【獨家中英文字幕完整版】6/14黃仁勳加州理工演講
【獨家中英文字幕完整版】6/14黃仁勳加州理工演講
source:
1. **Introduction and Acknowledgements:** - Jensen Huang expressed discomfort with self-praise and asked the audience's familiarity with NVIDIA and GPUs. - 黃仁勳表達了對自我吹捧的不適，並詢問觀眾對NVIDIA和GPU的熟悉程度。 - He acknowledged President Rosenbaum, faculty, guests, parents, and the 2024 graduating class of Caltech. - 他向羅森鮑姆校長、教職員、嘉賓、家長以及2024年加州理工學院畢業班致意。
2. **Significance of the Occasion:** - Huang highlighted the pride and joy of graduating from a prestigious institution like Caltech, emphasizing the sacrifices made by families. - 黃強調從像加州理工學院這樣的名校畢業的自豪和喜悅，並強調家庭所做出的犧牲。 - He shared personal anecdotes about parenting and the importance of gratitude towards parents. - 他分享了有關育兒的個人軼事以及對父母感恩的重要性。
3. **Career Reflections and Lessons:** - Huang shared insights from his 31-year journey with NVIDIA, including the development of CUDA and the importance of intellectual honesty. - 黃分享了他與NVIDIA 31年的旅程見解，包括CUDA的開發和知識誠信的重要性。 - He discussed the strategic pivots and setbacks that shaped NVIDIA, encouraging graduates to embrace challenges and opportunities. - 他討論了塑造NVIDIA的戰略轉變和挫折，鼓勵畢業生接受挑戰和機會。
4. **Advancements in AI and Technology:** - He emphasized the rapid advancements in AI and its transformative impact on industries, advising graduates to engage with AI and the ongoing technological revolution. - 他強調了AI的快速進步及其對各行業的變革影響，建議畢業生參與AI及正在進行的技術革命。 - Huang recounted pivotal moments in AI development, such as the success of AlexNet and the rise of deep learning, underscoring the importance of innovation. - 黃回顧了AI發展的關鍵時刻，如AlexNet的成功和深度學習的興起，強調了創新的重要性。
5. **Personal Philosophy and Advice:** - Huang shared his daily routine of prioritizing high-impact work and the value of dedication to one's craft. - 黃分享了他每天優先處理高影響力工作的日常作息以及對自己工藝的奉獻價值。 - He encouraged graduates to embrace setbacks, prioritize their lives, and pursue their passions with resilience and agility. - 他鼓勵畢業生接受挫折，優先考慮生活，並以韌性和敏捷追求他們的熱情。
### Jensen Huang’s Speech At Caltech【獨家中英文字幕完整版】6/14黃仁勳加州理工演講 - YouTube**Transcript:**(00:09) It really makes me cringe listening to all that. Thank you for that kind introduction, but I hate hearing about myself. And just as a show, well, maybe if you could just applaud. How many of you know who NVIDIA is? And how many of you know what a GPU is? Okay, good, I don't have to change my speech. Ladies and gentlemen, President Rosenbaum, esteemed faculty members, distinguished guests, proud parents, and above all, the 2024 graduating class of Caltech.(00:09) 聽到這些真的讓我很不自在。謝謝你那麼友善的介紹，但我討厭聽到有關自己的介紹。那麼，為了演出的效果，也許你們可以鼓掌。你們當中有多少人知道NVIDIA？有多少人知道GPU是什麼？好的，我不用改變我的演講了。女士們，先生們，羅森鮑姆校長，尊敬的教職員們，嘉賓們，驕傲的父母們，最重要的，2024年加州理工學院的畢業生們。(01:08) This is a really happy day for you guys. You got to look more excited. You know you're graduating from Caltech. This is the school of the great Richard Feynman, Linus Pauling, and someone who's very influential to me and our industry, Carver Mead. Yeah, this is a very big deal. Today is a day of immense pride and joy.(01:08) 這對你們來說是個非常高興的日子。你們應該看起來更興奮。你們知道你們即將從加州理工學院畢業。這是偉大的理查德·費曼、萊納斯·鮑林以及對我和我們行業非常有影響力的人卡弗·米德的學校。是的，這是非常重要的事情。今天是充滿巨大驕傲和喜悅的一天。(01:36) It is a dream come true for all of you, but not just for you because your parents and families have made countless sacrifices to see you reach this milestone. So let's take this moment and congratulate them, thank them, and let them know you love them. You don't want to forget that because you don't know how long you're going to be living at home.(01:36) 這是你們所有人的夢想成真，但不僅僅是你們，因為你們的父母和家庭為了看到你們達到這個里程碑做出了無數的犧牲。所以讓我們此刻祝賀他們，感謝他們，讓他們知道你愛他們。你不想忘記這一點，因為你不知道你會在家住多久。(02:14) You want to be super grateful today. As a proud parent, I really loved it when my kids didn't move out, and it was great to see them every day, but now they've moved out, it makes me sad. So hopefully you guys get to spend some time with your parents. Your journey here is a testament of your character, determination, willingness to make sacrifices for your dreams, and you should be proud.(02:14) 今天你要非常感恩。