SPEAKER_00: all right everybody welcome back to your favorite podcast it's the all-in podcast it's the summer it's august 6 having a hard time getting a quorum here on the podcast but david friedberg is here david friedberg is back our sultan of science how you doing brother great to be with you

SPEAKER_03: it's great to be with you and everybody loves brad gerstner is here he's your bruce wayne if markets are your game he brings that namaste to your payday yes his glasses at discount and he'll get you one of those fancy trump accounts all right welcome back to the program brad i love it i love it you bring the rhymes back i bring a little intro back we've been trying chamath is on the road right now chamath is on the road but we will get a field report from chamath and uh i i call daniel somehow sax is going to be here but you know how he is he's always late because you know you get a phone call from very important people but he will break in at some point oh wait i see in the text here oh there he is he made it how do you like my beautiful

SPEAKER_09: summer it's incredible it fits perfectly you look warm i don't know how chamath does this

SPEAKER_03: well here's the report everybody as everybody knows chamath is on the road he uh oh here he is he um this is a photo uh sax he went he went to check his data center progress uh i think that's in

SPEAKER_22: colorado or nevada where he's building a data center i think that's on dune oh it's on dune yes

SPEAKER_30: four oh yes there he is admiring himself blue oh look here's now you know when a meme has reached its peak when your wife starts dunking on you there it is and here we are this was at the christmas party i

SPEAKER_33: think oh bro you were on cnbc with andrew ross sparkin oh there you go i wasn't sure if it was my twitter feed that was just selecting into it but it nearly hit everyone right this was a viral thing this has

SPEAKER_36: hit everything all right listen we got a lot to get to enough with the shenanigans and small talk google had uh two major shakeups to its ai staff on wednesday demis hasabas has moved to chair of deep mind and chief scientist at google reports describe this as demis stepping down or being kicked upstairs we'll get into that but google framed it as a promotion and says he was stepping up here's axios's quote explaining the shakeup quote google's gemini 3.5 pro is months behind with some company sources telling axios that it's in part due to low morale interesting several top researchers including gemini's co-lead have left the firm for competing ai labs jeff dean plus three other ai superstars are leaving google to start a company called discovery loop dean is a legend freeberg and i think you worked with him at google one of the world's great ai engineers he was employee number 30 joined in 1999 and has worked there for what i understand continuously for 27 years discovery loops going to be focused on deep scientific breakthroughs in ai google shows down four percent on the news of dean leaving so 200 billion in lost market cap if you want to correlate those two things freeberg this is your alma mater what are your thoughts here is this creative destruction maybe these people weren't

SPEAKER_03: delivering and they wanted fresh blood or is this just the siren call of doing a startup in an age of

SPEAKER_36: unlimited capital for ai and unlimited opportunity just being too much for the ogs at google to not

SPEAKER_35: take advantage of maybe it's the third bucket which is if you're the board and the management you're having a debate about how to best deploy capital google has made a commitment to deploy 200 billion dollars in capex this year in ai infrastructure data center build out because of

SPEAKER_42: the capex and accelerated depreciation making an investment in ai compute in the us right now is hugely tax advantaged and because of the extreme demand for compute it's a pretty obvious kind of roic model return on invested capital so if you make this sort of an investment you have significant demand for that compute infrastructure you're very good at running the compute infrastructure that capital can deliver massive profit returns for you with very high confidence in some forecasted period building the most advanced frontier lab driven model also takes tens of billions of dollars of capital and the question really is can you deliver the profits from the model and in a world where open source is becoming so good and open weights models are catching up so quickly and all the frontier labs are catching up to each other so quickly does it really make as much sense to deploy tens of billions of dollars against building a model and i think that the scientists that we're seeing transition out are the scientists that have been at the core of model development of making these frontier models and they were certainly first out the gate you can look at some of the early interviews with jeff dean from a couple years ago where they actually had a chat gpt equivalent internally a year before chat gpt came out from open ai google chose not to release it for fear of cannibalizing search and so on that's when sergey stepped in and there was this whole kind of revitalization but as time has gone on and as everyone has competed on models as we've talked about many times on the show i think it's pretty obvious that it is very hard to get the same sort of return on capital invested in model development as it is in capital invested on compute infrastructure and being model agnostic what google has is probably one of the greatest install enterprise bases in the world for compute so they have the most enterprise customers they have the most consumers and in both cases they don't necessarily need to have the best model to make an incredible business they can be model agnostic they can work with anthropic they can work with open ai they can work with spacex they have a significant ownership stake in spacex and in anthropic and they can work with all the open weights models they can host them all so now if you're one of the great computer scientists you're demis you're jeff dean you're this whole crew and you're inside of google and they're allocating capital not to your models not to the things that you're most interested in but they're allocating capital to infrastructure and data centers and supporting the broad ecosystem of models you start to say well given the fact that i can go to the road and visit brad gerstner and a couple other people and raise a couple billion dollars at a multi-billion dollar pre-money with a powerpoint deck because i'm the greatest in the world at doing this that might be a better path for me and i think that that's the moment so i the way i would frame it is capex is high alpha low beta in data center infrastructure that capital and model development theoretically could be high alpha but it's very high beta it's a very risky way to deploy capital so so if i'm the board i'm the management i'm deploying more capital and compute infrastructure less capital into

SPEAKER_43: model development that's what i think's going on brad what's your take on this i think david nails it

SPEAKER_46: i mean listen the same thing's going on at microsoft right satya is out this week saying you know citing morgan stanley's report and saying they're seeing over a 30 return on invested capital in tokens as a

SPEAKER_47: service right so in the infrastructure business so i think david's exactly right those are such good businesses right you you you deploy capital everybody's running it from you but the scientists who want to be involved in super intelligence who want to cure cancer who want to be on the frontier of these models right they're sitting there dealing with this channel conflict at google because you know google cloud wants all of the compute in order to rent it out to anthropic and those for those building the frontier models internally want that compute in order to compete with anthropic so you have this inherent channel conflict uh between those wanting to build the models i think david said it really well um and i think that's a that's a big challenge for them it looks like it's being resolved in favor of being more of an infrastructure company so where it is you know telescope out for a second spacex also reported this week they also have channel conflict they're renting out their compute to anthropic at the same time they're trying to build their own model with grok and cursor you have that channel conflict at google you have that channel conflict at microsoft although i don't even really see them pushing the frontier anymore in terms of models meta's talking about getting into the infrastructure as a service game and then at anthropic and open ai you don't have any of that channel conflict they say we're not in the infrastructure business we're only in the model business so i think it's a you know uh uh a clarifying view as we look forward that we may in fact not have those companies on the frontier of model development if all these people

SPEAKER_35: leave by the way thanks to the law passed on capex depreciation if you assume a 26 corporate tax rate every dollar you deploy in capex because you get to write it off in this year you're basically getting

SPEAKER_00: 26 off you know that's money you get right back yeah yeah hey uh sax let me have you comment on uh this as well polymarket which companies will have the number one ai model by the end of this year on

SPEAKER_53: december 31st um now of course in the last time they did this anthropic one so they're not on the list they're the winner but who will have it uh going forward open ai 32 google 20 alibaba 14 and then you got moonshot xai meta by dense all at about 10 percent so sax your thoughts here on what's the better business is the better business being in the language model frontier model or is

