2025-01-29 Meta Platforms, Inc. (META) Q4 2024 Earnings Call Transcript

Meta Platforms, Inc. (NASDAQ:META) Q4 2024 Earnings Conference Call January 29, 2025 5:00 PM ET

Company Participants

Kenneth Dorell - Director, Investor Relations

Mark Zuckerberg - Founder, Chairman and Chief Executive Officer

Susan Li - Chief Financial Officer

Conference Call Participants

Brian Nowak - Morgan Stanley

Eric Sheridan - Goldman Sachs

Mark Shmulik - Bernstein

Justin Post - Bank of America

Douglas Anmuth - JPMorgan

Ron Josey - Citigroup

Ken Gawrelski - Wells Fargo

Ross Sandler - Barclays

Operator

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

下午好。我是 Krista，将担任今天的会议主持人。

At this time, I would like to welcome everyone to the Meta Fourth Quarter and Full-Year 2024 Earnings Conference Call.

现在，我想欢迎大家参加 Meta 2024 年第四季度及全年财报电话会议。

All lines have been placed on mute to prevent any background noise.

目前，所有线路均已静音，以防止背景噪音。

After the speaker's remarks, there will be a question-and-answer session. [Operator Instructions] And this call will be recorded.

在演讲结束后，将进行问答环节。[操作员指示] 此次电话会议将被录音。

Thank you very much. Kenneth Dorell, Metta's Director of Investor Relations, you may begin.

非常感谢。Meta 投资者关系总监 Kenneth Dorell 先生，您可以开始了。

Kenneth Dorell

Thank you. Good afternoon and welcome to Meta Platforms fourth quarter and full year 2024 earnings conference call.

谢谢。下午好，欢迎参加 Meta Platforms 2024 年第四季度及全年财报电话会议。

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

今天与我一起讨论财务业绩的是 CEO 马克·扎克伯格（Mark Zuckerberg）和 CFO 苏珊·李（Susan Li）。

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

在开始之前，我想借此机会提醒大家，我们今天的发言可能包含前瞻性声明。

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

实际结果可能与这些前瞻性声明存在重大差异。

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

可能导致实际结果与前瞻性声明存在重大差异的因素，已在今天的财报新闻稿以及我们提交给美国证券交易委员会（SEC）的 10-Q 季度报告中列出。

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

我们在本次电话会议上作出的任何前瞻性声明均基于截至今天的假设，我们不承担因新信息或未来事件而更新这些声明的义务。

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

在本次电话会议中，我们将同时提供 GAAP（美国通用会计准则）及某些非 GAAP 财务指标。

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

GAAP 与非 GAAP 指标的对比调节已包含在今天的财报新闻稿中。

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

财报新闻稿及相关投资者演示文稿可在我们的网站 investor.atmeta.com 上查阅。

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

现在，我将把电话交给马克。

Mark Zuckerberg

All right. Thanks, Ken. Thanks everyone for joining today.

好的，谢谢 Ken。感谢大家今天的参与。

We ended 2024 on a strong note with now more than 3.3 billion people using at least one of our apps each day.

我们以强劲的表现结束了 2024 年，目前每天至少有 33 亿人使用我们的应用之一。

This is going to be a really big year. I know it always feels like every year is a big year, but more than usual it feels like the trajectory for most of our long-term initiatives is going to be a lot clearer by the end of this year.

今年将是一个非常重要的年份。我知道，每一年都感觉很重要，但今年尤其如此，因为到今年年底，我们大多数长期计划的轨迹将变得更加清晰。

So I keep telling our teams that this is going to be intense, because we have about 48 weeks to get on the trajectory we want to be on.

所以我一直告诉我们的团队，今年将是一个紧张的年份，因为我们只有大约 48 周的时间来确保进入我们期望的轨道。

In AI, I expect this is going to be the year when a highly intelligent and personalized AI assistant reaches more than 1 billion people, and I expect Meta AI to be that leading AI assistant.

在人工智能方面，我预计今年将是高度智能化和个性化的 AI 助手触达超过 10 亿人的一年，而我期待 Meta AI 成为这一领域的领先助手。

Meta AI is already used by more people than any other assistant, and once a service reaches that kind of scale it usually develops a durable long-term advantage.

Meta AI 目前的用户数量已经超过了任何其他 AI 助手，而一旦服务达到这种规模，它通常会形成持久的长期优势。

We have a really exciting roadmap for this year with a unique vision focused on personalization.

我们今年制定了非常令人兴奋的路线图，独特的愿景聚焦于个性化体验。

We believe that people don't all want to use the same AI -- people want their AI to be personalized to their context, their interests, their personality, their culture, and how they think about the world.

我们认为，人们不想使用相同的 AI——他们希望 AI 能够根据自己的背景、兴趣、个性、文化以及对世界的理解进行个性化调整。

I don't think that there's just going to be one big AI that everyone uses that does the same thing.

我不认为未来会有一个单一的 AI 供所有人使用，并且执行相同的任务。

专业化的道路上有很多成功的做法是相通的。

People are going to get to choose how their AI works and what it looks like for them.

人们将能够选择他们的 AI 如何运行，以及它对他们而言的呈现方式。

I continue to think that this is going to be one of the most transformative products that we’ve made.

我仍然认为，这是我们打造过的最具变革性的产品之一。

And we have some fun surprises that I think people are going to like this year.

今年我们还准备了一些有趣的惊喜，我相信大家会喜欢。

I think this very well could be the year when Llama and open source become the most advanced and widely used AI models as well.

我认为，今年也可能是 Llama 和开源 AI 成为最先进、最广泛使用的 AI 模型的一年。

Llama 4 is making great progress in training.

Llama 4 的训练进展非常顺利。

Llama 4 mini is done with pre-training and our reasoning models and larger model are looking good too.

Llama 4 mini 已经完成了预训练，我们的推理模型和更大规模的模型也表现良好。

Our goal with Llama 3 was to make open source competitive with closed models, and our goal for Llama 4 is to lead.

Llama 3 的目标是让开源模型与封闭模型竞争，而 Llama 4 的目标则是引领行业。

Llama 4 will be natively multimodal -- it's an omni-model and will have agentic capabilities, so it's going to be novel and it’s going to unlock a lot of new use cases.

Llama 4 将原生支持多模态——它是一个全能模型，并将具备自主智能能力，这将带来创新，并解锁许多新的应用场景。

I'm looking forward to sharing more of our plan for the year on that over the next couple of months.

在接下来的几个月里，我期待与大家分享我们今年的更多计划。

I also expect that 2025 will be the year when it becomes possible to build an AI engineering agent that has coding and problem-solving abilities of around a good mid-level engineer.

我还预计，到 2025 年，AI 工程代理将具备相当于一名优秀中级工程师的编程和问题解决能力。

And this is going to be a profound milestone and potentially one of the most important innovations in history, as well as over time, potentially a very large market.

这将是一个深远的里程碑，可能成为历史上最重要的创新之一，并且长期来看，这也可能是一个极其庞大的市场。

Whichever company builds this first I think is going to have a meaningful advantage in deploying it through advance their AI research and shape the field.

我认为，率先开发出这种能力的公司，将在 AI 研究的推进和行业格局塑造方面占据重要优势。

So that's another reason why I think that this year is going to set the course for the future.

这也是我认为今年将决定未来发展方向的另一个重要原因。

Our Ray-Ban Meta AI glasses are a real hit, and this will be the year when we understand the trajectory for AI glasses as a category.

我们的 Ray-Ban Meta AI 眼镜非常受欢迎，而今年将是我们明确 AI 眼镜这一品类发展轨迹的一年。

Many breakout products in the history of consumer electronics have sold 5 million to 10 million units in their third generation.

在消费电子历史上，许多爆款产品在其第三代时的销量都达到了 500 万至 1000 万台。

This will be a defining year that determines if we're on a path towards many hundreds of millions and eventually billions of AI glasses and glasses being the next computing platform like we've been talking about for some time or if this is just going to be a longer grind.

今年将是决定性的一年，我们将确定 AI 眼镜是否能够走向数亿、甚至最终达到数十亿的规模，并真正成为我们长期以来讨论的下一个计算平台，还是需要更长时间的积累和突破。

But it's great overall to see people recognizing that these glasses are the perfect form factor for AI, as well as just great, stylish glasses.

不过，总体而言，看到人们认可这些眼镜不仅是 AI 的理想载体，同时也是时尚且实用的眼镜，这令人振奋。

These are all big investments, especially the hundreds of billions of dollars that we will invest in AI infrastructure over the long term.

所有这些都需要巨额投资，尤其是我们将在长期内投入数千亿美元用于 AI 基础设施建设。

I announced last week that we expect to bring online almost 1 gigawatt of capacity this year, and we're building a 2 gigawatt and potentially bigger AI datacenter, so big that it would cover a significant part of Manhattan if it were placed there.

我上周宣布，我们预计今年将上线近 1 吉瓦的算力，并且正在建设一个 2 吉瓦甚至更大规模的 AI 数据中心，如果放在曼哈顿，它的面积将覆盖相当大的一部分。

We're planning to fund all this by at the same time investing aggressively in initiatives that use these advances to increase revenue growth.

我们计划通过大力投资利用这些技术进步推动收入增长的项目来资助所有这些建设。

And we've put together a plan that will hopefully accelerate the pace of these initiatives over the next few years.

我们已经制定了一项计划，希望在未来几年加快这些项目的推进速度。

That’s what a lot of our new headcount growth is going towards.

这也是我们许多新增人员配置的主要方向。

And how well we execute on this will also determine our financial trajectory over the next few years.

我们在这一领域的执行力如何，也将决定我们未来几年的财务轨迹。

There are a number of other important product trends related to our family of apps that I think we’re going to know more about this year as well.

关于我们的应用家族，还有许多重要的产品趋势，我认为今年我们将会有更深入的了解。

We'll learn what's going to happen with TikTok, and regardless of that I expect Reels on Instagram and Facebook to continue growing.

我们将了解 TikTok 未来的发展情况，但无论如何，我预计 Instagram 和 Facebook 上的 Reels 仍将继续增长。

I expect Threads to continue on its trajectory to become the leading discussion platform and eventually reach 1 billion people over the next several years.

我预计 Threads 将继续沿着当前轨迹发展，成为领先的讨论平台，并在未来几年内覆盖 10 亿用户。

Threads now has more than 320 million monthly actives and has been adding more than 1 million sign-ups per day.

目前，Threads 的月活跃用户已超过 3.2 亿，并且每天新增注册用户超过 100 万。

I expect WhatsApp to continue gaining share and making progress towards becoming the leading messaging platform in the U.S. like it is in a lot of the rest of the world.

