Meta Platforms Inc (META) 2024 Q1 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 First Quarter Earnings Conference Call. (Operator Instructions) This call will be recorded. Thank you very much.

午安.我叫克里斯塔，今天我將擔任您的會議主持人。現在，我歡迎大家參加 Meta 第一季財報電話會議。 （操作員指示）此通話將會被錄音。非常感謝。

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

您可以請 Meta 投資者關係總監 Ken Dorell 開始。

Thank you. Good afternoon, and welcome to Meta Platform's First Quarter 2021 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 2021 年第一季財報電話會議。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. 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 annual report on Form 10-K filed with the SEC.

在我們開始之前，我想藉此機會提醒您，我們今天的演講將包括前瞻性陳述。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。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-K 表年度報告中列出。

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. 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.

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 指標的對帳表。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. Thanks, Ken, and everyone, thanks for joining. It's been a good start to the year, both in terms of product momentum and business performance. We estimate that more than 3.2 billion people use at least one of our apps each day, and we're seeing healthy growth in the U.S. And I want to call out WhatsApp specifically, where the number of daily actives and message sends in the U.S. keeps gaining momentum, and I think we're on a good path there. We've also made good progress on our AI and metaverse efforts, and that's where I'm going to focus most of my comments today.

好的。謝謝 Ken，也謝謝大家的加入。無論從產品動能或業務表現來看，今年都是一個好的開始。我們估計每天有超過 32 億人使用我們的至少一款應用，而且我們看到美國的應用程式成長勢頭良好。強勁，我認為我們正走在正確的道路上。我們在人工智慧和元宇宙方面的努力也取得了良好的進展，這也是我今天主要要討論的議題。

So let's start with AI. We're building a number of different AI services, from Meta AI, our AI assistant that you can ask any question across our apps and glasses, to creator AIs that help creators engage their communities and that fans can interact with, to business AIs that we think every business eventually on our platform will use to help customers buy things and get customer support to internal coding and development AIs to hardware like glasses for people to interact with AIs and a lot more.

那我們就從人工智慧開始吧。我們正在建立多種不同的人工智慧服務，從Meta AI（我們的人工智慧助手，你可以透過我們的應用程式和眼鏡詢問任何問題）到創作者人工智慧（幫助創作者參與社群並與粉絲互動）再到商業人工智慧（我們認為，我們平台上的每項業務最終都將用於幫助客戶購買商品、獲得客戶支援、內部編碼和開發人工智慧、以及用於人們與人工智慧互動的眼鏡等硬體等等。

Last week, we had the major release of our new version of Meta AI that is now powered by our latest model, Llama 3. And our goal with Meta AI is to build the world's leading AI service, both in quality and usage.

上週，我們發布了新版 Meta AI 的主要版本，現在由我們的最新模型 Llama 3 提供支援。

The initial rollout of Meta AI is going well. Tens of millions of people have already tried it. The feedback is very positive. And when I first checked in with our teams, the majority of feedback we were getting was people asking us to release Meta AI for them wherever they are. So we've started launching Meta AI in some English speaking countries, and we'll roll out in more languages and countries over the coming months.

Meta AI 的初步推出進展順利。數千萬人已經嘗試過。反饋非常正面。當我第一次與我們的團隊溝通時，我們收到的大部分回饋是人們要求我們為他們在任何地方發布 Meta AI。因此，我們已經開始在一些英語國家推出 Meta AI，並將在未來幾個月內推廣到更多語言和國家。

You all know our product development playbook by this point. We release an early version of a product to a limited audience to gather feedback and start improving it, and then once we think it's ready, then we make it available to more people. That early release was last fall and with this release, we are now moving to that next growth phase of our playbook. We believe that Meta AI with Llama 3 is now the most intelligent AI assistant that you can freely use. And now that we have the superior quality product, we are making it easier for lots of people to use it within WhatsApp, Messenger, Instagram and Facebook.

到目前為止，大家都已經了解了我們的產品開發劇本。我們向有限的受眾發布產品的早期版本，以收集反饋並開始改進它，然後一旦我們認為它準備就緒，我們就會將其提供給更多人。這個早期版本是在去年秋季發布的，隨著這次版本的發布，我們現在正進入劇本的下一個發展階段。我們相信，具有 Llama 3 的 Meta AI 是您目前可以自由使用的最聰明的 AI 助理。現在我們有了優質的產品，可以讓許多人更輕鬆地在 WhatsApp、Messenger、Instagram 和 Facebook 中使用它。

Now in addition to answering more complex queries, a few other notable and unique features from this release. Meta AI now creates animations from still images and now generates high-quality images so fast that it can create and update them as you are typing, which is pretty awesome. I've seen a lot of people commenting about that experience online and how they've never seen or experienced anything like it before.

現在，除了回答更複雜的查詢之外，此版本還具有其他一些值得注意的獨特功能。 Meta AI 現在可以根據靜止圖像創建動畫，並且可以非常快速地生成高品質圖像，以至於它可以在您打字時創建和更新它們，這非常棒。我看到很多人在網路上評論那次經歷，說他們從未見過或經歷過這樣的事情。

In terms of the core AI model and intelligence that's powering Meta AI, I'm very pleased with how Llama 3 has come together so far. The 8 billion and 70 billion parameter models that we released are best-in-class for their scale. The 400-plus billion parameter model that we're still training seems on track to be industry leading on several benchmarks. And I expect that our models are just going to improve further from open source contributions.

就驅動 Meta AI 的核心 AI 模型和智慧而言，我對 Llama 3 目前的進展感到非常滿意。我們發布的80億和700億參數模型在規模上是同類最佳的。我們仍在訓練的超過 4000 億個參數模型似乎有望在多個基準測試中領先業界。我希望我們的模型能夠透過開源貢獻得到進一步的改進。

Overall, I view the results our teams have achieved here as another key milestone in showing that we have the talent, data and ability to scale infrastructure to build the world's leading AI models and services. And this leads me to believe that we should invest significantly more over the coming years to build even more advanced models and the largest scale AI services in the world. As we're scaling CapEx and energy expenses for AI, we'll continue focusing on operating the rest of our company efficiently. But realistically, even with shifting many of our existing resources to focus on AI, we'll still grow our investment envelope meaningfully before we make much revenue from some of these new products.

總的來說，我認為我們的團隊在這裡取得的成果是另一個重要的里程碑，表明我們擁有人才、數據和擴展基礎設施的能力，以建立世界領先的人工智慧模型和服務。這讓我相信，我們應該在未來幾年投入更多資金來建立更先進的模式和世界上最大規模的人工智慧服務。隨著我們擴大人工智慧的資本支出和能源支出，我們將繼續專注於高效能營運公司的其他部分。但實際上，即使我們將許多現有資源轉移到人工智慧上，在我們從這些新產品中獲得大量收入之前，我們的投資額度仍將大幅增加。

I think it's worth calling that out that we've historically seen a lot of volatility in our stock during this phase of our product playbook, where we're investing in scaling a new product but aren't yet monetizing it. We saw this with Reels, Stories as newsfeed transition to mobile and more. And I also expect to see a multiyear investment cycle before we fully scale Meta AI, business AIs and more into the profitable services I expect as well. Historically, investing to build these new scaled experiences in our apps has been a very good long-term investment for us and for investors who have stuck with us. And the initial signs are quite positive here, too. But building the leading AI will also be a larger undertaking than the other experiences we've added to our apps, and this is likely going to take several years.

我認為值得一提的是，在我們的產品劇本的這個階段，我們的股票歷史上出現過很大的波動，我們正在投資擴大新產品的規模，但尚未將其貨幣化。我們在 Reels 和 Stories 等新聞源向行動裝置轉變的過程中看到了這一點。我還預計，在我們將 Meta AI、商業 AI 等全面擴展到我預期的盈利服務之前，將有一個多年的投資週期。從歷史上看，在我們的應用程式中投資建立這些新的規模體驗對於我們以及一直支持我們的投資者來說是一項非常好的長期投資。而且初步跡像也相當正面。但打造領先的人工智慧也將比我們添加到應用程式的其他體驗更為艱鉅，這可能需要幾年的時間。

On the upside, once our new AI services reach scale, we have a strong track record of monetizing them effectively. There are several ways to build a massive business here, including scaling business messaging, introducing ads or paid content into AI interactions and enabling people to pay to use bigger AI models and access more compute. And on top of those, AI is already helping us improve app engagement, which naturally leads to seeing more ads and improving ads directly to deliver more value. So if the technology and products evolve in the way that we hope, each of those will unlock massive amounts of value for people and business for us over time.

從好的方面來看，一旦我們的新 AI 服務達到規模，我們就會有有效地將其貨幣化的良好記錄。有幾種方法可以在這裡建立大規模業務，包括擴展業務訊息傳遞、在 AI 互動中引入廣告或付費內容以及讓人們付費使用更大的 AI 模型和訪問更多的計算。除此之外，人工智慧已經在幫助我們提高應用程式參與度，這自然會導致看到更多廣告，並直接改進廣告以提供更多價值。因此，如果科技和產品按照我們希望的方式發展，那麼隨著時間的推移，它們都會為我們的人們和企業釋放出巨大的價值。

We're seeing good progress on some of these efforts already. Right now, about 30% of the posts on Facebook feed are delivered by our AI recommendation system. That's up 2x over the last couple of years. And for the first time ever, more than 50% of the content that people see on Instagram is now AI recommended. AI has also been a huge part of how we create value for advertisers by showing people more relevant ads. And if you look at our 2 end-to-end AI-powered tools, Advantage+ shopping and Advantage+ app campaigns, revenue flowing through those has more than doubled since last year.

