Underwater robot reveals ocean carbon storage in real time

SINKER is an innovative new instrument equipped with advanced microscopes and cameras to collect detailed data about carbon ...
CIO

20 AI workflow tools for adding intelligence to business processes

Looking to unlock deeper data-driven insights or to build more intelligent business process automations? These popular tools ...

Vibe coding platform Cursor releases first in-house LLM, Composer, promising 4X speed boost

The vibe coding tool Cursor, from startup Anysphere, has introduced Composer, its first in-house, proprietary coding large language model (LLM) as part of its Cursor 2.0 platform update.
Nature

This ‘impressive’ AI model predicted Hurricane Melissa’s perilous growth

Compared with other hurricane models used by the NHC, the DeepMind model is “definitely toward the front of the pack if not ...
Frontiers

Artificial intelligence and deep learning for neural data analysis

Artificial intelligence and deep learning have revolutionized the field of neural data analysis in recent years. The explosion of complex, high-dimensional ...
Frontiers

Advancing Computational Material Science and Mechanics through Integrated Deep Learning Models

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...

IBM's open source Granite 4.0 Nano AI models are small enough to run locally directly in your browser

IBM is entering a crowded and rapidly evolving market of small language models (SLMs), competing with offerings like Qwen3, ...
IEEE

A Multimodal Deep Learning Model Integrating CNN and Transformer for Predicting Chemotherapy-Induced Cardiotoxicity

Abstract: Chemotherapy-induced cardiotoxicity presents a major risk to cancer patients, often leading to severe cardiac complications such as heart failure, myocardial infarction, and arrhythmias.
IEEE

A Novel Deep Generative Model via Semantic-Based Knowledge Distillation for Zero-Shot Learning

Abstract: Zero-Shot Learning (ZSL) aims to identify unseen target classes that lack training data. Most existing methods address the ZSL problem by generating samples of unseen classes based on the ...