Columbia News

An Interdisciplinary Project Investigates Art Images and AI

Latent spaces are abstract, high-dimensional areas within neural networks where patterns and relationships are encoded, but not readily interpretable by humans. Although latent space studies are still ...
MIT Technology Review

The Pentagon is planning for AI companies to train on classified data, defense official says

The generative AI models used in classified environments can answer questions but don't currently learn from the data they ...
University of California, San Francisco

This Multiview AI Imaging Can Improve Cardiac Diagnostic Accuracy

Heart disease is the leading cause of adult death worldwide, making cardiovascular disease diagnosis and management a global health priority. An echocardiogram, or cardiac ultrasound, is one of the ...
IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
Business Insider

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification BEIJING, Feb.06, 2026––WiMi Hologram ...
CNN

With ICE using Medicaid data, hospitals and states are in a bind over warning immigrant patients

The Trump administration’s move to give deportation officials access to Medicaid data is putting hospitals and states in a bind as they weigh whether to alert immigrant patients that their personal ...
techxplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
IEEE

Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification

Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...
MIT Technology Review

Using unstructured data to fuel enterprise AI success

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Slate

CNN Is Using an Election Polling Tool That Anyone Can Rig

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. By mid-October, the Democrats’ chances ...