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

Good afternoon. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to the Meta second-quarter earnings conference call. (Operator Instructions) This call will be recorded. Thank you very much.

午安.我叫克里斯塔，今天我將擔任你們的會議操作員。此時此刻，我歡迎大家參加 Meta 第二季財報電話會議。 （操作員說明）此通話將會被錄音。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，您可以開始了。

Thank you. Good afternoon, and welcome to Meta Platform's second-quarter 2024 earnings conference call. Joining me today to discuss our results are Mark Zuckerberg, CEO; and Susan Li, CFO.

謝謝。下午好，歡迎參加 Meta Platform 2024 年第二季財報電話會議。今天與我一起討論我們的結果的是執行長馬克祖克柏 (Mark Zuckerberg)；和財務長李蘇珊。

Before we get started, I would like to take this opportunity to remind you that our remarks today will include forward-looking statements. Actual results may differ materially from those contemplated by these forward-looking statements. 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.

在我們開始之前，我想藉此機會提醒您，我們今天的言論將包含前瞻性陳述。實際結果可能與這些前瞻性陳述預期的結果有重大差異。今天的收益新聞稿和我們向 SEC 提交的 10-Q 表格季度報告中列出了可能導致這些結果出現重大差異的因素。

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. During this call, we will present both GAAP and certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in today's earnings press release. The earnings press release and an accompanying investor presentation are available on our website at investor.fb.com.

我們在本次電話會議中所做的任何前瞻性陳述均基於截至目前的假設，我們不承擔因新資訊或未來事件而更新這些陳述的義務。在本次電話會議中，我們將介紹 GAAP 和某些非 GAAP 財務指標。今天的收益新聞稿中包含了 GAAP 與非 GAAP 指標的調整表。收益新聞稿和隨附的投資者簡報可在我們的網站 Investor.fb.com 上取得。

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. Thanks, Ken, and hey, everyone. Thanks for joining today. This was a strong quarter for our community and business. We estimate that there are now more than 3.2 billion people using at least one of our apps each day. The growth we're seeing here in the US has especially been a bright spot. 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.

好的。謝謝，肯，嘿，大家。感謝您今天加入。對於我們的社區和企業來說，這是一個強勁的季度。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。我們在美國看到的成長尤其是一個亮點。 WhatsApp 目前在美國每月活躍用戶超過 1 億，我們看到 Facebook、Instagram 和 Threads 在美國和全球的同比增長也良好。

I'm particularly pleased with the progress that we're making with young adults on Facebook. The numbers we're seeing, especially in the US, really go against the public narrative around who's using the app. 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. Another bright spot is Threads, which is about to hit 200 million monthly actives. We're making steady progress towards building what looks like it's going to be another major social app. And we're seeing deeper engagement and I'm quite pleased with the trajectory here.

我對我們在 Facebook 上與年輕人取得的進展感到特別滿意。我們看到的數字，尤其是在美國，確實與有關誰使用該應用程式的公眾敘述背道而馳。幾年前，我們開始將應用程式更專注於 18 至 29 歲的人群，很高興看到這些努力正在帶來良好的結果。另一個亮點是Threads，其月活躍量即將達到2億。我們正在穩步推進，打造看起來將成為另一個主要社交應用程式。我們看到了更深入的參與，我對這裡的發展軌跡非常滿意。

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. So let's start. Across Facebook and Instagram, advances in AI continue to improve the quality of recommendations and drive engagement. And we keep finding that as we develop more general recommendation models, content recommendations get better.

當然，現在的大主題是人工智慧，我今天的評論將集中在三個領域：人工智慧對我們的應用程式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會，以及人工智慧如何塑造我們的虛擬宇宙工作。那麼就讓我們開始吧。在 Facebook 和 Instagram 上，人工智慧的進步不斷提高推薦品質並提高參與度。我們不斷發現，隨著我們開發更通用的推薦模型，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. 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.

在本季度，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，將真正的較長視訊和直播帶入單一體驗。這使我們能夠擴展統一的人工智慧系統，與我們最初從 CPU 轉向 GPU 相比，該系統已經提高了 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. We're not there yet. There's still upside and we're making good progress here.

隨著時間的推移，我希望看到我們朝著一個統一的推薦系統發展，該系統為所有內容提供支持，包括您在我們所有服務中可能認識的人等內容。我們還沒到那兒。仍有上升空間，我們正在取得良好進展。

AI is also going to significantly evolve our services for advertisers in some exciting ways. 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. Eventually, we got to the point where our ad systems could better predict who would be interested than the advertisers could themselves. But today, advertisers still need to develop creative themselves. 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.

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。過去，廣告商帶著他們想要接觸的特定受眾來找我們，例如某個年齡層、地理位置或興趣。最終，我們的廣告系統可以比廣告商自己更好地預測誰會感興趣。但今天，廣告商仍然需要自己開發創意。在未來幾年，人工智慧也將能夠為廣告商產生創意，並且還能夠根據人們的看法對其進行個人化。

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

從長遠來看，廣告商基本上只能告訴我們業務目標和預算，我們將為他們做剩下的事情。隨著時間的推移，我們將逐步實現這一目標，但我認為這將是一件非常重要的事情。

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. We have an exciting road map ahead of things that we want to add. 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. Some of the use cases are utilitarian, like searching for information or role-playing difficult conversations before you have them with another person. 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.

繼續討論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，它有望實現我們在年底前成為最常用的人工智慧助理的目標。在我們想要添加的內容之前，我們已經制定了令人興奮的路線圖。但最重要的是，Meta AI 感覺它有望成為一項重要的服務，並且在智慧和功能方面都在快速改進。有些用例是功利性的，例如在與另一個人進行對話之前搜尋資訊或角色扮演困難的對話。其他用途則更具創意，例如新的「想像自己」功能，可讓您創建自己的圖像，以您想要的任何風格做任何您想做的事情。

And part of the beauty of AI is that it's general. So we're still uncovering the wide range of use cases that it's valuable for. 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. And this week, we launched AI Studio, which lets anyone create AIs to interact with across our apps. I think the creators are especially going to find this quite valuable.

人工智慧的部分優點在於它的通用性。因此，我們仍在探索它有價值的廣泛用例。我們願景的一個重要部分是，我們不僅僅是創建一個人工智慧，而是讓很多人能夠創建自己的人工智慧。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。我認為創作者們會特別發現這一點非常有價值。

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. But there are only so many hours in the day. 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. So I'm quite excited about this. But this goes beyond creators, too. 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.

我們的應用程式中有數百萬創作者，這些人希望與他們的社群進行更多的互動，而他們的社群也希望與他們進行更多的互動。但一天只有這麼多小時。因此，現在他們將能夠使用 AI Studio 創建 AI 代理，引導他們與社群聊天、回答人們的問題、創建內容等等。所以我對此感到非常興奮。但這也超出了創作者的範圍。任何人都可以根據自己的興趣或不同的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. We're still in alpha testing with more and more businesses. The feedback we're getting is positive so far. 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. 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. When this is working at scale, I think that this is going to dramatically accelerate our business messaging revenue. 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.

