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And one thing that became clear to me in the last year is that this next generation of services requires building full general intelligence. Previously, I thought that because many of the tools were social-, commerce- or maybe media-oriented that it might be possible to deliver these products by solving only a subset of AI's challenges. But now it's clear that we're going to need our models to be able to reason, plan, code, remember and many other cognitive abilities in order to provide the best versions of the services that we envision. We've been working on general intelligence research and FAIR for more than a decade. But now general intelligence will be the theme of our product work as well. Meta has a long history of building new technologies into our services, and we have a clear long-term playbook for becoming leaders.

And there are a few key aspects of this that I want to take some time to go through today. The first is world-class compute infrastructure. I recently shared that, by the end of this year, we'll have about 350,000 H100s, and including other GPUs, that will be around 600,000 H100 equivalents of compute. We're well positioned now because of the lessons that we learned from Reels. We initially underbuilt our GPU clusters for Reels. And when we were going through that, I decided that we should build enough capacity to support both Reels and another Reels-sized AI service that we expected to emerge so we wouldn't be in that situation again. And at the time, the decision was somewhat controversial, and we faced a lot of questions about CapEx spending, but I'm really glad that we did this.

Now going forward, we think that training and operating future models will be even more compute-intensive. We don't have a clear expectation for exactly how much this will be yet, but the trend has been that state-of-the-art large language models have been trained on roughly 10x the amount of compute each year. And our training clusters are only part of our overall infrastructure, and the rest, obviously, isn't growing as quickly. But overall, we're playing to win here, and I expect us to continue investing aggressively in this area. In order to build the most advanced clusters, we're also designing novel data centers and designing our own custom silicons specialized for our workloads. The second part of our playbook is open-source software infrastructure.

Our long-standing strategy has been to build an open-source general infrastructure while keeping our specific product implementations proprietary. In the case of AI, the general infrastructure includes our Llama models, including Llama 3, which is training now, and it's looking great so far, as well as industry standard tools like PyTorch that we've developed. And this approach to open source has unlocked a lot of innovation across the industry, and it's something that we believe in deeply. And I know that some people have questions about how we benefit from open sourcing, the results of our research and large amounts of compute. So I thought it might be useful to lay out the strategic benefits here. The short version is that open sourcing improves our models.

And because there's still significant work to turn our models into products because there will be other open-source models available anyway, we find that there are mostly advantages to being the open-source leader, and it doesn't remove differentiation for our products much anyway. And more specifically, there are several strategic benefits. First, open-source software is typically safer and more secure as well as more compute-efficient to operate due to all the ongoing feedback, scrutiny and development from the community. Now this is a big deal because safety is one of the most important issues in AI. Efficiency improvements and lowering the compute costs also benefit everyone, including us. Second, open-source software often becomes an industry standard.

And when companies standardize on building with our stack, that then becomes easier to integrate new innovations into our products. That's subtle, but the ability to learn and improve quickly is a huge advantage. And being an industry standard enables that. Third, open source is hugely popular with developers and researchers. And we know that people want to work on open systems that will be widely adopted. So this helps us recruit the best people at Meta, which is a very big deal for leading in any new technology area. And again, we typically have unique data and build unique product integrations anyway, so providing infrastructure like Llama as open source doesn't reduce our main advantage. This is why our long-standing strategy has been to open source general infrastructure and why I expect it to continue to be the right approach for us going forward.

The next part of our playbook is just taking a long-term approach towards the development. While we're working on today's products and models, we're also working on the research that we need to advance for Llama 5, 6 and 7 in the coming years and beyond to develop full general intelligence. It's important to have a portfolio of multiyear investments in research projects, but it's also important to have clear launch vehicles like future Llama models that help focus our work. We've worked on general intelligence in our lab, FAIR, for more than a decade, as I mentioned, and we produced a lot of valuable work. But having clear product targets for delivering general intelligence really focuses this work and helps us build the leading research program.

