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AI 也能得諾貝爾「物理學」獎!?電腦靠什麼模仿生物大腦?

PanSci 泛科學 100,276 3 months ago
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還在手動處理繁瑣的文書和數據?點擊連結,讓 AI 幫你省下時間👉 https://www.youtube.com/playlist?list=PLp-hFjVIn_eXvBXBOw0KwbKBmpbFs61xQ // 延伸閱讀 // Claude、ChatGPT 提示詞優化!4 個技巧讓 AI 更懂你的需求! https://pansci.asia/archives/376895 AI 可以幫你聽懂老婆的情緒了?AI 情緒理解原理解密! https://pansci.asia/archives/376881 // 參考資料 // https://www.nobelprize.org/prizes/physics/ J. J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, 1982, Proc Natl Acad Sci U S A. 1982 Apr; 79(8): 2554–2558 D. O. Hebb, The Organization of Behavior, 1949, New York: Wiley & Sons. https://case.ntu.edu.tw/blog/?p=36984 M. W. Macy, B. K. Szymanski, J. A. Hołyst, The Ising model celebrates a century of interdisciplinary contributions G. E. Hinton, T. J. Sejnowski, Learning and Relearning in Boltzmann Machines, 1986, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations (Cambridge: MIT Press). Hinton, Geoffrey E., Terrence J. Sejnowski, and David H. Ackley. Boltzmann machines: Constraint satisfaction networks that learn. Pittsburgh, PA: Carnegie-Mellon University, Department of Computer Science, 1984. Kirkpatrick S, Gelatt CD Jr, Vecchi MP. Optimization by simulated annealing. Science. 1983 May 13;220(4598):671-80. doi: 10.1126/science.220.4598.671. PMID: 17813860. https://lakshya3.medium.com/exploring-the-power-of-boltzmann-machines-from-foundations-to-innovations-in-machine-learning-a43d5ba07010 Ramsauer, H., Schäfl, B., Lehner, J., Seidl, P., Widrich, M., Adler, T., ... & Hochreiter, S. (2020). Hopfield networks is all you need. arXiv preprint arXiv:2008.02217. // 製作團隊 // 主持:泛科知識 #鄭國威知識長 企劃:謝富丞 腳本:柯智煌 剪輯:蘇庭緯 想和我們有更多互動嗎?加入會員 ► https://lihi1.com/BWeoe

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