Melvin

Total wafer fab equipment spending is projected to reach $145 billion in 2026, $200 billion in 2027 and $250 billion in 2028, a near doubling in three years driven almost entirely by HBM and advanced logic demand (Save this). And this image above shows exactly who collects a toll on every single chip that gets built. Before any HBM chip can exist, you need an ultra pure silicon wafer to build it on. Shin-Etsu Chemical and Siltronic are the dominant global silicon wafer suppliers, with Shin-Etsu controlling roughly 30% of global supply, one of the quietest monopolies in all of semiconductors. The most technically complex step is the TSV process drilling microscopic vertical holes through each silicon die so electrical signals can travel between stacked layers. Tokyo Electron (TEL), Applied Materials (AMAT), KLA Corporation (KLAC), and Lam Research (LRCX) dominate this step,and all four beat earnings, raised guidance, and reported sold out capacity simultaneously in the most recent cycle, an extraordinarily rare alignment that signals just how tight the HBM supply chain truly is. Applied Materials leads in deposition tools, Lam Research controls roughly 50% of the global etch market, and KLA holds a near monopoly at 55% share in process control and inspection, every wafer must pass through KLA's equipment to confirm chip integrity before moving forward. The TSV etching process also requires specialized industrial gases, C4F8 and SF6 that create the precise chemical reactions needed to carve through silicon without damaging surrounding material. Linde, Air Liquide, SK Materials, and Merck supply these gases and none of them are substitutable within current production timelines making them some of the most overlooked AI infrastructure plays in the market. Once the dies are prepared, they need to be stacked and bonded together, currently via Thermal Compression Bonding, but the industry is shifting toward Hybrid Bonding for HBM4 and beyond. Besi, ASMPT, Hanmi Semiconductor, and Kulicke & Soffa dominate the bonding equipment market, and the hybrid bonder market alone is projected to reach nearly $2 billion by 2028 as every memory maker upgrades to the next-generation process. After stacking, chips need to be thinned, cut and polished through grinding, dicing, and CMP processes where DISCO Corporation holds near-monopoly control in precision dicing equipment, with DuPont, Dow, CMC Materials, and Resonac supplying the CMP slurry chemicals needed to polish chips to atomic smoothness. All of this feeds into just three companies that actually build and sell HBM, SK Hynix with over 50% global market share, Micron ramping HBM4 for Nvidia's Rubin platform and Samsung fighting to regain ground after falling behind on qualification timelines. And at the very bottom of the supply chain sits the demand engine, every hyperscaler and chip designer whose AI accelerators require HBM to function, Nvidia, AMD, Broadcom, Google, Microsoft, Meta, AWS, Marvell, and Tesla. Every company in this supply chain is a toll booth and the traffic is only getting heavier. Make sure to follow me @MelvinInvests for more semiconductor opportunities.

