The results are really astonishing. Tests show that offices save up to 37% on their energy bills with AI-optimized and ...

This article explores how generative chemistry accelerates drug design, identifies novel compounds and complements ...

Keywords: multi-objective hyperparameter optimization, Bayesian optimization, neuromorphic computing, spiking neural networks, accurate and energy-efficient machine learning Citation: Parsa M, ...

By Ramesh Srivatsava ARUNACHALAM[1]The Third UN Ocean Conference (UNOC3), scheduled for June 9-13, 2025, in Nice, France, represents an unprecedented opportunity for global marine conservation as ...

The size and complexity of energy system optimization models have increased significantly in recent years, driven by the availability of high-resolution spatial data. We present complexity reduction ...

At the heart of Trade 350 App lies a proprietary AI engine that continuously learns and evolves. Rather than relying on ...

Solving the path planning problem of Autonomous Underwater Vehicles (AUVs) is crucial for reducing energy waste and improving operational efficiency. However, two main challenges hinder further ...

Uncrewed aerial vehicles (UAVs) require robust communication for operational reliability. Recent research has explored artificial intelligence techniques, particularly metaheuristic algorithms, to ...

It’s playing out in the quantum computers’ circuitry and deep neural networks’ algorithms as physicists try to shed light on what is at the center of a black hole.