Using GPT-4 fine-tuning to generate data explorations

We (a small startup) have recently seen considerable success fine-tuning LLMs (primarily OpenAI models) to generate data explorations and reports based on user requests. We provide relevant details of data schema as input and expect the LLM to generate a response written in our custom domain-specific language, which we then convert into a UI exploration.

We've shared more details in a blog post: https://www.supersimple.io/blog/gpt-4-fine-tuning-early-access

I'm curious if anyone has explored similar approaches in other domains or perhaps used entirely different …

data datascience domain expect fine-tuning generate gpt gpt-4 language llm llms openai openai models reports schema small startup success