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分析$SIVE股东结构剧变，瑞典资本撤离而美国资本接盘，控制权即将完成转移。
我之前说什么来着？$SIVE 正在经历所有权从瑞典向美国转移的过程…… 如果我正确解读了新的大股东名册（cap table）： 美国/西方现在持有 $SIVE 42.18% 的股份： ~$FNF（富达）- 11.5%（美国/西方） ~$SCHW（嘉信）- 11.4%（美国/西方） ~$IBKR - 9.25%（美国/国际） ~ 佩兴集团（纽约梅隆）- 4.15%（美国/西方） ~ 摩根士丹利 - 3.12% ~ 美林证券（$BOA）- 2.76% 欧洲：约 7.73%： 明讯银行（Clearstream Banking）- 6.16%（欧洲） 瑞士银行 - 1.57%（瑞典/欧盟） 而瑞典人现在只持有 $SIVE 约 7.49% 的股份： Avanza Pension 保险公司 - 4.76% Nordnet 人寿保险公司 - 2.73% 此前，Sivers 是一家约 60% 欧洲/瑞典散户持股的公司…… 从那以后一路下跌，接近于零，因为他们在不断抛售股份。 美国人即将获得接近绝对多数的控制权，恰在 2027 年 CPO（共封装光学）超级周期之前。 转让似乎快完成了？
英文原文
What did I say? $SIVE was undergoing a transfer of Swedish ownership over to the US... If I'm interpreting things right from the new cap table. The US / West now owns 42.18% of $SIVE: ~ $FNF (Fidelity) - 11.5% (US/West) ~ $SCHW (Schwab) - 11.4% (US/West) ~ $IBKR - 9.25% (US/International) ~ Pershing (BNY Melon) - 4.15% (US/West) ~ Morgan Stanley - 3.12% ~Merrill Lynch ( $BOA ) - 2.76% Europe: ~7.73%: Clearstream Banking - 6.16% (European) UBS Switzerland AG - 1.57% (Swedish/EU) While Swedish now hold ~7.49% of $SIVE: Försäkringsaktiebolaget Avanza Pension - 4.76% Nordnet Pensionsförsäkring AB - 2.73 Before, Sivers was a ~60% European/Swedish retail owned company... They went from that, down closer to 0 as they keep selling their shares. US has close to majority control, right before the CPO supercycle of 2027. Transfer seems almost complete?
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白银暴跌引发连锁清算，建议转向AI及高现金流标的防御。
市场正经历清算级联效应。白银的崩盘现已蔓延至加密货币及美/外股市。具体情况如下： 以下是预期走势： - $BMNR（加密货币） - $RKLB（高贝塔值） - $SNDK（AI） - 至三星（外国股票）。 “Warsh”美联储主席提名是引发抛售的初始触发因素，市场将其视为“鹰派”->量化紧缩（Quantitative Tightening）。然而，这是一个误解，因为美联储主席很可能与特朗普的政策保持一致，且由于AI因素，其近期立场偏向短期鸽派+降息。 然而，抛售的技术性原因是CME+交易所控制强制白银保证金清算。随着白银日内暴跌33%，机构被迫清算其他标的并进行对冲。因此，我们看到了： 1. 恐惧传染——当避险金属如此暴跌时，会在其他板块引发恐慌。 2. 避险情绪——投资者恐慌性抛售“风险”资产和股票/转向美元和国债。 为了进行防御性操作： - 最好将投机性标的重新配置为符合新政策的自由现金流（FCF）/盈利型多头头寸。 - 如 $GOOGL、$NVDA 跌至 $MU、$TSM、$JPM、三星等标的将受益最大。 - 从 $PYPL 到 $SNAP 等已处于低位（具有强劲预期自由现金流）且被进一步抛售的股票，呈现出不错的反弹上行空间。 尤其是鉴于美联储主席预计对从AI到银行业的许多板块持看涨态度，且由AI增长+生产力推动的降息预期强烈。 警告： - 更多不产生巨大自由现金流的投机性小盘股（从 $ONDS 到 $RKLB）可能因与高贝塔板块抛售的相关性而面临更大风险。 - 像 $BMNR 这样持有非流动性资产（例如Mr. Beast公司2亿美元）的杠杆基金，以及像 $QBTS 或 $RGTI 这样的投机性标的，可能会最终看到重置/清零。 - 像 $JD 到 $BABA 这样的外国市场标的或像 $MELI 这样的新兴市场标的可能会受到流动性流失的影响。 当然，日内交易者可能会在高贝塔标的的反弹时机上大显身手（例如，如果 $ETH 闪崩12%至$2.1K -> 恢复至$2.3K）。 话虽如此，这并不是说“卖出高贝塔”。 鉴于以太坊从$3k+跌至$2.18k，这只是对目前在高贝塔板块使用保证金的人发出的警告： 如果高贝塔股票出现持续抛售，风险相当大。（我个人将以太坊作为代理指标）。 这只是个人市场观点，但总体而言，随着中期选举临近+更多预期的降息+财报表现创历史新高（例如 $SNDK 的爆发），对市场保持极度看涨是好的。 市场在中期选举前看到绿色V型复苏只是时间问题。 基本面没有改变，但表象和短期流动性改变了。
英文原文
Markets are seeing liquidation cascades. Silver's crash is now extending into other markets like Crypto and US/Foreign stocks. Here's what's happening: And here's what to expect from: - $BMNR (Crypto) - $RKLB (High-Beta) - $SNDK (AI) - to Samsung (Foreign). The "Warsh" Fed Chair nomination was the initial trigger that caused the selloff as markets viewed him as a "Hawk" -> Quantitative Tightening. However, this is a mistake as the fed chair is likely aligned with Trump's policies, and his recent stance is dovish short term + rate cuts, due to AI. However, the technical reason for the selloff was CME + Exchange controls forcing margin liquidations on Silver. As silver crashed 33% intra-day, institutions are forced to liquidate other names and hedge. So, we're seeing both: 1. Fear Contagion - when a safe haven metal plummets this much, this causes a panic across other sectors. 