Twitter · 股票

@meidaoge Agility Robotics hasn’t gone public yet, I’m just waiting for listing announcement this quarter for $CCXI

@KrinschTM Process of elimination from disclosures from 2024 releases. https://t.co/tOCy9xmF0B

"Potential FCC rules on optical transceivers more likely to come at 3.2T" - $LITE, $AAOI, $COHR, $SIVE. Morgan Stanley met with Washington officials: - Restrictions would likely start at 3.2T modules made in China (800g/1.6T would be left alone) - Potential restrictions would likely keep laser market tight (combining US DSPs + lasers could meet the 65% US value threshold per MS) - Chinese modules could qualify if 65% of bill of materials is US content. Chinese modules using US DSPs and lasers are already near that level - Analysts expect the positive impact on laser pricing... to be more important than any broad redistribution of transceiver market share. - Analysts don't expect this to bottleneck hyperscaler AI buildouts, they name InP substrate supply as the key variable to watch (hello $AXTI ) TLDR: Component suppliers in general are really positive. Like $SMTC probably winner here for TIAs/drivers (I don't think this was listed), maybe $MXL for DSPs too. $AAOI another large beneficiary. $SIVE is high-key alpha for laser beneficaries since they have "tremendous capacity" coming online, and that points to US foundries (they haven't formally disclosed location). Since previous slideshows show 2 US foundries 1 Taiwan foundry (Win Semi) in terms of their capacity partnerships. And it's process of elimination. From CIOE Channel checks it does look like they're starting to work with Chinese pluggable players, (so they'd avenues moving forward as US supply chain component beneficiaries). Of course $LITE / $COHR would be happy. TLDR: Western supply chains for Lasers / DSPs / TIAs / others are already bottlenecked but qualified capacity becomes even more important.

@TomSzczypka I'm super glad to hear that and happy your family is doing great! Would love a tour around Toronto. I go there every now and then for one of the music festivals there.

@beauty_oe 今ちょっと風邪がひどいんだけど、無理せずゆっくりしてるよ。ここのみんなからたくさん応援してもらえて、本当に嬉しい。ありがとう！

soxl涨到161了，吗的104抄底108就没了，真他娘的人穷志短。 比起来a股真是纯诈骗。 https://t.co/jK8Lxu15gd

拼音都搞不对，我还是建议这个超级智能的缩写别叫Si，改成Sb I最好。 Super Big Ai，适合他们。 https://t.co/b9xRmg4SQQ

@mdyy0404 盖姐节日快乐

距离1011还有10天 https://t.co/EceRoDYbuw

软银第二家倒闭

你打算All In抄底耐克了吗？

AI财务暴雷之后，第一个归零的就是AVGO 大家自己小心吧 引爆点估计是中期选举和Anthropic IPO前后 😅😅😅

The Power of AI https://t.co/MsLYdFUWhz

日剧配乐的巅峰 我不知道仁医的剧作者，是如何把一件事，做到看似平和、安详的同时， 又让人内心涌起无法抑制的悲伤： https://t.co/DZbiwLikI7

外国是直接发钱、减税、发展经济提高民生 咱们中国则是靠思想品德教育 😅😅😅 https://t.co/aqawIhYiUY

He is a Legend But we all are doomed to die So, tell me Does it really matter?

@BoKuangyi Are U OK？

中期选举之前，绝对的顶部😅😅

中小银行要是全部暴雷了，那XMoney就搞笑了 😅😅

这本质上是一次人类历史上最大的科技政商寡头牛市

结束了 国债引发的Riot，结束了 联储发言恐怕是为了杀死今天国债的short squeeze 等大家意识到该加息还是要加息 叠加算力债务无力偿还，中期选举GOP大败 美股这一次世纪大顶 也就铸成了

10月1日，埃森哲涨幅一度扩大至22%，创历史盘中最大涨幅，现升21.52%，报222.84美元。 此前，埃森哲公布本财年第四财季营收187亿美元，高于市场预估的180.4亿美元，同比增长6.3%；每股收益3.29美元，上年同期2.25美元。 埃森哲预计第一季度营收189.5亿美元至196.0亿美元，同比增长2％至6％；预计2027年营收增长3％至6％；2027年每股收益14.39美元至14.81美元。

