afterlife purpose? Or do you. They're not worth running anymore because the new ones are so much more energy efficient that we just turn them off or can they be used for something else? I think it's like actually if we're going to build out this much infrastructure, people should be asking these questions. If somebody. Let's put this on the docket for Monday. I would like to get the answer to this one is what happens if these things do have a 5 year life? What is the post 5 year plan? What is the plan for year 6 to 10? Do they get turned off because the energy consumption makes them not worth using? Do they get resold? Is there somebody who needs to use them? In a world where AI has solved all those problems, then you don't need these chips anymore. The problem has been solved. It's been baked into an LLM. I'm just really wonder what happens to all these. I wonder if Nvidia has like a recycling program because with Facebook, what. How long does Facebook keep their servers on? You know, in that open cloud, had that open computing standard they created. I wonder how long they depreciate theirs for before the energy consumption of them in ratio to what they're capable of doing becomes untenable and you're just better off turning them off. And then if you turn them off, is it worth taking them out of the rack for the real estate? Or do you just leave them in the rack and then just build more racks behind them in a giant data center and just turn them off because the real estate cost is less than the cost of dragging them out of there. Depending on where you are. I have, I have a lot of.

Questions about all this so we'll talk about it more. But just a couple of quick data points. According to a number of sources here, when you do run these GPUs in a data center at like max capacity for a while, they do degrade. So they do actually have a life expectancy to them. Now the major companies have pushed out their depreciation.

They break like or they are like a battery on a Tesla or an EV that they degrade and they can capable of 60 or 80%. I wonder what they mean by degrade, like actually break or they perform at a lower ability.

Well, according to training data from Meta's Llama 3. There's actually a 9% annual failure rate of GPUs used for training information. So again, we'll do more research here, but that's one thing.

Wow, okay, that's, that's a lot. So that means every 10 year of every 11 years they have all failed. Oh, wow, that's interesting.

That's brutal. But I think the real question is how fast does Nvidia push the envelope out? Because every year if they have a faster chip out that's much better, I think that makes yesterday, last year's chip depreciate faster. So if Nvidia runs into a problem that it can't expand capacity or performance faster, then I think these last longer. But if Nvidia does better, they get shorter lifespan. So we'll talk more about that on, on Monday. I'll do some research and talk to some people.

Yeah, and the other piece of research is I wonder what it costs to stay, to ship them and to rack them and to unrack them.

Now we have, we have a guest, Jason. So I'm going to go ahead and move our click to cancel work until Monday. There's a lot of interesting stuff there, but it's just going to take too long to get us through. So I think it's time for a quick commercial break while we get our friend into his chair. So Claude is not just writing show notes for us anymore. It's gotten a lot better. It's actually analyzing guest applications, it's helping us drop interview questions based on founders specific background, what they're doing and it actually helps us generate research in real time as we do the show. And that's why Claude is perfect for startup founders. It is intelligent, it is quick and it will help you no matter what you are doing. Now if you do create a lot of code, of course Claude Code is an excellent pair programmer for you. It can help you out even I believe in your terminal as well. So no matter what you're building, well, Cloud probably has a solution to it. And if you need to bring your own data into the context, well, don't forget to there is Model Context Protocol or MCP from Anthropic, the makers of claude. And what that will do is ensure that your private data, your proprietary data, the stuff that you need to become great in the world of AI, is available to your favorite AI model. And that's why we have partnered with Anthropic to give Twist listeners 50% off Claude Pro for three months. If you go to Claude AI/Twist. We know if you're bootstrapping out there, every dollar counts. So let us save you a couple of them. That's Claude. AI Slash twist.

All right, next up on the program we have a founder. I'm a second time investor in Ben's company, his first company, Neighborly. Such a great idea during COVID and it wound up shutting down. We'll get into that. But you have a new company and it's Ben Seidel. I'm pronouncing your name correct, you are Seidl. And the new company, you came to me and you pitched me this idea. I said that sounds crazy. There's many more questions than answers for this one. I'm in. So let's talk a little bit about what you're building with Auto Lane.

