Workshop: Training Agents at the frontier of AI Industry

Covers how teams are applying RL to train agents on open models, including environment and benchmark design and scaling tooling. Useful for engineers considering post-training over prompting.

• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
• benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.

• videoLlama: Local AI on Your Mac
• videoPi Durable EXPLAINED: Build Always-On Agents with Local Models
• videoTraining Agents 3: Reinforcement Learning
• videoTraining Agents 2: Live tutorial on model distillation for training custom agents.

• videoTraining Agents 4: From reward functions to environments.Hugging Face
• videoRL for Agents Workshop - Deep Dive on Training Agents with RL and Open SourceHugging Face
• videoLearning on the Job: The Future of Post-Training — Raymond Feng, Applied ComputeAI Engineer

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