Good afternoon. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to the Meta First Quarter Earnings Conference Call. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, there will be a question-and-answer session. And this call will be recorded. Thank you very much. Kenneth Dorell, Meta's Director of Investor Relations, you may begin.

Thank you. Good afternoon, and welcome to Meta's first quarter 2025 earnings conference call. Joining me today to discuss our results 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 Annual Report on Form 10-K filed with the SEC. We undertake no obligation to update any forward-looking statement. 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. And now I'd like to turn the call over to Mark.

All right. Thanks, Ken. Thanks, everyone, for joining today. We've had a strong start to the year. Our community keeps growing with more than 3.4 billion people now using at least one of our apps each day. Our business is also performing very well, and I think we're well-positioned to navigate the macroeconomic uncertainty. The major theme right now, of course, is how AI is transforming everything we do and, as we continue to increase our investments and focus more for our resources on AI, probably useful today to lay out the five major opportunities that we are focused on. Those are improved advertising, more engaging experiences, business messaging, Meta AI, and AI devices. And these are each long-term investments that are downstream from us building general intelligence and leading AI models and infrastructure. Even with our significant investments, we don't need to succeed in all of these areas to have a good ROI. But if we do, then I think that we will be wildly happy with the investments that we are making. The first opportunity is improved advertising. Our goal is to make it so that any business can basically tell us what objective they're trying to achieve, like selling something or getting a new customer and how much they're willing to pay for each result, and then we just do the rest. Businesses used to have to generate their own ad creative and define what audiences they wanted to reach, but AI has already made us better at targeting and finding the audiences that will be interested in their products than many businesses are themselves, and that keeps improving. And now AI is generating better creative options for many businesses as well. I think that this is really redefining what advertising is into an AI agent that delivers measurable business results at scale. And if we deliver on this vision, then over the coming years, I think that the increased productivity from AI will make advertising a meaningfully larger share of global GDP than it is today. In just the last quarter, we are testing a new ads recommendation model for reels, which has already increased conversion rates by 5%, and we're seeing 30% more advertisers are using AI creative tools in the last quarter as well. The second opportunity is more engaging experiences. This will come in two forms, better recommendations for existing content types and better new types of content. In the last six months, improvements to our recommendation systems have led to a 7% increase in time spent on Facebook, a 6% increase on Instagram, and 35% on Threads. Threads now also has more than 350 million monthly actives and continues to be on track to become our next major social app. In addition to better recommendations for existing content types, AI is also enabling the creation of better content as well. Some of this will be helping people produce better content to share themselves. Some of this will be AI generating content directly for people that is personalized for them. Some of this will be in existing formats like photos and videos, and some of it will be increasingly interactive. I've often talked about this long-term trend of content becoming richer over time. Our feeds started mostly with text and then became mostly photos; we all got mobile phones with cameras, and then became mostly video when mobile networks became fast enough to handle that well. We are now in the video era, but I don't think that this is the end of the line. In the near future, I think that we're going to have content in our feeds that you can interact with, that will interact back with you rather than you just watching it. Over the long term, as AI unlocks more productivity in the economy, I also expect that people will spend more of their time on engaging experiences across all of these apps. The third opportunity is business messaging. Right now the vast majority of our business is advertising and feeds on Facebook and Instagram. But WhatsApp now has more than 3 billion monthly actives with more than 100 million people in the U.S. and growing quickly there. Messenger is also used by more than a billion people each month, and there are now as many messages sent each day on Instagram as there are on Messenger. So business messaging should be the next pillar of our business. In countries like Thailand and Vietnam, where there is a low cost of labor, we see many businesses conduct commerce through our messaging apps. There's