ChatGPT produces made-up nonexistent references
This is called "hallucination" and I find it to be the biggest flaw with GPT-3 interfaces like ChatGPT. Basically, the system will start convincingly BSing at any point and as a user, you're never sure if any particular detail it outputs is actually correct. The problem is, these large language models are inherently kind of a black box, so how do you fix this kind of behavior?I started looking and it turns out that OpenAI is keenly aware of the hallucination problem, and even wrote about how they're correcting for it in this blog post about InstructGPT: https://openai.com/blog/instruction-following/To summarize: it seems OpenAI is addressing this by taking human-labeled output data from GPT and feeding this into new models, using a reward function to train the future models to behave with less hallucination. This way of working struck me as a mix of software engineering and crop breeding.They discuss the trade-offs involved with doing this. The "hallucination" effect is probably one of the features that make GPT so creative.