Chamath Palihapitiya: guys this is one of the most amazing entrepreneurs that you're going to meet jim latinski this

SPEAKER_02: founder and ceo of mp materials thanks good to be here hey how are you so let me let me set this up

Chamath Palihapitiya: um jim was a hedge fund guy running a pretty successful hedge fund uh and he ended up basically investing in something called molly corp which went out of business yep no 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 uh largest and only i think supplier and refiner of rare earth materials and maker of magnets inside

SPEAKER_08: the united states we're 100 of the american industry 100 of the american industry you

Chamath Palihapitiya: just did two really incredible things actually in the last couple weeks one was you announced

SPEAKER_12: an enormous public private partnership with the dod 400 million dollars etc and then the second is you

SPEAKER_14: announced a really big deal with apple yes okay so yeah should i take take a huge step back talk to us

SPEAKER_17: why rare earths matter tell us about the supply chain for ai tell us why so rare earth magnets are really

SPEAKER_18: the feedstock to physical ai um 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 um so you mentioned uh the predecessor went bankrupt um there there was a feeling when i when i took over this site with my co-founder and this is this goes back to 2015 uh where is the site this oh it's in mountain pass california so if you you'll be familiar if you take a 45 minute drive from the las vegas strip uh just over the border in california uh is this site you actually can see it from the road and it's actually the really the best rare earth ore 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 a 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 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 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 um chamath as you know we took the company public in 2020 we built out the refining capability and then uh 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 uh sales to gm at the end of this year in in magnets and then chamath you referenced a couple it's been a busy few months for us um we announced a a pretty transformative public private partnership with the department of defense dod is um there's really three pillars to this deal uh dod is becoming our largest economic investor um as well as they're going to provide a price floor for our commodities so that the chinese sort of chinese mercantilism we can get into that uh 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 build out 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 off-take partner um uh customer and business partner because we'll be we'll be splitting

SPEAKER_23: profits 50 50 with the to just translate this it's not a handout from the government they didn't not at all 400 million dollars they invested in your company they have warrants they have equity yeah

SPEAKER_24: so they invested they they both are an owner uh they also are an upside participant in our commodity

SPEAKER_18: to the extent that the prices uh uh take off and then they're also a hundred percent off take 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 um 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 and other industries um but it would not surprise me if when we five years from now hopefully we'll do this conference and chamath 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 uh the taxpayer made money on doing this and i'll say yeah i actually think that that's going to be the outcome um 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 uh normalize for some of these things and free up our ability to

SPEAKER_29: invest and expand why go to the government for this investment as opposed to the private markets

SPEAKER_18: 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 uh did something you know totally unique that which piece 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 we there was no way we were going to make that commitment um we're fiduciaries right we have shareholders

SPEAKER_32: 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

SPEAKER_05: 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

SPEAKER_18: that we've been told yeah well i think that that is a question for there's much smarter guests on this for the rest i'll give a plug the rest of the day obviously you have the you know the best of the best providing that feedstock um i will say that i think one of the big drivers of our deal was the as we've seen um in ukraine in 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 than you know the defense needs but just from a defense standpoint this is this is a really important supply chain that we must have right we there's

SPEAKER_32: we can't be funding cutting-edge drone and robotics companies and then say okay but we're going to buy

SPEAKER_36: those magnets from china that makes no sense we have talent capacity or do we have a talent shortage

SPEAKER_38: secretary burgum gave me a stat which was pretty shocking to me that we only graduate 200 people a

SPEAKER_36: 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 it's a great question i think jason i

SPEAKER_43: think about this question a lot on days but yeah what's that dave oh my god david sorry no no it's

SPEAKER_45: all good i'm a huge fan of the pod and i just embarrass myself all the time yeah it's it's it's the

SPEAKER_49: old it's the token whites i know you know i'm a fan of the pod since day one and i've totally

SPEAKER_50: embarrassed myself there's only one correction i'll make where am i messing with you

SPEAKER_52: was this intentional um so huge fan of the pod yeah huge fan of the pod who are you again take a selfie later and i'm not the ai's are go ahead

SPEAKER_18: so we have we have uh 850 employees today at mp we're going to hire when we include what we're building out for apple uh 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 um 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 um you know at mountain pass and we we hire it all electricians um maintenance you know operators is you get people in you train them and then obviously you give people a career and so we we've been training a lot of people and it's a little bit more painstaking but there's there's absolutely talent out there people are hungry to do it why do you think it's been so hard to establish

Chamath Palihapitiya: that that idea like meaning you find it straightforward to find good hard-working

SPEAKER_05: people to get into these jobs but the sem the thought is always that wow these jobs are not desirable but they really are desirable by many people yeah absolutely i mean we you know our median

SPEAKER_18: wage is now pushing a hundred thousand dollars a year um and there's you know relative to some of the opportunities that i mean uh these are great these are great jobs and what are the

SPEAKER_67: starting salaries what's that what's the starting salary just so it really depends on the job

SPEAKER_18: function because you know there's there's i mean i think the easiest way to think about it is you can you can certainly as an operator make close to a hundred thousand dollars a year with us because by the way um everybody's an owner we have an owner operator culture everyone got stock when we

SPEAKER_68: went public in 2020 but somebody coming out of high school they can make 40 50 60k or more yeah or it

SPEAKER_18: depends are you if we we can't find enough electricians we can't find enough maintenance workers a maintenance worker can uh an electrician they can make six figures today tell us you said earlier

