This type of neural net is designed to closely approximate the physical structure of the brain. Spiking neural nets often move information according to rules collectively described as the "leaky ...

Because a neural net's one directive is to produce an answer to a prompt, if it can't figure out how to respond, it will return content that may be grammatically coherent but factually incorrect.

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the climate, and stabilize drones during flight.

An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown di ...

Two RIKEN researchers have used a scheme for simplifying data to mimic how the brain of a fruit fly reduces the complexity of ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

University of California - Santa Barbara. "Energy and memory: A new neural network paradigm." ScienceDaily. ScienceDaily, 14 May 2025. <www.sciencedaily.com / releases / 2025 / 05 / 250514164320.htm>.

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the ...

This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...