A quick peek at our NVIDIA GB300 NVL72 deployment process. NVIDIA #GB300# NVL72 brings next-generation rack-scale AI performance to the era of reasoning, with ultra-dense compute optimized for large-scale training and high-throughput inference. More to come. Stay tuned👐! #GPU# #AIInfrastructure# #neocloud#

SpaceX has almost finished writing V1.0 of an in-house AI training stack in C that exact-maps to 220k GB300s with 800G NICs, making heavy use of pipeline parallelism and getting as close to bare metal as possible. The potential speed improvement vs JAX for large training runs is over an order of magnitude.

AI Hardware Demand Growth and Representative US-Listed Companies June 2026 Executive Summary Nvidia’s transition to the Vera Rubin (VR200) platform marks a significant escalation in AI infrastructure complexity and cost. Our BOM teardown of the next-generation Rubin rack reveals a ~2x increase in total rack cost to approximately $7.8 million (vs. ~$4 million for GB300), driven not solely by the GPU/CPU but by sharp revaluations across the supply chain. Key highlights from downstream components include: • PCB content value +233% YoY, the largest increase. • MLCC +182%, reflecting higher density and count (e.g., ~600k MLCCs per VR200 NVL72 server, +30%+ vs. GB300). • ABF substrates +82%, power solutions +32%, and liquid cooling +12%. These upgrades align with broader AI scaling: 800G/1.6T optical transceivers ramping aggressively, glass-based technologies advancing for packaging and interconnects, and hyperscalers prioritizing performance, power efficiency, and thermal management. We expect sustained multi-year tailwinds for the AI hardware ecosystem into 2027+, with Rubin-driven demand accelerating in H2 2026. Investment Thesis: While Nvidia (NVDA) remains the core beneficiary, the supply chain offers diversified exposure. We favor companies with direct exposure to high-growth areas like advanced PCBs, high-speed optics, and glass substrates/optical interconnects. Risks include execution on new capacity, potential margin pressure from rapid scaling, and geopolitical supply chain factors. 1. PCB: Sharpest Value Uplift in Rubin BOM Morgan Stanley’s detailed analysis shows PCB content in the Rubin rack surging +233% versus GB300. This reflects needs for higher layer counts, advanced materials, better signal integrity, and larger formats to support increased power and interconnect density in AI servers. US Representative: TTM Technologies (TTMI) – Leading US PCB manufacturer with strong positioning in high-complexity boards for data center/AI applications. TTM has invested in capacity expansions (e.g., new facilities) to capture AI-driven demand for advanced HDI and high-layer PCBs. 2. MLCC: Density-Driven Surge Nvidia’s VR200 NVL72 platform requires ~600,000 MLCCs per server, over 30% more than GB300. Combined with the +182% value increase in the BOM, this underscores tightening supply for high-capacitance, high-reliability MLCCs in power delivery and decoupling for AI accelerators. Exposure Note: The MLCC market is dominated by Asian players (e.g., Murata, Samsung Electro-Mechanics, Yageo). US-listed indirect exposure may come through broader electronics or power solution providers, but direct pure-play opportunities are limited. Watch for capacity utilization tightness benefiting the ecosystem. 3. Optical Communication: 800G/1.6T Ramp Accelerating Chinese leader Zhongji Innolight reported Q1 2026 net profit +262% YoY, driven by strong 800G/1.6T shipments, with expectations of significant full-year growth. This mirrors industry-wide momentum as AI clusters shift toward higher-speed optics for reduced latency and power in scale-out/scale-up networking. Nvidia’s investments in photonics and CPO further validate the trend. US Representatives: • Coherent (COHR) and Lumentum (LITE): Key players in optical components and transceivers; Nvidia has made substantial equity investments to secure capacity. • Corning (GLW): Major beneficiary via optical fiber, connectivity, and glass technologies (detailed below). 4. Micro-LED/Glass Substrates & Optical Interconnects: Strategic Partnerships Accelerating On May 20, 2026, BOE announced a cooperation MOU with Corning covering glass-based encapsulation carriers, foldable glass, perovskite substrates, and optical interconnect applications. This aligns with industry shifts toward glass cores for superior flatness, thermal stability, and integration in advanced packaging and photonics—critical for next-gen AI as organic substrates hit limits. US Representative: Corning (GLW) – Central to Nvidia’s optical strategy with multi-billion partnerships, new US optical factories, and expansion in fiber/photonics for AI data centers. Recent deals position GLW for 10x+ capacity growth in key areas. AI Hardware Demand Growth & US-Listed Representative Companies Table Component Demand Growth (vs. GB300) Key Drivers US-Listed Reps Investment Rationale PCB +233% value Higher layers, HDI, signal integrity TTM Technologies (TTMI) Direct AI server/backplane exposure; US capacity expansion MLCC +182% value; +30%+ count Power density in servers Limited direct (ecosystem via power suppliers) Supply tightness supports pricing/volume Optical Comm (800G/1.6T) Strong ramp (e.g., +262% profit ex.) Scale-out networking, CPO transition Coherent (COHR), Lumentum (LITE), Corning (GLW) Nvidia investments; transceiver/fiber boom Glass Substrates/Interconnects Emerging (MOU-driven) Packaging, photonics, thermal/optical Corning (GLW) Nvidia factory deals; US manufacturing tailwinds Power & Liquid Cooling +32% / +12% Higher TDP (e.g., 2300W GPUs) Indirect (ecosystem) Secondary but critical for rack deployment Source: Morgan Stanley BOM analysis, company reports, industry data. Growth metrics approximate from Rubin teardown. Outlook & Risks We project robust 2026-2027 growth in AI capex, with Rubin shipments catalyzing another leg-up in component demand. Optical and advanced substrate shifts could extend the cycle beyond traditional GPU focus. Hyperscalers’ vertical integration and US onshoring (e.g., Corning/Nvidia factories) add resilience. Key Risks: Cyclical capex pauses, yield/execution challenges on new tech (glass/CPO), commodity volatility in passives, and intense competition in Asia-heavy segments. Valuation multiples in the space have expanded; selectivity is key. Recommendation: Overweight select supply chain names with strong Nvidia alignment (e.g., TTMI for PCBs, COHR/LITE/GLW for optics/glass). Monitor Q2 2026 earnings for confirmation of Rubin ramp momentum.

