In this context, "loop closing" likely refers to a method of addressing or resolving issues or gaps in a process or system. The speaker seems to be expressing frustration about a perceived lack of a method to counter misinformation or falsehoods when it comes to Language Model (LLMs) efficiency."""
So, same inference I made from the context (alone it sounds like citogenesis but the context suggests the opposite), and same lack of specific detail.
"A method". Yes, great, what is it?
Me: why did the commenter use the term “loop-closing”?
ChatGPT: The commenter used the term "loop-closing" to emphasize the concept of a feedback mechanism that corrects or validates information. In systems theory and engineering, a "closed loop" system is one where the output is continually fed back into the system as input for self-correction and optimization. This term is metaphorically applied here to describe a process where information is constantly reviewed and corrected, forming a self-regulating cycle.
In the context of Wikipedia, this loop-closing happens through community edits and oversight, where incorrect information is often quickly corrected by other users. The commenter is highlighting the absence of a similar, effective mechanism in Large Language Models (LLMs) to automatically correct or verify the information they produce. This comparison underscores a concern about the potential for LLMs to disseminate incorrect or misleading information without an inherent system for checking and correcting it. The choice of "loop-closing" as a term is to draw attention to this systematic difference in information validation between platforms like Wikipedia and LLMs.
That's why I used triple quotes around the block: https://chat.openai.com/share/cd5c8e5e-5925-46f8-8873-6e75c5...
As it happens, I just watched some of the OpenAI developer day videos, and they do talk about connecting the models with more traditional search engines/databases/API calls to a similar end.