LELBO=−Eqϕ(z|y)[logpθ(x|z)]+βKL(qϕ(z|y)∣∣∣∣p(z))

Question:
If maximising ELBO is 1. learn to reconstruct the data faithfully 2. regularising the latent space to generalise on similar but new data

Are the two terms in this formula doing 1 and 2 separately? If so, how?

Alien language

View as possible compression of human language? Can change my thoughts If they prove to have no consistency, or not interpretable/decodable by LLM.

Thanks for the post! Not sure if I understood (I like it) it correctly about the idea of alignment between the geometry and the learned dictionary: this produces "separation" between features that is closer to the "true" dictionary—maybe it's just a paraphrasing of the same thing, but what did you mean by "semantic continuity"?