Another way to overcome an LLM’s limitations, beyond just increasing the size of the model, is to provide a step-by-step solution of a problem within the prompt, a technique known as chain-of-thought prompting. Empirical studies have shown that this approach can give an LLM such as GPT-4 a newfound ability to solve more varieties of related tasks. It’s not exactly clear why, which has led many researchers to study the phenomenon. “We were curious about why it’s so powerful and why you can do so many things,” said Haotian Ye(opens a new tab), a doctoral student at Stanford University.
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