我們已經看到其中一些努力取得了良好進展。目前，Facebook 動態中大約 30% 的貼文是由我們的 AI 推薦系統提供的。較過去幾年，這一數字成長了 2 倍。而且，有史以來第一次，人們在 Instagram 上看到的超過 50% 的內容都是由 AI 推薦的。人工智慧在我們透過向人們展示更相關的廣告為廣告商創造價值的過程中也發揮了重要作用。如果你看看我們的兩個端到端人工智慧工具，Advantage+購物和Advantage+應用程式活動，你會發現自去年以來，透過這些工具產生的收入已經成長了一倍多。

We're also going to continue to be very focused on efficiency as we scale Meta AI and other AI services. Some of this will come from improving how we train and run models. Some improvements will come from the open source community, and we're improving cost efficiency is one of the main areas that I expect that open sourcing will help us improve similar to what we saw with Open Compute. We'll also keep making progress on building more of our own silicon. Our Meta training and inference accelerator chip has successfully enabled us to run some of our recommendations-related workloads on this less expensive stack. And as this program matures over the coming years, we plan to expand this to more of our workloads as well. And of course, as we ramp these investments, we will also continue to carefully manage headcount and other expense growth throughout the company.

在擴展 Meta AI 和其他 AI 服務時，我們也將繼續高度重視效率。其中一部分將來自於改進我們訓練和運行模型的方式。一些改進將來自開源社區，我們正在提高成本效率，這是我預計開源將幫助我們改進的主要領域之一，類似於我們在開放運算方面看到的情況。我們也將繼續在建造更多我們自己的矽片方面取得進展。我們的元訓練和推理加速器晶片成功地使我們能夠在這個較便宜的堆疊上運行一些與建議相關的工作負載。隨著該計劃在未來幾年逐漸成熟，我們計劃將其擴展到更多的工作量。當然，隨著我們增加這些投資，我們也將繼續謹慎管理整個公司的員工數量和其他費用的成長。

Now in addition to our work on AI, our other long-term focus is the metaverse. It's been interesting to see how these 2 themes have come together.

現在，除了我們在人工智慧方面的工作之外，我們另一個長期的關注點是元宇宙。看到這兩個主題如何結合在一起真是有趣。

This is clearest when you look at glasses. I used to think that AR glasses wouldn't really be a mainstream product until we had full holographic displays -- and I still think that, that's going to be awesome and is the long-term mature state for the product. But now it seems pretty clear that there's also a meaningful market for fashionable AI glasses without a display. Glasses are the ideal device for an AI assistant because you can let them see what you see and hear what you hear. So they have full context on what's going on around you as they help you with whatever you're trying to do. Our launch this week of Meta AI with Vision on the glasses is a good example where you can now ask questions about things that you're looking at.

當你看著眼鏡時這一點最為明顯。我過去認為，在我們擁有全像顯示器之前，AR 眼鏡不會真正成為主流產品——而我仍然認為，那將是一件很棒的事情，並且是該產品的長期成熟狀態。但現在似乎很明顯，沒有顯示器的時尚人工智慧眼鏡也有一個有意義的市場。眼鏡是人工智慧助理的理想設備，因為你可以讓它們看到你所看到的內容，並聽到你所聽到的內容。因此，他們可以全面了解周圍發生的情況並幫助您完成您想做的事情。我們本週推出的帶有視覺功能的 Meta AI 眼鏡就是一個很好的例子，你現在可以針對所看到的東西提出問題。

Now one strategy dynamic that I've been reflecting on is that an increasing amount of our Reality Labs work is going towards serving our AI efforts. We currently report on our financials as if Family of Apps and Reality Labs were 2 completely separate businesses, but strategically, I think of them as fundamentally the same business with the vision of Reality Labs to build the next generation of computing platforms in large part so that we can build the best apps and experiences on top of them. Over time, we'll need to find better ways to articulate the value that's generated here across both segments so it doesn't just seem like our hardware costs increase as our glasses ecosystem scales, but all the value flows to a different segment.

現在我一直在思考的一個策略動態是，我們現實實驗室的越來越多的工作將用於服務我們的人工智慧工作。目前，我們在財務報告中將Family of Apps 和Reality Labs 視為兩個完全獨立的業務，但從策略上講，我認為它們本質上是同一項業務，而Reality Labs 的願景是建立下一代運算平台，因此我們可以在它們的基礎上打造最好的應用程式和體驗。隨著時間的推移，我們需要找到更好的方法來表達這兩個領域所產生的價值，這樣，我們的眼鏡生態系統規模擴大後，我們的硬體成本就不會僅僅增加，而且所有的價值都會流向不同的領域。

The Ray-Ban Meta glasses that we built with Essilor Luxottica continue to do well and are sold out in many styles and colors. So we're working to make more and release additional styles as quickly as we can. We just released the new cat-eye Skyler design yesterday, which is more feminine. And in general, I'm optimistic about our approach of starting with the classics and expanding with an increasing diversity of options over time. If we want everyone to be able to use wearable AI, I think eyewear is a bit different from phones or watches in that people are going to want very different designs. So I think our approach of partnering with the leading eyewear brands will help us serve more of the market.

我們與 Essilor Luxottica 合作打造的 Ray-Ban Meta 眼鏡持續暢銷，多種款式和顏色都已售罄。因此，我們正在努力製作更多產品並儘快發布更多款式。我們昨天剛發布了新的貓眼Skyler設計，更有女人味。總的來說，我對我們的做法感到樂觀，即從經典開始，隨著時間的推移，選擇越來越多樣化。如果我們希望每個人都能使用穿戴式人工智慧，我認為眼鏡與手機或手錶略有不同，因為人們會想要非常不同的設計。因此我認為與領先眼鏡品牌合作的方式將幫助我們服務更多的市場。

I think a similar open ecosystem approach will help us expand the virtual and mixed reality headset market over time as well. We announced that we're opening up Meta Horizon OS, the operating system we've built to power Quest. As the ecosystem grows, I think there will be sufficient diversity in how people use mixed reality, that there will be demand for more designs than we'll be able to build. For example, a work-focused headset may be slightly less designed for motion but may -- you want to be lighter by connecting to your laptop; a fitness-focused headset may be lighter with sweat-wicking materials; an entertainment-focused headset may prioritize the highest resolution displays over everything else; a gaming-focused headset may prioritize peripherals and haptics or a device that comes with Xbox controllers and a game pass subscription out of the box.

我認為類似的開放生態系統方法也將幫助我們隨著時間的推移擴大虛擬和混合實境耳機市場。我們宣布開放為 Quest 提供支援而建置的作業系統 Meta Horizo​​n OS。隨著生態系統的發展，我認為人們使用混合實境的方式將會變得足夠多樣化，對設計的需求將會比我們所能建構的更多。例如，一款以工作為中心的耳機可能在運動方面的設計稍差一些，但可能——你希望透過連接到筆記型電腦來減輕重量；專注於健身的耳機可能會更輕，並採用吸汗材質；以娛樂為中心的耳機可能會優先考慮最高解析度的顯示器；以遊戲為中心的耳機可能會優先考慮週邊設備和觸覺，或配備 Xbox 控制器和開箱即用的遊戲通行證訂閱的設備。

Now to be clear, I think that our first-party Quest devices will continue to be the most popular headsets as we see today, and we'll continue focusing on advancing the state-of-the-art tech and making it accessible to everyone. But I also think that opening our ecosystem and opening our operating system will help the overall mixed reality ecosystem grow even faster.

現在需要明確的是，我認為我們的第一方 Quest 設備將繼續成為目前最受歡迎的耳機，我們將繼續專注於推進最先進的技術並讓每個人都能使用它。但我也認為，開放我們的生態系統和開放我們的作業系統將有助於整個混合實境生態系統更快發展。

Now in addition to AI and the metaverse, we're seeing good improvements across our apps. I touched on some of the most important trends already with WhatsApp growth in the U.S. and AI-powered recommendations in our feeds and reels already. But I do want to mention that video continues to be a bright spot. This month, we launched an updated full-screen video player on Facebook that brings together reels, longer videos and live content into a single experience with a unified recommendation system. On Instagram, reels and video continue to drive engagement, with reels alone now making up 50% of the time that's spent within the app.

現在，除了人工智慧和元宇宙之外，我們還看到了我們應用程式的良好改進。我已經談到了一些最重要的趨勢，例如 WhatsApp 在美國的發展以及我們在 feed 和 reels 中提供的 AI 推薦。但我確實想說一下，影片仍然是一個亮點。本月，我們在 Facebook 上推出了更新的全螢幕視訊播放器，它透過統一的推薦系統將捲軸、長視訊和直播內容整合到單一體驗中。在 Instagram 上，Reels 和影片繼續推動人們的參與度，光是 Reels 就佔據了應用程式內使用時間的 50%。

Threads is growing well, too. There are now more than 150 million monthly actives, and it continues to generally be on the trajectory that I hoped to see. And of course, my daughters would want me to mention that Taylor Swift is now on Threads, that one was a big deal in my house.

線程也成長得很好。現在每個月的活躍用戶已經超過 1.5 億，並且總體上繼續按照我希望看到的軌跡發展。當然，我的女兒們希望我提到泰勒絲現在在 Threads 上，這在我們家是一件大事。

All right. That is what I wanted to cover today. I am proud of the progress we've made so far this year. We've got a lot more execution ahead to fulfill the opportunities ahead of us. A big thank you to all of our teams who are driving all these advances and to all of you for being on this journey with us. And now here is Susan.

好的。這就是我今天想要講的內容。我對我們今年迄今所取得的進步感到自豪。我們還需要做更多的努力來抓住眼前的機會。非常感謝推動這些進步的所有團隊，也感謝與我們一起踏上這段旅程的所有人。現在蘇珊就在這裡。

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. Q1 total revenue was $36.5 billion, up 27% on both a reported and constant currency basis. Q1 total expenses were $22.6 billion, up 6% compared to last year.