actually so much business through messaging that those countries are both in our Top 10 or 11 by revenue, even though they're ranked in the 30s in global GDP. This phenomenon hasn't yet spread to developed countries because the cost of labor is too high, to make this a profitable model before AI, but AI should solve this. So in the next few years, I expect that just like every business today has an email address, social media account, and website, they'll also have an AI business agent that can do customer support and sales, and they should be able to set that up very easily given all the context that they've already put into our business platforms. And we're going to have more to share on upcoming calls about our progress in this area. The fourth opportunity is Meta AI. Across our apps, there are now almost a billion monthly actives using Meta AI. Our focus for this year is deepening the experience and making AI the leading personal AI with an emphasis on personalization, voice conversations, and entertainment. I think that we're all going to have an AI that we talk to throughout the day, while we're browsing content on our phones, and eventually, as we're going through our days with glasses. And I think that this is going to be one of the most important and valuable services that has ever been created. In addition to building Meta AI into our apps, we just released our first Meta AI standalone app. It is personalized, so you can talk to it about interests that you've shown while browsing reels or different content across our apps. And we built a social feed into it so you can discover entertaining ways that others are using Meta AI, and initial feedback on the app has been good so far. Over time, I expect that the business opportunity for Meta AI to follow our normal product development playbook. First, we build and scale the product, and then once it is at scale, then we focus on revenue. In this case, I think that there will be a large opportunity to show product recommendations or ads, as well as a premium service for people who want to unlock more compute for additional functionality or intelligence. But I expect that we're going to be largely focused on scaling and deepening engagement for at least the next year before we'll really be ready to start building out the business here. The fifth opportunity is AI devices, which is increasingly how we are thinking about our work on the next generation of computing platforms. Glasses are the ideal form factor for both AI and the Metaverse. They enable you to let an AI see what you see, hear what you hear, and talk to you throughout the day, and they let you blend the physical and digital worlds together with holograms. More than a billion people worldwide wear glasses today. And it seems highly likely that these will become AI glasses over the next five to ten years. Building the devices that people use to experience our services lets us deliver the highest quality AI and social experiences, and this will serve as an amplifier on all of the opportunities I've mentioned so far, as well as unlocking some new opportunities as well. Ray-Ban Meta AI Glasses have tripled in sales in the last year, and the people who have them are using them a lot. We've got some exciting new launches with our partner, EssilorLuxottica, later this year as well that should expand that category and add some new technological capabilities to the glasses. On Quest, we are also seeing deeper engagement as Quest 3 makes VR accessible to more people, and more people are creating experiences in Horizon with AI tools. Now, everything that I've talked about today is built on top of our AI models and our infrastructure. We released the first Llama 4 models earlier this month. They are some of the most intelligent, best multimodal, lowest latency, and most efficient models that anyone has built. We have more models on the way, including the massive Llama 4 behemoth model. Overall, we are focused on building full general intelligence. All of the opportunities that I've discussed today are downstream of delivering general intelligence and doing so efficiently. The pace of progress across the industry and the opportunities ahead for us are staggering. I want to make sure that we're working aggressively and efficiently, and I also want to make sure that we are building out the leading infrastructure and teams that we need to achieve our goals. So to that end, we are accelerating some of our efforts to bring capacity online more quickly this year, as well as some longer-term projects that will give us the flexibility to add capacity in the coming years as well. And that has increased our planned investment for this year. More broadly, this has been a good start to what I expect will continue to be an intense year. We've got a lot more exciting work in the pipeline that I'm looking forward to sharing soon. I continue to think that this year is going to be a pivotal moment for our industry, and I'm grateful for everyone who is working so hard at the Company to deliver all this amazing technology and new experiences. As always, thank you all for being on this journey with us, and now, Susan.

