实战练英文 | NVIDIA CEO 黄仁勋谈 AI 工业革

实战练英文 | NVIDIA CEO 黄仁勋谈 AI 工业革命：各行各业迟了就来不及了，AI 工厂与未来制造 | Hill & Valley Forum 202

发布于 2026-01-03 · 时长 21:29

字幕摘录

时间	英文	中文
0:08	Welcome to the Hill and Valley Forum.	欢迎来到山谷论坛
0:10	It's great to have you.	很高兴有你
0:11	You've positioned AI as a new industrial revolution with AI factories at the center of it.	你将AI定位为以AI工厂为中心的新工业革命.
0:17	Can you explain to us what is an AI factory and why is it important to understand in the	你能解释一下什么是人工智能工厂吗?
0:22	21st century economy?	21世纪经济?
0:23	AI.	大赦国际。
0:24	Well, we've been talking a lot about AI over the last several years.	我们在过去几年里一直在谈论AI
0:27	It's multifaceted and I think it's helpful to look at it in this lens.	这是多方面的,我认为从这个镜头来看是很有帮助的.
0:31	First, of course, AI is a new technology.	首先,当然,AI是一种新技术。
0:34	It's a new technology in the sense that it's built differently than software in the past	是一种新的技术,它和过去软件不同

展开字幕全文（342 条）

序号	英文	中文
1	Welcome to the Hill and Valley Forum.	欢迎来到山谷论坛
2	It's great to have you.	很高兴有你
3	You've positioned AI as a new industrial revolution with AI factories at the center of it.	你将AI定位为以AI工厂为中心的新工业革命.
4	Can you explain to us what is an AI factory and why is it important to understand in the	你能解释一下什么是人工智能工厂吗?
5	21st century economy?	21世纪经济?
6	AI.	大赦国际。
7	Well, we've been talking a lot about AI over the last several years.	我们在过去几年里一直在谈论AI
8	It's multifaceted and I think it's helpful to look at it in this lens.	这是多方面的,我认为从这个镜头来看是很有帮助的.
9	First, of course, AI is a new technology.	首先,当然,AI是一种新技术。
10	It's a new technology in the sense that it's built differently than software in the past	是一种新的技术,它和过去软件不同
11	and this new software can do things that software in the past could not do.	而这个新软件可以做过去软件无法做的事情.
12	So it's incredible technology.	所以这是令人难以置信的技术。
13	All the things it can do, all the things that we have to do to keep it safe, all the amazing	所有它能做的事情, 所有我们必须做的事情来保证它的安全, 所有惊人的
14	things that it's going to enable, fantastic.	东西,它将要启用, 真棒。
15	So there's the technology layer.	这就是技术层。
16	The second layer, which is rather new, in the last technology industry, software production,	第二层相当新, 在最后一个技术产业,软件生产,
17	it was done by humans typing.	是人类打字做的
18	Now we have a new industry and this software is produced with machinery.	现在我们有了一个新的产业, 这个软件是用机械生产的。
19	So you need a large supercomputer, you apply electricity to it and what comes flying out	所以,你需要一个大型的超级计算机, 你应用电力到它和什么飞出来
20	of it are tokens.	那是许多迹象。
21	And these tokens could be reformulated into numbers and words and proteins and images	这些符号可以重新编成数字和文字蛋白质和图像
22	and videos and three-dimensional structures.	视频和三维结构
23	You can reformulate these tokens into all kinds of things.	你可以把这些符号重塑成各种各样的东西.
24	We call it intelligence.	我们称之为情报。
25	And so this machinery looks different than the machinery of the past.	所以这个机器看起来和过去的机器不同。
26	And I call it an AI factory because it does one thing.	我称之为人工智能工厂因为它有一件事
27	Every single day it's producing tokens.	每一天,它都在制作代币.
28	And the layer above that is infrastructural.	上面的一层是基础设施。
29	And this is the reason why we now internalize that AI is likely going to be quite an extraordinary	这就是为什么我们现在将AI内部化很可能是一个相当不寻常的
30	industrial revolution in the sense that this new technology is going to enable a new industry	工业革命意味着这种新技术将促成一个新的工业
31	that I just mentioned, AI factories, the production of intelligence.	我刚刚提到,AI工厂,生产情报。
