Why I Think It’s Time to Bet on AI and Tech

This blog post is aimed at novice investors who are interested in investing in AI, robotics, and technology. Now might just be a great time to start. I try to include some helpful advice and paint a picture of the dynamics currently at play but…

Disclaimer: This blog entry represents my personal opinions, is for informational and entertainment purposes, and should not be interpreted as professional financial advice. I am not an investment analyst and have no qualifications in this area.  Always perform your own research and consider speaking to a financial consultant before making any investment decisions.

Approaching Superhuman Artificial Intelligence

As you probably know, AI technology is rapidly improving. Large language models (LLMs) are making incredible strides every month. Even two years ago, large language model were effectively an archived compression of the collective intelligence of the human species. But today, with the new bells and whistles, access to a state-of-the-art LLM is like having a thousand experts in your back pocket. Right now, this chatbot phase is more of a convenient novelty. But the form factor is changing. In a few years autonomous AI agents will be automating the entire economy.

I believe that now is not the time to buy that new car or to remodel your house. Now is the time to take liquid cash and place it in the market. Keep in mind that if you save that money now, rather than spending it on a new car, what you saved could be worth vastly more in just a few years. Not only that, but the quality of future cars will be much higher and the cost cheaper. This is because, as production lines become more automated and artificial neural networks streamline processes, the savings accrued from these efficiencies will be passed on to consumers. Also, let’s not forget that superintelligent AI will likely be capable of creating much more interesting products. Why indulge in mediocre luxuries now if you can wait and spend your dividends on cheaper and vastly more quality products in the near future?

Even finance professionals don't seem to be recognizing this. If you have your money managed by a large investment group, they are not currently recommending that their clients reallocate their portfolios toward tech. For example, services like Schwab Private Client continue to advise customers to focus on the same broad market sectors they emphasized 20 years ago. I believe this is mostly because they don’t have an insider’s perspective.

 

AI systems are now being trained to control computer systems using the keyboard and mouse. This training is rapidly improving their ability to navigate windows and use multiple apps to perform real computer work. These systems are also now “thinking” and “reasoning,” meaning that they can take a prompt from a human user and generate a large document (that the user never sees) to prompt itself to consider the users intent and think through the issues involved step by step to expand and refine the concepts it considers when generating its final response for the user. This self-prompting process is used to guide the AI through a chain of thought, allowing it to accomplish increasingly complex tasks. This is already allowing these systems to perform long time-horizon tasks, such as projects that might take a human hours to complete.

 

Relatively soon, there will be a tremendous number of expert, genius agents, that will be accomplishing tasks, assignments, projects, and the work of whole organizations. Soon after, they will work in groups to accomplish great scientific and technological feats too difficult for humans. This includes replacing human jobs, enhancing their own software and hardware, automating manufacturing processes, mastering quantum computing, curing human diseases, extending human longevity, and much else. The next section will discuss that it is likely that the companies already involved in this will continue to be involved.

 

 

Why The Biggest Companies May Be Good Gambles:

 

 

The companies that may be the best bets in the tech sector are the largest ones. Why? Because they are already established and thus are likely to be the ones distributing AI during the coming intelligence explosion. In other words, even if state-of-the-art AI foundation models continue to be open sourced (made free), they will still have to be hosted and made available to users. The major tech companies like FAANG (Facebook, Apple, Amazon, Netflix, and Google) and the magnificent seven (Apple, Amazon, Alphabet, Microsoft, Meta Platforms, Nvidia, and Tesla) are poised to do this.

 

Long-term the entire stock market may consolidate into just a handful of companies that become much more valuable than the rest because, once guided by superintelligence, only a few companies are needed to solve the world’s problems and provide services and products. Thus, the inefficiencies of capitalist competition may make many companies obsolete. This suggests to me that people should invest in the major AI players.

 

Now there will be many small startup companies with new ideas and tremendous potential for growth. But remember that most of them will fail and the few up-and-comers that succeed will just be acquired by major tech firms anyway. This is called elite power consolidation, and it is something you want to keep in mind when choosing investments. However, this does not necessarily mean that we should not include smaller players in our portfolios, because they will likely be absorbed by the larger ones, rather than being driven to bankruptcy. A good way to do this may be to buy ETFs focused on AI and technology because they offer diversified exposure.

