원문 보기
Let me tell you something that most investors completely misunderstand about artificial intelligence. They think we are in the middle of the AI revolution. They think the big gains have already been made. They look at what has happened over the past few years with companies like mine and they assume that the opportunity has passed them by.
They could not be more wrong. We are not in the middle of the AI revolution. We are at the very beginning. What you have seen so far, the chat bots, the image generators, the productivity tools, this is just the opening act, the real transformation, the one that will create more wealth than the internet, mobile computing, and cloud computing combined that is still ahead of us.
And I am going to share with you today the only four AI stocks that I believe have the potential to dominate this industry for the next 20 years. Now, I need to be very clear about something from the start. I have spent over 40 years building technology companies. I founded my company in 1993 when most people thought graphics chips were just for video games.
I have watched the technology industry go through multiple transformations. The personal computer revolution, the internet era, the mobile computing wave, the cloud computing shift. And I can tell you with absolute certainty that artificial intelligence represents the most significant technological shift I have ever witnessed in my entire career.
It is not just another technology cycle. It is a fundamental rewiring of how computing works. how businesses operate and how value gets created in the economy. The reason I wanted to share this with you today is because I see so many investors making the same mistakes over and over again. They chase the hot stock of the moment.
They buy whatever is in the headlines. They get excited about companies with great stories but no sustainable competitive advantages and then they wonder why their investments underperform over the long term. What I have learned over four decades is that the companies that truly dominate for 20 years or more share certain characteristics that are identifiable early on if you know what to look for.
Let me take you back to 1993 for a moment because this story shapes everything I am about to tell you. When I started my company, we had a vision that was considered crazy by almost everyone in the industry. We believed that graphics processing would become increasingly important for computing. We believe that parallel processing, the ability to do many calculations simultaneously, would eventually become more important than the sequential processing that traditional computer chips excelled at.
People laughed at us. They said we were building toys for gamers. They could not see what we saw. But here is what we understood that others did not. We understood that certain types of problems require massive parallel computation. Rendering graphics is one of those problems. But so is training neural networks.
So is processing natural language. So is analyzing vast amounts of data. The same architecture that made our chips perfect for video games turned out to be perfect for artificial intelligence decades later. That was not luck. That was understanding fundamental computing principles and betting on them for the long term.
When I evaluate AI companies today, I am looking for that same kind of fundamental insight. I am looking for companies that understand something deep about how this technology works. Companies that are positioned to benefit not just from this year's trends, but from the underlying physics and mathematics of artificial intelligence.
And I have identified four companies that I believe have these characteristics. Before I reveal these four companies, let me explain the framework I use to evaluate AI investments. Because if you understand this framework, you will be able to make better investment decisions for the rest of your life, whether you invest in these specific companies or not.
There are four criteria that I believe separate the AI winners from the losers over a 20-year time horizon. The first criterion is what I call infrastructure inevitability. The question is simple. Does this company provide something that AI systems will absolutely need regardless of how the technology evolves?
Think about it this way. In the early days of the internet, you could not be sure which websites would win. Would it be Yahoo or Google, MySpace or Facebook? But you could be certain that everyone would need servers. Everyone would need networking equipment. Everyone would need bandwidth. The companies that provided that infrastructure won regardless of which application succeeded.
The same principle applies to AI. There are certain things that AI systems will need no matter what. Computing power, data storage, the ability to move information quickly. Companies that provide these fundamental necessities have a form of inevitability to their success. The second criterion is what I call moat depth.
In technology, competitive advantages can be fleeting. A software company can see its moat evaporated in months if a competitor releases a better product. But some moes are much deeper than others. The deepest moes in AI tend to come from a few sources. Proprietary data that no one else can access. Network effects where the product gets better as more people use it.
Massive capital requirements that make it impossible for competitors to catch up. Switching costs that make it painful for customers to leave. I am looking for companies with multiple reinforcing modes, not just one. The third criterion is what I call management quality. Over 20 years, you will face multiple crises.
You will need to make strategic pivots. You will need to allocate capital wisely across different opportunities. The quality of the management team matters enormously over these longtime horizons. I look for founders who are still involved because founders tend to think longer term than hired executives.
I look for track records of navigating technological transitions. I look for capital allocation skills, the ability to invest in growth while maintaining profitability. The fourth criterion is what I call valuation sanity. Even the best company in the world is a bad investment if you pay too much for it.
