薩提亞：首先，非常感謝 Harry，很高興受邀作為演講嘉賓參加 CVPR。我們正在經歷一個前所未有的時期，能有這樣的機會和大家相聚在一起，探討計算機視覺等技術領域的重大突破、以及科技創新能為世界帶來的積極貢獻，讓我感到特別興奮，很高興能與大家共聚一堂！Harry 要我談談我的個人經歷，我在印度海得拉巴長大，在那裡度過了很多年，那時的我從未想到會有此時此景。20世紀70年代中期的海得拉巴和今天完全不同，那時有兩樣來自美國的東西，最終改變了我的一生。第一是美國的技術，個人電腦，我很幸運在那個時候接觸到了電腦，從此有了自己的夢想，第二是美國的移民政策，讓我有機會來到美國求學。之前我從未去過孟買西部，結果卻來到了美國的威斯康星，這在當時是個不可思議的選擇。但由此開啟的機遇，無論是上學還是進入微軟工作，最終成就了我的人生和我今天的樣子。因此，我對過去所經歷的一切始終心懷感激。今天我非常確信，機遇能帶來巨大的影響，它讓我這樣一個印度孩子活出了不一樣的人生。我認為這是一種殊榮，我們應該思考，對於我們這些有此殊榮的人來說，我們在創造技術和技術平臺的過程中，該如何推動它普遍造福於每一個人。這樣的想法，是推動我前進的根本動力。這也是微軟使命 “予力全球每一人、每一組織，成就不凡”的根基。它鞭策我每天努力工作，激勵我們全力以赴地做出最好的成果。
沈向洋：非常好，感謝薩提亞。你的故事非常鼓舞人心。CVPR 是計算機視覺的盛會，現在讓我們直奔主題。微軟從很早以前便投身於計算機視覺領域，就在幾天前我的好朋友、CVPR 2020 大會的主席 Gerard Medioni 教授還提醒我說，微軟研究院支援 CVPR 大會已經有差不多30年了。你能否與我們分享一下，微軟為何如此熱衷於計算機視覺？你在計算機視覺領域最關注的焦點有哪些？
薩提亞：當然可以。Harry，你本人就是微軟這個歷程的關鍵推動者。從21世紀初開始，我們在計算機視覺領域就開始了包括骨架追蹤、人體感知等基礎性的研究。在2010年，我們將這些技術轉化成了第一個商業產品，Kinect，我認為這是一個突破性的產品，而且它也的確成為了當年最暢銷的消費產品。在此基礎上，微軟劍橋研究院做出了能夠完全重構 3D 環境的 Kinect Fusion，隨後又有了 HoloDesk。我始終記得第一次看到演示的場景，它讓人與 3D 環境完全融為一體，讓你可以在桌面上擺弄一個 3D 物體。2015年，我們完成了產品化的 HoloLens，2019年，又推出了第二代的 HoloLens，HoloLens 2，它提供了兩倍的視野、兩倍的舒適度，並且還帶來了很多精彩應用。
除此之外，讓我感到特別興奮的，還是看到計算機視覺技術在雲和邊緣裝置上的創新應用。我們在2016年，在物體識別領域達到了接近人類的水平。2018年釋出的 Azure Kinect 提供了板載邊緣計算的能力，從此我們把 Azure 認知服務帶到了 Azure Kinect 上。有了這些完善的工具鏈，我們就可以圍繞計算機視覺，做出更有創意的研究和應用。事實上，已經有很多 ISV 和第三方開發者將 Azure Kinect 應用到從生產製造到醫療衛生的不同場景。在美國的醫院裡，每年平均會發生大約100萬起跌倒事故。一家名為 Ocuvera 的 ISV 開發出了影片監控解決方案，利用 Azure Kinect 來分析病人的動作特徵，當無人照料的患者試圖起身離開床的時候，系統就會向護士和護工發出警告，從而提前避免跌倒事故的發生，其準確率已經達到了96%。
位於俄亥俄州的美國全國兒童醫院，在使用 Kinect 對嬰兒行為不協調的情況進行早期篩查，發現腦癱等疾病的徵兆。他們使用計算機視覺模型搭建了原型，來判斷嬰兒動作的健康程度，讓護理人員能夠儘早採取干預治療手段。對於此類疾病，儘早治療極其重要。醫療裝置公司 Evolve 用 Kinect 來改善中風後遺症患者物理康復治療的效率，他們的方案將傳統的身體訓練與互動遊戲相結合，並且針對每一位患者的個人情況進行了定製。
當我們在 CVPR 大會上討論計算機視覺的未來時，有三個突破方向讓我尤其感興趣，我希望能推動它們的發展，給現實世界帶來積極的影響。第一個方向，我稱之為“4D理解（4D Understanding）”，之前我也和 Harry 聊過，可以把它發展成“現實即服務（Reality-as-a-Service）”。比如說，在醫院或者工廠車間這樣特別關注安全和質量的地方，如果我們想要利用實時的計算機視覺技術，對人、地、物這些要素進行推理以確保安全，這將是一個非常了不起的突破。我們已經在一些案例中看到了實際部署的情況，請讓我用一段影片，來動態展示一下效果。
薩提亞：在遠端協作無處不在的今天，另一個讓我感興趣的領域，是“背景替換（Background Matting）”。即使人在家中坐，我們也可以把你搬到舞臺上去。事實上，在最近舉辦的微軟 Build 開發者大會上，我們就把演講者在家中的影像拍攝下來，天衣無縫地投射到一個虛擬舞臺上，完全不需要使用綠幕。我想這也是計算機視覺的一項突破，下面的影片，將展示我們和華盛頓大學合作的成果。
薩提亞：第三個突破，是我們在將近一年前所展示的”全息瞬移（Holoportation）”。這段影片演示了我們的同事 Julia White 在臺上用英語演講，而她的全息影像同時在講日語，這其中綜合運用了神經網路文字到語音 TTS（Text-to-Speech）、全息計算等技術。像這樣自由地超越時間、空間和語言的侷限，在我看來是一項了不起的突破，我希望這樣的技術能夠得到加速發展。
“復刻版”Julia 的表情神態和語音語調與“本尊”如出一轍，更讓人震撼的是，她居然用流利的日語做起了演講（要知道，Julia 本人並不會日語）
沈向洋：非常精彩，薩提亞，這也喚起了我最寶貴的回憶。我想起了很多年前，我們在微軟剛剛成立計算機視覺研究小組時的情景，我們有 Rick Szeliski、Matthew Turk 還有很多了不起的人物。你也提到微軟研究院在全球有很多分院，比如英國的劍橋研究院、中國的亞洲研究院，還有印度研究院等等。很多來自微軟研究院的視覺技術，已經成功地融入到了微軟的產品中。最讓我興奮的，就像你所說的，是科學研究和產品之間的密切聯絡和轉化，比如你說的 Kinect、HoloLens 還有很多專案，像是 Julia White 的這個全息瞬移的影片。我想計算機視覺的發展前景，一定是不可限量的。
薩提亞：絕對如此。
沈向洋：接下來，讓我們從計算機視覺轉到人工智慧，AI。微軟投身人工智慧研究也有很長時間了，特別是在比爾·蓋茨先生1991年建立微軟研究院之後。我還記得微軟研究院最初成立的三個研究小組就是自然語言處理、語音和視覺，這些都是 AI 的基礎。最近，你也在反覆強調，雲端計算和人工智慧將是微軟未來成長的關鍵。上個月在 Build 大會上宣佈的 AI 超級計算機也非常激動人心。那麼，微軟對於人工智慧接下來的發展的看法是什麼？
薩提亞：確實像你說的，微軟研究院最初的三個研究小組就是語音、視覺和語言。到了2020年，我們仍然在關注這三個領域，但有了更大的雄心壯志，也取得了更大的成功，我對此充滿了期待。