2. Flight to Safety - investors panic-sell "risky" assets and stocks / move to U.S. Dollar and Treasury Bonds. To play defensive: - It's best to reposition speculative names into FCF/profit generating long positions aligning with these new policies. - Names like $GOOGL, $NVDA down to $MU, $TSM, $JPM, Samsung, and others stand to benefit the most. - Stocks that are already at lows (with strong expected FCF) from $PYPL to $SNAP that are being sold off even more present decent recovery upside. Especially since the Fed chair is expected to be bullish for many sectors from AI to Banking, with rate-cuts fueled by AI growth + productivity. For a warning: - More speculative small cap names (that don't generate massive FCF) from $ONDS to $RKLB may be more at risk due to correlation to high-beta sector selloffs. - Leveraged funds like $BMNR with iliquid assets (eg. $200M in Mr. Beast's company) to speculative names like $QBTS or $RGTI may finally see a reset/wipeout. - Foreign market names like $JD to $BABA or emerging market names like $MELI may be impacted from a liquidity drain. But of course, day-traders may have a field day timing rebounds on high-beta names (eg. if $ETH flash crashes 12% to $2.1K -> recovery to $2.3K). That being said this is not saying "Sell High-Beta". This is just a warning to people with margin on high-beta sectors now that given Ethereum's flush from $3k+ down to $2.18k: There's considerable risk if there's an extended selloff on high-beta stocks. (I've been personally looking at Ethereum as a proxy). This is just personal market opinion, but generally as midterms come up + more expected rate cuts + earnings coming out higher than ever (eg. $SNDK's blowout), it's good to remain extremely bullish on the market. And it's just a matter of time before markets see a green V recovery before midterms. Fundamentals haven't changed but optics have and short-term liquidity have.
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解析新任美联储主席 Warsh 政策对 AI、金属、加密及全球股市的差异化影响。
Kevin Warsh 是下一任美联储主席。 市场可能会误以为他是一只“鹰派”。 但他 2026 年的实际立场是微妙的。 以下是他的政策及其对市场的影响： 1. AI/半导体（$NVDA, $MU）：极度看涨 2. 金属（白银、黄金）：极度看跌 3. 加密货币（$BTC, $CRCL）：悖论式看涨 4. 银行与金融（$JPM, $BOA）：看涨 5. 住房与房地产：混合/不确定 6. 可再生能源：看跌 7. 小盘股（$RUT）：看涨 8. 外国股票（日本、韩国）：具有韧性 - 新兴市场（EM）：极度看跌 - 中国与香港：看跌 - 欧洲（$VGK, $EZU）：谨慎 1. AI/半导体（从 Nvidia 到 Micron）：极度看涨 Warsh 是 AI 多头。 在 2025 年底，他认为 AI 是一种强大的抗通胀力量。他相信 AI 驱动的生产力提升将使经济在不会引发通胀的情况下快速增长。 这种“生产力繁荣”为他提供了智力上的“掩护”，即使经济保持强劲，他也支持降息。（《美联储破碎的领导层》，2025 年 11 月 16 日《华尔街日报》） 这与他早期立场大相径庭，当时市场预计他会是僵化的通胀鹰派（希望利率更高的人）。 他倡导降息并希望加速 AI 发展。 2. 金属（白银、黄金）：极度看跌 投资者使用黄金作为对冲弱势美元和“印钞”的工具。因为 Warsh 希望缩减资产负债表并关闭“印钞机”，持有黄金的主要理由正在减弱。强势美元使得金属对国际买家来说更昂贵。 话虽如此，白银日内 33% 的下跌主要是由其他因素造成的，例如保证金变动引发的连锁清算，尽管新任美联储主席可能起到了次要作用。 3. 加密货币（$BTC, $CRCL）：悖论式看涨 他曾著名地表示：“如果你不到 40 岁，比特币就是你的新黄金。”他将比特币视为合法的价值储存手段，并认为这是从实物金属向代际转变。 他将区块链视为“最新、最酷的软件”，并相信美国必须在此领域保持领先，以在全球竞争中保持经济竞争力。 然而；“悖论”：为何价格下跌： 市场意识到，虽然 Warsh 希望降低利率，但他也希望美联储资产负债表更小。 投资者害怕我们进入“降息但不量化宽松（QE）”的时代。你可能会得到更便宜的贷款，但不会得到通常将 $BTC 推向历史新高的巨大“资金墙”。 所以我们有一个人对加密货币技术看涨，但他的货币纪律可能会损害短期流动性。 4. 银行与金融：看涨 由于他在摩根士丹利的经历以及对“使命蔓延”的直言不讳的批评，Warsh 是银行业界的宠儿。预计他将回滚复杂的银行资本要求（如巴塞尔协议 III）。分析师认为这对区域性和小盘银行是一个重大利好，因为它释放了用于贷款的资本。 5. 住房与房地产：混合 他希望激进地降低联邦基金利率。这将立即降低可调利率抵押贷款（ARMs）和建筑贷款的成本。 然而，看跌的情况是 Warsh 强烈反对美联储持有 2 万亿美元的抵押贷款支持证券（MBS）。许多经济学家警告，这可能会推高 30 年期固定抵押贷款利率（可能升至 7% 或 8%），即使美联储正在降低其他利率。 6. 可再生能源：看跌 他打算让美联储退出全球气候团体（如绿色金融系统网络）并结束银行的“气候压力测试”。 在杰罗姆·鲍威尔任内，美联储鼓励银行在贷款中考虑气候风险。Warsh 希望结束这种做法，这实际上消除了使绿色项目更容易从主要银行获得优惠贷款条款的“监管推动”。 