Confronting Cathie Wood About Her Fund’s 70% Decline

You manage more money than any other woman on earth.

>> Across the company, we're closing in on 40 billion.

>> She's called one of the most disruptive and innovative forces. Kathy Wood making some big headlines.

>> The ARC Innovation ETF soared over the early pandemic.

>> If I'm a believer in AI, what's the number one stock that I should own?

>> I think everyone knows about Nvidia.

We always try and answer that question with stocks people are not thinking about in the right way. So, here's the tough question.

If somebody else had your track record, would you invest in them?

>> Well, [Music] >> Kathy Wood, you're here.

I appreciate you doing this. You're a pretty remarkable person.

I've been watching you for a long time, and there's a good chance that you manage more money than any other woman on earth as a fund as an active fund manager. I don't know if that's exactly true, but you're maybe top five.

>> Yeah, probably. I don't know.

I don't know myself. I don't I don't have those numbers.

>> Yeah. I'm curious actually where what's the humble origins? So, what was Kathy Wood's first job?

>> McDonald's.

>> Cashier. What were you doing?

Flipping burgers?

>> No, I wasn't. I was at the register.

I was 16. I also worked at a supermarket.

I uh first girl allowed to push in carts at Vaughn Supermarket in Southern California.

Do you remember roughly what you were making when you worked at McDonald's hourly?

Gosh, >> I know. Well, right before that, I was babysitting for a quarter an hour.

>> So, so you went from maybe a quarter an hour to managing something like 2030 billion in a fund. And I think this is interesting.

The reason I ask is because in the world of entrepreneurship, we always hear these hustle stories.

And I don't think you go from McDonald's to to, you know, the top where you're at without hustles.

So, what's the hustle story you pride yourself on?

>> Well, the first big break was getting into the business. Art Laugher, I'm not sure if you know Laugher, Laugher Curve, Supply Side, Economics, Reganomics.

Uh, he was my professor at the University of Southern California.

>> He was like an adviser to presidents, right?

>> Oh, every president since Richard Nixon except for presidents Obama and Biden.

And you know he he was agnostic.

If if anyone didn't matter what party wanted to hear what he had to say about uh taxes, deregulation, uh monetary policy, he wanted to give his point of view.

And um you know we've come full circle Art and I because I and my team introduced art in 2015 to Bitcoin. And when he read our paper, he said, "This is what I've been waiting for since the US closed the gold window in 1971.

A global rules-based monetary system.

Wrong rule. quantity theory of money, you know, limited to 21 million units, but we'll get there. And of course, he was talking about stable coins.

So, now we have introduced him to stable coins, tether, circle, and so forth.

And he said, "Ah, the right rule.

" >> Have you seen this website, um, WTF happened in 1971?

>> It's amazing. There's an entire website basically saying, "What the f happened in 1971?

" and it shows like a series of charts where something happened in 1971 and the world was really never the same.

And it's just a it's a very compelling case.

It makes you want to go look at it.

And obviously I think that's the year that we went off the gold standard, right?

>> It's the year we went off the gold standard and all hell broke loose in monetary policy.

We went into massive inflation.

So anyway, it was in the late 70s that while I was in his class that Art introduced me to Capital Group.

I walked into Capital Group. I didn't even know what the investment business was.

I had been a a waitress. I had I was interested in economics, but I didn't know this business. And Capital was the premier f uh firm in Southern California at the time.

>> Sounds like that might be a tough job to get.

Art recommended me highly to Don Conlin who was the chief uh economist of Capitol Group and uh I walked in there and uh Don was losing a person who was going on to Harvard Business School.

So this woman, her name was Claudia Huntington, she was so good at what she did, he was looking for one and a half people to replace her. I was the half, but I I didn't want to be the half.

I wanted to be the one and a half.

>> So, let me ask you a question about that because I think everybody in their career, you know, will have an opportunity.

I had one when I moved to San Francisco when I was 24.

I didn't know anybody, but I wanted to be an entrepreneur.

I wanted to be in Silicon Valley and this billionaire was hiring for this role. I don't know how I got the job.

