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The semiconductor memory cycle has a timing problem. Sell-side consensus models for the DRAM supply-demand inflection largely ignore yield ramp realities, HBM wafer diversion, and the structural lag between capacity announcements and actual bit output. The gap between when the street expects the turn and when it actually arrives... is where the trade lives. That timing gap is precisely what this Play quantifies. It models five supply-demand variables across SK Hynix, Samsung, and Micron — producing a probability distribution for when DRAM transitions from shortage to oversupply, not a single date. Here's what the Play covers: Inflection Probability Timeline The model produces a quarter-by-quarter cumulative probability curve for when supply-demand balance tips. Rather than anchoring on one date, it shows the full distribution — helping investors identify where consensus positioning diverges from modeled likelihood. Supplier Capacity Tracker Each of the three major DRAM producers carries different expansion timelines, yield curves, and long-term agreement lock ratios. SK Hynix leads on yield and speed; Samsung carries the largest absolute capacity delta but with slower ramp; Micron's Idaho fab represents a significant future supply addition. The Play tracks each supplier's effective supply contribution quarter by quarter. Scenario Analysis Four distinct scenarios — ranging from aggressive capacity ramp to prolonged supply tightness — allow investors to stress-test positioning under materially different industry conditions. Each scenario adjusts multiple variables simultaneously to capture how correlated shifts in demand and supply interact. Sensitivity Tornado Ten independent variables are ranked by their impact on inflection timing. Initial days-of-inventory dominates the total swing. HBM bit demand growth and wafer diversion ratio follow. The tornado chart makes clear which assumptions to monitor — and which are noise. DRAM Memory Inflection is now live on FUNDA for all subscribers.show more

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13,076 次观看 • 1 个月前 •via X (Twitter)

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MICRON $MU CEO SAYS THE COMPANY CAN ONLY SUPPLY 50-65% OF WHAT CUSTOMERS NEED RIGHT NOW This isn’t just Micron, Samsung, or SK Hynix. It’s a full-stack constraint that benefits the broader memory and storage ecosystem, including NAND from $SNDK and $WDC, capacity-driven disks from $STX, and system-level storage platforms and arrays from $P. AI demand for DRAM is outpacing supply by an “unprecedented” gap. New fabs take years, and the shortage is expected to persist beyond 2026.

MICRON $MU CEO SAYS THE COMPANY CAN ONLY SUPPLY 50-65% OF WHAT CUSTOMERS NEED RIGHT NOW This isn’t just Micron, Samsung, or SK Hynix. It’s a full-stack constraint that benefits the broader memory and storage ecosystem, including NAND from $SNDK and $WDC, capacity-driven disks from $STX, and system-level storage platforms and arrays from $P. AI demand for DRAM is outpacing supply by an “unprecedented” gap. New fabs take years, and the shortage is expected to persist beyond 2026.

Sam Badawi

385,928 次观看 • 2 个月前

Micron is going to $4,000 and here is why (Save this). For 25 years, DRAM prices did one thing, they went down. Memory makers overbuilt, supply overwhelmed demand, buyers had all the negotiating leverage and that commodity trap crushed memory stocks every single cycle. What you are watching right now is a complete structural break from that 25 year trend. DRAM contract prices are up 700% year over year and the reason is AI and it is not going away. HBM3 was 12 layers, HBM4 in production and shipping now to Nvidia's latest GPUs is 16 layers. Each generation consumes significantly more wafer to produce than the last, meaning supply structurally tightens as the technology advances. Memory was 8% of hyperscaler capex in 2023 but is 35% in 2026 and is projected to hit 48% in 2027. Nearly half of everything Microsoft, Amazon, Google, and Meta spend on infrastructure will go to memory by next year. Going from the GB300 to the Vera Rubin 200 generation, GPU cost went up 57% while memory cost went up 435%. There are three companies on earth that can make DRAM at scale, Samsung, SK Hynix, and Micron. Both Samsung and SK Hynix are converting capacity to HBM which means conventional DRAM supply tightens further for everything else, and Micron captures pricing on both sides. Micron guided to $33.5 billion for Q3 and they reported $41.46 billion, a $7.96 billion beat, the largest earnings beat in the company's history. Gross margins came in at 85% above the 81% they guided. For Q4, they are now guiding to $50 billion in revenue with ~86% gross margins and $31 EPS. At $112 EPS in FY2027, the pre-earnings consensus and a 35x multiple, that is a $3,920 stock but with Q4 guiding to $31 EPS alone in a single quarter, FY2027 estimates will be revised meaningfully higher. Deutsche Bank says the supply-demand gap worsens through all of 2027 and into 2028. The market still thinks this is a cyclical bounce but this is far from it. This is the first chapters of a multi year repricing of the most critical component in the AI economy and Micron is at the center of it. Follow me Melvin for more AI, semis, and the next big market themes.

Micron is going to $4,000 and here is why (Save this). For 25 years, DRAM prices did one thing, they went down. Memory makers overbuilt, supply overwhelmed demand, buyers had all the negotiating leverage and that commodity trap crushed memory stocks every single cycle. What you are watching right now is a complete structural break from that 25 year trend. DRAM contract prices are up 700% year over year and the reason is AI and it is not going away. HBM3 was 12 layers, HBM4 in production and shipping now to Nvidia's latest GPUs is 16 layers. Each generation consumes significantly more wafer to produce than the last, meaning supply structurally tightens as the technology advances. Memory was 8% of hyperscaler capex in 2023 but is 35% in 2026 and is projected to hit 48% in 2027. Nearly half of everything Microsoft, Amazon, Google, and Meta spend on infrastructure will go to memory by next year. Going from the GB300 to the Vera Rubin 200 generation, GPU cost went up 57% while memory cost went up 435%. There are three companies on earth that can make DRAM at scale, Samsung, SK Hynix, and Micron. Both Samsung and SK Hynix are converting capacity to HBM which means conventional DRAM supply tightens further for everything else, and Micron captures pricing on both sides. Micron guided to $33.5 billion for Q3 and they reported $41.46 billion, a $7.96 billion beat, the largest earnings beat in the company's history. Gross margins came in at 85% above the 81% they guided. For Q4, they are now guiding to $50 billion in revenue with ~86% gross margins and $31 EPS. At $112 EPS in FY2027, the pre-earnings consensus and a 35x multiple, that is a $3,920 stock but with Q4 guiding to $31 EPS alone in a single quarter, FY2027 estimates will be revised meaningfully higher. Deutsche Bank says the supply-demand gap worsens through all of 2027 and into 2028. The market still thinks this is a cyclical bounce but this is far from it. This is the first chapters of a multi year repricing of the most critical component in the AI economy and Micron is at the center of it. Follow me Melvin for more AI, semis, and the next big market themes.

Melvin

92,821 次观看 • 21 天前

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!

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

260,384 次观看 • 18 天前

Micron is one of the most UNDERVALUED stocks in the entire AI trade right now and everyone should be buying at these prices. (Save this). Jensen laid out the situation in one sentence, the supply chain is lined up, the HBM is lined up with the Grace Blackwell GPUs, the only problem is that demand is much greater than the overall capacity of the world. And Michael Dell said it before Jensen even finished that memory is the single biggest supply constraint in the entire AI buildout right now. Every HBM chip that Micron, SK Hynix, and Samsung produce consumes three times the silicon wafer area of standard DRAM. Nvidia's Rubin GPU requires 288GB of HBM per chip, a 260% increase over the H100 in just two generations. Every major hyperscaler has locked up contracts through 2026, and Micron has said publicly it can only fulfill about two-thirds of medium-term demand for some customers. And it's HBM production is sold out entirely for 2026 and HBM4 is also already sold out. The numbers tell the story, DDR4 spot prices surged roughly 15x in eight months. DRAM contract prices rose 90-95% in a single quarter, TrendForce called it "essentially unprecedented" in the history of the memory market. Micron has rallied roughly 68% year to date in 2026, and yet it still trades at a P/E of 37.6x against an industry average of 75.3x. The shortage does not resolve until new fabs come online, Micron's new factories are not producing until 2027 and 2028 at the earliest, and the memory shortage is forecast to run until at least 2027. Milk Road Pro has been covering the HBM memory trade as a core AI infrastructure thesis before it became a consensus Wall Street call and our Pro members are already up massively in $MU. Come join us at the link in bio/below to see our full portfolio and the names we're watching before the rest of the market catches on.

