Understanding the meaning of embeddings created by the collaborative filtering

I have a dataset of some users and product ratings. I have created the user and product embeddings using the collaborative filtering approach taught in the Fast Ai sessions.

Say, I have a 50-dimensional embedding for the users and a 50-dimensional embedding of the products. Will a dot product of the Product1 embedding with the User1 embedding tell us how much the user prefers the product?

If the answer to the above is yes, how will the dot product happen if the embedding dimensions are different for the users and products