Guys, this is one of the most amazing entrepreneurs that you're going to meet. Jim Litinsky, this founder and CEO of MP Materials.
Jason, how are you? So, let me set this up. Jim was a hedge fund guy running a pretty successful hedge fund. And he ended up basically investing in something called Molycorp, which went out of business.
And you did this incredible thing, which is you said, 'You know what? Screw this.' You essentially shuttered the fund, took over the company, and fast forward many years later, you are the largest and only, I think, supplier and refiner of rare earth materials and maker of magnets inside the United States.
We're 100% of the American industry.
100% of the American industry. You just did two really incredible things actually in the last couple weeks. One was you announced an enormous public-private partnership with the DoD, $400 million etc. And then the second is you announced a really big deal with Apple.
Okay. So take us, take a huge step back. Talk to us why rare earths matter. Tell us about the supply chain for AI. Tell us why you're doing this.
Rare earth magnets are really the feedstock to physical AI. You know, robots, drones, everything we're talking about today, the biggest industry in the world to come. Essentially, electrified motion requires rare earth magnets. So you mentioned the predecessor went bankrupt. There was a feeling when I took over this site with my co-founder, and this goes back to 2015. There was...
This, oh, it's in Mountain Pass, California. So, if you'll be familiar, if you take a 45-minute drive from the Las Vegas strip just over the border in California is the site. You actually can see it from the road. And it's actually really the best rare earth body in the world. The thing about rare earths is that when you mine them, you also have to refine them. And it's really expensive and difficult to refine them. It's really a specialty chemical process. And so it's really a, think of it as a multi-billion dollar refinery that you need to have just to separate them. And then once you separate them, you need to turn them into metal and then a magnet. And so there's multiple layers of this stream to get this supply chain. And of course, you could have all the rare earths in the world, but if you don't make the magnets, you're sending it to China. Or you could have all of the magnetic capability in the world, but if you don't have the rare earths, you're relying on China. And so our vision from day one going back to, we originally bought these assets out of bankruptcy officially, it was a two-year battle, took it out in 2017. And there was a perception that we just couldn't compete against China. And what we discovered actually is we could. It's a world-class site, but we had to reorganize the process flow and then we had to make investments to move downstream. So over the last eight years we invested about a billion dollars. As you know, we took the company public in 2020. We built out the refining capability. And then about four years ago, we announced we were going to build a magnetics factory in Texas. We built that factory. We have GM as a foundational customer. We're now producing auto-grade magnets to GM spec and we'll be ramping up sales to GM at the end of this year in magnets. And then, as you referenced, a couple, it's been a busy few months for us. We announced a pretty transformative public-private partnership with the Department of Defense. DoD is, there's really three pillars to this deal. DoD is becoming our largest economic investor. As well as they're going to provide a price floor for our commodity so that the Chinese sort of Chinese mercantilism, we can get into that, won't take the price of the commodity below the cost of production. And then as a result of the DoD investment we're going to accelerate the buildout of the magnetic supply chain. So we're expanding our facility in Texas for Apple. I'll talk about that in a second. But we're then going to build a 10x facility to 10x our capacity with DoD as our 100% offtake partner, customer and business partner because we'll be splitting profits 50/50 with DoD.
So to just translate this, it's not a handout from the government. They didn't gift you $400 million. They invested in your company. They have warrants. They have equity.
Yeah. So they invested, they both are an owner. They also are an upside participant in our commodity to the extent that the prices take off. And then they're also a 100% offtake customer. We have a guaranteed level of profits to want to build out this facility, but above a certain threshold, they're a 50/50 economic participant. So, there's really, you, the taxpayer. Yeah. So, this is a, and maybe I'll say something wild here. This is a true win-win. Obviously, great for MP shareholders. Great from a national security and commercial national security standpoint because we're going to have enough magnets to provide, you know, real certainty in the supply chain for the physical AI revolution and other industries. But it would not surprise me if when we, 5 years from now hopefully we'll do this conference and you'll say to me Jim, you know, I remember that deal that was the first of its kind that you did with DoD and the government made money on you, the taxpayer made money on doing this. And I'll say yeah, I actually think that's going to be the outcome because there's sort of an element of mutually assured economic destruction. If the Chinese believe that America has national champions too, then there's no point in subsidizing the rest of the world. And so, I think you can start to see prices normalize for some of these things and free up our ability to invest and expand.
Why go to the government for this investment as opposed to the private markets?
Yeah. Well, because it's that issue that this is sort of one of those, you know, obviously you have to go back to World War II or the railroad boom where you really need government and credit. I mean, this administration did something, you know, totally unique that...
Why do you need the government?