 

I believe that a major reason to invest in big tech is because these companies are working on the computronium problem. This means they are trying to find how to arrange matter to be as efficient as possible at computation. Computronium is a theoretical concept describing a material optimized for maximum computational efficiency, and it represents an ultimate ambition in AI and computing. Companies that make computer hardware are trying to determine how to cheaply make powerful chips and processors. This is the problem that will dominate the next few millennia and perhaps will dominate the rest of time. Major tech companies are at the starting line for this important race.

 

I believe that one of the things we’re going to see is that these companies’ offerings are going to work and interact with each other synergistically. For example, Elon Musk’s companies will complement each other giving him major advantages. His AI company (XAI) will take advantage of the exclusive data coming from his other ventures, including Tesla self-driving data, Starlink data, Twitter data, and SpaceX data. Thus, these companies will benefit from, not just economies of scale, but also synergistic effects between their specializations. All the large tech giants are set up this way. Meta will continue to leverage the data they generate from Instagram, Facebook, and the Meta Quest to make more advanced AI systems. All this may be especially true for Google.

 

 

Why Might Google Be a Good Stock Pick?

 

Google may have several advantages. Google is one of the only groups training large models that isn't beholden to Nvidia because it already produces its own custom AI chips called TPUs (tensor processing units). Google invented the AI system that this whole AI wave has been surfing on called the Transformer architecture. Transformer is the “T” in GPT. They also invented the mixture of experts (MOE) model, that most transformer-based LLMs now use. After faltering a bit, Google currently has the most performant AI LLM called Gemini 2.5 Pro. Google is currently gunning for the AI enterprise space, and they are scrambling to create effective agents to do your job for you. I’m writing this blog using a free platform called Google Blogger which I have enjoyed and taken advantage of for over 13 years. Google has an incredible list of solid products that are highly productive and widely used. You have probably heard of or used many of them:

 

Google Search, YouTube, Waymo, Google Books, Deepmind, Gmail, Google Ads, Waze, Google Maps, Google Earth, Google Photos, Google Drive, Chrome browser, Chromebooks, Chromecast, Google Assistant, Google Chat, Google Pay, Google Play, Gemini, Bard, Nest, Fitbit, Android, Google Reviews, Pixel, Google Scholar, Google Translate, YouTube Music, Google Lens, Google Colab, Vertex AI agent builder, Universal sentence encoder, Tensor Flow, Google’s office suite (docs, sheets, slides, etc.), and many others

 

Google claims to have the best infrastructure for AI. I think they may be right. They are very forward thinking. Its deep investments in machine learning and huge army of Ph.D. researchers have placed it at the forefront of the AI platform shift. When Google‘s original founders created Google books many years ago, they were originally scanning books from all over the world to archive them to train future artificial intelligences. Of course, they are doing similar far-sighted planning now. Google truly has an overwhelming infrastructure advantage and this is not likely to change. 

 

Not everyone agrees with me though. This recently released projection for the most successful businesses by 2030 doesn’t even include Google in the top 30. Why? It might be due to the fact that AI is eating search (Google’s main service). People won’t need to use Google internet searches if AI can do a better job of informing them and answering their questions, and they certainly won’t have to go through Google to access it. Google has been my number one stock pick for at least seven years, now I am not so sure.

 

 

Here are the internal rate of returns (IRRs) implied by the list above. The IRRs for the biggest tech companies (The Mag 7) are single digit. This is clearly at odds with my argument above that the biggest companies will capture much of the AI growth. Honestly, I don't know what to think, but it is still clear to me that tech is where we want to put our money.

What about Nvidia? Nvidia has a significant moat with CUDA, it’s proprietary software for managing graphics and AI software workloads. Because of its size and complexity, humans will not be able to develop software that can compete with CUDA anytime soon. However, it’s possible that an AGI could write new code that completely mimics or even improves on CUDA. Thus, AI itself could significantly undermine Nvidia’s advantage. However, remember that no AI written code can mimic the large physical infrastructure of major tech companies. Rather, that code will be funneled through it.

