# (77) Cisco AI Summit | Special live event with Jensen Huang - YouTube
- Transcript ID: `6fbyiprhmss`
- Source tier: `youtube_auto`
- Original language: `en_or_source_language_unlabeled`
- Translation status: `agent_translated_reviewed` (89/89 chunks)
- Original source: https://www.youtube.com/watch?v=6fbyiPRhMSs
- Raw evidence: `data/transcripts/youtube/6fbyiPRhMSs.json`
> 中文是派生翻译，英文是留存的源文本。中文未复核时，以英文和原始音视频为准。
## 00:00:39
**中文**
嘿。对。回到这里。
**English / Original**
Hey. Yep. Back here.
## 00:01:47
**中文**
出去。嘿，热起来。热起来。
**English / Original**
out. Hey Heat. HEAT.
## 00:02:41
**中文**
热起来。热起来。热起来。热起来。
**English / Original**
HEAT. HEAT. HEAT. HEAT.
## 00:03:25
**中文**
热起来。热起来。嘿，
**English / Original**
HEAT. HEAT. HEY,
## 00:04:14
**中文**
嘿，嘿。［音乐］嘿，［音乐］嘿，
**English / Original**
HEY, HEY. >> [music] >> HEY, [music] HEY,
## 00:05:14
**中文**
嗯。［音乐］嘿，嘿，我是个……
**English / Original**
M. >> [music] >> HEY, HEY, I'm a
## 00:06:14
**中文**
［掌声］我感觉自己像是在抢别人的饭碗。［笑声］我们把一杯葡萄酒拿上来时，Jensen 提醒我说：“你知道这正在直播，对吧？”［笑声］——嘿，随便吧，已经很晚了。——嗯，那么……——第一原则是不造成伤害。——不造成伤害。对，对。——还要认识到自己多么幸运。
**English / Original**
>> [applause] >> I feel like I'm drinking one's job. [laughter] >> Jensen reminded me as we brought a glass of wine out here. He said, "You realize you're streaming this, right?" [laughter] >> Hey, whatever. It's late. >> Well, >> so, uh, >> the first principle is do no harm. >> Do no harm. Yeah. Yeah. >> And recognize how blessed you are.
## 00:06:41
**中文**
——是的。——首先，感谢大家经历了无比漫长的一天之后还留在这里。我们今天一早就开始了，一个演讲者接着一个演讲者；之后中间休息了大约两个半小时，大家又回来见你。所以……——我从凌晨 1 点就起床了。——这个人，［掌声］这已经是他为期两周、途经亚洲四五座城市之旅的尾声。——一天前我还在台湾，昨晚在休斯敦，现在我就在这里。［笑声］——不过他已经离家两周了，而我们正挡在他和……
**English / Original**
>> Yes. >> So, uh, first of all, thanks everybody for being here for an incredibly long day. We started this thing early this morning and, uh, we had speaker after speaker after speaker after speaker and then we had about a two and a half hour break and they came back to see you. So, uh, >> I've been up since 1:00 at >> So, this guy, [applause] this guy is on the tail end of a two week trip and four or five different cities in Asia. Uh, >> one day ago was in Taiwan. Last night I was in Houston. Here I am. [laughter] >> But he's been gone two weeks and we're standing [clears throat] between him and
## 00:07:22
**中文**
他自己家里的床之间——相对于酒店的床。所以我们会玩得开心，然后让他赶紧回去。不过，你其实不太需要介绍；谢谢你来到这里，伙计，我们真的非常感谢。——感谢你们的合作关系，我也真的为你们感到骄傲。
**English / Original**
his his personal bed versus a hotel. So, we're gonna >> we're going to have fun and then we're going to we're going to get him out of here. So, uh >> but uh you don't you don't need much of an introduction, but thank you for being here, man. We [clears throat] really appreciate it. >> Thanks for our partnership and really proud of you guys.
## 00:07:39
**中文**
——那我们就从这里开始。我们一直保持合作，而你提出了“AI 工厂”这个完整概念，我们也在共同推进。在企业领域，它的进展可能没有我们双方希望的那么快；但能否先谈谈，在你看来，AI 工厂是什么？——是这样。首先，请记住：这是 60 年来我们第一次重塑计算。过去是显式编程：我们编写程序，变量通过 API 传递，一切都非常明确；现在则转向……
**English / Original**
>> So, let let's let's start with uh let's start with that. We we have had a partnership and you you introduced this whole concept of AI factories and we're working on this together. It's probably not going as fast as either one of us would like in the in the enterprise space, but can we start by talking about what what do you what is an AI factory to you? Is that so? First of all, remember we're reinventing computing for the first time in 60 years. What used to be explicit programming, right? We wrote the programs and the variables that's passed through APIs and are very explicit to
## 00:08:19
**中文**
隐式编程。现在你只需告诉计算机你的意图，它就会自行出发，弄清如何解决你的问题。从显式到隐式，从本质上以计算为主的通用计算到人工智能，整个计算栈都被重新发明了。人们谈论计算时会说处理层在哪里——那正是我们所在的层。但请记住计算究竟是什么：其中有计算和处理，也有存储、网络与安全；我们说话的此刻，这一切都正在被重塑。所以……
**English / Original**
implicit programming. You now tell the computer what your intent is and it goes off and and it figures out um how to solve your problem. So from explicit to implicit uh from general purpose computing basically calculation to artificial intelligence the entire computing stack has been reinvented. Now people talk about computing u where the processing layer is which is where we are but remember what computing is there's computing there's the processing but there's storage networking and security all that is being reinvented as we speak and so the
## 00:09:00
**中文**
第一部分是，我们需要把 AI 发展到真正对人有用的程度，稍后我们还会谈到这一点。到目前为止，聊天机器人是你给它一个提示，它便想出该告诉你什么；这很有趣，也令人好奇，但并不实用。——有时能帮我做完填字游戏。
**English / Original**
first part the first part is we need to develop AI to a level and we'll talk about that we need to develop AI to a level that is useful to people And until now, uh, chatbots, where you give it a prompt and it figures out what to tell you, um, is interesting and curious but not useful. >> Helps me finish crossword puzzles sometimes.
## 00:09:26
**中文**
——是的，但它只能处理已经记忆并泛化过的东西。回到最初——其实距 ChatGPT 出现真的才三年——当时我们惊叹：“天哪，它能生成这么多文字，甚至能创作莎士比亚式的内容。”但这一切都建立在它记忆和泛化过的事物上。我们知道，智能在于解决问题；解决问题部分在于知道自己不知道什么，部分在于推理如何解决一个从未见过的问题。
**English / Original**
>> Yes. And and, uh, but only only on things that it had memorized and generalized. So if you look go back in the beginning of I mean it's a little little literally only three years ago when chatbt emerged uh that that we thought oh my gosh it's able to generate all these words it's able to to create Shakespeare um but it's all based on things that it memorized and generalized and but we know that intelligence is about solving problems and solving problems is partly about knowing what you don't know uh partly about reasoning ing uh how to solve a problem you've never seen before.
