供应链分析
产业链结构、上下游与瓶颈环节研究 · 共 1440 条 · 滚到底自动加载更多
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对比JTNC与AbsoLics，看好后者在CPO及玻璃基板领域的先发优势。
是 $JTNC 吗？很难想到多少纯概念股，但它们做的是 TGV，而非用于 $NVDA 共封装光学(CPO) 的光学方案，如康宁/AbsoLics。我原本更关注 CPO 方面，但还有其他机会。AbsoLics 似乎已是明确的首选，因为其市值仅 25 亿美元，获得美国 CHIPS 法案政府资助，且率先上市。尽管背负沉重包袱，但鉴于其体量较小，其玻璃基板垂直整合业务应能强力带动整体表现。
英文原文
Is it JTNC? Can't really think of many pure-play, but they're for TGV, not optical used for $NVDA CPO like Corning/Absolics. I was more focused on CPO aspect but there's other opportunities. Absolics seems like the clear favorite already since it's $2.5B MC, funded by US Gov from CHIPS, and first-to market. It does carry heavy baggage, but its glass substrate vertical should just hard-carry the rest given the small size.
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2026年十大主题投资：聚焦AI供应链瓶颈、软体机器人及支付颠覆。
2026年通讯。 主题投资：演进、颠覆与瓶颈 1. 软体机器人 - 向 $TSLA、$ONDS、波士顿动力演进。 2. 硅光子(SiPh) - 磷化铟(InP)瓶颈 | $AXTI、$LITE、$GOOGL 3. 玻璃基板 - 瓶颈 | $NVDA、$INTC、$TSM 4. 资金流动 - 对 $V、Stripe、$BOA 的颠覆 5. AI云层级 - 瓶颈 | $NBIS、$IREN、$HUT 6. LLM网络安全 - 向 $CRWD、$CSCO、$MSFT 演进 7. 低轨(LEO)太空基础设施 | 向 $RKLB、SpaceX、$ASTS 演进 8. 消费者代理工作流(50步) - 对消费者劳动力的颠覆，来自Manus、$PATH Cognition 9. 分布式计算延迟 - 瓶颈 | $TSLA、$AMZN、$GOOGL 10. 铜互连寿命延长 - 瓶颈 | $NVDA (LPU/Groq)、$AMD、$INTC _这是我对从公开信息综合及瓶颈二/三阶效应来看最感兴趣的主题投资的简要概述！_ 1. 软体机器人：向机器人的演进 传统机器人（Optimus、波士顿动力）依赖逆运动学控制刚性关节。软体机器人改变了数学模型。 我们已到达硬件（Optimus、波士顿动力、Figure）与LLM（Gemini、Grok、Opus）相遇的节点，正处于大规模商业化的开端。 通过使用受章鱼触手和人类皮肤启发的材料，机器人正从齿轮转向流体性，以处理极其精细的任务，如像人手一样处理农产品，或为 $ONDS/Andruil 无人机添加类章鱼延伸以拾取极重表面。 这种演进在于跳出思维定势思考机器人能做什么。我记得7年前曾与该领域的斯坦福博士合作，AI在多年研究后开始商业化，因此该领域也是如此。 将类生物流体性添加到刚性机器人中的可能性是无限的，这只是自然演进。 大多数可能是私人公司。 2. 硅光子 - AI基础设施的瓶颈“磷化铟(InP)卡脖子点” 从Blackwell Ultra集群到Google TPU已触及上限，需要光子互连 | 共封装光学(OCS)以实现扩展。 基板：$AXTI（通过Tongmei）和住友（日本）控制全球约60-70%的InP基板市场。 材料：Vital Materials（中国）和AXT等公司控制原材料铟本身的精炼（78%+的供应链）。 如果你是美国科技巨头，你2026年的整个“AI增长故事”取决于由地缘政治对手控制的材料。 唯一可扩展的解决方案是工程绕行，要么实现芯片上光传输，同时减少90%的铟使用，要么使用微小的磷化铟薄片代替大型昂贵晶圆。 瓶颈本身有机会，如AXT、住友。或帮助解决它的公司如 $POET。 3. 玻璃基板 - 解决从 $NVDA 到其他公司的共封装光学(CPO)瓶颈 向玻璃基板的转变本质上是半导体行业对当前材料物理极限的回答。 当前芯片位于有机材料（本质上是专用塑料）制成的基板上。随着芯片变大，如Nvidia巨大的GPU封装，塑料基板会翘曲。 因此，玻璃基板正成为共封装光学(CPO)的行业标准，因为它们解决了光子学中最大的对齐问题。 美国政府已视其为必要，我们看到巨额补贴流向这些公司。 $INTC、三星电子、Absolics（SKC子公司）、DNP等是主要受益者，尤其是随着MRVL和 $AVGO（推动光学开关的玻璃）推进CPO革命。 4. 资金流动 - 对卡网络、银行、交易所和支付的颠覆 几十年来，资金转移一直是“收费公路”业务。每次刷卡，2%到3%的钱流入卡网络（Visa/Mastercard）和发卡行的口袋。 或者从交易所买卖加密货币是0.2-1%。这是历史上最有利可图、“不可杀死”的商业模式。 直到现在。2025年的“天才法案”刚刚将金钱传输许可证或银行特许状交给像 $XRP 这样的公司，赋予了他们王国钥匙。 对我来说并非理论。我恰好正在自己的初创公司与创建V / $PYPL 实时支付网络的人一起从事这项工作。 但基本上，拥有现有MTL或追求银行特许状并利用天才法案及其他技术的公司，现在可以通过在美联储和区块链之上进行结算来绕过传统百分比费用，有效地将基于百分比的费用转化为几美分。 99%的公司会这样做吗？可能不会，因为支付行业的所有利润率都将归零。但我乐意看到。 但基本上，Stripe以11亿美元收购Bridge本应是对现有公司的红色警报，表明1天ACH、 interchange模式、25美元国际转账的日子即将结束。 这扩展到许多其他相邻领域，从低费用颠覆者如 $HOOD、Mercury，一直到稳定币新银行，或制作自己稳定币的公司如 $SOFI。 5. AI云层级 - 超大规模计算瓶颈的解决方案 当超大规模云厂商被困在3-5年的电网互连队列中时，像WULF和IREN这样的矿工今天就拥有即插即用的GW级算力。 这是千载难逢的机会，超大规模云厂商将其现金牛云收入流向小公司。 这里有不同的层级，从Fluidstack、Poolside、Fireworks在GPU编排层，到IREN等公司构建的裸金属层。 然后有成为超大规模云厂商本身，如NBIS拥有物理位置、GPU、软件编排，然后为推理提供简单接口。 这是少数小公司在未来一两年成为AWS或Azure，或被收购（例如GOOGL以47亿美元收购Intersect）的机会。 像NBIS、IREN、CRWV这样的新云，以及像CIFR、WULF、HUT这样的colo玩家（以及私人部门->能源）将受益。 6. LLM网络安全 - 向现代安全和漏洞防御的演进 最近的报告（例如来自Anthropic红队）显示，高级模型如Opus（及未来版本）可以自主扫描开源智能合约，并在几分钟内识别价值数百万美元的“零日”漏洞。 含义：如果AI能在不可变的区块链合约中找到逻辑缺陷，它也能在银行的SWIFT API或电网控制软件中找到缺陷。 同样适用于KYC/AML。像Gemini Nano Banana这样的模型能够创建逼真的图像/视频，人们能够绕过许多程序。 这个领域有很多不性感但具Alpha潜力的事情，如LLM自动化SOC2/PCI DSS合规，代理坐在服务器上，持续监控日志，并自动生成审计所需的证据。 7. 低轨(LEO)太空基础设施 | 向拓展最后疆域的演进 太空是下一个大事情。这并不新鲜。（希望你懂这个笑话）。但从像 $RKLB、SpaceX这样的公司，到解决轨道拥堵或发射节奏瓶颈的公司，再到像ASTS或Starlink这样商业化基础设施的公司，在未来一年呈现许多机会。 因此，像Impulse、Blue Origin、$ASOZF到RKLB、$ASTS这样的公司将受益于整个链条。 8. 消费者代理工作流(50步) - 对消费者劳动力的颠覆，来自Manus、PATH Cognition 这一点很简单，无需解释。但在对就业+成本节约的潜在影响上显而易见。 你如何自动化商务拓展？如何自动化营销？如何自动化软件工程师？ 这超越了ChatGPT的几步回答，直接进入现实世界，AI代理可以在X上漫游，找到合适的人，发送DM，继续对话，并在一个工作流中导致销售电话。 这是“聊天机器人”时代的结束和“行动”时代的开始，取代公司以前需要的所有人。 我尚未看到任何公司大规模做到这一点。拥有这些的公共公司如META并没有呈现最佳敞口。也许是 $PATH 在公共空间。 9. 分布式计算延迟 - 解决AI计算容量紧张的瓶颈 像GOOGL Cloud、MSFT Azure这样的超大规模云厂商已达最大容量。 Elon Musk已经提出分布式计算作为解决此问题的未来（例如，拥有 $TSLA 网络为LLM推理提供计算）。 “Tesla计算云”论点很迷人，但我识别出的最大物理障碍是：推理延迟。 要生成“Token B”，模型必须先生成“Token A”。它不能同时做两者。如果你将一个巨大模型（如Grok-3）拆分到5辆不同的汽车中以适应内存，你必须为每个生成的Token在这些汽车之间发送数据。 因此，如果汽车之间的网络延迟甚至是20ms（5G的乐观估计），而你生成50个Token，你刚刚在计算时间之上添加了1秒的纯“等待时间”（延迟）。在使用NVLink的数据中心中，该等待时间以纳秒计。 同样适用于零售用户拥有的任何备用计算机、GPU等。有数十亿消费级GPU（Teslas、iPhones、游戏PC）90%的时间闲置。 解决推理的“分布式延迟”问题呈现了计算史上最大的套利机会之一。 尚未看到任何公司大规模完成此任务。也许NVIDIA Dynamo、$AKAM、TSLA正在接近。 10. 铜互连寿命延长 - 解决Nvidia和其他公司的瓶颈 既然我们不能拥有无限的InP，我们必须用现有的东西（例如铜）进行工程绕行，所以铜电缆可以做物理上说它不应该做的事，如在不损失信号的情况下跨机架传输224G信号。 行业在InP上遇到了硬性停止，美国在物理上无法开采和精炼足够的InP将数据中心中的每个链接变成光纤。 如果有任何帮助，那就是好事。例如，NVDA对Groq团队和IP的200亿美元“收购雇佣”。LPU更多是关于推理延迟/架构，但它作为副产品解决了铜寿命延长。Groq的整个架构在延迟上击败了Nvidia，因为它拒绝了光学。Groq使用“确定性”网格，依赖芯片之间的直接电气（铜）连接，避免光学开关的“抖动”和转换时间。 像 $ALAB、$CRDO、Groq，或任何能找到用铜绕过光学瓶颈方法的公司将是赢家。 _这里有从私人部门投资到公共部门的众多交易！只是今天即兴写下了我的想法，但乐意稍后详细阐述。 无论如何，我相信这些主题投资中的许多： 从投资InQ瓶颈绕行（$POET）或瓶颈本身（$AXTI）到公共部门的颠覆者（$CRCL）。 到投资铜扩展瓶颈修复（Groq）、银行特许状颠覆者（Mercury）到私人部门的演进公司（Lightmatter、Festo）。 在2026年呈现不对称上行空间。 新年快乐！
英文原文
2026 Newsletter. Thematic Investments: Evolution, Disruption, and Bottlenecks 1. Soft Robotics - Evolution to $TSLA, $ONDS, Boston Dynamics. 2. SiPh - InP Bottleneck | $AXTI, $LITE, $GOOGL 3. Glass Substrates - Bottleneck | $NVDA, $INTC, $TSM 4. Money Movement - Disruption to $V, Stripe, $BOA 5. AI Cloud Layers - Bottleneck | $NBIS, $IREN, $HUT. 6. LLM Cybersecuirty - Evolution to $CRWD, $CSCO, $MSFT 7. LEO Space Infrastructure | Evolution to $RKLB, SpaceX, $ASTS 8. Consumer Agentic Workflows (50 Step) - Disruption to the Consumer Workforce, from Manus, $PATH Cognition 9. Distributed Computing Latency - Bottleneck | $TSLA, $AMZN, $GOOGL, 10. Copper Interconnect Life Extension - Bottleneck | $NVDA (LPU/Groq), $AMD, $INTC _ This is an light overview of thematic investments I find the most interesting from a public-information synthesis perspective + second/third-order effects from bottlenecks! _ 1. Soft Robotics: The Evolution to Robotics Traditional robotics (Optimus, Boston Dynamics) relies on Inverse Kinematics to rigid joints. Soft robotics changes the math. We've met the point where hardware (Optimus, Boston Dynamics, Figure) met LLMs (Gemini, Grok, Opus), and we're at the beginning of possible widespread commercialization. By using materials inspired by octopus tentacles and human skin, robots are moving away from gears and toward fluidity to handle extremely delicate tasks like handling produce like the human hand, to picking up extremely heavy surfaces adding Octopus-like extensions to $ONDS/Andruil Drones. The evolution is thinking outside the box in terms of what robotics can do. I remember working with some Stanford PHds in this field like 7 years ago, and it just so happens AI is starting to be commercialized after many years of research. So expected, this field to be as well. Possibilities are limitless adding organism-like fluidity to rigid robotics, this is just the