在我看來，過去幾年中最值得關注的一個事情，是大規模計算，能夠計算更多引數的模型將帶來更令人驚奇的結果，特別是在語言方面。你知道，從迴圈神經網路（RNN）到 Transformer 模型,最後得到的結果都是巨大無比的。當你還在微軟領導科研團隊時，我們釋出了帶有170億個引數的“圖靈模型”。現在，我們又和 Open AI 合作，把這個數字提高到了1700億，這是非常激動人心的進步。而我們還更進一步，特別為此打造了超級計算機。在處理這種級別的超大模型時，我們要面對種種挑戰，甚至需要克服“摩爾定律”的侷限，因此我們必須要重新發明整個系統，讓超大規模機器學習成為可能。很高興我們最終在 Azure 上建成了 AI 超級計算機，我們和 Open AI 正在上面訓練這些模型。同時我們正在把這些模型平臺化，讓其他人也可以在這些模型的基礎上，進行一些微調，來滿足他們自己的使用需求。讓我更加興奮的是，我們還可以舉一反三，將這些從文字、語音、影像中學習到的 AI 訓練的方法推而廣之，來對知識形成更好的表達。因此，我想，在接下來的幾年中，我們將看到來自系統層、建模技巧、訓練技巧，當然還有應用層面的更多突破。比如說在醫療保健領域，如果我們希望能在精準給藥方面有所進步，則需要在臨床報告、醫療影像等方面的創新，並且把這些創新匯聚起來推動真正的突破。
沈向洋：的確非常值得期待。關於你提到的170億個引數的圖靈模型，還有1750億個引數的 GPT-3 大規模模型，我還想補充幾句。我們知道，在微軟內部，很多研究小組不但在利用 Azure 訓練自己的模型，甚至實現了小樣本學習、單樣本學習，乃至零樣本學習。這其中蘊藏的機遇真的是非常驚人。薩提亞，今天我們的主題演講是透過虛擬的方式線上進行的，因為我們正在經歷一個特殊時期。既然計算機視覺、人工智慧有這麼多令人興奮的前景，我想請你分享你對於 AI 視覺技術最真實的想法：現在我們該如何利用這些技術幫助大家，過好自己的生活、做好自己的工作——不僅是在當前面對疫情的時候，更重要的，還是在疫情過後的世界裡。能否和我們分享一些案例，告訴我們微軟在做什麼，微軟在如何幫助人們，特別是幫助那些在一線工作的人。
薩提亞：的確如此，Harry，我想這場疫情將人們對數字技術的迫切需求推到了前臺，我們在思考技術該如何在全社會的規模上，幫助人們去應對、恢復、以及重構今後工作和生活的方式。我想，這三個階段其實是同時進行的，而包括計算機視覺在內的數字技術，將在其中發揮重要作用。事實上，我們剛才看到的那段影片，展現了工廠車間裡的遠端感知、遠端監控，以“現實即服務”的方式來確保安全，用數字孿生來保障安全執行，這對於製造業來說，都是非常重要的趨勢。我們在製造業看到的另一個應用，是對生產線進行及時、快速的調整，比如說迅速轉產製造呼吸機。在這個過程中需要專家的遠端指導，來幫助工人重組生產線，HoloLens 結合 Dynamics 的 Remote Guides 應用，在這個過程中發揮了重要的作用。這是在製造業上。
在醫療衛生領域，在英國的醫院裡，我們看到了 HoloLens 和 Microsoft Teams 結合的應用。醫生在照料受新冠病毒感染的患者時，不但穿著全套個人防護裝備，還佩戴著 HoloLens。HoloLens 能夠拍攝到醫生看到的視野，並將其透過 Microsoft Teams 傳送出來，讓隔離區外的其他醫生也能看到患者，並遠端給出治療建議。安全和協作以一種全新的方式，在抗擊疫情的第一線發揮著作用。在醫護教學方面，凱斯西儲大學醫學院讓學生在家使用 HoloLens 遠端參與解剖課的教學，確保能夠以逼真的體驗繼續教學課程。這是很了不起的突破。
總之，我認為無論是在製造業、醫療領域，還是教育方面，我們將看到一大批突破層出不窮地湧現出來，而計算機視覺，無疑將是這個“遠端無處不在”的世界的關鍵技術。
沈向洋：確實如此。我覺得你說的非常好。現在，數字化轉型正以某種方式加速推進。我想疫情迫使我們必須要想得更長遠些。我還想問問你，對於未來的工作方式，以及疫情過後的世界有什麼想法。你認為人們將越來越多地依靠遠端技術工作嗎？我記得你之前也說過，從今以後人們用完全虛擬的方式做一切事情是不可思議的？而現在有些公司已經宣佈將長期堅持遠端工作。
薩提亞：我覺得從核心層面來看，我們總是希望企業內部的每一項功能都可以實現遠端化。遠端銷售、遠端運營、遠端支援，真正大規模的遠端工作。我覺得這一點是毋庸置疑的。這將是企業維持業務連續性和彈性的基礎。我想接下來我們要學習的，是如何幫助不同行業中，不同功能部門的不同的角色，更好地提高遠端工作的效率。我相信，在某些行業中的某些角色是完全適合遠端工作的。事實上，在微軟，在疫情爆發之前，我們有很多職位就已經是100%遠端工作的，而且他們的工作都很高效。當然，也有某些職位需要人們有時候聚在一起相互協作。
我想說的是，我認為我們不是要用一種教條取代另一種教條，對我們來說，更重要的是透過實踐發現，我們在遠端工作中收穫的好處有哪些，並且要有目的地對其加以利用和放大。這樣，當我們走出疫情的影響時，我們就可以更好地發揮這種靈活性來幫助他人，不僅是用來工作，更是為人們謀福利和滿足人們的需要。比如說，現在我們在西雅圖地區的很多員工都在家工作，但我們發現，有些人希望在疫情結束後回到公司上班，因為他們希望有專門的工作場所和更好的網路連線——因為一些結構上的問題，即使是在西雅圖這樣的大城市，Wi-Fi 和寬頻也會存在侷限性。所以，我希望我們能夠理性地認識到世界不同地方的人們所面對的現實各不相同，要找到實現靈活性的最佳方式，重新認識遠端工作的優勢，並且真正為更多人提供助力。
沈向洋：很高興聽到你的想法，薩提亞。我的感悟是，無論我們面對怎樣的挑戰，比如當前的疫情，我們總能透過創新找到出路。儘管需要付出巨大的努力，但我們終將走出困境。薩提亞，讓我們回到微軟公司的話題上來。過去六年多，你做了大量的工作領導微軟實現了成功的轉型。你在社群建設上尤其投入了大量的精力，並且做出了很多大膽的嘗試，比如收購面向商業人才的 LinkedIn 和麵向開發者的 GitHub。事實上，CVPR 是一個匯聚了計算機視覺研究者和從業者的大社群，這兩年，每年 CVPR 大會的參與者已經達到了接近1萬人的規模。我們中的很多人都想從你和你的經歷中得到一些建議和啟示，來促進整個社群的成長。你認為，我們這個計算機視覺社群，應該如何相互幫助、共同工作、共同成長，並更好地貢獻社會呢？
薩提亞：當然，Harry。我們說予力全球每一人、每一組織，成就不凡，其中的關鍵就是利用數字技術，幫助人們以及人們所建立的機構和社群共同創造、共同繁榮。這是微軟使命的中心思想，也是微軟商業模式的核心所在。只有我們所服務的整個世界變得更好，我們才能變得更好。無論是幫助小企業更具生產力，幫助覆蓋全球的大型國際公司更具競爭力，還是幫助公共服務部門提高效率，幫助教育、醫療得到發展，幫助大型社群共同繁榮。對我們來說，這是核心所在。你剛才提到的那些收購，包括開發者社群 GitHub、面向商業人才的 LinkedIn，還有 Minecraft 等遊戲玩家社群，我們很榮幸能夠服務這些社群，同時這些社群也讓我們的根基更為紮實。
在計算機視覺領域也是同樣的道理。計算機視覺研究者相互團結，創造科技突破的傳統由來已久，微軟研究院與學術界合作，共同推進產品創新的先例也是不勝列舉。來自蘇黎世聯邦理工學院（ETH）的 Marc Pollefeys 就是最好的例證。他和微軟合作，推動了很多產品的創新，但同時他也在 ETH 創辦了世界級的研究中心。這樣的跨界合作正是社群建設的核心。這不僅限於計算機視覺，也適用於人工智慧的更廣大領域，並延伸到整個數字技術的範疇之中。在微軟，我們希望能夠促進生態系統平臺的思考，幫助社群團結在一起，更重要的，是促進不同社群之間的相互合作，透過合作放大社群的力量。
沈向洋：說得好，薩提亞，你帶給我們很多啟示。社群的一個重要屬性就是國際化。就像 GitHub 是國際化的，LinkedIn 是國際化的，遊戲社群是國際化的，計算機視覺的 CVPR 社群也不例外。那麼，作為一家跨國公司的領導者，面對很多你熟悉的學科社群，你覺得他們該如何更好地推進國際合作呢？
