Shadowing-Übung: NVIDIA CEO on Elon Musk, xAI, Colossus supercomputer and systems engineering | Jensen Huang - Englisch Sprechen Lernen mit YouTube

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you've highly lauded Elon and XAI's accomplishment in Memphis in building Colossus supercomputer,
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you've highly lauded Elon and XAI's accomplishment in Memphis in building Colossus supercomputer,
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probably in record time in just four months.
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It's now at 200,000 GPUs and growing very quickly.
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Is there something that you could speak to,
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understand about his approach that's instructive broadly to all the data center creators that enable that kind of accomplishment?
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his approach to engineering, his approach to the whole management of construction, everything.
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First of all, Elon is deep in so many different topics,
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yet he's also a really good systems thinker.
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And so he's able to think through multiple disciplines.
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And he obviously pushes things,
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questions everything, whether number one, is it necessary?
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number two does it have to be done this way
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and in other words you know does it have does it have to take this long
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and and so
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so he he has he has the he has the ability
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uh to question everything uh to the point where everything is
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down to its minimal amount that's necessary you can't take anything else out
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and and yet yet the the the the the necessary um capabilities of the product retains you know
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and so he's he is as minimalist as you could possibly imagine
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and he does it at a system system scale um i i also love the fact
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that he he is um he is represented he he is he is present at the point of action.
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You know, he'll just go there.
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If there's a problem, he'll just go there and show me the problem.
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You know, when you do all of this in combination,
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you overcome a lot of previous,
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this is just the way we do it.
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You know, I'm waiting for them.
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You know, I mean, it's just,
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everybody has a lot of excuses.
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And so, and then the last thing is,
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When you act personally with so much urgency,
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it causes everybody else to act with urgency.
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Every supplier has a lot of customers going on.
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Every supplier has a lot of projects going on.
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He makes it his business that he's the top priority of everybody else's projects.
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He does that by demonstrating it.
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I've been in a bunch of those meetings.
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It's fun to watch because really not enough people ask the question like,
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okay, so can this be done a lot faster and how?
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Why does it have to take this long?
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Yeah, right.
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And then that becomes an engineering question often.
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And yes, I think when you get the ground truth of actually,
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I remember one of the times I was hanging out with him,
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he literally is going through the entire process of how to plug in cables into a rack.
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He's working with an engineer on the ground that's doing that task,
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and he's just trying to understand what does that process look like so it can be less error-prone.
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And just building up that intuition from every single task involved in putting together the data center,
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you start to immediately get a sense at the detailed scale and at the broad system scale of where the inefficiencies are.
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And so you can make it more and more and more efficient.
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Plus, you have the big hammer of being able to say,
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let's do it totally different and remove all possible blockers.
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That's right.
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is there parallels in the nvidia extreme systems code design approach that you see in the way Elon approaches systems engineering?
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Well, first of all, co-design is an ultimate systems engineering problem.
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And so we approach the work that we do from that principle.
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The other thing that we do,
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and this is a philosophy that,
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a thought, a state of mind,
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I guess, a method that I started 30 years ago,
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and it's called the speed of light.
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A speed of light is not just about the speed.
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A speed of light is my shorthand for what's the limit of what physics can do.
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And so everything that we do is compared against the speed of light.
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Memory speed, math speed, power,
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cost, time, effort, number of people, manufacturing cycle time.
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and when you think about latency versus throughput,
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when you think about cost versus throughput,
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cost versus capacity, all of these things,
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you test against the speed of light to achieve all of these different constraints separately.
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And then when you consider it together,
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you know you have to make compromises because a system that achieves extremely low latency
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versus a system that achieves very high throughput are architected fundamentally differently.
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But you want to know what's the speed of light of a system that achieves high throughput?
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What's the speed of light of a system that achieves low latency?
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And then when you think about the total system, you could make trade-offs.
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And so I force everybody to think about what's the first principles,
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the limits the physical limits um for everything before we you know before we uh do anything
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and and we test everything against that and
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so that's a good frame of mind i don't love the other methods which is continuous improvement
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the problem with continuous improvement it first of all you should
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engineer something from first principles at the speed you know with speed of light thinking limited only by physical limits
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and and physics limits and um after
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that of course you would improve it over time um
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but i don't like going into a problem
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and somebody says hey you know it takes 74 days to do this today right now
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and we can do it for you in 72 days you know i'd rather strip it all back to zero
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and say first of all explain to me why it's 74 days in the first place
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and let's think about what's possible today.
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And if I were to build it completely from scratch,
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how long would it take?
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Oftentimes you'd be surprised and might come to six days.
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Now the rest of the six days to 74
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could be very well-reasoned and compromises and cost reductions and all kinds of different things,
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but at least you know what they are.
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And then now that you know that six days is possible,
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Then the conversation from 74 to 6 Surprisingly much more effective

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Schlüsselvokabeln & Phrasen

  • systems thinker - Systemdenker
  • multiple disciplines - verschiedene Disziplinen
  • minimal amount - minimaler Betrag
  • point of action - Handlungsort
  • urgency - Dringlichkeit
  • inefficiencies - Ineffizienzen
  • engineering question - Ingenieursfrage
  • error-prone - fehleranfällig

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