我预计 WhatsApp 将继续扩大市场份额，并在美国逐步成为领先的消息平台，就像它在世界许多其他地区一样。

WhatsApp now has more than 100 million monthly actives in the U.S.

目前，WhatsApp 在美国的月活跃用户已超过 1 亿。

Facebook is used by more than 3 billion monthly actives and we're focused on growing its cultural influence.

Facebook 的月活跃用户已超过 30 亿，我们正专注于提升其文化影响力。

And I'm excited this year to get back to some OG Facebook.

今年，我对回归一些 Facebook 的核心体验感到兴奋。

All right. So this is also going to be a pivotal year for the metaverse.

好的，今年对元宇宙来说也是至关重要的一年。

The number of people using Quest and Horizon has been steadily growing, and this is a year when a number of long-term investments that we've been working on that will make the metaverse more visually stunning and inspiring will really start to land.

使用 Quest 和 Horizon 的用户数量在稳步增长，而今年，我们多年来投入的许多长期投资将开始落地，使元宇宙在视觉上更加震撼、更加激励人心。

So I think we’re going to know a lot more about Horizon's trajectory by the end of this year.

因此，到今年年底，我认为我们将对 Horizon 的发展轨迹有更清晰的认识。

This is also going to be a big year for redefining our relationship with governments.

今年同样是重新定义我们与政府关系的重要一年。

We now have a U.S. administration that is proud of our leading companies, prioritizes American technology winning, and that will defend our values and interests abroad.

目前的美国政府为本国领先企业感到自豪，优先支持美国科技竞争获胜，并将在全球范围内捍卫我们的价值观和利益。

And I'm optimistic about the progress and innovation this is going to unlock.

我对这一变化将带来的进步和创新充满乐观。

So this is going to be a big year.

所以，今年将是关键的一年。

I think this is the most exciting and dynamic that I have ever seen our industry.

我认为，我们所处的行业正处于前所未有的激动人心和充满活力的阶段。

Between AI, glasses, massive infrastructure projects, doing a bunch of work to try to accelerate our business, and building the future of social media, we have a lot to do.

从 AI、智能眼镜、大规模基础设施建设，到努力加速业务发展并构建社交媒体的未来，我们有很多事情要做。

And I think we're going to build some awesome things that shape the future of human connection.

我相信，我们将打造一些非常出色的产品，从而塑造人类连接的未来。

As always, I'm grateful for everyone who is on this journey with us.

一如既往，我对所有与我们同行的人心怀感激。

Thank you and here’s Susan.

谢谢大家，接下来交给 Susan。

Susan Li

Thanks Mark and good afternoon everyone.

谢谢 Mark，大家下午好。

Let’s begin with our consolidated results. All comparisons are on a year-over-year basis unless otherwise noted.

我们先来看合并业绩表现。除非另有说明，所有数据均为同比比较。

Q4 total revenue was $48.4 billion, up 21% on both a reported and constant currency basis.

第四季度总收入为 484 亿美元，按报告和恒定汇率计算均同比增长 21%。

Q4 total expenses were $25 billion, up 5%, compared to last year.

第四季度总支出为 250 亿美元，同比增长 5%。

Before I cover the specific cost lines, I would note that our fourth quarter expense growth rate reflects a 13 percentage point favorable impact from legal accrual reductions in Q4 and lower year-over-year restructuring costs.

在介绍具体成本项目之前，我想强调，第四季度的支出增长率受到法律拨备减少带来的 13 个百分点的有利影响，同时本年度的重组成本同比下降。

In terms of the specific line items. Cost of revenue increased 15%, driven mostly by higher infrastructure costs.

具体来看，营业成本增长 15%，主要由于基础设施成本上升。

R&D increased 16%, primarily driven by higher employee compensation and infrastructure costs, which were partially offset by lower restructuring costs.

研发费用增长 16%，主要由于员工薪酬和基础设施成本增加，部分被较低的重组成本所抵消。

Marketing & Sales were approximately flat year-over-year.

市场与销售费用同比基本持平。

G&A decreased 67%, driven mostly by lower legal-related expenses due to a $1.55 billion reduction in legal accruals related to certain legal proceedings.

一般及行政费用下降 67%，主要由于法律相关费用减少，其中包括与某些法律诉讼相关的 15.5 亿美元法律拨备减少。

We ended the year with over 74,000 employees, up 10% year-over-year, with growth primarily driven by hiring in priority areas of monetization, infrastructure, generative AI, Reality Labs, as well as regulation and compliance.

截至年底，我们的员工总数超过 74,000 人，同比增长 10%。增长主要集中在变现、基础设施、生成式 AI、Reality Labs 以及监管合规等重点领域的招聘。

Fourth quarter operating income was $23.4 billion, representing a 48% operating margin.

第四季度运营利润为 234 亿美元，运营利润率为 48%。

Our tax rate for the quarter was 12%.

本季度的税率为 12%。

Net income was $20.8 billion or $8.02 per share.

净利润为 208 亿美元，每股收益 8.02 美元。

上一年同期是5.33美元，非常大的增幅。

Capital expenditures, including principal payments on finance leases, were $14.8 billion, driven by investments in servers, data centers and network infrastructure.

资本支出（包括融资租赁本金支付）为 148 亿美元，主要用于服务器、数据中心和网络基础设施投资。

Free cash flow was $13.2 billion.

自由现金流为 132 亿美元。

We paid $1.3 billion in dividends to shareholders, ending the year with $77.8 billion in cash and marketable securities and $28.8 billion in debt.

我们向股东支付了 13 亿美元的股息，并以 778 亿美元的现金和可流通证券以及 288 亿美元的债务结束了这一年。

Moving now to our segment results. I’ll begin with our Family of Apps segment.

接下来，我们来看各业务部门的业绩表现。首先是我们的应用家族（Family of Apps）业务。

Our community across the Family of Apps continues to grow, and we estimate more than 3.3 billion people used at least one of our Family of Apps on a daily basis in December.

我们的应用家族用户群持续增长，据估算，2024 年 12 月，每天至少有 33 亿人使用我们的某款应用。

Q4 Total Family of Apps revenue was $47.3 billion, up 21% year-over-year.

第四季度，应用家族总收入为 473 亿美元，同比增长 21%。

And Q4 Family of Apps ad revenue was $46.8 billion, up 21% on both a reported and constant currency basis.

第四季度，应用家族广告收入为 468 亿美元，按报告和恒定汇率计算均同比增长 21%。

Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth.

在广告收入方面，线上商业（电商）是同比增长的最大推动因素。

On a user geography basis, ad revenue growth was strongest in Rest of World at 27%, followed by Asia-Pacific and Europe at 23% and 22%, respectively. North America grew 18%.

按地域划分，广告收入增长最快的是“其他地区”（Rest of World），增长 27%；其次是亚太地区和欧洲，分别增长 23% 和 22%；北美增长 18%。

In Q4, the total number of ad impressions served across our services increased 6% and the average price per ad increased 14%.

第四季度，我们的整体广告展示次数增长 6%，广告的平均单价增长 14%。

Impression growth was mainly driven by Asia-Pacific.

广告展示增长主要由亚太地区推动。

Pricing growth benefited from increased advertiser demand, in part driven by improved ad performance.

广告单价增长受益于广告主需求的增加，部分原因是广告表现的提升。

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

但广告展示次数的增长，特别是在低变现地区和版位，一定程度上抵消了单价增长的影响。

Family of Apps other revenue was $519 million, up 55%, driven primarily by business messaging revenue growth from our WhatsApp Business Platform.

应用家族的其他收入为 5.19 亿美元，同比增长 55%，主要由 WhatsApp 业务平台的商业消息收入增长推动。

We continue to direct the majority of our investments toward the development and operation of our Family of Apps.

我们继续将大部分投资用于应用家族的开发和运营。

In Q4, Family of Apps expenses were $19 billion, representing 76% of our overall expenses.

第四季度，应用家族的总支出为 190 亿美元，占公司整体支出的 76%。

Family of Apps expenses were up 5%, primarily due to growth in infrastructure costs and employee compensation, which were partially offset by lower legal-related expenses.

应用家族的支出同比增长 5%，主要由于基础设施成本和员工薪酬的增长，部分被较低的法律相关费用所抵消。

Family of Apps operating income was $28.3 billion, representing a 60% operating margin.

应用家族的运营利润为 283 亿美元，运营利润率为 60%。

Within our Reality Labs segment, Q4 revenue was $1.1 billion, driven by hardware sales and up 1% year-over-year.

在 Reality Labs 业务板块，第四季度收入为 11 亿美元，主要由硬件销售推动，同比增长 1%。

Reality Labs expenses were $6 billion, up 6% year-over-year, driven primarily by higher infrastructure costs and employee compensation, partially offset by lower restructuring costs.

Reality Labs 的支出为 60 亿美元，同比增长 6%，主要由于基础设施成本和员工薪酬的增长，部分被较低的重组成本所抵消。

Reality Labs operating loss was $5 billion.

Reality Labs 运营亏损为 50 亿美元。

Turning now to the business outlook.

接下来，我们来看业务展望。

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.

影响我们收入表现的两个关键因素是：我们为用户社区提供引人入胜的体验的能力，以及我们长期变现这种用户参与度的有效性。

On the first, daily actives continue to grow across Facebook, Instagram and WhatsApp year-over-year, both globally and in the United States.

首先，Facebook、Instagram 和 WhatsApp 的日活跃用户数量持续增长，无论是在全球范围内还是在美国市场。

In Q4, global video time grew at double-digit percentages year-over-year on Instagram, and we’re seeing particular strength in the U.S. on Facebook, where video time spent was also up double-digit rates year-over-year.

第四季度，Instagram 的全球视频观看时长同比增长了两位数，在美国市场的 Facebook 也表现强劲，视频观看时长同比增长同样达到两位数。

We see continued opportunities to drive video growth in 2025 through ongoing optimizations to our ranking systems.

我们认为，在 2025 年，通过持续优化推荐排名系统，我们仍有机会推动视频增长。

We’re also making several product bets that are focused on setting up our platforms for longer-term success.

我们还在进行多项产品投资，以确保我们的平台实现长期成功。

Creators are one of our central focuses.

创作者群体是我们关注的核心之一。

On Instagram, we continue to prioritize original posts in recommendations to help smaller creators get discovered.

在 Instagram 上，我们继续在推荐系统中优先考虑原创内容，以帮助小型创作者获得更多曝光。

We also want to ensure creators have a place to experiment with their content, so we introduced a new feature in Q4 that allows creators to first share a Reel with people who don’t follow them.

