Replying to @⁨inari@piefed.zip⁩

Let me preface this by saying that I am generally against AI and I hate LLMs being pushed everywhere, but I currently hate facebook and social media even more than AI.

I think that ad blocking might actually be a good use of a model trained to detect ads: AI models are “black boxes” and it would make it difficult for facebook to find out precisely how the detection works and workaround it. Imagine a tiny classifier running locally, whose only job is to look at a post html or resulting rendered pixels and detecting if it’s an ad or not, and then generating the blocking rules.

It would be quite cool, because it would work on any website without an explicit list of ad-blocking rules that somebody needs to maintain.

Replying to @⁨Supercrunchy@programming.dev⁩

It would make a good second (or third) layer of defense. The problem with it is that it’s reactive not proactive, so you need to download the ad first before it can decide to block it or not. URL blacklists are the superior option, but hard to maintain. The ideal setup would be a URL blacklist that’s automatically updated on the fly by an AI classifier so anything that slips through the blacklist gets ban hammered by the AI and added to the blacklist to prevent future wasted bandwidth. If the blacklist updates were shared the same way some of the ad blockers do currently it could be incredibly effective as it would be essentially distributed realtime ad blocking.

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