Total wafer fab equipment spending is projected to reach $145 billion in 2026, $200 billion in 2027 and $250 billion in 2028, a near doubling in three years driven almost entirely by HBM and advanced logic demand (Save this). And this image above shows exactly who collects a toll on every single chip that gets built. Before any HBM chip can exist, you need an ultra pure silicon wafer to build it on. Shin-Etsu Chemical and Siltronic are the dominant global silicon wafer suppliers, with Shin-Etsu controlling roughly 30% of global supply, one of the quietest monopolies in all of semiconductors. The most technically complex step is the TSV process drilling microscopic vertical holes through each silicon die so electrical signals can travel between stacked layers. Tokyo Electron (TEL), Applied Materials (AMAT), KLA Corporation (KLAC), and Lam Research (LRCX) dominate this step,and all four beat earnings, raised guidance, and reported sold out capacity simultaneously in the most recent cycle, an extraordinarily rare alignment that signals just how tight the HBM supply chain truly is. Applied Materials leads in deposition tools, Lam Research controls roughly 50% of the global etch market, and KLA holds a near monopoly at 55% share in process control and inspection, every wafer must pass through KLA's equipment to confirm chip integrity before moving forward. The TSV etching process also requires specialized industrial gases, C4F8 and SF6 that create the precise chemical reactions needed to carve through silicon without damaging surrounding material. Linde, Air Liquide, SK Materials, and Merck supply these gases and none of them are substitutable within current production timelines making them some of the most overlooked AI infrastructure plays in the market. Once the dies are prepared, they need to be stacked and bonded together, currently via Thermal Compression Bonding, but the industry is shifting toward Hybrid Bonding for HBM4 and beyond. Besi, ASMPT, Hanmi Semiconductor, and Kulicke & Soffa dominate the bonding equipment market, and the hybrid bonder market alone is projected to reach nearly $2 billion by 2028 as every memory maker upgrades to the next-generation process. After stacking, chips need to be thinned, cut and polished through grinding, dicing, and CMP processes where DISCO Corporation holds near-monopoly control in precision dicing equipment, with DuPont, Dow, CMC Materials, and Resonac supplying the CMP slurry chemicals needed to polish chips to atomic smoothness. All of this feeds into just three companies that actually build and sell HBM, SK Hynix with over 50% global market share, Micron ramping HBM4 for Nvidia's Rubin platform and Samsung fighting to regain ground after falling behind on qualification timelines. And at the very bottom of the supply chain sits the demand engine, every hyperscaler and chip designer whose AI accelerators require HBM to function, Nvidia, AMD, Broadcom, Google, Microsoft, Meta, AWS, Marvell, and Tesla. Every company in this supply chain is a toll booth and the traffic is only getting heavier. Make sure to follow me @MelvinInvests for more semiconductor opportunities.

@coooooooopppppp @_Investinq That's literally me

@MelvinInvests @_Investinq Love these write ups. The only problem is I go down a 3 hour research hole after each one before realizing the time 🙃

@0xWuki good idea

@MelvinInvests Saving this gem.

@MilkRoadAI nice!

@MelvinInvests Double saved

I’m an analyst at Milk Road, and my job is to find underrated gems before the market catches on. We called names like MU, CRDO, NBIS, and BE over the last 3 months. Join me and my team for just $1. #1" target="_blank" rel="nofollow noopener">milkroad.com/pro/?utm_mediu…

Nebius will be the first Neocloud to hit $1 trillion and the data makes that case better than any hype ever could (Save this). US data center power demand is on a trajectory to go from 31 GW in 2025 to 66 GW by 2027 more than doubling in just two years. Goldman estimates that only 50–60% of planned capacity will actually come online on time due to power grid bottlenecks, labor shortages, transformer supply constraints and permitting delays. And even after discounting half the entire buildout, demand still massively outstrips supply. Data centers are on track to consume 8.5% of peak US summer electricity by 2027, up from just 4.1% today. The real story is that the grid, the labor force, and the supply chain physically cannot build fast enough to satisfy it and that structural gap is widening every single quarter. This is the single most important tailwind Nebius has and it is not going away. In a world where Microsoft, Meta and Amazon are collectively spending over $700 billion on AI infrastructure in 2026 alone but cannot build fast enough themselves, they are being forced to sign decade long contracts with purpose-built AI cloud providers who have already done the hard work of securing land, power interconnects, and GPU supply. Nebius has secured $27 billion in contracted capacity with Meta Platforms and $19.4 billion with Microsoft over $46 billion in total contracted backlog meaning its revenue for the next five years is essentially pre-sold before a single new customer signs up. The financial results confirm that this, Nebius reported $399 million in revenue in Q1 2026, up 684% year over year, with AI cloud revenue specifically up 841% in a single quarter. Full-year 2026 guidance calls for $3.0–$3.4 billion in revenue, with an annualized run rate of $7–$9 billion by year-end. The company has now contracted over 3.5 GW of power capacity across seven sites each over 100 MW including a 1.2 GW AI factory campus in Pennsylvania and a £1.7 billion expansion across three UK sites, targeting 4 GW by end of 2026. And critically, Nebius is not just a landlord renting GPU racks to the highest bidder. But rather building a full-stack AI platform, proprietary inference solutions, agentic deployment tools, and developer APIs that converts one-time infrastructure contracts into recurring high-margin software subscriptions over time, compressing the multiple the market should apply to its revenue as those software layers scale. The Goldman chart is essentially a map of Nebius's total addressable market and every quarter that supply falls further behind demand, that market gets bigger. Long Nebius and make sure to follow me @MelvinInvests for more long duration AI winners.