 

Next, let’s talk about Open AI. They make my chatbot of choice, ChatGPT. But, in many ways, Google, Meta, Microsoft, and XAI are far ahead of it. Open AI mostly just makes large language models, and the newest models from China and others are cheaper and nearly as performant as GPT models. Essentially, the models themselves are becoming commoditized. But again, the major tech companies like Tesla and Google have more than code. They produce self-driving cars, robots, social media platforms, and much more. Youtube and Twitter may be the most important data sets on the planet. But, Open AI is not yet prepared to make a foray into social data, robotics, or vehicle manufacturing.

 

Are Tech and AI Stocks Undervalued?

 

Many investors believe that the major tech companies are promising AI technologies that are actually years or decades away to artificially inflate their stock prices. The term for this on Wall Street is irrational exuberance. Major companies like Microsoft have towering capital expenditure this year. They have put this money toward research and development for large language models and yet many people are claiming that there is no transformative application and there may not be one. Critics see unfounded market optimism without a basis in fundamental economic realities.

 

It is very difficult to out predict the stock market. The Efficient Market Hypothesis (EMH) posits that asset prices always reflect the information available, making it impossible to consistently "beat the market."  Because prices are believed to be "fair" and reflect all knowledge, it's extremely difficult to foresee nonrandom patterns that the rest of the market has missed. But it is also true that investing generals wage the previous war and that regular investors exhibit herd behavior. However, I think the market is wrong, that major tech companies are undervalued, and that very few people fully appreciate the law or accelerating returns (LOAR) that applies to human-equivalent technologies. Better-that-human AI agents, their recursive self-improvement, and the synergy between information processing technologies is understated.

 

I would go as far as saying that the market is currently deluded into assuming that LLMs are not transformational. Those that disagree with me correctly recognize that some LLM responses are unhelpful, that LLMs have blindspots, and can make irrational mistakes and flat out hallucination (confabulations). It is true that there are still some questions that are simple for humans to answer that LLM’s fail at. But all this will be moot in the next few years.

 

Some market forecasters see the buzz in AI as akin to 3D movies, NFTs, crypto and VR. But these analysts don’t have an insider’s view. They have the view of an expert in economics, meaning they prioritize financial trends from the past. In my opinion, fictional technofuturism will be more useful in predicting the financial outcomes of artificial intelligence. We did not even have large language models just a few years ago, and now they are passing the bar exam, medical licensing exams and saturating every benchmark put before them. The doubters on Wall Street are why investing in AI is not yet saturated. And I think you and I can take advantage of that.

 

Conclusion and Some Stock Picks

 

The final perspective I want to leave you with is that of an automation engineer. These are IT professionals who utilize computer programs to automate specialized information processing jobs for companies. They spend weeks or months setting the system up and ensuring that it will works as intended. It can take a long time to test the code and line up all the duck before hand. However, when they finally turn it on, and the automation gets underway, it does an incredible amount of work all at once. Often, these engineers set the system loose overnight and come back in the morning to find that everything has been completed. It can be anticlimactic, because at that point, there is nothing left to do. That is what our economy is gearing up for, total automation.

 

Because AI is about to be able to perform human jobs, this exponential improvement that has been confined to computation is finally about to become coupled with the economy. It will be optimizing operations, reducing costs, and creating new markets and services. In a rapidly advancing technological world, not investing at this time could mean falling behind the global market, and after things take off, it could make it impossible to catch up.

 

Please take my advice with a grain of salt. I could be wrong about the major tech companies being highly overvalued.  We have to remember how companies like Cisco were buoyed up by the Internet bubble and that when the bubble burst, the value of Cisco stock declined drastically. Before investing, it's crucial to conduct thorough research and consider your investment goals, risk tolerance, and time horizon.

 

Keeping all of this in mind here are some tech companies that may be poised to take advantage of the coming technological tsunami.

 

 

The Major Players?