natural evolution. Most of these are prob private companies. _ 2. Silicon Photonics - Bottleneck of the AI Infrastructure "InP Chokepoint" Blackwell Ultra Clusters to Google TPUs have hit the upper wall and requires photonics for interconnects | OCS to scale up. The Substrates: $AXTI (via Tongmei) and Sumitomo (Japan) control roughly 60-70% of the world's InP substrate market. The Materials: Companies like Vital Materials (China) and AXT control the refining of the raw Indium itself (78%+ of supply chain). If you are a US tech giant, your entire "AI Growth Story" for 2026 depends on materials controlled by geopolitical rivals. The only scalable solution is engineering around it, either by delivering light-on-chip, while using 90% less InP or companies that use tiny slivers of Indium Phosphide instead of large, expensive wafers. There's opportunities with the bottleneck itself like AXT, Sumitomo. Or companies that help address it like $POET. _ 3. Glass Substrates - Fixing the Bottleneck for CPOs from $NVDA to others. The shift toward glass substrates is essentially the semiconductor industry’s answer to a physical wall they are hitting with current materials. Current chips sit on a substrate made of organic materials (essentially specialized plastic). As chips get larger, like Nvidia's massive GPU packages, plastic substrates warps. So, glass substrates is becoming the industry standard for Co-Packaged Optics (CPO) because they solve the single biggest problem in photonics with alignment. US Government already sees this as a necessity and we've seen huge subsidies funneling down to some of these companies. Companies like $INTC, Samsung Electronics, Absolics (SKC Subsidiary), DNP, and others are the main beneficiaries, especially as MRVL and $AVGO (driving glass for optical switches) move forward with CPO revolution. _ 4. Money Movement - The Disruption to Card Networks, Banking, Exchange, and Payments For decades, moving money has been a "toll road" business. Every time you swiped a card, 2% to 3% of that money vanished into the pockets of the Card Networks (Visa/Mastercard) and Issuing Banks. Or buying/selling crypto from an exchange would be .2-1%. It was the most profitable, "un-killable" business model in history. Until now. The "Genius Act" of 2025 just handed companies like $XRP with Money Transmitter Licenses or Banking Charters the keys to the kingdom. Not really theoretical for me. I happen to be working on this myself at my own startup with some folks who created V / $PYPL's real-time payment networks. But basically companies with existing MTLs or pursuing banking charters leveraging the Genius Act and some other tech can now bypass legacy % fees by doing settlement on top of the Federal Reserve and blockchains, effectively converting percentage-based fees into a few cents. Would 99% companies do it? Probably not since every single margin from across the payment industry would just go to 0. I'd be happy though. But basically Bridge's $1.1B acquisition by Stripe should have been a red-alarm to existing companies that days of 1-Day ACH, interchange models, $25 international transfers, are soon to be over. This extends to many other adjacents from low fee disruptions like $HOOD, Mercury all the way to Stablecoin Neobanks, or companies making their own stablecoins like $SOFI. _ 5. AI Cloud Layers - The Solution to HyperScaler compute Bottleneck While Hyperscalers are stuck in 3-5 year grid interconnection queues, miners like WULF and IREN are sitting on plug-ready GWs today This is the opportunity of a lifetime as hyperscaler funnel their cash cow Cloud revenues down to tiny companies. There's many different layers to this from Fluidstack, Poolside, Fireworks on the GPU orchestration layer, to the bare metal layer that companies like IREN are building. Then there's becoming the hyperscaler themselves like NBIS owning the physical locations, the GPU, software orchestration, and then providing simple interfaces for inference. This is the opportunity for a few small companies to become Amazon Web Service or Microsoft Azure over the next year or two, or get acquired (eg. GOOGL buying Intersect for $4.7B) Neoclouds like NBIS, IREN, CRWV, down to colo plays like CIFR, WULF, HUT (and private sectors -> Energy) stand to benefit. _ 6. LLM Cybersecurity - The Evolution to Modern Security and Vulnerability Defense Recent reports (e.g., from Anthropic's Red Team) showed that advanced models like Opus (and future iterations) could autonomously scan open-source smart contracts and identify "Zero-Day" exploits worth millions of dollars in minutes. The Implication: If an AI can find a logic flaw in a immutable Blockchain contract, it can find a flaw in a bank's SWIFT API or a power grid's control software. Same with KYC/AML. Models like Gemini Nano Banana are able to create realistic images/videos of people and people are able to get past a lot of programs. There's tons of things as an unsexy alpha in this field like LLMs automating away SOC2/PCI dss compliance to agents sitting on a server, continuously monitor logs, and auto-generate the evidence needed for auditors. 7. LEO Space Infrastructure | The Evolution to Expanding into the final frontier. Space is the next big thing. This is not anything new. (hope you got the joke). But anywhere from companies like $RKLB, SpaceX. Companies that fix orbital congestion or launch cadence bottlenecks. To companies that commercialize the infrastructure like ASTS or Starlink present many opportunities over the next year. So companies like Impulse, Blue Origin, $ASOZF to RKLB, $ASTS stand to benefit across the entire chain. 8. Consumer Agentic Workflows (50 Step) - Disruption to the Consumer Workforce, from Manus, PATH Cognition This one is simple and needs no explanation. But largely obvious in potential impact on employment + cost saving. How do you automate away business development? How do you automate away marketing? How do you automate away software engineers? This is going past few step ChatGPT answers and directly in to the real world where an AI agent can roam X, find the right people, DM someone, continue conversations, and lead to a sales call in just one workflow. This is the end of the "Chatbot" era and the beginning of the "Action" era replacing everyone previously required in a company. I haven't quite seen this done at scale yet with any company. Public companies like META that own these, don't really present the best exposure. Maybe $PATH for public space. 