Speaker 1Hello, everyone. Welcome to another episode of The Circuit. I am Ben Beharin. Greetings, programs. I am Jay Goldberg. Well, we have a lot to dig into this week. Let's start with Micron, who did a somewhat of a surprise webinar or a webinar, I guess. There's a lot in here. I don't think we'll get to go to all of it. But for the first time in, I don't want to say ever, but at least a really long time, Micron was pretty forthcoming about their roadmap, making a couple of specific things, talking up what they're going to do in 6F squared, why they didn't really see market scale opportunity in 4F squared, which might have been a dig at the Chinese players, that they're skipping a node, which I thought was actually super interesting. And needs to be unpacked. But more importantly, just broader commentary on what they, I think, wanted to get across, which was technology leadership, which obviously has to translate into a couple of different things. Premium prices, to some degree, market share gains in areas that you care about with high bandwidth memory. There was a lot of narrative on high bandwidth memory. So I think, you know, there's a lot of people's concerns that HBM is not a good technology, you're not going to be around a long time, or be replaced by HBF or something like that. So I think they tried to quell some of that, those concerns. But broadly, you know, they positioned it as a technology webinar, which, again, I think is why they spent so much time talking about the nitty gritty of some of their solutions. But, you know, the whole tone was pretty bullish on memory, seemed to hint at, it's going to remain constrained, wafers will be constrained through the end of the decade. But despite all of that, the market is pooping this week. So is what it is. But I thought it was a good webinar, as a whole, from a technology standpoint, at least.
Speaker 2I think that's fair. I didn't sit through the whole thing, I must admit. But it was I need to go back and reread the slides, because I thought it was interesting data. Like, there's a lot of nitty gritty in there. I kept asking myself, like, deeper questions about memory, because when I was listening to it, I was listening to it on one screen, and on my other screen, I was looking at all the red on my stock chart pages, which was very distracting. It was hard to reconcile the two. Um, that's a common theme this week. But yeah, I thought it was I thought it was interesting. I your comment about four square being being a dig at the at the CXMT is interesting. I hadn't thought about that. But I think you're right.
Speaker 1Yeah, I mean, they were pretty, you know, again, this is Micron's point of view. Obviously, they they want this point of view to be true. But there was a lot of points that that Scott DeBoer made, who is their, their lead sort of technologist, I think he's CTO, actually. The, the point being that, you know, they've looked at it, he was like, Look, we've looked at this, we've been looking at it for years, we just don't think there's a viable, viable scaling path here. And and really, they tried to point this picture around, you know, they are going to go to vertical stacking of HBM. So VHBM, or others call it IHBM, you know, all of these things. But what I think they pointed out, and I just I think this is important to to kind of caveat with this whole thing is, you know, this is innovation in memory is not easy. Every node jump plus every in this case, 3d stacking right of of memory creates more thermal challenges. So like to do this, you like you just have, your engineers just need to go solve problems. It's very much like, you know, the days of Intel and node jumps went on where they're like, look, getting to the next nodes hard, we're struggling, we've got to redo our transistors, we got to figure out how to do x, y, and z. And these are just problems engineers need need to go solve around memory. And I think that's what I think that's why they did what they did is they wanted to say, like, we're, we're pushing a culture of innovation. And if we do these things, if we create these innovations, if we go solve these really hard problems, we think it's important that, you know, the market will pay for those things. Like, I think that was, they were trying to show like, doing these things doesn't mean this is commodity, I guess, to a degree, which was another sort of subtle tone there, you know, I checked, but but on that point, I think it's interesting, I hadn't heard memory companies basically kind of segment their roadmap to talking about memory, like AI class type of solutions. And I say that to say, you know, I get they want to make this point, they've got a whole product roadmap, there's product derivatives that are specifically designed, and being in an innovated for AI. And I think they think that will command some premium pricing, some ASP increase for the memory that is innovated for and thus designed for AI versus that that's not right, that's maybe just, you know, onboard pin compatible types of so that's, that's my read, I just think they put a lot of time into it. And I think that's why they're pushing, we have to innovate. These things are hard. We hope to capture value is the clean pill. Yeah, I guess I'm Yeah, I agree there.
