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.Gareth Soloway called the Micron Technology $MU correction to the dot. The interview aired on March 18, right at the top, when Gareth revealed a short position on the Micron stock and since then, it's fallen 25%. Some reports #Google 's TurboQuant algos, which reduces memory consumption of #AI... show more

David Lin

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26,252 Aufrufe • vor 4 Monaten •via X (Twitter)

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$MU is now live on @Solana via Sunrise. Micron reports earnings this Wednesday, one of the most-watched reports in the AI-memory sector. Issued by Backpack 🎒 Securities, $MU brings a tokenized Micron share onchain, trading across Solana 24/7. Own something.

$MU is now live on @Solana via Sunrise. Micron reports earnings this Wednesday, one of the most-watched reports in the AI-memory sector. Issued by Backpack 🎒 Securities, $MU brings a tokenized Micron share onchain, trading across Solana 24/7. Own something.

Sunrise

112,419 Aufrufe • vor 1 Monat

Bank of America just upgraded $MU and memory saying that AI hardware infrastructure spending "is not slowing down." They also said that "the market is underestimating" Micron stock and note it as a "time to buy." Buy every major dip on memory and you will be rich in the future. 1. Sandisk $SNDK 2. Micron $MU All my buy and sell signals in Discord @

Bank of America just upgraded $MU and memory saying that AI hardware infrastructure spending "is not slowing down." They also said that "the market is underestimating" Micron stock and note it as a "time to buy." Buy every major dip on memory and you will be rich in the future. 1. Sandisk $SNDK 2. Micron $MU All my buy and sell signals in Discord @

StockWhale

68,613 Aufrufe • vor 17 Tagen

$Google just had its DeepSeek moment — and almost nobody's talking about it. Here's the story you need to know. 🧵 When DeepSeek dropped in early 2025, it didn't just impress people. It scared them. A model competing with the biggest AI players — at a fraction of the cost — through math, not hardware. Chip stocks tanked. The industry panicked. Then on March 24th, 2026, Google published a research paper called TurboQuant. Cloudflare's CEO immediately called it Google's DeepSeek moment. Memory chip stocks for Micron and Western Digital fell on the news. Why? Because TurboQuant compresses AI memory by 6x — through software alone. → No new chips needed → No retraining required → One server can now host more models than before The era of throwing hardware at AI problems is ending. The era of mathematical efficiency is here. ✅Save this post, you'll thank yourself when this reshapes every AI tool you use. 📌 Want the SOP? DM me.$

Google just had its DeepSeek moment — and almost nobody's talking about it. Here's the story you need to know. 🧵 When DeepSeek dropped in early 2025, it didn't just impress people. It scared them. A model competing with the biggest AI players — at a fraction of the cost — through math, not hardware. Chip stocks tanked. The industry panicked. Then on March 24th, 2026, Google published a research paper called TurboQuant. Cloudflare's CEO immediately called it Google's DeepSeek moment. Memory chip stocks for Micron and Western Digital fell on the news. Why? Because TurboQuant compresses AI memory by 6x — through software alone. → No new chips needed → No retraining required → One server can now host more models than before The era of throwing hardware at AI problems is ending. The era of mathematical efficiency is here. ✅Save this post, you'll thank yourself when this reshapes every AI tool you use. 📌 Want the SOP? DM me.

Julian Goldie SEO

12,731 Aufrufe • vor 3 Monaten

UNUSUAL The CEO of China’s Micron: Apple buys our memory chips for 5 dollars each, then puts them inside a metal casing and sells them to consumers for 99 dollars — and at the same time criticizes Micron when we ask for just 7 dollars. Meanwhile, reports indicate that Apple is in talks to obtain memory chips from the Chinese company CXMT, which was recently added to the U.S. blacklist.

UNUSUAL The CEO of China’s Micron: Apple buys our memory chips for 5 dollars each, then puts them inside a metal casing and sells them to consumers for 99 dollars — and at the same time criticizes Micron when we ask for just 7 dollars. Meanwhile, reports indicate that Apple is in talks to obtain memory chips from the Chinese company CXMT, which was recently added to the U.S. blacklist.

