Self-organizing 'infomorphic neurons' can learn independently

Self-organizing 'infomorphic neurons' can learn independently

Researchers have developed "infomorphic neurons" that learn independently, mimicking their biological counterparts more accurately than previous artificial neurons. A team of researchers from the Göttingen Campus Institute for Dynamics of Biological Networks (CIDBN) at the University of Göttingen and the Max Planck Institute for Dynamics and Self-Organization (MPI-DS) has programmed these infomorphic neurons and constructed artificial neural net…

Artificial neurons organize themselves

Novel artificial neurons learn independently and are more strongly modeled on their biological counterparts. A team of researchers has programmed these infomorphic neurons and constructed artificial neural networks from them. The special feature is that the individual artificial neurons learn in a self-organized way and draw the necessary information from their immediate environment in the network.

Infomorphic Neurons Bring AI One Step Closer to Brain-Like Learning

Researchers have developed a new kind of artificial neuron—called infomorphic neurons—that can independently learn and self-organize with nearby neurons, mimicking the decentralized learning of biological brains. Inspired by pyramidal cells in the cerebral cortex, these neurons process local signals to adapt and specialize in tasks without external control.

Self-Learning Infomorphic Artificial Neurons Inspired By Biology Revolutionize Machine Learning

A team from the University of Göttingen and Max Planck Institute developed self-organized artificial neurons inspired by biological brain networks, improving flexibility and energy efficiency compared to traditional models, as published in PNAS.