我们也希望确保创作者有一个空间来尝试他们的内容。因此，在第四季度，我们推出了一项新功能，允许创作者先向不关注他们的用户分享 Reels。

This allows them to test content and see what performs best before deciding to share it with their followers, and also helps introduce them to entirely new audiences.

这使他们可以先测试内容，看看哪些表现最佳，然后再决定是否分享给他们的粉丝，同时也能帮助他们触达全新的受众群体。

Creative tools is another area we’re investing in.

创意工具也是我们重点投资的领域之一。

In the coming weeks, we’ll launch a new standalone app called Edits that provides a full suite of creative tools to make it easier for creators to make great Reels on their phone.

在未来几周，我们将推出一款独立应用程序 Edits，它将提供一整套创意工具，使创作者更轻松地在手机上制作优质的 Reels。

Another focus is making it easier for people to connect over content.

另一个重点是让用户更轻松地通过内容建立联系。

Reels are already reshared over 4.5 billion times a day, and we’ve been introducing more features that bring together the social and entertainment aspects of Instagram.

Reels 目前每天被转发超过 45 亿次，我们一直在推出更多功能，以整合 Instagram 的社交和娱乐体验。

In the U.S., we recently launched a new destination in Reels that consists of content your friends have left a note on or liked.

在美国，我们最近推出了 Reels 的一个新板块，其中展示的是你的朋友留下评论或点赞的内容。

复制微信的做法。

We’re seeing very positive early results and will look to expand this globally in the coming months.

目前的初步反馈非常积极，我们计划在未来几个月将这一功能推广至全球。

On Threads, we made tremendous progress in 2024 and our focus this year is establishing Threads as the place people come to keep up with what they care about.

在 Threads 方面，2024 年我们取得了巨大进展，而今年的重点是将 Threads 打造成用户获取关心话题的首选平台。

We’re making a number of updates to our recommendation systems to prioritize more recent posts, surface content from top creators, and ensure people see more of the content from accounts they follow.

我们正在对推荐系统进行多项更新，以优先显示最新帖子、突出顶级创作者的内容，并确保用户能够看到更多他们关注的账号发布的内容。

We will also continue improving custom feeds so people can build personalized feeds on topics they’re interested in.

我们还将继续优化自定义信息流，使用户能够围绕自己感兴趣的话题打造个性化的信息流。

Finally, Meta AI usage continues to scale, with more than 700 million monthly actives.

最后，Meta AI 的使用规模持续增长，目前月活跃用户已超过 7 亿。

比Google的进展更好。

We’re now introducing updates that will enable Meta AI to deliver more personalized and relevant responses by remembering certain details from people’s prior queries and considering what they engage with on Facebook and Instagram to develop better intuition for their interests and preferences.

我们正在推出更新，使 Meta AI 能够提供更加个性化和相关的回答，它将记住用户先前查询的某些细节，并结合用户在 Facebook 和 Instagram 上的互动行为，以更精准地理解用户的兴趣和偏好。

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

接下来，我们来看影响收入表现的第二个关键因素：提升变现效率。

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

优化广告与自然互动的平衡是这项工作的第一步。

We continue to grow supply on lower monetizing surfaces, like video, while optimizing ad supply on each of our surfaces to deliver ads at the time and place they will be most relevant to people.

我们持续在变现能力较低的版块（如视频）上增加广告供应，同时优化各个平台上的广告供应，以确保广告在最合适的时间和位置呈现给最相关的用户。

For example, we are continuing to better personalize when ads show up, including the optimal locations in the depth of someone’s feed, to introduce ad supply when it’s most optimal for the user and revenue.

例如，我们正在进一步优化广告展示时机，包括在信息流的最优位置投放广告，以确保广告在用户体验最佳且收益最优的时刻出现。

This is enabling efficient supply growth.

这将帮助我们实现更高效的广告供应增长。

Longer term, we also see impression growth opportunities on unmonetized surfaces like Threads, which we are beginning to test ads on this quarter.

从长期来看，我们还在 Threads 等尚未变现的平台上看到了广告展示增长的机会。本季度，我们已经开始在 Threads 上测试广告。

We expect the introduction of ads on Threads will be gradual and don’t anticipate it being a meaningful driver of overall impression or revenue growth in 2025.

我们预计 Threads 上的广告投放将是一个渐进的过程，并不认为它会成为 2025 年整体广告展示或收入增长的重要驱动因素。

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

提升变现效率的第二个重点是优化营销表现。

The ongoing enhancements to our ads ranking systems are an important driver of this work.

我们对广告排名系统的持续优化，是推动这一工作的关键因素。

In the second half of 2024, we introduced an innovative new machine learning system in partnership with Nvidia, called Andromeda.

在 2024 年下半年，我们与 Nvidia 合作推出了一种创新的机器学习系统，名为 Andromeda。

This more efficient system enabled a 10,000 times increase in the complexity of models we use for ads retrieval, which is the part of the ranking process where we narrow down a pool of tens of millions of ads to the few thousand we consider showing someone.

这一高效系统使我们用于广告检索的模型复杂度提升了 10,000 倍。广告检索是广告排名过程中的关键环节，我们需要从数千万个广告中筛选出几千个可能展示给用户的广告。

The increase in model complexity is enabling us to run far more sophisticated prediction models to better personalize, which ads we show someone.

模型复杂度的提升，使我们能够运行更复杂的预测模型，以更精准地个性化推荐广告。

This has driven an 8% increase in the quality of ads that people see on objectives we’ve tested.

在我们测试的广告目标中，这一优化使用户看到的广告质量提高了 8%。

Andromeda’s ability to efficiently process larger volumes of ads also positions us well for the future as advertisers use our generative AI tools to create and test more ads.

Andromeda 能够高效处理大规模广告数据，这也让我们在未来更具优势，尤其是在广告主使用我们的生成式 AI 工具创建和测试更多广告的情况下。

Another way we’re delivering value for advertisers is through increased automation of their ad campaigns with Advantage+.

我们为广告主创造价值的另一种方式是通过 Advantage+ 提高广告投放的自动化水平。

Adoption of Advantage+ shopping campaigns continues to scale, with revenue surpassing a $20 billion annual run-rate and growing 70% year-over-year in Q4.

Advantage+ 购物广告的采用率持续增长，年化收入已超过 200 亿美元，并在第四季度实现了 70% 的同比增长。

Given the strong performance and interest we’re seeing in Advantage+ Shopping and our other end-to-end solutions, we’re testing a new streamlined campaign creation flow so advertisers no longer need to choose between running a manual or Advantage+ Sales or App campaign.

鉴于 Advantage+ 购物广告及我们的其他端到端解决方案表现强劲，并受到广告主的广泛关注，我们正在测试一个全新的简化广告创建流程，使广告主无需再在手动模式、Advantage+ 销售或 App 广告之间做选择。

In this new setup, all campaigns optimizing for sales, app or lead objectives will have Advantage+ turned on from the beginning.

在这一新设置中，所有针对销售、App 下载或潜在客户获取目标的广告系列将默认启用 Advantage+。

This will allow more advertisers to take advantage of the performance Advantage+ offers, while still having the ability to further customize aspects of their campaigns when they need to.

这样，更多广告主可以享受 Advantage+ 提供的优化效果，同时在需要时仍可对广告系列的某些方面进行进一步定制。

We plan to expand to more advertisers in the coming months before fully rolling it out later in the year.

我们计划在未来几个月向更多广告主推广该功能，并在今年晚些时候全面推出。

Advantage+ creative is another area where we’re seeing momentum.

Advantage+ 创意是另一个正在快速发展的领域。

More than 4 million advertisers are now using at least one of our generative AI ad creative tools, up from one million six months ago.

目前，已有超过 400 万广告主至少使用过我们的生成式 AI 广告创意工具，相比六个月前的 100 万大幅增长。

There has been significant early adoption of our first video generation tool that we rolled out in October, Image Animation, with hundreds of thousands of advertisers already using it monthly.

我们在 10 月推出的首款视频生成工具 Image Animation 已获得广泛应用，每月已有数十万广告主在使用它。

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

接下来，我想讨论我们的资本配置策略。

Our primary focus remains investing capital back into the business, with infrastructure and talent being our top priorities.

我们的主要重点仍然是将资本重新投入业务发展，基础设施和人才是我们最优先的投资方向。

On the first, we expect compute will be central to many of the opportunities we’re pursuing as we advance the capabilities of Llama, drive increased usage of generative AI products and features across our platform, and fuel core ads and organic engagement initiatives.

首先，我们预计计算能力将在许多业务机会中发挥核心作用，包括提升 Llama 的能力、推动生成式 AI 产品和功能在整个平台上的应用增长，以及支持核心广告和自然互动的增长。

We’re working to meet the growing capacity needs for these services by both scaling our infrastructure footprint and increasing the efficiency of our workloads.

我们正在通过扩展基础设施规模和提高工作负载效率，以满足这些服务不断增长的算力需求。

Another way we’re pursuing efficiencies is by extending the useful lives of our servers and associated networking equipment.

我们提升效率的另一种方式是延长服务器及相关网络设备的使用寿命。

Our expectation going forward is that we’ll be able to use both our non-AI and AI servers for a longer period of time before replacing them, which we estimate will be approximately 5.5 years.

展望未来，我们预计非 AI 和 AI 服务器的使用寿命都将延长，预计使用周期约为 5.5 年。

This will deliver savings in annual CapEx and resulting depreciation expense, which is already included in our guidance.

这将降低年度资本支出（CapEx）和相应的折旧费用，这些节省已纳入我们的财务指引。

这对NVIDIA不是好事，Amazon在此以前已经这么做了。

Finally, we’re pursuing cost efficiencies by deploying our custom MTIA silicon in areas where we can achieve a lower cost of compute by optimizing the chip to our unique workloads.

最后，我们正在通过部署自研的 MTIA（Meta Training and Inference Accelerator）芯片来提升计算成本效率，通过优化芯片以适应我们的独特工作负载，从而降低计算成本。

In 2024 we started deploying MTIA to our ranking and recommendation inference workloads for ads and organic content.

在 2024 年，我们已开始将 MTIA 应用于广告和自然内容的排名与推荐推理工作负载。

We expect to further ramp adoption of MTIA for these use cases throughout 2025 before extending our custom silicon efforts to training workloads for ranking and recommendations next year.

我们计划在 2025 年进一步扩大 MTIA 在这些应用中的使用范围，并在明年将自研芯片的应用扩展到排名和推荐的训练工作负载领域。

From a hiring standpoint, our focus continues to be on adding technical talent to support our strategic priorities.

从招聘的角度来看，我们的重点仍然是增加技术人才，以支持我们的战略重点。

In the fourth quarter, nearly 90% of our year-over-year headcount growth was within the R&D function.

