NVIDIA CEOのJensen Huangが国立台湾大学の卒業式（2023年5月27日）で行ったスピーチ、日本語字幕付き。

Summary

NVIDIAの創設者であるスピーカーは、NTUでの卒業式で、自分のキャリアとNVIDIAの旅を振り返ります。彼は、台湾のDr. ChengがNVIDIAのCUDAを利用して自宅でスーパーコンピュータを構築した話や、1984年に卒業した当時の技術的な限界と、現在AIがもたらす無限の可能性について語ります。失敗から学び、戦略的撤退の価値を理解し、革新と持続可能な成功を追求する重要性を強調しています。AIの時代の到来とともに、新しい産業が生まれ、AIを駆使することの重要性を説きます。スピーカーは、卒業生に対し、変化を恐れず、熱意を持って新しい技術を追求するよう励ますメッセージを伝えます。

Takeaways

• 😊 NVIDIA started from humble beginnings in a Taiwanese professor's DIY supercomputer lab
• 😮 Early big failures taught NVIDIA perseverance and pivoting skills that were key to later successes
• 💡 Taking strategic retreats and giving up some opportunities paved the way for much bigger successes later
• 👨‍🏫 Mentors like Sega's CEO showed compassion that kept NVIDIA alive in tough times
• 🤝 Long-term partnerships with companies like TSMC were key to NVIDIA's rise
• ⚙️ Innovations like CUDA GPU computing and AI laid the groundwork for industry transformation
• 😎 Embracing deep learning and AI was a huge risk that paid off enormously for NVIDIA
• 🚘 Retreating from phones to bet on automotive and robotics created a new multi-billion industry
• 🔮 The AI revolution is just beginning - huge opportunities exist for fresh ideas and startups
• 🚴‍♀️ Graduates must run towards opportunities quickly and decisively to stay ahead of competition

Q & A

NTUでの訪問時、Dr. Chengが何を作成したか、そしてそれはどのようにしてNVIDIAの旅の初期例となったのか。

Dr. Chengは、NVIDIAのCUDAを利用して、ゲーム用グラフィックスカードを使用した自家製スーパーコンピューターを構築しました。これは、量子物理シミュレーションのために彼の研究に革命をもたらし、NVIDIAの旅の初期の例となりました。

1984年には、どのような技術革新がPCおよびチップ産業の始まりを告げたか。

1984年にIBM PCATとApple Macintoshが発売され、PC革命を起こし、今日私たちが知るチップおよびソフトウェア産業の始まりとなりました。

AIがどのようにして毎日の仕事を変革しているかの具体例を挙げてください。

AIは、自動車の自動運転やX線画像の研究など、多くの業界でタスクの自動化を可能にしました。これにより、データエンジニアリング、プロンプトエンジニアリング、AIファクトリー運用、AI安全エンジニアなど、以前には存在しなかった新しい職業が生まれました。

NVIDIAの初期の失敗とその後の成功について説明してください。

NVIDIAは、3Dグラフィックスにおける新しいアプローチである前方テクスチャマッピングと曲線を開発しましたが、この戦略が間違っていたことに気付きました。しかし、Segaとの契約解除とRiva 128の開発により、会社は市場に衝撃を与え、存続することができました。

CUDAがGPU加速コンピューティングの普及にどのように貢献したか。

CUDAは新しいプログラミングモデルを作り、科学計算、物理シミュレーションから画像処理まで、さまざまなアプリケーションの加速を可能にしました。これは、既存の大規模なゲーマー市場を活用してCUDAの導入を加速し、最終的にはAI研究者によって発見されたことで、AI革命の火付け役となりました。

NVIDIAがモバイルチップ市場から撤退した理由とその結果は何でしたか。

NVIDIAはモバイルチップ市場から撤退する戦略的決定を下しました。これにより、会社はロボティクス市場へと方向転換し、自動車およびロボティクス事業で数十億ドル規模の新たな産業を創出することに成功しました。

NVIDIAの創設者は、過去の失敗からどのような教訓を得ましたか。

NVIDIAの創設者は、失敗を認め、謙虚に助けを求めることの重要性を学びました。これらの特性は、最も明るく成功した人々にとって最も難しいことですが、NVIDIAを救うのに役立ちました。

NVIDIAがAIと加速コンピューティングにおいてどのように業界をリードしているか。

NVIDIAはCUDAの開発とGPU加速コンピューティングの先駆者として、AI革命の中心となりました。ディープラーニングの可能性を早期に理解し、企業全体をこの新たな分野の進展に捧げました。

