alt Hacker Newswhen you say fine-tuning skills or talent are scarce, do you have specific skills in mind? perhaps engineering for training models (eg making model parallelism work)? or the more ML type skills of designing experiments, choosing which methods to use, figuring out datasets for training, hyperparam tuning/evaluation, etc?
The technical parts are less common and specialized, like understanding the hyperparameters and all that, but I don't think that is the main problem. Most people don't understand how to build a good dataset or how to evaluate their finetune after training. Some parts of this are solid rules like always use a separate validation set, but the task dependent parts are harder to teach. It's a different problem every time.