Meta Platforms Inc (META) 2025 Q3 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 third-quarter earnings conference call. (Operator Instructions) This call will be recorded. Thank you very much.

午安.我叫克麗斯塔，今天我將擔任你們的會議接線生。在此，我謹代表 Meta 公司歡迎各位參加第三季財報電話會議。（操作員指示）本次通話將會被錄音。非常感謝。

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

Kenneth Dorell，Meta 投資者關係總監。你可以開始了。

Thank you. Good afternoon, and welcome to Meta's third-quarter 2025 earnings conference call. Joining me today are Mark Zuckerberg, CEO; and Susan Li, CFO. Our remarks today will include forward-looking statements, which are based on assumptions as of today. Actual results may differ materially as a result of various factors, including those set forth in today's earnings press release and in our quarterly report on Form 10-Q filed with the SEC. We undertake no obligation to update any forward-looking statement.

謝謝。下午好，歡迎參加 Meta 2025 年第三季財報電話會議。今天和我一起出席的有執行長馬克·祖克柏和財務長蘇珊·李。我們今天的發言將包含一些前瞻性陳述，這些陳述是基於截至今日的假設而作出的。實際結果可能因各種因素而與預期有重大差異，包括今天發布的獲利新聞稿和我們向美國證券交易委員會提交的 10-Q 表格季度報告中所述的因素。我們不承擔更新任何前瞻性聲明的義務。

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.atmeta.com.

在本次電話會議中，我們將介紹 GAAP 財務指標和某些非 GAAP 財務指標。今天的獲利新聞稿中包含了GAAP與非GAAP指標的調節表。獲利新聞稿和隨附的投資者簡報可在我們的網站 investor.atmeta.com 上查閱。

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

現在我想把電話交給馬克。

All right. Thanks, Ken. Thanks, everyone, for joining today. We had another strong quarter with 3.5 billion people using at least one of our apps every day. Instagram had a major milestone with 3 billion monthly actives, and we're seeing good momentum across our other apps as well, including Threads which recently passed 150 million daily actives and remains on track to become the leader in its category.

好的。謝謝，肯。感謝各位今天的參與。我們又迎來了一個強勁的季度，每天有 35 億人至少使用我們的一款應用程式。Instagram 的每月活躍用戶數達到了 30 億，這是一個重要的里程碑。我們也看到其他應用程式的發展勢頭良好，包括 Threads，其每日活躍用戶數最近突破了 1.5 億，並有望成為該領域的領導者。

I am very focused on establishing Meta as the leading frontier AI lab. Building personal Superintelligence for everyone and delivering the app experiences and computing devices that will improve the lives of billions of people around the world. Our approach of advancing open source AI means that when Meta innovates, everyone benefits. Meta Superintelligence Labs is off to a strong start. I think that we've already built the lab with the highest talent density in the industry. We're heads down developing our next generation of models and products and I'm looking forward to sharing more on that front over the coming months.

我致力於將 Meta 打造成領先的前沿人工智慧實驗室。為每個人打造個人超級智能，並提供能夠改善全球數十億人生活的應用程式體驗和運算設備。我們推進開源人工智慧的方法意味著，當 Meta 進行創新時，每個人都會受益。Meta Superintelligence Labs 開局強勁。我認為我們已經建立了業界人才密度最高的實驗室。我們正在全力研發下一代車型和產品，我期待在接下來的幾個月與大家分享更多相關資訊。

We're also building what we expect to be an industry-leading amount of compute. Now there's a range of time lines for when people think that we're going to get superintelligence. Some people think that we'll get there in a few years. Others think it will be five, seven years or longer. I think that it's the right strategy to aggressively frontload building capacity so that way we're prepared for the most optimistic cases. That way, if super intelligence arrives sooner, we will be ideally positioned for a generational paradigm shift in many large opportunities.

我們也正在建立我們預計將成為業界領先的運算能力。現在人們對超級智慧何時到來有不同的預測。有些人認為我們幾年內就能實現這個目標。其他人則認為需要五年、七年甚至更長。我認為，積極提前建立產能是正確的策略，這樣我們就能為最樂觀的情況做好準備。這樣一來，如果超級智慧提前到來，我們將處於理想的位置，迎接許多重大機會帶來的世代典範轉移。

If it takes longer, then we'll use the extra compute to accelerate our core business, which continues to be able to profitably use much more compute than we've been able to throw at it. And we're seeing very high demand for additional compute, both internally and externally. And in the worst case, we were just slow building new infrastructure for some period while we grow into what we build.

如果需要更長時間，我們將利用額外的運算能力來加速我們的核心業務，而我們的核心業務仍然能夠獲利地利用比我們目前所能投入的更多的運算能力。我們看到，無論是內部還是外部，對額外運算能力的需求都非常高。最糟糕的情況是，在我們發展壯大的過程中，我們只是在一段時間內緩慢地建立新的基礎設施。

The upside is extremely high for both our existing apps and new products and businesses that are becoming possible to build. Across Facebook, Instagram, and Threads, our AI recommendation systems are delivering higher quality and more relevant content, which led to 5% more time spent on Facebook in Q3 and 10% on Threads. Video is a particular bright spot with video time spent on Instagram up more than 30% since last year. And as video continues to grow across our apps, Reels now has an annual run rate of over $50 billion.

無論是我們現有的應用程序，還是正在開發的新產品和新業務，其發展前景都非常廣闊。在 Facebook、Instagram 和 Threads 上，我們的 AI 推薦系統提供了更高品質、更相關的內容，這使得用戶在第三季度在 Facebook 上花費的時間增加了 5%，在 Threads 上花費的時間增加了 10%。影片尤其表現出色，Instagram 用戶觀看影片的時長比去年增長了 30% 以上。隨著影片在我們的應用程式中持續成長，Reels 目前的年收入已超過 500 億美元。

Improvements in our recommendation systems will also become even more leveraged as the volume of AI-created content grows. Social media has gone through two eras so far. First was when all content was from friends, family and accounts that you followed directly. The second was when we added all of the creator content.

隨著人工智慧產生的內容量不斷增長，我們推薦系統的改進也將得到更大的利用。社群媒體至今已經歷了兩個時代。最初，所有內容都來自朋友、家人和你直接關注的帳號。第二次是增加了所有創作者內容。

Now as AI makes it easier to create and remix content, we're going to add yet another huge corpus of content on top of those. Recommendation systems that understand all this content more deeply and can show you the right content to help you achieve your goals are going to be increasingly valuable.

現在，隨著人工智慧讓內容的創作和混音變得更加容易，我們將在此基礎上添加另一個龐大的內容庫。能夠更深入地理解所有這些內容，並向您展示正確的內容以幫助您實現目標的推薦系統，將變得越來越有價值。

Our ads business continues to perform very well, largely due to improvements in our AI ranking systems as well. This quarter, we saw meaningful advances from unifying different models into simpler, more general models, which drive both better performance and efficiency. And now the annual run rate going through our completely end-to-end AI-powered ad tools has passed $60 billion.

我們的廣告業務持續表現良好，這很大程度上也歸功於我們人工智慧排名系統的改進。本季度，我們看到透過將不同的模型統一為更簡單、更通用的模型而取得了顯著進展，這提高了性能和效率。現在，我們完全端到端人工智慧驅動的廣告工具的年運行率已超過 600 億美元。

And one way that I think about our company overall is that there are three giant transformers that run Facebook, Instagram and ads recommendations. We have a very strong pipeline of lots of ways to improve these models by incorporating new AI advances and capabilities. And at the same time, we were also working on combining these three major AI systems into a single unified AI system that will effectively run our family of apps and business using increasing intelligence to improve the trillions of recommendations that we'll make for people every day.

我認為我們公司整體上就像有三個巨大的變壓器在運行 Facebook、Instagram 和廣告推薦系統。我們有許多方法可以透過整合新的人工智慧技術和功能來改進這些模型，並為此制定了非常強大的進步方案。同時，我們也在努力將這三大人工智慧系統合併成一個統一的人工智慧系統，該系統將有效地運行我們的應用程式和業務，利用不斷增強的智慧來改進我們每天為人們提供的數萬億建議。

I'm also very excited about the new products that we're going to be able to build. More than 1 billion monthly actives already used Meta AI, and we see usage increase as we improve our underlying models. I'm very excited to get a frontier model into Meta AI and I think that the opportunity there is very large.

我對我們即將開發的新產品也感到非常興奮。Meta AI 的月活躍用戶已超過 10 億，隨著我們底層模型的改進，用戶數量還在不斷增長。我非常興奮能將前沿模型引入元人工智慧領域，我認為那裡的機會非常大。

The same goes for our business AI. Every day, people have more than 1 billion active Threads with business accounts across our messaging platforms, ranging from product questions to customer support. Our business AIs will enable tens of millions of businesses to scale these conversations and improve their sales at low cost and the better our models get, the better this is going to work for all businesses.

我們的企業人工智慧也是如此。每天，人們透過我們的訊息平台和企業帳戶進行超過 10 億次的活躍對話，內容涵蓋產品諮詢到客戶支援等各個方面。我們的商業人工智慧將使數千萬家企業能夠以低成本擴大這些對話的規模並提高銷售額，而且我們的模型越好，這對所有企業就越有利。

This quarter, we also launched Vibes which is the next generation of our AI creation tools and content experiences. Retention is looking good so far. And its usage keeps growing quickly week over week. I'm looking forward to ramping up the growth of Vibes over the coming months.

本季度，我們也推出了 Vibes，這是我們新一代的 AI 創作工具和內容體驗。目前來看，客戶留存率表現良好。而且它的使用量每週都在快速成長。我期待在接下來的幾個月加快 Vibes 的發展步伐。

More broadly, I think that Vibes is an example of a new content type enabled by AI, and I think that there are more opportunities to build many more novel types of content ahead as well. As our new models become ready, I'm looking forward to starting to show everyone some of the new kinds of products that we're working on.

更廣泛地說，我認為 Vibes 是人工智慧催生的一種新型內容類型的範例，我認為未來還有更多機會建構更多新穎的內容類型。隨著我們的新機型陸續準備就緒，我期待著向大家展示我們正在研發的一些新產品。

At Connect, we announced our 2025 line of AI glasses, and the response so far has been great. The new Ray-Ban Meta glasses and Oakley Meta Vanguards are both selling well. As people love the improved battery life, camera resolution, new AI capabilities and the great design. And there's our new Meta Ray-Ban display glasses, our first glasses with a high-resolution display, and the Meta Neural Band to interact with them.

