Researchers and scientists at Cambridge University have recently developed a self-organizing, AI brain-like system that emulates the key aspects of the human brain’s functionality.
As per the study that was published in Nature Machine Intelligence “reveals how imposing physical constraints on AI systems can lead to the evolution of brain-like characteristics, offering insights into the human cognitive processes and the future AI development.”
“When considered an integrated system, the human brain is a remarkable feat of nature. It is adept at optimizing information processing and energy efficiency to skillfully solve complex problems.”
The study co-author of the study Ph.D. student at Cambridge University, Jascha Achterberg, said, “Not only is the brain great at solving complex problems, it does so while using little energy. In our new work, we show that considering the brain’s problem – solving abilities alongside its goal of spending as few resources as possible can help us understand why brains look like they do.”
As per the study, “researchers successfully showed that by applying physical and energetic constraints to an AI system similar to those in human neutral networks, they could develop an AI brain-like system with organizational strategies and efficiencies akin to the human brain.”
The researchers wrote, “the AI system shows an internal structure similar to the human brain. That means that the ways individual parts and neutrons of the AI are connected is similar to the way that different parts in the human brain are connected. The AI system specifically shows a very brain-like and energy efficient internal wiring. ”Achterberg said, “Artificial brains allow us to ask questions that it would be impossible to look at in an actual biological system. We can train the system to perform tasks and then play around experimentally with the constraints we impose to see if it begins to look more like the brains of particular individuals.”