I have used this small R package that allows you to read the text content of a PDF and send it to a local llama model via ollama or one of the large LLM APIs. I could use that to get structured answers in JSON format on a whole folder of papers, but the context length of a typical model is only long enough to hold a single (roughly 40-page) paper in the memory. So I had to get separate structurer answers on each paper and then generate a complete summary from those. Unfortunately that is not user-friendly yet.
I know Python, R, the STATA ado-language (a horrible proprietary progamming language), MATLABs language, Javascript and some minimal C++. What I know really well though is R and Python. So typical profile for a (data) scientist.
Stuttgart has a few nice Art house cinemas. One is in an older building and has some nice retro vibe to it with it’s old sign from the 60s. The other is newer and has better equipment. Both have a really chill atmosphere and a good programme of movies
Wouldn’t porn have a clear bias due to selection issues, if fake moaning is more common in porn than in real live? Then again gathering experimental data would have an experimenter demand issue. Just imagine you are a participant in the natural human sex sounds study. Hard to imagine that you do not take that consciously into account.