SPEAKER_57: that getting quickly commoditized and really you want to be in the token sale business or is that also going to be a commodity and you just need to be on the application layer here's what i think is

SPEAKER_58: going on in terms of the the market structure is when i saw this google news my reaction was and then

David Sacks: there were two because like brad was saying we used to have five major companies in the hunt to be the leading frontier lab the leading frontier model just a year ago now we're really down to just anthropic and open ai so the market for frontier intelligence has become a duopoly now elon is still in the hunt i'm sure google would say they're still on the hunt but like brad is saying they may have contradictory incentives there because they can actually do quite well just with their compute so i think that the market for frontier intelligence has become a duopoly i think it's a very powerful duopoly i don't think it's being commoditized i think that what we're evolving to is a two-tier market structure where there's a market for frontier intelligence and there's a market for let's call it kind of commodity or lagging intelligence whatever you want to call it that's six to 12 months behind there is a market for those tokens those models but the reality is you can't charge anything for the weights you can charge for the compute you can charge for the

SPEAKER_60: inference that you're providing you can charge for essentially consulting services to help put the whole thing together but if you're not at the frontier you can't charge for the model layer itself if you

David Sacks: are at the frontier you can charge a premium and that's where anthropic and open ai are and i think the proof for this is just you look at the growth rates of these companies the latest we heard is anthropic is now over 80 billion of arr started the year at 10 it had forecast 100 billion as exit arr for the year and most people said that that would be impossible to achieve now it looks like they're going to do it with a couple of months to spare so their estimates are going up i mean 110 120 or higher for

SPEAKER_60: end of year arr open ai seeing acceleration so i think what you're seeing now is a very clear bifurcation of the market you've got a frontier model duopoly that can charge a premium i think of it like apple you know apple is competing against android it's open source android actually has more users in the world but all the monetization goes to apple because people are willing to pay for the premium experience i think in a similar way people are willing to pay a premium for true frontier intelligence if it's really at the leading edge but if you're not the leading edge there's a huge market for that too

David Sacks: but it's highly commoditized people are just willing to pay you for the compute so i mean that's what i

SPEAKER_53: see happening right now yeah what do you think jason what do you think uh well if you look at google cloud they posted 82 year over year revenue growth which is something we've never seen uh in the history of these cloud providers elon musk and xai just had the spacex earnings we're going to get into

SPEAKER_66: that but they also had massive uptick in their elon web services as i've dubbed it and if you look at google i still think google will be the number one uh ai company because they have so many people using ai inside of their products already they have five products now with over 3 billion monthly users each android search gmail chrome youtube all have over 3 billion if you've used any of these products recently uh they are becoming ai first products youtube especially but obviously chrome and gmail you're seeing um tools pop up there for ai and then freeberg you kind of alluded to this they have 13 products total with over a billion and that now includes gemini in q2 gemini had over 950 monthly

SPEAKER_37: active users tripling year over year they will be the number one ai company in terms of consumer usage by far i think this year that doesn't mean that the um frontier models are not great businesses they obviously are but i have been using exclusively non-frontier models and for 95 of the jobs i'm

SPEAKER_36: doing sacks it's good enough and i just posted about this you know um and elon and i got into it a little bit here and i think you referenced this in our group chat uh i i tweeted just the other day the difference between the open source models i'm using in frontier is negligible already i believe that to be a true statement for the work i'm doing and he said elon responded back to me it's actually a world of

SPEAKER_03: difference you know if you're doing something other than making a copy of a video game or you have incredible speed needs the frontier models are not necessary anymore they're just not necessary the people using the frontier models are doing it because their company set it up and they it's too

SPEAKER_36: hard to implement open source right now but it's going to get easier and easy to implement it so i'm

SPEAKER_22: still going with open source and gemini being the leaders yeah look i think it's true for your use

David Sacks: cases that let's say the cheaper commodity intelligence that middle of the market is good

SPEAKER_60: enough look an android phone would be good enough for me i could get by on a cheap android phone you know what i still pay a premium for this because i use it so much so if you're a business that let's say you are a hedge fund and you're in a highly competitive industry you don't want to take the chance that you're not getting the best intelligence to power your models you know and there's a lot of industries like that where the competitive dynamics will drive you to pay for the best intelligence

David Sacks: there's also situations this goes back to the blog post that decagon posted which is if you're

SPEAKER_60: looking for use cases you also want to use the true frontier because again when you're dealing with immature use cases you don't know where the value is going to be and you're searching for opportunity to use ai you just want to use the best because again the return on finding those use cases is going to be so much greater than the small premium you're paying at the token level so i think there's a lot of examples like that when you know the use case is immature where you're in a competitive industry where you're just deploying ai you want the convenience of the full so why not go frontier models yeah again you know unless your employees are doing something stupid like you create a leaderboard and they're token maxing i don't think the cost is that great and again the benefit that you're getting is huge so a lot of people just like give me the best i'm willing to pay a premium

SPEAKER_35: for the best i'll take a slightly different take i think that it's not necessarily do you take the

SPEAKER_42: best model or the open source model i think that there's a blend that's happening at least that's what i see for example we'll use open source open weights for a vast majority of simple workflow applications but when it comes to specialized applications where we really need to have high quality model proficiency for example in life sciences and genomics modeling i'm going to go for the premium model if i'm working at a media company and i'm trying to do ai rendering of video i'm going to use gemini's model that does video it is the best model or sora or whatever the best model is for that particular application so i think the idea that there's kind of a model that you pick for everything i think is the false assumption on the consumer side it is likely the case that the consumers are not going to be using some open weight model because they can pay 20 40 bucks a month and get chat gpt or gemini or claude and be very happy paying 40 bucks a month and they'll basically be able to minimize their cost to run that for consumers for enterprise i think the enterprise is going to be very active in selecting a blend of models that are going to make the most sense very cheap open weight model for simple workflow applications individual employees spinning up an app whatever and then more complex models for those really key workflow tasks and then specialized models and i will say it is way too early to count gemini out on building for sure incredible specialized models they have the best video data they have the best life sciences data they've been working on this for far longer than anthropic or open ai on the life sciences side they're very well ahead on that front i mean demis is still going to be running isomorphic labs so when it comes to these specialized models verticalized specialized models like video life sciences protein folding i think these are the things where you're really going to see gemini shine and then every enterprise is going to have a mixture but hey if you can be the cloud service provider with that mixture of models which is what

SPEAKER_43: google gcp can now be i'm going to sign up for working with gcp versus working just with anthropic

SPEAKER_36: one of the things this has created is downward pressure on the pricing we saw open ai and claude do massive price cuts for tokens so they are reacting they're not taking it sitting down and the orchestration between these models is being built into a lot of harnesses inside of enterprises so

SPEAKER_22: what's your take on the downward pressure on token pricing or is this just great for consumers and

SPEAKER_47: enterprises because listen we've got massive competition that's the thing america's winning this is exactly what you want we have massively competitive market we have chinese open source domestic open source frontier national labs that are doing what they're doing we have downward pressure on pricing you know david reference to duopoly you know i think it's hard to call it a duopoly when you're you know only a few years into this and you have giants like amazon microsoft and google i do think he's right i do think they've emerged you know as the pure plays their revenues would

