シャドーイング練習: NVIDIA CEO on Elon Musk, xAI, Colossus supercomputer and systems engineering | Jensen Huang - YouTubeで英語スピーキングを学ぶ
C2
you've highly lauded Elon and XAI's accomplishment in Memphis in building Colossus supercomputer,
97 文
文が短すぎたり長すぎる場合は、Editをタップして調整してください。
1
you've highly lauded Elon and XAI's accomplishment in Memphis in building Colossus supercomputer,
2
probably in record time in just four months.
3
It's now at 200,000 GPUs and growing very quickly.
4
Is there something that you could speak to,
5
understand about his approach that's instructive broadly to all the data center creators that enable that kind of accomplishment?
6
his approach to engineering, his approach to the whole management of construction, everything.
7
First of all, Elon is deep in so many different topics,
8
yet he's also a really good systems thinker.
9
And so he's able to think through multiple disciplines.
10
And he obviously pushes things,
11
questions everything, whether number one, is it necessary?
12
number two does it have to be done this way
13
and in other words you know does it have does it have to take this long
14
and and so
15
so he he has he has the he has the ability
16
uh to question everything uh to the point where everything is
17
down to its minimal amount that's necessary you can't take anything else out
18
and and yet yet the the the the the necessary um capabilities of the product retains you know
19
and so he's he is as minimalist as you could possibly imagine
20
and he does it at a system system scale um i i also love the fact
21
that he he is um he is represented he he is he is present at the point of action.
22
You know, he'll just go there.
23
If there's a problem, he'll just go there and show me the problem.
24
You know, when you do all of this in combination,
25
you overcome a lot of previous,
26
this is just the way we do it.
27
You know, I'm waiting for them.
28
You know, I mean, it's just,
29
everybody has a lot of excuses.
30
And so, and then the last thing is,
31
When you act personally with so much urgency,
32
it causes everybody else to act with urgency.
33
Every supplier has a lot of customers going on.
34
Every supplier has a lot of projects going on.
35
He makes it his business that he's the top priority of everybody else's projects.
36
He does that by demonstrating it.
37
I've been in a bunch of those meetings.
38
It's fun to watch because really not enough people ask the question like,
39
okay, so can this be done a lot faster and how?
40
Why does it have to take this long?
41
Yeah, right.
42
And then that becomes an engineering question often.
43
And yes, I think when you get the ground truth of actually,
44
I remember one of the times I was hanging out with him,
45
he literally is going through the entire process of how to plug in cables into a rack.
46
He's working with an engineer on the ground that's doing that task,
47
and he's just trying to understand what does that process look like so it can be less error-prone.
48
And just building up that intuition from every single task involved in putting together the data center,
49
you start to immediately get a sense at the detailed scale and at the broad system scale of where the inefficiencies are.
50
And so you can make it more and more and more efficient.
51
Plus, you have the big hammer of being able to say,
52
let's do it totally different and remove all possible blockers.
53
That's right.
54
is there parallels in the nvidia extreme systems code design approach that you see in the way Elon approaches systems engineering?
55
Well, first of all, co-design is an ultimate systems engineering problem.
56
And so we approach the work that we do from that principle.
57
The other thing that we do,
58
and this is a philosophy that,
59
a thought, a state of mind,
60
I guess, a method that I started 30 years ago,
61
and it's called the speed of light.
62
A speed of light is not just about the speed.
63
A speed of light is my shorthand for what's the limit of what physics can do.
64
And so everything that we do is compared against the speed of light.
65
Memory speed, math speed, power,
66
cost, time, effort, number of people, manufacturing cycle time.
67
and when you think about latency versus throughput,
68
when you think about cost versus throughput,
69
cost versus capacity, all of these things,
70
you test against the speed of light to achieve all of these different constraints separately.
71
And then when you consider it together,
72
you know you have to make compromises because a system that achieves extremely low latency
73
versus a system that achieves very high throughput are architected fundamentally differently.
74
But you want to know what's the speed of light of a system that achieves high throughput?
75
What's the speed of light of a system that achieves low latency?
76
And then when you think about the total system, you could make trade-offs.
77
And so I force everybody to think about what's the first principles,
78
the limits the physical limits um for everything before we you know before we uh do anything
79
and and we test everything against that and
80
so that's a good frame of mind i don't love the other methods which is continuous improvement
81
the problem with continuous improvement it first of all you should
82
engineer something from first principles at the speed you know with speed of light thinking limited only by physical limits
83
and and physics limits and um after
84
that of course you would improve it over time um
85
but i don't like going into a problem
86
and somebody says hey you know it takes 74 days to do this today right now
87
and we can do it for you in 72 days you know i'd rather strip it all back to zero
88
and say first of all explain to me why it's 74 days in the first place
89
and let's think about what's possible today.
90
And if I were to build it completely from scratch,
91
how long would it take?
92
Oftentimes you'd be surprised and might come to six days.
93
Now the rest of the six days to 74
94
could be very well-reasoned and compromises and cost reductions and all kinds of different things,
95
but at least you know what they are.
96
And then now that you know that six days is possible,
97
Then the conversation from 74 to 6 Surprisingly much more effective
アプリをダウンロード
話したすべての文をAIが採点
TRENDING
人気動画
このレッスンについて
このレッスンでは、著名な技術者が語るエロン・マスクとそのアプローチに基づくシステムエンジニアリングの考え方を学びます。リスニングスキルを高めるために、特にエロン・マスクの説明する方法や思考プロセスに焦点を当て、効率的なコミュニケーションのための重要なフレーズや語彙を習得します。英語の発音を良くするために、シャドーイング練習を通じて、実際の会話に近い速度での発音練習に挑戦しましょう。
重要な語彙とフレーズ
- システム思考 - 複数の分野を考慮した問題解決のアプローチ。
- 最小限 - 必要なものだけを維持し、不要な部分を排除すること。
- 緊急性を持って行動する - 自ら率先して行動することの重要性。
- 非効率性 - 効率が悪い部分の特定。
- プロセスの理解 - 具体的な作業工程を把握すること。
- 簡略化 - 複雑な工程を分かりやすくすること。
- 行動する - 実際に行うこと、やってみること。
- エンジニアリングの質問 - 効率向上のための問いを立てること。
練習のヒント
このビデオのスピードとトーンに合わせて英語スピーキング練習を行う際には、以下のポイントを心がけましょう。
- シャドーイングを行う場合、最初はビデオの速度を下げると良いでしょう。徐々に元の速度に戻しながら、発音やリズムを真似します。
- 重要なフレーズをリストアップしたら、声に出して練習します。特にエロン・マスクが使用している単語や表現を繰り返すことで、英語の発音を良くすることができます。
- 緊急性を持って行動するというテーマを意識し、自分の発音や表現に対しても迅速にフィードバックを行いましょう。
- 実際に内容を理解できるようになるまで、何度も繰り返し聴いて、内容と関連付けながらシャドーイングを行うことが大切です。
このプロセスを定期的に行うことで、英語シャドーイングのスキルが向上し、英語スピーキング練習にも確実に効果が現れます。
シャドーイングとは？英語上達に効果的な理由
シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。