## 00:10:07
**中文**
把问题拆成你很容易解决的元素，再通过组合解决从未见过的问题；还要提出执行任务的策略，也就是我们所说的计划：寻求帮助、使用工具、开展研究，等等。如今在“智能体 AI”的术语中，这些都是你们听过的基本能力，对吧？例如工具使用、研究……
**English / Original**
Breaking it down into elements that you know how to solve very easily so that in its composition that you're able to solve problems that you've never seen before and um uh to come up with a strategy what we call plan to to perform in a task. ask for help, use tools, do research, so on so forth. These are all fundamental things that now in the in the in the in the phrasiology of agentic AI, you've heard, isn't that right? tool use, research,
## 00:10:46
**中文**
还有检索增强生成——以事实为依据——以及记忆。这些都是你们在讨论智能体 AI 时开始听到的概念。但重要的是，要从采用显式编程的通用计算演进过来——我们过去用 Fortran、C、C++ 编程。——COBOL。——没错。——那可是好东西，Chuck，真是好东西。——那是我的退路工作。——好东西，真是好东西。——那是少数仍然很有价值的技能之一。——我知道。——对，我知道。
**English / Original**
uh, uh, retrieval, augmented generation, which is grounded on facts, um, memory. These are all things that that all of you in the in the context of talking about agentic AI, uh, you're starting to hear. But the important thing the important thing is in order to evolve from general purpose computing which is explicit programming we wrote in forran we wrote in C we wrote in C++ >> cobalt >> to that's right >> that's good stuff that's good stuff Chuck that's good stuff >> it's my fall it's my fallback job >> that's good stuff that's good stuff >> yeah that's one of those that's one of those skills that remains valuable >> I know >> yeah I know
## 00:11:29
**中文**
——它一直很有价值。——我收到了很多邀约。——恐龙永远有价值。——我们刚刚确认你比我年长。——我知道，而我属于史前时代。［笑声］——看起来不像，但确实如此。［欢呼与掌声］——好吧，这句挺妙。我可能是这个房间里年龄最大的人。
**English / Original**
>> that it remains valuable >> I've got a lot offers. >> Dinosaurs are valuable forever. >> We just established that you're older than me. >> I know. And I'm I'm the prehistoric. [laughter] >> It doesn't appear so, but it's true. [cheering and applause] >> All right, that was pretty good. I'm the only Probably the oldest person in this room.
## 00:12:03
**中文**
那么我们稍微谈谈：当你思考……——我们现在走到了这里。我去找 Chuck，说：“听着，我们需要重新发明计算，Cisco 必须成为其中的重要组成部分。”我们将推出全新的完整计算栈 Vera Rubin，Cisco 将与我们共同将其推向市场。这是计算层；同时还有网络层。Cisco 会整合我们的 AI 网络技术，但把它放进 Cisco Nexus 的控制平面，因此从你们的角度看，既能获得 AI 的全部性能，也能获得 Cisco 的可控性、安全性和……
**English / Original**
So how do you so let's talk a little bit about like as you as you think about the >> so so here we are uh I went to Chuck and I say hey listen uh we need to reinvent computing and Cisco's got to be a big part of it and so we've got we've got um uh we have a new new whole computing stack coming out Vera Rubin >> and uh Cisco is going to be ting market with us on on that and so that the computing layer but there's also the networking layer And um Cisco is going to uh integrate uh AI networking technology from us but put it into the Cisco Nexus plane control plane so that so that uh from your perspective you're going to get all the performance of AI but in the controllability and security and the
## 00:12:46
**中文**
可管理性。我们也会在安全方面采取同样做法。每一根支柱都必须被重新发明，企业计算才能利用它。不过最终——希望稍后还能回到这一点——为什么三年前企业 AI 尚未准备就绪，而今天你们却别无选择，必须尽快参与？不要落后。
**English / Original**
manageability of Cisco >> we're going to do the same thing with security and um and so each one of these pillars has to be reinvented so that so that enterprise computing could take advantage of it. But the but but ultimately and we'll come back to this hopefully that that um you know why is it that enterprise AI wasn't ready three years ago and why it is that you have no choice but to get engaged as quickly as you can. Okay. Don't don't fall behind.
## 00:13:15
**中文**
我认为，企业不必成为第一家利用 AI 的公司，但不要成为最后一家。——是的。嗯。如果你今天经营一家企业，你建议它为做好准备采取的第一、第二、第三步是什么？——人们会问我投资回报率之类的问题，我不会从那里入手。原因是，在所有技术部署的早期，都很难把一种新工具、新技术的投资回报率放进电子表格里计算。我会先找出……
**English / Original**
I think there's you don't have to be the first company to take advantage of AI but don't be the last. >> Yeah. Mhm. So if you're an enterprise today, what what's your recommendation on the first, second, third step they should take to begin to get ready? >> Well, I get questions like things like ROI and and um I I wouldn't I wouldn't go there. And the reason for that is because because um with all technology deployments in the beginning, it's hard to put into a spreadsheet um the ROI of of a new tool, a new technology. Um but what I would do is I would go find out what is the single
## 00:13:57
**中文**
我们公司最重要的是什么？公司的本质是什么？
**English / Original**
most what is the essence of my company?
## 00:13:59
**中文**
我们公司最具影响力的工作是什么？不要在边缘事务上浪费时间。我们公司就是让千花齐放；公司里的不同 AI 项目多得已经失控，而这很好。注意我刚才说的是：它失控了，而且很好。创新并不总是处于控制之中。如果你想一切尽在掌控，首先你得去接受心理治疗。
**English / Original**
What's the most impactful work that we do in our company? Don't don't mess around don't mess around with with peripheral stuff. I mean, in our company, we have we just let a thousand flowers bloom. We the number of different AI projects in our company is it's out of control and it's great. It notice I just said something. It's out of control and it's great. Innovation is not always in control. If you want to be in control, first of all, you got to seek therapy.
## 00:14:31
**中文**
其次，那是一种幻觉：你并没有掌控一切。如果希望公司成功，你就不可能控制它；你可以影响它，却无法控制它。因此我认为，第一，太多人、太多公司希望一切明确、具体，还要有可证明的投资回报率。
**English / Original**
But second, it's a it's a it's an illusion. you're not in control. If you want your company to succeed, you can't control it. You want to influence it, you don't can't control it. And so I think number one, um, too many people want too many companies I hear, they want it, they want it, they want us explicit. They want it specific. They want demonstrable ROI.
## 00:14:55
**中文**
而一件值得做的事情，在初期很难证明其价值。我的建议是让千花齐放，让人们试验，并让他们安全地试验。我们公司在尝试各种东西：Anthropic、Codex、Gemini，什么都用。当某个团队说“我想使用这个 AI”时，我的第一个回答是“可以”。我先说可以，再问为什么，而不是先问为什么、再决定是否同意。因为我希望公司得到的，和我希望孩子得到的一样：去探索生活。
**English / Original**
And, you know, showing the value of something worth doing in the beginning is hard. Um, but what I would do, what what I would say is that let a thousand flowers bloom. Let people experiment. Let the people experiment safely. And we're we're experimenting with all kinds of stuff in the company. We use Anthropic, we use Codeex, we use, you know, we use Gemini, we use everything. And and when a when one of our group says I'm interested in using this AI, my first answer is yes. And I ask why instead of why then yes. I say yes, then why. And the reason for that is because I want I want the same thing for for my company that I want for my kids. go explore life.
## 00:15:36
**中文**
他们说想尝试某件事，答案就是“可以”。然后他们会问为什么。你不会说：“先向我证明，做这件事未来一定会带来财务成功或某种幸福。证明给我看；在证明之前，我不会让你做。”我们在家里从不这样做，在工作中却会这样。
**English / Original**
They say they want to try something. The answer is yes. And then they say how come? You don't go prove it to me. Prove to me that doing this very thing is going to lead to financial success or some happiness someday. Prove to me. And until you prove it to me, I'm not going to let you do it. We never do that at home, but we do it at work.
