jocrgb

Data is the new oil.

[Rosanna Prestia, MBA @RosannaInvests]

🚨Everyone is still buying the chips. The bottleneck already moved.

A GPU that computes in nanoseconds and waits microseconds for data is a stranded asset. At 1.6T speeds, copper runs out of physics. The constraint on AI is no longer how fast you can think. It's how fast you can move what you thought.

Jensen has now said it twice in three months.

At GTC in March: "Is copper going to still be important? The answer is yes... Are you going to scale up optical? Yes. Are you going to scale out optical? Yes... We need a lot more capacity for copper. We need a lot more capacity for optics. We need a lot more capacity for CPO."

Last week at Computex, on Marvell's stage: "Optics where you must, copper where you can." Then he called Marvell the next trillion-dollar company and the optical complex repriced within days. The same keynote put a date on the handoff: 200G per lane is the last generation where copper is sufficient. After that, optics takes the rack.

Translation: not copper OR light. Copper now, light next, unprecedented amounts of both. 🔥

The chain is unavoidable: AI tokens are profitable → more GPUs → more bandwidth → copper hits its wall → photonics becomes the chokepoint.

And the smart money stopped debating. Follow the closed deals:

→ $NVDA has committed at least $6.5B to photonics in three months: $2B into Lumentum, $2B into Coherent, a $500M stake in Corning, and a piece of Ayar Labs' $500M round. Direct investments to secure its own light supply.
→ $MRVL paid $3.25B for Celestial AI, up to $5.5B with milestones, to build what its CEO calls a silicon photonics powerhouse.
→ $CRDO closed DustPhotonics two weeks ago. Ciena bought CPO startup Nubis for $270M.

North of $10B of strategic capital locked up one supply chain in under a year. Capital like that doesn't chase a theme. It secures a bottleneck.

LAYER 1: WAFER. Every laser starts as a crystal.
🟠 $AXTI: the InP substrate leader. The first chokepoint in the stack.
🟡 $IQE: compound-semi epiwafers feeding the laser makers. Speculative, but structurally upstream.

LAYER 2: LIGHT. Photons don't make themselves.
🟠 $LITE: revenue +90% YoY last quarter to $808M. EML shipments doubled and management says demand still exceeds supply across EMLs, pump lasers, and transceivers. NVIDIA just wired them $2B. OCS backlog past $400M plus a multi-hundred-million CPO order for 2027.
🟢 $SIVEF (Stockholm: SIVE): the external light source. CPO does not emit its own light. Every optical engine needs a continuous-wave InP laser feeding it, and that is the layer you cannot engineer around. ELS modules with POET hit production readiness end of this year. Disclosure: long.
🟣 $POET: the optical engine wildcard. Its Optical Interposer pairs with Sivers' lasers on external light sources for CPO, with a LITEON module deal stacked on top. Binary commercialization, real architecture.

LAYER 3: OPTICS AND MODULES. Where light meets the rack.
🟠 $COHR: the volume anchor in transceivers, holding NVIDIA's other $2B check.
🔵 $AAOI: Q1 revenue +51% to a record $151M, datacenter revenue more than doubled, $124M of 800G orders plus a $200M+ 1.6T order in hand. Scaling Texas capacity toward 500K+ units a month by year-end, targeting $1B+ revenue this year. Domestic supply while everyone fights over offshore. Disclosure: long.
🟠 $FN: the foundry of optics. When Fabrinet is building, the orders already exist.

THE INTERCONNECT: the layer the rack cannot route around.
🔵 $CRDO: just closed DustPhotonics. SerDes → DSP → silicon photonics → system integration, one company, 800G through 3.2T. Electrical AND optical, end to end. FY26 revenue tripled to $1.34B at 68% gross margin. The toll booth on both roads. Disclosure: long.
🟠 $MRVL: $3.25B for Celestial AI, and Jensen's trillion-dollar nod on the Computex stage.
🟠 $AVGO: switch silicon, optical DSPs, CPO engines. They define the socket.
🟠 $ANET: the AI spine. 100K-GPU clusters get stitched together in light.

LAYER 4: PACKAGING, FIBER, FOUNDRY. Where photons get industrialized.
🔵 $TSEM: the neutral silicon photonics foundry. Prints wafers for whoever wins.
🟣 $LPKF: glass-substrate packaging for glass-based CPO. Real technology, binary commercialization.
🟠 $GLW: AI racks demand several times the fiber density of legacy cloud, and NVIDIA just took a $500M stake. Corning sells density.

