Tiger_smith

[Tiger_smith @X0Pgn]

@Pzhivao @cuichenghao 当狗习惯了吧

[Tiger_smith @X0Pgn]

@SimomLiu @cuichenghao Sb

[Tiger_smith @X0Pgn]

@TnTfhcs0p @cuichenghao Sb

[Tiger_smith @X0Pgn]

@Z_Lib_official @itsgeohere 收费了？还是下载超过数量了

[Tiger_smith @X0Pgn]

@Astronaut_1216 我开了个找电子书的，十来个找我的，但是我就找到一本，哎，挣不到这个钱啊

[Tiger_smith @X0Pgn]

几百万的网红 sunny 被全网封杀，说是因为她杭州商k最近都关门了😂

身材确实好，视频质量都很高，可惜进去了

[Tiger_smith @X0Pgn]

快来观看 AstroPlaneet 的视频！#TikTok https://t.co/YoHZGMQD0T

[TheBigBerbowski @TheBigBerbowski]

Here's the alpha list.
Bookmark and use it for the next 10 years.

If you find it useful, please throw in a like / share.

LAYER 1: APPLICATION
AI Assistants & Chatbots:
Microsoft, Google, Meta
Enterprise AI SaaS:
Microsoft, Salesforce, ServiceNow, Adobe
AI-Native Vertical Apps:
Recursion Pharmaceuticals

LAYER 2: AI MODEL
Foundation Models:
Google, Meta
Fine-Tuned / Specialized Models:

LAYER 3: SOFTWARE INFRASTRUCTURE
ML Frameworks:
Google
GPU Programming Layer:
NVIDIA, AMD, Intel
Distributed Training Systems:
Microsoft
Container Orchestration:
IBM, Broadcom
Inference Optimization Stack:
NVIDIA

LAYER 4: CLOUD INFRASTRUCTURE
Hyperscaler Clouds:
Amazon, Microsoft, Google, Oracle
NeoClouds:
CoreWeave, Nebius
Edge / Inference Clouds:
Cloudflare, Fastly, Akamai
Data Center Colocation:
Equinix, Digital Realty, NTT

LAYER 5: COMPUTE HARDWARE
Training GPUs:
NVIDIA, AMD
Inference GPUs:
NVIDIA, AMD, Intel
Custom AI ASICs:
Google, Amazon, Microsoft, Meta
Dedicated Inference Accelerators:
Cerebras
Server CPUs:
AMD, Intel, NVIDIA, SoftBank
Networking ASICs / Switches:
Broadcom, NVIDIA, Marvell, Cisco

LAYER 6: MEMORY
HBM:
SK hynix, Samsung, Micron
DRAM:
Samsung, SK hynix, Micron
NAND Flash:
Samsung, Kioxia, Western Digital, Micron
LPDDR:
Samsung, SK hynix, Micron

LAYER 7: INTERCONNECT
Co-Packaged Optics:
Broadcom, NVIDIA, Marvell, Cisco
NVLink / Fabrics:
NVIDIA, AMD, Astera Labs, Broadcom
Optical Transceivers:
Coherent, Lumentum, Innolight, Eoptolink
Linear Pluggable Optics:
Credo, Marvell, Broadcom, Lumentum
Ethernet / InfiniBand:
NVIDIA, Broadcom, Cisco, Arista
Coherent Optical Transport:
Ciena, Nokia, Cisco
Long-Haul DWDM:
Ciena, Nokia, Cisco, Fujitsu
Submarine & Metro Fiber:
NEC, Prysmian
External Light Sources:
Coherent, Lumentum, Intel
Optical Connectors:
Corning, Amphenol
Optical Engines:
Broadcom, Marvell, Coherent
Fiber Cables:
Corning, Prysmian, Furukawa Electric

LAYER 8: ADVANCED PACKAGING
Wafer-Level Packaging:
TSMC, ASE Technology, Amkor, Samsung
HBM Integration:
SK hynix, Samsung, Micron, TSMC
FC-BGA Substrates:
Ibiden, Unimicron, Shinko Electric, AT&S
Glass Core Substrates:
Intel, Samsung Electro-Mechanics, Corning
Thermal Interface Materials:
Henkel, Shin-Etsu Chemical, Honeywell, Parker Hannifin

