$ARM Blue Candle: 26%+ … 2026+ is the year of efficiency. $ARM AGI CPU both fit the model. More inference per watt.

Summary: Bullish ARM (26%+ breakout target) and MU as efficiency-driven plays on 2026+ inference-per-watt and memory-per-accelerator buildout.

$ARM Blue Candle: 26%+

2026+ is the year of efficiency. $MU SOCAMM and $ARM AGI CPU both fit the model. More inference per watt. More memory per accelerator. The buildout demands it.

300+ charts daily. Try it free:
https://t.co/ZQDP5HCFyq https://t.co/9YbgJMqM7S

$ARM BLUE candle + Volume Node = Another breakout setup. Same pattern as the ones before it.

ARM's AGI CPU delivers 2x performance per rack at 300W. Hyperscalers get more inference per watt than any x86 alternative.

300+ charts daily. Try it free:
https://t.co/ZQDP5HCFyq https://t.co/P38iiIv97U


$MU SOCAMM and $ARM AGI CPU both fit the model. More inference per watt. More memory per accelerator. The buildout demands it.

structural marker; pre-classified as canonical yfinance ticker


Summary: Author claims MU and SNDK are the next big plays, implying continued upside from current levels, echoing prior 'Bargain of the Century' conviction.

Holy Shit

$SNDK From $214 → $2100
$MU From $62 → 1074

Since my Bargain of the Century callout. Thousands of conviction posts. The receipts are public.

Stop asking what's next. It's staring right at you.

Choose your notifications wisely $DRAM https://t.co/6sbGLJ0pXy

$MU Bargain of the Century

PE Ratio: 15.5
Sales Ratio: 2.33

50% Increase in HBM (AI Memory) Sequentially. DRAM/NAND prices are surging. https://t.co/uTq6YMFnb2


$SNDK From $214 → $2100
$MU From $62 → 1074

Since my Bargain of the Century callout. Thousands of conviction posts. The receipts are public.

Stop asking what's next. It's staring right at you.


Summary: Bullish ARM on technical breakout setup (blue candle + volume node) backed by AGI CPU performance advantage over x86.

$ARM BLUE candle + Volume Node = Another breakout setup. Same pattern as the ones before it.

ARM's AGI CPU delivers 2x performance per rack at 300W. Hyperscalers get more inference per watt than any x86 alternative.

300+ charts daily. Try it free:
https://t.co/ZQDP5HCFyq https://t.co/P38iiIv97U


Summary: Strongly bullish TSM: dismisses Taiwan invasion risk and argues the world cannot function without TSMC, endorsing the $2T market cap thesis.

$TSM Two types of idiots today.

Idiot 1: Believes China will invade Taiwan.

Idiot 2: Has no idea the world literally cannot function without TSMC.

SK Hynix, $MU, $AMD, $ARM, $NVDA, $QCOM, $AVGO and even its foundry competitors $INTC and Samsung all depend on TSMC's advanced nodes for cutting edge silicon and logic.

There is no version of reality in which China invades Taiwan to sabotage the entire global semi & AI economy, including their own, just to make 100 enemies at once. Especially under United State's watch.

I've spoken. $DRAM


Summary: Endorses upside surprise potential in MU EPS, supporting bullish thesis beyond $100 consensus.

@Jespabe Good point! This is the mid-point consensus. So the probabilities of the surprise upsides is there too.

@TradexWhisperer And that's assuming $MU makes $100 EPS. I'm convinced it will be more like $150.


Summary: Long TSMC as the key enabler of co-packaged optics via COUPE/CoWoS integration, with mass production targeted 2H26 and CPO penetration ~35% by 2030.

$TSM is a key enabler of CPO, co-packaged optics. Do not ever forget that.

CPO + CoWoS = Huge Synergy, Moat.

TSMC is actively integrating CPO into CoWoS packages using its COUPE (Compact Universal Photonic Engine) technology.

-The optical engine (PIC + EIC + fiber attach) is co-packaged within the same CoWoS structure.

-This enables "true" CPO where optics sit right next to the compute dies on the interposer/substrate.

Benefits: ~2x better power efficiency, up to 10x lower latency vs. pluggable optics, and better scaling for AI clusters

TSMC is advancing its co-packaged optics (CPO) technology with “COUPE on Substrate,” targeting mass production in the second half of 2026 (2H26). This extends CPO integration to the substrate level, marking a shift in AI chip development toward system-level integration and higher-speed optical interconnects for AI data centers.

