# Data Center Related Articles

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

$500 Billion, 20-Year Lease: OpenAI in Talks for 10GW Ohio Data Center, Nvidia Set to Act as Credit 'Backstop'

OpenAI is in advanced negotiations with SB Energy, a SoftBank subsidiary, to lease a massive 10-gigawatt AI data center campus planned for a former uranium enrichment site in Pike County, Ohio. The proposed 20-year lease could involve total rental payments amounting to tens of billions of dollars, with the first 800-megawatt phase slated for 2028. A key structural innovation reported is that Nvidia is in discussions to act as a credit guarantor for OpenAI's lease payments and SB Energy's project financing. This marks a significant expansion of a financing model where major tech firms back AI startups' infrastructure commitments, following similar reported arrangements between Google and Anthropic. The project is part of a larger U.S.-Japan investment framework and involves SB Energy building 9.2 GW of gas-fired power generation. The total cost for the required IT hardware, primarily Nvidia chips, is estimated at around $350 billion, for which OpenAI is seeking separate financing. This deal represents a shift in OpenAI's strategy towards large-scale bilateral agreements for its own compute infrastructure, moving away from earlier joint venture plans like the shelved "Stargate" project. This massive infrastructure commitment coincides with OpenAI's confidential IPO filing. Analysts expect its long-term cloud and compute obligations, totaling over $665 billion, to be a major focus for SEC scrutiny and investor due diligence. SB Energy has also announced its own IPO plans, creating a complex web of financial interdependencies between OpenAI, its infrastructure partner, and its key chip supplier.

marsbit06/10 03:36

$500 Billion, 20-Year Lease: OpenAI in Talks for 10GW Ohio Data Center, Nvidia Set to Act as Credit 'Backstop'

marsbit06/10 03:36

SemiAnalysis Report Claims Delay in Two Key Technologies, Triggers Sharp Decline in 'Optoelectronics', Sparking Online Debate Over CPO

A report from analysis firm SemiAnalysis, claiming significant delays in two key AI data center technologies, triggered a sharp sell-off in the photonics sector and sparked intense online debate. The report, dated June 10, states that NVIDIA's 800VDC power architecture rollout is pushed to 2028 and CPO (Co-Packaged Optics) mass production is likely delayed until 2028 or even 2029. Following the news, U.S. optical communication stocks fell sharply, with AAOI dropping 17% and Lumentum down about 8%. The delays were attributed to engineering challenges like photonic engine yield and cost-effectiveness, not a disappearance of demand. Simultaneously, an interview with NVIDIA's networking SVP Gilad Shainer presented an opposing, optimistic view, stating CPO is "the most exciting thing" and shipments would begin scaling in the second half of the year. This contradiction fueled debate on social media. Bears pointed to unresolved reliability and maintenance hurdles for CPO. Bulls argued the delay simply redirects capital to interim solutions like traditional pluggable optical modules and NPO (Near-Packaged Optics), extending their revenue runway. Some users questioned the report's internal logic and timing, noting similar views had circulated earlier. Analysts highlighted potential beneficiaries, including companies in the 1.6T pluggable modules, NPO, and 400VDC power transition supply chains. The consensus suggests the market reaction reflects a recalibration of the technology adoption timeline rather than a fundamental weakening of AI infrastructure demand, with key bottlenecks like power, storage, and GPUs remaining unchanged.

marsbit06/10 02:08

SemiAnalysis Report Claims Delay in Two Key Technologies, Triggers Sharp Decline in 'Optoelectronics', Sparking Online Debate Over CPO

marsbit06/10 02:08

South Korean Stocks Plunge, Global Funds Liquidate: Has the Semiconductor Fundamentals Really Changed?

