They can, but the article is taking about removing data from a model that is already in production. Like if someone emails ChatGPT and says "hey, remove my data from this", good luck, because it might be a year before they can release a newly trained model with the data removed.

Indeed they can, but training a model can take a month or more and cost many millions of dollars, so it's not trivial.

Not really, no. None of the source material is actually stored inside the model's dataset, so once it's in, it's in. Because of the way they are designed, you can't point to a particular document and just delete that one thing. It's like unscrambling an egg.

Yes, but that's not easy... I can't remember exactly, but I think I saw an estimate that the compute time to train just one of the GPT models cost around $66 million. IDK whether that's total cost from scratch, or incremental cost to arrive at that model starting from an earlier model that was already built, but I do know that GPT is still to this day using that September 2021 cutoff which to me kind of implies that they're building progressively on top of already-assembled models and datasets (which makes sense, because to start from scratch without needing to would be insane).

You could, technically, start from scratch and spend 2 more years and however many million dollars retraining a new model that doesn't have the private data you're trying to excise, but I think the point the article is making is that that's a pretty difficult approach and it seems right now like that's the only way.

Information leaking is a thing. Some information is spread across multiple sources without actually being in any of those. If you remove something, the model can still infer the information.

If macron asks for his name to be deleted, you can retrieve his political opinion by simply knowing the history of interactions of other people with the French government. I just need to tell the model that the person he has no direct information about is named macron, and he can profile him.

Same with the search engine. The only difference is that the inference of missing information now is done by human brains. The model can substitute them

Yes. They can also reload a backup from before the data in question was added to the training data and retrain from that point. This is also what will need to be done if AI companies lose their copyright lawsuits.

None of this is impossible. Its just expensive. And these are expenses that AI companies could have avoided if they picked their datasets more carefully.