The confidence has been selected for. You can train a model to always carefully claim that what they say may or may not be true, but that may not necessarily m

The confidence has been selected for. You can train a model to always carefully claim that what they say may or may not be true, but that may not necessarily make them easier to work with. IIUC what we're missing right now is the ability for the model to get a good estimate of how confident they _should_ be. This can be done "externally" or "internally". Doing it externally would mean: make the model not directly stream its train of thought directly to the end user but instead use it first to produce a query info some system that can help it weigh its confidence factor. Then a se and run on that output and its previous output can reformat the answer to be more balanced. Doing it internally would require this process to be part of the incremental output token production. I don't know about the field to know whether that's even doable and whether we have some progress on that front