Chamath Palihapitiya: that you suspect five years from now we're going to look back and this deal with the dod was a blueprint

SPEAKER_17: yeah 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 u.s supremacy yeah um there are some

SPEAKER_18: major categories obviously we've all heard about shipbuilding and advanced pharmaceutical ingredients i mean i think 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 um where there it's a vertical where there might not be a market large enough

SPEAKER_60: to to need five players but a good public private partnership can just solve that problem and then

SPEAKER_05: 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

SPEAKER_18: well and i i think that's you know our particular deal was led by dod and so i have to say that the pentagon leadership is extraordinary um and uh 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 and to be clear because i you know this story's not out there our process this was i've never worked so hard in my life i mean this was this was like a true aggressive private equity style investment and negotiation the transaction documents are public you can look at that so yeah that's they're tough yeah they are this was this was as tough as it gets tougher than you know think of any you know blue chip private equity or or uh distress lender type negotiation that's what this was and the key thing um 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 costs and so we're exposed if we get the costs wrong you know we we're making this investment and 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 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 you know certain customer issues um 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 quote picking a winner usually there's sort of money given to someone and it's sort of public risk private upside right this is not that this is private risk public risk public upside private upside it's a true shared win-win-win and again like i said hold me to these words i i hope uh i i hope i'm right on this but i think the uh 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 steve oh thanks thanks so much thanks brother yeah it's good all right take

SPEAKER_79: care steve thanks jacob i appreciate it yeah okay we'll see you hi lisa lisa it's a pleasure

SPEAKER_38: well thanks so much for being here with us today um 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 two nanometer line this administration and the private sector have talked

SPEAKER_36: a lot about on-shoring semiconductor manufacturing would love your thoughts of 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

SPEAKER_89: right well absolutely first of all it's a pleasure to be here um love the theme i think we're all super excited about winning the us um ai race and i thought if we're going to talk about chips david i should actually bring one oh awesome that's okay a little bit of show and tell so this is our latest generation um ai chip it's our mi355 chip 185 billion transistors takes about nine months to build lots of technology on it if i just uh this is um three nanometer and uh six nanometers so lots of

SPEAKER_96: different uh i'll be putting this on ebay later i'm gonna take it with me when i was at thank you uh but look to answer your question i think look these ai chips are extremely extremely complex um they have so much technology on it we're super excited about the progress in u.s manufacturing i

SPEAKER_89: would say you know 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 uh conversation about on-shoring manufacturing has been you know super good for the semiconductor industry and and you know frankly for you know all of us in um semiconductors uh we're in such an interesting place because you know chips are so essential to ensuring that we are able to win

SPEAKER_99: the ai race that um you know we want to make sure that there's a lot of geographic diversity and

SPEAKER_55: capability there but the reports out were that tsmc couldn't get good qualified trained employees they have to bring folks over is that accurate and like again like if we're going to scale like what's the

SPEAKER_36: 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

SPEAKER_88: to speak freely the best way to say it is no matter when you start something new it it's going to take

SPEAKER_96: work right it's it's going to be hard so sure in the beginning there there were some issues of you know the the tsmc has like a formula for how they build and they just you know 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 you know if we look at the the main thing that we look at is you know 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 about

SPEAKER_23: cost in arizona does it's unrealistic to think the united states could compete on cost am i correct

SPEAKER_107: we're going to pay a little bit more give us the ballpark 50 percent more 20 not not 50 more i mean

SPEAKER_96: look it it's going to be you know more than five percent but you know let's call it less than 20 percent so low low low double let's say low double digits and how does that impact the business if at

SPEAKER_109: all uh in terms of competition globally well i think the important thing is i mean just think

SPEAKER_96: about like everybody wants a gpu right like if you look across the industry you really say you know 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 you know the fact that you're not going for the the lowest cost you know every minute of the day is okay it's okay like obviously we're not going to build um not everything needs to be in the most advanced technologies and so we have a very geographically diverse supply chain you know i think taiwan continues to be important um in that view but the the focus um from this administration on getting uh on firm manufacturing in a big way not in a small

SPEAKER_23: way i think is 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

SPEAKER_96: would that look like globally yeah you have to look across um the supply chain but you know from a structure standpoint we all want to keep reserves for you know those those times uh but it's months

SPEAKER_70: it's not years we said there was uh two really interesting posts over the last couple of days one was

SPEAKER_05: from elon where he said in five 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

Chamath Palihapitiya: oracle that just pretends an enormous amount of chips that are necessary and power and if you forecast

SPEAKER_65: that how do we actually meet all of that what needs to happen that's not happening today inside of

SPEAKER_115: the united states to actually do that yeah it's it's a great great point i mean that's that's what

SPEAKER_96: we're seeing we're seeing this uh incredibly large demand uh for ai and they're coming from you know sam and elon are certainly uh you know the leaders a couple of the leaders uh there's there's a lot of demand elsewhere too i mean if you think about it nations want their own ai so there's a very high demand we're we're imagining that just the accelerator market so the chips for these um you know ai large computing systems will be like you know over 500 billion dollars in a couple of years so very high growth and when you say you know what do we need to do um it's the entire ecosystem needs to scale up so we need to scale up um 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 you know as i said i don't i think the u.s 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 u.s and and i think look i think

SPEAKER_112: today's um ai action plan is actually a really you know excellent blueprint and how do you see the

Chamath Palihapitiya: 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

SPEAKER_89: asics different designs different use cases yeah i i like that question because i 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

