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考研英語閱讀：IBM創(chuàng)造出世界上首個(gè)人造神經(jīng)元
World’s First Artificial Neuron: IBM’s Breakthrough Uses Phase-Change Material
IBM創(chuàng)造出世界上首個(gè)人造神經(jīng)元
導(dǎo)讀:IBM使用隨機(jī)相面材料發(fā)明世界上首個(gè)人造神經(jīng)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. 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.
對(duì)計(jì)算機(jī)科學(xué)家而言，建立神經(jīng)形態(tài)體系一直是一個(gè)長期目標(biāo)，該想法源于且模仿人類大腦中神經(jīng)元的構(gòu)成方式。如今對(duì)于神經(jīng)形態(tài)技術(shù)的發(fā)展尤其重要， 在IBM位于蘇黎世的實(shí)驗(yàn)室中一組研究人員宣布他們已經(jīng)發(fā)明了一個(gè)正在運(yùn)行的人造神經(jīng)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 insulator to a crystalline conductor when hit with a strong enough electric pulse — thus acting like both, a resister and capacitor, and mimicking, to a certain extent, the behavior of biological neurons’ lipid bilayer membrane.
此項(xiàng)發(fā)明在《自然納米技術(shù)》雜志上發(fā)表，此發(fā)明由兩個(gè)電極之間一小塊鍺銻碲構(gòu)成。鍺銻碲是制作光盤的常見材料，也就是所謂的相變材料。這便意味著當(dāng)遇到足夠強(qiáng)大的電子脈沖時(shí)，其能夠從無定形態(tài)絕緣體轉(zhuǎn)變?yōu)榫w態(tài)導(dǎo)體，因此它的工作原理既像是電阻器又像是電容器，從某種程度上來說，它模仿了生物神經(jīng)脂質(zhì)雙分子層的特性。
“In the published demonstration, the team applied 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 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. ”
“在發(fā)布的演示中，該團(tuán)隊(duì)在人造神經(jīng)元上施加了一系列電子脈沖，使相變材料不斷結(jié)晶，最終導(dǎo)致神經(jīng)元“點(diǎn)火”。在神經(jīng)科學(xué)領(lǐng)域，這一功能被稱為生物神經(jīng)元的集成—點(diǎn)火屬性，它是基于事件的計(jì)算基礎(chǔ)。從原理上說，與人們接觸某些熱東西后大腦的反應(yīng)一樣?！盜BM在周三發(fā)表的一份聲明中稱。
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, unpredictable results. Biological neurons are stochastic due to fluctuations within the cell — such as changes in ionic conductance and thermal background — while these artificial neurons are stochastic because the amorphous state of germanium antimony telluride always changes slightly after each reset.
這不是IBM神經(jīng)元與其有機(jī)變體的唯一相似性。人造結(jié)構(gòu)也表現(xiàn)出了“隨機(jī)特性”，或者能夠產(chǎn)生隨機(jī)的、不可預(yù)測的結(jié)果。由于細(xì)胞內(nèi)部的波動(dòng)，生物神經(jīng)元是隨機(jī)的，諸如離子導(dǎo)電的變化、熱背底的變化，而人造神經(jīng)元也表現(xiàn)出了隨機(jī)特性，因?yàn)殒N銻碲的無定形態(tài)在每次復(fù)位后都有輕微的變化。
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 predictable — something that may eventually lead to the creation of efficient "cognitive computers" that mimic the parallel processing architecture of the human brain.
那么為什么人造神經(jīng)元具有隨機(jī)特性，使得系統(tǒng)輸出本身具有不可預(yù)測性?正如研究人員所解釋的隨機(jī)性使得神經(jīng)元能夠完成一些任務(wù)，這些任務(wù)在輸出完全可以預(yù)測的情況下是無法完成的，這可能最終會(huì)促使高效“認(rèn)知計(jì)算機(jī)”的發(fā)明，用以模仿與人類大腦平行的處理架構(gòu)。
“Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses, could be a key enabler for the creation of a new generation of extremely dense neuromorphic computing systems,” co-author Tomas Tuma said in the statement.
“結(jié)合諸如人造神經(jīng)突觸等其他納米計(jì)算元素，隨機(jī)相變神經(jīng)元群體成為發(fā)明新一代高密度神經(jīng)形態(tài)計(jì)算體系的重要推動(dòng)者，”合著者托馬斯·圖馬在聲明中如是說。
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