7. 小盘股 Warsh 明确表示，他希望美联储关注经济的“真正驱动力”，即中小企业和企业家，而不是华尔街的“娇生惯养的王子”。 预计 Warsh 将领导大幅回滚复杂的银行资本要求。这对小盘股强烈看涨。他打算通过减轻从事大多数小企业贷款的小型和区域性银行的监管负担，扩大小企业获得资本的途径。 8. 外国股票 预计 Warsh 将在受益于强劲美国经济和易受强势美元及全球流动性收紧影响的国家之间造成分裂。 日本/韩国（三星、SK 海力士等）：日本和韩国“没问题”，因为它们拥有 Kevin Warsh 认为将拯救美国经济的 AI 和机器人交易的物理瓶颈。 通常，强势美元对外国股票不利，但对于日本和韩国来说，这是一种竞争武器： - 出口提振：由于他们的大多数 AI 和机器人合同以美元计价，强势美元意味着他们的收入（换算回日元等）大幅膨胀。 - 对美国更便宜：Warsh 的“强势美元”政策使得日本机器人和韩国芯片对美国公司来说更便宜。这加速了 Warsh 想要的“生产力繁荣”，同时增加了这些外国科技巨头的利润。 中国：强势美元给人民币带来压力，使中国人民银行（中国央行）更难降息以刺激其 struggling 的经济。 新兴市场：强势美元使得新兴国家偿还美元计价债务的成本更高。 欧洲：美元复苏可能会压低欧元，这有助于欧洲出口，但增加了其能源进口成本。 _ 周五，随着白银/黄金暴跌，市场大幅抛售，对冲操作抽走了系统中的流动性。 市场可能会将 Warsh 误认为是历史上的鹰派。 然而，最近的声明显示他短期内偏向鸽派，并支持由 AI 加速的降息。 市场目前正在定价同时降息和缩减资产负债表的可能性，但总体而言，预计从 AI 到小盘成长的许多交易将继续进行。
英文原文
Kevin Warsh is the next Federal Reserve Chair. Markets may confuse him as a "Hawk". His actual stance in 2026 is nuanced. Here's his policies and how they affect the markets: 1. AI/Semis ( $NVDA, $MU): Extremely Bullish 2. Metals (Silver, Gold): Extreme Bearish 3. Crypto ( $BTC, $CRCL ): Paradoxically bullish 4. Banking & Financials ( $JPM, $BOA ): Bullish 5. Housing & Real Estate: Mixed/Uncertain 6. Renewable Energy: Bearish 7. Small-Caps ( $RUT ) : Bullish 8. Foreign Stocks (Japan, Korea): Resilient - Emerging Markets (EM): Extremely Bearish - China & Hong Kong: Bearish - Europe ( $VGK, $EZU): Cautious 1. AI/Semis ( Nvidia to Micron ): Extremely Bullish Warsh is an AI Bull. In late 2025, he argued that AI is a powerful dis-inflationary force. He believes AI-driven productivity gains will allow the economy to grow rapidly without triggering inflation. This "productivity boom" gives him the intellectual "cover" to support rate cuts even if the economy remains strong. (The Federal Reserve’s Broken Leadership, November 16, 2025 WSJ) This is much different than his earlier stances where markets expected him to be a rigid inflation hawk (someone who wants higher rates). He is advocating for cuts and wants to accelerate AI development. 2. Metals (Silver, Gold): Extreme Bearish Investors use gold as a hedge against a weak dollar and "money printing." Because Warsh wants to shrink the balance sheet and turn off the "printing press," the primary reason for holding gold is diminishing. A stronger U.S. Dollar is making metals more expensive for international buyers. That being said the 33% intraday silver drop was mainly from other factors such as cascading liqudation from margin changes, though the new Fed chair likely played a minor role. 3. Crypto ( $BTC, $CRCL ): Paradoxically bullish He famously stated, "If you're under 40, Bitcoin is your new gold." He views Bitcoin as a legitimate store of value and a generational shift away from physical metals. He views the blockchain as "the newest and coolest software" and believes the U.S. must lead in this space to remain economically competitive against global rivals. However; The "Paradox": Why Prices are Dropping: The market is realizing that while Warsh wants lower interest rates, he also wants a smaller Fed balance sheet. Investors are terrified that we are entering an era of "Rate Cuts without QE." You might get cheaper loans, but you won't get the massive "wall of money" that usually sends $BTC to all-time highs. So we have a guy bullish on the technology of crypto, but his monetary discipline might hurt short-term liquidity. 