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Avi Verma was previously a researcher at OpenAI.

Ethan Knight worked at the ChatGPT maker earlier in his career but joined Meta from Elon Musk’s xAI.

A third researcher, Rishabh Agarwal, announced publicly on Monday he was leaving Meta’s lab as well. He joined the tech giant in April to work on generative AI projects before switching to a role at Meta Superintelligence Labs (MSL), according to his LinkedIn profile. While the reasons for Agarwal’s departure are not known, he is based in Canada and Meta’s AI teams are predominantly based in Menlo Park, California.

Meta is also losing another leader who has worked at the tech giant for nearly a decade. Chaya Nayak, the director of generative AI product management at Meta, is joining OpenAI to work on special initiatives, according to two sources with direct knowledge of the hire.

In July, Zuckerberg announced that another former OpenAI researcher, Shengjia Zhao, who played a key role in the creation of ChatGPT, would become the chief scientist of MSL. The announcement came after Zhao tried to return to OpenAI—even going so far as to sign employment paperwork—according to multiple sources with direct knowledge of the events.

“Shengjia cofounded MSL and has been our scientific lead since day one,” Arnold said in a statement to WIRED. “ We formalized his role once our recruiting had ramped and the team had taken shape.”

This is my last week at @AIatMeta. It was a tough decision not to continue with the new Superintelligence TBD lab, especially given the talent and compute density. But after 7.5 years across Google Brain, DeepMind, and Meta, I felt the pull to take on a different kind of risk.

The pitch from Mark and @alexandr_wang to build in the Superintelligence team was incredibly compelling. But I ultimately choose to follow Mark's own advice: “In a world that’s changing so fast, the biggest risk you can take is not taking any risk”.

In my short time at Meta, we did push the frontier on post-training for "thinking" models. Specifically:

  • Pushing an 8B dense model to near Deepseek-R1 performance with RL scaling.
  • Using synthetic data mid-training to warm-start RL.
  • Developing better on-policy distillation methods.

Really enjoyed working with @arohan, @brandfonbrener, Leo Li, @ErykHelenowski, @DatHuynh13, Xiaocheng, Jia, Boduo, and Yanjun.

1/ Today we’re proud to announce a partnership with @midjourney , to license their aesthetic technology for our future models and products, bringing beauty to billions.

2/ This technical collaboration between our research teams is part of our effort to team up with the best companies in the industry whose work and expertise complements our own.

3/ We are incredibly impressed by Midjourney. They have accomplished true feats of technical and aesthetic excellence, and we are thrilled to be working more closely with them.

4/ To ensure Meta is able to deliver the best possible products for people it will require taking an all-of-the-above approach. This means world-class talent, ambitious compute roadmap, and working with the best players across the industry.

5/ We look forward to showing you what we build together. More to come soon!

Google, opens new tab has struck a six-year cloud computing deal with Meta Platforms, opens new tab worth more than $10 billion, a source familiar with the matter told Reuters on Thursday, the search giant's second big agreement recently after one with OpenAI.

Under the agreement, Meta will use Google Cloud's servers, storage, networking and other services, the source, who asked not to be named because the discussions are confidential, said.

"All that's happening here is some basic organizational planning: creating a solid structure for our new superintelligence efforts after bringing people on board and undertaking yearly budgeting and planning exercises," a spokesperson for Meta said in an emailed statement to Reuters.

Superintelligence is coming, and in order to take it seriously, we need to organize around the key areas that will be critical to reach it — research, product and infra. We are building a world-class organization around these areas, and have brought in some incredible leaders to drive the work forward.

As we previously announced, Shengjia Zhao will direct our research efforts as Chief Scientist for MSL, Nat Friedman will lead our product effort and Rob Fergus will continue to lead FAIR. Today, I'm pleased to announce that Aparna Ramani will be moving over to MSL to lead the infrastructure necessary to support our ambitious research and product bets.

As part of this, we are dissolving the AGI Foundations organization and moving the talent from that team into the right areas. Teams whose work naturally aligns with and serves our products will move to Nat's team. Some of the researchers will move to FAIR to double down on our long term research while teams working on infra will transition into Aparna's org. Anyone who is changing teams will get an update from their manager or HRBP today, if you haven't already.

We're making three key changes to our organizational design that will help us to accelerate our efforts.

