Cathie Wood: How to Invest in a World Moving This Fast

We're able to cure disease and it's already happening. Closer to 5 years, I think that we'll have humanoid robots in our homes. We believe we're in the early stages of the AI revolution. Anything that's good for humanity is going to be highly valued. Think about that. What I've just described is 25 years of the rubber band stretching.

Thank you, Bryce. Happy to be here.

We have even been surprised and it takes a lot to surprise us because we're doing deep first principles research and to see AI taking off as quickly as it is. Well, we have some great leaders out there who are, you know, moving very aggressively. Then we've got China who's really focused on the space and I think there's nothing like competition to get us both going and accelerate the pace. I think the reason it's feeling so quickly is it's impacting every industry. So there are three, well many opportunities but we think every company can harness AI and there are huge productivity gains and what's happening is CEOs know okay we have to do this because we could be left out in the competition. So it's coming from the top down but it's also coming from the bottom up because people especially in or near entry level jobs are saying wait a minute AI could take my job and so I better use it to become more productive and I always say make your boss look brilliant you know and make sure I guarantee myself a place in this revolution. So top down, bottom up by company. That's the first thing that's happening.

But then the other thing that's happening is something called embodied AI. And what that means is really the physical and the digital worlds coming together. That is also what's surprising because there's a lot of inertia in certain spaces. There's an accelerated pace of change in certainly transportation for example, autonomous mobility. It feels very fast. But the first commercialization of a robo taxi was in 2018. It was Waymo in the US. And so as we were doing our research, we thought Tesla would get there before last year, June of last year. Now we're seeing it is moving faster than Waymo. And it helps us explain or illustrate slowly, slowly then all at once. It's not as though this happened overnight the data collection. So Tesla has about six million, seven million robots collecting data. I have two Model Y and a Model 3 collecting data. I have had my first one since 2018. It has been collecting data, sending it back every day to Tesla so Tesla could learn our roads through real-world driving as opposed to just simulation. So that's been a long time you know that was 2018 for me it was really 2015 so 11 years so slowly, slowly and then people say yeah, yeah, yeah this will never happen and then woo all at once and I think that's going to happen with robo taxis. You may not feel it here as much in Australia because you need to build out your charging system for electric vehicles and it took us a long time we had a lot of range anxiety too when it came to electric vehicles. Now robo taxis are going to be electric. So we needed that charging ecosystem so that they could be ubiquitous and not have to go down. So that's one manifestation of embodied AI. Seems like it might be happening fast now, but it took a lot of years to make it happen.

Another one, humanoid robots. Again Tesla, SpaceX will be and they'll probably combine will be at the bleeding edge of that. This is one where wouldn't we all love a humanoid robot at home to do all of our housework, right? It's a dream and many people including Elon are saying it'll be here in a couple of years. That's Elon time. It's probably going to be here in 3 to 5 years. And when I say that for all of us to be able to afford a humanoid robot, we need the unit growth to pick up in order to drive the cost down. And that's probably closer to 5 years, I think, that we'll have humanoid robots in our homes. That's going to be exciting. Again, slowly, slowly what's going to be the hold up? Data. There's a company in our venture capital fund called Figure AI and it has just given people cameras to wear and other sensors while they're doing their housework. And why is it doing this? Because there is no data on it. And for AI to really take off, you have to have a big body of data.

And so I went out to visit a company called Physical Intelligence in San Francisco. This CEO will not allow any fund into its rounds unless someone from the IC committee, the investment committee actually visits the CEO in person, which I did.

And what was so interesting, I walked in and Physical Intelligence, humanoid robots and so forth. Same thing. All of these people were there doing things physically so that the robot could learn from computer vision. But the data we're in such early days there and then in healthcare it's also slowly, slowly and all at once. I think healthcare is the most profound application of AI. We are now diagnosing cancer in stage one and soon thanks to the convergence of sequencing technologies and AI we'll be able to diagnose cancer we think and other diseases before stage one. And just to give you an example, Freenome in our venture capital fund actually was co-founded by one of the leaders of the venture capital fund who was an oncologist surgeon and said this is ridiculous. We need to get more data about cancer so that we can diagnose it so much earlier. So he became expert in AI and his company Freenome is now diagnosing colorectal cancer in stage one but he believes and this is just with blood tests you don't have to get a colonoscopy you're too young to have colonoscopies. I will be very happy not to have colonoscopy but with blood tests we're now able increasingly this is in trials to diagnose even the earliest stage of cancer or precancer with polyps which also shed into the blood if they are becoming cancerous. So think about that. Without AI, it would be impossible. Without sequencing technologies, impossible. Those two coming together, diagnosing disease, curing disease, add another thing to the mix. Sequencing technologies. Do you know how many cells you have in each of your bodies?

Yeah. Trillions.