Mercantilism. Straight up mercantilism because the Chinese will sell magnets for below the cost of raw materials. And so every time there's somebody who makes progress, they can put them out of business overnight. And so it's difficult to want to make the investment. And so frankly with the Department of Defense, the scale that they wanted us to build on the time frame that they wanted us to build, there was no way we were going to make that commitment. We're fiduciaries, right? We have shareholders. There's no way we're going to make that commitment without certainty that we would not be destroyed by mercantilism and that we would have a customer for the magnets.
How big of an industry is physical AI? Meaning, we see the robots, we're told the robots are coming, we're told there's going to be billions of them. Are they actually being deployed at the scale and at the pace that we've been told?
Yeah. Well, I think that is a question for, there's much smarter guests on this for the rest of the day. Obviously, you have the best of the best providing that feedstock. I will say that I think one of the big drivers of our deal was the, as we've seen in Ukraine and the Middle East, the future of warfare is physical AI, right? Robots and drones. And I think irrespective of the scale that robotics is ultimately going to be, and certainly the commercial business will be bigger than the defense needs, but just from a defense standpoint this is a really important supply chain that we must have. We can't be funding cutting-edge drone and robotics companies and then say okay but we're going to buy those magnets from China. That makes no sense.
Do we have talent capacity or do we have a talent shortage? Secretary Burgum gave me a stat which was pretty shocking to me that we only graduate 200 people a year in the United States in mining which is orders of magnitude different than China. What do we need to do to be competitive to build the industry here?
It's a great question. I think, Jason, I think about this question a lot. Yeah.
I'm a huge fan of the pod and I embarrass myself all the time. But it's the only, it's the token whites and you know I'm a fan of the pod since day one and I've totally myself.
That's only one correct messing with you. Nor am I messing with you. Was this intentional?
Um so huge fan of the pod.
Yeah, huge fan of the pod. Who are you?
We'll take a selfie later.
And I'm not the AI guy. Go ahead.
Um so we have 850 employees today at MP. We're going to hire, when we include what we're building out for Apple coupled with what we're going to build with DoD, we're going to need a couple thousand more people easily, not to mention the construction jobs. So, this is a key existential question for all of us as we build out this is where are we going to get the talent? I think what we have found at Mountain Pass, and we hire electricians, maintenance, operators, is you get people in, you train them and then obviously you give people a career. And so we've been training a lot of people and it's a little bit more painstaking but there's absolutely talent out there, people are hungry to do it.
Why do you think it's been so hard to establish that idea? Like meaning you find it straightforward to find good hardworking people to get into these jobs but the thought is always that wow these jobs are not desirable but they really are desirable by many people.
Yeah, absolutely. I mean, our median wage is now pushing $100,000 a year. And there's, relative to some of the opportunities set, these are great jobs.
What's the starting salary? Just curious.
So, it really depends on the job function because, you know, I think the easiest way to think about it is you can certainly as an operator make close to $100,000 a year with us because by the way, everybody's an owner. We have an owner-operator culture. Everyone got stock when we went public in 2020. But somebody coming out of high school, they can make 40, 50, 60k.
Yeah. Or it depends. We can't find enough electricians, we can't find enough maintenance workers.
A maintenance worker can, an electrician, they can make six figures today.
Tell us, you said earlier that you suspect 5 years from now, we're going to look back and this deal with the DoD was a blueprint. Give us other areas of either physical AI or software AI or other markets where you think these public-private partnerships are really necessary to embellish US supremacy.
Yeah. There are some major categories obviously we've all heard about ship building and advanced pharmaceutical ingredients. I mean I think those are important ones and then there are a number of sort of niche areas like industrial diamonds that are important for quantum computing and some of these things that you never would have thought of where there it's a vertical where there might not be a market large enough to need five players but a good public-private partnership can just solve that problem and then there's some other verticals and critical minerals.
Straightforward for you to find the right person within the Trump administration that said of course, this is obvious. Let's sit down and hash this out. Like,
Yeah. Well, and I think that's, our particular deal was led by DoD and so I have to say that the Pentagon leadership is extraordinary. And, you know, this was a mandate though directly from the president to solve this problem. And so, again, they deserve a lot of credit for being, you know, bold here. And to be clear, because I, you know, this story is not out there. Our process, this was, I've never worked so hard in my life. I mean this was like a true aggressive private equity style investment and negotiation.
The transaction documents are public. You can look at that.
So and that's you saying that they're tough.
They are. This was as tough as it gets. Tougher than you know think of any blue chip private equity or distress lender type negotiation. That's what this was. And the key thing was they were going to hold our feet to the fire to execute on an aggressive timeline. They were going to hold our feet to the fire on the cost. And so we're exposed if we get the costs wrong. You know, we're making this investment. And so the key piece of this which I think is a good model for all of us and is actually will be really effective is the goal. I don't speak for them, ask them, but I think their goal was, we're going to take the things off the table that you can't control, mercantilism, certain customer issues. We're going to be held to account for the things that we can control. Our ability to execute, our ability to execute on a good timeline, and our ability to control costs. So when we think about a lot of these historically the government sort of investing in a sector and picking a winner usually there's sort of money given to someone and it's sort of public risk private upside. This is not that. This is private risk, public risk, public upside, private upside. It's a true shared win-win. And again like I said hold me to these words, I hope I'm right on this, but I think to the credit to the Trump administration, I think they will make money on this and have solved the national security.
