Загрузка видео...

Не удалось загрузить видео

На главную

Dylan Patel says the memory shortage is not a normal cycle "Memory capacity is only growing 20, 30% a year for the next three years. And yet, demand is doubling, is doubling...memory prices are going to keep soaring." "Our point there was memory isn't a shortage, and this is...

firesidealpha's profile picture

Fireside Alpha

21,511 subscribers

140,650 просмотров • 3 месяцев назад •via X (Twitter)

Наука и технологииНовости и политика
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 6

Фото профиля Dean Marantis🇺🇸🇬🇷
Dean Marantis🇺🇸🇬🇷3 месяцев назад

What have I been saying about increase capacity and continued high memory prices? No one, other than me. has talked about that until now! If that news starts to hit mainstream stream media, you can forget about ever buying Micron cheaper than it is today. It will absolutely skyrocket! And BTW, Dylan Patel is a genius and the baddest dude there is on semiconductors! Nobody better than him! Let the media start talking about increase capacity and increase in memory prices for years to come and we will see Micron at $5000 a share way before anyone could believe it. It comes down to simple math again! And if Wall Street ever starts to believe the math will last, look out! Yeehaw! LFG!

Фото профиля Dental Biz Wiz
Dental Biz Wiz3 месяцев назад

Tomorrow he’ll write a piece for his high price subs saying it’s a bubble and get out asap 🤡

Фото профиля Pregory McRonald III née Citadel (in memoriam)
Pregory McRonald III née Citadel (in memoriam)3 месяцев назад

“We’re still not at 85% gross margins.” Didn’t micron just report 86% GM a couple of weeks ago?

Фото профиля Gabriel Khoo
Gabriel Khoo3 месяцев назад

Can anyone share me memory demand growing 3 4x p.a.? Higher than others?

Фото профиля Event Driven Edward
Event Driven Edward3 месяцев назад

Dylan Patel is a dweeb

Фото профиля CopperSilver
CopperSilver3 месяцев назад

@grok when did Dylan Patel said these things and this interview was conducted?

Похожие видео

Dylan Patel says memory gross margins are headed to 90% and then at some point will head back down to the 70s or even lower. "Memory companies, they're in a commodity market." "They let the spot market and contract market sort of supply-demand balance really adjust pricing." "And so you see these two, three axes in pricing, and someday you'll see pricing halve." "Because memory necessarily doesn't deserve a margin of 85%, which is where it's headed to. We're still not at 85, 90% gross margins for memory, but we'll get there." "And then at some point from there, it'll also halve back down to like 70s or maybe even lower. And so we'll see this oscillation in memory."
0:29

Dylan Patel says memory gross margins are headed to 90% and then at some point will head back down to the 70s or even lower. "Memory companies, they're in a commodity market." "They let the spot market and contract market sort of supply-demand balance really adjust pricing." "And so you see these two, three axes in pricing, and someday you'll see pricing halve." "Because memory necessarily doesn't deserve a margin of 85%, which is where it's headed to. We're still not at 85, 90% gross margins for memory, but we'll get there." "And then at some point from there, it'll also halve back down to like 70s or maybe even lower. And so we'll see this oscillation in memory."

Fireside Alpha

17,338 просмотров • 3 месяцев назад

SK Hynix recently reached a $1 trillion market cap. SanDisk started the year at $35B and is now worth $230B. Dylan (Dylan Patel) on why memory prices will still double or triple from here: "People are like, the memory story is overplayed. No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing." Publish date: April 23, 2026
1:59

SK Hynix recently reached a $1 trillion market cap. SanDisk started the year at $35B and is now worth $230B. Dylan (Dylan Patel) on why memory prices will still double or triple from here: "People are like, the memory story is overplayed. No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing." Publish date: April 23, 2026

Invest Like the Best

105,321 просмотров • 3 месяцев назад

Dylan on why memory prices will double again: "Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM, but whatever. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. People are like, "oh, the memory story is overplayed." No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing."
2:17

Dylan on why memory prices will double again: "Memory can only grow capacity low double digit percentages a year. 20-30% a year, even less for NAND, a little bit higher for DRAM, but whatever. Even though the demand signal was very strong at the end of 2025, the memory companies immediately started reacting. None of that incremental capacity really gets here until 2028, even if they wanted to build as fast as possible. So the result is memory prices have gone through the roof. They're going to double and triple again. DRAM, especially. People are like, "oh, the memory story is overplayed." No, you don't get it. DRAM will double or triple from here still, because that's how much capacity is required. And they have to steal capacity from somewhere else. And the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher pricing."

