Topic: GRPO

Today we examine how the startup "Yuaiweiwu" is leveraging AI-native applications to solve the long-standing "impossible triangle" of quality, scale, and cost in education. By integrating advanced Chain-of-Thought (CoT) scaling with a proprietary "Good Teacher's Red Book" of pedagogical knowledge, they have developed a model that prioritizes student guidance over simply providing answers. Our analysis highlights their use of Group Relative Policy Optimization (GRPO) to refine teaching paths and a self-developed multimodal voice model that pushes ASR accuracy from 80% to over 95% in noisy environments. We find that their unique approach, which combines specialized data fine-tuning with reinforcement learning, enables a million-user-scale platform to deliver one-on-one, human-like interaction. This technological leap signifies a shift from generic large language models to specialized educational agents capable of understanding context and emotional resonance.