联想大事件！杨元庆对话黄仁勋：看好这一新赛道（附全文）

发布时间：2025-04-24　点此：1153次

一觉醒来，联想搞起多件大事，首款AI PC展现，还牵手英伟达和AMD等芯片“顶流”。在美国举行的Lenovo Tech World2023上，联想出展现了首款AI PC，并称“个人电脑迎来全新的向阳”。叠加华为小米等手机厂商也在抢滩AI换机潮，未来每个人都能在终端具有自己的模型，或成为新趋向。在完成“从口袋到云端”核算才能的路上，联想“朋友圈”露脸。当日，联想与英伟达、AMD等巨子宣告战略协作。其间，杨元庆与黄仁勋联合发布严重方案，推出混合人工智能处理方案。在杨、黄对话环节，黄仁勋对轿车核算、AIGC等论题的观念和观点，更全面的展现出来。

“未来的个人电脑将是AI PC”

美国时刻10月24日，联想集团Tech World 2023开幕，主题为“AI for All”，展现出联想对人工智能全面进击、推进人工智能规模化落地的情绪和方向。联想集团董事长兼CEO杨元庆在现场展现了被联想视为“革新性产品”的AI PC。经过建个性化的本地常识库，经过模型紧缩技能，它能够运转个人大模型，完成AI天然交互。杨元庆以为，智能设备好比是赛车，它是人工智能触达终端用户的终极载体。“联想的大模型紧缩技能能让用户自己的智能终端和设备具有运转个人级大模型的才能。未来的个人电脑将是AI PC，未来的手机将是人工智能手机，未来的作业站将是人工智能作业站。”联想高档副总裁及智能设备事务集团总裁LucaRossi介绍，一年前，联想就现已把AI算法放入PC设备。未来在CPU根底上，联想PC还要引进NPU，完成更好办理AI作业量、提高功用、操控电池耗费等意图。个人模型方面，NPU的引进也能大大提高AI才能。AI PC能够带来哪些改变呢？比方，经过个人常识库，能够完成智能化行程组织，预订旅行航班、协助创立表格文档等。与运用其他软件比较，由所以放在端侧，更具有隐私性、安全性。因而，AI PC能为隐私和数据保驾护航。详细形式怎样？联想的个人AI Twin经过键盘上的AI交互和用户的天然言语、以及名为AI NOW的新概念功用来完成，这是针对AI PC 的个人AI帮手处理方案。从背面支撑来看，在这些支撑人工智能功用的设备和边际设备上，将建有本地常识库，更好地了解用户。个人大模型将运用存储在设备或家庭服务器上的个人数据进行推理。除非用户授权，不然用户的个人数据永久不会被同享或发送至公有云，然后保证了个人隐私和数据安全。它乃至能够依据个人的思想形式猜测使命，并自主寻觅处理方案。由此，设备就好像是用户的数字延伸，就像用户的双胞胎（AI Twin）相同。联想AI PC，并不只是单纯的硬件AI，软件也会有很大效果。一方面，联想在研制自己的大模型，另一方面也或许会有其他厂商的大模型引进。公司方面承受e公司记者采访时泄漏，现在还暂未考虑AI PC所带来的盈利形式重构问题。AI PC与没有加载AI的个人电脑比较，是一个高端产品。至于价格，公司方面没有能够给出详细数字，只是表明“价格还要取决于装备”。虽然进行了现场展现，不过联想清晰，AI PC本年无法问世，约下一年9月前后正式推向商场，且后续会不断进化焕新。从工业逻辑来看，PC商场十分老练。消费电子周期崎岖，疫情期间，全球PC商场曾到达近些年高峰，可是尔后也一度接连多季度跌落，苹果等头部玩家的出货量也呈现下滑。现在商场的共同判别是，PC商场正在呈现复苏向好。个人电脑出货量环比在曩昔两个季度均有所增加，其间第三季度环比增加11%。据Luca介绍，现在联想PC途径库存现已优化，而AI PC虽然短期不会成为干流，但也有望带来价格中枢上移。这有望推进PC商场的量价“双击”。

消费电子都在快上大模型

生成式AI、大言语模型对不少工业都带来“灯塔式指引”，但人工智能真实落地，离不开硬件和设备的负载。实际上，除了AI PC之外，在AI大势之下，作为用户量最广、用户粘性最高的智能终端，手机更是成为AI大爆炸大遍及的榜首载体。近一年来，包含华为、小米、OPPO、荣耀在内的我国智能手机职业参与者，都已高调入局大模型。以小米为例，其大模型技能的主力打破方向是轻量化和本地布置，现在小米自研的13 亿参数端侧模型现已在手机端跑通了 Demo，并且部分场景效果能够比美 60 亿模型在云端的运算效果。这折射出消费电子厂商在大模型方面“端云一体”“端云协同”的新趋势。我国信通院相关人士此前承受e公司记者采访时曾表明，假如能够在端侧模型处理的部分才能或许部分功用，就没有必要上升到云端去；假如在调用大模型的进程中需求用到更多信息和功用，就需求结合云端才能。杨元庆以为，要打造全景式的人工智能，“从口袋到云端”的核算才能, 多种形状的运用都是咱们所需求的，而不同职业的处理方案也十分要害。与此一起，人们既喜爱公共大模型答复问题的功用，又常常期望问出的问题和得到的答案只是留存在自己的设备上或企业内部。关于怎么能够做到“既要-也要”的问题，他给出的答案是，将公共大模型和个人大模型，以及企业级大模型相结合。

