PCB: Content Upside & PTFE Adoption Following our very early PTFE note on June 2, we provide update: • Nvidia Rubin platform a major catalyst for PCB content expansion
GB300 → ~US$440/GPU
VR200 → ~US$750/GPU
VR300 → US$1,000–1,500/GPU • Drivers: higher-end CCL materials, rising layer counts, and potential PTFE adoption into Rubin Ultra • VR200 upgrades
Compute tray: M8 + M6 CCL
Switch tray + new 44L midplane: M8.5 (Low-DK2/HVLP4)
→ Content rises to ~US$750 per GPU • VR300 further upside: M8.5 + M6 hybrid compute + M9 (Q-glass) switch/midplane → ~US$1,000/GPU
Oberon NVL576: hybrid PTFE switch boards (16+16L) under evaluation
If PTFE adopted → content could exceed US$1,500 per GPU • Stock preference
PCB: ZDT (4958 TT Buy) – new position in VR200 compute tray
PTFE CCL: Leading Chinese player primary; Taiflex (8039 TT) as potential second source #PCB# #PTFE# #EMC# #TAIFLEX# #CCL#

Non-stick cookware coated with PTFE releases perfluorocarbon compounds when heated above 500 degrees Fahrenheit. A pan on high heat reaches that temperature in minutes. These compounds are linked to thyroid disruption, immune dysfunction, and developmental issues in children. They accumulate in tissue and have a half-life in the human body of four to eight years. Cast iron, stainless steel, and carbon steel are the alternatives. They require more attention but introduce zero synthetic compounds into your food.

Market capital has a funny blind spot: many assumed PTFE-related designs would phase out glass fabrics entirely. The ground reality? We are seeing more and more next-gen designs migrating back to fabric-based solutions. ​Right now, the winning playbook for high-layer AI architectures is a co-existence scheme: leveraging Q-glass paired with CH resin Prepregs (PP). This isn't a temporary workaround; it is the blueprint for the next wave of hyperscale networking infrastructure. ​ ​#PCB# #AI# #Hardware# #SupplyChain# #Semiconductor#

The Q-glass vs. PTFE debate is still raging, but the ground truth is clear: ultra-high layer count AI boards are locked in for the M9 + Q-glass setup. 🧵👇 PTFE materials cause severe processing bottlenecks in drilling and lamination. It’s so problematic that even Shengyi Tech had to alter its PP formulations. Looking into 2027, the volume ramp-up of next-gen LPUs (featuring massive 52-layer designs) will trigger a massive surge in Q-glass demand. PTFE will remain strictly confined to low-layer topologies. #PCB# #Semiconductor# #AI# #SupplyChain# #Hardware#

Earlier, I noted that unreinforced PTFE (glass-free) is theoretically an engineering nightmare for stable PCB mass production. Looking at the latest architectural roadmap, here is how the split is actually playing out: 1️⃣ With GPU/Switch Silicon: Must stick to traditional fabric-reinforced solutions to meet strict mechanical & assembly requirements. 2️⃣ Pure Signal Transmission (e.g., Backplanes): Driven purely by electrical performance, designs can adopt unreinforced (glass-free) schemes, deviating from conventional PCB rules. End customers are definitively breaking away from legacy design logic. The supply chain has no choice but to adapt and execute. Time to move. 🚀 #PCB# #AI# #Hardware# #SupplyChain# #Semiconductor# #Materials#

From a tech roadmap perspective, here is how the materials are shifting: ​1️⃣ Compute/Switch/Motherboards: CCL is staying on the current PPO/CH track, starting at M8+ and scaling toward M9/M10 for next-gen nodes. ​2️⃣ Backplanes/Midplanes: To balance manufacturability and performance, we're seeing a hybrid approach. It leverages a glass-free PTFE Core paired with Q-glass/CH resin Prepregs (PP) for mechanical reinforcement. ​Co-existence is the actual winning playbook here. #AIInfrastructure# #PCB# #CCL# #MaterialScience# #PTFE# #QGlass#

