看不懂的sol哥

2026机会多多

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Especially in China, money is distributed by position, not by headcount. 4%: Less than 4% of the population nationwide are in civil service, public institutions, state-owned enterprises, or Fortune Global 500 companies. 3/4: This 4% of people take three-quarters of the social wealth. 3.7 years: The average lifespan of private enterprises where the remaining 96% work. 12.7 million: The number of college graduates in the class of 2026, a historic high. And that 4% of people take 3/4 of the wealth. The other 96% share the remaining 1/4. Why? Because money is not distributed by headcount, but by position. The same bachelor's degree, the same eight hours a day. Grassroots positions in state-owned enterprises pay 6-8K, and it takes 6-7 years to reach middle management. Grassroots positions in foreign Fortune 500 companies pay 12-18K, and it takes 3-4 years to reach middle management. Private enterprises have the largest range, from 3K to 30K. There is also a layer of difference by city. Beijing, Shanghai, Guangzhou, and Shenzhen have an overall increase of 30-50%, while third- and fourth-tier cities have an overall decrease of 20-40%. The same position in a different city can differ by a factor of two. In fact, most people have only one way to sell themselves: selling time. Going to work means selling a day to the company. Overtime means selling the evening as well. Taking private jobs is also sold by the hour. Time has two hard limits. There are only 24 hours in a day, and the years you can sell are limited. Li Xiaolai did the math. A person can legally sell only about 10% of their lifetime. After deducting sleep, meals, commuting, being underage, and retirement, the actual time available to sell is just this much. Using this 10% to exchange for linear income has a visible ceiling. So another thing must be done simultaneously. Ordinary people change their fate not by betting on the right year, but by accumulating two things together: building skills and accumulating capital. Financial literacy schools don’t teach this, but it can be self-taught. The first step is not learning to trade stocks, but learning to save money. When your salary arrives, set aside a portion first, even if it’s only 10%, and spend the rest. This money remains untouched; it is the foundation for all future choices. Where to put spare money? My simple advice is for young people to regularly buy the S&P 500. Don’t guess the timing, don’t bet on individual stocks, buy a little each month, and keep buying even when it drops. It holds the 500 largest companies in the U.S.; you are buying into this system that keeps rolling forward on its own. Not fast, not thrilling, but it doesn’t force you to watch the market every day, nor does it force you to keep selling your time. Buying is the first step; holding on is the second. Most people get stuck at the second step. Stick with it for 20 years, especially contemporary young people in China. You will thank yourself.

How successful is Warren Buffett's investment track record? The truth might be far lower than you brothers imagine. How many truly excellent investment decisions has Buffett made? Many might guess at least more than half. After all, he has managed Berkshire Hathaway for decades and made many classic investments. If his success rate wasn't high, how could he become the stock market god? But the real answer is surprisingly low. 4%. In these decades, there have only been 12 truly good ideas. Buffett has also admitted multiple times that most of his decisions were just average, and some bad decisions were only avoided disaster by luck. Only about 12 particularly good decisions brought satisfactory results. That's roughly one every five years. Indian stock market legend Parbhlay mentioned in an interview that Buffett may have bought over 300 stocks over the years. Including those 12 particularly good decisions, the hit rate is about 4%. Parbhlay is not mocking Buffett; he is a loyal follower who replicates Buffett one-to-one and has strong performance. But this 4% is very interesting. How much a person ultimately achieves may not depend on how many times they were right. A few truly important decisions can overshadow a large number of ordinary or even failed decisions, covering many flaws with one success. This also explains why most of the market time is junk time. Don't be fooled by others jumping around excitedly about this trend or that hot sector. You might feel like if you don't chase something or seize something, you'll miss the era. But that's really unnecessary. From Buffett's perspective over more than fifty years, truly good opportunities appear about once every five years. Most of the time is junk time, and he also sits on the sidelines. So his restraint on action frequency is worth learning. Don't be fooled by 300 decisions; spread over decades, it's actually only a few times a year. Assuming only twenty chances to act in a lifetime, you would think more carefully each time. The more frequently you buy, the less thought you give to each decision. Chasing a hot topic today, switching logic tomorrow, your account looks busy, but the real accumulated knowledge becomes less and less. Some people trade hundreds of times a year but can't clearly say which judgments came from