谷歌DeepMindCEO：谷歌最接近AGI的模型是Veo，不是Gemini 3！沒有引入廣告的計劃，曝AI眼鏡最新進展：殺手級應用將出現

51CTO技術棧

01/27

編輯 | 聽雨在達沃斯論壇之後，谷歌Deepmind CEO Demis Hassabis又連續上了兩個播客，放出了不少谷歌的新動向！出乎意料的是，相比於Gemini 3，Demis認為更接近AGI的系統是——視頻生成模型Veo。原因是它更接近世界模型：通過生成10-20秒的真實視頻，理解物理直覺、因果關係、物體如何在世界中運動。對於Anthorpic近期推出的Claude Cowrk，Demis...

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11:44","share_image_url":"https://static.laohu8.com/9a95c1376e76363c1401fee7d3717173","id":"2606823277","market":"us","top_or_hot":-1,"title":"谷歌DeepMindCEO：谷歌最接近AGI的模型是Veo，不是Gemini 3！沒有引入廣告的計劃，曝AI眼鏡最新進展：殺手級應用將出現","media":"51CTO技術棧","content":"<div>\n<p>編輯 | 聽雨在達沃斯論壇之後，谷歌Deepmind CEO Demis Hassabis又連續上了兩個播客，放出了不少谷歌的新動向！出乎意料的是，相比於Gemini 3，Demis認為更接近AGI的系統是——視頻生成模型Veo。原因是它更接近世界模型：通過生成10-20秒的真實視頻，理解物理直覺、因果關係、物體如何在世界中運動。對於Anthorpic近期推出的Claude Cowrk，Demis...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260127130736a45a7c26&s=b\">網頁鏈接</a>\n\n</div>\n","source":"tencent","html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>谷歌DeepMindCEO：谷歌最接近AGI的模型是Veo，不是Gemini 3！沒有引入廣告的計劃，曝AI眼鏡最新進展：殺手級應用將出現</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; 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3，Demis認為更接近AGI的系統是——視頻生成模型Veo。原因是它更接近世界模型：通過生成10-20秒的真實視頻，理解物理直覺、因果關係、物體如何在世界中運動。對於Anthorpic近期推出的Claude Cowrk，Demis...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260127130736a45a7c26&s=b\">網頁鏈接</a>\n\n</div>\n\n<div class=\"bt-text\">\n\n\n<p> 來源：<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260127130736a45a7c26&s=b\">51CTO技術棧</a></p>\n<p>為提升您的閱讀體驗，我們對本頁面進行了排版優化</p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","isBrief":false,"type":0,"news_type":1,"symbol":"LU2592432038.USD","symbol_name":"WELLINGTON MULTI-ASSET HIGH INCOME \"A\" (USD) 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3的編程能力也很滿意。