SPEAKER_00 0:00

And the reason for raising capex has always just been we need more compute, we need more flops, we need more intelligence. This quarter there was something different, which was. Hello everyone, and welcome to another semi-doped podcast. I'm Austin Lines with Chipstrat, and with me is Vic Shaker from Vic's Newsletter. Hey Vic, man, a lot has changed since the last time we recorded podcasts. What's up with you?

SPEAKER_01 0:28

Yeah, a lot has changed. So after 15 years of working in the semiconductor industry across like small, medium, and large companies, I finally decided to hang up that corporate hat and do the Substack, this podcast full time and see where it takes us, you know, in the podcast front. And I hope the Substack continues to grow too because it is so much fun that I figured, like, okay, let's give this a shot because I learned so much from like writing and you know reading about so many different things. And uh corporate roles tend to be a little bit more like hyper-focused, and I've spent 15 years doing kind of the same thing. So I was like, okay, instead of trying to try to change roles everywhere, I've kind of managed to carve out this role for myself. So I'm like, okay, I said let's try it for a while. What's the worst that can happen? Let's try it.

SPEAKER_00 1:25

Awesome. I love it. Yeah, so uh okay, so you'll have more time, presumably, for writing, podcasting, researching. Like, what are you most excited about?

SPEAKER_01 1:34

Yeah, I'm just gonna do the same thing. Like, I'm not trying to uh add too many things because I think we already added one other thing to the semi-doped umbrella, which we haven't really spoken about, which is semi-doped also has a substack presence now, and it is a free for all subscription. It does not have paywalls. And what uh Austin and I do here is uh just we just give our daily takes. So this is like a once-daily newsletter uh that's short to read, like within three to five minutes, just with some key highlights of what's happening in the day, because we monitor this stuff so much every day now that we figured, okay, like there's so much that goes like unmentioned, because we can't write everything in the newsletter and we can't talk about everything on a limited time podcast, but not everything requires a full deep dive Substack or a full hour podcast. But if we try to stick it in a podcast, it gets fragmented. So the best place for this kind of information, but that's also very relevant because the the reason you sign up for the semi-doped Substack is that you know you'll get you'll get one email a day. You open it up, you know, while you just have your coffee, you just like glance through it. Anything that piques your interest, you just read that section or or not, you know, you you'll get another email the next day. And it's an easy read. It's unlike our deep dives on Substack, which is highly researched and thought through and all that. These are just like quick hits. So that is that is the second project that's common to us, apart from the Substack.

SPEAKER_00 3:12

Yes, yes, yeah. I'm excited about it. I'm I'm looking forward to it. It's been fun this week. Um, you know, I think for listeners, definitely go sign up. It's just basically like uh Vic and I having a quick water cooler conversation and that you're part of, you know, hey, here's this news from yesterday. Vic will give a take, I'll give a quick take, move on to the next thing. I think it'll be fun, informative, and you'll just be more intelligent about semiconductors and AI for reading it.

SPEAKER_01 3:38

Yeah, just semidoped.com should get you there. Or you can just search for it on Substack, semidoped. You'll see the same logo of this sub uh this podcast, and you'll find it there. And the last thing that is like forming still in my life is the fact that now I am available to do consulting, and my newsletter itself actually runs under the umbrella of semi-exponent, which I came up as a name to say, like, this is the most exponential technology I like you know that ever existed. So I was like, okay, semi-exponent is a nice, it's like, you know, what is the exponent? You know, the exponent is zero, means it's a flat line, but it's never zero. So anything above zero is like an exponent. So I'm like, okay, that's a nice name. So the consulting arm is going to be under semi-exponent. So now I'm just starting to find you know clients who want to work with me on various different aspects of semiconductors, have chats, pick my brain on various aspects of what I write and talk about. We'll see how that goes. It should be fun. I like talking to people anyway.

SPEAKER_00 4:44

Yeah, yeah, nice, nice. So you'll be researching, writing, talking, and consulting. That that does sound like plenty.

SPEAKER_01 4:52

Yeah, that's enough. Right. That's why. That's why I'm not doing anything to the Substack. Things will continue as it is. And uh I hope there'll be more research involved because I have more time to think through carefully a lot more stuff. Yeah, totally. I've always tried to maintain a high, high level of you know quality on the Substack. So hopefully, if I've been doing my job well enough, you won't notice any changes.