Now the next key part of our playbook is learning from unique data and feedback loops in our products. When people think about data, they typically think about the corpus that you might use to train a model upfront. And on Facebook and Instagram, there are hundreds of billions of publicly shared images and tens of billions of public videos, which we estimate is greater than the common crawl data set. And people share large numbers of public text posts and comments across our services as well. But even more important in the upfront training corpus is the ability to establish the right feedback loops with hundreds of millions of people interacting with AI services across our products. And this feedback is a big part of how we've improved our AI systems so quickly with Reels and Ads, especially over the last couple of years when we had to re-architect it around new rules.

Now that brings me to the last part of our playbook for building leading services, which is our culture of rapid learning and experimentation across our apps. When we decide that a new technology, like AI-recommended Reels, is going to be an important part of the future, we're not shy about having multiple teams experimenting with different versions across our apps until we get it right. And then we learn what works and we roll it out to everyone. And there used to be this meme that we'd probably launch Stories on our Settings page at some point. And look, I think it's kind of funny because it gets to a core part of our approach. We start by learning and tuning our products until they perform the way we want, and then we roll them out very broadly.

And sometimes, occasionally, products will blow up before we're ready for them to, like Threads, although I'll note that Threads now has more people actively using it today than it did during its initial launch peak. So that one is, I think, on track to be a major success. But normally, we learn and we iterate methodically. And we started doing that with our AI services in the fall launching Meta AI, our assistant; AI Studio, which the precursor to Creator AIs; our Alpha with Business AIs; and the Ray-Ban Meta smart glasses. And we've been tuning each of these, and we're getting closer to rolling them out more widely. So you should expect that in the coming months. From there, we'll focus on rolling out services until they reach hundreds of millions or billions of people.

And usually, only when we reach that kind of scale do we start focusing on what monetization will look like. And although in this case, the way the business AIs will help business messaging grow and WhatsApp, Messenger and Instagram is pretty clear. But that's our basic approach, and I'm really excited about pointing our company at developing so many of these awesome things. Now we have 2 major parts of our long-term vision, and in addition to AI, the other part is the metaverse. We've invested heavily in both AI and the metaverse for a long time, and we will continue to do so. These days, there are a lot of questions more about AI that I get, and that field is moving very quickly. But I still expect that this next generation of AR, VR and MR computing platforms to deliver a realistic sense of presence that will be the foundation for the future of social experiences and almost every other category of experiences as well.

Reality Labs crossed $1 billion in revenue in Q4 for the first time with Quest having a strong holiday season. Quest 3 is off to a strong start, and I expect it to continue to be the most popular mixed reality device. With Quest 3 and Quest 2 both performing well, we saw that the Quest app was actually the most downloaded app in the App Store on Christmas Day. I want to give a shout-out to Asgard's Wrath2, which was developed by one of our in-house studios and received IGN's 10 out of 10 masterpiece rating, making it one of the best-rated games out there, not just in VR, but of any game on any platform ever. So it's a really good sign that we're able to deliver that quality of work at Meta. Horizon is growing quickly, too. It is now on Top 10 Most Used Apps on Quest, and we have an exciting road map ahead.

This is another example of applying the long-term playbook that I discussed earlier with AI but in another area. We take the time to build up the core technology and tune the experience. And then when it's ready, we're good at growing things. Now our focus for this year is going to be on growing the mobile version of Horizon as well as the VR One. Ray-Ban Meta smart glasses are also off to a very strong start, both in sales and engagement. Our partner, EssilorLuxottica is already planning on making more than we both expected due to high demand. Engagement and retention are also significantly higher than the first version of the glasses. The experience is just a lot better with Meta AI in there as well as there's a higher resolution camera, better audio and more.

And we also have an exciting road map of software improvements ahead, starting with rolling out multimodal AI and then some other really exciting new AI features later in the year. I said this before, but I think that people are going to want new categories of devices that seamlessly engage with AIs frequently throughout the AI without having to take out your phone and press a button and point it at what you want to see. And I think that smart glasses are going to be a compelling form factor for this, and it's a good example of how our AI and metaverse visions are connected. In addition to AI in the metaverse, we're continuing to improve our Apps and Ads businesses as well. Reels and our discovery engine remain a priority and major driver of engagement, and Messaging continues to be our focus for building the next revenue pillar of our business before our longer-term work reaches scale.

