- Participants debated the best way to extract structured data from PDFs: whether to feed raw PDF text to a CNN, render the PDF to an image and apply computer-vision techniques, or combine OCR with post-processing.  
- A hybrid pipeline was proposed: use OCR to locate text elements, then chain the actual PDF text found at those coordinates to avoid character-recognition errors.  
- justanotheruser reported that the hybrid approach still produced “a massive load of edge cases” on their dataset, suggesting the problem remains brittle in practice.  
- pasky argued that rendering the PDF to pixels and applying CNNs is “absolutely the right call,” but noted that open-source tooling in this space has lagged while commercial end-to-end solutions have advanced.  
- lsneff floated a pragmatic shortcut: run “shitty OCR” on the PDF and then pass the noisy output through GPT-3, asking the model to return a clean, labeled list of extracted items.