SPEAKER_00 5:15

There you go. There you go. Love it. All right, let's get into it. So this past week, you were on vacation. There was earnings week, they didn't wait for you. Um and but I stayed on top of it, and I know you you've caught up a lot on it. Um, so of course, listeners, I know you know all about this. Microsoft, Google, Meta, Amazon, Samsung, Sandus, Seagate, Western Digital, Quamcom, Cadence, NXP, even Rivian, which I love to follow, even though they're kind of downstream as like a semiconductor consumer. Um, all those companies reported. Impossible to listen to all of it. Um, but we are gonna cover it. And I thought the angle that we could take is actually starting with memory and storage companies. And here's why. You know, as everyone's been tracking, the big four hyperscalers have now committed to nearly 700 billion of 2026 CapEx, which is up from roughly 500 billion just in 2025. So they they every quarter, the story is always like, hey, did they keep CapEx or did they raise it even more? And the reason for raising CapEx has always just been we need more compute, we need more flops, we need more intelligence. This quarter there was something different, which was yes, we're raising CapEx, but it's because of needing extra dollars allocated specifically to cover rising component costs. Memory is more expensive, storage is more expensive, even things like fiber and optics are more expensive. And so I thought that was an interesting sort of shift of like, oh yeah, we are increasing capex, but it's just to pay, not to buy more flops, but just to pay for the things that we already committed to. Um, so I thought it'd be fun to start with the beneficiaries of this capex raise, which would be the memory and storage companies that reported. So we're gonna start there. How does that sound?

SPEAKER_01 7:06

Yeah, let's do it. Memory and storage is something I keep ranting on on the podcast. Like, how much more expensive is it going to get? Like, how much more are they going to raise prices? They expect a price hike every time, but if the price hike isn't good enough now, they're like, oh what? You're ex you're only doubling it? Why not? Why is it not five times? Yes, yes, investors totally.

SPEAKER_00 7:29

Man, aren't you happy that prices are going up? Not going up enough. Yep, your stock goes down. That is crazy. So, all right, let's start with Samsung or Samsung Electronics. Um, I the number that stuck out to me was that their memory revenue was up 101% year over year, which obviously is pretty crazy for memory. Um, they said as a company, their Q1 revenue and operating profit were at all-time highs. HBM sales are expected to triple year over year in 2026, and they expect HBM 4 to be 50% plus of HBM sales by Q3. So there's a mixed shift going from HBM 3, 3E to 4. Um, now, for people who haven't followed Samsung as closely, in the HBM market, um, the the story over the past couple years was they used to be there, there's there's basically three big players, SK Heinex, Samsung, and Micron. And Samsung used to be, you know, up there with SK Heinex, uh having a lot of market share on the order of even just about this time, you know, last year it was uh maybe like, or actually maybe like six quarters ago, that it was like 40% market share for Samsung. And in 2025, it dropped drastically down to like 13%, 15%, 20%. And so the story of Samsung is fall, they've fallen behind and now they're trying to catch back up. Now, of course, there's always a new technology, HBM3, HBM3, E, HBM 4. Um, and when a new standard comes out, there's an opportunity to try to be first to it and regain some market share. And so um, Samsung on their call, they were really trying to position that, like, sure, uh the past is behind us, but we're totally ready for HBM 4. And so I thought I'd read a couple quotes quick and then we can get into it. Um, but they wanted to make sure to say that they are the first and they are the best around HBM 4. So the quotes from the call, Jay, Jay Jun Kim, EVP of memory sales, said, after we became the world's first to commence commercial shipment of HBM 4 in February, and then also he called out, so so right there, like saying in passing, like, don't forget we're the world's first um shipping HBM 4. And then um he said, the differentiated performance of our HBM 4 led to concentration of demand, and our production ready capacity is fully booked and sold out. Our outstanding performance has been translating into actual premium on pricing. So the read-through there is there's always been a question around memory, around storage, which is is it is it just a commodity? A bit's a bit's a bit, it doesn't matter who it's from. And here uh Samsung was trying to say, hey, not only we're first, but our performance is the best, and that's why, and and we've got the capacity ready. So that's why we're sold out. Customers, and that's why we're able to have a premium on pricing, is because customers prefer us. Um any reaction to that, Vic?

