Meta Platforms Inc (META) 2024 Q3 法說會逐字稿

Good afternoon. My name is Krista and I will be your conference operator today. (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。 （操作員說明）此通話將會被錄音。非常感謝。

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

Meta 投資者關係總監 Kenneth Dorrell，您可以開始了。

Thank you. Good afternoon and welcome to Meta Platforms third 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 Platforms 2024 年第三季財報電話會議。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.

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。

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

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。現在我想把電話轉給馬克。

All right, thanks Ken. This was a good quarter with strong product and business momentum and with parts of our long term vision around AI and the future of computing coming into sharper focus. We estimate that there are now more than 3.2 billion people using at least one of our apps each day. And we're seeing rapid adoption of Meta AI and Llama, which is quickly becoming a standard across the industry.

好的，謝謝肯。這是一個良好的季度，產品和業務勢頭強勁，我們圍繞著人工智慧和運算未來的部分長期願景變得更加清晰。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。我們看到 Meta AI 和 Llama 的快速採用，它正迅速成為整個行業的標準。

So let's start with some highlights from the apps. For WhatsApp, the US remains one of our fastest growing countries and we just passed a milestone of 2 billion calls made globally every day. On Facebook, we continue to see positive trends with young adults, especially in the US.

讓我們從這些應用程式的一些亮點開始。對於 WhatsApp 而言，美國仍然是我們成長最快的國家之一，我們剛剛突破了全球每天撥打 20 億通電話的里程碑。在 Facebook 上，我們繼續看到年輕人的正面趨勢，尤其是在美國。

On Instagram, global growth remains strong. We also launched teen accounts this quarter which add built-in protections that limit who teens are messaging and what content they can see. On Threads, the community now has almost 275 million monthly actives. It's been growing more than 1 million sign ups per day, engagement is growing too. So we continue to be on track towards this becoming our next major social app.

Instagram 的全球成長依然強勁。我們本季也推出了青少年帳戶，增加了內建保護措施，限制青少年向誰發送訊息以及他們可以看到哪些內容。在 Threads 上，社群目前每月活躍人數接近 2.75 億人。每天的註冊人數已超過 100 萬，參與度也不斷增加。因此，我們繼續朝著成為我們下一個主要社交應用程式的方向前進。

We are making a lot of progress with our AI efforts too. And we're seeing AI have a positive impact on nearly all aspects of our work. From our core business engagement and monetization to our long term road maps for new services and computing platforms. And that this partially comes from having a vision and road map that is aligned with the direction that technology is heading. But even more importantly from our teams doing some really excellent work on execution on so many fronts.

我們在人工智慧方面的努力也取得了很大進展。我們看到人工智慧對我們工作的幾乎所有方面都產生了積極影響。從我們的核心業務參與和貨幣化到新服務和計算平台的長期路線圖。這部分來自於擁有與技術發展方向一致的願景和路線圖。但更重要的是，我們的團隊在許多方面都在執行上做了一些非常出色的工作。

Meta AI now has more than 500 million monthly actives. Improvements to our AI driven feed and video recommendations have led to an 8% increase in time spent on Facebook, and a 6% increase on Instagram this year alone. More than 1 million advertisers used our Gen AI tools to create more than 15 million ads in the last month. And we estimate that businesses using image generation are seeing a 7% increase in conversions. And we believe that there's a lot more upside here.

Meta AI 目前每月活躍人數超過 5 億人。光是今年，我們對 AI 驅動的資訊流和影片推薦的改進就使 Facebook 上花費的時間增加了 8%，Instagram 上花費的時間增加了 6%。上個月，超過 100 萬廣告商使用我們的 Gen AI 工具製作了超過 1500 萬則廣告。我們估計使用影像產生的企業的轉換率增加了 7%。我們相信這裡還有更多的好處。

We are also seeing great momentum with Llama. Llama token usage has grown exponentially this year. And the more widely that Llama gets adopted and becomes the industry standard, the more that the improvements to its quality and efficiency will flow back to all of our products. This quarter, we released the Llama 3.2 including the leading small models that run on device and open source multimodal models. We are working with enterprises to make it easier to use. And now we're also working with the public sector to adopt Llama across the US government.

我們也看到 Llama 的強勁勢頭。 Llama 代幣的使用量今年呈指數級增長。 Llama 得到越廣泛的採用並成為行業標準，其品質和效率的改進就越會回流到我們的所有產品中。本季度，我們發布了 Llama 3.2，包括在設備上運行的領先小型模型和開源多模式模型。我們正在與企業合作，使其更易於使用。現在我們也與公共部門合作，在美國政府範圍內收養 Llama。

The Llama 3 models have been something of an inflection point in the industry. But I'm even more excited about Llama 4, which is now well into its development. We're training the Llama 4 models on a cluster that is bigger than 100,000 H100s, or bigger than anything that I've seen reported for what others are doing.

Llama 3 型號已成為業界的轉捩點。但我對 Llama 4 更感興趣，它現在已經進入開發階段。我們正在一個超過 100,000 個 H100 的集群上訓練 Llama 4 模型，或者比我所看到的其他人正在做的事情報告的任何集群都大。

I expect that the smaller Llama 4 models will be ready first. And they'll be ready, we expect sometime early next year. And I think that there are going to be a big deal on several fronts, new modalities capabilities, stronger reasoning, and much faster. It seems pretty clear to me that open source will be the most cost effective, customizable, trustworthy, performant, and easiest to use option that is available to developers. And I am proud that Llama is leading the way on this.

我預計較小的 Llama 4 型號將首先準備就緒。我們預計明年初的某個時候，他們就會準備好。我認為，在幾個方面都會有重大進展：新的模式能力、更強的推理能力以及更快的速度。在我看來，開源將是開發人員可用的最具成本效益、可自訂、值得信賴、高效且最易於使用的選項。我很自豪 Llama 在這方面處於領先地位。

All right now, it's the time of the year at Meta when we plan our budget for the next year and that's still in progress. But I wanted to share a few things that have stood out to me as we've gone through this process so far. First, it's clear that there are a lot of new opportunities to use new AI advances to accelerate our core business that should have strong ROI over the next few years. So I think we should invest more there.

好吧，現在是 Meta 每年計劃明年預算的時候，而且仍在進行中。但我想分享一些在我們迄今為止經歷的過程中對我來說很突出的事情。首先，很明顯，有許多新的機會可以利用新的人工智慧進步來加速我們的核心業務，這些業務在未來幾年應該會產生強勁的投資報酬率。所以我認為我們應該在那裡投入更多。

And second, our AI investments continue to require serious infrastructure and I expect to continue investing significantly there too. We haven't decided on a final budget yet, but those are some of the directional trends that I'm seeing.

其次，我們的人工智慧投資仍需要嚴格的基礎設施，我預計也將繼續在這方面進行大量投資。我們尚未決定最終預算，但這些是我看到的一些方向趨勢。

Now, moving on this quarter, we also had several milestones around Reality Labs and the integration of AI in wearables, Ray-Ban Meta glasses are the prime example here. They are great looking glasses that let you take photos and videos, listen to music, and take calls. But what makes them really special is the Meta AI integration.

現在，在本季度，我們在現實實驗室和人工智慧在穿戴式裝置中的整合方面也取得了幾個里程碑，雷朋 Meta 眼鏡就是最好的例子。它們是一款外觀精美的眼鏡，可讓您拍攝照片和影片、聽音樂和接聽電話。但真正讓它們與眾不同的是 Meta AI 整合。

With our new updates, it'll be able to not only answer your questions throughout the day but also help you remember things, give you suggestions as you're doing things using real time multimodal AI, and even translate other languages right in your ear for you.

透過我們的新更新，它不僅能夠全天回答您的問題，還可以幫助您記住事情，在您使用實時多模式人工智能做事時為您提供建議，甚至可以在您耳邊翻譯其他語言為你。

I continue to think that glasses are the ideal form factor for AI because you can let your AI see what you see, hear what you hear, and talk to you. Demand for the glasses continues to be very strong. The new clear edition that we released at Connect, sold out almost immediately and has been trading online for over $1000. We've deepened our partnership with EssilorLuxottica to build future generations of smart eyewear that deliver both cutting edge technology and style.

我仍然認為眼鏡是人工智慧的理想外形，因為你可以讓你的人工智慧看到你所看到的，聽到你聽到的，並與你交談。對眼鏡的需求仍然非常強勁。我們在 Connect 上發布的新透明版本幾乎立即售空，線上交易價格超過 1000 美元。我們加深了與 EssilorLuxottica 的合作關係，打造兼具尖端技術和時尚風格的下一代智慧眼鏡。

At Connect, we also showed Orion, our first full holographic AR glasses. We've been working on this one for about a decade and it gives you a sense of where this is all going. We're not too far off from being able to deliver great looking glasses that let you seamlessly blend the physical and digital worlds so you can feel present with anyone no matter where they are. And we're starting to see the next computing platform come together and it's pretty exciting.

在 Connect 上，我們還展示了 Orion，我們的首款全像 AR 眼鏡。我們在這方面已經投入了大約十年的時間，它讓您了解這一切的進展。我們距離提供精美的眼鏡已經不遠了，它可以讓您無縫地融合物理世界和數位世界，讓您感受到與任何人在一起，無論他們身在何處。我們開始看到下一個計算平台的出現，這非常令人興奮。

All right, we also released our newest mixed reality headset, Quest 3S. It brings the best capabilities of Quest 3, high quality color passthrough, a new chip set and more at the much more accessible price point of $300. Reviews are great so far. And I'm looking forward to seeing how well it does this holiday season as more people get their hands on it.