32	But it's going to go back and revolutionize and transform every other industry.	但是,它要重新走向革命,改造和改造所有其他工业.
33	And so all of these tokens are going to go into healthcare and education.	所以所有这些标志都将进入保健和教育。
34	One of my favorites is education.	我最喜欢的就是教育
35	I use it every day for education, financial services, engineering.	我每天都用它做教育,金融服务,工程.
36	We use AI every day for software programming and supply chain management.	我们每天使用AI进行软件编程和供应链管理.
37	It's about to go into manufacturing and so on and so forth.	即将进入制造业等.
38	So when you think about it from these three layers, it's very clear.	因此,当你从这三层考虑的时候,它就非常清楚了.
39	This is as transformative, as impactful as electricity was before, and it's going to	这和之前的电力一样有影响并且将会
40	revolutionize every industry.	将每个行业都革命化。
41	So it's an industrial revolution.	所以这是一场工业革命.
42	So do you think it's a paradigm shift in modern computing and that every factory that's building	你觉得这是现代计算模式的转变吗? 每一个正在建造的工厂
43	physical things in the real world will also be accompanied by an AI factory?	现实世界的物理物质也会伴随着AI工厂?.
44	Yeah, perfect.	是啊,完美无缺。
45	Absolutely.	当然
46	Every company that makes things today, so long as they move, you know, so let's say	今天做事情的每个公司只要他们搬家,我们说
47	we make lawnmowers or they build construction machinery.	我们制造草坪或者他们建造建筑机械
48	Today it's largely manually manipulated.	今天它基本上被人工操纵.
49	In the future, it'll be autonomous or highly autonomous or semi-autonomous or assisted.	今后将实行自主或高度自主或半自主或协助.
50	When it becomes autonomous, then it'll be software defined.	当它变得自主时,它就会被定义为软件.
51	And so you're going to have to produce those tokens, those software that feeds that tractor.	所以,你必须生产这些代币, 那些软件供货拖拉机。
52	And so in the future, every company that builds things will have a factory that builds the	因此,在未来,每个建造东西的公司都会有一个工厂来建造
53	things that they sell.	他们卖的东西。
54	And then they'll have another factory that builds and produces the AI that runs on that	然后他们会有另一个工厂建造和生产 AI运行在那个上
55	thing that they sell.	他们卖的东西。
56	And so it's very clear when you look at look at car companies, you know, today's car companies	所以当你看汽车公司,你知道, 今天的汽车公司,
57	largely make cars.	主要是制造汽车。
58	But it's very clear that in 10 years time, every car company will also produce the tokens	但很清楚的是,在10年后,每个汽车公司都会生产代币
59	that runs in those cars.	在那些车上运行。
60	You've talked a little bit about physical AI, the concept of physical AI over the last	你讲了一点物理AI, 物理AI的概念在过去
61	year.	年数。
62	For policymakers who are thinking about the future of American policy, can you explain	对于考虑美国政策未来的决策者,你能解释一下:
63	to us a little bit what physical AI is and how we should be thinking about it?	对我们来说,什么是物理AI,我们应该如何思考它?
64	Take a step back.	退后一点
65	AI really came to consciousness, modern AI really came into consciousness about 12-14	AI真的来了意识,现代AI真的来了意识大约12-14
66	years ago when AlexNet came out and computer vision was this big giant breakthrough.	几年前当AlexNet出现时计算机视觉就是这个巨大的突破
67	And that was like, I guess, 2012.	这就像,我想,2012年。
68	Around that time, when you take a step back, what is computer vision in this largest context	那时,当你退后一步, 什么是计算机视觉在这个最大的背景
69	is perception, you know, perceiving the world, whether whatever modality of information,	是感知,你知道, 感知世界, 无论信息的方式,
70	it could be, of course, images, it could be sounds, it could be vibration, temperature.	它可能是,当然,图像, 它可以是声音, 它可以是振动,温度。
