Economics of OpenAI, Tesla’s Robotics Pivot, Hedonic Treadmill — With Slate Money

0:00The business of OpenAI gets weird. Tesla now wants to be a robotics company as its stock price drops. Plus, when is it time to get off the hedonic treadmill? All that and more coming up with the cast of Slate Money right after this.

0:42podcasts. Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. We have such a fun show today, one I've been looking forward to, the cast of the Slate Money Podcast. It's here to talk about a series of fun stories where tech, economics, and finance meet. We're going to do a home-and-home series, so they're here, and then I'll come over to their show in a couple of weeks, and I'm pumped for that. And so let's kick it off. I just want to welcome the cast here. Felix Salmon is here. He's the chief financial correspondent at Axios. Felix, welcome.

1:13Thank you very much. Emily Peck is also here. She's the markets correspondent at Axios. Emily, welcome. Hello. Hello. I'm excited to be described as the member of a cast because now I feel like I play myself on Slate Money. So that's spinning my head. Last but not least, Elizabeth Spires here. She's a contributing writer for the New York Times opinion section and she writes Slate's pay dirt. Elizabeth, welcome. Thanks for having us. Thanks for coming in. I think that the combination of economics and tech is very fascinating right now because we have this very weird situation where companies and investors keep plowing money into these AI startups.

1:50And we're not really sure what the return is going to be, what they're actually using that money for, what the business outcome. But yet we start to hear numbers like trillions of dollars of investment. Really, that's what we're hearing now. that that was sam altman with one of the craziest numbers i think i i think i might have called it deranged on axios um that i've ever heard he he sort of came out and said um well he didn't quite come out and say he was come out he he was reported to have said that he was looking to raise seven trillion dollars to build a whole new infrastructure around ai which is so far beyond any amount of investment that has ever been put into anything ever, that it kind of makes you think that maybe he just doesn't understand numbers?

2:37Well, it's also double the most valuable company in the world. And that's sort of what makes this conversation he had on 20VC with Harry Stebbings really interesting. And sort of we can riff on it because we are trying to find out what the economics of this AI business is. And so here's what Stebbings says. He goes, in terms of marginal cost versus marginal revenue? How do we think about when marginal revenue exceeds marginal cost? Basically, like, are you going to have a profitable business? And Sam goes, I mean, truly, I think of all the things we could talk about, that is the most boring. No offense, that's the most boring question I can imagine.

3:13Stephan goes, why is that boring? And Sam goes, well, you have to believe that the price of compute will continue to fall on the value of AI as the models get better and better will go up and up. And the equation works out really easily. So that's Altman's view. I want to know what his equation is because he does seem to talk about all of this as if the numbers don't really matter. You're just putting in one bigger number and there's a smaller one for the input. And for you, where's the line between techno-optimism and techno-naivete? So the argument he's making is, he's making two different arguments and both of them make sense but i feel like he can't make both at the same time um the first argument he's making and this is the same argument that jensen huang has been making from nvidia which is the price of compute has been coming down for decades and has now reached the point at which ai is possible and there is no indication that it's going to stop coming down and so long as it keeps on going down at the same um rate that it has been coming down which is more or less Moore's law um you don't need to worry about the long-term price of compute because it's going to go to zero very quickly and then all you need to worry about is do I get any revenues and if the revenues are going up and then at some point those lines cross and you become a very profitable company um that's a perfectly reasonable position to hold and then however at the same time Sam Altman has this other position which is basically in order for the price to come of compute to come down to a level where AI is profitable we need seven trillion dollars of investment and that is objectively something that is never going to happen there just isn't seven trillion dollars of freely available cash in the world to invest in anything and if there was it would not be going into AI mostly.

5:09So that kind of his own rhetoric is undercutting his own rhetoric there. Can I inject some nuance here, which is that the$7 trillion is a number that Sam hasn't fully confirmed yet. And it's also something that will be for compute and potentially other things, maybe training. But I think the core of your argument is totally right, which is that this stuff is going to cost a ton of money to train. And it does sort of contradict this idea that the idea of that the cost of computing is going to come down. It has already cost a ton of money. And every if you look at right now, you know, how much it costs to perform a single chat GPT for chat GPT to give a single answer to a single question, how much it costs for mid journey to produce a single image.