South Korean stocks experienced their sharpest decline of the year, with the KOSPI index plunging nearly 9% on Monday, triggering a market circuit breaker. Leading semiconductor firms Samsung Electronics and SK Hynix were heavily sold off, raising questions about whether the AI-driven bull market has reached an inflection point. This sell-off was largely triggered by a significant drop in the U.S. semiconductor sector late last week. Concurrently, NVIDIA CEO Jensen Huang visited Seoul over the weekend, meeting with top executives from SK Group, Samsung, LG, and NAVER. He announced a new multi-year partnership with SK Hynix to co-develop next-generation memory products for AI data centers. Huang emphasized that AI infrastructure build-out remains in its early stages, creating a stark contrast between market panic and ongoing, strengthened industry collaboration. The article argues that South Korea has become one of the most sensitive markets for global AI-related capital flows, functioning like a large AI memory ETF due to the heavy weighting of its chipmakers. The current market turmoil reflects a shift in investor focus: from simply betting on overall AI growth to scrutinizing which companies will actually capture the profits from that growth. This "profit pool reassessment" phase is causing high volatility based on supply chain news and earnings guidance. Ultimately, the direction of the Korean market will be determined by external factors—NVIDIA's orders, HBM supply-demand dynamics, and capital expenditures from cloud service providers—rather than domestic conditions. The disconnect between sharp price corrections and continued strong signals from the industry core leaves the market at a crossroads, awaiting clearer data on the durability of AI infrastructure demand.

marsbit06/08 04:29

South Korean Stocks Plunge, Global Funds Liquidate: Has the Semiconductor Fundamentals Really Changed?

marsbit06/08 04:29

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

"Old Dogs" Become AI's New Darlings: Revaluing Legacy Infrastructure The AI investment narrative is shifting. Beyond the spotlight on core chipmakers like Nvidia, a new wave of interest is rising for legacy tech companies—Dell, HPE, Nokia, Cisco, Corning, Western Digital—once labeled as slow-growth, outdated stories. This resurgence stems from AI's evolution from model development to real-world deployment, creating massive demand for physical infrastructure. As AI moves into data center construction and enterprise adoption, the focus turns to who can actually build and deliver complex systems. These established players hold decades of experience in supply chains, integration, networking, and enterprise delivery—assets now critical for scaling AI. The revaluation can be grouped into three key infrastructure areas: 1. **Servers & Integration (e.g., Dell, HPE):** They are becoming essential system integrators, transforming GPUs into full-scale AI servers with networking, power, and cooling, then delivering them to clients. Strong recent earnings and AI-specific revenue/order growth for Dell and HPE underscore this shift. 2. **Networking & Connectivity (e.g., Corning, Nokia, Cisco):** As AI clusters grow, high-speed data transfer becomes paramount. Corning benefits from fiber demand for data center links, Nokia is exploring AI-integrated wireless networks (AI-RAN), and Cisco sees surging orders for data center switches—all critical for efficient AI operations. 3. **Storage (e.g., Western Digital, Seagate):** The AI data explosion requires vast capacity. Beyond high-speed memory (HBM), there's growing need for high-capacity HDDs to store training data, logs, video, and cold/archival data cost-effectively. This revaluation, however, is not a blanket endorsement. True reassessment requires concrete proof: AI-driven orders and revenue growth, upward revisions to company guidance, and sustainable improvements in profit quality, not just top-line sales. In essence, AI is not turning all old tech firms into high-growth stocks; it is selectively re-pricing the "old assets" of companies that are mission-critical for building the new AI infrastructure, transforming their legacy capabilities into renewed growth engines.

marsbit06/05 00:55

From 'Old Dogs' to 'New Darlings': How AI is Revaluing Old Infrastructure, from Dell to Nokia

marsbit06/05 00:55

Standing in the Light: A Comprehensive Guide to the Optical Module and CPO Supply Chain

