These approaches are obviously great if your goal is to force marketing down people's throats, but it kills the integrity of the platform.
I don't get why people would continue using Google search (other than familiarity/momentum). As a site owner I'm questioning whether I even want to be indexed by Google.
What does your site do? If you're simply putting out information, I can catch your logic, but if you're trying to sell something, there's a good chance your audience is on Google.
- only advertisers with more than $10,000 monthly spend can participate in this AI Ads Model (sorry SMBs)
- using the same generative task pipeline you use for everything else, generate a training dataset: they are QA searches being answered by the ORGANIC content (rather than the advertiser-provided content) that utilizes the keywords the advertiser bids on / data instances with ORGANIC content that fulfills the objectives of the ad campaign.
- the count of the generated instances is proportional to the advertiser's spending
- fine tune the free Gemini models daily on this dataset along with the calibration dataset you already use for QAT or whatever.
that's it!
tiktok basically does the same thing. there, you are costco or redbull, you spend $100m on completely underperforming ads that nobody watches. but in exchange, tiktok tips the scales on organic content that mentions #costco or #redbull. that's it. it's not complicated. it's not even an ad!
These approaches are obviously great if your goal is to force marketing down people's throats, but it kills the integrity of the platform.
I don't get why people would continue using Google search (other than familiarity/momentum). As a site owner I'm questioning whether I even want to be indexed by Google.
What does your site do? If you're simply putting out information, I can catch your logic, but if you're trying to sell something, there's a good chance your audience is on Google.
here google research this one is free:
- only advertisers with more than $10,000 monthly spend can participate in this AI Ads Model (sorry SMBs)
- using the same generative task pipeline you use for everything else, generate a training dataset: they are QA searches being answered by the ORGANIC content (rather than the advertiser-provided content) that utilizes the keywords the advertiser bids on / data instances with ORGANIC content that fulfills the objectives of the ad campaign.
- the count of the generated instances is proportional to the advertiser's spending
- fine tune the free Gemini models daily on this dataset along with the calibration dataset you already use for QAT or whatever.
that's it!
tiktok basically does the same thing. there, you are costco or redbull, you spend $100m on completely underperforming ads that nobody watches. but in exchange, tiktok tips the scales on organic content that mentions #costco or #redbull. that's it. it's not complicated. it's not even an ad!