商業人工智慧是這裡的另一個重要部分。我們仍在對越來越多的企業進行 alpha 測試。到目前為止，我們得到的回饋是正面的。隨著時間的推移，我認為就像每個企業都有網站、社群媒體和電子郵件地址一樣，未來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。我們的目標是讓每個小型企業（最終是每個企業）都能輕鬆地將其所有內容和目錄提取到人工智慧代理中，從而推動銷售並節省資金。當它大規模發揮作用時，我認為這將極大地加速我們的商業消息收入。這裡還有很多其他新機會，我也對此感到興奮，但我會將這些機會留到另一天我們準備好推出它們時再討論。

The engine that powers all these new experiences is the Llama family of foundation models. 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. The 405 billion model has better cost performance relative to the leading closed models. 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. 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.

為所有這些新體驗提供動力的引擎是 Llama 系列基礎模型。本季度，我們發布了Llama 3.1，其中包括第一個前沿級開源模型以及業界領先的新型中小型模型。 4050億的機型相對於領先的封閉機型來說性價比更好。由於它是開放的，因此它立即成為微調和提煉您自己的自訂模型（無論您需要什麼尺寸）的最佳選擇。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. 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. 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.

我常被問到為什麼我這麼看好開源。我隨 Llama 3.1 版本一起寫了一封信，解釋了為什麼我相信開源對於開發人員、Meta 以及更廣泛的世界來說更好。我的觀點是，開源將更加安全，將促進創新，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. 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. But these models are ecosystems. They're not just kind of isolated pieces of software that we can develop by ourselves.

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。為此，我們需要獲得領先的技術基礎設施，並且不受競爭對手允許我們做的事情的限制。但這些模型就是生態系。它們不僅僅是我們可以自己開發的孤立軟體。

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. 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.

因此，如果我們希望圍繞我們的模型開發最強大的工俱生態系統、效率改進、晶片優化和其他集成，那麼我們需要它們被整個行業的開發人員廣泛使用。一旦我們知道我們將能夠接觸到領先的模型，那麼我就有信心我們將能夠建立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. We've saved billions of dollars with Open Compute Project by having supply chain standardized on our infra designs. Open sourcing tools like PyTorch and React has led to real benefits for us from all of the industry's contributions. This approach has consistently worked for us and I expect it will work here, too.

我對此如此樂觀的部分原因是我們在開源方面擁有悠久的成功記錄。透過在我們的基礎設施設計上實現供應鏈標準化，我們透過開放運算專案節省了數十億美元。 PyTorch 和 React 等開源工具為我們從行業的所有貢獻中帶來了真正的好處。這種方法一直對我們有效，我希望它在這裡也能發揮作用。

Another major area of focus is figuring out the right level of infra capacity to support training more and more advanced models. 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. We are planning for the compute clusters and data we'll need for the next several years. The amount of compute needed to train Llama 4 will likely be almost 10x more than what we used to train Llama 3.

另一個重點關注領域是確定適當水準的基礎設施能力來支援訓練越來越多的先進模型。 Llama 3 已經與最先進的型號競爭，我們已經開始開發 Llama 4，我們的目標是明年成為業界最先進的型號。我們正在規劃未來幾年所需的運算群集和數據。訓練 Llama 4 所需的計算量可能比我們訓練 Llama 3 所需的計算量多出近 10 倍。

And future models will continue to grow beyond that. It's hard to predict how this will trend multiple generations out into the future. 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. And as we scale these investments, we're of course going to remain committed to operational efficiency across the company.

未來的模型將繼續超越這一點。很難預測這將如何影響未來幾代人。但在這一點上，考慮到啟動新的基礎設施項目的準備時間很長，我寧願在需要之前冒險建立能力，而不是太晚。隨著我們擴大這些投資規模，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. Last quarter, I discussed how advances in AI have pulled in the timelines for some of our products. 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.

我想討論的最後一個領域是人工智慧如何塑造我們的虛擬世界工作，這仍然是我們的另一個長期重點。上個季度，我討論了人工智慧的進步如何縮短了我們某些產品的開發時間。幾年前，我預測全像 AR 將在智慧 AI 之前成為可能，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. Ray-Ban Meta glasses continue to be a bigger hit sooner than we expected, thanks in part to AI. Demand is still outpacing our ability to build them, but I'm hopeful that we'll be able to meet that demand soon. 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. Quest 3 sales are also outpacing our expectations. 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.

由於我們已經對現實實驗室進行了投資，因此我們已經做好了充分的準備。雷朋 Meta 眼鏡繼續比我們預期更受歡迎，這在一定程度上要歸功於人工智慧。需求仍然超過了我們建造它們的能力，但我希望我們很快就能滿足這項需求。 EssilorLuxottica 在這方面一直是個很好的合作夥伴，我們很高興能與他們合作，在我們繼續建立長期合作夥伴關係的同時，共同打造下一代人工智慧眼鏡。 Quest 3 的銷量也超出了我們的預期。我認為這是因為它不僅是同價位中最好的 MR 耳機，而且是市場上最好的耳機。

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. 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. 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.

除了遊戲之外，人們也越來越多地利用 Quest 作為通用運算平台的功能，花時間觀看影片、瀏覽網站、透過虛擬桌面擴展 PC 等。 Horizo​​n 在 VR、行動和桌面領域也持續成長，我預計它也將成為該生態系統中越來越重要的一部分。我們將於 9 月 25 日舉辦年度 Connect 會議，我們將圍繞我們所有的 AI 和元宇宙工作發布許多令人興奮的更新，所以我鼓勵您關注這一點。

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. 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. The progress we're making on both the foundational technology and product experiences suggests that we're on the right track. I'm proud of what our team has accomplished so far, and I'm optimistic about our ability to execute on the opportunities ahead. 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.

歸根結底，我們處於幸運的位置，我們在核心產品和業務中看到的強勁成果使我們有機會為未來進行深度投資。我計劃充分抓住這個機會，打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。我們在基礎技術和產品體驗方面取得的進展表明我們正走在正確的軌道上。我對我們團隊迄今為止所取得的成就感到自豪，並且對我們抓住未來機會的能力感到樂觀。一如既往，感謝我們的團隊推動所有這些重要工作的進展，並感謝你們所有人與我們一起踏上這段旅程。

And now here's Susan.

現在是蘇珊。

Thanks, Mark, and good afternoon, everyone. Let's begin with our consolidated results. All comparisons are on a year-over-year basis, unless otherwise noted. Q2 total revenue was $39.1 billion, up 22% or 23% on a constant currency basis. Q2 total expenses were $24.2 billion, up 7% compared to last year.