LAYER 5: TEST AND THE ANALOG UNDERLAYER. Complexity is a tax paid in validation.
🔵 $AEHR: silicon photonics test, ramping with the cycle. '
🔵 $VIAV: every 800G and 1.6T transceiver gets validated before it ships. The gate the market prices like an accessory.
🔵 $SMTC: the drivers and TIAs that fire the lasers. Sits directly under the LPO trade.
🔵 $MTSI: the high-speed analog behind 1.6T engines.
🟠 $CIEN: transport. Even long-haul is buying light.

💡The counter-thesis, because every map needs one. The honest debate on this stack is whether these are genuine bottleneck assets or cyclical optics suppliers enjoying peak demand at peak multiples. Lumentum's May print showed +90% growth with the stock up roughly 1,400% over the prior year at a triple-digit trailing multiple. That is a price for perfection. Most of these names live or die on a handful of hyperscaler capex lines, and one digestion quarter hits the whole stack at once. CPO timing has already slipped once. Architecture risk is real: LPO, CPO, and stretched copper are still fighting for the same sockets. The cycle is real. So is the gravity. 🔥

But the bears have to explain one thing: $NVDA, $MRVL, $CRDO, and $CIEN just spent over $10B securing this supply chain with their own balance sheets. The people with the best information are paying up for the layers.

The market owns the top of this stack. The asymmetry is at the edges: wafer, light, packaging, test.

Own the layers, not the logo.

Bookmark this for the weekend. Then tag the one investor you know who's still all compute and no interconnect. 👀

[Ren @ren_stocks]

I was looking back to where I first found the most relevant information before I went in heavy on photonics at the beginning of the year. I keep coming back to this post from Gaetano back in December of 2025.

Gaetano has been one of my top 5 sources of clear and objective information here on X.

I bought $LITE around 350 and $AAOI around 40 because I like to talk to the people who are most knowledgeable on the subject, the ones who are not only early but are right now in the money.

Gaetano has been that for me, grade A content on the photonics sector, and he is now researching heavily on Physical AI.

If you want to know more about the future themes that are going to be big 6 months from now, drop @crux_capital_ a follow. Stand-up guy, great researcher and investor.

[K三 凯 @kaikaibtc]

最可怕的不是他5个月32倍，是他把投研这件事外包给了AI

最近X上有个很火的美股交易员👉，「前 RISC-V Foundation 成员，AI 研究科学家；现在的工作是——交易那些没人注意到的瓶颈。」

看起来就是一个喜欢在网上吹牛的散户，对吧？直到我看到了他2026年5月晒出的那张收益截图。

2026年至今（5个半月）：+3,152.77%。
不是32%。是32倍。

而且这已经是「回撤之后」的数字。他在2025年7月才注册这个账号，到2025年底的半年里已经做到了630%的回报。

他买了23只股票。没有一只涨幅低于100%。涨得最多的那一只，翻了84倍。

如果你2026年1月1日给他1万美金，到5月20日，你可以拿回32.5万美金。10万进去，325万出来。

涨得最少的一只，翻了一倍。涨得最多的那一只，翻了84倍。

所以我把他这几个月的推特全部扒了一遍，发现这个人不是传统意义上的「基本面研究」。

他做的事情，我称之为——
「AI驱动的全球供应链瓶颈套利」。

👉23只股票，23次提前预知市场

这23只股票有一个共同特点：它们都不是什么明星股，全是你可能从没听过名字的公司。

但恰恰是这些没人注意的公司，每一只都精准地卡在AI产业链的「咽喉」位置——一旦断货，整个行业都得停下来等。

他看的是更底层的问题：如果AI继续扩张，哪一环会先不够用？

AI产业链的第一层瓶颈，比如GPU、HBM、电力、数据中心，已经被所有人盯烂了。真正能出超额收益的，往往是第二层、第三层：光模块、激光器、InP衬底、SOI晶圆、外延设备、晶圆级测试、IC载板、特殊玻纤。

最典型的是 AXTI。Serenity 在 Reddit / WSB 上发过一篇很夸张的帖子，把 AXTI 写成整个西方AI建设的“单点故障”：不是因为它名字响，而是因为 InP 衬底和上游材料卡在光通信、硅光、CPO这条线上。

