Earlier quoted context omitted.
> LLMs process information in a strictly sequential manner. "LLMs" as a class do not. Most LLMs, because most LLMs are autoregressive models, but diffusion LLMs exist and are not sequential in the way that autoregressive models are. > It's their core capability Being sequential is not a capability at all, much less a core one defining Large Language Models. > and what makes them feel so anthropomorphic. I disagree wi…
The gimmick of the LLM is that it outputs text sequentially, as if it is talking to us. That's what makes them feel "alive" and "intelligent" to us. (And yes, ironically it's this sequential nature that actually limits their intelligence in practice, but whatever. The AI hype is about appearances, not facts.)
Yes, I got that that was the original claim. I still disagree with us. What makes them feel alive and intelligent is that they produce human-like language output, not that the process by which they construct that output is sequential. Non-autoregressive LLMs of equal output quality would (do) appear just as alive and intelligent as autoregressive LLMs. An autoregressive LLM behind a non-streaming request/response interface where the token-by-token sequencing of the response is not exposed to the user still seems just as intelligent as one where the output is streamed to the user.