Imagine sites like facebook, reddit, and google themselves who have more monthly users than the FLoC ID has bits to count. Imagine they store each result for a given user, and assume that, with high probability, when that value changes it is fairly adjacent to the old value. Now, you build a graph database of IDs and their relations. Finally, you link it all to users' profile metadata. You can build statistical distributions around each ID node based on users' gender, race, family status, interests, etc. and use those probabilities to guess at the precise interests of each new and unknown visitor. Also, those sites have a lot of outbound links. Now you can figure out that a particular ID has a high correlation with a particular domain, too.

But only the big sites like google have enough users to birthday-paradox their way into a meaningful ID graph, so you're safe from that tiny ad startup that also happens to be threatening google's business model...