Speaker 2That was the undertone. The implicit message in the whole thing is that this is not a commodity. Right, which we've talked about a lot before, how the extent to which memory is or is not a commodity. And I thought, you know, they made a good case. I don't know, I don't know that I entirely bought it. But I thought. But the other thing that I thought was interesting is, I was the first, a lot of their discussion was was very, very technical. And so I thought it was very important that they did sort of tie it to specific use cases. Because one of my fears with with companies in general is that they get very, very focused on, oh, look, here's the next technology. Yeah. Engineers love to solve new, new things. But customers don't always want that. Right. And I've worked with lots of companies over the years where they're like, the engineering organization runs the product roadmap, and you end up in very strange places. Nobody ever asked what this is good for. And I thought, you know, they, and I, Mike, Mike run isn't doing that. I'm saying they're, they're like, I don't, they obviously didn't name specific customers, but they were trying to tie it towards end markets, which gave me some confidence that people actually want this. I mean, I'm talking about this in the context, we've talked about a lot lately, which is all the pushback, the memory companies got hot chips. Right? Do do do the AI companies really want more innovation? Do they want new things? Or do they just want more of what the existing stuff? And hot chips is by no means a clear statement of what customers, these customers want. So I, it sounds to me like Mike run has thought through a lot of this. And has talked to customers at a higher level. I also think they are signaling to people who aren't AI customers, that there is, you know, that they're thinking about this, that they're, that Mike run is thinking about them. Right? Don't you worry, Apple consumer electronics people, we think about you too. We have stuff for you as well. Although that definitely was a lesser focus.
Speaker 1Yeah. Yeah, I think this just brings clarity to, you know, where they're putting, you know, what bets they're making. You know, you're right, right, it has to pay off. I think there's at least an argument to be made that if infrastructure providers, right, and lab companies still want innovation and logic, that you also still want innovation and memory, because these two things sort of go together. I think the labs hope, right, that, that, that compute moves in a direction. And when I say compute, that includes logic, memory, and networking, that it moves in a direction that they can do more with their models, build more capable models, and whatnot. And so I think there's a case to be made. But again, I think the point here is, they, they put a roadmap out. And I think they're just trying to say, we're confident in this, and we're, we're confident we'll capture value. And the market's just going to have to believe that customers will have to care. But that's their, that's their posture. And I thought it was interesting, because you just don't hear this kind of like forward roadmap from memory companies. For all the things we've talked about before, they don't want to tell each other what they're doing. And so it's like, well, they just took a pretty bold bet. And I think that's super interesting.
Speaker 2Yeah, I always think about, about signaling, like, when I hear the memory companies talk because they do signal a lot to each other not about product roadmaps but about capacity more but that's a very active function in in the memory complex it has been for years there's a there yeah is a a triopoly possibly a quadopoly but there's there's essentially been a triopoly for a long time and they absolutely absolutely use public occasions to signal to each other mostly along the lines of samsung please don't add more capacity but this this was different this is this is i'm talking about technology and i wonder if they you know i was thinking about that who are they trying to send messages to clearly cxmt but yeah yes i think this is much more i think this is much less of that going on i think they're signaling to i think they're really trying to reach customers
Speaker 1i think no i think they were too but i also think they again a hundred percent my interpretation i think they were also trying to make it clear the chinese either can't do these things or will struggle greatly to do these things like i think it was trying to be like we're on another level than they are and that's going to be true of samsung and sk also but i i think there was a little bit of that at least as a hope going on also yeah so that makes sense that
Speaker 2makes sense because you think about it last week we had cxmt basically just come out with a press release saying hey we have a new memory structure right and then here we have micron a week later saying oh you got a structure we have we have a really good memory structure and then here we have roadmap with lots of structures on it yeah and
Speaker 1lots of money behind it and all the tooling and whatnot and knows how to do it and all of those things so um anyway i i thought it was good i i like technology roadmap webinars i thought it was good i hope they do more um and i think there's more more coming on this front of of memory innovation uh all right let's uh let's talk about lamb in the context now of memory and as they are actually highly uh uh exposed to memory uh wafer equipment uh so lamb reported nobody liked it despite the fact that both their numbers it was a record quarter and i think we all agree that wfe is just up and to the right um but what what was your take on i know you listened to what was your take so they
Speaker 2reported an inline quarter so right on top of consensus and they guided right on top of consensus and uh good enough results but apparently in today's day day and era good enough is not good enough and so stock traded off pretty heavily um i i think a lot of the questions they got asked were you've you know they they said there were constraints so a lot of analysts asked if there weren't constraints what would your numbers have been that was there was a few of those people and uh they they did not answer that um which is which is smart they didn't answer that but i think i think what they're saying is that they were supply constrained didn't didn't say what exactly that involved but they were supply constrained but also i think there was a another layer of the customers can't take delivery because they don't have clean rooms yet yeah and so that was that was a cap on their sales but at the same time i think much more interesting than the results was a lot of the commentary that they were giving around the industry and around different different niches within wfe uh and so they they raised their their guidance or their market estimate for next year they think it's going to be wfe is going to be a 200 billion dollar market up from call it 150 ish this year yeah which is a good growth rate
Speaker 1for this industry and just to put that into context right earlier in the year right when i were talking about these things and it was like could it hit one 50 like that was like what we were talking about could it hit 160 like 200 wasn't even in our minds that's the possibility yeah yeah