$NVDA & Supply Security: If CPO becomes the dominant architecture for future AI servers, NVIDIA may pursue long-term substrate deals, prepayments, or partnerships to secure high-end ABF (Ajinomoto Build-up Film) substrate capacity. This aims to prevent repeats of past shortages in CoWoS and HBM

Substrate Supply Risks: Surging demand from AI GPUs, ASICs, and CPO is expected to cause high-end ABF substrate shortages by 2027. AI chips require 5–10x more ABF material and larger/more layered substrates than traditional CPUs, with tight supply likely persisting due to AI and high-end networking growth.

CPO penetration in AI data center optical modules is projected to reach ~35% by 2030


$MU $70B → $1.2T

Chip Invasion Master Plan Does Not Stop Here.

The Bargain of the Century is not a price target. It is a trajectory.

Summary: Long MU with a $70B→$1.2T market cap trajectory thesis on HBM, surging DRAM/NAND prices, and AI memory demand.

$MU $70B → $1.2T

Chip Invasion Master Plan Does Not Stop Here.

Meta. $280 billion away.

The Bargain of the Century is not a price target. It is a trajectory. $DRAM https://t.co/F3UL1js62I


Summary: Bullish on the 'memory trio' for 5 years; structural shift means the bust cycle stays flat, making current valuations cheap.

Global memory semiconductor basket: MU, Hynix, Samsung, Kioxia

Forward PE 9 right now when the company is super strong means the market is expecting a downturn next 2 years. Market is trying to be "efficient." in fact what market is doing is trying to follow the historical boom and bust but all I've been saying is that I've seen that data and the bust might just be flat even in the most bearish cases so. The shift is structural. The memory trio will make lots of money next 5 years (all projections). Hence why this is cheap. There I defended my thesis.

@TradexWhisperer A thesis requires data yes but not confirmation bias. Anyways, 9 is cheap - that’s my question. You are a data scientist. Does this go deep enough? That’s all I’m asking…


Summary: Author endorses long DRAM/memory play; agrees AI-driven demand is just beginning.

@dramlonger You and I see eye to eye. Long DRAM.

@TradexWhisperer Think imma just hold $MU $SNDK $DRAM for awhile

I work in Finance at a Mag7 company and AI has literally just started - most ppl I know at work haven't even touched Claude Code yet


Summary: Prefers DRAM ETF over individual MU/SK positions; bullish on it.

@M0dermatt I like $DRAM. Not financial advice.

@TradexWhisperer Thank you for the post. Can I please ask, from your pov, is there more upside to be gained by buying MU and SK together on a standalone basis (eg 40/60 weighting), or would you rather buy DRAM to cover all the holdings (granted, at the allocated weight)? Thanks!


Summary: Shares Baird's $500 PT on NVDA implying +132% upside; author adopts bullish stance by sharing.

$NVDA $500 PT from Baird. That's +132% upside. Here's rest. https://t.co/E4u0bUEwAx


Summary: Bullish on MRVL; no view on BB.

@sherryoak12 $MRVL is bullish. No BB on $BB.

@TradexWhisperer Do you have a view on $BB and $MRVL ?


Summary: Expects RDDT upcoming earnings to show good growth; implied bullish.

industry='Internet Content & Information'

@Ap9xoce I think the earnings will show good growth.

@TradexWhisperer RDDT does have sustained momentum.


Summary: Expects Samsung to recover and turn positive next week despite short-term pain.

@JungleStocks So yeah short-term pain but I think samsung will go green next week.

@TradexWhisperer For memory theme yes but for Samsung I'm bot usre its good


Summary: Author calls MU to $1,500 after new all-time high, citing long-held conviction.

$MU New All Time High. Up ~12% today.

$62 to $1,096. Don't ever doubt my conviction.

$1,500 incoming. https://t.co/QWwsjoj4Df


$MU $DRAM Holy Shit … The partnership underscores that memory chips are now critical, specialized AI hardware. The Cognitive Capacity Layer.

Summary: Strongly bullish MU on Micron-Anthropic multi-year AI memory/storage deal including HBM, DRAM, SSDs, and strategic Anthropic investment.

$MU $DRAM Holy Shit

Micron and Anthropic Announce Strategic Agreement to Scale Next-Generation AI Infrastructure

Multi-year memory and storage supply agreement covering Micron’s full data center portfolio, including high-bandwidth memory (HBM), DRAM, and SSDs.

