Investment Opportunities in AI Agents

Every so often, certain technological advancements reshape our world and create unprecedented investment opportunities. These opportunies have the potential to generate astronomical returns for early investors. If you were around during the early days of the internet and were able to recognize the transformative power and potential of what it meant to be able to theoretically connect every man, woman, and child to the same network via computers, then you could have built an immense amount of wealth by investing even a small amount of money in the companies, both new and established, that would profit from this new technology.

One of the most prolific advancements in technology is Generative AI (Artificial Intelligence). When OpenAI's ChatGPT came on to the scene in November 2022, it took the world by storm. All of a sudden, business leaders were throwing money and resources into investigating how this new technology could be leveraged within their companies. While there are many, many articles out there right now about the investment opportunities in companies that either build or use Generative AI, I'm going to dig a bit deeper into the concept of AI Agents. AI Agents just might be the next transformative use case for Generative AI and, if so, warrants some investigation into potential investment opportunities.

First, let's clear up some terminology when it comes to Generative AI, which is the foundational technology behind products like ChatGPT, and others.

Terminology

AI Model - a computational system designed to mimic human intelligence by learning from data to perform specific tasks or make predictions.

Generative AI - AI systems capable of creating new content, such as text, images, or music, based on patterns learned from existing data.

LLM - Large Language Model; an advanced AI system trained on vast amounts of text data to understand, generate, and manipulate human language.

ChatGPT - A conversational AI model developed by OpenAI, designed to engage in human-like dialogue and assist with various tasks.

GPT-4 - One of OpenAI's Generative Pre-trained Transformer models, known for its advanced language understanding and generation capabilities.

Prompt Engineering - The art and science of crafting effective input prompts to elicit desired outputs from AI models, particularly in natural language processing tasks.

AI Agents - Autonomous software entities that can perceive their environment, make decisions, and take actions to achieve specific goals.

When people say they're using ChatGPT at work, it may be that they're not really using ChatGPT itself but the underlying Large Language Model via a license or agreement to do so. Many public companies disallow the use of public interfacing applications like ChatGPT due to the risk of an employee entering proprietary or sensitive data into the model, which could feasibly be used to further train the model, leading to a leakage of company data. Instead, companies have agreements in place to leverage the underlying model, in the ChatGPT case, GPT-3.5 or GPT-4, through OpenAI's partner company Microsoft. Data that is passed to and from the model in this case is confined to the company and Microsoft with an agreement in place that stipulates the data is not be be used for training or fine-tuning of any other models.

AI Agents

AI Agents are built around the concept that these Large Language Models, or LLMs, can reason when given specific instructions to do so. Because they can reason, they can make decisions on behalf of a user. While the models themselves don't actually perform actions on behalf of a user, they can return in their responses the decisions / actions that should be taken based on the relevant context, or input. This means, if I pass data to an LLM with a list of choices to take, the LLM should respond with a choice (decision), and optionally a reason for making that decision. The code that calls the LLM can interpret the decision and invoke the appropriate action. The action might be to ask the user for more clarifying information, or to make a request to another data source, or to search the web. Either way, the code that is interacting with the LLM can carry out the actions based on the LLM's decisions. In this scenario, the LLM is the brain, and the code that is executing is the body with arms, legs, eyes, ears, etc. This whole construct is what makes up an AI Agent, which is a combination of an LLM (brain) and the code that has access to the outside world via 'tools', such as data APIs, databases, internet searches, knowledge bases, documents, etc.

The Opportunity

To understand why these AI agents represent such a significant investment opportunity, we first need to grasp what they do and why they're different from what has come before. At their core, AI agents are about automation, but not in the traditional sense of simply doing a task faster or more efficiently than a human. Instead, they're about understanding and interacting with data in fundamentally new ways. They can read, interpret, and even generate human-like text, make decisions based on complex datasets, and learn from their interactions. This isn't just automation; it's like having an infinitely scalable, never-tiring brain at your disposal.

Now, why does this matter for investors? Because the companies building or leveraging these AI agents are laying the groundwork for the next wave of technological innovation. They're not just creating new products; they're creating new markets and transforming existing ones. They could revolutionize everything from customer service and content creation to legal research and software development.

But here's the catch: investing in these companies requires a different mindset. It's not enough to look at traditional metrics like quarterly earnings or market share. Instead, investors need to think about potential: which companies are building technologies that could become foundational to multiple industries? Which ones have the vision to see beyond the current applications of AI to what might be possible in five or ten years?

This is where the real opportunity lies. The companies that are leading in AI today are not just selling software; they're selling picks and shovels for the next gold rush. And like the gold rushes of old, the rewards will be enormous for those who can identify the key players early on.

However, this doesn't mean throwing caution to the wind. Investing in AI requires careful consideration of the ethical implications and potential societal impacts. As AI agents become more powerful, issues around privacy, bias, and control become increasingly important. The most successful companies will be those that navigate these challenges thoughtfully, building trust as well as technology.

So how does one go about identifying these investment opportunities? Start by looking at the problems being solved. The most valuable AI agents will be those that address universal needs or unlock new capabilities across multiple sectors. Pay attention to partnerships and collaborations, as they can signal both the strength of a company's technology and its ability to integrate with existing systems and workflows. Which companies are deeply involved in the AI Agent space: Microsoft, Alphabet (Google), OpenAI, Meta (Facebook), Amazon, and of course, NVidia. Keep an eye on the broader ecosystem—regulatory changes, advances in complementary technologies, and shifts in consumer behavior can all impact the trajectory of AI development.

This is not a recommendation to buy stock in these companies but is a recommendation to research and monitor the progress that these companies are making in AI. The information provided regarding investing in any security is for educational and informational purposes only and should not be construed as financial advice. The statements made are not intended to be a recommendation to buy or sell any security or to invest in any specific financial product. Investment decisions should be based on an individual's own financial situation, goals, and risk tolerance. It is recommended to consult with a financial advisor before making any investment decisions.