一、外刊閱讀：完型填空
AI can pick out specific odours from a combination of smells
An AI can sniff out certain scents, giving us a glimpse of how our nose might work in detecting them.
Thomas Cleland at Cornell University, New York, and Nabil Imam at tech firm Intel created an AI based on the mammalian olfactory bulb (MOB), the area of the brain that is responsible for processing odours (氣味；臭味). The algorithm mimics a part of the MOB that distinguishes between different smells that are usually (41) ______ as a mixture of compounds in the air.
This area of the MOB contains two key types of neuron: mitral cells, which are activated when an odour is present but don’t (42) ______ it, and granule cells that learn to become specialised and pick out chemicals in the smell. The algorithm mimics these (43) ______, says Imam.
Cleland and Imam trained the AI to (44) ______ 10 different odours, including those of ammonia and carbon monoxide. They used data from previous work that recorded the activity of chemical sensors in a wind tunnel (45) ______ these smells.
When fed that data, the AI learns to detect that a smell is present based on the sensors’ responses to the chemicals, and then goes on to identify it on the (46) ______ of the patterns in that data. As it does so, the AI has a spike of activity analogous to the spikes of electrical activity in the human brain, says Imam.
The AI refined its learning over five (47) ______ of exposure, eventually showing activity spikes specific to each odour. The researchers then tested the AI’s ability to sniff out smells among others that it hadn’t been trained to detect. They (48) ______ an odour successfully identified when the AI’s fifth spike pattern matched or was similar to the (49) ______ produced by the sensors.
The AI got it almost 100 per cent correct for eight of the smells and about 90 per cent correct for the (50) _____ two. To test how it might identify odorous contaminants in the environment, the researchers blocked 80 per cent of the smell (51) ______ to mimic more realistic scenarios. In these tests, the AI’s (52) ______ dipped to less than 30 per cent.
“I think the link [to the MOB] is quite strong – this algorithm might be an explanation to how it works in the human nose, to some (53) ______,” says Thomas Nowotny at the University of Sussex, UK. But the AI’s ability to (54) ______ real life problems, such as detecting bombs by picking out hazardous smells (55) ______ them, is still some way off, he says.
41.A. agreeable
B. present
C. sensitive
D. graceful
42.A. identify
B. discipline
C. praise
D. ignore
43.A. steps
B. rules
C. processes
D. preparations
44.A. question
B. refuse
C. experience
D. detect
45.A. in case of
B. in honor of
C. in need of
D. in response to
46.A. level
B. basis
C. extent
D. scale
47.A. labels
B. vehicles
C. cycles
D. devices
48.A. wandered
B. considered
C. trained
D. applied
49.A. support
B. evidence
C. pattern
D. approach
50.A. remaining
B. rewarding
C. relaxing
D. refreshing
51.A. substitute
B. commitment
C. milestone
D. signal
52.A. accuracy
B. objectivity
C. credibility
D. privacy
53.A. attraction
B. abstraction
C. interaction
D. distraction
54.A. answer
B. deal
C. solve
D. reply
55.A.completed with
B. joined by
C. involved in
D. associated with
二、參考答案
BACDD BCBCA DABCD
三、原文銜接
https://www.newscientist.com/article/2237534-ai-can-pick-out-specific-odours-from-a-combination-of-smells/
四、核心詞彙
abstract
abstracted
abstractedly
abstracting
abstraction
abstractions
abstractly
abstractness
abstracts
activate
activated
activates
activating
activation
activator
activators
inactivation
reactivate
reactivated
reactivates
reactivating
reactivation
reactivations
unactivated
compound
compoundable
compounded
compounding
compounds
contaminant
contaminants
detect
det
detectable
detected
detecting
detection
detective
detectives
detector
detectors
detects
undetectable
undetected
distinguish
distinguishable
distinguished
distinguishes
distinguishing
indistinguishable
undistinguished
explain
explained
explainer
explainers
explaining
explains
explanation
explanations
explanatory
unexplained
expose
exposed
exposes
exposing
exposure
exposures
unexposed
glimpse
glimpsed
glimpses
glimpsing
hazard
hazarded
hazarding
hazardous
hazardously
hazards
nonhazardous
sensor
sensors
sniff
sniffed
sniffer
sniffers
sniffing
sniffs
sniffy
五、原文翻譯
AI can pick out specific odours from a combination of smells
人工智能可以從混合氣味中辨別出特定的氣味
An AI can sniff out certain scents, giving us a glimpse of how our nose might work in detecting them.