謝謝，馬克，大家下午好。讓我們從我們的綜合結果開始。除非另有說明，所有比較均按年比較。第二季總營收為 391 億美元，以固定匯率計算成長 22% 或 23%。第二季總支出為 242 億美元，比去年成長 7%。

In terms of the specific line items, cost of revenue increased 23%, driven primarily by higher infrastructure and Reality Labs inventory costs. R&D increased 13%, primarily driven by higher headcount-related expenses and infrastructure costs, which were partially offset by lower restructuring costs. Marketing and sales decreased 14% due mainly to lower restructuring and headcount-related costs. G&A decreased 12% mostly due to lower legal-related expenses.

就具體項目而言，收入成本增加了 23%，這主要是由於基礎設施和 Reality Labs 庫存成本上升。研發成長 13%，主要是因為人員相關費用和基礎設施成本增加，但部分被重組成本下降所抵銷。行銷和銷售額下降 14%，主要是由於重組和人員相關成本下降。一般行政費用下降 12%，主要是因為法律相關費用減少。

We ended the first quarter with almost 70,800 employees, up 2% from Q1. Second-quarter operating income was $14.8 billion, representing a 38% operating margin. Our tax rate for the quarter was 11%. Net income was $13.5 billion or $5.16 per share.

第一季末，我們擁有近 70,800 名員工，比第一季成長 2%。第二季營業收入為 148 億美元，營業利益率為 38%。我們本季的稅率為 11%。淨利潤為 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. Free cash flow was $10.9 billion. 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.

受伺服器、資料中心和網路基礎設施投資的推動，資本支出（包括融資租賃本金支付）為 85 億美元。自由現金流為 109 億美元。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，本季末我們擁有 581 億美元的現金和有價證券以及 184 億美元的債務。

Moving now to our segment results. I'll begin with our family of apps segment. 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. Q2 total family of apps revenue was $38.7 billion, up 22% year-over-year. Q2 family of apps ads revenue was $38.3 billion, up 22% or 23% on a constant currency basis.

現在轉向我們的細分結果。我將從我們的應用程式系列部分開始。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應用程式系列之一。第二季應用系列總營收為 387 億美元，年增 22%。第二季應用程式系列廣告收入為 383 億美元，以固定匯率計算成長 22% 或 23%。

Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by gaming and entertainment and media. On a user geography basis, ad revenue growth was strongest in rest of world and Europe at 33% and 26%, respectively. Asia Pacific grew 20% and North America grew 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.

在廣告收入中，線上商務垂直領域是年成長的最大貢獻者，其次是遊戲、娛樂和媒體。從用戶地理來看，全球其他地區和歐洲的廣告收入成長最為強勁，分別為 33% 和 26%。亞太地區成長 20%，北美成長 17%。從廣告商地理來看，亞太地區的總營收成長仍然最為強勁，達到 28%，但由於我們經歷了中國廣告商需求強勁的時期，成長率低於第一季的 41%。

In Q2, the total number of ad impressions served across our services and the average price per ad both increased 10%. Impression growth was mainly driven by Asia Pacific and rest of world. Pricing growth was driven by increased advertiser demand, in part due to improved ad performance. This was partially offset by impression growth, particularly from lower monetizing regions and services. Family of apps other revenue was $389 million, up 73%, driven primarily by business messaging revenue growth from our WhatsApp business platform. We continue to direct the majority of our investments toward the development and operation of our family of apps.

第二季度，我們服務中的廣告展示總數和每個廣告的平均價格均增加了 10%。印象數成長主要由亞太地區和世界其他地區推動。廣告客戶需求增加推動了定價成長，部分原因是廣告效果改善。這部分被展示次數成長所抵消，尤其是來自貨幣化程度較低的地區和服務的展示次數成長。應用程式系列其他收入為 3.89 億美元，成長 73%，這主要是由 WhatsApp 業務平台的業務訊息收入成長所推動的。我們繼續將大部分投資用於我們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. Family of apps expenses were up 4%, mostly due to higher infrastructure and headcount-related expenses, which were partially offset by lower restructuring costs. Family of apps operating income was $19.3 billion, representing a 50% operating margin.

第二季度，應用程式系列支出為 194 億美元，約占我們整體支出的 80%。應用程式系列支出增加了 4%，主要是由於基礎設施和人員相關支出增加，但重組成本下降部分抵消了這筆支出。應用系列的營業收入為 193 億美元，營業利益率為 50%。

Within our Reality Labs segment, Q2 was $353 million, up 28%, driven primarily by Quest headset sales. 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 operating loss was $4.5 billion.

在我們的 Reality Labs 部門中，第二季銷售額為 3.53 億美元，成長 28%，這主要是由 Quest 耳機銷售推動的。 Reality Labs 支出為 48 億美元，較去年同期成長 21%，主要是由於人員相關支出和 Reality Labs 庫存成本增加。 Reality Labs 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. To deliver engaging experiences, we remain focused on executing our priorities, including video and in-feed recommendations. On Instagram, Reels engagement continues to grow as we make ongoing enhancements to our recommendation systems. 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. Now, more than half of recommendations in the US come from original posts.

現在轉向業務前景，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。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。在 Instagram 上，隨著我們不斷改進推薦系統，Reels 的參與度持續成長。這項工作的一部分重點是增加推薦中原創貼文的份額，以便人們可以發現 Instagram 的最佳內容，包括來自新興創作者的內容。現在，美國一半以上的推薦來自原創貼文。

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

在 Facebook 上，我們看到 6 月在全球推出統一視訊播放器和排名系統帶來的令人鼓舞的早期結果。這項舉措使我們能夠將Facebook 上的所有影片類型整合為一種觀看體驗，隨著我們越來越多地將較短的影片融入Facebook 影片參與的整體基礎中，我們預計這將為短影片帶來額外的成長機會。

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. These have already shown promising gains since we began using the new systems to support Facebook Reels recommendations last year. 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，隨著我們受益於 Facebook 上統一視訊排名和整合下一代推薦系統，影片推薦的相關性將繼續提高。自從我們去年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。我們預計在今年和明年擴展這些新系統，以支援 Facebook 影片之外的更多介面。

We're also seeing good momentum with our longer-term engagement priorities, including generative AI and Threads. People have used Meta AI for billions of queries since we first introduced it. 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. You can now use Meta AI in over 20 countries and 8 languages. 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.

我們也看到了長期參與優先事項的良好勢頭，包括生成式人工智慧和線程。自從我們首次推出 Meta AI 以來，人們已經使用它進行了數十億次查詢。我們在 WhatsApp 的保留率和參與度方面看到了特別有希望的跡象，恰逢印度成為我們最大的 Meta AI 使用市場。現在您可以在 20 多個國家/地區和 8 種語言中使用 Meta AI。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. There are two parts to this work. The first is optimizing the level of ads within organic engagement. 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.

