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 Second Quarter Earnings Conference Call. 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 Second Quarter 2025 Earnings Conference Call. Joining me today are Mark Zuckerberg, CEO; and Susan Li, CFO. Our remarks today will include forward-looking statements, which are based on assumptions as of today. Actual results may differ materially as a result of various factors, including those set forth in today's earnings press release and in our quarterly report on Form 10-Q filed with the SEC. We undertake no obligation to update any forward-looking statement. 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 had another strong quarter with more than 3.4 billion people using at least one of our apps each day and strong engagement across the board. Our business continues to perform very well, which enables us to invest heavily in our AI efforts. Over the last few months, we've begun to see glimpses of our AI systems improving themselves. And the improvement is slow for now but undeniable—developing superintelligence, which we define as AI that surpasses human intelligence in every way, we think, is now in sight. Meta's vision is to bring personal superintelligence to everyone so that people can direct it towards what they value in their own lives. And we believe that this has the potential to begin an exciting new era of individual empowerment. A lot has been written about all the economic and scientific advances that superintelligence can bring, and I'm extremely optimistic about this. But I think that if history is a guide, then an even more important role will be how superintelligence empowers people to be more creative, develop culture and communities, connect with each other, and lead more fulfilling lives. To build this future, we've established Meta Superintelligence Labs, which includes our foundations, product and FAIR teams as well as a new lab that is focused on developing the next generation of our models. We're making good progress towards Llama 4.1 and 4.2, and in parallel, we are also working on our next generation of models that will push the frontier in the next year or so. We are building an elite, talent-dense team. Alexandr Wang is leading the overall team, Nat Friedman is leading our AI Products and Applied Research, and Shengjia Zhao is Chief Scientist for the new effort. They are all incredibly talented leaders, and I'm excited to work closely with them and the world-class group of AI researchers, infrastructure, and data engineers that we're assembling. I've spent a lot of time building this team this quarter. And the reason that so many people are excited to join is that Meta has all of the ingredients that are required to build leading models and deliver them to billions of people. The people who are joining us are going to have access to unparalleled compute as we build out several multi-gigawatt clusters. Our Prometheus cluster is coming online next year, and we think it's going to be the world's first gigawatt-plus cluster. We're also building out Hyperion, which will be able to scale up to 5 gigawatts over several years, and we have multiple more titan clusters in development as well. We are making all these investments because we have conviction that superintelligence is going to improve every aspect of what we do. From a business perspective, I mentioned last quarter that there are five basic opportunities that we are pursuing: improved advertising, more engaging experiences, business messaging, Meta AI, and AI devices. So I can go into a bit of detail on each. On advertising, the strong performance this quarter is largely thanks to AI unlocking greater efficiency and gains across our ad system. This quarter, we expanded our new AI-powered recommendation model for ads to new surfaces and improved its performance by using more signals and longer context. It's driven roughly 5% more ad conversions on Instagram and 3% on Facebook. We're also seeing good progress with AI for ad creative with a meaningful percent of our ad revenue now coming from campaigns using one of our generative AI features. This is going to be especially valuable for smaller advertisers with limited budgets. While agencies will continue the important work to help larger brands apply these tools strategically. The second opportunity is more engaging experiences. AI is significantly improving our ability to show people content that they're going to find interesting and useful. Advancements in our recommendation systems have improved quality so much that it has led to a 5% increase in time spent on Facebook and 6% on Instagram, just this quarter. There is a lot of potential for content itself to get better too, we're seeing early progress with the launch of our AI video editing tools across Meta AI and our new Edits app. And there's a lot more to do here. The third opportunity is business messaging. I've talked before about how I believe every business will soon have a business AI, just like they have an email address, social media account and website. We are starting to see some product market fit in a number of countries where we're testing these agents, and we're integrating these business AIs into ads on Facebook and Instagram as well as directly into e-commerce websites. The fourth opportunity is Meta AI. Its reach is already quite impressive with more than 1 billion monthly actives. Our focus is now deepening the experience and making Meta AI the leading personal AI. As we continue improving our models, we see engagement grow. So our next generation of models is going to continue to really help here. And the fifth opportunity is AI devices. We continue to see strong momentum with our Ray-Ban Meta glasses with sales accelerating. We are also launching new performance AI glasses with the Oakley Meta HSTN, they have longer battery life, higher resolution camera, and are designed for sports. The percent of people using Meta AI is growing, and we are seeing new users AI retention increase too, which is a good sign for that continued use. I think that AI glasses are going to be the main way that we integrate superintelligence into our day-to-day lives. So it's important to have all of these different styles and products that appeal to different people in different settings. Finally, we're seeing people continue to spend more time with our Quest ecosystem, and the community continues to grow steadily. We launched the Meta Quest 3S Xbox Edition last month, and we're seeing record interest in cloud gaming. And beyond gaming, we continue to see a broader set of use cases with media and web browsing contributing a significant portion of engagement. We're going to have more to share on all of this, especially the Reality Labs work at Connect on September 17. So I encourage you all to tune into that. Overall, this has been a busy quarter. Strong business performance and real momentum in assembling both the talent and the compute that we need to build personal superintelligence for everyone. I am very grateful to our teams who are working hard to deliver all of this, and thanks to all of you for being on this journey with us. And now here is 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. Q2 total revenue was $47.5 billion, up 22% on both a reported and constant currency basis. Q2 total expenses were $27.1 billion, up 12% compared to last year. In terms of the specific line items, cost of revenue increased 16%, driven mostly by higher infrastructure costs and payments to partners, partially offset by a benefit from the previously announced extension of sever useful lives. R&D increased 23%, mostly due to higher employee compensation and infrastructure costs. Marketing and sales increased 9% primarily due to an increase in professional services related to our ongoing platform integrity efforts as well as marketing costs, partially offset by lower employee compensation. G&A decreased 27%, driven mostly by lower legal-related costs. We ended Q2 with over 75,900 employees, down 1% quarter-over-quarter, as the vast majority of the employees impacted by performance-related reductions earlier this year were no longer captured in our head count. This was partially offset by continued hiring in priority areas of monetization, infrastructure, Reality Labs, AI as well as regulation and compliance. Second quarter operating income was $20.4 billion, representing a 43% operating margin. Our tax rate for the quarter was 11%, which reflects excess