SPEAKER_96: use cases from you know whether you're talking about science or manufacturing or design or back end or you know 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 um that do that uh you know certainly the for the largest systems uh we tend to believe that uh you know you need the most compute you can get and so you know gpus are there but lots of asics

SPEAKER_120: are um in the in the process and you know we'll see a variety of different chips you opened up a really

SPEAKER_109: interesting line of questioning there when mainframes uh were so expensive and then eventually wound up having

SPEAKER_23: pc's that were more expensive on their desktop you alluded to ai being run locally yes when would we have a local computer a laptop a a desktop computer that would have the power we're seeing to run some

SPEAKER_29: of these llm models in your mind and do you see that as a specific market to go after look i definitely

SPEAKER_89: see the um the idea that ai will be at every part of our ecosystem um is a uh 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

SPEAKER_96: 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 right you know all over the place on that point can you make a

SPEAKER_38: prediction on when the the market for physical ai chips is greater than the market for chips and data

SPEAKER_89: centers uh that's a great question i'm a big believer in physical ai i still think it's let's call it

SPEAKER_126: five years you think five years is that that fast at least five years so you're saying five plus five

SPEAKER_38: plus yes okay but that but that is ultimately the biggest end market do you think is it you think

SPEAKER_96: physical ai becomes the biggest end market i think it becomes a significant end market um i think you look at chips in data centers and you look at chips at the edge they're also you know significant markets

Chamath Palihapitiya: when you look at the most cutting edge techniques today ev lithography all of this whole stuff to

SPEAKER_05: 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

Chamath Palihapitiya: method of manufacturing different materials different material sciences different approaches that we may

SPEAKER_05: not necessarily understand is any of that r d happening whether in amd or in other places like how are we trying to get beyond the physical limits of electrons shunting across a junction i i think this

SPEAKER_96: 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 you know

SPEAKER_138: ecosystem obviously you guys are you're a world-class chip design the fabs are getting reshored but how do you think about things like lithography like does that need to be you know sort of reshored or like does asml need to start building you know sort of machines in the united states or is it okay to have

SPEAKER_96: that type of you know supply chain risk on an ally look i think we're gonna we have to accept the fact that it's a global supply chain like even if you were to reshore you know 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 you know we have access to the latest generation technologies and uh you know that that is you know something that we protect given

SPEAKER_36: our intellectual property and going going to first principles and asking you the open-ended question

SPEAKER_38: 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

SPEAKER_96: probably a little bit biased as maybe some of your guests are today i'm a big believer in you know science and technology background as being you know sort of the stem background is you know so helpful when we think about the future workforce and the earlier we can get into the um you know sort of the process i think the better so some of the work that's being done to kind of revitalize the uh curriculum i think is is pretty important in the um sort of the next generation workforce and one of the things when i think about you know how we win in ai like there there's so many aspects of it but ensuring that you know america is the best place for ai talent is is also you know a key piece of

SPEAKER_131: that so kind of inspiring people when they're young to uh really you know study you know science

SPEAKER_149: technology when you um go to bed at night and you think about the best case scenario for this

SPEAKER_151: technology and this trajectory run which is accelerating and you're enabling what could the

SPEAKER_23: 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 um soon we hit that super intelligence what will the world look like in 10 years in the most optimistic scenario if we do this right well i think the

SPEAKER_96: exciting part about it and you know 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 orders of magnitude orders of magnitude and the reason is it's not just going after one aspect right you can actually take ai and make science better you can take ai and make medicine better you can take ai and make manufacturing better you can take ai and make every aspect of your business better and so you know in my mind 10 years from now we'd like to believe that we are um you know really leveraging it to solve some of the world's most important problems i i like to say like you know amd-ers get up in the morning and they say you know how can i use technology to solve some of the most important challenges in the world and you know ai is really our mechanism for doing that i have a business strategy question if we went

Chamath Palihapitiya: back 20 years and we wrote the tale of three companies nvidia amd intel and then you fast forwarded 20 years two have just absolutely thrived and one has not and if you had made the bet back then it would have been very inconclusive that you would have picked nvidia and amd and if anything there is a an amount of

SPEAKER_17: inherent belief that intel had just figured it all out can you just tell us sort of like the lessons learned of why you've thrived and maybe what you take away from their journey that you make sure amd

SPEAKER_89: doesn't play out well you know as a ceo we have to be paranoid every single day right so we don't rely

SPEAKER_96: on the past but i think there are lessons of the past and i think that probably the most important lesson that i can say for technology is you have to shoot ahead of the duck like you have to be thinking what is the most like your question jason great question we think about that all the time how do we shoot ahead of the duck and you know you have things that change you know technology is a beautiful place because you see big inflection points like five years ago ai was around but we wouldn't be able to gather this audience to talk about ai because people be like who cares but the fact is you had to invest many many years ago to be where we are today and i think you know i i like to say that you know you will you will be able to judge whether we've done a good job or not by how we perform five years from now like the decisions we're making will take you know five plus years to play out but that's the key thing in tech like nothing is fast but hopefully it's quite lasting and what do you think

Chamath Palihapitiya: is happening in countries not in the united states like what do you think is happening in chip design and

