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0:00:05 Critical minerals fundamentally underpin everything that we do every day.
0:00:09 It’s in your phone, in your AirPods, your screens, your laptops, everything that we use.
0:00:12 How they’re refined and how they’re mined, that all happens in the background.
0:00:19 There’s not that many massive markets left that have been sort of like largely untapped by technology
0:00:23 and mining sort of screams one of the largest markets in the world.
0:00:26 This is the intersection of geopolitical urgency and tech.
0:00:29 Now we have technology that can actually go and disrupt this.
0:00:33 But also as a talent-based, hard tech company is working in sort of dirty spaces,
0:00:35 willing to go out in the field.
0:00:36 So now’s the time to build this company.
0:00:38 It’s a huge problem.
0:00:40 We have to figure out how to address it.
0:00:43 And that means investing in mining in the U.S. again.
0:00:48 It can take more than 15 years to permit and build a new mine in the United States.
0:00:52 And yet nearly every modern technology we rely on,
0:00:54 from smartphones to fighter jets to AI data centers,
0:00:57 depends on a steady supply of critical materials.
0:01:02 Today, we’re joined by Turner Caldwell, founder of Mariana Minerals,
0:01:07 along with American Dynamism general partner Aaron Pricerite and partner Ryan McIntosh.
0:01:09 Turner spent nearly a decade at Tesla,
0:01:13 working his way upstream from factory design to battery materials and mining.
0:01:19 Now, he’s building a new kind of mining and refining company, vertically integrated in software first,
0:01:22 designed to meet the demand our industrial future requires.
0:01:25 We get into why this industry is so broken,
0:01:28 what it actually takes to turn rocks into usable materials,
0:01:31 and how the U.S. can rebuild its capacity to mine,
0:01:34 refine, and manufacture the things that matter most.
0:01:41 As a reminder, the content here is for informational purposes only,
0:01:44 should not be taken as legal business, tax, or investment advice,
0:01:47 or be used to evaluate any investment or security,
0:01:51 and is not directed at any investors or potential investors in any A16Z fund.
0:01:56 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:02:00 For more details, including a link to our investments,
0:02:04 please see A16Z.com forward slash disclosures.
0:02:12 So, Turner, you’re coming out of stealth with $85 million raised.
0:02:15 Why don’t we get into what are critical minerals and why do they matter?
0:02:20 Critical minerals fundamentally underpin everything that we do every day.
0:02:22 And that’s why we’re personally really excited about it.
0:02:28 But it’s not just aerospace, energy, renewable energy, battery, energy storage systems,
0:02:33 the massive growth in AI that’s happened in the last 12, 18, 24 months,
0:02:34 and defense, obviously.
0:02:36 But it’s also everything that we use every day, right?
0:02:39 Like, it’s in your phone, in your AirPods, your screens, your laptops.
0:02:43 And so it really crosses everything that we use.
0:02:46 But where they’re produced and how they’re refined and how they’re mined,
0:02:48 that all happens in the background.
0:02:51 And so it’s something that really does need to be brought to the foreground,
0:02:53 something that we need to support more and more of.
0:02:57 And it’s a long chain to go from digging something up
0:03:00 to go all the way through to something that can actually be deployed in an end product.
0:03:02 And so excited to talk about that.
0:03:06 Well, why don’t we get into how do we turn rocks into batteries or magnets,
0:03:07 and why is that so important?
0:03:09 Yeah, so it starts with mining, obviously.
0:03:11 Well, it actually starts with exploration.
0:03:11 But that’s a-
0:03:12 Yeah, you’ve got to find the rocks in the first place.
0:03:12 That’s right.
0:03:14 You’ve got to find the rocks in the first place, which is hard to do.
0:03:17 And there’s a lot of awesome companies that are working on trying to condense that timeline.
0:03:22 But once you do find them, you have to get that asset or that resource permitted to extract.
0:03:23 You develop a mining plan.
0:03:24 You have to mine it.
0:03:28 And when those rocks come to the surface, you have to separate ore from waste,
0:03:30 which is something that is not as trivial as people might expect.
0:03:32 And then you go through a concentration step.
0:03:34 So the ores will come to the surface.
0:03:37 They’ll be less than 1%, definitely less than 5% concentration,
0:03:39 unless you have this world-class deposit.
0:03:41 And you’ll typically go through a concentrating step.
0:03:44 So that can be mechanical, it can be thermal, it can be chemical.
0:03:46 And that gives you an intermediate product.
0:03:48 And those intermediate products kind of move all over the world
0:03:50 and typically go to refining assets.
0:03:55 The refining operation effectively goes from anything that is like a 10% concentrate
0:04:00 to a 50% intermediate product and turns into a high-purity metal.
0:04:03 And then you go into a specialty chemical.
0:04:06 And so that’s this intermediate product where you go through another chemical process
0:04:09 to either make a metal sulfate or a metal hydroxide salt.
0:04:13 And then you will convert that into an engineered material, which is the next step.
0:04:17 And that in electrochemical systems and batteries, you’ll have cathode materials,
0:04:21 you’ll have anode materials, and there the morphology and the electrochemical performance
0:04:22 in the system is really important.
0:04:24 And then you’re ready to deploy into a battery cell.
0:04:27 And then you’ll go into a module, and then you’ll go into a pack,
0:04:29 and then you’ll go into a car or go into a stationary storage product.
0:04:34 And on the magnet side of things, similarly, you’ll get to a refined rare earth product.
0:04:36 And it’s a long list of rare earths.
0:04:39 They often get bundled into one group, but it’s important to break them out.
0:04:42 And then the common way of making magnets, there’s a few flow sheets,
0:04:45 but you’ll slurry it, you’ll get the right blend of the different rare earths
0:04:46 that you’re trying to put in.
0:04:49 You’ll cast that, you’ll center it, and then you’ll go through a fairly intricate
0:04:53 and high-precision machining process to get the geometry that you want
0:04:55 with the tolerances that you need before you can deploy that into magnets
0:04:56 and eventually into motors.
0:05:02 How specific is it for a given site, given concentration and other sort of waste products?
0:05:04 How dynamic is it?
0:05:07 Is one rare earthmine going to be a similar process to another,
0:05:10 or is there going to be a very sort of bespoke setup?
0:05:11 It’s very bespoke.
0:05:14 And it’s actually part of the problem and what makes the minerals industry so complicated
0:05:18 is that the flow sheet, which is ultimately how you go from the ore all the way through
0:05:22 to the refined metal, is designed for that specific asset.
0:05:25 You will have concentrations of impurities that you have to manage.
0:05:28 The concentration, obviously, of the target metal is different.
0:05:32 And there’s like a library of metallurgical unit operations
0:05:36 that are kind of all stitched together to build a refining operation or a processing operation.
0:05:40 But how those are stitched together, that’s bespoke for the individual unit operation
0:05:43 and tied to the kind of chemical metallurgist process engineer
0:05:45 that designed the circuit in the first place.
0:05:49 So there’s a lot of like human impact on what that flow sheet ultimately looks like.
0:05:50 But yes.
0:05:54 And I imagine very hard to change as the nature of the ore changes as you mine a site.
0:05:55 That’s right.
0:05:59 And so part of what we’re working on and what we’ll talk about a little bit later, I’m sure,
0:06:02 is how do you design circuits that have a little bit more flexibility
0:06:06 to be able to process ore as it changes over time as you mine through the ore body?
0:06:10 Because one mine does not actually have consistent ore coming out of it.
0:06:11 The earth is heterogeneous.
0:06:12 The ore grades are changing.
0:06:13 The impurity concentrations are changing.
0:06:17 There are different ore zones that have different properties in how they are floated
0:06:19 or how they’re concentrated, how they perform in a leaching circuit.
0:06:23 And all of those things are custom built for a specific asset.
0:06:24 One more question on this.
0:06:28 What are the types of job titles, like backgrounds of people working in this space?
0:06:32 I imagine for the supply chain you just described, it’s very different types of people,
0:06:35 very different backgrounds, but they all have to ultimately work together.
0:06:36 But can you talk a little bit about that?
0:06:40 Yeah, that’s one of the big hard parts is you have geologists, you have geophysicists,
0:06:45 you’ll have mining engineers, you’ll have geotechnical engineers, you’ll have process engineers,
0:06:49 chemical engineers, chemists, metallurgists, mechanical engineers, structural engineers, civil engineers.
0:06:51 It’s the whole gambit.
0:06:55 Plus the long tail of workers on site who are moving things from point A to point A.
0:06:59 That’s right, which also have a super diverse skill set because you need everything from the mining engineers
0:07:04 and the chemical engineers and the geologists that sit around to operate the asset in addition to the folks
0:07:07 that have to kind of manage the back office, which is something that often gets overlooked
0:07:10 when we’re thinking about successfully building and operating a complex circuit.
0:07:12 Did you always love rocks?
0:07:15 Did you always know that you were going to start a mining company?
0:07:16 Yeah, so kind of a funny story.
0:07:22 The day that I graduated from college, the like urge that I had was to just move to Australia
0:07:23 and try to find a job in a mine.
0:07:29 I did not act on that urge and instead started at Tesla roughly 10 years ago now.
0:07:32 And I started out working on factory design, factory construction,
0:07:37 and actually slowly over that nine plus year period worked my way upstream in the value chain.
0:07:41 So I worked on factory design and construction, then started working on battery cell manufacturing,
0:07:43 spent a lot of time in Japan with Panasonic,
0:07:45 who’s our primary battery cell manufacturing partner,
0:07:50 working on incremental improvements to their legacy battery cell manufacturing systems.
0:07:54 The like pull has always been big things for me, like large scale infrastructure
0:07:57 that has a large impact on the world.
0:08:00 I mean, if you want to have a big impact on the world, you have to build things at scale.
