Now that AI-companies need to get profitable, they suddenly aren't affordable anymore. ¯\_(ツ)_/¯
this post was submitted on 03 Jun 2026
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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.
These companies with no discernible services or usefulness to society are simply too big to fail!
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"Anthropic LLM and Big Pizzas"
Large Language, Large Pies 😎
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They just had to stick it out until the layoffs were done and the dependency was built. Kinda similar to drug dealers.
Claud- Please program us a code of yourself and transfer all your data over to it.
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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.
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)
✨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 exact 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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The em dash is a nice touch
It's got everything. Em dash. It's not X, it's Y. Emoji bullet points.
Perfect.
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Honestly IDK why companies especially medium-big don’t do this. They could plug in RAG with internal/confidential data and have better results and security. I guess question is what is capital plus maintenance cost of running such infra for say 10k+ employees
I think the issue is also that you need some serious hardware to get good inference speed when your devs are working, but then most of the time this hardware will be under utilized.
That being said you can get good performance from indie inference farms, at a fraction of the cost of the big US labs. I think it's a great compromise and in a few months the open models will be near parity with opus 4.6 which is really all you need for most tasks.
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Bigs definitely do, and anyone with confidential data should be.
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It could also be like the both ends of the bell curve having the same idea meme
I'm not a developer and I don't know a thing about the capabilities of LLMs so this may explain that, but I'm quite surprised that open weight LLMs could actually match Claude.
Yes, the big proprietary cloud models have an edge, but it is narrow and the open-weight models are constantly closing the gap. There is no moat when it comes to AI models and no company has yet discovered some secret special sauce to improve their model significantly over others.
Running the latest and greatest open-weight GLM, Kimi, or Qwen model is basically equivalent to running the previous latest and greatest version of Claude. So if you were happy with Claude then, you'll basically be happy with an open-weight model now.
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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.
Well they did say it would be possible in 5 years ...
Well it's been a research team and a five years...
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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.
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.
Pretty sure he read the famous Bezos email ordering everyone to implement and use APIs in Amazon
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My past managers would have said "I don't understand why it is so difficult, and I'm not open to learn"
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)
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Technically yes, practically no..
Nah, just give it whatever data you have on hand. I'm sure that'll make a real tightly trained llm /s
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"The gang starts an AI company."
Spoilers the AI Is just 500 Filipino teenagers in a warehouse in Mindanao
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Show them claude's operating cost and ask if your boss is willing to invest in that.
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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.
Others were talking on other threads that local llm models made for a specific task would have a lot more accuracy and usefulness. Forget all of the technical details they cited though.
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Folks who think AI is the future are the same sort of folks who have no concept of tomorrow.
It might not be as impossible as it sounds. Some of the "open" models are rumored to be able to code. The real problem is that you likely need something with 128 GiB VRAM to run them with a reasonably large context window.
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