SPEAKER_01 10:39

I remember this, there was this whole discussion about uh how many gigabits per second uh you can get out of HBM memory by designing the base die for HBM4 to be uh on a certain node, or even if it doesn't matter what node it is, because there was some discussion that Micron was using a memory technology to make the bass die while the other competitors like Samsung and Skynix were actually using a true logic node. Um the point is that the speed becomes a differentiating factor, so it's no more memory is just memory. How it performs is become has become a very important factor for like which company Nvidia or AMD will pick for their performance, and not only that, it comes the other way too. The Jedex spec for HBM4 is like I think 8 gigabit per second per lane. But then because they want supremacy on inference performance and tokens output and tokens per watt per dollar and all that, they are pushing the speed per lane of HBM 4 faster and faster and faster. So it's become a competition as to who can get to like 11, 10 or 11 or 12 Gbps per print. And that is not even is way beyond the spec, but it has become the thing that drives sales and drives lock-in. Because once these hyperscalers choose and qualify uh HBM vendor, it is a sticky decision because qualification, if you remember like the HBM3, Samsung couldn't really get qualified at Nvidia for a long time. They had so many yield issues and things like that. So qualification and performance makes this very sticky. Uh as so it's not fungible. So you just can't take out Samsung and drop in Micron tomorrow. Although there are only three companies doing this.

SPEAKER_00 12:45

Yes. And so zooming out and hitting on what you said again for listeners, the the real interesting thing is there is a spec, this JEDEC spec, J-E-D-E-C, that defines the performance level that and you know, the various other things that a spec define about how it's supposed to work, how it's supposed to communicate, um, that these three companies are trying to hit. And normally if everyone just hits that spec exactly, it would be fungible. But but what Vic is saying is that you know, NVIDIA said, hey, wait a minute, I've got, you know, I've got to compete against AMD and against XPUs. And if I could, if you could give me um memory, HBM memory that's even faster, then I can get even better, you know, tokens per second, tokens per watt, that kind of thing. And so actually, there is a pull from the the silicon vendors to the memory manufacturers to say, I know the spec says eight gigabits per second per pin or whatever. Um, can you go higher? Right. And so then there's this interesting, like someone's trying to get to 11, and now the others have to try to get to 11 as well. So there's this interesting pull to go faster, and now this kind of like unwritten spec that this performance, you know, that they're all trying to compete on. And so as you move away from just everyone meets the spec, we're all fungible to like how fast can you go, at what yield, at what cost, it is more of a true competition on the things that do allow you to have premium pricing over commodity pricing, which is which is performance, you know, and yield and cost and that kind of thing. So that's that's a little bit of the story, the back, the backstory here for HBM4 and how Samsung is trying to regain market share is to to truly compete on you know performance. Okay, so here's an interesting thing. Uh as we move out of that, looking at the the competition there between the three companies, um, and go focusing back on Samsung, another quote that they had was our demand fulfillment rate is now at a record low. Customers who are concerned about supply shortages are actually bringing forward their demand for 2027 already. So I, you know, not surprising, but again, it's just crazy to hear, you know, if customers are asking for this much, maybe it used to be like we can only give you 80% of that or 50%, maybe now it's even lower than that. I don't know, I'm making up the numbers, but trying to illustrate the point that customers are asking for a lot of memory and the memory suppliers saying, I can give you less than ever. So that would be uh the environment that we're in.

SPEAKER_01 15:24

Yeah, that's crazy to me. Uh, how much longer is this going to continue? Because people, these hyperscalers are increasing their capex just to pay these memory companies. Literally, that's what that capex is going into, just to pay these players for HBM and like uh NAND memory and things like this. I'm not sure how much how much higher is going to keep going. I I keep thinking that that's it, but I'm always wrong.

SPEAKER_00 15:50

Yeah, you know, that's it's an interesting point. We can get into it more uh both here and and later, which is I am very bullish on CapEx continuing to get higher when it's buying more flops, when it's buying more compute, because I, like everyone else, believe that the more compute we have, the more intelligence we have, the more we can do. You know, I I too have experienced, I'm sure everyone has, you know, um, Chat GPT or Gemini or Cloud Code just spinning or saying, like, oh, I'm busy right now, you know, or like come back, we've reached our limits. So that's frustrating, and that just shows that, like, dude, they need more GPUs, they need more XPUs. But is this this is a different conversation when it's like, how high can you convince your CFO to let CapEx go when you're not buying any additional compute, but you're just paying increased memory prices? Is that gonna be the straw that breaks the camel's back? Exactly.

SPEAKER_01 16:46

Because if you, if like you say, if all of this money went into expanding compute, then a lot more users of AI tools or whatever get actually something out of it. They get better tools, they use it to build better projects, that drives revenue, that drives an economy. It completes the circle in some way. What is happening now is if all the capex is going to memory players, it's like you're siphoning all this money out into somebody's pocket. It's not going into the you know positive reinforcement loop that we want to see. So this is a bit concerning for me.