9. Distributed Computing Latency - Fixing the Bottleneck for AI Compute Capacity Strains Hyperscalers like GOOGL Cloud, MSFT Azure at max capacity. Elon Musk already floated distributed computing as the future of solving this issue (eg. having networks of $TSLA's providing compute for LLMs for inference). The "Tesla Compute Cloud" thesis is fascinating, but the single biggest physical barrier I've identified is: Inference Latency. Too generate "Token B," the model must first finish generating "Token A." It cannot do both at the same time. If you split a massive model (like Grok-3) across 5 different cars to fit it in memory, you have to send data between those cars for every single token generated. So, if your network latency between cars is even 20ms (optimistic for 5G), and you are generating 50 tokens, you just added 1 full second of pure "waiting time" (latency) on top of the compute time. In a data center using NVLink, that wait time is measured in nanoseconds. Same applies to any spare computer, GPU, and others owned by retail users. And there's billions of consumer GPUs (Teslas, iPhones, Gaming PCs) that sit idle 90% of the time. Solving the "distributed latency" problem for inference presents one of the single greatest arbitrage opportunity in the history of computing. Haven't really seen any companies that accomplished this at scale yet. Maybe NVIDIA Dynamo, $AKAM, TSLA, getting a little closer. 10. Copper Interconnect Life Extension - Addressing the Bottlenecks of Nvidia and Others Since we can't have infinite InP, we have to engineer around it with what we have (eg. Copper), so copper cables can do things that physics said it shouldnt like carrying 224G signals across a rack without signal loss. The industry is hitting a hard stop on InP where, US cannot physically cannot mine and refine enough InP to turn every link in a data center into fiber optics. If anything helps, then it's good. EG. NVDA's $20B "Acqui-hire" of Groq's team and IP. LPU is more about inference latency/architecture but it addresses copper life extension as a byproduct. Groq’s entire architecture beat Nvidia on latency because it rejected optics. Groq uses a "deterministic" mesh that relies on direct electrical (copper) connections between chips, avoiding the "jitter" and conversion time of optical switches. Companies like $ALAB, $CRDO, Groq, or anyone who can find ways to engineer around the optical bottleneck with copper will be a winner. _ There are tons of trades from both private sector investments to public! Just wrote up my thoughts on the fly today, but happy to elaborate later. Regardless I believe a lot of these thematic investments from: Investing in InQ Bottleneck Workarounds ( $POET ) or the bottleneck itself ( $AXTI ) to Disruptors ( $CRCL ) in the public sector. To Investing in copper extension bottleneck fixes (Groq), bank charter disruptors (Mercury) to evolutionary companies (Lightmatter, Festo) in the private sector. Present asymmetrical upside in 2026. Happy New Year!
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Benchmark 悄悄改口亚马逊芯片供应商，媒体误导严重。
SemiAnalysis 那就错了。Benchmark 最初声称：“我们现在有高度把握认为，该公司已将亚马逊的 Trainium3 和 4 设计输给了其台湾竞争对手 Alchip。”大量媒体对此进行了报道。但在股价下跌 14% 后，Benchmark 在无人关注时悄悄收回了该说法，基本改口称：亚马逊增加了 Alchip 作为第二设计支持供应商。媒体的框架设定糟透了。
英文原文
SemiAnalysis would be wrong then. Benchmark originally claimed: "We now have a high degree of conviction that the company has lost both Amazon's Trainium3 and 4 designs to its Taiwanese competitor, Alchip." Tons of media reported on that. But Benchmark silently walked that back after stock dropped 14%, when nobody was paying attention and basically said: Amazon added Alchip as second design support vendor. The media framing is atrocious.
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询问SKC与三星电机在CPO玻璃基板领域的看法。
@jukan05 说到三星，我很好奇你对 SKC/Absolics 和三星电机在共封装光学(CPO) 玻璃基板领域的看法，因为它们都是韩国公司。
英文原文
@jukan05 Speaking of Samsung, I’m curious what your opinion is on SKC/Absolics and Samsung Electro-mechanics on the glass substrates space for CPO, since they’re both Korean companies
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新云板块处于验证期，当前下跌是建立护城河前的黄金买入机会。
新云(Neoclouds)正处于“证明实力”阶段。 $NBIS 的年经常性收入(ARR)增长率高达700%+，达到70-90亿美元；$IREN 的数据也超过34亿美元。 许多公司拥有多年的收入可见性，并得到七大科技巨头(Mag7)超大规模云服务商的背书。 然而，市场表示： “这不是一个无限刷钱的漏洞”。 即股价上涨 -> 可转换票据/稀释 -> ARR增加 -> 循环往复。 它们现在都有资金，$NBIS 持有48亿美元以上的现金储备，$IREN 持有来自 $MSFT 预付款/票据的数十亿美元以完成建设并转化为自由现金流(FCF)。 尽管有《加速推进电气化法案(SPEED Act)》通过、OpenAI融资（降低交易对手风险）以及降息等顺风因素，但近期的下跌趋势似乎是年底税务收割、做空、主动式自动取款机(ATM)增发以及主要是： 等待证明这些公司能否从 $MSFT 与 IREN 的交易到 Nebius 的杠杆内部收益率(IRR)预测中，实现规模化的利润率。这似乎归结为执行力和等待下一次财报。 许多散户投资者在此期间似乎已经投降，但机构持股比例仅上升（$NBIS 从30%多升至50%以上）。 但非对称性就在这里： 如果 Nebius 管理层能实现20-30%的息税前利润(EBIT)利润率并达到70-90亿美元的 ARR 目标，那么在保守分析师给出200美元以上目标价(PT)的情况下，85美元的价格显得极其、极其低估。特别是考虑到 Clickhouse 的扩张/IPO 以及 Avride 与 Uber 合作的自动驾驶出租车规模化。 我在主题上也特别看好 $IREN 在微软交易上的杠杆 IRR 预测，以及来自 $CIFR / $WULF 与 $GOOGL 交易的新云数据中心(Colo)玩家。 简而言之：如果新云能在其预测的利润率、规模上执行到位，并在这2-3年的窗口期内建立自己的护城河，那么整个板块的抛售似乎是一个黄金机会。
英文原文
Neoclouds are in the "Prove It" phase. You have absurd 700%+ ARR growth rates to $7-9B from $NBIS and $3.4B+ figures from $IREN. Many have multiple year revenue visibility and backstop from Mag7 Hyperscalers. However, markets have said: "This is not an infinite money glitch". Where a stock goes up -> convertible note/dilution -> ARR increases -> repeat. They all have funding now, $NBIS sitting on a $4.8B+ cash stack, $IREN sitting on billions from $MSFT prepayment/notes to finish their buildout and turn that into FCF. Despite tailwinds from the initial SPEED act passing, OpenAI fundraising (for less counterpaty risk), and rate cuts, the recent downtrend seems to combine EoY tax harvesting with short selling, active ATMs, and mainly: Waiting for proof that these companies can deliver margins at scale from levered IRR projections on $MSFT's IREN deal to Nebius. It seems to comes down to execution and waiting for their next earnings report. Many retail investors seem to have capitulated during this time but institutional ownership has only gone up (30's from $NBIS to 50's+ now) But here's where the asymmetry comes in: If Nebius management scales to 20-30% EBIT margins with their $7-9B ARR target, this seems incredibly, incredibly off at $85 when conservative analysts are throwing out $200+ PTs. Especially considering possible Clickhouse ramp/IPO and Avride robotaxi scaling with Uber. I'm especially bullish thematically too with $IREN levered IRR projections on the Microsoft deal and Neocloud colo players from $CIFR / $WULF $GOOGL deals. TLDR: If Neoclouds can execute with their projected margins, scale, and create their own moats during this 2-3 year window, then the whole sector selloff seems like a golden opportunity.
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Cantos因光子学在ASIC部署中的关键作用，估值获溢价。
很棒的主题选择。乍一看，Cantos 似乎特别走在风险投资(VC)投资曲线的前面。虽然不清楚这家初创公司的具体细节，但仅在过去几个月里，其估值倍数可能又获得了一次溢价。尤其是考虑到光子学(Photonics)在超大规模云服务商(Hyperscaler)专用集成电路(ASIC)部署中日益增长的作用。
英文原文
Great thematic choice. Just from first glance, Cantos seems especially ahead of VCs investment curve. Don't know the details of the startup but there's likely another premium multiple applied in the past few months alone. Especially given photonics growing role in Hyperscaler ASIC deployments.
