java-snapshot-testing VS llm-classifier

In this PoC I will use origin-energy/java-snapshot-testing and as stated in "the testing framework loved by lazy productive devs" I use it whenever I find myself manually saving test expectations as text files 😅

We do this for the null hypothesis - is uses an LLM to bootstrap a binary classifier - which handles null easily

https://github.com/lamini-ai/llm-classifier

LLMs introduced zero-shot learning, or “prompt engineering” which is drastically easier to use and more effective than labeling data.

You can also retrofit “prompt engineering” onto good old fashion ML like text classifiers. I wrote a library to do just that here: https://github.com/lamini-ai/llm-classifier

IMO, it’s a short matter of time before this takes over all of what used to be called “deep learning”.