Collaboration on AI architecture design to optimize performance, efficiency, cost, and scaling for Anthropic’s Claude models (training and inference).
Micron is making a strategic investment in Anthropic’s Series H funding round.

Additional elements include enterprise adoption of Claude at Micron and joint analysis of memory/storage performance across AI workloads.

The partnership underscores that memory chips are now critical, specialized AI hardware.

The Cognitive Capacity Layer.


Summary: Confirms long DRAM position.

DRAM sub-sector basket: Micron, SK Hynix, Samsung


Summary: Bullish MU on record FCF trajectory, persistent HBM/DRAM/NAND tightness beyond 2026, AI memory bottleneck, and accelerating HBM4 ramp.

Key quotes and highlights from today's JP Morgan Conference $MU $DRAM $SNDK

"Our financial outlook has strengthened since our last earnings call. We're on track for another substantial record free cash flow in fiscal Q3. Our balance sheet has never been stronger, and that's underscored by multiple credit rating agencies actually from all 3 -- upgrades from all 3 credit rating agencies this year."

"Demand continues to outpace our ability and the industry's ability to supply due to persistent structural factors." Tightness in HBM, DRAM, and NAND is expected to persist "well beyond 2026." Structural issues include slower node transitions, larger HBM die sizes, and longer fab build times.

The AI boom is "still just getting started," with memory as "one of the biggest bottlenecks in the whole system." There's a shift to agentic/machine-to-machine workloads that are more memory-intensive, and memory is now a "strategic asset" for customers (higher performance/reliability directly improves model accuracy).

On technology ramps: Micron is on track for 1-gamma DRAM and Gen9 NAND, with both expected to become the majority of bit output by mid-year. Yields are ramping faster than prior nodes thanks to AI-driven manufacturing optimization.

On HBM progress: HBM4 production ramp is "running at twice the speed" of last year’s HBM3E ramp, with improving yields. It uses Micron’s 1-beta DRAM and in-house base die. Work on HBM4E has begun, with the first JEDEC-standard part ramping in 2027

Nothing short of bullish 🔥


Summary: Held long MU position up significantly from $62 entry; endorses MU as bargain on HBM growth and DRAM/NAND price surge.

$MU $62 + 1167

This is what conviction looks like. https://t.co/jvqthbSWDd


Summary: Bullish MU on valuation gap: generates more profit in one quarter than SpaceX's annual revenue yet trades at 51% lower market cap.

$MU generates more PROFIT in ONE QUARTER than $SPCX generates in revenue ALL YEAR.

$MU is 51% lower in market cap than $SPCX

Read that twice. https://t.co/QOULWHpHnt

---

Just to be clear. I want both companies to be successful. Micron more than SpaceX of course. SpaceX is changing the world. HBM is changing the world.

There is an Elon premium and I respect that. But Sanjay Mehrotra deserves some recognition. He founded SanDisk. He took over Micron and kept it alive competing against Samsung and SK Hynix with their government backing and vertically integrated conglomerates. He is the reason the United States still has a memory industry.

Both are building the future.


Summary: Bullish MU and HBM/DRAM on exponentially growing HBM per GPU from 80GB to 576GB+ with no end in sight.

$MU $DRAM HBM per GPU:

H100: 80GB
H200: 141GB
B200: 192GB
Rubin: 288GB
Rubin Ultra: 576GB

From 80GB to 576GB in five years. 7.2x more memory.

And Rubin Ultra is not the destination. It is the next stop. https://t.co/huLeXGWH9Y

$MU $DRAM

Blackwell needs more HBM than Hopper.

Vera Rubin needs more than Blackwell.

Rubin Ultra needs exponentially more than Vera Rubin

AI inference runs on HBM. And demand is only going one direction. https://t.co/BqVx49fyhX


AI inference runs on HBM. And demand is only going one direction.

HBM sub-sector of DRAM: Micron, SK Hynix, Samsung


Micron is projected to be more profitable than Amazon... The market is still pricing memory like it is 2019. That gap between perception and reality is not a risk. It is the opportunity.

Summary: Strongly bullish MU, Samsung, SK Hynix, SNDK: memory re-rated from cyclical storage to AI cognitive substrate; market still pricing 2019 valuations vs 2027 profitability projections.