Micron is one of the most UNDERVALUED stocks in the entire AI trade right now and everyone should be buying at these prices. (Save this). Jensen laid out the situation in one sentence, the supply chain is lined up, the HBM is lined up with the Grace Blackwell GPUs, the only problem is that demand is much greater than the overall capacity of the world. And Michael Dell said it before Jensen even finished that memory is the single biggest supply constraint in the entire AI buildout right now. Every HBM chip that Micron, SK Hynix, and Samsung produce consumes three times the silicon wafer area of standard DRAM. Nvidia's Rubin GPU requires 288GB of HBM per chip, a 260% increase over the H100 in just two generations. Every major hyperscaler has locked up contracts through 2026, and Micron has said publicly it can only fulfill about two-thirds of medium-term demand for some customers. And it's HBM production is sold out entirely for 2026 and HBM4 is also already sold out. The numbers tell the story, DDR4 spot prices surged roughly 15x in eight months. DRAM contract prices rose 90-95% in a single quarter, TrendForce called it "essentially unprecedented" in the history of the memory market. Micron has rallied roughly 68% year to date in 2026, and yet it still trades at a P/E of 37.6x against an industry average of 75.3x. The shortage does not resolve until new fabs come online, Micron's new factories are not producing until 2027 and 2028 at the earliest, and the memory shortage is forecast to run until at least 2027. Milk Road Pro has been covering the HBM memory trade as a core AI infrastructure thesis before it became a consensus Wall Street call and our Pro members are already up massively in $MU. Come join us at the link in bio/below to see our full portfolio and the names we're watching before the rest of the market catches on.

Milk Road AI

146,805 次观看 • 2 个月前

Micron is going to be a $4,000 stock and the CEO just told you exactly why in one interview (Save this). Micron is no longer a chip company but rather a America's monopoly on the most strategically critical material in the AI buildout. It's the only western company manufacturing memory at advanced nodes, sitting on $200 billion in committed domestic capex, with every unit of its highest value product already sold. let's start with the supply reality, Mehrotra said Micron can currently meet only 50% to two thirds of the demand from its key customers. That shortage will last well beyond 2027, and meaningful new supply from anyone in the industry does not arrive until 2028 at the earliest. Two more years of demand outpacing supply in a market growing 168% year over year and that is the floor on the bull case. Now layer on what makes this cycle structurally different from every one before it. Micron is the only American memory manufacturer on earth, Samsung and SK Hynix are South Korean. In a world where AI infrastructure has become a declared national security priority where Commerce Secretary Lutnick and Trade Ambassador Greer personally showed up to a fab dedication in Manassas, Virginia being the only US memory company is not just a competitive advantage. It is a government backed structural monopoly on the most critical input to the US AI buildout, backed by $6.2 billion in CHIPS Act subsidies across Idaho, New York, and Virginia. The $200 billion buildout spans Manassas for DDR4 defense and industrial memory, Boise for leading-edge DRAM with first wafers out mid 2027, a second Boise HBM fab with first wafers by end of 2028, and the Syracuse megafab, the largest semiconductor facility in US history, breaking ground January 2026 with up to four fabs over time. Combined, these sites take Micron's domestic production from 10% of its total output today to 40% over the next decade, and create 90,000 jobs in the process. The business model transformation is the real story. Come join Milk Road Pro for our full breakdown, our complete Micron valuation model incorporating the $200 billion domestic buildout and our entire AI thesis. Link below.

Micron is going to be a $4,000 stock and the CEO just told you exactly why in one interview (Save this). Micron is no longer a chip company but rather a America's monopoly on the most strategically critical material in the AI buildout. It's the only western company manufacturing memory at advanced nodes, sitting on $200 billion in committed domestic capex, with every unit of its highest value product already sold. let's start with the supply reality, Mehrotra said Micron can currently meet only 50% to two thirds of the demand from its key customers. That shortage will last well beyond 2027, and meaningful new supply from anyone in the industry does not arrive until 2028 at the earliest. Two more years of demand outpacing supply in a market growing 168% year over year and that is the floor on the bull case. Now layer on what makes this cycle structurally different from every one before it. Micron is the only American memory manufacturer on earth, Samsung and SK Hynix are South Korean. In a world where AI infrastructure has become a declared national security priority where Commerce Secretary Lutnick and Trade Ambassador Greer personally showed up to a fab dedication in Manassas, Virginia being the only US memory company is not just a competitive advantage. It is a government backed structural monopoly on the most critical input to the US AI buildout, backed by $6.2 billion in CHIPS Act subsidies across Idaho, New York, and Virginia. The $200 billion buildout spans Manassas for DDR4 defense and industrial memory, Boise for leading-edge DRAM with first wafers out mid 2027, a second Boise HBM fab with first wafers by end of 2028, and the Syracuse megafab, the largest semiconductor facility in US history, breaking ground January 2026 with up to four fabs over time. Combined, these sites take Micron's domestic production from 10% of its total output today to 40% over the next decade, and create 90,000 jobs in the process. The business model transformation is the real story. Come join Milk Road Pro for our full breakdown, our complete Micron valuation model incorporating the $200 billion domestic buildout and our entire AI thesis. Link below.

Milk Road AI

231,528 次观看 • 1 个月前

Jensen Huang just made a statement that every investor in AI infrastructure needs to hear (Save this). He said that the AI buildout is accelerating, the second half of this year is going to be much larger than the first half, and next year is going to be very, very large. Micron is the best positioned to win from this because every Nvidia GPU requires High Bandwidth Memory stacked directly on the chip to feed it data fast enough to keep up. There is no AI compute without memory, and right now there is simply not enough memory to go around. Micron's entire HBM supply for 2026 is already completely sold out under multi-year agreements before the year even started. Micron's own management has acknowledged they can only satisfy 50 to 65 percent of demand from some of their most important customers. That is not a problem that gets fixed quickly, because new fabs take years to build. Micron's Idaho expansion does not come online until mid-2026, a second Idaho facility is not expected until 2028, and a new New York fab is looking at 2030. The demand Jensen just described is arriving right now, and the supply to meet it is years away. The financial results already reflect this dynamic. Micron's Q2 fiscal 2026 revenue came in at $23.86 billion, nearly triple what it was a year earlier beating consensus by roughly $3.8 billion. The HBM market alone is expected to grow from $35 billion today to $100 billion by 2028, and Micron has been consistently ahead of that forecast. Jensen just told the world the second half of this year and all of next year are going to be larger than anything that came before. Micron is the company that supplies the memory those GPUs need to run, and it cannot build supply fast enough to keep up with demand. Come join Milk Road Pro for our full deep dive on Micron, the HBM supply thesis and our AI trade thesis! Link below!

