你仲應唔應該學編程？「人工智能教父」Geoffrey Hinton有答案
隨住人工智能系統日益進步，甚至開始接手寫代碼同埋執行代碼嘅工作，好多人喺科技界都擔心傳統嘅編程技能將會過時。 不過，被譽為「人工智能教父」嘅Geoffrey Hinton就認為呢種睇法太早下定論喇。佢堅持話，計算機科學學位仍然好有價值，因為佢唔單止教你編程，仲提供咗遠超編碼嘅基礎知識。
Geoffrey Hinton指出，即使AI接管部分編程工作，計算機科學學位依然重要。佢話：「計算機科學唔淨係教編程，隨住人工智能發展，了解科技嘅基本原理變得更加重要。」
Hinton反駁咗一啲人認為計算機科學學位會因為AI寫代碼嘅能力而失去價值嘅睇法。佢喺接受Business Insider訪問時講：「好多嘢以為計算機科學學位淨係學編程，但顯然，只靠做一個中等水平嘅程序員將來唔係一份長久嘅職業，因為AI可以做到。」佢強調，計算機科學學位嘅真正價值遠遠超出編碼本身。
Hinton把學編程比喻成文科生學習古語言：「我覺得學編程非常有用，即使最後唔係全部靠AI幫你寫代碼。我覺得學編程有啲似文科生學拉丁文，你永遠唔會用拉丁文溝通，但學呢樣嘢仍然有用。」佢又提到，一啲永遠有價值嘅技能，例如數學、統計學、概率論同線性代數，都係計算機科學嘅重要基礎。
其他AI界領袖亦持相似睇法，認為計算機科學教育嘅價值不會消失。OpenAI主席Bret Taylor喺Lenny嘅Podcast講：「我覺得學計算機科學同學編程係兩回事，但我亦認為學計算機科學非常有價值。因為計算機科學遠超編碼。」微軟CEO Satya Nadella亦強調基礎知識嘅重要性：「對軟件工程師嚟講，掌握軟件嘅基礎依然好重要，有計算思維能力非常關鍵。」
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評論與深入分析
Geoffrey Hinton嘅觀點提醒我哋，喺人工智能迅速進步嘅今天，單純靠學習編程語言可能不足以應對未來職場嘅挑戰。AI嘅崛起確實會令基礎編碼工作自動化，但計算機科學嘅核心——算法、數據結構、數學原理、邏輯思維——依然係驅動科技創新嘅根本。
Hinton將編程學習比喻成學拉丁文，呢個比喻相當貼切。拉丁文雖然唔再係日常語言，但學習拉丁文幫助理解歐洲多種語言嘅結構，提升語言能力同邏輯思維。同樣，編程唔淨係寫代碼，而係理解計算機如何運作，點樣思考問題，呢啲思維方式對所有科技相關工作都大有裨益。
此外，其他AI領袖嘅呼應亦凸顯咗「基礎教育」嘅重要性。唔好因為AI可以代替部分技術工作就放棄學習，反而應該加強對計算機科學理論嘅掌握，因為未來嘅挑戰唔止係寫代碼，而係設計、監督、優化同創新AI系統。
對香港同廣東話用戶嚟講，呢個觀點尤其重要。隨住AI技術普及，唔少傳統IT職位可能消失或轉型，唯有持續提升自己嘅計算思維同基礎知識，先可以喺新經濟環境中保持競爭力。教育機構同職業培訓亦應該重新審視課程設計，唔好淨係教語法，而係強調理論與思維模式嘅培養。
總括而言，Hinton嘅見解為我哋指明咗學習方向：AI會改變技術工作嘅形態，但計算機科學嘅根基永遠唔會過時。未來嘅科技人才，應該係懂得借助AI同時又能掌握背後原理嘅「雙重高手」，先至能真正掌握未來。
以上文章由特價GPT API KEY所翻譯及撰寫。而圖片則由FLUX根據內容自動生成。
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