Patrick OShaughnessy

189,478 просмотров • 6 месяцев назад

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.
1:09

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

Karl Mehta

25,716 просмотров • 4 месяцев назад

🚨 WHAT IF THE MEMORY SHORTAGE WAS MANUFACTURED? Samsung, SK Hynix, and Micron are being sued for allegedly engineering the DRAM shortage on purpose. The lawsuit claims they used the AI boom as cover to quietly cut normal memory supply. DRAM prices are up 500 to 700%. The damage is now showing up in iPhone and Mac prices. The makers say it's innocent: AI buyers showed up with huge money for HBM. But here's the bigger question. Memory stocks are priced for endless AI demand. If a court rules the scarcity was manufactured, how much of that demand was ever real?
0:37

🚨 WHAT IF THE MEMORY SHORTAGE WAS MANUFACTURED? Samsung, SK Hynix, and Micron are being sued for allegedly engineering the DRAM shortage on purpose. The lawsuit claims they used the AI boom as cover to quietly cut normal memory supply. DRAM prices are up 500 to 700%. The damage is now showing up in iPhone and Mac prices. The makers say it's innocent: AI buyers showed up with huge money for HBM. But here's the bigger question. Memory stocks are priced for endless AI demand. If a court rules the scarcity was manufactured, how much of that demand was ever real?

CryptoGoos

32,675 просмотров • 4 месяцев назад

Jensen Huang: “We need memory for… HBM memory for performance. We need LPDDR for low-power memory.” Reporter: Is memory constraint an issue for NVIDIA this year? Jensen Huang: “The entire supply chain is challenging this year because demand is so much more. Supply has been growing 100% every year, but demand is going faster than that. We are going to have a very good year.” We are entering a Memory Supercycle $MU
0:50

Jensen Huang: “We need memory for… HBM memory for performance. We need LPDDR for low-power memory.” Reporter: Is memory constraint an issue for NVIDIA this year? Jensen Huang: “The entire supply chain is challenging this year because demand is so much more. Supply has been growing 100% every year, but demand is going faster than that. We are going to have a very good year.” We are entering a Memory Supercycle $MU

NIK

217,217 просмотров • 9 месяцев назад

$MU CEO Sanjay Mehrotra said Micron can only supply ~60% of what key customers are requesting as AI demand creates an unprecedented memory shortage. Every wafer shifted into HBM can cost ~3x the standard DRAM output and demand keeps rising because inference, agents, robotics and autonomous systems are all memory-bandwidth-bound. Memory fab capacity takes three to five years to build so the shortage Mehrotra is describing today could define the supply curve for the rest of the decade.
0:28

$MU CEO Sanjay Mehrotra said Micron can only supply ~60% of what key customers are requesting as AI demand creates an unprecedented memory shortage. Every wafer shifted into HBM can cost ~3x the standard DRAM output and demand keeps rising because inference, agents, robotics and autonomous systems are all memory-bandwidth-bound. Memory fab capacity takes three to five years to build so the shortage Mehrotra is describing today could define the supply curve for the rest of the decade.

Shay Boloor

125,697 просмотров • 5 месяцев назад

Sparse attention fixes memory bandwidth, not memory capacity. “The whole idea of HiCache is trying to offload KV cache from the HBM to a lower tier, higher capacity but lower bandwidth memory, and only load the most relevant set of tokens during computation.” “Sparse attention doesn’t mitigate the memory capacity bottleneck. It’s a technique that helps a lot with memory bandwidth.” “During the sparse attention computation, you still need to select the tokens. So you still have to keep all the tokens in context, and you cannot discard them. At some point, it still has to be loaded into HBM.” “That’s where HiSparse becomes useful, because it can apply the typical caching rules so that you could load the most relevant parts into HBM.”
1:43

Sparse attention fixes memory bandwidth, not memory capacity. “The whole idea of HiCache is trying to offload KV cache from the HBM to a lower tier, higher capacity but lower bandwidth memory, and only load the most relevant set of tokens during computation.” “Sparse attention doesn’t mitigate the memory capacity bottleneck. It’s a technique that helps a lot with memory bandwidth.” “During the sparse attention computation, you still need to select the tokens. So you still have to keep all the tokens in context, and you cannot discard them. At some point, it still has to be loaded into HBM.” “That’s where HiSparse becomes useful, because it can apply the typical caching rules so that you could load the most relevant parts into HBM.”