5:57It's a huge amount of money. And all of these companies are losing money on every, you know, response, basically. And this is a reprise of the famous blitzscaling model, you know. And Tim O 'Reilly has a great column in the information about this. He's basically, what is going on right now is you have a handful of companies led by OpenAI who are trying to invest as much money as they can as early as possible in order to gain market share and ip and get the get the ai you know basically own the ais to and have and reach a point where no one else can afford to build one and or they own it in a way that you know they have patents on it or something it's very unclear but they want to monopolize ai going forwards and all of these incredibly high value with these multi-billion dollar valuations that we're seeing only make sense in a world where the companies have some kind of comparative advantage have some kind of monopoly on something and this is definitely the way the u.s tech industry has evolved over the course of this century right that is that you have a small handful of multi-trillion dollar tech companies that got that way by investing a huge amount of money and getting a bunch of market share before anyone else and then creating that kind of moat and becoming you know basically impossible to compete with and the bet that the investors are making is the same thing is going to happen and there's just going to be a handful of ai companies rather than AI being a sort of broad public utility, like say TCP IP, that everyone can use.

7:48Yeah, that also just creates an incentive for any tech CEO that's following that model to kind of stick a finger in the air in terms of determining how much capital they need and picking the biggest number possible, which seems to be part of what Altman's doing. But the difference here to the last time around, the building of the big tech monopolies, which seems to be how we ended up, is that the cost of entry into the AI space for a startup is so high that you already have monopolies. OpenAI is already pretty much a monopoly on AI. I mean, and it's mostly funded right by a big tech company. It doesn't seem like there's a lot of innovation around the startup space because of the cost to entry is so high.

8:29Well, we have one genuine monopoly in AI, which is NVIDIA, right? everyone everyone in the ai space is using the same h100 chip and one of the one of the reasons why zamilton wants a much bigger broader ecosystem is that he feels that it is unhealthy for nvidia to be the only company making ai chips and so it's like i want to build fabs like okay one fabs do not cost seven trillion dollars they cost like 50 billion dollars but two like even raising 50 billion dollars to build a fab is very hard given that you know a large number of companies have tried to build you know state-of-the-art fabs and have failed really only tsmc has shown itself capable of building those those fabs right and so there's that and it's that like nvidia tsmc duopoly that is that really owns most of the sort of moat around here if sam altman's right and the cost of the compute does come down there's also the other side of the scale right and we the revenue piece and are we at the point yet alex you follow this more closely that there's like a lot of money to be made in ai for real like i know nvidia is making a lot of money because it's selling chips to companies who hope that they can make a lot of money from ai but has anyone done anything where it's like that's the iphone of ai or whatever like certainly there's no consumer facing ai product that is making any revenue but like you're right in that kind of middle there's like um who was it i can't remember it was some big consultancy company um you know accenture or something said that they just made six billion dollars on ai consulting you know everyone is still like derivative stuff it's all derivative like it is very very hard that one of the things that we have seen in what is it alex like a year and a half since chat gpt came out and caused all of the crazy, is that there is very little real consumer demand from normal human beings who want to pay cash for this.

10:31The one last thing I think could be a moneymaker down the line is the labor cost savings. Jeffrey Katzenberg had some quote in Axios today, I think Dan Promek had it, where he said, with AI, the timeline for making a movie is basically cut in half. half, the amount of labor you need is cut in half. That seems like amazing amounts of money, but it's not sexy like some kind of consumer thing. So I do want to push back on the idea that OpenAI is a monopoly in this because you do have other companies, and this is going to lead into your other question, but you do have other companies building these frontier models, whether that are foundational models, whether that's Meta with Lambda 3 and Anthropic with Claude, like Claude recently surpassed OpenAI for a moment.

11:14And then this is where the interesting question about the economics happens for me, which is that, you know, if all these models become commodified, like you're going to have Meta's Llama 3 available for free, open source, then where's the actual value created? And does it actually accrue to the model creators or to the people that build on top? And I strongly believe that it's going to be accruing to the companies that build on top of these models. Whether that is a consumer product or business, this is like labor saving and these business efficiencies, the companies that use them innovatively are the ones that will actually make the money here.

11:51And that sort of goes to Meta's bet that's like, let's just give this away for free. It's not going to be worth really anything. And maybe that's going to Sam's point that the cost of intelligence is going to be low. But then you have a real ROI question. Yeah, no, this is exactly correct. I think emily's point is very well taken or jeffrey kassenberg's point is very well taken that you know one way to make lots of money out of a technology is to take the technology in charge for it another way to make lots of money out of the technology is to take a technology and use it to cut your costs and that does seem to be something that people are already doing with some genuine profitable effect and businesses are doing and is going to become much more common over the next few years.