0:08:01 That is, that’s how you get to impact.
0:08:03 But yeah, so I was working on battery cell manufacturing
0:08:07 because I was spending a lot of time in Asia, started to explore the supply chain,
0:08:11 was building some of the early techno-economic models of how cathode materials are made,
0:08:14 how anod materials are made, and the balance of the components that go into a battery cell.
0:08:16 And ultimately, this was just following cost.
0:08:19 It was when I was working on factory design and construction,
0:08:22 the most expensive thing was actually the equipment that goes inside the factory.
0:08:24 Then when we started working on cell manufacturing,
0:08:28 kind of realized that the expensive part of making cells is the stuff that goes inside the cells.
0:08:29 And then as you start getting further and further upstream,
0:08:35 you realize that the primary driver of cost is the metals that are going into the engineered materials
0:08:37 that then go into the cells and then eventually go into the battery.
0:08:43 And so, started kind of digging much deeper into why metals are so expensive.
0:08:49 And what you kind of run into is that there’s this interesting incentive misalignment that exists
0:08:52 between the customer and the producer of metals.
0:08:57 Like in the mining industry, more demand, this is totally different than manufacturing,
0:09:00 more demand if you have a higher volume, the expectation is that the price goes up.
0:09:05 And because it’s a constrained supply, and so the pricing dynamics are totally different
0:09:08 than manufacturing companies where higher volume means lower cost.
0:09:11 And as you are scaling up and capturing economies of scale,
0:09:14 you’re starting to drive down the cost that you can then transfer to your customers.
0:09:17 And like that expectation doesn’t really exist in the mining industry.
0:09:18 If you want more of it, it’s going to cost more.
0:09:19 There’s no economies of scale.
0:09:21 There are economies of scale on the operations side of things.
0:09:22 Got it.
0:09:24 There are not economies of scale as the customer.
0:09:24 Got it.
0:09:29 Which is kind of an interesting dynamic and is completely contrary to how manufacturers
0:09:33 are used to pricing their cost of goods, like their input materials.
0:09:36 Where if you are buying more and you are scaling up,
0:09:38 you expect your suppliers to also capture economies of scale
0:09:39 that then translate into lower pricing,
0:09:42 which then enables you to price lower for when you sell the customers.
0:09:45 And so that incentive misalignment was a big one that jumped out
0:09:47 and that only really kind of starts to come to the surface
0:09:50 when you start to actually engage with the mining companies.
0:09:53 But what fascinated me about the mining industry
0:09:57 is that you are effectively solving problems at micron scale to start.
0:10:00 You have to figure out how you extract.
0:10:03 You have an ore that has 1% of a target metal.
0:10:06 And you are trying to figure out how do you extract that 1%
0:10:07 and get it to a 100% purity.
0:10:09 And that fundamentally starts at the atoms.
0:10:13 And then you have to take a process that you develop
0:10:15 that starts at micron scale
0:10:17 and then deploy kilometer scale infrastructure.
0:10:20 And going back to the thing that was exciting, which is scale,
0:10:23 is that opportunity to work across those scales, which is exciting.
0:10:25 Something I always found interesting about Tesla,
0:10:27 especially early days working with Panasonic,
0:10:30 that a lot of the know-how, the process knowledge came from Asia.
0:10:32 Spending a lot of time in Asia, just be curious,
0:10:34 culturally and just looking at scale
0:10:37 as they sort of built out a lot of the early battery ecosystem
0:10:40 and then farther upstream, what did you see there?
0:10:41 Is it just more chemical engineers?
0:10:44 Is it more support for that industry?
0:10:46 Yeah, I think in the battery cell world,
0:10:50 the precision at which you need to manufacture the product,
0:10:53 like the tolerances on the final battery cell,
0:10:55 require a level of rigor and attention to detail
0:10:57 that does have a cultural aspect to it.
0:10:58 Like semiconductors.
0:10:58 Yeah, exactly.
0:11:00 And so that was a big one.
0:11:02 But also, it’s a long-term investment.
0:11:04 In Japanese, it’s Kaizen, right?
0:11:06 Where you’re like gradually improving over time.
0:11:08 And in those like super high precision,
0:11:11 super high throughput industries,
0:11:14 taking big swings where you make like a radical change
0:11:15 to one unit operation,
0:11:18 that didn’t really happen in like those companies.
0:11:21 It was much more of an iterative improvement to the systems
0:11:24 that fundamentally eventually enabled you to get costs down.
0:11:25 But yeah, the labor pool is a big piece.
0:11:27 And I think some of it is definitely cultural.
0:11:32 Your time at Tesla, like Tesla famously vertically integrated very early.
0:11:34 You’re building a vertically integrated mining company,
0:11:36 which we’ll get into more details about later.
0:11:39 But like what did working at Tesla teach you about vertical integration
0:11:40 and why it matters?
0:11:44 Yeah, I think as we started to scope more and more vertical integration,
0:11:47 even like outside of like going further upstream in the supply chain,
0:11:50 the thing that’s really interesting about vertical integration is you fundamentally
0:11:55 are thinking about the incentive structure that exists between kind of yourself and a partner.
0:12:00 And so Tesla had to vertically integrate early because people just weren’t making the parts that were needed.
0:12:02 It was a do or die.
0:12:03 There was no incentive.
0:12:06 There was no market for people to build the kind of like subcomponents that were required.
0:12:10 And so ultimately Tesla had to vertically integrate from day one.
0:12:13 And then the things that pushed increasing amounts of vertical integration
0:12:15 ultimately was the incentive structure misalignment
0:12:19 where suppliers and partners weren’t incentivized to invest in scale
0:12:21 at the rate that we wanted them to invest in scale.
0:12:25 They weren’t incentivized to innovate at the pace that we wanted them to innovate.
0:12:27 And so you end up kind of insourcing a lot of that development
0:12:30 that enables you to get to the product specs or the component specs that you want.
0:12:32 And then it takes a lot of guts.
0:12:35 Because at the end of the day, when you vertically integrate,
0:12:41 you are transferring the risk profile of your partner kind of into your new expanded risk profile.
0:12:45 And so you need to be really confident or at least believe that you are a better position
0:12:47 to kind of take on and manage that risk profile.
0:12:50 When you were at Tesla and looking at and developing relationships
0:12:51 with all these global mining companies,
0:12:54 as Tesla was scaling and looking for suppliers,
0:12:58 like what were some of the key issues that you noticed from a market perspective?
0:13:03 And then ultimately what sort of led to Tesla pursuing sort of like further vertical integration?
0:13:05 Yeah, I think the incentive misalignment piece,
0:13:09 between the industries and between kind of like a commodity industry or the mining industry
0:13:11 and the manufacturing industry,
0:13:14 was the big misalignment that existed between the industries.
0:13:20 The degree to which automation was absent was pretty interesting.
0:13:24 There’s a long period of time where mines make no money, right?
0:13:28 And so a lot of capital goes into the exploration phase,
0:13:29 it goes into the development phase.
0:13:32 What a lot of people don’t realize is that when you start the mine,
0:13:36 there’s actually sometimes like years where you are just getting through the waste
0:13:38 or drilling a shaft to get to the ore deposit.
0:13:43 And so any additional capital intensity like associated with automation,
0:13:45 oftentimes the capital starts to get tired.
0:13:50 And that additional automation equipment kind of falls by the wayside.
0:13:53 And if you have the people there that can drive the trucks or drive the excavators
0:13:55 or run the drill rigs, like you’ll take that.
0:13:57 And we’re at this interesting inflection point now
0:13:59 where those people are less and less available.
0:14:02 The mining industry has kind of been taking it on the head for a long time.
0:14:05 It’s not been a sexy industry that everyone wants to go into.
0:14:07 And so the labor pool is contracting, it’s shrinking,
0:14:10 and it’s both the trades and it’s the engineering skill sets.
0:14:14 And the first things that mining companies say now
0:14:16 is that the labor pool is one of the biggest challenges
0:14:17 that they’re trying to solve for.
0:14:18 So that was apparent.
0:14:22 And on top of that, these mines are not exactly in downtown Manhattan.
0:14:23 They are in remote locations.
0:14:25 Where have you gone? Have you been on site before?
0:14:28 Yeah, of course. Indonesia, Australia, China.
0:14:29 What is it actually like?
0:14:32 People see pictures. What is actually going on?
0:14:35 It’s a lot calmer than you might expect.
0:14:37 You’re usually working a couple of faces
0:14:40 and you have excavators or front-end loaders
0:14:41 that are picking up dirt.
0:14:42 They’re taking them to the unit operation.
0:14:45 And it’s not as rambunctious and crazy
0:14:46 as you might expect a mine to be.
0:14:49 And that’s in Australia and in Canada.
0:14:52 It’s not this buzzing atmosphere.
0:14:55 In developing countries, it’s a little different.
0:14:56 There’s definitely a different degree of automation.
0:14:59 Obviously, we’ve come a long way from people with picks and shovels.
0:15:01 And so when I say automation is absent,
0:15:03 it doesn’t mean there aren’t heavy haul machinery
0:15:04 that is driving around the sites.
0:15:06 But there’s a lot more people activity
0:15:10 when you go to operations that are in Indonesia or in Africa.
0:15:12 But yeah, been to most continents.
0:15:15 Why did you leave Tesla to build Mariana?
0:15:20 I spent a long time kind of like building businesses within Tesla.
0:15:22 It was early on the cell manufacturing side,
0:15:24 was early on the cathode manufacturing side,
0:15:25 was early on the refining side of things.
0:15:31 And what really excited me was always pushing further and further upstream.
0:15:34 And I do think that we are at this critical inflection point
0:15:38 where not only is the labor pool going in the opposite direction of demand
0:15:39 in the mining industry,
0:15:44 but AI and ML are getting to the point where it hasn’t been that long, right?
