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IBM創造出世界上首個人工相變神經元

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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.

對計算機科學家而言,建立仿神經形態體系一直是一個長期目標,該想法源於且模仿人類大腦中神經元的構成方式。

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,作爲關於神經形態技術的發展尤的重要一步,位於蘇黎世的IBM實驗室中,一組研究人員宣佈他們已經發明瞭一個正在運行的人造神經元。

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.

此項發明在《自然納米技術》雜誌上發表,此發明由兩個電極之間一小塊鍺銻碲構成。鍺銻碲是製作光盤的常見材料,也就是所謂的相變材料。這就意味着當遇到足夠強大的電子脈衝時,其能夠從無定形態絕緣體轉變爲晶體態導體,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,它模仿了生物神經脂質雙分子層的特性。

IBM創造出世界上首個人工相變神經元

"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 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在上週三發表的一份聲明中稱:"在發佈的演示中,該團隊在人造神經元上施加了一系列電子脈衝,使相變材料不斷結晶,最終導致神經元"點火"。在神經科學領域,這一功能被稱爲生物神經元的集成--點火屬性,它是基於事件的計算基礎。從原理上說,與人們接觸某些熱東西后大腦的反應一樣。"

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神經元與其有機變體的唯一相似性。人造結構也表現出了"隨機特性",或者能夠產生隨機的、不可預測的結果。由於細胞內部的波動,生物神經元是隨機的,諸如離子導電的變化、熱背底的變化,而人造神經元也表現出了隨機特性,因爲鍺銻碲的無定形態在每次復位後都有輕微的變化。

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.

那麼爲什麼人造神經元具有隨機特性,使得系統輸出本身具有不可預測性?正如研究人員所解釋的,隨機性使得神經元能夠完成一些任務,這些任務在輸出完全可以預測的情況下是無法完成的,這可能最終會促使高效"認知計算機"的發明,用以模仿與人類大腦平行的處理架構。

"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.

合著者托馬斯·圖馬在聲明中表示:"結合諸如人造神經突觸等其他納米計算元素,隨機相變神經元羣體成爲發明新一代高密度神經形態計算體系的重要推動者。"