Thanks, Mark, and good afternoon, everyone. Let's begin with our consolidated results. All comparisons are on a year-over-year basis unless otherwise noted. Q1 total revenue was $42.3 billion, up 16% or 19% on a constant currency basis. Q1 total expenses were $24.8 billion, up 9% compared to last year. In terms of the specific line items, cost of revenue increased 14%, driven primarily by higher infrastructure costs and payments to partners, partially offset by a benefit from the previously announced extension of server useful lives. R&D increased 22%, mostly due to higher employee compensation and infrastructure costs. Marketing and sales increased 8%, driven mainly by an increase in professional services related to our ongoing platform integrity efforts. G&A decreased 34%, driven primarily by lower legal-related costs. We ended Q1 with over 76,800 employees, up 4% quarter-over-quarter. First quarter operating income was $17.6 billion, representing a 41% operating margin. Our tax rate for the quarter was 9%, as we recognized excess tax benefits from share-based compensation due to the increase in our share price versus prior periods. Net expenditures, including principal payments on finance leases, were $13.7 billion, driven by investments in servers, data centers, and network infrastructure. Free cash flow was $10.3 billion. We repurchased $13.4 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders, ending the quarter with $70.2 billion in cash and marketable securities, and $28.8 billion in debt. Moving now to our segment results. I'll begin with our Family of Apps segment. Our community across the Family of Apps continues to grow, and we estimate more than 3.4 billion people used at least one of our Family of Apps on a daily basis in March. Q1 total Family of Apps revenue was $41.9 billion, up 16% year-over-year. Q1 Family of Apps' ad revenue was $41.4 billion, up 16% or 20% on a constant currency basis. Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth. On a user geography basis, ad revenue growth was strongest in the Rest of World and North America at 19% and 18%, respectively. Europe and Asia-Pacific grew 14% and 12%. In Q1, the total number of ad impressions served across our services increased 5%, and the average price per ad increased 10%. Impression growth was mainly driven by Asia-Pacific. Pricing growth benefited from increased advertiser demand, in part driven by improved ad performance. This was partially offset by impression growth, particularly from lower monetizing regions and surfaces. Family of Apps' other revenue was $510 million, up 34%, driven mostly by business messaging revenue growth from our WhatsApp Business platform, as well as Meta Verified subscriptions. We continue to direct the majority of our investments toward the development and operation of our Family of Apps. In Q1, Family of Apps' expenses were $20.1 billion, representing 81% of our overall expenses. Family of Apps' expenses were up 10%, mainly due to growth in employee compensation and infrastructure costs, which were partially offset by lower legal-related expenses. Family of Apps' operating income was $21.8 billion, representing a 52% operating margin. Within our Reality Labs segment, Q1 revenue was $412 million, down 6% year-over-year due to lower Meta Quest sales, which were partially offset by increased sales of RayBan Meta AI glasses. Reality Labs' expenses were $4.6 billion, up 8% year-over-year, driven primarily by higher employee compensation. Reality Labs' operating loss was $4.2 billion. 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, we're focused both on enhancing our core Family of Apps today and building the next generation of devices and experiences through Reality Labs. I'll start with our Family of Apps. In the first quarter, we saw strong growth in video consumption across both Facebook and Instagram, particularly in the U.S., where video time spent grew double-digits year-over-year. This growth continues to be driven primarily by ongoing enhancements to our recommendation systems, and we see opportunities to deliver further gains this year. We're also progressing on longer-term efforts to develop innovative new approaches to recommendations. A big focus of this work will be on developing increasingly efficient recommendation systems, so that we can continue scaling up the complexity and compute used to train our models while avoiding diminishing returns. There are promising techniques we're working on that will incorporate the innovations from LLM model architectures to achieve this. Another area that is showing early promise is integrating LLM technology into our content recommendation systems. For example, we're finding that LLM's ability to understand a piece of content more deeply than traditional recommendation systems can help better identify what is interesting to someone about a piece of content leading to better recommendations. We began testing using Llama and Threads recommendation systems at the end of last year, given the app's text-based content, and have already seen a 4% lift in time spent from the first launch. It remains early here, but a big focus this year will be on exploring how we can deploy this for other content types, including photos and videos. We also expect this to be complementary to Meta AI, as it can provide more relevant responses to people's queries by better understanding their interests and preferences through their interactions across Facebook, Instagram, and Threads. Earlier this year, we began testing the ability for Meta AI to better personalize its responses by remembering certain details from people's prior queries and considering what that person engages with on our apps. We are already seeing this lead to deeper engagement with people we've rolled it out to, and it is now built into Meta AI across Facebook, Instagram, Messenger, and our new standalone Meta AI app in the U.S. and Canada. We're also continuing to focus on helping people connect over content. In Q1, we launched a new experience on Instagram in the U.S. that consists of a feed of content your friends have left a note on or liked, and we're seeing good results. We also just launched Blend, which is an opt-in experience in direct messages that enables you to blend your reels algorithm with your friends to spark conversations over each other's interests. These features all lean into Instagram's position at the intersection of entertainment and social connection. WhatsApp remains at its core a private messaging app, but it has evolved to also become a place people come to get updates from accounts they are connected to or follow. Today, there are tens of billions of views of status posts on WhatsApp each day, and we continue to invest in the Updates tab as a place people can go to do more. Creators remain another big focus for us, and we're investing in tools to help them produce the best original content on our platforms. Last week, we launched our standalone Edits app, which supports the full creative process for video creators from inspiration and creation to performance insights. Edits has an ultra-high resolution short-form video camera and includes generative AI tools that enable people to remove the background of any video or animate still images, with more features coming soon. Moving to Reality Labs, we're seeing very strong traction with RayBan Meta AI glasses with over 4 times as many monthly actives as a year ago, and the number of people using voice commands is growing even faster as people use it to answer questions and control their glasses. This month, we fully rolled out live translations on RayBan Meta AI glasses to all markets for English, French, Italian, and Spanish. Now, when you are speaking to someone in one of these languages, you'll hear what they say in your preferred language through the glasses in real time. 