薩提亞：好的，Harry，接下來我們來聊一聊國際合作。無論是 CVPR 這樣的科研社群，還是微軟這樣的跨國公司，我想我們必須要理智思考的一件事是我們的工作，無論是相互合作還是獨自完成，如何才能真正幫到每一個國家的每一個社群。所謂全球化，如果不能讓當地從中獲益，就無從談起。事實上，從上一輪的全球化來看，我們看到它讓很多人受益，但也有很多人被撇在了後面。因此我現在想說，微軟應該在某種程度上有所作為，這就是為什麼我無論去到世界任何地方，都會注意觀察，並且表達微軟希望積極參與和幫助地區和國家發展的願望。我希望我們的星星之火，可以為促進小企業、大企業、公共服務部門、醫療、教育的發展，幫助改善當地資源供給、就業情況，提高技術水平，做出些許貢獻。作為一個全球社群，無論是科研社群還是跨國公司，我們必須在推動全球合作的同時，積極參與和對本地發展作出貢獻。如果我們能在這方面有更多的想法，在這個方向上貢獻出更大的力量，我們就越能保持發展的活力。
沈向洋：非常好的觀點，薩提亞。事實上，在 CVPR 社群以及其他的大規模計算社群，比如 ICCV，我們的想法也都是這樣。這也是為什麼 CVPR 大會幾乎在每一座擁有大學或者研究院的美國城鎮都舉辦過。ICCV 大會是在不同的大洲輪流舉辦，就像你說的，只有當地社群都得到繁榮發展，才能真正成為一個全球性的組織。非常好。那麼，薩提亞，我們現在還有一點時間，我這裡有幾個提前從觀眾那裡收到的問題。第一個問題是個很適時的問題，我知道你也在這上面思考了很多。關於人工智慧，關於有道德地運用人工智慧，關於負責任的人工智慧，我們意識到你和微軟花了大量精力來闡述這個問題，還在這方面做了很多艱難的決定。你能否分享一些在這方面心得和教訓？
薩提亞：當然了，Harry。我們一直在理智地思考，如何制定一套設計規則，確保在創造 AI 時，能夠將核心的道德思考烙印到工程開發的流程中去。在我們看來，確定 AI 安全和有道德地使用 AI 的設計原則，就像在程式設計時確定執行環境一樣重要。在這個設計原則中，我們首先建立了一套具體的工程學原則，從公平、可靠，到安全、隱私等。這樣，我們保證符合道德成為設計流程的一部分，我們將其作為首要的設計要求而不是一個抽象的概念。
在計算機視覺領域，我們一直在實踐這樣的要求。比如基於我們的 Face API 的面部識別。首當其衝的挑戰就是我們該如何確保消除偏見。感謝 NIST 推出了可靠的評分標準，現在可以對不同種族人群的面部識別效果進行比較，從而確保我們的模型中不存在偏見，由此創造出的透明度標準也很有幫助。很快，我們將為客戶提供幫助指南，告訴他們該如何根據自己的資料，去度量 Face API 的效能表現、設定正確的閾值，並對錯誤匹配進行平衡。這是一個例子。
在另一邊，是對執行環境和有道德地使用 AI 的思考。我們必須意識到，有時候，即使在設計過程中完全心懷善意，如果沒有在執行環境中植入能夠保護隱私和民主自由的措施，最終也可能在無意間得到壞的結果。過去兩年，我們一直專注於開發和執行嚴格的原則來管理我們的面部識別技術，自2018年以後，我們也在呼籲政府制定相應的嚴格保護法規。我們公開了我們在相關專案中採用的定義原則。我們還拒絕了很多不符合原則的專案。我們沒有把面部識別技術賣給美國警區域性門；我們也承諾，在美國出臺符合人權的嚴格的全國性法律之前，不會將這項技術賣給美國警區域性門。我們在積極呼籲制定嚴格的全國性法律，否則，我們將看到負責任的企業離開這個市場，讓另一些人乘虛而入。
面向未來，如微軟這樣的公司需要在打造負責任的人工智慧的實踐中做出最好的努力，以將其烙印到工程流程中，同時在技術被使用時確保它既符合我們堅持的原則，也滿足全球各地法律法規的相關要求。
沈向洋：這的確是規範 AI 的有效途徑。從設計原則和執行環境兩方面，讓人們必須認真思考 AI 設計的重要道德問題和責任。毫無疑問，計算機視覺也是其中一個重要的部分。那麼，薩提亞，最後一個問題是，作為全球第一號公司的 CEO，你每天都在思考重大的機遇，以及如何幫助更多的人們。那麼，能否告訴我們，你覺得今天最適合應用雲端計算、人工智慧，以及計算機視覺的行業有哪些？
薩提亞：非常好的問題，Harry，因為從某種意義上看，這是我和微軟的同事們思考最多的問題——下一步，我們怎樣才能讓數字技術產生更加深遠的影響呢？想想看，過去10到15年的發展很顯眼，但我想說有些應用場景其實要窄得多。消費級網際網路方面的突破有很多，但如果你去看生產力以及生產力推動經濟增長的曲線，觀察它對小企業、大企業，對經濟中的不同方面，對世界的不同地區帶來的影響，就會發現，我們的增長率甚至還不如20世紀90年代到21世紀初由 PC 興起帶來的增長。如果你去看 Robert Gordon 對美國生產力的評價，就會看到，他明確指出在1870到1940年代之間有著驚人的進步。他還指出資訊科技特別是個人電腦，帶來了20世紀90年代到21世紀初的生產力增長。但從那之後，我們就沒有實現生產力的明顯增長。原因何在？其中可能有統計學和計量方法上的偏差。但我想說的是，我希望在下一個階段，在人工智慧、雲端計算，以及計算機視覺這樣的技術的助力之下，我們能看到更多行業的普遍增長。
我對此滿懷期待。比如說醫療健康領域。美國 GDP 的19%來自醫療健康領域。那麼，我們是不是有可能在精準給藥方面獲得突破呢？我們可以利用臨床資料、分子影像，在如何治療病人以及管理診療方面真正取得突破。在這個一切皆可遠端的世界裡，自主性——無論是從內而外的還是自外向內的，例如我們在“現實即服務”的影片中看到的就是從內而外的經濟形態，人在運動，物也在運動，有人在觀察，並幫助確保這些人和物安全地執行，或者這些物體自動化地在現實世界裡執行。能在現實世界中自主運動的物體將徹底改變交通運輸，還有很多場合下的執行安全。零售業、商業，都將因此發生顯著的改變。現在大家都在說線下、線上的全渠道，事實上新冠疫情的影響推動了諸如無接觸購物、線上下單到店自取等解決方案的快速發展。我想這將是零售業的一個重大分水嶺。而能確保食物安全的精準農業，也將是另一個大的領域。
還有一個讓我興奮的領域，與計算機視覺尤其相關，那就是無障礙設計。全球有10億人因為身體不便無法參與到社會經濟中來。如今我們所掌握的技術，像是機器閱讀理解，可以幫助閱讀障礙的人們讀書；像微軟開發的Seeing AI這樣的工具，藉助最新的計算機視覺突破，為視覺障礙人士講述這個世界的模樣；還有 EyeGaze 專案，能夠透過追蹤漸凍症（ALS）患者目光的運動，幫助他們打字並與他人溝通。我由衷希望，我們在人工智慧領域能夠取得真正的突破，帶來更新、更強大的無障礙技術，幫助世界各地的這十幾億人，參與到社會活動和經濟生活中來。
所以，這些都是讓我興奮的領域。
沈向洋：的確都是非常非常令人期待的領域。在我聽來，你的核心思想還是聚焦於生產力，服務於全球每個地方、每個人的生產力。
薩提亞：是的，沒錯。
沈向洋：薩提亞，我的最後一個問題，我要替在場的觀眾提問：微軟是否會聘用更多計算機視覺方向的人才？
薩提亞：我們永遠都想要更多計算機視覺的人才，而且我們真心希望能夠與今天匯聚在這裡的計算機視覺社群進行合作。再次感謝你，Harry，為我提供了這個機會。這是一個非常重要的社群，儘管面對重重阻力，但我很高興看到大家仍然能匯聚一堂共同探討技術的進步。有一點你說的很對，最重要的不僅僅是我們的技術和技術突破本身，這次大會之所以能夠鼓舞大家，其關鍵在於，這項技術將如何引領經濟以更加包容、平等的方式發展，並真正幫助地球上的每一個人更好地實現他們的夢想。我想這才是我們每個人內心深處的聲音，真高興今天能有這個機會和大家一起暢所欲言。
沈向洋：非常感謝，薩提亞，非常精彩的演講。感謝你抽出時間參加大會，也感謝線上收看的各位觀眾，相信我們的計算機視覺將迎來美好的未來。謝謝大家！
以下為薩提亞·納德拉與沈向洋爐邊對談的完整英文實錄：