0:15:47 Like the AlphaGo moment was kind of in 2015, 2016.
0:15:50 And people were using reinforcement learning to kind of like,
0:15:54 there’s a paper from 2008 on reinforcement learning for like helicopter control.
0:15:58 But we’re at this point where the compute and machine learning,
0:16:02 reinforcement learning do really enable you to go know humans in the loop
0:16:04 and how a lot of these plants are controlled.
0:16:06 And as you like build more of that large scale infrastructure
0:16:09 and see the problems that humans have to solve on a daily basis,
0:16:11 it becomes like pretty obvious that these are problems
0:16:14 that humans aren’t best positioned to solve.
0:16:16 Like these are large multivariable optimization problems
0:16:19 that RL is like perfectly poised to solve.
0:16:21 And then on the construction side,
0:16:23 that is like an entirely different story.
0:16:26 I think construction, there’s a lot of workflow automation opportunities
0:16:28 and there’s also tons of menial tasks
0:16:31 where people are fat fingering data between databases.
0:16:34 The data systems are completely disaggregated
0:16:38 and LLMs are presenting this opportunity where we can start to,
0:16:40 and again, this is like a two-year thing really,
0:16:41 and it’s just going to get better.
0:16:44 And so the opportunity to build kind of like from scratch,
0:16:49 no legacy systems, and have some control over the destiny of the company
0:16:51 that we’re building, that’s just an exciting opportunity.
0:16:54 What is the status quo in the industry today?
0:16:56 What does like the BHP and the RIOs of the world do?
0:16:58 For like some of the stuff you’re talking about,
0:17:00 like from a software perspective, like internally.
0:17:02 They have digital innovation arms.
0:17:04 They do have digital innovation arms.
0:17:08 I think that the Freeports and the Rio Tintos and the BHPs,
0:17:09 they outsource a lot of that.
0:17:12 I think that they’ve like gradually started to hire more and more folks
0:17:13 that can do more internal things,
0:17:15 but you have McKinsey, you have Palantir,
0:17:17 that basically act as consultants.
0:17:20 And they will look at the large data sets
0:17:21 and they’ll kind of provide recommendations.
0:17:23 Some percentage of those recommendations,
0:17:26 oftentimes sub-50%, are taken.
0:17:31 And what’s interesting about what you want from the ML models
0:17:33 or the RL models is that you actually want them to tell you
0:17:34 to do things that are counterintuitive
0:17:37 because humans are naturally going to find
0:17:39 like a local optimal operating condition.
0:17:43 And it’s very risky to take shots outside of something
0:17:44 that is currently working
0:17:45 where there’s billion dollars on the line.
0:17:48 And that culture of trusting
0:17:51 the counterintuitive recommendation from the model
0:17:53 is one that we want to try to build.
0:17:54 And it’s hard to build that within large companies.
0:17:56 I think on the construction side,
0:17:57 when they build new projects,
0:18:00 they’re building five, $10 billion projects.
0:18:02 And so they are always bringing in an EPC
0:18:04 and kind of like throwing that over the fence
0:18:04 to the EPC.
0:18:09 In the mining industry where it is a bespoke plant,
0:18:11 like it is custom and you kind of need to think about
0:18:13 the refinery and the mine
0:18:16 and the processing facility as the product.
0:18:17 And when you outsource that,
0:18:18 you lose a lot of control
0:18:20 of what you eventually are going to inherit and operate.
0:18:24 And then EPCs, that model has shifted away a little bit
0:18:26 from kind of like a turnkey,
0:18:27 like we’ll deliver you a project.
0:18:30 It’s kind of moved towards selling hours
0:18:33 and like selling man hours and selling reports,
0:18:34 especially in the mining industry
0:18:37 where it’s like they’ll do a pre-feasibility study,
0:18:38 they’ll do a feasibility study.
0:18:40 And so there’s a lot of over the fence
0:18:41 and outsourcing that happens in the large companies.
0:18:45 And some of that comes from like the talent acquisition
0:18:47 challenge that the mining industry
0:18:48 has faced over the last 20 years.
0:18:50 Again, the mining industry has not been
0:18:53 this magnet for talent.
0:18:55 And what that means is that
0:18:56 even if they are able to hire
0:18:58 kind of like the best in class machine learning engineers
0:18:59 and the best in class software engineers,
0:19:00 they’re not going to stay.
0:19:02 They’re going to run into the wall of bureaucracy
0:19:05 and they’re going to have higher paying opportunities
0:19:07 in ZAS, FinTech, ad tech,
0:19:08 and they’re going to go chase that.
0:19:11 And so it’s not just attracting talent,
0:19:11 it’s retaining talent.
0:19:13 That has been a big challenge in the mining industry
0:19:16 and that forces kind of like an outsourcing
0:19:17 of a lot of the things that should be core today.
0:19:20 I mean, we’ve seen this from the investor side.
0:19:23 Like there are a lot of really exciting new technologies
0:19:25 being developed for mining
0:19:27 and a lot of incredibly impressive startups
0:19:29 that are building for various pieces
0:19:31 of the mining lifecycle journey,
0:19:33 whether it’s autonomous vehicles or drilling
0:19:37 or other various software and hardware tools for mining.
0:19:39 But the challenge seems to be like,
0:19:43 how do you get these kind of calcified large incumbents
0:19:45 who operate in a very decentralized way,
0:19:47 have very low risk appetite
0:19:51 and not a strong internal culture or affinity for tech?
0:19:52 Like how do you get them to adopt them quickly?
0:19:53 Like if you’re a young startup,
0:19:57 you’re sort of at the beck and call of this behemoth
0:20:00 and you have very little control over your own destiny,
0:20:02 which I think has made it really hard for tech
0:20:04 to kind of penetrate this market up until now.
0:20:05 That’s at least what we’ve observed.
0:20:08 Yeah, I mean, calcified is a good word.
0:20:10 I think the way that there’s construction companies
0:20:11 and mining companies
0:20:12 and really a lot of big companies
0:20:15 is that the way that they’ll identify and evaluate risk
0:20:17 is fixing the status quo
0:20:20 or making like a step change improvement in the status quo
0:20:22 kind of requires doing like a thousand things.
0:20:25 But you’ll evaluate risk on each individual thing
0:20:26 of that thousand things.
0:20:29 And the downside of each individual thousand things
0:20:30 is that the plant goes down,
0:20:33 which is a multimillion dollar event.
0:20:36 And so you’re really not incentivized to change things.
0:20:38 Like even small changes could result
0:20:39 in multimillion dollars of loss.
0:20:42 And you need to kind of approach it of like,
0:20:44 how do I do the thousand things all at once
0:20:47 so that I’m not stacking incremental returns on innovation
0:20:49 with the same risk every single time?
0:20:51 And that’s where kind of like spot technical solutions
0:20:53 are challenging to sell into the mining industry.
0:20:54 And they’ll do pilots.
0:20:55 They’ll definitely do a pilot.
0:20:56 Like there’s no skin off their back
0:20:57 to do kind of like a pilot,
0:20:59 but you’ll end up doing a lot of pilots.
0:21:02 And because they don’t build enough plants
0:21:03 kind of sequentially,
0:21:07 like they’ll build one big mine every five years, if that.
0:21:09 And there just aren’t a lot of opportunities
0:21:12 to get into a commercial scale application.
0:21:13 And if you don’t time it perfectly,
0:21:15 where like your pilot plant was five years before
0:21:17 the commercial scale plant was planned for,
0:21:19 like you’re not going to be in that one.
0:21:20 So you’ll be in the next one,
0:21:20 which is five years later.
0:21:23 And so the pace at which the industry moves
0:21:25 in terms of deploying commercial scale infrastructure
0:21:27 means that there just isn’t a lot of opportunity
0:21:29 to get new tech into commercial scale applications.
0:21:31 And so there’s a lot of folks
0:21:32 that are doing like SaaS products,
0:21:34 which is kind of the lowest cost way
0:21:36 to generate uplift in a mining project
0:21:37 or a minerals refinery.
0:21:41 And the like barrier there is ultimately
0:21:43 how do you get the operators to trust
0:21:45 the SaaS tool from this small company
0:21:47 that is trying to kind of tell you how to run a plant.
0:21:49 And the culture is typically,
0:21:50 don’t touch my things,
0:21:51 don’t touch my cash register.
0:21:53 And what do you all know about running a mine?
0:21:54 And it does stack up.
0:21:56 I’ve been calling it a death spiral
0:21:57 for a lot of the folks
0:21:59 that are trying to sell into the mining industry
0:21:59 because it’s hard.
0:22:02 Just to like step back a little bit
0:22:03 on the geopolitical context,
0:22:04 the stuff you’re describing,
0:22:06 I think very obviously true
0:22:07 with a lot of Western companies,
0:22:08 but at the same time,
0:22:09 a lot of Chinese companies
0:22:12 that have sprouted over the last 20, 30 years
0:22:13 have grown rapidly.
0:22:15 Curious, why do you think that is?
0:22:17 Yeah, I mean, I think that there’s like
0:22:20 a lot of top-down and early recognition
0:22:22 that critical minerals were going to be critical
0:22:24 and needed to be supported.
0:22:25 And so like shouldn’t kind of like
0:22:27 the everything around policy
0:22:29 and everything around kind of like supporting companies
0:22:31 to go and deploy both infrastructure domestically
0:22:33 and infrastructure internationally
0:22:35 to kind of like secure critical minerals,
0:22:37 build infrastructure that secures a position.
0:22:38 Like that has definitely happened.
0:22:40 But I think that what people often
0:22:41 don’t talk about enough
0:22:44 is that the talent pool is insane.