SPEAKER_00 17:19

No, you're totally right. I mean, put succinctly, there's no ROI on that additional capex.

SPEAKER_01 17:25

Except for a few companies.

SPEAKER_00 17:26

Yes, yes. But for the hyperscalers, yes, there's no ROI, no extra ROIC return on invested capital. It's just a tax, really. It's it's a tax.

SPEAKER_01 17:36

It's a memory tax.

SPEAKER_00 17:37

It's a memory tax. So, okay, let's move on. Um, so we're gonna talk sand disk. So we've talked when we talked Samsung, we were focused on HBM, focused on memory. So let's talk um other memory and storage. So we're gonna talk sand disk, but really quick, I thought I'd give a quick history sidebar because we haven't talked about sand disk on the podcast yet. So um disc, Western Digital, really quick. They're two companies. Um, back in 2016, Western Digital actually acquired Sandisk for around $20 billion. And the thesis, I think back then was having a full storage portfolio. So, can we own both hard disk drives and NANDFlash? And that therefore we can sell hyperscalers a complete stack. Makes a ton of sense right now in the era we're in. But prior to AI, um, that thesis didn't really age well. I think they're they're very different businesses. They have different cycle dynamics, capital intensity, customer mix. Um so running them under one roof wasn't as simple as like, oh great, um, we share customers and now we can more easily cross-sell into them. It was actually sort of like, oh, these are two different businesses, and there's some different customers at play, and we're not getting the quote unquote synergies that we thought we would. Um, so back in October of 2023, Western Digital announced that they were gonna split Sandisk back out. And by February 2025, that spin out happened, Sandisk re-emerged as a standalone publicly traded company. And so when now when you think about Sandisk, you can think about NAND Flash, SSDs, embedded flash. Um, they have a joint venture on some fabs in Japan with Keoxia, Keoksia, not sure how to pronounce that. Um, and then so Sandisk, you can think of Flash, SSDs, etc. And then Western Digital is eight hard disk drives only. Um, and they are working, we're not doing a little bit of research. Western Digital is working on this interesting next generation tech, HAMR Hammer. It stands for Heat Assisted Magnetic Recording. And it, I'd never heard of it, but uh the goal is to achieve 100 terabyte plus hard disk drive capacities for AI scale data, and they're planning volume production in 2027. Have you heard of this? Yes.

SPEAKER_01 19:58

So HAMR has been there for a while, actually. It's not that new. Okay. HAMR has been uh cited, I've heard this at least for like five years now. Uh I can't pinpoint exactly how long it's been around. So it's always been the next uh, you know, the next greatest thing in hard disk drive technology. But then what has happened recently is that if you look at uh you know quad level cell uh SSDs, QLC SSDs, those sand disk ones, for example, the highest capability, the highest capacity one is five uh 256 terabytes, and you get it in an SSD form factor already. So I'm like, what is this HAMR? And it's gonna give you what 100 terabytes? It's not not that great, honestly. Today's day and age, of course, the price point will be lower, uh it should be. Uh, but you know, HAMR, yeah, it's it's been around, but it's I don't know how relevant it is or how where we are on that right now. But I wanted to go back in the history a little bit more. I think you'll find this fun. So did do you does the name like Sanjay Merotra ring a bell to you? Uh yes, Micron? Yes, Micron, Micron. Yeah. Do you know who founded uh Sandisk? That Sanjay Merotra. Serious? What? What? It's true. He was he was one of the you know founder, you know, he was one of the founding members of Sandisk. Uh and you know this was like way before his he became the CEO of Sand of Micron only in 2017. But he was the original uh uh founder of Sandisc. So he's like real real memory guy. And another fun bit of trivia on the name, right? Uh one of the other founders, um whose name I uh Eli Harari, yeah. He's one of the other co founders, and so they've you know they were talking. And find a name for the company or whatever. And then his daughter comes in and looks at some of the discs lying there. You know, you know, these platters or something. And like, oh yeah, that looks like the sun. So they decided to call it sun disc. No way. You can look up early logos of sun disk, and you'll see like a plate like thing with like the sun's rays like coming out of it. That's their logo. Serious. Yeah. We could put a picture if we find one. Yes, we should. Totally. Oh, great trivia. Yeah, yeah, yeah. And what happens is that later they like Sun microsystems came after them for some trademark stuff, like, oh, well, you can't use Sun in it or something. So they changed Sun to SANDISC. Oh, okay.

SPEAKER_00 22:46

Fascinating. Yeah, I was wondering. I was like, Sun, how did it make it sand?