謝謝，馬克，大家下午好。讓我們從綜合結果開始。除非另有說明，所有比較均以同比為基礎。第一季總營收為 365 億美元，按報告和固定匯率計算均成長 27%。第一季總支出為 226 億美元，比去年同期成長 6%。

In terms of the specific line items, cost of revenue increased 9% as higher infrastructure-related costs were partially offset by lapping Reality Labs' inventory-related valuation adjustments. R&D increased 6%, driven mostly by higher headcount-related expenses and infrastructure costs, which were partially offset by lower restructuring costs.

就具體項目而言，收入成本增加了 9%，因為與基礎設施相關的成本增加被 Reality Labs 的庫存相關估值調整部分抵消。研發費用增加了 6%，主要原因是與員工人數相關的費用和基礎設施成本增加，但重組成本的降低部分抵消了這些費用的增加。

Marketing and sales decreased 16% due mainly to lower restructuring costs, professional services and marketing spend. G&A increased 20% as higher legal-related expenses were partially offset by lower restructuring costs.

行銷和銷售額下降 16%，主要原因是重組成本、專業服務和行銷支出減少。由於法律相關費用的增加被重組成本的降低部分抵消，一般及行政費用增加了 20%。

We ended the first quarter with over 69,300 employees, up 3% from Q4. First quarter operating income was $13.8 billion, representing a 38% operating margin. Our tax rate for the quarter was 13%. Net income was $12.4 billion or $4.71 per share.

截至第一季度，我們擁有超過 69,300 名員工，比第四季成長 3%。第一季營業收入為 138 億美元，營業利益率為 38%。我們本季的稅率為 13%。淨收入為 124 億美元，即每股 4.71 美元。

Capital expenditures, including principal payments on finance leases, were $6.7 billion, driven by investments in servers, data centers and network infrastructure. Free cash flow was $12.5 billion. We repurchased $14.6 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.

資本支出（包括融資租賃的本金支付）為 67 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。自由現金流為125億美元。我們回購了 146 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. I'll begin with our Family of Apps segment. Our community across the Family of Apps continues to grow, with approximately 3.2 billion people using at least one of our Family of Apps on a daily basis in March. Q1 total Family of Apps revenue was $36 billion, up 27% year-over-year. Q1 Family of Apps ad revenue was $35.6 billion, up 27% or 26% on a constant currency basis. Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by gaming and entertainment and media.

現在來看看我們的分部業績。我將從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，3 月每天約有 32 億人至少使用我們的一款應用程式。第一季應用程式系列總營收為 360 億美元，年增 27%。 Q1 家庭應用程式廣告收入為 356 億美元，成長 27%，以固定匯率計算成長 26%。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 40% and 33%, respectively. Asia Pacific grew 25% and North America grew 22%. In Q1, the total number of ad impressions served across our services increased 20%, and the average price per ad increased 6%. Impression growth was mainly driven by Asia Pacific and Rest of World. Pricing growth was driven by advertiser demand, which was partially offset by strong impression growth, particularly from lower-monetizing regions and services.

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 40% 和 33%。亞太地區成長了 25%，北美成長了 22%。第一季度，我們各項服務的廣告展示總數增加了 20%，每個廣告的平均價格上漲了 6%。展示量成長主要受到亞太地區和世界其他地區的推動。價格成長是由廣告商的需求推動的，但強勁的展示次數成長（尤其是來自貨幣化較低的地區和服務）部分抵消了這一成長。

Family of Apps other revenue was $380 million in Q1, up 85%, driven 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. In Q1, Family of Apps expenses were $18.4 billion, representing approximately 81% of our overall expenses. Family of Apps expenses were up 7% due mainly to higher legal and infrastructure costs that were partially offset by lower restructuring costs.

第一季度，應用程式系列的其他收入為 3.8 億美元，成長 85%，這得益於我們的 WhatsApp 商業平台的商業訊息收入成長。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。第一季度，應用程式系列的支出為 184 億美元，約占我們整體支出的 81%。應用程式系列的支出上漲了 7%，主要原因是法律和基礎設施成本增加，但重組成本降低部分抵消了這一影響。

Family of Apps operating income was $17.7 billion, representing a 49% operating margin. Within our Reality Labs segment, Q1 revenue was $440 million, up 30%, driven by Quest headset sales. Reality Labs expenses were $4.3 billion, down 1% year-over-year as higher head count-related expenses were more than offset by lapping inventory-related valuation adjustments and restructuring costs. Reality Labs operating loss was $3.8 billion.

應用程式系列營運收入為 177 億美元，營運利潤率為 49%。在我們的現實實驗室部門中，第一季營收為 4.4 億美元，成長 30%，這得益於 Quest 頭戴式耳機的銷售。 Reality Labs 的支出為 43 億美元，較上年同期下降 1%，因為與員工人數相關的支出增加被與庫存相關的估值調整和重組成本所抵消。 Reality Labs 的營運虧損為 38 億美元。

Turning now to the business outlook. There are 2 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. On the first, we remain pleased with engagement trends and have strong momentum across our product priorities. Our investments in developing increasingly advanced recommendation systems continue to drive incremental engagement on our platform, demonstrating that people are finding added value by discovering content from accounts they are not connected to. The level of recommended content in our apps has scaled as we've improved these systems, and we see further opportunity to increase the relevance and personalization of recommendations as we advance our models.

現在來談談商業前景。推動我們的收入表現的兩個主要因素是：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。首先，我們對參與度趨勢感到滿意，我們的產品重點保持強勁勢頭。我們在開發日益先進的推薦系統方面的投資繼續推動我們平台的增量參與，表明人們透過發現與他們無關的帳戶中的內容找到了附加價值。隨著我們不斷改進這些系統，我們應用程式中推薦內容的等級也不斷提高，隨著我們模型的改進，我們看到了進一步提高推薦的相關性和個人化的機會。

Video also continues to grow across our platform, and it now represents more than 60% of time on both Facebook and Instagram. Reels remains the primary driver of that growth, and we're progressing on our work to bring together Reel's longer-form video and live video into one experience on Facebook.

影片在我們的平台上也持續成長，現在佔據了 Facebook 和 Instagram 上 60% 以上的時間。 Reels 仍然是這一成長的主要驅動力，我們正在努力將 Reel 的長篇影片和直播影片整合到 Facebook 上的相同體驗中。

In April, we rolled out this unified video experience in the U.S. and Canada, which is increasingly powered by our next-generation ranking architecture that we expect will help deliver more relevant video recommendations over time.

今年4 月，我們在美國和加拿大推出了這種統一的視訊體驗，該體驗越來越多地受到我們下一代排名架構的支持，我們預計這將有助於隨著時間的推移提供更相關的影片推薦。

We're also introducing deeper integrations of generative AI into our apps in the U.S. and more than a dozen other countries. Along with using Meta AI within our chat surfaces, people will now be able to use Meta AI in search within our apps as well as feed and groups on Facebook. We expect these integrations will complement our social discovery strategy as our recommendation systems help people to discover and explore their interests, while Meta AI enables them to dive deeper on topics they're interested in. Threads also continues to see good traction as we continue to ship valuable features and scale the community.

我們還將在美國和其他十幾個國家的應用程式中引入生成式人工智慧的更深入整合。除了在我們的聊天介面中使用 Meta AI 之外，人們現在還可以使用 Meta AI 在我們的應用程式內進行搜尋以及在 Facebook 上的資訊流和群組中搜尋。我們預計這些整合將補充我們的社交發現策略，因為我們的推薦系統可以幫助人們發現和探索他們的興趣，而 Meta AI 使他們能夠更深入地了解他們感興趣的主題。的功能並擴大社區。

Now to the second driver of our revenue performance, increasing monetization efficiency. There are 2 parts to this work. The first is optimizing the level of ads within organic engagement. Here, we continue to advance our understanding of users' preferences for viewing ads to more effectively optimize the right time, place and person to show an ad to.

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。這項工作分為兩部分。首先是優化有機參與度內的廣告水平。在這裡，我們不斷加深對使用者觀看廣告偏好的理解，以便更有效地優化展示廣告的正確時間、地點和物件。

For example, we are getting better at adjusting the placement and number of ads in real time based on our perception of a user's interest and ad content and to minimize disruption from ads as well as innovating on new and creative ad formats. We expect to continue that work going forward, while surfaces with relatively lower levels of monetization, like video and messaging, will serve as additional growth opportunities.

例如，我們越來越善於根據對用戶興趣和廣告內容的理解，即時調整廣告的位置和數量，以最大限度地減少廣告的干擾，並在新的和有創意的廣告格式上進行創新。我們預計將繼續進行這項工作，而視訊和訊息傳遞等貨幣化程度相對較低的平台將成為額外的成長機會。

The second part of improving monetization efficiency is enhancing marketing performance. Similar to our work with organic recommendations, AI is playing an increasing role in these efforts. First, we are making ongoing ads modeling improvements that are delivering better performance for advertisers. One example is our new ads ranking architecture, Meta Lattice, which we began rolling out more broadly last year. This new architecture allows us to run significantly larger models that generalize learnings across objectives and surfaces in place of numerous smaller ad models that have historically been optimized for individual objectives and surfaces. This is not only leading to increased efficiency as we operate fewer models but also improving ad performance.

提升貨幣化效率的第二部分是提升行銷績效。與我們的有機推薦工作類似，人工智慧在這些工作中發揮著越來越重要的作用。首先，我們正在不斷改進廣告模型，以便為廣告商提供更好的效果。其中一個例子就是我們的新廣告排名架構 Meta Lattice，我們去年開始更廣泛地推出它。這種新架構使我們能夠運行更大的模型，這些模型可以將學習成果推廣到各個目標和介面，從而取代過去針對單一目標和介面進行最佳化的眾多小型廣告模型。這不僅由於我們經營的模型更少而提高了效率，而且還提高了廣告效果。

Another way we're leveraging AI is to provide increased automation for advertisers. Through our Advantage+ portfolio, advertisers can automate one step of the campaign setup process, such as selecting which ad creative to show, or automate their campaign completely using our end-to-end automation tools, Advantage+ shopping and Advantage+ app ads. We're seeing growing use of these solutions, and we expect to drive further adoption over the course of the year while applying what we learned to our broader ads investments.