All right, we appreciate you coming, Jim.
Yeah, it's great. All right. Take care, Jim.
Thanks, Jason. I appreciate it. Yeah. Okay.
Hi, Lisa. Nice to meet you.
Hi. Hi. Hi. Hi. Hi. Well, thanks so much for being here with us today. We don't have a lot of time, so we want to get into it. In April, it was announced that you achieved your first silicon output at the TSMC facility in Arizona on that 2nm line. This administration and the private sector have talked a lot about onshoring semiconductor manufacturing. Would love your thoughts on the on-the-ground experience in Arizona? How's it going? What's not going well? What does America need to do to get this right?
Well, absolutely. First of all, it's a pleasure to be here. Love the theme. I think we're all super excited about winning the US AI race. And I thought if we're going to talk about chips, David, I should actually bring one.
Little bit of show and tell. So, this is our latest generation AI chip. It's our MI 355 chip. 185 billion transistors. Takes about 9 months to build. Lots of technology on it. If I just...
This is 3 nanometer and 6 nanometer. So, lots of different...
I'll be putting this on eBay later.
I'm going to take it with me when I leave. How is that? Thank you. But look to answer your question I think look these AI chips are extremely extremely complex. They have so much technology on it. We're super excited about the progress in US manufacturing. I would say 12 months ago people weren't sure that we could do leading edge manufacturing in the United States. We've been very early in Arizona with TSMC and we did get our first chips out. They're actually four nanometer but what we see from it is where there's a will there's a way and I think all of the conversation about onshoring manufacturing has been super good for the semiconductor industry and frankly for all of us in semiconductors. We're in such an interesting place because chips are so essential to ensuring that we are able to win the AI race that we want to make sure that there's a lot of geographic diversity and capability there.
But the reports out were that TSMC couldn't get good qualified trained employees. They had to bring folks over. Is that accurate? And like again, like if we're going to scale, like what's the order of magnitude we're going from here? Is it 10x, 100x? And how are we going to build a workforce to support this industry which is a completely new industry for America?
And Lisa, you have permission to speak freely.
The best way to say it is no matter when you start something new, it's going to take work, right? It's going to be hard. So sure in the beginning there were some issues of, you know, TSMC has like a formula for how they build and they just rinse and repeat and they've learned how to do that well in Taiwan. So they had to learn how to do it well in the United States. But I have to tell you, we've been super impressed with the progress. And if we look at the main thing that we look at is yields and just how many chips do we get out on a given wafer? And I would say it's equivalent between what we get in Taiwan and what we cost in Arizona because it's unrealistic to think the United States could compete on cost. Am I correct?
We're going to pay a little bit more.
Give us the ballpark. 50% more, 20%?
Not 50% more. I mean look it's going to be more than 5% but let's call it less than 20%.
And how does that impact the business if at all in terms of competition globally?
Well, I think the important thing is I mean just think about like everybody wants a GPU, right? Like if you look across the industry, you really say, the people who are going to win in AI want to have as much compute in their foundation as possible and they want assurance of supply. We want to be able to supply this no matter what happens. And so if you put that in context, the fact that you're not going for the lowest cost every minute of the day, is okay. It's okay. Like obviously we're not going to build, not everything needs to be in the most advanced technologies and so we have a very geographically diverse supply chain. I think Taiwan continues to be important in that view but the focus from this administration on getting onshoring manufacturing in a big way not in a small way I think is very good.
How much time do we have? If there was a disruption, for whatever reason, we can come up with hypotheticals in Taiwan and we were unable to get chips from those factories. What would that look like globally?
Yeah, you have to look across the supply chain, but from a structure standpoint, we all want to keep reserves for those times. But it's months, it's not years.
Lisa, there was two really interesting posts over the last couple of days. One was from Elon where he said in 5 years he projected 50 million H100 equivalents just for xAI and the second was Sam Altman they signed a deal for a four, I think, gigawatt data center, 30 billion a year with Oracle that just portends an enormous amount of chips that are necessary and power. And if you forecast that how do we actually meet all of that what needs to happen that's not happening today inside of the United States to actually do that?