SPEAKER_96: all of these capabilities in china and other places right now we should believe that it's super super competitive i mean at the end of the day i think the world has recognized that um that semiconductors and chips are essential they're essential to national economies they're essential to national security and so assume that everyone's investing um i'd like to believe that we have a great head start you know because of the innovation pipeline because of you know the great uh companies that we have here but we should not be you know confused that everybody's investing and we need to keep our up our investments as well and i think that's why you know this whole idea of any one company can provide every solution that's necessary just isn't the case right i i love the idea of open ecosystems of uh you know companies collaborating of collaboration across the ecosystem so hardware software systems um you know collaboration across public private partnerships because that's what it's going to take like for us to win we have to be you know front-facing and realizing that bringing you know the the countries that win bring all of the smartest people and the best you know capabilities together and let them go as fast as they

SPEAKER_161: possibly can right really so thank you for being with us wonderful yeah great appreciate it thank you

SPEAKER_164: i'm chase lockmiller the uh co-founder and ceo of crusoe and i'm here to talk to you about the ai

SPEAKER_168: industrial revolution um i'm gonna start with a quote and it's from warren buffett in his 2020 shareholder letter shareholder letter to investors and he said in its brief 232 years of existence there has been no incubator for unleashing human potential like america despite some severe interruptions our country's economic progress has been breathtaking our unwavering conclusion never bet against america buffett's words were true then and as we enter this global race for technological dominance of artificial intelligence uh they ring even truer today american dynamism has always prevailed and it will continue to do so so in in in sort of the uh history of of really what's made america great is uh you know we live in a nation that's the freest nation in the world and we have uh we are just as rich in land and resources as we are in human ambition uh to drive progress and one of the things that's fundamentally enabled that progress to happen and that ambition to be unleashed is the leading investments that we've made in infrastructure over the course of his lifetime uh warren buffett got to witness uh investments in in power in transportation and in uh in power and transportation and in natural resources to uh to enable people to go pursue their dreams and live a better life now in 2025 we stand at a you know the start of a new era of infrastructure the infrastructure of intelligence investments and it's driving the biggest capital investment in human history uh this investment's being led by the hyperscalers uh who are investing hundreds of billions of dollars per year per year um to make this happen these are the companies with the biggest balance sheets in the history of business that are quite literally going all in to to make this happen and they're not the only ones you know there's also startups like crusoe and uh there's there's even nation states um that are following suit so so what's going on there what's the what's the prize that that they're going after um the you know the opportunity here is that uh for the first time in human history we've actually been able to manufacture intelligence um intelligence is the uh scarcest economic resource um in the history of the economy and and for the first time we're actually able to make it um and the opportunity here is to actually unlock access to what has uh historically been that scarce economic resource so um this is why the data centers of the future are not being referred to as data centers they're actually being referred to as ai factories it's a factory that takes as inputs data and algorithms and chips and energy and it outputs intelligence this is the alchemy of intelligence so this newly manufactured intelligence will spawn a new chapter of unprecedented productivity and development and that will serve to improve human quality of life so the idc estimates that ai will generate 20 trillion dollars in economic impact by 2030 so even if you can earn a small slice of that that hundreds of billions of dollars of investment will earn an amazing return for each dollar invested into uh business related ai is expected to generate four dollars and 60 cents uh as my friend jensen would say the more you buy the more you save um or in this case the more you buy the more you make and we can grow the pie together and usher in a new era of ai driven abundance so when we look at the history of american energy production and consumption uh as as the us industrialized we really ramped up energy generation and uh and also consumption but if you look at this chart you can see that you know it's kind of flatlined over the last 20 years uh where we're you know generating and consuming about 4 000 terawatt hours per year ai is fundamentally transforming this demand picture and uh and energy is quickly becoming the bottleneck to growth data centers are forecasted to account for 20 percent of the growth in power demand between now and 2030 and uh data center total power consumption is going to go from two and a half percent of u.s power consumption to 10 percent so what this means is that the technology industry that's sort of willing this infrastructure into existence fundamentally needs to bring its own power to support that growth which means massive investments not just in data centers but also in the energy infrastructure to support them and this will require people lots of people to build operate maintain uh and run these these large-scale energy investments um so if we look at data centers you know by the numbers i think it's important you know as people are sort of throwing around gigawatt scale data centers uh of looking at the amount of data center infrastructure that exists today uh northern virginia is sort of the center of the world for data centers but it's only you know at the end of 24 was only four and a half gigawatts today we have companies that are looking at building single five gigawatt facilities and if you look at this growth we're building more than a uh northern virginia every single year in the forecasted future so we need new in so if there's one thing that you're going to take away from this presentation it's that we need new infrastructure we need lots and we need lots of it and we need lots of people to build operate and maintain it this is what crusoe is focused on solving crusoe's in the business of activating energy for intelligence of building operating uh ai factories at scale from from the steel to the silicon from the electron to the token and if you look at our pipeline we have about 40 gigawatts of capacity that spans um all sorts of energy resources from new energy technologies like uh you know like like uh small modular reactors to uh renewables and and natural gas to to power this uh innovative future uh so revisiting my formula here i think we left off one critical component which is the people uh ai will be ai infrastructure will be the largest job creation catalyst that we've ever seen so i think it's important to sort of look at you know what this looks like in practice for the last year um crusoe's been building um a large large scale ai factory in abilene texas and uh you know speed is paramount again this event is winning the ai race uh in order to win a race you really need speed uh and crusoe's really been focused on on on using modular components on on rapidly scaling investment in in construction and infrastructure to support this and and and and we've actually built a lot of different modular components in in factories and brought them to site and they're kind of like uh they're kind of like lego blocks that sort of fit together to to build one of these ai factories at at rapid scale and speed um so if you look at if you look at what this looks like today um you know this is uh this is this is this is this this site will consume over 1.2 gigawatts of power and 400 000 nvidia gpus all in a single coherent cluster so uh this will essentially be a gigawatt scale computer to drive human progress forward um you know it's really amazing what you can kind of accomplish in a year you see just one year ago this is what the site looked like and this is what it looks like today um so what does this mean from a jobs perspective we have 4 000 people working on site every day to you know make this facility happen um and you know it's it's it's a bunch of different trades electricians and plumbers um and construction workers um and it's required a lot of capital too we raised 15 billion dollars to basically put this facility and and and bring it into existence um and it's also required manufacturing and that's and a lot of the critical components have happened off-site in these controlled manufacturing environments um but this isn't the only one this isn't a one-of-a-kind we also are building ai infrastructure and ai factories across america this site in west texas is going to be a gigawatt facility uh behind the meter with wind with incremental gas and grid interconnection uh we did a partnership with redwood materials where we built the largest uh uh we built the the largest microgrid with uh in the united states with 60 60 megawatt hours of batteries end of life ev batteries and uh 20 megawatts of solar to power an ai factory we have a partnership with ge vernova and engine number one uh for four and a half gigawatts of new uh gas generation capacity to power future ai data centers and finally uh we want to announce a new partnership that we're doing with tallgrass energy in wyoming that will initially power 1.3 gigawatts of total compute load uh alongside two gigawatts of power generation and ultimately we feel like this can scale to 10 gigawatts of power uh so we're really thrilled to partner with tallgrass so uh as a vertically integrated ai infrastructure company built here in america we believe that ai factories will be the ultimate economic engine creating utility for society uh and and and new jobs for the economy um this will usher in a massive new era of ai driven prosperity for the united states and i want to leave you with you know my final quote from warren buffett that you know in this ai race uh never bet against

