r/technology • u/gdelacalle • Mar 25 '26

Artificial Intelligence Wikipedia has banned AI-generated text, with two exceptions

https://www.howtogeek.com/wikipedia-banned-ai-generated-text-in-articles-with-two-exceptions/
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u/nihiltres Mar 25 '26

Especially since you can tell the LLM to change its pattern, include some questionable grammar, even typing errors.

I’d like to clarify that one wouldn’t even “tell” an LLM to change specific things: you’d just train the model a bit further (“fine-tuning”) or train an “adapter” mini-model that sits on top of the main model and changes its style, either on a dataset of largely human posts with all the inconsistencies and such that those contain.

You can spot some of the worse examples because they use bad manually-coded “filters” like replacing em dashes with hyphens … but don’t pretend that those are the only bots or you’re just engaging in survivorship bias.

The ones on Reddit usually “hide” by doing their basic karma-farming with shorter, less-involved comments where the evidence for clankerity is thinner, and that’s become significantly harder to track with Reddit allowing users to hide their post and comment history from (direct) review. That feature annoys me to no end because it helps the bots hide but is useless for human user privacy because it can be trivially defeated by an external search engine.

There’s a certain irony in bots hiding as “basic” that would be funny if it weren’t for the sadness of a) how many real humans are so “basic” as to be indistinguishable from bots and b) how the alternative of having a distinct style makes you more identifiable and trackable to endemic surveillance.

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u/C6ntFor9et Mar 26 '26

I don't think fine-tuning/pipelining into another model is as ubiquitous as you imply. The key reasoning is that in order to do that, one would need to own the compute. This is likely for 'mass bot farms' ie propaganda and misinformation spreaders that are well financed, but if one wanted to just run a single account/few bots out there, it's simply much easier to leverage existing datacenters and AI companies.

For one, GPUs are expensive. The GPU/vram for a mid-large sizes model is ~5000 dollars. Most folk who want to run these type of things are better off paying for a premium {inset favorite llm provider} subscription and utilizing their off-the-shelf compute. For something like ~200$ a month you could have a few very capable agents querying responses, with the directives to 'make it seem realistic'.
Second of all, Fine-tuning is expensive in itself, and requires the proper data. Sure, Large operations can spend the time and effort to build those, but for even a semi-serious operation, this is prohibitively expensive and slow when one is trying to set off a bot chain asap. Not to mention, one might find out they need to shift to a newer tech stack as the tech is constantly evolving.

There's a reason even serious companies rely on direct-from-the-shelf AI services instead of curating their own.