Jensen Huang just made a statement that every investor in AI infrastructure needs to hear (Save this). He said that the AI buildout is accelerating, the second half of this year is going to be much larger than the first half, and next year is going to be very, very large. Micron is the best positioned to win from this because every Nvidia GPU requires High Bandwidth Memory stacked directly on the chip to feed it data fast enough to keep up. There is no AI compute without memory, and right now there is simply not enough memory to go around. Micron's entire HBM supply for 2026 is already completely sold out under multi-year agreements before the year even started. Micron's own management has acknowledged they can only satisfy 50 to 65 percent of demand from some of their most important customers. That is not a problem that gets fixed quickly, because new fabs take years to build. Micron's Idaho expansion does not come online until mid-2026, a second Idaho facility is not expected until 2028, and a new New York fab is looking at 2030. The demand Jensen just described is arriving right now, and the supply to meet it is years away. The financial results already reflect this dynamic. Micron's Q2 fiscal 2026 revenue came in at $23.86 billion, nearly triple what it was a year earlier beating consensus by roughly $3.8 billion. The HBM market alone is expected to grow from $35 billion today to $100 billion by 2028, and Micron has been consistently ahead of that forecast. Jensen just told the world the second half of this year and all of next year are going to be larger than anything that came before. Micron is the company that supplies the memory those GPUs need to run, and it cannot build supply fast enough to keep up with demand. Come join Milk Road Pro for our full deep dive on Micron, the HBM supply thesis and our AI trade thesis! Link below!

Milk Road AI

77,554 次观看 • 1 个月前

AI companies just BROKE the global supply chain for every piece of technology you own. And the fallout is way worse than anyone predicted... Sony is delaying the next PlayStation to 2028 or 2029. Nintendo is hiking the Switch 2 price mid-cycle. Apple warned investors that iPhone margins are getting crushed. Cisco just posted its worst share loss in 4 years. Oppo is cutting phone shipments by 20%. Lenovo, Dell, HP, Acer, and ASUS are all raising laptop prices 15-20%. Samsung is now reviewing memory contracts QUARTERLY instead of annually because prices change too fast to plan. And Elon Musk just told investors Tesla has to build its own chip factory from scratch because no supplier on the planet can keep up. His exact words: "We've got two choices: hit the chip wall or make a fab." All of this happened in the last 3 weeks. Same cause. Every single time. AI data centers are buying every memory chip on Earth. And there's nothing left for everyone else. Here's how we got here: 3 years ago, ChatGPT launched and the AI arms race began. Since then, Samsung, SK Hynix, and Micron, the only 3 companies that make memory chips, quietly made a decision that's now reshaping the ENTIRE global economy. They stopped prioritizing consumer memory. Every factory. Every production line. Every wafer. All redirected toward one customer: AI data centers Why? Money. AI memory chips sell for 3-5X the margin of regular RAM. When Google calls offering to buy your entire output at premium pricing, you don't say no. So the 3 companies that control 90% of the world's memory supply chose their highest-paying customers and left everyone else fighting over scraps. The numbers from this week are insane: OpenAI's Stargate project ALONE will consume 40% of the entire world's DRAM output. HBM demand is surging 70% year over year in 2026. HBM now takes 23% of total DRAM wafer production, up from 19% last year. Meanwhile, there's a 4% gap between global DRAM supply and demand. And that doesn't even account for depleted inventories across multiple industries. DRAM prices have surged over 170% since early 2025. DDR5 contract prices are still jumping double digits month over month. And the memory makers? They're printing money. Micron's revenue is expected to more than DOUBLE this fiscal year. SK Hynix sales doubled in 2024 and are on pace to double AGAIN. Samsung just reported quarterly profit nearly tripling. 3 companies. $650 billion in AI spending chasing their products. And they get to name their price. But the collateral damage is everywhere: Every industry that uses memory, which is every industry, is getting squeezed. Smartphone manufacturers are getting destroyed. For a mid-range phone, memory now represents up to 30% of the total build cost. Triple what it was in early 2025. Chinese phone makers like Xiaomi, Oppo, and Transsion are cutting shipment forecasts and raising prices because they literally cannot afford the memory to build their phones. Lenovo's CFO called the cost surge "unprecedented" and admitted they stockpiled 50% more inventory than normal just to survive the next few months. The PC market could shrink by up to 9% this year according to IDC. Not because people don't want computers. But because they can't afford the memory that goes inside them. And the gaming industry? Sony is seriously considering pushing the next PlayStation to 2028 or 2029. Their carefully planned console cycle is getting blown up because they can't secure memory at prices that make a new console viable. Nintendo is looking at raising the Switch 2 price. In the middle of a launch cycle. Something console makers almost never do. Nvidia is cutting RTX GPU production because they can't get enough GDDR7 memory. Even the car industry is getting hit... Analysts are warning about a repeat of the pandemic-era chip shortage that shut down auto factories worldwide. All because AI companies decided their chatbots needed the memory more than your car does. And this doesn't get better for YEARS. Building a new memory fab takes 3-5 years minimum. Micron's new factory in Idaho won't meaningfully increase supply until 2027 at the earliest. By then, AI demand will have grown even more. Memory makers are already selling their 2027 AND 2028 capacity to AI customers today. There is no supply relief coming. That's why Elon is planning to build Tesla's own "TeraFab," a massive semiconductor plant that makes logic chips, memory, AND packaging all under one roof. He said existing suppliers including TSMC, Samsung, and Micron simply cannot supply Tesla at the levels the company needs. Think about that. One of the richest men in the world, running one of the largest companies on Earth, can't buy enough memory chips. So he's building his own factory. If ELON can't get supply, what chance does everyone else have? The AI revolution has a tax. And YOU'RE paying it. Every dollar Big Tech spends on AI infrastructure drives up the cost of the memory inside your phone, your laptop, your car, your TV, and your gaming console. $650 billion in AI spending this year. 3 companies controlling 90% of the memory supply. And every wafer they allocate to an Nvidia GPU is a wafer denied to the device in your pocket. The AI boom isn't free. You're subsidizing it every time you buy a piece of technology. And the bill just went up like crazy.

