Any particular case where one would want to use a FS where it's not recomemded to use more than 80% disk/pool capacity and encryption has side effects?
10GB, 1TB, 100TB? Memory mapping or does it need to fit into memory (RAM, VRAM?)? Is streaming supported - can I point to a 100TB dataset and cruise through it? 1 parquet file or parquet dataset? What about Delta lake? Are outliers drawn or are you doing some sort of sampling/smoothing?
Also would be great to have some comparison to similar tools in this space e.g. https://github.com/finos/perspective and HvPlot+Datashader.
Not sarcastic. Imagine a LLM fine tuned on your country's accounting standards, legal and tax docs. Instead of paying sbdy 250/h you can now just type "eli5 can I apply for a tax relief for R&D I'm doing in my company".
There's really no way back. AI is today helping design chips (check Google's report on how they use it for their own designs), drugs etc. And having a LLM connected to a simplistic enterprise app is a money printing machine. Really is a new ind revolution. And it's held back by not enough infra and power.