  1. Centralizing core, fundamental research efforts in TBD Lab and FAIR.
  2. Bolstering our product efforts with applied research that will work on product-focused models.
  3. Establishing a unified, core infrastructure team to support our research bets.

The work will map to four teams:

TBD Lab will be a small team focused on training and scaling large models to achieve superintelligence across pre-training, reasoning, and post-training, and explore new directions such as an omni model.

FAIR will be an innovation engine for MSL and we will aim to integrate and scale many of the research ideas and projects from FAIR into the larger model runs conducted by TBD Lab. Rob will continue to lead FAIR and Yann will continue to serve as Chief Scientist for FAIR, with both reporting to me.

Products & Applied Research will bring our product-focused research efforts closer to product development. This will include teams previously working on Assistant, Voice, Media, Trust, Embodiment and Developer pillars in AI Tech. Nat will continue to lead this work reporting to me.

MSL Infra team will unify elements of Infra and MSL's infrastructure teams into one. This team will focus on accelerating AI research and production by building advanced infrastructure, optimized GPU clusters, comprehensive environments, data infrastructure, and developer tools to support state-of-the-art research, products and AI development across Meta. Aparna will lead this team reporting to me.

Ahmad and Amir will continue reporting to me focusing on strategic MSL initiatives they will share more about later.

I recognize that org changes can be disruptive, but I truly believe that taking the time to get this structure right now will allow us to reach superintelligence with more velocity over the long term. We're still working through updated rhythms and our collaboration model across teams, including when we'll come together as a full MSL org.

Thank you all for your flexibility as we adapt to this new structure. Every team in MSL plays a critical role and I'm excited to get to work with all of you.

For our superintelligence effort, I'm focused on building the most elite and talent-dense team in the industry. We're also going to invest hundreds of billions of dollars into compute to build superintelligence. We have the capital from our business to do this.

SemiAnalysis just reported that Meta is on track to be the first lab to bring a 1GW+ supercluster online.

We're actually building several multi-GW clusters. We're calling the first one Prometheus and it's coming online in '26. We're also building Hyperion, which will be able to scale up to 5GW over several years. We're building multiple more titan clusters as well. Just one of these covers a significant part of the footprint of Manhattan.

Meta Superintelligence Labs will have industry-leading levels of compute and by far the greatest compute per researcher. I'm looking forward to working with the top researchers to advance the frontier!

Facebook parent Meta acquired just under 3% of Ray-Ban maker EssilorLuxottica, a stake worth around €3 billion ($3.5 billion) at the current market price, said the people, who asked not to be identified because deliberations are private.

Menlo Park, California-based Meta is considering further investment that could build the stake to around 5% over time, the people added, though those plans could still change.

Following the category-defining success of Ray-Ban Meta, the #1 selling AI glasses in the world which have sold millions of units since launch, Oakley Meta glasses will be the next product line to come from this long-term partnership.

Oakley Meta HSTN, the first product in the collection, will include key tech improvements, including Ultra HD 3K recording, so videos will be clearer and higher resolution than Full HD (1080p). People can enjoy their favorite music and podcasts with powerful open-ear speakers seamlessly integrated into the frames. Oakley Meta HSTN will also provide 40% longer battery life, lasting up to eight hours of typical use and up to 19 hours on standby. The glasses come with a charging case that can deliver up to 48 hours of charging on the go.

Consumers have the option to fit their Oakley Meta HSTN with Oakley PRIZM Lens technology, one of the most advanced innovations in lens design. This revolutionary technology fine-tunes the light spectrum, amplifying color while filtering out visual noise. This allows subtle visual cues to come sharply into view, helping wearers see more, react quicker, and perform at their peak.


“It’s part of a broader multi-brand, multi-technology strategy that reflects the scale of our ambition: to build a connected eyewear category that spans lifestyles, communities, and use cases. We’re combining design, utility, and emotion to deepen human connection and unlock new potential through the lens of every brand we touch. And there is far more to come.”

"Glasses have emerged as the ideal tool for people to listen to music, capture videos, and get the help of a powerful AI assistant,” said Alex Himel, VP of Wearables at Meta.

The Limited Edition Oakley Meta HSTN will be available for preorder starting July 11 for $499 USD, with the rest of the collection starting at $399 USD coming later this summer. Oakley Meta HSTN will be available in the US, Canada, UK, Ireland, France, Italy, Spain, Austria, Belgium, Australia, Germany, Sweden, Norway, Finland and Denmark. Oakley and Meta will be working to bring Oakley Meta HSTN to Mexico, India, and UAE later this year.