AI companies just BROKE the global supply chain for every piece of technology you own. And the fallout is way worse than anyone predicted... Sony is delaying the next PlayStation to 2028 or 2029. Nintendo is hiking the Switch 2 price mid-cycle. Apple warned investors that iPhone margins are getting crushed. Cisco just posted its worst share loss in 4 years. Oppo is cutting phone shipments by 20%. Lenovo, Dell, HP, Acer, and ASUS are all raising laptop prices 15-20%. Samsung is now reviewing memory contracts QUARTERLY instead of annually because prices change too fast to plan. And Elon Musk just told investors Tesla has to build its own chip factory from scratch because no supplier on the planet can keep up. His exact words: "We've got two choices: hit the chip wall or make a fab." All of this happened in the last 3 weeks. Same cause. Every single time. AI data centers are buying every memory chip on Earth. And there's nothing left for everyone else. Here's how we got here: 3 years ago, ChatGPT launched and the AI arms race began. Since then, Samsung, SK Hynix, and Micron, the only 3 companies that make memory chips, quietly made a decision that's now reshaping the ENTIRE global economy. They stopped prioritizing consumer memory. Every factory. Every production line. Every wafer. All redirected toward one customer: AI data centers Why? Money. AI memory chips sell for 3-5X the margin of regular RAM. When Google calls offering to buy your entire output at premium pricing, you don't say no. So the 3 companies that control 90% of the world's memory supply chose their highest-paying customers and left everyone else fighting over scraps. The numbers from this week are insane: OpenAI's Stargate project ALONE will consume 40% of the entire world's DRAM output. HBM demand is surging 70% year over year in 2026. HBM now takes 23% of total DRAM wafer production, up from 19% last year. Meanwhile, there's a 4% gap between global DRAM supply and demand. And that doesn't even account for depleted inventories across multiple industries. DRAM prices have surged over 170% since early 2025. DDR5 contract prices are still jumping double digits month over month. And the memory makers? They're printing money. Micron's revenue is expected to more than DOUBLE this fiscal year. SK Hynix sales doubled in 2024 and are on pace to double AGAIN. Samsung just reported quarterly profit nearly tripling. 3 companies. $650 billion in AI spending chasing their products. And they get to name their price. But the collateral damage is everywhere: Every industry that uses memory, which is every industry, is getting squeezed. Smartphone manufacturers are getting destroyed. For a mid-range phone, memory now represents up to 30% of the total build cost. Triple what it was in early 2025. Chinese phone makers like Xiaomi, Oppo, and Transsion are cutting shipment forecasts and raising prices because they literally cannot afford the memory to build their phones. Lenovo's CFO called the cost surge "unprecedented" and admitted they stockpiled 50% more inventory than normal just to survive the next few months. The PC market could shrink by up to 9% this year according to IDC. Not because people don't want computers. But because they can't afford the memory that goes inside them. And the gaming industry? Sony is seriously considering pushing the next PlayStation to 2028 or 2029. Their carefully planned console cycle is getting blown up because they can't secure memory at prices that make a new console viable. Nintendo is looking at raising the Switch 2 price. In the middle of a launch cycle. Something console makers almost never do. Nvidia is cutting RTX GPU production because they can't get enough GDDR7 memory. Even the car industry is getting hit... Analysts are warning about a repeat of the pandemic-era chip shortage that shut down auto factories worldwide. All because AI companies decided their chatbots needed the memory more than your car does. And this doesn't get better for YEARS. Building a new memory fab takes 3-5 years minimum. Micron's new factory in Idaho won't meaningfully increase supply until 2027 at the earliest. By then, AI demand will have grown even more. Memory makers are already selling their 2027 AND 2028 capacity to AI customers today. There is no supply relief coming. That's why Elon is planning to build Tesla's own "TeraFab," a massive semiconductor plant that makes logic chips, memory, AND packaging all under one roof. He said existing suppliers including TSMC, Samsung, and Micron simply cannot supply Tesla at the levels the company needs. Think about that. One of the richest men in the world, running one of the largest companies on Earth, can't buy enough memory chips. So he's building his own factory. If ELON can't get supply, what chance does everyone else have? The AI revolution has a tax. And YOU'RE paying it. Every dollar Big Tech spends on AI infrastructure drives up the cost of the memory inside your phone, your laptop, your car, your TV, and your gaming console. $650 billion in AI spending this year. 3 companies controlling 90% of the memory supply. And every wafer they allocate to an Nvidia GPU is a wafer denied to the device in your pocket. The AI boom isn't free. You're subsidizing it every time you buy a piece of technology. And the bill just went up like crazy.

Ricardo

567,053 次观看 • 5 个月前

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.

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

594,453 次观看 • 5 个月前

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.

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 次观看 • 20 天前

The selloff in Micron is one of the best buying opportunities you'll see this year (Save this). Sanjay Mehrotra just explained exactly why the old mental model for Micron, cyclical, commodity, mean reverting no longer applies. Every AI system, regardless of what device it runs on, requires more memory at higher performance to unlock its full potential. From data centers to smartphones to autonomous vehicles, memory is no longer a supporting actor but rather the critical bottleneck determining how fast AI can move. What makes this cycle structurally different starts with what happened in 2023. Certain customers drove industry pricing to one third of 2022 levels, forcing Micron into severe losses while still requiring $10 billion in investment just to stay competitive. Most companies in that situation cut spending and survive but Micron invested through the pain with the vision that the other side would be worth it. Those 2023 investments are now producing 84.9% gross margins, $41.46 billion in quarterly revenue, and Q4 guidance of $50 billion up from $11.3 billion in the same quarter just one year ago. That is what it looks like when a company bets on itself at exactly the right moment. Even Micron's own largest customers, Nvidia, Google, Amazon could not forecast the scale of AI memory demand that materialized. When the biggest technology companies in the world cannot project their own memory requirements, you are watching a structural transformation that nobody had models to predict, still in its early innings. Supply cannot respond quickly enough to close that gap. Mehrotra confirmed on air that tightness extends beyond 2027, new domestic fabs take years to bring online, and new HBM capacity which requires advanced 3D stacking that compounds in complexity at every generation won't meaningfully arrive until late 2028. There is no fast fix to a shortage of the most valuable memory on earth. The strategic customer agreements are the most underappreciated part of the entire story. Multi-year contracts with volume commitments and price floors now cover roughly 20% of DRAM volume and 30% of NAND volume, locking in a $100 billion contractual revenue base. The old Micron was at the mercy of customers who could crater prices overnight while the new Micron has contractual floors that make the 2023 scenario structurally impossible to repeat. Long Micron and make sure to follow me Melvin for more deep dives into AI and memory.

The selloff in Micron is one of the best buying opportunities you'll see this year (Save this). Sanjay Mehrotra just explained exactly why the old mental model for Micron, cyclical, commodity, mean reverting no longer applies. Every AI system, regardless of what device it runs on, requires more memory at higher performance to unlock its full potential. From data centers to smartphones to autonomous vehicles, memory is no longer a supporting actor but rather the critical bottleneck determining how fast AI can move. What makes this cycle structurally different starts with what happened in 2023. Certain customers drove industry pricing to one third of 2022 levels, forcing Micron into severe losses while still requiring $10 billion in investment just to stay competitive. Most companies in that situation cut spending and survive but Micron invested through the pain with the vision that the other side would be worth it. Those 2023 investments are now producing 84.9% gross margins, $41.46 billion in quarterly revenue, and Q4 guidance of $50 billion up from $11.3 billion in the same quarter just one year ago. That is what it looks like when a company bets on itself at exactly the right moment. Even Micron's own largest customers, Nvidia, Google, Amazon could not forecast the scale of AI memory demand that materialized. When the biggest technology companies in the world cannot project their own memory requirements, you are watching a structural transformation that nobody had models to predict, still in its early innings. Supply cannot respond quickly enough to close that gap. Mehrotra confirmed on air that tightness extends beyond 2027, new domestic fabs take years to bring online, and new HBM capacity which requires advanced 3D stacking that compounds in complexity at every generation won't meaningfully arrive until late 2028. There is no fast fix to a shortage of the most valuable memory on earth. The strategic customer agreements are the most underappreciated part of the entire story. Multi-year contracts with volume commitments and price floors now cover roughly 20% of DRAM volume and 30% of NAND volume, locking in a $100 billion contractual revenue base. The old Micron was at the mercy of customers who could crater prices overnight while the new Micron has contractual floors that make the 2023 scenario structurally impossible to repeat. Long Micron and make sure to follow me Melvin for more deep dives into AI and memory.

Melvin

130,037 次观看 • 16 天前

Elon Musk just described a project so large that most people will assume he is exaggerating (Save this). He is not. In the video, Musk lays out the central problem facing every AI company on earth, the entire global chip industry is on a path to produce roughly 100 gigawatts of AI compute per year. That sounds like a lot until you understand that his companies alone Tesla, SpaceX, and xAI will need orders of magnitude more than that. His answer is the TerraFab. It is a joint chip factory spanning 100 million square feet, ten times the size of Tesla's Gigafactory Texas announced in March 2026, with Grimes County, Texas commissioners approving the full scale facility site just last week. The goal is one full terawatt of AI compute output per year. For context, 1 terawatt is 1,000 gigawatts twice the current total electricity consumption of the United States. SpaceX has already committed an initial $55 billion to the prototype phase, with total investment estimates ranging into the trillions. Here is why this matters for Micron specifically. In the video, Musk named Nvidia's Rubin chips as the reference design for TerraFab's first orbital deployments, and said "You're going to need a lot of memory to go with that." A billion full radical equivalent chips per year, each requiring stacks of high bandwidth memory, that is the demand signal Micron just received from one of the most capital-intensive projects in human history. And Micron already cannot keep up with what exists today. Micron's entire 2026 HBM output is fully sold out contracted before the year began. HBM4 entered volume production ahead of schedule and sold out immediately. The structural reason Micron wins here is simple. Every AI chip ever built Nvidia H100s, Rubin chips, custom ASICs, TPUs is useless without high-bandwidth memory stacked directly on top of it. There are only three companies in the world that supply HBM at scale, Samsung, SK Hynix, and Micron. Samsung has had quality issues, SK Hynix is supply constrained. Micron is the only US headquartered HBM manufacturer which matters enormously given CHIPS Act subsidies, domestic procurement requirements, and the political push to keep critical AI memory production on American soil. TerraFab just made the memory deficit permanently larger. Come join Milk Road Pro for our full breakdown of Micron and our entire AI thesis just for $1. Link below!