12:37And that is going to be good for the economy. And that is going to be good for all of the companies that do it. And on some level, you know, if the cost savings are high enough, then the companies will be willing to pay some non-trivial amount of money for the AI that they're using on the other hand if the cost savings are kind of the same no matter which ai you use and you know some of the ai is open source and or you can just build your own with open source tools um then they'll probably go that way and there won't be a lot of direct revenues to the ai companies and so ai will be this force for productivity and profitability in the economy and the AI companies themselves, you know, OpenAI, Anthropic, and the rest of them will turn out to be not particularly valuable.

13:29And this, by the way, is an outcome that OpenAI has always envisaged, right? Like in the early days when they were asking for funding, they said, we would like you to consider your, you know, funding to be in the spirit of a donation. And they're still a nonprofit. and if that is the outcome that open ai winds up just making everyone else profitable without being profitable itself that is a good outcome for the economy and that is a good outcome for the world well another factor here that i think i'm not sure if altman has spoken directly to this is that you know you don't have infinite data and the cost of data acquisition has not as it certainly isn't following the way that cost of computing is falling you know right now you have AI companies looking at buying traditional book publishers just so that they can add to the corpus of things that they're training the models on.

14:22So the inherent value of the business isn't just about the algorithmic model. It's about what you can do with it within the limitations of the data you have to train it on. Are we thinking too small here? That's like the other question that's coming up. Because there's another thing that Sam Altman said last week that went even more viral than the thing that I mentioned. And whether we burn 500 million a year or 5 billion or 50 billion a year, I don't care. I genuinely don't. As long as we can, I think, stay on a trajectory where eventually we create way more value for society than that. And as long as we can figure out a way to pay the bills, like we're making AGI.

15:00It's going to be expensive. It's totally worth it. So, yeah, I mean, it is, it is, it really is. I hate to say this, but it kind of smells a little bit like Sam Bankman Freed, you know? Like, not saying that he's a, but that kind of, like, it doesn't matter how much it costs, just as long as you have, like, a positive EV somewhere down the road. um that idea of um you can lose any amount of money just so long as the value of your company is rising faster than the losses are piling up is a very dangerous game to play if you don't really have a sort of let's call it three to four year plan for turning it into profits like sam's idea here seems to be like well maybe at some point 10 years down the line we will have agi and then we will make lots of money and there are two um problems with that which is one that 10 years down the line is a very long time to be burning 50 billion dollars a year but two is that he seems to just assume that once there's agi then open ai will be a trillion dollar company and worth lots of money and again that's not obvious either um to to elizabeth's point you know i think what i think sam is already trying to move on from the llm um model right like right now most of the ai that is getting most of the buzz are these large language models that need to be trained on a bunch of like existing language but I think everyone kind of is in agreement that if you're gonna get AGI you know artificial general intelligence it's not gonna be a chat bot that basically gives language answers to language questions and because it's trained on language models like they're good he's gonna need to invest a huge amount of money in something we don't even know If AGI is possible.

17:06So it's sort of putting any timeline underneath it is, you know, speculative. And I realize that that's, you know, part of your job, if you're working in an innovative, you know, frontier tech company. But in the case of AGI specifically, even, you know, experts who have been studying this for decades, don't aren't sure that we will ever get to AGI. So even making estimates about what sort of resources it would take and how long it is. I mean, it's very strange to look at a company. You know, it's not a public company. I guess Altman can make sort of speculative statements about it. But he does so with such confidence when the underlying goal is not even something we know can be achieved.

17:50right but this is one of the things that silicon valley vcs love is people who have great confidence about things that are highly improbable and they have a bunch of you know they've learned by looking that like that by if you fund someone who is very confident about something that seems impossible then like there's a good chance you'll lose all your money but there's also like those are the ones that have the biggest returns as well. When he talks about it's good, more value for society, like what? What are the problems that AGI solve? Like I can like rattle off many problems with society and none of them in my head can be solved by Sam Altman and his company at all.

18:35I think the big answer on that front is scientific discovery. Like I think it's no accident that one of the things that DeepMind will tell you about is AlphaFold, like in the first breath, where they've been able to decode proteins because they think that, you know, will help for drug discovery. And maybe there's an idea that you train these bots on, you know, all the scientific literature and you give it some problem sets. And the thing that they're able to do now, or everybody's working on is reasoning. So they can break it down to the component parts and then, you know, try different solutions on each step and eventually get you to a solution.