SPEAKER_01 22:49

Uh I don't know if it changed really like seven years after the company was even found, like running. Okay. Seven years after the company was like fully functional, they changed the name to SANDISC thanks to Sun Microsystems. Nice.

SPEAKER_00 23:02

Well, we should talk to Sanjay sometime and ask him if the SAN came from his name too. Why not? Yeah. Yeah. Well, yeah, we should seriously see if he would talk to us about the history. That's so fascinating that he was a co-founder of Sandisc and now he's the CEO of Micron. Super interesting.

SPEAKER_01 23:18

Yes, yes. So I thought they'd mentioned that as part of a history lesson here.

SPEAKER_00 23:22

Oh man, good, good history lesson. Okay, so Sandisc. They reported earnings. Their CEO is not Sanjay. It is someone named David Geckler, I believe, Sandis CEO. So this quarter, they had revenue of almost six billion dollars. They were up 97%. The revenue is up 97% sequentially. So that's just quarter over quarter. And of course, how do you do that? You raise prices. They're up 251% year over year. Here's a couple things that stood out, which are pretty crazy. Gross margin, 78.4%. That's like gross margins of a software company.

SPEAKER_01 24:04

Yeah. Yeah, totally. I have my notes here that it was 51.1% the prior quarter. And you know the revenue estimate was supposed to come in like, I don't know, 4.8 billion or something. Yeah. They come in a billion above that. I'm like, what? Like they are up 250% year over year in like revenue. And you know the funny thing is that they haven't shipped like that many extra bits. This is all pricing. Yeah. This is not as much. You think like, oh, they sold maybe that much more, you know, to account for like 97% quarter over quarter increase. No, no, no, not really. You can't bring on that much capacity that quickly. Yeah. I mean, you're talking about making wafers and stuff and in a fab, and that stuff doesn't move in the time frame of a quarter. So this is all price increases.

SPEAKER_00 24:55

Totally. Wow. So you said their margins were 51% last quarter. Now they're up to in the 70s. 70s. And I think they're projected above 80 next quarter. Nuts.

SPEAKER_01 25:05

The guidance is above 80.

SPEAKER_00 25:06

They're gonna make yeah, NVIDIA look like they have work to do. NVIDIA is only like 75, right? Yeah, right. Totally. Totally. Oh yeah, of course, NVIDIA is a very, very large company and has had these margins for quarter after quarter after quarter. So the question is um, why is Sandis crushing it? Um and the what they the story that I heard on the earnings call was that they're they really believe that the NAND market is transitioning from commodity spot business to something less cyclical. Um, and so the the points that they made on the call, and I'll read some quotes here too. Um they have five multi-year supply partnerships signed. Um these three new ones in quarter three, they'd announced two previously and they had they had announced three more. Um, and those three new ones account for $42 billion of RPO remaining performance obligations. You can kind of think of it like a backlog. And this was the first time they've actually disclosed that. Um, so clearly there's long-term agreements for many years, and people are like signing up, and these customer commitments um already cover one-third of the fiscal year 27 bits. So it's not just people signing up for 2026, but they're already signing up and paying for and committing to 2027 bits, which actually have financial guarantees backing them. So it's not, you know, it people are putting their money where their mouth is. Oh, yeah, the CEO Geckler said he wanted to drive that, those long-term commitments to above 50% of bits. And already that one of the longest contracts was for five years. And so the quote that I thought was pretty telling on how Sandisk is perceiving this from the CEO. He said, last quarter we were engaged in discussions with customers on multi-year supply partnerships, what we refer to as new business models or NBMs. Um, I am pleased to share that we have successfully advanced those conversations with five multi-year partnerships signed so far. They are structured to lock in committed supply for our customers and committed financials for Sandisk. So kind of the customers are prepaying almost. Our customers' commitments are backed by firm financial guarantees. These partnerships support durable, structurally higher earnings in a significantly more predictable and less cyclical business for Sandisk. We believe this marks a fundamental evolution of our business, which is centered on deeper customer alignment, enhanced visibility, and long-term value creation. So, so far in this quote, he said, we're signing up people for the long run and they're paying for it. There hasn't yet, in my opinion, been an argument for why it's not cyclical. It could just be demand is crazy and people are signing up. Um as we talked about earlier with Samsung, when you're a commodity, when you're not a commodity, you're actually competing on performance, for example. And he hasn't talked about that yet. But then later, there was a quote that started to get into this, which I thought was interesting. Um, he said, as AI models scale from billions to trillions of parameters and deployments advance from simple inference to deep reasoning and increasingly agentic systems, NAND has become a critical component of the underlying infrastructure. Inference optimizations such as KV cache, along with workloads like Reg, will require substantial high performance, low latency flash to deliver real-time responsiveness and quality of user experience. And then he goes on to say basically, NAND Flash is emerging as the only economically viable solution to deliver that capacity, performance, and efficiency. And then he said, you know, goes on to make the argument that SANDISC is the best on these metrics. And therefore, um that's why they're capturing this value. So I want to throw it over to you, Vic. Do you think this is Sand disk? Is this AI, you know, truly needing lots of NAND and performance matters to your economics, to your token cost, um, or and bits are therefore no longer interchangeable? Um, or or is this just a demand thing where it's like, hey, they're locking up people for five years because they have supply, and it's sort of preventing true competition on like performance latency, that that kind of thing.