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解析AI供应链各环节标的风险收益特征，推荐TSM稳健、AXTI高弹性、NBIS高成长。
感谢关注！我来简单拆解一下：我看好金融科技(Fintech)和人工智能(AI)，这是我的两个主要成长型投资板块。像 $CRCL 这样的稳定币(Stablecoins)属于金融科技领域。至于 AI 领域，我专注于供应链投资： 新云厂商(Neoclouds) -> AI 顶层消费者/超大规模云提供商。$NBIS 是我的最爱。 顺着供应链往下，谁帮助制造 $NBIS 和 $IREN 购买的 GPU？ -> 来自 $NVDA 的 GPU，部分 $AMD，以及未来可能来自 $GOOGL、$MSFT、$AMZN 的 ASIC。 谁帮助生产这些 GPU？ -> $TSM 谁帮助在数据中心扩展这些 GPU 集群？ -> $LITE、$COHR、$AAOI 用于生产扩展 GPU 集群所需互连件的原材料是什么？ -> $AXTI 它们都主题性地搭乘 AI 资本支出(CapEx)浪潮，但敞口各不相同。 我通常不会说“1”，因为它们的风险特征不同。 如果必须为复利增长选择最安全的一个：$TSM 如果必须选择 6 个月内潜在上行空间最大的一个？$AXTI 可能因材料短缺而受益，但如果中国封锁出口也可能归零。 如果必须选择 2 年内最有可能实现 5-10 倍增长并成为超大规模云厂商的一个？$NBIS。但存在稀释风险，自动取款机(ATM)发行可能导致股价停滞数月，但从 70-90 亿 ARR 和 20% EBIT 的未来前景来看，长期非对称上行空间最大。 当然，如果 AI 资本支出浪潮放缓，它们都会下跌，因此分散投资于金融科技等其他板块是明智的。
英文原文
Thanks for following along! I'll just give you a breakdown: I like Fintech and AI, those are basically my two main growth investment baskets. Stablecoins like $CRCL are in the fintech domain. As for AI domain I am just supply chain investing: Neoclouds -> Top level consumer/hyperscaler cloud providers for AI. $NBIS is my favorite. Go down the supply chain, who helps manufacture the GPUs used that $NBIS and $IREN buy? -> GPUs from $NVDA, some $AMD, and maybe ASICs from $GOOGL, $MSFT, $AMZN down the road. Who helps create those GPUs -> $TSM Who helps scale up those GPU clusters in data centers? -> $LITE, $COHR, $AAOI What are those raw materials used to produce the interconnects to scale up those GPU clusters? -> $AXTI They're all ride the AI CapEx wave thematically, but the exposure is all different. I never typically never say "1" because they all have different risk-profiles. if I had to choose the safest one for just compounding: $TSM If I had to choose the one with the highest possible upside over 6 months? $AXTI from material shock, but it could also go to 0 if China blocks exports. If I had to choose the best chance to 5-10x and become a hyperscaler over 2 years? $NBIS. But there's risks from dilution, ATMs stalling out the stock for a few months, but highest asymmetrical upside over periods of time from 7-9B arr 20% ebit in the future But of course, if AI CapEx wave slows, then they all go down, which it's good to diversify in other segments like fintech.
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对比住友与AXTI，指出前者营收占比低但无出口管制风险。
并非如此。我个人认为这是一家很棒的公司，但其中有些细微差别。 衬底(Substrate)生产仅占住友电工(Sumitomo)总收入的很小一部分，因为它已经是一家庞大的公司，所以你无法获得相同的敞口(Exposure)。 此外，在上游方面，他们采购磷化铟(InP)材料，而 $AXTI 部分拥有10多家原材料公司，并自行进行精炼和加工。 话虽如此，与 AXT 相比，住友电工的风险更低，因为没有出口管制核弹(Export Control Nuke)的风险，而且可能有更多的西方资金流入供应链多元化。
英文原文
Not quite. I personally think it's a great company but there's nuances. Substrate prod is only a small fraction of Sumitomo's total revenue since it's already a massive company so you're not getting the same exposure. Also upstream there's InP materials that they buy while $AXTI partially owns 10+ raw material companies and does the refining and processing themselves. That being said, Sumitomo is de-risked compared to AXT since theres no export control nuke and there's probably more western money being funneled into supply chain diversification.
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COHR受上游InP原料瓶颈制约，超大规模数据中心或转向直接采购上游资源。
$COHR 表现惊人，凭借其新建的 6 英寸晶圆厂，可能是磷化铟(InP)衬底生产领域的美国领先企业。 两个细微差别： 1. 他们的产量远未达到超大规模数据中心(Hyperscalers)所需的规模，目前 $AXTI 和住友(Sumitomo)的产出量更大。 2. 他们受限于上游生长晶体所需的 InP 原料（由 Vital、$DOWA 和 $AXTI（自产）控制）。 CEO 在投资者关系(ER)会议中表示，其产能已满载，且受限于 InP 激光器（以及生产它们所需的上游一级 InP）。 我的思考过程是，超大规模数据中心可能不会继续向 $COHR 增加订单积压，而是向上游延伸。他们会直接从 Vital、$DOWA、$AXTI 等控制 InP 的企业采购 6n-7n 纯度原料，交给住友/$COHR 等晶圆厂，或者再高一级，直接收购 InP 衬底库存 -> 交给 $LITE 作为保险。 话虽如此，大量资金可能会注入西方供应链，但由于上游瓶颈，其产能仍远远不够。
英文原文
$COHR is amazing and probably the leading US company for InP substrate prod with their new 6in wafer fab. Two nuances: 1. Their production is nowhere close to the scale needed for hyperscalers that $AXTI and Sumitomo currently outputs 2. They are bottlenecked by upstream InP feedstock needed to grow crystals (owned by Vital, $DOWA, and $AXTI (captive)). CEO said in their ER that their capacity was maxed out and limited by InP lasers (and by 1 hop InP needed to produce them) My thought process is that instead of placing more order backlogs with $COHR, hyperscalers would go upstream. They would directly source 6n-7n from Vital, $DOWA, $AXTI and others that control InP, and give them to fabs like Sumitomo / $COHR or one level higher, buy out stock of InP substrates -> hand to $LITE as insurance. That being said a lot of money will likely be poured into Western supply chains but their capacity is nowhere enough since they're still bottlenecked upstream.
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质疑SMM图表代表性，指出海外采购成本远高于国内现货价。
嗯，那张SMM图表不只显示现货国内价格吗？考虑到许可证、关税和配额溢价等因素，我相当确定超大规模数据中心（hyperscalers）无法以那些价格采购。我很好奇你是否有关于西方公司支付价格与国内价格对比的更多信息，以证明这种价格分化（bifurcation）不会发生。
英文原文
Hmm, isn’t that SMM chart just showing spot domestic price though with the 10% price increase? I’m pretty sure hyperscalers can’t buy at those prices accounting for stuff like permits, tariffs, and allocation premium. I’m curious if you have more info about what Western companies pay compared to domestic rates to show that bifurcation wouldn’t occur
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澄清建模意图，探讨中美双层体系下国内产能对西方基板及原材料供需的影响。
噢，抱歉如果听起来我像是在按30倍建模，那只是一个理论示例，说明如果大幅增加成本，对物料清单(BOM)集群的影响只是轻微的。从西方角度来看，在供应冲击时期，超大规模云服务商可能会愿意支付当前价格数倍的保费作为保险。我真正想理解的是，既然看起来西方和中国之间形成了双层体系，如果国内产能提升，对于基板(substrate)级别和原材料(feedstock)的价格/供应，西方市场+超大规模云服务商会出现哪些细微差别？
英文原文
Oh, apologies if it sounded like I was modeling for 30x, it was just a theoretical example that if you increased costs by large amounts it would just be a dent in BOM clusters. In times of supply shock from a Western angle, hyperscalers would probably be willing to pay a few times current price for insurance. What I’m really trying to understand is that since it looks like a two tier system between the West and China, if domestic production ramps up, what nuances would come into play for prices/supply on Western markets + hyperscalers for substrate level + feedstock.
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分析InP原料在中美市场的供需差异及西方供应瓶颈。
你认为短缺问题是否因双层体系而更复杂？看中国国内，磷化铟(InP)原料价格正常，可能因供应充足。而在西方市场，据我所知，企业已为6N、7N纯度支付300-500%溢价。除非中国想倾销廉价材料（不太可能），否则任何有出口业务的企业都将受益于西方供应短缺带来的瓶颈。因此，若看中国国内市场，瓶颈可能没那么严重；但从西方超大规模数据中心(Hyperscaler)视角看，情况可能更严峻？
英文原文
Do you think the shortage is a bit more nuanced since it’s a two tier system? If you look at Chinese domestic InP feedstock is priced normally, maybe bc of supply availability. In western markets from the top of my head, companies are already paying a 300-500% premium for 6n, 7n. And anyone with exports would benefit from the bottleneck from a dearth in western supply unless China wants to dump cheap materials on the market (probably unlikely). So if you’re looking at bottleneck China domestic markets it might not be as dire but from a Western hyperscaler perspective it might be more serious?