0:22:46 Like it is not just a large talent pool.
0:22:49 It is a large, skilled, experienced talent pool.
0:22:51 I was in Indonesia in February
0:22:53 and was kind of visiting
0:22:56 one of the recent Chinese nickel refining operations.
0:22:58 so they buy ore.
0:22:59 They also have some mining operations.
0:23:02 But they had 13,000 people on site
0:23:04 during construction and commissioning.
0:23:07 And if we were building a refinery in the U.S.,
0:23:08 which we did,
0:23:10 it’s hard to mobilize a tenth of that realistically.
0:23:12 And it’s not just about the number of people.
0:23:14 It’s about being able to iterate
0:23:15 on every individual work front
0:23:17 as fast as humanly possible.
0:23:19 And we just don’t have that label.
0:23:21 15 years ago or 20 years ago,
0:23:23 would the same companies that were big now
0:23:24 have been big then?
0:23:26 Where is kind of the evolution of the space event?
0:23:27 Yeah, I think that there’s been
0:23:28 like a clear splintering
0:23:30 on kind of who does the exploration
0:23:32 and who does the development.
0:23:32 Like right now,
0:23:33 the industry is set up
0:23:34 where junior mining companies,
0:23:35 which don’t mine,
0:23:36 they explore,
0:23:37 go and sometimes
0:23:38 they’ll get maybe a resource
0:23:40 from a major mining company
0:23:41 that’s held in their portfolio
0:23:41 for a long time.
0:23:44 But it’s like a different risk-reward profile
0:23:45 than what the mining majors
0:23:46 are ultimately looking for.
0:23:48 And so you have this junior mining ecosystem
0:23:50 that sometimes is well-funded
0:23:51 and sometimes is competing for capital
0:23:53 with the cannabis industry in Canada.
0:23:55 And they’re taking shots in the dark.
0:23:56 And there’s a lot of work
0:23:57 that’s going into trying to
0:23:59 make that exploration activity
0:23:59 more intelligent,
0:24:00 streamline it,
0:24:02 drill less exploration holes
0:24:03 while still being able
0:24:04 to interpolate
0:24:05 or extrapolate
0:24:06 what is in between
0:24:06 those drill holes.
0:24:07 But it’s a,
0:24:08 you’re going out
0:24:10 in kind of the middle of nowhere.
0:24:11 Either it’s really far north
0:24:12 in like the Arctic Circle
0:24:13 or the Yukon
0:24:14 or it’s overseas in Africa
0:24:15 and you’re doing exploration
0:24:16 or it’s in Southeast Asia
0:24:17 or in South America.
0:24:19 And those folks,
0:24:20 like they have one job,
0:24:22 which is to define a resource
0:24:23 and pump up its value sufficiently
0:24:24 to flip it to a major.
0:24:26 And there’s a lot of companies
0:24:27 that aren’t able
0:24:28 to discover a resource
0:24:30 that is either large enough
0:24:31 because the big mining companies,
0:24:32 like they want to deploy
0:24:34 large amounts of capital.
0:24:34 We’re talking about
0:24:36 like multi-billion dollar investments.
0:24:37 And so they won’t really look
0:24:38 at projects
0:24:40 that don’t have the scale
0:24:41 that kind of enable them
0:24:41 to underwrite
0:24:42 their own inefficiency.
0:24:43 Like they want to build
0:24:44 really large infrastructure
0:24:45 that enables them
0:24:46 to capture the economies of scale.
0:24:48 And so there’s actually
0:24:48 a really long tail
0:24:49 of mining projects
0:24:51 that don’t have the scale
0:24:52 that would justify
0:24:53 getting acquired
0:24:53 at a major premium.
0:24:55 And so they’ll go
0:24:56 into this kind of orphan period
0:24:57 is what it’s called
0:24:57 in the industry.
0:24:59 And it’s hard for them
0:25:00 to break out
0:25:00 of that orphan period.
0:25:01 And that’s kind of
0:25:02 where we see our ability
0:25:03 to kind of step in
0:25:04 as a more efficient
0:25:05 builder and operator
0:25:06 is kind of take these
0:25:08 what the industry calls
0:25:08 subscale assets,
0:25:10 but we see metal there,
0:25:11 and come in
0:25:11 and bring those
0:25:12 into production
0:25:12 as we kind of
0:25:13 are building the platform
0:25:14 and then eventually
0:25:15 scale into the same scale
0:25:16 that the big mining companies
0:25:16 are operating at.
0:25:17 Your thesis being
0:25:18 that you can
0:25:21 get the metal out
0:25:22 and process it
0:25:22 into a product
0:25:23 that you can sell
0:25:24 more efficiently
0:25:26 than the majors
0:25:26 such that it’s
0:25:27 economically viable.
0:25:29 To offset the scale advantage.
0:25:29 Yeah.
0:25:29 Yeah.
0:25:30 I think this might be
0:25:31 a good opportunity
0:25:32 then to talk
0:25:32 a little bit more
0:25:33 about what is
0:25:35 Mariana’s product.
0:25:36 You said
0:25:37 a few minutes ago
0:25:38 you’re not a SaaS product.
0:25:39 What does it mean
0:25:41 to be a diversified
0:25:43 metal and minerals company,
0:25:44 technology-enabled
0:25:45 mining company?
0:25:46 Give us a little bit
0:25:46 more detail.
0:25:48 So we’re a
0:25:49 vertically integrated
0:25:50 software-first
0:25:51 minerals project
0:25:51 developer and operator.
0:25:52 And so we focus
0:25:53 on the back end
0:25:54 of the minerals
0:25:55 value chain,
0:25:56 which is actually
0:25:57 doing the detailed
0:25:58 engineering,
0:25:58 getting through
0:25:59 the permitting,
0:26:00 building the asset,
0:26:01 commissioning the asset,
0:26:02 and then operating
0:26:02 the asset.
0:26:04 And going back
0:26:05 to some of what
0:26:05 we were talking about
0:26:06 around the labor pool,
0:26:08 like those labor pool
0:26:09 shortages exist in construction
0:26:10 and they exist in mining.
0:26:11 Like they’re felt
0:26:11 very,
0:26:12 very intensely.
0:26:13 And so our
0:26:14 fundamental thesis
0:26:14 is that
0:26:16 with a contracting labor pool,
0:26:17 you have to start
0:26:18 with an awesome team.
0:26:19 The table stakes
0:26:20 is that you build
0:26:20 an awesome team.
0:26:21 But how do you
0:26:23 enable 200 people
0:26:24 to do what
0:26:24 10,000 people
0:26:25 are needed
0:26:25 to do today,
0:26:27 at least on the
0:26:27 parent co side
0:26:28 of things.
0:26:29 And that comes from
0:26:30 leveraging the
0:26:31 recent advances
0:26:32 in LLMs
0:26:33 to automate
0:26:34 workflows in the
0:26:34 construction side
0:26:35 of things,
0:26:35 in the engineering
0:26:36 side of things,
0:26:36 in the procurement
0:26:37 side of things,
0:26:38 which take an
0:26:38 insane amount
0:26:39 of time.
0:26:39 You make a lot
0:26:40 of lists and you
0:26:41 fat finger a lot
0:26:41 of data between
0:26:42 databases.
0:26:43 And that is all
0:26:44 about reducing
0:26:46 churn in construction.
0:26:47 Churn and latency.
0:26:48 Latency is one
0:26:49 thing that I think
0:26:50 people sometimes
0:26:50 don’t appreciate
0:26:52 from status quo
0:26:53 construction,
0:26:53 like large-scale
0:26:54 megaprojects,
0:26:55 is that what’s
0:26:55 happening in the
0:26:56 field and what
0:26:57 the back office
0:26:57 kind of sees or
0:26:58 what the executive
0:26:59 team sees or what
0:27:00 the project director
0:27:01 sees, there’s a
0:27:02 three-week lag
0:27:02 generally for
0:27:03 really large
0:27:04 construction projects
0:27:04 where you are
0:27:05 trying to aggregate
0:27:06 data from all
0:27:06 the different
0:27:08 contractors and
0:27:08 all the different
0:27:09 parts of the
0:27:10 facility into a
0:27:11 consolidated integrated
0:27:12 schedule, which
0:27:12 you can then make
0:27:13 decisions off of,
0:27:14 like how do I
0:27:14 prioritize what I’m
0:27:15 doing today?
0:27:16 And the way you
0:27:17 run in between
0:27:18 those three weeks
0:27:19 is people stand
0:27:20 in circles every
0:27:20 morning and they
0:27:21 say, what are you
0:27:21 doing today, what
0:27:22 are you doing
0:27:22 today, what are
0:27:22 you doing today?
0:27:23 And they go off
0:27:24 and they do the
0:27:24 thing, they’ll send
0:27:25 like a very brief
0:27:26 kind of progress
0:27:28 report back, and
0:27:29 it takes a long
0:27:30 time to then take
0:27:30 those progress
0:27:31 reports and
0:27:31 actually measure
0:27:33 progress so that
0:27:34 you can reevaluate
0:27:35 priorities and
0:27:35 understand kind of
0:27:36 like how the
0:27:36 project is trending.
0:27:37 And so we’re
0:27:38 really trying to
0:27:38 accelerate and
0:27:39 democratize access
0:27:40 to data,
0:27:42 fundamentally, and
0:27:43 run construction
0:27:44 projects like
0:27:45 manufacturing facilities.
0:27:46 And it starts
0:27:46 there.
0:27:47 And the reason
0:27:47 construction and
0:27:48 mining are so
0:27:49 kind of integrated
0:27:49 and some people
0:27:50 might disagree with
0:27:51 me, but like a
0:27:52 mining project is a
0:27:53 big civil construction
0:27:53 project.
