Qualcomm's Data Center Debut, OpenAI's Jalapeño, and the Memory-as-Strategic Infrastructure Debate | The Six Five Pod Ep. 310

The handpicked topics for this week are:

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1. Qualcomm Investor Day 2026 — The Data Center Debut: Pat and Dan break down Qualcomm's push into the data center after the company took the stage with Microsoft's Satya Nadella and Meta's Mark Zuckerberg as named customers. They unpack the new Dragonfly platform, including the C1000 250-core data center CPU with PCIe Gen 7 and CXL, the AI200 and AI250 inference accelerators, and a novel High Bandwidth Compute (HBC) architecture that stacks compute under LPDDR memory at dramatically lower cost than HBM. They highlight Qualcomm's ambitious growth targets: $15B data center revenue target for FY 2029, an increased total non-handset revenue goal from $22B to  $40B, and a shortened timeline for automotive revenue by two years. They also debate the identity of Qualcomm's unnamed hyperscaler customer and why its robotics opportunity may be flying under the radar. (The Decode)
   
   
2. OpenAI and Broadcom Unveil Jalapeño, OpenAI's First Custom Chip: A photo of Sam Altman and Hock Tan holding a wafer and packaged die kicked off OpenAI's reveal of Jalapeño, a custom inference chip built with Broadcom and slated for late-2026 deployment. The chip reached tape-out in roughly nine months, which is an aggressive cycle for an ASIC of this size, and uses HBM3E memory. Pat takes a victory lap on his long-standing heterogeneous compute thesis: every hyperscaler and now every model lab is building accelerators, and the XPU efficiency argument has played out as predicted. Dan frames OpenAI's broader move as existential: they cannot serve frontier models at premium margins if compute remains constrained. He flags that OpenAI is trying to do everything from chips and fabs to social networks and browsers, and that its IPO is now delayed. (The Decode)

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3. Anthropic and Micron Sign a Strategic Multi-Year Memory Agreement: Anthropic and Micron announced a multi-year supply agreement for HBM, DRAM, and SSDs, including co-designed next-generation memory for AI workloads, along with a strategic investment by Anthropic in Micron. The pattern mirrors Samsung and SK Hynix’s pre-funding Anthropic in May, and follows OpenAI's Jalapeño as another frontier lab moving to lock in supply chain control. Dan frames it as the same circular financing playbook NVIDIA ran two to three years ago, but with the ball now in the memory triopoly's court. Pricing-floor agreements with no ceilings, customized rather than commoditized memory architecture, and demand running well past the previously assumed 2027-2028 horizon. Pat notes that the rumored 14% free cash flow margin at Anthropic makes the strategic investment math work cleanly for both sides. (The Decode)

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4. SpaceX Signs $6.3B Compute Deal with Reflection AI: SpaceX inked a $6.3B compute lease with open-source AI lab Reflection AI, at $150M per month from July 2026 through 2029, giving Reflection access to NVIDIA GB300 chips inside the Colossus infrastructure. Combined with the $920M-per-month Google compute contract and existing xAI commitments, SpaceX now has a contracted backlog larger than most public AI startups' entire revenue base, with some calling it the largest commercial AI infrastructure provider at $80B in contracted revenue. Pat reads it as XAI failing to land with developers, consumers, or enterprises, leaving SpaceX with a pot of gold worth far more as wholesale capacity than as XAI's own training compute. Dan flags that Google owning 7% of SpaceX ahead of an IPO is not accidental, and the open question is whether this becomes a Nebius-style infrastructure trade or a full-stack Google-equivalent platform. (The Decode)

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5. Japan's Agentic Orchestrator Sakana AI Ships Fugu Plus and Fugu Ultra: Japan's Sakana AI released Fugu Plus and Fugu Ultra, an agentic orchestrator built on a multi-agent MOE approach that routes workloads across multiple underlying models rather than training a new frontier base model. Sakana claims agentic capabilities on par with or better than top frontier models at significantly lower input/output token costs, similar to the DeepSeek and GLM cost-undercut narrative. Pat compares the architecture to OpenRouter and notes the developer-facing parallel to Perplexity Computer's model-routing approach. Both agree that models themselves are no longer moats, and suggests the real moat is the harness, tooling, connectivity, looping, agentic stack, and total compute availability. Expect more sovereign agentic plays from Japan, the Middle East, and elsewhere on the same template. (The Decode)

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6. The Flip — Is the Era of Memory as a Commodity Over? Daniel takes the FOR side: memory has moved from commodity to strategic AI infrastructure, citing 16 multi-year agreements covering $22B in committed volume booked through 2027, 84.9% gross margins higher than NVIDIA's, the technology barriers of HBM yield/stacking/packaging that only three companies can clear, and demand drivers tied to HBM as the binding constraint on every AI accelerator rather than to elastic consumer cycles. Patrick takes the AGAINST side: long-term agreements and SCAs signal a commodity in a strong cycle, not a structural rerating; nearly every relevant memory standard — DDR5, MRDIMM, HBM3/3E/4, LPDDR5X/6, GDDR6/7, LPCAM2 — is JEDEC-standard and therefore commodity at the pin; and CXMT's China DDR5 production ramps in 2H 2026 with Lenovo already shipping and HP and Dell qualifying. Custom HBM4 and Qualcomm-style HBC are where strategic memory genuinely lives. (The Flip)

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7. NVIDIA's $25B Investment-Grade Bond Offering: NVIDIA priced a $25B multi-tranche bond offering on June 15, its first investment-grade debt sale since 2021, with seven tranches maturing between 2028 and 2056 and $85B in orders against an initial $20B target. Dan reads it as raising when capital is cheap, and oversubscription is real. NVIDIA doesn’t need the money, it has a gold balance sheet, and is establishing a credit benchmark rather than funding CapEx. Pat agrees the optics are clean, but flags the irony of NVIDIA, with negative debt, borrowing while the stock trades like dead money at a sub-20x forward P/E. Both note that NVIDIA's underperformance reflects the market's skepticism on memory-as-strategic and on NVIDIA's own capex pace relative to the buildout opportunity ahead. (Bulls & Bears)