71	And we've now developed AI models that understand the meaning of all of that information and	我们现在开发了AI模型来理解所有这些信息的意义
72	can be quite smart about it.	可以相当聪明。
73	The first layer, the first wave of AI was perception AI.	第一层,AI的第一波是知觉AI.
74	The second, what everybody started talking about maybe five years ago was generative	第二,人们开始谈论也许五年前是遗传性的
75	AI.	大赦国际。
76	And generative AI is where the AI model has learned how to understand the meaning of the	而基因AI是AI模型已经学会如何理解
77	information but translate it.	信息但翻译。
78	So for example, you could understand English and translate it to French.	例如,你可以理解英语,并翻译成法语。
79	You could understand English and translate it to images.	你可以听懂英语翻译成图像
80	And so you could prompt it to generate images.	这样你就可以促使它生成图像。
81	So generative AI is essentially a universal translator, if you will, a universal translator	所以基因AI本质上是一个通用翻译,如果你愿意的话,是一个通用翻译
82	that understand the language of humans.	理解人类的语言
83	And so that's the next wave.	所以这就是下一波。
84	The wave that we're in now is where you now have AIs that can understand, it can generate.	我们现在所经历的浪潮就是你们现在的人工智能能够理解,能够产生。
85	But as you know, intelligence requires us to solve problems and recognize conditions	但如你所知,情报需要我们解决问题和识别条件
86	that we've never seen before.	我们从来没有见过。
87	And the way we do that is we use reasoning.	我们这样做的方式就是运用推理。
88	We apply rules and laws and principles that we've learned in the past, and we break the	我们运用过去学到的规则、法律和原则,
89	problem down step by step by step.	问题一步一步地解决
90	And even though we've never solved this problem before, through reasoning, we can solve it.	尽管我们以前从来没有解决过这个问题,但是通过推理,我们可以解决这个问题.
91	Okay.	摆
92	And so one of the unique capabilities of intelligence.	所以情报的独特能力之一。
93	And so we're now in this age called reasoning AI.	现在我们在这个时代被称为推理AI。
94	And reasoning AIs allow you to produce a form of digital robots.	而推理AI允许你生产一种形式的数字机器人.
95	We call them genetic AI agents.	我们称他们为基因人工智能特工
96	It has agency.	它有机构
97	And so AI that can understand the tasks that's been given, it can go off and learn and read,	因此,AI能够理解已经赋予的任务, 它可以去学习和阅读,
98	apply, use tools like calculators and web browsers and spreadsheets, and then come back	应用,使用计算器、网页浏览器和电子表格等工具,然后返回
99	and does something for you.	为你做点事
100	And it could be something related to supply chains or access to SAP, it could be something	可能跟供应链有关也可能跟SAP有关
101	related to HR, access to Workday.	与人力资源有关,进入工作日。
102	So these genetic AIs are essentially robots, but they're digital workforce robots.	所以这些基因AI本质上是机器人,但它们是数字劳动力机器人.
103	And so in the future, we're going to be the generation of CEOs that are going to manage	因此,在未来,我们将是一代CEO,将管理
104	biological workforce as well as digital workforce.	生物劳动力以及数字劳动力。
105	And HR department for the biological workforce and our IT department are going to become	人力资源部的生物劳动力和我们的信息技术部门将变成
106	the HR of agentic AI.	(a) 大赦国际的人力资源。
107	This is kind of the phase we're in today.	这就是我们今天所处的阶段。
108	The next wave requires us to understand things like the laws of physics, friction, inertia,	下一波要求我们了解物理、摩擦、惯性
109	cause and effect, the fact that I tip that thing over, it's going to fall.	原因和结果,事实上,我倾斜这件事情,它会坠落。
110	When I said the bottle down, it's not going to go through the table.	我说瓶子倒下时,不会穿过桌子.
111	And so all of these common sense, physical reasoning abilities that children have, that	所以所有这些常识, 物理推理能力的孩子,
112	our pets have, most AIs don't have.	我们的宠物,大多数AI没有。
113	I roll a ball over the kitchen counter and it goes up over the top and it disappears.	我把一个球滚过厨房柜台然后球从顶部滚上来然后就消失了
114	Well, the AI thinks it's disappeared, but your dog knows it, it's on the other side.	好吧,AI认为它消失了, 但你的狗知道它, 它在另一边。
115	It understands this concept called object permanence and it didn't go into another metaverse.	它理解这个叫做物体永久的概念,并没有进入另一个元论.