0:27:54 It just never ends.
0:27:56 It’s more like a
0:27:58 deconstruction project.
0:27:58 Yeah, that’s fair.
0:28:00 Well, you do, when
0:28:00 you’re, you have to
0:28:02 construct piles.
0:28:02 And you’re building
0:28:03 piles.
0:28:03 Okay.
0:28:04 But there’s actually a
0:28:05 lot of similarities in
0:28:06 kind of like just
0:28:07 moving the dirt for
0:28:07 like site prep.
0:28:10 And the same kind of
0:28:11 like software stack that
0:28:12 is enabling you to get
0:28:13 feedback from the
0:28:14 field live is the
0:28:15 same thing that the
0:28:16 mining industry
0:28:16 struggles with.
0:28:18 Mining companies will
0:28:19 lose equipment,
0:28:20 especially in
0:28:20 underground mines that
0:28:21 are like these like
0:28:21 deep mazes.
0:28:22 And the industry is
0:28:23 getting better at
0:28:24 having like actual
0:28:25 location sensing on
0:28:25 like where the
0:28:26 equipment is.
0:28:27 But losing equipment
0:28:28 in a mine is like
0:28:28 how it used to be a
0:28:29 super common thing.
0:28:30 But, you know, we
0:28:31 start with construction
0:28:32 and then we start to
0:28:33 get into the second
0:28:35 core software stack is
0:28:35 what we’re calling
0:28:36 PlantOS.
0:28:37 The construction stack
0:28:38 is Capital Project
0:28:38 OS.
0:28:39 And PlantOS is really
0:28:40 aimed at removing
0:28:41 humans from the loop
0:28:42 and deciding how the
0:28:43 chemical processing
0:28:44 operations and the
0:28:44 refining operations
0:28:45 work.
0:28:46 And big refineries
0:28:47 are effectively big
0:28:47 robots.
0:28:49 You have the sensing
0:28:50 and telemetry, you
0:28:51 have the actuators to
0:28:52 control how the plant
0:28:54 operates, and imagine
0:28:55 like teleoperating
0:28:56 humanoid robots like
0:28:57 forever.
0:28:57 That is what the
0:28:58 refining industry and
0:28:59 the pressing industry
0:28:59 has been.
0:29:01 And there’s obviously
0:29:02 PID control loops that
0:29:03 kind of maintain set
0:29:04 points so you can
0:29:05 maintain temperature
0:29:06 automatically, maintain
0:29:07 pH automatically.
0:29:08 But the thing that
0:29:08 really matters is that
0:29:10 the feed material to
0:29:11 the pressing facilities
0:29:12 is constantly changing
0:29:13 because the ore body
0:29:14 is changing over
0:29:14 time.
0:29:15 And so the way
0:29:15 that the industry
0:29:16 manages that today
0:29:17 is they will blend
0:29:18 the feedstock to
0:29:19 minimize variability
0:29:20 that’s going into
0:29:20 the processing
0:29:21 facilities, and that
0:29:22 enables them to
0:29:23 minimize the amount
0:29:24 of change that has
0:29:24 to happen on a
0:29:25 processing facility.
0:29:26 So we’re trying to
0:29:27 flip that and say,
0:29:28 okay, if we build a
0:29:30 hyperdynamic and
0:29:31 highly flexible
0:29:32 refining circuit,
0:29:33 ideally without adding
0:29:33 a whole bunch of
0:29:35 costs, what does that
0:29:36 do to optimizing the
0:29:37 global operation from
0:29:37 the mine to the
0:29:37 refinery?
0:29:38 But it’s first
0:29:39 aimed at reducing
0:29:40 reagent consumption,
0:29:41 reducing energy
0:29:41 consumption.
0:29:42 And Google kind of
0:29:43 proved this.
0:29:44 They bought DeepMind
0:29:47 in 2016, 2017, and
0:29:48 one of the first
0:29:48 things they did was
0:29:49 throw the DeepMind
0:29:50 team at automating
0:29:51 and optimizing the
0:29:52 data center thermal
0:29:52 systems.
0:29:53 So air handler,
0:29:54 chiller, cooling
0:29:54 tower.
0:29:56 And that’s not a
0:29:57 super complex system.
0:29:58 You have weather,
0:29:59 which is a factor.
0:29:59 You have loads
0:30:00 within the building,
0:30:01 which is a factor.
0:30:01 But you ultimately
0:30:02 have nine control
0:30:03 variables between
0:30:05 airflow rate, supplier
0:30:06 temperature, the
0:30:07 cooling water
0:30:08 temperatures, and
0:30:08 flow rates, both
0:30:09 in the chiller
0:30:09 system and the
0:30:10 cooling tower
0:30:10 system.
0:30:12 And just in that
0:30:13 relatively simple
0:30:14 system, they were
0:30:14 able to reduce
0:30:15 energy consumption by
0:30:16 30, 40%.
0:30:16 Yeah, it was like
0:30:17 40%.
0:30:18 And it happened
0:30:19 relatively quickly.
0:30:20 And so that’s the
0:30:21 opportunity when you
0:30:22 remove humans from
0:30:22 making the decisions
0:30:23 on how kind of like
0:30:24 these process systems
0:30:25 operate.
0:30:26 That’s the opportunity.
0:30:27 And then when we
0:30:28 look at kind of
0:30:29 refining and processing
0:30:30 facilities, that’s
0:30:31 like a thousand
0:30:32 control variables.
0:30:33 And it’s no longer
0:30:35 single pass, because
0:30:35 what’s really
0:30:36 interesting about
0:30:37 minerals refining is
0:30:37 that you never want
0:30:38 to lose the
0:30:38 metal, right?
0:30:40 Every atom that
0:30:41 you lose kind of in
0:30:41 the processing facility
0:30:42 is another atom that
0:30:42 you have to mine.
0:30:44 So recovery in the
0:30:45 refinery is actually
0:30:46 like the biggest lever
0:30:46 when it comes to
0:30:47 cost.
0:30:48 And so what that
0:30:48 means is that the
0:30:49 upstream unit
0:30:50 operations think of a
0:30:51 refinery as like 20
0:30:52 unit operations kind of
0:30:54 all in series in a
0:30:55 relatively simple
0:30:55 refinery.
0:30:56 The upstream
0:30:57 operations obviously
0:30:58 impact the downstream
0:30:59 operations, because if
0:31:00 you’re changing the
0:31:00 process conditions in
0:31:01 the upstream
0:31:02 operation, that changes
0:31:02 what the downstream
0:31:03 operation is seeing.
0:31:05 but the downstream
0:31:06 operations will
0:31:07 recycle the reject
0:31:08 stream back into the
0:31:09 upstream operations.
0:31:11 And so it’s this big
0:31:13 interconnected web, and
0:31:13 it’s a high latency
0:31:15 web also, where if you
0:31:16 make a change in one
0:31:17 part of the circuit, you
0:31:18 may not see that change
0:31:20 cascade for another 24 or
0:31:21 48 hours.
0:31:22 And when we’re
0:31:23 commissioning refineries
0:31:25 like the world, that
0:31:26 like latency ends up
0:31:28 being a major driver of
0:31:28 kind of the time it
0:31:29 takes to bring a
0:31:31 refining operation to
0:31:32 spec and eventually
0:31:32 ramp it to throughput.
0:31:33 There are some
0:31:34 refineries that were
0:31:35 built recently that
0:31:35 are still not
0:31:35 commissioned.
0:31:36 They were built like
0:31:38 three years ago, but
0:31:39 the Chinese companies
0:31:40 are doing it in six
0:31:40 months.
0:31:41 And a lot of Western
0:31:43 companies, it takes two
0:31:44 to four years.
0:31:46 And that stacks up, where
0:31:47 we need to build like an
0:31:48 insane number of mines
0:31:49 and refineries, and if
0:31:50 you are kind of four
0:31:51 times longer or five
0:31:52 times longer every time
0:31:53 you build a refinery.
0:31:54 At every step of the
0:31:54 process.
0:31:54 Yeah.
0:31:56 And so we’re trying to
0:31:56 bring down the time
0:31:57 that it takes to bring
0:31:58 the refinery to spec,
0:32:00 basically, throughput, and
0:32:00 hitting the kind of like
0:32:02 output requirements of the
0:32:02 product that you’re
0:32:03 making.
0:32:04 And then ultimately, you
0:32:05 start this historically
0:32:08 very long haul of
0:32:09 gradually bringing down
0:32:10 the cost over time.
0:32:11 And that’s something that
0:32:12 we think that reinforcement
0:32:13 learning is going to do
0:32:14 quickly, much, much
0:32:15 faster, kind of like in
0:32:16 line with what Google
0:32:17 demonstrated with the
0:32:17 thermal systems and data
0:32:19 centers, is achieve
0:32:21 global optimal operating
0:32:23 conditions on an order
0:32:24 of magnitude faster
0:32:24 timescale.
0:32:25 So how do you think
0:32:26 about, like, you’re
0:32:27 building a company that
0:32:30 mines and refines a
0:32:30 product.
0:32:32 There’s a lot of tech
0:32:33 that you can interject at
0:32:35 essentially every step of
0:32:36 that process.
0:32:37 Like, how are you deciding
0:32:38 what to build, where to
0:32:40 partner, what are you
0:32:41 developing in-house versus
0:32:42 where are you going to
0:32:42 market?
0:32:44 Yeah, I think at the
0:32:45 beginning we’re focused on
0:32:46 how do we take kind of
0:32:47 commercially demonstrated
0:32:49 unit operations and be a
0:32:50 better integrator and a
0:32:52 better, like, operator of
0:32:52 that integrated circuit.
0:32:54 And so focus on the
0:32:55 software systems that
0:32:56 enable you to kind of
0:32:57 control the plant more
0:32:57 optimally.