## 00:16:01
**中文**
你明白我的意思吗？——明白。——在我看来这毫无道理。所以无论是 AI，还是此前的互联网、云，我们的做法都是先让千花齐放。到某个时点，你必须用自己的判断开始打理花园，因为千花齐放会让花园变得杂乱。但最终必须开始筛选，找出最好的方法或最佳平台，把所有资源集中到一支箭上；只是不能太早把全部资源押在一支箭上。
**English / Original**
Do you know what I'm saying? >> Yeah. It makes no sense to me. And so the way that we we treat AI and and and whether it's AI or the internet before or cloud before, just let a thousand flowers bloom. And then at some point, you have to use your own judgment to figure out when to start curating the garden >> because a thousand flowers bloom makes for a messy garden. But at some point you have to start curating to find what's the best approach or what's the best platform what's so that you could put all your wood behind one arrow. But you don't want to put all your wood behind one arrow too soon.
## 00:16:36
**中文**
——否则你可能选错箭。所以先让千花齐放，之后再筛选。作为参照，我现在还没开始筛选，到处都在千花齐放；但我鼓励每个人去尝试。不过，我非常清楚什么对公司最重要，当然清楚。公司的本质是什么？最重要的工作是什么？我确保有大量专长与能力集中于用 AI 革新这些工作。对我们而言，就是芯片设计、软件工程和系统工程。你们可能注意到，我们与……
**English / Original**
>> You pick the wrong arrow. So let thousand flowers bloom. At some point you curate. And so I haven't started curating yet just to put in perspective. I've got a thousand flowers bloom everywhere. But I encourage everybody to try. However, I know exactly what is most important to our company. Of course, I of course I do. What is the essence of our company? What are the most important work of our company? And I make sure that I've got a lot of expertise and a lot of capability focused on using AI to revolutionize that work. In our case, chip design, software engineering, system engineering. Notice you might have noticed that that that we partnered with
## 00:17:18
**中文**
Synopsys、Cadence、Siemens，以及今天的 Dassault Systèmes 建立了合作，以便把我们的技术嵌入进去；他们想要多少技术，我就注入多少。无论他们想要什么、需要什么，我都会提供，以革新我们用于设计产品的工具。——嗯。——我们到处使用 Synopsys、Cadence、Siemens 和 Dassault Systèmes。我会确保他们得到所需资源的百分之一千，让我拥有创造下一代产品所必需的工具。所以这说明了……
**English / Original**
Synopsis and Cadence and Seammens and today DO so that we could insert our technology and infuse as much technology as they want. Whatever they want, whatever they need, I will provide so that I could revolutionize the tools by which we use to design what we do. Mhm. >> We use synopsis everywhere. We use we use cadence everywhere. We use seammens everywhere. Use the so everywhere. I will make sure that they have a,000% of whatever they want so that I have the tools necessary so I could create the next generation. And so so that tells
## 00:17:59
**中文**
我如何看待自己最重视的事，以及我会怎样革新自己的工作。想想 AI 做了什么：AI 将智能成本降低了几个数量级，或者说创造了极大丰富的智能。这也意味着，过去需要一个单位时间完成的事——过去需要一年完成的事——现在可能一天就能完成。
**English / Original**
you something about how I my attitude about about uh what's most important to me and what I would do to revolutionize my own work. Think about think about think about what AI does. AI reduces the cost of intelligence or create the abundance of intelligence by orders of magnitude. That's another way of saying what we used to do that takes you know one unit of time. Now what what we used to to take a year could take a day now.
## 00:18:33
**中文**
过去花一年做的事，现在可能一小时即可完成，甚至能实时完成。原因在于我们身处一个丰裕的世界。摩尔定律？天哪，那太慢了，简直像蜗牛。记得吗？摩尔定律是每 18 个月翻一倍，每五年增长十倍，每十年增长一百倍。
**English / Original**
What we used to take take a year could take an hour. It could it could be done in real time. And the reason for that is because we are in the world of abundance. Moore's law, goodness gracious, that was slow. That's like snails. Remember Moore's law was two times every 18 months, 10 times every 5 years, a 100 times every 10.
## 00:18:57
**中文**
好，那现在是什么水平？每十年增长一百万倍。过去十年，AI 进步如此之大，以至于工程师会说：“嘿，你猜怎么着？何不用全世界的数据训练一个 AI 模型？”他们的意思不是“收集一下我硬盘上的所有数据”，而是“把全世界的数据都下载下来，训练一个 AI 模型”。这就是丰裕的定义。
**English / Original**
Okay. But where are we now? A million times every 10 years. In the last 10 years, we advanced AI so so far that engineers said, "Hey, guess what? Why don't we just train an AI model on all of the world's data?" They didn't mean, "Let's just collect all the the data from my disc drive. Let's just let's pull down all of the world's data and let's train an IM model." That's the definition of abundance.
## 00:19:28
**中文**
丰裕的定义是：看着一个巨大无比的问题，你说，“知道吗，我要全部解决。”我要治愈所有类别的疾病，而不只是癌症。你在开玩笑吗？那太疯狂了。我们要解决人类所有的苦难。这就是丰裕。如今思考工程和问题时，我会假定自己的技术、工具、仪器和飞船具有无限速度。
**English / Original**
The definition of abundance is you look at a problem so big and you say, you know what, I'll do it all. I'm going to cure every field of disease. I'm not going to just do cancer. Are you kidding me? That's insane. We'll just do all of human suffering. That's abundance. Um, when I think about engineering, when I think about a problem these days, I just assume my technology, my tool, my instrument, my spaceship is infinitely fast.
## 00:19:59
**中文**
去纽约需要多久？一秒就到。那么，如果一秒就能到纽约，我会采取什么不同做法？如果某件事过去要一年，现在却能实时完成，我会怎么做？如果某样东西过去很重，现在却像处于反重力状态，又会怎样？
**English / Original**
How long is it going to take for me to go to New York? I'll be there in a second. So, what would I do different if I can get to New York in a second? What would I do different if something used to take a year and then now takes real time? What would I do different if something, you know, used to weigh a lot and now it's just anti-gravity?
## 00:20:23
**中文**
所以你应以这种心态对待一切。当你这样做时，就是在运用 AI 思维。明白吗？例如，我们合作的很多公司都在做图分析，处理关系和依赖。这些图拥有极多的边与节点——数以万亿计。过去你只能把图切成小块来处理；如今，直接把整个图给我。
**English / Original**
And so, you approach everything with that attitude. When you approach everything with that attitude, you are applying AI sensibility. Does that make sense? For example, there are many companies that we're working with where the graph analytics, the dependency, the relationships and dependencies that you know these graphs, they have so many edges, so many nodes and edges, trillions of them. Back in the old days, you would you would process a graph, small pieces of it. These days, just give me the whole graph.
## 00:20:55
**中文**
它有多大？我不在乎。这种思维正在应用于各个领域。如果你没有采用这种思维，那就是做错了。速度重要吗？完全不重要，因为你处在光速。质量呢？你处在零重量、零重力状态。如果某件事过去不是难到疯狂，而你现在却能说“啊，不重要了”，但你没有应用这种逻辑……
**English / Original**
How big is it? I don't care. That sensibility is being applied everywhere. If you're not applying that sensibility, you're doing it wrong. If speed matters, not at all. You're at the speed of light. If mass is you're at zero weight, zero gravity. If you're not applying that logic, if this something is not insanely hard to you in the past and you go, "Ah, doesn't matter."