Gratitude

Team—

When I founded Scale in 2016, it was amidst some of the early Al breakthroughs—DeepMind had just released AlphaGo, and Google had just released Tensorflow—but it was still incredibly early. It was clear even then that data was the lifeblood of Al systems, and that was the inspiration behind starting Scale. Since then, the journey has been extraordinary.

We've grown to over 1,500 people and become the trusted partner for model builders, enterprises, and governments building and deploying the smartest Al tools and applications. Scale is now one of the most impactful companies in the world, accelerating the development of what may be the most important technology in human history. Today, we are announcing a massive new investment from Meta. This is a major milestone and a powerful validation of the hard work you've all put into Scale's mission.

With this foundation, it's now time to focus on the next chapter. Building this company alongside all of you has been my life—l started this company right out of freshman year of MIT and never looked back. Every moment and memory of the past decade has been surrounded by you all. And I wouldn't change a minute of it.

When this opportunity first presented itself, my immediate reaction was uncertainty. The idea of not being a Scalien was, frankly, unimaginable. But as I spent time truly considering it, I realized this was a deeply unique moment, not just for me, but for Scale as well. It offered a rare chance to give back to everyone who has helped shape Scale, while setting the company on an even stronger trajectory for what's ahead.

As you've probably gathered from recent news, opportunities of this magnitude often come at a cost. In this instance, that cost is my departure. It has been the absolute greatest pleasure of my life to serve as your CEO.

As to what is next for me, I will be leaving Scale to join Meta to work on Meta's Al efforts, along with a few other Scaliens. While it is bittersweet to depart as CEO, I would never leave Scale behind. ' stay on as a director on the Board, continuing to support Scale's mission and long-term vision.

As part of my transition, I'm excited to share that Scale's Board of Directors and I have agreed that Jason Droege will step in as Interim CEO. Jason's superpowers in building and evolving businesses like Uber Eats and AXON give him the experience and skillset that make him the best person for this role. Jason knows our business and knows what Scale must do to execute on the immense opportunity ahead. Jason is also working closely with our board to hire a strong CTO to bolster our engineering teams. And let me be clear, I wouldn't be in such strong support if I weren't confident that Jason and the rest of the team are the right leaders to carry our mission forward.

Today's investment also allows us to give back in recognition of your hard work and dedication to Scale over the past several years. The proceeds from Meta's investment will be distributed to those of you who are shareholders and vested equity holders, while maintaining the opportunity to continue participating in our future growth as ongoing equity holders. The exceptional team here has been the key to our success, so I'm thrilled to be able to return the favor with this meaningful liquidity distribution.

Thank you for everything.

Alex

SAN FRANCISCO, June 12, 2025 – Scale AI, Inc. (“Scale” or the “Company”), the humanity-first AI company, today announced a significant new investment from Meta Platforms, Inc. (Nasdaq: META) that values Scale at over $29 billion.

In addition, Scale’s founder, Alexandr Wang, is joining Meta to work on Meta’s AI efforts. Wang will continue to serve as a director on the Scale Board of Directors and support Scale’s ongoing work to unlock the power of AI and keep human values at the forefront.

Through the years, we created and nurtured dozens of projects that are now household names at Meta, used by dozens of teams to build better products: PyTorch, FAISS, Roberta, Dino, Llama, SAM, Codegen, Audiobox, ….

Today, as the world undergoes significant change, as the race for AI accelerates, and as Meta prepares for its next chapter, it is time to create space for others to pursue the work. I will be cheering from the sidelines, knowing that you have all the ingredients needed to build the best AI systems in the world, and to responsibly bring them into the lives of billions of people.

Following the unprecedented growth and momentum of our open source Llama collection of models and tools, we’re excited to introduce LlamaCon—a developer conference for 2025 that will take place April 29.

Quarterly Earnings ​

Q2 2025 ​

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.

We currently expect 2025 capital expenditures, including principal payments on finance leases, to be in the range of $66-72 billion, narrowed from our prior outlook of $64-72 billion and up approximately $30 billion year-over-year at the mid-point.
While the infrastructure planning process remains highly dynamic, we currently expect another year of similarly significant capital expenditures dollar growth in 2026 as we continue aggressively pursuing opportunities to bring additional capacity online to meet the needs of our artificial intelligence efforts and business operations.

