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Technical Trends in On-device Small Language Model Technology Development

온디바이스 소형언어모델 기술개발 동향

  • G. Kim ;
  • K. Yoon ;
  • R. Kim ;
  • J. H. Ryu ;
  • S. C. Kim
  • 김근용 (엣지컴퓨팅응용서비스연구실) ;
  • 윤기하 (엣지컴퓨팅응용서비스연구실) ;
  • 김량수 (엣지컴퓨팅응용서비스연구실) ;
  • 류지형 (엣지컴퓨팅응용서비스연구실) ;
  • 김성창 (엣지컴퓨팅응용서비스연구실)
  • Published : 2024.08.01

Abstract

This paper introduces the technological development trends in on-device SLMs (Small Language Models). Large Language Models (LLMs) based on the transformer model have gained global attention with the emergence of ChatGPT, providing detailed and sophisticated responses across various knowledge domains, thereby increasing their impact across society. While major global tech companies are continuously announcing new LLMs or enhancing their capabilities, the development of SLMs, which are lightweight versions of LLMs, is intensely progressing. SLMs have the advantage of being able to run as on-device AI on smartphones or edge devices with limited memory and computing resources, enabling their application in various fields from a commercialization perspective. This paper examines the technical features for developing SLMs, lightweight technologies, semiconductor technology development trends for on-device AI, and potential applications across various industries.

Keywords

Acknowledgement

본 연구는 산업통상자원부(MOTIE)와 한국에너지기술평가원(KETEP)의 지원을 받아 수행한 연구 과제입니다[No. 2021202090053B].

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