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UNIDIR:2024年探索人工智能与自主系统的合成数据入门指南(英文版)(32页).pdf

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1、FULL REPORTExploring Synthetic Data for Artificial Intelligence and Autonomous SystemsA PrimerHARRY DENGEXPLORING SYNTHETIC DATA FOR ARTIFICIAL INTELLIGENCE AND AUTONOMOUS SYSTEMS2AcknowledgementsSupport from UNIDIRs core funders provides the foundation for all of the Institutes activities.This pub-

2、lication was funded by the European Union as part of UNIDIRs Security and Technology Programme,which is supported by the governments of Czech Republic,Germany,Italy,the Netherlands and Swit-zerland,and by Microsoft.The author wishes to thank Dr.Giacomo Persi Paoli and Ioana Puscas for their advice a

3、nd assistance on this paper as well as Prof.Tim Watson and Dr.Leslie Sikos for their in-valuable contributions to this research.About UNIDIRThe United Nations Institute for Disarmament Research(UNIDIR)is a voluntarily funded,autonomous institute within the United Nations.One of the few policy instit

4、utes worldwide focusing on disarmament,UNIDIR generates knowledge and promotes dialogue and action on disarmament and security.Based in Geneva,UNIDIR assists the international community to develop the practical,innovative ideas needed to find solutions to critical security problems.CitationH.Deng,Ex

5、ploring Synthetic Data for Artificial Intelligence and Autonomous Systems:A Primer,Geneva,Switzerland:UNIDIR,2023.NoteThe designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United

6、Nations concerning the legal status of any country,territory,city or area,or of its authorities,or concerning the delimitation of its frontiers or boundaries.The views expressed in the publication are the sole responsibility of the individual authors.They do not necessary reflect the views or opinio

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本文主要探讨了合成数据在人工智能和自主系统中的应用,特别是在国际安全领域的应用。合成数据是通过人工在数字世界中创建的数据,旨在改善训练数据集的质量和实用性。文章指出,虽然合成数据不能解决所有数据问题,但它可以提高训练数据集的质量和实用性。合成数据的主要优势包括生成高度多样化的数据集、细粒度控制数据属性、自动标注或数据标签以及成本效益。然而,使用合成数据也存在风险,包括难以完全复制真实世界的复杂物理、数据中毒、意外偏见以及某些合成数据生成技术较低的隐私水平。因此,确保合成数据集的可靠性和质量至关重要。
合成数据在军事应用中的优势与风险是什么? 如何确保合成数据在训练AI系统时避免偏见? 合成数据能否完全替代真实数据用于AI训练?
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