根據《紐約時報》報道，美國情報人員曾秘密監聽一名中國情報線人，而與該線人通話的美國人正是英偉達（Nvidia）首席執行官黃仁勳（Jensen Huang）。
這名線人是愛麗絲‧黃（Alice Huang，中文名：黃樂），她是中國公民，也是一家名為Megaspeed的資料中心公司的高階主管。這家公司鮮為人知，但美國官員懷疑它在幕後運作，將英偉達的人工智慧（AI）晶片輸送至中國。
《紐約時報》報道稱，美國官員認定她一直在向北京輸送情報。
2024年6月，她與黃仁勳在台北一家酒吧被拍到一起喝威士忌；幾週後，Megaspeed的一家關聯公司便開始採購搭載英偉達技術的設備，總金額至少達到48億美元。
根據《紐約時報》報道，川普在大約一年前就獲悉了此事。
但他什麼也沒做。
據《紐約時報》稱，川普當時擔心，如果採取行動，可能會損害英偉達的晶片銷售——這些銷售額正有力推動著美國經濟和華爾街的表現——同時也可能使美中貿易關係變得複雜。
黃仁勳是川普最有影響力的盟友之一，但他甚至從未收到美國政府針對「被外國間諜盯上的美國公民」所提供的常規安全警示（即「防禦性簡報」）。
今年，Megaspeed仍在持續採購英偉達的產品，而其最大的客戶是阿里巴巴。
調查人員懷疑，部分晶片已被走私進入中國；此外，一名美國商務部官員在Megaspeed位於馬來西亞的設施中發現，相關設備仍原封不動地裝在箱子裡。
在英偉達的官方網站上，Megaspeed至今仍被列為雲端合作夥伴。
美國官員起初認為黃仁勳並不知曉此人的真實身份，但據《紐約時報》報道，川普政府的一些高級官員懷疑，他不可能對此一無所知。
中國在美國最重要的人工智慧公司內部安插了線人，而晶片則源源不斷地流入了中國。
US spies were secretly listening to a Chinese intelligence asset, and the American on the other end was Nvidia CEO Jensen Huang, The New York Times reports.
The asset was Alice Huang, also known as Huang Le, a Chinese citizen and top executive at Megaspeed, a little-known data center firm that US officials suspected of steering Nvidia’s AI chips to China.
The Times reports that US officials concluded she was funneling information to Beijing.
Weeks after she and Jensen were photographed drinking whiskey at a Taipei bar in June 2024, Megaspeed’s affiliate began buying what eventually totaled at least $4.8 billion in Nvidia-powered equipment.
Trump was briefed roughly a year ago, the Times says.
He did nothing.
According to the Times, he was wary of hurting Nvidia’s chip sales, which are boosting the economy and Wall Street, and of complicating trade with China.
Jensen, one of Trump’s most influential allies, was never even given the standard defensive briefing for Americans targeted by foreign spies.
Megaspeed kept buying Nvidia products this year, and its top customer is Alibaba.
Investigators suspect some chips were smuggled into China, and a Commerce official found the equipment at its Malaysia site still sitting in boxes.
Nvidia still lists Megaspeed as a cloud partner on its website.
Officials initially did not believe Jensen knew her role, but the Times says some senior Trump administration officials doubt he could have been unaware.
China had a source inside the inner circle of America’s most important AI company, and the chips kept flowing.
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Eve Holley
黃仁勳最近對英國講了一句很直接的話…
「就算有一百萬種成功的方法，
你們也會找出那一個不去做的理由。」
其實他不是覺得英國不夠強。
剛好相反。
他說英國有非常好的人才、世界級的大學、研究實力，也有資金。
問題是，明明手上有這麼好的牌，遇到新的機會時，卻很容易先去想：
會不會失敗？
風險在哪裡？
還有什麼問題沒有解決？
再加上基礎建設、制度和執行速度跟不上，很多很好的研究，最後沒有真的長成夠大的公司。
他講了一個我覺得很有趣的對比。
如果你告訴一個創業家：
「這件事只有百萬分之一的機會成功。」
創業家聽到的可能是：
「所以還是有機會。」
但他覺得，英國人很容易看到的是另外那 999,999 個失敗的可能。
這一點，在我長期接觸英國人與文化之後，其實滿能理解。
美國文化比較習慣直接講 企圖心 （ambition）、夢想、目標。
如果一個美國人說：
「I believe I can change the world.」
大家可能會幫他鼓掌。
但英國人很習慣 understatement、自嘲、互虧。
你突然很認真地說：
「我要改變世界。」
朋友可能第一個反應是先虧你兩句。
但我覺得這比較像是英美兩種文化表達 企圖心 的方式不一樣。
英國人不是沒有企圖心，很多時候只是不習慣把它講得那麼大聲。
而黃仁勳這次點出來的，是另一件事：
謹慎本來不是壞事，但如果每一次都先找到不做的理由，機會也可能就在分析的過程裡過去了。
所以他最後講得很直接：
Believe in yourself.
