Meta Platforms Inc (META) 2024 Q2 法說會逐字稿

Good afternoon.

午安.

My name is Krista, and I will be your conference operator today.

我叫克里斯塔，今天我將擔任您的會議主持人。

At this time, I would like to welcome everyone to the Meta second-quarter earnings conference call.

現在，我歡迎大家參加 Meta 第二季財報電話會議。

(Operator Instructions) This call will be recorded.

（操作員指示）此通話將會被錄音。

Thank you very much.

非常感謝。

Kenneth Dorell, Meta's Director of Investor Relations, you may begin.

Meta 投資者關係總監 Kenneth Dorell，您可以開始囉。

Thank you.

謝謝。

Good afternoon, and welcome to Meta Platform's second-quarter 2024 earnings conference call.

下午好，歡迎參加 Meta Platform 2024 年第二季財報電話會議。

Joining me today to discuss our results are Mark Zuckerberg, CEO; and Susan Li, CFO.

今天與我一起討論我們業績的有執行長馬克‧祖克柏 (Mark Zuckerberg)；以及財務長 Susan Li。

Before we get started, I would like to take this opportunity to remind you that our remarks today will include forward-looking statements.

在我們開始之前，我想藉此機會提醒您，我們今天的演講將包括前瞻性陳述。

Actual results may differ materially from those contemplated by these forward-looking statements.

實際結果可能與這些前瞻性陳述所預期的結果有重大差異。

Factors that could cause these results to differ materially are set forth in today's earnings press release and in our quarterly report on Form 10-Q filed with the SEC.

可能導致這些結果出現重大差異的因素已在今天的收益新聞稿和我們向美國證券交易委員會提交的 10-Q 表季度報告中列出。

Any forward-looking statements that we make on this call are based on assumptions as of today, and we undertake no obligation to update these statements as a result of new information or future events.

我們在本次電話會議上所做的任何前瞻性陳述均基於今天的假設，我們不承擔根據新資訊或未來事件更新這些陳述的義務。

During this call, we will present both GAAP and certain non-GAAP financial measures.

在本次電話會議中，我們將介紹 GAAP 和某些非 GAAP 財務指標。

A reconciliation of GAAP to non-GAAP measures is included in today's earnings press release.

今天的收益新聞稿中包含了 GAAP 與非 GAAP 指標的對帳表。

The earnings press release and an accompanying investor presentation are available on our website at investor.fb.com.

收益新聞稿和隨附的投資者介紹可在我們的網站 investor.fb.com 上查閱。

And now I'd like to turn the call over to Mark.

現在我想把電話轉給馬克。

All right.

好的。

Thanks, Ken, and hey, everyone.

謝謝，肯，大家好。

Thanks for joining today.

感謝您今天的加入。

This was a strong quarter for our community and business.

對於我們的社區和業務來說，這是一個強勁的季度。

We estimate that there are now more than 3.2 billion people using at least one of our apps each day.

我們估計，現在每天有超過 32 億人至少使用我們的一款應用程式。

The growth we're seeing here in the US has especially been a bright spot.

我們在美國看到的成長尤其令人欣喜。

WhatsApp now serves more than 100 million monthly actives in the US, and we're seeing good year-over-year growth across Facebook, Instagram, and Threads as well, both in the US and globally.

WhatsApp 目前在美國每月服務超過 1 億活躍用戶，而且我們看到 Facebook、Instagram 和 Threads 在美國和全球範圍內都呈現良好的同比增長。

I'm particularly pleased with the progress that we're making with young adults on Facebook.

我對 Facebook 在年輕人中取得的進展感到特別高興。

The numbers we're seeing, especially in the US, really go against the public narrative around who's using the app.

我們看到的數字，尤其是在美國，與公眾關於誰在使用該應用程式的說法完全相反。

A couple of years ago, we started focusing our apps more on 18 to 29 year olds, and it's good to see that those efforts are driving good results.

幾年前，我們開始將我們的應用程式更專注於 18 至 29 歲的人群，很高興看到這些努力正在取得良好的成果。

Another bright spot is Threads, which is about to hit 200 million monthly actives.

另一個亮點是 Threads，其月活躍用戶數即將達到 2 億。

We're making steady progress towards building what looks like it's going to be another major social app.

我們正在穩步推進構建另一個重要的社交應用程式。

And we're seeing deeper engagement and I'm quite pleased with the trajectory here.

我們看到了更深層的參與，我對這裡的發展軌跡感到非常滿意。

The big theme right now is, of course, AI, and I'll focus my comments today on three areas: what AI means for our family of apps and core business, what new AI experiences and opportunities we see, and how AI is shaping our metaverse work.

現在的大主題當然是人工智慧，我今天將重點討論三個方面：人工智慧對我們的應用系列和核心業務意味著什麼，我們看到了哪些新的人工智慧體驗和機遇，以及人工智慧如何塑造我們的元宇宙工作。

So let's start.

那麼我們就開始吧。

Across Facebook and Instagram, advances in AI continue to improve the quality of recommendations and drive engagement.

在 Facebook 和 Instagram 上，人工智慧的進步不斷提高推薦的品質並推動參與度。

And we keep finding that as we develop more general recommendation models, content recommendations get better.

我們不斷發現，隨著我們開發出更多通用的推薦模型，內容推薦會變得更好。

In this quarter, we rolled out our fullscreen video player and unified video recommendation service across Facebook, bringing real longer videos and live into a single experience.

本季度，我們在 Facebook 上推出了全螢幕視訊播放器和統一視訊推薦服務，將真正的更長的視訊和直播融入單一體驗中。

And this has allowed us to extend our unified AI systems, which had already increased engagement on Facebook Reels more than our initial move from CPUs to GPUs did.

這使我們能夠擴展統一的 AI 系統，該系統已經比我們最初從 CPU 轉移到 GPU 時更加提高了 Facebook Reels 的參與度。

Over time, I'd like to see us move towards a single unified recommendation system that powers all of the content, including things like people you may know across all of our services.

隨著時間的推移，我希望看到我們走向一個統一的推薦系統，該系統可以為所有內容提供支持，包括您可能在我們所有服務中認識的人等內容。

We're not there yet.

我們還沒到那裡。

There's still upside and we're making good progress here.

我們仍有上升空間，並且正在取得良好進展。

AI is also going to significantly evolve our services for advertisers in some exciting ways.

人工智慧也將以一些令人興奮的方式顯著改善我們為廣告商提供的服務。

It used to be that advertisers came to us with a specific audience they wanted to reach, like a certain age group, geography or interest.

廣告商過去總是帶著他們想要覆蓋的特定受眾來找我們，例如某個年齡層、某個地區或某個興趣。

Eventually, we got to the point where our ad systems could better predict who would be interested than the advertisers could themselves.

最終，我們的廣告系統能夠比廣告商自己更好地預測誰會感興趣。

But today, advertisers still need to develop creative themselves.

但今天，廣告主仍然需要自己開發創意。

And in the coming years, AI will be able to generate creative for advertisers as well, and will also be able to personalize it as people see it.

在未來幾年，人工智慧也將能夠為廣告商產生創意，並能夠根據人們的看法進行個人化設定。

Over the long term, advertisers will basically just be able to tell us a business objective and a budget, and we're going to go do the rest for them.

從長遠來看，廣告商基本上只需告訴我們業務目標和預算，我們會為他們完成其餘工作。

We're going to get there incrementally over time, but I think this is going to be a very big deal.

我們會隨著時間的推移逐步實現這一目標，但我認為這將是一件大事。

Moving on to some of the brand-new experiences that AI enables, last quarter, we started broadly rolling out our assistant, Meta AI, and it is on track to achieve our goal of becoming the most used AI assistant by the end of the year.

談到人工智慧帶來的一些全新體驗，上個季度，我們開始廣泛推出我們的助手 Meta AI，它有望實現我們的目標，即在今年年底前成為使用率最高的人工智慧助理。

We have an exciting road map ahead of things that we want to add.

對於我們想要添加的內容，我們有一個令人興奮的路線圖。

But the bottom line here is that Meta AI feels like it is on track to be an important service, and it's improving quickly both in intelligence and features.

但最重要的是，Meta AI 感覺它正在成為一項重要的服務，而且它在智慧和功能方面都在快速提升。

Some of the use cases are utilitarian, like searching for information or role-playing difficult conversations before you have them with another person.

有些用例是實用的，例如在與他人進行困難對話之前搜尋資訊或角色扮演。

And other uses are more creative like the new Imagine Yourself feature that lets you create images of yourself doing whatever you want in whatever style you want.

其他用途則更有創意，例如新的「想像自己」功能可讓您創建自己的圖像，做任何您想做的事情，採用任何您想要的風格。

And part of the beauty of AI is that it's general.

人工智慧的魅力之一就在於它具有通用性。

So we're still uncovering the wide range of use cases that it's valuable for.

因此，我們仍在探索其有價值的廣泛用例。

An important part of our vision is that we're not just creating a single AI but enabling lots of people to create their own AIs.

我們願景的一個重要部分是，我們不只是創造單一的人工智慧，而是讓許多人能夠創造自己的人工智慧。

And this week, we launched AI Studio, which lets anyone create AIs to interact with across our apps.

本週，我們推出了 AI Studio，任何人都可以創建 AI 來與我們的應用程式互動。

I think the creators are especially going to find this quite valuable.

我認為創作者尤其會發現這非常有價值。

There are millions of creators across our apps, and these are people who want to engage more with their communities, and their communities want to engage more with them.

我們的應用程式中有數百萬的創作者，這些人希望與他們的社群進行更多互動，他們的社群也希望與他們進行更多互動。

But there are only so many hours in the day.

但一天只有這麼多小時。

So now they're going to be able to use AI Studio to create AI agents that can channel them to chat with their community, answer people's questions, create content and more.

因此現在他們將能夠使用 AI Studio 來創建 AI 代理，以便他們與社群聊天、回答人們的問題、創建內容等。

So I'm quite excited about this.

所以我對此感到非常興奮。

But this goes beyond creators, too.

但這也超出了創作者的範圍。

Anyone is going to be able to build their own AIs based on their interests or different topics that they are going to be able to engage with or share with their friends.

任何人都可以根據自己的興趣或不同主題建立自己的人工智慧，並與朋友互動或分享。

Business AIs are the other big piece here.

商業人工智慧是這裡的另一個重要部分。

We're still in alpha testing with more and more businesses.

我們仍在與越來越多的企業進行 Alpha 測試。

The feedback we're getting is positive so far.

到目前為止我們收到的回饋是正面的。

Over time, I think that just like every business has a website, a social media presence, and an e-mail address, in the future, I think that every business is also going to have an AI agent that their customers can interact with.