Elon Musk just described a project so large that most people will assume he is exaggerating (Save this). He is not. In the video, Musk lays out the central problem facing every AI company on earth, the entire global chip industry is on a path to produce roughly 100 gigawatts of AI compute per year. That sounds like a lot until you understand that his companies alone Tesla, SpaceX, and xAI will need orders of magnitude more than that. His answer is the TerraFab. It is a joint chip factory spanning 100 million square feet, ten times the size of Tesla's Gigafactory Texas announced in March 2026, with Grimes County, Texas commissioners approving the full scale facility site just last week. The goal is one full terawatt of AI compute output per year. For context, 1 terawatt is 1,000 gigawatts twice the current total electricity consumption of the United States. SpaceX has already committed an initial $55 billion to the prototype phase, with total investment estimates ranging into the trillions. Here is why this matters for Micron specifically. In the video, Musk named Nvidia's Rubin chips as the reference design for TerraFab's first orbital deployments, and said "You're going to need a lot of memory to go with that." A billion full radical equivalent chips per year, each requiring stacks of high bandwidth memory, that is the demand signal Micron just received from one of the most capital-intensive projects in human history. And Micron already cannot keep up with what exists today. Micron's entire 2026 HBM output is fully sold out contracted before the year began. HBM4 entered volume production ahead of schedule and sold out immediately. The structural reason Micron wins here is simple. Every AI chip ever built Nvidia H100s, Rubin chips, custom ASICs, TPUs is useless without high-bandwidth memory stacked directly on top of it. There are only three companies in the world that supply HBM at scale, Samsung, SK Hynix, and Micron. Samsung has had quality issues, SK Hynix is supply constrained. Micron is the only US headquartered HBM manufacturer which matters enormously given CHIPS Act subsidies, domestic procurement requirements, and the political push to keep critical AI memory production on American soil. TerraFab just made the memory deficit permanently larger. Come join Milk Road Pro for our full breakdown of Micron and our entire AI thesis just for $1. Link below!

Milk Road AI

245,900 次观看 • 1 个月前

With Tim Cook stepping down, most people are talking about the iPhone, the App Store, and the stock price. But there is one move he made that almost nobody talks about and it is the single biggest reason iPhone crushed its competition in the early years. In 2005, two years before the iPhone launched, Cook made a bet. Flash storage was still relatively rare at the time and smartphones didn't exist yet. But Cook saw what was coming, a future where mobile devices would all need flash memory and he knew that if that future arrived without Apple having locked up supply, they'd be fighting for components against every phone maker on earth. So he prepaid $1.25B to suppliers including Samsung and Hynix to corner the market on NAND flash memory through 2010. The contract had a catch, suppliers had to prioritize Apple's orders over everyone else's. This was a massive gamble and if the iPhone flopped, Apple was still on the hook for the full purchase commitment. The iPhone did not flop. It went on to sell tens of millions of units in its first two years with zero supply chain slowdowns. And while Apple scaled freely, competitors couldn't get the components they needed to build a credible response. They were literally locked out of the supply chain. The move was so effective that Cook ran the same playbook across the business. He bought $100 million of holiday season air freight capacity in advance, months before competitors thought to book it, leaving rivals scrambling to ship products during the most critical sales window of the year. He cut Apple's component suppliers from 100 down to 24 and slashed inventory turnover time from 30 days to 6 days within his first seven months at the company. By 2012, Apple was turning over its inventory every 5 day, Dell took 10, Samsung took 21. Jobs is credited as the product visionary but Cook was the supply chain visionary and in the early smartphone wars, the supply chain was the moat.

With Tim Cook stepping down, most people are talking about the iPhone, the App Store, and the stock price. But there is one move he made that almost nobody talks about and it is the single biggest reason iPhone crushed its competition in the early years. In 2005, two years before the iPhone launched, Cook made a bet. Flash storage was still relatively rare at the time and smartphones didn't exist yet. But Cook saw what was coming, a future where mobile devices would all need flash memory and he knew that if that future arrived without Apple having locked up supply, they'd be fighting for components against every phone maker on earth. So he prepaid $1.25B to suppliers including Samsung and Hynix to corner the market on NAND flash memory through 2010. The contract had a catch, suppliers had to prioritize Apple's orders over everyone else's. This was a massive gamble and if the iPhone flopped, Apple was still on the hook for the full purchase commitment. The iPhone did not flop. It went on to sell tens of millions of units in its first two years with zero supply chain slowdowns. And while Apple scaled freely, competitors couldn't get the components they needed to build a credible response. They were literally locked out of the supply chain. The move was so effective that Cook ran the same playbook across the business. He bought $100 million of holiday season air freight capacity in advance, months before competitors thought to book it, leaving rivals scrambling to ship products during the most critical sales window of the year. He cut Apple's component suppliers from 100 down to 24 and slashed inventory turnover time from 30 days to 6 days within his first seven months at the company. By 2012, Apple was turning over its inventory every 5 day, Dell took 10, Samsung took 21. Jobs is credited as the product visionary but Cook was the supply chain visionary and in the early smartphone wars, the supply chain was the moat.

Milk Road AI

78,952 次观看 • 2 个月前

EXXON CEO WARNS $150 OIL WITHIN WEEKS: THE SHORTAGE THE MARKET IGNORED Josh Young of Bison Interests and Bison just laid out the numbers that flip the entire oil narrative on its head. The numbers coming out of the energy markets have flipped from bearish complacency to outright crisis faster than almost anyone modeled. A balanced global oil system has lost up to 14 million barrels of daily supply in a matter of weeks. Inventories are draining at hundreds of millions of barrels per month with virtually no demand destruction to offset the loss. THE SUPPLY SHOCK AND CYCLE REALITY ➡️ Global supply has dropped by 10 to 14 million barrels per day to around 90 to 92 million barrels daily. ➡️ The market was already 15 years into a down cycle of underinvestment before the conflict hit. ➡️ Traders had positioned for a glut that the fundamentals never supported. THE INVENTORY CRISIS ACCELERATES ➡️ Storage has plunged from 8.3 billion to nearly 7 billion barrels in just months. ➡️ Monthly depletion of 300 to 500 million barrels continues without relief. ➡️ Tank bottoms are approaching fast, threatening the basic functioning of global oil logistics. THE DEMAND AND RECOVERY DYNAMICS ➡️ Demand destruction remains minimal and largely availability driven rather than economic. ➡️ Even immediate reopening of key chokepoints would require two to three months for normalization. ➡️ Additional inventory losses of 500 million to 1 billion barrels are already locked in. THE $150 OIL WARNING FROM THE TOP ➡️ Exxon and Chevron CEOs stated within weeks they expect $150 plus physical oil. ➡️ Their conservative stance makes this warning all the more significant for the market. ➡️ The data on collapsing supply and vanishing storage fully supports their assessment. THE BOTTOM LINE The war has accelerated an already tightening oil cycle into a full-blown supply crisis. With inventories crashing and almost no demand response to cushion the blow, the market is now set for materially higher prices over an extended period. The old glut fears have been exposed as fundamentally misplaced. This is the supply crisis that forces the re-rating of oil higher. #OilSupplyCrisis #HigherOilPrices #InventoryDrawdown #EnergyBull #WTI #TankBottoms #SupplyShock HT: YouTube Natural Resource Stocks Josh Young

