Opportunities in AI
As you may know or will soon discover, artificial intelligence (AI) is transforming industries from healthcare to transportation to finance and many more...
“The global artificial intelligence market size is expected to reach USD 1,811.75 billion by 2030, expanding at a CAGR of 37.3% from 2023 to 2030, according to a new report by Grand View Research, Inc.” - Bloomberg.
Regardless of who does the research, there is one thing experts agree on: AI represents a massive and unique opportunity to get in on the ground floor of what many are calling the 4th Industrial Revolution.
There are multiple ways you can invest. Public companies or private companies. Company by company. Industry by industry. Individual stocks or baskets. Just investing in the S&P 500 will give you some exposure.
For more specific exposure, there are ETFs like BOTZ and IRBO which are baskets of public companies involved in AI, machine learning, and big data analytics. Then there are company by company investments in public and private markets.
You can to invest in SPY, IRBO, MSFT, NVDA, AMZN, or other publicly traded companies or ETF’s. We have all heard about OpenAI, but there are other lesser known competitors.
The most popular segment of the market in the last year has been “Generative AI”.
This is a massive and growing market. Many of these firms have raised at higher valuations since, but this is only touches on part of the opportunity. There are many categories and applications for AI, but 4 high level areas where I believe significant value will be generated.
?·??? Hardware: This includes the physical computing resources, such as GPUs, TPUs, servers, and edge devices, which are essential for AI model development and training. (Think Nvidia, Intel, AMD.)
?·??? Hosting: Refers to the hosting environment for AI models. A spot where the hardware referenced above “lives”. This can be on cloud platforms, on-premises servers, or within containers. This category covers the infrastructure needed to develop, deploy, and run AI models. (Think traditional hosting players like AWS, Azure, and Google, or AI specialized hosting companies like CoreWeave.)
?·??? Language Models (LLMs): Encompasses pre-trained models, custom-trained models, and API services that provide natural language processing and understanding capabilities. These models are crucial for applications that involve text and language and leverage the hardware and hosting services referenced above. (Think the LLM’s that power OpenAI’s ChatGPT, Anthropic’s Claude, or Cohere’s LLM built with a focus on enterprise.)
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·??? Software Applications: Represents the end-user applications that leverage AI models. This includes integrations with AI models, real-time processing of data, and user interfaces that allow users to interact with AI-powered features. This is the application that the end-user interfaces with and leverages all of the technology and infrastructure referenced above. (Think ChatGPT, GitHub Copilot, or Midjourney.)
There will be a tremendous amount of innovation across all of these areas.
Experts point to ChatGPT’s public launch as the “moment” for AI. This happened less than a year ago.
Since then, there has been an explosion in activity and funding. With an expectation for the second half of 2023 to outpace the first half.
Potential end-user applications are massive and meaningful across most industries.
For example:
The opportunities and applications are vast. CB Insights goes a bit broader...
Please let me know your thoughts, your interests, how you think about the space, and what opportunities are interesting to you.
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