19:09And I do, so I do wonder, let's say we don't get to AGI, but let's say we get some things that might, you know, maybe short, but close, right? So these agents that take action for us, this ability to reasoning, to reason, scientific discovery, making our everyday business operations more efficient. Maybe that is something that's, that's quite valuable. I don't, I wouldn't, you know, happily burn$50 billion a year on it, but, you know, to earnestly take up Sam's case, like maybe there is something there. I guess it's like cure for cancer. That's like the answer. But it's not just a cure for cancer.

19:44It's like a highly individualized cure for cancer, right? It's the ability for an individual person with an individual genome to go in with an individual cancerous growth and get a treatment that is tailored for them at a very low cost. Right now, that kind of exists, but it costs like over a million dollars. And if we can bring that down from a million dollars to, you know, a hundred dollars, that's pretty revolutionary. It does, but that's partly because of our healthcare system. But all the money being spent on, the healthcare system is so inefficient and expensive and the problems are so basic.

20:23It's not to be all like there are starving people and, you know, in other countries kind of an argument, but like there are more immediate and solvable healthcare problems that these billions and billions and billions of dollars could go to solve to better society right now versus you know spending 50 billion dollars or five billion dollars a year on something we may may not ever come to fruition and maybe no one can afford in the in the final answer so emily like i i don't you know like if you look at the people who are funding this some of them do have um what you might call quasi philanthropic goals they're like they do think of this as a form of like for-profit philanthropy matthew bishop would call it philanthropic capitalism and you know okay fine we can have a whole other segment on that if we want but i don't think anyone is you know i mean okay there are there's a small pocket of true believers saying that this is the first best place to invest money for the sake of the well-being of the planet and if you want to you know help the poor then this is the best way to do it that small pocket like kind of lost a lot of credibility when ftx imploded because a lot of them were you know effective altruists of some flavor and i think we've kind of moved on from that i think that to say that it is not the first best philanthropic place to invest your money to help the poor is not to say that it's a bad I mean, I agree with that.

21:55But I think there are two other things that we have to look at. One is that a lot of the sort of strategic money that's going into AI right now is still just about AI hype. And whenever you sort of scratch the surface of what a lot of people like Altman are saying, they're clearly relying on the fact that most people, when they think about AI, can't distinguish between, say, a large language model or machine learning or, you know, image-based visual or image-based generating. AI. It's all just one category. And these are very different technologies. And I know we were going to talk about Tesla a little bit.

22:31Elon Musk is now claiming that Tesla is an AI company. And when I see that, I just see an attempt to get money that's already flowing into a very specific sector to start flowing in his direction. Well, he's calling it a robotics company, which is different than AI. We can talk about that. He's also got a separate company called xai which is an ai company that he's raising like five billion dollars he also said that his robotics model will be sending it by 2025 and if that you know elon elon says lots of things but but to your point elizabeth insofar as the people making these investments and to be clear these investments are large but they're not enormous they're like you know some fraction of the vc money out there and the vc money out there is some small fraction of the total you know investor base um insofar as the people making these investments are being silly and making category errors and doing all of the things that you say that they're doing like these are vcs losing being silly and making category errors and and is what vcs do and the whole point about vc money is it's risk capital that literally everyone who is invested in a vc fund can afford to lose like this is the correct money to make dumb bets that are going to lose this is not it is not dangerous for vcs to light a billion dollars on fire it is perfectly fine they always have and they always will can i um let me give me a counterpoint on that one a lot of the money funding these companies have come from the big tech companies right so you think about microsoft has been a huge funder of open ai and google and anthrop google and amazon have been huge funders of Anthropic.

24:15And Meta has used its own money to build Lama 3. So like try to find someone who's like really made, taken VC monies and put it into the development of large language models. And it's a little bit tough to find it without big tech money. So actually, I think what you have is instead of VCs taking this money and sort of squandering it, you have these tech companies taking the investment capital of retail investors. It is not the investment capital of retail investors it is their own profits these are all highly profitable companies you know microsoft is famously just giving as your azure compute more than is um actual cash dollars um google has definitely invested a lot of money into deep mind over the years you know and and and facebook has famously bought billions of dollars worth of h100 chips and yeah fine but this is money they can afford to spend, you know, and again, I'm not, you know, these are already multi-trillion dollar companies.