隨著時間的推移，我認為就像每個企業都有一個網站、一個社群媒體和一個電子郵件地址一樣，在未來，我認為每個企業也將擁有一個可以與客戶互動的人工智慧代理商。

And our goal is to make it easy for every small business, eventually every business, to pull all of their content and catalog into an AI agent that drives sales and saves them money.

我們的目標是讓每家小型企業，最終是每家企業，都可以輕鬆地將他們的所有內容和目錄放到一個人工智慧代理商中，以推動銷售並節省成本。

When this is working at scale, I think that this is going to dramatically accelerate our business messaging revenue.

當這項技術大規模投入使用時，我認為這將大大加速我們的商業資訊收入。

There are a lot of other new opportunities here that I'm excited about too, but I'll save those for another day when we're ready to roll them out.

這裡還有很多其他的新機會讓我感到興奮，但我會把它們留到我們準備推出它們的另一天。

The engine that powers all these new experiences is the Llama family of foundation models.

驅動所有這些新體驗的引擎是 Llama 系列基礎車型。

In this quarter, we released Llama 3.1, which includes the first frontier-level open source model as well as new and industry-leading small- and medium-sized models.

本季度，我們發布了Llama 3.1，包含首個前沿級開源模型以及全新、業界領先的中小型模型。

The 405 billion model has better cost performance relative to the leading closed models.

4050億款相對主力封閉機型有更優的性價比。

And because it's open, it is immediately the best choice for fine-tuning and distilling your own custom models of whatever size you need.

而且由於它是開放的，它立即成為了您需要的任何規模的定制模型進行微調和提煉的最佳選擇。

I think we're going to look back at Llama 3.1 as an inflection point in the industry where open-source AI started to become the industry standard just like Linux is.

我認為我們將回顧 Llama 3.1，將其視為行業的轉折點，開源 AI 開始像 Linux 一樣成為行業標準。

I often get asked why I'm so bullish on open source.

我常被問到為什麼我這麼看好開源。

I wrote a letter, along with the Llama 3.1 release, explaining why I believe that open source is better for developers, for Meta, and for the world more broadly.

我在 Llama 3.1 發佈時寫了一封信，解釋了為什麼我認為開源對開發人員、對 Meta 以及對整個世界都更有利。

My view is that open source will be safer, will enable innovation that improves all of our lives faster and will also create more shared prosperity.

我的觀點是，開源將更加安全，將能夠推動創新，從而更快地改善我們所有人的生活，並將創造更多的共同繁榮。

For Meta's own interests, we're in the business of building the best consumer and advertiser experiences.

為了 Meta 自身的利益，我們致力於打造最佳的消費者和廣告商體驗。

And to do that, we need to have access to the leading technology infrastructure and not get constrained by what competitors will let us do.

為了做到這一點，我們需要掌握領先的技術基礎設施，而不受競爭對手的限制。

But these models are ecosystems.

但這些模型就是生態系。

They're not just kind of isolated pieces of software that we can develop by ourselves.

它們不僅僅是我們可以自己開發的孤立的軟體。

So if we want the most robust ecosystem of tools, efficiency improvements, silicon optimizations, and other integrations to develop around our models, then we need them to be widely used by developers across the industry.

因此，如果我們希望圍繞我們的模型開發最強大的工具、效率改進、矽片優化和其他整合生態系統，那麼我們需要它們被整個行業的開發人員廣泛使用。

And once we know that we're going to have access to the leading models, then I'm confident that we're going to be able to build the best social and advertising experiences.

一旦我們知道我們將能夠獲得領先的模式，我相信我們將能夠創造最好的社交和廣告體驗。

Part of why I'm so optimistic about this is that we have a long track record of success with open source.

我對此如此樂觀的原因之一是我們在開源領域有著長期的成功記錄。

We've saved billions of dollars with Open Compute Project by having supply chain standardized on our infra designs.

透過在我們的基礎設施設計上實現供應鏈標準化，我們利用開放運算專案節省了數十億美元。

Open sourcing tools like PyTorch and React has led to real benefits for us from all of the industry's contributions.

PyTorch 和 React 等開源工具為我們帶來了來自整個產業貢獻的真正利益。

This approach has consistently worked for us and I expect it will work here, too.

這種方法對我們來說一直很有效，我希望它在這裡也會有效。

Another major area of focus is figuring out the right level of infra capacity to support training more and more advanced models.

另一個重點領域是確定適當的基礎設施容量水平，以支援訓練越來越先進的模型。

Llama 3 is already competitive with the most advanced models, and we're already starting to work on Llama 4, which we're aiming to be the most advanced in the industry next year.

Llama 3 已經可以與最先進的車型相媲美，我們已經開始研發 Llama 4，我們的目標是明年讓它成為業界最先進的車型。

We are planning for the compute clusters and data we'll need for the next several years.

我們正在規劃未來幾年所需的運算群集和數據。

The amount of compute needed to train Llama 4 will likely be almost 10x more than what we used to train Llama 3.

訓練 Llama 4 所需的計算量可能比訓練 Llama 3 多 10 倍。

And future models will continue to grow beyond that.

未來的模型也將繼續超越這一點。

It's hard to predict how this will trend multiple generations out into the future.

很難預測這種趨勢將如何影響未來的世代。

But at this point, I'd rather risk building capacity before it is needed, rather than too late, given the long lead times for spinning up new infra projects.

但目前，考慮到啟動新基礎設施項目的準備時間很長，我寧願冒險在需要之前進行建設，而不是為時已晚。

And as we scale these investments, we're of course going to remain committed to operational efficiency across the company.

在擴大這些投資的同時，我們當然將繼續致力於提高整個公司的營運效率。

The last area that I want to discuss is how AI is shaping our metaverse work, which continues to be our other long-term focus.

我想要討論的最後一個領域是人工智慧如何塑造我們的元宇宙工作，這仍然是我們另一個長期的關注點。

Last quarter, I discussed how advances in AI have pulled in the timelines for some of our products.

上個季度，我討論了人工智慧的進步如何縮短我們某些產品的時間表。

A few years ago, I would have predicted that holographic AR would be possible before smart AI, but now it looks like those technologies will actually be ready in the opposite order.

幾年前，我曾預測全像 AR 會在智慧 AI 之前實現，但現在看來，這些技術實際上將以相反的順序準備就緒。

We're well positioned for that because of the Reality Labs investments that we've already made.

由於我們已經對 Reality Labs 進行了投資，因此我們已做好了充分的準備。

Ray-Ban Meta glasses continue to be a bigger hit sooner than we expected, thanks in part to AI.

雷朋 Meta 眼鏡比我們預期的更快成為熱門產品，這在一定程度上要歸功於人工智慧。

Demand is still outpacing our ability to build them, but I'm hopeful that we'll be able to meet that demand soon.

需求仍然超出了我們的生產能力，但我希望我們很快就能滿足這項需求。

EssilorLuxottica has been a great partner to work with on this, and we are excited to team up with them to build future generations of AI glasses as we continue to build our long-term partnership.

EssilorLuxottica 是我們在此方面的出色合作夥伴，我們很高興與他們聯手打造未來幾代 AI 眼鏡，並將繼續建立我們的長期合作夥伴關係。

Quest 3 sales are also outpacing our expectations.

Quest 3 的銷量也超出了我們的預期。

And I think that's because it is not just the best MR headset for the price but it's the best headset on the market, period.

我認為，這是因為它不僅是性價比最好的 MR 耳機，而且是市場上最好的耳機，僅此而已。

In addition to gaming, people are increasingly taking advantage of Quest's capabilities as a general computing platform, spending time watching videos, browsing websites, extending their PC via virtual desktop and more.

除了遊戲之外，人們越來越多地利用 Quest 作為通用計算平台的功能，花時間觀看影片、瀏覽網站、透過虛擬桌面擴展他們的 PC 等等。

Horizon also continues to grow across the VR, mobile, and desktop, and I expect that it will become an increasingly important part of that ecosystem as well.

Horizo​​n 也在 VR、行動裝置和桌面領域持續發展，我預計它也將成為該生態系統中越來越重要的一部分。

We're hosting our annual Connect Conference on September 25, and we will have lots of exciting updates around all of our AI and metaverse work, so I encourage you to tune into that.

我們將於 9 月 25 日舉辦年度 Connect 大會，屆時我們將發布有關我們所有 AI 和元宇宙工作的大量令人興奮的更新，因此我鼓勵您關注。

At the end of the day, we are in the fortunate position where the strong results that we're seeing in our core products and business give us the opportunity to make deep investments for the future.

總而言之，我們很幸運，我們的核心產品和業務所取得的強勁業績為我們提供了對未來進行深入投資的機會。

And I plan to fully seize that opportunity to build some amazing things that will pay off for our community and our investors for decades to come.

我計劃充分抓住這個機會，創造一些令人驚嘆的東西，在未來幾十年為我們的社區和投資者帶來回報。

The progress we're making on both the foundational technology and product experiences suggests that we're on the right track.

我們在基礎技術和產品體驗方面所取得的進展表明我們正走在正確的道路上。

I'm proud of what our team has accomplished so far, and I'm optimistic about our ability to execute on the opportunities ahead.

我為我們團隊迄今所取得的成就感到自豪，並對我們抓住未來機會的能力充滿信心。

As always, thank you to our teams who are pushing all this important work forward, and thanks to all of you for being on this journey with us.

一如既往，感謝我們的團隊推動所有這些重要工作，也感謝大家與我們一起踏上這段旅程。

And now here's Susan.

現在請蘇珊發言。

Thanks, Mark, and good afternoon, everyone.

謝謝，馬克，大家下午好。

Let's begin with our consolidated results.

讓我們從綜合結果開始。

All comparisons are on a year-over-year basis, unless otherwise noted.

除非另有說明，所有比較均以同比為基礎。

Q2 total revenue was $39.1 billion, up 22% or 23% on a constant currency basis.

第二季總營收為 391 億美元，成長 22%，以固定匯率計算成長 23%。

Q2 total expenses were $24.2 billion, up 7% compared to last year.

第二季總支出為 242 億美元，比去年同期成長 7%。

In terms of the specific line items, cost of revenue increased 23%, driven primarily by higher infrastructure and Reality Labs inventory costs.

就具體項目而言，收入成本增加了 23%，主要原因是基礎設施和 Reality Labs 庫存成本增加。

R&D increased 13%, primarily driven by higher headcount-related expenses and infrastructure costs, which were partially offset by lower restructuring costs.

研發費用增加了 13%，主要是由於員工人數相關費用和基礎設施成本的增加，但重組成本的降低部分抵消了這些費用的成長。

Marketing and sales decreased 14% due mainly to lower restructuring and headcount-related costs.

行銷和銷售額下降 14%，主要原因是重組和員工人數相關成本的降低。

G&A decreased 12% mostly due to lower legal-related expenses.