## 00:21:23
**中文**
那你就没做对。现在想象一下，把这种逻辑、这种思维应用于公司最棘手的问题，这才会带来实质性改变。其他人都是这样思考的。如果你没有这样思考，只需想象你的竞争对手正在这样思考；再想象一家即将成立的新公司正在这样思考。
**English / Original**
If you're not applying that logic, you're not doing it right. Now imagine you apply that logic, that sensibility to the hardest problems in your company. That's how you're going to move the needle. And that's how they all think. Now the people who are If you're not thinking that way, just all you have to do just imagine your competitors thinking that way. If you're not thinking that way, just imagine a company who is about to get founded is thinking that way.
## 00:21:49
**中文**
这会改变一切。因此，我会找出公司里影响最大的工作，对它应用“无限”、应用“零”、应用“光速”，然后问 Chuck 如何实现。［笑声］——不，我们就来谈谈如何实现。你有一个比喻……——直接打给我就好。——我们会打给你。
**English / Original**
It changes everything. And so I would go find where are the most impactful work in your company. Apply infinity to it. Apply zero to it. Apply the speed of light to it. And then ask Chuck how to make that happen. [laughter] >> No, let's talk about how to make that happen. So you have this analogy of >> Just call me. I'll >> We'll call you.
## 00:22:16
**中文**
——我们会一起做，一起做。你有一个“五层蛋糕”的比喻，因为大家都在谈基础设施、模型、应用。我应该怎样着手？请稍微谈谈。——成功人士会做的一件事，是推理某件事的本质：这里究竟发生了什么？大约 15 年前，一种算法在两位工程师手中解决了一个计算机视觉问题。
**English / Original**
>> We'll do it together. We'll do it together. you you have this analogy this five layer cake because everybody's talking about like infrastructure models apps I mean how do I how do I go about it talk about that a little bit >> well the first you know one of the things that that successful people do is they reason about what is something you know what's what's happening here so so almost 15 years ago um an algorithm uh was able to with two engineers um solve a computer vision problem.
## 00:22:53
**中文**
计算机视觉基本上是智能的第一部分——感知。智能包括感知、推理和规划。感知是：我是什么？正在发生什么？我的情境是什么？推理是：如何理解它？如何把它与目标比较？第三是提出解决方案、制定计划以实现目标。比如战斗机问题：感知、定位，然后行动。所以智能关乎这三件事。没有感知，就不可能有第二和第三部分；不理解情境，就无法弄清该……
**English / Original**
Computer vision is basically the first part of intelligence perception. Intelligence is perception, reasoning, planning. Perception, what am I? What what's going on? What's my context? Reasoning. How do I reason about how do I compare this to my goals? And then three, come up with a plan to solve that to achieve that. Okay. And so that's so you know for example the jet fighter problem you know perception localization and then and then action. And so so intelligence is about those three things. You can't have the second and third part without perception. You can't understand you can't figure out what to
## 00:23:34
**中文**
做什么。而情境高度多模态：有时是一份 PDF，有时是电子表格，有时是信息，有时只是感官和气味。我们在哪里？正在做什么？受众是谁？等等。还要能读懂现场气氛，诸如此类，对吧？
**English / Original**
do without understanding context. And context is highly multimodal. Sometimes it's a PDF sometimes is a spreadsheet. Sometimes it's information. Sometimes just you know senses and smells. You know what what where are we? What are we doing here? who's the audience, you know, so on and so forth. Reading the room, you know, so on so forth, right?
## 00:23:51
**中文**
这就是感知。大约十三四年前，我们在计算机视觉上实现了巨大飞跃，而计算机视觉是感知问题的第一层。这个问题极其困难：到底怎样解决计算机视觉？AlexNet 是我们看到的首个突破，像是人类与 AI 的“第一次接触”——我很喜欢那部电影《接触未来》。我们做的是问：这意味着什么？为什么两位工程师竟能战胜……
**English / Original**
And so that's about that's about perception. And so about about 13 14 years ago, we made a huge gigantic leap in computer vision, which is the p the first layer of the perception problem. And it was super hard, you know, how do you solve computer vision? and Alex Net and the first um the first breakthrough that we saw. It was kind of like the the first contact, you know, I love that movie, the first contact, you know, it was like our first contact to AI and and the thing that we did was we said, okay, what does that mean? How is it possible that two engineers was able to overcome
## 00:24:31
**中文**
我们所有人研究了约 30 年的算法？Ilya Sutskever——我昨天还和他谈过——以及 Alex Krizhevsky，这两个年轻人为什么能用几块 GPU 解决问题？这意味着什么？于是我们把问题彻底拆解。十年前我对此进行推理，得出的结论是：世界上多数可以解决、看似无法解决的难题，其实都能通过这种方式解决。原因是，世界上多数难题、多数最有价值的……
**English / Original**
the algorithms that were that we worked all of us worked on for some 30 years? you know, and Ilia Suscober, I talked to him yesterday, and and Alex Kashevsky and and uh how is it possible two kids with a couple of GPUs solve this problem? What does it mean? And so, we broke it all down and I reasoned about it a decade ago and I came to the conclusion that in fact most of the hard problems in the world that can be solved can be can't be solved can be solved this way. And the reason for that is most of the hard problems in the world, most of the most of the valuable
## 00:25:10
**中文**
问题，并不存在基于第一性原理的算法。没有 F=ma，没有麦克斯韦方程、薛定谔方程、欧姆定律，也没有某个热力学定律；它没有那么明确。最有价值的东西大多被我们称为直觉和智慧。Chuck，你我面对的那类问题，答案通常是“视情况而定”。你明白吧？如果答案是 3 就太好了；如果是 3.14，那更棒。
**English / Original**
problems have no no principled algorithms. There's no F= ma. There's no Maxwell's equation. There's no Schroingers equation. There's, you know, there's no Ohms law. There's no, it just doesn't exist. There's no law of thermodynamics. It's not that specific. most of the valuable things that we call intuition and wisdom and it's all you know the problems that you know you Chuck that the type of problems that you and I get the answer is it depends do you know what I'm talking about you know if it was if it was three it'd be great it was 3.14 it'd be fantastic
## 00:25:51
**中文**
那些才是好问题。但人生中多数难题、最有价值的问题，答案都是“视情况而定”，因为它取决于情境和处境。大约十二三年前，计算机视觉得到了解决；我们判断，由于深度学习，这套方法可以扩展，模型能够越来越大。只剩下一个问题：如何训练模型？重大突破是自监督学习或无监督学习——AI 自己设定目标并自行学习。
**English / Original**
okay those are those are the great ones but most of the hard problems in life most of the valuable problems in life are it depends because it depends depends on the context. It depends on a circumstance context and so so 12 years ago 13 years ago something like yeah um computer vision was solved and so we reasoned that in fact this could be scalable because of deep learning and you can make the models larger and larger and there was only one problem we had to solve which is how do we train that model and the big breakthrough was self-supervised learning or unsupervised learning self AI is that goal and learns
## 00:26:31
**中文**
请注意，今天我们早已不再受数据标注限制，甚至差得很远。这个突破打开了闸门，让模型从几百个参数、数亿参数扩展到数十亿乃至数万亿参数。我们可以编码的知识量、可以通过算法学会的技能数量，都出现了巨大增长；但基本方法并未改变。我们据此推断，计算将被全面重塑——这也是我们对话开头所说的——我们要重新发明……
**English / Original**
by itself. And and notice today we're not limited by labeling anymore. [clears throat] We're not limit not even close. And so that breakthrough opened up the floodgates for us to scale these models from a a few hundred parameters, a few hundred million parameters to billions to trillions. And the amount of knowledge we can codify, the number of skills we can learn algorithmically, you know, really largely exploded. But the basic approach was the same. And we reasoned that in fact, we're going to reinvent and is the beginning of our conversation. We're going to reinvent
## 00:27:10
**中文**
整个计算，从显式编程转向一种全新的计算方式：模型和软件将通过学习获得。再退一步，这对计算栈意味着什么？对软件开发意味着什么？公司里的工程组织会发生什么变化？定义产品的产品营销团队会怎样？把产品编码实现的工程团队会怎样？评估产品的 QA 团队又会怎样？未来这些产品本身会变成什么？我们如何部署产品？如何让它……
**English / Original**
computing altogether from from explicit programming to a new way of of doing computing where the models the software will be learned. Now what happens what does that mean if you take another step back and you go okay what does that mean to the computing stack? What does it mean to what does it mean to how you develop software? What does happen to the engineering organization in your company? What happens to the to the product marketing team that specifies the product? What happens to the engineering team that codifies the product? What happens to the the QA team that evaluates the product? What do these products even become someday? How do we deploy the product? How do we keep
## 00:27:50
**中文**
保持最新？如果它基于机器学习、在持续学习，又如何让它永远保持更新？怎样给软件打补丁？等等。关于未来计算，我问过的“如何”问题大概有上千个。最终我和公司都得出结论：这将改变一切。因此我们基于这一核心信念，推动整家公司转型。
**English / Original**
it up to date? If you're learning it in if it's based on machine learning, how do you keep it refreshed [clears throat] forever? Um how how do you patch software? And so how do you you know so on so forth? The number of hows I asked about about the future computing, you know, must have been a thousand questions and and I came to the conclusion, our company came to the conclusion that this is going to change everything. And so we pivoted the whole company based on that core belief.
