GitHub

Flash LiDAR Vehicle Detection with MATLAB Dataset and Deep Learning Benchmarks

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 ...
ZDNet

True agentic AI is years away - here's why and how we get there

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
Phys.org

Researchers call for more conversation-rich learning as AI spreads

Generative artificial intelligence could result in a renewed emphasis on conversational approaches to teaching, researchers say, as chatbots make it easier to bypass recall-based learning and test the ...
Hosted on MSN

Prank Calling a Brand New Primary School

In this prank call, I rang a brand new primary school with some very strange questions — like asking if they offer ninja training, have nap time for adults, or allow emotional support crayons. The ...
acm.org

Rediscovering Reinforcement Learning

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...
marktechpost

Weak-for-Strong (W4S): A Novel Reinforcement Learning Algorithm that Trains a weak Meta Agent to Design Agentic Workflows with Stronger LLMs

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...
IEEE

A TD3-Based Reinforcement Learning Algorithm With Curriculum Learning for Adaptive Yaw Control in All-Wheel-Drive Electric Vehicles

Abstract: A novel artificial intelligence-based approach for the direct yaw control (DYC) of an all-wheel drive (AWD) electric vehicle (EV) is proposed in this paper. To improve adaptability and ...
marktechpost

Alibaba Introduces Group Sequence Policy Optimization (GSPO): An Efficient Reinforcement Learning Algorithm that Powers the Qwen3 Models

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.