Speaker 2and then you sort of look at look at a lot of the estimates for wfe and and like everybody's talking about big numbers for next year yeah and um that there's a lot of potential growth there if we can get through these supply constraints and we can actually get clean rooms built on time um but i i was i think i was much more interested in like you know lamb lamb is sort of seen as an etch and deposition company but that's like multiple tools within each of those categories and they have a whole bunch of new ones and sort of going through that and they talk about sizing some of those segments and that's one of the hard things about talking about semi-cap equipment is there just so many different tools all doing slightly different things that all sound very similar but they're similar but are radically different um and it was i thought it was helpful for them to give color on what all you know what is being driven by what like more this kind of memory drives this kind of product those
Speaker 1kinds of things yeah yeah and i feel so this wasn't a part of the mic on urban but i actually feel like this is going to become more of a narrative next year more clarity on memory types for workloads memory innovation for those workloads because i i think i guess what i'm saying is i don't think you know historically we had not had to richly segment memory the same way that you do other categories and i feel like you're gonna have to do this now more acronyms just what the world needs category creation baby this is how us analysts stay in stay in the biz um yeah anyway um yeah it was it was interesting stuff i agree with you i mean i think i paid more attention to like the numbers i think they i'm you didn't expect them to answer you know what would it be constrained it was just kind of the same answer that jensen gave when he asked the same question which is like well it just would have been higher okay like that's right you're but again you're
Speaker 2up no no they said it would have been
Speaker 1higher jensen would say oh it would have been higher if it's just the much um but yes constrained in material and clean room is uh is apt um okay meta also had earnings and i i'm super intrigued by meta for for a couple of things um you know obviously they announced uh prometheus this week um i actually got some time to talk to uh ian buck from nvidia on this and some of the meta folks you know what was interesting was i think what i hadn't i'm making a meta i'm i hate that such as i hate that their names are the same i'm gonna say i'm gonna make a meta point and i mean like a big picture point and it's like i'm going to make a big picture point about meta um i i hadn't realized how important owning your a gigantic bit of your own training infrastructure was until i talked to them um and then i think this point also then translates to serving said things but you know they talked to me and kind of went into great detail like with the dot the the blog was about why why you need such large training clusters of compute to develop competitive models and you know one of the things points that they made was and they have right researchers on the back of this plus you've got you know training that happens in real time um whether that's reinforced or post or whatnot um but it actually is the kind of thing that lets them make a model and then do variants of it distill it down and make multiple other models so if you think of models as products right name your name your model that's one product and then you want to have other ones that do certain things or that might cost less like you you actually have to keep doing that in your training cycle and so one of the points that they made was like having this you know at our disposal means not only that we can make these big models we can actually make many of them at around the same time and more frequently so essentially they can launch products products or models they can make more more products they can launch products or models they can make more more products they can make more more products they can make more more they have to do it on other people's infrastructure and sure they might have great deals with google or amazon or whatever but it's still they don't still own that infrastructure and so there's economics at play here for meta that i think are actually super interesting to have have a gigawatt class right type of infrastructure um that again spans many destinations so scale out right across the board they mentioned dollar suppliers from broadcom with jericho to arista and all the peoples that that they work with to do this um but that but i say all of that to say it's interesting to me from an economics standpoint that you can make products serve those products monetize those products right and of course that don't that really this is that kind of a pretty important asset to have in the long scheme of ai models it's interesting you mentioned that
Speaker 2because i actually had a long long conversation with someone from one of the hyper scalers last night about this topic and the economics of models, the economics of owning your own data centers and your own models. And his point was that Meta is, he said Meta was the largest data center, not, like basically he said they had more gigawatts than anybody else or, you know, almost as much.
Speaker 1For AI. For AI. Yeah, because I don't think it's a true total, but for AI, I can see that.
Speaker 2But, which I thought was, I mean, because, you know, Meta is not AWS operating compute for thousands of other people. Right. Just do it for themselves. But they're still, you know, the largest, one of the largest overall data center players out there and largest or very close to largest, depending on how you want to measure it. Very large GPU AI capacity. I mean, let's not forget, like OCP, we were talking about OCP last week and what an important show it is, Meta founded OCP, right? They were the, you know. Yeah. They were the big driver behind it. So they've been doing, they have deep, longstanding expertise in this stuff. And if you compare them to, say, Amazon, who doesn't have their own models, and what does that mean long term? For the economics, you're always, you know, is Amazon always going to be dependent on other people's models? And what are the economics of that look like? It's, right. And then you sort of take that a step further and sift through, you know, sift through what that means for the chip vendors and how that, you know, there's a lot of value being moved around, I guess is what I'm coming to. There's a lot of value being moved around here. And I think it's not entirely clear where that value ends up, but owning your own data centers. Data centers is an important thing, as is owning your own models. And I like the way you think. But I don't think of models exactly as products, but certainly having your own model and then being able to tailor that to your different use cases. So you have a, you know, you have your big training runs, and then you have a model that serves up Muse, and you have another model that's distilled and honed for ad serving. Yeah. That's super powerful. And I, you know, I think, because there's a lot of debate now about open weight models, I don't really need to have my own model. I'll just wait for the Frontier Labs to do something, and then someone in China will come up with an open weight model that I can use that's almost as good as that. And I think, you know, there's costs to that, right? Every time you distill something, it becomes a little less good, a little less efficient. And so if you're waiting for someone else's to distill a model from the Frontier Labs, and then you distill it yourself and fine-tune it yourself, I wonder if you start to lose some of the quality. And then what I'm really getting at is the economics of open weight are not quite as compelling as you'd think. And there's still, right, there's lots of cases, I think, where you run through the math on running an open weight model versus, instead of having your own model, you use Anthropic API or whatever. Yeah. It is. You'd think the open weight would be more efficient, cheaper, but it may not always be that case. Right.