針對ChatGPT傳出增加廣告功能的消息，Demis堅定地表示：Gemini目前沒有引入廣告的計劃。在《大科技播客》中，Demis還透露了谷歌AI眼鏡的最新進展。谷歌已經與Warby Parker、Gentle Monster、三星等合作開發下一代眼鏡，AI眼鏡將於今年夏天推出。隨着Gemini 3這一強大AI模型的推出，他認為谷歌已經很接近實現這一點。","collect":0,"end_time":0,"defaultTopTitle":"qq.com","property":[],"viewcount":null,"language":"zh","relate_stocks":{"LU2592432038.USD":"WELLINGTON MULTI-ASSET HIGH INCOME \"A\" (USD) ACC","LU1032955483.USD":"NORDEA 1 STABLE RETURN \"HB\" (USDHDG) ACC","BK4587":"ChatGPT概念","LU1988902786.USD":"FULLERTON LUX FUNDS GLOBAL ABSOLUTE ALPHA \"I\" (USD) ACC","LU0444973449.USD":"CT (LUX) I GLOBAL TECHNOLOGY \"DU\" (USD) ACC","LU0498741114.HKD":"FRANKLIN GOLD & PRECIOUS METALS \"A\" (HKD) ACC","LU1642822529.SGD":"THREADNEEDLE (LUX) GLOBAL TECHNOLOGY \"A\" (SGD) ACC","LU2602419157.SGD":"HSBC ISLAMIC GLOBAL EQUITY INDEX \"AC\" (SGD) ACC","LU2191332357.HKD":"SCHRODER ISF SUSTAINABLE MULTI-ASSET INCOME \"A\" (HKDHDG) INC","USJW.SI":"ALPHAB 3xLongSG261006","LU1145028129.USD":"ALLIANZ INCOME AND GROWTH \"AQ\" (USD) 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There is no plan to introduce advertising, revealing the latest progress of AI glasses: killer applications will appear","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"GOOG":0.9,"GGLS":0.6,"GOOP":0.6,"GGLL":0.6,"GOOX":0.6,"GOU":0.6,"GOOGL":1.96,"GOOY":0.6,"GOOW":0.6,"USJW.SI":0.6},"content_text":"編輯 | 聽雨在達沃斯論壇之後，谷歌Deepmind CEO Demis Hassabis又連續上了兩個播客，放出了不少谷歌的新動向！出乎意料的是，相比於Gemini 3，Demis認為更接近AGI的系統是——視頻生成模型Veo。原因是它更接近世界模型：通過生成10-20秒的真實視頻，理解物理直覺、因果關係、物體如何在世界中運動。對於Anthorpic近期推出的Claude Cowrk，Demis不甘示弱地表示：谷歌對Gemini 3的編程能力也很滿意。不過，他也透露谷歌現在在代碼方面投入很大，除了推出全新IDE平台Antigravity，他們也在重點提升Gemini的編程和工具調用能力。針對ChatGPT傳出增加廣告功能的消息，Demis堅定地表示：Gemini目前沒有引入廣告的計劃。在《大科技播客》中，Demis還透露了谷歌AI眼鏡的最新進展。谷歌已經與Warby Parker、Gentle Monster、三星等合作開發下一代眼鏡，AI眼鏡將於今年夏天推出。