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OpenAI at QCon AI NYC: Fine Tuning the Enterprise
At QCon AI NYC 2025, Will Hang from OpenAI unveiled Agent RFT—a cutting-edge reinforcement fine-tuning approach for tool-using agents. By optimizing prompts and tasks before model adjustments, Hang showcased effective strategies to enhance decision-making and efficiency, emphasizing a balanced grading system. The session revealed a future where smarter agents reduce latency and improve outcomes. By Andrew Hoblitzell
Top posts from tech subreddits• Updated 6 minutes ago
Anyone else feel like the hardest part of agents is just getting them to do stuff reliably?
AI researcher Andrej Karpathy says he's "bearish on reinforcement learning" for LLM training
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stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
habitat-lab
A modular high-level library to train embodied AI agents across a variety of tasks and environments.
qlib
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Gymnasium
An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)