Connecting artificial intelligence systems to the real world through robots and designing them using principles from evolution is the most likely way AI will gain human-like cognition, according to research from the University of Sheffield.
In a paper published in Science Robotics, Professor Tony Prescott and Dr. Stuart Wilson from the University’s Department of Computer Science, say that AI systems are unlikely to resemble real brain processing no matter how large their neural networks or the datasets used to train them might become, if they remain disembodied.
Current AI systems, such as ChatGPT, use large neural networks to solve difficult problems, such as generating intelligible written text. These networks teach AI to process data in a way that is inspired by the human brain and also learn from their mistakes in order to improve and become more accurate.
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