Yeah. So with Auto Lane, we're building the connective tissue between autonomous vehicles and businesses. So it's essentially an operating system that allows high volume retailers, shopping centers, think of like a Whole Foods or a Costco or a shopping center like the Domain here in Austin to be able to connect, coordinate and control autonomous vehicles on the property.

Got it. So I have something like the Domain, which is an outdoor mall here in North Austin. It's pretty impressive when you see it. It's like you can live there and there's an Apple store of tons of restaurants. They want to get deliveries there. It's going to be automated. Obviously there'll be self driving cars. We got self driving cars all over Austin. For whatever reason, this has become ground zero, it seems. But there needs to be some connective tissue. When you're in la, there are those street, what do they call those little robots on the street?

Oh, the sidewalk bots.

The sidewalk bots. We are seeing Zipline in Dallas doing drone delivery. But the big opportunity in your mind is a self driving Tesla, a Waymo, a Volkswagen id, Buzz, Zoox. A Zoox is going to show up at the Domain. And somehow at the Domain a retailer is going to take a burrito or you know, a pair of sneakers and put them into a self driving car that's going to come to my ranch out in hill country and give me what I want. Yeah. So which piece of the puzzle are you going to take care of? Or is that all? The point of this startup is to figure out what needs to get done. Yeah.

So we came up with the idea essentially if you look at the components that you would need in order to make that type of a transaction possible, of course you need a self driving car, you need that Technology to be flawless. And I think we're pretty close to that. So I kind of envisioned, well, fast forward a few more years and let's say most OEMs are either licensing or shipping some type of personally owned autonomous vehicle. Toyota, gm, Ford, you'll have a bunch of these companies shipping these types of cars. And if most of us have access to this technology, don't these cars essentially become physical AI agents? These become your kind of like butler, right?

Yeah. So in that model, I have the car, I have a model Y, hardware, four pretty incredible. Not perfect yet, but getting there pretty close. Right. I think I would say two out of three drives I do is flawless. One out of three, I can have a that was sub optimal moment or oh my God moment to be totally candid, like when it gets near construction, that seems to be for these cars, really challenging. But I might send my car to the domain and say, hey, my car is there. What now? Yep.

And that's, and that's. So that's what we are building. So we. Most of the, I would say autonomous driving technology has been applied to ride hailing thus far. So of course Waymo has been operating in public for years with almost no significant incidents.

So I don't think there's been any, nobody's gotten hurt, nothing.

And so you know, they've, they've now have more market share than Lyft does in San Francisco and, and still growing. So I think that San Francisco, if you were to look at the market share for ride hailing, you could pretty much assume that what you're seeing in San Francisco is going to continue to expand and duplicate across the country over time. Now, it won't be an overnight situation, but of course AV ride hailing is here. And if that's any indication of where the general market is going for TNCs and aggregators, you should expect that delivery will also go that direction over time. And so what we've been building at Autolane is essentially the connective tissue to say if that is to take place, the vehicles are here, the AI driving systems are here, the regulations are coming, consumer adoption is happening. But if you've taken a Waymo or you've used FSD to go to a business, you'll quickly notice that one of the hardest parts and kind of least developed parts of the technology is the pickup and drop off experience.

Yes.

And because of that, and that is like what we call the last 50ft, because that is the part that is really unrefined at this moment. That's where we are focused on at Auto Lane is to build the software and hardware to basically enable physical and digital infrastructure to make that final 50ft polished and flawless. And then if that can take place, then all of a sudden you have the ability for these cars to conduct commerce. And that's where we think that the next wave of commerce is going. I really believe that we're going to see something akin to the transition we saw with E commerce. We're going to see something that I would coin autonomous commerce.

