To systematically analyze and fix LLM errors, think of the process in terms of classic ML error analysis.
Hopefully all this will become less needed as the chatbots internalize various strategies for doing work and for evaluating themselves for errors.
That seems to be the direction that the industry is taking.
In my experience few shot examples along with tuning temperature parameter in chatgpt API will help to consistently give less erroneous predictions.
I second that. Few-shot examples can really take you far, especially with Gemini.
Is this an AI-generated or -assisted article?
No. I like to write my own words.
Hopefully all this will become less needed as the chatbots internalize various strategies for doing work and for evaluating themselves for errors.
That seems to be the direction that the industry is taking.
In my experience few shot examples along with tuning temperature parameter in chatgpt API will help to consistently give less erroneous predictions.
I second that. Few-shot examples can really take you far, especially with Gemini.
Is this an AI-generated or -assisted article?
No. I like to write my own words.