Takeaways from the Sept Wrap-Up report - Cautious Market, Intact AI •July was tough; mild recovery through Aug/1H-Sept still felt challenging. Positioning remains cautious despite robust AI-infrastructure demand. Sentiment is more on worst-case capex & monetization fears. •Worst of the pullback looks behind us: positioning cleaned up, Sept rate hike was expected, and recent tech-CEO comments reinforced AI confidence. •Long-term AI/capex: US CSP capex forecast +85% / +45% / +20% YoY for 2026/27/28. CSP balance sheets (ex-Oracle) stay healthy — net leverage ~0.5x, net debt-to-equity only 18% by 2029. •Neoclouds + Nvidia’s $530bn off-balance-sheet backstop = Nvidia wins if demand holds, manageable if it weakens •GPT-6 is a step-up toward AGI: Unlocks monetizable automation across knowledge work, enterprise agents, DevOps/security, synthetic data/RL. •Scaling + inferencing demand continues even as CEOs talk about “pacing the frontier.” •Recent supply tour + SEMICON 2026: bullish on AI infra demand. Tight supply across wafer fab, advanced packaging, memory, LPS, substrate, DSP, etc. Strong backlogs + multi-year visibility. •Still like: NVDA, CPU, UMC/INTC, DRAM/HBM, thermal, interconnect/optics (Credo, SMTC), PCB/PTFE. •August data: TSMC sales +10% MoM (tracking inline). Neoclouds momentum helps OEMs. Substrate upcycle intact, CCL margin expansion. Aspeed +118% YoY with solid 4Q guide / likely BMC price hike. #AI# #Semis# #NVDA# #MU# #TSMC# #capex#

🚨 I HAVE NO MICROPLASTICS IN MY BALLS 🚨 This should not be possible. Studies show that 100% of men have microplastics in their semen. I am the first human ever to show a complete reduction to zero. This may be a world-first breakthrough in fertility research. I had 165 microplastic particles in my semen just 18 months ago. Now, I have zero. Five published studies have measured microplastics in human semen. Two found them in 100% of men. The other three found then in 44 to 76% of men tested, but those used methods that miss the smallest particles and the clear ones. Corrected for that, the real rate is likely 100%. Almost every man alive has plastic in his semen right now. The same applies to testicular tissue, testing 100% positive for microplastics. Microplastics hurt sperm. Human studies show the impact of various types of plastic, associated chemicals, and other toxins on male fertility: + 60% fewer normal shaped sperm (from PFAS) + 5x higher odds of low sperm count (from PTFE) + 10% lower sperm concentration (from PTFE) + 15% lower swimming ability (from PTFE) + 41% lower swimming ability (from PET) + 12% lower sperm swimming ability (from BPA) + 3x higher odds of low sperm count (from Phthalates) + 2x higher odds of poor swimming (from Phthalates) The effects compound: each extra type of plastic drops sperm swimming ability by about 21%. This matters even if you’re NOT trying to get pregnant. Sperm count is one of the cleanest biomarkers of overall health we have. And microplastics don't stop at the testes. The same particles are showing up everywhere we look. Studies show 4.5x higher rate of heart attack, stroke, and death in people with microplastics in their arterial plaque vs. those without. Microplastics were also found in 100% of human placentas tested. 100% of post-mortem human brains tested positive for microplastics. Brain concentrations rose ~50% between 2016 and 2024, and now sit at roughly 11x the levels found in the liver or kidney. Where do these come from? + PTFE, commonly in non-stick pans + PET, water bottles + Phthalates, makes plastic soft and bendy + BPA, can linings + PFAS, stain-resistant fabrics & food packaging Inside the body, plastic causes a kind of cellular rust. It triggers inflammation in the testicles, kills the cells that make sperm and drops testosterone. It's been confirmed across 39 animal and cell studies, then in human data. MY PROTOCOL: Note, what I did is n=1, not a controlled trial, I cannot prove cause. 1. Sauna (dry). My toxin blood panel confirms sauna clears plastic related chemicals: BPA, phthalates, PFAS, flame retardants, pesticides. The plastic particles themselves are too big to sweat out directly. Heat may activate other clearance routes: bile flow through the liver, the cell's internal cleanup system, and the gut barrier. Humans have almost no enzymes that can break plastic apart, so the body has to physically push it out. 2. Reverse osmosis water filter. Drinking water is likely a major source of microplastic getting into your body. A reverse osmosis filter pushes water through a very tight membrane and strains the particles out. I filter everything I drink. 3. Trying to rid my environment of the big plastic items: cutting boards, cups, plates, food storage containers, non-stick pans, cling wrap, tea bags, water bottles, kitchen utensils, kettles, and synthetic clothing. Note, as hard as I try, I'm always finding new plastic things in my life. This can be all-consuming thing so try to just knock out the big ones. I did all three interventions at the same time. I cannot say which one did the most work. What I can say is this: going from 165 to zero in 18 months is possible. Results: Nov 2024: 165 particles/mL Jul 2025: 20 particles/mL Apr 2026: 0 particles/mL The 18 month window also captures roughly 7 full spermatogenesis cycles.