NVIDIAの成功が台湾の企業にとってどのような意味を持つか。

NVIDIAの成功は、台湾がコンピュータ産業の基礎であり、次の10年間で世界の従来のコンピュータを新しい加速AIコンピュータに置き換える機会があることを示しています。

将来の卒業生に対するメッセージとは何か。

卒業生はAIの時代の始まりに立っており、すべての産業が新しいアイデア、彼らのアイデアによって革命を遂げる準備ができています。彼らには、情熱を持って追求し、AIと共に素晴らしいことを成し遂げる機会があります。

Outlines

00:00

🔬NTU訪問とAIの黎明

NVIDIAの創始者が台湾国立大学（NTU）での初訪問を回想し、Dr. Chengの自作スーパーコンピュータの話から始める。このエピソードは、NVIDIAのCUDA技術がどのように科学研究に革命をもたらしたか、そしてそれが自身の人生の仕事を実現するのにどう貢献したかを示している。彼は1984年の自身の大学卒業時と現在の技術革新の速度、特にAIの進化を比較し、学生たちに対し、これらの技術変革が新たな産業を生み、新しい仕事を創出するが、一方で既存の仕事を無くすこともあると警告する。彼はAIの時代の到来を強調し、学生たちにAIを学び、活用することの重要性を説く。

05:07

🔄NVIDIAの挑戦と進化

NVIDIAの創業期からの3つの重要な物語を通じて、企業が直面した困難、失敗、そしてそれらを乗り越えた方法を紹介する。最初の話は、セガとの契約を解消し、Riva 128の開発に成功したことで会社を救った経緯を述べる。次に、CUDAとGPU加速コンピューティングの推進による苦難の年々と、それがどのようにして最終的にAIの大爆発を引き起こしたかを説明する。最後に、モバイルチップ市場からの撤退と、その決断が自動運転車やロボティクスといった新しい分野への道を開いた話をする。これらの物語は、失敗から学び、柔軟に戦略を変えることの重要性を強調している。

10:15

🌐AI革命とNVIDIAの未来

NVIDIAがCUDAとGPU加速コンピューティングを開発し、推進してきた経緯と、これがどのようにしてAIの発展に貢献したかを説明する。2007年のCUDAの発表から、科学計算、画像処理、そして最終的には深層学習とAI研究に至るまで、NVIDIAが直面した挑戦と、それを乗り越えた方法に焦点を当てる。CUDAが開発者コミュニティに受け入れられ、AI研究に不可欠なツールとなった過程は、持続可能なイノベーションのモデルを示している。加えて、会社の戦略的撤退と新たな分野への転換は、将来的な成功への鍵であることを示す。

15:20

🚀AI時代の到来と影響

NVIDIAの創設者は、AIがもたらす新しい時代の重要性と、これが世界のあらゆる産業に革命をもたらすことを強調する。彼は学生たちに対し、AIと共に走り、新たな技術革新の波に乗るよう励ます。AIが創出する新しい仕事や、AIを活用することで変化する既存の職業についても触れ、技術の進化が個人と社会にどのような影響を与えるかを考察する。最後に、自身の経験とNVIDIAの歴史を通じて、失敗から学び、イノベーションを追求し続けることの重要性を学生たちに伝える。

Keywords

💡NVIDIA

NVIDIA is the company that Huang founded and runs. It pioneered graphics processing units (GPUs) for gaming and later for artificial intelligence. The transcript traces NVIDIA's origin story and how it overcame failures.

💡CUDA

CUDA is NVIDIA's parallel computing platform that allows developers to use the computing power of GPUs. It was key to popularizing GPU-accelerated computing.

💡artificial intelligence

Artificial intelligence, especially deep learning, is presented as the latest computing revolution that will transform every industry. NVIDIA focused on AI early and is now a leader.

💡Sega

Sega contracted NVIDIA to build a graphics chip for its game console. When NVIDIA's technology failed, Sega's CEO generously paid them anyway, saving the company.

💡phone market

NVIDIA entered the phone chip market but later strategically retreated from it to focus on inventing a new computer for robotics and AI.

💡Taiwan

Huang emphasizes Taiwan's foundational role in building the computer industry, from his early partnership with Morris Chang of TSMC to speaking at NTU.

💡entrepreneur

Huang encourages entrepreneurs to start companies to take advantage of the rise of AI, just as new companies drove progress in past computing eras.

💡automation

AI and automation will obsolete some jobs but also create new and enhanced jobs, requiring adapting skills.

💡sacrifice

Huang argues that strategic sacrifice and retreat from less promising opportunities paved the way for NVIDIA's success in AI.

💡computing revolution

Huang puts AI at the crest of the 5th great computing revolution, predicting immense technological and business transformations.