SPEAKER_178: america thank you so is this stuff real you guys you know started off as like a you know sort of bitcoin

SPEAKER_138: miner and now somehow all the hyperscalers are uh asking you to you know build non-stop data centers

SPEAKER_181: why you guys um you know i think again it comes back to this being a race and one of the things that crusoe's been able to do better than anyone is execute at speed and scale and i know there's been

SPEAKER_138: like some of the biggest constraints around you know sort of you know water energy um you know the land for this type of stuff like where have you seen what parts of the country you know are you guys able to actually do this or have you seen any of the local regulators start to step up to you know

SPEAKER_181: make this stuff easier for you um you know we've been building quite a bit in texas you know abilene texas is this you know initial facility that's gotten a lot of coverage uh you know we just sort of announced a another facility in texas uh wyoming's been a you know big area of investment for us but

SPEAKER_173: um you know there's a number of other states that we're sort of evaluating investing uh to build large

SPEAKER_138: scale is it only going to be the like you know so more rural you know sort of red states or do you think that like you know oregon washington etc will start to you know sort of get together and realize they've got cheap hydropower and you know cheap water and we'll try and get you there uh no you

SPEAKER_181: know believe it or not we're actually looking at something in california wow yeah california

SPEAKER_138: gavin is going to bring you in i would imagine it's going to take like 50 years with that right yeah maybe we'll see yeah and you did do you think that the you know sort of hyperscaler demand obviously we were just you know on with lisa sue talking about the demand for chips over the next couple years that's obviously correlated to the use of demand with data centers do you think that's actually going to play out the way that all the public markets are you know sort of projecting or are we like in 1999 peak you know everybody thinks that fiber is going to be deployed all over the world

SPEAKER_181: turns out all those projections were totally off um i think the important trend to watch is sort of the capital investment that's happening and and the term over which that's happening so i felt like meta

SPEAKER_138: backed off on it a little bit like did they like for a little bit talk about they were going to deploy like crazy and then pulled back although he's obviously spending a billion dollars on chief ai

SPEAKER_181: scientists now yeah i think you know the the investments they're making in people are actually rounding errors compared to the investments they're making in infrastructure and i think that's something to sort of appreciate in this moment in time like people are betting their entire balance sheets these are the biggest you know and best balance sheets in the history of business they're betting their entire balance sheet on on you know the future infrastructure that's going to power the

SPEAKER_138: modern economy and then like the you know data centers like texas like what's the limiting factor like is it like workforce to actually go build these things is like materials is the cooling towers is it the chips is the hyperscalers giving you the like you know you know sort of contracts what's the you

SPEAKER_181: you know sort of limiting reagent um you know uh labor is definitely like a major constraint you know like i i said you know we have about four thousand people on site um every day uh we're gonna multiple sites that are operating with thousands of you know uh folks uh basically building this infrastructure so you know uh labor is definitely like one of the one of the big bottlenecks and we're you know we think it's really important for america to make these massive investments in the workforce uh to really build the infrastructure of the future anything that requires some real

SPEAKER_138: real re-skilling where it's like people from oil and gas or like construction having to go into just totally net new fields or is it something where you guys are actually able to pull on

SPEAKER_181: pre-existing talent pools pretty quickly um both you know there's there's a lot of existing uh you know labor uh you know at that facility in abilene we're we're actually pulling labor from all 50 states at this point believe it or not um so making like a company town importing people yeah you know we have about 50 percent of the people are are uh you know from texas but um you know the uh we are