I was they literally told me, "You're not qualified for this, but we like you.

We'll bring you on.

We'll still hire somebody else qualified for that role, but we want you here anyway.

" So I had like my foot in the door and I think everybody has this opportunity to work hard but it's there's one thing to put in hours. So I think there's a lesson in like first one to be there, last one to leave, like put in a sheer number of hours. But what else goes into kind of like making an impression during that like sprint phase of your career when you can just like fully go full force?

What else besides sitting in the chair for a lot of hours matters do you think?

You know what's the mindset?

sitting in the chair uh maybe matters but I think the most important thing is and my objective was to bring new technology into the firm I was using economics time sharing system we were back in time sharing all the charts that you just brought up boom boom boom boom um back then each one would have cost in today's dollars 5 to10 $10,000.

So that just gives you a sense of how far we've come. Uh but sparingly uh I was able to use charts, you know, ones we made up, so original and then, you know, call them from people we trusted and um really develop little economic books for uh and presentations for Don to use.

>> Yeah, you you'll get what you want when you help other people get what they want.

So the fastest way to getting what you want is just to give other people what they want. And I like what you're pointing out, which is that as a young person, you're coming in without the experience, without the network, without maybe the the track record or any of those things.

Those are your disadvantages, but my maybe your advantage is tech and new things might be easier for you to pick up because you have time and maybe you grew up with those tools and it you're less set in old ways and so you bring something to the table and you that can be your thing.

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All right, let me get back to the episode.

I'm just curious like what is a day in the life of Kathy Wood look like?

What's your actual daytoday main thing that you focus on?

>> I hold sacred in terms of from the moment I get up in the morning until 10:30.

Uh uh that time is all about research.

And so we have our uh research meeting from 900 in the morning to 10:30.

First uh first half of it is just the entire research team together and investment team, portfolio management teams together uh really sharing information and then we focus on in the last half hour on one of the four teams. Uh so we have uh we're broken up into uh autonomous technology and robotics team, AI and cloud which um has forked another team uh which is consumer internet and um fintech.

Then we have our multiomics team which is really all about life sciences and how profoundly AI is going to transform healthcare. And I think that's the most inefficiently priced part of the market. And then we have our blockchain technology team.

On Fridays at uh 10:30 we have a brainstorm and the brainstorm is all our teams coming together or staying together.

But we have another I'm going to say another 40 people who who have followed us over the years and are passionate about innovation and uh we invite them to what's called a brainstorm and that is where we we try to get out of this not invented here we really want push back.

So these are venture capitalists, they're entrepreneurs, they're retired engineers, they're retired professors, they're people teaching in universities today.

and they are very vocal because they're every all all of us they probably more for their personal accounts but we're all trying to figure out how the world is going to work and we're trying to push the frontiers of knowledge forward as fast as we can anticipate what the next set of topics are going to be that people are discussing and trying to figure out where we should position ourselves.

>> That's pretty interesting. Do is that common?

Do you do other firms do this kind of Friday open door brainstorm with like external folks? That sounds pretty unique.

>> No. Um, they don't. And I've done this since 2001 when I was at my last firm.

I I just thought it was really important not to get stuck in our own research but to have it battle tested and and we took that to another level when I founded ARC uh with this notion that we're going to give our research away. We're going to give our research away not when it's finished because it's never finished but as it is evolving and we push it out.

Now, at the time, 2014, Twitter was for tween, teens, and celebrities, right?

So, I didn't think that was going to be our primary social network.

We thought maybe LinkedIn would be.

Instead, X has become the most important social network.

Even for crypto, uh I thought Telegram was where all of that was going to live.

And yeah, there are all kinds of conversations, but the ones that we need and that I need to see, they are on X.

Uh, and sometimes we stir the pot, you know, with our research and and get debates going.

So, uh, I feel that the world is moving so quickly today. It's not like it was in 1977.

Back in 1977, as I described, it was really expensive to get information.

uh and to travel places uh to pull information from managements and so research departments like the one at Capitol they were closed and that was their secret sauce. Today information is ubiquitous and it is all over the place.

