Most things that I could talk about were already addressed by other users (specially @OttoVonNoob@lemmy.ca), so I'll address a specific point - better models would skip this issue altogether.
The current models are extremely inefficient on their usage of training data. LLMs are a good example; Claude v2.1 was allegedly trained on hundreds of billions of words. In the meantime, it's claimed that a 4yo child hears something between 45 millions and 13 millions words through their still short life. It's four orders of magnitude of difference, so even if someone claims that those bots are as smart as a 4yo*, they're still chewing through the training data without using it efficiently.
Once this is solved, the corpus size will get way, way smaller. Then it would be rather feasible to train those models without offending the precious desire for greed of the American media mafia, in a way that still fulfils the entitlement of the GAFAM mafia.
*I seriously doubt that, but I can't be arsed to argue this here - it's a drop in a bucket.