NVIDIA AI Unveils ProRL Agent: A Decoupled Rollout-as-a-Service Infrastructure for Reinforcement Learning of Multi-Turn LLM Agents at Scale

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However, I encountered a significant obstacle: instructing the AI on REPL utilization. My initial approach involved tmux commands for REPL interaction, such as capturing and parsing pane contents. While functional, this method proved inefficient for AI-assisted development. The Claude model struggled considerably, while inferior AI systems performed even more poorly. I would exhaust substantial credits within minutes, receiving only mediocre Lisp implementations that required complete reworking. Attempts with economical alternatives like DeepSeek and Qwen – adequate for certain workplace applications – yielded similarly disappointing results.

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吴鹏,专栏作家,多年从业经验,致力于为读者提供专业、客观的行业解读。