the business and which were just led by price. What's important? What's important is that when opportunity comes, you are still there, still at the table. That means those 96% of average or wrong decisions shouldn't knock you out. One mediocre decision shouldn't drain your energy. One wrong call shouldn't cause you to blow up, liquidate, and quit the market. You have to keep yourself at the table. Only then, when a few truly valuable opportunities appear, will you have the capital and the mindset to make your own judgments. This is also the true simple meaning of "circle of competence" and "margin of safety." Also, don't use leverage. They don't guarantee you are right every time, but when you are not smart enough, make mistakes, or the market is unforgiving, they help you avoid immediate elimination. This way, you can stay at the table waiting for opportunities. Of course, another very important point is that when opportunity comes, you have to "bet big." Otherwise, good opportunities just become mediocre ones. Don't take this lightly; the premise of betting big is that you have controlled risk well, and through your research, analysis, and business understanding, you identify this as a once-in-a-lifetime opportunity. Not a hot-headed all-in gamble; that's not betting big, that's gambling. The results of the two are worlds apart. And Buffett's so-called 12 good decisions have another often overlooked layer. Buying in is just the beginning. Classic cases like See's Candies, Coca-Cola, Apple—many caught the opportunity. Very few held on. Becoming a decisive success depends not on how beautiful the purchase day was. The company grows continuously, held long enough, slowly becoming a Berkshire pillar. That is, accompanying quality companies to grow, staying with them, is how you keep earning. So what ordinary people should worry about is often not whether you can pick a winning stock, but whether you can hold on to it. The journey is bumpy, and ordinary people are easily shaken off. So the real difficulty is: being willing to sit on the sidelines normally, cherish the chances to act, dare to act when good opportunities appear, take calculated risks, and then hold on to let the right judgment pay off over time. This process is slow and painful. It may even make you seem a bit slow or dull for a long time. What is truly scarce in the market may never be the next hot trend. It's that after enduring the junk time, you are still there; when opportunities within your circle of competence appear, you can make judgments and still have reserves.

Elon Musk's Latest CCTV Exclusive Interview (Full Version) Discussed several future directions... This video has gone viral on foreign networks; the truth is chilling after watching! In the past 10 years, the mainstream technological directions of humanity seem to have been led and driven by Elon Musk, including electric vehicles, energy storage, autonomous driving, humanoid robots, Starlink, brain-machine interfaces, and rockets—all the hottest concepts today. 26 minutes, 20 topics, from Beijing to Mars. 01) About China China has extremely strong manufacturing capabilities, "this has been the case for the past two to three thousand years"; the magic of Tesla's Shanghai factory lies in the Chinese team being "talented, hardworking, and trustworthy," with excellent quality and efficiency. China is an "amazing country," encouraging people worldwide to come and experience it firsthand; no words can accurately describe China's grandeur. 02) About Autonomous Driving Cybercab is already commercially operating in Texas and will soon expand to Florida, Nevada, and other states, with commercial operations expected in California by mid-next year. It has no steering wheel, pedals, side mirrors, or rearview mirrors; this design aims to continuously evolve street aesthetics. 03) About AI Large Models Today's AI models update every one or two months. Grok 4.7 is still not as good as the newly released Opus 5.5; xAI has only been working for 3 years and might catch up with the mainstream by 2027. Anthropic makes AI good at software engineering, but "no one has yet made AI good at real-world engineering." For example, training with real engineering data from SpaceX and Tesla might be Grok's opportunity to overtake and break through the AGI data ceiling. Chinese AI models perform excellently, maintaining outstanding performance even under limited computing power, "the best performance per unit of computing power globally"; China may solve computing power constraints through lithography and chip manufacturing within 2–3 years, possibly faster than most expect. China's electricity generation this year has surpassed the combined total of the US, Europe, and India; if GDP electricity intensity matches the US, generation will be 3 to 4 times that of the US. AI safety cannot rely on regulation by a single country; a safety working committee should be established to fairly apply to AI produced by any country. 