China pulse 🇨🇳

28,381 Aufrufe • vor 28 Tagen

John Gillen: The guy who called Micron at $60 before anyone understood the AI memory bottleneck is now laser-focused on $BTC and $ETH. Jordy Visser (former head of macro at Morgan Stanley) rode Micron from under $100 to $1,200. Now he's saying "a year from now, Bitcoin is going to be the crowded trade. Ethereum is going to be the crowded trade." Retail is usually last to figure this out. And when they do, they're one of the strongest drivers of the bull run. FT John Gillen - WartimeEthereum.eth LG DOUCET Securitize.

John Gillen: The guy who called Micron at $60 before anyone understood the AI memory bottleneck is now laser-focused on $BTC and $ETH. Jordy Visser (former head of macro at Morgan Stanley) rode Micron from under $100 to $1,200. Now he's saying "a year from now, Bitcoin is going to be the crowded trade. Ethereum is going to be the crowded trade." Retail is usually last to figure this out. And when they do, they're one of the strongest drivers of the bull run. FT John Gillen - WartimeEthereum.eth LG DOUCET Securitize.

Milk Road

99,309 Aufrufe • vor 10 Tagen

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 Aufrufe • vor 25 Tagen

Micron is going to $4,000 and once you understand what inference actually is, the number stops sounding crazy (Save this). Dylan Patel just said that by 2030, OpenAI and Anthropic alone will need over 100 gigawatts of compute combined and by 2040, we may not even be measuring AI infrastructure in gigawatts anymore. We may be talking about terawatts. Every single one of those gigawatts needs memory to function. Without it, the compute is worthless. Most people heard that and thought about Nvidia but they should be thinking about Micron. Every AI model generating a response has two phases. The first is prefill, processing your prompt which is compute-heavy and the second is decode generating each word one token at a time and that phase is almost entirely memory-bound, not compute-bound. During decode, the GPU's processing units sit idle more than 95% of the time, waiting for data to arrive from memory. Google confirmed it in a research paper that decode-phase bottlenecks are dominated by memory bandwidth and capacity not raw compute. The GPU is not the bottleneck but the memory feeding the GPU is. This matters because inference is now where all the money lives. Training a model happens once, Inference happens billions of times a day every ChatGPT response, every Claude output, every agentic workflow running in the background and every one of those token streams is a billing event tied directly to memory performance. Adding more GPUs does not fix this because GPUs are already underutilized in inference because they are sitting idle waiting on memory. Adding more memory bandwidth and capacity is what directly reduces token cost, reduces latency, and allows the same cluster to serve dramatically more users simultaneously. Longer context windows compound the problem further, a model running a 1 million token context window requires dramatically more memory per session than a 10,000 token window, and every new model generation pushes context longer. The market treats memory as a downstream beneficiary of Nvidia orders. The correct framework is the opposite, Micron is the upstream constraint on how much value every Nvidia GPU can actually generate at inference scale. Micron guided Q4 to $50 billion in revenue, has HBM4 ramping at twice the pace of the prior generation, and CEO Sanjay Mehrotra has said supply will not catch demand before the end of 2027. At 8x forward earnings on $112 projected FY2027 EPS, Micron is the most undervalued infrastructure company in the entire AI stack. Inference is memory. Memory is Micron and the inference ramp has barely started. Milk Road Pro members are already up massively on this position and we're just getting started. If you want the full breakdown of what we're buying and why, come join us for just a dollar using the link below!