好吧，我們也發布了最新的混合實境耳機 Quest 3S。它以更實惠的 300 美元價格帶來了 Quest 3 的最佳功能、高品質色彩直通、新晶片組等。到目前為止，評論都很棒。隨著越來越多的人使用它，我期待看到它在這個假期的表現如何。

So overall, this has been a good quarter. I'm pretty amped about all the work that we're doing right now. This may be the most dynamic moment that I've seen in our industry and I am focused on making sure that we build some awesome things and make the most of the opportunities ahead. And if we do this well then the potential for Meta and everyone building with us will be massive. As always, I'm grateful for everyone who is on this journey with us, our teams, our partners and our investors.

總的來說，這是一個不錯的季度。我對我們現在正在做的所有工作感到非常興奮。這可能是我在我們的行業中見過的最具活力的時刻，我專注於確保我們創造一些很棒的東西並充分利用未來的機會。如果我們做得好，那麼 Meta 以及與我們一起建立的每個人的潛力將是巨大的。一如既往，我感謝與我們一起踏上這段旅程的每個人、我們的團隊、我們的合作夥伴和我們的投資者。

And now, here's Susan.

現在，蘇珊來了。

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. Q3 total revenue was $40.6 billion, up 19% or 20% on a constant currency basis. Q3 total expenses were $23.2 billion, up 14% 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。第三季總營收為 406 億美元，以固定匯率計算成長 19% 或 20%。第三季總支出為 232 億美元，較去年成長 14%。

In terms of the specific line items, cost of revenue increased 19%, driven primarily by higher infrastructure costs. R&D increased 21%, mostly driven by higher headcount-related expenses and infrastructure costs. Marketing and sales decreased 2%, driven primarily by lower restructuring costs. G&A decreased 10%, driven primarily by lower legal-related expenses.

就具體項目而言，收入成本增加了 19%，主要是由於基礎設施成本上升。研發成長 21%，主要是因為人員相關費用和基礎設施成本增加。行銷和銷售額下降 2%，主要是由於重組成本下降。一般行政費用下降 10%，主要是因為法律相關費用減少。

We ended the third quarter with over 72,400 employees, up 9% year-over-year, with growth primarily driven by hiring in our priority areas of monetization, infrastructure, Reality Labs, Generative AI as well as regulation and compliance.

截至第三季末，我們擁有超過 72,400 名員工，年增 9%，成長主要由貨幣化、基礎設施、現實實驗室、產生人工智慧以及監管和合規等優先領域的招聘推動。

Third quarter operating income was $17.4 billion, representing a 43% operating margin. Our tax rate for the quarter was 12%. Net income was $15.7 billion or $6.03 per share. Capital expenditures, including principal payments on finance leases were $9.2 billion, driven by investments in servers, data centers, and network infrastructure. Our capital expenditures were impacted in part by the timing of third quarter server deliveries which will be paid for in the fourth quarter.

第三季營業收入為 174 億美元，營業利益率為 43%。我們本季的稅率為 12%。淨利潤為 157 億美元，即每股 6.03 美元。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 92 億美元。我們的資本支出部分受到第三季伺服器交付時間的影響，這些伺服器將在第四季度支付。

Free cash flow was $15.5 billion. In Q3, we completed a debt offering of $10.5 billion, repurchased $8.9 billion of our Class A common stock, and paid $1.3 billion in dividends to shareholders, ending the quarter with $70.9 billion in cash and marketable securities and $28.8 billion in debt.

自由現金流為 155 億美元。第三季度，我們完成了105 億美元的債務發行，回購了89 億美元的A 類普通股，並向股東支付了13 億美元的股息，本季末現金和有價證券為709 億美元，債務為288 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 more than 3.2 billion people using at least one of our Family of Apps on a daily basis in September. Q3 total Family of Apps revenue was $40.3 billion, up 19% year-over-year. Q3 Family of Apps ad revenue was $39.9 billion, up 19% or 20% 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，9 月每天至少有超過 32 億人使用我們的應用程式系列之一。第三季應用系列總營收為 403 億美元，較去年同期成長 19%。第三季應用程式系列廣告收入為 399 億美元，以固定匯率計算成長 19% 或 20%。

Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by health care, and entertainment and media. On a user geography basis, ad revenue growth was strongest in Rest of World and Europe at 23% and 21%, respectively. Asia Pacific grew 18% and North America grew 16%.

在廣告收入中，線上商務垂直領域是年成長的最大貢獻者，其次是醫療保健、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 23% 和 21%。亞太地區成長 18%，北美成長 16%。

On an advertiser geography basis, total revenue growth was strongest in North America and Europe at 21%. Rest of World was up 17%, while Asia Pacific was the slowest-growing region at 15%, decelerating from our second quarter growth rate of 28% due mainly to lapping a period of stronger demand from China-based advertisers.

從廣告客戶地理位置來看，北美和歐洲的總營收成長最為強勁，達到 21%。世界其他地區成長了 17%，而亞太地區成長最慢，為 15%，較第二季 28% 的成長率有所放緩，這主要是由於中國廣告商的需求強勁。

In Q3, the total number of ad impressions served across our services increased 7% and the average price per ad increased 11%. 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 surfaces.

第三季度，我們服務中的廣告展示總數增加了 7%，每個廣告的平均價格增加了 11%。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，特別是來自較低貨幣化區域和表面的展示次數成長。

Family of Apps other revenue was $434 million, up 48%, driven primarily by business messaging revenue growth from our WhatsApp Business platform. We continue to direct the majority of our investments for the development and operation of our Family of Apps. In Q3, Family of Apps expenses were $18.5 billion, representing approximately [80%] of our overall expenses.

應用程式系列其他收入為 4.34 億美元，成長 48%，這主要是由 WhatsApp Business 平台的商業訊息收入成長所推動的。我們繼續將大部分投資用於應用程式系列的開發和營運。第三季度，應用程式系列支出為 185 億美元，約占我們整體支出的 [80%]。

Family of Apps expenses were up 13%, primarily due to higher infrastructure and headcount-related expenses, partially offset by lower legal-related expenses. Family of Apps operating income was $21.8 billion, representing a 54% operating margin.

應用程式系列支出增加了 13%，主要是由於基礎設施和人員相關支出增加，但部分被法律相關支出減少所抵消。 Family of Apps 營業收入為 218 億美元，營業利益率為 54%。

Within our Reality Lab segment, Q3 revenue was $270 million, up 29%, driven by hardware sales. Reality Labs expenses were $4.7 billion, up 19% year-over-year, driven primarily by higher headcount-related expenses and infrastructure costs. Reality Labs operating loss was $4.4 billion.

在我們的現實實驗室部門中，受硬體銷售的推動，第三季營收為 2.7 億美元，成長 29%。 Reality Labs 支出為 47 億美元，年增 19%，主要是因為人員相關支出和基礎設施成本增加。 Reality Labs 營運虧損為 44 億美元。

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

現在轉向業務前景。推動我們收入表現的主要因素有兩個：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。

On the first, we are focused on both improving people's experiences within our apps today and investing in longer-term initiatives that have the potential to contribute to engagement in the years ahead. We expect our content recommendations road map will span both of these time frames as we have nearer-term work streams focused on improving recommendations as well as multiyear initiatives to develop innovative new approaches.

首先，我們專注於改善人們在當今應用程式中的體驗，並投資於有可能在未來幾年促進參與的長期計劃。我們預計我們的內容推薦路線圖將跨越這兩個時間框架，因為我們的近期工作流程專注於改進推薦以及開發創新新方法的多年計劃。

I'll focus first on the near term. In the third quarter, we continue to see daily usage grow year-over-year across Facebook and Instagram, both globally and in the US. On Facebook, we're seeing strong results from the global rollout of our unified video player in June.

我將首先關注近期。第三季度，我們繼續看到 Facebook 和 Instagram 在全球和美國的每日使用量較去年同期成長。在 Facebook 上，我們看到六月在全球推出統一視訊播放器帶來的強勁成果。

Since introducing the new experience and prediction systems that power it, we've seen a 10% increase in time spent within the Facebook video player. This month, we've entered the next phase of Facebook's video product evolution. Starting in the US and Canada, we are updating the stand-alone video tab to a full screen viewing experience, which will allow people to seamlessly watch videos in a more immersive experience. We expect to complete this global rollout in early 2025.

自從引入為其提供支援的新體驗和預測系統以來，我們發現 Facebook 影片播放器上花費的時間增加了 10%。本月，我們進入了 Facebook 影片產品演變的下一階段。從美國和加拿大開始，我們正在將獨立視訊標籤更新為全螢幕觀看體驗，這將使人們能夠以更身臨其境的體驗無縫觀看影片。我們預計將於 2025 年初完成全球部署。

On Instagram, Reels continues to see good traction, and we're making ongoing progress with our focus on promoting original content, with more than 60% of recommendations now coming from original posts in the US. This is helping people find unique and differentiated content on Instagram while also helping earlier stage creators get discovered.