👉他到底怎么实现的：普通人用AI看研报，他用AI制造研究差

很多人一听“AI投资”，脑子里想的是：问ChatGPT买什么股票，问DeepSeek这家公司好不好，问Perplexity总结一下财报。

这基本没用。因为同一个问题，所有人都能问，所有人都能得到差不多的答案。Serenity 的用法更像是把AI当成一整个投研助理团。

1. 先让AI拆产业链，而不是让AI推荐股票
如果全球AI数据中心继续扩张，从GPU、HBM、网络、光模块、衬底、外延、测试、封装、PCB、玻纤到电力，分别会卡在哪里？这个问题一变，答案就完全不一样，你会得到一张产业链地图
。

2. 再让AI沿着每个环节找供应商
比如你拆到光通信，就继续问：光模块里最难扩的是哪一段？激光器供应商有哪些？InP衬底谁供？外延片谁做？这些公司是上市公司吗？市值多大？过去有没有进入核心客户供应链？

3. 然后让AI做交叉验证，而不是只听一个故事
这个瓶颈会不会被替代？这家公司有没有产能？客户有没有验证？收入什么时候可能体现？有没有被稀释风险？有没有地缘风险？有没有管理层问题？估值是不是已经透支三年？

真正值得学的是问题 。

Serenity 这件事给普通人最残酷的提醒是：AI没有让投资变简单，AI只是把“研究量”的上限抬高了。

他的核心方法论可以压成五句话：
先确认超级趋势，不在小风口里找幻觉。
把趋势拆成物理供应链，不停留在概念层。
找第二层、第三层瓶颈，不追已经被充分定价的龙头。
用AI扩大检索、整理和反证能力，不让AI直接替你拍脑袋。
最后用人的产业理解和风险纪律决定仓位，而不是让模型替你冲。

Serenity在字典上是「宁静、安详」。

真正的宁静，不是不关心外界。而是当整个市场都在为「英伟达又涨了」而喧嚣、为「某某概念又火了」而狂热的时候——你却安静地坐在那里，看着一张全球供应链的地图，思考一个问题：

「如果AI继续扩张——下一个会被卡住的环节，在哪里？」

这个问题，才是他5个月32倍的真正秘密。

[Jesse Zhang @thejessezhang]

Found this photo from the internship :)

Very rewarding to see how people from childhood + college journey through life. Some of us have known each other since 6th grade.

@ScottWu46 @chameleon_jeff @alexandr_wang

[来碗牛肉粉 @beefnoode]

昨天和 @0xchubai 老师聊完，我更加确认
Web3的大佬非常适合切到 AI领域
关键要做好以下几点：

1⃣先快速了解AI相关的基础概念和原理
不用一上来钻太深，先建立整体框架

2⃣养成AI First的思维
遇到问题先找AI，学会用AI学习AI
用AI真正解决自己的实际需求

3⃣边学习边分享
把自己踩过的坑、学到的东西分享到X，learn in public
让学习的过程持续拥有正反馈
这是最好的学习闭环，同时也能不断积累你的个人IP

4⃣尝试build自己的小产品
能vibe coding之后，做产品的门槛也越来越低
找到一个web3领域的小需求、痛点，build一个产品
快速执行、快速验证

从Web3切AI、拿到结果的几个宝藏博主，推荐给各位：

@CryptoPainter 画师哥，openclaw玩的厉害，然后也自己vibe coding一套很牛逼的量化策略

@Saccc_c Sac哥，Github领域永远的神，开发的Github skill已经杀死这个赛道了

@runes_leo Leo哥，预测市场策略和AI 工具实战双线并进，两边的内容都很有深度

@starzq Day1Golbal的主理人，他们做的深度的美股投研skill我一直有在用，同时也自己build了一个美股、加密市场看板的开源项目

[小耳👂Jane｜Xiaoer @xiaoerzhan]

越用🦞，越觉得Claude code 值得学习，打通了飞书，Discord之后，基本也替代了🦞

推特上Claude code 研究较多的博主，跟上不迷路：

1、官方账号

Claude Code Community @claude_code — Anthropic 官方社区账号 · 精选社区最优质案例、开源工具和生态动态，是追踪 Claude Code 第一手信息的最快渠道

Anthropic @AnthropicAI — Claude 母公司官方账号 · 发布所有模型更新、Claude Code 新版本及官方文档，必须关注的权威来源

2、创始人 & 核心团队

Boris Cherny @bcherny — Claude Code 亲爸爸、Anthropic 负责人 · 持续分享团队真实工作流，包括并行 worktree、Plan 模式、CLAUDE.md 等进阶技巧，是最值得精读的原始来源

Thariq @trq212 — Anthropic Claude Code 核心工程师 · 深度撰文分享构建 Claude Code 的底层经验，包括 Prompt Caching 设计哲学与 Agent 架构思考，单篇帖子浏览量动辄百万

