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cheschire | on: 25 Years of Eggs
Absolutely loved the article, the process, and the results. Hated the price.

You could pay a human to read receipts, 1 every 30 seconds (that’s slow!), $15/hr (twice the US federal minimum wage!), plus tax and overhead ($15x1.35) comes out to $20.25/hr over 5 hours. $101 all in.

Sure, sure, a human solution doesn’t scale. But this sort of project makes me feel like we haven’t hit the industrialization moment that i thought we had quite yet.

PaulHoule | parent | next
My wife complains about people complaining about the price of eggs every time the subject comes up because it's her duty as a housewife to know about the price of all the protein sources and they are still a bargain -- who'd have thought that the price of transcribing the receipts would be seen as even more onerous?

Receipt scanning OCR has been around for a long time. Circa 2010 I ran enough HITs on Mechanical Turk [1] that I got my own account representative at AWS and I wondered what other kind of HITs other people were running and thought I would "go native" and try making $100 from Turk.

I am pretty good at making judgements for training sets, I have many times made data sets with 2,000-20,000 judgements; I can sustain the 2000 judgements/day of the median Freebase annotator and manage short burst much higher than that with mild perceptual side effects.

I gave up as a Turk though because the other HITs that were easy to find was the task of accurately transcribing cell phone snaps of mangled, damaged, crumpled, torn, poorly printed, poorly photographed or otherwise defective receipts. I can only imagine that these receipts had been rejected by a rather good classical OCR system. The damage was bad enough I could not honestly say I had done a 100% correct job on any single receipt, as I was being asked to do.

[1] in today's lingo: Multimodal with prompts like "Is this a photograph of an X?" and "Write a headline to describe this image"

knollimar | parent | next
There's no way there wasnt a more efficient way of doing this. Way too many tokens per receipt.

I'd wager gemini flash could get decent results. Id be willing to try on 100 receipts and report cost

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stavros | parent | next
One issue is that the human was less accurate than the LLM. The other is that the author probably didn't pay $1,500 for this, they probably paid $20 on a subscription.
moron4hire | parent | next
You're counting just the egg-having receipts, but there were over 11 thousand receipts they had to go through to get to that 500-ish subset. I'm assuming OP wanted to process all of the receipts and then selected just eggs for a simple analytics job. With your rates, the human would cost almost $2000.
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N_Lens | parent | next
AI has some weird unexpected uses that haven’t been fully uncovered yet, while it fails to scale or match the needed accuracy on expected usecases.
qoez | parent | next
Imagine how many 2001 era eggs he could have bought with that $101
wolfram74 | parent | next
I mean, at over 1000% the cost, the machine solution doesn't scale either?
ProllyInfamous | root | parent | next
Not yet.

>>So I told Codex “we have unlimited tokens, let’s use them all,” and we pivoted to sending every receipt through Codex for structured extraction. From that one sentence, Codex came back with a parallel worker architecture - sharding, health management, checkpointing, retry logic. The whole thing. When I ran out of tokens on Codex mid-run, it auto-switched to Claude and kept going. I didn’t ask it to do that. I didn’t know it had happened until I read the logs.

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For anybody still thinking my goodness, how wasteful is this SINGLE EXAMPLE: remember that all of the receipts from the article have helped better-train whichever GPT is deciphering all this thermalprinting.

For a small business owner (like my former self), paying $1500 to have an AI decipher all my receipts is still a heck of a lot cheaper than my accountant's rate. It would also motivate me to actually keep receipts (instead of throw-away/guessing), simply to undaunt the monumental task of recordskeeping.

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>>But the runs kept crashing. Long CLI jobs died when sessions timed out. The script committed results at end-of-run, so early deaths lost everything. I watched it happen three times. On the fourth attempt I said “I would have expected we start a new process per batch.” That was the fix ... Codex patched it, launched it in a tmux session, and the ETA dropped from 12 hours to 3. Not a hard fix. Just the kind of thing you know after you’ve watched enough overnight jobs die at 3 AM.

>>11,345 receipts processed. The thing that was supposed to take all night finished before I went to bed.

cheschire | root | parent
I think at a certain scale we're talking about switching to local trained models which don't have the same operating costs as running a frontier model for OCR. That would reduce the ongoing costs significantly. Might take longer than 30 seconds to read each receipt if you run multiple passes to ensure accuracy, but could run 24/7/365 without the same tax and administration overhead of humans.

Spherical cows aside though, I do agree with you that I should not consider scalability as a given.

wolfram74 | root | parent
I suppose if we had access to a public data set like this receipt bank, programmers could time themselves setting up a solution with off the shelf OCR algos. If they could clock in at under 10 hours they could advertise themselves as being "just as good as an LLM, but significantly cheaper." Downside for the managerial class that wants generative algos for the complete lack of legal protections.