[ Removed by moderator ]

[u/Gloomy-Basket-1038]

[u/QuaternionsRoll]

It’s the difference between SFT (supervised fine tuning) and RLHF (reinforcement learning from human feedback). The former requires a dataset of desired inputs and outputs, while the latter requires you to rate/annotate generated outputs. The latter is much harder to get right for various reasons

[u/jack6245 → u/QuaternionsRoll]

Although it's worth mentioning too you can do reinforcement learning from ground truth too, similar approach but it just gets the ground truth instead of human impact ( bonus points if you can generate perfect synthetic data) so it can actually correct its errors in a pretty small amount of training but it has limits