To be more charitable to TFA, machine translation is a field where there aren't great alternatives and the downside is pretty limited. If something is in another language you don't read it at all. You can translate a bunch of documents and benchmark the result and demonstrate that the model doesn't completely change simple sentences. Another related area is OCR - there are sometimes mistakes, but it's tractable to create a model and verify it's mostly correct.
LLMs being applied to everything under the sun feels like we're solving problems that have other solutions, and the answers aren't necessarily correct or accurate. I don't need a dubiously accurate summary of an article in English, I can read and comprehend it just fine. The downside is real and the utility is limited.
LLMs being applied to everything under the sun feels like we're solving problems that have other solutions, and the answers aren't necessarily correct or accurate. I don't need a dubiously accurate summary of an article in English, I can read and comprehend it just fine. The downside is real and the utility is limited.