In fact you have to figure out is it real or fake you know so you know so that takes another skill. Uh so I I thought you know the closed world is probably not where we are best suited for for what we want to do and that is focus exclusively on technologically enabled disruptive innovation.

That's all we want to do.

Well, there's so much information out there and uh we knew we could harness it and it's how you put it together and what you what what you place priorities on in terms of the kind of information uh and the kinds of assumptions that you're making uh that become more important.

>> And you um this might be a dumb question, but like you will go on TV and you'll say, "I think Tesla's going to $2,000 a share," or, whatever your target price is. And everyone says, "Oh my gosh, that's really bullish." And you say, "Here's why we believe.

Here's what, you know, here's what we believe the future looks like." And I hold Tesla and I hope that that all comes true.

But you are very active. Like you're buying and selling Tesla all the time.

I looked in the last like 24 hours, your firm has made like 20 trades or something like that, like millions of dollars in and out of these positions. If you believe Tesla's going to, you know, some $2,000 a share, um, why don't you just buy it and hold it? what what is all the active trading for?

And like are are you day trading?

I mean, I'm I'm not from the investor world, so I'm trying to understand.

>> You know, you have sort of the Buffett mentality and then, you know, you have you're very very active. I don't really get that.

>> Yeah, that's another great question.

I know it must seem confusing. Uh so, and we often do describe ourselves, few people believe this, but we believe it uh as a deep value manager like a Warren Buffett.

if you give us 5 years.

Um, and you know, Warren Buffett, he was the first to admit I don't invest in technology.

He made a few good ones like Apple was great, IBM not so, but um, he knew where his strengths were or he knows where his strengths are.

He's still with us.

>> Um, uh, and he did not feel that technology was where he was where he had an edge.

That's where we do have our edge.

And so you can say we're a great complement to the Warren Buffett strategy if you give us a fiveyear investment time horizon. So why do we trade so much?

Well, because of what has happened to the markets and really since I got into the business um I think more than 75% of the trading is algorithmic and high frequency trading.

There's a huge amount of volatility in the market itself, but especially in our stocks.

So if you look at our trading in Tesla, we are using it, we are using the volatility to our advantage.

So rarely has Tesla dropped below the number one position in our flagship portfolio, ARK.

What has happened? It has gone from $100 to $500 and becomes you know 13 14% of the portfolio from a portfolio management point of view we are effectively rebalancing that's a lot of hard work 100 to 500 and we know we know we know we know Tesla is a controversial stock Elon Musk is a controversial individual and we are going to have opportunities at lower prices to move back in. And so that's the kind of trading that you see uh around our high conviction stocks.

>> Okay. So let's take what you just said.

So you said give us 5 years, right?

Because we're betting on these sort of long-term technology scurves that we're we we think are playing out.

So here's the tough question. um over the last 10 years you've been making hundreds of millions in fees but haven't outperformed the simple index like QQQ.

Do you think that's a fair criticism?

>> So can I can I give you a reset here?

I love the question. You're giving me an opportunity to answer a question that I I know is on many people's minds even if they don't ask it. So thank you.

So our objective as a as a firm is to deliver a minimum 15% compound annual rate of return over five years. So you are absolutely right.

We have not done that.

We have done that since inception.

So since inception our compound annual rate of return is over 15%.

Now what happened in the middle there because you're this you're focused on endpoint sensitivity and I understand why people use 5 years 10 years all of that.

>> Sure. If you use 10 years uh and you look at Morning Star and uh just their quantitative metrics which have no human input, they just have their rules-based system based on the benchmark they selected for us. We didn't choose the benchmark.

We are benchmark agnostic.

We are in the fourth percentile of performance for that benchmark.

Now that benchmark is midcap growth, >> right?

>> Uh which kind of fits because we consider ourselves all cap but you know if you average you'll get mid to midish cap let's say. So that's good.

You know that's that's actually saying something.

the space we've been in, anything less than large cap and especially mega cap growth, especially in the tech space has been very tough. Okay, so that's another marker.

