# Сопутствующие статьи по теме Supply Chain

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Supply Chain", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Retail Investors' 'Lead Brother' Serenity vs. Newly Minted Stock God Leopold: How Are the Two Top Hunters Mining AI's 'Physical Limits'?

The article profiles two prominent figures, Serenity and Leopold Aschenbrenner, who are gaining attention for their unconventional investment strategies focused on the physical constraints of the AI boom, moving beyond mainstream software narratives. Serenity, an anonymous online trader, advocates a "shiso leaf" theory. He targets small-cap companies with monopolies on critical, overlooked components in the AI hardware supply chain, such as specific semiconductor materials. His deep, technical analysis of bottlenecks in areas like co-packaged optics (CPO) has reportedly yielded massive returns, though his anonymity and focus on illiquid micro-cap stocks pose significant risks for followers. Leopold Aschenbrenner, a former OpenAI researcher, founded a multi-billion dollar hedge fund. His macro thesis argues that physical infrastructure—power grids, land, data centers—is the true bottleneck for AI growth, lagging far behind chip production. Consequently, his fund employs an infrastructure arbitrage strategy: heavily investing in storage and compute infrastructure companies while placing massive bearish bets (put options) against major semiconductor stocks, betting their valuations will correct as physical constraints become apparent. While their methods differ—Serenity drills into microscopic supply chain details, while Leopold takes a macroscopic, infrastructure-focused view—both share a core belief: the real power and investment alpha in the AI era lie in controlling scarce physical resources, not just software. The article concludes by noting the inherent risks in both approaches, such as liquidity issues for micro-caps and timing risks for macro bets, but suggests they signal a broader market re-evaluation of AI's foundational assets.

marsbit05/27 15:10

Retail Investors' 'Lead Brother' Serenity vs. Newly Minted Stock God Leopold: How Are the Two Top Hunters Mining AI's 'Physical Limits'?

marsbit05/27 15:10

This New Generation of US Stock Trading Gods No Longer Read Financial Reports

The new generation of "stock gods" in the 2026 US AI bull market are not analyzing traditional financial reports. Instead of focusing on giants like NVIDIA, figures like the 22-year-old Leopold Aschenbrenner (who reportedly turned $200M into $14B) and influencers like Serenity on platforms like Reddit's WallStreetBets, X, and Substack are gaining fame and returns by targeting obscure, low-cap "micro-cap" stocks. Their strategy, dubbed "supply chain sniping," involves identifying critical, often monopolistic, bottlenecks in the AI hardware supply chain—such as specific materials or components essential for giants like Google and NVIDIA—that are missed by mainstream Wall Street analysts. Serenity's call on AXTI, a $700M company supplying indium phosphide substrates crucial for photonics and optical interconnects, saw the stock soar from ~$12 to nearly $150. Similarly, accounts like KawzInvests and PhotonCap focus on thematic, supply-chain-driven research in areas like AI infrastructure, optics, and cloud services for SMEs, bypassing traditional valuation metrics. This shift represents a cultural move away from Warren Buffett-style value investing based on deep financial statement analysis. The new approach thrives on low liquidity, early narratives, and strong community propagation on social media, similar to meme stocks or crypto. However, this "attention economy" strategy carries risks: it depends on sustained information gaps, the underlying companies' ability to deliver fundamental results, and the potential for crowded, volatile exits as narratives shift. The trend also shows crypto traders applying their narrative-sensing skills to US micro-caps, marking a significant evolution in trading culture.

marsbit05/27 11:55

This New Generation of US Stock Trading Gods No Longer Read Financial Reports

marsbit05/27 11:55

2-Year Return of 225x? Uncovering Mysterious Researcher Serenity's AI 'Choke Point' Investment Strategy

"2 Years, 225x Returns? Decoding Serenity's AI 'Chokepoint' Investment Strategy" This article profiles Serenity (formerly AleaBito on Reddit's WallStreetBets), a pseudonymous researcher known for exceptional returns by applying a "Chokepoint Theory" to AI investments. His methodology involves a bottom-up, reverse-engineering approach of the AI hardware supply chain. He identifies critical, irreplaceable physical bottlenecks (chokepoints) that could cripple entire AI systems if disrupted, bypassing Wall Street's top-down focus on major tech firms. Key examples include pinpointing essential suppliers in the emerging Silicon Photonics and Co-Packaged Optics (CPO) sector—components vital for next-generation AI data center interconnects—such as niche companies providing external laser sources, molecular beam epitaxy equipment, or ultra-pure raw materials. Similarly, he highlights geopolitical "chokepoints" in the humanoid robotics supply chain, where key hardware components and rare earth elements are concentrated in Asia. Serenity validates his investment theses through rigorous adversarial AI debates before publication. He leverages institutional blind spots, directing a sophisticated network of retail followers toward undervalued, under-covered micro-cap stocks across global exchanges, driving significant price movements in names like Sivers ($SIVE), Soitec, and Raspberry Pi ($RPI). While presenting a powerful framework for finding critical system dependencies, the strategy carries inherent risks: extreme concentration on specific technological paths, liquidity issues in small-cap stocks, and accusations of market manipulation. Ultimately, the core takeaway is not to copy his trades, but to adopt his analytical lens: to ask which silent, physical switches hold irreplaceable power within a complex system and invest ahead of the market's recognition of their value.