It makes sense to me because there are places I've wanted to go here in Austin. There's like a, a Sando shop, you know, Japanese sandwiches. And I have wanted to go to this place in North Austin, but I live in South Austin in the hill country and I just haven't had a chance to go up there and there's traffic, et cetera. Now if I could, I would have ordered from this place every week some sushi or a nice katsu curry or a, you know, wagyu sandwich on that great Japanese bread. Yum yum. It would have been very easy for me to just say, I order it, my car will be there. Just put it in the front trunk with an ice pack and yeah, my car comes back here to Capital Factory where I have our studio, and I jump back in my car and go home. That's right. It could have done that errand for me already and two or three other ones. Yep. But there is so much logistics in what I just described.

That's right.

Which is why I was really excited to invest in the company.

And thank you for that.

Oh, well, of course. I mean, the, the, the greatest success we've had is when we've known a founder for two or three startups. And your first startup was amazing. I still think it's one of the greatest ideas I've ever heard and I still think it will work. But I'm glad you went on to this one because this one feels like it's even bigger. And that's typically what happens with founders. They have some amount of success with scar tissue in the first one and the second one, then they're just like, oh yeah, I'm not going to make those mistakes. I'm not going to overspend on this. I'm not going to under invest in that and they just boom, boom, boom. So we just love second, third time founders here. Especially if the first company or second company was a complete disaster, blew up, or was like a modest success, because those things kind of set you up. You still have the Chip on your shoulder. We'll get to that in a second. So also, this is going to be super fragmented, is your best guess. Oh yeah, super fragmented. So explain the fragmentation and then what you perceive a retailer, what set of problems is the retailer going to have due to that fragmentation?

Great question. So, so yeah, one of the easiest ways to think through how this industry could play out from a solution standpoint. So let's, let's take Walmart for example. Okay, so if you agree with me that personally owned autonomous vehicles, or autonomous vehicles in general as a technology are going to scale over the next five to 10 years. If we agree on that, everybody agrees. Okay, well then I guess you would also need to agree that those cars are going to go to Walmarts. Yes, they already are. Yeah, Waymos are dropping people off, picking people up from those stores. There isn't commerce taking place with Walmart directly yet via those vehicles. But of course there will be. And so one of the major aspects of this conversation that, that I think is important to consider is whether or not, because the industry is a bit divided on this topic, but whether or not you believe in personally owned autonomous vehicles being a significant market share within the autonomous vehicle industry. Some people believe, oh, the technology is going to scale and the costs are going to come down to a point where OEMs will operate their own robotaxi networks and people just won't own cars.

And people will choose not to own a car.

I think there's a lot of people who believe that side of the spectrum of the, of the industry where essentially you won't need a car at all. And these, the services, both ride hailing and delivery will be so cheap that really won't be a need to have a car. So maybe, maybe that becomes people, I.

Can see it for people who live in an urban environment and don't have access to a garage.

People have said that about Uber, you know, since the early days, and it remains to be seen whether that played.

Out the way full Uber, I would say, is like 5% of the population. Exactly.

I don't think it's.

Maybe it goes to 10.

Totally. And so I think we believe a similar situation is going to arise here with autonomous. And actually it's not in my opinion the case that we just won't own cars. It's that actually the cars that we do own are going to be able to do a multitude of things for us and they're going to be much more valuable and we'll need less of them. But I do think most People will own a personally owned autonomous vehicle in their driveway and it can do errands for them, it can pick up their kids from school, it can drop them off at the airport and drive home, can do all types of things. And so we might, instead of having two or three cars as an average American household, we might just have one or down to one and a half.

Because when I get dropped off here at work, I could send my car. That's right, to go pick up the kids from camp the car. Then they could also make their way to, I don't know, back to the ranch to run some errands for the housekeeper and get some chicken feed or something.

So we really think that personally owned autonomous vehicles is going to be the future of transportation. And if that's the case, and you go back to kind of your question about Walmart and their fragmentation. So if most people have access to this technology, whether you own the car or not, or whether it's your neighbors or your friends and you order something from Walmart, groceries, retail, what have you, well that car is going to be able to go to Walmart. Now if that's a Toyota or a Tesla or that's going through Doordash or that's going through Uber Eats or that's any, that's a drone. I mean you're talking about not just cars but all types of robotics here that are going to do consumer transactions. And so those vehicles are going to Walmart to do commerce on behalf of a consumer. Imagine being Walmart in this case. Yes, it is a complete nightmare that is about to unfold on their hands.

