Name: AI教父黃仁勳：Nvidia最大貢獻係將CPU、GPU成本降低100萬倍｜人工智能雖不是由第一原理推演答案 但可模擬人類生物學 香港科技大學可建設世界第一間AI醫院｜HKUST｜美股投資｜CC字幕
Uploaded: 2024-12-01T04:54:05.000Z
Duration: 27 min 19 s
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Imagine if there's something in the world that you rely on.

We reduced it in the last 10 years by 1 million times.

Well, when something happens, when the cost of something reduces by a million times, your habits fundamentally change.

How you think about computing fundamentally changed.

That is the single greatest contribution NVIDIA ever made.

Some of our professors here may slightly disagree because you still need a lot of money to buy your GPUs.

I gave you a million times discount in the last 10 years.

Ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha.

Jensen, it's just so nice to have you here at HKUST and in Hong Kong.

Let me just say, can we just please show how much we love Jensen?

Jensen, you know, I have been preparing for this moment.

I thought it's definitely a highlight of my HKUST career, for sure.

I just couldn't sleep last night for one very important reason.

Because I am going to introduce you as the number one CEO in this universe.

Maybe entire universe, at least in this universe.

This company, Apple's stock was going up last night.

And yours wasn't doing that particularly well.

And I couldn't wait until the market was closed.

I asked my wife, I said, did Nvidia hang on there?

So we have less than an hour this afternoon.

I'm just diving, Jensen, with some tough questions for you.

So you have been leading this technology field, AI field, for a long period of time.

Just for the sake of our audience, just tell us how you think about AI, more specifically, recently, artificial general intelligence, the impact AI is having and will have for all the society and the industry.

Thank you for the opportunity to spend time with you.

Harry is one of the most consequential computer scientists of our time.

And he's been a hero of mine and many others around the world for a very long time.

Harry, as you know, the transformative, the groundbreaking capability happened when an artificial intelligence network can learn to understand data of all kinds.

Of course, language, and images, and sequences of proteins, and sequences of amino acids, and sequences of chemicals.

And all of a sudden, we now have computers that can understand the meaning of words and such.

And because of generative AI, we can translate from one modality of information to another modality of information.

For example, from text to images, from text to text, from protein to text, from text to protein, from text to chemicals.

This universal, initially a universal function approximator, evolved into a universal language translator of every kind.

And so the question then is, what can we do with that?

And you see the number of startups around the world and a number of capabilities with the combination of all these different modalities and capabilities.

And so I think the really amazing breakthrough is that we can now understand the meaning of information.

And so what does that mean to you if you are a digital biologist, so that you can understand the meaning of the data you're looking at, so that you could find a needle in a haystack?

What does that mean if you are, in the case of NVIDIA, a chip designer, system designer?

What does that mean to you if you're an ag tech, or climate science, or climate tech, or energy looking for a new material?

So this is really the groundbreaking thing, is that we now have the concept of a universal translator.

Yeah, Jensen, in May, we were at a Microsoft CEO summit.

So many of us listened to your really description about the amazing impacts of AI on the society.

I thought that what you said really resonated with me.

So you kind of took us back to the entire history of a human being.

You said, well, there's this agricultural revolution, so we actually manufacture more food.

Then we have industrial revolution, we actually manufacture more iron steels.

Then we have information technology, we actually have more information.

Now, in this intelligence, this era, so what you are doing at NVIDIA, what AI is doing is actually manufacturing intelligence.

Can you elaborate a little bit more on why this thing is just so enormously important?

Yeah, when you look at what we've done together, Harry, and you were in the middle of all of this, from the perspective of computer science, we've reinvented the whole stack.

Meaning, the way we used to develop software, and when you think about computer science, you have to think about software development, how software is done.

And so we used to code software with our hands.

We imagined what the function it is that we would like to implement, whatever algorithm we'd like to implement, and we use our own creativity, we type it into the computer.

I started with Fortran, and I learned Pascal, and then C and C++, and of course, each one of these languages allow us to express our thoughts into code.

All of a sudden, now we use observed data, and we give this observed data to a computer, and we say, what is the function that you see inside this code?

What are the patterns and relationships that you observe by studying all of the data that we presented to you?

And instead of using code, coding, we now use machine learning.

And the machine generates not software, it generates neural networks that are processed on GPUs.

And so from coding to machine learning, from CPUs to GPUs, and because GPUs are so much more powerful, the type of software we can now develop is extraordinary.

And what sits on top of it is artificial intelligence.

And so computer science has really been transformed pretty much at the description I just said.

Now the question is, what happens to our industry?

Of course, we're all racing to use machine learning to go discover new AIs.

And maybe that's, of course, one of the things about AI that you know very well is the automation of cognition.

And problem solving could be distilled down to, if I could, three basic ideas that you observe and perceive the environment, understand it, reason about it, and then come up with a plan to interact with it, whatever you decide your goals are.

And so perception, reasoning, and planning.

The three fundamental steps of problem solving.

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AI教父黃仁勳：Nvidia最大貢獻係將CPU、GPU成本降低100萬倍｜人工智能雖不是由第一原理推演答案但可模擬人類生物學香港科技大學可建設世界第一間AI醫院｜HKUST｜美股投資｜CC字幕

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AI教父黃仁勳：Nvidia最大貢獻係將CPU、GPU成本降低100萬倍｜人工智能雖不是由第一原理推演答案 但可模擬人類生物學 香港科技大學可建設世界第一間AI醫院｜HKUST｜美股投資｜CC字幕

entire

enormous

material

basically

AI教父黃仁勳：Nvidia最大貢獻係將CPU、GPU成本降低100萬倍｜人工智能雖不是由第一原理推演答案但可模擬人類生物學香港科技大學可建設世界第一間AI醫院｜HKUST｜美股投資｜CC字幕