What are the segment embeddings and position embeddings in BERT? They only reference in the paper that the position embeddings are learned, which is different from what was done in ELMo.

ELMo paper - https://arxiv.org/pdf/1802.05365.pdf

BERT paper - https://arxiv.org/pdf/1810.04805.pdf
These embeddings are nothing more than token embeddings.

You just randomly initialize them, then use gradient descent to train them, just like what you do with token embeddings.