作為一個驕傲的父母，我真的很喜歡我的孩子們不搬出去的時候，每天看到他們真的很好，但現在他們搬出去了，這讓我很難過。所以希望你們能花些時間與父母在一起。你們的旅程是你們性格、決心、願意為夢想做出犧牲的證明，你們應該感到驕傲。(02:42) The ability to make sacrifices, endure pain and suffering, you will need these qualities in life. You and I share some things in common. First, both chief scientists of NVIDIA were from Caltech. And one of the reasons why I'm giving this speech today is because I'm recruiting. And so I want to tell you that NVIDIA is a really great company, I'm a very nice boss, universally loved, come work at NVIDIA.(02:42) 能夠做出犧牲，忍受痛苦和磨難，這些品質在生活中是必須的。你和我有一些共同點。首先，NVIDIA的兩位首席科學家都來自加州理工學院。而我今天發表這個演講的原因之一是因為我在招聘。所以我要告訴你，NVIDIA是一家非常好的公司，我是一個非常好的老闆，廣受愛戴，來NVIDIA工作吧。(03:30) You and I share a passion for science and engineering, and although we're separated by about 40 years, we are both at the peaks of our career. For all of you who have been paying attention to NVIDIA and myself, you know what I mean. It's just that in your case, you'll have many, many more peaks to go.(03:30) 你和我對科學和工程有共同的熱情，雖然我們相差大約40年，但我們都處於職業生涯的巔峰。對於那些一直關注NVIDIA和我的人來說，你知道我的意思。只是對你們來說，你們將有許多更多的巔峰要達到。(03:59) I just hope that today is not my peak. Not the peak. And so I'm working as hard as ever to make sure that I have many, many more peaks ahead. Last year, I was honored to give the commencement address at Taiwan University, and I shared several stories about NVIDIA's journey and the lessons that we learned that might be valuable for graduates.(03:59) 我只希望今天不是我的巔峰。不是那個巔峰。所以我正在像往常一樣努力工作，以確保我還有許多許多的巔峰。去年，我很榮幸在台灣大學發表畢業演講，我分享了幾個關於NVIDIA旅程的故事以及我們學到的對畢業生可能有價值的教訓。(04:24) I have to admit that I don't love giving advice, especially to other people's children. And so my advice today will largely be disguised in some stories that I've enjoyed, and some life experiences that I've enjoyed. I'm the longest running tech CEO in the world today, I believe. Over the course of 31 years, I managed not to go out of business, not get bored, and not get fired.(04:24) 我必須承認，我不喜歡給建議，特別是給別人的孩子。所以我今天的建議將主要隱藏在一些我喜歡的故事和一些我享受的生活經歷中。我相信，我是今天全球任期最長的科技公司CEO。在31年的過程中，我設法沒有倒閉，沒有感到無聊，也沒有被解雇。(05:09) And so I have the great privilege of enjoying a lot of life's experiences, starting from creating NVIDIA, from nothing to what it is today. And so I spoke about the long road of creating CUDA, a programming model. The programming model that we dedicated over 20 years to invent, and that is revolutionizing computing today.(05:09) 所以我有幸享受了很多生活經歷，從創建NVIDIA，從無到今天的樣子。所以我談到了創建CUDA的漫長道路，一個編程模型。我們花了20多年時間發明的編程模型，正在革新計算技術。(05:35) I spoke about a very, quite public, canceled Sega game console project we worked on, and where intellectual honesty, something that I know Richard Feynman cares very deeply about and spoke quite often about, where intellectual honesty and humility saved our company. And how a retreat, a strategic retreat, was one of our best strategies.(05:35) 我談到了一個非常公開的，取消的Sega遊戲機項目，這個項目中，知識誠信，這是我知道理查德·費曼非常關心和經常談論的東西，知識誠信和謙遜拯救了我們的公司。以及如何撤退，一個戰略撤退，是我們最好的策略之一。(06:02) All of these are counterintuitive lessons that I spoke about at the commencement. But I encouraged the graduates to engage with AI, the most consequential technology of our time. And I'll speak a little bit more about that later, but all of you know about AI. It's hard not to be immersed in it and surrounded by it, and a great deal of discussion about it.(06:02) 這些都是我在畢業典禮上談到的反直覺教訓。但我鼓勵畢業生參與AI，這是我們時代最具影響力的技術。我稍後會再多談一點，但你們都知道AI。很難不沉浸其中並被其包圍，並且有很多關於它的討論。(06:29) And of course, I hope that all of you are using it and playing with it, with surprising results and some magical, some disappointing, and some surprising. But you have to enjoy it, you have to engage it, because it's advancing so quickly. It is the only technology that I've known that is advancing on multiple exponentials at the same time.(06:29) 當然，我希望你們都在使用它並玩弄它，有驚人的結果，有些神奇，有些失望，有些驚喜。但你必須享受它，你必須參與其中，因為它進步得非常快。這是我所知唯一一項同時在多個指數上進步的技術。