Over 20 years, valuation matters more than most people think. If you buy a company at 100 times earnings, you need decades of perfect execution just to justify your purchase price. But if you can find a great company at a reasonable valuation, the returns can be extraordinary. Now in AI specifically, almost everything looks expensive by traditional metrics, but some things are more expensive than others, and some growth rates justify higher multiples better than others.
With that framework in mind, let me tell you about the four AI stocks that I believe could dominate for the next 20 years. The first stock is Microsoft. Now, I know what you are thinking. Microsoft, the company that makes Office and Windows, how is that an AI play? But let me tell you why Microsoft might be the single best position company to benefit from AI over the next two decades.
Microsoft understood something crucial earlier than almost anyone else in big tech. They understood that the AI revolution would require massive computing infrastructure and that building that infrastructure would be enormously expensive. While other companies were treating AI as a research project, Microsoft was building the infrastructure to deploy AI at scale.
Their Azure cloud platform is now one of the largest computing platforms in the world. And it is increasingly optimized for AI workloads. But here is what really sets Microsoft apart. Their investment in open AI and their integration of AI across their entire product suite. Think about what Microsoft has done.
They have taken the most advanced AI technology in the world and embedded it into products that hundreds of millions of people use every day. Word, Excel, PowerPoint, Outlook, Teams, Windows itself. Every one of these products is being transformed by AI. This creates something incredibly powerful distribution.
The hardest problem for any AI company is getting their technology into the hands of users. Microsoft already has those users. They already have the relationships with enterprise customers. They already have the trust of it departments. When Microsoft rolls out an AI feature, it goes to hundreds of millions of users overnight.
No startup can compete with that. Let me give you a specific example of why this matters. GitHub C-Pilot. This is an AI tool that helps programmers write code. Microsoft owns GitHub, which is where most of the world's code already lives. They trained an AI on that code and now they have a product that is becoming essential for software developers.
There are already millions of developers using C-pilot. It makes them more productive. And once you start using it, once you get used to having an AI assistant helping you code, going back to coding without it feels primitive, that is a switching cost. That is a moat. And Microsoft is creating these moes across their entire product portfolio.
C-pilot for Office, C-pilot for Windows, C-pilot for their security products, C-pilot for their business applications. Every one of these creates stickiness. Every one of these generates recurring revenue. Every one of these makes Microsoft more essential to how businesses operate. Now, let us talk about the infrastructure side.
Azure is growing rapidly and AI workloads are driving a huge portion of that growth. When companies want to deploy AI applications, they need massive computing power. They need specialized chips. They need data storage. They need networking. Azure provides all of that. And Microsoft has been investing billions of dollars in building out this infrastructure.
They are building data centers around the world. They are buying chips, including mine, by the hundreds of thousands. They are positioning themselves to be the computing platform for the AI era. Here is another thing that people underestimate about Microsoft, their enterprise relationships. Microsoft has been selling to enterprises for 40 years.
They understand how big companies buy technology. They understand procurement processes. They understand security requirements. They understand compliance needs. When a Fortune 500 company wants to deploy AI, who are they going to trust? a startup that did not exist 5 years ago or Microsoft who they have been working with for decades.
The management quality at Microsoft is exceptional. Satcha Nadella has been one of the best CEOs in technology over the past decade. He transformed Microsoft from a stagnant company losing relevance to a cloud and AI powerhouse. He made the open AI investment when others thought it was crazy. He has been willing to cannibalize existing products to embrace new technology.
That is exactly the kind of leadership you want over a 20-year time horizon. And the valuation, while not cheap by historical standards, is reasonable given the growth trajectory. Microsoft is trading at a premium to the broader market. But the company is growing faster than the broader market and has a clearer path to sustained growth.
When I look at where Microsoft will be in 20 years, I see a company that will be even more essential to how businesses operate than it is today. The second stock is Amazon. And again, I am not talking about the retail business. I am talking about Amazon Web Services, which is the largest cloud computing platform in the world and is rapidly becoming an AI powerhouse.
AOS has a remarkable advantage that most people do not fully appreciate. They have relationships with millions of developers and businesses. They have been providing cloud infrastructure for almost 20 years. When companies think about where to run their applications, AWS is usually the first place they consider.