Over the last few months we have begun to see glimpses of our AI systems improving themselves. 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.

We're making good progress towards Llama 4.1 and 4.2 -- and in parallel, we're also working on our next generation of models that will push the frontier in the next year or so.

We're building an elite, talent-dense team. Alexandr Wang is leading the overall team, ANat Friedman is leading our AI products and applied research, and AShengjia Zhao is Chief Scientist for the new effort.

I've spent a lot of time building this team this quarter, and the reason that so many people are excited to join is because Meta has all the ingredients required to build leading models and deliver them to billions of people. The people who are joining us will have access to unparalleled compute as we build out several multi-GW clusters. Our Prometheus cluster is coming online next year and we think it'll be the world's first 1GW+ cluster. We're also building out Hyperion, which will be able to scale up to 5GW over several years. And we have multiple more titan clusters in development as well.

From a business perspective, I mentioned last quarter that there are five basic opportunities that we're pursuing: improved advertising, more engaging experiences, business messaging, Meta AI, and AI devices.

It's driven roughly 5% more ad conversions on Instagram and 3% on Facebook.

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.

We're 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.

Meta AI's reach is already quite impressive with more than a billion monthly actives.

We continue to see strong momentum with our Ray-Ban Meta glasses, with sales accelerating. We're also launching new performance AI glasses with the Oakley Meta HSTNs. ... 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 these different styles that appeal to different people in different settings.

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.

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 server useful lives.

G&A decreased 27%, driven mostly by lower legal-related costs.

We also made $15.1 billion in non-marketable 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.

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

Family of Apps other revenue was $583 million, up 50%, driven by WhatsApp paid messaging revenue growth as well as Meta Verified subscriptions.

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 operating loss was $4.5 billion.

We are also seeing promising results from using LLMs in Threads recommendation systems. The incorporation of LLMs are 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 in recommendation systems to our other apps.

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.

In Q2, we also began introducing ads within Feed on Threads and the Updates tab on 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.

First is our ads systems, where we’re innovating in both the ads retrieval and ranking stages to serve more relevant ads to people.

The Andromeda model architecture we began introducing in the second half of 2024 powers the ads retrieval stage of our ads system, where we select the few thousand most relevant ads from tens of millions of potential candidates. ... 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 ads 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. ... 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. ... 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.

we’re seeing good momentum in business messaging, particularly in the US where click-to-message revenue grew more than 40% year-over-year in Q2. The strong US growth is benefiting from a ramp in adoption of our Website to Message ads, which drive people to a businesses’ website for more information before choosing to launch a chat with the business in one of our messaging apps.

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

We expect talent additions across all of our priority areas will continue to drive overall headcount growth through this year and 2026, while headcount 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.

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.

Which I think is one of the things that our company is the best in the world at is basically when we take a technology, we’re good at driving that through all of our apps and our ad systems and all that stuff, it’s not just going to kind of sit on the vine.

We also expect a greater mix of our CapEx to be in shorter-lived assets in 2025 and ‘26 than it has been in prior years. And then the other component of infra cost growth next year would come from higher operating expenses including energy costs, leases, maintenance and operational expenses that are associated with maintaining that fleet.

In terms of the shape of the effort overall, I guess I’ve just gotten a little bit more convinced around the ability for small talent-dense teams to be the optimal configuration for driving frontier research. And it’s a bit of a different setup than we have on our other world-class machine learning systems.

So if you look at like what we do in Instagram or Facebook or our ad system, we can very productively have many hundreds or thousands of people basically working on improving those systems, and we have very well-developed systems for kind of individuals to run tests and be able to test a bunch of different things. You don’t need every researcher there to have the whole system in their head.

But I think for this -- for the leading research on superintelligence, you really want the smallest group that can hold the whole thing in their head, which drives, I think, some of the physics around the team size and how -- and the dynamics around how that works.

And a big focus of this work is going to be on optimizing the systems to make them more efficient, so that we can continue to scale up the capacity that we use for our recommendation systems without eroding the ROI that we deliver.

One is that we’re getting models that are so big that they’re just not practical for a lot of other people to use. So it’s -- we would kind of wrestle with whether it’s productive or helpful to share that or if that’s really just primarily helping competitors or something like that.