Speaker 1No, I agree. But I think, you know, I think what I walked away with is exactly, you know, sort of this viewpoint where meta is more vertical than I guess I gave them credit for before. Like, I think I would have said Google is, you know, the one trying to do a Frontier model and is vertical. I think you put meta cleanly in that now. So, you know, I don't think that's the right way to go about it. So, again, I get that they are largely using this for themselves. So, it's a little bit of a different comp, but at the same time, we do, again, you talk to enterprises, we just fielded a big CIO, CTO and CSO survey. And, you know, they're weary about Chinese open source models. Like, they want to use open models. They want to be able to route to model that's more affordable economically than the Frontier. So, even though they might control those or someone else might distill them, I think they're going to want to use a U.S. companies based open models. And that could be Google. That's basically going to be Google, maybe Nemotron from Nvidia or meta. Those are your three best options at this point. But where I'm going is having that class of infrastructure. And I think this is what meta was trying to do, why they wanted, why they were willing to talk to me. And the point of Prometheus is having that class of infrastructure lets them pace the Frontier or perhaps lead the Frontier as well. Even if that's for internal things competitively and/or doing things with an open weight model that's Frontier class for people, companies, whoever.
Speaker 2Yeah, I think this is another example of how quickly things move. And how you have to be wary of accepting any long-term predictions about somebody's model being the best or somebody's model being the worst. Because not so long ago, people were saying, "Oh, meta's all screwed up." Because they absolutely had very serious internal problems around their AI or it was very confused for a long time. And so people kind of wrote them off and now here they are with clearly a Frontier class model or close enough Frontier class in the ballpark and I think Google isn't kind of. It's funny to me how quickly it rotates. Every three months, somebody is a leader and somebody else is in the doghouse and no, they're all competing very heavily. They're all going to be coming out with models on a slightly different timeframe. And so just because someone is the leader today doesn't mean that. The last leader is finished. They're just working on the next version and they'll catch up. Which does though open the question to what are Microsoft and Amazon going to do? Because they have been very quiet on the model front.
Speaker 1I mean, I don't. What can they do? Yeah, I don't know. I just don't think this is something they're going to do, right? But again, just tying this back down. I think it's interesting. You kind of heard some of this from OpenAI too around their newest models being kind of Blackwell-trained. Meta sort of made the same point, right? We've got leading class infrastructure, which is what's letting us do this with models, which again, I think they. Because it'll allow them to do this more quickly, keep up with the Frontier more quickly, if not perhaps surpass the Frontier. I'm not going to lose that out. Yeah. It raises an interesting question about Google's infrastructure. And I think what Google has made is good, but why did it take so long? If TPUs. You have a ton of scale and TPUs are great. It took a really long time for them to get to Argonne. And I think I'm saying all of this to say, I think that infrastructure. Per Meta's point, actually does play a critical role in how fast the Frontier can go. Now, I get we were talking about pacing and concerns and all these things. Fine. But that infrastructure is directly relative to how quickly you can make new, more capable models and variants of those models with different economics and capabilities. And so again, I just say all that to bring it back to the importance of the right infrastructure to do this, to have competitive advantage. Yeah. For your models. I agree with all of
Speaker 2that, except for the part about Google. I think they've been there all along. I don't think they're that far behind. I think Google is a little bit different because they have TPU and TPUs are much more efficient for the things Google needs it to do. And so their power needs have not been. Maybe with GCP, but really for most of their workloads for TPUs, it's much more efficient. And so they were never as far behind as say Amazon or Microsoft was, or Amazon is. And so they haven't been as vocal, but they're absolutely, I think they've been spending pretty heavily. And I mean, they just did that big equity offering a few months ago to keep it going. But I think your point is right. So owning your own infrastructure and having your own models matters tremendously.
