Teaching machines how to “think” has been a tantalizing goal since the early days of computing, and recent advances in generative AI have brought us closer to achieving it. However, whether AI-generated “buy/sell/hold” signals can be used for investing is partly a question of whether the value outweighs the risk. One only needs to read a few passages of AI-written content to notice that it is a simulacrum. When asked to write an essay, the program may line the words up, but the text may lack humour, nuance or deeper insight. It can struggle to solve simple math problems. Sometimes, the model will even come up with an excuse to avoid doing what you asked. Missing the mark can be harmless and amusing if nothing is at stake, but investing based on unverified AI input or output presents a real problem.
The generative AI revolution
Of course, much of the buzz around AI stems from the release of ChatGPT in 2022. Under the hood, the original ChatGPT used a variant of a large language model called GPT-3.5, which was trained on a dataset containing hundreds of billions of words collected from the internet. One particular strength of generative large language models is their ability to summarize long blocks of text. As an example of how this could help investors, the model could parse lengthy regulatory filings for critical information that a human could overlook. A less obvious but more intriguing possibility is for the model to distill that summary into a rating or other quantitative metric.
Perhaps surprisingly, given its apparent capabilities, the model is trained only to predict the next word in a sentence as accurately as it can. Though complex in the details, the training itself amounts to having the model guess the next word, checking how big of a mistake it made, and adjusting some of its billions of model parameters (“neurons”) so it makes a smaller mistake in the future.
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