一般及行政開支下降 12%，主要因為法律相關費用降低。

We ended the first quarter with almost 70,800 employees, up 2% from Q1.

截至第一季，我們共有員工近 70,800 人，比第一季成長 2%。

Second-quarter operating income was $14.8 billion, representing a 38% operating margin.

第二季營業收入為148億美元，營業利益率為38%。

Our tax rate for the quarter was 11%.

我們本季的稅率為 11%。

Net income was $13.5 billion or $5.16 per share.

淨收入為 135 億美元，即每股 5.16 美元。

Capital expenditures, including principal payments on finance leases, were $8.5 billion, driven by investments in servers, data centers, and network infrastructure.

資本支出（包括融資租賃的本金支付）為 85 億美元，主要由對伺服器、資料中心和網路基礎設施的投資推動。

Free cash flow was $10.9 billion.

自由現金流為109億美元。

We repurchased $6.3 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders, ending the quarter with $58.1 billion in cash and marketable securities and $18.4 billion in debt.

我們回購了 63 億美元的 A 類普通股，並向股東支付了 13 億美元的股息，本季末我們的現金和有價證券為 581 億美元，債務為 184 億美元。

Moving now to our segment results.

現在來看看我們的分部業績。

I'll begin with our family of apps segment.

我將從我們的應用程式系列部分開始。

Our community across the family of apps continues to grow, with approximately 3.27 billion people using at least one of our family of apps on a daily basis in June.

我們的應用程式系列社群持續成長，6 月每天約有 32.7 億人至少使用我們的一款應用程式系列。

Q2 total family of apps revenue was $38.7 billion, up 22% year-over-year.

第二季應用程式系列總營收為 387 億美元，年增 22%。

Q2 family of apps ads revenue was $38.3 billion, up 22% or 23% on a constant currency basis.

第二季應用程式系列廣告營收為 383 億美元，成長 22%，以固定匯率計算成長 23%。

Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by gaming and entertainment and media.

在廣告收入方面，線上商務垂直產業是年成長的最大貢獻者，其次是遊戲、娛樂和媒體。

On a user geography basis, ad revenue growth was strongest in rest of world and Europe at 33% and 26%, respectively.

從用戶地理來看，全球其他地區和歐洲的廣告收入增幅最為強勁，分別為 33% 和 26%。

Asia Pacific grew 20% and North America grew 17%.

亞太地區成長了 20%，北美成長了 17%。

On an advertiser geography basis, total revenue growth continued to be strongest in Asia Pacific at 28%, though growth was below the first quarter rate of 41% as we lapped a period of stronger demand from China-based advertisers.

從廣告商地理來看，亞太地區總營收增幅持續保持最強勁，達到 28%，但由於中國廣告商需求強勁，增幅低於第一季的 41%。

In Q2, the total number of ad impressions served across our services and the average price per ad both increased 10%.

第二季度，我們服務中投放的廣告展示總數和每個廣告的平均價格均增加了 10%。

Impression growth was mainly driven by Asia Pacific and rest of world.

印象增長主要受到亞太地區和世界其他地區的推動。

Pricing growth was driven by increased advertiser demand, in part due to improved ad performance.

價格成長主要是因為廣告主需求增加，而廣告效果的提升也推動了價格成長。

This was partially offset by impression growth, particularly from lower monetizing regions and services.

這被印象增長（特別是來自貨幣化較低的地區和服務）部分抵消。

Family of apps other revenue was $389 million, up 73%, driven primarily by business messaging revenue growth from our WhatsApp business platform.

應用程式系列的其他收入為 3.89 億美元，成長 73%，主要得益於我們的 WhatsApp 商業平台的商業訊息收入成長。

We continue to direct the majority of our investments toward the development and operation of our family of apps.

我們將繼續把大部分投資用於應用程式系列的開發和營運。

In Q2, family of apps expenses were $19.4 billion, representing approximately 80% of our overall expenses.

第二季度，應用程式系列的支出為 194 億美元，約占我們整體支出的 80%。

Family of apps expenses were up 4%, mostly due to higher infrastructure and headcount-related expenses, which were partially offset by lower restructuring costs.

應用程式系列的費用上漲了 4%，主要是由於基礎設施和員工人數相關費用的增加，但重組成本的降低部分抵消了這一增長。

Family of apps operating income was $19.3 billion, representing a 50% operating margin.

應用程式系列營業收入為 193 億美元，營業利潤率為 50%。

Within our Reality Labs segment, Q2 was $353 million, up 28%, driven primarily by Quest headset sales.

在我們的現實實驗室部門中，第二季的營收為 3.53 億美元，成長 28%，主要得益於 Quest 頭戴式裝置的銷售。

Reality Labs expenses were $4.8 billion, up 21% year over year, driven mainly by higher headcount-related expenses and Reality Labs inventory costs.

Reality Labs 的支出為 48 億美元，年增 21%，主要原因是與員工人數相關的支出和 Reality Labs 的庫存成本增加。

Reality Labs operating loss was $4.5 billion.

Reality Labs 的營運虧損為 45 億美元。

Turning now to the business outlook, there are two primary factors that drive our revenue performance: our ability to deliver engaging experiences for our community, and our effectiveness at monetizing that engagement over time.

現在談到業務前景，有兩個主要因素推動我們的收入表現：我們為社區提供引人入勝的體驗的能力，以及我們隨著時間的推移將這種參與貨幣化的有效性。

To deliver engaging experiences, we remain focused on executing our priorities, including video and in-feed recommendations.

為了提供引人入勝的體驗，我們仍然專注於執行我們的優先事項，包括影片和資訊流推薦。

On Instagram, Reels engagement continues to grow as we make ongoing enhancements to our recommendation systems.

在 Instagram 上，隨著我們不斷增強推薦系統，Reels 的參與度持續成長。

Part of this work has been focused on increasing the share of original posts within recommendations so people can discover the best of Instagram, including content from emerging creators.

這項工作的部分重點是增加原創貼文在推薦中的份額，以便人們能夠發現 Instagram 上的精彩內容，包括新興創作者的內容。

Now, more than half of recommendations in the US come from original posts.

現在，美國超過一半的推薦都來自原創貼文。

On Facebook, we're seeing encouraging early results from the global rollout of our unified video player and ranking systems in June.

在 Facebook 上，我們在 6 月在全球推出了統一的視訊播放器和排名系統，並看到了令人鼓舞的早期成果。

This initiative allows us to bring all video types on Facebook into one viewing experience, which we expect will unlock additional growth opportunities for short-form video as we increasingly mix shorter videos into the overall base of Facebook video engagement.

這項舉措使我們能夠將Facebook 上的所有影片類型整合到一個觀看體驗中，隨著我們越來越多地將短影片融入Facebook 影片參與度的整體基礎中，我們預計這將為短影片帶來更多的成長機會。

We expect the relevance of video recommendations will continue to increase as we benefit from unifying video ranking across Facebook and integrating our next-generation recommendation systems.

我們預計，隨著我們受益於 Facebook 統一影片排名並整合下一代推薦系統，影片推薦的相關性將繼續提高。

These have already shown promising gains since we began using the new systems to support Facebook Reels recommendations last year.

自從去年我們開始使用新系統支援 Facebook Reels 推薦以來，這些已經顯示出可喜的成果。

We expect to expand these new systems to support more surfaces beyond Facebook video over the course of this year and next year.

我們預計將在今年和明年擴展這些新系統，以支援 Facebook 影片以外的更多平台。

We're also seeing good momentum with our longer-term engagement priorities, including generative AI and Threads.

我們也看到我們的長期參與重點（包括生成式人工智慧和 Threads）呈現出良好的動力。

People have used Meta AI for billions of queries since we first introduced it.

自從我們首次推出 Meta AI 以來，人們已使用 Meta AI 進行了數十億次查詢。

We're seeing particularly promising signs on WhatsApp in terms of retention and engagement, which has coincided with India becoming our largest market for Meta AI usage.

我們在 WhatsApp 的留存率和參與度方面看到了特別令人鼓舞的跡象，這恰逢印度成為我們使用 Meta AI 的最大市場。

You can now use Meta AI in over 20 countries and 8 languages.

現在您可以在 20 多個國家/地區和 8 種語言中使用 Meta AI。

And in the US, we're rolling out new features like Imagine Edit, which allows people to edit images they generate with Meta AI.Beyond generative AI, the Threads community also continues to grow and deepen their engagement as we ship new features and enhance our content recommendation systems.

在美國，我們正在推出 Imagine Edit 等新功能，它允許人們編輯使用 Meta AI 生成的圖像。我們的內容推薦系統。

Now to the second driver of our revenue performance, increasing monetization efficiency.

現在談談我們收入表現的第二個驅動因素，即提高貨幣化效率。

There are two parts to this work.

這項工作分為兩部分。

The first is optimizing the level of ads within organic engagement.

首先是優化有機參與度內的廣告水平。

We continue to see opportunities to grow ad supply on lower monetizing surfaces like video, including within Facebook as the mix of overall video engagement shifts more to shorter videos over time, which creates more ad insertion opportunity.

我們繼續看到在視頻等盈利能力較低的領域增加廣告供應的機會，包括在Facebook 內部，因為隨著時間的推移，整體視頻參與度更多地轉向更短的視頻，這創造了更多的廣告插入機會。

More broadly, we are continuing to get better at determining the best ads to show and when to show them during a person session across both Facebook and Instagram.

更廣泛地說，我們正在繼續改進，以便確定在 Facebook 和 Instagram 上的個人會話期間展示的最佳廣告以及何時展示這些廣告。

This is enabling us to drive revenue growth and conversions without increasing the number of ads or, in some cases, even reducing ad load.

這使得我們能夠在不增加廣告數量，甚至在某些情況下不減少廣告負載的情況下推動收入成長和轉換。

The second part of improving monetization efficiency is enhancing marketing performance.

提升貨幣化效率的第二部分是提升行銷績效。

We continue to be pleased with our progress here, with AI playing an increasingly central role.

我們對這方面取得的進展感到非常高興，人工智慧正發揮著越來越重要的作用。

We're improving ad delivery by adopting more sophisticated modeling techniques made possible by AI advancements, including our Meta Lattice ad ranking architecture, which continued to provide ad performance and efficiency gains in the second quarter.

我們正在透過採用人工智慧進步所帶來的更複雜的建模技術來改善廣告投放，其中包括我們的 Meta Lattice 廣告排名架構，該架構在第二季度繼續提供廣告效能和效率的提升。

We're also making it easier for advertisers to maximize ad performance and automate more of their campaign setup with our Advantage+ suite of solutions.

我們也利用 Advantage+ 解決方案套件來幫助廣告主更輕鬆地最大限度地提高廣告效果，並實現更多廣告活動設定的自動化。

We're seeing these tools continue to unlock performance gains, with a study conducted this year demonstrating 22% higher return on ad spend for US advertisers after they adopted Advantage+ shopping campaigns.

