Here's the part of how does this work that's my TL;DR.
> A browser with FLoC enabled would collect information about its user’s browsing habits, then use that information to assign its user to a “cohort” or group. Users with similar browsing habits—for some definition of “similar”—would be grouped into the same cohort. Each user’s browser will share a cohort ID, indicating which group they belong to, with websites and advertisers. According to the proposal, at least a few thousand users should belong to each cohort (though that’s not a guarantee).
> If that sounds dense, think of it this way: your FLoC ID will be like a succinct summary of your recent activity on the Web.
> Google’s proof of concept used the domains of the sites that each user visited as the basis for grouping people together. It then used an algorithm called SimHash to create the groups. SimHash[0] can be computed locally on each user’s machine, so there’s no need for a central server to collect behavioral data. However, a central administrator could have a role in enforcing privacy guarantees. In order to prevent any cohort from being too small (i.e. too identifying), Google proposes that a central actor could count the number of users assigned each cohort. If any are too small, they can be combined with other, similar cohorts until enough users are represented in each one.
> In computer science, SimHash is a technique for quickly estimating how similar two sets are. The algorithm is used by the Google Crawler to find near duplicate pages. It was created by Moses Charikar.
So...in addition, Google can use all the users' CPUs instead of their own.
> A browser with FLoC enabled would collect information about its user’s browsing habits, then use that information to assign its user to a “cohort” or group. Users with similar browsing habits—for some definition of “similar”—would be grouped into the same cohort. Each user’s browser will share a cohort ID, indicating which group they belong to, with websites and advertisers. According to the proposal, at least a few thousand users should belong to each cohort (though that’s not a guarantee).
> If that sounds dense, think of it this way: your FLoC ID will be like a succinct summary of your recent activity on the Web.
> Google’s proof of concept used the domains of the sites that each user visited as the basis for grouping people together. It then used an algorithm called SimHash to create the groups. SimHash[0] can be computed locally on each user’s machine, so there’s no need for a central server to collect behavioral data. However, a central administrator could have a role in enforcing privacy guarantees. In order to prevent any cohort from being too small (i.e. too identifying), Google proposes that a central actor could count the number of users assigned each cohort. If any are too small, they can be combined with other, similar cohorts until enough users are represented in each one.
[0] https://en.wikipedia.org/wiki/SimHash
> In computer science, SimHash is a technique for quickly estimating how similar two sets are. The algorithm is used by the Google Crawler to find near duplicate pages. It was created by Moses Charikar.
So...in addition, Google can use all the users' CPUs instead of their own.