谷歌和 Alphabet 在智能眼鏡上有很深的歷史積累，但Demis指出，過去的問題在於：設備太笨重、電池不夠，最重要的是——沒有「殺手級應用」。他認為「殺手級應用」應該是一個通用的數字助理，能在手機、電腦、眼鏡等各種界面上與用户進行交互，理解周圍的環境。隨着Gemini 3這一強大AI模型的推出，他認為谷歌已經很接近實現這一點。他坦言，谷歌AI眼鏡是他們正在進行的最令人興奮的項目。此外，Demis也肯定了世界模型是 AGI 的關鍵，因為它允許系統在現實世界中進行長期規劃——這點與Yann LeCun的觀點一致。不過LeCun之前在一期節目中表示：通用智能」這一概念本身純屬無稽之談！還引來了Demis的反駁和辯論：Yann LeCun混淆了通用智能和「萬物智能」。關於這場爭論，Demis也在本期《金融時報》的播客中給出了正面回應。Demis在這兩次播客中也重申了一些他此前的觀點，比如：Scaling Law沒有撞牆，谷歌內部能看到很明顯的進步，現有範式還有很大上升空間；通往AGI還需要1-2個Transformer級別的重大突破，比如持續學習、更好的長期記憶機制、更高效的上下文窗口；距離實現AGI還有5-10年，不過這次Demis更新了一個説法：2030年可能有50%概率實現AGI；中國AI公司的進展目前相比美國頭部公司只差6個月，但中國還沒有做出Transformer級別的原創突破，並且Demis覺得西方對DeepSeek的反應有點被誇大了。以下是Demis在《大科技播客》和《金融時報》兩期訪談內容的整理，有部分刪減和潤色，enjoy：現有範式還有很大上升空間Veo是最接近AGI的模型Alex：一年前，外界還在質疑 AI 的進展是否已經開始放緩。當時很流行的一種説法是：大語言模型是否已經撞牆了。但現在看來，這些問題似乎已經被現實回答了——過去一年裏，AI 取得了巨大的進展。你能否具體談談，是什麼讓整個行業從「是否撞牆」的質疑，走到了今天這個階段？Demis Hassabis：坦率地説，我們內部從未真正懷疑過這一點。我們一直看到非常明顯的進步，所以對外界當時的擔憂其實有點困惑。其中一個擔憂來自「數據是否用完了」。確實，現有的人類數據被大量使用過了，人們會問：合成數據是否真的有用？但事實證明，我們依然可以從現有架構和數據中「榨出更多價值」。無論是在預訓練、後訓練、還是推理範式上，以及這些方法如何結合在一起，我們都看到了巨大的潛力。所以我認為，即便只使用我們已經掌握的技術，並在其基礎上持續創新，仍然有非常大的上升空間。Alex：懷疑論者會説：你們其實是在大語言模型之上疊加了大量「技巧」，比如 scaffolding、orchestration、工具調用、搜索網頁等。但問題在於：模型在一個會話裏學到的東西，一旦關閉就忘了。這是不是 LLM 範式本身的根本限制？Demis Hassabis：我確實認為，在通往 AGI 的路上，我們可能還需要一到兩個真正重大的突破。比如持續學習、更好的長期記憶機制、更長或更高效的上下文窗口（不是把一切都存進去，而是只保留重要信息——這正是人腦的做法）、更強的長期推理與規劃能力。目前還不確定，僅靠現有技術不斷 scale 是否足夠，還是需要全新的、深刻的架構創新。如果一定要我選，我更偏向後者。但無論如何，大型基礎模型一定會是最終 AGI 系統的核心組成部分。我並不認同像 Yann LeCun 那樣認為 LLM 是「死衚衕」的觀點。真正的分歧在於：它們是唯一組件，還是關鍵組件之一。DeepMind 的優勢在於我們擁有非常深厚的研究積累，可以同時在兩條路徑上全速推進：一邊繼續擴展和改進現有範式（包括預訓練層面的創新），一邊探索全新的藍天式架構想法——就像過去十多年我們發明 Transformer 那樣。Alex：那如果一個系統裏有大量「硬編碼」的結構，它還能被稱為 AGI 嗎？Demis Hassabis這取決於你所説的「多少」。我對混合系統非常感興趣，也有人稱之為神經符號系統。AlphaGo、AlphaFold 就是很好的例子——它們結合了深度學習與蒙特卡洛搜索等明確的結構。我們也在研究把大語言模型與進化算法結合起來，比如AlphaEvolve，讓系統能夠主動發現新知識。