Comment by og_kalu
2 days ago
It's definitely a tired and semantical one because as he said, it brings no insight and is not even good at the analogy level. I can't have a conversation with Dracula and Dracula can't make decisions that affect the real world, so LLMs already break key aspects and assumptions of the 'Document Simulator'.
Pre-trained LLMs will ask clarifying questions just fine. So I think this is just another consequence of post-training recipes.
> Dracula can't make decisions that affect the real world, so LLMs already break key aspects and assumptions of the 'Document Simulator'.
Nonsense, we are already surrounded by mindless algorithms (and their outputs) that "affect the real world" because many of us have full-time jobs ensuring it happens! "
When someone uses a SimCity-esque program to generate a spreadsheet used for real-world bus schedules, does that "break key aspects and assumptions of a traffic simulator"? Does the downstream effect elevate it to a microcosm of tiny lives? Nope!
You’re talking past the point I was making.
My point about Dracula isn't just that he's fictional, but that he cannot make decisions that have unscripted consequences in the real world, nor can he engage in a novel, interactive conversation. Dracula, as a character, only "acts" or "speaks" as an author (or game designer, etc.) has already written or programmed him to. He has no independent capacity to assess a new situation and generate a novel response that affects anything beyond his fictional context. If I "talk" to Dracula in a game, the game developers have pre-scripted his possible responses. The text of Dracula is immutable.
A LLM, by contrast, performs fresh inference every time it’s prompted: it weighs competing continuations and selects one. That selection is a bona-fide decision (a branch taken at run-time). The “document-simulator” picture collapses that distinction, treating a dynamic decision process as if it were a block of pre-written prose. It's just nonsensical.
Your SimCity example is open loop: the simulation runs, a human inspects the results, and then decides whether to publish new bus schedules. Nothing in the simulator is tasked with interrogating the human, updating its model of their intent, or steering the outcome. In production LLM systems the loop is often closed: the model (often with tool-wrapper code) directly drafts emails, modifies configs, triggers API calls, or at minimum interrogates the user (“What city are we talking about?”) before emitting an answer.
Your argument is tired and semantical because it fails at the most fundamental level - It's not even a good analogy.
> LLMs already break key aspects and assumptions of the 'Document Simulator'. [...] The “document-simulator” picture collapses that distinction, treating a dynamic decision process as if it were a block of pre-written prose. It's just nonsensical.
I feel you've erected a strawman under your this "document simulator" phrase of yours, something you've arbitrarily defined as a strictly one-shot process for creating an immutable document. Yeah, it's boring and "nonsensical" because you made it that way.
In contrast, everybody else here has been busy talking about iterative systems which do permit interaction, because the document is grown via alternate passes of (A) new content from external systems or humans and (B) new content predicted by the LLM.
3 replies →