Comment on Selfhosted & AI
midribbon_action@lemmy.blahaj.zone 23 hours agoOK, but still, just a clarification like “I’m not buying nor will I ever buy nvidia chips, now here’s a thing I made with ai…” is enough context, in my opinion. Just blindly saying “ai is good for this” is promoting the bubble, as the vast vast majority of llm users are running nvidia chips.
Also, whatever financials you showed to convince them it was a good investment, whatever type of business it is, I think it was bullshit. I haven’t seen any proof of efficiency gains at any company rollout of ai, certainly not on macs. Most companies are currently pulling back on token usage is my understanding. ROI has been unmeasurable so far. At best, you informed your clients explicitly this was a highly speculative purchase and may not benefit them.
curbstickle@anarchist.nexus 22 hours ago
Thats certainly a take.
I don’t show financials or propose these decisions, I get paid to design and sometimes implement.
As far as whether or not its a benefit, I’m going to have to completely disagree. As I previously mentioned - its a tool. They are great at detecting potential security issues in code data extraction and classification (especially with unstructured or poorly structured sources, like PDFs), knowledge base searches (especially where that knowledge may be spread across multiple internal sources like a wiki, memos, miscellaneous docs, etc), doc review for tone to meet standards, etc.
Your statement that it essentially doesn’t pay to use llms is intrinsically tied to the OpenAI/MS/NVidia/Anthropic/etc “everything can be done with AI now!” marketing nonsense just the same as believing it has payoff for all scenarios. You recognize the “all uses are good uses” as being complete bs, but you’re jumping to “that means no uses are good uses”.
And that is decidedly not true.
The best example is that data ingest I mentioned. I had a client looking to bring in a bunch of differently formatted forms to a database. What they had been doing was taking their regular employees who handle these forms and using them for data entry - a pretty poor use of their time.
Instead, these scans were evaluated by a tuned model specific to their needs. Each form has a unique ID (though the way it could be numbered was very different), which then gets assigned to one of these folks for review at ingest. They are given a new unique number, and a verification flag (3 stages - first employee review, second employee review, and final import acceptance) which was basically the same flow as the previous setup.
The difference is that each person didnt need to hunt across the form to find the details. When the comparison comes up for approval at each stage, they get the snippet being brought in and the field its being applied to. It can be approved for that field, sent back for reevaluation, or sent for human only review (often this is because the scan sucked).
The project took less than 10% of the original timeframe, and the people handling the forms (and previously assigned for ingest) didn’t end up with the stupidly increased workload that originally got assigned.
Again, using a tool at what its good for is what’s important. Using it for what you think that it can do (ie: the executive method) is just piss poor practice due to easily convinced c suite who gobble up marketing nonsense.
midribbon_action@lemmy.blahaj.zone 22 hours ago
I don’t think you need hardly any hardware to do ocr. USPS started doing reliable ocr on 80s hardware. You really think an ai cluster is necessary for that?
Anyways, cool anecdote, not an actual financial study or report, and very long-winded honestly.
curbstickle@anarchist.nexus 22 hours ago
OCR <> data ingest
OCR wouldn’t work, as I mentioned, because of the varying structures of the forms.
I’m sorry my answer was too “long winded” for you, I was trying to be informative, but clearly you aren’t interested in that. Enjoy your day.
midribbon_action@lemmy.blahaj.zone 21 hours ago
Don’t think that’s true. You can run the whole form through, come out with an identical pdf with searchable/copyable text. Even a completely novel form uses the same alphabet. Add some regex to pull out the fields you need to enter, and on failure give it to a human. All of that can be done with python on a raspberry pi. A decade ago.
github.com/ocrmypdf/OCRmyPDF