Harry: Good morning everyone. Welcome to CVPR 2020, and welcome to Seattle. Really appreciated everyone log on from everywhere around the world. My name is Harry Shum, I'm your host for the first keynote at CVPR. Thank you for joining the fireside chat with Satya Nadella, CEO of Microsoft Corporation. Hi, Satya, we are very honored to have you joining at the CVPR 2020. I have known you for almost 20 years and had the privilege to work for you over many years. but for our audience, first of all can you please share with us your journey from growing up in India, just studying computer science in the US, to joining Microsoft in 1992 and ultimately becoming the CEO of Microsoft.
Satya: First of all, Harry thank you so much, it's such a pleasure to join you and be a speaker at CVPR and I know we're living through unprecedented times on many dimensions, and so for this group to come together and talk about sort of the breakthroughs of computer vision and technology, and also the positive impact that technology can have in the world is really great, and it's an honor for me to join you all. To your point Harry, I mean, I grew up in the city of Hyderabad in India for most of my life and never did I think that I would be here. You know, as I was growing up in at that time in the mid 70’s, Hyderabad was a very different place than it is even today. But I must say I've been shaped by I think 2 very uniquely American things, American technology, the PC, even reaching me where I was growing up even letting me dream the dream so to speak, and then later on the American immigration policy that let me come here go to school. I had never been to western Bombay and then I showed up in Wisconsin, that was quite a shock to the system, but that said the opportunities that were given to me whether it's in school or at, you know, at Microsoft, really shaped a lot of obviously my life and who I am today and I'm very very thankful for all of it. And now I'm very grounded given that opportunity in the platform is what's the impact? As for a kid growing up in India to be able to live the life I've lived. I also know that that's a privilege and the question is for those of us who have that privilege what are we doing, in terms of creating technology and technology platforms in particular so that it can truly democratize access, so that's what I think fundamentally motivates me, it's what grounds even Microsoft's mission in which you well know about empowering every person and every organization on the planet to achieve more, is what excites me to come to work each day and make sure that we are doing our very best work.
Harry: That’s great. Thank you, Satya. Certainly, your story is very inspiring to many of us, including many computer vision researchers. So since we had the CVPR so let's get straight into computer vision. Microsoft has a long history in the computer vision space. In fact it just a few days ago you know my good friends, chairman of CVPR 2020, professor Gerard Medioni reminded me that Microsoft Research (MSR) has been the supporter of CVPR for almost 30 years. So can you share with us why Microsoft is so excited about computer vision, you know, what you are particularly excited about the computer vision now.