Speaker 1So here's the other one then, where rubber meets the road. I tried to do some math on A, how many gigawatts of compute just agents, individual personal agents will add to our gigawatt demands. Because this is not. running on existing existing compute demand it's right they talked about right muse is basically everybody's getting their own vm you're essentially getting a core or a core or two or whatever right that translates to so that's additional compute demand to just run reasoning models executing models etc um people have sort of brought this between you know anywhere a number between uh tied tied to users like for every hundred million it could be you know somewhere between three and five gigawatts if you just kind of just run the math on right the basics here if and i did this so not including the entire internet let's just say that half the internet two and a half billion people use personal agents just that alone would demand another 35 gigawatts of compute a year just to run the agents not not to execute the agents not to handle those models just to run those agents now i say that to also say there's an economic cost to doing this if you are open ai or anthropic or whoever and you're having to run agents on uh at market token rates it could be quite expensive one person's personal agent could be anywhere from 50 to 100 a year just just to execute that right so you've got to monetize that um here here though meta i think is actually in a really interesting position that they can keep those costs down still expensive right to serve those agents per one person that increases your you have to arpu that right in some degree but i think they that owning that infrastructure means they can keep those costs a little lower perhaps than a competitor who doesn't own that infrastructure with this kind of individual personal agent cost to serve is what i'm getting at yeah i i see that
Speaker 2i think that is interesting a lot of agents there are going to be a lot of agents out there i actually i think one of the things that really stood out for me was they were talking about how much it costs to run agents because we're talking about muse here really for meta yeah and i i think he said it explicitly is they're never going to charge for muse right and right and that seems confusing right because you you just outlined how much it costs to run muse and they're saying they're not going to charge for it which means they're not dumb so they have some other way to monetize that and i think that's i think that's important because because one i think meta is very very good at monetizing engagement and muse is just one more way to engage people yeah whether it's instagram or whatsapp or right or muse right you're you're going to spend more time on meta properties and they'll find a way to make money off of you they'll arpu you i like that as a verb they'll arpu you uh and i think that's important because i think there are lots of other companies out there like open ai and that need to still need to figure out that that piece of it agree um beyond subscriptions agree and and meta is a is a really good example of like hey yeah there are other ways to do this
Speaker 1yeah yeah i mean google's gonna have to do this too right i i think i think it's a fair assumption i i'm not gonna make a timeline on when this happens but i think it's a fair assumption that every person in both a consumer personal context and then probably a secondary work context is going to have an agent that they're going to use and it's going to go do things for you um i believe we'll get there and that's again that's going to have a cost to serve that's different than token cost to serve to go and execute for you and it's going to draw a different set of power in fact these are also very highly cpu dependent workloads um so that alone like just shows you both the gigawatt of compute and the demand we need for more cpus to go and do to to run personal agents um but that my point yeah there's a cost to that and economics play that factor and you recovering that particularly at a consumer level and i think we would all probably assume meta wants to take some skin off transactions to a degree which would make sense so you do need to be transacting on their platform or with with muse but things like that i think become where they can yeah are are per you on top of their cost to serve agents um makes sense yeah um okay let's uh let's talk supply chain um in a couple different ways i want to talk about supply chain and then i want to talk about some other little bit of news that happened today and then i think we should end on cyber security since that's again a hot topic even though i and you have been talking about it for some time people are finally waking up to the reality i tried to outline in june um so all right let's talk nvidia nvidia is master of the supply chain um using balance sheet to buy up all the goods again straight out apple's playbook in the mobile era buy all the things so nobody else can or they have to pay really high prices for them uh crowd out your competitors with your uh with your supply chain mastery um and so that's happening again right yeah so this this week
Speaker 2is gtc berlin and nvidia had a whole bunch of announcements as they are want to do all kinds of different partners doing different things with ai but deep in there also was they have gone out and bought uh substrates from a couple companies i'm blanking on which ones right they've they've been they've made commitments to substrate companies before this is another set of them and it's big numbers it's you know billion billion dollar or i guess it's not that big a number for nvidia it's billion here a billion there it's tiny tiny little things um but you know they have gone through and made purchase commitments through every part of the supply chain stack that they can touch anybody who has capacity they're willing to allocate to them and they're willing to allocate to them and they're willing to allocate to them for sale to nvidia has has gotten it right lasers substrates packaging capacity foundry i imagine they've done all kinds of interesting things on test as well you just go down the list of where nvidia is they are aggressively deploying their cash flow to lock everything down all the things that might be in short supply and i don't see how that's not a problem for their competition next year because other than broadcom i don't know who has the who has the the balance sheet to stand up against that i mean that's i think it's going to be a real issue oh and memory and of course memory right it's going to be very very tricky for anyone to get any of those things next year um just because it's tight and then nvidia is locked down anything that's locked down a ball
