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>Models don't need to have been trained on every single possibility - it's possible for them to generalize and interpolate/extrapolate. They do have some in-di
by fauigerzigerk 2y ago
>Models don't need to have been trained on every single possibility - it's possible for them to generalize and interpolate/extrapolate.
They do have some in-distribution generalisation capabilities, but human intentions are not a generalisation of visual information.
- Ukv 2y ago"human intentions are not a generalisation of visual information" is a bit confusing category-wise. Question would be to what extent you can predict someone's next action, like running out to retrieve a ball, given just what a human driver can sense. Clearly that's possible to some extent, and in theory it should be possible for some system receiving the same inputs to reach human-level performance on the task, but it seems very challenging given the imposed constraints. Also, for clarity, note that the limitations don't require the model be trained only on driver-view data. It may be that reasoning capability is better learned through text pretraining for instance.