We want to understand the future, based on our knowledge of the past. However, training a neural net on the past might not lead it to generalise well about the future. Instead, we can train a network to be a guide to reasoning about the future, by evaluating its outputs based on how well humans with access to it can reason about the future
I don’t think this is right. I’ve put my proposed modifications in cursive:
We want to understand the future, based on our knowledge of the past. However, training a neural net on the past might not lead it to generalise well about the future. Instead, we can train a network to be a guide to reasoning about the future, by evaluating its outputs based on how well humans with access to it can reason about the past [we don’t have ground-truth for the future, so we can’t test how well humans can reason about it] and how well humans think it would generalise to the future. Then, we train a separate network to predict what humans with access to the previous network would predict about the future.
(It might be a good idea to share some parameters between the second and first network.)
I don’t think this is right. I’ve put my proposed modifications in cursive:
We want to understand the future, based on our knowledge of the past. However, training a neural net on the past might not lead it to generalise well about the future. Instead, we can train a network to be a guide to reasoning about the future, by evaluating its outputs based on how well humans with access to it can reason about the past [we don’t have ground-truth for the future, so we can’t test how well humans can reason about it] and how well humans think it would generalise to the future. Then, we train a separate network to predict what humans with access to the previous network would predict about the future.
(It might be a good idea to share some parameters between the second and first network.)
Ooops, yes, this seems correct. I’ll edit mine accordingly.