- What's harder, perception
or control for these problems.
So being able to perfectly
perceive everything
or figuring out a plan once
you perceive everything,
how to interact with all the
agents in the environment.
In your sense, from a
learning perspective,
is perception or action harder?
In that giant, beautiful,
multi-task learning neuro network?
- The hardest thing is having
accurate representation
of the physical objects in vector space.
So, taking the visual
input, primary visual input,
some sonar and radar
and then creating an accurate
vector space representation
of the objects around you.
Once you have an accurate
vector space representation,
the planning and control
is relatively easier.
It's relatively easy.
Basically once you have accurate
vector space representation
then you're kind of like a video game,
like cars in like Grand
Theft Auto or something.
They work pretty well,
they drive down the road,
they don't crash, pretty much,
unless you crash into them.
That's because they've got
an accurate vector space representation
of where the cars are
and then they're rendering
that as the output.