LAYER 9: SEMICONDUCTOR FOUNDRY
Leading Edge Foundry:
TSMC, Samsung Foundry, Intel Foundry
Mature Node Foundry:
GlobalFoundries, UMC, Tower Semiconductor, Vanguard International
Silicon Photonics Foundry:
GlobalFoundries, TSMC, Intel
Compound Semiconductor Foundry:
Wolfspeed, Qorvo, MACOM, WIN Semiconductors
OSAT:
ASE Technology, Amkor, JCET, Powertech Technology

LAYER 10: SEMICONDUCTOR EQUIPMENT
Lithography:
ASML, Nikon, Canon
Deposition:
Applied Materials, Lam Research, Tokyo Electron, ASM International
Etch:
Lam Research, Tokyo Electron, Applied Materials
Burn-In & Reliability Testing:
Advantest, Teradyne, Cohu, Aehr Test Systems
Metrology & Inspection:
KLA, ASML, Onto Innovation, Hitachi High-Tech
Compound Semiconductor Growth:
Aixtron, Veeco, Taiyo Nippon Sanso

LAYER 11: SEMICONDUCTOR MATERIALS
Silicon Wafers:
Shin-Etsu Chemical, SUMCO, GlobalWafers, Siltronic
SOI Wafers:
Soitec, Shin-Etsu Chemical, GlobalWafers
InP Substrates:
AXT, Sumitomo Electric
GaAs Substrates:
AXT, Sumitomo Electric
SiC Wafers:
Wolfspeed, Coherent, onsemi, ROHM
Photoresist:
Tokyo Ohka Kogyo, Shin-Etsu Chemical, DuPont
Anti-Stick Coatings:
Merck KGaA, AGC, Daikin
Specialty Gases:
Air Liquide, Linde, Merck KGaA, SK Materials

LAYER 12: CRITICAL MINERALS
Silicon:
Wacker Chemie, OCI Holdings, GCL Technology
Copper:
Freeport-McMoRan, BHP, Glencore
Gallium:
5N Plus, Dowa Holdings
Indium:
Korea Zinc, Teck Resources, Dowa Holdings, 5N Plus
Germanium:
Yunnan Germanium, Umicore, 5N Plus, Teck Resources
Hafnium:
ATI
Tantalum:
AMG Critical Materials, Ningxia Orient
Tungsten:
Xiamen Tungsten, CMOC, Almonty Industries
Cobalt:
Glencore, CMOC
Lithium:
Albemarle, SQM, Ganfeng Lithium, Tianqi Lithium
Rare Earths:
MP Materials, Lynas Rare Earths, China Northern Rare Earth, Iluka Resources

THERMAL MANAGEMENT
Air Cooling:
Vertiv, Schneider Electric, Delta Electronics, Johnson Controls
Direct-to-Chip Cooling:
Vertiv
Thermal Interface Materials:
Henkel, Honeywell, Shin-Etsu Chemical, Parker Hannifin
Heat Exchangers / CDUs:
Vertiv, Alfa Laval

SECURITY
AI Security:
Check Point, Palo Alto Networks, F5
Cybersecurity:
CrowdStrike, Palo Alto Networks, Google, Zscaler
Post-Quantum Cryptography:
IBM
Optical Network Encryption:
Ciena, ADTRAN, Nokia, Cisco
Hardware Root of Trust:
Intel, AMD, Arm, Microchip Technology

EDGE & PHYSICAL AI
Edge AI:
NVIDIA, Qualcomm, Intel
Edge Compute:
Qualcomm, NVIDIA, Apple, Google
Autonomous Vehicles:
Tesla, Mobileye, NVIDIA
Quantum Computing:
IBM, Google, IonQ
Humanoid Robotics:
Tesla
Drones / UAVs:
AeroVironment
Driver Monitoring:
Seeing Machines, Smart Eye, Tobii, Cipia
Edge Inference Chips:
Qualcomm, NVIDIA, Ambarella
AR / VR Devices:
Meta, Apple, Sony, HTC
Neuromorphic Computing:
Intel, BrainChip

$NVDA, $AVGO, $TSM, $AMD, $ASML, $MU, $MRVL, $ANET, $VRT, $CRWV, $EQIX, $DLR, $AMAT, $LRCX, $KLAC, $GFS, $ALAB, $COHR, $CRDO, $MP, $ALB

I hope it helps.