We just have different analysts within our Pro, as you probably already know. We all have different views. I don’t want to speak for Martin but I think demand for compute is at an all time high and will continue to go up, even as free open weight models catch up. Just look at Anthropic’s and OpenAI’s revenue. That will continue to accelerate, which means they are all going to need more compute. Google just limited Meta’s compute because they clearly don’t have enough capacity, even after signing a deal with SpaceX. I think some of the biggest beneficiaries of this will be neocloud providers like Nebius and CoreWeave.

@MelvinInvests @milkroaddaily Didn’t milk road recently analyzed that token cost has come down rapidly because improving free ai models? I’m super bullish data centers but that recent article from milk road was a bearish read for me. Could you please help me connect the dots?

@milkroaddaily as you should

@MelvinInvests On my way to buy more!

@MilkRoadAI Yes sir!

@MelvinInvests Nebius to the moon!

I’m an analyst at Milk Road, and my job is to find underrated gems before the market catches on. We called names like MU, CRDO, NBIS, and BE over the last 3 months. Join me and my team for just $1. #1" target="_blank" rel="nofollow noopener">milkroad.com/pro/?utm_mediu…

The humanoid robot market is projected to reach $7 trillion by 2050 with some forecasts going as high as $9 trillion when software and services are included (Save this). Every major bank covering this space agrees on one thing, this will eventually dwarf the entire global auto industry but the real money is not in the companies assembling the robots. Tesla, Hyundai and Xiaomi will compete brutally for share, compress each other's margins, and fight wars of attrition for the next 20 years just like every auto manufacturer before them. The companies that print money regardless of who wins that war are the ones supplying the components every single robot on earth must have, no matter which assembler's logo is on the chest. Here is how that plays out across each layer of the value chain shown above. The brain is the safest and most liquid layer to own. Nvidia (NVDA) is the backbone, its Isaac platform is becoming the default operating system for training and deploying physical AI meaning every humanoid robot essentially runs on Nvidia infrastructure before it ever takes a step. TSMC (TSM) manufactures the chips inside every competitive robot brain regardless of whose design wins, making it the toll booth of the entire sector. Arm (ARM) and Broadcom (AVGO) sit deeper in the stack as the architecture and connectivity layer that nobody talks about but everyone depends on. The body is where the highest conviction asymmetric plays live. Harmonic Drive Systems makes the precision gearboxes that give robot joints their accuracy, there is currently no viable substitute and every serious humanoid maker uses them, making this the closest thing to a monopoly in the entire value chain. Mobileye (MBLY) and Hesai supply the vision and LiDAR systems that let robots perceive the world, the same sensors that cracked autonomous vehicles are now being re-deployed into humanoid perception stacks. Monolithic Power Systems (MPWR) and Navitas supply the power management chips that determine how long a robot can operate, a silent but critical bottleneck as robots move from factory floors to field deployment. The bottleneck Layer is the most overlooked and potentially the most important. ASML (ASML) and Lam Research (LRCX) are the picks and shovels of semiconductor manufacturing, you cannot build robot chips at scale without their equipment, full stop. SK Hynix and Micron (MU) supply the memory that robot brains need to process real-time sensory data, the same HBM supercycle driving AI data centers will eventually power mobile robot intelligence. Amphenol (APH) and TE Connectivity (TEL) make the connectors and cables inside every robot, unglamorous, high margin, and impossible to disintermediate. MP Materials (MP) mines the rare earth magnets that go inside every actuator motor with China controlling most of the world's rare earth supply, MP is the only US-listed pure-play on this critical material. The applications layer, Intuitive Surgical, Symbotic, and Serve Robotics shows you what monetized robotics looks like right now, before humanoids go mass market. These companies are already generating real revenue from robotic systems in surgery, warehousing, and food delivery, and they de-risk the investment case because they don't require you to wait until 2035 for the thesis to pay off. For the lazy route, the chart lists KOID, BOTZ, ROBO, and ROBT as ETF vehicles that spread exposure across the full value chain. The framework is simple, bet on the toll roads, not the car companies. Make sure to follow me @MelvinInvests for more overlooked opportunities in AI and robotics.