$MU $DRAM By 2027:

Micron is projected to be more profitable than Amazon
Samsung more profitable than NVIDIA
SK Hynix more profitable than Microsoft

This is not a cyclical upturn. The purpose of memory itself has fundamentally changed, and the market has not caught up yet.

Think about what happened to NVIDIA. It was a gaming GPU company. Then data centers rewrote its entire identity, turning GPUs into AI Accelerators and its re-valuation followed.

HBM, DRAM, and NAND are no longer storage. They are AI cognitive capacity. More memory means more context. More context means deeper reasoning and greater intelligence. Memory has crossed from passive infrastructure into active substrate for machine intelligence.

The entire relationship between memory and compute has been rewired at a foundational level. The market is still pricing memory like it is 2019. That gap between perception and reality is not a risk. It is the opportunity. $SNDK


Samsung in memory context = Samsung Electronics 005930.KS


Summary: Long DRAM ETF as the all-tiers AI inference play; constituent longs include MU, SNDK, STX, WDC across HBM/DRAM/NAND/HDD.

$DRAM The ticker is misleading. Not because the holdings are wrong. Because the framework most investors are using to evaluate it is wrong.

At its core it covers memory and storage. But even those two words do not do justice to what is actually being captured here. They miss the intelligence entirely.

The right framework for the AI Inference era is Cognitive Capacity. How much can an AI think, reason, retrieve, and remember at any given moment. Not as a hardware specification. As an intelligence ceiling.
That ceiling is built on four tiers. G1 cache through G4 cache. And this single ticker covers all of them.

Here is what each tier does and who owns it.

G1 Tier HBM: The active thinking desk.
Every word you typed. Every word the AI is forming right now. All of it lives here in real time through something called KV Cache. KV Cache is the AI's active attention. It holds every piece of the conversation the model is tracking simultaneously. Bigger desk means more ideas stay in front of the AI while it thinks. The moment the desk fills up ideas fall off and the AI starts forgetting what you said earlier. Shorter answers. Shallower reasoning. Lost context.

SK Hynix. 60% global HBM market share.

$MU Micron. The US pure play.

Samsung. HBM3E yield challenges but catching Up. Potentially HBM4 leader.

G2 Tier DRAM: The overflow desk.
When the main desk fills up work spills here. Model weights live here during active inference. Still faster than anything below it. But the AI has to reach further. Every millisecond of extra reach is throughput the GPU never gets back. The latency gap between G1 and G2 is real and costly at scale.

$MU Micron. DRAM is the core business. SOCAMM2 leader. Potentially 3D DRAM too.

Samsung. Largest DRAM producer by volume globally.

SK Hynix. Strong DRAM portfolio alongside HBM leadership.

Nanya. Commodity DRAM. No HBM roadmap. Serves cost sensitive markets.

G3 Tier NAND: The reference library down the hall.
This is where RAG lives. RAG stands for Retrieval Augmented Generation. When the AI needs to answer something beyond its active context it reaches into an external knowledge base and pulls relevant information back into the response in real time. Think of it as the AI pausing mid thought to look something up in a filing cabinet and continuing the answer with that new information folded in. Every enterprise AI chatbot answering questions about internal documents runs on RAG. The speed and density of NAND determines how fast and how rich that retrieval is. Slower NAND means the AI waits. Waiting means higher cost per token.

$SNDK SanDisk. Pure NAND play. Enterprise SSD leader.

Kioxia. Joint venture partner with SanDisk on NAND wafer supply.

$MU Micron. Samsung. SK Hynix

G4 Tier HDD: The warehouse across town.
Cold storage including cold RAG. The AI does not touch this during a live conversation. But every model ever trained was built from what lives here. Raw training data at petabyte scale. The entire internet. Common Crawl. Books. Code repositories. Video and image datasets for multimodal models. Pre processed training shards waiting for the next training run. Model version archives. Compliance logs. Backup snapshots of the entire AI infrastructure stack.

KV Cache has never lived here. Not once. The physics do not allow it. Spinning magnetic disk runs on microseconds. Active inference needs nanoseconds. HDD was never a candidate.

But hyperscalers are buying petabytes of HDD capacity to store the raw material AI was built from and will keep being built from. That is a real and growing thesis.

$STX Seagate. Pure HDD. Scaling HAMR technology for high capacity AI data lake storage.

$WDC Western Digital. Pure HDD now. HAMR drives targeting 36TB and 44TB configurations for hyperscale AI storage.