在 Instagram 上，Reels 繼續保持良好的吸引力，我們在推廣原創內容方面不斷取得進展，目前超過 60% 的推薦來自美國的原創貼文。這有助於人們在 Instagram 上找到獨特且與眾不同的內容，同時也幫助早期創作者被發現。

Next, let me talk more about our multiyear road map for recommendations. Previously, we operated separate ranking and recommendation systems for each of our products because we found that performance did not scale if we expanded the model size and compute power beyond a certain point.

接下來，讓我多談談我們的多年建議路線圖。以前，我們為每個產品運行單獨的排名和推薦系統，因為我們發現，如果我們將模型大小和運算能力擴展到某個點以上，效能就不會擴展。

However, inspired by the scaling laws we were observing with our large language models, last year, we developed new ranking model architectures capable of learning more effectively from significantly larger data sets. To start, we have been deploying these new architectures to our Facebook video ranking models, which has enabled us to deliver more relevant recommendations and unlock meaningful gains in watch time.

然而，受到我們在大型語言模型中觀察到的縮放定律的啟發，去年，我們開發了新的排名模型架構，能夠從更大的資料集中更有效地學習。首先，我們一直在將這些新架構部署到我們的 Facebook 影片排名模型中，這使我們能夠提供更相關的推薦並在觀看時間方面獲得有意義的收益。

Now we're exploring whether these new models can unlock similar improvements to recommendations on other services. After that, we will look to introduce cross-surface data to these models, so our systems can learn from what is interesting to someone on one surface of our apps and use it to improve their recommendations on another. This will take time to execute and there are other explorations that we will pursue in parallel.

現在我們正在探索這些新模型是否可以對其他服務的推薦帶來類似的改進。之後，我們將尋求將跨表面數據引入這些模型，以便我們的系統可以從我們應用程式的一個表面上的某人感興趣的內容中學習，並使用它來改進他們對另一個表面的推薦。這需要時間來執行，我們將同時進行其他探索。

However, over time, we are optimistic that this will unlock more relevant recommendations while also leading to higher engineering efficiency as we operate a smaller number of recommendations.

然而，隨著時間的推移，我們樂觀地認為，這將解鎖更多相關的建議，同時由於我們運行的建議數量較少，因此還可以提高工程效率。

Beyond recommendations, we're making progress with our other longer-term engagement priorities, including Generative AI and Threads. Meta AI usage continues to scale as we make it available in more countries and languages. We're seeing lifts in usage as we improve our models and have introduced a number of enhancements in recent months to make Meta AI more helpful and engaging.

除了建議之外，我們還在其他長期參與優先事項上取得進展，包括產生人工智慧和執行緒。隨著我們在更多國家和語言中提供元人工智慧，其使用量不斷擴大。隨著我們改進模型並在最近幾個月引入了許多增強功能，使 Meta AI 更加有用且更具吸引力，我們看到了使用量的提升。

Last month, we began introducing voice, so you can speak with Meta AI more naturally, and it's now fully available in English to people in the US, Australia, Canada, and New Zealand. In the US, people can now also upload photos to Meta AI to learn more about them, write captions for post, and add, remove, or change things about their images with a simple text prompt. These are all built with our first multimodal foundation model, Llama 3.2.

上個月，我們開始引入語音，這樣您就可以更自然地與 Meta AI 交談，現在美國、澳洲、加拿大和紐西蘭的用戶可以完全使用英語。在美國，人們現在還可以將照片上傳到 Meta AI 以了解有關它們的更多信息，為帖子編寫標題，並通過簡單的文本提示添加、刪除或更改有關圖像的內容。這些都是用我們的第一個多模式基礎模型 Llama 3.2 建構的。

Threads remains another area where we see exciting potential. We are bringing on an increasing number of new users each quarter while depth of engagement also continues to grow. Looking ahead, we plan to introduce more features to make it even easier for people to stay up to date on topics they care about.

線程仍然是我們看到令人興奮的潛力的另一個領域。我們每季都會吸引越來越多的新用戶，同時參與深度也不斷成長。展望未來，我們計劃推出更多功能，讓人們更輕鬆地了解他們關心的主題的最新動態。

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.

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。我們繼續看到在影片等盈利能力較低的領域增加廣告供應的機會。

Within Facebook, video engagement continues to shift to short form following the unification of our video player, and we expect this to continue with the transition of the video tab to a full screen format. This is resulting in an organic video impressions growing more quickly than overall video time on Facebook, which provides more opportunities to serve ads.

在 Facebook 內部，隨著視訊播放器的統一，視訊互動繼續轉向短格式，我們預計隨著視訊標籤向全螢幕格式的轉變，這種情況也將繼續下去。這導致自然影片展示量的成長速度比 Facebook 上的整體影片時間成長得更快，從而提供了更多投放廣告的機會。

Across both Facebook and Instagram, we're also continuing our broader work to optimize when and where we should show ads within a person's session. This is enabling us to drive revenue and conversion growth without increasing the number of ads.

在 Facebook 和 Instagram 上，我們也持續更廣泛的工作，以優化在用戶會話中展示廣告的時間和地點。這使我們能夠在不增加廣告數量的情況下推動收入和轉換率成長。

The second part of improving monetization efficiency is enhancing marketing performance. Similar to organic content ranking, we are finding opportunities to achieve meaningful ads performance gains by adopting new approaches to modeling. For example, we recently deployed new learning and modeling techniques that enable our ad systems to consider the sequence of actions a person takes before and after seeing an ad.

提高變現效率的第二部分是提升行銷績效。與自然內容排名類似，我們正在尋找機會透過採用新的建模方法來實現有意義的廣告效果提升。例如，我們最近部署了新的學習和建模技術，使我們的廣告系統能夠考慮人們在看到廣告之前和之後採取的操作順序。

Previously, our ad system could only aggregate those actions together without mapping the sequence. This new approach allows our systems to better anticipate how audiences will respond to specific ads. Since we adopted the new models in the first half of this year, we've already seen a 2% to 4% increase in conversions based on testing within selected segments.

以前，我們的廣告系統只能將這些操作聚合在一起，而無法映射順序。這種新方法使我們的系統能夠更好地預測受眾對特定廣告的反應。自從我們在今年上半年採用新車型以來，根據選定細分市場的測試，我們已經看到轉換率增加了 2% 到 4%。

We're also evolving our ads platform to ensure that the results we drive are customized to each business' objectives and to the way they measure value. In Q3, we introduced changes to our ads ranking and optimization models to take more of the cross-publisher journey into account, which we expect to increase the Meta attributed conversions that advertisers see in their third-party analytics tools.

我們也正在改進我們的廣告平台，以確保我們推動的結果根據每個企業的目標及其衡量價值的方式進行客製化。在第三季度，我們對廣告排名和優化模型進行了更改，以更多地考慮跨發布商的旅程，我們預計這將增加廣告商在第三方分析工具中看到的元歸因轉換。

We're also testing new features and settings for advertisers that will allow them to optimize their campaigns for what they value most, such as driving incremental conversions rather than absolute conversions.

我們也正在為廣告主測試新功能和設置，使他們能夠根據自己最重視的目標來優化廣告系列，例如推動增量轉換而不是絕對轉換。

Finally, there is continued momentum with our Advantage+ solutions, including our ad creative tools. We're seeing strong retention with advertisers using our Generative AI-powered image expansion, background generation, and text generation tools, and they're already driving improved performance for advertisers even at this early stage.

最後，我們的 Advantage+ 解決方案（包括我們的廣告創意工具）持續保持強勁勢頭。我們看到使用我們的生成式人工智慧驅動的圖像擴展、背景生成和文字生成工具的廣告商保留率很高，即使在這個早期階段，他們也已經在推動廣告商業績的提高。

Earlier this month, we began testing our first video generation features, video expansion and image animation. We expect to make them more broadly available by early next year.

本月早些時候，我們開始測試我們的第一個影片生成功能、影片擴充和圖像動畫。我們預計到明年初將更廣泛地提供它們。

Next, I'd like to discuss our approach to capital allocation. We continue to take a long-term view in running the business, which involves investing in a portfolio of opportunities that we expect will generate returns over different time periods. We are very optimistic about the set of opportunities in front of us and believe that investing now in both infrastructure and talent will not only accelerate our progress, but increase the likelihood of maximizing returns within each area.

接下來，我想討論一下我們的資本配置方法。我們繼續以長遠的眼光來經營業務，這涉及投資於我們預計在不同時期產生回報的機會組合。我們對擺在我們面前的一系列機會感到非常樂觀，並相信現在對基礎設施和人才的投資不僅會加速我們的進步，而且會增加每個領域最大回報的可能性。

This includes investing in both near-term initiatives to deliver continued healthy revenue growth within our core business as well as longer-term opportunities that have the scale to deliver compelling returns over time. Given the lead time of our longer-term investments, we also continue to maximize our flexibility so that we can react to market developments.

這包括投資於短期計劃，以在我們的核心業務中實現持續健康的收入成長，以及長期機會，以隨著時間的推移提供可觀的回報。鑑於我們長期投資的準備時間，我們也持續最大限度地提高靈活性，以便我們能夠對市場發展做出反應。

Within Reality Labs, this has benefited us as we've evolved our road map to respond to the earlier-than-expected success of smart glasses. Within Generative AI, we expect significantly scaling up our infrastructure capacity now, while also prioritizing its fungibility will similarly position us well to respond to how the technology and market develop in the years ahead.