4. Banking & Financials: Bullish Warsh is a favorite of the banking sector due to his experience at Morgan Stanley and his vocal criticism of "mission creep." He is expected to roll back complex bank capital requirements (like Basel III). Analysts see this as a major win for regional and small-cap banks, as it frees up capital for lending. 5. Housing & Real Estate: Mixed He wants to cut the Federal Funds Rate aggressively. This would immediately lower the cost of Adjustable-Rate Mortgages (ARMs) and construction loans. However, the bear case is that Warsh is a fierce opponent of the Fed owning $2 trillion in Mortgage-Backed Securities (MBS). Many economists warn this could push the 30-year fixed mortgage rate higher (potentially toward 7% or 8%) even as the Fed is cutting other interest rates. 6. Renewable Energy: Bearish He intends to withdraw the Fed from global climate groups (like the Network for Greening the Financial System) and end "climate stress tests" for banks. Under Jerome Powell, the Fed encouraged banks to consider climate risks in their lending. Warsh wants to end this, which effectively removes the "regulatory nudge" that made it easier for green projects to get favorable loan terms from major banks. 7. Small-Caps Warsh has explicitly stated that he wants the Federal Reserve to focus on the "true drivers of the economy", small businesses and entrepreneurs, rather than just the "pampered princes" of Wall Street. Warsh is expected to lead a significant rollback of complex banking capital requirements. This is strongly bullish for small caps. He intends to broaden access to capital for small firms by reducing the regulatory burden on the small and regional banks that do the majority of small-business lending. 8. Foreign Stocks Warsh is expected to createa a divide between countries that benefit from a strong U.S. economy and those that are vulnerable to a stronger U.S. Dollar and tighter global liquidity. Japan/Korea (Samsung, SK Hynix, etc): Japan and Korea are "fine" because they own the physical bottlenecks of the AI and robotics trades that Kevin Warsh believes will save the U.S. economy. Usually, a strong USD is bad for foreign stocks, but for Japan and Korea, it’s a competitive weapon: - Export Boost: Since most of their AI and robotics contracts are priced in USD, a stronger dollar means their revenue (when converted back to Yen, etc.) is massively inflated. - Cheaper for the U.S.: Warsh’s "Strong Dollar" policy makes Japanese robots and Korean chips cheaper for American companies to buy. This accelerates the "Productivity Boom" Warsh wants while padding the profits of these foreign tech giants. China: A stronger dollar puts pressure on the Yuan, making it harder for the PBoC (China's central bank) to cut their own rates to stimulate their struggling economy. Emerging Markets: A stronger U.S. Dollar makes it much more expensive for emerging countries to service their dollar-denominated debt. Europe: Dollar recovery could push the Euro lower, which helps European exports but increases their energy import costs. _ On Friday, markets sold off sharply on Silver/Gold crashing, and hedging pulled liquidity out of the system. Markets might confuse Warsh as a historical hawk. However, recent statements show he's near term dovish and supports lower rates, accelerated by AI. Markets are currently pricing in the possibility of simultaneous rate cuts and balance sheet reductions but generally, many trades from AI to small cap growth are expected to continue.
