Right, I understand all that. I just don't understand how to interpret the resulting map (or how to formulate a search) to provide useful information, specifically "who knows what".
Thank you for being so clear on where we are failing you. We're basically computing your semantic space as compared to the whole community. The map shows the relevant instances in that space. As you browse your concepts the space changes and we link to the relevant comments from the associated threads. Who knows what is prioritizing the user and the semantics / voice of that user amidst the noise of the whole community speaking at once.
We'd love to hear your feedback as you play with it more and we improve all of the above.
It obviously isnt intuitive, but I suppose one could learn to read it over time. For example, there is a lobe at (5, 10) that lights up like a Christmas tree if a user was engaged with Covid vaccines and mandate discussion. Of course, it seems like there is no discrimination between the different stances a user took, or the veracity of their commentary.
Then you encode a search query the same way and return the nearest N vectors/users. That's vector search.
It seems they did the above for HN comments.