在第四季度，我们的员工同比增长中，近 90% 发生在研发部门。

The remaining growth was primarily in cost of revenue as we added infrastructure headcount to support our data center operations.

其余的增长主要体现在营业成本方面，我们增加了基础设施团队的人员，以支持数据中心的运营。

In 2025, we expect headcount growth will continue to be primarily driven by technical roles across our priority initiatives within infrastructure, monetization, Reality Labs, generative AI, as well as regulation and compliance.

在 2025 年，我们预计员工增长仍将主要集中在技术岗位，覆盖基础设施、变现、Reality Labs、生成式 AI 以及监管和合规等优先领域。

We anticipate headcount growth in our business functions will remain relatively limited.

我们预计业务职能部门的员工增长将保持相对有限。

To achieve our ambitions in these areas, we will need to continue executing at a rapid pace.

为了实现这些领域的目标，我们需要继续以高效的节奏执行。

We’re supporting this by building tools to help our engineering base be more productive.

为此，我们正在开发工具，以提高工程师团队的工作效率。

As part of our efficiency focus over the past two years, we’ve made significant improvements in our internal processes and developer tools and introduced new tools like our AI-powered coding assistant, which is helping our engineers write code more quickly.

作为过去两年效率提升的一部分，我们大幅改进了内部流程和开发工具，并推出了 AI 代码助手等新工具，帮助工程师更快地编写代码。

Looking forward, we expect that the continuous advancements in Llama’s coding capabilities will provide even greater leverage to our engineers, and we are focused on expanding its capabilities to not only assist our engineers in writing and reviewing our code, but also to begin generating code changes to automate tool updates and improve the quality of our code base.

展望未来，我们预计 Llama 在代码能力上的持续进步将为我们的工程师提供更强的支持。我们专注于扩展其功能，不仅帮助工程师编写和审核代码，还将自动生成代码变更，以优化工具更新并提升代码库的质量。

Finally, we expect our strong financial position will enable us to support these investments while continuing to return capital to shareholders through share repurchases and dividends.

最后，我们预计强劲的财务状况将使我们能够支持这些投资，同时通过股票回购和分红，持续向股东回报资本。

Moving to our financial outlook.

接下来是我们的财务展望。

We expect first quarter 2025 total revenue to be in the range of $39.5 billion to $41.8 billion.

我们预计 2025 年第一季度的总收入将在 395 亿美元至 418 亿美元之间。

This reflects 8% to 15% year-over-year growth, or 11% to 18% growth on a constant currency basis as our guidance assumes foreign currency is an approximately 3% headwind to year-over-year total revenue growth, based on current exchange rates.

这意味着同比增长 8% 至 15%，或按恒定汇率计算同比增长 11% 至 18%。我们的业绩指引假设当前汇率水平下，外汇因素对同比总收入增长造成约 3% 的负面影响。

This also reflects the effect of lapping leap day in the first quarter of 2024.

这也包括 2024 年第一季度因闰年额外一天带来的基数效应。

While we are not providing a full-year 2025 revenue outlook, we expect the investments we’re making in our core business this year will give us an opportunity to continue delivering strong revenue growth throughout 2025.

尽管我们没有提供 2025 年全年的收入指引，但我们预计，今年对核心业务的投资将为我们提供机会，使 2025 年的收入持续强劲增长。

Turning now to the expense outlook.

接下来是支出展望。

We expect full-year 2025 total expenses to be in the range of $114 billion to $119 billion.

我们预计 2025 年全年的总支出将在 1140 亿美元至 1190 亿美元之间。

We expect the single largest driver of expense growth in 2025 to be infrastructure costs, driven by higher operating expenses and depreciation.

我们预计 2025 年支出增长的最大驱动因素将是基础设施成本，主要由更高的运营费用和折旧支出推动。

We expect employee compensation to be the second-largest factor as we add technical talent in the priority areas that I referenced earlier.

我们预计员工薪酬将是第二大成本因素，因为我们将在之前提到的重点领域增加技术人才。

Turning now to the CapEx outlook.

接下来是资本支出（CapEx）展望。

We anticipate our full-year 2025 capital expenditures will be in the range of $60 billion to $65 billion.

我们预计 2025 年全年资本支出将在 600 亿美元至 650 亿美元之间。

We expect CapEx growth in 2025 will be driven by increased investment to support both our generative AI efforts and our core business.

我们预计 2025 年资本支出的增长将由对生成式 AI 以及核心业务的投资增加所推动。

The majority of our CapEx in 2025 will continue to be directed toward our core business.

2025 年的大部分资本支出仍将用于支持我们的核心业务。

On to tax. Absent any changes to our tax landscape, we expect our full-year 2025 tax rate to be in the range of 12% to 15%.

关于税务问题，在当前税务环境不变的情况下，我们预计 2025 年全年的税率将在 12% 至 15% 之间。

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

此外，我们将持续关注动态变化的监管环境，包括欧盟和美国的法律与监管挑战，这些因素可能会对我们的业务和财务业绩产生重大影响。

In closing, this was a good year for our company, with investments across our priority areas delivering strong business performance and innovative new products for our community.

最后总结而言，这对我们公司而言是一个良好的一年，我们在重点领域的投资推动了强劲的业务表现，并为用户社区带来了创新的产品。

We have a compelling set of opportunities to invest in this year, which we expect will help us drive continued strong growth and develop transformative technologies that shape the future of our company and of the industry.

今年，我们拥有一系列引人瞩目的投资机会，我们预计这些投资将帮助我们实现持续强劲增长，并开发出变革性的技术，塑造公司及整个行业的未来。

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

好了，Krista，我们现在进入问答环节。

Question-and-Answer Session

Operator

Thank you. Thank you. We will now open the lines for a question-and-answer session. [Operator Instructions] And our first question comes from the line of Brian Nowak with Morgan Stanley. Please go ahead.

谢谢。我们现在进入问答环节。[操作员指示] 我们的第一位提问者是 Morgan Stanley 的 Brian Nowak。请开始提问。

Brian Nowak

Thanks for taking my questions. Mark, I appreciate all the excitement about this year and all the innovation to come.

谢谢回答我的问题。Mark，我很欣赏你对今年的展望和即将到来的各种创新。

I know there's a lot of announcements throughout the course of the year, but I wonder if you could just share a few sort of high-level examples of your vision on new potential use cases and offerings that could drive utility for your users and value for your advertisers.

我知道今年会有很多重要发布，但我想请你分享几个高层次的例子，说明你对新的潜在应用场景和产品的愿景，这些产品如何为用户提供更大价值，并为广告主创造更多机会？

As you sort of think about Llama 4 and Meta AI changing throughout 2025?

尤其是在你考虑 Llama 4 和 Meta AI 在 2025 年的发展时？

And then the second one on custom silicon, maybe a question for either of you.

第二个问题是关于定制芯片的，也可以请你们两位任何一位回答。

Just any learnings on the difference between your custom silicon and third-party chips in your ranking models and results?

你们在排名模型和结果中对比自研芯片与第三方芯片时，有哪些重要发现？

And how should we think about the main gating factors as to how quickly you'd be able to move a higher percentage of your engagement to your custom silicon? Thanks.

我们应该如何理解你们在推进更多计算任务转向自研芯片方面的主要限制因素？谢谢。

Mark Zuckerberg

On the first one, I tried to lay this out in my opening comments a bit.

关于第一个问题，我在开场发言中已经稍微提到过。

I mean we're very focused on Meta AI as a highly intelligent and personalized assistant that you can access across our apps.

我们的核心重点是 Meta AI，它是一个高度智能化和个性化的助手，用户可以在我们的各个应用中使用它。

There's a website, you can access it outside of our apps, too.

此外，我们还推出了网页版，用户可以在我们的应用之外访问它。

I think that the quality of this is just -- it's going to keep on improving and improved a lot over the last year.

我认为这个产品的质量会不断提升，过去一年已经有了显著改进。

We're also finding more ways that it's useful to integrate it into our services to help more people discover it.

我们还在探索更多方法，使其更好地融入我们的服务，让更多用户发现并使用它。

I think that, that's undoubtedly why so many hundreds of millions of people are using it today, obviously, because it's kind of easy to discover what we're doing and then keep using it.

我认为，这无疑是为什么今天有数亿人使用它的原因之一——它很容易被用户发现并持续使用。

I don't know. I want to keep some surprises and fun for the stuff that we're going to release this year.

我不想透露太多，因为我们今年还有一些惊喜，希望给大家带来更多期待和乐趣。

I gave a bit of detail on what we're planning to do with Llama 4 that I'm sure technical people will enjoy, because we haven't talked about that before.

我稍微提及了我们对 Llama 4 的规划，我相信技术人员会对这些信息感兴趣，因为我们此前还没有公开谈论过这些内容。

But I'm going to refrain from adding a whole lot more on what we're launching this year.

不过，我暂时不会透露太多即将发布的内容。

But it's the different things that I talked about. It's Meta AI. I do expect Llama 4 to be a very exciting set of releases.

但我可以说，我们的重点包括 Meta AI，以及 Llama 4，它将是一个非常激动人心的发布系列。

It's not just one thing. Just like with Llama 3, there were kind of a few different models at different dates, I think we'll see that with Llama 4 too.

它不会只是一个单独的模型。就像 Llama 3 一样，我们在不同时间推出了多个版本的模型，我预计 Llama 4 也会采取类似的策略。

And then the AI engineer piece, I'm really excited about it.

此外，我对 AI 工程师项目也感到非常兴奋。

I mean, I don't know that that's going to be an external product anytime soon.

不过，我不确定它会在短期内成为一个对外产品。

But I think for what we're working on, our goal is to advance AI research and advance our own development internally.

目前，我们的目标是推动 AI 研究，并在内部提升我们的开发效率。

And I think it's just going to be a very profound thing.

我认为，这将是一个极具变革性的进展。

So I mean that's something that I think will show up through making our products better over time.

我认为，这项技术的影响会逐步体现，通过提升我们的产品质量来展现它的价值。

And then as that works, there will potentially be a market opportunity down the road.

如果这项技术发展顺利，未来可能会带来新的市场机会。

But I mean, for now and this year, we're really -- I think this is -- I don't think you're going to see this year like an AI engineer that is extremely widely deployed, changing all of development.

但就目前而言，尤其是今年，我认为我们不会看到 AI 工程师技术被大规模部署，并彻底改变整个开发流程。

I think this is going to be the year where that really starts to become possible and lays the groundwork for a much more dramatic change in '26 and beyond.

我认为，今年将是这项技术开始成为现实的一年，并为 2026 年及未来更大的变革奠定基础。

I don't know yes, that's kind of it.