在 Connect 大會上，我們發布了 2025 年的 AI 眼鏡系列，目前為止反應非常好。新款雷朋 Meta 眼鏡和 Oakley Meta Vanguard 眼鏡的銷售量都很好。人們喜歡它改進的電池續航力、相機解析度、新的人工智慧功能和出色的設計。還有我們全新的 Meta Ray-Ban 顯示眼鏡，這是我們第一款配備高解析度顯示器的眼鏡，以及用於與它們互動的 Meta Neural Band。

They sold out in almost every store within 48 hours with demo slots fully booked through the end of next month. So we're going to have to invest in increasing manufacturing and selling more of those. This is an area where we are clearly leading and have a huge opportunity ahead.

48小時內，幾乎所有門市的產品都已售罄，試聽時段也已全部預訂到下月底。所以我們需要加大投資，增加這些產品的生產和銷售。在這個領域，我們顯然處於領先地位，並且擁有巨大的發展機會。

Taking a step back, if we deliver even a fraction of the opportunity ahead for our existing apps and the new experiences that are possible, then I think that the next few years will be the most exciting period in our history. We've got a lot to do. But we're making real progress, delivering strong business results, building the talent density and infrastructure needed for the next era and leading the way on AI devices that will define the next computing platform.

退一步講，如果我們能夠為現有應用程式和可能的新體驗帶來哪怕一小部分機遇，我認為未來幾年將是我們歷史上最令人興奮的時期。我們有很多事要做。但我們正在取得真正的進步，取得了強勁的業務成果，建構了下一個時代所需的人才密度和基礎設施，並在人工智慧設備領域引領潮流，這些設備將定義下一個運算平台。

I am proud of how our teams are rising to the challenge, and I'm grateful for their dedication, hard work and creativity. As always, thank you all for being a part of this journey with us.

我為我們團隊迎接挑戰的方式感到自豪，並感謝他們的奉獻精神、辛勤工作和創造力。一如既往，感謝大家與我們一路同行。

And now here is Susan.

現在蘇珊就在這裡。

Thanks, Mark, and good afternoon, everyone. Let's begin with our segment results. All comparisons are on a year-over-year basis, unless otherwise noted. Our community across the family of apps continues to grow, and we estimate more than 3.5 billion people used at least one of our family of apps on a daily basis in September.

謝謝馬克，大家下午好。讓我們先來看看細分市場的結果。除非另有說明，所有比較均以同比為基礎。我們的應用程式家族用戶群持續成長，據估計，9 月每天至少有 35 億人使用過我們家族的一款應用程式。

Q3 total family of apps revenue was $50.8 billion, up 26% year over year. Q3 family of apps ad revenue was $50.1 billion, up 26% or 25% on a constant currency basis. In Q3, the total number of ad impressions served across our services increased 14%. Impression growth was healthy across all regions driven by engagement and user growth, particularly on video services. The average price per ad increased 10% year over year, benefiting from increased advertiser demand, largely driven by improved ad performance. This was partially offset by impression growth, particularly from lower monetizing regions and services.

第三季應用程式總收入為 508 億美元，年增 26%。第三季應用程式系列廣告營收為 501 億美元，年增 26%，以固定匯率計算成長 25%。第三季度，我們各項服務的廣告展示總次數增加了 14%。在所有地區，曝光量成長勢頭良好，這主要得益於用戶參與度和用戶成長，尤其是在視訊服務方面。平均每則廣告的價格年增了 10%，這主要得益於廣告效果的提升，進而推動了廣告主需求的成長。曝光量的成長部分抵消了這一影響，尤其是來自盈利能力較低的地區和服務的曝光量增長。

Family of apps other revenue was $690 million, up 59%, driven by WhatsApp paid messaging revenue growth as well as Meta-verified subscriptions. Within our Reality Lab segment, Q3 revenue was $470 million, up 74% year over year. The significant year-over-year growth in Q3 was partly due to retail partners stocking up on Quest headsets ahead of the holiday season. We did not have a similar benefit in the third quarter of last year since our Quest 3S headset launched in the fourth quarter of 2024. Aside from this, strong AI glasses revenue also contributed to revenue growth in Q3.

該系列應用的其他收入為 6.9 億美元，成長 59%，主要得益於 WhatsApp 付費訊息收入的成長以及 Meta 驗證訂閱。在我們的 Reality Lab 業務部門，第三季營收為 4.7 億美元，年增 74%。第三季較去年同期顯著成長的部分原因是零售合作夥伴在假日季前大量囤積 Quest 頭戴裝置。去年第三季我們並沒有獲得類似的收益，因為我們的 Quest 3S 頭戴裝置是在 2024 年第四季發布的。除此之外，人工智慧眼鏡的強勁收入也為第三季的營收成長做出了貢獻。

Moving now to our consolidated results. Q3 total revenue was $51.2 billion, up 26% or 25% on a constant currency basis. Q3 total expenses were $30.7 billion, up 32% compared to last year. Year-over-year expense growth accelerated 20 percentage points from Q2 due primarily to three factors: First, legal-related expense growth was higher than in Q2 due to charges we recorded in the third quarter as well as us lapping a period of accrual reversals in the third quarter a year ago.

接下來來看我們的綜合業績。第三季總營收為 512 億美元，年增 26%，以固定匯率計算成長 25%。第三季總支出為 307 億美元，比去年同期成長 32%。與去年同期相比，第二季支出成長加快了 20 個百分點，主要原因有三：首先，由於我們在第三季提列了費用，以及我們在去年第三季衝回了應計項目，法律相關支出成長高於第二季。

Second, employee compensation growth accelerated, driven by technical hires, particularly AI talent. Finally, growth in infrastructure costs accelerated due to increased infrastructure operating costs associated with our expanded data center fleet, depreciation on our incremental CapEx spend, and third-party cloud spend.

其次，受技術人才（尤其是人工智慧人才）招募的推動，員工薪資成長加速。最後，由於資料中心擴容帶來的基礎設施營運成本增加、新增資本支出折舊以及第三方雲端支出，基礎設施成本成長加速。

We ended Q3 with over 78,400 employees, up 8% year over year, driven by hiring in priority areas of monetization, infrastructure, Reality Labs, Meta Superintelligence Labs as well as regulation and compliance. Third-quarter operating income was $20.5 billion, representing a 40% operating margin. Q3 interest and other income was $1.1 billion, driven primarily by unrealized gains on our marketable equity securities.

第三季末，我們的員工人數超過 78,400 人，年增 8%，這主要得益於在貨幣化、基礎設施、現實實驗室、元超級智慧實驗室以及監管和合規等優先領域的招聘。第三季營業收入為 205 億美元，營業利益率為 40%。第三季利息和其他收入為 11 億美元，主要得益於我們可交易股權證券的未實現收益。

Our tax rate for the quarter was 87%, which was unfavorably impacted by a onetime, noncash reduction in deferred tax assets that we no longer anticipate using under new US tax law. Our tax rate would have been 14%, excluding this charge. Although the transition to the new US tax law resulted in an accounting charge in the third quarter, we continue to expect we will recognize significant cash tax savings for the remainder of the current year and future years under the new law, and this quarter's charge reflects the total expected impact from the transition to the new US tax law.

本季我們的稅率為 87%，這受到了一次性非現金遞延所得稅資產減少的不利影響，根據新的美國稅法，我們預計不再使用該資產。不計入這筆費用，我們的稅率本應為14%。儘管過渡到新的美國稅法導致第三季度產生了一筆會計費用，但我們仍然預計，根據新稅法，我們將在本年度剩餘時間和未來幾年確認大量的現金稅收節省，而本季度的費用反映了過渡到新的美國稅法所帶來的預期總影響。

Net income was $2.7 billion, or $1.05 per share. Excluding the onetime tax charge, our net income and EPS would have been $18.6 billion and $7.25 per share, respectively. Capital expenditures, including principal payments on finance leases were $19.4 billion. driven by investments in servers, data centers, and network infrastructure. Free cash flow was $10.6 billion. We repurchased $3.2 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders. We ended the quarter with $44.4 billion in cash and marketable securities and $28.8 billion in debt.

淨利為27億美元，即每股1.05美元。如果不計入一次性稅項支出，我們的淨收入和每股盈餘將分別為 186 億美元和 7.25 美元。資本支出（包括融資租賃的本金支付）為 194 億美元，主要投資於伺服器、資料中心和網路基礎設施。自由現金流為106億美元。我們回購了價值 32 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，我們持有現金及有價證券444億美元，負債288億美元。

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. On the first, daily actives continue to grow year over year across Facebook, Instagram and WhatsApp. We're continuing to see improvements to our products and recommendations drive incremental engagement with year-over-year growth in global time spend accelerating on both Facebook and Instagram in Q3.

現在來看看業務前景。影響我們營收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，以及隨著時間的推移將這種參與度變現的有效性。第一天，Facebook、Instagram 和 WhatsApp 的每日活躍用戶數持續較去年同期成長。我們持續看到產品改進和推薦帶來的參與度提升，第三季全球用戶在 Facebook 和 Instagram 上的使用時間較去年同期成長速度加快。

In the US, overall time spent on Facebook and Instagram grew double digits year over year, driven by continued video strength as well as healthy growth in non-video time on Facebook. The engagement gains continue to be driven by product work and ongoing improvements to our recommendation systems as we optimize our model architectures, implement advanced modeling techniques, and integrate more signals about people's interests. We also continue to focus on increasing the freshness of recommended content. On Facebook, our systems are now surfacing twice as many wheels published that day than at the start of the year.

在美國，用戶在 Facebook 和 Instagram 上花費的總時間同比增長了兩位數，這得益於視頻的持續強勁增長以及 Facebook 上非視頻內容瀏覽時間的健康增長。用戶參與度的持續提升得益於產品開發和推薦系統的不斷改進，我們不斷優化模型架構，實施先進的建模技術，並整合更多與用戶興趣相關的訊號。我們也會持續致力於提高推薦內容的新鮮度。在 Facebook 上，我們的系統現在每天顯示的輪子數量是年初的兩倍。

Looking to 2026, we expect to advance our recommendation systems across several dimensions. On Instagram, one focus is evolving our systems to surface content across a broader set of topics that cater to the diverse interest of each person. This follows a similar approach we've implemented on Facebook that has driven good results.