SPEAKER_46: suggest that they're you know they're gaining share of wallet but there are two points i want to make here because i think they're non-consensus views that were spoken this week one was elon's response to you jason right over the last two weeks everybody's been saying that the chinese have caught up that

SPEAKER_47: open source tokens have caught up in intelligence that they're much cheaper etc and elon comes out and says not so fast we're entering the singularity and the frontier models are way further ahead than people think i believe that to be true i think for your use case they're very similar but i don't think that's the most sophisticated use case that people are trying to train on and trying to experience and then jensen came out this week and said closed models are actually cheaper you know if you don't have to build it for yourself if you don't have to uh you know the training costs and a lot of expertise to fine-tune and maintain and guard rail and keep it safe so he's basically making the argument that not only are the the frontier models further ahead but that the cost differential between the two is not what everybody's making it out to see to be which i think explains why they continue to run away with it on the revenue side of the equation um but i think we have healthy competition i you're right jcal you know for the vast majority of use cases i think token consumption is going up for the open source guys while share of economics is going up for the frontier labs i think that's what we want to

David Friedberg: see yeah and it's just android versus iphone all over again one platform makes the profit one gets

SPEAKER_37: the majority of users at least globally and usage uh all right let's talk spacex here uh they had their first earnings report as a public company shares dropped 13 percent uh i think because people

SPEAKER_66: were a little concerned about the surging ai capex it's down 30 since going public in june but

SPEAKER_53: it's now trading at it seems to have settled in at a 1.4 trillion dollar valuation went public obviously above 2 trillion q2 results were uh spectacular is the only way to put it 7.8 billion

SPEAKER_36: in revenue up 92 percent year over year let that sink in uh and 67 quarter over quarter ai revenue elon web services more than tripled quarter over quarter to 2.6 billion dollars that's not cursor that hasn't closed yet uh but that's going to be one of the great purchases in history this is from elon web services uh renting out compute specifically to anthropic and google from the colossus uh collection of servers but capex was up 18.4 billion in the quarter that's 6x year over year obviously you can do the math there for a run rate of about 75 billion dollars i'll stop there and get your reaction brad

SPEAKER_83: to the spacex ipo i know you've been tracking this and commented on it yeah i mean listen i think that

SPEAKER_85: won't first let's start off 1.4 trillion dollars of value creation for this company is extraordinary so the fact that from peak to trough it's down 40 or 50 from the ipo we had that chart out a few weeks ago remember that within six months of the ipo almost all these tech stocks are down 50 percent peak to

SPEAKER_47: trough we see it again here with spacex i thought it was a really solid quarter i thought his guides were pretty extraordinary a hundred billion in arr by the end of the year and he pulled forward the one trillion dollar target in arr by a year from 2031 to 2030. now to just put that in perspective morgan stanley's 2030 revenue estimate is 325 billion which is also extraordinary remember this company did 18 billion in revenue last year so whether you're taking morgan stanley's numbers or elon's numbers clearly the market is not pricing that in at 2 trillion we were pricing ahead a couple years i think now it's you know the the value reflects kind of where we are the market has questions about a few things here's what they are number one on the rental business the rental of compute business he rented out a huge block of compute to anthropic it's the question that we've been talking about here are you going to use the compute to build your own frontier model or are you going to rent it out and if you rent it out are you going to be able to find those people who have the capital to off take that compute he's talking enormous numbers 10 to 20 gigs and people are wondering how they're going to be able to finance that and remember those businesses the gpu rental businesses tend to trade at very low multiples look at core weave etc on the frontier model business i think this is the sleeper i think he said on the call that grok tripled tokens in the month of july that doesn't include cursor cursor was already on a path to go from 3 billion to 10 billion by the end of the year cursor plus grok could be at 10 to 20 billion by the end of the year that would be an extraordinarily valuable asset going to trade at a much higher multiple than the data center business and then of course we haven't even talked about starlink and what he's going to do uh you know i think going to run the table on mobile so this is the normal consolidation we have funds like uh across silicon valley that are distributing their shares the stock is traded down a bit nothing surprising surprising to me here now it's all about execution i think the most important thing to watch the two most important things to watch are number one how do the grok and cursor revenues end the year and number two um you know the traction they get on um you know continuing to replace traditional

SPEAKER_88: mobile carriers with starling the distribution started i think today or yesterday i got my first distribution from a fund i'm in i'm in a couple of funds that are in spacex seems like everybody's in

SPEAKER_53: that and that will obviously create downwind pressure if you are amongst the people who want to cash out and been in for a long time but i'm holding these for my grandkids sax your take on these spectacular

SPEAKER_30: yeah i guess is the only way to describe them results coming from a vertical that wasn't part of

SPEAKER_58: spacex's business but nine months ago yeah look i thought it was a very bullish earnings call i was

David Sacks: a little bit surprised that the stock went down after the earnings call because not only was it a beaten raise but also i think elon spoke to a lot of their plans the only thing i would add to what brad said was around starship elon basically said we all saw it right that the starship test flight was successful the starship floating in the ocean the heat shield worked that's going to enable more flights of starship now at a more accelerated rate that paves the way for the v3 satellite which enables much more bandwidth for the starlink network which then powers the whole direct to cell play so you had that piece of it i mean just the whole telecom aspect seemed very on track and they're very bullish about that and then you've got the whole ai data center play now on the data centers

SPEAKER_60: i think what they said is that they expected to go from 1.4 gigawatts to compute to about two by the end of the year and elon said that the spot price for computes in the 30 to 50 dollars per watt

David Sacks: range so you know you do the math that gigawatt is a billion watts so 30 to 50 dollars per watt means 30 to 50 billion per gigawatt and i think they're at the high end of that range right now so when elon says look we're going to end the year at 100 billion of arr all you have to believe is that they're at two gigawatts of compute running for 50 a watt to hit that that doesn't include starlink or the launch business or the grok cursor piece or any of these things so i think that's why they're

SPEAKER_40: so multiple ways to win is what you're saying sax there's multiple ways to win with the stock i think starlink's just an unbelievable juggernaut cash machine if you look at the financials

SPEAKER_42: their segment reports space connectivity and ai and on the connectivity side the starlink side they generated 2.6 billion dollars in adjusted ebitda you can kind of approximate that to be kind of operating cash flow space was kind of you know negative 200 million to call it break even and ai was plus 1.1 billion but ai to brad's point it's unclear whether the pricing they're getting on compute rental today is temporary and at a premium because of the lack of compute available in the market today and people that need compute are paying elon a premium for that cube so i think there's a question mark where that goes but the connectivity piece on starlink 4.3 billion in the quarter and 2.6 billion in adjusted ebitda he's got 12 million subscribers that's doubled year over year 66 arpu per month what people are paying per month and he grew 20 quarter over quarter so if you extrapolate this out he's pretty close to being at a 24 million subscriber run rate on this multiple i'm assuming this enterprise stuff which is like airlines and other things scale which they seem to be scaling with the consumer business starlink alone could be generating on the order of 40 billion dollars of revenue top line with a huge amount of that flowing to free cash that could be a 30 billion dollar free cash flow within the year that alone provides the cash flow to fund much of what elon's doing and if you just put a 30x multiple on that which i think you can because these subscription businesses are very high renewal rate very low cac i think you could probably get a 30x just on the starlink business the starlink business alone could be a trillion dollar market cap within two years within 18 months let's say that i think funds all of the rest of this is kind of science projects and upside so i'm kind of making a bull case it's crazy to me how well the starlink business performs and you can see it in at&t and verizon huesnet via sat i mean these companies have been decimated i used to have a huesnet satellite dish on my sonoma county ranch in order to get internet that's what we had to use it was like you know 200 bucks a month or terrible because those are