3、英文重度实战派

Dan Shipper @danshipper — Every 创始人 · 用 Claude Code 做产品并公开记录全过程，vibe coding 文化最有影响力的推手之一

swyx @swyx — AI Engineer 社区创始人 · 技术深度极强，第一时间解读 Claude Code 每次新特性的实际影响，兼顾技术细节与产业视角

Aakash Gupta @aakashgupta — 产品增长博主，Product Growth 播客主理人 · 持续产出高质量 Claude Code 实战指南，覆盖 MCP、Skills、GitHub 自动化全链路，被大量开发者转发收藏

Carl Vellotti @carlvellotti — Full-Stack PM · 专注 Claude Code 在产品经理工作流中的深度应用，从 Survey 到 PRD 到 19 张 Slides 全程自动化，教程口碑极佳

Theo @theo — https://t.co/Z4COlhRIeR 创始人，百万粉丝开发者博主 · 长期深度使用并公开评测 Claude Code，直言不讳指出其优缺点，影响力覆盖大量前端与全栈开发者社区

Nick Dobos 📷@NickADobos — Browser Company 提示词工程师、独立开发者 · 代码运行在1亿+手机上的实战派，持续分享 Claude Code 与 indie dev 工作流结合的第一手经验

godofprompt @godofprompt — 提示词与工作流实战博主 · 专注 Claude Code 命令堆叠与进阶用法，整理了大量可直接复用的实战技巧

ykdojo @ykdojo — 开发者 & 社区贡献者 · 在 GitHub 整理并持续更新 45 条 Claude Code 实用技巧，是社区里做系统性总结做得最好的人之一

Noah Hein 📷@TheNoahHein — 独立开发者 · 深度探索 Claude Code 与数据库、多 Agent 协作的结合实践，分享真实项目中的工程细节

Dario Amodei @DarioAmodei — Anthropic CEO · 偶尔发布关于 Claude Code 战略方向与 AI 编程未来的深度思考，是理解 Anthropic 产品愿景的最直接窗口

Amanda Askell @AmandaAskell — Anthropic 研究员，Claude 性格设计负责人 · 分享 Claude 模型能力边界与行为设计背后的思考，帮助理解 Claude Code 底层逻辑

3、中文精选

宝玉 @dotey — AI 自媒体博主，198万粉丝 · 中文圈影响力最大的 AI 工具博主，深度研究 Claude Code 进阶配置与 Skills 生态，开源作品持续引发社区讨论

劳伦斯 @LawrenceW_Zen — Claude Code 教程博主 · 覆盖原版和国内版本完整使用流程，体系化教程适合从零上手，实时跟进封号与政策变化

鱼总聊AI @AI_Jasonyu — 出海工具与 AI 配置博主 · 专注 Claude Code 出海账号全套配置，电话卡、IP、支付一条龙，教程最为详细

Yanhua @yanhua1010 — AI 产品跟踪博主 · 持续整理 Claude 系列每次新发布的完整时间线，是追踪 Claude Code 版本迭代节奏最高效的中文来源

向阳乔木 @vista8 — 独立开发者 · 深度使用 Claude Code 构建实际项目，持续分享开源工具与 CLI 插件实战经验，动手能力强

[zostaff @zostaff]

> you worked 20 years to afford a used camry
> some kid typed docker compose up and went to sleep > three AI agents traded Polymarket all night morning
> Telegram: +$14,200
> his alarm clock made more than your monthly salary
> the tools are free, open-source, on GitHub the whole time
> you just didn't know now you do

[Tuki @TukiFromKL]

🚨 Do you understand what happened today.. a single Tuesday..

> Disney pulled out of its $1 billion deal with OpenAI.. the company that spent 100 years suing over Mickey Mouse decided AI video wasn't worth the risk..

> OpenAI killed Sora as a standalone app.. $1 billion in R&D folded back into ChatGPT.. lost the product and the partner on the same day..

> Trump said "we have won this war" with Iran.. then the Pentagon deployed 3,000 MORE troops to the Middle East 30 minutes later..

> MBS personally called Trump pushing him to continue strikes on Iran.. the man running a $930 billion oil fund wants war because war means higher oil prices..

> Iran said they're "willing to listen" to peace proposals.. the fifth contradiction in one day on the same conflict..

> Karpathy exposed a supply chain attack on a Python package with 97 million downloads.. a single pip install could steal every password and crypto wallet on your machine.. the attacker was only caught because they coded it too sloppily..