116	So it runs around the table and gets it.	所以它绕着桌子跑,得到它。
117	And a robot needs to learn that if you want to go from this side of the table to that	一个机器人需要学会如果你想从桌子的这边走到那
118	side of the table, you can't go through the table.	桌子的一侧,你不能穿过桌子。
119	You're going to have to reason about how to go around the table.	须知如何绕席.
120	And so all of these type of physical reasoning things is what's called physical AI.	所以所有这些类型的物理推理就是所谓的物理AI.
121	And when you take that physical AI and then you put it into a physical object called a	当你把身体的AI,然后你把它在一个物理物体,叫做
122	robot, you get robotics.	机器人,你会得到机器人。
123	And this is really important for us now because we're building plants and factories all over	这对我们很重要,因为我们正在建造工厂和工厂
124	United States.	美国。
125	And we'd like to build it in a way that takes advantage of the latest technology.	我们希望利用最新技术来建造它。
126	And so hopefully in the next 10 years, as we build out this new generation of plants	希望在未来10年里,随着我们造出这新一代的植物
127	and factories, they're highly robotic and they're helping us deal with the severe labor	和工厂,他们是高机器人他们正在帮助我们处理严重的劳动力
128	shortage that we have all over the world.	我们在世界各地都缺少这种资源。
129	So many people have talked about this concept about the fact that we're in an AI race globally.	很多人都谈到这个概念,认为我们是在全球的AI竞赛.
130	What do you think the US government needs to do to win that AI race to have the very	你觉得美国政府需要做什么才能赢得AI比赛
131	best AI technology?	最好的人工智能技术?
132	First, in order to have a race to do well in a race, you have to understand the race and	首先,为了在比赛中有一个好成绩的比赛, 你必须了解比赛和
133	you have to understand the resources that you're working with, the assets that you have,	你必须了解你的工作资源, 你拥有的资产,
134	the assets you don't have, your advantages and your disadvantages.	你没有的资产,你的利弊。
135	And some of the things to realize is that that AI is fundamentally at this core level,	有些事情要意识到 AI从根本上讲就是这个核心层面
136	going back to the three levels that we're talking about at each level, we have to make	回到我们谈论的每个层次的三个层次, 我们必须使
137	sure that we understand the game.	确保我们理解游戏
138	And this game isn't there's no 60 minute clock on this thing.	游戏里没有60分钟的时钟
139	This is an infinite game.	这是一个无限的游戏。
140	And so most people aren't very good at playing infinite games.	所以大多数人不太擅长玩无限游戏.
141	Nvidia is now 33 years old.	恩维迪亚现年33岁.
142	We've been through three computer revolutions from the PC revolution to the internet to	我们经历了三次计算机革命从PC革命到互联网
143	mobile and now we're in AI.	移动,现在我们在AI。
144	And so in order to thrive across all of these different changes in the environment, you	所以为了在环境的所有这些变化中蓬勃发展你
145	have to understand how to play games.	要懂得怎么玩游戏
146	And so the things that I just described, understanding the game, understanding the	所以我刚刚描述的事情, 理解游戏,理解
147	assets you have, really important.	你拥有的资产,真的很重要。
148	At the first layer, at the technology layer, the most important thing to understand is	在第一层,在技术层, 最重要的事情是
149	the intellectual capital.	知识资本。
150	And remember, 50% of the world's AI researchers are Chinese.	记住,世界上50%的AI研究者是中国人.
151	First, just take a step back and recognize that important factor has to play into how	首先,退一步,认识到重要因素必须发挥
152	we think about the game.	我们考虑一下比赛
153	The next is AI factories.	接下来是AI工厂.
154	In order to do well there, you need to have energy because fundamentally we transform	为了在那里做得好,你需要精力因为从根本上,我们改造
155	electricity into digital tokens, just as the last industrial revolution transformed	就像上次工业革命一样
156	atoms through energy into steel things and physical things that we know, cars and things	原子通过能量变成钢铁和我们所认识的物理物质汽车和事物
157	like that, buildings and things like that.	像这样,建筑之类的东西。
158	And the generation before that, we gave it water into a machine called the Dynamo and	在那之前的一代人, 我们给它水在一个叫做迪纳摩和
159	what came out was electricity.	出来的东西是电。
160	And so now we have electricity go in and tokens come out.	所以,现在我们有电力进入, 和征兆出来。
161	So the next layer requires energy.	所以下一层需要能量。
162	The layer above that is just happening now.	上面的一层刚刚发生。
163	And it's really, really important that we understand that ultimately the winners of	这真的,真的很重要,我们必须了解,最终的胜利者
164	the last industrial revolution wasn't the country that invented it.	上次工业革命不是发明它的国家。
