It does look like we are entering diminishing returns territory though. The biggest evidence for this is that Chinese companies have now basically caught up to Anthropic and OpenAI. If the progress at the frontier was still happening at the same rate, then the gap wouldn't be closing so quickly. There's also a lot less noticeable difference between stuff like Claude 4.6 and Claude 5. When they went from 3.x to 4.x it was very noticeable. And at least for agentic coding, most of the improvement seems to come from the harness now. I expect improvements will continue, but at a much more gradual pace. It's also possible people will figure out a new architecture that's superior to LLMs, or works with them. World models are one promising area already being explored.

Is that really the most reasonable take?

So that's one of the biggest questions in AI right now. Are we going to hit a wall? It does kind of seem like the big models aren't improving as much anymore, and the small models are catching up. But at the same time, Moore's law has been going for way longer than people expected, maybe AI will be the same.

Edit: wording on last sentence of first paragraph

he RAM/VRAM divide is kind of a legacy thing at this point, doing more harm than good in the x86

That has nothing to do with x86 though...

but I suspect they are still going to be bigger than most can comfortably host for time being

ARM and CXMT both have the potential to change this situation rather dramatically.

ARM: The RAM/VRAM divide is kind of a legacy thing at this point, doing more harm than good in the x86 (desktop OS) space, but ARM doesn’t have the same baggage.

CXMT: We know the DRAM cartel have previously engaged in price-fixing, and the current shortage looks suspiciously similar to their old behavior. When confronted by a new challenger, they might be forced to actually compete.

And if course LLM's are not going to be the end point of the search for AGI. Whatever their architecture they will still need copious amounts of compute.