Seek .(US:SKLTY) Zhong Guo Xin Wen Wang·2025-09-18 02:55Core Insights - DeepSeek, a Chinese company focused on large language models (LLM) and artificial general intelligence (AGI), has gained attention for its open-source AI model DeepSeek-R1, which employs a large-scale inference model training method [1] - The training method was published in the prestigious journal Nature, revealing that the reasoning capabilities of LLMs can be enhanced through pure reinforcement learning, thereby reducing the human input required for performance enhancement [1] - The model outperformed traditional LLMs in tasks related to mathematics, programming competitions, and graduate-level STEM problems [1] Group 1 - DeepSeek-R1 includes a supervised in-depth training phase to optimize the reasoning process, utilizing reinforcement learning instead of human examples to develop reasoning steps, which reduces training costs and complexity [2] - The model achieved scores of 77.9% and 79.8% in mathematical benchmark tests for DeepSeek-R1-Zero and DeepSeek-R1, respectively, and also excelled in programming competitions and graduate-level biology, physics, and chemistry problems [2] - A concurrent article in Nature highlighted some limitations of the current version of DeepSeek-R1, such as language mixing and sensitivity to prompt engineering, indicating areas for improvement in future versions [2] Group 2 - The DeepSeek-AI team concluded that future research should focus on optimizing the reward process to ensure reliable reasoning and task outcomes [3]