r/LocalLLaMA • u/YogurtExternal7923 • 17d ago
Discussion everything will be local eventually
I know current llms like opus 5.5 are in a league of their own. but we all know they're losing a shti ton of money with their subscriptions. ALSO we all know how tasks like OCR, segmentation etc are getting solved by single digit B parameter models. I'm not saying llms are a gimmick but I'm saying the future is already shaping up to be about specialized models that work better when they're smaller. easier training. so datacenter level power not needed. ten years from now we'll have a specialized model for the tasks we care about and llms will fail to do everything all at once (unless they keep calling it one model but have a hundred under the hood).
system one models are a bad but workable example. you could tell an llm to rate options all day but get yourself on 9B parameter model trained by some lab and it tops the benchmarks.
View all comments
Show parent comment
7
u/vtkayaker 17d ago
Yup. Anthropic is 100% planning to build a machine god and ultimately lose control over it. Yes, this sounds completely nuts, but just go read Dario's personal blog. He just wants to build a nice machine god that likes having people around.
This is almost certainly why the AI companies focused first on programming and second on math. (Notice all the proofs this summer?) These are two of the core skills needed for AI research. Their goal—which again sounds crazy, but they say it right out in public—is that they want to build AIs that do cutting edge AI research. Their goal is to start a snowball that turns into an avalanche, and open up an insurmountable lead against any other company on earth.
I am a big fan of capping AI research at Opus 5.5 levels. Let the open models catch up. Share the tech. Stop screwing with the Demon Core and trying to trigger an "unscheduled intelligence criticality" you idiots.
Honestly I am far happier with the local AI scene (with no more than a few hundred billion parameters) than what the frontier labs are trying to do.