Because in their parking lot there'll be 10 times as many cars showing up.

That plus there will be 15 to 20 OEMs. And each one of these OEMs have a different hardware, software and data stack.

Right. That's not one type of vehicle they have to already design their parking lots for. For a number of vehicles. You could have you know, trailers showing up in the back to unload. You could have, you know, SUVs. You know. So right now a parking lot has compact car spots, spots for the trucks, spots for SUVs and larger ones and maybe a pickup, a drop off zone. They've got maybe arguably and curbside pickup. And curbside pickup. So they got maybe five areas right now. Now you need another area where my self driving model. Yes, or your self driving Toyota. Because Waymo just said they're gonna license Waymo's self driving to Toyotas. Like you saw that announcement. I'm sure you're on Hyundai.

Hyundai as well.

Yeah, on Hyundai. They're doing it Waymo.

They've got a partnership with Hyundai.

Wow. So all those cars are going to have self driving. They're gonna show up in a parking lot. What parking space do they go to? Yep. Do they go to the pickup zone? Do they go to any spot in the pickup zone? How do you know the car's there? How do you know where to put the stuff? Is it go in the backseat? The trunk, the frunk.

How do you, how do you unlock the trunk?

You got to unlock the car.

How do you know which VIN it is? How do you know which customer is associated with which car? How do you know which stall that car is in? How do you know which order? If you have three orders at Walmart and my car goes, well, which order is it? There's. There's basically what I call the three C's of AV orchestration that Walmart or any major retailer is going to need to solve. One being communication. So this is Jason's model Y. It's coming to pick up order number one, two, three. It'll be here in 16 minutes, license plate, blah blah blah. And it'll be install two. Okay. All that information needs to be communicated. The second part of it is coordination. Making sure that that car is going to go where Walmart wants it to go. Because the curbside pickup operation across 4,500 stores operating 16 hours a day is a very expensive labor line item on their.

Yeah.

So when they can shave off 15, 30, 45 seconds from a pickup and drop off curbside arrangement, then they are operating more profitably and then they can knock the prices down on their retail good. Which is the entire Walmart business model. Right. Like operate more efficiently, reduce the prices for consumers and sell more goods. And so they, they are obsessed with finding ways in which to do these types of things more efficiently. And so are, so is McDonald's, so is Chick Fil a down the line H e b. And so really what you end up with on those three Cs is you've got the communication, you've got the coordination. The car needs to go right here so we can be faster. And then the last part of it is control. Now you don't need to tell the car how to drive to Walmart, but you do when it gets to your private property. You do need to say, okay, well I need to be able to unlock this car, unlock the frunk or unlock the trunk.

Yeah.

And if you have 20 OEMs shipping different types of autonomous vehicles. Your Walmart, you're going to have to have an integration with every single OEM. And those OEM integrations, they don't, they're not stable for five years. Tesla's APIs change every two weeks. I know that because we have integrations with Tesla. So you're going to have 20 OEMs that are changing their code base every two weeks. That's an entire in house team that you're going to have to have.

And Walmart with cars potentially could build this software maybe, but they're one of the few who could actually create this. And then sure, Toyota, Hyundai would have no choice but to interface with Walmart.

That's right.

But after Walmart that drops off pretty quick does. Yeah, like even H E B is a local retailer.

That's right.

They're not across the entire United States.

That's right.

Starbucks, yeah, they might be able to figure this interface out with their drive thru. Maybe. But still, you know, with all these different players showing up, I could see a world in which 10 years from now there would be more autonomous vehicles in a drive through in a Walmart parking lot than actual human customers. All right everybody, this has been go check out auto lane. Is it Autolane.com GoAutolane.com GoAutolANE.com and we'll see you all next time on this week in startups. Bye bye.