SPEAKER_138: importing a lot of labor to to make the project happen and um you know do you do you see the company starting to go more full stack beyond just like the operations of like the you know sort of data centers or how do you think about like you know you started off with you know focus on like you know sort of energy arbitrage now into data centers where do you see you guys yourselves going

SPEAKER_167: over time yeah crusoe is a vertically integrated ai infrastructure business so you know data centers

SPEAKER_181: is a key component to that and you know i think one of the most important pieces to be building right now and and one of the hardest things to do at speed um but we also have you know this

SPEAKER_173: managed ai cloud services layer that um enables innovators to build uh large-scale ai applications

SPEAKER_138: on the platform makes sense well yeah chase thanks so much for uh you guys are joining us on stage and um yeah thank you appreciate the talk yeah thanks dylan okay everybody we got a real treat for you

SPEAKER_107: jensen wrong is here sit here sit here sit here the hot seat thanks for coming thank you

SPEAKER_209: thank you thank you the number one podcast in the world we were saying the number one company in the

SPEAKER_211: world wow thank you yeah you're a fan of the pod you listen to the pod this is norman our host yeah

SPEAKER_214: yes and there's steve uh what's the story with the jacket you got one of those you have like six i

SPEAKER_216: have something like 50 or 60 of them you really yeah wow what is that tom ford i think so this one

SPEAKER_214: is i think yeah it's nice i like it i tried that on it was like you way too much money well you guys

SPEAKER_220: are all so fashionable yeah coming from you guys it actually means something yeah oh yeah oops oh

SPEAKER_214: look at you look at you uh hey we've been talking a lot about opportunity you've talked

David Friedberg: shaman is like a model he is he is okay he's definitely in his head he's like

SPEAKER_224: is tom ford your favorite who's your favorite my favorite is whatever my wife gets me ah she dresses you as soon as she gets it for me it's my favorite yes same with me smart man um

SPEAKER_226: how you got nobody wears nobody wears a suit better than jacob good god yeah he's a handsome man just

SPEAKER_227: trying to keep up with you guys um i have two questions for you take them in whichever order you

SPEAKER_109: like um we've been talking a lot about job displacement opportunity short term long term obviously you get to see everybody applying the technology because hey listen you've got the best product in town to build on therefore everybody explains to you their hopes their dreams so you have a unique way of looking at the playing field you have complete information that we don't have so i want to know what you think don't worry we'll fix it um what you think kind of fix that and edit what you think about job creation transfer displacement etc and then the second one i've just always been curious you got all these important people knocking on your door you got suck you got e you got uh uh sam altman he seems like he's a little bit of a headache i'll be honest um but he's great he's great i'm joking i'm joking how do you allocate the h100s and whatever else you're selling them and still have them all like you because they must ask sometimes hey can i get

SPEAKER_214: extra i'll pay you extra so just the allocation of a finite amount of resources and then jobs

SPEAKER_235: first of all i wrote off five billion dollars worth of hoppers if anybody would like to have some extras just give me a call uh jobs uh we use ai across our whole company every single software engineer

SPEAKER_236: today uses ai not one left behind 100 of our chip designers use ai we are busier than ever and the reason for that is because we have so many ideas that we want to go pursue ai makes it possible for us to go pursue those ideas now that we're not doing the mundane stuff and so i i think the first idea is the more productive you are as a company um so long as you have more ideas you could pursue those ideas you'll go after those ideas and i i think that that ai in my case is creating jobs it causes us to be able to create things that other people would uh customers would like to buy uh it drives more growth it drives more jobs you know all that goes together the other thing that that to remember is that ai is the greatest technology equalizer of all time okay explain everybody's a programmer now yes you used to have to know c and then c plus plus and python and you know in the future everybody could program a computer right just have to get up and if you don't know how to program a computer you don't even know how to program an ai just go up to the ai and say

SPEAKER_239: how do i program an ai the ai explains to you exactly how to program the ai even when you're not sure exactly how to ask a question what's the best way to ask the question and i'll actually write the question for you it's incredible yeah and so it's a great equalizer everybody is going to be augmented by ai everybody's an artist now everybody's an author now everybody's a programmer now that is all true and so we know that ai is a great equalizer we also know that it's not likely

SPEAKER_236: that although everybody's job will be different as a result of ai everybody's jobs will be different some jobs will be obsolete but many jobs will be created the one thing that we know for certain is that if you're not using ai you're going to lose your job to somebody who uses ai that i think we know for certain yeah there's not a software programmer in the future who's going to be able to hold their own i mean you know typing by themselves yeah you can't raw dog it no no not

SPEAKER_246: anymore no raw dog not anymore you can't raw dog it and so tell us i'll be sure to go home and tell

SPEAKER_247: people yeah exactly you're not going to raw dog this yeah get your co-pilot on now what about the

SPEAKER_248: allocation of all these okay so the way we allocate is this yeah the way we allocate is this uh place a po

SPEAKER_250: okay let's say you go to the register you pay you order first you know first in in the old days with

SPEAKER_236: hopper it happened so fast it was impossible to keep up with the demand but now uh we we uh this we disclose our roadmap to all of our partners uh a year in advance gives everybody a chance to plan with us they decide how much power and how much data center space and how much capex they want to allocate we plan together we work on transitions it's really quite orally these days what's the

SPEAKER_253: lifespan now you you know i was looking into how they're amortizing you know these units four or

SPEAKER_109: five years what happens to this massive build out in your six seven and eight what will be the use of

SPEAKER_214: those computers if you keep building such great products that replace them at two three four