但無論採用什麼架構，學習能力都是 AGI 的核心，甚至可以説是定義本身。「通用」指的就是通用學習能力——能否在任何領域學習新知識。對我而言，學習幾乎等同於智能。Alex：但如果學習等同於智能，而當前模型還無法持續學習，它們能搜索互聯網、當下「理解」問題，但並不會真正改變模型本身。你們對如何解決持續學習問題，有什麼方向性的想法嗎？Demis Hassabis：我可以給你一些線索。我們確實在這方面投入了大量精力。過去我們在 AlphaZero、AlphaGo Zero 中已經展示過：系統可以從零開始學習，或者在已有知識基礎上繼續學習——但這些都發生在非常狹窄、規則明確的領域（比如遊戲）。現實世界要複雜得多，這些方法是否能真正泛化仍有待驗證。但至少我們已經知道：這些技術在受限環境下可以做到非常驚人的事情。現在關鍵的問題是：能否將這些方法與大型基礎模型融合起來。我們當然希望模型不僅在訓練階段學習，也能在「現實世界」中持續學習，包括個性化。一個真正優秀的助手，必須理解你、為你工作。我們上周啱啱發布了第一代「個人智能」能力，但那還只是把數據放進上下文窗口裏。真正理想的狀態，是模型本身會隨着時間發生變化——而這一點，目前還沒有被真正攻克。Alex：説到 AGI，我之前和 Sam Altman 聊過。他説 AGI 的定義本身就很模糊，甚至希望大家能承認「我們已經越過 AGI，正在邁向超級智能」。你同意這種説法嗎？Demis Hassabis：我理解他為什麼希望這麼説，但我完全不同意。AGI 不應該變成一個營銷概念。它一直有明確的科學定義：一個系統，能夠展現出人類所具備的全部認知能力。不僅是解題，而是提出突破性的理論；不僅是生成藝術，而是像畢加索、莫扎特那樣創造全新的藝術範式；不僅是思維能力，還包括物理智能——對身體、運動、現實世界的控制。今天的系統，在我看來離這一點還非常非常遠。我認為真正的 AGI，至少還需要5 到 10 年。Alex：你最近提到，最接近 AGI 的系統並不是 Gemini 3，而是一個圖像生成模型 「Nano Banana」。這讓我非常驚訝。Demis Hassabis：名字確實有點玩笑性質。但更重要的是像我們的視頻生成模型Veo。從 AGI 的角度看，它更有意義。一個能夠生成 10–20 秒真實視頻的模型，本質上是在學習世界模型——理解物理直覺、因果關係、物體如何在世界中運動。世界模型是 AGI 的關鍵，因為它允許系統在現實世界中進行長期規劃。這正是人類輕鬆做到、但當前 AI 仍然無法完成的事情。這對機器人尤為重要：想象機器人在腦中模擬多種可能軌跡，再選擇最優路徑執行任務。谷歌AI眼鏡預計今年夏天推出殺手級應用：通用數字助理Alex：我們聊點產品。我看了紀錄片《The Thinking Game》，發現你一直拿着手機對着現實世界問 AI。我當時就在想：你真的需要一副 AI 眼鏡。手機顯然不是正確的形態。你怎麼看 AI 眼鏡？什麼時候會推出？Demis Hassabis：你説得完全對。我們內部「自用」這些系統時也非常明顯：手機能用，但不是最佳形態。很多場景，比如做飯、在城市中導航、輔助視障人群，都需要解放雙手。對戴眼鏡的人來説，把 AI 放在眼鏡上是非常自然的下一步。Google 和 Alphabet 在智能眼鏡上有很深的歷史積累。過去的問題在於：設備太笨重、電池不夠，更重要的是——沒有殺手級應用。現在我認為殺手級應用應該是一個通用數字助理，在手機、電腦、眼鏡等任何界面都能用，理解你周圍的每個環境。我認為我們已經很接近了，尤其是Gemini 3出來後，我們擁有了強大的AI能力，能讓它成為現實。這是我們正在進行的最興奮的項目之一，也是我個人正在努力的方向——讓智能眼鏡真正發揮作用。我們已經和 Warby Parker、Gentle Monster、三星等合作開發下一代眼鏡，如果進展順利，你們可能在今年夏天就能看到它們。Gemini目前沒有引入廣告的計劃Alex：我們來聊聊廣告吧。現在這個時間點，真的適合在 AI 裏引入廣告嗎？最近有一些消息稱，Gemini 未來可能會加入廣告；你們的一些競爭對手也有類似傳聞。