Hi! This is a hate-free zone, where I research Memory, Semis, Power, Robots, Space, data centers, and aligned areas.
Houston
Joined March 2009
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Jim P., down in Texas retweeted
20 AI stocks with massive projected EPS growth next year!
1. $SPCX | SpaceX | +24,472%
2. $AAOl | Applied Optoelectronics | +576%
3. $AMD | Advanced Micro Devices | +107%
4. $SMTC | Semtech | +84%
5. $BE | Bloom Energy | +82%
6. $CLS | Celestica | +78%
7. $MRVL | Marvell Technology| +74%
8. $NVDA | NVIDIA +72%
9. $GEV | GE Vernova | +68%
10. $AVGO | Broadcom | +66%
11. $LITE | Lumentum | +65%
12. $CIEN | Ciena +65%
13. $WDC | Western Digital | +61%
14. $ALAB | Astera Labs | +58%
15. $MOD | Modine Manufacturing | +55%
16. $CRDO | Credo Technology | +53%
17. $TTMI | TTM Technologies | +52%
18. $COHR | Coherent | +49%
19. $PLTR | Palantir Technologies | +45%
20. $AMAT Applied Materials | +44%
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Jim P., down in Texas retweeted
The HBM market is setting up for one of the BIGGEST supply demand imbalances in the entire AI buildout.
Just look at what Bloomberg Intelligence is projecting. HBM shipments could grow from roughly 2.5 billion GB in 2025 to nearly 18 billion GB by 2030. That's approximately a 7X increase in volume in just FIVE years. Normally, when an industry dramatically increases production, you would expect prices to decline as supply catches up with demand. Yet Bloomberg's projections are showing the complete opposite. Average HBM prices are expected to climb from roughly $13 per GB in 2025 to $35 per GB by 2030. Think about how insane that is. We're potentially looking at a market where shipments increase roughly 7X while average selling prices nearly triple.
And this is exactly why I'm so bullish on memory. Every new generation of AI accelerators requires increasingly sophisticated memory to deliver the bandwidth needed to keep those GPUs running efficiently. And as models become larger, inference workloads explode, and autonomous agents and physical AI begin scaling, the demand for memory is only going to accelerate. What makes HBM particularly interesting is that supply cannot simply expand overnight. Manufacturing HBM requires advanced packaging, complex stacking processes, enormous capital investment, and significant production capacity. Not to mention, expanding HBM production can consume manufacturing capacity that would otherwise go toward conventional DRAM, potentially tightening supply across the broader memory market as well. This is why I continue to believe memory is one of the most attractive opportunities in the AI infrastructure trade.
South Korea's stock market is in FREE FALL and the panic surrounding the memory trade is getting completely out of control.
The KOSPI just plunged another 7%, bringing its decline to roughly 40% from its June highs. Samsung and SK Hynix are getting absolutely destroyed, and the selling pressure is spreading across the entire AI infrastructure trade. I went on Making Money with @cvpayne today to talk about the memory selloff and why I believe investors are losing sight of what's actually happening in this industry.
And now we're getting ANOTHER warning out of South Korea. A new column published by Maeil Business Newspaper is raising concerns that the global memory industry could face oversupply beginning in 2029 as new manufacturing capacity starts coming online. The argument is that South Korea has become increasingly dependent on Samsung and SK Hynix, and that the country has roughly two to three years to develop other growth industries before the memory cycle potentially reverses. Now, I think this is something investors should absolutely pay attention to but here's where I disagree with the panic.
We're talking about a potential oversupply problem in 2029 while the industry is still struggling to meet demand TODAY. Memory manufacturers are already dealing with capacity constraints, AI customers are securing long term supply agreements, and demand for HBM continues to grow as Nvidia $NVDA and other AI chipmakers push toward increasingly memory intensive systems. And people need to understand that building additional manufacturing capacity doesn't automatically mean we're going to have an oversupply problem. These fabs take years to construct, equipment needs to be installed, production yields need to improve, and manufacturers still have to qualify their products with customers. Not to mention, HBM manufacturing is substantially more complicated than traditional DRAM, and not all additional memory capacity can immediately be used to produce the most advanced AI memory products.
Now, could we eventually see oversupply in 2029? ABSOLUTELY. Memory is a cyclical industry and I've never argued that these companies will enjoy record pricing and margins forever. But there's a massive difference between acknowledging that possibility and acting like the memory cycle is already over. I still believe the fundamentals of the memory trade remain incredibly strong, especially for companies positioned to benefit from HBM and the broader AI infrastructure buildout. Bullish on memory and if you want to see how I’m investing through this selloff and check out my full portfolio below. link.milkroad.com/tx5qip
Jim P., down in Texas retweeted
BREAKING: Jensen Huang just said we're still in the EARLY innings of the buildout of this new computing architecture.
Fear and Greed just hit EXTREME FEAR.
I'm investing in these 9 companies that are currently on sale:
1. $AVGO - Broadcom
Down 31% from its 52-week high. Broadcom guided Q4 AI semiconductor revenue to $21.7B, up 236% year over year, and Hock Tan says supply is secured to roughly double AI revenue to about $115B in fiscal 2027.
