Technology

Yeah I've read that before. I don't necessarily agree with their framework. And even working within their framework, this article is about a challenge to their third bullet.

I'm just not quite ready to rule out the idea that if you can scale single models above a certain boundary, you'll get a fundamentally different/ novel behavior. This is consistent with other networked systems, and somewhat consistent with the original performance leaps we saw (the ones I think really matter are ones from 2019-2023, its really plateaued since and is mostly engineering tittering at the edges). It genuinely could be that 8 in a MoE configuration with single models maxing out each one could actually show a very different level of performance. We just don't know because we just can't test that with the current generation of hardware.

Its possible there really is something "just around the corner"; possible and unlikely.

What we need are more efficient models, and better harnessing. Or a different approach, reinforced learning applied to RNNs that use transformers has been showing promise.

Could be. I'm not sure tittering at the edges is going to get us anywhere, and I think I would agree with just.. the energy density argument coming out of the dettmers blog. Relative to intelligent systems, the power to compute performance (if you want to frame it like that) is trash. You just can't get there in computation systems like we all currently use.