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Putting Andrew Ng's OCR models to the test
’s OCR Models to The Test Today, Andrew Ng, one of the legends of the AI world, released a new document extraction service that went viral on X (link here). At Pulse, we put the models to the test with complex financial statements and nested tables – the results were underwhelming to say the least, and suffer from many of the same issues we see when simply dumping documents into GPT or Claude.
At Pulse, we put the models to the test with complex financial statements and nested tables – the results were underwhelming to say the least, and suffer from many of the same issues we see when simply dumping documents into GPT or Claude. With probabilistic LLM models, each extraction introduces a new chance for error, and these probabilities compound across thousands of documents, making the failure rate unacceptably high for real-world applications where precision is non-negotiable. If your organization processes financial, legal, or healthcare documents at scale and needs complete reliability (or really any industry where accuracy is non-negotiable), we'd love to show you how Pulse can transform your workflow.
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