Jensen Huang just handed every AI cloud investor the clearest framework for picking winners and the question is who actually understands what he said (Save this). Compute is not just infrastructure anymore but rather revenue, and performance per watt is the mechanism by which that revenue becomes profit. The argument Jensen made at Computex deserves to be unpacked fully because it completely reframes the neocloud investment thesis. Every AI factory operates inside a fixed power envelope and once your data center is built and your power contracts are signed, that ceiling does not move. One gigawatt means one gigawatt and the only variable that determines how much money you make is how many profitable tokens you can squeeze out of each watt of electricity flowing through your facility. An operator who chooses cheaper, lower efficiency chips because the upfront cost looks attractive is not saving money and they are permanently handicapping their revenue ceiling for the life of that asset. Every watt that produces fewer tokens is a watt that will never recover those lost revenues, for as long as that infrastructure runs. Jensen's second point is about asset longevity and it is equally important to understand. AI software is evolving every few months from CNNs to Transformers to Mixture of Experts to agentic systems and that pace is not slowing down. A hardware architecture that cannot adapt to new software paradigms has a short useful life, and a short useful life means a high total cost of ownership. Infrastructure built on Nvidia's CUDA ecosystem has a built in software longevity advantage because every new model, framework, and optimization is written for CUDA first. Now apply that framework directly to Nebius, which is the most important stock in the neocloud category. Nebius built its entire infrastructure around full Nvidia integration from the ground up. Nvidia and Nebius announced a formal strategic partnership in March 2026 specifically to develop the next generation of hyperscale AI cloud deployments together. Nebius is already offering Blackwell Ultra GB300 NVL72-powered instances to customers, meaning it has the highest-performance GPU currently available commercially running inside its own infrastructure. The token economics follow directly from the architecture. Contracted power has now passed 3.5 gigawatts, with more than 75% of that capacity owned outright rather than leased. The Meta deal alone is worth $27 billion over five years, and the Microsoft agreement is worth up to $19.4 billion. The 2026 plan targets 480 megawatts of live AI cloud capacity, 150,000 GPUs deployed, and $3.7 billion in annualized revenue implying next twelve month revenue growth of roughly 489%. Q1 2026 revenue was $399 million, up 684% year-over-year, and the CEO said on the earnings call that everything Nebius builds gets sold immediately. Fully booked capacity at an AI cloud running Nvidia's best hardware, inside a power-scarce environment where performance per watt is the direct driver of profitability, means Nebius's revenue ceiling moves in direct proportion to the power it can bring online. CoreWeave, a direct comparable, trades at a materially higher multiple on a smaller contracted power base. Nebius owns more of its capacity outright, has a longer-dated and larger contract backlog on a per-gigawatt basis, and is growing revenue at a faster rate. Milk road remains extremely bullish on Nebius and come join Milk Road Pro and get our full Nebius positioning breakdown and our other AI trades for just a dollar. Link down below!

