Chatting about ChatGPT

Every once in a while, something comes along that makes everyone pause, take notice, and ask: is this the next big thing? Will this change the way we operate everyday life and disrupt industries, society, and maybe even financial markets as we know them? Self-driving cars, space travel, and robots are just a few of the technologies we’ve been expecting to mature and change society for the past few years. But who would have thought an enhanced chatbot could generate as much buzz? ChatGPT-3 has ignited a debate on everything from the future of education to the future of work. Is this latest example of artificial intelligence evolutionary or revolutionary? Should we fear for our jobs? And what investment opportunities does it present?

We ask and answer five key questions around AI and chatbots, in as human a way as possible…and no, we didn’t ask ChatGPT (but we probably could have!).

What is ChatGPT?

ChatGPT-3 is a chatbot developed by OpenAI, a US-based artificial intelligence research lab. It’s part of a broader family of artificial intelligence tools called large language models (LLMs). These are systems that understand and can generate text in an entirely familiar, human way.

LLMs use enormous amounts of data. ChatGPT-3 ingested content from books, academic papers, and the entirety of Wikipedia. The system takes all this information and learns to predict the next word in a sequence of text. So if I said “I hear the dog…”, you (and ChatGPT) would likely respond “barking.” This combination of a vast amount of ingested content and massive computing power resulted in a model with 175 billion parameters, making it one of the largest language models ever created. Parameters in large language models are essentially the values that the model is solving.

With minimal training, LLMs can complete sentences, translate a foreign language, summarize information from a multitude of sources, and generate content ranging from technical answers to humorous vignettes. We’re not sure if ChatGPT actually has a sense of humor, but it does tell some pretty funny jokes.

All kidding aside, one near-term use case is in internet search. Microsoft, which is an investor in OpenAI, is integrating ChatGPT into its Bing search engine. The use of a large language model enables more complex and more natural searches and extracts deeper meaning and better context from source material. This is ultimately expected to deliver more robust and useful results.

Ultimately, we see ChatGPT and other large language models as engines that will eventually power human interactions with computer systems in a familiar, natural, and intuitive way.

Is it the only player in town?

While ChatGPT has captured press headlines and consumers’ enthusiasm, there are a number of other large language models in use at scale today. Alphabet, the holding company for Google, and Meta Platforms (fka as Facebook) have their own large language models, and there are a good number of open-source LLMs. ChatGPT is differentiated by its size, with at least twice as many parameters as its next closest competitor.

Is it coming for our jobs?

Probably not. Every wave of new and disruptive technology has incited fears of mass job losses due to automation, and we are already seeing those fears expressed relative to AI generally and ChatGPT specifically. There are certainly historical cases of job displacement due to new technology adoption. We’re sure 1908, the year Henry Ford rolled out the Model-T, wasn’t a good year to be a buggy whip maker. But 1964, the year IBM introduced its first mainframe and the six decades that have followed have been good years to be information workers despite the widespread concerns at the time over computers taking office worker jobs. History shows that technology of any sort ultimately makes productive workers more productive and is net additive to employment and economic growth.

How big is the opportunity?

The broad AI hardware and services market was nearly USD 36bn in 2020, based on IDC and Bloomberg Intelligence data. We expect the market to grow by 20% CAGR to reach USD 90bn by 2025. We see strong interest from enterprises to integrate conversational AI into their existing ecosystem.

Our estimate may prove to be conservative. Growth in LLMs and other generative AI technologies could be even faster than we expect given advancements in machine learning and deep learning capabilities. Additionally, we think the early success for chatbots could drive attract more technology talent, and drive faster adoption by enterprises and governments.

How to invest?

We see artificial intelligence as a horizontal technology that will have important use cases across a number of applications and industries. From a broader perspective, AI, along with big data and cybersecurity, forms what we call the ABCs of technology. We believe these three major foundational technologies are at inflection points and should see faster adoption over the next few years as enterprises and governments increase their focus and investments in these areas.

Outside of publicly traded equities, investors can also consider opportunities in private equity (PE). We believe the tech sector is currently undergoing a new innovation cycle after 12–18 months of muted activity, which provides interesting and new opportunities that PE can capture through early-stage investments.

Co-authored by Kevin Dennean, Technology & Telecom Equity Sector Srategist

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