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The recent semiconductor selloff has spread worldwide because the supply chain spans U.S. chip design and cloud spending, Taiwanese manufacturing, Korean memory, Japanese materials, European equipment and Southeast Asian packaging. That makes $MSFT earnings today massive as its June fiscal year-end offers the first major look at spending plans... show more

Shay Boloor

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78,929 görüntüleme • 12 gün önce •via X (Twitter)

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If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.

If $MU confirms tomorrow that DRAM, NAND and HBM tightness can last into 2027 or 2028 then memory companies have more reason to keep spending on capacity and advanced manufacturing tools. That matters for $ASML because it sits at the most important equipment layer of the semiconductor supply chain where more advanced memory capacity means more demand for lithography systems.

Shay Boloor

430,868 görüntüleme • 1 ay önce

I said earlier in the week that $MSFT could be the catalyst that reminded investors the AI buildout was nowhere near over. That is exactly what happened as Microsoft’s June fiscal year-end gave the first major look into first half of 2027 spending and confirmed demand remains above capacity across chips, memory, networking, optics, packaging, power and equipment. Then this morning we learned why the suppliers sold off since Leopold Aschenbrenner’s Situational Awareness ran ~$24B at up to 4x leverage with $NBIS, $SNDK, $CRWV, $IREN, $BE and $TE among its largest positions and was forced to dump its entire public book in one block. The AI infrastructure thesis never broke but the leveraged fund behind the selling did.

I said earlier in the week that $MSFT could be the catalyst that reminded investors the AI buildout was nowhere near over. That is exactly what happened as Microsoft’s June fiscal year-end gave the first major look into first half of 2027 spending and confirmed demand remains above capacity across chips, memory, networking, optics, packaging, power and equipment. Then this morning we learned why the suppliers sold off since Leopold Aschenbrenner’s Situational Awareness ran ~$24B at up to 4x leverage with $NBIS, $SNDK, $CRWV, $IREN, $BE and $TE among its largest positions and was forced to dump its entire public book in one block. The AI infrastructure thesis never broke but the leveraged fund behind the selling did.

Shay Boloor

242,344 görüntüleme • 11 gün önce

Jensen Huang just said the semiconductor industry needs to grow 5-10x over the next decade and he named the exact bottlenecks investors should be watching (Save this). His argument is that this isn't a normal cyclical boom that will bust like past chip cycles because it's driven by a structural shift, the world needs a whole new intelligence layer of infrastructure on top of energy, internet, and roads and that layer runs entirely on chips. Using WSTS's 2026 industry estimate of $1.5 trillion, a 5-10x expansion would put the semiconductor industry at roughly $7.5 trillion to $15 trillion within ten years. He specifically called out five areas that are already in shortage, memory, storage, optical interconnects, packaging, and TSMC foundry capacity, and said the whole industry is short because this is infrastructure demand, not seasonal demand. Here's who stands to benefit in each of those five bottlenecks he named. Memory and storage is the most direct beneficiary, since Micron is the only major US based DRAM and NAND producer and has been reporting surging prices tied to AI server demand while SK Hynix and Samsung, both foreign, dominate the high bandwidth memory that feeds directly into GPUs like Nvidia's. Optical interconnects benefits companies like Coherent and Lumentum which make the optical transceivers moving data between GPU clusters, alongside Credo Technology, which makes high speed interconnect chips for the same data movement problem inside AI clusters. Packaging is where Nvidia's own chips get bottlenecked, since advanced packaging capacity mostly sits with TSMC, but Amkor Technology and ASE Technology are the independent outsourced packaging players that pick up overflow demand when TSMC can't keep up. Chip equipment makers that supply the tools needed to actually build more capacity across all these bottlenecks also benefit, including ASML for lithography, and Lam Research, KLA Corporation and Applied Materials for etching, deposition, and inspection equipment, since a 5-10x industry expansion requires massive new fab buildout that all runs through these companies first. Milk Road Pro is tracking the entire supply chain bottlenecks, if you want our entire AI trades around this, you can come join us just for a dollar.

