@yijiangren: The robotics sector is never just about humanoid robots (nine primary sectors). The three major U.S. stock sectors: 240,000 views. Photonics: 80,000 views. The primary domain under photonics: nearly 30,000 views. Taking advantage of $MU's earnings call, the CEO of MU made several predictions: 1. The memory demand cycle driven by humanoid robots will last for decades. 2. Humanoid robots will require about ten times the memory of today's L2+ autonomous vehicles. 3. This wave of demand will begin before the end of this decade.

The robotics sector is never just about humanoid robots (nine primary sectors). The three major U.S. stock sectors: 240,000 views. Photonics: 80,000 views. The primary domain under photonics: nearly 30,000 views. Taking advantage of $MU's earnings call, the CEO of MU made several predictions: 1. The memory demand cycle driven by humanoid robots will last for decades. 2. Humanoid robots will require about ten times the memory of today's L2+ autonomous vehicles. 3. This wave of demand will begin before the end of this decade. Today, let's talk about the sectors under robotics. The robotics line will definitely get hotter in the future. The biggest misunderstanding in the market about robotics is that when people mention robots, the only image that comes to mind is humanoid robots. Of course, that's sexy. As shown in the picture, UBTECH's robots may have given some people the idea: robots might not be bad after all. OK, enough fantasy. A robot that looks like a human, can walk, carry things, enter factories, and go into homes sounds like the next super entry point. Especially something like Tesla's Optimus, once it enters mass production, the market can easily imagine it as the next ultimate hardware after electric vehicles, smartphones, or even AI. But investment is never just about the sexiest layer. The real robotics sector is a whole industry chain. It is not a single-point concept but a combination of AI, manufacturing, sensors, precision components, industrial software, healthcare, logistics, and defense. The first step in robotics is not to ask "whose robot looks most human." The first step should be: in which scenario does this robot create value? From an investment perspective, the robotics sector can be roughly divided into nine primary sectors. The top layer is the AI brain of robots. In the past, robots were more like automated equipment, performing fixed actions according to fixed programs. But now it's different. With large models, vision-language models, simulation training, and edge inference chips entering robots, robots are transforming from "automated machines" into "AI in the physical world." The most core target in this layer is naturally NVIDIA. Because robots need GPUs for training, platforms like Omniverse and Isaac for simulation, and edge computing like Jetson Thor for running on machines. NVIDIA doesn't directly sell robots, but it is very likely to be the most foundational infrastructure company in the entire robotics era. Similar companies include AMD, Qualcomm, and Google. They may not all become pure-play robotics targets, but they control the computing power, models, and software ecosystem behind robots. The second layer is the most familiar: humanoid robots. The most representative listed company in this field is Elon Musk's $TSLA. Tesla's Optimus is important not just because Musk tells good stories, but because Tesla indeed possesses several advantages that few others can simultaneously have: AI capabilities, mass production ability, motor and electronic control capabilities, supply chain management, and real factory scenarios. These factors together constitute Tesla's core advantage in making humanoid robots. Humanoid robots are the layer with the largest imagination space in the robotics sector, but also the one with the greatest uncertainty. Currently, most humanoid robots are still in the stage of demonstrations, pilot projects, and early deployment. Truly large-scale commercialization still needs to solve issues like cost, reliability, safety, battery life, maintenance, and task generalization. Therefore, I would view humanoid robots as the "options" in the robotics sector. They can bring the greatest flexibility, but you cannot bet the entire robotics investment logic on this layer alone. The third layer is the industrial robot body itself. This is the most mature layer in the robotics industry with the most real revenue. Representative targets include ABB, Fanuc, Yaskawa, Rockwell, and Siemens. These companies produce robotic arms, collaborative robots, control systems, and factory automation solutions. They may not be as sexy as humanoid robots, but they have been operating in automotive, electronics, semiconductor, metalworking, packaging, welding, painting, and assembly scenarios for many years. Industrial robots are essentially tied to manufacturing capital expenditures. When manufacturing expands, reshoring, or upgrades automation, they benefit. When the manufacturing cycle declines and companies cut capital expenditure, they also face pressure. So this layer is not purely a growth stock logic, but a "manufacturing cycle + automation penetration rate" logic. The fourth layer is core components and motion control. I personally really like this layer. Because no matter what form a robot takes, it ultimately cannot avoid several things: reducers, servo motors, controllers, bearings, ball screws, pneumatic components, and transmission systems. These things may sound less sexy than humanoid robots, but they are the foundation for robots to actually move. Representative targets include Nabtesco, Harmonic Drive, Nidec, SMC, THK, as well as China's Inovance Technology (Inovance is in my city, and I even had an online interview with them), Estun, etc. The most critical among them is the reducer. For robot joints to be powerful, precise, and stable, reducers are very core components. Common in industrial robots are RV reducers and harmonic drives. If humanoid robots really go into mass production in the future, the number of joints will be huge, and the demand for high-precision, lightweight, low-cost reducers will be further amplified. So this line is somewhat like the optical modules, liquid cooling, and power infrastructure in AI. It may not be in the spotlight, but when the entire industry scales up, component companies are often the first to receive orders from the industry chain. The fifth layer is vision, sensors, and machine perception. For robots to enter the real world, the first thing is not to act but to see. They need to recognize objects, judge distances, detect defects, read barcodes, avoid obstacles, locate, measure dimensions, and recognize postures. Behind these capabilities are machine