SPEAKER_236: times what do we do with all that concepts are happening right now the first thing first thing is every generation we increase the performance by x factors yeah um if the perf per doll perf per watt goes up by x factors whatever your data center power is we just increase your revenues by x factors right so perf per watt is equal to revenues perf per dollar equals the cost and so when we increase your perf per dollar by x factors we reduce your cost by x factors does that make sense that's the first idea and so every single the reason why we're moving so fast is we're trying to increase everybody's revenues we're trying to decrease everybody's cost so that we have the benefit of driving ai cost down as far as possible so that we can have thinking ai right it's not that we're trying to make you know ai so that generates a thousand tokens and that's it in the future you're going to be generating millions of tokens and that generates an answer as a result of that you got to think a long time and so you got to get that cost down the second idea is if you look at the residual value of nvidia gear right now hopper for example one year one year later it's probably about 80 percent 75 to 80 percent of the value of the original value and then one year later is another kind of like 65 percent and then one year later it's like 50 the reason and right now if you try

SPEAKER_250: to get hoppers in the cloud it's all sold out the reason for that is because cuda is so programmable and we're constantly the whole world not just us the whole world is doing open source development improving its effectiveness and so what's amazing is the performance of hopper increases over time because we're improving the software stack it hopper improved in performance by us and others by a factor of four right in the time that we shipped it now you can't get that out of a cpu right

SPEAKER_59: jensen can you explain to us um elon's tweet and the impact to you to your industry he said

Chamath Palihapitiya: we're going to have 50 million h100 equivalents by in five years from now and everybody started to feverishly do the math because if he has 50 million h100 equivalents then open ai will have that much or more meta will have that much or more google etc etc etc can you just explain to us layman what that means

SPEAKER_236: what he just said and how it impacts your business um one of the biggest observations about ai is that there's there's the industry of applications that ai has created it's a revolutionary technology every industry would will be revolutionized new applications will be created so on so forth that all the things that we know agentic ai reasoning ai robotics ai so on so forth we we know all those things now every industry healthcare education transportation you name manufacturing all revolutionized the one part that that that we observed and and made a great contribution to is that in order to sustain those applications you need factories of ai you have to produce ai unlike unlike software you write the software and that's it in the case of ai you have to continuously produce it generate the tokens right in a lot of the same ways that energy production was a large part of the economy a couple two three hundred years ago i think it actually peaked out at 30 percent yeah there's a whole there's going to be a whole industry of just producing tokens and this is going to be the new infrastructure just as we have the energy production infrastructure we have the internet infrastructure and we got to build out that plumbing and now we got to we have to build out the ai infrastructure my sense is that we're probably you know a couple of hundred billion dollars maybe a few hundred billion dollars into a multi-trillion dollar infrastructure build out per year yeah what

SPEAKER_271: what about manufacturing and the reason for that is because you want the new infrastructure which increases revenue driving your cost down right that's right what about manufacturing in the u.s

SPEAKER_38: so where are we we um you know we've seen stories of tsmc in arizona we asked this question earlier about how it's going is the u.s equipped uh what is it going to take for us to get there to have

SPEAKER_274: onshore fabs first of all you guys know you're talking about the united states uh the the uh i know that

SPEAKER_236: there's there's lots of concerns and and everybody's you know worried about competition and things like that but we are talking about america here this is this is unquestionably the most technology rich country in the world and this is the most innovative countries in the world and the computer industry i don't have to i have the honor to serve is the single greatest industry our country has ever produced i think we could acknowledge that yep the the level of leadership of the computer industry the technology industry is just unimaginable worldwide and so this is our national treasure this is one of our country's assets we have to make sure that we continue to to to advance it um on shoring next generation manufacturing is going to be insanely technology driven uh robotics technology ai technology you're going to have factories that are going to be orchestrated by ai orchestrating a whole bunch of robots that are ai building products that are effectively ai's right so you're going to have this in layers of inception and the amount of technology necessary to create that is really insane we've i i love president trump's vision bold vision of re-industrializing the united states that entire band of industry that's missing we out we outsource too much of it frankly we don't need to insource all of it but we ought to bring on shore the most advanced the most economy sustaining driving national security enhancing parts of the industry you know people always degrade down to tennis shoes we don't have to go there we just manufacture chips and ai supercomputers in arizona and texas we will in the next four years probably produce about half a trillion dollars worth of ai supercomputers about half a trillion dollars with ai supercomputers will probably drive a few trillion dollars worth of ai industry and so that's only in the next several

SPEAKER_287: years and and uh they're doing great arizona's doing great and so there's um there's a lot of talk

SPEAKER_289: about american competitiveness today and the white house ruled out its ai action plan and nvidia is making very big bets on the united states and so as a ceo of a global company what do you see

SPEAKER_236: are america's unique advantages that other countries don't have america's unique advantage that no country

SPEAKER_235: possibly have is president trump and let me let me explain why one uh on the first day of his administration he realized the importance of ai and he realized the importance of energy

SPEAKER_293: energy for the last i don't know how many years energy production was was vilified if you guys remember

SPEAKER_235: yeah we can't create new industries without energy you can't reshore manufacturing without energy you

SPEAKER_236: can't sustain a brand new industry like artificial intelligence without energy if we decide as a country the only thing we want is ip to be an ip only a services only country then we don't need much energy but if we want to produce things something as vital as artificial intelligence and we need energy and so i'm just delighted to see pro to accelerate ai innovation to accelerate the growth of energy so that we can sustain this this new industry and um you know go after the the new industrial