EXXON CEO WARNS $150 OIL WITHIN WEEKS: THE SHORTAGE THE MARKET IGNORED Josh Young of Bison Interests and Bison just laid out the numbers that flip the entire oil narrative on its head. The numbers coming out of the energy markets have flipped from bearish complacency to outright crisis faster than almost anyone modeled. A balanced global oil system has lost up to 14 million barrels of daily supply in a matter of weeks. Inventories are draining at hundreds of millions of barrels per month with virtually no demand destruction to offset the loss. THE SUPPLY SHOCK AND CYCLE REALITY ➡️ Global supply has dropped by 10 to 14 million barrels per day to around 90 to 92 million barrels daily. ➡️ The market was already 15 years into a down cycle of underinvestment before the conflict hit. ➡️ Traders had positioned for a glut that the fundamentals never supported. THE INVENTORY CRISIS ACCELERATES ➡️ Storage has plunged from 8.3 billion to nearly 7 billion barrels in just months. ➡️ Monthly depletion of 300 to 500 million barrels continues without relief. ➡️ Tank bottoms are approaching fast, threatening the basic functioning of global oil logistics. THE DEMAND AND RECOVERY DYNAMICS ➡️ Demand destruction remains minimal and largely availability driven rather than economic. ➡️ Even immediate reopening of key chokepoints would require two to three months for normalization. ➡️ Additional inventory losses of 500 million to 1 billion barrels are already locked in. THE $150 OIL WARNING FROM THE TOP ➡️ Exxon and Chevron CEOs stated within weeks they expect $150 plus physical oil. ➡️ Their conservative stance makes this warning all the more significant for the market. ➡️ The data on collapsing supply and vanishing storage fully supports their assessment. THE BOTTOM LINE The war has accelerated an already tightening oil cycle into a full-blown supply crisis. With inventories crashing and almost no demand response to cushion the blow, the market is now set for materially higher prices over an extended period. The old glut fears have been exposed as fundamentally misplaced. This is the supply crisis that forces the re-rating of oil higher. #OilSupplyCrisis #HigherOilPrices #InventoryDrawdown #EnergyBull #WTI #TankBottoms #SupplyShock HT: YouTube Natural Resource Stocks Josh Young

Mark

18,685 次观看 • 1 个月前

$Jeff Currie of Carlyle went on live television and said the oil market is completely mispriced. He said futures price crude at around $100 a barrel, but physical oil delivered to Asian refiners is actually costing between $130 and $170. At one point this month, Oman crude, the benchmark for oil on the free side of the Strait spiked all the way to $173 a barrel. The paper market and the real world have completely split from each other and Currie was explicit about why that split is dangerous. He said jet fuel spiked to $230 a barrel in Singapore last week, then the same spike hit Rotterdam at $220 a barrel, then Thailand, then the Philippines, then New Zealand, then Australia. He called it molecular contagion, a physical shortage virus spreading across global supply hubs one by one. To understand why that phrase matters, consider what the Strait of Hormuz actually is. Before the war, roughly 20 million barrels of oil per day moved through that single 100-mile waterway. The IEA now says flows have dropped from 20 million barrels per day to what they described as a trickle and Barclays estimates the effective supply loss at 13 to 14 million barrels per day in a prolonged closure scenario. Currie said there are no more spare barrels in the system. The price spread between Singapore and Rotterdam which normally tells traders where surplus oil is sitting has completely disappeared and when that spread goes to zero, there is no buffer left anywhere on earth. He said this supply shock is nearly equal in size to the COVID demand crash, and he reminded viewers what COVID did to global supply chains. COVID wiped out approximately 20 million barrels per day of demand and fractured supply chains for two full years. This war has now wiped out a comparable volume of supply and supply chains cannot work from home. The data behind his warning is already visible. Middle Eastern crude exports to Asia have collapsed from roughly 19 million barrels per day in February to under 7 million barrels per day in March. Dubai crude surged past $166 a barrel on March 19, hitting an all-time record and Oman crude crossed $150 for the first time in history just days before. Meanwhile, Chevron's CEO and Shell's CEO both stood up at the CERAWeek conference in Houston and confirmed the same thing Currie said, physical disruptions are now spreading from South Asia into Southeast Asia, Northeast Asia and are beginning to reach Europe. Currie said the reason WTI and Brent paper prices stayed suppressed is that Russian Urals crude rallied 65 to 70 dollars a barrel after sanctions were lifted. That closed the gap between cheap Russian oil and expensive Western benchmarks. Once that gap closed, the last pressure valve in the global system shut off and now the entire complex has nowhere to hide.$

Jeff Currie of Carlyle went on live television and said the oil market is completely mispriced. He said futures price crude at around $100 a barrel, but physical oil delivered to Asian refiners is actually costing between $130 and $170. At one point this month, Oman crude, the benchmark for oil on the free side of the Strait spiked all the way to $173 a barrel. The paper market and the real world have completely split from each other and Currie was explicit about why that split is dangerous. He said jet fuel spiked to $230 a barrel in Singapore last week, then the same spike hit Rotterdam at $220 a barrel, then Thailand, then the Philippines, then New Zealand, then Australia. He called it molecular contagion, a physical shortage virus spreading across global supply hubs one by one. To understand why that phrase matters, consider what the Strait of Hormuz actually is. Before the war, roughly 20 million barrels of oil per day moved through that single 100-mile waterway. The IEA now says flows have dropped from 20 million barrels per day to what they described as a trickle and Barclays estimates the effective supply loss at 13 to 14 million barrels per day in a prolonged closure scenario. Currie said there are no more spare barrels in the system. The price spread between Singapore and Rotterdam which normally tells traders where surplus oil is sitting has completely disappeared and when that spread goes to zero, there is no buffer left anywhere on earth. He said this supply shock is nearly equal in size to the COVID demand crash, and he reminded viewers what COVID did to global supply chains. COVID wiped out approximately 20 million barrels per day of demand and fractured supply chains for two full years. This war has now wiped out a comparable volume of supply and supply chains cannot work from home. The data behind his warning is already visible. Middle Eastern crude exports to Asia have collapsed from roughly 19 million barrels per day in February to under 7 million barrels per day in March. Dubai crude surged past $166 a barrel on March 19, hitting an all-time record and Oman crude crossed $150 for the first time in history just days before. Meanwhile, Chevron's CEO and Shell's CEO both stood up at the CERAWeek conference in Houston and confirmed the same thing Currie said, physical disruptions are now spreading from South Asia into Southeast Asia, Northeast Asia and are beginning to reach Europe. Currie said the reason WTI and Brent paper prices stayed suppressed is that Russian Urals crude rallied 65 to 70 dollars a barrel after sanctions were lifted. That closed the gap between cheap Russian oil and expensive Western benchmarks. Once that gap closed, the last pressure valve in the global system shut off and now the entire complex has nowhere to hide.

