23 korrents from this recording
Every claim below is a statement made in this recording, quoted word for word and linked to the second it was said, so you can hear it rather than take our word for it. The wording comes from the transcript published alongside the recording; the sentence above each quote is our reading of the claim, not their wording.
0:11:27 · watch on youtube.com↗ · Jensen Huang
Their wordsThey come to a computing platform because the install base is large. Because a developer, like anybody else, wants to develop software that reaches a lot of people. So, the install base is, in fact, the single most important part of an architecture.
0:24:47 · watch on youtube.com↗ · Jensen Huang
Their wordsThe amount of data that we use to train models is going to continue to scale to the point where we're no longer limited… Training is no longer limited by… Data is now limited by compute. And the reason for that is most of the data is synthetic.
0:25:32 · watch on youtube.com↗ · Jensen Huang
Their wordsthat was always illogical to me because inference is thinking, and I think thinking is hard. Thinking is way harder than reading.
0:27:44 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd so the next scaling law is the agentic scaling law. It's kind of like multiplying AI. Multiplying AI, we could spin off agents as fast as you want to spin off agents. And so, you know, I… You know, I have four scaling laws.
0:28:12 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd so this loop, this cycle, is gonna go on and on and on. It kinda comes down to basically intelligence is gonna scale by one thing, and that's compute.
0:33:13 · watch on youtube.com↗ · Jensen Huang
Their wordsYou know, a lot of people would say, "You know AI is gonna completely destroy software. We don't need software anymore. We don't even need tools anymore." That's ridiculous.
0:35:26 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd I think OpenClaw did for agentic systems what ChatGPT did for generative systems. And I just think it's a very big deal.
0:38:51 · watch on youtube.com↗ · Jensen Huang
Their wordsYou know, our computer price is going up, but our token generation effectiveness is going up so much faster that token cost is coming down. It's just coming down an order of magnitude every year.
0:50:28 · watch on youtube.com↗ · Jensen Huang
Their wordsNow, the second thing is we have to build data centers that gracefully degrade.
0:58:01 · watch on youtube.com↗ · Jensen Huang
Their wordsI don't love the other methods, which is continuous improvement. The problem with continuous improvement, it… First of all, you should engineer something from first principles at the speed, you know, with speed of light thinking. Limit it only by physical limits, and physics limits. And after that, of course you would improve it over time.
1:03:47 · watch on youtube.com↗ · Jensen Huang
Their wordsSo you get this rapid, incredible great talent, rapid innovation because of open source and just, you know, the nature of friends, and, and insane competition. Among the company, what emerges is incredible stuff. And so this is the fastest innovating country in the world today
1:07:37 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd if everything is proprietary, it's hard to do research and it's hard to innovate on top of, around, with. And so… Open source is fundamentally necessary for many industries to join the AI revolution.
1:14:38 · watch on youtube.com↗ · Lex Fridman
Their wordsI think NVIDIA, both NVIDIA and TSMC are two of the greatest companies in the history of human civilization.
1:28:10 · watch on youtube.com↗ · Jensen Huang
Their wordsYou know, the idea that somebody's willing to pay $1000 per million tokens is just around the corner. It's not if, it's only when.
1:29:08 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd so when you take these things in combination, I am absolutely certain that the world's GDP is going to accelerate in growth. I'm absolutely certain the percentage of that GDP that will be used for computation will be 100 times more than the past
1:29:58 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd then the rest of it, to me, is: is it possible for NVIDIA to be a, you know, $3 trillion revenue company in the near future? The answer is, of course, yes. And the reason for that is because it's not limited by any physical limits.
1:56:31 · watch on youtube.com↗ · Jensen Huang
Our reading
Asked when an AI could build a billion-dollar business on its own: AGI has already arrived.
Their wordsI think it's now. I think we've achieved AGI.
2:00:38 · watch on youtube.com↗ · Jensen Huang
Their wordsThe number of software engineers at NVIDIA is gonna grow, not decline. And the reason for that is because the purpose of a software engineer and the task of a software engineer coding are related, not the same.
2:01:45 · watch on youtube.com↗ · Jensen Huang
Their wordsSo the question is, how many people could do that? Describe a specification for a computer to go… telling the computer what to go build. How many people? I think we just went from 30 million to probably 1 billion. And so every carpenter in the future will be a coder
2:07:20 · watch on youtube.com↗ · Jensen Huang
Their wordsIf we were to hire a new college graduate today, and I have a choice between two, one that has no clue what AI is and one that is expert in using AI, I would hire the one who's expert in using AI.
2:13:46 · watch on youtube.com↗ · Jensen Huang
Their wordsI don't over-fantasize about, and I don't over-romanticize about intelligence. Intelligence is… And people have heard me say it before, I actually think intelligence is a commodity.
2:17:42 · watch on youtube.com↗ · Jensen Huang
Their wordsAnd so some of the things that of course are practical things, like how do we think about succession planning? And I'm famous in saying that I don't believe in succession planning.
2:24:14 · watch on youtube.com↗ · Jensen Huang
Their wordsUnderstanding the biological machine is right around the corner. It's, it's not 10 years. It's five years probably.