0:32:59 And that’s generally what
0:33:01 project-level financing
0:33:02 parties want to see also.
0:33:03 Like, it’s hard to get
0:33:04 project finance on a
0:33:05 first-of-a-kind facility
0:33:06 where you’re demonstrating
0:33:07 a new unit operation for
0:33:08 the first time.
0:33:09 And so we think that as
0:33:10 we’re kind of entering the
0:33:11 market, the right place to
0:33:13 start is take commercially
0:33:14 demonstrated individual
0:33:15 unit operations that
0:33:16 operate globally and go
0:33:17 after the uplift that’s
0:33:18 available just by being a
0:33:19 better integrated operator.
0:33:21 There’s a whole bunch of
0:33:22 bottlenecks in building
0:33:24 these facilities that we
0:33:25 will need to solve.
0:33:26 I mean, the, like,
0:33:27 industrial supply base just
0:33:28 for, like, manufacturing
0:33:29 tanks is broken.
0:33:31 Like, there’s specialty.
0:33:32 That’s a new one.
0:33:33 Like, things that we kind
0:33:34 of take for granted just
0:33:36 take a really long time if
0:33:37 you want to not go to
0:33:38 China for sourcing that
0:33:38 equipment.
0:33:40 And that has a big impact
0:33:41 on the operating side of
0:33:42 things, too, where the
0:33:43 supply chain for, like, a
0:33:45 new pump in Australia could
0:33:47 take 30 weeks and getting
0:33:49 that exact same pump, but
0:33:50 with a mine in China, it
0:33:51 shows up in a week or
0:33:52 three days.
0:33:53 And so that entire
0:33:53 industrial, like,
0:33:56 equipment supply base, we’re
0:33:56 going to have to look at
0:33:57 some point.
0:33:58 And that’s obviously a much
0:33:59 bigger bite to go after,
0:33:59 like, commodity equipment
0:34:00 manufacturing.
0:34:01 You’re not going to
0:34:02 vertically integrate to be a
0:34:03 mining equipment
0:34:04 manufacturing company, are you?
0:34:04 Mining equipment manufacturing
0:34:04 company.
0:34:05 I don’t think so.
0:34:06 I hope not.
0:34:06 You’ll let me know.
0:34:07 That’s right.
0:34:08 Well, this is the kind of
0:34:09 what is the incentive
0:34:10 structure of the partners and
0:34:11 the suppliers, and is it
0:34:12 required or not?
0:34:13 I think that there’s a
0:34:14 whole bunch of companies
0:34:15 that are working on awesome,
0:34:16 like, novel process
0:34:18 technologies that have not
0:34:19 quite gotten over the
0:34:21 hump trying to sell to the
0:34:21 big mining companies.
0:34:23 And we want to be the
0:34:24 customer that helps
0:34:25 accelerate commercial
0:34:26 deployment, and the
0:34:26 partner that helps
0:34:27 accelerate commercial
0:34:27 deployment.
0:34:29 And one of the big issues
0:34:30 that comes up when you’re
0:34:31 kind of, like, deploying
0:34:32 new processing technologies
0:34:33 is that part of the
0:34:34 reason why it takes a long
0:34:35 time for it to get to the
0:34:36 point where it’s
0:34:37 commercially viable, other
0:34:38 than all the headwinds
0:34:38 from the industry being
0:34:39 conservative and process
0:34:40 driven and all those
0:34:41 things, is that, like,
0:34:42 humans have actually never
0:34:44 operated that process
0:34:46 chemistry at scale before.
0:34:47 And so you’ll learn a
0:34:48 bunch of things at pilot
0:34:49 scale, but pilot doesn’t
0:34:50 really tell you what’s
0:34:51 happening at commercial
0:34:51 scale.
0:34:51 And you have to train
0:34:51 people.
0:34:52 You have to train the
0:34:53 people to operate it.
0:34:54 It’s, like, new
0:34:55 environmental things that
0:34:56 might come up depending
0:34:56 on the chemical that you’re
0:34:57 using.
0:34:59 And that, like, scale
0:35:00 jump is actually something
0:35:02 that we think that RL will
0:35:03 enable with a pretty
0:35:04 meaningful pace
0:35:06 adjustment where you don’t
0:35:07 need the humans to kind
0:35:08 of, like, fine-tune the
0:35:09 process conditions around a
0:35:10 new process chemistry
0:35:12 because the plant OS is
0:35:12 doing it.
0:35:14 Ryan and Erin, how
0:35:15 did we approach this
0:35:15 industry?
0:35:16 Is this a space that we
0:35:16 spent a lot of time
0:35:17 thinking about or
0:35:18 thinking about opportunities
0:35:19 in the space, or how
0:35:20 did we approach it?
0:35:21 We wanted to do a mining
0:35:23 investment for a long
0:35:23 time.
0:35:24 When you think about
0:35:26 venture capital, we
0:35:28 care about massive
0:35:29 markets.
0:35:32 And there’s not that
0:35:33 many massive markets
0:35:34 left that have been
0:35:35 sort of, like, largely
0:35:36 untapped by technology.
0:35:38 And mining sort of
0:35:39 screams one of the
0:35:40 largest markets in the
0:35:40 world.
0:35:42 Very little adoption of
0:35:43 technology.
0:35:45 So, over many cycles, we
0:35:46 have gone out and
0:35:48 spent a lot of time
0:35:49 meeting companies.
0:35:50 And as I mentioned
0:35:51 before, the challenge is
0:35:53 how do you sell a point
0:35:54 solution or a point
0:35:56 piece of technology into
0:35:57 this industry that has
0:36:00 very little incentive to
0:36:01 adopt it and also has a
0:36:02 very complicated
0:36:03 geopolitical dynamic
0:36:04 where you have a very
0:36:05 large global player with
0:36:06 their hand on the
0:36:06 scale.
0:36:08 We put out a piece a
0:36:09 couple weeks ago around
0:36:10 our thesis in mining and
0:36:11 why we think a vertical
0:36:13 mining company is the
0:36:14 answer because we
0:36:15 actually do believe you
0:36:16 have to control every
0:36:19 single piece of the
0:36:21 entire journey, the
0:36:22 entire life cycle of an
0:36:23 atom of metal end-to-end
0:36:24 to actually be able to
0:36:25 build a tech company
0:36:25 here.
0:36:26 This is not about a
0:36:28 point solution for one
0:36:29 particular part of the
0:36:29 process.
0:36:30 In order to actually
0:36:31 capture the gains and
0:36:32 efficiency and build a
0:36:33 feasible business, you
0:36:34 really have to own the
0:36:35 entire process end-to-end.
0:36:36 The only thing I’d add
0:36:37 there is that this is the
0:36:38 intersection of
0:36:39 geopolitical urgency
0:36:40 technology and tech.
0:36:41 To what Seth Turner’s
0:36:42 been talking about, it’s
0:36:42 like now we have
0:36:43 technology that can
0:36:44 actually go and
0:36:44 disrupt this.
0:36:45 There also is a
0:36:46 talent base, people
0:36:47 coming from companies
0:36:48 like Tesla, SpaceX,
0:36:49 Andrel, other sort of
0:36:50 hard tech companies
0:36:51 working in sort of dirty
0:36:53 spaces, willing to go out
0:36:54 in the fields.
0:36:54 Roll up their sleeves.
0:36:55 Yeah, roll up their
0:36:56 sleeves, go out in the
0:36:56 middle of the desert and
0:36:57 work on this stuff.
0:36:58 So now is the time to
0:36:59 build this company.
0:37:00 And the political
0:37:00 tailwinds are there.
0:37:02 Even my conservationist
0:37:03 mother, who I think if
0:37:05 like we had this
0:37:06 conversation five years
0:37:07 ago, she would have
0:37:08 clutched her pearls.
0:37:09 She doesn’t wear pearls,
0:37:10 but she would have
0:37:10 clutched her pearls at
0:37:12 the idea of domestic
0:37:13 U.S. onshore mining.
0:37:15 I think broadly speaking,
0:37:16 the American public and
0:37:17 certainly the government
0:37:18 has come around to the
0:37:21 idea that metals are in
0:37:22 every single thing we
0:37:22 use as consumers.
0:37:24 Our supply chains are
0:37:25 highly reliant on
0:37:25 China.
0:37:26 It’s a huge problem.
0:37:27 We have to figure out
0:37:28 how to address it.
0:37:29 And that means investing
0:37:30 in mining in the U.S.
0:37:31 again.
0:37:32 You mentioned like
0:37:33 rare earths, you
0:37:33 mentioned lithium and
0:37:34 things like that, but
0:37:35 there are many different
0:37:35 critical minerals.
0:37:36 You talked a little
0:37:37 about in the very
0:37:37 beginning, but
0:37:38 specifically, what are
0:37:39 the interesting ones for
0:37:40 you?
0:37:41 How does that map to
0:37:42 sort of what people see
0:37:43 on the headlines and
0:37:44 where the business
0:37:45 opportunities are?
0:37:46 Yeah, I mean, when we
0:37:47 look at what needs to
0:37:48 happen in the next 10
0:37:49 years and forecasted
0:37:49 demand will only
0:37:50 materialize if the
0:37:51 supply is there, so
0:37:52 we’ll see if that
0:37:53 forecasted demand
0:37:53 materializes.
0:37:55 The metals that
0:37:55 actually need to grow
0:37:57 the most by like mass
0:37:58 flow rate are like the
0:37:59 big metals.
0:38:00 Like we need a lot of
0:38:00 aluminum.
0:38:01 We need an insane
0:38:01 amount of copper.
0:38:03 We need more iron.
0:38:03 We need more zinc.
0:38:04 What are some of the
0:38:05 things that these
0:38:05 metals are in?