我在社交媒體上看到一個挺好笑、但也挺尖鋭的評論，有人説：「如果商業模式還是廣告，那這些東西離 AGI 還遠得很，也不可能成為真正顛覆世界的技術。」你同意這種説法嗎？Demis Hassabis：這個問題很有意思，我認為這其實是一個「信號」。行動往往比言辭更有説服力。如果有人一邊説「AGI 已經近在眼前」，一邊又在認真考慮往產品裏塞廣告，那確實會讓人產生疑問：如果真的快到 AGI 了，你為什麼還要折騰廣告？這是一個合理的問題。就我們目前而言，如果你問的是Gemini 應用本身——我們現在沒有任何引入廣告的計劃。當然，我們會非常謹慎地觀察競爭對手（比如 ChatGPT）最終會怎麼做。但這裏面存在一個非常重要的張力：如果你想打造的是一個真正「為你服務」的個人助理，那最核心的是什麼？信任。包括信任、安全、隱私。你希望把自己的生活交給它，就必須確信：它是在代表你的利益行動，而不是其他人的利益。所以廣告這件事必須極其小心。理論上也許存在可行方案，但一旦廣告邏輯「滲透」進推薦系統，就會讓用户開始困惑：「它現在推薦這個，是為了我，還是為了廣告主？」這是一個非常微妙、但極其關鍵的挑戰。Alex：Sundar 在最近的財報電話會上提到，Google 內部確實在討論「如何以正確方式處理這件事」。那你個人怎麼看廣告這件事？Demis Hassabis我們還在頭腦風暴階段，沒有定論。但我想補充一點：如果你把視角放到眼鏡、可穿戴設備這些新形態上，其實是存在其他商業模式的，不一定非要走傳統廣告那條路。所以這是一個需要非常慎重思考的領域。Alex我還是想再確認一次，得到一個明確回答。我看到一些報道説：Google 去年曾對廣告商表示，計劃在2026 年把廣告引入 Gemini 聊天機器人。Demis Hassabis不。我們目前沒有這樣的計劃。我只能説到這裏。谷歌正在全面提升Gemini的編程和工具調用能力Alex：Anthropic 的Claude Code、Claude Cowork 最近引發了巨大討論。一位前亞馬遜高管説，他用 Claude Code一天半就搭了一個定製 CRM。你怎麼看？你們會推出類似的東西嗎？Demis Hassabis：這真的非常令人興奮。必須要説一句：Anthropic 做得非常好。我們對Gemini 3 的編程能力也非常滿意，尤其是在前端方面。我自己在聖誕假期用它做了小遊戲原型，效果非常驚人。説實話，它讓我重新找回了寫代碼的樂趣。我非常喜歡現在正在發生的「vibe coding」浪潮。這會極大解放設計師、創意人、藝術家，過去他們必須依賴程序員團隊，現在很多事情可以自己完成了。這將創造大量新的創作可能性。我們在代碼方向投入很大，啱啱發布了自己的 IDE ——Antigravity，需求非常旺盛，甚至有點供不應求。我們正在全力提升 Gemini 在編程和工具調用方面的能力。但公平地説，Anthropic 的策略非常聚焦：他們不做圖像模型、不做世界模型、不做多模態，只專注在語言和代碼，而且確實做得非常出色。一方面我們很高興能在某些層面與他們合作，另一方面，這也給了我們持續進步的動力。Alex：我們從更宏觀的角度聊聊 AI 行業的商業前景。我有一個關於「AI 會如何崩塌」的理論，想聽聽你的看法。它是一個三步過程：大模型訓練的邊際收益開始下降出現像 Gemini Flash 這樣的超便宜模型，算力成本接近搜索鉅額算力與基礎設施投入因此變得多餘，引發連鎖崩潰這是一個合理的擔憂嗎？Demis Hassabis：這是一個可能發生的情景，但我不認為它是最有可能的。AI 已經證明了自己的價值，尤其是在科學領域——AlphaFold、藥物發現等方向。我們已經遠遠越過了「AI 是否真的有用」的階段。我確信AI 會成為人類歷史上最具變革性的技術。真正的不確定性只是時間尺度：是 2 年？還是 5 年？但無論如何，對如此重大的變革來説，都是「非常快」。我認為現在反而存在一個巨大的能力滯後：即便是今天的模型，能做的事情也遠遠超出我們真正部署和理解的範圍。對 Google 來説，我們才啱啱開始把 AI 深度嵌入到已有產品中，更不用説全新的 AI 原生產品。比如AI Inbox（誰願意做郵件管理？）、瀏覽器代理、YouTube、搜索，機會是巨大的。Alex：所以你怎麼看「AI 泡沫」這個説法？