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 optimize ad supply across each service to better deliver ads at the time and place they are most relevant to people. We are also starting to introduce ads on unmonetized surfaces like Threads, which we opened up to all eligible advertisers this month to reach people in over 30 different markets to start, including the U.S. As we do for any newly monetized surface, we expect to gradually ramp ad supply as we optimize the ad formats and ensure they feel native to the app. We don't expect Threads to be a meaningful driver of overall impression or revenue growth in 2025. The second part of increasing monetization efficiency is improving marketing performance. We're continuing to improve our ad systems by developing new modeling technologies to more efficiently predict the right ad to show. In Q1, we introduced our new Generative Ads Recommendation Model, or GEM for ads ranking. This model uses a new architecture we developed that is twice as efficient at improving ad performance for a given amount of data and compute. This efficiency gain enabled us to significantly scale up the amount of compute we use for model training with GEM trained on thousands of GPUs, our largest cluster for ads training to date. We began testing the new model for ads recommendations on Facebook Reels earlier this year and have seen up to a 5% increase in ad conversions. We're now rolling it out to additional services across our apps. On the ads product side, we're seeing continued momentum with our Advantage+ suite of AI-powered solutions. We've been encouraged by the initial tests of our streamlined campaign creation flow for sales, app, and lead campaigns, which starts with Advantage+ turned on from the beginning for advertisers. In April, we rolled this out to more advertisers and expect to complete the global rollout later this year. We're also seeing strong adoption of Advantage+ creative. This week, we are broadening access of video expansion to Facebook Reels for all eligible advertisers, enabling them to automatically adjust the aspect ratio of their existing videos by generating new pixels in each frame to optimize their ads for full-screen surfaces. We also rolled out Image Generation to all eligible advertisers, and this quarter, we plan to continue testing a new virtual try-on feature that uses Gen AI to place clothing on virtual models, helping customers visualize how an item may look and fit. Last, we continue to evolve our ads platform to drive results that are optimized for each business's objectives and the way they measure value. One example of this is our incremental attribution feature, which enables advertisers to optimize for driving incremental conversions or conversions we believe would not have occurred without an ad being shown. We're seeing strong results in testing so far with advertisers using incremental attribution in tests, seeing an average 46% lift in incremental conversions compared to their business-as-usual approach. We expect to make this available to all advertisers in the coming weeks. Next, I would like to discuss our approach to capital allocation. Our primary focus remains investing capital back into the business, with infrastructure and talent being our top priorities. Starting with headcount, our hiring continues to be targeted at technical roles within our company priorities. In the first quarter, the significant majority of the roughly 2,800 employees we added were to support our priorities of monetization, infrastructure, generative AI, regulation and compliance, and Reality Labs. On infrastructure, we have two primary focuses to meet the growing compute needs of our services and AI initiatives. The first way is by significantly scaling up our infrastructure footprint. Our CapEx growth this year is going toward both generative AI and core business needs, with the majority of overall CapEx supporting the core. We expect the significant infrastructure footprint we are building will not only help us meet the demands of our business in the near term, but also provide us an advantage in the quality and scale of AI services we can deliver. We continue to build this capacity in a way that grants us maximum flexibility in how and when we deploy it to ensure we have the agility to react to how the technology and industry develop in the coming years. The second way we're meeting our compute needs is by increasing the efficiency of our workloads. In fact, many of the innovations coming out of our ranking work are focused on increasing the efficiency of our systems. This emphasis on efficiency is helping us deliver consistently strong returns from our core AI initiatives. For example, we shared on the Q3 2024 call that improvements to our AI-driven feed and video recommendations drove a roughly 8% lift in time spent on Facebook and a 6% lift on Instagram over the first nine months of last year. Since then, we've been able to deliver similar gains in just six months’ time with improvements to our AI recommendations delivering 7% and 6% time spent gains on Facebook and Instagram, respectively. Before moving to our financial guidance, I want to acknowledge the dynamic macro environment and note that our range reflects the potential for a wider set of outcomes. We continue to feel good about the fundamental drivers of revenue growth and believe the past work we've done to streamline our operations and cost profile puts us in a strong position to navigate a variety of outcomes. Moving to our financial outlook. We expect second quarter of 2025 total revenue to be in the range of $42.5 billion to $45.5 billion. Our guidance assumes foreign currency is an approximately 1% tailwind to year-over-year total revenue growth based on current exchange rates. Turning now to the expense outlook. We expect full year 2025 total expenses to be in the range of $113 billion to $118 billion, lowered from our prior outlook of $114 billion to $119 billion. Turning now to the CapEx outlook. We anticipate our full year 2025 capital expenditures, including principal payments on finance leases, will be in the range of $64 billion to $72 billion, increased from our prior outlook of $60 billion to $65 billion. This updated outlook reflects additional data center investments to support our AI efforts as well as an increase in the expected cost of infrastructure hardware. The majority of our CapEx in 2025 will continue to be directed to our core business. 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%. In addition, we continue to monitor an active regulatory landscape, including legal and regulatory headwinds in the EU and the US, that could significantly impact our business and our financial results. The European Commission recently announced its decision that our subscription for no ads model is not compliant with the DMA. Based on feedback from the European Commission in connection with the DMA, we expect we will need to make some modifications to our model, which could result in a materially worse user experience for European users and a significant impact on our European business and revenue as early as the third quarter of 2025. We will appeal the Commission's DMA decision, but any modifications to our model may be imposed before or during the appeal process. In closing, this was another solid quarter for our business. We believe the investments we're making across our company priorities will position us well in the coming years to continue delivering engaging services for our community, compelling results for advertisers, and strong business performance. With that, Krista, let's open up the call for questions.

