Name: Nvidia 執行長黃仁勳：AI 將徹底改變我們計算一切的方式！ (Nvidia CEO Jensen Huang: AI is going to fundamentally change how we compute everything)
Uploaded: 2026-02-10T08:46:48.000Z
Duration: 8 min 35 s

to 不定詞

It's an interesting time to have you obviously, which any time is, but

很高興你來了，其實任何時候都很棒，但

especially given what's been happening within the market today looks a lot different than the last couple of days.

尤其考量到今天市場上發生的事，跟前幾天比起來很不一樣。

現在進行式

Have the market obviously concerned with what's happening on the spending side of the hyperscalers and this big build out in AI, what's your take from that?

市場顯然很關心雲端服務巨頭的支出狀況，以及這波大型 AI 建置潮，你怎麼看？

The way the market continues to react to this demand is sky high and there's a fundamental reason for that.

市場對這個需求的反應持續高漲，而且有其根本原因。

We're in the once in a generation infrastructure buildout.

我們正處於一代才一次的基礎設施建置潮。

This is the largest infrastructure buildout in human history and there's a fundamental reason for that.

這是人類史上最大規模的基礎設施建置，而且有其根本原因。

Artificial intelligence is going to fundamentally change how we compute everything.

人工智慧將從根本上改變我們所有的運算方式。

Everything from database processing, the way we do search, the way we do recommender systems that you shot, the way you watch movies, and

從資料庫處理、搜尋方式、你剛提到的推薦系統、你看電影的方式，到

of course these new agentic systems that are being developed and evolved.

當然還有這些正在開發和演進的新型代理系統。

Last year, this last year, we saw an inflection point in AI.

去年，就在去年，我們看到了人工智慧的轉捩點。

No longer hallucinating, it's generating informed content, its reasoning, it's thinking, it's doing research, it's able to use tools.

它不再是胡說八道，而是產生有根據的內容，進行推理、思考、研究，並且能夠使用工具。

All of a sudden AI over the last couple of years went from being curious to super useful.

在過去幾年裡，人工智慧突然從令人好奇變得超級實用。

If they could have twice as much compute, the revenues would go up four times as much.

如果他們能有兩倍的運算能力，營收就會增加四倍。

I mean literally, these guys are so demand, so compute constrained and the demand is so incredibly great.

我的意思是，這些公司真的非常缺算力，需求又極其龐大。

The number of enterprise users, the number of consumer users, the number of startups are being built on top of these companies.

企業用戶、消費者用戶、新創公司在其基礎上建立的數量。

So when you see numbers that are frankly remarkable, that $660 billion this year will be spent by the hyperscalers, as we continue to learn, like we did from Amazon last night, you sit back and think to yourself that's completely justified.

所以當你看到這些令人驚嘆的數字，今年超大規模用戶將花費 6600 億美元，就像我們昨晚從亞馬遜學到的那樣，你會坐下來想，這完全是合理的。

Based on what you see, it is appropriate and sustainable.

根據你看到的，這是恰當且可持續的。

And the reason for that is because all of these companies, cash flows are going to start rising.

這樣做的原因是，所有這些公司的現金流都將開始上升。

You know, people are comparing it to cash flows.

你知道，人們把它們和現金流做比較。

We are addressing the largest software opportunity in history for the very first time.

我們正在首次解決歷史上最大的軟體機會。

Now software uses tools, so these AIs use Excel.

現在軟體會用到工具，所以這些人工智慧會用到 Excel。

And so I think the opportunity for this new era of software is incredible.

我覺得這個新時代軟體的機會真的太棒了。

And we're seeing it already moving the earnings of meta.

我們已經看到它正在帶動 Meta 的營收成長。

沒有人比 Meta 更懂如何運用人工智慧。

And so if you look at the way that they're using AI, AI went from a classical recommender system running on CPUs to now a generative AI agentic system that is making recommendations.