Jensen Huang just said the semiconductor industry needs to grow 5-10x over the next decade and he named the exact bottlenecks investors should be watching (Save this). His argument is that this isn't a normal cyclical boom that will bust like past chip cycles because it's driven by a structural shift, the world needs a whole new intelligence layer of infrastructure on top of energy, internet, and roads and that layer runs entirely on chips. Using WSTS's 2026 industry estimate of $1.5 trillion, a 5-10x expansion would put the semiconductor industry at roughly $7.5 trillion to $15 trillion within ten years. He specifically called out five areas that are already in shortage, memory, storage, optical interconnects, packaging, and TSMC foundry capacity, and said the whole industry is short because this is infrastructure demand, not seasonal demand. Here's who stands to benefit in each of those five bottlenecks he named. Memory and storage is the most direct beneficiary, since Micron is the only major US based DRAM and NAND producer and has been reporting surging prices tied to AI server demand while SK Hynix and Samsung, both foreign, dominate the high bandwidth memory that feeds directly into GPUs like Nvidia's. Optical interconnects benefits companies like Coherent and Lumentum which make the optical transceivers moving data between GPU clusters, alongside Credo Technology, which makes high speed interconnect chips for the same data movement problem inside AI clusters. Packaging is where Nvidia's own chips get bottlenecked, since advanced packaging capacity mostly sits with TSMC, but Amkor Technology and ASE Technology are the independent outsourced packaging players that pick up overflow demand when TSMC can't keep up. Chip equipment makers that supply the tools needed to actually build more capacity across all these bottlenecks also benefit, including ASML for lithography, and Lam Research, KLA Corporation and Applied Materials for etching, deposition, and inspection equipment, since a 5-10x industry expansion requires massive new fab buildout that all runs through these companies first. Milk Road Pro is tracking the entire supply chain bottlenecks, if you want our entire AI trades around this, you can come join us just for a dollar.

Milk Road AI

28,384 görüntüleme • 17 gün önce

🚨 We’re getting our first look at what SpaceX’s Terafab facility will look like in Grimes County, TX just outside Bryan-College Station. 💬 From SpaceX : “The foundations for an exciting future are being built in Texas. Earlier this year, SpaceX and Tesla announced Terafab – the most epic-chip building effort in the world – combining logic, memory and advanced packaging all under one roof. In April, Tesla broke ground on a new research fab on the North Campus of Giga Texas – the precursor to Terafab. And today, we are announcing that Terafab will be built in Grimes County, Texas. The facility will be an advanced semiconductor fab that will bridge the divide between current global chip supply and the compute demand of the future.” Find our coverage on KBTX’s app and website!

🚨 We’re getting our first look at what SpaceX’s Terafab facility will look like in Grimes County, TX just outside Bryan-College Station. 💬 From SpaceX : “The foundations for an exciting future are being built in Texas. Earlier this year, SpaceX and Tesla announced Terafab – the most epic-chip building effort in the world – combining logic, memory and advanced packaging all under one roof. In April, Tesla broke ground on a new research fab on the North Campus of Giga Texas – the precursor to Terafab. And today, we are announcing that Terafab will be built in Grimes County, Texas. The facility will be an advanced semiconductor fab that will bridge the divide between current global chip supply and the compute demand of the future.” Find our coverage on KBTX’s app and website!

Rusty Surette

17,557 görüntüleme • 4 gün önce

$ORCL is borrowing aggressively to build AI data centers for a customer base heavily tied to OpenAI and the market is starting to question whether Oracle can fund that buildout without $MSFT, $GOOGL, $AMZN or $META level cash generation. The upside is that OCI now has one of the largest AI backlogs in the market at ~$640B which gives Oracle a real shot at becoming the fourth major AI cloud platform if that demand converts into durable revenue. If cloud growth stays above 50% and customer prepayments ease the funding burden then this selloff could eventually look like the painful capital cycle before the harvest phase.

$ORCL is borrowing aggressively to build AI data centers for a customer base heavily tied to OpenAI and the market is starting to question whether Oracle can fund that buildout without $MSFT, $GOOGL, $AMZN or $META level cash generation. The upside is that OCI now has one of the largest AI backlogs in the market at ~$640B which gives Oracle a real shot at becoming the fourth major AI cloud platform if that demand converts into durable revenue. If cloud growth stays above 50% and customer prepayments ease the funding burden then this selloff could eventually look like the painful capital cycle before the harvest phase.