好奇日本的公共福利支出占Gdp百分之多少？ https://t.co/SyTzR3fbyY

什么循环债，AVGO不但不收钱，反而还要给Anthropic提供420亿的贷款 😅😅😅😅😅

特朗普拒绝将 OpenAI 和 Anthropic 国有化，但表示美国政府可能会参照入股英特尔的模式，持有约 10% 的股权。

杰斐逊表示，美联储可能需要“更多时间”来决定下一步行动。 又不加息了？😅😅😅

到顶了，降息了 All in了， 新高！

美国房地产即将彻底崩盘：

从动量守恒定律来看，今天应该就是10月份10yr收益率的顶了 但这不意味着美股会继续毫无阻力的走牛 因为美股的牛市几乎完全都来自AI投资 而AI投资的国策 背后几乎完全来自那一个人 那一个党 估计，最多还能坚持到下次选举后吧 😭😭😭

主力？你猜主力背后是谁 你猜他背后的大佬下台之后，这批主力还有没有存在的可能？ 你猜下一次选举是什么时候？

国债的威力，还是出现了？ 😅😅😅

美国国债现在仅存的所谓“海外买盘”原来全都来自开曼群岛？ 这真的不是特朗普政府和硅谷巨头、华尔街资本之间的Py交易吗？ 😅😅😅

十月第一天。多头进场准备了😅😅

别画了，天天画这种图，看着都烦死

@catmangox nb

500万美元的期权交易押注：美国10年期国债收益率将在10月9日前升至5.1%。——彭博社（Bbg）

空头跑了，半导体马上、立刻、迅速、绝对新高！

@nobita_3D 我爱死你，我爱你一辈子！

@nobita_3D 我是贴主的老公！

才8%？我还以为10%呢 失控的那一瞬间估计能到10%

All In！！！！！！！

这位，这家公司，和这个人 他们从美股中赚的确实有点太多了。

AI Agent 的基础设施使用量超越人类 a16z 最新发布的《State of Markets II》报告数据显示，近期 OpenRouter 上 AI Agent 的 7 日平均 Token 使用量已经达到 7.3 万亿。自 2026 年 2 月 AI Agent 的使用量首次超过人类用户以来，这一数字已经增长了 14 倍。 与此同时，亚马逊、微软等 Hyperscaler 已经向数据中心和芯片投入数十亿美元。自 2022 年以来，半导体行业的利润从约 500 亿美元增长至 4,000 亿美元，而这些科技巨头自身的现金流却出现下降。 尽管目前已经有 69% 的标普 500 公司正式部署了 AI 应用，但只有 2% 的公司会追踪具体的长期 AI 效果指标。 这表明 AI 的企业采用虽然已经非常广泛，但整体应用深度仍然有限；与此同时，真正的 AI 重度用户正在迅速扩大领先优势。

我为什么要活着？ 请大家在评论区给我解答 如果找不到100个活下去的理由 我就去死掉 谢谢大家

太可怕了。太 疯狂了

Why, because people had to buy memories ?

@xihyou 至少不会同流合污

外卖员也要失业了 我感觉第三次社会运动马上要诞生了

为什么黄仁勋会说，美国的最大优势是特朗普？因为特朗普是个商人，他给美国几乎所有商人都开了绿灯。 这会出现商业上前所未有的繁荣，但背后的社会经济风险也是不可忽视的。通胀将长期，处于高位。国债将长期，深度贬值。因为私人企业家不关心这些问题 他们只关心自己的GPU能卖多少，自己的AI能赚多少钱，自己的公司如何上市 美国人失不失业，房贷利率是不是到10%，通胀水平如何，普通人还能否安详的养老，所谓K型经济（其实也就是贫富差距的另一种说法）能恶化到什么地步， 甚至自己公司工程师程序员在AI压榨下每天要加班多少小时，他们是绝对不会花一分钟时间关心的。 华尔街和白宫如此深度的利益绑定，历史上都不知道有没有先例。 白宫之前还会关心一下选票，现在是自己直接下场买股票了。所以你如果真的这么看好美国的话，不如直接跟白宫下场炒股就好，稳赚不赔 这也是为什么25年以来，他们稳赚不赔背后真正的逻辑。 科技巨头拿到投资和政策绿灯（比如AI监管和电力方面），白宫拿到内幕消息炒股，华尔街奉旨做多拉盘 美国的实际情况其实就是现在这样，现在到底是all in mu/sndk，soxl，tqqq，还是sgov，qqqm，voo，qqqi，chpy 完全是各位自己的主观选择了。和对市场“什么时候崩盘”的判断，实际上反而是没有什么很大关系

