So, what is machine learning in the first place? And if the machines are so smart, why are they still so dumb? The point of ...

The seven decades of "artificial intelligence" have been marked by exaggerated promises, surprising developments and ...

This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be replaced with ...

This article introduces the energy-driven graph neural OOD (EGN-OOD) detector, a novel framework designed to address the complexities of OOD data in dynamic Internet of Things (IoT) environments. By ...

Most people assume if they have knee pain, it is due to a problem with the knee joint. This is not always the case. While the discomfort can be due to a knee condition, it can also be the result of a ...

Tinymind is a Neural Network and Machine Learning project intended to provide a C++ template library for neural nets and machine learning algorithms within embedded systems.

One of the central problems in neuroscience is the characterization and understanding of the neural code. In 1968 Perkel and Bullock defined four key functions for a candidate neural code ...

Penticton's fire chief is reflecting on many successes during his first full year at the helm of the local fire department. Chief Mike Larsson joined the Penticton team in 2023, and has since ...

AI models like artificial neural networks and language models help scientists solve a variety of problems, from predicting the 3D structure of proteins to designing novel antibiotics from scratch.

The result? A fully self-training, neural network-based thrust vector control (TVC) system that promises smarter and more efficient stabilization in real time. The journey started with a basic 3D ...