Skill issue. I used AI to create a web application that extracts the serial number from an image into text. This allows us to just simply take a picture rather than than having to type the serial number manually while using a magnifying glass. Significantly speeding up the process and lowering error rate.
You could’ve just looked for off the shelf OCR software and it would probably be better, no LLM needed. OCR has been around for far longer than the current LLM bubble.
Yea you could argue semantically that using an LLM to turn text in an image into machine readable format falls within “Optical Character Recognition”. I was referring specifically to OCR algorithms like Tesseract (pytesseract) and EasyOCR.
No. There’s nothing to argue there, it’s the definition of OCR.
Also, do you believe that LLMs found a new, novel way of doing OCR? That’s not how they work, LLMs don’t invent, they don’t innovate, they’re simply unable to do that. What they do, when they work correctly, is that they use already known and established techniques and tools. So to quote your top comment in this chain:
OCR is a very, very old AI system that for decades we’ve scanned documents and saved to pdf with. The old system is far from perfect, but it does work well enough in most cases. If an AI recognition model can do the same job with less mistakes, that is an improvement.
Skill issue. I used AI to create a web application that extracts the serial number from an image into text. This allows us to just simply take a picture rather than than having to type the serial number manually while using a magnifying glass. Significantly speeding up the process and lowering error rate.
You could’ve just looked for off the shelf OCR software and it would probably be better, no LLM needed. OCR has been around for far longer than the current LLM bubble.
No, I tried OCR and it was less accurate.
You’re reading text from a picture. That is OCR.
Yea you could argue semantically that using an LLM to turn text in an image into machine readable format falls within “Optical Character Recognition”. I was referring specifically to OCR algorithms like Tesseract (pytesseract) and EasyOCR.
No. There’s nothing to argue there, it’s the definition of OCR.
Also, do you believe that LLMs found a new, novel way of doing OCR? That’s not how they work, LLMs don’t invent, they don’t innovate, they’re simply unable to do that. What they do, when they work correctly, is that they use already known and established techniques and tools. So to quote your top comment in this chain:
indeed, anyone with skills would have whipped that up in noetime without AI… or use any of the many apps that already do that
For real, you can copy text out of images on most modern phones so this isn’t really an issue anymore
Yea, you can do that, but have fun doing that 1000 times a day. Manually copying was the problem, I created a system that automated that process.
Ok but how does the phone extract the text? The fact that a modern phone can do it does not mean there’s no AI involved
OCR is a very, very old AI system that for decades we’ve scanned documents and saved to pdf with. The old system is far from perfect, but it does work well enough in most cases. If an AI recognition model can do the same job with less mistakes, that is an improvement.
Then why was I the one to do it if anyone could have done it?
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If I have a low ability in that specific area then why was I able to achieve success?