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

Thank you for taking my questions. I have two. The first one is on Llama. Mark, as the LLM landscape continues to evolve and become increasingly competitive, can you talk us through some of the key areas of advancement you are focusing on and are excited about as we consider future versions of Llama? The second question is about Meta AI, which has almost a billion users globally. Can you provide insights on the traction you're seeing in the US and the types of recurring user behaviors in the early Meta AI use cases? Thank you.

Sure. I can discuss the LLMs. Regarding Meta AI usage, I’m not sure if we have more statistics to provide at the moment. I'll let Susan handle any updates on that. As for the LLM, we are making significant progress across various areas. We want to develop this technology for two main reasons: first, it is crucial for our business to maintain control over our future and not rely on another company for something so essential. Second, we aim to ensure that the development of this technology is tailored to suit our infrastructure and the specific use cases we envision. To this end, Llama 4, with 17 billion parameters per expert, was specifically designed for our infrastructure to deliver low latency experiences optimized for voice interaction. For voice conversations with AI, low latency is essential; it ensures there is no significant delay between when a user stops speaking and when the AI responds. Every aspect of the model's design, our research efforts, and the techniques we implement are aligned with this goal. Another area we've emphasized is the context window length, where we excel within the industry. This is vital for us as we focus on providing a personalized user experience. One way to incorporate personalization into an LLM is through the context window, which can accommodate extensive background information shared by users across our apps. These elements illustrate the types of products we are developing and the specific technical decisions and research focus we've chosen to create the user experiences we aim to deliver. I could elaborate further, but it's also essential to mention the importance of creating larger models like Behemoth. While we may not deploy these models in production, they are crucial for the technique of distilling intelligence from larger models. The Llama 4 models we have already published and those we will create in the future are essentially distilled from the Behemoth model, achieving 90% to 95% of the larger model's intelligence while being much lower in latency and more efficient. These factors are all significant. We wouldn’t be able to perform such distillation with other closed models, which gives you an insight into our approach to this development. Moreover, the models and infrastructure we are building will support all the opportunities I mentioned earlier.

Brian, I'm happy to answer your second question about Meta AI. The top use case right now for Meta AI from a query perspective is really around information gathering as people are using it to search for and understand and analyze information, followed by social interactions from casual chatting to more in-depth discussion or debate. We also see people use it for writing assistance, interacting with visual content, seeking help. And we see Meta users engage with Meta AI from several different entry points. WhatsApp continues to see the strongest Meta AI usage across our family of apps. Most of that WhatsApp engagement is in one-on-one Threads, followed by Facebook, which is the second largest driver of Meta AI engagement, where we're seeing strong engagement from our Feed deep-dives integration that lets people ask Meta AI questions about the content that's recommended to them. And we're obviously excited about the launch of the Meta AI standalone app.

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

Thanks so much for taking the question. Maybe following up on Brian's question and coming at it from a different angle, and appreciate the color on the use cases you're seeing today for Meta AI. How would you suspect those use cases evolve with a standalone app? Can you bring us into a little bit the decision process to do a standalone app, what that might change in terms of utility, frequency, or scale relative to what you see inside Family of Apps today? And how do you think about positioning Meta AI as a standalone app against the competitive landscape today of other standalone sorts of consumer AI apps? Thank you.

