Rahul Naskar has years of experience writing news and features related to Android, phones, and apps. Outside the tech world, he follows global events and developments shaping the world of geopolitics.
This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...
In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
In reinforcement learning (RL), an agent learns to achieve its goal by interacting with its environment and learning from feedback about its successes and failures. This feedback is typically encoded ...
Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...
Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...
The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...
Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.
AgiBot announced a key milestone this week with the successful deployment of its Real-World Reinforcement Learning system in a manufacturing pilot with Longcheer Technology. The pilot project marks ...
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