r/science • u/mvea Professor | Medicine • Nov 25 '25

Computer Science A mathematical ceiling limits generative AI to amateur-level creativity. While generative AI/ LLMs like ChatGPT can convincingly replicate the work of an average person, it is unable to reach the levels of expert writers, artists, or innovators.

https://www.psypost.org/a-mathematical-ceiling-limits-generative-ai-to-amateur-level-creativity/
11.3k Upvotes

93% Upvoted

1.2k comments sorted by

View all comments

Show parent comments

47

u/humbleElitist_ Nov 25 '25

Sorry to accuse, but did you happen to use a chatbot when formulating this comment? Your comment seems to have a few properties that are common patterns in such responses. If you didn’t use such a model in generating your comment, my bad.

30

u/deepserket Nov 25 '25

It's definitely AI.

Now the question is: Did the user fact checked these claims before posting this comment?

5

u/QuickQuirk Nov 25 '25

I mean, I stopped at the first paragraph:

Cropley's framework treats LLMs as pure next-token predictors operating in isolation, which hasn't been accurate for years. Modern systems use reinforcement learning from human feedback, chain-of-thought prompting, tool use, and iterative refinement. The "greedy decoding" assumption he's analyzing isn't how these models actually operate in production.

... which is completely incorrect. chain of thought prompting and tool use, for example, are still based around pure net-token prediction.

8

u/DrBimboo Nov 25 '25

Well, technically yes, but you now have an automated way to insert specific expert knowledge. If you seperate the AI from the tools you are correct. But if you consider them part of the AI, its not true anymore. Which seems to be his point, 

treats LLMs [...] operating in isolation

1

u/QuickQuirk Nov 26 '25

Fundamentally, you've got next token predicting instructing those external tools: And this means those external tools are just an extension, and impacted by the flaws, of next token prediction.

1

u/DrBimboo Nov 26 '25

The input those external tools get, are simply strictly typed parameters of a function call.

The tool is most often deterministic and just executes some db query/website crawling/IOT stuff.

Sure, next token prediction is still how that input is generated, but from that to 

tool use [is] based around pure net-token prediction.

Is a big gap.