Speaker 1so again i think it's going to be i think obviously suppliers don't want to want to get in a position where their customer concentration is one but but again like you saw this in the apple era with suppliers where they were the vast majority of someone's supplier because they essentially guaranteed your scale like you could just print that money with them it was a variable for other players they didn't always know so they were happy to supply it to them and they were happy to sell it to them and they were happy to sell it to apple even though it was very hard and they didn't get you know the numbers that they might from others because apple negotiates supply chain hard but i assume that nvidia is doing the same thing but they're using this right this really again this really does come down to who can manage this supply chain a very complex supply chain to go and build complex systems across the board and nvidia is doing this you know again as well as anybody right maybe second only to broadcom who who wants to also enable a whole set of customers um but you got to get all the things right memory and baseboards and all of the the supply componentry around that analog whatnot and uh they have the balance sheet to do it right it's just another way they're using their balance sheet for competitive advantage is uh is soaking up the supply chain you know i
Speaker 2we're not going to be at the supply chain constraint until we're running out of msg that's my take on this everything is so tight right now uh it's just it's going to be it's going to be a challenge next year i actually wonder if we're at the point now where it starts to become a real headwind for companies like we haven't seen anybody miss well i guess we just saw lamb miss we're not missed but we saw lamb have problems with their results but i think i think we're going to see more of that next year as companies just like hey we're leaving demand on the table we couldn't satisfy all our customers because we just couldn't get enough you know pcb boards like pcb boards are short like what what what timeline are we on there's just not enough pcb boards out there it's a it's a it's a it's a weird time it's a good time if you make any of
Speaker 1those things yep yep um okay so i do want to talk about i don't know if we've talked about this but i do want to talk about the news ish that some of the bear bears propped up about i think it was a ft article or information that somebody talked to amazon and they have gpus sitting in warehouses and this was made to be like a big oh my god nvidia's channel stuffing and that's what's making this whole thing a whole problem um so i think it's important to talk about this in a couple contexts uh because i checked with some of my friendlies who build data centers for said people and uh and essentially the term they use is like this is entirely common in the supply chain it's called staged integration you buy you get the things you need across the board and then you have to phase when that gets built out because data centers you just can't build to demand like you can't you can't plan and say hey this is my timeline and so unlike iphones which try to build supply to demand in real time do real-time demand you just can't do that with data centers and their point was these things never sit idle for more than six months like two quarters is the max then they go and get installed as a part of the the integration site um but a lot of stuff sits there right their substations sit there waiting to be installed they've got a whole slew of equipment it's either in close proximity or it's on campus and then uh gets involved in it in its staged integration and so i i get that there's concern right about that but it's not the kind of thing like these things don't sit idle for very long like no nobody who does this right their businesses depend on has has given me any of that indication um and it's just the complexity of that supply chain from you got to build this thing then you got to install everything then you got to get it all plugged in and you have to have everything already ordered right to do that and that's just how this works and there's just there's really not any other way around it because you have to order these things in it well in advance so that you can then install them when it's ready to be installed and there's just timeline discrepancies in construction think of it like right you're waiting on wood you're waiting on cabinets you're waiting on whatever like the more you have ready to go the better your timeline is and this is just how you build things and that now componentry or compute supply chain comes along with that so i think that's that's point one the other is if i'm a data center provider and i need to buy gpus um i'm certainly not going to be like oh man like i need an extra six months can you like hold my order or whatever for an extra six months like well then why not just give that to a competitor who could install right now right and so you have to secure that capacity so that it doesn't go to somebody else when you need it so it can get installed when your build starts to happen right and so this is just this is just how these things happen like the the comments i heard you know around this point in concern was more like oh well they shouldn't have ordered it it's like well that's stupid like that's not how construction works like that's when you're building something you order what you need and it has to get installed in the timeline some reasonable timeline it doesn't have anything to do with there's no demand is my point that was they're trying to be like oh there's no demand it's like again it's not a demand issue it's a timeline of construction and that's just the reality of building things so
Speaker 2so all right so i i agree there's no demand but i think there is something else at play here um because i actually think the i think it was the information reported this and they i think they were reporting on comments that andy jassy himself made that led to this and i think the the point that he was trying to make was they don't have enough electricity sure right it wasn't a question of demand they don't have enough electricity and that is leading them having to stockpile stage gpus right um so it's not a problem of demand i don't you know uh it's not a problem demand but it's it is it is not a it's it is a problem um and i think this is what i was saying before a minute ago about what's what we're in store for next year i think we're going to see a lot more of this which is just things things in the supply chain are going to trip people up and it's going to be somewhat seems somewhat random it'll be gas turbines for someone it'll be some kind of weird regulatory thing at another place it'll be like a shortage of electricians in some area right there'll be lots of little things like that percolating out there and i think it's going to be something that we're going to see a lot more and i think it's going to be something like that percolating out there and there is a risk that that leads to a significant delay sure right if if a big enough site faces some kind of problem um it will it will ripple through the rest of the supply chain yeah and if it's just a few months you're right it won't matter like oh we can't get the interconnect because there's a seasonal migration of whatever bird across where we have to lay the power cables for three months right i i that probably doesn't matter but if it's something more significant say if the the shortage is around financing i you know i i think that'll be that will cause people to get a little more concerned um so i it's something i'm i'm watching for pretty carefully and i don't think it's yeah right i was just saying this a minute ago it's like amazon amazon doesn't have people inside amazon are complaining they can't get enough compute for their own projects um and so it's not a question of demand um but it supply chain is is is snarled up and it's going to get more snarled up and i think that yeah you know i don't think we know how how the industry or the markets will react to that yet