Now, what about the last five years?

Well, we had COVID in 2020 uh because this this is when we blew up.

Uh I'm I'm not sure if you know uh this part of the history, but because we were the only investment firm putting our research out on social media and the only one posting our trades every day.

We went viral during COVID because everyone was sitting in in front of their computers trying to figure out what to do with their time, right?

And their extra money, by the way.

>> Yeah. And their extra money.

We were actually uh the really one of the few out there teaching people about investing uh bringing them along on our journey.

In 2020 we were up 150%. And at the end of that year, remember we're five years away from that. This is what we're comparing against.

At the end of that year, I was on Eric Shatsker's show on Bloomberg.

It was a holiday show and they gave us a lot of time and uh one of my main messages was hey keep some powder dry this we know what goes up like this is going to come down it's just too much capital chasing chasing the opportunity perhaps too soon and the re and that that last point I probably should have said more loudly to myself and to our team, >> right?

>> Because even though our modeling stock by stock got us to a 15% compound annual rate of return over the next 5 years, which was very low.

Normally we're normally we we're expecting 25 to 40% compound annual rate of return.

So it had dropped because of the appreciation in stocks to 15%. But what also had happened and what we did not appreciate enough was many people think oh the interest rate increase that wasn't as much the problem the problem was supply chain bottlenecks.

Our models are driven by unit growth and when there's an interruption in unit growth our uh our model our the the rate of return expectations come down >> and I I thought and we thought we were going to come out of this um out of this crisis in a V-shaped recovery and we did.

That was correct. But we didn't catch how long it was going to take supply chains to reorient. And that that I think was a big big lesson for us.

Um if I had just focused on that one variable, I would have said um all right, let's move more into larger cap tech stocks with a big cash position that are innovating. and it would have been the mag six and and all of that.

>> We did not do that. What we did, we owned them and as we uh because that we had started doing that in the bull market, we always diversify as a bull market extends because our stocks do tend to go crazy to the upside.

So, we were already doing that. But then in 21 uh those stocks kept going up and our stocks so smaller cap and midcap stocks started going down. And so what we always do is rebalance. We took profits there.

We bought that was just way too soon.

It worked out and I think history will show that everything is fine.

uh we had to have people stick with us and there are so many people who piled in at the top even though we're saying uh hold your horses and who left us at the bottom which is classic. It's classic.

And so we're going to be out there in this cycle a lot more saying along the way rebalance, sell, take profit so that when our our strategies go through a weak spot, a sinking spell, then you'll have the psychological wherewithal to buy.

It's called rebalancing and it's a basic investment concept.

>> Betting against you as betting against a combination of things that I would never want to bet against.

It's betting against AI. It's betting against crypto.

It's betting against innovation and it's betting against Elon Musk and those are just that's not who I, you know, that's like the Monstars and Space Jam.

I'm just not trying to bet against that.

You might even be right on some on any one of those individual things maybe for a period of time. It's just not where I would want to be positioned against long term.

Uh at the same time, like I'm a normal person and it's pretty crazy when >> uh like this is in venture capital too, by the way. In venture capital VCs, it's a rigged game. I heard this a long time ago and I it never left me which is venture capital is a great game.

You make 2% annually on on your fees regardless of whether you make money or lose money.

And I think what you do is very similar, right? Like if you have like I don't let's just use a round number 20 billion in assets across your ETFs.

Is that about right?

>> Across the company we're closing in on 40 billion.

>> Okay. That includes uh digital assets, private funds, everything.

>> Yes, it So we do have a venture fund.

So I know what you're talking about.

Uh we're doing ours a little differently.

We don't have a carry so that anyone with $500 can can get onto the cap tables of SpaceX, OpenAI, Neuralink and so forth.

>> You don't have carry. So how do you make money in that just on fees?

>> What we do is we do have a high fee.

So I think it's um uh 2.75%.

