Jensen Huang says $NVDA Vera Rubin is “in full production” and now takes less than 5 minutes to assemble per node versus 2 hours for Grace Blackwell with zero cables and 100% liquid cooling. That’s over 24x faster assembly which could mean faster deployments and better margins as Nvidia ramps its next generation of AI systems.

Citadel founder and CEO Ken Griffin says investors are “almost certainly” in the midst of an AI bubble during an interview with Bloomberg's Dani Burger at Citadel's annual Future of Global Markets Conference in New York youtu.be/mV1V0FXixDE

Former $GOOGL employee on why data center capacity and electricity are the real bottlenecks, not GPU production itself, and how unreliable some of the neoclouds are ($AMZN, $GOOGL, $MSFT, $NVDA): 1. According to the expert, open-source models are closing the gap with frontier models faster than expected, with customers increasingly replacing Anthropic and OpenAI models in multi-agent architectures with open-source alternatives starting from Q2 of this year. The shift started with simple tasks like tool calling and MCP, but has moved up the stack to low-level orchestration. 2. The expert identifies capacity as the biggest constraint at the moment, with certain companies' traffic growing 5x while GPU availability, particularly in the U.S. where latency requirements are tightest, simply cannot keep up. Sourcing capacity overseas in Asia or Australia is technically possible but adds latency that most customers will not accept. 3. Hyperscalers offer reliability but are expensive, require multi-year commitments of three or more years, and have limited availability of the latest hardware, with customers already chasing B300s. AI-native companies tend to gravitate toward neoclouds due to hyperscaler pricing and contract rigidity, but neoclouds come with their own reliability issues, with GPUs dropping off unexpectedly and requiring engineering resources to manage fleet stability around the clock. 4. The third tier consists of smaller independent operators who have invested in GPU racks, seeing the opportunity to lease out capacity and recoup costs within a year or two, with the remainder being pure profit. The expert describes these as essentially unusable in practice, with operators who do nothing more than find land, install racks, connect electricity, and set up cooling, with no real cloud management, maintenance, or operational expertise behind them. 5. The expert expects overall GPU availability to increase meaningfully over the next year or two, with $NVDA continuing to ramp production. The real bottleneck is not GPUs themselves but data center capacity and electricity in the U.S. On the supply side, the expert also sees players $SPCX beginning to lease out spare capacity to the market, with more likely to follow. 6. The expert notes that U.S.-based neoclouds typically require 20-30% prepayment upfront, with the remainder paid monthly or quarterly over the contract term, and rebates negotiated at the end for any reliability incidents like traffic loss. APAC-based providers operate differently, with no prepayment required at all. found on @AlphaSenseInc

This chart shows the key risk to the AI trade, and it's missing from the latest revenue announcements. The AI boom is fundamentally driven by a top 1% of companies that drive 80% of spend. Within that top 1%, 80% are venture-backed. That's all fine if the AI trade works out, and if, as some prominent investors say, everyone wins. But if it doesn't work out, then we have a cascading effect of large customers simultaneously pulling back their AI spend.

Glass fiber cloth is a massive supply chain bottleneck - needed for GPUs, ASICs, 800G/1.6T switches. Nittobo have 90% share in T-glass & 70% in NER-glass. But they don't have enough capacity until mid-2027 to meet the demand. So demand is going to alternative suppliers. Most interesting alternatives to Nittobo imo: 1. Taiwan Glass Industry (1802.TW) - one of the strongest near-term AI plays imo. - low-CTE (T-glass equivalent) capacity expansion is on track (mass production ramped in Q1 2026) w/ $NVDA / $AMD certification. 2. Fulltech Fiber Glass (1815.TW): - shifting capacity aggressively toward higher margin T-glass. - advancing Thailand plant for diversification. - they benefit from Nittobo's shortage; increase pricing + volume in CCL/substrate supply chains. 3. Nan Ya Plastics (1303.TW): - quite an attractive integrated play via their Nittobo partnership. - 2025 results showed strong AI-driven growth in glass fabrics, IC substrates + CCL (with pricing expansion) - momentum continues this yr too w/ vertical integration providing direct leverage to server/substrate demand. 4. Nippon Electric Glass (5214.T): - developing low-CTE fibers w/ client proposals targeted for 2026. 5. Unitika (3103.T): - IP on producting world’s thinnest glass fabrics - “Entry into AI semiconductor package substrate market, with mass-production technologies to be established in FY 2025 and full-scale sales from FY 2026.” (Unitika Report 2025). - $QCOM visited Unitika to explore production ramps to diversify away from Nittobo. To me, Unitika seemed most compelling even though they're not pure-play (I have a position): - asymmetric upside if $QCOM or other hyperscalers commit to multi-year agreements. - and since they're so small, it leaves room for expansion beyond 2027 as Nittobo's supply come back online.

The most popular account pages on X by traffic share (September 2026): 1. @thsottiaux 2. @FabrizioRomano 3. @elonmusk 4. @25YearsAgoLive 5. @ngnchiikawa 6. @DiscussingFilm 7. @HYPEX 8. @whyyoutouzhele 9. @ActuFoot_ 10. @Osint613 11. @MadridXtra 12. @WARDOGS 13. @yagosabuncuoglu 14. @TouchlineX 15. @LegendDeols

Putting my Intern Pierre hat on and showing you demand for On shoes before the store even opens.

Recommended reading for the weekend: 1. @FundaAI — Physical AI: From the Robot-Data Race to a Second Demand Curve for Compute 2. @Citadel — October Update: Fundamentals in Focus 3. @satyanadella — Models as Insider Risks in the Super Intelligence Era 4. @KobeissiLetter — The "Stealth" Bear Market: A Historic Opportunity 5. @arthurmensch — Build or surrender 6. @Cayden_Liao — The Biggest Hack in Crypto History That Never Happened Have a great weekend!