throwaway084t95

What is the "first principles" argument that observability decomposes into logs, metrics, and tracing? I see this dogma accepted everywhere, but I'm inquisitive about it

"Strategic value" is hardly the only thing that matters for the welfare of a country -- actually it sounds more like an outsider's perspective on how a country can be useful for some other people. Also, it is totally false that Korea (or Japan) was never "truly democratic". Sure, they've had their issues and continue to, but that's why it is important that they keep moving in the right direction. This has actually been a very common path for lots of countries around the world to have troubled democracies and gradually improve but not without some hiccups.

The relevant embeddings here are computed by a neural network on high-dimensional input, like an image or a string of text. For instance, https://openai.com/research/clip. So they are not learned by backpropagating to the embedding itself (which is a common approach when you have a relatively small, fixed number of possible inputs, so you can just put your embeddings in a table). The embedding network will of course be trained by backpropagation, using some form of self-supervised learning

Let's consider an example that would be a case of Simpson's Paradox. Suppose you are A/B testing two different landing pages, and you want to know which will make more people become habitual users. You partition on whether the user adds at least one friend in their first 5 minutes on the platform. It might be that landing page A makes people who add a friend in the first 5 minutes more likely to become habitual users, and it also makes people who don't add a friend in the first 5 minutes more likely to become habitual users. But page A makes people less likely to add a friend in the first 5 minutes, and people who add a friend in the first 5 minutes are overwhelmingly more likely to become habitual users than people who don't. So, in this case at least, it seems like the aggregate statistics are most relevant, but the fact that page A is bad mainly because it makes people less likely to add a friend in the first 5 minutes is also very interesting; maybe there is some way of combining A and B to get the good qualities of each and avoid the bad qualities of both

That's not Simpson's Paradox. Simpson's Paradox is when the aggregate winner is different from the winner in each element of a partition, not just some of them