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2026年十大主题投资：聚焦AI供应链瓶颈、软体机器人及支付颠覆。
2026年通讯。 主题投资：演进、颠覆与瓶颈 1. 软体机器人 - 向 $TSLA、$ONDS、波士顿动力演进。 2. 硅光子(SiPh) - 磷化铟(InP)瓶颈 | $AXTI、$LITE、$GOOGL 3. 玻璃基板 - 瓶颈 | $NVDA、$INTC、$TSM 4. 资金流动 - 对 $V、Stripe、$BOA 的颠覆 5. AI云层级 - 瓶颈 | $NBIS、$IREN、$HUT 6. LLM网络安全 - 向 $CRWD、$CSCO、$MSFT 演进 7. 低轨(LEO)太空基础设施 | 向 $RKLB、SpaceX、$ASTS 演进 8. 消费者代理工作流(50步) - 对消费者劳动力的颠覆，来自Manus、$PATH Cognition 9. 分布式计算延迟 - 瓶颈 | $TSLA、$AMZN、$GOOGL 10. 铜互连寿命延长 - 瓶颈 | $NVDA (LPU/Groq)、$AMD、$INTC _这是我对从公开信息综合及瓶颈二/三阶效应来看最感兴趣的主题投资的简要概述！_ 1. 软体机器人：向机器人的演进 传统机器人（Optimus、波士顿动力）依赖逆运动学控制刚性关节。软体机器人改变了数学模型。 我们已到达硬件（Optimus、波士顿动力、Figure）与LLM（Gemini、Grok、Opus）相遇的节点，正处于大规模商业化的开端。 通过使用受章鱼触手和人类皮肤启发的材料，机器人正从齿轮转向流体性，以处理极其精细的任务，如像人手一样处理农产品，或为 $ONDS/Andruil 无人机添加类章鱼延伸以拾取极重表面。 这种演进在于跳出思维定势思考机器人能做什么。我记得7年前曾与该领域的斯坦福博士合作，AI在多年研究后开始商业化，因此该领域也是如此。 将类生物流体性添加到刚性机器人中的可能性是无限的，这只是自然演进。 大多数可能是私人公司。 2. 硅光子 - AI基础设施的瓶颈“磷化铟(InP)卡脖子点” 从Blackwell Ultra集群到Google TPU已触及上限，需要光子互连 | 共封装光学(OCS)以实现扩展。 基板：$AXTI（通过Tongmei）和住友（日本）控制全球约60-70%的InP基板市场。 材料：Vital Materials（中国）和AXT等公司控制原材料铟本身的精炼（78%+的供应链）。 如果你是美国科技巨头，你2026年的整个“AI增长故事”取决于由地缘政治对手控制的材料。 唯一可扩展的解决方案是工程绕行，要么实现芯片上光传输，同时减少90%的铟使用，要么使用微小的磷化铟薄片代替大型昂贵晶圆。 瓶颈本身有机会，如AXT、住友。或帮助解决它的公司如 $POET。 3. 玻璃基板 - 解决从 $NVDA 到其他公司的共封装光学(CPO)瓶颈 向玻璃基板的转变本质上是半导体行业对当前材料物理极限的回答。 当前芯片位于有机材料（本质上是专用塑料）制成的基板上。随着芯片变大，如Nvidia巨大的GPU封装，塑料基板会翘曲。 因此，玻璃基板正成为共封装光学(CPO)的行业标准，因为它们解决了光子学中最大的对齐问题。 美国政府已视其为必要，我们看到巨额补贴流向这些公司。 $INTC、三星电子、Absolics（SKC子公司）、DNP等是主要受益者，尤其是随着MRVL和 $AVGO（推动光学开关的玻璃）推进CPO革命。 4. 资金流动 - 对卡网络、银行、交易所和支付的颠覆 几十年来，资金转移一直是“收费公路”业务。每次刷卡，2%到3%的钱流入卡网络（Visa/Mastercard）和发卡行的口袋。 或者从交易所买卖加密货币是0.2-1%。这是历史上最有利可图、“不可杀死”的商业模式。 直到现在。2025年的“天才法案”刚刚将金钱传输许可证或银行特许状交给像 $XRP 这样的公司，赋予了他们王国钥匙。 对我来说并非理论。我恰好正在自己的初创公司与创建V / $PYPL 实时支付网络的人一起从事这项工作。 但基本上，拥有现有MTL或追求银行特许状并利用天才法案及其他技术的公司，现在可以通过在美联储和区块链之上进行结算来绕过传统百分比费用，有效地将基于百分比的费用转化为几美分。 99%的公司会这样做吗？可能不会，因为支付行业的所有利润率都将归零。但我乐意看到。 但基本上，Stripe以11亿美元收购Bridge本应是对现有公司的红色警报，表明1天ACH、 interchange模式、25美元国际转账的日子即将结束。 这扩展到许多其他相邻领域，从低费用颠覆者如 $HOOD、Mercury，一直到稳定币新银行，或制作自己稳定币的公司如 $SOFI。 5. AI云层级 - 超大规模计算瓶颈的解决方案 当超大规模云厂商被困在3-5年的电网互连队列中时，像WULF和IREN这样的矿工今天就拥有即插即用的GW级算力。 这是千载难逢的机会，超大规模云厂商将其现金牛云收入流向小公司。 这里有不同的层级，从Fluidstack、Poolside、Fireworks在GPU编排层，到IREN等公司构建的裸金属层。 然后有成为超大规模云厂商本身，如NBIS拥有物理位置、GPU、软件编排，然后为推理提供简单接口。 这是少数小公司在未来一两年成为AWS或Azure，或被收购（例如GOOGL以47亿美元收购Intersect）的机会。 像NBIS、IREN、CRWV这样的新云，以及像CIFR、WULF、HUT这样的colo玩家（以及私人部门->能源）将受益。 6. LLM网络安全 - 向现代安全和漏洞防御的演进 最近的报告（例如来自Anthropic红队）显示，高级模型如Opus（及未来版本）可以自主扫描开源智能合约，并在几分钟内识别价值数百万美元的“零日”漏洞。 含义：如果AI能在不可变的区块链合约中找到逻辑缺陷，它也能在银行的SWIFT API或电网控制软件中找到缺陷。 同样适用于KYC/AML。像Gemini Nano Banana这样的模型能够创建逼真的图像/视频，人们能够绕过许多程序。 这个领域有很多不性感但具Alpha潜力的事情，如LLM自动化SOC2/PCI DSS合规，代理坐在服务器上，持续监控日志，并自动生成审计所需的证据。 7. 低轨(LEO)太空基础设施 | 向拓展最后疆域的演进 太空是下一个大事情。这并不新鲜。（希望你懂这个笑话）。但从像 $RKLB、SpaceX这样的公司，到解决轨道拥堵或发射节奏瓶颈的公司，再到像ASTS或Starlink这样商业化基础设施的公司，在未来一年呈现许多机会。 因此，像Impulse、Blue Origin、$ASOZF到RKLB、$ASTS这样的公司将受益于整个链条。 8. 消费者代理工作流(50步) - 对消费者劳动力的颠覆，来自Manus、PATH Cognition 这一点很简单，无需解释。但在对就业+成本节约的潜在影响上显而易见。 你如何自动化商务拓展？如何自动化营销？如何自动化软件工程师？ 这超越了ChatGPT的几步回答，直接进入现实世界，AI代理可以在X上漫游，找到合适的人，发送DM，继续对话，并在一个工作流中导致销售电话。 这是“聊天机器人”时代的结束和“行动”时代的开始，取代公司以前需要的所有人。 我尚未看到任何公司大规模做到这一点。拥有这些的公共公司如META并没有呈现最佳敞口。也许是 $PATH 在公共空间。 9. 分布式计算延迟 - 解决AI计算容量紧张的瓶颈 像GOOGL Cloud、MSFT Azure这样的超大规模云厂商已达最大容量。 Elon Musk已经提出分布式计算作为解决此问题的未来（例如，拥有 $TSLA 网络为LLM推理提供计算）。 “Tesla计算云”论点很迷人，但我识别出的最大物理障碍是：推理延迟。 要生成“Token B”，模型必须先生成“Token A”。它不能同时做两者。如果你将一个巨大模型（如Grok-3）拆分到5辆不同的汽车中以适应内存，你必须为每个生成的Token在这些汽车之间发送数据。 因此，如果汽车之间的网络延迟甚至是20ms（5G的乐观估计），而你生成50个Token，你刚刚在计算时间之上添加了1秒的纯“等待时间”（延迟）。在使用NVLink的数据中心中，该等待时间以纳秒计。 同样适用于零售用户拥有的任何备用计算机、GPU等。有数十亿消费级GPU（Teslas、iPhones、游戏PC）90%的时间闲置。 解决推理的“分布式延迟”问题呈现了计算史上最大的套利机会之一。 尚未看到任何公司大规模完成此任务。也许NVIDIA Dynamo、$AKAM、TSLA正在接近。 10. 铜互连寿命延长 - 解决Nvidia和其他公司的瓶颈 既然我们不能拥有无限的InP，我们必须用现有的东西（例如铜）进行工程绕行，所以铜电缆可以做物理上说它不应该做的事，如在不损失信号的情况下跨机架传输224G信号。 行业在InP上遇到了硬性停止，美国在物理上无法开采和精炼足够的InP将数据中心中的每个链接变成光纤。 如果有任何帮助，那就是好事。例如，NVDA对Groq团队和IP的200亿美元“收购雇佣”。LPU更多是关于推理延迟/架构，但它作为副产品解决了铜寿命延长。Groq的整个架构在延迟上击败了Nvidia，因为它拒绝了光学。Groq使用“确定性”网格，依赖芯片之间的直接电气（铜）连接，避免光学开关的“抖动”和转换时间。 像 $ALAB、$CRDO、Groq，或任何能找到用铜绕过光学瓶颈方法的公司将是赢家。 _这里有从私人部门投资到公共部门的众多交易！只是今天即兴写下了我的想法，但乐意稍后详细阐述。 无论如何，我相信这些主题投资中的许多： 从投资InQ瓶颈绕行（$POET）或瓶颈本身（$AXTI）到公共部门的颠覆者（$CRCL）。 到投资铜扩展瓶颈修复（Groq）、银行特许状颠覆者（Mercury）到私人部门的演进公司（Lightmatter、Festo）。 在2026年呈现不对称上行空间。 新年快乐！