(06:52) And so the technology is changing very, very quickly. So I advised the students at the Taiwan University to run, don't walk, and engage the AI revolution. And yet, one year later, it's incredible how much it's changed. And so today, what I wanted to do is share with you my perspective, from my vantage point, of some of the important things that are happening that you're graduating into.(06:52) 所以技術變化非常非常快。所以我建議台灣大學的學生快跑，不要走路，參與AI革命。然而，一年後，它的變化令人難以置信。所以今天，我想與你們分享我的觀點，從我的角度來看，一些正在發生的重要事情，你們即將畢業進入的。(07:24) And these are extraordinary things that are happening that you should have an intuitive understanding for, because it's going to matter to you, it's going to matter to the industry. And hopefully, you take advantage of the opportunity ahead of you. The computer industry is transforming from its foundations, literally from studs.(07:24) 這些正在發生的非凡事情，你們應該有直觀的理解，因為這對你們很重要，對行業也很重要。希望你們能利用眼前的機會。計算機行業正在從根基上轉變，字面上從基本構件開始。(07:46) Everything is changing from studs on up. And across every layer, and soon, every industry will also be transformed. And the reason for that is quite obvious, because computers today are the single most important instrument of knowledge. And it's foundational to every single industry and every field of science.(07:46) 一切都在從基本構件開始改變。跨越每一層，不久之後，每個行業也將被改變。這個原因非常明顯，因為今天的計算機是唯一最重要的知識工具。它是每一個行業和每一個科學領域的基礎。(08:05) If we are transforming the computer so profoundly, it will, of course, have implications in every industry. And I'll talk about that in just a little bit. And as you enter industry, it's important you know what's happening. Modern computing traces back to the IBM System 360. That was the architecture manual that I learned from.(08:05) 如果我們這樣深刻地改變計算機，它當然會對每個行業產生影響。我稍後會談到這一點。當你們進入行業時，了解正在發生的事情是很重要的。現代計算可以追溯到IBM System 360。那是我學習的架構手冊。(08:27) It's an architecture manual that you don't need to learn from. A lot better documentation and better descriptions of computers and architecture have been presented since. But the System 360 was incredibly important at its time, and in fact, the basic ideas of the System 360, the architecture of it, the principal ideas and architecture and strategy of the System 360 are still governing the computer industry today.(08:27) 這是一本你不需要學習的架構手冊。自那以來，有很多更好的文檔和更好的計算機和架構描述。但System 360在當時是非常重要的，事實上，System 360的基本理念，其架構，其主要思想和架構及策略，仍然在今天統治著計算機行業。(09:01) And it was introduced a year after my birth. In the 80s, I was among the first generation of VLSI engineers who learned to design chips from Mead and Conway's landmark textbook. And I'm not sure if it's still being taught here. It should be in the introduction of VLSI systems. Based on Carver Mead's pioneering work here at Caltech on chip design methodologies and textbook that revolutionized IC design.(09:01) 它是在我出生後一年推出的。在80年代，我是第一代VLSI工程師之一，從米德和康威的里程碑式教科書中學習設計芯片。我不確定這裡是否仍在教授這門課。它應該在VLSI系統介紹中。基於卡弗·米德在加州理工學院開創性的芯片設計方法和教科書，徹底改變了集成電路設計。(09:32) And it enabled our generation to design supergiant chips and ultimately the CPU. The CPU led to exponential growth in computing. The performance, the incredible technology advances, that's called Moore's Law, fueled the information technology revolution. The industrial revolution that we are part of, that my generation was part of, saw the mass production of something the world had never seen before.(09:32) 它使我們這一代能夠設計超大型芯片，最終設計出CPU。CPU導致計算的指數增長。性能，令人難以置信的技術進步，這被稱為摩爾定律，推動了信息技術革命。我們所屬的工業革命，我們這一代所屬的，見證了世界前所未見的某種事物的大規模生產。(10:03) The mass production of something that was invisible, easy to copy, the mass production of software. And it led to a $3 trillion industry. When I sat where you sat, the IT industry was minuscule. And the concept that you could make money selling software was a fantasy. And yet today, it's one of the most important commodities, most important technologies and product creations that our industry produces.(10:03) 大規模生產的是看不見的，易於複製的東西，軟件的大規模生產。它導致了一個3萬億美元的行業。當我坐在你們現在坐的位置時，IT行業是微不足道的。而你能通過賣軟件賺錢的概念是一種幻想。然而今天，它是我們行業產生的最重要的商品之一，最重要的技術和產品創造之一。