地球上为什么会有这么多人 为什么会有这么多奇葩的事情 那我活着 到底算个什么呢？？

DoorDash 推出“短信下单”AI 与自主配送无人机 在 Dash Forward 活动上，DoorDash 发布了 DoorDash Air——一套低噪音自主配送无人机系统。该系统基于 DoorDash 多年来积累的配送数据进行设计，旨在实现从餐厅到消费者家门口的快速配送，并将率先与 Chipotle 和 Popeyes 合作，在北加州启动服务。 DoorDash 同时在苹果 Messages（信息）App 中推出了一款 AI Agent。用户只需通过简单的短信甚至群聊，就可以让 AI 帮助完成下单、餐厅及商品推荐，甚至可以告诉 AI 冰箱里现有的食材，让它提供相应的食谱和用餐建议。 CEO Tony Xu 表示，这些技术不仅能够加快本地商业和配送效率，也将帮助 DoorDash 扩大零售业务覆盖范围，包括 Macy’s、Vans 等零售品牌，让消费者通过更加无缝的技术体验购买更多种类的商品。

Ai时代，越来越多的人会被淘汰 越来越少的人，会拿到这个世界，绝大多数的财富 这就是这个地球发展到最后，最不幸的现实 我确实在怀疑 我们这样子活下去，究竟是为了什么呢？ 为了让金字塔顶端的人，更好的发展Ai 更好地控制我们？

@DevinOlsenn Maybe because, more people will lose their jobs?

别啊，这一轮，Ai要建设到2032年？ 人类还要活下去吗 还有必要吗？？？

@David_Yanggg 不要污蔑我啊…

@bnchen 记错了，那就是新年放的烟花

立即分辨出哪些留言是Ai回复了，看来Ai没看懂

@h2s_st 不是～～

@EricDengCa @SupplyRadarX 加拿大毕竟贴着美国，还好一点

@XiaoZha62335239 😛

国庆节我一般躲着玩游戏，对“维港烟花”向来没什么热情 上次看还是2019年，记得那年的烟花花团锦簇，但刚一开始，就忽然迎头一场大雨倾盆而下 今年不知怎么又起了兴致，探头望了一眼。烟花声声依旧，只是不知为何，一丝风也没有。烟霾沉沉久久不散，白放了半天，连颜色都看不清 https://t.co/Teims0Wvl4

@tmj55289729 @BabybusFL 萧条真会

@SupplyRadarX AI带动的半导体需求是机会也是挑战 稳定需求下无法被超越的产业链也可能被赶超。现在欧洲所有产业链都完全无法扩产 我在想，十年后还会剩下多少

@MichaelHXHX 天啊‼️

@wangwatchworld 能不带预设立场，理性看待历史的人太少了👍

@blueaibird 这档口缺电、总不能拿电去建算力中心吧 欧洲AI彻底落伍了

@ashinagen32 日本强得多

@diamondrapids 而且可能整个大陆南非化，真是三十年河东、四十年河西 现在纠错能力也很堪忧，德国Afd选赢也没愿意跟他组阁

欧洲是两场低烈度、永续战的绝对、最大loser 两场仗都极大影响能源供应，加之欧洲更左、本身不够pro business，导致他在AI竞赛开始直接被甩下车 30年后，希望我们不会以今天看南非的眼光看欧洲

删了之前转的“friends”，在香港还得小心点

@labubu_trader DeepMind team has never really focused much on commercializing their work

@TY20255718 美债跌了才需要rebalance呀

@Dreamerfreez @Balder13946731 对～astra读语言能力也不强，做文字数据标注也非他所长 sol编程就很厉害，不能让3D专家去写作文，术业有专攻

