Earlier quoted context omitted.
what would be required for trusting an LLM? 1: 100% transparency. Open Source code, fully (and correctly) attributed training data. 2: A predictable model of what these models are actually encoding (so that hypothetical new models (or modifications) can be reasoned about).
Transparency won't help a lot from a technical standpoint (seems more like a solution to a legal issue than a technical one). I can't trust LLMs because they just...recombine text by probabilities and aren't deterministic. I get incorrect information every time I ask them a thing, and it's incorrect in different ways every time. The only things they seem to get consistently correct are very widespread facts that are…
If you care about veracity then image generation works about as well as text. Frequently you can find details of the image that are just bizarrely wrong, such as hands or food or other basic things. It's the same basic problem: there's no intelligence behind what it's doing, it just regurgitates mostly realistic-seeming pixels that are pretty good at fooling the casual viewer.
Really, it's like those moths with eyespots on them: good at fooling the brain's heuristics but obviously not real.