StockMarket.News

360,188 次观看 • 3 个月前

Markets don't move on data alone — they move on stories. The question is not just whether a narrative is right, but where it is in its lifecycle: just beginning to spread, already fully priced in, or somewhere in between. Most investors sense this intuitively, but lack a systematic way to track it. That timing is the core problem. A compelling thesis can generate alpha at the right stage and destroy it at the wrong one. The same trade that delivers triple-digit returns during its diffusion phase can become a crowded exit trap once consensus forms. Today we're launching Narrative Tracker on our full-stack research platform to tell the difference. Here's what the Play covers: Alpha Opportunities The Play identifies narratives that have reached institutional confirmation and are still generating excess returns relative to broader markets. Each opportunity is ranked by realized alpha since confirmation, with lifecycle staging that indicates how much room remains before the trade becomes consensus. Emerging Narratives Before a narrative reaches confirmation, the Play tracks it in its earliest stages — initial institutional attention and cross-channel diffusion. Each emerging narrative carries a probability score reflecting confidence that alpha will materialize, giving investors a watchlist of themes before they become crowded. Exit Watch Not every confirmed narrative stays productive. The Play monitors exit urgency across multiple risk dimensions — retail frenzy, trade crowding, price absorption, heat decay, and counter-narrative strength. When conditions deteriorate, the system flags exit priority levels so investors can reduce exposure before the reversal. News-to-Narrative Mapping Fresh catalysts are mapped to their parent narratives in real time, with signal strength ratings. Rather than scanning headlines individually, investors see which news events reinforce or challenge existing theses — and which tickers are directly impacted. Narrative Tracker is now live on FUNDA for institutional clients. For a limited time, all paid Substack subscribers can access the full set through June 5, 2026. Feedback is more than welcome.

Markets don't move on data alone — they move on stories. The question is not just whether a narrative is right, but where it is in its lifecycle: just beginning to spread, already fully priced in, or somewhere in between. Most investors sense this intuitively, but lack a systematic way to track it. That timing is the core problem. A compelling thesis can generate alpha at the right stage and destroy it at the wrong one. The same trade that delivers triple-digit returns during its diffusion phase can become a crowded exit trap once consensus forms. Today we're launching Narrative Tracker on our full-stack research platform to tell the difference. Here's what the Play covers: Alpha Opportunities The Play identifies narratives that have reached institutional confirmation and are still generating excess returns relative to broader markets. Each opportunity is ranked by realized alpha since confirmation, with lifecycle staging that indicates how much room remains before the trade becomes consensus. Emerging Narratives Before a narrative reaches confirmation, the Play tracks it in its earliest stages — initial institutional attention and cross-channel diffusion. Each emerging narrative carries a probability score reflecting confidence that alpha will materialize, giving investors a watchlist of themes before they become crowded. Exit Watch Not every confirmed narrative stays productive. The Play monitors exit urgency across multiple risk dimensions — retail frenzy, trade crowding, price absorption, heat decay, and counter-narrative strength. When conditions deteriorate, the system flags exit priority levels so investors can reduce exposure before the reversal. News-to-Narrative Mapping Fresh catalysts are mapped to their parent narratives in real time, with signal strength ratings. Rather than scanning headlines individually, investors see which news events reinforce or challenge existing theses — and which tickers are directly impacted. Narrative Tracker is now live on FUNDA for institutional clients. For a limited time, all paid Substack subscribers can access the full set through June 5, 2026. Feedback is more than welcome.

FUNDA

15,480 次观看 • 1 个月前

Gavin Baker just spotted a massive contradiction inside the AI market. The valuations across the AI supply chain don't add up when you hold them side by side. - Memory names: trading at 3-5x PE. - Nvidia: trading at a very low PE. - Some accelerator companies: reasonable multiples. - Power and cooling names: discounting a much higher future. These multiples can't all be right at the same time. If power and cooling names are priced correctly, then Nvidia and memory are way too cheap. They're going up a lot from here. If Nvidia and memory are priced correctly, then power and cooling will significantly underperform from here. One side is wrong. Both can't be true. Baker's word for it: the AI market is "cross-sectionally inefficient" right now. For investors, the question isn't just "am I bullish on AI?" The real question is: which part of the stack is priced correctly and which part is priced for a scenario that isn't going to play out? Note: Baker runs Atreides Management, one of the most respected tech-focused growth funds in the world. He doesn't make calls like this lightly. When the best investors in tech spot a cross-sectional mismatch this size, the trade is figuring out which side wins. Our analysts are already positioning inside the AI supply chain. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Follow their exact portfolios for $1 at Milk Road PRO, link in bio.

Gavin Baker just spotted a massive contradiction inside the AI market. The valuations across the AI supply chain don't add up when you hold them side by side. - Memory names: trading at 3-5x PE. - Nvidia: trading at a very low PE. - Some accelerator companies: reasonable multiples. - Power and cooling names: discounting a much higher future. These multiples can't all be right at the same time. If power and cooling names are priced correctly, then Nvidia and memory are way too cheap. They're going up a lot from here. If Nvidia and memory are priced correctly, then power and cooling will significantly underperform from here. One side is wrong. Both can't be true. Baker's word for it: the AI market is "cross-sectionally inefficient" right now. For investors, the question isn't just "am I bullish on AI?" The real question is: which part of the stack is priced correctly and which part is priced for a scenario that isn't going to play out? Note: Baker runs Atreides Management, one of the most respected tech-focused growth funds in the world. He doesn't make calls like this lightly. When the best investors in tech spot a cross-sectional mismatch this size, the trade is figuring out which side wins. Our analysts are already positioning inside the AI supply chain. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Follow their exact portfolios for $1 at Milk Road PRO, link in bio.

Milk Road Macro

162,479 次观看 • 1 个月前

Oil is down, and down big. The headlines make it sound obvious. Iran peace deal, supply normalizing, the war premium coming out. But the rest of the markets are saying something very different. The clean story makes sense. Iran deal appears, crude sells off. The fundamental value of oil is closer to 50 a barrel than 150. But if this were only supply normalizing, the oil curve would stay in backwardation. The market would still want barrels today. It is not. Backwardation is vanishing. The front of the curve is about 80 cents from contango. The three-month spread has collapsed from around 30 to just over 2. Contango is what a glut looks like in the futures market. And the curve is heading there fast. Then the IEA cut its 2026 demand growth forecast by about 700,000 barrels a day. It warned of a major supply overhang in 2027. That is not supply. That is demand breaking. Inflation markets agree. TIPS break-evens are collapsing. The 5-year is down about 40 basis points in a month, back near its weakest levels of the year. That is not a market afraid of inflation. It is a market pricing the oil shock as temporary and demand-destructive. The Treasury curve says the same. The 2-year jumped to about 4.2%. The 10-year barely moved. The 2s10s spread flattened to about 29 basis points. The front end is taking the Fed's hawkish dots seriously. The long end refuses to price growth. That is not an inflation signal. It is a policy-mistake signal. Because the Fed is looking at this exact setup and seeing inflation. Its dots moved up about half a point from March. A majority of the FOMC now thinks it might have to hike for oil. We have seen this movie. Trichet and the ECB hiked into weakness in 2008 and again in 2011, mistaking a commodity shock for real inflation. It was a disaster both times, and the markets told them so in advance. Here is what they keep missing. Oil is a relative price shock, not inflation. For it to become inflation you need it to spread. Wages chasing prices. Businesses with pricing power. Demand strong enough to absorb higher costs. None of that is happening. So falling oil is not automatically bullish. Cheaper oil because supply came back is good. Cheaper oil because the economy is breaking is not. The market is pricing both, and the curve is where the fight shows up. Oil down by itself is good news. Oil down with flattening curves, collapsing break-evens, and demand downgrades is something else entirely.