SemiAnalysis

26,102 просмотров • 21 дней назад

𝐒𝐂𝐀𝐑𝐘: For the first time in 30 years, Nvidia will not release a gaming GPU this year due to global memory chip shortage.
0:20

𝐒𝐂𝐀𝐑𝐘: For the first time in 30 years, Nvidia will not release a gaming GPU this year due to global memory chip shortage.

Coinvo

1,001,531 просмотров • 4 месяцев назад

🚨 HOLY SH*T IT'S CONFIRMED... $MU IS GOING TO THE MOON Data centers are set to triple by 2030 due to the immense spending boom... Do you have any idea what the core part of data centers is? MEMORY. Memory which $MU leads. But it's not only stocks like Micron, it's also things like DRAM and SanDisk. I've said it for months... memory will lead the next phase. And here we are.
0:34

🚨 HOLY SH*T IT'S CONFIRMED... $MU IS GOING TO THE MOON Data centers are set to triple by 2030 due to the immense spending boom... Do you have any idea what the core part of data centers is? MEMORY. Memory which $MU leads. But it's not only stocks like Micron, it's also things like DRAM and SanDisk. I've said it for months... memory will lead the next phase. And here we are.

Coinvo Trading

36,743 просмотров • 2 месяцев назад

SK Hynix's Hoshik Kim admits high bandwidth memory "is not the answer" to the memory-wall problem, and SK is working on different solutions to solve the bottleneck. "No, actually, I kind of agree with Pat. So HBM is not the answer." [SK Hynix is admitting that HBM is a bad memory?] "Nothing is a bad memory. It's a good memory, but it's not the final answer. So actually, HBM will not solve the memory-wall problem. Memory-wall problem is an inherent AI problem, which you cannot avoid." "So we try our best to provide higher bandwidth with this memory, with HBM technology even though it has some limitation, as Pat already mentioned, with thermal, IOs, cost, a lot of stuff. "But that's the only thing we got right now to help ease this memory-wall problem, memory-bottleneck problem. But at the same time, we are working in different directions to solve this memory-wall problem with different solutions."
0:51

SK Hynix's Hoshik Kim admits high bandwidth memory "is not the answer" to the memory-wall problem, and SK is working on different solutions to solve the bottleneck. "No, actually, I kind of agree with Pat. So HBM is not the answer." [SK Hynix is admitting that HBM is a bad memory?] "Nothing is a bad memory. It's a good memory, but it's not the final answer. So actually, HBM will not solve the memory-wall problem. Memory-wall problem is an inherent AI problem, which you cannot avoid." "So we try our best to provide higher bandwidth with this memory, with HBM technology even though it has some limitation, as Pat already mentioned, with thermal, IOs, cost, a lot of stuff. "But that's the only thing we got right now to help ease this memory-wall problem, memory-bottleneck problem. But at the same time, we are working in different directions to solve this memory-wall problem with different solutions."

Fireside Alpha

161,722 просмотров • 3 месяцев назад

Ben Thompson says the memory makers are Iran, and by making the Strait of Hormuz mistake are inviting the whole industry to build around them "The other thing, the risk they run, is Apple. Apple's lobbying to get Chinese memory, right?" "And what is the number one focus of algorithmic changes? How can we use less memory?" "I think the memory makers probably screw themselves in the long run by creating such a massive target on their back." "I've analogized memory makers to Iran. The issue with the Strait of Hormuz is it's very effective. It's more effective if you don't use it, cuz then it's always hanging out there as something you could do. Now they did it. Turns out it worked." "But the UAE and Saudi Arabia, they're going to build pipelines. They're going to build new ports. They're not going to let this happen again." "It's very painful right now. But say Iran wants to close the Strait of Hormuz in 2035. It's not going to have any effect, because it will have been built around." "My concern for the memory makers is they might have done the same thing. No one's going to let themselves get in this situation again as far as memory goes."
0:58