Shay Boloor

132,000 görüntüleme • 1 ay önce

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

260,701 görüntüleme • 1 ay önce

Many still don’t understand why Elon is building Terafab Terafab is an extension to all the chip makers in the world It’s not about replacement, not a rivalry and absolutely not competing It’s being built to fulfill the massive chip orders that Tesla, SpaceX and xAI actually need TSMC’s most advanced 2nm capacity is totally booked through 2028 Tesla signed a massive $16.5 billion deal with Samsung back in July 2025 to produce AI6 chips at their Taylor, Texas factory and Samsung is building a Tesla Exclusive chip manufacturing plant to full fill this orders When Elon announced Terafab on March 21, 2026...he made it clear: “That rate is much less than we’d like. We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab” He basically told the chip makers: “Produce as much as you comfortably can. We will take them all. Actually we want even more” Even today Elon said: "SpaceX/Tesla will be always be major customers of TSMC and not competitors in the normal sense of the word" Current production rates are much less than they need....That’s why Terafab exists Terafab is an extension to every chip maker… not competition, not rivalry, absolutely not Even Intel has joined as a partner Even if chip supply improves, massive bottlenecks still exist with memory and advanced packaging You simply can't risk those supply chain breaks at this scale That’s why Terafab is being built to vertically integrate everything - chips, memory, advanced packaging all under one roof, targeting 1 terawatt of AI compute capacity per year This is a ludicrous amount of chips that no chipmaker currently produces at this scale. I don't think even TSMC and Samsung truly understand these numbers yet It’s about building the capacity the future actually demands

Many still don’t understand why Elon is building Terafab Terafab is an extension to all the chip makers in the world It’s not about replacement, not a rivalry and absolutely not competing It’s being built to fulfill the massive chip orders that Tesla, SpaceX and xAI actually need TSMC’s most advanced 2nm capacity is totally booked through 2028 Tesla signed a massive $16.5 billion deal with Samsung back in July 2025 to produce AI6 chips at their Taylor, Texas factory and Samsung is building a Tesla Exclusive chip manufacturing plant to full fill this orders When Elon announced Terafab on March 21, 2026...he made it clear: “That rate is much less than we’d like. We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab” He basically told the chip makers: “Produce as much as you comfortably can. We will take them all. Actually we want even more” Even today Elon said: "SpaceX/Tesla will be always be major customers of TSMC and not competitors in the normal sense of the word" Current production rates are much less than they need....That’s why Terafab exists Terafab is an extension to every chip maker… not competition, not rivalry, absolutely not Even Intel has joined as a partner Even if chip supply improves, massive bottlenecks still exist with memory and advanced packaging You simply can't risk those supply chain breaks at this scale That’s why Terafab is being built to vertically integrate everything - chips, memory, advanced packaging all under one roof, targeting 1 terawatt of AI compute capacity per year This is a ludicrous amount of chips that no chipmaker currently produces at this scale. I don't think even TSMC and Samsung truly understand these numbers yet It’s about building the capacity the future actually demands

X Freeze

53,291 görüntüleme • 3 ay önce

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

Shay Boloor

261,814 görüntüleme • 2 ay önce

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

235,568 görüntüleme • 1 ay önce

Elon Musk said Tesla will soon reveal the location and full plans for Terafab and the announcement will get its own dedicated spotlight: “Terafab is going to be an amazing initiative and a necessary one Without it, we will be constrained in our ability to scale Optimus production because we simply will not have enough AI chips We have to solve memory, logic and packaging in order to scale Optimus” Tesla has already placed equipment orders for a development fab in Austin that will bring: • Lithography mask production • Logic chips • Memory • Advanced packaging • Chip testing All under one roof This would allow Tesla to design a new AI chip, manufacture it, package it, test it and quickly iterate on the next version from the same facility A building like this does not exist anywhere else on Earth Terafab is not just another factory It is going to become the chip-development engine Tesla needs to scale Optimus and pursue high-risk, high-reward AI hardware breakthroughs at unprecedented speed