@jedy12787209 @Balder13946731 我用自己编的

LOL 😂 exactly Doubt this fake news actually helps them

@Ryanhingshing 对～我周五就觉得这个能跌一下，但在不是很值得操作 机器跑的手快的除外

@Balder13946731 编程能力Astra裸模型也很弱 coding场景需要在agent层面做收敛，而不是让模型自己不停探索 更多是Claude code和codex层面的事情

Compute is the true entry ticket for models The game is simply: you either build up the computing power to train, or find a good “teacher” to distill from

LMAO～ “Wait, CNN fake news” He really does have a beef with CNN

@Hamilton8021 yes

@CuiMao 我的笑点是：“wait ~~ CNN fake news” 看完第一反应是，这视频是不是你做的😂

@BabybusFL thus，也是大总统的敌人了 再缺货～～给skhy 80%已经很慷慨了

Pension rebalance came and went with less impact than a lot of ppl feared Partially because of improving Middle East headlines, but also light positioning from both hf and fundamentals

@shouda233 @Strideracc 是为了写

@NiNibili @Strideracc frontier model写的太弱，训小模型因为我没算力训大的 而且训小模型已经可以秒杀frontier model了

@Pathusa 我爽一下，等等就删了

@xzcfrank Yes it’s been a great ride since 09/17

Semicap names are flying 🚀🚀🚀, thanks to $MU

I hope Google can launch their personal AI agents products soon instead of trying to beat OAI/Anth on the coding side. As one of the top three companies in the world(outside of CN) who can distribute apps to consumers with low cost, also running apps of great penetration and retention. I have a hard time understanding why they didn’t move forward in this direction. Seems to be a low hanging fruit for them.

@LiamSherline I guess I shouldn’t limit Limit anymore!

@AnalysisOp I was just about to do it...

@LXC_X_ It’s fun seeing what I can do with it!

@SVTrivo Awesome! 🙌

@PhotonCap I should do that too.

Vicor’s stock has had quite a run lately, and the company has made a clever move: customers can pay for patent rights to use competing modules, then get a royalty discount if they also buy Vicor’s products. It earns licensing income while giving customers a reason to buy its hardware. I took a closer look at how much profit this could actually generate. $VICR

https://t.co/qUJV3sjBUb

https://t.co/cJnyB2Lm4M

@Hodl5x 🤣

@Hodl5x 💯

@SupplyRadarX Sirin好強！

@TJ_Research 感謝TALK君轉發!

@JoeyOnMarkets @zephyr_z9 😮

👀 https://t.co/itLdSqhqeq

AI Networking’s Next Growth Engine: Citi Sees an ~$11B OCS Market by 2030, Led by $LITE and $COHR Citi expects optical circuit switching to become a major growth driver as AI networks demand greater bandwidth and power efficiency. Lumentum ($LITE) and Coherent ($COHR) are its key beneficiaries, projected to capture 80%+ of the merchant OCS market by 2030, subject to adoption and production execution.

@RYANHINGSHING What is this? Not under my radar either lol

$ARM $INTC $AMD CPU supercycle is coming! https://t.co/tuDR58dgea

@AIQuanting Sorry, but I haven’t seen $MU give a firm date for when the second Taichung site actually contributes volume. Mid-October is the facility handover/opening, not the production ramp.

@abbysuyuyan 真的還假的啦

$MU Is Running Out of Room to Package Its Own HBM Rising HBM demand has outgrown $MU’s existing backend capacity in Taichung. Its second advanced-packaging facility is set to open in mid-October, followed by equipment installation and debugging. Plenty of money for new fabs, but still no love for Taiwan employees? 😂 $MU Taiwan employees, you know what to do. Teach them a lesson. 😂 Source: https://t.co/SQgFmXtRg7

$ARM🤭🤭 $NVDA has observed AI agents exceeding approved permissions, including unauthorized writes and network requests. Its safety platform combines OpenShell’s software controls with BlueField hardware monitoring and is optimized for Vera and BlueField systems. Vera uses the $Arm architecture, so wider adoption of NVIDIA’s agent safety platform could expand $ARM’s footprint in AI infrastructure. https://t.co/438KaNKkAz