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8. Tim Cook Calls Apple’s Memory Crunch Price Raises on MacBook and iPad "Unsustainable": Apple announced MacBook and iPad price increases of up to $300, with Tim Cook telling the WSJ the memory cost environment is unsustainable. AAPL fell ~5% on the news, the broader rally was momentarily wiped out before Micron held the gains by close. Dan frames it as a moment when the market saw who is going to pay for the AI buildout: the consumer. He notes Apple's pricing power and inelasticity test is now live. Pat traces the backstory to Apple's negative-margin pricing pressure on Micron during the 2022-2023 memory downturn. The question is whether consumer-price blowback will eventually flow back to the memory vendors. (Bulls & Bears)

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9. Micron Blows the Doors Off Fiscal Q3 — $41.46B Revenue, 84.9% Gross Margin: The memory story continues as Micron reported its largest beat in company history with fiscal Q3 revenue of $41.46B versus a $35.69B consensus, EPS of $25.11, year-over-year growth of more than 340%, and a record 84.9% gross margin that is roughly 10 points above NVIDIA's. Q4 guidance came in at a $50B midpoint against a $43B consensus. The 16 multi-year strategic customer agreements add up to $22B in committed volume, with most contracts containing pricing floors but no ceilings on most of the volume — a structurally asymmetric setup. Pat notes 95% of the beat came from price, not units, which reinforces his commodity argument; Dan flips it as the early innings of an NVIDIA-style run that puts Micron's 2027 profit on par with Google. (Bulls & Bears)

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10. Cerebras' First Earnings Report Since IPO — Revenue Doubles, Margins Compress: Cerebras (CBRS) reported its first earnings as a public company, doubling year-over-year revenue and beating the top line while missing EPS, but the stock sold off hard amid gross margin deterioration. Core revenue came in at $191M, up 12% sequentially, with a $194M Q2 guide that is essentially flat, core gross margins at 47% guiding to 36-38% and 38-41% for the year, and operating margins flipping from positive 2% to a guided -30% to -32%. Customer concentration is shifting from Core42 and G42 (86% of FY25 revenue) to OpenAI, which loaned Cerebras $1B and gets paid quarterly in warrants. Pat flags that Cerebras' uncontested speed claim is no longer uncontested with Groq, TPU v8i, and Tenstorrent putting up real numbers. Cathie Wood is down 52% on her position. (Bulls & Bears)

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Patrick Moorhead:
Welcome to The Six Five Pod. It is episode 310. Dan and I are back from New York City to make sure we can shoot this. Daniel, how you doing, my friend?

Daniel Newman: 

Man, I'm doing good. It's Friday. Shout out to my Youngest child, Matthew, 10 at 10 years old. So I've been kind of doing daddy duty this morning, celebrating his big day, double digits, you know? He knew me back when he wasn't even here. He knew me back when he wasn't here. So it's, time's flying. Time is flying, but excited, exciting day.

Patrick Moorhead: 

Yeah, I'm going to hit hit up my family. So my my son Patrick is moving out officially today. Moving trucks are going to be there taking his stuff. He's got a nice apartment not too far away in case I get lonely and need to need to, you know, go see how he's doing. But I might shoot over there after work and and see how it's going. Definitely has a an amazing apartment. Really proud of that kid. So busy day, sorry, busy week, man. We spent three, literally three full days in New York City. We're going to talk about the Qualcomm Investor Day. Dan pretty much was on every single possible show you could be on out there as well and broadcast. I hit up two but You know, I am, I'm blessed to do that. We've got a great, got a great show for you though. I mean, we're essentially talking about the control layer. Like everybody wants control. Like is it, is it, is it chips? Is it software? Is it the, the model makers? Is it, you know, the energy producers? It's just, is it just the memory? vendors at this point, right? Are we lacking money for capital? But anyways, I'm looking forward to pulling the thread on those two. Not a lot of earnings this week, but Micron and Cerebrus were two, I think, telling indicators. And we're going to talk a little bit about NVIDIA's $25 billion bond anchor as well.

Daniel Newman: 

Dude, it was the Super Bowl of tech earnings this week. You don't need a lot of earnings when you have micro. I mean, micro, storage, memory, commodity, right? I mean, I'm kidding.

Patrick Moorhead: 

I mean, I'm waiting for the trifecta, the triopoly of memory just to start buying compute companies now with all that swimming in cash, right?

Daniel Newman: 

I mean, think like 2 years ago when my crime was just dying, it was just a disaster. We'll get to that. One of these hyperscalers had bought them. Like how different things could be.

Patrick Moorhead: 

Yeah, totally. I saw some discussion about what if Amazon had bought Micron. It's good stuff. Now, we have a great show for you, but hey, let's jump into the decode where we separate the signal from the noise about the biggest tech topics either on the news or in shit posting on social media. Let's dive in. All right, Daniel, we could probably spend half the show on the payload of news that came after this, but you and I both went to the Qualcomm Investor Day. It really was the data center day. They did talk about a lot of other important topics, but it really was all about the data center. Daniel, let's break this down and hopefully you can leave me some oxygen.

Daniel Newman: 