165	It was the country that applied it.	是国家应用的。
166	And the United States applied steel, applied energy faster than any country.	而美国应用钢铁,应用能量比任何国家都快.
167	Everybody else was worried about things like labor and horses being replaced by cars and	其他人都担心像劳动和马匹被汽车取代
168	those kind of matters.	这些事情
169	But the United States, we just took it and ran with it.	但是,美国,我们只是把它和它一起运行。
170	And so the infrastructural layer above that is about the application of the technology.	所以上面的基础设施层是关于技术的应用。
171	It's about not being afraid of it, wanting to engage it, re-skilling our workforce so	这是关于不害怕,想参与, 重新训练我们的员工
172	that we're able to apply it, encouraging people to adopt it.	我们可以应用它,鼓励人们收养它。
173	And so when you look at AI through the lens that I just described, the framework that	所以当你从我刚才描述的镜头看AI时, 框架就是
174	I just described, each one of the layers has its own, if you will, challenges and opportunities.	我刚才描述,每一层都有自己的,如果你愿意的话,挑战与机会。
175	And the game's a little different in each one.	而每场比赛都略有不同.
176	On the workforce point, the press has been so focused on weaving the narrative that AI	关于劳动力问题,媒体一直把注意力集中在编织叙事上,以至于AI
177	could potentially lead to the mass displacement of labor and mass unemployment.	可能导致劳动力大规模流离失所和大规模失业。
178	Could you help paint a picture a little bit about what your prediction is for the impact	你能帮我画一幅图片一点点关于你的预测是什么对撞击
179	of AI on the job market, but also more specifically on what you see as the potentially new categories	更具体地说,你所认为的潜在新类别
180	of jobs that we're potentially not even thinking about today that could actually come into being?	那些我们甚至根本没想过的今天真正可能实现的工作?
181	Some jobs, well, new jobs will be created.	有些工作会创造新的工作
182	Some jobs will be lost.	有些工作会丢掉的
183	Every job will be changed.	每个工作都会改变
184	Okay, so let's just break it down.	好吧,让我们只是打破它。
185	It's always easy to go to one extreme from another, but I always find it helpful when	从一个极端到另一个极端总是容易的但我总觉得当
186	you break the problem down, reason about it from its first principles.	你打破了问题, 理由从它的第一原则。
187	And again, in this framework that I just described, at the lowest layer, as you know,	再说一遍,在我刚才描述的这个框架内, 在最低层,你知道,
188	and Jacob, you're deeply integrated into venture investment and you know what's going on in AI.	和雅各布,你深深地融入了风险投资你知道AI中发生了什么。
189	And you know at the foundational layer, it's because of AI that San Francisco's back.	你知道在基础层, 是因为AI,旧金山的背。
190	Anybody who lives in San Francisco, you'll know what I'm talking about.	住在旧金山的任何人你都会知道我在说什么
191	Just about everybody evacuated San Francisco.	所有人疏散旧金山
192	Now it's thriving again.	现在它又繁荣起来了
193	It's all because of AI.	皆因阿难.
194	And AI creates a new type of job.	而AI创造了一种新的工作类型.
195	And the fundamental reason is because it's software development, but done in a different way.	而其根本原因是因为它是软件的开发,但以不同的方式完成.
196	We've changed every layer of the technology as a result of AI.	由于AI的缘故,我们改变了技术的每一层.
197	What used to be human coded software running on CPUs are now machine learning	在CPU上运行的人类编码软件现在正在机器学习
198	generated software running on GPUs.	生成运行在 GPU 上的软件。
199	And so every single layer, the tooling of it, the compilers of it, the methodology of it,	所以每一层工具编译器方法
200	the way you collect data, curate data, use AI to guardrails, use AI to teach you,	收集资料,整理资料,用人工智能做护栏,用人工智能教你
201	use AI to keep the AI safe.	使用AI来保证AI的安全.