But since I went a bit longer in the other areas today, I'm just going to mention a few highlights here. Reels continues to do very well across both Instagram and Facebook. People re-share Reels 3.5 billion times every day. Reels is now contributing to our net revenue across our apps. The biggest opportunity going forward is unifying our recommendation systems across Reels and other types of video that will help people discover the best content across our systems no matter what format it's in. WhatsApp is also doing very well. And the most exciting new trend here is that it is succeeding more broadly in the United States, where there's a real appetite for a private, secure and cross-platform messaging app that everyone can use. And given the strategic importance of the U.S. and its outsized importance for revenue, this is just a huge opportunity.

Threads is also growing steadily with more than 130 million monthly actives. And I'm optimistic that we can keep the pace of improvements in growth going and show that a friendly, discussion-oriented app can be as widely used as the most popular social apps. All right. That's what I wanted to cover today. Our communities are growing, and our business is back on track. Once again, a big thank you to all of our employees, partners, shareholders and everyone in our community for sticking with us and for making 2023 such a success. I'm looking forward to another exciting year ahead. And now here's Susan.

Susan Li: 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. Q4 total revenue was $40.1 billion, up 25% or 22% on a constant currency basis. Q4 total expenses were $23.7 billion, down 8% compared to last year. In terms of the specific line items, cost of revenue decreased 8%, 0driven mainly by lower restructuring costs that were partially offset by higher infrastructure-related costs. R&D increased 8% driven primarily by higher head count-related costs from Family of Apps and Reality Labs as well as higher non-head count-related Reality Labs operating expenses, which were partially offset by lower restructuring costs. Marketing and sales decreased 29% due mainly to lower marketing spend and restructuring costs.

G&A decreased 26% due mainly to lower restructuring expenses. We ended the fourth quarter with over 67,300 employees, down 22% from a year ago while up 2% from Q3 as our hiring efforts have resumed. Fourth quarter operating income was $16.4 billion, representing a 41% operating margin. Our tax rate for the quarter was 17%. Net income was $14 billion or $5.33 per share. Capital expenditures, including principal payments on finance leases, were $7.9 billion, driven by investments in servers, data centers and network infrastructure. Free cash flow was $11.5 billion, which reflects a $1.6 billion payment of income taxes deferred from prior quarters of 2023. We ended the year with $65.4 billion in cash and marketable securities and $18.4 billion in debt.

In the fourth quarter, we repurchased $6.3 billion of our Class A stock, bringing our total share repurchases for the full year to $20 billion. We had $30.9 billion remaining on our prior authorization as of December 31. And today, we announced a $50 billion increase in our stock repurchase authorization. Moving now to our segment results. I'll begin with our Family of Apps segment. In Q4, we saw continued community growth across the Family of Apps as well as Facebook, specifically. We're sharing today that as previewed when we first introduced our family metrics, we are transitioning away from reporting Facebook-specific metrics. As part of this transition, we will no longer report Facebook daily and monthly active users or family monthly active people.

In Q1, we will instead begin reporting year-over-year changes in ad impressions and the average price per ad at the regional level while continuing to report family daily active people. For full year 2023, Family of Apps total revenue was $133 billion and ad revenue was $131.9 billion, each up 16% year-over-year. The largest contributors to year-over-year ad revenue growth were the online commerce, CPG, entertainment and media and gaming verticals. The online commerce and gaming verticals benefited from strong demand by advertisers in China reaching people in other markets. In 2023, revenue from China-based advertisers represented 10% of our overall revenue and contributed 5 percentage points to total worldwide revenue growth. Turning back to Q4 results.

Q4 total Family of Apps revenue was $39 billion, up 24% year-over-year. Q4 Family of Apps ad revenue was $38.7 billion, up 24% or 21% on a constant currency basis. Within ad revenue, the online commerce vertical was the largest contributor to year-over-year growth, followed by CPG and gaming. On a user geography basis, ad revenue growth was strongest in Europe and Rest of World at 33% and 32%, respectively, followed by Asia Pacific at 23% and North America at 19%. Foreign currency was a tailwind to advertising revenue growth in all international regions. In Q4, the total number of ad impressions served across our services increased 21%, and the average price per ad increased 2%. Impression growth was mainly driven by Asia Pacific and Rest of World.