No, I'm going to take it all. I'm going to hog it. You already did all the rounds and TV. I didn't get a chance to talk about it. So the first of all, this is the moment for a victory lap. It's for many, many months, maybe even a year now. I have, and I know you have too, been very outspoken and despite quite a bit of, you know, I would say contention or even negative sentiment across a lot of parts of the technology pundit, analyst, and equity side, Qualcomm is going to make an entry into data center this time and it's going to be different. I think the challenges and Nobody knows this better than you, Pat, but when a company has kind of tried to get into something in the past and failed, that particular history tends to weigh heavily on them when they try again. There was skepticism around AMD for a long time because it had exited a business, came back and I mean obviously now they're back with a vengeance and I think that stock only goes up. I mean I'm joking but it's like been just a parabolic run. But for a long time we basically said that look Qualcomm has the IP you know going back to Nuvia but deals with Ventana, deals with AlphaWave. They've been buying pieces for some time and they've been showing their hand, but they haven't been super crystal about what they're doing. While the entire market ripped for three years, Qualcomm was left to be a smartphone licensing IP company with an interesting auto business. And so this had to be the coming out part. And so over the last few months, there's been little bits of news. Humane win, potential, a couple of the hyperscale wins. They announced an AI200 to replace a fairly low volume AI100 part. And an AI250, is it rack scale? Is it not rack scale? They showed Rack, looks like a Rack scale, but you know, how are they going to come out? Are they going to do merchant type parts for the hyperscalers? Or are they going to do custom? Are they going to do both? What about IO? Because if they don't have IO, you can't go Rack scale. So all these things have been sort of just ruminating about Qualcomm. And so this was the day that we started to get some clarity. So what are they doing? Well, Actually, it looks like they're going to do a little bit of all the above, except maybe not the rack scale. That didn't really seem to be a thing that came out, but the AlphaWave acquisition clearly entered them into a number of custom hyperscaler agreements. They talked about two, didn't tell us who they were. I have some ideas. I don't know, maybe you and I can come back to that. I'll leave that for now. They also announced these CPUs, so they're going to have custom data center CPUs, but they're also going to have a standardized CPU that comes later, a high-scale volume version. They're going to have I.O., and they're going to do network chips, and then they're going to have an AI accelerator. I think the two big moments during the presentation from their new data center leader, Tony Pialis, was his getting both Meta and Microsoft to present. But not only getting them both to present, he didn't get tier twos and tier threes to show up and endorse. He got the A-team. Satya, standing in front of his usual bookshelf doing his usual thing, announced a custom CPU deal for Microsoft, and then Meta announced multiple generations of CPUs that they're going to build together. This was probably the proof point. And what did that all amount to? Well, they're talking about all this together. They put a really, I think, a really modest target on revenue, $5 billion of 27 FY, which, by the way, FY27 for Qualcomm means later in 26. And then 15 billion in 29. So my feeling in my gut was they basically forecasted the revenue they already have in the bag. Just a guess. Obviously, everyone knows custom and partnerships on these chips. We're seeing it play out with Broadcom. We're seeing it play out with MediaTek. We're seeing it play out with Marvell. No guarantees first generation succeed. No guarantee multi-generation deals all scale and ramp. So all those things are still to be proven. So that's kind of what the biggest things that caught my attention there. And I'll just call out they also, because because why not, announced a $3.9 billion deal to acquire software play, modular. And this one's interesting because their story is all about making hardware agnostic, an AI runtime compiler that works on any chip. Is this a lock-in against CUDA? Is CUDA even still a lock-in? It's an interesting debate with a lot of developers right now with AI code development. But having said that, among the developers, my reading, I'm not a full stack engineer, despite the rumor, is that this was an interesting platform that had a lot of potential. And now people are sort of watching closely how Qualcomm deploys this, because it's history, Arduino, other softwares, they haven't necessarily come in immediately and embraced open community. But some of the conversations we had there, Pat, seemed to indicate that the customer is open, or sorry, Qualcomm is more conscious of this and is going to play that their hand. Well, you know, I suggested a little bit like IBM played the Red Hat hand. Yeah, might be the right way to play this one. So I said a lot, but I didn't say I didn't go into tons of detail. So I'll give you some air to maybe go into some of the details. And, you know, this was like you said, how we spent like two and a half days. So a lot here.

Patrick Moorhead: 

No, I did a good breakdown. And essentially, you know, Qualcomm didn't just show up with a roadmap, right, which a lot of companies do. It really showed up with Satya and Zuck as named customers, an important software acquisition to give proof points and add capabilities that they can do data center software too, in addition to spreading that out across their entire edge to cloud portfolio and put up a beefy, but I think very conservative $15 billion, 2029 target. And by the way, for people to say, oh my gosh, you know, 5 billion so low folks, we're talking, you know, zero to, essentially zero to five billion at this course, you know, with a little bit in there, or alpha wave, IP, that is huge. And just to give you that proportion, AMD, in their entire first year of their first GPU accelerator for AI did $5 billion of revenue, okay. And I think that's a good sobering point here. Now, most of that $5 billion is going to be the custom, the two custom wins that were named. I'm going to go out on a limb here. You had Satya out there who talked. You had Meta and Zuck. Well, who's left? You got Google with TPU. They already have two to four vendors helping them full scale and back end already. So I don't think it's going to be Google, but it sure seems like it could be Amazon at this point. And my big learning into talking to all the hyperscalers the last six months, and you can also buttress this up against NVIDIA's newfound heterogeneous compute and disaggregated compute view, is you're going to need more than one accelerator, folks, okay? So, you know, let's say there's Tranium or let's say you're trying to do some interesting package of pulling an Amazon CPU Graviton with a Tranium, you know, that might make a really interesting kind of high bandwidth and who knows, you know, maybe the interconnects NVLink between the two. Anyways, I'm just making up stuff at this point, but just given by who was on stage, and them saying there's a US hyperscaler in there, it's not too hard to figure out who it might be. The only, I'm gonna call it oddball, or the only, could it be Oracle? I mean, I guess, but Oracle, Qualcomm's accelerator isn't ready yet. And from a CPU perspective, they're buying Ampere chips already.

Daniel Newman: 

What about a Chinese hyperscaler, could it be?

Patrick Moorhead: 

Yeah, I mean, Bloomberg had a ByteDance rumor on that and I could see high probability and probably they don't want to bring it on stage because it's China, right? Even though most of Qualcomm's handset revenue comes from China, right?

Daniel Newman: 

Yeah. Qualcomm's very strategic in China. It just would not surprise me for one of the wins to be China.

Patrick Moorhead: 

Yeah. Hey, one of the key technologies that Qualcomm brought out was this HBC. And that's basically an architecture. Don't confuse this with HBM. But instead of having a separate package for the memory, Um, it, it actually, um, um, is layered on as a metal layer, uh, just like you would do a monolithic chip. So, um, this isn't what I would say, you know, I'm not Babe Ruthing this, uh, because you know, and, and, you know, Daniel, you and I kind of had the same old, Hey, if this is so good, why isn't everybody else doing it? a type of thing, that doesn't mean it's low value, it could be absolutely breakthrough. And it's not only available on the CPU, but also on the accelerator, which is pretty cool. And essentially puts the compute under the LPDDR RAM stack. So, you know, is it packaging? No. Does it accomplish very similar things as what you might expect with HBM at a dramatically lower cost? Yes. Has Microsoft and Meta signed up and do they have confidence enough? I did hear that the chip had been taped out. And that doesn't mean that, uh, taping out something, uh, is, is an amazing thing and it's good and you got to get the samples. Uh, but there's work to do on how to, how to do high, um, high volume, uh, manufacturing on that. So very exciting. So Qualcomm bringing in an architectural. differentiation, you know, when people want to ask, like, why do we need more? Like, why do we need more accelerators? Why do we need more data center CPUs? So, There weren't a lot of details about the CPU family, and it's three, right? One for a head node, one for kind of a general purpose CPU, and one for an agentic version. I don't know any details around that. With agents, it's more about the bandwidth than it is about the, you know, you know, int performance, but it would be nice to know what's going on there. I didn't expect this. The other thing I didn't expect was them getting into networking. And, you know, I think I said on X, I shouldn't be surprised, but I am surprised. It was just how many, you know, AlphaWave was a core IP developer for some of the biggest hyperscalers, by the way, including Amazon. I don't know if people know that or not. But they happen to have a good SERTES, even though nobody talks about them having a good SERTES. And for all of those out there, SERTES is essentially the core building block for all networking. And you know, they they gave a pretty good case, albeit this is going to be, you know, part of the revenue that hits a little later, they did give a a three year roadmap. I mean, they do have in production 800 gig Copper 800 gig optical and he sees in 26 and 27 is 1.6 T and then in development for 2028 3.3 point terabit optical modules and an AC. This is serious business and this. This, it's funny, was probably my biggest surprise coming out of this. And Daniel, to your point, you know, they're not bringing out a full scale-up solution at this point. But scale-out and scale-across seem very possible at this point. Is there anything we may have missed, Daniel? I don't think so.

