DeepSeek: A holistic survey of foundations, applications and ethical consideration

Abstract

In recent years, the fields of scientific research have been significantly influenced by advancements in artificial intelligence (AI), machine learning, and tools such as ChatGPT. Recently, Deepseek has emerged as a prominent player in this domain, evolving into a sophisticated large language model (LLM) that has attracted considerable attention for its innovative contributions to AI initiatives. Deepseek is characterized by enhanced efficiency and reasoning capabilities, which contribute to cost reduction in various applications. This paper aims to deliver a thorough review of Deepseek's background, its diverse applications, the challenges it faces, biases, ethical considerations, limitations, and its future prospects. The advancements made by Deepseek, particularly in areas such as code generation, mathematical reasoning, and natural language processing, position it as a competitive alternative to established AI models like ChatGPT. Nevertheless, issues related to computational resource limitations, biases, and ethical considerations pose significant challenges to its effective implementation and widespread adoption. Additionally, this paper will explore the ethical implications associated with open-source AI models and their vulnerability to misuse. It is important to acknowledge that despite the controversies and challenges surrounding Deepseek, its ongoing enhancements—such as multilingual capabilities and community-driven research—indicate a promising trajectory for the future. This review seeks to provide a deeper understanding of the emerging Deepseek AI technology, its influence on AI research, and potential avenues for future development.