The Artificial Intelligence Bubble and assumptions around LLMs

[...]

Guessing the next word without understanding the meaning of the resulting sentence makes unsupervised LLMs unsuitable for high-stakes tasks. The whole AI bubble is based on convincing investors that one or more of the following is true:

I. There are low-stakes, high-value tasks that will recoup the massive costs of AI training and operation;

II. There are high-stakes, high-value tasks that can be made cheaper by adding an AI to a human operator;

III. Adding more training data to an AI will make it stop hallucinating, so that it can take over high-stakes, high-value tasks without a "human in the loop."

These are dubious propositions. There's a universe of low-stakes, low-value tasks – political disinformation, spam, fraud, academic cheating, nonconsensual porn, dialog for video-game NPCs – but none of them seem likely to generate enough revenue for AI companies to justify the billions spent on models, nor the trillions in valuation attributed to AI companies [...]