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铟价持续上涨，预计2026年中出现瓶颈，$AXTI 受益最大。
更正一下上面关于铟(In)价格的内容。 6N级铟（2024年1月、2025年1月、2025年12月）~$680/公斤 -> ~$840/公斤 -> ~$1,110–$1,350/公斤 7N级铟 ~$1,150/公斤 -> ~$1,800/公斤 -> $3,450+/公斤 1.6T工艺需要7N级铟。 因此价格已经开始上涨，但我预计巨大的瓶颈(chokepoint)将出现在2026年年中。 不确定价格最终去向，但我预计会出现为确保材料供应的竞价战，且$AXTI 相比住友(Sumitomo)等其他公司，可能对此有最直接的敞口(exposure)。
英文原文
Just to make a correction to the Indium price above 6N grade Indium (Jan 2024, Jan 2025, Dec 2025) ~$680 / kg -> ~$840 / kg -> ~$1,110 – $1,350 / kg 7N grade Indium ~$1,150 / kg -> ~$1,800 / kg -> $3,450+ / kg 1.6T requires 7N. So prices have already started to ramp up, but I expect the huge chokepoint to come mid 2026. Not sure where the price goes, I just expect a bidding war to secure materials and $AXTI probably had the most direct exposure to this over Sumitomo and others.
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分析InP材料供应瓶颈，通过历史案例说明关键材料博弈论，预判超大规模云商将抢购InP衬底产能。
当我发WSB帖子时，我半开玩笑地提到$AXTI。但对于极端瓶颈和InP供应冲击，我可不是开玩笑的。这是一个关于关键材料博弈论的呼唤。 如果我们回顾历史上许多瓶颈案例： 1. 镝(Dysprosium)：约2300%涨幅（约$100/kg -> $2400/kg，2010-11年） 2. 氖气(Neon Gas)：约1000%-2000%涨幅（2022年） 3. 铑(Rhodium)：约$3,000/盎司 -> 约$29,000/盎司（约860%） 当前铟(In)的价格涨幅与其他材料相比如何？ 89%：（约$440/kg -> 约$832/kg）。 用于半导体的关键材料（如用于光刻激光器的氖气），因为芯片制造商如英特尔和三星在乌克兰冲突期间进行了储备，价格暴涨超过2000%。他们吸收了成本，因为氖气只占芯片价值的一小部分。 与氖气一样，磷化铟(InP)是一种关键的"赋能"材料。晶圆成本相对于AI集群成本（$100的晶圆对比$30,000的GPU）来说很小。超大规模云商宁愿吸收巨大的价格上涨，也不愿延迟部署。InP目前还没有出现这种情况，但我们很可能会看到。 传统分析师和许多AI模型不知道如何建模关键瓶颈，因为历史上很少有这样的案例：一种极其廉价的商品（如InP，TAM只有几亿美元）突然成为价值数万亿美元的AI建设中最关键的材料。 目前，超大规模云商可能已经向下游供应商Coherent/$LITE下了订单，但可能没有意识到激光器生产和产能受到上游材料短缺的制约而排满。 InP衬底（$AXTI + Sumitomo + JX生产）和磷化铟原料（$AXTI、Vital、$DOWA）都存在供应储备，需求超过供应数倍。 $NVDA最初通过锁定EML大量产能加剧了供应短缺。但短缺早在超大规模云商扩产之前就已经存在，大部分需求将在2026年底至2027年Trainium或Maia出现时涌入。 但如何绕过原始瓶颈并确保AI部署？ 直接从（$AXTI、Sumitomo）购买衬底产能，或者更进一层，购买InP原料并将其交给衬底生产商，以确保谷歌的TPU项目不会停滞。 与其他关键材料（如氖气用于光刻激光器）类似，磷化铟和InP衬底对整个AI建设更为关键： 1. Nvidia：InfiniBand / NVLink（光学 - 800G/1.6T EML光模块）- 对InP高度依赖 2. Google：Jupiter / Apollo（光学 - OCS），高度依赖 3. Microsoft：Azure Maia：高（800G DR4/FR4） 4. Meta：F16 / Artemis（800G）高 这还不包括其他Mag7公司如$AMZN或使用光子技术扩展ASIC的其他公司。 目前，分析师基于TAM对InP公司进行建模。例如，2024年InP晶圆市场总规模为$183M-$205M（Straits Research, Mordor Intelligence，2024年） - 6英寸（150mm）细分市场TAM：$65M - 预计2032年InP总TAM：$580M-$700M 现在看激光级磷化铟原料的TAM： - 多晶InP原料TAM：约$3亿 - 高纯度铟（6N/7N）仅：约$4亿 衬底数据：Mordor Intelligence（InP晶圆市场2025-2030）和Straits Research。 原料数据：Market Report Analytics（磷化铟多晶行业分析2025）。 这是一种极其便宜的电信产品，现在成为整个供应链中最珍贵的材料之一。 价格上涨3000%只会占$GOOGL TPU部署或$MSFT MAIA部署BOM值的低个位数。而仅微软2027年的扩产就会占用全部InP产能的两位数百分比。 就像2022年的英特尔或半导体行业一样，超大规模云商可能会像当时囤积氖气一样，直接购买InP衬底+InP作为"保险"。 如果"TAM"实际上只有几亿美元，但每个超大规模云商如果不确保这种材料就会面临部署延迟，那么这就变成了一场博弈论竞标战。 在一个因$100衬底而停滞的价值$200亿的TPU部署中，超大规模云商会毫不犹豫地支付$10,000（比当前价格高出100倍）。 这就是为什么当你看到InP衬底公司有$5000万订单积压（来自2024年），同样的$5000万产能对未来来说在极端情况下可能价值$5亿、$50亿甚至更多。 这是一个"尾部风险"投资，如果超大规模云商被这种材料卡住，回报是极高的，但并非没有重大的地缘政治风险和稀释。 我不知道会发生什么，但我预计2026年InP衬底和InP原料都会出现巨大瓶颈。 那么，如果像$AXTI这样的公司拥有整个InP供应链40%的份额（来源：AXT CEO），而估值只有$7亿，你会给它什么估值？
英文原文
When I made my WSB post, I'm half joking about $AXTI. But not about the extreme bottleneck and InP supply shock. This is a call on critical materials game theory. If we see many historically at bottlenecks: 1. Dysprosium: ~2,300% increase (~$100/kg -> $2400/kg 2010-11) 2. Neon Gas: ~1000%-2,000% increase (2022) 3. Rhodium: ~$3,000/oz -> ~$29,000/oz (~860%) The current Indium spike compared to others? 89% : (~$440 / kg -> ~$832 / kg). Critical materials used for semiconductors like Neon Gas (semi-grade lithography lasers), spiked over 2000% because chipmakers like Intel and Samsung had stockpiled during Ukraine conflicts. They absorbed the cost because neon is a small fraction of the chip's value. Like Neon, InP is a critical "enabler" material. The cost of the wafer is small relative to the cost of the AI cluster ($100 wafer vs $30,000 GPU). Hyperscalers would happily absorb huge price increases rather than delay deployment. We haven't seen that yet with InP, but we likely will. Traditional analysts and many AI Models do not understand how to model critical bottlenecks because there's not many examples in history where an extremely cheap commodity like InP with few hundred million TAM suddenly became the most critical material for the multi-trillion+ AI buildout. Currently, hyperscalers likely placed backlogs on downstream providers Coherent / $LITE, but likely didn't realize that laser production and capacity are backlogged because of materials shortage upstream. There is a supply storage both for InP substrates ( $AXTI + Sumitomo + JX production) as well as the Indium Phosphide feedstock ( $AXTI, Vital, $DOWA) where demand exceeds supply by multiple factors. $NVDA originally contributed to the supply shortage by locking in a large percent of capacity of EML. But shortage is already pre-hyperscaler ramp, where majority of the demand will come in late 2026 into 2027 when Trainium or Maia show up. But how do you get around original chokepoint and securing your AI deployment? Buying out substrate capacity directly from ( $AXTI, Sumitomo) or going one step lower and buying InP feedstock and passing them to substrate producers so Google's TPU program doesn't stall. And similar to how other critical materials were needed for lithography lasers. Indium Phopshide and InP substates are even more critical to the entire AI buildout: 1. Nvidia: InfiniBand / NVLink (optical - 800G/1.6T EML Transceivers) - Extreme dependency on InP 2. Google: Jupiter / Apollo (optical - OCS), Extreme dependency 3. Microsoft: Azure Maia: High (800G DR4/FR4) 4. Meta: F16 / Artemis (800G) High and this is not considering other Mag7 companies like $AMZN or other companies scaling out ASICs with photonics. Currently, analysts are modeling InP companies based on TAM. For example, the total InP Wafer Market from 2024 is $183M – $205M Straits Research, Mordor Intelligence (2024) - 6-inch (150mm) Segment TAM: $65m - Projected Total InP TAM (2032): $580M – $700M Now looking at TAM for Laser-Grade Indium Phosphide Feedstock: - Polycrystalline InP Feedstock TAM: ~$300 Million - High-Purity Indium (6N/7N) Only: ~$400 Million Substrate Data: Mordor Intelligence (InP Wafer Market 2025-2030) and Straits Research. Feedstock Data: Market Report Analytics (Indium Phosphide Polycrystalline Industry Analysis 2025). This was an extremely cheap telecom product and now it's one of the most precious materials in the entire supply chain. Increasing prices 3000% would only be low single digits of BOM value to $GOOGL TPU deployments or $MSFT MAIA deployments. And the project Microsoft ramp in 2027 alone would take up double digits of all InP capacity. Like Intel or semis back in 2022, hyperscalers will likely buy insurance directly with InP substrates + InP, similar to how semis stockpiled Neon Gas. If the "TAM" really was a few hundred million, but every single hyperscaler would face deployment delays if they don't secure this material. Then this becomes a game theory bidding war. In a $20B TPU deployment is stalled because of a $100 substrate, a hyperscaler would easily pay $10,000 (100 times current prices) for it without hesitation. That's why when you look at InP substrate companies and see $50m backlog (from 2024), that same $50m worth of capacity for future ones could be valued at $500m, $5B or more in an extreme scenario. This is a "tail-risk" investment, extremely reward if hyperscalers get bottlenecked by this material, but not without significant geopolitical risk and dilution. I don't know what's going to happen, but I do expect there to be an immense bottleneck in 2026 both in InP substrates and InP feedstock. So, if companies like $AXTI owns 40% of the entire InP supply chain (source: AXT CEO) and is valued at $700m, what value would you place on it?