Elon Musk said Tesla will soon reveal the location and full plans for Terafab and the announcement will get its own dedicated spotlight: “Terafab is going to be an amazing initiative and a necessary one Without it, we will be constrained in our ability to scale Optimus production because we simply will not have enough AI chips We have to solve memory, logic and packaging in order to scale Optimus” Tesla has already placed equipment orders for a development fab in Austin that will bring: • Lithography mask production • Logic chips • Memory • Advanced packaging • Chip testing All under one roof This would allow Tesla to design a new AI chip, manufacture it, package it, test it and quickly iterate on the next version from the same facility A building like this does not exist anywhere else on Earth Terafab is not just another factory It is going to become the chip-development engine Tesla needs to scale Optimus and pursue high-risk, high-reward AI hardware breakthroughs at unprecedented speed

X Freeze

18,749 görüntüleme • 19 gün önce

If $MU says NAND pricing is still strong, enterprise SSD demand is picking up and AI inference is creating more storage demand then $SNDK should benefit because SanDisk is one of the more direct ways to own that part of the cycle. Hyperscalers are still figuring out the right mix of DRAM, HBM, TLC NAND, QLC NAND and other storage architectures which can keep supply tighter for longer as memory companies are going to be hesitant to add too much capacity before demand becomes clearer. I'm going to be listening closely for Micron’s QLC commentary because QLC NAND for read-heavy inference workloads is the big driver and if Micron calls that out then it would show that the storage side of the AI memory story is still earlier than DRAM.

If $MU says NAND pricing is still strong, enterprise SSD demand is picking up and AI inference is creating more storage demand then $SNDK should benefit because SanDisk is one of the more direct ways to own that part of the cycle. Hyperscalers are still figuring out the right mix of DRAM, HBM, TLC NAND, QLC NAND and other storage architectures which can keep supply tighter for longer as memory companies are going to be hesitant to add too much capacity before demand becomes clearer. I'm going to be listening closely for Micron’s QLC commentary because QLC NAND for read-heavy inference workloads is the big driver and if Micron calls that out then it would show that the storage side of the AI memory story is still earlier than DRAM.

Shay Boloor

108,953 görüntüleme • 1 ay önce

Semiconductors are on track for their worst month since 2022 as several macro shocks hit the market’s most crowded trade at once. The market going back into "war mode" raised fears around oil, inflation, interest rates and supply chains breaking momentum before concerns over AI infrastructure returns and Kimi K3 revived many of the same fears that followed DeepSeek. I view this as a macro and positioning reset rather than evidence that the AI cycle is breaking simultaneously across every layer of the semiconductor supply chain from $NVDA, $AMD and $INTC to $TSM, $ASML $MU, $SKHY.

Semiconductors are on track for their worst month since 2022 as several macro shocks hit the market’s most crowded trade at once. The market going back into "war mode" raised fears around oil, inflation, interest rates and supply chains breaking momentum before concerns over AI infrastructure returns and Kimi K3 revived many of the same fears that followed DeepSeek. I view this as a macro and positioning reset rather than evidence that the AI cycle is breaking simultaneously across every layer of the semiconductor supply chain from $NVDA, $AMD and $INTC to $TSM, $ASML $MU, $SKHY.

