# Supply Chain Related Articles

HTX News Center provides the latest articles and in-depth analysis on "Supply Chain", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Both OpenAI and Anthropic are 'Developing Their Own Chips' — Beyond Cost, the Control Over Computing Power is Paramount

OpenAI and Anthropic are both advancing plans to develop custom AI chips, driven by the need to control computing power and reduce costs. According to reports, Anthropic is in early-stage development of its own chips and in talks with Samsung for manufacturing, while OpenAI is collaborating with Broadcom and TSMC, aiming to deploy its first inference chip by late 2026. The primary motivation extends beyond just lowering expenses. For these large model companies, chips are core production assets. By designing specialized hardware (ASICs) tailored to their specific model architectures—OpenAI's being more sparse and Anthropic's more dense—they aim to achieve deeper software-hardware co-design. This synergy can significantly improve inference speed, energy efficiency, and overall unit economics, offering advantages that off-the-shelf GPUs cannot. This move does not signify an immediate replacement for suppliers like Nvidia. The process from design to deployment takes 18-24 months, and Nvidia's GPU ecosystem remains deeply entrenched. Instead, custom chips provide a strategic alternative and negotiating leverage, allowing companies to use them for specific, high-volume workloads like inference while still relying on external GPUs and TPUs for other tasks. The trend reflects a broader industry shift where AI competition is evolving from pure algorithmic prowess to integrated control over the entire software-hardware stack. Companies like Google, Amazon, Meta, and Microsoft are already on this path. For foundries like Samsung, securing orders from AI leaders like Anthropic represents a significant opportunity to expand its footprint in the advanced semiconductor market for AI. Ultimately, the race for "computing sovereignty" is now a central battleground for major AI players.

marsbit07/03 13:38

Both OpenAI and Anthropic are 'Developing Their Own Chips' — Beyond Cost, the Control Over Computing Power is Paramount

marsbit07/03 13:38

While Semiconductor Stocks Plunge, Anthropic Plans to Develop a 2nm Chip

Anthropic, the AI company behind Claude, is exploring the development of its own custom AI chip, according to a report from The Information. The company is in early discussions with Samsung Electronics to manufacture the chip using Samsung's most advanced 2-nanometer process and packaging technology. While the project is still in preliminary stages, including defining chip specifications, and could be abandoned, it marks a strategic step for Anthropic. The move comes as the company seeks greater control over its computing costs and hardware optimization, particularly for inference tasks to run its models more efficiently and cheaply. Samsung's potential involvement follows its participation as a strategic investor in Anthropic's recent $65 billion funding round. For Samsung, partnering with a major AI lab represents a significant opportunity for its foundry business to compete with market leader TSMC in advanced semiconductor manufacturing. Anthropic's CEO, Dario Amodei, has previously highlighted the immense financial challenge of securing enough computing power for anticipated growth, making cost-effective inference a critical focus. The company would join other tech giants like Google, Amazon, Microsoft, Meta, and OpenAI in pursuing custom AI silicon. However, analysts note this trend creates deeper interdependencies rather than independence, as US AI labs become more tightly woven into Asian semiconductor supply chains. Despite this move, Anthropic remains heavily reliant on a multi-cloud, multi-vendor strategy for its immediate computing needs. It has secured massive, long-term commitments for capacity from Amazon Web Services (Trainium chips), Google (TPUs), and even leased a large GPU cluster from xAI. For now, Nvidia continues to dominate the AI chip market, with its share reportedly growing to 74%.

链捕手07/03 09:54

While Semiconductor Stocks Plunge, Anthropic Plans to Develop a 2nm Chip

链捕手07/03 09:54

Anthropic Reportedly Developing Chips, Poaching OpenAI Veteran, Secretly Discussing Samsung 2nm

Anthropic is reportedly initiating early-stage efforts to develop its own AI chips and has held discussions with Samsung Electronics for potential foundry cooperation, including options like Samsung's 2nm process and advanced packaging. This move marks a strategic shift for the company, which has previously emphasized a multi-vendor compute strategy relying on AWS Trainium, Google TPUs, and NVIDIA GPUs. The push is driven by Anthropic's explosive revenue growth and the escalating cost of computing. Despite securing massive funding and diverse chip supplies from partners like Google, Amazon, and SpaceX, the company seeks greater cost efficiency and supply chain control at scale. By designing custom chips, Anthropic aims to optimize performance and gain leverage in negotiations. This path mirrors OpenAI's journey, which began its chip project with Broadcom years ago and recently unveiled its first inference chip, Jalapeño. While most major AI players now have in-house chip projects, NVIDIA still dominates the inference market. Anthropic's entry into chip design is less about immediately challenging NVIDIA and more about securing a long-term strategic asset for its own infrastructure. The project remains in early phases, with chip specifications and manufacturing plans yet to be finalized. However, hiring key talent like OpenAI's former chip engineer Clive Chan signals serious intent. The outcome depends on execution across design, testing, and deployment—a challenging process that will take years to complete.

