I don’t understand why if common usage of such terms is fine and even desirable in daily context, the same terms should not be used in scientific communication. If people are unclear or ambiguous, then of course that’s undesirable and should be corrected, however, if certain terms are fully clear within their context then I don’t see the harm of the same term having a different meaning in the study of cognition and a different meaning when the term is used in the context of the analysis of an ML algorithm. The whole field is called machine “learning” after all.
Re:Talking About Large Language Models
by gillesjacobs on Sunday December 11, 2022 @07:51AM
(#33942728)
For scientific papers, it is required to be specific and precise with terminology. Everyday communication affords more liberties and leeway.
For the journal paper genre which is highly technical, more specific and appropriate terminology is always available that sidestep the whole issue.
I name my bots and machines and of course in daily discussions the loaded words ("thinking", ""believing", "meaning", "knowing") are used. Simulating any human behaviour will elicit a sympathetic response, especially if it has utility to the user. But in the context of peer-review of scientific engineering papers that is inappropiate.