Satya: Absolutely. I mean, Harry you obviously were very much part of the Microsoft journey here all through even, starting with the early 2000’s where there was basic research on computer vision with skeleton tracking, you know, human sensing and that obviously got translated into the very first product into 2010, Kinect, which I think was a breakthrough product at and in fact it is the best-selling consumer product of the year, and then, you know, that led to I think our Cambridge team doing some amazing work around Kinect Fusion to be able to do full 3D reconstruction. Then the HoloDesk. I'll always remember the first time I saw that demo where you could do a full synthesis of a 3D environment, put a 3D object on it in this case on a desk, that you know open our eyes to what ultimately became HoloLens product in 2015. Of course now you know in 2019 we now even have the next generation HoloLens with HoloLens 2 with twice the field of view, twice the comfort, with amazing breakthrough applications. In parallel one of the other exciting things was to see how will now innovating on computer vision with the cloud in the edge. And so whether it's object recognition parity that we achieved in 2016 or the release of Azure Kinect with its onboard edge computing capability in 2018, now it creates between the cognitive services in Azure and Azure Kinect, you really have I think a fantastic tool chain to do very innovative computer vision research as well as applications. In fact, we've seen many ISVs and 3rd party developers apply the power of Azure connect to scenarios across industries including healthcare. Consider that roughly one million falls occur in the US hospitals each year. Ocuvera is an ISV that built a video-based monitoring solution that uses Azure Kinect to analyze the patients movement patterns and senses when they're trying to get out of bed unassisted. It alerts the nurse and caregivers before a fall occurs with 96% accuracy. Researchers at Nationwide Children's Hospital in Columbus, OH are using Kinect for early detection movement disorders like cerebral palsy in infants. The prototype they built uses a computer vision model to classify an infant’s movement as healthy or at risk so that caregiving and caregivers can intervene early, super important. And medical device company evolve is using it to improve the efficacy of physical therapy for stroke survivors. Their solution incorporates traditional therapeutic exercises in interactive games, which are tailored to each patient’s individual needs. And so as I'm thinking about CVPR and the future of computer vision there are three great breakthroughs that I'm excited about that will push the frontiers of the impact of computer vision in the real world. The first is what I would call 4D understanding. Sometimes you and I have talked about it as Reality-as-a-Service. So if you take a space like a hospital or manufacturing plant and especially around safety and quality. If we want to be able to reason over people, the place, and the things – and in real time using computer vision -- help ensure safety, that can be an amazing breakthrough and we're seeing that already in deployment in many cases. So I just wanted to roll the video to show you that in action.