25:14If they burn a few billion dollars, they will still be multi-trillion dollar companies. It's kind of no harm, no foul. Okay. So we've talked a little bit about Elon Musk's trying to pivot to robotics within Tesla. Why don't we take a break and come back and unpack that? So we'll right after this. Did you know your credit card points and miles can lose value to inflation? Credit card companies often reduce the redemption value of your points and miles. Now imagine a credit card with rewards that can grow in value. With the Gemini credit card, you can earn Bitcoin or one of over 50 other cryptos instantly with no annual fee.

25:52Every swipe at the store or gas pump earns you instant rewards deposited straight to your account. Plus, sign up now for a$200 Bitcoin bonus to kickstart your rewards. Visit Gemini.com slash card today. Check out the link in the description for more information on rates. Again, if you're looking to invest in Bitcoin but don't know where to start, the Gemini credit card makes it easy. The Gemini credit card is issued by WebBank. In order to qualify for the$200 crypto intro bonus, you must spend$3 ,000 in your first 90 days. Some exclusions apply to instant rewards in which rewards are deposited when the transaction posts.

26:29This content is not investment advice and trading crypto involves risk. The Gemini credit card cannot be used to make gambling related purchases.

26:40You're used to hearing my voice on the world bringing you interviews from around the globe. And you hear me reporting environment and climate news. I'm Carolyn Buehler. And I'm Marco Werman. We're now with you hosting The World Together. More global journalism with a fresh new sound. Listen to the world on your local public radio station and wherever you find your podcasts.

27:07And we're back here on Big Technology Podcast with the cast of Slate Money. Great to have you all here. Thanks for having me. We're cast members. The cast members. I remember when I joined Disney, they were like, congratulations on becoming a cast member. And I was like, okay, this is a really weird company to work for. Yes. Well, okay. So maybe we'll use a different word, the hosts of Slate Money. How's that? Anyway, so we talked a little bit before the break about the Tesla robotics play. It's happening in this moment where Tesla seems to be in rough shape. And I know you've talked about it on the show, but just for context, it's down 25 % year to date, though it's up 8 % over the past like one year, which is interesting.

27:46It's sort of kind of lost in this narrative. But BBC just had a story asking if the wheels have come off for Tesla, saying there was a time where it seemed like it could do no wrong. But now the company is struggling and it really captures it with falling car sales, intense competition from Chinese brands, problems with the cyber truck. Low sales have hit revenues and hurt profits. And the share price has gone more than a quarter since the start of the year. It's now in the process of cutting 14 ,000 employees. And it's also cut the entire team responsible for its much admired supercharger network.

28:18So what is going on with Tesla? And then we can get in a little bit to this robotics pivot. But what's the state? I know you've talked a lot about it. My big picture theory of Tesla is that it had first moved for advantage. And for a long time, its EVs were three years ahead of everyone else. And they're not anymore. And now they're basically zero years ahead of everyone else. it's you know or maybe like a tiny bit depending on what you're looking for and if you look at the stock market valuation you know it is trading at 50 times forward earnings compared to standard company standard card car companies that trade at like four or five times forward earnings and good ones like you know toyota so um so something doesn't compute something doesn't add up there The idea behind that massive multiple that it trades on is that it has some kind of unique competitive advantage over the rest of the car industry.

29:27And if you look around at who's making the best EVs and the best value EVs out there, it's BYD. It's not Tesla. And we're talking about global companies here. tesla has a nice little advantage in the united states because the united states government is doing everything it can to avoid chinese evs being sold here so it gets to avoid that competition in the u.s but that's not the case in the rest of the world and the rest of the world on our show we've talked about tesla not infrequently as a meme stock and while it's not game stock there is a lot of the i think uh stock the value of the stock is heavily wrapped up in elon as a personality and a brand and so some of this i think is uh at least ross gerber who's a big tesla shareholder argues that some of the fall in the stock price is really about elon sort of being a chaos monkey within his own company right and elon like he can't stop founding new companies right he's just he's got he's got xai now he's got neural link he's got the boring company he's got twitter um i'm sure there's a few i'm i'm forgetting he's SpaceX.

30:35Oh, SpaceX, of course. And he's trying to do all of these things at once while tweeting maniacally through the whole thing. And so at some point you have to ask, when does Elon stop being the reason why Tesla's multiple is 10x everyone else and starts being actually a weight on the stock that is, and if he left, the stock price would go up rather than down. I wonder if he's just so on our show, I guess last week, I we talked about the supercharger situation, you know, layoffs and cutting out this part of Tesla's business that is widely admired and believed it can someday be profitable. And why does this make sense?