Yes, I can discuss that. We plan to focus on both integrating it more into our Family of Apps and creating a standalone experience. Some users might prefer quicker access or a more comprehensive feature set than what can be included in an app like WhatsApp, making the standalone app quite valuable. I also believe the standalone app will be especially significant in the United States, as WhatsApp is the largest platform for using Meta AI. This integration enhances the experience for users who want to text an AI. While over 100 million people use WhatsApp in the U.S., we are not the leading messaging app there; that title belongs to iMessage. We aspire to lead in the future, but our situation in the U.S. differs from our global presence with WhatsApp. Therefore, the Meta AI app as a standalone will be particularly crucial in the U.S. for establishing our leadership as the preferred personal AI. We will continue to enhance experiences across all these various areas.

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

Great. Thank you. A couple of questions. Just on the guide in the second quarter, there are reports of potential supply issues in e-commerce. How you thought about that in the guide, and maybe how you're thinking about it for the back half? And then on a bigger picture question, your CapEx spend is now on close to some hyperscalers with very big client bases? Just help us conceptualize the kind of ecosystem you're building with your CapEx. I know you gave a lot of help on the intro, but maybe the ROI works without direct enterprise spend to drive revenues. How you're thinking about that? Thank you.

Thanks, Justin. There is some uncertainty regarding our Q2 guidance, particularly about how the macro environment evolves and its potential impact on various segments of our business. Our revenue outlook for Q2 reflects this uncertainty, which is why we've set a range of $3 billion to accommodate different possible outcomes. We've noticed reduced spending from US-based e-commerce exporters coming from Asia, likely in anticipation of the de minimis exemption ending on May 2nd. Although some of that spending has shifted to other markets, the overall spending from these advertisers is below the levels seen before April. However, our outlook for Q2 is based on trends observed in April, which have been generally positive. It's still early, and it's difficult to predict how things will unfold over the quarter and into the rest of the year. Your second question relates to our increased investment in capital expenditures. We believe that enhancing our world-class infrastructure provides a significant advantage in developing leading AI technologies and services in the coming years. There are also numerous opportunities to enhance our core business by allocating more computing power to our ads and recommendation efforts. Despite the capacity we plan to bring online in 2025, we are struggling to keep up with the demand for computing resources across the company. Therefore, we will continue to invest significantly in our infrastructure while aiming to build this capacity in a manner that allows us maximum flexibility in how and when we utilize it in the years ahead, enabling us to adapt to market and technological changes.

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

Thanks for taking the questions. I just wanted to follow up on CapEx and infrastructure spending. Just on the higher range for CapEx, can you just help us understand how much of that is tied to the additional data center investments versus the increased hardware costs, and really what's driving those higher hardware costs? And then separately, there have been some articles suggesting that you've been looking to partner to share some of the costs of the AI infrastructure build-out. Can you just help us understand your thought process there and some of the pros and cons of going alone versus partnering? Thanks.

Thanks, Doug. Our updated capital expenditure outlook reflects increased spending on data centers this year as we adjust our build strategy to enhance capacity more rapidly in 2025 and 2026. We haven't detailed the specific factors, but the elevated costs for infrastructure hardware this year are largely due to suppliers operating in various countries, creating considerable uncertainty amid ongoing trade discussions. This uncertainty is reflected in the broader range we are providing. We are also implementing measures to optimize our supply chain, and our outlook represents our best understanding of the potential impact of this uncertainty. Regarding the second part of your question, we are pleased to have partners like AWS and Azure investing alongside us and assisting in bringing Llama to market. We continually seek opportunities to deepen or expand these partnerships, but we are funding the infrastructure necessary for training Llama, and we do not anticipate any changes to that arrangement at this time.

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

Yes, thanks for taking the questions. Mark, in your conversation last night with Satya, I think you both discussed a bit around kind of the portion of code being written internally by AI. Kind of back to some of your previous comments around this being a year where we might see AI kind of the place of a mid-level engineer. With the world evolving so quickly, can you share some places where you've seen strong traction there? And are we progressing kind of faster, slower as you expected towards this milestone? And then, Susan, with the expense guidance coming down just a touch, how should we think about just the overall cadence of expected spending, really as it relates to kind of core business performance and just the realities of the day-to-day world we're living in? Thank you.

