Thanks! Agree that functional form uncertainty is a big deal here; I think that implicitly this uncertainty is causing me to up-weight Short Horizon Neural Network more than I otherwise would, and also up-weight “Larger than all hypotheses” more than I otherwise would.
With that said, I do predict that in clean artificial cases (which may or may not be relevant), we could demonstrate linear scaling. E.g., consider the case of inserting a frame of static or a blank screen in between every normal frame of an Atari game or StarCraft game—I’d expect that modifying the games in this way would straightforwardly double training computation requirements.
Thanks! Agree that functional form uncertainty is a big deal here; I think that implicitly this uncertainty is causing me to up-weight Short Horizon Neural Network more than I otherwise would, and also up-weight “Larger than all hypotheses” more than I otherwise would.
With that said, I do predict that in clean artificial cases (which may or may not be relevant), we could demonstrate linear scaling. E.g., consider the case of inserting a frame of static or a blank screen in between every normal frame of an Atari game or StarCraft game—I’d expect that modifying the games in this way would straightforwardly double training computation requirements.