31:23And I tried to argue that I think one of our readers called it the 40 chess, you know, argument that like, it seems so irrational. There has to be some reason that Elon Musk did this, that like he can't be this like unhinged and wild. And so I kind of thought that even though I'm not like exactly like an Elon stan or anything. And someone wrote in and was like, no, this was just really unhinged and wild. And no one wants him to do this. His own company didn't want this to happen. He has a long history. It's just possible. The man is out of control now. He has a long history of erratic and impulsive behavior too.

31:59And sometimes people, I think part of his lore is that you can be a certain kind of charismatic entrepreneur and there's a class of people who admires you for that kind of chaos or the sort of very confident, you know, impulsive decision making where it's always framed as, you know, I went with my gut. And Elon sort of embodies that and some people admire it. I personally think it's a sign of a CEO who's not terribly stable, and I wouldn't like it if I were an investor, but I understand the appeal to certain people. But at a certain point, it's like the wheels have come off, and the stuff you used to do isn't working anymore.

32:41You used to never do your homework and get great math grades, and then at some point, your math grades start going down, and you have to put in the work. And it's a problem. Exactly. but isn't that telling him a tiny bit short now i agree with a lot of this but also like he did he has been able to build tesla and spacex is doing well i mean x is i think a disaster but like so space so space like i think i think this is this is a super interesting question is that the more that what you're doing is solving an engineering problem the better he tends to do spacex has two big advantages one is that he kind of doesn't touch it very much he doesn't spend much time on it he has a woman named gwynne shotover who runs it runs it who by all accounts is excellent and he kind of trusts her to do the right thing and it runs itself but also it's solving engineering problems it's how do we get really heavy things up into space and he's like i can solve that problem in the early days of tesla what he had was an engineering problem how do i build an electric car electric cars were something that didn't really exist he wanted to build an electric car that was you know more powerful and better and just as affordable as as an ice car and everyone said it couldn't be done and he did it and that was an engineering problem and that was his great contribution to the world right he showed that it could be done um but then having shown that it could be done other people especially in china realized that they could do it too and now they are doing it too and they're doing it frankly just as well if not better than he is um if you go further away from engineering problems into say you know take boring company he thinks it's an engineering problem like how do you build a tunnel in fact it's a you know zoning problem and a track in the transit problem and a trying to deal with local government problem and he's terrible at that and it's going nowhere and it's a disaster if you buy twitter there's no engineering there at all it's all about like working with humans and networks and moderation and all of this kind of stuff and he has no idea how to do that so i think that you know there are things he's good at but the kind of things that tesla needs to do in order to be successful going forwards are not really engineering problems it's the world is not sitting here going you know evs need to be technologically much more advanced in order to be successful no one is desperately holding their breath waiting for you know full self-driving cars and autonomy to arrive If it comes, it comes.

35:24But for the time being, if you want to compete on EVs, you've got to compete, frankly, on cost. And it's very hard to compete with the Chinese on cost. In fact, it's impossible. I agree with the top line thesis that Elon's success with these companies is correlated to whether or not it's an engineering problem. But I believe it for exactly the opposite reason that Felix does. I don't think Elon's really an engineer. And where he can... Did I say he was an engineer? I didn't say that. You did imply that he knows how to solve these engineering problems, and I don't think that's what's happening.

35:56I think where you see him being successful is at the very early stage of a company when his two biggest skills are writing the check for capital intensive business. Nobody else wants to put money in and then managing shareholder expectations. And then the more mature these companies get, the more he's not mediated by PR people and lawyers. People sort of begin to understand that he's not the best manager. his engineering capabilities are not barely existent he's not an engineer by you know education or trade no he's a he's a ceo and so the question is is he a good ceo he's not a good product person necessarily um and and the things you expect a ceo to do are manage well manage shareholder expectations communicate well externally and that's where he's shooting himself in the foot constantly right and i think the more he gets involved in that product surf like the weirder it gets like as we saw with the cyber truck which is clearly a creature of you know elon musk's product manager or all of the crazy back and forth insanity around twitter blue and who gets check marks and who doesn't and that those kind of product decisions when he makes them are tend to work out very badly that said you know the model s when it came out was as a product genuinely revolutionary and amazing and everyone's mind was blown the you know the amazing videos of spacex rockets like landing vertically and staying upright after going to space you're like okay that's a really legitimately impressive product did elon musk personally design them no but he was you know he he has enough engineering now to at least kind of understand what's going on there So can we then think about this robotics thing as the next in the line of engineering problems that he's tackled and tried to solve?