korrents

Jensen Huang

@jensen-huang · 22 positions · 0 changes of mind

Co-founder and CEO of NVIDIA since 1993.

Jensen Huang did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

  1. Our reading

    The install base is the single most important part of a computing architecture, and everything else about it is secondary.

    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.
    spoken · official transcript hear it at 0:11:27 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 1st of 22 in this recording

    Interesting

  3. Our reading

    Training is no longer limited by data but by compute, because most of the data models learn from is now synthetic.

    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.
    spoken · official transcript hear it at 0:24:47 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 2nd of 22 in this recording

    Interesting

  5. Our reading

    Inference was never going to be the easy, cheap half of AI, because inference is thinking, and thinking is far harder than reading.

    Their wordsthat was always illogical to me because inference is thinking, and I think thinking is hard. Thinking is way harder than reading.
    spoken · official transcript hear it at 0:25:32 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 3rd of 22 in this recording

    Interesting

  7. Our reading

    After pre-training, post-training and test-time scaling, the fourth scaling law is agentic: multiplying AI by spawning agents, and the whole loop scales on one thing, compute.

    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.
    spoken · official transcript hear it at 0:27:44 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 4th of 22 in this recording

    Interesting

  9. Our reading

    Intelligence is going to scale by exactly one thing, and that thing is compute.

    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.
    spoken · official transcript hear it at 0:28:12 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 5th of 22 in this recording

    Interesting

  11. Our reading

    The idea that AI will destroy software and make tools unnecessary is ridiculous: an agent, like a humanoid in your kitchen, will use the tools that already exist.

    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.
    spoken · official transcript hear it at 0:33:13 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 6th of 22 in this recording

    Interesting

  13. Our reading

    OpenClaw did for agentic systems what ChatGPT did for generative ones.

    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.
    spoken · official transcript hear it at 0:35:26 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 7th of 22 in this recording

    OpenAI

    Interesting

  15. Our reading

    The cost of a token is falling by an order of magnitude every year, even as the price of the computers that make them goes up.

    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.
    spoken · official transcript hear it at 0:38:51 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 8th of 22 in this recording

    Interesting

  17. Our reading

    Data centres should be built to degrade gracefully when the grid needs its power back, instead of demanding perfect uptime from utilities that have idle capacity most of the year.

    Their wordsNow, the second thing is we have to build data centers that gracefully degrade.
    spoken · official transcript hear it at 0:50:28 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 9th of 22 in this recording

    data centersenergy

    Interesting

  19. Our reading

    Engineer from the physical limits first, then improve, rather than shaving a few days off a 74-day process by continuous improvement.

    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.
    spoken · official transcript hear it at 0:58:01 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 10th of 22 in this recording

    Interesting

  21. Our reading

    China is the fastest-innovating country in the world today, on the strength of its talent, its open-source habit and its ferocious internal competition.

    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
    spoken · official transcript hear it at 1:03:47 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 11th of 22 in this recording

    open sourceChina

    Interesting

  23. Our reading

    Open-source models are fundamentally necessary for most industries, countries and researchers to join the AI revolution at all.

    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.
    spoken · official transcript hear it at 1:07:37 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 12th of 22 in this recording

    open source

    Interesting

  25. Our reading

    Someone paying a thousand dollars per million tokens is just around the corner, because intelligence is a product that segments by grade like phones do.

    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.
    spoken · official transcript hear it at 1:28:10 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 13th of 22 in this recording

    Interesting

  27. Our reading

    World GDP growth is certain to accelerate, and the share of GDP spent on computation will be a hundred times what it was, because a computer is now a factory rather than a warehouse.

    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
    spoken · official transcript hear it at 1:29:08 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 14th of 22 in this recording

    Interesting

  29. Our reading

    NVIDIA can be a three-trillion-dollar-revenue company in the near future, because nothing physical stands in the way.

    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.
    spoken · official transcript hear it at 1:29:58 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 15th of 22 in this recording

    Interesting

  31. 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.
    spoken · official transcript hear it at 1:56:31 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 16th of 22 in this recording

    AGI

    Interesting

  33. Our reading

    The number of software engineers at NVIDIA will grow, not shrink, because the purpose of a job and the tasks it uses are related but not the same, as radiology already showed.

    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.
    spoken · official transcript hear it at 2:00:38 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 17th of 22 in this recording

    AI and jobs

    Interesting

  35. Our reading

    Coding is now specification, and the number of people who can do it just went from thirty million to a billion.

    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
    spoken · official transcript hear it at 2:01:45 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 18th of 22 in this recording

    AI and jobs

    Interesting

  37. Our reading

    Between two graduates in any field, he would hire the one who is expert at using AI.

    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.
    spoken · official transcript hear it at 2:07:20 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 19th of 22 in this recording

    AI and jobs

    Interesting

  39. Our reading

    Intelligence is a commodity, and it is not the same word as humanity.

    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.
    spoken · official transcript hear it at 2:13:46 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 20th of 22 in this recording

    Interesting

  41. Our reading

    He does not believe in succession planning; the real work is passing on knowledge continuously, and he hopes to die on the job.

    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.
    spoken · official transcript hear it at 2:17:42 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 21st of 22 in this recording

    Interesting

  43. Our reading

    Understanding the biological machine is about five years away, not ten.

    Their wordsUnderstanding the biological machine is right around the corner. It's, it's not 10 years. It's five years probably.
    spoken · official transcript hear it at 2:24:14 · all korrents from this recording

    ↗Jensen Huang: NVIDIA - The $4 Trillion Company & the AI Revolution | Lex Fridman Podcast #494youtube.com 22nd of 22 in this recording

    Interesting