And now, as those companies want to add AI capabilities, AWS is right there ready to help them. Amazon has been investing aggressively in AI infrastructure. They are one of my largest customers. They are buying chips at enormous scale. They are building custom AI chips of their own. They are creating a comprehensive platform for companies that want to build AI applications.
And because they already have the customer relationships, they have a massive advantage in selling these new services. Let me explain something about the economics of AI infrastructure that most people do not understand. Running AI models requires enormous amounts of computing power. When you use an AI assistant, when you generate an image, when you get a recommendation, there are massive computations happening in a data center somewhere.
Most companies cannot afford to build their own AI infrastructure. The costs are too high. The expertise required is too specialized. So, they rent that infrastructure from cloud providers like AWS. This creates a beautiful business model, recurring revenue that grows as companies use more AI, high switching costs, because moving your AI applications from one cloud provider to another is incredibly difficult.
Capital requirements that make it nearly impossible for new competitors to enter. Amazon has been reinvesting profits from retail and advertising into AWS infrastructure for years. That head start is enormous. Amazon is also building their own AI products. Alexa was one of the first mainstream AI assistants.
Amazon Bedrock provides access to multiple AI models through a single platform. They are working on AI for logistics, for their retail operations, for advertising. Every part of Amazon's business is being transformed by AI and they are building the technology in-house rather than depending entirely on others.
The management situation at Amazon is interesting. Andy Jasse, who built AWS from scratch, is now the CEO. This is a founder adjacent situation. Jasse understands cloud computing and AI at a deep level. He built the business that is now driving Amazon's growth. That kind of expertise at the top matters over long time horizons.
What I particularly like about Amazon is the diversification. They are not just betting on one AI application succeeding. They are building infrastructure that will benefit regardless of which AI applications win. They are integrating AI across their retail, advertising, and logistics businesses. They have multiple paths to winning in AI.
That kind of optionality is valuable over 20 years. The valuation has become more reasonable in recent years. Amazon went through a significant correction in 2022 and while the stock has recovered, it is not at the extreme valuations we saw a few years ago. For a company with Amazon's growth profile and competitive position in AI infrastructure, the current valuation seems reasonable.
The third stock is Alphabet, Google's parent company. And this one might be controversial because there has been a lot of narrative recently about Google falling behind in AI, but I think that narrative is wrong. And I think Alphabet is one of the best positioned companies for the next 20 years of AI.
Let me tell you why. Google has been doing AI research longer than almost anyone. Deep Mind, which Google acquired in 2014, is one of the premier AI research labs in the world. They have made breakthrough after breakthrough. Alph Go, Alphafold, Gemini. Google has more AI research talent than perhaps any other company on Earth.
Yes, Open AI gets more attention right now, but attention is not the same as capability. Google has something even more valuable than research talent data. Unimaginable amounts of data. Every Google search, every YouTube video, every Gmail message, every Google Maps query, every Android phone, Google has been collecting and organizing the world's information for 25 years.
AI systems learn from data. The company with the most data has an enormous advantage. No one has more data than Google. And then there is distribution. This is the same advantage I talked about with Microsoft, but in some ways even more powerful. Google Search has over 90% market share in most countries.
YouTube has over 2 billion users. Android runs on billions of phones. Gmail has over a billion users. Chrome is the dominant web browser. When Google adds AI to these products, it reaches essentially everyone on the internet. Think about what is happening with Google search right now. They are integrating AI generated answers directly into search results.
Some people see this as a threat to Google's business model. I see it differently. I see Google using AI to make their search product even more valuable, even more essential. When you ask Google a question and it gives you a direct answer generated by AI, you are even more dependent on Google than before.
You are less likely to click through to websites. You are more likely to stay on Google. That is not bad for Google. That is good for Google. YouTube and AI is another massive opportunity. AI can help with content moderation at scale. AI can improve recommendations. AI can help creators make better videos.
AI can enable new forms of content entirely. Google is just beginning to explore these possibilities. Over 20 years, AI could transform YouTube into something we cannot even imagine today. There is also Whimo, Google's autonomous vehicle subsidiary. This is a long-term bet that most investors underappreciate.
Whimo has more autonomous driving data than any other company. They have been working on this problem longer than anyone. And autonomous vehicles represent one of the largest potential markets for AI. If Whimo succeeds, it could be worth hundreds of billions of dollars on its own. That optionality is not fully reflected in Alphabet stock price.