Highlights

Dr. Cheng had built a homemade supercomputer, the Taiwanese way, out of gaming graphics cards.

Automated tasks will obsolete some jobs. And for sure, AI will change every job, supercharging the performance of programmers, designers, artists, marketers, and manufacturing planners.

We invented an unconventional 3D approach called forward texture mapping and curves. Our approach was substantially lower cost.

Confronting our mistake and with humility asking for help, save NVIDIA. These traits are the hardest for the brightest and most successful, like yourself.

Creating a new computing model is incredibly hard and rarely done in history.

Then in 2012, AI researchers discovered CUDA. The famous AlexNet trained on GeForce GTX 580 started the big bang of AI.

We believed the time for accelerated computing would come. We created a conference called GTC and promoted CUDA tirelessly worldwide.

To retreat from a giant phone market to create a zero billion dollar robotics market.

Strategic retreat, sacrifice, deciding what to give up is at the core, the very core of success.

Every industry will be revolutionized, reborn, ready for new ideas, your ideas.

In 40 years, we created the PC, Internet, mobile, cloud, and now the AI era. What will you create?

Remember, either you're running for food or you are running from being food.

1984 was a perfect year to graduate. I predict that 2023 will be as well.

At NVIDIA, I experienced failures, great big ones, all humiliating and embarrassing. Many, nearly doomed us.

Fortunately, we realized the potential of deep learning as a whole new software approach and turned every aspect of our company to advance this new field.

Transcripts

I came to NTU for the first time over a decade ago. Dr. Cheng invited me to visit his computational

physics lab. As I recall, his son, based in Silicon Valley, had learned of NVIDIA's

CUDA invention and recommended his father utilize it for his quantum physics simulations.

When I arrived, he opened the door to show me what he had made. NVIDIA GeForce gaming

cards filled the room, plugged into open PC motherboards, and sitting on metal shelves

in the aisles were oscillating Datong fans. Dr. Cheng had built a homemade supercomputer,

the Taiwanese way, out of gaming graphics cards. He started an early example of NVIDIA's

journey. He was so proud that he said to me, Mr. Huang, because of your work, I can do

my life's work in my lifetime. Those words touched me today. I was so proud of him.

I am so happy to be back at NTU and to be your commencement address. The world was simpler

when I graduated from Oregon State University. TVs were not flat yet. There was no cable

television and MTV. The words mobile and phone didn't go together. The year was 1984. The

IBM PCAT and Apple Macintosh launched the PC revolution and started the chip and software

industry that we know today. You enter a far more complex world with geopolitical, social,

and environmental changes and challenges. Surrounded by technology, we are now perpetually

connected and immersed in a digital world that parallels our real world. Cars are starting

to drive by themselves. Forty years after the computer industry created the home PC,

we invented artificial intelligence. Like software that automatically drives a car or

studies x-ray images, AI software has opened the door for computers to automate tasks for

the world's largest multi-trillion dollars of industries. Healthcare, financial services,

transportation, and manufacturing. AI has opened immense opportunities. Agile companies

will take advantage of AI and boost their position. Companies less so will perish. Entrepreneurs,

many of them here today, will start new companies and like in every computing era before, create

new industries. AI will create new jobs that didn't exist before, like data engineering,

prompt engineering, AI factory operations, and AI safety engineers. These are jobs that

never existed before. Automated tasks will obsolete some jobs. And for sure, AI will

change every job, supercharging the performance of programmers, designers, artists, marketers,

and manufacturing planners. Just as every generation before you embraced technologies

to succeed, every company and you must learn to take advantage of AI and do amazing things

with an AI copilot by your side. While some worry that AI may take their jobs, someone

who expert with AI will. We are at the beginning of a major technology era, like PC, internet,

mobile, and cloud. But AI is far more fundamental, because every computing layer has been reinvented.

From how we write software to how it's processed, AI has reinvented computing from the ground

up. In every way, this is a rebirth of the computer industry and a golden opportunity

for the companies of Taiwan. You are the foundation and bedrock of the computer industry. Within

the next decade, our industry will replace over a trillion dollars of the world's traditional

computers with new, accelerated AI computers. My journey started 40 years before yours.

1984 was a perfect year to graduate. I predict that 2023 will be as well. What can I tell

you as you begin your journey? Today is the most successful day of your life so far. You're

graduating from the National Taiwan University. I was also successful until I started NVIDIA.

At NVIDIA, I experienced failures, great big ones, all humiliating and embarrassing. Many

nearly doomed us. Let me tell you three NVIDIA stories that define us today. We founded NVIDIA

to create accelerated computing. Our first application was 3D graphics for PC gaming.

We invented an unconventional 3D approach called forward texture mapping and curves.

Our approach was substantially lower cost. We won a contract with Sega to build their

game console, which attracted games for our platform and funded our company. After one

year of development, we realized our architecture was the wrong strategy. It was technically

poor. And Microsoft was about to announce Windows 95 Direct 3D based on inverse texture

mapping and triangles. Many companies were already working on 3D chips to support this

standard. If we completed Sega's game console, we would have built inferior technology, be

incompatible with Windows, and be too far behind to catch up. But we would be out of

money if we didn't finish the contract. Either way, we would be out of business. I contacted

the CEO of Sega and explained that our invention was the wrong approach, that Sega should find

another partner, and that we could not complete the contract and the console. We had to stop.

But I needed Sega to pay us in whole, or NVIDIA would be out of business. I was embarrassed

to ask. Irimajiri-san, the CEO of Sega, to his credit and my amazement, agreed. His understanding

and generosity gave us six months to live. With that, we built Riva 128, just as we were

running out of money. Riva 128 shocked the young 3D market, put us on the map, and saved

the company. The strong demand for our chip led me back to Taiwan after leaving at the

age of four to meet Morris Chang at TSMC and started a partnership that has lasted 25 years.

Confronting our mistake and with humility asking for help, save NVIDIA. These traits

are the hardest for the brightest and most successful, like yourself. In 2007, we announced

CUDA GPU accelerated computing. Our aspiration was for CUDA to become a programming model

that boosts applications from scientific computing and physics simulations to image processing.

Creating a new computing model is incredibly hard and rarely done in history. The CPU computing

model has been the standard for 60 years since the IBM System 360. CUDA needed developers

to write applications and demonstrate the benefits of the GPU. Developers needed a large

installed base. And a large CUDA installed base needed customers buying new applications.

So to solve the chicken or the egg problem, we used GeForce, our gaming GPU, which already

had a large market of gamers, to build the installed base. But the added cost of CUDA

was very high. NVIDIA's profits took a huge hit for many years. Our market cap hovered

just below, just above $1 billion. We suffered many years of poor performance. Our shareholders

were skeptical of CUDA and preferred we focused on improving profitability. But we persevered.

We believed the time for accelerated computing would come. We created a conference called

GTC and promoted CUDA tirelessly worldwide. Then the applications came. Seismic processing,

CT reconstruction, molecular dynamics, particle physics, fluid dynamics, and image processing.

One science domain after another they came. We worked with each developer to write their

algorithms and achieved incredible speedups. Then in 2012, AI researchers discovered CUDA.

The famous AlexNet trained on GeForce GTX 580 started the big bang of AI. Fortunately,

we realized the potential of deep learning as a whole new software approach and turned

every aspect of our company to advance this new field. We risked everything to pursue

deep learning. A decade later, the AI revolution started. And NVIDIA is the engine of AI developers

worldwide. We invented CUDA and pioneered accelerated computing and AI. But the journey

forged our corporate character to endure the pain and suffering that is always needed to

realize a vision. One more story. In 2010, Google aimed to develop Android into a mobile

computer with excellent graphics. The phone industry had chip companies with modem expertise.

NVIDIA's computing and graphics expertise made us an ideal partner to help build Android.

So we entered the mobile chip market. We were instantly successful and our business and

stock price surged. The competition quickly swarmed. Modem chip makers were learning how

to build computing chips and we were learning how to build modems. The phone market is huge.

We could fight for share. Instead, we made a hard decision and sacrificed the market.

NVIDIA's mission is to build computers to solve problems that ordinary computers cannot.

We should dedicate ourselves to realizing our vision and to making a unique contribution.

Our strategic retreat paid off. By leaving the phone market, we opened our minds to invent

a new one. We imagined creating a new type of computer for robotic computers with neural

network processor, safety architectures that run AI algorithms. At the time, this was a

zero billion dollar market. To retreat from a giant phone market to create a zero billion

dollar robotics market. We now have billions of dollars of automotive and robotics business

and started a new industry. Retreat does not come easily to the brightest and most successful

people like yourself. Yet, strategic retreat, sacrifice, deciding what to give up is at

the core, the very core of success. Class of 2023, you're about to go into a world

witnessing great change. And just as I was with the PC and chip revolution, you're at

the beginning, at the starting line of AI. Every industry will be revolutionized, reborn,

ready for new ideas, your ideas. In 40 years, we created the PC, Internet, mobile, cloud,

and now the AI era. What will you create? Whatever it is, run after it like we did.

Run, don't walk. Remember, either you're running for food or you are running from being

food.