tax benefits from share-based compensation due to the increase in our share price versus prior periods. Net income was $18.3 billion or $7.14 per share. Capital expenditures, including principal payments on finance leases, were $17 billion, driven by investments in servers, data centers, and network infrastructure. Free cash flow was $8.5 billion. We repurchased $9.8 billion of our Class A common stock and paid $1.3 billion in dividends to shareholders. We also made $15.1 billion in nonmarketable equity investments in the second quarter, which includes our minority investment in Scale AI, along with other investment activities. We ended the quarter with $47.1 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 June. Q2 total Family of Apps revenue was $47.1 billion, up 22% year-over-year. Q2 Family of Apps ad revenue was $46.6 billion, up 21% or 22% on a constant currency basis. Within that 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 Europe and Rest of World at 24% and 23%, respectively. North America and Asia Pacific grew 21% and 18%. In Q2, the total number of ad impressions served across our services increased 11%, with growth mainly driven by Asia Pacific. Impression growth accelerated across all regions due primarily to engagement tailwinds on both Facebook and Instagram and to a lesser extent, ad load optimizations on Facebook. The average price per ad increased 9%, benefiting from increased advertiser demand, largely driven by improved ad performance. Pricing growth slowed modestly from the first quarter due to the accelerated impression growth in Q2. Family of Apps other revenue was $583 million, up 50%, driven by WhatsApp paid messaging revenue growth 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 Q2, Family of Apps expenses were $22.2 billion, representing 82% of our overall expenses. Family of Apps expenses were up 14% and mainly due to growth in employee compensation and infrastructure costs, partially offset by lower legal-related costs. Family of Apps operating income was $25 billion, representing a 53% operating margin. Within our Reality Labs segment, Q2 revenue was $370 million, up 5% year-over-year due to increased sales of AI glasses, partially offset by lower Quest sales. Reality Labs expenses were $4.9 billion, up 1% year-over-year, driven by higher non-headcount-related technology development costs. Reality Labs operating loss was $4.5 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, daily actives continue to grow across Facebook, Instagram, and WhatsApp as we make additional improvements to our recommendation systems and product experiences. We continue to see momentum with video engagement, in particular. In Q2, Instagram video time was up more than 20% year-over-year globally. We're seeing strong traction on Facebook as well, particularly in the U.S., where video time spent similarly expanded more than 20% year-over-year. These gains have been enabled by ongoing optimizations to our ranking systems to better identify the most relevant content to show. We expect to deliver additional improvements throughout the year as we further scale up our models and make recommendations more adaptive to a person's interests within their session. Another emphasis of our recommendations work is promoting original content. On Instagram, over 2/3 of recommended content in the U.S. now comes from original posts. In the second half, we'll be focused on further increasing the freshness of original posts, so the right audiences can discover original content from creators soon after it is posted. We are also making good progress on our longer-term ranking innovations that we expect will provide the next leg of improvements over the coming years. Our research efforts to develop cross-surface foundation recommendation models continue to progress. We are also seeing promising results from using LLM in Threads recommendation systems. The incorporation of LLMs is now driving a meaningful share of the ranking-related time spent gains on Threads. We're now exploring how to extend the use of LLMs and recommendation systems to our other apps. We're leveraging Llama and several other back-end processes as well, including actioning bug reports so we can identify and resolve recurring issues more quickly and efficiently. This has resulted in top-line bug reports in the U.S. and Canada in Facebook Feed and notifications dropping by roughly 30% over the past 10 months. The primary way we're using Llama in our apps today is to power Meta AI which is now available in over 200 countries and territories. WhatsApp continues to be the largest driver of queries as people message Meta AI directly for tasks such as information gathering, homework assistance, and generating images. Outside of WhatsApp, we're seeing Meta AI become an increasingly valuable complement to our content discovery engines. Meta AI usage on Facebook is expanding as people use it to ask about posts they see in Feed and find content across our platform in Search. Another way we expect Meta AI will help with content discovery is through the automatic translation and dubbing of foreign language content into the audience's local language. We'll have more to share on our efforts there later this year. Moving to Reality Labs. The growth of Ray-Ban Meta sales accelerated in Q2, with demand still outstripping supply for the most popular SKUs despite increases to our production earlier this year. We're working to ramp supply to better meet consumer demand later this year. 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 surface to better deliver ads at the time and place they are most relevant to people. In Q2, we also began introducing ads within Feed on Threads and the Updates tab of WhatsApp, which is a separate space away from people's chats. As of May, advertisers globally can now run video and image ads to Threads users in most countries, including the United States. While ad supply remains low and Threads is not expected to be a meaningful contributor to overall impression growth in the near term, we are optimistic about the longer-term opportunity with Threads as the community and engagement grow and monetization scales. On WhatsApp, we are rolling out ads in status and channels, along with channel subscriptions in the Updates tab to help businesses reach the more than 1.5 billion daily actives who visit that part of the app. We expect the introduction of ads and status will be gradual over the course of this year and next, with low levels of expected ad supply initially. We also expect WhatsApp ads and status to earn a lower average price than Facebook or Instagram ads for the foreseeable future, due in part towards WhatsApp skew toward lower monetizing markets and more limited information that can be used for targeting. Given this, we do not expect ads and status to be a meaningful contributor to total impressions or revenue growth for the next few years. The second part of increasing monetization efficiency is improving marketing performance. There are three areas of this work that I'll focus on today: improving our ad systems, advancing our ads products, including by building tools that assist in ad creation, and evolving our ads platform to drive results that are optimized for each business' objectives. First is our ad systems where we're innovating in both the ads retrieval and ranking stages to serve more relevant ads to people. A lot of this work involves us continuing to advance the modeling innovations we've introduced previously while expanding their adoption across our platform. The Andromeda model architecture we began introducing in the second half of 2024 powers the ads retrieval stage of our ad system, where we select the few thousand most relevant ads from tens of millions of potential candidates. In Q2, we made enhancements to Andromeda that enabled it to select more relevant and personalized ad candidates while also expanding coverage to Facebook Reels. These improvements have driven nearly 4% higher conversions on Facebook Mobile Feed and Reels. Our new Generative Ads Recommendation system, or GEM, powers the ranking stage of our ad system, which is the part of the process after ads retrieval where we determine which ads to show someone from candidates suggested by our retrieval engine. In Q2, we improved the performance of GEM by further scaling our training capacity and adding organic and ads engagement data on Instagram. We also incorporated new advanced sequence modeling techniques