我們看到這些工具繼續帶來績效提升，今年進行的一項研究表明，美國廣告商在採用 Advantage+ 購物廣告系列後，廣告支出回報率提高了 22%。

Advertiser adoption of these tools continues to expand, and we're adding new capabilities to make them even more useful.

廣告商對這些工具的採用不斷擴大，我們正在添加新的功能以使它們更加有用。

For example, this quarter, we introduced flexible format to Advantage+ shopping, which allows advertisers to upload multiple images and videos in a single ad that we can select from and automatically determine which format to serve in order to yield the best performance.

例如，本季度，我們為 Advantage+ 購物引入了靈活的格式，允許廣告商在單一廣告中上傳多張圖片和視頻，我們可以從中進行選擇並自動確定採用哪種格式以獲得最佳效果。

We have also now expanded the list of conversions that businesses can optimize for using Advantage+ shopping to include an additional 10 conversion types, including objectives like add to cart.

我們現在還擴展了企業可使用 Advantage+ 購物進行優化的轉換列表，包括另外 10 種轉換類型，包括添加到購物車等目標。

Looking forward, we believe generative AI will play a growing role in how businesses market and engage with customers at scale.

展望未來，我們相信生成式人工智慧將在企業大規模行銷和與客戶互動方面發揮越來越重要的作用。

We expect this technology will continue to make it easier for businesses to develop customized and diverse ad creatives.

我們期待這項技術將繼續幫助企業更輕鬆地開發客製化和多樣化的廣告創意。

We've seen promising early results since introducing our first generative AI ad features, image expansion, background generation, and text generation, with more than 1 million advertisers using at least one of these solutions in the past month.

自從我們推出第一款生成式AI 廣告功能、圖像擴展、背景生成和文字生成以來，我們已經看到了令人鼓舞的早期成果，過去一個月有超過100 萬廣告商使用了至少一種這些解決方案。

In May, we began rolling out full image generation capabilities into Advantage+ creative, and we're already seeing improved performance from advertisers using the tool.

今年 5 月，我們開始在 Advantage+ 創意中推出完整的圖像生成功能，並且我們已經看到使用該工具的廣告商的表現有所提升。

Finally, we expect AI will help businesses communicate with customers more efficiently through messaging.

最後，我們希望人工智慧能夠幫助企業透過訊息傳遞更有效地與客戶溝通。

We're starting by testing the ability for businesses to use AI in their chats with customers to help sell their goods and services and to generate leads.

我們首先測試企業在與客戶聊天中使用人工智慧來幫助銷售商品和服務並產生潛在客戶的能力。

While we are in the early stages, we continue to expand the number of advertisers we're testing with and have seen good advances in the quality of responses since we began using Llama 3.

雖然我們還處於早期階段，但我們仍在繼續擴大測試的廣告商數量，自從我們開始使用 Llama 3 以來，我們已經看到了響應品質的良好進步。

Next, I would like to discuss our approach to capital allocation, which remains unchanged.

接下來我想討論我們的資本配置方法，這個方法保持不變。

We continue to invest both in enhancing our core experiences in the near term and developing technologies that we believe will transform how people engage with our services in the years ahead.

我們將繼續投資於短期內增強我們的核心體驗以及開發我們相信將在未來幾年改變人們使用我們服務的方式的技術。

We expect that having sufficient compute capacity will be central to many of these opportunities.

我們預計，擁有足夠的運算能力對於這些機會來說至關重要。

So we are investing meaningfully in infrastructure to support our core AI work in content ranking and ads as well as our generative AI and advanced research efforts.

因此，我們正在對基礎設施進行大量投資，以支援我們在內容排名和廣告方面的核心人工智慧工作以及我們的生成人工智慧和高級研究工作。

Our ongoing investment in core AI capacity is informed by the strong returns we've seen and expect to deliver in the future as we advance the relevance of recommended content and ads on our platform.

我們對核心人工智慧能力的持續投資源於我們已經看到的強勁回報，並有望在我們提昇平台上推薦內容和廣告的相關性的同時，在未來帶來回報。

While we expect the returns from generative AI to come in over a longer period of time, we are mapping these investments against the significant monetization opportunities that we expect to be unlocked across customized ad creative, business messaging, a leading AI assistant, and organic content generation.

雖然我們預計生成式人工智慧的回報將在較長時期內顯現，但我們正在將這些投資與我們預計將在客製化廣告創意、商業訊息傳遞、領先的人工智慧助理和有機內容中釋放的巨大盈利機會進行對比一代。

As we scale generative AI training capacity to advance our foundation models, we will continue to build our infrastructure in a way that provides us with flexibility in how we use it over time.

隨著我們擴展生成式人工智慧訓練能力以推進我們的基礎模型，我們將繼續以一種能夠讓我們隨著時間的推移而靈活地使用它的方式建立我們的基礎設施。

This will allow us to direct training capacity to gen AI inference or to our core ranking and recommendation work when we expect that doing so would be more valuable.

當我們認為這樣做更有價值時，這將使我們能夠將訓練能力引導到產生 AI 推理或我們的核心排名和推薦工作上。

We will also continue our focus on improving the cost efficiency of our workloads over time.

我們也將繼續致力於隨著時間的推移提高工作負載的成本效率。

Reality Labs remains our other long-term initiative that we continue to invest meaningfully in.

現實實驗室仍然是我們另一個長期計劃，我們將繼續對其進行大力投資。

Quest 3 is selling well and Ray-Ban Meta smart glasses are showing very promising traction with the early signals that we are seeing across demand, usage, and retention increasing our confidence in the long-run potential of AR glasses.

Quest 3 銷售良好，雷朋 Meta 智慧眼鏡也表現出非常良好的發展勢頭，我們在需求、使用和保留方面看到的早期訊號增強了我們對 AR 眼鏡長期潛力的信心。

Finally, as we pursue these investments across near and long-term priorities, we will remain focused on operating the business efficiently.

最後，當我們進行短期和長期投資時，我們將繼續專注於高效能營運業務。

Turning now to the revenue outlook.

現在來談談收入前景。

We expect third-quarter 2024 total revenue to be in the range of $38.5 billion to $41 billion.

我們預計 2024 年第三季的總營收將在 385 億美元至 410 億美元之間。

Our guidance assumes foreign currency is a 2% headwind to year-over-year total revenue growth based on current exchange rates.

我們的指導假設是，根據當前匯率，外幣將對年比總收入成長造成 2% 的阻力。

Turning now to the expense outlook.

現在來談談費用前景。

We expect full-year 2024 total expenses to be in the range of $96 (technical difficulty) with our expanded infrastructure footprint.

隨著基礎設施覆蓋範圍的擴大，我們預計 2024 年全年總支出將在 96 美元（技術難度）左右。

Turning now to the CapEx outlook.

現在來談談資本支出前景。

We anticipate our full-year 2024 capital expenditures will be in the range of $37 billion to $40 billion, updated from our prior range of $35 billion to $40 billion.

我們預計 2024 年全年資本支出將在 370 億美元至 400 億美元之間，高於先前的 350 億美元至 400 億美元。

While we continue to refine our plans for next year, we currently expect significant CapEx growth in 2025 as we invest to support our AI research and our product development efforts.

在我們繼續完善明年計畫的同時，我們目前預計 2025 年的資本支出將大幅成長，因為我們將投資支持我們的人工智慧研究和產品開發工作。

On to tax.

談到稅收。

Absent any changes to our tax landscape, we expect our full-year 2024 tax rate to be in the mid-teens.

如果我們的稅收狀況沒有任何變化，我們預計 2024 年全年稅率將在 15% 左右。

In addition, we continue to monitor an active regulatory landscape, including the increasing legal and regulatory headwinds in the EU and the US that could significantly impact our business and our financial results.

此外，我們繼續關注活躍的監管環境，包括歐盟和美國日益增加的法律和監管阻力，這些可能會對我們的業務和財務表現產生重大影響。

In closing, Q2 was another good quarter.

總而言之，第二季又是表現良好的季度。

We continue to execute well across our business priorities and have exciting opportunities in front of us to deliver more value to the people and businesses using our products around the world.

我們繼續在業務重點上執行良好，並面臨著令人興奮的機遇，可以為全球使用我們產品的人和企業提供更多價值。

With that, Krista, let's open up the call for questions.

克里斯塔，下面讓我們開始提問吧。

(Operator Instructions) Brian Nowak, Morgan Stanley.

（操作員指示） 摩根士丹利的 Brian Nowak。

I have two: one for Mark, one for Susan.

我有兩個：一個給馬克，一個給蘇珊。

Mark, I wanted to sort of go back to some of the new generative AI-enabled use cases for users and advertisers.

馬克，我想回顧一下針對用戶和廣告商的一些新的生成式人工智慧用例。

You talked about Meta AI, Studio, chatbots, [foundation] models.

您談到了 Meta AI、Studio、聊天機器人、[基礎]模型。

If you could just sort of hone in on one or two of those that you're most excited about, where you're seeing good signal that could be a real driver for the business in '25, '26, just so we sort of know where are you most focused on all those opportunities, it'd be helpful.

如果你能集中討論你最感興趣的一兩個方面，看看這些方面是否有好的信號，這些信號可能會成為 2025 年和 2026 年業務的真正驅動力，那麼我們知道在所有這些機會中你最關注什麼，這將會很有幫助。

And the second one, Susan, you have a lot of CapEx priorities from building new infrastructure for next-generation models, compute capacity.

第二，蘇珊，您有很多資本支出優先事項，包括為下一代模型建立新的基礎設施、運算能力。

Just walk us through again on the CapEx philosophy and any guardrails you have around ensuring you generate a healthy return on invested capital for investors from all the CapEx.

請再次向我們介紹資本支出概念以及您所採取的任何措施，以確保從所有資本支出中為投資者帶來健康的投資回報。

I can take the first one.

我可以拿第一個。

So I think the things that will drive the most results in '25 and '26 are actually the first category of things that I talked about in my comments, which are the ways that AI is shaping the existing products.

因此，我認為在 25 年和 26 年推動最大成果的因素實際上是我在評論中談到的第一類因素，即人工智慧塑造現有產品的方式。

So the ways that it's improving recommendations and helping people find better content as well as making the advertising experiences more effective.

因此，它可以改進推薦並幫助人們找到更好的內容，並使廣告體驗更有效。

I think there's a lot of upside there.

我認為那裡有很多好處。

Those are already products that are at scale.

這些已經是規模化的產品。

The AI work that we're doing is going to improve that.

我們正在進行的人工智慧工作將會改善這一點。

It will improve the experience and the business results.

