[blt]

My pet peeve is when AI researchers coin new terms for objects that can be described by well-established mathematical terms. For example, saying a neural network layer has "256 units" instead of "output dimensionality of 256".

But at some point you need to name things for brevity. I understand why people say "activation function" instead of "elementwise monotonic nonlinear function".

Misuse is also rampant, like using "inference" to describe evaluating a neural network on an input, even when the NN isn't part of a probabilistic model.

[mdp2021]

To be fair, give high degrees of interdisciplinarity and imperfect acquaintance with all the terminologies (and imperfect memory), and given that we mix natural language and conventional technical language, and with some continuity, and given that natural language itself mixes original core root meanings and posterior conventions, and given that even biologically the best term may be occasionally (polysense) hard to find, the mess is expected.