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2026年1月1日美股评级：推荐SMCI、INTC等复苏及AI基建标的，回避高估量子及零售股。
欢迎来到2026年。1月1日评级： 强烈买入： $TTD $SMCI $AIRO $INTC $HIMS $AXTI $TSM $NBIS $CIFR 三星电子 (KRX: 005930) $HUT $IREN $WULF $GLXY $TSSI $META $ETOR $CRCL 买入： $KRKNF $ONDS $GEMI $NVDA $MU $AMKR SK海力士 $SNAP $RDDT $AAOI $COHR $FISV $FLY $DJT $LITE $AMZN $MRVL $AVGO $OSS $BULL $ORCL $CRDO $ALAB 回避： $RGTI $QBTS $RGTI $BMNR $ETH $PLTR $WMT _ 简而言之的想法： TTD - 估值完全重置，年初至今下跌67%，叠加年底税务抛售。进入2026年是极佳的复苏标的。 SMCI - 仅因推迟一个季度以符合新Blackwell规格而交易得像一家困境公司。前瞻收入同比增长50%，市销率(P/S)接近0.5。税务收割后的极佳复苏标的。 AIRO - 资产负债表约1/6为现金。随着政府加速投资，无人机领域备受追捧。另一只被抛售的IPO新股。进入2026年，尤其在热门细分领域，是极佳的复苏标的。市销率约3.8倍，相比ONDS的25-30倍市销率，当然其教育等业务对利润率计算有很大干扰。 INTC - 它实际上已成为美国政府的半导体臂膀。超大规模云厂商很可能被激励（强烈施压）在有机会时优先使用Intel而非TSM、三星等。我不会赌美国政府会输。 HIMS - 进入2026年前大幅抛售。从70多美元下跌。销售/流量下降，但Zava收购/增长应在2026年带来巨大顺风。尤其是有数亿美元回购，前两个月是强劲的复苏标的。 AXTI - 之前发过相关论点。CEO称“40%的磷化铟(InP)供应链”，InP将是2026-2027年超大规模AI建设中的巨大瓶颈，直到2028年有足够时间通过工程手段绕过它。 TSM - 我引用过很多次。利润率提升。需求最大化。未来几年极好的复利增长者。 三星电子 - 受益于代工/存储。在所有顺风助力业务方面简直是金蛋。 NBIS - 极强买入，$7-90亿年度经常性收入(ARR)，它实际上是5家不同公司，每年三位数增长。管理层引用20-30%息税前利润(EBIT)率，这只是等待游戏。 CIFR, HUT, IREN, WULF, GLXY - 整个数据中心板块在Oracle/OpenAI担忧后极度超卖。OpenAI最近融资$400亿，$AMZN再投$100亿等。因此关于资本支出(Capex)的担忧已大幅降低风险。这也是多方面的，例如比特币下跌影响$CIFR资产负债表，$GLXY在加密领域。但总体而言，新云(neoclouds)板块有巨大的复苏/扩张潜力。 TSSI - 类似SMCI。递延收入=核弹级利空。税务收割后应恢复，且大量收入将被确认。 META - 财报后因一次性税务问题遭遇巨大算法抛售。他们还削减了现实实验室等部门的资本支出/运营支出，这应为2026年的每股收益(EPS)带来巨大顺风。 ETOR - 市值$28亿，坐拥$12亿现金，仍保持双位数同比增长。$1.5亿回购应是不错的顺风，且年初至今表现带来的税务收割效应应会消退。 CRCL - 稳定币论点在2026年应非常稳固。 买入 KRKNF - Anduril合作伙伴+规模。2026年可能转板，国防支出带来大量顺风。 ONDS - 收入增长极具爆炸性，到处都有新的$1000万合同。大量现金余额资助研发。市销率很高，但该领域的投机性领导者如RKLB有估值溢价。 GEMI - 通常我不喜欢交易所，但Gemini从$30+ IPO跌至$10以下。极佳的复苏标的。 NVDA - 巨大的积压订单。大家都知道Nvidia的牛市逻辑。 MU - 存储火热。 SK海力士 - 存储火热。 AMKR - 受益于“美国制造”芯片生产扩张。 SNAP - 存储运营支出削减，存储货币化增加收入，Perplexity贡献$4亿。季度收入$15亿。如果他们将所有这些转化为$10亿+自由现金流(FCF)/年，即使收入完全停止增长，也会完全重估Snap。 RDDT - 说实话，未来10+年不会消失。它是社交媒体界的Robinhood，通过新的收入货币化方式极速增长，且极其盈利。 AAOI - Amazon, MSFT ASIC规模化的互连标的。 COHR - 受益于下一代ASIC的光子学部署。 FISV - 财报后抛售过多，税务收割后是强劲的复苏标的。 FLY - SpaceX IPO带动太空领域火热。税务收割结束后应表现良好，且即将有Northrop的中期催化剂。 DJT - 我从没想过会把它放在这里，但这只是因为他们的TAE合并。 LITE - Google TPU部署带来巨大的物料清单(BOM)，估值有吸引力。Google TPU修正预估后轻微抛售，但它基本存在于每个超大规模ASIC部署中。 AMZN - 七大科技巨头中估值不过高的一个。 MRVL - 分析师误导导致抛售，进入2026年强烈买入。尤其是MSFT Maia收入翻倍时，Marvell当前收入也将随之增长。 AVGO - 像NVDA一样，随着AI基础设施部署加速，强劲的长期持有标的。 OSS - 我曾发帖推测他们是Anduril的供应商之一。但无论如何，边缘计算在2026年将很火热，其1.8亿市值呈现有吸引力的上行空间。 BULL - 类似Robinhood，拥有巨大用户群，但他们只需找出货币化方法。 Oracle - 我认为抛售过多。几个月前我将其列入回避，但从$330跌至$190后，尤其在OpenAI再融资$400亿后，再次具有吸引力。 CRDO - 极高利润率，数据中心部署所需的必要连接。 ALAB - 极高利润率，数据中心部署所需的必要连接。 回避： 有很多在“高估名单”上的东西，比如$RKLB，我喜欢但除了这些之外我不会说回避它们。 RGTI, QBTS, RGTI - 量子名称仍然高估，且可能在未来几年无法交付自由现金流。 BMNR, ETH - 如果你看过我的ETH帖子，我不太看多，因为每天ETH燃烧量只是个位数到低双位数，这简直是笑话。 PLTR - 最被高估的AI名称之一。 WMT - 这怎么是40倍市盈率？这是沃尔玛？ __ （这些基于今日价格） 简而言之： Circle, Etoro, AIRO, Klarna, Figma等IPO名称在下跌+税务收割后进入2026年呈现有吸引力的上行空间。 大量如SMCI, HIMS等过去3个月下跌约40%的名称，在税务收割+一月效应后是极好的波段/复苏交易标的。 许多如FiserV或The Trade Desk等暴跌的名称在税务收割后也是良好的复苏交易标的。 许多数据中心股票如nebius, iren, cifr, wulf, galaxy也是极好的复苏交易标的。 许多其他领域如存储、瓶颈、光子学等在2026年只是极好的长期持有标的，尽管各自都触及历史新高。 仍有相当多高估的名称，从量子到某些太空股票（如planet或rocketlab），特定AI名称如Palantir到零售股票如沃尔玛，我可能会暂时回避，直到有轻微回调。 这只是一个简而言之，如果我仅做短期交易（非长期），但欢迎提问。
英文原文