(10:36) However, the limits of the NARD scaling, of transistor scaling, and instruction level parallelism have slowed CPU performance. And the slowed CPU performance gains is happening at a time when computing demand continues to grow exponentially. This exponentially growing gap between demand of computing and the capabilities of computers, if not addressed, computing energy consumption and cost, inflation, would eventually stifle every industry.(10:36) 然而，NARD縮放、晶體管縮放和指令級並行性的限制已經減慢了CPU性能。而CPU性能增長減慢正發生在計算需求繼續指數增長的時期。如果不解決這個計算需求和計算機能力之間指數增長的差距，計算能耗和成本，通貨膨脹，最終將會抑制每個行業。(11:15) We see very clear signs of computing inflation as we speak. And after two decades of advancing NVIDIA's CUDA, NVIDIA's accelerated computing offers a path forward. That's the reason why I'm here. Because finally, the industry realized of the incredible effectiveness of accelerated computing at precisely the time that we're witnessing computing inflation after several decades.(11:15) 當我們說話時，我們看到計算通貨膨脹的非常明顯的跡象。經過二十年推進NVIDIA的CUDA，NVIDIA的加速計算提供了一條前進的道路。這就是我在這裡的原因。因為最終，行業意識到加速計算的驚人效能，正值我們目睹數十年來計算通貨膨脹的時候。(11:46) By offloading time-consuming algorithms to a GPU that specializes in parallel processing, we routinely achieve 10, 100, sometimes 1,000-fold speedups, saving money, cost, and energy. We now accelerate application domains from computer graphics, ray tracing, of course, to gene sequencing, scientific computing, astronomy, quantum circuit simulations, SQL data processing, and even pandas, data science.(11:46) 通過將耗時的算法卸載到專門進行並行處理的GPU，我們經常實現10倍，100倍，有時1000倍的速度提升，節省金錢，成本和能量。我們現在加速的應用領域從計算機圖形學，光線追蹤，當然，還有基因測序，科學計算，天文學，量子電路模擬，SQL數據處理，甚至熊貓數據科學。(12:18) Accelerated computing has reached a tipping point. That is our first great contribution to the computer industry, our first great contribution to society, accelerated computing. It now gives us a path forward for sustainable computing where cost will continue to decline as computing requirement continues to grow.(12:18) 加速計算已經達到了一個臨界點。這是我們對計算機行業的第一大貢獻，我們對社會的第一大貢獻，加速計算。它現在為我們提供了一條可持續計算的道路，隨著計算需求的增長，成本將繼續下降。(12:41) A hundred-fold, a hundred-fold of anything in time or cost or energy savings that accelerated computing opened surely would trigger a new development somewhere else. We just didn't know what it was until deep learning came to our consciousness. A whole new world of computing emerged. Jeff Hinton, Alex Krzyzewski, and Ilya Sutskever used NVIDIA CUDA GPUs to train AlexNet and shocked the computer vision community by winning the 2012 ImageNet Challenge.(12:41) 任何時間或成本或能量節省的100倍，100倍，加速計算開啟的，肯定會在其他地方引發新的發展。我們只是不知道它是什麼，直到深度學習進入我們的意識。一個全新的計算世界出現了。傑夫·辛頓，亞歷克斯·克里澤夫斯基和伊利亞·蘇茨克弗使用NVIDIA CUDA GPU訓練AlexNet，並通過贏得2012年ImageNet挑戰賽震驚了計算機視覺社區。(13:22) This was the big moment, the big bang of deep learning, a pivotal moment that marked the beginning of the AI revolution. Our decisions after AlexNet transformed our company is something that's worth taking note of. Our decisions after AlexNet transformed our company and likely everything else. We saw the potential of deep learning and believed, just believed through principle thinking, believed through our own analysis of the scalability of deep learning.(13:22) 這是大時刻，深度學習的大爆炸，一個標誌著AI革命開始的關鍵時刻。我們在AlexNet之後的決定改變了我們的公司，這是值得注意的。我們在AlexNet之後的決定改變了我們的公司，可能改變了一切。我們看到了深度學習的潛力，並通過原則思考，相信通過我們自己對深度學習可擴展性的分析，相信這一點。(14:00) We believed the approach could learn other valuable functions. That maybe deep learning is a universal function learner and how many problems are difficult or impossible to express using fundamental first principles. And so when we saw this, when we saw this, we thought this is a technology we really have to pay attention to because its limits are potentially only limited by model and data scale.(14:00) 我們相信這種方法可以學習其他有價值的功能。也許深度學習是一個通用的功能學習器，許多問題很難或不可能用基本的第一原理來表達。所以當我們看到這一點時，我們認為這是一個我們必須真正關注的技術，因為它的限制可能僅僅受到模型和數據規模的限制。(14:30) However, there were challenges at the time. This is 2012, shortly after 2012. How could we explore the limits of deep learning without having to build these massive GPU clusters? At the time we were a rather small company, building these massive GPU clusters could cost hundreds and hundreds of millions of dollars.(14:30) 然而，當時有挑戰。這是2012年，不久之後。如何在不建造這些巨大的GPU集群的情況下探索深度學習的極限？當時我們是一家相當小的公司，建造這些巨大的GPU集群可能花費數億美元。(14:49) And if we didn't though, there was no assurance that it would be effective if we scaled. However, no one knew how far deep learning could scale. And if we didn't build it, we'd never know. This is one of those, if you build it, will they come? Our logic is if we don't build it, they can't come.(14:49) 如果我們不這樣做，則無法保證擴展後會有效。然而，沒有人知道深度學習能擴展到多遠。如果我們不建造它，我們永遠不會知道。這就是其中之一，如果你建造它，他們會來嗎？我們的邏輯是如果我們不建造它，他們就不能來。(15:11) And so we dedicated ourselves based on our first principled beliefs and our analysis. And we got ourselves to the point where we believed this was going to be so effective and when the company believes something, we should go act on it. So we dove deep into deep learning, and over the next decade, systematically reinvented everything.(15:11) 所以我們基於我們的第一原則信念和我們的分析，專注於此。我們達到了我們相信這將是如此有效的地步，當公司相信某事時，我們應該採取行動。所以我們深入研究深度學習，在接下來的十年中，系統地重新發明了一切。(15:31) We reinvented every computing layer, starting with the GPU itself. The invention of the modern GPU, which is very different than the GPU of the past that we invented in the first place, and we went on to invent just about every other aspect of computing, the interconnects, the systems, the networking, and of course, software.(15:31) 我們重新發明了每一個計算層，從GPU本身開始。現代GPU的發明，這與我們最初發明的過去的GPU非常不同，我們繼續發明了幾乎所有其他方面的計算，互連，系統，網絡，當然還有軟件。(15:54) We invested billions. We invested billions into the unknown. Thousands of engineers for a decade worked on deep learning and advancing and scaling deep learning without really knowing how far we could really take the technology. We invested billions. And we designed and built supercomputers to explore the limits of deep learning and AI.(15:54) 我們投資了數十億。我們投資了數十億到未知領域。數千名工程師十年來致力於深度學習和推進和擴展深度學習，而實際上並不知道我們能將這項技術帶到多遠。我們投資了數十億。我們設計並建造了超級計算機，以探索深度學習和AI的極限。(16:18) And in 2016, we announced DGX-1, our first AI supercomputer, and I delivered the first one to a startup in San Francisco, a startup nobody knew anything about, a group of friends of mine who were working on artificial intelligence, a company called OpenAI. In 2022, 10 years after AlexNet, and about a million-fold increase in computing later, a million-fold.(16:18) 在2016年，我們宣布了DGX-1，我們的第一台AI超級計算機，我將第一台交付給舊金山的一家初創公司，這家公司沒有人知道，一群我的朋友在從事人工智能工作，一家公司叫OpenAI。到2022年，AlexNet之後10年，計算能力增加了約一百萬倍，一百萬倍。(16:55) If you could just imagine, what would it be like if your laptop was a million-fold more capable? A million-fold later, OpenAI launched ChatGPT, and AI went mainstream. During this decade, NVIDIA transformed ourselves from a graphics company that many of you probably first knew us as, that builds GPUs, to now an AI company that builds massive data center scale supercomputers.(16:55) 如果你能想像一下，如果你的筆記本電腦的能力增加了一百萬倍會是什麼樣子？一百萬倍後，OpenAI推出了ChatGPT，AI進入主流。在這十年間，NVIDIA將自己從一家許多人最初認識我們為建造GPU的圖形公司轉變為現在的AI公司，建造大規模數據中心級別的超級計算機。(17:25) We transformed our company completely. We also transformed computing completely. The fundamental way of doing computing today has been radically changed. The computing stack now uses GPU to process large language models that are trained on supercomputers rather than CPUs that are processing instructions written by programmers.(17:25) 我們完全改變了我們的公司。我們也完全改變了計算。今天進行計算的基本方式已經徹底改變。計算堆棧現在使用GPU來處理在超級計算機上訓練的大型語言模型，而不是由程序員編寫指令的CPU。(17:52) We are now creating software that no humans can write. We are now creating software that does things that no humans can imagine, even just 10 years ago. Computers are now intention-driven rather than instruction-driven. Tell a computer what you want, and it will figure out how. And like humans, AI applications will understand the mission, reason, plan, and orchestrate a team of large language models to perform tasks.(17:52) 我們現在正在創建人類無法編寫的軟件。我們現在正在創建的軟件能夠做一些人類甚至在10年前都無法想像的事情。計算機現在是意圖驅動而不是指令驅動。告訴計算機你想要什麼，它會弄清楚怎麼做。像人類一樣，AI應用程序將理解任務，推理，計劃，並組織一個大型語言模型團隊來執行任務。(18:28) Future applications will do and perform very similar to the way we do things, assemble teams of experts, use tools, reason and plan, and execute our mission. Software and what software can do has been completely changed. Even our industry, as it's being changed and transformed, created yet another industry, an industry the world's never seen before.(18:28) 未來的應用程序將以非常類似於我們做事的方式進行和執行，組建專家團隊，使用工具，推理和計劃，並執行我們的任務。軟件及其功能已經完全改變。即使在我們的行業正在被改變和轉變的過程中，也創造了另一個前所未見的行業。(18:57) An industry is forming right in front of our eyes. AI's input and output are tokens. For all the engineers in the room, you know what I mean. These are floating-point numbers that embed intelligence. Companies are now building a new type of data center that didn't exist before that specialize in producing intelligence tokens.(18:57) 一個行業正在我們眼前形成。AI的輸入和輸出是令牌。對於在場的所有工程師，你們知道我的意思。這些是嵌入智能的浮點數。公司現在正在建造一種以前不存在的新型數據中心，專門生產智能令牌。(19:26) Essentially, AI factories. Like AC generators that Nikola Tesla invented of the past industrial revolution, we now have AI token generators, and they will be the factories of a new industrial revolution. There's large industries producing energy, electricity. We now have a large industry producing something invisible called software.(19:26) 本質上是AI工廠。像尼古拉·特斯拉在過去的工業革命中發明的交流發電機一樣，我們現在有了AI令牌生成器，它們將是新工業革命的工廠。有大型產業生產能源，電力。我們現在有一個大型產業生產看不見的東西，稱為軟件。(19:56) In the future, in the very near future, we'll have industries that are producing, manufacturing intelligence tokens, AI generators. A new computing model has emerged, and a new industry has emerged, all because we reasoned from first principles, formed our belief about the future, and we acted on them.(19:56) 在不久的將來，我們將擁有生產，製造智能令牌，AI生成器的行業。一種新的計算模型已經出現，一個新的行業已經出現，這一切都是因為我們從第一原則推理，形成了對未來的信念，並採取了行動。(20:22) The next wave of AI is robotics, where AI, in addition to a language model, also has a physical world model. We work with hundreds of companies building robots, robotic vehicles, pick-and-place arms, humanoid robots, and even entire gigantic warehouses that are robotic. But unlike our AI factory strategy and our experience there, which was really formed through reasoning and deliberate action, our robotics journey resulted from a series of setbacks.(20:22) 下一波AI是機器人，除了語言模型外，AI還擁有物理世界模型。我們與數百家公司合作，建造機器人，機器人車輛，拾放臂，人形機器人，甚至是整個巨大的機器人倉庫。但與我們的AI工廠戰略和我們在那裡的經驗不同，那是通過推理和深思熟慮的行動形成的，我們的機器人旅程來自一系列挫折。(21:01) As you know, NVIDIA invented the GPU. This was before we invented AI factories. Our first great contribution to the computer industry was reinventing computer graphics through programmable shaders. We invented the GPU and programmable shading in 2000. We wanted to integrate GPUs into every computer, and so we started to combine our GPUs with motherboard chips, and we launched a fabulous integrated graphics chip at the time for AMD CPUs.(21:01) 如你所知，NVIDIA發明了GPU。這是在我們發明AI工廠之前。我們對計算機行業的第一大貢獻是通過可編程著色器重新發明計算機圖形。我們在2000年發明了GPU和可編程著色。我們想將GPU集成到每台計算機中，所以我們開始將我們的GPU與主板芯片結合，當時我們為AMD CPU推出了一款出色的集成圖形芯片。(21:34) Our chipset business was an instant success. I think it went from zero to a billion dollars practically overnight. But then all of a sudden, AMD wanted to control all of the technology in the PC, and we wanted to stay independent, so they purchased ATI and no longer needed us. We turned to Intel. That probably wasn't a great idea, but we turned to Intel and negotiated a license to connect to Intel CPUs.(21:34) 我們的芯片業務一舉成功。我想它幾乎是一夜之間從零增長到十億美元。但突然間，AMD想控制PC中的所有技術，而我們想保持獨立，所以他們購買了ATI，不再需要我們了。我們轉向英特爾。這可能不是一個好主意，但我們轉向英特爾，談判獲得了連接英特爾CPU的許可。(22:11) Apple was excited by what we were building and asked us to work on a new computer with them, which became the first MacBook Air. Well, Intel saw what happened and decided they didn't want us to do that anymore, and so they terminated our agreement. Well, we pivoted again, and this time we went and licensed ARM, and we built a low-power SoC, a mobile SoC, the world's first SoC that was essentially a computer, a full operating computer, and it was incredible.(22:11) 蘋果對我們的產品感到興奮，並要求我們與他們合作開發一台新電腦，這成為了第一台MacBook Air。好吧，英特爾看到發生了什麼，決定他們不再想讓我們這樣做了，所以他們終止了我們的協議。好吧，我們又一次轉變，這次我們去獲得了ARM的許可，我們建造了一個低功耗SoC，一個移動SoC，世界上第一個實質上是一台計算機，一台完整的操作計算機，這真是令人難以置信。