By the time Carnegie Mellon University (CMU) researcher Hans Moravec published his seminal book on robotics “Mind Children” ...
Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Overview: AI-powered algorithms now drive a major share of global trading activity.Modern trading systems rely more on ...
V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs ...
Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Abstract: Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms ...
Researchers from the University of Vienna (Austria), National Institute of Technology—Wakayama College (NITW; Japan), and Shimane University (Japan) present the largest cephalopod genome sequenced to ...
Energy startup Commonwealth Fusion Systems (CFS) said Thursday it’s working with Google’s DeepMind division to fine tune — and even improve — the operation of its forthcoming Sparc reactor using AI.
Introduction: Optimizing the operation of interconnected hydropower systems presents significant challenges due to complex non-linear dynamics, hydrological uncertainty, and the need to balance ...
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