The cloud business, Google Cloud, is smaller than AWS and Azure, but growing rapidly. They have differentiated themselves with AI capabilities. Their Vertex AI platform is gaining traction with enterprises. As AI workloads grow, Google Cloud has an opportunity to capture a meaningful share of that growth.
Management has been a question mark at Alphabet. The company has had issues with focus and with monetizing new products, but Sundar Pichai has been becoming more decisive. The recent cost cutting measures suggest a company that is getting more disciplined and ultimately the quality of Alphabet's assets is so high that even mediocre management can produce good results.
Great management could produce exceptional results. The valuation at Alphabet is actually quite reasonable among the big AI companies. Alphabet trades at one of the lowest multiples. The market seems to be discounting the AI narrative concerns. I think that is a mistake. Google is not behind in AI. They are deploying AI across products with billions of users.
They have the data, the talent, the distribution, and the financial resources to compete for decades. The fourth stock is my company's stock, Nvidia. Now, I know I am biased here, but let me make the objective case for why this is one of the best AI investments for the next 20 years. We make the chips that power artificial intelligence, not just some AI systems, almost all of them.
When OpenAI trains a new model, they use our chips. When Microsoft runs Azure AI services, they use our chips. When Amazon deploys AI on AWS, they use our chips. When Google trains Gemini, they use our chips. We are the picks and shovels of the AI gold rush. Let me explain why this position is so defensible.
Training AI models requires a specific type of computing called parallel processing. You need to do trillions of mathematical operations simultaneously. Traditional computer processors, CPUs, are designed for sequential processing. They do one thing at a time very fast. But AI needs to do millions of things at the same time.
That is what our GPUs are designed for. We did not stumble into this position by accident. We have been building parallel computing technology for over 30 years. We have invested billions of dollars in software that makes our chips easy to use. This software ecosystem called CUDA is used by millions of developers.
Every AI framework, every AI tool, every AI application works with our chips because we have built the software to make that possible. Recreating that ecosystem would take a competitor years and billions of dollars. Some people worry about competition. They point to custom chips being developed by cloud providers.
They point to new startups trying to build AI chips. But here's what they miss. The market is growing faster than any competitor can take share. Even if someone builds a chip that is better for certain workloads, the overall demand for AI computing is exploding so fast that we continue to grow. We are not fighting for a fixed pie.
We are capturing a growing share of an exponentially expanding market. Our data center business has grown from virtually nothing a decade ago to tens of billions of dollars in quarterly revenue. And I believe we are still in the early innings. AI adoption is still concentrated in a relatively small number of companies.
As AI spreads to every industry as AI becomes embedded in every application, demand for computing power will continue to grow. We are also expanding beyond just chips. Our networking business, which we built through the Melanox acquisition, provides the connections between chips and AI data centers.
Our software platform which includes tools for AI development, inference and deployment, generates recurring revenue and creates switching costs. We are building a complete platform for AI computing, not just selling hardware. The automotive business is another long-term opportunity. Autonomous vehicles require massive computing power.
We have been working with car manufacturers for years, providing the processors for their AI systems. As vehicles become more autonomous, they will need more powerful computers. We are positioned to provide those computers. Here is something that makes our business model particularly powerful. We sell to everyone.
Microsoft, Amazon, Google, Meta, Tesla, they all compete with each other, but they all buy chips from us. We do not have to pick a winner. We win regardless of which AI applications or which cloud platforms succeed. That kind of neutrality in a fast moving industry is incredibly valuable. The management team, and I say this with obvious bias, has navigated technology transitions for over 30 years.
We have reinvented ourselves multiple times from gaming to professional visualization to data centers to AI. We understand that technology changes and that you need to evolve with it. That track record of adaptation is something I believe will continue. The valuation is high by traditional metrics. But let me offer a different perspective.
If AI is as transformative as I believe it is, if demand for AI computing continues to grow at the rates we are seeing, then the current valuation might actually be reasonable. The market is trying to price in growth that seems almost impossible, but which might actually happen. That is always the challenge with transformative technologies.
Now, let me bring all of this together and explain why I chose these four companies. Specifically, these four companies share several characteristics that I believe are essential for 20-year dominance in AI. First, they all have infrastructure inevitability. Microsoft and Amazon provide the cloud infrastructure that AI applications run on.
Google has the data and distribution that AI applications need. NVIDIA provides the computing power that makes AI possible. These are not companies betting on specific AI applications succeeding. These are companies that benefit regardless of which applications win second. They all have deep moes. Microsoft has distribution and enterprise relationships.
