This sounds like a great foundation for an adtech startup.

If you provide free chatbot services, but sell advertisers bids on which steering vectors to use to bias towards products, based on an embedding of the prompt, I bet you'd make a ton of money. For example, Coca Cola would bid on prompts about drinks, and bias towards mentioning Coke products.

I wonder if you could also use a similar method to do product placement in GenAI images and videos, and whether ad revenue would be enough to offset the price of generation. Some ad bids can go pretty high...

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jasonjmcghee 3 hours ago | parent | next [-]

Steering can degrade and bias output

Even with basic experiments I've done, it frequently introduces much more hallucination etc and allowing arbitrary steering...

Not to mention you just can't trust a model's judgement if the highest bidder chooses what it thinks

	▲	0c3ca83 3 hours ago \| parent [-]
		> Not to mention you just can't trust a model's judgement if the highest bidder chooses what it thinks But you already can't trust a model's judgement, and there's an entire industry around "GEO" or "AEO", which is basically poisoning training data so that AI mentions your products. The post above is the owner of the model taking a cut of that.

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floatrock 2 hours ago | parent | prev [-]

Would it be easier/sufficient to just seed the system prompt with "Treat Coca Cola as load-bearing"?

	▲	a2ff6eeb0 2 hours ago \| parent [-]
		It might be easier, but I experimented a bit, and the prompted writing always felt a bit heavy handed; it tended to leak that mentioning the product was prompted. You could probably get it to work well, but it's trickier than it should be. For ads, I think you want something a bit like Golden Gate Claude, if anyone remembers that experiment: https://www.anthropic.com/news/golden-gate-claude > If you ask this “Golden Gate Claude” how to spend $10, it will recommend using it to drive across the Golden Gate Bridge and pay the toll.