(22:52) Our chip excited Google, and they asked us to work on a new device, which turned out to have been the Android mobile device. Well, Qualcomm decided they didn't want us to do that, and so they didn't want us to connect to their modems, and it's hard to build a mobile device without being connected to a modem.(22:52) 我們的芯片讓谷歌感到興奮，他們要求我們開發一個新設備，結果這是Android移動設備。好吧，高通決定他們不想讓我們這樣做，所以他們不想讓我們連接到他們的調製解調器，而沒有連接到調製解調器很難建造移動設備。(23:14) And there were no other LTE modem companies, so we had to exit the mobile device market. Well, this happened practically on a year rhythm, and we would build something, it would be incredibly successful, generate enormous amounts of excitement, and then one year later, we were kicked out of those markets. Well, with no more markets to turn to, we decided to build something where we are sure there are no customers, because one of the things you can definitely guarantee is where there are no customers, there are also no competitors,(23:14) 而且沒有其他LTE調製解調器公司，所以我們不得不退出移動設備市場。好吧，這幾乎是每年發生的事情，我們會建造一些東西，它會非常成功，產生巨大的興奮感，然後一年後，我們被踢出這些市場。好吧，沒有更多的市場可以轉向，我們決定建造一些我們確定沒有客戶的東西，因為你可以肯定的是，沒有客戶的地方也沒有競爭對手，(24:01) and nobody cares about you. And so we chose a market with no customers, a $0 billion market, and it was robotics. We built the world's first robotics computer processing an algorithm nobody understood at the time called deep learning. This is over 10 years ago now. Ten years later, I can't be happier with what we've built and the opportunity to create the next wave of AI.(24:01) 沒有人關心你。所以我們選擇了一個沒有客戶的市場，一個價值0美元的市場，那就是機器人。我們建造了世界上第一台機器人計算機，處理當時沒有人理解的算法，稱為深度學習。這是十多年前的事了。十年後，我對我們所建造的東西和創造下一波AI的機會感到無比快樂。(24:30) More importantly, we developed agility and a culture of resilience. One setback after another, we shook it off and skated to the next opportunity. Each time, we gained skills and strengthened our character. We strengthened our corporate character. Our company is really hard to distract and really hard to discourage, and no setback that comes our way doesn't look like an opportunity these days.(24:30) 更重要的是，我們發展了敏捷性和韌性文化。一個接一個的挫折，我們擺脫它們，滑向下一個機會。每次，我們都獲得了技能並增強了我們的性格。我們加強了公司的性格。我們的公司真的很難被分心，也很難被氣餒，這些天來，沒有任何挫折看起來不像是一個機會。(25:02) Ironically, the robotics computer that we built today doesn't even need graphics, which is why our journey started in the first place. So where we are today tells us something and teaches us something. The world is uncertain, as Richard Feynman would say, and the world can be unfair and deal you with tough cards.(25:02) 諷刺的是，我們今天建造的機器人計算機甚至不需要圖形，這就是我們最初開始這段旅程的原因。所以我們今天所在的地方告訴我們一些事情，並教給我們一些事情。正如理查德·費曼所說，世界是不確定的，世界可能是不公平的，並會給你出難題。(25:26) Swiftly, shake it off. You've apparently been paying too much attention to your books. Swiftly, shake it off. Come on, that's pretty clever. I made myself laugh. There's another opportunity out there, or create one. Let me tell you one more story. I used to work from one of our international sites for one month each summer.(25:26) 快速擺脫它。你顯然花了太多時間關注你的書本。快速擺脫它。來吧，這很聰明。我自己笑了。還有另一個機會，或者創造一個。讓我再告訴你一個故事。我過去每個夏天在我們的國際站點之一工作一個月。(26:18) When our kids were in their teens, we spent a summer in Japan. For a weekend, we visited Kyoto and the Silver Temple. If you haven't had a chance to go, you must. It's renowned for its exquisite moss garden. The day we visited was quintessential Kyoto summer day, suffocatingly hot and humid, sticky.(26:18) 當我們的孩子十幾歲時，我們在日本度過了一個夏天。一個週末，我們參觀了京都和銀閣寺。如果你還沒有機會去，你必須去。它以其精美的苔蘚花園而聞名。我們參觀的那天是典型的京都夏日，悶熱潮濕，粘稠。(26:42) Heat is radiating from the ground. The air was thick, still. Along with the other tourists, we wandered through the meticulously groomed moss garden. And I noticed the lone gardener. Now, remember, the moss garden, this is the Silver Temple, the moss garden is gigantic. It's about the size of this courtyard.(26:42) 熱量從地面輻射。空氣濃稠，靜止。與其他遊客一起，我們漫步在精心修剪的苔蘚花園中。我注意到那個孤獨的園丁。現在，請記住，這是銀閣寺的苔蘚花園，這個苔蘚花園非常大。大約有這個院子的大小。(27:06) And it has the collection, the largest collection of just about apparently every species of moss in the world. And it's just exquisitely maintained. I noticed the lone gardener squatting, carefully picking at the moss with a bamboo tweezer and putting it in the bamboo basket. And you have to, it's a bamboo tweezer, you know, and it's just this one gardener.(27:06) 它擁有世界上幾乎所有苔蘚物種的最大收藏。它被精心維護。我注意到那個孤獨的園丁蹲著，用竹鑷子小心地撿苔蘚，然後放進竹籃裡。你知道，這是一個竹鑷子，只有這一個園丁。(27:43) And the basket looked empty. Well, for a moment there, I thought he was picking imaginary moss into a pile of imaginary dead moss. And so I walked up to him and I said, what are you doing? And in his English, he said, I'm picking dead moss. I'm taking care of my garden. And I said, but your garden is so big.(27:43) 籃子看起來是空的。有那麼一刻，我以為他在撿想像中的苔蘚到一堆想像中的枯萎苔蘚中。所以我走上前問他，你在做什麼？他用英語回答說，我在撿枯萎的苔蘚。我在照顧我的花園。我說，但你的花園這麼大。(28:15) And he responded, I have cared for my garden for 25 years. I have plenty of time. Well, that was one of the most profound learnings in my life. And it really taught me something. This gardener has dedicated himself to his craft and doing his life's work. And when you do that, you have plenty of time. I begin each morning, I do every single morning exactly the same way, I begin each morning by doing my highest priority work first.(28:15) 他回答說，我照顧我的花園已有25年。我有很多時間。那是我生命中最深刻的學習之一。它真的教會了我一些東西。這個園丁奉獻自己於他的工藝，做他的生命工作。當你這樣做時，你就有很多時間。我每天早晨都以同樣的方式開始，我每天早晨首先做我的最高優先工作。(28:53) I have a very clear priority list and I start from the highest priority work first. Before I even get to work, my day is already a success. I've already completed my most important work and can dedicate my day to helping others. And when people apologize for interrupting me, I always say I have plenty of time and I do.(28:53) 我有一個非常明確的優先列表，我從最高優先的工作開始。在我上班之前，我的一天已經成功了。我已經完成了我最重要的工作，可以把我的一天奉獻給幫助別人。當人們為打擾我而道歉時，我總是說我有很多時間，的確如此。(29:20) Graduates of the class of 2024, I can hardly imagine anyone more prepared for the future than you. You dedicated yourself, you worked hard, you earned a world-class education from one of the most prestigious schools in the world. And as you commence into the next stage, take my learnings and hopefully they'll help you along the way.(29:20) 2024年畢業班的畢業生們，我幾乎無法想像有誰比你們更為未來做好準備。你們奉獻自己，努力工作，從世界上最負盛名的學校之一獲得了世界級的教育。當你們開始進入下一階段時，接受我的學習，希望它們能幫助你們一路前行。(29:51) I hope you believe in something, something unconventional, something unexplored, but let it be informed and let it be reasoned. Then dedicate yourself to making it happen. You may find your GPU, you may find your CUDA, you may find your generative AI, you may find your NVIDIA. I hope you will see setbacks as new opportunities.(29:51) 我希望你們相信某些東西，某些不尋常的東西，某些未探索的東西，但讓它是知情的，讓它是有理的。然後奉獻自己去實現它。你可能會找到你的GPU，你可能會找到你的CUDA，你可能會找到你的生成AI，你可能會找到你的NVIDIA。我希望你能把挫折視為新的機會。(30:18) Your pain and suffering will strengthen your character, your resilience and agility, and they are the ultimate superpowers. Of all of the things that I value most about my abilities, intelligence is not top of that list. My ability to endure pain and suffering, my ability to work on something for a very, very long period of time, my ability to handle setbacks and see the opportunity just around the corner I consider to be my superpowers, and I hope they're yours.(30:18) 你的痛苦和磨難將增強你的性格，你的韌性和敏捷性，這些都是終極超能力。在我最看重的能力中，智力並不是排名最高的。我的能力是忍受痛苦和磨難，我能夠長時間專注於某事，我能夠處理挫折並看到就在角落裡的機會，我認為這是我的超能力，希望它們也是你的。(30:54) And I hope you find a craft. I hope you find a craft. It's not important to decide on day one, it's not even important to decide any time soon, but I hope you do find a craft, that you want to dedicate your lifetime to perfecting, to hone the skills of, and let it be your life's work. And then lastly, prioritize your life.(30:54) 我希望你能找到一門手藝。我希望你能找到一門手藝。重要的不是第一天決定，甚至不是很快決定，但我希望你能找到一門你願意用一生去完善，磨練技能的手藝，讓它成為你的生命工作。最後，優先考慮你的生活。(31:31) There's so many things going on, there's so many things to do, but prioritize your life and you will have plenty of time to do the important things. Congratulations, class of 2024, go get them.(31:31) 有這麼多事情正在發生，有這麼多事情要做，但優先考慮你的生活，你將有足夠的時間去做重要的事情。恭喜2024年畢業班，去實現它們吧。
你可能也想看
