[Jugurtha]

When I was in EE at university, I worked on heart anomaly detection and multi-phase flow classification for oil & gas. The papers I was reading used synthetic data with a nice noise dust sprinkled on it. Meanwhile, I worked on data from hospitals acquired on restless, sweaty, hairy, dudes with rusty, banged up electrodes and abused probes.

Needless to say, the data I saw on these papers looked nothing like the data I worked with, whether from hospitals or what I saw at Schlumberger in the Sahara.

The real world tends to be ... interesting.

[cpard]

That makes sense, do you think LLMs have or can potentially change that and end up having more realistic synthetic data than what you've seen in the past? I guess the data you were working were more like time series data but still if an large language model can be perceived as a universal approximator of some sort, might be able to generate more realistic synthetic data than the approach you described with the noise dust sprinkled on data.