I can talk about the coding agent work. I don't think that there's been any real change in our prediction for the timing of this. So I'd say, it's basically still on track for something around a mid-level engineer, kind of starting to become possible sometime this year, scaling into next year. So I'd expect that by the middle to end of next year, AI coding agents are going to be doing a substantial part of AI research and development. So we're focused on that. Internally, we're also very focused on building AI agents or systems that can help run different experiments to increase recommendations across our other AI products, like the ones that do recommendations across our feeds and things like that. So I think that if it works should just accelerate our progress in those areas. That's the basic bet that we're making.

On your second question about our lowered expense outlook, really, we are four months into the year the lowered outlook reflects more refined forecasts, including updated expectations for both employee compensation as well as some other non-headcount-related operating expenses this year. And that's partially offset by higher expected infrastructure costs related to our increased CapEx outlook as well as higher expected Reality Labs cost of goods sold. And we've maintained our $5 billion range just given the more dynamic operating environment that we're in. And what I would say is our investment posture today reflects the significant opportunities that we see across each of the Company and priorities that we're investing in this year. We will obviously continue evaluating depending on how macro conditions more broadly evolve. But we really feel like these are big strategic priorities for us and are critical for us to continue investing in. And in fact, I think one of the aims of our efficiency work over the last two years was to put us in a stronger financial position so that we can continue investing in key priorities through tougher financial cycles.

Your next question comes from the line of Ross Sandler with Barclays. Please go ahead.

Great. Mark, in one of your recent podcasts or presentations, you mentioned that several projects your teams want to pursue are currently constrained by AI capacity, as noted by Susan earlier. Additionally, some testing the ad ranking team wishes to conduct is facing delays. Looking ahead, when do you anticipate some of these constraints will start to ease? Also, considering we are three years post-IDFA impact on your business, where do you believe we stand regarding improvements to the ad ranking system and the ROI you are able to achieve? In your opinion, how far along are we in this process? Thank you very much.

I can take a shot at both of those, and Mark, you can obviously chime in. On the first question, the capacity landscape we are in is pretty dynamic, both in terms of the many moving parts in terms of us bringing capacity online, but also in terms of the demand from different product groups in our company, whether they are in the Gen AI teams or whether they're doing more of the core AI work around ranking and recommendation. So both the supply and demand are quite fluid and so we don't have a sort of fixed answer in terms of when we expect that we will sort of have enough supply to meet all demand, but that's something that we are working very hard to alleviate and it's part of why we accelerated bringing more data center space online this year and also we're very focused on increasing the efficiency of our workloads over the course of the year. On your second question about ads performance ads ranking. We have invested for many years and continue to invest in driving ad performance improvements. Year-over-year conversion growth remains strong, and in fact, we continue to see conversions grow at a faster rate than ad impressions in Q1. So, reflecting increased conversion rates. And ads ranking and modeling improvements are a big driver of overall performance gains. We have a lot of innovations in model architecture in both the ads retrieval and ranking stages of the ads delivery process to serve more relevant ads to people. We talked about the introduction of the new GEM ads recommendation model in Q1, and we have talked about some of the prior model architecture improvements like Lattice and Andromeda in past quarters. For us, we really believe first and foremost that advertising is a relative performance game, and that's especially important for us, because the vast majority of our business is direct response advertising. So we feel good about how the prior investments are paying off, and we continue to invest in a lot of different work to constantly improve our ads ranking and recommendations performance.

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

Thank you so much. Two for me, please. First, maybe Mark. How should we think about the timing of AI capabilities necessary to drive WhatsApp for business adoption in higher labor cost markets? What is Meta doing to accelerate that adoption? And do you see this as mostly incremental to SME ad spend that you're already capturing? And then first, Susan, one, please. What does the revised CapEx outlook for this year for '25 mean about future years? Does it mean anything, or you talked about this being an acceleration in your revised outlook statement. Should we think about this as a new starting point for '26 and beyond? Or should we just start fresh in '26 and think about the needs and capacity at that point? Thank you.

