All the one-shot approaches I've seen are IMO transfer learning in disguise, which raises the question of "what are you transferring from?". So while these should hopefully reduce the need for truly gigantic datasets about everything, there is still a limit of how much info you can extract from a fixed amount of data.

Large datasets will still be important for all but strictly perceptual tasks.