Satya: The next area, Harry, that we're also excited about in this world of remote everything, is background matting, so if you want, say you're presenting at home, but we want to put you on stage, in fact we recently had the build developer conference and we were able to take presenters who just recorded themselves at home, and then we were able to in fact superimpose them in a virtual stage without needing that green screen. And that's I think again breakthroughs in computer vision that in fact we worked with the University of Washington on, so let's roll the video.
Satya: And Harry the third breakthrough I would say is what we demoed in fact just exactly probably a year ago around Holoportation. So this is a video which shows Julia White, who is one of our colleagues, presenting on stage in English. And there is a hologram of her speaking Japanese because of the combination of neural TTS, holographic computing coming together where you can, in fact, transcend time and space and language. And that, to me, is just an amazing breakthrough and I hope that these are the types of technologies that will get further accelerated.
Harry: Yes Satya, I think this is just so fantastic, you know, really bring back you know my fond memory of, you know, when we even started the first computer vision group, you know, many years ago. Now with great people like Rick Szeliski and Matthew Turk and others, and you also mentioned about the Microsoft Research has many different labs internationally like the Cambridge lab, in China and India. And many vision technologies coming from MSR have contributed to the successful products from Microsoft. Even more exciting to me, you know, from what you described is really this reinforcement between research and product., from the Kinect to more research, then to HoloLens now. You are talking about this amazing video from Julia White with the Holoportation. I think in the future with computer vision is very exciting.
Satya: Absolutely.
Harry: Thank you Satya. So next I'd like to move from computer vision to artificial intelligence, to AI. So Microsoft has invested in AI for a long time. Especially since Bill Gates started Microsoft Research in 1991. I remember the first three groups from MSR were Natural Language Processing, Speech and Vision – all very much AI. And the recently you made it very clear that the cloud and AI are the key for Microsoft’s future growth. And it's also very exciting to see the AI supercomputer announced just last month at Build conference. So what is Microsoft's vision in AI going forward.
Satya: Yeah you know it's so fascinating as you said, in fact the first three groups that were created in Microsoft Research were Speech, Vision and Language. And here we are in 2020 talking about the same three with higher ambition and more success. But it's definitely great to see. I think that for me, one of the fundamental things that we are being at least doing in the last couple of years is looking at these large scale, you know, high-parameter-count models, that are yielding amazing results in particular on language. Especially with you know going from RNNs to these transformer models and the results we are seeing are tremendous. We released something called the Turing model with 17 billion parameters even when you are leading that team right here at Microsoft, and now we've gone you know and partnered even with Open AI and they of course have taken it to the next level with 170 billion parameters or what have you, and yeah it's pretty stunning to see that. And the thing that we did even was build specialized compute like, I mean, after all when you are doing these kind of large scale models, and with all of the challenges you have even with Moore's Law as we speak, we have had to sort of reinvent the system on which you can do these large scale learning. And it's great to see, we’ve built essentially the world’s supercomputer, an AI supercomputer right in Azure, on which we, you know Open AI is training these models, and in fact we're going to use these models as platforms, so others can use these models to do even tuning on top of it for their particular use cases. So we're very excited. I'm also excited about this with the multimodal nature. The dream is always being how can you have these AI training regimes that are learning from text, learning from speech, learning from images. So that there is better representation of knowledge. And so therefore I think that that's all things where I think in the years to come you'll see breakthroughs in systems layer, the modeling techniques and the training techniques and of course the breakthroughs around applications, which I think like in healthcare, you know, if I look at what needs to happen around precision medicine. You need breakthroughs where you're able to take the clinical notes, you're able to take the clinical images, and bring all of it together in order to really drive breakthroughs.
Harry: It’s really exciting. I just want to respond a little bit about that those large models you mentioned about from the Turing model with 17 billion parameters to GPT-3 with 175 billion parameters. And those models and you know Microsoft using Azure to really enable and empower in many research groups in the company to not only train their own models but even apply to the few-shot learning, one-shot learning, even no-shot learning. And the opportunities there is really really amazing. Satya, you know, now even with these keynotes you are doing, you know, we're doing this online that virtually, right now we're really living in this extraordinary time. And with all this excitement in computer vision and AI, I want you pick your brain and how you really think about that the AI vision technologies, and how they should be applied to help people, to deal with their daily lives, daily work during the pandemic right now and even more importantly are in the post COVID world. Can you share with us some examples, how Microsoft is doing it and how Microsoft is helping other people, especially you also mention about how we can help first responders?
Satya: You know absolutely, Harry, I mean. I think one of the things is this crisis has perhaps brought to the fore the need of digital technology and how it can help us at large as a society, both respond, recover as well as reimagine how we work and live going forward. I think all these three phases are going to be happening simultaneously and digital technology including computer vision is going to play a huge role in it. In fact, the video we saw earlier of how remote sensing, remote monitoring of a manufacturing plant, that reality as a service, to ensure safety and safety of operations with Digital Twins, can be very very important for in the manufacturing sector. In fact, the other the application we saw in manufacturing was, you know, we had to rejigger production lines in real time, for example, in order to make ventilators. And that means you needed expertise that was remote to help people who were reformatting those production lines, and that was all done through these HoloLens applications and Dynamics applications called Remote Guides, which is amazing to see. That is one example in manufacturing. In health care, in hospitals in the United Kingdom, we saw a very interesting use of both HoloLens and Teams in combination. So a doctor would go in care for the COVID patient wearing their HoloLens along with the rest of PPE. But the HoloLens, since it saw everything and transmitted that capture back through Teams so that all the other doctors could be outside the patients’ room, and yet you know give instructions on care. So there is really brought to fore both safety and collaboration in new ways in the front lines. And when it comes to medical teaching we saw Case Western Reserve University's Medical School, in fact, send their students home with HoloLens and were able to continue their education around the anatomy class, where the students and the teacher were able to fully ensure that that curriculum continued with full fidelity and it's amazing to see that type of breakthrough. So I think that we're going to start seeing breakthroughs in whether it's in manufacturing, whether it's in healthcare or an education where computer vision is going to be key to this world of remote everything.