大概就是这些。

Susan Li

Brian, I'm happy to take your second question about custom silicon.

Brian，我很高兴回答你关于定制芯片的第二个问题。

So first of all, we expect that we are continuing to purchase third-party silicon from leading providers in the industry.

首先，我们预计将继续从行业领先的供应商采购第三方芯片。

And we are certainly committed to those long-standing partnerships, but we're also very invested in developing our own custom silicon for unique workloads, where off-the-shelf silicon isn't necessarily optimal.

我们仍然致力于维持这些长期合作伙伴关系，但同时，我们也在大力投资自研芯片，以满足某些特定的计算需求，因为现成的芯片可能并不总是最优的选择。

And specifically, because we're able to optimize the full stack to achieve greater compute efficiency and performance per cost and power.

特别是因为，我们可以优化整个计算架构，使计算效率更高，并在成本和功耗方面获得更好的性能。

Our workloads might require a different mix of memory versus network, bandwidth versus compute, and so we can optimize that really to the specific needs of our different types of workloads.

我们的计算任务可能需要不同的内存与网络配置、带宽与计算资源分配，因此，我们可以根据不同任务的具体需求进行优化。

Right now, the in-house MTIA program is focused on supporting our core ranking and recommendation inference workloads.

目前，我们自研的 MTIA（Meta Training and Inference Accelerator）芯片主要用于支持核心排名和推荐推理任务。

We started adopting MTIA in the first half of 2024 for core ranking and recommendations inference.

我们在 2024 年上半年开始将 MTIA 应用于核心排名和推荐推理任务。

We'll continue ramping adoption for those workloads over the course of 2025 as we use it for both incremental capacity and to replace some GPU-based servers when they reach the end of their useful lives.

2025 年，我们将继续扩大 MTIA 的应用范围，既用于扩充算力，也用于在 GPU 服务器使用寿命到期时替换部分 GPU 服务器。

Next year, we're hoping to expand MTIA to support some of our core AI training workloads and over time, some of our Gen AI use cases.

明年，我们希望进一步扩展 MTIA 的应用，将其用于部分核心 AI 训练任务，并逐步支持一些生成式 AI 的应用场景。

Operator

Your next question comes from the line of Eric Sheridan with Goldman Sachs. Please go ahead.

下一位提问的是 Goldman Sachs 的 Eric Sheridan。请开始提问。

Eric Sheridan

Thank you so much for taking the question.

非常感谢回答我的问题。

Maybe I can go back to your comments on open source.

我想回到你们对开源的观点。

Can you help us understand how your views continue to evolve with respect to the competitive dynamic around your approach with open source versus others in the industry?

能否请你们谈谈，关于开源战略与行业其他参与者的竞争动态，你们的观点如何在不断演变？

And how your approach to open source could possibly bend the cost curve and improve return on capital for AI over the medium to long-term?

此外，你们的开源战略如何在中长期降低 AI 成本曲线，并提高资本回报率？谢谢。

Mark Zuckerberg

Yes. I mean on open source, I think the best analogy for us is what we did with open compute, where we weren't first to building the system.

是的，我认为对于开源，最好的类比是我们当初在 Open Compute 项目上的做法。当时，我们并不是第一个开发该系统的公司。

So then by the time that we got around to building it, it wasn't really a big advantage to have it be proprietary. So we shared it.

所以，当我们最终开始开发时，专有化并没有太大优势，因此我们选择了开放共享。

And then a lot of the industry adopted what we were doing, contributed innovations back to it.

随后，许多行业参与者采用了我们的方案，并为其贡献了创新。

By standardizing it on it, that meant that a bunch of supply chain standardized on building it, which made prices more efficient for everyone.

随着行业标准的确立，供应链也开始围绕这一标准进行优化，使得成本更具效率，对整个行业都有利。

I think what we see here is as Llama becomes more used, it's more likely, for example, that silicon providers and others -- other APIs and developer platforms will optimize their work more for that and basically drive down the costs of using it and drive improvements that we can, in some cases, use too.

我们在 Llama 方面看到的情况是，随着它的使用范围扩大，越来越多的芯片供应商、API 提供商和开发者平台可能会围绕 Llama 进行优化，从而降低使用成本，同时也带来改进，而这些改进在某些情况下，我们也能受益。

开源的好处是吸收第三方的智慧。

So I think that the strategy will continue to be effective, and yes, I mean, I continue to be optimistic on this.

因此，我认为这种策略将继续奏效，并且我对这一方向保持乐观。

I think it's kind of -- I think it's working.

我认为它正在发挥作用。

I also just think in light of some of the recent news, the new competitor DeepSeek from China, I think it also just puts -- it's one of the things that we're talking about is there's going to be an open source standard globally.

此外，考虑到最近的一些新闻，比如来自中国的竞争对手 DeepSeek，这也让我们更加关注全球开源标准的制定。

And I think for our kind of national advantage, it's important that it's an American standard.

从国家竞争力的角度来看，我们认为确保这一标准是美国主导的至关重要。

So we take that seriously, and we want to build the AI system that people around the world are using and I think that if anything, some of the recent news has only strengthened our conviction that this is the right thing for us to be focused on.

因此，我们对此非常重视，并希望构建一个全球用户都在使用的 AI 体系。事实上，最近的一些动态只会让我们更加坚定，认为这是我们应该专注投入的正确方向。

Operator

Your next question comes from the line of Mark Shmulik with Bernstein. Please go ahead.

下一位提问的是 Bernstein 的 Mark Shmulik。请开始提问。

Mark Shmulik

Yes, thank you for taking my questions.

是的，谢谢你们回答我的问题。

Mark, I appreciate we may get an answer this here.

Mark，我理解可能今年我们就能得到一些答案。

But looking out, as you kind of track the progress of smart glasses, Orion and so forth,

但从长远来看，当你观察智能眼镜（如 Orion）的发展进展时，

do you view that as a better form factor to get the most out of the Meta AI assistant you highlighted in your opening remarks?

你认为它是更理想的 AI 设备形态，以最大化发挥 Meta AI 助手的作用吗？

Or is it more complementary to kind of the in-app experience in the way you've seen people use it today?

还是它更像是对当前用户使用的应用内 AI 体验的一种补充？

And then, Susan, the last few quarters, we've kind of seen pricing growth is the dominant driver of ad revenue growth.

然后，Susan，过去几个季度，我们看到广告收入增长主要由单价提升推动。

Given the efforts you've highlighted around driving deeper, more commercial engagement and better advertiser ROI,

考虑到你们在推动更深入的商业互动和提升广告主 ROI 方面所做的努力，

how do we just think about the contribution of the formula for ad revenue growth going forward?

我们应该如何看待未来广告收入增长的构成？谢谢。

Mark Zuckerberg

Yes. I mean, I can talk about glasses.

是的，我可以谈谈智能眼镜。

I mean it's -- yes, I mean, I've said for a while that I think that glasses are the ideal form factor for an AI device, because you can let an AI assistant on your glasses see what you see and hear what you hear, which gives it the context to be able to understand everything that's going on in your life that you would want to talk to it about and get context on.

是的，我之前已经说过一段时间了，我认为眼镜是 AI 设备的理想形态，因为 AI 助手可以通过眼镜看到你所看到的，听到你所听到的，这让 AI 能够理解你的生活环境，并帮助你处理你希望与它交流的任何事情，并提供上下文信息。

So -- but look, I mean, I think the glasses are going to be a very important computing platform in the future.

所以，我认为，智能眼镜将在未来成为一个非常重要的计算平台。

When phones became the primary computing platform, it's not like computers went away.

当手机成为主要计算平台时，电脑并没有消失。

I think we'll have phones for some time.

我认为，手机还会存在相当长的一段时间。

But there are a lot of people in the world who have glasses.

但全球有大量用户佩戴眼镜。

It's kind of hard for me to imagine that a decade or more from now, all the glasses aren't going to basically be AI glasses,

我很难想象，十年或更长时间后，所有的眼镜不会成为 AI 眼镜。

as well as a lot of people who don't wear glasses today, finding that to be a useful thing.

同时，那些目前不戴眼镜的人，未来也可能会发现 AI 眼镜是一种有用的工具。

So I'm incredibly optimistic about this.

所以，我对这个领域持极为乐观的态度。

And like I shared last year, I think one of the big surprises last year was I previously thought that glasses weren't going to become a major form factor until we got these --the full kind of holographic displays that we started showing in the prototype for Orion.

正如我去年分享的那样，去年让我感到意外的一点是，我之前认为，智能眼镜不会成为主流形态，除非我们能够实现完整的——类似于我们在 Orion 原型机中展示的全息显示技术。

But now I think it's pretty clear that AI is actually going to drive at least as much of the value as the holographic AR is.

但现在，我认为很明显，AI 本身所带来的价值至少可以和全息 AR 相媲美。

苹果的Vision Pro很可能走错了方向，事前谁也没有想到，Meta能不能保持领先？

So that's a cause to be excited.

这让我感到非常兴奋。

But look, the Ray-Ban Metas were hit.

不过，从市场表现来看，Ray-Ban Meta 眼镜已经取得了成功。

We still don't know what the long-term trajectory for this is going to be.

但我们仍然不确定其长期发展轨迹如何。

And I think we're going to learn a lot this year.

我认为，今年我们会获得很多新的认知和经验。

So I think that this is a really important year for that.

因此，我认为今年对智能眼镜来说是一个至关重要的年份。

Susan Li

And I can take the second question on pricing growth.

我来回答关于广告价格增长的第二个问题。

So first of all, what I would say is over the long term, we think we have continued opportunity to drive revenue growth across both pricing and impression growth, so both sort of supply and demand dimensions.

首先，从长期来看，我们认为在价格增长和广告展示量增长两个维度上，我们都有持续推动收入增长的机会，也就是从供需两个方面进行优化。

When we look at pricing, our reported growth can be influenced by different factors such as supply because of the auction dynamics by the mix shift of the different types of surfaces where ads show up.

当我们考虑广告价格时，其增长受多个因素影响，例如由于广告拍卖机制的动态变化，不同广告投放位置的组合调整都会影响整体价格。

For example, services like video or lower monetization efficiency, relatively speaking.

例如，相比于其他广告形式，视频广告的变现效率相对较低，这也会影响价格。

And then, of course, broader macro factors.

此外，整体宏观经济环境也是影响因素之一。

But we generally expect that we are going to be able to deliver ongoing ad performance improvements through a lot of the ongoing work that we're doing across our monetization road map and that will have the sort of effect of benefiting pricing overall.

