中英對照讀新聞》Evolution of circuits for machine learning 機器學習電路的進化
◎劉宜庭
Artificial intelligence （AI） has allowed computers to solve problems that were previously thought to be beyond their capabilities. There is therefore great interest in developing specialized circuits that can complete AI calculations faster and with lower energy consumption than can current devices.
人工智慧（AI）讓電腦能夠解決此前被認為超出計算機能力範圍的問題。人們因此相當關注專門電路的開發，以實現比現有裝置更快速、能源消耗更低的人工智慧計算。
Writing in Nature, Tao Chen et al. demonstrate an unconventional electrical circuit in silicon that can be evolved in situ to carry out basic machine-learning operations.
陳滔（譯音）等人刊登在《自然》的研究，演示一種在矽材料上的非常規電路，它能直接執行基本的機器學習運算。
Previous work by some of the current authors produced isolated charge puddles from a collection of gold nanoparticles that were randomly deposited on a silicon surface, with insulating molecules between them. These puddles are at the heart of Chen and colleagues’ circuit design.
該研究的其中一些作者先前在矽材料的表面隨機堆積奈米黃金顆粒，並用絕緣分子隔開這些電荷坑。金奈米電荷坑是陳博士團隊的電路設計核心。
英倫翻譯社轉自https://features.ltn.com.tw/english/article/paper/1354193
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