Demis Hassabis：我不覺得這是一個非黑即白的問題。我認為AI 行業的某些部分確實存在泡沫，另一些則沒有。比如，當你看到一些公司在沒有產品、沒有研究成果的情況下，就完成數十億美元的融資，這在正常市場裏顯然是不可持續的。但另一方面，我們這樣的公司有着龐大的既有業務和產品體系，AI 如何提升效率和生產力是非常清晰的。至於聊天機器人、眼鏡等全新 AI 產品的市場規模，它們很可能非常巨大，但確實還需要時間驗證。我的工作，是確保無論泡沫是否存在、是否破裂，DeepMind 和 Alphabet 都能贏。在保守情形下，我們可以強化既有業務；在樂觀情形下，我們站在最前沿。信息是宇宙最基本的單位Alex：你最近説過，你認為信息，而不是能量或物質，是宇宙最基本的單位。能簡單解釋一下嗎？Demis Hassabis很難用兩分鐘講清，但我試試。如果你從生物學角度看：生命本質上是對抗熵增的信息系統。我們試圖在混亂中維持結構與信息。從更宏觀的角度看：行星、山脈、小行星之所以能長期穩定存在，是因為它們的信息結構在某種「選擇壓力」下得以保留。AlphaFold 正是一個很好的例子。蛋白質結構理論上有無限可能，但只有極少數是穩定的。理解這個「信息拓撲結構」，問題就不再是「大海撈針」。這正是 AI 將如何幫助我們發現新藥、材料、超導體，本質上是在信息空間中導航。Alex：在 AlphaGo 之後，你們讓 AlphaZero 完全脱離人類知識，自主探索，結果它發現了人類從未想到的走法。如果有一天，大模型也完全掌握了人類全部知識，然後被「放飛」，會發生什麼？Demis Hassabis：我覺得那會非常令人興奮。那一刻，才是真正的 AGI。它可能會發現室温超導體、全新的能源形式、更優的電池架構這些東西在物理規律中是可能的，只是我們還沒找到。一旦系統達到人類知識上限，再加上類似 AlphaZero 的機制，它就能進入真正的未知領域。Alex：就像把整個天氣系統接入它的大腦。Demis Hassabis：對，正是這個意思。中國AI公司進展相比美國只差6個月美國對DeepSeek過度反應了Roula：你此前也談到過 AI 競賽，以及與中國之間的競爭。但從我的觀察來看，中國似乎並不存在你們所説的那種「AI 競賽」。那裏並沒有圍繞 AGI 的競速，而是更多聚焦在應用落地和效率提升上。這種路線，會不會反而更現實一些？Demis Hassabis:這或許是一種風險更低的路徑，但是否「更現實」，我不太確定。不過我想補充一點：據我了解，中國市場內部的競爭同樣非常激烈，並不比西方公司之間弱。只是你説得對，他們更關注短期內能做什麼——眼下可以落地的應用，而不是那些更偏研究導向、指向 AGI 的前沿能力。這本身沒有問題。但我當初創辦 DeepMind，如今在 Google DeepMind 和 Alphabet，我們的目標非常明確：構建 AGI。我們認為這是終極目標，一旦實現，將解鎖我們多次討論過的、極其廣闊的世界級機遇。AGI 是我們的北極星。在通往它的過程中，我們當然也會創造大量有用的技術，但如果你想以儘可能具有創新性的方式推動研究，就必須有這樣一個長期目標。這也是為什麼在我看來，西方公司目前仍然領先。Roula:那你認為領先優勢有多大？是以「年」為單位，還是只是幾個月？Demis Hassabis:我猜現在可能只差幾個月。有意思的是，我和一些中國的領軍企業家交流過，他們自己覺得落後得更多一些。我並不確定這是否準確。在我看來，也許是6 個月左右的差距。我還想説一點：像DeepSeek這樣的案例，在西方引發的反應，我認為有點被誇大了。中國的實驗室確實在越來越快地追趕前沿，但他們還沒有證明自己能夠超越前沿進行原創性突破——比如提出「下一個 Transformer」級別的架構創新。這一點，他們目前還沒有展示出來。與Yann LeCun的AGI分歧：通用智能 vs 「萬物智能」Roula：最近幾個月，關於 AGI 的討論很多。你和 Yann LeCun 在這個問題上存在明顯分歧，他認為「根本不存在通用智能」。你是研究大腦的專家，能否解釋一下你為什麼不同意他的觀點？Demis Hassabis：是的，Yann 和我在會議上經常進行這種「友好的爭論」，這次只是發生在網上。