Amazon has scale and customer lock and Google has data and search dominance. Nvidia has technology and ecosystem advantages. These moes reinforce each other and are extremely difficult for competitors to attack. Third, they all have quality management with long-term track records. Microsoft has Nadella who transformed the company.
Amazon has Jasse who built AWS. Google has decades of technical leadership. Nvidia has management that has navigated multiple technology transitions. These are teams you can trust with your capital for 20 years. Fourth, while none of them are cheap, they are all reasonably valued given their growth profiles and competitive positions.
You are not paying lottery ticket prices for these stocks. You are paying premium prices for premium businesses, which is exactly what you should do for long-term investments. Let me address some concerns that investors might have about this approach. The first concern is concentration risk. These are four of the largest companies in the world.
Is it risky to have your AI investments concentrated in a few big names? My view is that in AI specifically, size is an advantage, not a disadvantage. The capital requirements are so high, the data advantages are so important, the distribution challenges are so significant. Big companies have real advantages in AI that smaller companies cannot easily replicate.
Yes, there will be successful AI startups but the infrastructure layer uh the layer will so the value will be captured is dominated by large companies. The second concern is valuation. These stocks are all expensive by historical standards. What if there is a market correction? My response is that over 20 years starting valuation matters less than business quality.
If you bought Microsoft in 2000 at the absolute peak of the dot bubble at valuations that were truly insane, you would still have made money holding to today. Not great returns, but positive returns. If you bought at any other time in the past 25 years, you would have made excellent returns. Business quality eventually overwhelms valuation over longtime horizons.
The third concern is disruption risk. What if some new technology makes AI obsolete? What if quantum computing changes everything? What if some startup invent something that makes these companies irrelevant? My view is that these companies are well positioned to navigate technological transitions. They have the resources to acquire threatening startups.
They have the research capabilities to develop new technologies. They have the distribution to deploy new innovations. Could something unexpected happen? Of course, but these are the companies most likely to survive and adapt. Let me share some thoughts on how to actually implement this investment strategy.
I am not a financial adviser and everyone's situation is different, but there are some general principles that I think apply. First, think long-term. I said 20 years and I meant it. These are not trades. These are ownership stakes in businesses. You should expect volatility. You should expect periods where these stocks underperform.
You should expect scary headlines and market corrections. The key is not reacting to short-term noise. Second, do not try to time the market. No one consistently times the market successfully. If you believe in these companies for the long term, the best time to invest is now. Waiting for a better entry point usually means missing out on gains.
Third, consider dollar cost averaging. Instead of investing a large amount all at once, invest smaller amounts regularly over time. This smooths out volatility and prevents you from investing everything at a market peak. Fourth, reinvest dividends. Microsoft and Alphabet pay dividends. Amazon and Nvidia do not currently, but might in the future.
Reinvesting dividends compounds your returns over time and takes advantage of temporary price declines. Fifth, do not check your portfolio every day. This is probably the hardest advice to follow, but it is some of the best. Checking prices constantly creates anxiety and encourages trading. Over 20 years, the daily price movements are meaningless noise.
What matters is business performance over time. Let me close with a broader perspective on what is happening with artificial intelligence and why I believe so strongly in this opportunity. We are at the beginning of a technological revolution that will transform every industry on earth not just technology companies.
Every industry, healthcare, transportation, manufacturing, agriculture, education, entertainment, finance, everything. I will make workers more productive. It will automate routine tasks. It will enable new products and services that we cannot even imagine today. It will solve problems that seemed unsolvable.
It will create new problems that we will need to solve. It will change how we work, how we learn, how we communicate, how we live. The companies that provide the infrastructure for this transformation, that build the platforms that AI runs on, that control the data that AI learns from, that design the chips that power AI computation, these companies will capture an enormous share of the value created.
Not all of them will succeed equally. There will be surprises. But as a group, infrastructure companies will do well. I have been building technology for over 40 years. I have seen many technology cycles come and go. The PC revolution, the internet, mobile computing, cloud computing, AI is bigger than all of them.
It is more transformative, more fundamental, more pervasive and it is just getting started. The investors who recognize this opportunity and position themselves appropriately will build generational wealth. The investors who dismiss AI as hype, who wait too long to invest, who chase the wrong companies, they will miss out on one of the greatest wealth creation opportunities in human history.