展望2026年，我們希望在多個方面推進我們的推薦系統。在 Instagram 上，我們的一個重點是改進系統，以便呈現涵蓋更廣泛主題的內容，從而滿足每個人的不同興趣。這與我們之前在 Facebook 上實施的、並取得了良好效果的方法類似。

We also expect to make significant progress on our longer-term ranking innovations in 2026. We're seeing promising new results from our research efforts to create foundational ranking models and expect the new model innovations we're developing as part of this will enable us to significantly scale up the amount of data and compute we use to train our recommendation models in 2026, yielding more relevant recommendations.

我們也期望在 2026 年在長期排名創新方面取得重大進展。我們在創建基礎排名模型的研究工作中看到了令人鼓舞的新成果，並期望我們正在開發的新模型創新能夠使我們能夠在 2026 年大幅增加用於訓練推薦模型的數據和計算量，從而產生更相關的推薦。

Another large focus next year is leveraging LLM to improve content understanding. We expect this is going to enable our systems to more precisely label the keywords and topics within videos and posts, which will allow our systems to both develop deeper intuition about a person's interest and retrieve the content that matches them.

明年另一個重點是利用LLM來提高對內容的理解。我們預計這將使我們的系統能夠更精確地標記影片和貼文中的關鍵字和主題，從而使我們的系統能夠更深入地了解一個人的興趣，並檢索與其匹配的內容。

Finally, we're making good progress with Meta AI and Threads. The number of people using Meta AI across our family of apps continues to grow, and we're increasingly leveraging first-party content into Meta AI results. with the majority of Meta AI's responses to Facebook Deep Dive queries in the US now showing related reels.

最後，我們在元人工智慧和線程方面取得了良好進展。使用我們旗下所有應用程式的 Meta AI 用戶數量持續成長，我們也越來越多地將第一方內容融入 Meta AI 的搜尋結果中。目前，Meta AI 對美國 Facebook Deep Dive 查詢的大部分回應都顯示了相關的 Reels 短片。

We're also seeing a lot of traction with media generation. People have created over 20 billion images using our products. And since launching Vibes within Meta AI in September, we have seen media generation in the app increased more than tenfold. On Threads, we see strong growth in both daily actives and the depth of engagement as we continue to improve recommendations. The ranking optimizations we made in Q3 alone drove a 10% increase in time spent on threats. We also continue to ship new features, including launching direct messaging in Q3, so anyone on threads can now message one another within the app.

我們也看到媒體生成領域取得了很大的進展。人們已經使用我們的產品創作了超過200億張圖片。自 9 月在 Meta AI 中推出 Vibes 以來，我們看到該應用程式中的媒體生成量增加了十倍以上。在 Threads 平台上，隨著我們不斷改進推薦功能，我們看到每日活躍用戶數和用戶參與度都實現了強勁成長。僅在第三季度，我們所做的排名優化就使威脅處理時間增加了 10%。我們也會繼續推出新功能，包括在第三季推出直接訊息功能，讓任何參與討論的人現在都可以在應用程式內互相傳送訊息。

Now to the second driver of our revenue performance, increasing monetization efficiency. The first part of this work is optimizing the level of ads within organic engagement. We continue to refine ad supply across each of our major surfaces within Facebook and Instagram to better deliver ads at the time and place they are most relevant to people.

現在來談談影響我們營收績效的第二個因素：提高貨幣化效率。這項工作的第一部分是優化自然互動中的廣告投放水準。我們將繼續優化 Facebook 和 Instagram 各個主要平台上的廣告投放，以便在最相關的時間和地點更好地向用戶投放廣告。

Longer term, we have exciting ad supply opportunities on both Threads and WhatsApp status. Ads are now running globally in feed on Threads and we're following our typical monetization playbook of optimizing the ads formats and performance before we ramp supply. Within WhatsApp status, we're continuing to gradually introduce ads and expect to complete the rollout next year.

從長遠來看，我們在 Threads 和 WhatsApp 狀態上都有令人興奮的廣告投放機會。現在，Threads 的資訊流中已在全球範圍內投放廣告，我們正遵循我們典型的盈利模式，在增加投放量之前，先優化廣告格式和成效。在 WhatsApp 狀態中，我們將繼續逐步引入廣告，並預計明年完成推廣。

The second part of increasing monetization efficiency is improving marketing performance. Advancing our ad systems remains a critical aspect of this work, and we are driving performance gains through ongoing improvements in our larger scale ads ranking models. For example, we continue to broaden the adoption of Lattice, our unified model architecture.

提高獲利效率的第二部分是提高行銷績效。推進我們的廣告系統仍然是這項工作的關鍵方面，我們正在透過不斷改進更大規模的廣告排名模型來推動效能提升。例如，我們將繼續擴大 Lattice（我們的統一模型架構）的應用範圍。

In Q3, we rolled out Lattice to app ads, which drove a nearly 3% gain in conversions for that objective. Since introducing Lattice back in 2023, along with other back-end improvements, we have now cut the number of ads ranking and recommendation models by approximately 100 as we consolidated smaller and more specialized models into larger ones that use the Lattice architecture to generalize learnings across surfaces and objectives. We continue to observe performance improvements as we combine models and expect to drive additional gains as we consolidate another 200 models over the coming years into a smaller number of highly capable models.

第三季度，我們將 Lattice 應用於應用程式廣告，使該目標的轉換率提高了近 3%。自 2023 年引入 Lattice 以來，以及其他後端改進，我們已經將廣告排名和推薦模型的數量減少了大約 100 個，因為我們將較小和更專業的模型合併為更大的模型，這些模型使用 Lattice 架構來概括跨表面和目標的學習。隨著我們不斷合併車型，我們持續觀察到性能的提升，並期望在未來幾年內將另外 200 款車型整合為數量更少、功能更強大的車型，從而獲得更大的收益。

In addition to advancing our foundational ads models, we're innovating on our run time models we use downstream of them for ads inference. For example, we began piloting a new run time ads ranking model in Q3 that leverages more compute and data than our prior models to select more relevant ads. In testing, we've seen this new model drive a more than 2% lift in conversions on Instagram.

除了推進我們的基礎廣告模型之外，我們還在創新用於下游廣告推理的運行時模型。例如，我們在第三季開始試行一種新的運行時廣告排名模型，該模型利用比我們之前的模型更多的計算和數據來選擇更相關的廣告。在測試中，我們發現這種新模式使 Instagram 上的轉換率提高了 2% 以上。

We also significantly improved performance of Andromeda in Q3 and by combining models across retrieval and early-stage ranking into a single model, driving a 14% increase in ads quality on Facebook Surfaces. Within our ads products, we're seeing continued momentum with Advantage Plus. In Q3, we completed the rollout of our streamlined campaign creation flow for Advantages lead campaigns. So now advertisers running sales app or lead campaigns have end-to-end automation turned on from the beginning, allowing our systems to look across our platform to optimize performance by automatically choosing criteria like who to show the ads to and where to show them.

第三季度，我們顯著提高了 Andromeda 的效能，透過將檢索和早期排名模型合併到單一模型中，使 Facebook Surfaces 上的廣告品質提高了 14%。在我們的廣告產品中，Advantage Plus 持續保持成長動能。第三季度，我們完成了針對 Advantages 潛在客戶開發活動的簡化版活動創建流程的推出。因此，現在運行銷售應用程式或潛在客戶活動的廣告商從一開始就啟用了端到端自動化，使我們的系統能夠掃描整個平台，透過自動選擇諸如向誰展示廣告以及在哪裡展示廣告等標準來優化效果。

The annual run rate of revenue running through our end-to-end automated solutions has now reached $60 billion following the implementation of the new streamlined creation flow, as we continue to see more advertisers leverage the performance benefits of our solutions. Within our Advantage Plus Creative Suite, the number of advertisers using at least one of our video generation features was up 20% versus the prior quarter as adoption of image animation and video expansion continues to scale.

隨著新的精簡創建流程的實施，我們端到端自動化解決方案的年收入運行率已達到 600 億美元，我們看到越來越多的廣告商利用我們解決方案的效能優勢。在我們的 Advantage Plus 創意套件中，使用我們至少一項影片生成功能的廣告客戶數量比上一季增長了 20%，圖像動畫和視訊擴充的採用率持續擴大。

We've also added more generative AI features to make it easier for advertisers to optimize their ad creatives and drive increased performance. In Q3, we introduced AI-generated music, so advertisers can have music generated for their ad that aligns with the tone and message of the creative. Finally, business messaging remains a significant opportunity for us. We're seeing strong growth across our portfolio of solutions, including with click-to-WhatsApp ads, which grew revenue 60% year over year in Q3.

我們也增加了更多生成式人工智慧功能，讓廣告主更容易優化廣告創意並提高廣告成效。第三季度，我們推出了人工智慧生成的音樂，廣告主可以為他們的廣告產生與創意基調和訊息相符的音樂。最後，商業訊息傳遞對我們來說仍然是一個重要的機會。我們看到，我們的解決方案組合均實現了強勁成長，包括點擊到 WhatsApp 廣告，第三季營收年增了 60%。

We're also making good progress on our business AI efforts where we've been focused on building a turnkey AI that helps businesses generate leads and drive sales. We've been opening access in recent months to more businesses within our initial test markets, the Philippines and Mexico. And I've seen strong usage with millions of conversations between people and business AIs taking place since July.

我們在商業人工智慧方面也取得了良好進展，我們一直致力於建立一個交鑰匙人工智慧系統，幫助企業產生潛在客戶並促進銷售。近幾個月來，我們已逐步向最初的測試市場（菲律賓和墨西哥）中的更多企業開放了准入權限。我看到自 7 月以來，人們與企業人工智慧之間已經進行了數百萬次對話，使用率非常高。

This month, we expanded availability within WhatsApp and Messenger to all eligible businesses in Mexico and the Philippines, respectively. In the US, we're also starting to roll out the ability for merchants to add their business AIs to their website so we can support the full-sale funnel from ad to purchase.