它將改善體驗和業務成果。

The other areas that we're working on, I mean, I think you all know this from following our business for a while, but we have a relatively long business cycle of starting a new product, scaling it to something that reaches 1 billion people or more, and only then really focusing on monetizing at scale.

我們正在進行的其他領域，我想你們都知道，因為我們已經關注我們的業務有一段時間了，但我們從推出新產品到將其擴展到覆蓋 10 億人的產品，有一個相對較長的業務週期甚至更多，然後才真正專注於規模化盈利。

So realistically, for things like Meta AI or AI Studio, these are things that I think will increase engagement in our products and have other benefits that will improve the business and engagement in the near term.

因此，從現實角度來看，對於 Meta AI 或 AI Studio 之類的東西，我認為它們會增加我們產品的參與度，並帶來其他好處，從而在短期內改善業務和參與度。

But before we're really talking about monetization of any of those things by themselves, I mean, I don't think that anyone should be surprised that I would expect that that will be years, right?

但在我們真正談論這些東西本身的貨幣化之前，我的意思是，我認為任何人都不會感到驚訝，我預計這將會花費數年時間，對吧？

I think that that's like what we've seen with Reels.

我認為這就像我們在 Reels 上看到的一樣。

It's what we sell with all these things.

這就是我們所銷售的東西。

But I think for those who have followed our business for a long time, you can also get a pretty good sense of when things are going to work years in advance.

但我認為，對於那些長期關注我們業務的人來說，你也可以提前幾年很好地了解事情的發展。

And I think that the people who bet on those early indicators tend to do pretty well, which is why I wanted to share in my comments the early indicator that we had on Meta AI, which is, I mean, look, it's early.

我認為那些押注這些早期指標的人往往會做得相當好，這就是為什麼我想在我的評論中分享我們對 Meta AI 的早期指標，我的意思是，看，它還處於早期階段。

Last quarter, we -- I think it just started rolling it out a week or two before our earnings call.

上個季度，我們 - 我認為它是在收益電話會議前一兩週才開始推出的。

This time, we're a few months later.

這次，我們晚了幾個月。

And what we can say is I think we are on track to achieve our goal of being the most used AI assistant by the end of this year.

我認為我們預計在今年年底前實現成為最常用的人工智慧助理的目標。

And I think that's a pretty big deal.

我認為這是一件大事。

Is that the only thing we want to do?

這是我們唯一想做的事嗎？

No.

不。

I mean, we obviously want to grow that and grow the engagement on that to be a lot deeper, and then we'll focus on monetizing it over time.

我的意思是，我們顯然希望發展這一領域，並更深入地參與其中，然後我們將專注於隨著時間的推移將其貨幣化。

But the early signals on this are good, and I think that that's kind of all that we could reasonably have insight into at this point.

但這方面的早期訊號是好的，我認為這就是我們目前可以合理了解的全部內容。

But I do think that part of what's so fundamental about AI is it's going to end up affecting almost every product that we have in some way.

但我確實認為，人工智慧的根本性部分在於它最終將以某種方式影響我們擁有的幾乎所有產品。

It will improve the existing ones and will make a whole lot of new ones possible.

它將改善現有的技術並使許多新的技術成為可能。

So it's why there are all the jokes about how all the tech CEOs get on these earnings calls and just talk about AI the whole time.

所以這就是為什麼會有那麼多笑話說，所有的科技公司 CEO 在財報電話會議上全程談論人工智慧。

It's because it's actually super exciting, and it's going to change all these different things over multiple time horizons.

因為它實際上非常令人興奮，而且它將在多個時間範圍內改變所有這些不同的事情。

And Brian, I can take the second question.

布萊恩，我可以回答第二個問題。

On the ROI part of your question, I would broadly characterize our AI investments into two buckets: core AI and gen AI.

關於你問題的投資報酬率部分，我會將我們的人工智慧投資大致分為兩類：核心人工智慧和通用人工智慧。

And the two are really at different stages as it relates to driving revenue for our businesses and our ability to measure returns.

在推動我們業務收入和衡量回報的能力方面，兩者實際上處於不同的階段。

On our core AI work, we continue to take a very ROI-based approach to our investment here.

在我們的核心人工智慧工作中，我們繼續採取基於投資報酬率 (ROI) 的投資方式。

We're still seeing strong returns as improvements to both engagement and ad performance have translated into revenue gains, and it makes sense for us to continue investing here.

由於參與度和廣告效果的提升轉化為收入成長，我們仍然看到強勁的回報，因此繼續在此進行投資對我們來說是合理的。

Gen AI is where we're much earlier, as Mark just mentioned in his comments.

正如馬克在評論中提到的那樣，Gen AI 是我們更早進入的領域。

We don't expect our gen AI products to be a meaningful driver of revenue in '24.

我們預期我們的新一代人工智慧產品不會成為2024年營收的重要推手。

But we do expect that they're going to open up new revenue opportunities over time that will enable us to generate a solid return off of our investment while we're also open sourcing subsequent generations of Llama.

但我們確實預計，隨著時間的推移，它們將開闢新的收入機會，使我們能夠從投資中獲得可觀的回報，同時我們也將開放後續幾代 Llama 的源代碼。

And we've talked about the four primary areas that we're focused here on the gen AI opportunities to enhance the core ads business, to help us grow in business messaging, the opportunities around Meta AI, and the opportunities to grow core engagement over time.

我們已經討論了我們關注的四個主要領域，即增強核心廣告業務的人工智慧機會，幫助我們在商業訊息傳遞方面發展，圍繞元人工智慧的機會，以及增加核心參與度的機會。

The other thing I would say is we're continuing to build our AI infrastructure with fungibility in mind so that we can flex capacity where we think it will be put to best use.

我想說的另一件事是，我們將繼續建立我們的人工智慧基礎設施，並考慮到可替代性，以便我們可以在我們認為最佳利用的地方靈活調整容量。

The infrastructure that we build for gen AI training can also be used for gen AI inference.

我們為新一代人工智慧訓練所建構的基礎設施也可以用於新一代人工智慧推理。

We can also use it for ranking and recommendations by making certain modifications like adding general compute and storage.

我們還可以透過添加通用計算和儲存等修改來將其用於排名和推薦。

And we're also employing a strategy of staging our data center sites at various phases of development, which allows us to flex up to meet more demand and less lead time if needed while limiting how much spend we're committing to in the outer years.

我們也採用了在不同開發階段分階段部署資料中心的策略，這使我們能夠靈活地滿足更多需求，並在必要時縮短交付週期，同時限制我們在未來幾年的支出。

So while we do expect that we are going to grow CapEx significantly in 2025, we feel like we have a good framework in place in terms of thinking about where the opportunities are and making sure that we have the flexibility to deploy it as makes the most sense.

因此，雖然我們確實預計 2025 年資本支出將大幅增長，但我們覺得，我們已經建立了一個良好的框架，可以思考機會在哪裡，並確保我們能夠靈活地部署這些機會，從而最大限度地提高感覺。

Mark Shmulik, Bernstein.

馬克‧施穆里克，伯恩斯坦。

Just as we look at the revenue guidance and the outlook, Susan, any color you can share on just kind of the state of the overall digital ad market?

就像我們看一下收入指引和前景一樣，蘇珊，您能分享一下整個數位廣告市場的狀況嗎？

And you've highlighted some areas where you're seeing strength versus kind of some of the idiosyncratic efforts you've made to kind of improve the efficacy of the ad product.

您已經強調了一些您認為具有優勢的領域，以及您為提高廣告產品的效果所做的一些特殊努力。

We're continuing to see healthy global advertising demand, and we're also delivering ongoing ad performance improvements just related to all of the investments that we've continued to make over time in improving the sort of ads, targeting ranking, delivery, all of the fundamental infrastructure there.

我們持續看到全球廣告需求健康成長，我們也持續改善廣告效果，這與我們長期以來在改善廣告類型、定位排名、投放等方面所做的投資有關。

And we expect that all of that will continue to benefit ad spend in Q3.

我們預計，所有這些都將繼續有利於第三季的廣告支出。

We do expect year-over-year growth to slow in Q3 as we are lapping strong growth from China-based advertisers as well as strong Reels impression growth from a year ago.

我們確實預計第三季的同比增長將放緩，因為我們正在享受來自中國廣告商的強勁增長以及與去年同期相比強勁的 Reels 展示次數增長。

And we also expect modestly larger FX headwinds in Q3 based on current rates.

而且根據當前利率，我們預計第三季外匯逆風將略有加劇。

Eric Sheridan, Goldman Sachs.

高盛的艾瑞克‧謝裡丹 (Eric Sheridan)。

I'll just ask one.

我只問一個。

You called out building community size and what's happened in the United States as well as Threads.

您呼籲建立社區規模並討論美國和 Threads 發生的事情。

How are you thinking about those newer faster-growing elements of either Messaging or Threads as a platform and the mix between the potential for engagement growth and overall monetization longer term of either the messaging layer or Threads and what you're most excited about there to build to sort of capitalize on scale but bring it back towards monetization?

您如何看待訊息傳遞或線程平台中那些較新、增長較快的元素，以及訊息傳遞層或線程的長期參與度成長潛力和整體貨幣化之間的結合，以及您最興奮的是什麼？來充分利用規模但又將其帶回貨幣化？

I can start, and Susan can jump in if she has anything else that she wants to add.

我可以開始了，如果蘇珊還有什麼想補充的，也可以加入。

So the WhatsApp stat, I think, is really important as a business trend just because the United States punches above its weight in terms of, it's such a large percent of our revenue.

因此，我認為 WhatsApp 統計數據作為一種商業趨勢確實非常重要，因為美國在我們的收入中佔據了很大的比重。

So before, WhatsApp was sort of the leading messaging app in many countries around the world but not in the US And I think now that we're starting to make inroads into leading in the US as more and more people use the product and realize that, hey, it was a really good experience, the best experience for cross-platform communication and groups and on all these different things, I think that, that's going to just mean that all of the work that we're doing to grow the business opportunity there over time is just going to have a big tailwind if the US ends up being a big market.

之前，WhatsApp 是世界上許多國家領先的訊息應用程序，但在美國卻不是。非常好的體驗，是跨平台溝通和群組的最佳體驗，在所有這些不同的事情上，我認為這意味著我們為發展業務所做的所有工作如果美國最終成為一個大市場，那麼隨著時間的推移，那裡的機會將會產生巨大的順風。

So that's one reason why it's really relevant.

這就是它如此重要的原因之一。

It's obviously also personally somewhat gratifying to see all the people around us starting to use WhatsApp, so I think that's pretty fun but maybe somewhat less relevant from a business perspective.

看到我們周圍的所有人都開始使用 WhatsApp，我個人顯然也感到有些欣慰，所以我認為這很有趣，但從商業角度來看可能不太相關。

Threads, I think it's another example of something that it got off to about as good of a start of any app that I can think of.

