• Title/Summary/Keyword: superintelligence

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Why should we worry about controlling AI? (우리는 왜 인공지능에 대한 통제를 고민해야 하는가?)

  • Rheey, Sang-hun
    • Journal of Korean Philosophical Society
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    • v.147
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    • pp.261-281
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    • 2018
  • This paper will cover recent discussions on the risks of human being due to the development of artificial intelligence(AI). We will consider AI research as artificial narrow intelligence(ANI), artificial general intelligence(AGI), and artificial super intelligence(ASI). First, we examine the risks of ANI, or weak AI systems. To maximize efficiency, humans will use autonomous AI extensively. At this time, we can predict the risks that can arise by transferring a great deal of authority to autonomous AI and AI's judging and acting without human intervention. Even a sophisticated system, human-made artificial intelligence systems are incomplete, and virus infections or bugs can cause errors. So I think there should be a limit to what I entrust to artificial intelligence. Typically, we do not believe that lethal autonomous weapons systems should be allowed. Strong AI researchers are optimistic about the emergence of artificial general intelligence(AGI) and artificial superintelligence(ASI). Superintelligence is an AI system that surpasses human ability in all respects, so it may act against human interests or harm human beings. So the problem of controlling superintelligence, i.e. control problem is being seriously considered. In this paper, we have outlined how to control superintelligence based on the proposed control schemes. If superintelligence emerges, it is judged that there is no way for humans to completely control superintelligence at this time. But the emergence of superintelligence may be a fictitious assumption. Even in this case, research on control problems is of practical value in setting the direction of future AI research.

Design and Implementation of a Time-series Index for Blockchain Analysis Platform (블록체인 분석 플랫폼을 위한 시계열 인덱스 설계 및 구현)

  • Jongho Won;Mi-Young Jang;Dong-Myung Sul;Ji-Yong Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.245-247
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    • 2023
  • 블록체인 분석 플랫폼은 블록체인에 저장된 데이터 기반의 다양한 산업분야 활용성 증대를 위하여 분산 블록체인 기반 대규모/대용량 데이터에 대한 고속 분석을 통하여 신뢰성이 보장되는 보안과 신뢰 기반의 데이터 서비스를 제공하기 위한 분석 플랫폼이다. 본 논문에서는 블록체인 분석 플랫폼에서 제공하는 데이터 분석 중 시계열 데이터에 대한 고성능의 분석을 제공하기 위한 시계열 데이터 인덱스의 설계와 구현에 대하여 기술한다.

EMOS: Enhanced moving object detection and classification via sensor fusion and noise filtering

  • Dongjin Lee;Seung-Jun Han;Kyoung-Wook Min;Jungdan Choi;Cheong Hee Park
    • ETRI Journal
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    • v.45 no.5
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    • pp.847-861
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    • 2023
  • Dynamic object detection is essential for ensuring safe and reliable autonomous driving. Recently, light detection and ranging (LiDAR)-based object detection has been introduced and shown excellent performance on various benchmarks. Although LiDAR sensors have excellent accuracy in estimating distance, they lack texture or color information and have a lower resolution than conventional cameras. In addition, performance degradation occurs when a LiDAR-based object detection model is applied to different driving environments or when sensors from different LiDAR manufacturers are utilized owing to the domain gap phenomenon. To address these issues, a sensor-fusion-based object detection and classification method is proposed. The proposed method operates in real time, making it suitable for integration into autonomous vehicles. It performs well on our custom dataset and on publicly available datasets, demonstrating its effectiveness in real-world road environments. In addition, we will make available a novel three-dimensional moving object detection dataset called ETRI 3D MOD.

Education Improvement Plan Related to Data Analysis & Processing in the ICT Field for the Era of Hyperconnectivity & Superintelligence

  • LEE, Seung-Woo;LEE, Sangwon
    • International Journal of Advanced Culture Technology
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    • v.9 no.4
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    • pp.102-109
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    • 2021
  • Since the 4th Industrial Revolution is implemented based on superintelligence, new insights must be provided through convergence studies with other fields to find optimal solutions to create new ideas. In this paper, we intende to present improvement measures for probability and statistical education, which is an athlete's subject on data analysis and processing in the ICT(Information & Communication Technologies) field in the era of superintelligence of the 4th industrial revolution. This paper aims to strengthen competitiveness through early development and commercialization of new technologies by presenting probabilities and statistical curriculums that require linkage in the ICT field. Second, it is necessary to present an educational system diagram linking probabilities and statistics in the ICT field to prepare a mid- to long-term response strategy for ICT education in response to innovative changes. Third, through a survey, we intend to present an effective educational operation plan linking probability and statistics to ICT major subjects by analyzing the perception of probability, statistical importance, and utilization of majors in this field.

A Study on Brain Tumor Diagnosis and Classification using CNN Model: BTX (Brain Tumor X(BTX): CNN 모델을 활용한 뇌종양 진단 및 분류에 관한 연구)

  • Honggu Kang;Huigyu Yang;Duc-Tai Le;Hyunseung Choo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.574-575
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    • 2023
  • 뇌종양은 인체에 발생하는 여러 종양 중 세 번째로 많이 나타난다. 뇌종양 환자 수는 지속해서 증가하고 있으며, 별도의 예방법이 존재하지 않아 빠른 진단 및 종양 종류에 따른 치료가 매우 중요하다. 현재 뇌종양 진료는 전문의가 전용 소프트웨어로 뇌 Magnetic Resonance Imaging(MRI) 이미지를 확대, 축소하여 자세히 살펴보면서 종양의 크기, 위치, 양성/악성 여부 등을 판단한다. 이 방식은 의사의 숙련도에 따라 진료 시간과 판독의 차이가 크고 오진 가능성이 있다. 본 논문은 뇌종양 종류별 MRI 이미지가 학습된 CNN 모델을 사용한 의사의 뇌종양 진단 시간 단축, 진단 정확도 향상을 통해 환자 치료의 효율성을 높이는 방안으로 Brain Tumor X를 제안한다.

