Name: Nvidia 的 Jensen Huang 和 Meta 的 Mark Zuckerberg 在 Siggraph 上談論人工智能：9 分鐘瞭解一切 (Nvidia's Jensen Huang & Meta's Mark Zuckerberg Talk AI at Siggraph: Everything in 9 Minutes)
Uploaded: 2024-07-31T02:52:54.000Z
Duration: 9 min 3 s

馬克，歡迎你第一次參加 SIGGRAPH！

現在進行式

How do you see the advances of generative AI at Meta today, and how do you apply it to either enhance your operations or introduce new capabilities that you're offering?

您如何看待生成式人工智能在 Meta 目前所取得的進步，以及您是如何將其應用於加強營運或推出新功能的？

With generative AI, I think we're going to quickly move into the zone where not only is the majority of the content that you see today on Instagram just recommended to you from stuff that's out there in the world that matches your interests and whether or not you follow the people,

有了生成式人工智能，我認為我們將很快進入這樣一個領域：不僅你今天在 Instagram 上看到的大部分內容都是根據你的興趣推薦給你的，而且無論你是否關注這些人、

I think in the future a lot of this stuff is going to be created with these tools too.

我認為，將來很多東西也會用這些工具來製作。

Some of that is going to be creators using the tools to create new content, some of it I think eventually is going to be content that's either created on the fly for you or kind of pulled together and synthesized through different things that are out there.

其中一些將由創作者使用工具來創建新的內容，還有一些我認為最終將由內容創建者為你即時創建，或者通過現有的不同內容整合在一起。

I kind of dream of one day you can almost imagine all of Facebook or Instagram being a single AI model that has unified all these different content types and systems together that actually have different objectives over different time frames.

我夢想有一天，你幾乎可以想象所有的 Facebook 或 Instagram 都是一個單一的人工智能模型，它將所有這些不同的內容類型和系統統一在一起，在不同的時間範圍內實現不同的目標。

Some of it is just showing you what's the interesting content that you want to see today, but some of it is helping you build out your network over the long term, people you may know or accounts you might want to follow.

有些只是向你展示你今天想看的有趣內容，但有些是幫助你建立長期的網絡，你可能認識的人或你可能想關注的賬戶。

These multimodal models tend to be much better at recognizing patterns, weak signals and such.

這些多模態模型在識別模式、弱信號等方面往往更勝一籌。

It's so interesting that AI has been so deep in your company.

人工智能已經深入貴公司，這太有意思了。

You've been building GPU infrastructure, running these large recommender systems for a long time.

你們構建 GPU 基礎設施、運行這些大型推薦系統已經有很長一段時間了。

I'm a little slow on it actually, getting to GPUs.

實際上，在 GPU 方面我做得有點慢。

Tell everybody about the Creator AI and AI Studio that's going to enable you to do that.

告訴大家，Creator AI 和 AI Studio 可以讓你們做到這一點。

We've talked about it a bit, but we're rolling it out a lot wider today.

我們已經談了一些，但今天我們要在更大範圍內推廣。

A lot of our vision is that I don't think there's just going to be one AI model.

我們的很多願景是，我認為不會只有一種人工智能模式。

This is something that some of the other companies in the industry, they're building one central agent.

業內的其他一些公司正在建立一箇中央代理。

We'll have the MetAI assistant that you can use, but a lot of our vision is that we want to empower all the people who use our products to basically create agents for themselves.

我們會有一個 MetAI 助手，你可以使用它，但我們的很多願景是，我們希望讓所有使用我們產品的人都能為自己創建代理。

Whether that's all the many, many millions of creators that are on the platform or hundreds of millions of small businesses, we eventually want to just be able to pull in all your content and very quickly stand up a business agent and be able to interact with your customers and do sales and customer support and all that.

無論是平臺上數以百萬計的創作者，還是數以億計的小企業，我們最終都希望能夠拉入您的所有內容，並快速建立一個業務代理，與您的客戶互動，進行銷售和客戶支持等所有工作。

The one that we're just starting to roll out more now, we call it AI Studio.

我們現在剛剛開始推廣的，我們稱之為人工智能工作室。

It basically is a set of tools that eventually is going to make it so that every creator can build an AI version of themselves as an agent or an assistant that their community can interact with.

