• Title/Summary/Keyword: 인공지능 기술 특허

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Analysis of Korea's Artificial Intelligence Competitiveness Based on Patent Data: Focusing on Patent Index and Topic Modeling (특허데이터 기반 한국의 인공지능 경쟁력 분석 : 특허지표 및 토픽모델링을 중심으로)

  • Lee, Hyun-Sang;Qiao, Xin;Shin, Sun-Young;Kim, Gyu-Ri;Oh, Se-Hwan
    • Informatization Policy
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    • v.29 no.4
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    • pp.43-66
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    • 2022
  • With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.

Analysis of Artificial Intelligence's Technology Innovation and Diffusion Pattern: Focusing on USPTO Patent Data (인공지능의 기술 혁신 및 확산 패턴 분석: USPTO 특허 데이터를 중심으로)

  • Baek, Seoin;Lee, Hyunjin;Kim, Heetae
    • The Journal of the Korea Contents Association
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    • v.20 no.4
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    • pp.86-98
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    • 2020
  • The artificial intelligence (AI) is a technology that will lead the future connective and intelligent era by combining with almost all industries in manufacturing and service industry. Although Korea is one of the world's leading artificial intelligence group with the United States, Japan, and Germany, but its competitiveness in terms of artificial intelligence patent is relatively low compared to others. Therefore, it is necessary to carry out quantitative analysis of artificial intelligence patents in various aspects in order to examine national competitiveness, major industries and future development directions in artificial intelligence technology. In this study, we use the IPC technology classification code to estimate the overall life cycle and the speed of development of the artificial intelligence technology. We collected patents related to artificial intelligence from 2008 to 2018, and analyze patent trends through one-dimensional statistical analysis, two-dimensional statistical analysis and network analysis. We expect that the technological trends of the artificial intelligence industry discovered from this study will be exploited to the strategies of the artificial intelligence technology and the policy making of the government.

A Technology Landscape of Artificial Intelligence: Technological Structure and Firms' Competitive Advantages (인공지능 기술 랜드스케이프 : 기술 구조와 기업별 경쟁우위)

  • Lee, Wangjae;Lee, Hakyeon
    • Journal of Korea Technology Innovation Society
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    • v.22 no.3
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    • pp.340-361
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    • 2019
  • This study analyzes the technological structure of artificial intelligence (AI) and technological capabilities of AI companies based on patent information. 2589 AI patents registered in USPTO from 2007 to 2017 were collected and analyzed by the Latent Dirichlet Allocation (LDA) to derive 20 AI technology topics. Analysis of technology development trends by AI technology reveals that visual understanding, data analysis, motion control, and machine learning are growing, while language understanding and speech technology are sluggish. In addition, we also investigated leading companies in each sub-field of AI as well as core competencies of global IT companies. The findings of this study are expected to be fruitfully used for formulation and implementation of technology strategy of AI companies.

Research on Core patent mining methods based on key components of Generative AI (생성형 인공지능 기술의 핵심 구성 요소 기반 주요 특허 발굴 방법에 관한 연구)

  • Gayun Kim;Beom-Seok Kim;Jinhong Yang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.292-300
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    • 2023
  • This paper proposes a patent discovery method and strategy for Generative AI-related patents by utilizing qualitative evaluation indicators established based on the core components of the technology. Currently, the evaluation of patent quality relies on quantitative indicators, but existing quantitative indicators cannot represent the characteristics of Generative AI technology, making it difficult to accurately evaluate. Therefore, there is a need for additional qualitative indicators that consider technical characteristics based on patent claims, which can reveal the actual strength of the patent. In this paper, we propose a new evaluation index considering the technical characteristics of Generative AI. Core patents were selected using the proposed evaluation index, and the appropriateness of the proposed index was verified through the existing quantitative evaluation method for the selected core patents.

A study on a multi-dimensional national technological-level evaluation on artificial intelligence technology case (인공지능 분야에 대한 국가 기술수준 다차원 평가 실증 연구)

  • Cho, Ilgu
    • Proceedings of the Korea Contents Association Conference
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    • 2018.05a
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    • pp.89-90
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    • 2018
  • 최근 4차 산업혁명의 핵심분야로 부상한 인공지능 기술에 미국, 중국, 일본, EU 등 주요국가와 국내 인공지능 기술수준을 보다 신뢰성 높은 전문가, 특허, 논문 등 다차원 평가를 통해 객관적인 기술수준 평가와 이를 바탕으로 인공지능 분야의 기술경쟁력 확보를 위한 연구개발(R&D) 투자전략 수립 및 사업 추진에 대한 기본방향 설정에 대한 기술경영 프레임워크를 제안한다.

