If you want theory there’s this: https://arxiv.org/abs/2001.08361 https://arxiv.org/abs/2001.08361 (I haven’t actually read this but I know roughly what it’s ab

If you want theory there’s this: https://arxiv.org/abs/2001.08361 https://arxiv.org/abs/2001.08361 (I haven’t actually read this but I know roughly what it’s about) It’s saying that so far the abilities of an LLMs have scaled up with its parameter count and training data size. Of course there’s no way to be sure without actually training larger models but I don’t see why the point where it stops would be just after our current best LLMs. Many properties have already emerged from making it bigger so I don’t see why this would be the exception