I'm happy to address both of those questions, and Mark, feel free to jump in whenever you want. Mark shared some insights about our vision, which is that every business will soon have an AI expert to interact with customers, similar to how they currently utilize email, websites, and social media. We are in the process of testing business AIs with a select group of businesses in the U.S. and a few other countries on platforms like WhatsApp, Messenger, and through ads on Facebook and Instagram. Our initial focus has been on small businesses, helping them sell their products and services using these AIs. Ultimately, we aim to provide tools that assist businesses throughout the entire customer journey, from lead generation to order management and customer service. A key focus right now is enabling businesses to customize and control the AI agents to achieve desired outcomes. We have introduced a new management experience and dashboard that simplifies the training of AI based on existing information from their website, WhatsApp profile, and their pages on Instagram and Facebook. We're beginning by enabling businesses to activate AI in their customer chats. Additionally, we are testing business AIs in Facebook and Instagram ads that can answer questions about product and return policies or help with purchases through our in-app browser. Our ultimate goal is to create a unified experience that serves customers across all these platforms, where the AI remembers their history and preferences. We're receiving positive feedback, particularly regarding how these AIs are saving time for the businesses involved in our testing and helping them identify which conversations are worth their attention. Your second question was about our capital expenditure plans for 2026. Infrastructure planning is quite dynamic, especially with ongoing advancements in AI and our discoveries of beneficial use cases for capacity in our core AI ranking and recommendations. Therefore, it's too early to discuss our plans beyond 2025.

Your next question comes from the line of Youssef Squali with Truist Securities. Please go ahead.

Great. Thank you guys for taking the question. So Mark, in a world where we now have maybe five to 10 chatbots, including Meta AI, on our smartphones doing virtually the same thing. Do you think this is a market much like Search, where the winner takes most, or is it likely to be much more fragmented? But in either case, what would you say are the top two or three competitive advantages of Meta AI? And then, Susan, on the EU decision connection with the DMA, what kind of modifications will you need to make to the apps? And can you maybe just help us gauge the potential financial fallout, understanding that it may still obviously be too early? Thank you.

Yes. I believe there will be various agents that people use, similar to how they utilize different apps for different tasks. While I don't think individuals will rely on multiple agents for the same specific purpose, I can envision that a tool designed for enterprise productivity could differ from one aimed at personal productivity, and this might be distinct from something optimized for entertainment and social interaction. I expect there will be various experiences. One emerging trend is the personalization across these agents. Currently, if an experience lacks personalization, users can access different apps for similar answers to their inquiries. However, once an AI starts to understand user preferences and builds memory from previous conversations, it will likely become a notable differentiator. This is one aspect we believe will be significant. Additionally, the ability to handle various modalities—like answering questions not just through text but also via voice, images, and videos, while effectively engaging in discussions about these formats—will be crucial. So, while I think Meta AI is in a strong position, there's still substantial work ahead to establish it as the leading personal AI.

And Youssef, on your second question, it is really too early to speak about what those changes could be because we are in the process of engaging with the European Commission. I think maybe the most useful sort of metric I could give you is just that our advertising revenue in the European economic area in Switzerland, which would be the geographies impacted here, was 16% of our worldwide total revenue in 2024. Again, we are continuing to engage actively with the European Commission further on this. So we hope to have more clarity by next quarter's call.

Krista, we have time for one last question.

Your last question comes from the line of Mark Mahaney with Evercore ISI. Please go ahead.

Thanks. I have a couple of questions. You mentioned that China-based retailers might be a weaker advertising sector. Are there any other areas you would highlight? Also, is the auto industry experiencing any weakness? Regarding Reality Labs and the consistent losses of about $4 billion each quarter for quite some time, is there any indication of improvement? What factors could lead to a reduction in those losses, and when might that happen? Thank you.

Mark, let me take your first question about other verticals. We generally saw healthy growth in most verticals in Q1. We did see some weakness in gaming and politics. So, year-over-year growth in gaming was negative in Q1, as we lapped a period of strong spend from China-based advertisers that were promoting a larger volume of game titles in Q1 of 2024. And then year-over-year growth in the government and politics vertical dropped sharply as expected with the conclusion of U.S. elections and but that continues to just be a very small vertical overall. And then your second question on Reality Labs. Yes.

We are primarily focused on enhancing our efficiency, but with the success of the AI glasses, I've mentioned this in several calls. There are additional investments that we believe are necessary to ensure we can distribute and grow these products quickly. If you look at leading consumer electronics in other categories, by their third generation, they often reach sales of 10 million units and continue to scale from there. While I can't guarantee we'll reach that exact figure, it does represent the kind of opportunity we have, and we are focused on scaling to that level and beyond in future generations. Some of our efforts will make us more efficient in certain areas, and as more of our products begin to succeed and outpace the initial milestones, we will keep expanding our distribution. Eventually, similar to other products we develop, we will reach a scale where our main focus will be on monetizing and building a sustainable business around them. That's where we currently stand. We are definitely committed to being more efficient while remaining optimistic about the results we are seeing, particularly regarding the AI glasses.

Great. Thank you, everyone, for joining us today. Excuse me, and we look forward to speaking to you again soon.