“朋友圈”顶流

微软、NVIDIA、英特尔、AMD、高通等全球尖端AI科技公司CEO同日都参加了这次大会。其间，环绕设备、根底设施和处理方案范畴，联想与多家顶流之间还宣告了多项战略协作。在智能化处理方案范畴，联想集团将个人人工智能双胞胎和企业级人工智能双胞胎的相关愿景，构建进与微软的未来处理方案中。在根底设施范畴，联想集团与NVIDIA协作推出新的混合人工智能方案。此外，联想还与英特尔携手推进AI在客户端、边际、网络和云端的一切作业负载上的规模化运用。联想集团与AMD在智能设备、根底设施和处理方案等方面持续严密协作。一起，高通正在发力具有数十亿参数的生成式人工智能模型，使联想产品能够为用户的生产力和创造力供给更多支撑。最受重视的仍是杨元庆与黄仁勋发布的严重方案——推出混合人工智能处理方案。这意味着，作为英伟达的商场协作伙伴，联想将供给根据NVIDIA MGX架构的新的企业级AI处理方案、联想混合人工智能服务及其他从层面的服务。这些处理方案使企业能够选用混合云办法——经过NVIDIA AI Foundation云服务构建自定义人工智能模型，然后由NVIDIA最新的生成式人工智能规划的硬件设备和软件驱动的联想本地体系运转它们。杨元庆介绍，在与NVIDIA的严密协作下，联想将供给彻底集成的体系，将人工智能驱动的算力引进数据生成的各个当地，从边际到云端，协助企业轻松布置定制化的生成式人工智能运用，推进创新和转型，掩盖千行百业。此外值得重视的是，大会现场，杨元庆与黄仁勋进行了一场深度对话。论题环绕轿车核算、AIGC等论题打开。黄仁勋表明，继此前25年的相识、协作之后，英伟达和联想还要备战下一个25年的协作。黄仁勋在对话中泄漏，交通运输业将前所未有地成为一个核算机工业；关于AIGC，他以为，需求创立根底设施和处理方案仓库，使每个公司都有或许获益于人工智能。附：杨元庆（YY）与黄仁勋（Jensen Huang）对话全文YY: So Jensen, I know our media friend here have a lot of questions for you. But today, I want to try to ask you some questions on behalf of that, they can tell me so whether I’m a good interview or not. How about that?元庆：Jensen，我知道咱们的媒体朋友有许多问题要问你。今日，我想试着代表他们问你一些问题，他们能够告诉我，我是否是一个好的发问者。怎么样？So definitely, my first question is about the vehicle computing. We have worked on that for quite a while to capture the opportunity, although it's not what we want to focus today, but we really want to hear from you. So, what's your perspective on future vehicle computing?我的榜首个问题是关于车核算的。咱们现已在这一范畴尽力了很长时刻，以捉住这个时机，虽然这不是咱们今日要点重视的，但咱们真的很想听听你的定见。你对未来轿车核算的观点是什么呢？Jensen Huang: The largest industry in the world is transportation, and it is about to become a computer industry for the very first time. So what's inside the computer? What's inside the car used to be engines and electronic parts, but in the future is gonna be a computer. And so this is gonna be one gigantic new market for the computer industry. And it's terrific that Lenovo is going to be part of it with your heritage and building extraordinary computers. You'll be able to bring that to the automotive industry.黄仁勋：世界上最大的工业是交通运输业，现在它将前所未有地成为一个核算机工业。那么电脑里边是什么？轿车里曾经是发动机和电子零件，但在将来，轿车里边会是一台电脑。因而，这关于核算机职业来说是一个极端巨大的全新商场。联想对此早已布局并打造特殊的核算机，这真是太棒了。你将能够把核算机带到轿车职业。YY: Thank you, Jensen. Beyond vehicle computing, we collaborate broadly in workstation, gaming pc, high performance computer, now extending into AI and smart infrastructure. Recently, definitely, the hottest topic is Chat-GPT. NVIDIA has had such an important role enabling this new era. You have been the leader of AI for more than a decade. So could you share with us your insight on generative AI particularly what's the prospect of its applications?元庆：谢谢你，Jensen。除了车载核算，咱们还在作业站、游戏pc、高功用核算机方面进行广泛协作，现在已扩展到人工智能和智能根底设施范畴。最近，最抢手的论题无疑是Chat-GPT。NVIDIA在使能AI新时代发挥了重要的效果。十多年来，你一向是人工智能的领导者。那么，你能和咱们共享一下你对生成式人工智能的见地吗？特别是它的运用远景怎么？Jensen Huang: We saw some pretty cool examples of generative AI just now in the demos. But when you take a step back and think about what happened in the last decade, several very important inventions were discovered. For the very first time, a computer could write software that no humans can, that requires AI infrastructure, a new type of computing infrastructure. This is the largest time expansion in the history of our partnership. We've been working together now for 25 years. Yes. Could you imagine YY and me 25 years ago? So it's been a very, very long ago.黄仁勋：咱们刚才在演示中看到了一些生成式人工智能的十分酷的比如。当你退一步考虑曩昔十年产生的作业时，你会发现一些十分重要的创造呈现了。人类历史上初次，核算机能够编写人类无法编写的软件，这需求人工智能根底设施，一种新式的核算根底设施。这是咱们最为持久的协作。咱们现已协作了25年了。你能幻想25年前的元庆和我吗？这是很久曾经的事了。Over the years, we've worked on workstations and laptops and servers and super computers. The most energy efficient super computers in the world are powered by NVIDIA and Lenovo. Now, there's a brand new type of computer. I call it AI factory. This AI factory is a dedicated computing infrastructure with the super computers that we build that are dedicated to optimize artificial intelligence. This AI factory has a singular purpose. It takes raw material data that comes into it, and a process it and refines it with a great deal of processing, and it outputs intelligence.