現在我們的收入表現的第二個驅動因素是提高貨幣化效率。這項工作有兩個部分。首先是優化有機參與中的廣告層面。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，整體視頻參與度將更多地轉向較短的視頻，從而創造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. This is enabling us to drive revenue growth and conversions without increasing the number of ads or, in some cases, even reducing ad load.

更廣泛地說，我們正在繼續更好地確定在 Facebook 和 Instagram 上的個人會話中展示的最佳廣告以及何時展示它們。這使我們能夠在不增加廣告數量、甚至在某些情況下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. We continue to be pleased with our progress here, with AI playing an increasingly central role. 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.

提高變現效率的第二部分是提升行銷績效。我們仍然對我們在這方面取得的進展感到滿意，人工智慧發揮著越來越重要的作用。我們正在透過採用人工智慧進步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. 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.

我們也透過我們的 Advantage+ 解決方案套件，讓廣告主更輕鬆地最大限度地提高廣告成效並自動化更多的廣告活動設定。我們看到這些工具繼續帶來效果提升，今年進行的一項研究表明，美國廣告商在採用 Advantage+ 購物活動後，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. 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. 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.

廣告商對這些工具的採用不斷擴大，我們正在添加新功能以使它們更加有用。例如，本季度，我們在 Advantage+ 購物中引入了靈活的格式，允許廣告商在單一廣告中上傳多個圖像和視頻，我們可以從中選擇並自動確定要提供的格式，以產生最佳效果。我們現在還擴展了企業可以使用 Advantage+ 購物進行優化的轉換列表，包括額外的 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. We expect this technology will continue to make it easier for businesses to develop customized and diverse ad creatives. 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. 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.

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。我們預計這項技術將繼續讓企業更輕鬆地開發客製化且多樣化的廣告創意。自從推出第一個生成式AI 廣告功能、圖像擴展、背景生成和文字生成以來，我們已經看到了有希望的早期成果，在過去的一個月裡，超過100 萬廣告商至少使用了其中一種解決方案。五月份，我們開始將完整的圖像生成功能引入 Advantage+ 廣告素材中，我們已經看到使用該工具的廣告商的效能有所提高。

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

最後，我們預期人工智慧將幫助企業透過訊息傳遞更有效地與客戶溝通。我們首先測試企業在與客戶的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。雖然我們還處於早期階段，但我們仍在繼續擴大正在測試的廣告客戶數量，並且自從我們開始使用 Llama 3 以來，我們已經看到了回應品質的顯著進步。

Next, I would like to discuss our approach to capital allocation, which remains unchanged. 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. We expect that having sufficient compute capacity will be central to many of these opportunities. 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.

接下來，我想討論我們的資本配置方式，這方式沒有改變。我們繼續投資於增強近期的核心體驗和開發技術，我們相信這些技術將在未來幾年改變人們使用我們服務的方式。我們預計，擁有足夠的運算能力將是許多機會的核心。因此，我們正在對基礎設施進行有意義的投資，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. 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.

隨著我們提高平台上推薦內容和廣告的相關性，我們對核心人工智慧能力的持續投資是基於我們已經看到並期望在未來實現的強勁回報。雖然我們預計生成式人工智慧的回報將在更長的時間內實現，但我們正在將這些投資與我們期望在客製化廣告創意、商業訊息、領先的人工智慧助理和有機內容中釋放的重大貨幣化機會進行映射。

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

隨著我們擴大生成式人工智慧訓練能力以推進我們的基礎模型，我們將繼續以一種為我們提供隨著時間的推移使用它的靈活性的方式來建立我們的基礎設施。當我們期望這樣做會更有價值時，這將使我們能夠將訓練能力直接用於產生人工智慧推理或我們的核心排名和推薦工作。隨著時間的推移，我們也將繼續致力於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. 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. Finally, as we pursue these investments across near and long-term priorities, we will remain focused on operating the business efficiently.

Reality Labs 仍然是我們繼續進行有意義投資的另一個長期計劃。我們對AR 眼鏡的長期潛力充滿信心。最後，當我們在短期和長期優先事項上追求這些投資時，我們將繼續專注於高效能經營業務。

Turning now to the revenue outlook. We expect third-quarter 2024 total revenue to be in the range of $38.5 billion to $41 billion. Our guidance assumes foreign currency is a 2% headwind to year-over-year total revenue growth based on current exchange rates.

現在轉向收入前景。我們預計 2024 年第三季總營收將在 385 億美元至 410 億美元之間。我們的指引假設，根據當前匯率，外幣對總收入年增有 2% 的阻力。

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

現在轉向費用前景。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）範圍內。現在轉向資本支出前景。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，先前的範圍為 350 億美元至 400 億美元。在我們繼續改善明年的計畫的同時，我們目前預計 2025 年資本支出將大幅成長，因為我們將進行投資以支援我們的人工智慧研究和產品開發工作。

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

到稅收。如果我們的稅收模式沒有任何變化，我們預計 2024 年全年稅率將在十幾歲左右。此外，我們繼續監控積極的監管環境，包括歐盟和美國日益增加的法律和監管阻力，這些阻力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. 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.

最後，第二季又是一個不錯的季度。我們繼續出色地執行我們的業務重點，並擁有令人興奮的機會，為世界各地使用我們產品的人們和企業提供更多價值。

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

克里斯塔，讓我們開始提問吧。

(Operator Instructions) Brian Nowak, Morgan Stanley.

（操作員指示）Brian Nowak，摩根士丹利。

I have two: one for Mark, one for Susan. Mark, I wanted to sort of go back to some of the new generative AI-enabled use cases for users and advertisers. You talked about Meta AI, Studio, chatbots, [foundation] models. 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.

我有兩份：一份給馬克，一份給蘇珊。馬克，我想回到一些為用戶和廣告商提供的新的生成人工智慧用例。您談到了 Meta AI、Studio、聊天機器人、[基礎]模型。如果你能專注於一兩個你最興奮的事情，你會看到良好的信號，這可能會成為 25 年、26 年業務的真正驅動力，所以我們可以知道你最關注所有這些機會的哪裡，這會很有幫助。

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

第二個，蘇珊，您有很多資本支出優先事項，包括為下一代模型、運算能力建立新的基礎設施。只需再次向我們介紹資本支出理念以及您擁有的任何護欄，確保您從所有資本支出中為投資者帶來健康的投資資本回報。

I can take the first one. 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. So the ways that it's improving recommendations and helping people find better content as well as making the advertising experiences more effective. I think there's a lot of upside there. Those are already products that are at scale. The AI work that we're doing is going to improve that. It will improve the experience and the business results.

我可以拿第一個。因此，我認為將在 25 和 26 年推動最大成果的事情實際上是我在評論中談到的第一類事情，它們是人工智慧塑造現有產品的方式。因此，它改善推薦、幫助人們找到更好的內容以及使廣告體驗更有效的方式。我認為那裡有很多好處。這些已經是規模化的產品。我們正在做的人工智慧工作將改善這一點。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. 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. 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? I think that that's like what we've seen with Reels. It's what we sell with all these things.

