Whats funny is the oil and gas industry has orders of magnitude worse units. So much so, I would say the imperial system is scared of it.

Entertaining video ranting about this

The meme also assumes billionares are spending all that money on one side. They spend it on both (bankman-fried who publicly donated to dems and secretley donated to republicans so he could guide regulations, have the ear of government, maybe even get an edge on people.) So its not like the parties truly are that different.

If thats using pre-ukraine ratios that’s believable but this war has been extremely lethal for both sides. Instead of cassevac in hours it can sometimes take weeks so a survivable injury in Afghanistan becomes a death sentence in Ukraine. Look at that one dude who was stuck in his position wounded for months. They used a drone to cassevac him because rescue kept getting attacked and killed and the russian drones wouldn’t let him leave.

It looks like a giant lizard skull so all they need to make the link is dead lizard skeletons to refer to?

I really wish it were law that your subtotal included a field called “profit to the shareholders” to transparently show you exactly how hard you’re getting fucked over.

My local butcher shop sells whole pork side ribs for like $13 CDN and still make a profit. Walmart charges $18 and makes a killing any time they sell one. My local butcher pays living wages while walmart doesnt…

The unironic best trap ever is two tall cans (think monster or whiteclaw or sometjing) skewered on a wire or rod over a bucket. Smear peanut butter on it and that bucket will have literally every rat and mouse in a 500 meter radius.

“Kid, you’re 18 now. You have to decide. Do you want to breathe toxic fumes the rest of your life or sit in front of a computer for 10 hours a day?”

Strata is a good runner for that. It also can run Qwen3.8-flash-next which is also great

.ssh/config and tab autocomplete are how I manage. I do the squinting once if I can help it

Its ok, text is also really ambiguous so I don’t blame you

Yeah I know I was agreeing with you

Stm32 has made micro controllers with neural processors for years now and you don’t need LLMs to do a lot of useful stuff for a spyware company. A small model can run even in really constrained hardware if you train it specifically for it. Afaik the STM32 ones are for machine vision processing on limited hardware where power is a concern. I’m sure you can do a lot more with a TV with constant power.

Plus studies on skill decay when using AI. Also the linux maintainer onboarding pipeline—which was already critically endangered—is now no longer building understanding through writing code, just monitoring it’s generation.

I personally think you need to write a language by hand without AI doing it for you to learn in detail. It’s like trying to learn how to do math or how to write mandarin by just supervising an AI doing it… you need to do it yourself. Supervising is fine if you’re already fluent in mandarin and have been writing it for years and years. If you’re just learning it’s less than useless. If anything its directly harmful to learning.

Same with speaking a language yourself without crutching your native language as the best method to learn to speak it (immersion)

Edit: The long term externalities of AI—like pretty much everything nowadays—is going to be made worse by short term thinking. Quarterly profits and yearly results take precedence over long term skill development. Even OSS like linux will eat its seed corn out of expediency because of a lack of maintainers and new candidates being onboarded into the ivory tower mailing lists…

Like wire tapping enron 3 months pre meltdown

This is where things seem to be headed. Local models can be pretrained and crammed full of your work’s information, and opencode and other harnesses can pick the right model for the task ahead of time. I could be wrong but i’ve been predicting a drop in frontier model credit usage especially if they hike token prices again. People will only use it if they have to especially if you can find a way to task a local model with a lot of the grunt work.

Here’s a video on it

Qwen3.8-flash-next is making waves since its near frontier or frontier (according to some i havent used it) that can be run on an ancient 8GB video card (12GB or more is recommended. 16GB is best.) with around 32GB of RAM using Strata.

Strata

It’s a mixture of experts MoE model, so while it’s around 66GB (depending on which quantization you decide to run) you’re only really using about 6B parameters per token processed, meaning the VRAM requirements are a lot lower.

I personally don’t see the value proposition in paying $4/1M tokens when i can generate around 30tok/s on 500W of power. I pay ¢13/kWh so to generate 1M output tokens takes me 9.25 hours and costs $0.60.

I’m also running an ancient video card and have a new one in the mail. If i got 200 tok/s even at higher power use i’m still a fraction of the cost of paying for API access and I want that GPU for other things regardless.

I feel lile medium and large businesses have a strong incentive to rent or buy inference using open weight models for a fraction the cost of paying OpenAI or Anthropic. Especially if you can pre load them with everything about your org to make them better suited for internal use.

The vast majority of uses can use a open weight locally run model. I think you would only want to pay for frontier models for really complex tasks with lots of steps, and even then there are usually ways to be smart about how you task agents with work to get better output and use less money.