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0 pointskrackers2mo ago0 comments

Here's an evil business idea: Use the LLMs to identify the users most likely to be "vocal influencers" and then prioritize resources for them, ensuring they get the best experience. You can engineer a bubble this way.

And then the next step is to dynamically vary resources based on prediction of user stickiness. User is frustrated and thinking of trying competitor -> allocate full resources. User is profiled as prone to gambling and will tolerate intermittent rewards -> can safely forward requests to gimped models. User is an resolute AI skeptic and unlikely to ever preach the gospels of vibecoding -> no need to waste resources on him.

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vibe422mo ago

This is part of why running open models on hardware you control is valuable. They may trail SOTA by 6-12 months (really less for many use cases) but there's more reliability, control etc.

oro442mo ago

"Here's an evil business idea: Use the LLMs to identify the users most likely to be "vocal influencers" and then prioritize resources for them, ensuring they get the best experience. You can engineer a bubble this way."

Its quite likely this is already happening buddy...

The 'random' degradation across all LLM-based services is obvious at this point.

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