Pricing growth was driven by advertiser demand and currency tailwinds, which were partially offset by strong impression growth, particularly from lower-monetizing services and regions. Family of Apps other revenue was $334 million in Q4, up 82%, driven by business messaging revenue growth from our WhatsApp Business platform. We continue to direct the majority of our investments toward the development and operation of our Family of Apps. In Q4, Family of Apps expenses were $18 billion, representing approximately 76% of our overall expenses. Family of Apps expenses were down 13% due to lower restructuring expenses. Family of Apps operating income was $21 billion, representing a 54% operating margin. Within our Reality Labs segment, Q4 revenue was $1.1 billion, up 47%, driven by Quest 3 sales during the holiday season.

Reality Labs expenses were $5.7 billion, up 14% year-over-year due primarily to higher head count-related expenses and non-head count-related R&D spend. Reality Labs operating loss was $4.6 billion. Turning now to the business outlook. There are 2 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 remain pleased with engagement trends and have strong momentum across our product priorities. We're seeing sustained growth in Reels and Video overall as daily watch time across all video types grew over 25% year-over-year in Q4, driven by ongoing ranking improvements. In-feed recommendations of posts from accounts you're not connected to also continue to drive incremental engagement as we increasingly personalize recommendations, and we expect to deliver further improvements this year.

On Instagram, we're making strong progress increasing the freshness of recommended content. And a big focus for Facebook this year will be unifying our video experiences and ranking across the app, which should create a more seamless user experience and deliver increasingly relevant video recommendations. On WhatsApp, community growth remains strong, and we're seeing good traction with our Channels product, which has quickly scaled to over 500 million monthly active users since we rolled it out globally in September. We are also making good progress in areas that have the potential to grow people's engagement with our products in the longer term, such as Threads and generative AI. On Threads, we're coming into 2024 with strong product momentum and remain focused on introducing additional valuable features and further scaling the community this year.

With generative AI, we fully rolled out our Meta AI assistant and other AI chat experiences in the U.S. at the end of the year and began testing more than 20 GenAI features across our Family of Apps. Our big areas of focus in 2024 will be working towards the launch of Llama 3, expanding the usefulness of our Meta AI assistant and progressing on our AI Studio road map to make it easier for anyone to create an AI. For the experiences in our apps, we'll follow our typical approach of making them great before we lean into growth and eventually monetization. But this continues to be an exciting area that has the potential to transform how people engage on our services in the years ahead. Now to the second driver of our revenue performance, increasing monetization efficiency.

There are 2 parts to this work. The first part is growing the level of ad inventory within organic engagement. Our approach to optimizing ad levels in our apps has become increasingly sophisticated over the years as we've developed a better understanding of the optimal place, time and person to show an ad, which has enabled us to adopt a more dynamic approach to serving apps. We expect to continue that work going forward, while services with relatively lower levels of monetization like video and messaging will serve as additional growth opportunities. The other part to increasing monetization efficiency is improving marketing performance. To do this, we're focused on 3 areas. The first is AI. We continue to leverage AI across our ad systems and product suite.

We're delivering continued performance gains from ranking improvements as we adopt larger and more advanced models, and this will remain an ongoing area of investment in 2024. We're also building out our Advantage+ portfolio of solutions to help advertisers leverage AI to automate their advertising campaigns. Advertisers can choose to automate part of the campaign creation setup process, such as who to show their ad to with Advantage+ audience, or they can automate their campaign completely using Advantage+ shopping, which continues to see strong growth. We're also now exploring ways to apply this end-to-end automation to new objectives. On the ads creative side, we completed the global rollout of 2 of our generative AI features in Q4, Text Variations and Image Expansion, and plan to broaden availability of our background generation feature later in Q1.