本月，我們將 WhatsApp 和 Messenger 的服務範圍分別擴大到墨西哥和菲律賓所有符合資格的企業。在美國，我們也開始逐步推出商家將他們的業務人工智慧加入其網站的功能，以便我們能夠支援從廣告到購買的完整銷售流程。

Next, I would like to discuss our approach to capital allocation. Our primary focus is deploying capital to support the company's highest order priorities, including developing leading AI products models and business solutions. As we make significant investments in infrastructure to support this work, we are focused on preserving maximum long-term flexibility to ensure we can meet our future capacity needs while also being able to respond to how the market develops in the years ahead.

接下來，我想談談我們的資本配置方法。我們的主要重點是部署資金以支援公司最重要的優先事項，包括開發領先的人工智慧產品模型和業務解決方案。為了支持這項工作，我們對基礎設施進行了大量投資，同時我們也致力於保持最大的長期靈活性，以確保我們能夠滿足未來的產能需求，並能夠應對未來幾年市場的發展。

We're doing so in several ways, including staging data center sites, so we can spring up capacity quickly in future years as we need it as well as establishing strategic partnerships that give us option value for future compute needs. The strong financial position and cash generation of our business enable us to make these investments while also accessing additional pools of cost-efficient capital.

我們正在透過多種方式來實現這一目標，包括建立資料中心站點，以便在未來幾年根據需要快速增加容量，以及建立策略合作夥伴關係，從而為未來的運算需求提供選擇價值。我們公司雄厚的財務實力和現金流使我們能夠進行這些投資，同時也能獲得其他成本效益高的資金來源。

Moving to our financial outlook. We expect fourth-quarter 2025 total revenue to be in the range of $56 million to $59 billion. Our guidance assumes foreign currency is an approximately 1% tailwind to year-over-year total revenue growth based on current exchange rates. Our outlook reflects an expectation for continued strong ad revenue growth partially offset by lower year-over-year Reality Labs revenue in Q4. The anticipated reduction in Reality Labs revenue is due to us lapping the introduction of Quest 3S in Q4 of last year, as well as retail partners procuring Quest headsets during Q3 of this year to prepare for the holiday season, which were recorded as revenue in the third quarter.

接下來談談我們的財務展望。我們預計 2025 年第四季總營收將在 5,600 萬美元至 590 億美元之間。根據目前的匯率，我們的預測認為外匯因素將對年比總收入成長起到約 1% 的推動作用。我們的展望反映了對廣告收入持續強勁成長的預期，但第四季 Reality Labs 營收年減將部分抵銷這一成長。Reality Labs 收入預計減少的原因是，我們在去年第四季度錯過了 Quest 3S 的上市時間，以及零售合作夥伴在今年第三季度採購 Quest 頭顯以備戰假日季，這些採購收入已計入第三季度。

Turning to the expense and CapEx outlooks. I'll first start with 2025 before providing some commentary on our planning for 2026. We expect full-year 2025 total expenses to be in the range of $116 million to $118 billion, updated from our prior outlook of $114 million to $118 billion and reflecting a growth rate of 22% to 24% year over year. We currently expect 2025 capital expenditures, including principal payments on finance leases to be in the range of $70 million to $72 billion, increased from our prior outlook of $66 billion to $72 billion.

接下來談談費用和資本支出前景。我先從 2025 年說起，然後再對我們 2026 年的計畫做一些評論。我們預計 2025 年全年總支出將在 1.16 億美元至 1,180 億美元之間，較我們先前的 1.14 億美元至 1,180 億美元的預期有所調整，年增 22% 至 24%。我們目前預計 2025 年資本支出（包括融資租賃的本金支付）將在 7,000 萬美元至 720 億美元之間，高於我們先前預測的 660 億美元至 720 億美元。

On to tax. Absent any changes to our tax landscape, we expect our fourth-quarter 2025 tax rate to be 12% to 15%.

接下來是稅務問題。在稅收環境沒有變化的情況下，我們預計 2025 年第四季的稅率為 12% 至 15%。

Turning now to 2026. We are at an exciting point for our company. where we have continued runway to improve our core services today as well as the opportunity to build new AI-powered experiences and services that will transform how people engage with our products in the future. We expect the set of investments we're making within our ads and organic engagement initiatives next year will enable us to continue to deliver strong revenue growth in 2026. while our progress on AI models and products will position us to capitalize on new revenue opportunities in the years to come.

現在展望2026年。我們公司正處於一個令人興奮的發展階段。我們既有持續的資金支援來改善我們目前的核心服務，也有機會建立全新的人工智慧驅動體驗和服務，這將改變人們未來與我們產品互動的方式。我們預計明年在廣告和自然互動計劃方面的一系列投資將使我們能夠在 2026 年繼續實現強勁的收入增長，同時我們在人工智慧模型和產品方面的進展將使我們能夠在未來幾年抓住新的收入機會。

A central requirement to realizing these opportunities is infrastructure capacity. As we have begun to plan for next year, it's become clear that our compute needs have continued to expand meaningfully, including versus our own expectations last quarter. We are still working through our capacity plans for next year, but we expect to invest aggressively to meet these needs, both by building our own infrastructure and contracting with third-party cloud providers.

實現這些機會的核心要求是基礎設施能力。隨著我們開始為明年做計劃，很明顯，我們的計算需求持續顯著增長，甚至超過了我們上個季度的預期。我們仍在製定明年的容量計劃，但我們預計將大力投資以滿足這些需求，包括建立我們自己的基礎設施和與第三方雲端供應商簽訂合約。

We anticipate this will provide further upward pressure on our CapEx and expense plans next year. As a result, our current expectation is that CapEx dollar growth will be notably larger in 2026 than 2025. We also anticipate total expenses will grow at a significantly faster percentage rate in 2026 than 2025, with growth primarily driven by infrastructure costs, including incremental cloud expenses and depreciation.

我們預計這將進一步推高我們明年的資本支出和費用計劃。因此，我們目前的預期是，2026 年資本支出美元成長將明顯高於 2025 年。我們也預計，2026 年總支出成長率將比 2025 年快得多，成長主要由基礎設施成本驅動，包括新增雲端支出和折舊。

Employee compensation costs will be the second largest contributor to growth. as we recognize a full year of compensation for employees hired throughout 2025, particularly AI talent and add technical talent in priority areas. Finally, we continue to monitor active legal and regulatory matters, including the increasing headwinds in the EU and the US that could significantly impact our business and financial results.

員工薪酬成本將是成長的第二大因素，因為我們將為2025年全年招募的員工支付全年薪酬，特別是人工智慧人才，並在重點領域增加技術人才。最後，我們將繼續關注活躍的法律和監管事務，包括歐盟和美國日益增長的不利因素，這些因素可能會對我們的業務和財務表現產生重大影響。

For example, in the EU, we continue to engage constructively with the European Commission on our less personalized ads offering. However, we cannot rule out the commission imposing further changes to that offering that could have a significant negative impact on our European revenue as early as this quarter. In the US, a number of youth-related trials are scheduled for 2026 and may ultimately result in a material loss.

例如，在歐盟，我們繼續與歐盟委員會就我們個人化程度較低的廣告服務進行建設性溝通。但是，我們不能排除歐盟委員會對該產品進行進一步修改的可能性，這最早可能在本季度就會對我們的歐洲收入產生重大負面影響。在美國，2026 年將進行多起與青少年有關的審判，這些審判最終可能導致重大損失。

In closing, this was another good quarter for our business. We have an exciting set of opportunities to continue improving our core business while delivering innovative new experiences and services for the people and businesses using our products in the years to come.

總之，這又是我們公司業績表現不錯的一個季度。未來幾年，我們將迎來一系列令人興奮的機遇，在不斷改進核心業務的同時，為使用我們產品的個人和企業提供創新的新體驗和服務。

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)

（操作說明）

Brian Nowak, Morgan Stanley.

Brian Nowak，摩根士丹利。

I have two for Susan. The first one, Susan. So the pipeline for core improvements to come in '26 with models and ad ranking models and more types of compute seems very exciting and the infrastructure build team sizable behind that. So can you help us a little understand some of the early quantifiable signals you're seeing on AB tests from some of these improvements to come that sort of make you most excited and give you confidence you're going to get ROIC from all this CapEx? That's the first one.

我有兩個給蘇珊。第一個，蘇珊。因此，2026 年即將推出的核心改進方案，包括模型、廣告排名模型以及更多類型的計算，看起來非常令人興奮，而且背後還有一支規模龐大的基礎設施建設團隊。那麼，您能否幫助我們理解一下，您在 A/B 測試中看到的一些早期可量化的信號，這些信號來自即將進行的改進，是什麼讓您最興奮，並讓您相信所有這些資本支出都能獲得投資回報率？這是第一個。

Second one is a little faster. How large is the Reality Labs revenue headwind in the 4Q guidance?

第二個速度稍快一些。Reality Labs第四季營收預期面臨的阻力有多大？

Thanks, Brian, for the question. I think your first question had a couple of parts to it. So I'm going to try to disaggregate those parts, and let me know if this addresses what you're getting to. I will say that the growth in 2026 CapEx relative to 2025 comes from growth in each of the core areas: MSL, core AI, as well as non-AI spend. So all of those areas are growing, but the MSL AI needs are growing the most.

謝謝你的提問，布萊恩。我認為你的第一個問題包含幾個部分。所以我會試著把這些部分拆解開來，看看這樣是否能解決你所遇到的問題。我要說的是，2026 年資本支出相對於 2025 年的成長來自各個核心領域的成長：MSL、核心 AI 以及非 AI 支出。所以所有這些領域都在發展，但MSL AI的需求成長最為顯著。

In terms of the core AI pipeline, I think we talked about last year when we were going into the 2025 budget process, we had a road map of resource investments across both head count and compute that we thought would pay off in 2026. And it's really a very broad range of sort of different ads ranking and performance efforts. And we're continuing to see that those have paid off through the course of the year.

就核心人工智慧管道而言，我認為我們在去年進入 2025 年預算流程時討論過，我們制定了一項資源投資路線圖，涵蓋人員配備和計算能力，我們認為這將在 2026 年獲得回報。而且，這實際上涵蓋了非常廣泛的各種不同的廣告排名和效果優化措施。我們持續看到，這些努力在一年中都取得了成效。

There is a long list of specific efforts, but one of the measures that we look at to monitor this is how are we driving ad performance? How are conversions growing? Conversions is a complex metric for us because advertisers optimize for so many different conversions on different values. But when we control for that and look at value-added conversion rates, we're seeing very strong year-over-year growth and conversion -- weighted conversions continue to grow faster than impressions.