不过，我们总体预计，通过我们在变现策略上的持续优化，广告表现将不断提升，从而对整体广告价格产生积极影响。

And part of what I think is kind of important to think about here when we think about price growth is we really -- the average price per ad as we reported, is really blending, it's an output metric.

在讨论广告价格增长时，有一个重要的点需要考虑，那就是我们报告的广告平均单价实际上是一个综合指标，它是一个最终的输出数据。

It's blending a lot of things that are happening, including what our advertisers bidding for, what are their bids for those things? What is the average cost of their actions.

它综合了多个因素，包括广告主竞价的目标、他们的出价水平，以及他们所优化的转化目标的平均成本。

So given that there are so many different objectives that advertisers can optimize for that have different values, it's a very complex metric that tries to distill that into one thing.

由于广告主可以优化的目标种类繁多，每个目标的价值不同，因此这个指标实际上非常复杂，需要将多种影响因素汇总成一个数据。

Overall, we are seeing healthy cost per action trends for advertisers for whatever is the action that they are optimizing for.

总体来看，无论广告主优化的是哪种转化目标，我们都看到他们的每次转化成本趋势保持健康。

And we believe we'll continue to get better at driving conversions for advertisers.

我们相信，我们的能力将不断提升，能够帮助广告主实现更高的转化率。

And when we do, that will have the effect of continuing to lift CPMs over time,

当我们在这方面取得进展时，这将推动 CPM（千次展示成本）在长期内持续增长，

because we're delivering more conversions per impression served, resulting in higher value impressions.

因为我们每次广告展示带来的转化会越来越多，从而提升广告展示的整体价值。

Operator

Your next question comes from the line of Justin Post with Bank of America. Please go ahead.

下一位提问的是来自 Bank of America 的 Justin Post。请开始提问。

Justin Post

Great, thanks. Maybe one for Mark and one for Susan.

太好了，谢谢。我有一个问题给 Mark，另一个给 Susan。

Mark, you mentioned political changes in the U.S. and better positioning maybe for U.S. companies abroad.

Mark，你提到了美国的政治变化，以及美国公司在海外可能获得更有利的竞争环境。

But how do you think about it in the U.S. as far as usage and advertiser adoption, you got rid of fact checking.

但在美国市场，你如何看待这一变化对用户使用和广告主投放的影响？你们取消了事实核查（fact-checking）。

So do you think the content could change? Could it appeal to more users? Will that impact advertising at all?

你认为这会改变平台上的内容吗？这是否会吸引更多用户？广告业务会受到影响吗？

And then Susan, on Meta AI, I know people are pretty excited about the use case, but also thinking about the revenue case.

然后，Susan，关于 Meta AI，大家对其应用场景感到兴奋，但也在关注它的商业化前景。

How do you think about monetizing that? Could it be CPC ads? Or how are you thinking about that? Thank you.

你们如何考虑变现方式？会是按点击付费（CPC）广告吗？或者你们的思路是什么？谢谢。

Mark Zuckerberg

The question was about fact checking and our content policies.

这个问题是关于事实核查和我们的内容政策。

I mean, look, I think we're trying to build the service that we think is the best for people.

我们一直在努力打造最适合用户的平台。

I believe in free expression for quite a while.

我一直以来都支持言论自由。

People don't want to see misinformation, but you need to build an effective system that gives people more context.

用户不希望看到虚假信息，但关键是要构建一个有效的系统，为他们提供更多的背景信息。

And I think what we found over time is that the community note system, I think, is just going to be more effective than the system that we had before.

我们发现，随着时间推移，社区注释（Community Notes）系统比我们之前使用的系统更加有效。

And I'm not afraid to admit when someone does something that's better than us.

我并不害怕承认，当别人做得比我们更好时，我们应该学习并改进。

I think it's sort of our job to go and just do best work and implement the best systems.

我们的职责就是去做最好的产品，采用最有效的系统。

So I think that there's been a lot of people who have read this announcement as if we somehow don't care about adding context to things that are on our platform that are misinformation, that's not right.

很多人可能误解了我们的公告，以为我们不再关心如何为平台上的虚假信息提供背景信息。但事实并非如此。

I actually think that the community note system, like what X has had for a while, is actually just more effective than what we were doing before.

实际上，我认为社区注释系统——类似于 X 平台（前 Twitter）已经运行了一段时间的模式——比我们之前的做法更加有效。

And I think our product is going to get better because of it.

我相信，这一变化将使我们的产品变得更好。

Susan Li

I would add to that, just to say, we also haven't seen any noticeable impact from our content policy changes on advertiser spend.

我想补充一点，我们尚未观察到内容政策变化对广告支出的明显影响。

So we're continuing to see strong advertiser demand.

我们仍然看到强劲的广告主需求。

Again, particularly for AI-powered tools that are helping businesses maximize the value of their ad spend.

尤其是在 AI 赋能的广告工具方面，这些工具正在帮助企业最大化广告支出的价值。

So our commitment to brand safety is unchanged, and we expect that we will invest in our suite of tools to meet the needs of advertisers.

因此，我们对品牌安全的承诺不会改变，并且我们将继续投资广告工具，以满足广告主的需求。

On your second question in terms of monetizing Meta AI, our initial focus for Meta AI is really about building a great consumer experience, and that's frankly, where all of our energies are kind of directed to right now.

关于你提到的 Meta AI 变现问题，我们的初始重点仍然是打造出色的用户体验，坦率地说，目前我们的全部精力都集中在这一方面。

There will, I think, be pretty clear monetization opportunities over time, including paid recommendations and including a premium offering,

我认为，随着时间推移，Meta AI 将会有非常明确的变现机会，其中可能包括付费推荐以及高级订阅服务。

but really not where we are focused in terms of the development of Meta AI today.

但目前，这些都不是我们在 Meta AI 发展阶段的重点。

Operator

Your next question comes from the line of Douglas Anmuth with JPMorgan. Please go ahead.

下一位提问的是 JPMorgan 的 Douglas Anmuth。请开始提问。

Douglas Anmuth

Thanks for taking the questions. One for Mark, one for Susan.

谢谢回答我的问题。我有一个问题给 Mark，另一个给 Susan。

Mark, just following up on open source as DeepSeek and other models potentially leverage Llama or others to train faster and cheaper.

Mark，关于开源，DeepSeek 以及其他模型可能会利用 Llama 或其他开源模型进行更快速和低成本的训练。

How does this impact in your view?

你认为这对 Meta 有什么影响？

And what could have been for the trajectory of investment required over a multiyear period?

这可能会如何影响你们未来多年的投资轨迹？

And then, Susan, just as we think about the $60 billion to $65 billion CapEx this year,

然后，Susan，今年你们预计的 600 亿到 650 亿美元资本支出（CapEx），

does the composition change much from last year when you talked about servers as the largest part followed by data centers and networking equipment?

其构成与去年相比是否发生了较大变化？去年你们提到服务器是最大支出项，其次是数据中心和网络设备。

And how should we think about that mix between like training and inference just following up on Jan's post this week? Thanks.

此外，在训练（training）和推理（inference）之间的支出分配应该如何理解？谢谢。

Mark Zuckerberg

I can start on the DeepSeek question.

我先来回答关于 DeepSeek 的问题。

I think there's a number of novel things that they did that I think we're still digesting. And there are a number of things that they have advances that we will hope to implement in our systems.

我认为，他们在一些方面做出了一些创新，我们仍在消化和分析这些内容。他们在某些领域的进展是我们希望在自己的系统中实现的。

And that's part of the nature of how this works, whether it's a Chinese competitor or not.

无论他们是否是来自中国的竞争对手，这都是技术发展的自然过程。

I kind of expect that every new company that has an advance -- that has a launch is going to have some new advances that the rest of the field learns from.

我预计，每一家推出新产品的公司都会带来新的技术突破，而整个行业都会从中学习和借鉴。

And that's sort of how the technology industry goes.

这基本上就是科技行业的发展模式。

I don't know -- it's probably too early to really have a strong opinion on what this means for the trajectory around infrastructure and CapEx and things like that.

目前，我不确定这对于我们的基础设施投资和资本支出（CapEx）轨迹意味着什么，现在下定论可能还为时过早。

There are a bunch of trends that are happening here all at once.

这个领域正在发生多种趋势变化。

There's already sort of a debate around how much of the compute infrastructure that we're using is going to go towards pretraining versus as you get more of these reasoning time models or reasoning models where you get more of the intelligence by putting more of the compute into inference, whether just will mix shift how we use our compute infrastructure towards that.

目前已经有讨论在进行，关于我们使用的计算基础设施有多少会用于预训练，以及随着推理模型的进步，是否会有更多计算资源投入到推理阶段，在推理阶段投入更多算力，提升模型智能水平，这是否会导致我们在计算基础设施上的资源配置发生变化。

That was already something that I think a lot of the other labs and ourselves were starting to think more about and already seemed pretty likely even before this, that -- like of all the compute that we're using, that the largest pieces aren't necessarily going to go towards pre-training.

这其实是我们以及许多其他实验室早就在考虑的问题，甚至在这次讨论之前，就已经相当明显了，即我们所使用的计算资源中，最大的一部分可能并不会主要用于预训练。

But that doesn't mean that you need less compute, because one of the new properties that's emerged is the ability to apply more compute at inference time in order to generate a higher level of intelligence and a higher quality of service,

但这并不意味着计算需求会减少，因为一个新的趋势是，在推理阶段投入更多算力，以生成更高级别的智能并提供更高质量的服务。

which means that as a company that has a strong business model to support this, I think that's generally an advantage that we're now going to be able to provide a higher quality of service than others, who don't necessarily have the business model to support it on a sustainable basis.

这意味着，对于一个拥有强大商业模式来支持这些计算需求的公司来说，这实际上是一种优势，因为我们能够提供更高质量的服务，相比之下，那些缺乏可持续商业模式支持的公司可能无法维持同样的水平。

符合逻辑的推理。

The other thing is just that when we're building things like Meta AI, but also how we're implementing AI into all the feeds and ad products and things like that, we're just serving billions of people, which is different from, okay, you start to pretrain a model, and that model is sort of agnostic to how many people are using it, like at some level, it's going to be expensive for us to serve all of these people, because we are serving a lot of people.

另一个需要考虑的因素是，当我们开发像 Meta AI 这样的产品时，以及我们如何将 AI 应用于信息流、广告产品等领域时，我们的服务对象是数十亿用户，这与简单地训练一个 AI 模型是不同的，因为一个预训练模型在某种程度上是不受用户数量影响的，但在我们的业务中，服务如此庞大的用户群体确实是昂贵的，因为我们的用户规模极其庞大。

And so I'm not sure what the kind of net effect of all of this is.

