The hardware is the software

被引:1
作者
Laydevant, Jeremie [1 ,2 ]
Wright, Logan G. [1 ,3 ,4 ]
Wang, Tianyu [1 ,6 ]
Mcmahon, Peter L. [1 ,5 ]
机构
[1] Cornell Univ, Sch Appl & Engn Phys, Ithaca, NY 14853 USA
[2] USRA Res Inst Adv Comp Sci, Mountain View, CA 94035 USA
[3] NTT Res Inc, NTT Phys & Informat Labs, Sunnyvale, CA 94085 USA
[4] Yale Univ, Dept Appl Phys, New Haven, CT 06511 USA
[5] Cornell Univ, Kavli Inst Cornell Nanoscale Sci, Ithaca, NY 14853 USA
[6] Boston Univ, Dept Elect & Comp Engn, Boston, MA 02215 USA
基金
美国国家科学基金会;
关键词
D O I
10.1016/j.neuron.2023.11.004
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Human brains and bodies are not hardware running software: the hardware is the software. We reason that because the physics of artificial intelligence hardware and of human biological "hardware"is distinct, neuromorphic engineers need to be selective in the inspiration we take from neuroscience.
引用
收藏
页码:180 / 183
页数:4
相关论文
共 10 条
  • [1] [Anonymous], 1999, Cambrian Intelligence: The Early History of the New AI
  • [2] Brown TB, 2020, ADV NEUR IN, V33
  • [3] Hooker S, 2021, COMMUN ACM, V64, P58, DOI 10.1145/3467017
  • [4] NEURONS WITH GRADED RESPONSE HAVE COLLECTIVE COMPUTATIONAL PROPERTIES LIKE THOSE OF 2-STATE NEURONS
    HOPFIELD, JJ
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1984, 81 (10): : 3088 - 3092
  • [5] Deep learning
    LeCun, Yann
    Bengio, Yoshua
    Hinton, Geoffrey
    [J]. NATURE, 2015, 521 (7553) : 436 - 444
  • [6] Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number
    Levy, William B.
    Calvert, Victoria G.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2021, 118 (18)
  • [7] Physics for neuromorphic computing
    Markovic, Danijela
    Mizrahi, Alice
    Querlioz, Damien
    Grollier, Julie
    [J]. NATURE REVIEWS PHYSICS, 2020, 2 (09) : 499 - 510
  • [8] How we created neuromorphic engineering
    Mead, Carver
    [J]. NATURE ELECTRONICS, 2020, 3 (07) : 434 - 435
  • [10] Sutton R, 2019, The Bitter Lesson