多年来，咱们一向致力于打造作业站、笔记本电脑、服务器和超级核算机。世界上最节能的超级核算机由NVIDIA和联想携手打造。现在，有一种全新的电脑，我称之为AI工厂。这个AI工厂是一个专门的核算根底设施，配套着咱们制作的专门用于优化人工智能的超级核算机。这个AI工厂仅有一个单一意图，行将进入其间的原始数据进行处理，并经过很多处理进行提炼，输出智能。Now, a decade ago, the type of intelligence we were able to produce was understanding the meaning of the data, understanding speech, understanding images, understanding the meaning of the data. But now, for the very first time, you saw some examples of that, just a second ago, we are able to generate data.十年前，咱们能够制作的智能是了解数据的意义，了解语音，了解图画，了解数据的意义。但现在，就在一秒钟前，你榜初次看到了一些这样的比如，咱们能够生成数据。Now, the ability for a computer do not only understand data of all kinds, unstructured all kinds. It could be words and sounds and pixel images, and it could be proteins and chemicals. It could be a motion, whatever information could be digitized. Computers now have the ability to understand the meaning of it. What is the meaning that's embedded in the data? Now we can generate it. And this revolution started in the cloud, but it's now one of the biggest opportunities is for us to bring it to the enterprise. And the reason for that is because the vast majority of the world's data is embedded in enterprises. It is for us, that data is confidential as proprietary, is intensely sensitive, for some people is regulated and unable to move to the cloud.现在，核算机的才能不只是是了解各种数据，各种非结构化的数据。它可所以单词、声响和像素图画，也可所以蛋白质和化学物质，可所以一个运动，任何信息都能够数字化。核算机现在有才能了解它的意义。数据中的意义是什么？现在咱们能够生成它了。这场革新始于云，现在最大的时机之一是咱们将它带到企业中。由于世界上绝大多数数据都嵌入在企业中。数据是保密的，是十分灵敏的，关于有些人来说是遭到监管的，且无法转移到云端。And so what we need to do is to create the infrastructure as well as the solution stack that makes it possible for every company to be able to take advantage of artificial intelligence. It includes four parts. We have a back here showing you there are four parts. The first part is the pre-trained models. We call that AI foundation. These foundational models are in our cloud, and they're optimized to deliver the most performance that could be as interactive as possible as well as most cost efficient. These models are quite large process, and the faster we can process it, the lower the cost.因而，咱们需求做的是创立根底设施和处理方案仓库，使每个公司都有或许获益于人工智能。咱们向您展现了四个部分。榜首部分是预练习模型，咱们称之为人工智能根底。这些根底模型在咱们的云中，它们经过优化，能够供给尽或许交互式和最具本钱效益的最佳功用。这些模型需求适当巨大的进程，咱们处理得越快，本钱就越低。The second thing is how do we take this AI model, which fundamentally is kind of like a brain, but it doesn't really do anything unless you turn it into an application. One of the things you hear plenty about in the near future. And surely in this conference is the notion called a retrieval augmented generation. It's another way of saying creating a chat bot and this chat bot has the ability that's augmented by data that's yours. We now have the capability to vectorizer, turn this database into a semantic database, not a relational database, not an unstructured database, but a semantic database, a database that understands meaning. You could talk to this database, ask questions, and because it understands the words that you're using, and it understands the meaning of the data that's inside the storage and the vector database. It has the ability now to respond in a way that makes sense to you.第二部分是咱们怎么看待这个人工智能模型，它本质上有点像大脑，但除非你把它变成一个运用程序，不然它什么都不会做。这是你在不久的将来常常听到的作业之一，有一个概念被称为检索增强生成（RAG）。这是创立谈天机器人的另一种说法，这个谈天机器人的功用能够经过你的数据得到强化。咱们现在有才能矢量化，把这个数据库变成一个语义数据库，不是联系数据库，不对错结构化数据库，而是语义数据库，一个能够了解意义的数据库。你能够与这个数据库攀谈，提出问题，由于它能了解你正在运用的单词，也了解存储和向量数据库中数据的意义。它现在有才能以一种你能了解的方法做出回应。The second component is what is called a RAG, a retrieval augmented generative models. We can take this application, this new form of enterprise application, which is about assembling AIs. This is the way applications will be built in the future. We assemble the AIs. Instead of writing code or writing SQL queries, we're gonna assemble AIs like we assemble teams. And these AIs will perform all kinds of things. They'll perform things like customer service. It'll help you create marketing campaigns. It'll monitor all the activities in and out of your company to detect fraud. One of my favorite examples is talking to data. You'll be able to talk to your storage, whatever you have in your PC. You'll be able to talk to data.