## 00:28:20
**中文**
简单来说，Chuck 的意思是，我们来自一个一切都预先录制好的世界。Chuck 当年开发的软件……——那可是非常好的东西。——它运行了很久。郑重声明，确实如此；它甚至在希伯来文中就已有描述。［笑声］——这是真的。——那又是另一项技能。我的意思是……
**English / Original**
Simplistically, what Chuck is saying is that we came from a world where everything was pre-recorded. The software that Chuck worked on. >> Really good stuff. >> It It ran a very long time. Just for the record, >> it was indeed it was it was it was described in the Hebrew. [laughter] >> That is true. >> That was another skill. I mean,
## 00:29:00
**中文**
——这个房间里只有他既懂希伯来语又懂 COBOL。总之，［笑声］那一切都是预先录制的。我们设计并描述算法，也就是描述自己的想法，再把随附的数据放进去；一切都预先写好。过去的软件之所以预先录制，是因为它装在 CD-ROM 里。
**English / Original**
>> the only person in the room that knows Hebrew cobalt and so anyways anyways [laughter] anyways anyways that that was pre-recorded. We engineer we described our algorith. to describe our thoughts and then we put we put data that goes along with it. It's everything is pre-recorded. The reason why it's pre-recorded, the reason why you know software in the past was pre-recorded is because it came in a CDROM.
## 00:29:24
**中文**
——对吧？——是的。——它是预先录制的。那么今天的软件是什么？它具有情境性和动态性；每个情境不同，每个软件用户不同，每条提示不同，你给出的前置条件、先验信息和情境也不同。软件的每次实例运行都不一样。过去所需的计算只是读取预先录制的内容，所以叫作“基于检索”。
**English / Original**
>> Isn't that right? >> Yes. >> It was pre-recorded. Okay. What is software now? because it's contextual dynamic >> and every context is different and every time everybody who uses the software is different and every prompt is different and all the and the pre the precursor you give it the priors you give it the context is different. Every single instance of the software is different which is the reason why the amount of computation necessary in the past which is pre-recorded is called retrievalbased.
## 00:30:04
**中文**
观察自己就知道：使用手机时，你触碰某处，它就去检索某个软件、文件或图像，再呈现给你。未来一切都会像现在这样由生成而来。这场对话从未发生过；其中的概念和先验信息以前存在，但这个序列中的每一个词从未以同样方式出现过。
**English / Original**
All you have to do is check yourself. When you use your phone you touch something it went and retrieved some software some files some images and brought it to you. In the future, everything is gonna be generative just like is happening right now. This conversation has never happened before. The concepts existed before. The priors existed before, but every single word in this sequence has never happened before.
## 00:30:32
**中文**
而原因显然是，我们已经喝了四杯葡萄酒。——COBOL 和希伯来语从没一起出现过。——冷萃咖啡。对，COBOL、希伯来语。不。——谢天谢地，这不是在园区里，也没有直播。——对，对。——好，我们……——你明白我的意思吗？所以结果是……——你明白自己在说什么吗？
**English / Original**
And the reason for that is obviously we're four wines in >> cobalt and Hebrew have never come out of the >> cold brew. Yes. Cobalt, Hebrew. No. >> Thank goodness this is not on campus >> or being streamed. >> Yeah. Yeah. >> All right. Let's let's let's >> Do you do you understand what I'm saying? And so as a result as a result >> Do you understand what you're saying?
## 00:31:04
**中文**
［笑声］Chuck 今天到现在为止唯一喂给我的，就是四杯葡萄酒。——公平地说，我只给了你其中一杯，另外三杯是你从自助餐台拿的。——我一直盯着食物，说：“我太饿了，就一直看着那些食物。”它们始终离我大约 40 英尺。——因为你当时在拍照。
**English / Original**
[laughter] The only thing that Chuck has fed me today so far is four glasses of wine. And >> to be fair, I only fed you. I fed you one of them. You took the other three off the buffet. >> I was I was eyeing the food. I was like, "So, I'm so hungry. I'm eyeing the food." It was forever about 40 feet away from me. It's >> cuz you were taking photos.
## 00:31:33
**中文**
——但我就是觉得，太近了，太近了。［笑声］有一次我真的向食物倾了过去，却又被推了回来。［笑声］——你知道发生了什么吗？你的团队提前告诉我们：给他喝三杯葡萄酒，他会达到最佳状态；如果让他喝下第四杯，就会精彩绝伦。
**English / Original**
>> But it was I was like, it was so close. It was so close. [laughter] And I I actually leaned towards the food one time, but I was pushed back again. [laughter] >> You know what? You know what happened? Your team your your team actually told us ahead of time, if you get three glasses of wine in, he's optimal. >> If you get the fourth one in, it's going to be incredible.
## 00:31:54
**中文**
——现在是次优状态。总之，听着，听着。AI 是什么？我们总得留下一点智慧。——能再来一杯葡萄酒吗？——这不只是 Dave Chappelle 式的段子。——好，我们谈点事情，再谈一件。——能源。——芯片。
**English / Original**
>> This is suboptimal. So anyways, anyways, anyways, listen, listen, listen, listen. So what is AI? We have to leave some wisdom behind. >> Can we get another glass of wine, please? >> This is not >> This is not just Dave Chappelle stuff. >> Okay, let's talk about something. Let's talk about one other thing. >> Energy. >> That chips.