相信你們自己。
因為連 NVIDIA 都真的把錢投進去了。
NVIDIA 表示，近年在歐洲科技生態系投資超過 100 億美元，而且大部分在英國；這次也繼續宣布新的英國投資。
所以他的意思其實很像：
「我一個外面的人都相信你們有這個能力，你們自己不要先把自己否定掉。」
我看到這段話很有感…
有時候我們不是不知道自己可以做什麼。
只是太習慣先把所有風險想完、所有問題處理完，才願意開始。
但很多事情真的沒有辦法等到 100% 確定。
先找到那一個可以做的理由，然後往前走一步。
只有先跨出第一步，才知道下一步在哪裡。
ps 我把影片放在留言，黃仁勳真的超級直白 😂
King, Jensen.Infinite machine
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科學發現的偉大時代來了..
這是80年代ai 學者如 h a simon的著作等.....Sir Demis Hassabis (born 27 July 1976) The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence is a 2026 biography by Sebastian Mallaby.書評見The Economist等；
- About the Subject: Demis Hassabis is portrayed as a unique, driven figure focused on scientific discovery rather than mere wealth, leading DeepMind (now Google DeepMind) in an intense race to build AGI.
- Author's Access: Author Sebastian Mallaby, a two-time Pulitzer finalist, conducted hundreds of hours of interviews with Hassabis, his team, and rivals over three years to create this comprehensive portrait.
- Core Themes: The book explores the high-stakes, expensive, and sometimes controversial nature of AI development, including the potential for AGI to reshape humanity, often drawing parallels to the development of the atomic bomb.
- Unique Perspective: Unlike many Silicon Valley narratives, this book highlights Hassabis's decision to remain in Britain and his critical view of the tech industry, emphasizing his goal of, as described in this NPR interview, "scientific enlightenment".
- Content: The book covers the journey from AlphaGo, the creation of AI systems that can learn like humans, to the broader implications for society.
Sir Demis Hassabis | |
|---|---|
 Hassabis in 2025 | |
| Born | 27 July 1976 |
| Alma mater | |
| Known for | |
Sir Demis Hassabis (born 27 July 1976)[6] is a British artificial intelligence (AI) researcher and entrepreneur. He is the chief executive officer and co-founder of Google DeepMind[7] and Isomorphic Labs,[8][9][10] and a UK Government AI Adviser.[11] In 2024, Hassabis and John M. Jumper were jointly awarded the Nobel Prize in Chemistry for their AI research contributions for protein structure prediction.[12][13][14]
Hassabis is a Fellow of the Royal Society and has won awards for his research efforts, including the Breakthrough Prize, the Canada Gairdner International Award and the Lasker Award. In 2017 he was appointed a CBE and was included in the Time 100, a list of the most influential people in the world. In 2024 Hassabis was knighted for his work on AI.[15] He was listed in the Time 100 again in 2025, this time featured in one of the five covers of the printed version.[16]
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https://en.wikipedia.org/wiki/Demis_Hassabis
他致力於想像力、記憶和失憶症領域的研究，曾與他人合著多篇具有影響力的論文，發表於《自然》、《科學》、《神經元》和《美國國家科學院院刊》[48]。他的第一篇學術論文發表於《美國國家科學院院刊》[49]，是一篇里程碑式的論文，首次系統性地證明，海馬體受損（已知會導致失憶症）的患者也無法想像自己置身於新的體驗之中。這項發現建立了想像的建構過程與情景記憶提取的重構過程之間的連結。基於這項工作以及後續的功能性磁振造影（fMRI）研究[50]，哈薩比斯提出了情景記憶系統的新理論，將場景建構（即生成和在線維持複雜連貫的場景）視為記憶提取和想像的關鍵基礎過程[51]。這項工作在主流媒體上得到了廣泛報道[52]，並被《科學》雜誌評為年度十大科學突破之一[53]。他後來將這些想法推廣開來，提出了「思維模擬引擎」的概念，其作用是想像事件和場景，以幫助更好地進行規劃。 [54][55]
Working in the field of imagination, memory, and amnesia, he co-authored several influential papers published in Nature, Science, Neuron, and PNAS.[48] His very first academic work, published in PNAS,[49] was a landmark paper that showed systematically for the first time that patients with damage to their hippocampus, known to cause amnesia, were also unable to imagine themselves in new experiences. The finding established a link between the constructive process of imagination and the reconstructive process of episodic memory recall. Based on this work and a follow-up functional magnetic resonance imaging (fMRI) study,[50] Hassabis developed a new theoretical account of the episodic memory system identifying scene construction, the generation and online maintenance of a complex and coherent scene, as a key process underlying both memory recall and imagination.[51] This work received widespread coverage in the mainstream media[52] and was listed in the top 10 scientific breakthroughs of the year by the journal Science.[53] He later generalised these ideas to advance the notion of a 'simulation engine of the mind' whose role it was to imagine events and scenarios to aid with better planning.[54][55]
WWWW
2025年，當AI成為最火熱科技名詞，紀錄片《思考遊戲》（The Thinking Game）上線引發社群轟動。因為它揭開的幕後祕辛，是從稱霸圍棋界到摘下諾貝爾獎桂冠都難不倒的人工智慧公司：Google DeepMind。
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