News

Neurosymbolic AI is the answer to large language models’ inability to stop hallucinating
Neurosymbolic AI combines the learning of LLMs with teaching the machine formal rules that should make them more reliable and ...
AI tool reveals single-cell structure of chromosomes—in 3D
In a leap forward for genetic and biomedical research, two scientists at the University of Missouri have developed a powerful ...
IEEE21h
Ohm's Law + Kirchhoff's Current Law = Better AI: Neural-Network Processing Done in Memory with Analog Circuits will Save Energy
Abstract: Machine learning and artificial intelligence (AI) have already penetrated so deeply into our life and work that you might have forgotten what interactions with machines used to be like. We ...
IEEE3d
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks
Abstract: The last decade of machine learning has seen drastic increases in scale and capabilities. Deep neural networks (DNNs) are increasingly being deployed in the real world. However, they are ...
GitHub3d
Modern Convolutional Neural Network Architectures
Convolutional Neural Networks (ConvNets or CNNs) are a class of neural networks algorithms that are mostly used in visual recognition tasks such as image classification, object detection, and image ...