DeepSeek AI: Efficiency, Architecture, and Global Implications

• Author(s): Tejas Shinde; Sanket Salve; Abrashmeena Shaikh
• Paper ID: 1717720
• Page: 2175-2176
• Published Date: 18-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

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

Citations

IRE Journals:
Tejas Shinde, Sanket Salve, Abrashmeena Shaikh "DeepSeek AI: Efficiency, Architecture, and Global Implications" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 2175-2176 https://doi.org/10.64388/IREV9I11-1717720

IEEE:
Tejas Shinde, Sanket Salve, Abrashmeena Shaikh "DeepSeek AI: Efficiency, Architecture, and Global Implications" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717720