that helped us double the length of event sequences we use, enabling our systems to consider a longer history of the content or ads that a person has engaged with in order to provide better ad selections. The combination of these improvements increased ad conversions by approximately 5% on Instagram and 3% on Facebook Feed and Reels in Q2. Finally, we expanded coverage of our Lattice model architecture in Q2. We first began deploying Lattice in 2023 with our later-stage ads ranking efforts, allowing us to run significantly larger models that generalize learnings across objectives and surfaces in place of numerous smaller ads models that have historically been optimized for individual objectives and surfaces. In April, we began deploying Lattice to earlier-stage ads ranking models as well. This is leading not only to greater capacity and engineering efficiency but also improved performance with the recent Lattice deployments driving a nearly 4% increase in ad conversions across Facebook Feed and Reels in Q2. Next, ad products. Here, we're seeing strong momentum with our Advantage+ suite of AI-powered solutions. In Q2, we completed the rollout of our streamlined campaign creation flow for Advantage+ sales and app campaigns, which makes it easier for advertisers to realize the performance benefits from Advantage+ by having it turned on at the beginning. We've seen lifts in advertiser adoption of sales and app campaigns since we've expanded availability and are working to complete the rollout for leads campaigns in the coming months. Within our Advantage+ Creative suite, adoption of genAI ad creative tools continues to broaden. Nearly 2 million advertisers are now using our video generation features, image animation and video expansion, and we're seeing strong results with our text generation tools as we continue to add new features. In Q2, we started testing AI-powered translation so that advertisers can automatically translate the caption of their ads to 10 different languages. While it's early, we have seen promising performance lifts in our prelaunch tests. We're also continuing to see strong adoption of image expansion among small- and medium-sized advertisers, which speaks to how these tools help businesses who have fewer resources to develop creative. With larger advertisers, we expect agencies will continue to be valuable partners in helping apply these new tools to drive performance. Outside of Advantage+, we're seeing good momentum in business messaging, particularly in the U.S., where click to message revenue grew more than 40% year-over-year in Q2. The strong U.S. growth is benefiting from a ramp in adoption of our website to message ads, which drive people to a business's website for more information before choosing to launch a chat with the business in one of our messaging apps. Finally, we continue to evolve our ads platform to drive results that are optimized for each business' objectives and the way they measure results. In Q2, we completed the global rollout of our incremental attribution feature, which is the only product on the market that optimizes for and reports on incremental conversions, which are conversions that would not have happened without a person seeing the ad. We also launched omnichannel ads globally in Q2 and which enable advertisers to optimize for incremental sales, both in-store and online with just one campaign. In tests, advertisers using omnichannel ads have seen a median 15% reduction in total cost per purchase compared to website-only optimization. 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. I'll start with hiring. Our approach to adding head count continues to be targeted at the company's highest priority areas. We expect talent additions across all of our priority areas will continue to drive overall head count growth through this year and 2026. While head count growth in our other functions remains constrained, within AI, we've had a particular emphasis on recruiting leading talent within the industry as we build out Meta Superintelligence Labs to accelerate our AI model development and product initiatives. Next, infrastructure. We expect having sufficient compute capacity will be central to realizing many of the largest opportunities in front of us over the coming years. We continue to see very compelling returns from our AI capacity investments in our core ads and organic engagement initiatives and expect to continue investing significantly there in 2026. We also expect that developing leading AI infrastructure will be a core advantage in developing the best AI models and product experiences. So we expect to ramp our investments significantly in 2026 to support that work. Moving to our financial outlook. We expect third quarter 2025 total revenue to be in the range of $47.5 billion to $50.5 billion. Our guidance assumes foreign currency is an approximately 1% tailwind to year-over-year total revenue growth, based on current exchange rates. While we are not providing an outlook for fourth quarter revenue, we would expect our year-over-year growth rate in the fourth quarter of 2025 to be slower than the third quarter as we lap a period of stronger growth in the fourth quarter of 2024. Turning now to the expense outlook. We expect full year 2025 total expenses to be in the range of $114 billion to $118 billion, narrowed from our prior outlook of $113 billion to $118 billion and reflecting a growth rate of 20% to 24% year-over-year. While we're still very early in planning for next year, there are a few factors we expect will provide meaningful upward pressure on our 2026 total expense growth rate. The largest single driver of growth will be infrastructure costs, driven by a sharp acceleration in depreciation expense growth and higher operating costs as we continue to scale up our infrastructure fleet. Aside from infrastructure, we expect the second largest driver of growth to be employee compensation as we add technical talent in priority areas and recognize a full year of compensation expenses for employees hired throughout 2025. We expect these factors will result in a 2026 year-over-year expense growth rate that is above the 2025 expense growth rate. Turning now to the CapEx outlook. We currently expect 2025 capital expenditures, including principal payments on finance leases, to be in the range of $66 billion to $72 billion, narrowed from our prior outlook of $64 billion to $72 billion and up approximately $30 billion year-over-year at the midpoint. While the infrastructure planning process remains highly dynamic, we currently expect another year of similarly significant CapEx dollar growth in 2026 as we continue aggressively pursuing opportunities to bring additional capacity online to meet the needs of our AI efforts and business operations. On to tax. With the enactment of the new U.S. tax law, we anticipate a reduction in our U.S. federal cash tax for the remainder of the current year and future years. There are several alternative ways of implementing the provisions of the act, which we are currently evaluating. While we estimate that the 2025 tax rate will be higher than our Q2 tax rate, we cannot quantify the magnitude at this time. In addition, we continue to monitor an active regulatory landscape, including the increasing legal and regulatory headwinds in the EU that could significantly impact our business and our financial results. For example, we continue to engage with the European Commission on our Less Personalized Ads offering or LPA, which we introduced in November 2024 and based on feedback from the European Commission in connection with the DMA. As the commission provides further feedback on LPA, we cannot rule out that it may seek to impose further modifications to it that would result in a materially worse user and advertiser experience. This could have a significant negative impact on our European revenue as early as later this quarter. We have appealed the European Commission's DMA decision, but any modifications to our model may be imposed during the appeal process. In closing, this was another strong quarter for our business as our investments in infrastructure and technical talent continue to improve core ads performance and engagement on our platforms. We expect the significant investments we're making now will allow us to continue leveraging advances in AI to extend those gains and unlock a new set of opportunities in the years to come. With that, Krista, let's open up the call for questions.