 

Google (GOOG)
Microsoft (MSFT)
Meta (META)
Amazon (AMZN)
Nvidia (NVDA)
Tesla (TSLA)
TSMC (TSM)
Apple (AAPL)
AMD (AMD)

 

 

Other Promising Companies

 

Adobe (ADBE)
Alibaba (BABA)
Arista (ANET)
Astera Labs (ALAB)
Broadcom (AVGO)
Cisco (CSCO)
Cloudflare (NET)
Datadog (DDOG)
Disney (DIS)
Eli Lilly (LLY)
General Electric (GE)
IBM (IBM)
Intel (INTC)
Micron Technology (MU)
Netflix (NFLX)
Oracle (ORCL)
Palantir (PLTR)
Qualcomm (QCOM)
Samsung (005930.KQ) [Korea Exchange]
SK Hynix (000660.KQ) [Korea Exchange]
Sony (SONY)
Symbotic AI (SYM)
TenCent (TCEHY)

 

 

 

Promising Tech ETFs

 

ARK Autonomous Technology & Robotics ETF (ARKQ)

Fidelity Select Technology Portfolio (FSPTX)

First Trust Nasdaq Artificial Intelligence and Robotics ETF (ROBT)

Global X Artificial Intelligence & Technology ETF (AIQ)

Global X Robotics & Artificial Intelligence ETF (BOTZ)

Invesco Technology Fund (ITYAX)

iShares Exponential Technologies ETF (XT)

iShares Robotics and Artificial Intelligence ETF (IRBO)

ROBO Global Robotics & Automation Index ETF (ROBO)

Roundhill Generative AI & Technology ETF (CHAT)

T. Rowe Price Science & Technology Fund (PRSCX)

WisdomTree Artificial Intelligence and Innovation Fund (WTAI)

 

 

 

Previously Foundational Holdings

 

BRK/B

COST

FNDA

FNDE

FNDF

FNDX

IWM

IWR

PFXF

QQQ

SCHE

SCHX

SCITX

TFIFX

TMO

VEA

VGT

VLEIX

 

 

 

I recently took a course with the “Great Courses” entitled Understanding Investments. I took copious notes. Allow me to leave you with what I think is some of the best investment advice for beginners.

 

Best Investing Advice Condensed:

Start Early: Begin investing as soon as possible to maximize the benefits of compound interest. Even small, consistent investments can grow significantly over time.

Diversify Your Portfolio: Avoid concentrating all your funds in a single investment. Spread investments across various asset classes (e.g., stocks, bonds, real estate) and sectors to mitigate risk.

Set Clear Goals: Define your investment objectives (e.g., retirement, home purchase, education) and tailor your strategy to your timeline and risk tolerance.

Understand Your Risk Tolerance: All investments involve risk. Assess your comfort level with potential losses. Younger investors might tolerate more risk, while those nearing retirement may prefer safer investments.

Do Your Research: Thoroughly investigate any asset before investing. Understand its mechanics, growth potential, and associated risks. Avoid investing based solely on rumors or tips without proper due diligence.

Consider Low-Cost Index Funds and ETFs: For long-term investors, low-cost index funds (available as mutual funds or Exchange-Traded Funds - ETFs) offer broad market exposure with minimal fees.

Avoid Timing the Market: Predicting market fluctuations is extremely difficult. Focus on a long-term investment strategy rather than trying to buy low and sell high repeatedly.

Utilize Dollar-Cost Averaging: Invest a fixed amount regularly, regardless of market conditions. This strategy can reduce the impact of volatility and mitigate the risk of poorly timed investment decisions.

Rebalance Your Portfolio Periodically: Review your investments regularly and adjust your asset allocation to maintain your desired balance as your circumstances or market conditions evolve.

Maintain an Emergency Fund: Before investing, especially in riskier assets, ensure you have an emergency fund covering 3-6 months of living expenses. This prevents needing to sell investments during downturns to cover unexpected costs.

Invest in What You Understand: While trendy investments can be tempting, it's generally safer to invest in industries and businesses you are familiar with, enabling more informed decisions.

Stay Patient and Disciplined: Markets experience ups and downs. Maintaining discipline and patience, avoiding emotional reactions to short-term fluctuations, is crucial for long-term success. The stock market is wealth transfer from the impatient to the patient. Time in the market beats timing the market.

Consider ETFs: Studies consistently show that low-fee index funds and ETFs tend to outperform most actively managed funds over the long term. Consider funds tracking broad indices like:

·       S&P 500 (Examples: VOO, SPY)

·       Total U.S. Stock Market (Examples: VTI, ITOT)

·       Total International Stock Market (Examples: VXUS, IXUS)

·       Total U.S. Bond Market (Examples: BND, AGG)