SPEAKER_01 29:29

Yeah, yeah. This is this is good. Did you look at uh the deep seek v4 announcement? Did you look into what is happening there?

SPEAKER_00 29:36

Oh, a little bit, but please tell us about it. It's rel it's related to it.

SPEAKER_01 29:42

You can see basically how uh Deep Seek V4 has compressed KV cache massively compared to the previous version 3.2, I think. And you would think like, why would you need NAND now if your KV cache is compressed? The problem is that the KV cache still, when you're doing agentic AI and agentic multi-turn AI, none of it fits in HBM. You're running hundreds of agents, they all have to have long context, long running context, multi-turn context. All of those key value cache pairs are just too much to store in HBM or DRAM. So if you see the Deep Seek V4 inventions recently, it is optimized to be an entirely SSD-centric inference system where uh KV cache is stored almost entirely on SSDs. It is pretty amazing, actually. And earlier uh after GTC, when uh uh Jensen announced the inference context storage system, which now I think he calls CTX uh context storage or whatever. So you basically this is a bunch of uh SSDs in a rack that is sitting there and connected uh via like high bandwidth fabrics to the GPUs so that they can offload the KB cache matrices into this this like SSD storage. That is becoming uh very important. And at that time I wrote a substract post pointing out how this is going to change the inference tokenics forever. Because one of the ways you can save on inference cost when you're using you know the API, you can look this up for any model, is that it really depends on a few things. First of all, you've got the input tokens, you've got a certain number of tokens uh cost per million tokens. Then you've got the output number of uh dollars per output tokens, right? And it's usually like a four or five is to one. Output tokens are like five times more expensive than input tokens because it go undergoes this like reasoning, this thinking process, right? The thinking process costs a lot more money, so the output tokens are more expensive than input tokens. In the middle, you have another pricing point called the cash hit or cash miss. So what that means is that if you have KV cash and your uh inference is able to reuse that KV cash as much as you possibly can, right? You have a cash hit. And when you have a cash hit, your cost of inference goes down massively. So what people do now is to basically have a bunch of system instructions right up front, and then they'll like only append to the bottom so that you can maintain your cache hierarchy completely. So this is like cash aware uh inferencing. And Deep Seek, for example, like it's uh there was some metric saying that like in agenti use, you can make it use 95% of cash hit rates. So 95% of the time it's hitting cash. It in very few cases it even goes to 99%, it's hitting cash. So even now, if you go to the Deep Seek uh API pricing page and see how much the cost has dropped for the Deep Seek V4 Pro, okay, it has gone down to a fraction of a cent per million tokens. Okay. You can compare that to Opus. I don't remember the number right now, but it's like significantly higher. So what this says is basically SSD-driven uh inference is basically the only way forward. Deep Seek has kind of portrayed that clearly now. And you cannot store all of this information on DRAM on or HBM. It's just too much. It's too much. And you almost have an infinite storage of SSDs. You know, the cost per unit is like an order of magnitude higher uh when it comes to DRAM versus SSD. So you've got this essentially free storage, and now you have like capacity is a solved problem if you go to SSDs. The only problem is then uh you have this bandwidth pattern bottleneck because you can't access stuff as fast uh from SSDs as you are. Right. So you know, so I've been meaning to read this new paper that's come out from the Deep Seek team called I have it on my screen right now. It's called Dual Path, breaking the storage bandwidth bottleneck in LLM instance, especially agentic LLMs. So I want to see exactly how all of this ties in together. So I've basically given a surface level overview of justifying why Sandisk is saying that NAND storage is so important in the future of agentic AI, because DeepSeq is already a data point that is heading in this direction. There's a long answer to your rather simple.

