LLMs: The End of OCR as We Know It?
From the 1870s Optophone, a reading machine for the blind, to today's OCR, document processing has come a long way. Yet, challenges remain due to the complexities of human writing habits. Traditional OCR struggles with non-standardized documents and handwritten annotations. However, the advent of multimodal LLMs like Gemini-Flash-2.0 is changing the game. Leveraging the Transformer architecture's global context understanding and vast internet training data, LLMs can comprehend complex document structures and even extract information from images with minimal text, like technical drawings. While LLMs are more expensive and have limited context windows, their advantages in document processing are significant, promising a solution to document processing challenges within the next few years. The focus will shift towards automating the flow from document to system of record, with AI agents already proving helpful.