Science Daily

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...
Deep Learning with Yacine on MSN

RMSProp optimization from scratch in Python

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...
Semiconductor Engineering

Spiking Neural Networks: Hardware & Algorithm Developments

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...
eWeek

Neural Networks vs. Deep Learning

Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...
Diginomica

Generative AI needs better context - you can't talk about Large Language Models without reverse neural networks and backpropagation

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...
Science Daily

A new neural network makes decisions like a human would

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...
Semiconductor Engineering

A Survey Of Recent Advances In Spiking Neural Networks From Algorithms To HW Acceleration

A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of ...