Daniel Newman: 

No, I mean, we could dive into robotics and stuff, and I think we can just put a very quick point. Nicole de Gaulle, who's led the automotive, was able to put an exclamation point. That's been a steady diversification and probably part of what I call their permission to win in a new category has been their ability to enter that category so successfully. And then the only thing I'd say is in robotics, they are really trying to build a stack that kind of cuts across all their different portfolios and, you know, very software centric. And I do think even more so than data center path that robotics is an area that they really do have the right sort of IP, the right sort of low power, the right supply chain. Like they just have what looks like, and this is just a little further in the future, but I don't think people are valuing that part of their business at all right now. I think it's kind of like the way IBM's quantum is viewed. It's just something in the future, but I think it's something to keep an eye on.

Patrick Moorhead: 

Yeah, that's a good point. I will note that the company did pull in their automotive revenue target by two years. And they also said that they will shortly become the largest automotive electronics supplier on the planet. So given all the dispersions that were cast years before, it just shows what the company can do. I'll also add that the company updated its 29 revenue targets. And they essentially doubled their non-handset business from a 20% CAGR to around a 40% CAGR, $22 billion to $40 billion. By the way, the only reason the stock didn't rocket ship was because the balance of the handsets.

Daniel Newman: 

By the way, I put a rocket ship after one of the tweets. That might have helped.

Patrick Moorhead: 

No, it may have.

Daniel Newman: 

Yeah, absolutely. You should try it. It works well.

Patrick Moorhead: 

Okay, I think we we drain that gave it it's gave it enough credit there.

Daniel Newman: 

Let's dive into the show.

Patrick Moorhead: 

Exactly. Hey, let's get into some more AI and chip news. There was a picture out there on x, by the way, if you're not an ex, just you need to be on X. It's, it's where it's happening. It's where CEOs, it's where Daniel and Pat are constantly shit posting and, but you got to get in there. But a picture of Sam Altman and Hawk Tan, essentially, you know, not only showing a, a full wafer of their new jalapeno chip, but also, you know, a small little packaged dye shot. So, you know, I, without trying to get in, there were people trying to dissect whether it was an HBM4 or 3E. It's likely 3E. There were people saying it looks like a training chip, and other people were saying it's an inference chip. The companies themselves said that it was inference, but I also remind everybody that Trainium train is actually primarily, can train, but it's primarily used as an inference chip. I want to do a victory lap here, which was years and years and years ago. Three years ago, I was talking about the benefits of heterogeneous compute and the value it brings. And I was very clear that for an XPU, if you know what software you want to use, it is going to be more efficient. You may not be able to use it as long as a GPU, but it is more efficient and now everybody and their mother is is doing a an accelerator not only on the hyperscaler side, but but now on the On the on the model side. So that's really that's really the I think that's really the the big picture here and everybody You know telling me that everybody's stupid for not not not using Nvidia I mean listen There are cons to not using GPUs out there, but what is clear is these companies are willing to look beyond that and make it happen.

Daniel Newman: 

Yeah, I think that we've probably beaten this philosophically to death. It's an and, not an or. There will continue to be utilization within all these hyperscalers of heterogeneous compute architectures, both compute types, you know, CPUs and NPUs and DPUs and XPUs and GPUs and blah, blah, blah. But also in, you know, within even certain categories, you know, they're going to need more compute. Let's be clear. They have capacity constraints, they have demand, they have to fill that demand. And a lot of deals right now are being done with both short term in mind, how much compute can I get immediate access to? And then they're being done with longer term in mind, like, can I continue to pay 75-80% margin to have access to what we could argue is the best end-to-end compute platform in NVIDIA. I think what will end up happening is you're just going to end up with an amalgamation of all of the above, and it's going to be necessary because we just still don't have enough. I think in the long-term, these companies have to be thinking about their margins and their business and their revenue streams. OpenAI is just an interesting one though because they want to do everything. You heard their IPO got delayed this week. They're building chips. They're going to build fabs. They're going to build social networks. They're going to build browsers. They just need to figure out what they are. That's a little bit of a different thing here. But one thing I do know is if they're going to serve the most advanced models beyond the frontier and absolutely be able to command premium margins, premium valuations, and get the support of Wall Street when they do go public, they can't have constraint on compute. So, you know, they need to control their destiny and I think this is part of that process. You know, we'll see when it, when it gets, you know, it gets deployed, how, how, how well it does. And like we'd said earlier, Pat, first round, how good will it be? Because so far, uh, TV one wasn't great. Um, training one wasn't great. Uh, you know, uh, like what, where's, what is an example of a custom AI chip that on his first pass absolutely crushed it? Is there, is there one?

Patrick Moorhead: 

No, there really isn't. Gosh, I'm embarrassed I didn't bring that up. But Daniel, you're kind of the chip guy now.

Daniel Newman: 

You're more handsets and PCs. Oh, that is so true. Oh, my God. You're the guy, you're the device. I'm the SaaS guy now, right? You did finally really make that leap. I'm really glad it worked. Because all these years you were sort of chasing, I think I want to be in software. And you're like, but I'm a chip guy, you know, I'm a chip guy, hardware guy. But you're like, I want to work with software. And now finally, all the software companies are like, Pat, I really want to work with you now.

Patrick Moorhead: 

Yeah, I mean, it's very similar to my investment strategy, right? Which is just double down on investment, when stuff is going cold, and then get get out of the stuff as it's about rocket ship.