英文原文
2026 Newsletter. Thematic Investments: Evolution, Disruption, and Bottlenecks 1. Soft Robotics - Evolution to $TSLA, $ONDS, Boston Dynamics. 2. SiPh - InP Bottleneck | $AXTI, $LITE, $GOOGL 3. Glass Substrates - Bottleneck | $NVDA, $INTC, $TSM 4. Money Movement - Disruption to $V, Stripe, $BOA 5. AI Cloud Layers - Bottleneck | $NBIS, $IREN, $HUT. 6. LLM Cybersecuirty - Evolution to $CRWD, $CSCO, $MSFT 7. LEO Space Infrastructure | Evolution to $RKLB, SpaceX, $ASTS 8. Consumer Agentic Workflows (50 Step) - Disruption to the Consumer Workforce, from Manus, $PATH Cognition 9. Distributed Computing Latency - Bottleneck | $TSLA, $AMZN, $GOOGL, 10. Copper Interconnect Life Extension - Bottleneck | $NVDA (LPU/Groq), $AMD, $INTC _ This is an light overview of thematic investments I find the most interesting from a public-information synthesis perspective + second/third-order effects from bottlenecks! _ 1. Soft Robotics: The Evolution to Robotics Traditional robotics (Optimus, Boston Dynamics) relies on Inverse Kinematics to rigid joints. Soft robotics changes the math. We've met the point where hardware (Optimus, Boston Dynamics, Figure) met LLMs (Gemini, Grok, Opus), and we're at the beginning of possible widespread commercialization. By using materials inspired by octopus tentacles and human skin, robots are moving away from gears and toward fluidity to handle extremely delicate tasks like handling produce like the human hand, to picking up extremely heavy surfaces adding Octopus-like extensions to $ONDS/Andruil Drones. The evolution is thinking outside the box in terms of what robotics can do. I remember working with some Stanford PHds in this field like 7 years ago, and it just so happens AI is starting to be commercialized after many years of research. So expected, this field to be as well. Possibilities are limitless adding organism-like fluidity to rigid robotics, this is just the natural evolution. Most of these are prob private companies. _ 2. Silicon Photonics - Bottleneck of the AI Infrastructure "InP Chokepoint" Blackwell Ultra Clusters to Google TPUs have hit the upper wall and requires photonics for interconnects | OCS to scale up. The Substrates: $AXTI (via Tongmei) and Sumitomo (Japan) control roughly 60-70% of the world's InP substrate market. The Materials: Companies like Vital Materials (China) and AXT control the refining of the raw Indium itself (78%+ of supply chain). If you are a US tech giant, your entire "AI Growth Story" for 2026 depends on materials controlled by geopolitical rivals. The only scalable solution is engineering around it, either by delivering light-on-chip, while using 90% less InP or companies that use tiny slivers of Indium Phosphide instead of large, expensive wafers. There's opportunities with the bottleneck itself like AXT, Sumitomo. Or companies that help address it like $POET. _ 3. Glass Substrates - Fixing the Bottleneck for CPOs from $NVDA to others. The shift toward glass substrates is essentially the semiconductor industry’s answer to a physical wall they are hitting with current materials. Current chips sit on a substrate made of organic materials (essentially specialized plastic). As chips get larger, like Nvidia's massive GPU packages, plastic substrates warps. So, glass substrates is becoming the industry standard for Co-Packaged Optics (CPO) because they solve the single biggest problem in photonics with alignment. US Government already sees this as a necessity and we've seen huge subsidies funneling down to some of these companies. Companies like $INTC, Samsung Electronics, Absolics (SKC Subsidiary), DNP, and