DeepSeek has introduced a powerful new AI system called DeepSeek-GRM that teaches itself how to think, critique, and improve its own answers using a method called Self-Principled Critique Tuning (SPCT).
This approach allows their 27B model to outperform even massive models like GPT-4o in several benchmarks by using repeated sampling and meta reward models.
Meanwhile, OpenAI is upgrading ChatGPT with enhanced memory features and preparing to release new models like GPT-4.1, showing how fast self-improving AI is evolving.
🔍 Key Topics:
- DeepSeek unveils DeepSeek-GRM, a 27B self-teaching AI model using SPCT
- Outperforms GPT-4o and Nemotron-4-340B in benchmarks like Reward Bench and PPE
- Introduces meta reward models and repeated sampling for smarter, more accurate outputs
🎥 What You’ll Learn:
- How SPCT trains AI to critique and improve its own answers without human feedback
- Why repeated sampling and meta RM filtering boost accuracy and flexibility
- What this means for smaller models, real-world applications, and future AI development
📊 Why It Matters:
This video breaks down how DeepSeek-GRM is changing the AI game by proving smaller, self-improving models can match or beat giants like GPT-4o—pushing AI toward more adaptable, efficient, and intelligent systems.
DISCLAIMER:
This video explores DeepSeek-GRM’s architecture, training method, and benchmark results, showing its growing impact on the AI landscape and how it stacks up against top-tier models.
