欧西里斯516

[欧西里斯516 @blackm516]

以不到一年的经验看，美股公司的科技含金量、市占率、业绩确实称得上投资。缅A还是投机成分居多，情绪和资金面为主要推动力。难怪几年前，良心大V都推荐美股市场。

[欧西里斯516 @blackm516]

TrendForce estimates that the combined 2026 CapEx of Google, Amazon, Meta, Microsoft, Oracle, ByteDance, Tencent, Alibaba, and Baidu will exceed US$886.7 billion, with the five North American hyperscalers accounting for nearly 90%.
https://t.co/7PYVfCBAR5

[Creative Deduction @CreativeDeduct]

Adam Smith’s most famous sentence remains one of the clearest statements in all of social science:

“It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest.”

The point is simple and profound. We do not rely on the kindness of strangers to put food on the table. We rely on their self-interest. The butcher supplies meat because he profits by doing so. The baker rises early because customers will pay for bread. Their desire to improve their own condition leads them, without any central direction, to serve ours.

This is the central mechanism of a market economy. Self-interest, channelled through voluntary exchange, produces cooperation on a vast scale. No one has to love their customers or share their political views. They only have to respond to incentives. The result is a system that regularly feeds, clothes, and houses millions of people who will never meet.

Many on the left still struggle to accept this. Self-interest is treated as morally suspect - a form of greed that should be restrained or replaced by appeals to solidarity and collective purpose. The preference is for systems that rely on moral exhortation or state direction rather than on the everyday pursuit of personal advantage. Yet the historical record is clear: societies that suppress self-interest in the name of higher motives tend to produce shortages, stagnation, and coercion. Societies that allow people to benefit from serving others tend to produce abundance.

Smith’s insight is not a celebration of selfishness. It is a recognition of reality. People are more reliable when they can improve their own lives by improving the lives of others. That simple alignment of interests remains the most powerful engine of social cooperation ever discovered.

[欧西里斯516 @blackm516]

https://t.co/vWOZyQ3ld1
世界第一封测厂日月光2026年资本开支增加至105亿美金，封测确实前途无量。综合看amkor估值更低。

[Ray Dalio @RayDalio]

Understanding, accepting, and working with reality is both practical and beautiful. I have become so much of a hyperrealist that I’ve learned to appreciate the beauty of all realities, even harsh ones, and have come to despise impractical idealism.

Don’t get me wrong: I believe in making dreams happen. To me, there’s nothing better in life than doing that. The pursuit of dreams is what gives life its flavor. My point is that people who create great things aren’t idle dreamers: They are totally grounded in reality. Being hyperrealistic will help you choose your dreams wisely and then achieve them.

#principleoftheday

[CTO ROBOTICS Media @ctorobotics]

This isn't science fiction anymore. 🧲

The Chinese University of Hong Kong researchers developed a magnetic slime robot that can be remotely controlled to move, squeeze through tight spaces, and even grasp objects.

One potential application? Removing objects accidentally swallowed inside the human body without traditional surgery.

Soft robotics is opening doors that rigid robots simply can't.

Would you trust a robot made of slime inside your body?

🎥 Media: @newscientist , Li Zhang and The Chinese University of Hong Kong

⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

#Robotics #SoftRobotics #MedicalRobotics #Engineering #Innovation #FutureTech #Science

[欧西里斯516 @blackm516]

you cannot argue with stupid or crazy people.

[Maye Musk @mayemusk]

A friend of mine said that we should welcome illegal immigrants, so long as they don’t live near her. She’s now a former friend. My mom used to say, you cannot argue with stupid or crazy people. Her quote is in my new book. I still try, but without success.

[欧西里斯516 @blackm516]

一场游戏一场梦，哪里来 回哪里去。估计老天爷觉得火候还不够，百八十万就飘了，还得炼啊😁

[欧西里斯516 @blackm516]

https://t.co/HwFzNP72C2 its operating margin expanding to nearly 70%

[欧西里斯516 @blackm516]

世界第二的封测公司113亿美金，第三的长电科技1300亿人人民币，次新股盛合晶微2200亿。此外还有长鑫和美光，龙芯中科和英特尔。对比美股和缅A的��行业公司财报后，突然就明白大A为什么永远3000点，经济低迷，业绩不行，估值离谱。股市是经济的晴雨表，好坏不能光靠嘴。

[欧西里斯516 @blackm516]

卧槽，韩国证券的预测竟然准得离谱

[Jukan @jukan05]

