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Reinforcement Learning
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AI EngineerYouTubeSmall Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI
RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation
Closing the Inference to Post-Training Loop
ART-Optimized Megatron (AOM): 12x higher training throughput
Introducing Clef: our open-source decision models, and new RL fine-tuning platform
RLTL;DR: Self-Improvement by Internalizing Self-Generated Feedback
Reinforcement learning: Why alignment of numerics and MoE routing matter
Getting started with the Agent Reinforcement Trainer (ART)
From Simulation-to-Reality for Robotics
AI EngineerYouTubeBeating RL With Reflection: GEPA and Optimize Anything — Lakshya A. Agrawal, GEPA
AI EngineerYouTubeRobot Demos Are Easy. Reliability Is Hard — Jason Ma, Dyna Robotics
How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows
AI EngineerYouTubeFrom Scratch to SOTA: Training a 3B State-Space Vision Model — Krishna Prasad Srinivasan, Sarvam
Every byte counts: ARCv3 and the case for cross-region RL
REVERSAL-BENCH: A Reversibility Axis and Reset Oracle for Measuring the Reset-Free RL Cliff
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