chart from @TacticzH

@GeorgeOomm32323 Not my chart, I saw somewhere on my feed

@MelvinInvests Excellent work Melvin

I’m an analyst at Milk Road, and my job is to find underrated gems before the market catches on. We called names like MU, CRDO, NBIS, and BE over the last 3 months. Join me and my team for just $1. #1" target="_blank" rel="nofollow noopener">milkroad.com/pro/?utm_mediu…

@MilkRoadAI Good

@MelvinInvests Saving this right now!

Goldman Sachs Research estimates that Korean companies will command 30% of global humanoid robot production by 2035, rising from near zero today to over 412,000 units annually (Save this). That chart above tells the whole story, it's a hockey stick and Korea is at the base of the blade right now. The reason Korea wins this is because of decades of automotive manufacturing excellence translate directly into humanoid robot components. The Korean government is backing this with 700 billion won (~$500M) in 2026 robotics investment, targeting 1,000 domestically produced humanoids per year by 2029. On the investment side, Korean robotics stocks have already repriced hard across the board. The biggest mover is LG Electronics (066570.KS) and most people don't think of LG as a robotics company but they produce 41 million motors annually and are now commercializing their Actuator Axium brand directly into humanoid robots with Figure AI already as a customer. This is the classic sleeper play, a massive industrial manufacturer that already has the capability, just now getting credit for it. Hyundai Motor (005380.KS) is arguably the most vertically integrated humanoid bet on the planet, they own Boston Dynamics, are launching a robot training facility in Q3 2026, and have the manufacturing scale to go from prototype to mass production faster than almost anyone. Hyundai Mobis (012330.KS) is the cleaner pure play within the Hyundai group and is a confirmed actuator supplier inside the next-gen Atlas robot meaning revenue visibility is already there. Rainbow Robotics (277810.KQ) is the highest risk, highest-reward name, it builds full humanoid systems, has Samsung Electronics as its largest shareholder and trades at premium multiples because the market sees it as Korea's answer to Figure AI or 1X. Robotis (108490.KQ) is the pure play actuator maker and appears in virtually every Korean humanoid ETF as a core holding, smaller cap, higher volatility, but maximum direct exposure to the component ramp. Doosan Robotics (454910.KQ) sits at the intersection of collaborative robots and humanoid systems, with established industrial customers already paying for its technology. For investors who don't want single-stock risk, the ACE K Humanoid Robot Industry TOP2+ ETF returned 37% in its first month after launch and overweights Hyundai Motor and Robotis. The TIGER Korea Humanoid Robot Industry ETF from Mirae Asset covers the full value chain, components, manufacturing, and software and is the broadest expression of this theme in a single ticker. Korean pension funds are already piling in, robot ETFs drew 3 trillion won in pension inflows in June 2026 alone, which signals this is no longer just a retail momentum trade. The main risk is valuation, several names have priced in years of perfect execution, and the investors who will win are the ones who separate companies with real signed contracts and confirmed component orders from the ones riding the hype wave. Make sure to follow me @MelvinInvests for more overlooked opportunities in AI and robotics.

@vadim_deem Maybe 👀

@MelvinInvests Are we getting a trade alert on that soon? :-)