"Standing in the Light: Understanding the Optical Module and CPO Industry Chain" This article analyzes the critical role of optical communication technology, specifically optical modules and Co-Packaged Optics (CPO), as the "nervous system" for modern AI data centers. With exponential growth in AI computational demands (e.g., NVIDIA's Vera Rubin architecture), traditional electrical interconnects using copper cables face severe bottlenecks in bandwidth, power consumption, and signal integrity over distance. The core function of an optical module is to act as a "translator," converting electrical signals from chips into optical signals for transmission over fiber (and vice-versa). Key internal components include lasers, modulators, photodetectors, drivers, and DSP chips. The industry is currently transitioning from 800G to 1.6T modules. However, the future lies in CPO. This next-generation technology integrates the optical engine directly with the switch ASIC/XPU on the same package substrate, drastically reducing power consumption (by ~3.5x according to NVIDIA), overcoming bandwidth density limits, and minimizing signal attenuation compared to traditional pluggable modules. Key challenges for CPO include advanced packaging capacity (dominated by TSMC), thermal management, repairability, and standardization. The article details the broader technology landscape, including Near-Packaged Optics (NPO, a pragmatic intermediate step), Linear-drive Pluggable Optics (LPO), Optical I/O (OIO for chip-level integration), and Optical Circuit Switches (OCS). A comprehensive CPO industry chain is mapped, highlighting shifting power dynamics: * **Architecture Definers:** NVIDIA, Broadcom, and Marvell now hold greater influence. * **Advanced Packaging & Manufacturing:** TSMC is central; Fabrinet is a key EMS player. * **Lasers ("The Heart"):** A strategic bottleneck. EML lasers are led by Lumentum and Coherent (both receiving major NVIDIA investments). CW lasers, favored for CPO/silicon photonics, see strong Chinese players like Source Photonics and Sicoya. * **Silicon Photonics Chips:** The mainstream path for CPO engines, with key players like Broadcom, Intel, Marvell, and China's Accelink. * **Fiber Connectivity Components:** A major new, high-growth market created by CPO, including Fiber Array Units (FAU), Polarization-Maintaining Fiber (PMF), and MPO connectors. Companies like Tianfu Communication and US Conec are leaders. * **Fiber & Cable:** Experiencing a super-cycle (e.g., Corning, Yangtze Optical Fiber). * **PCB/Substrates:** Requiring advanced materials (e.g., Shengyi Tech). * **DSP & SerDes:** Functions are integrated into switch ASICs in the CPO era (e.g., Broadcom, Astera Labs). * **Optical Module Makers:** Transitioning from standalone module suppliers to providers of optical engines and NPO/LPO solutions while riding the current pluggable boom (e.g., Zhongji Innolight, Eoptolink). The investment timeline is segmented: Short-term (2026-2027) features the "last feast" for pluggable modules and CPO's initial rollout. Medium-term (2027-2029) will see CPO expand and NPO peak. Long-term (2029-2032+) involves CPO/OIO penetration into intra-rack scaling. In conclusion, optical interconnects are fundamental to AI infrastructure. The competitive landscape sees US firms leading in architecture and high-end chips, TSMC in advanced packaging, and Chinese firms holding strong positions in modules, connectivity components, CW lasers, and fiber/cable. The future belongs to companies that can navigate the technological shift from "selling shovels" (modules) to "building highways" (CPO/OIO infrastructure).

marsbit06/04 10:10

Standing in the Light: A Comprehensive Guide to the Optical Module and CPO Supply Chain

