Among high school students and adults, girls and women are much more likely to use traditional, step-by-step algorithms to ...

Tight PPA constraints are only one reason to make sure an NPU is optimized; workload representation is another consideration.

Recent survey delivers the first systematic benchmark of TSP solvers spanning end-to-end deep learners, hybrid methods and ...

New research shows that advances in technology could help make future supercomputers far more energy efficient. Neuromorphic computers are modeled after the structure of the human brain, and researche ...

Learn a clear, step-by-step approach to solving coding problems—from understanding the prompt and planning an algorithm to ...

Abstract: Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). Among them, ...

AI’s predictive power is transformative, but its lack of explainability, contextual understanding, and causal reasoning ...

Unveiled at CES 2026, this collaboration combines Boston Dynamics' engineering brilliance with Google DeepMind's innovative ...

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex ...

The next frontier in automotive AI is about equipping vehicles to learn, adapt and evolve through orchestrated data that ...

New Analysis Platform Explores Why Household Tasks and Physical Automation Require Embodied Intelligence Beyond Traditional Computer Approaches The next wave of AI is physical AI. AI that understands ...

Online spaces are complex, influential and potentially dangerous — but the education system still treats tech like an optional extra ...