AI Inference needs all four tiers firing simultaneously every single time an AI responds to you. Agentic AI raises the stakes even higher. An AI agent does not answer one question and stop. It plans across multiple steps. It holds context across long running tasks. It retrieves external knowledge mid execution. It writes results back. Every step of that loop stresses a different tier of the memory hierarchy. Run out of G1 and the agent loses the thread mid task. Wait on slow G3 retrieval and the agent burns cost per token sitting idle.

That is what makes $DRAM one of the most fitting ETFs ever constructed for the AI Inference and Agentic AI era. $DRAM covers the entire stack.

Long DRAM, I mean Long AI Inference and G1-G4 Cache/Context.


$SNDK SanDisk. Pure NAND play. Enterprise SSD leader.


$STX Seagate. Pure HDD. Scaling HAMR technology for high capacity AI data lake storage.


$WDC Western Digital. Pure HDD now. HAMR drives targeting 36TB and 44TB configurations for hyperscale AI storage.


Summary: Bullish DRAM/HBM: supply cannot reach oversupply as HBM consumes 22% of wafers at 1/3 bit efficiency and keeps growing, precluding any oversupply.

DRAM sector basket: Micron, SK Hynix, Samsung

I know right. Even if HBM wasn't the issue (let's say some other AI memory took off in an alternative universe), DRAM demand would've consumed all wafers  anyway because of AI servers demands (not GPU racks). Now, back to our reality, our universe, the HBM is going to eat 22% of wafers next year and produces 1/3 of DRAM bits produced for the same amount. The crazy part is HBM isn't stopping it's going up every year.

@TradexWhisperer New wafers get swallowed by the hbm density.  I am trying to figure out how we can end up in an over supply situation .
Hint - I cant.


Summary: Deployed most PLTR gains into MU; active long position in Micron.

@DudeWhoInvests It is and I've put most of my $PLTR gains into $MU.

@TradexWhisperer Absolute monster $DRAM is wow dude


Summary: Strongly bullish MU: Micron's SOCAMM first-mover advantage in energy-efficient AI inference will dominate procurement over the next 5 years.

$MU $DRAM $TSM just flagged a major shift in AI chip design priorities. Energy efficiency is now more critical than raw compute power. Surging electricity demand from AI applications is forcing the entire industry to rethink the equation.

This is not a future trend. It is already the buying criteria.

By next year every major procurement decision will have one non negotiable requirement. The new chip must be more energy efficient than what it replaces. No exceptions.

SOCAMM will be huge next 5 years.

Micron was first to this with SOCAMM. Built for energy efficient AI inference at scale.

I've spoken.

$MU In the race for AI dominance, ultra-efficient low-power DRAM will be the ultimate winner for power-hungry data centers.

Micron pioneered this revolution through a five-year collaboration with $NVDA, developing LPDDR5X-based SOCAMM and the advanced SOCAMM2 modules.

2/3 lower https://t.co/L13gw5QPEC


Summary: HBM memory prices will at least double next year; strongly bullish on HBM pricing trajectory.

HBM sub-sector basket: Micron, SK Hynix, Samsung

@athuinvests It did. HBM is going at least double in price next year.

@TradexWhisperer It’s where AI think. Changed everything!


Summary: MU trading at 9x forward PE is seen as deeply undervalued given Mehrotra's legacy and competitive position vs Samsung/Hynix.

Sanjay Mehrotra founded $SNDK. Took $MU from $26 to $1000 competing against memory giants Samsung & SK Hynix.

He is the reason the US still has a memory industry.

Not asking for @elonmusk level recognition. But 9x forward PE for what he built?

That is disrespectful @MicronCEO


Summary: Bullish TSM to $3 trillion market cap; confident long call.

$TSM TMSC will be a $3 trillion company. Very easy. 🤷♂ https://t.co/eujVJOM1e2


Summary: Strongly bullish MU and HBM/DRAM memory on structural AI-driven demand transformation; compiles CEO quotes to argue the supply shortage is durable into 2027-2030.

$MU $DRAM The most powerful CEOs on earth are telling you memory is in a structural transformation.

12 most important quotes.

