- “Now, a USC research team has developed an AI that uses human-like capabilities to imagine a never-before-seen object with different attributes.
- ‘Humans can separate their learned knowledge by attributes–for instance, shape, pose, position, color–and then recombine them to imagine a new object. Our paper attempts to simulate this process using neural networks.’
- This is one of the long-sought goals of AI: creating models that can extrapolate. This means that, given a few examples, the model should be able to extract the underlying rules and apply them to a vast range of novel examples it hasn’t seen before.
- In this new study, the researchers attempt to overcome this limitation using a concept called disentanglement. Disentanglement can be used to generate deepfakes, for instance, by disentangling human face movements and identity. By doing this, said Ge, ‘people can synthesize new images and videos that substitute the original person’s identity with another person, but keep the original movement.’”