And what we did to arrive there is we said okay what do the best venture capital firms in the world deliver over time in terms of compound annual rate of return for their clients and how much of the benefit do they derive? uh and the the best ones and and maybe they're going to be north of 2.75% per year on average and especially in this kind of a market where AI is just out of sight but uh the best ones if you do a very long-term historical retrospective the historical is retrospective uh 2.75% was the landing point but we are offering direct to cap table these are not SPV not SPD.

So there are no fees upon fees upon fees, >> right?

And so you know I think that the challenge is basically on a 20 or$40 billion in total assets.

There's a guarantee as a this is why finance and fund management is like one of the best businesses in the world is you get you know hundreds of millions in fees guaranteed regardless of whether you're up whether you're down and then you know like the more you go up maybe you you have additional carrier.

there's other things that uh you know in venture capital that that you benefit from and so I think that's the that's the um the challenge right like Munger used to say you know show me your incentive I'll show you your outcome it's like I think all all finance and fund management is generally suited towards grow assets under management we make money either way and then like try to do your best in terms of the performance and in the long run you know you will be judged on the performance but in the short run it's hard to tell right like uh what's what's working what's not which is why when Buffett I think started he he basically said I'll take nothing for the first 6% which I think was like kind of the sort of the index standard at the time and he said but above if I beat if I beat market then I want 25% of profits and I thought like you know >> that was a a great structure and I think the world of finance has moved away from that cuz why would you if you could I would do it too if I could take the guaranteed fees I'm going to take it >> well you know it's interesting from the I'm going to say from the 80s on when I saw hedge fund structures and venture capital I said I'm an economist s I said h that game's going to end that's you know that th those kinds of excesses excessive return shall we say they they go away with competition but in the venture world uh and there is a huge amount of competition but if you look at where the real money is made it's in the top you know 10 the top 10 is where a disproportionate amount of the returns are and of course that's what we're aspiring to and of course everyone is aspiring to it but there's some kind of network effect and and I think it has to do with the the network effect is is not a viral app it is the community >> well venture has one different property than what you do uh outside of your venture stuff which is in startups it's the only asset class where the um the security selects the investor so you know for Buffett or any public stock market I get to just pick what I want to be in and I push a button I'm in I'm in the stock whereas the hot startups want to be with the hot funds and only the hot funds get to be on the cap table. So the security selects the the investor not just the investor selecting the security.

So it has this like that's where the network effect comes in. That's where the brand effects come in and that's why Sequoia and Benchmark and these other guys will keep showing up in the top because if I'm one of the top startups I want them and so they get they get the access even if another investor was totally right in their thesis they just can't get get them to capital. It's a it's a self yes there is there is self- selection you're seeing in the hedge fund world big changes though in that world the fee structure is changing because passive the the indexes were outperforming active it was a self-fulfilling prophecy because the pendulum was swinging there I believe that that pendulum swing I think I think that and consider the source Right.

But I think the pendulum swing, the final swish in that direction was in the last few years towards the mag six and now they're so con one of the reasons they're such concentrated parts of the now. Are they all going to benefit from all of these new technologies?

You know, our focus on robotics, energy storage, AI, blockchain technology, multiomics.

Uh some of them will.

Apple we've been watching for a long time.

Finally, it's out.

They don't know what they're doing in in AI.

Uh now I think they're scrambling a bit.

So, you know, we'll see what happens.

Uh each one of them has a weakness.

Each of the mag six has a weak a weak spot.

Uh sure, they'll participate in the wave, but they also have some weaknesses caused by the disruptions associated with these new ways of doing things.

Uh, and I think we're at the beginning of that pendulum swing in the other direction.

As I just said, consider the source.

That would be great for us because we don't own the mag six in our top 10.

It's not like we won't own them, but we don't own them for the most part in the top 10.

>> If I'm a believer in AI, what's the number one stock that I should own to benefit from the oncoming AI wave?

Well, I think everyone knows about Nvidia.

We always try and answer that question with stocks.

People either they don't know or they're not quite thinking about them in the right way.

Uh so >> yeah, misunderstood. Maybe not maybe not unknown but misunderstood or mispriced if you >> so.

So yes, as we were selling in Nvidia and and we got all kinds of flack.

