शैडोइंग अभ्यास: NVIDIA CEO on Elon Musk, xAI, Colossus supercomputer and systems engineering | Jensen Huang - YouTube के साथ अंग्रेजी बोलना सीखें
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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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इस वीडियो के साथ बोलने का अभ्यास क्यों करें?
जेंसन हुआंग का यह वीडियो आपको अंग्रेजी बोलने में सहायता कर सकता है, क्योंकि यह ना सिर्फ तकनीकी विषयों पर केंद्रित है, बल्कि इस वीडियो में मुख्य मुद्दों पर विचार करने का अच्छा अवसर भी देता है। जब आप इस वीडियो को सुनते हैं और उसके साथ बोलने का प्रयास करते हैं, तो आप न केवल शब्दावली सीखते हैं, बल्कि इस प्रक्रिया में अपनी अंग्रेजी उच्चारण में सुधार भी कर सकते हैं। इस तरह का अभ्यास आपकी बोलने की क्षमता को बढ़ाने के साथ-साथ संचार कौशल को भी मजबूत करता है। वीडियो में उपयोग किए गए तकनीकी और प्रबंधन विचार स्पष्टता प्रदान करते हैं, जिन्हें आप अपने दैनिक संवाद में शामिल कर सकते हैं।
व्याकरण एवं संदर्भ में अभिव्यक्तियाँ
जेंसन हुआंग ने कई महत्वपूर्ण व्याकरणिक संरचनाओं और अभिव्यक्तियों का उपयोग किया है, जैसे:
- “Is it necessary?” - यहाँ एक प्रश्नवाचक संरचना का उपयोग किया गया है, जो विचार करने के लिए प्रेरित करती है।
- “He has the ability to question everything” - यह वाक्यांश व्यक्ति के संज्ञानात्मक कौशल को परिभाषित करता है।
- “It can be less error-prone” - यह एक उदाहरण है जहां संभावनाओं को इंगित किया गया है।
- “How to plug in cables into a rack” - यह एक क्रिया वाक्य है, जो प्रक्रिया को स्पष्ट रूप से प्रस्तुत करता है।
इन संरचनाओं का अध्ययन करने से आप अलग-अलग संदर्भों में अंग्रेजी का उपयोग करना सीखेंगे, जिससे आपका shadow speech कौशल बेहतर होगा।
सामान्य उच्चारण की बाधाएँ
इस वीडियो में कुछ शब्द और उच्चारण चुनौतीपूर्ण हो सकते हैं:
- “Colossus” – यह शब्द अक्सर गलत उच्चारित किया जाता है, इसलिए इसे सही से बोलने का अभ्यास करें।
- “Efficiency” – यह शब्द बोलने में कठिनाई पैदा कर सकता है; इसे सटीक रूप से उच्चारण करने का प्रयास करें।
- “Systems” – यह शब्द उच्चारण में पेचीदगी ला सकता है, इसलिए इसे दोहराने से न चूकें।
जब आप सही उच्चारण पर ध्यान केंद्रित करते हैं, तो आप अपने shadowspeak कौशल को अद्भुत रूप से बढ़ा सकते हैं। अपने अभ्यास को नियमित बनाएं और विभिन्न शब्दों को बोलने में निपुणता प्राप्त करें।
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शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।
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