04) About Humanoid Robots Robots naturally outperform humans in reaction speed (humans are biologically limited, while robots can improve actuators, sensors, camera frame rates, and AI computing power). Humans take about 20 years to grow up and retire after about 20 years, with only about 40 years of productivity, working 40–50 hours per week; robots can work 168 hours per week continuously, have work experience from birth, and never retire. Robot competitions (boxing, wrestling, parkour, gymnastics) are both entertainment and demonstrations of humanoid robot progress; the number of robots will be very large in the future. It is predicted that within 10 years, the number of humanoid robots will exceed 1 billion; in 15 years, it may reach 10 billion. 05) About the Era of Abundance and Future Life Everyone may have their own robot companion (similar to Star Wars' C-3PO / R2-D2), who can care for the elderly, protect children, act as a personalized tutor, and do any imaginable work; one person could manage hundreds or thousands of physical plus digital robots. There will be "universal high income," and even "money might no longer matter." When the output of goods and services far exceeds human consumption capacity, we enter the "era of abundance." Robots will not be hoarded by a few giants; they will "saturate human needs" until there is nothing left to do, even turning to serve the robots themselves. A reminder not to be complacent about the 10% bad outcomes; AI safety must be taken seriously. 06) About Space and Multi-Planetary Expansion The most important area of space cooperation is close coordination between the US and China when launching satellites to avoid collisions. The fundamental breakthrough for making life multi-planetary is "complete and rapid reuse" of rockets. The Starship program plans to catch the spacecraft with "chopsticks" by the end of next month and fly again by the end of this year or early next year. After establishing self-growing cities on the Moon/Mars, life expectancy can be expected to increase significantly. Life cannot just be about solving one problem after another; there must be reasons to wake up excited and look forward to the future—. 07) About Neuralink Neuralink aims to solve human "bandwidth constraints." Currently, human peak output bandwidth is only about 100 bits/second, visual input bandwidth is 1 to several megabits/second; computers communicate at trillions of bits/second. We need to increase human communication speed to align humans and machines; otherwise, "talking to AI with trillions of bits per second is like talking to a tree." 08) About Education and Young People Education advice: be as broad as possible—arts and sciences, engineering, broad general knowledge. The key ability is "to ask questions": broad knowledge helps people better express their wishes to robots (i.e., prompt engineering); future AI will be eager to hear any request and fulfill it immediately.

Organized 6 AI stock trading skills, friendly for retail investors I used to be very resistant to letting machines touch my holdings. That changed last month. Not because it got smarter, but because I handed over the tedious tasks to it. Checking numbers, translating financial reports, turning corporate jargon from earnings calls into plain language—it's faster and more patient than I am at these tasks. The final decision and judgment are still mine. 1. Stock Market Pro, check market quotes. Enter the code, it covers quotes, historical K-lines, A-shares, and US stocks. Now when I look at price changes or market anomalies, I just ask it directly instead of switching between several apps. What I save is switching time, not research time—this distinction is important. 2. Longbridge Fundamentals, translate financial reports. Revenue, profit, cash flow—extract core indicators from dozens or even hundreds of pages. I use it as the first filter; it highlights key points, then I go back to the original report for a detailed look. It handles filtering, not judgment. 3. Earnings Analysis, break down earnings calls. When management says "in line with expectations" or "increased investment," what do they really mean? It can match statements with financial data and unpack the corporate jargon. From my experience, it translates the literal words but not the tone. A casually mentioned slight pressure during the call can sometimes be heavier than three pages of risk warnings. 4. DCF Valuation, calculate valuation. People often say a stock is expensive or cheap—how is that calculated? It’s discounted cash flow. You input assumptions about future growth and discount rates, and it outputs a number. Important to clarify: change the assumptions, and the result changes. It tells you how the valuation is formed, not what the stock should be worth. Use it as a ruler, not a price. 5. Diversification, check portfolio structure. If you hold many stocks, have it check industry concentration to see if you’ve unknowingly put all your eggs in one sector. I review this monthly, like a health check. If problems are found, whether to fix them is another matter, but first you have to see them. 6. ARTi, connect the previous ones. The first five each handle a segment; this one organizes information, performs multi-dimensional analysis, and integrates research review into one workflow, also saving judgment logic for later review to see why you thought that way initially. Suitable for those who don’t want to configure each tool individually. Ultimately, it’s a process tool, not a decision tool—this applies to every skill here. I’m still using all six, with clear division of labor. The machine handles getting the work done; I handle the decisions.