## 00:32:22
**中文**
——能源听起来不错。——能源、芯片、基础设施，包括硬件与软件；再上面是 AI 模型。但 AI 最重要的部分是应用。对每个国家、每家公司而言，下面所有层都只是基础设施。你们需要做的是应用这项技术。看在老天的分上，用起来吧。使用 AI 的公司不会陷入危险；危险的是那些不使用它的公司。你不会因为 AI 而输掉……
**English / Original**
>> Energy sounds good. >> Energy, chips, infrastructure, both hardware and software. Then the AI model. But the most important part of AI is applications. every single country, every single company, all that layer underneath is just infrastructural stuff. What you need to do is apply the technology. For God's sakes, apply the technology. A company that uses AI will not be in peril. It's the company who, you know, you're not going to lose it.
## 00:32:56
**中文**
你的工作；你会把工作输给使用 AI 的人。——所以赶紧行动，这是最重要的。——然后尽快给 Chuck 打电话。——你打给我，我再打给他。明白。——我们的时间不多了，所以我不确定……——我们拥有全世界所有的时间。
**English / Original**
You're not going to lose your job to AI. You're going to lose your job to someone who uses AI. >> So, get to it. That's the most important thing. Yeah. >> And call Chuck as soon as possible. >> You call me, I'll call him. Yeah. Got it. >> So, we don't have a lot of time, so I'm not sure. >> We got all the time in the world.
## 00:33:12
**中文**
——真的吗？——还有多少？——你看，Chuck 做事盯着时间，他按时钟来建设；我甚至不戴表。——看看。——Chuck……——我这里记着时间。——对，我们进展很好。你让人按时钟做事。——没错。——我不一样，价值没有交付我就不走。［掌声］——看吧。——哪怕需要整晚，我也不会……嘿，我要折磨你们所有人，直到……——Jensen，这就是我们这种人需要手表的原因。［笑声］——好吧，你能……——直到你们可以说自己学到了……
**English / Original**
>> Do we? >> How much? >> Look, look, Chuck. Chuck like he runs. He builds on the clock. I don't even wear a watch. >> Look at that. >> Look at that. Chuck, >> I got you right here. >> Yeah. Yeah. We're doing great. You build people on the clock. Oh, yeah. Not me. I'm not leaving until value's delivered. [applause] >> See, >> if it takes all night, I'm not Hey, look, I'm going to torture all of you until >> Jensen. That's why guys like me need a watch. [laughter] >> All right. Can you Can you >> Until you could say that you learned
## 00:33:55
**中文**
东西，否则你们就会被困在这里。——对，我们要折磨大家，直到交付价值。——我确认过了，还有葡萄酒。你能不能谈谈目前对物理 AI 最关注的想法？——还记得软件是什么吗？软件是一种工具。现在有一种说法，工具行业正在衰退，并会被 AI 取代。
**English / Original**
something, you're you are going to be trapped in here. >> Yeah. We're going to torture everybody until value is delivered. >> I did check there is more wine. Um, can you just give us your top of mind on physical AI? Remember what remember what software is? Software is a tool. There's this notion that the tool industry is in decline and will be replaced by AI.
## 00:34:28
**中文**
你能看出来，因为许多软件公司的股价承受巨大压力，仿佛 AI 会取代它们。这是世上最不合逻辑的事，时间最终会证明。让我们做一个终极思想实验：假设我们拥有终极 AI——人工通用机器人，也就是终极 AI 的物理版本。
**English / Original**
You could tell because there's a whole bunch of software companies whose stock prices are under a lot of pressure >> because somehow AI is going to replace them. It is the most illogical thing in the world and time will prove itself. Let's just give it let's give ourselves the the ultimate thought experiment. Suppose we are the ultimate AI artificial general robotics. The ultimate AI the physical version of us.
## 00:34:57
**中文**
当然，它能解决任何问题，因为它具有人形并且能够行动。如果你是一台人形机器人，你会直接使用螺丝刀，还是重新发明一种螺丝刀？我会直接用现成的。你会用锤子还是重新发明锤子？会用链锯还是重新发明链锯？不会重新发明。首先，理想情况下它们根本不使用链锯。但你明白我的意思吗？如果你是人形机器人，是人工通用机器人，你会使用工具还是重新发明工具？
**English / Original**
You could of course solve any problem because you know you're humanoid. You could do things. If you were a human or robot, would you use a use a screwdriver or invent a new screwdriver? I would just use one. Would you use a hammer or invent a new hammer? Would you use a chainsaw or invent a new chainsaw? It just don't. First of all, ideally they don't use it at all. But but do you understand what I'm saying? If you were a human or robot, artificial general robotics, would you use tools or reinvent tools?
## 00:35:36
**中文**
答案显然是使用工具。现在再看它的数字版本：如果你是人工通用智能，会使用 ServiceNow、SAP、Cadence、Synopsys 这样的工具，还是重新发明一台计算器？当然会直接使用计算器。这就是 AI 最新突破集中于什么的原因：工具使用。
**English / Original**
The answer obviously is to use tools. And so now do the digital version of that. If you were a artificial general intelligence, would you use the tools like Service Now and SAP and Cadence and Synopsis or would you reinvent a calculator. Of course, you would just use a calculator. That's the reason why the latest breakthroughs in AI is what? Tool use.
## 00:36:07
**中文**
因为工具被设计成明确、精确地工作。我们的世界有很多问题遵循 F=ma，拜托不要再给它提出另一个版本。［笑声］——F 不是“大致等于”ma，它就是 ma。还有 V=IR，不是“大致是”IR，不是“近似”或“统计意义上的”IR，它就是 IR。明白我的意思吗？所以我认为，我们希望人工通用机器人和人工通用智能使用工具。
**English / Original**
Because the tools are designed to be explicit. There are many problems in our world where F equals MA. Please could you please not come up with another version? [laughter] >> FA is not kind of MA. >> It's just [clears throat] MA. Do you guys Oh, V equals IR. It's not kind of IR. You know, approximately IR, statistically IR, it is IR. Okay, do you understand what I'm saying? And so, so I I think we want the artificial general robotics, artificial general intelligence to use tools.
## 00:36:47
**中文**
这就是核心理念。我认为下一代物理 AI 将理解物理世界，理解因果关系：如果我推倒这个，它会把那些也都撞倒。它们要理解多米诺骨牌的概念。注意，一个孩子能够理解推倒一块骨牌意味着什么；多米诺骨牌这个概念极其深刻。
**English / Original**
Well, that's the big idea. I think that that in the next generation of physical AI, we're going to have AIs that understand the physical world, understand causality. If I tip this over, it's going to tip all of that over. They understand the concept of a domino. Just the concept of a domino, notice a child understands if you tip that over, the concept of the domino is extremely in it's like deeply profound.
## 00:37:14
**中文**
因果关系、接触、重力和质量，全都融入了推倒多米诺骨牌这件事。一个很小的骨牌可以推倒更大的骨牌，再推倒更大的，最终另一端甚至是一吨重的东西；孩子理解这个概念毫不费力，大语言模型却完全不懂。
**English / Original**
the co causality, contact, gravity, mass, all of that is integrated into a domino. Tipping dominoes over. The idea that you could have a little tiny domino, tip a larger domino, tip a larger domino, tip a larger domino to the point where there's a ton on the other side, a child has no trouble with that concept. A large language model will have no idea.
## 00:37:39
**中文**
所以我们必须教会它，必须创造一种新的物理 AI。机会在哪里？迄今为止，Chuck 和我所在的行业一直在制造工具，我们一辈子都在做螺丝刀和锤子的生意。历史上第一次，我们将创造人们所说的“劳动力”，更准确地说，是增强型劳动力。
**English / Original**
And so we have to teach, we have to create a new type of physical AI. Well, what's the opportunity? So far, the industry that Chuck and I have been part of is about creating tools. We have been in the screwdriver hammer business. Our entire life has been about creating screwdrivers and hammers. For the first time in history, we are going to create what people call labor, but augmented labor.