Initial adoption of these features has been strong, and tests are showing promising early performance gains. This will remain a big area of focus for us in 2024. The second area of our work is helping businesses connect their marketing data and measure results. Here, we're continuing to invest in conversions API to make it easier for advertisers to not only adopt but maximize its impact. The last area is investing in new and engaging on-platform ad experiences. Business messaging remains a priority here. Click-to-message ads continue to grow, and we're seeing advertisers increasingly use these ads to drive down funnel conversions. Paid messaging is growing quickly, and we are focused on broadening adoption in 2024 by making it easier for businesses to buy marketing messages and more easily adopt our Flows product to develop richer in-Thread experiences for consumers.

We're also progressing with our early testing on WhatsApp and Messenger of AIs for businesses that can provide conversational support in chat. We'll take our time to get these experiences right, but we think this will be a compelling opportunity that we're well positioned to deliver on. Outside of business messaging, we're making strong progress with our shops' ads products, which crossed a $2 billion annual run rate in Q4. Next, I would like to discuss our approach to capital allocation. We are in the fortunate position of being able to invest in many organic opportunities to improve the performance of our core business in the near term while also making 2 significant longer-time horizon investments in AI and Reality Labs. AI is a growing area of investment for us in 2024 as we hire to support our road map.

We are also investing more in our AI infrastructure capacity this year. And given many of our ambitious forward-looking plans will rely on having sufficient compute capacity, we expect this to be an area we invest more aggressively in over the coming years. Reality Labs is the other long-term initiative we continue to invest heavily in as we progress on our efforts to develop the next computing platform. Aside from organic investments, returning capital to shareholders remains important to us. We believe our strong financial position and performance will enable us to invest in the business while also continuing to return capital to investors over time. We've historically done so through share repurchases. And while we expect to maintain an active share repurchase program, we are modestly evolving our approach going forward by returning a portion of capital through a regular dividend subject to quarterly Board approval.

In addition, we continue to monitor the active regulatory landscape, including the increasing legal and regulatory headwinds in the EU and the U.S. that could significantly impact our business and our financial results. Of note, the FTC is seeking to substantially modify our existing consent order and impose additional restrictions on our ability to operate. We are contesting this matter, but if we are unsuccessful, it would have an adverse impact on our business. Turning now to the revenue outlook. We expect first quarter 2024 total revenue to be in the range of $34.5 billion to $37 billion. Our guidance assumes foreign currency is neutral to year-over-year total revenue growth based on current exchange rates. Turning now to the expense outlook.

We expect full year 2024 total expenses to be in the range of $94 billion to $99 billion, unchanged from our prior outlook. We continue to expect a few factors to be drivers of total expense growth in 2024. First, we expect higher infrastructure-related costs this year. Given our increased capital investments in recent years, we expect depreciation expenses in 2024 to increase by a larger amount than in 2023. We also expect to incur higher operating costs from running a larger infrastructure footprint. Second, we anticipate growth in payroll expenses as we work down our current hiring underrun and add incremental talent to support priority areas in 2024, which we expect will further shift our workforce composition toward higher-cost technical roles.

Finally, for Reality Labs, we expect operating losses to increase meaningfully year-over-year due to our ongoing product development efforts in AR/VR and our investments to further scale our ecosystem. Turning now to the CapEx outlook. We anticipate our full year 2024 capital expenditures will be in the range of $30 billion to $37 billion, a $2 billion increase of the high end of our prior range. We expect growth will be driven by investments in servers, including both AI and non-AI hardware, and data centers as we ramp up construction on sites with our previously announced new data center architecture. Our updated outlook reflects our evolving understanding of our AI capacity demands as we anticipate what we may need for the next generations of foundational research and product development.

While we are not providing guidance for years beyond 2024, we expect our ambitious long-term AI research and product development efforts will require growing infrastructure investments beyond this year. On to tax. Absent any changes to U.S. tax law, we expect our full year 2024 tax rate to be in the mid-teens. In closing, this was a pivotal year for our company. We increased our operating discipline, delivered strong execution across our product priorities and improved advertising performance for businesses who rely on our services. We will look to build on our priorities in each of those areas in 2024 while advancing our ambitious longer-term efforts in AI and Reality Labs. With that, Krista, let's open up the call for questions.

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