“Current self-driving cars fall short, and will always fall short, because they rely upon a statistical model of the world instead of naturally embracing unexpected real-time events.”
is mistaken. The artificial minds of self-driving cars are missing one all-important technological ingredient. Consciousness.
It took about 70 years of machine learning research for computers to surpass us in many of our most prized forms of intelligence, such as winning at chess, composing compelling music, and writing thoughtful essays. But three billion years of autonomy development in living minds has proven to be a far steeper mountain to climb.
to the constant honking of horns to judge the location of the honker. The challenge for a self-driving car is to continuously segment environmental information coming from every direction into objects and events, identify and prioritize risks and act upon prioritized risks instantly, all while continuously recalculating the optimal route to the destination
Following the success of Deep Learning algorithms , the standard approach to designing self-driving minds is to model the vehicle’s expected environment based upon statistical regularities, such as how often red dots in the periphery are traffic lights and how quickly cars typically accelerate away after a green light. In effect, self-driving cars create a statistical model of the world in the past, then attempt to fit all future events into this historical model.
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