因此，目前我无法确定所有这些因素最终会带来怎样的综合影响。

The field continues to move quickly.

这个领域的发展速度依然很快。

There's a lot to learn from releases from basically everyone who does something interesting,

我们可以从几乎所有具有创新性的发布中学习到有价值的东西，

not just the ones over the last month.

而不仅仅是最近一个月发生的事情。

We'll continue to kind of incorporate that into what we do

我们会继续将这些经验和技术整合到我们的工作中，

as well as making novel contributions to the field ourselves.

同时，我们也会在这个领域做出自己的创新贡献。

And I continue to think that investing very heavily in CapEx and infra is going to be a strategic advantage over time.

我仍然认为，在资本支出（CapEx）和基础设施（infra）方面进行大规模投资，从长期来看会是一个战略优势。

It's possible that we'll learn otherwise at some point,

当然，未来某个时候，我们可能会得出不同的结论，

but I just think it's way too early to call that.

但现在下这样的定论还为时过早。

And at this point, I would bet that the ability to build out that kind of infrastructure

目前，我仍然认为，建立这种大规模基础设施的能力，

is going to be a major advantage for both the quality of the service

将在服务质量方面带来巨大优势，

and being able to serve the scale that we want to.

同时也能确保我们能够服务我们希望覆盖的庞大用户规模。

Susan Li

I'm happy to add a little more color about our 2025 CapEx plans to your second question.

苏珊·李

很高兴就你的第二个问题，对我们的 2025 年资本支出（CapEx）计划补充一些细节。

So we certainly expect that 2025 CapEx is going to grow across all three of those components you described. Servers will be the biggest growth driver that remains the largest portion of our overall CapEx budget.

因此，我们预计 2025 年的资本支出将在你提到的三个部分全面增长。其中，服务器仍将是最大的增长动力，并继续占据我们整体资本支出预算的最大份额。

We expect both growth in AI capacity as we support our gen AI efforts and continue to invest meaningfully in core AI, but we are also expecting growth in non-AI capacity as we invest in the core business, including to support a higher base of engagement and to refresh our existing servers.

我们预计 AI 计算能力将增长，一方面是为了支持生成式 AI（Gen AI）相关工作，另一方面也会继续对核心 AI 进行重大投资。此外，我们也预计非 AI 计算能力会增长，因为我们正在投资核心业务，包括支持更高的用户互动基础，并更新现有服务器。

On the data center side, we're anticipating higher data center spend in 2025 to be driven by build-outs of our large training clusters and our higher power density data centers that are entering the core construction phase.

在数据中心方面，我们预计 2025 年的数据中心支出将增加，主要是由于我们正在建设大型训练集群，以及正在进入核心施工阶段的高功率密度数据中心。

We're expecting to use that capacity primarily for core AI and non-AI use cases.

我们预计这些数据中心的容量将主要用于核心 AI 和非 AI 相关的应用场景。

On the networking side, we expect networking spend to grow in ‘25 as we build higher-capacity networks to accommodate the growth in non-AI and core AI-related traffic along with our large Gen AI training clusters.

在网络基础设施方面，我们预计 2025 年的网络支出将增长，因为我们正在建设更高容量的网络，以满足非 AI 业务和核心 AI 相关流量的增长，同时支持大规模的生成式 AI 训练集群。

We're also investing in fiber to handle future cross-region training traffic.

此外，我们正在投资光纤，以支持未来的跨区域训练流量。

And then in terms of the breakdown for core versus Gen AI use cases, we're expecting total infrastructure spend within each of Gen AI, non-AI and core AI to increase in '25 with the majority of our CapEx directed to our core business with some caveat that, that is -- that's not easy to measure perfectly as the data centers we're building can support AI or non-AI workloads and the GPU-based servers, we procure for gen AI can be repurposed for core AI use cases and so on and so forth.

关于核心 AI 与生成式 AI 之间的投资分配，我们预计 2025 年在生成式 AI、非 AI 以及核心 AI 这三个方面的基础设施支出都会增加，其中大部分资本支出仍将投入到核心业务。不过，这一划分并不容易精确衡量，因为我们建设的数据中心既可以支持 AI 也可以支持非 AI 业务，而用于生成式 AI 的 GPU 服务器也可以被重新用于核心 AI 相关的应用，依此类推。

But overall, I would reiterate what Mark said. We are committed to building leading foundation models and applications.

但总体而言，我要重申马克的观点：我们致力于打造领先的基础模型和应用。

We expect that we're going to make big investments to support our training and inference objectives, and we don't know exactly where we are in the cycle of that yet.

我们预计将在训练和推理方面进行大规模投资，但目前尚不清楚我们处于这一投资周期的哪个阶段。

Operator

Your next question comes from the line of Ron Josey with Citigroup. Please go ahead.

主持人

下一位提问来自花旗集团的 Ron Josey，请发言。

Ron Josey

Hey, thanks for taking the question. Mark, I want to get back to your comment on getting back to the OG Facebook, and I want to understand a little bit more on the use cases and how that could expand?

Ron Josey

你好，谢谢你接受我的提问。Mark，我想回到你之前提到的“回归最初的 Facebook”（OG Facebook），我想进一步了解它的使用场景以及如何扩展？

Video is clearly a benefit. Local marketplace groups have all been positive. So any insights on the OG Facebook?

视频显然是一个优势，本地市场和社群也表现良好。那么关于“最初的 Facebook”，你有什么见解吗？

And then back to Meta AI, given the adoption we're seeing on the 600-plus MAUs, just how does the user experience evolve to? What are people doing with Meta AI? Thank you.

另外，回到 Meta AI，鉴于我们看到其月活跃用户（MAU）已超过 6 亿，用户体验如何演变？用户主要在用 Meta AI 做什么？谢谢。

Mark Zuckerberg

Okay. So for Facebook, a lot of people use Facebook every day, and it's an important part of their lives.

Mark Zuckerberg

好的，就 Facebook 而言，很多人每天都在使用它，它已经成为他们生活中重要的一部分。

And I think that there are a lot of opportunities to make it way more culturally influential than it is today.

我认为，我们有很多机会让它比今天更具文化影响力。

And I think that, that's sort of a fun and interesting goal that will take our product development in some interesting directions that we maybe have a focus on it as much over the last several years.

我认为这是一个有趣且令人兴奋的目标，它将引导我们的产品开发朝一些新的方向发展，而这些方向可能在过去几年里没有被充分关注。

So I don't know that I have anything much more specific on this other than that this is going to be one of my focus areas for this year.

所以目前我没有更多具体的内容可以分享，但可以说，这将是我今年关注的重点之一。

I mean, I think it's an investment area and something I'm going to spend some time on it.

我认为这将是一个值得投入的领域，我也会花时间在上面。

It might mean that in the near term, we make some trade-offs to kind of focus on some product areas of what we're doing ahead of just kind of maximizing business results in the near term on it.

这可能意味着，在短期内，我们会在某些业务方面做出取舍，以便优先专注于某些产品领域，而不仅仅是短期内的业务最大化。

But overall, I'm really excited about doing some exciting stuff here.

但总体来说，我对这个方向感到非常兴奋，我们将做出一些激动人心的创新。

And I'm not going to get into many specifics now, but we'll get -- we'll follow up on this over the next, I don't know, call it, a year as we start rolling it out and I think some of this will kind of get back to how Facebook was originally used back in the day.

目前我不会透露太多细节，但我们将在接下来的一年左右持续推进这个方向。当我们逐步推出这些新变化时，我认为它会让 Facebook 回归到最初的一些使用方式。

So I think it will be fun.

所以我觉得这会很有趣。

Susan Li

I'm happy to share a little bit more about Meta AI and what people are doing with it.

苏珊·李

很高兴分享更多关于 Meta AI 以及用户如何使用它的信息。

We are in a phase where we are really learning a lot from the way that people engage with Meta AI.

我们目前正处于一个阶段，在这个过程中，我们正在深入学习用户如何与 Meta AI 互动。

So from an app perspective, WhatsApp continues to see the strongest Meta AI usage across our family of apps.

从应用的角度来看，WhatsApp 仍然是我们整个应用生态中 Meta AI 使用最活跃的平台。

People there are using it most frequently for information seeking and educational queries along with emotional support use cases.

用户在 WhatsApp 上最常使用 Meta AI 进行信息查询、教育相关的问题，以及情感支持相关的用途。

Most of the WhatsApp engagement is in one-on-one threads, though we see some usage in group messaging.

大多数 WhatsApp 上的 Meta AI 互动都发生在一对一的聊天中，尽管我们也看到了一些群聊中的使用情况。

And on Facebook, which is the second largest driver of Meta AI engagement, we're seeing strong engagement from our feed deep dives integration that lets people ask Meta AI questions about the content that is recommended to them.

在 Facebook 上，Meta AI 的使用量排名第二。我们看到，与“Feed 深度探索”功能的整合推动了较强的互动，用户可以向 Meta AI 询问关于推荐内容的问题。

So across, I would say, all query types, we continue to see signs that Meta AI is helping people leverage our apps for new use cases.

总体而言，我们在各种查询类型中都观察到，Meta AI 正在帮助用户探索新的使用场景。

We talked about information gathering, social interaction and communication. Lots of people use it for humor and casual conversation.

除了信息收集、社交互动和沟通，很多人还用它来进行幽默对话和轻松聊天。

They use it for writing and editing research recommendations.

用户还会使用 Meta AI 进行写作、编辑以及研究推荐。

And as we look forward to 2025 in our Meta AI road map, we are really focused on doing more to make it feel more personalized.

展望 2025 年，我们在 Meta AI 的发展路线图中，重点关注如何让它变得更加个性化。

So I would say some of the most exciting features we're working on, including improving sort of the memory dimension of the Meta AI experience.

我们正在研发的一些最令人兴奋的功能之一，就是提升 Meta AI 体验中的“记忆能力”。

chatGPT看样子是为他人做嫁衣，最适用的场景是社交软件，微信和Facebook。

We'll be able to remember certain details that people share in one-on-one chats, for example, and use those details to personalize its responses.

例如，它将能够记住用户在一对一聊天中分享的某些信息，并利用这些细节来个性化其回应。

And then really increasing its ability to deliver great content recommendations and enhance really what makes Facebook and Instagram so valuable for people today.

此外，我们还在大幅提升 Meta AI 的内容推荐能力，进一步增强 Facebook 和 Instagram 的核心价值，使它们对用户更加有吸引力。

Operator

Your next question comes from the line of Ken Gawrelski with Wells Fargo. Please go ahead.

主持人

下一位提问来自富国银行的 Ken Gawrelski，请发言。

Ken Gawrelski

Thank you very much. Two for me, please.