Oil is down, and down big. The headlines make it sound obvious. Iran peace deal, supply normalizing, the war premium coming out. But the rest of the markets are saying something very different. The clean story makes sense. Iran deal appears, crude sells off. The fundamental value of oil is closer to 50 a barrel than 150. But if this were only supply normalizing, the oil curve would stay in backwardation. The market would still want barrels today. It is not. Backwardation is vanishing. The front of the curve is about 80 cents from contango. The three-month spread has collapsed from around 30 to just over 2. Contango is what a glut looks like in the futures market. And the curve is heading there fast. Then the IEA cut its 2026 demand growth forecast by about 700,000 barrels a day. It warned of a major supply overhang in 2027. That is not supply. That is demand breaking. Inflation markets agree. TIPS break-evens are collapsing. The 5-year is down about 40 basis points in a month, back near its weakest levels of the year. That is not a market afraid of inflation. It is a market pricing the oil shock as temporary and demand-destructive. The Treasury curve says the same. The 2-year jumped to about 4.2%. The 10-year barely moved. The 2s10s spread flattened to about 29 basis points. The front end is taking the Fed's hawkish dots seriously. The long end refuses to price growth. That is not an inflation signal. It is a policy-mistake signal. Because the Fed is looking at this exact setup and seeing inflation. Its dots moved up about half a point from March. A majority of the FOMC now thinks it might have to hike for oil. We have seen this movie. Trichet and the ECB hiked into weakness in 2008 and again in 2011, mistaking a commodity shock for real inflation. It was a disaster both times, and the markets told them so in advance. Here is what they keep missing. Oil is a relative price shock, not inflation. For it to become inflation you need it to spread. Wages chasing prices. Businesses with pricing power. Demand strong enough to absorb higher costs. None of that is happening. So falling oil is not automatically bullish. Cheaper oil because supply came back is good. Cheaper oil because the economy is breaking is not. The market is pricing both, and the curve is where the fight shows up. Oil down by itself is good news. Oil down with flattening curves, collapsing break-evens, and demand downgrades is something else entirely.

Jeffrey P. Snider

32,892 次观看 • 28 天前

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!

Milk Road AI

14,578 次观看 • 25 天前

In 2023, the Saudi Crown Prince (MBS) made strong statements about the future of competing oil-producing countries: “For example, the United States will not be an oil-producing country in ten years. Today it produces around 11 million barrels per day; in ten years, it will barely produce 2 million barrels. China currently produces about 4 million barrels domestically, but within four to seven years it will be producing close to zero by 2030, or only a marginal amount. Russia today produces around 11 million barrels, but in 19 years it will produce about 1 million barrels, or slightly more or less. So, supply will decline much more sharply than demand. Oil demand is expected to grow through 2030 and continue growing to 2040 according to most analysts, but supply will start to decline gradually within five years. This means that, in the future, it will fall on Saudi Arabia to increase its production to meet global oil demand. This is a promising aspect, but we should not rely on it alone.” And after three years, this vision is becoming clearer: both Russia and the United States are striving hard to secure even a small share of the future global energy market. Saudi Arabia had already anticipated this scenario forty years ago by building pipelines to transport and export oil via the Red Sea at full production capacity, without the need to rely on the Strait of Hormuz.

In 2023, the Saudi Crown Prince (MBS) made strong statements about the future of competing oil-producing countries: “For example, the United States will not be an oil-producing country in ten years. Today it produces around 11 million barrels per day; in ten years, it will barely produce 2 million barrels. China currently produces about 4 million barrels domestically, but within four to seven years it will be producing close to zero by 2030, or only a marginal amount. Russia today produces around 11 million barrels, but in 19 years it will produce about 1 million barrels, or slightly more or less. So, supply will decline much more sharply than demand. Oil demand is expected to grow through 2030 and continue growing to 2040 according to most analysts, but supply will start to decline gradually within five years. This means that, in the future, it will fall on Saudi Arabia to increase its production to meet global oil demand. This is a promising aspect, but we should not rely on it alone.” And after three years, this vision is becoming clearer: both Russia and the United States are striving hard to secure even a small share of the future global energy market. Saudi Arabia had already anticipated this scenario forty years ago by building pipelines to transport and export oil via the Red Sea at full production capacity, without the need to rely on the Strait of Hormuz.

🇸🇦

155,195 次观看 • 3 个月前

Micron will be a $4,000 stock and here is why (Save this). As Sanjay Mehrotra puts it "We are only in the early innings of the significant innovation and productivity that can be unleashed in every part of the global economy over time." That is a roadmap and the math behind it points toward something most investors still haven't fully priced in. Q4 revenue guidance came in at $50 billion nearly $7 billion above what Wall Street was expecting for a single quarter. That number alone would have been Micron's entire annual revenue just two years ago and yet data centers are only the first chapter of this story. Mehrotra specifically called out robotics, humanoids, and fully autonomous vehicles as the next demand wave on tonight's call and the numbers behind those markets are genuinely staggering. A Level 4 autonomous vehicle requires over 300GB of DRAM, nearly 20 times more than a standard car today in every single vehicle that rolls off the assembly line. A humanoid robot will require between 64 and 128GB of DRAM and up to 2TB of NAND storage per unit, giving each one a memory footprint comparable to a high end server. There are projections for tens of millions of humanoid robots and hundreds of millions of autonomous vehicles over the next decade, and every single one of them runs on Micron memory. Mehrotra said directly tonight that tight supply conditions are expected to persist beyond calendar 2027 and even with aggressive capital spending Micron can only meet 50 to 67% of medium-term customer demand. Competitors new capacity will not meaningfully come online until late 2027 at the earliest, meaning the pricing environment Micron operates in today has years left to run. There was also 16 Strategic Customer Agreements with $100 billion in minimum committed revenue and $22 billion in customer cash deposits already paid, mean that even when the cycle eventually softens, Micron's floor has been permanently reset at a level no prior version of this company ever reached. Gross margins contractually protected above any peak in the company's prior history, locked through 2030, across half or more of total revenue and that is not a commodity business anymore. Bullish on memory. Follow Melvin for more AI, semis, and the next big market themes.

Micron will be a $4,000 stock and here is why (Save this). As Sanjay Mehrotra puts it "We are only in the early innings of the significant innovation and productivity that can be unleashed in every part of the global economy over time." That is a roadmap and the math behind it points toward something most investors still haven't fully priced in. Q4 revenue guidance came in at $50 billion nearly $7 billion above what Wall Street was expecting for a single quarter. That number alone would have been Micron's entire annual revenue just two years ago and yet data centers are only the first chapter of this story. Mehrotra specifically called out robotics, humanoids, and fully autonomous vehicles as the next demand wave on tonight's call and the numbers behind those markets are genuinely staggering. A Level 4 autonomous vehicle requires over 300GB of DRAM, nearly 20 times more than a standard car today in every single vehicle that rolls off the assembly line. A humanoid robot will require between 64 and 128GB of DRAM and up to 2TB of NAND storage per unit, giving each one a memory footprint comparable to a high end server. There are projections for tens of millions of humanoid robots and hundreds of millions of autonomous vehicles over the next decade, and every single one of them runs on Micron memory. Mehrotra said directly tonight that tight supply conditions are expected to persist beyond calendar 2027 and even with aggressive capital spending Micron can only meet 50 to 67% of medium-term customer demand. Competitors new capacity will not meaningfully come online until late 2027 at the earliest, meaning the pricing environment Micron operates in today has years left to run. There was also 16 Strategic Customer Agreements with $100 billion in minimum committed revenue and $22 billion in customer cash deposits already paid, mean that even when the cycle eventually softens, Micron's floor has been permanently reset at a level no prior version of this company ever reached. Gross margins contractually protected above any peak in the company's prior history, locked through 2030, across half or more of total revenue and that is not a commodity business anymore. Bullish on memory. Follow Melvin for more AI, semis, and the next big market themes.

Melvin

35,969 次观看 • 23 天前