我們採取的具體措施有很多，但我們用來監控這些措施的其中一項指標是：我們如何提升廣告成效？轉換率是如何成長的？轉換次數對我們來說是一個複雜的指標，因為廣告主會針對許多不同的轉換次數和不同的數值進行最佳化。但當我們控制住這些因素，並查看增值轉換率時，我們發現年比成長和轉換率非常強勁——加權轉換率的成長速度持續超過展示次數的成長速度。

We also talked about some of the new model architecture over the course of the year, and the degree to which the new model architecture is enabling us also to take advantage of having more data and more compute to drive ads performance. So we expect that that's going to be a continued story in 2026. We are, in fact, at the beginning of our 2026 budgeting process now, and we see a similar list of revenue investments. that we're excited to be able to invest in. And so we think that, that's going to be a big part of our ability to continue to drive strong revenue performance throughout the year.

我們也討論了一些新的模型架構，以及新的模型架構在多大程度上使我們能夠利用更多的資料和運算能力來提升廣告效果。因此我們預計，這種情況在 2026 年還會持續下去。事實上，我們現在正處於2026年預算編制過程的初期，我們看到了一份類似的收入投資清單，我們很高興能夠對這些投資進行投資。因此我們認為，這將是我們全年持續保持強勁營收表現的關鍵因素。

On your second question, which is the Reality Labs revenue headwind. I don't think we have quantified the exact size of that. We expect that Q4 Reality Labs revenue will be lower than last year for a couple of reasons that I alluded to, the biggest factor is we're lapping the introduction of Quest 3S in Q4 of last year, and we don't have a new headset in the market this year. We also recorded all of our holiday-related Quest 3S sales in Q4 '24, since the headset was launched in October '24.

關於你的第二個問題，也就是 Reality Labs 的收入所面臨的逆風。我認為我們還沒有量化出它的確切規模。由於我之前提到的幾個原因，我們預計 Reality Labs 第四季的營收將低於去年同期，其中最大的因素是我們錯過了去年第四季 Quest 3S 的上市時間，而今年我們還沒有新的頭顯產品上市。由於 Quest 3S 頭顯於 2024 年 10 月發布，因此我們所有與假期相關的 Quest 3S 銷售額都記錄在 2024 年第四季。

This year, we're recognizing some of those Quest 3S sales in Q3 as retail partners have procured Quest headsets in advance of the holiday season. We're still expecting significant year-over-year growth in AI Glasses revenue in Q4 as we benefit from strong demand for the recent products that we've introduced, but that is more than offset by the headwinds to the Quest headsets.

今年，我們將在第三季確認部分 Quest 3S 的銷售額，因為零售合作夥伴已提前採購了 Quest 頭顯，以迎接假期季節的到來。我們仍然預計第四季度 AI 眼鏡收入將實現顯著的同比增長，因為我們受益於近期推出的產品的強勁需求，但這被 Quest 頭顯面臨的不利因素完全抵消了。

Doug Anmuth, JPMorgan.

道格·安穆斯，摩根大通。

I appreciate the strategy to front-load capacity for Superintelligence. Can you just talk about your thought process and kind of triangulating the CapEx dollar growth and the significantly faster expense growth next year with core growth in the business and then the impact on earnings and free cash flow? And do you have targets that we should be thinking about for cash on hand or net cash overall?

我讚賞這種提前部署超級智慧能力的策略。您能否談談您的思考過程，以及如何將資本支出成長和明年業務核心成長帶來的更快支出成長進行三角分析，並分析這對收益和自由現金流的影響？那麼，你們有沒有我們應該考慮的現金儲備或淨現金目標呢？

Thanks, Doug. We're, right now, I would say, in the process of -- relatively early, actually, still in the process of putting together our budget for 2026. And it is on the capacity side, a particularly dynamic process. We're certainly seeing that we wish we had more capacity today than we do. We would be able to put it towards good use, certainly, not only with the MSL team appreciate having more capacity, but we'd be able to put it towards good and ROI-positive use in the core business as well.

謝謝，道格。目前，我想說，我們正處於——實際上還處於相對較早的階段——仍在製定 2026 年預算的過程中。而且，產能方面是一個特別動態的過程。我們當然希望我們今天的產能能更大一些。我們當然可以好好利用它，不僅 MSL 團隊會樂於擁有更多產能，而且我們還可以將其用於核心業務，從而獲得良好的投資回報率。

So we're really trying to plan ahead not only to ensure that we have the capacity we need in 2026, but also to give ourselves the sort of flexibility and option value to have the capacity that we think we could need in '27 and '28. So that said, there are lots of moving pieces in the budget. It's not baked yet. It's still sort of in the process of coming together. We don't have specific targets to share, but we do feel like our strategic priority is really making sure that we have the compute that we need to be well positioned to succeed at AI, and that's sort of the foremost priority as we're putting together the budget.

因此，我們正在努力提前規劃，不僅是為了確保我們在 2026 年擁有所需的產能，也是為了給自己留出一定的靈活性和選擇餘地，以便在 2027 年和 2028 年擁有我們認為可能需要的產能。也就是說，預算中有很多變數。還沒烤好。它還在逐步成型的過程中。我們沒有具體的目標可以分享，但我們確實認為我們的策略重點是確保我們擁有足夠的運算能力，以便在人工智慧領域取得成功，這可以說是我們制定預算時的首要任務。

Yes. I mean, I'll add a few thoughts on this, too, although I mean, as Susan said, we're still working through the actual budget, and I think we'll typically have more to share on that early next year. But to date, we keep on seeing this pattern where we build some amount of infrastructure to what we think is an aggressive assumption. And then we keep on having more demand to be able to use more compute, especially in the core business in ways that we think would be quite profitable, then we end up having compute for.

是的。我也會補充一些想法，不過正如蘇珊所說，我們仍在製定實際預算，我想我們通常會在明年初分享更多相關資訊。但到目前為止，我們不斷看到這樣的模式：我們根據我們認為過於樂觀的假設，建構一定數量的基礎設施。然後，我們對使用更多運算能力的需求不斷增長，尤其是在核心業務中，我們認為這將非常有利可圖，最終我們擁有了足夠的運算能力。

So I think that that suggests that being able to make a significantly larger investment here is very likely to be a profitable thing over some period because if the primary use of it is going to be to accelerate the AI research and the new AI work that we're doing and how that relates to both the core business and new products. But any compute that we don't need for that we feel pretty good that we're going to be able to absorb a very large amount of that to just convert into more intelligence and better recommendations in our family of apps and ads in a profitable way.

所以我認為，這表明，如果主要用途是加速人工智慧研究和我們正在進行的新人工智慧工作，以及這些工作與核心業務和新產品之間的關係，那麼在這裡進行更大幅度的投資很可能在一段時間內是有利可圖的。但對於我們不需要用於此的任何計算，我們很有信心能夠吸收其中很大一部分，並以盈利的方式將其轉化為我們應用程式和廣告系列的更多智慧和更好的推薦。

Now, I mean, it's, of course, possible to overshoot that, right? And if we do, I mean, this is what I mentioned in my comments, then we see that there's just a lot of demand for other new things that would build internally, externally. Like almost every week, people come to us from outside the company asking us to stand up an API service, or ask if we have different compute that they could get from us. And we haven't done that yet. But obviously, if you got to a point where you ever built, you could have that as an option.

當然，我的意思是，這樣做當然有可能過猶不及，對吧？如果我們這樣做，我的意思是，正如我在評論中提到的，那麼我們就會看到，無論是在內部還是外部，對其他新事物都有很多需求。幾乎每週都有公司外部的人來找我們，要求我們建立 API 服務，或詢問我們是否可以提供他們可以從我們這裡獲得的不同運算能力。我們還沒有做到這一點。但很顯然，如果你到了要建造房屋的地步，這也可以作為一種選擇。

And then the kind of the very worst case would be that we effectively have just prebuilt for a couple of years, in which case, of course, there would be some loss and depreciation, but we'd grow into that and use it over time. So my view on this is that rather than continuing to be constrained on CapEx and feeling in the core business like we have significant investments that we could make that we're not able to make that would be profitable, but the right thing to do is to try to accelerate this to make sure that we have the compute that we need, both for the AI research and new things that we're doing and to try to get to a different state on our compute stance on the core business.

最糟糕的情況是我們實際上只是預先建造了幾年的設備，在這種情況下，當然會有一些損失和折舊，但隨著時間的推移，我們會逐漸適應並使用它。因此，我的看法是，與其繼續受限於資本支出，感覺核心業務中我們有一些可以進行但無法進行的、有利可圖的重大投資，不如嘗試加快這一進程，以確保我們擁有所需的計算能力，無論是用於人工智能研究還是我們正在進行的新項目，並努力使我們在核心業務的計算能力方面達到不同的狀態。

So that's kind of how I'm thinking about that, overall. Of course, there's a lot of operational constraints too on what one can build, right? So we're basically trying to work through this all, and I think we'll have more to share in the coming months and over the course of next year. But I can think there's just a huge, huge amount of opportunities ahead here.

總的來說，我的想法大概就是這樣。當然，在建造方面也有很多營運方面的限制，對吧？所以我們正在努力解決所有這些問題，我認為在接下來的幾個月和明年，我們會分享更多。但我認為這裡蘊藏著巨大的機會。

Eric Sheridan, Goldman Sachs.

艾瑞克‧謝裡丹，高盛集團。

Mark, I wanted to reflect on some of your comments with respect to scaling towards Superintelligence and bringing it back to consumer AI. Maybe reflect a little bit on the signals you've gotten on the way consumers across family of apps interact with Meta AI today? And how you think about scaling and exiting models from the Superintelligence effort might change the utility and behavior around Meta AI in the years ahead.

馬克，我想就你關於擴展超級智慧並將其帶回消費級人工智慧的一些評論做一些反思。或許可以稍微反思一下，你從使用者在使用 Meta AI 系列應用程式時的反應中獲得了哪些資訊？你如何看待超級智慧計畫中模型的擴展和退出，可能會在未來幾年改變元人工智慧的用途和行為。

Yes. I mean A lot of people use Meta AI today. I mean, as I said in my comments upfront, there's more than 1 billion people who use it on a monthly basis. And what we see is that as we improve the quality of the model, primarily for post-training Lama at this point. We are -- we continue to see improvements in usage. So our view is that when we get the new models that we're building MSL in there and get like truly frontier models with novel capabilities that you don't have in other places, then I think that this is just a massive latent opportunity, right?

