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世界一へと挑む サッカー日本代表の 進化論。 ⠀ サッカー日本代表 映画『ONE CREATURE』 6月5日(金)公開 ⠀ ═══════════════ SAMURAI BLUE Project for FIFA World Cup 2026 『𝙊𝙉𝙀 𝘾𝙍𝙀𝘼𝙏𝙐𝙍𝙀』 無数の個性、ひとつの生きもの。 ═══════════════

President Trump: 🇨🇳🇺🇸 He said he's not going to give military equipment. But at the same time, he said, you know, they buy a lot of their oil there, and they'd like to keep doing that. He'd like to see Hormuz straight opened.

AI时代，半导体公司到底该怎么估值？ 昨天听了@ShanghaoJin 老师的space，获益匪浅。 但我对于存储板块，乃至整个半导体板块的在目前ai产业革命超级周期背景下的估值方法，有一些不同的想法，所以简单记录一下，也供herman老师拍砖。 过去很长时间里，半导体一直是典型周期行业。景气时利润暴涨，低谷时利润迅速蒸发。很多公司上一年PE几十倍，下一年直接亏损。所以过去市场并不太相信半导体公司的利润持续性，更喜欢用 PB、重置成本、EV/EBITDA，而不是PE。因为市场默认这些利润大概率只是周期利润，而不是长期利润。 但AI时代正在改变这一切。HBM、CoWoS、AI Networking、光模块、先进封装、电力与数据中心基础设施，开始出现长期供需失衡。整个行业的估值逻辑，也开始从“资产思维”转向“现金流思维”。 截至2026年，行业仍处在AI驱动的强景气阶段。根据 SIA 数据，2025年全球半导体销售额达到7917亿美元，同比增长25.6%，并预计2026年接近1万亿美元。SEMI 也预计设备销售将在2026、2027继续增长。这种环境下，很多股票估值已经提前包含高增长预期。重要的是增长质量，以及它所处的周期位置。 很多人喜欢只看 PE、forward PE 或 PEG，但半导体行业的问题在于，“周期 + 高成长 + 高资本开支 + 技术代际”全部混在一起，单一估值倍数很容易骗人。周期顶部时，利润爆炸，PE反而会显得特别便宜；周期底部时，利润低迷，PE又会显得特别贵，甚至失去意义。重要的是判断当前利润到底处在周期的哪个位置。 PE 本质上是： PE = \frac{Market\ Cap}{Net\ Income} 它看的是最终归属于股东的利润，因此会受到利息、税率、折旧和资本结构影响。而 EV/EBITDA 更接近企业经营本身的赚钱能力： EV/EBITDA = \frac{Enterprise\ Value}{EBITDA} 其中： EV = Market\ Cap + Debt - Cash 很多人会疑惑为什么现金要减掉。因为 EV 本质上是在看“买下整个公司的真实净成本”。债务需要接手，而账上的现金买下后也归你，所以现金会降低真实收购成本。重要的是理解 EV 关注的是经营业务本身值多少钱，而不是公司账上堆了多少现金。 这也是为什么 Apple、Alphabet、Meta Platforms 经常出现 EV 小于市值的情况，因为它们账上现金太多。 但AI时代又带来了一个新问题。很多公司的现金已经不再是“闲置现金”，而是GPU储备、数据中心扩张储备、AI基础设施战争储备。重要的是区分 Excess Cash、Operating Cash 和 Strategic Cash。有些现金未必真的应该全部减掉。 AI时代另一个巨大变化，是行业进入超级重资本时代。EUV越来越贵，High-NA越来越贵，CoWoS扩产越来越贵，HBM扩产越来越贵，数据中心基础设施越来越贵。整个行业折旧（D&A）正在快速上升。于是很多公司的 EBITDA 非常漂亮，但净利润没有那么夸张，因为大量利润被折旧吞掉了。重要的是现在 PE 和 EV/EBITDA 的差异，正在明显扩大。 不同子行业差异尤其明显。Fabless公司差异最小，比如 NVIDIA、AMD、Broadcom。因为它们不自己建厂，折旧压力较低，因此 EV/EBITDA 往往只比 PE 低20%-40%。 但 Foundry 完全不同。比如 Taiwan Semiconductor Manufacturing Company、Samsung Electronics、Intel。这些公司 CapEx 极大，折旧极高，厂房设备生命周期极长，所以 PE 和 EV/EBITDA 差异会明显扩大。TSMC 当前常见情况大概是 PE 20-30x，而 EV/EBITDA 只有12-18x。重要的是理解很多折旧本质上其实是“增长投资”。 存储行业更加极端。Micron Technology、SK hynix 过去长期是最典型的周期行业，市场几乎不相信利润持续性。但 HBM 改变了部分逻辑，市场开始认为其中一部分利润可能是结构性利润，于是行业开始重新定价。重要的是 HBM 让市场开始重新评估存储行业的长期盈利能力。 而半导体设备公司则是另一种情况。比如 ASML、Applied Materials、Lam Research、KLA。这些公司更像“拥有工业外壳的软件公司”，因为它们毛利率高、ROIC高、FCF强、资本效率极高，所以市场已经越来越多使用 PE、EV/EBITDA、EV/FCF 和 ROIC 来定价。 真正的问题，从来不是哪个指标最好。重要的是哪个指标适合哪个子行业。 Trailing PE 适合盈利稳定的成熟公司，但周期股在景气高点 PE 会显得特别便宜，在低谷又会显得特别贵。Forward PE 更重要，因为市场买的是未来12-24个月利润。重要的是盈利预期是否还在持续上修，而不是单纯看一个低 forward PE。 PEG 对稳定高成长公司很好用，但对周期行业非常危险。很多时候 EPS 从低谷恢复，会让 PEG 看起来异常便宜。重要的是判断这个增长到底来自长期成长，还是仅仅来自周期反弹。 EV/EBITDA 更适合设备、IDM、存储这些资本结构差异大的行业。重要的是最好使用中周期 EBITDA，否则很容易在周期顶部被误导。 我个人更喜欢 FCF Yield 和 EV/FCF。重要的是这两个指标会逼着你回答一个问题：这些利润最后到底能不能变成真钱。 EV/Sales 只适合高增长、利润暂时被投入压低的平台型公司。重要的是结合毛利率、经营杠杆和长期利润率一起看。 不同子行业应该看不同指标。AI/fabless 芯片更应该看 forward PE、EV/FCF、收入增速、毛利率、客户集中度和平台护城河；半导体设备更应该看 EV/EBITDA、订单、积压和 WFE 周期；存储更应该看 P/B、EV/EBITDA、库存以及 DRAM/NAND/HBM 价格；晶圆代工和 IDM 更应该看利用率、CapEx、折旧、ROIC 和 FCF；模拟、功率和车规更应该看 FCF yield、库存周期和工业需求；EDA/IP 更应该看 EV/Sales、EV/FCF 和长期增长确定性。 所以不要只按 PE、forward PE 或 PEG 买半导体股。重要的是先分子行业，再做多指标综合。 我的框架会更简单一些。第一看质量，包括毛利率、营业利润率、ROIC、技术壁垒和客户粘性。第二看增长。重要的是增长到底来自结构性需求，还是只是周期复苏。第三看现金流，包括 FCF margin、CapEx 强度、库存变化和应收变化。第四才是估值，包括 forward PE、EV/EBITDA、EV/FCF、PEG，并与同行和自身历史区间比较。最后才是风险，包括客户集中、出口限制、库存、产能过剩和盈利预期下修风险。 半导体行业最重要的一点，是不要被低PE欺骗。重要的从来不是今天便不便宜，而是未来3-5年的现金流和竞争地位，能不能支撑今天的估值。 AI时代最大的变化，本质上也是这个。过去市场担心的是“下一轮周期会不会崩”，现在市场开始关心的是“这些利润到底是周期性的，还是结构性的”。 如果市场认为只是周期，那么 EV/EBITDA 不会给太高，PE 也不会持续扩张。如果市场开始相信 AI需求是长期的、基础设施建设是长期的、供需失衡是长期的、行业进入结构性短缺，那么整个行业的估值体系就会继续升级，从 PB → EV/EBITDA → PE → FCF 一路向上迁移。 最终获得长期高估值的公司，往往都是那些 ROIC 持续提升、资本效率持续改善、拥有长期定价权、能把AI需求持续转化为现金流的企业。