@ren_stocks did the heavy lifting.

[Tiger_smith @X0Pgn]

突发新闻：

英伟达首席执行官詹森·黄刚刚在CNBC直播中说：

“在IPO时购买SpaceX、OpenAI和Anthropic将就像在早期购买$AMZN、$GOOG或$META一样。”

这个家伙掌管着全球最昂贵的市值达5万亿美元的公司

他绝对知道些什么！！

[Tiger_smith @X0Pgn]

2004到2026的变化

[Serenity @aleabitoreddit]

Okay... just some more weekend shower thoughts about $XFAB.

I still feel like it could be the next $TSEM, just early stage at a $1.4B MC?

They kinda leapfrogged current gens (which $TSEM are getting volume from) to compete for H2 2027 CPO scale up inflection point ($ASX docs cite Xfab (aka. photonixFAB) as focusing on CPO)

By building out some black magic MTP (transfer printing) architecture for lasers w/ other stuff like TFLN.

Basically next-gen integration IP, they're still behind on yields, sure.

But $NVDA evaluating it for transceivers/switches to see if it can volume ramp. That $NOK sets the specifications/assembly for. (nvidia invested in nokia for this these switches/networking too btw).

And if their MTP supply chain works... (eg. with Smartphotonics providing lasers, EU players doing assembly).

It basically volume ramps with $NVDA just like why Nvidia signed long term agreements with $TSEM?

Downside risk?

Already below replacement book value, can always go lower yeah, but typically to a certain point.

Maybe more CHIPS act subsidies next few months from chips act 2. If it doesn't go well there's SiC (152% Y/Y Growth, 195% Y/Y SiC wafer shipment growth)/GaN power semi upside.

Europeans /LLMs will say "oh evaluations doesn't mean it's a future contract!".

This is kinda different since the European Union is behind this effort and $XFAB for soverign photonic supply chains.

Not your typical company + hyperscaler evaluation, since $NVDA wants to be nice to Europe's regulators. They'd prob be pissed if nvidia just stayed in US/Taiwan/China.

So if they can make this MTP black magic work with mass production, feels almost for sure nvidia/nokia volume ramp on some tiny $1.4B silicon photonics foundry or at least throw them a bone with smaller contracts.

In terms of timelines, maybe just a months early since it volume ramps H2 2027/H1 2028 (which happens to be in line with CPO scale up timelines)...

Or just unknown because they named their project something stupid like photonixfab?

Like XFAB Photonics would have been better? so institutions/screeners can connect the dots when looking at CPO silicon photonic foundry players?

Automotive should also coming out of a slump medium term, sped up by self-driving (TSM Chairmain comments yesterday said ai automotive was TSM's growth vector alongside robotics). So their core business also should pick up speed too medium term.

Obviously markets/europeans want a "Nvidia signs $2B+ contract, XFab volume ramping 2027!"

But by then it will be a $9B+ company and you miss out on all the upside. And especially since everyone analyst/institution is blind to volume expectations for these....

Normally don't invest in companies in evaluation stages, but this just seems very de-risked by EU sovereignty + Gov backing, and you have Nvidia + Nokia there for volumes if they can make the IP work.

I think markets are probably missing something here... there's almost 0 value being assigned to being CPO exposure in Europe as their long term upside.

[Tiger_smith @X0Pgn]

@cherryPayment 大哥你在哪买的美股啊

[Annie 所长 @web3annie]