No, nobody bothered to notice that we put it in the portfolio in 2014 because of autonomous driving at I think 20 cents on the current stocks uh stocks basis at 20 cents per share. Um and we held it for years and no one would listen to us.

No one. I talked about robotics, talked about autonomous driving, talked about uh nope, it was a PC gaming chip company and that's all it was. And then it explodes with chat GBT and you know we we start selling it and and and we sold it too soon in the uh in the flagship.

I mean meaning we exited it. We're back in it now when it dropped during tariff turmoil.

But >> what did we put the m in portfolio management?

You have to not look at what adjust what was sold, but what did you do with the proceeds?

How about Palunteer, which I think from that point has done better than Nvidia. I I I don't know.

It was that was the case at one point.

How about Coinbase when the SEC was suing it? That's one of the that that's what we use some of the Nvidia for.

It has done pretty darn well.

Um I think almost as well as Nvidia.

So you have to do so today of course Nvidia still I mean we we it it still has a a very important role. Palunteer still has a very important role. It is the premier uh platform as a service company.

We think embodied AI is underappreciated.

What is that? Embodied AI is physical AI physical and digital worlds meeting.

You know what I'm going to say next?

Tesla is the largest AI project on Earth and it's not just robo taxis anymore.

It is humanoid robots. It is humanoid robots and according to our research while the robo taxi opportunity globally for everyone including China is an 8 to10 trillion revenue opportunity in the next 5 to 10 years from maybe a billion now.

So think about that a billion to 8 to 10 trillion.

and the whole ecosystem with the platform companies like Tesla getting half of that.

So that's 4 to 5 trillion.

That's a big market. Uh according to our uh estimates uh the humanoid robot market will be a $26 trillion market in the next I'll say 7 to 15 years.

>> I wanted to ask you about this because you put out this great deck or ARC put out a great deck. Um, and I love this slide.

So, uh, if you're on YouTube, you'll be able to see this. If you're on audio, um, sorry, you know, go go to YouTube and and or Spotify and check this out.

So, on this slide, I'll just describe it.

So, it's basically the cost per mile, like how much does it cost to travel to transport a human being one mile?

And you started like in the 1800s like horse and carriage. And, you know, adjusted for inflation and all that, it's not it looks like it's $210 to travel a mile when you're back when you're on horse and carriage.

Then, you know, you get the the Ford, you know, Henry Ford era and you're at a$110.

And basically, for like, I don't know, almost a h 100red years, it's been roughly the same number. It's been a$110 to travel a mile.

>> And then your estimate is that with self-driving cars where you don't have a driver in there and you're on an electric self-driving car that the cost per mile could drop to your estimate is a quarter.

So, uh, you know, four times cheaper than what it currently costs or what it has cost for the last 100 years.

Did I summarize your slide correctly?

>> That is correct. That is correct.

And and you know when we first did this research, we too were astonished with that.

Wait a minute. It cost the same inflation adjusted.

Uh that that and then one of the reasons for that is because the the automobile matured fairly quickly, right? And we're all about rights law. Writes law tries to understand, okay, you've got this new technology.

You're starting from a low base.

For every cumulative doubling in that base, so from one to two, two to four, four to eight, for every cumulative doubling, cost decline at a consistent percentage rate for each technology.

Well, the internal combustion engine is mature and so it has no shot against EVs. Even though I know I know that's not the prevailing wisdom uh in this political climate or I'm just using economics and learning curves.

So technology >> sorry what do you mean by it has no shot?

You mean like um no shot in what sense?

The cost comparative comparison or just >> No, because of the chart you just showed.

You can't get that cost down any lower the there there are no more cumulative doublings.

Everybody's got one.

you know, it's a bit of an exaggeration.

In the emerging markets, they don't, but uh they're not going to be paying up for for uh internal.

They're going to be looking for the cheapest solutions to cars, and those are going to be electric.

>> And the part that the part that I didn't get was um so, okay, great. The cost is going to go down because it's a self-driving electric vehicle.