Speaker 1yeah yeah i mean i i don't think they'd react favorably even though you could argue that again it has nothing to do with demand but i i think my point of this is my and having conversations with my friendlies like you get an appreciation of just in general how unpredictable your timelines are for construction like it's never the best case scenario like it's never like i've hit my timelines it's like ah i'm i get hit somewhere so i gotta i gotta balance that and you gotta manage that
Speaker 2accordingly yeah yeah i i think we like it's a little bit different though because you know we're dealing with the world's biggest builders right and i you know i know people who who are on the neocloud side and like they have project plans from the builders months in advance of the first shovel coming on site right and it's a detailed timeline of what every how everything stage when it's going to happen yeah right it's it's not like you're you're you're you're like you said your kitchen getting remodeled and your contractor flakes out and just doesn't show up for a week because he's right you know just doing something else like this is this is really this is very professional very very efficient organizations at work here and and certainly they've all become very very good at this the issue is more around random unpredictable things which is to your point um that are just beyond anybody's control so the timelines i think are very very clear but there are still quite a number of x factors somewhere along the supply chain right that are going to disrupt us
Speaker 1right and i think my point is is like if you're those people if you're one of these data center builders or whatever and again you ha you have a timeline it's again it's not going to be perfect but it's at least for what you hear like now it's unlikely to be like a year again maybe something comes up right but but to a degree like i have not heard anybody be like yeah man we're going to be set back 12 to 18 months um like again if you're the vendor do you do you not order something or do you order something because you know you need it you order to what you need and sure you have to wait to install it or whatnot but you're not going to not order it like you don't want to lose that allocation from to a competitor right
Speaker 2yeah i i i think that's the way it is certainly the way it was last year and probably right now i i don't know that we'll be there in a year right i just i i think there's there's a there is there's a lot of things going on in the market right and there's a lot of things going on in the market right and there's there's a there is there's there's a there is there's there's a there is a risk that like things aren't like certain things will be things aren't like certain things will be things aren't like certain things will be sold out but other things might not be sold out but other things might not be sold out but other things might not be and so and so and so i i think there is a risk that i i think there is a risk that i i think there is a risk that we do see we do see we do see a one you know i like i've said this a one you know i like i've said this a one you know i like i've said this before there's no such thing as a one before there's no such thing as a one before there's no such thing as a one quarter problem and so a data center quarter problem and so a data center quarter problem and so a data center comes along and says hey we're pushing comes along and says hey we're pushing comes along and says hey we're pushing out our stuff by a quarter out our stuff by a quarter out our stuff by a quarter then it compounds yeah then you know some then it compounds yeah then you know some then it compounds yeah then you know some then the odm has to say oh it's you know then the odm has to say oh it's you know then the odm has to say oh it's you know it compounds and the odm is pushing it compounds and the odm is pushing it compounds and the odm is pushing things out and then they're pushing things out and then they're pushing things out and then they're pushing things out to their suppliers things out to their suppliers things out to their suppliers like i could i could see it rippling like i could i could see it rippling like i could i could see it rippling through and through and through and i think if this had happened if there's i think if this had happened if there's i think if this had happened if there's this kind of delay had happened six this kind of delay had happened six this kind of delay had happened six months ago no one would care the street months ago no one would care the street months ago no one would care the street would look through it would look through it would look through it i just don't know where people's heads i just don't know where people's heads i just don't know where people's heads will be in a year right right will be in a year right right will be in a year right right um and so you know um and so you know um and so you know it sounds it sounds crazy now but i it sounds it sounds crazy now but i it sounds it sounds crazy now but i think there's a real risk that think there's a real risk that think there's a real risk that some company some large ship company some company some large ship company some company some large ship company random one pick a random one i'm not random one pick a random one i'm not random one pick a random one i'm not thinking of anybody in particular thinking of anybody in particular thinking of anybody in particular someone like says oh someone like says oh someone like says oh we were going to supply this data we were going to supply this data we were going to supply this data center and they're delayed center and they're delayed center and they're delayed and so we're going to miss our quarter
Speaker 1and so we're going to miss our quarter and so we're going to miss our quarter yeah i think it's fair right i think and yeah i think it's fair right i think and yeah i think it's fair right i think and again it comes down to is there another again it comes down to is there another again it comes down to is there another waiting customer or not right and then waiting customer or not right and then waiting customer or not right and then said person was host because it was said person was host because it was said person was host because it was interesting um the uh the point was made around memory similarly that the by gavin uh baker on i forget which podcast he was on where he was basically like if if you the customer know that memory is constrained right your supply chain and why would you because i think the contest of the question was like well people don't have to abide by their ltas and i was like well why would you when you have again the the three main players that you need and memory's constrained why would you not honor your ltas when then that would just piss them off and they go well i'm gonna give it to your competitor so it's like you got another customer just waiting there you know that's how high demand is and so if you back out right or don't want to pay i'll give it somebody else and it's not a problem i thought