Shay Boloor

74,383 görüntüleme • 13 gün önce

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

567,606 görüntüleme • 5 ay önce

Broadcom's CEO just exposed the real fight underneath Google's AI chip strategy. It is not Google versus Broadcom. It is Google and Broadcom trying to make Nvidia replaceable. Within two minutes at Bloomberg Tech, Hock Tan was asked whether Google bringing more chip design in house keeps him up at night. His exact words: "So we just compete against my own customer." Then he named the real enemy: "the real competitor facing all this is the GPU out of Nvidia." That is the part most people miss. Custom AI chips are not just cheaper GPUs. They are ownership claims. If Google owns the workload, the compiler stack, the cloud customer, and the TPU roadmap, Nvidia becomes a benchmark instead of the toll booth. But Broadcom is still in the room because independence is not binary. The hard part is not drawing a chip. The hard part is shipping generation after generation at scale, matching Nvidia's cadence, keeping networking tight, and making the whole system useful enough that developers do not care what silicon sits underneath. That is why Tan can say Google is trying to create customer owned tooling and still sound calm. Broadcom is not selling picks and shovels. It is selling the bridge out of Nvidia dependency. The numbers explain why this is suddenly a board level issue. Broadcom reported $22.2 billion of Q2 2026 revenue. Its AI semiconductor revenue hit $10.8 billion, up 143 percent year over year. For Q3, Broadcom guided AI semiconductor revenue to $16.0 billion, up more than 200 percent year over year. In the clip, Tan says Broadcom has exactly 6 custom AI accelerator customers. He says OpenAI has been engaged for over 2 years, its accelerator is already working in labs and data centers, and production is on track for late this year. That is the hidden mechanism: The AI labs are not becoming software companies with some chips attached. They are becoming capacity companies with model interfaces attached. Once your margin depends on tokens, latency, memory bandwidth, power contracts, packaging slots, networking gear, and a private accelerator schedule, the "model company" label starts to look like a costume. The precedent is Apple. Apple did not move into custom silicon because it wanted a cute chip branding story. It moved because the iPhone needed control over performance per watt, release cadence, and differentiation. A series chips in 2010. M1 in 2020. More than a decade of slowly pulling the bottleneck inside the company. But Apple still needed TSMC. That is the useful analogy for Google, OpenAI, and the other AI giants. They want Nvidia's margin pool. They want Nvidia's roadmap power. They want Nvidia's ability to decide who gets capacity first. But the first supplier they replace becomes the supplier they cannot live without. Broadcom is the customs officer at the border of private silicon. Second order consequence: AI company valuation will shift from model demos to infrastructure custody. Who owns the workload? Who controls the accelerator roadmap? Who has memory secured? Who can afford to keep a bad first generation alive long enough to get to the second and third? My bet: by the end of 2027, at least one major AI lab will be judged more by its custom chip execution than by its model benchmark lead. The model race is public. The margin race is being negotiated in silicon.

Broadcom's CEO just exposed the real fight underneath Google's AI chip strategy. It is not Google versus Broadcom. It is Google and Broadcom trying to make Nvidia replaceable. Within two minutes at Bloomberg Tech, Hock Tan was asked whether Google bringing more chip design in house keeps him up at night. His exact words: "So we just compete against my own customer." Then he named the real enemy: "the real competitor facing all this is the GPU out of Nvidia." That is the part most people miss. Custom AI chips are not just cheaper GPUs. They are ownership claims. If Google owns the workload, the compiler stack, the cloud customer, and the TPU roadmap, Nvidia becomes a benchmark instead of the toll booth. But Broadcom is still in the room because independence is not binary. The hard part is not drawing a chip. The hard part is shipping generation after generation at scale, matching Nvidia's cadence, keeping networking tight, and making the whole system useful enough that developers do not care what silicon sits underneath. That is why Tan can say Google is trying to create customer owned tooling and still sound calm. Broadcom is not selling picks and shovels. It is selling the bridge out of Nvidia dependency. The numbers explain why this is suddenly a board level issue. Broadcom reported $22.2 billion of Q2 2026 revenue. Its AI semiconductor revenue hit $10.8 billion, up 143 percent year over year. For Q3, Broadcom guided AI semiconductor revenue to $16.0 billion, up more than 200 percent year over year. In the clip, Tan says Broadcom has exactly 6 custom AI accelerator customers. He says OpenAI has been engaged for over 2 years, its accelerator is already working in labs and data centers, and production is on track for late this year. That is the hidden mechanism: The AI labs are not becoming software companies with some chips attached. They are becoming capacity companies with model interfaces attached. Once your margin depends on tokens, latency, memory bandwidth, power contracts, packaging slots, networking gear, and a private accelerator schedule, the "model company" label starts to look like a costume. The precedent is Apple. Apple did not move into custom silicon because it wanted a cute chip branding story. It moved because the iPhone needed control over performance per watt, release cadence, and differentiation. A series chips in 2010. M1 in 2020. More than a decade of slowly pulling the bottleneck inside the company. But Apple still needed TSMC. That is the useful analogy for Google, OpenAI, and the other AI giants. They want Nvidia's margin pool. They want Nvidia's roadmap power. They want Nvidia's ability to decide who gets capacity first. But the first supplier they replace becomes the supplier they cannot live without. Broadcom is the customs officer at the border of private silicon. Second order consequence: AI company valuation will shift from model demos to infrastructure custody. Who owns the workload? Who controls the accelerator roadmap? Who has memory secured? Who can afford to keep a bad first generation alive long enough to get to the second and third? My bet: by the end of 2027, at least one major AI lab will be judged more by its custom chip execution than by its model benchmark lead. The model race is public. The margin race is being negotiated in silicon.