202	All of that technology is being invented right now and it creates tons of jobs.	现在所有的技术都被发明出来,它创造了大量的就业机会。
203	At the next layer, this is where the giant opportunity is.	在下一层,这是巨大的机会所在。
204	Remember, I just said that we're going to create a new type of factory.	记住,我刚说我们要建立一个新型工厂
205	And this factory has electricity come in and it generates tokens out.	这家工厂有电力供应并生产出代币。
206	A one gigawatt factory, and we're in the horizon building something like 7, 8,	一千兆瓦的工厂,我们正在地平线上建造一些像7,8,
207	10 gigawatts of AI factories.	10千兆瓦的AI工厂.
208	One gigawatt factory is $60 billion.	一千兆瓦工厂为600亿美元.
209	$60 billion for one gigawatt.	600亿美元一千兆瓦。
210	A hundred megawatt factory is pretty commodity now.	一百兆瓦的工厂现在相当的商品。
211	It's pretty commonplace.	这很平常
212	And so you just divide that by 10.	所以,你只是除以10。
213	But $60 billion is the annual, one factory is the annual revenues of Boeing.	但每年600亿美元,一家工厂是波音的年收入.
214	And to build it, you have to finance it, creates a lot of jobs.	为了建造它,你必须资助它,创造很多工作。
215	You have to build out the site, the shell, creates a bunch of jobs, construction.	你必须建造工地,外壳,创造一堆工作,建筑.
216	You got carpenters, you got steelworkers, you got masons.	你有木匠,有钢铁工人,还有泥工
217	You got to build out that factory.	你得把工厂建起来
218	$60 billion factory.	600亿元工厂.
219	This thing is gigantic.	这东西是巨大的。
220	You have to have mechanical engineers, electrical engineers, plumbers.	你必须有机械工程师,电气工程师,水管工.
221	And then after that, all the low voltage stuff, all the IT and the networking.	之后,所有的低电压东西, 所有的IT和网络。
222	After that, operations.	之后是手术
223	That entire cycle is about three years.	整个周期是三年左右。
224	A whole bunch of new trade jobs have to be created.	必须创造一整批新的贸易就业机会。
225	These trade jobs, in the last computer industry, the last computing platform shift,	这些贸易岗位,在最后的计算机行业, 最后的计算平台转变,
226	the number one critical path for most companies growth is software engineers.	软件工程师是大多数公司增长的头号关键路径。
227	This next layer, AI factories, the number one is going to be trades.	接下来的一层,AI工厂, 头号将是贸易。
228	The tradecraft.	手工业
229	And I think this is terrific.	我认为这是伟大的。
230	Our country needs to acknowledge that tradecraft is respectable work and it's critical work.	我国需要承认,手工业是值得尊敬的工作,是关键的工作.
231	And it's necessary to build our country.	亦须建国.
232	And so we want to encourage tradecraft.	所以我们想鼓励手工业。
233	Electricians, plumbers, carpenters, steelworkers, the whole span of it.	电工水管工木工钢工整个过程
234	We're going to need a whole bunch.	我们需要一整帮人
235	And then now, above that is when we can start talking about how are these AI agents going	然后,现在,上面是当我们可以开始谈论这些AI特工如何去
236	to change the work of doctors or financial service professionals or customer care.	改变医生或金融服务专业人员的工作或客户护理。
237	Or in our company, just as a starting point, every single software engineer	或者在我们公司作为起点每个软件工程师
238	is now assisted by AI assistants.	现在由人工智能助理协助。
239	And the amount of code that we check into the company is incredible.	我们查查公司的代码数量是不可思议的。
240	As a result, our productivity has shot up through the roof and we're hiring more people	结果是,我们的生产力被打穿了屋顶,我们正在雇用更多的人
241	because it enabled us to create more things that the world desires.	因为它使我们能够创造世界所希望的更多东西。