我們利用人工智慧的另一種方式是為廣告主提供更高的自動化程度。透過我們的 Advantage+ 產品組合，廣告主可以自動執行廣告活動設定流程的一個步驟，例如選擇要顯示的廣告創意，或使用我們的端到端自動化工具 Advantage+ 購物和 Advantage+ 應用程式廣告完全自動化他們的廣告活動。我們看到這些解決方案的使用越來越廣泛，我們希望在今年內推動進一步的採用，同時將我們所學到的知識應用到我們更廣泛的廣告投資中。

Next, I'd like to discuss our approach to capital allocation. We continue to see compelling investment opportunities to both improve our core business in the near term and capture significant longer-term opportunities in generative AI and Reality Labs. As we develop more advanced and compute-intensive recommendation models and scale capacity for our generative AI training and inference needs, we expect that having sufficient infrastructure capacity will be critical to realizing many of these opportunities. As a result, we expect that we will invest significantly more in infrastructure over the coming years.

接下來，我想討論一下我們的資本配置方法。我們繼續看到引人注目的投資機會，既可以在短期內改善我們的核心業務，又可以在生成人工智慧和現實實驗室中抓住重要的長期機會。隨著我們開發出更先進、運算密集的推薦模型，並擴大生成式人工智慧訓練和推理能力，我們預計，擁有足夠的基礎設施容量對於實現其中的許多機會至關重要。因此，我們預計未來幾年我們將在基礎設施方面投入更多資金。

Our other long-term initiatives that we're continuing to make significant investments in is Reality Labs. We are also starting to see our AI initiatives increasingly overlap with our Reality Labs work. For example, with Ray-Ban Meta smart glasses, people in the U.S. and Canada can now use our multimodal Meta AI assistant for daily tasks without pulling out their phone.

我們將繼續進行大量投資的另一個長期計劃是現實實驗室 (Reality Labs)。我們也開始看到我們的人工智慧計畫與現實實驗室的工作越來越重疊。例如，有了雷朋 Meta 智慧眼鏡，美國和加拿大的人們現在可以使用我們的多模式 Meta AI 助理完成日常任務，而無需拿出手機。

Longer term, we expect generative AI to play an increasing role in our mixed reality products, making it easier to develop immersive experiences. Accelerating our AI efforts will help ensure we can provide the best version of our services as we transition to the next computing platform. We expect to pursue these opportunities while maintaining a focus on operating discipline, and we believe our strong financial position will allow us to support these investments while also returning capital to shareholders through share repurchases and dividends.

從長遠來看，我們預計生成式人工智慧將在我們的混合實境產品中發揮越來越重要的作用，從而更輕鬆地開發沉浸式體驗。加快我們的人工智慧努力將有助於確保我們在過渡到下一個運算平台時能夠提供最佳版本的服務。我們希望在關注經營紀律的同時尋求這些機會，我們相信，強大的財務狀況將使我們能夠支持這些投資，同時透過股票回購和股利向股東返還資本。

In addition, we continue to monitor an active regulatory landscape, including the increasing legal and regulatory headwinds in the EU and the U.S. that could significantly impact our business and our financial results. We also have a jury trial scheduled for June in a suit brought by the state of Texas regarding our use of facial recognition technology, which could ultimately result in a material loss.

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。我們還計劃在 6 月就德克薩斯州就我們使用臉部辨識技術提起的訴訟進行陪審團審判，最終可能會導致物質損失。

Turning now to the revenue outlook. We expect second quarter 2024 total revenue to be in the range of $36.5 billion to $39 billion. Our guidance assumes foreign currency is a 1% headwind to year-over-year total revenue growth based on current exchange rates.

現在來談談收入前景。我們預計 2024 年第二季的總營收將在 365 億至 390 億美元之間。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 1% 的阻力。

Turning now to the expense outlook. We expect full year 2024 total expenses to be in the range of $96 million to $99 billion, updated from our prior outlook of $94 million to $99 billion due to higher infrastructure and legal costs.

現在來談談費用前景。我們預計 2024 年全年總支出將在 9,600 萬美元至 990 億美元之間，由於基礎設施和法律成本增加，高於我們先前預測的 9,400 萬美元至 990 億美元。

For Reality Labs, we continue to expect operating losses to increase meaningfully year-over-year due to our ongoing product development efforts and our investments to further scale our ecosystem.

對於 Reality Labs 而言，由於我們正在進行的產品開發工作以及進一步擴大生態系統的投資，我們預計經營虧損將比去年同期大幅增加。

Turning now to the CapEx outlook. We anticipate our full year 2024 capital expenditures will be in the range of $35 billion to $40 billion, increased from our prior range of $30 billion to $37 billion as we continue to accelerate our infrastructure investments to support our AI road map. While we are not providing guidance for years beyond 2024, we expect CapEx will continue to increase next year as we invest aggressively to support our ambitious AI research and product development efforts.

現在來談談資本支出前景。我們預計 2024 年全年資本支出將在 350 億美元至 400 億美元之間，高於先前的 300 億美元至 370 億美元，因為我們將繼續加快基礎設施投資以支持我們的 AI 路線圖。雖然我們沒有提供 2024 年以後的指導，但我們預計明年的資本支出將繼續增加，因為我們積極投資以支持我們雄心勃勃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.

談到稅收。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 closing, Q1 was a good start to the year. We're seeing strong momentum within our Family of Apps and are making important progress on our longer-term AI and Reality Labs initiatives that have the potential to transform the way people interact with our services over the coming years.

總而言之，第一季對於今年來說是一個良好的開始。我們看到我們的應用程式家族呈現出強勁的發展勢頭，並在長期人工智慧和現實實驗室計劃方面取得了重要進展，這些計劃有可能在未來幾年改變人們與我們服務的互動方式。

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) And your first question comes from the line of Eric Sheridan from Goldman Sachs.

(操作員指示)您的第一個問題來自高盛的 Eric Sheridan。

Maybe I'll ask a two-parter. Mark, you used the analogy of other investments cycles you've been through around products like Stories and Reels. I know you're not giving long-term guidance today, but using those analogies, how should investors think about the length and depth of this investment cycle with respect to either AI and/or Reality Labs more broadly and mixed reality?

也許我會問一個雙人問題。馬克，你用其他產品（如 Stories 和 Reels）經歷過的投資週期來做類比。我知道您今天不會提供長期指導，但是使用這些類比，投資者應該如何考慮這個投資週期的長度和深度，包括人工智慧和/或更廣泛的現實實驗室和混合實境？

And you both talked about the impact AI is having on the advertising ecosystem. What are you watching for in terms of adoption or utility on the consumer side to know that AI adoption is tracking along with the investment cycle?

你們都談到了人工智慧對廣告生態系統的影響。就消費者方面的採用或效用而言，您正在關注什麼，以了解人工智慧的採用是否與投資週期同步？

Yes. In terms of the timing, I think it's somewhat difficult to extrapolate from previous cycles. But I guess like the main thing that we see is that we will usually take, I don't know, a couple of years, I mean, it could be a little more, it could be less to focus on building out and scaling the products. And we typically don't focus that much on monetization of the new areas until they reach significant scale because it's so much higher leverage for us just to improve monetization on other things before these new products are at scale.

是的。就時間而言，我認為從先前的周期中推斷出來有些困難。但我想我們看到的主要情況是，我們通常需要幾年的時間，我的意思是，我們可能會多花一點時間，也可能會少花一點時間專注於建造和擴大產品。而且，我們通常不會過度關注新領域的貨幣化，直到它們達到相當大的規模，因為在這些新產品達到規模之前，僅僅提高其他方面的貨幣化對我們來說就有更高的槓桿作用。

So you enter this period where I think kind of smart investors see that the product is scaling and that there's a clear monetizable opportunity there even before the revenue materializes. And I think we've seen that with Reels and with Stories and with the shift to mobile and all these things, where basically, we build out the inventory first for a period of time and then we monetize it.

所以當你進入這個時期時，我認為聰明的投資者會看到產品正在擴大規模，並且在收入實現之前就存在明顯的獲利機會。我認為我們已經透過 Reels 和 Stories 以及向行動裝置的轉變等看到了這一點，基本上，我們首先在一段時間內建立庫存，然後再將其貨幣化。

And during that time, when it's scaling, sometimes it's not just the case that we're not making money from that thing. It can often actually be the case that it displaces other revenue from other things. So like you saw with Reels, I mean, it scaled and there was a period where it was not profitable for us as it was scaling before it became profitable. So I think that's more the analogy that I'm making on this.

而在這段時間裡，當它擴大規模時，有時我們不僅僅是無法從中賺錢。事實上，它常常會取代其他事物的收入。就像你在 Reels 中看到的那樣，我的意思是，它在擴大規模之後，有一段時間它對我們來說是無利可圖的，因為它在實現盈利之前一直在擴大規模。所以我認為這更像是我對此所做的類比。

But I think it's -- what that suggests is that what we should all be focused on for the next period is as the consumer products scale, Meta AI really just launched in a meaningful way so we don't have any kind of hard stats to share on that. But I'd say that's the main thing that I'm focused on for this year and probably a lot of next year is growing that product and the other AI products and the engagement around them. And I think we should all have quite a bit of confidence that if those are on a good track to scale, then they're going to end up being very large businesses. So that's the main point that I was trying to make there.

