IBM创造出世界上首个人工相变神经元

 　　For computer scientists, creation of neuromorphic systems — those inspired by and modeled after the way neurons in the human brain are structured — has been a longstanding goal.

　　对计算机科学家而言，建立仿神经形态体系一直是一个长期目标，该想法源于且模仿人类大脑中神经元的构成方式。
　　Now, in a significant step toward the development of neuromorphic technologies, a group of researchers IBM's research laboratory in Zurich have announced that they have built a working, artificial version of a neuron.
　　如今，作为关于神经形态技术的发展尤的重要一步，位于苏黎世的IBM实验室中，一组研究人员宣布他们已经发明了一个正在运行的人造神经元。
　　The invention, described in a paper published in the journal Nature Nanotechnology, consists of a small square of germanium antimony telluride held between two electrodes. Germanium antimony telluride, a common ingredient in optical disks, is what is known as phase-change material. This means it can change its phase from an amorphous 1 insulator 2 to a crystalline conductor when hit with a strong enough electric pulse — thus acting 3 like both, a resister and capacitor, and mimicking 5, to a certain extent, the behavior of biological neurons' lipid bilayer membrane 6.
　　此项发明在《自然纳米技术》杂志上发表，此发明由两个电极之间一小块锗锑碲构成。锗锑碲是制作光盘的常见材料，也就是所谓的相变材料。这就意味着当遇到足够强大的电子脉冲时，其能够从无定形态绝缘体转变为晶体态导体，因此它的工作原理既像是电阻器又像是电容器，从某种程度上来说，它模仿了生物神经脂质双分子层的特性。
　　IBM创造出世界上首个人工相变神经元
　　"In the published demonstration 7, the team applied 8 a series of electrical pulses to the artificial neurons, which resulted in the progressive crystallization of the phase-change material, ultimately causing the neuron to fire. In neuroscience, this function is known as the integrate-and-fire property of biological neurons," IBM said in a statement released last Wednesday. "This is the foundation for event-based computation and, in principle, is similar to how our brain triggers a response when we touch something hot. "IBM在上周三发表的一份声明中称："在发布的演示中，该团队在人造神经元上施加了一系列电子脉冲，使相变材料不断结晶，最终导致神经元"点火"。在神经科学领域，这一功能被称为生物神经元的集成--点火属性，它是基于事件的计算基础。从原理上说，与人们接触某些热东西后大脑的反应一样。"This is not the only similarity between IBM's neurons and their organic counterparts. The artificial structures also exhibit "stochasticity," or the ability to produce random 9, unpredictable results. Biological neurons are stochastic due to fluctuations 10 within the cell — such as changes in ionic conductance and thermal 11 background — while these artificial neurons are stochastic because the amorphous state of germanium antimony telluride always changes slightly after each reset 12.
　　这不是IBM神经元与其有机变体的唯一相似性。人造结构也表现出了"随机特性"，或者能够产生随机的、不可预测的结果。由于细胞内部的波动，生物神经元是随机的，诸如离子导电的变化、热背底的变化，而人造神经元也表现出了随机特性，因为锗锑碲的无定形态在每次复位后都有轻微的变化。
　　So why is this stochasticity — which makes the output of a system inherently unpredictable — desirable in an artificial neuron? As the researchers explain, stochasticity lets the neurons accomplish tasks that they would not be able to do if their output were perfectly 13 predictable — something that may eventually lead to the creation of efficient "cognitive 14 computers" that mimic 4 the parallel processing architecture of the human brain.
　　那么为什么人造神经元具有随机特性，使得系统输出本身具有不可预测性？正如研究人员所解释的，随机性使得神经元能够完成一些任务，这些任务在输出完全可以预测的情况下是无法完成的，这可能最终会促使高效"认知计算机"的发明，用以模仿与人类大脑平行的处理架构。
　　"Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses 15, could be a key enabler for the creation of a new generation of extremely dense 16 neuromorphic computing 17 systems," co-author Tomas Tuma said in the statement.
　　合著者托马斯·图马在声明中表示："结合诸如人造神经突触等其他纳米计算元素，随机相变神经元群体成为发明新一代高密度神经形态计算体系的重要推动者。"