Posted by theanonymousone 1 day ago
e.g. AI + a good database of what your company does seems like an excellent combination.
Although they may internally use LLM, I wanna say said they were not going to allow their core offering to be integrated with LLM
Although maybe they reversed course?
(yes yes RAG exists)
I remember this being done more than 10 years ago.
The other uses cases you describe also were being done. Of course with AI maybe it’s become easier and cheaper?
EDIT: The other activities, yes I think it made it cheaper and easier. They both required human intervention to make an accurate forecast or execution plan. Forecasting requires humans to do things like apply smoothing factors, identify abormal demand over huge datasets, or identify seasonal demand cycles, etc. Constraint scheduling requires a human to intervene in dispatching and resource allocation as well. AI can do 95% of the work with a proposal, or even control the process. Supposedly much better than historical algorithms. I haven't implemented this part of it, but I've seen it done.
The documentation part is much more robust. You can ask it complex questions, like "How do I setup a phantom blow-through part in a MS level 1 BoM?" and it walks you through the entire thing. With the sales suggestions, it can identify things like "The customer is buying spaghetti and pancetta" AI: "They are probably making carbonara, how about some garlic bread?"
Then take a photo of a document and throw it into ChatGPT, or Gemini, along with the word "Transcribe".
ChatGPT wins, by a landslide. BUT AI's advantage doesn't stop there.
"Take this picture of some idiot filling in form 49, I've also attached the PDF, fill in the PDF fields, provide a database record according to the schema attached and flag if there are any obvious problems with the entries".
That works too. "Produce a latex document of this kid's math homework and flag any problems" - works. "Produce a MS word document of this letter" - works. "Read this bill and produce a JSON version following the schema from this example" ... and so on and so forth.
More than that, it is starting to work pretty well with Gemma 31B local model (will still do 30 document analyses on cpu only, at Q4 on a DDR4 or higher machine. Yes it's mostly memory speed that matters) at this point. I mean, that's GPT 5.0 or so quality (95% correct with the occasional problem), but hey, Qwen 3.8 27B may be coming out next week ...
AI/ML yes, LLM's no (unless someone is naively using LLM's for forecasting)
Would love to hear how AI is going to help here. This is like a young engineer thinking the CDC machine they just bought, is going to make Airbus and Boeing obsolete...
I think that is one aspect but not the biggest issue.
The specific shape of data and shape of functionality gets built around for decades due to incompleteness of any system, expanding dependencies and changing business needs.
Decades of building around the system results in a mountain of work when trying to replace the system, typically a larger body of work than implementing the base system itself.
They’re a lot more than a data store or system whose primary value is ingesting info and producing reports.
For a lot of business, replacing the ERP is on par with replacing Excel. It’s not about getting the data into another system; it’s about all of the complexity and expertise required to use it.
Seriously, why the duck aren't they running their own AI systems in house???
“Under the policy, only Al-related hiring, customer-facing travel and trips directly linked to the company's Al initiatives or mission-critical employee Al training are exempt, reflecting SAP's focus on "be disciplined in how we spend" while expanding its Al capabilities.”
no-paywall: https://news.ycombinator.com/item?id=49222851
You can’t make this stuff up.
"No, kids, it means you will be eating less."