DeepSeek AI: Efficiency, Architecture, and Global Implications

@article{1717720,
      author = {Tejas Shinde, Sanket Salve, Abrashmeena Shaikh},
      title = {DeepSeek AI: Efficiency, Architecture, and Global Implications},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {2175-2176},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1717720.pdf},
      abstract = {This paper presents a comprehensive study of DeepSeek AI, a Chinese artificial intelligence startup that has gained global recognition for its cost-efficient large language model (LLM) training and deployment. Founded in 2023, DeepSeek has released models such as DeepSeek-V2, V3, R1, and DeepSeek-Coder, which demonstrate competitive performance at a fraction of the training cost of Western models. The paper explores DeepSeek’s architecture, innovations, applications, and risks, while also discussing broader geopolitical, ethical, and economic implications. It concludes with a reflection on future research directions and the need for transparent, responsible AI development.},
      keywords = {DeepSeek AI, Large Language Models, Artificial Intelligence, Efficiency, Open Source, Geopolitics},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1717720}
  }