Jim P., down in Texas retweeted
An in-depth breakdown of the 5 layers of the photonics value chain and key businesses:
𝗟𝗮𝘆𝗲𝗿 𝟭: 𝗺𝗮𝘁𝗲𝗿𝗶𝗮𝗹𝘀 & 𝘄𝗮𝗳𝗲𝗿𝘀
$GLW: Manufactures optical fibers, cables, and connectivity products for telecommunications and data centers.
$AXTI: Produces indium phosphide, gallium arsenide, and germanium substrates for optical and electronic devices.
$IQE: Supplies epitaxial wafers that enable lasers, optical sensors, and wireless semiconductor devices.
$AIXA: Builds equipment that deposits semiconductor material layers for lasers, LEDs, and power electronics.
$AMS: Manufactures LEDs, lasers, and optical sensors for automotive, industrial, and consumer applications.
𝗟𝗮𝘆𝗲𝗿 𝟮: 𝗽𝗵𝗼𝘁𝗼𝗻𝗶𝗰 𝗱𝗲𝘃𝗶𝗰𝗲𝘀
$IPGP: Builds fiber lasers for industrial cutting, welding, cleaning, and medical applications.
$COHR: Produces lasers, optical components, and transceivers for communications and industrial applications.
$LITE: Produces optical networking components for data centers and telecommunications, plus industrial lasers.
$LASR: Produces semiconductor and fiber lasers for industrial processing, aerospace, and defense.
$SIVE: Develops semiconductor lasers for optical communications, data centers, LiDAR, and sensing.
𝗟𝗮𝘆𝗲𝗿 𝟯: 𝗰𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 & 𝗺𝗼𝗱𝘂𝗹𝗲𝘀
$AAOI: Manufactures optical transceivers, lasers, and networking components for data centers and telecommunications.
$MTSI: Designs photonic and radio frequency semiconductors for data centers, telecommunications, and defense.
$FN: Provides contract manufacturing, optical packaging, and assembly services for communications equipment makers.
$VIAV: Produces optical filters and light shaping components for 3D sensing and imaging.
$LPTH: Manufactures precision optics, infrared lenses, and thermal imaging assemblies for defense and industrial applications.
𝗟𝗮𝘆𝗲𝗿 𝟰: 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 & 𝗲𝗾𝘂𝗶𝗽𝗺𝗲𝗻𝘁
$ASML: Builds lithography machines that pattern semiconductor wafers for advanced chip manufacturing.
$BESI: Manufactures semiconductor assembly equipment for attaching, bonding, and packaging chips.
$ASM: Builds deposition equipment that applies thin material layers during semiconductor wafer manufacturing.
$LPK: Manufactures laser production systems for electronics, semiconductor packaging, glass processing, and solar cells.
$MKSI: Supplies lasers, optics, vacuum systems, and process controls for advanced manufacturing.
𝗟𝗮𝘆𝗲𝗿 𝟱: 𝘁𝗲𝘀𝘁, 𝗺𝗲𝘁𝗿𝗼𝗹𝗼𝗴𝘆 & 𝘆𝗶𝗲𝗹𝗱
$CAMT: Builds inspection and metrology equipment that detects semiconductor defects and improves manufacturing yields.
$FORM: Supplies probe cards and test systems that evaluate semiconductor performance and reliability.
$AEHR: Builds semiconductor test and burn-in systems that screen devices for early reliability failures.
$ONTO: Provides optical metrology, defect inspection, and process control systems to improve semiconductor manufacturing yields.
$VIAV: Supplies network testing and monitoring tools that verify communications performance and reliability.
And that covers the most important business in the value chain!
If you like to learn more about the value chain, give the article below a read. I think you'll like it.
Jim P., down in Texas retweeted
$NBIS $MU $LITE $COHR $AAOI $SIVE
I had the chance to sit and dig deep into Bank of America's latest AI data center forecast, and it's the most bullish table I've seen this year.
BofA sees AI data center systems going from ~$280B in 2025 to ~$2.2T by 2030.
That's roughly 8x in five years and a 40% CAGR from 2026. By then, AI makes up 86% of all data center spend, up from 55% last year, while non-AI data centers grow just 7% a year.
BofA has the memory market going from $110B in 2025 to ~$494B in 2026, taking memory from 22% of data center spend to 59% in a single year. DRAM alone passes $1T by 2030.
Interconnect is the fastest-growing part of the stack.
AI networking grows 43% a year to ~$394B, AI switching 51%, and optical reaches $111B. Co-packaged optics goes from basically zero to $14B by 2030.
AI CPUs for agentic workloads grow from $18.5B to $180B, a 44% CAGR.
Every AI layer on this table compounds three to four times faster.
I’m positioning myself to capture most of the up and coming upside.
You simple are not bullish enough for the AI trade.
Jim P., down in Texas retweeted
THE AI NETWORKING STACK. 🔥
Goldman Sachs projects AI networking TAM could expand from $15B to $154B across next-generation AI platforms.