在 Reality Labs 中，這讓我們受益匪淺，因為我們已經制定了路線圖，以應對智慧眼鏡早於預期的成功。在生成人工智慧中，我們預計現在將顯著擴大我們的基礎設施容量，同時優先考慮其可替代性，這將使我們能夠很好地應對未來幾年技術和市場的發展。

Moving now to our financial outlook. We expect fourth quarter 2024 total revenue to be in the range of $45 billion to $48 billion. Our guidance assumes foreign currency is approximately neutral to year-over-year total revenue growth based on current exchange rates.

現在轉向我們的財務前景。我們預計 2024 年第四季的總營收將在 450 億美元至 480 億美元之間。我們的指導假設根據當前匯率，外幣對年比總收入成長大致呈現中性。

Turning now to the expense outlook. We expect full year 2024 total expenses to be in the range of $96 million to $98 billion, updated from our prior range of $96 billion to $99 billion. For Reality Labs, we continue to expect 2024 operating losses to increase meaningfully year-over-year due to our ongoing product development efforts and investments to further scale our ecosystem.

現在轉向費用前景。我們預計 2024 年全年總支出將在 9,600 萬美元至 980 億美元之間，從先前的 960 億美元至 990 億美元區間更新。對於 Reality Labs 來說，由於我們持續進行產品開發工作和進一步擴大生態系統的投資，我們仍然預計 2024 年的營運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 $38 billion to $40 billion, updated from our prior range of $37 billion to $40 billion. We continue to expect significant capital expenditure growth in 2025. Given this, along with the back-end weighted nature of our 2024 CapEx, we expect a significant acceleration in infrastructure expense growth next year as we recognize higher growth in depreciation and operating expenses of our expanded infrastructure fleet.

現在轉向資本支出前景。我們預計 2024 年全年資本支出將在 380 億美元至 400 億美元之間，先前的範圍為 370 億美元至 400 億美元。我們仍預計2025 年資本支出將大幅成長。更快。

Onto tax, absent any changes to our tax landscape, we expect our fourth quarter 2024 tax rate to be in the low 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.

在稅收方面，如果我們的稅收格局沒有任何變化，我們預計 2024 年第四季的稅率將在十幾歲以下。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, this was another good quarter for our business. Our global community continues to grow. We're seeing ongoing momentum across our core priorities and we have exciting opportunities ahead of us to drive further growth in our core business in 2025 and capitalize on the longer-term opportunities ahead.

最後，這是我們業務的另一個好季度。我們的全球社區不斷發展。我們看到我們核心優先事項的持續勢頭，我們面臨著令人興奮的機會，可以在 2025 年推動我們核心業務的進一步成長，並利用未來的長期機會。

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)

（操作員說明）

Brian Nowak, Morgan Stanley.

布萊恩·諾瓦克，摩根士丹利。

Thanks for taking my questions. I have two, one for Mark and one for Susan. Mark, I wanted to sort of ask you about Meta AI a little bit. Can you help us understand some of the more recurring types of interactions or query types you're seeing with this product and whether they have commercial intent?

感謝您回答我的問題。我有兩本，一本給馬克，一本給蘇珊。馬克，我想問你一些關於 Meta AI 的問題。您能否幫助我們了解您在該產品中看到的一些更常見的互動類型或查詢類型以及它們是否具有商業意圖？

And then just over time, how do you think about building your own in-house search offering as opposed to partnering and having another player partner those queries?

然後隨著時間的推移，您如何考慮建立自己的內部搜尋產品，而不是合作並讓其他玩家合作這些查詢？

And then Susan, I wanted to ask you about sort of head count because you talked a lot about sort of infrastructure investment in '25. How do we sort of think about relative head count investments into '25 to sort of support all that infrastructure versus what you've been doing in 2024? Thanks.

然後蘇珊，我想問你有關人員數量的問題，因為你在 25 年談論了很多基礎設施投資的問題。與您在 2024 年所做的事情相比，我們如何看待 25 年為支援所有基礎設施而進行的相對人員投資？謝謝。

Brian, thanks for the question. This is Susan. So your first question was around what kinds of recurring interactions that we see between people and their usage of Meta AI. And we're seeing -- first of all, I think, as Mark mentioned, just we're excited about the progress of Meta AI. It's obviously very early in its journey, but it continues to be on track to be the most used AI assistant in the world by end of year and it has over 500 million monthly actives.

布萊恩，謝謝你的提問。這是蘇珊。所以你的第一個問題是關於我們在人們之間看到什麼樣的重複互動以及他們對元人工智慧的使用。我們看到——首先，我認為，正如馬克所提到的，我們對元人工智慧的進展感到興奮。顯然，它的發展還處於早期階段，但到年底，它仍有望成為世界上使用最多的人工智慧助手，每月活躍用戶數超過 5 億。

And people are using it for many things. A number of the frequent use cases we're seeing include information gathering, help with how-to tasks, which is the largest use case. We also see people using it to go deeper on interest, to look for content on our services, for image generation, that's also been another pretty popular use case so far.

人們正在用它來做很多事情。我們看到的許多常見用例包括資訊收集、幫助完成操作任務，這是最大的用例。我們也看到人們使用它來更深入地了解興趣，在我們的服務上尋找內容，用於圖像生成，這也是迄今為止另一個非常流行的用例。

And I would say that in the near term, our focus is really on making Meta AI increasingly valuable for people and if we are successful, we think there will be a broadening set of queries that people use it for including more monetizable queries over time.

我想說的是，在短期內，我們的重點實際上是讓元人工智慧對人們越來越有價值，如果我們成功，我們認為隨著時間的推移，人們會使用它來包含更多可獲利的查詢，從而擴大查詢範圍。

The second part of your question, Meta AI draws from content across the web to address timely questions from users, and it provides sources for those results from our search engine partners. We've integrated with Bing and Google, both of whom offer great search experiences. Like other companies, we also train our Gen AI models on content that is publicly available online, and we crawl the web for a variety of purposes.

您問題的第二部分，Meta AI 從網路上的內容中提取內容來及時解決用戶提出的問題，並為我們的搜尋引擎合作夥伴提供這些結果的來源。我們已經與 Bing 和 Google 集成，兩者都提供出色的搜尋體驗。與其他公司一樣，我們也根據線上公開的內容來訓練我們的 Gen AI 模型，並且我們出於各種目的而抓取網路。

Your second question was really, I think, around maybe how we're thinking about head count in 2025. And we are still working through our budgeting processes for '25. That's in part why we changed our forward-looking guidance approach to give guidance in the next call. But as we're working through this, we are looking at where there are opportunities for us to invest in our strategic priorities and that includes monetization, infrastructure, Reality Labs, Gen AI, our ongoing investments in regulation and compliance.

我認為，你的第二個問題實際上是關於我們如何考慮 2025 年的員工人數。這就是我們改變前瞻性指導方法以在下一次電話會議中提供指導的部分原因。但在我們解決這個問題的過程中，我們正在尋找哪些機會可以投資我們的策略重點，其中包括貨幣化、基礎設施、現實實驗室、Gen AI、我們在監管和合規方面的持續投資。

And we're really evaluating each of those opportunities with an eye towards what, either the measurable ROI looks like or what the strategic opportunity looks like, depending on what the area is. And we're supporting that by continuing to really focus on streamlining our operations elsewhere. So we don't have specifics to share about head count growth in 2025, but that gives you a little bit of the flavor of where we are in the budgeting process.

我們確實在評估每一個機會，著眼於可衡量的投資報酬率或策略機會，這取決於該領域是什麼。我們透過繼續真正專注於簡化我們在其他地方的運作來支持這一點。因此，我們沒有關於 2025 年員工人數增長的具體信息，但這讓您對我們在預算過程中的進展有一些了解。

Eric Sheridan, Goldman Sachs.

艾瑞克‧謝裡丹，高盛。

Thanks so much for taking the question. Maybe just one building on that question from Brian and going back to Mark's comments about the learnings as you do go through the business planning process. Mark, I wanted to understand better what you continue to learn about what the biggest opportunity sets are to apply AI to when you think about your platform, your product portfolio, and your internal processes?

非常感謝您提出問題。也許只是以布萊恩提出的問題為基礎，然後在您進行業務規劃過程時回到馬克對所學到的知識的評論。馬克，我想更了解您在考慮您的平台、產品組合和內部流程時，繼續了解應用人工智慧的最大機會集是什麼？

Because you sound quite optimistic about key learnings and now they continue to ramp and maybe even accelerate in terms of the potential for return profile. I just want to go a little bit deeper into what your key learnings are as you go through that process. Thank you.

因為你聽起來對關鍵的學習非常樂觀，現在它們繼續成長，甚至可能在回報潛力方面加速。我只是想更深入地了解您在經歷這個過程時學到的關鍵知識。謝謝。

I think the main point here is just that it seems broadly applicable to a very wide variety of products. So there are areas that are more part of our core business from making feed more relevant and Reels more relevant to making ads more relevant to helping advertisers generate better ads to helping people create the content that they want, helping our integrity operations, and compliance, and the work that we do there, that's important.

我認為這裡的要點是它似乎廣泛適用於各種各樣的產品。因此，有些領域是我們核心業務的一部分，從使Feed 更相關、讓Reels 更相關、讓廣告更相關、幫助廣告商產生更好的廣告、幫助人們創建他們想要的內容、幫助我們的誠信經營和合規性，我們在那裡所做的工作非常重要。

It's very valuable across all these aspects of the core business, but then it also is going to enable completely new types of services. Like we didn't have something like Meta AI before. We didn't have something like the Ray-Ban Meta glasses before. And AI is going to be a really important ingredient of all of these things.

