New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI systems less resource-intensive, higher performing, and designed to emulate the human brain. The .
New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI systems less resource-intensive, higher performing, and designed to emulate the human brain. The research was published in Patterns, titled “Dimensionality and dynamics for next-generation neural networks.”
As AI models grow ever larger, so do their costs and limitations. Researchers at RPI and City University of Hong Kong offer a potential solution: instead of expanding outward with more layers and data, they propose building upward—adding internal structure that mirrors a 3D biological neural network and incorporating recursive loops to enhance network introspection.
This vertical dimension and loop allow artificial neural networks to process information more effectively and efficiently, potentially transforming AI’s ability to learn and adapt in 3D and higher dimensions.
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