Description
Large Language Models (LLM) change the way how we write scientific image data analysis code. In this talk we will discuss the current state of the art, learn about benchmarks in this domain and open questions, e.g. in the context of reproducibility and transparency of the code-generation process using LLMs. We will see multiple human-computer-interfaces in action that facilitate how data scientists analyse bioimaging data using LLM-generated code.