人工智能可以嗅出特定的氣味，讓我們看到我們的鼻子在探測這些氣味時的工作原理。
Thomas Cleland at Cornell University, New York, and Nabil Imam at tech firm Intel created an AI based on the mammalian olfactory bulb (MOB), the area of the brain that is responsible for processing odours. The algorithm mimics a part of the MOB that distinguishes between different smells that are usually present as a mixture of compounds in the air.
紐約康奈爾大學的托馬斯·克萊蘭和科技公司英特爾的納比爾·伊瑪目基於哺乳動物嗅覺球（MOB）創造了一種人工智能，大腦中負責處理氣味的區域。該算法模擬了MOB的一部分，用來區分空氣中通常以混合物形式存在的不同氣味。
This area of the MOB contains two key types of neuron: mitral cells, which are activated when an odour is present but don’t identify it, and granule cells that learn to become specialised and pick out chemicals in the smell. The algorithm mimics these processes, says Imam.
這個區域包含兩種關鍵類型的神經元：二尖瓣細胞，當氣味存在但無法識別時被激活；顆粒細胞，學習成為專門細胞並從氣味中提取化學物質。伊曼姆說，該算法模擬了這些過程。
Cleland and Imam trained the AI to detect 10 different odours, including those of ammonia and carbon monoxide. They used data from previous work that recorded the activity of chemical sensors in a wind tunnel in response to these smells.
克萊蘭和伊曼姆訓練人工智能檢測10種不同的氣味，包括氨和一氧化碳的氣味。他們使用了先前工作中的數據，記錄了風洞中化學傳感器對這些氣味的反應。
When fed that data, the AI learns to detect that a smell is present based on the sensors’ responses to the chemicals, and then goes on to identify it on the basis of the patterns in that data. As it does so, the AI has a spike of activity analogous to the spikes of electrical activity in the human brain, says Imam.
當輸入這些數據時，人工智能學會根據傳感器對化學物質的反應來檢測氣味的存在，然後根據數據中的模式來識別氣味。當它這樣做時，人工智能有一個類似於人類大腦電活動峰值的活動峰值，伊曼姆說。
The AI refined its learning over five cycles of exposure, eventually showing activity spikes specific to each odour. The researchers then tested the AI’s ability to sniff out smells among others that it hadn’t been trained to detect. They considered an odour successfully identified when the AI’s fifth spike pattern matched or was similar to the pattern produced by the sensors.
人工智能通過五個週期的接觸提煉了它的學習，最終顯示出每種氣味特有的活動峰值。研究人員隨後測試了人工智能的嗅出氣味的能力，其中包括它沒有被訓練來探測的氣味。他們認為，當人工智能的第五個尖峰模式與傳感器產生的模式匹配或相似時，氣味就被成功識別。
The AI got it almost 100 per cent correct for eight of the smells and about 90 per cent correct for the remaining two. To test how it might identify odorous contaminants in the environment, the researchers blocked 80 per cent of the smell signal to mimic more realistic scenarios. In these tests, the AI’s accuracy dipped to less than 30 per cent.
人工智能對其中八種氣味幾乎100%正確，對其餘兩種氣味大約90%正確。為了測試它如何識別環境中的氣味汙染物，研究人員屏蔽了80%的氣味信號，以模擬更真實的情況。在這些測試中，人工智能的準確度下降到30%以下。
“I think the link [to the MOB] is quite strong – this algorithm might be an explanation to how it works in the human nose, to some abstraction,” says Thomas Nowotny at the University of Sussex, UK. But the AI’s ability to solve real life problems, such as detecting bombs by picking out hazardous smells associated with them, is still some way off, he says.
英國蘇塞克斯大學的托馬斯·諾沃特尼說：“我認為（與MOB）的聯繫相當緊密——這種算法可能是對它在人類鼻子中工作原理的一種解釋，也可能是某種抽象的解釋。”但他說，人工智能解決現實生活問題的能力，比如通過挑選與炸彈相關的危險氣味來探測炸彈，還有一段路要走。
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（https://www.newscientist.com/article/2237534-ai-can-pick-out-specific-odours-from-a-combination-of-smells/）
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