链捕手05/27 09:12

2-Year Return of 225x? Uncovering Mysterious Researcher Serenity's AI 'Choke Point' Investment Strategy

链捕手05/27 09:12

To Those Ordinary People Who Haven't Invested in AI: You Think You're Late, You're Just Lacking Your Own Worldview

**Summary:** The article argues that ordinary investors feeling FOMO over missing the AI investment boom lack not timing, but their own independent worldview. Most people chase "what to buy" based on others' opinions (FOMO, envy) rather than fundamental analysis. This leads to costly mistakes: not knowing when to exit winning trades or cut losses on losing ones. The core solution is to develop a personal, long-term (5-10 year) worldview about societal shifts and technological bottlenecks. For most, building this from scratch (Path A) is too demanding. A practical alternative (Path B) is to follow the **capital expenditures (capex)** and strategic investments of visionary leaders, as their money reveals true conviction more reliably than their words. Five key figures to track for different AI perspectives are highlighted: Jensen Huang (NVIDIA, infrastructure), Elon Musk (Tesla/SpaceX/xAI, capex signals), Sam Altman (OpenAI, commercialization, but beware hype), Dario Amodei (Anthropic, technical/safety focus), and Liang Wenfeng (DeepSeek, efficiency/anti-consensus view). The article details how to read capex signals from hyperscalers' financial reports, NVIDIA's revenue breakdown, and strategic investments. It maps the complete AI产业链 (supply chain) from raw materials/energy to models/applications, explaining value flow and inter-dependencies (e.g., how a model release triggers demand across chips, memory, and optics). Finally, it provides an action plan: secure personal finances first, allocate a limited portfolio percentage (max 25%) to the theme, prefer broad ETFs (like QQQ), use dollar-cost averaging over 6-12 months, and write down strict investment rules beforehand to combat emotional errors during market volatility. The conclusion is that a stable, personally-held worldview enables disciplined, long-term investment far more than chasing short-term trends.

marsbit05/26 09:10

To Those Ordinary People Who Haven't Invested in AI: You Think You're Late, You're Just Lacking Your Own Worldview

marsbit05/26 09:10

Metrics Ventures Market Watch: The Brewing Storm

In the past month, the market has been actively trading contrasting expectations, balancing global supply chain disruptions fueling re-inflation against both actual and anticipated (Walsh) interest rate hikes. This volatility has impacted commodities and most equities, though tech has temporarily benefited from concentrated short-term liquidity. Fundamentally, as previously analyzed regarding the Strait of Hormuz situation, the US faces deep-seated balance sheet issues beyond what any single Fed chair can resolve. Hypotheses around a figure like Walsh could only materialize if AI fundamentally reshapes production relations. Until then, most non-AI-leading nations (effectively all except the US and China) risk fiscal and monetary policy collapse, rendering the identity of the Fed chair ultimately irrelevant. For crypto assets, there is currently no clear role in these dominant narratives. The market remains strongly capped by the 200-day moving average. While trends may shift from "anything but AI" to "anything but mines," this phase is dominated by the silicon vs. carbon (AI vs. traditional) dichotomy, leaving little room for crypto—though its time will come. **Market Overview & Commentary** The crypto market lacks significant catalysts beyond hype, plagued by low volume and scarce innovation, with clear technical resistance. Currently, crypto struggles for attention as global focus lies elsewhere. Assets like gold, oil, and grains are more direct hedges against supply-chain-driven inflation/stagflation. Bitcoin needs more time for capitulation and consolidation; this reset is expected to last until at least Q4 2026. Looking ahead, three factors will likely drive future market volatility: 1. Whether Walsh repeats the patterns of predecessors like Bassant or Musk, shifting stance into a new policy cycle. 2. The market underestimates the severity of global supply chain damage and the prolonged time needed for repair, which will eventually lead to recognition of acute resource shortages and price swings. 3. AI non-beneficiary, high-inflation nations (e.g., UK, Japan) will face severe fiscal and monetary crises. Rapid AI-driven displacement could trigger a collapse of existing credit and welfare systems. Ultimately, the market may realize that an AI bubble burst could spark contagious sovereign credit crises. The monetary and fiscal responses to such a scenario could serve as the ultimate catalyst for Bitcoin's next major bull run.