marsbit07/03 07:55

Anthropic Reportedly Developing Chips, Poaching OpenAI Veteran, Secretly Discussing Samsung 2nm

marsbit07/03 07:55

The Most Hidden AI Winners

"The Most Under-the-Radar AI Winners" While core AI giants and their direct suppliers have dominated headlines, a group of seemingly unrelated, decades-old manufacturing companies have emerged as major beneficiaries. A key example is Japan's TOTO, famous for bathroom fixtures. Its stock soared 145% in a year, driven not by its mainstay toilet business but by its nearly 40-year-old semiconductor ceramic component unit. Specifically, TOTO manufactures electrostatic chucks—critical, hard-to-replace parts for advanced chip manufacturing processes like etching and EUV lithography. This segment, though only 9% of revenue, contributed over 54% of operating profit in FY2025 with a 43% margin. High barriers to entry, including deep know-how in high-purity ceramic sintering and long supplier certification cycles (5+ years), secure its position. This pattern repeats across industries. Nitto Boseki, a 128-year-old glass fiber maker, saw its stock rise 325% due to near-monopoly supply of T-glass, an essential low-expansion material for AI chip substrates. Similarly, Ajinomoto, the global MSG leader, commands 80-95% of the market for ABF film, a vital insulating layer in chip packaging. These "hidden" segments, often born from deep materials science expertise, are now bottleneck supplies in the AI hardware chain, enjoying pricing power and high margins. In China's A-share market, the theme combines this AI-driven demand with domestic substitution. Companies like Zhongci Electronic (advancing in electrostatic chucks) and Honghe Technology & Feilihua (in high-end electronic glass fabrics) are gaining traction. The investment thesis hinges on whether these domestic players can rapidly scale qualified capacity to capture the supply gap within the critical time window. Ultimately, these cases show that in the AI supply chain, high-profit concentrations exist not only at the cutting-edge tech frontier but also in indispensable, difficult-to-replicate materials and components. Market recognition often lags behind fundamental profit shifts, creating potential for significant re-ratings as traditional industrial firms are re-evaluated as key enablers of advanced semiconductor manufacturing.

marsbit07/02 00:34

The Most Hidden AI Winners

marsbit07/02 00:34

The Most Secretive Winners of the AI Boom

"The Most Hidden AI Winners" An unlikely group of companies are emerging as major beneficiaries of the AI boom, not from designing chips, but from supplying critical materials and components essential for advanced semiconductor manufacturing. These 'hidden winners' are traditional manufacturers whose deep expertise in materials science has become indispensable. Japanese companies are leading this trend. Toto, globally known for bathroom fixtures, has seen its stock surge 145% over the past year, driven by its 40-year-old semiconductor ceramics business, which now contributes over half of its operating profit. Its electrostatic chucks are vital for advanced chip production and require years of expertise to manufacture. Similarly, Nittobo, a 128-year-old textile firm, controls 90% of the market for T-glass, a low-expansion glass fiber essential for AI chip substrates. Ajinomoto, the world's largest MSG producer, dominates the market (80-95% share) for ABF insulating film used in chip packaging. The core insight is that chasing "advanced" chips paradoxically increases reliance on traditional, high-precision material science where supply cannot be quickly replicated. These materials are now critical bottlenecks in the AI supply chain. This trend is mirrored in China's A股 market, framed by the theme of 'import substitution'. Companies like Zhongci Dianzi (electrostatic chucks) and Honghe Technology (ultra-thin electronic cloth) are making progress, but face the test of scaling production and matching Japanese rivals' quality. The key tension lies in the slow change of market perception. While profit structures rapidly shift towards high-margin tech components, these firms retain their traditional industry classifications, creating a valuation gap that is gradually closing as their roles in the AI ecosystem become undeniable.

链捕手07/02 00:26

The Most Secretive Winners of the AI Boom

链捕手07/02 00:26

Dialogue with IOTA Foundation's Jens: From Kenya to the UK, TWIN Propels Global Trade into the '5-Minute' Era

