The speaker considers function-space analyses more useful because their predictions align better with expectations than predictions from parameterized analyses.

“over time. And that of course makes the analysis way way better that you can now effectively also model not only the laser learning but also the feature learning domain. But has a huge limitation now that it becomes much much harder to analyze.”

“Still I think that from an analysis point of view these end up being more useful. Specifically because the predictions end up lining up a lot better than what we would expect for the parameterized world. Like in parameterized world”