Ken Gawrelski

非常感谢，我有两个问题。

First, could you talk a little bit -- I know you talked a little bit on the capital intensity side and the recent developments, and it's hard to see it's hard to tell yet where things are going?

首先，我知道你们之前谈到了一些资本密集度方面的情况以及最近的发展，但目前还很难判断未来的趋势。

But maybe you could just talk a little bit more near term, '25, the CapEx budget you laid out or the CapEx forecast.

但是，你能否就 2025 年的资本支出（CapEx）预算或预测再多谈一些？

Could you talk a little bit about the constraints you're seeing or where you're seeing constraints, either internally resources planning or externally and any one -- any parts of the ecosystem?

你们目前在执行资本支出计划时遇到了哪些限制？无论是内部资源规划，还是外部因素，包括整个生态系统中的任何环节，都有哪些制约因素？

And then on the second one, I'm curious, as you think about your needs for hiring and we just think about -- we know you gave the OpEx guide for this year.

第二个问题是关于招聘需求。你们已经公布了今年的运营支出（OpEx）指引，但未来的招聘需求是怎样的？

But as we think about future needs for hiring, could you just give us a sense of how we should think about that?

未来在招聘方面，我们应该如何看待公司的需求？

You announced the performance-related reductions earlier this -- for early this year.

你们今年早些时候宣布了基于绩效的裁员计划。

Could you just talk about how we should be thinking about that '26, '27 and beyond? Thank you.

你能否谈谈 2026 年、2027 年及之后的招聘需求趋势？谢谢。

Susan Li

Sure. I'm happy to take both of those.

苏珊·李

当然，我很高兴回答这两个问题。

So on your first question on just where do we see constraints in our ability to execute against our CapEx plans.

关于你的第一个问题，即我们在执行资本支出计划时面临的限制。

Obviously, we are staying on top of supply availability.

显然，我们正在密切关注供应链的可用性。

That is certainly one of the factors that will influence our CapEx spend in 2025, but we don't really have any updates to share on supply availability right now.

这无疑是影响我们 2025 年资本支出的因素之一，但目前我们没有关于供应情况的最新消息可提供。

We are planning to significantly ramp up deployment of GPUs in 2025, and we'll continue to engage with our vendors and invest in our own silicon to meet those needs.

我们计划在 2025 年大规模增加 GPU 部署，并将继续与供应商合作，同时投资自研芯片，以满足这些需求。

When you asked how to think about capital intensity, we're not really -- as both Mark and I alluded to in our prior comments, I think it is really too early to determine what long-run capital intensity is going to look like.

关于如何看待资本密集度问题，就像 Mark 和我之前提到的，我们认为现在判断长期资本密集度还为时过早。

There are so many different factors. The pace of advancement in underlying models, how efficient can they be?

影响因素非常多，比如底层模型的进步速度，它们的效率如何提升？

What is the adoption and use case of our Gen AI products, what performance gains come from next-generation hardware innovations, both our own and third-party?

我们的生成式 AI 产品的应用和使用场景如何？下一代硬件（包括自研和第三方硬件）的性能提升会带来哪些收益？

And then ultimately, what monetization or other efficiency gains our AI investments unlock.

最终，我们的 AI 投资能够带来怎样的变现能力或其他效率提升。

So again, I think we are sort of early in the journey here, and we don't have -- I would say we don't have kind of anything to share about long-run capital intensity yet.

所以总体来看，我们仍然处于早期阶段，目前还无法就长期资本密集度提供明确的信息。

Your second question was about thinking about hiring needs.

你的第二个问题是关于招聘需求。

So it's a good segue after infrastructure, employee compensation is the next largest driver of expense growth in 2025.

在基础设施之外，员工薪酬是 2025 年支出增长的第二大驱动因素。

And here, growth in employee comp and headcount more broadly is primarily driven by those areas that I mentioned, infrastructure monetization, generative AI, Reality Labs and regulation and compliance.

员工薪酬和整体人员增长主要由以下领域推动：基础设施、变现、生成式 AI、Reality Labs 以及监管和合规。

And those generally are more technical organizations. That means that it is a higher cost base relative to business functions where we are also expecting to keep headcount growth constrained.

这些通常是技术导向的团队，因此相较于其他业务职能部门，它们的成本基数较高。与此同时，我们预计将在业务职能部门控制人员增长。

And I would say we are -- we're focused on running the company efficiently.

总体而言，我们的重点是高效运营公司。

But at the same time, it is -- we feel like we're in a critical period in terms of making sure that we are investing to win, and we want to make sure that we staff those priority areas in a way that really positions us to best do that.

但与此同时，我们认为当前是一个关键时期，我们必须确保在重要领域进行投资，以保持竞争力。因此，我们会优先确保这些重点领域的人员配置，以实现最佳效果。

Kenneth Dorell

Krista, we have time for one last question.

肯尼思·多雷尔

Krista，我们还有时间回答最后一个问题。

Operator

And that question comes from the line of Ross Sandler with Barclays. Please go ahead.

主持人

最后一个问题来自巴克莱银行的 Ross Sandler，请发言。

Ross Sandler

Yes. One for Mark, on agents. So we all saw OpenAI's operator demo last week.

Ross Sandler

好的，我的问题是关于 AI 代理（agents）的，提问给 Mark。我们上周都看到了 OpenAI 的 Operator 演示。

So Mark, as the industry moves from chat to agentic behavior and more commercial intent moves into these AI products?

那么，Mark，随着行业从聊天式交互（chat）向代理式行为（agentic behavior）演进，同时更多商业意图融入 AI 产品？

I guess how are you thinking about monetization potential for Meta AI?

你是如何看待 Meta AI 的变现潜力的？

And then how might Llama 4 reasoning help drive some of these new agentic experiences for Meta AI? Thank you.

此外，Llama 4 的推理能力如何助力 Meta AI 推动这些新的代理式体验？谢谢。

Mark Zuckerberg

Yes. So I guess a couple of things that I'd say on this.

马克·扎克伯格

是的，我有几点想说的。

One is when you're thinking about agents and reasoning, a lot of this is about being able to perform multistep tasks.

首先，当我们谈论 AI 代理和推理能力时，其中很大一部分是关于执行多步骤任务的能力。

So right now, the way that a lot of these systems work as you kind of say something and then it responds and it's almost chat like.

目前，大多数 AI 系统的工作方式是用户输入信息后 AI 立即响应，基本上是聊天（chat）式交互。

But I think that the direction that it's going is you're going to be able to give it an intent or a task and it's going to be able to go off and use sort of an arbitrary amount of compute as much as you want to use on it to be able to do a task.

但我认为，未来的方向是，你可以给它一个意图或任务，然后 AI 代理可以自主执行，不受限地调用计算资源，以完成任务。

Some of the tasks might be pretty simple for people go buy a specific thing.

有些任务可能比较简单，比如帮用户购买某样东西。

Some of them might be really hard, like go write an app or optimize this code and like really make it as good as possible.

但有些任务可能会非常复杂，比如开发一个应用程序、优化一段代码，并尽可能提升其质量。

And that type of thing, I think, is just going to start becoming more and more prevalent over the next a year or two.

我认为，这类 AI 代理能力将在未来一到两年内越来越普及。

So I think it's very exciting. It's sort of we'll feel in some ways like the current products are just getting smarter and others, it will feel like sort of a new form factor, because it won't be as much like chat.

所以我觉得这很令人兴奋。从某些角度来看，这可能会让现有产品变得更智能，而从另一些角度来看，它可能会成为一种全新的交互方式，而不仅仅是聊天式的体验。

But it's sort of another generation of these products. So I think it's just in general, there's a lot to build and be excited about.

这将是一代新的 AI 代理产品，未来仍有很多值得开发和期待的地方。

I guess my note of caution or just my kind of periodic reminder on our product development process, if you will, is we build these products.

我想提醒大家，或者说作为对我们产品开发流程的定期说明，我们的产品是这样构建的。

We try to scale them to reach usually 1 billion people or more.

我们通常会努力将其规模扩大到 10 亿以上的用户。

And it's at that point once they're at scale that we really start focusing on monetization.

当产品达到这个规模时，我们才会真正开始关注变现。

So sometimes we'll experiment with monetization before, we're running some experiments with Threads now, for example.

有时，我们会在此之前进行一些变现实验，例如，我们目前正在 Threads 上进行一些实验。

But we typically don't really ramp these things up or see them as meaningfully contributing to the business until we reach quite a big scale.

但通常情况下，我们不会在产品规模较小的时候大规模推进变现，也不会认为它对业务有重大贡献，直到它真正达到相当大的规模。

So the thing that I think is going to be meaningful this year is the kind of getting of the AI product to scale.

所以我认为，今年最重要的事情是让 AI 产品实现大规模普及。

Last year was sort of the introduction and starting to get to be used.

去年，我们主要是推出这些产品，并开始让用户使用。

This year my kind of expectation and hope is that we will be at a sufficient scale and have sufficient kind of flywheel of people using it and improvement from that, that this will have a durable advantage.

今年，我的期望是，我们能够达到足够的规模，并形成足够的飞轮效应——更多的人使用 AI 产品，产品不断改进，从而形成长期的竞争优势。

But that doesn't mean that it's going to be a major contributor to the business.

但这并不意味着它会在今年成为业务的主要贡献者。

This year the improvements of the business are going to be taking the AI methods and applying them to advertising and recommendations and feeds and things like that.

今年，业务上的改进将主要体现在 AI 方法的应用，比如将 AI 用于广告、推荐系统和信息流等方面。

So the actual business opportunity for Meta AI and AI Studio and business agents and people interacting with these AIs remains outside of '25 for the most part.

因此，Meta AI、AI Studio、商业 AI 代理（business agents）以及人与 AI 交互的实际商业机会，大部分仍然是在 2025 年之后。

And I think that's an important thing for us to communicate and for people to internalize as you're thinking about our prospects here.

我认为，这一点非常重要，我们需要向大家清晰传达，并让大家在评估我们的前景时考虑到这一点。

But nonetheless, we've run a process like this many times.

尽管如此，我们已经多次成功执行类似的产品开发流程。

We build a product. We make it good. We scale it to be large. We build out the business around it. That's what we do.

我们先打造产品，然后优化体验，扩展规模，最后围绕产品建立商业模式。这就是我们的做法。

I'm very optimistic, but it's going to take some time.

我对此非常乐观，但这需要时间。

Kenneth Dorell

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

肯尼思·多雷尔

非常好。感谢大家今天的参与，我们非常感谢你们的时间，期待尽快与大家再次交流。

Operator

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

主持人

本次电话会议到此结束。感谢您的参与，现在可以断开连接。

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