In a recent Views & Comments column published in Engineering, researchers Jinghai Li and Li Guo from the Chinese Academy of Sciences offer profound insights into the future development of data science ...

Advances in artificial intelligence, particularly large language models (LLMs), have been driven by the "scaling law" paradigm: performance improves with more data, computation, and larger models.

Biochar, a carbon-rich material derived from organic waste, is gaining attention for its ability to enhance soil quality, purify water, and sequester carbon. A new review in Biochar X highlights how ...

A single freehand sketch is all it takes! Deep3DSketch-im uses AI to turn abstract lines into detailed 3D models, paving the way for user-friendly design tools in everything from home interiors to ...

Physicians at UC San Diego Health are utilizing artificial intelligence (AI) to develop a non-invasive, computer-based mapping system that has led to a new approach for treating ventricular arrhythmia ...

Say goodbye to hours of tuning hyperparameters! University of Tokyo researchers introduce ADOPT, a groundbreaking optimizer that stabilizes deep learning training across diverse applications without ...

Relocatable modular buildings (RMBs) are emerging as a flexible, sustainable alternative to traditional construction. Built from prefabricated “modules” that can be quickly assembled, dismantled, and ...

A new AI-driven materials map unifies experiments and theory, helping scientists spot look-alike high-performance materials faster, cutting trial-and-error and ...

Contrary to fears that AI will destabilize global emissions, researchers have shown that current adoption trends contribute little to national carbon footprints, and could even help drive cleaner ...

With a novel switching mechanism and analog-digital flexibility, this new memristor tackles one of AI’s biggest flaws: the tendency to forget learned tasks when new ones are introduced—just like the ...

Climate change is already altering weather patterns and ecosystems worldwide. Long-term consequences may include dramatic increases in extreme events or even the collapse of entire ecosystems.

A new interdisciplinary framework reveals how machines and humans generalize knowledge in fundamentally different ways, a breakthrough that could shape the future of sustainable, human-aligned AI.