Update: Interesting paper, thanks. Comment on selection for Hydra — you mention v1 uses an arithmetic mean across timescales for prediction. Taking this analogy of the longer windows encapsulating different timescales, I’d propose it would be interesting to train a layer to predict weighting of the timescale predictions. Essentially — is this a moment where I need to focus on what just happened, or is this a moment in which my long range predictions are more important?