坦率地説，我覺得他在這個問題上的論證有些站不住腳。他混淆了兩個概念：通用智能和「萬能智能」——即能理解一切可能存在之物。人類顯然擁有前者。我們的文明本身就是最好的證明。人類是製造工具的物種，這是我們與其他動物的根本區別。從飛機、計算機，到如今的 AI，本質上都是工具。AI 可以看作是計算工具的終極形態。如果你把這些都納入考慮——科學、工程、技術體系，人類智能顯然是高度通用的。它並不是「能處理任何可能刺激視網膜的信號」，但這並不重要，它仍然是通用的。我還會從艾倫·圖靈的角度來論證。圖靈證明了：圖靈機可以計算一切可計算的問題。這是一個極其通用的計算模型，而所有現代計算機都建立在這個基礎之上。大多數神經科學家也會同意：人腦在近似意義上是圖靈完備的。這意味着，在理論上，我們可以理解幾乎所有「可計算的事物」。關鍵區別在於：是否具備學習能力，而不是是否已經掌握了全部知識。單個人類當然是有限的，但從整體上看，人類大腦系統極其強大、靈活，而且高度通用。Isomorphic Labs新進展：與強生官宣藥物項目新合作Roula：我們來聊聊Isomorphic Labs。最初你們曾説計劃在 2025 年第四季度進入臨床試驗，但後來變成了「臨床前階段」。發生了什麼？Demis Hassabis：其實沒有發生任何問題，是我當時口誤了。幾年前的一次採訪中我説錯了，正確的説法一直都是臨床前階段。我們去年已經進入了臨床前試驗，目前有多個藥物項目在推進，進展非常順利。一旦準備就緒，就會進入正式臨床試驗。Roula：那第一款由 AI 設計的藥物，什麼時候能真正問世？Demis Hassabis：我希望在未來幾年內，但這取決於臨床前和臨床試驗的進展。Roula：這件事比你原先預期的要困難嗎？Demis Hassabis：完全沒有。事實上，進展非常好。我們昨天啱啱宣佈與強生（J&J）達成新的合作。目前我們已經與J&J、禮來（Eli Lilly）和諾華（Novartis）合作，再加上我們自己的內部項目，總共有大約17 個藥物項目。今年上半年你們會聽到我們公布更多進展。Roula：你們還宣佈將在英國建立一個材料科學實驗室，能多介紹一些嗎？Demis Hassabis目前還處在比較早期階段，但我認為：AI 在材料科學上的潛力巨大，包括半導體、超導體、電池等關鍵材料。現在的階段，大致相當於AlphaFold 1的水平——已經有非常有前景的研究原型，但還需要走得更遠。關鍵在於：我們需要能快速驗證 AI 設計出的新材料。因此我們在考慮建立一種高度自動化的實驗室，用來測試 AI 提出的理論化合物。2030年有50%概率實現AGIRoula：我幾乎每次見你都會問：AGI 的時間表是什麼？最近我注意到，你們似乎都不太願意再給出明確時間點了。Sam Altman 甚至説，我們幾乎已經「到了那個階段」。你現在的判斷是什麼？Demis Hassabis我的判斷其實一直很一致：5 到 10 年。如果要更新一下，那可能是4 到 9 年，甚至4 到 8 年。2030 年左右，可能是一個最早有 50% 概率的時間窗口。我仍然堅持這個判斷。一些此前更激進的人，可能正在把時間線往後調，變得更現實一些。經驗告訴我：即便在如此快的進展速度下，事情往往還是比我們最初預期的要慢一些。但即便如此，這依然是非常、非常快的時間表。只是，它不會是明年。參考鏈接：https://www.youtube.com/watch?v=bgBfobN2A7Ahttps://www.youtube.com/watch?v=-RPbxvz6sB8——好文推薦——Yann LeCun新動向：加入邏輯智能！新公司AMI Labs官宣核心路線：幾年內構建真正理解物理世界的系統；曝離職原因：工業界已經被LLM洗腦了又一開源項目橫掃硅谷！幾天狂飆25k星！手機發消息即遙控Mac設備！網友直呼：比ChatGPT好用，賈維斯終於來了！僅需5美刀OpenAI首次攤開Codex內核！內部工程師自曝反直覺上下文壓縮機制：OpenAI故意不用優化接口。網友：這次開源就比CC強，無需逆向","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"}}}