Micron is going to $4,000 and once you understand what inference actually is, the number stops sounding crazy (Save this). Dylan Patel just said that by 2030, OpenAI and Anthropic alone will need over 100 gigawatts of compute combined and by 2040, we may not even be measuring AI infrastructure in gigawatts anymore. We may be talking about terawatts. Every single one of those gigawatts needs memory to function. Without it, the compute is worthless. Most people heard that and thought about Nvidia but they should be thinking about Micron. Every AI model generating a response has two phases. The first is prefill, processing your prompt which is compute-heavy and the second is decode generating each word one token at a time and that phase is almost entirely memory-bound, not compute-bound. During decode, the GPU's processing units sit idle more than 95% of the time, waiting for data to arrive from memory. Google confirmed it in a research paper that decode-phase bottlenecks are dominated by memory bandwidth and capacity not raw compute. The GPU is not the bottleneck but the memory feeding the GPU is. This matters because inference is now where all the money lives. Training a model happens once, Inference happens billions of times a day every ChatGPT response, every Claude output, every agentic workflow running in the background and every one of those token streams is a billing event tied directly to memory performance. Adding more GPUs does not fix this because GPUs are already underutilized in inference because they are sitting idle waiting on memory. Adding more memory bandwidth and capacity is what directly reduces token cost, reduces latency, and allows the same cluster to serve dramatically more users simultaneously. Longer context windows compound the problem further, a model running a 1 million token context window requires dramatically more memory per session than a 10,000 token window, and every new model generation pushes context longer. The market treats memory as a downstream beneficiary of Nvidia orders. The correct framework is the opposite, Micron is the upstream constraint on how much value every Nvidia GPU can actually generate at inference scale. Micron guided Q4 to $50 billion in revenue, has HBM4 ramping at twice the pace of the prior generation, and CEO Sanjay Mehrotra has said supply will not catch demand before the end of 2027. At 8x forward earnings on $112 projected FY2027 EPS, Micron is the most undervalued infrastructure company in the entire AI stack. Inference is memory. Memory is Micron and the inference ramp has barely started. Milk Road Pro members are already up massively on this position and we're just getting started. If you want the full breakdown of what we're buying and why, come join us for just a dollar using the link below!

Milk Road AI

128,522 Aufrufe • vor 26 Tagen

$MU customers are basically telling Micron that memory is no longer something they can casually buy later because AI has turned it into a strategic resource that needs to be secured years in advance. When customers put down deposits, sign multi-year agreements and accept minimum pricing then they're taking on part of the cyclical risk that Micron used to carry alone. Thats why I think Micron deserves to trade at least 15x earnings because a memory company with no visibility deserves a commodity multiple but a memory company with customer deposits, take-or-pay commitments, minimum pricing and multi-year supply agreements deserves more credit for earnings durability.

$MU customers are basically telling Micron that memory is no longer something they can casually buy later because AI has turned it into a strategic resource that needs to be secured years in advance. When customers put down deposits, sign multi-year agreements and accept minimum pricing then they're taking on part of the cyclical risk that Micron used to carry alone. Thats why I think Micron deserves to trade at least 15x earnings because a memory company with no visibility deserves a commodity multiple but a memory company with customer deposits, take-or-pay commitments, minimum pricing and multi-year supply agreements deserves more credit for earnings durability.

Shay Boloor

147,744 Aufrufe • vor 1 Monat

We finished a cycle for memory, and now we're looking for red (4). Buy the dips and can add to memory stocks at the moving averages. Expect tech to remain weaker until the end of the year. 1. Micron $MU 2. Sandisk $SNDK 3. RoundHill Memory ETF $DRAM Make sure you position yourself on these larger red weeks/months ahead so you can make millions on the next bull-run after October. All my buy and sell signals in Discord @

We finished a cycle for memory, and now we're looking for red (4). Buy the dips and can add to memory stocks at the moving averages. Expect tech to remain weaker until the end of the year. 1. Micron $MU 2. Sandisk $SNDK 3. RoundHill Memory ETF $DRAM Make sure you position yourself on these larger red weeks/months ahead so you can make millions on the next bull-run after October. All my buy and sell signals in Discord @

StockWhale

174,750 Aufrufe • vor 20 Tagen

What if the AI bubble was built on an engineered memory shortage? $MU just crashed over 17% from its recent high right as Micron, Samsung, and SK Hynix got hit with a federal lawsuit accusing them of restricting DRAM supply while AI demand sent prices up nearly 700%. The scary part? Samsung and SK Hynix already pleaded guilty to memory chip price fixing once before. And now the entire AI boom runs on their chips.

What if the AI bubble was built on an engineered memory shortage? $MU just crashed over 17% from its recent high right as Micron, Samsung, and SK Hynix got hit with a federal lawsuit accusing them of restricting DRAM supply while AI demand sent prices up nearly 700%. The scary part? Samsung and SK Hynix already pleaded guilty to memory chip price fixing once before. And now the entire AI boom runs on their chips.