Daniel Newman: 

By the top, baby, sell the bottom you and Kathy would keep following. You know, she like she went all in on Cerberus at like 350.

Patrick Moorhead: 

Oh, I know. That's so bad. By the way, I am looking for a potential way into both SpaceX and cerebrus when they hit the pavement.

Daniel Newman: 

But yeah, it's like my 4020 foot spreads in 2028. The ones where I can buy it at like 36 bucks if it goes there. Yeah. Um, by the way, everybody might hear this and get mad about that idea. I don't really believe it'll get there. But if you know a little bit about options trading, I'm collecting premiums, um, on the idea that someone does believe it'll go there. And if it does land there, I'm going to be happy to buy it there, because I think it'll be a great deal.

Patrick Moorhead: 

I love that, Daniel. OK, let's go to our next topic. We talked about everybody's trying to get a one up on each other. And now even the frontier labs are trying to leverage supply chains. I mean, quite frankly, the OpenAI jalapeno chip. Hopefully it's not too hot and it's not good. That's essentially trying to, you know, take control of your supply chain. Now we've got Anthropic and Micron kind of locking in a multi-year deal, right? A similar pattern as Samsung and SK Onyx pre-funding Anthropic in May. I mean, Daniel, it's just this, just a bunch of circular mumbo jumbo or are these frontier labs truly trying to disconnect?

Daniel Newman: 

Can it be both? Yes. I mean, can it be both? I mean, it's, in my opinion, it's the same circular stuff that NVIDIA was doing two and three years ago now, but the ball has moved. I mean, look at it, you know, the Jim Chanos complaint, he's a famous short seller that always talks about like the companies that control the means should do better than the ones that are dependent on it. Well, guess who's dependent on Micron right now? Everybody. And everybody is dependent on these memory companies. NVIDIA is dependent on like, so like when the Neo clouds are ripping and core, we even nebulous are running and people are going, well, why isn't NVIDIA? Well, now you got micro that basically gets to, you know, be daddy over everything. So, you know, I think this is when you have the kind of cashflow they're creating, you have the kind of leverage that they have. This is where you start placing your chips on the table strategically. So. They're doing the same thing. They're basically starting to pick winners. They're aligning strategically. We'll talk about it in the earnings with all the new strategic agreements that they've set out. Much of those agreements, which have basically floors but no ceilings on much of the agreement, other pricing. I mean, people are so desperate right now for capacity and just access to supply in the future that they're willing to do these kinds of deals. So this is interesting. And I mean, this isn't going to be unique to Micron. Samsung will do this. SK will do this. Because we, you know, the constraint and, you know, we'd heard 27, 28. Our data says 2030 minimum. And it's just a lot. So, but what does it include? I mean, this is a multi-year HBM DRAM SSD, you know, supply across their data center portfolio, co-designed next-gen memory. So that's interesting, co-designing, you know, for storage architecture for AI workloads. more and more customized versus commoditized potentially here. Micron strategic investment, that's the part where everybody says it's circular. And then the, you know, Micron's going to use Claw. I bet you they already were. That's really not a, that's really not a big thing. So that's kind of the headline here. And like I said, I think everyone that either makes a chip or needs chips right now wants to become friendly. Remember the trips to Taiwan? We talked about why Jensen and Lisa are so good. because they made those trips to Taiwan and they sat down with Sisi and they, you know, and that people didn't understand that, you know, if you don't make that trip and build that relationship, you will not get the supply that you need. And people are just up sourcing this now. They have to make a trip to Taiwan, but now they got to stop in Korea on the way home. And apparently they have to make a pass through Idaho as well.

Patrick Moorhead: 

I love that, dude. I love that. Honestly, not not too much to add here. Right. And we can we're going to debate the whole memory, strategic memory, tactical, and slop. But yeah, this is going to be a fun one. No, listen. Pragmatically, and there was a recent rumor, I don't know if it's correct, that even Anthropic has a 14% FCF margin. Um, which, you know, very rarely do you, do you hear about an FCF margin, but just the fact that their cashflow positive is absolutely insane. And at a time like this, when your valuation is so high and you're actually making cash, why not? Why not try to, and you're not disintermediating people necessarily. You're, you're, um, just trying to take more control. All right, let's get into our next topic here. SpaceX signs a $6.3 billion compute deal with Reflection AI, $150 million per month. So it's funny, some people are saying that SpaceX is now the largest commercial AI infrastructure provider with $80 billion in revenue. It's funny, if you combine the 300 megawatt Colossus One lease at $1 billion per month, you got Google at $920 per month, now Reflection, SpaceX sitting on $80 billion in contracted on revenue and that alone is $150 million per month is larger than most public AI startups entire revenue base. So this is absolutely crazy. This just came out of left field. You know, Danny, you can't think that the, that SpaceX or XAI's theory was we're gonna buy a boatload of GPUs and then become a hyperscaler. I think the fact that XAI has not hit, hasn't hit for developers, it hasn't hit for consumers, and hasn't hit for really, for business users, is they were just sitting on a pot of gold. Maybe at the time when they bought it, it was 10, but through lack of use, it ended up being absolute, gold. So I mean, SpaceX kind of figured out how to be AWS without even shipping a console. And the backlog is is surprisingly bigger than than most clouds.

Daniel Newman: 

Yeah, I mean, look, I'm like so torn on SpaceX because I'm like such a fan over like the next 10 years. But I'm such a just I can't like and I'm you know, I'm the rocket ships guy. But like, I can't make this make sense. You got a $5 billion rocket business, you know, that's 85% of the market that's growing its single digit percentage. You've got a basically satellite communications business, which is interesting and it could disintermediate a lot of mobile connectivity businesses potentially. I read something today that maybe they're going to come out with something to compete directly with T-Mobile, Verizon, like a mobile service. Super interesting for phone. But that entire industry together is like half a trillion bucks, maybe like three quarters max. Then they got an AI Cloud business, which again is starting to look more like Nebbius. then it looks like anthropic, right? I mean, it's basically become a massive, and to its credit, like great growth. I did call this out, like Google owns 7% of SpaceX, so doing that deal right ahead of the IPO probably wasn't accidental. But look, all that capacity that they have, that they don't feel the need to reserve it for what they're building is interesting to me.

Patrick Moorhead: 

It's just interesting to me, like, well, you've almost, they're almost planning, um, XAI to be, to fail.

