There really is no difference. Either there is utility or there isn't. "Fake" intelligence that produces results is just something that does not make any sense.

There really is no difference. Either there is utility or there isn't. "Fake" intelligence that produces results is just something that does not make any sense. LLMs may be worse but Humans confidently state something they are uncertain about all the time lol. Maybe not experts in general but then that's still comparing LLMs to a small percentage of humanity. At any rate, Unlike many seem to think, The issue is not in fact the lack of ability to distinguish truth and fact from fiction. Turns out being able to distinguish the two and having the incentive to communicate that are 2 different things. GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r https://imgur.com/a/3gYel9r Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975 https://arxiv.org/abs/2305.14975 Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334 https://arxiv.org/abs/2205.14334 Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221 https://arxiv.org/abs/2207.05221 The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets - https://arxiv.org/abs/2310.06824 https://arxiv.org/abs/2310.06824