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探讨InP原料与衬底瓶颈差异，指出原料冲击利好AXT而非Sumitomo。
@zephyr_z9 我很好奇。鉴于磷化铟(InP)衬底控制和磷化铟(InP)材料是两个不同的瓶颈，你会更看重哪一个？ 如果上游的磷化铟(InP)原料供应出现冲击，主要的受益者将是像AXT/DOWA这类公司，而不是无法捕获上行收益的住友电工(Sumitomo)。
英文原文
@zephyr_z9 I’m curious. Would you place more value on InP substrate control or indium phosphide since they’re two different bottlenecks? If InP feedstock has a supply shock upstream, the main beneficiaries would be your AXT/DOWA type companies instead of Sumitomo that don’t capture upside
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InP涨价对集群成本影响微，长期担忧超大规模云服务商转向定制ASIC。
好问题！关于 $CRWV、$NBIS 和 $IREN，我尚未对 B300 集群进行物料清单(BOM)分析，但光网络(Optical Networking)资本支出占比可能在 10-20% 左右。 我记得做过测算，即使磷化铟(InP)价格上涨 30 倍，集群价格仅边际增加 3%，这对 Google 来说微不足道，仅对内部收益率(IRR)造成极微小的影响。 话虽如此，我不确定 InP 成本是仅边际增加，还是因总可寻址市场(TAM)极小且突然用于 AI 导致供应受限而上涨 50 倍。 总之，短中期影响甚微。长期我更担心超大规模云服务商(Hyperscaler)转向定制 ASIC 并将英伟达作为过渡期。 我们需要观察 Neoclouds 是否能在拥有极大杠杆的 2-3 年窗口期内，基本转变为超大规模云服务商。
英文原文
Good question! As for $CRWV, $NBIS, and $IREN, I haven’t done a BOM on B300 clusters, but optical networking is probably around 10-20% of capex. I remember doing calculations and increasing InP prices by 30 times would only create a 3% marginal increase on cluster prices, which is extremely negligible to Google but hurts IRR just a tiny tiny bit. That being said I don’t know if InP costs just marginally increases or it goes up 50 times because it’s incredibly low TAM and suddenly it’s used for AI/supply constrained. So basically little effect short-medium term. Longer term I’d be more worried about hyperscaler shift to custom ASICs and using nvidia as a transition period. We’d need to see if Neoclouds can basically become hyperscalers themselves in the 2-3 year window where they have extreme leverage
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AXTI掌控磷化铟关键瓶颈，制约AI光互联扩展。
$AXTI CEO：“我们占据了磷化铟(Indium Phosphide)供应链的40%份额。” 是否曾有一家如此小规模（市值7亿美元）的公司，掌控着一个数万亿美元产业的关键瓶颈？
英文原文
$AXTI CEO - “We are 40% of the Indium Phosphide supply chain” Has there ever been a company this small ($700M) that controlled a critical bottleneck for a multi-trillion dollar industry? https://t.co/tn7EOMPgas
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磷化铟供应链集中度高，是光子器件未来关键瓶颈。
@brandy117 声称控制了全球 40% 的磷化铟(Indium Phosphide)供应链，这令人震惊。特别是当光子器件依赖该材料时，它将成为未来巨大的瓶颈。 https://t.co/3u29jRnTT8
英文原文
@brandy117 The claims were mindblowing controlling 40% of the world's Indium Phosphide supply chain. Especially when photonic components depend on the material, it's a huge future chokepoint. https://t.co/3u29jRnTT8
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分析InP供应链瓶颈，指出AXT受益于垂直整合，需求总体仍超供应。
我理解你的观点是基于仅看中国国内市场，而未考虑西方AI的扩张。两点如下： 一是整体需求的极端增长。即使有6英寸磷化铟(InP)晶圆，超大规模云服务商(Hyperscaler)的需求仍将超过供应。因此，无论是否存在竞争性替代品，需求不会消失，但可能会分散到中国国内市场的竞争者中。 二是垂直整合。你提到了西方阵营的$DOWA，特别是磷化铟(InP)领域。$AXTI控制了全球绝大部分的InP供应。如果超大规模云服务商为保险起见直接高价采购，再转交给$COHR，那么这对住友电工(Sumitomo)来说问题更大。而AXT则从这两层瓶颈中受益。新耀/JFS进入供应链只是增加了参与者，并非末日景象。例如存储领域（SK海力士；MU，三星）。 当然，如果中国实施出口管制，我们仅看中国国内市场，上述观点可能失效。但总体而言，即使增加更多参与者，需求仍超过供应（例如COHR已满产）。
英文原文
I can see that if you look at China domestic markets only but not western AI ramp. So two things: One is extreme ramp in general. Hyperscaler demand will always outstrip supply even with 6-inch InP wafers. So competitive alternative or not, demand doesn’t disappear but might get spread out through competitive alternatives in China’s domestic market. The other is vertical integration. You mentioned $DOWA on the western side and especially InP. $AXTI controls a huge percent of the world’s InP supply and if those prices gets jacked up from hyperscaler buying direct for insurance-> handing them to $COHR, then it’s more of an issue for Sumitomo. And AXT benefits from both layers of the bottlenecks. Xinyao/JFS entering the supply chain just makes adds one more player to the equation so it’s not doom and gloom. Eg memory (sk Hynix; MU, Samsung) Of course these points might get thrown out the drain if China export controls and we’re looking at China domestic market only. But generally demand outstrips supply (eg. COHR is at max) even if we add in more players.
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梳理AI光子学及InP衬底供应链核心标的，涵盖从底层材料到芯片的全链条。
呃，根据我个人的研究，为了全面覆盖我看好的一切： 1. $AXTI 位于整个供应链的最底端，占据 1/3 的磷化铟(InP)衬底和 1/4 的磷化铟(InP)份额。AI 供应链竟然与这只市值 7 亿美元的股票紧密相连，这完全出乎意料。 2. $DOWA + 住友电气，用于在衬底和材料方面进行西方对冲。 3. $AAOI, $LITE 针对超大规模云服务商的芯片，一家服务于 $AMZN/$MSFT，另一家服务于其他客户但更侧重于 $TPU。 4. $MRVL + $AVGO 我认为这就足以捕捉光子学物料清单(BOM)的价值以及磷化铟(InP)供应冲击。 还有一些其他有趣的标的，比如 Landmark Opto，我正在关注。 $POET 没进这个名单，反正你可以通过 $MRVL 获得敞口，除非我漏掉了什么。
英文原文
Uhh, from my own personal research so far, to cover all grounds I’ve liked: 1. $AXTI at the very bottom of the entire supply chain + 1/3rd of InP substrates 1/4th of InP. Completely unheard of that AI supply chain is tethered to this $700m stock. 2. $DOWA + Sumitomo Electric for Western Hedge on substrate + materials. 3. $AAOI, $LITE for hyperscaler chips, one for $AMZN/ $MSFT, the other for everything but more levered to $TPU 4. $MRVL + $AVGO I think that’s kind of all you need to capture photonics BOM value + InP supply shock. There’s some other interesting ones like Landmark Opto that I’m looking at now. $POET didn’t quite make that list and you’d be getting exposure through $MRVL anyway, unless there’s something I missed
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对比住友与AXTI在磷化铟供应链中的地位及风险。
住友电气(Sumitomo)受磷化铟(InP)价格上涨影响，但如果$GOOGL直接向$DOWA或其他供应商采购原料，其影响将减弱。 $AXTI拥有完整的供应链，并占据激光级磷化铟的巨大份额。但明显的下行风险是中国出口管制。 不过住友电气体量巨大，因此你获得的并非最直接的敞口。
英文原文
Sumitomo is subject to hikes in InP prices though if $GOOGL goes direct to $DOWA or others for feedstock. $AXTI owns the whole supply chain, and a huge portion of laser grade inp. But downside is obviously anuke from China exports. Sumitomo Electric is huge though so you’re not exactly getting the most direct exposure.
