More akin to something like the twitter verified program where companies can bid for relevance in the training set to buy a greater weight so the model will be trained to prefer them. Would be especially applicable for software if azure and aws start bidding on whose platform it should recommend. Or something like when Convex just came out to compete with depth of supabase/firebase training in current model they could be offered to retrain the model giving a higher weight to their personally selected code bases given extra weight for a mere $Xb.

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KellyCriterion 3 hours ago | parent [-]

But this is upfront, during training?

How does X then change "on the fly" if ad deals are changing? Constantly re-training with whatever advertiser is the current highest paying on?

In google ad times, this was realtime bidding in the background - for AI ads this does not work, if Im right?

	▲	yunwal 3 hours ago \| parent [-]
		Companies pay for entire sports stadiums for brand recognition. That’s also not something you can change on the fly, it’s a huge upfront cost and takes a significant effort to change. That doesn’t stop it from happening it’s just a different ad model.