## 00:38:10
**中文**
举个例子：自动驾驶汽车是什么？它是数字司机。数字司机值多少钱？很多，远比汽车本身值钱。原因在于，在数字司机的整个使用寿命中，其经济价值远大于汽车。我们第一次面对一个大 100 倍的总体可寻址市场；从数学上说，这确实如此。
**English / Original**
Give you an example. What is a self-driving car? What's a digital chauffeur? What's a digital chauffeur valued at? A lot. A lot more than the car. And the reason for that is because in the lifetime of the digital chauffeur, the economics of the dig digital chauffeur is a lot more than the car. For the very first time, we are exposed to a TAM that is 100 times larger. Literally mathematically true.
## 00:38:44
**中文**
IT 产业大约是一万亿美元，对吧？上下浮动几万亿。但全球经济约为一百万亿美元。我们第一次将触及全部经济。因此，今天在这个房间里的每个人，都有机会应用这项技术，把自己的公司变成科技公司。
**English / Original**
The IT industry is about a trillion dollars, right? Or so plus or minus a couple. And yet the e the economy of the world is about hundred trillion dollars. For the very first time, we're going to be exposed to all of that. So it is the it is the case that all of you all of you everybody in in this room today you have the opportunity to apply this technology to become a technology company.
## 00:39:11
**中文**
举几个例子。我非常喜欢 Disney，也喜欢与 Disney 合作，但我很确定它宁愿成为 Netflix。我喜欢 Mercedes，今天也是坐 Mercedes 来的，但我确信它宁愿成为 Tesla。我喜欢 Walmart，也确信它宁愿成为 Amazon。到目前为止大家同意吗？三个例子都说中了吗？
**English / Original**
Let me give you some examples. I really believe as much as I look I love Disney and we I love working with Disney. I'm pretty sure they'd rather be Netflix. I love Mercedes. I came in a Mercedes. I am certain they'd rather be Tesla. I love Walmart. I am certain they'd rather be Amazon. Do you guys agree so far? Am I three for three?
## 00:39:45
**中文**
——你们所有人都是如此。我相信，我们有机会帮助每家公司转变成科技公司：科技优先。科技是你的超级能力，而行业领域是你的应用；而不是反过来——把行业领域当作自己的身份，再四处寻找技术。原因在于，科技优先的公司处理的是电子，而不是原子。
**English / Original**
>> All of you are that way. I believe that we have an opportunity to help transform every single company into a technology company. Technology first. Technology first. Technology is your superpower and the domain is your application versus the other way which is the domain is who you are and you're seeking for technology. And the reason that's so, the reason that's so is because companies who are technology first, you're dealing with electrons, not atoms.
## 00:40:25
**中文**
电子多得多；原子则受质量限制。这就是为什么一旦从 CD-ROM 转向电子形态，公司的价值会暴增一千倍。你们需要像我们一样，成为一家电子公司——换句话说，就是科技公司。我认为机会已经来到你们面前。另一种思考方式是 AI，正如我们前面所说。
**English / Original**
And electrons, there's a lot more of them. Atoms, you're limited by mass, which is the reason why the moment they went from CDROMs to electrons, the value of the company exploded by a thousand times. you need to be like us, an electron, an an electronics company, electron company, which is another way of saying a technology company. And so I I think that that the opportunity for you is here. Another way to think about that is AI and we just said it earlier.
## 00:41:05
**中文**
甚至 Chuck——他只会用希伯来语编程。［笑声］——这是一种天赋。他选择的编程工具是从右向左书写，［笑声］因为你们知道，否则墨迹会被抹花。——其实还挺聪明。——聪明人会做聪明事。——对。所以美妙之处在于……
**English / Original**
Even Chuck, who only knows how to program in Hebrew, >> [laughter] >> It's a gift. His instrument choice is a right to left [laughter] because as you know it smears otherwise. >> It is pretty smart actually. >> Smart people do smart things. >> Yeah. And so so the beautiful thing is that as you know
## 00:41:46
**中文**
对于全世界的编程语言以及你们所有公司而言，你们可能觉得：“天哪，软件不是我们的强项。”但知识、直觉和领域专长正是你们的强项。历史上第一次，你现在可以用自己的语言，向计算机准确解释自己想要什么。还记得我们从哪里开始吗？从显式编程转向隐式编程。
**English / Original**
the programming language of the world and for all of your companies you kind of feel like oh my gosh you know software is not our strength but knowledge intuition domain expertise is your strength. Well you get to you now for the first time can explain exactly what you want to a computer in your language. Do you remember where we started from explicit programming to implicit programming?
## 00:42:12
**中文**
历史上第一次，你可以用隐式方式给计算机编程：只需告诉它你想要什么、表达的是什么意思，计算机就会编写代码。因为事实证明，编码只是打字，而打字已经商品化。这正是你们的巨大机会。你们所有人都可以升到过去那些原子层面限制之上，也可以摆脱“软件工程师不够多”这一限制，因为事实证明，打字是一种……
**English / Original**
For first time in history, you could program a computer implicitly. Just tell it what you want. Tell it what you mean and the computer will write the code because coding as it turns out is just typing. And typing as it turns out is a commodity. And that's the great opportunity for you. All of you could be levitated above the atomic limitations that you were limited by before. All of you could escape from this limitation which is we don't have enough software engineers because as it turns out typing is a
## 00:42:52
**中文**
商品。而你们拥有极有价值的东西：领域专长，理解客户，也理解问题。这才是终极价值——理解意图。你知道，一个人刚从大学毕业时可能是超级程序员，却完全不知道客户想要什么，也不知道该解决什么问题。但这些正是你们知道的：你们知道客户想要什么，也知道要解决什么问题。
**English / Original**
commodity. And all of you have something of great value which is domain expertise to understand the customer, understand the problem. And that is the ultimate value. That is the ultimate value to understand the intent. You know, as you know, when you graduate from software software, when you graduate from college, you could be a super programmer, but you have no idea what customers want. You have no idea what problems to solve. But that's what all of you know. You know what customers want. You know what problems to solve.
## 00:43:28
**中文**
编码部分很容易，告诉 AI 去做就行了。所以领域专长就是你们的超级能力。Chuck 和我来这里，就是要让你们能够做到这一点。这段总结是在我喝了五杯葡萄酒之后完成的。［笑声］——听着，这确实是个奇迹。——一个靠桌子工作的人，真正展现了人工智能。［掌声］——也许这是“增强智能”。我只想告诉大家，能与你们合作是莫大的荣幸。
**English / Original**
The coding part of it is easy. just tell the AI to do it. And so that's your superpower. So Chuck and I are here to enable you to do that. That closing was done with five glasses of wine in me. [laughter] So >> hey, listen. as it's a miracle indeed >> between this is somebody who works off a table true representation of artificial intelligence [applause] >> maybe that's enhanced I just want to tell you that that it's a great pleasure
## 00:44:09
**中文**
Cisco 拥有极其深厚的专长，覆盖计算发明中的两大重要支柱。没有 Cisco，就没有现代计算：一根支柱当然是网络，另一根是安全。在 AI 世界里，这两根支柱都已被重新发明。我们非常熟悉的计算部分在许多方面已成为商品，而 Cisco 所掌握的东西则具有深层价值。我们两家公司携手，会很乐意帮助大家进入……
**English / Original**
working with all of you um Cisco as you know has extreme extreme expertise and two very important pillars of the invention of computing. Without Cisco, there is no modern computing. One of them is of course supports networking and the other one's security. And those both of those pillars have been reinvented in the world of AI. And the part that we know very well which is the computing part of it in a lot of ways is a commodity and the the the stuff that that Cisco knows is deeply valuable and between the two of us we're going to you know we'll be delighted to help all of you uh engage
## 00:44:51
**中文**
AI 世界。早些时候有人问我一个问题，我认为值得重复：应该只租用云端资源，还是也值得花力气自建计算机？我的建议与我给孩子的建议完全相同：自己组装一台计算机。
**English / Original**
the world of AI. And then somebody asked me earlier and just I just said you know I think it's worth repeating. Somebody asked me earlier, should you do should you do just rent the cloud or should you even make the effort to to u uh build your own computer? Here here's what I I would tell you. I would advise you to do exactly the same thing I advise my children. Build a computer.
