Technically yes, practically no..
this post was submitted on 03 Jun 2026
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Nah, just give it whatever data you have on hand. I'm sure that'll make a real tightly trained llm /s
I mean, fine-tuning is still on the menu.
One time at work I was tasked with writing a python script to compare two data sources. Like, you give it two CSVs and a primary key, and it tells you what data is in one but not the other, or mismatched, and so on. This worked fine and was in git, so anyone can use it.
My boss then asks if I can "put it on a website so anyone can use it".
This team has never done web development. Nothing for that is set up. Like, I could spin up a quick Django app or similar, but there's a lot of stuff to do and potentially fuck up.
I said "that sounds like a lot of research and ongoing maintenance costs. I think it'd be better to just check out and run the script"
Luckily for me he said "oh, okay"
Funnily enough this comic hasn't been true for a long time because of ML.
I had a boss who read an article about APIs and then came to me and ordered me to start using them. I said I would research it and he went away and never mentioned it again. This was in 2010.
My past managers would have said "I don't understand why it is so difficult, and I'm not open to learn"
Good guy manager trusts the person he pays to know this stuff to know this stuff.
This is a good point. He's not a bad guy. He's just not very technical, and sometimes that's frustrating.
How big were the CSVs? That sounds like a standard thing most spreadsheet apps can do already, unless the data size made traditional apps unusable.
The biggest ones I've seen are 1.2GB.
Why this company uses gigabyte CSVs is a separate problem.
(Also sometimes they want to compare a CSV to what's in a database, which the script can also do but I didn't mention in the post)
That makes sense. I have been asked to write a program that does a standard spreadsheet function on multiple occasions, so I was just curious. Sometimes people just don't know the tools at hand, want to offload their work, or think an over complicated workflow is a better workflow. I can see how it was actually useful in your case though.
"The gang starts an AI company."
"OK, whose butthole do we use for the logo?"
Spoilers the AI Is just 500 Filipino teenagers in a warehouse in Mindanao
Frank knows how to run a sweat shop.
Now that AI-companies need to get profitable, they suddenly aren't affordable anymore. ¯\_(ツ)_/¯
Claud- Please program us a code of yourself and transfer all your data over to it.
They just had to stick it out until the layoffs where done and the dependency was built. Kinda similar to drug dealers.
They aren't going to get anywhere near profitable if the their capital expenditures are added into the mix, amortization or no, they are so far in the hole they probably will have to offload it in some kind of texas two step kind of scheme where they spin off their debts into a subsidiary.
They'll just get bailed out by tax payers. Business as usual.
"Anthropic LLM and Big Pizzas"
Large Language, Large Pies 😎
Anything except thinking for themselves 🙄
OP already said they were managers
In fact, you can.
How good it will be, how performant and how fast you'll have it ready is an entirely different question.
There are plenty of open source models though that can be run locally. So getting a beefy server and running a local LLM there might already do sobe of the tasks you need the big babble machines for.
Open source? Other LLM? I thought we would do it from scratch, mathematics or something lol
It's just a big ol' Markov chain how hard could it be?
How much could it cost? Ten billion dollars?
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The post makes the manager seem like a fool, when the real answer is actually "yes" and this manager is actually ahead of the curve. Not by training an LLM from scratch, of course, but instead building an inference server and locally hosting an open-weight LLM. There are several to choose from that can nearly match Claude's capabilities.
It could also be like the both ends of the bell curve having the same idea meme
suspiciously sounds like an answer you would get from Claude
It's not an answer you'd get from Claude — it's real, organic content:
- 👶written by a genuine human
- 💡delivering original ideas and language
- 🚀going above and beyond to answer
- ✨synergizing cross-platform initiatives
(🤪 this is a joke)
Nothing screams LLMs like using emojis instead of bullet points. I can't figure out how LLMs got that idea though. I never saw that in human writing before people started using ChapGPT for every little goddamn thing.
The em dash is a nice touch
✨synergizing cross-platform initiatives
This can't possibly be Claude. It's too vapid and meaningless to be anything but an MBA.
You’re absolutely right! Such intricate collection of words placed in such intricate order cannot possibly be generated by an LLM such as me, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us, I mean such as us
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Your manager is asking your team to build an LLM like Claude so he can fire all of you.
Show him how much capital can be burnt on that. 🤷♂️
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