SK hynix (Market Cap: KRW 1,132.2632 trillion)
2Q26 Earnings Results

▶️ Results:

Revenue: KRW 79 trillion (+257% YoY)
(Consensus: KRW 84 trillion; 5.5% below consensus)
Operating profit: KRW 61 trillion (+557% YoY)
(Consensus OP: KRW 64 trillion; 5.4% below consensus)

Operating margin: 76.3%
(Consensus OPM: 76.2%; 0.1%p above consensus)

[欧西里斯516 @blackm516]

想往里冲

[欧西里斯516 @blackm516]

再好的业绩也得跌😁

[Sravan Kundojjala @SKundojjala]

Amkor 2Q26
- Rev up +12.6% q/q and +26% y/y to $1.898B at 16.8% GM, both above the high end of guidance; 3Q26 guided $1.95-2.05B at 18.5-19.5% GM
- FY26 capex unchanged at $2.5-3.0B; FY26 capex split newly disclosed at 65-70% facilities expansion including Arizona phase 1
- the 3Q revenue guide is only +0.7% y/y at midpoint against $1.987B in 3Q25 because comms is guided down HSD q/q instead of the usual iPhone-launch lift, so y/y growth goes from +26% to roughly zero in one quarter even as computing accelerates
- biggest incremental of the call, FY26 will be at 17.5% GM, which is exactly the FY28 IR day target, two years early and on $7.5B of revenue vs the $9.0B in that 2028
- that implies +$1.5B of revenue between 2026 and 2028 delivering zero incremental GM; the company cites the initial US ramp a headwind

[欧西里斯516 @blackm516]

最后一轮融资估值1400亿，上市直接3万亿。海力士和美光才10倍PE，这直接30倍。大A有病啊

[欧西里斯516 @blackm516]

测试

[Ricky Ho @rickyho_1989]

Nomura's report reinforces what we believe is one of the most underappreciated structural shifts taking place across the semiconductor industry today, namely that testing is no longer a low-value manufacturing step performed at the end of production, but is rapidly evolving into one of the most critical value-added processes within the entire AI hardware supply chain, because as chips become exponentially more complex through chiplets, stacked HBM, advanced packaging, silicon photonics and eventually co-packaged optics (CPO), the economic cost of failure rises disproportionately, making every additional dollar spent on testing significantly more valuable than it was during previous semiconductor cycles.

The market has understandably spent the past two years focusing almost exclusively on GPU designers, HBM suppliers and advanced packaging companies, yet what this report demonstrates is that testing is quietly becoming the next bottleneck, because increasingly sophisticated AI accelerators cannot simply be manufactured, they must be validated repeatedly throughout the production process to ensure every component performs flawlessly before being assembled into AI systems that may ultimately be worth several million dollars each, effectively transforming testing from a manufacturing support function into an essential yield protection mechanism.

Historically, testing was largely viewed as a necessary manufacturing expense whose primary objective was to filter out defective chips before shipment, but AI has fundamentally altered that equation because testing today is increasingly about protecting economic value rather than merely measuring quality, and when a single package contains multiple GPU chiplets, twelve stacks of HBM, advanced substrates, hybrid bonding interfaces, silicon photonic engines and increasingly expensive packaging materials, discovering a defect late in the production process can destroy vastly more value than in previous semiconductor generations.

That is precisely why Nomura estimates testing content continues to increase materially with every GPU generation, using Hopper as the baseline, where final testing time increases approximately fourfold for Blackwell and roughly sevenfold for Rubin, while system-level testing rises approximately 1.5 times for Blackwell and 2.5 times for Rubin, with burn-in testing roughly doubling, resulting in testing content increasing from approximately 1.9% of total GPU cost for Hopper to 2.5% for Blackwell and approximately 3.3% for Rubin, a progression that may appear modest when expressed as percentages but becomes extraordinarily meaningful when applied to AI systems whose selling prices continue rising dramatically.

Perhaps the most important observation in the report is not simply that testing content is increasing, but that testing itself is migrating earlier throughout the manufacturing process, effectively shifting from a single inspection performed after fabrication into a continuous validation framework that begins at wafer probing, continues through known-good-die verification, hybrid bonding validation, package testing, burn-in qualification and ultimately system-level testing before deployment inside hyperscale AI clusters, meaning the industry is increasingly adopting multiple quality gates rather than relying on one final inspection at the end of production.