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分析AXTI/中国磷化铟瓶颈对AI供应链的致命影响及关键材料估值逻辑。
这是一份关于 $AXTI/中国 在衬底生产和激光级磷化铟方面导致整个 AI 基础设施建设出现单点故障的研究笔记。我并未对个别公司进行估值分析。但如果这一流程中断，$LITE、$COHR、$AVGO 乃至 $GOOGL、$MSFT 都将面临极端的延迟。如果你们感兴趣，我会另写一篇文章关于如何对关键材料瓶颈进行估值。基本上，如果 2024 年的积压订单为 5000 万美元，而总可寻址市场 (TAM) 为 1.5 亿美元。而现在，由于它是关键材料，如果谷歌愿意为此支付 50 倍的溢价（仅为保持生存而增加 BOM 成本的百分之几），那么原本 5000 万美元积压订单的估值逻辑就会转变为未来产能的 25 亿美元。
英文原文
This is a research note on point failure of the entire AI buildout in $AXTI/China from both substrate production and laser-grade Indium Phosphide. I’m not doing valuation analysis on individual companies But if this flow stops, $LITE, $COHR, $AVGO to $GOOGL, $MSFT faces extreme delays. I’ll write something else about valuing critical material bottlenecks if you want. But basically if a backlog was $50m from 2024 and TAM was $150m. And now because it’s a critical material, if Google would be willing to pay 50 times that (only a few percent increase on BOM cost to stay alive), then the valuation math of that original $50m backlog -> $2.5B for future capacity changes.
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Coherent虽为西方希望，但受制于磷化铟原料垄断，面临供应链瓶颈风险。
我认为超大规模云计算厂商尚未意识到其中的危险。$COHR 是领先的“近乎垂直整合”的美国公司。但风险在于，它仍受制于磷化铟(InP)原料的瓶颈，并从现货市场购买6N级磷化铟多晶（原料）。 如果上述公司停止销售6N多晶，Coherent 的激光和收发器业务将随着超大规模云计算厂商的建设而有效受阻。 Coherent 并不拥有像 Vital Materials 或 $AXTI 那样规模的主要铟矿或大规模6N合成工厂。 简单来说：Coherent 是打破住友与 $AXTI 之间衬底双寡头垄断的“西方希望”，但他们目前却是磷化铟原料垄断的人质。
英文原文
Don’t think hyperscalers understand the danger yet. $COHR is the leading “virtually integrated” American company. But the risk is it’s still stuck in the bottleneck for InP feedstock and buys 6N InP polycrystal (feedstock) from the merchant market. If the companies above stop selling 6N polycrystal, Coherent’s laser and transceiver business effectively hits a wall alongside the hyperscaler buildout. Coherent does not own major Indium mines or high-volume 6N synthesis plants on the scale of Vital Materials or $AXTI. To put it more simply: Coherent is the "Western Hope" for breaking the substrate duopoly between Sumitomo and $AXTI, but they are currently a hostage to the InP feedstok monopoly.
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AI光互连依赖磷化铟，其原料78%在中国，AXTI成关键瓶颈。
“瓶颈中的瓶颈”：磷化铟(InP) $AXTI 和 $SMTOY 构成双寡头。它们控制了全球 60% 以上的磷化铟(InP)衬底，是 AI 建设的关键瓶颈。 更令人警觉的是：这依赖于磷化铟(InP)。 磷化铟(InP)是垄断市场。78% 由 $AXTI 和中国控制。 这就是“瓶颈中的瓶颈”： 磷化铟(InP)衬底市场已是日本和中国实体之间的双寡头。然而，上游激光级原料（如住友所需）的生产主要由 $AXTI（再次出现）和中国公司主导。 主要问题在于： AI 行业极度依赖光子学来实现规模化。无论收发器是“基于磷化铟”还是“基于硅”，光源始终是：磷化铟(InP)。 随着 AI 集群从 1 万颗 GPU 扩展到 10 万颗以上，“铜缆瓶颈”迫使全面转向光互连。这使得磷化铟(InP)对 AI 规模化的重要性超过几乎任何其他单一材料。 此外，激光级原料纯度必须至少达到 6N（99.9999%）。即使是微量杂质（硅、硫、锌）也不像 LED 等其他领域那样可接受。大多数研究可能混淆了激光级原料与普通磷化铟产出。 住友是磷化铟衬底市场最著名的名字。他们在高端激光衬底领域占据巨大市场份额。但贸易数据显示，他们越来越依赖来自 $DOWA 和中国公司的外部磷化铟原料。（由于自有回收和储备，他们可能仍被计入原料所有权列表中） 所以，如果认为整个西方 AI 建设因有一家日本公司作为双寡头之一而感到安全，请三思。 瓶颈的源头被 $AXTI 和中国供应商所瓶颈。 如果我们看生产，以下是深度研究估算的控制权分布： Vital Materials - 35%（现货市场） - Vital 在 2020 年收购凡亚金属交易所库存（3600 吨铟），使其掌控全球铟市场。他们利用这一优势成为最大的磷化铟多晶生产商。主导成本领先者；控制原生铟供应（凡亚库存）。 $AXTI - 25%（北京同美晶体技术） - 主要自给自足。其大部分多晶生产被自家晶体生长炉消耗以制造晶圆。但他们也向现货市场销售原材料和化合物，是混合型玩家。 他们是全球唯一从矿山、精炼厂到磷化铟衬底产出的公司，鉴于他们同时拥有原材料和磷化铟衬底控制权，这是一个绝对疯狂的瓶颈。供应自家晶圆生产；关键的非日本来源。 株洲科能新材料 - 18% - 科能实现了“磷化铟多晶量产”并拥有“高度集成的自动多晶生产能力”。他们是中国铟出口配额的关键接收方。纯合成专家；主要出口商。 然后外部： $DOWA - 12% - 西方公司中最大的供应商（是的，日本）。在采矿（秋田锌）方面根基深厚，因此是高纯度金属有机化合物和化合物的领先供应商。 “日本企业”（住友、JX）的“来源” Wafer Technology Ltd - 5% - IQE plc 的子公司。对于需要非中国原料的北约联盟供应链来说，这是关键战略资产，尽管他们目前正在进行资产清算。 InPACT（法国）- 3% - InPACT 称他们通过高压合成的水平梯度凝固(HGF)生产多晶锭，以满足（诺基亚、爱立信）和一些欧洲国防部门的要求。 世界其他地区 - 2% 这包括主要衬底制造商（Coherent、住友）、小规模研究生产以及试图打破垄断的韩国或台湾新兴玩家。 现实是，全球 78% 的激光级磷化铟原料产能位于中国。 光组件的需求已经以数倍超过供应/生产。这还是在上量之前。整个 AI 建设被两家公司瓶颈。 但 1/4 的材料来自：$AXTI。而约 1/3 的磷化铟衬底产出再次来自激光级原料。 整个 AI 建设依赖于一家随机的 7 亿美元公司，它既是瓶颈中的瓶颈，也是瓶颈本身。 扩大磷化铟衬底和激光级原料的生产既是国家安全问题。
英文原文
"Bottleneck within a Bottleneck": Indium Phosphide $AXTI | $SMTOY is a duopoly. They control 60%+ of the world's InP substrates as the bottleneck of the AI buildout. What's even more alarming? This is dependent on: Indium Phosphide. InP is a Monopoly. 78% control by $AXTI / China. Here's the bottleneck within a bottleneck: The InP substrates is already a duopoly between Japanese and Chinese entities. However, upstream production of laser-grade feedstock required by companies like Sumitomo is dominated by $AXTI (again) and Chinese companies. Here's the major issue: The AI industry is extremely reliant on photonics to scale. Whether, transceivers are "InP-based" or "Silicon-based" the photon source remains: Indium Phosphide. As AI clusters move from 10,000 to 100,000+ GPUs, the "copper bottleneck" is forcing a total shift to optical interconnects. This makes InP more critical to AI scaling than almost any other single material. On top of that, laser-grade feedstock must be at least 6N (99.9999%) pure. Even trace amounts of impurities (Silicon, Sulfur, Zinc), cannot be used like they do in other segments like LED. And most research probably confuses laser-grade feedstock with regular InP outputs. Sumitomo is arguably the most famous name in the InP substrate market. They hold a massive market share in the high-end laser substrate segment. Yet trade data suggest they are increasingly reliant on external feedstock for Indium Phosphide from companies like $DOWA and from China. (They're likely still included in feedstock ownership lists bc of captive recycling and reserves) So if the entire Western AI buildout feels safe regarding a Japanese company as a duopoly, think again. The source of the bottleneck is bottlenecked by Chinese suppliers like $AXTI and Chinese companies. If we look at production there's are estimates from deep research breakdown of estimate controls: Vital Materials - 35% (Merchant) - Vital acquired Fanya Metal Exchange inventory (3,600 tonnes of Indium) in 2020 gave them large control over the global Indium market. They have leveraged this to become the largest producer of InP polycrystal. Dominant cost leader; controls raw Indium supply (Fanya stocks). $AXTI - 25% (Beijing Tongmei Xtal Technology) - Primarily Captive. Most of their polycrystal production is consumed by their own crystal growth furnaces to make wafers. However, they also sell raw materials and compounds to the merchant market, making them a hybrid player. They're the only company in the world that goes from mines, refineries -> InP substrate output, which is an absolutely crazy bottleneck given they own both the raw materials into InP substrate controls. Feeds own wafer production; key non-Japan source. Zhuzhou Keneng New Material - 18% - Keneng has achieved "mass production of polycrystalline indium phosphide" and possesses "highly integrated automatic polycrystalline production capacity". They are a key recipient of China's export quotas for Indium. Pure-play synthesis specialist; major exporter. Then Outside: $DOWA - 12% - The biggest supplier out of any Western company (yeah Japanese). Deep roots in mining (Akita Zinc), so they're the leading supplier of high-purity metal organics and compounds. The "source" for Japan Inc. (Sumitomo, JX) Wafer Technology Ltd - 5% - A subsidiary of IQE plc. Critical strategic asset for NATO-aligned supply chains that require non-Chinese feedstock, even though they're going through asset liquidations right now. InPACT (France) - 3% - InPACT states they produce polycrystalline ingots via Horizontal Gradient Freeze (HGF) using high-pressure synthesis so they meet requirements from (Nokia, Ericsson) and some European defense sectors. Rest of World - 2% This includes major substrate makers (Coherent, Sumitomo), small-scale research production, and emerging players in Korea or Taiwan who are attempting to break the monopoly. The reality is that 78% of the global capacity for laser-grade InP feedstock is located in China. The demand for optical components already exceeds supply/production by multiple factors. This is pre-ramp too. The entire AI buildout is bottlenecked by two companies. But 1/4th of the materials comes from: $AXTI. And ~1/3rd of InP Substrate outputs again comes from laser-grade feedstock. The entire AI buildout is dependent on some random $700m company that serves as both the bottleneck of a bottleneck and the bottleneck. It's both national security issue to scale up InP production both for substrate and laser-grade feedstock.