Harry: Yeah indeed. I think that you said it very well. It's now, in a way, this acceleration of digital transformation. I think the pandemic just made us to think about that even furthermore. You know one thing I want to ask you is actually your view about the future of work and in this post COVID world. Did you see that you know people will do that more remotely and I think I’ve read somewhere you said that is unthinkable that we will only do things now from now on virtually? Even so some other companies are actually announcing more and more along this line.
Satya: I think that you know I think at a core level I think we will always want to have this capability of remoting every function inside of our enterprise. Whether it's remote sales, remote operations, remote support, remote work at scale. So I think that there's no question. Because I think it's going to be foundational to business continuity and resilience. I think we're also going to learn a lot Harry about what is the effectiveness of remote work for what role, in which industry, in which function. I'm positive that there will be certain roles, in certain industries which absolutely. In fact, if you look at even Microsoft even before pandemic, we had many roles that were 100% remote. And they were very productive. And there were certain roles that required people to come together to collaborate sometimes. So I would say I think what I see is instead of replacing one dogma with another dogma, what is more important is for us to exercise, in fact, the advantage we now have, that we now have the ability to remote anything, to then purpose fit it, so once we come out of the COVID-19 crisis we will use the flexibility to help people, not only their productivity but also their wellbeing, their needs, for example even in the in Seattle region where we have now sent a lot of people home, we're realizing that some people would rather have workspace at work once the COVID-19 crisis goes away, because they want dedicated workspace with good network connectivity, because we have some structural problems, even in the developed countries and in cities like Seattle where Wi-Fi and bandwidth constraints exist. So I want us to be grounded in the realities of people everywhere around the world, and what is the best way to exercise the flexibility, recognizing that remote work can be fantastic and empowering for many people.
Harry: That’s great to hear your thoughts, Satya. My takeaway is that whatever challenges we face, like the pandemic right now, we can always innovate out of this. And it takes a lot of effort, but we’ll go through this. So Satya let's get back to a Microsoft, back to the company. So you have done a marvelous job leading and transforming Microsoft in the past 6 plus years. You have always paid attention and made big bets on communities. Such as LinkedIn for business professionals and GitHub for developers. in fact, the CVPR is a big community for computer vision researchers and the industry practitioners. In fact, the last couple of years the attendance at the conferences approaching 10,000 people a year. So many of us would like to ask you some advice and wisdom, from you and your experience, you know, with fostering the communities. How each of us in the computer vision community can help each other, work together, grow together and the contribute for even better society.
Satya: Absolutely Harry. I mean to us, when we talk about empowering every person and every organization on the planet to achieve more, you know, the central point of that is through digital technology, how do we help people and institutions and communities people built, to thrive. That's been central to Microsoft's mission, is central to Microsoft's business model. We only do well if the world around us that we're serving, whether it's small businesses becoming more productive, large multinational companies in every part of the world becoming more competitive, public sector institutions are becoming more efficient, educational outcomes, health outcomes and communities at large are thriving. So it's very central to us. And in fact even the acquisitions you mentioned, whether it was the developer community with GitHub, the professionals with LinkedIn or even gamers with Minecraft are all communities we have the privilege to serve and it's about their outcomes that ground us. And similarly with computer vision, I think that there's a very rich history of computer vision researchers coming together to create technology breakthroughs, in fact, even though the work we're doing across academia as well as Microsoft Research in our product innovation, and you know Marc Pollefeys at ETH is a great example of that. He obviously is working with us on some of the product breakthroughs, he's also really creating a great world-class research center at ETH, that cross-pollination is core to community building. And it's also not just about computer vision, it’s about computer vision in the broader field of AI, it's the broader field of digital technologies. So I think we absolutely at Microsoft we want to be someone who can help bring that ecosystem platform thinking, so that these communities can come together, and more importantly, can work together with other communities to amplify their work.
Harry: That's really great to hear Satya, there’s a lot of wisdom there. And the one particular aspect of communities is actually international. Just like GitHub is international, LinkedIn is international, gamers are international, computer vision CVPR community is no exception. So, as you think about how you run this multinational company and now with even more communities in some lessons you have learned how can do better in terms of international collaboration.
Satya: Yeah in fact I would say, Harry, this next phase of international collaboration, whether it's for the research community at CVPR or even for a multinational company like Microsoft. I think one thing we have to be very grounded on is how is our work, collectively and individually, helping every community in every country. Talking about globalization, without its benefits being locally relevant, I think we lose permission. In fact if anything that is what we have learned, I think is in the last phase of globalization, many benefited but unfortunately many were left behind. So I think what we have to talk about now and Microsoft that's why I sort of ground us whenever I go to any part of the world I sort of look and say what has Microsoft's participation in that region, that country, led to the local surplus – those small businesses, large businesses, public sector, health outcomes, education outcomes. So unless and until we can concretely point to points of light, progress around local supplies, local employment, local skills. I think we as a global community of, whether it's researchers or multinational companies, will lose permission to even operate. So I think that that's what I would say we all need to recommit ourselves to that next phase of local impact while globally cooperating. I think the more we can think about it and frame what we do in those lines I think we will really be able to keep the progress going.
Harry: That's really great point, Satya, you might be also happy to hear that you know in fact in the CVPR community and even the large computing community like ICCV as always kind of thinking like that as well. That's why practically every University town and college town in the US has probably by now has hosted a CVPR in some year. And ICCV of course also rotates in different continents, as you said that only, you know, when we have local communities thriving can we actually have a global organization. That's fantastic. So Satya we still have a little bit of time, so I actually want to ask you a couple questions that we have received from the audience, you know, ahead of time. The first one is actually a very timely one I know you have been thinking about a lot. It's about AI, it’s about the ethical use of AI, it’s the responsibility of AI and we have noticed that you and the Microsoft have paid a lot of attention to space and even make some tough decisions along this line. So I wonder if you can share with the audience, you know, some of the lessons.