Okay, I get that. Uh I could see why the cost goes down.

>> Uh and I assume when the cost goes down, the demand goes up. It's cheaper to travel.

More people travel.

it's gets selected over all the other more expensive ways to travel.

>> Um, >> but the estimate you have where it's like the cyber taxi revenue, I think you had the autonomous revenue is sort of like in the uh what did you say you said 10 trillion or something like that global.

>> Yeah. Yeah. Totally.

>> Right now, if I just take Uber, Lyft, Door Dash, like kind of the the revenue of all those companies, which today I would say ride sharing is not like a new idea.

It's pretty pretty prevalent.

I think Uber's at 40 billion.

You add Lyft, that's another six billion.

And then Door Dash, it does about 10 billion.

So like the total of all three of those companies is only in the like 50 60 billion range. But you're saying that >> but but that is even different from what we're talking about here. They are not autonomous and they are not in the pole position.

I mean Door Dash will harness autonomous.

That's very interesting one because we think delivery is with especially with drones and rolling robots and everything is very interesting use case but Uber and Lyft are not in the pole position for this new world.

>> Right. Right. But I guess what I'm saying is that's what's spent today on taking rides from a a ride like a push a button get a ride service.

>> Um why would why is self-driving going to be 20 times more revenue generated?

Why is it going to be 10 trillion when all of those add up to 60 billion?

>> Right? What we're doing is moving from a very narrow uh subset of transportation called ride hail today to all of transportation.

Right? So we're we're moving the entire market to autonomous to get that number.

There are very small slice very very small.

And in fact, what's so interesting in San Francisco, um I think that Whimo, uh we're finding research is showing that uh people are willing to wait longer and pay more for a Whimo, right, >> than for an Uber or Lyft. And I believe this has already happened. The number of miles even though in San Francisco Whimo is geo fenced and is not. Uh the number of miles in San Francisco the San Francisco metropolitan area that Whimo is driving per day has surpassed Lyft and is heading for Uber.

Isn't that remarkable? People are willing to pay up.

Now that's not in our 8 to10 trillion.

We assume that sure they'll start maybe right at or below the prevailing prices ruber and they will drop over time to that 25 cent.

So starting in the $2 and it's surge pricing you know it can be $8 per mile.

Um starting$2ish dollars$ 250 maybe and dropping to 25 cents.

25 cents is at scale, right?

>> So that's the8 to10 trillion.

And you know, just think about it. I mean, I would prefer to take an Uber today, even though I have I have two Teslas and and I love them, but I still have to pay some attention on the road. Right.

>> Right. I'm curious, uh, how much of the Tesla market cap, I think Tesla's 1.3 or 1.4 trillion.

How much of that is Elon?

Meaning if I took Elon off the company, if Elon went to sleep for the next 20 years and we weren't going to have Elon running running the company, would you keep your position the same way?

And and how I guess just pie chart, right, of that 1.3 trillion, what do you think that number goes to if there's no Elon?

>> Well, if you had asked the question like 5 years ago, the answer would have been different.

But I think what has happened and one of the reasons Elon has spent so much time doing other things some of which people didn't agree with uh is because I think he feels they have pretty much solved the last mile in FSD and if they have done that then they're going to capture the robo uh taxi opportunity.

They're going to be able to scale.

We would not, however, uh, start incorporating humanoid robots in the way we we haven't done much yet in our $2,600 price target. Uh, uh, and we'll update that.

We usually update it each spring uh, for public consumption.

Uh, and so we have very little for humanoid.

We'd probably uh, be be much less optimistic on humanoid robots. And so we wouldn't put as much in as we perhaps will with Elon at the helm.

>> Right. Wonderful. Well, Kathy, I appreciate you coming on. Uh it was fun to hear some of your stories.

It was good to hear, you know, your take on some of the tougher questions.

So, I appreciate you doing this.

>> Yeah. Thank you, Sean. And thank you for the tougher questions.

They're important. Thank you for giving me a platform on which to answer uh those questions because it is important.

It is important.

>> Great. Well, thank you. I hope to do it again.

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