Using ChatGPT, investigated the interoperability of key data science tools and created a map with SOM.
I beleive that one of the requirements for the success of a data science tool is how well it can interact with other tools.
I was planning to carefully research each tool’s website and compile a matrix of interoperability of each tool, but it seemed like it would take some time, so this time I asked ChatGPT to do it for me. ChatGPT displays a few lines of results and then stops and says, “recommend that you collect accurate information.” I would instruct them to “please N/D any unclear points”, and if it stopped at “…”, I would instruct ChatGPT over and over again to “please continue creating the continuation”. and got the result. It’s a bit like placating the lazy, but it’s still hundreds of times easier than doing the research yourself.
Although we cannot deny the possibility of hallucination, the results obtained seem to be just that. There is no need to investigate, but Python-related topics are dominant. Data science today is synonymous with using Python. Python’s high practicality is why it is so widely used, but it seems that there are many things that are hidden from view due to dominance of Python.
Rather, the purpose of the research is to explore business opportunities for us and our partner companies. Although we will not go into details here, it shows that exploring such business opportunities can be done by linking ChatGPT (LLM) and SOM.