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Research on the Development Direction of Language Model-based Generative Artificial Intelligence through Patent Trend Analysis (특허 동향 분석을 통한 언어 모델 기반 생성형 인공지능 발전 방향 연구)

  • Daehee Kim;Jonghyun Lee;Beom-seok Kim;Jinhong Yang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.279-291
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    • 2023
  • In recent years, language model-based generative AI technologies have made remarkable progress. In particular, it has attracted a lot of attention due to its increasing potential in various fields such as summarization and code writing. As a reflection of this interest, the number of patent applications related to generative AI has been increasing rapidly. In order to understand these trends and develop strategies accordingly, future forecasting is key. Predictions can be used to better understand the future trends in the field of technology and develop more effective strategies. In this paper, we analyzed patents filed to date to identify the direction of development of language model-based generative AI. In particular, we took an in-depth look at research and invention activities in each country, focusing on application trends by year and detailed technology. Through this analysis, we tried to understand the detailed technologies contained in the core patents and predict the future development trends of generative AI.

Technology Convergence Map Creation and Country Profile Analysis in the Field of Artificial Intelligence (인공지능 분야의 기술융합맵 생성 및 국가 프로파일 분석)

  • Kim, Hyun-Woo;Noh, Kyung-Ran;Ahn, Sejung;Kwon, Oh-Jin
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.1
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    • pp.139-146
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    • 2017
  • The interest about Artificial Intelligence through the AlphaGo Match in Korea has been increasing rapidly. So far, very little has been done in Artificial Intelligence. The aim of this paper is to reveal technology convergence and to assess the country profile in the field of artificial intelligence(AI). Technology convergence map was created after extracting USPTO patent grants and Web of Science data and generating matrics in the field of AI. Several Indicators were obtained by extracting and calculating SCOPUS Data that KISTI has. According to USPTO patent grants, it shows that AI technology has a strong relationship with several sectors such as cost/price determination, image analysis, and surgery, etc. Also, AI has a active convergence with some fields of Electrical and Electronic Engineering, BioTechnologies, and Medicine etc. According to country profile analysis, Korea reaches a global average growth index. However, in terms of specialization index (SI) and average of relative citations (ARC), there is a large gap between Korea and research leading countries.

Analyzing employment trends in response to AI exposure: K-shaped labor polarization in Korea (인공지능 노출 정도에 따른 고용 추세 분석: K자형 고용 양극화)

  • Lee, Yeseul;Hwang, Hyeonjun
    • Informatization Policy
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    • v.30 no.3
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    • pp.69-91
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    • 2023
  • The impact of technological advancements on employment is a matter of ongoing debate, with discussions on the effects of AI technology development on employment being particularly scarce. This study employs the natural language processing technique (SBERT) and patents to calculate an occupation-based AI exposure score and to analyze employment trends by group. It proposes a method for calculating the AI exposure score based on the similarity between Korean patent information and US job descriptions and linking SOC(U.S.) and KSCO(Korea). The analysis of domestic AI patent applications and regional employment data in the KOSIS Database since 2013 reveals a K-shaped polarization pattern in Korean employment trends among groups with above and below average levels of AI exposure.

첨단기술 어디까지 왔나 - 산업기계분야에서 인공지능기술의 개발동향(1)

  • 문인혁
    • 발명특허
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    • v.16 no.10 s.188
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    • pp.52-57
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    • 1991
  • 인간이 지닌 지적인 능력을 규명하여 컴퓨터로 하여금 지능이 필요로 하는 일을 수행할 수 있도록 하는 인공지능(Artificial Intelligence, 이하 AI)기술에 관한 관심이 높아지고 있는 가운데 선진각국에서는 철강, 자동차, 산업기계 등 다양한 분야에서 제품의 라이프 사이클 단축, 다품종 소량 생산, 효율적인 조업, 고도의 품질제어 요구에 유연하게 대처하기 위하여 인공지능 개발 프로젝트를 활발히 진행중이다. 본고에서는 산업기계분야에서 인공지능 개발에 필요한 기반환경에 대하여 살펴보고 선진국의 주요 개발동향 및 우리나라의 개발실태를 살표보고자 한다.

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첨단기술 어디까지 왔나 - 산업기계분야에서 인공지능기술의 개발동향(완)

  • 문인혁
    • 발명특허
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    • v.16 no.11 s.189
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    • pp.50-53
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    • 1991
  • 인간이 지닌 지적인 능력을 규명하여 컴퓨터로 하여금 지능이 필요로 하는 일을 수행할 수 있도록 하는 인공지능(Artificial Intelligence, 이하 AI)기술에 관한 관심이 높아지고 있는 가운데 선진각국에서는 철강, 자동차, 산업기계 등 다양한 분야에서 제품의 라이프 사이클 단축, 다품종 소량 생산, 효율적인 조업, 고도의 품질제어 요구에 유연하게 대처하기 위하여 인공지능 개발 프로젝트를 활발히 진행중이다. 본고에서는 산업기계분야에서 인공지능 개발에 필요한 기반환경에 대하여 살펴보고 선진국의 주요 개발동향 및 우리나라의 개발실태를 살펴보고자 한다.

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