線程，我想這是另一個例子，它可以和我能想到的任何應用程式一樣很好地開始。

I think it was the fastest-growing app to 100 million people.

我認為它是成長速度最快達到 1 億的應用程式。

And it's a good reminder that even when you have that start, the path from there to 1 billion people using an app is still multiple years.

這提醒我們，即使有了這個開始，從那時到 10 億人使用應用程式仍然需要數年時間。

And that's our product cycle.

這就是我們的產品週期。

And I think that that's something that is a little bit different about Meta in the way we build consumer products and the business around them than a lot of other companies that ship something and start selling it and making revenue from it immediately.

我認為 Meta 在打造消費產品及其周邊業務的方式上與許多其他公司略有不同，他們推出產品後立即開始銷售並賺取收益。

So I think that's something that our investors and folks thinking about analyzing the business, if needed, to always grapple with is all these new products, we ship them and then there's a multiyear time horizon between scaling them and then scaling them into not just consumer experiences but very large businesses.

因此，我認為這是我們的投資者和那些正在考慮分析業務的人需要始終解決的問題，即所有這些新產品，我們都會發貨，然後需要多年的時間才能將它們擴大到不僅僅是消費者市場。

But the thing that I think is just super exciting about Threads is that we've been building this company for 20 years, and there are just not that many opportunities that come around to grow 1 billion-person app.

但我認為 Threads 最令人興奮的地方在於，我們已經創建這家公司 20 年了，但發展一款擁有 10 億用戶的應用程式的機會並不多。

I mean, there are, I don't know, maybe a dozen of them in the world or something, right?

我的意思是，我不知道，世界上可能有十幾個這樣的人，對吧？

I mean, there are certainly more of them outside the company than inside the company, but we do pretty well and being able to add another one to the portfolio if we execute really well on this is just really exciting to have that potential.

我的意思是，公司外部的人才肯定比內部的多，但我們做得很好，如果我們在這方面執行得非常好，就能夠在投資組合中再增加一個，擁有這種潛力真的非常令人興奮。

Now obviously, there's a ton of work between now and there.

顯然，從現在到那時還有很多工作要做。

I mean, we're almost at 200 million.

我的意思是，我們已經快達到 2 億了。

So it's a really good milestone, I'm excited about that.

所以這是一個非常好的里程碑，我對此感到非常興奮。

A lot of work between this and it being a large part of the business.

這其中涉及很多工作，而且它是業務的很大一部分。

But I do think that these kind of opportunities are pretty rare and that's something that we're just really excited about.

但我確實認為這種機會非常罕見，這是我們真正感到興奮的事情。

I think the team is doing great work on it.

我認為該團隊在這方面做得很好。

Eric, I would just add to that in terms of nearer-term sources of impression growth, we really expect that video is going to remain a source of impression growth for us in the second half.

艾瑞克，我想補充一點，就近期印象成長來源而言，我們確實預計影片將在下半年繼續成為我們印象成長的來源。

On Instagram, we expect Reels to continue to drive growth, while on Facebook, we expect to grow overall video time while increasing the mix of short-form video, which creates more impression growth opportunities.

在 Instagram 上，我們預計 Reels 將繼續推動成長；而在 Facebook 上，我們預計整體影片時間將增加，同時增加短影片的組合，從而創造更多的印象增長機會。

And generally, we expect continued community growth across our apps.

總體而言，我們預計我們的應用程式社群將繼續蓬勃發展。

Doug Anmuth, JPMorgan.

摩根大通的道格安穆斯 (Doug Anmuth)。

One for Mark, one for Susan.

一份給馬克，一份給蘇珊。

Mark, just in terms of infrastructure and CapEx, you've talked about currently building out not just for Llama 3 and 4 but really out to 7 perhaps and then Llama 4, 10x the compute required versus Llama 3.

馬克，僅就基礎設施和資本支出而言，您談到目前的建設範圍不僅限於Llama 3 和4，而且實際上可能擴展到Llama 7，然後是Llama 4，所需的計算量是Llama 3 的10倍。

Just given how much you're building ahead, how does that influence the shape of the CapEx curve over a multiyear period?

考慮到你未來的建設規模，這會對多年期資本支出曲線的形狀產生什麼影響？

And then Susan, if you could talk a little bit more about the 3Q outlook.

然後蘇珊，您能否再談談第三季的前景？

I know you're talking about tougher comps, but at the same time, it really suggests only one point of FX neutral decel at the high end.

我知道您在談論更強的競爭對手，但與此同時，它實際上只表明高端的 FX 中性減速點只有一個。

So just curious if there's anything else you can point to more specifically that's driving the expected strength here.

所以我很好奇，您是否可以更具體地說明其他什麼因素推動了預期的實力？

Thanks, Doug.

謝謝，道格。

I can go ahead and talk about both of those.

我可以繼續談論這兩點。

So your first question was sort of about the longer-term CapEx outlook.

所以您的第一個問題是關於長期資本支出前景。

We haven't really shared an outlook sort of on the longer-term CapEx trajectory.

我們還沒有真正分享長期資本支出走勢的展望。

In part, infrastructure is an extraordinarily dynamic planning area for us right now.

在某種程度上，基礎設施對我們來說現在是一個非常活躍的規劃領域。

We're continuing to work through what the scope of the gen AI road maps will look like over that time.

我們將繼續研究在此期間新一代人工智慧路線圖的範圍。

Our expectation, obviously again, is that we are going to significantly increase our investments in AI infrastructure next year, and we'll give further guidance as appropriate.

顯然，我們的預期是，明年我們將大幅增加對人工智慧基礎設施的投資，並將在適當的情況下提供進一步的指導。

But we are building all of that CapEx, again with the factors in mind that I talked about previously, thinking about both how to build it flexibly so we can deploy to core AI and gen AI use cases as needed and making sure that we both feel good about the returns that we're seeing on the core AI investments, which we're able to measure more immediately.

但我們正在建立所有這些資本支出，同樣要考慮到我之前談到的因素，思考如何靈活地建構它，以便我們可以根據需要部署到核心人工智慧和新一代人工智慧用例中，並確保我們都感覺我們對核心人工智慧投資的回報感到滿意，我們能夠更立即地進行衡量。

And then we feel good about the opportunities in the gen AI efforts.

我們對新一代人工智慧領域的發展機會感到十分樂觀。

Your second question was about the Q3 revenue outlook.

您的第二個問題是關於第三季營收前景。

Again, I mentioned this earlier, we have seen healthy global advertising demand on our platform.

我之前再次提到過，我們看到了我們平台上健康的全球廣告需求。

We're delivering ongoing ad performance improvements, which, again, we feel like is a result of many, many quarters of effort that have accrued and will continue to accrue value to our platform.

我們正在不斷改進廣告效果，我們再次認為這是我們許多季度努力的結果，這些努力已經累積並將繼續為我們的平台創造價值。

And we saw basically in Q2 where revenue grew 22%, that there was broad-based strength across regions and verticals, including particular strength among smaller advertisers, and we expect that generally to continue into Q3.

我們在第二季度看到營收成長了 22%，各地區和垂直產業都呈現普遍成長勢頭，其中小型廣告商的增幅尤其大，我們預計這種勢頭將持續到第三季。

Justin Post, Bank of America.

美國銀行的賈斯汀·波斯特 (Justin Post)。

I just want to get back to the comment on US young adult user growth, especially maybe on Facebook and Instagram.

我只是想回到關於美國年輕用戶成長的評論，尤其是在 Facebook 和 Instagram 上。

I know you made a big change with Reels a couple of years ago.

我知道幾年前您對 Reels 做了很大的改變。

But what are those users doing on Facebook and Instagram?

但是這些用戶在 Facebook 和 Instagram 上做什麼呢？

And can you give us any quantification of the usage growth?

您能為我們提供使用量成長的量化數據嗎？

Thanks, Justin.

謝謝，賈斯汀。

So building products with young adults in mind has been a core priority area for the Facebook team in recent years, and we've been very encouraged to see these efforts translate into engagement growth with this cohort.

因此，打造針對年輕人的產品一直是 Facebook 團隊近年來的核心優先領域，我們非常高興看到這些努力轉化為年輕人群體參與度的成長。

We've seen healthy growth in young adult app usage in the US and Canada for the past several quarters.

過去幾個季度，我們看到美國和加拿大年輕人應用程式的使用量健康成長。

And we've seen that products like Groups and Marketplace have seen particular traction with young adults.

我們發現，團體和市場等產品對年輕人特別有吸引力。

Posting to groups in the US and Canada has been growing.

在美國和加拿大的群組中發佈的數量一直在增加。

That's been boosted mainly by young adults.

這主要得益於年輕人。

And we also see that they are active users of Marketplace, which has benefited from product improvements and strong demand for secondhand products in the US.

我們也看到他們是 Marketplace 的活躍用戶，受益於產品的改進和美國對二手產品的強勁需求。

Mark Mahaney, Evercore ISI.

馬克‧馬哈尼 (Mark Mahaney)，Evercore ISI。

I was going to ask about Marketplace so that's a nice segue.

我本來想詢問有關 Marketplace 的問題，所以這是一個很好的過渡。

It's a great, somewhat under-monetized or arguably very under-monetized asset.

這是一項偉大的資產，但其貨幣化程度有些不足，或可說是嚴重不足。

I know you indirectly monetize it and it's a very large marketplace.

我知道你間接地將其貨幣化，這是一個非常大的市場。

It may even be bigger than eBay.

它甚至可能比 eBay 還要大。

Your thoughts on what you may want to do in the future in terms of monetizing it, in part, maybe even improve the quality of the Marketplace.

您對未來可能希望如何將其貨幣化的想法，在某種程度上甚至可能改善市場的品質。

And then secondly, I just want to ask you about headcount.

其次，我只想問您有關員工人數的問題。

It's down about 1% year over year.

與去年同期相比下降了約 1%。

You're pretty much back at par with where the employee headcount was prior to significant reduction.

您的員工人數基本上恢復到了大幅削減之前的狀態。

How should we think about headcount growth going forward?

我們該如何看待未來的員工數量成長？

Did you talk about a significant growth in CapEx?

您談到資本支出的大幅成長嗎？

Should we expect a moderate growth in headcount significant?

我們是否應該預期員工人數會出現適度成長？

Any thoughts on that would be helpful.

對此的任何想法都會有幫助。

Thanks, Mark.

謝謝，馬克。

On your first question about Marketplace, again, we're obviously excited that it's been one of the drivers of strength in young adults.

關於您關於 Marketplace 的第一個問題，我們再次感到非常高興，因為這是推動年輕人力量成長的動力之一。

I would probably just say that more generally, Marketplace is one prong in a broader commerce strategy that we have, which continues to be focused on basically creating the best shopping experience on our platform.

