Thinking Machines Lab offers enterprises a US alternative in open-weight AI

Inkling, a 975-billion-parameter model, can be customized through Tinker and supports a 1-million-token context window, but ...
Tech Xplore

Daydreaming algorithm helps AI remember what matters

During the day, our brain acquires new memories; at night, during sleep, it consolidates the important ones and eliminates ...

New method separates brain signals to show how complex actions are organized

A new Northwestern Medicine study has introduced a novel machine learning method for analyzing how the brain organizes ...
Tech Xplore

Self-driving cars: Near-miss driving data can expedite AV algorithm training

The safety performance of autonomous vehicle (AV) algorithms is boosted by 90% using simulation data that better incorporates ...

AI identifies new particle models that may explain neutrinos' tiny mass

Physicists at the University of California, Irvine, have developed an artificial intelligence system that can autonomously ...
eLife

Neural activity profiles reveal overlapping, intermingled subpopulations spanning area borders in mouse sensorimotor cortex

Single neurons in mouse sensorimotor cortex are organized by their activity features into distinct subpopulations with area-spanning footprints whose boundaries align closely with anatomical and ...
GitHub

Through-the-Wall Radar Human Activity Recognition WITHOUT Using Neural Networks

This paper is dedicated to the memory of my grandma. This is probably the only paper in my life that was written in a hospital the entire time. This is also at the same time the very first work in my ...
IEEE

Artificial Neural Network-Based Fault Detection and Classification for Enhanced Reliability in Electrical Power Transmission Networks

Abstract: The electrical power transmission networks (EPTNs), playing major role to transmit electrical power from location to remote location. The faults in the EPTN may degrade the performance of ...
IEEE

Implementation of Deep Learning Using Matlab-Based Convolutional Neural Network for Covid-19 Forecasting and Classification

Abstract: The outbreak of the Corona Virus Disease or better known as the Korona virus or Covid-19 was first detected to appear in China precisely in China's Wuhan ...
GitHub

Crack detection using one-class SVM

This demo shows how to detect the crack images using one-class SVM. In anomaly detection, normal images can be obtained a lot, while the anomaly images are not frequenctly obtained; we cannot get ...
eLife

Interpreting wide-band neural activity using convolutional neural networks

Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires ...