Devdiscourse

AI takes the helm in power systems facing renewable and carbon pressures

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
Morning Overview on MSN

Tesla FSD v14 feels human on real roads, says NVIDIA’s Jim Fan

Tesla’s latest Full Self-Driving software is not just edging closer to autonomy, it is starting to convince seasoned AI ...
Analytics Insight

Avoid These 10 Machine Learning Project Mistakes

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...
The Diplomat

Japan’s Long Return to Artificial Intelligence

Once a pioneer that helped the world lay the foundations of machine learning, Japan’s renewed push into artificial ...
IEEE

Data-Driven Motion Planning: A Survey on Deep Neural Networks, Reinforcement Learning, and Large Language Model Approaches

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.
TMCnet

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...
IEEE

Deep Reinforcement Learning with Graph Neural Networks: An Indepth Analysis of Algorithms and Applications

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...