How Generative AI is solving document understanding problems that OCR and NLP couldn't crack for 150 years
By
universesquid
Baker's choice. Dense with flavour, light on filler.
Summary
The article discusses how traditional OCR and NLP-based document understanding systems (like Tesseract and Abbyy) have struggled for over 150 years to reliably extract text from human-written documents. It contrasts this with the recent breakthrough of Generative AI models (like GPT-5 and beyond), which are now solving document understanding problems that legacy IDP (Intelligent Document Processing) stacks could never handle well, particularly with messy, irregular, or human-written documents.
Key quotes
· 4 pulledThe first idea resembling something like the idea of OCR got developed in 1870 as a reading machine for the blind - the Optophone.
150 years of research, engineering breakthroughs and hundreds of IDP products later we were finally able to scan a receipt and have the fields be filled out - if it looked nice and friendly enough to the OCR model.
Unfortunately for Tesseract, Abbyy and co. they suffer from the complication that documents are written by humans.
The stack that for decades provided document understanding is now losing against Generative AI.
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