它基本上是一套工具，最終將使每個創作者都能打造一個人工智能版的自己，成為他們的社區可以與之互動的代理或助手。

There's a fundamental issue here where there's just not enough hours in the day.

這裡有一個根本問題，那就是每天的時間不夠用。

If you're a creator, you want to engage more with your community, but you're constrained on time.

如果你是一名創作者，你想更多地參與社區活動，但時間有限。

Similarly, your community wants to engage with you, but it's tough.

同樣，你的社區希望與你互動，但這很難。

The next best thing is allowing people to basically create these artifacts.

其次是允許人們創造這些藝術品。

It's an agent, but you train it on your material to represent you in the way that you want.

它是一家代理公司，但你可以根據自己的材料對它進行培訓，讓它以你想要的方式為你代理。

I think it's a very creative endeavor, almost like a piece of art or content that you're putting out there.

我認為這是一項非常有創意的工作，幾乎就像一件藝術品或你要發佈的內容。

It's going to be very clear that it's not engaging with the creator themselves, but I think it'll be another interesting way, just like how creators put out content on these social systems to be able to have agents that do that.

這將會非常清楚，它並不是與創作者本身互動，但我認為這將是另一種有趣的方式，就像創作者如何在這些社交系統上發佈內容一樣，能夠讓代理來做這件事。

One of the interesting use cases that we're seeing is people using these agents for support.

我們看到的一個有趣用例是，人們使用這些代理提供支持。

This was one thing that was a little bit surprising to me.

One of the top use cases for meta-AI already is people basically using it to role-play difficult social situations.

元人工智能的主要用途之一就是讓人們在社交場合進行角色扮演。

Whether it's a professional situation, it's like, I want to ask my manager how do I get a promotion or raise, or I'm having this fight with my friend, or I'm having this difficult situation with my girlfriend.

無論是職業上的情況，比如我想問我的經理如何才能升職或加薪，或者我和朋友吵架了，或者我和女朋友之間遇到了困難。

Basically having a completely judgment-free zone where you can basically role-play that and see how the conversation will go and get feedback on it.

在這裡，你基本上可以進行角色扮演，看看對話將如何進行並獲得反饋。

A lot of people, they don't just want to interact with the same agent, whether it's meta-AI or ChatGPT or whatever it is that everyone else is using.

很多人並不想只與同一個代理互動，無論是元人工智能還是 ChatGPT，或是其他人正在使用的任何東西。

We built this concept to call it an AI foundry around it so that we can help everybody build.

我們圍繞這個概念建立了一個人工智能代工廠，這樣我們就能幫助每個人建立人工智能。

A lot of people, they have a desire to build AI.

很多人都有建立人工智能的願望。

It's very important for them to own the AI because once they put that into their flywheel, their data flywheel, that's how their company's institutional knowledge is encoded and embedded into an AI.

對他們來說，擁有人工智能非常重要，因為一旦他們將其放入飛輪、數據飛輪，他們公司的機構知識就會被編碼並嵌入到人工智能中。

They can't afford to have that AI flywheel, that data flywheel, that experience flywheel somewhere else.

他們不能讓人工智能飛輪、數據飛輪和經驗飛輪去別的地方。

Open source allows them to do that, but they don't really know how to turn this whole thing into an AI.

開放源代碼允許他們這樣做，但他們並不真正知道如何把整個東西變成人工智能。

We created this thing called an AI foundry.

我們創建了一個人工智能代工廠。

We provide the tooling. We provide the expertise.

我們提供工具。我們提供專業知識。

Llama technology, we have the ability to help them turn this whole thing into an AI service.

Llama 技術，我們有能力幫助他們把整個事情變成一項人工智能服務。

Then when we're done with that, they take it, they own it.

當我們完成這項工作後，他們就可以拿走它，擁有它。

其輸出結果就是我們所說的 NIM。

This NIM, this Neural Micro NVIDIA Inference Microservice, they just download it, they take it, and they run it anywhere they like, including on-prem.

這個 NIM，即 Neural Micro NVIDIA Inference Microservice，他們只需下載，就能在任何地方運行，包括內部運行。

We have a whole ecosystem of partners from OEMs that can run the NIMs to GSIs like Accenture that we've trained and worked with to create Llama-based NIMs and pipelines.