"The future of artificial intelligence will be shaped as much by memory as by computing power." -Jensen Huang

"Go ahead and build memory fabs; however much capacity you add, NVIDIA will consume it." -Jensen Huang

"The whole industry supply chain, everything from wafers to packaging to silicon photonics... everything's in short supply because the demand is so high. It is going to persist for several years." -Jensen Huang

"The entire supply chain is challenging this year because demand is so much more. Supply has been growing 100% every year, but demand is going faster than that." -Jensen Huang

"I think it will be for quite a few years to come... Demand is so massive." -Jensen Huang

"I would say memory in advanced silicon, it's kind of the 25 times 25... From 80 gig to 2 terabytes is 25 times more memory per accelerator. And in that timeframe, you'll have about 25 times more accelerators. So 25 times 25 is 625 times." -Michael Dell (Dell CEO)

"Demand is in excess of the supply by quite a lot... So we have a severe shortage in memory silicon and also in some other areas." -Michael Dell (Dell CEO)

"As memory per accelerator and system scale expand simultaneously in AI infrastructure, a structure is forming where total memory demand increases by approximately 625 times. We are still in the early stages of technology adoption." -Michael Dell (Dell CEO)

"[US Expansion] is a tiny fraction of the memory that's needed, and in fact, even if you take the best case assumptions of the memory makers... it is not enough to meet the demand that is anticipated." -Elon Musk

"We see that tightness continuing into 2027, so we see durable industry fundamentals over the foreseeable future, driven by AI demand." -Sanjay Mehrotra (Micron CEO)

"AI actually wants to have a lot of HBM, and once you make the HBM...we have to use a lot of wafers... The current shortage could continue until 2030, so we expect more than a 20% shortage of the wafers." -Chey Tae-won (SK Group Chairman)

"Without the HBM memory, there is no AI supercomputer." -Jensen Huang

I've been calling the Context Trade since $62. It was never just my opinion.

What exactly are you waiting for?


$MU $DRAM The most powerful CEOs on earth are telling you memory is in a structural transformation.


Summary: Endorses TSM as a can't-miss holding.

@JapanStockAlpha You can't go wrong with $TSM


Holy Structural Shit… The ripple effect matters more than HBM itself.

Summary: Bullish MU and DRAM broadly: HBM supply constraints drive $3.6T incremental non-HBM revenue upside through 2031.

$MU $DRAM Holy Structural Shit

"HBM sales will add $1.4T in DRAM revenue by 2031 and an incremental $3.6T in non HBM revenue due to higher pricing from HBM related supply constraints."

The ripple effect matters more than HBM itself.

-June Memory Research Report.


HBM sales will add $1.4T in DRAM revenue by 2031 and an incremental $3.6T in non HBM revenue due to higher pricing from HBM related supply constraints.


Summary: DRAM supply never catches up: HBM consumes 30-40% of wafers, new fabs cover only a fraction of demand — structurally bullish MU and DRAM.

$MU $DRAM Wanna know when supply catches up?

→ HBM eats 30% of all DRAM wafers next year. Possibly 40% by 2028.

→ That leaves 60% for everything else, Mobile, PC, Server, Automotive.

→ New fabs are only a fraction of future demand.

Never https://t.co/RVihBIC5cZ


HBM eats 30% of all DRAM wafers next year. Possibly 40% by 2028. New fabs are only a fraction of future demand. Never


Summary: Bullish on Korean memory stocks if South Korea wins; implied long on the sector.

Korean memory stocks: SK Hynix and Samsung Electronics

@rokhardsolid Then let's root for South Korea. Memory Stocks Moon.

@TradexWhisperer Korea winning will send the Kospi to 10K


Summary: Bullish semiconductors over next 5 years; expects massive wealth creation for patient investors.

@suchmoon_ Patient semiconductor investors will become multi millionaires next 5 years.

@TradexWhisperer Thanks for the warm reply!😊

Semiconductors are incredible, right?
I'm certain the field has a massive future ahead!😆

Thank you for supporting Team Japan!⚽
Sending good vibes to Team USA for a win over Australia.🇺🇸

Let's stay in touch!
Sending love from Japan☺

P.S.
By


Summary: Bullish memory stocks (MU, SNDK, DRAM) on Nomura's $1.4T 2030 data-center memory revenue estimate.

$1.4 trillion.

That is Nomura's 2030 Data Center ONLY memory revenue estimate.

Seems a little aggressive but I will take it.

$MU $SNDK $DRAM


Explosive AI demand from Google, Microsoft, Meta, and Amazon has quadrupled memory and storage chip prices since last year. Prices expected to keep rising into 2027.

Summary: Memory/DRAM supercycle driven by AI server demand + consumer AI inflection; prices rising into 2027, bullish MU, SNDK, Kioxia.