242	It increases our revenues and increases our ability to hire.	它增加了我们的收入,提高了我们的雇佣能力。
243	And so I think that that layer above really wants to engage AIs as early as you can.	所以我觉得上面的一层真的想尽早接触AI。
244	Remember, it's not AI that's going to take your job.	记住,不是人工智能会占用你的工作。
245	It's not AI that's going to destroy your company.	不是AI会毁了你的公司
246	It's the company and the person who uses AI that's going to take your job.	公司和使用人工智能的人会接你的工作
247	And so that's something to internalize.	故曰内化.
248	There's been such a huge amount of focus lately on bringing manufacturing back.	最近有如此巨大的关注使制造业恢复。
249	A lot of people in the AI space have talked about the concept of how digital twins	AI空间的很多人都谈到了数码双胞胎的概念
250	and manufacturing plants adopting digital twins could actually help enable	和制造工厂采用数码双胞胎实际上有助于
251	rebooting manufacturing here.	重新开始这里的制造业。
252	And simultaneously, the CEO of Apple, Tim Cook, recently said that one of the main bottlenecks	同时,苹果公司的首席执行官蒂姆·库克(Tim Cook)最近说,这是主要的瓶颈之一
253	to reshoring and making the iPhone here was having a good and precise robotic arm technology.	恢复和制造iPhone 是一个良好和精确的机器人臂技术。
254	So on both counts, it really seems like AI could be an enabling technology	因此,从两个方面来看,它似乎真的 AI可能是一种有利的技术
255	for manufacturing and reshoring.	用于制造和还原。
256	Could you tell us a little bit more about what your prognosis is on that?	你能多告诉我们一些关于你的预后是什么?
257	Yeah.	对
258	Well, first of all, manufacturing is not about low cost labor.	首先,制造业不是低成本劳动力。
259	Advanced manufacturing today is software.	今天的先进制造是软件.
260	The entire factory is software driven.	整个工厂都是软件驱动的.
261	The entire factory is one giant robot.	整个工厂是一个巨大的机器人。
262	And it's a robot orchestrating a whole bunch of robots inside.	它是一个机器人组织一整群机器人在里面。
263	And so these advanced factories has a lot of people in it, but it's largely technology.	所以这些先进的工厂里面有很多人, 但主要是技术。
264	So I think the first part of it is in our industry, and I'll just talk about mine,	所以,我认为它的第一部分在我们的行业, 我会只是谈论我的,
265	the ability for us to manufacture end-to-end from silicon to the AI supercomputers here on	我们制造从硅到AI超级计算机的能力
266	shore is a terrific opportunity.	岸是绝佳的机会
267	And I'm delighted that the administration is really encouraging and supporting	我很高兴政府真的鼓励和支持
268	the industry on shore manufacturing.	岸上制造业
269	This is high quality work.	这是高质量的工作。
270	It's advanced technology work.	这是先进技术工作.
271	Doing it on shore is a fantastic opportunity.	在岸上做是一个奇妙的机会。
272	And I'm very enthusiastic about it.	我很热心
273	We're huge proponents of it.	我们是它的巨大支持者。
274	And we're fortunate that we have partners around the world who are supporting us to do that.	我们幸运的是,我们在世界各地有合作伙伴支持我们这样做。
275	That's number one.	即第一义.
276	Second, if we don't get good at manufacturing, we're going to leave behind a giant industry.	第二,如果我们不善于制造,我们就会留下一个巨大的工业.
277	What country doesn't want to get engaged in this new industry called AI?	哪个国家不想参与这个叫做AI的新产业?
278	Why would you not want to produce AI?	为什么你不想生产人工智能?
279	Why would you not want to engage in one of the most advanced manufacturing?	为什么你不想参与最先进的制造业呢?
280	It's manufacturing.	这是制造。
281	It just happens to be numbers when it's done.	恰巧是数字当它完成。
282	And just like it was electrons at the last industrial revolution,	就像上次工业革命时的电子一样
283	most people couldn't understand that you could create this thing	大多数人都不明白你能创造这个东西