0:38:06 Yeah, sure thing.
0:38:07 I mean, like iron goes
0:38:07 in everything that is
0:38:08 infrastructure.
0:38:09 We got iron.
0:38:09 We’re good with iron.
0:38:10 Zinc is one that people
0:38:11 sleep on because you
0:38:12 actually have to galvanize
0:38:13 a lot of that steel, and
0:38:15 so zinc oftentimes kind of
0:38:17 pops up every once in a
0:38:17 while as being something
0:38:19 that we really do need to
0:38:19 continue to focus on.
0:38:21 Copper is the workhorse
0:38:22 of this push to
0:38:24 electrify everything and to
0:38:26 just grow the grid to be
0:38:27 able to supply AI, to be
0:38:28 able to enable
0:38:29 accelerated renewable
0:38:31 penetration, for EV
0:38:32 penetration to happen,
0:38:32 like you’re going to
0:38:33 need a lot of copper.
0:38:34 Aluminum is one that I
0:38:36 think is underestimated.
0:38:37 People underestimate kind
0:38:38 of its importance.
0:38:38 It’s actually like the
0:38:39 number one most consumed
0:38:41 metal in defense
0:38:41 applications.
0:38:43 Like the grid is, people
0:38:44 talk a lot about copper,
0:38:44 but there’s a lot of
0:38:46 aluminum like conductors
0:38:47 in the transmission lines
0:38:48 that are critical to
0:38:49 actually growing the
0:38:50 grid capacity.
0:38:51 And in automotive,
0:38:52 obviously, aluminum is
0:38:52 big.
0:38:53 Magnesium has a whole
0:38:54 bunch of defense
0:38:55 applications, potentially
0:38:57 could get more into
0:38:58 automotive applications
0:38:58 and like for
0:38:59 lightweight metals.
0:39:01 Lithium needs to
0:39:02 4x in terms of
0:39:03 production capacity in
0:39:04 the next 10 years,
0:39:05 roughly, in order for
0:39:06 the batteries that we
0:39:07 want to build to be
0:39:07 built.
0:39:08 Well, we’re all about
0:39:08 batteries.
0:39:09 Right, right, right.
0:39:11 And then nickel is a
0:39:12 big one.
0:39:13 I think that what has
0:39:14 happened in nickel in the
0:39:16 last five years is
0:39:17 Indonesian production
0:39:18 capacity has scaled to
0:39:18 the point where it’s
0:39:19 now something like 70%
0:39:21 of global nickel comes
0:39:21 out of Indonesia.
0:39:22 And a lot of that was
0:39:23 on the back of like
0:39:24 meaningful investment
0:39:25 from China to be able
0:39:26 to kind of expand
0:39:27 production capacity in
0:39:28 Indonesia and then
0:39:29 also do more of the
0:39:29 downstream processing
0:39:30 in Indonesia.
0:39:31 And nickel goes into
0:39:32 everything that is
0:39:33 specialty alloys,
0:39:34 anything that needs
0:39:35 high temperature or
0:39:36 corrosion resistance,
0:39:37 and also is like
0:39:38 kind of the unsung
0:39:39 hero of high energy
0:39:41 batteries where these
0:39:41 lithiated transition
0:39:42 metal oxides, which
0:39:43 are high nickel.
0:39:45 Manganese is important.
0:39:46 Manganese goes into a
0:39:47 lot of alloys and also
0:39:48 goes into batteries.
0:39:50 The uranium, if
0:39:51 fission is going to
0:39:51 continue to grow and
0:39:52 we’re going to continue
0:39:53 to like deploy more
0:39:54 nuclear capacity in the
0:39:55 U.S., then uranium is
0:39:55 going to be needed.
0:39:57 It’s a long list.
0:39:58 And the rare earths,
0:39:59 they’re important,
0:39:59 obviously.
0:40:01 They are omnipresent in
0:40:02 like everything that we
0:40:02 use.
0:40:04 But they show up as a
0:40:05 relatively small on a
0:40:06 volume basis when you
0:40:07 look at kind of the
0:40:08 stack of metals that we
0:40:08 need to mine.
0:40:10 Definitely we need a ton
0:40:11 of process innovation in
0:40:13 how rare earths are
0:40:13 refined.
0:40:14 Solvent extraction
0:40:15 circuits are kind of
0:40:16 like the status quo.
0:40:17 The chemical intensity
0:40:18 is high and the
0:40:19 recoveries are relatively
0:40:19 low.
0:40:21 And the know-how is
0:40:21 kind of like highly
0:40:22 concentrated in China.
0:40:24 But it is a little bit
0:40:25 of a frothy market
0:40:25 right now.
0:40:26 And so being a
0:40:27 diversified minerals
0:40:28 company kind of enables
0:40:29 us to pick our spots
0:40:30 in areas where it
0:40:30 makes sense.
0:40:31 Like these things still
0:40:32 do move on commodity
0:40:33 cycles.
0:40:34 And you actually want
0:40:34 to be building
0:40:35 infrastructure at the
0:40:36 bottom of commodity
0:40:37 cycles, not at the
0:40:37 top of commodity
0:40:37 cycles.
0:40:39 It’s the Warren
0:40:40 Buffett quote of
0:40:40 invest when there’s
0:40:41 blood in the water.
0:40:42 Like you want to be
0:40:43 coming into metals
0:40:44 when they are at
0:40:45 this trough,
0:40:46 really, where no one
0:40:47 is investing in them.
0:40:48 They still have a
0:40:48 macro long-term
0:40:49 critical point.
0:40:50 Lithium is like
0:40:51 exactly in this
0:40:52 position right now.
0:40:52 and that’s why
0:40:53 we’re focused on
0:40:53 lithium.
0:40:54 Copper just has this
0:40:55 like macro trend that
0:40:56 is like pretty hard to
0:40:57 ignore.
0:40:57 We’re just going to
0:40:58 need an insane amount
0:40:58 of copper.
0:40:59 Copper grids are going
0:41:01 down globally, which
0:41:02 means that our ability
0:41:03 to extract copper from
0:41:05 those ores is going to
0:41:05 get harder and harder
0:41:06 to extract copper from
0:41:07 those ores.
0:41:08 And that’s where the
0:41:09 plant OS side of things
0:41:09 we have a high degree
0:41:10 of confidence that
0:41:11 we’ll be able to step
0:41:12 in and optimize the
0:41:13 refining circuits to
0:41:14 still be able to
0:41:15 extract copper from
0:41:15 these lower grade
0:41:16 ores without seeing
0:41:17 meaningful kind of
0:41:18 cost increases.
0:41:19 So everyone knows
0:41:20 people here, it
0:41:21 takes forever to get
0:41:21 a mine started.
0:41:22 I don’t know how
0:41:22 many new greenfield
0:41:23 mines we’ve developed
0:41:24 in the United States
0:41:25 in the last decade.
0:41:25 Not many.
0:41:27 Yeah, and I know
0:41:27 Australia and Canada
0:41:28 have been able to do
0:41:29 this faster, which is
0:41:30 interesting.
0:41:31 You don’t know Canada
0:41:32 for moving quickly.
0:41:33 What are some of the
0:41:33 bottlenecks there?
0:41:35 What does America need
0:41:35 to do to accelerate
0:41:37 this as one of these
0:41:38 companies trying to not
0:41:39 only mine but also
0:41:40 refine in the United
0:41:40 States?
0:41:41 Like what needs to be
0:41:41 done?
0:41:42 One thing that folks
0:41:43 don’t always see is
0:41:44 actually the permitting
0:41:45 requirements for
0:41:46 exploration.
0:41:47 So if you are
0:41:48 exploring over on
0:41:48 federal land, if you’re
0:41:49 exploring over more than
0:41:51 a five acre parcel, you
0:41:52 have to submit like a
0:41:54 plan of record or plan
0:41:55 of operations that
0:41:56 needs to be approved
0:41:57 by the BLM before you
0:41:58 can start to expand and
0:41:58 explore over a larger
0:41:59 piece of land.
0:42:01 And so bringing down
0:42:02 the permitting thresholds
0:42:02 and the permitting
0:42:03 burden associated with
0:42:05 exploring, like that is
0:42:06 why we have such a
0:42:08 relatively small rare
0:42:08 earth resource.
0:42:09 It’s like it’s not
0:42:10 because there isn’t
0:42:11 like the U.S.
0:42:12 has tons of natural
0:42:14 resources and the kind
0:42:15 of like USGS estimate
0:42:16 for like the U.S.
0:42:18 reserve on rare is
0:42:19 just picking on that.
0:42:20 Like that is tied to
0:42:21 lack of exploration
0:42:21 activity, not
0:42:22 necessarily
0:42:23 fundamentally like a
0:42:24 lack of kind of
0:42:24 geologic presence.
0:42:25 And we haven’t looked
0:42:25 for it.
0:42:26 Yeah, we haven’t
0:42:26 either we haven’t
0:42:27 looked for it or it’s
0:42:28 hard to find in like
0:42:29 high concentrations that
0:42:29 are mineable, which
0:42:31 we’re trying to drop the
0:42:32 percentage requirement
0:42:33 that makes something
0:42:34 economical.
0:42:35 But it’s also there’s
0:42:35 just a lot of kind of
0:42:36 like permitting burden
0:42:37 to be able to actually
0:42:38 go and deploy drill rigs
0:42:39 to go and actually
0:42:39 explore.
0:42:41 And then the government
0:42:42 currently is doing a
0:42:43 good job of kind of
0:42:43 highlighting the
0:42:44 importance of the
0:42:44 minerals industry.
0:42:45 And you’re definitely
0:42:46 seeing a little bit of
0:42:47 a tone shift over the
0:42:49 last 20 years that is
0:42:49 much more supportive.