Your first question comes from the line of Eric Sheridan with Goldman Sachs.

Mark, when you think about where the AI parts of your business have been evolving over the last 3 to 6 months, I wanted to know what your key learnings were as you went deep into that strategy that informed some of the shifts in both talent acquisition and compute, coupled with some of the blogs you put out recently in terms of how that strategy might have evolved based on those key learnings? And Susan, building on Mark's comments on scaling talent and compute, I want to know if you can go a little bit deeper on how we should be thinking about those two components driving some of the commentary you've given around OpEx and CapEx over the next 12 to 18 months.

Yes, sure. I can start. At a high level, I think that there are all these questions that people have about what are going to be the time lines to get to really strong AI or superintelligence or whatever you want to call it. And I guess that each step along the way so far, we've observed that the more aggressive assumptions, or the fastest assumptions, have been the ones that have most accurately predicted what would happen. I think that continues to happen over the course of this year, too. I've given a number of those anecdotes on these earnings calls in the past. Certainly, the work that we're seeing with teams internally being able to adapt Llama 4 to build autonomous AI agents that can help improve the Facebook algorithm to increase quality and engagement is a fairly profound thing if you think about it. It's happening in low volume right now, so I'm not sure that result by itself was a major contributor to this quarter's earnings, but I think the trajectory on this stuff is very optimistic. Running a business like this now presents an interesting challenge because it seems like there's a very high chance the world is going to look quite different in a few years from now. On one hand, there are improvements to our core products that exist. On the other, we have this principle that we believe in across the company, which is to take superintelligence seriously. We think it is going to shape all of our systems sooner rather than later. Not necessarily on the trajectory of a quarter or two, but on the trajectory of a few years. This is going to change many assumptions across the company. We are continually observing and trying to determine how this works and the pace of AI progress has been. I believe it continues to be on a faster end, which informs a lot of decisions about the importance and value of having the absolute best and most elite talent-dense team at the company, ensuring that we have a leading compute fleet so that researchers have more compute per person to lead their research and roll it out to billions of people. It’s about driving products through everything that we do. We think we are the best in the world at taking technology and getting it in front of billions of people. We are pushing aggressively on all of this, and at some level, it is a bet on the trajectory we are seeing and those signals we perceive.