I want to share one more perspective that most people overlook when thinking about AI investments. The concept of compounding advantages in technology. Advantages tend to compound over time. A company with better AI gets more users. More users generate more data. More data makes the AI even better, which attracts even more users.
This flywheel effect means that early advantages become insurmountable over time. Think about what this means for the four companies I have discussed. Microsoft is already integrating AI into products used by hundreds of millions of people. Every interaction generates data that improves their AI. Every improvement makes users more dependent on Microsoft products.
The flywheel is already spinning. Amazon's AWS is already running AI workloads for hundreds of thousands of companies. Every workload generates insights about how to optimize their infrastructure. Every optimization makes AWS more attractive for AI workloads. The flywheel accelerates. Google has been running this flywheel for two decades with search.
Now they are doing it with AI. Every AI generated answer generates feedback. Every piece of feedback improves the AI. Every improvement makes Google search more valuable. The flywheel that built Google into a trillion dollar company is now being supercharged with AI. And my company's flywheel might be the most powerful of all.
Every chip we sell gets used by developers. Every developer builds software optimized for our chips. Every piece of software makes our chips more valuable. Every increase in value drives more chip sales. The ecosystem compounds on itself. This is why I believe these four companies will continue to dominate not just because they are big today but because their advantages compound over time.
The rich get richer in technology and these are the richest companies in AI. I also want to address the question of what could go wrong because no investment is without risk and you should understand the risks before you invest. The most significant risk is regulatory intervention. Governments around the world are becoming more concerned about AI.
They might impose restrictions that slow down AI development. They might break up large technology companies. They might require AI systems to meet certain safety standards that slow innovation. This is a real risk that could affect all four of these companies. Another risk is the possibility that AI development hits a wall.
Current AI systems have impressive capabilities, but they also have significant limitations. If it turns out that we cannot make AI systems much more capable than they are today, the growth expectations embedded in these stock prices might not be realized. I do not believe this will happen. I believe AI will continue to improve rapidly.
But it is a risk you should consider. There is also execution risk. Large companies sometimes fail to capitalize on opportunities even when they have all the advantages. Microsoft missed mobile. Google has failed to monetize many of its innovations. Amazon has had numerous failed ventures. Just because these companies are well positioned does not guarantee they will execute well.
Management matters and management can make mistakes. Finally, there is the risk of unforeseen competition. Technology history is full of examples of dominant companies being displaced by startups. with better technology. IBM dominated computing until Microsoft displaced them. Microsoft dominated until Google displaced them in internet services.
Google might be displaced by someone we have never heard of. The specific companies that win over 20 years might not be the ones I have named. But here is my response to these risks. Over a 20-year time horizon. I would rather own companies with strong competitive positions facing these risks than own companies without competitive positions trying to navigate the same environment.
Risk is unavoidable. The question is whether the potential reward justifies the risk for these four companies. I believe it does. Let me also discuss something that many investors fail to appreciate about AI investing. the importance of staying invested through volatility. These stocks will not go up in a straight line.
There will be corrections. There will be years where they underperform the broader market. There will be scary headlines about competition or regulation or technology failures. The investors who panic and sell during these periods will miss out on the long-term gains. I have lived through multiple technology cycles.
I have seen my company's stock drop by 50% or more on several occasions. Each time, investors who sold locked in their losses. Investors who held on, or better yet, bought more, were rewarded when the stock recovered and went to new highs. The same pattern will play out with AI stocks over the next 20 years.
This is why I emphasize the 20-year time horizon, not because that is how long it will take to see returns. You might see excellent returns in 5 years or 10 years. But because thinking in 20ear terms changes your behavior. It helps you hold through volatility. It helps you avoid selling at exactly the wrong time.
It helps you benefit from the compounding that only happens when you stay invested. I have told you the four companies I believe are best positioned. I have explained the framework I use to evaluate AI investments. I have shared my perspective on why AI is so transformative. I have discussed the risks and the importance of staying invested through volatility.
Now the decision is yours. What you do with this information, whether you act on it or not, that is up to you. But 20 years from now, I believe we will look back at this moment as the beginning of something extraordinary. The companies that provide the infrastructure for artificial intelligence will have generated trillions of dollars in value.
The investors who recognize this opportunity early and position themselves appropriately will have built generational wealth. The question is whether you will be part of it.
Comments 0