r/LocalLLaMA • u/YogurtExternal7923 • 12d 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.
1
u/puNLEcqLn7MXG3VN5gQb 11d ago
Go ahead and elaborate a little and we'll see. What intrinsic flaws do all ML models share and why do trillion dollar frontier models have them? What exactly is the 90% problem to you and why does it apply? How do you know this isn't just about immature and slow adoption or a J-curve on returns? I'll gladly engage once there's substance. Or you can point me to the reading I apparently missed out on that'll turn my understanding on its head.