Crypto Rover

91,882 Aufrufe • vor 27 Tagen

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 Aufrufe • vor 1 Monat

Investors called Micron $MU frothy after a 50% rally last year but it's up more than 1,000% since then. It's another example that shows how the bears waiting for a market crash have missed a generational bull market. I discuss on Yahoo Finance with Julie Hyman Jake Conley.

Investors called Micron $MU frothy after a 50% rally last year but it's up more than 1,000% since then. It's another example that shows how the bears waiting for a market crash have missed a generational bull market. I discuss on Yahoo Finance with Julie Hyman Jake Conley.

Phil Rosen

23,984 Aufrufe • vor 1 Monat

The most important part of $MU earnings was the strategic customer agreement structure Micron is building around the business. Micron has now signed 16 SCAs with 14 of them representing ~$100B of cumulative revenue at minimum contract pricing over the remaining term which shifts a huge portion of the business away from pure spot-market exposure and toward committed customer demand. Thats why the multiple discussion needs to change because a memory company with no visibility deserves a commodity multiple but a memory company with customer deposits, minimum pricing and long-term supply commitments deserves more credit for earnings durability.

The most important part of $MU earnings was the strategic customer agreement structure Micron is building around the business. Micron has now signed 16 SCAs with 14 of them representing ~$100B of cumulative revenue at minimum contract pricing over the remaining term which shifts a huge portion of the business away from pure spot-market exposure and toward committed customer demand. Thats why the multiple discussion needs to change because a memory company with no visibility deserves a commodity multiple but a memory company with customer deposits, minimum pricing and long-term supply commitments deserves more credit for earnings durability.

Shay Boloor

155,117 Aufrufe • vor 1 Monat

President Trump announced he’ll buy equity stakes in US, AI companies These are the 5 best opportunities in the market right now 1) Micron - $MU 2) Nebius - $NBIS 3) Applied Optoelectronics - $AAOI 4) Credo Technology - $CRDO 5) Marvell Technology- $MRVL AI is just getting started We’re still in the early stages, and this could be one of those once in a generation opportunities you don’t want to look back on and wish you hadn’t missed

President Trump announced he’ll buy equity stakes in US, AI companies These are the 5 best opportunities in the market right now 1) Micron - $MU 2) Nebius - $NBIS 3) Applied Optoelectronics - $AAOI 4) Credo Technology - $CRDO 5) Marvell Technology- $MRVL AI is just getting started We’re still in the early stages, and this could be one of those once in a generation opportunities you don’t want to look back on and wish you hadn’t missed

JUST KAWS

137,637 Aufrufe • vor 1 Monat

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

146,832 Aufrufe • vor 2 Monaten

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 Aufrufe • vor 1 Monat

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 Aufrufe • vor 1 Monat

Elon Musk: AI could be one of the reasons for World War III. “One of the reasons for World War III would be if one country has advanced AI technology, and other powers, worried about some country gaining advanced AI that would give them a strong advantage in war, then they may be tempted to attack before the country that is developing the strong AI has that for use in weapons technology.” Source: WELT interview, March 26, 2022.

Elon Musk: AI could be one of the reasons for World War III. “One of the reasons for World War III would be if one country has advanced AI technology, and other powers, worried about some country gaining advanced AI that would give them a strong advantage in war, then they may be tempted to attack before the country that is developing the strong AI has that for use in weapons technology.” Source: WELT interview, March 26, 2022.

ELON CLIPS

29,959 Aufrufe • vor 11 Tagen

Right now, when you send a query to an LLM, it gets decrypted on the server. The LLM sees your data in plain text. Prof. Ajay Joshi (BU, CipherSonic AI ) on fully homomorphic encryption, which may be key for the future of AI privacy: how we can compute on data without ever decrypting it. The catch: it's a brutally memory-bound workload. Exactly the bottleneck wafer-scale was built to solve.

Right now, when you send a query to an LLM, it gets decrypted on the server. The LLM sees your data in plain text. Prof. Ajay Joshi (BU, CipherSonic AI ) on fully homomorphic encryption, which may be key for the future of AI privacy: how we can compute on data without ever decrypting it. The catch: it's a brutally memory-bound workload. Exactly the bottleneck wafer-scale was built to solve.

Cerebras

293,415 Aufrufe • vor 1 Monat