我們正在研究的其他領域，我想你們透過一段時間的關注我們的業務都知道這一點，但是我們有一個相對較長的商業週期來啟動一個新產品，並將其擴展到覆蓋 10 億人的產品或更多，然後才真正專注於大規模貨幣化。事實上，對於 Meta AI 或 AI Studio 這樣的東西，我認為這些東西將增加我們產品的參與度，並具有其他好處，可以在短期內改善業務和參與度。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，我認為任何人都不應該對我預計這將需要幾年的時間感到驚訝，對吧？我認為這就像我們在 Reels 中看到的那樣。這就是我們與所有這些東西一起出售的東西。

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. 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. Last quarter, we -- I think it just started rolling it out a week or two before our earnings call. This time, we're a few months later. 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. And I think that's a pretty big deal.

但我認為，對於那些長期關注我們業務的人來說，您也可以提前幾年很好地了解何時會發揮作用。我認為那些押注於這些早期指標的人往往會做得很好，這就是為什麼我想在我的評論中分享我們在 Meta AI 上的早期指標，我的意思是，看，現在還很早。上個季度，我們—我認為它在我們的財報電話會議前一兩週才開始推出。這一次，我們已經是幾個月後的事了。我們可以說的是，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。我認為這是一件大事。

Is that the only thing we want to do? No. 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. 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. 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. It will improve the existing ones and will make a whole lot of new ones possible. 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. It's because it's actually super exciting, and it's going to change all these different things over multiple time horizons.

這是我們唯一想做的事嗎？不，我的意思是，我們顯然希望擴大這一點，並加深對此的參與，然後我們將專注於隨著時間的推移將其貨幣化。但早期的訊號是好的，我認為這就是我們目前可以合理洞察的全部內容。但我確實認為人工智慧最根本的部分是它最終將以某種方式影響我們擁有的幾乎所有產品。它將改進現有的技術，並使許多新的技術成為可能。這就是為什麼有很多關於科技公司執行長如何在這些財報電話會議上一直談論人工智慧的笑話。這是因為它實際上非常令人興奮，並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. On the ROI part of your question, I would broadly characterize our AI investments into two buckets: core AI and gen AI. And the two are really at different stages as it relates to driving revenue for our businesses and our ability to measure returns.

布萊恩，我可以回答第二個問題。關於你問題的投資報酬率部分，我將我們的人工智慧投資大致分為兩個部分：核心人工智慧和一代人工智慧。兩者確實處於不同的階段，因為這關係到我們業務的收入成長和衡量回報的能力。

On our core AI work, we continue to take a very ROI-based approach to our investment here. 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. Gen AI is where we're much earlier, as Mark just mentioned in his comments. We don't expect our gen AI products to be a meaningful driver of revenue in '24. 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.

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的投資方法。我們仍然看到了強勁的回報，因為參與度和廣告效果的改善已轉化為收入成長，我們繼續在這裡投資是有意義的。正如馬克剛剛在評論中提到的那樣，Gen AI 是我們更早的領域。我們預計我們的新一代人工智慧產品不會成為 24 年收入的有意義的驅動力。但我們確實預計，隨著時間的推移，他們將開闢新的收入機會，這將使我們能夠從投資中獲得豐厚的回報，同時我們也將開源 Llama 的後代。

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在這裡重點關注的四個主要領域，即人工智慧增強核心廣告業務的機會、幫助我們在業務消息方面發展的機會、圍繞元人工智慧的機會以及提高核心參與度的機會時間。

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. The infrastructure that we build for gen AI training can also be used for gen AI inference. We can also use it for ranking and recommendations by making certain modifications like adding general compute and storage. 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. 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.

我要說的另一件事是，我們將繼續建立我們的人工智慧基礎設施，同時考慮到可替代性，以便我們可以在我們認為能夠得到最佳利用的地方靈活調整容量。我們為生成人工智慧訓練所建構的基礎設施也可以用於產生人工智慧推理。我們還可以透過進行某些修改（例如添加通用計算和儲存）來將其用於排名和推薦。我們還採用了在不同開發階段部署資料中心站點的策略，這使我們能夠靈活地滿足更多需求並縮短交付時間（如果需要），同時限制我們在未來幾年承諾的支出。因此，雖然我們確實預計 2025 年資本支出將大幅增長，但我們認為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它，以充分利用它。

Mark Shmulik, Bernstein.

馬克·什穆里克，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? 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.

就像我們關注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？您也強調了一些您看到優勢的領域，以及您為提高廣告產品功效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. And we expect that all of that will continue to benefit ad spend in Q3. 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. And we also expect modestly larger FX headwinds in Q3 based on current rates.

我們繼續看到健康的全球廣告需求，我們也提供持續的廣告成效改進，這與我們長期以來在改進廣告類型、定位排名、投放等方面持續進行的所有投資相關。我們預計所有這些將繼續有利於第三季的廣告支出。我們確實預計第三季的年成長將放緩，因為我們正在經歷來自中國廣告商的強勁成長以及一年前強勁的 Reels 印象成長。根據目前的匯率，我們也預期第三季的外匯阻力將適度加大。

Eric Sheridan, Goldman Sachs.

艾瑞克‧謝裡丹，高盛。

I'll just ask one. You called out building community size and what's happened in the United States as well as Threads. 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?

我就問一個吧您提到了社區規模建設、美國以及 Threads 所發生的事情。您如何看待訊息傳遞或 Threads 作為平台的那些更新更快的元素，以及訊息傳遞層或 Threads 的參與度成長潛力和長期整體貨幣化之間的組合，以及您最興奮的是什麼建立某種程度的規模資本，但將其帶回貨幣化？

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

我可以開始了，如果蘇珊還有什麼要補充的，她也可以加入。因此，我認為 WhatsApp 的統計數據作為一種商業趨勢非常重要，因為美國在我們收入中所佔的比例非常大。

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.

所以以前，WhatsApp 在世界上許多國家都是領先的訊息應用程序，但在美國卻不是。這是一次非常好的體驗，跨平台交流和團體以及所有這些不同事物的最佳體驗，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，隨著時間的推移，那裡的機會將會有很大的推動力。

So that's one reason why it's really relevant. 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. 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. I think it was the fastest-growing app to 100 million people. 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. And that's our product cycle.

這就是它真正相關的原因之一。看到我們周圍的所有人開始使用 WhatsApp，顯然我個人也感到有些欣慰，所以我認為這很有趣，但從商業角度來看可能不太相關。線程，我認為這是我能想到的任何應用程式的一個很好的開始的另一個例子。我認為它是擁有 1 億用戶成長最快的應用程式。這是一個很好的提醒，即使你有了這樣的開始，從那裡到 10 億人使用應用程式仍然需要多年的時間。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. 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.