第二个组成部分是所谓的RAG，一种检索增强生成模型。咱们能够选用这种新形式的企业运用程序来整合AI的。这便是未来构建运用程序的方法，咱们将像整合团队相同整合AI，而不是经过编写代码或编写SQL言语。这些AI将履行各式各样的作业，他们会做客户服务之类的作业，协助您创立营销活动，监控您公司表里的一切活动以发现诈骗行为。我最喜欢的比如之一是与数据沟通，你将能够与你的存储设备对话，不管你的电脑里有什么。RAG has the ability to create all kinds of applications. It now needs to run On-Prem. This is where our partnership with Lenovo really comes in. The first part is the operating system. We've been working with VMware. VMware is an operating system enterprise, 500,000 enterprises around the world uses VMware. We've been working with VMware to turn that operating system, which was originally designed for virtualization, which is now designed for artificial intelligence. And it's called VMware private AI we've been working on it for some 4 years. And that operating system runs on a run TAM (unclear) called and NVIDIA AI enterprise. That run TAM does all of the data processing, all the deep learning, all of everything from training, fine tuning, to guard railing, all the way to inference and deployment of the models. That entire stack runs on a Lenovo Think Server that we've been working on together. These are the four components, the four parts of our partnership, taking generative AI to the world's enterprise.RAG具有创立各种运用程序的才能，它现在需求On-Prem上运转。这便是与联想协作真实发挥效果的当地。榜首部分是操作体系。咱们一向在与VMware协作，全球约有50万家企业运用VMware。咱们与VMware协作，将开端规划用于虚拟化的操作体系转变为用于人工智能的操作体系,它被称为VMware私有人工智能，咱们现已研讨了大约4年。该操作体系运转在一个名为和NVIDIA AI Enterprise的TAM上。TAM完成了一切的数据处理、一切的深度学习，从练习、微调到防护栏杆，一向到模型的揣度和布置。整个仓库运转在咱们一向在协作的联想服务器上。这是咱们协作伙伴联系的四个组成部分，将生成式人工智能带入世界各地的企业。YY: Yeah, Jenson. I 100 % agree with you. So I believe more generative AI application will happen in enterprise space. My second question is, how can we partner to bring generative AI to more vertical industries and enterprises?元庆：是的，Jensen。我百分之百赞同你的观点。因而，我信赖更多的生成式人工智能运用将呈现在企业范畴。我的第二个问题是，咱们应怎么协作将生成式人工智能带给更多笔直职业和企业？Jensen Huang: There are four components. There's the pre-trained model, the knowledge of how to build these applications. How do you vectorize the databases? How do you put some semantic features into databases? How do you create these applications out of generative AI. And how do you deploy it? Installing and implementing the operating system, knowing how to orchestrate these workloads and then running it in your data center? I can't imagine a better partnership than the two of us, where the knowledge and the technologies and the reach of the world's markets from transportation to health care, to financial services. The reach of the world's markets is so broad with the Lenovo team, the combination between us, we can bring this technology that just by everybody.黄仁勋：共有四个组成部分。这里有预练习模型，以及怎么构建这些运用程序的常识。怎么对数据库进行矢量化？怎么将一些语义特征放入数据库？怎么从生成式人工智能中创立这些运用程序？怎么布置、装置和运转操作体系，怎么和谐这些作业负载，然后在数据中心中运转它。我想不出有比咱们两个更好的协作伙伴了，咱们的常识和技能以及在世界商场的影响力，从交通到医疗保健，再到金融服务。有了联想团队整个世界商场是如此宽广，经过咱们的结合能够把这项技能带给一切人。YY: Yeah, so Jensen, I'm so happy to take our partnership to the next level. So today, actually, we are very excited to announce a new joint hybrid AI initiative. We want to bring the next generation of cloud AI technology to enterprise everywhere. That means as your time to market partner, Lenovo will deliver new enterprise AI solutions, based on NVIDIA MGX architecture, Lenovo hybrid AI services and so much more.元庆：是的，Jensen，我很快乐能把咱们的协作联系提高到一个新的水平。事实上，今日咱们十分兴奋地宣告一项新的混合人工智能联合建议。咱们期望将下一代云人工智能技能带到各地的企业中。这意味着，作为你的协作伙伴，联想将供给根据NVIDIA MGX架构、联想混合人工智能服务等的全新的企业级人工智能处理方案。Jensen Huang: That's right. This is one of the major pillars of Lenovo vision and strategy of AI for all. It's terrific.黄仁勋：没错。这是联想“AI for All”人工智能愿景和战略的首要支柱之一。太棒了。YY: Thank you, Jensen. For your trust and great partnership. Let's continue to unleash the power of AI to drive innovation and transformation, starting from celebrating this hybrid AI initiative.元庆：谢谢你，Jensen。感谢您的信赖和杰出的协作伙伴联系。让咱们从庆祝这一建议开端，持续开释人工智能的力气，推进创新和转型。Jensen Huang: Thank you YY. For the next 25 years.黄仁勋：谢谢YY，也为了接下来的25年。

责编：张骞爻校正：彭其华

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