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  • What is consciousness?

    什麼是意識?

  • Can an artificial machine really think?

    人造機器真的能思考嗎?

  • Does the mind just consist of neurons in the brain, or is there some intangible spark at its core?

    心智只是由腦的神經元所組成,還是有無形的聰明才智在腦的核心嗎?

  • For many, these have been vital considerations for the future of artificial intelligence.

    對多數人而言, 這一直是未來人工智慧的主要考慮因素。

  • But British computer scientist Alan Turing decided to disregard all these questions in favor of a much simpler one: Can a computer talk like a human?

    但英國電腦科學家阿蘭•圖靈決定不理會這諸多問題, 而支持更簡單的一種:電腦能和人一樣交談嗎?

  • This question led to an idea for measuring aritificial intelligence that would famously come to be known as the Turing test.

    這問題後來發展出 一個測量人工智慧的理念, 也就是眾所周知的「圖靈測試」。

  • In the 1950 paper, "Computing Machinery and Intelligence," Turing proposed the following game.

    在 1950 年的一篇論文《電腦機器與智能》, 圖靈提出了以下的測試。

  • A human judge has a text conversation with unseen players and evaluates their responses.

    一位審判員和不被看見的被測試者做文字對話, 並評估他們的回答。

  • To pass the test, a computer must be able to replace one of the players without substantially changing the results.

    要通過測試, 電腦必須能取代被測試者之一, 但不會明顯改變最後結果。

  • In other words, a computer would be considered intelligent if its conversation couldn't be easily distinguished from a human's.

    換言之,此電腦會被認定是有智慧 ── 若其對話不易與人類的區分時。

  • Turing predicted that by the year 2000, machines with 100 megabytes of memory would be able to easily pass his test.

    圖靈預言在 2000 年之前 , 具備 100 MB 記憶體的電腦將能輕易通過圖靈測試,

  • But he may have jumped the gun.

    但他可能言之過早了。

  • Even though today's computers have far more memory than that, few have succeeded,

    即使目前配備更多記憶體的電腦,也很少成功,

  • and those that have done well focused more on finding clever ways to fool judges than using overwhelming computing power.

    而那些通過測試的著重在欺騙審判員的小技巧,而非運用強大的運算能力。

  • Though it was never subjected to a real test, the first program with some claim to success was called ELIZA.

    雖然從未接受真正測試, 第一個程式聲明它已成功的是 ELIZA,

  • With only a fairly short and simple script, it managed to mislead many people by mimicking a psychologist,

    它僅以簡短的程式腳本, 模仿心理學家,成功迷惑許多人,

  • encouraging them to talk more and reflecting their own questions back at them.

    鼓勵他們說得更多些, 同時也反問他們的問題。

  • Another early script PARRY took the opposite approach by imitating a paranoid schizophrenic who kept steering the conversation back to his own preprogrammed obsessions.

    另一個早期程式腳本 PARRY 採取相反的方式, 模仿偏狂型精神分裂症病患,一直把話題轉回它預設的執著事物。

  • Their success in fooling people highlighted one weakness of the test.

    它們成功愚弄人們 突顯出這測驗的弱點,

  • Humans regularly attribute intelligence to a whole range of things that are not actually intelligent.

    人們通常把許多和聰明才智無關的事物視為「智慧」。

  • Nonetheless, annual competitions like the Loebner Prize, have made the test more formal with judges knowing ahead of time that some of their conversation partners are machines.

    儘管如此,年度競賽例如羅布納獎已使測試變得更正式了, 審判員已預先知道其中有些他們的對話者是機器。

  • But while the quality has improved, many chatbot programmers have used similar strategies to ELIZA and PARRY.

    雖然品質已有改善, 但許多聊天機器人的程式員是採用類似 ELIZA 和 PARRY 的方法。

  • 1997's winner Catherine could carry on amazingly focused and intelligent conversation, but mostly if the judge wanted to talk about Bill Clinton.

    1997 年的獲獎者 Catherine 能夠進行驚人地專注且聰明的對話, 但多半只在審判員願意談有關比爾•克林頓的事時。

  • And the more recent winner Eugene Goostman was given the persona of a 13-year-old Ukrainian boy,

    最近的獲獎者尤金•古斯特曼是個偽裝成 13 歲烏克蘭男孩的機器人,

  • so judges interpreted its nonsequiturs and awkward grammar as language and culture barriers.

    審判員將它不合邏輯及蹩脚的文法視為是語言及文化的障礙所致。

  • Meanwhile, other programs like Cleverbot have taken a different approach by statistically analyzing huge databases of real conversations to determine the best responses.

    同時,另一程式,例如 Cleverbot 則採用不同的方法,藉著統計分析大量真正對話的資料庫, 以決定最佳回應。

  • Some also store memories of previous conversations in order to improve over time.

    有些還儲存先前對話的記憶, 以便長期改善。

  • But while Cleverbot's individual responses can sound incredibly human, its lack of a consistent personality and inability to deal with brand new topics are a dead giveaway.

    雖然 Cleverbot 的每次回應聽起來極像人類,但它缺乏前後一致的個性, 而且無法應付嶄新的話題,因而明顯露出馬腳。

  • Who in Turing's day could have predicted that today's computers would be able to pilot spacecraft,

    在圖靈時代的人怎能預料到今日的電腦能駕駛太空船、

  • perform delicate surgeries and solve massive equations, but still struggle with the most basic small talk?

    執行精細手術、能解開龐大的方程式、,卻仍難以處理最基本的小交談呢?

  • Human language turns out to be an amazingly complex phenomenon that can't be captured by even the largest dictionary.

    人類語言原來就是一種驚人複雜的現象, 甚至連最大的字典也無法記錄。

  • Chatbots can be baffled by simple pauses, like "umm..." or questions with no correct answer.

    一個簡單的暫停就能難倒聊天機器人, 例如「嗯……」或沒有正確解答的問題。

  • And a simple conversational sentence, like, "I took the juice out of the fridge and gave it to him, but forgot to check the date,"

    一個簡單的對話句子,例如:「我從冰箱拿出果汁給他,但忘了檢查保存期限。」

  • requires a wealth of underlying knowledge and intuition to parse.

    這需要很多基本理解及直覺語法分析。

  • It turns out that simulating a human conversation takes more than just increasing memory and processing power,

    事實証明模擬人類對話不是只要增加記憶體及數據處理能力而已,

  • and as we get closer to Turing's goal, we may have to deal with all those big questions about consciousness after all.

    當離圖靈的目標越近時,我們終究要去處理所有有關「意識」的大難題。

What is consciousness?

什麼是意識?

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B1 中級 中文 TED-Ed 圖靈 電腦 對話 測試 程式

【TED-Ed】圖靈測試:電腦能取代人類嗎? (【TED-Ed】The Turing test: Can a computer pass for a human? - Alex Gendler)

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    黃于珍 發佈於 2022 年 10 月 22 日
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