SPEAKER_00 34:42

No, this is this is so good. Okay, so I'm gonna summarize it and then I have a follow-up question for you. Okay, so you're saying, hey, look, Deep Seek is showing us that uh SSDs are more important than ever, NANDFlash are more important than ever. And if you think about the tokenomics, it's way more economical when you've got these cash hits versus cash misses. So you got to think really hard about can we have a very big cash or memory hierarchy and can we store as much as possible? And people are going to be very incentivized. Even the end customers using APIs, running agents and stuff are gonna be incentivized to actually think about memory and think about caching. Um, therefore, SSD market is gonna just continue to grow. Um, but my question for you then is okay, SSD market, SSD TAM, gonna explode. All good news. Invest in these companies, but why sand disk?

SPEAKER_01 35:36

Not advice.

SPEAKER_00 35:37

Oh, yes, not not this is not investment advice. This is not investment advice. We are just thinking very hypothetically here. Um do your own due diligence, you know. Uh don't hold the Knight accountable. Okay, so uh the SSD TAM is gonna explode or is exploding, but is there is a bit, is an SSD bit a bit, a bit, or is is Sandisk's bit better than someone else's?

SPEAKER_01 36:03

I think a bit is a bit. I mean, is this NAND is a rather established technology. There isn't a controller. Actually, there is a controller difference. Sandisk controller for the QLC NAND is called Stargate, and they're still working on it. And usually the more bits you add, so in going from a triple level cell uh to a quad level cell, you go from having nine states. A single cell has nine states in a triple level cell. In a quad level cell, it has 16 states, a single cell. And now, depending on how you program this cell, you should be able to distinguish between nine or 16 different states. Otherwise, you don't know what bit is holding. Is it holding like a pattern 10 or pattern 15? So the complexity of the controller for this NAND gets significantly higher even when you add a single bit. Like if you go to penta level cells, which exists in research mode, you will go to 32 levels. Now you have to distinguish between 32 levels, you know. That makes it very difficult. Um, I have a whole article on how all of this works. But yes, there is a difference in controller and how they how it works and all that, but it's not really a differentiating factor. Okay. The controller needs to work well. And as far as I can understand it, please correct me if you know there are any storage experts out there who actually work on this stuff on a day-to-day basis, they always know better. But as far as I know, a bit is a bit.

SPEAKER_00 37:34

Yeah, we should follow up and bring on someone, Micron, Sandisk, Samsung, whoever is listening out there, of course, to talk memory, but also to talk storage. Let's I would love to talk storage here and hear like a product manager's argument for a bit is not a bit, because it probably comes down to things like reliability or pricing per bit or or other factors than just straight up read latency or write latency.

SPEAKER_01 38:04

Yeah, yeah, yeah, yeah. Maybe there's some controller magic there because a lot of the latency comes from adjusting the voltages just right to read this particular state of the cell. So what it does is it it iteratively programs the right voltage to reach that state. That takes time, you know. So if there's like some fancy new algorithm that can go quickly and you know that you can reduce the latency that way, that may be a differentiating factor. Actually, from IEDM last year, and if I think we spoke about this on a past episode, we spoke about a totally different kind of cell where you can dramatically increase uh the reliability while still having like 36 states to a cell, you know? That's right. Yes.

SPEAKER_00 38:49

It was like the circle one or something.

SPEAKER_01 38:51

The circle one, yes, yes, yes, yes.

SPEAKER_00 38:53

All right, the listeners go check out our backlog. Yeah. Okay, this has been a super good memory deep dive. Let's keep let's carry on real quick. Okay, so let's talk hyperscaler earnings quick. Um, so hey, it was a good quarter for Samsung, it was a good quarter for SandDisk. Um memory, storage, price through the roof, demand through the roof. What does this mean for the hyperscalers? We kind of already hinted about it. Um, Microsoft disclosed um $190 billion of CapEx for 2026. And the CFO Amy Hood said roughly $25 billion of the calendar 2026 CapEx is specifically higher component pricing. So that's pretty crazy. We are only a few years removed from someone like Microsoft spending a total of $25 billion per quarter just on all of their capex. And now we're talking about in a year they're gonna spend like kind of a quarter's worth of capex just on higher memory storage component prices. Um just give it to the memory guys. Yeah, yeah, right, pretty much. Uh hey, good good time to be a memory guy. Meta raised their capex. Um and Zuck on the call said most of the raise is higher component costs, particularly memory pricing. Google has a higher capex, although they didn't talk about that as much. Um Sundar did say that their cloud, their oh their cloud business was up 63%, um, which was insane. And Sundar said that that would have actually been higher if they were able to meet demand. So still talking about demand and capacity being the bottleneck there. And then Amazon, they didn't uh talk specifically about uh component prices and impacting their capex, but but check this out. This was an interesting question, like uh commentary that came out. The CEO Andy Jassy was asked if memory constraints um are negatively impacting them. And he answered by saying that for their cloud business, for AWS, memory constraints are actually driving cloud growth. And here, and that feels very counterintuitive. And here's what he said who knows how big this is in aggregate, but he said one of the interesting things that we see right now with the change in price and in supply on things like memory is it is actually a further impetus pushing companies who have been on-premises infrastructure into the cloud. And it's because these suppliers, the memory suppliers, are prioritizing their very largest customers, the hyperscalers cloud providers. And so, therefore, there's a number of enterprises who can't get on-prem infrastructure and it's actually pushing them to speed up their move to the cloud. So I thought that was pretty interesting.