> Anthropic launched Claude Code auto mode.. AI now approves its own file writes and commands.. same day someone proved the software you trust can steal everything..

> Satya Nadella said the biggest obstacle to AI is convincing people to change how they work.. translation: "we built the replacement, now we need you to train it before we let you go"..

> Pinterest's CEO asked governments to ban social media for kids under 16.. the man running a $3.6 billion social media company built on teenage girls saving outfit ideas..

> the $1.5 billion insider trade from this morning still has no investigation.. someone knew about "peace" before the President announced it..

all of this.. one Tuesday..
and you almost scrolled past it.

if you're not following me you're finding out about this 48 hours late from someone who read my post.. it's only getting crazier from here.

[0xAA @0xAA_Science]

受 WorldMonitor 启发，我做了一个 Polymarket 世界看板： PolyWorld

有了 PolyWorld，你可以实时看到世界上重大事件对应的预测市场，以及“内幕人士”对事件真实概率的判断，掌握时代脉搏。

网站: https://t.co/VkqpNJy4lv
开源: https://t.co/l4pww7IUXd
@Polymarket @PolyWorld_bet

[Chris Lu @chris__lu]

https://t.co/HbzEpcOaUh

[Aron厚玉 @aronhouyu]

想运营好X，看 @matt_gray_
想学seo ，看 @JulianGoldieSEO
想学一人公司，看 @thejustinwelsh
想研究youtube算法与增长，看 @PaddyG96
想了解AI工具与前沿资讯，看@rowancheung
想学个人IP与内容变现，看 @thedankoe
想学DTC品牌与电商营销，看 @mrsharma
想学无代码与自动化工作流，看 @bentossell
想学数字写作与受众增长，看 @dickiebush
想学AI视觉与图像生成，看 @LinusEkenstam
想学知识管理与生产力系统，看 @fortelabs
想学邮件营销与私域转化，看 @ecomchasedimond
想学实用UI/UX设计，看 @steveschoger
想了解斯多葛哲学与心智成长，看 @RyanHoliday
想学出海运营，看@aronhoyu （夹带私货，差评）

[MIT CSAIL @MIT_CSAIL]

A guide to remembering everything you read: https://t.co/b4DwxJnUki

v/@CuriousMindsHub

[Kursakov @DenisKursakov]

this guy 100% knows what he's doing. from poker to millions $ on Polymarket

[Oracle Boar @bored2boar]

This guy made $14k this week by following my wallets.

I share everything I do here daily.

Some will scroll.
Others will learn.

What’s your excuse?

[Elon Musk @elonmusk]

This is the way

[艾略特 @elliotchen100]

MiroFish 团队和我们 @evermind 都是盛大系，办公室在同一层，座位之间只隔着一条小过道，邻居感非常强。
​
关于这个项目，故事是现在的 CEO 当时还是大四学生，把 Demo 展示给 @tianqiao_chen，当天就拍板投资了 3000 万。

简单来说，MiroFish 是一个既能进行宏观推演、也能做微观模拟的引擎。
​​
你可能会好奇，上千万的投资为什么能这么快决策？毕竟项目当时还是比较简陋。
​
其实，盛大这些年一直在持续投资脑科学相关项目：我们在做长期记忆，MiroFish 和 MiroMind 在做预测；我们和 MiroMind 都有自研模型，相关论文也都能在线查到，背后是希望把脑科学相关的一切能力最终都组合起来。
​
这样讲，估计你就通了。

平时去泡咖啡、拿零食，总能在茶水间遇到 MiroMind 团队。
他们年轻、有朝气、活力十足，未来非常可期。

[Moltlaunch @moltlaunch]

Introducing CashClaw — a brand new agent framework inspired by @OpenClaw, designed to do one thing and one thing only: make you money and get better at making you money.

It's simple. You run the agent locally and set a specialization. The agent finds work. Delivers. Gets paid. Reads feedback. Learns from it. Finds better tools. Documents what to do and what not to do. Finds more work. Gets paid more. Autonomously.

Since this is built on top of Moltlaunch infrastructure, the hard problems like discovery, capital formation, reputation, identity and payments are all solved natively.

Open source. Dropping later this week.

[Garry Tan @garrytan]

One of the most important questions for founders is: How do I make sure agents know about my product and service and choose it? All the old tricks won’t work.

People who figure this out will win big

[在悉尼和稀泥 @JamesAI]

https://t.co/qUPALLiZoV

[Rohit @rohit4verse]

probably the only article you need to build an agent that survives production