SPEAKER_40: terrible service orbit right and they take forever to terrible service and that market got decimated

SPEAKER_42: by starlink and if he launches the handset thing that subscriber growth is going to go right now he's adding two million subscribers on the consumer side a quarter you could see that going to four to five million a quarter you could actually see an acceleration in the consumer subscription

SPEAKER_100: 400 million mobile subs just in the united states just i think you can make you can make the bull case

SPEAKER_43: on starlink alone and then the rest of it is like hey is elon going to do well with investing the excess capital that's spitting off of starlink how's elon going to do with that money well i don't know who else i give it to to like you know do what he's doing with starship and with ai compute and the

SPEAKER_33: terra fab oh my god this is a science fiction uh i mean like if you want to talk about county texas

SPEAKER_43: how the us gets off of this dependency with taiwan and china from semiconductors if elon takes this on

SPEAKER_42: his shoulders and he delivers what he's showing as a vision here today this is going to be the greatest

SPEAKER_85: semiconductor fabrication site on planet earth well you know i i would say something you know david to your point you know how many ceos or founders would just take that starlink business which is such an exceptional business trillion dollar business going to two trillion and they

SPEAKER_47: would not take any of these other risks they would not do terra fab they would not try to build out the data center they would not try to build their own model that's highly risky but highly important investments that are being made i mean it is heroic and important that we have this level of i just think um bridled enthusiasm for innovation uh on the frontier that elon's doing and i wish we saw more ceos more public companies willing to take this level of risk we just got done talking about you know some ceos maybe that were taking less risk because the safe bet was was easier to make elon refuses just to take the safe bet he's taking all the dollars from this thing where he has an extraordinary business and plowing them back into these things that are critically important to the united states and by

SPEAKER_37: the way brad such a good point because if you look at other ceos and other management teams they're

SPEAKER_66: getting in on this they're starting to realize that buying back your shares giving dividends is not as important as betting on the future doordash got taken to the woodshed because they're investing too much in capex obviously google got smacked with their capex spend so that keeps happening over and over again and just on the headwinds that spacex is going to face the arguments that i think will turn out to be wrong but they're valid to talk about here are hey is this demand for tokens and compute

SPEAKER_36: going to keep up or does on-prem and desktops and open source models getting smaller better does that actually mute at some point demand i don't think it does i don't know there's an upper uh i don't know there's an upper bound for on-demand intelligence the second one obviously is starlink is for people who are in a rural neighborhood if you've got verizon fiber to your building or spectrum you're not putting nor can you put a starlink on your building so the piece there that's going to be explained probably in the next year or two is every single tesla sold is going to have starlink in it when they get that merger done what that means is you're going to have wi-fi networks uh connecting any phone to any tesla say all those robo taxis out there you'll be able to connect also directly with the next generation of starlink so your phone will be able to direct if it's got clear line of sight it's going to be able to connect to any tesla on the road which there are many that all future ones will have a starlink built into them so those are super promising and then finally you know there's been a lot of speculation about the valuation brad you brought it up i think that liquidity when

SPEAKER_66: people were asking you and i heard you talk about it hey private companies venture capital we are a voting mechanism and then when it goes public it becomes a weighing mechanism and sometimes you'll have this moment in time uh where there's hand-wringing about those valuations and the hand-wringing peaked in the last quarter you had 160 times uh price to sales ratio for tesla when it first came out 160 times right you take this two or three trillion dollar market cap and you put it against a smaller revenue number well if you look at the revenue number increasing now we're down to a 45 times price to sales ratio so some kind of uh balance is occurring here yeah brad between these private and

SPEAKER_84: public markets as well as the increase in revenue yeah i i mean honestly i think this is all super

SPEAKER_46: healthy i think the spacex ipo was extraordinary i think the consolidation here is perfectly predictable and now you have a company at 1.4 trillion that i think if you take a three or four year view

SPEAKER_47: you can see yourself tripling your money in this business at a very reasonable valuation on the morgan stanley numbers or on the elon numbers or whatever but that's always been the bet do you believe that elon is the greatest innovator and a great allocator of capital but the price of entry matters right when you get carried away on day one of an ipo and you buy this thing over 2 trillion you got to know that this is going to happen i was on cnbc the day of the ipo and i said i would want to own this company but i'm not sure today's the day i would buy the company right and so i you know entry price matters i mean it's just a fundamental but but let me give you another one you know like we've talked about the anthropic ipo uh or a lot of people have talked about it later this year i hear a lot of people saying 1.5 or 2 trillion dollars david just talked earlier that it's going to be run rating over a hundred billion maybe by the end of the year that's like 10 to 15 times revenue that is not that much for a company that just grew 10x and is rumored to be profitable in q2 and so i look at the market the consolidation we saw in the month of july you know we put in the leopold bottom hopefully in july that you know a lot of semi stocks were done hey hey listen the guy's doing great he can he's apparently still up 80 for the year just made another big private investment i i i think he's done an extraordinarily good job building a firm in a short period of time but the market did panic around that yeah um as as he had to cover i think all of that is really good so as i look ahead marching to these ipos later in the year on the back of the spacex ipo i think we're in in really

SPEAKER_46: good shape um you know particularly if these revenues continue at pace you know what elon's

SPEAKER_35: really good at is just building stuff like factories physical physical physical sites that is such a core advantage in this world where everyone's competing for data centers and fabs the software

SPEAKER_42: layer needs hardware in the physical world in order to deliver their software services and there is no one better than elon at actually doing that look at how gigafactories have been stood up around the world this is his core competency so brad like when you put elon up against a dario and a sam and even an alphabet which has 27 years of doing this i i mean man elon's got a core advantage of this is what

David Sacks: this world comes down to he said something like that on the call where he said look putting up data centers is nothing compared to the difficulty of putting up a rocket right it's like you know creating data centers is not rocket science so they take some of those hardware expertise that they have

SPEAKER_60: from spacex and they put them into data centers and that's why they've been able to stand up you know more data centers or bigger data centers faster than all the competitors a couple points there is it clear why starship is so important to starlink okay let me just explain this quickly so basically spacex has developed a new v3 satellite that has 10x the bandwidth

David Sacks: of its v2 satellite so currently the starlink network is powered by v2 satellites they deploy them on the falcon 9 rocket and they launch about 27 satellites per launch and that adds about 2.6 terabits per second of total network capacity starship deploys 60 of these v3 satellites per launch

SPEAKER_60: that would add 60 terabits per second of total network capacity per launch so over 20 times more capacity per launch that's the power of it so if they get starship working by the way the last test not only did it prove that the heat shield worked my understanding is they actually launched