它在核心業務的所有這些方面都非常有價值，但它也將支援全新類型的服務。就像我們以前沒有像 Meta AI 這樣的東西一樣。我們以前沒有雷朋 Meta 眼鏡之類的東西。人工智慧將成為所有這些事情的一個非常重要的組成部分。

There are also other new products like that, things around AI Studio. This year, we really focused on rolling out Meta AI as kind of our are kind of single assistant that people can ask any question to, but I think there's a lot of opportunities that I think we'll see ramp more over the next year in terms of both consumer and business use cases, for people interacting with a wide variety of different AI agents, consumer ones with AI Studio around whether it's different creators or kind of different agents that people create for entertainment.

還有其他類似的新產品，圍繞著 AI Studio 的東西。今年，我們真正專注於推出 Meta AI，作為我們的單一助手，人們可以向其提出任何問題，但我認為明年我們會看到更多的機會。不同的人工智慧代理進行互動的人來說，無論是不同的創作者還是人們為娛樂而創建的不同代理，AI Studio 的消費者都是如此。

Or on the business side, we do want to continue making progress on this vision of making it set any small business or any business over time can -- with a few clicks stand up in AI agent that can help do customer service and sell things to all of their customers around the world, and I think that's a huge opportunity. So it's very broad.

或者在業務方面，我們確實希望在這一願景上繼續取得進展，讓任何小型企業或任何企業隨著時間的推移都可以——只需點擊幾下人工智能代理即可幫助提供客戶服務並向其銷售產品他們遍布世界各地的所有客戶，我認為這是一個巨大的機會。所以它的範圍非常廣泛。

And I think part of what we're seeing is that there are a lot of opportunities. Some of the longer-term ones are on Meta AI or AI Studio, those aren't necessarily next few years, massive profit opportunity. But there are a lot of things in the core business around engagement and monetization which I think will be over the next few years. So I think we're trying to make sure that we get the right people working on this and that we have the right amount of investment that's just going towards what we view as a very, very large opportunity.

我認為我們所看到的部分原因是存在著許多機會。一些長期的項目是在 Meta AI 或 AI Studio 上，這些不一定是未來幾年的巨大利潤機會。但核心業務中有很多圍繞參與度和貨幣化的事情，我認為這將在未來幾年內發生。所以我認為我們正在努力確保我們有合適的人來做這件事，並且我們有適量的投資，這只是我們認為非常非常大的機會。

Doug Anmuth, JPMorgan.

道格·安姆斯，摩根大通。

Great. Thanks for taking the questions. Maybe just a follow-up first on Meta AI, Mark. I mean, helpful context certainly to understand how people are using the platform today. Maybe you can just talk more about some of that functionality over time as agents are introduced, just how you really expect use cases to expand beyond just longer and more complex queries?

偉大的。感謝您提出問題。也許只是 Meta AI 的後續行動，馬克。我的意思是，上下文肯定有助於了解人們今天如何使用該平台。也許隨著時間的推移，隨著代理的引入，您可以更多地討論其中的一些功能，您真正期望用例如何擴展到更長、更複雜的查詢之外？

And then, Susan, on CapEx, just trying to understand your comment on 4Q a little bit more. It sounds like some of the payments pushed into 4Q with the guidance suggesting $15 billion to $17 billion in CapEx in the quarter? And is that something we should think about as run rate into 2025? Thank you.

然後，蘇珊，關於資本支出，我只是想進一步了解您對第四季度的評論。聽起來有些付款被推到了第四季度，指導建議該季度的資本支出為 150 億至 170 億美元？我們是否應該考慮 2025 年的運行率？謝謝。

Yeah. I mean I can take the Meta AI question, although I'm sort of intentionally now not saying too much about the new capabilities and modalities that we're launching with Llama 4 that are coming to Meta AI. I mean I noted in the comments upfront that there -- with each major generational update, I expect that there will be large new capacities that get added. But I think that, that's just going to be -- that's partially what I'm excited about, and we'll talk more about that next year when we're ready to.

是的。我的意思是，我可以回答 Meta AI 問題，儘管我現在有意不過多談論我們與 Llama 4 一起推出的 Meta AI 的新功能和模式。我的意思是，我在前面的評論中指出，隨著每一次重大代更新，我預計都會添加大量新功能。但我認為，這就是我感到興奮的部分原因，明年準備好時我們會更多地討論這個問題。

One of the trends that I do think we're going to see though is having the models not just power Meta AI or single assistant, but across AI Studio and business agents have that grow. I mean, this year, if you look back to where we were about a year ago, we were starting to roll out Meta AI. This year, we have really so far succeeded in having that grow and having a lot of people use that. There's obviously a lot more depth of engagement and new use cases that we want to add over time.

我確實認為我們將看到的趨勢之一是，這些模型不僅為 Meta AI 或單一助理提供動力，而且在 AI Studio 和業務代理中都有這種增長。我的意思是，今年，如果你回顧大約一年前的情況，我們就開始推出元人工智慧。今年，到目前為止，我們確實成功地實現了這一增長，並讓許多人使用它。顯然，隨著時間的推移，我們希望添加更多深度的參與和新的用例。

But I'd say that we're -- today, with AI Studio and business AIs about where we were with Meta AI about a year ago. So I think in the next year, our goal around that is going to be to try to make those pretty widespread use cases, even though there's going to be a multiyear path to getting kind of the depth of usage and the business results around that we want. So there's a lot to do here, though, and I'm excited to talk about that starting earlier next year.

但我想說的是，我們今天的 AI Studio 和商業人工智慧與大約一年前的 Meta AI 的情況差不多。因此，我認為明年，我們的目標將是嘗試製作那些相當廣泛的用例，儘管需要多年的時間才能獲得使用深度和圍繞我們的業務成果。因此，這裡還有很多事情要做，我很高興能從明年初開始談論這一點。

Thanks, Doug. So your second question was about Q4 CapEx. The expected step-up in Q4 CapEx from Q3 is the part of that comes from increases in server spend and to a lesser extent, data center CapEx. But with servers, there are these timing dynamics at play that you referred to because we had these server deliveries that landed late in Q3. And so the cash doesn't go out the door basically until Q4, and that's when you'll see the CapEx show up.

謝謝，道格。所以你的第二個問題是關於第四季的資本支出。預期第四季資本支出較第三季增加的部分原因是伺服器支出的增加，以及較小程度上資料中心資本支出的增加。但對於伺服器來說，您提到的這些時間動態正在發揮作用，因為我們的伺服器交付時間是在第三季末。因此，現金基本上要到第四季才會流出，那時你就會看到資本支出出現。

And given the nature of capital expenditures, generally, there is some -- actually quite a bit of lumpiness quarter-to-quarter. So it's a little bit hard to sort of extrapolate from any particular quarter. Overall, I'd say we're growing our infrastructure investments significantly this year, and we expect significant growth again in 2025.

考慮到資本支出的性質，一般來說，每個季度都有一些——實際上相當多的波動。因此，從任何特定季度進行推斷有點困難。總體而言，我想說，今年我們的基礎設施投資將大幅成長，預計 2025 年將再次大幅成長。

Justin Post, Bank of America.

賈斯汀·波斯特，美國銀行。

Great. I think I'll ask a cost question this time. Just thinking about use of AI and employee productivity, how are you able to utilize AI internally? And are you seeing big productivity gains in your R&D group?

偉大的。我想這次我會問一個成本問題。僅考慮人工智慧的使用和員工生產力，您如何在內部利用人工智慧？您是否看到研發團隊的生產力大幅提升？

And second, I know I got to the head count one more time. But Susan, how flexible is your head count as you think about cost growth in other areas? Thanks.

其次，我知道我再次清點了人數。但是蘇珊，當您考慮其他領域的成本成長時，您的員工人數有多靈活？謝謝。

Justin, so I'll take a crack at both of those. On the use of AI and employee productivity, it's certainly something that we're very excited about. I don't know that we have anything particularly quantitative that we're sharing right now. I think there are different efficiency opportunities with AI that we've been focused on in terms of where we can reduce costs over time and generate savings through increasing internal productivity in areas like coding, for example.

賈斯汀，所以我會嘗試這兩個。關於人工智慧的使用和員工生產力，這當然是我們非常興奮的事情。我不知道我們現在有什麼特別定量的資訊可以分享。我認為人工智慧有不同的效率機會，我們一直關注這些機會，例如，我們可以隨著時間的推移降低成本，並透過提高編碼等領域的內部生產力來節省成本。

It's early, but we're seeing a lot of adoption internally of our internal assistant and coding agent, and we continue to make Llama more effective at coding, which should also make this use case increasingly valuable to developers over time.

現在還為時過早，但我們看到我們的內部助理和編碼代理在內部得到了大量採用，並且我們將繼續使Llama 在編碼方面更加有效，隨著時間的推移，這也應該使這個用例對開發人員越來越有價值。

There are also places where we hope over time that we'll be able to deploy these tools against a lot of our content moderation efforts to help make the big body of content moderation work that we undertake to help it make it more efficient and effective for us to do so.