Weekly|AI Slowdown by Sector, GPT-6 Astra Computer Use, Delta VPD Re-accel, Enterprise AI Vol.3, SAIL FY27Q2, EMC Price Hikes The tape last week split again: broader indices leaned soft into PPI/CPI and the next FOMC, while semis held up on company-specific news, where SOX finished higher even as mega-cap tech traded mixed. That is the same relative setup we have been tracking since memory broke out: hardware names responding to incremental AI infrastructure demand while the index still waits on the macro prints. The research week was dominated by compute demand from a different angle. GPT-6 Astra is OpenAI’s first flagship with computer use as a core capability, and we read it as the Claude 3.7 moment for knowledge work: the demos moved from terminals into CAD, Excel, Blender and tax forms, and the addressable pool is an order of magnitude larger than coding. Multi-step reliability is still the gap, but the trajectory is visible, and OpenAI’s RSI note put numbers on the loop already turning inside the labs: agent hours at 3.1x human hours, with compute as one of the constraints that tightens as other bottlenecks ease. That framing matters more for the next pre-training cycle than any single benchmark. Separately, the Anthropic-led slowdown debate is back on X. Our take is that release cadence is not the same as training cadence, and a single brake would miss how uneven the stack already is. Coding, math and cyber are remaking workflows where RL data and feedback loops exist; most other industries still lack workflow traces and a usable context layer. Finance is the familiar case. GPT chats and Notion notes are easy to log, while the research-to-EPS judgment path is not. If policy slows anything, the useful version is sector by sector, with more effort lifting the laggards than cutting the frontier to match. Power and enterprise spend filled in the rest of the stack. We initiated on Delta: 2H26 re-acceleration is AI PSU plus VPD, with DC/DC still underweighted by the market at an estimated 8.3%/12.2% of revenue in 2026/2027 and >70% VPD share at $400-600 content per TPU. Enterprise AI Vol.3 went out with ten more samples: spend is still growing, but the questions have shifted to who needs the expensive models, whether time saved converts into revenue or real cost cuts, and how budgets get reallocated once caching, defaults and local models bite. This Week’s Reports AI Slowdown by Sector — release pace is not training pace, and a uniform brake misses how uneven the stack already is. Our debut Column argues coding, math and cyber remake workflows where RL data and feedback loops exist, while most other industries still lack workflow traces and a usable context layer; if policy slows anything, the useful version is sector by sector, lifting the laggards rather than cutting the frontier to match. GPT-6 Astra — computer use is the Claude 3.7 moment for knowledge work, and RSI is already turning the compute loop inside the labs. Astra is the first flagship with computer use as a core capability, OSWorld at 72.6%, and a visible path from coding’s trillion-dollar pool toward white-collar work an order of magnitude larger; OpenAI’s RSI note put agent hours at 3.1x human hours with compute as a binding constraint. Delta Electronics — 2H26 re-acceleration is AI PSU plus VPD, and DC/DC is still underweighted. We initiate on as a grid-to-core AI power name: VPD takes DC/DC to about 8.3%/12.2% of revenue in 2026/2027 with >70% share and $400-600 content per TPU, while we model FY27/FY28 revenue growth of 53%/28%. Enterprise AI Vol.3 — spend is still growing, but the next budget round is gated by usage depth, model tiering and measurable ROI. Ten more enterprise samples show broad basic access with highly concentrated heavy users, production agents in a few names, and cost controls (defaults, caching, local offload) that often get reinvested rather than cutting the total AI envelope. Premium Report Snapshot A portion of our research is reserved for Premium subscribers and is not distributed via Substack. Below is a snapshot of what Premium subscribers received this week beyond the Substack feed. Deep | EMC: Price Hikes Continue into 26Q4; High-End Leadership Intact Preview & Review | $SAIL FY27Q2: Headline Results Broadly in Line; AI Commercialization Better Than Expected Weekly Expert Interviews Summary A snapshot of the expert interviews we conducted during the past week is below; full transcripts and takeaways are available on the FUNDA platform. Google — TPU v8 Internal Priority and v7 Price Pressure (GOOGL, AVGO) Astera Labs — Scale-Up Interconnect and Memory Expansion Roadmap (ALAB, AMZN, MRVL, CRDO) Bloom Energy — Manufacturing Capacity Expansion and Service Risk (BE, NBIS) SailPoint — AI Identity Products Broaden Growth Sources (SAIL, OKTA, MSFT) Enterprise AI — API Migration Reshaping Cost and Workflows PCB/CCL Supply Chain — PTFE Backplanes and Material Bottlenecks (NVDA) Legal AI — Spend Growth, Productivity ROI and Headcount Pressure AI Servers — Rack Power Architecture and Cooling Mix (AMD, ORCL, META) Detailed Report