That’s a 10× TAM expansion!
Here’s the stack: 👇
1. AI Networking & Switches
$NVDA $ANET $CSCO $HPE $NOK
2. Networking Semiconductors
$AVGO $MRVL $ALAB $CRDO $SMTC
3. Photonics & Optical Components
$LITE $COHR $AAOI $MTSI $AXTI
4. Fiber, Connectivity & Transport
$GLW $APH $TEL $CIEN $ADTN
5. Networking Hardware Manufacturing
$FN $CLS $SANM $TTMI $FLEX
Explosive AI-driven demand.
Constrained optical supply.
A massive infrastructure buildout ahead.
Jim P., down in Texas retweeted
The 5 layers powering the AI data center boom.
$VST — Supplies electricity powering massive AI data centers and hyperscalers.
$NVDA — Builds GPUs that power AI training and inference workloads.
$MU — Supplies high-bandwidth memory essential for advanced AI computing systems.
$ANET — Builds high-speed networking switches connecting thousands of AI servers.
$VRT — Provides cooling and power infrastructure keeping AI data centers operational.
$AMZN — Operates AWS, building hyperscale data centers for global AI workloads.
Jim P., down in Texas retweeted
One number decides whether a stock earns a spot in my portfolio.
I call it the Opportunity Score (0–100).
Here's what's under the hood 👇
1️⃣ QUALITY — 50%
Is it worth the trouble? → NTM growth
Is it a great business? → Gross margin
Is it making money? → EBITDA + FCF margin
Are shareholders keeping the gains? → Dilution
2️⃣ TREND — 30%
Is the story getting better or worse?
→ Growth, growth acceleration, margins, profits, quality & analyst revisions
3️⃣ VALUATION — 20%
Am I paying too much?
→ Implied upside vs. analyst + model price targets
The score also sizes the bet:
80+ → up to 15%
60–80 → up to 10%
50–60 → up to 5%
Below 50 → pass
This week:
• 7 names clear 80
• Memory still leads: $MU 88, $SKHY 87, $SNDK 84
• $SITM is the trend story: biggest green bar in Tier 1
• I own 14 of the top 20
The goal isn't just finding great companies.
It's great businesses, getting better, at a price that still leaves room to win.
Bookmark this. Scores update every week.
Not investment advice.
Jim P., down in Texas retweeted
Tarihsel verilere göre S&P 500 endeksi ara seçimlerden önce Ekim'in ilk haftası dip yapıyor. Sonrasında yıl bitimine kadar güçlü bir yükseliş takip ediyor.
Yani alamadım diye üzülmeyin, çok büyük ihtimalle tekrar bir fırsat olacak.
Jim P., down in Texas retweeted
JENSEN IS A LIAR, HE IS UNDERPROMISING & OVERDELIVERING 🚀🚀🚀 At GTC 2026, Jensen only claimed 3x better perf per watt on Rubin NVL72 versus GB300 NVL72, but our tests SHOW 7x BETTER PERF PER WATT.
Jim P., down in Texas retweeted
A Stanford professor took two average stocks, rebalanced them daily, and turned $100,000 into $7 million without predicting a single price.
Bookmark & watch today, no matter what.
Readers added context they thought people might want to know
Thomas Cover's example used two specific volatile stocks; the ~$7M from $100k is the best hindsight constant-rebalanced return on 1963-1985 data, not his causal universal portfolio's result.
youtube.com/watch?v=wsd8ns…
gwern.net/doc/statistics…
Jim P., down in Texas retweeted
Yes, absolutely sharing!!!!
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Jim P., down in Texas retweeted
Gold production Q2 — Majors
🇺🇸 Newmont — 1,300 koz
🇨🇦 Agnico Eagle Mines — 856 koz
🇨🇦 Barrick Mining — 796 koz
🇺🇿 Navoi Mining & Metallurgical — 772 koz
🇨🇳 Zijin Mining Group — 746 koz
🇺🇸 AngloGold Ashanti — 744 koz
🇿🇦 Gold Fields — 634 AuEq koz
🇨🇦 Kinross Gold — 492 AuEq koz
🇦🇺 Northern Star Resources — 436 koz
🇿🇦 Harmony Gold Mining — 356 koz
🇬🇧 Endeavour Mining — 283 koz
🇨🇦 B2Gold — 204 koz
🇺🇸 Freeport-McMoRan — 192 koz
🇨🇦 Iamgold — 188 koz
🇦🇺 Evolution Mining — 180 koz
🇨🇦 Equinox Gold — 177 koz
🇨🇦 Pan American Silver — 166 koz
🇺🇸 Coeur Mining — 163 koz
🇲🇽 Fresnillo — 155 koz
🇿🇦 Sibanye-Stillwater — 154 koz
🇦🇺 BHP Group — 149 koz
🇨🇦 OceanaGold — 139 koz
🇨🇦 Alamos Gold — 131 koz
🇨🇦 Lundin Gold — 119 koz
🇬🇧 Rio Tinto — 116 koz