所以如果你看看他們使用人工智慧的方式，人工智慧已經從運行在 CPU 上的傳統推薦系統，轉變為現在能做出推薦的生成式人工智慧代理系統。

Everything from the way the social media works and the way they recommend ads and help advertisers create content has fundamentally been changed and their earnings show it.

從社群媒體的運作方式、他們推薦廣告的方式，到協助廣告商創作內容，一切都已經徹底改變，他們的營收也證明瞭這一點。

And that's the reason why they're investing so hard.

這也是他們如此大力投資的原因。

They see just a much larger future potential for it.

他們看到了它更大的未來潛力。

This is going to affect AWS shopping and the way they recommend goods.

這將會影響 AWS 的購物體驗以及他們推薦商品的方式。

This is going to affect how Microsoft's enterprise software works.

這將會影響 Microsoft 的企業軟體運作方式。

Every single company is seized the same inflection point and that's why everybody leaning in so hard.

每家公司都抓住了相同的轉捩點，這也是為什麼大家這麼用力投入。

I feel like that's the point that you were.

我覺得這就是你提到的那個點。

It sort of turns the way you need to think about these businesses on its head, that if you're just fixated on the spending side, as you were talking earlier about, oh, they're spending such a huge portion of their free cash flow, you're kind of missing the story.

這有點顛覆了你對這些企業的思考方式，如果你只專注在花費方面，就像你之前說的，哦，他們花了這麼大比例的自由現金流，你就錯過了重點。

The market needs to get its arms around that.

If you turn the clock back, Scott, to 2008, 2009, Amazon could have taken their profits and sent them back to us by way of dividends.

如果我們把時間倒回到 2008、2009 年，Amazon 可以把他們的利潤透過股息發還給我們。

Instead, Jeff Bezos said, I'm going to invest in this thing called us.

但 Jeff Bezos 說，我要投資這個叫做「我們」的東西。

You have to spend a lot of money to dig the gold mine before you get the money, before you get the gold out.

你必須花很多錢去挖金礦，才能賺到錢，才能把黃金挖出來。

These guys are digging the biggest gold mine in the history of software.

這些人正在挖軟體史上最大的金礦。

Now the question is, do you believe Andy Jassy and Mark, you know, Mark Zuckerberg and Sundar and Jensen, that this opportunity is that big, or do you have a special insight that causes you to understand there's no gold in the bottom of the gold mine?

現在的問題是，你相信 Andy Jassy 和 Mark，你知道，Mark Zuckerberg、Sundar 和 Jensen 嗎？相信這個機會有這麼大，還是你有什麼特別的見解，讓你覺得金礦底下根本沒有黃金？

身為一個投資人，我只想告訴你。

I want my personal net worth, I want my funds net worth levered against AI because all human progress is going to be derived from machines helping humans think and augment human thinking.

我希望我的個人淨資產，我希望我的基金淨資產能槓桿化 AI，因為所有人類的進步都將來自於機器協助人類思考和增強人類的思維。

And so whether it's owning Nvidia, which is our largest public position, or whether it's anthropic or open air, all of these companies are going to be tremendous beneficiaries and they're doing it at scale.

所以，無論是持有 Nvidia，這是我們最大的公開部位，還是 Anthropic 或 OpenAI，所有這些公司都將是巨大的受益者，而且他們正在大規模地進行。

There are increasing advantages to scale.

And so I think it's hard for people to get their arms around now, just like it was in 2008 and 2009.

所以我覺得現在大家很難理解，就像 2008 年和 2009 年那時候一樣。

但謝天謝地，Jeff Bezos 這麼做了。

Now it's $140 billion business generating 30 billion a year in annual profits that people criticized him for investing in back then.

現在這是一個 1400 億美元的事業，每年能賺 300 億美元的利潤，這是在當時被大家批評他投資的。

How just it's incredible that Open Air And Anthropic are $20 billion run rate companies.

