I just got Qwen 3.8 Flash Next running locally. It’s damn good on an older machine with a newer GPU. Local LLMs should scare them the most.
Yeah but who’s making the models?
It will be interesting to see, but stories have come out for a while about some thing will pop the bubble, and a big recession has been right around the corner for at least a decade. What stage is this bubble in the progression to the .com pop, months, a year? Or is this different, with more profitable companies investing in infrastructure, rather than speculative startups without clear revenue plans? That was part of the take MMM made and I want to be hopeful. It reminded me about my circle of control, reduce attachment to outcomes beyond it, but do what I want within my circle. mrmoneymustache.com/2026/09/25/will-the-ai-bubble-destroy-our-retirement/
This is poised to be the biggest financial crash in history. These assholes are fighting every day to push the crash further away so they can divest themselves quietly or make ot to an IPO, and in doing so are making the upcoming disaster much worse.
And so much investment has been dumped into this scheme I don’t know how our economic system.will survive. Unchecked capitalism needs to go away, but having it collapse all at once is gonna be really, really bad.
This is silly, we can just print more money to cover the losses, ez pz !!!
“We lose money on every sale, but we make up for it in volume!”
I can’t imagine how much money Google is losing right now. They do 8.5 to 13.7 billion searches a day (+1 because I just googled that). By forcing LLM first, they’ve got to be burning cash.
Character.AI discovered the one conversation its bots couldn’t keep going: the one with its accountants. $56 million in compute costs in eight months, and the monetization strategy was apparently: hope the next investor is even lonelier than our users. Silicon Valley keeps confusing engagement with a business model.
If LLMs can’t be made more power efficient, then the technology isn’t ready yet for general use. There may have to be fundamental engineering breakthroughs before what these systems do can be more than a very expensive and inefficient worldwide proof of concept.
Of course, the military and the surveillance industry will still want to keep it, even if no one else can afford it, and we’ll be the ones paying for it.
someone else replied with what i said
If LLMs can’t be made more power efficient, then the technology isn’t ready yet for general use.
Hm, I don’t see the harm in powering local models with solar.
Well that is an alternative. But I bet each query to a local 27b model takes less energy anyway than the same query to Claude Opus or Fable in some data centre. So it is also a case of improving energy efficiency by running smaller models.
Let’s hope the rest follows.
Didn’t all of their devs get poached by Google after being bought out?
