A trick with iterative prompting teaches you how to ‘tame’ it

Large Language Models (LLM) often make mistakes? Don’t panic, there’s a solution!

Although Large Language Models (LLM) perform impressively, providing accurate information is a challenge. Where does the problem lie? It turns out that LLMs may become overly confident when faced with simple prompts, leading to inaccurate results.

New iterative prompting to ‘tame’ these LLMs. Just like solving a problem step by step, this method can refine model responses and improve accuracy.

How about that? Doesn’t it seem magical?

Limitations of Simple Iterative Prompting

Iterative prompting sounds a bit sophisticated, but it’s actually a way to make our artificial intelligence smarter.

How does it work? It’s by giving AI small hints, allowing it to continuously improve its previous answers, becoming more and more accurate.

For example, if AI initially guesses the temperature in Beijing to be 15 degrees, but we know it’s very cold in Beijing during winter, we could remind AI to think again, and it might then…