在某些地方，我們希望隨著時間的推移，我們能夠針對我們的大量內容審核工作部署這些工具，以幫助我們進行大量的內容審核工作，幫助其提高效率和效果。

And there are lots of other places around the company where I would say we're relatively early in exploring the way that we can use LLM-based tools to make different types of work streams more efficient. So all it to say, it's something we're pretty excited about. We have lots of teams focused on it. There are sort of small opportunities and G&A functions to what we hope will be big opportunities in areas like content moderation and coding productivity over time.

我想說，公司內還有很多其他地方，我們在探索如何使用基於 LLM 的工具來提高不同類型的工作流程效率方面相對較早。總而言之，這是我們非常興奮的事情。我們有很多團隊專注於此。我們希望隨著時間的推移，在內容審核和編碼效率等領域，會有一些小機會和一般行政管理職能，而這些機會和一般行政職能將成為大機會。

On your second question about headcount. We're really -- again, we're still mid budget. So there's -- we don't have very much that is definitive to share about this at the time. But as we're evaluating where there are opportunities for us to make good investments, we really think about there is a bucket of very ROI-driven head count opportunities.

關於你的第二個問題，關於員工人數。我們真的——再說一遍，我們的預算仍然處於中等水平。因此，我們目前對此沒有太多明確的資訊可以分享。但當我們評估哪裡有機會進行良好投資時，我們確實認為存在大量由投資回報率驅動的人員數量機會。

We're very rigorous about the way we think about returns there and what the return opportunity is and how -- what we think is the likelihood of those returns and what is the aggregate incrementality of those investments and those are all things that sort of we're evaluating when we think about where to invest in the core business and where we think we can deliver sort of ROI on a near-term basis.

我們對回報的思考方式非常嚴格，回報機會是什麼，以及如何回報——我們認為這些回報的可能性是什麼，這些投資的總增量是多少，這些都是我們所關心的。核心業務上投資的地方以及我們認為可以在短期內提供投資回報率的地方時，我們正在評估。

And then at the same time, we're also assessing what the opportunities look like in some of the more medium- and long-term strategic areas of investment. And that includes our efforts in Gen AI and the infrastructure needed to support it. It includes our investments in Reality Labs. And so those are all things that we're kind of assessing in kind of a portfolio of what we could -- what we think we would do in 2025.

同時，我們也在評估一些中長期策略投資領域的機會。這包括我們在 Gen AI 方面的努力以及支持它所需的基礎設施。它包括我們對現實實驗室的投資。因此，這些都是我們正在評估的所有事情，這些事情是我們可以做的事情——我們認為我們在 2025 年會做的事情。

With a couple of thoughts, one is, again, where can we sort of build the most flexibility into the way that we're thinking about either infrastructure or head count plans. And the second is we're really focused across the company on our efficiency efforts broadly and making sure that we feel like we're continuing to push the whole company, including areas in which we expect that we will be making additional head count investments to think about how they can be more efficient in '25 than they were in '24.

有幾個想法，我們再一次思考，我們在考慮基礎設施或人數計劃時如何實現最大的靈活性。其次，我們確實在整個公司範圍內廣泛關注我們的效率工作，並確保我們感覺我們正在繼續推動整個公司，包括我們預計將進行額外人員投資的領域想想他們如何在25 年比24 年更有效率。

Ross Sandler, Barclays.

羅斯·桑德勒，巴克萊銀行。

Great. Just two quick ones, Mark. You said something along the lines of the more standardized Llama becomes, the more improvements will flow back to the core Meta business. And I guess, could you just dig in a little bit more on that? So series of Llama models are being used by lots of developers building different things in AI. I guess, how are you using that vantage point to incubate new ideas inside Meta?

偉大的。只是兩個快點，馬克。您說過，Llama 越標準化，就越多的改進將回流到核心元業務。我想，你能再深入一點嗎？因此，許多開發人員正在使用一系列 Llama 模型在人工智慧中建立不同的東西。我想，你是如何利用這個有利位置在 Meta 中孵化新想法的？

And then second question is, you mentioned on one of the podcasts after the Meta Connect that assuming scaling laws hold up, we may need hundreds of billions of compute CapEx to kind of reach our goals around Gen AI. So I guess, how quickly could you conceivably stand up that much infrastructure given some of the constraints around energy or custom ASICs or other factors? Just any more color on the speed by which we could get that amount of compute online at Meta? Thank you.

第二個問題是，您在 Meta Connect 之後的播客中提到，假設擴展定律成立，我們可能需要數千億的計算資本支出才能實現我們圍繞 Gen AI 的目標。所以我猜想，考慮到能源或客製化 ASIC 或其他因素的一些限制，您能多快建立起如此多的基礎設施？關於我們在 Meta 上在線獲得如此多計算量的速度還有更多的信息嗎？謝謝。

Yes. I can try to give some more color on this. I mean, the improvements to Llama, I'd say come in a couple of flavors. There's sort of the quality flavor and the efficiency flavor. There are a lot of researchers and independent developers who do work and because Llama is available, they do the work on Llama. And they make improvements and then they publish it and it becomes -- it's very easy for us to then incorporate that both back into Llama and into our Meta products like Meta AI or AI Studio or Business AIs because the work -- the examples that are being shown are people doing it on our stack.

是的。我可以嘗試對此提供更多色彩。我的意思是，對 Llama 的改進有幾種風格。有品質風味和效率風味之分。有很多研究人員和獨立開發人員在做工作，因為 Llama 可用，所以他們在 Llama 上進行工作。他們進行改進，然後發布它，然後我們很容易將其合併到 Llama 和我們的 Meta 產品中，例如 Meta AI 或 AI Studio 或 Business AI，因為工作 - 這些例子是所顯示的是人們在我們的堆疊上執行此操作。

Perhaps more importantly, is just the efficiency and cost. I mean this stuff is obviously very expensive. When someone figures out a way to run this better if that -- if they can run it 20% more effectively, then that will save us a huge amount of money. And that was sort of the experience that we had with open compute and part of why we are leaning so much into open source here in the first place, is that we found counterintuitively with open compute that by publishing and sharing the architectures and designs that we had for our compute, the industry standardized around it a bit more. We got some suggestions also that helped us save costs and that just ended up being really valuable for us.

也許更重要的是效率和成本。我的意思是這些東西顯然非常昂貴。當有人想出一種更好的方法來運行它時——如果他們能夠更有效地運行 20%，那麼這將為我們節省大量資金。這就是我們在開放運算方面的經驗，也是我們首先如此依賴開源的部分原因，我們發現開放運算違反直覺，透過發布和分享我們所需要的架構和設計，對於我們的計算，產業圍繞著它進行了更多標準化。我們也得到了一些建議，這些建議幫助我們節省了成本，而且最終對我們來說非常有價值。

Here, one of the big costs is chips. A lot of the infrastructure there. What we're seeing is that as Llama gets adopted more, you're seeing folks like NVIDIA and AMD optimize their chips more to run Llama specifically well, which clearly benefits us.

在這裡，最大的成本之一是晶片。那裡有很多基礎設施。我們看到的是，隨著 Llama 被更多地採用，您會看到 NVIDIA 和 AMD 等公司更多地優化他們的晶片，以更好地運行 Llama，這顯然使我們受益。

So it benefits everyone who's using Llama, but it makes our products better, right, rather than if we were just on an island building a model that no one was kind of standardizing around the industry. So that's some of what we're seeing around Llama and why I think it's good business for us to do this in an open way.

因此，它使每個使用 Llama 的人受益，但它使我們的產品變得更好，對吧，而不是我們只是在一個島上建立一個沒有人在行業中標準化的模型。這就是我們在 Llama 周圍看到的一些情況，以及為什麼我認為以開放的方式進行這件事對我們來說是一件好事。

In terms of scaling infra, I mean when I talk about our teams executing well, some of that goes towards delivering more engaging products and some of it goes towards delivering more revenue. On the infra side, it goes towards building out the expenses faster, right? So I think part of what we're seeing this year is the infra team is executing quite well.

在擴展基礎設施方面，我的意思是，當我談論我們的團隊執行得很好時，其中一些是為了提供更具吸引力的產品，其中一些是為了提供更多收入。在基礎設施方面，它有助於更快地增加支出，對嗎？所以我認為我們今年看到的部分原因是基礎設施團隊執行得相當好。

And I think that's, why over the course of the year, we've been able to build out more capacity. I mean going into the year, we had a range for what we thought we could potentially do. And we have been able to do, I think, more than, I think, we'd kind of hoped and expected at the beginning of the year. And while that reflects as higher expenses, it's actually something that I'm quite happy that the team is executing well on.

我認為這就是為什麼在這一年裡我們能夠建立更多的產能。我的意思是，進入這一年，我們有一個我們認為可以做的事情的範圍。我認為，我們所做的事情比我們年初所希望和預期的要多。雖然這反映出更高的費用，但實際上我很高興團隊執行得很好。

And I think that will -- so that execution makes me somewhat more optimistic that we're going to be able to keep on building this out at a good pace. But that's part of the whole thing. This is -- this part of the formula around kind of building out the infrastructure is maybe not what investors want to hear in the near term that we're growing that.

我認為這會——所以執行讓我更加樂觀，我們將能夠繼續以良好的速度建立這個專案。但這是整個事情的一部分。這就是——圍繞基礎設施建設的公式的這一部分可能不是投資者在短期內希望聽到的我們正在發展的基礎設施。

But I just think that the opportunities here are really big. We're going to continue investing significantly in this. And I'm proud of the teams that are doing great work to stand up a large amount of capacities that way we can deliver world-class models and world-class products.