我認為 Meta 建立消費產品及其周圍業務的方式與許多其他交付產品並立即開始銷售並立即從中獲利的公司有所不同。因此，我認為我們的投資者和人們在考慮分析業務時，如果需要的話，要始終解決所有這些新產品，我們交付它們，然後在擴展它們並將它們擴展到不僅僅是消費者之間存在多年的時間跨度經驗豐富，但業務規模大。

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

但我認為 Threads 最令人興奮的一點是，我們已經創建這家公司 20 年了，但沒有那麼多機會來發展 10 億人的應用程式。我的意思是，我不知道，世界上可能有十幾個這樣的人，對嗎？我的意思是，公司外部的人肯定比公司內部的人多，但我們做得很好，如果我們執行得很好，能夠在投資組合中添加另一個人，擁有這種潛力真的很令人興奮。

Now obviously, there's a ton of work between now and there. I mean, we're almost at 200 million. So it's a really good milestone, I'm excited about that. A lot of work between this and it being a large part of the business. But I do think that these kind of opportunities are pretty rare and that's something that we're just really excited about. I think the team is doing great work on it.

顯然，從現在到那時還有大量的工作要做。我的意思是，我們已經快有 2 億了。所以這是一個非常好的里程碑，我對此感到興奮。這與它成為業務的很大一部分之間有很多工作。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。我認為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. 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. And generally, we expect continued community growth across our apps.

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。在 Instagram 上，我們預計 Reels 將繼續推動成長，而在 Facebook 上，我們預計會增加整體影片時長，同時增加短影片的組合，從而創造更多印象增長機會。一般來說，我們預計我們的應用程式社群將持續成長。

Doug Anmuth, JPMorgan.

道格·安姆斯，摩根大通。

One for Mark, one for Susan. 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. Just given how much you're building ahead, how does that influence the shape of the CapEx curve over a multiyear period?

一份給馬克，一份給蘇珊。馬克，就基礎設施和資本支出而言，您談到目前不僅為Llama 3 和4 構建，而且實際上可能構建到7 個，然後是Llama 4，所需計算量是Llama 3 的10 倍。出您的數量即可。

And then Susan, if you could talk a little bit more about the 3Q outlook. 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. So just curious if there's anything else you can point to more specifically that's driving the expected strength here.

然後蘇珊，您能多談談第三季的前景嗎？我知道您正在談論更嚴格的比較，但與此同時，它確實表明高端僅存在一點外匯中性減速。因此，我想知道是否有其他更具體的內容可以推動這裡的預期強度。

Thanks, Doug. I can go ahead and talk about both of those. So your first question was sort of about the longer-term CapEx outlook. We haven't really shared an outlook sort of on the longer-term CapEx trajectory. In part, infrastructure is an extraordinarily dynamic planning area for us right now. We're continuing to work through what the scope of the gen AI road maps will look like over that time.

謝謝，道格。我可以繼續討論這兩個問題。所以你的第一個問題是關於長期資本支出前景的。我們還沒有真正分享長期資本支出軌跡的展望。在某種程度上，基礎設施目前對我們來說是一個非常動態的規劃領域。我們正在繼續研究屆時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. 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. And then we feel good about the opportunities in the gen AI efforts.

顯然，我們的期望是明年我們將大幅增加對人工智慧基礎設施的投資，並且我們將酌情提供進一步的指導。但我們正在建立所有的資本支出，再次考慮到我之前談到的因素，思考如何靈活地建立它，以便我們可以根據需要部署到核心人工智慧和一代人工智慧用例，並確保我們都覺得我們對核心人工智慧投資的回報感到滿意，我們可以更立即地衡量這些回報。然後我們對新一代人工智慧工作中的機會感到滿意。

Your second question was about the Q3 revenue outlook. Again, I mentioned this earlier, we have seen healthy global advertising demand on our platform. 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. 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.

你的第二個問題是關於第三季的營收前景。我之前再次提到過，我們在我們的平台上看到了健康的全球廣告需求。我們正在提供持續的廣告效果改進，我們再次認為這是許多很多季度努力的結果，這些努力已經並將繼續為我們的平台帶來價值。我們基本上在第二季度看到收入成長了 22%，跨地區和垂直行業都有廣泛的優勢，包括小型廣告商的特殊優勢，我們預計這種情況通常會持續到第三季。

Justin Post, Bank of America.

賈斯汀·波斯特，美國銀行。

I just want to get back to the comment on US young adult user growth, especially maybe on Facebook and Instagram. I know you made a big change with Reels a couple of years ago. But what are those users doing on Facebook and Instagram? And can you give us any quantification of the usage growth?

我只想回到對美國年輕成人用戶成長的評論，尤其是在 Facebook 和 Instagram 上。我知道幾年前您對 Reels 做出了重大改變。但這些用戶在 Facebook 和 Instagram 上做什麼呢？您能給我們使用量成長的量化數據嗎？

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

謝謝，賈斯汀。因此，開發年輕人的產品一直是 Facebook 團隊近年來的核心優先領域，看到這些努力轉化為這群人的參與度成長，我們感到非常鼓舞。過去幾個季度，我們看到美國和加拿大的年輕人應用程式使用量健康成長。

And we've seen that products like Groups and Marketplace have seen particular traction with young adults. Posting to groups in the US and Canada has been growing. That's been boosted mainly by young adults. 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.

我們已經看到，像群組和市場這樣的產品對年輕人特別有吸引力。在美國和加拿大的群組中發文的人數一直在增加。這主要是由年輕人推動的。我們也看到他們是 Marketplace 的活躍用戶，這得益於美國的產品改進和對二手產品的強勁需求。

Mark Mahaney, Evercore ISI.

馬克·馬哈尼，Evercore ISI。

I was going to ask about Marketplace so that's a nice segue. It's a great, somewhat under-monetized or arguably very under-monetized asset. I know you indirectly monetize it and it's a very large marketplace. It may even be bigger than eBay. 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.

我本來想問市場，所以這是一個很好的延續。這是一項偉大的、貨幣化程度有些不足或可以說貨幣化程度非常不足的資產。我知道你間接地將其貨幣化，這是一個非常大的市場。它甚至可能比 eBay 還要大。您對未來可能想做的事情的想法在貨幣化方面甚至可能會提高市場的品質。

And then secondly, I just want to ask you about headcount. It's down about 1% year over year. You're pretty much back at par with where the employee headcount was prior to significant reduction. How should we think about headcount growth going forward? Did you talk about a significant growth in CapEx? Should we expect a moderate growth in headcount significant? Any thoughts on that would be helpful.