But we do take very seriously that this is a just massive amount of capital to convert into many gigawatts of compute which we think is going to help us produce leading research and quality products and running the business, I do look for opportunities to basically convert capital into quality of products that we can deliver for people.

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? Thanks.

On your second question about how we expect to finance the growing CapEx next year. We certainly expect that we will finance some large share of that ourselves, but we’re also exploring ways to work with financial partners to codevelop data centers.

And then, of course, to make sure that we are building the training capacity that we think we need in order to build frontier AI models. And to make sure that we’re preparing ourselves for the types of inference use cases that we might have ahead of us as we eventually focus not only on developing frontier models, but also how we can expand into the kinds of consumer use cases that we think will be hopefully widely useful and engaging for our users.

So again, on the core AI side, we continue to see strong ROI. Our ability to measure that is quite good, and we feel sort of very good about the rigorous measurement and returns that we see there.

On the GenAI side, we are clearly much, much earlier on the return curve and we don’t expect that the GenAI work is going to be a meaningful driver of revenue this year or next year.

The last thing I would add here is we are building the infrastructure with fungibility in mind. Obviously there are a lot of things that you have to build up front in terms of the data center shells, the networking infrastructure, et cetera. But we will be ordering servers, which ultimately will be the biggest bulk of CapEx spend as we need them and when we need them and making sort of the best decisions at those times in terms of figuring out where the capacity will go to use.

I mean going back to the last question a little bit, it’s sort of when you compare this business to some of the cloud businesses, it’s like we do have this delay where we focus on building research and then doing research and then ramping consumer products, and it often does take some period of time before we really are ramping up the business around it.

Our primary focus from a profitability perspective is driving consolidated operating profit growth over time. And it won’t be linear.

In some years, we’ll deliver above-average profit growth. And in years where we’re making big investments, I think we will see that impact the amount of operating profit growth that we can deliver.

And at the moment, we see a lot of attractive investment opportunities that we believe are going to set us up to deliver compelling profit growth in the coming years for all of our investors.

And so we’re focused on constraining investments elsewhere as we pursue those investments. But we really believe that this is a time for us to really make investments in the future of AI as I think it will open up both new opportunities for us in addition to strengthen our core business.

I wear contact lenses, I feel like if I didn’t have my vision corrected, I’d be sort of at a cognitive disadvantage going through the world. And I think in the future, if you don’t have glasses that have AI or some way to interact with AI, I think you’re kind of similarly probably be at a pretty significant cognitive disadvantage compared to other people who you’re working with, or competing against.

And we generally believe that our strong financial position is going to allow us to support these investments while continuing to repurchase shares as part of the sort of buyback program that offsets equity compensation and as well as provide quarterly cash dividend distributions to our investors.

Q1 2025 ​

Specifically, we have seen some reduced spend in the U.S. from Asia-based ecommerce exporters, which we believe is in anticipation of the de minimis exemption going away on May 2nd. A portion of that spend has been redirected to other markets, but overall spend for those advertisers is below the levels prior to April.

The higher costs we expect to incur for infrastructure hardware this year really comes from suppliers who source from countries around the world. And there’s just a lot of uncertainty around this, given the ongoing trade discussions.

We’re pleased to have partners investing alongside us and bringing Llama to market like AWS and Azure who are helping us host Llama.
We’re always looking for opportunities to continue deepening or expanding those partnerships. But we are funding the infrastructure that is being used to train Llama, and we don’t have any expectation that that will change at this point.

Our advertising revenue in the European economic area and Switzerland, which would be the geographies impacted here, was 16% of our worldwide total revenue in 2024.

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. But that continues to just be a very small vertical overall.

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We are in the fortunate position where the strong results that we're seeing in our core products and business give us the opportunity to make deep investments for the future. And I plan to fully seize that opportunity to build some amazing things that will pay off for our community and our investors for decades to come. The progress we're making on both the foundational technology and product experiences suggests that we're on the right track.

~ Mark Zurkburg

Q1 2024 ​

I think it's worth calling that out that we've historically seen a lot of volatility in our stock during this phase of our product playbook where we're investing in scaling a new product, but aren't yet monetizing it. We saw this with reels, stories as newsfeed transitioned to mobile and more and I also expect to see a multi-year investment cycle before we fully scaled Meta AI, business AIs and more into the profitable services I expect as well.

~ Mark Zurkburg

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