SPEAKER_38: revolution big big deal can you talk about physical ai versus data center ai we talked we talked a little bit about this today is there a threshold where you see physical ai accelerating and ultimately the deployment of chips outpaces the deployment of chips and data centers is that where the world evolves to or what do you think everything in the world of the world looks like yeah excellent everything

SPEAKER_236: in the world that moves will be autonomous someday and that someday is probably around the corner so everything that moves we already know that your lawn mower is going to you know who's going to be pushing a lawn mower around that's craziness unless you want to i mean it's you know and so so i think everything that moves will be autonomous and every machine every company that builds machines will have

SPEAKER_235: two factories there's the machine factory for example cars and then there's the ai factory to create the ai for the cars and so maybe you're uh a machine factory to build human or robots you need an ai factory to build a brain for the human or robot right and so every company in the future in fact the the future of

SPEAKER_236: industry is really two factories no tesla already has two factories right elon has a giant ai factory he's he was very early in recognizing that he needs to have an ai factory to sustain the cars that he has now he's got ais in the car but in the future instead of you know i imagine that in the future instead of a whole whole lot of people remote remotely monitoring air traffic control it'll be a giant ai that's doing the remote control and then only in the case of the the giant ai um can handle it with a person come in to to intercept and so so i think you see that that these industries in the future every industrial company will be an ai company or you're not going to be an industrial company

SPEAKER_17: there was a couple of moments throughout the course of this year where people almost threw in the towel and said oh we lost to china right there was the deep seek moment then maybe this week last week there was this kimmy model moment um but then it kind of fizzled out can you just uh explain to us how big of a threat they really are in terms of getting to supremacy

SPEAKER_05: getting there first to whether it's agi or you know super intelligence yeah excellent question um the

SPEAKER_236: chinese ai labs are the world world's leading open open model companies they they offer the most advanced open models open source is fantastic if not for open source we know startups won't exist and to the extent that we believe that the future is going to be the future industry is going to be today startups they're going to need open open source models and deep seek when it came out it was a great win for the united states it was an incredible win what people didn't and two two reasons first imagine if

SPEAKER_250: deep sea came out and only ran on huawei i just want us to pretend use that thought experiment totally right you got two parallel universe exactly could you imagine if qn came out and only worked on non-american

SPEAKER_236: tech stack and these are the top three open models in the world today it has downloaded hundreds of millions of times so the fact of the matter is american tech stack all over the world being the world's standard is vital to the future of winning the ai race you can't do it any other way we've got to be you know as you know any computing platform wins because of developers yeah and half of the world's developers are in china so speaking of developers the second the second i'm sorry the second thing is really big deal when deep sea came out we were thrilled for the second reason which is we now have a super efficient reasoning model and the reason for that is because the old models are one shot you give it a question everything was memorized you know the pre-training is basically memorization and generalization two concepts post training is teaching you how to think and so now with deep seek r1 kimi kimi k2 q1 3 you now have reasoning models that can allow that help you think and so the reason

SPEAKER_319: why i was so excited is if each pass of a thought is energy efficient then you can think for a long time

SPEAKER_17: right yeah the last question from for me is that we see uh this capital being applied to human capital in a way that we never thought was possible used to be nba players signing 300 million dollar contracts now it's you know uh model researchers and then there was a there was a post this weekend that that

SPEAKER_05: said that there was a person that was offered a billion dollars over four years by meta now if

SPEAKER_72: that's happening at this layer why hasn't it happened at your layer because you are the enabler of all of that and how do you think all of this human capital is going to actually play out first of all i've

SPEAKER_236: created more billionaires on my management team than any ceo in the world they're doing just fine okay and so and and they're doing don't don't feel sad for anybody at my layer yeah everybody's doing okay yeah my layer is doing just fine i tell i but but the important the big idea though is that you're highlighting is that the impact of a 150 or so ai researchers can probably create with enough funding behind them create an open ai it's a it's not a 150 people yeah it's not a it's not well deep seek's 150 people moonshots 150 people right right and so i mean look at the original uh open ai was about 150 people uh deep mine you know and they're all about that size i think i think um you know there's something about the elegance of small teams and that's not a small team that's a good good-sized team with the right infrastructure and so that kind of tells you something 150 people if you're willing to pay say 20 billion dollars 30 billion dollars to buy a startup with 150 ai researchers why wouldn't you pay one right yeah speaking of options by the way we told me we need to wrap because i don't know but

SPEAKER_335: we have i'm going to do this one question somebody who is inside your organization told me with the options that you have a secret pool of options and that you will randomly just if somebody does a great job dropped a bunch of rsu's on top of them and that you have this like little bag of options you carry

SPEAKER_323: around and that you have them out that's nuts is that true i yeah i'm carrying in my pocket right now

SPEAKER_235: so listen so this is what happens i review i review everybody's compensation up to this day

SPEAKER_236: yeah at the end of every cycle when they present it and they said they send me everybody's everybody's recommended a comp i go through the whole company i've got my methods of doing that and i use machine learning i do all kinds of technology and i sort through all 42 000 employees and a hundred percent of the time i increase the company's spend on opx and the reason for that is because you take care of people everything else take care of takes care of themselves yeah all right well done thank you

SPEAKER_341: thank you jesse great to see you great to see you we have an event in la we'd love to continue the

SPEAKER_344: conversation so we'll send you the world's number one podcast there you go thank you