Welcome to 2026. Jan 1st ratings: Strong Buy: $TTD $SMCI $AIRO $INTC $HIMS $AXTI $TSM $NBIS $CIFR Samsung Electronics (KRX: 005930) $HUT $IREN $WULF $GLXY $TSSI $META $ETOR $CRCL Buy: $KRKNF $ONDS $GEMI $NVDA $MU $AMKR SK Hynix $SNAP $RDDT $AAOI $COHR $FISV $FLY $DJT $LITE $AMZN $MRVL $AVGO $OSS $BULL $ORCL $CRDO $ALAB Avoid: $RGTI $QBTS $RGTI $BMNR $ETH $PLTR $WMT _ TLDR thoughts: TTD - Complete valuation reset dropping 67% YTD, compounded by EOY tax sell-off. Great recovery play going into 2026. SMCI - Trades like distressed company just because they delayed revenue by 1 quarter for new blackwell specs. Forward revenue is increasing 50% Y/Y, P/S close to .5 now. Great recovery play from tax harvesting. AIRO - Roughly ~1/6th balance sheet was cash. Everyone seems to be into drones, especially with accelerated gov inevstments. Another IPO name that got sold off. Great recovery play going into 2026 with esp. hot segment. Roughly ~3.8x P/S compared to ONDS trading at 25-30 P/S, but obviously there's quite a lot of other businesses like their education sector which messed up margin calculations quite a bit. INTC - It's literally become the semi arm of the US government. Hyperscalers will likely be incentived (strongly pressured) to use Intel whatever chance it gets over TSM, Samsung, etc. I would not bet against the US government. HIMS - Huge selloff going into 2026. Down from $70's. Sales/Traffic is down, but Zava acquisition/growth should add a huge tailwind going into 2026. Esp. with few hundred mill buybacks, strong recovery play first two monts in. AXTI - Posted thesis on this earlier. CEO - "40% of Inp supply chain", InP will be a huge, huge bottleneck for hyperscaler AI buildout 2026-2027 until there's enough time to engineer around it in 2028. TSM - I've covered this quote a lot. Increasing margins. Maxed out demand. Just extremely good compounder next few years. Samsung Electronics - benefits from foundry/memory. just golden egg regarding all the tailwinds helping the buisness. NBIS - Extremely strong buy, $7-9B ARR, it's literally 5 different companies growing triple digits Y/Y. management quoted 20-30% EBIT margins, it's just a waiting agme. CIFR, HUT, IREN, WULF, GLXY - Whole datacenter space is extremely sold off after Oracle/OpenAI fears. OpenAI recently raised $40B, another $10B from $AMZN, and more. So a lot of fears regarding capex spend has been de-risked. It's multifaceted too, eg. Bitcoin drop, affects $CIFR balance sheet, $GLXY in crypto space. But generally huge recovery play/ramp for neoclouds sector. TSSI - Similar to SMCI. deferred revenue = nuke. Should recover after tax harvesting + lot of revenue gets recognized META - Huge algorithmic selloff post earnings due to one-time tax. They also cut capex/opex spend of their reality labs and other departments and this should be a huge tailwind for EPS going into 2026. ETOR - Literally sitting on $1.2B with a $2.8B marketcap and growing double digits Y/Y still. $150M buyback should be a nice tailwind, and tax harvesting from YTD performance should subside. CRCL - Same as stablecoin thesis should be really solid going into 2026 Buy KRKNF - Anduril partner+ scale. Probable uplisting in 2026, lot of tailwinds from defense spending. ONDS -pretty explosive revenue growth, new $10m contracts left and right. large cash balance to fund r&d. Pretty high p/s but there's valuation premiums for speculative leaders in the space like rklb. GEMI - So i typically dont like exchanges, but gemini got nuked from $30+ IPO sub $10. pretty solid recovery play. NVDA - Huge backlog lol. Everyone knows bull case for nvidia MU - Memory is hot SK Hynix - Memory is hot AMKR - benefits from "made in america" chip expansion in prod. SNAP - Opex Cut from memory, increase revenue from memory monetization, $400m from perplixity. $1.5B revenue/quarter. They could literally stop growing revenue complelty if they convert all of that to $1B+ FCF/year, it would re-rate snap completly. RDDT - This is not going anywhere for the next 10+ years tbh, it's like robinhood of social media, growing extremely fast from new ways to monetize revenue, and just extrmeely profitable. AAOI - interconnect play for amzn, msft asic scale up. COHR - benefits from photonics rollout for next gen asics. FISV - Nuked a bit too much post ER, strong recovery play esp. post tax-harves.t FLY - Space is hot from SpaceX IPO. Should do well given tax harvesting is over, and they have medium lift coming up with northrop. DJT - I never thought i'd put this here lol, but this is just because of their TAE merger. LITE - Large BOM from Google TPU rollout, attractive valuation. Slight selloff after Google TPU revised est. but it's basically in every single hyperscaler asic deployment. AMZN - one of the mag7 that's not overvalued MRVL - Selloff from analyst misinformation, strong buy going into 2026. Especially with msft maia revenue doubling Marvell's current revenue when it ramps up AVGO - Like NVDA just strong long, as AI infrastructure deployment ramps up OSS - I made a post speculating that they're one of andruils' suppliers. but regardless, edge computing will be hot 2026 and its 180m mc presents attracctive upside. BULL - similar to robinhood where they have a huge userbase, but they just need to figure out monetization Oracle - Sold off a bit too much imo. I put this on avoid months ago but after the from from $330 to $190, it's more attractive again esp. after openai raised another $40B CRDO -extremely high margin, necessary connectivity for dc rollout ALAB - extremely high margin, necessary connectivity for dc rollout Avoid: There's a lot of stuff on the "overvalued list" like $RKLB that i like but I wouldn't quite say avoid it either aside from these. RGTI , QBTS, RGTI - Quantum names are still overvalued and likely won't deliver fcf in the next few ytears. BMNR, ETH - if you saw my eth post, not exactly bullish since the amount of ETH burn is just single-low double digits every day, which is a joke. PLTR - one of the most overvalued ai names WMT - How is this 40 p/e? This is Walmart? __ (these are based on today's prices) TLDR: IPO names like Circle, Etoro, AIRO, Klarna, Figma, present attractive upsides post drop + tax harvesting going into 2026. Tons of names like SMCI, HIMS that dropped 40% or so past 3 months, are amazing swing/recovery trades post-tax harvest + Jan effect. Lot of the names that doom dropped like FiserV or The Trade Desk present good recovery trades too post-tax harvest. Many datacenter stocks like nebius, iren, cifr, wulf, galaxy, are amazing recovery trades too. Lot of other segments like memory, bottlenecks, photonics, and others are just great longs in 2026, despite each hitting ATHs. There's still quite a lot of overvalued names from Quantum, to certain Space stocks (eg. planet or rocketlab), specific AI names like Palantir to retail stocks like Walmart that I would probably avoid for the time being until there's a slight correction. This was a TLDR just if I'm short term trading-only (not long term) but feel free to ask questions.
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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!