I learned about tensors in a math course in grad school. It was about the scalars, vectors, and higher-order tensors used in physics and differential geometry. It talked about metric tensors, co-variance and contra-variance, with examples from continuum mechanics, general relativity, etc.
Thirty years later I'm reading about artificial intelligence, neural networks, and Tensor Flow. It's clear to me that tensors in this context are higher-order extensions of 2D matrices from linear algebra.
The term tensor is overloaded for me. My first thought always goes back to my first exposure from continuum mechanics.
Can someone explain the relationship between the two and suggest references for further reading about the connection?