they have a non-smooth capability curve, where they can demonstrate proficiency in activities that in regular computer programs or people would imply a complete and continuous path of capability that has been mastered to achieve the demonstration, but ai systems are weird in that can do amazing things, but have loads of little holes and failure modes along the way.
for example: gpt-3 can write you a shell script that will emit a c program that prints a poem about people you know, but will fail at very basic logic, sometimes.
in light of that, having additional support data like radar or lidar seems like the right move for plugging all those little holes in capability that turn up in real ai systems.
because at the end of the day, when you're driving a car in the real world and lives are at stake, simply interpolating or averaging over uncertainty seems awfully deadly and the only way to ameliorate that uncertainty seems to have multiple redundant sensory systems that can stand in for each other as conditions change. just like us!