KMSAV: Korean multi-speaker spontaneous audiovisual dataset

  • Kiyoung Park;Changhan Oh;Sunghee Dong
    • ETRI Journal
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    • v.46 no.1
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    • pp.71-81
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    • 2024
  • Recent advances in deep learning for speech and visual recognition have accelerated the development of multimodal speech recognition, yielding many innovative results. We introduce a Korean audiovisual speech recognition corpus. This dataset comprises approximately 150 h of manually transcribed and annotated audiovisual data supplemented with additional 2000 h of untranscribed videos collected from YouTube under the Creative Commons License. The dataset is intended to be freely accessible for unrestricted research purposes. Along with the corpus, we propose an open-source framework for automatic speech recognition (ASR) and audiovisual speech recognition (AVSR). We validate the effectiveness of the corpus with evaluations using state-of-the-art ASR and AVSR techniques, capitalizing on both pretrained models and fine-tuning processes. After fine-tuning, ASR and AVSR achieve character error rates of 11.1% and 18.9%, respectively. This error difference highlights the need for improvement in AVSR techniques. We expect that our corpus will be an instrumental resource to support improvements in AVSR.

Unleashing the Potential of Vision Transformer for Automated Bone Age Assessment in Hand X-rays (자동 뼈 연령 평가를 위한 비전 트랜스포머와 손 X 선 영상 분석)

  • Kyunghee Jung;Sammy Yap Xiang Bang;Nguyen Duc Toan;Hyunseung Choo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.687-688
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    • 2023
  • Bone age assessment is a crucial task in pediatric radiology for assessing growth and development in children. In this paper, we explore the potential of Vision Transformer, a state-of-the-art deep learning model, for bone age assessment using X-ray images. We generate heatmap outputs using a pre-trained Vision Transformer model on a publicly available dataset of hand X-ray images and show that the model tends to focus on the overall hand and only the bone part of the image, indicating its potential for accurately identifying the regions of interest for bone age assessment without the need for pre-processing to remove background noise. We also suggest two methods for extracting the region of interest from the heatmap output. Our study suggests that Vision Transformer holds great potential for bone age assessment using X-ray images, as it can provide accurate and interpretable output that may assist radiologists in identifying potential abnormalities or areas of interest in the X-ray image.

Determining UAV Flight Direction Control Method for Shooting the images of Multiple Users based on NUI/NUX (NUI/NUX 기반 복수의 사용자를 촬영하기 위한 UAV 비행방향 제어방법)

  • Kwak, Jeonghoon;Sung, Yunsick
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.445-446
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    • 2018
  • 최근 무인항공기 (Unmanned Aerial Vehicle, UAV)에 장착한 카메라를 활용하여 사용자의 눈높이가 아닌 새로운 시각에서 사용자를 촬영한 영상을 제공한다. 사용자를 추적하며 촬영하기 위해 저전력 블루투스 (Bluetooth Low Energy, BLE) 신호, 영상, 그리고 Natural User Interface/Natual User Experience(NUI/NUX) 기술을 활용한다. BLE 신호로 사용자를 추적하는 경우 사용자의 후방에서 추적하며 사용자만을 추적하며 촬영 가능한 문제가 있다. 하지만 복수의 사용자를 전방에서 추적하며 촬영하는 방법이 필요하다. 본 논문에서는 복수의 사용자를 추적하며 전방에서 촬영하기 위해 UAV의 비행방향을 결정하는 방법을 설명한다. 복수의 사용자로부터 측정 가능한 BLE 신호들을 UAV에서 측정한다. 복수개의 BLE 신호의 변화를 활용하여 UAV의 비행방향을 결정한다.

Design of Photographing System for Multiple Users based on UAV (UAV 기반 복수의 사용자를 촬영하기 위한 촬영 시스템 설계 연구)

  • Kwak, Jeonghoon;Sung, Yunsick
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.479-480
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    • 2018
  • 최근 무인항공기(Unmanned Aerial Vehicle, UAV)에 부착된 카메라로 사용자를 촬영함으로써 레저 및 여행 중 영상을 기록하기 위해 활용하고 있다. UAV에 부착된 카메라로 사용자를 촬영하기 위해 사용자가 직접 조종하거나 NUI/NUX 기술을 활용한다. UAV가 비행해야 되는 비행경로를 미리 설정하거나 단일 사용자를 추적해서 자동적으로 UAV가 비행하며 UAV에 부착된 카메라로 단일 사용자 중심으로 촬영한다. 하지만 레저 및 여행 중 영상을 기록하는 과정에서 단일 사용자 중심이 아니라 복수의 사용자를 고려하여 촬영해야 되는 경우가 있다. UAV가 복수의 사용자 위치를 고려하여 복수의 사용자를 촬영하는 시스템이 필요하다. 본 논문에서는 복수의 사용자를 촬영하기 위한 촬영 시스템을 설계한다. 촬영 시스템은 복수의 사용자 위치의 변화를 기반으로 UAV를 제어한다.

Artificial Intelligence for the Fourth Industrial Revolution

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1301-1306
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    • 2018
  • Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.