Ben Thompson says the memory makers are Iran, and by making the Strait of Hormuz mistake are inviting the whole industry to build around them "The other thing, the risk they run, is Apple. Apple's lobbying to get Chinese memory, right?" "And what is the number one focus of algorithmic changes? How can we use less memory?" "I think the memory makers probably screw themselves in the long run by creating such a massive target on their back." "I've analogized memory makers to Iran. The issue with the Strait of Hormuz is it's very effective. It's more effective if you don't use it, cuz then it's always hanging out there as something you could do. Now they did it. Turns out it worked." "But the UAE and Saudi Arabia, they're going to build pipelines. They're going to build new ports. They're not going to let this happen again." "It's very painful right now. But say Iran wants to close the Strait of Hormuz in 2035. It's not going to have any effect, because it will have been built around." "My concern for the memory makers is they might have done the same thing. No one's going to let themselves get in this situation again as far as memory goes."

Fireside Alpha

205,967 просмотров • 2 месяцев назад

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.
0:58

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.

Ricardo

595,131 просмотров • 9 месяцев назад

"Everyone's making fun of these Koreans for being long memory stocks. But we're talking single-digit P/E multiples. It's probably going to last 2-3 more years. Triple digit growth." — tae kim "Layer that onto the fact that 4 years ago, all these memory companies saw their revenue get cut in half. So they didn't expand capacity. And it takes 3-4 years to expand capacity." "We're going to see mega pricing power. We haven't seen anything yet. These stocks are going to keep going higher, and their revenue rates are going to be astronomical."
1:32

"Everyone's making fun of these Koreans for being long memory stocks. But we're talking single-digit P/E multiples. It's probably going to last 2-3 more years. Triple digit growth." — tae kim "Layer that onto the fact that 4 years ago, all these memory companies saw their revenue get cut in half. So they didn't expand capacity. And it takes 3-4 years to expand capacity." "We're going to see mega pricing power. We haven't seen anything yet. These stocks are going to keep going higher, and their revenue rates are going to be astronomical."

TBPN

156,362 просмотров • 5 месяцев назад

Gavin Baker, CIO of Atreides Management made one of the most important and nuanced calls on memory stocks in recent months (Save this). His argument is that based on every memory cycle of the last 25 years, the setup today, prices elevated, sentiment high, supply ramping is textbook time to sell but he adds a critical exception. The one cycle in modern memory history where selling was catastrophically wrong was the mid-1990s, which Baker calls the last true capacity cycle in memory. In that cycle, demand was structurally exploding as the internet era required entirely new computing infrastructure to be built from scratch, and memory had to scale with it in a way that had never happened before. His point is that AI may be that same kind of cycle and not a normal boom bust but a once in a generation capacity buildout where the underlying demand is structural, not cyclical. The reason this argument holds weight is the fundamental shift in what memory is in the AI era. Traditional DRAM was a pure commodity, identical specs, interchangeable suppliers, price determined entirely by supply and demand swings. HBM is the opposite because it is custom engineered to fit a specific customer's chip, co-designed between the memory maker and the GPU designer, with SK Hynix's Vice President literally describing it as shifting from a commodity to a customer-tailored custom business. A single Blackwell Ultra GPU now requires up to 288GB of HBM3E, a 3.6x increase over the H100 and major suppliers like SK Hynix and Micron have already sold out their entire HBM production capacity through the end of the year. Because HBM requires advanced packaging processes like CoWoS that can't be spun up overnight, the bottleneck isn't just wafer capacity but rather runs across the entire manufacturing stack. Bank of America projects the global HBM market grows 58% this year alone to $54.6 billion, and Nomura expects the broader memory sector to nearly double to $445 billion. Long Micron!
0:42