但我認為這表明，我們接下來應該關注的是，隨著消費品規模的擴大，Meta AI 剛剛以有意義的方式推出，所以我們沒有任何硬性統計數據可以分享。但我想說這是我今年關注的重點，明年的重點可能是發展該產品和其他人工智慧產品以及圍繞它們的參與度。我認為我們都應該有相當大的信心，如果這些企業能夠順利擴大規模，那麼最終它們將會發展成非常大的企業。這就是我在此想要表達的要點。

Your next question comes from the line of Brian Nowak from Morgan Stanley.

您的下一個問題來自摩根士丹利的布萊恩諾瓦克 (Brian Nowak)。

Thanks for taking my questions, I have 2. The first one is on sort of the recommendation engine improvements and even, Susan, when you talked about further opportunities to increase the relevance of the models. Could you just unpack that a little bit for us? Can you give us examples of where you're still running the model in a suboptimal basis or opportunities for improved signal capture use or data you're not using? Where are sort of the areas of improvement you see from here?

感謝您回答我的問題，我有兩個問題。您能為我們稍微解釋一下嗎？您能否舉例說明您仍在以次優方式運行模型，或改善訊號擷取使用或您未使用的資料的機會？您認為這裡可以改進的地方有哪些？

And then the second one, when you talk about driving incremental adoption of AI tools for advertisers, what are sort of some of the main gating factors you've encountered to get advertisers to test these tools? And how do you think about sort of addressing that throughout '24 and '25?

然後第二個問題，當您談到推動廣告商逐步採用人工智慧工具時，您遇到了哪些主要的限制因素，以促使廣告商測試這些工具？您認為在 24 年和 25 年期間該如何解決這個問題？

Thanks, Brian. So to your first question, where are there more opportunities for us to leverage and improve our recommendations models to drive engagement? One of the things I would say is, historically, each of our recommendation products, including Reels, in-feed recommendations, et cetera, has had their own AI model.

謝謝，布萊恩。那麼對於您的第一個問題，我們在哪些方面有更多機會利用和改進我們的推薦模型來推動參與？我想說的一件事是，從歷史上看，我們的每個推薦產品，包括 Reels、資訊流推薦等，都有自己的 AI 模型。

And recently, we've been developing a new model architecture with the aim for it to power multiple recommendations products. We started partially validating this model last year by using it to power Facebook Reels. And we saw meaningful performance gains, 8% to 10% increases in watch time as a result of deploying this.

最近，我們一直在開發一種新的模型架構，旨在為多種推薦產品提供支援。我們去年開始透過使用該模型為 Facebook Reels 提供支援來部分驗證該模型。部署此功能後，我們看到了顯著的效能提升，觀看時間增加了 8% 到 10%。

This year, we're actually planning to extend the singular model architecture to recommend content across not just Facebook Reels, but also Facebook's video tab as well. So while it's still too early to share specific results, we're optimistic that the new model architecture will unlock increasingly relevant video recommendations over time. And if it's successful, we'll explore using it to power other recommendations.

今年，我們實際上計劃擴展單一模型架構，不僅在 Facebook Reels 上推薦內容，還在 Facebook 的影片標籤上推薦內容。因此，雖然現在分享具體結果還為時過早，但我們樂觀地認為，隨著時間的推移，新的模型架構將解鎖越來越相關的影片推薦。如果成功的話，我們會探索利用它來支持其他推薦。

And analog exists, I would say, on the ad side. We've talked a little bit about the new model architecture Meta Lattice that we deployed last year that consolidates smaller and more specialized models into larger models that can better learn what characteristics improve ad performance across multiple services, like feed and Reels and multiple types of ads and objectives at the same time. And that's driven improved ad performance over the course of 2023 as we deployed it across Facebook and Instagram to support multiple objectives.

我想說，廣告上也有類似情況。我們談到了去年部署的新模型架構Meta Lattice，它將更小、更專業的模型整合到更大的模型中，從而更好地了解哪些特徵可以提高多種服務（如feed 和Reels）中的廣告效果，以及多種類型的同時實現廣告和目標。隨著我們在 Facebook 和 Instagram 上部署它以支援多個目標，這推動了 2023 年廣告成效的提升。

And over the course of 2024, we expect to further enhance model performance and include support for even more objectives like web and app and ROAS. So there's a lot of work that we're investing in, in the underlying model architecture for both organic engagement and ads that we expect is going to continue to deliver increasing ads performance over time.

到 2024 年，我們希望進一步提高模型效能，並支援更多目標，例如網路、應用程式和 ROAS。因此，我們在有機參與和廣告的底層模型架構上投入了大量工作，我們期望隨著時間的推移，這些模型架構將繼續提高廣告的效果。

The second question you asked was around getting advertisers to test and adopt gen AI tools. There are 2 flavors of this. The more near-term version is around the gen AI ad creative features that we have put into our ads creation tools. And it's early, but we're seeing adoption of these features across verticals and different advertiser sizes.

您提出的第二個問題是讓廣告主測試和採用新一代人工智慧工具。此種口味有兩種。近期版本是圍繞著我們已放入廣告創作工具中的新一代 AI 廣告創意功能。雖然還處於早期階段，但我們看到不同垂直行業和不同規模的廣告商正在採用這些功能。

In particular, we've seen outsized adoption of image expansion with small businesses, and this will remain a big area of focus for us in 2024, and I expect that improvements to our underlying foundation models will enhance the quality of the outputs that are generated and support new features on the road map. But right now, we have features supporting text variations, image expansion and background generation, and we're continuing to work to make those more performant for advertisers to create more personalized ads at scale.

尤其是，我們看到小型企業大量採用影像擴展，這仍將是我們在 2024 年關注的重點領域，我預計，我們底層基礎模型的改進將提高生成的輸出品質並支援路線圖上的新功能。但現在，我們已經有了支援文字變化、圖像擴展和背景生成的功能，我們正在繼續努力使這些功能更加高效，以便廣告商能夠大規模地創建更個人化的廣告。

The longer-term piece here is around business AIs. We have been testing the ability for businesses to set up AIs for business messaging that represent them in chats with customers, starting by supporting shopping use cases such as responding to people asking for more information on a product or its availability. So this is very, very early. We've been testing this with a handful of businesses on Messenger and WhatsApp, and we're hearing good feedback with businesses saying that the AIs have saved them significant time while customer -- consumers noted more timely response times. And we're also learning a lot from these tests to make these AIs more performant over time as well. So we'll be expanding these tests over the coming months, and we'll continue to take our time here to get it right before we make it more broadly available.

這裡的長期主題是圍繞著商業人工智慧。我們一直在測試企業設定用於商業訊息傳遞的人工智慧的能力，這些人工智慧可以代表他們與客戶聊天，首先是支援購物用例，例如回應人們詢問有關產品或其可用性的更多資訊。所以現在還非常非常早。我們已經在 Messenger 和 WhatsApp 上與少數企業一起測試了此功能，並且我們聽到了良好的反饋，企業表示人工智慧為他們節省了大量時間，而客戶——消費者也注意到回應時間更加及時。我們也從這些測試中學習到了很多東西，以便讓這些人工智慧隨著時間的推移而更有效率。因此，我們將在未來幾個月內擴大這些測試，並且我們將繼續花時間做好測試，然後再將其推廣到更廣泛的地區。

Your next question comes from the line of Mark Shmulik from Bernstein Research.

您的下一個問題來自伯恩斯坦研究公司的馬克‧施穆里克 (Mark Shmulik)。

I guess back to that product playbook that we talked about a few times, with kind of Reels now such a large share of kind of time spent on Instagram and Facebook, how do we think about the next leg of kind of monetization growth from here? In particular, as we kind of get back to kind of shopping on platform or other ways to monetize, any color there on the road map kind of just beyond ad insertion from here?

我想回到我們幾次談論過的產品劇本，現在 Reels 佔據了 Instagram 和 Facebook 上如此大一部分時間，我們如何看待下一步的貨幣化增長？特別是，當我們回到平台購物或其他貨幣化方式時，除了廣告插入之外，路線圖上還有什麼其他亮點嗎？

And then, Susan, just on the ad market, in particular, previously, we heard a lot about kind of Chinese-based advertiser contribution. Any color you could share there on kind of how that spend is trending?

然後，蘇珊，僅就廣告市場而言，特別是之前，我們聽到了很多關於中國廣告商貢獻的信息。能分享一下這方面的支出趨勢嗎？

Sure. Thanks, Mark. So Reels revenue continued to grow across Instagram and Facebook in Q1, and that's driven both by higher engagement and increased monetization efficiency through our ads ranking and delivery improvements. And we -- as we've mentioned before, we don't plan on quantifying the impact from Reels going forward, but it remains a positive contributor to overall revenue. And we expect that there are going to be opportunities for us to continue improving performance and growing supply.

當然。謝謝，馬克。因此，Reels 的營收在第一季在 Instagram 和 Facebook 上繼續成長，這得益於更高的參與度以及透過廣告排名和投放改進而提高的貨幣化效率。而且正如我們之前提到的，我們不打算量化 Reels 未來的影響，但它仍然對整體收入產生積極貢獻。我們預計我們將有機會繼續提高業績並增加供應。

So on the performance improvements, we are investing in ongoing ranking improvements. We're continuing to make ads easier and more intuitive to interact with through work like optimizing call to actions and post-click experiences, which are especially important for DR performance. And we're also optimizing ads to feel more native to Reels.

