Local models are already winning. Those benchmarked a year behind the biggest of big boys, a year ago. Six months ago they were six months behind. Yesterday Qwen released 3.6 27B and it outperforms 3.5 397B… from February.
Either we’re plateauing toward the asymptotic limit of LLM capabilities, and the endgame runs as well on a toaster as it does on a server - or breakthroughs use big fat models as a glorified search space to be rapidly discarded. Both options point toward neural networks as a lump of algebra that sits on your hard drive and occasionally spins your fans. Remote computing loses, as it basically always must, and the drastically reduced requirements for competing on local software favor clever new competitors who aren’t a bajillion dollars in debt.
They’re fucked.
Local models are already winning. Those benchmarked a year behind the biggest of big boys, a year ago. Six months ago they were six months behind. Yesterday Qwen released 3.6 27B and it outperforms 3.5 397B… from February.
Either we’re plateauing toward the asymptotic limit of LLM capabilities, and the endgame runs as well on a toaster as it does on a server - or breakthroughs use big fat models as a glorified search space to be rapidly discarded. Both options point toward neural networks as a lump of algebra that sits on your hard drive and occasionally spins your fans. Remote computing loses, as it basically always must, and the drastically reduced requirements for competing on local software favor clever new competitors who aren’t a bajillion dollars in debt.