Gavin Baker, CIO of Atreides Management made one of the most important and nuanced calls on memory stocks in recent months (Save this). His argument is that based on every memory cycle of the last 25 years, the setup today, prices elevated, sentiment high, supply ramping is textbook time to sell but he adds a critical exception. The one cycle in modern memory history where selling was catastrophically wrong was the mid-1990s, which Baker calls the last true capacity cycle in memory. In that cycle, demand was structurally exploding as the internet era required entirely new computing infrastructure to be built from scratch, and memory had to scale with it in a way that had never happened before. His point is that AI may be that same kind of cycle and not a normal boom bust but a once in a generation capacity buildout where the underlying demand is structural, not cyclical. The reason this argument holds weight is the fundamental shift in what memory is in the AI era. Traditional DRAM was a pure commodity, identical specs, interchangeable suppliers, price determined entirely by supply and demand swings. HBM is the opposite because it is custom engineered to fit a specific customer's chip, co-designed between the memory maker and the GPU designer, with SK Hynix's Vice President literally describing it as shifting from a commodity to a customer-tailored custom business. A single Blackwell Ultra GPU now requires up to 288GB of HBM3E, a 3.6x increase over the H100 and major suppliers like SK Hynix and Micron have already sold out their entire HBM production capacity through the end of the year. Because HBM requires advanced packaging processes like CoWoS that can't be spun up overnight, the bottleneck isn't just wafer capacity but rather runs across the entire manufacturing stack. Bank of America projects the global HBM market grows 58% this year alone to $54.6 billion, and Nomura expects the broader memory sector to nearly double to $445 billion. Long Micron!

Milk Road AI

260,701 просмотров • 4 месяцев назад

David Einhorn says there's a big bubble in tech-sector corporate profit, because a chunk of it is just a price transfer that creates no new economic value "Right now there's a big bubble in corporate profit within the tech sector, and it's driving all of the returns and the excitement." "And you hear, I mean, Morgan Stanley's probably calculated how fast earnings growth was this quarter and so forth. But if you think about how that's being constructed, some people have talked about the mark-to-market gains and the private investments, take that out." "But think about another big source of profits, which is the capital spending boom that's happening in AI, where say memory prices have gone up five times." "If memory prices have gone up five times, it means the memory provider is selling to the hyperscaler at five times the price." "Now, no new economic value is being created. If they sold it at the previous price, just as much memory would be going back and forth, just as much compute capacity would be created. The increased price just reflects a transfer from one corporation to another." "So the hyperscaler is paying to the memory provider a higher price, and that higher price shows up as profit today for the memory provider, and it's booking 85, 90% margins on stuff that traditionally is a commodity...and that flows right on through to NASDAQ earnings." ________ For key memory-architecture lectures from the Father of HBM:
1:24

David Einhorn says there's a big bubble in tech-sector corporate profit, because a chunk of it is just a price transfer that creates no new economic value "Right now there's a big bubble in corporate profit within the tech sector, and it's driving all of the returns and the excitement." "And you hear, I mean, Morgan Stanley's probably calculated how fast earnings growth was this quarter and so forth. But if you think about how that's being constructed, some people have talked about the mark-to-market gains and the private investments, take that out." "But think about another big source of profits, which is the capital spending boom that's happening in AI, where say memory prices have gone up five times." "If memory prices have gone up five times, it means the memory provider is selling to the hyperscaler at five times the price." "Now, no new economic value is being created. If they sold it at the previous price, just as much memory would be going back and forth, just as much compute capacity would be created. The increased price just reflects a transfer from one corporation to another." "So the hyperscaler is paying to the memory provider a higher price, and that higher price shows up as profit today for the memory provider, and it's booking 85, 90% margins on stuff that traditionally is a commodity...and that flows right on through to NASDAQ earnings." ________ For key memory-architecture lectures from the Father of HBM:

Fireside Alpha

84,511 просмотров • 1 месяц назад

Gavin Baker, CIO of Atreides Management made one of the most important and nuanced calls on memory stocks in recent months (Save this). His argument is that based on every memory cycle of the last 25 years, the setup today, prices elevated, sentiment high, supply ramping is textbook time to sell but he adds a critical exception. The one cycle in modern memory history where selling was catastrophically wrong was the mid-1990s, which Gavin Baker calls the last true capacity cycle in memory. In that cycle, demand was structurally exploding as the internet era required entirely new computing infrastructure to be built from scratch, and memory had to scale with it in a way that had never happened before. His point is that AI may be that same kind of cycle and not a normal boom bust but a once in a generation capacity buildout where the underlying demand is structural, not cyclical. The reason this argument holds weight is the fundamental shift in what memory is in the AI era. Traditional DRAM was a pure commodity, identical specs, interchangeable suppliers, price determined entirely by supply and demand swings. HBM is the opposite because it is custom engineered to fit a specific customer's chip, co-designed between the memory maker and the GPU designer, with SK Hynix's Vice President literally describing it as shifting from a commodity to a customer-tailored custom business. A single Blackwell Ultra GPU now requires up to 288GB of HBM3E, a 3.6x increase over the H100 and major suppliers like SK Hynix and Micron have already sold out their entire HBM production capacity through the end of the year. Because HBM requires advanced packaging processes like CoWoS that can't be spun up overnight, the bottleneck isn't just wafer capacity but rather runs across the entire manufacturing stack. Bank of America projects the global HBM market grows 58% this year alone to $54.6 billion, and Nomura expects the broader memory sector to nearly double to $445 billion. This is exactly why we’re still tracking memory so closely at Milk Road. HBM is becoming less of a commodity and more of a critical custom component for AI, and we think that changes how this cycle should be valued. If you want to see what we’re actually buying and trading around this theme, come join us for just $1 using the link:
0:42