Great list 🫡

$ASX Adds 449,340 Sq. Ft. of Semiconductor Capacity $ASX’s Singapore unit approved a US$68.44 million factory purchase in Yishun Industrial Park, adding 449,340 sq. ft. for future capacity expansion. Industry sources say the site could support AI-related advanced packaging. That is not company-confirmed yet, but the physical expansion is real—and gives $ASX more room to scale its packaging and testing footprint in Southeast Asia. Source: https://t.co/H3lneBK4d0

And once the base die sits on an advanced logic process, it can do more than relay signals. Samsung points to SRAM repair resources, monitoring, connections to external memory, even selected computation under the DRAM become possible with a custom controller. To learn more about who will be using custom HBM, its implications, and where the value accrues, subscribe to our memory model. (3/3) https://t.co/Q7LydC5RYj

Custom HBM tackles this issue head on. First, the wide standard PHY gets replaced with a compact die-to-die link. Samsung shows that its standard HBM4 PHY occupies 8mm x 4mm, while the custom D2D interface needs just 8.5mm x 1.5mm, roughly 60% less area. The better D2D interface also delivers more bandwidth per unit of interface area and simplifies interposer routing. Second, the memory controller moves off the compute die entirely and onto the HBM base die. Together, these free up a meaningful chunk of the compute die to be handed back for compute or cache. (2/3) Source: Samsung Hot Chips 2026

Real estate on the compute die is extremely valuable, yet a surprising share of it is spent just interfacing with memory. We estimate that HBM4 controllers and PHYs take up roughly 16% of Nvidia's Rubin compute die. That is a lot of leading-edge silicon spent talking to memory instead of performing computations. (1/3)🧵 Source: Nvidia

We criticized Lambda in ClusterMAX 2.0 for their reliability; in this round of testing, it was one of Lambda’s points of emphasis. Their passive health checks cover the relevant conditions and ultimately autoremediated three errors we simulated during testing. Two synthetic XIDs were autoremediated in less than 15 minutes, and there were connected dashboards to monitor node health. Our test that triggered a genuine XID 79 by performing a PCIe secondary bus reset brought the node into `NotReady` with no `GpuXid`, no cordon, and no monitoring visibility on the Kubernetes layer, but it ultimately rejoined the fleet after 2 hours. Our node-reboot tests on the Kubernetes layer also completed without incident. Great work by the Lambda team on the ClusterMAX Sliver!

While Qualcomm announced a month ago that it would implement FlexCache in its Snapdragon 8 Elite Gen 6 processors, Apple has already done the same in their M6 chip without much fanfare. For the first time, Apple combines heterogeneous cores in the same shared L2 cache domain, allowing them to introduce a 3rd core type (branded P but identified as M) without adding a separate M cluster with its own L2. https://t.co/7kCF4KwdKm

This work informs our proposed Bronze / Silver / Gold SLA terms: clear downtime definitions, credits, acceptance tests, monthly reviews, buyer termination rights. Measure restored usable capacity, not closed tickets. Full report👇️ (6/6) https://t.co/lLAtzulRsy

Real example from our TensorWave evaluation: node MIA1-P01-G57 was draining at 3:56 PM and replaced by MIA1-P01-G61 at 4:39 PM (43 min). That visible drain → approve → replace trail is what buyers need, and the SLA should verify the spare is healthy and jobs run on it. (5/6) https://t.co/1ahzqfM3nB

Hardware changes the recovery plan. An HGX cluster can swap a failed 8-GPU node for a hot spare. In an NVL72, a failed 4-GPU tray affects the NVLink domain; the rack may run degraded or need a larger replacement. The SLA must reflect what capacity actually returns. (4/6)

The response has to fit the failure. A contained XID 94 may need an application restart; an uncontained XID 95 needs GPU recovery. Rebooting for every XID kills healthy work. Leaving a seriously faulty GPU schedulable risks more crashes. (3/6)

A dashboard should show the failed component, affected jobs, scheduler state, and when each check last ran. A stale green result is not evidence that the cluster is healthy. (2/6)

🚨 IMPORTANT THREAD FOR GPU RENTERS 🚨 GPU cluster reliability is measured when something breaks. During ClusterMAX assessments, we inject failures and follow the path from detection to restored capacity. Providers differ sharply in how well they handle that path. (1/6)🧵 https://t.co/R3Bxq16IP7