Satya: Absolutely Harry. I mean one of the things that we have been grounded in is when we create AI, how do we ensure we have a set of design principles that codify the core ethical considerations right into the engineering process. It's helpful in fact to think about AI safety and ethical use of AI has a design time as well as a runtime engineering consideration. So, for example on the design time, we started by establishing a set of concrete engineering principles, from fairness to accountability, to security, privacy and so on. So that we can ensure that is part of the design process, we have these as first-class constructs not just abstractions. Then in the context of computer vision we're practicing this. Take what's happening with facial recognition in our face API. One of the first challenges was how do we ensure that there is no bias. And thanks to NIST there are robust benchmarks now to measure the performance against the number of ethnic groups to ensure that there's no bias in our models, and to create a level of transparency that is very helpful. And soon we’ll be providing guidance to our customers and how they can measure the face API performance relative to their own data, to set the right thresholds and balance these false matches. So that's one example. Then on the other side are the runtime considerations and the ethical use of AI. And I think we will all have to realize that sometimes even with all the good intentions during design time, if you don't have safeguards in runtime protecting privacy and our Democratic freedoms for example, they could be really bad unintended consequences. And for the past two years, we've been focused on developing and implementing strong principles that govern our use of facial recognition, and we've also been calling for strong government regulation since 2018. We have published principles that we use to define which projects for example we’ll engage on. And there are many projects we say no to, which fall outside these guidelines. We do not sell our facial recognition technology to police departments in the United States today. And we made that commitment that we will not sell this technology to US police departments until there is a strong national law grounded in human rights. We need to use this moment to advocate for strong national law, otherwise we'll see responsible companies leaving the market and others stepping in. So we think that going forward, companies like ours need to do our best work around the practice of responsible AI, by building it into our engineering process and then when it comes to usage during runtime we have both principles we have to adhere to as well as government regulation around the world.
Harry: Right that's actually a great way to frame it. There’s actually designed time and the run time, that we have to really think about those important ethical and the responsibility problems for AI, and of course computer vision is very important part of that. So Satya my last question for you is that, as the CEO of the number-one company in this universe, and every day you must be thinking about the all those big opportunities and how you can help more people. So, tell us which industry you are most excited about right now to apply the cloud and the AI, and computer vision.
Satya: I mean it's like it's a great question, Harry, because in some sense one of the things I think a lot about and we at Microsoft think a lot about is, how can digital technology in this next phase have much broader impact. I mean if you think about it, the last 10, 15 years have been phenomenal. But I would claim that some of the usage scenarios are narrower. There have been a lot more consumer Internet breakthroughs. But if you look at the broad arc of productivity and productivity leading to economic growth that is helping small businesses, large businesses, helping every sector of the economy, in every part of the world, we've not really achieved even some of the growth rates that were there in the 90’s and the early 2000’s, thanks to the PC. I mean in fact if you go to Robert Gordon's critique of productivity in the United States, in particular, he sorts of points out that between 1870 and 1940 there was amazing progress, and he will even claim that you know the information technology especially the PC led to productivity growth in the 90’s in the early 2000’s. But since then, we've not had great productivity gain, why is it? Some of it could be statistics and how we measure it. But that said, I hope that in this next phase, thanks to AI, thanks to cloud and technologies like this in computer vision, we can see broad sectorial growth. I'm excited about, for example, healthcare. After all, in the US 19% of our GDP is in healthcare. So can we really have breakthroughs in precision medicine, where we are able to take clinical data, the molecular profile and then really make breakthroughs in how people are treated and how care is administered. Autonomy, after all, in a remote everything world, whether it's inside-out or outside-in, like that video we saw of Reality-as-a-Service, is what I described as inside-out economy, which is people are moving, things are moving, and someone is observing and helping to keep things safe. Or if it’s an autonomous object that is moving in the real world. I think autonomy will change transportation as well as operational safety in many many locations. Retail, commerce, we know that's going to be significantly changing even. There it's going to be omni-channel, right? It's offline and online, in fact even COVID-19 has brought forth some of these solutions like contactless shopping, curbside pickup. These are going to be I think will have a huge ramification around how retail is done. Precision agriculture for food security, because that's another huge area. The other area where I'm very excited about is even with computer vision, is accessibility. We have a billion people in the world who still don't participate in our society and economy because of their accessibility needs. And I think that we now have technologies, whether it's machine reading and comprehension technologies for people with dyslexia, so that they can read, or it's Seeing AI-like tools that we built are using latest breakthroughs in computer vision for someone with visual impairment to be able to interpret the world. So, or eye gaze, someone with a ALS to be able to type and communicate with just the gaze of their eyes. So I think that, I hope, we will have real breakthroughs in AI that even bring, you know, newer and greater accessibility technology empowering the billion-plus people in the world who need to participate in our societies and economies. So I'm excited about all of these.
Harry: Indeed it’s really really exciting and you know I picked up the core of your thesis here is productivity. It’s productivity for everyone and everywhere.
Satya: Yeah, that is correct.
Harry: Satya, my real last question, my real last question for you, that I have to ask you for this audience, is that, are you, is Microsoft going to hire more computer vision people.
Satya: We always are there to hire more computer vision people and quite frankly to partner even with all the computer vision people out there in this community. Again, thank you so much Harry, for the opportunity. I think that this is a very important community. I'm so glad even with all the constraints that this community is getting together to talk about the advances. And as you rightfully said, to me what matters the most is not just our technology and technology breakthrough for its own sake, but I know what motivates everyone at this conference is how is this technology leading to that economic growth that is more inclusive, more equitable and really helping everyone on the planet get better at achieving their dreams. And that I think is what each of us cares deeply about and it's fantastic to have this opportunity to talk to you all.
Harry: Thank you very much Satya, it’s so wonderful. I really appreciate your time joining us and thanks everyone online for tuning in, and we’ll have a wonderful future with computer vision. Thank you!