Eric, for the second part of your question, we haven't, in fact, kicked off our budgeting process for 2026. So thinking about next year, there are clearly many moving pieces in a very dynamic operating environment. However, we have some visibility into today, including the rough shape of our 2026 infrastructure plans, and that flows through into our expense expectations next year. We also have some visibility into the compensation expense growth that we'll recognize from the AI talent that we're hiring this year. Those two factors are part of why we provided a preview into our expectations for growth for 2026 total expenses as well as for 2026 CapEx. On total expenses side, we expect infrastructure will be the single largest contributor to 2026 expense growth. This is driven primarily by a sharp acceleration in depreciation expense growth, largely reflecting recognizing incremental depreciation from assets purchased and placed in service in 2026 as well as from infrastructure deployed through 2025 that will recognize a full year of depreciation next year. We expect a greater mix of our CapEx to be in shorter-lived assets than in prior years, adding to infrastructure cost growth. In 2026, we also expect to increase spending on cloud services to meet our capacity needs as well as growth in network-related costs. There’s a lot going on with infrastructure as it contributes to total expense growth for 2026. After that, employee compensation is the next largest driver of expense growth in 2026, primarily driven by investments in technical talent and recognizing a full year of compensation expense for the AI talent hired this year. I realize this answer is getting a bit long, so I’ll wrap up quickly: On the CapEx side, the main driver of increased CapEx in 2026 will be scaling genAI capacity as we build out training capacity, leading to higher spend across servers and data centers next year. We also expect to continue investing significantly in core AI in 2026, and while this remains a dynamic area of planning, we wanted to share our early thoughts.

