Current artificial intelligence (AI) systems are nowhere near the cognition abilities of a human. In a new paper, researchers argue that to bridge the gap, agents will need three things: biological plausibility (creating an AI architecture that imitates the human brain's), temporal dynamics (artificial agents need to be able to exist in the world in much the same way as humans do), and social embodiment (the creation of a literal body for the agent).
However, there's no true road map toward human-level AI. The researchers are attempting to bring the worlds of cognitive and computer science together with engineering and robotics in a way we haven't seen before. This is, arguably, just another attempt to squeeze a miracle out of deep learning technology. Short of a new calculus or class of algorithm, we might be as close to human-level AI agents as traditional reinforcement learning can take us.
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