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Recent research suggests that a number of neuronal characteristics, traditionally believed to stem from the cell body or soma, may actually originate from processes in the dendrites. This discovery has significant implications for the study of degenerative diseases and for understanding the differen

New understandings could impact research on the origin of degenerative diseases, as well as sleep-and-awake states of brain activity.

Enhancing existing architectures using global decisions can pave the way for improved AI, which can improve its classification tasks without the need for additional layers.

Deep Learning (DL) performs classification tasks using a series of layers. To effectively execute these tasks, local decisions are performed progressively along the layers. But can we perform an all-encompassing decision by choosing the most influential path to the output rather than performing these decisions locally? In an article published today in Scientific Reports, researchers from Bar-Ilan University in Israel answer this question with a resounding "yes". Pre-existing deep archi...

In 1990, Australian roboticist Rodney Brooks published a paper titled "Elephants don't play chess," which introduced the concept that AI can improve by

Artificial neural networks based on human brain dynamics can outperform current deep learning models in learning capabilities.

Artificial intelligence stems from human brain dynamics, but brain learning is restricted in a number of significant aspects compared to deep learning.

Get latest articles and stories on Science at LatestLY. Artificial intelligence has traditionally been derived from human brain dynamics. However, as compared to deep learning, brain learning has several important limitations (DL). First, efficient DL wire topologies (architectures) have several tens of feedforward (consecutive) layers, whereas brain dynamics have just a few feedforward layers. Science News | Is Brain Learning Slower Than Artificial Intelligence? Read on to Know What This Study...