因此，在效能改進方面，我們正在投資持續的排名改進。我們將繼續透過優化行動號召和點擊後體驗等工作，使廣告更容易、更直觀地進行互動，這對於 DR 表現尤其重要。我們也正在優化廣告，讓其在 Reels 上顯得更原生。

In Q1, we rolled out our gen AI image expansion tools across Facebook and Instagram Reels after having introduced it to Instagram feed in Q4, and we're seeing, again, outsized adoption with small businesses. So we're excited about the opportunities to continue making these ads more performant. And even though ads -- the Reels ad loads, sorry, has increased over the last year, it remains lower on a per time basis than both Feed and Stories. So we're going to continue to look for opportunities to thoughtfully grow it in the future and invest in creative ways to address the structural supply constraints of the Reels format being more video-heavy, including higher density experiences and formats and increasingly personalizing ad loads, which we think will make sure that we're really putting ads in front of people when they're most likely to be interested and engaged with them.

繼第四季度將我們的新一代 AI 圖像擴展工具引入 Instagram 動態消息之後，我們於第一季將其推廣至 Facebook 和 Instagram Reels，並且我們再次看到小型企業的廣泛採用。因此，我們很高興有機會繼續提高這些廣告的效果。儘管 Reels 的廣告載入量在過去一年有所增加，但以每次計算，其廣告載入量仍然低於 Feed 和 Stories。因此，我們將繼續尋找機會在未來進行深思熟慮地發展它，並以創造性的方式進行投資，以解決Reels 格式結構性供應限制，即視頻內容更加豐富，包括更高密度的體驗和格式，以及日益個性化的廣告負載我們認為，這將確保我們在人們最有可能感興趣和參與的時候將廣告展示在他們面前。

The second question you asked was around China. Growth in spend from China advertisers remained strong in Q1. This was driven by online commerce and gaming, and it's reflected in our Asia Pacific advertisers segment, which remained the fastest-growing region, at 41% year-over-year in Q1. Now we did see strength across other geographies as well, including a 6-point acceleration in total revenue growth from North America advertisers.

你問的第二個問題是關於中國的。第一季中國廣告商的支出成長依然強勁。這是由線上商務和遊戲推動的，並反映在我們的亞太廣告商領域，該領域仍然是成長最快的地區，第一季同比增長 41%。現在我們也看到了其他地區的強勁表現，包括來自北美廣告商的總收入成長率加速了 6 個百分點。

So I would say that we aren't quantifying the Q1 contribution from China, and we don't have forward-looking expectations to share on quarterly China-based ad revenue, but I will say that we are lapping periods of increasingly strong demand over the course of 2024 given the recovery of China-based advertisers in 2023 from their prior pandemic-driven headwinds.

因此，我想說的是，我們並沒有量化中國第一季的貢獻，我們也沒有前瞻性地預期季度中國廣告收入，但我要說的是，我們正處於需求日益強勁的時期。商數將在2023 年從先前疫情引發的逆風中復甦，2024 年的走勢將會有所改善。

Your next question comes from the line of Doug Anmuth from JPMorgan.

您的下一個問題來自摩根大通的 Doug Anmuth。

Can you just talk about what's changed most in your view in the business and the opportunity now versus 3 months ago? And is there anything you're more cautious about in revenue in the ad market? And is the AI opportunity just even bigger, and therefore, requiring more investment than expected?

您能否談談與三個月前相比，您認為現在的業務和機會最大的變化是什麼？在廣告市場的收入方面，您是否更謹慎？人工智慧的機會是否更大，因此需要比預期更多的投資？

And then, Susan, can you also just comment on how you're thinking about that ability to sustain growth rates over the next few quarters as you face tougher comps off a big base of ad dollars?

然後，蘇珊，您能否評論一下，在面臨大量廣告費用帶來的更嚴峻競爭情況下，您如何看待未來幾季維持成長率的能力？

Yes, I can speak to the first one. I think we've gotten more optimistic and ambitious on AI. So previously, I think that our work in this -- I mean when you were looking at last year, when we released Llama 2, we were very excited about the model and thought that, that was going to be the basis to be able to build a number of things that were valuable that integrated into our social products. But now I think we're in a pretty different place. So with the latest models, we're not just building good AI models that are going to be capable of building some new good social and commerce products. I actually think we're in a place where we've shown that we can build leading models and be the leading AI company in the world. And that opens up a lot of additional opportunities beyond just ones that are the most obvious ones for us.

是的，我可以談談第一個人。我認為我們對人工智慧的看法變得更加樂觀和雄心勃勃。所以之前，我認為我們在這方面的工作——我的意思是，當你回顧去年，當我們發布 Llama 2 時，我們對這個模型感到非常興奮，並認為，這將是能夠建立一些有價值的東西並將其融入我們的社交產品中。但現在我認為我們處在一個截然不同的情況。因此，利用最新的模型，我們不僅可以建立優秀的 AI 模型，還可以建立一些新的優秀的社交和商業產品。事實上，我認為我們已經證明我們可以建立領先的模型，並成為世界領先的人工智慧公司。這不僅為我們帶來了最明顯的機會，也帶來了許多額外的機會。

So that's -- this is what I was trying to refer to in my opening remarks where I just view the success that we've seen with the way that Llama 3 and Meta AI have come together as a real validation technically that we have the talent, the data and the ability to scale infrastructure to do leading work here.

這就是我在開場白中試圖提到的，我認為 Llama 3 和 Meta AI 的成功結合從技術上證明了我們擁有人才、數據以及擴展基礎設施的能力，以便在此開展主導工作。

And with Meta AI, I think that we are on our path to having Meta AI be the most used and best AI assistant in the world, which I think is going to be enormously valuable. So all of that basically encourages me to make sure that we're investing to stay at the leading edge of this.

有了 Meta AI，我認為我們正在讓 Meta AI 成為世界上使用最廣泛、最好的人工智慧助手，我認為這將具有巨大的價值。所以，所有這些基本上都鼓勵我確保我們進行投資以保持領先地位。

And we're doing that at the time when we're also scaling the product before it is making money. So that's the analogy that I was making before, which is we've gone through some of those cycles before. But fundamentally, I think if you look at the facts of what our team is able to produce, I think it just -- our optimism and ambition have just grown quite a bit, and I think that this is just going to end up being quite an important set of products for us. So it was already going to be. Now I think it has the potential to be even more important.

我們在產品獲利之前擴大產品規模時也這麼做了。這就是我之前所做的類比，即我們之前經歷過一些這樣的週期。但從根本上講，我認為如果你看看我們團隊能夠取得的成果，我認為這只是——我們的樂觀情緒和雄心已經增長了很多，我認為這最終會變得相當對我們來說這是一組重要的產品。事情已經如此了。現在我認為它有可能變得更加重要。

And I can take that second question, Doug. So we aren't giving full year 2024 guidance. And obviously, our revenue for the full year will be influenced by many factors, including macro conditions and things that are harder to predict the further out you go. And of course, over the course of 2024, we will also be lapping periods of increasingly strong demand. With that said, we expect to see good opportunities to continue growing engagement across our products, driven by the investments we made in AI-based content recommendations, our ongoing video work. And we also expect that we will continue to drive ads performance gains and continue to make our ads sort of more effective and deliver increasing value to advertisers.

我可以回答第二個問題，道格。因此我們不會提供 2024 年全年業績指引。顯然，我們的全年收入將受到許多因素的影響，包括宏觀條件以及一些越往後越難預測的因素。當然，在 2024 年，我們也將迎來需求日益強勁的時期。話雖如此，我們預計，在我們對基於人工智慧的內容推薦和正在進行的視訊工作的投資的推動下，我們將看到繼續提高我們產品參與度的良好機會。我們也預計將繼續推動廣告效果的提升，並使我們的廣告變得更加有效，並為廣告商帶來越來越多的價值。

One thing I'd share, for example, is that we actually grew conversions at a faster rate than we grew impressions over the course of this quarter. So we are -- we're expecting to -- which basically suggests that our conversion grade is growing and is one of the ways in which our ads are becoming more performant. So I feel like there's a lot of opportunity for us, both with our organic engagement growth and with continuing to make the ads better and to continue driving more results for advertisers.

例如，我想分享的一件事是，本季我們的轉換量成長速度實際上快於印象量的成長速度。所以我們 - 我們預計 - 這基本上表明我們的轉換率正在提高，並且是我們廣告效果更好的方式之一。因此，我覺得我們有很多機會，既可以實現有機參與度成長，也可以繼續改進廣告並繼續為廣告商帶來更多成果。

Your next question comes from the line of Justin Post from Bank of America.

您的下一個問題來自美國銀行的賈斯汀·波斯特 (Justin Post)。

First on the CapEx, mostly, you're kind of talking about an investment cycle here. Is there any way you could kind of use some of the metaverse spend over into AI? Are they converging and kind of use some of the money from the other areas to kind of fund the AI?

首先關於資本支出，主要是，你在這裡談論的是投資週期。有沒有辦法可以將部分元宇宙支出用於人工智慧？他們是否會聯合起來，使用來自其他領域的部分資金來資助人工智慧？

And then second, longer-term investors are very focused on returns on capital. Obviously, great returns on CapEx in the past with your margins today. How do we think about the returns on the capital you're spending? How are you thinking about it, I guess, going forward 2, 3 years out?

其次，長期投資者非常關注資本回報。顯然，過去的資本支出回報率與今天的利潤率相符。我們如何看待您所花費的資本的回報？我想，您對於未來 2 至 3 年的發展有什麼看法？

So on the -- I would say -- well, I can start with the second part, and then I'll defer to Mark on the first one. In terms of measuring the ROI on our CapEx investments, we've broadly categorized our AI investments into 2 buckets. I think of them as sort of core AI work and then strategic bets, which would include gen AI and the advanced research efforts to support that. And those are just really at different stages as it relates to being able to measure the return and drive revenue for our business. So with our core AI work, we continue to have a very ROI-driven approach to investment, and we're still seeing strong returns as improvements to both engagement and ad performance have translated into revenue gains.

