Skip to main content

DeepSeek

Diagrams | Matrices | X List

DeepSeek | Whitepaper

Context​

Analysis​

Reasoning Mechanisms

  • Chain-of-Thought (CoT) Reasoning: The model breaks down problems into logical steps, mimicking human problem-solving. For example, it might solve a math problem by first identifying variables, then applying formulas, and finally verifying intermediate results.
  • Self-Reflection: During training, DeepSeek-R1 developed the ability to review its reasoning steps independently, pausing to reassess approaches when inconsistencies arise25. This "aha moment" behavior emerged naturally through RL training.
  • Exploratory Learning: Rather than relying on memorization, the model tests multiple solution paths to find optimal approaches.

Leadership​

Coding​