Holistic Artificial Intelligence

被引:0
作者
Feng, Junlan [1 ]
机构
[1] Artificial Intelligence and Smart Operation Center, China Mobile Institute, Beijing
来源
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2024年 / 47卷 / 04期
关键词
artificial intelligence; atomization; big loop; network native; secure; trusty;
D O I
10.13190/j.jbupt.2023-306
中图分类号
学科分类号
摘要
Artificial intelligence (AI) technology represented by foundation models has achieved remarkable results, raising the overall level of machine intelligence to an unprecedented height. Foundation models, computing power, networks, and data are gradually becoming important fundamental infrastructure in the field of artificial intelligence. In order to rely on the above infrastructure to provide ubiquitous and secure social-level intelligent services, and make them as ubiquitous as water, electricity, and 5G services, with the almost zero marginal costs, the holistic artificial intelligence (HAI) technology framework is proposed and elaborated. In this framework, intelligence needs can be flexibly expressed through natural language, graphics, images, component arrangement, and other methods. Based foundational big model, HAI understands the user's needs and forms an execution plan which includes the models, capabilities, data, and computing network resources needed to complete the tasks. HAI then deploys models and capabilities to corresponding computing network resources, flexibly schedules and jointly optimizes to meet the requirements of business. The proposed framework utilizes core technologies including big loop AI for artificial intelligence services, atomized AI capabilities, network native AI, and secure and trusty AI services. © 2024 Beijing University of Posts and Telecommunications. All rights reserved.
引用
收藏
页码:1 / 10
页数:9
相关论文
共 50 条
  • [41] Artificial Intelligence and Education
    Florea, Adina Magda
    Radu, Serban
    2019 22ND INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE (CSCS), 2019, : 381 - 382
  • [42] Trustworthiness of Artificial Intelligence
    Jain, Sonali
    Luthra, Manan
    Sharma, Shagun
    Fatima, Mehtab
    2020 6TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION SYSTEMS (ICACCS), 2020, : 907 - 912
  • [43] Trustworthy artificial intelligence
    Thiebes, Scott
    Lins, Sebastian
    Sunyaev, Ali
    ELECTRONIC MARKETS, 2021, 31 (02) : 447 - 464
  • [44] Animation and Artificial Intelligence
    Stark, Luke
    PROCEEDINGS OF THE 2024 ACM CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY, ACM FACCT 2024, 2024, : 1663 - 1671
  • [45] Artificial intelligence in glaucoma
    Nair, Megha
    Tagare, Shivraj
    Venkatesh, Rengaraj
    Odayappan, Annamalai
    INDIAN JOURNAL OF OPHTHALMOLOGY, 2022, 70 (05) : 1868 - 1869
  • [46] ARTIFICIAL SOCIAL INTELLIGENCE
    BAINBRIDGE, WS
    BRENT, EE
    CARLEY, KM
    HEISE, DR
    MACY, MW
    MARKOVSKY, B
    SKVORETZ, J
    ANNUAL REVIEW OF SOCIOLOGY, 1994, 20 : 407 - 436
  • [47] Artificial Intelligence in Teledermatology
    Mulin Xiong
    Jacob Pfau
    Albert T. Young
    Maria L. Wei
    Current Dermatology Reports, 2019, 8 : 85 - 90
  • [48] Artificial intelligence in colonoscopy
    Joseph, Joel
    LePage, Ella Marie
    Cheney, Catherine Phillips
    Pawa, Rishi
    WORLD JOURNAL OF GASTROENTEROLOGY, 2021, 27 (29) : 4802 - 4817
  • [49] Artificial intelligence in glaucoma
    Zheng, Chengjie
    Johnson, Thomas V.
    Garg, Aakriti
    Boland, Michael V.
    CURRENT OPINION IN OPHTHALMOLOGY, 2019, 30 (02) : 97 - 103
  • [50] Artificial Intelligence Ethics
    Massaguer Gomez, German
    TEOREMA, 2022, 41 (01): : 141 - 149