所以 — — 我想說 — — 好吧，我可以從第二部分開始，然後我會將第一部分交給馬克。在衡量我們的資本支出投資報酬率方面，我們大致將人工智慧投資分為兩類。我認為它們是某種核心的人工智慧工作以及策略賭注，其中包括人工智慧和支援人工智慧的先進研究工作。它們實際上處於不同的階段，與衡量回報和推動我們的業務收入有關。因此，透過我們的核心人工智慧工作，我們繼續採取以投資回報率為導向的投資方式，而且我們仍然看到強勁的回報，因為參與度和廣告效果的改善轉化為收入的成長。

Now the second area, strategic bets, is where we are much earlier. Mark has talked about the potential that we believe we have to create significant value for our business in a number of areas, including opportunities to build businesses that don't exist on us today. But we'll need to invest ahead of that opportunity to develop more advanced models and to grow the usage of our products before they drive meaningful revenue.

現在，我們在第二個領域，即戰略投注方面處於更早的階段。馬克談到了我們認為可以在多個領域為我們的業務創造巨大價值的潛力，包括建立目前尚不存在的業務的機會。但我們需要在這一機會到來之前進行投資，開發更先進的模型，並擴大我們產品的使用範圍，然後才能為它們帶來可觀的收入。

So while there is tremendous long-term potential, we're just much earlier on the return curve than with our core AI work. What I'll say though is we're also building our systems in a way that gives us fungibility in how we use our capacity so we can flex it across different use cases as we identify what are the best opportunities to put that infrastructure toward.

因此，雖然存在巨大的長期潛力，但我們的回報曲線比核心人工智慧工作要早得多。不過，我想說的是，我們也在以一種方式建立我們的系統，使我們在使用容量的方式上具有可互換性，這樣我們就可以在不同的用例中靈活運用它，因為我們確定了將該基礎設施投入使用的最佳機會。

And then on the question of shifting resources from other parts of the company. I would say, broadly, we actually are doing that in a lot of places in terms of shifting resources from other areas, whether it's compute resources or different things in order to advance the AI efforts. For Reality Labs specifically, I'm still really optimistic about building these new computing platforms long term. I mentioned in my remarks upfront that one of the bigger areas that we're investing in Reality Labs is glasses. We think that that's going to be a really important platform for the future.

然後是關於從公司其他部門轉移資源的問題。我想說，從廣義上講，我們實際上在很多地方都在這樣做，從其他領域轉移資源，無論是計算資源還是其他東西，以推進人工智慧的發展。具體來說，對於 Reality Labs，我仍然對長期建立這些新的運算平台非常樂觀。我在前面的評論中提到過，我們在 Reality Labs 投資的較大領域之一就是眼鏡。我們認為這將是未來一個非常重要的平台。

Our outlook for that, I think, has improved quite a bit because previously, we thought that, that would need to wait until we have these full holographic displays to be a large market. And now we're a lot more focused on the glasses that we're delivering in partnership with Ray-Ban, which I think are going really well. And -- so that, I think, has the ability to be a pretty meaningful and growing platform sooner than I would have expected. So it is true that more of the Reality Labs work, like I said, is sort of focused on the AI goals as well. But I still think that we should focus on building these long-term platforms, too.

我認為，我們對此的展望已經有了很大的改善，因為之前我們認為這需要等到這些全像顯示器成為一個龐大的市場。現在我們更專注於與雷朋合作推出的眼鏡，我認為進展得非常順利。因此，我認為，它能夠比我預期的更快成為一個相當有意義且不斷發展的平台。所以確實，正如我所說，現實實驗室的更多工作也集中在人工智慧目標上。但我仍然認為我們也應該專注於建造這些長期平台。

Your next question comes from the line of Youssef Squali from Truist Securities.

您的下一個問題來自 Truist Securities 的 Youssef Squali。

Mark, with the upcoming ban or sale of TikTok signed into law earlier today, how do you think that will impact the U.S. social media landscape? And then, in particular, what do you say to people who believe that this is potentially a slippery slope in terms of the government picking up -- picking winners and losers?

馬克，今天早些時候，美國簽署了即將禁止或出售 TikTok 的法律，您認為這將對美國社交媒體格局產生什麼影響？然後，特別是，對於那些認為這可能是一個滑坡，政府將選擇贏家和輸家的人，您想說什麼？

And Susan, how big is Advantage+ in terms of the spend on the platform and just in terms of its impact on overall CPM stabilizing?

蘇珊，從平台支出來看，Advantage+ 有多大？

Thanks, Youssef. We've obviously been following the events related to TikTok closely, but at this stage, it is just too early, I think, to assess its impact or what it would mean for our business.

謝謝，優素福。我們顯然一直在密切關注與 TikTok 相關的事件，但我認為，現階段評估其影響或對我們的業務意味著什麼還為時過早。

To your second question on Advantage+, we're continuing to see good traction across our Advantage+ portfolio, including both with solutions, I mentioned this, that automate individual steps of a campaign creation setup as well as ones that automate the full end-to-end process. So on the single-step automation, Advantage+ audience, for example, has seen significant growth in adoption since we made it the default audience creation experience for most advertisers in Q4. And that enables advertisers to increase campaign performance by just using audience inputs as a suggestion rather than a hard constraint. And based on tests that we ran, campaigns using Advantage+ audience targeting saw, on average, a 28% decrease in cost per click or per objective compared to using our regular targeting.

關於 Advantage+ 的第二個問題，我們的 Advantage+ 產品組合繼續保持良好的發展勢頭，包括我之前提到的可以自動執行廣告系列創建設置各個步驟的解決方案，以及可以自動執行完整端到端的解決方案。結束進程。因此，在單步驟自動化方面，自從我們在第四季度將 Advantage+ 受眾作為大多數廣告商的預設受眾創建體驗以來，其採用率顯著增長。這樣，廣告商只需將受眾的意見視為建議而非硬性約束，就能提高廣告活動的效果。根據我們進行的測試，與使用常規定位相比，使用 Advantage+ 受眾定位的廣告系列的每次點擊費用或每個目標的費用平均降低了 28%。

On the end-to-end automation products like Advantage+ shopping and Advantage+ app campaigns, we're also seeing very strong growth. Mark mentioned the combined revenue flowing through those 2 has more than doubled since last year. And we think there's still significant runway to broaden adoption, so we're trying to enable more conversion types for Advantage+ shopping. In Q1, we began expanding the list of conversions that businesses could optimize for. So previously, it only supported purchase events, and now we've added 10 additional conversion types. And we're continuing to see strong adoption now across verticals.

在 Advantage+ 購物和 Advantage+ 應用活動等端對端自動化產品方面，我們也看到了非常強勁的成長。馬克提到，這兩家公司的總收入自去年以來增加了一倍多。我們認為，擴大採用範圍還有很大的空間，因此，我們正嘗試為 Advantage+ 購物提供更多轉換類型。在第一季度，我們開始擴大企業可以優化的轉換清單。以前它只支援購買事件，現在我們增加了10種轉換類型。而且我們現在繼續看到各個垂直領域的強勁採用。

So generally, I would say we are building a lot more functionality into the Advantage+ tools over time. also where a lot of our gen AI ads creative features have been introduced and where advertisers have the opportunity to experiment with those. And we'll keep looking to apply what we learn from these products more broadly to our ads investments over the course of the year.

所以總的來說，我想說我們會隨著時間的推移在 Advantage+ 工具中建立更多功能。我們也推出了許多新一代人工智慧廣告創意功能，廣告主有機會對這些功能進行嘗試。我們將繼續尋求將從這些產品中獲得的經驗更廣泛地應用到我們今年的廣告投資中。

Your next question comes from the line of Ken Gawrelski from Wells Fargo.

您的下一個問題來自富國銀行的 Ken Gawrelski。

As you look out through the coming period of product investment, how should we think about the relationship between Family of Apps revenue and cost growth? Is there any insight you can give us there?

展望未來一段時間的產品投資，我們該如何看待應用家族收入與成本成長的關係？您能給我們什麼見解嗎？

And then maybe just one that's a little bit more specific to the G&A growth in 1Q. You called out legal expenses. Just wanted to see if there's anything onetime in there that would cause the elevated growth in 1Q.

然後可能只更具體地針對第一季的 G&A 成長。您要求支付法律費用。只是想看看其中是否存在什麼一次性事件，會導致第一季的成長加速。

Yes. On the second part of your question first, so on the G&A side, that was really driven by legal expenses. We recognized some accruals in Q1 related to ongoing legal matters, and you'll see more detail on that in the 10-Q.

是的。首先回答你問題的第二部分，就 G&A 方面而言，這實際上是由法律費用所驅動的。我們確認第一季與正在進行的法律事務相關的一些應計費用，您將在 10-Q 中看到更多詳細資訊。

On the first part of your question, which is really about sort of the kind of long-term margin profile of Family of Apps, we aren't giving guidance on that per se. But one of the things that we really have been very disciplined about over the course of 2023 and continuing is really operating the business in a very efficiency oriented way. So we're being very disciplined with allocation of new resources. This is a muscle that we really built over 2023 that we believe is important for us to keep carrying forward. And I think you'll see us continue to emphasize that, especially with the Family of Apps business being at the scale that it is.

關於你問題的第一部分，實際上是關於應用程式系列的長期利潤率狀況，我們本身並沒有提供這方面的指導。但在 2023 年期間我們確實非常嚴謹的一件事就是以非常注重效率的方式經營業務。因此，我們對新資源的分配非常嚴格。這是我們在 2023 年真正打造的實力，我們相信這對我們繼續前進至關重要。我想你會看到我們繼續強調這一點，特別是在應用程式系列業務達到如此規模的情況下。

Your next question comes from the line of Ross Sandler from Barclays.

您的下一個問題來自巴克萊銀行的羅斯桑德勒 (Ross Sandler)。

Great. Mark, you partnered with Google and Bing for Meta AI organic search citations. So I guess stepping back, do you think that Meta AI longer term could bring in search advertising dollars at some point? Or do you view this as what others are doing, where you kind of attach a premium subscription tier once people kind of get going on it?