marsbit05/26 07:43

Metrics Ventures Market Watch: The Brewing Storm

marsbit05/26 07:43

US Stock Market Signal Master Serenity: Leading Institutions in Low Position Building, Annual Return 3840%

Serenity, an anonymous online trading figure known as the "Stock Call King," has gained significant attention by reportedly achieving staggering annual returns of 3840% in 2026 and 2256% over two years. Operating primarily on social media platform X, he shares free investment insights focused on the AI and semiconductor supply chains. His core strategy, the "Chokepoint" investment theory, involves identifying small, critical "bottleneck" companies within the AI infrastructure that are essential yet undervalued before major institutional investment. Examples include his multi-year call on stock AXTI, which saw gains exceeding 10,000%. Despite his popularity, Serenity's true identity and the specific dollar amounts behind his percentage gains remain undisclosed, leading to some skepticism. Critics question if he manipulates low-market-cap stocks, while supporters see him as disrupting traditional finance by providing free, high-quality research. He advocates against paid communities and emphasizes that his goal is to empower retail investors with information before institutional players act. Whether Serenity represents a genuine market visionary or a sophisticated narrative-driven player remains an open question debated by his followers and observers.

marsbit05/26 03:03

US Stock Market Signal Master Serenity: Leading Institutions in Low Position Building, Annual Return 3840%

marsbit05/26 03:03

The 'Stock Call King' Serenity: 3840% Annual Return, Beating Institutions to the Punch

This article profiles the mysterious stock trader and analyst known as Serenity, who has gained significant influence on social media platform X as a "stock call king." Serenity claims extraordinary annual returns of 3840% for the current year and 2256% over the past two years, primarily by focusing on overlooked companies within the AI and semiconductor supply chains. Operating anonymously, Serenity describes himself as a former Reddit WallStreetBets trader, an AI/semiconductor supply chain analyst, and a former AI research scientist. His core investment strategy, termed the "Chokepoint" theory, involves identifying small, critical bottleneck companies in the AI infrastructure ecosystem—such as those in photonics, substrates, and materials—that are essential yet undervalued. He argues these "invisible champions" become crucial as demand for AI hardware surges, creating significant investment opportunities before large institutions take notice. A frequently cited example is stock AXTI, which he has recommended for over two years and claims has yielded over 10,000% returns. The article notes that while Serenity's free, public posts on X have garnered a large following, his identity and exact portfolio size remain unverified, leading to some skepticism. Critics question if his reported returns are fabricated or if he might be manipulating prices of low-market-cap stocks. Serenity counters that he shares research freely to democratize information, allowing retail investors to benefit before institutional buy-ins, and that percentage returns are more meaningful than disclosing specific dollar amounts. Ultimately, the article presents Serenity as a polarizing figure—either a visionary analyst with a superior research framework or a potentially sophisticated market player. It concludes that the truth of his claims and legacy will only be determined by time.

Odaily星球日报05/26 03:00

The 'Stock Call King' Serenity: 3840% Annual Return, Beating Institutions to the Punch