Andrej Drats

10,572 görüntüleme • 1 ay önce

$CBRS is a very unique company because it keeps a huge amount of compute and memory very close together which helps it deliver extremely fast inference and makes the architecture well positioned for agentic AI workloads where fast tokens matter more. OpenAI validated the tec but the stock is getting hit because we still don't have enough visibility into how Cerebras turns that technical advantage into a broad, diversified and high-margin business. Customer concentration remains a massive risk especially with so much revenue tied to its own investor and the company still has to solve the physical infrastructure side of the business across power, cooling, data center capacity and deployment timing. If $NVDA is trading at a below-market multiple while still growing faster than Cerebras then why buy the Nvidia alternative instead of just owning Nvidia?

$CBRS is a very unique company because it keeps a huge amount of compute and memory very close together which helps it deliver extremely fast inference and makes the architecture well positioned for agentic AI workloads where fast tokens matter more. OpenAI validated the tec but the stock is getting hit because we still don't have enough visibility into how Cerebras turns that technical advantage into a broad, diversified and high-margin business. Customer concentration remains a massive risk especially with so much revenue tied to its own investor and the company still has to solve the physical infrastructure side of the business across power, cooling, data center capacity and deployment timing. If $NVDA is trading at a below-market multiple while still growing faster than Cerebras then why buy the Nvidia alternative instead of just owning Nvidia?

Shay Boloor

197,484 görüntüleme • 1 ay önce

Micron is going to $4,000 and this exactly why (Save this). Hyperscaler Capex, the combined spending of Amazon, Google, Meta, Microsoft and Oracle was $261 billion in 2024 and it hit $449 billion in 2025. Morgan Stanley now expects $805 billion in 2026 and $1.1 trillion in 2027. Memory consistently runs at 35–48% of that total hardware spend, apply that range to Morgan Stanley's numbers and you get somewhere between $280 billion and $530 billion flowing into memory stocks over the next two years alone. That is the market Micron is selling into right now and the company just reported $41.5 billion in revenue in a single quarter with 85% gross margins. But data centers are only the first wave. L2+ vehicles, cars with meaningful driver assistance carry over five times the memory of a standard car and that mix is doubling to over 20% of all vehicles sold this year, and Micron expects it to hit 40% by 2030. Autonomous vehicles will require over 300 gigabytes of DRAM per car, an 18x increase in memory content per unit, applied across tens of millions of cars a year. The third wave is the one that makes automotive look small, humanoid robots. A humanoid robot carries 10 times the memory of an average L2 vehicle. Tesla, Figure, and a growing list of US robotics companies are still in the very early stages while China is already scaling humanoid production fast. When the US robotics boom arrives and it will, the memory requirement per unit is orders of magnitude larger than anything that has come before. The one risk worth naming is if the hyperscalers signal a pause in spending in 2027, that puts real pressure on the thesis. But Morgan Stanley has raised their capex forecast by $630 billion in six months alone. The data center boom is already here,the car boom is arriving and the robotics boom hasn't started yet. Micron is the only US-based company that can supply all three. Follow me Melvin for more AI, semis and the next big market themes.