**Summary: IOTA's TWIN Project is Speeding Up Global Trade** Jens Munch Lund-Nielsen, Head of Global Trade & Supply Chain at the IOTA Foundation, discusses how the TWIN (Trade and Logistics Information Network) project is addressing long-standing inefficiencies in global trade. Traditionally, cross-border trade involves numerous parties, extensive paperwork, and delays spanning weeks. TWIN, built on IOTA's decentralized, scalable, and low-cost infrastructure, aims to replace this fragmented, paper-based system with a real-time, trusted, and interconnected digital collaboration layer. As a neutral digital public infrastructure, TWIN allows governments, businesses, and ports to exchange verifiable data and documents without ceding control to a single entity. This solves a core coordination problem that previous, proprietary platforms failed to address due to a lack of trust and neutrality. Key real-world implementations include: * **TLIP in East Africa:** Reduced document retrieval times for flower, coffee, and tea exports from 6-7 hours to ~30 minutes, cutting administrative work by 50-60%. * **UK Ecosystem of Trust Trials:** Provided border agencies with much earlier visibility (up to 20+ hours) of incoming chilled poultry shipments from Poland, enabling better resource planning. * Other pilots focus on supply chain traceability for fruits/vegetables, port efficiency, and critical mineral sourcing. TWIN ensures interoperability across jurisdictions by adopting global standards (e.g., UN/CEFACT data models), leveraging decentralized identity systems (DIDs), and supporting legal frameworks like MLETR. Looking ahead, Jens is optimistic that a trusted "connective layer" like TWIN will scale in the coming years. Its success could fundamentally transform global trade, most notably by helping to close the current $2.5 trillion trade finance gap. By providing lenders with access to verifiable, real-time supply chain data, TWIN could unlock capital and reshape how businesses discover partners and secure financing.

marsbit06/30 02:06

Dialogue with IOTA Foundation's Jens: From Kenya to the UK, TWIN Propels Global Trade into the '5-Minute' Era

marsbit06/30 02:06

"Shocking" CPO: How Does the Glass Bridge Actually Work? Detailed Explanation from Corning

Chinese CPO stocks plunged over 6% following Corning's announcement of its Glass Bridge platform at a Seoul tech conference. The new technology utilizes wafer-level glass ion-exchange waveguides for passive alignment between fibers and photonic chips, potentially simplifying traditional CPO architectures that rely on complex Fiber Array Units and active alignment equipment. This raised market concerns about reduced long-term demand for mid-stream CPO components. Corning's official documentation details Glass Bridge as a platform for fiber-to-PIC connectivity in NPO, CPO, and high-density modules. Its key features include wafer-level manufacturing for consistent, cost-effective production; a standardized, removable MT ferrule interface for ecosystem integration; and a separable high-density connector design supporting over 24 channels for assembly flexibility. Corning positions the technology as complementary to FAUs, addressing limitations in ultra-high-fiber-count scenarios. The market reaction reflects a broader reassessment of the AI optical interconnect value chain. Funds shifted from CPO and PCB manufacturing stocks towards glass substrate concept stocks like Kaisheng Technology and Dyer Laser. Analysts note glass substrates are seen as a next-gen advanced packaging material, offering a potential path for domestic industry differentiation amid AI-driven demand for high-performance, large-scale packaging, marking a structural migration in value towards upstream specialty materials.

marsbit06/28 10:41

"Shocking" CPO: How Does the Glass Bridge Actually Work? Detailed Explanation from Corning

marsbit06/28 10:41

Apple and the Power Rebalancing with 'The Microns': Dissecting the Profit Ledger Behind the iPhone

The article analyzes the shifting profit dynamics and power balance between Apple and memory suppliers like Micron within the iPhone supply chain. It highlights a social media post criticizing Apple for raising iPhone prices while blaming memory chip cost increases, despite historically paying suppliers like Micron very little. An estimated iPhone 18 cost breakdown is referenced. Historically, memory was a minor cost component. In 2017's iPhone X, memory accounted for only about 1.6-2.3% of the price, with Apple capturing nearly 50% net profit. Over time, memory's share of the Bill-of-Materials (BOM) cost has grown significantly, reaching an estimated 12-15% for the iPhone 17 series. The core driver of this change is soaring demand for memory from the AI industry, particularly for High Bandwidth Memory (HBM) and AI servers, which is diverting production capacity and squeezing supply for consumer electronics. Memory manufacturers, after enduring periods of low profits, now hold greater pricing power. This is reflected in their recent strong financials, like Micron's 84.6% gross margin. Apple CEO Tim Cook initially described the memory price pressure as unprecedented in his 40-year career, later calling it a "once-in-a-century flood," before Apple announced price hikes across several product lines, causing a significant stock drop. Elon Musk echoed Cook's sentiment about the dramatic cost surge. The article concludes that the era of memory suppliers being at the mercy of Apple's pricing power has temporarily reversed, thanks to AI-driven demand. It notes Apple is reportedly seeking to diversify its supply chain, including exploring chips from China's CXMT.

Odaily星球日报06/28 06:03

Apple and the Power Rebalancing with 'The Microns': Dissecting the Profit Ledger Behind the iPhone

Odaily星球日报06/28 06:03

活动图片