marsbit06/04 10:10

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

Marvell Technology's stock price surged from under $10 in 2016 to a record $290 in June 2026, fueled not by making GPUs, but by dominating AI infrastructure connectivity. This analysis argues the market misvalues MRVL as merely a smaller Broadcom in custom AI chips, overlooking its true, unique position. Marvell's core strength lies in enabling high-speed data flow for AI clusters through three interconnected businesses. First, it holds a commanding ~70% market share in high-speed optical DSPs (essential for data center light modules), a deep-moat business with accelerating growth. Second, its custom AI chip design business serves hyperscalers like AWS, Microsoft, and Google, with a significant revenue pipeline despite lower margins. Third, stable cash flows come from Ethernet switch chips and enterprise storage controllers. Together, they form a full-stack "AI data movement" platform. CEO Matt Murphy's transformative leadership since 2016, involving strategic divestments, key acquisitions (like Inphi for optical DSPs), and securing long-term agreements with major cloud providers, repositioned the company. A pivotal $2 billion strategic investment from NVIDIA in 2026 underscored Marvell's critical role in the AI ecosystem, particularly through collaborations like NVLink Fusion. While Marvell faces risks—including client concentration (losing the Amazon Trainium3 design), lower-margin business mix, competitive threats, insider selling, and complex supply chains—its fundamentals remain strong. The optical interconnect moat is widening with the acquisition of Celestial AI (photonics fabric), and financial metrics show accelerating revenue growth and operating leverage. With a PEG ratio suggesting undervaluation relative to its growth, the thesis is that the market undervalues Marvell's monopolistic position in AI "plumbing" while overemphasizing its competitive custom chip segment. The story transcends investing, symbolizing how in any complex system—from the internet to AI—the value of "connection" ultimately surpasses that of individual "nodes."

marsbit06/04 06:40

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

marsbit06/04 06:40

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

**Summary:** At Computex 2026, Arm CEO Rene Haas announced that ByteDance and Oracle have adopted Arm's self-designed Arm AGI data center CPU. The company expects significant revenue growth from this product, projecting $20 billion in demand for the 2027/2028 fiscal years. Haas noted that restricting AI-capable CPUs from the US to China is nearly impossible due to their widespread applications. Arm's stock has surged dramatically this year, notably rising 16% after NVIDIA's Arm-based Vera CPU and RTX Spark announcements. A highlight was the informal, humorous on-stage conversation between Haas and NVIDIA CEO Jensen Huang. Huang joked about NVIDIA's failed attempt to acquire Arm and playfully lamented selling his Arm shares. Both executives showed a clear sense of camaraderie and shared regret over the missed merger. Key technical topics were discussed: 1. **AI PC Design:** Huang explained NVIDIA's RTX Spark superchip (with a 20-core Arm CPU) is designed for future AI agents that will autonomously run and use tools on PCs, blending local and cloud processing. 2. **Agent vs. OS:** Huang emphasized the operating system remains crucial, as AI agents rely on its APIs and tools to function. 3. **Growth Constraints:** He identified the shift to "useful AI" that generates profitable tokens as a primary driver for immense, almost limitless, computational demand. Haas outlined Arm's strategy across PC and data centers. For PCs, Arm collaborates with partners like NVIDIA and MediaTek, offering its compute subsystem (CSS) for custom SoCs. In data centers, its Arm AGI CPU (built on TSMC's 3nm process) has gained major partners including OpenAI, Meta, and now ByteDance and Oracle. Arm presented a multi-year roadmap for its in-house CPU line. The article concludes that while GPUs dominated the AI training race, the explosion of AI agents is shifting significant focus to CPUs for inference, state management, and tool orchestration. The industry is trending towards vertical integration, with companies like cloud providers designing chips and chip/IP firms offering full solutions, all competing to deliver more efficient computing per watt.

marsbit06/04 04:51

ByteDance Adopts Arm CPUs, Jensen Huang: So Sad I Didn't Buy Arm

marsbit06/04 04:51

After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

The stock price of Marvell Technology surged 32.5% on June 2nd, driven by NVIDIA CEO Jensen Huang highlighting its custom ASICs and optical interconnects as core to AI data center architecture. This event brought attention to the Chinese semiconductor family behind Marvell: the Dai siblings. The story centers on three siblings, all UC Berkeley graduates, whose three-decade entrepreneurial journey aligns with major semiconductor industry shifts. In 1995, youngest sister Dai Wei Li co-founded Marvell with her husband Sehat Sutardja and his brother, focusing on storage controllers. Eldest brother Dai Wei Min founded EDA company Ultima, later sold to Cadence, and later founded VeriSilicon (芯原) in China, becoming a leading semiconductor IP provider. Second brother Dai Wei Jin co-founded EDA firm Silicon Perspective (sold to Cadence) and GPU IP company Vivante, later acquired by VeriSilicon. The combined "Dai-Sutardja" family network extends beyond Marvell. Their ventures and investments form a comprehensive ecosystem for the post-Moore's Law, chiplet era. Key holdings include: Dream Big Semiconductor (AI SuperNICs, acquired by Arm), Alphawave (high-speed SerDes IP, acquired by Qualcomm), and Silicon Box (a chiplet advanced packaging foundry). VeriSilicon itself thrives on the AI ASIC and IP boom in China. Collectively, the family's AI infrastructure-related portfolio is estimated at over $22 billion. Their strategy represents a distinct path: building critical components for open standards and key manufacturing capacity in the chiplet era, rather than pursuing standalone AI chip dominance. While this path may not create the next NVIDIA, it has enabled repeated successful exits and sustained influence within the global semiconductor industry.