Micron is going to $4,000 and this exactly why (Save this). Hyperscaler Capex, the combined spending of Amazon, Google, Meta, Microsoft and Oracle was $261 billion in 2024 and it hit $449 billion in 2025. Morgan Stanley now expects $805 billion in 2026 and $1.1 trillion in 2027. Memory consistently runs at 35–48% of that total hardware spend, apply that range to Morgan Stanley's numbers and you get somewhere between $280 billion and $530 billion flowing into memory stocks over the next two years alone. That is the market Micron is selling into right now and the company just reported $41.5 billion in revenue in a single quarter with 85% gross margins. But data centers are only the first wave. L2+ vehicles, cars with meaningful driver assistance carry over five times the memory of a standard car and that mix is doubling to over 20% of all vehicles sold this year, and Micron expects it to hit 40% by 2030. Autonomous vehicles will require over 300 gigabytes of DRAM per car, an 18x increase in memory content per unit, applied across tens of millions of cars a year. The third wave is the one that makes automotive look small, humanoid robots. A humanoid robot carries 10 times the memory of an average L2 vehicle. Tesla, Figure, and a growing list of US robotics companies are still in the very early stages while China is already scaling humanoid production fast. When the US robotics boom arrives and it will, the memory requirement per unit is orders of magnitude larger than anything that has come before. The one risk worth naming is if the hyperscalers signal a pause in spending in 2027, that puts real pressure on the thesis. But Morgan Stanley has raised their capex forecast by $630 billion in six months alone. The data center boom is already here,the car boom is arriving and the robotics boom hasn't started yet. Micron is the only US-based company that can supply all three. Follow me Melvin for more AI, semis and the next big market themes.

Melvin

27,296 görüntüleme • 1 ay önce

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

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

105,024 görüntüleme • 26 gün önce

Brad took so much heat here for saying memory may not be cyclical this time. I would normally be very hesitant to claim something that has historically been cyclical is no longer cyclical, but I think it may be correct this time. As the required memory capacity and bandwidth grow, HBM turns something like a process business rather than a product business. Vertically connecting DRAM stacks into a HBM has gone through two generationa of bonding tech, thermal compression bonding and mass reflow molded underfill, and now the next-gen hybrid bonding is coming. Each generation required more capex and expertise, and this will continue through generations. Meanwhile bandwidth and capacity demand from AI accelerators will keep growing vertically. This will create an environment where only the incumbents with strong cash flows will be able to make necessary capex spending and customers won’t risk diversifying away, keeping the process expertise trapped with the incumbents, just like it happened with $TSM in foundry business. So, memory names can really be ridiculously cheap.

Brad took so much heat here for saying memory may not be cyclical this time. I would normally be very hesitant to claim something that has historically been cyclical is no longer cyclical, but I think it may be correct this time. As the required memory capacity and bandwidth grow, HBM turns something like a process business rather than a product business. Vertically connecting DRAM stacks into a HBM has gone through two generationa of bonding tech, thermal compression bonding and mass reflow molded underfill, and now the next-gen hybrid bonding is coming. Each generation required more capex and expertise, and this will continue through generations. Meanwhile bandwidth and capacity demand from AI accelerators will keep growing vertically. This will create an environment where only the incumbents with strong cash flows will be able to make necessary capex spending and customers won’t risk diversifying away, keeping the process expertise trapped with the incumbents, just like it happened with $TSM in foundry business. So, memory names can really be ridiculously cheap.

Oguz Erkan

77,171 görüntüleme • 3 ay önce

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."

$MU $SKHY $DRAM Holy Shit $AMD's Lisa Su just spent two full minutes at the 2026 AI keynote raving about HBM4 capacity as the thing that separates Helios from the competition. Not compute. Memory. "When you compare Helios to the competition, we're delivering 15% more compute, 50% more HBM4 memory capacity and memory bandwidth, and 50% more scale-out bandwidth." Notice which number is bigger. "What that means is that every Helios can deliver more performance for the largest models, more capacity for longer context, and the bandwidth to scale across thousands of racks.... More than 18,000 CDNA five GPU compute units, over 4,600 Zen 6 CPU cores, and 31 terabytes of HBM4 memory, all in a single rack." "That's what it takes to run agentic AI at scale. Today, I'm excited to announce that Helios is in full production. We have shipments on track to start at the end of the third quarter and ramping into the fourth quarter in the second half of the year. I can tell you, customer demand for Helios is extremely strong, we're extremely proud of the work that we have done across the leading AI labs to adopt Helios."

Trade Whisperer

179,812 görüntüleme • 18 gün önce