Odaily星球日报05/26 03:00

Huawei's "Tao Law": A Comprehensive Overview of Core Companies

Huawei's "Tau Law": Core Companies Overview On May 25, 2026, Huawei's Director and President of the Semiconductor Business Division, He Tingbo, formally introduced the "Tau (τ) Law" at ISCAS 2026, marking a significant principle guiding industry development in the global semiconductor field from China. The Tau Law shifts focus from traditional Moore's Law, which pursues geometric transistor scaling, to "time scaling"—continuously compressing signal propagation delay (time constant τ) without solely relying on extreme feature size reduction. The core implementation path is "logic folding." This technique transforms circuit layouts from two-dimensional planes to multi-layer 3D stacks, using short vertical interconnects to replace long horizontal wiring, thereby drastically reducing τ. Huawei has already designed and mass-produced 381 chips following this principle over the past six years, with plans to launch a Kirin chip utilizing logic folding in Fall 2026. By 2031, high-end chips based on the Tau Law are expected to achieve performance levels equivalent to a 1.4nm process node. This development impacts several key industry segments, with related Chinese companies poised to benefit: 1. **EDA Design Software**: Essential for circuit-level optimization. Key players include: * **Empyrean Technology** (Huada Jiutian): China's largest full-flow EDA provider. * **Primarius Technologies** (Gailun Dianzi): Specializes in device modeling and verification. * **Semitronix** (Guangliwei): Focuses on yield enhancement and test chip EDA. 2. **Chiplet & Advanced Packaging**: Logic folding's 3D stacking necessitates advanced packaging (e.g., TSV, hybrid bonding). Core participants are: * **Tongfu Microelectronics**: A leader in advanced packaging and a key partner for AMD's Chiplet products. * **JCET Group** (Changdian Keji) & **Tianshui Huatian Technology**: Major OSATs with advanced packaging capabilities. * **VeriSilicon** (Xinyuan Gufen): Provides Chiplet-based design platforms and IP. 3. **Foundry Manufacturing**: Optimization must be implemented in transistor structures and process parameters. Potential foundries for Huawei's future chips include: * **SMIC**: China's leading foundry with advanced FinFET capabilities, the most likely candidate for next-gen Kirin chips. * **Hua Hong Semiconductor** (Huahong Gongsi): A leader in specialty processes (power, embedded memory). * **Nexchip Semiconductor** (Jinghe Jicheng): Major foundry for display driver ICs and MCUs. The Tau Law represents a strategic move towards architectural innovation and design-process co-optimization, driving demand across the domestic semiconductor supply chain.

marsbit05/25 11:33

Huawei's "Tao Law": A Comprehensive Overview of Core Companies

marsbit05/25 11:33

MLCC Capacitor Price Increase: A Comprehensive Overview of Beneficiary Companies

Recent teardown reports of Nvidia's next-generation AI chips have reignited investor interest in the MLCC (Multi-Layer Ceramic Capacitor) sector. Analysis of the Rubin architecture VR200 server reveals a 30% increase in MLCC count and a 182% surge in component value per rack compared to the previous generation, with GPU board usage nearly doubling. High-power, high-voltage hardware designs are driving massive adoption of high-end, high-withstand-voltage, and large-capacity MLCCs, exacerbating supply shortages. The global MLCC supply-demand balance remains tight. Leading Japanese and Korean manufacturers have successively raised prices across series, compounded by overseas capacity constraints and long-term customer order locks at major factories. Delivery lead times for high-end products now exceed 20 weeks, with capacity struggling to keep pace with surging orders. Demand drivers include AI servers, automotive electronics, and recovering consumer electronics, leading to both volume and price increases for MLCCs. The industry chain beneficiaries are outlined as follows: **1. MLCC Product Manufacturers:** Direct beneficiaries of price hikes. Key Chinese companies include Fenghua Advanced Technology (leading domestic player), Sanhuan Group (vertical integration from materials to products), and others like Hongyuan Electronics (military focus) and Torch Electron (specialty ceramics). **2. MLCC Raw Materials & Components:** The foundation of the supply chain. * **Release Film:** A critical consumable in production. Companies include Jiemei Technology (domestic leader), Shuangxing New Materials, and Sidike. * **Metal Powders (Ni/Cu):** Core materials for internal electrodes. Key suppliers are Boqian New Materials, Yuean New Materials, and Gripm Advanced Materials. * **Dielectric Ceramic Powder:** The core material determining MLCC performance. Sinocera Advanced Materials is a global leader, while Sanhuan Group and Fenghua Advanced Technology also have significant in-house capabilities. The report highlights that rising AI server power is significantly increasing requirements for chip capacitors and inductors, forecasting explosive industry growth aligned with projected GPU/TPU shipments through 2027-2028.

marsbit05/25 02:57

MLCC Capacitor Price Increase: A Comprehensive Overview of Beneficiary Companies

marsbit05/25 02:57

The Underlying Logic of Bottleneck Propagation in the AI Computing Power Industry Chain

The article analyzes the evolving bottleneck progression within the AI compute supply chain. Initially constrained by GPU chip and advanced packaging capacity (2022-2024), the primary bottleneck shifted to HBM memory (2024-2025) due to massive model parameter growth. As cluster scale expands, physical limits of copper interconnects are making optical interconnect technologies the next critical phase (2025-2026). The ultimate, emerging constraint is power delivery and advanced liquid cooling (from 2026 onward), driven by skyrocketing rack power densities exceeding traditional infrastructure limits. The core thesis is that AI compute demand follows a "Leontief" production function where solving one bottleneck immediately exposes the next in the sequence: Compute (GPU) → Memory (HBM) → Interconnect (Optics) → Power & Cooling. Each shift reallocates value and investment across the semiconductor and infrastructure landscape.

marsbit05/22 12:25

The Underlying Logic of Bottleneck Propagation in the AI Computing Power Industry Chain