## 00:45:17
**中文**
即使 PC 无处不在、市场已经成熟、技术已经发展完善，看在老天的分上，也请亲手组装一台，弄明白所有部件。如果你要进入汽车业或交通运输业，不要只会使用 Uber；打开引擎盖，换一次机油，了解所有部件。务必弄懂它如何工作。
**English / Original**
Even though the PC is everywhere, even though it's mature, even though technology is developed, for God's sakes, build one. know why all the components exist. If you were to to to uh be in the world of automotive, the automobile industry, the transportation industry, don't just use Uber. For God's sakes, lift the hood, change the oil, understand all the components. For God's sakes, understand how it works.
## 00:45:46
**中文**
这至关重要。这项技术对未来太重要了，你必须对它有一些亲手操作的理解。打开引擎盖，换机油，亲手造点东西；不必很大，造点东西即可。你也许会发现自己极其擅长，也许会发现自己需要这种技能，还可能发现世界并非只有“全部租用”与“全部自有”两种选择。你会想租用一部分、拥有一部分，因为公司中的某些部分应在本地部署。
**English / Original**
It is vital. This technology is so important to the future. You must have some tactile tactile understanding of it. Lift the hood, change the oil, build something. Doesn't have to be large. Build something. You might discover you're actually insanely good at it. You might discover that you need that skill. You might discover that the world is not about all rent versus all own. that you want to rent some and own some because some part of your company should be built on prem.
## 00:46:25
**中文**
例如，为了主权和专有信息；又或者，你就是不愿意与所有人共享自己提出的问题。举个概念性的例子：去见心理治疗师时，你不会希望自己问的问题出现在网上。［笑声］明白我的意思吗？
**English / Original**
For example, sovereignty and proprietary information and just you just you're not comfortable you're not comfortable sharing your questions with everybody. You know the reason why I've never I this is a conceptual example. You know that when you go see a therapist, you don't want the questions to be online. >> [laughter] >> you know, you know what I'm saying?
## 00:46:52
**中文**
——好，我只是想象一下这种情况。［笑声］——纯属假设。假设来说，我认为你的许多问题、对话、讨论和不确定性都应该保密。公司也是如此。我没有信心，也没有安全感把 Nvidia 的所有对话都放进云端，所以我们在本地构建了系统。
**English / Original**
Okay, I'm just >> I'm imagining this one. [laughter] >> Okay, hypothetically. >> And so, hypothetically, I I think that a lot of questions you have, a lot of conversations you have, a lot of dialogue, a lot of uncertainties you have ought to be kept private. Companies are the same way. I am not confident. I am not secure about putting all of Nvidia's conversations in the cloud, which is the reason why we built it locally.
## 00:47:20
**中文**
我们在本地构建了一套超级 AI 系统，因为我实在不愿共享这些对话。事实证明，对我来说，最有价值的知识产权不是答案，而是问题。明白吗？我的问题才是最宝贵的知识产权；我正在思考的，就是我的问题。答案已经商品化。
**English / Original**
We've built a super AI system locally because I'm just not confident to share that conversation because conversa my as it turns out the most valuable IP to me is not my answers. It's they're my questions. Are you following me? My questions are the most valuable IP to me. What I'm thinking about are my questions. The answers are a commodity.
## 00:47:48
**中文**
只要知道该问什么，我就在识别什么最重要。我不希望别人知道我认为什么重要。我希望这些内容留在一间小屋里，留在本地，只属于我自己；我还想创建自己的 AI。既然已经 11 点了，再说最后一个想法。［笑声］过去有一种观点，认为 AI 应当始终让人处于环路中。这个想法完全错误，恰好说反了。
**English / Original**
If I simply knew what to ask. I'm identifying what's important. And I don't want people to know what I think is important. And I want that to be in a small room. I want that to be on prem. I want that to be by myself. And I want to create my own AI. And then one last thought since it's already 11 o'clock. [laughter] One last thought. There was an idea that AI should always have have human in the loop. It's exactly the wrong idea. It's backwards.
## 00:48:27
**中文**
每家公司都应该让 AI 处于环路中。原因是，我们希望公司每天都变得更好、更有价值、更有知识；永远不想倒退，不想停滞，也不想每次从头开始。这意味着，只要 AI 在环路中，它就能捕捉我们的生活与工作经验。
**English / Original**
Every company should have AI in the loop. And the reason for that is because we want our company to be better and more valuable and more knowledgeable every single day. We never want to go backwards. We never want to go flat. We never want to start from the beginning. Which means that if we have AI in the loop, it will capture our life experience.
## 00:48:52
**中文**
未来每一位员工都会让 AI——许多个 AI——处于工作环路中，而这些 AI 会成为公司的知识产权。这就是未来的公司。因此我认为，大家立即给 Chuck 打电话是明智之举。——我已经给 Jensen 打了电话。［笑声］——总之，这就是我的结语。——听着，在路上奔波了两周……
**English / Original**
Every single employee in the future will have AI, lots of AIs in the loop. And those AIs will become the company's intellectual property. That's the future company. And therefore, I think it sensible for all of you to call Chuck immediately. >> I called Jensen. [laughter] >> Anyhow, that's my closing. >> Listen, let's uh two weeks on the road.
## 00:49:25
**中文**
Jensen 专程飞到这里，在终于能久违地睡回自己家里的床之前，把旅程的最后一个晚上留给了我们。我们永远心怀感激，谢谢你来到这里。——非常感谢。还有……［掌声］——谢谢你，伙计。——还有……［掌声］我用眼角余光看到那边有好多烤串。
**English / Original**
Jensen flew here, spent his last night, last evening with us before he gets to sleep in his bed for the first time in a long time. We're forever grateful. Appreciate you being here. Thank you. >> Thank you very much. And I I [applause] >> Thank you, man. >> And and and [applause] from the corner of my eye, there were all these skewers.
## 00:49:51
**中文**
——还有人在那里。——那袋 Fritos 玉米片在哪里？［笑声］——好了，我们走吧。谢谢，谢谢大家。——谢谢你们……嘿，
**English / Original**
>> Somebody was still there. >> Where's the bag of Fritos? >> [laughter] >> All right, let's go. Thank you. Thank you everybody. >> Thank you for Hey,
## 00:50:39
**中文**
嘿，嘿。热起来。热起来。
**English / Original**
hey, hey. Heat. Heat.
## 00:51:33
**中文**
嘿。
**English / Original**
Hey,