是的。我的意思是，現在很多人都在使用元人工智慧。我的意思是，正如我一開始所說，每月有超過 10 億人使用它。我們看到，隨著我們提高模型的質量，尤其是在訓練後的 Lama 模型方面。我們看到使用情況持續改善。因此，我們的觀點是，當我們把我們正在建造的MSL新模型放進去，得到像真正具有其他地方沒有的新穎功能的尖端模型時，我認為這就是一個巨大的潛在機會，對吧？

We know -- I mean I would guess that Meta I think has the best track record of any company out there of taking a new product that people love, and getting it to billions of people in terms of usage. So I think that the ability to plug in leading models is going to, I would predict lead, to a very large amount of use of these things over the coming years. So I'm very excited about that in terms of new products. It's not just Meta AI is an assistant. I think that there are going to be all kinds of new products around different content formats, and we're starting to see that with video and content creation, but I think there's going to be a lot more like that, that I'm quite excited about.

我們知道——我的意思是，我猜 Meta 在所有公司中擁有最好的業績記錄，它能夠將一款深受人們喜愛的新產品推廣到數十億用戶手中。所以我認為，能夠連接領先模型將會，我預測，在未來幾年裡，這些技術將會得到非常廣泛的應用。所以，我對新產品方面感到非常興奮。Meta AI 不僅僅是一個助手。我認為未來會湧現出各種圍繞著不同內容形式的新產品，我們已經開始在影片和內容創作領域看到這種趨勢，但我認為未來還會有更多類似的產品出現，對此我感到非常興奮。

And then there are the business versions of all these two, like business AI. And then that's, of course, one part of the story is the new things that will be possible to build. And then the other part is how more intelligent models are just going to improve the core business. And improve the recommendations that we make across the family of apps and improve the recommendations and advertising. And I think there's just a -- as we've shown, there's sort of this very large amount of headroom and the opportunity there keeps growing as we as we are improving and optimizing the AI there.

此外，還有這兩者的商業版本，例如商業人工智慧。當然，故事的一部分是未來可以建造的新事物。另一方面，更聰明的模型將如何改善核心業務？並改進我們所有應用程式的推薦，以及改進推薦和廣告。我認為正如我們所展示的，人工智慧領域還有很大的提升空間，隨著我們不斷改進和優化人工智慧，這個領域的機會也在不斷增長。

And I think that, that really shows no sign of being near the end. I think that there's quite a bit more to do there. And like I said in response to the last question, we are sort of perennially operating the family of apps and ads business and a compute-starved state at this point, which is, on the one hand, sort of an odd thing to say, given the compute that we built up. But we really are taking a lot of the resources and using them to advance future things that we're doing, and we think that there's a lot more compute that we could put towards these that would just unlock a huge amount of opportunity in the core business as well.

我認為這絲毫沒有接近尾聲的跡象。我認為那裡還有很多事情要做。正如我在回答上一個問題時所說，我們一直都在經營應用程式和廣告業務，目前處於計算資源匱乏的狀態，考慮到我們已經累積的計算資源，這在某種程度上來說有點奇怪。但我們確實正在利用大量資源來推進我們正在進行的未來項目，我們認為可以投入更多運算資源，這將為核心業務釋放巨大的機會。

Mark Shmulik, Bernstein.

馬克舒穆利克，伯恩斯坦。

Susan, as you think about the visibility into kind of the runway next year of continued add performance and engagement improvements, how do you think about kind of the scale of those improvements versus kind of the progress we've seen over the last two years?

蘇珊，當你思考明年能否繼續提升廣告成效和用戶參與度時，你如何看待這些改進的規模與我們在過去兩年中看到的進展相比如何？

And then, Mark, as you think about kind of the timing of some of these newer efforts coming out of Superintelligence Labs, is us anchoring to kind of an updated frontier model launch sometime next year like the right way for us to think about it? Or should we be looking at kind of progress from new products you're excited to see ship like wise?

那麼，馬克，當你思考超級智慧實驗室推出的一些新舉措的時機時，我們是否應該將明年某個時候推出更新的前沿模型作為重點，這是否是正確的思考方式？或者，我們應該關註一下您同樣期待上市的新產品所取得的進展？

Thanks, Mark. So on the sort of adds improvement side, some of the innovations that we have been launching actually involve sort of improving our larger-scale models. So we don't use our larger model architectures like for inference because their size and complexity would make it too cost prohibitive. The way that we drive performance from those models is by using them to transfer knowledge to smaller lightweight models that are used at run time. And then in addition to the foundation model work, we are working on advancing our inference models by developing new techniques and architectures that then allow us to scale up compute and complexity in an ROI-positive way.

謝謝你，馬克。因此，在改進方面，我們推出的一些創新實際上涉及改進我們的大規模模型。因此，我們不使用較大的模型架構進行推理，因為它們的規模和複雜性會導致成本過高。我們提高這些模型性能的方法是利用它們將知識傳遞給運行時使用的更小、更輕量級的模型。此外，除了基礎模型工作之外，我們還致力於透過開發新技術和架構來推進我們的推理模型，以投資回報率為正的方式擴展運算能力和複雜性。

So in general, we obviously, have a very large base of advertisers. There's a lot of demand liquidity in the system and even small-scale improvements that we are able to make in terms of driving basis point improvements in the performance of ads or single-digit increases in conversions relative to impressions in a given quarter off of a large base. I mean that we're really able to continue to grow the absolute dollars of revenue growth in a pretty meaningful way.

所以總的來說，我們顯然擁有非常龐大的廣告客戶群。系統中存在大量的需求流動性，即使是小規模的改進，我們也能夠在較大的基數上，推動廣告效果提高基點，或者在特定季度內轉換率相對於展示次數實現個位數增長。我的意思是，我們確實能夠以相當有意義的方式繼續實現營收絕對值的成長。

Justin Post, Bank of America.

賈斯汀·波斯特，美國銀行。

Justin, just give us one second. I think there was a second Mark's question that we just want to get to on MSL.

賈斯汀，請稍等一下。我認為馬克還有第二個問題，我們想在 MSL 上討論一下。

Yes. I mean, I'll keep it quick. I mean I don't think we have any specific timing to announce certainly on the models or products, but I expect that you will see both. We expect to build novel models and novel products, and I'm excited to share more when we have it.

是的。我的意思是，我會長話短說。我的意思是，我認為我們目前還沒有具體的發佈時間，可以公佈具體的型號或產品，但我預計你們會看到這兩款產品。我們期待打造全新的車款和產品，一旦有了更多消息，我會非常興奮地與大家分享。

So Mark, you mentioned the prior two constant cycles, and obviously, you've been able to generate very attractive margins on them. As we get into the AI cycle, obviously, some concerns on the investment. But can you talk a little bit about how you're thinking about tools that could be coming out for users? I know there's some new competition.

馬克，你提到了前兩個週期，顯然，你已經從中獲得了非常可觀的利潤。隨著我們進入人工智慧週期，很顯然，投資方面會出現一些問題。您能否談談您正在考慮推出哪些面向使用者的工具？我知道現在出現了一些新的競爭對手。

And then secondly, how do you think about margins in this content cycle? Any reason to think they would be different versus prior cycles?

其次，您如何看待這個內容週期中的利潤空間？有什麼理由認為它們會與之前的周期有所不同嗎？

I think it's too early to really understand what the margins are going to be for the new products that we build. I mean, I think certainly, every each product has somewhat different characteristics. And I think we'll kind of understand how that goes over time.

我認為現在要真正了解我們開發的新產品的利潤率還為時過早。我的意思是，我認為當然，每種產品都有其獨特的特點。我想隨著時間的推移，我們會慢慢明白這是怎麼回事。

I mean, my general goal is to build a business that maximizes value for the people who use our products and maximizes profitability, not margin. So I think we'll kind of just try to build the best things that we can and try to deliver the most value that we can for most people.

我的意思是，我的總體目標是打造一個能夠為使用我們產品的人創造最大價值並實現最大盈利能力（而不是利潤率）的企業。所以我覺得我們會盡力打造最好的產品，並努力為大多數人提供最大的價值。

Ross Sandler, Barclays.

羅斯·桑德勒，巴克萊銀行。

Great. Mark, some of the goals for competing AI labs are around achieving AGI or these other milestones that are kind of like out there and a little esoteric. How are you setting up your new team in terms of achieving those types of goals versus products that can generate revenue from Meta kind of right out of the gate? And is the goal that you had articulated to us previously around giving billions of people kind of a personal AI to use still the direction of travel that you see? Or is there other things like kind of the Vibes or Sora angle that you think are potentially important? How should we think about like the overall direction?

偉大的。馬克，一些人工智慧實驗室的競爭目標是實現通用人工智慧（AGI）或其他一些比較遙遠、有點深奧的里程碑。你們的新團隊在實現這些目標方面，是如何安排的？是專注於那些能夠立即從 Meta 平台產生收入的產品嗎？您之前向我們闡述的目標，為數十億人提供某種個人人工智慧，現在仍然是您認為的發展方向嗎？或者，你認為還有其他方面，像是 Vibes 或 Sora 之類的，可能也很重要嗎？我們該如何考慮整體方向？

Sure. So the way that I think about this is that the research is going to enable new technological capabilities to exist. And then those capabilities can get built into all kinds of different products. So the ability to reason more intelligently is, for example, very important across a large number of things. It would be useful for an assistant.

當然。所以我認為，這項研究將催生新的技術能力。然後，這些功能可以整合到各種不同的產品中。因此，例如，在很多方面，更聰明的推理能力都非常重要。對助手來說會很有用。

It will also be useful in business AI. It will also be useful in the AI agent that we're building to help advertisers figure out what their campaigns are going to be. It will also have implications for eventually how we do ranking and recommendations of people's feeds and make different decisions there. That's just one example.

