How do AI coding agents work? We look under the hood.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Open-source software sheds light on cancer's hidden genetic networks

University of Navarra (Spain) researchers have developed RNACOREX, a new open-source software capable of identifying gene ...
IEEE

Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network

Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
EurekAlert!

New multi-modal AI framework brings human-like reasoning to self-driving vehicles

Autonomous driving systems increasingly rely on data-driven approaches, yet many still struggle with reasoning, handling rare scenarios, and transparently explaining their actions. A new study ...
Modern Engineering Marvels on MSN

Hassabis reveals AI-driven infrastructure threats and rising AGI risks

Could the next cyberattack on a nation’s power grid be orchestrated by artificial intelligence? According to Demis Hassabis, CEO of Google DeepMind, that possibility is no longer a theoretical one.
IEEE

Learning-Based Motion Planning Leveraging Multivariate Deep Evidential Regression

Abstract: Learning-based motion planning methods have shown significant promise in enhancing the efficiency of traditional algorithms. However, they often face performance degradation in novel ...
GitHub

Variational autoencoder with Kolmogorov-Arnold Network for spatial domain detection.

Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121, torch_geometric==2.3.1, torch-sparse==0.6.18+pt21cu121, and torchvision==0.16.0+cu121. The stkan is an ...