我可能只是想更廣泛地說，Marketplace 是我們更廣泛的商業策略的一個方面，該策略將繼續專注於在我們的平台上創造最佳的購物體驗。

Marketplace is obviously consumer-oriented.

市場顯然是以消費者為導向的。

The broader part of the commerce strategy is about making it easier for businesses to advertise their products, for buyers to find and purchase relevant items on our platform.

商業策略的更廣泛的部分是讓企業更容易宣傳他們的產品，讓買家更容易在我們的平台上找到並購買相關產品。

And to that end, I would say that we feel quite happy with also the investments we've been making in Shops ads.

為此，我想說我們對我們在商店廣告方面的投資感到非常滿意。

Shops ads revenue is growing at a strong year-over-year pace.

商店廣告收入較去年同期強勁成長。

We're seeing Shops ads drive incremental performance for advertisers, and it's also working well in combination with some of our other products like Advantage+ shopping.

我們看到商店廣告為廣告主帶來了增量業績，並且與我們的一些其他產品（如 Advantage+ 購物）結合使用效果也很好。

Your second question was about headcount.

您的第二個問題是關於員工人數的。

We continue to be disciplined about where we're allocating new headcount to ensure that it's really focused on our core company priorities, but we're also working down a prior hiring underrun.

我們將繼續嚴格控制新員工的分配，以確保他們真正專注於我們公司的核心重點，但我們也在努力減少先前的招聘不足。

And as we further close that hiring underrun over the course of this year, I do expect that we will end 2024 with in-seat reported headcount that is meaningfully higher than where we ended 2023.

隨著我們在今年進一步彌補招募不足，我預計，到 2024 年底，我們的在職員工人數將比 2023 年底大幅增加。

We aren't providing sort of 2025 headcount growth expectations yet as we haven't started our budgeting process yet.

由於我們尚未開始預算編制流程，因此我們尚未提供 2025 年員工人數成長預期。

But again, I expect that we will primarily target our hiring to focus on priority areas, and we will be running a very disciplined headcount process.

但我再次強調，我們預期招募的主要重點是優先領域，我們將執行非常嚴謹的員工人數統計流程。

Youssef Squali, Truist Securities.

Truist Securities 的 Youssef Squali。

So the AI system using Llama 3.1 has been incorporated in different variations and looks really impressive and seems to be getting closer to becoming a full search engine for virtually everything except for commercial queries so far.

因此，使用 Llama 3.1 的 AI 系統已被納入不同的變體，看起來確實令人印象深刻，而且到目前為止似乎越來越接近成為幾乎所有內容（商業查詢除外）的完整搜尋引擎。

So are there any plans to open it up to the broader web?

那麼有沒有計劃將其向更廣泛的網路開放呢？

Kind of like what may be OpenAI is off to testing, maybe link it to third-party marketplaces for commercial search, et cetera.

有點像 OpenAI 正在進行的測試，也許將其連結到第三方市場進行商業搜尋等等。

And then on Ray-Ban, can you maybe talk a little bit more about the opportunity to deepen your relationship with EssilorLuxottica?

然後說到雷朋，您能否再談談加深與 EssilorLuxottica 關係的機會？

What would that look like?

那會是什麼樣子的呢？

What kind of areas are the most exciting to you, Mark, in that relationship?

馬克，在你們的這段關係中，哪些方面最讓你興奮？

Yes.

是的。

I'm very excited with how Llama 3.1 landed.

我對 Llama 3.1 的發布感到非常興奮。

I think the team there is doing really great work going from the first version of Llama, the Llama 2 last year that was a generation behind the frontier and now Llama 3.1, which is basically competitive and, in some ways, leading the other top closed models.

我認為那裡的團隊做得非常出色，從第一版Llama 開始，到去年比Frontier 落後一代的Llama 2，再到現在的Llama 3.1，基本上已經具備競爭力，並且在某些方面領先於其他頂級封閉式模型。

Meta AI uses a version of Llama 3.1 as well as a bunch of other services that we've built to kind of build a cohesive product.

Meta AI 使用 Llama 3.1 版本以及我們建立的一系列其他服務來建立一個有凝聚力的產品。

And when I was talking before about we have the initial usage trends around Meta AI but there's a lot more that we want to add, things like commerce and you can just go vertical by vertical and build out specific functionality to make it useful in all these different areas are eventually, I think, what we're going to need to do to fulfill the potential around just being the ideal AI assistant for people.

我之前說過，我們初步了解了 Meta AI 的使用趨勢，但我們還想添加更多功能，例如商業，你可以逐個垂直地發展，建立特定的功能，讓它在所有這些領域發揮作用我認為，我們最終需要在不同的領域開展工作，才能發揮其潛力，成為人類理想的人工智慧助理。

So it's a long road map.

所以這是一份漫長的路線圖。

I don't think that this stuff is going to get finished in the next couple of quarters or anything like that.

我認為這些事情不會在接下來的幾個季度或類似的時間內完成。

But this is part of what's going to happen over the next few years as we build something that will, I think, just be a very widely used service.

但這只是未來幾年將要發生的事情的一部分，因為我們將建立一項我認為將會被廣泛使用的服務。

So I'm quite excited about that.

所以我對此感到非常興奮。

And we're going to continue working on Llama, too.

我們也將繼續致力於 Llama 的開發。

So I mean, you mentioned Llama, and I think the question was a little more about Meta AI but they're both -- I mean, they're related.

所以我的意思是，你提到了 Llama，我認為問題更多的是關於 Meta AI，但它們都是 - 我的意思是，它們是相關的。

Llama is sort of like the engine that powers the product and it's open source, and I'm just excited about the progress that we're making on both of those.

Llama 有點像是驅動產品的引擎，它是開源的，我對我們在這兩方面的進展感到非常興奮。

On the smart glasses, EssilorLuxottica is a great partner.

在智慧眼鏡方面，EssilorLuxottica 是個很好的合作夥伴。

We are now in the second generation of the Ray-Ban Meta glasses.

我們現在正處於第二代雷朋 Meta 眼鏡的時代。

They're doing well, better than I think we had expected, and we expected them to grow meaningfully from the first generation so that's been a very positive surprise.

他們的經營狀況很好，比我們預期的要好，我們預計他們將從第一代開始實現有意義的成長，所以這是一個非常積極的驚喜。

And I think part of that is that it's just well positioned to dovetail well with the AI revolution that we're seeing and offering all kinds of new functionality there.

我認為部分原因在於它能夠與我們正在看到的人工智慧革命完美契合，並在其中提供各種新功能。

So that was great.

這真是太棒了。

But EssilorLuxottica is a great company that has a lot of different products that we hope to be able to partner with to just continue building new generations of the glasses and deepen the AI product and make it better and better.

但 EssilorLuxottica 是一家很棒的公司，擁有許多不同的產品，我們希望能夠與其合作，繼續打造新一代眼鏡，深化 AI 產品，使其越來越好。

I think there's a lot more to go from here.

我認為接下來還有很長的路要走。

And compared to what we thought at this point, it's doing quite well compared to, I think, what it needs to be, to be like a really leading piece of consumer electronics, I think we're still early but all the signs are good.

與我們目前的想法相比，我認為它的表現相當不錯，與它需要達到的水平相比，要成為真正領先的消費性電子產品，我認為我們還處於早期階段，但所有跡像都是好的。

Ron Josey, Citi.

花旗銀行的 Ron Josey。

I want to get back, Mark, to the commentary on open source and Llama 3.

馬克，我想回到對開源和 Llama 3 的評論。

Totally understand that Meta is not offering a public cloud, and so what I wanted to hear from you is maybe a little bit more on the product vision of products that come out of Llama 3.

我完全理解 Meta 不提供公有雲，因此我想從您那裡聽到更多關於 Llama 3 產品的產品願景的資訊。

And meaning potentially offering some of these products to other companies, call it, for customer service or call center offerings or other verticals.

這意味著可能會將其中一些產品提供給其他公司，用於客戶服務或呼叫中心產品或其他垂直市場。

And so any insights on just how you envision maybe the open source and Llama 3.1 can sort of offer greater enterprise services for others to benefit from?

那麼，您對開源和 Llama 3.1 如何為其他人提供更優質的企業服務有何看法？

So Llama is the foundation model that people can shape into all kind of different products.

因此，Llama 是人們可以塑造成各種不同產品的基礎模型。

So whether it's Meta AI for ourselves or the AI Studio or the business agents or like the assistant that's in the Ray-Ban glasses, like all these different things are basically products that have been built with Llama.

因此，無論是我們自己的 Meta AI，還是 AI Studio、商業代理或雷朋眼鏡中的助手，所有這些不同的東西基本上都是用 Llama 打造的產品。

And similarly, any developer out there is going to be able to take it and build a whole greater diversity of different things as well.

同樣地，任何開發人員都能夠利用它並建立出更多樣化的不同事物。

Like I talked about, I think the reason why open sourcing -- this is so valuable for us is that we want to make sure that we have the leading infrastructure to power the consumer and business experiences that we're building.

正如我所說的，我認為開源對我們來說如此有價值的原因是我們希望確保我們擁有領先的基礎設施來支持我們正在建立的消費者和商業體驗。

But the infrastructure, it's not just a piece of software that we can build in isolation.

但是基礎設施不僅僅是我們可以孤立地建立的軟體。

It really is an ecosystem with a lot of different capabilities that other developers and people are adding to the mix, whether that's new tools to distill the models into the size that you want for a custom model, or ways to fine-tune things better or make inference more efficient or all different other kinds of methods that we haven't even thought of yet, the silicon optimizations that the silicon companies are doing, all the stuff.

它確實是一個生態系統，擁有許多不同的功能，其他開發人員和人員正在將其添加到組合中，無論是將模型提煉成自訂模型所需大小的新工具，還是更好地微調事物的方法，使推理更有效率，或所有我們還沒想到的其他不同類型的方法，矽片公司正在進行的矽片優化，等等。

It's an ecosystem.

這是一個生態系統。

So we can't do all that ourselves.

所以我們無法自己做這一切。

And if we built Llama and just kind of kept it within our walls, then it wouldn't actually be as valuable for us to build all the products that we're building as it's going to end up being.

如果我們建造了 Llama 並且只是將它局限於自己的公司內部，那麼我們建造的所有產品實際上都不會像最終那樣有價值。

So that's the business strategy around that.

這就是圍繞該問題的商業策略。

And that's why we don't feel like we need to necessarily build a cloud and sell it directly in order for it to be a really positive business strategy for us.

這就是為什麼我們認為我們不一定需要建立雲端並直接銷售它，才能使其成為我們真正積極的商業策略。

And part of what we're doing is working closely with AWS, I think, especially did great work for this release.