Daniel Newman: 

Well, at least as a real frontier lab, and maybe it just becomes a massive infrastructure play and that's okay, but that doesn't trade it. It's a different multiple. It's a different business. It's a different promise. So that's, what's really interesting to me is like, is it. What is XAI going to be? Is it, like I said, a new core week? Is it just a massive compute deployment? And what kind of valuation does that deserve, even if it's the biggest versus a full stack, which is really what I think the sale is, is that they're more like Google, right? They are. models, frameworks, development, platforms, and of course, infrastructure all in one shop. And of course, they don't even have their own silicon yet. So they're still dependent on, you know, others. And we do know Elon's building a TerraFab. So I mean, that could change in the future. So anyways, all the things, all the things, but this one's interesting, but I mean, look, at least they're not sitting there empty. I mean, God, you'd think in this current economy, how shameful it would be to have that much AI compute and not have anybody using it. It'd be wild.

Patrick Moorhead: 

Yeah. And let's jump into the next, the final flip topic, essentially, sorry.

Daniel Newman: 

Decode, right? Are we going to flip?

Patrick Moorhead: 

Sorry. No, no, we're doing the decode. The interesting thing, you don't hear much about Japan and AI, but Japan's Sakana AI shipped Fugu Plus plus Fugu Ultra. This is not a big, huge base model. This is more of an agentic orchestrator, but it is interesting. If nothing else, you've got a Japanese sovereign play.

Daniel Newman: 

Yeah, I mean, this one was interesting. I don't pay a ton of attention to what's going on in Japan, but the way it was sort of pitched was that this thing has some agentic capabilities that outperformed the kind of top available frontier models and even potentially were on par with some of the now unavailable fable mythos models. Um, it's more MOE, right? This is more distillation MOE than it is a true model. And I think it was your son that came over the top and called it lame in my tweet and said, there's doesn't even have like a harness or something. He was, he was telling me like why it's not cool. Um, right. Yeah. But anyways, I mean- I ignore him. What does he know? What does that kid know? But probably one of the most interesting things is they try to, and this is another deep seek thought thing too, where they're trying to sell it as, oh, it's meaningfully cheaper. There was another story about GLM 5.2 this week, but they love these stories that it's cheaper, input token, output token, it costs less. But look, I think what's interesting is increasingly models themselves are not moats. I think that's the interesting part. It's got to be something more. It's the full stack. It's the harness. It's the tooling. It's the connectivity. It's the looping. It's the agentic. It's the total compute capacity availability. Because, again, as a whole, the open source community is doing a good job, and less to speak specifically to Japan and more to just speak generally to even what's going on in China, is they are building really good distillations of the top models. they probably are stealing a lot of the IP because that's how they do it. But like, the mode itself has got to be more. And so we're, I think we'll just kind of continue to hear this stuff. New models, we'll probably hear from the Middle East, they're going to do this too. Or these new locations are putting out new models that have attributes that are on par, if not better in some cases than some of the more popular frontier lines.

Patrick Moorhead: 

Yeah. I mean, the way that I look at this is, is it's kind of like open router. I mean, people can correct me on social media, but it just, because really what they're talking about doing is taking different parts of the workload and applying the right model. Ironically, it's like perplexity computer, which is, Hey, I'm going to offer a lot of different models and I'm going to route you to the right, to the right thing. This is more of the developers version. Um, of that versus the vibe coders like me. But I agree with you, Daniel, we are going to see stuff like this. The thing about Sakana AI is it primarily uses, you know, a lot of the different, you know, it has its own models, but it also is doing a multi-agent routing across all of this. And the Fable claim is very similar to the OpenRouter claim is, hey, I can take 4.8 plus 5.5, break up the workload, and get the same response as Fable. I like the innovation. That's why I really like this one. So, hey, let's move to the flip here, Daniel. You know, all this talk about memory and, you know, triopolies, not monopolies. I use the term paybacks on X in my X posting, but hey.

Daniel Newman: 

Don't cry on me, Tim Cook. Yeah. You abused us at your top and our bottom.

Patrick Moorhead: 

Exactly. So the question is, is the era of memory a commodity over, or has the beginning of memory as a strategic AI requirement, or are we here? So let's flip the coin. I saw a big Dan there. He got this. So Daniel, you are saying the era of memory as a commodity is over.

Daniel Newman: 

It is over. This is different. Period, period, period, period, rocket ship. Memory is strategic infrastructure, Pat. Look, the commodity cycle didn't get extended. It got replaced. Memory moved from critical path of the AI build-out, and now it is the rules, now the rules that have governed it for 30 years, the boom and bust cycles of memory, unfortunately, my friend, no longer apply. And look, look no further than the 16 multi-year agreements, 22 billion committed volume, allocated book through 2027. Commodities don't get bought on multi-year take or pay contracts. Infrastructure does. The buyers are revealing what they believe. And supply is scarce, strategic, and it's worth locking in years in advance. And margins. Margins are the other thing. They tell you you have a moat. Margins aren't going down. They aren't even stabilizing. Margins are going up. 84.9 percent. That's higher than NVIDIA. A true commodity can't hold that, you know, because what happens is capital floods in, they build more capacity, and then it crushes it. But the problem is, is this an oligopoly, Pat? It's a triopoly, as you called it. We have yield problems, stacking problems, packaging challenges, and that only three companies can solve this and no one else can. And that right now is a technology barrier, not a pricing accident. And then the biggest thing is the demand drivers change under the asset. You know, prior cycles were PCs, phone, servers, but a lot of it was consumer discretionary. It was sentiment driven, pretty elastic. This cycle runs on AI compute. HBM is the binding constraint on every accelerator chip. Memory is no longer riding this cycle. It's gating it. So supply can't physically respond to the old timeline. Leading edge HBM capacity takes years to stand up. Management puts supply times past 2027. We have it past 2030. When supply can't answer demand for years, which by the way, demand has been underestimated every part of this cycle, guess what? The well-known memory cycle has been disabled for the duration. The anthropic agreements are just another exclamation point here of how strategic memory has become. Memory now controls everything. Supply constraint, technology modem, demand inelastic, sold on long-term contract, memory now checks every box of strategic. This print isn't memory getting expensive, it's memory getting repriced as infrastructure.