但我只是覺得這裡的機會真的很大。我們將繼續在這方面進行大量投資。我為這些團隊所做的出色工作感到自豪，他們擁有大量的能力，這樣我們就可以提供世界一流的模型和世界一流的產品。

Ron Josey, Citi.

羅恩喬西，花旗銀行。

Great. Thanks for taking the question. Maybe a bigger picture one as well, Mark, just this time on Threads. We're now one of the core apps, on its way to becoming the next major social app and 275 million MAUs. I wanted to hear your thoughts on how this product evolves over time, specifically from a monetization perspective, but also next steps on users?

偉大的。感謝您提出問題。也許還有一個更大的圖景，馬克，只是這次在線程上。我們現在是核心應用程式之一，正在成為下一個主要社交應用程式並擁有 2.75 億月活躍用戶。我想聽聽您對該產品如何隨著時間的推移而發展的想法，特別是從貨幣化的角度來看，以及對用戶的後續步驟？

And then, Susan, with pricing up 11% in the quarter, I wanted to hear more about the pricing dynamics on the platform. I think you talked about just pricing increasing due to greater advertising demand and improved ad performance. So help us understand that a little bit more. Thank you.

然後，Susan，本季定價上漲了 11%，我想了解更多有關該平台定價動態的資訊。我認為您談到了由於廣告需求增加和廣告效果改善而導致價格上漲。所以請幫助我們更多地理解這一點。謝謝。

Thanks, Ron. So your first question was about Threads. We're making good progress there. We are continuing to launch more features and make improvements to our ranking stack. We feel very good about the continued user growth on Threads. We're bringing on an increasing number of users each quarter and depth of engagement also continues to grow. And in Q3, we saw especially strong user growth in key markets like the US, Taiwan and Japan.

謝謝，羅恩。所以你的第一個問題是關於線程的。我們在那裡取得了良好的進展。我們將繼續推出更多功能並改進我們的排名堆疊。我們對 Threads 用戶的持續成長感到非常滿意。我們每季吸引的用戶數量不斷增加，參與深度也不斷成長。在第三季度，我們看到美國、台灣和日本等關鍵市場的用戶成長尤其強勁。

And we've added a number of new features over the course of Q3, including account insights for businesses and creators to see how they're post perform, the ability to save multiple drafts continuing to deliver on our commitment to integrate Threads with fediverse and basically, we're very focused on continuing to build out the sort of functionality of Threads over time and being responsive to what users tell us that they're interested in.

我們在第三季度添加了許多新功能，包括為企業和創作者提供帳戶洞察以了解他們的後期表現，保存多個草稿的能力，繼續履行我們將 Threads 與 fediverse 集成的承諾，以及基本上，我們非常專注於隨著時間的推移繼續建立Threads 的功能，並對用戶告訴我們他們感興趣的內容做出回應。

Specifically, as it pertains to monetization, we don't expect Threads to be a meaningful driver of 2025 revenue at this time. We've been just pleased with the growth trajectory and again, are really focused on introducing features that the community finds valuable and working to deepen growth and engagement.

具體來說，由於它與貨幣化有關，我們預計 Threads 目前不會成為 2025 年收入的有意義的驅動力。我們對成長軌跡感到滿意，並且再次真正專注於引入社區認為有價值的功能，並努力深化成長和參與。

Your second question was about the increase in average price per ad. So that grew 11% year-over-year, driven by strong advertiser demand and part of that is because of better ad performance over time also. And we saw that CPM growth accelerate slightly from 10% in Q2, in part because we experienced lower impression growth in Q3.

您的第二個問題是關於每個廣告的平均價格的成長。因此，在強勁的廣告客戶需求的推動下，這一數字同比增長了 11%，部分原因是隨著時間的推移，廣告效果越來越好。我們發現每千次曝光費用 (CPM) 成長較第二季的 10% 略有加快，部分原因是第三季的展示次數成長較低。

But more broadly, as we think about pricing growth and this metric, the year-over-year growth in reported price per ad, there's a lot that goes into that, including the auction dynamics resulting from fluctuations and impression growth. And one of the things that we feel like we're very focused on is really the input metrics. What are the conversions that we are delivering to advertisers? Are they getting more value over time?

但更廣泛地說，當我們考慮定價成長和這個指標時，每個廣告報告價格的同比增長，其中涉及許多因素，包括波動和印象增長引起的拍賣動態。我們覺得我們非常關注的事情之一確實是輸入指標。我們為廣告商提供了哪些轉換？隨著時間的推移，他們會獲得更多價值嗎？

The sort of blended reported price per ad is complicated because all of those things get rolled up into it. There are so many different objectives the advertisers are optimizing for. Those objectives have very different values that make them hard to compare on an apples-to-apples basis.

每個廣告的混合報告價格很複雜，因為所有這些東西都匯總到其中。廣告商正在優化許多不同的目標。這些目標具有截然不同的價值觀，因此很難進行同類比較。

But we care a lot about conversion growth, which is growing, continues to grow faster than impression growth. And are we seeing healthy cost per action or cost per conversion trends, which we are. And as long as we continue to get better at driving conversions for advertisers that should have the effect of lifting CPMs over time, because we're delivering more conversions per impression served and that will result in higher value impressions.

但我們非常關心轉化成長，轉化成長正在成長，並且持續比印象成長更快。我們是否看到了健康的每次操作成本或每次轉換成本趨勢，而我們確實如此。只要我們繼續更好地推動廣告商的轉化，隨著時間的推移，每千次展示費用就會提高，因為我們每次展示次數都會帶來更多的轉化，這將帶來更高價值的展示次數。

Ken Gawrelski, Wells Fargo.

肯‧加維爾斯基（Ken Gawrelski），富國銀行。

Thanks for the opportunity. I appreciate that. I have a bigger picture kind of like ecosystem question here is -- when we think -- I'm curious, how far do you think we are from seeing a proliferation of third-party AI applications, specifically on the kind of the consumer side? I know we're seeing more and more on the enterprise side, agents, et cetera. But when do we see -- how far out until we see proliferation of consumer applications in the AI space?

感謝您提供的機會。我很欣賞這一點。我有一個更大的圖景，有點像生態系統問題，當我們思考時，我很好奇，你認為我們離看到第三方人工智慧應用程式的激增還有多遠，特別是在消費者方面？我知道我們在企業、代理商等方面看到的情況越來越多。但我們什麼時候才能看到人工智慧領域的消費者應用程式激增？

And how would you think about -- and how does Meta think of itself as one of those key applications in the mobile internet and the desktop internet? But now you're also seemingly an infrastructure player as well. So I'd love to hear your thoughts there. Thank you.

您會如何看待——Meta 如何將自己視為行動互聯網和桌面互聯網的關鍵應用程式之一？但現在您似乎也是基礎設施參與者。所以我很想聽聽你的想法。謝謝。

Yeah. I mean there are a lot of consumer products that we're working on. And with Llama, I would expect that app developers will be able to build a lot of really good things, too. I've touched on Meta AI and AI Studio and Business AI as a bunch, and I expect those to be important parts of the consumer experience.

是的。我的意思是我們正在開發很多消費品。透過 Llama，我希望應用程式開發人員也能夠建立許多真正好的東西。我已經談到了 Meta AI、AI Studio 和 Business AI，我希望它們成為消費者體驗的重要組成部分。

Another part that I haven't talked about quite as much yet is the opportunity for AI to help people create content that just makes people's feed experiences better. But if you look at the big trends and feeds over the history of the company, it started off as, its friends, right? So all the updates that were in there were basically from your friends' posting things. And then we went into this era where we added in creator content too.

我還沒有談到的另一部分是人工智慧有機會幫助人們創建內容，從而使人們的提要體驗變得更好。但如果你看看公司歷史上的大趨勢和動態，你會發現它一開始就是它的朋友，對嗎？所以那裡的所有更新基本上都是來自你朋友發布的內容。然後我們進入了這個時代，我們也加入了創作者內容。

We're -- now a very large percent of the content on Instagram and Facebook is not from your friends. It may not even be from people that you're following directly. It could just be recommended content from creators that we can algorithmically determine is going to be interesting and engaging and valuable to you.

現在，Instagram 和 Facebook 上的很大一部分內容都不是來自您的朋友。它甚至可能不是來自您直接關注的人。它可能只是來自創作者的推薦內容，我們可以透過演算法確定這些內容對您來說將是有趣的、有吸引力的和有價值的。

And I think we're going to add a whole new category of content, which is AI generated or AI summarized content or kind of existing content pulled together by AI in some way. And I think that, that's going to be just very exciting for Facebook and Instagram and maybe Threads or other kind of feed experiences over time.

我認為我們將添加一個全新的內容類別，這是人工智慧生成的或人工智慧總結的內容或由人工智慧以某種方式整合在一起的現有內容。我認為，隨著時間的推移，這對於 Facebook 和 Instagram 以及 Threads 或其他類型的提要體驗來說將會非常令人興奮。

It's something that we're starting to test different things around this. I don't know if we know exactly what's going to work really well yet. Some things are promising. I don't know that -- this isn't going to be a big impact on the business in '25 would be my guess.