我們的工作之一就是與 AWS 密切合作，我認為，我們為此次發布做出了巨大貢獻。

Other companies like Databricks, NVIDIA, of course, other big players like Microsoft with Azure, and Google Cloud, they're all supporting this.

當然，其他公司，例如 Databricks、NVIDIA，以及其他大公司，例如擁有 Azure 的微軟和 Google Cloud，都支援這一點。

And we want developers to be able to get it anywhere.

我們希望開發人員能夠在任何地方獲得它。

I think that's one of the advantages of an open source model like Llama is -- it's not like you're locked into one cloud that offers that model, whether it's Microsoft with OpenAI or Google with Gemini or whatever it is, you can take this and use it everywhere and we want to encourage that.

我認為這是 Llama 等開源模型的優勢之一——它不會將你鎖定在提供該模型的某一個雲端平台中，無論是微軟的 OpenAI 還是谷歌的 Gemini，你都可以使用它並在任何地方使用它，我們希望鼓勵這樣做。

So I'm quite excited about that.

所以我對此感到非常興奮。

The enterprise and business applications that we're going to be most focused on, though, in addition to just optimizing the advertiser experience like I talked about in my comments earlier, it is the business agent piece.

我們最關注的企業和商業應用程序，除了優化廣告商體驗（就像我之前在評論中提到的）之外，還有商業代理部分。

I just think that there's a huge potential like I said earlier.

我只是認為，就像我之前說的，它有巨大的潛力。

I think pretty much every business today has an e-mail address, they have a website, they have social media accounts.

我認為當今幾乎每家企業都有一個電子郵件地址、一個網站和一個社群媒體帳號。

I think in the future, they're going to have at least one, if not multiple, business agents that can do the whole range of things from interacting to help people buy things to helping support the sales that they've done if they have issues with the product, if they need to get in touch with you for something.

我認為，在未來，他們將至少擁有一個（如果不是多個）業務代理，可以處理從互動到幫助人們購買商品到幫助支持他們所做的銷售等所有事情。與您聯繫。

And we already see people interacting with businesses over messaging working quite well in countries that have low cost of labor.

我們已經看到，在勞動成本低廉的國家，人們透過簡訊與企業互動的效果相當好。

But the thing is that in order to have someone answering everyone's questions is quite expensive in a lot of countries.

但問題是，在許多國家，讓一個人回答所有人的問題的成本相當高。

And I think that this is like a thing that AI, I think, is just going to be very well suited towards doing.

我認為這正是人工智慧非常適合做的事情。

And when we can make that easy for the hundreds of millions of businesses that use our platforms to pull in all their information and their catalogs and the history and all the content that they've shared and really just quickly stand up an agent, I think that's going to be awesome.

當我們能夠讓使用我們平台的數億企業輕鬆地獲取他們的所有資訊、目錄、歷史記錄和他們分享的所有內容，並真正快速地建立代理時，我認為那將會非常棒。

So we can combine Llama with a lot of custom work that we're doing in our business teams and couple that with all the other investment that the rest of the ecosystem is doing to make Llama good.

因此，我們可以將 Llama 與我們在業務團隊中所做的大量客製化工作相結合，並將其與生態系統其他部分為完善 Llama 所做的所有其他投資結合起來。

And I think that's going to be huge, but that's just one area.

我認為這將會是一個巨大的進步，但這只是一個領域。

This really goes across all of the different products that we're building, both consumer and business.

這實際上涉及我們正在開發的所有不同產品，包括消費者產品和商業產品。

So it's a lot of exciting stuff.

所以這有很多令人興奮的事情。

Krista, we have time for one last question.

克里斯塔，我們還有時間問最後一個問題。

Ross Sandler, Barclays.

巴克萊銀行的羅斯桑德勒。

Mark, so on Monday in your interview with Jensen, you said something along the lines of if scaling ended up stopping one day, you'd have five years of product work to do and ahead of you.

馬克，週一在你接受 Jensen 採訪時，你說過類似這樣的話：如果有一天擴展停止了，那麼你將有五年的產品工作要做。

So outside of agents or AI assistants, what other areas in AI are you thinking about or looking at in that five-year road map?

那麼，除了代理商或人工智慧助理之外，在五年路線圖中，您還在考慮或關注人工智慧的哪些其他領域？

And then the second question is maybe one more stab at the capacity question.

第二個問題也許是對容量問題的再一次嘗試。

You guys said that Llama 3.1 was trained on 16,000 H100s.

你們說 Llama 3.1 在 16,000 台 H100 上進行了訓練。

You've also said that you're going to have 600,000 available by year-end.

您還說過到年底您將有 60 萬個可用庫存。

So even if we kind of go up to 160,000 GPUs for Llama 4, we have plenty of extra capacity for inference and future products.

因此，即使我們為 Llama 4 配置多達 160,000 個 GPU，我們也有足夠的額外容量用於推理和未來產品。

How are you guys modeling out this entire kind of CapEx road map between training, inference, and future things?

你們如何在訓練、推理和未來事物之間建模整個資本支出路線圖？

That's all.

就這樣。

I can start with the first one, and then I'll let Susan answer the second one.

我可以從第一個問題開始，然後請蘇珊回答第二個問題。

It's an interesting question.

這是一個有趣的問題。

It's a little hypothetical because I mean, I do think it's true that if, let's say, there were no future foundation models.

這有點假設，因為我的意思是，我確實認為，如果說沒有未來的基礎模型，那麼這是真的。

I think there would just be a huge amount of product innovation that the industry would bring to bear, and that just takes time.

我認為該行業將會帶來大量的產品創新，但這需要時間。

But then at the same time, there are going to be future foundation models and they're going to be awesome and unlock new capabilities and we're planning our products around those.

但同時，未來將會有基礎模型，它們將會非常棒並釋放新的功能，我們正在圍繞這些模型規劃我們的產品。

So I'm not really planning our product roadmap assuming that there isn't future innovation.

因此，我實際上並沒有在假設未來沒有創新的情況下規劃我們的產品路線圖。

On the contrary, we are planning what's going to be in Llama 4 and Llama 5 and beyond based on what capabilities we think are going to be most important for the road map that I just laid out for having the breadth of utility that you're going to need in something like Meta AI, making it set businesses and creators and individuals can stand up any kind of AI agents that they want, that you're going to have these kind of real-time, multimodal glasses with you all the time that will just be increasingly useful for all the things that you're doing.

相反，我們正在規劃 Llama 4、Llama 5 及以後版本，這些功能基於我們認為對我剛剛列出的路線圖來說最重要的功能，以便提供您所需的廣泛實用性需要像Meta AI 這樣的東西，讓企業、創作者和個人能夠創建他們想要的任何類型的人工智慧代理，這樣你就可以隨時帶著這種實時、多模式的眼鏡這對你正在做的所有事情都會越來越有用。

I guess this kind of dovetails what I'd expect Susan to talk about next.

我想這與我期望蘇珊接下來要談論的內容很吻合。

And we do have this huge set of use cases already about people wanting to discover content and interact with their friends and businesses reaching people, and all that stuff is getting better with this, too.

我們確實已經擁有大量的用例，關於人們想要發現內容、與他們的朋友互動以及企業接觸人們，而這一切也都會變得更好。

I guess my point there was it's just there's some lag between the technology becoming available and the products becoming kind of fully explored in the space.

我的觀點是，技術的普及和產品在該領域的充分探索之間存在著一定的滯後。

And I just think that that was kind of my way of saying that I think that this is just a very exciting area where there's just going to be a lot of innovation for a long time to come.

我只是認為，這只是我表達的一種方式，我認為這是一個非常令人興奮的領域，在未來很長一段時間內將會出現大量的創新。

I'll let Susan take a stab at the numbers around the GPUs and all that.

我會讓蘇珊嘗試計算 GPU 和所有這些方面的數字。

Thank you.

謝謝。

We are clearly in the process of building out a lot of capacity, and Mark has alluded to that in his comments about what we have needed to train prior generations and the next generation of Llama.

顯然，我們正在不斷增強自身能力，馬克在談到我們需要培訓前幾代和下一代駱駝時也提到了這一點。

And that's driving sort of what we've talked about in terms of the significant growth in CapEx in 2025.

這正是我們所談論的 2025 年資本支出大幅成長的動力。

And we aren't really in the position now to share a longer-term outlook.

而我們現在還無法真正分享長期前景。

When we think about sort of any given new data center project that we're constructing, we think about how we will use it over the life of the data center.

當我們考慮正在建置的任何新資料中心專案時，我們都會考慮如何在資料中心的整個生命週期中使用它。

We think about the amount of capacity we would use in terms of training whatever the subsequent generations of Llama are and architected around that.

我們會考慮用於訓練後續幾代 Llama 所需的容量，並圍繞這一點進行架構設計。

But then we also look at how we might use it several years into its lifetime towards other use cases across our core business, across what we think might be future needs for inference, for generative AI-based products.

但隨後，我們也會研究如何在其生命週期的幾年內將其應用於我們核心業務的其他用例，應用於我們認為未來可能對推理和基於生成人工智慧的產品的需求。

So there's sort of a whole host of use cases for the life of any individual data center ranging from gen AI training at its outset to potentially supporting gen AI inference to being used for core ads and content ranking and recommendation and also thinking through the implications, too, of what kinds of servers we might use to support those different types of use cases.

因此，任何單一資料中心的生命週期中都有一系列的用例，從最初的人工智慧訓練到可能支援人工智慧推理，再到用於核心廣告和內容排名和推薦，同時也要考慮其影響，我們可能使用什麼類型的伺服器來支援不同類型的用例。

So we are really mapping across a wide range of potential use cases when we undertake any given project.

因此，當我們承擔任何給定項目時，我們實際上都在映射各種潛在的用例。

And we're really doing that with both a long time horizon in mind, again, because of the long lead times in spinning up data centers, but also recognizing that there are multiple decision points in the lifetime of each data center in terms of thinking through when to order servers and what servers to order and what you'll put them towards.

我們這樣做確實是為了長遠考慮，因為啟動資料中心需要很長的準備時間，但我們也認識到，每個資料中心在生命週期中都有多個決策點，需要考慮透過何時訂購伺服器、訂購什麼伺服器以及將它們用於什麼用途。

And that gives us flexibility to make the sort of the best decisions based on the information we have in the future.

這使我們能夠靈活地根據未來掌握的資訊做出最佳決策。

Great.

偉大的。

Thank you all for joining us today.

感謝大家今天的參與。

We appreciate your time, and we look forward to speaking with you again soon.

感謝您的時間，我們期待很快再次與您交談。

This concludes today's conference call.

今天的電話會議到此結束。

Thank you for your participation, and you may now disconnect.

感謝您的參與，您現在可以斷開連接。