偉大的。馬克，您與 Google 和 Bing 合作推出了 Meta AI 自然搜尋引用。所以我想退一步來說，您是否認為 Meta AI 從長遠來看可以在某個時候帶來搜尋廣告收入？或者您認為這是其他人正在做的事情，一旦人們開始使用它，您就會附加高級訂閱層？

And then the second question is, you mentioned that you guys are working on building AI tools for businesses and creators. So just, I guess, how do you see the business model evolving when we all get to the stage of interacting with something like Taylor Swift's custom AI for merchandise or tickets or something like that. How is that going to play out?

第二個問題是，您提到你們正在致力於為企業和創作者建立人工智慧工具。所以，我想，當我們都進入與泰勒·斯威夫特的商品或門票定制人工智慧等進行互動的階段時，您如何看待商業模式的發展。結果會怎樣？

All right. So yes, on the Google and Microsoft partnerships, yes, I mean we work with them to have real-time information in Meta AI. It's useful. I think it's pretty different from search. We're not working on search ads or anything like that. I think this will end up being a pretty different business.

好的。所以是的，關於與Google和微軟的合作，是的，我的意思是我們與他們合作以在 Meta AI 中獲取即時資訊。它很有用。我認為它與搜索有很大不同。我們沒有從事搜尋廣告或類似業務。我認為這最終會成為一項截然不同的業務。

I do think that there will be an ability to have ads and paid content in Meta AI interactions over time as well as people being able to pay for whether it's bigger models or more compute or some of the premium features and things like that. But that's all very early in fleshing out.

我確實認為，隨著時間的推移，Meta AI 互動中將能夠出現廣告和付費內容，同時人們也將能夠為更大的模型或更多的計算或一些高級功能等付費。但這一切都還處於早期階段。

The thing that I actually think is probably -- the biggest clear opportunity is all the work around business messaging. That's in addition to the stuff that we're already doing, just generate to increase engagement and ads quality in the apps. But business messaging thing, I mean, whether it's a creator or one of the 100-plus million businesses on our platform, we basically want to make it very easy for all of these folks to set up an AI to engage with their community. For a business, that's going to be able to do sales and commerce and customer support. And I think it will be similar for creators, although there will be more of a kind of just fun and engaging part there, but a lot of creators are on the platform because they see this as a business too, whether they're trying to sell concert tickets or products or whatever it is that their business goal is.

我實際上認為最大的明顯機會可能是圍繞商業訊息傳遞的所有工作。這是我們目前所做的事情的補充，只是為了提高應用程式的參與度和廣告品質。但對於商業訊息傳遞的事情，我的意思是，無論是創作者還是我們平台上的1 億多企業之一，我們基本上都希望讓所有這些人都能非常輕鬆地設置AI 來與他們的社區互動。對於企業來說，這將能夠進行銷售、商業和客戶支援。我認為對於創作者來說情況也會類似，儘管其中會有更多的樂趣和參與部分，但很多創作者之所以使用這個平台，是因為他們也把這視為一門生意，無論他們是想銷售音樂會門票或產品或無論他們的商業目標是什麼。

And a lot of these folks either aren't advertising as much as they could or, in business, the business messaging parts, I think, are still relatively undermonetized compared to where they will be. And I think a lot of that is because the cost of engaging with people in messaging is still very high. But AI should bring that down just dramatically for businesses and creators. And I think that, that has the potential. That's probably the -- beyond just increasing engagement and increasing the quality of the ads, I think that, that's probably one of the nearer-term opportunities, even though that will -- it's not like next quarter or the quarter after that scaling thing, but it's -- but that's not like a 5-year opportunity either.

而且我認為，這些人中的許多人要么沒有盡可能多地投放廣告，要么在商業領域，商業訊息傳遞部分的盈利能力與他們未來所處的水平相比仍然相對較低。我認為這在很大程度上是因為透過訊息傳遞與人交流的成本仍然很高。但人工智慧應該能大幅降低企業和創作者的這一成本。我認為這是有潛力的。這可能是——除了增加參與度和提高廣告品質之外，我認為，這可能是近期的機會之一，儘管這不會像下個季度或下個季度的擴張那樣，但這也不像是一個五年的機會。

So I think -- that is one that I think is going to be pretty exciting to look at. But yes, I mean, as Meta AI scales too, I think that, that will have its own opportunities to monetize, and we'll build that out over time. But like I tried to emphasize, we're in the phase of this where the main goal is getting many hundreds of millions or billions of people to use Meta AI as a core part of what they do. That's the kind of next goal, building something that is super valuable. We think this has the potential to be at a very large scale. And that's sort of the next step on the journey.

所以我認為——我認為這將會是一件非常令人興奮的事情。但是的，我的意思是，隨著 Meta AI 的擴展，我認為它將有自己的盈利機會，並且我們會隨著時間的推移逐漸建立它。但就像我試圖強調的那樣，我們正處於這個階段，主要目標是讓數億或數十億人將 Meta AI 作為他們工作的核心部分。這就是下一個目標：創造一些非常有價值的東西。我們認為這有潛力實現非常大規模。這就是旅程的下一步。

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。

And that question comes from the line of Ron Josey from Citi.

這個問題來自花旗銀行的 Ron Josey。

Mark, I want to follow up on a prior question that you mentioned optimism has grown internally quite a bit just with all the improvements and investments and innovations you're making. And we're seeing that in the experience for a few days of Meta AI. So can you just talk to us maybe how the $400 billion parameter model just might evolve the experience on Meta or how you think things might change over the next, call it, months, years, et cetera, as maybe messaging becomes a greater focus and things along those lines? So just a vision longer term.

馬克，我想跟進你之前提到的一個問題，隨著你所做的所有改進、投資和創新，公司內部的樂觀情緒已經大大增強。我們在 Meta AI 的幾天體驗中看到了這一點。那麼，您能否和我們談談，價值4000 億美元的參數模型可能會如何改變Meta 的體驗，或者您認為未來幾個月、幾年等情況將如何變化，因為訊息傳遞可能會變成更大的焦點，類似這樣的事？所以這只是一個長期願景。

Yes. I mean I think that the next phase for a lot of these things are handling more complex tasks and becoming more like agents rather than just chat bots, right? So when I say chatbot, what I mean is you send it a message and it replies to your message, right? So it's almost like almost a 1:1 correspondence.

是的。我的意思是，我認為這些東西的許多下一階段將處理更複雜的任務，變得更像代理而不僅僅是聊天機器人，對嗎？所以當我說聊天機器人時，我的意思是你給它發送一條訊息，它會回覆你的訊息，對嗎？因此這幾乎就像是 1：1 的對應關係。

Whereas what an agent is going to do is you give it an intent or a goal, then it goes off and probably actually performs many queries on its own in the background in order to help accomplish your goal, whether that goal is researching something online or eventually finding the right thing that you're looking to buy. There's a lot of complexity and sort of different things. I think people don't even realize that they will be able to ask computers to do for them.

而代理要做的是你給它一個意圖或目標，然後它就會開始行動，並可能在後台自行執行許多查詢，以幫助實現你的目標，無論這個目標是在線研究某些東西還是最終找到您想購買的正確商品。其中有很多複雜性和各種不同的事情。我認為人們甚至沒有意識到他們能夠讓電腦為他們做事。

And I think basically, the larger models and then the more advanced future versions that will be smaller as well are just going to enable much more interesting interactions like that. So I mean if you think about this, I mean, even some of the business use cases that we talked about, you don't really just want like sales or customer support chatbot that can just respond to what you say. And if you're a business, you have a goal, right? You're trying to support your customers well and you're trying to position your products in a certain way and encourage people to buy certain things that map to their interests and would they be interested in? And that's more of like a multiturn interaction, right?

我認為，基本上，更大的模型以及未來更先進、更小的版本將能夠實現更有趣的互動。所以我的意思是，如果你考慮一下，即使是我們談到的一些商業用例，你也不會真的只想要像銷售或客戶支援聊天機器人那樣能夠回應你所說的話。如果你是一家企業，你就有一個目標，對嗎？您正在嘗試更好地支持您的客戶，您正在嘗試以某種方式定位您的產品並鼓勵人們購買符合他們興趣並他們會感興趣的東西？這更像是多圈互動，對嗎？

So the type of business agent that you're going to be able to enable with just a chatbot is going to be very naive compared to what we're going to have in a year even, but beyond that, too, is just the reasoning and planning abilities if these things grow to be able to just help guide people through the business process of engaging with whatever your goals are as a creator of a business.

因此，與我們一年後將擁有的相比，僅使用聊天機器人就能實現的業務代理類型將非常幼稚，但除此之外，也只是推理而已和規劃能力，如果這些東西發展到能夠幫助指導人們完成業務流程，實現您作為企業創辦人所設定的目標。

So I think that that's going to be extremely powerful. And I think the opportunity is really big. So -- and on top of that, I think what we've shown now is that we have the ability to build leading models in our company. So I think it makes sense to go for it, and we're going to. And I think it's going to be a really good long-term investment. But I did just want to spell out on this call today, the extent to which we're focusing on this and investing in this for the long term because that's what we do.

所以我認為這將會非常強大。我認為這個機會真的很大。所以——最重要的是，我認為我們現在已經展示出我們有能力在公司內建立領先的模型。因此我認為這樣做是合理的，而且我們也會這麼做。我認為這將是一項非常好的長期投資。但我今天只是想在這次電話會議上詳細說明我們對此的關注程度以及對此的長期投資，因為這就是我們的工作。

Great. Thank you for joining us today. We appreciate your time, and we look forward to speaking with you again soon.

偉大的。感謝您今天加入我們。感謝您的時間，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。