I have two. The first one, Mark, just to kind of go back to the intelligence labs and sort of the vision for superintelligence. As you sort of sit here now versus 12 months ago, can you just sort of walk us through any changes of technological constraints or technological gating factors that you are most focused on overcoming in the next 24 months that may have been different from the past? And then the second one to Susan or Mark, one on the core. You've made so many improvements to the core to drive higher engagement, recommendations, etc. Can you just walk us through a couple of factors you're still most excited about that could drive a further lift in engagement on the core platform?

Yes, sure. In terms of the research agenda, one area that we're focused on is self-improvement. There are different scaling paradigms, and I don't want to go too deep into the detail of research we're conducting. To develop superintelligence, at some level, it needs to learn to improve itself, which I think is a fundamental consideration with broad implications for our product development and the company overall. In terms of the overall effort's structure, I’ve grown more convinced about the effectiveness of small, talent-dense teams for driving frontier research. It differs from our setup on other technologic systems like Instagram or Facebook. We can have many hundreds or thousands working on these systems and develop robust testing infrastructure. But I think that for superintelligence research, we want the smallest group that can comprehend the whole system. That drives the physics of team size and dynamics.

Brian, on the forward-looking roadmap for the core recommendation engine, we're focused on some immediate factors. One is making recommendations more adaptive to the user's engagement during their session to show the most relevant content at that moment. We're optimizing to help smaller creators break out by matching content to the right audience soon after it is posted. We're also working on improving our systems to discover more diverse interests through user preferences. Additionally, we're planning to scale up our models and incorporate advanced techniques to improve the overall recommendation quality. There are a lot of long-term bets on foundational models that will support recommendations across multiple services and incorporating LLMs more deeply into our systems.

One for Mark and one for Susan. Mark, Meta has been a huge proponent of open-source AI. Has your thinking changed here at all, just as you pursue superintelligence and push for even greater returns on your significant infrastructure investments? And then, Susan, your comments on '26 CapEx suggest more than $100 billion of spend next year potentially. Do you continue to expect to finance all this yourself? Or could there be opportunities to partner here?

Yes, in terms of open source, I don't think our thinking has particularly changed on this. We've always open-sourced some of our models and not open-sourced everything that we've done. I would expect that we will continue to produce and share leading open-source models but also recognize certain trends. There's a point where models become so large that they are impractical for many users. We often wrestle with whether sharing is productive or may benefit competitors. As we approach superintelligence, new safety concerns arise that must be taken seriously. While I expect to be a leader in open source, we will also selectively choose what we make available to the public. This is a huge investment and a massive amount of capital to convert into compute that will improve our quality of products.