David Sacks: or rather they deployed 20 v3 satellites as a test and they were able to make connection with those satellites and prove that it worked they even had cameras on them the reason we were able to see

SPEAKER_102: the starship was because they're like yolo let's put some cameras hd cameras on them right now i think

SPEAKER_60: those satellites basically it was just a test and they they burned up so i think the next big milestone here will be when they launch starship with let's say 60 of these v3 satellites put them in the correct orbit make connection with them add the bandwidth to the network that's going to be a big milestone but you play this out to his logical conclusion and the bandwidth available to the starlink network

David Sacks: goes up 10x or eventually 100x times and that's when they can do all the interesting things like direct to cellular there were some interesting hints that when shotwell talked about about with ground

SPEAKER_131: stations about what they could potentially do there and i think and they might buy t-mobile or something like that sax it's easily within their range of purchases and i think elon mentioned something

SPEAKER_60: about potentially the the starlink network could eventually handle roughly half of internet traffic so i mean this this thing could get so much bigger than just 12 million subscribers to your point freeberg but look i want to actually talk about the data centers for a second brad i do have a couple of questions about this so elon mentioned that okay we're going to be at two gigawatts by the end of the year he said that we will be at five to ten next year closer to ten than five so let's just say eight okay so i'm just making that up but it's on their range so let's just say that's an ad of six gigawatts so they go from two to eight okay to me there's two questions there one is how do you know that the spot price is going to stay where it is you know can it stay at 50 dollars per watt how do we know how do we track that how much risk is there around that i got the sense on the call that elon thinks that number is going up because the market is memory constrained right now i think he mentioned

David Sacks: that we might see a 20 increase in memory production next year but the demand is going up 200 plus so the

SPEAKER_60: market is constrained by whatever the bottleneck is at that time right now the bottleneck is memory so where do you see the spot price going how do we know how much risk is around that and then the other question i would have is if you go from two to eight gigawatts that you have net a six we know that a gigawatt power data center is you know 50 billion of capex right so six incremental gigawatts of compute would be 300 billion of capex next year assuming they build that right i mean they have optionality around that i'm sure so how do you finance that you know what's the most non-dilutive way they said their payback is a year or less i'm sure that's tied to the spot price so you only have to finance it for a year and the question do you think nvidia gives them that financing or how will this play out i guess

SPEAKER_46: is my question it's a great framing david first it's 50 billion dollars per gigawatt to build minimum okay so you're 300 billion dollars so in order to finance that it seems to me you either have to go

SPEAKER_47: into the market and borrow the money or you have to do a dilutive equity raise neither of which they want to do um or you get nvidia to backstop it um which they've indicated that they're going to do more of but the problem there is nvidia shareholders don't want them back stopping unlimited because the fear in the world is that that sprite spot price at some point right may go against you and when it does the payback period changes now nobody thinks that the payback period is going to be one year even though the spot price is suggesting that it is that today right just a few years ago people thought you would get paid or not a few years ago a few months ago people thought you'd get payback over four years so you basically spend 50 you then earn 10 to 15 per year you get payback over four to five years and then hopefully you get the six year which really takes you up well above 20 percent in terms of your returns um right now the shortage is so acute and the willingness to pay from the front frontier labs is so high because they all recognize they're on the verge of some massive breakthroughs that they're willing to pay three four five x market pricing in order to get at scale compute and that's what happened with the anthropic deal uh with spacex i think anthropic would buy a lot more of that today if they could same with open ai you're saying brad they would be

SPEAKER_136: willing to overpay by a factor of up to five x well that's the 50 that you know that's the 50

SPEAKER_47: per watt that david was referencing they would be willing to pay this 30 to 50 if they could get at scale compute that would give them a competitive advantage over the other people in the market and remember there aren't a lot of people who have the off-take revenue that can afford to buy compute at the scale right it wasn't the chinese open source companies that were buying you know spacex's excess compute or building the 10 gigawatt you know plant in in ohio that's open ai and anthropic so the vast majority of the off-take commitments are coming from anthropic open ai and nvidia right when you hear about the hyperscalers building all of this you know this compute out they're building it out to sell to the people that we uh you know that we just mentioned so david net net if he builds six gigawatts next year and by the way probably only elon um you know can actually stand up that much in that time frame like jensen said to me on the pod he's like nobody comes close microsoft doesn't come close you know google doesn't come close in terms of standing it up in that time frame um i think that he's going to have a challenge you know getting all of the componentry right i know he can stand it up but can he get the memory can he get the chips can he get the land powered shell all in time i think the off take is there right but to put it perspective this year anthropic and open ai combined their starting total compute was like five gigawatts so he's talking

SPEAKER_137: about incrementally adding more than they had as combined companies right that's not that much of an

SPEAKER_140: increase when anthropic is growing 10x year over year and open ai is maybe at what 4x or maybe higher now

SPEAKER_46: so the demand exists in the world the demand exists in the world today i think it will exist in the world for well you know the next 12 to 24 months but there is a wall of worry in the market the

SPEAKER_47: reason we saw the pullback in july is kimmy scared people into thinking oh my gosh they're going to undercut the frontier's revenues and if they undercut the frontier labs revenues who the hell is going to to pay for all this compute that's why you saw a 40 trade down in the core weaves of the world and you

SPEAKER_108: know the the all of the the semiconductor stocks and semiconductor related ai in some ways the fact

SPEAKER_66: that there's a discussion going on that this next 10 gigawatts is going to cost you know sax 500 billion dollars and you ask the question where does that come from a secondary offering does nvidia put it on their books do they create spvs off their books like some people are doing you know the fact that we're having this conversation everybody's aware of it the market has been educated on it means i think people will be able to change in real time if it doesn't come to pass or if it slows down which i

SPEAKER_53: suspect this cannot keep up at this pace you know more than another two years or so although as our good

SPEAKER_47: friend bill gurley likes to remind us he's like i can't believe that we're all just taking in stride this level of seller financing right he would call it circular revenues right but the market has gotten comfortable with this and remember like we saw in july if there is a scare about demand the whole sector trades down yeah everything will trade down you know together because that's just the leverage that you're pumping into the system you're effectively backstopping people's ability to build ahead of their revenue so it becomes much more violent if you ever see demand slippage um you know famous last words i don't see it today over the course the next 12 to 18 months um but you know you have these unknown unknown moments that certainly causes people to be fearful credit spreads are blowing you know have continued to to stay wide on these deals so there is fear in the market about them all right everybody

SPEAKER_66: the fifth annual if it's september you know it's time for the all-in summit the fifth annual is happening yes that's right uh david freeberg's been at work and we have an all-star all-star list of people

SPEAKER_36: joining us jensen wong founder and ceo of nvidia if you care about where ai is headed you won't want to miss this conversation the best the oracle satya nadella ceo of microsoft fan of the pod will be coming on for the second time jared isaacman from nasa the one the only brad gerstner and bill gurley bg2 coming back spacex is gwen shotwell my guy jake paul nick shirley a lot of incredible people

SPEAKER_03: coming martin shirelli maybe is even coming he's that's going to be fun go to theallinsummit.com to

SPEAKER_36: apply today allin.com or theallinsummit.com any of those will get you there and we're taking over universal studios again we'll have our own private playground dave friedberg great job on the summit

