I can’t see how this is true. It isn’t obvious to me that one could conclude anything from a video like that without a substantial prior knowledge of mathematical physics. Seeing a red, vaguely circular object, move across a screen tells me nothing unless I already know an enormous amount.
This DeepMind paper describes their neural network learning from an emulated Atari 2600 display as its only input and eventually learning to directly use its output to the emulated Atari controls to do very well at several games. The neural network was not built with prior knowledge of Atari game systems or the games in question, except for the training using the internal game score as a direct measurement of success.
More than 3 frames from the display were used for training, but it arguably wasn’t a superintelligence looking at them.
This DeepMind paper describes their neural network learning from an emulated Atari 2600 display as its only input and eventually learning to directly use its output to the emulated Atari controls to do very well at several games. The neural network was not built with prior knowledge of Atari game systems or the games in question, except for the training using the internal game score as a direct measurement of success.
More than 3 frames from the display were used for training, but it arguably wasn’t a superintelligence looking at them.