它在商業人工智慧領域也將發揮作用。它還將對我們正在建立的人工智慧代理商有所幫助，該代理商可以幫助廣告商確定他們的廣告活動方向。這最終也會對我們如何對用戶的資訊流進行排名和推薦以及做出不同的決策產生影響。這只是一個例子。

I mean certainly, the capability to be able to produce very high-quality good video is going to be useful for giving people new creative tools. It will help increase the amount of content inventory that can be shown in Instagram and Facebook and therefore, should enable an increase in engagement there. It should help advertisers be able to create creative that will help us monetize better.

我的意思是，當然，能夠製作高品質的優質影片對於為人們提供新的創作工具將非常有用。這將有助於增加可在 Instagram 和 Facebook 上展示的內容庫存量，從而提高用戶參與度。這應該有助於廣告商創造出能幫助我們更好地實現獲利的創意內容。

So you can just go kind of down the list of capabilities that you'd expect. And I think each one will enable a bunch of different things. And I think the art of product development here is looking at the list of technology capabilities and figuring out what new products are going to be useful and prioritizing those. But fundamentally, I would sort of expect this exponential curve in new-technology capabilities that are going to become available.

所以你可以按你期望的功能清單逐一查看。我認為每一項都能實現許多不同的事情。我認為產品開發的藝術在於審視技術能力清單，找出哪些新產品會有用，並決定其優先順序。但從根本上講，我預計新技術能力的出現將呈指數級增長。

And the other thing that I expect is that I think being the best in a given area will drive great returns rather than -- this is not like a check-the-box exercise of like, okay, we can generate some kind of content and someone else can. I think that like the company that is the best at each of these capabilities, I think, will get a large amount of the potential value for doing that. So there are lots of different capabilities to build. I'm not sure that any one company is going to be the best at all of them. I doubt that's going to be the case.

而且我預期的另一件事是，我認為在某個領域做到最好會帶來巨大的回報，而不是——這不像是一個走過場的活動，比如，好吧，我們可以創作一些內容，其他人也可以。我認為，在這些能力上都做到最好的公司，將會從中獲得很大的潛在價值。因此，有很多不同的功能需要建置。我不確定哪家公司能夠在所有方面都做到最好。我懷疑情況不會如此。

But a lot of what we're trying to do is not like not kind of do some things that others have done. We're really trying to build novel capabilities. And I'm keeping this high level because I'm not -- I don't want to necessarily from a competitive or strategic perspective, get into what we're prioritizing. But that hopefully gives you a sense of how we're thinking about what we're doing.

但我們嘗試做的很多事情並不是重複別人做過的事情。我們正在努力建立全新的能力。我之所以保持這種高屋建瓴的態度，是因為我不想──從競爭或策略的角度來看，深入探討我們的優先事項。但希望這能讓您了解我們是如何思考我們正在做的事情的。

We want to be able to kind of build novel things, build them into a lot of our products, and then have the compute to scale them to billions of people. And we think that that's going to both show up in terms of new products being possible in new businesses and very significant improvements to the current business, too.

我們希望能夠創造出新穎的東西，將它們融入我們的許多產品中，然後擁有足夠的運算能力，將它們擴展到數十億人。我們認為，這不僅體現在新產品在新業務中的出現，也體現在現有業務的重大改進上。

Mark Mahaney, Evercore ISI.

Mark Mahaney，Evercore ISI。

Just a ask just a question on Meta AI and both product and a monetization path. So when you look at it, what you've seen that's most encouraging to you in terms of the adoption and the use of Meta AI? And then when you think about -- I know you generally like to roll out and then deepen engagement and then later think about monetization. Where do you think you are on that path now? Is it clear to you what the monetization options are for Meta AI?

我只是想問一下關於 Meta AI 的問題，包括產品和獲利模式。那麼，從您的角度來看，在元人工智慧的採用和使用方面，最令您感到鼓舞的是什麼？然後當你思考的時候——我知道你通常喜歡先推出產品，然後加深用戶參與，之後再考慮獲利問題。你覺得自己現在在這條路上處於什麼位置？您是否清楚 Meta AI 的獲利模式有哪些？

I mean, I think the most promising thing that we're seeing is, one, that we were able to build something that a large number of people use, and I think that's valuable. And then secondly, that as we -- there is a clear correlation as we improve the models in ways that we think make them better, that people use them more. So that shows that we have a runway to basically be able to improve engagement and turn this into a product that's leading over time.

我的意思是，我認為我們目前看到的最有希望的事情是，第一，我們能夠建立很多人使用的東西，我認為這很有價值。其次，我們發現，當我們以我們認為更好的方式改進模型時，人們使用它們的次數也會顯著增加。所以這表明我們有足夠的空間來提高用戶參與度，並使之成為隨著時間的推移而領先的產品。

In terms of where we are on this, and we basically just did this huge effort to boot up Meta Superintelligence Labs and build what I am very proud of is, I think, the highest talent density lab in the industry at this point. There are a lot of really great researchers and infrastructure folks and data folks who are now a part of the effort who are focused on training the next generation of work and doing some really novel work. And when that is ready, I think that we will be able to plug that into a number of the products that we're building, and I think that, that will be very exciting.

就我們目前所處的位置而言，我們基本上投入了巨大的努力來啟動 Meta Superintelligence Labs，並建立了我認為目前業內人才密度最高的實驗室，我為此感到非常自豪。現在有許多非常優秀的科學研究人員、基礎設施人員和資料人員參與這項工作中，他們致力於培養下一代人才，並進行一些真正新穎的工作。當它準備好時，我認為我們可以將其應用到我們正在開發的許多產品中，我認為這將非常令人興奮。

But I think that that's really the next thing that we're looking at. And then from there, I think that these models will also improve monetization in all of the different ways that we've talked about so far in terms of improving engagement, improving advertising, helping advertisers engage.

但我認為這才是我們接下來真正要關注的事情。然後，我認為這些模型也將從我們目前討論過的各個方面改善獲利能力，例如提高用戶參與度、改善廣告成效、幫助​​廣告商參與。

I mean there's one opportunity that we just usually talk about it on these calls, but hasn't come up as much here is just the ability to make it so that advertisers are increasingly just going to be able to give us a business objective and give us a credit card or bank account and like have the AI system basically figure out everything else that's necessary, including generating video or different types of creative that might resonate with different people that are personalized in different ways, finding who the right customers are. All of these -- all of the capabilities that we're building, I think, go towards improving all of these different things. So I'm quite optimistic about that.

我的意思是，我們通常會在這些電話會議上討論一個機會，但在這裡卻很少被提及，那就是讓廣告商能夠越來越容易地向我們提供業務目標，並提供信用卡或銀行帳戶信息，然後讓人工智能係統基本上弄清楚所有其他必要的事情，包括生成視頻或不同類型的創意，這些創意可能會引起不同人群的共鳴，並以不同的方式進行定制客戶化，從而找到合適的客戶化。我認為，我們正在建立的所有這些能力，都是為了改進所有這些不同的方面。所以我對此相當樂觀。

Ronald Josey, Citi.

羅納德‧喬西，花旗銀行。

And this maybe dovetails perfectly off Mark, what you just talked about. We heard a lot about [in ad] automations here, I think, reaching a $60 billion ARR. Wanted to hear about -- if you can talk to us more just about adoption rates amongst the advertisers? And then maybe bigger picture, as you incorporate ranking recommendation changes like Andromeda or Gems or Lattice, just talk to us how this automation is driving, call it, a higher ROI for advertisers overall, as we bring it all together.

馬克，這或許正好和你剛才說的完全吻合。我們在這裡聽到了很多關於廣告自動化的討論，我認為，廣告自動化已經達到了 600 億美元的年度經常性收入 (ARR)。想了解一下－能否詳細談談廣告商的採用率？然後，從更宏觀的角度來看，當您整合 Andromeda、Gems 或 Lattice 等排名推薦變更時，請與我們探討這種自動化如何為廣告商帶來更高的整體投資回報率，因為我們會將所有這些整合在一起。

Yes. So we've been we've been sort of laying the continued brick-by-brick build of Advantage Plus and extending the set of objectives that it applies to over time. And so in Q3, we completed the global rollout of the streamlined campaign creation flow for Advantage Plus lead campaigns. So now advertisers who are running sales app or lead campaigns have end-to-end automation turned on from the beginning. And like the kind of application of the streamlined campaign creation flow for other objectives, this generally allows advertisers to optimize and automate several aspects of the campaign setup process at once.

是的。因此，我們一直在一步一步地建造 Advantage Plus，並隨著時間的推移擴展其適用的目標範圍。因此，在第三季度，我們完成了 Advantage Plus 線索行銷活動簡化版活動創建流程的全球推廣。因此，現在投放銷售應用程式或潛在客戶廣告活動的廣告主從一開始就啟用了端到端自動化功能。與將簡化的廣告活動建立流程應用於其他目標類似，這通常允許廣告商一次性優化和自動化廣告系列設定流程的多個方面。

That includes things like audience selection where to show the ad, how the budget gets paced and distributed across ad sets to drive the most efficient outcomes. And we see that Advantage Plus continues to drive performance gains, advertisers who run lead campaigns using Advantage Plus are seeing a 14% lower cost per lead on average than those who are not.

這包括受眾選擇、廣告投放位置、預算的分配方式以及如何在各個廣告群組中合理分配預算以實現最佳效果等事項。我們看到 Advantage Plus 持續推動業績提升，使用 Advantage Plus 進行潛在客戶開發活動的廣告主，平均每次獲客成本比未使用該服務的廣告主低 14%。

And I would say that we think there is still a lot of opportunity generally to grow adoption of Advantage Plus. A lot of advertisers only use our end-to-end automated solutions for a portion of their campaigns so we can grow share there. And to capture that opportunity, we're focused on driving continued performance improvements and addressing some of the key use cases that we still need in order to grow adoption.

我認為，整體而言，Advantage Plus 的普及應用仍有很大的發展空間。許多廣告商只在部分廣告活動中使用我們的端到端自動化解決方案，以便我們能夠擴大市場份額。為了抓住這個機會，我們專注於持續改進效能，並解決一些我們仍然需要解決的關鍵用例，以擴大用戶群。

We're also working to broaden adoption among advertisers who use one of our single-step automated solutions. For example, advertisers who might only use a piece of it like Advantage Plus audiences by helping them understand the benefits of using more than one automated solution at the same time.