The answer is you're very close. 35 to 40 trillion cells in each of our bodies. And so what are we? We are walking data factories because there's something called single cell sequencing. Now think about that. We're going to be able scientifically to know what's going wrong in our bodies. We could not do that before. But now thanks to sequencing, AI, and CRISPR gene editing, we're able to cure disease. And it's already happening. Beta-thalassemia and sickle cell disease, two rare blood diseases, they're being cured. CRISPR Therapeutics is the company. And it's not just going to be rare diseases that we're going to be able to cure. I say we able to cure proverbially. But it is going to be common diseases. In CRISPR Therapeutics pipeline is a therapy to basically cure bad cholesterol.

These stocks are priced as though really they're not going to go anywhere. This is what happens in innovation a lot of people doubt in the beginning, doubt, doubt, doubt and then boom.

Well, first we do our research. So whenever we see a new technology, we'll go investigate it. I'll give you an example from the earliest days of ARK in 2014. We told Tasha Keany, Elon Musk is talking about in his master plan, autonomous vehicles. What's an autonomous vehicle? What does that mean? And so Tasha went out and because we do a lot of our outreach on social media, like we give our research away. Not when it's finished. It's never finished but as it's evolving on social media because we want to meet those who are innovating in this space and we do. I never dreamed when we started the firm that Twitter which was for tweens and celebrities at the time that Twitter would become as X our most important social network for research. And so through research you know social media academia you know tech analysts I mean she went everywhere to try and figure this out. And she came back one time and she said, 'It appears that the brains of an autonomous vehicle are going to be GPUs.' And this was 2014. At the time, you're going to find this difficult to believe, but at the time, Nvidia was selling off. It was below $10 billion in market cap. It was selling off because it was nothing more than a PC gaming chip company and PCs were being displaced by laptops. So, they were falling at a double-digit rate. And so, when she came in and said that, I said, 'Oh my gosh, nobody knows that. Let's keep doing that research. We'll do our top down. We'll do our bottom up research which we do a lot of and if you're on to anything here this should become the top holding in our portfolios and or many of our portfolios.' And we did and the rest is history we were there nobody was paying attention to us we said GPUs autonomous driving AI robotics for years that was in 2014 we didn't have the ChatGPT moment until late '22 nobody was listening to us we were there and you know we took a lot of profit. Some would say prematurely. It was premature but you always have to look at the other side. What do we do with those profits? How about Palantir when it was selling at $10 or $9? It was the same theme. It was just getting at it from a different angle.

I think it's in the healthcare space and the reason this has happened is the DNA in healthcare, DNA of a financial analyst in healthcare versus one in technology is night and day. Tech analysts don't like dealing with healthcare because it's very slow, regulated, bureaucratic, political, it's hostage to insurance companies and governments and tech analysts don't want to have anything to do with that. Healthcare analysts move fast and break things. They don't want to do that. They're regulated. They're political. They're in a political environment. So, I think that's the most inefficiently priced part of the market as it relates to AI. And so, I gave you one name, CRISPR Therapeutics. Another name in that space these have the most robust patents is Intellia. Intellia now it's an earlier stage than CRISPR and it has been demolished just to give you an example in when we first took our positions in the late teens I don't know if it was '18 or '19 when we took our first position by the time 2020 rolled around Intellia and CRISPR were both $200 billion stocks in terms of market cap today. Intellia is less than $5 billion.

And the reason is this divide between healthcare and tech analysts. And I've heard some healthcare analysts saying curing disease that's a terrible model. Why? Because we're not going to get our annuity the pill every day or injection every month. That is a ridiculous answer. First of all, anything that's good for humanity is going to be highly valued. And in this case, a cure. Insurance companies today have no problem paying $2.2 million for a cure.

Why? Why? Because it saves so much in terms of sick care. So, sickle cell disease onset as early on life. And for 50, 60 years, these poor people, there were no cures. So they would have to go into the hospital 10 to 20 times a year on an emergency basis for blood transfusions. Of course they want to be cured and of course insurance companies want them to be cured because that's really expensive. That's sick care. Turning sick care into health care I think is one of the biggest opportunities we have. I would say 75 to 80% of all healthcare dollars are dedicated to sick care. With cures that's going to diminish and we'll have more funds to allocate to prevention, diagnosis very early and actual cures. So we're pretty excited about that space.

Yeah.

Pretty incredible.

Right. We've talked about diagnosing disease early. We've talked about cures. How about the discovery and development of new drugs? So people are very surprised to learn that a large pharma or biotech company in order to discover and develop one new drug and this includes the trial failures along the way cost $2.4 billion and takes 13 years. So with AI and sequencing technologies we believe that in the next five years that the cost will drop from $2.4 billion to $600 to $700 million and the time will drop from 13 years to 8 years or fewer years. Now these drugs the patent lives they're 21, 22 years. If you add five years of revenue generation that's huge. That's huge. So we think and this is where active equity management comes in. Some companies are going to do this well and some companies are not. They're not going to move quickly enough and oh by the way they're going to lose $300 billion in revenue because their drugs are falling off patent cliffs and they go to generic pricing. So they need to do this. And so we're excited about what's going on in healthcare. Thank you for giving me a chance to talk about it because you know most it's been a terrible area to invest and it's because of this divide that I talked to you about but it's probably the most underestimated and most inefficiently priced part of the market when it comes to how much AI is going to transform it.

Yes.