其次，我只想問你關於員工人數的問題。年減約1%。員工人數幾乎回到了大幅裁員之前的水平。我們該如何看待未來的員工成長？您是否談到了資本支出的顯著成長？我們是否應該預期員工人數會顯著適度成長？對此的任何想法都會有所幫助。

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

謝謝，馬克。關於你關於 Marketplace 的第一個問題，我們顯然很高興它成為年輕人力量的驅動力之一。我可能只是想說，更廣泛地說，Marketplace 是我們更廣泛的商業策略的一個組成部分，該策略繼續致力於在我們的平台上創造最佳的購物體驗。

Marketplace is obviously consumer-oriented. 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. And to that end, I would say that we feel quite happy with also the investments we've been making in Shops ads. Shops ads revenue is growing at a strong year-over-year pace. 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.

市場顯然是以消費者為導向的。商務策略更廣泛的部分是讓企業更容易宣傳他們的產品，讓買家在我們的平台上找到並購買相關商品。為此，我想說，我們對商店廣告的投資也感到非常滿意。商店廣告收入較去年同期強勁成長。我們看到商店廣告為廣告主帶來了增量效果，而且它與我們的一些其他產品（例如 Advantage+ 購物）結合起來效果也很好。

Your second question was about headcount. 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.

你的第二個問題是關於員工人數的。我們繼續嚴格限制新員工的分配，以確保其真正專注於我們公司的核心優先事項，但我們也在解決先前的招聘不足問題。

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

隨著我們在今年進一步解決招聘不足的問題，我確實預計到 2024 年年底，我們報告的在職員工人數將明顯高於 2023 年年底的人數。開始預算流程。但我再次希望我們的招募主要集中在優先領域，並且我們將運行非常嚴格的員工統計流程。

Youssef Squali, Truist Securities.

優素福‧斯誇裡 (Youssef Squali)，Truist 證券公司。

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. So are there any plans to open it up to the broader web? Kind of like what may be OpenAI is off to testing, maybe link it to third-party marketplaces for commercial search, et cetera.

因此，使用 Llama 3.1 的人工智慧系統已經融入了不同的變體，看起來確實令人印象深刻，並且似乎越來越接近成為迄今為止除了商業查詢之外幾乎所有內容的完整搜尋引擎。那麼有計劃將其開放給更廣泛的網路嗎？有點像 OpenAI 即將開始測試，可能會將其連結到第三方市場進行商業搜索，等等。

And then on Ray-Ban, can you maybe talk a little bit more about the opportunity to deepen your relationship with EssilorLuxottica? What would that look like? What kind of areas are the most exciting to you, Mark, in that relationship?

關於雷朋 (Ray-Ban)，您能否多談談加深與 EssilorLuxottica 關係的機會？那會是什麼樣子呢？馬克，在這段關係中，哪些領域最讓你興奮？

Yes. I'm very excited with how Llama 3.1 landed. 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. 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.

是的。我對 Llama 3.1 的發布感到非常興奮。我認為，從Llama 的第一個版本、去年的Llama 2（落後前沿一代一代）到現在的Llama 3.1（基本上具有競爭力，並且在某些方面領先於其他頂級封閉版本），團隊做了非常出色的工作。 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.

當我之前談到我們圍繞Meta AI 有了初步的使用趨勢時，但我們還想添加更多內容，例如商業，你可以逐個垂直地進行，並建立特定的功能，使其在所有這些方面都有用。 我認為，為了發揮成為人們理想的人工智慧助理的潛力，我們最終需要在不同的領域開展工作。

So it's a long road map. I don't think that this stuff is going to get finished in the next couple of quarters or anything like that. 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. So I'm quite excited about that. And we're going to continue working on Llama, too. 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. 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.

所以這是一個漫長的路線圖。我認為這些事情不會在接下來的幾季或類似的事情中完成。但這是未來幾年將發生的事情的一部分，因為我們建造的東西將成為一種非常廣泛使用的服務。所以我對此感到非常興奮。我們也將繼續致力於 Llama。所以我的意思是，你提到了 Llama，我認為這個問題更多的是關於 Meta AI，但它們都是——我的意思是，它們是相關的。 Llama 有點像是為產品提供動力的引擎，而且它是開源的，我對我們在這兩個方面取得的進展感到興奮。

On the smart glasses, EssilorLuxottica is a great partner. We are now in the second generation of the Ray-Ban Meta glasses. 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. 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. So that was great.

在智慧眼鏡方面，EssilorLuxottica是個很好的合作夥伴。我們現在使用的是第二代 Ray-Ban Meta 眼鏡。他們做得很好，比我想像的要好，我們預計他們會從第一代開始有意義地成長，所以這是一個非常積極的驚喜。我認為部分原因是它正好與我們所看到的人工智慧革命很好地契合，並在那裡提供各種新功能。所以那太好了。

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

但 EssilorLuxottica 是一家很棒的公司，擁有許多不同的產品，我們希望能夠與之合作，繼續打造新一代眼鏡，深化人工智慧產品，使其變得越來越好。我認為接下來還有很多事情要做。與我們目前的想法相比，我認為，與真正領先的消費性電子產品相比，它的表現相當不錯，我認為我們還處於早期階段，但所有跡像都很好。

Ron Josey, Citi.

羅恩喬西，花旗銀行。

I want to get back, Mark, to the commentary on open source and Llama 3. 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. And meaning potentially offering some of these products to other companies, call it, for customer service or call center offerings or other verticals. 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?

Mark，我想回到關於開源和 Llama 3 的評論。向其他公司提供其中一些產品，稱為客戶服務或呼叫中心產品或其他垂直行業。那麼，您對開源和 Llama 3.1 可以如何為其他人提供更好的企業服務並從中受益有什麼見解嗎？

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

所以 Llama 是人們可以塑造成各種不同產品的基礎模型。因此，無論是我們自己的 Meta AI、AI Studio、業務代理還是雷朋眼鏡中的助手，所有這些不同的東西基本上都是用 Llama 構建的產品。

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. 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.

同樣，任何開發人員都將能夠利用它並建立更加多樣化的不同事物。正如我所說，我認為開源對我們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為我們正在建立的消費者和業務體驗提供動力。

But the infrastructure, it's not just a piece of software that we can build in isolation. 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. It's an ecosystem. So we can't do all that ourselves.

但基礎設施不僅僅是我們可以單獨建構的軟體。它確實是一個具有許多不同功能的生態系統，其他開發人員和人們正在將其添加到組合中，無論是將模型提煉為自訂模型所需的大小的新工具，還是更好地調整事物的方法或使推理更加高效，或者我們還沒有想到的所有其他類型的方法，矽公司正在做的矽優化，所有的東西。這是一個生態系統。所以我們不能自己做這一切。

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. So that's the business strategy around that. 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.

如果我們建造了 Llama 並且只是將其保留在我們的圍牆內，那麼對我們來說，建造我們正在建造的所有產品實際上不會像它最終會那樣有價值。這就是圍繞此的商業策略。這就是為什麼我們認為我們不需要建立雲端並直接出售它才能使其成為我們真正積極的業務策略。

And part of what we're doing is working closely with AWS, I think, especially did great work for this release. Other companies like Databricks, NVIDIA, of course, other big players like Microsoft with Azure, and Google Cloud, they're all supporting this. And we want developers to be able to get it anywhere. 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. So I'm quite excited about that.

