Artificial Intelligence | 人工智慧

  • 人工智慧是什麼?
    人工智慧(Artificial Intelligence)是電腦科學的一個廣泛分支。人工智慧的目標是創造出具有智慧功能獨立運行的機器,並且擁有像人類一樣的工作能力及反應。為了達成這些目的,機器、軟體及各種應用程序運用了和人類相同的方法去獲取智慧 - 通過保存記憶資訊並隨著時間的演進變得更聰明。

    人工智慧不是一個新概念,這個想法自1950年代起就一直開始備受討論,但由於近代電腦技術的進步 ─ 例如我們現在具備了蒐集大量資訊並儲存的能力,得以獲取足夠的數據量,讓現實中得以實現機器學習的開發,加上硬體處理速度和運算能力的快速提升,這使得處理蒐集的數據用於訓練機器/應用程序並使其“更智慧”的目標成真。

  • 為何需要?
    雖然大部分人會將AI與「自我感知機器人」的形象連結在一起,這種機器人可以像人類一樣移動,行動和思考(就像科幻電影中一樣),但在現實生活中其實你比想像中的更容易接觸到AI,例如YouTube及Netflix依靠AI來產生針對使用者的影片推薦,還可以自動分類內容或審查不適當的資訊;像亞馬遜Alexa或Google翻譯這樣的語音識別或是翻譯平台也導入了AI,更精準的理解真實世界的語言或執行翻譯,透過記憶使用者行為或回饋,應用程序將變得更加聰明。在未來即將成為主流的自動駕駛技術或運送包裹無人機各種領域,人工智慧也是推動其進步的關鍵。

  • 技嘉的特色
    目前在開發人工智慧最廣泛採用的方法之一是機器學習(Machine Learning),其先進的變異深度學習,採用深度神經網絡(DNN - Deep Neural Network)模型 - 複雜的演算法在結構和功能上與人類大腦相似。深度學習不僅需要大量數據(可以使用GIGABYTE的儲存伺服器 / 高密度伺服器進行儲存和計算),還需要大量的平行運算能力來根據數據資料訓練演算法。GIGABYTE的G系列GPU 協同運算伺服器(如G481-S80G291-280)非常適合這項任務。

    GIGABYTE還開發了深度學習訓練系統,這是一個基於G481-HA1伺服器的軟硬體整合方案,用於機器學習環境設置,管理和監控,並包括軟硬體的優化,可減少運算時間並改善DNN學習的準確性。

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