Though it's worth mentioning that inference from context (which an LLM OCR tool is presumed to do) is precisely what a human transcriptionist does. This can re

Though it's worth mentioning that inference from context (which an LLM OCR tool is presumed to do) is precisely what a human transcriptionist does. This can result in "nonfaithful" reproduction where, say, a tyop in an original document is corrected, consciously or unconsciously, when transcribing. Taking into account both the local context (on a given page) and the larger context of a work (within a subject area, collection, etc.) I'd expect an AI-based OCR tool would behave similarly. For archival / academic work, what would be nifty would be a tool which would note the original text image context, a certainty probability score, and possible alternative transcriptions in cases of ambiguity. It's a nice idea to get humans in the loop, but realistically this simply won't always be possible, and it's helpful to think of what next-best approaches might be. It wouldn't surprise me if AIs turned out to be more generally reliable in such cases, though I would also expect some wild mis-fires and fumbles along the way.