I don't mind people doing blog-posts advertising they're own companies - but I feel like i'd like a little bit more substance within this topic. It is interesting in a way, I find I turn to things like gemini 2.5 within simple OCR/NLP and now more substantial image editing than specific models.
I think that's more because of the current state of the industry, a lot of those models are either internal, paywall locked or annoying to use. I don't want to waste effort in trying to sign up for a 4 week trail of X service to perform a one off task.
Unfortunately, this post didn't really elucidate or go into an interesting topic within this space.
I'm not expecting a research paper, but it would be great to get some stats, graphs, examples and meat on the bones. I opened this up expecting some actual examples of problems within OCR & NLP and showing how X multi-modal model solves them.
Really looking for something we can run locally in terms of OCR LLM, I think a lot of people doing a lot of OCR and document extraction aren’t looking to upload every file into the cloud and the use is more narrow than typing into a chatbot.
While Gemini is nice, it would be nice to have a pipeline that works locally on a reasonably RAM’d unified memory Mac or Framework AMD board.
OCRs don't hallucinate outputs = if it says "212.99mm" on architecture diagram it doesn't suddenly turn into "2413m" on the other end, because LLM thought this feels better. I remember reading on HN where that was happening in a such case (but sadly my google foo fails me to find a link)
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[ 2.4 ms ] story [ 28.3 ms ] threadCurrent 80/20-rule-ignoring AI dogma in a nutshell.
And I assume the multimodal tools still use OCR for text extraction, or am I missing something?
My understanding is that they're still doing OCR+NLP, just differently than traditional approaches.
I think that's more because of the current state of the industry, a lot of those models are either internal, paywall locked or annoying to use. I don't want to waste effort in trying to sign up for a 4 week trail of X service to perform a one off task.
Unfortunately, this post didn't really elucidate or go into an interesting topic within this space.
I'm not expecting a research paper, but it would be great to get some stats, graphs, examples and meat on the bones. I opened this up expecting some actual examples of problems within OCR & NLP and showing how X multi-modal model solves them.
While Gemini is nice, it would be nice to have a pipeline that works locally on a reasonably RAM’d unified memory Mac or Framework AMD board.