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Baobao Algorithm Notes
Baobao Algorithm Notes
Dec 7, 2025 · Artificial Intelligence

Key Lessons from Scaling Agent RL Training: Stability, Tooling, and Reward Design

Over recent months of extensive agent reinforcement‑learning experiments across search, data‑analysis, and multi‑source scenarios, the author shares twelve practical insights covering stability, environment‑reward‑algorithm priorities, tool‑call reliability, reward hacking pitfalls, evaluation alignment, and scaling tricks for larger models.

PPO EWMARL ScalingReward Design
0 likes · 7 min read
Key Lessons from Scaling Agent RL Training: Stability, Tooling, and Reward Design
Architect
Architect
Feb 19, 2025 · Artificial Intelligence

Does Scaling Law Still Hold for Grok 3? A Deep Dive into LLM Training Economics

The article critically examines whether the pre‑training Scaling Law still applies to Grok 3, compares its compute usage and model size with DeepSeek and OpenAI models, evaluates the cost‑effectiveness of pre‑training, RL and test‑time scaling, and explores how these insights shape future large‑language‑model development strategies.

Grok-3Model EfficiencyPre‑training
0 likes · 11 min read
Does Scaling Law Still Hold for Grok 3? A Deep Dive into LLM Training Economics
Architect
Architect
Sep 28, 2024 · Artificial Intelligence

How Does OpenAI’s o1 Model Leverage Self‑Play RL and New Scaling Laws?

The article provides an in‑depth technical analysis of OpenAI’s multimodal o1 model, explaining its self‑play reinforcement‑learning pipeline, the novel train‑time and test‑time compute scaling laws, its long‑think reasoning abilities demonstrated through a cipher example, and speculative architectures for generator‑verifier systems.

InferenceOpenAIRL Scaling
0 likes · 35 min read
How Does OpenAI’s o1 Model Leverage Self‑Play RL and New Scaling Laws?