others are the main beneficiaries, especially as MRVL and $AVGO (driving glass for optical switches) move forward with CPO revolution. _ 4. Money Movement - The Disruption to Card Networks, Banking, Exchange, and Payments For decades, moving money has been a "toll road" business. Every time you swiped a card, 2% to 3% of that money vanished into the pockets of the Card Networks (Visa/Mastercard) and Issuing Banks. Or buying/selling crypto from an exchange would be .2-1%. It was the most profitable, "un-killable" business model in history. Until now. The "Genius Act" of 2025 just handed companies like $XRP with Money Transmitter Licenses or Banking Charters the keys to the kingdom. Not really theoretical for me. I happen to be working on this myself at my own startup with some folks who created V / $PYPL's real-time payment networks. But basically companies with existing MTLs or pursuing banking charters leveraging the Genius Act and some other tech can now bypass legacy % fees by doing settlement on top of the Federal Reserve and blockchains, effectively converting percentage-based fees into a few cents. Would 99% companies do it? Probably not since every single margin from across the payment industry would just go to 0. I'd be happy though. But basically Bridge's $1.1B acquisition by Stripe should have been a red-alarm to existing companies that days of 1-Day ACH, interchange models, $25 international transfers, are soon to be over. This extends to many other adjacents from low fee disruptions like $HOOD, Mercury all the way to Stablecoin Neobanks, or companies making their own stablecoins like $SOFI. _ 5. AI Cloud Layers - The Solution to HyperScaler compute Bottleneck While Hyperscalers are stuck in 3-5 year grid interconnection queues, miners like WULF and IREN are sitting on plug-ready GWs today This is the opportunity of a lifetime as hyperscaler funnel their cash cow Cloud revenues down to tiny companies. There's many different layers to this from Fluidstack, Poolside, Fireworks on the GPU orchestration layer, to the bare metal layer that companies like IREN are building. Then there's becoming the hyperscaler themselves like NBIS owning the physical locations, the GPU, software orchestration, and then providing simple interfaces for inference. This is the opportunity for a few small companies to become Amazon Web Service or Microsoft Azure over the next year or two, or get acquired (eg. GOOGL buying Intersect for $4.7B) Neoclouds like NBIS, IREN, CRWV, down to colo plays like CIFR, WULF, HUT (and private sectors -> Energy) stand to benefit. _ 6. LLM Cybersecurity - The Evolution to Modern Security and Vulnerability Defense Recent reports (e.g., from Anthropic's Red Team) showed that advanced models like Opus (and future iterations) could autonomously scan open-source smart contracts and identify "Zero-Day" exploits worth millions of dollars in minutes. The Implication: If an AI can find a logic flaw in a immutable Blockchain contract, it can find a flaw in a bank's SWIFT API or a power grid's control software. Same with KYC/AML. Models like Gemini Nano Banana are able to create realistic images/videos of people and people are able to get past a lot of programs. There's tons of things as an unsexy alpha in this field like LLMs automating away SOC2/PCI dss compliance to agents sitting on a server, continuously monitor logs, and auto-generate the evidence needed for auditors. 7. LEO Space Infrastructure | The Evolution to Expanding into the final frontier. Space is the next big thing. This is not anything new. (hope you got the joke). But anywhere from companies like $RKLB, SpaceX. Companies that fix orbital congestion or launch cadence bottlenecks. To companies that commercialize the infrastructure like ASTS or Starlink present many opportunities over the next year. So companies like Impulse, Blue Origin, $ASOZF to RKLB, $ASTS stand to benefit across the entire chain. 