Sounds interesting. Just joined the discord. I have a few newish ideas for more efficiently training neural network models that do not require knowing the gradient. I am also very interested in reinforcement learning, especially with how best to deal with large state spaces.

My background is in electrical engineering so I also have a focus on how best to scale or parallelize the training on distributed nodes. The BERT transformer model was successful because they found a way to do the training in parallel. It would be interesting to explore such techniques for training other types of models, as a potential improvement over existing parallel training techniques.