黄皮衣：AI 的算力需求还要增加1000x，未来的能源需求还要增加1000x！

下一个能源100倍股：👇

1. 英伟达 $NVDA
黄仁勋喊未来算力暴涨1000倍，本质就是继续给英伟达打广告

2. 台积电 $TSM
台积电就是整个AI帝国的芯片印钞机

3. 博通 $AVGO
很多人只知道英伟达，但AI服务器内部高速连接、交换芯片，大量都靠博通

4. 超微电脑 $SMCI
英伟达GPU最后要装进服务器才能赚钱，属于AI军火运输队

5. GE Vernova $GEV
未来最大瓶颈不是芯片，是电，GEV就是搞发电设备、电网升级、能源的

6. Vistra 能源 $VST
Vistra同时拥有核电、天然气、储能

7. Constellation Energy $CEG
美国最大核电运营商之一

8. Cameco $CCJ
全球铀矿核心玩家

9. NextEra Energy $NEE
新能源超级巨头

10. Vertiv $VRT
AI机房空调之王

11. Eaton 伊顿 $ETN
变压器、���电、电力管理都会爆发

12. Schneider Electric 施耐德电气 $SBGSY
复杂能源调度、供电系统、智能管理，施耐德在这一块全球顶级

13. 亚马逊 $AMZN
现在亚马逊已经开始疯狂升级AI数据中心电力系统

14. 微软 $MSFT
微软现在已经不是软件公司，已经开始亲自布局核电和能源

15. Credo Technology $CRDO
AI服务器之间的数据传输速度越来越重要，CRDO专门做高速互联芯片

你最看好哪一个？

[麦通MSX @MSX_CN]

🚀 MSX Pre-IPO 二期即将上线。

一期 Cerebras 刚刚点燃市场热情，
这一次，MSX 带着两个备受瞩目的优质项目又来了：

🔹 Anthropic
Claude 背后的 AI 大模型公司
认购价：855 USDT｜最新估值：9500 亿美元

🔹 Polymarket
Web3 预测市场代表平台
认购价：152 USDT｜最新估值：150 亿美元

从 AI 大模型，到预测市场，
MSX 继续为用户寻找更早期、更稀缺的优质资产机会。

公告详情👇
https://t.co/6QyILL9o1C

#MSX #麦通 #链上美股用麦通 #PreIPO #AI #Polymarket

[Tiger_smith @X0Pgn]

@0xJoveXu 坐等互关

[落叶知秋 @haiou1850962]

全网最“危险”的艺术品！火柴狼点火全过程，极度舒适。

[孙云冉.eth @sunyunran]

ai真是强大，离番号片也不远了吧

[Tiger_smith @X0Pgn]

@xtony1314 期待૮ ºﻌºა站岗

[看不懂的SOL @DtDt666]

兄弟们少刷抖音15分钟，认真看完这个视频，改变你的投资认知！

1962年，沃伦·巴菲特买下了一家叫伯克希尔·哈撒韦的纺织厂。

这是他后来说的"一生中最愚蠢的决定"。

纺织厂一直在亏钱。

工厂老旧，设备落后，工人却认真得要命。

巴菲特每次去工厂视察，都能看到工人们在缝纫机前埋头干活，午饭只休息二十分钟。

他在那里站了很久。

回到奥马哈之后，他给合伙人查理·芒格打了一个电话。

芒格问："你打算关掉纺织厂吗？"

巴菲特沉默了很久，说："我关不掉。"

芒格说："为什么？从财务上看，早就该关了。"

巴菲特说：

"我知道。每一张报表都告诉我应该关掉它。但我今天站在车间里，看着一个在这里干了三十年的女人。她的缝纫速度是我见过最快的。她的全部人生都在这台机器前面。"

"如果我关掉工厂，数字会变好看。但我要看着她的眼睛告诉她。"

他没有关。

他让纺织厂继续运营了二十三年。

每一年都在亏钱。

他用伯克希尔其他业务赚的钱，养着这个不赚钱的工厂。

直到1985年，实在撑不住了，他才宣布关闭。

关闭的时候，他做了两件事。

第一，提前半年通知所有工人，帮每一个人安排再就业或退休方案。

第二，他去了一趟工厂，跟那些工人一个一个握手。

有人问他："你养了一家亏损的工厂二十三年，值得吗？"

巴菲特后来在致股东信里写了一段话：

"从经济角度来说，我在纺织厂上犯了一个大错误。 我应该更早关掉它。 但我不后悔晚关了二十三年。"
"因为有些账不是用钱算的。 一个人把一辈子交给你的机器， 你欠他的不是一张遣散支票， 是尽可能多的时间。"
芒格后来在股东大会上评价这件事，只说了一句：

"沃伦在投资上是冷血的理性主义者。 但在面对人的时候， 他的理性里有一条不可逾越的线。 那条线就是—— 你不能只用数字衡量的东西， 恰恰是最值钱的东西。"