284	through a machinery called Dynamo.	通过一个叫迪纳摩的机器
285	Now we call it NVIDIA AI supercomputers.	现在我们把它叫做NVIDIA AI超级计算机。
286	But back then, a Dynamo, what came out of it was invisible.	但那时,一个Dynamo, 从里面出来的东西是看不见的。
287	It's electricity.	是电
288	Don't touch it, but it's electricity.	别碰它,但它是电。
289	It's electrons.	这是电子。
290	And now it's a new form of electrons.	现在它是一种新的电子形式.
291	It's numbers.	这是数字。
292	And so of course, we want to engage in this new industry.	当然,我们想参与这个新的产业。
293	And in order to do that, we have to have manufacturing on shore.	为了做到这一点,我们必须让制造业上岸。
294	Now the thing that is absolutely the case,	现在事情是绝对的,
295	because manufacturing is so technology intensive,	因为制造技术很密集
296	we should do it in a digital twin first.	我们应该先用数码双胞胎
297	We should do it in virtual reality first.	我们首先应该在虚拟现实中做到这一点。
298	NVIDIA designs the most complex systems in the world.	NVIDIA设计了世界上最复杂的系统.
299	Each one of our generation, R&D, call it $20 billion, maybe more now.	我们这一代的人,研发, 都称之为200亿美元, 也许现在更多。
300	But call it $20 billion of R&D just to produce a family of chips.	但称其为200亿美元的研发,只是为了生产一个芯片家族.
301	We designed those chips completely in their digital twin.	这些芯片是我们用数字双胞胎设计的
302	They existed for months and months and months,	他们存在了好几个月,
303	long before we ever produced it.	早在我们制作之前
304	The moment I produced it, I know it to be perfect.	我制作的那一刻我知道它是完美的。
305	I know it because we've simulated it exhaustively,	我知道,因为我们已经彻底模拟它,
306	and we emulated it, and we put it into its paces.	我们仿照了它,我们把它投入它的步伐。
307	We should do the same with digital factories, large factories.	我们应该同样对待数字工厂,大型工厂.
308	We should completely create digital twins,	我们应该完全创造数码双胞胎,
309	use artificial intelligence to create these digital twins,	利用人工智能创造这些数码双胞胎,
310	operate it, virtual integration,	操作它,虚拟集成,
311	integrate these magnificent structures completely digitally,	把这些宏伟的结构完全数字化地融合起来,
312	operate it, optimize it,	操作它,优化它,
313	and use it for planning your output completely digitally.	用它来完全数字化地规划你的输出
314	And in the future, every factory will have a digital twin version.	而在未来,每个工厂都会有一个数字双版.
315	In the future, and I'm hoping,	在未来,我希望,
316	every human will have a digital twin version.	每个人类都会有一个数字双版.
317	Every car has a digital twin version.	每辆车都有数字双版.
318	Every building has a digital twin version.	每栋建筑都有数字双版.
319	Every city has a digital twin version.	每个城市都有数字双版.
320	So this idea of digital twins is happening now,	所以这个数字双胞胎的想法现在正在发生,
321	and it's all happening because of artificial intelligence.	这一切都是因为人工智能。
322	What is your expectation on the timeline by which we live in a world	你对我们生活在一个世界上的时间有何期望?
323	where AI-enabled robots become a ubiquitous part of everyday human life?	人工智能机器人成为人类日常生活中无处不在的一部分?
324	A self-driving car is a robot.	自驾车是机器人.
325	Now, it's taken us about 10 years.	现在,我们花了大约10年。
326	And now Waymo is in cities around the nation and is doing fantastically.	而现在Waymo正在全国的城市里做着令人惊奇的事情
327	It's terrific to see the Waymos driving around in San Francisco and other cities.	看到Waymos在旧金山和其他城市里开车真是太好了
328	It took about 10 years.	花了大约10年时间.
329	Robots will take less time.	机器人会花更少的时间。
330	And the reason for that is because we can constrain the environments where the robots operate.	之所以如此,是因为我们可以限制机器人运行的环境。
331	And so the robots don't have to be as general purpose as a car.	因此机器人不必像汽车那样通用.
332	Once you're in San Francisco,	你一到旧金山
333	you got to work in every street and every single condition.	你必须在每一个街道和每个条件工作。
334	So in the case of a robot, we could be a lot more constrained.	因此,就机器人而言,我们可能会受到更多的制约。
335	From the moment that something is prototypable,	从有东西可以原型化的那一刻起
336	fairly functional to the time that it becomes a high-volume product, call it five years.	在它成为高产量产品时,称为五年。
337	And so we have quite high-functioning robots today.	因此我们今天有相当高功能的机器人。
338	And so in some five years' time,	所以在五年的时间内
339	we're going to see robots get pumped out of these factories.	我们将会看到机器人被泵出这些工厂。
340	And every car company who makes cars today will be very good at building robots.	而今天制造汽车的每一个汽车公司都会非常擅长制造机器人.
341	They just have to get good at the software part of it, the AI part of it.	他们只需要精通软件部分 AI部分
342	But that technology is fairly available.	但是这种技术是相当可用的。

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