我們也在努力擴大使用我們一步式自動化解決方案的廣告商群。例如，廣告主可能只會使用其中的一部分，例如 Advantage Plus 受眾，透過幫助他們了解同時使用多個自動化解決方案的好處。

So I would say Advantage Plus is sort of an ongoing platform by which we both continue to expand the feature set that is available in Advantage Plus, and then expand the extensibility or the coverage of that feature set to sort of the broader set of advertisers. I think Mark mentioned that the annual revenue run rate now for advertisers who are using these automated options is $60 billion. And again, we see that there is room to continue growing that.

因此，我認為 Advantage Plus 是一個持續發展的平台，我們透過該平台不斷擴展 Advantage Plus 的功能集，並將該功能集的擴展性或覆蓋範圍擴展到更廣泛的廣告商群。我認為馬克提到過，目前使用這些自動化選項的廣告商的年收入運行率為 600 億美元。我們再次看到，這方面還有繼續發展的空間。

Youssef Squali, Truist Securities.

Youssef Squali，Truist Securities。

Great. Mark, on wearables, in particular, do you think you'll be able to sell enough hardware to recoup your investment? Or is that dependent on maybe creating new avenues for revenue from things like advertising services and commerce through that new computing platform? And if so, what are kind of the gating factors there?

偉大的。馬克，特別是關於可穿戴設備，你認為你能賣出足夠的硬體來收回你的投資嗎？或者，這取決於能否透過這個新的運算平台，從廣告服務和商業等領域創造新的收入來源？如果確實如此，那麼其中的關鍵因素是什麼？

And then Susan, how do you see the on-balance sheet versus off-balance sheet financing of your AI initiatives? You've recently struck out for the Louisiana data center. Is that part of the CapEx guide for '26? And if it's not, how significant will that way of funding for Meta going forward? And basically, would that slow down your CapEx growth past 2026?

那麼，Susan，您如何看待人工智慧專案的資產負債表內融資與資產負債表外融資？您最近造訪路易斯安那州資料中心失敗了。這是2026年資本支出指南的一部分嗎？如果不是這樣，這種融資方式對 Meta 未來的發展有多重要？那麼，這是否會減緩您2026年以後的資本支出成長速度呢？

I can talk about wearables, and then Susan can jump in on the other part. So there are a few pieces here. One is that the work on Ray-Ban Meta and the Oakley Meta product is going very well. I think, yes, I mean, at some point, if these continue going as well as it has been, then I think it will be a very profitable investment. I think that there's some revenue that we get from basically selling the devices and then some that will come from additional services from the AI on top of it.

我可以談談可穿戴設備，然後蘇珊可以接著談談其他方面。這裡有幾件東西。一是 Ray-Ban Meta 和 Oakley Meta 產品的研發工作進展非常順利。是的，我的意思是，如果這種情況繼續像現在這樣發展下去，那麼我認為這將是一項非常有利可圖的投資。我認為，我們主要透過銷售設備獲得一些收入，然後也透過人工智慧提供的額外服務獲得一些收入。

So I think that there's a big opportunity. Certainly, the investment here is not just to kind of build just the device. It's also to build these services on top. Right now, a lot of people get the devices for a range of things that don't even include the AI even though they like the AI. But I think over time, the AI is going to become the main thing that people are using them for, and I think that that's going to end up having a big business opportunity by itself.

所以我認為這裡蘊藏著巨大的機會。當然，這裡的投資不僅僅是為了製造這個設備。這也是為了在此基礎上建構這些服務。現在很多人購買這些設備是為了各種各樣的用途，即使他們喜歡人工智慧，但這些用途甚至不包括人工智慧。但我認為隨著時間的推移，人工智慧將成為人們使用它們的主要用途，而且我認為這本身最終會帶來巨大的商業機會。

But as products like the Ray-Ban Meta and Oakley Meta are growing, we're also going to keep on investing in things like the more full field of view, product form of the Orion prototype that we showed at Connect last year. So those things are obviously earlier in their curve towards getting to being a sustaining business. And our general view is that we want to build these out to reach many hundreds of millions or billions of people and that's the point at which we think that this is going to be just an extremely profitable business.

但隨著 Ray-Ban Meta 和 Oakley Meta 等產品的發展，我們也將繼續投資於視野更廣闊的產品形式，例如我們去年在 Connect 上展示的 Orion 原型產品。所以很明顯，這些項目還處於發展成為永續業務的早期階段。我們的總體看法是，我們希望將這些業務擴展到數億甚至數十億人，我們認為，到那時，這將是一項極其有利可圖的業務。

Youssef, to your second question. So the JV that we announced with Blue Owl is sort of an example of finding a solution that enabled us to partner with external capital providers to co-develop data centers in a way that gives us long-term optionality in supporting our future capacity needs just given both the magnitude, but also uncertainty of what the capacity outlook in future years looks like.

尤瑟夫，關於你的第二個問題。因此，我們與 Blue Owl 宣布的合資企業就是一個例子，它讓我們能夠與外部資本提供者合作，共同開發資料中心，從而為我們未來的容量需求提供長期的選擇權，因為未來幾年的容量前景既龐大又不確定。

In terms of how that is recognized as CapEx, our prior CapEx reflected a portion of the data center build cost prior to the joint venture being established. Going forward, the construction cost of the data center will not be recorded in CapEx as the data center is constructed, we will contribute 20% of the remaining construction costs required, which is in line with our ownership stake, and those will be recorded as other investing cash flows.

就如何將其認定為資本支出而言，我們先前的資本支出反映了合資企業成立之前資料中心建設成本的一部分。展望未來，資料中心的建造成本將不會計入資本支出，因為在資料中心建置過程中，我們將出資剩餘所需建造成本的 20%，這與我們的持股比例相符，這些成本將作為其他投資現金流記錄。

Ken Gawrelski, Wells Fargo.

Ken Gawrelski，富國銀行。

Just one for me, please. Mark, as you think about with the, hopefully, a leading frontier model next year in hand, could you talk about where you think the value will accrue in this evolving ecosystem? Will it be with the platforms? Or do you think that this will be mostly -- the value will accrue to the scaled first-party applications?

請給我來一份。馬克，考慮到明年預計推出的領先前沿模型，你能否談談你認為在這個不斷發展的生態系統中，價值將在哪些方面體現出來？會透過這些平台嗎？或者您認為這主要會是——價值將歸於規模化的第一方應用程式？

I guess I'm not exactly sure what you mean by platform versus application in this context. But I mean I think that -- I mean, I think there's just a lot of value to create with AI overall. So I mean, clearly, you're seeing the people who are making the hardware. NVIDIA is doing an amazing job, right, I think extremely well-deserved success. The cloud partners and companies are making -- are doing very well. I think that, that will likely continue. I think there's a huge opportunity there.

我不太明白你在這個語境下所說的平台和應用程式的區別。但我的意思是，我認為——我的意思是，我認為人工智慧整體上能創造很多價值。所以我的意思是，很明顯，你看到的是那些製造硬體的人。英偉達做得非常出色，對吧？我認為他們的成功實至名歸。雲端合作夥伴和公司正在取得非常好的成績。我認為這種情況很可能會持續下去。我認為那裡存在著巨大的機會。

And -- but if you look at it today, the companies that are building apps, I mean, a lot of the apps are still relatively small. And I think that that's obviously going to be a huge opportunity. And I think what we've seen overall is basically people take like individual technology advances and build them into products that then build either communities or other kinds of network effects and then end up being very sustaining businesses. And I think what we haven't really seen as much in the history of the technology industry is the rate of new capability is being introduced because around each of these capabilities. You can build many new products that I think each will turn into interesting businesses.

但是——如果你看看現在的情況，那些開發應用程式的公司，我的意思是，很多應用程式的規模仍然相對較小。我認為這顯然將是一個巨大的機會。我認為我們總體上看到的是，人們將單一技術進步融入產品中，然後這些產品會建立社群或其他類型的網路效應，最終發展成為非常永續的企業。我認為，在科技業的歷史上，我們還沒有真正看到新功能的推出速度，因為每項新功能都圍繞著它們。你可以開發很多新產品，我認為每一個都會發展成有趣的商業項目。

So yes. I don't know. I mean I'm generally pretty optimistic about there being a very large opportunity. But in terms of new things to build, I think being able to build them and then scale them to billions of people is a huge muscle that Meta has developed, and I think we do very well. And I certainly think that that's going to deliver a huge amount of value, both in the core business for all the ways that we talked about, how it's going to improve recommendations and the quality of the services as well as unifying the models together.

是的。我不知道。我的意思是，我總體上對這裡存在著巨大的機會持相當樂觀的態度。但就建立新事物而言，我認為能夠建造它們並將其擴展到數十億人是 Meta 已經培養出的一項強大的能力，我認為我們做得非常好。我當然認為這將帶來巨大的價值，無論是在我們討論過的所有核心業務方面，它將改善推薦和服務質量，並將模型統一起來。

And so that way, when these systems are deciding what to show they can just pull from a wider pool. And that we've -- these are things that we've just seen over the 20-plus years of running the company that they just deliver consistent wins that we're going to keep on being able to make the systems more general and smarter and make better recommendations for people and have a larger pool of inventory. And that is all going to be great.

這樣一來，當這些系統決定顯示什麼內容時，它們就可以從更廣泛的資源池中進行選擇。而我們——這些都是我們在公司運營 20 多年中看到的，它們持續帶來成功，我們將繼續使系統更加通用和智能，為人們提供更好的建議，並擁有更大的庫存池。這一切都會很棒的。

And then there's going to be a lot of new things that I think we're going to be able to take and scale to billions of people over time and build new businesses, whether that's advertising or commerce supported or people paying for it or different kinds of things. So yes, it's -- I think it's pretty early, but I think we're seeing the returns in the core business. That's giving us a lot of confidence that we should be investing a lot more. And we want to make sure that we're not under-investing.

然後，我認為我們將能夠把許多新事物推廣到數十億人，並隨著時間的推移建立新的業務，無論是廣告、商業支援、人們付費或其他各種類型的業務。是的，雖然現在還為時過早，但我認為我們已經在核心業務中看到了回報。這讓我們更有信心加大投資力道。我們希望確保不會投資不足。

Great. Thank you, everyone, for joining us today. We look forward to speaking with you again soon.

偉大的。謝謝各位今天蒞臨。我們期待盡快再次與您聯繫。

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了。