Patrick Moorhead: 

Daniel, I've lived through nine memory cycles. I worked for manufacturers for 21 years. I have crawled through memory factories, PCA, PCB, chip flipping. I mean, you name it. And so first by definition, long-term agreements and these new strategic customer agreements, LOL, very much signal that you're a commodity just in a current era of strength. That's the way that I read those. Nothing more than, I need more. and I can raise prices on you and I'm going to force you into making long-term purchase and at a certain price agreements. That is a commodity to the max. The second thing is that architecturally, let's look at what's a commodity and what's not. In other words, what's industry standard and what's not. What defines either pins or micro bumps is an organization called Jetik. And let me go through the data center and PC stuff that is Jetik compliant, meaning anybody can make it. DDR5, QDIM, MRDIM, HBM3, HBM3e, HBM4, LPDDR5, 5X, LPDDR6, CAM2, LPCAM2, GDDR6, GDDR7. So these are all things that are essentially, I'll call them commodity at the pin. And the only reason I brought that up is there were some people talking about, that on X. Now where it's going is like we talked about with Qualcomm with HBC. There's nothing standard about that LPDDR that sits underneath the hood and each custom HBM4 is obviously not going to be standard. It's going to be custom and that's the way that I would view is if it's strategic. I think memory is headed that direction for HBM, but that's pretty much. That's pretty much it. One final thing here is new supply is coming, right? And I brought this up on Yahoo Finance. China DDR5 production ramps in the second half of 26. You have Lenovo already using it. You have HP and Dell who are qualifying it. We will see, Daniel, if it's strategic. Once China comes online, maybe the U.S. government comes in to save it. That would be so dumb. But you've got CMXT coming on and I don't think this is a deep seek moment at all. I think this is real. I can't say if it's high quality memory yet because it's stuff's being qualified, but. I do believe that at the end of the day, memory prices will get back to more than normal. Final point, another final point, on these SCAs, a little fact check on there out there, it's not cash flow. Unlike TSMC that takes pre-buys on CapEx, these customer deposits are not cash flow. This is vendor financing embedded in these agreements. It flatters the optics and how it looks, but it's not the same as a durable free cash flow. I'll rest my case there.

Daniel Newman: 

I fell asleep. What happened?

Patrick Moorhead: 

So much action.

Daniel Newman: 

I'm going to have to tweet that you're a big time China bull. That is a memory bull for China. It's like all in China. I love it. I love it.

Patrick Moorhead: 

All right. Good conversation. Let's jump into bulls and bears.

Daniel Newman: 

All right, Daniel. What do you really think? Is it a commodity?

Patrick Moorhead: 

Yes. I do.

Daniel Newman: 

Okay.

Patrick Moorhead: 

Because there's so many standards around it. If you look at all of the other, um, um, like you look at a GPU view, like between NVIDIA and, and, and, and NVIDIA, NVIDIA and AMD. And it's like, those are so fricking different. There are six uniquely different accelerator architectures out there. And like, that's not commodity because they're different. When you're building to a JEDEC standard, it is by default a commodity. You might be cheaper, you might be faster, you may have built more CAPEX, but yeah, maybe we just differ on the way we look at strategic. Okay, now let's really get into bulls and bears.

Daniel Newman: 

I don't think we had to do that again, but I love the ding, ding, ding, so we can do it twice.

Patrick Moorhead: 

I asked for it and I got it. So back off.

Daniel Newman: 

You got it.

Patrick Moorhead: 

So arguably one of the most successful companies in the history of technology, NVIDIA is actually going out to get financing, $25 billion in investment grade bonds. Daniel, why does NVIDIA need it? And this is a good sign or a bad sign?

Daniel Newman: 

They don't need it. I'm going to be really clear here. This is raising money when it's cheap, available, and when you're in the cash flow situation they're in, never hurts. When your balance sheet is gold, when investors are 3, 4x oversubscribing this thing, they're not raising it to do things like the hyperscalers are. They're literally just putting a monster pile of cash in reserve. giving them ultimate flexibility in the long run. So this is a totally different situation than Meta or Google or any of these other companies raising. And like I said, best time to raise, best time to go get money is when you don't need it. That's all I got to say about that. There's no red flag here.

Patrick Moorhead: 

I can't argue with anything that you've said. I mean, you know, when a company with negative debt, um, is, is the one rushing to borrow, um, you know, and you don't need it. Yeah, you're right. It's a perfect, but then again, why would you do it? Do you do it? Do you buy it? Do you bring it to do more buybacks? Like, why do you, what are you going to sit on the cash for? What are you going to do?

Daniel Newman: 

Maybe they're concerned about rate increases, less, less, uh, you know, accessible cash longterm. Um, there's, like I said, you know, you're just piling on a balance sheet right now. I mean, there is some concerns about rates going up. So, I mean, but, but really, I mean, with the type of cash they're bringing in quarter to quarter, they certainly didn't need it.

Patrick Moorhead: 

Yeah.

Daniel Newman: 

Maybe it's just a flex, like, haha, we can raise and no one can challenge us. Of course, their stock performing like absolute dog shit. So the market clearly does not love Nvidia's long-term, which is still really hard for me to understand.

Patrick Moorhead: 

Yeah. I've seen, um, even the most ardent, um, Nvidia, uh, stock supporters call it dead money. Right. Like it's just not going anywhere.

Daniel Newman: 

to one

Patrick Moorhead: 

All right, Daniel. I mean, with that 10X forward PE before the big blow up, I mean, my God, the only reason that it doesn't even go up even higher is because nobody believes that it's memory is strategic and the company isn't investing enough in CapEx to make a difference in the future. So, but yeah, I mean, listen, the shiny, shiny object has to change. And that's especially true with the retail stock market. Hey, let's go to the next topic, Daniel. Oh, my gosh. The hundred year flood scenario. Memory prices going up. Apple fell five points based on MacBook price hikes. Tim Cook says it's unsustainable, right? No, and really, really set that off. And you even had a chief revenue officer at Micron in a coded method, essentially say what I've been saying, which is it's paybacks. And, you know, going from negative 80% gross margins and your buyers are asking you to lower prices even more, you know, you can't invest in the CapEx. And here we are with what was it, 87% gross margin, Daniel? Micron ended with 85.9.

Daniel Newman: 

It depends on constant currencies and everything. But yeah, it's in the mid 80s now. And it's up from 81. And, you know, Apple, the backstory, well, you need your topic, right? So go. Do you have anything else on this one?

Patrick Moorhead: 

Just essentially, this is, you know, Micron telling Apple to suck it. And then you've got Apple basically, you know, blaming memory. And then you've got Bernie Sanders blaming Apple for raising this on consumers. But I do wonder if there could be a potential blowback to the memory vendors based on the consumer prices going up, just like we saw with energy prices going up with, uh, with, uh, some of the, some of the data. Yeah.