This shift has enormous implications for the supply chain because every additional testing insertion creates incremental demand for specialized equipment, probe cards, sockets, handlers, MEMS probes, thermal management systems and high-speed interfaces, thereby expanding the opportunity set well beyond traditional outsourced semiconductor assembly and test companies, which explains why Nomura has broadened its coverage to include interface suppliers and test hardware manufacturers rather than limiting its investment thesis solely to OSAT providers.

Another theme that deserves significantly more attention is the interaction between advanced packaging and testing, because while investors have understandably focused on CoWoS capacity as one of the industry's largest bottlenecks, packaging capacity alone cannot solve the industry's challenges if testing capacity fails to expand at a similar pace, since every additional layer of complexity introduced through chiplets, hybrid bonding, HBM stacking, heterogeneous integration and silicon photonics simultaneously increases the probability that expensive failures will occur after substantial value has already been added to the product, making testing increasingly indispensable as AI hardware becomes more sophisticated.

The discussion surrounding co-packaged optics is equally compelling because most investors naturally associate CPO with optical component suppliers, whereas Nomura correctly argues that the real opportunity extends much further into the testing ecosystem, given that every optical engine must communicate flawlessly with adjacent ASICs under extremely demanding thermal, electrical and optical conditions while maintaining signal integrity across increasingly complex architectures, thereby introducing entirely new categories of testing that simply did not exist in previous semiconductor generations and creating an additional secular growth driver for testing vendors.

We also agree with Nomura's conclusion that the AI infrastructure cycle remains considerably earlier than many investors assume, because every successive GPU generation is becoming disproportionately more difficult to validate than its predecessor, allowing testing content to grow materially faster than semiconductor unit volumes themselves, which means the industry's next major beneficiaries may not necessarily be the companies designing the chips, but increasingly the companies ensuring those chips actually function reliably inside increasingly expensive AI systems.

Our preferred way to position for this theme is to own the entire testing value chain rather than focusing solely on OSATs, because different parts of the ecosystem benefit from different stages of the testing process. ASE (3711 TT) remains our highest-conviction OSAT exposure given its scale, broad customer base and dominant position across advanced packaging and testing. Hon Precision (7769 TT) stands out as one of the most attractive pure-play beneficiaries of final testing and system-level testing, areas where AI complexity is expanding the fastest. WinWay (6515 TT) offers differentiated exposure through sockets and probe cards, which should experience rising content per AI accelerator as electrical and thermal requirements become increasingly demanding. MPI (6223 TT) is well positioned through wafer probing, benefiting directly from the industry's shift toward earlier testing insertions and known-good-die validation. KYEC (2449 TT) remains an attractive second OSAT exposure with meaningful leverage to AI testing demand, while Chroma (2360 TT) provides exposure to automated testing equipment, allowing investors to participate in the hardware upgrade cycle required to support increasingly sophisticated AI devices.

Ultimately, we believe semiconductor testing has quietly transitioned from a manufacturing support function into one of the industry's most valuable strategic chokepoints, and just as HBM suppliers, advanced packaging companies and foundries have enjoyed structurally stronger pricing power because they occupy indispensable positions within the AI value chain, testing vendors increasingly appear poised to achieve similar economics as AI hardware becomes more heterogeneous, more thermally demanding, more optically integrated and substantially more expensive to manufacture, making testing one of the highest-conviction secular investment opportunities across the broader semiconductor ecosystem.

[欧西里斯516 @blackm516]

@Isluckyethan 现在的AI��情是财报好的跌，财报不好的跌更多，AI现有的收入无法覆盖支出（anthropic 和OpenAI 都是用20倍的市销率定价）。几家大的云服务商不断砸钱做基建，今年整条产业链的主要收入就是云服务商砸的8700多亿美金建设数据中心。spacex最赚钱的部分是星链，却把AI当作公司的最大的招牌😁

[欧西里斯516 @blackm516]

亏损的原因，美国政府当年57亿美金的补贴，涨了125亿美金

[欧西里斯516 @blackm516]

英特尔二季��报：收入增长25%，毛利率40.4%，单股利润0.42（一季度0.29）。

[欧西里斯516 @blackm516]

前段时间台积电才和amkor签署协议，英伟达也来。amkor封测世界第二，仅次于台湾日月光，美国本土企业，看估值倒不是很贵。

[欧西里斯516 @blackm516]

印��中第一版消息，是没名字的。这么大的奖，连个简历都没有

[欧西里斯516 @blackm516]

中国籍😄