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三星遭中方窃取存储芯片机密，恐被逐出中国市场，处罚力度引争议。
哇，中国知识产权间谍活动并非新鲜事，但这一事件对三星以及美国/韩国而言简直是灾难性的。窃取全球最先进存储芯片的秘密，然后交给中国国有背景的公司……随后很可能将三星/美光切断出中国国内市场。对于这10名被起诉者，即使只有丝毫牵连，终身监禁作为威慑都不足以构成惩罚。如果他们10年后出狱还能拿到5000万美元的薪水，那这就足以激励这些人继续盗窃。
英文原文
Wow, Chinese IP espionage is not new but this one just catastrophic for Samsung and US/Korea. Stealing secrets of the world's most advanced memory chips then handing them over China’s state backed company…. Then likely cut off Samsung/Micron from China’s domestic market. Maximum life in prison for deterrence isn’t even enough of a punishment for this, from the 10 indicted, even with an iota of involvement. If they get out of jail 10 years later with a $50M paycheck, then that’s incentive enough for these people to continue theft
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构建模型对比磷化铟激光级原料的垂直整合与公开市场供应。
@dr_lmfao_ 是的，绝对如此。我正在构建一个模型，以标准化磷化铟(Indium Phosphide)激光级原料的拥有权，对比像 $AXTI 这样的私有垂直整合玩家，与像 $DOWA 或 Vital Materials 这样在公开市场销售的其他公司。 这极其复杂 lol
英文原文
@dr_lmfao_ Yeah absolutely, I’m working on a model to normalize ownership of indium phosphide for just laser grade feedstock from private vertically integrated players like $AXTI vs others like $DOWA or Vital Materials that sell on open markets. It’s extremely complex lol
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AI供应链瓶颈类似当年锂和HBM，衬底及关键组件面临短缺与估值难题。
同意，对于交易者而言，这应该是一个有趣的机会，就像2021年电动车兴起时的锂，或者当前SK海力士和美光的高带宽内存(HBM)，如果人们能早期识别瓶颈的话。 机会众多（$AAOI尽管获得新的超大规模客户订单，年初至今仅上涨2.9%。这与Maia/Tranium等超大规模客户的部署挂钩）。 $MRVL需求极度旺盛，但主要来自Maia在2026年第四季度至2027年的需求，年初至今下跌22%。$POET作为$MRVL扩产的间接受益者。 磷化铟(InP)衬底在整个供应链中普遍短缺。$GOOGL加速TPU部署，利好$LITE，以及$COHR的垂直整合+创纪录积压订单。 像$AXTI这样极其荒谬的玩家，市值仅7亿美元，却几乎是未来AI扩产的单点故障(SPOF)。真不知道该如何给这个估值，哈哈。 $COHR、$LITE和衬底供应商现在正触及产能极限。我们将看到这需要多长时间才能达到像内存那样的极端程度。
英文原文
Agreed, for traders, this should be an interesting opportunity like Lithium in 2021 when EVs came about or HBM currently with Sk Hynix and Micron if people recognized the bottlenecks early. Tons of opportunity ($AAOI only up 2.9% YTD despite new hyperscaler orders. Tied to hyperscaler deployments like Maia/Tranium). $MRVL with extreme demand but mainly in q4 2026, into 2027 from Maia, down 22% YTD. And $POET as an indirect beneficiary of $MRVL ramp too. Shortages throughout the entire supply chain with InP substrates. $GOOGL ramping up TPU which benefits $LITE and vertical integration + record backlog from $COHR Extremely absurd players like $AXTI with a $700m marketcap basically being the single point of failure for the future AI ramp. Not quite sure how you place a value on that lol. $COHR, $LITE and substrate providers are hitting the capacity limits now. We’ll see how much time it takes for his to go to the extremes like memory.
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AXTI估值低反映其风险，AI供应链对其光子学衬底依赖加剧脆弱性。
$AXTI 确实存在很大风险。这就是为什么它的估值仅为 7 亿美元，像是一只仙股，而不是像 $SMTOY 那样超过 300 亿美元，尽管两者都是垂直整合企业且都是最重要的供应商之一。此外，AI 供应链极度依赖该公司提供的用于光子学的 inp 衬底（inp substrates）原材料以实现产能爬坡，这一事实进一步加剧了本已脆弱的 AI 基础设施建设所面临的风险。
英文原文
There is a lot risk with $AXTI for sure. That’s why it’s valued like a penny stock at $700m and not $30B+ like $SMTOY despite being both vertically integrated and one of the most important suppliers. And when you combine with the fact the AI supply chain is extremely reliant on this company for raw materials -> inp substrates they provide for photonics in order to ramp, that’s even a greater risk to the already fragile AI buildout.
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澄清Grok误解，指出AVGO依赖AXTI等InP衬底，AXTI具备全产业链优势。
Grok 可能混淆了晶圆制造(wafer fab)与磷化铟(InP)衬底制造。$AVGO 的 Penn 工厂仍需从住友、$AXTI 或 JX 采购 InP 衬底来制造激光器（这就是瓶颈所在），且它们很可能是客户。 而那家市值仅 7 亿美元的化合物半导体公司 $AXTI 可能是其中唯一一家实现端到端控制的企业，从镓、铟等初始原材料精炼开始就拥有上游资源。 因此，“主要不进口 InP 晶圆/衬底”这一说法可能是错误的。
英文原文
Grok is likely conflating wafer fab with InP substrate manufacturing. $AVGO's penn fab still requires InP substrates from Sumitomo, $AXTI, or JX to build the lasers (hence the bottleneck) and they're likely customers. And that small $700M MC company $AXTI is probably the only one of the bunch that does this end-to-end by owning Gallium, Indium, etc. on from the initial raw material refining. So the "does not primarily import InP wafers/substrates” part is probably wrong.
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光子供应链瓶颈或现类似HBM的投资机会
是的，$LITE 和 $COHR 表现惊人，自拥有强大定价权以来涨幅显著。 若深入挖掘 $AXTI（垂直整合）、住友 -> 同和等更深层环节，集中度风险与瓶颈会发出警示信号。 在 HBM（高带宽内存）领域，当人们发现瓶颈时便出现了投资机会。如今在光子供应链中，随着超大规模云厂商囤积材料并收购产能，很可能存在同样的被忽视的机会。
英文原文
Yep, $LITE and $COHR are amazing and are up quite a bit since they tons pricing power. Go few levels deeper into $AXTI (vertically integrated), Sumitomo -> Dowa, etc. the concentration risk + bottleneck flashes warning signs. With HBM, it was an investment opportunity when people found that bottleneck. There's likely that same overlooked opportunity with photonic supply chains now when hyperscalers hoard materials and acquire capacity.