我們開始圍繞著這個測試不同的事情。我不知道我們是否確切地知道什麼會真正有效。有些事情是有希望的。我不知道——我猜這不會對 25 年的業務產生重大影響。

But I think that there is -- I have high confidence that over the next several years, this is going to be an important trend and one of the important applications. But you're going to get that, you're going to get Meta AI, AI Studio, Business AIs and a whole lot of things that developers would do with Llama too.

但我認為，我非常有信心在接下來的幾年裡，這將成為一個重要的趨勢和重要的應用之一。但你會得到這一點，你會得到 Meta AI、AI Studio、商業 AI 以及開發人員也可以使用 Llama 做的很多事情。

Youssef Squali, Truist Securities.

優素福‧斯誇裡 (Youssef Squali)，Truist 證券公司。

Yeah, thank you very much. Mark, it appears that Meta AI now calls the web and provides conversational answers about pretty much anything including current events. And so with over [10 million] advertisers and one of the best [Reality Labs] offerings out there in your core business, Just wondering if there are any plans to start maybe testing ads on commercial queries, and move Meta AI closer to becoming a real answer engines for the billionth queries that you guys are already seeing?

是的，非常感謝。馬克，看來 Meta AI 現在可以調用網路並提供幾乎所有內容（包括時事）的對話答案。因此，擁有超過 [1000 萬] 廣告商和核心業務中最好的 [現實實驗室] 產品之一，只是想知道是否有計劃開始在商業查詢上測試廣告，並使 Meta AI 更接近成為你們已經看到的十億個查詢的真正答案引擎是什麼？

And then Susan, one of the biggest areas of pushback we get is around Reality Labs and the ongoing losses there, I think, $16 billion last year, probably north of $20 billion this year. The question is, are we getting any closer to peak losses there or alternatively, what products do you think have the biggest potential there over the next couple of years? Thanks.

然後蘇珊，我們遇到的最大阻力領域之一是現實實驗室，我認為那裡的持續損失去年為 160 億美元，今年可能超過 200 億美元。問題是，我們是否正在接近損失峰值，或者您認為哪些產品在未來幾年內具有最大潛力？謝謝。

I'm happy to take both of these, Youssef. So your first question was on plans to provide ads on commercial queries. I think I alluded to this maybe in a much earlier question. Right now, we're really focused on making Meta AI as engaging and valuable a consumer experience as possible over time. We think there will be a broadening set of queries that people use it for. And I think that the monetization opportunities will exist when -- over time as we get there. .

我很高興接受這兩件事，尤瑟夫。所以你的第一個問題是關於在商業查詢上提供廣告的計劃。我想我可能在更早的問題中提到過這一點。目前，我們真正專注於讓 Meta AI 隨著時間的推移盡可能成為有吸引力且有價值的消費者體驗。我們認為人們會使用它來進行更廣泛的查詢。我認為，隨著時間的推移，當我們到達那裡時，貨幣化機會就會存在。 。

But right now, I would say we are really focused on the consumer experience above all and this is sort of a playbook for us with products that we put out in the world where we really dial in the consumer experience before we focus on what the monetization could look like.

但現在，我想說的是，我們首先真正關注的是消費者體驗，這對我們來說是一本劇本，我們在世界各地推出的產品，在我們關注貨幣化之前，我們真正關註消費者體驗。

The second part of your question is about Reality Labs. We aren't sharing expectations beyond 2024 at this point. And as we think about the 2025 budgeting process for Reality Labs, we're certainly thinking about where we want to make sure we're putting our sort of focus and energy. We are very excited, again, about the progress that we've seen with our smart glasses as well as the sort of strong consumer interest in them. And so we're kind of thinking about where we want to make sure that we are investing appropriately behind the consumer momentum that we see.

你問題的第二部分是關於現實實驗室的。目前我們不會分享 2024 年後的預期。當我們考慮 Reality Labs 的 2025 年預算流程時，我們當然會考慮我們要確保將重點和精力放在哪裡。我們再次對智慧眼鏡所取得的進步以及消費者對它們的強烈興趣感到非常興奮。因此，我們正在考慮如何確保我們在所看到的消費者動能背後進行適當的投資。

Overall, I'd say Reality Labs is clearly one of our strategic long-term priorities, and we expect it will be an area of significant investment in -- as we build out towards the very ambitious product road map that we have there.

總的來說，我想說現實實驗室顯然是我們的長期戰略優先事項之一，我們預計它將成為一個重大投資領域——因為我們正在朝著我們在那裡制定的非常雄心勃勃的產品路線圖發展。

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。

Mark Mahaney, Evercore ISI.

馬克·馬哈尼，Evercore ISI。

Let me throw two questions, please. One, this is a year in which we've had a lot of unusual events that could be driving ad revenue, major elections in not just the US, but Europe and in India and major sports events like World Cup and I know there's some other things. Is there any, just in thinking about comps for next year and maybe in the future, anything Susan, you would call out, like how much of an impact that may have come from these one in every four or five year events? .

請容許我提出兩個問題。第一，今年我們發生了很多不尋常的事件，這些事件可能會推動廣告收入，不僅在美國，而且在歐洲和印度都有重大選舉，以及世界盃等重大體育賽事，我知道還有其他一些事物。蘇珊，在考慮明年甚至未來的比賽時，您是否會提到，例如每四年或五年的一次賽事可能會產生多大的影響？ 。

And then secondly, could you just talk a little bit more about what's ad monetization and where you are with that now? It sounds like the business messaging part is really feeding it nicely into other revenue. But help us think about where the monetization levels of WhatsApp are now versus where they can be two or three years down the road? How far away we are from optimization? Thank you.

其次，您能多談談什麼是廣告貨幣化以及您現在的情況嗎？聽起來商務訊息部分確實很好地融入了其他收入。但請幫我們思考一下 WhatsApp 目前的獲利水準與未來兩三年的獲利水準有何不同？我們距離優化還有多遠？謝謝。

Thanks, Mark. So your first question was about sort of revenue backdrop in 2024, you mentioned events that occur once every four or five years. So I imagine we're talking about the Olympics. We historically have not meaningful incremental contribution from events like the Olympics. We believe that was largely the case this year.

謝謝，馬克。所以你的第一個問題是關於 2024 年的收入背景，你提到了每四、五年發生一次的事件。所以我想我們正在談論奧運。從歷史上看，我們並沒有從奧運等活動中做出有意義的增量貢獻。我們認為今年的情況基本上是如此。

So when we think about the Q4 outlook and when we think about going into next year, we generally expect growth to continue to benefit from the healthy global advertising demand that we've seen. We think that our investments in improving our ads performance, we'll continue to accrue benefits to advertisers.

因此，當我們考慮第四季度的前景以及進入明年時，我們通常預計成長將繼續受益於我們所看到的健康的全球廣告需求。我們認為，我們在改善廣告效果方面的投資將持續為廣告商帶來利益。

But obviously, there's a big range of possible macro backdrops and that's something that we try to reflect in the range of revenue guidance that we give. So -- but I don't know that there are a lot of specific events that we would say had a material sort of idiosyncratic to 2024 type of revenue impact.

但顯然，可能存在很大範圍的宏觀背景，這也是我們試圖在我們給出的收入指導範圍中反映出來的。所以，但我不知道有很多具體事件我們會說對 2024 年的收入產生了某種特殊的實質影響。

Your second question was around WhatsApp monetization and where we are. And right now, what I would say, again, is click-to-message is really the big focus area for us here. We're seeing continued traction in this area. And in particular, growth in click-to-WhatsApp adds remain particularly strong.

你的第二個問題是關於 WhatsApp 的利潤以及我們的現狀。現在，我想說的是，點擊發送訊息確實是我們這裡的重點領域。我們看到該領域持續受到關注。特別是，點擊 WhatsApp 新增的成長仍然特別強勁。

And so we're continuing to focus both on scaling click-to-WhatsApp ads in more markets where WhatsApp has strong user adoption like Brazil, for example. It's obviously earlier in the US, but we're seeing good growth in click-to-WhatsApp ads and are continuing to invest in scaling and consumer adoption of WhatsApp in the US also, which will create bigger opportunities down the line.

因此，我們將繼續專注於在 WhatsApp 擁有強大用戶採用率的更多市場（例如巴西）擴大點擊 WhatsApp 廣告的規模。在美國顯然還早，但我們看到點擊 WhatsApp 廣告的良好成長，並繼續投資於美國 WhatsApp 的擴充功能和消費者採用，這將創造更大的機會。

So -- and then, of course, a lot of work that we're doing to make the click-to-messaging ads more effective and helping to focus towards a particular -- helping advertisers optimize, sorry, for the particular conversion events that they care about.

因此，當然，我們正在做大量工作，使點擊訊息廣告更加有效，並幫助專注於特定的目標，幫助廣告商優化，抱歉，針對特定的轉換事件他們關心。

The other element of revenue on WhatsApp, I would say, is paid messaging that continues to grow at a strong pace again this quarter, remains in fact, the primary driver of growth in our Family of Apps other revenue line, which was up 48% in Q3. And we're seeing generally a strong increase in the volume of paid conversations driven both by growth in the number of businesses adopting paid messaging as well as in the conversational volume per business.

我想說，WhatsApp 收入的另一個要素是付費訊息傳遞，該收入在本季度再次繼續強勁增長，事實上，這仍然是我們應用程式系列其他收入線增長的主要驅動力，該收入增長了 48%在第三季。我們發現，由於採用付費訊息傳遞的企業數量以及每個企業的對話量的成長，付費對話量普遍強勁成長。

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。