## Earnings Wrap-Up ### **AMD (Buy) | TP: $511** * **Guidance slightly beat expectations ($11.2bn vs. $10.5bn Bloomberg consensus, Buy side $10.96b). ***Server CPU TAM** now projected at >35% CAGR. AMD’s leadership will be further strengthened by Venice and a diversified CPU portfolio. ***Progress on **MI455/Helios** remains on track. * **Outlook:** Some investors were a bit cautious before the print; additionally, the frequent demand upward revision misled analysts’ near-term estimates. That said, the pause before the print could further boost the share price outperformance. Overall, we remain bullish ### **Lumentum (LITE - Buy) | TP: $1,168** * **Slightly below** FY3Q revenue ($808m) slightly missed buy-side targets, and F4Q’s $985m below buy sides $1bn, though gross margins expanded to **47.9%**. * **Key Drivers:** Laser supply remains structurally tight as demand outpaces capacity. OCS is gaining momentum via multi-year agreements. * **Outlook:** While the FY4Q guidance led to a brief after-hours pull-back, earnings power is expected to scale dramatically into CY2027. ### **Supermicro (SMCI - Hold) | TP: $43** * **Shares jumped 18% after hours following a strong Gross Margin beat. * **Key Drivers:** Margin gains were driven by a better customer mix (enterprise) and fewer low-margin GB300s. * **Outlook:** While margins are expected to remain elevated, the rating remains **Hold** due to uncertain top-line growth and limited visibility on new GB300 bookings.

Part 4  Close Associates of Chen Zhi 1. Li Tian (also known as Thet Li,Figure1) Date of Birth: July 6, 1987 Place of Birth: Beijing, China Citizenship: Cambodia and Vanuatu Passport: RV091789 (Vanuatu) Li Tian obtained a Bachelor’s degree in E-commerce from Beijing Information Science and Technology University in 2009. As Chief Financial Officer (CFO) of the Prince Group, Li Tian was responsible for managing illicit financial flows within the organization, including the handling of laundered funds and the coordination of large-scale cash smuggling operations. In April 2020, Li Tian became the ultimate controlling shareholder of Hong Kong-listed company FSM Holdings Limited (Stock Code: 1721), holding approximately 60.23% of its issued shares. According to records from the Hong Kong Companies Registry, Li Tian also serves as a director of four additional companies registered in Hong Kong: Concept Planet (HK) Limited Silver Prosper International Limited Sky Talent Investment Limited STAR MAX DEVELOPMENT LIMITED 2. Zhou Yun (also known as Sandy Zhou,Figure2) Date of Birth: October 17, 1982 Place of Birth: Hubei Province, China Identification: Hong Kong Identity Card and Hong Kong SAR Passport Passport: G30024177 (China) Sandy Zhou  serves as Chen Zhi’s financial assistant and wealth manager. She has been designated under United States sanctions programs. Multiple insurance brokerage and securities firms of Mighty Divine Group in Hong Kong, which were beneficially owned or controlled by Chen Zhi through Sandy Zhou , have been subject to enforcement actions and regulatory intervention. 3. Wei Qianjiang （Figure3) Date of Birth: April 28, 1983 Wei Qianjiang graduated in January 2015 from the Open University of China (formerly the Central Radio and Television University), obtaining an Associate Degree in Business Administration. Through a Bitcoin mining enterprise in Laos operated by the Prince Group, namely Warp Data Technology Lao Sole Co., Ltd., large volumes of Bitcoin (BTC) were allegedly transferred to cryptocurrency wallets controlled by Chen Zhi. Wei Qianjiang served as the person in charge of this operation. Key business activities include: 2014: Established Chongqing Venture Capital and Longxun Technology in Chongqing, China  2017: Registered a Hong Kong entity under the same name, Loncent Technology, with plans to pursue an IPO on the HKEX August 2018: Appointed as a Non-Independent Executive Director of HKEX-listed company Geotech Holdings Ltd. (Stock Code: 1707), a company controlled by Chen Zhi July 2020: Loncent Technology was investigated by police for promoting gambling services and facilitating cyber-enabled criminal activities; multiple senior executives were detained or defected to authorities, while Wei Qianjiang, as the company’s legal representative and owner, was handled in a separate case 2020: Registered Merak Technology (Hong Kong) Limited in Hong Kong @BBCWorld @BBCBreaking @WSJ @business @nytimes @cnni @Reuters @Forbes @TIME @TheEconomist @UN @AP @washingtonpost @MarketWatch @WSJecon @FAANews @NTSB_Newsroom @FoxNews @FT @YahooFinance @SkyNews  @NBCNews