我們擁有一整套合作伙伴生態系統，從可以運行 NIM 的原始設備製造商到像埃森哲這樣的 GSI，我們對他們進行了培訓，並與他們合作創建了基於 Llama 的 NIM 和管道。

Now we're off helping enterprises all over the world do this.

現在，我們開始幫助世界各地的企業這樣做。

It's really all triggered off of the Llama open sourcing, the Ray-Ban Metaglass, for bringing AI into the virtual world.

這一切都源於將人工智能引入虛擬世界的 Llama 開放源代碼和雷朋 Metaglass。

It's really interesting. Tell us about that.

Yeah, well, okay, a lot to unpack in there.

是啊，好吧，好吧，這裡面有很多東西要解開。

The Segment Anything model that you're talking about, we're actually presenting, I think, the next version of that here at SIGGRAPH, Segment Anything 2.

你所說的 Segment Anything 模型，我們將在 SIGGRAPH 上展示它的下一個版本 Segment Anything 2。

It now works. It's faster. It works with...

現在能用了。速度更快了。它能與...

I think these are actually cattle from my ranch in Kauai.

我想這些其實是我在可愛島牧場的牛。

Mark came over to my house and we made Philly cheesesteak together.

馬克來我家，我們一起做了費城芝士牛排。

I'd say you did. I was more of a sous-chef.

The fun effects will be able to be made with this and because it'll be open a lot of more serious applications across the industry too.

它不僅能製作出有趣的效果，還能為整個行業帶來許多更嚴肅的應用。

Scientists use this stuff to study coral reefs and natural habitats and evolution of landscapes and things like that.

科學家們用它來研究珊瑚礁和自然棲息地，以及地貌演變之類的問題。

Being able to do this in video and having it be a zero shot and be able to interact with it and tell it what you want to track, it's pretty cool research.

能夠在視頻中做到這一點，並讓它成為一個零鏡頭，還能與它互動，告訴它你想跟蹤什麼，這真是一項很酷的研究。

I think what you're going to end up with is just a whole series of different potential glasses products at different price points with different levels of technology in them.

我認為，你最終會看到一系列不同價位、不同技術水平的潛在眼鏡產品。

I kind of think based on what we're seeing now with the Ray-Ban Metas,

我認為，這與我們現在看到的雷朋梅塔斯（Ray-Ban Metas）是一致的、

I would guess that display-less AI glasses at a $300 price point are going to be a really big product that tens of millions of people or hundreds of millions of people eventually are going to have.

我猜測，300 美元價位的無顯示屏人工智能眼鏡將成為一個真正的大產品，最終會有數千萬或數億人擁有它。

You're going to have super interactive AI that you're talking to.

你將與超級交互式人工智能對話。

You have visual language understanding that you just showed.

你有視覺語言理解能力，這一點你剛才已經展示過了。

The display is obviously going to be great too, but it's going to add a little bit of weight to the glasses and it's going to make them more expensive.

顯示屏顯然也會很棒，但它會增加眼鏡的重量，也會讓眼鏡變得更貴。

There will be a lot of people who want the full holographic display, but there are also going to be a lot of people for whom they want something that eventually is going to be really thin glasses.

會有很多人想要完整的全息顯示屏，但也會有很多人想要最終會非常薄的眼鏡。

So you guys know when Zuck calls it H100, his data center of H100s,

所以你們知道，當扎克稱之為 H100 時，他的數據中心就是 H100、

That's how you get the Jensen Q&A at SIGGRAPH.

這就是在 SIGGRAPH 上獲得詹森問答的方法。

女士們，先生們，有請馬克-扎克伯格。

Nvidia 的 Jensen Huang 和 Meta 的 Mark Zuckerberg 在 Siggraph 上談論人工智能：9 分鐘瞭解一切 (Nvidia's Jensen Huang & Meta's Mark Zuckerberg Talk AI at Siggraph: Everything in 9 Minutes)

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Nvidia 的 Jensen Huang 和 Meta 的 Mark Zuckerberg 在 Siggraph 上談論人工智能：9 分鐘瞭解一切 (Nvidia's Jensen Huang & Meta's Mark Zuckerberg Talk AI at Siggraph: Everything in 9 Minutes)

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