My own work focuses on an alternative to deep learning, called Sparse Predictive Hierarchies (SPH). It is implemented in a library called AOgmaNeo (Python bindings also exist). It does not use backpropagation, runs fully online/incremental/continually (non-i.i.d.). Its main advantages are the online learning but also that it runs super fast. Recently, I was able to play Atari Pong (with learning enabled!) on a Teensy 4.1 microcontroller, and still get 60hz.

If you would like to know more about it, here is a link to a presentation I gave a while back (Google Drive).

Other than my own work, I find the Tsetlin Machine interesting as well.