我認為，我們正在做的部分工作是與 AWS 密切合作，特別是為此版本做了出色的工作。其他公司，例如 Databricks、NVIDIA，當然還有其他大公司，例如 Microsoft 的 Azure 和 Google Cloud，他們都支援這一點。我們希望開發人員能夠在任何地方獲得它。我認為這是像 Llama 這樣的開源模型的優點之一 - 它不像你被鎖定在一個提供該模型的雲中，無論是 Microsoft 的 OpenAI 還是 Google 的 Gemini 或其他什麼，你都可以接受這個並在任何地方使用它，我們希望鼓勵這樣做。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. I just think that there's a huge potential like I said earlier. I think pretty much every business today has an e-mail address, they have a website, they have social media accounts. 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.

不過，我們最關注的企業和業務應用程序，除了像我之前在評論中談到的那樣優化廣告商體驗之外，它是業務代理部分。我只是認為就像我之前所說的那樣，有巨大的潛力。我認為今天幾乎每個企業都有一個電子郵件地址，他們有一個網站，他們有社交媒體帳戶。我認為將來，他們將擁有至少一個（如果不是多個的話）業務代理，他們可以做各種各樣的事情，從互動幫助人們購買東西到幫助支持他們所做的銷售（如果他們有）產品出現問題，如果他們需要與您聯繫以解決某些問題。

And we already see people interacting with businesses over messaging working quite well in countries that have low cost of labor. But the thing is that in order to have someone answering everyone's questions is quite expensive in a lot of countries. And I think that this is like a thing that AI, I think, is just going to be very well suited towards doing.

我們已經看到，在勞動成本較低的國家，人們透過訊息傳遞與企業互動的效果非常好。但問題是，在許多國家，要有人回答每個人的問題是相當昂貴的。我認為這就像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. 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. And I think that's going to be huge, but that's just one area. This really goes across all of the different products that we're building, both consumer and business. So it's a lot of exciting stuff.

當我們能夠讓數以億計的企業使用我們的平台輕鬆獲取他們所有的資訊、目錄、歷史記錄以及他們共享的所有內容，並且真正快速地建立一個代理時，我想那會很棒的。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結合起來，並將其與生態系統其他部分正在做的所有其他投資相結合，以使 Llama 變得更好。我認為這將是巨大的，但這只是一個領域。這確實涉及我們正在建立的所有不同產品，包括消費者產品和企業產品。所以這是很多令人興奮的事情。

Krista, we have time for one last question.

克里斯塔，我們有時間回答最後一個問題。

Ross Sandler, Barclays.

羅斯·桑德勒，巴克萊銀行。

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. 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?

馬克，週一在詹森的採訪中，您說了一些類似的話，如果有一天規模最終停止，那麼您將需要完成五年的產品工作。那麼，除了智慧型或人工智慧助理之外，您在五年路線圖中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. You guys said that Llama 3.1 was trained on 16,000 H100s. You've also said that you're going to have 600,000 available by year-end. 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. How are you guys modeling out this entire kind of CapEx road map between training, inference, and future things? That's all.

第二個問題可能是對容量問題的另一個嘗試。你們說 Llama 3.1 在 16,000 個 H100 上進行了訓練。您也說過，到年底您將擁有 60 萬個可用資源。因此，即使我們為 Llama 4 增加了 160,000 個 GPU，我們也有足夠的額外容量用於推理和未來的產品。你們如何在訓練、推理和未來之間建立整個資本支出路線圖？就這樣。

I can start with the first one, and then I'll let Susan answer the second one. It's an interesting question. 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. I think there would just be a huge amount of product innovation that the industry would bring to bear, and that just takes time. 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. So I'm not really planning our product roadmap assuming that there isn't future innovation.

我可以從第一個開始，然後讓蘇珊回答第二個。這是一個有趣的問題。這有點假設，因為我的意思是，我確實認為如果未來沒有基礎模型的話，這是真的。我認為該行業將會帶來大量的產品創新，而這需要時間。但同時，未來將會出現基礎模型，它們將會非常棒並釋放新功能，我們正在圍繞這些模型規劃我們的產品。因此，我並不是假設未來沒有創新的情況下真正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，我們正在計劃 Llama 4 和 Llama 5 及更高版本中的內容，基於我們認為對於我剛剛制定的路線圖最重要的功能，以實現您所期望的實用廣度需要像Meta AI 這樣的東西，讓企業、創作者和個人可以支援他們想要的任何類型的人工智慧代理，這樣你就可以一直擁有這種即時、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. 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. 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. 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.

我想這與我期望蘇珊接下來要談論的內容相吻合。我們確實已經擁有大量的用例，涉及人們想要發現內容並與他們的朋友和企業互動的人，所有這些東西也因此變得更好。我想我的觀點是，技術的可用和產品在該領域的充分探索之間存在一些滯後。我只是認為這就是我表達的方式，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有很多創新。

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

我會讓 Susan 來看看 GPU 等方面的數字。

Thank you. 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. And that's driving sort of what we've talked about in terms of the significant growth in CapEx in 2025. And we aren't really in the position now to share a longer-term outlook.

謝謝。顯然，我們正在建立大量能力，馬克在他關於我們需要什麼來培訓前幾代和下一代駱駝的評論中提到了這一點。這在某種程度上推動了我們所討論的 2025 年資本支出的顯著增長。

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. 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. 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.

當我們考慮正在建造的任何給定的新資料中心專案時，我們都會考慮如何在資料中心的整個生命週期中使用它。無論下一代 Llama 是什麼，我們都會考慮在訓練方面使用的容量，並圍繞此進行構建。但隨後我們也會考慮如何在其生命週期的幾年內將其用於我們核心業務的其他用例，以及我們認為未來可能對推理和基於人工智慧的產品的推理需求。

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

因此，任何單一資料中心的生命週期都有大量的用例，從一開始的人工智慧訓練到潛在支援人工智慧推理，再到用於核心廣告和內容排名和推薦，並思考其影響，此外，我們還可以使用哪些類型的伺服器來支援這些不同類型的用例。因此，當我們進行任何給定專案時，我們實際上是在繪製廣泛的潛在用例。

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

我們這樣做時確實考慮到了很長的時間範圍，因為啟動資料中心的準備時間很長，但我們也認識到，在思考方面，每個資料中心的生命週期中有多個決策點何時訂購伺服器、訂購哪些伺服器以及您將它們用於什麼目的。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. Thank you all for joining us today. We appreciate your time, and we look forward to speaking with you again soon.

偉大的。感謝大家今天加入我們。感謝您抽出寶貴的時間，我們期待很快再次與您交談。

This concludes today's conference call. Thank you for your participation, and you may now disconnect.

今天的電話會議到此結束。感謝您的參與，您現在可以斷開連接。