Tech Xplore on MSN

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
pv magazine International

PV energy forecasting based on genetic algorithms, dynamic neural network

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...
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 ...
JSTOR Daily

A Gillespie Algorithm for Non-Markovian Stochastic Processes

The Gillespie algorithm provides statistically exact methods for simulating stochastic dynamics modeled as interacting sequences of discrete events including systems of biochemical reactions or ...
eWeek

Types of AI Models: A Deep Dive into AI Architecture

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
EurekAlert!

Drug treatment alters performance in a neural microphysiological system of information processing

Assessment of pharmacological intervention on in vitro neural systems often emphasises molecular and structural changes. However, neural systems fundamentally process and act on information. For ...
InfoWorld

Styles of machine learning: Intro to neural networks

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks. Artificial intelligence ...