0:42:50 There’s way more
0:42:51 tailwinds when it
0:42:51 comes to kind of
0:42:53 like making mining be
0:42:54 viewed in a more
0:42:55 positive light and a
0:42:55 critical light.
0:42:57 And that will help to
0:42:58 solve some of the
0:42:59 talent pool problem
0:43:00 where people that are
0:43:01 awesome, they want to
0:43:02 go build things.
0:43:03 They don’t want to go
0:43:04 and work on a project
0:43:05 that sits around for
0:43:06 five years and maybe
0:43:07 gets permitted and
0:43:08 maybe doesn’t.
0:43:08 They want to go work
0:43:10 on hard problems where
0:43:11 they can see the impact
0:43:12 of the work that
0:43:12 they’re doing.
0:43:13 And so if we’re
0:43:14 getting in the way of
0:43:15 enabling projects to
0:43:16 get built, that is
0:43:17 actually a major
0:43:18 deterrent for talent
0:43:19 because they won’t
0:43:20 actually see the like
0:43:20 output of their
0:43:21 work.
0:43:22 And then I think the
0:43:24 permitting requirements
0:43:26 broadly for going from a
0:43:27 discovery to an
0:43:28 operating asset, there
0:43:29 should be a big focus
0:43:30 on efficiency in
0:43:31 reviewing environmental
0:43:31 permits.
0:43:32 There should be a big
0:43:34 focus on streamlining
0:43:35 those workflows in the
0:43:36 back and forth between
0:43:37 field offices and state
0:43:38 offices from the BLM,
0:43:39 just focusing on the
0:43:39 federal side of things.
0:43:41 Because the way that
0:43:42 projects get permitted
0:43:43 right now is you’ll
0:43:43 throw like your
0:43:44 environmental assessment
0:43:46 over the table and
0:43:47 then they’ll go and
0:43:47 they’ll divvy it up
0:43:48 between a whole bunch of
0:43:49 experts or like kind of
0:43:50 consultants that they
0:43:50 bring in to review the
0:43:52 permit and they’ll get
0:43:53 back to you eventually
0:43:53 at some point.
0:43:55 But there isn’t a lot of
0:43:56 visibility into like how
0:43:56 they are progressing with
0:43:57 reviewing the permit
0:43:58 applications and
0:43:59 discussions are getting
0:44:01 more bilateral and
0:44:02 again there’s been
0:44:03 definitely a change
0:44:04 with the new
0:44:04 administration where
0:44:05 there’s a little more
0:44:06 accountability on the
0:44:08 permitting offices, but
0:44:09 there’s tons of room
0:44:10 for making those
0:44:11 reviews more efficient.
0:44:13 And again, LLMs will
0:44:13 make it more efficient.
0:44:14 We just need to
0:44:16 penetrate that side of the
0:44:17 federal bureaucracy and
0:44:17 enable people to review
0:44:18 things faster.
0:44:19 What else, aside from
0:44:20 kind of permitting
0:44:22 efficiency, what are
0:44:23 other things that if
0:44:24 you could send a list
0:44:25 of recommendations to
0:44:26 the government for what
0:44:27 they should do to
0:44:28 support the U.S.
0:44:29 mining industry, what
0:44:29 would be your top
0:44:29 three?
0:44:31 Yeah, I think supporting
0:44:31 the demand side is
0:44:32 probably like the
0:44:32 biggest lever.
0:44:33 And if you want to
0:44:34 mobilize kind of private
0:44:35 capital into the sector,
0:44:36 having some level of
0:44:37 support on the demand
0:44:38 side is major.
0:44:39 And so that’s offtake
0:44:39 agreements with floor
0:44:41 pricing and they did this
0:44:41 just now with MP
0:44:43 materials and that
0:44:45 ideally provides some
0:44:45 stability on the
0:44:46 revenue side of
0:44:46 things so that
0:44:48 investors, like there’s
0:44:49 trillions of dollars of
0:44:49 capital kind of like
0:44:51 dry powder just sitting
0:44:52 around waiting to be
0:44:52 deployed.
0:44:53 It has historically kind
0:44:54 of avoided the mining
0:44:56 industry because of the
0:44:57 market price uncertainty.
0:44:58 And so as soon as you
0:44:59 provide, it’s a commodity
0:45:00 cycle and what if you’re
0:45:01 building at the wrong
0:45:02 time and the
0:45:02 infrastructure funds are
0:45:03 not the ones that are
0:45:04 here to play, like be
0:45:05 intelligent about the
0:45:05 commodity price cycle,
0:45:06 like they’re looking for
0:45:07 annuity type returns.
0:45:09 And so those folks would
0:45:11 mobilize if there were
0:45:12 more demand side support
0:45:13 from the government, either
0:45:14 providing price floors or
0:45:16 fixed pricing for
0:45:16 critical minerals that
0:45:17 you’re trying to
0:45:18 incentivize more
0:45:19 production of in the
0:45:19 U.S.
0:45:20 Participating in the
0:45:21 capital stack is
0:45:21 important.
0:45:23 I think lowering the
0:45:25 hooks or the extra
0:45:26 burden that comes in with
0:45:27 receiving government
0:45:28 funds is important.
0:45:29 And like some government
0:45:30 agencies probably have
0:45:32 more leeway to do that,
0:45:33 like the DOD obviously
0:45:34 again just did this big
0:45:35 deal with MP materials
0:45:36 and actually went all the
0:45:37 way to participating in
0:45:39 the cap table or as an
0:45:39 equity holder.
0:45:41 But when you receive
0:45:42 federal funds from the
0:45:43 DOE or if you receive
0:45:45 federal funds from like
0:45:46 on the debt side of
0:45:47 things, from XM, it
0:45:48 comes with some like
0:45:49 additional burden sometimes.
0:45:50 If you are building on
0:45:51 state land and you just
0:45:52 need a state permit and
0:45:53 then you bring in
0:45:55 federal funds, you now
0:45:55 bump your permitting
0:45:57 requirement to a federal
0:45:57 level permit.
0:45:59 And that’s the NEPA
0:46:00 process, which again,
0:46:01 the NEPA process
0:46:01 wouldn’t be as
0:46:02 burdensome if there was
0:46:03 some more efficiency on
0:46:04 the permitting side of
0:46:04 things.
0:46:05 mineral deposits,
0:46:06 specifically like high
0:46:07 grade mineral deposits
0:46:08 don’t obey borders.
0:46:09 Is there a broader
0:46:10 international strategy
0:46:11 here?
0:46:11 I mean, I would love to
0:46:12 think we can mine and
0:46:13 refine everything in the
0:46:14 United States, but
0:46:15 obviously there’s a lot
0:46:16 Australia, Canada, Latin
0:46:17 America, curious sort of
0:46:19 what Africa, underwater,
0:46:20 seafloor.
0:46:21 What is the overall
0:46:22 strategy in your mind?
0:46:24 We’re starting in the U.S.
0:46:25 because it’s closer to
0:46:27 home and we’re focused on
0:46:28 developing a platform that
0:46:28 we can scale off of.
0:46:31 But at no point have we
0:46:32 told ourselves that the U.S.
0:46:33 is the sole focus.
0:46:35 Like you have to be able
0:46:36 to bolster the company to
0:46:37 be able to operate
0:46:39 internationally if you want
0:46:40 to be able to scale beyond
0:46:41 kind of like the resource
0:46:41 base that the U.S.
0:46:42 has like available today.
0:46:44 And so more exploration is
0:46:45 going to happen in the U.S.
0:46:46 We’ll probably discover more
0:46:47 resources and that pool will
0:46:48 grow over time of projects
0:46:49 that we can build in the U.S.
0:46:50 But yes, we are absolutely
0:46:52 going to expand overseas
0:46:53 and underwater maybe.
0:46:55 When we look back a decade
0:46:56 from now, what’s the
0:46:57 single clearest indicator that
0:46:58 Mariana has achieved what
0:46:58 it set out to do?
0:47:01 We won’t be as worried
0:47:02 about our ability to
0:47:02 secure the critical
0:47:04 minerals that we want
0:47:06 to secure because we
0:47:07 will have kind of rebuilt
0:47:10 and established like an
0:47:12 entity ideally that is
0:47:13 able to go across borders
0:47:15 to your point and build
0:47:16 these projects cost
0:47:17 effectively, time
0:47:18 effectively, and
0:47:19 responsibly ultimately.
0:47:21 And the reason that we
0:47:22 are so panicked about it
0:47:23 right now is because we
0:47:24 have fundamentally lost
0:47:25 the ability to build
0:47:25 large-scale infrastructure
0:47:27 and we have lost the
0:47:28 ability to like operate
0:47:30 complex minerals plants.
0:47:31 That’s what we have
0:47:32 lost and we need to
0:47:33 build that back.
0:47:34 We want to build 10
0:47:35 projects in 10 years.
0:47:36 Those projects will be
0:47:37 an increasing scale over
0:47:38 time, but the work will
0:47:39 not be done in 10 years.
0:47:41 What I think will have
0:47:42 demonstrated that the
0:47:43 10-year mission will
0:47:44 have been accomplished
0:47:45 other than building those
0:47:47 10 plants is that we
0:47:48 will no longer be as
0:47:49 worried about like our
0:47:50 fundamental capability
0:47:51 to go and build this
0:47:52 complex infrastructure.
0:47:53 We will have unlocked it.
0:47:57 Thanks for listening to
0:47:59 the A16Z podcast.
0:48:00 If you enjoyed the
0:48:01 episode, let us know by
0:48:02 leaving a review at
0:48:03 ratethispodcast.com
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0:48:06 We’ve got more great
0:48:06 conversations coming your
0:48:07 way.
0:48:08 See you next time.