真的好難以置信，OpenAI 和 Anthropic 已經是年收入 200 億美元的公司了。

Generating profitable revenues and accelerating growth all at the same time.

同時創造獲利營收並加速成長。

These are extraordinary things and it makes perfect sense from where we sit.

這些都是非凡的事情，從我們的角度來看是完全說得通的。

How can we be so certain that the amount of compute we think we'll need and that we continue to hear from CEOs like you that we will need is actually going to come to fruition?

我們怎麼能如此確定，我們認為我們需要的運算量，以及我們不斷聽執行長們說我們需要的運算量，真的會實現呢？

Isn't it inevitable that we're going to at some point overdo it, but

我們總有一天會不會做得太多了，但

we're not going to know that until it's too late.

Once you lay it down, it stays fairly useful for a long time.

一旦建置好了，它就能維持相當長一段時間的實用性。

The way computers work is you build up the infrastructure, but

電腦的運作方式是，你先建好基礎設施，

then you start replacing it five, six, seven years later.

然後在五年、六年、七年後開始替換它。

And so I think it's going to take us some seven years, eight years to build up to the level that we have to sustain.

所以我認為，我們會需要大約七、八年的時間來建置到我們必須維持的等級。

And after that we're going to be refreshing and slightly growing.

在那之後，我們會進行更新和稍微的成長。

And so we've got several years of build out ahead of us.

所以我們還有好幾年的建置期。

The important thing is this, you have to go back to first principles.

重要的是這個，你必須回到基本原則。

It used to be pre recorded Excel and PowerPoint and all these tools and all the software is pre compiled.

以前都是預錄好的 Excel、PowerPoint 和所有這些軟體，全部都預先編譯好了。

The way software works now because it's contextually aware, every single time you use it, it takes into consideration the context, who you are, what you're asking about, what's happening to the world, what other information you give it, the context.

現在軟體運作的方式，因為它有情境感知能力，你每次使用它時，都會考慮到情境，像是你是誰、你在問什麼、世界上發生了什麼事、你還提供了哪些資訊，也就是情境。

And every single context is different and every single response is different.

而且每一個情境都不一樣，每一個回應也都不一樣。

So from now on, every single pixel, every single beep of a sound, every video that comes out of the computer is generated in real time.

所以從現在開始，每一個像素、每一個聲音的嗶聲、電腦輸出的每一個影片，都是即時產生的。

And that's the reason why we need computers to operate software at such a large scale going forward.

這就是為什麼我們未來需要電腦以這麼大的規模來運作軟體。

And all these tokens are what we call intelligence.

而所有這些 token，就是我們所說的人工智慧。

And for the first time we have, we're generating something of tremendous value, intelligence as numbers and these things.

這是我們第一次能夠產生極具價值的東西，也就是數字形式的智慧和這些東西。

As I mentioned earlier this last year we went through an inflection point because these tokens became profitable.

就像我之前提到的，去年我們經歷了一個轉捩點，因為這些 token 開始變得有利可圖。

所以我們只能想辦法多產生一些。

Can you blame, in some ways investors who have PTSD from the last time tech went through this revolution and evolution at the same time for seeing certain things that remind them of then and worry that they'll happen again?

某種程度上，投資人經歷過科技產業同時經歷革命和演進的創傷，看到某些相似之處時會擔心重蹈覆轍，這能怪他們嗎？

History informs us, but history doesn't repeat.

歷史能給我們啟發，但歷史不會重演。

And so you have to take into consideration what's actually happening.

所以你必須考慮實際發生的事情。

Always go back to first principles and think about what is actually happening right now.

永遠回到基本原則，思考現在到底發生了什麼。

The fundamental difference, a huge difference between now and some things that happened in the past.

現在和過去某些時期之間，有一個根本的、巨大的差異。

With the Internet, there was a ton of dark fiber.

網際網路時代，有大量的暗光纖。