Gavin Baker, CIO of Atreides Management made one of the most important and nuanced calls on memory stocks in recent months (Save this). His argument is that based on every memory cycle of the last 25 years, the setup today, prices elevated, sentiment high, supply ramping is textbook time to sell but he adds a critical exception. The one cycle in modern memory history where selling was catastrophically wrong was the mid-1990s, which Gavin Baker calls the last true capacity cycle in memory. In that cycle, demand was structurally exploding as the internet era required entirely new computing infrastructure to be built from scratch, and memory had to scale with it in a way that had never happened before. His point is that AI may be that same kind of cycle and not a normal boom bust but a once in a generation capacity buildout where the underlying demand is structural, not cyclical. The reason this argument holds weight is the fundamental shift in what memory is in the AI era. Traditional DRAM was a pure commodity, identical specs, interchangeable suppliers, price determined entirely by supply and demand swings. HBM is the opposite because it is custom engineered to fit a specific customer's chip, co-designed between the memory maker and the GPU designer, with SK Hynix's Vice President literally describing it as shifting from a commodity to a customer-tailored custom business. A single Blackwell Ultra GPU now requires up to 288GB of HBM3E, a 3.6x increase over the H100 and major suppliers like SK Hynix and Micron have already sold out their entire HBM production capacity through the end of the year. Because HBM requires advanced packaging processes like CoWoS that can't be spun up overnight, the bottleneck isn't just wafer capacity but rather runs across the entire manufacturing stack. Bank of America projects the global HBM market grows 58% this year alone to $54.6 billion, and Nomura expects the broader memory sector to nearly double to $445 billion. This is exactly why we’re still tracking memory so closely at Milk Road. HBM is becoming less of a commodity and more of a critical custom component for AI, and we think that changes how this cycle should be valued. If you want to see what we’re actually buying and trading around this theme, come join us for just $1 using the link:

Milk Road AI

31,015 просмотров • 2 месяцев назад

The AI bottleneck is not power. It is memory. Intel CEO Lip Bu Tan Lip-Bu Tan: "Everybody knows right now memory is the biggest shortage." Building fab capacity to fix it takes years. HBM and DRAM tightness is the primary speed limit on AI cluster deployment right now. Power gets the headlines, memory gates the build. Corroborated: Marvell CEO Matt Murphy said the same at COMPUTEX a week earlier. Watch HBM and DRAM pricing as the binding gauge: Source: No Priors -
0:32

The AI bottleneck is not power. It is memory. Intel CEO Lip Bu Tan Lip-Bu Tan: "Everybody knows right now memory is the biggest shortage." Building fab capacity to fix it takes years. HBM and DRAM tightness is the primary speed limit on AI cluster deployment right now. Power gets the headlines, memory gates the build. Corroborated: Marvell CEO Matt Murphy said the same at COMPUTEX a week earlier. Watch HBM and DRAM pricing as the binding gauge: Source: No Priors -

Podcast Alpha

17,327 просмотров • 4 месяцев назад

Semi Analysis Dylan Patel: People are like, 'oh, the memory story is overplayed, everyone gets it.' No, no, no — you don't get it. DRAM will double or triple from here still, because that's how much capacity is required, and they have to steal capacity from somewhere else. And the only way to steal capacity in a capitalist economy is demand destruction via higher pricing.
1:09

Semi Analysis Dylan Patel: People are like, 'oh, the memory story is overplayed, everyone gets it.' No, no, no — you don't get it. DRAM will double or triple from here still, because that's how much capacity is required, and they have to steal capacity from somewhere else. And the only way to steal capacity in a capitalist economy is demand destruction via higher pricing.

Wall St Engine

209,673 просмотров • 6 месяцев назад