I think that one of the most incredible datasets anyone could make would be for a Polars Dataframe library (the extremely efficient training dataset by converting some of the SQL or Pandas datasets.

Data processing is such a huge part of the AI process and depending on how you look at it, extremely expensive or a huge opportunity to reduce costs in both compute and time. The performance improvements that Polars brings to data preparation are simply incredible.

However, since the library is still relatively new and evolving, it's really poorly understood by nearly all of the models, especially building performant custom expressions. I would happily chip in to a project that built a large training dataset that can help us fine-tune efficient data processing LLMs.