SPEAKER_01 41:42

And I think people are generally comfortable in using like AWS cloud. It's it's a very easy switch to go and do your stuff on there because it has been the bread and butter for like pretty much the software industry for the last decade, right?

SPEAKER_00 41:59

Yeah, totally. It would be interesting to dive in with them because at this point you ask, well, who's still running running on-prem? And it's it's gotta be people who are still just thinking about like, oh, what data do I keep on-prem because I'm in the financial industry or health industry or something. But even those folks are still moving to the cloud and uh they're getting pulled there faster because the only place they can get compute and memory is actually from the cloud players, which is very, very fascinating.

SPEAKER_01 42:29

Yes, yeah.

SPEAKER_00 42:31

That's the only place you can get it. That's where you go. I mean, it doesn't matter what you want, right? It's like, yo, sorry, compliance team. I know we're we're dotting all the I's and crossing all the T's, but literally we have to. We have to make this move happen right now.

SPEAKER_01 42:45

Yes, if you can buy memory from the memory guys, then maybe.

SPEAKER_00 42:49

Yeah, yeah, exactly. Exactly. Yeah, you go you go find it. You go find it. Okay. Um, so okay, AI accelerators were talked a lot about across the hyperscalers. Google said you know, publicly on their earnings call that the TPU will be sold in a merchant capacity for the first time and at multi-gigawatt scale. And and then actually, if you look in the 10Q, there was some risk language now confirming that the the risk to doing that is getting coas and HBM allocation. So I thought that that was interesting.

SPEAKER_01 43:21

Um eMib. Forget about co-ops.

SPEAKER_00 43:24

Hey, there you go. Yeah, go to EMIB.

SPEAKER_01 43:26

That's for the win.

SPEAKER_00 43:28

Yes. I hope to write something about eMib here shortly soon, comparing it to like CoAS L, which also has bridges, but to unpack that for people. Um, AWS talked about trainium um at a $20 billion run rate, growing triple digits. And of course, people are not generally asking to buy trainium, and they're not even necessarily uh renting it directly, but they are consuming Amazon bedrock and all these services that run on top of trainium. Um Tranium 2 largely sold out. Tranium 3 nearly fully subscribed. And Jassy said on the call that because they do custom XPUs, they will save tens of billions of dollars of CapEx savings each year, which translates into several hundred basis points of operating margin advantage versus relying on merchant chips. And on the one hand, normally I'd been like, wow, that's so incredible. They're gonna save tens of billions of dollars. But then right away I thought, oh, so they can pay for their memory.

SPEAKER_01 44:31

Yeah. Yeah. Making our own uh chips so we can pay the memory guys. Yeah, right. What is happening right now, but yeah, we'll see.

SPEAKER_00 44:41

Totally. So um then Meta mentioned, of course, they've had tons of uh press releases building up to this quarter about one gigawatt worth of MTIA with Broadcom, and they had showed their roadmap of you know four chips in two years, uh MTIA XPUs. We had a great conversation with Meta recently on that with Matt Steiner, and hopefully we'll have more getting into it further. Um, they now Meta did mention significant deployments with AMD and then also running on some new NVIDIA. So they were talking uh up all their multi-silicon vendor uh partners. Um, so with that, we've run long. I think we should call it quits here. Thank you everyone for listening. Um, YouTube, YouTube folks, thank you for your comments. We see that you would like Vic to explain again from our Google TPU one why is it seven hops with I think it was with board fly and not 16 hops. So we will follow up with you. We'll draw a picture sometime. So keep writing your comments, keep writing your questions. Thanks for everyone for listening, watching us on YouTube, watching us on X, and reach out. Uh, thanks again. We'll talk to you guys later.