TTT-Discover optimizes GPU kernels 2x faster than human experts — by training during inference

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...
Dot Physics on MSN

Modeling sliding bead on tilting wire using Python | Lagrangian explained

Explore advanced physics with **“Modeling Sliding Bead On Tilting Wire Using Python | Lagrangian Explained.”** In this tutorial, we demonstrate how to simulate the motion of a bead sliding on a ...
IEEE

A Review of Safe Reinforcement Learning Methods for Modern Power Systems

Abstract: Given the availability of more comprehensive measurement data in modern power systems, reinforcement learning (RL) has gained significant interest in ...
Microsoft

New Clickfix variant ‘CrashFix’ deploying Python Remote Access Trojan

CrashFix crashes browsers to coerce users into executing commands that deploy a Python RAT, abusing finger.exe and portable Python to evade detection and persist on high‑value systems.
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Reinforcement learning and organizational management

Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...
GitHub

4_Reinforcement_Learning

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
IEEE

Reinforcement Learning for Multi-Agent Path Finding in Large-Scale Warehouses via Distributed Policy Evolution

Abstract: Efficient multi-agent path finding (MAPF) is essential for large-scale warehousing and logistics systems. Despite the potential of reinforcement learning (RL) methods, current approaches ...