Yeah, it's a great point. I mean that's what we're seeing. We're seeing this incredibly large demand for AI and they're coming from, Sam and Elon are certainly the leaders, a couple of the leaders. There's a lot of demand elsewhere too. I mean if you think about it nations want their own AI so there's very high demand. We're imagining that just the accelerator market so the chips for these AI large computing systems will be like over $500 billion in a couple of years. So very high growth and when you say what do we need to do, it's the entire ecosystem needs to scale up. So, we need to scale up certainly what we're doing in chip design is trying to get chips out as fast as possible. But we're also scaling up the entire manufacturing ecosystem. And as I said, I think the US is going to be a huge piece of it. So, it's not just about the silicon. There's all of the various other pieces of the ecosystem that have to come to the US. And I think look, I think today's AI action plan is actually a really excellent blueprint.
And how do you see the market evolving in these next five or six years? Is it there's a standard set of chips for training, a standard set for inference or do you just see an explosion like a Cambrian explosion of different ASICs, different designs, different use cases?
Yeah, I like that question because I am a believer in there will be diversity of chips. And the reason is there's so many use cases, right? If you think about use cases from, whether you're talking about science or manufacturing or design or backend or, frankly personal AI, I think we're going to see AI in everything that we do. You know, certainly in your phones and your PCs and so you have all these pieces. You're going to have different types of chips that do that. Certainly for the largest systems we tend to believe that you need the most compute you can get and so GPUs are there but lots of ASICs are in the process and we'll see a variety of different chips.
You opened up a really interesting line of questioning there when mainframes were so expensive and then eventually wound up having PCs that were more expensive on their desktop. You alluded to AI being run locally. When would we have a local computer, a laptop, a desktop computer that would have the power we're seeing to run some of these LLM models in your mind? And do you see that as a specific market to go after?
Look, I definitely see the idea that AI will be at every part of our ecosystem is a real thing. I think that's one of the advantages. If you think about the power of AI, you want it everywhere and you want it across all different applications. And I think when you think about PCs today, we're putting significant amount of AI in them to run local models. And why would you want that? It's like, well, maybe I don't want all my personal data all over the place.
On that point, can you make a prediction on when the market for physical AI chips is greater than the market for chips in data centers?
That's a great question. I'm a big believer in physical AI. I still think it's let's call it five years.
You think five years? Is that that fast?
It's at least five years.
So you're saying five plus?
Okay. But that is ultimately the biggest end market. Do you think physical AI becomes the biggest end market?
I think it becomes a significant end market. I think you look at chips in data centers and you look at chips at the edge they're also significant markets.
When you look at the most cutting edge techniques today, EUV lithography, all of this whole stuff to make chips. One of the things that's observable is we're only as good as what humans have been able to invent. And I often ask the recursive question, what happens when the AI is able to invent its own method of manufacturing, different materials, different material sciences, different approaches that we may not necessarily understand? Is any of that R&D happening whether at AMD or in other places? Like how are we trying to get beyond the physical limits of electrons shunting across a junction?
I think this idea that the AI can be extremely smart and extremely capable, like we think about how AI can design the future chips and it will design pieces of it but there's still a creativity of bringing it all together that I think humans are still absolutely at the center of that. So I don't necessarily see the AI designing our next generation GPU, right? But I do see it helping us design the next generation GPU much faster and more reliably. So...
You talked about the need to like reshore more parts of the ecosystem. Obviously you guys are world class chip design, the fabs are getting reshored but how do you think about things like lithography, like does that need to be reshored or like does ASML need to start building machines in the United States or is it okay to have that type of supply chain risk on an ally?
Look, I think we're going to, we have to accept the fact that it's a global supply chain. Like even if you were to reshore, x number of components, you would still have y components that are across the world. I think it's important for us to have our allies together. So that's a key piece of the conversation and ensuring that we have access to the latest generation technologies and that is something that we protect given our intellectual property.
And going to first principles and asking you the open-ended question what should be done about American education. I'm going to ask this a lot today. Assume there's no college, high school, nothing. You arrive in America the situation is what it is today. What do you do? How do you build an education system to prepare the next generation for the evolving workforce?
Yeah, I'm probably a little bit biased as maybe some of your guests are today. I'm a big believer in science and technology background as being sort of the STEM background is so helpful when we think about the future workforce and the earlier we can get into the process I think the better. So some of the work that's being done to kind of revitalize the curriculum I think is pretty important in the next generation workforce. And one of the things when I think about how we win in AI, there's so many aspects of it but ensuring that America is the best place for AI talent is also a key piece of that. So kind of inspiring people when they're young to really study science.
So when you go to bed at night and you think about the best case scenario for this technology and this trajectory we're on which is accelerating and you're enabling what could the world look like in 10 years. We let's say pretty obvious we're hitting artificial general intelligence at this moment. I think we'd all agree we're starting to see that but super intelligence can't be far behind that. I assume you agree with that. Assume we hit that super intelligence. What would the world look like in 10 years in the most optimistic scenario if we do this right?
Well, I think the exciting part about it and I can say this very sincerely, I mean this is the most transformational technology sort of in our lifetimes. I mean that's the way we should think about it.