SPEAKER_35: casino night too i heard it's gonna be a big casino night biggest yet and the concert to be announced who will be performing at the concert but it is going to be incredible so i'll just say one of the things about the summit we've had people come to the summit from over 60 countries it's really incredible to meet all these people entrepreneurs investors people that are just really interested in the topics that we talk about we try and have the world's most important conversations but it's really this amazing community experience that's what brings folks back so we try and invest more and more every year in making it an amazing experience not just cool content on a stage

SPEAKER_148: which i think is what a lot of these other shows really deliver but it's like how do you actually come and have a have an experience for a couple days it's going to be awesome so it really is those three

SPEAKER_66: things that we focus on one you're going to learn something right you got these great people on stage you're going to learn something from them you're going to meet new people you're going to network

SPEAKER_53: and then you're going to have these great experiences it's the trifecta folks you're excited brad you excited to be back what what are the dates what are the dates again look at your

SPEAKER_47: calendar you're speaking september 13th through 15th in la this couldn't be better dates for the summit i mean we're going to be within 60 days of an election midterm election we're going to be within 30 days of an ipo you know potentially of anthrop i mean like it's going to be heated the sass

SPEAKER_66: apocalypse not the saxpocalypse this is the sasspocalypse is i guess winding its way out the indigestion might be clearing air table just got acquired for less than it raised it's a profitable sass company a great product 480 million dollars half a billion dollars in annual revenue growing 20 a year respectable if it was a public company with almost a billion dollars in cash has been sold it's been sold for 1.28 billion about 10 of its peak valuation which was 11.7 billion in 2021 now they did have a bunch of cash so if you include the cash position sale was 2.25 billion they were acquired by a firm called bending spoons this is an italian company milan based company they buy

SPEAKER_36: challenged but you know interesting businesses aol's legacy business evernote eventbrite vimeo

SPEAKER_53: meetup.com and they just went public last month shares that is uh bending spoons went public last month shares jumped 15 on the air table news sacks when we look at this this was a company that had

SPEAKER_36: done a lot of things right had a massive amount of cash in their war chest but rumors were maybe the founders were a little exhausted maybe some of the investors were exhausted who bought in at a high

SPEAKER_158: level what can we take away from this transaction in bending spoons are they the buyer of last resort

SPEAKER_58: now well i think they're creating a great business for themselves because i think this will end up being a fairly profitable acquisition for them let me just add a piece to this which is air table spun

David Sacks: out its ai agent business which is known as hyper agent into a separate independent company prior to this acquisition so i think what's going on here is that the founders and talent of the company they said look we don't want to have to make this legacy product work that's basically a private equity play

SPEAKER_60: i'll explain what that means in a second we want to focus on the new thing the ai company that's where the big value creation is going to be in the future or the potential for it so essentially the

David Sacks: talent is going to focus on the venture play and then they're selling the private equity play to bending spoons now why do i think this could be a good acquisition for bending spoons i think there was a really interesting data point that i saw in the commentary on this which is only 30 percent of air table sales team was making quota they had a 30 sales attainment number and that told me a lot about this business okay what it told me is and i'm reading between the lines here but this was a

SPEAKER_60: company that had a successful plg motion in other words organic growth product-led growth and they were growing about 20 percent a year but that was not good enough for its board you know these are investors some of whom invested at an 11 billion dollar peak valuation so they're looking for a venture type outcome so what happens the board pressures the founders to do something that frankly is unnatural for them which is they say look you should bolt on a traditional sales-led motion here to get the growth up faster does that work no they probably get a little bit of growth out of it but they only get 30 percent attainment so they've got hundreds and hundreds of sales reps here trying to push on a string and it's not making it grow faster so now what's the opportunity for the acquirer here bending spoons can go in here and do what elon did at twitter eliminate 85 90 of the cost structure don't do this sales lead motion just go back to your product lead growth roots you'll probably keep most of that 20 percent growth and it'll be a very profitable company you'll be able to 80 percent profitable probably right

SPEAKER_159: probably i mean 400 million to the bottom line pays for the acquisition in a couple years people are

SPEAKER_60: saying they're only going to generate 30 percent ebitda margin i think like you're saying it could be 80 90 percent i don't think you need to keep most of this business or most of the cost structure associated with this business um airtable is a company that has its fans um i think they will probably stick with it and you know you'll you'll be generating i don't know you could probably generate 300 million of ebitda a year or 400 million uh while growing you know 10 to 20 percent so

SPEAKER_66: that's the play for bending spoons but the venture investors here sacks they're happy to get their money back and move on to the next thing it's a bit of a push for them you know in terms of at the blackjack

SPEAKER_164: table rather than they've got to go 10x just to catch up and then they would have to go 10x again

SPEAKER_60: to make their lps happy it's not going to happen i think the question is if bending spoons can basically take this business that's not making money and probably generate 400 million a year of ebitda and pay for the acquisition in just three years amazing why isn't that something that the company could do on its own and i think that's the structural problem is i think it's very hard for both vcs who are on the board and the founders to shift into private equity mode why because they're gonna have to demolition what they've built right they've got all this loyalty to the team they don't want to think about how do i eliminate 80 90 of the cost structure it's just not what they do i mean what founders want to do and the outcome that the board members are going for is a venture backed outcome and i think they could have done this they could do what bending spoons does but they're not built for it they're not built for it and moreover the structure of the cap table is all wrong because they're sitting behind this giant liquidation preference all these investors have to get paid back who invested at this 11 billion dollar valuation and and you know all the way up the incentives are

SPEAKER_66: broken brad right and you you yourself at your firm altimeter you were pretty frisky in this period

SPEAKER_36: you made a lot of bets so i don't know if air table was one of them uh but you made some sas bets there some of them were at high valuations how are you looking back at that time period

SPEAKER_46: any lessons that you take going forward multiples of revenue can compress very quickly right it works great when the company's growing greater than 50 but remember it's just a heuristic it's just a very rough estimate used almost exclusively in silicon valley you know so people

SPEAKER_47: are saying oh my god this thing sold for two times revenue but when you actually look at it on a look through basis probably sold for maybe 30 times free cash flow i don't think it's easy to get it to 400 million in ebitda i think if it was the board would have done that i'm uh you know we're involved

SPEAKER_46: in some of these companies once they slow down the company morale goes to hell turnover among your customers uh you know begins to spike um it starts to feed on itself so it sucks to go to work every

SPEAKER_47: day what do you need to keep what do you need to be very tricky i don't know the core product and what's happening in terms of turnover in the core product david but my hunch is that the core product has started uh to really fizzle as the advances in the core product has slowed down you're seeing a bunch of churn out of it on the product side and now people are saying listen it's almost impossible for a software company today to keep any decent sales people to keep any different decent product

SPEAKER_46: development people because they all want to go work on ai agree but you don't need them for this

SPEAKER_60: product i mean the market the market's being efficient i mean look this is where i think bending spoons has an advantage that the company's board and founders wouldn't have which is they already have an infrastructure right they have a core team at bending spoons that's managing now i don't know dozens of these properties and so they can plug this in i think ai in a way makes their job easier because in the past the reason why of course you couldn't eliminate like all of the talent the infrastructure is because you needed the institutional memory you needed people who knew the code base now ai can learn the code base instantly that's an interesting insight and so yeah maintaining is easier with ai i think maintenance mode becomes way easier with ai because you don't need the historical knowledge anymore the ai can go in and sort of reconstitute that that historical