Daniel Newman: 

Well, listen, this, uh, the market fell fast when this announcement came out and it was expected, but it happened. And remember the whole rally got momentarily wiped out and then, you know, only micron was up by the end of the day, a lot of AI because, um, You know, the market for the first time saw who's going to pay for all this, and it's going to be the consumers. You know, when the consumer starts to pay, that's when you start to get strained in the economy. You know, paying $150, $200 more for that phone, that's a lot. Sanders' point, which he's an idiot, but his point is that Apple still makes a ton of money, even at these higher costs. The problem is, is what he's not thinking about is which shareholders are going to be like, yeah, sure, take eat the cost and, you know, like go ahead and make less money next year. Apple will still want to be in the stock like they can't do that. They're absolutely have to continue to show growth. The market is ruthless. It is absolutely unapologetically ruthless. So Apple has no choice but to raise the prices. And then you got to see what kind of inelasticity the. The pricing on Apple and iPhones and MacBooks really, really have. So anyways, that's kind of my read on this one. But like, the backstory is Apple absolutely took it to Micron when Micron was weak. They made a terrible deal that nearly almost crushed Micron. So what I'm saying is like, I'm sure Sanjay and Samit and the team are kind of laughing into the bank right now, because Apple can certainly afford it.

Patrick Moorhead: 

All right, Daniel, let's go into your favorite company and your favorite topic. Micron blew the door.

Daniel Newman: 

I don't even know that we need to do it, do we? I mean, I guess we can just just hit the headlines, right? Um, Largest beat in company history, $41.46 billion, 346%. Doesn't this remind you of the early Nvidia prints? Doesn't this really remind you of the early Nvidia prints? Crushing a $35.69 billion consensus, $25.11 per share earnings, 1,215% year-over-year growth. beating 2049 expectation, 84.9% record margins, 10% higher than NVIDIA, by the way, a $50 billion midpoint guide versus a $43 billion consensus. This thing absolutely ripped. They had the 16 multi-year agreements, $22 billion in customer contracts, The agreements were all from what they explained like 100 plus billion dollar agreements over their lifetimes. I think 14 of 16 at least were for sure. And again. only somewhere around a third of the contract had any sort of ceiling on price. I think it was maybe up to 40%. So meaning most of these contracts, it's all about just securing supply they need. They don't even have a cost. And that's some of the things that makes it feel uniquely asymmetrical long-term for Micron is that historically entering a long-term agreement should have had some additional benefit beyond just getting capacity. But at this point, it doesn't seem to. That's it. I mean, we've talked so much about it. I don't really have anything else to say. It was unfreaking believable. But actually at the same time, it was what we expected.

Patrick Moorhead: 

Yeah, it's interesting, Daniel. It was an amazing beat. But what's amazing to me is how they did it. And it was 95% price increases. They had no unit increases across the line. So essentially, they gouged their customers. you know, in its paybacks, like, like I've said before, and, you know, it goes both ways. And the buyers in memory, the OEMs and the ODMs are, are now seeing the, the ascend. of that. So it's not sustainable without these SCAs, but this is how you absolutely mentally turn this into a commodity. Let's move to an interesting one. You've got Cerebris that had their first earnings since they went public. Doubled revenue year over year. Their guide Um, ended up, excuse me, they beat on revenue. They missed on EPS. Uh, they beat on, on revenue, but, uh, really had a huge sell off on, on the gross gross margin, uh, deterioration. And listen, I just want to say that I, I'd love for Cerberus to do well as a company because they have a novel approach and, and the world needs, uh, as much competition as, as the market will allow, but listen, Growth stalled sequentially, right? Core revenue was $191 million, up 12%. The Q2 guide was $194 million, essentially flat. Margins are headed the wrong way. Core gross margins were 47%, going to 36% to 38%, and 38% to 41% for the year. Um, it's it's that that's tough if you're a public company and you're not dominating, uh, somewhere profitability is deteriorating as well. Operating margins went to around 2%, uh, to a guided, um, minus, sorry, minus two to minus 30 to minus 32%. Um, That's kind of big. Concentration moved, right? It went from Core 42 and G42, that was 86% of 25 revenue to OpenAI, who lent Cerebrus a billion dollars and gets paid quarterly in warrants. They're kind of trading concentration risk between that. And then finally, On performance, Fastest AI is no longer uncontested. You've got Grok bringing up some amazing numbers. You've got TPU8i bringing that up. You've got Tence Torrent putting up some pretty beefy numbers. So again, I'd love to see the company do well. I read it as tough earnings.

Daniel Newman: 

Yeah, I mean, look, the this was one that just ripped absolutely on the idea that AI is just has unfettered demand for anything that can be built. There's still a lot of questions about this company, about their product, about utilization. It's got some interesting, another near-memory sort of idea for strong inference. Very little in the wild right now, so there's just a lot to be seen here. But the initial RIP was typical IPO nonsense. And now again, you know, anytime Cathie Wood buys at the top, that's, that's a, that's become the Jim Cramer sell signal for me at this point. But look, I mean, they've got a bear, a bull case in open AI. If they can produce and succeed, that'll be a good, good case for them. But the the margins compressing is is something to be worried about at this point, but it feels like when it feels like margins are going up, but I imagine some of that sits in memory for them too.

Patrick Moorhead: 

Yeah. Cathie Wood is down, uh, 52% on her.

Daniel Newman: 

I don't even know how she gets, I don't know how she keeps raising money.

Patrick Moorhead: 

She made about a load of money and in a prior, prior boom cycle.

Daniel Newman: 

And you know, she made a lot of money for how long before people are like, okay, I'm not going to give you any more money to invest.

Patrick Moorhead: 

I don't know if you watch CNBC this morning, but I'm trying to remember the name of the gentleman who came on and Uh, he was interviewed for an hour on, uh, on, on why you should sell. And he made his name, um, basically during the dot bomb. Right. And that was the, the only call he had made, uh, kind of, kind of since then. Um, and who's the guy that made the big short call? Michael Berry. Yeah. He's getting buried on, um, on a lot of his, his calls right now, but yeah, it's interesting. Yeah. All right, guys. Great show. Thanks for sticking in there. Appreciate you joining. I hope you guys had a great weekend. This will be coming out on Monday. Hit that subscribe button. Be part of our community. We'd love to have you. And, you know, get on X and tell Daniel and I where we're off or where we did victory laps. Appreciate you and take care.