vision and sensors. Representative targets include Keyence, Cognex, Teledyne, Ouster, Hesai, etc. Keyence and Cognex are typical machine vision companies. They may not tell huge robot stories, but the more robots and automation spread, the stronger the demand for visual inspection, industrial cameras, 3D recognition, and AI detection. The logic of this layer is clear: the smarter the robot, the more it needs eyes. The sixth layer is warehousing logistics and AMRs. AMRs are autonomous mobile robots. I think this line is worth paying close attention to because it is easier to commercialize before humanoid robots. In warehouses, factories, and distribution centers, there is a large amount of repetitive work: moving, sorting, picking, replenishment, and pallet transfer. These task environments are relatively closed, paths are relatively controllable, and ROI is easier to calculate. Representative targets include Symbotic, Teradyne, Zebra, Ocado, AutoStore, and Serve Robotics. Symbotic focuses on large-scale warehouse automation systems and has a deep relationship with Walmart. Teradyne owns Universal Robots and Mobile Industrial Robots, one for collaborative robots and the other for mobile robots. Zebra acquired Fetch Robotics, an important player in the warehouse AMR space. The advantage of this line is the real demand, but the disadvantage is that it is project-based, and many companies have high customer concentration. For companies like Symbotic, orders may look big, but investors must look at customer structure and delivery capabilities. The seventh layer is medical robots. The most mature business model in this layer is Intuitive Surgical. Its da Vinci surgical robot has formed a very strong ecosystem of installations, consumables, services, and doctor training. Medical robots are different from ordinary industrial robots; they have high regulatory barriers, and once doctors form habits, switching costs are high. So medical robots may not have the most exciting rises, but they have the clearest business model in the robotics sector. Representative targets include ISRG, Stryker, Medtronic, Zimmer Biomet, etc. The core of this line is not "robots replacing doctors," but robots helping doctors perform surgeries more stably, precisely, and minimally invasively. The eighth layer is agriculture, construction machinery, and outdoor robots. This layer is easy to overlook. But scenarios like agriculture, mining, construction, and landscaping have long faced a problem: it's increasingly difficult to hire people, and the environment is tough, so the incentive to replace humans with machines is very strong. Representative targets include Deere, Caterpillar, Trimble, CNH, Komatsu. Deere is typical. On the surface, it is an agricultural machinery company, but in essence, it is increasingly becoming an "agricultural robot + precision agriculture + autonomous machinery" company. The characteristic of such companies is that robots won't stand up and walk like in sci-fi movies, but they will directly enter the real world as unmanned tractors, automatic seeding, automatic spraying, automatic harvesting, and automatic construction equipment. This is also the most pragmatic line for robot commercialization. The ninth layer is defense unmanned systems. This line has changed rapidly in the past few years. The nature of warfare is changing. Drones, loitering munitions, unmanned wingmen, unmanned ground platforms, and low-cost expendable equipment are becoming increasingly important. In the future, defense robots may not be Iron Man-style humanoid robots, but more likely large numbers of low-cost, expendable, networked, and autonomously mission-capable unmanned systems. Representative targets include AeroVironment, Kratos, Red Cat, Palantir, and larger traditional defense contractors like Lockheed Martin, Northrop Grumman. AeroVironment represents drones and loitering munitions. Kratos represents unmanned combat aircraft, target drones, and unmanned systems. Red Cat focuses on smaller drones and tactical drones. Palantir is not a robot hardware company, but it has a position in defense AI, mission systems, and data decision-making. The core catalyst for this line is geopolitics and defense budgets. But the risks are clear: policy-driven, uneven order rhythms, and valuations easily inflated by sentiment. So what is the framework for the robotics sector? First, the sexiest are humanoid robots, but the earliest to make money may not be humanoid robots. Second, the areas with higher certainty are industrial automation, core components, machine vision, medical robots, and warehouse logistics, which already have commercial scenarios. Third, robotics is not a replacement for AI but the next spillover of AI. AI first enters screens, then software, then office workflows, and eventually will enter the physical world. Fourth, when investing in robotics, you shouldn't just look at whose video is the flashiest; you need to see who can sell robots, who can deliver consistently, who has a supply chain, who has customers, who has gross margins, and who has recurring revenue and consumables. From a risk-reward perspective, I would divide the robotics sector into three categories. First category: underlying infrastructure, such as $NVDA, Keyence, Cognex, Nabtesco, Harmonic Drive, SMC. These companies may not have the largest flexibility, but they are more like the "shovel sellers" of the robotics era. Second category: mature application scenarios, such as ISRG, SYM, TER, DE, AVAV, KTOS. These companies correspond to medical, warehouse, agriculture, and defense, where robots can already land. Third category: high-flexibility narratives, such as TSLA, UBTECH, SERV, RCAT. These targets have huge imagination space but also large volatility, more suitable as thematic flexibility rather than blindly heavy positions. The most important change in the robotics sector is not that robots suddenly become human-like. It is that AI is beginning to move from the digital world to the real world. In the past few years, the market has been hyping computing power, large models, and cloud AI. Next, if AI is to continue spilling over, it must enter factories, warehouses, hospitals, farms, battlefields, and homes. And robots are the physical bodies for AI to enter the physical world. This sector is worth watching in the long term. But the more it is worth watching in the long term, the less you should be led by short-term concepts. A genuinely good robotics investment is not chasing the hottest names but finding those companies that can continuously deliver, continuously make money, and continuously improve efficiency in the real world. Because the story of robots ultimately relies not on imagination but on the ability to land.