marsbit06/03 11:16

After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

marsbit06/03 11:16

CPU, Quietly Returning to the Center of the AI Computing Power Stage

Over the past three years, AI computing power narratives have been dominated by GPUs. However, starting in 2026, this story began to shift. While training large models remains GPU-intensive, the rapid growth of inference and AI agent workloads, which require high levels of task orchestration, concurrency, and data flow management, has highlighted a renewed critical role for CPUs. These are tasks GPUs are not designed to handle. Intel's recent launch of the Xeon 6+ processor, built on its Intel 18A process and featuring up to 288 efficiency cores (E-cores), exemplifies this strategic pivot. It is positioned not as a mere companion to GPUs but as the essential "control plane" for AI infrastructure, optimized for high-density, energy-efficient, and high-throughput workloads characteristic of AI agents and inference. This "CPU resurgence" is not about CPUs outperforming GPUs in raw computation. It reflects a systemic bottleneck: as AI scales from training single models to deploying countless intelligent agents, the demand for coordination and data handling surges. Major cloud providers are also developing their own high-density ARM-based server CPUs for similar workloads. However, Intel's success with this strategy faces significant challenges. Competition includes NVIDIA's integrated CPU-GPU solutions, the expanding adoption of cloud vendors' in-house ARM CPUs, and the crucial market test of Intel's 18A manufacturing process against rivals like TSMC's N2. In conclusion, CPUs are indeed reclaiming a central, though redefined, role in AI compute—managing the complex orchestration that enables massive-scale AI deployment. While the trend is clear, which company will ultimately lead this CPU resurgence remains an open question to be decided in the data centers of 2027 and beyond.

marsbit06/03 10:42

CPU, Quietly Returning to the Center of the AI Computing Power Stage

marsbit06/03 10:42

AMD Stock Price Forecast 2026 to 2030: Wall Street Signals a Major $657 Target!

AMD's stock has seen a dramatic rally, rising over 130% year-to-date to around $510 as of mid-2026. This surge is driven by a fundamental shift in the company's business, with its Data Center segment now the core contributor, posting a record $5.8 billion in Q1 2026 revenue (up 57% YoY) and exceeding 50% of total revenue for the first time. CEO Dr. Lisa Su raised the long-term server CPU Total Addressable Market (TAM) forecast to over $120 billion annually by 2030. Analyst sentiment is bullish. The consensus rating is a "Strong Buy" with a 12-month average price target of $472.17, though several firms have recently set higher targets, with Barclays issuing a street-high target of $665. Long-term models project a 2030 price range of approximately $493 to $822, with a baseline scenario near $657, anchored to AMD's expanded TAM guidance. Key growth catalysts include strong demand for EPYC server CPUs and Instinct AI GPUs, partnerships with OpenAI and Meta, and the upcoming MI450 series and Helios rack-scale platform. However, significant risks remain, including a high forward P/E ratio exceeding 169x and increased competition, notably from NVIDIA's planned entry into the server CPU market. Investors must weigh the strong execution and growth trajectory against these substantial valuation and competitive pressures.

marsbit06/02 13:12

AMD Stock Price Forecast 2026 to 2030: Wall Street Signals a Major $657 Target!