SPEAKER_53: knowledge let me get you in here freeberg uh if i may when we look at the lessons from peak zurp and sass and then we look at you know this moment in time this surging ai market any parallels that we

SPEAKER_66: might find here uh or lessons uh between the two between zurp and ai era the zurp sass era we had a lot of very high valuations a lot of enthusiasm a lot of suspending disbelief we're here in the ai era we just talked about you know the price of compute and all these companies being at 100x uh price

SPEAKER_00: sales ratio any parallels here or not it's a kind of a softball question for you no this is a very

SPEAKER_35: different paradigm uh the ai capex build out and model training which is where the predominance of the capital is flowing is not about some high multiple on revenue which is where capital was flowing into sass it's like oh you get a 20x multiple turn a dollar into 20 that's great let's do it all day long this is a very different structure and strategy and capital um allocation process so i don't think that i i would look at them as being linked it was a softball question to

David Sacks: be honest i was letting you hit it out of the park look i mean obviously sass companies were overvalued during the zurp era for two reasons one is that we had artificially low interest rates so we had a kind of a a speculative asset super bubble but the other is that people were treating these things like guaranteed annuities and actually growing annuities they'd look at it and see oh 120 net dollar retention so this thing will just grow 20 year over year forever as a base case right and they were then priced that way but what we've seen with ai is obviously there's disruption and you can't to brad said i'm sure they're seeing elevated churn right now and it's not an annuity things can change so

SPEAKER_60: obviously now these things are trading at a much greater discount all of that being said let me just

David Sacks: say i don't think you can extrapolate to the entire sass space based on this one company air table i think there's some things about air table that make it very different than i don't know let's say a sales

SPEAKER_60: force or a workday is you know air table was always a little bit of a quirky product i remember at the peak hype for this company people were saying like oh this is like a new excel or a new google sheets new microsoft office yeah yeah it was basically a spreadsheet for words that's how people were were viewing it is it's like this new kind of spreadsheet for for words as opposed to numbers and it never achieved that kind of promise it never achieved that kind of ubiquity people understand how to use spreadsheets everyone uses them air table never got to that point most people still don't know what air table is again it had its dedicated fans but it was a hard product to explain to people when do you use it it had a cult following but it never it never achieved that sort of level of acceptance it was never self-explanatory in terms of why you should use it what the use cases are they never were able to kind of get the market right because of that and to be honest if you look at

SPEAKER_66: claude co-work perplexity computer agents those things are now doing what air table did so it never

SPEAKER_60: carved out i think a niche where it was super clear when you were always supposed to use air table and and really it was part of this hodgepodge of this grab bag you should you could say of no code tools this is the category it was put in and no code has to be the most impacted the most disrupted area of sas right now because i mean what is claude code really good at i mean that's the ultimate it's no

SPEAKER_189: lovable claude code perplexity i mean the thing with all of these harnesses yeah the thing with air

SPEAKER_60: table or retool things like this is it's true you didn't need to be a coder to use them but you had to learn how to use air table you had to learn how to use retool all these it was kind of these you know alternative programming languages in a way and you just don't need to learn any of that anymore i mean you use claude and you just tell it what you want it to create and so you know if you do want to create some sort of new dashboard some sort of i don't know like a verbal spreadsheet or whatever you just tell claude what you want you don't have this learning curve look all of sas is being impacted right now but this has got to be the most impacted area so i don't know that you can totally extrapolate based on what's happening to air table i don't necessarily think that you want to replace

SPEAKER_191: your crm your erp your hr system with something that's been vibe coded you want the certainty

SPEAKER_66: you know for anything that involves compliance i got i gotta be honest my team sacks made i don't do you use like a portfolio uh off the shelf sas tool for managing crafts like um portfolios and

SPEAKER_196: everything well we vibe coded something actually so yeah we just did the same too so my team just

SPEAKER_66: built something that is so mind-blowing that to buy with off the shelf software would have been a quarter million dollars in software and like a million dollars in integration over two or three

SPEAKER_53: years and we built it in a month and and now we have complete insight into the whole portfolio the competitive set the founders everything going on keep in mind that one of the reasons why leopold got

SPEAKER_60: blown out okay i mean it is because he bet on the saspocalypse remember it wasn't just that he was super long these chip stocks that had a correction oh is that right he was sure he was short adobe and a whole bunch of other sas companies and those trades also moved the wrong way on him so again i just think that it's painting with too broad a brush to say that all of sas is going to get obliterated here yeah and there was a really good post about this let me just quote from this where they said nobody buys microsoft because microsoft writes the best code they buy microsoft because microsoft is the rail that everything else runs on active directory is where your employee identities live excel is where your board decks numbers come from teams is where the compliance recorded conversation happens azure holds a fed ramp high authorization and department of defense impact level 5 clearance which means a defense contractor cannot casually swap it out for something cheaper and so on down the line so there's a lot of really good compliance reasons why if you're a large enterprise you're not going to want to spend tens of millions of dollars ripping out something that costs you a million dollars a year it just that just doesn't make sense and i noticed that benioff just tweeted five minutes ago that 15 out of 15 cabinet agencies run on salesforce look the government is not going to rip and replace that over with something vibe coded

SPEAKER_128: so look not all sas is equal in this dimension i just want some uh figma i just think some of these

SPEAKER_53: sas companies with great founders who are in it for the long term and they have like passionate user bases i think they will make the jump to ai first products and i put figma in that bucket just to

SPEAKER_46: wrap this this section please igv is up 20 in the last six months it's up 20 in the last five years

SPEAKER_47: explain right please so the high growth software stock index right snowflakes uh 88 in the last six months that's it it's an igv is an etf of igv is an etf of of gross software companies right so to david's point there was a panic about software companies there was a big trade out you know honestly they they performed pretty well and and as he mentioned in the month of july they were up when a lot of the semiconductor ai stocks were down and some of these companies databricks snowflake clickhouse etc are doing extraordinarily well as i just mentioned snowflakes up 90 in the last six months which puts it in the same category as the semiconductor ai stocks so to david's point you can't throw them all in the same bucket but i do think that for these no code a lot of these application software companies they're realizing like that you know the game is up sell the company get what you can get you know importantly here in the air table story all the late stage investors right we passed on this in the last three funding rounds right which i think were at 2 billion 5 billion 11 billion but all those late stage investors which were the most venerable of growth firms they all got their money back and the early stage investors ended up making a lot so if this is a failure this

SPEAKER_208: is a pretty good failure for silicon this is one of the points that was made at that time which is hey

SPEAKER_66: this is a strong enough company and team and revenue base that if we just get our money back with the optionality hey maybe this would be a good investment you could say the same thing about

David Sacks: some ai bets well this is one of those cases where the liquidation preference actually mattered you know absolutely normally it doesn't matter but well i think they got straight money here i my

SPEAKER_66: understanding is this wasn't like they had like a seven percent you know interest rate or they didn't have like a participating preferred where you get two times your money back and then they do the trade