Doug, regarding how we expect to finance the growing CapEx next year. We certainly expect to self-finance a substantial share, but we're also exploring ways to work with financial partners to co-develop data centers. We don't have any finalized transactions to announce, but we believe that there will be models to attract significant external financing for large-scale data center projects. This flexibility will also support variance in our infrastructure requirements over time.

I'll ask another one on infrastructure. Mark, your spend is now approaching some of the biggest hyperscalers out there. Do you think of all this capacity mostly for internal uses? Or do you think there's a way to share or even come up with a business model where leveraging that capacity for external uses? And then Susan, when you think about the ROI on this CapEx, I'm sure you have internal models, I'm sure you can't share all that, but how are you thinking about the ROI? And are you optimistic about the long-term returns?

Justin, I can tackle both of those. Currently, we focus on ensuring sufficient capacity for internal use cases, including core AI work supporting recommendations on organic content, ads ranking, and training capacity for frontier AI models. We're not presently considering external use cases for our infrastructure. Regarding ROI on CapEx, we continue to see strong returns on AI investments and can measure that quite well. We're optimistic about the monetization opportunities opened through our ongoing investments. While genAI ROI is earlier in the curve, we are positive about its long-term prospects. We are constructing infrastructure with flexibility to adjust as necessary, optimizing the timing of server orders.

Mark, as you go after the superintelligence vision, especially for those of us on the outside, what are kind of some of the markers or KPIs that you're tracking to gauge your progress? Is it really against those five pillars you outlined above, or should we be thinking more broadly? And Susan, obviously AI delivers great ROI today, and all those investments build toward longer-term goals. Has there been an adjustment in how you think about the relationship between revenues or core business performance and the cadence of investment?

In terms of markers to look for, we should review the quality of our teams, models, rate of improvement of our AI systems, and how the leading foundation models we are creating enhance our other systems. This translates into standard product operations: building high-quality products that scale to billions of users. However, there will be inherent lag in this process, requiring our focus first on quality and then on business ramp-up over a few years.

Regarding profitability, our principal focus is driving consolidated operating profit growth over time, but it won’t be linear. There will be years of above-average growth and years where significant investments affect profit growth. Currently, we see many attractive investment opportunities that will set us up to deliver compelling profit growth in coming years, and we're focused on constraining investments elsewhere to prioritize these.

Mark, I wanted to ask you about Meta AI. You've mentioned growing engagement overall, particularly on WhatsApp with 1 billion users. How will next-gen models drive adoption here, especially with Behemoth coming online? Additionally, as users interact with Meta AI on WhatsApp, what's the potential for monetizing that?

I won’t dive too deeply into the roadmap, but we anticipate that improvements in models behind Meta AI will lead to increased engagement. As we upgrade from Llama 4 to Llama 4.1, we expect these enhancements will cater to various user needs. The models are designed to be quite general, so improvements will be felt across various user requests. This continual development should positively impact user engagement.

I have two. Mark, the Ray-Ban initiative has been hallmark for you guys so far. Where are we on the glasses' development? Has the new computational platform you mentioned progressed faster or slower than expected? Do you believe glasses will ultimately replace smartphones, or do you need a new form factor that’s AI-first? And then, Susan, as you look at SBC over the next few years, will it grow materially faster than revenue and OpEx? How do you minimize shareholder dilution?

Yes, I'm excited about the progress we're making. I think both the Ray-Ban Metas and the Oakley Meta HSTNs are doing quite well. This product category is clearly resonating. It's fashionable eyewear that's functional. The integration of Meta AI is growing, and user engagement is increasing. I believe glasses represent an ideal form factor for AI—implementing superintelligence could enhance how individuals interact with their environment. Much like how vision correction is critical today, I believe interacting seamlessly with AI through glasses will soon be essential.

The effect of increased compensation costs, including SBC from AI hires, reflects in our revised 2025 expense outlook. This is a significant driver of expense growth for 2026. While we accurately incorporate this into our expense planning, we aim to manage dilution and maintain our strong financial position. This allows us to support ongoing investments while continuing share repurchases that help offset equity compensation.

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