$MU $DRAM $SNDK $KIOXIA "100-Year Flood."

$AAPL CEO Tim Cook told WSJ, “Unfortunately, price increases are unavoidable."

Tim Cook called it a "hundred year flood." Unprecedented in his 40+ years.

Apple needs more DRAM for upcoming AI features including a rebooted Siri. Consumer AI is now about to kick in. Second vector.

Explosive AI demand from Google, Microsoft, Meta, and Amazon has quadrupled memory and storage chip prices since last year. AI servers are prioritized, leaving less supply for consumer devices.

Prices expected to keep rising into 2027.


Prices expected to keep rising into 2027.


Kioxia listed on TSE as 285A.T since 2024


Apple needs more DRAM for upcoming AI features including a rebooted Siri. Consumer AI is now about to kick in. Second vector.


Summary: Bullish NVDA; recommends rotating into Nvidia as the core driver of the entire market rally.

@shortelonmusk To show gratitude, I think we should all start taking small profits on memory, optics, servers and CPU and start buying the mothership. Nvidia is the whole reason why the entire market is exploding.

@TradexWhisperer What’s your take on NVDA?


Summary: Bullish on HBM memory; expects a major price surge.

@Junjunjun120511 HBM is going to the moon

@TradexWhisperer 要するに2つとも爆上げで合っていますか？🚀


Summary: Strongly endorses long MU position from parent.


Summary: Prefers TSM over NVDA; decisive buy lean on TSM.

@dramlonger GOAT. WTF is EUV? I like $TSM over $NVDA. Not financial advice.


The discount will not last. The market is applying a cyclical discount to a structural business. That Micron is gone. It's now AI Cognitive Capacity, G1-G3 Context Enabler.

Summary: Bullish MU: market wrongly prices it as cyclical; structural AI business warrants re-rating toward semi sector avg ~34x PE, implying $1,100–$1,600 targets.

$MU Two firms. $1,100 price targets

And $1,600 is still only 16x Forward PE.
Semi sector average: 34x.

The market is applying a cyclical discount to a structural business. That Micron is gone. It's now AI Cognitive Capacity, G1-G3 Context Enabler.

The discount will not last. https://t.co/EsTVmn09oi


It might not be inconceivable that Micron, the supplier of HBMs, might be more valuable than Meta in the next 6 to 12 months. That lines up with the Fibonacci target I shared last month

Summary: Bullish MU over 6–12 months; author endorses Perplexity CEO's thesis that Micron could surpass Meta in market cap, aligning with own prior Fibonacci target.

$MU $DRAM $SNDK

"It might not be inconceivable that Micron, the supplier of HBMs, might be more valuable than Meta in the next 6 to 12 months."

Aravind Srinivas, Perplexity CEO.

That lines up with the Fibonacci target I shared last month: https://t.co/wkOHrQLiXp


Summary: Long GLW: AI data centers need 36x more fiber, severe supply shortages, Meta $6B deal + NVDA $300M investment driving multi-year demand surge with relief not until 2027+.

$GLW AI data centers require 36 times more fiber than designs with standard servers, severe glass shortages push cable lead times out to a full year

Major Chinese manufacturers (Hengtong, FiberHome) are at full capacity with orders booked into early 2027. Delivery times have stretched from weeks to months (or up to a full year for smaller buyers).

Demand surge: Data center fiber demand grew ~76% year-on-year in 2025 and is projected to represent 30% of global fiber demand by 2027 (up from under 5% in 2024).

Regional gap: In North America, demand is growing 22–25% this year while supply expansion lags at 12–19%.

Meta signed a $6 billion multi-year supply deal with Corning.

Nvidia invested $300 million in Corning to build three new U.S. fiber plants (North Carolina and Texas), boosting capacity over 50%.

Corning is also expanding existing facilities, but new production won’t come online until 2027 or later. Fiber preform production itself can take up to two years to scale.

The AI boom is creating another major supply-chain bottleneck (joining power, water, chips, and memory), with relief still 1–2 years away. This is driving up costs and lead times across the industry.

$GLW East-West AI Traffic Bottleneck

AI data centers need 10x more fiber interconnects than traditional cloud setups to enable server-to-server or intra-data center traffic. It just can't keep pace with GPU advancements.

AI Reasoning and Context is fiber hungry. https://t.co/Q2QUqQjyNp