SPEAKER_137: does anybody know because i looked deeply into this i think that net of cash they may have come in a little bit less than the total cash raise but it seemed like everybody got made whole yeah but if

SPEAKER_66: they had the i guess sacks that we live through moments in time where companies had to guarantee a 1x right

David Sacks: you know 1x liquidation preference is standard it just means you get your money back before other people start to profit which is appropriate but also the interest rates were taken out right of these deals uh i think during the standard terms you know what's known as clean terms is just a simple 1x liquidation preference right the preferred just gets their money back before the common starts to participate in a successful sale of the company that just makes sense right yeah but participating preferred is the double dip right yeah and look we've never done that you know we believe in clean terms no one's trying to be punitive towards founders it's just it doesn't make sense for some people in the cap table to be making money while other people are losing money yeah it just doesn't make sense right that's just a transfer of value from some people in the cap table to other people in the cap table so the standard thing you do is you make sure that the investors get paid back

SPEAKER_66: and then everybody is participating in the upside okay fourth story here china is training on u.s data from u.s providers forbes published an investigation called these american startups are making china's ai smarter and i think this relates to a lot of your work in the early part of the administration sacks they claim u.s data labeling startups are selling valuable training data to chinese labs which in turn is helping them catch up with the u.s frontier ones two startups surge ai and mercore are both valued at over 20 billion dollars they sell training data sets to people like open ai anthropic federal agencies they all sell the same data sets to top chinese ai companies

SPEAKER_36: according to this report like tencent by tense alibaba moonshot etc top six ai labs in china according to this report uh are spending 500 million dollars a year buying what forbes calls secret sauce uh phd written content reinforcement learning knowledge pipelines uh all that kind of great stuff i have investments in a couple of these companies including micro one the founder of micro one didn't participate in selling to china he made that decision sex what do you think here about this new wrinkle in terms of really the secret sauce behind a lot of these models is the data we've run out of uh open data on the web obviously we talked last week about the books being uh you know having the spines taken off of them and scanned in i mean people are looking for data mercore micro one all these companies are providing it should they be providing the same data and selling it to chinese open source

SPEAKER_58: companies or not well look i think we got to decide what our objective is here are we trying to just get in like a full-blown economic war with china are we just trying to prevent all of our

David Sacks: companies from doing business over there if that's our objective then you can take that position historically the rules have been that you want to be careful about technology transfer of technology that has a dual use right that it has a military application my sense of data is that it's largely a commodity i mean data labeling certainly is if you basically tell them that they can't use data labeling i guarantee you there's no shortage of labor in china that they can use to do the data labeling in fact they probably are what i'm saying is there's a lot of ways to get this data so look if we basically ban these companies from selling to china we should expect reciprocal actions taken by china to ban companies over there selling to us maybe rare earths these two countries are not completely independent of each other by the way i want us to be as independent and sovereign as possible i don't want to have any dependencies

SPEAKER_60: but we still at this moment in time do have some dependencies so i think you have to ask the question is this data really proprietary does it have a dual use does it have a military application yeah i don't

SPEAKER_66: think it has military it's definitely not data labeling this is like hiring phds hiring super

SPEAKER_233: professionals to you know create unique data sets so it's science it's china can do that too and i

David Sacks: guarantee you they are i don't think this is going to give us a decisive advantage in the ai race it's going to annoy it's going to create annoyance it's going to create friction and how bad you want our relationship with them to be do you want to risk starting another trade war look i'm not against restrictions when i think they're going to pack a punch for example i'm really glad that the first trump administration limited the export of euv lithography machines to china you know that was all the way back i think in 2019 so that was a really important decision and so look i think targeted strategic controls make sense i would just make sure that this one actually meets that bar brad

SPEAKER_235: any thoughts here on this open source catch up the data being sold to china and our adversaries are

SPEAKER_66: you concerned about these open source models and then us providing data to them first you know i'm

SPEAKER_46: in absolute agreement with david that we want maximum competition at as we sit here today the us

SPEAKER_47: is winning we talked about it at the start our frontier labs are winning our open source is winning and we have fairly limited regulations right she's coming here in september in a bilateral meeting to meet with the president we're advancing relations on a variety of fronts so i think everything looks good and you want to continue down that path with that said i will tell you that this will irritate people in washington who feel that this along with distillation and other things um could be the export of chips all of which at a certain level makes sense cause people to wonder whether or not we're making it too easy on the chinese labs to catch up with american labs uh you know in the race to frontier intelligence so you know it's the type of story jason that i think will continue to muddy the waters that will continue uh to be monitored the reason i don't think it will cause us to change our stance with respect to china is because we're winning but if the president asks his advisors you know one of these days six months down the line are we winning against china and all of a sudden he gets a response no we're no longer winning they've caught up they passed us etc then these things will get

SPEAKER_46: a lot more scrutiny uh than they're getting today i think the only reason they pass muster today is

SPEAKER_240: because we're still leading the race i gotta say using kimmy and quen and you know glm 52 for the last 60 days my lord these things are good and i don't think it's very patriotic to be giving them an advantage i wouldn't do it i'm glad the company sorry what's the advantage what's the data set

SPEAKER_110: that you you're worried about that's so proprietary any of these data sets are um created by experts

SPEAKER_53: here in america who are given like the queries that have errors in them so when you give them you know a thumbs down to a query that's highly technical it could be code it could be biology and

SPEAKER_66: science these are you know phds going in there and putting in the latest and greatest content and then verifying it double verifying it and that's why we're getting better and better results out of the llms so essentially you're just helping them catch up and this could be a big advantage for america if we weren't sending it there i think a big reason these models are getting better is because

SPEAKER_58: data is being leaked to them but what makes you think that china can't do this they have tons of

SPEAKER_66: phds over there they would have to hire no no if they were to do it at this scale they would need to hire the best and brightest uh scientists and experts in the west so basically all the knowledge of the west is being um you know put into packages for our llms to get better they're sending those same packages and reselling them to chinese companies which means they catch up just as quick i think it's a big part of why they're catching up in line with distillation you know they're it's it's really

David Sacks: very similar process look if there's something truly proprietary here i don't want us to sell our secret sauce to china so you know i'd have to look into that and see like is there some real secret sauce here but this idea that it would seriously disadvantage china you know they're graduating more math and science graduates every year than the rest of the world combined i mean they don't have

SPEAKER_248: a shortage of smart people especially and we're graduating kicking them out of the country that's the other problem we got to get that fixed well it's like it's a lot of different issues here i

David Sacks: don't know i mean you want to conflate but i this idea that they can't yeah but the this idea that they can't recreate those data sets i mean look if there's something truly proprietary here if it has a dual use if it's military related but i don't know that that's what this is well they're all

SPEAKER_251: proprietary by design but i don't know about the dual use because i don't have the data sets here

SPEAKER_53: all right folks that's another amazing episode of your all in podcast thank you so much brad for joining us chamath good luck on your world tour hope you're enjoying a little rest and good luck um trying to buy a white turtleneck this season they're sold out everywhere so go to the all in dot com store all in dot com slash store we have 1 000 signature chamath autographed white sweaters coming you can sign up in advance for this all proceeds go to charity and by charity i mean

SPEAKER_253: chipots yacht fund all right we'll see you next week everybody bye bye