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Scientists Discover Amazing Similarities Between Neural Networks and the Human Brain
Spitting image
A team of scientists have discovered that there is a surprising similarity between the human brain and the way artificial neural networks recognize the world.
In the human brain, visual information passes through several cortex, each interpreting different aspects of the image, and ultimately connects the perceptions of the world around us. A New research Published in the journal on Thursday Current biology It turns out that aspects of 3D shapes such as bumps and spheres are interpreted early in the process. And the same thing happens with artificial neural networks.
Convergent evolution
It may seem less shocking for neural networks, a type of artificial intelligence architecture that explicitly models the brain, to interpret information in the same way.But scientists didn’t know about this particular aspect of how the biological brain works before looking at it in the algorithm. AlexNet..
“I was surprised to see a powerful and clear signal in 3D shape on V4 as early as possible,” said Edconner, a neuroscientist and research author at Johns Hopkins University. Said in a press release, Refers to a specific visual cortex. “But I never imagined the same thing would happen with AlexNet, which was trained just to convert 2D photos to object labels, for a million years.”
Circular learning
Unexpected parallel hints that neural networks can tell you about our brains, just as we develop new neural networks using what we know about our brains.
“Artificial networks are the most promising current model for understanding the brain,” Connor said. “On the contrary, the brain is the best source of strategies to bring artificial intelligence closer to natural intelligence.”
read more: Researchers discover “eerie” similarities in how the brain and computers see [Johns Hopkins University]
Neural network details: Physicist: The entire universe could be a neural network
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