Computational neurobiology meets semiconductor engineering

D. Hammerstrom
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引用次数: 16

Abstract

Many believe that the most important result to come out of the last ten years of neural network research is the significant change in perspective in the neuroscience community towards theory of computational neurobiology and functional neuro-models. Arriving on a fast moving train from the other direction is semiconductor technology, one of the greatest technology success stories of all time transistors are now approaching deep submicron (less than 100 nanometers) in size, and we will soon be building silicon chips with over 1 billion transistors. The marriage of these two technologies is creating what Andy Grove (ex-CEO of Intel) refers to as a strategic inflection point. Although previous attempts at merging these technologies were premature, silicon and computational neurobiology are now merging to create an extremely powerful, and radically new form of computation.
计算神经生物学与半导体工程
许多人认为,过去十年神经网络研究最重要的成果是神经科学界对计算神经生物学理论和功能神经模型的观点发生了重大变化。从另一个方向而来的是半导体技术,这是有史以来最伟大的技术成功故事之一,晶体管的尺寸正在接近深亚微米(小于100纳米),我们很快就会制造出拥有超过10亿个晶体管的硅芯片。这两种技术的结合创造了英特尔(Intel)前首席执行官安迪•格罗夫(Andy Grove)所说的战略拐点。尽管之前试图融合这些技术的尝试还不成熟,但现在硅和计算神经生物学正在融合,创造出一种极其强大的、全新的计算形式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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