8. Consumer Agentic Workflows (50 Step) - Disruption to the Consumer Workforce, from Manus, PATH Cognition This one is simple and needs no explanation. But largely obvious in potential impact on employment + cost saving. How do you automate away business development? How do you automate away marketing? How do you automate away software engineers? This is going past few step ChatGPT answers and directly in to the real world where an AI agent can roam X, find the right people, DM someone, continue conversations, and lead to a sales call in just one workflow. This is the end of the "Chatbot" era and the beginning of the "Action" era replacing everyone previously required in a company. I haven't quite seen this done at scale yet with any company. Public companies like META that own these, don't really present the best exposure. Maybe $PATH for public space. 9. Distributed Computing Latency - Fixing the Bottleneck for AI Compute Capacity Strains Hyperscalers like GOOGL Cloud, MSFT Azure at max capacity. Elon Musk already floated distributed computing as the future of solving this issue (eg. having networks of $TSLA's providing compute for LLMs for inference). The "Tesla Compute Cloud" thesis is fascinating, but the single biggest physical barrier I've identified is: Inference Latency. Too generate "Token B," the model must first finish generating "Token A." It cannot do both at the same time. If you split a massive model (like Grok-3) across 5 different cars to fit it in memory, you have to send data between those cars for every single token generated. So, if your network latency between cars is even 20ms (optimistic for 5G), and you are generating 50 tokens, you just added 1 full second of pure "waiting time" (latency) on top of the compute time. In a data center using NVLink, that wait time is measured in nanoseconds. Same applies to any spare computer, GPU, and others owned by retail users. And there's billions of consumer GPUs (Teslas, iPhones, Gaming PCs) that sit idle 90% of the time. Solving the "distributed latency" problem for inference presents one of the single greatest arbitrage opportunity in the history of computing. Haven't really seen any companies that accomplished this at scale yet. Maybe NVIDIA Dynamo, $AKAM, TSLA, getting a little closer. 10. Copper Interconnect Life Extension - Addressing the Bottlenecks of Nvidia and Others Since we can't have infinite InP, we have to engineer around it with what we have (eg. Copper), so copper cables can do things that physics said it shouldnt like carrying 224G signals across a rack without signal loss. The industry is hitting a hard stop on InP where, US cannot physically cannot mine and refine enough InP to turn every link in a data center into fiber optics. If anything helps, then it's good. EG. NVDA's $20B "Acqui-hire" of Groq's team and IP. LPU is more about inference latency/architecture but it addresses copper life extension as a byproduct. Groq’s entire architecture beat Nvidia on latency because it rejected optics. Groq uses a "deterministic" mesh that relies on direct electrical (copper) connections between chips, avoiding the "jitter" and conversion time of optical switches. Companies like $ALAB, $CRDO, Groq, or anyone who can find ways to engineer around the optical bottleneck with copper will be a winner. _ There are tons of trades from both private sector investments to public! Just wrote up my thoughts on the fly today, but happy to elaborate later. Regardless I believe a lot of these thematic investments from: Investing in InQ Bottleneck Workarounds ( $POET ) or the bottleneck itself ( $AXTI ) to Disruptors ( $CRCL ) in the public sector. To Investing in copper extension bottleneck fixes (Groq), bank charter disruptors (Mercury) to evolutionary companies (Lightmatter, Festo) in the private sector. Present asymmetrical upside in 2026. Happy New Year!