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🚨 node-ipc is compromised again. Three new malicious versions just dropped: 9.1.6, 9.2.3, and 12.0.1. Socket’s AI scanner flagged them as malware within three minutes of publication. The attack vector: a dormant maintainer account (atiertant) was likely taken over via an expired email domain. The attacker registered the lapsed domain, triggered an npm password reset, and gained publish rights to a package with millions of historical downloads. The payload is a credential stealer embedded in the CommonJS entrypoint (node-ipc.cjs). It activates on require(“node-ipc”), not through a postinstall script. Here’s what it does: •Fingerprints the host (OS, arch, hostname, uname) •Harvests 113-127 credential file patterns depending on platform (AWS, GCP, Azure, SSH keys, Kubernetes configs, npm tokens, .env files, shell histories, macOS Keychain databases, and more) •Dumps the entire process.env, capturing every CI secret and cloud credential in memory •Builds a gzip archive in a temp directory •Exfiltrates everything over DNS TXT queries to bt[.]node[.]js, using a bootstrap resolver at sh[.]azurestaticprovider[.]net:443 (a deliberate lookalike of Microsoft’s Azure Static Web Apps domain) The DNS exfiltration is chunked. A 500 KB archive generates roughly 29,400 TXT queries. The body is XOR-encrypted with a SHA-256 keystream, base64-encoded, alphabet-substituted, and split into 31-character chunks before hex-encoding into DNS labels. Header, data, and footer queries use xh, xd, and xf prefixes respectively. The malware forks a detached child process (env var __ntw=1) so credential theft runs silently in the background. It also exposes a __ntRun export, meaning any downstream code that calls require(“node-ipc”).__ntRun() can trigger a second collection/exfiltration cycle. ESM-only consumers using the import path are not affected by the reviewed package metadata. CommonJS consumers are. This is the same package involved in the 2022 protestware incident. It has a history. If you use node-ipc: •Do not install 9.1.6, 9.2.3, or 12.0.1 •Audit your lockfiles for these versions •If you loaded the CommonJS entrypoint, treat all environment variables, SSH keys, cloud credentials, npm tokens, and local secrets as compromised. Rotate immediately. •Hunt for DNS TXT queries to bt[.]node[.]js and sh[.]azurestaticprovider[.]net in your network logs •Check for temp files matching /nt-/.tar.gz Credit to Ian Ahl (@TekDefense) for first publicly identifying the expired-domain account takeover vector. Developing story. Full technical breakdown and IOCs on the Socket blog:

I'm traveling the world for a bit, starting with China but then hopping around the globe, anywhere. Open to any adventure. No plans, only a backpack. Hoping to meet & get to know humans from all walks of life. The pic is from a long hike on the Great Wall. For me, as a fan of history, this was an epic experience. In China, first I'm visiting a few big cities & talking to engineers at the heart of China's AI revolution. After that, if feeling crazy enough, I'm hitchhiking (first time) across rural China for a few weeks. Hitchhiking because I think it's the best way to meet rural folks who I would otherwise never get the chance to meet. I hope to do the same in US and other places. I have a request, if you have a travel recommendation, fill out the form(s) below if you feel like it. Or share with folks who might have advice about such travel. Form 1 - travel recommendation: If you can, recommend to me an interesting place I should visit anywhere in the world. For this, fill out form 1. Not touristy stuff, but something off the beaten path, that tourists may not know about, but is legendary. It could be as remote as meeting a herder in the mountains who is a local legend. Asia, Middle East, Europe, India, South/North America, Africa, Australia, anywhere. In China, I'm hoping to visit maybe Heibei, Shanxi, Shaanxi, Gansu, Sichuan, Yunnan, etc, so recommendations for spots to visit are helpful. Form 2 - coffee: If you want to grab a coffee with me anywhere in the world, fill out form 2 (please don't use form 1 for that). Anyway, I hectically tossed stuff in backpack. Realizing I don't have a clear plan of any kind, which is probably the only way to do it. LFG. Love you all ❤️

China says ready to work with U.S. to translate new vision of ties into actions in same direction China is ready to work with the U.S. side to translate the new vision of bilateral ties into actions in the same direction, to jointly promote the steady, sound and sustainable development of bilateral relations, Foreign Ministry Spokesperson Guo Jiakun said here on Thursday. Responding to a query at a regular press conference, Guo said Chinese President Xi Jinping held talks with U.S. President Donald Trump on Thursday morning, during which the two sides reached common understandings on the new vision of building a constructive China-U.S. relationship of strategic stability, which is expected to provide strategic guidance for bilateral relations over the next three years and beyond. Source: Xinhua News

NEWS: OpenAI hit with Class-Action Privacy Lawsuit for Sharing ChatGPT Data with Google and Meta. Sam Altman's OpenAI secretly embedded Meta’s Facebook Pixel and Google Analytics into ChatGPT, turning your most private conversations about health, finances, legal issues, and confidential company data into ad-targeting data sent straight to Meta and Google without consent. This violates federal wiretap laws. OpenAI enabled surveillance for profit.

Elon Musk was seen posing for selfies with Lei Jun, the head of Chinese tech giant Xiaomi, and Tim Cook at a state banquet for President Donald Trump in Beijing on Thursday, held as part of the U.S. president’s official visit to China. Video from the gathering captured Musk making the same playful expression in photos with both tech executives.