object detection:
detect bounding box of an object(s) within its environment
object:
a structure that is detached from its environment by another substance
where, another substance may be:
- air
- ground
- grass
- water
- object
etc.
i think object detection can be done with fair accuracy using classical logic algorithms, given algorithm has enough data of the observation.
although what happens if we have car on top of car? in this case classical algorithm based on substance detection would only see one car object.
also classical algorithm is not language algorithm, so it does not have concept of a car.
what classical algorithm should be able to do, is use the most abstract form of object detection, which for example can be useful on systems like collision detectors:
it is enough to know some object exist, its boundaries and its movement direction etc.
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animals dont use language much, they dont care about situations like this:
is car on top of car or is it single car
language models are only necessary if language response is needed
intelligent observation and adaptation to environment is not language dependent