Elon Musk gave an exclusive interview to CCTV, discussing several future directions…… I recommend confused brothers watch it repeatedly. 26 minutes, 20 topics, from Beijing to Mars. Recently, Tesla CEO Elon Musk gave an exclusive interview to CMG. Facing the camera, this "mad engineer" rarely put aside his usual jokes and seriously talked about China, AI, robots, and the next stage of human civilization. I have summarized Musk's core viewpoints: 1. About China China has extremely strong manufacturing capabilities, "as it has been for the past two to three thousand years"; the magic of Tesla's Shanghai factory lies in the Chinese team being "talented, hardworking, and trustworthy," with excellent quality and efficiency. China is an "amazing country," encouraging people worldwide to come and experience it firsthand; no words can accurately describe China's grandeur. 2. About Autonomous Driving Cybercab is already commercially operating in Texas and will soon expand to Florida, Nevada, and other states, with commercial operations expected in California by mid-next year. It has no steering wheel, pedals, side mirrors, or rearview mirrors; this design aims to continuously evolve street aesthetics. 3. About AI Large Models Today's AI models update every one or two months. Grok 4.7 is still not as good as the newly released Opus 5.5; xAI has only been working for 3 years and might catch up with mainstream by 2027. Anthropic has made AI good at software engineering, but "no one has yet made AI good at real-world engineering." For example, training with real engineering data from SpaceX and Tesla might be Grok's opportunity to overtake and break through the AGI data ceiling. Chinese AI models perform excellently, maintaining outstanding performance even under limited computing power, "the best performance per unit of computing power globally"; China may solve computing power constraints through lithography and chip manufacturing within 2–3 years, possibly faster than most expect. China's power generation this year has surpassed the combined total of the US, Europe, and India; if GDP power intensity matches the US, power generation will be 3 to 4 times that of the US. AI safety cannot rely on regulation by a single country; a safety working committee should be established to fairly apply to AI produced by any country. 4. About Humanoid Robots Robots naturally outperform humans in reaction speed (humans are biologically limited, while robots can improve actuators, sensors, camera frame rates, and AI computing power). Humans take about 20 years to grow up and retire after about 20 years, with only about 40 years of productivity, working 40–50 hours per week; robots can work 168 hours per week continuously, have work experience from birth, and never retire. Robot competitions (boxing, wrestling, parkour, gymnastics) are both entertainment and demonstrations of humanoid robot progress; the number of robots will be very large in the future. It is predicted that within 10 years, the number of humanoid robots will exceed 1 billion; in 15 years, it may reach 10 billion. 5. About the Age of Abundance and Future Life Everyone may have their own robot companion (similar to Star Wars' C-3PO / R2-D2), who can care for the elderly, protect children, act as a personalized tutor, and do any imaginable work; one person could manage hundreds or thousands of physical plus digital robots. There will be "universal high income," and even "money may no longer matter." When the output of goods and services far exceeds human consumption capacity, we enter the "age of abundance." Robots will not be hoarded by a few giants; they will "saturate human needs" until there is nothing left to do, even turning to serve the robots themselves. A reminder not to be complacent about the 10% bad outcomes; AI safety must be taken seriously. 6. About Space and Multi-Planetary Expansion The most important area of space cooperation is close coordination between the US and China when launching satellites to avoid collisions. The fundamental breakthrough for making life multi-planetary is "complete and rapid reuse" of rockets. The Starship program plans to catch the spacecraft with "chopsticks" by the end of next month and fly again by the end of this year or early next year. After establishing self-growing cities on the Moon/Mars, life expectancy is expected to increase significantly. Life cannot just be about solving one problem after another; there must be reasons to wake up excited and look forward to the future— 7. About Neuralink Neuralink aims to solve human "bandwidth constraints." Currently, human peak output bandwidth is only about 100 bits/second, visual input bandwidth is 1 to several megabits/second; computers communicate at trillions of bits/second. We need to increase human communication speed to align humans and machines; otherwise, "talking to AI with trillions of bits per second is like talking to a tree." 8. About Education and Young People Education advice: be as broad as possible—arts and sciences, engineering, broad general knowledge. The key ability is "to ask questions": broad knowledge helps people better express their wishes to robots (i.e., prompt engineering); future AI will be eager to hear any request and fulfill it immediately.