https://lab.enverge.ai/b200-challenge/ - making high-end compute available to a few researchers, who are conscious about the impact of data centers on climate and local communities.
Readit Newstudorizer commented on Ask HN: What Are You Working On? (December 2025) · Posted by u/david927
I'm working on something that proves to be more ambitious than initially thought:
pure Python notebooks + zero-emission GPUs + git = https://lab.enverge.ai
Currently struggling with an experiment where DeepSeek-R1 is being overly verbose.
tudorizer commented on Periodic Table of Cognition kk.org/thetechnium/the-pe... · Posted by u/garspin
There's a smell of pseudo-science here. That weird blend of interesting + plausible with sprinkles of heavy-handed parallels.
After "Isaac Newton, who may have been the smartest person who ever lived" the level of trust fell drastically.
Sure, the periodic table was extremely useful and we were using electricity before we understood it, but we understand LLMs far better, mostly because they are our own creation.
Maybe the lines between exploration, creation and discovery are fuzzy sometimes, but this article tips over into AI propaganda.
tudorizer commented on Units of Economics of LLMs. Reply to Ed Zitron's "AI Is a Money Trap" · Posted by u/tudorizer
The piece isn't an independent analysis as the author has an obvious interest in Zitron being wrong. In fact, the piece closes off with a nice marketing self-plug. But that aside, the author doesn't actually refute Zitron's points. One of the main argument is "the comparison with Netflix is wrong", which doesn't prove anything in itself; and then tries to show that inference is profitable. Though just as in their baker analogy, you must factor in all other costs, including training new models. Worthless marketing plug.
Well ... what is independent analysis? The author is not a reporter, but someone who understands business principles.
I think you got the causality the other way around here.
tudorizer commented on Units of Economics of LLMs. Reply to Ed Zitron's "AI Is a Money Trap" · Posted by u/tudorizer
I would say this article is very shallow. Zitron criticizes what he calls the AI bubble from multiple angles, it's not just "they will never be profitable" — and I agree this would be a wild claim. Even in the worst-case scenario where AI is a giant con, as Zitron paints it, they might just become profitable if they can con enough people. I also don't expect people with a stake in any of this to read Zitron's posts and immediately stop doing what they're doing. That would be silly. I don't think Zitron writes for them, and that what he writes needs "debunking". For how I see it, Zitron mainly advocates for a more critic journalism. Regardless of whether he's right or wrong, he does attempt to critically report on AI.
Right, but critiquing with the right perspective is important. Statements about making a loss must contain the entire economic picture, otherwise they simply aren't true at some point.
A business can't be scrutinized unless the units of economics are understood.
tudorizer commented on Units of Economics of LLMs. Reply to Ed Zitron's "AI Is a Money Trap" · Posted by u/tudorizer
It's a good analysis, but I am not sure why you are spending time doing this. People who care about your company (investors, users, partners etc) are probably sufficiently familiar with AI to disregard shallow analyses like Ed Zitron's one. You know the saying: a fool can throw a stone in a pond and 100 wise men can't take it out. It's not worth spending time debunking these pieces.
Most likely tickling an own itch. Also to validate/invalidate if sanity wasn't lost.
Plus, Ed's articles have been circulated in some investment groups and nobody expressed a clear counter-point.
PS. I wasn't familiar with that saying.
tudorizer commented on Units of Economics of LLMs. Reply to Ed Zitron's "AI Is a Money Trap" · Posted by u/tudorizer
Interesting read!
This stood out to me:
> ChatGPT 5 and ChatGPT OSS are here with the purpose of profitability
This is economically good, but it's also a signal that their capacity to moonshot is stalling either through lack of funding or lack of innovation. They're now pivoting to a more sustainable model.
Models have seen diminishing returns over the last 2 generations of model: GPT3.5 to 4o to 5.
Doubling parameter size does not double model ability/quality.
In the long term models will become commodities that can be interchanged with competitors and open source models, there's no moat, it's not likely anyone is going to sustainably have a hugely better model than the next company.
Claude Code is already showing that you can win in a niche with specialization.
I expect 3 things:
1. We won't see massive jumps on model performance again for a while without new techniques. 2. Model makers will specialize in specific use cases like claude code 3. Moonshot projects like stargate will not have outsized returns, the step change from o3/o4 models to whatever comes next will not be groundbreaking. Partly because of diminishing returns and partly because the average person is bad at explaining what they want an LLM to do.
> because the average person is bad at explaining what they want an LLM to do
Agreed. It's the saving grace for most platform which integrate LLMs even right now. Eg. v0 narrows the scope of general purpose LLMs and offers educated guides.
tudorizer commented on VHS-C: When a lazy idea stumbles towards perfection [video] youtube.com/watch?v=HFYWH... · Posted by u/surprisetalk
This video nerd-sniped me so hard. All these mechanics put a smile on my face.