Speaker 2it was interesting point this is my point i want to end this video and i'll see you in the next one bye on a happy note so i'm gonna i'm gonna let that go absolutely you're right
Speaker 1okay all right lastly let's just talk about security uh freak people freaking out for for good reason like it's it's interesting because one like crowd strike and then some others were like hey we think people are feeling out what they can break into like right now we don't we don't know where it's coming from but there's some definite like phishing people are trying to log in it's coming at scale um banks were sort of like you know like you know like you know like you know like you know like we're sort of saying same thing like we got people trying to log in we got we don't know what's happening in our systems um this you said you didn't want to add negative like this is actually one of my bigger concerns that like something really bad happens in security and that slows the spend or deployment of ai pretty broadly because as we know agents are running around ungoverned i have data around this that will show um you got to haul these things in it is absolutely a security risk and people i think are now just realizing the degree that this is a security risk and either i mean i was talking to once here on cto and they were like we're about to have a blank check for agentic security like we're gonna we have to solve this it's it's top priority number one everybody's gonna start spending insane amounts of money to figure out how to secure this but but these little things that keep coming out show the magnitude of this problem like let's start spending a lot of money on this problem let's solve this sooner than later but because this could be really really bad but you're starting to see hints of how bad this could be we're all doomed run i mean i do need a vacation jay so like the fundamental collapse of the infrastructure so that i could just kind of hang out eat some food be on my farm and not be insane with work you know it would be i guess welcome
Speaker 2so yeah i'm i'm with you on this one like i i think like i don't want to dismiss it clearly ai is immensely capable of enabling bad people to do bad things and i think it is very likely that we see even more significant uh attacks right there was this thing last week with with somebody figured out how to turn off all the refrigerators at a supermarket chain in france like all of them and so all the meat spoiled in france right and so i think it's very likely that we see even more significant attacks right there was this thing last week with with somebody figured out how to turn off all the right that's like that's kind of that we're going to see more of that and it's going to be worse stuff but i also don't think it is this unmanageable infinite problem it reminds me a lot of like what was it like 20 years ago when the internet finally got really robust and we started seeing open source security tools that people then reverse engineered and weaponized yep and we we saw a lot of a lot of cyber attacks back then um and there was this whole concept of of script kitties do you know this right there were just like there are a lot of open source security tools and malware tools that got released at one point and it just allowed any teenager any bored teenager with an internet connection to do all kinds of malicious attacks um on like you know their school website to change their grades that kind of stuff or you know the defense department and i i think we're we're seeing that repeat itself now because the class of tools have gotten infinitely more capable um and there's a lot of scope for doing creative things in a bad way yeah but i also think like one i i i think like you said everyone's very alert to this and people are being proactive and giving security real budgets for the first time right the knock on the knock on corporate security is that like it's everyone talks about it but they never funded enough that that is probably changed radically this this week and and then on top of it i think it really shows that like this this is why having frontier models is going to remain important right after coding cyber security is going to be i think the number one ai use case because if if all the all the script kitties and uh global mafias have access to n class a hundred frontier models somebody has to come up with the n plus one class yeah and um yeah it's look it's i i have to believe that or i have to like move to the woods and build a faraday cage around my around my house and yes
Speaker 1just farm my own things but
Speaker 2what's interesting is
Speaker 1like you know nsa goes something like hey you might if you're running on php like you might want to you know fix this and you're going to have to do it again and again and again and again and again and again and again and again and again and again and again and again and again and again and and then like oh you know don't worry about it what's what runs on php only your electrical grid and water systems and a whole slew of things like uh but but but i do want to say like you're exactly right because i have for years had conversations with those in it around this and they're always like yeah security is the top spend like that's all right so how much did you spend on security this year that's about the same the difference is none of i don't think they ever really like they didn't they kind of had to worry about it but they didn't really have to worry about it they weren't hacked they weren't breached and i don't think they also knew how bad it was and this is what everybody we talked to has like walked away with with this mythos moment which is that they used it to test vulnerabilities and basically we're like this is really bad like yes we have insane vulnerability and so now they know this they have to go figure out and spend to patch it and solve it and that's why i think this spend is a different cycle like you now know how bad it is and that anybody like you said with a model from your model can come and attack you and exploit your vulnerabilities so security spend is going to be significant to say the least yep yep yeah all right well let's end on a i'm terrified but in a good way in fact i had i was giving i was just giving this talk yesterday to a big uh venture capital group on the state of ai and i kind of like lent landed this point that i said you know it's interesting that ai is both simultaneously one of the most if not the most transformational technology we've ever seen and one of the most dangerous at the same time and so there you go move to the woods and build bunkers everybody we're just kidding all right thanks for listening uh we will talk to you next time as next week is an insane earnings week for hyperscalers so that will be amazing and uh and we'll talk about it so
Speaker 2we'll talk to you then thank you for listening everybody tell your friends your neighbors your agents click like subscribe thank you
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