I've also read GPL code and that doesn't make anything I write GPL. It matters if the code was substationally copied or not.
So I think I would apply the same rules to AI. In general not all code produced is infringing on the copyright of all authors of training data. However there have been some clear cases of copying (GPL license text and a matrix multiplication routine for example) that do appear as copyright violations.
Imagine a model. It reads source code, and learns by heard how to execute it. Now you use that model to execute GPLed code + some changes to the code you instruct your model to also take into account. You don't need to adhere to the GPL license because your machine is merely "learning" not executing – Tadaa!
Truth is that the insight that there is no difference on data and program code in particular stands here. If the model can act on the code. It can be said to execute it.
Could you not say the same about a human? Also what you described is probably fine under the GPL because the input is source code which the users could view and edit (and if it’s not running locally the GPL doesn’t apply, only AGPL)
So I think I would apply the same rules to AI. In general not all code produced is infringing on the copyright of all authors of training data. However there have been some clear cases of copying (GPL license text and a matrix multiplication routine for example) that do appear as copyright violations.